Software Simulation Research Articles

Electric vehicle charger energy management by considering several sources and equalizing battery charging

This article proposes a novel energy management structure for electric vehicles, consisting of a supercapacitor and two types of batteries, to improve efficiency and navigable distance. The key features of a suitable energy storage system include high power and energy density, low cost and weight, minimal maintenance, and long life. Although batteries are the primary power storage source in electric vehicles, they have power limitations. Therefore, a high-power-density supercapacitor is added to the battery to create a hybrid energy storage system, reducing stress on the battery and increasing its lifespan. The article presents a new structure for hybrid storage systems based on the existence of a main battery, a replaceable battery, a supercapacitor, and a DC-DC converter. An active charge equalizer circuit for the main battery in standby mode and its control system are also introduced. A control method for dividing power between different sources under different conditions is presented, and the design parameters of the energy storage system are optimized using a genetic algorithm to minimize mass and losses. The performance of the proposed system is evaluated through simulation in MATLAB software and tested in a small-scale laboratory sample. The article also provides a detailed analysis of different working modes, including electric motor acceleration, low-speed mode, high-speed mode, and electric regenerative braking mode. Additionally, a control method for energy management between batteries and supercapacitors is introduced, aiming to increase efficiency. The results show that the proposed hybrid energy storage system can effectively improve the efficiency of electric vehicles.

Design of Variable Valve Timing and Electronic Control for Honda R18A

Abstract: This paper explores the Variable Valve Timing and Lift Electronic Control (VTEC) system developed by Honda, focusing on its mechanisms, design methodology, and impact on engine performance. VTEC optimizes engine efficiency and power by switching between cam profiles suited for low-RPM stability and high-RPM power output, controlled by the engine's computer based on operational conditions. We examine the intricate workings of the VTEC system, detailing its hydraulic actuation and the resulting enhancements in torque and horsepower. Our study centers on the Honda R18A engine, targeting increased maximum RPM and power output. Using theoretical analysis validated through Ricardo Wave software and MATLAB simulations, we determine optimal valve lift and timing to achieve the desired performance. Additionally, the research addresses the geometric parameters influencing airflow through the valves, providing a comprehensive understanding of the VTEC system's contribution to engine efficiency and driving experience. This investigation not only underscores the technological advancements in variable valve timing but also presents practical insights for automotive engineering applications.

Enhancing Administrative Penalty Enforcement in Market Supervision through Block chain-based Control and Timeliness Assurance

Abstract: This study delves into the complexities of market supervision in China, aiming to explore the integration of blockchain technology into this regulatory landscape. It primarily focuses on tackling challenges related to data access control and timely enforcement of administrative penalties using blockchain. Leveraging its decentralized and immutable ledger system, blockchain offers a promising solution to enhance security and transparency across sectors. By applying blockchain to market supervision, the objective is to establish a robust platform for managing administrative penalties efficiently and accountably. To assess its viability, sophisticated software simulation techniques are employed. Rigorous analysis evaluates security protocols, data availability, and overall system performance. This assessment is vital for identifying vulnerabilities and ensuring compliance with China's regulatory standards. Additionally, the study recognizes the importance of advancing blockchain technology continually. Staying updated on emerging trends is crucial for optimizing system performance, bolstering data privacy, and ensuring legal compliance. By addressing these areas, the study aims to provide actionable insights for designing and implementing blockchain solutions in China's market supervision. Through collaborative efforts and knowledge sharing, it seeks to drive innovation and enhance transparency, efficiency, and accountability in the market environment

Impact of semi-private open spaces on outdoor thermal comfort in a residential neighbourhood in warm humid climate

ABSTRACT Semi-private open spaces are indispensable as they enhance society’s growth and contribute to individuals’ health and well-being, thereby improving the quality of life in residential neighbourhoods. However, at present, the integration of such open spaces into the planning of housing projects is often neglected and results in incidental open spaces in the built environment. These incidental open spaces, if designed and integrated carefully, can enhance thermal comfort and community activities significantly. Therefore, this study aims to assess the impact of semi-private open spaces on outdoor thermal comfort in a residential neighbourhood in Kochi, India. A low-rise residential neighbourhood was selected for the study, and the semi-private open spaces were categorized into six typologies based on location, shape, proportions, orientation, aspect ratio, sky view factor, and albedo. Further, the outdoor thermal comfort conditions of these typologies were assessed through simulations in Envi-Met software for a critical summer day. The comfort conditions were assessed through comfort indices namely physiological equivalent temperature and mean radiant temperature (MRT) and were compared to arrive at appropriate design recommendations for semi-private open spaces. The study found a significant correlation between orientation, aspect ratio, sky view factor, and shading with outdoor thermal comfort. The study found a sky view factor of 0.3–0.5, an aspect ratio greater than 1.5, orientation of open spaces in the N-S axis, and shading by trees with canopies above 2.5 m height as appropriate design strategies to reduce the heat stress in semi-private open spaces in low-rise residential neighbourhoods. The study recognizes the importance of integrating planned semi-private open spaces in the local building regulations which can improve the quality of open spaces and enhance public health and well-being while contributing to a better microclimate.

