Crashworthiness Design and Multi-Objective Optimization for Bio-Inspired Hierarchical Thin-Walled Structures

Thin-walled structures have been used in many fields due to their superior mechanical properties.In this paper,two types of hierarchical multi-cell tubes,inspired by the self-similarity of Pinus sylvestris,are proposed to enhance structural energy absorption performance.The finite element models of the hierarchical structures are established to validate the crashworthiness performance under axial dynamic load.The theoreticalmodel of themean crushing force is also derived based on the simplified super folded element theory.The finite element results demonstrate that the energy absorption characteristics and deformation mode of the bionic hierarchical thin-walled tubes are further improved with the increase of hierarchical sub-structures.It can be also obtained that the energy absorption performance of corner self-similar tubes is better than edge self-similar tubes.Furthermore,multiobjective optimization of the hierarchical tubes is constructed by employing the response surface method and genetic algorithm,and the corresponding Pareto front diagram is obtained.This research provides a new idea for the crashworthiness design of thin-walled structures.

A Hierarchical Modeling Framework for Electrochemical Behaviors in Lithium-Ion Batteries with Detailed Structures

The accurate representation of lithium plating and aging phenomena has posed a persistent challenge within the battery research community.Empirical evidence underscores the pivotal role of cell structure in influencing aging behaviors and lithium plating within lithium-ion batteries(LIBs).Available lithium-ion plating models often falter in detailed description when integrating the structural intricacies.To address this challenge,this study proposes an innovative hierarchical model that intricately incorporates the layered rolling structure in cells.Notably,our model demonstrates a remarkable capacity to predict the non-uniform distribution of current density and overpotential along the rolling direction of LIBs.Subsequently,we delve into an insightful exploration of the structural factors that influence lithium plating behavior,leveraging the foundation laid by our established model.Furthermore,we easily update the hierarchical model by considering aging factors.This aging model effectively anticipates capacity fatigue and lithium plating tendencies across individual layers of LIBs,all while maintaining computational efficiency.In light of our findings,this model yields novel perspectives on capacity fatigue dynamics and local lithium plating behaviors,offering a substantial advancement compared to existing models.This research paves the way for more efficient and tailored LIB design and operation,with broad implications for energy storage technologies.

Oxidative desulfurization of model and real oil samples using Mo supported on hierarchical alumina–silica: Process optimization by Box–Behnken experimental design

The catalytic performance of Mo supported on hierarchical alumina–silica(Si/Al = 15) with Mo loadings of 3, 6 and 15 wt% was investigated for the oxidative desulfurization(ODS) of model and real oil samples. Hierarchical alumina–silica(h Al–Si) was synthesized by economical and ecofriendly silicate-1 seed-induced route using cetyltrimethylammonium bromide(CTAB) as mesoporogen. The effect of CTAB on the structure of catalyst was studied by characterization techniques. The results revealed that 6%Mo/h Al–Si had the highest sulfur removal compared to the other catalyst loadings. The effect of operating parameters was evaluated using Box–Behnken experimental design. The optimal desulfurization conditions with the 6%Mo/h Al–Si catalyst were determined at oxidation temperature of 67 ℃, oxidation time of 42 min, H2O2/S molar ratio of 8 and catalyst dosage of 0.008 g·ml^-1 for achieving a conversion of 95%. Under optimal conditions, different sulfur-containing compounds with initial concentration of 1000 ppm, Dibenzothiophene(DBT), Benzothiophene(BT) and Thiophen(Th), showed the catalytic oxidation reactivity in the order of DBT > BT>Th. According to the regeneration experiments, the 6%Mo/h Al–Si catalyst was reused 4 times with a little reduction in the performance. Also, the total sulfur content of gasoline and diesel after ODS process reached 156.6 and 4592.2 ppm, respectively.

