California   Polytechnic   State   University,   San   Luis   Obispo
College   of   Architecture   and   Environmental   Design
Project   10,   Number   3   November   2010
Determining   Multidiscipline   Time ‐ Space   Relationships   for   Building   Information
Modeling   of   Mechanical,   Electrical,   and   Plumbing   Systems   (MEP)   Systems
Thomas   M.
Korman,   Ph.D,   PE,   PLS
Associate   Professor
Department   of   Construction   Management   tkorman@calpoly.edu
Summary
The   recent   introduction   of   BIM   software   solutions   is   able   to   provide   a   virtual   construction   solution,   which   includes   the   following   elements:   design   (3 ‐ D),   scheduling   (4 ‐ D),   cost   (5 ‐ D)   and   life ‐ cycle   (6 ‐ D).
These   elements   can   be   interlinked;   however,   practitioners   still   face   similar   problems   as   they   have   in   the   past.
Entry   of   incorrect   data   or   faulty   assumptions   into   the   BIM   system   results   in   project   personnel   being   misled   by   the   output   from   the   system.
While   most   BIM   software   solution   have   the   ability   to   contain   information   and   data   regarding   a   project,   they   do   not   contain   knowledge ‐ based   logic   and   reasoning   structures   to   assist   users   during   the   planning   and   design   and   therefore   lack   the   capability   to   assist   in   the   resolution   of   time ‐ space   conflicts.
To   be   able   to   fully   realize   to   the   potential   of   BIM   software   solutions   in   the   future,   knowledge   capture   and   the   integration   of   logic   and   reasoning   structures   is   imperative.
As   stated   above,   by   using   BIM   software   solutions,   the   determination   of   physical   interferences   has   become   a   mundane   task.
BIM   software   solutions   are   able   to   contain   scheduling   (4 ‐ D)   data   and   link   it   with   the   geometric   model.
The   research   funded   by   the   PDCI   assisted   me   to   devote   the   necessary   time   to   collect   the   data   needed   to   prepare   an   improved   proposal   to   submit
to   NSF   under   the   Research   for   Undergraduate   Institutions   (RUI)   grant   program.
This   involved   identifying   and   classifying   time ‐ space   relationships   for   MEP   systems   and   developing   a   preliminary   theory   for   a   logic
and   reasoning   structure   to   assist   with   the   project   scheduling   of   MEP   systems   in   BIM

Table   of   Contents
Executive   Summary......................................................................................................................... 1
NSF   Grant   Application..................................................................................................................... 3
Project   Summary ......................................................................................................................... 3
Project   Description ...................................................................................................................... 4
Background,   Motivation,   and   Point   of   Departure   for   the   Research ...................................... 4
Research   Questions ................................................................................................................ 9
Research   Objectives.............................................................................................................. 10
Research   Methodology.............................................................................................................. 10
Knowledge   acquisition.......................................................................................................... 10
Knowledge   representation ................................................................................................... 11
Building   reasoning   structures ............................................................................................... 12
Methodology   Example.......................................................................................................... 14
Project   Work   Plan ...................................................................................................................... 16
Year   1   –   Data   Acquisition,   Identification,   and   Analysis ........................................................ 16
Year   2   –   Prototype   Tool   Development,   Testing,   and   Validation .......................................... 17
Year   3   –   Development   of   Teaching   Modules   and   Dissemination......................................... 17
Significance   and   Impact   of   the   Research................................................................................... 18
Intellectual   Merit .................................................................................................................. 18
Broader   Impacts.................................................................................................................... 18
Educational   and   Outreach   Activities..................................................................................... 19
Appendix   –   Field   Notes ................................................................................................................. 20

Executive   Summary
Building   Information   Modeling   (BIM)   technology   provides   a   virtual   construction   solution   including   four   elements:   design   (3 ‐ D),   scheduling   (4 ‐ D),   cost   (5 ‐ D)   and   life ‐ cycle   (6 ‐ D),   where   these   elements   can   be   interlinked.
Prior   to   the   use   of   BIM   software   solutions,   the   collusion   detection   phases   of   mechanical,   electrical,   and   plumbing   (MEP)   coordination   was   a   major   challenge.
The   process   involved   overlaying   two ‐ dimensional   drawings   representing   each   trade   over   each   other   to   determine   physical   interferences   in   the   effort   to   spatially   arrange   the   numerous   components   of   each   MEP   system.
Using   BIM   technology,   the   collusion   detection   task   has   become   an   automated   routine   task.
With   the   ability   of   BIM   systems   to   associate   scheduling   (4 ‐ D)   data,   time ‐ space   conflicts   can   also   be   identified   between   multiple   disciplines;
however,   no   logic   or   reasoning   structure   currently   exist   to   resolve   them.
In   July   2009,   I   submitted   a   multi ‐ year   research   proposal   to   the   National   Science   Foundation
(NSF)   titled   “Non ‐ Concurrent   Product   Lifecycle   Integration   for   Co ‐ Existing   Systems”   in   the   amount   of   $453,933   under   the   Faculty   Early   Career   Development   (CAREER)   grant   program.
The   premise   of   the   research   proposal   expanded   on   my   research   from   my   doctoral   dissertation   on
Mechanical   Electrical   and   Plumbing   (MEP)   coordination,   where   I   studied   the   MEP   coordination   process   and   identified   critical   factors   necessary   for   consideration   of   the   spatial   arrangement   of
MEP   systems.
This   work   was   completed   prior   to   the   use   and   development   of   BIM   technology   software.
The   spatial   coordination   of   the   MEP   systems   has   always   been   a   challenge   due   to   the   fact   that   it   must   consider   critical   design,   construction,   performance,   operations,   and   maintenance   criteria.
With   the   recent   development   of   BIM   software,   specialty   contractors   have   been   able   to   greatly   reduce   the   number   of   physical   interferences   of   MEP   systems   with   each   and   with   the   structural   and   architecture   of   a   facility   prior   to   the   construction.
This   is   primarily   due   to   the   ability   of   specialty   contractors   to   represent   the   MEP   building   systems   in   a   single   three ‐ dimensional   model   and   perform   collision   checks   to   identify   physical   interferences   between   the   multiple   systems.
The   research   proposed   under   the   CAREER   grant   sought   to   identify   and   classify   time ‐ space   relationships   for   MEP   systems   and   develop   a   logic   and   reasoning   structure   to   assist   with   project   scheduling   in   BIM   systems,   and   as   the   course   co ‐ champion   for   the   Specialty   Contracting   Construction   Management   course   in   the   CAED
Construction   Management   Department,   it   has   always   been   a   primary   interest   of   mine   to   further   pursue   research   in   MEP   coordination   considering   the   scheduling,   estimating,   and   life ‐ cycle   aspects   of   mechanical,   electrical,   and   plumbing   systems.
Therefore,   the   emphasis   of   the   research   proposal   was   to   first   generate   fundamental   knowledge   regarding   the   integration   of   non ‐ concurrent   product   lifecycles   for   co ‐ existing   systems,   and   second,   develop   a   new   comprehensive   theory   for   integrating   the   non ‐ concurrent   lifecycles   for   co ‐ existing   systems   for
use   in   performing   coordination.
