A Hybrid Level Set Optimization Design Method of Functionally Graded Cellular Structures Considering Connectivity

With the continuous advancement in topology optimization and additive manufacturing(AM)technology,the capability to fabricate functionally graded materials and intricate cellular structures with spatially varying microstructures has grown significantly.However,a critical challenge is encountered in the design of these structures–the absence of robust interface connections between adjacent microstructures,potentially resulting in diminished efficiency or macroscopic failure.A Hybrid Level Set Method(HLSM)is proposed,specifically designed to enhance connectivity among non-uniform microstructures,contributing to the design of functionally graded cellular structures.The HLSM introduces a pioneering algorithm for effectively blending heterogeneous microstructure interfaces.Initially,an interpolation algorithm is presented to construct transition microstructures seamlessly connected on both sides.Subsequently,the algorithm enables the morphing of non-uniform unit cells to seamlessly adapt to interconnected adjacent microstructures.The method,seamlessly integrated into a multi-scale topology optimization framework using the level set method,exhibits its efficacy through numerical examples,showcasing its prowess in optimizing 2D and 3D functionally graded materials(FGM)and multi-scale topology optimization.In essence,the pressing issue of interface connections in complex structure design is not only addressed but also a robust methodology is introduced,substantiated by numerical evidence,advancing optimization capabilities in the realm of functionally graded materials and cellular structures.

Design and comparison of hybrid multi-bend achromat lattices for HALF storage ring

The Hefei Advanced Light Facility(HALF)proposed by the National Synchrotron Radiation Laboratory is a green-field vacuum ultraviolet and soft X-ray diffraction-limited storage ring light source with a beam energy of 2.2 GeV and emittance goal of less than 100 pm rad.Inspired by the ESRF-EBS hybrid multi-bend achromat(HMBA),SLS-2,and Diamond-II lattices,we have proposed and designed a modified H6BA lattice as the baseline lattice of the HALF storage ring with 20 identical cells and a natural emittance of approximately 86 pm rad.In this paper,three other types of HMBA lattices including two H7BA lattices and a H6BA lattice are designed for HALF with the same number of cells.The main storage ring proper-ties of these four HMBA lattices are compared.Because the intra-beam scattering(IBS)effect is significant in the HALF storage ring,we calculate and compare the equilibrium emittances of the four lattices with IBS included.These comparisons show that the present modified H6BA lattice,which has a relatively low equilibrium emittance and more straight sections,is preferred for the HALF storage ring after a comprehensive consideration.

Optimization of mechanical properties using D-optimal factorial design of experiment: Electromagnetic stir casting process of A357-SiC nanocomposite

Electromagnetic stir casting process of A357-Si C nanocomposite was discussed using the D-optimal design of experiment(DODOE) method. As the main objective, nine random experiments obtained by DX-7 software were performed. By this method, A357-Si C nanocomposites with 0.5, 1.0 and 1.5 wt.% Si C were fabricated at three different frequencies(10, 35 and 60 Hz) in the experimental stage. The microstructural evolution was characterized by scanning electron and optical microscopes, and the mechanical properties were investigated using hardness and roomtemperature uniaxial tensile tests. The results showed that the homogeneous distribution of Si C nanoparticles leads to the microstructure evolution from dendritic to non-dendritic form and a reduction of size by 73.9%. Additionally, based on DODOE, F-values of 44.80 and 179.64 were achieved for yield stress(YS) and ultimate tensile strength(UTS), respectively, implying that the model is significant and the variables(Si C fraction and stirring frequency) were appropriately selected. The optimum values of the Si C fraction and stirring frequency were found to be 1.5 wt.% and 60 Hz, respectively. In this case, YS and UTS for A357-Si C nanocomposites were obtained to be 120 and 188 MPa(57.7% and 57.9 % increase compared with those of the as-cast sample), respectively.

