Non-uniform Temperature Distribution Research Articles

Microwave heating and fracturing of granite: Insights from infrared thermal imaging

Microwave heating has been considered as one of the promising rock breaking technologies. However, the non-uniform temperature distribution of microwave treated rocks has not been quantitatively studied and the microwave rock fracturing mechanisms have not been systematically revealed. In this paper, microwave heating tests were implemented using a 6 kW industrial microwave system. The ratio of maximum temperature to average temperature () was studied to characterize the non-uniformity of temperature. The temperature gradient and maximum temperature difference were calculated to quantitatively characterize the thermal stress. Experimental results indicate that the granite fracture temperature threshold is about 200 °C and cracking typically occurs at a minimum temperature gradient of 6 °C/mm. As either power level or irradiation time increases, the thermal gradient and temperature difference increase. For a fixed microwave energy, microwave heating at higher power levels for a shorter duration has a higher and a greater temperature difference and temperature gradient, which explains that the combination of high power and short heating time yields better rock weakening effects.

Thermo-large deflection coupled dynamic characteristics of rotating thickness-varying plates subjected to thermal shock

Thermal shock load has an important influence on dynamic characteristics of blades in turbomachines. Due to higher level operating thermal shock for improving the efficiency, the damage to the blades has greatly increased. Considering the major effect of variable thickness and large deflection on thermal dynamic behavior of blades, their thermo-large deflection-variable thickness coupled dynamic characteristics are unknown. This paper develops a thermo-large deflection coupled semi-analytical model based on a rotating variable thickness plate under thermal shock. Geometric nonlinear governing equation and an analytical solution of heat transfer equation are derived. Numerical examples of natural frequencies are investigated to validate the proposed model. The non-uniform temperature distribution features of the rotating variable thickness plate are found. Besides, when the thermal shock is serious, the large deflection theory must be considered to analyze thermo-large deflection coupled dynamic characteristics. Based on theoretical and experimental results, deformation characteristic of the cantilever plate subjected to thermal shock is obtained, which is helpful to find the optimal thickness distribution. Finally, the effect of variable thickness on thermo-large deflection coupled dynamics of the rotating plate is demonstrated. The vibration induced by thermal shock can be reduced by thickening the plate on its free side or both fixed–free sides. However, when thickening other positions, the vibration is either intensified or unchanged. Results are helpful to reduce blade’s vibrations under thermal shock.

(Digital Presentation) Effects of Non-Uniform Temperature Distribution on the Degradation of Liquid-Cooled Lithium-Ion Cells

Non-uniform temperature distribution develops inside lithium-ion (Li-ion) cells due to heat generation and low thermal conductivity in the thickness direction. Such non-uniform temperature distribution can cause non-uniform and accelerated degradation of Li-ion cells, as shown in our previous work on an air-cooled stack consisting of five Li-ion cells1, 2. Compared with air cooling, liquid cooling is more widely used for large-size Li-ion cells due to its stronger cooling capability. Liquid cooling would cause larger temperature gradient in Li-ion cells than air-cooling. It was therefore hypothesized that the degradation of liquid-cooled Li-ion cells will be more non-uniform than air-cooled cells. To test the hypothesis, a stack of water-cooled parallel-connected Li-ion cells, as schematically shown in Figure 1, were tested and compared with the air-cooled stack. Each cell has a nominal capacity of 3 Ah. As expected, the temperature distribution in the liquid-cooled stack was very non-uniform (Figure 2) and the cells degraded differently (Figure 3). Unexpected, however, the middle cell in the water-cooled stack degraded slower than the side cells, which is opposite to the trend of the air-cooled stack. Further investigation suggested that the opposite trend can be attributed to the combined effects of temperature rise and temperature gradient. Moreover, capacity drop and recovery was observed for the cells in the liquid-cooled stack after reference performance test, which could be attributed to the anode overhang effects3. References G. M. Cavalheiro, T. Iriyama, G. J. Nelson, S. Huang and G. Zhang, Journal of Electrochemical Energy Conversion and Storage, 17 (2020).H. J. Gonzalez Malabet, G. M. Cavalheiro, T. Iriyama, A. Gabhart, G. J. Nelson and G. Zhang, Journal of The Electrochemical Society, 168, 100507 (2021).B. Gyenes, D. A. Stevens, V. L. Chevrier and J. R. Dahn, Journal of The Electrochemical Society, 162, A278 (2014). Figure 1

