Accurate determination of rock mass parameters is essential for ensuring the accuracy of numericalsimulations. Displacement back-analysis is the most widely used method;however, the reliability of thecurrent approache...Accurate determination of rock mass parameters is essential for ensuring the accuracy of numericalsimulations. Displacement back-analysis is the most widely used method;however, the reliability of thecurrent approaches remains unsatisfactory. Therefore, in this paper, a multistage rock mass parameterback-analysis method, that considers the construction process and displacement losses is proposed andimplemented through the coupling of numerical simulation, auto-machine learning (AutoML), andmulti-objective optimization algorithms (MOOAs). First, a parametric modeling platform for mechanizedtwin tunnels is developed, generating a dataset through extensive numerical simulations. Next, theAutoML method is utilized to establish a surrogate model linking rock parameters and displacements.The tunnel construction process is divided into multiple stages, transforming the rock mass parameterback-analysis into a multi-objective optimization problem, for which multi-objective optimization algorithmsare introduced to obtain the rock mass parameters. The newly proposed rock mass parameterback-analysis method is validated in a mechanized twin tunnel project, and its accuracy and effectivenessare demonstrated. Compared with traditional single-stage back-analysis methods, the proposedmodel decreases the average absolute percentage error from 12.73% to 4.34%, significantly improving theaccuracy of the back-analysis. Moreover, although the accuracy of back analysis significantly increaseswith the number of construction stages considered, the back analysis time is acceptable. This studyprovides a new method for displacement back analysis that is efficient and accurate, thereby paving theway for precise parameter determination in numerical simulations.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
Compared to other energy sources,nuclear reactors offer several advantages as a spacecraft power source,including compact size,high power density,and long operating life.These qualities make nuclear power an ideal ene...Compared to other energy sources,nuclear reactors offer several advantages as a spacecraft power source,including compact size,high power density,and long operating life.These qualities make nuclear power an ideal energy source for future deep space exploration.A whole system model of the space nuclear reactor consisting of the reactor neutron kinetics,reactivity control,reactor heat transfer,heat exchanger,and thermoelectric converter was developed.In addition,an electrical power control system was designed based on the developed dynamic model.The GRS method was used to quantitatively calculate the uncertainty of coupling parameters of the neutronics,thermal-hydraulics,and control system for the space reactor.The Spearman correlation coefficient was applied in the sensitivity analysis of system input parameters to output parameters.The calculation results showed that the uncertainty of the output parameters caused by coupling parameters had the most considerable variation,with a relative standard deviation<2.01%.Effective delayed neutron fraction was most sensitive to electrical power.To obtain optimal control performance,the non-dominated sorting genetic algorithm method was employed to optimize the controller parameters based on the uncertainty quantification calculation.Two typical transient simulations were conducted to test the adaptive ability of the optimized controller in the uncertainty dynamic system,including 100%full power(FP)to 90%FP step load reduction transient and 5%FP/min linear variable load transient.The results showed that,considering the influence of system uncertainty,the optimized controller could improve the response speed and load following accuracy of electrical power control,in which the effectiveness and superiority have been verified.展开更多
Border-associated macrophages are located at the interface between the brain and the periphery, including the perivascular spaces, choroid plexus, and meninges. Until recently, the functions of border-associated macro...Border-associated macrophages are located at the interface between the brain and the periphery, including the perivascular spaces, choroid plexus, and meninges. Until recently, the functions of border-associated macrophages have been poorly understood and largely overlooked. However, a recent study reported that border-associated macrophages participate in stroke-induced inflammation, although many details and the underlying mechanisms remain unclear. In this study, we performed a comprehensive single-cell analysis of mouse border-associated macrophages using sequencing data obtained from the Gene Expression Omnibus(GEO) database(GSE174574 and GSE225948). Differentially expressed genes were identified, and enrichment analysis was performed to identify the transcription profile of border-associated macrophages. CellChat analysis was conducted to determine the cell communication network of border-associated macrophages. Transcription factors were predicted using the ‘pySCENIC' tool. We found that, in response to hypoxia, borderassociated macrophages underwent dynamic transcriptional changes and participated in the regulation of inflammatory-related pathways. Notably, the tumor necrosis factor pathway was activated by border-associated macrophages following ischemic stroke. The pySCENIC analysis indicated that the activity of signal transducer and activator of transcription 3(Stat3) was obviously upregulated in stroke, suggesting that Stat3 inhibition may be a promising strategy for treating border-associated macrophages-induced neuroinflammation. Finally, we constructed an animal model to investigate the effects of border-associated macrophages depletion following a stroke. Treatment with liposomes containing clodronate significantly reduced infarct volume in the animals and improved neurological scores compared with untreated animals. Taken together, our results demonstrate comprehensive changes in border-associated macrophages following a stroke, providing a theoretical basis for targeting border-associated macrophages-induced neuroinflammation in stroke treatment.展开更多
Background:Receptor-interacting protein kinases(RIPKs)regulate cell death,inflammation,and immune responses,yet their roles in cancer are not fully understood.This study investigates the expression,genomic alterations...Background:Receptor-interacting protein kinases(RIPKs)regulate cell death,inflammation,and immune responses,yet their roles in cancer are not fully understood.This study investigates the expression,genomic alterations,and functional implications of RIPK family members across various cancers.Methods:We collected multi-omics data from The Cancer Genome Atlas and other public databases,including gene expression,copy number variation(CNV),mutation,methylation,tumor mutation burden(TMB),and microsatellite instability(MSI).Differential expression and survival analyses were performed using DESeq2 and Cox proportional hazards models.CNV and mutation data were analyzed with GISTIC2 and Mutect2,and methylation data with the ChAMP package.Correlations with TMB and MSI were assessed using Pearson coefficients,and gene set enrichment analysis was conducted with the MSigDB Hallmark gene sets.Results:RIPK family members show significant differential expression in various cancers,with RIPK1 and RIPK4 frequently altered.Survival analysis reveals heterogeneous impacts on overall survival.CNV and mutation analyses identify high alteration frequencies for RIPK2 and RIPK7,affecting gene expression.RIPK1 and RIPK7 are hypermethylated in several cancers,inversely correlating with RIPK3 expression.RIPK1,RIPK2,RIPK5,RIPK6,and RIPK7 correlate positively with TMB,while RIPK3 shows negative correlations in some cancers.MSI analysis indicates associations with DNA mismatch repair.G ene set enrichment analysis highlights immune-related pathway enrichment for RIPK1,RIPK2,RIPK3,and RIPK6,and cell proliferation and DNA repair pathways for RIPK4 and RIPK5.RIPK family members showed heterogeneous alterations across cancers:for example,RIPK7 was mutated in up to~15%of u terine c orpus e ndometrial c arcinoma and l ung s quamous c ell c arcinoma cases,and RIPK1 and RIPK7 exhibited frequent promoter hypermethylation in multiple tumor types.Several genes displayed context-dependent associations with overall survival and with TMB/MSI.Conclusion:This pan-cancer analysis of the RIPK family reveals their diverse roles and potential as biomarkers and therapeutic targets.The findings emphasize the importance of RIPK genes in tumorigenesis and suggest context-dependent functions across cancer types.Further studies are needed to explore their mechanisms in cancer development and clinical applications.展开更多
