Curtis Smith – författare

Risk-informed Methods and Applications in Nuclear and Energy Engineering: Modelling, Experimentation, and Validation presents a comprehensive view of the latest technical approaches and experimental capabilities in nuclear energy engineering. Based on Idaho National Laboratory's popular summer school series, this book compiles a collection of entries on the cutting-edge research and knowledge presented by proponents and developers of current and future nuclear systems, focusing on the connection between modelling and experimental approaches. Included in this book are key topics such as probabilistic concepts for risk analysis, the survey of legacy reliability and risk analysis tools, and newly developed tools supporting dynamic probabilistic risk-assessment.

This book is an insightful and inspiring compilation of work from top nuclear experts from INL. Industry professionals, researchers and academics working in nuclear engineering, safety, operations and training will gain a board picture of the current state-of-practice and be able to apply that to their own risk-assessment studies.

Through compelling ethnography, Homelessness and Housing Advocacy: The Role of Red-Tape Warriors reveals the creative and ambitious methods that social service providers use to house their clients despite the conflictual conditions posed by the policies and institutions that govern the housing process.

Combining in-depth interviews, extensive fieldwork, and the author’s own professional experience, this book considers the perspective of social service providers who work with people experiencing homelessness and chronicles the steps they take to navigate the housing process. With assertive methods of worker-client advocacy at the center of its focus, this book beckons attention to the many variables that affect professional attempts to house homeless populations. It conveys the challenges that social service providers encounter while fitting their clients into the criteria for housing eligibility, the opposition they receive, and the innovative approaches they ultimately take to optimize housing placements for their clients who are, or were formerly, experiencing homelessness.

Weaving as it does between issues of poverty, social inequality, and social policy, Homelessness and Housing Advocacy will appeal to courses in social work, sociology, and public policy and fill a void for early-career professionals in housing and community services.

Through compelling ethnography, Homelessness and Housing Advocacy: The Role of Red-Tape Warriors reveals the creative and ambitious methods that social service providers use to house their clients despite the conflictual conditions posed by the policies and institutions that govern the housing process.

Combining in-depth interviews, extensive fieldwork, and the author’s own professional experience, this book considers the perspective of social service providers who work with people experiencing homelessness and chronicles the steps they take to navigate the housing process. With assertive methods of worker-client advocacy at the center of its focus, this book beckons attention to the many variables that affect professional attempts to house homeless populations. It conveys the challenges that social service providers encounter while fitting their clients into the criteria for housing eligibility, the opposition they receive, and the innovative approaches they ultimately take to optimize housing placements for their clients who are, or were formerly, experiencing homelessness.

Weaving as it does between issues of poverty, social inequality, and social policy, Homelessness and Housing Advocacy will appeal to courses in social work, sociology, and public policy and fill a void for early-career professionals in housing and community services.

Bayesian Inference for Probabilistic Risk Assessment provides a Bayesian foundation for framing probabilistic problems and performing inference on these problems. Inference in the book employs a modern computational approach known as Markov chain Monte Carlo (MCMC). The MCMC approach may be implemented using custom-written routines or existing general purpose commercial or open-source software. This book uses an open-source program called OpenBUGS (commonly referred to as WinBUGS) to solve the inference problems that are described. A powerful feature of OpenBUGS is its automatic selection of an appropriate MCMC sampling scheme for a given problem. The authors provide analysis “building blocks” that can be modified, combined, or used as-is to solve a variety of challenging problems.

The MCMC approach used is implemented via textual scripts similar to a macro-type programming language. Accompanying most scripts is a graphical Bayesian network illustrating the elements of the script and the overall inference problem being solved. Bayesian Inference for Probabilistic Risk Assessment also covers the important topics of MCMC convergence and Bayesian model checking.

Bayesian Inference for Probabilistic Risk Assessment is aimed at scientists and engineers who perform or review risk analyses. It provides an analytical structure for combining data and information from various sources to generate estimates of the parameters of uncertainty distributions used in risk and reliability models.