Investigation of SiC MOSFET Body Diode Reverse Recovery and Snappy Recovery Conditions

This paper investigates the behavior of SiC MOSFETs body diode reverse recovery as a function of different operating conditions. The knowledge of their effects is crucial to properly designing and driving power converters based on SiC devices, in order to optimize the MOSFETs commutations aiming at improving efficiency. Indeed, reverse recovery is a part of the switching transient, but it has a significant role due to its impact on recovery energy and charge. The set of different operating conditions has been properly chosen to prevent or force the snappy recovery of the device under testing. The experimental results and specific software simulations have revealed phenomena unknown in the literature. More specifically, the analysis of the reverse recovery charge, Qrr, revealed two unexpected phenomena at high temperatures: it decreased with increasing gate voltage; the higher the device threshold, the higher the Qrr. TCAD-Silvaco (ATLAS v. 5.29.0.C) simulations have shown that this is due to a displacement current flowing in the drift region due to the output capacitance voltage variation during commutation. From the analysis of the snappy recovery, it has emerged that there is a minimum forward current slope, below which the reverse recovery cannot be snappy, even for a high current level. Once this current slope is reached, Qrr varies with the forward current only.

Control of overflows in interception wells based on water quantity and quality in rainwater pipelines for reducing pollution to rivers

ABSTRACT The separate sewer system has led to severe river pollution because of domestic sewage infiltrations and initial rainfall pollution. Therefore, interception wells (IWs) are installed to divert sewage to the wastewater treatment plant but similarly contribute to overflow-induced river pollution on rainy days. The aim of the present study is to propose a control strategy for the regulation of IWs’ overflow based on the online monitoring data, control measures, and software simulation. The results indicate that during light rain, overflow from the IWs is minimal, requiring no control measures. However during heavy rainfall, the overflow of sewage leads to an increase in the river’s concentration of NH3-N from 0.25 to 3.04 mg/L. Finally, Simulations demonstrate a reduction in river NH3-N levels from 2.27 to 1.33 mg/L after implementation. The results indicated the substantial effectiveness of measures in mitigating the pollution originating from IWs’ overflows during rainfall events.

#729 Application of ChatGPT to support nutritional recommendations for dialysis patients