The sulfation and decomposition process has proven effective in selectively extracting lithium from lepidolite.It is essential to clarify the thermochemical behavior and kinetic parameters of decomposition reactions.A...The sulfation and decomposition process has proven effective in selectively extracting lithium from lepidolite.It is essential to clarify the thermochemical behavior and kinetic parameters of decomposition reactions.Accordingly,comprehensive kinetic study by employing thermalgravimetric analysis at various heating rates was presented in this paper.Two main weight loss regions were observed during heating.The initial region corresponded to the dehydration of crystal water,whereas the subsequent region with overlapping peaks involved complex decomposition reactions.The overlapping peaks were separated into two individual reaction peaks and the activation energy of each peak was calculated using isoconversional kinetics methods.The activation energy of peak 1 exhibited a continual increase as the reaction conversion progressed,while that of peak 2 steadily decreased.The optimal kinetic models,identified as belonging to the random nucleation and subsequent growth category,provided valuable insights into the mechanism of the decomposition reactions.Furthermore,the adjustment factor was introduced to reconstruct the kinetic mechanism models,and the reconstructed models described the kinetic mechanism model more accurately for the decomposition reactions.This study enhanced the understanding of the thermochemical behavior and kinetic parameters of the lepidolite sulfation product decomposition reactions,further providing theoretical basis for promoting the selective extraction of lithium.展开更多
This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for ...This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for identifying critical failure modes and their root causes,while BN introduces flexibility in probabilistic reasoning,enabling dynamic updates based on new evidence.This dual methodology overcomes the limitations of static FTA models,offering a comprehensive framework for system reliability analysis.Critical failures,including External Leakage(ELU),Failure to Start(FTS),and Overheating(OHE),were identified as key risks.By incorporating redundancy into high-risk components such as pumps and batteries,the likelihood of these failures was significantly reduced.For instance,redundant pumps reduced the probability of ELU by 31.88%,while additional batteries decreased the occurrence of FTS by 36.45%.The results underscore the practical benefits of combining FTA and BN for enhancing system reliability,particularly in maritime applications where operational safety and efficiency are critical.This research provides valuable insights for maintenance planning and highlights the importance of redundancy in critical systems,especially as the industry transitions toward more autonomous vessels.展开更多
AIM:To explore the causal relationship between several possible behavioral factors and high myopia(HM)using multivariable Mendelian randomization(MVMR)approach and to find the mediators among them with mediation analy...AIM:To explore the causal relationship between several possible behavioral factors and high myopia(HM)using multivariable Mendelian randomization(MVMR)approach and to find the mediators among them with mediation analysis.METHODS:The causal effects of several behavioral factors,including screen time,education time,time spent outdoors,and physical activity,on the risk of HM using univariable Mendelian randomization(MR)and MVMR analyses were first assessed.Genome-wide association study summary statistics of serum metabolites were also used in mediation analysis to determine the extent to which serum metabolites mediate the effects of behavioral factors on HM.RESULTS:MR analyses indicated that both increased time spent outdoors and a higher frequency of moderate physical activity significantly reduced the risk of HM.Further MVMR analysis confirmed that moderate physical activity independently contributed to a lower risk of HM.Additionally,MR analyses identified 13 serum metabolites significantly associated with HM,of which 12 were lipids and one was an amino acid derivative.Mediation analysis revealed that six lipid metabolites mediated the protective effects of moderate physical activity on HM,with the highest mediation proportion observed for 1-(1-enyl-palmitoyl)-GPC(p-16:0;30.83%).CONCLUSION:This study suggests that in addition to outdoor time,moderate physical activity habits may have an independent protective effect against HM and pointed to lipid metabolites as priority targets for the prevention due to low physical activity.These results emphasize the importance of physical activity and metabolic health in HM and underscore the need for further study of these complex associations.展开更多
AIM:To summarize publication trends in the field of strabismus over the past 30y and predict future research hotspots.METHODS:A total of 2915 English-language articles and reviews on strabismus,published between 1993 ...AIM:To summarize publication trends in the field of strabismus over the past 30y and predict future research hotspots.METHODS:A total of 2915 English-language articles and reviews on strabismus,published between 1993 and 2022,were retrieved from the Web of Science Core Collection.Bibliometric analyses were performed using VOSviewer and CiteSpace software to explore publication trends,as well as the contributions and collaborative networks of countries/regions,authors,institutions,and journals.RESULTS:The annual number of publications on strabismus showed a consistent upward trend.The United States(USA)maintained a leading position in this research field while Republic of Korea and China emerged as rapidly advancing contributors over the last decade.The University of California,Los Angeles ranked as the most productive institution,and Jonathan M.Holmes from USA was the most productive author.Journal of AAPOS was the leading journal with the most strabismus publications,whereas the two most highly cited articles were both published in Ophthalmology.Co-occurrence analysis identified pivotal keywords and burst terms,including intermittent exotropia(IXT),acute acquired comitant esotropia(AACE),functional magnetic resonance imaging(fMRI),and surgical treatment,which were confirmed as predominant and frontier topics.CONCLUSION:This study provides a comprehensive bibliometric analysis of strabismus research,revealing the evolution of research hotspots over the past 30y and outlining several cutting-edge directions for future investigation.展开更多
Based on improved multi-objective particle swarm optimization（MOPSO） algorithm with principal component analysis（PCA） methodology, an efficient high-dimension multiobjective optimization method is proposed, which,...Based on improved multi-objective particle swarm optimization（MOPSO） algorithm with principal component analysis（PCA） methodology, an efficient high-dimension multiobjective optimization method is proposed, which, as the purpose of this paper, aims to improve the convergence of Pareto front in multi-objective optimization design. The mathematical efficiency,the physical reasonableness and the reliability in dealing with redundant objectives of PCA are verified by typical DTLZ5 test function and multi-objective correlation analysis of supercritical airfoil,and the proposed method is integrated into aircraft multi-disciplinary design（AMDEsign） platform, which contains aerodynamics, stealth and structure weight analysis and optimization module.Then the proposed method is used for the multi-point integrated aerodynamic optimization of a wide-body passenger aircraft, in which the redundant objectives identified by PCA are transformed to optimization constraints, and several design methods are compared. The design results illustrate that the strategy used in this paper is sufficient and multi-point design requirements of the passenger aircraft are reached. The visualization level of non-dominant Pareto set is improved by effectively reducing the dimension without losing the primary feature of the problem.展开更多
