TY - GEN
T1 - Discrete Event Simulation to Predict Construction Equipment Emissions on a Digital Twin Platform
AU - Hong, Kepeng
AU - Apostolidis, Alexandros
AU - Teizer, Jochen
N1 - Publisher Copyright:
© 2024 ISARC. All Rights Reserved.
PY - 2024
Y1 - 2024
N2 - Emissions from machinery that is primarily fueled by Diesel represent a
significant environmental concern in the construction sector.
Traditional monitoring methods, including both Simplified and Portable
Emissions Measurement Systems (SEMS and PEMS, respectively) encounter
practical and financial constraints when deployed extensively across the
diverse machinery types. This paper introduces a novel approach on
predicting emissions and fuel consumption by leveraging a priori
recorded emissions data from non-road mobile machinery (NRMM) in a
Discrete Event Simulation (DES) as part of a Digital Twin Platform
(DTP). Focusing on three types of construction machines (drilling rig,
loading excavator, and hauling dump truck) the DES models their basic
operations on a DTP purposed for earthwork and foundation activities for
a high-rise building project in Denmark. With the input of different
configurations (e.g., machine quantity and type, location,), DES allows
for the prediction of emissions and work output. Verification of the
approach occurred in a field-realistic outdoor construction laboratory
setting while the validation was demonstrated on a construction site.
The results provide an efficient and economical avenue for monitoring
emissions related to construction equipment operations. Beyond the
environmental benefits, the proposed method generates knowledge that can
supply construction managers with critical insights into performing
proper resource leveling.
AB - Emissions from machinery that is primarily fueled by Diesel represent a
significant environmental concern in the construction sector.
Traditional monitoring methods, including both Simplified and Portable
Emissions Measurement Systems (SEMS and PEMS, respectively) encounter
practical and financial constraints when deployed extensively across the
diverse machinery types. This paper introduces a novel approach on
predicting emissions and fuel consumption by leveraging a priori
recorded emissions data from non-road mobile machinery (NRMM) in a
Discrete Event Simulation (DES) as part of a Digital Twin Platform
(DTP). Focusing on three types of construction machines (drilling rig,
loading excavator, and hauling dump truck) the DES models their basic
operations on a DTP purposed for earthwork and foundation activities for
a high-rise building project in Denmark. With the input of different
configurations (e.g., machine quantity and type, location,), DES allows
for the prediction of emissions and work output. Verification of the
approach occurred in a field-realistic outdoor construction laboratory
setting while the validation was demonstrated on a construction site.
The results provide an efficient and economical avenue for monitoring
emissions related to construction equipment operations. Beyond the
environmental benefits, the proposed method generates knowledge that can
supply construction managers with critical insights into performing
proper resource leveling.
KW - Construction equipment emissions
KW - Digital Twin
KW - Discrete Event Simulation
KW - Site layout optimization
KW - Non-road Mobile Machinery
KW - Portable Emission Measurement System
KW - Prediction and avoidance
U2 - 10.22260/ISARC2024/0036
DO - 10.22260/ISARC2024/0036
M3 - Article in proceedings
T3 - Proceedings of the ISARC
SP - 267
EP - 274
BT - Proceedings of the 41st International Symposium on Automation and Robotics in Construction (ISARC 2024)
PB - International Association for Automation and Robotics in Construction (IAARC)
T2 - 41<sup>st</sup> International Symposium on Automation and Robotics in Construction
Y2 - 3 June 2024 through 7 June 2024
ER -