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Adopting large eddy simulation (LES) to simulate the complex flow in turbomachinery is appropriate to overcome the limitation of current Reynolds-Averaged Navier–Stokes modelling and it provides a deeper understanding of the complicated transitional and turbulent flow mechanism; however, the large computational cost limits its application in high Reynolds number flow. This study aims to develop a three-dimensional GPU-enabled parallel-unstructured solver to speed up the high-fidelity LES simulation.

Compared to the central processing units (CPUs), graphics processing units (GPUs) can provide higher computational speed. This work aims to develop a three-dimensional GPU-enabled parallel-unstructured solver to speed up the high-fidelity LES simulation. A set of low-dissipation schemes designed for unstructured mesh is implemented with compute unified device architecture programming model. Several key parameters affecting the performance of the GPU code are discussed and further speed-up can be obtained by analysing the underlying finite volume-based numerical scheme.

The results show that an acceleration ratio of approximately 84 (on a single GPU) for double precision algorithm can be achieved with this unstructured GPU code. The transitional flow inside a compressor is simulated and the computational efficiency has been improved greatly. The transition process is discussed and the role of K-H instability playing in the transition mechanism is verified.

The speed-up gained from GPU-enabled solver reaches 84 compared to original code running on CPU and the vast speed-up enables the fast-turnaround high-fidelity LES simulation.

The GPU-enabled flow solver is implemented and optimized according to the feature of finite volume scheme. The solving time is reduced remarkably and the detail structures including vortices are captured.

In today’s Taiwan, sha-cha sauce is an indispensable ingredient for beef hot pot and stir-fried dishes. The purpose of this paper contextualizes the history of sha-cha sauce in Tainan, the oldest city in Taiwan, and argues that sha-cha sauce, introduced by Chaoshan immigrants, has contributed to new styles and habits of beef consumption tastes and habits in the post-1949 Tainan and beyond.

This paper uses documentary materials, oral interviews and diaries to explore the relationship between beef consumption and sha-cha sauce. It begins with an historical overview of Taiwan’s beef consumption during the Japanese colonial era (1895-1945). Then, it focuses on two Chaoshan business enterprises: the Bull-Head, which makes the world’s largest “canned sha-cha sauce,” and the Xiao Haozhou, a Tainan restaurant specializing in sha-cha beef hot pot. Finally, this study analyzes Xinrong Wu, a Tainan gentry whose diary entries from 1933 to 1967 documented the changing dietary habits of beef consumption among Taiwanese.

The Chaoshan migrants played an important role in introducing the sha-cha sauce to postcolonial Tainan, and this input bolstered the beef consumption among Taiwanese. The production of sha-cha provided a reliable source of income for these migrants in Tainan, and major businesses like the Bull-Head became the international brands of Taiwanese food products.

The study, though limited to Tainan, reveals the symbiosis between popularization of sha-cha sauce and widespread beef consumption in Taiwan.

This study helps researchers examine the connection between Chinese migrations and food culture.

This paper is an original scholarly investigation of the relationship between food diet and Chaoshan migration in postcolonial Tainan.

This study provides a comprehensive overview of the research landscape of Kansei engineering (KE) within the domain of emotional clothing design. It explores the pivotal technologies, challenges and potential future directions of KE, offering application methodologies and theoretical underpinnings to support emotional clothing design.

This study briefly introduces KE, outlining its overarching research methodologies and processes. This framework lays the groundwork for advancing research in clothing Kansei. Subsequently, by reviewing literature from both domestic and international sources, this research initially explores the application of KE in the design and evaluation of clothing products as well as the development of intelligent clothing design systems from the vantage point of designers. Second, it investigates the role of KE in the customization of online clothing recommendation systems and the optimization of retail environments, as perceived by consumers. Finally, with the research methodologies of KE as a focal point, this paper discusses the principal challenges and opportunities currently confronting the field of clothing Kansei research.

At present, studies in the domain of clothing KE have achieved partial progress, but there are still some challenges to be solved in the concept, technical methods and area of application. In the future, multimodal and multisensory user Kansei acquisition, multidimensional product deconstruction, artificial intelligence (AI) enabling KE research and clothing sales environment Kansei design will become new development trends.

This study provides significant directions and concepts in the technology, methods and application types of KE, which is helpful to better apply KE to emotional clothing design.

China's defense industry is analyzed by comparing the technical level of the military and civilian products manufactured by China's nuclear, space, aviation, shipbuilding, ordnance, and electronics industries with their advanced counterparts. Generally, China's defense industry is about 20 years behind the global leaders. Thus, it is inappropriate to declare China's emergence as the world’s second military power. However, if it continues on its current development trajectory, it will attain that status in the near future.