Principles Of Extreme Mechanics Xm In Design For Reliability Dfr

Principles of Extreme Mechanics (XM) in Design for Reliability (DfR).

Principles of Extreme Mechanics (XM) in Design for Reliability (DfR)

This book addresses issues pertinent to mechanics and stress generation, especially in recent advanced cases of technology developments, spanning from micrometer interconnects in solar photovoltaics (PV), next-gen energy storage devices to multilayers of nano-scale composites enabling novel stretchable/flexible conductor technologies. In these cases, the mechanics of materials have been pushed to the extreme edges of human knowledge to enable cutting-edge, unprecedented functionalities and technological innovations. Synchrotron X-ray diffraction, in situ small-scale mechanical testing combined with physics-based computational modeling/simulation, has been widely used approaches to probe these mechanics of the materials at their extreme limits due to their recently discovered distinct advantages. The techniques discussed in this manuscript are highlights specially curated from the broad body of work recently reported in the literature, especially ones that the author had led the pursuits at the frontier himself. Extreme stress generation in these advanced material leads to often new failure modes, and hence, the reliability of the final product is directly affected. From the recent topics and various advanced case studies covered in this book, the reader gets an updated knowledge of how new mechanics can and has been applied in Design-for-Reliability (DfR) for some of the latest technological innovations known in our modern world. Further, this also helps in building better designs, which may avoid the pitfalls of the current practiced trends.

AI Techniques for Renewable Source Integration and Battery Charging Methods in Electric Vehicle Applications

Artificial intelligence techniques applied in the power system sector make the prediction of renewable power source generation and demand more efficient and effective. Additionally, since renewable sources are intermittent in nature, it is necessary to predict and analyze the data of input sources. Hence, further study on the prediction and data analysis of renewable energy sources for sustainable development is required. AI Techniques for Renewable Source Integration and Battery Charging Methods in Electric Vehicle Applications focuses on artificial intelligence techniques for the evolving power system field, electric vehicle market, energy storage elements, and renewable energy source integration as distributed generators. Covering key topics such as deep learning, artificial intelligence, and smart solar energy, this premier reference source is ideal for environmentalists, computer scientists, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.