Energy Transport Research Articles

Effect of Stray and High Voltage Exposure on Livestock: An Overview

Electricity is essential to dairy farming and electrically powered machines are used for milking, automatic feed dispensers and heated water bowls. Leakage of current from these equipments, high voltage lines or faulty connections between the electrical circuit and the earth can lead to an undesirable electrical phenomenon called stray voltage. Stray voltage is a small voltage (<10V) that can be measured between two possible contact points. Cows can sense voltages at approximately one-tenth of a human being. Humans have inherently higher body resistance than cows and generally have shoes or boots while working in barns, which further increases resistance. Consequently, humans do not feel what animals feel. Stray voltages less than 0.5 volts are considered normal. Stray voltages vary, depending on the circuits used and the amount of moisture in the soil around the grounding rod. Impact of stray currents on livestock at current 1 - 3 mA: At current 4 - 6 mA: common behavioral response such as flinching or delaying drinking water. At current > 6 mA (up to 10): Feed intake is reduced, resulting in lower meat and milk production. Common symptoms of stray voltage in cows include hesitation to enter the parlor, they may stampede or rush out of the parlor when released, cows dance or step around constantly while in the milking parlor, Normal milk letdown is interrupted, Increased milking time, Udder irritation caused by residual milk and increased somatic cell count which increases the incidence of mastitis.

HIV subtypes and molecular transmission characteristics among elderly HIV-infected individuals aged 50 and above: a cross-sectional study in Huzhou City, Eastern China

ObjectiveTo analyse the HIV-1 subtypes and molecular transmission characteristics of HIV-infected older individuals aged 50 and above in Huzhou City, and provide a scientific basis for prevention and treatment strategies...

AmiA and AliA peptide ligands, found in Klebsiella pneumoniae, are imported into pneumococci and alter the transcriptome

Klebsiella pneumoniae releases the peptides AKTIKITQTR and FNEMQPIVDRQ, which bind the pneumococcal proteins AmiA and AliA respectively, two substrate-binding proteins of the ABC transporter Ami-AliA/AliB oligopeptide permease. Exposure to these peptides alters pneumococcal phenotypes such as growth. Using a mutant in which a permease domain of the transporter was disrupted, by growth analysis and epifluorescence microscopy, we confirmed peptide uptake via the Ami permease and intracellular location in the pneumococcus. By RNA-sequencing we found that the peptides modulated expression of genes involved in metabolism, as pathways affected were mostly associated with energy or synthesis and transport of amino acids. Both peptides downregulated expression of genes involved in branched-chain amino acid metabolism and the Ami permease; and upregulated fatty acid biosynthesis genes but differed in their regulation of genes involved in purine and pyrimidine biosynthesis. The transcriptomic changes are consistent with growth suppression by peptide treatment. The peptides inhibited growth of pneumococcal isolates of serotypes 3, 8, 9N, 12F and 19A, currently prevalent in Switzerland, and caused no detectable toxic effect to primary human airway epithelial cells. We conclude that pneumococci take up K. pneumoniae peptides from the environment via binding and transport through the Ami permease. This changes gene expression resulting in altered phenotypes, particularly reduced growth.

Critical-edge based tabu search algorithm for solving large-scale multi-vehicle Chinese postman problem

The min–max multi-vehicle Chinese postman problem is an NP-hard problem, which is widely used in path planning problems based on road network graphs, such as urban road structure probing planning, urban road underground cavity detection planning, high-voltage line inspection planning, and so on. With the rapid increase in the number of nodes and connections of road network graph, the solution time and path equilibrium constraints pose new challenges to the problem solving. In this paper, we propose a critical-edge tabu search algorithm, CTA-kroutes, for solving the min–max multi-vehicle postman problem for large-scale road networks. First, the initial solution with balanced path lengths is obtained by segmenting the Eulerian paths; second, the critical edges are moved in the initial solution to construct the neighborhood solution, and the tabu search algorithm is used to find the optimal solution iteratively; and lastly, the solution optimization algorithm is used at the end of each iteration to de-duplicate and optimally reconstruct the current search result. Experiments show that the CTA-kroutes algorithm can effectively improve the equalization of multi-vehicle paths and its applicability to large-scale road networks.

The Metal-Insulator Transition in Vanadium Oxide Nanofilms Enables Microkelvin-Resolution Thermometry.