Discrete logistics network design model under interval hierarchical OD demand based on interval genetic algorithm

Aimed at the uncertain characteristics of discrete logistics network design,an interval hierarchical triangular uncertain OD demand model based on interval demand and network flow is presented.Under consideration of the system profit,the uncertain demand of logistics network is measured by interval variables and interval parameters,and an interval planning model of discrete logistics network is established.The risk coefficient and maximum constrained deviation are defined to realize the certain transformation of the model.By integrating interval algorithm and genetic algorithm,an interval hierarchical optimal genetic algorithm is proposed to solve the model.It is shown by a tested example that in the same scenario condition an interval solution[3275.3,3 603.7]can be obtained by the model and algorithm which is obviously better than the single precise optimal solution by stochastic or fuzzy algorithm,so it can be reflected that the model and algorithm have more stronger operability and the solution result has superiority to scenario decision.

Design of Hierarchical Classifier to Improve Speech Emotion Recognition

Automatic Speech Emotion Recognition(SER)is used to recognize emotion from speech automatically.Speech Emotion recognition is working well in a laboratory environment but real-time emotion recognition has been influenced by the variations in gender,age,the cultural and acoustical background of the speaker.The acoustical resemblance between emotional expressions further increases the complexity of recognition.Many recent research works are concentrated to address these effects individually.Instead of addressing every influencing attribute individually,we would like to design a system,which reduces the effect that arises on any factor.We propose a two-level Hierarchical classifier named Interpreter of responses(IR).Thefirst level of IR has been realized using Support Vector Machine(SVM)and Gaussian Mixer Model(GMM)classifiers.In the second level of IR,a discriminative SVM classifier has been trained and tested with meta information offirst-level classifiers along with the input acoustical feature vector which is used in primary classifiers.To train the system with a corpus of versatile nature,an integrated emotion corpus has been composed using emotion samples of 5 speech corpora,namely;EMO-DB,IITKGP-SESC,SAVEE Corpus,Spanish emotion corpus,CMU's Woogle corpus.The hierarchical classifier has been trained and tested using MFCC and Low-Level Descriptors(LLD).The empirical analysis shows that the proposed classifier outperforms the traditional classifiers.The proposed ensemble design is very generic and can be adapted even when the number and nature of features change.Thefirst-level classifiers GMM or SVM may be replaced with any other learning algorithm.

Configurable Product Design Considering the Transition of Multi-hierarchical Models

The current research of configurable product design mainly focuses on how to convert a predefined set of components into a valid set of product structures. With the scale and complexity of configurable products increasing, the interdependencies between customer demands and product structures grow up as well. The result is that existing product structures fails to satisfy the individual customer requirements and hence product variants are needed. This paper is aimed to build a bridge between customer demands and product structures in order to make demand-driven fast response design feasible. First of all, multi-hierarchical models of configurable product design are established with customer demand model, technical requirement model and product structure model. Then, the transition of multi-hierarchical models among customer demand model, technical requirement model and product structure model is solved with fuzzy analytic hierarchy process （FAHP） and the algorithm of multi-level matching. Finally, optimal structure according to the customer demands is obtained with the calculation of Euclidean distance and similarity of some cases. In practice, the configuration design of a clamping unit of injection molding machine successfully performs an optimal search strategy for the product variants with reasonable satisfaction to individual customer demands. The proposed method can automatically generate a configuration design with better alternatives for each product structures, and shorten the time of finding the configuration of a product.

A Feature Definition Hierarchy for Supporting Design Process

The adaptability of features definition to applications is an essential condition for implementing feature based design. This paper makes attempt to present a hierarchical definition structure of features. The proposed scheme divides feature definition into application level, form level and geometric level, and provides links between different levels with feature semantics interpretation and enhanced geometric face adjacent graph. respectively. The results not only enable feature definition to abate from the specific dependence and become more extensive, but also provide a theoretical foundation for establishing the concurrent feature based design process model.

