detc2012-71168 · bridging fuel; the only way that the dilemmas can be managed is that people will...

1 Copyright © 2102 by ASME

Proceedings of the ASME 2012 International Design Engineering Technical Conferences &

Computers and Information in Engineering Conference

IDETC/CIE 2012

August 12-15, 2012, Chicago, IL, USA

DETC2012-71168

DRAFT: MANAGING DILEMMAS EMBODIED IN 21ST CENTURY ENGINEERING

Salman Ahmed1, Minting Xiao

1, Jitesh H. Panchal

2, Janet K. Allen

1 and Farrokh Mistree

1

1The Systems Realization Laboratory @ OU

2The Collective Systems Laboratory

University of Oklahoma Washington State University Norman, Oklahoma 73019 Pullman, Washington 99164 ABSTRACT

In this session we describe in four parts the pedagogy and

outcomes of a course Designing for Open Innovation designed to

empower 21st century engineering students to develop competencies

associated with innovating in an inter-connected technologically flat

world:

1. Competencies for Innovating in the 21st Century, [1].

2. Developing Competencies In The 21st Century Engineer, [2]

3. Identifying Dilemmas Embodied in 21st Century Engineering,

[3]

4. Managing Dilemmas Embodied in 21st Century Engineering -

this paper.

In the first paper we describe the core characteristics of the

engineering in an interconnected world and identify the key

competencies and meta-competencies that 21st century engineers will

need to innovate and negotiate solutions to issues associated with the

realization of systems.

In the second paper, we describe our approach to fostering

learning and the development of competencies by an individual in a

group setting. We focus on empowering the students to learn how to

learn as individuals in a geographically distanced, collaborative

group setting.

We assert that two of the core competencies required for success

in the dynamically changing workplace are the competencies to first

identify and then to manage dilemmas. In the third paper, we

illustrate how students have gone about identifying dilemmas and in

the fourth paper how they have attempted to manage dilemmas. In

papers three and four students have briefly described the challenges

that they faced and their take-aways in the form of team learning and

individual learning.

In this the last of four papers in this session, we focus on how

students learned to manage dilemmas associated with the realization

of complex, sustainable, socio-techno-eco systems, namely, energy

policy design. The example involves the identification of a bridging

fuel that balances environmental, economic and socio-cultural

concerns. The principal outcome is clearly not the result attained but

a student‟s ability to learn how to learn as illustrated through the

development of personal competencies in a collaborative learning

framework and environment.

1 FRAME OF REFERENCE

1.1 Educational context This paper is heavily scaffolded from the course AME5740

Designing for Open Innovation orchestrated by Dr. Mistree and Dr.

Panchal in Fall 2011. The course was aimed for the students to

develop some meta competencies which are given in the following

list-

1. Ability to identify the competencies and meta-competencies you

need to develop to be successful at creating value in a cultur-

ally diverse, distributed engineering world.

2. Ability to identify and manage dilemmas associated with the

realization of complex, sustainable, socio-techno-eco systems.

3. Ability to continue learning through reflection and the associated

creation and articulation of knowledge.

4. Ability to account for sustainability considerations in formulating,

partitioning, and executing multidisciplinary, systems-design

problems that are characterized by the open innovation con-

struct.

5. Ability to speculate and to identify research topics worthy of

investigation.

We, the students, were asked in the course to identify some meta

competencies that are needed to be a successful designer of energy

infrastructure in the year of 2030 by posing the Question of the

Semester:

We imagine a future in which individuals are empowered

to participate in the global value network where geograph-

ically distributed people (including engineers) collabora-

tively develop, build, and test solutions to complex socio-

techno-eco problems.

Bridging fuel: What are the technology, policy and communication

dilemmas associated with utilizing natural gas as bridging fuel for

next 25 years, while minimizing the adverse impact on quality of

life?


Policies for distributed generation technologies: What are the

technology, policy and communication dilemmas associated with

implementing the Feed-In-Tariff (FIT) policy while maximizing the

adoption of distributed generation technologies?

This is the way the course had started by presenting the question

for semester as a common platform and pushing the students out of

their comfort zone by asking them to speculate the future and identify

the competencies and learning objectives that are needed to do that.

Throughout the course Dr. Mistree and Dr. Panchal have assisted the

students to reach their competencies by introducing to them many

concepts such as learning is a conscious activity, Globalization 3,

dilemmas, sustainability, learning organization, Bloom‟s Taxonomy,

Deep Reading, Attention Directing Tools and assignments which

were either scaffolded or non-scaffolded, either on individual level or

in a group stetting where the students were both geographically and

culturally diverse etc. For additional information see [2].

After giving all this building blocks to the students, in the end of

the course student were set free and asked to answer the question for

the semester by looking back and connecting the dots by the help of

the competencies and learning objectives that the students wanted to

develop in the beginning of the course. Thus the students have been

transformed from being a tool user to tool maker.

In this paper we, Salman and Minting, present our finding about

the first part of the question for the semester. It is because after taking

the course we have learned that in 21st century we seldom face prob-

lems that are remote and have win-win solution but rather we face

with complex intertwined dilemmas that have no win-win solutions.

Dilemmas arise from requirements from multiple regions. On one

hand, conflicts of the objectives exist, on the other hand, all the

requirement regions are significant for human living; poor satisfac-

tion of requirements of any region may lead to disaster. This means

dilemmas cannot be solved, the goal of managing dilemmas can only

be to minimize loss.

Thus it is important that we identify the critical dilemmas and then

manage the dilemmas in the means of looking for trade-offs between

conflicting goals and seeking for a balanced solution.

In this paper, we describe how students learned to manage

dilemmas associated with the realization of complex, sustainable,

socio-techno-eco systems. These competencies are being developed

throughout this course and have helped us to come up with the work

in this paper. As the students in this course are in a learning

organization, with different strengths from each individual, we have

different focus on different parts of the question for the semester,

which in all result in a comprehensive thinking on some important

issues for current world. Bertus and co-authors presented an approach

to identify the dilemmas, in the context of designing FIT policies [3],

by developing the objectives and the requirements of stakeholders

and policy makers, and analyzing their interactions with Feed-In-

tariff policies.

In this paper we present findings for the first part of question for

semester which is about the bridging fuel. So as a summary, the

motivational question in this paper is „What are the dilemmas associ-

ated in eco-socio-eco system that needs to be considered? What is

the approach of finding a bridging fuel for 2030 and how does it

manages dilemmas?’

It is because after taking this course we have learned that human

being needs to adopt such engineering system that will enable us to

live in harmony with nature for the sake of sustainability. As people

have become aware of negative effects that fossil fuels are bringing

to human life, people are looking for bridging fuels that can satisfy

the energy needs of human being in the near future. However, we do

not always make decisions that will lead us to sustainable engineering

system due to the dilemmas of meeting our increased life expectancy

while using our limited resources. We need to understand that in

order to sustain we have to manage dilemmas rather than solving

specific problems. We assert that a sustainable engineering system

can be achieved if we can identify the dilemmas in the aspects of eco-

socio-eco and manage it by the help of technology.

FIGURE1 TECHNOLOGY PRISM

In Figure 1 we present a technology prism which has been taken

from the course, where the key issues in the individual aspects of

eco-socio-eco has been shown and the dilemmas between the aspects

has been identified and technology is considered as a means to

achieve sustainable engineering system. Likewise we believe that

selecting a bridging fuel which can manage the dilemmas in the

aspects of eco-socio-eco system can be a step towards sustainable

energy system. Some assumptions are made while writing the paper follow:

1. Only eco-socio-eco region has been considered as the boundary

for dilemma management and for achieving Sustainable

engineering system.

2. Our approach to manage the dilemmas is to find an appropriate

bridging fuel; the only way that the dilemmas can be managed is

that people will largely transit from dependent on current fossil

fuel system to the bridging fuel. We assume that the bridging

fuel energy system will be adopted in the next few years.

3. There are many methods for selection; each has its limitation

and advantage. The one chosen to be used in this paper has its

limitation in applying to dilemma management. However, it is

used here for demonstration process to provide some insight of

how the dilemmas can be managed.

4. Assumptions are made that the potential fuel sources used in

carrying out the selection methods are the most suitable candi-

dates.

5. The decisions regarding comparison of each attributes of each

fuel sources in preliminary selection is based on intuition.