The   recent   introduction   of   BIM   software   solutions   is   able   to   provide   a   virtual   construction   solution,   which   includes   the   following   elements:   design   (3 ‐ D),   scheduling   (4 ‐ D),   cost   (5 ‐ D)   and   life ‐ cycle   (6 ‐ D).
These   elements   can   be   interlinked;   however,   practitioners   still   face   similar   problems   as   they   have   in   the   past.
Entry   of   incorrect   data   or   faulty   assumptions   into   the   BIM
1

system   results   in   project   personnel   being   misled   by   the   output   from   the   system.
While   most
BIM   software   solution   have   the   ability   to   contain   information   and   data   regarding   a   project,   they   do   not   contain   knowledge ‐ based   logic   and   reasoning   structures   to   assist   users   during   the   planning   and   design   and   therefore   lack   the   capability   to   assist   in   the   resolution   of   time ‐ space
.
conflicts.
To   be   able   to   fully   realize   to   the   potential   of   BIM   software   solutions   in   the   future,   knowledge   capture   and   the   integration   of   logic   and   reasoning   structures   is   imperative.
As   stated   above,   by   using   BIM   software   solutions,   the   determination   of   physical   interferences   has   become   a   mundane   task.
BIM   software   solutions   are   able   to   contain   scheduling   (4 ‐ D)   data   and   link   it   with   the   geometric   model.
The   research   funded   by   the   PDCI   assisted   me   to   devote   the   necessary   time   to   collect   the   data   needed   to   prepare   an   improved   proposal   to   submit   to   NSF   under   the   Research   for   Undergraduate   Institutions   (RUI)   grant   program.
This   involved   identifying   and   classifying   time ‐ space   relationships   for   MEP   systems   and   developing   a   preliminary   theory   for   a   logic   and   reasoning   structure   to   assist   with   the   project   scheduling   of
MEP   systems   in   BIM
I   would   like   to   acknowledge   and   thank   Rosendin   Electric,   Marelich   Mechanical,   and   the
International   Brotherhood   of   Electrical   Workers   (IBEW)   who   assisted   me   in   collecting   data   for   this   project   as   well   as   the   staff   at   Stanford   Universities   Center   for   Integrated   Facility
Engineering   (CIFE)   for   their   time   and   assistance   in   assisting   me   during   my   office   and   site   visits.
During   the   next   month,   I   will   be   submitting   the   proposal   to   NSF   under   the   RUI   grant   program.
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NSF   Grant   Application
Project   Summary
This   proposal   proposes   to   support   an   integrated   program   of   research   and   teaching   that   will   both   strengthen   professional   engineering   design   activity   and   enhance   engineering   and   construction   education   by   broadening   the   fundamental   understanding   of   integrating   non ‐ concurrent   lifecycles   for   co ‐ existing   systems,   as   applied   to   the   active   systems   of   buildings.
The   educational   component   of   this   proposal   promotes   the   explicit   recognition   of   system   lifecycles   as   a   common   thread   through   the   engineering   design   and   construction   curriculum.
It   will   prepare   students   for   a   recently   approved   integrated   design   and   construction   curriculum   and   beyond,   where   they   are   engaged   in   the   solution   of   realistic   problems   as   they   study   a   specific   sector   of   the   construction   industry   in   a   synergistic,   multi ‐ disciplinary   project ‐ based   learning   environment.
Research   in   the   role   of   integrating   non ‐ concurrent   lifecycles   for   co ‐ existing   systems   will   complement   the   educational   efforts   described   above.
This   research   focuses   on   advancing   a   more   thorough   and   fundamental   understanding   of   the   "systems   integration   and   assembly"   and   its   application   through   the   extension   of   current   design,   analysis,   fabrication,   and
assembly   methods.
The   basis   for   this   research   is   the   development   of   a   model   to   assist   with   the   constructability   and   coordination   evaluations   for   the   active   systems   of   a   building;   i.e.,   mechanical,   electrical,   plumbing,   etc.
The   broader   impacts   of   these   activities   include:   (a)   involvement   of   engineering   and   construction   management   students   in   the   entire   life ‐ cycle   of   a   project   –   conceptual   design   through   disposal/recycle,   (b)   collaboration   with   other   educational   institutions  ‐‐  universities,   community   colleges,   and   institutions   serving   underrepresented   groups  ‐‐  in   the   dissemination   of   teaching   techniques   and   materials   related   to   constructability   and   coordination,   (c)   outreach   to   K   through12   students   and   teachers   in   "science   summer   camp"   and   ACE   mentorship   programs,   (d)   participation   in   the   development   of   national   standards   for   building   information   modeling   that   accurately   reflect   the   current   state   of   knowledge   in   systems   lifecycles,   and   (e)   partnering   with   industry   to   validate   research   results   and   facilitate   the   transfer   of   new   analysis
methods   to   practitioners.
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Project   Description
Background,   Motivation,   and   Point   of   Departure   for   the   Research
The   active   systems   of   a   building/facility   include,   but   are   not   limited   to   the   mechanical,   electrical,   plumbing,   fire   detection   and   protection,   and   control   and   communication   systems.
These   systems   co ‐ exist   to   meet   the   programming   expectations   of   the   facility   users.
They   are   critical   to   the   building’s   function   and   must   meet   performance   expectations   for   comfort   and   safety.
For   example,   the   mechanical   system   provides,   circulates,   filters,   and   tempers   fresh   air   for   occupants.
The   electrical   system   provides   energy   to   power   lighting   and   electrical   circuits   to   serve   workspace   equipment   as   well   as   for   other   building   systems.
The   plumbing   system   provides   water   to   plumbing   fixtures   and   conveys   water   utilized   by   building   occupants   to   an   exit   point.
The   fire   detection   and   protection   system   provides   a   safety   mechanism   by   sensing   and   detecting   the   presence   of   a   fire   and   executing   a   method   to   extinguish   and   deter   the   spread   of   a   fire.
The   control   and   communication   systems   provide   a   means   for   monitoring   the   facility   and   enable   communication   among   occupants.
It   is   not   uncommon   to   encounter   facilities   with   as   many   as   a   dozen   or   more   co ‐ existing   systems   depending   on   the   programming   of   the   facility.
For   example   residential   building   may   have   as   little   as   four   systems,   while   a   biotechnology   manufacturing   facility   may   have   eighteen   systems   in   order   to   meet   key   manufacturing   equipment   requirements.
As   shown   in   Table   1,   the   active   systems   of   a   building   range   from   25   to   70   percent   of   the   total   building   cost.
In   an   effort   to   create   a   sustainable   environment,   green   building   construction   practices   will   force   the   technology   for   these   systems   to   evolve.