(Digital Presentation) Simulating Coupled Effect of Heat Generation and Capacity Degradation on Performance of Lithium-Ion Cells

Lithium-ion batteries are gaining significant interest as energy storage devices in high power demand applications like power grids and EVs as the world seeks to reduce dependence on fossil fuels. High energy and power densities, high coulombic efficiency and low self-discharge of lithium-ion batteries make them a preferred choice in such applications. When a cell is cycled, various degradation processes occur, leading to a reduction in cell capacity over time. Among the various ageing mechanisms, electrolyte decomposition at the graphite electrode is the most significant contributor to capacity loss due to the consumption of cyclable lithium ions. Another mechanism for capacity loss is lithium plating on the surface of the graphite electrode particles and is observed under harsh cycling conditions or after extended cycling. These reactions lead to the formation of a passive layer, called the solid-electrolyte interface (SEI) layer, on the surface of the anode graphite particles. The ionic resistance offered by the SEI layer to the flow of lithium ions in the electrolyte leads to increased heat generation within the cell, thereby leading to higher cell temperature for the same operating conditions with cell ageing. Moreover, the ageing of the cell due to capacity loss, power reduction and impedance rise, is strongly dependent on the cell’s operating temperature and current. The internal cell temperature can be significantly different from its surface temperature for large-format cells when subjected to high current and different extent of forced cooling leading to a spatially varying degradation effects.Even though highly relevant, the coupled effect of current flow, heat generation and capacity fade have not been adequately examined in the literature. While several works have simulated the temperature distribution in large format cells [1,2] or capacity fade for cells [3] under isothermal conditions, very few have examined their coupled effect. Studies considering the coupled effect of capacity fade with heat generation have incorporated a pseudo-2D electrochemical degradation model [4,5]. The thermal model ranges from one to three-dimensional, with higher dimensional thermal models considering uniform heat generation within the cell. However, in a practical scenario, a large-format cell suffers from a non-uniform temperature distribution, leading to non-uniform electrochemical reactions and degradation.Hence, a detailed coupled thermo-electrochemical, capacity-fade model is required to understand cell degradation and temperature rise during its operational life. In a step towards this goal, a two-dimensional physics-based, coupled thermo-electrochemical model with capacity degradation will be demonstrated for cylindrical lithium-ion cells. The electrochemical model with capacity fade is based on the porous-electrode and concentrated solution theories [6]. The thermal model considers the effect of ohmic heat in various cell components and the reversible and irreversible heat of reactions in the electrodes. The contribution of side reactions in heat generation is incorporated. The effect of changing porosity and thermal and electronic impedance with ageing on the cell is considered in the model. The results will give a better understanding of (a) the safe operation of the cell as the internal temperature of the cell changes with ageing, and of (b) the dependence of cell ageing on temperature. Fig.1 shows the spatial distribution of temperature at the end of discharge for an LMO cell under different convective heat transfer coefficients. The cells were subjected to a 5C current at an ambient temperature of 25°C. While the temperature reached for a convective heat transfer coefficient h=5 W/m2.K is much higher, the temperature gradient developed is more significant for h=50 W/m2.K. This can be attributed to the increased Biot number for the cell under forced cooling. A difference of 8°C for h=50 W/m2.K between the internal and external cell temperature show that the capacity-fade model needs to consider the local temperature distribution within the cell for better prediction of cell degradation with cycling.

A General Three-Dimensional Electrochemical-Thermal Modeling Framework to Study Large-Format Batteries