6. Relative importance of attributes of selection process is based

on intuition.

7. Attribute ratings of selection process are based on intuition after

reflecting from hard information.

8. The principal outcome is clearly not the result attained but

a student‟s ability to learn how to learn as illustrated

through the development of personal competencies in a

collaborative learning framework and environment.

Our approach for managing dilemmas is illustrated in Figure 2.

The inner triangle represents the dilemmas from three regions of the


most important issues that human are facing with. In order to

minimize the damage, we come up with the approaches to deal with

the dilemmas, by using different domains of knowledge in Bloom‟s

Taxonomy introduced in this course. The earlier steps of managing

the dilemmas are included in the outer triangle, which involves

Knowledge, Analysis and Evaluation. The later steps of managing the

dilemma, which is the process of carrying out the numerical models,

is the synthesis of the previous steps and the dilemma prism, is in the

center of the picture.

The road map of this paper is explained in terms of the steps of

the approach to deal with dilemmas.

1. List the dilemmas. The approach to identify the dilemmas is

introduced by Bertus and co-authors [3]. In this paper the dilem-

mas are listed in Section 1.1

2. Analyze and break down each dilemma to find the conflicting

goals within the dilemma. The requirements we come up with

are in Section 2.1

3. Categorize the dilemmas into different regions of eco-socio-

eco.*

4. Prioritize and rank the dilemmas according to their importance.*

The relative importance of different requirements are presented

in the tables of Selection Process in Section 2.3.

5. List the alternatives/methods that can possibly solve the conflict-

ing goals. This is in Section 2.1.

6. Evaluate the strength and weakness of the alternatives against

meeting the goals. The evaluation against the general require-

ments of each region is presented in Preliminary Selection phase

in Table 1.4, and the evaluation with more information against

more specific requirements are presented in the Selection Pro-

cess.

7. Come up with a number of most-likely-to-succeed alternatives

based on the strength and weakness with regard to the general of

each alternative, and the prioritizing of the conflicting goals.

This is the Preliminary Selection Process, and the numerical

model is explained in Section 2.2.

8. Select the fuel that is best in reaching a balance that is desired

because of our relative priority of the goals. This is the Selection

Process, and the numerical model is explained in Section 2.3.

FIGURE 2 STRUCTURE OF THE PAPER ON AN APPROACH FOR MANAGING DILEMMAS

* The dilemmas are categorized and prioritized based on

technology prism concept.

1.2 Dilemmas in an economic, socio-cultural,

ecological system

Before identifying the dilemmas, first it is necessary to

understand the concept of dilemma. As it has been defined in

Wikipedia „A dilemma is a problem offering two possibilities,

neither of which is practically acceptable. One in this position

has been traditionally described as "being on the horns of a

dilemma", neither horn being comfortable. This is sometimes

more colorfully described as "Finding oneself impaled upon

the horns of a dilemma", referring to the sharp points of a

bull's horns, equally uncomfortable (and dangerous)‟. So, we

understand that there is no win-win solution in a dilemma

because it cannot be solved. We have to find balances between

the conflicting objectives in order to reduce the harmful ef-

fects.

A seven step method is described for identifying

dilemmas in context of FIT; see [3]. We have followed those

seven steps in a general way and used it in context of

sustainability to identify dilemmas. Based on the Technology

Prism in Figure 1, we have identified that the stakeholders for

sustainable system are three regions consisting of economical,

socio-cultural and ecological. We have analyzed the demand

and wishes of those three regions and synthesized the

dilemmas by merging the conflicting demands and wishes

from each region. The dilemmas are given as follows-

Ecology - Economic

1 The fuel should be such that it is environmental friendly

and has low lifecycle cost.

2 The need to reduce the toxic waste of the fuel over the

need to decrease lifecycle cost.

Ecologic - Socio-Cultural

3 The need of the fuel to be renewable and also to be capa-

ble of meeting huge public demand.

4 The need of the fuel to be environmentally friendly

(Renewable energy, like wind energy) over the need of

the fuel to meet the demand of geographically distributed

customers.

Economic – Socio-Cultural

5 The need to consume less in order to preserve ecological

system over the need to improve the quality of life

6 The need of the fuel to meet the demand of public over

the need to reduce dependence on foreign oil.

7 The need to transit to new energy infrastructure based on

domestic/reliable fuel source (considering national secu-

rity) over the cost of transition.

It is seen that the issues from different regions are not iso-

lated but rather they are interconnected and create dilemmas

which must be managed. In Section 2.22 we have presented

the requirement criteria that a bridging fuel must have to man-

age the dilemmas mentioned above.

As it has been stated in the abstract that our focus is about

presenting an approach to manage the dilemmas with the help of

selection tools . So in the next section we have shown literature

review of selection methods. The result of selecting a

bridging fuel is discussed in Section 3. And how the

process of selection a bridging fuel helps managing the

dilemma is explained in Section 4.

http://en.wikipedia.org/wiki/Problem

http://en.wiktionary.org/wiki/be_on_the_horns_of_a_dilemma

http://en.wiktionary.org/wiki/be_on_the_horns_of_a_dilemma


2 LITERATURE REVIEW ON SELECTION METHODS

Engineers often face situations where decisions need to be

made between conflicting objectives and they rely on Multi

Criteria Decision Making (MCDM) to support their decision

making. There are over 70 MCDM methods in existence

however all of them have fundamental short comings and

majority of them are nothing more them attention directing

tools, [4]. According to George Hazelgigg

regarding the

verification and validation of selection methods, there is only

one true MCDM methods and the rest of them completely or

partly fail to meet the criteria, [5]-

1. The method should provide a rank ordering of candidate

designs.

2. The method should not impose preferences on the

designer, that is, the alternatives should be ranked in

accordance with the preferences of the designer.

3. The method should permit the comparison of design

alternatives under conditions of uncertainty and with risky

outcomes, including variability in manufacture, materials,

etc., which pervade all of engineering design.

4. The method should be independent of the discipline of

engineering and manufacture for the product or system in

question.

5. If the method recommends design alternative A when

compared to the set of alternatives S¼{B, C, D, . . . },

then it should also recommend A when compared to any

reduced set SR, such as {C, D, . . . } or {B, D, . . . } or

{D, . . . }, etc.

6. The method should make the same recommendation

regardless of the order in which the design alternatives are

considered.

7. The method itself should not impose constraints on the

design or the design process.

8. The method should be such that the addition of a new

design alternative should not make existing alternatives

appear less favorable.

9. The method should be such that obtaining clairvoyance on

any uncertainty with respect to any alternative must not

make the decision situation less attractive (information is

always beneficial).

10. The method should be self-consistent and logical, that is, it

should not contradict itself and it should make maximum

use of available information for design alternative selec-

tion.

In addition to fail to meet the criteria, different MCDM

methods provide different result for the same problem and

hence it is extremely important that the Decision Makers

(DM) are aware of the problem in hand, limitations of MCDM

methods and interpretation of results.

In this paper, attention directing tool is used because of the

quality and quantity of available information. An attention

directing tools acts as a guide, a result is produced, with the

DM making the final selection, considering the area of

applicability the tool, the limitations and assumptions associ-

ated with it, and an analysis of the consistency and sensitivity

of the results. When using a selection method the DM

assumes that complete information is available; hence the data

input is a perfect reflection of the physical situation. The use

of an attention directing tool does not require the DM to make

this assumption, and allows for the DM to attempt to compen-

sate and investigate the effects of this imperfect and incom-

plete representation.

2.1 An Approach to Selection Methods

The approach for selection of the bridging fuel is based on

the Preliminary Selection DSP and Selection DSP methods

proposed by Mistree and co-authors [10].. They proposed two

methods for selection namely preliminary selection and

selection process. The preliminary selection Decision support

problem is to be formulated and solved when a decision is to

be based on experience based soft information. A selection

decision support problem is to be formulated and solved when

meaningful hard information is available.

Preliminary selection involves the selection of the most-

likely to succeed concepts for further development into feasi-

ble alternatives. A flow chart of preliminary selection is

shown in Figure 3.

Figure 3 FLOW CHART OF PRELIMINARY SELECTION

The selection DSP facilitates the ranking of alternatives

based on multiple attributes of varying importance. The order

indicates not only the rank but also by how much one alterna-

tive is preferred to another. Both science based objective

information and experience based subjective information can

be used. A flow chart of selection is shown in Figure 4.