With the high speed, the rotor of magnetically suspended permanent magnet synchronous motor(MSPMSM) suffers great thermal stress and mechanical stress resulting from the temperature rise problem caused by rotor losses...With the high speed, the rotor of magnetically suspended permanent magnet synchronous motor(MSPMSM) suffers great thermal stress and mechanical stress resulting from the temperature rise problem caused by rotor losses, which leads to instability and inefficiency.In this paper, the mechanical–temperature field coupling analysis is conducted to analyze the relationship between the temperature field and structure, and multi-objective optimization of a rotor is performed to improve the design reliability and efficiency. Firstly, the temperature field is calculated by the 2 D finite element model of MSPMSM and the method of applying the 2 D temperature result to the 3 D finite element model of the motor rotor equivalently is proposed. Then the thermal–structure coupling analysis is processed through mathematic method and finite element method(FEM),in which the 3 D finite element model is established precisely in a way and approaches the practical operation state further. Moreover, the impact produced by the temperature and structure on the mechanical strength is analyzed in detail. Finally, the optimization mathematical model of the motor rotor is established with Sequential Quadratic Programming-NLPQL selected in the optimization scheme. Through optimization, the strength of the components in the motor rotor increases obviously and satisfies the design requirement, which to a great extend enhances the service life of the MSPMSM rotor.展开更多
A multi-objective optimization and analysis model of the sintering process based on BP neural network is presented. Genetic algorithms are combined to simplify the BP neural network, which can reduce the learning time...A multi-objective optimization and analysis model of the sintering process based on BP neural network is presented. Genetic algorithms are combined to simplify the BP neural network, which can reduce the learning time and increase the forecasting accuracy of the network model. This model has been experimented in the sintering process, and the production cost, the energy consumption, the quality （revolving intensity）, and the output are considered at the same time. Moreover, the relation between some factors and the multi-objectives has been analyzed, and the results are consistent with the process. Different objectives are emphasized at different practical periods, and this can provide a theoretical basis for the manager.展开更多
The pressurizing pipeline of hot press resonates under the excitation load,which poses a serious hidden danger to the safety of the equipment and the operator.In order to increase the natural frequency of the pressuri...The pressurizing pipeline of hot press resonates under the excitation load,which poses a serious hidden danger to the safety of the equipment and the operator.In order to increase the natural frequency of the pressurizing pipeline,modal analysis of the pressurizing pipeline is carried out to study the mechanism of pipeline vibration and common vibration reduction measures.A method of increasing the natural frequency of the pressurizing pipeline was analyzed.The influence of pipeline clamp assembly stiffness,pipeline clamp number and pipeline clamp installation position on the mode of the pressurizing pipeline is studied.Sensitivity analysis is carried out to study the influence of the various parameters on the mode of the pressurizing pipeline.Genetic algorithm based on Pareto optimality is introduced for multi-objective optimization of pressurizing pipeline.The optimization results show that the natural frequency of the pressurizing pipeline increases by 2.4%and the displacement response is reduced by 17.7%.展开更多
Real-time prediction of excavation-induced displacement of retaining pile during the deep excavation process is crucial for construction safety.This paper proposes a modified back analysis method with multi-objective ...Real-time prediction of excavation-induced displacement of retaining pile during the deep excavation process is crucial for construction safety.This paper proposes a modified back analysis method with multi-objective optimization procedure,which enables a real-time prediction of horizontal displacement of retaining pile during construction.As opposed to the traditional stage-by-stage back analysis,time series monitoring data till the current excavation stage are utilized to form a multi-objective function.Then,the multi-objective particle swarm optimization (MOPSO) algorithm is applied for parameter identification.The optimized model parameters are immediately adopted to predict the excavation-induced pile deformation in the continuous construction stages.To achieve efficient parameter optimization and real-time prediction of system behavior,the back propagation neural network (BPNN) is established to substitute the finite element model,which is further implemented together with MOPSO for automatic operation.The proposed approach is applied in the Taihu tunnel excavation project,where the effectiveness of the method is demonstrated via the comparisons with the site monitoring data.The method is reliable with a prediction accuracy of more than 90%.Moreover,different optimization algorithms,including non-dominated sorting genetic algorithm (NSGA-II),Pareto Envelope-based Selection Algorithm II (PESA-II) and MOPSO,are compared,and their influences on the prediction accuracy at different excavation stages are studied.The results show that MOPSO has the best performance for high dimensional optimization task.展开更多
In order to improve the crashworthiness of thin-walled columns, the energy absorption characteristics of three columns under quasi-static axial crushing loads were analyzed through LS-DYNA. Numerical results show that...In order to improve the crashworthiness of thin-walled columns, the energy absorption characteristics of three columns under quasi-static axial crushing loads were analyzed through LS-DYNA. Numerical results show that the energy absorption capability of the bitubular hexagonal columns with middle to middle(MTM) ribs is the best, followed by the bitubular hexagonal columns with corner to corner(CTC) ribs and the bitubular hexagonal columns without(NOT) ribs, respectively. Then, the MTM rib was optimized by using multi-objective particle swarm optimization algorithm. Through the analysis of the Pareto front for specific energy absorption(SEA, A_(se)) and peak crushing force(PCF, F_(pc)), it is found that there is a vertex on the Pareto front. The vertex has the design parameters of t_1=1.2 mm, t_2=1.2 mm, A_(se)=11.3729 k J/kg, F_(pc)=235.8491 kN. When the PCF is in a certain size, on the left of the vertex, the point with t_2=1.2 mm has the biggest SEA, meanwhile on the right of the vertex, the point with t_1=1.2 mm has the biggest SEA. Finally, the global sensitivity analysis was conducted to investigate the effect of two design parameters. The result is obtained that both SEA and PCF for MTM are more sensitive to t_1 rather than t_2 in the design domain.展开更多
