use of bio-product/phase change material composite in the
TRANSCRIPT
APPROVED: Weihuan Zhao, Major Professor Xiaohua Li, Committee Member Kuruvilla John, Committee Member and
Chair of the Department of Mechanical and Energy Engineering
Yan Huang, Interim Dean of the College of Engineering
Victor Prybutok, Dean of the Toulouse Graduate School
USE OF BIO-PRODUCT/PHASE CHANGE MATERIAL COMPOSITE IN THE
BUILDING ENVELOPE FOR BUILDING THERMAL CONTROL
AND ENERGY SAVINGS
Aravind Reddy Boozula
Thesis Prepared for the Degree of
MASTER OF SCIENCE
UNIVERSITY OF NORTH TEXAS
August 2018
Boozula, Aravind Reddy. Use of Bio-Product/Phase Change Material Composite in the
Building Envelope for Building Thermal Control and Energy Savings. Master of Science
(Mechanical and Energy Engineering), August 2018, 92 pp., 6 tables, 30 figures, 42 numbered
references.
This research investigates the bio-products/phase change material (PCM) composites for
the building envelope application. Bio-products, such as wood and herb, are porous medium,
which can be applied in the building envelope for thermal insulation purpose. PCM is infiltrated
into the bio-product (porous medium) to form a composite material. The PCM can absorb/release
large amount of latent heat of fusion from/to the building environment during the
melting/solidification process. Hence, the PCM-based composite material in the building
envelope can efficiently adjust the building interior temperature by utilizing the phase change
process, which improves the thermal insulation, and therefore, reduces the load on the HVAC
system. Paraffin wax was considered as the PCM in the current studies. The building energy
savings were investigated by comparing the composite building envelope material with the
conventional material in a unique Zero-Energy (ZØE) Research Lab building at University of
North Texas (UNT) through building energy simulation programs (i.e., eQUEST and
EnergyPlus). The exact climatic conditions of the local area (Denton, Texas) were used as the
input values in the simulations. It was found that the EnergyPlus building simulation program
was more suitable for the PCM based building envelope using the latent heat property.
Therefore, based on the EnergyPlus simulations, when the conventional structure insulated panel
(SIP) in the roof and wall structures were replaced by the herb panel or herb/PCM composite, it
was found that around 16.0% of energy savings in heating load and 11.0% in cooling load were
obtained by using PCM in the bio-product porous medium.
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ACKNOWLEDGMENTS
I would like to appreciate my major professor Dr. Weihuan Zhao for her guidance,
motivation, and suggestions, which facilitated me to perform my thesis successfully. And also, I
appreciate my professor for encouraging me to publish and present my work in the 3rd Thermal
and Fluids Engineering Conference where many scientists and researchers came to express their
thoughts and respective works.
I would also like to thank Dr. Sheldon Q. Shi and Dr. Liping Cai for helping me prepare
the infiltrated bio-product samples for the experimental testing.
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TABLE OF CONTENTS
Page
ACKNOWLEDGMENTS ............................................................................................................. iii
LIST OF TABLES ......................................................................................................................... vi
LIST OF FIGURES ...................................................................................................................... vii
CHAPTER 1. INTRODUCTION ................................................................................................... 1
1.1 Background of Buildings and their Performances .................................................. 1
1.2 Research, Goal and Objectives ............................................................................... 3
CHAPTER 2. LITERATURE REVIEW ........................................................................................ 5
2.1 Demand and Scope for Insulation in Buildings Envelope ...................................... 5
2.2 Usage of PCM in Wall Boards................................................................................ 5
2.3 PCM Infiltration into the Porous Materials Making a Composite .......................... 7
2.4 PCM Replacement with Wall Composites ............................................................. 8
2.5 Composite Encapsulation Techniques .................................................................. 10
2.6 Results and their Feasibility Obtained in the Simulation...................................... 11
2.7 Energy Savings with Different Techniques .......................................................... 12
2.8 Influence of Location and Climatic Conditions in Choosing PCM ...................... 13
2.9 Uniqueness of this Research ................................................................................. 14
CHAPTER 3. METHODOLOGY ................................................................................................ 15
3.1 Open Porosity Measurement by Pycnometer ........................................................ 15
3.2 Hot Disk Thermal Constant Analyzer for Thermal Conductivity Measurement .. 16
3.3 Heat Capacity Measurement by Differential Scanning Calorimeter (DSC) ......... 20
3.4 Temperature Variation Measurements .................................................................. 22
3.5 eQUEST Energy Simulations ............................................................................... 23
3.5.1 HVAC System in Zero Energy Building (GSHP) .................................... 23
3.5.2 Wall Layers in ZØE Building ................................................................... 24
3.5.3 Conduction Transfer Function (CTF) for Heat Transfer Equations ......... 25
3.6 EnergyPlus Simulations ........................................................................................ 27
CHAPTER 4. CHARACTERIZATIONS OF THE BIO-PRODUCT/PCM COMPOSITES’ THERMAL PROPERTIES ........................................................................................................... 29
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4.1 Open Porosities and Densities of Bio-Product and Bio-Product/PCM Composites............................................................................................................................... 29
4.1.1 Non-Infiltrated Samples ............................................................................ 29
4.1.2 Infiltration Samples ................................................................................... 30
4.1.3 Half-Cut Samples ...................................................................................... 30
4.2 Thermal Conductivities ......................................................................................... 32
4.3 Specific Heat and Latent Heat of Fusion .............................................................. 33
4.4 Temperature Control by Using Bio-Product/PCM composites ............................ 38
4.4.1 Infiltrated and Infiltrated Pine Samples .................................................... 38
4.4.2 Non-Infiltrated and Infiltrated Cherry Samples ........................................ 39
4.4.3 Space Temperature Control by Using Herb/PCM Composites ................ 40
4.4.4 Temperature Difference Comparison between Pine, Cherry and Herb/PCM Composites ................................................................................................ 41
4.4 Alternatives to Overcome Inflamability of Paraffin Wax..................................... 42 CHAPTER 5. BUILDING ENERGY SIMULATION RESULTS .............................................. 44
5.1 Results on eQUEST .............................................................................................. 44
5.2 Results Obtained on EnergyPlus ........................................................................... 47
5.2.1 Comparison of the Heating and Cooling Loads between Conventional and Bio-Product/PCM Composite Embedded Building Envelopes ................ 47
5.2.2 Replacing SIP Layer by Composite Materials .......................................... 49
5.2.3 Replacement and Addition of Composite Materials for Wall and Roof Structures .................................................................................................. 52
5.2.4 Inside and Outside Wall Face Temperature Distribution (Hourly) for a Single Hot and Cold Days of the Year...................................................... 55
CHAPTER 6. CONCLUSIONS AND FUTURE RESEARCH ................................................... 61
6.1 Conclusions ........................................................................................................... 61
6.2 Future Research .................................................................................................... 61 APPENDIX A. RAW MATERIAL DATA .................................................................................. 63 APPENDIX B. eQUEST ENERGY INPUTS .............................................................................. 72 APPENDIX C. ENERGYPLUS INPUTS .................................................................................... 79 REFERENCES ............................................................................................................................. 89
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LIST OF TABLES
Page
Table 3.1: Specifications of TPS 1500 [35] .................................................................................. 17
Table 3.2: Wall construction layers for the ZØE lab .................................................................... 24
Table 4.1: Summary of porosities and densities ........................................................................... 31
Table 4.2: Summary of average latent heat of fusions for various bio-product composites ........ 38
Table 5.1: Summary of typical energy savings in eQUEST ......................................................... 46
Table 5.2: Summary of typical Energy savings in EnergyPlus .................................................... 55
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LIST OF FIGURES
Page
Figure 3.1: Pycnometer (Ultra-Foam 1200e) ................................................................................ 16
Figure 3.2: (a) Hot plate thermal constant analyzer setup, (b) TPS 1500, (c) Dynamic sensor ... 20
Figure 3.3: Schematic DSC test on PCM [37] .............................................................................. 21
Figure 3.4: (a) DSC chamber set-up (b) Chiller ........................................................................... 21
Figure 3.5: (a) sample containers placed on the hot plate which is set to 100oC (b) DAQ (c) DAQ software which tracks the temperature variation. ......................................................................... 22
Figure 3.6: 3D Extruded image, .................................................................................................... 23
Figure 3.7: 3D HVAC (water circulation) in eQUEST. ............................................................... 24
Figure 3.8: ZØE building designed in SketchUp for EnergyPlus simulation............................... 27
Figure 4.1: Open porosity of non- infiltrated pine and cherry woods .......................................... 29
Figure 4.2: Open porosity of infiltrated pine and cherry woods ................................................... 30
Figure 4.3: Open porosity of sliced infiltrated woods .................................................................. 31
Figure 4.4: Thermal conductivity measurements for various types of woods and infiltrated woods. (a) For non-infiltrated pine wood samples, (b) for infiltrated pine wood samples with PCM, (c) for non-infiltrated cherry wood samples, (d) for infiltrated cherry wood samples with PCM. ............................................................................................................................................. 33
Figure 4.5: Specific heat and latent heat of fusion of pure paraffin wax ...................................... 34
Figure 4.6: Specific heat and latent heat of fusion of the wood samples and the wood/PCM composite materials from the DSC measurements (a to f). .......................................................... 36
Figure 4.7: Specific heat and latent heat of fusion of the herb /PCM composite materials from the DSC measurements (a, b) ............................................................................................................. 38
Figure 4.8: Typical temperature vs time curves (comparison of infiltrated and non-infiltrated pine woods) ........................................................................................................................................... 39
Figure 4.9: Typical temperature vs time curves (comparison of infiltrated and non-infiltrated cherry woods)................................................................................................................................ 40
Figure 4.10: Typical temperature vs time curves (comparison of infiltrated and non-infiltrated herbs)............................................................................................................................................. 41
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Figure 4.11: Temperature reduction using infiltrated bio-products compared to non-infiltrated ones ............................................................................................................................................... 42
Figure 5.1: Energy consumption in the ZØE lab through the eQUEST simulations (a) Annual energy consumption, (b) Energy consumption in the summer month (July). ............................... 45
Figure 5.2: (a) Monthly utility bills through out a year (b) Utility bills exclusively for the month of July (Summer) .......................................................................................................................... 45
Figure 5.3: Energy consumption in the ZØE lab when replaced with PCM composite in roof and wall constructions ......................................................................................................................... 46
Figure 5.4: (a) Monthly heating load distribution (b) Monthly cooling load distribution (c) Annual cooling power savings for different combinations with composites, compared with SIP roof ................................................................................................................................................ 49
Figure 5.5: (a) Monthly heating load distribution, (b) Annual heat load savings for different composites compared with wood/ herb......................................................................................... 50
Figure 5.6: (a) Monthly cooling load distribution (b) Annual cooling power savings for different composites compared with wood/ herb......................................................................................... 51
Figure 5.7: (a) Monthly heating load distribution, (b) Annual heating load savings for different composites compared with wood/ herb......................................................................................... 53
Figure 5.8: (a) Monthly cooling load distribution (b) Annual cooling power savings for different composites compared with wood/herb.......................................................................................... 54
Figure 5.9: Hourly temperature distributions along (a) Summer inside wall (b) Summer outside wall faces (c)Winter inside wall (d) Winter outside wall faces .................................................... 57
Figure 5.10: Hourly temperature difference between conventional SIP and herb/PCM composite roof conditions in (a) summer interior face of the roof (b) summer exterior face of the roof (c) winter interior face of the roof (d) winter exterior face of the roof .............................................. 60
1
CHAPTER 1
INTRODUCTION
Buildings have always been addressing the changing social needs of people. With the
growing demand of energy worldwide, the expected decline of energy sources and their potential
harmful effects on the environment especially the fossil fuels, a lot of research is in progress to
make buildings more energy efficient. A prominent approach to achieve energy efficiency in
buildings was addressed by the building envelope materials. Use of phase change materials
(PCMs) in building envelope is a promising approach to achieve huge amount of heat storage,
and thereby, to mitigate the peak energy consumption. Besides, improving the strength of PCM
by infiltrating it into some suitable porous mediums.
1.1 Background of Buildings and their Performances
Historically, the construction of buildings started with simple forms [1], just sheltering
people from wind, sun and rain. As time went on, the desire for better shelter grew, at the same
time the suitable materials had been identified. The best example was the vernacular architecture
for the wise and effective usage of available materials like mud, grass, bamboo, thatch or sticks
to counter the environmental fluctuations based on the understanding of the climate. As the
society was growing, the buildings evolved from slow change in the design, building materials
and construction techniques to a very high pace dictated by the requirements. For many
centuries, walls in Europe were being built with masonry (bricks), wood, or clay material.
