Although energy consumption during product use can lead to significant environmental impacts, the relationship between a product's usage context and its environmental performance is rarely considered in design evaluations. Traditional analyses rely on broad, average usage conditions and do not differentiate between contexts for which design decisions are highly beneficial and contexts for which the same decision may offer limited benefits or even penalties in terms of environmental performance. In contrast, probabilistic graphical models (PGMs) provide the capability of modeling usage contexts as variable factors. This research demonstrates a method for representing the usage context as a PGM and illustrates it with a lightweight vehicle design example. Factors such as driver behavior, alternative driving schedules, and residential density are connected by conditional probability distributions derived from publicly available data sources. Unique scenarios are then defined as sets of conditions on these factors to provide insight into sources of variability in lifetime energy use. The vehicle example demonstrates that implementation of realistic usage scenarios via a PGM can provide a much higher fidelity investigation of use stage energy savings than commonly found in the literature and that, even in the case of a universally beneficial design decisions, distinct scenarios can have significantly different implications for the effectiveness of lightweight vehicle designs.

References

References
1.
Telenko
,
C.
,
2012
, “
Probabilistic Graphical Modeling as a Use Stage Inventory Method for Environmentally Conscious Design
,” Ph.D. thesis, The University of Texas at Austin, Austin, TX.
2.
Baumers
,
M.
,
Tuck
,
C.
,
Wildman
,
R.
,
Ashcroft
,
I.
, and
Hague
,
R.
,
2011
, “
Energy Inputs to Additive Manufacturing: Does Capacity Utilization Matter?
,”
Proceedings of the 2011 Solid Freeform Fabrication Symposium
, Austin, TX, The University of Texas at Austin, pp.
30
40
.
3.
Telenko
,
C.
, and
Seepersad
,
C. C.
,
2010
, “
A Methodology for Identifying Environmentally Conscious Guidelines for Product Design
,”
ASME J. Mech. Des.
,
132
(
9
), p. 091009.10.1115/1.4002145
4.
Reap
,
J.
,
Roman
,
F.
,
Duncan
,
S.
, and
Bras
,
B.
,
2008
, “
A Survey of Unresolved Problems in Life Cycle Assessment, Part 1: Goal and Scope and Inventory Analysis
,”
Int. J. Life Cycle Assess.
,
13
(
4
), pp.
290
300
.10.1007/s11367-008-0008-x
5.
Reap
,
J.
,
Roman
,
F.
,
Duncan
,
S.
, and
Bras
,
B.
,
2008
, “
A Survey of Unresolved Problems in Life Cycle Assessment, Part 2: Impact Assessment and Interpretation
,”
Int. J. Life Cycle Assess.
,
13
(
5
), pp.
374
388
.10.1007/s11367-008-0009-9
6.
Finnveden
,
G.
,
2000
, “
On the Limitations of Life Cycle Assessment and Environmental Systems Analysis Tools in General
,”
Int. J. Life Cycle Assess.
,
5
(
4
), pp.
229
238
.10.1007/BF02979365
7.
Du
,
X.
, and
Chen
,
W.
,
2002
, “
Efficient Uncertainty Analysis Methods for Multidisciplinary Robust Design
,”
AIAA J.
,
40
(
3
), pp.
545
552
.10.2514/2.1681
8.
Lloyd
,
S. M.
, and
Ries
,
R.
,
2007
, “
Characterizing, Propagating, and Analyzing Uncertainty in Life-Cycle Assessment: A Survey of Quantitative Approaches
,”
J. Ind. Ecol.
,
11
(
1
), pp.
161
179
.10.1162/jiec.2007.1136
9.
Allen
,
J. K.
,
Seepersad
,
C.
,
Choi
,
H.
, and
Mistree
,
F.
,
2006
, “
Robust Design for Multiscale and Multidisciplinary Applications
,”
ASME J. Mech. Des.
,
128
(
4
), pp. 832–843.10.1115/1.2202880
10.
