Abstracts – Browse Results
Click on the titles below to expand the information about each abstract.
Viewing 18 results ...
Bai, S, Li, M, Song, L and Kong, R (2021) Developing a Common Library of Prefabricated Structure Components through Graphic Media Mapping to Improve Design Efficiency. Journal of Construction Engineering and Management, 147(01).
Ernstsen, S N, Whyte, J, Thuesen, C and Maier, A (2021) How Innovation Champions Frame the Future: Three Visions for Digital Transformation of Construction. Journal of Construction Engineering and Management, 147(01).
Joubert, F, Steyn, E and Pretorius, L (2021) Using the HAZOP Method to Conduct a Risk Assessment on the Dismantling of Large Industrial Machines and Associated Structures: Case Study. Journal of Construction Engineering and Management, 147(01).
Kim, H and Ham, Y (2021) Increasing Reliability of Participatory Sensing for Utility Pole Condition Assessment Using Fuzzy Inference. Journal of Construction Engineering and Management, 147(01).
Korb, S and Sacks, R (2021) Agent-Based Simulation of General Contractor–Subcontractor Interactions in a Multiproject Environment. Journal of Construction Engineering and Management, 147(01).
Li, M, Baek, M and Ashuri, B (2021) Forecasting Ratio of Low Bid to Owner’s Estimate for Highway Construction. Journal of Construction Engineering and Management, 147(01).
Love, P E D, Matthews, J and Fang, W (2021) Envisioning Rework in Practice: Emergent Insights from a Longitudinal Study. Journal of Construction Engineering and Management, 147(01).
Ma, L, Guo, H and Fang, Y (2021) Analysis of Construction Workers’ Safety Behavior Based on Myers-Briggs Type Indicator Personality Test in a Bridge Construction Project. Journal of Construction Engineering and Management, 147(01).
Mohamad, M and Tran, D Q (2021) Risk-Based Prioritization Approach to Construction Inspections for Transportation Projects. Journal of Construction Engineering and Management, 147(01).
Moon, S, Lee, G, Chi, S and Oh, H (2021) Automated Construction Specification Review with Named Entity Recognition Using Natural Language Processing. Journal of Construction Engineering and Management, 147(01).
Shabani Ardakani, S and Nik-Bakht, M (2021) Functional Evaluation of Change Order and Invoice Management Processes under Different Procurement Strategies: Social Network Analysis Approach. Journal of Construction Engineering and Management, 147(01).
Tai, H, Chen, J, Cheng, J, Wei, H, Hsu, S and Liu, H (2021) Determining Worker Training Time for Precast Component Production in Construction: Empirical Study in Taiwan. Journal of Construction Engineering and Management, 147(01).
Tetik, M, Peltokorpi, A, Seppänen, O, Leväniemi, M and Holmström, J (2021) Kitting Logistics Solution for Improving On-Site Work Performance in Construction Projects. Journal of Construction Engineering and Management, 147(01).
Wu, H, Qian, Q K, Straub, A and Visscher, H (2021) Stakeholder Perceptions of Transaction Costs in Prefabricated Housing Projects in China. Journal of Construction Engineering and Management, 147(01).
Wu, J, Sadraddin, H L, Ren, R, Zhang, J and Shao, X (2021) Invariant Signatures of Architecture, Engineering, and Construction Objects to Support BIM Interoperability between Architectural Design and Structural Analysis. Journal of Construction Engineering and Management, 147(01).
Yu, X and Ergan, S (2021) Key Variables in Determining Energy Shaving Capacity of Buildings during Demand Response Events. Journal of Construction Engineering and Management, 147(01).
- Type: Journal Article
- Keywords:
- ISBN/ISSN: 0733-9364
- URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0001949
- Abstract:
In the US, the increasing electricity demand lays massive pressure on national grids. Demand response (DR) programs provide an economical way to avoid electrical blackouts by incentivizing end-consumers to reduce their demand during peak hours and emergencies. However, the estimation of the power demand shaving capacity (PSC) (i.e., the amount of power demand that can be curtailed) of buildings is often inaccurate in the current practice because it only relies on oversimplified building design specifications. Moreover, existing estimation models of PSC either require detailed information (e.g., thermal resistance value) that are not readily available and hard to acquire, or that are building/system-specific and hard to scale up. In this study, the authors implemented the state-of-the-art feature explanation approach to identify key variables by evaluating the contribution of all related variables extracted from previous DR research efforts and current practices of DR programs. By identifying key variables, the authors attempted to find the sweet spot of PSC estimation models that can ensure accuracy, generality, and scalability. The proposed data-driven PSC estimation model using only key variables (47% reduction from all identified information items) and trained using 28 different buildings showed 81% better performance as compared with the benchmark of the current practice.
Yu, X, Mehmood, K, Paulsen, N, Ma, Z and Kwan, H K (2021) Why Safety Knowledge Cannot be Transferred Directly to Expected Safety Outcomes in Construction Workers: The Moderating Effect of Physiological Perceived Control and Mediating Effect of Safety Behavior. Journal of Construction Engineering and Management, 147(01).
Zhang, S, Li, J, Li, Y and Zhang, X (2021) Revenue Risk Allocation Mechanism in Public-Private Partnership Projects: Swing Option Approach. Journal of Construction Engineering and Management, 147(01).