A dilute fluorine-free electrolyte design for high-voltage hybrid aqueous batteries

Fluorinated salts and/or high salt concentrations are usually necessary to produce protective films on the electrodes for high-voltage aqueous batteries,yet these approaches increase the cost,toxicity and reaction resistances of battery.Herein,we report a dilute fluorine-free electrolyte design to overcome this dilemma.By using the LiClO_(4) salt and polyethylene glycol dimethyl ether(PED)solvent and optimizing the LiClO_(4)/PED/H_(2)O molar ratio,we formulate a 1 mol kg^(-1)3 V-class hybrid aqueous electrolyte that enables reversible charge/discharge of 2.5 V LiMn_(2)O_(4)|Li_(4)Ti_(5)O_(12) full cell at both low(0.5C,92.4%capacity retention in 300 cycles)and high(5C,80.4%capacity retention in 2000 cycles)rates.This excellent performance is reached even without the generation of protective film on either anode or cathode as identified by in/ex situ characterizations.The selection of appropriate ingredients that have both high stability and strong interactions with water is critical to widen the potential window of electrolyte while suppressing parasitic reactions on the electrodes.This work suggests that expensive and toxic fluorinate salts are no longer necessary for 3 V-class aqueous electrolytes,boosting the development of low-cost,environmentally-friendly,high-power and high-energy-density aqueous batteries.

Optimization of Proportion and Formulation Process of Jinweng Granule by D-Optimal Mixture Design

[Objectives] To study the optimal proportion and formulation process of Jinweng granule,the physicochemical properties of the optimal preparing process was observed. [Methods] Adopting the D-optimal mixture design method,selecting the mixing ratio of starch,dextrin,fumei powder and lactose as tested factors,and selecting the most significant factor between hygroscopicity,formability,solubility as the evaluation index,the optimal proportion of filler was examined by system experiments. Granularity,solubility,the angle of repose,and critical relative humidity( CRH) were used to evaluate the optimal proportion and formulation process of Jinweng granule. [Results]The optimal prescription of Jinweng granule is extract∶ starch∶ dextrin∶ lactose∶ fumei powder( 1∶ 0. 5∶ 0. 05∶ 0. 3∶ 0. 15),and the binder was consisted of 1% sodium carboxymethylcellulose( CMC) slurry and 3% starch syrup. The CRH of the optimum formulation process of granule is 72%,and the fluidity,solubility and granularity were qualified. [Conclusions] The process model established by D-optimum mixture design has good predictability,and the granule prepared by the optimal proportion has good repeatability,and the granule proportion and formulation process is stable and reliable.

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.

基于Hybrid A^(*)算法的变压器声级巡检系统研究与设计

随着国内变电站数目逐步增加,采用固定式声级监测终端对变压器声级检测的方式已经满足不了日常检测的需求。为解决固定式声级监测终端方式成本高、维护复杂、设备利用率低等问题,该文率先提出了一种变压器声级巡检系统,并设计了最优声级巡检路径。通过场地定位传感器生成变压器场地栅格图信息,采用Hybrid A^(*)算法将场地栅格图信息生成符合国标所要求的最优声级巡检路径检测点;针对所开发的变压器声级巡检装置,采用生成的巡检路径对变压器进行声级测定作业,对测定的声级数据进行分析处理。测试结果表明,该文开发的系统与设计算法的变压器声级巡检时间、检测效率以及数据的采集准确性都优于固定式声级监测终端方式,系统完成变压器声级巡检全过程的成功率可达95%。

Crystalline and amorphous metal sulfide composite electrode materials with long cycle life:Preparation and performance of hybrid capacitors

Crystalline@amorphous NiCo_(2)S_(4)@MoS_(2)(v-NCS@MS)nanostructures were designed and constructed via an ethylene glycol-induced strategy with hydrothermal synthesis and solvothermal method,which simultaneously realized the defect regulation of crystal NiCo_(2)S_(4) in the core.Taking advantage of the flexible protection of an amor-phous shell and the high capacity of a conductive core with defects,the v-NCS@MS electrode exhibited high specif-ic capacity(1034 mAh·g^(-1) at 1 A·g^(-1))and outstanding rate capability.Moreover,a hybrid supercapacitor was assembled with v-NCS@MS as cathode and activated carbon(AC)as anode,which can achieve remarkably high specific energy of 111 Wh·kg^(-1) at a specific power of 219 W·kg^(-1) and outstanding capacity retention of 80.5%after 15000 cycling at different current densities.

