Design of a novel modular self-reconfigurable robot capable of self-turning

To solve the problem of inaccurate angle adjustment in the self-assembly process, a new homogenous hybrid modular self-reconfigurable robot-Xmobot is designed. Each module has four rotary joints and a self-turning mechanism. With the proposed self-turning mechanism, the angle adjusting accuracy of the module is increased to 2°, and the relative position adjusting efficiency of the module in the self-assembly process is also improved. The measured maximum moving distance of the proposed module in a gait cycle is 11.0 cm. Aiming at the multiple degree of freedom （MDOF） feature of the proposed module, a motion controller based on the central pattern generator （CPG） is proposed. The control of five joints of the module only requires two CPG oscillators. The CPG-based motion controller has three basic output modes, i. e. the oscillation, the rotation, and the fixed modes. The serpentine and the wheeled movements of the H-shaped robot are simulated, respectively. The results show that the average velocities of the two movements are 15. 2 and 20. 1 m/min, respectively. The proposed CPG-based motion controller is evaluated to be effective.

Structure Design Considerations of a Sub-50nm Self-Aligned Double-Gate MOSFET

A comprehensive way to design a sub 50nm SADG MOSFET with the ability of being fabricated by improved CMOS technique is described.Under this way,the gate length and thickness of Si island of DG device show many different scaling limits for various elements.Meanwhile,the spacer insulator shows a kind of width thickness on device drain current and circuit speed.A model about that effect is developed and offers design consideration for future.A new design of channel doping profile,called SCD,is also discussed here in detail.The DG device with SCD can achieve a good balance between the volume inversion operation mode and the control of V th .Finally,a guideline to make a SADG MOSFET is presented.

水田动力底盘逆向建模与质心验证——基于Geomagic Design X

针对目前农业机械仿真和优化模型精度不高的问题,提出了一种构建精确模型的逆向建模方法。应用光学扫描仪采集点云数据,基于Geomagic Design X处理点云数据并重构零部件模型,在SolidWorks中完成水田动力底盘的装配。以VP6D-CQ型水田动力底盘为例,将测得的实际质心位置与所建的模型质心位置进行比较,并对提出的逆向建模方法进行了试验验证以及误差分析。结果表明:总质量、x坐标、y坐标、z坐标的误差值分别为4.55%、3.62%、2.23%、4.81%,误差值均在5%内。此方法可构建准确的三维模型,为后续仿真优化数据精确性奠定了基础,与传统的研发相比较,可缩短农业机械研发周期、降低设计成本。

App Designer辅助教学方法探索与实践——以软件无线电课程为例

软件无线电作为通信学科的必修课程,具有承上启下的重要作用。因课程原理抽象、理论公式复杂,学员在学习过程存在理解掌握难、实践应用难等问题。通过对当前软件无线电教学过程中存在的不足与困难进行分析,提出利用MATLAB App Designer辅助课程教学,从教学准备、课堂互动、自主实验、反馈提升四个方面开展课程教学改革。实践表明,该方法对于提升学员的工程思维、系统思维具有显著效果,同时可以增强学员理论联系实际的能力。

SELF-ORGANIZED SEMANTIC FEATURE EVOLUTION FOR AXIOMATIC DESIGN

Aiming at the problem existing in the computer aided design process that how to express the design intents with high-level engineering terminologies, a mechanical product self-organized semantic feature evolution technology for axiomatic design is proposed, so that the constraint relations between mechanical parts could be expressed in a semantic form which is more suitable for designers. By describing the evolution rules for semantic constraint information, the abstract expression of design semantics in mechanical product evolution process is realized and the constraint relations between parts are mapped to the geometric level from the semantic level; With semantic feature relation graph, the abstract semantic description, the semantic relative structure and the semantic constraint information are linked together; And the methods of semantic feature self-organized evolution are classified. Finally, combining a design example of domestic high-speed elevator, how to apply the theory to practical product development is illustrated and this method and its validity is described and verified. According to the study results, the designers are able to represent the design intents at an advanced semantic level in a more intuitional and natural way and the automation, recursion and visualization for mechanical product axiomatic design are also realized.

