Solid-state batteries are widely recognized as the next-generation energy storage devices with high specific energy,high safety,and high environmental adaptability.However,the research and development of solid-state b...Solid-state batteries are widely recognized as the next-generation energy storage devices with high specific energy,high safety,and high environmental adaptability.However,the research and development of solid-state batteries are resource-intensive and time-consuming due to their complex chemical environment,rendering performance prediction arduous and delaying large-scale industrialization.Artificial intelligence serves as an accelerator for solid-state battery development by enabling efficient material screening and performance prediction.This review will systematically examine how the latest progress in using machine learning(ML)algorithms can be used to mine extensive material databases and accelerate the discovery of high-performance cathode,anode,and electrolyte materials suitable for solid-state batteries.Furthermore,the use of ML technology to accurately estimate and predict key performance indicators in the solid-state battery management system will be discussed,among which are state of charge,state of health,remaining useful life,and battery capacity.Finally,we will summarize the main challenges encountered in the current research,such as data quality issues and poor code portability,and propose possible solutions and development paths.These will provide clear guidance for future research and technological reiteration.展开更多
To investigate the overall performance of reverse energy bypass scramjet,firstly a variable spe⁃cific heat method combined with a chemical balance calculation module for combustion products were used to es⁃tablish a b...To investigate the overall performance of reverse energy bypass scramjet,firstly a variable spe⁃cific heat method combined with a chemical balance calculation module for combustion products were used to es⁃tablish a benchmark scramjet performance evaluation model.Based on the test data of typical flying point of Mach 7 with the altitude of 29 km,the reliability of the model was verified.The deviations of parameters such as the to⁃tal pressure loss of combustor between the model and the test data were analyzed.Furtherly,an analytical method for post-combustion magnetohydrodynamic power generation was established;by embedding the above method into the overall performance evaluation model,performance prediction considering the power generation effect was realized.Finally,based on the above model,variety regulations of the inlet and the outlet parameters of the power generation channel and performance parameters including the engine specific impulse and the unit thrust under different enthalpy extraction ratios and load factors were analyzed.It could be concluded that the model can reliably predict the variations of key parameters.As the value of the load factor increases,the value of the conduc⁃tivity required to reach the specified enthalpy extraction ratio first decreases and then increases,which is approxi⁃mately parabolic.In order to reduce the demand for the gas conductivity for MHD power generation,the load fac⁃tor should be around 0.5.When the load factor is 0.4 and the magnetic induction intensity is 2.5 T,if the enthalpy extraction ratio reaches 0.5%,the engine specific impulse performance reduces about 3.58%.展开更多
Sand production and high water content in oil wells are two major challenges that restrict high and stable production in loose sandstone reservoirs.In this paper,nano SiO_(2),coupling agent triethoxysilane,phenolic re...Sand production and high water content in oil wells are two major challenges that restrict high and stable production in loose sandstone reservoirs.In this paper,nano SiO_(2),coupling agent triethoxysilane,phenolic resin and n-octanol were used to synthesize the main agent SCA-2.Hexamethylenetetramine and vinyl carbonate were selected to prepare the curing agent YGA-1,which was then compounded with SCA-2 to develop a sand fixation and water plugging system.Firstly,single-factor experiments were conducted to determine the optimal concentrations of SCA-2 and YGA-1,subsequently,the system’s sand fixation and water blocking performance were evaluated.Finally,a pilot test was carried out in the mining site.Experimental results showed that the optimal formula composition of the system was 10%SCA-2+5%YGA-1.The gelation time of the system was 180 minutes and the viscosity after gelation could reach 108.4 mPa·s.When the dosage of the drug system was 0.6 PV,the sand production rate remained below 0.08%.Dual-tube parallel experiments showed that the sand fixation and water plugging system had a water flow channel plugging rate of 87.5%,while the oil flow channel plugging rate was only 11.3%,indicating minimal damage to the oil-bearing reservoir.The field test showed that after the measures taken in Well M of X oilfield,the sand free oil recovery period exceeded 360 days,the water content decreased by 5.0%and the cumulative oil production increased by 7092 m^(3).This study provides new ideas for efficient development of loose sandstone reservoirs.展开更多
During the final proofing stage of the paper,the wrong version of Fig.2 was accidently used when replacing it with a high-resolution version.The star and circle marks were missing in the published version.
Long-bone fractures are common complaints in orthopedic surgery.In recent years,significant progress has been made in robot-assisted fracture-reduction techniques.As a key medical device for diverse fracture morpholog...Long-bone fractures are common complaints in orthopedic surgery.In recent years,significant progress has been made in robot-assisted fracture-reduction techniques.As a key medical device for diverse fracture morphologies and sites,the design of the reduction robot has a profound impact on the reduction outcomes.However,existing reduction robots have practical limitations and cannot simultaneously satisfy clinical requirements in terms of workspace,force/torque,and structural stiffness.To overcome these problems,we first analyze the potential placement areas and performance requirements of reduction robots according to clinical application scenarios.Subsequently,a 3UPS/S-3P hybrid configuration with decoupled rotational and translational degrees of freedom(DOFs)is proposed,and a kinematic model is derived to achieve the motion characteristics of the remote center of motion(RCM).Furthermore,the structural design of a hybrid reduction robot with an integrated distal clamp and proximal fixator was completed,and a mechanical prototype was constructed.The results of the performance evaluations and static analysis demonstrate that the proposed reduction robot has acceptable workspace,force,and torque performance and excellent structural stiffness.Two clinical case simulations further demonstrated the clinical feasibility of the robot.Finally,preliminary experiments on bone models demonstrated the potential effectiveness of the proposed reduction robot in lower-limb fracture reduction.展开更多
Evaluating firms’financial performance is important for survival in the competitive environment arising from technological advancements and gaining a competitive advantage.This study aims to assess the financial perf...Evaluating firms’financial performance is important for survival in the competitive environment arising from technological advancements and gaining a competitive advantage.This study aims to assess the financial performances of firms traded on the Istanbul Stock Exchange 100 Index(Borsa Istanbul(BIST)100 Index)between 2018 and 2022 using an integrated multi-criteria decision-making(MCDM)method.This is the first study to use a new combined approach proposed based on the indifference thresholdbased attribute ratio analysis(ITARA)and cost estimation,benchmarking,and risk assessment(COBRA)methods,which have not been applied to corporate performance assessment.The ITARA method is used to find the weights of the criteria,and the ranking of the firms in terms of financial performance is obtained using the COBRA method.The results show that the firms with the highest financial performance are ISMEN,ALGYO,PGSUS,KOZAA,and IPEKE.The companies with the lowest financial performance are AKFGY,BAGFS,MGROS,KOZAL,and GOZDE.The results of this ranking provide important information for firms to recognize their position and for investors who want to invest in firms in the BIST 100 Index.Additionally,sensitivity analyses are performed to assess the impact of changes in the criteria on the ranking of the firms and to validate the results of the proposed method.A comparative analysis is made with different MCDM methods like the technique for order preference by similarity to ideal solution(TOPSIS),and combined compromise solution(CoCoSo)methods and Spearman’s rank correlation test results are presented.This approach leads to the conclusion that the proposed approach can be a useful and effective tool for assessing the financial performance of firms.展开更多