Figure 4 FLOW CHART OF SELECTION

2.2 Preliminary Selection

Each of the following section is based on the Steps shown

in Figure 3.

2.2.1 Step I- Potential Candidates of Fuel Sources We have identified the following nine alternatives for bridging

fuels. They are presented in no specific order. Each is listed with an

acronym, a small summary, and a basic list of advantages and disad-

vantages relating to that particular alternative.

Nuclear (old and new plants) - NF


Encompassing fission and fusion, nuclear power focuses on

reactions between particles on the atomic and subatomic levels which

produce high amounts of energy. Nuclear fission involves the split-

ting of Uranium atoms to create heat. That heat is contained and

routed to power steam turbines which, in turn, power generators that

create electricity. Nuclear fusion could nearly be considered com-

pletely opposite of fission as it joins, rather than separates, multiple

atoms together. This process requires a significant amount of heat to

begin the reaction but the results are explosive. Unlike fission,

nuclear fusion is not well controlled to where the energy can be easily

harvested

Petroleum - OIL

One of the fossil fuels in this list, petroleum in a very strict sense

refers solely to crude oil. More commonly it refers to the different

possible states of hydrocarbons. In general, fossil fuels are used in

power plants similar to nuclear fission in that they mainly provide

heat to turn a turbine, in turn turning a generator, and produce

electricity. The main difference is that a fossil fuel power plant

requires combustion of the fuel. The heat from combustion converts

water into steam which is then used to turn the turbines.

Coal (old plants and plants with carbon-capture technology) - CL

Another of the fossil fuels listed here, coal is made up of carbon

and various other elements including hydrogen. As with petroleum,

coal is burned to heat steam to power turbines which turn generators

and produce electricity. One main difference between coal and petro-

leum is that coal must be crushed into a fine dust to be burned. Coal

currently provides roughly a quarter of our energy.

Natural Gas - NG

Natural gas is a naturally occurring gas mixture consisting

primarily of methane, typically with 0–20% higher hydrocarbons

(primarily ethane). It is found associated with other hydrocarbon fuel,

in coal beds, as methane clathrates, and is an important fuel source

and a major feedstock for fertilizers.

Most natural gas is created by two mechanisms: biogenic and

thermo genic. Biogenic gas is created by methanogen organisms in

marshes, bogs, landfills, and shallow sediments. Deeper in the earth,

at greater temperature and pressure, thermo genic gas is created from

buried organic material.

Before natural gas can be used as a fuel, it must undergo pro-

cessing to remove almost all materials other than methane. The by-

products of that processing include ethane, propane, butanes, pen-

tanes, and higher molecular weight hydrocarbons, elemental sulfur,

carbon dioxide, water vapor, and sometimes helium and nitrogen.

Natural gas is often informally referred to as simply gas, especially

when compared to other energy sources such as oil or coal.

Solar (photovoltaic, concentrated solar, solar heating, solar energy

chemical storage [like hydrogen generation]) - SL

Solar energy, radiant light and heat from the sun, has been har-

nessed by humans since ancient times using a range of ever-evolving

technologies. Solar radiation, along with secondary solar-powered

resources (such as wind and wave power, hydroelectricity and bio-

mass) account for most of the available renewable energy on earth.

Only a minuscule fraction of the available solar energy is used.

Solar powered electrical generation relies on heat engines and

photovoltaic. Solar energy's uses are limited only by human ingenu-

ity. A partial list of solar applications includes space heating and

cooling through solar architecture, potable water via distillation and

disinfection, day lighting, solar hot water, solar cooking, and high

temperature process heat for industrial purposes. To harvest the solar

energy, the most common way is to use solar panels.

Solar technologies are broadly characterized as either passive

solar or active solar depending on the way they capture, convert and

distribute solar energy. Active solar techniques include the use of

photovoltaic panels and solar thermal collectors to harness the

energy. Passive solar techniques include orienting a building to the

Sun, selecting materials with favorable thermal mass or light dispers-

ing properties, and designing spaces that naturally circulate air.


Wind (on-shore, off-shore) –WD

Wind power is the conversion of wind energy into a useful form

of energy, such as using wind turbines to make electricity, windmills

for mechanical power, wind pumps for water pumping or drainage, or

sails to propel ships.

Biomass – BM

Biomass, as a renewable energy source, is biological material

from living, or recently living organisms. As an energy source, bio-

mass can either be used directly, or converted into other energy prod-

ucts such as biofuel.

In the first sense, biomass is plant matter used to generate

electricity with steam turbines & gasifies or produce heat, usually by

direct combustion. Examples include forest residues (such as dead

trees, branches and tree stumps), yard clippings, wood chips and even

municipal solid waste. In the second sense, biomass includes plant or

animal matter that can be converted into fibers or other industrial

chemicals, including biofuels. Industrial biomass can be grown from

numerous types of plants, including miscanthus, switch grass, hemp,

corn, poplar, willow, sorghum, sugarcane, and a variety of tree spe-

cies, ranging from eucalyptus to oil palm (palm oil).

Geothermal (heating and electricity) – GT

Geothermal energy is thermal energy generated and stored in the

Earth. Thermal energy is the energy that determines the temperature

of matter. Earth's geothermal energy originates from the original

formation of the planet (20%) and from radioactive decay of minerals

(80%)4

Hydropower (dams, miniature dams, river hydropower, wave power,

tidal power, rain power) – HP1,2

Hydropower is power that is derived from the force or energy of

falling water, which may be harnessed for useful purposes. Since

ancient times, hydropower has been used for irrigation and the opera-

tion of various mechanical devices, such as watermills, saw mills,

textile mills, dock cranes, and domestic lifts. In modern times it is

used to produce electricity by building dams.

Hydro is one of the largest producers of electricity in the United

States. Water power supplies about 10 percent of the entire electricity

that we use

2.2.2 Step II-Requirement criteria of Bridging Fuel The dilemmas associated in using fuels is presented in Section

1.1 the requirement criteria of bridging fuel under the region of ecol-

ogy, social and economic of the bridging fuel is identified.

Environmental

• Effects on environmental elements (soil, water, air, etc.) [EEE]

- It covers the side effects that are incurred on earth, water, air

etc. due to its usage.

• Renewability/Recyclability [RW] - It tries to classify whether

the fuel is renewable and also whether it can be recycled or not

• Reduction of toxic wastes. [RTW] - It means that the fuel

which is less toxic is the better one.

Economic

• Lifecycle cost [LCC] - It is the sum of all recurring and one-

time (non-recurring) costs over the full life span or a specified

period of a good, service, structure, or system. In includes pur-

chase price, installation cost, operating costs, maintenance and

upgrade costs, and remaining (residual or salvage) value at the

end of ownership or its useful life.(From Business dictionary)

• Cost per kilowatt hour to produce [CPP] - It is the price to pro-

duce energy.

• Reduce dependence on foreign oil [RDFO] - It is implying that

domestic fuel source should be preferred over foreign fuel

source so that it can make a secured energy sector.

• Meet the demand of geographically distributed customers

[DGDC] - It means that the fuel can delivered wherever there

is demand i.e. the availability of fuel is high and it can reach its

customers easily.

Socio-Cultural

• Maintains or improves the quality of life [QL] - This relates

basically to the overall health of the population. The bridging

fuel should not cause or contribute to any negative effects on

individual health.

• Available to all that desire to use the fuel [ADF] - Relating in

part to its versatility, the bridging fuel must be in ample supply

to be purchased for personal and commercial use.


• Available on demand, reliable [DR] - The general population

has become accustomed to on-demand electricity and energy.

The standard of living is not expected to decline because of the

selection of the bridging fuel.

• Empowers customers [EC] - In this wired and interconnected

world that is continually being flattened, individuals are able to

partake in activities that could not be done previously. A

bridging fuel that supports more individuals' efforts to compete

in the G3 world is vital.

Engineering

• Secure [SC] - In basic terms, this refers to how safe the bridg-

ing fuel is with respect to personal, national, and source secu-

rity. Personal security consists mainly of safety through per-

sonal use. National security refers to the safety of our nation

at all times. Source safety includes supply amount,

accessibility, and reliability.

