The key parameters that characterize the morphological quality of multi-layer and multi-pass metal laser deposited parts are the surface roughness and the error between the actual printing height and the theoretical m...The key parameters that characterize the morphological quality of multi-layer and multi-pass metal laser deposited parts are the surface roughness and the error between the actual printing height and the theoretical model height.The Taguchi method was employed to establish the correlations between process parameter combinations and multi-objective characterization of metal deposition morphology(height error and roughness).Results show that using the signal-to-noise ratio and grey relational analysis,the optimal parameter combination for multi-layer and multi-pass deposition is determined as follows:laser power of 800 W,powder feeding rate of 0.3 r/min,step distance of 1.6 mm,and scanning speed of 20 mm/s.Subsequently,a Genetic Bayesian-back propagation(GB-BP)network is constructed to predict multi-objective responses.Compared with the traditional back propagation network,the GB-back propagation network improves the prediction accuracy of height error and surface roughness by 43.14%and 71.43%,respectively.This network can accurately predict the multi-objective characterization of morphological quality of multi-layer and multi-pass metal deposited parts.展开更多
When assessing seismic liquefaction potential with data-driven models,addressing the uncertainties of establishing models,interpreting cone penetration tests(CPT)data and decision threshold is crucial for avoiding bia...When assessing seismic liquefaction potential with data-driven models,addressing the uncertainties of establishing models,interpreting cone penetration tests(CPT)data and decision threshold is crucial for avoiding biased data selection,ameliorating overconfident models,and being flexible to varying practical objectives,especially when the training and testing data are not identically distributed.A workflow characterized by leveraging Bayesian methodology was proposed to address these issues.Employing a Multi-Layer Perceptron(MLP)as the foundational model,this approach was benchmarked against empirical methods and advanced algorithms for its efficacy in simplicity,accuracy,and resistance to overfitting.The analysis revealed that,while MLP models optimized via maximum a posteriori algorithm suffices for straightforward scenarios,Bayesian neural networks showed great potential for preventing overfitting.Additionally,integrating decision thresholds through various evaluative principles offers insights for challenging decisions.Two case studies demonstrate the framework's capacity for nuanced interpretation of in situ data,employing a model committee for a detailed evaluation of liquefaction potential via Monte Carlo simulations and basic statistics.Overall,the proposed step-by-step workflow for analyzing seismic liquefaction incorporates multifold testing and real-world data validation,showing improved robustness against overfitting and greater versatility in addressing practical challenges.This research contributes to the seismic liquefaction assessment field by providing a structured,adaptable methodology for accurate and reliable analysis.展开更多
Transportation structures such as composite pavements and railway foundations typically consist of multi-layered media designed to withstand high bearing capacity.A theoretical understanding of load transfer mechanism...Transportation structures such as composite pavements and railway foundations typically consist of multi-layered media designed to withstand high bearing capacity.A theoretical understanding of load transfer mechanisms in these multi-layer composites is essential,as it offers intuitive insights into parametric influences and facilitates enhanced structural performance.This paper employs an improved transfer matrix method to address the limitations of existing theoretical approaches for analyzing multi-layer composite structures.By establishing a twodimensional composite pavement model,it investigates load transfer characteristics and validates the accuracy through finite element simulation.The proposed method offers a straightforward analytical approach for examining internal interactions between structural layers.Case studies indicate that the concrete surface layer is the main load-bearing layer for most vertical normal and shear stresses.The soil base layer reduces the overall mechanical response of the substructure,while horizontal actions increase the risk of interfacial slip and cracking.Structural optimization analysis demonstrates that increasing the thickness of the concrete surface layer,enhancing the thickness and stiffness of the soil base layer,or incorporating gradient layers can significantly mitigate these risks of interfacial slip and cracking.The findings of this study can guide the optimization design,parameter analysis,and damage prevention of multi-layer composite structures.展开更多
