Probability Concepts In Engineering Planning And D

Apply the principles of probability and statistics to realistic engineering problems The easiest and most effective way to learn the principles of probabilistic modeling and statistical inference is to apply those principles to a variety of applications. That’s why Ang and Tang’s Second Edition of Probability Concepts in Engineering (previously titled Probability Concepts in Engineering Planning and Design) explains concepts and methods using a wide range of problems related to engineering and the physical sciences, particularly civil and environmental engineering. Now extensively revised with new illustrative problems and new and expanded topics, this Second Edition will help you develop a thorough understanding of probability and statistics and the ability to formulate and solve real-world problems in engineering. The authors present each basic principle using different examples, and give you the opportunity to enhance your understanding with practice problems. The text is ideally suited for students, as well as those wishing to learn and apply the principles and tools of statistics and probability through self-study. Key Features in this 2nd Edition: A new chapter (Chapter 5) covers Computer-Based Numerical and Simulation Methods in Probability, to extend and expand the analytical methods to more complex engineering problems. New and expanded coverage includes distribution of extreme values (Chapter 3), the Anderson-Darling method for goodness-of-fit test (Chapter 6), hypothesis testing (Chapter 6), the determination of confidence intervals in linear regression (Chapter 8), and Bayesian regression and correlation analyses (Chapter 9). Many new exercise problems in each chapter help you develop a working knowledge of concepts and methods. Provides a wide variety of examples, including many new to this edition, to help you learn and understand specific concepts. Illustrates the formulation and solution of engineering-type probabilistic problems through computer-based methods, including developing computer codes using commercial software such as MATLAB and MATHCAD. Introduces and develops analytical probabilistic models and shows how to formulate engineering problems under uncertainty, and provides the fundamentals for quantitative risk assessment.

This new edition of a classic text has now been extensively updated to include the latest developments in risk analysis and water quality assessment and management. It takes into account the role of ecological water quality in integrated regional and transboundary water resources management, according to the latest UNESCO programmes and the new EU-Water Framework Directive. This practice-oriented textbook is a unique tool for identifying and evaluating local and regional environmental risks from pollution hazards in groundwater, river water and coastal seawaters. The book explains different risk-based probabilistic methodologies and fuzzy logic-based approaches and includes various mathematical models for water quality simulation and theories, such as the decision analysis, the utility theory and the integrated risk-based multi-criteria assessment and management, in order to thoroughly evaluate several case studies from the real world. Questions testing the reader?s understanding are given at the end of each chapter, and a useful appendix provides hints for answering them as well the solutions themselves.

Reliability-based design is the only engineering methodology currently available which can ensure self-consistency in both physical and probabilistic terms. It is also uniquely compatible with the theoretical basis underlying other disciplines such as structural design. It is especially relevant as geotechnical design becomes subject to increasing codification and to code harmonization across national boundaries and material types. Already some codes of practice describe the principles and requirements for safety, serviceability, and durability of structures in reliability terms. This book presents practical computational methods in concrete steps that can be followed by practitioners and students. It also provides geotechnical examples illustrating reliability analysis and design. It aims to encourage geotechnical engineers to apply reliability-based design in a realistic context that recognises the complex variabilities in geomaterials and model uncertainties arising from a profession steeped in empiricism. By focusing on learning through computations and examples, this book serves as a valuable reference for engineers and a resource for students.

Statistics and Probability for Engineering Applications provides a complete discussion of all the major topics typically covered in a college engineering statistics course. This textbook minimizes the derivations and mathematical theory, focusing instead on the information and techniques most needed and used in engineering applications. It is filled with practical techniques directly applicable on the job. Written by an experienced industry engineer and statistics professor, this book makes learning statistical methods easier for today's student. This book can be read sequentially like a normal textbook, but it is designed to be used as a handbook, pointing the reader to the topics and sections pertinent to a particular type of statistical problem. Each new concept is clearly and briefly described, whenever possible by relating it to previous topics. Then the student is given carefully chosen examples to deepen understanding of the basic ideas and how they are applied in engineering. The examples and case studies are taken from real-world engineering problems and use real data. A number of practice problems are provided for each section, with answers in the back for selected problems. This book will appeal to engineers in the entire engineering spectrum (electronics/electrical, mechanical, chemical, and civil engineering); engineering students and students taking computer science/computer engineering graduate courses; scientists needing to use applied statistical methods; and engineering technicians and technologists. * Filled with practical techniques directly applicable on the job * Contains hundreds of solved problems and case studies, using real data sets * Avoids unnecessary theory