Toward a Multi-Hop, Multi-Path Fault-Tolerant and Load Balancing Hierarchical Routing Protocol for Wireless Sensor Network

This paper describes a novel energy-aware multi-hop cluster-based fault-tolerant load balancing hierarchical routing protocol for a self-organizing wireless sensor network (WSN), which takes into account the broadcast nature of radio. The main idea is using hierarchical fuzzy soft clusters enabling non-exclusive overlapping clusters, thus allowing partial multiple membership of a node to more than one cluster, whereby for each cluster the clusterhead (CH) takes in charge intra-cluster issues of aggregating the information from nodes members, and then collaborate and coordinate with its related overlapping area heads (OAHs), which are elected heuristically to ensure inter-clusters communication. This communication is implemented using an extended version of time-division multiple access (TDMA) allowing the allocation of several slots for a given node, and alternating the role of the clusterhead and its associated overlapping area heads. Each cluster head relays information to overlapping area heads which in turn each relays it to other associated cluster heads in related clusters, thus the information propagates gradually until it reaches the sink in a multi-hop fashion.

CADGen:Computer-aided design sequence construction with a guided codebook learning

Computer-aided design(CAD)software continues to be a crucial tool in digital twin application and manufacturing,facilitating the design of various products.We present a novel CAD generation method,an agent that constructs the CAD sequences containing the sketch-and-extrude modelling operations efficiently and with high quality.Starting from the sketch and extrusion operation sequences,we utilise the transformer encoder to encode them into different disentangled codebooks to represent their distribution properties while considering their correlations.Then,a combination of auto-regressive and non-autoregressive samplers is trained to sample the code for CAD sequence con-struction.Extensive experiments demonstrate that our model generates diverse and high-quality CAD models.We also show some cases of real digital twin applications and indicate that our generated model can be used as the data source for the digital twin platform,exhibiting designers'potential.

Application of Fractal Theory in Landscape Design

Research and application of fractal theory in landscape design has greatly enriched the concepts and techniques of garden creation,and pushed forward landscape design closer to the natural world.By elaborating internal connection between fractal theory and landscape design,this paper uses iterative function system of the fractal theory and matlab to draw fractal trees.Two designed experiments demonstrate that the fractal theory can be employed to realize the vivid drawing of natural landscapes with the support of limited data.Therefore,fractal theory is a practical tool used to draw vivid natural landscapes efficiently.

Functionally Graded Cellular Structure Design Using the Subdomain Level Set Method with Local Volume Constraints

Functional graded cellular structure(FGCS)usually shows superiormechanical behaviorwith lowdensity and high stiffness.With the development of additivemanufacturing,functional graded cellular structure gains its popularity in industries.In this paper,a novel approach for designing functionally graded cellular structure is proposed based on a subdomain parameterized level set method(PLSM)under local volume constraints(LVC).In this method,a subdomain level set function is defined,parameterized and updated on each subdomain independently making the proposed approach much faster and more cost-effective.Additionally,the microstructures on arbitrary two adjacent subdomains can be connected perfectly without any additional constraint.Furthermore,the local volume constraint for each subdomain is applied by virtue of the augmented Lagrange multiplier method.Finally,several numerical examples are given to verify the correctness and effectiveness of the proposed approach in designing the functionally graded cellular structure.From the optimized results,it is also found that the number of local volume constraints has little influence on the convergence speed of the developed approach.

Optimum Designing of Gas Distribution Networks of Ilam Province by Using GIS Network and Spatial Analysis

Undoubtedly, pipeline transport is considered as significant economical artery of country and national valuable resources, so it is necessary to use latest technologies, major standards and instructions and the best human resources in designing, operation and supervision in construction and also protection of it. Also, all authorities and involved of construction and operation of gas industries installation should observe safety criteria, health and environment and aware of them ever. In fact, in designing of these programs, in addition to technical and economical points, environmental characteristics should be considered in order to their construction has minimum damage to environment. On the other hand, common and traditional approaches of pipeline routing are based on using costly and time-consuming methods. In these methods, it is not easily to use all effective parameters in determining optimum way. According to capability of analysis of network spatial information systems in incorporation of spatial data, for using all effective parameters in routing, this environment is used, therefore weighted overlay analysis (Boleyn, index and fuzzy) and shortest path are modeled for finding optimum path of pipeline in GIS environment.