• Ability to scale with demand [SD] - Energy demand is varia-

ble, dependent on far too many factors to list. Scaling down

when demand is low and scaling up when demand peaks is

extremely important since energy or electricity cannot be

easily stored.

• Versatile [V] - Many current technologies require the same

fuel source for operation. Choosing an appropriate bridging

fuel for the future means it may be utilized in varying fields

for various purposes. Its ability to meet the requirements for

each of these fields is of considerable importance.

• Easily transported [ET] - Energy in the form of electricity is

easily transported from place to place by means of the mil-

lions of miles of power lines. Since electricity is not har-

vested directly, it is important that the bridging fuel can be set

up for converting immediately to electricity after extraction or

can be transported quickly and easily to a power plant to do

the same.

• Efficient [EFF] - The generic definition of thermal efficiency

is simply stated as the ratio of what comes out of the system

to what goes in. A greater efficiency is desired as a given

process with higher efficiency will yield more products or re-

quire less input to yield a constant amount of product

2.2.3 Step III- Viewpoints of Attributes In order to work efficiently in the selection process, general

viewpoints are given here as guidelines to creating the Comparison of

Concepts tables with respect to the datum. A table of comparison of

some fuels with nuclear power (NF) is given in 2.24 as an example,

see Table 1. The justification of viewpoints for that comparison with

NF as datum is included below.

[EEE] - Does the bridging fuel alternative cause or have the

potential to cause more or more severe environmental effects than the

datum? If so, -1. If it will produce similar effects on the

environment, 0. If it will produce less harsh effects on the

environment so that it will be better than the datum, 1. With regard to

this attribute, all other fuels are better than nuclear power,

considering the risk of accidents which will bring disaster to

environment from nuclear power.

[RW] - Is the bridging fuel alternative renewable or recyclable?

If yes and the datum is not, 1. If not and the datum is not OR if so

and the datum is also, 0. If not and the datum is, -1. Among all the

fuels here in Table 1, only biomass (BM) is renewable, and others are

not, thus BM gets „1‟ and others get „0‟.

[RTW] - Does the bridging fuel alternative produce toxic waste

or utilize toxic materials? If yes and the datum does not, -1. If not

and the does not OR if so and the datum does as well, 0. If not and

the datum does, 1. Since the possible leaking or waste from nuclear

power station is much more toxic than other fuels in Table 1, all other

fuels get „1‟ with regard to this attribute.

[LCC] - The lifecycle cost refers to all costs involved with the

harvesting (time, labor, and technology), any safety costs, the support

costs, transporting costs, etc., all the way to disposal costs. Will the

bridging fuel alternative cost less than the datum over their lifecy-

cles? If so, 1. If not, -1. If they will be about the same, 0. Consider-

ing the significant cost of money and strict requirement of technology

and time it takes to build qualified nuclear power station to generate

power, and relatively lower cost for other bridging fuels, all other

bridging fuels get „1‟ with regard to this attribute.

[CPP] - This focuses solely on the cost to produce a kilowatt

hour of electricity. If this price is greater than the datum, -1. If this

price is the same as the datum, 0. If this price is less than the datum,

1. As clarified for LCC, the high lifecycle cost of nuclear makes the

cost per kilowatt hour of electricity from nuclear also higher than

other fuels compared here. Thus other fuels get „1‟ here.

[RDFO] - Does the bridging fuel alternative utilize or have the

potential to utilize only domestic product? If the bridging fuel

alternative does and the datum does not, 1. If the bridging fuel does

not and the datum does, -1. Else, 0.

[DGDC] - Is the bridging fuel alternative of a form that it can be

transported before being converted to electricity? If the bridging fuel

alternative is and the datum is not, 1. If the bridging fuel is not and

the datum is, -1. Else, 0. Among the fuels in Table 1, only oil and

natural gas can be easily transported, thus these two alternatives get

„1‟ while others get „0‟.

[QL] - Will the bridging fuel alternative contribute to or create

poor health in individuals of the population? If the bridging fuel will

and the datum does not, -1. If the bridging fuel will not and the

datum will, 1. Else, 0. Nuclear power is related to possible negative

effect on living environment thus threatening the health of

individuals, while other fuels in the table only result in extra carbon

dioxide, which is not a threat to human health, thus all other

alternatives get „1‟.

[ADF] - Is the bridging fuel alternative available for personal

and commercial use? Alternatively, does it provide fuel or energy to

the consumer? If the bridging fuel is available for personal or

commercial use and the datum is not, 1. If the bridging fuel is not

available for personal or commercial use and the datum is, -1. Else,

0.

[DR] - Does the bridging fuel alternative once converted to

energy/electricity have a delay in delivery or is it practically available

at all times? If it is always available and the datum is not, 1. If it is

not always available and the datum is, -1. Else, 0.

[EC] - Will the bridging fuel alternative allow the consumer to

participate and compete in the G3 world? If the bridging fuel will

and the datum will not, 1. If the bridging fuel will not and the datum

will, -1. Else, 0. It requires large cost and high technology for

extracting energy for utility from oil, natural gas, coal and nuclear

power, thus these alternatives hardly allow individuals to participate

in energy generation. Biomass especially requires specific technology

that is not broadly developed， which even is more difficult for

individuals to participate in. Thus alternatives all get „0‟ and BM get

„-1‟.

[SC] - How reliably can the bridging fuel alternative be sourced

or are there issues with personal safety or national security? If there

are these issues with the bridging fuel alternative and none with the

datum, -1. If these issues do not exist with the bridging fuel but do

with the datum, 1. Else, 0. Considering the national security

regarding sourcing, alternatives that can be supplied sufficiently

within the nation is considered good. Dependent of oil sourcing is

related to oil monopoly and potential risk of shortage, thus it gets -1.

[SD] - Is the bridging fuel alternative able to be scaled

appropriately to meet demands at peak and downtimes? If so, and the


datum is not, 1. If not and that datum can, -1. Else, 0. All other

alternatives in the table are better in the ability to immediate scaling

than nuclear power, due to the nature and technology limitation that

nuclear power is generated.

[V] - Does the bridging fuel alternative have the ability to meet

the requirements of various fields? If so and the datum does not, 1.

If not and the datum does, -1. Else, 0. The infrastructure and facility

makes oil and natural gas can be adapted to more diverse fields than

the other three alternatives.

[ET] - Is the bridging fuel alternative in its unconverted form

(i.e., not yet converted to electricity) easily transportable or set up in

such a way that it does not need to be transportable? If so and the

datum is not, 1. If not and the datum is, -1. Else, 0.

[EFF] - When compared to the datum, does the bridging fuel

alternative produce more or less energy per a constant given amount

of fuel? If more, 1. If less, -1. If the same, 0. Regarding the

efficiency of power generating, nuclear power has a significant

disadvantage considering the consuming of substance in the process

of power generating, thus others get 1.

2.2.4 STEP IV-Preliminary Selection Process In Scenario 1, the datum is nuclear power (NF), meaning the

remainder of the alternatives are compared directly to and only to it.

The same carries through for the later scenarios for their respective

datum. The lower the value of the rank, the "better" is the choice.

As an example of preliminary selection process, one table is shown

below.

