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In this study, the authors propose a novel digital twinning approach specifically designed for controlling transient thermal systems. The purpose of this study is to harness the combined power of deep learning (DL) and physics-based methods (PBM) to create an active virtual replica of the physical system.

To achieve this goal, we introduce a deep neural network (DNN) as the digital twin and a Finite Element (FE) model as the physical system. This integrated approach is used to address the challenges of controlling an unsteady heat transfer problem with an integrated feedback loop.

The results of our study demonstrate the effectiveness of the proposed digital twinning approach in regulating the maximum temperature within the system under varying and unsteady heat flux conditions. The DNN, trained on stationary data, plays a crucial role in determining the heat transfer coefficients necessary to maintain temperatures below a defined threshold value, such as the material’s melting point. The system is successfully controlled in 1D, 2D and 3D case studies. However, careful evaluations should be conducted if such a training approach, based on steady-state data, is applied to completely different transient heat transfer problems.

The present work represents one of the first examples of a comprehensive digital twinning approach to transient thermal systems, driven by data. One of the noteworthy features of this approach is its robustness. Adopting a training based on dimensionless data, the approach can seamlessly accommodate changes in thermal capacity and thermal conductivity without the need for retraining.

Polymer-based thermal interface materials (TIMs) are having pump out problem and could be resolved for reliable application. Solid-based interface materials have been suggested and reported. The purpose of this paper is suggesting thin film-based TIM to sustain the light-emiting diode (LED) performance and electronic device miniaturization.

Consequently, ZnO thin film at various thicknesses was prepared by chemical vapour deposition (CVD) method and tested their thermal behaviour using thermal transient analysis as solid TIM for high-power LED.

Low value in total thermal resistance (R_th-tot) was observed for ZnO thin film boundary condition than bare Al boundary condition. The measured interface (ZnO thin film) resistance {(R_th-bhs) thermal resistance of the interface layer (thin film) placed between metal core printed circuit board (MCPCB) board and Al substrates} was nearly equal to Ag paste boundary condition and showed low values for ZnO film prepared at 30 min process time measured at 700 mA. The T_J value of LED mounted on ZnO thin film (prepared at 30 min.) coated Al substrates was measured to be 74.8°C. High value in junction temperature difference (ΔT_J) of about 4.7°C was noticed with 30 min processed ZnO thin film when compared with Al boundary condition. Low correlated colour temperature and high luminous flux values of tested LED were also observed with ZnO thin film boundary condition (processed at 30 min) compared with both Al substrate and Ag paste boundary condition.

Overall, 30 min CVD processed ZnO thin film would be an alternative for commercial TIM to achieve efficient thermal management. This will increase the life span of the LED as the proposed material decreases the T_J values.

The purpose of this study is to investigate the thermoforming process of 3D-printed parts made from polylactic acid (PLA) and explore its application in producing wrist-hand orthoses. These orthoses were 3D printed flat, heated and molded to fit the patient’s hand. The advantages of such an approach include reduced production time and cost.

The study used both experimental and numerical methods to analyze the thermoforming process of PLA parts. Thermal and mechanical characteristics were determined at different temperatures and infill densities. An equivalent material model that considers infill within a print is proposed. Its practical use was proven using a coupled finite-element analysis model. The simulation strategy enabled a comparative analysis of the thermoforming behavior of orthoses with two designs by considering the combined impact of natural convection cooling and imposed structural loads.

The experimental results indicated that at 27°C and 35°C, the tensile specimens exhibited brittle failure irrespective of the infill density, whereas ductile behavior was observed at 45°C, 50°C and 55°C. The thermal conductivity of the material was found to be linearly related to the temperature of the specimen. Orthoses with circular open pockets required more time to complete the thermoforming process than those with hexagonal pockets. Hexagonal cutouts have a lower peak stress owing to the reduced reaction forces, resulting in a smoother thermoforming process.

This study contributes to the existing literature by specifically focusing on the thermoforming process of 3D-printed parts made from PLA. Experimental tests were conducted to gather thermal and mechanical data on specimens with two infill densities, and a finite-element model was developed to address the thermoforming process. These findings were applied to a comparative analysis of 3D-printed thermoformed wrist-hand orthoses that included open pockets with different designs, demonstrating the practical implications of this study’s outcomes.

This paper aims to study the impact of transient velocity changes on sealing performance during reciprocating sealing processes.

