Current topology optimization methods for nonlinear continuum structures often suffer from low computational efficiency and limited applicability to complex nonlinear problems.To address these issues,this paper propos...Current topology optimization methods for nonlinear continuum structures often suffer from low computational efficiency and limited applicability to complex nonlinear problems.To address these issues,this paper proposes an improved bi-directional evolutionary structural optimization(BESO)method tailored for maximizing stiffness in nonlinear structures.The optimization program is developed in Python and can be combined with Abaqus software to facilitate finite element analysis(FEA).To accelerate the speed of optimization,a novel adaptive evolutionary ratio(ER)strategy based on the BESO method is introduced,with four distinct adaptive ER functions proposed.The Newton-Raphson method is utilized for iteratively solving nonlinear equilibrium equations,and the sensitivity information for updating design variables is derived using the adjoint method.Additionally,this study extends topology optimization to account for both material nonlinearity and geometric nonlinearity,analyzing the effects of various nonlinearities.A series of comparative studies are conducted using benchmark cases to validate the effectiveness of the proposed method.The results show that the BESO method with adaptive ER significantly improves the optimization efficiency.Compared to the BESO method with a fixed ER,the convergence speed of the four adaptive ER BESO methods is increased by 37.3%,26.7%,12%and 18.7%,respectively.Given that Abaqus is a powerful FEA platform,this method has the potential to be extended to large-scale engineering structures and to address more complex optimization problems.This research proposes an improved BESO method with novel adaptive ER,which significantly accelerates the optimization process and enables its application to topology optimization of nonlinear structures.展开更多
The optimization of volume ratio(V_(An)/V_(A)/V_(0))and nitrate recycling ratio(R)in a two-sludge denitrifying phosphorus removal(DPR)process of Anaerobic Anoxic Oxic-Moving Bed Biofilm Reactor(A^(2)/O-MBBR)was invest...The optimization of volume ratio(V_(An)/V_(A)/V_(0))and nitrate recycling ratio(R)in a two-sludge denitrifying phosphorus removal(DPR)process of Anaerobic Anoxic Oxic-Moving Bed Biofilm Reactor(A^(2)/O-MBBR)was investigated.The results showed that prolonged anaerobic retention time(HRT An:1.25→3.75 hr)exerted favorable effect on chemical oxygen demand(COD)removal(57.26%→73.54%),poly-β-hydroxyalkanoates(PHA)synthesis(105.70→138.12 mg COD/L)and PO_(4)^(3-)release(22.3→38.9 mg/L).However,anoxic retention time(HRT A)and R exhibited positive correlation with PHA utilization(43.87%-81.34%)and denitrifying phosphorus removal(DPR)potential(NO_(3)-/PO^(3-)_(4):0.57-1.34 mg/mg),leading to dramatical TN removal variations from 68.86%to 81.28%.Under the V An/V A/V O ratio of 2:6:0,sludge loss deteriorated nutrient removals but the sludge bioactivity quickly recovered when the oxic zone was recovered.The sludge characteristic and microstructure gradually transformed under the dissolved oxygen(DO)control(1.0-1.5→1.5-2.0 mg/L),in terms of sludge volume index(SVI:194→57 m L/g VSS),median-particle-size(D 50:99.6→300.5μm),extracellular polymeric substances(EPS)(105.62→226.18 mg/g VSS)and proteins/polysaccharides(PN/PS)ratio(1.52→3.46).Fluorescence in situ hybridization(FISH)results showed that phosphorus accumulation organisms(PAOs)(mainly Cluster I of Accumulibacter,contribution ratio:91.79%-94.10%)dominated the superior DPR performance,while glycogen accumulating organisms(GAOs)(mainly Competibacter,contribution ratio:82.61%-86.89%)was responsible for deteriorative TN and PO_(4)^(3-)removals.The optimal HRT A and R assembled around 5-6.5 hr and 300%-400%based on the PHA utilization and DRP performance,and the oxic zones also contributed to PO_(4)^(3-)removal although it showed low dependence on DO concentration and oxic retention time(HRT_(0)).展开更多
Because there is neither waste rock nor mill tailings in the gypsum mine, and the buildings on the goaf of gypsum mine are needed to be protected, the research proposed the scheme of the clay filling technology. Gypsu...Because there is neither waste rock nor mill tailings in the gypsum mine, and the buildings on the goaf of gypsum mine are needed to be protected, the research proposed the scheme of the clay filling technology. Gypsum, cement, lime and water glass were used as adhesive, and the strength of different material ratios were investigated in this study. The influence factors of clay strength were obtained in the order of cement, gypsum, water glass and lime. The results show that the cement content is the determinant influence factor, and gypsum has positive effects, while the water glass can enhance both clay strength and the fluidity of the filing slurry. Furthermore, combining chaotic optimization method with neural network, the optimal ratio of composite cementing agent was obtained. The results show that the optimal ratio of water glass, cement, lime and clay (in quality) is 1.17:6.74:4.17:87.92 in the process of bottom self-flow filling, while the optimal ratio is 1.78:9.58:4.71:83.93 for roof-contacted filling. A novel filling process to fill in gypsum mine goaf with clay is established. The engineering practice shows that the filling cost is low, thus, notable economic benefit is achieved.展开更多
In this study, an enthalpy-concentration method was applied in order to model a steady state continuous benzene-toluene mixture distillation column. For a distillation tower such as the benzene- toluene splitter, ther...In this study, an enthalpy-concentration method was applied in order to model a steady state continuous benzene-toluene mixture distillation column. For a distillation tower such as the benzene- toluene splitter, there are relatively few degrees of freedom that can be manipulated in order to minimize the total annualized cost. The reflux ratio can influence the steady-state operating point and therefore influence the total annualized cost. The trade-offs between reflux ratios and total annualized cost were discussed. The Cuckoo optimization algorithm was applied to obtain a correlation for the optimum value of the reflux ratio as a power function of the economic parameters of energy price and capital cost. The results show that, at low energy price or high capital cost, the optimum reflux factor is high.展开更多
To improve the crashworthiness and energy absorption performance,a novel crash box negative Poisson’s ratio(NPR)structure is proposed according to the characteristics of low speed collision of bumper system.Taking th...To improve the crashworthiness and energy absorption performance,a novel crash box negative Poisson’s ratio(NPR)structure is proposed according to the characteristics of low speed collision of bumper system.Taking the peak collision force and the average collision force as two subsystems,a multidisciplinary collaborative optimization design is carried out,and its optimization results are compared with the ones optimized by NSGA-II algorithm.Simulation results show that the crashworthiness and energy absorption performance of the novel crash box is improved effectively based on the multidisciplinary optimization method.展开更多
