The energy, petrochemical, aerospace and other industries all require materials able to withstand high temperatures. High temperature strength is defined as the resistance of a material to high temperature deformation and fracture. This important book provides a valuable reference to the main theories of high temperature deformation and fracture and the ways they can be used to predict failure and service life.
Analyses creep behaviour of materials, the evolution of dislocation substructures during creep, dislocation motion at elevated temperatures and importantly, recovery-creep theories of pure metalsExamines high temperature fracture, including nucleation of creep cavity, diffusional growth and constrained growth of creep cavitiesA valuable reference to the main theories of high temperature deformation and fracture and the ways they can be used to predict failure and service life

This book introduces wireless traffic steering as a paradigm to realize green communication in multi-tier heterogeneous cellular networks. By matching network resources and dynamic mobile traffic demand, traffic steering helps to reduce on-grid power consumption with on-demand services provided. This book reviews existing solutions from the perspectives of energy consumption reduction and renewable energy harvesting. Specifically, it explains how traffic steering can improve energy efficiency through intelligent traffic-resource matching. Several promising traffic steering approaches for dynamic network planning and renewable energy demand-supply balancing are discussed. This book presents an energy-aware traffic steering method for networks with energy harvesting, which optimizes the traffic allocated to each cell based on the renewable energy status. Renewable energy demand-supply balancing is a key factor in energy dynamics, aimed at enhancing renewable energy sustainability to reduce on-grid energy consumption. Dynamic network planning adjusts cell density with traffic variations to provide on-demand service, which reduces network power consumption with quality of service provisioning during off-peak hours. With intra- or inter-tier traffic steering, cell density is dynamically optimized with regards to the instant traffic load for conventional homogeneous and multi-tier heterogeneous cellular networks, respectively. This book is beneficial for researchers and graduate students interested in traffic management and future wireless networking.

This SpringerBrief presents spatio-temporal data analytics for wind energy integration using stochastic modeling and optimization methods. It explores techniques for efficiently integrating renewable energy generation into bulk power grids. The operational challenges of wind, and its variability are carefully examined. A spatio-temporal analysis approach enables the authors to develop Markov-chain-based short-term forecasts of wind farm power generation. To deal with the wind ramp dynamics, a support vector machine enhanced Markov model is introduced. The stochastic optimization of economic dispatch (ED) and interruptible load management are investigated as well. Spatio-Temporal Data Analytics for Wind Energy Integration is valuable for researchers and professionals working towards renewable energy integration. Advanced-level students studying electrical, computer and energy engineering should also find the content useful.

This book introduces wireless traffic steering as a paradigm to realize green communication in multi-tier heterogeneous cellular networks. By matching network resources and dynamic mobile traffic demand, traffic steering helps to reduce on-grid power consumption with on-demand services provided. This book reviews existing solutions from the perspectives of energy consumption reduction and renewable energy harvesting. Specifically, it explains how traffic steering can improve energy efficiency through intelligent traffic-resource matching. Several promising traffic steering approaches for dynamic network planning and renewable energy demand-supply balancing are discussed. This book presents an energy-aware traffic steering method for networks with energy harvesting, which optimizes the traffic allocated to each cell based on the renewable energy status. Renewable energy demand-supply balancing is a key factor in energy dynamics, aimed at enhancing renewable energy sustainability to reduce on-grid energy consumption. Dynamic network planning adjusts cell density with traffic variations to provide on-demand service, which reduces network power consumption with quality of service provisioning during off-peak hours. With intra- or inter-tier traffic steering, cell density is dynamically optimized with regards to the instant traffic load for conventional homogeneous and multi-tier heterogeneous cellular networks, respectively. This book is beneficial for researchers and graduate students interested in traffic management and future wireless networking.

This SpringerBrief explains how to leverage mobile users' social relationships to improve the interactions of mobile devices in mobile networks. It develops a social group utility maximization (SGUM) framework that captures diverse social ties of mobile users and diverse physical coupling of mobile devices. Key topics include random access control, power control, spectrum access, and location privacy. This brief also investigates SGUM-based power control game and random access control game, for which it establishes the socially-aware Nash equilibrium (SNE). It then examines the critical SGUM-based spectrum access game, and pseudonym change game for personalized location privacy. The authors propose future work on extending the SGUM framework to negative social ties, to demonstrate relevance to security applications and span the continuum between zero-sum game (ZSG) and non-cooperative game (NCG). Social Group Utility Maximization targets researchers and professionals working on mobile networks and social networks. Advanced-level students in electrical engineering and computer science will also find this material useful for their related courses.