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
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
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
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
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
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
In April of 2006, a base population of the noble scallop Chlamys nobilis was established by collecting parental breeders from the stocks in Wushi, Zhanjiang. In December of 2006, 200 individuals were randomly sampled ...In April of 2006, a base population of the noble scallop Chlamys nobilis was established by collecting parental breeders from the stocks in Wushi, Zhanjiang. In December of 2006, 200 individuals were randomly sampled from the base population and subjected for correlation and path coefficient analysis. It was found that there were statistically significant phenotypic correlations among the traits （P 〈 0.01）. Total weight was significantly and positively correlated with the shell length （r = 0.934 3）, shell height （r = 0.895 9）, shell width （r = 0.899 1 ）, muscle weight （r = 0.882 0） and shell weight （r = 0.937 9）, respectively. Shell length, shell width, muscle weight, shell height and shell weight had positive and direct effects on the total weight, with values of 0.397 1, 0.321 9, 0.172 1, 0.089 6 and 0.066 9, respectively. Shell length, shell width and muscle weight had higher direct effects on the total weight than shell height and shell weight. A combined evaluation of correlation, direct effects and indirect effects showed that direct selection for shell length, shell width, muscle weight, shell height and shell weight would be effective to improving the total weight. It was concluded that these traits could be regarded as the selection criteria in breeding programs of the species.展开更多
[Objective] This study was tween yield-related traits and yield of conducted to understand the relationship be- Yunmai 52 which is a high-quality high-yield multi-resistant new wheat variety, and make contribution of ...[Objective] This study was tween yield-related traits and yield of conducted to understand the relationship be- Yunmai 52 which is a high-quality high-yield multi-resistant new wheat variety, and make contribution of yield-related traits to the yield of Yunmai 52 clear. [Method] Wheat variety regional trial data in Yunnan Province in 2005-2007 were subjected to correlation analysis and path analysis in the paper. [Result] Correlationanalysis showed that the yield of Yunmai 52 was in- very significant positive correlation with spikelet number per ear, maximum tiller number and grains per ear （r=0.726^＊＊, 0.717^＊＊ and 0.695^＊＊, respectively）, in signif- icant positive correlation with 1 000-grain weight （r=0.491^＊）, but in significant nega- tive correlation with sterile spikelet number per ear, and in non-significant correlation with basic seedlings, effective ears and percentage of ear bearing tillers. Partial correlation analysis showed that the yield of Yunmai 52 was in very significant posi- tive correlation with spikelet number per ear （r=0.711^＊＊）, significant positive correla- tion with 1 000-grain weight （r=0.641 =）, but in non-significant correlation with other 6 traits. Path analysis showed that spikelet number per ear （P=-0.595）, maximum tiller number （P=0.462） and t 000-grain weight （P=0.263） had more contribution to yield of Yunmai 52. [Conclusion] Therefore, in extension and application of Yunmal 52 that is a high-quality high-yield multi-resistant new wheat variety, supply of fertilizer and water should be increased in tillering stage and jointing stage, to ensure its characteristics of high tilledng ability and large ear, as well as high 1 000-grain weight, and coordinated development of other yield-related traits is beneficial to im- provement of yield of Yunmai 52.展开更多
[Objective]The experiment aimed to study the effects of meteorological factors under different weather conditions on soil respiration. [ Method] The path analysis was used to analyze meteorological factors which influ...[Objective]The experiment aimed to study the effects of meteorological factors under different weather conditions on soil respiration. [ Method] The path analysis was used to analyze meteorological factors which influenced soil respiration of wheat field under different weather condition and at jointing stage. [ Result] In sunny day, the correlations between ground temperature at 5 cm, solar radiation, air relative humidity, air temperature and soil respiration were all at significant level while solar radiation and ground temperature at 5 cm were the major factors which influenced soil respiration. In cloudy day, solar radiation was a major factor which influenced soil respiration.[ Conclusion] The soil respiration and surplus path coefficient in sunny day were all higher than these in cloudy day, which demonstrated that except influenced by ground temperature, air temperature, solar radiation and air relative humidity, the soil respiration was also influenced by other factors especially biological factor.展开更多
