The rapid advancements in computer vision(CV)technology have transformed the traditional approaches to material microstructure analysis.This review outlines the history of CV and explores the applications of deep-lear...The rapid advancements in computer vision(CV)technology have transformed the traditional approaches to material microstructure analysis.This review outlines the history of CV and explores the applications of deep-learning(DL)-driven CV in four key areas of materials science:microstructure-based performance prediction,microstructure information generation,microstructure defect detection,and crystal structure-based property prediction.The CV has significantly reduced the cost of traditional experimental methods used in material performance prediction.Moreover,recent progress made in generating microstructure images and detecting microstructural defects using CV has led to increased efficiency and reliability in material performance assessments.The DL-driven CV models can accelerate the design of new materials with optimized performance by integrating predictions based on both crystal and microstructural data,thereby allowing for the discovery and innovation of next-generation materials.Finally,the review provides insights into the rapid interdisciplinary developments in the field of materials science and future prospects.展开更多
Automated essay scoring(AES)systems have gained significant importance in educational settings,offering a scalable,efficient,and objective method for evaluating student essays.However,developing AES systems for Arabic...Automated essay scoring(AES)systems have gained significant importance in educational settings,offering a scalable,efficient,and objective method for evaluating student essays.However,developing AES systems for Arabic poses distinct challenges due to the language’s complex morphology,diglossia,and the scarcity of annotated datasets.This paper presents a hybrid approach to Arabic AES by combining text-based,vector-based,and embeddingbased similarity measures to improve essay scoring accuracy while minimizing the training data required.Using a large Arabic essay dataset categorized into thematic groups,the study conducted four experiments to evaluate the impact of feature selection,data size,and model performance.Experiment 1 established a baseline using a non-machine learning approach,selecting top-N correlated features to predict essay scores.The subsequent experiments employed 5-fold cross-validation.Experiment 2 showed that combining embedding-based,text-based,and vector-based features in a Random Forest(RF)model achieved an R2 of 88.92%and an accuracy of 83.3%within a 0.5-point tolerance.Experiment 3 further refined the feature selection process,demonstrating that 19 correlated features yielded optimal results,improving R2 to 88.95%.In Experiment 4,an optimal data efficiency training approach was introduced,where training data portions increased from 5%to 50%.The study found that using just 10%of the data achieved near-peak performance,with an R2 of 85.49%,emphasizing an effective trade-off between performance and computational costs.These findings highlight the potential of the hybrid approach for developing scalable Arabic AES systems,especially in low-resource environments,addressing linguistic challenges while ensuring efficient data usage.展开更多
The development of high-performance structural and functional materials is vital in many industrial fields.High-and medium-entropy alloys(H/MEAs)with superior comprehensive properties owing to their specific microstru...The development of high-performance structural and functional materials is vital in many industrial fields.High-and medium-entropy alloys(H/MEAs)with superior comprehensive properties owing to their specific microstructures are promising candidates for structural materials.More importantly,multitudinous efforts have been made to regulate the microstructures and the properties of H/MEAs to further expand their industrial applications.The various heterostructures have enormous potential for the development of H/MEAs with outstanding performance.Herein,multiple heterogeneous structures with single and hierarchical heterogeneities were discussed in detail.Moreover,preparation methods for compositional inhomogeneity,bimodal structures,dualphase structures,lamella/layered structures,harmonic structures(core-shell),multiscale precipitates and heterostructures coupled with specific microstructures in H/MEAs were also systematically reviewed.The deformation mechanisms induced by the different heterostructures were thoroughly discussed to explore the relationship between the heterostructures and the optimized properties of H/MEAs.The contributions of the heterostructures and advanced microstructures to the H/MEAs were comprehensively elucidated to further improve the properties of the alloys.Finally,this review discussed the future challenges of high-performance H/MEAs for industrial applications and provides feasible methods for optimizing heterostructures to enhance the comprehensive properties of H/MEAs.展开更多
In this work,an oscillating-body wave energy converter(OBWEC)with a hydraulic power take-off(PTO)system named“Dolphin 1”is designed,in which the hydraulic PTO system is equivalent to a transfer station and plays a c...In this work,an oscillating-body wave energy converter(OBWEC)with a hydraulic power take-off(PTO)system named“Dolphin 1”is designed,in which the hydraulic PTO system is equivalent to a transfer station and plays a crucial role in ensuring the stability of the electrical energy output and the efficiency of the overall system.A corresponding mathematical model for the hydraulic PTO system has been established,the factors that influence its performance have been studied,and an algorithm for solving the optimal working pressure has been derived in this paper.Moreover,a PID control method to enable the hydraulic PTO system to automatically achieve optimal performance under different wave conditions has been designed.The results indicate that,compared with single-chamber hydraulic cylinders,double-chamber hydraulic cylinders have a wider application range and greater performance;the accumulator can stabilize the output power of the hydraulic PTO system and slightly increase it;excessively large or small hydraulic motor displacement hinders system performance;and each wave condition corresponds to a unique optimal working pressure for the hydraulic PTO system.In addition,the relationship between the optimal working pressure P_(m)and the pressure P_(h)of the wave force acting on the piston satisfies P_(m)^(2)=∫_(t_(1))^(t_(2))P_(h)^(2)dt/(t_(2)-t_(1)).Furthermore,adjusting the hydraulic motor displacement automatically via a PID controller ensures that the actual working pressure of the hydraulic PTO system consistently reaches or approaches its theoretically optimal value under various wave conditions,which is a very effective control method for enhancing the performance of the hydraulic PTO system.展开更多
Amid the deepening implementation of rural revitalization strategies and rapid fintech development,rural commercial banks-core financial institutions serving agriculture,rural areas,and farmers(the“three rurals”)and...Amid the deepening implementation of rural revitalization strategies and rapid fintech development,rural commercial banks-core financial institutions serving agriculture,rural areas,and farmers(the“three rurals”)and county economies-have seen their tellers’service quality and operational efficiency directly impact market competitiveness and sustainable development capabilities.This study examines teller performance management in rural commercial banks from a business management perspective.By analyzing structural issues in existing performance management systems and integrating theoretical frameworks with industry case studies,it proposes systematic optimization measures.The research aims to provide practical references for establishing scientific and efficient teller performance management systems in rural commercial banks,thereby enhancing service quality,strengthening talent support,and better serving the rural financial market.展开更多