With the widespread application of Internet of Things(IoT)technology,the processing of massive realtime streaming data poses significant challenges to the computational and data-processing capabilities of systems.Alth...With the widespread application of Internet of Things(IoT)technology,the processing of massive realtime streaming data poses significant challenges to the computational and data-processing capabilities of systems.Although distributed streaming data processing frameworks such asApache Flink andApache Spark Streaming provide solutions,meeting stringent response time requirements while ensuring high throughput and resource utilization remains an urgent problem.To address this,the study proposes a formal modeling approach based on Performance Evaluation Process Algebra(PEPA),which abstracts the core components and interactions of cloud-based distributed streaming data processing systems.Additionally,a generic service flow generation algorithmis introduced,enabling the automatic extraction of service flows fromthe PEPAmodel and the computation of key performance metrics,including response time,throughput,and resource utilization.The novelty of this work lies in the integration of PEPA-based formal modeling with the service flow generation algorithm,bridging the gap between formal modeling and practical performance evaluation for IoT systems.Simulation experiments demonstrate that optimizing the execution efficiency of components can significantly improve system performance.For instance,increasing the task execution rate from 10 to 100 improves system performance by 9.53%,while further increasing it to 200 results in a 21.58%improvement.However,diminishing returns are observed when the execution rate reaches 500,with only a 0.42%gain.Similarly,increasing the number of TaskManagers from 10 to 20 improves response time by 18.49%,but the improvement slows to 6.06% when increasing from 20 to 50,highlighting the importance of co-optimizing component efficiency and resource management to achieve substantial performance gains.This study provides a systematic framework for analyzing and optimizing the performance of IoT systems for large-scale real-time streaming data processing.The proposed approach not only identifies performance bottlenecks but also offers insights into improving system efficiency under different configurations and workloads.展开更多
Seismic source locations can characterize the spatial and temporal distributions of seismic sources,and can provide important basic data for earthquake disaster monitoring,fault activity characterization,and fracture ...Seismic source locations can characterize the spatial and temporal distributions of seismic sources,and can provide important basic data for earthquake disaster monitoring,fault activity characterization,and fracture growth interpretation.Waveform stacking-based location methods invert the source locations by focusing the source energy with multichannel waveforms,and these methods exhibit a high level of automation and noise-resistance.Taking the cross-correlation stacking(CCS)method as an example,this work attempts to study the influential factors of waveform stacking-based methods,and introduces a comprehensive performance evaluation scheme based on multiple parameters and indicators.The waveform data are from field monitoring of induced microseismicity in the Changning region(southern Sichuan Basin of China).Synthetic and field data tests reveal the impacts of three categories of factors on waveform stacking-based location:velocity model,monitoring array,and waveform complexity.The location performance is evaluated and further improved in terms of the source imaging resolution and location error.Denser array monitoring contributes to better constraining source depth and location reliability,but the combined impact of multiple factors,such as velocity model uncertainty and multiple seismic phases,increases the complexity of locating field microseismic events.Finally,the aspects of location uncertainty,phase detection,and artificial intelligencebased location are discussed.展开更多
As an evaluation index,the natural frequency has the advantages of easy acquisition and quantitative evaluation.In this paper,the natural frequency is used to evaluate the performance of external cable reinforced brid...As an evaluation index,the natural frequency has the advantages of easy acquisition and quantitative evaluation.In this paper,the natural frequency is used to evaluate the performance of external cable reinforced bridges.Numerical examples show that compared with the natural frequencies of first-order modes,the natural frequencies of higher-order modes are more sensitive and can reflect the damage situation and external cable reinforcement effect of T-beam bridges.For damaged bridges,as the damage to the T-beam increases,the natural frequency value of the bridge gradually decreases.When the degree of local damage to the beam reaches 60%,the amplitude of natural frequency change exceeds 10%for the first time.The natural frequencies of the firstorder vibration mode and higher-order vibration mode can be selected as indexes for different degrees of the damaged T-beam bridges.For damaged bridges reinforced with external cables,the traditional natural frequency of the first-order vibration mode cannot be used as the index,which is insensitive to changes in prestress of the external cable.Some natural frequencies of higher-order vibration modes can be selected as indexes,which can reflect the reinforcement effect of externally prestressed damaged T-beam bridges,and its numerical value increases with the increase of external prestressed cable force.展开更多
In the context of intelligent manufacturing,the modern hot strip mill process(HSMP)shows characteristics such as diversification of products,multi-specification batch production,and demand-oriented customization.These...In the context of intelligent manufacturing,the modern hot strip mill process(HSMP)shows characteristics such as diversification of products,multi-specification batch production,and demand-oriented customization.These characteristics pose significant challenges to ensuring process stability and consistency of product performance.Therefore,exploring the potential relationship between product performance and the production process,and developing a comprehensive performance evaluation method adapted to modern HSMP have become an urgent issue.A comprehensive performance evaluation method for HSMP by integrating multi-task learning and stacked performance-related autoencoder is proposed to solve the problems such as incomplete performance indicators(PIs)data,insufficient real-time acquisition requirements,and coupling of multiple PIs.First,according to the existing Chinese standards,a comprehensive performance evaluation grade strategy for strip steel is designed.The random forest model is established to predict and complete the parts of PIs data that could not be obtained in real-time.Second,a stacked performance-related autoencoder(SPAE)model is proposed to extract the deep features closely related to the product performance.Then,considering the correlation between PIs,the multi-task learning framework is introduced to output the subitem ratings and comprehensive product performance rating results of the strip steel online in real-time,where each task represents a subitem of comprehensive performance.Finally,the effectiveness of the method is verified on a real HSMP dataset,and the results show that the accuracy of the proposed method is as high as 94.8%,which is superior to the other comparative methods.展开更多