Lithium-ion batteries’ performance, degradation, and safety are highly sensitive to their operating temperature [1-3]. Depending upon the form-factor, construction, and thermal boundary conditions, large temperature variations may be present within a battery in more than one direction. Physics-based battery models, such as single-particle model (SPM), enhanced single-particle model (ESPM), tank-in-series model, and the widely used pseudo-two-dimensional (p2D) model, ignore the effect of temperature variations in one or more directions [4]. Specifically, p2D model can resolve temperature variation within anode, cathode, and separator of a single stack but this is often not useful as the temperature variation within a single stack will be negligible due to the small length scale. Also, a commercial-scale Li-ion battery is a multi-stack system with possibly significant temperature variation across the stacks as compared to within a single stack. The recently developed thermal tank-in-series battery model accounts for temperature variation across a multi-stack battery system but does not account for temperature variation in the direction parallel to the current collector [5]. In the case of large-format batteries, significant temperature variations are also expected along the directions corresponding to the longer dimensions. This would typically involve temperature variations in the directions parallel to the current collector. Multi-scale multi-domain (MSMD) models have been developed in the past to extend the single-stack level physics-based models to account for temperature nonuniformity in these directions [6-8]. However, temperature variation in the direction corresponding to the shortest dimension may also be appreciable due to the anisotropic/orthotropic nature of heat transfer in the battery system at the macroscale [9,10]. This is because the heat transfer in this direction may be severely impeded by the multi-stack construct leading to poor thermal conductivity in that direction. This in turn may lead to a large temperature gradient even along the direction corresponding to the shortest dimension of the large-format battery system. This suggests the need for careful formulation of MSMD battery models considering the construction, design parameters, and external thermal conditions of a particular battery system. In the present work, we propose a general three-dimensional modeling framework that accounts for the effect of the three-dimensional temperature field on the local variations in thermodynamics, transport processes, and reaction kinetics in the battery system. This type of battery modeling framework can be used to study nonuniform temperature distribution driven spatially uneven degradation, particularly in large-format batteries. Additionally, this modeling framework can help design physics-aware battery-specific thermal management systems to improve performance and reduce degradation. This will be a drastic departure from the present approach of designing battery thermal management system which treats the battery in a rather simplistic manner.

A Systematic Review and Analysis of MPPT Techniques for TEG Systems Under Nonuniform Temperature Distribution

As a waste heat recovery power generation technology, the thermoelectric generation (TEG) system is popular and promising for its high reliability and environmental benefits. However, because of its low conversion efficiency, it has not been in large-scale use. To raise the efficiency of the TEG system, maximum power point tracking (MPPT) techniques are effective ways to gain the maximum power of the TEG system. But in practical engineering scene, TEG usually works under nonuniform temperature distribution (NTD) conditions; this will bring some difficulties on MPPT controlling, such as local maximum power point (LMPP) and oscillations around the maximum power point (MPP). For this reason, many intelligent MPPT algorithms have been emerged to solve aforementioned problems. In this article, the mathematical model and NTD condition will be introduced. Then, the latest research on classical and intelligent MPPT technologies will be reviewed, which includes a comparison of complexity, economy, efficiency, adaptive ability, and other aspects of these methods, in which researchers can obtain information in related fields.

Experimental study of the effect of the state of charge on self-heating ignition of large ensembles of lithium-ion batteries in storage

• Both the cell thermal runaway temperature ( T c, c ) and critical ambient temperature ( T a, c ) triggering ignition decrease as SOC increases. • The T c, c is independent of the number of cells, while the T a, c decreases as the number of cells increases. • The T a, c should be use to guide storage rather than the standard suggested critical temperature increase rate, which does not represent the criticality of ignition. • The laboratory results are upscale to predict the T a, c using storage. Self-heating can cause the ignition of open-circuit Lithium-ion batteries. Current safety literature focuses on the self-heating chemistry of a single cell, ignoring the effects of heat transfer. However, a large ensemble of batteries has a non-uniform temperature distribution and therefore self-heating ignition is dominated by both heat transfer and chemistry. This type of ignition is of importance when batteries are stored for long periods of time and in large ensembles but has been rarely studied to date. This paper studies the effect of the state of charge (SOC) on the self-heating behavior of LiCoO 2 prismatic cells. The SOC of 0% (of interest in the safety of waste facilities), 30% (transport), 50% (storage), 80% (aged battery) and 100% (fully-charged battery), and 1, 2 and 4 cells stacked together were studied using oven experiments. Results show that cells at all SOC can self-ignite. Flames were only observed for SOC larger than 80%. We compare two temperature criteria: the temperature of the middle cell using the critical increase rate of 10 ℃/min defined in standard SAE-J2464, and the ambient temperature around the ensemble when triggering ignition. Both temperature criteria decrease with increasing SOC showing that the hazard grows with energy density. The cell temperature criterion is independent of the number of cells, while the ambient temperature criterion decreases as the number of cells increases, which indicates the increased risk of self-heating ignition when cells are stacked together in ensembles. Thus, the ambient temperature criterion should be used to design safe storage rather than the standard cell temperature increase rate, which does not represent well the criticality of ignition. The effective kinetics and thermal properties at different SOCs are extracted based on the Frank-Kamenetskii theory and are used to upscale laboratory results to storage conditions. The results in this work can improve the safety of the storage and provide scientific insight for safety standards.