Increasing the texture complexity of high-performance surfaces can enhance their antifriction properties by altering their distribution and retention of lubricating oils.When a fluid flows through a fish-scale texture...Increasing the texture complexity of high-performance surfaces can enhance their antifriction properties by altering their distribution and retention of lubricating oils.When a fluid flows through a fish-scale texture,a lubricating layer is formed,effectively reducing friction.In this study,a bionic fish-scale structure is proposed,and ceramic components are fabricated and analyzed using micro/nano additive-manufacturing technology.First,the effects of various parameters on the antifriction performance of the fish-scale texture under hydrodynamic lubrication conditions are investigated.Then,the pressure distribution of the oil film—including both positive and negative pressures—is simulated by adjusting parameters such as the angleα,ratio of textured area to total surface area,and depth of the fish-scale texture.The results indicate that for a textured area that accounts for 20%of the total surface,texture depth of 150μm,and angleαof 30°,the pressure differential reaches its maximum.Finally,based on the optimized parameters,the designed fish-scale structure is fabricated using micro/nano ceramic three-dimensional-printing technology.Friction and wear tests are conducted on the sintered samples.The experimental results align well with the simulation data,indicating that the structure can reduce the friction coefficient by approximately 15%,thereby significantly improving the antifriction performance.This study provides a valuable reference for the surface engineering of other high-performance functional structures.展开更多
Aqueous zinc-halogen batteries are promising candidates for large-scale energy storage due to their abundant resources,intrinsic safety,and high theoretical capacity.Nevertheless,the uncontrollable zinc dendrite growt...Aqueous zinc-halogen batteries are promising candidates for large-scale energy storage due to their abundant resources,intrinsic safety,and high theoretical capacity.Nevertheless,the uncontrollable zinc dendrite growth and spontaneous shuttle effect of active species have prohibited their practical implementation.Herein,a double-layered protective film based on zinc-ethylenediamine tetramethylene phosphonic acid(ZEA)artificial film and ZnF2-rich solid electrolyte interphase(SEI)layer has been successfully fabricated on the zinc metal anode via electrode/electrolyte synergistic optimization.The ZEA-based artificial film shows strong affinity for the ZnF2-rich SEI layer,therefore effectively suppressing the SEI breakage and facilitating the construction of double-layered protective film on the zinc metal anode.Such double-layered architecture not only modulates Zn2+flux and suppresses the zinc dendrite growth,but also blocks the direct contact between the metal anode and electrolyte,thus mitigating the corrosion from the active species.When employing optimized metal anodes and electrolytes,the as-developed zinc-(dual)halogen batteries present high areal capacity and satisfactory cycling stability.This work provides a new avenue for developing aqueous zinc-(dual)halogen batteries.展开更多
In recent years,surrogate models derived from genuine data samples have proven to be efficient in addressing optimization challenges that are costly or time⁃intensive.However,the individuals in the population become i...In recent years,surrogate models derived from genuine data samples have proven to be efficient in addressing optimization challenges that are costly or time⁃intensive.However,the individuals in the population become indistinguishable as the curse of dimensionality increases in the objective space and the accumulation of surrogate approximated errors.Therefore,in this paper,each objective function is modeled using a radial basis function approach,and the optimal solution set of the surrogate model is located by the multi⁃objective evolutionary algorithm of strengthened dominance relation.The original objective function values of the true evaluations are converted to two indicator values,and then the surrogate models are set up for the two performance indicators.Finally,an adaptive infill sampling strategy that relies on approximate performance indicators is proposed to assist in selecting individuals for real evaluations from the potential optimal solution set.The algorithm is contrasted against several advanced surrogate⁃assisted evolutionary algorithms on two suites of test cases,and the experimental findings prove that the approach is competitive in solving expensive many⁃objective optimization problems.展开更多
The biomass and coal co-pyrolysis (BCP) technology combines the advantages of both resources, achieving efficient resource complementarity, reducing reliance on coal, and minimizing pollutant emissions. However, this ...The biomass and coal co-pyrolysis (BCP) technology combines the advantages of both resources, achieving efficient resource complementarity, reducing reliance on coal, and minimizing pollutant emissions. However, this process still encounters numerous challenges in attaining optimal economic and environmental performance. Therefore, an ensemble learning (EL) framework is proposed for the BCP process in this study to optimize the synergistic benefits while minimizing negative environmental impacts. Six different ensemble learning models are developed to investigate the impact of input features, such as biomass characteristics, coal characteristics, and pyrolysis conditions on the product profit and CO_(2) emissions of the BCP processes. The Optuna method is further employed to automatically optimize the hyperparameters of BCP process models for enhancing their predictive accuracy and robustness. The results indicate that the categorical boosting (CAB) model of the BCP process has demonstrated exceptional performance in accurately predicting its product profit and CO_(2) emission (R2>0.92) after undergoing five-fold cross-validation. To enhance the interpretability of this preferred model, the Shapley additive explanations and partial dependence plot analyses are conducted to evaluate the impact and importance of biomass characteristics, coal characteristics, and pyrolysis conditions on the product profitability and CO_(2) emissions of the BCP processes. Finally, the preferred model coupled with a reference vector guided evolutionary algorithm is carried to identify the optimal conditions for maximizing the product profit of BCP process products while minimizing CO_(2) emissions. It indicates the optimal BCP process can achieve high product profits (5290.85 CNY·t−1) and low CO_(2) emissions (7.45 kg·t^(−1)).展开更多
Vat photopolymerization(VPP)3D printing is an optimized technology for complex-shaped ceramic cores,in which the solid loading of ceramic slurries greatly infiuences the microstructure and property of the final cerami...Vat photopolymerization(VPP)3D printing is an optimized technology for complex-shaped ceramic cores,in which the solid loading of ceramic slurries greatly infiuences the microstructure and property of the final ceramic parts.However,the high solid loading of slurries is highly limited by the high viscosity.In this study,silica-based ceramic core slurries with solid loading up to 68vol.%were achieved by the composition design to optimize the performance,considering the curing,rheological,and double bond conversion rate.The slurries demonstrate superior curing and rheological performance with mass ratio of monomers being 3:2 and mass fraction of BYK111 being 4wt.%.Afterwards,the impact of solid loading on the morphology and mechanical properties was investigated.As the solid loading increases,the microstructure becomes gradually dense,leading to an improved flexural strength of 19.5 MPa.Additionally,the sintering shrinkage becomes more uniform,satisfying the casting requirements effectively.This work serves as a guide for the preparation of ceramic slurries with a high solid loading.展开更多