In order to analyze the effects of forward-swept angle and skin ply-orientation on the static and dynamic aeroelastic characteristics, the aeroelastic modeling and calculation for high-aspect-ratio composite wings wit...In order to analyze the effects of forward-swept angle and skin ply-orientation on the static and dynamic aeroelastic characteristics, the aeroelastic modeling and calculation for high-aspect-ratio composite wings with different forward-swept angles and skin ply-orientation are performed. This paper presents the results of a design study aiming to optimize wings with typical forward-swept angles and skin ply-orientation in an aeroelastic way by using the genetic/sensitivity-based hybrid algorithm. Under the conditions of satiated multiple constraints including strength, displacements, divergence speeds and flutter speeds, the studies are carried out in a bid to minimize the structural weight of a wing with the lay-up thicknesses of wing components as design variabies. In addition, the effects of the power of spanwise variation function of lay-up thicknesses of skins and iugs on the optimized weights are also analyzed.展开更多
Batch distillation,basically different from continuous distillation which is a steady stateprocess,appears to be an unsteady state process in its mathematical description.The theoreticalanalysis of its operation compr...Batch distillation,basically different from continuous distillation which is a steady stateprocess,appears to be an unsteady state process in its mathematical description.The theoreticalanalysis of its operation comprises a concomitant consideration of the stage-wise separation andthe equations of material balance as well as enthalpy balance.Based upon the batch distillationpractice of NMP-water system,this paper reveals the necessity and advantage of a computerizedtreatment for this purpose.Numerical results not only explain the experimental phenomena andprovide a design scheme,but also lead to the optimization of the operation condition.展开更多
Optimization of structural parameters aimed at improving the load carrying capacity of spatial flexible redundant manipulators is presented in this paper. In order to increase the ratio of load to mass of robots, the ...Optimization of structural parameters aimed at improving the load carrying capacity of spatial flexible redundant manipulators is presented in this paper. In order to increase the ratio of load to mass of robots, the cross-sectional parameters and constructional parameters are optimized respectively. The cross-sectional and configurational parameters are optimized simultaneously. The numerical simulation of a 4R spatial manipulator is performed. The results show that the load capacity of robots has been greatly improved through the optimization strategies proposed in this paper.展开更多
Natural frequency and dynamic stiffness under transient loading are two key performances for structural design related to automotive,aviation and construction industries.This article aims to tackle the multi-objective...Natural frequency and dynamic stiffness under transient loading are two key performances for structural design related to automotive,aviation and construction industries.This article aims to tackle the multi-objective topological optimization problem considering dynamic stiffness and natural frequency using modified version of bi-directional evolutionary structural optimization(BESO).The conventional BESO is provided with constant evolutionary volume ratio(EVR),whereas low EVR greatly retards the optimization process and high EVR improperly removes the efficient elements.To address the issue,the modified BESO with variable EVR is introduced.To compromise the natural frequency and the dynamic stiffness,a weighting scheme of sensitivity numbers is employed to form the Pareto solution space.Several numerical examples demonstrate that the optimal solutions obtained from the modified BESO method have good agreement with those from the classic BESO method.Most importantly,the dynamic removal strategy with the variable EVR sharply springs up the optimization process.Therefore,it is concluded that the modified BESO method with variable EVR can solve structural design problems using multi-objective optimization.展开更多
The prediction model for mechanical properties of RAC was established through the Bayesian optimization-based Gaussian process regression(BO-GPR)method,where the input variables in BO-GPR model depend on the mix ratio...The prediction model for mechanical properties of RAC was established through the Bayesian optimization-based Gaussian process regression(BO-GPR)method,where the input variables in BO-GPR model depend on the mix ratio of concrete.Then the compressive strength prediction model,the material cost,and environmental factors were simultaneously considered as objectives,while a multi-objective gray wolf optimization algorithm was developed for finding the optimal mix ratio.A total of 730 RAC datasets were used for training and testing the predication model,while the optimal design method for mix ratio was verified through RAC experiments.The experimental results show that the predicted,testing,and expected compressive strengths are nearly consistent,illustrating the effectiveness of the proposed method.展开更多
The relationship between stiffness distribution and aeroelastic performance for a beam-frame model and a3-D model is investigated based on aeroelastic optimization of global stiffness design for high-aspect-ratio wing...The relationship between stiffness distribution and aeroelastic performance for a beam-frame model and a3-D model is investigated based on aeroelastic optimization of global stiffness design for high-aspect-ratio wings.The sensitivity information of wing spanwise stiffness distribution with respect to the twist angle at wing tip,the vertical displacement at wing tip,and the flutter speed are obtained using a sensitivity method for both models.Then the relationship between stiffness distribution and aeroelastic performance is summarized to guide the design procedure.By using the genetic/sensitivity-based hybrid algorithm,an optimal solution satisfying the strength,aeroelastic and manufacturing constraints is obtained.It is found that the summarized guidance is well consistent with the optimal solution,thus providing a valuable design advice with efficiency.The study also shows that the aeroelastic-optimization-based global stiffness design procedure can obtain the optimal solution under multiple constraints with high efficiency and precision,thereby having a strong application value in engineering.展开更多