As a key sector in advancing China’s“carbon neutrality”goal,the machinery manufacturing industry has achieved remarkable development in recent years.Against this backdrop,the scientific and objective evaluation of ...As a key sector in advancing China’s“carbon neutrality”goal,the machinery manufacturing industry has achieved remarkable development in recent years.Against this backdrop,the scientific and objective evaluation of the financial performance of machinery manufacturing enterprises has become a pressing issue in financial research.This topic is not only crucial for optimizing enterprise management and improving operational efficiency but also essential for enhancing overall industry performance and promoting sustainable development.This paper first introduces the concept of financial performance,followed by an analysis of related financial performance evaluation theories.It then focuses on the application of the entropy method in evaluating the financial performance of machinery manufacturing enterprises,detailing its analytical steps.Finally,a financial performance evaluation index system is constructed based on four dimensions:profitability,solvency,operational efficiency,and growth potential.展开更多
The continuous growth in per capita national disposable income has propelled the global cosmetics industry to significant growth over the past decade.Taking Proya Cosmetics Co.,Ltd.as an example,this paper adopts a st...The continuous growth in per capita national disposable income has propelled the global cosmetics industry to significant growth over the past decade.Taking Proya Cosmetics Co.,Ltd.as an example,this paper adopts a stakeholder perspective.By selecting financial indicators from Proya’s annual reports from 2017 to 2022,standardizing the data using SPSS software,and applying factor analysis,a series of financial performance evaluation models for Proya were constructed.A total of 15 listed companies in the same industry and Proya’s financial indicators over the past six years were selected for horizontal and vertical comparative analysis and evaluation.The analysis reveals that creditors,employees,and the government are the primary stakeholders influencing Proya’s financial performance.Based on these findings,corresponding strategies are proposed:safeguarding creditor interests from multiple angles;prioritizing value creation to enhance employee satisfaction;and strengthening social responsibility awareness while actively cooperating with government initiatives.展开更多
Aeroengines,often regarded as the heart of aircraft,are crucial for flight safety and performance.Comprehensive performance evaluation of aeroengines supports Prognostics and Health Management(PHM)and aeroengine digit...Aeroengines,often regarded as the heart of aircraft,are crucial for flight safety and performance.Comprehensive performance evaluation of aeroengines supports Prognostics and Health Management(PHM)and aeroengine digital engineering.Due to their highly integrated nature,aeroengines present challenges in performance evaluation because their test-run data are high-dimensional,large-scale,and exhibit strong nonlinear correlations among test indicators.To solve this problem,this study proposes a unified framework of the comprehensive performance evaluation of aeroengines to assess performance objectively and globally.Specifically,the network model and the dynamics model of aeroengine performance are constructed driven by test-run data,which can explain the patterns of system state changes and the internal relationship,and depict the system accurately.Based on that,three perturbations in the model are used to simulate three fault modes of aeroengines.Moreover,the comprehensive performance evaluation indexes of aeroengines are proposed to evaluate the performance dynamically from two dimensions,the coupling performance and the activity performance.Thirteen test-run qualified and four test-run failed aeroengines are used to validate and establish the qualified ranges.The results demonstrate that the comprehensive evaluation indexes can distinguish test-run qualified and test-run failed aeroengines.By changing the dynamic parameters,the comprehensive performance under any thrust and inlet guide vanes(IGV)angle can be estimated,broadening the test-run scenarios beyond a few typical states.This novel approach offers significant advancements for the comprehensive performance evaluation and management of aeroengines,paving the way for future PHM and aeroengine digital engineering developments.展开更多
With the acceleration of urban and rural development,the problem of rural idle residential land has become increasingly prominent,and its effective revitalization and utilization is of great significance for optimizin...With the acceleration of urban and rural development,the problem of rural idle residential land has become increasingly prominent,and its effective revitalization and utilization is of great significance for optimizing the allocation of land resources and promoting the sustainable development of rural economy.Based on the performance evaluation of the revitalization and utilization of rural idle residential land in previous studies,this paper discusses the theoretical framework and method system of the current evaluation system.This study first defines the concept connotations of rural idle residential land and their revitalization and utilization.It then summarizes the progress of domestic and international research on performance evaluation,and sorts out and explores the existing relevant research methods for land performance performance by domestic scholars,thereby making the reflective summary of the performance evaluation on the revitalization and utilization of rural idle residential land,and pointing out the possible future research direction.展开更多
Thermal barrier coatings(TBCs)are extensively utilized in aero-engines and heavy-duty gas turbines due to their outstanding properties,including low thermal conductivity,corrosion,high-temperature oxidation,and wear r...Thermal barrier coatings(TBCs)are extensively utilized in aero-engines and heavy-duty gas turbines due to their outstanding properties,including low thermal conductivity,corrosion,high-temperature oxidation,and wear resistance.The rising thrust-to-weight ratio and service temperature in engine hot sections have presented a significant challenge in TBC's materials,structure,and preparation process;it is one of the current research hotspots in the aviation field.This paper reviews the recent advancement in turbine blade TBCs.It focuses on the TBC's structure,deposition mechanism and the key performance evaluation indexes for TBCs applied to turbine blades.Finally,the future research field of TBCs for turbine blades is also be prospected.展开更多
Sponge city(SPC)is proposed to solve the issues such as the degradation of urban water ecosystem environment,imbalanced water resource allocation,urban water logging,and water contamination.The PPP(Public Private Part...Sponge city(SPC)is proposed to solve the issues such as the degradation of urban water ecosystem environment,imbalanced water resource allocation,urban water logging,and water contamination.The PPP(Public Private Partnership)model is combined to release the government pressure of SPC project construction.The development of the SPC-PPP model makes significant contributions to the sustainable development and the enhancement of urban resilience against water-related disasters.However,there is no scientific performance evaluation system on its operation period has been conducted.Therefore,the SPC-PPP Evaluation model aims to objectively and reasonably assess project effectiveness,promote its development and refine the evaluation framework.This paper has set up the MEE model for performance evaluation,with improved Matter-Element Extension method to assign values to the evaluation indices.The research results show that:(1)The MEE model is more accurate in the performance evaluation and its effectiveness is reflected in its ability to capture the correlation among different indices in the same membership,rather than merely focusing on individual indices.(2)The proposed approach provided a new aspect for performance evaluation,improving the accuracy of evaluation and promoting the development of SPC-PPP project.展开更多