Table 1.1 PRELIMINARY SELECTION, SCENARIO 1



OIL NG COAL NF BM

ENVIRONMENTAL

EEE 1 1 1 0 1

RW 0 0 0 0 1

RTW 1 1 1 0 1

Score 2 2 2 0 3

Normalized score 2/3 2/3 2/3 0 1

ECONOMICAL

LCC 1 1 1 0 1

CPP 1 1 1 0 1

DGDC 1 1 0 0 0

Score 3 3 2 0 2

Normalized score 1 1 2/3 0 2/3

SOCIAL

QL 1 1 1 0 1

EC 0 0 0 0 -1

Score 1 1 1 0 0

Normalized score 1 1 1 0 0

ENGINEERING

SC -1 1 0 0 1

SD 1 1 1 0 1

V 1 1 0 0 0

EFF 1 1 1 0 1

Score 2 4 2 0 3

Normalized score 1/2 1 1/2 0 3/4

OVERALL SCORES AND RANKS

Sum of normalized scores 3.167 3.667 2.833 0.000 2.417

Ranks 2 1 3 5 4

ATTRIBUTESALTERNATIVES

SCENARIO 1 DATUM: NF

OIL NG COAL NF BM

ENVIRONMENTAL

EEE -1 -1 -1 -1 0

RW -1 -1 -1 -1 0

RTW -1 -1 -1 -1 0

Score -3 -3 -3 -3 0


ECONOMICAL

LCC 1 1 1 -1 0

CPP 1 1 1 0 0

DGDC 1 1 1 0 0

Score 3 3 3 -1 0

Normalized score 1 1 1 0 1/4

SOCIAL

QL -1 -1 -1 -1 0

EC 1 1 1 -1 0

Score 0 0 0 -2 0


ENGINEERING

SC -1 1 1 0 0

SD 0 0 0 -1 0

V 1 1 1 0 0

EFF -1 -1 0 -1 0

Score -1 1 2 -2 0

Normalized score 1/4 3/4 1 0 1/2


Sum of normalized scores 2.250 2.750 3 0 2.750

Ranks 4 2 1 5 2

SCENARIO 2 DATUM: BM

ATTRIBUTES ALTERNATIVES

OIL NG COAL NF BM

ENVIRONMENTAL

EEE 1 1 0 -1 1

RW 0 0 0 0 1

RTW 1 1 0 -1 1

Score 2 2 0 -2 3

Normalized score 4/5 4/5 2/5 0 1

ECONOMICAL

LCC 1 1 0 -1 -1

CPP -1 -1 0 -1 -1

DGDC 1 1 0 0 0

Score 1 1 0 -2 -2

Normalized score 1 1 2/3 0 0

SOCIAL

QL 1 1 0 -1 1

EC 0 0 0 0 -1

Score 1 1 0 -1 0

Normalized score 1 1 1/2 0 1/2

ENGINEERING

SC -1 0 0 -1 1

SD 1 1 0 0 0

V 1 1 0 -1 -1

EFF 1 1 0 -1 0

Score 2 3 0 -3 0

Normalized score 5/6 1 1/2 0 1/2


Sum of normalized scores 3.633 3.800 2.067 0 2

Ranks 2 1 3 5 4

SCENARIO 3 DATUM: COAL





2.2.5 STEP V-Assigning Weights and Normalizing

A table is created where, for a particular scenario, one of the

generalized criteria is considered more important than the others. In

scenario one, that is Environmental; in scenario two it is Economical,

and so on. In Scenario 5, a staggered weighting is given rather than a

single, overriding criteria.

Table 2 WEIGHT OF THE ATTRIBUTES

In the second table we have determined the total normalized

score for each alternative and, further, for each scenario. The chart is

aligned so as to act as an extension of the above chart. That is, the

column just to the right of the alternatives is for Scenario 1 and the

final column below is for Scenario 5. The equation to determine the

different scores is given in a general form in the table as well.

TABLE 3 TOTAL SCORE

2.3 Selection DSP

After preliminary selection, the most-likely-to-succeed alterna-

tives have been identified by using soft information. Then a selection

Decision Support Problem to identify the best concept is to be solved.

At this stage, both soft and hard information is involved, and the

preference for alternatives is considered with regard to different

emphasis on attributes for each alternative respectively.

The selection process is divided in several steps as shown in

Figure 4 for ease of carrying out the process.

2.3.1 Different Steps of Selection DSP STEP I

Table 4 is produced to introduce the candidates of fuel sources

Table 4 CANDIDATES OF FUEL SOURCES

STEP II

OIL NG COAL NF BM

ENVIRONMENTAL

EEE -1 0 -1 -1 1

RW 0 0 0 0 1

RTW -1 0 -1 0 1

Score -2 0 -2 -1 3

Normalized score 0 0.4 0 0.2 1

ECONOMICAL

LCC -1 0 -1 -1 -1

CPP -1 0 1 -1 -1

DGDC 0 0 -1 -1 -1

Score -2 0 -1 -3 -3

Normalized score 1/3 1 2/3 0 0

SOCIAL

QL -1 0 -1 -1 1

EC 0 0 0 0 -1

Score -1 0 -1 -1 0


ENGINEERING

SC -1 0 0 -1 0

SD 0 0 0 -1 -1

V 0 0 -1 -1 -1

EFF 0 0 1 -1 -1

Score -1 0 0 -4 -3

Normalized score 3/4 1 1 0 1/4


Sum of normalized scores 1.083 3.400 1.667 0.200 2.250

Ranks 4 1 3 5 2

SCENARIO 4 DATUM: NG


OIL NG COAL NF BM

ENVIRONMENTAL

EEE 0 1 -1 -1 1

RW 0 0 0 0 1

RTW 0 1 -1 -1 1

Score 0 2 -2 -2 3

Normalized score 2/5 4/5 0 0 1

ECONOMICAL

LCC 0 1 -1 -1 -1

CPP 0 1 1 -1 -1

DGDC 0 0 1 -1 -1

Score 0 2 1 -3 -3

Normalized score 3/5 1 4/5 0 0

SOCIAL

QL 0 1 -1 -1 1

EC 0 0 0 0 -1

Score 0 1 -1 -1 0


ENGINEERING

SC 0 1 1 -1 1

SD 0 1 0 -1 -1

V 0 0 -1 -1 -1

EFF 0 -1 1 -1 -1

Score 0 1 1 -4 -2



Sum of normalized scores 2.300 3.800 1.800 0 1.900

Ranks 2 1 4 5 3

SCENARIO 5 DATUM: OIL


One Two Three Four Five

Environmental 0.4 0.2 0.2 0.2 0.2

Economical 0.2 0.4 0.2 0.2 0.3

Social 0.2 0.2 0.4 0.2 0.2

Engineering 0.2 0.2 0.2 0.4 0.3

Generalized

Criteria

Scenario Number

Alternative

Oil 0.767 0.650 0.927 0.367 0.600

NG 0.867 0.750 0.960 0.880 0.960

Coal 0.700 0.800 0.513 0.533 0.540

Nuclear 0.000 0.000 0.000 0.040 0.000

Biomass 0.683 0.600 0.500 0.475 0.420

Σ[(Scorenormalized)x(Weight)]

Name Acronym Description

Alternative

1Nuclear NF Splitting Uranium Atom

Alternative

2Petroleum OIL Crude Oil and Hydrocarbons

Alternative

3Coal COAL Mostly Carbon

Alternative

4Natural Gas NG Mostly Methane

Alternative

5Biomass BM Biological Matter


In Table 5, the relative importance of the attributes is shown

based on giving more weights in each of the regions of socio,

economics and ecology. For example, to show more weight on socio-

cultural we have given highest priority on Attributes 11 and 12.

Similarly when economy or ecology is most important then highest

priority is given to Attributes 4, 5 or Attributes 1, 3 respectively. The

cumulative sum of the relative importance is equal to 1.

Table 5 ASSIGNING RELATIVE IMPORTANCE TO THE ATTRIBUTES

Table 6 SCALES

STEP III

The scale in Table 6 is used for all attributes except for AT#5

and AT#12. The scales for those two attributes are given below,

respectively.

Table 7 SCALES FOR AT#5

Table 8 SCALES FOR AT#12

Table 9 ATTRIBUTE RATINGS

STEP IV

Table 10 NORMALIZED ATTRIBUTE RATINGS

STEP V

The data for relative importance of the attributes are taken from the

column weighted ecology Table 5.

Attribute

(AT)Description

Acro

nym

Relative

Importance

Weigted

Socio

Relative

Importance

Weigted

Economy

Relative

Importance

Weigted

Ecology

#1

Effects on environmental elements

(soil, water, air, etc.) Ordinal

converted to interval scale. Range of

rating values: 0-5. Larger number

preference.

EEE 0.0769 0.0128 0.1538

#2

Renewability or Recyclability. Ordinal


rating values: 0-5. Larger number

preference.

RW 0.0513 0.0256 0.0769

#3

Reduction of toxic waste. Ordinal


rating values: 0-5. Large number

preference.

RTW 0.0385 0.0385 0.1410

#4

Lifecycle costs. Ordinal converted to

interval scale. Range of rating values:

0-5. Large number preference.

LCC 0.0641 0.1538 0.1282

#5

Cost per kilowatt hour to produce.

Ordinal converted to interval scale.

Range of rating values: 0-3. Large

number preference.

CPP 0.0128 0.1410 0.0513

#6

Meet the demand of geographically

distributed customers. Ordinal

converted interval scale. Range of


preference.