Rotor airfoil design is investigated in this paper. There are many difficulties for this highdimensional multi-objective problem when traditional multi-objective optimization methods are used. Therefore, a multi-layer...Rotor airfoil design is investigated in this paper. There are many difficulties for this highdimensional multi-objective problem when traditional multi-objective optimization methods are used. Therefore, a multi-layer hierarchical constraint method is proposed by coupling principal component analysis(PCA) dimensionality reduction and e-constraint method to translate the original high-dimensional problem into a bi-objective problem. This paper selects the main design objectives by conducting PCA to the preliminary solution of original problem with consideration of the priority of design objectives. According to the e-constraint method, the design model is established by treating the two top-ranking design goals as objective and others as variable constraints. A series of bi-objective Pareto curves will be obtained by changing the variable constraints, and the favorable solution can be obtained by analyzing Pareto curve spectrum. This method is applied to the rotor airfoil design and makes great improvement in aerodynamic performance. It is shown that the method is convenient and efficient, beyond which, it facilitates decision-making of the highdimensional multi-objective engineering problem.展开更多
It is difficult to collect the prior information for small-sample machinery products when their reliability is assessed by using Bayes method. In this study, an improved Bayes method with gradient reliability(GR) resu...It is difficult to collect the prior information for small-sample machinery products when their reliability is assessed by using Bayes method. In this study, an improved Bayes method with gradient reliability(GR) results as prior information was proposed to solve the problem. A certain type of heavy NC boring and milling machine was considered as the research subject, and its reliability model was established on the basis of its functional and structural characteristics and working principle. According to the stress-intensity interference theory and the reliability model theory, the GR results of the host machine and its key components were obtained. Then the GR results were deemed as prior information to estimate the probabilistic reliability(PR) of the spindle box, the column and the host machine in the present method. The comparative studies demonstrated that the improved Bayes method was applicable in the reliability assessment of heavy NC machine tools.展开更多
To implement the prediction of the logistics demand capacity of a certain region,a comprehensive index system is constructed,which is composed of freight volume and other eight relevant economic indices,such as gross ...To implement the prediction of the logistics demand capacity of a certain region,a comprehensive index system is constructed,which is composed of freight volume and other eight relevant economic indices,such as gross domestic product(GDP),consumer price index(CPI),total import and export volume,port's cargo throughput,total retail sales of consumer goods,total fixed asset investment,highway mileage,and resident population,to form the foundation for the model calculation.Based on the least square method(LSM)to fit the parameters,the study obtains an accurate mathematical model and predicts the changes of each index in the next five years.Using artificial intelligence software,the research establishes the logistics demand model of multi-layer perceptron(MLP)neural network,makes an empirical analysis on the logistics demand of Quanzhou City,and predicts its logistics demand in the next five years,which provides some references for formulating logistics planning and development strategy.展开更多
The multi-layer ceramic capacitor (MLCC) alignment system aims at the inter-process automation between the first and the second plastic processes.As a result of testing performance verification of MLCC alignment syste...The multi-layer ceramic capacitor (MLCC) alignment system aims at the inter-process automation between the first and the second plastic processes.As a result of testing performance verification of MLCC alignment system,the average alignment rates are 95% for 3216 chip,88.5% for 2012 chip and 90.8% for 3818 chip.The MLCC alignment system can be accepted for practical use because the average manual alignment is just 80%.In other words,the developed MLCC alignment system has been upgraded to a great extent,compared with manual alignment.Based on the successfully developed MLCC alignment system,the optimal transfer conditions have been explored by using RSM.The simulations using ADAMS has been performed according to the cube model of CCD.By using MiniTAB,the model of response surface has been established based on the simulation results.The optimal conditions resulted from the response optimization tool of MiniTAB has been verified by being assigned to the prototype of MLCC alignment system.展开更多
基金National Natural Science Foundation of China(52175237)。
文摘The key parameters that characterize the morphological quality of multi-layer and multi-pass metal laser deposited parts are the surface roughness and the error between the actual printing height and the theoretical model height.The Taguchi method was employed to establish the correlations between process parameter combinations and multi-objective characterization of metal deposition morphology(height error and roughness).Results show that using the signal-to-noise ratio and grey relational analysis,the optimal parameter combination for multi-layer and multi-pass deposition is determined as follows:laser power of 800 W,powder feeding rate of 0.3 r/min,step distance of 1.6 mm,and scanning speed of 20 mm/s.Subsequently,a Genetic Bayesian-back propagation(GB-BP)network is constructed to predict multi-objective responses.Compared with the traditional back propagation network,the GB-back propagation network improves the prediction accuracy of height error and surface roughness by 43.14%and 71.43%,respectively.This network can accurately predict the multi-objective characterization of morphological quality of multi-layer and multi-pass metal deposited parts.