The multiple determination tasks of chemical properties are a classical problem in analytical chemistry. The major problem is concerned in to find the best subset of variables that better represents the compounds. The...The multiple determination tasks of chemical properties are a classical problem in analytical chemistry. The major problem is concerned in to find the best subset of variables that better represents the compounds. These variables are obtained by a spectrophotometer device. This device measures hundreds of correlated variables related with physicocbemical properties and that can be used to estimate the component of interest. The problem is the selection of a subset of informative and uncorrelated variables that help the minimization of prediction error. Classical algorithms select a subset of variables for each compound considered. In this work we propose the use of the SPEA-II （strength Pareto evolutionary algorithm II）. We would like to show that the variable selection algorithm can selected just one subset used for multiple determinations using multiple linear regressions. For the case study is used wheat data obtained by NIR （near-infrared spectroscopy） spectrometry where the objective is the determination of a variable subgroup with information about E protein content （%）, test weight （Kg/HI）, WKT （wheat kernel texture） （%） and farinograph water absorption （%）. The results of traditional techniques of multivariate calibration as the SPA （successive projections algorithm）, PLS （partial least square） and mono-objective genetic algorithm are presents for comparisons. For NIR spectral analysis of protein concentration on wheat, the number of variables selected from 775 spectral variables was reduced for just 10 in the SPEA-II algorithm. The prediction error decreased from 0.2 in the classical methods to 0.09 in proposed approach, a reduction of 37%. The model using variables selected by SPEA-II had better prediction performance than classical algorithms and full-spectrum partial least-squares.展开更多
Driven by the goal of“carbon neutrality,”the increase in use of renewable energy power systems will be inevitable in the future.Uncontrolled output power and random volatility make it difficult to balance power in r...Driven by the goal of“carbon neutrality,”the increase in use of renewable energy power systems will be inevitable in the future.Uncontrolled output power and random volatility make it difficult to balance power in real time during system operation.Therefore,energy storage is considered to be an effective way to ensure the real-time balance of system power.However,cost of energy storage is relatively expensive.As a solution,energy storage can be used to balance the system power in order to reduce system operating costs.Taking the high proportion of wind power systems as an example,the impact of the“supply side”low-carbon transformation on the economics and reliability of power system operation is explored.In order to solve the problem of power system operation configuration optimization under the background of“carbon neutrality,”this paper establishes a multi-objective programming model.展开更多
A multidisciplinary optimization was conducted to simultaneously improve the efficiency and reduce the radial force of a single-channel pump for wastewater treatment. A hybrid multi-objective evolutionary algorithm wa...A multidisciplinary optimization was conducted to simultaneously improve the efficiency and reduce the radial force of a single-channel pump for wastewater treatment. A hybrid multi-objective evolutionary algorithm was coupled with a surrogate model to optimize the geometry of the single-channel pump volute. Steady and unsteady Reynolds-averaged Navier-Stokes equations with a shear stress transport turbulence model were discretized using finite volume approximations and were then solved on tetrahedral grids to analyze the flow in the single-channel pump. The three objective functions represented the total efficiency, the sweep area of the radial force during one revolution, and the distance of the mass center of sweep area from the origin while the two design variables were related to the cross-sectional area of the internal flow of the volute. Latin hypercube sampling was employed to generate twelve design points within the design space, and response surface approximation models were constructed as surrogate models for the objectives based on the values of the objective function at the given design points. A fast non-dominated sorting genetic algorithm for local search was coupled with the surrogate models to determine the global Pareto-optimal solutions. The trade-off between the objectives was determined and was described in terms of the Pareto-optimal solutions. The results of the multi-objective optimization showed that the optimum design simultaneously improved the efficiency and reduced the radial force relative to those of the reference design.展开更多
To enhance the output torque and minimize the torque ripple of coaxial magnetic gear(CMG),a novel auxiliary flux modulator CMG with unequal magnetic poles is proposed.This design incorporates an inner rotor with an as...To enhance the output torque and minimize the torque ripple of coaxial magnetic gear(CMG),a novel auxiliary flux modulator CMG with unequal magnetic poles is proposed.This design incorporates an inner rotor with an asymmetric sector and a trapezoidal combined N-S pole structure,featuring Halbach arrays for the arrangement of permanent magnets(PMs).The outer rotor PMs adopt a Spoke-type configuration.To optimize the CMG for high output torque and low torque ripple,a sensitivity analysis is conducted to identify key size parameters that significantly influence the optimization objectives.Based on the sensitivity hierarchy of these parameters,a multi-objective optimization analysis is performed using a genetic algorithm(GA)to determine the optimal structural parameter values of the CMG.In addition,a coaxial magnetic gear(CMG)topology with 4 inner and 17 outer pole pairs is adopted,and the parametric model is established.Finally,the electromagnetic properties of the CMG are evaluated using the finite element method.The results indicate a remarkable reduction in torque ripple,specifically by 46.15%.展开更多
The operation parameters and well layout parameters of aquifer thermal energy storage(ATES)system directly influence the thermal energy storage performance.How to optimize the parameters to obtain the optimal process ...The operation parameters and well layout parameters of aquifer thermal energy storage(ATES)system directly influence the thermal energy storage performance.How to optimize the parameters to obtain the optimal process scheme is of great significance to promote thefield application of ATES.Taking the thermal storage performance of shallow aquifer as the optimization objective,this paper compares the influence degrees of key factors on thermal storage performance by means of gray correlation analysis(GCA),and prepares the optimal thermal storage scheme by using the multi-objective optimization method.The following results are obtained.First,the great difference between inlet temperature and aquifer weakens the thermal storage capacity of the system,while the thermal interference between thermal storage wells of the same type is favorable for thermal storage capacity instead.Second,aquifer thickness and well number have a greater impact on the thermal loss rate,while injection rate and well spacing have a significant influence on the thermal recoveryrate.The inlet temperature has the least effect on both of them.Third,the optimal thermal storage scheme is the single well system with inlet temperature of 25 ℃,aquifer thickness of 106.597 m and injection rate of 30 kg/s.In conclusion,the influence degrees of the key parameters on thermal loss rate and thermal recovery rate are different,so in order to improve the thermal storage performance,equilibrium optimization is necessary between both of them.In addition,the optimization scheme effectively expands the thermal storagevolume,and reduces the heat loss while improving the thermal recovery,with thermal loss rate and thermal recovery rate of the whole system optimized by 12.69%and 3.19%respectively on the basic case,which can provide a reference for the rational design of ATES system.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.52090081,52079068)the State Key Laboratory of Hydroscience and Hydraulic Engineering(Grant No.2021-KY-04).
