Experimental Tests Research Articles

Optimization Design of Cogging Torque for Electric Power Steering Motors

Excessive cogging torque can cause torque fluctuations, noise, and vibration in electric power steering (EPS) motors, which is a key factor in the high-precision and high-performance optimization design of EPS motors for electric vehicles. This article takes a 12-slot 10-pole electric power steering motor for a certain car as an example. By establishing the corresponding electromagnetic field model and theoretical analysis of the motor, the influence of the pole arc coefficient and eccentricity parameters of the permanent magnet on the cogging torque of the electric power steering motor is explored. A comprehensive optimization scheme for reducing the cogging torque of the motor structure is proposed. The effectiveness of the designed scheme was verified through finite-element simulation and experimental testing of motor electromagnetism. Compared with the original design, the optimized structure of the EPS motor resulted in an 86.62% reduction in cogging torque during experimental testing.

Identification of key drivers of antimicrobial resistance in Enterococcus using machine learning.

With antimicrobial resistance (AMR) rapidly evolving in pathogens, quick and accurate identification of genetic determinants of phenotypic resistance is essential for improving surveillance, stewardship, and clinical mitigation. Machine learning (ML) models show promise for AMR prediction in diagnostics but require a deep understanding of internal processes to use effectively. Our study utilized AMR gene, pangenomic, and predicted plasmid features from 647 Enterococcus faecium and Enterococcus faecalis genomes across the One Health continuum, along with corresponding resistance phenotypes, to develop interpretive ML classifiers. Vancomycin resistance could be predicted with 99% accuracy with AMR gene features, 98% with pangenome features, and 96% with plasmid clusters. Top pangenome features overlapped with the resistance genes of the vanA operon, which are often laterally transmitted via plasmids. Doxycycline resistance prediction achieved approximately 92% accuracy with pangenome features, with the top feature being elements of Tn916 conjugative transposon, a tet(M) carrier. Erythromycin resistance prediction models achieved about 90% accuracy, but top features were negatively correlated with resistance due to the confounding effect of population structure. This work demonstrates the importance of reviewing ML models' features to discern biological relevance even when achieving high-performance metrics. Our workflow offers the potential to propose hypotheses for experimental testing, enhancing the understanding of AMR mechanisms, which are crucial for combating the AMR crisis.

Structural Damage Model of Steel Structure Connections with Initial Defects: A Review

As the application of steel structures in construction continues to grow, research into their seismic performance is becoming increasingly important. This paper focuses on steel structure connections, specifically those between components with varying profiles such as H-profiles, box-profiles, and L-profiles. Additionally, it encompasses three core areas: seismic performance (bearing capacity, ductility, stiffness), initial defects (initial cracks, residual stresses, manufacturing imperfections), and damage models (weld fractures, bolt failures, plate buckling). In addition, this paper employs experimental testing and finite element, with a focus on conducting parametric analyses for the connections. Based on the primary findings, the presence of initial defects such as cracks, residual stresses, and manufacturing imperfections can lead to premature failure, concentrating damage near welds and exacerbating stress concentrations. This adversely affects factors like fatigue strength, fracture toughness, and buckling strength, ultimately reducing the seismic performance of the connections. Moreover, factors like bolt over-tensioning, geometric deviations in plate components, and corrosion can further impact bearing capacity, fatigue performance, and ductility. Crucially, these initial defects not only compromise the seismic resistance of structures but also increase the risk of structural failure. However, majority of existing research has focused on monotonic and cyclic loading studies, with limited exploration of connections under seismic conditions. Acknowledging this gap, this paper outlines a future research agenda aimed at refining the design of steel structure connections. This initiative seeks to mitigate potential adverse consequences stemming from formidable seismic events, thereby enhancing the overall resilience of these crucial connections.