OPTIMIZING DESIGN OF MECHANICAL SELF-CENTERING DEVICE FOR SUSPENSION HEIGHT

Firstly, in view of the respective defects of existing self-centering devices for vehicle suspension height, the design scheme of the proposed mechanical self-centering device for suspension height is described. Taking the rear suspension of a certain light bus as a research example, the structures and parameters of the novel device are designed and ascertained. Then, the road excitation models, the performance evaluation indexes and the half-vehicle model are built, the simulation outputs of time and frequency domain are obtained with the road excitations of random and pulse by using MATLAB/Simulink software. So the main characteristics of the self-centering suspension are presented preliminarily. Finally, a multi-objective parameter design optimization model for the self-centering device is built by weighted sum approach, and optimal solution is obtained by adopting complex approach. The relevant choosing-type parameters for self-centering device components are deduced by using discrete variable optimal method, and the optimal results are verified and analyzed. So the performance potentials of the self-centering device are exerted fully in condition of ensuring overall suspension performances.

Improving self-assembly quality of colloidal crystal guided by statistical design of experiments

A versatile and reliable approach is created to fabricate wafer-scale colloidal crystal that consists of a monolayer of hexagonally close-packed polystyrene （PS） spheres. Making wafer-scale colloidal crystal is usually challenging, and it lacks a general theoretical guidance for experimental approaches. To obtain the optimal conditions for self-assembly, a systematic statistical design and analysis method is utilized here, which applies the pick-the-winner rule. This new method combines spin-coating and thermal treatment, and introduces a mixture of glycol and ethanol as a dispersion system to assist self-assembly. By controlling the parameters of self-assembly, we improve the quality of colloidal crystal and reduce the effect of noise on the experiment. To our best knowledge, we are first to pave this path to harvest colloidal crystals. Importantly, a theoretical analysis using an energy landscape base on our process is also developed to provide insights into the PS spheres＇ self-assembly.

Architecture Design and Interface Engineering of Self-assembly VS_(4)/rGO Heterostructures for Ultrathin Absorbent

The employment of microwave absorbents is highly desirable to address the increasing threats of electromagnetic pollution.Importantly,developing ultrathin absorbent is acknowledged as a linchpin in the design of lightweight and flexible electronic devices,but there are remaining unprecedented challenges.Herein,the self-assembly VS_(4)/rGO heterostructure is constructed to be engineered as ultrathin microwave absorbent through the strategies of architecture design and interface engineering.The microarchitecture and heterointerface of VS_(4)/rGO heterostructure can be regulated by the generation of VS_(4) nanorods anchored on rGO,which can effectively modulate the impedance matching and attenuation constant.The maximum reflection loss of 2VS_(4)/rGO40 heterostructure can reach−43.5 dB at 14 GHz with the impedance matching and attenuation constant approaching 0.98 and 187,respectively.The effective absorption bandwidth of 4.8 GHz can be achieved with an ultrathin thickness of 1.4 mm.The far-reaching comprehension of the heterointerface on microwave absorption performance is explicitly unveiled by experimental results and theoretical calculations.Microarchitecture and heterointerface synergistically inspire multi-dimensional advantages to enhance dipole polarization,interfacial polarization,and multiple reflections and scatterings of microwaves.Overall,the strategies of architecture design and interface engineering pave the way for achieving ultrathin and enhanced microwave absorption materials.

Design of Full-Ocean-Depth Self-Floating Sampler and Analysis of Factors Affecting Core Penetration Depth

The hadal zone(ocean depths of 6 – 11 km) is one of the least-understood habitats on Earth because of its extreme conditions such as high pressure, darkness, and low temperature. With the development of deep-sea vehicles such as China's 7000 m manned submersible Jiaolong, abyssal science has received greater attention. For decades, gravity-piston corers have been widely used to collect loose subsea-sediment long-core samples. However, the weight and length of the gravity sampler cables and the operating environment limit sampling capacity at full ocean depths. Therefore, a new self-floating sediment sampler with a spring-loaded auto-trigger release and that incorporates characteristics from traditional gravity-driven samplers is designed. This study analyzes the process by which a gravity-piston corer penetrates the sediment and the factors that affect it. A formula for obtaining the penetration depth is deduced. A method of optimizing the sampling depth is then developed based on structure design and parametric factor modeling. The parameters considered in the modeling include the sampling depth, balance weight, ultimate stress friction coefficient, dimensions of the sampler, and material properties. Thus, a new deep-sea floating parametric sampler designed based on virtual prototyping is proposed. Accurate values for all the design factors are derived from calculations based on the conservation of energy with penetration depth, analyses of the factors affecting the penetration depth, and analyses of the pressure bar stability. Finally, experimental data are used to verify the penetration-depth function and to provide theoretical guidance for the design of sediment samplers.