Negative Poisson’s ratio(NPR)metamaterials are attractive for their unique mechanical behaviors and potential applications in deformation control and energy absorption.However,when subjected to significant stretching...Negative Poisson’s ratio(NPR)metamaterials are attractive for their unique mechanical behaviors and potential applications in deformation control and energy absorption.However,when subjected to significant stretching,NPR metamaterials designed under small strain assumption may experience a rapid degradation in NPR performance.To address this issue,this study aims to design metamaterials maintaining a targeted NPR under large deformation by taking advantage of the geometry nonlinearity mechanism.A representative periodic unit cell is modeled considering geometry nonlinearity,and its topology is designed using a gradient-free method.The unit cell microstructural topologies are described with the material-field series-expansion(MFSE)method.The MFSE method assumes spatial correlation of the material distribution,which greatly reduces the number of required design variables.To conveniently design metamaterials with desired NPR under large deformation,we propose a two-stage gradient-free metamaterial topology optimization method,which fully takes advantage of the dimension reduction benefits of the MFSE method and the Kriging surrogate model technique.Initially,we use homogenization to find a preliminary NPR design under a small deformation assumption.In the second stage,we begin with this preliminary design and minimize deviations in NPR from a targeted value under large deformation.Using this strategy and solution technique,we successfully obtain a group of NPR metamaterials that can sustain different desired NPRs in the range of[−0.8,−0.1]under uniaxial stretching up to 20% strain.Furthermore,typical microstructure designs are fabricated and tested through experiments.The experimental results show good consistency with our numerical results,demonstrating the effectiveness of the present gradientfree NPR metamaterial design strategy.展开更多
In this paper, a global optimization algorithm is proposed for nonlinear sum of ratios problem （P）. The algorithm works by globally solving problem （P1） that is equivalent to problem （P）, by utilizing linearizat...In this paper, a global optimization algorithm is proposed for nonlinear sum of ratios problem （P）. The algorithm works by globally solving problem （P1） that is equivalent to problem （P）, by utilizing linearization technique a linear relaxation programming of the （P1） is then obtained. The proposed algorithm is convergent to the global minimum of （P1） through the successive refinement of linear relaxation of the feasible region of objective function and solutions of a series of linear relaxation programming. Numerical results indicate that the proposed algorithm is feasible and can be used to globally solve nonlinear sum of ratios problems （P）.展开更多
The methods of moment and genetic algorithm (GA) are combined to optimize the Yagi Uda antenna array and Log periodic dipole antenna (LPDA) array. The element lengths and spacing are optimized for the Yagi Uda arra...The methods of moment and genetic algorithm (GA) are combined to optimize the Yagi Uda antenna array and Log periodic dipole antenna (LPDA) array. The element lengths and spacing are optimized for the Yagi Uda array; while the ratio factor of spacing to length as well as the ratio of length to diameter of the elements are optimized for LPDA array. The results show that the main parameters, such as gain and pattern, have been improved apparently; and the high back lobe level of LPDA can be reduced greatly, therefore, GA is a very competent method for optimizing the linear array as well as in other fields.展开更多
Bivariate statistical analysis of data-driven approaches is widely used for landslide susceptibility assessment, and the frequency ratio(FR) method is one of the most popular. However, the results of such assessments ...Bivariate statistical analysis of data-driven approaches is widely used for landslide susceptibility assessment, and the frequency ratio(FR) method is one of the most popular. However, the results of such assessments are dominated by the number of classes and bounds of landslide-related causative factors, and the optimal assessment is unknown. This paper optimizes the frequency ratio method as an example of bivariate statistical analysis for landslide susceptibility mapping based on a case study of the Caiyuan Basin, a region with frequent landslides, which is located in the southeast coastal mountainous area of China. A landslide inventory map containing a total of 1425 landslides(polygons) was produced, in which 70% of the landslides were selected for training purposes, and the remaining were used for validationpurposes. All datasets were resampled to the same 5 m × 5 m/pixel resolution. The receiver operating characteristic(ROC) curves of the susceptibility maps were obtained based on different combinations of dominating parameters, and the maximum value of the areas under the ROC curves(AUCs) as well as the corresponding optimal parameter was identified with an automatic searching algorithm. The results showed that the landslide susceptibility maps obtained using optimal parameters displayed a significant increase in the prediction AUC compared with those values obtained using stochastic parameters. The results also showed that one parameter named bin width has a dominant influence on the optimum. In practice, this paper is expected to benefit the assessment of landslide susceptibility by providing an easy-to-use tool. The proposed automatic approach provides a way to optimize the frequency ratio method or other bivariate statistical methods, which can furtherfacilitate comparisons and choices between different methods for landslide susceptibility assessment.展开更多
The identification of maximum road friction coefficient and optimal slip ratio is crucial to vehicle dynamics and control.However,it is always not easy to identify the maximum road friction coefficient with high robus...The identification of maximum road friction coefficient and optimal slip ratio is crucial to vehicle dynamics and control.However,it is always not easy to identify the maximum road friction coefficient with high robustness and good adaptability to various vehicle operating conditions.The existing investigations on robust identification of maximum road friction coefficient are unsatisfactory.In this paper,an identification approach based on road type recognition is proposed for the robust identification of maximum road friction coefficient and optimal slip ratio.The instantaneous road friction coefficient is estimated through the recursive least square with a forgetting factor method based on the single wheel model,and the estimated road friction coefficient and slip ratio are grouped in a set of samples in a small time interval before the current time,which are updated with time progressing.The current road type is recognized by comparing the samples of the estimated road friction coefficient with the standard road friction coefficient of each typical road,and the minimum statistical error is used as the recognition principle to improve identification robustness.Once the road type is recognized,the maximum road friction coefficient and optimal slip ratio are determined.The numerical simulation tests are conducted on two typical road friction conditions（single-friction and joint-friction）by using CarSim software.The test results show that there is little identification error between the identified maximum road friction coefficient and the pre-set value in CarSim.The proposed identification method has good robustness performance to external disturbances and good adaptability to various vehicle operating conditions and road variations,and the identification results can be used for the adjustment of vehicle active safety control strategies.展开更多
