Finding Symbolic and All Numerical Solutions for Design Optimization Based on Monotonicity Analysis and Solving Polynomial Systems

A method for determining symbolic and all numerical solutions in design optimization based on monotonicity analysis and solving polynomial systems is presented in this paper. Groebner Bases of the algebraic system equivalent to the subproblem of the design optimization is taken as the symbolic (analytical) expression of the optimum solution for the symbolic optimization, i.e. the problem with symbolic coefficients. A method based on substituting and eliminating for determining Groebner Bases is also proposed, and method for finding all numerical optimum solutions is discussed. Finally an example is given, demonstrating the strategy and efficiency of the method.

Stability analysis of underground engineering based on multidisciplinary design optimization

Aiming at characteristics of underground engineering,analyzed the feasibility of Multidisciplinary Design Optimization (MDO) used in underground engineering,and put forward a modularization-based MDO method and the idea of MDO to resolve problems in stability analysis,proving the validity and feasibility of using MDO in underground engi- neering.Characteristics of uncertainty,complexity and nonlinear become bottle-neck to carry on underground engineering stability analysis by MDO.Therefore,the application of MDO in underground engineering stability analysis is still at a stage of exploration,which need some deep research.

An Efficient Method for Reliability-based Multidisciplinary Design Optimization

Design for modem engineering system is becoming multidisciplinary and incorporates practical uncertainties; therefore, it is necessary to synthesize reliability analysis and the multidisciplinary design optimization （MDO） techniques for the design of complex engineering system. An advanced first order second moment method-based concurrent subspace optimization approach is proposed based on the comparison and analysis of the existing multidisciplinary optimization techniques and the reliability analysis methods. It is seen through a canard configuration optimization for a three-surface transport that the proposed method is computationally efficient and practical with the least modification to the current deterministic optimization process.

A Study of Design Optimization Using Response Surface Analysis and Fabricaiton MEMS Probe Tip

In semiconductor manufacturing process, probe station that is testing equipment is important. Inspection step is for detecting defects on semiconductor before the packaging. Probe card is a part of probe station and contains probe tip that contacts to semiconductor. Through probe tip, it can inspect defects of semiconductor. In this paper, optimization method is used with response surface analysis to design MEMS type probe tip. And fabricating probe tip uses maskless lithography, electro-plating and lapping process.

EFFICIENT METHOD FOR MULTIDISCIPLINARY DESIGN OPTIMIZATION BY CONSIDERING UNCERTAINTY

A new reliability-based multidisciplinary design optimization （RBMDO） framework is proposed by combining the single-loop-based reliability analysis （SLBRA） method with multidisciplinary feasible （MDF） method. The Kriging approximate model with updating is introduced to reduce the computational cost of MDF caused by the complex structure. The computational efficiency is remarkably improved as the lack of iterative process during reliability analysis. Special attention is paid to a turbine blade design optimization by adopting the proposed method. Results show that the method is much more efficient than the commonly used double-loop based RBMDO method. It is feasible and efficient to apply the method to the engineering design.

Uncertainty-based Multidisciplinary Design Optimization using An Approximated Second-Order Reliability Analysis Strategy

In uncertainty-based multidisciplinary design optimization(UBMDO),all reliability limitation factors are maintained due to minimize the cost target function.There are many reliability evaluation methods for reliability limitation factors.The second-order reliability method(SORM)is a powerful most possible point(MPP)-based method.It can provide an accurate estimation of the failure probability of a highly nonlinear limit state function despite its large curvature.But the Hessian calculation is necessary in SORM,which results in a heavy computational cost.Recently,an efficient approximated second-order reliability method(ASORM)is proposed.The ASORM uses a quasi-Newton method to close to Hessian without the direct calculation of Hessian.To further improve the UBMDO efficiency,we also introduce the performance measure approach(PMA)and the sequential optimization and reliability assessment(SORA)strategy.To solve the optimization design problem of a turbine blade,the formula of MDO with ASORM under the SORA framework(MDO-ASORM-SORA)is proposed.