DGDC 0.0897 0.0897 0.0897

#7

Maintains or improves the quality of

life. Ordinal converted interval scale.


number preference.

QL 0.1026 0.1026 0.1026

#8

Empowers customers. Ordinal



preference.

EC 0.1282 0.1282 0.0128

#9

Secure energy source with respect to

supply, reduce long-term price

volatility, and the capacityto promote a

more resilient electricity system.

Ordinal converted interval scale.


number preference.

SC 0.0256 0.1154 0.1154

#10

Ability to scale with demand. Ordinal



preference.

SD 0.1538 0.0641 0.0641

#11

Versatile. Ordinal converted interval

scale. Range of rating values: 0-5.

Large number preference.

V 0.1410 0.0769 0.0256

#12

Produce energy efficiently. Ordinal

converted to interval. Range of rating

values: 0-2. Large number preference

EFF 0.1154 0.0513 0.0385

Interval Ordinal

0 Unacceptable 0-20% chance of success in meeting the attribute; major revisions required for improvements

3 Very Good 60-80% probability of meeting a fair amount of the attribute

40-60% probability of meeting the attribute

1 Below Average 20-40% probability of meeting the attribute

2 Average

RatingsDescription

5, 4 Excellent Over 80% probability of meeting or exceeding the attribute

Ratings

Ratio

3 Very Economical (< $0.09/kWh)

2 Affordable to majority ( $0.09 ≤ C ≤ $0.16/kWh)

1 Affordable to few ( $0.17 ≤ C ≤ $0.23/kWh)

0 Costly (> $0.23/kWh)

Description

Ratings

Ratio

2 Highly Efficient (>40% efficient)

1 Moderately Efficient (20-40% efficient)

0 Poor Efficiency (<20% efficient)

Description

Alternatives AT#1 AT#2 AT#3 AT#4 AT#5 AT#6 AT#7 AT#8 AT#9 AT#10 AT#11 AT#12

NF 0 0 0 0 0 1 0 0 3 2 1 0

OIL 2 0 2 2 1 3 3 3 1 5 5 3

COAL 1 0 1 5 3 3 2 3 3 3 3 3

NG 3 0 3 2 2 3 4 2 3 2 3 3

BM 3 3 2 2 0 1 2 2 3 1 1 1

Scale O-I O-I O-I O-I O-I O-I O-I O-I O-I O-I O-I O-I

Range 0-5 0-5 0-5 0-5 0-3 0-5 0-5 0-5 0-5 0-5 0-5 0-2

Units None None None None None None None None None None None None

AlternativesAT#1 AT#2 AT#3 AT#4 AT#5 AT#6 AT#7 AT#8 AT#9 AT#10AT#11AT#12

NF 0 0 0 0 0 0 0 0 1.000 0.25 0 0

OIL 0.667 0 0.667 0.400 0.333 1.000 0.750 1 0 1.000 1 1.000

COAL 0.333 0 0.333 1 1.000 1.000 0.500 1.000 1.000 0.500 0.500 1.000

NG 1 0 1 0.4 0.67 1 1 0.667 1 0.25 0.500 1.000

BM 1 1 0.67 0.400 0.000 0 0.5 0.667 1.000 0.000 0.000 0.333


Table 11 MERIT FUNCTION VALUES SYNTHESIS

STEP VI

Table 12 MERIT FUNCTION VALUES AND FINAL RANKING (WITH HIGHER NUMBER PREFERENCE)

2.4 Sensitivity Analysis Table 13 is produced by changing the weights from one region

to another and it can be observed that changing the weight drastically

change the result. In Table 13a, oil comes out to be the bridging fuel

when the weight is on Socio- cultural and the runner up is natural gas

which is closely followed by coal. Thus a sensitivity analysis is done

by increasing and decreasing the relative importances of the attributes

but still oil come out to be the winner when the weight is on socio-

cultural. Similarly in Table 13 b and c, coal comes as winner when

weight is on economy and natural gas comes out to be the winner

when ecology is given more weight. Even after sensitivity analysis

each winner stands on their positions firmly.

Table 13 SENSITIVITY ANALYSIS a) Weight on Socio-cultural

b) Weight on Economy

c) Weight on Ecology

3 RESULTS

The result of Preliminary Selection DSP and Selection DSP is

given in the following sections

3.1 Preliminary Selection The graph below is produced based on the two Tables 2 and 3.

Table 2 is a weight table where, for a particular scenario, one of the

generalized criteria is considered more important than the others. In

scenario one, that is Environmental; in scenario two it is Economical,

and so on. In Scenario 5, a staggered weighting is given rather than a

single, overriding criteria.

Figure 5 GRAPHICAL REPRESENTATIONS OF PRELIMI-NARY SELECTION SCORE

In Table 3, we determined the total normalized score for each

alternative and, further, for each scenario. The equation to determine

the different scores is given in a general form in the table as well.

From the synthesis of the five preliminary scenarios, natural gas

was determined to be the bridging fuel with the most potential to

succeed. From Figure 5, it can be seen that natural gas is at the top of

the rankings in four of the five scenarios. The runner-up is coal

which remained fairly consistent through each scenario and is the top

choice in Scenario 2 when natural gas came in second.

An interesting result is illustrated in Figure 5, nuclear power is

deemed the most likely to fail as a bridging fuel. We realize that this

is not a section-ending selection method and that a true selection

process is required to determine the best option for a bridging fuel.

3.2 Selection Process

In selection process we considered all of the possible scenarios

by shifting weight from one region to another and came to the

understanding that shifting weights changes the outcome also. In

Table 13a it is seen that oil comes as winner when weight is more on

the socio-cultural. Similarly in Table 13b and Table 13c, coal comes

as winner when weight is more on economy and natural gas comes as

Alternatives AT#1 AT#2 AT#3 AT#4AT#5AT#6AT#7 AT#8 AT#9 AT#10AT#11AT#12

Relative

Importance:0.15385 0.07692 0.141026 0.13 0.05 0.09 0.1 0.01 0.12 0.06 0.03 0.04

NF 0 0 0 0 0 0 0 0 0.12 0.02 0 0

OIL 0.10256 0 0.094017 0.05 0.02 0.09 0.08 0.01 0 0.06 0.03 0.04

COAL 0.05128 0 0.047009 0.13 0.05 0.09 0.05 0.01 0.12 0.03 0.01 0.04

NG 0.15385 0 0.141026 0.05 0.03 0.09 0.1 0.01 0.12 0.02 0.01 0.04

BM 0.15385 0.07692 0.094017 0.05 0 0 0.05 0.01 0.12 0 0 0.01

NF 0.1314 0.1380 0.1248

OIL 0.5726 0.6013 0.5440

COAL 0.6303 0.6619 0.5988

NG 0.7639 0.8021 0.7257

BM 0.5641 0.5923 0.5359

Merit

Function

Value

AlternativesIncrease

5%

Decrease

5%

Alternatives

Merit

Function

Value

AT1 -5%

AT8 +5%

AT3 -5%

AT12 +5%

AT4 -5%

AT5 +5%

AT9 -5%

AT10 +5%

AT7 -5%

AT2 +5%

NF 0.0641 0.0641 0.0641 0.0641 0.0647 0.0641

OIL 0.8120 0.8158 0.8165 0.8109 0.8197 0.8081

COAL 0.6731 0.6782 0.6782 0.6705 0.6756 0.6705

NG 0.6774 0.6778 0.6812 0.6765 0.6780 0.6722

BM 0.3803 0.3808 0.3810 0.3791 0.3791 0.3803

Alternatives

Merit

Function

Value

AT1 -5%

AT8 +5%

AT3 -5%

AT12 +5%

AT4 -5%

AT5 +5%

AT9 -5%

AT10 +5%

AT7 -5%

AT2 +5%

NF 0.1314 0.1314 0.1314 0.1314 0.1264 0.1314

OIL 0.6299 0.6359 0.6312 0.6292 0.6331 0.6261

COAL 0.8184 0.8246 0.8203 0.8177 0.8142 0.8158

NG 0.7058 0.7094 0.7064 0.7074 0.7008 0.7006

BM 0.3949 0.3985 0.3944 0.3918 0.3891 0.3936

Alternatives

Merit

Function

Value

AT1 -5%

AT8 +5%

AT3 -5%

AT12 +5%

AT4 -5%

AT5 +5%

AT9 -5%

AT10 +5%

AT7 -5%

AT2 +5%

NF 0.1314 0.1314 0.1314 0.1314 0.1264 0.1314

OIL 0.5726 0.5682 0.5699 0.5709 0.5759 0.5688

COAL 0.6303 0.6284 0.6299 0.6265 0.6262 0.6278

NG 0.7639 0.7566 0.7588 0.7630 0.7589 0.7588

BM 0.5641 0.5568 0.5600 0.5615 0.5583 0.5654


winner when weight is more on ecology respectively. So it can be

inferred form Table 13 that which fuel is to be selected based on

which region we want to prioritize.