Heat Spreader Thermal Switch for Power Converter Isothermalization

Power module heat dissipation with spatial inhomogeneity and induced nonuniform temperature distribution presents a challenging concern for system reliability due to thermo-mechanical stresses. These reliability challenges are especially important for nonplanar designs using 3-D packaging principles. Here, we develop a heat spreader thermal switch capable of actively reducing temperature gradients between silicon carbide (SiC) devices in a three-level T-type power converter, which can change depending on electronic operating conditions. The heat spreader thermal switch consists of a stainless-steel (SS) heat spreader and a copper sliding switch embedded within the spreader. Heat transfer from the SiC devices and within the spreader can be controlled by moving the slider between positions within the spreader. To understand heat transfer mechanisms and design the heat spreader thermal switch, we conducted 3-D finite element method simulations to calculate the minimum attainable temperature difference between SiC devices. We used the finite element simulation to quantify the reduction in junction temperature swing during dynamic operation and coupled the results to the Coffin–Manson reliability model to quantify lifetime to failure. We integrated the heat spreader thermal switch with one phase of a three-phase T-type converter and demonstrated isothermalization at different working conditions. At 2.4-kW converter power, each hot SiC device dissipated 4.7 W of heat, resulting in a device case temperature of 43 °C, with each cold SiC device dissipating 1.7 W at 38 °C. The device-to-device temperature difference was decreased from 5 °C to 0 °C by moving the switch a distance of 20 mm. Finite volume method (FVM) simulations of the conjugate heat transfer problem validate the experimental results and support analysis of key performance parameters. This work demonstrates successful isothermalization of a power converter with an active heat spreader thermal switch and develops simulation and design guidelines for successful electro-thermal codesign and implementation of thermal switches for other electronics applications for which isothermalization and enhanced device reliability is a key issue.

Analysis of the effect of nonuniform surface temperature distribution on the performance of a thermoelectric generator

The present paper analyses the effect of an inhomogeneous surface temperature distribution on the operation of a thermoelectric generator (TEG), experimentally and numerically. In the steady-state measurements, a spatially inhomogeneous temperature distribution is imposed on the colder surface of the TEG. The hotter surface temperature distribution is kept homogeneous. The maximum-to-minimum difference in the TEG cold side surface temperature distribution has been changing between 10 °C and 25 °C during the measurements, while the difference of the area averaged cold surface temperature to the hot side temperature has been varying within the range 70 °C and 150 °C. Tests are also performed with homogeneous cold side temperature distributions. Measurements with the variable and uniform cold side temperatures are compared. The comparison shows that a local surface variation within the considered ranges does not have a noticeable effect on the TEG performance.A finite element method (FEM) based computational model is developed and validated based on the measured data. Using the FEM model, it has been possible to increase the applied temperature inhomogeneity to higher levels beyond those, which were possible in the experiments. The FEM model predicts a deviation at very high temperature inhomogeneity on the cold side, which can be justified with the temperature dependency of the material properties.

Multiphysics Modeling to Assist Microwave Cavity Design for Food Processing

Microwave technology has many current applications. It is very useful for food processing, including domestic cooking and warming-up and industrial heating and drying. It heats faster than conventional applications; however, in most cases result in non-uniform temperature distribution. Adequate cavity and equipment designs can reduce the impact of these heterogeneities and using multiples magnetrons is a possibility to mitigate hot and cold spots. Yet, the literature lacks methods to evaluate and compare multiple magnetrons designs. This study aimed to develop a procedure to evaluate the number and position of magnetrons connected to an application cavity using multiphysics modelling and simulation of the microwave distribution and heating of a food model. It was based on evaluating the electric field distribution into a selected working volume filled with air or a mixture of air-potato and the consequent effective power absorbed and temperature distribution into the air-potato medium. The assisted methodology with process simulation offers an insight into food temperature distribution, which would be very difficult to obtain experimentally or in any equipment design methodology. In this case study, it was found that up to 6 magnetrons are good enough when active in approximately 0.16 m3 cavity with a load that fills 10% of its volume.

