{"ID":2845909,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2511.03684","arxiv_id":"2511.03684","title":"Simulation-Based Validation of an Integrated 4D/5D Digital-Twin Framework for Predictive Construction Control","abstract":"Persistent cost and schedule deviations remain a major challenge in the U.S. construction industry, revealing the limitations of deterministic CPM and static document-based estimating. This study presents an integrated 4D/5D digital-twin framework that couples Building Information Modeling (BIM) with natural-language processing (NLP)-based cost mapping, computer-vision (CV)-driven progress measurement, Bayesian probabilistic CPM updating, and deep-reinforcement-learning (DRL) resource-leveling. A nine-month case implementation on a Dallas-Fort Worth mid-rise project demonstrated measurable gains in accuracy and efficiency: 43% reduction in estimating labor, 6% reduction in overtime, and 30% project-buffer utilization, while maintaining an on-time finish at 128 days within P50-P80 confidence bounds. The digital-twin sandbox also enabled real-time \"what-if\" forecasting and traceable cost-schedule alignment through a 5D knowledge graph. Findings confirm that integrating AI-based analytics with probabilistic CPM and DRL enhances forecasting precision, transparency, and control resilience. The validated workflow establishes a practical pathway toward predictive, adaptive, and auditable construction management.","short_abstract":"Persistent cost and schedule deviations remain a major challenge in the U.S. construction industry, revealing the limitations of deterministic CPM and static document-based estimating. This study presents an integrated 4D/5D digital-twin framework that couples Building Information Modeling (BIM) with natural-language p...","url_abs":"https://arxiv.org/abs/2511.03684","url_pdf":"https://arxiv.org/pdf/2511.03684v1","authors":"[\"Atena Khoshkonesh\",\"Mohsen Mohammadagha\",\"Navid Ebrahimi\"]","published":"2025-11-05T18:07:03Z","proceeding":"cs.CE","tasks":"[\"cs.CE\",\"cs.AI\",\"cs.LG\",\"eess.SY\"]","methods":"[]","has_code":false}