High-resolution thermometry is critical for probing nanoscale energy transport. Here, we demonstrate how high-resolution thermometry can be accomplished using vanadium oxide (VOx), which features a sizable temperature-dependence of its resistance at room temperature and an even stronger dependence at its metal-insulator-transition (MIT) temperature. We microfabricate VOx nanofilm-based electrical resistance thermometers that undergo a metal-insulator-transition at ∼337 K and systematically quantify their temperature-dependent resistance, noise characteristics, and temperature resolution. We show that VOx sensors can achieve, in a bandwidth of ∼16 mHz, a temperature resolution of ∼5 μK at room temperature (∼300 K) and a temperature resolution of ∼1 μK at the MIT (∼337 K) when the amplitude of temperature perturbations is in the microkelvin range, which, in contrast to larger perturbations, is found to avoid hysteric resistance responses. These results demonstrate that VOx-based thermometers offer a ∼10-50-fold improvement in resolution over widely used Pt-based thermometers.

Enhancement of transmission line parameters for the supply of energy in the Rivers state local government area of Obio Akpor

Efficient energy transmission is crucial for meeting the growing demand for electricity, particularly in urban and rural areas. In the Rivers State Local Government Area of Obio Akpor, Nigeria, ensuring reliable power supply is essential for supporting economic development and improving quality of life. However, challenges such as transmission line losses, voltage fluctuations, and inadequate infrastructure hinder the effective distribution of energy in the region. This article presents a comprehensive study on enhancing transmission line parameters to improve energy supply in Obio Akpor. Through field measurements, data analysis, and simulation studies, the performance of existing transmission lines is evaluated, and strategies for enhancing efficiency and reliability are proposed. The literature review explores previous research on transmission line optimization, emphasizing factors such as conductor material, line design, and insulation to minimize losses and maximize power transfer capability. Materials and methods encompass data collection, including impedance measurements, voltage profiles, and load characteristics, followed by computer simulations to assess proposed enhancements.

Vibration energy transfer in forced laminated composite box structure

This study investigates the dynamics of laminated composite box structures from the viewpoint of energy flow transmission. Using a substructure-based technique, the power flow and dynamic responses are defined and obtained. The relationship between natural frequencies and the fiber orientations is explored. The influence of excitation frequencies, fiber angles, and boundary conditions on power flow and energy transmission paths (ETPs) is examined. The fiber orientations of box structure and boundary conditions are shown to have a substantial impact on ETPs and the positions of sinks. By modifying fiber angles, vibration suppression of box structure can be achieved.

Critical role of transport phenomena in the performance of a catalytic fixed bed reactor for the CO2 hydrogenation to CH4 evaluated by modeling and simulation

CO2 hydrogenation with renewable hydrogen enables the production of CH4 to be used as energy carrier (CO2 + 4H2 ⇆ CH4 + 2H2O). Steady state 1D pseudo-homogeneous and heterogeneous models, in the absence or presence of mass and energy transport in the axial direction of the reactor and inside the solid phase, are considered to simulate a non-isothermal fix bed reactor. Numerical strategies for solving these models in Matlab R2022b are discussed. The pseudo-homogeneous plug-flow model is not able to describe the experimental results irrespective of the global heat transfer coefficient considered. The inclusion of mass and energy transport in the reactor axial direction is crucial for describing the experimental data. The inclusion of mass and heat transport inside the solid phase by the heterogeneous model enables the best fitting. This work provides a valuable modeling tool for future industrial-scale reactor design.

Optimization of a hybrid system (PV-fuel cell) of energy production for an isolated site

In recent years, there has been a significant shift in the design and implementation of autonomous micro-grid systems, moving away from the traditional reliance on fossil fuels. Instead, these systems are now integrating existing renewable energy sources available in specific geographic locations to promote sustainability and environmental responsibility in the energy sector. One particularly promising approach for energy storage and transmission is through the utilization of hydrogen and solar energy, especially in remote regions where hybrid techniques can effectively meet the required energy demands. Our research focuses on electrifying an agricultural site located in the SBAA region, specifically in the city of ADRAR, southwest Algeria. We propose the implementation of an independent small electric network that combines various renewable energy sources, including photovoltaic (PV) systems and fuel cells. To ensure cost-effectiveness and optimize the system's performance, we aim to carefully control and size the system's components through a meticulous selection process. The primary objective of this study is to evaluate the technical and economic feasibility of implementing renewable energy systems in the targeted region. Our goals are to reduce the total net cost, minimize energy expenses and unfulfilled load, while simultaneously mitigating CO2 emissions. To achieve these objectives, we employ the HOMER Pro simulation program, which enables us to conduct a comprehensive analysis of the proposed system's performance and economic viability. The proposed system incorporates a hybrid configuration of PV panels and fuel cells, leveraging the complementary nature of these two renewable energy sources. PV panels harness the abundant solar energy during daytime hours, while fuel cells provide a reliable and consistent energy source during periods of low solar irradiance or at night. By integrating these two technologies, we aim to establish a self-sufficient and sustainable energy system capable of meeting the energy demands of the remote agricultural site. Overall, the proposed renewable energy system demonstrates positive results in electrifying remote areas while maintaining a conservative cost of electrical energy. By implementing this system, we not only contribute to the establishment of sustainable regions but also promote environmental stewardship by reducing carbon emissions and dependence on fossil fuels.

