基于Design-Expert的电链锯锯齿结构参数优化

为提高电链锯的锯切效率,对电链锯锯齿的齿形结构参数进行研究,以单位锯切功为电链锯锯切效率的衡量指标,通过对电链锯锯切过程的仿真研究,得出不同结构锯齿的单位锯切功。以电链锯锯齿中的外形前角、侧刃楔角和顶刃楔角等结构参数作为影响因子,采用Box-Benhnken中心组合试验方法设计多因素正交试验,使用Design-expert软件进行数据分析得出最优齿形结构参数组合。研究结果表明,所选取的齿形结构参数对单位锯切功影响程度由大到小顺序依次为外形前角、侧刃楔角、顶刃楔角,并获得最优齿形结构参数组合,外形前角为10.92°、侧刃楔角为45.7°、顶刃楔角为45.41°。

基于Design-Expert的碱激发粉煤灰建筑外墙腻子配合比优化试验研究

为了拓展工业固体废弃物粉煤灰的回收利用途径,减少对环境造成的污染,增加其在筑材料中回收利用率。在建筑外墙腻子中加入碱性激发剂(Ca(OH)_(2)、Na_(2)SiO_(3))、粉煤灰,研究碱性激发剂的激发效果。同时通过Design-Expert设计试验,分析主要组分对腻子漆膜粘结强度、吸水量的影响。结果表明:加入碱性激发剂5%,粉煤灰32.5%时,吸水量减少14%,粘结强度增加43%。乳胶粉对吸水量、粘结强度的影响非常显著(P<0.0001),其次是粉煤灰的加入量。通过加入碱性激发剂、提高乳胶粉占比,粉煤灰掺量能达到32%~65%,原配比中水泥的掺量相对减少0%~16%。

基于ANSYS和Design-Expert的农用挖掘机斗杆机构优化设计

JKW-20山地农用挖掘机斗杆机构存在设计冗余,在保证安全可靠的前提下,为解决斗杆机构材料冗余问题,实现轻量化改进,建立了农用挖掘机挖掘装置斗杆机构耦合模型,通过ANSYS软件静力学仿真及拓扑优化,确定了斗杆机构拓扑优化新结构。由于拓扑优化结构不符合实际生产要求,基于优化结果设计斗杆变量,确定优化目标函数,利用Design-Expert进行斗杆机构尺寸优化求解。由优化结果对比可知:运用Design-Expert优化后的斗杆结构相对原结构具备更轻的质量和更大的强度,该方法不仅节约了JKW-20山地农用挖掘机的生产成本,还可为类似的机构设计提供优化思路。

基于Design-Expert优化一款中药空气抑菌剂配方的研究

目的:以多种中药挥发油作为原料,开发一款高效广谱抑菌的空气抑菌剂。方法:选取丁香、艾叶、香茅3种挥发油,采用Design-Expert 12.0中自带的Optimal(custom)试验设计进行最优混料配方筛选试验。通过采样我校饭堂空间空气浮游菌,先按软件设计配方加样抑菌孵育并计数,再拟合出孵育菌落数与各挥发油配方比例的模型方程,最后计算出最佳抑菌效能配方比例,并采用实验室试验和现场试验验证优选配方。结果:利用286组抑菌孵育数据计算得出,孵育菌落数(Y)与各挥发油配方比例之间的拟合方程为Y=17.60A+53.01B+36.76C-106.11AB-84.87AC-63.93BC+782.79A^(2)BC-1178.89AB^(2)C+413.15ABC2。丁香与艾叶、香茅挥发油抑菌的交互作用对孵育菌落数量有显著影响(p<0.05)。最终选择的丁香、艾叶、香茅挥发油比例为45.2:41.6:13.2,该配方的实验室试验和现场试验验证了其抑菌效能良好。结论:中药抑菌挥发油复配后具有明显的增效作用。该配方的空气抑菌剂抑菌效果明显,气味芳香易于被人们接受,具有良好的市场前景和推广价值。

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。

基于Design-expert的醋酸纤维/煤基分级多孔炭制备优化

当前煤层气利用的主要方式是直接燃烧,该过程会产生大量温室气体(CO_(2))排放,且会造成稀缺资源的低附加值利用。为实现煤层气的高附加值利用,拟通过在煤中原位添加醋酸纤维和KOH活化的方法制备一种醋酸纤维/煤基分级多孔炭材料,并将其应用于煤层气直接裂解制氢,不仅可以获得高纯氢气,还能得到一定数量的纳米碳材料。醋酸纤维/煤基分级多孔炭在制备过程中需要考虑温度、碱碳质量比、溶剂量和其他碳源添加量对制备过程和转化率的影响,利用Design-expert软件对试验方案进行优化设计。通过响应曲面法和部分试验数据对各影响因素与转化率的关系进行分析,建立相应拟合回归方程,得出理论最优解。通过将最优解与试验结果进行对比分析,验证Design-expert软件在多因素多水平条件下的预测可靠性,同时也阐明最优条件下炭材料催化裂解煤层气的机理。结果表明,温度和碱碳质量比是醋酸纤维/煤基分级多孔炭制备过程的最大影响因素,建立相关因素与转化率之间的拟合回归方程并求出理论最优解。理论最优解与试验值之间的最大误差为3.05%,说明Design-expert软件对制备过程的优化准确可靠。醋酸纤维/煤基分级多孔炭催化裂解煤层气较原煤炭材料具有高的转化率和稳定性,前者反应后表面生成大量碳球,而后者表面则生成少量碳纤维和大量碳球。