Robust design of self-starting drains using Random Forest

Groundwater lowering is one of the most important countermeasures to avoid the risk of rainfall-triggered landslides.However,the long-term reliability of many drainage methods is often a matter of concern since the drains may easily get clogged.A new hydraulic-driven self-starting drainage method is presented in this paper.In the proposed Random Forest(RF)based robust design approach for the selfstarting drains,the datasets are generated using an automatically controlled numerical modeling technology.The deterministic analysis is carried out based on uncertain soil parameters and the specific designs selected using Uniform Design(UD).The ensemble of RF models is applied in the design process to improve computing efficiency.Safety requirements,design robustness,and cost efficiency are simultaneously considered utilizing multiobjective optimization.A straightforward and efficient framework that focuses on difficulties caused by an enormous design space is established for the robust design of the self-starting drains,and improved computation efficiency is achieved.The effectiveness of the proposed approach is illustrated with a case study,the Qili landslide in Zhejiang Province,China.

Self-Synchronous Principle and Design of Vibrating Machines in Asymmetric System

Self-Synchronous principle of vibrating machines in asymmetric system is studied, and a design method is put forward. Based on Hamilton’s principle, a stable difference of phase angle is obtained,and this design method is proved correct.

Self-organized evolution of mechanism kinetic scheme based on axiomatic design

The self-organized evolution technology of the mechanism kinetic scheme based on axiomatic design is presented. This technology tries to express the constraints between kinetic mechanisms briefly in a semantic form which is more familiar to the designers. Through the mapping process between the kinetic chain unit and the unit instance, the evolution from abstract unit to concrete engineering instance is achieved. The subdivision of unit coupling semantics is studied, and the evolution of semantics is finished. Also, the semantic constraints evolution of unit coupling semantics is described. The product structure models with function and assembly meanings are constructed based on the kinematic chain unit and unit coupling. It provides a basis to realize the inheritance and transfer of constraint information from conceptual design to design for assembly （DFA）. As the engineering practice result shows, the method can help the engineers express their And the automation, recursion and design intension more clearly and naturally in a high semantic level. visualization of the mechanism kinetic scheme design are realized

Spatial batch optimal design based on self-learning Gaussian process models for LPCVD processes

Low pressure chemical vapor deposition(LPCVD) is one of the most important processes during semiconductor manufacturing.However,the spatial distribution of internal temperature and extremely few samples makes it hard to build a good-quality model of this batch process.Besides,due to the properties of this process,the reliability of the model must be taken into consideration when optimizing the MVs.In this work,an optimal design strategy based on the self-learning Gaussian process model(GPM) is proposed to control this kind of spatial batch process.The GPM is utilized as the internal model to predict the thicknesses of thin films on all spatial-distributed wafers using the limited data.Unlike the conventional model based design,the uncertainties of predictions provided by GPM are taken into consideration to guide the optimal design of manipulated variables so that the designing can be more prudent Besides,the GPM is also actively enhanced using as little data as possible based on the predictive uncertainties.The effectiveness of the proposed strategy is successfully demonstrated in an LPCVD process.

Web Layout Design of Large Cavity Structures Based on Topology Optimization

Large cavity structures are widely employed in aerospace engineering, such as thin-walled cylinders, blades andwings. Enhancing performance of aerial vehicles while reducing manufacturing costs and fuel consumptionhas become a focal point for contemporary researchers. Therefore, this paper aims to investigate the topologyoptimization of large cavity structures as a means to enhance their performance, safety, and efficiency. By usingthe variable density method, lightweight design is achieved without compromising structural strength. Theoptimization model considers both concentrated and distributed loads, and utilizes techniques like sensitivityfiltering and projection to obtain a robust optimized configuration. The mechanical properties are checked bycomparing the stress distribution and displacement of the unoptimized and optimized structures under the sameload. The results confirm that the optimized structures exhibit improved mechanical properties, thus offering keyinsights for engineering lightweight, high-strength large cavity structures.

