Predictive Modeling of Dynamic Processes provides an overview of hydrocode technology, applicable to a variety of industries and areas of engineering design. Covering automotive crash, blast impact, and hypervelocity impact phenomena, this volume offers readers an in-depth explanation of the fundamental code components. Chapters include informative introductions to each topic, and explain the specific requirements pertaining to each predictive hydrocode. Successfully blending crash simulation, hydrocode technology and impact engineering, this volume fills a gap in the current competing literature available.

This book examines the testing and modeling of materials and structures under dynamic loading conditions. Readers get an in-depth analysis of the current mathematical modeling and simulation tools available for a variety of materials, alongside discussions of the benefits and limitations of these tools in industrial design. Following a logical and well organized structure, this volume uniquely combines experimental procedures with numerical simulation, and provides many examples.

This book examines the testing and modeling of materials and structures under dynamic loading conditions. Readers get an in-depth analysis of the current mathematical modeling and simulation tools available for a variety of materials, alongside discussions of the benefits and limitations of these tools in industrial design. Following a logical and well organized structure, this volume uniquely combines experimental procedures with numerical simulation, and provides many examples.

A growing urbanization, an increasing complexity of critical infrastructure and the formation of new threats are new challenges for urban areas and require a sustainable development and a stronger coping capacity with potential adverse events. Sustainability requires a strengthening of resilience. Within this work, an integrated mathematical approach for the quantification of resilience is defined. This method allows a comprehensive evaluation of urban areas and the identification of weak spots. Statistical data are combined with physical models to assess the occurrence of multiple threats and their potential consequences. This risk based assessment is combined with time dependent recovery models to result in a quantity for resilience. Results of this framework can be applied to evaluate the effectiveness of single resilience phases, like prepare, prevent, protect, response and recover. Besides the mathematical formulation, application examples in this work assess exemplarily terroristic threats in urban surroundings with empirical information of historical events and engineering models to assess possible structural damage effects. The comparison of different urban footprints builds the basis for a resilient urban planning process.