As threats of landslide hazards have become gradually more severe in recent decades,studies on landslide prevention and mitigation have attracted widespread attention in relevant domains.A hot research topic has been ...As threats of landslide hazards have become gradually more severe in recent decades,studies on landslide prevention and mitigation have attracted widespread attention in relevant domains.A hot research topic has been the ability to predict landslide susceptibility,which can be used to design schemes of land exploitation and urban development in mountainous areas.In this study,the teaching-learning-based optimization(TLBO)and satin bowerbird optimizer(SBO)algorithms were applied to optimize the adaptive neuro-fuzzy inference system(ANFIS)model for landslide susceptibility mapping.In the study area,152 landslides were identified and randomly divided into two groups as training(70%)and validation(30%)dataset.Additionally,a total of fifteen landslide influencing factors were selected.The relative importance and weights of various influencing factors were determined using the step-wise weight assessment ratio analysis(SWARA)method.Finally,the comprehensive performance of the two models was validated and compared using various indexes,such as the root mean square error(RMSE),processing time,convergence,and area under receiver operating characteristic curves(AUROC).The results demonstrated that the AUROC values of the ANFIS,ANFIS-TLBO and ANFIS-SBO models with the training data were 0.808,0.785 and 0.755,respectively.In terms of the validation dataset,the ANFISSBO model exhibited a higher AUROC value of 0.781,while the AUROC value of the ANFIS-TLBO and ANFIS models were 0.749 and 0.681,respectively.Moreover,the ANFIS-SBO model showed lower RMSE values for the validation dataset,indicating that the SBO algorithm had a better optimization capability.Meanwhile,the processing time and convergence of the ANFIS-SBO model were far superior to those of the ANFIS-TLBO model.Therefore,both the ensemble models proposed in this paper can generate adequate results,and the ANFIS-SBO model is recommended as the more suitable model for landslide susceptibility assessment in the study area considered due to its excellent accuracy and efficiency.展开更多
Use of hot-stamped high strength steels （HSHSS） not only reduces the vehicle weight, but also improves the crash safety, therefore more and more mentioned steels are used to produce automobile parts. However, there ...Use of hot-stamped high strength steels （HSHSS） not only reduces the vehicle weight, but also improves the crash safety, therefore more and more mentioned steels are used to produce automobile parts. However, there are several problems especially the low ductility and toughness, which have restricted the application of HSHSS in automobile body. Suitable process parameters are very crucial to improve strength and toughness. In order to study the effect of austenization temperature, soaking time and start deformation temperature on strength and toughness of boron steel 22MnB5, an L9 （34） orthogonal experiment which was analyzed by means of comprehensive evaluation was carried out based on Kahn tear method to obtain the value of fracture toughness. The results indicate that the ex- cellent formability, high strength and toughness of boron steel 22MnB5 with 1.6 mm in thickness are obtained when the austenization temperature is in the range of 920- 950 ℃, the soaking time is 1 min and the start deformation temperature is in the range of 650- 700 ℃. The optimal parameters were used for typical hot stamping structural parts tests. Properties of samples such as tear strength, unit initiation energy and ratio of strength to toughness （RST） were improved by 10.91%, 20.32% and 22.17%, respectively. Toughness was increased substantially on the basis of a small decrease of strength.展开更多
For high-purity distillation processes,it is difficult to achieve a good direct product quality control using traditional proportional-integral-differential(PID)control or multivariable predictive control technique du...For high-purity distillation processes,it is difficult to achieve a good direct product quality control using traditional proportional-integral-differential(PID)control or multivariable predictive control technique due to some difficulties,such as long response time,many un-measurable disturbances,and the reliability and precision issues of product quality soft-sensors.In this paper,based on the first principle analysis and dynamic simulation of a distillation process,a new predictive control scheme is proposed by using the split ratio of distillate flow rate to that of bottoms as an essential controlled variable.Correspondingly,a new strategy with integrated control and on-line optimization is developed,which consists of model predictive control of the split ratio,surrogate model based on radial basis function neural network for optimization,and modified differential evolution optimization algorithm. With the strategy,the process achieves its steady state quickly,so more profit can be obtained.The proposed strategy has been successfully applied to a gas separation plant for more than three years,which shows that the strategy is feasible and effective.展开更多
In this paper,a Double-stage Surrogate-based Shape Optimization(DSSO)strategy for Blended-Wing-Body Underwater Gliders(BWBUGs)is proposed to reduce the computational cost.In this strategy,a double-stage surrogate mode...In this paper,a Double-stage Surrogate-based Shape Optimization(DSSO)strategy for Blended-Wing-Body Underwater Gliders(BWBUGs)is proposed to reduce the computational cost.In this strategy,a double-stage surrogate model is developed to replace the high-dimensional objective in shape optimization.Specifically,several First-stage Surrogate Models(FSMs)are built for the sectional airfoils,and the second-stage surrogate model is constructed with respect to the outputs of FSMs.Besides,a Multi-start Space Reduction surrogate-based global optimization method is applied to search for the optimum.In order to validate the efficiency of the proposed method,DSSO is first compared with an ordinary One-stage Surrogate-based Optimization strategy by using the same optimization method.Then,the other three popular surrogate-based optimization methods and three heuristic algorithms are utilized to make comparisons.Results indicate that the lift-to-drag ratio of the BWBUG is improved by 9.35%with DSSO,which outperforms the comparison methods.Besides,DSSO reduces more than 50%of the time that other methods used when obtaining the same level of results.Furthermore,some considerations of the proposed strategy are further discussed and some characteristics of DSSO are identified.展开更多
基金Supported by National Natural Science Foundation of China(Grant No.52105271).