基于Design-Expert的UHPC强度及收缩率计算模型研究

为实现关键配比参数调整下超高性能混凝土(UHPC)的性能指标控制并得到各性能之间的相互影响规律,利用软件Design-Expert分析了UHPC的主要性能影响因素,基于主要因素对鮑罗米(Bolomy)公式进行了修正,建立了关于UHPC抗压强度、收缩率的计算模型。结果表明:对UHPC抗压强度、收缩率影响较大的三个配比因素分别为水胶比、胶砂比、粉煤灰掺量;基于主要影响因素,利用Design-Expert对UHPC配合比进行了优化,得到了抗压强度≥176 MPa,且收缩率≤320μm·m-1的UHPC试件;通过主要影响因素构建了Bolomy抗压强度及收缩率计算模型,并由计算数据与实验数据对比分析可知,修正后的Bolomy计算模型,可准确反映出抗压强度及收缩率与各主要影响因素之间的关系。

以色彩为媒介的Design Thinking在艺术设计中的创新实践

色彩作为Design Thinking中的重要媒介,在艺术设计创新实践中具有重要潜力。本文探讨了以色彩为媒介的Design Thinking在艺术设计创新实践中的应用。色彩不仅在Design Thinking中占据重要地位,而且对人类的情绪和行为产生影响,同时在设计中起着至关重要的作用。将Design Thinking引入艺术实践领域,旨在培养艺术创新思维和问题解决能力,强调创新实践和跨学科合作。职业院校在艺术设计创新实践中面临着诸多挑战,但也存在机遇。通过案例分析,本文展示了如何实施基于色彩的Design Thinking艺术设计实践以及这种创新对艺术创新能力的积极影响。

基于“Design Thinking”理念的职业院校创新创业人才培养模式

随着我国经济不断发展和社会进步,创新创业已经成为推动经济增长的关键驱动力,在2015年全国人民代表大会上,李克强总理将“大众创业、万众创新”明确列为我国经济增长的“双引擎”之一,彰显了创新创业对于推动社会发展的重要地位。为响应国家政策,各高校积极开展创新创业教育,将其纳入高等教育综合改革的重要议程,成为培养未来人才的重要途径。本文分析了“Design Thinking”理念下职业院校创新创业人才培养的必要性,围绕新时期专业院校创新创业人才培养的要求,提出了基于“Design Thinking”理念的职业院校创新创业人才培养模式的有效策略,为职业院校人才培养效率的强化提供了参考性意见。

基于Cast Designer的壳体铸件铸造工艺设计及智能优化

使用Cast Designer铸造仿真分析软件,通过可铸性评估系统DFM,完成浇冒系统的辅助设计,然后使用DOE技术和基于遗传算法GA的智能优化技术,评估不同工艺设计方案与铸造过程参数对壳体铸件质量的影响,分析在不同的冒口、冷铁和浇注温度条件下得料率和缩孔量的关系。根据对DOE模拟结果的分析,发现顶冒口和侧冒口尺寸是影响得料率和缩孔量的关键因数,再利用遗传算法GA选择最佳设计方案和参数。通过帕累托曲线得到了生产壳体铸件的最优工艺方案。

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.

A Comparative Study of Metaheuristic Optimization Algorithms for Solving Real-World Engineering Design Problems

Real-world engineering design problems with complex objective functions under some constraints are relatively difficult problems to solve.Such design problems are widely experienced in many engineering fields,such as industry,automotive,construction,machinery,and interdisciplinary research.However,there are established optimization techniques that have shown effectiveness in addressing these types of issues.This research paper gives a comparative study of the implementation of seventeen new metaheuristic methods in order to optimize twelve distinct engineering design issues.The algorithms used in the study are listed as:transient search optimization(TSO),equilibrium optimizer(EO),grey wolf optimizer(GWO),moth-flame optimization(MFO),whale optimization algorithm(WOA),slimemould algorithm(SMA),harris hawks optimization(HHO),chimp optimization algorithm(COA),coot optimization algorithm(COOT),multi-verse optimization(MVO),arithmetic optimization algorithm(AOA),aquila optimizer(AO),sine cosine algorithm(SCA),smell agent optimization(SAO),and seagull optimization algorithm(SOA),pelican optimization algorithm(POA),and coati optimization algorithm(CA).As far as we know,there is no comparative analysis of recent and popular methods against the concrete conditions of real-world engineering problems.Hence,a remarkable research guideline is presented in the study for researchersworking in the fields of engineering and artificial intelligence,especiallywhen applying the optimization methods that have emerged recently.Future research can rely on this work for a literature search on comparisons of metaheuristic optimization methods in real-world problems under similar conditions.