Fabrication, Modeling, and Testing of a Prototype Thermal Energy Storage Containment

Abstract Increasing penetration of variable renewable energy resources requires the deployment of energy storage at a range of durations. Long-duration energy storage (LDES) technologies will fulfill the need to firm variable renewable energy resource output year round; lithium-ion batteries are uneconomical at these durations. Thermal energy storage (TES) is one promising technology for LDES applications because of its siting flexibility and ease of scaling. Particle-based TES systems use low-cost solid particles that have higher temperature limits than the molten salts used in traditional concentrated solar power systems. A key component in particle-based TES systems is the containment silo for the high-temperature (>1100 ∘C) particles. This study combined experimental testing and computational modeling methods to design and characterize the performance of a particle containment silo for LDES applications. A laboratory-scale silo prototype was built and validated the congruent transient finite element analysis (FEA) model. The performance of a commercial-scale silo was then characterized using the validated model. The commercial-scale model predicted a storage efficiency above 95% after 5 days of storage with a design storage temperature of 1200 ∘C. Insulation material and concrete temperature limits were considered as well. The validation of the methodology means the FEA model can simulate a range of scenarios for future applications. This work supports the development of a promising LDES technology with implications for grid-scale electrical energy storage, but also for thermal energy storage for industrial process heating applications.

Performance of GFRP Sheets in Strengthening Concrete Beams in Flexure

Plain concrete beam repair and strengthening are increasingly important in structural strengthening and retrofitting. This study examines the glass fibre-reinforced polymer (GFRP) sheets in plain concrete beams under flexural behaviour by using its patching sheets. Through the implementation of a symmetrical four-point static loading technique, a series of tests were conducted on plain concrete beams that had been externally joined with GFRP sheets. These beams were subjected to rigorous testing until they reached their ultimate failure point. The experimental test consists of casting nine plain concrete beams with identical specifications. Three beams are utilised as control beams; three are reinforced with GFRP sheets measuring 50 mm × 100 mm, and another three are reinforced with GFRP sheets measuring 100 mm × 200 mm. The flexural test is designed to determine the tensile strength of concrete under bending. Compared to the control beams, the specimens strengthened with GFRP sheets demonstrated a significantly enhanced ultimate load capacity. The beams with larger GFRP sheets exhibited a higher ultimate load of 14.84 kN, while those with smaller sheets showed an ultimate load of 8.54 kN, marking an appreciable improvement in performance. Moreover, the smaller area GFRP-reinforced beams failed at a 45% higher shear stress compared to those with a larger area GFRP, indicating a differential impact based on the size of the reinforcement used. This study highlights the effectiveness of GFRP sheets in enhancing the structural performance of plain concrete beams, providing crucial insights into the benefits of different sizes of reinforcement.

Effect of swirl injection parameters on cooling performance of vortex-cooled bipropellant thruster

The cooling performance of a 10N-class gaseous Propane/GOx bi-propellant thruster with vortex cooling was investigated in this experimental study. Injecting oxidizer with a vortex was proposed as a potential cooling method for a semi-thermoplastic constructed thruster and demonstrated as a promising integrated cooling method that can be fabricated using 3D printing technology. Compared to other cooling types, vortex cooling has low system complexity and can be 3D printed as a single solid piece along with a thruster, reducing design complexity, weight, and manufacturing time. The experimental testing examined various injection configurations and their associated parameters to determine the most optimal injection combination. The test collected a comprehensive amount of data to evaluate the cooling performance with respect to varying operational parameters: oxygen-to-fuel ratio, propellant mass flow rate, and injection configuration. The study found that the acrylic chamber operated safely with a proper injection configuration identified maintaining the temperature of the thruster chamber walls below 60 °C, lower than the melting point of the acrylic material, with no damage observed. It was found that the downstream swirl injection had more favourable vortex cooling performance than the upstream injection for the scale of the thruster considered in this study.

Baryon-number — flavor separation in the topological expansion of QCD

Gauge invariance of QCD dictates the presence of string junctions in the wave functions of baryons. In high-energy inclusive processes, these baryon junctions have been predicted to induce the separation of the flows of baryon number and flavor. In this paper we describe this phenomenon using the analog-gas model of multiparticle production proposed long time ago by Feynman and Wilson and adapted here to accommodate the topological expansion in QCD. In this framework, duality arguments suggest the existence of two degenerate junction-antijunction glueball Regge trajectories of opposite C\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\mathcal{C} $$\\end{document}-parity with intercept close to 1/2. The corresponding results for the energy and rapidity dependence of baryon stopping are in reasonably good agreement with recent experimental findings from STAR and ALICE experiments. We show that accounting for correlations between the fragmenting strings further improves agreement with the data, and outline additional experimental tests of our picture at the existing (RHIC, LHC, JLab) and future (EIC) facilities.