文摘Current topology optimization methods for nonlinear continuum structures often suffer from low computational efficiency and limited applicability to complex nonlinear problems.To address these issues,this paper proposes an improved bi-directional evolutionary structural optimization(BESO)method tailored for maximizing stiffness in nonlinear structures.The optimization program is developed in Python and can be combined with Abaqus software to facilitate finite element analysis(FEA).To accelerate the speed of optimization,a novel adaptive evolutionary ratio(ER)strategy based on the BESO method is introduced,with four distinct adaptive ER functions proposed.The Newton-Raphson method is utilized for iteratively solving nonlinear equilibrium equations,and the sensitivity information for updating design variables is derived using the adjoint method.Additionally,this study extends topology optimization to account for both material nonlinearity and geometric nonlinearity,analyzing the effects of various nonlinearities.A series of comparative studies are conducted using benchmark cases to validate the effectiveness of the proposed method.The results show that the BESO method with adaptive ER significantly improves the optimization efficiency.Compared to the BESO method with a fixed ER,the convergence speed of the four adaptive ER BESO methods is increased by 37.3%,26.7%,12%and 18.7%,respectively.Given that Abaqus is a powerful FEA platform,this method has the potential to be extended to large-scale engineering structures and to address more complex optimization problems.This research proposes an improved BESO method with novel adaptive ER,which significantly accelerates the optimization process and enables its application to topology optimization of nonlinear structures.
基金supported by the Natural Science Foundation of China(No.51808482)the Postdoctoral Science Foundation of China(No.2018M632392)the Jiangsu Open Research Project of Water Environmental Protection Technology and Equipment Engineering Laboratory(No.W1904)。
文摘The optimization of volume ratio(V_(An)/V_(A)/V_(0))and nitrate recycling ratio(R)in a two-sludge denitrifying phosphorus removal(DPR)process of Anaerobic Anoxic Oxic-Moving Bed Biofilm Reactor(A^(2)/O-MBBR)was investigated.The results showed that prolonged anaerobic retention time(HRT An:1.25→3.75 hr)exerted favorable effect on chemical oxygen demand(COD)removal(57.26%→73.54%),poly-β-hydroxyalkanoates(PHA)synthesis(105.70→138.12 mg COD/L)and PO_(4)^(3-)release(22.3→38.9 mg/L).However,anoxic retention time(HRT A)and R exhibited positive correlation with PHA utilization(43.87%-81.34%)and denitrifying phosphorus removal(DPR)potential(NO_(3)-/PO^(3-)_(4):0.57-1.34 mg/mg),leading to dramatical TN removal variations from 68.86%to 81.28%.Under the V An/V A/V O ratio of 2:6:0,sludge loss deteriorated nutrient removals but the sludge bioactivity quickly recovered when the oxic zone was recovered.The sludge characteristic and microstructure gradually transformed under the dissolved oxygen(DO)control(1.0-1.5→1.5-2.0 mg/L),in terms of sludge volume index(SVI:194→57 m L/g VSS),median-particle-size(D 50:99.6→300.5μm),extracellular polymeric substances(EPS)(105.62→226.18 mg/g VSS)and proteins/polysaccharides(PN/PS)ratio(1.52→3.46).Fluorescence in situ hybridization(FISH)results showed that phosphorus accumulation organisms(PAOs)(mainly Cluster I of Accumulibacter,contribution ratio:91.79%-94.10%)dominated the superior DPR performance,while glycogen accumulating organisms(GAOs)(mainly Competibacter,contribution ratio:82.61%-86.89%)was responsible for deteriorative TN and PO_(4)^(3-)removals.The optimal HRT A and R assembled around 5-6.5 hr and 300%-400%based on the PHA utilization and DRP performance,and the oxic zones also contributed to PO_(4)^(3-)removal although it showed low dependence on DO concentration and oxic retention time(HRT_(0)).
基金supported by the National Basic Research and Development Program of China (No. 2010CB732004)the joint funding of the National Natural Science Foundation and Shanghai Baosteel Group Corporation of China (No. 51074177)
文摘Because there is neither waste rock nor mill tailings in the gypsum mine, and the buildings on the goaf of gypsum mine are needed to be protected, the research proposed the scheme of the clay filling technology. Gypsum, cement, lime and water glass were used as adhesive, and the strength of different material ratios were investigated in this study. The influence factors of clay strength were obtained in the order of cement, gypsum, water glass and lime. The results show that the cement content is the determinant influence factor, and gypsum has positive effects, while the water glass can enhance both clay strength and the fluidity of the filing slurry. Furthermore, combining chaotic optimization method with neural network, the optimal ratio of composite cementing agent was obtained. The results show that the optimal ratio of water glass, cement, lime and clay (in quality) is 1.17:6.74:4.17:87.92 in the process of bottom self-flow filling, while the optimal ratio is 1.78:9.58:4.71:83.93 for roof-contacted filling. A novel filling process to fill in gypsum mine goaf with clay is established. The engineering practice shows that the filling cost is low, thus, notable economic benefit is achieved.
