A novel and intelligent product development approach is required in this fast-growing and advanced technological era. Therefore, textile researchers have worked intensively to create efficient and transparent solutions for complex developments by using advanced modeling and simulation tools and techniques. This paper addresses a process for the thermal simulation of sportswear by considering the human thermophysiological model and important thermal properties of fabrics, i.e., thermal resistance, evaporative resistance, and permeability index. The results of the simulation are illustrated in terms of core body and mean skin temperatures. Moreover, results are validated by wear trials showing good consistency. This study is beneficial to the development of clothing for specific sports and the evaluation of comfort and heat stress during different sports activities.
Thermophysiological comfort is one of the most important aspects of wear comfort. Currently, there are no software solutions available for the combined consideration of material physical and mechanical characteristics, fit, and thermophysiological behavior. Thus, a laborious empirical process is typically required to determine an appropriate design matching new textile materials to pattern cuts as well as changing climatic conditions. A detailed wear trial in a climatic chamber supports this process. The objective of this research is to analyze the thermal comfort of clothing with different thermal characteristics through the simulation of heat regulation in the human body, microclimate, clothing, and environment.
Hybrid systems such as Cyber Physical Systems (CPS) are becoming more important with time. Apart from CPS there are many hybrid systems in nature. To perform a simulation based analysis of a hybrid system, a simulation framework is presented, named SAHISim. It is based on the most popular simulation interoperability standards, i.e. High Level Architecture (HLA) and Functional Mock-up Interface (FMI). Being a distributed architecture it is able to execute on cluster, cloud and other distributed topologies. Moreover, as it is based on standards so it allows many different simulation packages to interoperate, making it a flexible and robust solution for simulation based analysis. The underlying algorithm which enables the synchronization of different simulation components is discussed in detail. A test example is presented, whose results are compared to a monolithic simulation of the same model for verification of results.
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