The spoke as a key component has a significant impact on the performance of the non-pneumatic tire(NPT).The current research has focused on adjusting spoke structures to improve the single performance of NPT.Few studi...The spoke as a key component has a significant impact on the performance of the non-pneumatic tire(NPT).The current research has focused on adjusting spoke structures to improve the single performance of NPT.Few studies have been conducted to synergistically improve multi-performance by optimizing the spoke structure.Inspired by the concept of functionally gradient structures,this paper introduces a functionally gradient honeycomb NPT and its optimization method.Firstly,this paper completes the parameterization of the honeycomb spoke structure and establishes the numerical models of honeycomb NPTs with seven different gradients.Subsequently,the accuracy of the numerical models is verified using experimental methods.Then,the static and dynamic characteristics of these gradient honeycomb NPTs are thoroughly examined by using the finite element method.The findings highlight that the gradient structure of NPT-3 has superior performance.Building upon this,the study investigates the effects of key parameters,such as honeycomb spoke thickness and length,on load-carrying capacity,honeycomb spoke stress and mass.Finally,a multi-objective optimization method is proposed that uses a response surface model(RSM)and the Nondominated Sorting Genetic Algorithm-II(NSGA-II)to further optimize the functional gradient honeycomb NPTs.The optimized NPT-OP shows a 23.48%reduction in radial stiffness,8.95%reduction in maximum spoke stress and 16.86%reduction in spoke mass compared to the initial NPT-1.The damping characteristics of the NPT-OP have also been improved.The results offer a theoretical foundation and technical methodology for the structural design and optimization of gradient honeycomb NPTs.展开更多
High-pressure die cast(HPDC)AZ91 magnesium alloy is widely used in automotive components such as transmission housings and brackets for its excellent strength-to-weight ratio.Zinc-based cold spray coatings can be appl...High-pressure die cast(HPDC)AZ91 magnesium alloy is widely used in automotive components such as transmission housings and brackets for its excellent strength-to-weight ratio.Zinc-based cold spray coatings can be applied selectively to vulnerable areas to enhance corrosion resistance,minimize galvanic coupling with dissimilar metals,and eliminate the need for full-surface oxide coatings,making the process more efficient and targeted.A comprehensive evaluation of 16 combinations of nitrogen carrier gas temperatures and pressures led to the identification of an optimal range of process parameters,yielding Zn coatings with porosity<0.5% by area,wear rates reduced by a factor of two compared to uncoated AZ91,and adhesion strengths up to 35 MPa.The enhanced mechanical performance of the coating is attributed to the low porosity and the formation of a metallurgical bond at the coating-substrate interface.Corrosion studies using macroscale potentiodynamic polarization(PDP)and electrochemical impedance spectroscopy(EIS)revealed a significant decrease in corrosion rate and a shift to more noble corrosion potentials(ZCP)for coated substrates.Furthermore,the Zn cold-sprayed samples exhibited significantly lower corrosioninduced evolved hydrogen content compared to the base AZ91 substrate and AZ91 coated with industrial coatings,demonstrating that the Zn layer effectively protects the substrate from the corrosive environment.Overall,cold spray Zn coatings significantly improve the mechanical and corrosion performance of AZ91 Mg alloys,addressing key material challenges and enabling their broader use in automotive applications.展开更多
Performance-based warranties(PBWs)are widely used in industry and manufacturing.Given that PBW can impose financial burdens on manufacturers,rational maintenance decisions are essential for expanding profit margins.Th...Performance-based warranties(PBWs)are widely used in industry and manufacturing.Given that PBW can impose financial burdens on manufacturers,rational maintenance decisions are essential for expanding profit margins.This paper proposes an optimization model for PBW decisions for systems affected by Gamma degradation processes,incorporating periodic inspection.A system performance degradation model is established.Preventive maintenance probability and corrective renewal probability models are developed to calculate expected warranty costs and system availability.A benefits function,which includes incentives,is constructed to optimize the initial and subsequent inspection intervals and preventive maintenance thresholds,thereby maximizing warranty profit.An improved sparrow search algorithm is developed to optimize the model,with a case study on large steam turbine rotor shafts.The results suggest the optimal PBW strategy involves an initial inspection interval of approximately 20 months,with subsequent intervals of about four months,and a preventive maintenance threshold of approximately 37.39 mm wear.When compared to common cost-minimization-based condition maintenance strategies and PBW strategies that do not differentiate between initial and subsequent inspection intervals,the proposed PBW strategy increases the manufacturer’s profit by 1%and 18%,respectively.Sensitivity analyses provide managerial recommendations for PBW implementation.The PBW strategy proposed in this study significantly increases manufacturers’profits by optimizing inspection intervals and preventive maintenance thresholds,and manufacturers should focus on technological improvement in preventive maintenance and cost control to further enhance earnings.展开更多
In wire arc additive manufacturing(WAAM),a trade-off exists among deposition efficiency,microstructure,and mechanical properties.Addressing this challenge,this work proposes an innovative multi-objective optimization ...In wire arc additive manufacturing(WAAM),a trade-off exists among deposition efficiency,microstructure,and mechanical properties.Addressing this challenge,this work proposes an innovative multi-objective optimization framework tailored for WAAM of AZ31 magnesium alloy components,which integrates deposition efficiency and microstructure as coupled objectives and is resolved through the NSGA-Ⅱ algorithm.The proposed framework employs quadratic regression to correlate process parameters with deposition efficiency through geometric morphology mediation,while addressing uncertainties in WAAM by integrating theoretical insights with data-driven stacked ensemble learning for grain size prediction,establishing the hybrid physics-informed data method for WAAM microstructure prediction.The optimized process achieved a deposition rate of 6257 mm3/min,with effective width and average layer height maintained at 10.1 mm and 4.13 mm,respectively.Microstructural optimization produced a fine,uniform,fully equiaxed grain structure with an average grain size of 38μm.These findings underscore the significant industrial potential of intelligent optimization strategies in WAAM for manufacturing lightweight,high-performance components in aerospace and transportation sectors.展开更多
The integration of additive manufacturing(AM)and topology optimization(TO)has revolutionized the design and production of advanced equipment,providing innovative approaches to solving complex engineering challenges.In...The integration of additive manufacturing(AM)and topology optimization(TO)has revolutionized the design and production of advanced equipment,providing innovative approaches to solving complex engineering challenges.In the nuclear energy sector,achieving an optimal balance between the thermal and hydraulic performance of prismatic fuel elements has long been a key challenge.This study utilizes a coupled fluid-thermal TO method to design fuel elements with one,three,five,and seven inlets/outlets configurations suitable for AM.We systematically examine the impact of varying the number of inlets/outlets on the thermal-hydraulic performance of the elements.The results show that increasing the number of inlets/outlets can enhance the thermal performance of the fuel elements while sacrificing the hydraulic performance.Compared with the conventional design,the 5 inlets/outlets configuration achieved a coordinated improvement in both thermal and hydraulic performance,with a 2.38%enhancement in thermal performance and a 4.38%improvement in hydraulic performance.These findings highlight the significant potential of TO in improving the performance of fuel elements and strongly demonstrate the advantages of the collaborative application of AM and TO.展开更多