Considering their size or massiveness, these walls were very strong and durable while providing
the thermal protection through their natural heat storage capacity and thermal insulation
properties.
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Vernacular adobe buildings of New Mexico and Roman buildings made of bricks and
concrete related to the Trajan Baths, which was an epitome of modern building engineering
technology were built to absorb, store, and release ambient heat and captured solar energy so that
the net energy flow could be balanced for several days. In chilling climate areas where masonry
(bricks) were not available, log houses or half-timber with clay infill or earth treatments were built
for optimal insulation.
The term “building envelope” implies total wall, roof, floor and fenestration aspects of a
building structure [2]. Building envelope is the separation between the conditioned and
unconditioned environment to provide thermal resistance.
Currently, the building envelope is a composition of various thermal and permeable
layers composed of components with different structural properties. The choice of envelope is
governed by the local climate and society needs for the better efficiencies based on the ASHRAE
standards [4] and estimated by two contrary design concepts: the open frame shell and the closed
shell.
In harsh climates including noise or visual clutter, the designer most often considers the
building envelope as some closed shell and proceeds to selectively punch holes in it to make
limited and special contact with the outdoors. When external conditions are close to the desired
internal ones, the envelope often conceives as an open structural frame, which is exclusively
designed to overcome only few factors like wind, sunlight etc.
The flow of heat through the building envelope varies both by season and by the path of
the heat. These complexities must be considered by a material engineer who intends to deliver
comfort and energy optimization.
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In order to say that a building is efficient, it is essential that a common set of
measurements be used, and the results reported must be following certain protocols [5].
American Society of Heating, Refrigerating and Air-Conditioning Engineers ASHRAE’s
Performance Measurement Protocols (PMP) for Commercial Buildings, suggested some
standardized set of protocols, for different ranges of cost and energy consumption accuracy, to
facilitate the appropriate comparison of measured water, energy and indoor environmental
quality performance of commercial buildings, while maintaining acceptable levels of building
service for the occupants and to rate the building’s quality by its performance and sends out the
feedback if the performance is not up to the design intent. Targets are included in the rules
proposed to facilitate comparison to peer buildings.
1.2 Research, Goal and Objectives
The main goal of the current study is to find the importance of bio-product infiltrated
with phase change materials (PCMs) for residential buildings and small offices in reducing the
load on HVAC systems thereby, improving the energy savings. Two types of bio-products were
investigated by this research, i.e., wood and herb. As the wood is predominantly used for the
construction purposes in the United States, the infiltration of wood could play a pivotal role in
the future. On the other hand, the herb material provides moisture-durability, pest resistance,
cavity-filling, air-movement-retarding, ecologically-sound insulation with substantial insulation
for retrofit/renovation projects. The reason of using PCM in the building envelope is for its
property of being able to absorb large amount of latent heat during the melting process and
release the heat back to the building environment during the solidification process.
Consequently, it can efficiently control the building interior temperature. Furthermore, the direct
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infiltration of PCMs in the bio-product based porous medium will minimize the effect on the
original building envelop structure, and therefore, simplify the assembling procedure. In this
work, paraffin wax was used as the PCM embedded in two types of woods (cherry wood and
pine wood) as well as in herb cellulose chips. The bio-product/PCM composite has been
investigated for its suitability as a prospect for energy storage thereby, enhancing the thermal
insulation of the building envelope.
The effects of the composite materials on building interior temperature and energy
savings were investigated based in a Zero-Energy (ZØE) lab building at University of North
Texas (UNT). ZØE lab is a distinctive building in Texas designed mainly to test and demonstrate
various alternative energy generation technologies in order to achieve a net-zero energy power
consumption. The lab is spread over an area of 1200 square foot, including a living quarter with
a bedroom and a kitchen, and a working space. As part of its mission, the current study is mainly
concentrating on reducing the load on HVAC system by replacing one of the layers in the
structural insulated panel (SIP) wall with a bio-product/PCM composite based panel in the
building.
The objectives of this research are to (1) characterize the properties of bio-product/PCM
composites, (2) study the effect of PCM infiltrated bio-product porous materials on thermal
insulation in terms of energy savings in building through the simulation of a simple office
building-type building (the ZØE lab at UNT).
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CHAPTER 2
LITERATURE REVIEW
2.1 Demand and Scope for Insulation in Buildings Envelope
United States is currently consuming 50% of its energy for the buildings and expected to
raise by 56% in the world between 2010 and 2040. We’re living in a world of power-hungry
equipment, resulting in electricity demand swelling [6]. Hence, the demands for the energy
savings as well as thermal comfort are increasing. Different techniques have been developed to
improve the effective usage of electricity. One way is to improve the heat capacities and thermal
resistances of the building envelope materials. Suresh B. Sadineni et al. [7] made an elaborative
technical review of the building envelope constituents which included wall materials, structure
layers, and their relevant improvements from energy savings view point. Energy efficient walls
such as Trombe walls, ventilated walls and glazed walls had been studied, with emphasis on
performance of various fenestration technologies which included aerogel, vacuum glazing and
frames. Innovations in energy efficient roofs like green roofs, photovoltaic roofs, radiant-
transmittive barrier and evaporative roof cooling systems were studied in this review paper. And
came up with a holistic design to reduce the mechanical system costing.
2.2 Usage of PCM in Wall Boards
Vineet Veer Tyagi et al. [8] made a cogent study on various methods for conditioning in
buildings, where he discussed the thermal performance of various types of systems like PCM
trombe wall as in the case of previous reference, PCM wallboards, PCM shutters, PCM building
blocks, air-based heating systems, floor heating, ceiling boards etc and materials used with
melting range of 20oC to 32oC. Later, suggested passive &active system storages for various wall
6
thicknesses and demand for heat transfer rate applications. Jaume Gasia et al. [9] explained about
phase change property in energy storage especially the usage of waste heat obtained from
industrial and domestic appliances by using RT58 as the PCM, by studying its thermal and
cycling stability, health hazard, phase change thermal range, enthalpy and specific heat, besides
analyzing the effect of heat on gravity, thermal cycling and infrared spectroscopy. Furthermore,
J.S. Sage-Lauck et al. [10] explored the use of PCMs to reduce the number of overheated hours
and improve thermal comfort for a case study of passive house duplex, which is located in
Portland, Oregon, USA. For that a duplex home was thoroughly probed to monitor indoor air
quality metrics and building energy power consumption. A unit of the duplex attached to a 130
Kgs of PCM. The performance of the PCM was evaluated through computer simulation by
EnergyPlus building energy simulation model compared with obtained experimental results. The
study observed that with PCM installation could reduce estimated overheated hours throughout
the year from 400 hours to 200 hours. Also reducing the melt temperature of the PCM below
25 °C would negatively impact human thermal comfort. Finally, location change of PCM from
behind the drywall to the interior wall surface reduced zone hours overheating by more than
60%. On the other hand, Jan Kośny et al. [11] investigated the ways to improve the thermal
design of the residential home roofs and floors to minimize the cooling energy consumption in
the cooling-dominated and mixed climatic conditions focusing on dynamic thermal
characteristics of PCM contribution towards insulation. They found that the encapsulation of
PCM into the floor and roof could provide notable reductions of thermal loads by 25% to 35% at
the attic level besides, 5-hour cooling peak load shift in time. The above analysis strengthens the
point that, temporary energy storage can lead to the reduction in power consumption by the
buildings. Talking about uniform temperature maintaining of the buildings by using PCMs,
7
Francesco Fiorito et al. [12] found that these materials, were able to supply dynamic thermal
capacity, especially in light weight building constructions to minimize the fluctuating radiant
temperatures. A test room, with naturally conditioned typical office, had been simulated in
EnergyPlus with the PCM property input. The various locations of unit within the component
and the thickness are carefully studied for optimal savings besides, thermal comfort for
desirability. Interestingly, the influence of the PCM material is directly depending on the
thickness of its layer and on the area of exposed. However, the thermal comfort is valid only for
limited thicknesses. Not only that, in some very well insulated buildings, the thermal resistance
because of the insulation, makes the PCM not effective if integrated in innermost layer
(Conventional). Shazim Ali Memon et al. [13] conducted an extensive study on the embodiment
of PCM into construction materials through various techniques including infiltration and
elements by direct incorporation, with other methods and form-stable composite PCMs. The
comparison between shape-stabilized and form-stable composite PCM has been made to find out
the optimal structure. Besides influence of materials like diatomite, expanded perlite and graphite
etc. that are used to stabilize composite PCM. To determine the chemical compatibility, thermal
properties, thermal stability and thermal conductivity of PCM composite, FT-IR, DSC, TGA and
hot wire method had been proposed and advised that, durability, fire resistance and long term
thermal behavior of PCM enhanced wallboards & concrete should be researched.
2.3 PCM Infiltration into the Porous Materials Making a Composite
The infiltration of PCMs in building envelope has been investigated for many years.
Athienitis et al. [14] have studied about the effect of wall latent heat storage on the thermal
performance of a passive solar test-room by using PCM infiltrated Gypsum inside wall lining.
8
They found that the application of PCMs in building envelope components can reduce the room
temperatures in the morning by 4°C as well as the heating load at nights, due to absorption of
solar heat in the PCM board which is in turn conjunction with melting of the butyl stearate. This
paper also gave a substantial evidence to conclude that PCM applied over a large surface area in
a passive solar building is effective for storage of solar gains and improvement of thermal
comfort. Further the study to maintain constant temperature for a long time in the buildings with
the help of PCM concentration in the building walls was studied by Amar M. Khudhair et al.
[15], summarized the investigation and analysis of thermal energy storage systems and their
efficiency. More importantly, a group headed by Mario A. Medina et al. [16] worked on heat
transfer reduction rate with the help of combining PCMs with Structural Insulated Panels (SIPs)
forming PCMSIP. The heat transfer rate per unit area reduced by the PCMSIPs of 10% and 20%
PCM were 37% and 62%, respectively. The average reductions in heat transfer rate on daily
basis across the PCMSIPs were 33% and 38% by replacing of 10% and 20% SIP with PCM,
respectively. They found that, greater the temperature difference between day and night, the
better the PCM works to reduce the heat transfer through the walls. Wang et al. [17] reviewed
the research on various phase change building materials, thermal energy storage building
envelopes and their thermal performance designs.
2.4 PCM Replacement with Wall Composites
Angela C. Evers et al. [18] incorporated PCMs in building materials for use as latent heat
storage leading to energy savings. In this work two types of PCMs namely, paraffin-based and
hydrated salt-based, were mixed into loose-fill cellulose (obtained from recycled newsprint)
insulation with concentrations of 10% and 20% in a 1.22 m × 1.22 m (48 in. × 48 in.) frame wall
9
cavity. The paraffin-based PCM-enhanced insulation reduced the average peak heat flux by up to
9.2% and total daily heat flow up to 1.2%, when thermally-enhanced frame walls were heated
and allowed to cool down in a dynamic wall simulator on a typical summer day phenomenon.
The hydrated salt-based PCM-enhanced insulation was not suitable for the building application
because of its hygroscopic behavior. Hence, they concluded that paraffin-based PCMs were a
suitable medium for thermal storage in building envelope. J.F. Belmonte et al. [19] discussed
about the importance of PCMs for cooling applications especially in buildings to reduce the
indoor air temperature fluctuations to maximum extent due to solar and internal gains, enabling
passive solar, HVAC system downsizing or off-peak cooling designs. The approach towards
studying discharging heat stored in PCM, differed from the conventional practice of
accomplishing this task by either night cooling ventilation or embedding an active heat
exchanger into the PCM of the wall. Rather in this paper, a PCM was incorporated into the floor,
and a hydronic radiant ceiling system was used as the energy discharge system. The advantages
and disadvantages of this approach in terms of cooling energy demands, thermal comforts of
occupants and design parameters were analyzed using the simulation software TRNSYS and
GenOpt. The results showed that with air-air heat recovery system saved more than 50% cooling
energy demand compared to the same building without PCM. Frédéric Kuznik et al. [20]
conducted a comprehensive review about integration of PCMs in building walls, in which
physical properties of building envelope and PCMs, phase change material integration, thermo-
physical property measurements and advantages and disadvantages of numerical studies were
particularly mentioned. M.A. Izquierdo-Barrientos et al. [21] revealed some interesting details
about the application of PCMs which helped to diminish the extent of instantaneous heat flux
across the wall during the summer due to the elevated solar radiation fluxes. However, there was
10
no noticeable reduction in the total heat lost during the winter regardless of the wall orientation
or PCM transition temperature. Inclusion of a PCM layer increased the thermal load during the
day while decreasing it during the night indicates the high thermal inertia of the walls. A one-
dimensional transient heat transfer model is developed to study the influence of PCMs in
external building walls and solved by a finite differencing method. Later, different external
building wall constructions were being analyzed for a common building wall with changing
PCM layer location, the orientation of the wall, the ambient conditions and the phase transition
temperature of the PCM between temperatures of 5oC and 35oC.
