Scientific editing of the Greek edition: Charalampos Barvoglis, Aristotle University of Thessaloniki.

Thermodynamics deals with the study of energy, and energy is the driving force of the modern world. All modern technology relies on thermodynamics, and this will continue to be true for the new technologies of the future. Therefore, it is important for engineers to have a deep understanding of the fundamental principles of thermodynamics, so they can continue to develop technology aimed at improving the world.

The aim of this book is to provide students of polytechnic schools, the future engineers, with an easily understandable introduction to the operation of energy systems and how their performance is affected by changes in their operating parameters. Additionally, the book aims to rectify the weaknesses that characterized the teaching of thermodynamics in the past and includes a balanced presentation of theory and related practical applications.

Special features of the book include, among other things: An accessible presentation of the concepts of thermodynamics and a focus on everything a student needs to learn in order to be able to work as an engineer. Numerous examples and problems of parametric analysis help students gain an intuitive understanding of how thermodynamic systems operate. A large number of diagrams and images make the presentation of the material interesting and enjoyable.

Students are encouraged to develop computational mathematical models of configurations, processes, and energy cycles, and to utilize the plethora of online programs and applications for the easy finding of thermodynamic data.

Contents:

• Problem solving with mathematical models
• Deterministic optimization models in operations research
• Improving search
• Linear programming models
• Simplex search for linear programming
• Duality, sensitivity, and optimality in linear programming
• Interior point methods for linear programming
• Multi-criteria optimization and goal programming
• Shortest paths and discrete dynamic programming
• Network flows and graphs
• Discrete optimization models
• Exact methods for discrete optimization
• Large-scale optimization methods
• Theory of computational complexity
• Heuristic methods for approximate discrete optimization
• Non-linear programming without constraints
• Non-linear programming with constraints – Appendices: (Group projects, Answers to selected exercises).