gateway arch, st louis · doe, nsf, usda ifp ineos nitriles intevep johnson matthey marathon oil...

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CHEMICAL REACTION ENGINEERING LABORATORY

http://www.wustl.edu Gateway Arch, St Louis

WUSTL is counted among the world's leaders in teaching and research and draws students and faculty to St. Louis from all 50 states in the US and more than 90 other nations.

St. Louis is a demographic center of the US and home to the Gateway Arch

First, I would like to thank the organizers for inviting me and allowing me to talk on a topic very dear to my heart which is reaction engineering. Before I start my lecture, I would like to introduce you briefly to my university, department and laboratory. Washington University in St. Louis, WUSTL, is located almost at the very demographic center of the US at the mouth of the mighty Missouri river, explored by Lewis and Clark in 1804, to the Mississippi. It is the home of the Gateway Arch a remarkable piece of art and engineering that commemorates President Jefferson’s Louisiana purchase and opening of the West. WUSTL is a private university well known world wide for its schools of medicine and liberal arts.

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CHEMICAL REACTION ENGINEERING LABORATORY (CREL) (http://crelonweb.eec.wustl.edu/)

M. P. Dudukovic M. H. Al-DahhanP. A. Ramachandran

PreviouslyDepartment of Chemical Engineering Now

Department of Energy Environmental and Chemical Engineering

SEAS at WUSTL

http://crelonweb.eec.wustl.edu

Our Chemical Reaction Engineering Laboratory (CREL) is located in the School of Engineering and Applied Science (SEAS) at WUSTL and was part of the Department of Chemical Engineering which, to reflect better the challenges ahead, was renamed as the Department of Energy Environmental and Chemical Engineering (EECE). My colleagues Ramachandran and Al Dahhan conduct together with me their research via CREL.

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• Education and training of students in multiphase reaction systems• Advancement of reaction engineering methodology• Transfer of state-of-the-art reaction engineering to industrial practice


Objectives of CREL since 1974

CREL Sponsors and Collaborators

SponsorsCollaborators

Industrial Sponsors

Governmental SponsorsDOE, NSF, USDA

IFPIneos Nitriles

IntevepJohnson Matthey

Marathon OilMitsubishi

PraxairSasolShell

StatoilSyntroleum

TotalUOP

ADMABB LummusAir Products

BayerBP

Chevron TexacoConocoPhillips

CorningDow Chemical

DupontEnitechnologie

EatsmanChemicalsExxon - Mobil

CREL objectives, since I joined WUSTL in 1974, have been to advance the state of the art of multiphase reaction engineering via education and research and to transfer these advances to industrial practice. Firmly believing that reaction engineering, as an academic discipline, can only flourish if it is related to industrial practice we sought and received cooperation and support from numerous companies and government agencies. This places me in a good position to provide a personal perspective on the challenges that lie ahead.

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IS MULTIPHASE REACTION ENGINEERING RELEVANT TO MODERN TECHNOLOGICAL CHALLENGES?

CAMURE-6 and ISMR-5NCL,Pune, India, January 14 to 17, 2007

Yes sincerational scale-up of molecular discoveries to sustainable

practices is the key challenge in meeting the future energy, environmental and materials needs

• Importance of multiphase reactors to clean energy, environmental protection and sustainable processing

• Contribution of micro systems to scale-up in parallel, process intensification and distributed production

• Vertical scale-up: novel tools for multiphase flow visualization, CFD validation and reactor model development

• Other means of process intensification• Key role of SCALE-UP• Summary and conclusions

M.P. DudukovicChemical Reaction Engineering Laboratory (CREL)

Washington University in St. Louis (WUSTL), Missouri, USAhttp://crelonweb.eec.wustl.edu

S1

So what is then the relevance of multiphase reaction engineering (MRE) to modern technological challenges that lie ahead? I believe that our success in responding to our energy, materials and environmental needs depends on advances in MRE. As an academician I firmly believe that only improved understanding and development of rational basis for scale-up and design will ultimately bring us to improved atom, mass and energy process efficiencies. The outline of my talk is as follows: First, a reminder of what we as chemical engineers are supposed to do, and of the importance of multiphase chemical reactors in all of these endeavors. Then, I will discuss the approach to multiphase reactors selection and scale up for commercial applications. Here; I will mention the emerging role of micro-systems. Then, I will spend the rest of my talk outlining some other ideas for process intensification. Finally, when vertical scale-up cannot be avoided, I will introduce new tools for visualization of multiphase flows, validation of CFD models and development of appropriate rational models for scale up and design.

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Total population

S2

Key Factors Affecting the Environment and Sustainability

• Agricultural practices• Mining practices• Energy utilization

Lifestyle

• Recreational activities• Manufacturing practices

The two key factors that affect the environment and sustainability of our practices is the total number of people and their life style.Agricultural practices, clearing of forest for arable land, irrigation of deserts, the extent of use of herbicides and pesticides, etc., obviously are important.Mining for finite mineral or energy resources, strip, deep shaft, etc., affect the environment.Energy utilization, drilling for oil in pristine areas and oceans, use of hydroelectric power, etc., have environmental impact.Recreational activities, such as country skiing or driving a snow mobile, walking or using a dune buggy, have different environmental consequences.As important as all of the above are, it is the manufacture of products from fuels to chemicals, plastics, pesticides that make alternate life styles possible and that is the realm of chemical and process engineering, which I wish to discuss.

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Raw Materials and Derived Intermediates

Products

Non Renewable:• Petroleum• Coal• Ores• Minerals

Renewable:• Plants• Animals

FuelsMaterialsPlasticsPharmaceuticalsFoodFeedetc.

Chemical andPhysical

Transformations

Environmental impact and

sustainability

The domain of chemical engineering consists of chemical (biological) and physical transformations of starting materials to products

Challenges: Cleaner, sustainable processes; increased atom and energy efficiency; improved safety; ability to scale-upTunca, Ramachandran, Dudukovic “Role of CRE in Sustainable Development”, Sustainable Engineering Principles, M. Abraham, et. al, Ed., Elsevier (2007)

Energy

It is fair to say that the domain of chemical engineering consists of all physical and chemical transformations (and that includes biological) of starting materials derived from non-renewable and renewable resources into a variety of products for the market on which we depend to support our life style. The key to economically, environmentally friendly and energy efficient process is in choosing the right chemical transformation, the right catalyst for it, and the right reactor type and being able to scale up these transformations for commercial use and public benefit.

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Pollution(Damage ToEnvironment)

S4

PopulationPopulation

GNPGNP

EnergyEnergy

Pollution×⎟

⎠

⎞⎜⎝

⎛×⎟⎠⎞

⎜⎝⎛×⎟

⎠

⎞⎜⎝

⎛=

- Depends on level of available technologyEnergy

Pollution

GNPEnergy

PopulationGNP

Population

- Depends on the market forces

- Depends on economic growth

- Depends on population growth

Let us take a brief global look as to the damage to the environment created by our technological activities. The total pollution generated can be, in the first approximation, expressed as a product of four factors. 1) Pollution generated per unit of energy used, which depends on the level of available technology and process efficiency, 2) energy used for GNP generation which depends on market forces, 3) GNP/per capita, which is affected by economic growth, and 4) total population.

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CHEMICAL REACTION ENGINEERING LABORATORYS5

GLOBAL VIEWOptimistic Assessment

( ) ( ) ( )P ollu tion 1 - p rocess efficiency consum ption per cap ita population

process inefficiency

∝14444244443

Pop

ulat

ion

Con

sum

ptio

n P

er C

apita

Pro

cess

Effi

cien

cy

Time Time Time (Investment)

One can further simplify this global view of the pollution problem and present the total pollution as a product of consumption per capita, population and process inefficiency = 1 – process efficiency. Then it seems self-evident that pollution can be reduced by controlling population growth, and/or by reducing consumption per capita. In contrast, process efficiency increases only asymptotically to unity. One should also note that further increases in process efficiency require considerable investment of capital and time. Improving efficiency of one process may lead to inefficiency elsewhere. Hence, a holistic system’s approach and life cycle analysis are needed.

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GLOBALLY, Pollution prevention and reduction (as well as achieving sustainability) will ultimately depend either on population and consumption control OR on introduction of environmentally benignand highly efficient sustainable technologies.

On a national level, in the USA the focus has been on waste reduction via

- Better education and operation practices at existing manufacturing facilities (more than pays for itself)

- Retrofitting of existing facilities (done only if resulting in improved profitability)

- Installation of pollution abatement equipment (done only if under regulatory or peer pressures)

- Moving and opening new manufacturing facilities off-shore (let them have our pollution while we manage their money – service industry)

- Development and installation of cleaner processes (requires substantial capital expenditures and new concepts for ultra pure systems, has to rely on multi-scale CRE methodology) S6

The desire to become more ‘green’ in processing is tied to the requirement to be profitable. In attempting to reduce the damage to the environment by the process industry during the last 15 plus years we in the US have focused on the following activities. Better education of personnel at existing manufacturing facilities resulted in better operating practices and paid for itself. Retrofitting of existing facilities was done whenever it was clear that it will result in improved profitability ( otherwise offending facilities were closed). Installation of end-of –the –pipe clean-up equipment was pursued when required by law or peer pressure provided processing remained economical. Moving and opening facilities off-shore was often practice to increase profitability. Unfortunately, this almost always resulted in licensing of old ( ‘post world two technology’) at locations with more favorable regulatory and labor cost climate. Instead what we need is the development and installation of new cleaner and more efficient technologies. This requires substantial capital expenditures and is perceived as involving considerable risk and is not done at the moment. Clearly, by investing more in the science of scale-up such risk will be reduced and the willingness to implement new technology will increase. This is the challenge for multiphase reaction engineering in the next few decades.

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The Rich and The Poor

S8

1393Paved Roads (% of Total)6.9470PCs Per 1000 People

391,250Fixed & Mobile Phones (per 1000 People)

Technology & Infrastructure45028,550GNI Per Capita (US $)

Economy

3028,340Electricity Per Capita (KWH)

5085,350Energy Use Per Capita (Kg Oil EQ)32 million35 millionSurface Area (Sq KM)

Environment5998Literacy

825.4Infant Mortality (Per 1000 Births)

3.71.7Fertility Rate

5878Life Expectancy1.80.5Population Growth (% Annual)2.3 billion0.97 billionTotal Population

PoorRichPeople

Source: The World Bank Group

Another reason while eventually we will have to embrace the new efficient process technologies is the fact that the enormous gapbetween the rich and poor nations must be bridged if we are going to avoid serious social upheavals in the future. And using the current inefficient technology will not do it since this is too wasteful in energy usage.