Exploring Dynamic Changes in HIV-1 Molecular Transmission Networks and Key Influencing Factors: Cross-Sectional Study.

The HIV-1 molecular network is an innovative tool, using gene sequences to understand transmission attributes and complementing social and sexual network studies. While previous research focused on static network characteristics, recent studies' emphasis on dynamic features enhances our understanding of real-time changes, offering insights for targeted interventions and efficient allocation of public health resources. This study aims to identify the dynamic changes occurring in HIV-1 molecular transmission networks and analyze the primary influencing factors driving the dynamics of HIV-1 molecular networks. We analyzed and compared the dynamic changes in the molecular network over a specific time period between the baseline and observed end point. The primary factors influencing the dynamic changes in the HIV-1 molecular network were identified through univariate analysis and multivariate analysis. A total of 955 HIV-1 polymerase fragments were successfully amplified from 1013 specimens; CRF01_AE and CRF07_BC were the predominant subtypes, accounting for 40.8% (n=390) and 33.6% (n=321) of the specimens, respectively. Through the analysis and comparison of the basic and terminal molecular networks, it was discovered that 144 sequences constituted static molecular networks, and 487 sequences contributed to the formation of dynamic molecular networks. The findings of the multivariate analysis indicated that the factors occupation as a student, floating population, Han ethnicity, engagement in occasional or multiple sexual partnerships, participation in anal sex, and being single were independent risk factors for the dynamic changes observed in the HIV-1 molecular network, and the odds ratio (OR; 95% CIs) values were 2.63 (1.54-4.47), 1.83 (1.17-2.84), 2.91 (1.09-7.79), 1.75 (1.06-2.90), 4.12 (2.48-6.87), 5.58 (2.43-12.80), and 2.10 (1.25-3.54), respectively. Heterosexuality and homosexuality seem to exhibit protective effects when compared to bisexuality, with OR values of 0.12 (95% CI 0.05-0.32) and 0.26 (95% CI 0.11-0.64), respectively. Additionally, the National Eight-Item score and sex education experience were also identified as protective factors against dynamic changes in the HIV-1 molecular network, with OR values of 0.12 (95% CI 0.05-0.32) and 0.26 (95% CI 0.11-0.64), respectively. The HIV-1 molecular network analysis showed 144 sequences in static networks and 487 in dynamic networks. Multivariate analysis revealed that occupation as a student, floating population, Han ethnicity, and risky sexual behavior were independent risk factors for dynamic changes, while heterosexuality and homosexuality were protective compared to bisexuality. A higher National Eight-Item score and sex education experience were also protective factors. The identification of HIV dynamic molecular networks has provided valuable insights into the characteristics of individuals undergoing dynamic alterations. These findings contribute to a better understanding of HIV-1 transmission dynamics and could inform targeted prevention strategies.

An efficient neighbor nodes trust tagging model for optimized route detection in smart grids with secure data transmission

Smart Grids are the control and transmission networks of the future; they allow suppliers and customers to interact in real time to optimize and intelligently manage resources. Although wireless mesh network technology can facilitate these smart functionalities, it is important to address the vulnerabilities and cyber-attack risks that are inherent to it. Smart Grid's reliance on the Internet amplifies security concerns. A number of methods have been proposed to address this issue; while some have made promises, they all need substantial amounts of computational resources. With this technology, channels based on trust can be set up. The security of the system is built utilizing a family relationship-based method, which makes use of measures that may be used to gauge a node's originality. Additionally, the power consumption and signal strength of the node are taken into account. The complexity and extent of the network need the development of new types of smart grid communication. Finding a way to detect and thwart major assaults on routing protocols is another design challenge. Smart grids rely on these protocols in its data system for efficient interchange of renewable energy. A unique secure energy routing mechanism is developed in this proposed model for secure data communication. In the proposed model, a new method for Neighbor Nodes Trust Tagging Model for Optimized Route Detection (NNTT-ORD) is proposed for establishing secure route for data communication in smart grids. The proposed model is compared with the existing model and the results represent that the proposed model route provides a secure environment for data transmission.