Finite-discrete element modelling of fracture development in bimrocks

Block-in-matrix rocks (bimrocks) are a complex geological feature composed of hard blocks in a weak matrix bonded together via a weak interface. The failure mechanism and deformation behavior of the bimrocks is quite complex due to the simultaneous existence of blocks with different shapes, strengths and proportions in a matrix. Therefore, it is of great importance to characterize the bimrocks under different situations. This study employs the combined finite-discrete element method (FDEM) to characterize the failure pattern and load carrying capacity of the bimrocks considering changes in various parameters, including block size, volumetric block proportion (VBP), the strength ratio of block-matrix interface to matrix, and the shape of the blocks (angular, circular, and elliptical shapes). First, the robustness and feasibility of the FDEM in modeling fracture development is verified against an analytical solution as well as a series of experimental tests accompanied with the digital image correlation (DIC) method. Then, the verified model is used to model disc specimens with various block shapes and properties. The results indicate the remarkable influence of VBP, block size and block-matrix interface characteristics on the bimrock mechanical behavior under the same VBP. The results are assessed based on macroscopic observations to investigate the influence of determinative physical properties of bimrocks. The results are also evaluated based on the mode of failure, mode I, II, or mixed mode, to qualitatively elucidate the influence of key factors on the formation of different cracks in different places, including the interface of matrix-blocks or intergrain or intragrain. The results show that since the loading is a quasi-static scheme, all the cracks are intergrain and no intragrain crack is observed for any VBP. The simulations outcomes shows that the block sizes determine the failure pattern, failure mode, and load–displacement behavior, where the larger blocks exhibiting the lowest load carrying capacity due to experiencing more interface breakage in shear. It is found that the VBP is a crucial parameter in the deformation of the bimrocks, showing that the strength of the bimrocks significantly increases with a decrease in the VBPs and the ones with greater VBPs experience more breakage and thus less resistance to loading. The block-interface strength is found to be the most critical factor in the deformation of the bimrocks (regardless of the value of the VBP). Finally, the effect of block shape is shown to have a considerable impact on bimrocks with the higher VBPs (more than 70%).

Research on Structural Design and Optimisation Analysis of a Downhole Multi-Parameter Real-Time Monitoring System for Intelligent Well Completion

In this paper, based on electro-hydraulic composite intelligent well-completion technology, a new type of downhole multi-parameter real-time monitoring system design scheme is established. Firstly, a multi-parameter real-time monitoring system with a special structure is designed; secondly, its reliability is analysed by applying the method of numerical simulation; finally, in order to verify the reliability of the simulation results, a principle prototype is developed, and indoor experimental tests of fluid flow are carried out. The experimental results show that the flow rate is directly proportional to the differential pressure, and when the flow rate is certain, the higher the water content, the higher the differential pressure. The indoor experimental flow rate of 400~1000 m3/d is measured with high accuracy, and the error range is within 5%. Numerical simulation and experimental results with a high degree of fit, a flow rate of 400–1000 m3/d, the two error range within 10%, the integrated flow coefficient of the experimental value is stable between 0.75–0.815, the simulation value is stable between 0.80–0.86. The mutual verification of the two shows that the flow monitoring design meets the requirements and provides a reference basis for the structural design of the intelligent, well-completion multi-parameter real-time monitoring system.

An experimental test of endfire synthetic aperture sonar for sediment characterisation

AbstractThe validation of seafloor scattering models used for seabed characterisation requires quantifying the contributions from the sediment interface and volume to the total acoustic returns. At low‐frequencies, direct measurements of sediment volume scattering have rarely been made, due to the bias in interface roughness scattering caused by large beamwidths of low‐frequency sonars. Endfire Synthetic Aperture Sonar (EF‐SAS) can achieve narrower beamwidths by forming a vertically oriented synthetic array as a transmitter and/or receiver and moving it through the water column. The narrower beamwidths achieved by EF‐SAS allow for more accurate measurements of volume scattering by reducing interface scattering bias in acoustic returns. The application of EF‐SAS for sediment characterisation is explored for the first time. The authors demonstrate that EF‐SAS can be used to construct the angular response curve for both interface and volume scattering as well as to estimate the attenuation and reflection coefficients, which can be inverted for grain size.