So to bring the standard of living of Asia and Africa to American level with current technology is clearly unsustainable.

Let us plan considering only the new technologies, that we must start to develop and implement proper understanding and application ofreaction engineering principles will be essential.

We should note, however, that in all the current and future methods of pollution reduction, chemical reaction engineering plays a pivotal role. That is true in retrofitting activities, in end-of-the-pipe treatment and certainly in the development of cleaner new green processes.

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To raise the living standards of the poor while positively impacting the environment and the world economy, novel process and product manufacturing technologies are needed for

-Distributed power systems

- Consumer products and health care devices

-Reliable and clean energy carriers

-Recyclable materials

- Efficient production of chemicals, fuels and materials that is sustainable

Also needed more conservation and recyclables oriented life style that minimizes waste and energy and materials inefficiencies.

This slide is self-explenatory.

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),()( bbb TCRCL η=

∑ ηΔ−=j

bbjjRbh TCRHTLj

),()()(

( )transport;kineticsf=η00 P,C,T

P,C,T

product, QREACTOR PERFORMANCE = f ( input & operating variables ; rates ; mixing pattern )

Reactor choice determines plant costs; Need improved reactor selection and scale-up

REACTOR MOLECULAR SCALEEDDY/PARTICLEfeed, Q

Chemical Reaction Engineering (CRE) Methodology

MOLECULAR SCALE (RATE FORMS)

Strictly Empirical Mechanism Based Elementary Steps

REACTOR SCALE

Axial Dispersion CFDPhenomenological Models

EDDY OR PARTICLE SCALE TRANSPORT

DNS / CFDEmpirical Micromixing Models

PROCESS SCALE

Steady State Balances Dynamic Models forControl & Optimization

10-10 m

102 m

10-16 (s)

104 (s)

PFR/CSTR

Dudukovic, Larachi, Mills, Catalysis Reviews (2002), 44(1), 123-246

The powerful chemical reaction engineering (CRE) methodology, developed over the last 50 years, offers a rational way to quantifying reactor performance based on mass, energy and momentum balances by relating to the prevalent multi-scale transport and kinetic phenomena. Understanding these multi-scale transport kinetic interactions is the key to the selection of the best reactor type for a given chemistry and catalyst and to successful scale-up.The choice of the proper reactor type and operating conditions for a given

process chemistry is the key factor in determining volumetric productivity and selectivity. So although the reactor typically represents between 5 – 15% of capital and operating costs of the plant, its choice determines the number and load on pre-reactor and post-reactor separation units and dictates the cost of the whole process.That is why the choice of the proper reactor type is essential and it should be based on a rational approach based on a reactor model. Such model must capture the events on a multitude of scales at the right level, and provide the ability to scale test tube discoveries to commercial processes. The complexity arises from the fact that the interactions of events on various scales are dependent on the scale of the equipment.It is increasingly necessary for use of novel more active catalysts to understand the change of the flow pattern with reactor scale and the interaction of it with meso-scale transport.Hence moving our level of understanding of all scales affecting reactor performance from the left to the right, that is being more quantitative and predictive, is needed for safer scale-up and design of the next generation of reactors. Unless, of course, one avoids vertical scale-up completely, and here

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Environmental Acceptability,as Measured by the E-Factor

Industry

Oil refining

Bulk chemicals

Fine chemicals

Pharmaceuticals

Product tons

per year

106 – 108

104 – 106

102 – 104

100 - 103

Waste/product

ratio by weight

~ 0.1

< 1 – 5

5 – 50

25 - > 100

The enclosed table illustrates the so-called E factor of various industries. Clearly, those that practice CRE at the high level produce the fewest undesirable products per unit desired product. So-called high tech industries, which are really high value added industries, like the electronic industry used to be and pharmaceutical industry is now, have terribly high E-factors and are not high tech at all from the environmental standpoint.The other point that should be understood is that the so-called principles of green chemistry are just one of the prerequisites for a green process. Whether the process will be successful or not, depends on selection of proper reactor type and its proper operation. A great number of new processes is often abandoned due to inability to scale up reliably. Hence, understanding of the multi-scale aspects of reaction engineering is lacking.

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Green Chemistry and Green Processing

Raw MaterialsEnergy

Value Added Products, Fuels

Waste or pollutants

ReactorPretreatment Separator

Raw Materials

Energy

Energy Energy

Global Scale

Plant Scale Waste or pollutants

CRE

S8

In the past and at present we have always adhered to the principle that the process must be economical. ( Our students are taught that ‘thou shall make profit’). Now to develop new sustainable ‘green’ processing technologies we need also to consider all the twelve principles of green chemistry. Hence for ‘green’ to prevail it must be made profitable, means to do this will be discussed later. At the moment we should note that the center of each process is a chemical reactor in which key chemical transformations take place. Once the right catalyst has been identified to promote the desired “green” chemistry, the selection of the reactor type to be used and the way it is operated, dictate the number and size of separation units needed, and to a great extent determine the burden on the environment and energy efficiency of the process. Proper reactor selection and operation leads to optimal plants, minimizes the pollution burden and environmental concerns and helps maximize energy efficiency.

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Implementation of green manufacturing principles would greatly benefit from:

Providing globally the tax structure that encourages corporations to implement green manufacturing. Create incentives for improved profitability through green manufacturing.

Mastery of the art and science of scale-up, use of CRE methodology and not copying blindly designs of the past.

It is clear that adopting green manufacturing principles requires both technological as well as political changes.

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Ideal R & D approach:Select the best chemistry (use green chemistry principles)Select the most suitable reactor type (based on multi-scale

considerations)Consider possibilities for separation-reaction multi-functionalityScale –up bench scale results with care based on as complete

understanding of the system as possible to minimize riskPrevalent current R & D approach:Find chemistry that does the job by trial and error Use familiar reactors and add needed separations (contractors)Build the plant with minimal scale-up expendituresExperiment with the plant to determine ‘best conditions’ via

statistical analysis

The key function of engineers is to transfer scientific discoveries into new technologies and practice for benefit of mankind. For chemical engineers the ability to function in process research and development (R&D) environment effectively is vital!!!

Let us then briefly consider how should Process R&D be conducted and compare this to what happens in everyday practice. Ideally, we should seek the best chemistry that maximizes atom, mass and energy efficiency. Based on the understanding of the reaction pathways involved, we should seek the reactor with the best flow pattern and phase contacting pattern. We should examine opportunities for effective coupling of reaction and separation. Then bench scale experiments should be scaled-up. How to do that I will address in the next slide. Here, I want to describe how most of the current R&D seems to be conducted. The chemistry that will do the job is found by trial and error (combinatorial analysis, etc). Usually reactors that the company is familiar with are tried, and best operating conditions are sought by statistical approaches with limited understanding of the underlying phenomena. Plants are build based on construction companies procedures that essentially are 1950s correlations dressed up in Excel or Power Point. These plants, especially reactors, invariably have problems and experimentation with full plants continues and is becoming a norm. So “optimized” poor reactor choice remains inferior to the properly selected reactor type that iisproperly scaled-up, thus resulting in more waste and lower efficiency.

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Bench scale achieved desired conversion, yield, selectivity, productivity

S2 CHEMICAL REACTION ENGINEERING LABORATORYS7

Commercial productionScale-up

Alternatives:1. Scale-up in parallel (Scale-out, scale-up by multiplication.)2. Scale-up vertically – account for effect of change in equipment scale on multi-scale interaction of transport and kinetic phenomena.3. Consider combining reaction and separation in a multifunctional reactor.

The key scale-up issue is the following: Once the reaction system was successfully run in the laboratory to produce the desired conversion, yield and selectivity, how to reproduce the results at a commercial scale.

Now horizontal scale-up (scale-up in parallel or scale-up by multiplication or scale-out)) offers one alternative while vertical scale up offers another. Only the latter must account for the effect of equipment scale on the interplay of transport and kinetics. The former keeps the geometry, flow and contacting pattern and flow regime the same but has to deal with the logistics of system integration and flow distribution. Hence, without proper understanding of the system, relying solely on statistical approaches has a high likelihood of failure.

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Petroleum Refining

Polymer andMaterials

Manufacture

EnvironmentalRemediation

Synthesis & Natural Gas Conversion

BulkChemicals

Fine Chemicals &Pharmaceuticals

HDS, HDN, HDM,Dewaxing, Fuels,Aromatics, Olefins, ...

MeOH, DME, MTBE,Paraffins, Olefins,Higher alcohols, ….

Aldehydes, Alcohols,Amines, Acids, Esters,LAB’s, Inorg Acids, ...

Ag Chem, Dyes,Fragrances, Flavors,Nutraceuticals,...

Polycarbonates,PPO, Polyolefins,

Specialty plastics; semiconductors etc

De-NOx, De-SOx,HCFC’s, DPA,“Green” Processes ..

Value of Shipments:

$US 640,000 Million

Uses of Multiphase Reactor Technology

BiomassConversion

Syngas, Methanol, Ethanol, Oils, High

Value Added Products

EnergyCoal, oil, gas, nuclear power plants

In USA alone

In particular, it is important to recognize that at the heart ofchemical transformations in all process and energy industries is multiphase reactor technology as over 99% of reactor systems require the presence of more than one phase for proper operation.This multiphase reactor technology spans numerous industrial sectors (e.g. energy, syngas and natural gas conversion, production of bulk chemicals, fine chemicals and pharmaceuticals, biomass conversion, petroleum refining, polymer manufacture, production of materilas such as semiconductors and optical fibers, environmental remediation etc) and generates a large contribution to the Gross Domestic Product (GDP) in the US.In all of the above industrial sectors, to implement commercially a new technology one needs to be able to predict how will the molecules get together and react in commercial installations and how will the rates and selectivity in such systems differ from those in lab scale

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FREQUENTLY USED CLASSICAL MULTIPHASE REACTOR TYPES• Wall catalyzed and/or wall cooled packed tubes• Massive packed beds• Moving beds• Monoliths• Trickle beds/ packed bubble columns• Bubble (slurry bubble) columns• Risers and fluidized beds• Stirred tanks

PROCESS INTENSIFICATION• Micro Reactors• Rotating packed bed• Structured packing

COMBINATION OF REACTION AND SEPARATION• Reactive / catalytic distillation• In situ adsorption• Membrane reactors

Classical reactor types in various technologies include packed beds, wall catalyzed reactors, bubble columns, stirred tanks and risers and fluidized beds. Novel designs attempt at combining reaction as and separation via reactive distillation, catalytic distillation, in situ adsorption, membrane reactors, etc. let us consider what approach to scale-up we use in these and what remains to be done to make scale-up more reliable.