2.5 Composite Encapsulation Techniques
PCM encapsulation can be done in two ways: 1. Macro-encapsulation, 2. Micro-
encapsulation. As the PCM was infiltrated into porous medium, the composite could be
encapsulated by a sheet like membrane (e.g. plastic), which could restrict the PCM flow out of
the porous medium [22]. The plastic sheets were made into containers, sealed with plastic foils,
which were used for the encapsulation of PCM composite. It made a better suit to block all the
vents on the surface of the infiltrated porous medium to restrict the flow, besides being cost
effective. To ensure tightness in the container, the plastic foils were combined with the metallic
layers to improve its strength thereby to stop PCM to settle at the bottom of the container.
On the other hand, micro encapsulation process is simple but compared to macro-
encapsulation, not a cost-effective process. The micro-size PCM was encapsulated in a solid
shell to perform the phase change process. Mahyar Silakhori et al. [23] conducted a research on
thermal cycling of micro-encapsulated paraffin wax/polyaniline for Solar Thermal Energy
Storage, where they used paraffin wax, aniline (C6H7N) as a core (PCM) and shell materials
11
respectively in various ratios like 0.1/0.9, 0.2/0.8, 0.3/0.7, 0.7/0.3 g. The average latent heats of
melting and freezing were around 60–65 J/g for each composite, which makes them reliable in
terms of the thermal cycling test. At the same time, according to Fourier Transform Infrared
Spectrophotometer Results (FTIR), accelerated thermal cycling does not cause any degradation
in the chemical structure of the PCM. Hence, depending on the requirement the type of
encapsulation should be chosen. For current study, as the PCM was already been imbedded in
porous media, macro-encapsulation is a better option.
2.6 Results and their Feasibility Obtained in the Simulation
Zwanzig et al. [24] conducted numerical simulations of phase change material composite
wallboard in the multi-layered building envelope, and realized that the energy consumption can
be reduced, and the peak electricity load can also be shifted by using PCM composite wallboard
when used in the building. The most striking research was done by Augustin Tardieu et al. [25],
to predict the thermal performance of office size test rooms located at the Tamaki Campus,
University of Auckland, New Zealand using EnergyPlus software. Both the simulation and actual
data collected has shown that the use of phase change material wallboards improves the thermal
inertia of buildings for long-term measurements. It showed that PCM-gypsum wallboard as
internal wall linings are successful in capturing solar energy. The simulated results showed that
the additional thermal mass of the PCM could reduce up to 4°C indoor temperature fluctuations
on a typical summer day, showing the ability of the PCM to remain at the comfort level without
air-conditioning. When it comes to the veracity of the building energy estimation, experimental
studies are more accurate than the commercial software tools available in the market like Trane
trace, EnergyPlus, eQUEST, HAP etc. To find the accuracy of them, Chun-long Zhuang et al.
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[26] surveyed the EnergyPlus constructions solution algorithm besides, heat balance method and
came up with a new conduction finite difference solution algorithm and enthalpy-temperature
function features. For that two types of envelopes are considered namely A and B. The relativity
difference on ‘A’ envelope is 12.41% and the least is 0.71% between the simulation and testing
value in 36 hours stretch, whereas on the ‘B’ envelope condition the most relativity difference is
8.33% and the least is 0.33% in sequential 72 hours. The results showed good agreement with
well-established in this simulation tools and shown that the algorithm defined in EnergyPlus
could simulate the latent heat property of PCMs in building construction. When it came to the
authenticity of the EnergyPlus simulation software, Paulo Cesar Tabares-Velasco et al, [27]
showed the procedure to verify and validate the PCM model in EnergyPlus using an approach as
dictated suggested by ASHRAE Standard 140, with analytical verification, comparative testing,
and empirical validation as part of it. This process was valuable, for the reason that, two issues
related to variable thermal conductivities which was later fixed by sizing the variable thermal
conductivity array, and version 7.1 of EnergyPlus was updated with proved PCM model effects.
Preliminary results using whole-building energy analysis showed that careful analysis should be
done when designing PCMs in homes, as their thermal performance depended on several
variables such as PCM properties and location in the building envelope. This research opened
multiple dimensions for future research on PCMs, including the ability to confidently investigate
different PCM material properties, configurations, and locations within a house.
2.7 Energy Savings with Different Techniques
Albeit performance, the investment is also a factor for a success of the product so,
Kaushik Biswas et al. [28] described in his article about a novel PCM made of naturally
13
occurring fatty acids/glycerides trapped into high density polyethylene (HDPE) pellets and its
performance in a building envelope application. The mixture of PCM–HDPE pellets with
cellulose insulation and tested for several months by placing it in the building exterior walls. To
demonstrate the savings of the PCM-enhanced cellulose insulation in reducing the building
envelope heat gains and losses, a parallel comparison was performed with another wall section
filled with only cellulose insulation. Further, numerical modeling of the test wall was performed
to determine the actual impact of the PCM–HDPE pellets on wall-generated heating and cooling
loads and the associated electricity consumption. Yassine Khar bouch et al. [29] aimed to
optimize the design of an air-conditioned multi-zone house integrated PCMs considering the
north Moroccan climate conditions. The objective of this optimization was to minimize the
heating and cooling loads. The methodology of this optimization was based on the coupling
between EnergyPlus as a dynamic simulation tool and GenOpt as an optimization tool for
parametric study. The results show that the obtained optimal design allows minimizing the
energy consumption compared to conventional envelopes.
2.8 Influence of Location and Climatic Conditions in Choosing PCM
After deciding and finding out that the PCM incorporation would have a significant effect
on the power savings, it is very much important to find out the location of it in one of the wall
layers for optimal savings. Xing Jin et al. [30] emphasized the dependence of thermal
performance on PCM location for optimal PCM location study for test system. For that, PCMs
were incorporated in walls between thermal shields, firstly it was encapsulated with polyethylene
flat bubbles then sandwiched between two layers of special custom-made Al foil called “PCM
thermal shield (PCMTS)”. The thermal performance with PCMTS was studied experimentally
14
with Conduction Finite Differentiating Algorithm by a dynamic wall simulator. The optimal
position for PCM was found out to be the farthest from the source simulator close to internal
surfaces. On the other hand, the optimal location for a PCMTS was at 1/5 times thickness of the
insulation cavity distance from the internal surface of the bounding wallboard. The average peak
heat flux reduction and load shifting time were approximately 41% and 2 hours, respectively at
the specified location. Nevertheless, much of research on PCM embedded building envelope is
focusing on PCM embedded in metal (such as aluminum), Gypsum wallboards, concrete, clay
bricks or insulation materials in the building envelope [31-34].
2.9 Uniqueness of this Research
The bio-product materials used in the current study are available in the market at low
prices compared to the other building envelope materials such as steel, aluminum, or other
metals. For this reason, bio-products, such as wood etc., are being, and have the great potential to
be, used in the most of residential building envelopes. When the paraffin wax is used directly as
one of the wall layers, as some damage occurs, the liquid PCM may drain out quickly. Whereas,
bio-product/PCM composite provides certain level of resistance against the leakage and gives
time to rectify and fill the gaps.
This research work conducted comprehensive studies on the bio-product/PCM composite
materials’ thermal properties and the building energy savings by using various bio-product based
composites.
15
CHAPTER 3
METHODOLOGY
3.1 Open Porosity Measurement by Pycnometer
The amount of PCM that could be infiltrated into the bio-products, determined by the
empty space inside it (open porosities). And the instrument called Pycnometer (Figure 3.1) could
be utilized to calculate that property. This instrument is specially designed to measure the true
volume, densities, and porosities of foam and bulk solid materials by employing Archimedes’
principle of fluid displacement and technique of gas expansion (Boyle’s law). Basically, a gas is
used as displacing fluid, since it penetrates through the finest pores with promising maximum
accuracy. Helium gas is highly recommended as fluid, since its small atomic dimensions with
assuring accuracies up to the pore sizes close to 0.2 nm in diameter.
To find the open porosities of the foam materials like woods, a specified Ultra-Foam
version in Pycnometer as shown in figure 3.1 was used which automatically measures the open
and closed cell content. For this study two types of wood samples were being tested – cherry and
pine woods. The sizes of each wood sample for the test was around 2.7cm×2.6cm×2.1cm, which
happens to be accommodated by medium size cell of about 28.9583 cm3 under 6 psi pressure.
Finally, the absolute volumes, densities and open porosities were obtained by providing the
system and sample properties like pressure, purge time, number of runs, cell size, weight and
volume. The governing equation of Pycnometer to find the absolute volume, which leads to the
calculation of open porosities is as indicated in the equation 3.1
𝑉𝑉𝑐𝑐 = Vcal + 𝑉𝑉𝐴𝐴(P2/𝑃𝑃1)−1
(3.1)
Where Vc is the volume of the whole cell (where sample can be placed), Vcal is the
calculated solid volume of the porous sample, which was later being provided to the Pycnometer,
16
VA is the absolute volume of the sample, obtained when Helium gas was passed through the
pores, P2 is the pressure in the value that was connected to the cell and P3 is the final pressure
after the value was being released.
Figure 3.1: Pycnometer (Ultra-Foam 1200e)
3.2 Hot Disk Thermal Constant Analyzer for Thermal Conductivity Measurement
Though the current research is focused on to find out the importance of latent heat
capacity of bio-products/PCM composite in improving the building envelope insulation, thermal
conductivity would help to overcome the minor energy saving errors. Hot disk thermal constant
analyzer is currently one the best instrument used to calibrate the thermal conductivity, specific
heat capacity, diffusivity and other thermal properties. It uses a transient plane source (TPS)
thermal characterization technique (procedure of a transiently heated plane sensor) for optimal
accuracy in complex materials, like Nano-particles.
17
The thermal conductivities of wood and wood/PCM composite materials were measured
on a Hot plate thermal constant analyzer (TPS 1500), with specifications mentioned as in Table
3.1. The sample was placed in such a way that two wood specimens sandwich the Kapton sensor
(has Ni spiral for heating), which is used as both the heat source and a temperature sensor (9 mm
diameter circular flat sheet for large samples). The whole set was in turn placed in an enclosure
to restrict any air current influence on readings. The test was conducted over a 160 second period
with a power of 37.6 mW and a reference resistance of 6.2 ohms to raise the temperature by 3oC.
Finally, the heat supplied per unit time and unit area would be used to determine the thermal
conductivity. The experimental set-up is displayed in Fig 3.2 (a), (b) &(c).
Table 3.1: Specifications of TPS 1500 [35]
Thermal Conductivity 0.01 to 400 W/m/K.
Thermal Diffusivity 0.01 to 100 mm²/s.
Specific Heat Capacity Up to 5 MJ/m³K.
Measurement Time 20 to 5120 seconds.
Reproducibility Typically, better than 1 %.
Accuracy Better than 5 %.
Temperature Range -50 °C to 750 °C.
Core Instrument Ambient
With Furnace Up to 750 °C
With Circulator -35 °C to 200 °C.
Power Requirements Adjusted to the line voltage in the country of use.
Smallest Sample Dimensions
3 mm × 13 mm diameter or square for bulk testing. 20 mm × 7 mm diameter or square for one-dimensional testing.
Sensor Types Available Kapton sensors: 5465, 5501, 8563, 4922, 5599. Mica sensors: 5465, 5082, 4921, 4922, 5599. Teflon sensors: 5465, 5501
The governing equation for in-plane and through-plane thermal conductivities for Hot
disk thermal constant analyzer is indicated in the equation 3.2. The first term represents
18
accumulation of thermal energy, the second term radial (referred to as in-plane in our
experiments) heat conduction, the third term axial (referred to as through-plane in our
experiments) heat conduction, and the final term is a heat source.
