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Abbasi, S, Taghizade, K and Noorzai, E (2020) BIM-Based Combination of Takt Time and Discrete Event Simulation for Implementing Just in Time in Construction Scheduling under Constraints. Journal of Construction Engineering and Management, 146(12).

Assaad, R, El-adaway, I H, El Hakea, A H, Parker, M J, Henderson, T I, Salvo, C R and Ahmed, M O (2020) Contractual Perspective for BIM Utilization in US Construction Projects. Journal of Construction Engineering and Management, 146(12).

Assaad, R, El-adaway, I H, Hastak, M and Needy, K L (2020) Commercial and Legal Considerations of Offsite Construction Projects and their Hybrid Transactions. Journal of Construction Engineering and Management, 146(12).

Bangaru, S S, Wang, C, Zhou, X, Jeon, H W and Li, Y (2020) Gesture Recognition–Based Smart Training Assistant System for Construction Worker Earplug-Wearing Training. Journal of Construction Engineering and Management, 146(12).

Chang, S, Castro-Lacouture, D and Yamagata, Y (2020) Estimating Building Electricity Performance Gaps with Internet of Things Data Using Bayesian Multilevel Additive Modeling. Journal of Construction Engineering and Management, 146(12).

  • Type: Journal Article
  • Keywords: Performance gaps; Internet of things (IoT); Planning building energy; Monitoring energy model;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0001930
  • Abstract:
    Energy models should be simplified to handle data limitations and should predict reliable energy use. Currently, it remains challenging to ensure an appropriate level of detail for simplifying building energy models and to avoid performance gaps when predicting electricity consumption. In this respect, this research proposes to identify an appropriate level of simplifying a building energy model, predict electricity demands and performance gaps using the simplified energy model, and expand the model usability through the operational stage. Building electricity demands predicted through EnergyPlus (version 8.7.0) simulation are compared with actual electricity data collected through Internet of Things (IoT) sensors. Consideration of performance gaps increases the predictability of electricity consumption of a simplified energy model. Also, the Bayesian multilevel additive model updates the performance gaps along with the collection of new IoT data. The findings of this study contribute to forecasting electricity demands with a simplified energy model by predicting performance gaps that can be applied to predicting the electricity needs of similar buildings in the design stage and controlling operational electricity use in the operational stage by comparing sensor measurement with reference data provided by the energy model.

Erol, H, Dikmen, I, Atasoy, G and Birgonul, M T (2020) Exploring the Relationship between Complexity and Risk in Megaconstruction Projects. Journal of Construction Engineering and Management, 146(12).

Jallan, Y and Ashuri, B (2020) Text Mining of the Securities and Exchange Commission Financial Filings of Publicly Traded Construction Firms Using Deep Learning to Identify and Assess Risk. Journal of Construction Engineering and Management, 146(12).

Kong, F and Dou, D (2020) RCPSP with Combined Precedence Relations and Resource Calendars. Journal of Construction Engineering and Management, 146(12).

Li, H, Luo, X and Skitmore, M (2020) Intelligent Hoisting with Car-Like Mobile Robots. Journal of Construction Engineering and Management, 146(12).

Loosemore, M, Sunindijo, R Y and Zhang, S (2020) Comparative Analysis of Safety Climate in the Chinese, Australian, and Indonesian Construction Industries. Journal of Construction Engineering and Management, 146(12).

Mahdavian, A and Shojaei, A (2020) Hybrid Genetic Algorithm and Constraint-Based Simulation Framework for Building Construction Project Planning and Control. Journal of Construction Engineering and Management, 146(12).

Nguyen, P H D, Tran, D Q and Lines, B C (2020) Empirical Inference System for Highway Project Delivery Selection Using Fuzzy Pattern Recognition. Journal of Construction Engineering and Management, 146(12).

Roupé, M, Johansson, M, Maftei, L, Lundstedt, R and Viklund-Tallgren, M (2020) Virtual Collaborative Design Environment: Supporting Seamless Integration of Multitouch Table and Immersive VR. Journal of Construction Engineering and Management, 146(12).

Sarihi, M, Shahhosseini, V and Banki, M T (2020) Multiskilled Project Management Workforce Assignment across Multiple Projects Regarding Competency. Journal of Construction Engineering and Management, 146(12).

Shi, J, Liu, B, Tan, J, Dai, J, Chen, J and Ji, R (2020) Experimental Studies and Microstructure Analysis for Rapid-Hardening Cement Emulsified Asphalt Mortar. Journal of Construction Engineering and Management, 146(12).

Signor, R, Love, P E D, Marchiori, F F and Felisberto, A D (2020) Underpricing in Social Infrastructure Projects: Combating the Institutionalization of the Winner’s Curse. Journal of Construction Engineering and Management, 146(12).

Wang, D, Wang, Y and Lu, Y (2020) Impact of Regulatory Focus on Uncertainty in Megaprojects: Mediating Role of Trust and Control. Journal of Construction Engineering and Management, 146(12).

Wu, W, Sandoval, A, Gunji, V, Ayer, S K, London, J, Perry, L, Patil, K and Smith, K (2020) Comparing Traditional and Mixed Reality-Facilitated Apprenticeship Learning in a Wood-Frame Construction Lab. Journal of Construction Engineering and Management, 146(12).

Xu, X, Chen, K and Cai, H (2020) Automating Utility Permitting within Highway Right-of-Way via a Generic UML/OCL Model and Natural Language Processing. Journal of Construction Engineering and Management, 146(12).

Yin, X, Bouferguene, A and Al-Hussein, M (2020) Data-Driven Sewer Pipe Data Random Generation and Validation. Journal of Construction Engineering and Management, 146(12).