Performance evaluation,as a multidimensional and comprehensive assessment tool,plays a pivotal role in accurately reflecting the quality of higher education and effectively promoting institutional governance.In the ev...Performance evaluation,as a multidimensional and comprehensive assessment tool,plays a pivotal role in accurately reflecting the quality of higher education and effectively promoting institutional governance.In the evolving landscape of educational reform,nonprofit private universities in China face pressing challenges in leveraging performance evaluations to standardize internal operations,guide strategic development,and foster public trust.This paper focuses on these institutions and conducts an in-depth analysis of existing problems in performance evaluation practices.Drawing on contemporary theoretical frameworks and empirical experiences,it proposes feasible,targeted governance strategies.The aim is to offer both theoretical insights and practical guidelines to support the sustainable development of non-profit private universities and to help these institutions better integrate into the national education system while fulfilling their social missions.展开更多
Muscle strength training can effectively reduce muscle atrophy,activate muscle tissue and promote muscle strength recovery and growth.Based on our previous research,we developed four muscle strength training strategie...Muscle strength training can effectively reduce muscle atrophy,activate muscle tissue and promote muscle strength recovery and growth.Based on our previous research,we developed four muscle strength training strategies by further imitating the clinical muscle strength training methods,namely,Isokinetic centriPetal-centriPetal Exercise(IPPE),Isokinetic centriPetal-centriFuge exercise(IPFE),Isokinetic centriFuge-centriPetal Exercise(IFPE)and Isokinetic centriFuge-centriFuge Exercise(IFFE).To quantitatively evaluate the performance of the developed strategies,experiments were carried out with elbow and knee joints as examples,and muscle Endurance Ratio(ER),Flexion and Extension torque ratio(F/E)and the degree of muscle activation were extracted and calculated based on angle/torque and Surface ElectroMyoGraphy(sEMG)signals.Experimental results showed that the ER value of IFFE was significantly reduced compared with IPPE,while the F/E value of IFPE was significantly increased;this suggests that muscle centrifugation corresponds to higher training intensity;In addition,flexor and extensor muscle groups showed different levels of muscle activation in different training strategies.The results reveal that combining different muscle movement characteristics,isokinetic exercise can exert special muscle strength training effects.The study can lay the foundation for exploring subject-specific adaptive muscle strength training strategies to better adapt to different levels of muscle strength.展开更多
This paper proposes virtual impedance adaptation of the lower-limb exoskeleton for human performance augmentation(LEHPA) based on deep reinforcement learning(VIADRL) to mitigate reliance on model accuracy and address ...This paper proposes virtual impedance adaptation of the lower-limb exoskeleton for human performance augmentation(LEHPA) based on deep reinforcement learning(VIADRL) to mitigate reliance on model accuracy and address the ever-changing human-exoskeleton interaction(HEI) dynamics. The classical sensitivity amplification control strategy is expanded to the virtual impedance control strategy with more learnable virtual impedance parameters. The adjustment of these virtual impedance parameters is formalized as finding the optimal policy for a Markov Decision Process and can then be effectively resolved using deep reinforcement learning algorithms. To ensure safe and efficient policy training, a multibody simulation environment is established to facilitate the training process, supplemented by the innovative hybrid inverse-forward dynamics simulation approach for executing the simulation. For comparison purposes, the SADRL strategy is introduced as a benchmark. A novel control performance evaluation method based on the HEI forces at the back, thighs, and shanks is proposed to quantitatively evaluate the performance of our proposed VIADRL strategy. The VIADRL controller is systematically compared with the SADRL controller at five selected walking speeds. The lumped ratio of HEI forces under the SADRL strategy relative to those under the SADRL strategy is as low as 0.81 in simulation and approximately 0.89 on the LEHPA prototype. The overall reduction of HEI forces demonstrates the superiority of the VIADRL strategy in comparison to the SADRL strategy.展开更多
The average stiffness performance indices throughout the workspace are commonly used as global stiffness performance indices to evaluate the overall stiffness performance of parallel mechanisms,which involves an analy...The average stiffness performance indices throughout the workspace are commonly used as global stiffness performance indices to evaluate the overall stiffness performance of parallel mechanisms,which involves an analysis of the stiffness performance of numerous discrete points in the workspace.This necessitates time-consuming and inefficient calculation,which is particularly pronounced in the optimization design stage of the mechanism,where the variations in the global stiffness performance indices versus various dimensional and structural parameters need to be analyzed.This paper presents a semi-analytical approach for stiffness modeling of the novel(R(RPS&RP))&2-UPS parallel mechanism(referred to as the Trifree mechanism)and proposes“local”stiffness performance indices as alternatives to global indices.Drawing on the screw theory,the Cartesian stiffness matrix of the Trifree mechanism is formulated explicitly by considering the compliances of all elastic elements and the over-constraint characteristics inherent in the mechanism.Based on the spherical motion pattern of the Trifree mechanism,four special reference configurations are extracted within the workspace.This yields“local”stiffness performance indices capable of accurately evaluating the overall stiffness performance of the mechanism and effectively improving the computational efficiency.The variations in global and“local”stiffness performance indices versus key design parameters are investigated.Furthermore,the proposed indices are applied to the Tricept and Trimule mechanisms.The results demonstrate that the proposed indices exhibit excellent computational accuracy and efficiency in evaluating the overall stiffness performance of these spherical parallel mechanisms.Moreover,the stiffness performance of the novel parallel mechanism investigated in this study closely resembles that of the well-known Tricept and Trimule mechanisms.This research proposes a semi-analytic stiffness model of the Trifree mechanism and“local”stiffness performance indices to evaluate the overall stiffness performance,thereby substantially improving the computational efficiency without sacrificing accuracy.展开更多
基金the National Key Research Program of China under granted No.92164201National Natural Science Foundation of China for Distinguished Young Scholars No.62325403+2 种基金Natural Science Foundation of Jiangsu Province(BK20230498)Jiangsu Funding Program for Excellent Postdoctoral Talent(2024ZB427)the National Natural Science Foundation of China(62304147).