𝜌𝜌𝐶𝐶𝑝𝑝𝜕𝜕𝜕𝜕𝜕𝜕𝜕𝜕
= kin1𝑟𝑟 𝜕𝜕𝜕𝜕𝑟𝑟𝑟𝑟 𝜕𝜕𝜕𝜕
𝜕𝜕𝑟𝑟 + 𝑘𝑘𝜕𝜕ℎ𝑟𝑟𝑟𝑟
𝜕𝜕2𝜕𝜕𝜕𝜕2𝑧𝑧
+ 𝑄𝑄𝑟𝑟𝛿𝛿(𝑟𝑟 − 𝑟𝑟′)𝛿𝛿(𝑧𝑧)𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 (3.2)
where ρ is the density (kg/m3), Cp is the specific heat of the sample (J/(kg·K)), T is the
temperature (K), kin and kthru are the in-plane and through-plane thermal conductivities of the
sample (W/m·K), t is the time of the measurement (s), δ is the Dirac delta function ( 𝛿𝛿(𝑧𝑧) =
1𝑎𝑎√𝜋𝜋
𝑒𝑒−𝑧𝑧𝑎𝑎
2
, z and a indicate length through plane and amplitude of the curve, respectively), r’ is
the radius of one of the ring sources, and Qr is the power supplied to that ring per unit length of
the ring (W/m). The total power for each ring is proportional to the circumference of the ring
2𝜋𝜋r’, the cumulative of all such power for the rings together is Q (W). This total power Q is an
input parameter to the Hot Disk Thermal Constants Analyzer. The initial sample temperature was
provided in order to compare with the consecutive temperature readings.
The average transient temperature increase of the sensor is simultaneously measured by
recording the change in electrical resistance of the nickel sensor by equation 3.3:
÷÷ø
öççè
æ-=D 11
no
n
RR
Tb (3.3)
where ΔT is the change in temperature (K) at time t, β is the temperature coefficient of resistance
(TCR) of the Ni sensor material, Rno is the electrical resistance of the Ni (Ω) at time 0, Rn is the
electrical resistance of the Ni (Ω) at time t. The thermal conductivities from equation 3.2 of the
specimen is estimated by correlating temperature difference from equation 3.3 through the
following equation:
19
∆𝑇𝑇 = 𝑃𝑃
𝜋𝜋32 𝑎𝑎 𝐾𝐾𝑖𝑖𝑖𝑖𝐾𝐾𝑡𝑡ℎ𝑟𝑟𝑟𝑟
𝐹𝐹(𝜏𝜏) (3.4)
where P is the power dissipation in the probe and )(tF is a dimensionless time dependent
function of τ=(αint)/𝑎𝑎2 that describes the heat conduction of sensor with given by an integral
of a double series over the number of rings m:
ò å å úû
ùêë
é÷øö
çèæ
÷÷ø
öççè
æ +-+=
= =
--t
sss
st0 1 1
22022
2222
24exp)]1([)( d
mlkI
mklklmmF
m
l
m
k (3.5)
Equations 3.2 through 3.5 are used to determine the in-plane and through-plane thermal
conductivity of the composite. Where αin is the in-plane thermal diffusivity, a is the radius of the
largest ring (of Ni disk) and t is the time step, I0 is the modified Bessel function. To calculate the
thermal conductivity, a series of computational plots of ΔT versus F(τ) are made for a range of
αin values. The value of αin will yield a straight line for the ΔT versus F(τ) plot. This optimization
process can be done by the software until an optimized value of αin is found [36].
(a) (b)
20
(c) Figure 3.2: (a) Hot plate thermal constant analyzer setup, (b) TPS 1500, (c) Dynamic sensor
3.3 Heat Capacity Measurement by Differential Scanning Calorimeter (DSC)
In order to categorize the best bio-product/PCM composite with high latent heat capacity,
DSC helps to differentiate them based on the distribution and consistency of PCM by testing
them at various locations. The basic principle of detecting phase transformations (latent heat of
fusion) is that when the sample undergoes a phase transitions, heat needs to flow into it to
maintain the reference (sapphire) temperature close to the sample. Amount of heat flow to the
sample depends on whether the process is exothermic or endothermic. Heat addition is due to the
absorption of heat by the sample as it undergoes the endothermic phase transition from solid to
liquid to maintain equilibrium temperature with reference and vice versa in the case of
exothermic phase transformation according to the equation 3.3 and represented in Figure 3.3.
H= C·A (3.6)
where C indicates calorimetric constant and A indicates area under the latent heat curve
21
Figure 3.3: Schematic DSC test on PCM [37]
For the experiment, 5 mg specimens from various locations of the samples were tested by
placing them in a holding pan with lid. Later, the temperature was varied from 20oC to 70oC at
the heating/cooling rate of 0.5oC/min with 13 steps including 2-minute gap between each process
for almost 1.2 hours. The cooling and heating of chamber where the sample and reference were
placed, was taken care by the water bath (chiller) located beneath the equipment (Figure 3.4 (a),
(b)) with Nitrogen gas as sample purge.
(a) (b)
Figure 3.4: (a) DSC chamber set-up (b) Chiller
22
3.4 Temperature Variation Measurements
Data acquisition systems are meant to collect the information regarding some phenomena
or process of a specific quantity. For the current study the temperature variation in the different
containers (bio-product and their composites) on a hot plate maintained at 100 °C, were being
sensed by K-type thermocouple and later deciphered with the help of OMB-DAQ-2416 (device
that can read various types of electrical signals generated by thermocouple). It was found that the
latent heat capacity of the infiltrated bio-product composite takes more time, to reach a specific
temperature than the other. The containers holding different samples were identical and heated
up under the same conditions besides that, thermocouples were fixed in the same position in each
container for the comparison. The set-up is as shown in the Figure 3.5 (a), (b), (c).
(a) (c) Figure 3.5: (a) sample containers placed on the hot plate which is set to 100oC (b) DAQ (c) DAQ software which tracks the temperature variation.
(b)
23
3.5 eQUEST Energy Simulations
The effect of specific heat capacity in improving the building envelope insulation and
reducing the power consumption was primarily studied in eQUEST in which, a 2-D CAD model
was built in the Auto-CAD with the dimensions of the ZØE lab spreading across the 1200ft2 area.
The model was separated into 3 thermal zones namely living zone, working zone and rest room
zone by walls. Then, it was imported to eQUEST, where it was extruded to the height of 12ft up
above the ground as shown in the Figure 3.6.
Figure 3.6: 3D Extruded image,
3.5.1 HVAC System in Zero Energy Building (GSHP)
The ZØE lab uses the Ground Source Heat Pumps (GSHP) for temperature control in the
building. The pumps extract and imbue heat (based on the outside temperatures) to the building
by circulating fluid through buried pipes in horizontal trenches or vertical boreholes. The ground
water temperatures are usually stable throughout the year, around 17oC in the Denton, Texas
area. Therefore, the cold water is extracted to cool the lab environment in summers while the
warm water is used to heat up the lab in winters. A well designed GSHP system provides the
lowest running cost of any heating/cooling system because it uses a small amount of electricity
to transfer a large amount of energy from the ground into the lab building. The power required to
pump the water from the ground to the lab is obtained from two sources. One is from the solar
24
panels on the roof top with the 5.6kW grid capacity, the other is from a vertical wind turbine
with the capacity of 3.5 kW. Figure 3.7 indicates the HVAC system water circulation type
throughout the year. And the total power is estimated with the help of supply fan power
consumption in winter as well as summer.
Figure 3.7: 3D HVAC (water circulation) in eQUEST.
3.5.2 Wall Layers in ZØE Building
Three types of wall construction layers, namely masonry, metal panel and structural
insulated panel (SIP) were used for the ZØE lab building. Each wall type was illustrated in detail
in Table 3.2. In the present simulation study, the SIP wall structure and roof were replaced by the
infiltrated wood and non-infiltrated wood. Their impacts on the HVAC (GSHP in the ZØE lab)
load reduction were studied.
Table 3.2: Wall construction layers for the ZØE lab
Masonry wall Metal panel wall SIP wall
1. Masonry 1. Corrugated Metal Panel 1. Textured Coating
2. Building Wrap 2. Building Wrap 2. SIP (Replaced by Wood or Wood/PCM Composite)
25
Masonry wall Metal panel wall SIP wall
3. ½” THK Sheathing 3. ½” THK Sheathing 3. 43MIL MTL studs at 16” OC
4. 43MIL MTL studs at 16” OC
4. 43MIL MTL studs at 16” OC 4. 5/8” THK GYP BD
5. Full Batt Insulation 5. Full Batt Insulation 5. Sealant
6. 5/8” THK GYP BD 6. 5/8” THK GYP BD
7. J-Trim, Typ-Finish to match panel
3.5.3 Conduction Transfer Function (CTF) for Heat Transfer Equations
To find the effect of the material, there are many software tools commercially available to
energy model buildings, like eQUEST, EnergyPlus, HAP, Trane Trace etc. In this section,
eQUEST has been used for tracing out the heat transfer difference between different wall layer
compositions. There are two types of constructions in this tool, quick constructions and delayed
constructions. In reality, all constructions are delayed (i.e. constructions have thermal mass and
therefore there is a time-delay whenever temperature changes, involving specific heat capacity).
The mathematic model required to solve for heat transfer through delayed constructions is much
more complicated than a simple conduction heat transfer calculation. Instead, it uses transfer
functions to approach experimental observation.
Conduction transfer function method is one of the widely used approaches for solving
heat conduction equations. CTF coefficients are a closed form representation of conduction
response factor series that are used to calculate 1-D heat transfer through multi-layer walls, roofs
and floors. [38]. CTFs represent material’s thermal response determined by their own material
properties that include specific heat capacity. This method leads to a simple linear equation
previous and current heat fluxes and temperatures as indicated in the equations 3.8 and 3.10.
26
Whereas equations 3.7 and 3.9 indicate the current hour’s surface temperature and previous total
flux value at exterior surface
(3.7)
qo,θ=-Y0Tis,θ+X0Tos,θ+Qo (3.8)
For the inside heat flux, and
(3.9)
qi,θ=-Z0Tis,θ+Y0Tos,θ+Qi (3.10)
where:
· qo,θ and qi,θ are heat flux at exterior and interior surfaces. Xk, Yk and Zk are exterior,
cross and interior CTFs.
· Tis and Tos are the interior and exterior surface temperatures. Nx, Ny and Nz are
number of exterior, cross and interior CTFs terms.
· φk is the flux coefficient. Nφ is the number of flux history terms. The subscript θ
represents the current time, and δ is time step.
As there was no textbox to enter the property of latent heat capacity in eQUEST, a
technique of converting to specific heat by averaging was being used. i.e. the monthly enthalpy
was calculated by considering a fixed reference temperature pertaining to that month and divided
by the average temperature of Denton which happen to be 18.7oC
𝑄𝑄𝑜𝑜 = −𝑌𝑌𝑘𝑘𝑇𝑇𝑖𝑖𝑖𝑖 ,𝜃𝜃−𝑘𝑘𝛿𝛿+ 𝑁𝑁𝑁𝑁
𝑘𝑘=1
𝑋𝑋𝑘𝑘𝑇𝑇𝑜𝑜𝑖𝑖 ,𝜃𝜃−𝑘𝑘𝛿𝛿+ 𝑁𝑁𝑁𝑁
𝑘𝑘=1
𝜑𝜑𝑘𝑘𝑞𝑞𝑜𝑜 ,𝜃𝜃−𝑘𝑘𝛿𝛿 𝑁𝑁𝜑𝜑
𝑘𝑘=1
𝑄𝑄𝑖𝑖 = −𝑍𝑍𝑘𝑘𝑇𝑇𝑖𝑖𝑖𝑖 ,𝜃𝜃−𝑘𝑘𝛿𝛿+ 𝑁𝑁𝑧𝑧
𝑘𝑘=1
𝑌𝑌𝑘𝑘𝑇𝑇𝑜𝑜𝑖𝑖 ,𝜃𝜃−𝑘𝑘𝛿𝛿+ 𝑁𝑁𝑁𝑁
𝑘𝑘=1
𝜑𝜑𝑘𝑘𝑞𝑞𝑖𝑖 ,𝜃𝜃−𝑘𝑘𝛿𝛿 𝑁𝑁𝜑𝜑
𝑘𝑘=1
27
3.6 EnergyPlus Simulations
EnergyPlus is a building energy simulation program designed by the U.S. Department of
Energy. It has the capacity to perform many types of calculations for building loads, but for this
study the focus was on heating and cooling loads. The program can be set up to provide output
detailing the heating and cooling load for each zone within the building. EnergyPlus was opted
over eQUEST, as there is no scope for inputting latent heat property of PCMs.