复杂建设环境下基于Hybrid A^(*)算法的铁路平面线形绿色优化设计

随着“双碳经济下绿色铁路”理念的兴起,将“绿色生态”融入到铁路平面线路优化已成为近年来的研究热点。本文以铁路建设成本与生态破坏成本的协同优化为目标,引入并改进了一种自动驾驶导航算法(Hybrid A^(*)算法),以适应复杂的铁路设计问题,同时考虑最小曲线半径、最大曲线半径、最短曲线长度、最短夹直线长度、缓和曲线长度等铁路线形约束。研究结果表明:(1)改进后算法以离散网格方式整合外部环境因素,实现渐进式全局探索,获取接近全局最优的铁路线路设计结果;(2)该方法在复杂外部环境约束下,无需预设水平交点位置和数量,可自动生成符合线路-环境耦合约束的优化平面线路方案。

A New D-optimal Design Scheme for the Identification of Cubic Polynomials

In this paper, the limitations of the single cube D-optimal design scheme is studied, and a double cube D-optimal design scheme is suggested in order to overcome the limitations. For a sort of incomplete cubic polynomials, the test design of the identification is developed with this new scheme, and the comparation with the single cube scheme is also given. This scheme is shown to be perfectly suitable for the optimal identification of the complete cubic polynomials.

The Construction of Locally D-Optimal Designs by Canonical Forms to an Extension for the Logistic Model

Logistic regression models for binary response problems are present in a wide variety of industrial, biological, social and medical experiments;therefore, optimum designs are a valuable tool for experimenters, leading to estimators of parameters with minimum variance. Our interest in this contribution is to provide explicit formulae for the D-optimal designs as a function of the unknown parameters for the logistic model where q is an indicator variable. We have considered an experiment based on the dose-response to a fly insecticide in which males and females respond in different ways, proposed in Atkinson et al. (1995) [1]. To find the D-optimal designs, this problem has been reduced to a canonical form.

Series-parallel Hybrid Vehicle Control Strategy Design and Optimization Using Real-valued Genetic Algorithm

Despite the series-parallel hybrid electric vehicle inherits the performance advantages from both series and parallel hybrid electric vehicle, few researches about the series-parallel hybrid electric vehicle have been revealed because of its complex co nstruction and control strategy. In this paper, a series-parallel hybrid electric bus as well as its control strategy is revealed, and a control parameter optimization approach using the real-valued genetic algorithm is proposed. The optimization objective is to minimize the fuel consumption while sustain the battery state of charge, a tangent penalty function of state of charge（SOC） is embodied in the objective function to recast this multi-objective nonlinear optimization problem as a single linear optimization problem. For this strategy, the vehicle operating mode is switched based on the vehicle speed, and an ＂optimal line＂ typed strategy is designed for the parallel control. The optimization parameters include the speed threshold for mode switching, the highest state of charge allowed, the lowest state of charge allowed and the scale factor of the engine optimal torque to the engine maximum torque at a rotational speed. They are optimized through numerical experiments based on real-value genes, arithmetic crossover and mutation operators. The hybrid bus has been evaluated at the Chinese Transit Bus City Driving Cycle via road test, in which a control area network-based monitor system was used to trace the driving schedule. The test result shows that this approach is feasible for the control parameter optimization. This approach can be applied to not only the novel construction presented in this paper, but also other types of hybrid electric vehicles.