Establish a model of transient mixed lubrication, solve the transient Reynolds equation, consider the effect of temperature rise at the seal interfaces, and determine the behavior of the seal interfaces, such as film thickness and fluid pressure. Evaluation with friction and leakage rate, calculate the variation of sealing performance with reciprocating velocity under different working conditions, and verify it through bench experiments.

Within a reciprocating stroke, the frictional force decreases with increasing velocity, and the frictional force of the outstroke is greater than that of the instroke; at the time of the stroke transition, the fluid pressure is smallest and the rough peak contact pressure is greatest. At present, the dynamic pressure effect of fluids is the largest, and the friction force also increases, which increases the risk of material wear and failure. Friction and leakage increase with increasing pressure and root mean square roughness. As temperature increases, friction increases and leakage decreases. In studying the performance variations of seal components through a reciprocating sealing experiment, it was found that the friction force decreases with increasing velocity, which is consistent with the calculated results and more similar to the calculated results considering the temperature rise.

This study provides a reference for the study of transient sealing performance.

Light emitting diode (LED) has been the best resource for commercial and industrial lighting applications. However, thermal management in high power LEDs is a major challenge in which the thermal resistance (R_th) and rise in junction temperature (T_J) are critical parameters. The purpose of this work is to evaluate the R_th and T_j of the LED attached with the modified heat transfer area of the heatsink to improve thermal management.

This paper deals with the design of metal substrate for heatsink applications where the surface area of the heatsink is modified. Numerical simulation on heat distribution proved the influence of the design aspects and surface area of heatsink.

T_J was low for outward step design when compared to flat heatsink design (ΔT ∼ 38°C) because of increase in surface area from 1,550 mm² (flat) to 3,076 mm² (outward step). On comparison with inward step geometry, the T_J value was low for outward step configuration (ΔT_J ∼ 6.6°C), which is because of efficient heat transfer mechanism with outward step design. The observed results showed that outward step design performs well for LED testing by reducing both R_th and T_J for different driving currents.

This work is authors’ own design and also has the originality for the targeted application. To the best of the authors’ knowledge, the proposed design has not been tried before in the electronic or LED applications.

As data centres grow in size and complexity, traditional air-cooling methods are becoming less effective and more expensive. Immersion cooling, where servers are submerged in a dielectric fluid, has emerged as a promising alternative. Ensuring reliable operations in data centre applications requires the development of an effective control framework for immersion cooling systems, which necessitates the prediction of server temperature. While deep learning-based temperature prediction models have shown effectiveness, further enhancement is needed to improve their prediction accuracy. This study aims to develop a temperature prediction model using Long Short-Term Memory (LSTM) Networks based on recursive encoder-decoder architecture.

This paper explores the use of deep learning algorithms to predict the temperature of a heater in a two-phase immersion-cooled system using NOVEC 7100. The performance of recursive-long short-term memory-encoder-decoder (R-LSTM-ED), recursive-convolutional neural network-LSTM (R-CNN-LSTM) and R-LSTM approaches are compared using mean absolute error, root mean square error, mean absolute percentage error and coefficient of determination (R²) as performance metrics. The impact of window size, sampling period and noise within training data on the performance of the model is investigated.

The R-LSTM-ED consistently outperforms the R-LSTM model by 6%, 15.8% and 12.5%, and R-CNN-LSTM model by 4%, 11% and 12.3% in all forecast ranges of 10, 30 and 60 s, respectively, averaged across all the workloads considered in the study. The optimum sampling period based on the study is found to be 2 s and the window size to be 60 s. The performance of the model deteriorates significantly as the noise level reaches 10%.

The proposed models are currently trained on data collected from an experimental setup simulating data centre loads. Future research should seek to extend the applicability of the models by incorporating time series data from immersion-cooled servers.

The proposed multivariate-recursive-prediction models are trained and tested by using real Data Centre workload traces applied to the immersion-cooled system developed in the laboratory.

Thermal protection of a flange is critical for preventing tower icing and collapse of wind turbines (WTs) in extremely cold weather. This study aims to develop a novel thermal protection system for the WTs flanges using an electrical heat-tracing element.

A three-dimensional model and the Poly-Hexacore mesh structure are used, and the fluid-solid coupling method was validated and then deployed to analyze the heat transfer and convection process. Intra-volumetric heat sources are applied to represent the heat generated by the heating element, and the dynamic boundary conditions are considered. The steady temperature and temperature uniformity of the flange are the assessment criteria for the thermal protection performance of the heating element.