文摘In this study, an enthalpy-concentration method was applied in order to model a steady state continuous benzene-toluene mixture distillation column. For a distillation tower such as the benzene- toluene splitter, there are relatively few degrees of freedom that can be manipulated in order to minimize the total annualized cost. The reflux ratio can influence the steady-state operating point and therefore influence the total annualized cost. The trade-offs between reflux ratios and total annualized cost were discussed. The Cuckoo optimization algorithm was applied to obtain a correlation for the optimum value of the reflux ratio as a power function of the economic parameters of energy price and capital cost. The results show that, at low energy price or high capital cost, the optimum reflux factor is high.
文摘To improve the crashworthiness and energy absorption performance,a novel crash box negative Poisson’s ratio(NPR)structure is proposed according to the characteristics of low speed collision of bumper system.Taking the peak collision force and the average collision force as two subsystems,a multidisciplinary collaborative optimization design is carried out,and its optimization results are compared with the ones optimized by NSGA-II algorithm.Simulation results show that the crashworthiness and energy absorption performance of the novel crash box is improved effectively based on the multidisciplinary optimization method.
文摘In order to analyze the effects of forward-swept angle and skin ply-orientation on the static and dynamic aeroelastic characteristics, the aeroelastic modeling and calculation for high-aspect-ratio composite wings with different forward-swept angles and skin ply-orientation are performed. This paper presents the results of a design study aiming to optimize wings with typical forward-swept angles and skin ply-orientation in an aeroelastic way by using the genetic/sensitivity-based hybrid algorithm. Under the conditions of satiated multiple constraints including strength, displacements, divergence speeds and flutter speeds, the studies are carried out in a bid to minimize the structural weight of a wing with the lay-up thicknesses of wing components as design variabies. In addition, the effects of the power of spanwise variation function of lay-up thicknesses of skins and iugs on the optimized weights are also analyzed.
文摘Batch distillation,basically different from continuous distillation which is a steady stateprocess,appears to be an unsteady state process in its mathematical description.The theoreticalanalysis of its operation comprises a concomitant consideration of the stage-wise separation andthe equations of material balance as well as enthalpy balance.Based upon the batch distillationpractice of NMP-water system,this paper reveals the necessity and advantage of a computerizedtreatment for this purpose.Numerical results not only explain the experimental phenomena andprovide a design scheme,but also lead to the optimization of the operation condition.
文摘Optimization of structural parameters aimed at improving the load carrying capacity of spatial flexible redundant manipulators is presented in this paper. In order to increase the ratio of load to mass of robots, the cross-sectional parameters and constructional parameters are optimized respectively. The cross-sectional and configurational parameters are optimized simultaneously. The numerical simulation of a 4R spatial manipulator is performed. The results show that the load capacity of robots has been greatly improved through the optimization strategies proposed in this paper.
基金funded by the National Natural Science Foundation of China(Grant No.51505096)the Natural Science Foundation of Heilongjiang Province(Grant No.LH2020E064).
文摘Natural frequency and dynamic stiffness under transient loading are two key performances for structural design related to automotive,aviation and construction industries.This article aims to tackle the multi-objective topological optimization problem considering dynamic stiffness and natural frequency using modified version of bi-directional evolutionary structural optimization(BESO).The conventional BESO is provided with constant evolutionary volume ratio(EVR),whereas low EVR greatly retards the optimization process and high EVR improperly removes the efficient elements.To address the issue,the modified BESO with variable EVR is introduced.To compromise the natural frequency and the dynamic stiffness,a weighting scheme of sensitivity numbers is employed to form the Pareto solution space.Several numerical examples demonstrate that the optimal solutions obtained from the modified BESO method have good agreement with those from the classic BESO method.Most importantly,the dynamic removal strategy with the variable EVR sharply springs up the optimization process.Therefore,it is concluded that the modified BESO method with variable EVR can solve structural design problems using multi-objective optimization.
基金Funded by the National Natural Science Foundation of China(No.51908183)the Natural Science Foundation of Hebei Province(No.E2023202101)。
文摘The prediction model for mechanical properties of RAC was established through the Bayesian optimization-based Gaussian process regression(BO-GPR)method,where the input variables in BO-GPR model depend on the mix ratio of concrete.Then the compressive strength prediction model,the material cost,and environmental factors were simultaneously considered as objectives,while a multi-objective gray wolf optimization algorithm was developed for finding the optimal mix ratio.A total of 730 RAC datasets were used for training and testing the predication model,while the optimal design method for mix ratio was verified through RAC experiments.The experimental results show that the predicted,testing,and expected compressive strengths are nearly consistent,illustrating the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China (Nos.11302011,11372023, 11172025)
文摘The relationship between stiffness distribution and aeroelastic performance for a beam-frame model and a3-D model is investigated based on aeroelastic optimization of global stiffness design for high-aspect-ratio wings.The sensitivity information of wing spanwise stiffness distribution with respect to the twist angle at wing tip,the vertical displacement at wing tip,and the flutter speed are obtained using a sensitivity method for both models.Then the relationship between stiffness distribution and aeroelastic performance is summarized to guide the design procedure.By using the genetic/sensitivity-based hybrid algorithm,an optimal solution satisfying the strength,aeroelastic and manufacturing constraints is obtained.It is found that the summarized guidance is well consistent with the optimal solution,thus providing a valuable design advice with efficiency.The study also shows that the aeroelastic-optimization-based global stiffness design procedure can obtain the optimal solution under multiple constraints with high efficiency and precision,thereby having a strong application value in engineering.
基金the support of the National Science Foundation of China(12372120,12172075)the Liaoning Revitalization Talents Program(XLYC2007027)Fundamental Research Funds for the Central Universities(DUT21RC(3)067).