Combining Deep Learning with Knowledge Graph for Design Knowledge Acquisition in Conceptual Product Design

The acquisition of valuable design knowledge from massive fragmentary data is challenging for designers in conceptual product design.This study proposes a novel method for acquiring design knowledge by combining deep learning with knowledge graph.Specifically,the design knowledge acquisition method utilises the knowledge extraction model to extract design-related entities and relations from fragmentary data,and further constructs the knowledge graph to support design knowledge acquisition for conceptual product design.Moreover,the knowledge extraction model introduces ALBERT to solve memory limitation and communication overhead in the entity extraction module,and uses multi-granularity information to overcome segmentation errors and polysemy ambiguity in the relation extraction module.Experimental comparison verified the effectiveness and accuracy of the proposed knowledge extraction model.The case study demonstrated the feasibility of the knowledge graph construction with real fragmentary porcelain data and showed the capability to provide designers with interconnected and visualised design knowledge.

荷兰代尔夫特理工大学Urban Design工作坊教学模式对我国城市设计课程教学的启示

荷兰代尔夫特理工大学的Urban Design工作坊小组教学模式,为我国城市设计教育提供了创新路径。该模式强化学生跨学科思维与问题解决能力,通过项目实践培育评审、模拟、谈判、决策及冲突管理等技能,教师角色转变为引导者和促进者,激励创新并深化团队协作与沟通。针对我国城市设计教育现状,建议加强综合能力的培养,促进理论教学与设计实践的深度结合,并构建均衡的课程评估框架。此模式的本土化将有力推动我国城市设计教育的创新与发展。

基于Smart Design的校园光伏电站仿真研究

基于智能光伏设计软件Smart Design,对株洲市某高校图书馆屋顶的工商业光伏电站进行了设计与仿真。通过评估当地太阳能资源和气象参数,确定了光伏电站的最佳选址和倾角。利用软件的3D建模和电气设计功能,完成了光伏板排布和电气连接,采用隆基绿能双面光伏组件和华为光伏优化器及逆变器,提高了电站效率。仿真结果显示,该电站具有良好的发电量、经济效益和社会贡献。

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.

Machine learning for membrane design and discovery

Membrane technologies are becoming increasingly versatile and helpful today for sustainable development.Machine Learning(ML),an essential branch of artificial intelligence(AI),has substantially impacted the research and development norm of new materials for energy and environment.This review provides an overview and perspectives on ML methodologies and their applications in membrane design and dis-covery.A brief overview of membrane technologies isfirst provided with the current bottlenecks and potential solutions.Through an appli-cations-based perspective of AI-aided membrane design and discovery,we further show how ML strategies are applied to the membrane discovery cycle(including membrane material design,membrane application,membrane process design,and knowledge extraction),in various membrane systems,ranging from gas,liquid,and fuel cell separation membranes.Furthermore,the best practices of integrating ML methods and specific application targets in membrane design and discovery are presented with an ideal paradigm proposed.The challenges to be addressed and prospects of AI applications in membrane discovery are also highlighted in the end.

Review on the design of high-strength and hydrogen-embrittlement-resistant steels

Given the carbon peak and carbon neutrality era,there is an urgent need to develop high-strength steel with remarkable hydrogen embrittlement resistance.This is crucial in enhancing toughness and ensuring the utilization of hydrogen in emerging iron and steel materials.Simultaneously,the pursuit of enhanced metallic materials presents a cross-disciplinary scientific and engineering challenge.Developing high-strength,toughened steel with both enhanced strength and hydrogen embrittlement(HE)resistance holds significant theoretical and practical implications.This ensures secure hydrogen utilization and further carbon neutrality objectives within the iron and steel sector.Based on the design principles of high-strength steel HE resistance,this review provides a comprehensive overview of research on designing surface HE resistance and employing nanosized precipitates as intragranular hydrogen traps.It also proposes feasible recommendations and prospects for designing high-strength steel with enhanced HE resistance.

Quantum algorithm for minimum dominating set problem with circuit design

Using quantum algorithms to solve various problems has attracted widespread attention with the development of quantum computing.Researchers are particularly interested in using the acceleration properties of quantum algorithms to solve NP-complete problems.This paper focuses on the well-known NP-complete problem of finding the minimum dominating set in undirected graphs.To expedite the search process,a quantum algorithm employing Grover’s search is proposed.However,a challenge arises from the unknown number of solutions for the minimum dominating set,rendering direct usage of original Grover’s search impossible.Thus,a swap test method is introduced to ascertain the number of iterations required.The oracle,diffusion operators,and swap test are designed with achievable quantum gates.The query complexity is O(1.414^(n))and the space complexity is O(n).To validate the proposed approach,qiskit software package is employed to simulate the quantum circuit,yielding the anticipated results.

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.