Today's business environment involves design decisions with significant uncertainty. To succeed, decision-makers should replace deterministic methods with a risk-based approach that accounts for the decision maker’s risk tolerance. In many problems, it is impractical to collect data because rare or one-time events are involved. Therefore, we need a methodology to model uncertainty and make choices when we have limited information. This methodology must use all available information and rely only on assumptions that are supported by evidence. This book explains theories and tools to represent uncertainty using both data and expert judgment. It teaches the reader how to make design or business decisions when there is limited information with these tools. Readers will learn a structured, risk-based approach, which is based on common sense principles, for design and business decisions. These decisions are consistent with the decision-maker’s risk attitude. The book is exceptionally suited as educational material because it uses everyday language and real-life examples to elucidate concepts. It demonstrates how these concepts touch our lives through many practical examples, questions and exercises. These are designed to help students learn that first they should understand a problem and then establish a strategy for solving it, instead of using trial-and-error approaches. This volume is intended for undergraduate and graduate courses in mechanical, civil, industrial, aerospace, and ocean engineering and for researchers and professionals in these disciplines. It will also benefit managers and students in business administration who want to make good decisions with limited information.

The proceedings of this conference contain keynote addresses on recent developments in geotechnical reliability and limit state design in geotechnics. It also contains invited lectures on such topics as modelling of soil variability, simulation of random fields and probability of rock joints. Contents: Keynote addresses on recent development on geotechnical reliability and limit state design in geotechnics, and invited lectures on modelling of soil variability, simulation of random field, probabilistic of rock joints, and probabilistic design of foundations and slopes. Other papers on analytical techniques in geotechnical reliability, modelling of soil properties, and probabilistic analysis of slopes, embankments and foundations.

This book is based on the contributions of several authors and attempts to describe the roles human activities play in causing geohazards either directly or indirectly through man-made climate change. The risk of these man-made geohazards and the risk assessment are also discussed in this book. Each chapter keeps the authors' notations that vary from chapter to chapter. These authors' notations have been maintained to reduce unintended confusion and errors. Readers should be aware of this variation.

Proceedings of the NATO Advanced Research Workshop on Coping with Flash Floods: Lessons Learned from Experience, Malenovice, Czech Republic, May 16-21, 1999

With the expansion of new technologies, materials, and the design of complex systems, the expectations of society upon engineers are becoming larger than ever. Engineers make critical decisions with potentially high adverse consequences. The current political, societal, and financial climate requires engineers to formally consider the factors of uncertainty (e.g., floods, earthquakes, winds, environmental risks) in their decisions at all levels. Uncertainty Modeling and Analysis in Civil Engineering provides a thorough report on the immediate state of uncertainty modeling and analytical methods for civil engineering systems, presenting a toolbox for solving problems in real-world situations. Topics include Neural networks Genetic algorithms Numerical modeling Fuzzy sets and operations Reliability and risk analysis Systems control Uncertainty in probability estimates This compendium is a considerable reference for civil engineers as well as for engineers in other disciplines, computer scientists, general scientists, and students.

Transportation Engineering: Theory, Practice and Modeling, Second Edition presents comprehensive information related to traffic engineering and control, transportation planning and evaluation of transportation alternatives. The book systematically deals with almost the entire transportation engineering area, offering various techniques related to transportation modeling, transportation planning, and traffic control. It also shows readers how to use models and methods when predicting travel and freight transportation demand, how to analyze existing transportation networks, how to plan for new networks, and how to develop traffic control tactics and strategies. New topics addressed include alternative Intersections, alternative interchanges and individual/private transportation. Readers will also learn how to utilize a range of engineering concepts and methods to make future transportation systems safer, more cost-effective, and "greener". Providing a broad view of transportation engineering, including transport infrastructure, control methods and analysis techniques, this new edition is for postgraduates in transportation and professionals needing to keep up-to-date with the latest theories and models. Covers all forms of transportation engineering, including air, rail, road and public transit modes Examines different transportation modes and how to make them sustainable Features a new chapter covering the reliability, resilience, robustness and vulnerability of transportation systems