Enlarging the heating area and increasing the heating power improved the flange's temperature and temperature uniformity. A heating power of 4.9 kW was suitable for engineering applications with the lowest temperature nonuniformity. Compared with continuous heating, the increased temperature nonuniformity was buffered, and the electrical power consumption was reduced by half using pulse heating. Pulse heating time intervals of 1, 3 and 4 h were determined for the spring, autumn and winter, respectively.

The originality of this study is to propose a novel electrical heat-tracing thermal protection system for the WTs flanges. The effect of different arrangements, heating powers and heating strategies was studied, by which the theoretical basis is provided for a stable and long-term utilization of the WT flange.

The purpose of this paper is to examine the impact of moisture and temperature changes on the behavior of a semi-infinite solid cylinder made of T300/5208 composite material. This study aims to provide analytical solutions for temperature, moisture and thermal stress through the de-coupling technique and the method of integral transforms. Both coupled and uncoupled cases are considered.

This study investigates the hygrothermo-elastic response of a semi-infinite solid circular cylinder using an integral transform technique that includes Hankel and Fourier transforms. The cylinder is subjected to prescribed sources, and a numerical algorithm is developed for the numerical computation of the results. The goal is to understand how the cylinder responds to changes in temperature and moisture.

The paper presents an analytical solution for temperature, moisture and thermal stress in a semi-infinite solid cylinder obtained through the use of an integral transform technique. The study focuses on a graphite fiber-reinforced epoxy matrix composite material (T300/5208) and discusses the coupled and uncoupled effects of temperature, moisture and thermal stress on the material. The results of the transient response hygrothermo-elastic field are presented graphically to provide a visual representation of the findings.

The research presented in this article is primarily hypothetical and focused on the analysis of mathematical models.

To the authors' best knowledge, this study is the first to investigate the hygrothermal effect in a semi-infinite circular cylinder. Additionally, the material properties used in the analysis are both homogenous and isotropic and independent of both temperature and moisture. These unique aspects of the study make it a novel contribution to the field.

Gas metal arc-based directed energy deposition (GMA-DED) process experiences residual stress (RS) developed due to heat accumulation during successive layer deposition as a significant challenge. To address that, monitoring of transient temperature distribution concerning time is a critical input. Finite element analysis (FEA) is considered a decisive engineering tool in quantifying temperature and RS in all manufacturing processes. However, computational time and prediction accuracy has always been a matter of concern for FEA-based prediction of responses in the GMA-DED process. Therefore, this study aims to investigate the effect of finite element mesh variations on the developed RS in the GMA-DED process.

The variation in the element shape functions, i.e. linear- and quadratic-interpolation elements, has been used to model a single-track 10-layered thin-walled component in Ansys parametric design language. Two cases have been proposed in this study: Case 1 has been meshed with the linear-interpolation elements and Case 2 has been meshed with the combination of linear- and quadratic-interpolation elements. Furthermore, the modelled responses are authenticated with the experimental results measured through the data acquisition system for temperature and RS.

A good agreement of temperature and RS profile has been observed between predicted and experimental values. Considering similar parameters, Case 1 produced an average error of 4.13%, whereas Case 2 produced an average error of 23.45% in temperature prediction. Besides, comparing the longitudinal stress in the transverse direction for Cases 1 and 2 produced an error of 8.282% and 12.796%, respectively.

To avoid the costly and time-taking experimental approach, the experts have suggested the utilization of numerical methods in the design optimization of engineering problems. The FEA approach, however, is a subtle tool, still, it faces high computational cost and low accuracy based on the choice of selected element technology. This research can serve as a basis for the choice of element technology which can predict better responses in the thermo-mechanical modelling of the GMA-DED process.

The purpose of this paper is to present a new system frequency response model with participation of wind-hydro-thermal units to overcome frequency deviations.

The extracted minimum frequency equation is considered as a constraint in security-constrained unit commitment calculations. Because of high-order polynomials in the frequency transfer function and high degree of nonlinearity of minimum frequency constraint, Routh stability criterion method and piecewise linearization technique are used to reduce system order and linearize the system frequency response model, respectively.

The results of this paper indicate that by using this model, the hourly minimum frequency is improved and is kept within defined range.

This combined model can be used to evaluate the frequency of the power system following unexpected load increase or generation disturbances. It also can be used to investigate the system frequency performance and ensure power system security which are caused by peak load or loss of generation in presence of renewable energies.