ArticleCardiovascular engineering and technology2025
Effects of Implemented Residual Stresses on Mechanical Responses and Behavior of the Full-Layered Murine Aortic Medial Ring: A Parametric Finite Element Study.
Article in Cardiovascular engineering and technology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
purposeIt is known that elastic laminae (ELs) in the aortic wall, especially the inner layers, are structurally buckled due to residual stresses under unpressurized conditions. Herein, we aimed to develop a realistic computational model, replicating the mechanical behavior of an aortic ring from no-load to physiological conditions by considering inherent residual stresses, which has not been widely included in conventional modeling studies.
methodsWe determined specific conditions to reproduce EL buckling with a "preferable" residual stress distribution under no-load conditions by combining the design of experiments and multiobjective optimization. Subsequently, we applied these conditions to two ring models with distinct wall structures comprised ELs and smooth muscle layers (SMLs), and compared their mechanical responses to assess the effect of implemented residual stresses by tracking changes in stress distribution in the aortic wall and corresponding EL waviness under no-load and pressurized conditions.
resultsWe successfully reproduced EL buckling with a steady upward residual stress distribution that was considered "preferable" under no-load conditions. Furthermore, we replicated radially cut ring models that spontaneously opened in vitro, and confirmed that an SML circumferential stress distribution approached a uniform state under pressurized conditions, effectively mediating stress concentrations induced at the inner layers.
conclusionsWe established a ready-to-use scheme to implement intrinsic residual stresses in the aortic wall. Our computational model of the aortic ring, reproducing realistic mechanical responses and behavior, represents a valuable tool that offers essential insights for hypertension prevention and potential new clinical applications.
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