Hybrid Data-Driven and Mechanistic Modeling Approaches for Multiscale Material and Process Design

The world’s increasing population requires the process industry to produce food,fuels,chemicals,and consumer products in a more efficient and sustainable way.Functional process materials lie at the heart of this challenge.Traditionally,new advanced materials are found empirically or through trial-and-error approaches.As theoretical methods and associated tools are being continuously improved and computer power has reached a high level,it is now efficient and popular to use computational methods to guide material selection and design.Due to the strong interaction between material selection and the operation of the process in which the material is used,it is essential to perform material and process design simultaneously.Despite this significant connection,the solution of the integrated material and process design problem is not easy because multiple models at different scales are usually required.Hybrid modeling provides a promising option to tackle such complex design problems.In hybrid modeling,the material properties,which are computationally expensive to obtain,are described by data-driven models,while the well-known process-related principles are represented by mechanistic models.This article highlights the significance of hybrid modeling in multiscale material and process design.The generic design methodology is first introduced.Six important application areas are then selected:four from the chemical engineering field and two from the energy systems engineering domain.For each selected area,state-ofthe-art work using hybrid modeling for multiscale material and process design is discussed.Concluding remarks are provided at the end,and current limitations and future opportunities are pointed out.

Rational Design of Hybrid Peptides: A Novel Drug Design Approach

Peptides play crucial roles in various physiological and pathological processes. Consequently, the investigation of peptide-based drugs is a highlight in the research and development of new drugs. However, natural peptides are not always ideal choices for clinical application due to their limited number and sometimes cytotoxicity to normal cells. Aiming to gain stronger or specific or novel biological effects and overcome the disadvantages of natural peptides, artificial hybrid peptides have been designed by combining the sequence of two or more different peptides with varied biological functions. Compared to natural peptides, hybrid peptides have shown better therapeutic potentials against bacteria, tumors, and metabolic diseases. In this review, design strategies, structure features and recent development of hybrid peptides are summarized;future directions for the research and development of hybrid peptide drugs are also discussed.

Conceptual design of oil palm fibre reinforced polymer hybrid composite automotive crash box using integrated approach

A hybrid conceptual design approach was introduced in this study to develop a conceptual design of oil palm polymer composite automotive crash box(ACB). A combination of theory of inventive problem solving(TRIZ), morphological charts and biomimetics was applied where the foremost requirements in terms of the material characteristics, function specifications, force identification, root cause analysis, geometry profile and design selection criteria were considered. The strategy was to use creations of nature to inspire five innovative conceptual designs of the ACB structure and the AHP method was applied to perform the pairwise analysis of selecting the best ACB conceptual design. A new conceptual design for a composite ACB was conceived bearing in mind the properties of natural fibre, unlike those of conventional materials such as steel alloys and aluminium alloys. The design with the highest ranking(26.6 %) was chosen as the final conceptual design, which was the one with a honeycomb structure for the outermost profile, reinforced with a spider web structure inside the part, supported by fibre foam structure extracted from the woodpecker sponge tissue at the centre to maximize the energy absorption capability. The new design could solve the problem of bending collapse which is a major cause of failure to absorb maximum impact energy for ACB during collision. However, the final conceptual design will still need several modifications for production and assembly purposes, which will be completed in a further study.

Design and Fuel Consumption Optimization for a Bio-Inspired Semi-floating Hybrid Vehicle

Based on a bionic concept and combing air-cushion techniques and track driving mechanisms, a novel semi-floating hybrid concept vehicle is proposed to meet the transportation requirements on soft terrain. First, the vehicle scheme and its improved duel-spring flexible suspension design are described. Then, its fuel consumption model is proposed accordingly with respect to two vehicle operating parameters. Aiming at minimizing the fuel consumption, two Genetic Algorithms （GAs） are designed and implemented. For the initial one （GA-1）, despite getting an acceptable result, there still existed some problems in its optimiza- tion process. Based on an analysis of the defects of GA-1, an improved algorithm GA-2 was developed whose effectiveness and stability were embodied in the optimization process and results. The proposed design scheme and optimization approaches can provide valuable references for this new kind of vehicle with industry, military or scientific exploitations, etc. promising applications in the areas of agriculture, petroleum industry, military or scientific explaitations, etc.