文摘Solid-state batteries are widely recognized as the next-generation energy storage devices with high specific energy,high safety,and high environmental adaptability.However,the research and development of solid-state batteries are resource-intensive and time-consuming due to their complex chemical environment,rendering performance prediction arduous and delaying large-scale industrialization.Artificial intelligence serves as an accelerator for solid-state battery development by enabling efficient material screening and performance prediction.This review will systematically examine how the latest progress in using machine learning(ML)algorithms can be used to mine extensive material databases and accelerate the discovery of high-performance cathode,anode,and electrolyte materials suitable for solid-state batteries.Furthermore,the use of ML technology to accurately estimate and predict key performance indicators in the solid-state battery management system will be discussed,among which are state of charge,state of health,remaining useful life,and battery capacity.Finally,we will summarize the main challenges encountered in the current research,such as data quality issues and poor code portability,and propose possible solutions and development paths.These will provide clear guidance for future research and technological reiteration.
文摘To investigate the overall performance of reverse energy bypass scramjet,firstly a variable spe⁃cific heat method combined with a chemical balance calculation module for combustion products were used to es⁃tablish a benchmark scramjet performance evaluation model.Based on the test data of typical flying point of Mach 7 with the altitude of 29 km,the reliability of the model was verified.The deviations of parameters such as the to⁃tal pressure loss of combustor between the model and the test data were analyzed.Furtherly,an analytical method for post-combustion magnetohydrodynamic power generation was established;by embedding the above method into the overall performance evaluation model,performance prediction considering the power generation effect was realized.Finally,based on the above model,variety regulations of the inlet and the outlet parameters of the power generation channel and performance parameters including the engine specific impulse and the unit thrust under different enthalpy extraction ratios and load factors were analyzed.It could be concluded that the model can reliably predict the variations of key parameters.As the value of the load factor increases,the value of the conduc⁃tivity required to reach the specified enthalpy extraction ratio first decreases and then increases,which is approxi⁃mately parabolic.In order to reduce the demand for the gas conductivity for MHD power generation,the load fac⁃tor should be around 0.5.When the load factor is 0.4 and the magnetic induction intensity is 2.5 T,if the enthalpy extraction ratio reaches 0.5%,the engine specific impulse performance reduces about 3.58%.
文摘Sand production and high water content in oil wells are two major challenges that restrict high and stable production in loose sandstone reservoirs.In this paper,nano SiO_(2),coupling agent triethoxysilane,phenolic resin and n-octanol were used to synthesize the main agent SCA-2.Hexamethylenetetramine and vinyl carbonate were selected to prepare the curing agent YGA-1,which was then compounded with SCA-2 to develop a sand fixation and water plugging system.Firstly,single-factor experiments were conducted to determine the optimal concentrations of SCA-2 and YGA-1,subsequently,the system’s sand fixation and water blocking performance were evaluated.Finally,a pilot test was carried out in the mining site.Experimental results showed that the optimal formula composition of the system was 10%SCA-2+5%YGA-1.The gelation time of the system was 180 minutes and the viscosity after gelation could reach 108.4 mPa·s.When the dosage of the drug system was 0.6 PV,the sand production rate remained below 0.08%.Dual-tube parallel experiments showed that the sand fixation and water plugging system had a water flow channel plugging rate of 87.5%,while the oil flow channel plugging rate was only 11.3%,indicating minimal damage to the oil-bearing reservoir.The field test showed that after the measures taken in Well M of X oilfield,the sand free oil recovery period exceeded 360 days,the water content decreased by 5.0%and the cumulative oil production increased by 7092 m^(3).This study provides new ideas for efficient development of loose sandstone reservoirs.
文摘During the final proofing stage of the paper,the wrong version of Fig.2 was accidently used when replacing it with a high-resolution version.The star and circle marks were missing in the published version.
基金Supported by National Natural Science Foundation of China(Grant Nos.52405001,52175001,62373010,82472537)China Postdoctoral Science Foundation(Grant No.2024M760166)+2 种基金Postdoctoral Fellowship Program of CPSF(Grant No.GZC20230186)Shenzhen Municipal Science,Technology,and Innovation Commission(Grant No.SGDX20220530111005036)Beijing Natural Science Foundation(Grant Nos.3222002,3232004,L222061).
文摘Long-bone fractures are common complaints in orthopedic surgery.In recent years,significant progress has been made in robot-assisted fracture-reduction techniques.As a key medical device for diverse fracture morphologies and sites,the design of the reduction robot has a profound impact on the reduction outcomes.However,existing reduction robots have practical limitations and cannot simultaneously satisfy clinical requirements in terms of workspace,force/torque,and structural stiffness.To overcome these problems,we first analyze the potential placement areas and performance requirements of reduction robots according to clinical application scenarios.Subsequently,a 3UPS/S-3P hybrid configuration with decoupled rotational and translational degrees of freedom(DOFs)is proposed,and a kinematic model is derived to achieve the motion characteristics of the remote center of motion(RCM).Furthermore,the structural design of a hybrid reduction robot with an integrated distal clamp and proximal fixator was completed,and a mechanical prototype was constructed.The results of the performance evaluations and static analysis demonstrate that the proposed reduction robot has acceptable workspace,force,and torque performance and excellent structural stiffness.Two clinical case simulations further demonstrated the clinical feasibility of the robot.Finally,preliminary experiments on bone models demonstrated the potential effectiveness of the proposed reduction robot in lower-limb fracture reduction.