Robust Design Optimization Method for Centrifugal Impellers under Surface Roughness Uncertainties Due to Blade Fouling

Blade fouling has been proved to be a great threat to compressor performance in operating stage. The current researches on fouling-induced performance degradations of centrifugal compressors are based mainly on simplified roughness models without taking into account the realistic factors such as spatial non-uniformity and randomness of the fouling-induced surface roughness. Moreover, little attention has been paid to the robust design optimization of centrifugal compressor impellers with considerations of blade fouling. In this paper, a multi-objective robust design optimization method is developed for centrifugal impellers under surface roughness uncertainties due to blade fouling. A three-dimensional surface roughness map is proposed to describe the nonuniformity and randomness of realistic fouling accumulations on blades. To lower computational cost in robust design optimization, the support vector regression（SVR） metamodel is combined with the Monte Carlo simulation（MCS） method to conduct the uncertainty analysis of fouled impeller performance. The analyzed results show that the critical fouled region associated with impeller performance degradations lies at the leading edge of blade tip. The SVR metamodel has been proved to be an efficient and accurate means in the detection of impeller performance variations caused by roughness uncertainties. After design optimization, the robust optimal design is found to be more efficient and less sensitive to fouling uncertainties while maintaining good impeller performance in the clean condition. This research proposes a systematic design optimization method for centrifugal compressors with considerations of blade fouling, providing a practical guidance to the design of advanced centrifugal compressors.

Robust Design Optimization and Improvement by Metamodel

The robust design optimization(RDO)is an effective method to improve product performance with uncertainty factors.The robust optimal solution should be not only satisfied the probabilistic constraints but also less sensitive to the variation of design variables.There are some important issues in RDO,such as how to judge robustness,deal with multi-objective problem and black-box situation.In this paper,two criteria are proposed to judge the deterministic optimal solution whether satisfies robustness requirment.The robustness measure based on maximum entropy is proposed.Weighted sum method is improved to deal with the objective function,and the basic framework of metamodel assisted robust optimization is also provided for improving the efficiency.Finally,several engineering examples are used to verify the advantages.

Review: Recent Developments in the Uncertainty-Based Aero-Structural Design Optimization for Aerospace Vehicles

With the increasing demands of aircraft design,the traditional deterministic design can hardly meet the requirements of fine design optimization because uncertainties may exist throughout the whole lifecycle of the aircraft. To enhance the robustness and reliability of the aircraft design, Uncertainty Multidisciplinary Design Optimization( UM DO) has been developing for a long time. This paper presents a comprehensive reviewof UM DO methods for aerospace vehicles,including basic UM DO theory and research progress of its application in aerospace vehicle design. Firstly,the UM DO theory is preliminarily introduced,with giving the definition and classification of uncertainty as well as its sources corresponding to the aircraft design. Then following the UM DO solving process, the application in different coupled disciplines is separately discussed during the aircraft design process,specifically clarifying the UM DO methods for aerostructural optimization. Finally,the main challenges of UM DO and the future research trends are given.

Structural Design Optimization of a Vertical Axis Wind Turbine for Seismic Qualification and Lightweight

Recently, there is a growing interest in seismic qualification of ridges, buildings and mechanical equipment worldwide due to increase of accidents caused by earthquake. Severe earthquake can bring serious problems in the wind turbines and eventually lead to an interruption to their electric power supply. To overcome and prevent these undesirable problems, structural design optimization of a small vertical axis wind turbine has performed, in this study, for seismic qualification and lightweight by using a Genetic Algorithm (GA) subject to some design constraints such as the maximum stress limit, maximum deformation limit, and seismic acceleration gain limit. Also, the structural design optimizations were conducted for the four different initial design variable sets to confirm robustness of the optimization algorithm used. As a result, all the optimization results for the 4 different initial designs showed good agreement with each other properly. Thus the structural design optimization of a small vertical-axis wind turbine could be successfully accomplished.