On this slide classical multiphase reactor types as well as some novel designs are listed. We will briefly consider how much is really known about some of these.

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SOME KEY SCALE-UP REQUIREMENTS

• Match mean residence time or mean contact time

• Match [or account for the change in] dimensionless variance of residence ( contact) times

• Match [or account for change in] covariance of sojourn times in different environments (phases) of the system

• Match heat transfer per unit volume, or account for the change with change in scale of equipment

Key scale-up considerations require us to match mean residence times or mean contact times in multiphase systems. This requires the knowledge of phase holdups. To ensure the same performance we must also match the variance of residence times in the reaction environment and/or the covariance of sojourn times in different phases. This requirement is often neglected. Naturally we must also ensure the same heat transfer per unit volume. Let us see what reactor types are of interest.

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Direct Scale-up of Tubular and Packed Bed Wall-Cooled Reactors: Scale-up by Multiplication

LPF

Single tube of diameter dt and length L at given feed conditions (Po, To, Co) and given feed rate Q (l/h), produces the desired product at the rate of (mol P/h) and the desired selectivity.

S Identical tubes of diameter dt and length L produce then the commercial production rate FpC (S = FpC ( ), using identical feed conditions and flow rate, at the desired selectivity.Possible Problems: - External heat transfer coefficient

- Flow manifold for flow distribution

SAME PRINCIPLE USED IN MICROREACTORS

LPF

o

o

CT

CT

o

o

CT

CT

Scale up by multiplication is practiced routinely for wall cooled tubular and packed bed reactors. Once the satisfactory performance of one tube is accomplished, the number of tubes needed for commercial production is determined.Key to success: reliable single tube data, good knowledge base for manifold

and flow distributor design, avoiding external heat transfer limitations upon scale-up.For many decades’ industrial chemists were experimenting with a catalytic

tube of 1” to 2” in diameter of desired lengths ( - 2 m or longer). Once the feed temperature and composition and flow rate used (i.e., mean residence time) produce the desired result, scale-up is simple in principle. It requires using N tubes identical to the one used in the laboratory, packed with the same catalyst particle and receiving the same feed at the same flow rate as the tube in the lab. The number of tubes N needed is given by the ratio of the desired commercial production rate and that achieved in the laboratory that is by the scale- up ratio. Lurgi and others build reactors with up to 50,000 tubes! This concept of the ability to scale up in parallel is a great advantage that micro reactors offer also. Let us look now at some of the other advantages.

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●High surface-to-volume area; enhanced mass and heat transfer;

●High volumetric productivity;

●Laminar flow conditions; low pressure drop

Advantages of Micro reactors

S2 CHEMICAL REACTION ENGINEERING LABORATORY

• Residence time distribution and extent of back mixing controlled

• Low manufacturing, operating, and maintenance costs, and low power consumption

• Minimal environmental hazards and increased safety due to small volume

• “Scaling-out” or “numbering-up” instead of scaling-up

Clearly micro reactors offer a whole series of advantages such as: 1) high surface to volume ratios and, due to small dimensions enhanced mass and heat transfer coefficients by one to two orders of magnitude, 2) laminar flow conditions and low pressure drop but ability to make RTD narrow by introduction of another phase, 3) controllable RTD and back mixing, 4) high volumetric productivity, 5) low manufacturing and operating costs, 6) increased safety due to small amount of material, 7) scale up in parallel (scale out).

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Multiphase Flows in mFluidic Systems• Multiphase flows are important

– Reactions – oxidation, hydrogenation, fluorination, …– Materials synthesis – crystallization, nanoparticles, colloids, …– Separation – extraction, gas-liquid separation, ….

• Performance = f(understanding and ability to manipulate)

immiscible liquid-liquid

gas-liquid

liquid-solid

gas-liquid-solidKlavs Jensen’s group at MIT

The MIT group of Klavs Jensen, among others, has recognized the importance of being able to manipulate multiphase systems in micro reactors and have shown that one can get competitive performance for various reactions, separations and in material synthesis. The achieved performance of the micro reactor depends on the level of understanding of the chemical system and the ability to manipulate micro reactor design so as to meet the reaction contacting requirements best. If the desired figures of merit are met, then scale up in parallel ensues.

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Scaling Out Micro reactors

• Uniform flow distribution and nature of contacting pattern• Methods for design of multi-phase reactors• Integrated sensors for gas-liquid flows

Single channelFlow regimes, • Interfacial area• Mass transfer

• Scale-out μg ⇒ g ⇒ ton

Multi-channel design

churnslug

annular

bubbly

0.001

0.01

0.1

1

10

j L(m

/s)

0.1 1 10 100j G (m/s)

wavy annularμ Heat-

exchangers

μReactors

SlugSlug

Annular

N. de Mas, et al., Ind. Eng. Chem Research, 42(4); 698-710 (2003)

Jensen and his co-workers have also shown that, via multi-channel integrated design , in principle, scale up to large production rates is possible even for highly exothermic reactions such as direct fluorination of aromatics.

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t (min)

d m(n

m)

σ(%)

Silica Synthesis: Laminar Flow Reactor

• Wide particle size distribution (PSD) at low residence times– Particle growth is fastest, and hence most sensitive to residence

time variations• PSD at high residence times approaches batch synthesis results (8%

vs. 5%)

1 µm

Khan, et al., Langmuir (2004), 20, 8604

Pratsinis, Dudukovic,Friedlander, CES(1986) effect of RTD on size pdf

They proved that concept in colloid silica synthesis from TEOS, ammonium hydroxide, ethyl alcohol and de-ionized water. In laminar flow in micro channels a wide particle size distribution (PSD) occurs and the standard deviation of the PSD approaches that of the batch system (8% vs 5%) only at large sizes and large residence times (due to Taylor diffusion effect).

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Silica Synthesis: Segmented Flow Reactor

• SFR enables continuous synthesis with results that mirror those obtained from batch synthesis

1 µmGas Gas

σ (%)

BatchSFR

LFR

Khan, et al., Langmuir (2004), 20, 8604

In contrast, in the segmented flow aided by gas bubbles, a more uniform size distribution is obtained with considerable lower standard deviation of the PSD.

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Review of gas-liquid, gas-liquid-solid contacting patterns and transport properties in micro-reactors

- falling film- falling film on catalytic wall- overlapping channel and mesh

micro reactor- micro bubble columns- foam micro-reactors- packed bed micro-reactor- wall cooled micro-reactor

Improved mass and heat transfer coefficients, much larger interfacial area, controllable RTD, increased volumetric productivity, ease of scale-out

Applications demonstrated in lab scale- direct fluorinations- oxidations with fluorine- chlorinations- sulphonations- hydrogenations

Hessel et al, I&EC Research, 44, 9750-9769 (2005)also presented at CAMURE-5 & ISMR-4

In their comprehensive review paper at CAMURE-5 and ISMR-4 Hessel et al, summarize well the contacting principles in gas-liquid and gas-liquid-solid micro reactors. They review the characteristics of a variety of contacting patterns attempted and report a vastly improved mass and heat transfer coefficients, much larger interfacial areas, controllable RTDs, increased volumetric productivity, ease of scale out. They offer demonstrations of successful bench scale use in direct fluorinations, oxidations with fluorine, chlorinations, sulphonations and hydrogenations.

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Companies Currently Moving Micro-channelTechnology from R&D to Commercialization:

• Degussa: running a demonstration project for the evaluation of microreaction technology or DEMiSTM for propylene epoxidation with hydrogen peroxide

• Clariant: opened its Competence Centre for Microreactor Technology (C3MRT) to increase efficiency, improve safety and reduce the costs of pharmaceutical synthesis

- Continuous pilot plan for the synthesis of azopigments

• Axiva developed a process for continuous polymerization of acrylates (8 kg/h) using micro mixers

• Velocys using micro channels formed by a patented process in steel proposes to replace the conventional packed catalytic tubes in methane reformers.

Enthused by potential for significant process intensification a number of companies are involved in R&D for potential commercialization. Degussa, Clariant,,Axiva, Velocys and others are in hot pursuit of implementation of micro reactor technology.

29

Perceived Disadvantages of Micro Reactors:• Short residence times require fast reactions• Fast reactions require very active catalysts that are stable (The

two most often do not go together)• Catalyst deactivation and frequent reactor repacking or

reactivation• Fouling and clogging of channels• Leaks between channels• Malfunctioning of distributors• Reliability for long time on stream

Challenge of overcoming inertia of the industry to embrace new technology for old processes

Most likely implementation of micro-reactors in the near term:• Consumer products• Distributed small power systems• Healthcare• In situ preparation of hazardous and explosive chemicals

S18 The following question then arises. With all their perceived advantages, and the technologies available to manufacture micro reactors in silicon, in glass and in steel, or other metals, why aren’t they more widely used? The answer is that they require very fast reactions and active stable catalyst (usually these two do not go together). Most importantly micro reactors are, due to small dimensions, more prone to fouling and clogging, leaks between channels, and their reliability and life on stream is an unknown.All of these are potentially solvable problems on a case by case basis. However,

the perceived risk factor is too large for them to replace existing installations. Most likely acceptance of micro-devices will occur in the consumer products, distributed power systems, highly energetic fast reactions, in-situ production of hazardous chemicals. Other applications will be slower.

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Reservoir

P

P

Air Supply

Distributor

RotameterMonolith

PumpU

G (c

m/s

)

UL (cm/s) 30 40 50

50

40

30 Less uniform σ=0.075

More uniform σ=0.04


Uniform σ=0.046

Less uniform σ=0.058





Gamma Ray Tomography of Gas-Liquid Holdup Distribution in Monoliths

Al-Dahhan, et al. 2003

S. Roy et al, CES (2004); Kreutzer et al 2001-2005.

Scale-up in parallel was suggested for monoliths also, were the argument that monolith performance can be predicted based on single channel performance is often made. During the last four decades monoliths made inroads only in few applications: –automobile exhaust (multiple distributed units), and -power plant gas cleanup (SCR of NOx) for which they are the largest known reactors (up to 1000 m3 in size).

Applications in other areas, especially for gas-liquid-solid reactions, are slow to come The customer resistance factor is too large. Studies in our laboratory by gamma ray tomography reveal that in gas liquid flows uniform distribution in monolithic channels cannot be taken for granted as there is only a narrow window of flow conditions that allows it. Outside that window of operation the flow distribution can be highly non-uniform and considering the monolith to be a bundle of identical channels would not model reality right.