Abstract Background and Aims The rising diversity of food preferences and the desire to provide better personalized care provide challenges to renal dietitians working in dialysis clinics. To address this situation, we explored the use of a Large Language Model (LLM), specifically, ChatGPT using the GPT-4 model (openai.com), to support nutritional advice given to dialysis patients. Method We applied a prompt that allows us to consider various factors that determine personalized dietary recommendations, menu options, and nutritional analysis. The prompt integrates several domains, including patient demographics (age, sex, race, and ethnicity) and food preferences (vegetarian, Indian, Latin American, Mediterranean, East Asian), laboratory data (levels of serum phosphate, potassium, albumin, calcium, and normalized protein catabolic rate), and clinical characteristics (height, BMI, comorbidities, and dialysis modality). Twenty virtual patients were created using Monte Carlo simulation in the statistical software R; we provided the characteristics of one randomly selected patient to ChatGPT (Fig. 1). The resulting daily recipe recommendations, cooking instructions, and nutritional analyses were reviewed and rated on a five-point Likert scale by an experienced renal dietitian. In addition, we entered the ChatGPT-generated recipes into an USDA-approved nutrient analysis software (ESHA research, Salem, OR, USA) for comparison. A pre-defined kidney-friendly recipe from the website of a large dialysis organization (Fresenius Medical Care (FMC), Waltham, MA, USA) was included for comparison as well. We were able to narrow down and personalize requests in a short dialogue with the bot, for example: “John is a hemodialysis patient. Age, years: 63.58; Height, cm: 181.52; BMI: 37.27; Serum albumin, g/dL: 3.08; Serum phosphate, mg/dL: 4.39; Serum potassium, mmol/L: 5.08; Total serum calcium, mg/dL: 8.63; nPCR, g/kg/day: 0.709; Sex: Male; Race/Ethnicity: Black; DM: No; CHF: No; Diet Restriction: No restriction; Food preferences: Latin American; Dialysis modality: HD; Budget: around $25. Can you create a one-day sample menu for this hemodialysis patient with recipes and nutritional analyses?” Results A daily menu comprising five recipes was created. The renal dietitian rated the recipes (2.9 on the 5-point Likert scale) and cooking instructions (4.8) as moderately satisfactory, but the nutritional analysis (2) was questionable. While ChatGPT's carbohydrate content estimation was relatively accurate, it underestimated calories by 36%, protein by 28%, and fat, phosphorus, potassium, and sodium by around 50% (Fig. 2A). Discrepancies observed with potassium may be partly explained by the analyses of raw vs. cooked ingredients (which may be altered by cooking techniques), unspecified portion sizes, and limited data for ChatGPT training (e.g., potassium is not a required nutrition label component). Interestingly, these discrepancies are much smaller with recipes garnered from the FMC website (Fig. 2B). The percentage differences between USDA's (=100%) and ChatGPT's estimations of recipes from different sources were shown in Fig. 2C. In addition, we explored the use of ChatGPT to create personalized dietary recommendations/menus in different languages, such as Mandarin. The translations, as judged by native speakers, were reliable. Conclusion While LLMs such as ChatGPT hold promise to provide personalized nutritional guidance to diverse populations of dialysis patients, we think that there is substantial room for improvement. Our findings underscore the importance of a critical approach and the need to assess qualitatively and quantitatively the output created by LLMs, especially regarding medical use cases.

Inductance Estimation Based on Wavelet-GMDH for Sensorless Control of PMSM

In permanent magnet synchronous motor (PMSM) sensorless drive systems, the motor inductance is a crucial parameter for rotor position estimation. Variations in the motor current induce changes in the inductance, leading to core magnetic saturation and degradation in the accuracy of rotor position estimation. In systems with constant load torque, the saturated inductance remains constant. This inductance error causes a consistent error in rotor position estimation and some performance degradation, but it does not result in speed estimation errors. However, in systems with periodic load torque, the error in the saturated inductance varies, consequently causing fluctuations in both the estimated position and speed errors. Periodic speed errors complicate speed control and degrade the torque compensation performance. In this paper, we propose a wavelet denoising-group method of data handling (GMDH) based method for accurate inductance estimation in PMSM sensorless control systems with periodic load torque compensation. We present a method to analyze and filter the collected three-phase current signals of the PMSM using wavelet transformation and utilize the filtered results as inputs to GMDH for training. Additionally, a method for magnetic saturation compensation using the inductance parameter estimator is proposed to minimize periodic speed fluctuations and improve control accuracy. To replicate the load conditions and parameter variations equivalent to the actual system, experiments were conducted to measure the speed ripples, inductance variations, and torque component of the current. Finally, software simulation was performed to confirm the inductance estimation results and verify the proposed method by simulating load conditions equivalent to the experimental results.

A model-based proportional-integral observer design for adhesion estimation in the wheel-rail interface: LMI approach

Adhesion estimation in wheel and rail interface is a crucial element as it has a direct effect on the locomotive characteristics and performance. Since the adhesion condition depends on unpredictable factors and dynamic models, its estimation is a complex task. In this paper, a dynamic model for a single wheelset including parameters in detail is developed to improve the accuracy of the model. Then, a model-based Proportional–Integral Observer (PIO) is designed to estimate adhesion during uncertainties and nonlinear parameters. The stability of the proposed PI observer is proved with Lyapunov theory and Linear Matrix Inequality (LMI). Finally, the performance of the method is evaluated via numerical simulation in MATLAB software, and it is validated with a model set-up in the SIMPACK Multibody Simulation (MBS) software.