Design optimization of a torpedo shell structure

An optimized methodology to design a more robust torpedo shell is proposed. The method has taken into account reliability requirements and controllable and uncontrollable factors such as geometry, load, material properties, manufacturing processes, installation, etc. as well as human and environmental factors. The result is a more realistic shell design. Our reliability optimization design model was developed based on sensitivity analysis. Details of the design model are given in this paper. An example of a torpedo shell design based on this model is given and demonstrates that the method produces designs that are more effective and reliable than traditional torpedo shell designs. This method can be used for other torpedo system designs.

Vibration Control of the Rail Grinding Vehicle with Abrasive Belt Based on Structural Optimization and Lightweight Design

As a new grinding and maintenance technology,rail belt grinding shows significant advantages in many applications The dynamic characteristics of the rail belt grinding vehicle largely determines its grinding performance and service life.In order to explore the vibration control method of the rail grinding vehicle with abrasive belt,the vibration response changes in structural optimization and lightweight design are respectively analyzed through transient response and random vibration simulations in this paper.Firstly,the transient response simulation analysis of the rail grinding vehicle with abrasive belt is carried out under operating conditions and non-operating conditions.Secondly,the vibration control of the grinding vehicle is implemented by setting vibration isolation elements,optimizing the structure,and increasing damping.Thirdly,in order to further explore the dynamic characteristics of the rail grinding vehicle,the random vibration simulation analysis of the grinding vehicle is carried out under the condition of the horizontal irregularity of the American AAR6 track.Finally,by replacing the Q235 steel frame material with 7075 aluminum alloy and LA43M magnesium alloy,both vibration control and lightweight design can be achieved simultaneously.The results of transient dynamic response analysis show that the acceleration of most positions in the two working conditions exceeds the standard value in GB/T 17426-1998 standard.By optimizing the structure of the grinding vehicle in three ways,the average vibration acceleration of the whole car is reduced by about 55.1%from 15.6 m/s^(2) to 7.0 m/s^(2).The results of random vibration analysis show that the grinding vehicle with Q235 steel frame does not meet the safety conditions of 3σ.By changing frame material,the maximum vibration stress of the vehicle can be reduced from 240.7 MPa to 160.0 MPa and the weight of the grinding vehicle is reduced by about 21.7%from 1500 kg to 1175 kg.The modal analysis results indicate that the vibration control of the grinding vehicle can be realized by optimizing the structure and replacing the materials with lower stiffness under the premise of ensuring the overall strength.The study provides the basis for the development of lightweight,diversified and efficient rail grinding equipment.

Uncertainty analysis and probabilistic design optimization of hybrid rocket motors for manned lunar landing

To obtain a conceptual design for a hybrid rocket motor(HRM)to be used as the Ascent Propulsion System in the Apollo lunar module,the deterministic design optimization(DDO)method is applied to the HRM design.Based on the results of an uncertainty analysis of HRMs,an uncertainty-based design optimization(UDO)method is also adopted to improve the design reliability.The HRM design process,which is a multidisciplinary system,is analyzed,and a mathematical model for the system design is established to compute the motor performance from the input parameters,including the input variables and model parameters.The input parameter uncertainties are quantified,and a sensitivity analysis of the model parameter uncertainties is conducted to identify the most important model parameter uncertainties for HRMs.The DDO and probabilistic UDO methods are applied to conceptual designs for an HRM to be used as a substitute for the liquid rocket motor(LRM)of the Ascent Propulsion System.The conceptual design results show that HRMs have several advantages as an alternative to the LRM of the Ascent Propulsion System,including nontoxic propellant combination,small motor volume,and comparable functions,such as restarting and throating.Comparisons of the DDO and UDO results indicate that the UDO method achieves more robust and reliable optimal designs than the DDO method.The probabilistic UDO method can be used to develop better conceptual designs for HRMs.