Table   1   –   Building   systems   as   a   percentage   of   total   building   cost   (Korman)
Facility   Type   Percentage   of   total   building   cost
High   Medium   Low
Biotechnology   plants
Commercial   office   buildings
Heavy   industrial   plants
Hospitals
70
40
60
50
55
30
50
40
45
25
40
30
Multi ‐ residential   complex
Research   laboratories
35
50
30
40
25
30
Semiconductor   plants   65   50   40
A   phase   common   to   all   buildings   during   the   project   delivery   process   is   the   arrangement   and   positioning   of   all   active   building   system   components   (piping,   conduit,   equipment,   etc.)   within   the   constraints   of   the   buildings   architecture   and   structure.
Most   engineering   and   construction   professionals   refer   to   this   phase   as   building   systems   coordination.
Building   systems   coordination   involves   defining   the   locations   for   and   arranging   the   components   of   building   systems,   in   what   are   often   congested   spaces,   in   order   to   avoid   physical   interferences,   so   that   they   fit   within   the   constraints   of   the   building   architecture   and   structure.
The   problem,   however,   is   that   simply   arranging   all   building   system   components   so   that   they   do   not   physically   interfere   with   each   other   does   not   ensure   constructability   of   the   systems,   nor   does   it   ensure
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that   the   systems   have   been   well   coordinated.
Furthermore,   during   the   building   systems   coordination   process,   the   entire   project   lifecycle   knowledge   is   rarely   considered,   which   means   that   design,   construction,   operations,   and   maintenance   criteria,   is   overlooked   and   ignored,   which   ultimately   affects   the   systems   fabrication   and   installation   cost,   performance,   and   the
amount   of   energy   consumed   by   the   system   over   its   lifespan.
Although   the   life   spans   of   the   active   building   systems   overlap,   they   are   not   necessarily   installed   at   the   same   time,   they   are   often   commissioned   and   decommissioned   at   different   times,   and   their   life   spans   are   rarely   the   same.
As   technology   for   the   individual   systems   evolves,   upgrades   are   required   at   different   times   and   maintenance   schedules   for   each   system   do   not   coincide   with   one   other,   either.
In   addition,   expansion   of   systems   is   often   required   as   the   programming   for   the   building/facility   changes.
Each   individual   system   requires   a   specialized   knowledge   for   commissioning,   operations,   maintenance,   and   possibly   future   expansion.
Therefore,   the   active   building   systems   are   essentially   co ‐ existing   systems   with   non ‐ concurrent   lifecycles.
In   order   for   the   building   systems   coordination   effort   to   be   considered   successful,   the   building   systems   coordination   process   must   comply   with   diverse   design,   construction,   operations,   and   maintenance   criteria.
Ideally,   the   result   of   the   coordination   evaluation   is   the   most   economical   arrangement   that   considers   the   lifecycle   of   each   building   system,   meeting   critical   design,   construction,   performance,   operations,   and   maintenance   criteria.
The   level   of   difficulty
associated   with   this   process   directly   relates   to   the   complexity   and   number   of   active   building   systems   necessary   for   the   programming   of   the   building.
Figure   1   –   Rendering   of   building   systems   located   within   a   typical   building   corridor
While   construction   cost   estimators   are   able   to   quantify   the   building   system’s   cost,   the   cost   associated   with   building   systems   coordination   is   more   difficult.
Many   engineering   and   construction   industry   professionals   have   cited   building   systems   coordination   as   one   of   the   most
5

challenging   tasks   encountered   during   the   construction   project   delivery   process.
Most   professionals   agree   that   the   difficulty   is   due   to   inherent   fragmentation   that   exist   throughout   the   architecture,   engineering   and   construction   (AEC)   industry.
For   example,   each   system   is   independently   designed   without   consideration   of   the   other.
Furthermore   fabrication   and   installation   of   each   system   is   performed   by   others   unassociated   and   unfamiliar   with   the   design   of   the   system   they   install.
There   are   many   reasons   why   this   occurs:   engineering   designers   usually   limit   themselves   to   the   design   of   one   type   of   system   due   to   the   specialized   knowledge   that   is   required   to   perform   the   engineering   design.
Specialty   construction   engineers,   who   fabricate   and   install   the   systems,   usually   limit   themselves   to   the   fabrication   and   installation   of   one   type   of   system   due   to   the   large   capital   investment   required   to   manufacture   and   fabricate
each   system.
During   the   building   system   coordination   phase,   the   multiple   organizations   for   each   system   must   interact   to   share   critical   knowledge   in   order   to   converge.
However,   there   are   no   current   guidelines   to   assist   architects   and   engineers   in   the   coordination   of   building   systems.
The   current   work   process   is   as   follows:    Engineering   design   consultants   or   design ‐ build   construction   engineers   design   their   own   systems   (mechanical,   electrical,   plumbing,   etc.),   independently   focusing   only   on   their   systems.
(There   are   often   multiple   design   consultants   due   to   the   specialized   knowledge   required   and   national   and   state   board   licensing   requirements   for   the   design   of   various   building   systems.)    The   design   is   then   provided   to   a   specialty   construction   engineer   who   will   fabricate   and   install   the   multiple   systems.
(Again,   there   are   typically   different   construction   engineers   for   each   individual   building   system   due   to   the   specialized   training   required   and   state   licensing   requirements.)    Contract   specifications   commonly   place   the   responsibility   of   a   constructability   and   coordination   evaluation   of   the   building   systems   on   the   specialty   construction   engineers   who   fabricate   and   install   the   systems.
During   the   process,   in   the   effort   to   eliminate   the   physical   interferences   between   the   multiple   building   systems   so   that   they   can   be   fabricated   and   installed   by   the   multiple   specialty   construction   engineers,   the   design   intent   and   performance   of   the   building   systems   is   often   compromised   in   order   to
position   the   systems’   components   in   the   allocated   space.
Recently,   a   technology   known   as   Building   Information   Modeling   (BIM)   software   has   assisted   in   improving   the   current   process,   primarily   with   its   ability   to   represent   the   co ‐ existing   building   systems   in   a   single   three ‐ dimensional   model   and   with   its   capability   to   identify   physical   interferences   between   the   multiple   systems.
However,   the   primary   limitation   of   BIM   technology   is   that   it   only   resolves   the   physical   interferences,   whish   as   stated   above   is   know   by   most   familiar   with   the   product   design   cycle,   as   configurationally   design.
The   current   use   of   BIM
technology   does   not   consider   the   other   diverse   design   and   other   product   life ‐ cycle   criteria   as   shown   in   Figure   No.
2.
6

Maintenance
Disposal/ recycle
Evaluate market share, quality and cost
Perceived need or technical opportunity
Conceptual product
Custom er support
Synthesis
Customer feedback
Distribution
Design of design process
Mass production Abstraction
Organization assembly
(staff + tools)
P refabrication or manufacturing of small lots
Creation of construction equipment or m anufacturing facilities
Detailed design of construction/ manufacturing process
Configurational
Detailed design or simulation design
Building System s coordination using
BIM
Figure   2   –   Tasks/Information   related   to   the   product   cycle
As   mentioned   above,   each   active   building   system   has   a   unique   product   lifecycle,   but   must   co ‐ exist   within   the   building/facility   to   meet   its   performance   expectations.
