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The electrification of powertrains is rising as the objective for a more viable future is intensified. To ensure continuous and reliable operation without undesirable malfunctions, it is essential to monitor the internal temperatures of…
Deep learning is having a tremendous impact in many areas of computer science and engineering. Motivated by this success, deep neural networks are attracting an increasing attention in many other disciplines, including physical sciences. In…
The recent technological advances in digitalization have revolutionized the industrial sector. Leveraging data analytics has now enabled the collection of deep insights into the performance and, as a result, the optimization of assets.…
This paper investigates the existing resource management approaches in Cloud Data Centres for energy and thermal efficiency. It identifies the need for integrated computing and cooling systems management and learning-based solutions in…
High-throughput computational and experimental design of materials aided by machine learning have become an increasingly important field in material science. This area of research has emerged in leaps and bounds in the thermal sciences, in…
Building operations represent a significant percentage of the total primary energy consumed in most countries due to the proliferation of Heating, Ventilation and Air-Conditioning (HVAC) installations in response to the growing demand for…
As processor performance advances, increasing power densities and complex thermal behaviors threaten both energy efficiency and system reliability. This survey covers more than two decades of research on power and thermal modeling and…
Different factors such as thermal comfort, humidity, air quality, and noise have significant combined effects on the acceptability and quality of the activities performed by the building occupants who spend most of their times indoors.…
Artificial intelligence (AI) is shifting the paradigm of two-phase heat transfer research. Recent innovations in AI and machine learning uniquely offer the potential for collecting new types of physically meaningful features that have not…
Heat management is crucial for state-of-the-art applications such as passive radiative cooling, thermally adjustable wearables, and camouflage systems. Their adaptive versions, to cater to varied requirements, lean on the potential of…
Continuous improvement in silicon process technologies has made possible the integration of hundreds of cores on a single chip. However, power and heat have become dominant constraints in designing these massive multicore chips causing…
Microgrids have emerged as a pivotal solution in the quest for a sustainable and energy-efficient future. While microgrids offer numerous advantages, they are also prone to issues related to reliably forecasting renewable energy demand and…
In small satellites there is less room for heat control equipment, scientific instruments, and electronic components. Furthermore, the near proximity of electronic components makes power dissipation difficult, with the risk of not being…
Recent technological advances have greatly improved the performance and features of embedded systems. With the number of just mobile devices now reaching nearly equal to the population of earth, embedded systems have truly become…
Active thermal control is crucial in achieving the required accuracy and throughput in many industrial applications, e.g., in the medical industry, high-power lighting industry, and semiconductor industry. Thermoelectric Modules (TEMs) can…
With the increased attention on thermal imagery for Covid-19 screening, the public sector may believe there are new opportunities to exploit thermal as a modality for computer vision and AI. Thermal physiology research has been ongoing…
Machine learning has had an enormous impact in many scientific disciplines. Also in the field of low-temperature plasma modeling and simulation it has attracted significant interest within the past years. Whereas its application should be…
Classical methods to control heating systems are often marred by suboptimal performance, inability to adapt to dynamic conditions and unreasonable assumptions e.g. existence of building models. This paper presents a novel deep reinforcement…
Thermally coupled distillation is a new energy-saving method, but the traditional thermally coupled distillation simulation calculation process is complicated, and the optimization method based on the traditional simulation process is…
Analyzing data centers with thermal-aware optimization techniques is a viable approach to reduce energy consumption of data centers. By taking into account thermal consequences of job placements among the servers of a data center, it is…