As a core power device in strategic industries such as new energy power generation and electric vehicles,the thermal reliability of IGBT modules directly determines the performance and lifetime of the whole system.A s...As a core power device in strategic industries such as new energy power generation and electric vehicles,the thermal reliability of IGBT modules directly determines the performance and lifetime of the whole system.A synergistic optimization structure of“inlet plate-channel spoiler columns”is proposed for the local hot spot problem during the operation of Insulated Gate Bipolar Transistor(IGBT),combined with the inherent defect of uneven flow distribution of the traditional U-type liquid cooling plate in this paper.The influences of the shape,height(H),and spacing from the spoiler column(b)of the plate on the comprehensive heat dissipation performance of the liquid cooling plate are analyzed at different Reynolds numbers,A dual heat source strategy is introduced and the effect of the optimized structure is evaluated by the temperature inhomogeneity coefficient(Φ).The results show that the optimum effect is achieved when the shape of the plate is square,H=4.5 mm,b=2 mm,and u=0.05 m/s,at which the HTPE=1.09 and Φ are reduced by 40%.In contrast,the maximum temperatures of the IGBT and the FWD(Free Wheeling Diode)chips are reduced by 8.7 and 8.4 K,respectively,and ΔP rises by only 1.58 Pa while keeping ΔT not significantly increased.This optimized configuration achieves a significant reduction in the critical chip temperature and optimization of the flow field uniformity with almost no change in the system flow resistance.It breaks through the limitation of single structure optimization of the traditional liquid cooling plate and effectively solves the problem of uneven flow in the U-shaped cooling plate,which provides a new solution with important engineering value for the thermal management of IGBT modules.展开更多
Seamless steel tubes,owing to their excellent integrity,structural properties,and processability,are widely applied in industries such as petroleum transportation,power and chemical industries,and national defense.How...Seamless steel tubes,owing to their excellent integrity,structural properties,and processability,are widely applied in industries such as petroleum transportation,power and chemical industries,and national defense.However,the stability of product quality in seamless steel tube production is often poor,particularly regarding the mechanical properties of intermediate products,which may not meet the required standards.This results in non-conforming products being unable to smoothly proceed to downstream processes.These issues mainly arise from the compactness of the production process,the characteristics of batch production,and the difficulty in managing order insertion.Consequently,optimizing the production process to minimize the impact of non-conforming products on subsequent processes has become a key challenge in seamless steel tube production.An intelligent reorganization production mechanism is proposed based on the full life cycle of seamless steel tubes,aiming at addressing the scheduling problems of tubes with abnormal performance.The mechanism utilizes a performance anomaly prediction model to detect and forecast potential anomalies in steel tubes,and in conjunction with intelligent scheduling strategies,rearranges the production plan for abnormal tubes.Experimental results demonstrate that the proposed mechanism can effectively improve the detection rate of abnormal tubes,significantly reduce time losses and energy consumption during production,and optimize both production cycles and stability.Specifically,the production cycle was shortened by 52 h,and energy consumption was reduced by approximately 12%.Through the intelligent scheduling model,the production plan was successfully optimized,reducing the production cycle and costs while improving production efficiency.The optimized scheduling scheme saved about 12%in production time,while enhancing the stability of the production plan and capacity utilization.展开更多
Heat Recovery Ventilators(HRVs)are essential for improving indoor air quality(IAQ)and reducing energy consumption in residential buildings situated in cold climates.This study considers the efficiency and performance ...Heat Recovery Ventilators(HRVs)are essential for improving indoor air quality(IAQ)and reducing energy consumption in residential buildings situated in cold climates.This study considers the efficiency and performance optimization of HRVs under cold climatic conditions,where conventional ventilation systems increase heat loss.A comprehensive numerical model was developed using COMSOL Multiphysics,integrating fluid dynamics,heat transfer,and solid mechanics to evaluate the thermal efficiency and structural integrity of an HRV system.The methodology employed a detailed geometry with tetrahedral elements,temperature-dependent material properties,and coupled governing equations solved under Tehran-specific boundary conditions.A multi-objective optimization was implemented in the framework of the Nelder-Mead simplex algorithm,targeting the maximization of the average outlet temperature and minimization of the maximum von Mises thermal stress,with inlet flow velocity as the design variable(range:0.5–1.2m/s).Results indicate an optimal velocity of 0.51563 m/s,achieving an average outlet temperature of 289.44 K and maximum von Mises stress of 221 MPa,validated through mesh independence and detailed contour analyses of temperature,velocity,and stress distributions.展开更多
To further enhance the recovery rate of low-temperature waste heat,the low-temperature flue gas in the sinter annular cooler was chosen as the heat source of an organic Rankine cycle(ORC)system,and the comprehensive e...To further enhance the recovery rate of low-temperature waste heat,the low-temperature flue gas in the sinter annular cooler was chosen as the heat source of an organic Rankine cycle(ORC)system,and the comprehensive evaluation of energy,exergy and economic performance of the ORC system was conducted deeply.The energy,exergy and economic performance models of the ORC system were established,and proper candidate organic working fluids(OWFs)were selected based on the thermo-physical properties of OWF and operating characteristics of ORC system.Then,the effects of ORC crucial parameters on the system energy,exergy and economic performances were evaluated in detail.Finally,the bi-objective optimization based on the genetic algorithm was conducted to analyze the optimal performance of the ORC system under the designed ORC crucial parameters,and the exergy efficiency and electricity production cost were set as the evaluation indexes of parametric optimization.The results indicate that the ORC system with the higher evaporation temperature and lower condensation temperature can obtain the larger system exergy efficiency and smaller electricity production cost.The smaller the superheat degree of OWF and pinch-point temperature difference in the evaporator are,the better the energy and exergy performances of the ORC system are.Under the optimization results,R245fa has the best comprehensive performance with the exergy efficiency of 46.34%and electricity production cost of 0.12123$/kWh among the selected candidate OWFs,which should be preferentially chosen as the OWF of the ORC system.展开更多
基金financially supported by the National Science Fund for Distinguished Young Scholars,China(No.52025041)the National Natural Science Foundation of China(Nos.52450003,U2341267,and 52174294)+1 种基金the National Postdoctoral Program for Innovative Talents,China(No.BX20240437)the Fundamental Research Funds for the Central Universities,China(Nos.FRF-IDRY-23-037 and FRF-TP-20-02C2)。
文摘The rapid advancements in computer vision(CV)technology have transformed the traditional approaches to material microstructure analysis.This review outlines the history of CV and explores the applications of deep-learning(DL)-driven CV in four key areas of materials science:microstructure-based performance prediction,microstructure information generation,microstructure defect detection,and crystal structure-based property prediction.The CV has significantly reduced the cost of traditional experimental methods used in material performance prediction.Moreover,recent progress made in generating microstructure images and detecting microstructural defects using CV has led to increased efficiency and reliability in material performance assessments.The DL-driven CV models can accelerate the design of new materials with optimized performance by integrating predictions based on both crystal and microstructural data,thereby allowing for the discovery and innovation of next-generation materials.Finally,the review provides insights into the rapid interdisciplinary developments in the field of materials science and future prospects.