The ZØE building was designed in the exclusive architectural commercial design
software called SketchUp with the area stretching up to 1200ft2 besides, 12ft ceiling height
(Figure 3.8). The design is made into three zones, 1. Mechanical Room 2. Electrical Room 3.
Conditioned Zone, which is relatively different from what has been considered in eQUEST.
Later with the help of extensions, the file had been converted into idf file and imported into
EnergyPlus.
The building version, schedules, people, zones, materials, construction and so on, are
defined and Conduction Finite Differencing algorithm is used for evaluating the latent heat
property to find out the envelope ‘R’ value. The outputs have been studied under Output:
variables tab as cooling and heating loads. The latent heat properties of infiltrated herbs (100.0-
121.8 J/g) and infiltrated pine (45.0 J/g) had been studied and simulated to find out the savings.
Figure 3.8: ZØE building designed in SketchUp for EnergyPlus simulation
28
The governing equation to estimate heat transfer through the wall is represented by the
equation 3.11 [39]. The Conduction Finite Differencing algorithm is used in the EnergyPlus to
solve by Crank-Nicholson solver (numerical method).
𝜕𝜕ℎ𝜕𝜕𝜕𝜕
= 𝜕𝜕𝜕𝜕𝑥𝑥𝛼𝛼 𝜕𝜕ℎ
𝜕𝜕𝑥𝑥 − 𝜌𝜌 ∗ 𝐿𝐿 𝜕𝜕𝑓𝑓
𝜕𝜕𝜕𝜕 (3.11)
where h is volumetric enthalpy, t is time, x indicates the direction heat flow (into the building), α
is the thermal diffusivity, ρ is density of the material, L is the latent heat of fusion of PCM
composite, f is liquid fraction of melt.
29
CHAPTER 4
CHARACTERIZATIONS OF THE BIO-PRODUCT/PCM COMPOSITES’ THERMAL
PROPERTIES
Bio-products, including woods and herbs, were infiltrated by the PCM (paraffin wax) to
form the bio-product based composite materials. In this chapter, the open porosity and density
which define the PCM infiltration performance, thermal conductivity, specific heat, and latent
heat of fusion of composites are characterized. And also, the investigation on temperature
variations of various composites to preliminarily demonstrate the temperature control by PCM is
presented.
4.1 Open Porosities and Densities of Bio-Product and Bio-Product/PCM Composites
4.1.1 Non-Infiltrated Samples
Four non-infiltrated wood samples, in which, two of each cherry and pine wood were
tested. The open porosities of cherry woods were around 42.5% while those of pine woods about
75.0%, as indicated in Figure 4.1.
Figure 4.1: Open porosity of non- infiltrated pine and cherry woods
Pine Cherry0
20
40
60
80
Ope
n Po
rosi
ty o
f N
on-In
filtra
ted
Woo
d Sa
mpl
es in
%
Wood types
30
4.1.2 Infiltration Samples
The wood samples (pine and cherry) were immersed in the liquid paraffin wax. As the
liquid wax was infiltrated into the wood pore through the self-diffusion process, the densities of
infiltrated samples raised. Open porosities of nine samples of each pine and cherry woods, which
were being tested, ranging from 6.7% to 14.4% and 8.7% to 14.6% respectively, as shown in
Figure 4.2. The average weights of pine and cherry woods were 6 g and 8 g compared to 8 g and
9 g for infiltrated woods, respectively. Whereas, the average densities of pine and cherry woods
were 0.40 g/cc and 0.55 g/cc compared to the infiltrated samples of 0.57 g/cc and 0.64 g/cc
respectively.
Figure 4.2: Open porosity of infiltrated pine and cherry woods
4.1.3 Half-Cut Samples
The above infiltrated samples were cut into two halves and tested for open porosities. It
was found that the infiltration was not very uniform inside the wood samples. Very little PCM
permeated to the center of the wood sample. Hence, the average open porosities of the sliced
samples were higher than those of unsliced ones due to the non-uniform infiltration, as indicated
in Figure 4.3. The porosity value increased up to 16.2% in the sliced infiltrated cherry sample,
and up to 19.8% in the sliced infiltrated pine sample.
Pine Cherry0
5
10
15
20
Ope
n Po
rosi
ty o
f In
filtra
ted
Woo
d Sa
mpl
es in
%
Wood types
31
Figure 4.3: Open porosity of sliced infiltrated woods
The porosities of woods are being characterized in Table 4.1.
Table 4.1: Summary of porosities and densities
Type of woods Open porosity ranges
Average densities
Pine 74.7% -75.1% 0.40 g/cc
Cherry 42.5% -42.8% 0.55 g/cc
Infiltrated pine 6.7% -14.4% 0.57 g/cc
Infiltrated cherry 8.7% - 14.6% 0.64g/cc
Half-cut infiltrated pine 13.1 % - 16.1%
Half-cut infiltrated cherry 8.6% -19.8%
The above open porosity measurements were conducted under certain moisture content in
the samples. By mounting them in an oven maintained at 103oC temperature for 24 hours, the
samples were dried, and therefore, the moisture content was determined in these samples. It has
7.0% to 7.1% moisture content for cherry wood samples, 8.1 to 8.3% moisture content in the
pine, and about 0.0% for herb samples by comparing the mass of these samples before and after
the drying process.
Pine Cherry
0
5
10
15
20
Ope
n Po
rosi
ty o
f H
alf-
Cut
In
filtra
ted
Woo
d Sa
mpl
es in
%
Wood types
32
4.2 Thermal Conductivities
Thermal conductivity measurements were conducted on six different samples of each
pine and cherry for four test runs. The experimental results (Figure 4.4) showed a very negligible
difference of thermal conductivities between infiltrated and non-infiltrated wood blocks. The
thermal conductivities of pine and cherry woods were in the range of 0.15-0.2 W/m-K. The same
measurement range were observed for the wood/PCM composites as displayed in Figures 4.4(b)
and (d). Hence, the PCM did not affect the original thermal resistance of the wood materials.
This phenomenon may be explained by K. Lafdi et al. [40], in which the effects of
porosity and pore size of aluminum foam on the overall thermal conductivity of the Al/PCM
composite were investigated. It was observed that, by using bigger pore size aluminum foams,
the heat transfer performance was worse than the smaller pore size foams. When PCM was
infiltrated into the foam, the natural convection of liquid PCM inside the pore can help to
enhance the heat transfer performance. On the other hand, lower porous size has greater heat
conduction through material, making heat transfer rate close to the non-infiltrated Al sample.
(a) (b)
0
0.05
0.1
0.15
0.2
1 2 3
Ther
mal
Con
duct
ivity
(W/m
K)
Infiltrated Pine Wood Samples
0
0.05
0.1
0.15
0.2
1 2 3Ther
mal
Con
duct
ivity
(W/m
K)
Non-Infiltrated Pine Wood Samples
33
(c) (d)
Figure 4.4: Thermal conductivity measurements for various types of woods and infiltrated woods. (a) For non-infiltrated pine wood samples, (b) for infiltrated pine wood samples with PCM, (c) for non-infiltrated cherry wood samples, (d) for infiltrated cherry wood samples with PCM.
4.3 Specific Heat and Latent Heat of Fusion
When the atmospheric temperature falls in the melting range of PCM, it would undergo
phase change process during which the material can absorb/release huge amount of heat while
maintaining constant temperature for efficient thermal control in the building. The latent heat of
fusion and specific heat of the bio-product/PCM composite materials were measured by the
differential scanning calorimeter (DSC). The measurement temperature range was from 20 °C to
70 °C with the heating/cooling rate of 0.5 °C/min in the DSC. Three test runs were repeated for
each test sample. The average values of the three runs were obtained for 25 samples of pine,
cherry and herb composites at various locations indicated in Figures 4.6 and 4.7
The specific heat and the latent heat of fusion measurement results for wood samples and
wood/PCM composite samples are shown in Figure 4.6. The specific heat of both pine and
cherry woods are similar based on the DSC measurements, around 2.3 J/g·°C at room
temperature as indicated in the figures 4.6(a) and (c). The latent heat of fusion of pure paraffin
wax was measured about 146 J/g with the peak melting point at 52.5 °C. Its melting temperature
0
0.05
0.1
0.15
0.2
0.25
1 2 3
Ther
mal
Con
duct
ivity
(W
/mK
)
Non-Infiltrated Cherry Wood samples
34
range was between 45 °C and 58 °C as shown in figure 4.5. The average latent heat of fusion was
around 30 J/g with the peak melting point of 54 °C for the infiltrated cherry wood while it was
approximately 45 J/g with the peak melting point of 54 °C for the infiltrated pine wood. The
results were consistent with open porosity measurements. Due to the high-volume occupation of
the PCM in the pine wood, the latent heat of fusion of the pine/PCM composite was higher than
that of the cherry/PCM composite.
However, because of the non-uniform infiltration in the wood samples, there was little
PCM filled at the center of the sample. Thus, very low latent heat values were detected at the
center of the infiltrated cherry and pine samples, as shown in Figures 4.6 (c) and (f). Wood is
usually a hydrophilic material, while wax is hydrophobic material. Therefore, the paraffin wax
did not show a good and uniform infiltration in the wood samples. In order to improve the self-
diffusion of liquid wax into wood, the temperature of the liquid was increased from 70 °C to 90
°C during the infiltration process to help the self-diffusion of molten wax into the wood porous
media. Nevertheless, it was found that the effect of liquid temperature on the infiltration process
was very minor for the wax and wood materials. Hence, to improve the infiltration of PCM into
the porous media, it is proposing to use the similar hydrophobic or hydrophilic materials for
PCM and porous media.
Figure 4.5: Specific heat and latent heat of fusion of pure paraffin wax
35
(a) Non-infiltrated cherry wood sample
(b) Infiltrated cherry wood sample
(c) Non-infiltrated pine wood sample
36
(d) Infiltrated pine wood sample
(e) Infiltration at the center in cherry
(f) Infiltration at the center in pine
Figure 4.6: Specific heat and latent heat of fusion of the wood samples and the wood/PCM composite materials from the DSC measurements (a to f).
37
Therefore, another bio-product, herb cellulose chips, was investigated due to its
hydrophobic property. It was found that the infiltration rate of paraffin wax in the herb cellulose
chips was significantly increased. The mass percentage of PCM in the infiltrated herb composite
was much higher than that in the infiltrated wood composite. The mass of herb/PCM composite
samples was around 8 grams compared to that of pure herb samples before infiltration of
approximately 2 grams. Significant amount of paraffin wax was permeated into the herb porous
media because of the hydrophobic nature of the herbs. The latent heat of fusion of herb/PCM
composite reached around 100 J/g when the infiltration process was conducted under one
atmosphere pressure and increased to 121 J/g when the infiltration process was under high
pressure of 100 psi. The latent heat of fusion and specific heat of the herb/PCM composite were
depicted in the following figures (Figure 4.7). Table 4.2 summarized the latent heat of fusions of
various bio-product/PCM composite samples.
Infiltrated herb material through self-diffusion process
38
Infiltrated Bio-product material by adding additional pressure (100psi)
Figure 4.7: Specific heat and latent heat of fusion of the herb /PCM composite materials from the DSC measurements (a, b)
Table 4.2: Summary of average latent heat of fusions for various bio-product composites
Type of Bio-Product Composites Average Latent Heat of Fusion Infiltrated pine 45 J/g Infiltrated cherry 30 J/g Self-diffused herb by PCM 100 J/g Pressure- diffused herb by PCM (under 100 psi) 121 J/g
4.4 Temperature Control by Using Bio-Product/PCM composites
It was found that the temperature increase was slower in the case of bio-product/PCM
composite material, conveying that phase change process around the melting temperature range
of PCM could help to mitigate the temperature increase, and therefore, could achieve energy
savings if used in the building envelope.