Neural Network Modeling of the Solar Photovoltaic Thermal Module Performance

The design of photovoltaic thermal modules (PVT modules) features a nonuniform distribution of coolant temperature in the channel, and the solar cells (SC) that are in thermal contact with the PVT module channel are under different temperature conditions. The nonuniform distribution of the SC temperature causes undesirable effects that are complex and nonlinear, such as a drop of generated power and SC damage resulting from the occurrence of hot spots. The aim of the work is to develop a mathematical model for modeling the PVT module thermal and electrical performance based on a feedforward artificial neural network (FNN). A two-layer FNN with sigmoid hidden neurons and linear output neurons has been developed. The input layer is made up of the ambient temperature, coolant flowrate and environmental variables (the total insolation). The output layer represents the PVT module thermal and electrical efficiencies. The developed FNN was trained and adapted on the basis of modeling and an experimental database on the PVT module input and output parameters. The developed FNN was trained using the Levenberg–Marquardt algorithm. The mean absolute error achieved during the training is in the range from –0.319 to 0.448 for electrical efficiency and from –0.129 to 0.198 for thermal efficiency. The r.m.s error is 0.0678 for electrical efficiency and 0.0247 for thermal efficiency; the training time is 15 s or longer. An effective model has been developed that implements a new approach to modeling the performance of PVT modules based on artificial neural network algorithms with fairly close values of thermal and electrical efficiencies.

A Combination of Alloy Modification and Heat Treatment Strategies toward Enhancing the Properties of LPBF Processed Hot Working Tool Steels (HWTS)

Hot working tool steels (HWTS) are popular for industrial applications such as injection molding tools, and casting dies because of their high wear resistance, fatigue, strength, and toughness properties, even at elevated temperatures. Conventionally, they go through multi-stage heat treatments in order to attain targeted microstructures. Achieving such microstructures with a laser powder bed fusion (LPBF) process will require tailor-made process parameters since it is characterized by non-equilibrium conditions, non-uniform temperature distribution, and metastable phase formation. Recent advances in the LPBF qualification of 1.2343/4 HWTS have shown commendable results but are still fraught with the limitations of poor ductility or extra post-heat treatment steps. For the industrial competitiveness of LPBF HWTS, the enhancement of strength and ductility and elimination of post processing is critical. Therefore, minimizing retained austenite in the as-built samples through pre-heat treatment or alloying to reduce post heat treatments without sacrificing strength will be economically important for industry. In this work, 1.2343 HWTS and its modified form were LPBF printed both in the as-built, pre- and post-heat-treated conditions. The results are discussed based on the correlations of the powder properties with LPBF—part density, microstructure, and mechanical properties.

Experimental Study on the Thermal Performance of 3D-Printed Enclosing Structures

Three-dimensional printing, or additive manufacturing, is one of the modern techniques emerging in the construction industry. Three-Dimensional Printed Concrete (3DPC) technology is currently evolving with high demand amongst researchers, and the integration of modular building systems with this technology would provide a sustainable solution to modern construction challenges. This work investigates and develops energy-efficient 3D-printable walls that can be implemented worldwide through energy efficiency and sustainability criteria. Numerical research and experimental investigations, bench tests with software packages, and high-precision modern equipment have been used to investigate the thermal performance of 3DPC envelopes with different types of configurations, arrangements of materials, and types of insulation. The research findings showed that an innovative energy-efficient ventilated 3DPC envelope with a low thermal conductivity coefficient was developed following the climatic zone. The annual costs of heat energy consumed for heating and carbon footprint were determined in the software package Revit Insight to assess the energy efficiency of the 3D-printed building. The thermal properties of the main wall body of the tested 3D-printed walls were calculated with on-site monitoring data. The infrared thermography technique detected heterogeneous and non-uniform temperature distributions on the exterior wall surface of the 3DPC tested envelopes.