VIRTUAL SCREENING OF ZANTHOXYLUM ACANTHOPODIUM DC. FRUIT BIOACTIVE COMPOUNDS AS NATURAL ANGIOTENSIN-CONVERTING ENZYME INHIBITORS

The angiotensin-converting enzyme inhibitors (ACEi) is a widely prescribed anti-hypertensive drugs targeting the renin-angiotensin system (RAS). These drugs still have limitations due to their side effects. This study aims to identify the potential of bioactive compounds from Andaliman fruit (Zanthoxylum acanthopodium DC.) as natural ACEi for the treatment of hypertension with an in-silico approach. Phytoconstituents from Z. acanthopodium fruits were screened using the SwissADME web server for their bioavailability. The selected compounds were then paired to human ACE (PDB ID: 1O86) by site-specific docking to the ACE binding pocket. The stability of the interaction between ligand and protein was evaluated using molecular dynamics simulations in YASARA software. From a total of 39 compounds, we predict that 5 compounds namely kaempferol, quercetin, abscisic acid, benzophenone, and cis-3,5,3,4-tetrahydroxystilbene can bind to ACE with good affinity and form interactions with key residues. The presence of these compounds may reduce the binding affinity of angiotensin I to ACE and alter the interaction site. Molecular dynamics simulations show the compounds have good interaction stability with ACE and remain in the active site until the end of the simulation. This study showed that five bioactive compounds from Andaliman fruit act potentially as natural ACE-inhibiting agents.

Time-frequency analysis of plate-shell coupled structures under moving stochastic load

Random vibration is of critical importance in understanding the dynamic behavior of engineering structures, especially the nonstationary responses for their coupled enclosers consisting of plates and shells subjected to moving stochastic loads. In this study, the pseudo excitation method (PEM) is integrated into the method of reverberation ray matrix (MRRM) to establish a full-domain stochastic dynamic system. With the help of rearrangement matrices and coupling spring connection technologies, the two plate-shell models of sequential and reinforced coupling are considered by employing the simple first-order shear deformation shell theory (S-FSDST) and Hamilton's principle. Then, the continuous movement of the excitation between each substructure is achieved through load coordinate normalization in nonhomogeneous equations, which are separated from the generalized solutions in the frequency domain. Therefore, it can be easily converted into a global pseudo-excitation and obtain the time-history responses relying on the inverse Laplace transform. After matching the present results with the finite element software and Monte Carlo simulation (MCS), the accuracy and efficiency of the proposed RRM-PEM are well-confirmed. Finally, by performing a series of numerical cases of power spectral density (PSD) and time-varying root mean square (RMS) under different loading velocities, frequency bands and system modal dampings, the time-frequency rules for different substructures of closed plate-shell coupled system under moving random loads are revealed for the first time.

Controllable Electrical Properties of ZrO2/BiFeO3 Bilayer Memristor from Synaptic Mimic to TRNG Circuit Application by Modulating Compliance Currents

AbstractApart from simulating biological synapses, memristors can also be used in the secure encryption by exploiting their inherent random resistive switching (RS) properties. In this work, nonvolatile Ta/BiFeO3/ZrO2/Pt memristor is fabricated with 2 nm inserting BiFeO3 layer. At a high compliance current of 10 mA, it presents gradual RS characteristics during the set process, which resulting in 30 conductance states. Synaptic behavior can be successfully mimicked by precise conductance modulating under pulse electrical stimulation. Whereas under a low compliance current of 500 µA, it exhibits abrupt RS behavior, and the set voltage ranged from 0.3–0.8 V, which can be effectively as an entropy source for true random number generator (TRNG). Due to its Shannon entropy of 300 bits is 0.99987, Hamming weights and intra‐Hamming distances tend to be 50%. Furthermore, the software simulation of encryption and decryption of cat image is achieved by combining the key generated by TRNG. The controllable electrical properties of the Ta/BiFeO3/ZrO2/Pt device can be modulated by the compliance current, thus meeting the computing or safety requirements, which provides a solid foundation for the development of integrating computation and security at the hardware level.

Hardware software co-design for leveraging STDP in a memristive neuroprocessor

In neuromorphic computing, different learning mechanisms are being widely adopted to improve the performance of a specific application. Among these techniques, spike-timing-dependent plasticity (STDP) stands out as one of the most favored. STDP is simply managed by the temporal information of an event, which is biologically inspired. However, most of the prior works on STDP are focused on circuit implementation or software simulation for performance evaluation. Previous works also lack a comparative analysis of the performances of different STDP implementations. This study aims to provide a comprehensive assessment of STDP, centering on the performance across various applications such as classification (static and temporal datasets), control, and reservoir computing. Different applications necessitate distinct STDP configurations to achieve optimal performance with the neuroprocessor. Additionally, this work introduces an application-specific integrated circuit design of STDP circuitry. The design is based on current-controlled memristive synapse principles and utilizes 65 nm CMOS technology from IBM. The detailed presentation includes circuitry specifics, layout, and performance parameters such as energy consumption and design area.