基金funded by Deanship of Graduate studies and Scientific Research at Jouf University under grant No.(DGSSR-2024-02-01264).
文摘Automated essay scoring(AES)systems have gained significant importance in educational settings,offering a scalable,efficient,and objective method for evaluating student essays.However,developing AES systems for Arabic poses distinct challenges due to the language’s complex morphology,diglossia,and the scarcity of annotated datasets.This paper presents a hybrid approach to Arabic AES by combining text-based,vector-based,and embeddingbased similarity measures to improve essay scoring accuracy while minimizing the training data required.Using a large Arabic essay dataset categorized into thematic groups,the study conducted four experiments to evaluate the impact of feature selection,data size,and model performance.Experiment 1 established a baseline using a non-machine learning approach,selecting top-N correlated features to predict essay scores.The subsequent experiments employed 5-fold cross-validation.Experiment 2 showed that combining embedding-based,text-based,and vector-based features in a Random Forest(RF)model achieved an R2 of 88.92%and an accuracy of 83.3%within a 0.5-point tolerance.Experiment 3 further refined the feature selection process,demonstrating that 19 correlated features yielded optimal results,improving R2 to 88.95%.In Experiment 4,an optimal data efficiency training approach was introduced,where training data portions increased from 5%to 50%.The study found that using just 10%of the data achieved near-peak performance,with an R2 of 85.49%,emphasizing an effective trade-off between performance and computational costs.These findings highlight the potential of the hybrid approach for developing scalable Arabic AES systems,especially in low-resource environments,addressing linguistic challenges while ensuring efficient data usage.
基金National Natural Science Foundation of China(52261032,51861021,51661016)Science and Technology Plan of Gansu Province(21YF5GA074)+2 种基金Public Welfare Project of Zhejiang Natural Science Foundation(LGG22E010008)Wenzhou Basic Public Welfare Scientific Research Project(G2023020)Incubation Program of Excellent Doctoral Dissertation-Lanzhou University of Technology。
文摘The development of high-performance structural and functional materials is vital in many industrial fields.High-and medium-entropy alloys(H/MEAs)with superior comprehensive properties owing to their specific microstructures are promising candidates for structural materials.More importantly,multitudinous efforts have been made to regulate the microstructures and the properties of H/MEAs to further expand their industrial applications.The various heterostructures have enormous potential for the development of H/MEAs with outstanding performance.Herein,multiple heterogeneous structures with single and hierarchical heterogeneities were discussed in detail.Moreover,preparation methods for compositional inhomogeneity,bimodal structures,dualphase structures,lamella/layered structures,harmonic structures(core-shell),multiscale precipitates and heterostructures coupled with specific microstructures in H/MEAs were also systematically reviewed.The deformation mechanisms induced by the different heterostructures were thoroughly discussed to explore the relationship between the heterostructures and the optimized properties of H/MEAs.The contributions of the heterostructures and advanced microstructures to the H/MEAs were comprehensively elucidated to further improve the properties of the alloys.Finally,this review discussed the future challenges of high-performance H/MEAs for industrial applications and provides feasible methods for optimizing heterostructures to enhance the comprehensive properties of H/MEAs.
基金financially supported by the National Natural Science Foundation of China(Grant Nos.52071094 and 51979065).
文摘In this work,an oscillating-body wave energy converter(OBWEC)with a hydraulic power take-off(PTO)system named“Dolphin 1”is designed,in which the hydraulic PTO system is equivalent to a transfer station and plays a crucial role in ensuring the stability of the electrical energy output and the efficiency of the overall system.A corresponding mathematical model for the hydraulic PTO system has been established,the factors that influence its performance have been studied,and an algorithm for solving the optimal working pressure has been derived in this paper.Moreover,a PID control method to enable the hydraulic PTO system to automatically achieve optimal performance under different wave conditions has been designed.The results indicate that,compared with single-chamber hydraulic cylinders,double-chamber hydraulic cylinders have a wider application range and greater performance;the accumulator can stabilize the output power of the hydraulic PTO system and slightly increase it;excessively large or small hydraulic motor displacement hinders system performance;and each wave condition corresponds to a unique optimal working pressure for the hydraulic PTO system.In addition,the relationship between the optimal working pressure P_(m)and the pressure P_(h)of the wave force acting on the piston satisfies P_(m)^(2)=∫_(t_(1))^(t_(2))P_(h)^(2)dt/(t_(2)-t_(1)).Furthermore,adjusting the hydraulic motor displacement automatically via a PID controller ensures that the actual working pressure of the hydraulic PTO system consistently reaches or approaches its theoretically optimal value under various wave conditions,which is a very effective control method for enhancing the performance of the hydraulic PTO system.
文摘Amid the deepening implementation of rural revitalization strategies and rapid fintech development,rural commercial banks-core financial institutions serving agriculture,rural areas,and farmers(the“three rurals”)and county economies-have seen their tellers’service quality and operational efficiency directly impact market competitiveness and sustainable development capabilities.This study examines teller performance management in rural commercial banks from a business management perspective.By analyzing structural issues in existing performance management systems and integrating theoretical frameworks with industry case studies,it proposes systematic optimization measures.The research aims to provide practical references for establishing scientific and efficient teller performance management systems in rural commercial banks,thereby enhancing service quality,strengthening talent support,and better serving the rural financial market.