Björklund
,
A. E.
,
2002
, “
Survey of Approaches to Improve Reliability in LCA
,”
Int. J. Life Cycle Assess.
,
7
(
2
), pp.
64
72
.10.1007/BF02978849
11.
He
,
L.
,
Chen
,
W.
,
Hoyle
,
C.
, and
Yannou
,
B.
,
2012
, “
Choice Modeling for Usage Context-Based Design
,”
ASME J. Mech. Des.
,
134
(
3
), p. 031007.10.1115/1.4005860
12.
Yannou
,
B.
,
Wang
,
J.
, and
Yvars
,
P.-A.
,
2010
, “
Computation of the Usage Contexts Coverage of a Jigsaw With CSP Techniques
,”
Proceedings of the ASME 2010 International Design Engineering Technical Conferences & Computer and Information in Engineering Conference
, Montreal, Quebec, Aug. 15–18, Paper No. DETC2010–28677.
13.
Yannou
,
B.
,
Yvars
,
P.-A.
,
Hoyle
,
C.
, and
Chen
,
W.
,
2013
, “
Set-Based Design by Simulation of Usage Scenario Coverage
,”
J. Eng. Des.
,
24
(
8
), pp.
575
603
.10.1080/09544828.2013.780201
14.
Koller
,
D.
, and
Friedman
,
N.
,
2009
,
Probabilistic Graphical Models: Principles and Techniques
,
MIT
,
Cambridge
, MA.
15.
Peffer
,
T.
,
Pritoni
,
M.
,
Meier
,
A.
,
Aragon
,
C.
, and
Perry
,
D.
,
2011
, “
How People Use Thermostats in Homes: A Review
,”
Build. Environ.
,
46
(
12
), pp.
2529
2541
.10.1016/j.buildenv.2011.06.002
16.
Shipworth
,
D.
,
2006
, “
Qualitative Modeling of Sustainable Energy scenarios: an Extension of the Bon Qualitative Input–Output Model
,”
Constr. Manag. Econ.
,
24
(
7
), pp.
695
703
.10.1080/01446190600658917
17.
Lomas
,
K.
,
Oreszczyn
,
T.
, and
Shipworth
,
D.
,
2006
, “
Carbon Reduction in Buildings (CaRB): Understanding the Social and Technical Factors that Influence Energy Use in UK Buildings
,”
Proceedings of the Annual Research Conference of the Royal Institution of Chartered Surveyors
, London, UK, Sept. 7–8.
18.
Olivier
,
C.
,
2008
, “
Modeling UK Home Energy Use Using Bayesian Networks Documentation and Experiments
,” Online, accessed: Dec. 2012, ofrancois.tuxfamily.org/carb/
19.
Shipworth
,
M.
,
Firth
,
S. K.
,
Gentry
,
M. I.
,
Wright
,
A. J.
,
Shipworth
,
D. T.
, and
Lomas
,
K. J.
,
2010
, “
Central Heating Thermostat Settings and Timing: Building Demographics
,”
Build. Res. Inf.
,
38
(
1
), pp.
50
69
.10.1080/09613210903263007
20.
Moullec
,
M.-L.
,
Bouissou
,
M.
,
Jankovic
,
M.
,
Bocquet
,
J.-C.
,
Réquillard
,
F.
,
Maas
,
O.
, and
Forgeot
,
O.
,
2013
, “
Toward System Architecture Generation and Performances Assessment Under Uncertainty Using Bayesian Networks
,”
ASME J. Mech. Des.
,
135
(
4
), p. 041002.10.1115/1.4023514
21.
Shahan
,
D. W.
, and
Seepersad
,
C. C.
,
2012
, “
Bayesian Network Classifiers for Set-Based Collaborative Design
,”
ASME J. Mech. Des.
,
134
(
7
), p. 071001.10.1115/1.4006323
22.