Investigation of the performance of a newly designed solar chimney for enhancing natural ventilation and mitigation of summer overheating

The significant challenge encountered in utilizing Trombe walls for winter heating is summer overheating, which limits the overall feasibility of the system. In response to this issue, the present study introduces a novel model of a Trombe wall-solar chimney system designed to enhance natural ventilation and address the problem of summer overheating. To assess the performance of the proposed model, a full-scale experimental test rig is constructed in Kirkuk, Iraq. This rig comprises a test room integrated with a Trombe wall-solar chimney system. Additionally, a numerical simulation based on the CFD approach along with a computer code is developed to investigate the behavior of the system. System analysis is conducted for the period August 14th–15th. The parameters studied include chimney height (ranging from 0.0m to 2.0m in 0.5m increments), chimney width (0.2m, 0.3m, 0.4m, and 0.5m), room inlet vent height (ranging from 0.2m to 0.4m with 0.05m increments), and chimney inlet vent height (ranging from 0.2m to 0.4m with 0.05m increments). The results highlight the crucial role of the massive storage wall in sustaining nighttime ventilation in the absence of solar energy by utilizing stored heat to warm the air and maintain the ventilation process. The study establishes that chimney height and width significantly influence airflow rate, while other factors have marginal effects. An empirical equation is formulated to predict the 24-h averaged air changes per hour (ACH), which is a critical measure of system performance in ventilation. This equation is developed using artificial neural network (ANN) techniques. Finally, the findings indicate that the suggested model effectively reduces summertime overheating while generating a satisfactory ventilation rate. This enhances the overall versatility and year-round usability of Trombe wall systems, making them more adaptive and efficient in regions with diverse climatic conditions.

Enhancing CLT floor vibration mitigation with pre-strained shape memory alloy-tuned mass dampers

Cross-laminated timber (CLT), recognised for its environmental benefits, faces challenges in its excessive human-induced vibration due to its lightweight nature. This research investigates the application of a tuned mass damper (TMD) for vibration control in CLT floor slabs, focusing on enhancing the structural performance of using this sustainable building material. The study introduces a solution by integrating Shape memory alloy (SMA) into TMD systems (SMA-TMD), utilising the properties of SMAs for effective self-centring and consistent damping, and it aims to incorporate pre-strained SMAs into TMDs to improve the damping performance of the system. Experimental testing and finite element simulations confirm that pre-straining SMA bars not only contribute to the self-centring but also considerably increase the equivalent viscous damping ratio of the SMA-TMD. Findings from the simulations demonstrate that the optimised SMA-TMD system can substantially reduce CLT floor vibration and accelerates the energy dissipation effect under human footfall loadings, overcoming one of the primary limitations of CLT in construction applications. This advancement supports the broader adoption of CLT as a sustainable building material by providing a viable solution for vibration control.

Strength capacity of RC beams without shear reinforcement: Numerical analysis and comparisons with code provisions

The investigation of the behavior of reinforced concrete (RC) elements without shear reinforcement is a current focal point, driven by the incomplete consolidation of predictive formulas for shear strength in RC elements. Currently, the literature provides, indeed, a limited number of experimental and numerical studies on this subject. This paper seeks to advance the comprehension of the behavior and collapse mechanisms of RC beams not provided of shear reinforcement, as commonly employed in RC slabs of bridges. The paper commences with a critical review of several predictive formulas for the shear strength of RC elements lacking transverse reinforcement, as stipulated by various international codes. The objective is to identify the principal parameters involved in the formulations and discuss their roles also by means of sensitivity analysis. Following this, the results of nonlinear numerical analyses, based on a three-dimensional finite element (FE) model, are presented. The FE model was initially calibrated using experimental results from a benchmark beam lacking shear reinforcement, retrieved from the literature, which exhibited a brittle shear failure. Subsequently, several specimens were prepared for the numerical investigation, assuming multiple combinations of geometrical and mechanical parameters. For specimens experiencing shear failure, the strength was compared with that provided by code formulas, as well as using the strut-and-tie approach for the cases characterized by a reduced shear span-to-depth ratio. In general, these analytical tools significantly underestimated the numerical strength, underscoring the necessity for further insights based on experimental tests. The numerical outcomes have been, indeed, prodromal to design an experimental campaign.