High variability in physician estimations of flow-diverting stent deployment versus PreSize Neurovascular software simulation: a comparison study

BackgroundPhysician variablity in preoperative planning of endovascular implant deployment and associated inaccuracies have not been documented. This study aimed to quantify the variability in accuracy of physician flow diverter (FD)...

Optimization of substation enclosure performance and carbon emission analysis based on OED

To explore the thermal performance parameters of substation enclosure parameters and interaction and influence degree, using the DeST software simulation and orthogonal test method to building load minimum as the target parameters, select external wall heat transfer coefficient, roof heat transfer coefficient, outer window heat transfer coefficient and orthogonal test factors, carry out the four factors three level L9 (34) Orthogonal test analysis, studied the influence of each factor and its interaction on the building load, and finally obtained the optimal combination of factors under the comprehensive boundary conditions. At the same time, the correlation between load and outdoor temperature in the optimal scheme of unmanned substation and the carbon emission results before and after optimization are also explored. The results show that through univariate analysis, with the heat transfer coefficient of exterior wall, roof and window, the cumulative cooling load is not linear. Through the orthogonal experimental analysis, the significance of substation building is> roof exterior wall> south Angle> window, and the optimal is A1-B1-C2-D2The annual cumulative building cooling load is 20165.59 kW h, and the peak cooling load appears on July 24. The operating condition of 0 ~ 9kW accounts for 90.6% of the annual operating time. There is a strong linear correlation between the building cooling load and the outdoor temperature (R2=0.65), the energy saving rate of the final optimized scheme is 17.71%, and the carbon saving rate is 26.72%. The research content of this paper provides reference for the renovation of existing buildings and the design of new buildings in substation buildings.

Quantitative characterization of 3D pore structures and percolation characteristics in bioturbated reservoir media based on X-ray micro-CT: a case study of the Neogene Sanya Formation in the Qiongdongnan Basin, Northern South China Sea

Organisms alter the primary texture of sediments, leading to alteration in petrophysical properties mediated by a textural and mineralogical contrast between burrow-fill and sediment host, which affects reservoir properties and fluid flow characteristics. In this article, in order to understand the microscopic pore structure and flow state of fluids in microscopic pores of bioturbated reservoirs, Ophiomorpha-bearing bioturbated reservoirs in the Neogene Sanya Formation of the Qiongdongnan Basin in the northern South China Sea were selected to research. Micro-CT was applied to scan selected core plugs, and a 3D pore structure model was established. The geometric characteristics of the microscopic pore structure were quantitatively and visually characterized by a modified maximal ball algorithm, and connectivity analysis of the pore structure was carried out. Numerical simulations of the percolation characteristics of the analyzed bioturbated reservoir samples were performed using digital core software (Avizo) and multi-physics field simulation software (Comsol). The results show that: (1) 3D pore structures reveal that pore volume, pore area, pore equivalent radius, throat area, throat equivalent radius and throat length have a large distribution range; among them, the pore volume has the largest distribution range, which can vary by six orders of magnitude, indicating that the pore size distribution of the bioturbated reservoir is uneven and has strong heterogeneous characteristics; (2) the connected pore structure is very complex, and as the equivalent radius of connected pore increases, the coordination number also gradually increases, the better the connectivity. Numerical percolation simulation results also suggested that larger connected pore space plays a key role in the effective permeability of the reservoir. This study has important implications for analyzing the modification effect of bioturbation on oil and gas reservoirs, and enhancing production and recovery in the study area.

Анализ влияния местных сопротивлений горных выработок на общешахтное аэродинамическое сопротивление

This paper aims to provide a quantitative assessment of the effect of local aerodynamic resistance on total mine airflow resistance with account for the friction resistance. The research includes laboratory tests, computer simulations in the Ansys CFD software as well as analytical inferences. The performed studies specified the magnitudes of local resistances at the turnings of mine workings. It has been established that the value of local resistance in all the sections can exceed 10% of the total mine aerodynamic friction resistance. This depends on the geometric parameters of the mine workings, which may result in a significant increase in the ratio of the local resistance value to the aerodynamic friction resistance value. The correlation of the two coefficients, i.e. the friction coefficient and the coefficient of local resistances, are proved to have a significant impact. The sharper the turns of the mine workings are, the greater the ratio of the local resistance to the aerodynamic friction resistance value is. Therefore, it is necessary to take this type of resistance into account when designing mine ventilation systems.