This   research   seeks   to   focus   on   the   point   where   current   BIM   technology   ends   and   seeks   to   build   a   knowledge ‐ based   model   that   will   consider   the   entire   lifecycle   for   each   individual   system   while   considering   the   requirements   of   the   other   systems   with   which   it   must   co ‐ exist.
My   vision   is   to   develop   a   comprehensive   theory   and   model   to   assist   with   the   integration   of   non ‐ concurrent   product   lifecycles   for   co ‐ existing   systems,   as   applied   to   the   active   systems   for   buildings.
Ideally,   my   goal   is   to   fundamentally   change   the   design   methodology   to   optimize   the   physical   arrangement   of   building   systems   while   considering   the   non ‐ concurrent   lifecycles   of   the   co ‐ existing   systems.
The   development   of   the   model   will   assist   with   building   systems   coordination,   while   increasing   the   fundamental   understanding   of   integrating   non ‐ concurrent   lifecycles   for   co ‐ existing   systems.
In   addition,   we   desire   to   advance   the   knowledge   and   understanding   in   the   areas   of   project ‐ based   learning,   multi ‐ disciplinary   projects,   undergraduate   research,   and   teamwork,   as   we   will
elaborate   upon   below.
Effective   building   systems   coordination   requires   recalling   and   integrating   the   lifecycle   knowledge   for   each   system  ‐‐  design,   construction,   operations,   and   maintenance,   etc.
‐‐  not   only   resolving   physical   interferences.
Missing   from   the   use   of   BIM   technology   is   the   critical   lifecycle   knowledge   regarding   each   individual   building   system.
A   work   process   utilizing   BIM   still   requires   individuals   to   meet   and   share   knowledge   regarding   their   system.
Currently,   using   BIM
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technology   only   assists   in   resolving   physical   conflicts,   through   computational   geometry.
As   described   above,   resolving   all   physical   interference   during   the   building   systems   coordination   process   does   not   necessarily   ensure   that   a   facility   has   been   well   coordinated.
This   concept   expands   current   professional   practice   and   suggests   that   there   are   multiple   types   of   interferences   beyond   physical   interferences,   which   affects   the   overall   cost   and   schedule   of   a   project.
During   coordination,   trades   must   consider   all   aspects   from   design,   construction,   and   operations,   and   maintenance.
It   is   difficult   to   integrate   this   lifecycle   knowledge   into   the   building   systems   coordination   process.
As   described   above,   the   AEC   is   inherently   fragmented   and   often   the   stakeholders   involved   do   not   take   the   opportunity   to   align   goals   and   define   requirements.
In   addition,   design   engineers   have   not   been   educated   on   lifecycle   issues.
For   example,   designers   must   make   assumptions   about   the   constructability   about   a   particular   system   or   ignore   the   issue   completely.
There   is   a   lack   of   understanding   between   the   design   engineers   who   design   the   systems   and   the   construction   engineers   who   fabricate   and   install   the   systems.
Each   engineering   discipline   focuses   on   its   own   design   and   construction   requirements,   failing   to   consider   the   how   all   the   co ‐ existing   systems   will   interact.
Many   building   systems   construction   engineers   are   unaware   of   unique   installation   requirements   for   the   other   building   systems   and   lack   a   mechanism   for   learning   more   about   the   other   building   systems.
A   knowledge   based   model   that   is   able   to   integrate   the   life ‐ cycle   knowledge   (design,   construction,   operations,   maintenance,   etc.)   regarding   multiple   systems   would   be   able   to   provide   valuable   insight   to   design   and   construction   engineers   assisting   them   in   performing   coordination.
Based   on   the   experience   of   the   engineering   and   construction   faculty   and   feedback   from   the
California   Center   for   Construction   Education   (CCCE)   industrial   advisory   board,   a   knowledge   and   skills   gap   exists   between   the   engineering   and   construction   curriculum,   which   creates   a   communication   barrier   between   those   who   design   and   those   who   build.
The   Construction   Management   (CM)   department   at   California   Polytechnic   State   University,   San
Luis   Obispo   (CPSLO)   recently   approved   an   integrated   design   and   construction   curriculum,   where   students   are   engaged   in   the   solution   of   realistic   problems   as   they   study   a   specific   sector   of   the   construction   industry   in   a   synergistic   multi ‐ disciplinary,   project ‐ based   learning   environment.
One   required   laboratory   course   in   this   new   curriculum   is   the   specialty   contracting   laboratory   course,   of   which   we   were   elected   to   be   the   course   “champion”   by   the   department   because   of   my   professional   work   experience   and   educational   background   in   the
related   field.
The   course   brings   engineering   and   construction   engineering   students   together   to   study   the   design,   fabrication,   installation,   operations,   and   maintenance   of   active   building   systems   in   a   project ‐ based   learning   environment,   in   which   we   plan   to   include   building   systems   coordination   laboratory   exercises.
The   impetus   of   the   integrated   curriculum   proposal   at   CPSLO   was   the   completion   of   the   Construction   Innovations   Center   (CIC)   on   the   CPSLO   campus.
During   the   early   programming   process   for   this   building,   faculty   and   industry   representatives   were   encouraged   to   think   about   the   future   of   the   design   and   construction   industry   and   knowledge   that   will   be   required   by   future   professionals   who   enter   into   it.
Academic   programs   build   new
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buildings   perhaps   every   50   years,   so   participants   wrestled   with   the   question,   “What   will   the   profession   of   construction   be   like   in   2050?”    Only   then   could   they   ask,   “What   is   the   best   curricular   model   to   prepare   those   professionals   in   50   years?”    Only   then   could   the   question   be   addressed,   “What   physical   spaces   are   needed   to   support   that   curriculum   model?”    While   the   specifics   of   this   industry   cannot   be   discerned   50   years   in   advance,   certain   trends   can   be   identified.
Design   and   construction   professionals   will   need   to   be   prepared   for   multiple   changes   in   job   assignments   and   perhaps   companies   during   their   careers,   so   specializing   in   just   one   area   will   not   support   that   flexibility.
Collaboration   will   be   the   key   to   successful   projects,   so   future   engineers   will   need   to   master   the   ability   to   solve   multiple   problems   at   once   that   cut   across   boundaries   of   expertise   and   responsibility.
Working   in   a   complex   profession,   design   and   construction   engineers   will   need   to   realize   that,   for   most   of   these   problems,   there   will   not   be   a   single   solution,   but   instead   many   possible   approaches   and   strategies,   some   more   applicable   than   others.
Unlike   the   product   design   process   for   mass   manufacturing,   the   production   of   a   prototype   model   is   not   feasible   due   to   financial   or   scheduling   constraints.
As   discussions   evolved,   it   became   increasingly   clear   that   a   knowledge   and   skills   gap   exists   between   the   engineering   and   construction   professionals.
Engineers   are   educated   on   design   fundamentals   through   theory   and   calculations   often   lacking   practical   applications.