31

FOR VERTICAL SCALE-UP ADVANCES IN MULTIPHASE REACTORS REQUIRE:a) capturing the physics of flow by experimental means;

b) using CFD models and validating the results experimentally;c) physically based engineering reactor models for flow, mixing and reaction

G

G

S

S

G

G

LS

G

G

G

G L+S

G

G

L

L

Ramachandran & Chaudhari, Multiphase catalytic reactors (1980,1983)Dudukovic, AICHE Symposium Ser., 321, 30-50 (1999)

Dudukovic, Larachi, Mills, Catalysis Reviews (2002), 44(1), 123-246

REACTOR SCALE MODELS FOR CONTACTING OF TWO MOVING PHASESIdeal Reactor Concepts:

A) Plug Flow (PFR)

B) Stirred Tank (CSTR)U1

U2

K1

2C) Axial Dispersion Model

D) Need More Accurate Flow & Mixing Description ViaPhenomenological models based on: 1) CFD Models (Euler-Euler Formulation)2) Experimental Validation: Holdup Distribution and Velocity Field

U1

U2K

1

2

When we have a reactor system with two moving phases it is important to be able to describe the flow pattern of each. In the past we relied on ideal reactor assumptions of treating each phase as being either in plug flow or perfectly mixed. When reality did not conform to these assumptions the axial dispersion model is often used to match experimental observations. It has been recognized, however, that ADM is not predictive and that one needs more accurate flow and mixing models based on the physical phenomena that occur in the system. Since multiphase systems like these are opaque, it was important to develop means to measure phase holdup and velocity distribution in them. Such data is essential for validation of CFD models that must be used on these reactor scales.

Thus, the modern approach to reactor modeling and scale-up requires:a) capturing the physics of flow by experimental meansb) using appropriate CFD models and validating the results experimentallyc) completing physically based engineering models for flow and mixing..

32

COMPUTER TOMOGRAPHY (CT)

Superficial Gas Velocity 18 cm/s at 7 atm.

0.300.35

0.400.45

0.500.55

0 2 4 6 8r (cm)

Gas

Hol

dup


Single source CT is a technique for measurement of the cross-sectional density distribution of two phase flow by measuring the attenuation distribution in two phase systems ( e.g. G-L, …).

Diameter of scan region = 12 inchesTotal number of Projections 22,275Number of views = 99

∑=−=l

ijij,eff0

l)(IIlnA ρμ

∑=K

ij,Kij,Kij,eff )()( ερμρμ

Kumar (1994), Kumar et al., (1995)

For this purpose we built a gamma ray CT scanner that can provide us with the density distribution at any desired cross-section of the reactor. Shown is the schematic of the equipment, its actual picture as it scans a bubble column at atmospheric pressure and the result at elevated pressure and at , very high gas velocity. Note that in these conditions of churn turbulent flow the average gas holdup is very high and is a parabolic function of the radius. So gamma ray CT can provide us with the accurate time averaged distribution of the phases.

33

Radioactive Particle Tracking

CARPT (RPT) Schematic Experimental Setup

Lin et al. (1985), Moslemian (1986), Devanathan (1990), Devanathan et al. (1991), Chaouki, Larachi and Dudukovic (1997)


To measure the motion of the solids or liquid phase we have introduced computer assisted single radioactive particle tracking (CARPT) to obtain the Lagrangian trajectories of a single tracer particle (labeled with Sc 46) made dynamically similar to the phase being traced. For monitoring solids motion a particle of the same density and size as the solids used is employed, for liquids a neutrally bouyant particle is used whenever possible.

34

Particle Tracking in Multiphase Systems

S2 CHEMICAL REACTION ENGINEERING LABORATORY

Dudukovic, Oil & Gas Sci. and Tech., Rev. IFP, 55(2), 135-158, (2000)

We see the glass bubble column on the right operated at relatively low superficial gas velocity of a few centimeters per second and at atmospheric pressure.

On the left we are looking at the radioactive particle tracer moving in a slurry stainless steel column 16 cm in diameter at 20% wt solid loading at gas superficial velocity of 45 cm/s.

From the obtained Lagrangian trajectories, the instantaneous velocities are obtained, as well as time average ( ensemble average) velocity values, as well as various statistical properties of the fow (i.e. eddy difusivities).

Let us illustrate the power of CARPT/CT on a number of examples!

35


Let us look now at the application of CARPT-CT in developing an improved model for many of the bubble column uses. We have proven the validity of this model for FT, methanol and DME synthesis. In process industry bubble columns are operated at very high superficial velocity to increase their productivity. These are buoyancy dominated churn turbulent flows.

The working assumption in design companies is that liquid is perfectly mixed (and that can cause problems with over design) and gas is assumed either well mixed or in plug flow, neither of which is realistic. CARPT-CT allows us to do better.

36

Bubble Column ExampleCARPT-CT and other measurements are used to develop an appropriate phenomenological reactor flow and mixing model. CFD generated data are used to assess model parameters at pilot plant or plant conditions. Reactor flow and mixing model are coupled with the kinetic information.Degaleesan et al., Chem. Eng. Sci., 51, 1967(1996); I&EC Research, 36,4670 (1997); Gupta et al., Chem. Eng. Sci., 56, 1117 (2001)

Dzz

Drr

uz(r)

1-εL(r)

0-R R

CT CT SCAN

CARPTFLOW PATTERN

CFD + CARPT + CT

AFDU

0 100 200 300 400

10.8

0.6

0.4

0.20

Detector Level 1

0 100 200 300 400

10.8

0.6

0.4

0.20

Detector Level 6

Run 14.6

0.0

0.2

0.4

0.6

0.8

1.0

0 20 40 60 80 100

Time (sec)

Norm

aliz

ed R

espo

nse

Sim_L1Exp_L1Sim_L4Exp_L4Sim_L7Exp_L7

Pressure = 50 atmTemperature =250 Deg. CUg = 25 cm/s

0 20 40 60 80 100

10.8

0.6

0.4

0.20

7

6

5

4

3

2

1

Liquid Tracer

Gas TracerGas

Gas

DET.

Data

ModelPrediction

time (s)

time (s)

time (s)

We have learned from tomography, as shown earlier, that gas holdup profile is almost parabolic in churn turbulent flow. This profile drives, by buoyancy force differences, a single liquid recirculation cell (in a time averaged sense) which is confirmed by CARPT studies. CARPT also provides the axial and radial eddy diffusivities from the Lagrangian tracer trajectories.

When the model is applied on a pilot plant column (of the same diameter as the cold flow model) for methanol synthesis, both gas phase and liquid phase tracer responses are well predicted at seven different elevations ( not shown here). The same is true (not shown) for FT and DME synthesis.

Of course the CARPT, CT data were obtained on the equipment of the same diameter, and holdup profile was experimentally determined.

To have a scale up tool we need to show that CFD can predict CT-CARPT data and then use CFD to generate the parameters of our engineering model.

37

Ensemble Averaged Equations for TwoEnsemble Averaged Equations for Two--Phase FlowPhase Flow

( ) 0=ε+∂ε∂

ccc .t

u∇ ( ) 0=ε+∂ε∂

ddd .t

u∇

( ) ( ) ( )bccccvmdccccc

ccc p

tσ∇.σ∇.∇.∇ ε+ε++−ε−ερ=⎟

⎠

⎞⎜⎝

⎛ +∂

∂ερ MMguuu ( )vmdddddd

ddd p

tMMguuu

++ε−ερ=⎟⎠

⎞⎜⎝

⎛ +∂

∂ερ ∇.∇

Liquid Phase Gas Phase

CLOSURESCLOSURES

⎟⎠

⎞⎜⎝

⎛ −εε=Dt

DDt

DC dc

vmdcvmuuM

21

InterInter--Phase Momentum ExchangePhase Momentum Exchange StressesStresses

)(O.C ddvm23231 ε+ε+=

;d

6d3

p

dcd FM

πεε

=

( )dcdcD2pcd Cd

81 uuuuF −−πρ=

( ) ⎥⎦⎤

⎢⎣⎡

++=

438150124 6870

EoEof,Re.

RemaxC .

D

2

23

79

671867171

⎭⎬⎫

⎩⎨⎧

εε+

=c

c

..f

( ) )(O; ddc

*c

c*cc ε+ε+=

μμ

+μ=251T

cuu ∇∇σ

'u'u cccbc ρ−=σ

( ) dcpdbtbc

tbc

bc dk; uuuu T

c −ε=ν+νρ= ∇∇σ

)ttanConsEmpirical(2.1k b =

τρ≡≡ 2pcdgNumberEotvosEo

cdcpcdNumberynoldsReBubbleRe μ−ρ≡≡ uu

Input Parameter : Bubble Size, dp

S52S2 CHEMICAL REACTION ENGINEERING LABORATORY

To extend the findings to other diameters we need a CFD model which then is validated at the different scale. The usually used Euler-Euler two interpenetrating fluid equations are shown here. We have executed them in CFDLIB (of Los Alamos), FLUENT and CFX. Closures are needed for liquid turbulence (e.g., bubble induced turbulence is shown here but k-epsilon and other models were also used) and for the drag (e.g. classical expression modified for presence of other bubbles is used).

Originally computations were based on experimentally observed orassumed bubble diameter., now we incorporate the population balance with coalescence and breakup. This eliminates the need to assign bubble diameter and finally yields much improved prediction of experimentally observed holdup profiles!

38

COMPARISON OF COMPUTED (CFDLIB) AND MEASURED FLOW FIELDCOMPARISON OF COMPUTED (CFDLIB) AND MEASURED FLOW FIELD

Dzz

(cm

2 /s)

τ (sec)

Ug = 12 cm/sDc = 8”

Dzz

(cm

2 /s)

τ (sec)

Ug = 10 cm/sDc = 18”

-60.0

-40.0

-20.0

0.0

20.0

40.0

60.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Dimensionless Radius

Tim

e-av

erag

ed L

iqui

d A

xial

Vel

ocity

, cm

/s

CARPTTwo-fluidASMM, DVASMM, SV

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Dimensionless Radius

Tim

e-av

erag

ed H

oldu

p

CTTwo-fluidASMM, DVASMM, SV

44 cm – IDUg = 10 cm/s

Chen and Dudukovic, CES, AICHEJ(2004, 2005))

Now we get good agreement in predictions of both time averaged velocity with CARPT data and holdup profiles and CT data and , most importantly, of the computed eddy diffusivities and CARPT data, This completes the validation of not only the mean flow field and holdup distribution, but of dynamic features of our model for bubble columns .