Matthews
,
P. C.
,
2010
, “
Challenges to Bayesian Decision Support Using Morphological Matrices for Design: Empirical Evidence
,”
Res. Eng. Des.
,
22
(
1
), pp.
29
42
.10.1007/s00163-010-0094-1
23.
Varis
,
O.
,
1997
, “
Bayesian Decision Analysis for Environmental and Resource Management
,”
Environ. Modell. Software
,
12
(
2–3
), pp.
177
185
.10.1016/S1364-8152(97)00008-X
24.
Zhu
,
J.
, and
Deshmukh
,
A.
,
2003
, “
Application of Bayesian Decision Networks to Life Cycle Engineering in Green Design and Manufacturing
,”
Eng. Appl. Artif. Intell.
,
16
(
2
), pp.
91
103
.10.1016/S0952-1976(03)00057-5
25.
Seo
,
K.
,
Min
,
S.
, and
Yoo
,
H.
,
2005
, “
Artificial Neural Network Based Life Cycle Assessment Model for Product Concepts using Product Classification Method
,”
International Conference on Computational Science and Its Applications
, Springer-Verlag, Singapore, Singapore, pp.
458
466
.
26.
Pacheco
,
J. E.
,
Amon
,
C. H.
, and
Finger
,
S.
,
2003
, “
Bayesian Surrogates Applied to Conceptual Stages of the Engineering Design Process
,”
ASME J. Mech. Des.
,
125
(
4
), pp. 664–672.10.1115/1.1631580
27.
Wang
,
P.
,
Kloess
,
A.
,
Youn
,
B. D.
, and
Xi
,
Z.
,
2009
, “
Bayesian Reliability Analysis With Evolving, Insufficient, and Subjective Data Sets
,”
ASME J. Mech. Des.
,
131
(
11
), p. 111008.10.1115/1.4000251
28.
Du
,
X.
,
Sudjianto
,
A.
, and
Huang
,
B.
,
2005
, “
Reliability-Based Design With the Mixture of Random and Interval Variables
,”
ASME J. Mech. Des.
,
127
(
6
), pp. 1068–1076.10.1115/1.1992510
29.
Gunawan
,
S.
, and
Papalambros
,
P. Y.
,
2006
, “
A Bayesian Approach to Reliability-Based Optimization With Incomplete Information
,”
ASME J. Mech. Des.
,
128
(
4
), pp.
909
918
.10.1115/1.2204969
30.
Matthews
,
P. C.
, and
Philip
,
A. D. M.
,
2012
, “
Bayesian Project Diagnosis for the Construction Design Process
,”
Artif. Intell. Eng. Des. Anal. Manuf.
,
26
(
04
), pp.
375
391
.10.1017/S089006041200025X
31.
Youn
,
B. D.
,
Hu
,
C.
, and
Wang
,
P.
,
2011
, “
Resilience-Driven System Design of Complex Engineered Systems
,”
ASME J. Mech. Des.
,
133
(
10
), p. 101011.10.1115/1.4004981
32.
Jensen
,
F. V.
,
Kj
,
U.
,
Kristiansen
,
B.
,
Langseth
,
H.
,
Skaanning
,
C.
,
Vomlelov
,
M.
,
Kjærulff
,
U.
,
Vomlel
,
Í.
, and
Vomlelová
,
M.
,
2001
, “
The SACSO Methodology for Troubleshooting Complex Systems the SACSO Methodology for Troubleshooting Complex Systems
,”
Artif. Intell. Eng. Des. Anal. Manuf.
,
15
(
4
), pp.
321
333
.10.1017/S0890060401154065
33.
Chen
,
W.
,
Tsui
,
K.-L.
,
Wang
,
S.
, and
Xiong
,
Y.
,
2007
, “
A Design-Driven Validation Approach Using Bayesian Prediction Models
,”
ASME J. Mech. Des.
,
130
(
2
), p. 021101.10.1115/1.2809439
34.