文摘Accurate determination of rock mass parameters is essential for ensuring the accuracy of numericalsimulations. Displacement back-analysis is the most widely used method;however, the reliability of thecurrent approaches remains unsatisfactory. Therefore, in this paper, a multistage rock mass parameterback-analysis method, that considers the construction process and displacement losses is proposed andimplemented through the coupling of numerical simulation, auto-machine learning (AutoML), andmulti-objective optimization algorithms (MOOAs). First, a parametric modeling platform for mechanizedtwin tunnels is developed, generating a dataset through extensive numerical simulations. Next, theAutoML method is utilized to establish a surrogate model linking rock parameters and displacements.The tunnel construction process is divided into multiple stages, transforming the rock mass parameterback-analysis into a multi-objective optimization problem, for which multi-objective optimization algorithmsare introduced to obtain the rock mass parameters. The newly proposed rock mass parameterback-analysis method is validated in a mechanized twin tunnel project, and its accuracy and effectivenessare demonstrated. Compared with traditional single-stage back-analysis methods, the proposedmodel decreases the average absolute percentage error from 12.73% to 4.34%, significantly improving theaccuracy of the back-analysis. Moreover, although the accuracy of back analysis significantly increaseswith the number of construction stages considered, the back analysis time is acceptable. This studyprovides a new method for displacement back analysis that is efficient and accurate, thereby paving theway for precise parameter determination in numerical simulations.
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supported by the National Natural Science Foundation of China(12305185)Natural Science Foundation of Hunan Province,China(No.2023JJ50122)+1 种基金International Cooperative Research Project of the Ministry of Education,China(No.HZKY20220355)Scientific Research Foundation of the Education Department of Hunan Province,China(No.22A0307).
文摘Compared to other energy sources,nuclear reactors offer several advantages as a spacecraft power source,including compact size,high power density,and long operating life.These qualities make nuclear power an ideal energy source for future deep space exploration.A whole system model of the space nuclear reactor consisting of the reactor neutron kinetics,reactivity control,reactor heat transfer,heat exchanger,and thermoelectric converter was developed.In addition,an electrical power control system was designed based on the developed dynamic model.The GRS method was used to quantitatively calculate the uncertainty of coupling parameters of the neutronics,thermal-hydraulics,and control system for the space reactor.The Spearman correlation coefficient was applied in the sensitivity analysis of system input parameters to output parameters.The calculation results showed that the uncertainty of the output parameters caused by coupling parameters had the most considerable variation,with a relative standard deviation<2.01%.Effective delayed neutron fraction was most sensitive to electrical power.To obtain optimal control performance,the non-dominated sorting genetic algorithm method was employed to optimize the controller parameters based on the uncertainty quantification calculation.Two typical transient simulations were conducted to test the adaptive ability of the optimized controller in the uncertainty dynamic system,including 100%full power(FP)to 90%FP step load reduction transient and 5%FP/min linear variable load transient.The results showed that,considering the influence of system uncertainty,the optimized controller could improve the response speed and load following accuracy of electrical power control,in which the effectiveness and superiority have been verified.
基金supported by Qingdao Key Medical and Health Discipline ProjectThe Intramural Research Program of the Affiliated Hospital of Qingdao University,No. 4910Qingdao West Coast New Area Science and Technology Project,No. 2020-55 (all to SW)。
文摘Border-associated macrophages are located at the interface between the brain and the periphery, including the perivascular spaces, choroid plexus, and meninges. Until recently, the functions of border-associated macrophages have been poorly understood and largely overlooked. However, a recent study reported that border-associated macrophages participate in stroke-induced inflammation, although many details and the underlying mechanisms remain unclear. In this study, we performed a comprehensive single-cell analysis of mouse border-associated macrophages using sequencing data obtained from the Gene Expression Omnibus(GEO) database(GSE174574 and GSE225948). Differentially expressed genes were identified, and enrichment analysis was performed to identify the transcription profile of border-associated macrophages. CellChat analysis was conducted to determine the cell communication network of border-associated macrophages. Transcription factors were predicted using the ‘pySCENIC' tool. We found that, in response to hypoxia, borderassociated macrophages underwent dynamic transcriptional changes and participated in the regulation of inflammatory-related pathways. Notably, the tumor necrosis factor pathway was activated by border-associated macrophages following ischemic stroke. The pySCENIC analysis indicated that the activity of signal transducer and activator of transcription 3(Stat3) was obviously upregulated in stroke, suggesting that Stat3 inhibition may be a promising strategy for treating border-associated macrophages-induced neuroinflammation. Finally, we constructed an animal model to investigate the effects of border-associated macrophages depletion following a stroke. Treatment with liposomes containing clodronate significantly reduced infarct volume in the animals and improved neurological scores compared with untreated animals. Taken together, our results demonstrate comprehensive changes in border-associated macrophages following a stroke, providing a theoretical basis for targeting border-associated macrophages-induced neuroinflammation in stroke treatment.
基金supported by grants from the Tianjin Health Technology Project(Grant no.2022QN106).