During path planning, it is necessary to satisfy the requirements of multiple objectives. Multi-objective synthesis is based on the need of flight mission and subjectivity inclination of decision-maker. The decision-m...During path planning, it is necessary to satisfy the requirements of multiple objectives. Multi-objective synthesis is based on the need of flight mission and subjectivity inclination of decision-maker. The decision-maker, however, has illegibility for under- standing the requirements of multiple objectives and the subjectivity inclination. It is important to develop a reasonable cost performance index for describing the illegibility of the decision-maker in multi-objective path planning. Based on Voronoi dia- gram method for the path planning, this paper studies the synthesis method of the multi-objective cost performance index. Ac- cording to the application of the cost performance index to the path planning based on Voronoi diagram method, this paper ana- lyzes the cost performance index which has been referred to at present. The analysis shows the insufficiency of the cost per- formance index at present, i.e., it is difficult to synthesize sub-objective flmctions because of the great disparity of the sub-objective fimctions. Thus, a new approach is developed to optimize the cost performance index with the multi-objective fuzzy optimization strategy, and an improved performance index is established, which could coordinate the weight conflict of the sub-objective functions. Finally, the experimental result shows the effectiveness of the proposed approach.展开更多
Runoff formation is a complex meteorological-hydrological process impacted by many factors,especially in the inland river basin.Based on the data of daily mean air temperature,precipitation and runoff during the perio...Runoff formation is a complex meteorological-hydrological process impacted by many factors,especially in the inland river basin.Based on the data of daily mean air temperature,precipitation and runoff during the period of 1958-2007 in the Kaidu River watershed,this paper analyzed the changes in air temperature,precipitation and runoff and revealed the direct and indirect impacts of daily air temperature and precipitation on daily runoff by path analysis.The results showed that mean temperature time series of the annual,summer and autumn had a significant fluctuant increase during the last 50 years（P 0.05）.Only winter precipitation increased significantly（P 0.05） with a rate of 1.337 mm/10a.The annual and winter runoff depthes in the last 50 years significantly increased with the rates of 7.11 mm/10a and 1.85 mm/10a,respectively.The driving function of both daily temperature and precipitation on daily runoff in annual and seasonal levels is significant in the Kaidu River watershed by correlation analysis.The result of path analysis showed that the positive effect of daily air temperature on daily runoff depth is much higher than that of daily precipitation in annual,spring,autumn and winter,however,the trend is opposite in summer.展开更多
Improvement of yield in rice(Oryza sativa L.) is vital for ensuring food security in China. Both rice breeders and growers need an improved understanding of the relationship between yield and yield-related traits. New...Improvement of yield in rice(Oryza sativa L.) is vital for ensuring food security in China. Both rice breeders and growers need an improved understanding of the relationship between yield and yield-related traits. New indica cultivars(53 in 2007 and 48 in 2008) were grown in Taoyuan,Yunnan province, to identify important components contributing to yield. Additionally, two standard indica rice cultivars with similar yield potentials, II You 107(a large-panicle type) and Xieyou 107(a heavy-panicle type), were planted in Taoyuan, Yunnan province and Nanjing,Jiangsu province, from 2006 to 2008 to evaluate the stability of yield and yield-related attributes.Growth duration(GD), leaf area index(LAI), panicles per m2(PN), and spikelets per m2(SM) were significantly and positively correlated with grain yield(GY) over all years. Sequential path analysis identified PN and panicle weight(PW) as important first-order traits that influenced grain yield. All direct effects were significant, as indicated by bootstrap analysis. Yield potential varied greatly across locations but not across years. Plant height(PH), days from heading to maturity(HM), and grain weight(GW) were stable traits that showed little variation across sites or years, whereas GD(mainly the pre-heading period, PHP) and PN varied significantly across locations. To achieve a yield of 15 t ha-1, a cultivar should have a PH of 110–125 cm, a long GD with HM of approximately 40 days, a PN of 300–400 m-2, and a GW of 29–31 mg.展开更多