Periodic driving shape controls energy transmission.

In the early 2000s, Geniet and Leon [Phys. Rev. Lett. 89, 134102 (2002)0031-900710.1103/PhysRevLett.89.134102] discovered the nonlinear supratransmission (NST) in a medium with a forbidden frequency band gap. It is a process in which nonlinear structures are created by a sinusoidal harmonic boundary condition imposed at a frequency in the band gap. The present study extends this concept and shows that an optimal shape of a periodic nonsinusoidal excitation may induce (or inhibit) energy flow through the lattice below (or above) the NST threshold, demonstrating that nonlinear supratransmission is reliant not only on the driving amplitude but also on its shape. This is evidenced through numerical simulations and mathematical calculations varying the excitation signal shape in the Fermi-Pasta-Ulam case study. Setting the shape parameter to zero recovers the results of the literature in relation to the sinusoidal signal.

Impact of Different Protrusions in Energy Transfer and Fluid Flow Characteristics Using Al₂O₃ Nanofluid in Pipe Flow

The study investigates how the protruded surface (the part sticking out of an otherwise flat surface) over the small channel affects flow characteristics and heat transfer within a circular flow regime, utilizing computational methods. This investigation uses an alumina nanofluid to compare and analyze the thermo-physical parameters of protruding pipes such as boxes, cylinders, dimples, and pyramids in pipe flow. Alumina nanofluid with varying volume fractions was evaluated as a thermo-fluid under laminar flow conditions, exploring its ability to enhance energy transmission (heat) over the protruded channels. The protruded surface induces turbulence around the protruded region, altering the coolant's physical characteristics. Since heat transfer predominantly occurs on surfaces, the alteration in surface geometry due to the protruded shape increases detectable heat transfer and the Nusselt number. With an increase in the volume percentage of nanofluids, there's a tendency for pressure loss to rise along the flow direction's centerline. The dimpled channel exhibits the highest Nusselt number among all protruding channels, indicating that increasing the Reynolds number also increases the surface heat transfer coefficient for all protrusions. When compared to the base fluid, cylindrical protrusions show the greatest pressure drop. Additionally, comparing a protruded channel with base fluid to one with a 4% volume of alumina nanofluid, it can be observed that the latter significantly improves heat transfer, followed by volume fractions of 1% to 3%.

Novel Hierarchical Energy Management System for Enhanced Black Start Capabilities at Distribution and Transmission Networks

A novel energy management system featuring a unique framework involving multiple hierarchical controllers at the distribution and transmission network levels is proposed. The unique objective function of this energy management system is designed to enhance system inertia during black start and optimise load shedding. The objective function further aims to increase reliance on renewable energy sources, prioritising solar power along with battery and fuel cell technologies. This work delves deeply into the dynamics of multi-area power networks, where some areas possess black start capabilities (BSAs) while others do not (NBSAs). The proposed energy management system specifically explores the complex interplay between these black start capabilities and the hierarchical load restoration order. During grid blackouts, the systems located in BSA areas are tasked with first restoring essential loads in their own regions before extending aid to the adjacent NBSA areas, taking into account factors such as their available reserved power and geographical proximity. This work is extended to analyse complex multi-area power network architectures. This extended analysis provides invaluable insights for enhancing power restoration processes and facilitating the large-scale integration of sustainable energy solutions in complex systems. The proposed energy management system is validated using the IEEE 39-Bus network, which consists of ten distinct areas, each differing in their black start capabilities. The results demonstrate the superiority of the proposed system.