4.4.1 Infiltrated and Infiltrated Pine Samples
It was observed in the graph that the surrounding temperature with the infiltrated sample
(red line) of weight 7.4 gm increased slowly compared to that with the non-infiltrated wood (blue
line) of 6.3 gm. After a period of time, the temperature inside the container reached steady state
39
and leveled off for both non-infiltrated and infiltrated pine wood sample conditions as shown in
Figure 4.8 as typical sample. Through the studies of the temperature profiles, it was found that
the PCM could help mitigate the temperature increase in the space.
Figure 4.8: Typical temperature vs time curves (comparison of infiltrated and non-infiltrated pine woods)
4.4.2 Non-Infiltrated and Infiltrated Cherry Samples
Similar as the previous case, the infiltrated cherry wood sample of 8.7 gm could also
mitigate the temperature increase rate in the space compared to the non-infiltrated cherry sample
of 8.0 gm, as shown in Figure 4.9 as typical sample.
40
Figure 4.9: Typical temperature vs time curves (comparison of infiltrated and non-infiltrated cherry woods)
4.4.3 Space Temperature Control by Using Herb/PCM Composites
From Figure 4.10, it is evident that the environment temperature with infiltrated herb
samples takes more time than that with non-infiltrated herbs to reach a specific temperature due
to the latent heat capacity of PCM. The herb sample was 1.8 gm, whereas maximum infiltrated
herb was 7.2 gm. As the amount of PCM is higher in this case, the curve compared to the pine
and cherry, which is more consistent.
41
Figure 4.10: Typical temperature vs time curves (comparison of infiltrated and non-infiltrated herbs)
4.4.4 Temperature Difference Comparison between Pine, Cherry and Herb/PCM Composites
The gap i.e. temperature reduction between bio-products and their composites are being
plotted against the time to find which one of it would hold more heat. It is evident from Figure
4.11 that, herb/PCM composite absorbs more heat than pine and cherry wood composites, as the
amount of paraffin wax in it was 5.4 gm compared to 1 gm and 0.7gm for pine and cherry/PCM
composites respectively. More PCM implies higher latent heat of fusion, and this in turn
determines the resistance towards heat transfer in the walls, which is directly proportional to
energy savings.
42
Figure 4.11: Temperature reduction using infiltrated bio-products compared to non-infiltrated ones
4.4 Alternatives to Overcome Inflamability of Paraffin Wax
Though the paraffin wax performs well in storing the energy, they are inflammable, which
increases the risk of fire accidents in building envelope [41]. Using other types of PCMs, such as
inorganic PCMs or fatty acid esters could restrict to maximum extent.
Inorganic materials (such as CaCl2∙6H2O, KF∙3H2O etc.) have similar latent heat per unit
mass as organic PCMs, in fact, their volumetric latent heat values are higher because of the
higher density. The melting ranges of inorganic PCMs are from 41° to 266°F (5° to 130°C).
However, their main drawbacks are severe super cooling and separation problems.
43
On the other hand, fatty acid esters are less expensive and significantly less flammable.
They are made from waste feed stocks such as soybean oils, coconut oils, palm oils, and beef
tallow. These fatty-acid ester PCMs are expected to remain stable during thousands of phase-
change cycles with no risk of oxidation as they are fully hydrogenated [42]. Furthermore, there
are coatings available in the market to overcome fire accidents, which are water based nontoxic,
thin film intumescent fire retardant and resistant paint. These coatings can reduce the risk of fire
incidents when applied on organic PCM based composite materials.
44
CHAPTER 5
BUILDING ENERGY SIMULATION RESULTS
The effect of bio-product/PCM composite in the building envelope on the energy savings
was studied through building simulation tool (eQUEST and EnergyPlus). A unique Zero Energy
(ZØE) Research Laboratory at University of North Texas (UNT) was used as a simple
apartment-type building model for the simulations. The ZØE lab has the area of 1200ft2. Various
conditions in the lab were considered in the simulation model, including the cooling/heating
technologies, wall construction layers, lighting, glaring and other factors.
The PCM melting range is considered from 13oC to 22oC with peak of 18.7oC (Butyl
Stearate paraffin) which is an average temperature of Denton (similar to DFW area) throughout
the year.
5.1 Results on eQUEST
Through the simulations, it was found that the space cooling power consumption was
reduced by 2.7% and the spacing heating power consumption was reduced by 11.3% annually by
using the wood/PCM composite compared to using non-infiltrated wood in the SIP wall
construction as shown in Figure 5.1(a). The simulations were using Butyl Stearate paraffin as the
PCM (melting point around 18°C) considering the annual temperatures in the Texas area.
Different PCMs could be used based on the different local weather conditions. For instance,
Vinyl Stearate paraffin with melting point of 27°C was used when we just consider the reduction
of the HVAC power consumption in the summer time in the Denton, Texas area. The simulation
results show that the space cooling power consumption could be reduced by 8.1% in July
(summer season) as conveyed by Figure 5.1 (b)
45
(a) (b)
Construction layers with wax-infiltrated wood Construction layers with conventional wood
Figure 5.1: Energy consumption in the ZØE lab through the eQUEST simulations (a) Annual energy consumption, (b) Energy consumption in the summer month (July).
The following graph (figure 5.2 (a), (b)) indicates that, from November through April, the
monthly bills are significantly less for the walls with infiltrated wood which is close to 2%
savings throughout a year by comparing to the non-infiltrated wood panel in the wall structure,
and 4.1% savings for the month of July (summer season only)
(a) (b) Pure wood
Wall with wax infiltrated wood
Figure 5.2: (a) Monthly utility bills through out a year (b) Utility bills exclusively for the month of July (Summer)
46
Figure 5.3 shows the annual power consumption variation with and without PCM
(paraffin wax) in the wood in both wall structure and roof layer. It is evident that the space
heating power consumption has been reduced by 16.7%, with negligible change in the cooling
load. Finally, Table 5.1 represents the summary of savings for various wall conditions in
eQUEST.
Figure 5.3: Energy consumption in the ZØE lab when replaced with PCM composite in roof and wall constructions
Table 5.1: Summary of typical energy savings in eQUEST
Comparison between bio-products and bio-product/PCM composite composite Replacement in Cooling energy savings (%) Heating energy savings (%)
In the wall 2.7 11.3 In the wall and roof Negligible 16.7 The herb/PCM composite based building envelope was also simulated by using eQUEST,
but it showed the similar energy savings for the herb/PCM composite compared to the wood
based composite. Hence, inputting average effective specific heat value to indicate the latent heat
47
of fusion in eQUEST is not a very accurate way to find out the energy savings. The software tool
is ineffective in evaluating the importance of latent heat property of PCM when it is used in the
wall structure. So, to study the effect of latent heat on energy savings, a more sophisticated tool
i.e., EnergyPlus should be employed.
5.2 Results Obtained on EnergyPlus
5.2.1 Comparison of the Heating and Cooling Loads between Conventional and Bio-Product/PCM Composite Embedded Building Envelopes As the number of layers increase in the wall construction the percentage savings would
be reduced. Figures 5.4 (a), (b), (c) are the examples to explain this phenomena. The heating
power consumption throughout the year for SIP layer in the wall and roof was 1,602 kWh. When
it was replaced by a pressurized PCM infiltrated herb material, the consumption would be 1,561
kWh, which was reduced by 2.6%. On the other hand, when the herb composite was added to the
SIP roof, it consumed about 1,280 kWh of power annually, which is 20.0% less than the original
SIP layer roof.
The cooling power consumption in a year for only SIP Layer in the wall and roof was
5,590 kWh compared to 6,114 kWh when it was replaced by pressurized PCM infiltrated herb,
which was increased by 9.4%. Conversely, when the herb/PCM composite layer was added to
the SIP roof, it consumed 5,248 kWh of power anually, which was 6.1% less than the original
SIP roof.
48
(a)
(b)
0
100
200
300
400
500
Pow
er C
onsu
mpt
ion
Months
Space Heating Power Consumption(kWh)
Only SIP Maximum infiltrated herb SIP + maximum infiltrated herb
0200400600800
100012001400160018002000
Pow
er C
onsu
mpt
ion
Months
Space Cooling Power Consumption (kWh)
Only SIP Maximum infiltrated herb SIP + maximum infiltrated herb
49
(c)
Figure 5.4: (a) Monthly heating load distribution (b) Monthly cooling load distribution (c) Annual cooling power savings for different combinations with composites, compared with SIP roof
5.2.2 Replacing SIP Layer by Composite Materials
The SIP layers are present in both roof and SIP wall structure. When replaced with bio-
products and PCM infiltrated bio-products, the output results were obtained and plotted as shown
in the figures. Figures 5.5 (a) and (b) indicate the space heating power consumption comparison
monthly and annual savings. The results are as follows:
Annual heating power consumption was 1,561 kWh with pressurized wax infiltrated
herb in the building envelope compared to the power consumption of 1,859 kWh for non-
infiltrated bio-products imbedded building envelope, i.e., 16.0% of power savings were obtained.
Similarly, for the self-diffused wax infiltrated herb the consumption was 1,574 kWh and the
savings were 15.3%.
Only infiltrated herb
SIP + infiltrated herb with pressure
-10
-5
0
5
10
15
20Sa
ving
s (%
)
Types of wall layer materials
Load Comparision with SIP layer
Heating Load Savings (%) Cooling Load Savings (%)
50
On the other hand, for wax infiltration pine the heating power consumption was 1,652
kWh with only 11.0% of energy savings compared to non-infiltrated pine material. This shows
that the latent heat of fusion playes a crucial role in the heat load savings and could be more if
the value is higher.
(a)
(b)
Figure 5.5: (a) Monthly heating load distribution, (b) Annual heat load savings for different composites compared with wood/ herb
Figure 5.6 (a) and (b) indicates the space cooling power consumption comparison
monthly and annual savings. Annual cooling power consumption was 6,114 kWh with
0100200300400500600700
Pow
er C
onsu
mpt
ion(
KWh)
Months
Space Heating Power Consumption(kWh)
Herb with maximum infiltration Self -diffused herb
Average infiltrated pine Wood/ Herb
Herb with maximum infiltration
Herb with self-diffused infiltration
Average wax infiltrated pine
02468
1012141618
Savi
ngs(
%)
Types of Bio-Products
Heating Load Savings
51
pressurized wax infiltrated herb in the building envelope compared to the power consumption of
6,875 kWh for non-infiltrated bio-products imbedded building envelope, i.e., 11.0% of power
savings were obtained. Similarly, for self-diffused wax infiltrated herb, the consumption was
6,184 kWh and the savings were 10.0%.
On the other hand, for wax infiltrated pine space cooling power consumption was 6,456
kWh with only 6.0% of energy savings compared to non-infiltrated pine material. Once again it
proves that the latent heat of fusion plays a crucial role in the savings.
(a)
(b)
Figure 5.6: (a) Monthly cooling load distribution (b) Annual cooling power savings for different composites compared with wood/ herb
0500
100015002000
Pow
er C
onsu
mpt
ion(
KWh)
Months
Space Cooling Power Consumption (kWh)
Herb with maximum infiltration Self-diffused infiltrated herb
Averagewax infiltrated pine Wood/Herb
Herb with maximim infiltration
Herb with self-diffused infiltration
Average wax infiltrated pine
0
2
4
6
8
10
12
14
Savi
ngs
(%)
Types of Wood
Cooling load Savings
52
5.2.3 Replacement and Addition of Composite Materials for Wall and Roof Structures
In this case the SIP layer in one of the wall structure was replaced with the bio-
product/PCM composites. For the roof, another composite layer was added on the SIP. Figures
5.7 (a) and (b) indicate the monthly space heating power consumption and annual savings,
respectively.
Annual heating power consumption was 1,280 kWh with pressurized wax infiltrated herb
in the building envelope compared to the power consumption of 1,374 kWh for non-infiltrated
bio-products embedded building envelope, i.e., 6.9% of power savings were obtained. For self-
diffused wax infiltrated herb the consumption was 1,286 kWh and the savings were 6.4%. On the
other hand, for wax infiltrated pine space heating power consumption was 1,328 kWh with 3.4%
savings only. It was quite evident that when number of insulating layers increased in walls, the
percentage of savings by PCM would be reduced, because the SIP layer was already efficient for
the indoor thermal control.