4 DILEMMA MANAGEMENT In the last sections, the dilemmas associated to critical regions to be

managed are presented, and a numerical approach for selecting a

bridging fuel is shown. In this section, we explain and discuss how

the approach for selecting the bridging fuel effectively manages the

dilemmas we are faced with.

4.1 Effectiveness of the Approach In this subsection, it is explained how our approach for selecting

a bridging fuel effectively result in a balanced satisfaction of our

different goals with different relative importance.

The objective of the dilemma management problem is: To

find the alternative that is satisficing to our conflicting objectives

with our different emphasis. The alternative should be selected

according to the relative importance of the requirements as well

as the ability of the alternatives to satisfy the requirements. The

approach should be one such that alternative that has more

strength against the requirement that we put more emphasis on

has more likelihood to win. In Section 1.1, we described the

concept of dilemma and used the method shown in Ref. [3] to

identify dilemmas.

In Section 2, we find by preliminary selection DSP that natural

gas is the bridging fuel In preliminary selection, the general

performance of the alternative bridging fuels in each region is

considered. The way that the scores for each fuel are calculated is

shown on the top of Table 2. The nature of this calculating method

accounts for both the relative importance of the requirements in

sustainability prism and the performance of the alternative fuels in

each region.

In Table 2 the weights are shifted from one region to the other

and based on that total normalized score is shown in Table 3. From

Table 2 and 3, it can be seen that when the weight is on

environmental then the total score of natural gas is 0.867 and it is the

highest among other all other alternatives. Similarly in other

scenarios except economy, natural gas is the highest scorer 0.96, 0.88

and 0.96 when the weights are in social, engineering, economy and

engineering combined respectively. Only when the weight is on

economy, coal comes up as the bridging fuel by scoring 0.8 and

natural gas as runner up by scoring 0.75 which is slightly below than

that of coal.

In selection DSP different attributes are preferred over other ac-

cording to the weight put on the regions of socio-cultural, economy

and ecology. At this stage, by calculating the merit function it is

similar that alternative with more strength on requirement of more

emphasis are likely to have higher merit function value, and have

higher likelihood to win.

For example from Table 10 and Table 11 we see that NG has the

highest merit function value, this attributes to the fact that NG is

rated one of the highest among all the alternatives for attribute #1, #3

and #7, and these three attributes are the ones that have highest rela-

tive importance. At the same time, Oil has quite high score for attrib-

ute #11, but it doesn‟t get high merit function value, because attribute

#11 does not have high relative importance compared to others.

Now we change the relative importance of the requirements

which is to change weightages, When the weight is on socio-cultural

then Attribute 10 and Attribute 11 in Table 5 get the highest relative

importance 0.1538 and 0.141 respectively and as a result from Table

13a it can be seen that oil scores 0.812 which is the highest among

all. Attribute 10 refers to how much the fuel has the potential to meet

the demand scale of society and Attribute 11 refers to how much the

fuel is versatile, i.e., how wide is the fuel‟s applicability and

acceptance to society. Similarly in Table 5 when the weight is shifted

to economy and ecology, the relative importance of the attributes is

also shifted to Attribute 4, 5 and Attribute 1, 3 respectively. And in

the Table 13b and Table 13c, it can be seen that coal scores 0.8184

which is the highest and natural gas scores 0.7639 which is also the

highest respectively. A sensitivity analysis is done by increasing or

decreasing each of the relative importance of the attributes by 5

percent in Table 13 a, b and c to confirm the result. So, it is inferred

from different results from Table 13 a, b and c that oil should be the

bridging fuel when the socio-cultural is prioritized, coal should be the

bridging fuel when economy is prioritized and natural gas should be

the bridging fuel when ecology is prioritized.

Our focus is about selecting a bridging fuel which favors

sustainability system and hence natural gas is selected as bridging

fuel as it meets the ecology demands better than that of coal and oil.

4.2 How the Selected Bridging Fuel Manages the

Dilemmas In this section, we show how the bridging fuel, i.e., natural gas man-

ages each of the dilemmas listed previously by achieving tradeoffs

between conflicting objectives.

Ecology - Economic

1 The fuel should be such that it is environmental friendly and has

low lifecycle cost.

Here we have issues of being environmentally friendly and at

the same time low life cycle cost and as we are putting more weight

on ecology so natural gas manages the dilemma better than that of oil

and coal, as natural gas is more environmental friendly

2 The need to reduce the toxic waste of the fuel over the need to

decrease lifecycle cost.

Here the issues are about reducing toxic waste and also being

low lifecycle cost, and natural gas has less toxic waste than that of

coal, oil, biomass and nuclear fuel thus natural gas is better at manag-

ing this dilemma as well than any other sources

3 The need of the fuel to be renewable and also to be capable of

meeting huge public demand.

Here the issues are about being renewable and also being capa-

ble of meeting the public demand. Biomass is the only fuel source

that is renewable but it cannot meet the huge demands as good as

natural gas, coal and oil does

4 The need of the fuel to be environmentally friendly (Renewable

energy, like wind energy) over the need of the fuel to meet the

demand of geographically distributed customers.

Here one issue is about renewability and thus biomass is the best

option but the other issue is about meeting the need of geographically

distributed customers where oil, gas and coal are better than that of

biomass.

5 The need to consume less in order to preserve ecological system

over the need to improve the quality of life

Here issues of preserving ecological system and improving the

quality of life are mentioned and natural gas is better at managing this

dilemma than other because it has less carbon foot print than oil and

coal


6 The need of the fuel to meet the demand of public over the need

to reduce dependence on foreign oil.

Here issues about meeting public demand and also security

dependency. Only natural gas and coal can manage this dilemma as

oil increases security dependency though it has capability to meet

public demand and on the other hand biomass do not increase secu-

rity dependency but it lacks the capability to meet demands

7 The need to transit to new energy infrastructure based on domes-

tic/reliable fuel source (considering national security) over the

cost of transition.

Here the issues are about transiting to a new energy infrastruc-

ture which decreases security dependency and at the same time

considering the cost of it. Oil fails to manage this dilemma as it

increases security dependency but coal, natural gas and biomass all

have a fair chance

In the end if we combine the issues of all the regions i.e.,

ecological, social and economic together then the dilemmas is about a

need of a fuel which is environment friendly, decrease security

dependency, low life cycle cost and able to meet the public demand

at the same time. Oil does not manage the dilemma as it increases

security dependency and carbon foot print. Coal does not manage this

dilemma as it is not environment friendly though it is cheap and able

to meet the demand. Similarly, Biomass does not manage the dilem-

mas in spite being renewable because it is not capable of meeting

huge demand. So, the only other option left is natural gas and it has

the capability of managing the dilemmas better than any other and is

the bridging fuel.

From table 2 and table 3 we see, changing of weights of the

requirement regions lead to changing of winning bridging fuel. In

table 2 Scenario one, where the ecological requirements have the

highest weight, NG has the highest score, because NG has highest

score for the requirements related to environmental-friendliness. In

table 2 Scenario two, where economical requirements are dominant,

Coal has the highest score largely due to its high score on economical

criteria.

In Selection, after some good alternatives have stood out, we go with

more information to identify the relative importance of each require-

ment, instead of general requirements in each region in the

sustainability prism, and we identify the relative strength of each

alternative over each requirement respectively. At this stage, by

calculating the merit function it is similar that alternative with more

strength on requirement of more emphasis are likely to have higher

merit function value, and have higher likelihood to win.

5. LEARNING STATEMENTS By taking the course Designing for Open Innovation, we

Salman and Minting have learned many lessons. We have leveraged

our work from AME5740 in this paper to present an approach for

selecting a bridging fuel and an approach about how to manage

dilemmas. We have faced a lot of challenges in connecting the dots

that were presented in the course and coming up with whitespaces to

write this paper. Some challenges that we faced in writing this paper

is as follows-

We are challenged when we are facing a quite open question to

answer, and to search for an approach to answer it.