Reliability-based design optimization of offshore wind turbine support structures using RBF surrogate model

An efficient reliability-based design optimization method for the support structures of monopile offshore wind turbines is proposed herein.First,parametric finite element analysis(FEA)models of the support structure are established by considering stochastic variables.Subsequently,a surrogate model is constructed using a radial basis function(RBF)neural network to replace the time-consuming FEA.The uncertainties of loads,material properties,key sizes of structural components,and soil properties are considered.The uncertainty of soil properties is characterized by the variabilities of the unit weight,friction angle,and elastic modulus of soil.Structure reliability is determined via Monte Carlo simulation,and five limit states are considered,i.e.,structural stresses,tower top displacements,mudline rotation,buckling,and natural frequency.Based on the RBF surrogate model and particle swarm optimization algorithm,an optimal design is established to minimize the volume.Results show that the proposed method can yield an optimal design that satisfies the target reliability and that the constructed RBF surrogate model significantly improves the optimization efficiency.Furthermore,the uncertainty of soil parameters significantly affects the optimization results,and increasing the monopile diameter is a cost-effective approach to cope with the uncertainty of soil parameters.

Uncertainty analysis and design optimization of hybrid rocket motor powered vehicle for suborbital flight

Abstract In this paper, we propose an uncertainty analysis and design optimization method and its applications on a hybrid rocket motor （HRM） powered vehicle. The multidisciplinary design model of the rocket system is established and the design uncertainties are quantified. The sensitivity anal- ysis of the uncertainties shows that the uncertainty generated from the error of fuel regression rate model has the most significant effect on the system performances. Then the differences between deterministic design optimization （DDO） and uncertainty-based design optimization （UDO） are discussed. Two newly formed uncertainty analysis methods, including the Kriging-based Monte Carlo simulation （KMCS） and Kriging-based Taylor series approximation （KTSA）, are carried out using a global approximation Kriging modeling method. Based on the system design model and the results of design uncertainty analysis, the design optimization of an HRM powered vehicle for suborbital flight is implemented using three design optimization methods： DDO, KMCS and KTSA. The comparisons indicate that the two UDO methods can enhance the design reliability and robustness. The researches and methods proposed in this paper can provide a better way for the general design of HRM powered vehicles.

Design Optimization of Ocean Thermal Energy Conversion(OTEC)Considering the Off-Design Condition

The comprehensive optimization of thermodynamic and economic performances is significant for the engineering application of ocean thermal energy conversion(OTEC).Motivated by this,this paper develops a thermo-economic OTEC model and conducts a sensitivity analysis of the OTEC system concerning its thermodynamic and economic performances.Specifically,the impact of warm-seawater temperature and cold-seawater pumping depth on the net thermal efficiency and the total investment cost are investigated.The results indicate that,an increase in warm-seawater temperature and cold-seawater pumping depth can improve the net thermal efficiency and a higher installed capacity is beneficial to the system economics.Building on these,a design optimization method with considering the on-design and off-design conditions is proposed in this paper,and the dynamic variation of warm-seawater temperature are considered in this method.In multi-objective optimization procedure,with the objective functions being the average net thermal efficiency and unit power cost within the operational cycle,the non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ) is employed to maximize the net thermal efficiency and minimize the unit power investment cost,resulting in the Pareto front.The net thermal efficiencies of OTEC systems using ammonia and R245fa as working fluids are 4.13% and 3.8%,respectively.This represents an improvement of 19.4% and 57.0%,respectively,compared to traditional optimization methods that do not account for off-design conditions.