Construction   engineerins   are   educated   on   construction   and   fabrication   methods   lacing   the   design   fundamentals   necessary   to   comprehend   the   complex   engineering   decision   and   reasoning   involved   in   the   design   process.
In   professional   practice,   a   design   must   translate   into   something   that   can   be   fabricated   and   installed,   and   historically   education,   for   design   and   construction   engineers   has   occurred   in   discipline   specific   silos.
More   importantly,   neither   receives   an   education   that   considers   the   entire   project   or   product   lifecycle.
In   a   multi ‐ disciplinary   integrated   project ‐ based   curriculum,   both   engineering   and   construction   students   will   be   educated   on   life ‐ cycle   issues   related   to   a   particular   system   through   project ‐ based   laboratory   exercises.
Furthermore,   as   the   use   of   integrated   project   delivery   methods,   such   as   design ‐ build,   continues   to   grow,   the   depth   of   lifecycle   knowledge   students   will   need,   will   continue   to
increase   as   well.
My   intent   is   all   that   students   who   will   participate   in   the   project ‐ based   learning   course   will   use   the   model   developed   as   part   of   the   research   in   this   course   and   beyond.
This   arrangement   will   allow   students   to   experience   true   concurrent   engineering   through   an   integrated   design,   manufacturing,   and   testing   experience.
By   using   the   model   developed   with   this   research,   students   will   learn   how   to   communicate   and   overcome   obstacles   in   a   multidisciplinary   team   and   they   will   gain   valuable   skills   needed   to   transition   to   jobs   in   industry   and   to   participate   in   more   advanced   projects.
The   new   integrated   curriculum   and   project ‐ based   learning   component   will   provide   students   with   an   enriched   learning   experience   and   will   address   engineering   and   construction   program   assessment   outcomes.
Research   Questions
The   research   has   been   designed   to   answer   the   following   research   questions:
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1.
How   can   project   lifecycle   knowledge   for   co ‐ existing   systems   be   structured   in   a   knowledge   based   model   to   provide   reasoning   capabilities   that   will   assist   in   the   coordination   process?
2.
How   are   engineering   and   construction   students   currently   educated   on   the   lifecycle   issues   that   concern   the   projects   and   systems   they   design   and   build?
3.
How   can   the   education   for   engineering   and   construction   students   be   enhanced   to   include   lifecycles   regarding   project   and   systems   they   design   and   build?
Research   Objectives
The   research   has   been   designed   with   the   following   research   objectives:
1.
Generate   fundamental   knowledge   regarding   the   integration   of   non ‐ concurrent   product   lifecycles   for   co ‐ existing   systems
2.
Develop   a   new   comprehensive   theory   for   integrating   the   non ‐ concurrent   lifecycles   for   co ‐ existing   systems   for   use   in   performing   coordination.
3.
Standardize   a   methodology   for   integrating   the   non ‐ concurrent   lifecycles   for   co ‐ existing   systems   for   use   in   performing   coordination,   as   applied   to   the   active   systems   for   buildings/facilities.
4.
Develop,   test,   and   validate   knowledge   based   model   for   integrating   the   non ‐ concurrent   lifecycles   for   co ‐ existing   systems
5.
Determine   and   develop   an   approach,   including   teaching   modules,   laboratory   activities,   etc.
that   will   better   serve   engineering   and   construction   students   to   learn   about   product   lifecycles   using   the   knowledge   collected   during   the   observation   of   professionals.
6.
Outreach   to   K   through   12   students   and   teachers   in   "science   summer   camp"   and
Architecture   Construction   and   Engineering   (ACE)   mentorship   programs.
Research   Methodology
The   method   of   research   involves   participating   in   and   collecting   data   regarding   current   coordination   activities   on   complex   buildings   and   industrial   projects.
The   data   will   then   be   analyzed   and   used   to   describe   current   coordination   processes.
Furthermore,   it   will   identify   potential   improvements   through   the   use   of   information   technology.
The   primary   method   for   representing   and   implementing   reasoning   to   the   knowledge   for   a   knowledge   based   model   will   be   symbolic   modeling.
This   approach   has   been   used   to   formalize   product   and   process   models   in   engineering   and   has   allowed   researchers   to   solve   engineering   and   construction ‐ engineering   problems   as   discussed.
Knowledge   acquisition
Knowledge   acquisition   begins   with   choosing   and   defining   the   tasks   that   the   knowledge ‐ based   system   or   expert   system   is   to   perform.
These   tasks   directly   affect   the   type   of   knowledge   acquired;   therefore,   knowledge   acquisition   becomes   the   transfer   or   transformation   of   potential   problem ‐ solving   knowledge   from   one   source   to   another   (Dym).
Therefore,   acquiring   knowledge   becomes   extremely   important   in   building   knowledge   frameworks.
This   research   will   use   four   major   approaches   to   acquire   knowledge   regarding   building   systems   coordination:
• review   of   written   information   sources
• personal   interviews   with   experts   in   the   field
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• observations   of   experts   working   in   project   meetings
Review   of   written   information   sources   is   often   a   very   effective   initial   technique   for   acquiring   knowledge.
Possible   sources   include   trade   journals,   books,   government   publications,   company   procedure   manuals,   and   current   and   historical   project   data.
These   materials   provide   information   in   a   very   unobtrusive   manner.
No   expert   time   is   required   and   knowledge   engineers   can   accomplish   most   of   the   review   independently   by   studying   project   documents
(Carrico).
The   majority   of   construction   knowledge   originates   from   experience   in   previous   projects   and   requires   a   feedback   loop   that   crosses   organizational   boundaries.
Currently,   there   are   no   generally   accepted   methods   to   formalize   construction   knowledge   (Luiten).
Therefore,   researchers   collect   an   abundant   amount   of   written   information   (Carrico).
In   this   research   project,   data   from   current   and   completed   construction   projects   will   be   the   primary   source   of   written   information   since   very   little   published   information   is   available   about   building   systems   coordination.
The   personal   interview   is   one   of   the   most   effective   ways   to   gain   expertise   and   to   receive   immediate   feedback.
Communication   with   experts   is   essential.
It   allows   researchers   to   acquire   a   portion   of   the   “domain   vocabulary”   experts   develop   to   deal   with   specific   types   of   problems   in   their   field.
It   is   preferable   to   consult   more   than   one   expert   for   multiple   perspectives   on   the   problem   (Carrico).
In   this   research,   interviews   will   be   conducted   with   engineering   managers,
design   engineers,   project   coordinators,   detailers,   and   construction   journeymen.
Observations   of   experts   on   the   job   and   in   project   meetings   are   also   excellent   ways   to   gather   information   and   to   understand   how   participants   exchange   information.
One   is   able   to   observe   design   and   construction   engineers   involved   in   building   systems   coordination   naturally   without   feeling   that   they   are   being   put   on   the   spot.
This   allows   observation   of   how   they   deal   with   actual   problems   and   how   they   handle   surprises   during   problem ‐ solving   sessions.
This   process   helps   to   define   the   problem   and   feeds   further   stages   of   knowledge   acquisition   (Carrico).
