Using porous metals to enhance heat transfer in phase change materials (PCMs)

Heat transfer enhancement mechanism of Phase Change Materials (PCMs) by high-porosity metal foams was investigated in this study. The Darcy-Brinkman-Forchheimer modified flow model was employed in the numerical simulations to consider the non-Darcy effects in metal foams: viscous flow resistance and inertia flow resistance. Local Non-Thermal Equilibrium (LNTE) model was used to consider the temperature difference between PCM and metal foam. The results showed that in the solid and two-phase zone the heat transfer rate in PCMs was significantly increased by metal foams, whilst in the liquid zone, natural convection was found to be weakened by the large flow resistance of metal foams, despite which the overall heat transfer rate was still higher than the case where metal foams were not used. Metal foams of low porosity and high pore density were found to perform better than the ones of high porosity and low pore density

High-sensitivity Fiber Bragg grating temperature sensor at high temperature

A method of making full use of the durable strain which fiber Bragg grating (FBG) can undertake is presented, which hugely improves the sensitivities of FBG temperature sensors at high temperature. When a sensor is manufactured at room temperature, its FBG should be given a pre-relaxing length according to the temperature it is asked to measure; once the temperature rise to the asked one, its FBG starts to be stretched and it starts to work with high sensitivity. The relationship between the pre-relaxing length and the working temperature is analyzed. In experiments, when the pre-relaxing lengths are 0.2mm、0.5mm、0.6mm, the working temperatures rise 25℃、50℃、61℃, respectively, and the sensitivities are almost the same (675pm/℃). The facts that the experimental results agree well with the theoretical analyses verify this method’s validity

室内植物表型平台及性状鉴定研究进展和展望

Plant phenomics is under rapid development in recent years, a research field that is progressing towards integration, scalability, multi-perceptivity and high-throughput analysis. Through combining remote sensing, Internet of Things (IoT), robotics, computer vision, and artificial intelligence techniques such as machine learning and deep learning, relevant research methodologies, biological applications and theoretical foundation of this research domain have been advancing speedily in recent years. This article first introduces the current trends of plant phenomics and its related progress in China and worldwide. Then, it focuses on discussing the characteristics of indoor phenotyping and phenotypic traits that are suitable for indoor experiments, including yield, quality, and stress related traits such as drought, cold and heat resistance, salt stress, heavy metals, and pests. By connecting key phenotypic traits with important biological questions in yield production, crop quality and Stress-related tolerance, we associated indoor phenotyping hardware with relevant biological applications and their plant model systems, for which a range of indoor phenotyping devices and platforms are listed and categorised according to their throughput, sensor integration, platform size, and applications. Additionally, this article introduces existing data management solutions and analysis software packages that are representative for phenotypic analysis. For example, ISA-Tab and MIAPPE ontology standards for capturing metadata in plant phenotyping experiments, PHIS and CropSight for managing complicated datasets, and Python or MATLAB programming languages for automated image analysis based on libraries such as OpenCV, Scikit-Image, MATLAB Image Processing Toolbox. Finally, due to the importance of extracting meaningful information from big phenotyping datasets, this article pays extra attention to the future development of plant phenomics in China, with suggestions and recommendations for the integration of multi-scale phenotyping data to increase confidence in research outcomes, the cultivation of cross-disciplinary researchers to lead the next-generation plant research, as well as the collaboration between academia and industry to enable world-leading research activities in the near future

Creating the future for a better world

WFF is a grant-making foundation, based in Singapore, but for the world. It provides financial support to a number of organizations and programs related to environmental and social sustainability research. Through these programs, WFF hopes to bring forth a wide range of new technologies for the benefit of the current generation and generations to come. WFF is the first philanthropic foundation in Singapore funded by entrepreneurs from mainland China, and is professionally managed by an international team. This not only highlights globalization in the philanthropy sector, but also reflectsthe central status of Singapore in the global philanthropic domain. WFF is a private foundation. It does not raise funds from public, rather it invites public-spirited and influential Chinese entrepreneurs and professionals to join and lend their strengths to accomplish these great undertakings. WFF's motto, "For Our World, For Our Future", reflects its founders' ambitions and aspirations.This report relates to the 5th Anniversary of WFF, remembering and analyzing the most important projects and prizes organized by the foundation and how it has impacted positevely in society

Evolutionary algorithms in dynamic environments

The file attached to this record is the author's final peer reviewed version.Evolutionary algorithms (EAs) are widely and often used for solving stationary optimization problems where the fitness landscape or objective function does not change during the course of computation. However, the environments of real world optimization problems may fluctuate or change sharply. If the optimization problem is dynamic, the goal is no longer to find the extrema, but to track their progression through the search space as closely as possible. All kinds of approaches that have been proposed to make EAs suitable for the dynamic environments are surveyed, such as increasing diversity, maintaining diversity, memory based approaches, multi-population approaches and so on