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35,820 result(s) for "Thermal models"
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Perspective of Thermal Analysis and Management for Permanent Magnet Machines, with Particular Reference to Hotspot Temperatures
Permanent magnet (PM) machines have been extensively used for various applications. Nevertheless, thermal effect, particularly hotspot temperature, not only severely restricts power/torque density but also leads to deteriorations in electromagnetic performance, service life, and reliability. Starting with foundations of PM machines and heat transfer mechanisms, this paper reviews the development of thermal analysis methods over the last thirty years and the state-of-the-art research achievements, and the hotspot temperatures of winding and PM are particularly evaluated. In the overview, various machine losses and cooling techniques are first introduced, which are the essential reasons for temperature rise and the most straightforward way to remove the generated heat. Afterwards, the mainstream thermal analysis techniques, i.e., numerical techniques, lumped-parameter thermal model, and hybrid thermal models, as well as the online electrical parameter-based and thermal model-based temperature monitoring techniques, are reviewed and assessed in depth. In addition, this paper also reviews the analytical thermal modelling methods for winding and PM. Finally, future research trends are highlighted.
The Impact of Environmental Factors on the Thermal Characteristic of a Lithium–ion Battery
To draw reliable conclusions about the thermal characteristic of or a preferential cooling strategy for a lithium–ion battery, the correct set of thermal input parameters and a detailed battery layout is crucial. In our previous work, an electrochemical model for a commercially-available, 40 Ah prismatic lithium–ion battery was validated under heuristic temperature dependence. In this work the validated electrochemical model is coupled to a spatially resolved, three dimensional (3D), thermal model of the same battery to evaluate the thermal characteristics, i.e., thermal barriers and preferential heat rejection patterns, within common environment layouts. We discuss to which extent the knowledge of the batteries’ interior layout can be constructively used for the design of an exterior battery thermal management. It is found from the study results that: (1) Increasing the current rate without considering an increased heat removal flux at natural convection at higher temperatures will lead to increased model deviations; (2) Centralized fan air-cooling within a climate chamber in a multi cell test arrangement can lead to significantly different thermal characteristics at each battery cell; (3) Increasing the interfacial surface area, at which preferential battery interior and exterior heat rejection match, can significantly lower the temperature rise and inhomogeneity within the electrode stack and increase the batteries’ lifespan.
Entropy theory and its application in environmental and water engineering
Entropy Theory and its Application in Environmental and Water Engineering responds to the need for a book that deals with basic concepts of entropy theory from a hydrologic and water engineering perspective and then for a book that deals with applications of these concepts to a range of water engineering problems. The range of applications of entropy is constantly expanding and new areas finding a use for the theory are continually emerging. The applications of concepts and techniques vary across different subject areas and this book aims to relate them directly to practical problems of environmental and water engineering. The book presents and explains the Principle of Maximum Entropy (POME) and the Principle of Minimum Cross Entropy (POMCE) and their applications to different types of probability distributions. Spatial and inverse spatial entropy are important for urban planning and are presented with clarity. Maximum entropy spectral analysis and minimum cross entropy spectral analysis are powerful techniques for addressing a variety of problems faced by environmental and water scientists and engineers and are described here with illustrative examples. Giving a thorough introduction to the use of entropy to measure the unpredictability in environmental and water systems this book will add an essential statistical method to the toolkit of postgraduates, researchers and academic hydrologists, water resource managers, environmental scientists and engineers.  It will also offer a valuable resource for professionals in the same areas, governmental organizations, private companies as well as students in earth sciences, civil and agricultural engineering, and agricultural and rangeland sciences. This book: * Provides a thorough introduction to entropy for beginners and more experienced users * Uses numerous examples to illustrate the applications of the theoretical principles * Allows the reader to apply entropy theory to the solution of practical problems * Assumes minimal existing mathematical knowledge * Discusses the theory and its various aspects in both univariate and bivariate cases * Covers newly expanding areas including neural networks from an entropy perspective and future developments.
Thermal Model Validation Process for Building Environment Simulation: A Case Study for Single-Family House
Currently, more and more emphasis is being placed on reducing energy consumption in buildings to reduce greenhouse gases in the atmosphere. Building performance simulation is very useful to predict energy demand and indoor environment quality. An indispensable element of the simulation is the validation and calibration of the model, which is an arduous process. The aim of the study was to present a four-level validation (using measurement results) and calibration of a thermal model of a naturally ventilated single-family house. Numerical calculations using co-simulation between EnergyPlus and Contam were performed. The results of the one-year simulation measurements of the indoor temperature and ventilation airflows were compared. After the calibration was performed, a high convergence of the results was found. The normalized mean bias error for hourly and monthly values did not exceed 1% and the coefficient of variation of the root mean squared error was a maximum of 7% with a simultaneous high correlation of the results in the range from 0.85 to 0.89. It was found that the final results were significantly influenced by the appropriate modeling of air exchange in the building, including the opening of windows.
A VLBI delay model for gravitational deformations of the Onsala 20 m radio telescope and the impact on its global coordinates
Deformations of the reflectors of radio telescopes used in geodetic and astrometric VLBI observations belong to the class of systematic error sources which affect the estimated position of the telescope and which necessitates correction at the observation level. The determination of the gravitationally induced deformations requires some effort and needs specific modeling of the impact on the VLBI delay observables. This has been exercised on the Onsala 20 m radio telescope. In this publication, we present an elevation-dependent model for the contributions of the gravitational deformations to the delay observables for application in VLBI data analysis. New is that thermal expansion in some of the contributing components need to be applied also to the gravitational deformation effects. A further novelty is that we can substantiate the validity of and the need for these corrections. Concerning the validity we show that the empirical model used by astronomical colleagues for deliberately shifting the sub-reflector for gain optimization, exactly (within 0.5 mm RMS) matches the measured gravitationally induced displacement of the sub-reflector plus the change in focal length. The other evidence is the impact on the vertical component of the telescope’s coordinates of − 6.1 mm, which reduces the discrepancy determined in the computations of the ITRF2014 to 1.7 mm.
Heuristic Global Optimization for Thermal Model Reduction and Correlation in Aerospace Applications
This study addresses the challenge of accurately correlating detailed and reduced thermal models in aerospace applications by using heuristic global optimization methods. In the context of increasingly complex thermal systems, traditional manual correlation methods are usually a time-consuming task. This research employs a series of numerical simulations using methods such as Genetic Algorithms, Cultural Algorithms, and Artificial Immune Systems, with an emphasis on parameter tuning to optimize the reduced thermal model correlation. Results indicate that these heuristic methods can achieve high-accuracy correlations, with transient simulations exhibiting temperature differences below 3 °C, thereby validating the hypothesis that heuristic methods can effectively navigate complex parameter optimizations. Moreover, a comparative analysis of fitness function performance across various optimization methods underscores both the potential and computational challenges inherent in these approaches. The findings suggest that while heuristic global optimization provides a robust framework for thermal model reduction and correlation, further refinement—particularly in scaling to larger, more complex models and adaptive parameter tuning—is necessary. Overall, this work contributes to the theoretical understanding and practical application of advanced optimization strategies in aerospace thermal analysis, paving the way for improved predictive reliability and more efficient engineering processes.
Surveillance of work environment and heat stress assessment using meteorological data
Health surveillance and workplace surveillance are two related but different aspects of occupational health services. The assessment of heat stress using heat indices and thermal models in connection with meteorological data is an important part of surveillance of workplace heat. The assessment of heat exposure provides the basis for occupational health services. Workers should have health surveillance if the high heat stress cannot be reduced.