Knowledge   representation
Once   the   knowledge   acquisition   is   completed,   knowledge   will   be   encoded   in   a   form   usable   by   a   knowledge ‐ based   system   (KBS).
Most   knowledge   engineers   consider   this   step   the   most   critical   activity.
The   goal   is   to   create   a   structure   that   reflects   the   complexity   and   variety   of   all   the   components,   yet   remains   simple   enough   to   facilitate   decision ‐ making   and   assist   in   problem   solving.
Therefore,   the   trade ‐ off   a   knowledge   engineer   must   is   between   trying   to   represent   the   knowledge   completely   and   creating   a   robust   reasoning   structure   (Hunter).
Object   hierarchies   and   slot   tables   serve   as   the   primary   form   of   representation   in   this   research.
The   structure   of   the   object   hierarchy   is   important   because   its   layout   determines   how   the   represented   objects   interact   with   each   other   in   the   symbolic   model.
The   attributes   of   the   slot   tables   also   require   careful   study   because   these   slots   determine   what   data   about   objects   are   stored.
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Good   representation   of   knowledge   should   make   things   very   explicit   and   expose   natural   constraints   that   are   inherent   to   the   problem   being   solved   (Hunter).
Representing   knowledge   from   large   domains   is   difficult;   the   larger   the   domain,   the   more   difficult   it   becomes   to   create   a   reasoning   structure   (Carrico).
A   key   limitation   in   knowledge   representation   is   the   inability   to   account   for   all   possible   global   interactions   in   the   representation   structure   (Hunter).
Other   problems   often   arise   when   structuring   knowledge   into   flowcharts   to   provide   a   basis   for   good   decision ‐ making.
These   include   overlap   of   knowledge   representation   overlap   and   incorrectly   classifying   knowledge.
For   this   research,   in   order   to   the   meet   the   objectives   and   avoid   these   problems,   the   knowledge   structure   will   focus   directly   on   those   components   most   pertinent   to   building   systems   coordination.
In   addition,   specific   attention   will   be   applied   to   how   the   reasoning   structure   would   use   the   knowledge   framework.
Building   reasoning   structures
Reasoning   structures   found   in   KBS   perform   diagnostics.
The   reasoning   methods   described   below   provide   a   general   framework   for   the   reasoning   commonly   found   in   these   systems.
Reasoning   typically   uses   the   following   methods:   heuristics,   model ‐ based   reasoning   (MBR),   and   case ‐ based   reasoning   (CBR).
A   KBS   can   use   heuristics,   MBR,   or   CBR   only,   or   it   can   combine   two,   or   all   three,   of   the   reasoning   methods   (Kunz).
The   intent   of   this   research   is   to   assist   engineers   during   the   design   stage,   which   requires   integrating   design,   construction,   operations,   and   maintenance   knowledge.
In   this   research,   heuristics   and   MBR   will   be   utilized   to   provide   the   necessary   feedback   for   building   systems   coordination.
Heuristic   reasoning
Heuristics   provide   a   basis   for   reasoning   mechanisms   in   classic   expert   systems.
A   traditional   KBS   uses   heuristics   to   express   its   knowledge.
The   heuristic   classification   system   works   by   abstracting   measurable   data   and   relating   them   to   a   predefined   potential   problem.
The   system   matches   the   problem   with   a   solution,   and   then   refines   the   solution.
Heuristics   can   represent   many   different   kinds   of   knowledge.
They   may   express   aspects   of   fundamental   principles,   experimental   rules   of   thumb,   and   high ‐ level   knowledge   about   how   to   use   other   kinds   of
knowledge   (Dym).
Figure   2   shows   how   a   heuristic   reasoning   structure   works.
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Problem class –
Identification of
Interference Type
2. Heuristic matching
Solution class –
Detailing, Layout, Positioning,
Application, Layout
3. Solution refinement 1. Data Abstraction
Raw data –
Components interfering
Specific solution –
Alter component attributes based on recommendation of solution class
Figure   2  ‐  Heuristic   reasoning   structure
In   this   research,   the   heuristic   reasoning   will   be   utilized   because   it   is   able   to   match   the   human   process   for   resolving   coordination   conflicts.
It   lends   itself   well   to   programming   the   building   systems   coordination   tool   to   determine   and   resolve   coordination   problems.
First,   the   heuristic   reasoning   structure   is   able   to   abstract   coordination   information   (raw   data)   from   a   geometric   model.
Second,   the   reasoning   structure   can   then   classify   the   conflicts   by   classes   by   making   heuristic   matches.
Finally,   the   solution   refinement   mechanism   can   select   a   specific   solution   to   resolve   coordination   conflicts.
Model ‐ based   reasoning
Model ‐ based   reasoning   (MBR)   involves   creating   a   product   model   to   form   the   basis   for   the   reasoning   mechanism.
In   this   research,   the   geometric   representation   inside   the   computer   tool   will   serve   as   the   model.
In   order   to   use   heuristic   reasoning   effectively,   MBR   is   essential.
MBR   provides   the   means   to   create   a   virtual   representation   of   the   building   systems.
Groups   of   individual   components   from   each   building   system   collectively   comprise   the   product   model.
For   reasoning   purposes,   each   component   consists   of   a   description   of   the   information   needed   to   represent   and   reason   about   the   component;   experts   often   refer   to   this   as   component   definition
(McKinney).
Heuristic   reasoning   uses   MBR   to   abstract,   test,   and   analyze   data.
The   advantage   of   MBR   is   the   ability   to   abstract   graphical,   geometrical,   topological,   and   behavioral   characteristics   from   the   components   in   the   model   for   the   reasoning   processes.
In   this   research,   MBR   reasoning   tracks
the   effects   of   the   geometrical   and   topological   changes   made   during   the   resolution   of   coordination   issues   and   conflicts   found.
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Scheduling Data
(4th-Dimension)
Architectural System
Structural System
Electrical System
Mechanical System
3-D Model
Coordinated
BIM Model considering Time-
Space Relationships
Plumbing System
Architecture
Fire Protection System Time-Space
Logic and Reasoning
Structure
Figure   3   –   Logic   and   Reasoning   Structure   Module   for   use   with   BIM   software   solutions
Case ‐ based   reasoning
Case ‐ based   reasoning   (CBR)   uses   pre ‐ formulated   solution   sets   for   a   specific   problem   as   the   basis   for   the   reasoning   mechanism.
In   CBR,   an   expert   creates   a   set   of   cases,   each   of   which   includes   some   descriptions   of   a   situation   and   an   associated   statement   of   the   problem’s   cause   and   suggested   correction   method.
Reasoning   essentially   involves   matching   observed   data   with   the   data   of   each   case.
The   advantage   of   CBR   is   its   ability   to   test   a   prototype   solution   through   a   series   of   libraries   that   contain   alternative   solutions.
This   method   can   find   an   optimal   solution.
The   prototype   solution   can   also   be   refined   to   meet   the   specific   needs   of   the   problem   at   hand
(Dym).