文摘Evaluating firms’financial performance is important for survival in the competitive environment arising from technological advancements and gaining a competitive advantage.This study aims to assess the financial performances of firms traded on the Istanbul Stock Exchange 100 Index(Borsa Istanbul(BIST)100 Index)between 2018 and 2022 using an integrated multi-criteria decision-making(MCDM)method.This is the first study to use a new combined approach proposed based on the indifference thresholdbased attribute ratio analysis(ITARA)and cost estimation,benchmarking,and risk assessment(COBRA)methods,which have not been applied to corporate performance assessment.The ITARA method is used to find the weights of the criteria,and the ranking of the firms in terms of financial performance is obtained using the COBRA method.The results show that the firms with the highest financial performance are ISMEN,ALGYO,PGSUS,KOZAA,and IPEKE.The companies with the lowest financial performance are AKFGY,BAGFS,MGROS,KOZAL,and GOZDE.The results of this ranking provide important information for firms to recognize their position and for investors who want to invest in firms in the BIST 100 Index.Additionally,sensitivity analyses are performed to assess the impact of changes in the criteria on the ranking of the firms and to validate the results of the proposed method.A comparative analysis is made with different MCDM methods like the technique for order preference by similarity to ideal solution(TOPSIS),and combined compromise solution(CoCoSo)methods and Spearman’s rank correlation test results are presented.This approach leads to the conclusion that the proposed approach can be a useful and effective tool for assessing the financial performance of firms.
基金funded by the Joint Project of Industry-University-Research of Jiangsu Province(Grant:BY20231146).
文摘With the widespread application of Internet of Things(IoT)technology,the processing of massive realtime streaming data poses significant challenges to the computational and data-processing capabilities of systems.Although distributed streaming data processing frameworks such asApache Flink andApache Spark Streaming provide solutions,meeting stringent response time requirements while ensuring high throughput and resource utilization remains an urgent problem.To address this,the study proposes a formal modeling approach based on Performance Evaluation Process Algebra(PEPA),which abstracts the core components and interactions of cloud-based distributed streaming data processing systems.Additionally,a generic service flow generation algorithmis introduced,enabling the automatic extraction of service flows fromthe PEPAmodel and the computation of key performance metrics,including response time,throughput,and resource utilization.The novelty of this work lies in the integration of PEPA-based formal modeling with the service flow generation algorithm,bridging the gap between formal modeling and practical performance evaluation for IoT systems.Simulation experiments demonstrate that optimizing the execution efficiency of components can significantly improve system performance.For instance,increasing the task execution rate from 10 to 100 improves system performance by 9.53%,while further increasing it to 200 results in a 21.58%improvement.However,diminishing returns are observed when the execution rate reaches 500,with only a 0.42%gain.Similarly,increasing the number of TaskManagers from 10 to 20 improves response time by 18.49%,but the improvement slows to 6.06% when increasing from 20 to 50,highlighting the importance of co-optimizing component efficiency and resource management to achieve substantial performance gains.This study provides a systematic framework for analyzing and optimizing the performance of IoT systems for large-scale real-time streaming data processing.The proposed approach not only identifies performance bottlenecks but also offers insights into improving system efficiency under different configurations and workloads.
基金supported by National Natural Science Foundation of China(Nos.42374076,42174128 and 42004115)Natural Science Foundation for Excellent Young Scholars of Hunan Province,China(No.2022JJ 20057)+1 种基金Central South University Innovation-Driven Research Programme(No.2023CXQD063)the Guangdong Provincial Key Laboratory of Geophysical High-resolution Imaging Technology(No.2022B1212010002).
文摘Seismic source locations can characterize the spatial and temporal distributions of seismic sources,and can provide important basic data for earthquake disaster monitoring,fault activity characterization,and fracture growth interpretation.Waveform stacking-based location methods invert the source locations by focusing the source energy with multichannel waveforms,and these methods exhibit a high level of automation and noise-resistance.Taking the cross-correlation stacking(CCS)method as an example,this work attempts to study the influential factors of waveform stacking-based methods,and introduces a comprehensive performance evaluation scheme based on multiple parameters and indicators.The waveform data are from field monitoring of induced microseismicity in the Changning region(southern Sichuan Basin of China).Synthetic and field data tests reveal the impacts of three categories of factors on waveform stacking-based location:velocity model,monitoring array,and waveform complexity.The location performance is evaluated and further improved in terms of the source imaging resolution and location error.Denser array monitoring contributes to better constraining source depth and location reliability,but the combined impact of multiple factors,such as velocity model uncertainty and multiple seismic phases,increases the complexity of locating field microseismic events.Finally,the aspects of location uncertainty,phase detection,and artificial intelligencebased location are discussed.
基金supported by Henan Province Science and Technology Research Funding Project(No.222102320129)the Key Research Project of Henan Higher Education Institutions(Grant Nos.22A560004,22A56005).
文摘As an evaluation index,the natural frequency has the advantages of easy acquisition and quantitative evaluation.In this paper,the natural frequency is used to evaluate the performance of external cable reinforced bridges.Numerical examples show that compared with the natural frequencies of first-order modes,the natural frequencies of higher-order modes are more sensitive and can reflect the damage situation and external cable reinforcement effect of T-beam bridges.For damaged bridges,as the damage to the T-beam increases,the natural frequency value of the bridge gradually decreases.When the degree of local damage to the beam reaches 60%,the amplitude of natural frequency change exceeds 10%for the first time.The natural frequencies of the firstorder vibration mode and higher-order vibration mode can be selected as indexes for different degrees of the damaged T-beam bridges.For damaged bridges reinforced with external cables,the traditional natural frequency of the first-order vibration mode cannot be used as the index,which is insensitive to changes in prestress of the external cable.Some natural frequencies of higher-order vibration modes can be selected as indexes,which can reflect the reinforcement effect of externally prestressed damaged T-beam bridges,and its numerical value increases with the increase of external prestressed cable force.
基金supported by the National Natural Science Foundation of China(NSFC)under Grants(Nos.U21A20483,62373040 and 62273031).