Spring snowmelt peak flow （SSPF） can cause serious damage. Precipitation as rainfall directly contributes to the SSPF and influences the characteristics of the SSPF, while temperature indirectly impacts the SSPF by ...Spring snowmelt peak flow （SSPF） can cause serious damage. Precipitation as rainfall directly contributes to the SSPF and influences the characteristics of the SSPF, while temperature indirectly impacts the SSPF by shaping snowmelt rate and determining the soil frozen state which partitions snowmelt water into surface runoff and soil infiltration water in spring. It is necessary to identify the important and significant paths of climatic factors influencing the SSPF and provide estimates of the magnitude and significance of hypothesized causal connections between climatic factors and the SSPF. This study used path analysis with a selection of five factors - the antecedent precipitation index （API）, spring precipitation （SP）, winter precipitation as snowfall （WS）, 〈0℃ temperature accumulation in winter （[ATNI）, and average 〉0℃temperature accumulation in spring （AT） - to analyze their influences on the SSPF in the Kaidu River in Xinjiang, China. The results show that {ATN}, AT and WS have a significant correlation with the SSPF, while API and SP do not show a significant correlation. AT and WS directly influence the SSPF, while as the influence of[ATN] on SSPF is indirect through WS and AT. The indirect influence of [ATN[ on SSPF through WS accounts for 69% of the total influence of [ATN] on SSPF. Compared to the multiple linear regression method, path analysis provides additional valuable information, including influencing paths from independent variables to the dependent variable as well as direct and indirect impacts of external variables on the internal variable. This information can help improve the description of snow melt and spring runoff in hydrologic models as well as the planning and management of water resources.展开更多
Using correlation and path analysis, the genetic correlation between weight traits and morphological traits was determined in the marine gastropod Glossaulax reiniana. A total of 100 G. reiniana individuals from a wil...Using correlation and path analysis, the genetic correlation between weight traits and morphological traits was determined in the marine gastropod Glossaulax reiniana. A total of 100 G. reiniana individuals from a wild population were used. Shell width （X1）, shell height （X2）, umbo-callus height （X3）, body width （X4）, operculum length （X5）, operculum width （X6）, body weight （Y1） and soft-tissue weight （Y2） were measured, and the correlation coefficient matrix calculated. Morphological traits were used as independent variables and weight traits as dependent variables for path coefficient analysis. Path coefficients, correlation indices and determination coefficients were also determined. Results indicate that the correlation coefficients associated with each morphological and weight trait were all highly significant （P〈0.01）. After deleting redundant independent variables, the following optimum multiple regression equations were obtained using stepwise multiple regression analysis： Y1=-29.317＋0.362X2＋0.349X4＋ 1.190）（5 for body weight; and Y2=-17.292＋0.166X1＋0.171X2＋0.703X5, for soft-tissue weight. Operculum height had the highest positive direct correlation with both body weight and soft-tissue weight, which was in accordance with the test results obtained from determinate coefficient analysis. The indication of high genetic correlations between weight traits and morphological traits will provide valuable information for G. reiniana breeding programs.展开更多
The 6-DOF manipulator provides a new option for traditional shipbuilding for its advantages of vast working space,low power consumption,and excellent flexibility.However,the rotation of the end effector along the tool...The 6-DOF manipulator provides a new option for traditional shipbuilding for its advantages of vast working space,low power consumption,and excellent flexibility.However,the rotation of the end effector along the tool axis is functionally redundant when using a robotic arm for five-axis machining.In the process of ship construction,the performance of the parts’protective coating needs to bemachined tomeet the Performance Standard of Protective Coatings(PSPC).The arbitrary redundancy configuration in path planning will result in drastic fluctuations in the robot joint angle,greatly reducing machining quality and efficiency.There have been some studies on singleobjective optimization of redundant variables,However,the quality and efficiency of milling are not affected by a single factor,it is usually influenced by several factors,such as the manipulator stiffness,the joint motion smoothness,and the energy consumption.To solve this problem,this paper proposed a new path optimization method for the industrial robot when it is used for five-axis machining.The path smoothness performance index and the energy consumption index are established based on the joint acceleration and the joint velocity,respectively.The path planning issue is formulated as a constrained multi-objective optimization problem by taking into account the constraints of joint limits and singularity avoidance.Then,the path is split into multiple segments for optimization to avoid the slow convergence rate caused by the high dimension.An algorithm combining the non-dominated sorting genetic algorithm(NSGA-II)and the differential evolution(DE)algorithm is employed to solve the above optimization problem.The simulations validate the effectiveness of the algorithm,showing the improvement of smoothness and the reduction of energy consumption.展开更多