In   this   research,   CBR   is   not   used   due   to   the   number   of   diverse   solutions   possible   for   resolving   coordination   issues   and   conflicts.
Heuristics   and   MBR   provide   a   more   robust   reasoning   system   because   they   rely   more   heavily   on   individual   component   attributes   rather   than   solution   sets   as   used   with   case   based   reasoning.
Methodology   Example
Figure   3   depicts   an   example   of   how   the   methodology   described   above   will   be   applied.
In   this   example,   two   components   from   co ‐ existing   systems   are   found   to   interfere   with   each   other  ‐‐  a   pressurized   domestic   water   supply   pipe   and   a   gravity ‐ driven   waste   pipe.
The   KBS   may   classify   the   interference   by   evaluating   the   attributes   in   question.
In   this   case,   the   two   components
physically   interfere;   however,   the   slope   attribute   of   the   gravity   line   is   also   in   question.
Therefore,   the   KBS   may   further   classify   the   interference   as   a   functional   interference.
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Problem class –
(Identification of Interference Type)
Functional
Interference
1. Data Abstraction
Raw data –
Components interfering
Pressurized domestic water supply pipe
Solution class –
2. Heuristic match
- Horizontal Layout
- Vertical Positioning
- System Performance
- Etc.
Specific solution –
Move component based on recommendation of solution class
3. Solution refinement
Gravity driven waste pipe
Figure   4   –   Methodology   example
Using   heuristics,   the   KBS   may   select   a   solution,   which   includes:   horizontal   layout,   vertical   positioning,   system   performance   etc.
However,   the   solution   must   involve   considering   all   aspects   of   the   co ‐ existing   systems’   lifecycles.
In   this   basic   example,   the   design   intent   of   both   systems   must   be   maintained.
The   gravity ‐ driven   waste   line   must   convey   waste   away   from   a   use   point   in   a   downward   sloping   pipe.
The   pressurized   domestic   water   supply   pipe   must   convey   water   to   a   point   of   use.
Any   changes   from   the   original   design   must   be   evaluated   from   constructability   (fabrication   and   installation)   point   of   view   considering   time   and   cost   to   fabricate   and   install   any   reconfiguration   of   either   system.
Coincidentally,   any   changes   from   the   original   design   must   be   evaluated   from   an   operational   point   of   view   –   i.e.
considering   the   changes   in   the   amount   of   energy   used   from   any   reconfiguration.
In   addition,   the   proposed   reconfigured   solution   must   be   evaluated   from   a   maintenance   point   of   view,   considering   how   the   reconfigured   layout   will   affect   the   ability   to   maintain   the   system.
In   this   case,   after   a   complete   lifecycle   evaluation   and   in   order   to   maintain   the   design   intent   of   the   gravity ‐ driven   waste   pipe,   the   pressurized   domestic   water   supply   line   must   yield   to   a   the   gravity ‐ driven   waste   pipe.
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Detection of Time-Space Conflict
Gravity Sewer piping is scheduled to installed prior to domestic water supply piping, but Gravity Sewer piping is located at a higher elevation creating conflicts during installation
Pressurized domestic water supply pipe
Identify Solution Set
1. Reschedule conflicting components
2. Relocate conflicting components
3. Reconfigure conflicting components
Gravity driven waste pipe
Figure   5   –   Example   of   Time ‐ Space   Conflict
Project   Work   Plan
To   perform   the   proposed   research,   the   research   objectives   and   activities   are   scheduled   to   occur   over   the   five   years   allotted   by   the   grant   requirements:
•
Year   1   –   Data   Acquisition,   Identification,   Analysis,   and   Development   of   a   Knowledge   framework
•
Year   2  ‐  Prototype   Tool   Development,   Testing,   and   Validation
• Year   3   –   Development   of   Teaching   Modules   and   Dissemination
A   summary   of   the   proposed   research   to   be   conducted,   by   year,   is   described   below.
Year   1   –   Data   Acquisition,   Identification,   and   Analysis
The   research   will   begin   be   identifying   the   types   of   lifecycle   knowledge   that   will   be   collected.
This   will   include   the   identification   of   relevant   constructs   regarding   effective   coordination   practices   and   team   processes   that   influence   the   coordination   of   multiple   systems   with   non ‐ concurrent   project   lifecycles.
The   step   will   include   documenting   and   analyzing   the   practices   of   building   systems   coordination   teams   through   videotaping   and   interviews.
In   order   to   achieve
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and   ensure   that   the   correct   type   of   data   is   being   collected   a   preliminary   step   will   be   to   identify   attributes   and   indicators   of   good   coordination   efforts.
Additionally,   during   the   first   year   we   will   focus   data   analysis   and   development   of   the   knowledge   framework   to   represent   the   knowledge   collected   during   the   first   year.
The   knowledge   framework   will   be   designed   so   that   an   analysis   methodology   can   be   applied   in   the   knowledge ‐ based   system.
Factors   affecting   the   knowledge   framework   development   include   comparing   the   building   systems   coordination   teams   practices   and   results   for   project   which   meet   the   criteria   of   a   well   coordinated   project   to   the   practices   and   results   of   projects   with   others   who   did   not   meet   the   criteria   of   a   well   coordinated   project   using   the   methods   described   above.
Year   2   –   Prototype   Tool   Development,   Testing,   and   Validation
The   focus   of   the   third   year   will   be   on   the   development,   testing,   and   validation   of   knowledge ‐ based   model.
Activities   will   focus   on   1)   developing   an   empirically   grounded   theory   to   explain   what   work   practices   and   team   processes   affect   coordination   and   how   2)   validate   the   theory   by   predicting   the   overall   constructability   of   the   systems   based   on   observed   coordination   practices.
This   phase   of   the   research   will   include   partnering   and   collaborating   with   industry   to   validate   results   and   facilitate   the   transfer   of   new   analysis   methods   to   practitioners.
Year   3   –   Development   of   Teaching   Modules   and   Dissemination
The   focus   of   the   fourth   year   will   be   on   the   development   of   teaching   modules   and   exercises.
The   design   approach   for   the   teaching   modules   and   exercises   will   incorporate   two   qualities   that   are   critical   for   engineers   in   the   21st   century:   1)   utilizing   a   systems   approach   to   design   and   2)   emphasizing   ethical,   environmental,   health   and   safety,   sustainability,   social,   political,   and   manufacturability   issues.
In   addition,   we   plan   to   incorporate   six   principles   that   have   proven   to   be   effective   in   achieving   higher   retention   of   underrepresented   individuals   in   engineering   and   promoting   deeper   learning   in   the   students:   1)   providing   meaningful   context   (i.e.,   a   "real   world"   application);   2)   integrating   concepts   from   math,   science   and   technology;   3)   emphasizing   active   learning   and   design;   4)   facilitating   meaningful   connections   among   students;   5)   promoting   reflection   and   self ‐ assessment   of   learning;   and   6)   creating   significant   interaction   between   students   and   faculty,   with   faculty   acting   as   coaches.
