Over the last fifty years, the ability to carry out analysis as a precursor to decision making in engineering design has increased dramatically. In particular, the advent of modern computing systems and the development of advanced numerical methods have made computational modelling a vital tool for producing optimized designs. This text explores how computer-aided analysis has revolutionized aerospace engineering, providing a comprehensive coverage of the latest technologies underpinning advanced computational design. Worked case studies and over 500 references to the primary research literature allow the reader to gain a full understanding of the technology, giving a valuable insight into the world’s most complex engineering systems. Key Features: Includes background information on the history of aerospace design and established optimization, geometrical and mathematical modelling techniques, setting recent engineering developments in a relevant context. Examines the latest methods such as evolutionary and response surface based optimization, adjoint and numerically differentiated sensitivity codes, uncertainty analysis, and concurrent systems integration schemes using grid-based computing. Methods are illustrated with real-world applications of structural statics, dynamics and fluid mechanics to satellite, aircraft and aero-engine design problems. Senior undergraduate and postgraduate engineering students taking courses in aerospace, vehicle and engine design will find this a valuable resource. It will also be useful for practising engineers and researchers working on computational approaches to design.

Computational Approaches in Physics reviews computational schemes which are used in the simulations of physical systems. These range from very accurate ab initio techniques up to coarse-grained and mesoscopic schemes. The choice of the method is based on the desired accuracy and computational efficiency. A bottom-up approach is used to present the various simulation methods used in Physics, starting from the lower level and the most accurate methods, up to particle-based ones. The book outlines the basic theory underlying each technique and its complexity, addresses the computational implications and issues in the implementation, as well as present representative examples. A link to the most common computational codes, commercial or open source is listed in each chapter. The strengths and deficiencies of the variety of techniques discussed in this book are presented in detail and visualization tools commonly used to make the simulation data more comprehensive are also discussed. In the end, specific techniques are used as bridges across different disciplines. To this end, examples of different systems tackled with the same methods are presented. The appendices include elements of physical theory which are prerequisites in understanding the simulation methods.

This book presents recently developed computational approaches for the study of reactive materials under extreme physical and thermodynamic conditions. It delves into cutting edge developments in simulation methods for reactive materials, including quantum calculations spanning nanometer length scales and picosecond timescales, to reactive force fields, coarse-grained approaches, and machine learning methods spanning microns and nanoseconds and beyond. These methods are discussed in the context of a broad range of fields, including prebiotic chemistry in impacting comets, studies of planetary interiors, high pressure synthesis of new compounds, and detonations of energetic materials. The book presents a pedagogical approach for these state-of-the-art approaches, compiled into a single source for the first time. Ultimately, the volume aims to make valuable research tools accessible to experimentalists and theoreticians alike for any number of scientific efforts, spanning many different types of compounds and reactive conditions.

Semantic change — how the meanings of words change over time — has preoccupied scholars since well before modern linguistics emerged in the late 19th and early 20th century, ushering in a new methodological turn in the study of language change. Compared to changes in sound and grammar, semantic change is the least understood. Ever since, the study of semantic change has progressed steadily, accumulating a vast store of knowledge for over a century, encompassing many languages and language families. Historical linguists also early on realized the potential of computers as research tools, with papers at the very first international conferences in computational linguistics in the 1960s. Such computational studies still tended to be small-scale, method-oriented, and qualitative. However, recent years have witnessed a sea-change in this regard. Big-data empirical quantitative investigations are now coming to the forefront, enabled by enormous advances in storage capability and processing power. Diachronic corpora have grown beyond imagination, defying exploration by traditional manual qualitative methods, and language technology has become increasingly data-driven and semantics-oriented. These developments present a golden opportunity for the empirical study of semantic change over both long and short time spans. A major challenge presently is to integrate the hard-earned knowledge and expertise of traditional historical linguistics with cutting-edge methodology explored primarily in computational linguistics. The idea for the present volume came out of a concrete response to this challenge. The 1st International Workshop on Computational Approaches to Historical Language Change (LChange'19), at ACL 2019, brought together scholars from both fields. This volume offers a survey of this exciting new direction in the study of semantic change, a discussion of the many remaining challenges that we face in pursuing it, and considerably updated and extended versions of a selection of the contributions to the LChange'19 workshop, addressing both more theoretical problems — e.g., discovery of "laws of semantic change" — and practical applications, such as information retrieval in longitudinal text archives.

This volume of original chapters written by experts in the field offers a snapshot of how historical built spaces, past cultural landscapes, and archaeological distributions are currently being explored through computational social science. It focuses on the continuing importance of spatial and spatio-temporal pattern recognition in the archaeological record, considers more wholly model-based approaches that fix ideas and build theory, and addresses those applications where situated human experience and perception are a core interest. Reflecting the changes in computational technology over the past decade, the authors bring in examples from historic and prehistoric sites in Europe, Asia, and the Americas to demonstrate the variety of applications available to the contemporary researcher.

Computational Approaches for Understanding Dynamical Systems: Protein Folding and Assembly, Volume 170 in the Progress in Molecular Biology and Translational Science series, provides the most topical, informative and exciting monographs available on a wide variety of research topics. The series includes in-depth knowledge on the molecular biological aspects of organismal physiology, with this release including chapters on Pairwise-Additive and Polarizable Atomistic Force Fields for Molecular Dynamics Simulations of Proteins, Scale-consistent approach to the derivation of coarse-grained force fields for simulating structure, dynamics, and thermodynamics of biopolymers, Enhanced sampling and free energy methods, and much more. Includes comprehensive coverage on molecular biology Presents ample use of tables, diagrams, schemata and color figures to enhance the reader's ability to rapidly grasp the information provided Contains contributions from renowned experts in the field

The development of materials for clean and efficient energy generation and storage is one of the most rapidly developing, multi-disciplinary areas of contemporary science, driven primarily by concerns over global warming, diminishing fossil-fuel reserves, the need for energy security, and increasing consumer demand for portable electronics. Computational methods are now an integral and indispensable part of the materials characterisation and development process. Computational Approaches to Energy Materials presents a detailed survey of current computational techniques for the development and optimization of energy materials, outlining their strengths, limitations, and future applications. The review of techniques includes current methodologies based on electronic structure, interatomic potential and hybrid methods. The methodological components are integrated into a comprehensive survey of applications, addressing the major themes in energy research. Topics covered include: • Introduction to computational methods and approaches • Modelling materials for energy generation applications: solar energy and nuclear energy • Modelling materials for storage applications: batteries and hydrogen • Modelling materials for energy conversion applications: fuel cells, heterogeneous catalysis and solid-state lighting • Nanostructures for energy applications This full colour text is an accessible introduction for newcomers to the field, and a valuable reference source for experienced researchers working on computational techniques and their application to energy materials.