Multi-Physics Simulation and Optimization of Jet Electrodeposition for Ni–Diamond Composite Coatings

This work investigated the influence of current density, plating solution flow rate, and nozzle outlet-to-cathode distance on the properties of Ni–diamond composite coatings. A multi-physics field simulation was employed to analyze the interplay between current density, plating solution flow rate, and nozzle outlet-to-cathode distance on the flow field and electric field distribution. Additionally, particle tracing simulations were incorporated into the model to evaluate the incorporation efficiency of diamond particles during composite electrodeposition. It was found that when the inlet flow rate of the electrolyte was 5 L/min, the distance between the nozzle outlet and the cathode was 3 mm, and the current density was 60 A/dm2, the composite electrodeposited coating had a higher particle content and better uniformity. The simulation results were validated through experimental preparation and performance testing. This combined approach provides valuable insights for optimizing the jet electrodeposition process for Ni–diamond composite coatings with superior properties.

Acceleration of Iron-Rich Olivine CO2 Mineral Carbonation and Utilization for Simultaneous Critical Nickel and Cobalt Recovery

CO2 mineral carbonation is an important method to sequester carbon dioxide (CO2) in the form of stable mineral carbonates for permanent storage. The slow kinetics of carbonation, especially for iron-rich olivine, is the major challenge for potential application. This work proposes methods to accelerate the mineral carbonation process of different materials in the general mineral grouping of divalent metals–olivine for simultaneous nickel and cobalt recovery. It is found that nickel-olivine is facile for mineral carbonation compared to ferrous and magnesium olivine. Ferrous olivine is the most difficult form of olivine to carbonate as illustrated in both thermodynamics and experimental test results. The increase in iron content in olivine inhibits the CO2 mineral carbonation process by forming an iron-silica-rich passivation interlayer. The use of a reducing gas or reagent can enhance the mineral carbonation of olivine probably through hindering oxidation of Fe(Ⅱ). The addition of sodium nitrilotriacetate (NTA) as a metal complexing agent is much more efficient for the acceleration than usage of a reducing atmosphere. The combination of sodium bicarbonate/CO2 gas supply and NTA can enhance the diffusion of all divalent metal ions from the reacting olivine surface, thereby limiting the formation of the passivation interlayer. Meanwhile, highly selective nickel and cobalt leaching can be simultaneously achieved along with the CO2 mineral carbonation, 94% nickel, and 92% cobalt leaching as well as 47% mineral carbonation versus only 10% iron and 1% magnesium leached in 2 h. This work provides a novel direction to achieve critical metals recovery with accelerated mineral carbonation process.

EFFECT OF ECO ENZYME ADDITION ON THE IMPROVEMENT OF WATER QUALITY, REDUCTION OF AMMONIA AND METAL IN DUG WELL WATER

This study aims to: (1) Analyze the effect of artificial eco enzyme addition on improving the quality of dug well water based on pH, TDS, TSS, and DO parameters; (2) Analyze the effect of artificial eco enzyme addition on reducing ammonia and metal content in dug well water. The type of research is a laboratory-scale experiment with a quantitative approach to dug well water samples treated using a complete randomized design (CRD). The characteristics of the experimental test are 4 times treatment 1 time repetition in a homogeneous sample population. The conclusion of the research is that the provision of artificial eco enzyme has an effect in the form of an average increase and decrease in each parameter of the water quality of the dug well, namely pH 0,4, TDS 22 mg/l, TSS 13,3 mg/l, DO 4,2 mg/l, NH3 2,5 mg/l, Fe 0,4 mg/l, and Mn 0,03 mg/l. Based on one-way ANOVA testing resulted in sig. 0.001 0.05 and Duncan testing resulted in different number notations in each sample with sig. 1.000 0.05 which means the addition of eco enzyme gives a real influence on improving the quality of well water.