文摘When assessing seismic liquefaction potential with data-driven models,addressing the uncertainties of establishing models,interpreting cone penetration tests(CPT)data and decision threshold is crucial for avoiding biased data selection,ameliorating overconfident models,and being flexible to varying practical objectives,especially when the training and testing data are not identically distributed.A workflow characterized by leveraging Bayesian methodology was proposed to address these issues.Employing a Multi-Layer Perceptron(MLP)as the foundational model,this approach was benchmarked against empirical methods and advanced algorithms for its efficacy in simplicity,accuracy,and resistance to overfitting.The analysis revealed that,while MLP models optimized via maximum a posteriori algorithm suffices for straightforward scenarios,Bayesian neural networks showed great potential for preventing overfitting.Additionally,integrating decision thresholds through various evaluative principles offers insights for challenging decisions.Two case studies demonstrate the framework's capacity for nuanced interpretation of in situ data,employing a model committee for a detailed evaluation of liquefaction potential via Monte Carlo simulations and basic statistics.Overall,the proposed step-by-step workflow for analyzing seismic liquefaction incorporates multifold testing and real-world data validation,showing improved robustness against overfitting and greater versatility in addressing practical challenges.This research contributes to the seismic liquefaction assessment field by providing a structured,adaptable methodology for accurate and reliable analysis.
基金supported by Fundamental Research Funds for the Central Universities(No.lzujbky-2024-05)Innovation Foundation of Provincial Education Department of Gansu(2024B-005)+2 种基金Scientific Department of Gansu(24CXGA083,24CXGA024,JK2024-28,JK2024-32 and 23CXJA0007)Industrial Support Plan Project of Provincial Education Department of Gansu(2025CYZC-003 and CYZC-2024-10)the Hunan Natural Science Foundation Science and Education Joint Fund Project(2022JJ60109).
文摘Transportation structures such as composite pavements and railway foundations typically consist of multi-layered media designed to withstand high bearing capacity.A theoretical understanding of load transfer mechanisms in these multi-layer composites is essential,as it offers intuitive insights into parametric influences and facilitates enhanced structural performance.This paper employs an improved transfer matrix method to address the limitations of existing theoretical approaches for analyzing multi-layer composite structures.By establishing a twodimensional composite pavement model,it investigates load transfer characteristics and validates the accuracy through finite element simulation.The proposed method offers a straightforward analytical approach for examining internal interactions between structural layers.Case studies indicate that the concrete surface layer is the main load-bearing layer for most vertical normal and shear stresses.The soil base layer reduces the overall mechanical response of the substructure,while horizontal actions increase the risk of interfacial slip and cracking.Structural optimization analysis demonstrates that increasing the thickness of the concrete surface layer,enhancing the thickness and stiffness of the soil base layer,or incorporating gradient layers can significantly mitigate these risks of interfacial slip and cracking.The findings of this study can guide the optimization design,parameter analysis,and damage prevention of multi-layer composite structures.
