Navid Changizi

TL;DR: A computationally efficient methodology for stress-based topology optimization of steel frame structures with cross-sectional properties that are mapped from I-beam properties is presented.

TL;DR: In this article, a robust stress-based topology optimization methodology for frame structures under geometric uncertainty is proposed, which uses stochastic perturbation method to propagate these uncertainties up to the response level, expressed by the maximum of expected values of von Mises stresses throughout the domain.

TL;DR: In this article, a robust topology optimization algorithm for frame structures in the presence of geometric or material properties uncertainties is proposed, which uses stochastic perturbation method for propagating these uncertainties to the structural response level, measured in terms of compliance and optimizes the expected value plus multiple factors of the standard deviation of the response.

TL;DR: The topology of four frame structures featuring moment-resisting connections and member cross-sectional properties mapped from the American Institute of Steel Construction design manual are optimized with the proposed algorithm to verify its effectiveness in optimizing structural performance while maintaining factors of safety against overall and individual member instabilities.

TL;DR: Sensitivity analyses indicate that cancer cells and adipocytes’ diffusion rates are the most sensitive parameters, followed by influx and diffusion rates of cytotoxic T cells, implying that targeting them is a possible treatment strategy for breast cancer.