Directed Energy System Performance Prediction

This book presents a unique and comprehensive introduction to performance prediction of directed energy (DE) systems using mathematical modeling frameworks, with focus on high power radio frequency and high energy laser performance. It provides system designers with a means for predicting DE system performance and measuring the required power levels necessary to neutralize targets including UAVs and other unmanned swarms. The book begins with a systematic and concise overview of DE systems, including its historical roots. You will then learn how to develop effective mathematical models and understand how to use these models to implement safer and efficient use of DE systems in various scenarios. A special section is devoted to examples and attributes of unmanned systems since these are viewed as primary targets suitably disabled by DE systems. There is also an extensive survey of the relevant tools of mathematics and physics for DE systems, together with a series of pertinent references you can follow for further information. The final section of the book outlines potential future research directions that interested researchers are encouraged to pursue. With its exclusive and unmatched coverage of predictive modeling for DE systems and performance, this is an important book for engineers and operators working in the defense industry, including government and private contractors, as well as research practitioners at universities and engineering organizations worldwide working in the field of DE system performance.

State-of-the-Art Approaches to Advance the Large-Scale Green Computing Movement Edited by one of the founders and lead investigator of the Green500 list, The Green Computing Book: Tackling Energy Efficiency at Large Scale explores seminal research in large-scale green computing. It begins with low-level, hardware-based approaches and then traverses up the software stack with increasingly higher-level, software-based approaches. In the first chapter, the IBM Blue Gene team illustrates how to improve the energy efficiency of a supercomputer by an order of magnitude without any system performance loss in parallelizable applications. The next few chapters explain how to enhance the energy efficiency of a large-scale computing system via compiler-directed energy optimizations, an adaptive run-time system, and a general prediction performance framework. The book then explores the interactions between energy management and reliability and describes storage system organization that maximizes energy efficiency and reliability. It also addresses the need for coordinated power control across different layers and covers demand response policies in computing centers. The final chapter assesses the impact of servers on data center costs.