基金supported by Shanghai Collaborative Innovation Project(Grant No.XTCX-KJ-2024-01)the National Natural Science Foundation of China(Grant No.52205493).
文摘Increasing the texture complexity of high-performance surfaces can enhance their antifriction properties by altering their distribution and retention of lubricating oils.When a fluid flows through a fish-scale texture,a lubricating layer is formed,effectively reducing friction.In this study,a bionic fish-scale structure is proposed,and ceramic components are fabricated and analyzed using micro/nano additive-manufacturing technology.First,the effects of various parameters on the antifriction performance of the fish-scale texture under hydrodynamic lubrication conditions are investigated.Then,the pressure distribution of the oil film—including both positive and negative pressures—is simulated by adjusting parameters such as the angleα,ratio of textured area to total surface area,and depth of the fish-scale texture.The results indicate that for a textured area that accounts for 20%of the total surface,texture depth of 150μm,and angleαof 30°,the pressure differential reaches its maximum.Finally,based on the optimized parameters,the designed fish-scale structure is fabricated using micro/nano ceramic three-dimensional-printing technology.Friction and wear tests are conducted on the sintered samples.The experimental results align well with the simulation data,indicating that the structure can reduce the friction coefficient by approximately 15%,thereby significantly improving the antifriction performance.This study provides a valuable reference for the surface engineering of other high-performance functional structures.
基金support from the National Natural Science Foundation of China(22209089,22178187)Natural Science Foundation of Shandong Province(ZR2022QB048,ZR2021MB006)+2 种基金Excellent Youth Science Foundation of Shandong Province(Overseas)(2023HWYQ-089)the Taishan Scholars Program of Shandong Province(tsqn201909091)Open Research Fund of School of Chemistry and Chemical Engineering,Henan Normal University.
文摘Aqueous zinc-halogen batteries are promising candidates for large-scale energy storage due to their abundant resources,intrinsic safety,and high theoretical capacity.Nevertheless,the uncontrollable zinc dendrite growth and spontaneous shuttle effect of active species have prohibited their practical implementation.Herein,a double-layered protective film based on zinc-ethylenediamine tetramethylene phosphonic acid(ZEA)artificial film and ZnF2-rich solid electrolyte interphase(SEI)layer has been successfully fabricated on the zinc metal anode via electrode/electrolyte synergistic optimization.The ZEA-based artificial film shows strong affinity for the ZnF2-rich SEI layer,therefore effectively suppressing the SEI breakage and facilitating the construction of double-layered protective film on the zinc metal anode.Such double-layered architecture not only modulates Zn2+flux and suppresses the zinc dendrite growth,but also blocks the direct contact between the metal anode and electrolyte,thus mitigating the corrosion from the active species.When employing optimized metal anodes and electrolytes,the as-developed zinc-(dual)halogen batteries present high areal capacity and satisfactory cycling stability.This work provides a new avenue for developing aqueous zinc-(dual)halogen batteries.
基金Sponsored by Scientific and Technological Innovation Programs of Higher Education Institutions in Shanxi(Grant No.2022L294)Taiyuan University of Science and Technology Scientific Research Initial Funding(Grant Nos.W2022018,W20242012)Foundamental Research Program of Shanxi Province(Grant No.202403021212170).
文摘In recent years,surrogate models derived from genuine data samples have proven to be efficient in addressing optimization challenges that are costly or time⁃intensive.However,the individuals in the population become indistinguishable as the curse of dimensionality increases in the objective space and the accumulation of surrogate approximated errors.Therefore,in this paper,each objective function is modeled using a radial basis function approach,and the optimal solution set of the surrogate model is located by the multi⁃objective evolutionary algorithm of strengthened dominance relation.The original objective function values of the true evaluations are converted to two indicator values,and then the surrogate models are set up for the two performance indicators.Finally,an adaptive infill sampling strategy that relies on approximate performance indicators is proposed to assist in selecting individuals for real evaluations from the potential optimal solution set.The algorithm is contrasted against several advanced surrogate⁃assisted evolutionary algorithms on two suites of test cases,and the experimental findings prove that the approach is competitive in solving expensive many⁃objective optimization problems.
基金support from the National Natural Science Foundation of China(22108052).
文摘The biomass and coal co-pyrolysis (BCP) technology combines the advantages of both resources, achieving efficient resource complementarity, reducing reliance on coal, and minimizing pollutant emissions. However, this process still encounters numerous challenges in attaining optimal economic and environmental performance. Therefore, an ensemble learning (EL) framework is proposed for the BCP process in this study to optimize the synergistic benefits while minimizing negative environmental impacts. Six different ensemble learning models are developed to investigate the impact of input features, such as biomass characteristics, coal characteristics, and pyrolysis conditions on the product profit and CO_(2) emissions of the BCP processes. The Optuna method is further employed to automatically optimize the hyperparameters of BCP process models for enhancing their predictive accuracy and robustness. The results indicate that the categorical boosting (CAB) model of the BCP process has demonstrated exceptional performance in accurately predicting its product profit and CO_(2) emission (R2>0.92) after undergoing five-fold cross-validation. To enhance the interpretability of this preferred model, the Shapley additive explanations and partial dependence plot analyses are conducted to evaluate the impact and importance of biomass characteristics, coal characteristics, and pyrolysis conditions on the product profitability and CO_(2) emissions of the BCP processes. Finally, the preferred model coupled with a reference vector guided evolutionary algorithm is carried to identify the optimal conditions for maximizing the product profit of BCP process products while minimizing CO_(2) emissions. It indicates the optimal BCP process can achieve high product profits (5290.85 CNY·t−1) and low CO_(2) emissions (7.45 kg·t^(−1)).
基金financially supported by the National Natural Science Foundation of China(No.52102062)the Xi’an Science and Technology Plan Project(No.23LLRH0004)the Key Research and Development Project of Shaanxi Province of China(2024GX-YBXM-352)。
文摘Vat photopolymerization(VPP)3D printing is an optimized technology for complex-shaped ceramic cores,in which the solid loading of ceramic slurries greatly infiuences the microstructure and property of the final ceramic parts.However,the high solid loading of slurries is highly limited by the high viscosity.In this study,silica-based ceramic core slurries with solid loading up to 68vol.%were achieved by the composition design to optimize the performance,considering the curing,rheological,and double bond conversion rate.The slurries demonstrate superior curing and rheological performance with mass ratio of monomers being 3:2 and mass fraction of BYK111 being 4wt.%.Afterwards,the impact of solid loading on the morphology and mechanical properties was investigated.As the solid loading increases,the microstructure becomes gradually dense,leading to an improved flexural strength of 19.5 MPa.Additionally,the sintering shrinkage becomes more uniform,satisfying the casting requirements effectively.This work serves as a guide for the preparation of ceramic slurries with a high solid loading.
