Bøger af Xian Wen Ng

This concise text contains the most commonly-encountered examination problems in the topic of Optimization Models and Methods, an important module in engineering and other disciplines where there exists an increasing need to operate optimally and sustainably under constraints, such as tighter resource availability, environmental consideration, and cost pressures. This book is comprehensive in coverage as it includes a diverse spectrum of problems from numerical open-ended questions that probe creative thinking to the relation of concepts to realistic settings. The book adopts many examples of design scenarios as context for curating sample problems. This will help students relate desktop problem-solving to tackling real-world problems. Succinct yet rigorous, with over a 100 pages of problems and corresponding worked solutions presented in detail, the book is ideal for students of engineering, applied science, and market analysis.

This book provides targeted support for students taking courses at the undergraduate level involving electrochemical methods and voltammetry, precision analytical techniques used in chemical engineering, chemical research and development, and pharmaceutical science.

The book complements other key topics in science and engineering courses well, such as the branch of thermodynamics which relates closely to the core design principles for heat exchanger networks (FThis book serves as an extensive practice manual for the understanding and practice of heat exchanger design fundamentals and principles.

This pocket guide serves as a supplementary learning resource to help students deconstruct challenging problems in the topic of rheology commonly encountered in engineering examinations, as well as those in related courses such as in the STEM disciplines.

This textbook supplement deconstructs some of the most commonly-encountered and challenging problems arising within engineering domains such as thermodynamics, separation processes, chemical kinetics, fluid dynamics, and engineering mathematics that are foundational to most engineering programs, as well as many courses in STEM disciplines.