39

KEY CHALLENGES IN BUBBLE COLUMNS - Quantifying the Churn Turbulent Regime

• Understanding bubble-liquid interactions at sparger

• Understanding bubble-bubble interactions and interfacial area renewal dynamics (breakup coalescence problem)

• Effect of column diameter on dynamics• Validation of CFD codes for predictive purposes• Scale-up principles to very large column sizes• New approaches are needed not more of the

same (challenge problem, workshop, systematic comparison of approaches)

Extensive studies of bubble columns (e.g. Joshi et al., Ranade et al., Krishna et al., Mudde et al., Fan et all., Scouten et al., etc.) still key questions regarding scale up remain.

Scale up of bubble columns to very large diameters is still subject to uncertainty due to lack of reliable theory for multiphase turbulence and breakup-coalescence problem using internals to enable scale-up in parallel may provide an answer. In systems with multitude of reaction time constants understanding the dynamics of bubble formation and interfacial area renewal is essential.

40

Radioactive Particle Tracking (CARPT) Provides Solids Velocity and Mixing Information

Computer Tomography (CT) Provides Solids Density Distribution

HOPPER

R

I

S

E

R

EDUCTOR

High Pressure Side (80-100 psi)

Low Pressure Side ( <80 psi)

WATER TANK

PUMP

RECYCLE LINE

6′11"

6′′

PP

P

P

9′11"

Cold Flow Model

Tracer Studies Confirm Liquid In Plug Flow (N > 20)Solids Flow and Distribution??


Liquid solid riser has been considered as a reactor for solid acid catalyzed alkylations in replacing HF and sulfuric acid. The key design issue, due to rapid catalyst deactivation, is the flow pattern of liquid and solids in the riser, and the extent of backmixing of the solid catalyst in the riser. Classical impulse response tracer studies confirm that liquid is in plug flow. How about solids? The working design assumption is plug flow of solids, or some leakage of solids backwards interpreted by empirical axial dispersion coefficient. Use of CARPT and CT provides the data base coupled with CFD model for an improved model of solids flow and solids backmixing.

41

Trace over 38 s (1900 positions)

CARPT Results

-505

t = 60 sTime Average(25 - 100 s)

Z = 100 cm

Z = 125 cm

0

50

100

150

-7.6 -2.6 2.4 7.4

x-Position, cm

z-Po

sitio

n, c

m

-8

-3

2

7

12

17

0 1 2 3 4 5 6 7

Radial Position, cm

Axial Solids Velocity, cm/s

0

0.05

0.1

0.150.2

0.25

0.30.35

0.4

0 1 2 3 4 5 6 7

Radial Position, cm

Solids Holdup

0

10

20

30

40

50

60

70

80

0 1 2 3 4 5 6 7Radial Position, cm

Granular Temperature, cm2/s2

Comparison of CFD with Data

Ready for plant design, optimization and model based control

Final2-D Convection

DiffusionReactor Model for

the Riser

CFD Results

UL

Us

Dz

Dr

Roy and Dudukovic, I&EC Res., 40, 5440 (2001); AICHEJ (2005)

A single radioactive particle, monitored by CARPT, exhibits a tortuous path through the riser during a single visit . Multiplying the difference in subsequent positions with the sampling frequency yields instantaneous velocities. Averaging 2000 or more of such pathways yields a symmetric solids ensemble averaged velocity profile, with particles rising in the middle and falling by the wall. CFD computations reveal a highly complex 3 dimensional instantaneous flow structure (which explains the single particle trajectory) but 75 seconds of averaging produces the symmetric flow pattern of rising solids in the middle and falling by the wall. The agreement between simulations and data is great for solids velocity, solids holdup distribution and granular temperature, i.e., solids kinetic energy.

This now provides us with the proper model for the riser. It consists of plug flow of liquid, developed solids velocity profile with superimposed axial and radial diffusivities. This model can now be coupled with appropriate reaction and deactivation kinetics. CFD can predict all the model parameters.

42

0

50

100

150

200

-8 -4 0 4 8

Trajectories

0 10 20 30 40 50 600

0 .1

0 .2

0 .3

0 .4Tota l N um ber of Trajectories = 1473

Residence Time, s

Freq

uenc

y

Ul= 15 cm/s; S/L = 0.15

0 10 20 30 40 50 600

0 .1

0 .2

0 .3

0 .4Total N um ber of Tra jectories = 877

Residence Time, s

Freq

uenc

y

0 10 20 30 40 50 600

0 .1

0 .2

0 .3

0 .4Tota l N um ber of Trajectories = 1833

Residence Time, s

Freq

uenc

y

Ul= 20 cm/s; S/L = 0.10 Ul= 23 cm/s; S/L = 0.20

SOLIDS RESIDENCE TIME DISTRIBUTIONS

2302 .D =σ

4602 .D =σ2602 .D =σ

2 ≤ Nsolids < 6OVERALL 610180 2 .. D ≤σ≤


As a bonus, by monitoring the time of entry and exit of the tracer particle from the riser section by CARPT one obtains the residence time distribution of the solids in the riser. This confirms that solids flow deviates sometimes significantly from plug flow!

43

Full characterization of the solids flow in liquid-solid riser has been accomplished.

The CFD model developed should be tested for other similar liquid-solids flows and extended to particles of different size and density.

The slide is self-explenatory.

44

CIRCULATING FLUID BED (CFB) REACTORMaleic Anhydride

Inert Gas

Air

Off-gas (COx, H2O,..)

ButaneFeed GasReoxidized

Catalyst

ReducedCatalyst

O2 O2V+3 V+4 V+5

HC HC

RiserRiser

Regenerator Riser

Catalyst Catalyst RedoxRedox

O OO

O2

Main ReactionMain Reaction

SolidsFlow

Direction

V+5


Consider now a Circulating Fluidized bed (CFB) with a gas solid riser. Gas solid risers have been used in Fluid Catalytic Cracking (FCC) for many decades but more recently they were advocated as a reactor of choice for catalysts that can undergo an oxidation-reduction cycle and be made attrition resistant. For example, inproducing maleic anhydride from butane on a vanadium catalyst the hydrocarbon selective oxidation occurs in the riser and the catalyst regeneration by oxidation is done in the fluid bed prior to catalyst recirculation. Clearly, the solids flow pattern is a critical issue and its change with the scale of the equipment. Amazingly we still did not have conclusive answers for predicting the true extent of solids back-mixing in the riser or even for prediction of its residence timedistribution. Most importantly we did not know how flow pattern, flow regime and mixing vary with scale and this can lead to failure of scale-up. So a pilot plant may work well but the commercial plant will not if the mean contact time and its variance are not reproduced well.

45

GAS-SOLID RISER Gas-Solid Riser

Gas-Liquid or Liquid Fluidized Bed CARPT Detectors on Gas-Solid Riser


So we assembled a cold flow model where we could measure the arrival and departure of the tracer particle from the riser to establish the residence time distribution of solids at desired operating conditions. Far above the entry to the riser we instrumented a section for CARPT and did CT measurements at the same elevations.

46


Evaluation of Residence Time and First Passage Time DistributionEvaluation of Residence Time and First Passage Time Distributionss

Time spent by the tracer between B-C should not be counted in the residence time

Solids from Solids from hopperhopper

Air inlet

Riser

Solids + air into Solids + air into disengagement sectiondisengagement section

D

O

W

N

C

O

M

ER

Lead shields

Solids from Solids from hopper

Air inlet

Riser

Solids + air into Solids + air into disengagement sectiondisengagement section

D

O

W

N

C

O

M

ER

Lead shields

Typical trajectory of the tracer

BCA

D

20 30 40 50 600

200

400

600

800

Time (sec)

Cou

nts

(#)

Part of raw data from 3 detectors

Riser bottomRiser topDow ncomer top

( 1 ) A

( 2 ) B

(3 ) C D

Residence time

20 30 40 50 600

200

400

600

800

Time (sec)

Cou

nts

(#)

Part of raw data from 3 detectors

Riser bottomRiser topDow ncomer top

( 1 ) A

( 2 ) B

(3 ) C D

Residence time

Conventional tracer injection

FPTD

Bhusarapu et al., Chem. Eng. Sci., 59/22-23, 5381-5387, 2004

This slide illustrates that our CARPT technique provides the only way to determine residence times of solids precisely as it distinguishes whether the solid particle is entering or leaving the system at the entry or exit plane. For example, it is easy to determine that the time between A and B the solid spends in the system this is part of its residence time (while the time between B and C does not belong to residence time as the solid particle was outside (re-exited through the inlet plane). If one wants first passage times then only time C to D counts. This information cannot be deduced from traditional impulse-response experiments and, as well established by Nauman and Shinnar, such experiments are incapable of providing RTD information. Only CARPT can!

47


Bhusarapu et al., Ind. & Eng. Chem. Res., 44, 9739-9749, 2005

What is the true Dz?

FPTD versus Actual RTDFPTD versus Actual RTD

0 1 4 50

0.05

0.1

0.15

θ (τ = 13.52 )

Ε (

θ)

0

0.5

1Solids FPTD in the Riser with "closed-closed" Boundaries

F - c

urve

0

0.01

0.03

0.04

Ε (

θ)

0 1 4 50

0.5

1Solids RTD in the Riser with "open -open" Boundaries

θ (τ = 39.7 )

F -c

urve

Mean of FPTD = 13.52 secStdev of FPTD = 33.6 sec σ2 = 6.2 Dz = 2.1 m2/s

sec

Mean of RTD = 39.7 secStdev of RTD = 59.94 sec

σ2 = 2.3 Dz = 0.8 m2/s

sec

12

Actual

FPTD and RTD in FF regime (shown)Differences in mean residence time of 66%:

Differences in

Dimensionless variance by 170%

Dispersion coefficient by 163%

FPTD and RTD in DPT

( not shown)Differences:Dimensionless variance by 195%Dispersion coefficient by 207%

Ugriser = 3.2 m.s-1 ; Gs = 30.1 kg.m-2.s-1

To illustrate the distinction between RTD and FPTD, and point out the confusion that may arise from impulse-response measurements when it is unclear as to what is measured, we present this slide. Clearly, the mean residence time and the variance and, hence, the solids backmixing inferred from the variance is vastly different, indicating that great caution is advised when interpreting the results from the literature which are not based on CARPT experiments!

