2026 ASEE Annual Conference & Exposition
Digital Twins for Renovation in Underserved Communities: A Sustainable and Adaptive Framework
Presented at CIT Technical Session 4: Capacity Building, and Skill Development.
A growing housing shortage exists alongside increasing building deterioration, leaving many units vacant or unsafe, while financing stalls due to uncertain conditions. This paper will introduce a digital twin (DT) framework that addresses the main barrier to restoring homes: uncertainty about structural integrity, scope, and post-retrofit performance. The approach will operate under partial observability. The framework is structured as a clear six-stage process: Capture, Assemble, Analyze, Decide, Deliver, and Verify/Operate. A digital twin will be created using exterior/safe-zone capture and typical envelope values, then refined with on-site evidence, and will include screening checks such as structural assessments, moisture analysis, and a brief life-cycle assessment to compare rehabilitation options. For inaccessible spaces, the model will incorporate evidence-based estimations like roofline deviation, out-of-plane drift, crack patterns, damp/thermal anomalies, and construction era, each marked with uncertainty and a plan for ongoing verification.
Analyses will remain decision-focused and easy to interpret. We start with structural stability screening based on geometric change detection and simple rules applied at spans, bearings, and openings. Next, we estimate building performance to project energy use intensity (EUI) and comfort hours. The model begins with standard envelope values of walls, roof, windows, and infiltration, derived from similar buildings from the same period and refined with on-site evidence. Finally, a life-cycle assessment compares retain versus replace options for the structure and envelope, highlighting embodied carbon impacts alongside operational effects. Alternative renovation pathways, such as stabilize-and-occupy, targeted retrofit, or deeper adaptive reuse, will be compared with clear ranges to ensure transparency in trade-offs.
Results will be presented as a concise set of decision artifacts that turn uncertainties into quantifiable, testable assumptions; a scope-of-work map indicating what to keep, fix, or replace; and a risk-to-contingency summary revealing where and why allowances are necessary. Additionally, a plain-language Key Performance Indicator (KPI) scorecard will be used for approval and funding decisions. KPIs will focus on housing outcomes, units restored to safe occupancy, expected cost range, projected timeframe, predicted EUI and comfort, material reuse/waste diversion, and embodied carbon savings from retention. By converting uncertainty into bounded, testable inputs, this framework aims to facilitate renovation decisions, accurately size contingencies, and speed up the return of safe, energy-efficient housing in underserved communities while lowering energy costs and carbon footprint
-
Tolulope Abiri Morgan State University [biography]
-
Ayobami Christianah Dunmoye Morgan State University [biography]
-
Dr. Oludare Adegbola Owolabi P.E. Morgan State University [biography]
The full paper will be available to logged in and registered conference attendees once the conference starts on June 21, 2026, and to all visitors after the conference ends on June 24, 2026