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Zhang Hao: Mechanical Equipment
Mechanism Design

Mechanical Equipment Mechanism Design

100 Cases

A guide to the retro-tech we loved and lost

Gizmo

Smart Technologies and Digital Transformation in Additive Manufacturing

Woodhead Publishing Series in Welding and Other Joining Technologies

Mechanical Joining by Material Flow provides sought-after experimental information on process design, process modeling, and joint characterization techniques for students, researchers, and engineering professionals who want to learn about advanced joining systems for lightweight materials. Chapters cover mechanical joining by plastic deformation, including clinching and self-piercing riveting, and friction-based processes, such as friction stir welding to form a mechanical joint. Though these processes are mainly used to establish metallurgical bonding, their unique characteristics and the material flow they generate has led to an increased use of these techniques for joining difficult-to-weld materials. Other sections introduce innovative technologies developed based on material flow to meet existing industry needs to join materials with different structural properties in different scales or shapes. To furnish readers with a more usefully comprehensive coverage, the team of experts behind the book has included methodological principles as well as discussions on advantages, drawbacks, and future directions of each technique, alongside application examples and case studies.

Mechanical Joining by Material Flow

Power, Conflict, and Possibilities

Atlas of Green Energy Transitions

Design, Science and Engineering of How Things are Made

Manufacturing

Urban and Industrial Environments

Nature, Trade, and Power in the Race for Lithium

Living Minerals

A Design Oriented Approach using MATLAB

Elements of Mechatronic Systems

Human Factors in Design, Engineering, and Computing

Modern Technologies in Ergonomics and Workplace Safety

Woodhead Publishing Series in Civil and Structural Engineering

Emerging Concepts and Technologies

Net Zero Transition in Buildings

Underground Hydrogen Storage: Prospects, Opportunities, and Challenges presents a comprehensive analysis of the technical and economic aspects of underground hydrogen storage. In addition to providing a detailed examination of the fundamentals, properties, storage options, reaction kinetics, modeling, and economics of underground hydrogen storage, the book offers pragmatic solutions to the demand-supply gap caused by conventional hydrogen storage systems and intermittency challenges associated with renewable energy sources. In addition, users will find this to be a foundational introduction to underground hydrogen storage and a detailed review of the properties of hydrogen. Other sections are dedicated to depleted gas reservoirs, oil reservoirs, aquifers (including saline aquifers), salt caverns, coal mines, lined hard rock caverns, and refrigerated mined caverns. Influencing parameters such as permeability, density and viscosity, interfacial tension and surface tension, wettability, capillary pressure, absorption, desorption, solubility, and diffusivity are also covered as are reaction kinetics, including methanogenesis, acetogenesis, sulphate reduction, and iron reduction, and much more.

Prospects, Opportunities, and Challenges

Underground Hydrogen Storage

Expert reference on building surrogate models, optimization using them, prediction uncertainty associate with them, and their potential failure, with practical implementation in MATLAB Surrogate Modeling and Optimization explains the meaning of different surrogate models and provides an in-depth understanding of such surrogates, emphasizing how much uncertainty is associated with them, and when and how a surrogate model can fail in approximating complex functions and helping readers understand theory through practical implementation in MATLAB. This book enables readers to obtain an accurate approximate function using as few samples as possible, thereby allowing them to replace expensive computer simulations and experiments during design optimization, sensitivity analysis, and/or uncertainty quantification. The book is organized into three parts. Part I introduces the basics of surrogate modeling. Part II reviews various theories and algorithms of design optimization. Part III presents advanced topics in surrogate modeling, including the Kriging surrogate, neural network models, multi-fidelity surrogates, and efficient global optimization using Kriging surrogates. The book is divided into 10 chapters. Each chapter contains about 10 examples and 20 exercise problems. Lecture slides and a solution manual for exercise problems are available for instructors on a companion website. Sample topics discussed in Surrogate Modeling and Optimization include: <ul> <li>Various designs of experiments, such as those developed for linear and quadratic polynomial response surfaces (PRS) in a boxlike design space</li> <li>Criteria for constrained and unconstrained optimization and the most important optimization theories</li> <li>Various numerical algorithms for gradient-based optimization</li> <li>Gradient-free optimization algorithms, often referred to as global search algorithms, which do not require gradient or Hessian information</li> <li>Detailed explanations and implementation on Kriging surrogate, often referred to as Gaussian Process, especially when samples include noise</li> <li>The combination of a small number of high-fidelity samples with many low-fidelity samples to improve prediction accuracy</li> <li>Neural network models, focusing on training uncertainty and its effect on prediction uncertainty</li> <li>Efficient global optimization using either polynomial response surfaces or Kriging surrofates</li> </ul> Surrogate Modeling and Optimization is an essential learning companion for senior-level undergraduate and graduate students in all engineering disciplines, including mechanical, aerospace, civil, biomedical, and electrical engineering. The book is also valuable for industrial practitioners who apply the surrogate model to solve their optimization problems.

Theories, Applications, and Limitations

Surrogate Modeling and Optimization

Smart Innovations and Technological Advancements in Mechanical and Materials Engineering

Technology, and Applications

Digital Manufacturing of Bioimplants

Mechanical Equipment Mechanism Design

Weitere Titel zum Thema