48


Instantaneous Particle Traces Instantaneous Particle Traces –– FF RegimeFF Regime

-1 -.5 0 .5 132.8

33.5

34.1

34.7

35.4

36.1

36.7

37.4

x / R

Z / D

-1 -.5 0 .5 132.8

33.5

34.1

34.7

35.4

36.1

36.7

37.4

y / R

Z / D

No. of Occurences = 55 (Positions) Residence time = 0.275 sec

Ugriser = 3.2 m.s-1

Gs = 26.6 kg.m-2.s-1

◙ Few times tracer passed through the section straight, while many more times tracer underwent internal recirculation in the section.

◙ Tracer downflow (negative axial velocity) near the center(core region) observed.

◙ Span of residence times – 0.1-100 sec! Three orders of magnitude !!

Zone of Investigation (Z/D) – 33.5-36.7

No.of Occurrences = 207 (positions) Residence Time = 1.035 sec -1-.5 0 .5 1

32.8

33.5

34.1

34.7

35.4

36.1

36.7

37.4

x / R-1-.5 0 .5 1

32.8

33.5

34.1

34.7

35.4

36.1

36.7

37.4

y / R

Z / D

Bhusarapu et al., 2005a, Powder Tech., In review

Some of the typical trajectories of the tracer particle captured in the riser section between 33.5 and 36.7 Z/D in the FF regime is depicted here. A few trajectories are almost straight up and the particle travels upward at the center of the column. Many more trajectories exhibit multiple loops including strong tracer down-flow even close the center of the column. The tracer particle residence time in this section spans three orders of magnitude. The particle that moves straight up stays very short in the section, the one caught in numerous down drafts stays very long. Only about 20% of the particles goe straight up without exhibiting downward velocities n the section of interegogation.

49


High and Low fluxes High and Low fluxes –– Axial Velocity Axial Velocity PDF’sPDF’s

0 1000 20000

5

10

15

Freq

uenc

y

r / R = 0.07

-1000 0 1000 20000

5

10

15

20r / R = 0.44

-500 0 500 10000

20

40

60

Z =

24

r / R = 0.94

n = 323<v> = -42.8 = 164.9

n = 148<v> = 440.4 = 303.3

n = 131<v> = 793.2 = 313.5 σ σ σ v v v

-1000 0 10000

20

40

60r / R = 0.063

Freq

uenc

y

-1000 0 10000

20

40

60r / R = 0.438

-1000 0 10000

200

400

600r / R = 0.938

Z / D

= 3

6

n = 407<v> = 190.25 = 382.66

v σ

n = 384<v> = 147.02

= 340.11 σ v

n = 2208<v> = -9.84

= 169.41 σ v

FF Regime –

◙ Bimodal in low, uni-modal at high fluxes- center

◙ No negative vel’s at center at high fluxes

→ Clustering phenomenon prevalent across CS – low

→ Mainly near walls - high

High Solids Flux

Low Solids Flux

DPT Regime –

◙ Time-averaged vel’s are negative near the wall - high

→ Downflow velocity in the annulus increases with flux

0 1000 20000

5

10

15

20

25

Freq

uenc

y

-1000 0 1000 20000

5

10

15

20

25

Axial velocity (cm/s)-500 0 500 1000

0

50

100

150

200

250

Z =

24

n = 158<v> = 1156.5 = 234.1

n = 168<v> = 746.9 = 378.9

n = 809<v> = -18.7 = 165.7 σ

σ σ v v v

n-Number of occurrences in the voxel (#); <v>-Mean axial velocity (cm/s); -Standard deviation of the velocity (cm/s)σ v

High Solids Flux

This slide shows how the p.d.f. of axial solids velocity characterize the flow dynamics. In the FF regime at high solids fluxes all solids flow up in the center of the column, some down-ward flow is observed at r/R = 0.44 and mainly down-ward flow at r/R = 0.94 close to the wall. In contrast, in the same FF regime at low solids fluxes, a bimodal p.d.f. is observed at the center of the column with many solid particles flowing downward even there as well as at r/R of 0.44 and near the wall. A very slow moving solids seems to be present at the wall.

In the DPT regime one never observes negative or even small positive velocities near the center with most of the downward flow occurring at the wall. That downward velocity increases with solids flux.

50


Effect of Operating Effect of Operating Conditions Conditions –– Mean VelocitiesMean Velocities

◙ “Similar profiles” in both FF and DPT regimes and at low and high fluxes

0 0.2 0.4 0.6 0.8 1

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

Non-dimensional radius ( )

Rel

ativ

e m

ean

axia

l vel

ocity

0 0.2 0.4 0.6 0.8 1

0

200

400

600

800

1000

1200

Non-dimensional radius ( )

Mea

n A

xial

Vel

ocity

(cm

/s)

FF- 3.2, 26.6, 53.1

FF- 3.2, 30.1, 61.49

DPT- 3.9, 33.7, 133.18

FF- 5.56, 144.5, 222.75

DPT- 5.49, 102, 172.51

DPT- 7.71, 119, 339.6

ξ

ξ

Ug Gsm/s kg/m2/s

<Vz>cs

cm/s

<Vz>------<Vz>

cs

<Vz>

Bhusarapu et al., 2005b, I&ECR, In review

CREL Riser (Low Flux)

Sandia’s Riser (High Flux)

Mean = Ensemble average

This slide shows that, normalized with respect to the cross sectional average velocity , the solids axial ensemble average velocity profile is almost universal independent of flow regime and riser. Clearly mean axial solids velocity increases with solids flux.

51


0 2 4 60

0.5

1

1.5

2

2.5

3E

(t/<

t>),

1/se

c

0 2 4 60

0.5

1

t/<t> (<t>= 1.19 sec)

F- c

urve

0 2 4 60

0.005

0.01

0.015

0.02

l/<l>, (<l> = 358.4 cm)

E (l

/<l>

), 1/

cm

Mean of RTD = 1.19 sec St.dev. of RTD = 2 sec Total trajectories = 1379 Dz = 0.62 Pe = 2.5

Mean of trajectory len. = 358.4 cm St.dev. of trajectory len. = 469.2 cmTotal number of trajectories = 1379

0 2 4 60

2

t/<t> (<t> = 10.1 sec)

E (t

/<t>

), 1/

sec

0 2 4 60

0.5

1

F-cu

rve

0 2 4 60

.002

.004

.006

.008

.01

.012

l/<l> (<l> = 1733 cm)

E (l

/<l>

), 1/

cm

0 2 4 6

l

Mean of RTD = 10.1 sec St.dev. of RTD = 13.9 sec Total trajectories = 708 Dz = 0.37 m2/sPe = 6.2

Mean of trajectory len. = 1733 cm St.dev. of trajectory len. = 2333 cmTotal number of trajectories = 708

Solids Solids BackmixingBackmixing –– RTD, RTD, TLDsTLDs

◙ Core-annulus flow structure in riser results in a RTD with extended tail in the DPT regime, while in the FF regime it results in a hint of a dual peak along with the extended tail.

◙ ‘Macromixing index’ decreases with flux (not shown)

Bhusarapu et al., Ind. & Eng. Chem. Res., 44, 9739-9749, 2005

lengthsticCharacterilengthtrajectoryofMeanM

⋅⋅⋅⋅

=

FF - Ugriser = 3.2 m.s-1; Gs = 26.6 kg.m-2.s-1

DPT - Ugriser = 5.49 m.s-1; Gs = 102 kg.m-2.s-1

M = 5.4

M = 9.6

m2/s

◙ Use of axial dispersion model leads to wrong conclusions regarding the effect of operating conditions on solids back-mixing and model predictions scale wrongly with column length.

The core-annulus flow structure in the riser results in the RTD with extended tail in the DPT regime and in a hint of a dual peak in the FF regime along with the extended tail.

The macromixing index decreases with flux indicating approach to plug flow.

Clearly, the use of the axial dispersion model leads to the wrong conclusion regarding the effect of operating conditions on the extent of solids backmixing.

52

CARPT provided for the first time:

• residence time distribution of solids in the riser• first passage time distribution of solids in the

riser• macromixing index of solids• full Lagrangian description of solids flow

– CFD validation is needed– Extension to different particle size and density

is needed

The slide is self explenatory.

53

Molecular scale:Particle scale:

Reactor scale:

Flow pattern & phase distributionsKinetics (chemistry)Liquid - Solid:

Gas – Liquid:

Gas – Solid:

Contacting

&

Transport

Reactor

scale

Uniform distribution

Maldistribution, stagnancy and bypassing

Particle scale: Completely wetted Partially wettedG G

L

L

G

G

L

L G

GL

Reactions can be gas or liquid reactant limited

Suggested scale-up of trickle beds maintains equal LHSV ( = liquid superficial velocity/reactor height)

With scale-up, reactor height and liquid velocity increase and affect phenomena below.

Ramachandran &Smith, 1978; Dudukovic and Mills, 1990; etc

Let us turn our attention now to scale-up of trickle bed reactors used in a number of industries. The celebrated rule of thumb is to keep constant LHSV which guarantees the constant volumetric flow of liquid per volume of the catalyst. It is inferred then that the mean contact time is the same. The problem with this approach is that the mean contact time between solids and liquid may not be the same because the liquid-solid contacting on the particle scale increases with increasing liquid mass velocity with increase in reactor scale. Hence, in absence of reactor scale mal-distribution scale up is forgiving for liquid limited reactions prevalent in the petroleum industry such as HDS etc., since contacting increases with reactor scale at constant LHSV. Unfortunately, for gas limited reactions the effect is the opposite , as an additional resistance for the gas arrival to the solid is created at larger liquid velocities. This points to the pitfalls of not understanding what rules of thumb really imply in a given system. Moreover, it is not just tj he mean contact time but its c variance that should be preserved upon scale-up.

54

Increased Particle Wetting with Increased Liquid Mass Velocity iIncreased Particle Wetting with Increased Liquid Mass Velocity in TBR n TBR Results inResults inSuccessful ScaleSuccessful Scale--up for Liquid Limited Reactions with LHSV = const.up for Liquid Limited Reactions with LHSV = const.

Key Phenomena:Key Phenomena:•• Partial external wetting at low LPartial external wetting at low L•• Complete internal wetting by capillarityComplete internal wetting by capillarity•• Reactor scale phase segregation (preventable Reactor scale phase segregation (preventable

by distributor and quench designs)by distributor and quench designs)

LiquidLiquid

GasGasSolidSolid

Porous particlesPorous particlesIncompletely external Incompletely external irrigated at low liquid irrigated at low liquid mass velocity, Lmass velocity, L

LiquidLiquid

GasGasSolidSolid

Porous particlesPorous particlesengulfed by liquid at engulfed by liquid at high mass velocity, Lhigh mass velocity, L

0.6

0.7

0.8

0.9

1.0

0.0 1.0 2.0 3.0 4.0 5.0

Liquid mass velocity, kg/m2/s

Con

tact

ing

effic

ienc

y

( ) 91

33.0 //1Re04.1 ⎥⎦

⎤⎢⎣

⎡ Δ+=

L

LLCE Ga

gZP ρη

(Al-Dahhan and Dudukovic’, 1995)

kk CEapp Λ

Λ=

tanhη

* With scale-up L increases so does kapp* The opposite is true for gas-limited

reactions.