Introduction to Reliability Engineering A complete revision of the classic text on reliability engineering, written by an expanded author team with increased industry perspective Introduction to Reliability Engineering provides a thorough and well-balanced overview of the fundamental aspects of reliability engineering and describes the role of probability and statistical analysis in predicting and evaluating reliability in a range of engineering applications. Covering both foundational theory and real-world practice, this classic textbook helps students of any engineering discipline understand key probability concepts, random variables and their use in reliability, Weibull analysis, system safety analysis, reliability and environmental stress testing, redundancy, failure interactions, and more. Extensively revised to meet the needs of today’s students, the Third Edition fully reflects current industrial practices and provides a wealth of new examples and problems that now require the use of statistical software for both simulation and analysis of data. A brand-new chapter examines Failure Modes and Effects Analysis (FMEA) and the Reliability Testing chapter has been greatly expanded, while new and expanded sections cover topics such as applied probability, probability plotting with software, the Monte Carlo simulation, and reliability and safety risk. Throughout the text, increased emphasis is placed on the Weibull distribution and its use in reliability engineering. Presenting students with an interdisciplinary perspective on reliability engineering, this textbook: Presents a clear and accessible introduction to reliability engineering that assumes no prior background knowledge of statistics and probability Teaches students how to solve problems involving reliability data analysis using software including Minitab and Excel Features new and updated examples, exercises, and problems sets drawn from a variety of engineering fields Includes several useful appendices, worked examples, answers to selected exercises, and a companion website Introduction to Reliability Engineering, Third Edition remains the perfect textbook for both advanced undergraduate and graduate students in all areas of engineering and manufacturing technology.

This book presents the latest research findings in the field of maintenance and safety of aging infrastructure. The invited contributions provide an overview of the use of advanced computational and/or experimental techniques in damage and vulnerability assessment as well as maintenance and retrofitting of aging structures and infrastructures such

This volume contains thirty-one papers presented at the Twelfth Scientific Meeting of the IFIP Working Group on Reliability and Optimization of Structural Systems which took place in Aalborg, Denmark, from May 22-25, 2005. The Working Group Conference was organized by the IFIP (International Federation for Information Processing) Working Group 7.5 of the Technical Committee on Modelling and Optimization. The purpose of the Working Group is to promote modern structural system reliability and optimization theory and its applications, to stimulate research, development and application of structural system reliability and optimization theory, to assist and advance research and development in these fields, to further the dissemination and exchange of information on reliability and optimization of structural systems, and to encourage education in structural system reliability and optimization theory.

The focus of this book is aimed at providing a mechanism to determine the individual and cumulative contribution of portfolio components to strategic objectives so that the right decisions can be made regarding those components. Project portfolio management (PfM) is a critically important discipline, which organizations must embrace in order to extract the maximum value from their project investments. Essentially, PfM can be defined as the translation of strategy and organizational objectives into projects, programs, and operations (portfolio components); the allocation of resources to portfolio components according to organizational priorities; alignment of components to one or more organizational objectives and the management and control of these components in order to achieve organizational objectives and benefits. The interest and contribution to the body of knowledge in project portfolio management has been growing significantly in recent years, however, a particular area of concern is the decision-making, during the management of the portfolio, regarding which portfolio components to accelerate, suspend, or terminate. Failing to determine how the individual and cumulative components of a portfolio contribute to an organization’s strategic objectives leads to poorly informed decisions that negate the positive effect that a sound understanding of project portfolio management could have in an organization.

Health Monitoring of Bridges prepares the bridge engineering community for the exciting new technological developments happening in the industry, offering the benefit of much research carried out in the aerospace and other industrial sectors and discussing the latest methodologies available for the management of bridge stock. Health Monitoring of Bridges: Includes chapters on the hardware used in health monitoring, methodologies, applications of these methodologies (materials, methods, systems and functions), decision support systems, damage detection systems and the rating of bridges and methods of risk assessment. Covers both passive and active monitoring approaches. Offers directly applicable methods and as well as prolific examples, applications and references. Is authored by a world leader in the development of health monitoring systems. Includes free software that can be downloaded from http://www.samco.org/ and provides the raw data of benchmark projects and the key results achieved. This book provides a comprehensive guide to all aspects of the structural health monitoring of bridges for engineers involved in all stages from concept design to maintenance. It will also appeal to researchers and academics within the civil engineering and structural health monitoring communities.