Martin
,
J. D.
, and
Simpson
,
T. W.
,
2006
, “
A Methodology to Manage System-Level Uncertainty During Conceptual Design
,”
ASME J. Mech. Des.
,
128
(
4
), pp. 959–968.10.1115/1.2204975
35.
Sha
,
Z.
, and
Panchal
,
J. H.
,
2014
, “
Estimating Local Decision-Making Behavior in Complex Evolutionary Systems
,”
ASME J. Mech. Des.
,
136
(
6
), p. 061003.10.1115/1.4026823
36.
Takai
,
S.
, and
Ishii
,
K.
,
2008
, “
A Decision-Analytic System Concept Selection for a Public Project
,”
ASME J. Mech. Des.
,
130
(
11
), p. 111101.10.1115/1.2976455
37.
Takai
,
S.
,
Yang
,
T. G.
, and
Cafeo
,
J. A.
,
2010
, “
A Bayesian Framework for Predicting Customer Need Distributions
,”
Proceedings of the ASME 2010 International Design Engineering Technical Conferences & Computer and Information in Engineering Conference
, Montreal, Quebec, Aug. 15–18, Paper No. DETC2010-28230.
38.
Yannou
,
B.
,
Jankovic
,
M.
,
Leroy
,
Y.
, and
Okudan Kremer
,
G. E.
,
2013
, “
Observations From Radical Innovation Projects Considering the Company Context
,”
ASME J. Mech. Des.
,
135
(
2
), p. 021005.10.1115/1.4023150
39.
Telenko
,
C.
, and
Seepersad
,
C. C.
,
2012
, “
Probabilistic Graphical Models as Tools for Evaluating the Impact of Usage Context on the Environmental Performance of Products
,”
Proceedings of the ASME 2012 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference
, Chicago, IL, Aug. 12–15, Paper No. DETC2012–71160.
40.
Thomas
,
A.
,
Spiegelhalter
,
D.
,
Best
,
N.
,
Lunn
,
D.
, and
Rice
,
K.
,
2012
, “
OpenBUGS
,” GNU Gen. Public Licens. version 2 accessed: Dec. 2012. Available at: http://www.openbugs.info/w/
41.
Gelman
,
A.
,
2003
,
Bayesian Data Analysis
,
Chapman & Hall/CRC
,
London
, UK.
42.
Peter
,
J.
,
2004
, “
Lightweight Champion
,”
Automot. Ind.
,
184
(
4
), pp.
27
28
.
43.
Davies
,
G.
,
2003
,
Materials for Automobile Bodies
,
Butterworth-Heinemann, Elsevier, Ltd.
,
Burlington, MA
.
44.
Neil
,
M.
,
Fenton
,
N.
, and
Nielson
,
L.
,
2000
, “
Building Large-Scale Bayesian Networks
,”
Knowl. Eng. Rev.
,
15
(
03
), pp.
257
284
.10.1017/S0269888900003039
45.
Phadke
,
M. S.
,
1989
,
Quality Engineering Using Robust Design
,
Prentice Hall
,
Englewood Cliffs, NJ
.
46.
Wood
,
K. L.
, and
Otto
,
K. N.
,
2001
,
Product Design: Techniques in Reverse Engineering and New Product Development
,
Prentice Hall
,
Upper Saddle River, NJ
.
47.
Steven
,
D.
, and
Eppinger
,
T. R. B.
,
2012
,
Design Structure Matrix Methods and Applications
,
MIT
,
Cambridge, MA
.
48.
Illinois Department of Transportation,
2012
, “
Bureau of Design and Environment Manual
.” Available at: http://dot.state.il.us/desenv/BDEManual/BDE/pdf/Cover.pdf
49.
Davis
,
S. C.
,
Diegel
,
S. W.
, and
Boundy
,
R. G.
,
2010
,
The Transportation Energy Data Book
,
Oak Ridge National Laboratory
,
Oak Ridge, TN
.
50.