Simulation on the Electric and Thermal Fields of a Microwave Reactor for Ex Situ Biomass Tar Elimination

Microwave treatment is an emerging technique for biomass tar elimination. The electric and thermal fields of the microwave reactor are the key to high elimination efficiency and energy utilization. In this work, we simulated the electric and thermal fields of a microwave reactor with various parameters including irradiation feed position, microwave power, silicon carbide length and flow velocity. Results show that the irradiation feed position that locates 5 mm vertically to the central plane can obtain the highest electric intensity and silicon carbide temperature (ca. 1100 K) after wave absorbing. Both the electric and thermal fields are strengthened when microwave power is increased. Extending the silicon carbide bed length will decrease the bed temperature and heating rate. A high flow velocity leads to non-uniform temperature distribution of the silicon carbide. For the purpose of achieving a high microwave energy utilization and uniform bed temperature, suitable irradiation feed position (zi = 5 mm), high microwave power (P = 1000 W), short silicon carbide bed length (lSiC = 100 mm) and low flow velocity (v = 0.02 m/s) are preferred, but the chemical kinetics of biomass tar elimination should also be considered in the practical application.

Advanced simulation of a 750 t/d municipal solid waste grate boiler to better accommodate feedstock changes due to waste classification

To better accommodate changes in municipal solid waste (MSW) properties due to waste classification, advanced computational fluid dynamics (CFD) simulations are carried out for a 750 t/d MSW moving-grate boiler. A moving-grate bed model is developed and iteratively coupled to the freeboard simulation which is performed in Ansys Fluent. The model is first validated by the measurement data for the daily operation case incinerating current feedstock. Then, the model is deployed to investigate the impacts of feedstock change and adjust boiler operation for better accommodating the new MSW. The results indicate incineration of the new MSW leads to irrational utilization of oxygen, non-uniform temperature distribution and low mixing, while maintaining current operation conditions. Subsequently, adjustments of air supply and thermal input are proposed and conducted by the model, which address the potential issues and benefit boiler operation and energy recycling. Finally, the uniformity of velocity and turbulent kinetic energy which indicates mixing, are compared for different cases. The latter is increased by 51.39% and 81.04% after the adjustments of air supply and thermal input. The investigation provides solid references for incinerating new MSW in the current boiler.

Evaluation of in-cylinder endoscopic two-colour soot pyrometry of diesel combustion

Flame temperature and soot concentration imaging was performed using endoscopic two-colour (2C) soot pyrometry to investigate the characteristics of in-cylinder diesel engine combustion processes and provide validation data for engine simulation and design. To appropriately interpret the 2C image results, this paper focuses on the uncertainty and challenges of the technique, the line-of-sight nature of the measurement and presents comparable information for validation exercises. A line-of-sight flame light intensity model was created to explore how the temperature T and soot concentration KL measured by the 2C technique can relate to non-uniform flame temperature and soot distributions. It was found that T and KL measured from the 2C technique were likely to relate differently to the actual distribution depending on where in the flame the measurement was taken and on assumptions made about the flame spatial structure. Assessment has been made of the range of the maximum and minimum flame temperatures (assumed to correspond to reaction zone temperature and flame centreline respectively) that are consistent with measured temperature T and soot concentration KL. The analysis of uncertainties, flame temperature and soot distribution along the line-of-sight, and image averaging allows for better quantitative comparison of 2C soot pyrometry images to CFD simulation, which increases confidence in simulation-driven engine development.

Establishment and analysis of numerical model of deuterium fuel ice migration in indirect-drive cryogenic target

A cryogenic target is the core component in inertial confinement fusion. For meeting the experimental requirements, the uniformity of the fuel ice layer in the capsule needs to reach 99% at least. The capsule has a nonuniform temperature distribution natively resulting from the columnar hohlraum geometry, leading to a nonuniform fuel ice layer profile. A proper temperature distribution along the hohlraum can be used to improve the uniformity of the fuel ice layer. A numerical model that can predict the kinetics of the fuel solid-vapor interface during the migration process is proposed by coupling the heat transfer and flow equations with the Stefan condition. This numerical model has good calculational accuracy verified with the pure-ice sublimation experiment. By studying different hohlraum temperatures and fuel ice layer initial eccentricities, the basic characteristic of ice immigration has been figured out. For the manufacture process, a temperature control scheme has been proposed by which the uniformity of the fuel ice layer can reach 99.57%. For the retention process, a perfectly uniform fuel ice layer can be maintained for 2000s before it cannot meet the ignition standard. These results are of significant guidance on cryogenic target experiments.