基金supported by the National Natural Science Foundation of China (No. 11402288 and 11372254)the National Basic Research Program of China (No. 2014CB744804)
文摘Rotor airfoil design is investigated in this paper. There are many difficulties for this highdimensional multi-objective problem when traditional multi-objective optimization methods are used. Therefore, a multi-layer hierarchical constraint method is proposed by coupling principal component analysis(PCA) dimensionality reduction and e-constraint method to translate the original high-dimensional problem into a bi-objective problem. This paper selects the main design objectives by conducting PCA to the preliminary solution of original problem with consideration of the priority of design objectives. According to the e-constraint method, the design model is established by treating the two top-ranking design goals as objective and others as variable constraints. A series of bi-objective Pareto curves will be obtained by changing the variable constraints, and the favorable solution can be obtained by analyzing Pareto curve spectrum. This method is applied to the rotor airfoil design and makes great improvement in aerodynamic performance. It is shown that the method is convenient and efficient, beyond which, it facilitates decision-making of the highdimensional multi-objective engineering problem.
基金Supported by the National Science and Technology Major Project of China(No.2009ZX04002-061)the National Science and Technology Support Program(No.2013BAF06B00)the Natural Science Foundation of Tianjin(No.13JCZDJC34000)
文摘It is difficult to collect the prior information for small-sample machinery products when their reliability is assessed by using Bayes method. In this study, an improved Bayes method with gradient reliability(GR) results as prior information was proposed to solve the problem. A certain type of heavy NC boring and milling machine was considered as the research subject, and its reliability model was established on the basis of its functional and structural characteristics and working principle. According to the stress-intensity interference theory and the reliability model theory, the GR results of the host machine and its key components were obtained. Then the GR results were deemed as prior information to estimate the probabilistic reliability(PR) of the spindle box, the column and the host machine in the present method. The comparative studies demonstrated that the improved Bayes method was applicable in the reliability assessment of heavy NC machine tools.
基金Educational Research Project of Social Science for Young and Middle Aged Teachers in Fujian Province,China(No.JAS19371)Social Science Research Project of Education Department of Fujian Province,China(No.JAS160571)Key Project of Education and Teaching Reform of Undergraduate Universities in Fujian Province,China(No.FBJG20190130)。
文摘To implement the prediction of the logistics demand capacity of a certain region,a comprehensive index system is constructed,which is composed of freight volume and other eight relevant economic indices,such as gross domestic product(GDP),consumer price index(CPI),total import and export volume,port's cargo throughput,total retail sales of consumer goods,total fixed asset investment,highway mileage,and resident population,to form the foundation for the model calculation.Based on the least square method(LSM)to fit the parameters,the study obtains an accurate mathematical model and predicts the changes of each index in the next five years.Using artificial intelligence software,the research establishes the logistics demand model of multi-layer perceptron(MLP)neural network,makes an empirical analysis on the logistics demand of Quanzhou City,and predicts its logistics demand in the next five years,which provides some references for formulating logistics planning and development strategy.
基金supported by the Second Stage of Brain Korea 21 Projectssupported (in part) by the Solomon Mechanics Inc
文摘The multi-layer ceramic capacitor (MLCC) alignment system aims at the inter-process automation between the first and the second plastic processes.As a result of testing performance verification of MLCC alignment system,the average alignment rates are 95% for 3216 chip,88.5% for 2012 chip and 90.8% for 3818 chip.The MLCC alignment system can be accepted for practical use because the average manual alignment is just 80%.In other words,the developed MLCC alignment system has been upgraded to a great extent,compared with manual alignment.Based on the successfully developed MLCC alignment system,the optimal transfer conditions have been explored by using RSM.The simulations using ADAMS has been performed according to the cube model of CCD.By using MiniTAB,the model of response surface has been established based on the simulation results.The optimal conditions resulted from the response optimization tool of MiniTAB has been verified by being assigned to the prototype of MLCC alignment system.