文摘Background:Receptor-interacting protein kinases(RIPKs)regulate cell death,inflammation,and immune responses,yet their roles in cancer are not fully understood.This study investigates the expression,genomic alterations,and functional implications of RIPK family members across various cancers.Methods:We collected multi-omics data from The Cancer Genome Atlas and other public databases,including gene expression,copy number variation(CNV),mutation,methylation,tumor mutation burden(TMB),and microsatellite instability(MSI).Differential expression and survival analyses were performed using DESeq2 and Cox proportional hazards models.CNV and mutation data were analyzed with GISTIC2 and Mutect2,and methylation data with the ChAMP package.Correlations with TMB and MSI were assessed using Pearson coefficients,and gene set enrichment analysis was conducted with the MSigDB Hallmark gene sets.Results:RIPK family members show significant differential expression in various cancers,with RIPK1 and RIPK4 frequently altered.Survival analysis reveals heterogeneous impacts on overall survival.CNV and mutation analyses identify high alteration frequencies for RIPK2 and RIPK7,affecting gene expression.RIPK1 and RIPK7 are hypermethylated in several cancers,inversely correlating with RIPK3 expression.RIPK1,RIPK2,RIPK5,RIPK6,and RIPK7 correlate positively with TMB,while RIPK3 shows negative correlations in some cancers.MSI analysis indicates associations with DNA mismatch repair.G ene set enrichment analysis highlights immune-related pathway enrichment for RIPK1,RIPK2,RIPK3,and RIPK6,and cell proliferation and DNA repair pathways for RIPK4 and RIPK5.RIPK family members showed heterogeneous alterations across cancers:for example,RIPK7 was mutated in up to~15%of u terine c orpus e ndometrial c arcinoma and l ung s quamous c ell c arcinoma cases,and RIPK1 and RIPK7 exhibited frequent promoter hypermethylation in multiple tumor types.Several genes displayed context-dependent associations with overall survival and with TMB/MSI.Conclusion:This pan-cancer analysis of the RIPK family reveals their diverse roles and potential as biomarkers and therapeutic targets.The findings emphasize the importance of RIPK genes in tumorigenesis and suggest context-dependent functions across cancer types.Further studies are needed to explore their mechanisms in cancer development and clinical applications.
基金financially supported by the National Natural Science Foundation of China(Nos.52034002 and U2202254)the Fundamental Research Funds for the Central Universities,China(No.FRF-TT-19-001)。
文摘The sulfation and decomposition process has proven effective in selectively extracting lithium from lepidolite.It is essential to clarify the thermochemical behavior and kinetic parameters of decomposition reactions.Accordingly,comprehensive kinetic study by employing thermalgravimetric analysis at various heating rates was presented in this paper.Two main weight loss regions were observed during heating.The initial region corresponded to the dehydration of crystal water,whereas the subsequent region with overlapping peaks involved complex decomposition reactions.The overlapping peaks were separated into two individual reaction peaks and the activation energy of each peak was calculated using isoconversional kinetics methods.The activation energy of peak 1 exhibited a continual increase as the reaction conversion progressed,while that of peak 2 steadily decreased.The optimal kinetic models,identified as belonging to the random nucleation and subsequent growth category,provided valuable insights into the mechanism of the decomposition reactions.Furthermore,the adjustment factor was introduced to reconstruct the kinetic mechanism models,and the reconstructed models described the kinetic mechanism model more accurately for the decomposition reactions.This study enhanced the understanding of the thermochemical behavior and kinetic parameters of the lepidolite sulfation product decomposition reactions,further providing theoretical basis for promoting the selective extraction of lithium.
基金supported by Istanbul Technical University(Project No.45698)supported through the“Young Researchers’Career Development Project-training of doctoral students”of the Croatian Science Foundation.
文摘This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for identifying critical failure modes and their root causes,while BN introduces flexibility in probabilistic reasoning,enabling dynamic updates based on new evidence.This dual methodology overcomes the limitations of static FTA models,offering a comprehensive framework for system reliability analysis.Critical failures,including External Leakage(ELU),Failure to Start(FTS),and Overheating(OHE),were identified as key risks.By incorporating redundancy into high-risk components such as pumps and batteries,the likelihood of these failures was significantly reduced.For instance,redundant pumps reduced the probability of ELU by 31.88%,while additional batteries decreased the occurrence of FTS by 36.45%.The results underscore the practical benefits of combining FTA and BN for enhancing system reliability,particularly in maritime applications where operational safety and efficiency are critical.This research provides valuable insights for maintenance planning and highlights the importance of redundancy in critical systems,especially as the industry transitions toward more autonomous vessels.
基金Supported by the Central High Level Hospital Clinical Research Funding(No.BJ-2024-089).
文摘AIM:To explore the causal relationship between several possible behavioral factors and high myopia(HM)using multivariable Mendelian randomization(MVMR)approach and to find the mediators among them with mediation analysis.METHODS:The causal effects of several behavioral factors,including screen time,education time,time spent outdoors,and physical activity,on the risk of HM using univariable Mendelian randomization(MR)and MVMR analyses were first assessed.Genome-wide association study summary statistics of serum metabolites were also used in mediation analysis to determine the extent to which serum metabolites mediate the effects of behavioral factors on HM.RESULTS:MR analyses indicated that both increased time spent outdoors and a higher frequency of moderate physical activity significantly reduced the risk of HM.Further MVMR analysis confirmed that moderate physical activity independently contributed to a lower risk of HM.Additionally,MR analyses identified 13 serum metabolites significantly associated with HM,of which 12 were lipids and one was an amino acid derivative.Mediation analysis revealed that six lipid metabolites mediated the protective effects of moderate physical activity on HM,with the highest mediation proportion observed for 1-(1-enyl-palmitoyl)-GPC(p-16:0;30.83%).CONCLUSION:This study suggests that in addition to outdoor time,moderate physical activity habits may have an independent protective effect against HM and pointed to lipid metabolites as priority targets for the prevention due to low physical activity.These results emphasize the importance of physical activity and metabolic health in HM and underscore the need for further study of these complex associations.
基金Supported by National Natural Science Foundation of China(No.82020108006,No.81730025).
文摘AIM:To summarize publication trends in the field of strabismus over the past 30y and predict future research hotspots.METHODS:A total of 2915 English-language articles and reviews on strabismus,published between 1993 and 2022,were retrieved from the Web of Science Core Collection.Bibliometric analyses were performed using VOSviewer and CiteSpace software to explore publication trends,as well as the contributions and collaborative networks of countries/regions,authors,institutions,and journals.RESULTS:The annual number of publications on strabismus showed a consistent upward trend.The United States(USA)maintained a leading position in this research field while Republic of Korea and China emerged as rapidly advancing contributors over the last decade.The University of California,Los Angeles ranked as the most productive institution,and Jonathan M.Holmes from USA was the most productive author.Journal of AAPOS was the leading journal with the most strabismus publications,whereas the two most highly cited articles were both published in Ophthalmology.Co-occurrence analysis identified pivotal keywords and burst terms,including intermittent exotropia(IXT),acute acquired comitant esotropia(AACE),functional magnetic resonance imaging(fMRI),and surgical treatment,which were confirmed as predominant and frontier topics.CONCLUSION:This study provides a comprehensive bibliometric analysis of strabismus research,revealing the evolution of research hotspots over the past 30y and outlining several cutting-edge directions for future investigation.