文摘Negative Poisson’s ratio(NPR)metamaterials are attractive for their unique mechanical behaviors and potential applications in deformation control and energy absorption.However,when subjected to significant stretching,NPR metamaterials designed under small strain assumption may experience a rapid degradation in NPR performance.To address this issue,this study aims to design metamaterials maintaining a targeted NPR under large deformation by taking advantage of the geometry nonlinearity mechanism.A representative periodic unit cell is modeled considering geometry nonlinearity,and its topology is designed using a gradient-free method.The unit cell microstructural topologies are described with the material-field series-expansion(MFSE)method.The MFSE method assumes spatial correlation of the material distribution,which greatly reduces the number of required design variables.To conveniently design metamaterials with desired NPR under large deformation,we propose a two-stage gradient-free metamaterial topology optimization method,which fully takes advantage of the dimension reduction benefits of the MFSE method and the Kriging surrogate model technique.Initially,we use homogenization to find a preliminary NPR design under a small deformation assumption.In the second stage,we begin with this preliminary design and minimize deviations in NPR from a targeted value under large deformation.Using this strategy and solution technique,we successfully obtain a group of NPR metamaterials that can sustain different desired NPRs in the range of[−0.8,−0.1]under uniaxial stretching up to 20% strain.Furthermore,typical microstructure designs are fabricated and tested through experiments.The experimental results show good consistency with our numerical results,demonstrating the effectiveness of the present gradientfree NPR metamaterial design strategy.
基金Foundation item： Supported by the National Natural Science Foundation of China（10671057） Supported by the Natural Science Foundation of Henan Institute of Science and Technology（06054）
文摘In this paper, a global optimization algorithm is proposed for nonlinear sum of ratios problem （P）. The algorithm works by globally solving problem （P1） that is equivalent to problem （P）, by utilizing linearization technique a linear relaxation programming of the （P1） is then obtained. The proposed algorithm is convergent to the global minimum of （P1） through the successive refinement of linear relaxation of the feasible region of objective function and solutions of a series of linear relaxation programming. Numerical results indicate that the proposed algorithm is feasible and can be used to globally solve nonlinear sum of ratios problems （P）.
文摘The methods of moment and genetic algorithm (GA) are combined to optimize the Yagi Uda antenna array and Log periodic dipole antenna (LPDA) array. The element lengths and spacing are optimized for the Yagi Uda array; while the ratio factor of spacing to length as well as the ratio of length to diameter of the elements are optimized for LPDA array. The results show that the main parameters, such as gain and pattern, have been improved apparently; and the high back lobe level of LPDA can be reduced greatly, therefore, GA is a very competent method for optimizing the linear array as well as in other fields.
基金funded by the National Natural Science Foundation of China(Grant NO.41525010,41807291,41421001,41790443 and 41701458)the Strategic Priority Research Program of Chinese Academy of Sciences(CAS)(Grant NO.XDA23090301 and XDA19040304)+1 种基金the Key Research Program of Frontier Sciences of Chinese Academy of Sciences(CAS)(Grant NO.QYZDY-SSW-DQC019)the Second Tibetan Plateau Scientific Expedition and Research(STEP)program(Grant No.2019QZKK0904)
文摘Bivariate statistical analysis of data-driven approaches is widely used for landslide susceptibility assessment, and the frequency ratio(FR) method is one of the most popular. However, the results of such assessments are dominated by the number of classes and bounds of landslide-related causative factors, and the optimal assessment is unknown. This paper optimizes the frequency ratio method as an example of bivariate statistical analysis for landslide susceptibility mapping based on a case study of the Caiyuan Basin, a region with frequent landslides, which is located in the southeast coastal mountainous area of China. A landslide inventory map containing a total of 1425 landslides(polygons) was produced, in which 70% of the landslides were selected for training purposes, and the remaining were used for validationpurposes. All datasets were resampled to the same 5 m × 5 m/pixel resolution. The receiver operating characteristic(ROC) curves of the susceptibility maps were obtained based on different combinations of dominating parameters, and the maximum value of the areas under the ROC curves(AUCs) as well as the corresponding optimal parameter was identified with an automatic searching algorithm. The results showed that the landslide susceptibility maps obtained using optimal parameters displayed a significant increase in the prediction AUC compared with those values obtained using stochastic parameters. The results also showed that one parameter named bin width has a dominant influence on the optimum. In practice, this paper is expected to benefit the assessment of landslide susceptibility by providing an easy-to-use tool. The proposed automatic approach provides a way to optimize the frequency ratio method or other bivariate statistical methods, which can furtherfacilitate comparisons and choices between different methods for landslide susceptibility assessment.
基金Supported by National Hi-tech Research and Development Program of China(863 Program,Grant No.2006AA110101)
文摘The identification of maximum road friction coefficient and optimal slip ratio is crucial to vehicle dynamics and control.However,it is always not easy to identify the maximum road friction coefficient with high robustness and good adaptability to various vehicle operating conditions.The existing investigations on robust identification of maximum road friction coefficient are unsatisfactory.In this paper,an identification approach based on road type recognition is proposed for the robust identification of maximum road friction coefficient and optimal slip ratio.The instantaneous road friction coefficient is estimated through the recursive least square with a forgetting factor method based on the single wheel model,and the estimated road friction coefficient and slip ratio are grouped in a set of samples in a small time interval before the current time,which are updated with time progressing.The current road type is recognized by comparing the samples of the estimated road friction coefficient with the standard road friction coefficient of each typical road,and the minimum statistical error is used as the recognition principle to improve identification robustness.Once the road type is recognized,the maximum road friction coefficient and optimal slip ratio are determined.The numerical simulation tests are conducted on two typical road friction conditions（single-friction and joint-friction）by using CarSim software.The test results show that there is little identification error between the identified maximum road friction coefficient and the pre-set value in CarSim.The proposed identification method has good robustness performance to external disturbances and good adaptability to various vehicle operating conditions and road variations,and the identification results can be used for the adjustment of vehicle active safety control strategies.