Alloy design for laser powder bed fusion additive manufacturing:a critical review

Metal additive manufacturing(AM)has been extensively studied in recent decades.Despite the significant progress achieved in manufacturing complex shapes and structures,challenges such as severe cracking when using existing alloys for laser powder bed fusion(L-PBF)AM have persisted.These challenges arise because commercial alloys are primarily designed for conventional casting or forging processes,overlooking the fast cooling rates,steep temperature gradients and multiple thermal cycles of L-PBF.To address this,there is an urgent need to develop novel alloys specifically tailored for L-PBF technologies.This review provides a comprehensive summary of the strategies employed in alloy design for L-PBF.It aims to guide future research on designing novel alloys dedicated to L-PBF instead of adapting existing alloys.The review begins by discussing the features of the L-PBF processes,focusing on rapid solidification and intrinsic heat treatment.Next,the printability of the four main existing alloys(Fe-,Ni-,Al-and Ti-based alloys)is critically assessed,with a comparison of their conventional weldability.It was found that the weldability criteria are not always applicable in estimating printability.Furthermore,the review presents recent advances in alloy development and associated strategies,categorizing them into crack mitigation-oriented,microstructure manipulation-oriented and machine learning-assisted approaches.Lastly,an outlook and suggestions are given to highlight the issues that need to be addressed in future work.

A Study on the Evolution of Labor Self-Organizations and the Design of Governmental Mechanism from A Complex Network Perspective

Self-organization theory informs an analysis on the evolution of labor self-organizations (LSOs), but lacks technical analysis on the evolution of their organizational structures. Fortunately, complex network technology offers a new approach to analyzing these structures. Built on an extension of the Barabási-Albert (BA) model, we can simulate the evolution of LSOs by analyzing indicators including the clustering coefficient, degree distribution (DD) and average path length (APL) of workers, thereby demonstrating the evolving patterns of LSOs. Accordingly, governmental mechanism designs based on such patterns may not only stimulate energy growth and functional realization of LSOs, but also reduce the social percussions of abrupt evolutions. A comparative analysis of the evolutionary trajectories of LSOs in China and the U.S. finds that the U.S. government’s mechanism designs for protecting capitalism not only prevented the effective gathering of workers, but also prolonged the history of industrial conflicts. Such mechanism designs also led to the early dispersion and decline of LSOs and hindered the evolution of the working class. In contrast, the Chinese government established a socialist system that allowed workers to become the underlying force of socialist productivity. This design reduced labor strife while accelerating the evolution of workers towards higher stages.

Design Principles and Mechanistic Understandings of Non-Noble-Metal Bifunctional Electrocatalysts for Zinc-Air Batteries

Zinc-air batteries(ZABs)are promising energy storage systems because of high theoretical energy density,safety,low cost,and abundance of zinc.However,the slow multi-step reaction of oxygen and heavy reliance on noble-metal catalysts hinder the practical applications of ZABs.Therefore,feasible and advanced non-noble-metal elec-trocatalysts for air cathodes need to be identified to promote the oxygen catalytic reaction.In this review,we initially introduced the advancement of ZABs in the past two decades and provided an overview of key developments in this field.Then,we discussed the work-ing mechanism and the design of bifunctional electrocatalysts from the perspective of morphology design,crystal structure tuning,interface strategy,and atomic engineering.We also included theoretical studies,machine learning,and advanced characterization technologies to provide a comprehensive understanding of the structure-performance relationship of electrocatalysts and the reaction pathways of the oxygen redox reactions.Finally,we discussed the challenges and prospects related to designing advanced non-noble-metal bifunctional electrocatalysts for ZABs.