We are challenged to make connections of part of our work done

in the course Design for Open Innovation to abstract it to

another work.

We are challenged to make associated creation based on our

existing knowledge and methods

We are challenged to properly organize our knowledge in a

connected way and convey our ideas so others can understand.

is summarizing the work of the whole

The classes of the Course AME5740 continued only for one

semester but the lessons we, Salman and Minting, learned from this

course has and will continue to have effect on us for the rest of our

life. So, we present some learning statements that we find most

valuable. The course has been offered in both individual and in group

setting so the learning statements are divided into Team Learning and

Individual Learning. This section concludes our learning in the

context of this course.

Team Learning

We (Salman and Minting) learned where to go when faced of a

quite open question. We learned to speculate on the current and

future to identify holes and make evaluations with scaffolding.

In this way continue learning takes place.

We (Salman and Minting) learned how to use different domains

of knowledge in Bloom‟s Taxonomy to reflect on the existing

knowledge and on this basis make associated creation of new

knowledge.

We (Salman and Minting) learned that Learning Organization

works smoothly and becomes very powerful in achieving things

when everyone knows everyone‟s strength and weakness and

this can be done by sharing background, competencies and

learning objects

We (Salman and Minting) learned through working in a

collaborative environment that how people have different

strength and pay attention to different parts of a same thing, thus

distribution of task should be done according to the mental

model of individuals.

We (Salman and Minting) learned that Learning organization‟s

success depend on each and every one of the members through

what does not work out in our learning organization.

We (Salman and Minting) learned that A strong team contract is

important and it can be done by explicitly specifying the amount

of work each member should do, along with a hard dead line.

We (Salman and Minting) learned that While working in a

culturally diverse group with people of different backgrounds,

then ideas from different perspectives rather than a single is put

on the table and a fusion of those ideas are the one that are most

likely to succeed.

We (Salman and Minting) become aware of how to deal with

dilemmas that we are facing with, to minimize loss in the con-

text of a complex ecology-social-economy system in a G3

world.

Individual Learning

I (Salman) learned that learning is a conscious activity and it

starts when someone knows what he does not know and has a

desire to learn.

I (Salman) learned that the advent of G3 has made the world flat

because of the emergence of cheap computer and cheap internet

connection.

I (Salman) learned that the world seldom provides solution to

problems; it provides dilemmas i.e., offering two possibilities

where neither of them is feasible.

I (Salman) learned that environment, society and economy

dilemmas should be considered while designing a product for

sustainability and technology can help us to achieve it.

I (Salman) learned speculating the future and finding white

spaces is very important

I (Salman) learned self-evaluation and continuous improvement

is necessary to be successful.


I (Minting) learned how powerful a sharing-to-gain environment

can be if people work in a learning organization to achieve

things.

I (Minting) become aware of the challenges that are possible to

come when working in G3 world and have started thinking on

how to improve working in it. By working with people from

different culture and education background with different gen-

der, and even from geographically far away,

I (Minting) learned how continuous learning works. I learned to

take on responsibility of my own learning by starting from

identifying what to learn and on this bases to find out how to

learn by using different levels of cognitive learning in Bloom‟s

Taxonomy.

Through these student learning statements, the instructors

(Mistree and Panchal) able to gain confidence in their

hypothesis that using the notion of dilemmas as the core of the

graduate level design course is helpful in getting the students

to think in terms of broader system-level challenges necessary

for the 12st century rather than merely focusing on specific

methods and tools for designing technical systems.

6 CLOSURE In this paper we have drawn a boundary for finding the

dilemmas among ecological, social and economic regions

associated with fuel sources that power the current world and

have presented an approach on how to select bridging fuel. We

have also developed an approach on how to manage dilemmas

to achieve sustainability. In the dilemma management process

we have identified the crucial steps that are needed to analyze

and then synthesize a decision on how to manage dilemmas.

In the selection DSP process, we have focused on the ap-

proach of selecting a bridging fuel rather than finding the

bridging fuel itself thus the result obtained may not necessarily

reflect the best bridging fuel. The final decisions made in the

selection approaches are based on intuition after reflecting

corresponding hard information. However, we believe that

using more hard information and reflection, a bridging fuel

can be selected by using the approach presented in the paper.

The effectiveness of dilemma managing of this selection DSP

technique comes from its nature that requirements with differ-

ent preference and bridging fuels with different strength and

weakness against different criteria are considered. It is also

explained that how the result of the selection in this paper –

natural gas, with its characteristics, verifies that this approach

is effective.

This paper is part of the work done through this course in

a learning organization. The four papers in this series demon-

strates that we are in a bigger learning organization consisting

of sharing-to-gain between different inter-university that is

able to make comprehensive achievement At the same time,

each group is also a learning organization in which we learn

together and achieve things.

Our learning throughout the course as both learning

organization and individual are summarized in the end of the

paper. Here how the core competencies proposed in Refs. 1

and 2 are developed in the part of work that is associated to

this paper is explained.

Throughout the work in the Learning Organization, we

have gained the ability to identify the competencies and meta-

competencies we need to develop to be successful at creating

value in a culturally diverse, distributed engineering world.

This determines where we go in learning. By using different

domains of knowledge in the Bloom‟s Taxonomy to reflect on

an approach to manage the dilemmas, we think a lot on the

most critical issues in the current world, and seek for the prob-

lems that will be faced now and in the near future. This helps

us to develop some of the competencies we proposed. The

thinking on the nature of the dilemmas and an approach of

managing the dilemmas proves that we have developed

competency to manage the dilemmas associated with complex

sustainable systems to a large extent. In this paper we come up

with an approach for the problem that we are newly faced with

by reflecting and associated creation of knowledge, and

learned to articulate it.

Comment: We have run out of time. We recognize that this

paper needs quite a bit of editorial work. If accepted we

commit to fixing the paper to meet the expected standards for

this conference. Farrokh Mistree and Jitesh Panchal

ACKNOWLEDGEMENTS This paper evolves from the core concept of Technology

Prism which was offered in the AME5740 Designing for Open

Innovation in Fall 2011. The Preliminary Selection and

Selection DSP were originally used by Team Gamma to select

the bridging fuel in partial completion of Assignment 4 and

Assignment 6. The Team Gamma consists of Isaac Burbank,

Ryan Drobny and Vignesh Venkat from WSU and Brian

Chapman and Andrew Kooiman form OU along with the first

two authors of this paper.

REFERENCES 1. Siddique, Z., Panchal, J.H., Schaefer, D., Allen, J.K. and

Mistree, F., 2012, "Competencies for Innovating in the 21st

Century," ASME International Conference on Design

Education, Chicago, IL. Paper Number: DETC2012-71170.

2. Hawthorne, B., Sha, Z., Panchal, J.H. and Mistree, F., 2012,

"Developing Competencies in the 21st Century Engineer,"

ASME International Conference on Design Education, Chicago,

IL. Paper Number: DETC2012-71153.

3. Bertus, C., Khosrojerdi, A., Panchal, J.H., Allen, J.K. and

Mistree, F., 2012, "Identifying Dilemmas Embodied in 21st

Century Engineering," ASME International Conference on

Design Education, Chicago, IL. Paper Number: DETC2012-

71163.

4. Roman, F., Rolander, N., Fernández, M.G., Bras, B, Allen, J.K.,

Mistree, F., Chastang, P. Depince, P., and Bennis, F, 2004,.

"Selection Without Reflection is a Risky Business...,”

AIAA/ISSMO Multidisciplinary Analysis and Optimization

Conference, Albany, NY. Paper Number AIAA-2004-4429.

5. Hazelrigg, G. A., 2003, “Validation of Engineering Design

Alternative Selection Methods,” Engineering Optimization, Vol.

35, No. 2, pp. pp. 103-120.

6. Mistree, F., Lewis, K. and Stonis, L., “Selection in the

Conceptual Design of Aircraft,” AIAA/NASA/USAF/ISSMO

Symposium on Multidisciplinary Analysis and Optimization,

Panama City, Florida, September 7-9, 1994, 1153-1166. Paper

No. AIAA-94-4382-CP

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