基金Supported by National Natural Science Foundation of China(Grant Nos.52072156,52272366)Postdoctoral Foundation of China(Grant No.2020M682269).
文摘The spoke as a key component has a significant impact on the performance of the non-pneumatic tire(NPT).The current research has focused on adjusting spoke structures to improve the single performance of NPT.Few studies have been conducted to synergistically improve multi-performance by optimizing the spoke structure.Inspired by the concept of functionally gradient structures,this paper introduces a functionally gradient honeycomb NPT and its optimization method.Firstly,this paper completes the parameterization of the honeycomb spoke structure and establishes the numerical models of honeycomb NPTs with seven different gradients.Subsequently,the accuracy of the numerical models is verified using experimental methods.Then,the static and dynamic characteristics of these gradient honeycomb NPTs are thoroughly examined by using the finite element method.The findings highlight that the gradient structure of NPT-3 has superior performance.Building upon this,the study investigates the effects of key parameters,such as honeycomb spoke thickness and length,on load-carrying capacity,honeycomb spoke stress and mass.Finally,a multi-objective optimization method is proposed that uses a response surface model(RSM)and the Nondominated Sorting Genetic Algorithm-II(NSGA-II)to further optimize the functional gradient honeycomb NPTs.The optimized NPT-OP shows a 23.48%reduction in radial stiffness,8.95%reduction in maximum spoke stress and 16.86%reduction in spoke mass compared to the initial NPT-1.The damping characteristics of the NPT-OP have also been improved.The results offer a theoretical foundation and technical methodology for the structural design and optimization of gradient honeycomb NPTs.
基金the support of the U.S.Department of Energy’s Vehicle Technologies Office.
文摘High-pressure die cast(HPDC)AZ91 magnesium alloy is widely used in automotive components such as transmission housings and brackets for its excellent strength-to-weight ratio.Zinc-based cold spray coatings can be applied selectively to vulnerable areas to enhance corrosion resistance,minimize galvanic coupling with dissimilar metals,and eliminate the need for full-surface oxide coatings,making the process more efficient and targeted.A comprehensive evaluation of 16 combinations of nitrogen carrier gas temperatures and pressures led to the identification of an optimal range of process parameters,yielding Zn coatings with porosity<0.5% by area,wear rates reduced by a factor of two compared to uncoated AZ91,and adhesion strengths up to 35 MPa.The enhanced mechanical performance of the coating is attributed to the low porosity and the formation of a metallurgical bond at the coating-substrate interface.Corrosion studies using macroscale potentiodynamic polarization(PDP)and electrochemical impedance spectroscopy(EIS)revealed a significant decrease in corrosion rate and a shift to more noble corrosion potentials(ZCP)for coated substrates.Furthermore,the Zn cold-sprayed samples exhibited significantly lower corrosioninduced evolved hydrogen content compared to the base AZ91 substrate and AZ91 coated with industrial coatings,demonstrating that the Zn layer effectively protects the substrate from the corrosive environment.Overall,cold spray Zn coatings significantly improve the mechanical and corrosion performance of AZ91 Mg alloys,addressing key material challenges and enabling their broader use in automotive applications.
基金supported by the National Natural Science Foundation of China(71871219).
文摘Performance-based warranties(PBWs)are widely used in industry and manufacturing.Given that PBW can impose financial burdens on manufacturers,rational maintenance decisions are essential for expanding profit margins.This paper proposes an optimization model for PBW decisions for systems affected by Gamma degradation processes,incorporating periodic inspection.A system performance degradation model is established.Preventive maintenance probability and corrective renewal probability models are developed to calculate expected warranty costs and system availability.A benefits function,which includes incentives,is constructed to optimize the initial and subsequent inspection intervals and preventive maintenance thresholds,thereby maximizing warranty profit.An improved sparrow search algorithm is developed to optimize the model,with a case study on large steam turbine rotor shafts.The results suggest the optimal PBW strategy involves an initial inspection interval of approximately 20 months,with subsequent intervals of about four months,and a preventive maintenance threshold of approximately 37.39 mm wear.When compared to common cost-minimization-based condition maintenance strategies and PBW strategies that do not differentiate between initial and subsequent inspection intervals,the proposed PBW strategy increases the manufacturer’s profit by 1%and 18%,respectively.Sensitivity analyses provide managerial recommendations for PBW implementation.The PBW strategy proposed in this study significantly increases manufacturers’profits by optimizing inspection intervals and preventive maintenance thresholds,and manufacturers should focus on technological improvement in preventive maintenance and cost control to further enhance earnings.
基金supported by the National Natural Science Foundation of China(Nos.52475317 and 52305331).
文摘In wire arc additive manufacturing(WAAM),a trade-off exists among deposition efficiency,microstructure,and mechanical properties.Addressing this challenge,this work proposes an innovative multi-objective optimization framework tailored for WAAM of AZ31 magnesium alloy components,which integrates deposition efficiency and microstructure as coupled objectives and is resolved through the NSGA-Ⅱ algorithm.The proposed framework employs quadratic regression to correlate process parameters with deposition efficiency through geometric morphology mediation,while addressing uncertainties in WAAM by integrating theoretical insights with data-driven stacked ensemble learning for grain size prediction,establishing the hybrid physics-informed data method for WAAM microstructure prediction.The optimized process achieved a deposition rate of 6257 mm3/min,with effective width and average layer height maintained at 10.1 mm and 4.13 mm,respectively.Microstructural optimization produced a fine,uniform,fully equiaxed grain structure with an average grain size of 38μm.These findings underscore the significant industrial potential of intelligent optimization strategies in WAAM for manufacturing lightweight,high-performance components in aerospace and transportation sectors.
基金supported by National Natural Science Foundation of China(Grant No.1257021702)National Key Research and Development Program of China(Grant No.2022YFB4603101).
