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The development of strategies for energy efficiency optimization in buildings has become a fundamental way to reduce buildings’ environmental impact because the amount of energy consumed by buildings is responsible for one‐third of total global energy consumption. The purpose of this research is to evaluate the performance of buildings in terms of their indoor operative temperature dynamics considering the impact of other neighbouring buildings. The goal of the paper is to verify whether close spatial relationships of buildings and urban morphology within a local network of buildings could cause a considerable effect on indoor thermal behaviour.

The authors simulated buildings in an existing city block in Albany, New York, USA. The block consisted of six single‐family houses.

The results demonstrate that buildings mutually impact the indoor thermal behaviour of other buildings in the network with indoor operative temperature differences of over 20 percent in summer and over 40 percent in winter for the test case examined. The research also compares this result with improvements in indoor operative temperature achieved through traditional envelope improvements. It was found that during the summer, certain envelope improvement strategies have nearly the same impact in terms of indoor thermal behaviour. During winter, the presence of neighbouring buildings causes a variation that is more than double the value of the effect caused by a typical envelope modification.

It is concluded that this mutual impact on indoor operative temperature across spatially proximal buildings should be included in dynamic analyses of buildings. Future research should examine the effect of these indoor operative temperature deviations on the energy performance predictions of buildings in urban and quasi‐urban settings.

The purpose of this paper is to present a method for thermal computations of power devices based on a coupling between thermal and pressure networks. The concept of the coupling as well as the solution procedure is explained. The included examples demonstrate that the new method can be efficiently used for design of transformers and other power devices.

The bidirectional propagation of temperature signal is introduced to the pressure network, which enables control of the power flow and a close coupling to the thermal network. The solution method is based on automatic splitting of the network definition (netlist) into two separate networks and iteratively solving the model using the Newton-Raphson approach as well as the adaptive relaxation enhanced by the direction change control.

The proposed approach offers reliable convergence behaviour even for models with unknown direction of the fluid flow (bidirectional flows). The accuracy is sufficient for engineering applications and comparable with the computational fluid dynamics method. The computation times in the range of milliseconds and seconds are attractive for using the method in engineering design tools.

The new method can be considered as a foundation for a consistent network modelling system of arbitrary thermodynamic problems including fluid flow. Such a modelling system can be used directly by device designers since the complexity of thermodynamic formulations is encapsulated in predefined network elements while the numerical solution is based on a standard network description and solvers (Spice).

The application of dry-type transformers is growing in the market because the technology is non-flammable, safer and environmentally friendly. However, the unit dimensions are normally larger and material costs become higher, as no oil is present for dielectric insulation or cooling. At designing stage, a transformer thermal model used for predicting temperature rise is fundamental and the modelling of cooling system is particularly important. This paper aims to describe a thermal model used to compute dry transformers with different cooling system configurations.

The paper introduces a fast-calculating thermal and pressure network model for dry-transformer cooling systems, preliminarily verified by analytical methods and advanced CFD simulations, and finally validated with experimental results.

This paper provides an overview of the network model of dry-transformer cooling system, describing its topology and its main variants including natural or forced ventilation, with or without cooling duct in the core, enclosure with roof and floor ventilation openings and air barriers. Finally, it presents a formulation for the new heat exchanger element.

The network approach presented in this paper allows to model efficiently the cooling system of dry-type transformers. This model is based on physical principles rather than empirical assessments that are valid only for specific transformer technologies. In comparison with CFD simulation approach, the network model runs much faster and the accuracies still fall in acceptable range; therefore, one is able to utilize this method in optimization procedures included in transformer design systems.

For a lightweight and accurate description of bearing temperature, this paper aims to present an efficient semi-empirical model with oil–air two-phase flow and gray-box model.

First, the role of lubricant/coolant in bearing temperature was discussed separately, and the gray-box models on the heat convection inside a bearing cavity were also created. Next, the bearing node setting scheme was optimized. Consequently, a novel semi-empirical two-phase flow thermal grid for high-speed angular contact ball bearings was planned. With this model, the thermal network for the selected motored spindle was built, and the numerical solutions for bearing temperature rise were obtained and contrasted with the experimental values for validation. The polynomial interpolation on test data, meanwhile, was also performed to help us observe the temperature change trend. Finally, the simulations based on the current models of bearings were implemented, whose corresponding results were also compared with our research work.

The validation result indicates that the thermal prediction is more accurate and efficient when the developed semi-empirical oil–air two-phase flow model is employed to assess the thermal change of bearings. Clearly, we provide a more proper model for the thermal assessment of bearing and even spindle heating.

To the best of the authors’ knowledge, this paper introduced the oil–air separation and gray-box model for the first time to describe the heat exchange inside bearing cavities and accordingly presents an efficient semi-empirical oil–air two-phase flow model to evaluate the bearing temperature variation by using thermal network method.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-06-2023-0180/

Thermal analysis is an important design aspect and becoming a more important component of the electric motor design process due to the push for reduced weights and costs and increased efficiency. The purpose of this paper is to demonstrate that the accuracy of analytical thermal models depends on the accuracy of the thermal resistance computation and on the number of nodes in the equivalent thermal circuit.

In this paper, several thermal analytical models with different numbers of nodes are compared against with each other and with experimental data.