Research on Influencing Factors and Wind Deflection Warning of Transmission Lines Based on Meteorological Prediction

Transmission lines are affected by external environmental factors such as strong winds and ice cover. In recent years, extreme weather events have increased, leading to recurrent disturbances in transmission lines because of wind deflection. These incidents have resulted in significant financial losses and have disrupted regular industrial and domestic activities. In this paper, the ANSYS Workbench 2020 R2 finite element analysis platform was used to establish a transmission line-hanging insulator string system model. Calculations on transmission lines were conducted considering variations in different stall spacing, height differences, wind speed, and the wind attack angle. The impact of these diverse factors on the wind deflection of insulators was scrutinized, leading to the derivation of patterns describing how the wind deflection angle shifts in response to changes in stall spacing, height differences, wind speed, and the wind attack angle. Based on the generalized linear regression network and particle swarm improved support vector machine algorithm, a meteorological prediction-based early warning method for wind deflection of transmission lines was proposed, a transmission line wind deflection early warning model was established, and the practical effect of the model was evaluated. The outcomes of this study provide crucial data for the formulation and development of ultra-high voltage (UHV) and extra-high voltage (EHV) transmission networks. Furthermore, they can contribute to the advanced detection of wind deflection issues.

Detection of partial discharge patterns in hybrid high voltage power transmission lines based on parallel recognition method

Due to their specially designed structures, the partial discharge detection of hybrid high-voltage power transmission lines (HHVPTL) composed of overhead lines and power cables has made it difficult to monitor the conditions of power transmission lines. A parallel recognition method for partial discharge patterns of HHVPTLs is proposed by implementing wavelet analysis and improved backpropagation neural network (BPNN) to address the shortcomings of low efficiency, poor accuracy, and inability to parallel analysis of current partial discharge (PD) detection algorithms for HHVPTLs. Firstly, considering the non-smoothness of the partial discharge of the HHVPTLs, the wavelet packet decomposition algorithm is implemented to decompose the PD of the HHVPTL and resolve the relevant signal indicators to form the attribute vectors. Then, BPNN is implemented as a classification model. A beetle optimization (DBO) algorithm based on orthogonal contrastive learning improvement is introduced to optimize the BPNN parameters since BPNN has a slow convergence problem and fails easily into a local optimum. The proposed IDBO-BPNN is employed as the model that recognizes and analyzes the parallel partial discharge patterns of HHVPTLs. Finally, the suggested model is implemented to investigate the local discharge data of an HHVPTL in the Kaggle Featured Prediction Competition and is compared with other algorithms. The experimental results indicate that the proposed model can more accurately identify whether PDs occur in an HHVPTL and detect phases where PDs occur, with higher overall accuracy and efficiency. An excellent practical performance is achieved. The proposed model can achieve the recognition accuracy of 95.5%, which is 5.3333% higher than that of the DBO-BPNN and far more than other recognition algorithms.

The social-ecological benefits of grain for green program based on coupled coordination network: Taking the China’s Loess Plateau as an example

The Grain for Green Program (GFGP) is the world’s largest payment for ecosystem services (PES). In the past 20 years, the Chinese government has implemented three stages of GFGP, which have profoundly affected the social-ecological benefits (SEB) of China’s Loess Plateau (LP), one of the regions with the most severe soil erosion and the most fragile ecological environment in the world. Therefore, we explored the changes and coupling coordination relationships of LP’s SEB in the past three stages of GFGP, and examined the spatial correlation network relationships between various units and their roles of GFGP, which was particularly important for the rationality and implementation direction of LP’s GFGP in the future. We found that in different GFGP stages, changes in LP’s SEB showed stage differences and spatiotemporal differences. The comprehensive social benefits (CSB) changed slowly (1.342 dropped to 1.232), and there was an obvious “northwest-southeast” regional division in space. The changes in comprehensive ecological benefits (CEB) fluctuated more obviously (1.481, 1.638, 0.597). After experiencing significant improvements of CEB in two stages, it entered a bottleneck period in the third stage. For a long time, the LP’s SEB have been in a state of coupling coordination, but the coupling coordination degree dropped to 0.493 in the third stage. With climate change, the continuous increase in potential grain yield has led to increasing losses in CSB. It was difficult to promote further coordination of LP’s SEB by accelerating the improvement of CEB. The coupling coordination degree has gradually moved from overall coupling coordination to mild imbalance. At the same time, the overall density of the SEB coupling coordination space network correlation was 0.218, which has shown an obvious network structure, and formed four major sectors: main beneficiary sector, broker sector, net overflow sector, and bidirectional overflow sector in each stage of GFGP. The role of each county has undergone regional changes in the entire GFGP, and there were recurring power transmission mechanisms and complex network formation factors. Based on this, we proposed to promote the coupling coordination and positive network transmission of SEB in the next stage of LP’s GFGP through “low-carbonization of agricultural production”, “further improvement of the compensation mechanism”, and “fusion of power transmission mechanism and network formation factors”.