文摘The integration of additive manufacturing(AM)and topology optimization(TO)has revolutionized the design and production of advanced equipment,providing innovative approaches to solving complex engineering challenges.In the nuclear energy sector,achieving an optimal balance between the thermal and hydraulic performance of prismatic fuel elements has long been a key challenge.This study utilizes a coupled fluid-thermal TO method to design fuel elements with one,three,five,and seven inlets/outlets configurations suitable for AM.We systematically examine the impact of varying the number of inlets/outlets on the thermal-hydraulic performance of the elements.The results show that increasing the number of inlets/outlets can enhance the thermal performance of the fuel elements while sacrificing the hydraulic performance.Compared with the conventional design,the 5 inlets/outlets configuration achieved a coordinated improvement in both thermal and hydraulic performance,with a 2.38%enhancement in thermal performance and a 4.38%improvement in hydraulic performance.These findings highlight the significant potential of TO in improving the performance of fuel elements and strongly demonstrate the advantages of the collaborative application of AM and TO.
基金supported by Tianjin Science and Technology Planning Project(22YDTPJC0020).
文摘As a core power device in strategic industries such as new energy power generation and electric vehicles,the thermal reliability of IGBT modules directly determines the performance and lifetime of the whole system.A synergistic optimization structure of“inlet plate-channel spoiler columns”is proposed for the local hot spot problem during the operation of Insulated Gate Bipolar Transistor(IGBT),combined with the inherent defect of uneven flow distribution of the traditional U-type liquid cooling plate in this paper.The influences of the shape,height(H),and spacing from the spoiler column(b)of the plate on the comprehensive heat dissipation performance of the liquid cooling plate are analyzed at different Reynolds numbers,A dual heat source strategy is introduced and the effect of the optimized structure is evaluated by the temperature inhomogeneity coefficient(Φ).The results show that the optimum effect is achieved when the shape of the plate is square,H=4.5 mm,b=2 mm,and u=0.05 m/s,at which the HTPE=1.09 and Φ are reduced by 40%.In contrast,the maximum temperatures of the IGBT and the FWD(Free Wheeling Diode)chips are reduced by 8.7 and 8.4 K,respectively,and ΔP rises by only 1.58 Pa while keeping ΔT not significantly increased.This optimized configuration achieves a significant reduction in the critical chip temperature and optimization of the flow field uniformity with almost no change in the system flow resistance.It breaks through the limitation of single structure optimization of the traditional liquid cooling plate and effectively solves the problem of uneven flow in the U-shaped cooling plate,which provides a new solution with important engineering value for the thermal management of IGBT modules.
基金financially supported by Jiangxi Provincial Key R&D ProgrammeProjects(No.20223BBE51032)National Natural Science Foundation of China(No.52305336)the Opening Project of Guangdong Provincial Key Laboratory for Processing and Forming of Advanced Metallic Materials,South China University of Technology(No.GJ202411).
文摘Seamless steel tubes,owing to their excellent integrity,structural properties,and processability,are widely applied in industries such as petroleum transportation,power and chemical industries,and national defense.However,the stability of product quality in seamless steel tube production is often poor,particularly regarding the mechanical properties of intermediate products,which may not meet the required standards.This results in non-conforming products being unable to smoothly proceed to downstream processes.These issues mainly arise from the compactness of the production process,the characteristics of batch production,and the difficulty in managing order insertion.Consequently,optimizing the production process to minimize the impact of non-conforming products on subsequent processes has become a key challenge in seamless steel tube production.An intelligent reorganization production mechanism is proposed based on the full life cycle of seamless steel tubes,aiming at addressing the scheduling problems of tubes with abnormal performance.The mechanism utilizes a performance anomaly prediction model to detect and forecast potential anomalies in steel tubes,and in conjunction with intelligent scheduling strategies,rearranges the production plan for abnormal tubes.Experimental results demonstrate that the proposed mechanism can effectively improve the detection rate of abnormal tubes,significantly reduce time losses and energy consumption during production,and optimize both production cycles and stability.Specifically,the production cycle was shortened by 52 h,and energy consumption was reduced by approximately 12%.Through the intelligent scheduling model,the production plan was successfully optimized,reducing the production cycle and costs while improving production efficiency.The optimized scheduling scheme saved about 12%in production time,while enhancing the stability of the production plan and capacity utilization.
文摘Heat Recovery Ventilators(HRVs)are essential for improving indoor air quality(IAQ)and reducing energy consumption in residential buildings situated in cold climates.This study considers the efficiency and performance optimization of HRVs under cold climatic conditions,where conventional ventilation systems increase heat loss.A comprehensive numerical model was developed using COMSOL Multiphysics,integrating fluid dynamics,heat transfer,and solid mechanics to evaluate the thermal efficiency and structural integrity of an HRV system.The methodology employed a detailed geometry with tetrahedral elements,temperature-dependent material properties,and coupled governing equations solved under Tehran-specific boundary conditions.A multi-objective optimization was implemented in the framework of the Nelder-Mead simplex algorithm,targeting the maximization of the average outlet temperature and minimization of the maximum von Mises thermal stress,with inlet flow velocity as the design variable(range:0.5–1.2m/s).Results indicate an optimal velocity of 0.51563 m/s,achieving an average outlet temperature of 289.44 K and maximum von Mises stress of 221 MPa,validated through mesh independence and detailed contour analyses of temperature,velocity,and stress distributions.
基金the financial support for this work provided by the National Natural Science Foundation of China(51974087)Anhui Provincial Natural Science Foundation(1908085QE203)+1 种基金University Natural Science Research Foundation of Anhui Province(2022AH050262)Science Research Foundation of Anhui Jianzhu University(2020QDZ02).
文摘To further enhance the recovery rate of low-temperature waste heat,the low-temperature flue gas in the sinter annular cooler was chosen as the heat source of an organic Rankine cycle(ORC)system,and the comprehensive evaluation of energy,exergy and economic performance of the ORC system was conducted deeply.The energy,exergy and economic performance models of the ORC system were established,and proper candidate organic working fluids(OWFs)were selected based on the thermo-physical properties of OWF and operating characteristics of ORC system.Then,the effects of ORC crucial parameters on the system energy,exergy and economic performances were evaluated in detail.Finally,the bi-objective optimization based on the genetic algorithm was conducted to analyze the optimal performance of the ORC system under the designed ORC crucial parameters,and the exergy efficiency and electricity production cost were set as the evaluation indexes of parametric optimization.The results indicate that the ORC system with the higher evaporation temperature and lower condensation temperature can obtain the larger system exergy efficiency and smaller electricity production cost.The smaller the superheat degree of OWF and pinch-point temperature difference in the evaporator are,the better the energy and exergy performances of the ORC system are.Under the optimization results,R245fa has the best comprehensive performance with the exergy efficiency of 46.34%and electricity production cost of 0.12123$/kWh among the selected candidate OWFs,which should be preferentially chosen as the OWF of the ORC system.
