Metaheuristic aided structural topology optimization method for heat sink design with low electromagnetic interference.

This study investigates the application of the Metaheuristic Aided Structural Topology Optimization (MASTO) method as a novel approach to address the multiphysics design challenge of creating a heat sink with both high heat conductivity and minimal Electromagnetic Interference (EMI). A distinctive 2D layout with elongated fins is examined for electromagnetic traits, highlighting resonance-related EMI concerns. MASTO proves to be a valuable tool for navigating the complex design space, yielding thoughtfully optimized solutions that harmonize efficient heat dissipation with effective EMI control. By merging simulation findings with practical observations, this study underscores the potential of the MASTO method in achieving effective designs for intricate multiphysics optimization problems. Specifically, the method's capacity to address the complex interplay of heat transfer with convection and the suppression of electromagnetic emissions is showcased. Moreover, the study demonstrates the feasibility of translating these solutions into tangible outcomes through manufacturing processes.

The consumers' response to product design: a narrative review.

This paper reviews the research ideas around consumer response to product design. From the product side, we discuss the most significant design features preferred by average consumers, such as aesthetics and utility. And from the consumer side, we investigate the human factors influencing consumer perceptions. We present the main approaches used to measure the consumer response to product design and summarize the multiple biases that occur during the evaluation. Finally, we present in detail the most commonly used methods to analyze consumer response data and their roles in the design evaluation context. Practitioner Summary: To answer the question: What causes differences in design response? We summarise the research findings related to product design features and human factors. We highlight the biases that can emerge from the measurement approach. And discuss the most common analysis methods used for product design response information.