Accelerated design of high-performance Mg-Mn-based magnesium alloys based on novel bayesian optimization

Magnesium(Mg),being the lightest structural metal,holds immense potential for widespread applications in various fields.The development of high-performance and cost-effective Mg alloys is crucial to further advancing their commercial utilization.With the rapid advancement of machine learning(ML)technology in recent years,the“data-driven''approach for alloy design has provided new perspectives and opportunities for enhancing the performance of Mg alloys.This paper introduces a novel regression-based Bayesian optimization active learning model(RBOALM)for the development of high-performance Mg-Mn-based wrought alloys.RBOALM employs active learning to automatically explore optimal alloy compositions and process parameters within predefined ranges,facilitating the discovery of superior alloy combinations.This model further integrates pre-established regression models as surrogate functions in Bayesian optimization,significantly enhancing the precision of the design process.Leveraging RBOALM,several new high-performance alloys have been successfully designed and prepared.Notably,after mechanical property testing of the designed alloys,the Mg-2.1Zn-2.0Mn-0.5Sn-0.1Ca alloy demonstrates exceptional mechanical properties,including an ultimate tensile strength of 406 MPa,a yield strength of 287 MPa,and a 23%fracture elongation.Furthermore,the Mg-2.7Mn-0.5Al-0.1Ca alloy exhibits an ultimate tensile strength of 211 MPa,coupled with a remarkable 41%fracture elongation.

Formulation of self-nanoemulsifying drug delivery systems containing monoacyl phosphatidylcholine and Kolliphor^(■) RH40 using experimental design

The development of self-nanoemulsifying drug delivery systems(SNEDDS) to enhance the oral bioavailability of lipophilic drugs is usually based on traditional one-factor-at-a-time approaches. These approaches may be inadequate to analyse the effect of each excipient and their potential interactions on the emulsion droplet size formed when dispersing the SNEDDS in an aqueous environment. The current study investigates the emulsion droplet sizes formed from SNEDDS containing different levels of the natural surfactant monoacyl phosphatidylcholine to reduce the concentration of the synthetic surfactant polyoxyl 40 hydrogenated castor oil(Kolliphor ~? RH40). Monoacyl phosphatidylcholine was used in the form of Lipoid S LPC 80(LPC, containing approximately 80% monoacyl phosphatidylcholine, 13% phosphatidylcholine and 4% concomitant components). The investigated SNEDDS comprised of long-chain or medium-chain glycerides(40% to 75%), Kolliphor ~? RH40(5% to 55%), LPC(0 to 40%) and ethanol(0 to 10%). D-optimal design, multiple linear regression, and partial least square regression were used to screen different SNEDDS within the investigated excipient ranges and to analyse the effect of each excipient on the resulting droplet size of the dispersed SNEDDS measured by dynamic light scattering. All investigated formulations formed nano-emulsions with droplet sizes from about 20 to 200 nm. The use of mediumchain glycerides was more likely to result in smaller and more monodisperse droplet sizes compared to the use of long-chain glycerides. Kolliphor~? RH40 exhibited the most significant effect on reducing the emulsion droplet sizes. Increasing LPC concentration increased the emulsion droplet sizes, possibly because of the reduction of Kolliphor~? RH40 concentration. A higher concentration of ethanol resulted in an insignificant reduction of the emulsion droplet size. The study provides different ternary diagrams of SNEDDS containing LPC and Kolliphor ~? RH40 as a reference for formulation developers.

Inverse design of mechanical metamaterial achieving a prescribedconstitutive curve

Besides exhibiting excellent capabilities such as energy absorption,phase-transforming metamaterials offer a vast design space for achieving nonlinear constitutive relations.This is facilitated by switching between different patterns under deformation.However,the related inverse design problem is quite challenging,due to the lack of appropriate mathematical formulation and the convergence issue in the post-buckling analysis of intermediate designs.In this work,periodic unit cells are explicitly described by the moving morphable voids method and effectively analyzed by eliminating the degrees of freedom in void regions.Furthermore,by exploring the Pareto frontiers between error and cost,an inverse design formulation is proposed for unit cells.This formulation aims to achieve a prescribed constitutive curve and is validated through numerical examples and experimental results.The design approach presented here can be extended to the inverse design of other types of mechanical metamaterials with prescribed nonlinear effective properties.