It is demonstrated that the more sophisticated and detailed model having a larger number of nodes can be used to calibrate the simpler but faster models with less nodes. The models are all for the same range of small totally enclosed non‐ventilated induction motors.

This paper shows that simplified and/or detailed analytical thermal models can be successfully used in predicting the temperature rise in small induction motors. The level of detail and accuracy of these models strongly depends on the number of nodes and how the thermal resistances are set up. The calibration process for various reduced nodal model has been successfully described. Once calibrated, the reduced node thermal models give both satisfactory accuracy and allow very fast and robust thermal calculations.

This paper aims to address the influence of diamond-like carbon (DLC) coatings on the frictional power loss of spur gears. It shows potentials for friction and bulk temperature reduction in industrial use. From a scientific point of view, the thermal insulation effect on fluid friction is addressed, which lowers viscosity in the gear contact due to increasing contact temperature.

Thermal insulation effect is analyzed in detail by means of the heat balance and micro thermal network of thermal elastohydrodynamic lubrication contacts. Preliminary results at a twin-disk test rig are summarized to categorize friction and bulk temperature reduction by DLC coatings. Based on experiments at a gear efficiency test rig, the frictional power losses and bulk temperatures of DLC-coated gears are investigated, whereby load, speed, oil temperature and coatings are varied.

Experimental investigations at the gear efficiency test rig showed friction and bulk temperature reduction for all operating conditions of DLC-coated gears compared to uncoated gears. This effect was most pronounced for high load and high speed. A reduction of the mean gear coefficient of friction on average 25% and maximum 55% was found. A maximum reduction of bulk temperature of 15% was observed.

DLC-coated gears show a high potential for reducing friction and improving load-carrying capacity. However, the industrial implementation is restrained by the limited durability of coatings on gear flanks. Therefore, a further and overall consideration of key durability factors such as substrate material, pretreatment, coating parameters and gear geometry is necessary.

Thermal insulation effect of DLC coatings was shown by theoretical analyses and experimental investigations at model test rigs. Although trial tests on gears were conducted in literature, this study proves the friction reduction by DLC-coated gears for the first time systematically in terms of various operating conditions and coatings.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2020-0257/

The purpose of this paper is to consider thermal analysis as part of an automated sizing and design process. The temperature estimation at characteristic points of the machine, and in particular in permanent magnets, is essential to accurately simulate the electromagnetic behavior and avoid irreversible demagnetization.

In this paper, an electromagnetic dimensioning model, parameterized by finite element analysis, is coupled to a thermal lumped‐parameter model to constitute a fast and efficient design tool for electrical machines.

A parameterized and hybrid FE‐analytical electromagnetic model, which combines analytical and numerical advantages, to archive a fast and accurate electromagnetic simulation results is combined with a thermal lumped‐parameter model for water‐cooled and passive air‐cooled surface mounted permanent magnet synchronous machines (PMSM).

Sizing, electromagnetic and thermal modeling aspects are integrated into an automated design process. The whole design process is demonstrated on two standard industrial servo motors for passive and active water cooling and afterwards compared with available measurements.

The proposed method allows considering thermal aspects during the iterative automated electromagnetic design process of PMSM.

The purpose of this paper is to approximate the convective heat transfer using a few non-dimensional parameters in the design process of large synchronous machines. The computed convective wall heat transfer coefficient can be used in circuit models or can be defined in numerical heat conduction (HC) models to compute the thermal field in the solid domains without the time consuming computation of the fluid domain.

Computational fluid dynamics (CFD) has been used to include a wide range of different designs, operating conditions and cooling schemes to ensure accurate results for a wide range of possible machines. Neural networks are used to correlate the computed heat transfer coefficients to various design parameters. The data set needed to define the weights and bias layers in the network has been obtained by several CFD simulations. A comparison of the evaluated solid temperatures with those obtained using the conjugate heat transfer (CHT) method has been carried out. The results have also been validated with calorimetric measurements.

The validation of the HC model has shown that this model is capable of yielding accurate results in a few minutes, in contrast to the several hours needed by the CHT solution. The workflow to determine the convective heat transfer in a specific part of an electrical machine has been also been established. The approximation of the convective wall heat transfer coefficient is shown to be obtainable in sufficient detail by using a neural network.

The paper describes a method to approximate the convective heat transfer accurately in a few seconds, which is very useful in the design process. The heat convection can then be characterized in a HC model including the solid domains only. The losses can be defined as sources in the solid domains, e.g. copper and iron, obtained by electromagnetic calculations and the thermal field can hence be easily computed in these parts. This HC model has the main advantage that the time consuming computation of the fluid domain is avoided.

The novelty in this work is the approximation of the convective heat transfer by using a neural network with an accuracy of less than 5 percent as well as the development of a HC model to compute the temperature in the solid domains. The investigations presented pinpoint relevant issues influencing the thermal behavior of electrical machines.

Thermal issues are becoming increasingly serious with the scaling down of integrated circuits and the increasing density brought in by advanced packaging techniques. Consequently, thermal issues need to be considered during both design and test. The present paper addresses thermal testing, and more specifically thermal transient testing.

In this contribution a linear thermal model for hybrid circuits is presented. Both the heat dissipated in screen printed resistors and in mounted components such as transistors and integrated circuits is taken into account.