(a)
0
100
200
300
400
500
Pow
er C
onsu
mpt
ion
(KW
h)
Months
Space Heating Power Consumption(kWh)
Herb with maximum infiltration Self diffused infiltrated herbAverage wax infiltrated pine wood Wood/ Herb
53
(b)
Figure 5.7: (a) Monthly heating load distribution, (b) Annual heating load savings for different composites compared with wood/ herb
Figures 5.8 (a) and (b) indicate the monthly space cooling power consumption and annual
savings, respectively. Annual cooling power consumption was 5,248 kWh for the pressurized
wax infiltrated herb imbedded building envelope compared to the power consumption of 5,459
kWh for the non-infiltrated bio-products based envelope structure, i.e., 3.9% of power savings
were obtained by using PCM. For the self-diffused wax infiltrated herb, the power consumption
was 5,266 kWh and savings were 3.5%. On the other hand, for wax infiltrated pine wood space
cooling power consumption was 5,342 kWh with 2.2% of energy savings only.
The range of energy savings for maximum infiltrated herb, self-diffused herb was
comparitively less in all cases between 0.05 to 0.15%, because of their consistant wax
infiltration. Whereas, for average infiltrated pine, the range was from 0.1 to 0.3%.
Herb with maximum infiltration
Herb with self-diffused infiltration
Average wax infiltrated pine
0
1
2
3
4
5
6
7
8(%
) Sav
ings
Types of Wood
Savings Heating (%)
54
(a)
(b)
Figure 5.8: (a) Monthly cooling load distribution (b) Annual cooling power savings for different composites compared with wood/herb
Specifically, in all cases the heating and cooling load savings were higher for the months
of April, October and November as the average temperatures are falling in the range of PCM
melting temperature, i.e., 18.7oC (average annual temperature of Denton, TX). Nevertheless, for
0200400600800
1000120014001600
Pow
erCo
nsum
ptio
n(K
Wh)
Months
Space Cooling Power Consumption(kWh)
Herb with maximum infiltration Self-diffused infiltration
Average wax infiltrated pine Wood/Herb
Herb with maximum infiltration
Herb with self-diffused infiltration
Average wax …0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
(%) S
avin
gs
Types of Woods
Savings Cooling (%)
55
the months of June, July and August which have the average temperatures above 25oC, the
savings were less. Table 5.2 represents the summary of savings for various cases.
Table 5.2: Summary of typical Energy savings in EnergyPlus
Replaced by composites in SIP wall structure and compared with conventional building envelope Case 1 (Maximum infiltrated herb) Heating load savings (%) Cooling load savings (%) Composite Added to the roof 20.0 6.1 SIP replaced by composite in the roof 2.6 -9.4 Replaced SIP layer in SIP wall construction, roof by bio-products and compared with composite bio-products Case 2 (All bio-product types) Heating load savings (%) Cooling load savings (%) Maximum infiltrated herb 16.0 11.0 Self-diffused herb 15.3 10.0 Average infiltrated pine 11.0 6.0 Replaced SIP layer in SIP wall structure by bio-products, added to roof and compared with composite bio-products Case 3 (All bio-product types) Heating load savings (%) Cooling load savings (%) Maximum infiltrated herb 6.9 3.9 Self-diffused herb 6.4 3.5 Average infiltrated pine 3.4 2.2
5.2.4 Inside and Outside Wall Face Temperature Distribution (Hourly) for a Single Hot and
Cold Days of the Year Figures 5.9 (a), (b), (c), (d) indicate the hourly temperature distribution at inside and
outside faces of a wall on hot day (July 28th) and cold day (December 7th) in DFW area. The
yellow curve distribution (SIP replaced by maximum infiltrated herb in SIP and roof structures)
in all graphs represent more consistancy (or stability) than others, the second position would be
for SIP replacent by maximum infiltrated herb in wall and roof structures. This test proves that,
latent heat property relates to thermal control of the building envelope.
56
With usage of herb/PCM composite ,the total of heat gained at the exterior position of
the walls, to be reduced by a drastic amount which results in lower heat gains to the conditioned
space (as the temperature on the interior walls is low).
The energy savings obtained for the herb/PCM composite in the wall and roof, is based
on the net peak load shift. In figure 5.9 (a) from 8:00AM to 7:00PM (summer) the peak load has
been mitigated, however, in the night during heat rejection, interior wall temperature raised. This
overall shift during the day and nights would determine the energy savings. And vice versa
would the case for winters.
(a)
(b)
20
22
24
26
28
30
1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4TEM
PERA
TURE
(CEL
SIU
S)
HOURS
SUMMER INSIDE ROOF SIP conventional
SIP replaced with max.infiltrated herb
Infiltrated herb replaces the SIP wall and adds above the SIP in the roof
0
50
100
1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4TEM
PERA
TURE
(CEL
SIU
S)
HOURS
SUMMER OUTSIDE ROOFSIP conventionalSIP replaced with max.infiltrated herbInfiltrated herb replaces the SIP wall and adds above the SIP in the roofoutside air temperature
57
(c)
(d)
Figure 5.9: Hourly temperature distributions along (a) Summer inside wall (b) Summer outside wall faces (c)Winter inside wall (d) Winter outside wall faces
10
12
14
16
18
20
22
1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4
TEM
PERA
TURE
(CEL
SIU
S)
HOURS
WINTER INSIDE ROOFSIP conventional
SIP replaced with max.infiltrated herb
Infiltrated herb replaces the SIP wall and adds above the SIP in the roof
-5
0
5
10
15
20
1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4
WINTER OUTSIDE ROOFSIP conventional
SIP replaced with max.infiltrated herb
Infiltrated herb replaces the SIP wall and adds above the SIP in the roof
outside air temperature
58
Figures 5.10 (a), (b), (c), (d) represent the temperature difference at the interior and
exterior roof faces between conventional SIP roof and herb/PCM composite roof conditions in
summer and winter days (i.e., the temperature difference is equal to temperature for conventional
SIP roof condition minus that for herb/PCM composite roof condition). The “yellow curve”
condition has much more temperature reduction during summer peak hours while less
temperature increase in the nights due to the peak temperature shift. On the other hand, for
winter day, the interior face temperatures would raise at nights when outside roof face
temperatures are low because of the same effect of peak temperature shift. The simulation results
demonstrate that the PCM can effectively mitigate the peak temperature during a day to save the
building HVAC energy consumption.
(a)
-4
-3
-2
-1
0
1
2
3
4
1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4
TEM
PERA
TURE
RED
UCT
ION
(CEL
SIU
S)
HOURS
SIP replaced with max.infiltrated herb
Infiltrated herb replaces the SIP wall and adds above the SIP in the roof
59
(b)
(c)
-10
-5
0
5
10
15
1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4
TEM
PERA
TURE
DIF
FERE
NCE
(CEL
SIU
S)
HOURS
SIP replaced with max.infiltrated herb
Infiltrated herb replaces the SIP wall and adds above the SIP in the roof
-1
-0.5
0
0.5
1
1.5
2
2.5
3
1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4
TEM
PERA
TURE
DIF
FERE
NCE
(CEL
SIU
S)
HOURS
SIP replaced with max.infiltrated herb
Infiltrated herb replaces the SIP wall and adds above the SIP in the roof
60
(d)
Figure 5.10: Hourly temperature difference between conventional SIP and herb/PCM composite roof conditions in (a) summer interior face of the roof (b) summer exterior face of the roof (c) winter interior face of the roof (d) winter exterior face of the roof
-8
-6
-4
-2
0
2
4
6
8
1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4
TEM
PERA
TURE
DIF
FERE
NCE
(CEL
SIU
S)
HOURS
SIP replaced with max.infiltrated herb
Infiltrated herb replaces the SIP wall and adds above the SIP in the roof
61
CHAPTER 6
CONCLUSIONS AND FUTURE RESEARCH
6.1 Conclusions
The main observations from the current study are as follows:
· PCMs involve in large amount of heat storing through phase changing process, which
increases the overall heat capacity of the material, and therefore, helps to reduce the rate of
temperature modulation by using the bio-product/PCM composite. The heat capacity of bio-
product/PCM composites in the current study was increased by 2 to 5 times than traditional non-
infiltrated bio-products when adding the latent heat of fusion of paraffin wax.
· The main function of PCM is to reduce the indoor and outdoor temperature
fluctuations and thereby, to shift the peak temperatures from high to low temperature hours for
effective thermal control. Simulation results implied that, the peak temperatures could be
mitigated by 0.5oC to 4oC using bio-product/PCM composite layer compared to conventional SIP
layer in all seasons.
· Annually, the heating and cooling load savings could range up to 20% and 11%
respectively based on the various bio-product/PCM composite wall layer conditions, comparison
with conventional SIP and non-infiltrated bio-product layer conditions. Specifically, for the
months of April, October and November, the energy savings are ranging from 25% to over 40%,
as the average temperatures for those months are falling in the range of PCM melting
temperature.
6.2 Future Research
Future work in this area should focus on study of wetting behavior between porous
62
medium and PCMs to obtain higher infiltration rate thereby, improving the latent heat property
of the composite, as it was inferred from the EnergyPlus simulations that, the amount of PCM
inside the composite material would determine the energy savings. A comprehensive study has to
be made to find out the bio-product pore size and porosity influence on thermal conductivity,
although there is some information (on Aluminum) available about the effect of porosity and
pore size on thermal conductivities. As paraffin wax happened to be an inflammable material,
research has to be extended to fatty acid esters as PCMs, which are less expensive and
significantly less flammable, also are not prone to super-cooling, separation problems as
inorganic PCMs. Boundary sealing encapsulation techniques for the bio-product/PCM composite
based wall panel have to be studied, to prevent the leaking of molten PCMs from the building
envelope surface.
Build and test the bio-product/PCM composite wall panel at real physical building
structure (i.e., ZØE lab at UNT) to seek the potential savings on HVAC system and verify the
simulation model for future more complicated building simulations. Besides, optimizing the wall
structure layers containing PCM to maximize the HVAC system energy savings, as embedding
bio-product/PCM composite in different wall structure layers may have different savings on
HVAC systems. Finally, Cost analysis should be conducted to determine whether the bio-
product/PCM composite based wall structure is economically suitable for the building
applications.
64
Various pine, cherry and their composite’s open porosity, absolute density values
represented in tables (a) and (b) and Pycnometer parameters are indicated in Table (c).
Cherry wood material properties Samples Open cell
porosity(avg)% Closed cell porosity(avg)%
Absolute densities (avg)g/cc
Standard deviation of open cell (avg)%
Density deviation (cc)
C1 10.97% 89.03% 0.8386 0.144 0.0014 C2 8.703 91.296 0.9294 0.1194 0.0012 C3 11.31 88.688 0.9902 0.1197 0.0013 C4 10.5077 89.492 0.9236 0.5516 0.0057 C5 14.6447 85.355 0.926 0.1012 0.0011 C6 13.2761 86.274 0.6788 0.1693 0.0013 C7 10.0681 89.932 0.7196 0.2368 0.0019 C8 10.1144 89.886 0.6491 0.7112 0.0051 C9 11.9946 88.005 0.6429 0.6028 0.0044 C10 10.343 89.657 0.7205 0.4578 0.0037 C21 (Non-infiltrated)
42.5108 57.489 0.915 0.3453 0.0055
C22(Non-infiltrated)
48.0007 51.999 1.1516 0.296 0.0066
C2L 13.0926 86.907 0.9226 0.0561 0.0006 C3L 14.0305 85.969 0.9999 0.0502 0.0006 C5L 14.9541 85.046 0.9446 0.0786 0.0009 C6L 16.1998 83.8 0.6952 0.058 0.0005 C7L 11.3877 88.612 0.7283 0.0501 0.0004 C2R 15.0940 84.906 0.9403 0.0737 0.0008 C3R 13.2336 86.766 0.9835 0.1024 0.0012 C5R 16.1164 83.334 0.9069 0.0987 0.0016 C6R 14.6314 85.369 0.6752 0.1894 0.0015
‘L’ indicates left half of the samples ‘R’ indicates right half of the samples ’C’ indicates cherry wood Pine wood material properties
Samples Open cell porosity(avg)%
Closed cell porosity(Avg)%
Density (avg) g/cc
Standard deviation %
Density deviation (cc)
P1 8.2255 91.775 0.9344 0.1454 0.0015 P2 14.443 85.557 0.7043 0.076 0.0006 P3 12.485 87.515 0.8411 0.1364 0.0013
65
P4 12.5833 87.417 0.6859 0.0789 0.0006 P5 11.5418 88.458 0.9018 0.1063 0.0011 P6 8.5516 91.448 0.5819 0.0435 0.0003 P7 14.9913 85.005 0.5177 0.157 0.001 P8 12.951 87.049 0.5197 0.0334 0.0002 P9 13.1337 86.866 0.5624 0.0622 0.0044 P10 6.7915 93.209 0.4899 0.0663 0.0003 P24(Non-infiltrated)
74.748 25.252 1.5694 0.0751 0.0047
P25(Non-infiltrated)
75.0811 24.919 1.574 0.1042 0.0066
P1L 13.747 86.253 0.8918 0.0.2081 0.0022 P2L 18.3213 81.679 0.761 0.0904 0.0008 P5L 15.7078 84.292 0.9178 0.1272 0.0014 P7L 19.6636 80.336 0.5305 0.1735 0.0011 P10L 10.5193 89.481 0.5015 0.1115 0.0006 P1R 18.8024 81.198 0.9577 0.2321 0.0027 P2R 14.4606 85.539 0.6592 0.2251 0.0017 P5R 12.2712 87.729 0.8829 0.2331 0.0023 P7R 14.2278 85.772 0.5429 0.1985 0.0013 P10R 8.6895 91.310 0.4988 0.1175 0.0006
‘P’ indicates pine wood Analysis parameters
Parameters Inputs Pressure 6 psi Purge time 3 minutes Purge type Flow Number of runs 10 Cell size Medium
Figures (a) to (e) indicate the approach in providing the material properties of the samples
for the thermal conductivity testing in the Hot Disk Thermal Constant Analyzer.