Unlike the shortest path problem that has only one optimal solution and can be solved in polynomial time, the muhi-objective shortest path problem （ MSPP ） has a set of pareto optimal solutions and cannot be solved ...Unlike the shortest path problem that has only one optimal solution and can be solved in polynomial time, the muhi-objective shortest path problem （ MSPP ） has a set of pareto optimal solutions and cannot be solved in polynomial time. The present algorithms focused mainly on how to obtain a precisely pareto optimal solution for MSPP resulting in a long time to obtain multiple pareto optimal solutions with them. In order to obtain a set of satisfied solutions for MSPP in reasonable time to meet the demand of a decision maker, a genetic algo- rithm MSPP-GA is presented to solve the MSPP with typically competing objectives, cost and time, in this pa- per. The encoding of the solution and the operators such as crossover, mutation and selection are developed. The algorithm introduced pareto domination tournament and sharing based selection operator, which can not only directly search the pareto optimal frontier but also maintain the diversity of populations in the process of evolutionary computation. Experimental results show that MSPP-GA can obtain most efficient solutions distributed all along the pareto frontier in less time than an exact algorithm. The algorithm proposed in this paper provides a new and effective method of how to obtain the set of pareto optimal solutions for other multiple objective optimization problems in a short time.展开更多
Correlation and path coefficient analyses were conducted for 10 characteristics of 24 pure lines of flue-cured tobacco such as plant height, knot distance, leaf number, the central leaf length and width, ratio of the ...Correlation and path coefficient analyses were conducted for 10 characteristics of 24 pure lines of flue-cured tobacco such as plant height, knot distance, leaf number, the central leaf length and width, ratio of the length to width, stem girth, dates of budding, leaf yield and ratio of the prime-medium tobacco. The leaf number and the central leaf length showed a positive or a strong positive correlation with the yield per plant. And the leaf number and leaf yield per plant showed a strong positive correlation with the ratio of prime-medium tobacco. The results showed that the leaf yield per plant among these characteristics played a major role in determining the ratio of prime-medium tobacco while the others were less related with the ratio. Square sum of deviation method cluster analyses showed that 24 pure lines of flue-cured tobacco were clustered into two groups. Of the pure lines, Line T1706 and Line T1245 had a far relationship with all other lines, and also had a heterosis when crossed with the other lines. Lines Guangdonghuang 1 and R72（3）B-2-1 were closely related.展开更多
The objective of this study was to determine the relationship between PM10 and PM2.5 levels as related to meteorological conditions and traffic flow using both a linear regression analysis and a path analysis. The Par...The objective of this study was to determine the relationship between PM10 and PM2.5 levels as related to meteorological conditions and traffic flow using both a linear regression analysis and a path analysis. The Particulate matter（PM） samples were collected from Sukhumvit road, Bangkok, Thailand, at both open（104 samples） and covered（92 samples）areas along the road. Fifteen percent of all samples were separated before the statistical models were run and used for model validation. The results from the path analysis were more elaborate than those from the linear regression, thus indicating that meteorological conditions had a direct effect on the particulate levels and that the effects of traffic flow were more variable in open areas. The model also indicated that meteorological conditions had an indirect effect and that traffic flow had a direct effect on particulate levels in covered areas. The model validation results indicated that for open areas, the R^2 values were not very different between the path analysis and the linear regression model, but that the path analysis was more accurate than the linear regression model at very low PM concentrations. At high PM concentrations, the path analysis model also had a better fit than did the linear regression, so the predictions from the path analysis model were more accurate than those from the linear regression.展开更多
Operational transfer path analysis(OTPA)is an advanced vibration and noise transfer path identification and contribution evaluation method.However,the application of OTPA to rail transit vehicles considers only the ex...Operational transfer path analysis(OTPA)is an advanced vibration and noise transfer path identification and contribution evaluation method.However,the application of OTPA to rail transit vehicles considers only the excitation amplitude and ignores the influence of the excitation phase.This study considers the influence of the excitation amplitude and phase,and analyzes the contribution of the secondary suspension path to the floor vibration when the metro vehicle runs at 60 km/h,using an analysis based on the OTPA method.The results show that the vertical direction of the anti-rolling torsion bar area provides the maximum contribution to the floor vibration,with a contribution of 22.1%,followed by the longitudinal vibration of the air spring area,with a contribution of 17.1%.Based on the contribution analysis,a transfer path optimization scheme is proposed,which may provide a reference for the optimization of the transfer path of metro vehicles in the future.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.