Bureau of Transportation Statistics,
2010
, “
Table 1-41: Principal Means of Transportation to Work
,” National Transportation Statistics, Online; accessed: Dec
2012
. Available at: http://www.bts.gov/publications/national_transportation_statistics/html/table_01_41.html
51.
United States Census Bureau,
2010
, “
2010 Census Urban and Rural Classification and Urban Area Criteria
,” Online; accessed: Dec 2012. Available at: http://www.census.gov/geo/www/ua/2010urbanruralclass.html
52.
United States Census Bureau,
2012
, “
Table AVG1: Average Number of People per Household, by Race and Hispanic origin, Marital Status, Age, and Education of Households: 2012
,” Online accessed: Dec 2012. Available at: www.census.gov/hhes/families/data/cps2012.html
53.
McDowell
,
M.
,
Fryar
,
C.
,
Ogden
,
C.
, and
Flegal
,
K.
,
2008
, “
Anthropometric Reference Data for Children and Adults: United States, 2003–2006
,” National Health Statistics Reports, U.S. Department of Health and Human Services.
54.
Oak Ridge National Laboratory,
2009
, “
Table Designer
,” National Household Transportation Surv, Online: accessed: Dec. 2012, http://nhts.ornl.gov/tools.shtml
55.
United States Environmental Protection Agency,
2012
, “
Dynamometer Drive Schedules
,” online; accessed: Dec. 2012. Available at: www.epa.gov/nvfel/testing/dynamometer.htm
56.
United States Environmental Protection Agency, and Environmental Protection Agency,
2006
, “
Fuel Economy Labeling of Motor Vehicles: Revisions to Improve Calculation of Fuel Economy Estimates
,”
Fed. Regist.
,
71
(
248
), pp.
77872
77969
.
57.
Ross
,
M.
,
1997
, “
Fuel Efficiency and the Physics of Automobiles
,”
Contemp. Phys.
,
38
(
6
), pp.
37
41
.10.1080/001075197182199
58.
Office of Highway Policy Information,
2010
, “
Table VM-2: Vehicle-Miles of Travel, by Functional System
,” Highway Statistics 2010, accessed: Dec. 2012. Available at: http://www.fhwa.dot.gov/policyinformation/statistics/2010/vm2.cfm
59.
U.S. Department of Energy,
2012
, “
Real-World MPG Estimates: 2004 Chevrolet Malibu Maxx
,” FuelEconmoy.gov accessed: Dec. 2012. Available at: http://www.fueleconomy.gov/feg/Find.do?action=yourMpgVehicle&id=19838
60.
Larsson
,
H.
, and
Ericsson
,
E.
,
2009
, “
The Effects of an Acceleration Advisory Tool in Vehicles for Reduced Fuel Consumption and Emissions
,”
Transp. Res. Part D Transp. Environ.
,
14
(
2
), pp.
141
146
.10.1016/j.trd.2008.11.004
61.
Berry
,
I. M.
,
2010
, “
The Effects of Driving Style and Vehicle Performance on the Real-World Fuel Consumption of U.S. Light-Duty Vehicles
,” Ph.D. thesis, Massachusetts Institute of Technology, Cambridge, MA.
62.
Bjelkengren
,
C.
,
2008
, “
The Impact of Mass Decompounding on Assessing the Value of Vehicle Lightweighting
,” Ph.D. thesis, Massachusettes Institute of Technology, Cambridge, MA.
63.
Office of Highway Policy Information,
2010
, “
State Motor Vehicle Registrations
,” Highway Statistics 2010, accessed Dec. 2012. Available at: http://www.fhwa.dot.gov/policyinformation/statistics/2010/mv1.cfm
64.
Greene
,
D. L.
,
Goeltz
,
R.
,
Hopson
,
J.
, and
Tworek
,
E.
,
2006
, “
Analysis of In-Use Fuel Economy Shortfall by Means of Voluntarily Reported Fuel Economy Estimates
,”
Transp. Res. Rec.
,
1983
, pp.
99
105
.10.3141/1983-14
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