Biocomposite silk fibroin hydrogel with stretchability, conductivity and biocompatibility for wireless strain sensor

As a natural biopolymer material, silk fibroin with unique mechanical properties can be used in the preparation of biocomposite hydrogels for strain sensors. But, the electromechanical properties of biocomposite hydrogel strain sensors are still insufficient, such as the deterioration of electrical signals and low sensitivity, which need to develop a hydrogel with a stable transmission network for electric conduction. Herein, a silk fibroin biocomposite hydrogel is prepared by incorporating tannic acid and MXene nanosheets into a polyacrylamide and silk fibroin double network. The electromechanical properties of hydrogels are improved by optimizing the proportion of material components. As a result, the double network structure and supramolecular interaction enhance the stretchability of hydrogels (692% fracture strain). The hydrogel also exhibits good biocompatibility and conductivity (0.85 S/m), which shows the application prospect in wearable sensors. The wireless strain sensor assembled by this biocomposite hydrogel presents good portability and sensing performance, such as high sensitivity (gauge factor = 6.04), wide working range (500% strain), and outstanding stability (1000 cycles at 100% strain). The results indicate that the hydrogel strain sensor can be used to monitor human body movement. The biocomposite hydrogel is expected to be applied in the field of wearable strain sensors, and this study can provide a new way for the design of flexible electronic materials.

Analysis of Model Predictive Control-Based Energy Management System Performance to Enhance Energy Transmission

A supervisory control system using Model Predictive Control (MPC) has been designed to evaluate the efficiency of wind and solar power and is consistent with the cost function in the supervisory MPC optimization problem. A two-layer Economic Model Predictive Control (EMPC) framework has been developed and has improved results such as cost reductions compared to recent advanced methods. A speed Generalized Predictive Control (GPC) scheme intended for wind energy conversion systems was developed last year, with simulation results indicating superior performance over previous models. A Hierarchical Distributed Model Predictive Control (HDMPC) can work under different weather conditions with improved economic performance and keep a good balance between power delivery and load demand. An energy management system (EMS), built on the basis of MPC, can be quite lucrative for the sphere in the present climate scenario, with the selection and testing of suitable algorithms, controlled processes, cost functions, and a set of constraints as well as with proper optimizations carried out. Previous research indicates that an MPC-based EMS has the potential to be a good solution to manage energy well and also introduced it to the world experimentally. The key intention of this research study is to explore the existing advances that have been introduced and to analyze their performance in terms of cost function, different sets of constraints, variant conversion processes, and scalability to achieve more optimized operation of MPC-based EMS.

Optimizing electrical and thermal performance in AlGaN/GaN HEMT devices using dual‐metal gate technology

AbstractThe investigation of aluminum gallium nitride/gallium nitride high electron mobility transistor (AlGaN/GaN HEMT) devices with a dual‐metal gate (DMG) structure encompasses both electrical and thermal characteristics. As efforts to enhance heat dissipation progress, there is a concurrent exploration of novel semiconductor materials boasting high thermal conductivity, like boron arsenide and phosphide. Combining these materials into a model and measuring their interface achieves efficient energy transport. Minimizing the self‐heating impact in AlGaN/GaN HEMTs is essential for enhancing device efficiency. This research exposes the heterogenous combination of boron arsenide and phosphide cooling substrates with metals, GaN semiconductors and HEMT. In this research, the autoencoder deep neural network techniques in GaN HEMT for self‐heat reduction is driven by the ability to effectively analyze and model the thermal behavior of the device. Autoencoders learn complex relationships within temperature data and identify patterns associated with self‐heating. By leveraging these learned representations, the deep neural network optimizes control strategies to mitigate self‐heating effects in GaN HEMT devices, ultimately contributing to improved thermal management and enhanced overall performance. In this research, the use of genetic algorithms in GaN HEMT aims to optimize device parameters systematically, to minimize self‐heating effects and enhance overall thermal performance. The structure also enhances electron mobility within the channel. Results show DMG structures, exhibiting higher saturation output currents and transconductance despite self‐heating. The DMG exhibits a maximum gm value of 0.164 S/mm, which is 10% higher significantly enhancing GaN‐based HEMTs for improved reliability and efficiency in various applications.