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.
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.
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.
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.
文摘In April of 2006, a base population of the noble scallop Chlamys nobilis was established by collecting parental breeders from the stocks in Wushi, Zhanjiang. In December of 2006, 200 individuals were randomly sampled from the base population and subjected for correlation and path coefficient analysis. It was found that there were statistically significant phenotypic correlations among the traits （P 〈 0.01）. Total weight was significantly and positively correlated with the shell length （r = 0.934 3）, shell height （r = 0.895 9）, shell width （r = 0.899 1 ）, muscle weight （r = 0.882 0） and shell weight （r = 0.937 9）, respectively. Shell length, shell width, muscle weight, shell height and shell weight had positive and direct effects on the total weight, with values of 0.397 1, 0.321 9, 0.172 1, 0.089 6 and 0.066 9, respectively. Shell length, shell width and muscle weight had higher direct effects on the total weight than shell height and shell weight. A combined evaluation of correlation, direct effects and indirect effects showed that direct selection for shell length, shell width, muscle weight, shell height and shell weight would be effective to improving the total weight. It was concluded that these traits could be regarded as the selection criteria in breeding programs of the species.
基金Supported by National key R&D Projects(2016YFD0101603)National Planning Project Co-supported by Yunnan Province(2014GA016)Science&Technology Specific Project for Benefiting People in China(2014RA056)~~
文摘[Objective] This study was tween yield-related traits and yield of conducted to understand the relationship be- Yunmai 52 which is a high-quality high-yield multi-resistant new wheat variety, and make contribution of yield-related traits to the yield of Yunmai 52 clear. [Method] Wheat variety regional trial data in Yunnan Province in 2005-2007 were subjected to correlation analysis and path analysis in the paper. [Result] Correlationanalysis showed that the yield of Yunmai 52 was in- very significant positive correlation with spikelet number per ear, maximum tiller number and grains per ear （r=0.726^＊＊, 0.717^＊＊ and 0.695^＊＊, respectively）, in signif- icant positive correlation with 1 000-grain weight （r=0.491^＊）, but in significant nega- tive correlation with sterile spikelet number per ear, and in non-significant correlation with basic seedlings, effective ears and percentage of ear bearing tillers. Partial correlation analysis showed that the yield of Yunmai 52 was in very significant posi- tive correlation with spikelet number per ear （r=0.711^＊＊）, significant positive correla- tion with 1 000-grain weight （r=0.641 =）, but in non-significant correlation with other 6 traits. Path analysis showed that spikelet number per ear （P=-0.595）, maximum tiller number （P=0.462） and t 000-grain weight （P=0.263） had more contribution to yield of Yunmai 52. [Conclusion] Therefore, in extension and application of Yunmal 52 that is a high-quality high-yield multi-resistant new wheat variety, supply of fertilizer and water should be increased in tillering stage and jointing stage, to ensure its characteristics of high tilledng ability and large ear, as well as high 1 000-grain weight, and coordinated development of other yield-related traits is beneficial to im- provement of yield of Yunmai 52.
基金Supported by the Scientific Research Foundation of Nanjing Universityof Information Science and Technology(80124)~~
文摘[Objective]The experiment aimed to study the effects of meteorological factors under different weather conditions on soil respiration. [ Method] The path analysis was used to analyze meteorological factors which influenced soil respiration of wheat field under different weather condition and at jointing stage. [ Result] In sunny day, the correlations between ground temperature at 5 cm, solar radiation, air relative humidity, air temperature and soil respiration were all at significant level while solar radiation and ground temperature at 5 cm were the major factors which influenced soil respiration. In cloudy day, solar radiation was a major factor which influenced soil respiration.[ Conclusion] The soil respiration and surplus path coefficient in sunny day were all higher than these in cloudy day, which demonstrated that except influenced by ground temperature, air temperature, solar radiation and air relative humidity, the soil respiration was also influenced by other factors especially biological factor.
