Open Access. Powered by Scholars. Published by Universities.®
- Publication
- Publication Type
Articles 1 - 2 of 2
Full-Text Articles in Engineering
A Simulation–Optimization Framework For Post-Disaster Allocation Of Mental Health Resources, Stephen Cunningham, Steven J. Schuldt, Christopher M. Chini, Justin D. Delorit
A Simulation–Optimization Framework For Post-Disaster Allocation Of Mental Health Resources, Stephen Cunningham, Steven J. Schuldt, Christopher M. Chini, Justin D. Delorit
Faculty Publications
Extreme events, such as natural or human-caused disasters, cause mental health stress in affected communities. While the severity of these outcomes varies based on socioeconomic standing, age group, and degree of exposure, disaster planners can mitigate potential stress-induced mental health outcomes by assessing the capacity and scalability of early, intermediate, and long-term treatment interventions by social workers and psychologists. However, local and state authorities are typically underfunded, understaffed, and have ongoing health and social service obligations that constrain mitigation and response activities. In this research, a resource assignment framework is developed as a coupled-state transition and linear optimization model that …
Data- Driven Asset Degradation Modeling: An Enterprise-Wide Roof System Case Study, Kurt R. Lamm
Data- Driven Asset Degradation Modeling: An Enterprise-Wide Roof System Case Study, Kurt R. Lamm
Theses and Dissertations
Organizations with large facility and infrastructure portfolios have used asset management databases for over ten years to collect and standardize asset condition data. Decision makers use this data to predict asset degradation and expected service life, enabling prioritized maintenance, repair, and renovation actions that reduce asset life-cycle costs and achieve organizational objectives. However, these asset condition forecasts are calculated using standardized, self-correcting distribution models that rely on continuous functions. This research presents four step wise asset condition forecast models that utilize historical asset inspection data to improve prediction accuracy: (1) Slope, (2) Weighted Slope, (3) Condition-intelligent Weighted Slope, and (4) …