Bridging BIM and Stochastic Simulation: A Conceptual Framework and Illustrative Application

In construction project management, the execution phase relies on deterministic scheduling methods that cannot represent activity-level uncertainty or support quantitative corrective-action testing before physical commitment. This study presents a conceptual framework and proof-of-concept application that addresses this gap by integrating Building Information Modeling (BIM) with the COSMOS Simulator—a construction-specific discrete-event engine benchmarked against industry simulators in prior work. The framework formalizes a semi-automated pipeline from Autodesk Revit through Dynamo BIM to COSMOS via a governed parameter store, converting BIM-derived quantity takeoffs into stochastic simulation inputs. This study makes two contributions: The first is the development of a governed BIM-to-simulation data pipeline in which an identifier-keyed data contract and in-flow validation establish an auditable chain of custody from design element to simulation input. The second is an advancement toward addressing a limitation the engine’s own validation studies identify—execution-phase site–data integration—through a control loop that couples Earned Value Analysis in a 4D BIM environment (Synchro) with iterative COSMOS-based scenario testing, enabling managers to evaluate corrective actions quantitatively before site implementation. Feasibility is demonstrated on an illustrative reinforced concrete building schedule, in which a schedule-performance shortfall triggers the loop and stochastic forecasting exposes an upper-tail completion risk hidden by the deterministic estimate. By establishing a governed pathway from BIM to the previously BIM-isolated COSMOS engine, this work provides a basis from which field-based evaluation of BIM-integrated stochastic project control can proceed.