文摘During path planning, it is necessary to satisfy the requirements of multiple objectives. Multi-objective synthesis is based on the need of flight mission and subjectivity inclination of decision-maker. The decision-maker, however, has illegibility for under- standing the requirements of multiple objectives and the subjectivity inclination. It is important to develop a reasonable cost performance index for describing the illegibility of the decision-maker in multi-objective path planning. Based on Voronoi dia- gram method for the path planning, this paper studies the synthesis method of the multi-objective cost performance index. Ac- cording to the application of the cost performance index to the path planning based on Voronoi diagram method, this paper ana- lyzes the cost performance index which has been referred to at present. The analysis shows the insufficiency of the cost per- formance index at present, i.e., it is difficult to synthesize sub-objective flmctions because of the great disparity of the sub-objective fimctions. Thus, a new approach is developed to optimize the cost performance index with the multi-objective fuzzy optimization strategy, and an improved performance index is established, which could coordinate the weight conflict of the sub-objective functions. Finally, the experimental result shows the effectiveness of the proposed approach.
基金supported by the National Natural Sciences Foundation of China (40871027)the Initial Project of State Key Basic R & D Program of China (2009CB426309)the Knowledge Innovation Project of Chinese Academy of Sciences (KZCX2-YW-334)
文摘Runoff formation is a complex meteorological-hydrological process impacted by many factors,especially in the inland river basin.Based on the data of daily mean air temperature,precipitation and runoff during the period of 1958-2007 in the Kaidu River watershed,this paper analyzed the changes in air temperature,precipitation and runoff and revealed the direct and indirect impacts of daily air temperature and precipitation on daily runoff by path analysis.The results showed that mean temperature time series of the annual,summer and autumn had a significant fluctuant increase during the last 50 years（P 0.05）.Only winter precipitation increased significantly（P 0.05） with a rate of 1.337 mm/10a.The annual and winter runoff depthes in the last 50 years significantly increased with the rates of 7.11 mm/10a and 1.85 mm/10a,respectively.The driving function of both daily temperature and precipitation on daily runoff in annual and seasonal levels is significant in the Kaidu River watershed by correlation analysis.The result of path analysis showed that the positive effect of daily air temperature on daily runoff depth is much higher than that of daily precipitation in annual,spring,autumn and winter,however,the trend is opposite in summer.
基金supported by the National Key Technology R&D Program of China (2011BAD16B14, 2012BAD20B05, 2012BAD04B08, and 2013BAD20B05)
文摘Improvement of yield in rice(Oryza sativa L.) is vital for ensuring food security in China. Both rice breeders and growers need an improved understanding of the relationship between yield and yield-related traits. New indica cultivars(53 in 2007 and 48 in 2008) were grown in Taoyuan,Yunnan province, to identify important components contributing to yield. Additionally, two standard indica rice cultivars with similar yield potentials, II You 107(a large-panicle type) and Xieyou 107(a heavy-panicle type), were planted in Taoyuan, Yunnan province and Nanjing,Jiangsu province, from 2006 to 2008 to evaluate the stability of yield and yield-related attributes.Growth duration(GD), leaf area index(LAI), panicles per m2(PN), and spikelets per m2(SM) were significantly and positively correlated with grain yield(GY) over all years. Sequential path analysis identified PN and panicle weight(PW) as important first-order traits that influenced grain yield. All direct effects were significant, as indicated by bootstrap analysis. Yield potential varied greatly across locations but not across years. Plant height(PH), days from heading to maturity(HM), and grain weight(GW) were stable traits that showed little variation across sites or years, whereas GD(mainly the pre-heading period, PHP) and PN varied significantly across locations. To achieve a yield of 15 t ha-1, a cultivar should have a PH of 110–125 cm, a long GD with HM of approximately 40 days, a PN of 300–400 m-2, and a GW of 29–31 mg.