Saddlepoint Approximation Method in Reliability Analysis:A Review

The escalating need for reliability analysis(RA)and reliability-based design optimization(RBDO)within engineering challenges has prompted the advancement of saddlepoint approximationmethods(SAM)tailored for such problems.This article offers a detailed overview of the general SAM and summarizes the method characteristics first.Subsequently,recent enhancements in the SAM theoretical framework are assessed.Notably,the mean value first-order saddlepoint approximation(MVFOSA)bears resemblance to the conceptual framework of the mean value second-order saddlepoint approximation(MVSOSA);the latter serves as an auxiliary approach to the former.Their distinction is rooted in the varying expansion orders of the performance function as implemented through the Taylor method.Both the saddlepoint approximation and third-moment(SATM)and saddlepoint approximation and fourth-moment(SAFM)strategies model the cumulant generating function(CGF)by leveraging the initial random moments of the function.Although their optimal application domains diverge,each method consistently ensures superior relative precision,enhanced efficiency,and sustained stability.Every method elucidated is exemplified through pertinent RA or RBDO scenarios.By juxtaposing them against alternative strategies,the efficacy of these methods becomes evident.The outcomes proffered are subsequently employed as a foundation for contemplating prospective theoretical and practical research endeavors concerning SAMs.The main purpose and value of this article is to review the SAM and reliability-related issues,which can provide some reference and inspiration for future research scholars in this field.

Multi-parameter Sensitivity Analysis and Application Research in the Robust Optimization Design for Complex Nonlinear System

The current research of complex nonlinear system robust optimization mainly focuses on the features of design parameters, such as probability density functions, boundary conditions, etc. After parameters study, high-dimensional curve or robust control design is used to find an accurate robust solution. However, there may exist complex interaction between parameters and practical engineering system. With the increase of the number of parameters, it is getting hard to determine high-dimensional curves and robust control methods, thus it＇s difficult to get the robust design solutions. In this paper, a method of global sensitivity analysis based on divided variables in groups is proposed. By making relevant variables in one group and keeping each other independent among sets of variables, global sensitivity analysis is conducted in grouped variables and the importance of parameters is evaluated by calculating the contribution value of each parameter to the total variance of system response. By ranking the importance of input parameters, relatively important parameters are chosen to conduct robust design analysis of the system. By applying this method to the robust optimization design of a real complex nonlinear system-a vehicle occupant restraint system with multi-parameter, good solution is gained and the response variance of the objective function is reduced to 0.01, which indicates that the robustness of the occupant restraint system is improved in a great degree and the method is effective and valuable for the robust design of complex nonlinear system. This research proposes a new method which can be used to obtain solutions for complex nonlinear system robust design.

Probabilistic-Ellipsoid Hybrid Reliability Multi-Material Topology Optimization Method Based on Stress Constraint

This paper proposes a multi-material topology optimization method based on the hybrid reliability of the probability-ellipsoid model with stress constraint for the stochastic uncertainty and epistemic uncertainty of mechanical loads in optimization design.The probabilistic model is combined with the ellipsoidal model to describe the uncertainty of mechanical loads.The topology optimization formula is combined with the ordered solid isotropic material with penalization(ordered-SIMP)multi-material interpolation model.The stresses of all elements are integrated into a global stress measurement that approximates the maximum stress using the normalized p-norm function.Furthermore,the sequential optimization and reliability assessment(SORA)is applied to transform the original uncertainty optimization problem into an equivalent deterministic topology optimization(DTO)problem.Stochastic response surface and sparse grid technique are combined with SORA to get accurate information on the most probable failure point(MPP).In each cycle,the equivalent topology optimization formula is updated according to the MPP information obtained in the previous cycle.The adjoint variable method is used for deriving the sensitivity of the stress constraint and the moving asymptote method(MMA)is used to update design variables.Finally,the validity and feasibility of the method are verified by the numerical example of L-shape beam design,T-shape structure design,steering knuckle,and 3D T-shaped beam.

The Structural Design, Simulation Analysis and Parameter Optimization of the Cheetah Robot's Lumbar Vertebrae

The quality of skeleton system for the cheetah robot goes hand in hand with its bionic result of its shape, structure and functions. In view of the skeleton system constitution and structural characteristic of the cheetah, the team applied structure design, stimulation analysis and parameter optimization to developing the cheetah robot. In addition, after the invention of cheetah robot＇s anterior lumbar vertebra based on its functional attribute and connectivity attribute, the Solidworks Simulation was utilized to analyze the design, according to which improvement on the lumbar vertebra was made. Plus, the advantages of the CAD and CAE made the high efficiency of design work and high quality of the cheetah robot possible.