We   plan   to   identify   and   establish   collaborations   between   disciplines   and   institutions,   among   the   U.S.
academic   institutions,   industry   and   government   and   with   international   partners,   which   will   help   me   to   develop,   adopt,   adapt   or   disseminate   effective   models   and   pedagogic   approaches   to   science,   mathematics   and   engineering   teaching.
During   this   stage   we   plan   to   develop   research ‐ based   educational   materials   or   contribute   to   databases   useful   in   teaching,   specifically   in   the   form   of   a   “summer   science”   program   aimed   at   students   in   the   K   through   8   levels   and   the   through   the   ACE   mentorship   program   for   students   in   the   9   through   12   level.
Both   of   which   will   broaden   participation   of   underrepresented   groups.
The   educational   and   outreach   activities   will   increase   the   participation   of   industry   and   students   in   the   study   of   building   systems   coordination.
Dissemination   activities   include:   (1)   Workshops   and   seminars   for   practitioners,   apprenticeship   programs,   and   community   colleges.
The   close
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collaboration   with   industry   associations   and   centers   will   function   both   as   a   source   of   expertise   and   access   to   projects,   and   as   channels   for   systematic   dissemination   of   the   effective   practices.
(2)   Integration   of   the   research   with   graduate   and   undergraduate   specialty   contracting   courses   who   focus   on   the   active   systems   of   a   building.
Case   studies   and   research ‐ based   field   assignments   will   increase   the   students'   exposure   to   the   actual   work   practices,   and   provide   them   with   a   framework   for   understanding   and   interpreting   practice.
Field   assignments   will   also   be   used   for   data   collection   during   validation.
(3)   Development   of   simulation   games   as   learning   modules.
These   activities   will   increase   awareness   of   product   and   system   lifecycles   and   will   be   design   to   attract   underrepresented   students   to   engineering   disciplines   as   they   see   how   design   engineering   and   construction   professionals   work   together.
(4)   Make   campus   visits   and   presentations   at   institutions   that   serve   underrepresented   groups.
(5)   Participate   in   developing   new   approaches   (e.g.,   use   of   information   technology   and   connectivity)   to   engage   underserved   individuals,   groups,   and   communities   in   science   and   engineering.
(6)   Participate   in   conferences,   workshops   and   field   activities   where   diversity   is   a   priority.
Lastly,   we   plan   to   disseminate   the   knowledge   to   the   broader   community,   specifically   by   designing   a   prototype   museum   exhibit,   which   would   be   appropriate   for   a   science   and   industry   museum,   to   educate   the   general   public   on   the   importance   of   lifecycles   of   the   active   systems   of   buildings.
We   intend   to   demonstrate,   through   the   exhibit,   how   the   systems   provide   comfort   and   safety   to   our   buildings/facilities   and   how   the   consideration   of   their   lifecycles   affects   energy   use.
Significance   and   Impact   of   the   Research
This   work   has   significant   scientific   and   intellectual   merit   as   the   research   proposes   to   generate   fundamental   knowledge   regarding   the   integration   of   non ‐ concurrent   product   lifecycles   for   co ‐ existing   systems,   and   standardize   a   methodology   for   performing   building   systems   coordination,   which   can   then   be   applied   to   other   fields.
The   proposed   project   is   part   of   the   principal   investigator's   research   program   to   increase   fundamental   understanding   of   processes   of   construction   innovation   and   to   provide   mechanisms   and   strategies   for   technological   advancement   in   construction.
Intellectual   Merit
This   research   will   generate   fundamental   knowledge   regarding   the   integration   of   non ‐ concurrent   product   lifecycles   for   co ‐ existing   systems.
It   will   develop   a   new   comprehensive   theory   for   conducting   building   systems   coordination   for   building   systems,   grounded   on   several   fields   of   knowledge   and   validated   with   empirical   studies.
This   theory   will   integrate   the   concepts   of   product   lifecycles   considering   constructability   and   coordination   and   open   the   way   for   new   directions   the   design   and   construction   of   co ‐ existing   building   systems.
The   research   will   also   develop   a   new   methodology   for   performing   building   systems   coordination.
The   new   theory   and   methodology   will   be   of   value   to   other   researchers.
Finally,   the   findings   will   provide   a   basis   for   future   modeling   and   simulation.
Broader   Impacts
Most   researchers   in   the   engineering   and   construction   fields   envision   computer   aided   design   system   to   become   more   than   what   they   are   used   for   today,   which   is   essentially   an   electronic   drafting   tool   with   little ‐ to ‐ no   knowledge   base.
BIM   technology   has   allowed   use   to   expand   to
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project   planning   and   control   systems,   but   still   has   a   limited   knowledge   base   that   must   be   input   by   the   user.
This   research   seeks   to   integrate   lifecycle   knowledge   into   models.
Capturing   and   formalizing   the   knowledge   related   to   the   integration   of   systems   whose   lifecycles   are   non ‐ concurrent   will   enable   systematic   development   of   a   future   design   methodologies   and   work   processes.
This   will   have   a   significant   impact   on   how   the   universities   educate   and   train   future   engineers.
Educational   and   Outreach   Activities
The   proposed   work   will   advance   the   understanding   of   how   to   design   learning   experiences   for   greater   retention   of   engineering   and   construction   students.
Students   are   motivated   by   the   experience   of   mastery.
The   educational   component   of   this   research   will   be   focused   on   designing   an   educational   experience   not   only   to   enable   students   to   experience   varying   degrees   of   mastery,   but   also   to   allow   them   to   experience   the   joy   of   being   able   to   assist   individuals   in   need.
Providing   these   experiences   is   particularly   important   for   both   engineering   and   construction   students.
These   experiences   are   also   critical   during   the   first   two   years,   since   that   is   when   students   are   most   likely   to   drop   out   of   engineering   because   they   lack   to   see   how   their
designs   will   translate   into   something   tangible.
The   proposed   work   will   advance   the   understanding   of   how   to   design   learning   experiences   to   equip   engineers   for   the   complex   constructability   and   coordination   issues   that   they   will   face   as   the   products   they   design   transfer   into   tangible   products.
The   Accreditation   Board   of
Engineering   and   Technology   (ABET)   requires   programs   to   demonstrate   that   students   are   able   to   formulate   engineering   solutions   within   the   design   constraints   of   ethical,   environmental,   health   and   safety,   sustainability,   social,   political,   and   manufacturability   issues   in   design.
The   American
Council   for   Construction   Education   (ACCE)   requires   programs   to   demonstrate   responsiveness   to   social,   economic,   and   technical   developments   and   reflects   the   application   of   evolving   knowledge   in   construction   and   in   the   behavioral   and   quantitative   sciences.
However,   no   clear   methodology   has   emerged   to   integrate   these   considerations   into   the   engineering   and   construction   curriculums.
Designing   for   constructability   and   coordination   requires   an   understanding   of   these   issues.
This   work   will   demonstrate   the   effectiveness   in   developing   the
intellectual   attributes   required   of   the   21st   century   design   and   construction   engineers.
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Appendix   –   Field   Notes

Appendix – Field Notes