基金financially supported by the Project of State Key Basic R & D Program of China (973 Program, Grant No. 2010CB951002)the key deployment project of Chinese Academy of Sciences (Grant No. KZZD-EW-12-2)Chinese Academy of Sciences Visiting Professorship for Senior International Scientists (Grant No. 2011T2Z40)
文摘Spring snowmelt peak flow （SSPF） can cause serious damage. Precipitation as rainfall directly contributes to the SSPF and influences the characteristics of the SSPF, while temperature indirectly impacts the SSPF by shaping snowmelt rate and determining the soil frozen state which partitions snowmelt water into surface runoff and soil infiltration water in spring. It is necessary to identify the important and significant paths of climatic factors influencing the SSPF and provide estimates of the magnitude and significance of hypothesized causal connections between climatic factors and the SSPF. This study used path analysis with a selection of five factors - the antecedent precipitation index （API）, spring precipitation （SP）, winter precipitation as snowfall （WS）, 〈0℃ temperature accumulation in winter （[ATNI）, and average 〉0℃temperature accumulation in spring （AT） - to analyze their influences on the SSPF in the Kaidu River in Xinjiang, China. The results show that {ATN}, AT and WS have a significant correlation with the SSPF, while API and SP do not show a significant correlation. AT and WS directly influence the SSPF, while as the influence of[ATN] on SSPF is indirect through WS and AT. The indirect influence of [ATN[ on SSPF through WS accounts for 69% of the total influence of [ATN] on SSPF. Compared to the multiple linear regression method, path analysis provides additional valuable information, including influencing paths from independent variables to the dependent variable as well as direct and indirect impacts of external variables on the internal variable. This information can help improve the description of snow melt and spring runoff in hydrologic models as well as the planning and management of water resources.
基金Supported by the Modern Agro-Industry Technology Research System(No.CARS-48)
文摘Using correlation and path analysis, the genetic correlation between weight traits and morphological traits was determined in the marine gastropod Glossaulax reiniana. A total of 100 G. reiniana individuals from a wild population were used. Shell width （X1）, shell height （X2）, umbo-callus height （X3）, body width （X4）, operculum length （X5）, operculum width （X6）, body weight （Y1） and soft-tissue weight （Y2） were measured, and the correlation coefficient matrix calculated. Morphological traits were used as independent variables and weight traits as dependent variables for path coefficient analysis. Path coefficients, correlation indices and determination coefficients were also determined. Results indicate that the correlation coefficients associated with each morphological and weight trait were all highly significant （P〈0.01）. After deleting redundant independent variables, the following optimum multiple regression equations were obtained using stepwise multiple regression analysis： Y1=-29.317＋0.362X2＋0.349X4＋ 1.190）（5 for body weight; and Y2=-17.292＋0.166X1＋0.171X2＋0.703X5, for soft-tissue weight. Operculum height had the highest positive direct correlation with both body weight and soft-tissue weight, which was in accordance with the test results obtained from determinate coefficient analysis. The indication of high genetic correlations between weight traits and morphological traits will provide valuable information for G. reiniana breeding programs.
文摘The 6-DOF manipulator provides a new option for traditional shipbuilding for its advantages of vast working space,low power consumption,and excellent flexibility.However,the rotation of the end effector along the tool axis is functionally redundant when using a robotic arm for five-axis machining.In the process of ship construction,the performance of the parts’protective coating needs to bemachined tomeet the Performance Standard of Protective Coatings(PSPC).The arbitrary redundancy configuration in path planning will result in drastic fluctuations in the robot joint angle,greatly reducing machining quality and efficiency.There have been some studies on singleobjective optimization of redundant variables,However,the quality and efficiency of milling are not affected by a single factor,it is usually influenced by several factors,such as the manipulator stiffness,the joint motion smoothness,and the energy consumption.To solve this problem,this paper proposed a new path optimization method for the industrial robot when it is used for five-axis machining.The path smoothness performance index and the energy consumption index are established based on the joint acceleration and the joint velocity,respectively.The path planning issue is formulated as a constrained multi-objective optimization problem by taking into account the constraints of joint limits and singularity avoidance.Then,the path is split into multiple segments for optimization to avoid the slow convergence rate caused by the high dimension.An algorithm combining the non-dominated sorting genetic algorithm(NSGA-II)and the differential evolution(DE)algorithm is employed to solve the above optimization problem.The simulations validate the effectiveness of the algorithm,showing the improvement of smoothness and the reduction of energy consumption.