文摘In the context of intelligent manufacturing,the modern hot strip mill process(HSMP)shows characteristics such as diversification of products,multi-specification batch production,and demand-oriented customization.These characteristics pose significant challenges to ensuring process stability and consistency of product performance.Therefore,exploring the potential relationship between product performance and the production process,and developing a comprehensive performance evaluation method adapted to modern HSMP have become an urgent issue.A comprehensive performance evaluation method for HSMP by integrating multi-task learning and stacked performance-related autoencoder is proposed to solve the problems such as incomplete performance indicators(PIs)data,insufficient real-time acquisition requirements,and coupling of multiple PIs.First,according to the existing Chinese standards,a comprehensive performance evaluation grade strategy for strip steel is designed.The random forest model is established to predict and complete the parts of PIs data that could not be obtained in real-time.Second,a stacked performance-related autoencoder(SPAE)model is proposed to extract the deep features closely related to the product performance.Then,considering the correlation between PIs,the multi-task learning framework is introduced to output the subitem ratings and comprehensive product performance rating results of the strip steel online in real-time,where each task represents a subitem of comprehensive performance.Finally,the effectiveness of the method is verified on a real HSMP dataset,and the results show that the accuracy of the proposed method is as high as 94.8%,which is superior to the other comparative methods.
文摘As a key sector in advancing China’s“carbon neutrality”goal,the machinery manufacturing industry has achieved remarkable development in recent years.Against this backdrop,the scientific and objective evaluation of the financial performance of machinery manufacturing enterprises has become a pressing issue in financial research.This topic is not only crucial for optimizing enterprise management and improving operational efficiency but also essential for enhancing overall industry performance and promoting sustainable development.This paper first introduces the concept of financial performance,followed by an analysis of related financial performance evaluation theories.It then focuses on the application of the entropy method in evaluating the financial performance of machinery manufacturing enterprises,detailing its analytical steps.Finally,a financial performance evaluation index system is constructed based on four dimensions:profitability,solvency,operational efficiency,and growth potential.
文摘The continuous growth in per capita national disposable income has propelled the global cosmetics industry to significant growth over the past decade.Taking Proya Cosmetics Co.,Ltd.as an example,this paper adopts a stakeholder perspective.By selecting financial indicators from Proya’s annual reports from 2017 to 2022,standardizing the data using SPSS software,and applying factor analysis,a series of financial performance evaluation models for Proya were constructed.A total of 15 listed companies in the same industry and Proya’s financial indicators over the past six years were selected for horizontal and vertical comparative analysis and evaluation.The analysis reveals that creditors,employees,and the government are the primary stakeholders influencing Proya’s financial performance.Based on these findings,corresponding strategies are proposed:safeguarding creditor interests from multiple angles;prioritizing value creation to enhance employee satisfaction;and strengthening social responsibility awareness while actively cooperating with government initiatives.
基金supported by the National Natural Science Foundation of China(72231008,72171193,and 72071153)the Science and Technology Innovation Group Program of Shaanxi Province(2024RS-CXTD-28)the Open Fund of Intelligent Control Laboratory(ICL-2023-0304).
文摘Aeroengines,often regarded as the heart of aircraft,are crucial for flight safety and performance.Comprehensive performance evaluation of aeroengines supports Prognostics and Health Management(PHM)and aeroengine digital engineering.Due to their highly integrated nature,aeroengines present challenges in performance evaluation because their test-run data are high-dimensional,large-scale,and exhibit strong nonlinear correlations among test indicators.To solve this problem,this study proposes a unified framework of the comprehensive performance evaluation of aeroengines to assess performance objectively and globally.Specifically,the network model and the dynamics model of aeroengine performance are constructed driven by test-run data,which can explain the patterns of system state changes and the internal relationship,and depict the system accurately.Based on that,three perturbations in the model are used to simulate three fault modes of aeroengines.Moreover,the comprehensive performance evaluation indexes of aeroengines are proposed to evaluate the performance dynamically from two dimensions,the coupling performance and the activity performance.Thirteen test-run qualified and four test-run failed aeroengines are used to validate and establish the qualified ranges.The results demonstrate that the comprehensive evaluation indexes can distinguish test-run qualified and test-run failed aeroengines.By changing the dynamic parameters,the comprehensive performance under any thrust and inlet guide vanes(IGV)angle can be estimated,broadening the test-run scenarios beyond a few typical states.This novel approach offers significant advancements for the comprehensive performance evaluation and management of aeroengines,paving the way for future PHM and aeroengine digital engineering developments.
文摘With the acceleration of urban and rural development,the problem of rural idle residential land has become increasingly prominent,and its effective revitalization and utilization is of great significance for optimizing the allocation of land resources and promoting the sustainable development of rural economy.Based on the performance evaluation of the revitalization and utilization of rural idle residential land in previous studies,this paper discusses the theoretical framework and method system of the current evaluation system.This study first defines the concept connotations of rural idle residential land and their revitalization and utilization.It then summarizes the progress of domestic and international research on performance evaluation,and sorts out and explores the existing relevant research methods for land performance performance by domestic scholars,thereby making the reflective summary of the performance evaluation on the revitalization and utilization of rural idle residential land,and pointing out the possible future research direction.
基金supported by the National Natural Science Foundation of China(Grant No.52271087).
文摘Thermal barrier coatings(TBCs)are extensively utilized in aero-engines and heavy-duty gas turbines due to their outstanding properties,including low thermal conductivity,corrosion,high-temperature oxidation,and wear resistance.The rising thrust-to-weight ratio and service temperature in engine hot sections have presented a significant challenge in TBC's materials,structure,and preparation process;it is one of the current research hotspots in the aviation field.This paper reviews the recent advancement in turbine blade TBCs.It focuses on the TBC's structure,deposition mechanism and the key performance evaluation indexes for TBCs applied to turbine blades.Finally,the future research field of TBCs for turbine blades is also be prospected.
基金supported by the Open Fund of Hubei Key Laboratory of Construction Management in Hydropower Engineering(Grant No.2016KSD04)the Open Fund of Engineering Research Center of Eco-environment in Three Gorges Reservoir Region,Ministry of Education(Grant No.KF2016-11).
