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Date of Award
2025
Document Type
Campus Access Master's Report
Degree Name
Master of Science in Civil Engineering (MS)
Administrative Home Department
Department of Civil, Environmental, and Geospatial Engineering
Advisor 1
Raymond A. Swartz
Committee Member 1
Qingli Dai
Committee Member 2
Daniel M. Dowden
Abstract
Roof collapses due to excessive loads pose a significant structural concern in cold regions often leading to property damage, financial loss and life-threatening situations. Roof geometry plays a crucial role on how snow accumulate and how structures respond under extreme conditions. Traditional monitoring methods rely on visual inspections and seasonal snowfall estimate, which often fail to capture real time structural response leading to unexpected failures. To address this limitation, the study proposes the development of a strain based early warning system that utilizes the axial capacity of timber roof trusses to monitor the performance of roof trusses under snow loads.
The study examines the influence of architectural styles, truss configuration, material variability and snow load magnitude on the structural response of timber truss. Different roof designs interact with snow accumulation in different ways, influencing load distribution and failure risks. Through Monte Carlo simulation, the study evaluates how strain monitoring can be optimized for both balanced and unbalanced snow loads. A threshold based on the axial capacity of critical member is proposed incorporating safety factors that adjust the nominal strength of the member.
Findings indicate that a fixed threshold is insufficient for ensuring a reliable detection across varying structural and environmental conditions. Higher material variability increases the likelihood of missed alarms. The results emphasize the need for an adaptive warning system that capable of distinguishing between safe high load condition and impending failure. By integrating architectural design consideration, real time strain monitoring and reliability-based threshold selection, the study contributes to development of proactive structural health monitoring solution for snow prone regions.
Recommended Citation
Mensah, Caleb Kwadwo Osei, "DEVELOPMENT OF A PROTOTYPE FOR AN EARLY ALERT SYSTEM THAT MEASURES STRAINS IN TIMBER ROOF TRUSS MEMBERS", Campus Access Master's Report, Michigan Technological University, 2025.