This slide depicts the extent of external liquid particle wetting ( contacting efficiency) which is incomplete at low liquid mass velocities and increases to complete at high liquid mass velocities. The apparent rate constant for nonvolatile liquid limited reactions increases with increased contacting efficiency as that assures better supply of the liquid reactant to the catalyst. Hence, scale-up for liquid limited reactions at constant LHSV is forgiving as it guarantees the same or better apparent rate constant in larger reactor which has a higher velocity.

55

0.511.0Contacting efficiency0.90.4Conversion (xB)

3/16 ´´ x 1/8´´3/16´´ x1/8´´Catalyst tablets 0.4250.425Bed porosity 110110Temperature (C) 7070Pressure (bar)312312GHSV (hr-1)

0.0671000H2 FLOW (STD) (m3hr-1)0.2626UL (LSV) (mhr-1)1.31.3LHSV (hr-1)

0.03410.455Diameter (m)0.23519.4Height (m)LABPLANTDATA

Example of Improper TBR Scale-UpAldehyde Hydrogenation, Scale-up done based on equal LHSV

3100,

, ≈==LCE

PCE

L

P

L

P

LL

HH

ηη

Lappapp

PL

kkmkgLmkgL

,

22

44.0sec/6sec/06.0

≈==

For gas limited reaction, need both LHSV = constant and HR = constant

Unaware of this, and blindly following the constant LHSV rule, led to a major embarrassment in a major chemical company as shown here. This could have easily been prevented as the result can be anticipated based on the understanding of the system

56

Effect of Cycle Split and Total Cycle Period on Trickle Effect of Cycle Split and Total Cycle Period on Trickle Bed Performance EnhancementBed Performance Enhancement

Gas Limited Conditions (γ ~ 20)Operating Conditions : Pressure=30 psig

Cycle Split (σ)= Liquid ON Period/Total Cycle Period (τ)

CREL

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

0 50 100 150Total Cycle Period, s

X(U

S)/X

(SS)

P=30 psig, C(AMS) feed = 1627 mol/m3Cycle Split = 0.33, L (mean) 0.24 kg/m2s

• Reduction in cycle split improves gaseous reactant supply and performance enhancement (~50% over steady state)

• Region of feasibility for performance enhancement between gas starvation (low cycle period) and liquid starvation (high cycle period) zones

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0 0.2 0.4 0.6 0.8 1 1.2Cycle Split (ON time/Total Cycle Time)

Con

vers

ion

(X)

Khadilkar (CREL), 1998

Enhancement in trickle bed reactor performance achievable by forced cycling of the feed can be predicted based on the proper model of the system and has been confirmed experimentally. Unfortunately, there is large inertia to use it in industry due to improper understanding of the systems involved.

57

Liquid Distribution in Trickle Bed Reactors - Experimental Setup

• Exit Liquid Distribution

• Computed TomographyDISTRIBUTOR

Single point10mm diameter

liquid inlet

PACKING6’’ (14 cm)

Column

1<L/D<4

3mm diameterglass beads

COLLECTINGTRAY

25 crosssectional areas

x/R

y/R

-1 -0.5 0 0.5 1-1

-0.5

0

0.5

1

0.400.360.320.280.240.200.160.120.080.040.00

εL

x/D=0.34 Hbed= 2D

x (mm)

y(m

m)

-60 -40 -20 0 20 40 60

-60

-40

-20

0

20

40

60

6.56.05.55.04.54.03.53.02.52.01.51.00.50.0

Exit liquid distribution, % of total flux (FT)

L/D = 2, FT = 85 kg.m-2.s-1, Mf = 0.054UL = 4 mm.s-1, UG = 0 m.s-1

• Computed TomographyLiquid holdup

Cross-sectional liquid holdup and exit liquid distribution are compared in the region close to the reactor bottom. Figures show that results are in good qualitative agreement even though two different parameters (i.e. liquid holdup and exit liquid fluxes) are compared.

• Exit Liquid Distribution

To help enhanced understanding of the steady and dynamic behavior of these systems we run both CT scans and appropriate CFD models, hoping that this will result in enhanced phenomenological models for scale-up and design.

58

Relationships between liquid holdup distribution and liquid and gas fluxes on different packing are needed.

Effect of packing on gas and liquid distribution must be quantified.

Meso-scale particle wetting effects should be incorporated in a reactor model.

CFD should be validated for liquid and gas flow distribution.

How to assess, describe and predict voidage distribution and voidage space configuration in large beds?

Research needs on trickle bed reactors consist of the items listed on the slide.

59

Motor

Detector

Calibration Rod

Radioactive Particle

Particle trajectories Azimuthally Averaged Velocity vector plot :zr V,V

Plane including baffles

Plane including baffleszr VV x

Single phase flow in STR : Single phase flow in STR : results at a glanceresults at a glance

Plane at bottom of the tank

θV,Vr

Disc

Blades

Baffles

Rammohan et al., Chem. Eng. Research & Design (2001), 79(18), 831-844.

(150 rpm) Reimp – 12,345

Since stirred tanks are used in such a wide area of applications, we have confirmed that CARPT is capable of faithfully capturing the mean flow features, the intensity of vorticity and up to 80% of turbulent kinetic energy in single phase flow, where CARPT data is compared to LDA, PIV, etc. It takes only 16 hours for CARPT to obtain this information that takes months for other techniques to acquire. But CARPT data can be obtained in two and three phase flows where laser based techniques are useless.

60

CHEMICAL REACTION ENGINEERING LABORATORYCHEMICAL REACTION ENGINEERING LABORATORY

Overview of CFDOverview of CFD--Based Compartmental Approach Based Compartmental Approach

i,j,k

i,j,k+1

i,j,k-1

i-1,j,k i+1,j,k

i,j-1,k

i,j+1,k

uθ

uθ

ur ur

uz

uz

Solve macroscopicequations for all compartments simultaneously

Solve flow equations using CFD to generate the flow field in the tank

Calculate flows in and out of the compartments; Estimate the exchanges due to fluctuations

Macroscopic equation consist of convection due to main flow, dispersion due to turbulence (modeled as compartmental exchange term) and the reaction terms

i,j,k

i,j,k+1

i,j,k-1

i-1,j,k i+1,j,k

i,j-1,k

i,j+1,k

uθ

uθ

ur ur

uz

uz

i,j,k

i,j,k+1

i,j,k-1

i-1,j,k i+1,j,k

i,j-1,k

i,j+1,k

uθ

uθ

ur ur

uz

uz

i,j,k

i,j,k+1

i,j,k-1

i-1,j,k i+1,j,k

i,j-1,k

i,j+1,k

uθ

uθ

ur ur

uz

uz

Solve macroscopicequations for all compartments simultaneously

Solve flow equations using CFD to generate the flow field in the tank

Calculate flows in and out of the compartments; Estimate the exchanges due to fluctuations

Macroscopic equation consist of convection due to main flow, dispersion due to turbulence (modeled as compartmental exchange term) and the reaction terms

The compartmental model for a stired tank is outlined on the slide. Flows, convective as well as by turbulence, are obtained from CFD computations.

61


Compartment Compartment DiscretizationDiscretization Scheme Scheme Overall Criterion:For a given reactive system, the hydrodynamic information from CFD should be extracted such that,

In each compartment, the overall residence time is less than the characteristic reaction time scale, i.e. locally Da ≤ 1 for each compartment

(Guha et al., AIChE J., 2006)

Mixing Effect for Multiple ReactionsMixing Effect for Multiple Reactions

Reaction Scheme:

A + B R

R + B S

Desired Product

Paul & Treybal, 1971

k1 >> k2

The rules used in the discretization scheme are outlined in the slide. The model is then tested to evaluate the effect of the position of the injection port ( top feed for line 1, bottom feed for line 2) for the injection of reactant B over a short time period ( 15 seconds) into the batch of reactant A at fixed total reactant mole ratio of 1 to 1. the reults are compared to the experimental work of treybal and Pau.

62

0

10

20

30

40

50

60

70

80

Yiel

d of

R [%

]

Top Bottom

Feed Locations

Paul & Treybal (1971)Compartmental ModelFull CFDPerfect Mixing


Yield of Desired ProductYield of Desired Product

Experiment and simulation results are in reasonable agreementExperiment and simulation results are in reasonable agreementEffect of feed location capturedEffect of feed location captured

Yield of R at the completion of the reactionReactor Capacity: 5 liters

• Impeller Speed: 1600 RPM• Semi-batch addition of B into pre-charged A• Initial A concentration: 200 mol/m3

• B concentration in feed: 2000 mol/m3

• Feeding time of B: 15 s• Molar ratio of A to total B fed: 1• Number of Compartments used: 1560 (rxθxz:10x12x13)• Yield = CR/CA0

(Guha et al., AIChE J., 2006)

In their work Paul and Treybal measured the yield of R after the reaction reached completion. This shows a quantitative comparison of the measured and simulated yields of R for the two feed locations. Simulations are conducted using three models: 1) the perfect mixer model which cannot distinguish the location of the injection, 2) the proposed compartmental model, and 30 the full CFD Euler model with superimposed species conservation balances. The experiment and compartmental model simulation results are in reasonable agreement and there are no advantages to using the full blown CFD model.

63

HT=DT

DT=200mm

DT/3

DT/10

Gas Jets from

Sparger with 8 holes

Time Averaged Gas Holdup Profile

0

0.01

0.02

0.03

0.04

0.05

0 2 4 6 8 10

Radial Location (cms)

Frac

tiona

l Gas

Hol

dup

eg

Impeller

Region

Shaft + Hex Nut

Wall Region

CTCT CARPTCARPT

Two phase flow in STR : Two phase flow in STR :

results at a glanceresults at a glance

Rammohan et al. I&EC Research, 42, 2589 (2003; Ranade et al, 2004 etc)

In gas-liquid flow in stirred tanks other techniques do not work but CARPT (and CT) continue to provide data for validation of CFD codes. Note how the impeller jet weakens compared to single phase flow and how the whole flow pattern changes, subject to a substantial increase in the flow rate of gas, from impeller driven flow to bubble column type flow.