基金supported by the National Natural Science Foundation of China (No.11402288)
文摘Based on improved multi-objective particle swarm optimization（MOPSO） algorithm with principal component analysis（PCA） methodology, an efficient high-dimension multiobjective optimization method is proposed, which, as the purpose of this paper, aims to improve the convergence of Pareto front in multi-objective optimization design. The mathematical efficiency,the physical reasonableness and the reliability in dealing with redundant objectives of PCA are verified by typical DTLZ5 test function and multi-objective correlation analysis of supercritical airfoil,and the proposed method is integrated into aircraft multi-disciplinary design（AMDEsign） platform, which contains aerodynamics, stealth and structure weight analysis and optimization module.Then the proposed method is used for the multi-point integrated aerodynamic optimization of a wide-body passenger aircraft, in which the redundant objectives identified by PCA are transformed to optimization constraints, and several design methods are compared. The design results illustrate that the strategy used in this paper is sufficient and multi-point design requirements of the passenger aircraft are reached. The visualization level of non-dominant Pareto set is improved by effectively reducing the dimension without losing the primary feature of the problem.
基金co-supported by the Excellent Youth Science Foundation of China(No.51722501)the China Postdoctoral Science Foundation(No.2016M600027)+1 种基金the National Natural Science Foundation of China(Nos.51575025 and 61703022)the Preliminary Exploration of Project of China(No.7131474)
文摘With the high speed, the rotor of magnetically suspended permanent magnet synchronous motor(MSPMSM) suffers great thermal stress and mechanical stress resulting from the temperature rise problem caused by rotor losses, which leads to instability and inefficiency.In this paper, the mechanical–temperature field coupling analysis is conducted to analyze the relationship between the temperature field and structure, and multi-objective optimization of a rotor is performed to improve the design reliability and efficiency. Firstly, the temperature field is calculated by the 2 D finite element model of MSPMSM and the method of applying the 2 D temperature result to the 3 D finite element model of the motor rotor equivalently is proposed. Then the thermal–structure coupling analysis is processed through mathematic method and finite element method(FEM),in which the 3 D finite element model is established precisely in a way and approaches the practical operation state further. Moreover, the impact produced by the temperature and structure on the mechanical strength is analyzed in detail. Finally, the optimization mathematical model of the motor rotor is established with Sequential Quadratic Programming-NLPQL selected in the optimization scheme. Through optimization, the strength of the components in the motor rotor increases obviously and satisfies the design requirement, which to a great extend enhances the service life of the MSPMSM rotor.
文摘A multi-objective optimization and analysis model of the sintering process based on BP neural network is presented. Genetic algorithms are combined to simplify the BP neural network, which can reduce the learning time and increase the forecasting accuracy of the network model. This model has been experimented in the sintering process, and the production cost, the energy consumption, the quality （revolving intensity）, and the output are considered at the same time. Moreover, the relation between some factors and the multi-objectives has been analyzed, and the results are consistent with the process. Different objectives are emphasized at different practical periods, and this can provide a theoretical basis for the manager.
文摘The pressurizing pipeline of hot press resonates under the excitation load,which poses a serious hidden danger to the safety of the equipment and the operator.In order to increase the natural frequency of the pressurizing pipeline,modal analysis of the pressurizing pipeline is carried out to study the mechanism of pipeline vibration and common vibration reduction measures.A method of increasing the natural frequency of the pressurizing pipeline was analyzed.The influence of pipeline clamp assembly stiffness,pipeline clamp number and pipeline clamp installation position on the mode of the pressurizing pipeline is studied.Sensitivity analysis is carried out to study the influence of the various parameters on the mode of the pressurizing pipeline.Genetic algorithm based on Pareto optimality is introduced for multi-objective optimization of pressurizing pipeline.The optimization results show that the natural frequency of the pressurizing pipeline increases by 2.4%and the displacement response is reduced by 17.7%.
基金supported by the National Natural Science Foundation of China(Grant Nos.52208380 and 51979270)the Open Research Fund of State Key Laboratory of Geomechanics and Geotechnical Engineering,Institute of Rock and Soil Mechanics,Chinese Academy of Sciences(Grant No.SKLGME021022).
文摘Real-time prediction of excavation-induced displacement of retaining pile during the deep excavation process is crucial for construction safety.This paper proposes a modified back analysis method with multi-objective optimization procedure,which enables a real-time prediction of horizontal displacement of retaining pile during construction.As opposed to the traditional stage-by-stage back analysis,time series monitoring data till the current excavation stage are utilized to form a multi-objective function.Then,the multi-objective particle swarm optimization (MOPSO) algorithm is applied for parameter identification.The optimized model parameters are immediately adopted to predict the excavation-induced pile deformation in the continuous construction stages.To achieve efficient parameter optimization and real-time prediction of system behavior,the back propagation neural network (BPNN) is established to substitute the finite element model,which is further implemented together with MOPSO for automatic operation.The proposed approach is applied in the Taihu tunnel excavation project,where the effectiveness of the method is demonstrated via the comparisons with the site monitoring data.The method is reliable with a prediction accuracy of more than 90%.Moreover,different optimization algorithms,including non-dominated sorting genetic algorithm (NSGA-II),Pareto Envelope-based Selection Algorithm II (PESA-II) and MOPSO,are compared,and their influences on the prediction accuracy at different excavation stages are studied.The results show that MOPSO has the best performance for high dimensional optimization task.
基金Projects(U1334208,51405516,51275532)supported by the National Natural Science Foundation of ChinaProjects(2015ZZTS210,2015ZZTS045)supported by the Fundamental Research Funds for the Central Universities,China
文摘In order to improve the crashworthiness of thin-walled columns, the energy absorption characteristics of three columns under quasi-static axial crushing loads were analyzed through LS-DYNA. Numerical results show that the energy absorption capability of the bitubular hexagonal columns with middle to middle(MTM) ribs is the best, followed by the bitubular hexagonal columns with corner to corner(CTC) ribs and the bitubular hexagonal columns without(NOT) ribs, respectively. Then, the MTM rib was optimized by using multi-objective particle swarm optimization algorithm. Through the analysis of the Pareto front for specific energy absorption(SEA, A_(se)) and peak crushing force(PCF, F_(pc)), it is found that there is a vertex on the Pareto front. The vertex has the design parameters of t_1=1.2 mm, t_2=1.2 mm, A_(se)=11.3729 k J/kg, F_(pc)=235.8491 kN. When the PCF is in a certain size, on the left of the vertex, the point with t_2=1.2 mm has the biggest SEA, meanwhile on the right of the vertex, the point with t_1=1.2 mm has the biggest SEA. Finally, the global sensitivity analysis was conducted to investigate the effect of two design parameters. The result is obtained that both SEA and PCF for MTM are more sensitive to t_1 rather than t_2 in the design domain.