Optimization of fermentation conditions for P450 BM-3 monooxygenase production by hybrid design methodology

Factorial design and response surface techniques were used to design and optimize increasing P450 BM-3 expression in E, coll. Operational conditions for maximum production were determined with twelve parameters under consideration： the concentration of FeCl3, induction at OD578 （optical density measured at 578 nm）, induction time and inoculum concentration. Initially, Plackett-Burman （PB） design was used to evaluate the process variables relevant in relation to P450 BM-3 production. Four statistically significant parameters for response were selected and utilized in order to optimize the process. With the 416C model of hybrid design, response surfaces were generated, and P450 BM-3 production was improved to 57.90×10^-3 U/ml by the best combinations of the physicochemical parameters at optimum levels of 0,12 mg/L FeCl3, inoculum concentration of 2.10%, induction at OD578 equal to 1.07, and with 6.05 h of induction.

APPLICATION OF HYBRID GENETIC ALGORITHM IN AEROELASTIC MULTIDISCIPLINARY DESIGN OPTIMIZATION OF LARGE AIRCRAFT

The genetic/gradient-based hybrid algorithm is introduced and used in the design studies of aeroelastic optimization of large aircraft wings to attain skin distribution,stiffness distribution and design sensitivity.The program of genetic algorithm is developed by the authors while the gradient-based algorithm borrows from the modified method for feasible direction in MSC/NASTRAN software.In the hybrid algorithm,the genetic algorithm is used to perform global search to avoid to fall into local optima,and then the excellent individuals of every generation optimized by the genetic algorithm are further fine-tuned by the modified method for feasible direction to attain the local optima and hence to get global optima.Moreover,the application effects of hybrid genetic algorithm in aeroelastic multidisciplinary design optimization of large aircraft wing are discussed,which satisfy multiple constraints of strength,displacement,aileron efficiency,and flutter speed.The application results show that the genetic/gradient-based hybrid algorithm is available for aeroelastic optimization of large aircraft wings in initial design phase as well as detailed design phase,and the optimization results are very consistent.Therefore,the design modifications can be decreased using the genetic/gradient-based hybrid algorithm.

Configuration design and control of hybrid tracked vehicle with three planetary gear sets

The hybrid tracked vehicles(HTV)usually adopt series hybrid powertrain with extra steering mechanism,which has relatively low transmission efficiency and reduces the flexibility of structural arrangement.To overcome the disadvantages,a new kind of single-mode powertrain has been proposed.The power-split hybrid powertrain is composed of three planetary gear(PG)sets connected to one engine,left and right track outputs,and three motors.The proposed powertrain can realize steering while going forward by controlling the output torque on each side without extra steering mechanism or steering shaft.Due to the diversity of the connection way between components and planetary gear sets,a rapid configuration design approach is proposed for the design selection of HTV.The automated dynamic modelling method can show the one-to-one correspondence with the selected feasible groups by establishing two characteristic matrices,which is more simple than other researches.The analytically-based method is proposed to classify all possible connection designs into several groups to decrease the searching scope with improved design efficiency.Finally,the optimal control strategy is used to find the design with optimal fuel economy under typical condition of HTV.The case study is implemented by the proposed design approach which demonstrates better design performances compared with the existing series-hybrid HTV.

3D Digital Design of Cranes' Structures Based on Hybrid Software Architecture

3D digital design for cranes’ structures based on hybrid software architecture of Client/Server and Browser/Server is introduced in this paper. Based on Pro/ENGINEER platform,3D parametric model family is built to allow generation of feasible configurations of cranes’ structures in Client/Server framework. Taking use of Visual C++,the second exploiting software kit provided by Pro/ENGINEER and ANSYS GUI/APDL modeling patterns,an integration method of 3D CAD and CAE is achieved,which includes regeneration of 3D parametric model,synchronous updating and analysis of FEA model. As in Browser/Server framework,the 3D CAD models of parts,components and the whole structure could also be displayed in the customer’s browser in VRML format.