Water injection in single well model case study

This study compares two water injection patterns (line drive and five-spot) using CMG software in a cubic reservoir model based on Buzergan field data. Line drive injection showed higher water cut rates due to direct water flow, while the five-spot pattern distributes water flow across the area, resulting in lower water cuts. Economic analysis favors the line drive pattern for its lower setup cost and reduced water injection requirements. These findings offer insights for optimizing injection patterns and maximizing oil production in reservoir management. Highligt: Injection Pattern Comparison: Direct vs. Distributed Water Flow Analysis. CMG Software Simulation: Accurate Reservoir Modeling and Analysis Tool. Cost-Effective Optimization: Maximizing Oil Production with Economical Injection Strategies. Keyword: Water Injection Patterns, CMG Software, Reservoir Management, Oil Production Optimization, Economic Analysis

Evaluating tidal impact on ground source heat exchanger performance under fluctuating groundwater levels

Coastal regions undergo dynamic changes due to tidal forces, posing distinct challenges for groundwater management and utilization of ground source heat pump (GSHP) systems. This study examines the impact of tidal fluctuations on groundwater levels and the performance of ground heat exchangers (GHEs), specifically focusing on the suitability of horizontal directional drilling (HDD) technology in high-tidal zones. Itoman City in Okinawa Prefecture, Southern Japan, serves as an ideal location for this study due to its complex coastal hydrogeological conditions and increasing interest in renewable energy solutions. Employing a comprehensive approach involving field experiments, FEFLOW software simulations, and model validation, we aim to elucidate the intricate relationship between tidal dynamics, groundwater behavior, and GHE performance. Furthermore, our investigation assesses the effectiveness of HDD-GHEs installed in highly tidal-affected zones to determine the optimal installation depth for this type of GHE in coastal regions. According to our research, the layer at a depth of 30 m is most affected by tidal influence and fluctuations in groundwater levels in coastal regions. This layer is the most suitable for installing horizontal HDD-GHEs, with an average heat exchange rate of about 89 W/m. This rate is approximately four and two times higher than the depths above and below this layer, respectively, due to groundwater saturation and flow in the formation. Furthermore, we noticed that the heat exchange rate increases from the top to the bottom of this layer, but the extent of this increase diminishes as the depth increases. This is because deeper depths are less affected by tidal fluctuations in groundwater levels.

Design of Radial Distribution System to Study Load-Flow and Short Circuit Analysis Using ETAP Software

This work's analysis provides information on fault analysis and load flow studies, which help to understand how radial distribution networks operate both in normal and emergency circumstances. The research explores optimization methods, describing capacitor placement, transformer size, and feeder reconfiguration in order to lower losses and increase system efficacy. Moreover, the work looks at reliability-focused maintenance techniques, stressing the need of predictive maintenance and condition monitoring in raising the dependability of radial distribution networks. Modern electrical power networks depend heavily on their radial distribution system, which effectively and dependable distributes electricity to customers. Many radial distribution system-related topics are covered in detail on this website, including analytical methods, optimization processes, and dependability enhancement strategies. Power flow, voltage control, and losses in radial networks are investigated in this paper under a range of operational situations. The last and crucial stage of a power system, the electrical distribution system makes sure that customers have a steady supply of electricity. Regretfully, because it is often neglected and exposed to environmental risks, our distribution network has a number of problems. Our distribution feeder is rigorously analyzed for load flow and short-circuits in order to overcome these challenges and find and fix problems. The main topics of this study are the load flow and short-circuit analysis of a radial distribution feeder, which is mostly constructed with (ETAP). The final and crucial part of a power system, the electrical distribution system ensures that consumers receive an uninterrupted and steady supply of electricity. Our distribution feeder undergoes a rigorous and cautious process to address these issues front on because of the uncontrollable nature and susceptibility of our network to environmental hazards. This paper delves deeply into the issues of short-circuiting and load flow in radial distribution feeders. Both symmetrical and asymmetrical faults are thoroughly investigated by mathematical computations and ETAP simulations; the results of the software simulations are contrasted with those of the mathematical analysis. These discoveries will definitely influence the development and management of our system and point us in the direction of workable and practical solutions.