基金supported by the National Natural Science Foundation of China(Grant Nos.41807192,41790441)Innovation Capability Support Program of Shaanxi(Grant No.2020KJXX-005)Natural Science Basic Research Program of Shaanxi(Grant Nos.2019JLM-7,2019JQ-094)。
文摘As threats of landslide hazards have become gradually more severe in recent decades,studies on landslide prevention and mitigation have attracted widespread attention in relevant domains.A hot research topic has been the ability to predict landslide susceptibility,which can be used to design schemes of land exploitation and urban development in mountainous areas.In this study,the teaching-learning-based optimization(TLBO)and satin bowerbird optimizer(SBO)algorithms were applied to optimize the adaptive neuro-fuzzy inference system(ANFIS)model for landslide susceptibility mapping.In the study area,152 landslides were identified and randomly divided into two groups as training(70%)and validation(30%)dataset.Additionally,a total of fifteen landslide influencing factors were selected.The relative importance and weights of various influencing factors were determined using the step-wise weight assessment ratio analysis(SWARA)method.Finally,the comprehensive performance of the two models was validated and compared using various indexes,such as the root mean square error(RMSE),processing time,convergence,and area under receiver operating characteristic curves(AUROC).The results demonstrated that the AUROC values of the ANFIS,ANFIS-TLBO and ANFIS-SBO models with the training data were 0.808,0.785 and 0.755,respectively.In terms of the validation dataset,the ANFISSBO model exhibited a higher AUROC value of 0.781,while the AUROC value of the ANFIS-TLBO and ANFIS models were 0.749 and 0.681,respectively.Moreover,the ANFIS-SBO model showed lower RMSE values for the validation dataset,indicating that the SBO algorithm had a better optimization capability.Meanwhile,the processing time and convergence of the ANFIS-SBO model were far superior to those of the ANFIS-TLBO model.Therefore,both the ensemble models proposed in this paper can generate adequate results,and the ANFIS-SBO model is recommended as the more suitable model for landslide susceptibility assessment in the study area considered due to its excellent accuracy and efficiency.
基金Sponsored by National Natural Science Foundation of China(50901011,10932003)National Basic Research Project of China(2010CB832700)+1 种基金"04"Great Project of Ministry of Industrialization and Information of China(2011ZX04001-21)Fundamental Research Funds for Central Universities of China(DUT12LK03)
文摘Use of hot-stamped high strength steels （HSHSS） not only reduces the vehicle weight, but also improves the crash safety, therefore more and more mentioned steels are used to produce automobile parts. However, there are several problems especially the low ductility and toughness, which have restricted the application of HSHSS in automobile body. Suitable process parameters are very crucial to improve strength and toughness. In order to study the effect of austenization temperature, soaking time and start deformation temperature on strength and toughness of boron steel 22MnB5, an L9 （34） orthogonal experiment which was analyzed by means of comprehensive evaluation was carried out based on Kahn tear method to obtain the value of fracture toughness. The results indicate that the ex- cellent formability, high strength and toughness of boron steel 22MnB5 with 1.6 mm in thickness are obtained when the austenization temperature is in the range of 920- 950 ℃, the soaking time is 1 min and the start deformation temperature is in the range of 650- 700 ℃. The optimal parameters were used for typical hot stamping structural parts tests. Properties of samples such as tear strength, unit initiation energy and ratio of strength to toughness （RST） were improved by 10.91%, 20.32% and 22.17%, respectively. Toughness was increased substantially on the basis of a small decrease of strength.
基金Supported by the National High Technology Research and Development Program of China（2007AA04Z193） the National Natural Science Foundation of China（60974008 60704032）
文摘For high-purity distillation processes,it is difficult to achieve a good direct product quality control using traditional proportional-integral-differential(PID)control or multivariable predictive control technique due to some difficulties,such as long response time,many un-measurable disturbances,and the reliability and precision issues of product quality soft-sensors.In this paper,based on the first principle analysis and dynamic simulation of a distillation process,a new predictive control scheme is proposed by using the split ratio of distillate flow rate to that of bottoms as an essential controlled variable.Correspondingly,a new strategy with integrated control and on-line optimization is developed,which consists of model predictive control of the split ratio,surrogate model based on radial basis function neural network for optimization,and modified differential evolution optimization algorithm. With the strategy,the process achieves its steady state quickly,so more profit can be obtained.The proposed strategy has been successfully applied to a gas separation plant for more than three years,which shows that the strategy is feasible and effective.
基金This research was financially supported by the National Natural Science Foundation of China(Grant Nos.51875466 and 51805436)the China Postdoctoral Science Foundation(Grant No.2019T120941)the China Scholarships Council(Grant No.201806290133).
文摘In this paper,a Double-stage Surrogate-based Shape Optimization(DSSO)strategy for Blended-Wing-Body Underwater Gliders(BWBUGs)is proposed to reduce the computational cost.In this strategy,a double-stage surrogate model is developed to replace the high-dimensional objective in shape optimization.Specifically,several First-stage Surrogate Models(FSMs)are built for the sectional airfoils,and the second-stage surrogate model is constructed with respect to the outputs of FSMs.Besides,a Multi-start Space Reduction surrogate-based global optimization method is applied to search for the optimum.In order to validate the efficiency of the proposed method,DSSO is first compared with an ordinary One-stage Surrogate-based Optimization strategy by using the same optimization method.Then,the other three popular surrogate-based optimization methods and three heuristic algorithms are utilized to make comparisons.Results indicate that the lift-to-drag ratio of the BWBUG is improved by 9.35%with DSSO,which outperforms the comparison methods.Besides,DSSO reduces more than 50%of the time that other methods used when obtaining the same level of results.Furthermore,some considerations of the proposed strategy are further discussed and some characteristics of DSSO are identified.