Application and Optimization of the Thin Electric Heater in Micro-Injection Mold for Micropillars.

The development of variotherm systems has helped to improve the quality of micro-injection molded products. Thin electric heaters have significant advantages in size, efficiency and installation convenience. However, the use of thin electric heaters has brought the problem of non-uniform temperature distribution of the insert. The good replication of the functional surfaces containing microstructures quickly and uniformly is still a challenge. In this work, the heating performance of the thin electric heater in a variotherm system is investigated by combining numerical simulations with experiments. Micro-injection molding of PP micropillars was also performed. The obtained results show that the addition of a transition layer with high thermal conductivity in the heating structure can optimize the uniformity of the temperature distribution of the insert. Furthermore, the replication heights of the micropillars can be significantly increased by the developed variotherm mold, which provides a new idea for the optimal design of a local variotherm system.

Generalized regression neural network and fitness dependent optimization: Application to energy harvesting of centralized TEG systems

The thermoelectric generator (TEG) system has attracted extensive attention because of its applications in centralized solar heat utilization and recoverable heat energy. The operating efficiency of the TEG system is highly affected by operating conditions. In a series-parallel structure, due to diverse temperature differences, the TEG modules show non-linear performance. Due to the non-uniform temperature distribution (NUTD) condition, several maximum power points (MPPs) appear on the P/V curve. In multiple MPPs, the true global maximum power points (GMPP) are very important for optimum action. The existing conventional technologies have slow tracking speed, low productivity, and unwanted fluctuations in voltage curves. To overcome the TEG system behavior and shortcomings, A novel control technology for the TEG system is proposed, which utilizes the improved generalized regression neural network and fitness dependent optimization (GRNNFDO) to track the GMPP under dynamic operating conditions. Conventional TEG system control techniques are not likely to trace true GMPP. Our novel GRNNFDO can trace the true GMPP for NUTD and under varying temperature conditions In this article, some major contributions in the area of the TEG systems are investigated by solving the issues such as NUTD global maxima tracking, low efficiency of TEG module due to mismatch, and oscillations around optimum point. The results of GRNNFDO are compared with the Cuckoo-search algorithm (CSA), and grasshopper optimization (GHO) algorithm and particle swarm optimization (PSO) algorithm. Results of GRNNFDO are verified with experiments and authenticated with MATLAB/SIMULINK. The proposed GRNNFDO control technique generates up to 7% more energy than PSO and 60% fast-tracking than meta-heuristic algorithms.

Mechanical Behavior and Microstructure Evolution during Hot Torsion Deformation of Aluminum Alloy AA2219

This study comprehensively analyzes the mechanical behavior and microstructural evolution of aluminum alloy AA2219‐T87 undergoing high deformation and strain rates at elevated temperatures via hot torsion tests. An integrated experimental and modeling approach is employed, where a finite element model (FEM) is developed with ABAQUS to address local deformation and nonuniform temperature distribution along the specimen gauge section. A Johnson–Cook constitutive material model is calibrated based on the calculated and measured torque curves at different conditions. The grain structure distribution is characterized through optical microscopy and electron backscatter diffraction (EBSD) analysis. Combined with the ABAQUS calculated local thermomechanical conditions, microstructure modeling, using established literature‐based equations, is established to provide insights into grain size distribution and recrystallization mechanisms. The calibrated material constitutive model, recrystallization model, and grain size model can be utilized to model various manufacturing processes, which involve hot deformation of aluminum alloys in the intermediate strain rate range of 14–78 s−1. The constitutive model shows adequate matching of the experimental torque curves at 400, 450, and 500 °C. The recrystallization prediction model functions at over 94% accuracy and the grain size model provides an average deviation between predicted and measured grain size reduction of 11.5%.