文摘Sponge city(SPC)is proposed to solve the issues such as the degradation of urban water ecosystem environment,imbalanced water resource allocation,urban water logging,and water contamination.The PPP(Public Private Partnership)model is combined to release the government pressure of SPC project construction.The development of the SPC-PPP model makes significant contributions to the sustainable development and the enhancement of urban resilience against water-related disasters.However,there is no scientific performance evaluation system on its operation period has been conducted.Therefore,the SPC-PPP Evaluation model aims to objectively and reasonably assess project effectiveness,promote its development and refine the evaluation framework.This paper has set up the MEE model for performance evaluation,with improved Matter-Element Extension method to assign values to the evaluation indices.The research results show that:(1)The MEE model is more accurate in the performance evaluation and its effectiveness is reflected in its ability to capture the correlation among different indices in the same membership,rather than merely focusing on individual indices.(2)The proposed approach provided a new aspect for performance evaluation,improving the accuracy of evaluation and promoting the development of SPC-PPP project.
文摘Performance evaluation,as a multidimensional and comprehensive assessment tool,plays a pivotal role in accurately reflecting the quality of higher education and effectively promoting institutional governance.In the evolving landscape of educational reform,nonprofit private universities in China face pressing challenges in leveraging performance evaluations to standardize internal operations,guide strategic development,and foster public trust.This paper focuses on these institutions and conducts an in-depth analysis of existing problems in performance evaluation practices.Drawing on contemporary theoretical frameworks and empirical experiences,it proposes feasible,targeted governance strategies.The aim is to offer both theoretical insights and practical guidelines to support the sustainable development of non-profit private universities and to help these institutions better integrate into the national education system while fulfilling their social missions.
基金supported in part by the Beijing Natural Science Foundation under Grant Nos.3232004 and 3222002in part by the National Natural Science Foundation of China under Grant Nos.62373010 and 52175001.
文摘Muscle strength training can effectively reduce muscle atrophy,activate muscle tissue and promote muscle strength recovery and growth.Based on our previous research,we developed four muscle strength training strategies by further imitating the clinical muscle strength training methods,namely,Isokinetic centriPetal-centriPetal Exercise(IPPE),Isokinetic centriPetal-centriFuge exercise(IPFE),Isokinetic centriFuge-centriPetal Exercise(IFPE)and Isokinetic centriFuge-centriFuge Exercise(IFFE).To quantitatively evaluate the performance of the developed strategies,experiments were carried out with elbow and knee joints as examples,and muscle Endurance Ratio(ER),Flexion and Extension torque ratio(F/E)and the degree of muscle activation were extracted and calculated based on angle/torque and Surface ElectroMyoGraphy(sEMG)signals.Experimental results showed that the ER value of IFFE was significantly reduced compared with IPPE,while the F/E value of IFPE was significantly increased;this suggests that muscle centrifugation corresponds to higher training intensity;In addition,flexor and extensor muscle groups showed different levels of muscle activation in different training strategies.The results reveal that combining different muscle movement characteristics,isokinetic exercise can exert special muscle strength training effects.The study can lay the foundation for exploring subject-specific adaptive muscle strength training strategies to better adapt to different levels of muscle strength.
文摘This paper proposes virtual impedance adaptation of the lower-limb exoskeleton for human performance augmentation(LEHPA) based on deep reinforcement learning(VIADRL) to mitigate reliance on model accuracy and address the ever-changing human-exoskeleton interaction(HEI) dynamics. The classical sensitivity amplification control strategy is expanded to the virtual impedance control strategy with more learnable virtual impedance parameters. The adjustment of these virtual impedance parameters is formalized as finding the optimal policy for a Markov Decision Process and can then be effectively resolved using deep reinforcement learning algorithms. To ensure safe and efficient policy training, a multibody simulation environment is established to facilitate the training process, supplemented by the innovative hybrid inverse-forward dynamics simulation approach for executing the simulation. For comparison purposes, the SADRL strategy is introduced as a benchmark. A novel control performance evaluation method based on the HEI forces at the back, thighs, and shanks is proposed to quantitatively evaluate the performance of our proposed VIADRL strategy. The VIADRL controller is systematically compared with the SADRL controller at five selected walking speeds. The lumped ratio of HEI forces under the SADRL strategy relative to those under the SADRL strategy is as low as 0.81 in simulation and approximately 0.89 on the LEHPA prototype. The overall reduction of HEI forces demonstrates the superiority of the VIADRL strategy in comparison to the SADRL strategy.
基金Supported by National High-quality Development Project of China(Grant No.2340STCZB193).
文摘The average stiffness performance indices throughout the workspace are commonly used as global stiffness performance indices to evaluate the overall stiffness performance of parallel mechanisms,which involves an analysis of the stiffness performance of numerous discrete points in the workspace.This necessitates time-consuming and inefficient calculation,which is particularly pronounced in the optimization design stage of the mechanism,where the variations in the global stiffness performance indices versus various dimensional and structural parameters need to be analyzed.This paper presents a semi-analytical approach for stiffness modeling of the novel(R(RPS&RP))&2-UPS parallel mechanism(referred to as the Trifree mechanism)and proposes“local”stiffness performance indices as alternatives to global indices.Drawing on the screw theory,the Cartesian stiffness matrix of the Trifree mechanism is formulated explicitly by considering the compliances of all elastic elements and the over-constraint characteristics inherent in the mechanism.Based on the spherical motion pattern of the Trifree mechanism,four special reference configurations are extracted within the workspace.This yields“local”stiffness performance indices capable of accurately evaluating the overall stiffness performance of the mechanism and effectively improving the computational efficiency.The variations in global and“local”stiffness performance indices versus key design parameters are investigated.Furthermore,the proposed indices are applied to the Tricept and Trimule mechanisms.The results demonstrate that the proposed indices exhibit excellent computational accuracy and efficiency in evaluating the overall stiffness performance of these spherical parallel mechanisms.Moreover,the stiffness performance of the novel parallel mechanism investigated in this study closely resembles that of the well-known Tricept and Trimule mechanisms.This research proposes a semi-analytic stiffness model of the Trifree mechanism and“local”stiffness performance indices to evaluate the overall stiffness performance,thereby substantially improving the computational efficiency without sacrificing accuracy.