68
Main window
Thermal material properties and their residues are indicated in the Tables (d) and (e) that
are obtained in the Hot Disk Thermal Constant Analyzer.
Thermal conductivities of pine and cherry woods
Other variables calculated by measuring device
Non- infiltrated cherryFile Samples Temperature Th.Conductivity Th.Diffusivity Spec.Heat Th.Effusivity Pr.Depth Temp.Incr.E:\hot disk Cherry_1 24.0 °C 0.1973 W/mK 0.2787 mm²/s 0.7077 MJ/m³K 373.6 Ws¹´²/(m²K) 9.44 mm 2.96 KE:\C3.hotbCherry_2 24.4 °C 0.1962 W/mK 0.2834 mm²/s 0.6921 MJ/m³K 368.5 Ws¹´²/(m²K) 9.52 mm 3.03 KE:\C4.hotbCherry_3 24.4 °C 0.1891 W/mK 0.2809 mm²/s 0.6732 MJ/m³K 356.8 Ws¹´²/(m²K) 9.48 mm 3.030 K
Infiltrated CherryFile Samples Temperature Th.Conductivity Th.Diffusivity Spec.Heat Th.Effusivity Pr.Depth Temp.Incr.E:\hot disk Cherry_1 24.0 °C 0.1878 W/mK 0.2518 mm²/s 0.7458 MJ/m³K 374.2 Ws¹´²/(m²K) 8.98 mm 2.96 KE:\C5.hotbCherry_2 24.4 °C 0.2068 W/mK 0.2267 mm²/s 0.9119 MJ/m³K 434.2 Ws¹´²/(m²K) 8.52 mm 3.030 KE:\C6.hotbCherry_3 24.4 °C 0.2002 W/mK 0.2185 mm²/s 0.9162 MJ/m³K 428.3 Ws¹´²/(m²K) 8.36 mm 3.03 K
Non- infiltrated PineFile Samples Temperature Th.Conductivity Th.Diffusivity Spec.Heat Th.Effusivity Pr.Depth Temp.Incr.E:\hot disk Pine_1 24.0 °C 0.1629 W/mK 0.3125 mm²/s 0.5213 MJ/m³K 291.4 Ws¹´²/(m²K) 10.00 mm 2.96 KE:\P3.hotbPine_2 24.4 °C 0.1653 W/mK 0.3102 mm²/s 0.5328 MJ/m³K 296.7 Ws¹´²/(m²K) 9.96 mm 3.03 KE:\P4.hotbPine_3 24.4 °C 0.1619 W/mK 0.2922 mm²/s 0.5540 MJ/m³K 299.5 Ws¹´²/(m²K) 9.67 mm 3.03 K
Infiltrated PineFile Samples Temperature Th.Conductivity Th.Diffusivity Spec.Heat Th.Effusivity Pr.Depth Temp.Incr.E:\hot disk Pine_1 24.0 °C 0.1466 W/mK 0.2658 mm²/s 0.5516 MJ/m³K 284.4 Ws¹´²/(m²K) 9.22 mm 2.96 KE:\P5.hotbPine_2 24.4 °C 0.1612 W/mK 0.2954 mm²/s 0.5455 MJ/m³K 296.5 Ws¹´²/(m²K) 9.72 mm 3.04 KE:\P6.hotbPine_3 24.4 °C 0.1570 W/mK 0.2933 mm²/s 0.5352 MJ/m³K 289.9 Ws¹´²/(m²K) 9.69 mm 3.04 K
Total/Temp.Incr. Total/Char.Time Time Corr. Mean Dev. Disk Res. Calc settings3.64 K 0.543 0.100 s 1.740E-4 K 12.570699 Ω Standard Start:28 End:200, Time corr, default heat capacity3.13 K 0.552 0.100 s 1.286E-4 K 12.569883 Ω Standard Start:59 End:200, Time corr, default heat capacity3.24 K 0.547 0.1000 s 1.562E-4 K 12.557056 Ω Standard Start:63 End:200, Time corr, default heat capacity
69
The gap between the bio-product and infiltrated bio-product samples depends on the
amount of paraffin wax present, conditions under which the test was being conducted, the
location of the thermocouple placed to trace the temperature variation. It takes longer time for
the infiltrated bio-products to reach a specific temperature than non-infiltrated products due to
the latent heat of fusion property of PCM. This occurrence is illustrated in following figures (j),
(f), and (h). Figure (i) Indicates the temperature reduction between bio-products and their
composites. This plot is to find which one of the bio-product/PCM composites has higher heat
capacities. Due to the higher weight percentage of PCM, herb composite could hold more heat
than bio-product composites.
(a) Temperature vs time curves (comparison between pine and infiltrated pine woods)
70
(b) Temperature vs time curves (comparison between cherry and infiltrated cherry)
(c) Temperature vs time curves (comparison between herb and infiltrated herb)
73
Below figures (a)-(j) indicate the inputs given starting from building footprint to wall
layer allocation. In the first figure, foot print shapes and zones are customized by manually
specifying the contours besides, mentioning the floor height to be extruded and lighting
schedule.
Figures (b) and (e) indicate the window and door types respectively. As of the ZOE
building all those are made of low emissive glasses (with emissivity of 0.3). Further the specific
position of their location is also specified by clicking on the “Custom Door/ Window placement”
button.
Figure (c) indicates the building operation schedule. Currently, the building which is
being considered for simulation is a “low use type” with working hours - 8:00AM to 5:00PM
from Monday through Friday. Whereas, closed on the weekends. One main aspect of the
building simulation is the thermostat set points, which is divided in to two parts 1. Occupied 2.
Unoccupied settings 76oF and 82oF respectively for cooling the zones, 70oF and 64oF for
heating. In order to maintain that temperature, the supply air should be designed with optimal
supply parameters (0.5 cfm/ ft2) as mentioned in the figure 4.2 (d). Electric utility charges are
specified in the last slide of schematic wizard as mentioned in the figure 4.2 (f) ranging from
$0.0781 to $0.1165 / kWh.
Figure (g) indicates the hourly building lighting schedule with no lighting before 6:00AM
and almost negligible after 6:00PM. The total lighting in all zones are estimated as 0.375W/ft2.
So the ratios mentioned in the figures are multiplied with the estimated lighting power to get the
actual usage of power per square foot.
Figure (h) indicates the layer which was being replaced with the infiltrated pine wood
with specified latent heat capacity average in terms of specific heat capacity. Lighting capacity is
74
indicated in the figure (i) with 0.3225 W/ft2. It could be calculated by considering the lighting
equipment capacity and dividing it by the total area of the building.
(a) Building footprint
(b) Exterior windows
80
Figures from (a) to (h) indicate the main input windows of EnergyPlus simulation tool, in
which figure (a) and (b) indicates the algorithm and its solving technique i.e. Conduction Finite
Difference Algorithm and Crank Nicolson Second Order solver. For the current study, DFW area
had been simulated and the details of the location are mentioned in the Figure (c). To create the
24-hour weather profile used for sizing and to test the other simulation parameters, Design Day
window is helps to estimate a typical summer and winter days as shown in the Figure (d). To
simulate the desired days of the month throughout the year run period tab in the window was
utilized as shown in the Figure (e). The PCM effect and other building construction material
properties inputting windows respectively is indicated in Figure (f) and (g). Finally, the three
zones, conditioned, mechanical and electrical thermal zones and people were provided in order
to distinguish the degree of conditioning for the simulator as shown in the Figures (h) and (i).
(a) Conduction Finite Difference algorithm allocation
85
The outside roof temperatures are higher than the outside wall temperatures, because of
the direct solar radiation and represented in the following Figures (j), (k), (l), (m). Figs (n), (o),
(p), and (q) represents the temperature difference between conventional SIP wall and herb/PCM
composite wall conditions of interior and exterior faces in summer and winter days (i.e., the
temperature difference is equal to temperature for conventional SIP wall condition minus that for
herb/PCM composite wall condition.).
(j)
(k)
20
22
24
26
28
1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4
TEM
PERA
TURE
(CEL
SIU
S)
HOURS
SUMMER INSIDE WALLSIP conventional
SIP replaced with max.infiltrated herb
Infiltrated herb replaces the SIP wall and adds above the SIP in the roof
10
20
30
40
50
60
70
1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4
TEM
PERA
TURE
(CEL
SIU
S)
TIME (HOURS)
SUMMER OUTSIDE WALLSIP conventionalSIP replaced with max.infiltrated herbInfiltrated herb replaces the SIP wall and adds above the SIP in the roofoutside air temperature
86
(l)
(m)
10
11
12
13
14
15
16
17
18
1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4
TEM
PERA
TURE
(CEL
SIU
S)
HOURS
WINTER WALL INTERIOR
SIP conventional
SIP replaced with max.infiltrated herb
Infiltrated herb replaces the SIP wall and adds above the SIP in the roof
-3
2
7
12
1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4
TEM
PERA
TURE
(CEL
SIU
S)
TIME (HOURS)
WINTER OUTSIDE WALL SIP conventionalSIP replaced with max.infiltrated herbInfiltrated herb replaces the SIP wall and adds above the SIP in the roofoutside air temperature
87
(n)
(o)
-2.5
-2
-1.5
-1
-0.5
0
0.5
1
1.5
1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4
TEM
PERA
TURE
DIF
FERE
NCE
(CEL
SIU
S)
HOURS
TEMPERATURE DIFFERENCE BETWEEN CONVENTIONAL SIP AND FOLLOWING HERB/PCM COMPOSITE WALL
CONDITIONS IN SUMMER AT INSIDE WALL FACE
SIP replaced with max.infiltrated herb
Infiltrated herb replaces the SIP wall and adds above the SIP in the roof
-4-202468
10121416
1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4
TEM
PERA
TURE
DIF
FERE
NCE
(CEL
SIU
S)
HOURS
TEMPERATURE DIFFERENCE BETWEEN CONVENTIONAL SIP AND FOLLOWING HERB/PCM COMPOSITE WALL CONDITIONS IN SUMMER AT OUTSIDE WALL FACE
SIP replaced with max.infiltrated herb
Infiltrated herb replaces the SIP wall and adds above the SIP in the roof
88
(p)
(q)
0
0.5
1
1.5
2
1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4TEM
PERA
TURE
DIF
FERE
NCE
(CEL
SIU
S)
HOURS
TEMPERATURE DIFFERENCE BETWEEN CONVENTIONAL SIP AND FOLLOWING HERB/PCM COMPOSITE WALL CONDITIONS IN WINTER AT INSIDE WALL FACE
SIP replaced with max.infiltrated herb
Infiltrated herb replaces the SIP wall and adds above the SIP in the roof
-5
-4
-3
-2
-1
0
1
2
3
1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4
TEM
PERA
TURE
DIF
FERE
NCE
(CEL
SIU
S)
HOURS
TEMPERATURE DIFFERENCE BETWEEN CONVENTIONAL SIP AND FOLLOWING HERB/PCM COMPOSITE WALL CONDITIONS
IN WINTER AT OUTSIDE WALL FACESIP replaced with max.infiltrated herb
Infiltrated herb replaces the SIP wall and adds above the SIP in the roof
89
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