Response Surface Methodology Approach for Modeling and Performance Optimization of a PEM Fuel Cell

A Polymer Electrolyte Membrane (PEM) fuel cell is a popular green source of electrical energy and is often used in applications like electric vehicles due to its environmentally friendly operation. This type of fuel cell has a low operating temperature, light weight, and negligible emission of greenhouse gases. However, the PEM fuel cell is a complex multivariable system with a large number of input and output factors, and most of the input factors affect output factors directly or indirectly. As a result, it is conventionally quite difficult to determine which input factor has a major effect on a particular output factor. Statistical methods are very popular for finding the individual and interaction effects of input factors on output factors. In this paper, for the first time, a simple and realistic MATLAB SIMULINK model for a PEM fuel cell is presented to conduct various experimental tests. The developed MATLAB SIMULINK model and statistical design of experiments, Response Surface Methodology (RSM), are used to develop metamodels (mathematical models of the simulation model) for the PEM fuel cell to find the individual and interaction effects of various input factors on output factors. The developed metamodels can be used to find the region for optimum operation of the presented fuel cell. The metamodels are validated by conducting four different statistical tests. The optimum point of operation is presented by calculating stationary points from the metamodels.

Fatigue life prediction of friction-stir-welded aluminum bridge decks – Experimental tests and numerical framework

This paper presents the results of experimental tests and proposes a numerical framework for the prediction of the fatigue behaviour of friction stir welded (FSW) butt-lap joints of aluminium bridge deck extrusions. Fatigue test specimens made of welded real roadway bridge deck extrusions were subjected to cyclic bending under different loading conditions. The fatigue failure modes were thoroughly analyzed. A numerical framework incorporating a 2D finite element (FE) model based on the theory of critical distances (TCD) and a simplified linear elastic fracture mechanics (LEFM) model was developed to predict the fatigue failure initiation location and the fatigue life of the specimens under the test conditions. The location of the failure initiation played a key role in the choice of the numerical approach adopted in the prediction of fatigue life. For fatigue failures initiating from the base metal, the framework utilizes the TCD formulations while for failures in the weld joint, the LEFM model was applied. The proposed numerical framework showed a good agreement with the experimental data.

An Empirical Study on the Upcycling of Glass Bottles into Hydrocyclone Separators

Cyclones are pivotal in mechanical process engineering and crucial in the complex field of separation technology. Their robustness and compact spatial requirements render them universally applicable and versatile across various industrial domains. Depending on the utilized fluid and field of application, both gas-based cyclones and hydrocyclones (HCs) are well established. Regarding HC design, enduring elongated flat cones have seen minimal alterations in shape and structure since their introduction over more than a hundred years ago. Experimental investigations regarding unconventional cone designs within scientific studies remain the exception. Therefore, this study focuses on alternative geometric configurations of the separation chambers and highlights their impact on separation and energy efficiency. To achieve this objective, different geometric shapes are investigated and retrofitted into HCs. The geometric foundation is derived from upcycled glass bottles. The repurposed bottles with a volume of 750 mL are used in conjunction with an inlet part, following the established Rietema design. Experimental tests are conducted with dilute phase separation, using 0.1–200 µm test particles in water. Comparisons between a bottle-based HC and a conventional Rietema design were conducted, establishing a benchmark against the standard. The findings revealed a noticeable correlation between separation efficiency and cone geometry. Conical designs demonstrated enhanced separation, particularly at lower volume flows. At the highest volume flow of 75 L min−1, the best performing bottle cyclones showed separation efficiencies of 78.5%, 78.4% and 77.9% and therefore are in a competitive range with 78.0% efficiency, achieved using the commercial Rietema design. Minimal disparities in cut sizes were observed in terms of separation grade efficiency among the models tested. Variations in separation efficiency and fractional efficiency curves indicated nuanced differences in classification efficiency.

A Fault Recovery Method for Distribution Networks With Distributed Power Sources Based on 5G Smart Terminal

Firstly, a smart terminal is designed based on 5G communication technology, which is embedded with various protection measurement devices to form a 5G smart terminal. A distributed control model for the distribution network is constructed based on 5G smart terminals, and an objective function is designed taking into account factors such as restoring important loads, surplus power supply in the distribution network, network losses, and the number of switch actions. Finally, the Sparrow Search Algorithm (SSA) is improved using elite reverse learning strategy and dynamic sine perturbation strategy, and it is used to solve the objective function. Based on the IEEE33 distribution network node system, experimental tests are conducted, and the results show that the average delay of 5G smart terminals is about 30ms. Taking 14:00 as an example, the proposed method achieves network loss, number of switch actions, recovered important load power, and power supply surplus of 46.39 kW, 3 times, 185.65 kW, 240.28 kW, respectively. The fault recovery effect of the distribution network is ideal.