Hence, again the CARPT –CT techniques are generating the data base needed for validation of CFD models and for development of simpler engineering models for the flow patterns and mixing observed.

64


Comparison of Sojourn Time Distributions (STD) between Comparison of Sojourn Time Distributions (STD) between CARPT Data and LES of CARPT Data and LES of DerksenDerksen ( Delft) 2007( Delft) 2007

Mea

n

Sta

ndar

d D

evia

tion

1% Solids (v/v), 1000 RPM

0.00

0.04

0.08

0.12

0.16

0.20

0 0.2 0.4 0.6 0.8 1

z/T [-]

Mea

n [s

]

CARPTLES

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0 0.2 0.4 0.6 0.8 1z/T [-]

Stan

dard

Dev

iatio

n [s

]

CARPTLES

The tank height is divided into 10 axial regions each 2cm in height

The mean and variances of the STDs are defined as

∑∞

=

Δ=0

)(,st

ssisi ttEtMean μ ∑∞

=

Δ−=0

22 )()(,st

ssiisi ttEtVariance μσ∑∞

=

Δ=0

)(,st

ssisi ttEtMean μ ∑∞

=

Δ−=0

22 )()(,st

ssiisi ttEtVariance μσ

The STD at axial location is defined asi

fraction of occurrences in the location that has sojourn times between and =Δ ssi t)t(E i st ss tt Δ+

In the recent studies for liquid –solid flows in stirred tanks, conducted in collaboration with Delft University, a reasonable agreement was obtained between LES computations and CARPT experiments on the residence times of solids in various locations of the stirred tank, providing support for the extension of the compartmental model to solid – liquid systems.

65

CFD validation of multiphase flows in stirred tank is needed.

Improved description of micromixing is needed.

The slide reminds us of the obvious that in multiphase flows confirmation of the CFD models is always needed.

66

•Dynamic operation ( e.g. swing adsorption)•Periodic (symmetric) operation of packed beds with exothermic reactions

•Coupling of an exothermic and endothermic reaction in a periodically operated packed bed

•Induced pulsing in trickle beds•Counter current flow in gas-liquid-solid catalyzed systems

ADDITIONAL ATTRACTIVE OPTIONS FOR IMPROVED REACTOR PERFORMANCE CAN BE SOUGHT VIA MULTIFUNCTIONALITY AND PERIODIC OPERATION:

• Catalytic distillation

• Membrane reactors

• Flowing solids adsorbent

• Expanded solvents ( especially carbon dioxide)

IN SITU REACTOR SEPARATIONS ARE ATTRACTIVE AND CAN BE ACHIEVED VIA

Additional improved reactor performance can be achieved by the methods outlined on the slide.

67

Schematic of Bubble Column Type of Photo Reactors (Commercially Used)

A train of bubble columns (sparged reactors) through which liquid toluene and chlorinated products flow in series while chlorine is added into each column and hydrogen is removed from the column.

Typical selectivity to benzyl chloride: 90% But Toluene conversion is less than 30%.Can one do better?

Process Intensification via Multi-functionality.

Xue and Dudukovic, Chem. Eng. Sci., 54(10), 1397-1403 (1999)

This brings us to the need for other means of process intensification that can be implemented on micro or larger scale. Thus, we will look at broader than the multi-scale approach introduced earlier. This involves coupling of reaction and separation. In our laboratory we studied photochemical chlorination of toluene to benzyl chloride as desired product. Since with respect to toluene we have consecutive reactions and with respect to chlorine competitive reactions, reaction engineering 101 teaches us that we need plug flow of toluene and the liquid phase and cross flow that is backmixed flow for chlorine. Commercially, to achieve the favorable flow pattern for the formation of the intermediate, the liquid phase flows through a series of bubble columns, with light wells, while chlorine is fed in parallel to keep its concentration low. So the liquid experiences plug flow and gas is close to well mixed at its exit composition. Typical selectivity of 90% can be obtained at toluene conversion 30% or lower.

68

Process Intensification via Multifunctionality by Reaction – Separation Coupling : Proposed Technology

Configured into a Semi-Batch Mode

Schematic of Photo Reactive Distillation System

Allows in situ product removal and toluene recycle.

Selectivity to benzyl chloride: 96% + up to toluene conversion of 98%.

Xue and Dudukovic, Chem. Eng. Sci., 54(10), 1397-1403 (1999)

We have shown that by conducting the process in photo reactive distillation mode we can achieve selectivity of better than 90% at toluene conversion well above 90%. A continuous system would operate even better. Clearly, this idea can be implemented, in principle, on the micro scale or macro scale, but this reaction may be too slow for the micro scale.

69

F. Cottrell (U.S. Patent, 1938)-Foul Gas Deodorizer

S22 In running adiabatic packed beds for exothermic reactions it is well known that the temperature rise adversely affects the achievable exit conversion due to equilibrium limitations, since the equilibrium constant goes down with increased temperature. Hence, an idea patented by Cottrell in the 1930s, of swinging the bed feed from one side to the other to achieve a more favorable inverted U temperature profile, was embraced by many in the reverse flow concept which was commercially implemented in sulfuric acid manufacture and VOC abatement etc.

70

Asymmetric Reverse Flow ProcessWrong-Way Coupling (Kulkarni and Dudukovic (1996-1998)

Exo: Methanol combustionEndo: Methane Steam Reforming

S23 We have carried that idea further in our CREL by coupling an exothermic reaction (like methane combustion) with an endothermic one (like methane reforming) in periodic operation with feed switching from end to end. Modeling shows that there is a region of operability where complete conversion for both reactions and high thermal efficiency can be achieved. This concept was carried further in Hans Kuipers and Gerhard Eigenberger Laboratory and we are again working on it. Again it can be implemented from the micro to the large scale.

71

Summary and Conclusions● Advances in micro-technology have resulted in phenomenal

advances in micro-reactors offering intriguing alternatives for highly energetic, fast, and hazardous processes especially when distributed systems are desirable. Scale-up in parallel.

● Advances in non-invasive monitoring of multiphase opaque flows make validation of practical CFD codes possible and open the door for rational and successful vertical scale-up of a large number of reactor types.

● Implementation of these advances brings us closer to cleaner and more efficient processes.

● Tax incentives for implementation of novel more efficient technologies globally are called for to provide a boost to modern process development techniques.

I can briefly summarize as follows.

72

Past & Present… … Future

Environmentally Benign Catalytic Processing ...

Art Science


By improving our quantitative understanding of all the scales is the only way to process development of multiphase systems from the state of art to science.

73

Center for Environmentally Center for Environmentally Beneficial CatalysisBeneficial Catalysis

Designing environmentally responsible molecules, products, and processes –from the molecular scale to the plant scale.

Lead Institution: University of Kansas (KU)

Core Partners: University of Iowa (UI); Washington University in St. Louis (WUStL); Prairie View A&M University (PVAMU)

Director: Bala Subramaniam (KU); Deputy Director: Daryle Busch (KU)

Associate Directors: John Rosazza (UI); Milorad Dudukovic (WUStL); Irvin Osborne-Lee (PVAMU)

I also need to bring to your attention our National Science Foundation (NSF) Engineering Research Center: Center for Environmentally Beneficial Catalysis (CEBC) in which CREL is a core partner. This center presents a great opportunity for leveraging of resources and its focus is: Designing environmentally responsible molecules, products, and processes –from the molecular scale to the plant scale

74


Environmentally BeneficialCatalytic Engineered Systems

TG1: Catalyst Design and Preparation

TG2: Media and Catalyst Supports

TG3: Experimental Design and Advanced Measurements

TG4: Multi-scale Process Model- Quantum effects- Molecular dynamics- Rate theories- Solvent thermodynamics and

kinetic effect- Micromixing- Multi-component transport- Turbulence- Mixing- Computational fluid dynamics- Reactor simulation- Plant simulation- Control- Optimization

CEBC – U. of Kansas, U. of Iowa, CREL-WUStL,Prairie View A&M University (PVAMU)

The center embraces the systems approach in development of environmentally beneficial catalytic engineered systems. We have joined the lead of the University of Kansas, and with them and U of Iowa, and Texas A&M Prarie View University entered into a partnership for formation of a Center for Environmentally Beneficial Catalysis. CEBC became a reality as one of the 4 new NSF ERCs on September 1, 2003.The idea is to implement a highly interactive multi-scale approach consisting of experiments and modeling for development of new environmentally beneficial catalytic processes.

75

Acknowledgement of Financial Support and Effort in Advancing Multiphase Reaction Engineering and

Establishing Unique CARPT/CT Techniques

Department of Energy: DE-FC22 95 95051, DE-FG22 95 P 95512

CREL Industrial Sponsors: ABB Lummus, Air Products, Bayer, Chevron, Conoco, Dow, DuPont, Exxon-Mobil, ENI Technologie, IFP, Intevep, Johnson Mathey,MEMC, Mitsubishi, Monsanto, Sasol, Shell, Statoil,Syntroleum, Total, Union Carbide, UOP

CREL post-docs and J. Chen, S. Degaleesan, N. Devanathan,Graduate Students: ,P. Gupta, A. Kemoun, B.C. Ong, Y. Pan, N.

Rados, S. Roy, A. Rammohan, Y. Jiang, M. Khadilkar, Y. Jiang, A. Kemoun, B.C. Ong, Y. Pan, N. Rados, Shantanu Roy. H. Luo, S. Bhusarapu, Shaibal Roy

Special Thanks to: B.A. Toseland, Air Products and Chemicals, M. Chang, ExxonMobil, J. Sanyal, FLUENT, USA,B. Kashiwa, Los Alamos, V. Ranade, NCL, India

SPECIAL APPRECIATION TO Prof. Klavs JENSEN OF MIT FOR SLIDES ON MULTIPHASE MICRO-REACTORSMany thanks to CAMURE organizers for making my trip to India possible!

I need to acknowledge the effort and financial support of many. Special thanks are due to professor Klavs Jensen of MIT for his slides on multiphase micro-reactors.

76

CONVENTIONAL APPROACH:End-of-the-pipe-clean-up, improved house-keeping, waste reduction, retrofitting, recycle, environmentally benign processing.

UNCONVENTIONAL INNOVATIVE IDEA DISCUSSED BY TWO GENTLEMEN ABOVE: “The only other solution is that, with the help of genetic engineering, we may evolve into a species immuneto all this junk”.

Just to ensure that you can think outside the box let me inspire youwith this cartoon. Since all research money seems to be flowing into the genome related research perhaps this unconventional idea is less far fetched than you think.

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