文摘Unlike the shortest path problem that has only one optimal solution and can be solved in polynomial time, the muhi-objective shortest path problem （ MSPP ） has a set of pareto optimal solutions and cannot be solved in polynomial time. The present algorithms focused mainly on how to obtain a precisely pareto optimal solution for MSPP resulting in a long time to obtain multiple pareto optimal solutions with them. In order to obtain a set of satisfied solutions for MSPP in reasonable time to meet the demand of a decision maker, a genetic algo- rithm MSPP-GA is presented to solve the MSPP with typically competing objectives, cost and time, in this pa- per. The encoding of the solution and the operators such as crossover, mutation and selection are developed. The algorithm introduced pareto domination tournament and sharing based selection operator, which can not only directly search the pareto optimal frontier but also maintain the diversity of populations in the process of evolutionary computation. Experimental results show that MSPP-GA can obtain most efficient solutions distributed all along the pareto frontier in less time than an exact algorithm. The algorithm proposed in this paper provides a new and effective method of how to obtain the set of pareto optimal solutions for other multiple objective optimization problems in a short time.
基金Supported by Platform Construction for Germplasm Resources of China Tobacco (2007, 152)
文摘Correlation and path coefficient analyses were conducted for 10 characteristics of 24 pure lines of flue-cured tobacco such as plant height, knot distance, leaf number, the central leaf length and width, ratio of the length to width, stem girth, dates of budding, leaf yield and ratio of the prime-medium tobacco. The leaf number and the central leaf length showed a positive or a strong positive correlation with the yield per plant. And the leaf number and leaf yield per plant showed a strong positive correlation with the ratio of prime-medium tobacco. The results showed that the leaf yield per plant among these characteristics played a major role in determining the ratio of prime-medium tobacco while the others were less related with the ratio. Square sum of deviation method cluster analyses showed that 24 pure lines of flue-cured tobacco were clustered into two groups. Of the pure lines, Line T1706 and Line T1245 had a far relationship with all other lines, and also had a heterosis when crossed with the other lines. Lines Guangdonghuang 1 and R72（3）B-2-1 were closely related.
文摘The objective of this study was to determine the relationship between PM10 and PM2.5 levels as related to meteorological conditions and traffic flow using both a linear regression analysis and a path analysis. The Particulate matter（PM） samples were collected from Sukhumvit road, Bangkok, Thailand, at both open（104 samples） and covered（92 samples）areas along the road. Fifteen percent of all samples were separated before the statistical models were run and used for model validation. The results from the path analysis were more elaborate than those from the linear regression, thus indicating that meteorological conditions had a direct effect on the particulate levels and that the effects of traffic flow were more variable in open areas. The model also indicated that meteorological conditions had an indirect effect and that traffic flow had a direct effect on particulate levels in covered areas. The model validation results indicated that for open areas, the R^2 values were not very different between the path analysis and the linear regression model, but that the path analysis was more accurate than the linear regression model at very low PM concentrations. At high PM concentrations, the path analysis model also had a better fit than did the linear regression, so the predictions from the path analysis model were more accurate than those from the linear regression.
基金Supported by National Natural Science Foundation of China(Grant Nos.U1934203,U1734201)Sichuan Science and Technology Program(Grant No.2020YJ0254)Fundamental Research Funds for the State Key Laboratory of Traction Power(Grant No.2019-Q02).
文摘Operational transfer path analysis(OTPA)is an advanced vibration and noise transfer path identification and contribution evaluation method.However,the application of OTPA to rail transit vehicles considers only the excitation amplitude and ignores the influence of the excitation phase.This study considers the influence of the excitation amplitude and phase,and analyzes the contribution of the secondary suspension path to the floor vibration when the metro vehicle runs at 60 km/h,using an analysis based on the OTPA method.The results show that the vertical direction of the anti-rolling torsion bar area provides the maximum contribution to the floor vibration,with a contribution of 22.1%,followed by the longitudinal vibration of the air spring area,with a contribution of 17.1%.Based on the contribution analysis,a transfer path optimization scheme is proposed,which may provide a reference for the optimization of the transfer path of metro vehicles in the future.