文摘The multiple determination tasks of chemical properties are a classical problem in analytical chemistry. The major problem is concerned in to find the best subset of variables that better represents the compounds. These variables are obtained by a spectrophotometer device. This device measures hundreds of correlated variables related with physicocbemical properties and that can be used to estimate the component of interest. The problem is the selection of a subset of informative and uncorrelated variables that help the minimization of prediction error. Classical algorithms select a subset of variables for each compound considered. In this work we propose the use of the SPEA-II （strength Pareto evolutionary algorithm II）. We would like to show that the variable selection algorithm can selected just one subset used for multiple determinations using multiple linear regressions. For the case study is used wheat data obtained by NIR （near-infrared spectroscopy） spectrometry where the objective is the determination of a variable subgroup with information about E protein content （%）, test weight （Kg/HI）, WKT （wheat kernel texture） （%） and farinograph water absorption （%）. The results of traditional techniques of multivariate calibration as the SPA （successive projections algorithm）, PLS （partial least square） and mono-objective genetic algorithm are presents for comparisons. For NIR spectral analysis of protein concentration on wheat, the number of variables selected from 775 spectral variables was reduced for just 10 in the SPEA-II algorithm. The prediction error decreased from 0.2 in the classical methods to 0.09 in proposed approach, a reduction of 37%. The model using variables selected by SPEA-II had better prediction performance than classical algorithms and full-spectrum partial least-squares.
文摘Driven by the goal of“carbon neutrality,”the increase in use of renewable energy power systems will be inevitable in the future.Uncontrolled output power and random volatility make it difficult to balance power in real time during system operation.Therefore,energy storage is considered to be an effective way to ensure the real-time balance of system power.However,cost of energy storage is relatively expensive.As a solution,energy storage can be used to balance the system power in order to reduce system operating costs.Taking the high proportion of wind power systems as an example,the impact of the“supply side”low-carbon transformation on the economics and reliability of power system operation is explored.In order to solve the problem of power system operation configuration optimization under the background of“carbon neutrality,”this paper establishes a multi-objective programming model.
文摘A multidisciplinary optimization was conducted to simultaneously improve the efficiency and reduce the radial force of a single-channel pump for wastewater treatment. A hybrid multi-objective evolutionary algorithm was coupled with a surrogate model to optimize the geometry of the single-channel pump volute. Steady and unsteady Reynolds-averaged Navier-Stokes equations with a shear stress transport turbulence model were discretized using finite volume approximations and were then solved on tetrahedral grids to analyze the flow in the single-channel pump. The three objective functions represented the total efficiency, the sweep area of the radial force during one revolution, and the distance of the mass center of sweep area from the origin while the two design variables were related to the cross-sectional area of the internal flow of the volute. Latin hypercube sampling was employed to generate twelve design points within the design space, and response surface approximation models were constructed as surrogate models for the objectives based on the values of the objective function at the given design points. A fast non-dominated sorting genetic algorithm for local search was coupled with the surrogate models to determine the global Pareto-optimal solutions. The trade-off between the objectives was determined and was described in terms of the Pareto-optimal solutions. The results of the multi-objective optimization showed that the optimum design simultaneously improved the efficiency and reduced the radial force relative to those of the reference design.
文摘To enhance the output torque and minimize the torque ripple of coaxial magnetic gear(CMG),a novel auxiliary flux modulator CMG with unequal magnetic poles is proposed.This design incorporates an inner rotor with an asymmetric sector and a trapezoidal combined N-S pole structure,featuring Halbach arrays for the arrangement of permanent magnets(PMs).The outer rotor PMs adopt a Spoke-type configuration.To optimize the CMG for high output torque and low torque ripple,a sensitivity analysis is conducted to identify key size parameters that significantly influence the optimization objectives.Based on the sensitivity hierarchy of these parameters,a multi-objective optimization analysis is performed using a genetic algorithm(GA)to determine the optimal structural parameter values of the CMG.In addition,a coaxial magnetic gear(CMG)topology with 4 inner and 17 outer pole pairs is adopted,and the parametric model is established.Finally,the electromagnetic properties of the CMG are evaluated using the finite element method.The results indicate a remarkable reduction in torque ripple,specifically by 46.15%.
基金supported by the Youth Fund of the National Natural Science Foundation of China(No.52104034)the Open Project of the Key Laboratory of Shallow Geothermal Energy of the Ministry of Natural Resources(No.KLSGE202301-05)the New Cross Disciplinary Culti-vation Fund of the Southwest Jiaotong University(No.2682022KJ034,2682023ZTPY030).
文摘The operation parameters and well layout parameters of aquifer thermal energy storage(ATES)system directly influence the thermal energy storage performance.How to optimize the parameters to obtain the optimal process scheme is of great significance to promote thefield application of ATES.Taking the thermal storage performance of shallow aquifer as the optimization objective,this paper compares the influence degrees of key factors on thermal storage performance by means of gray correlation analysis(GCA),and prepares the optimal thermal storage scheme by using the multi-objective optimization method.The following results are obtained.First,the great difference between inlet temperature and aquifer weakens the thermal storage capacity of the system,while the thermal interference between thermal storage wells of the same type is favorable for thermal storage capacity instead.Second,aquifer thickness and well number have a greater impact on the thermal loss rate,while injection rate and well spacing have a significant influence on the thermal recoveryrate.The inlet temperature has the least effect on both of them.Third,the optimal thermal storage scheme is the single well system with inlet temperature of 25 ℃,aquifer thickness of 106.597 m and injection rate of 30 kg/s.In conclusion,the influence degrees of the key parameters on thermal loss rate and thermal recovery rate are different,so in order to improve the thermal storage performance,equilibrium optimization is necessary between both of them.In addition,the optimization scheme effectively expands the thermal storagevolume,and reduces the heat loss while improving the thermal recovery,with thermal loss rate and thermal recovery rate of the whole system optimized by 12.69%and 3.19%respectively on the basic case,which can provide a reference for the rational design of ATES system.