基于PSO-BP神经网络的磨机传动系统模型修正

针对磨机传动系统结构的复杂性、部件间约束条件的不确定性以及非线性等因素,提出了一种基于PSO-BP神经网络的有限元模型修正方法。通过改进BP神经网络逼近设计参数和特征量间的非线性映射关系,结合实际结构响应,利用神经网络的泛化特性,得到了模型设计参数值。修正后频率误差从最高18%降到4%左右,修正系数误差范围均在0.5%以内,明显提高了有限元模型精度;同时,又不需要大量迭代求解步骤,避开了传统反问题模型修正法的复杂非线性优化过程,提升了效率,验证了PSO-BP神经网络法应用于大型磨机传动系统上的可行性,为后续传动系统整体分析奠定了基础。

基于对分课堂理念的蔬菜嫁接实验课堂教学改革

“以学生为中心”的对分课堂教学模式是一种新型教学模式,突出强调内化吸收和讨论环节。传统的蔬菜嫁接实验课堂教学模式不能充分调动学生课堂参与的积极性和主动性,也不能提升学生的创新能力。基于学生主体性与潜能发挥,结合蔬菜嫁接实验本身,提出了“以学生为中心”的蔬菜嫁接实验对分课堂教学模式,对教学内容进行了层次化设计,增加了实验的综合性和创新性。实验过程增加了实验设计、小组讨论和答辩环节,建立了实验全过程的考核体系。教学实践证明,“以学生为中心”的蔬菜嫁接实验对分课堂教学模式激发和培养了学生的实践和创新能力,有效提高了实验教学效果。

基于形体特征层次分析的概念设计原型评价与演化方法

为对概念设计原型进行定量评价,实现具有形位公差需求的机械零件成形时间与制造质量之间的均衡,提出一种基于形体特征层次分析(Shape Feature Hierarchical Analysis,SFHA)的概念设计原型评价与演化方法。针对概念设计形体的孔和轴的形态特性,采用最大内切圆柱和最小外接圆柱构建特征模型,计算由分层策略所导致偏移的实际轴线位置,推算圆柱度误差大小。进行基于形位公差的自适应分层,在保证圆柱度等公差满足设计需求的情况下尽可能减少所需层数。通过改进粒子群算法进行非凸优化求解,遴选出最优的分层序列。计算特征层次化模型向正平面V(XOZ)和侧平面W(YOZ)的平行正投影面积及绝对梯度变化,实现基于SFHA的概念设计原型特征定量化描述与动态演化。以典型支座零件为例进行验证,采用熔融沉积成形设备进行物理试验,基于高精度结构光三维扫描仪获取原型零件的圆柱度误差,相较于均匀分层方法,所提出的SFHA方法制造时间可减少26.97%。

交通工程专业设计类课程高质量教材建设刍议

在新工科建设背景下,交通工程专业设计类课程教材建设面临层级目标的设定、教材内容与标准规范的联系、知识表达形式、教材的修编再版等挑战,围绕“层级目标、专业实战、多元资源”课程教材建设目标,创新性提出了对教材内容进行从基础设计能力到创新设计能力的层级模块化编排和设计类教材核心词汇语言表达方式的教材建设思路,以实战为导向探索设计类教材知识多样化表现手法,并针对设计类课程的特点,提出教材“编写—修订—再版”全过程动态监测评估的建设技术路径。

层级目标下沈阳市老旧住宅适老改造研究

随着我国老龄化程度加深,探究与完善老旧住宅的适老化改造刻不容缓。以沈阳老旧住宅为研究对象,以分层级改造的目标出发,从老年人的心理需求、生理需求来确定适老化改造层级。结合现有优秀案例,针对发现的问题提出安全性改造、舒适化改造和健康改造三个从老年人需求层级出发的适老化改造策略。

微通道换热器拓扑结构优化与性能研究

换热器结构拓扑优化可将传热强化设计问题转化为数学优化问题进行求解,对于设计新颖高效换热器具有重要价值。然而,拓扑优化数学模型难以直接解释优化结果的几何特征及相应强化机理。以传热量为目标,对微通道换热器进行拓扑优化设计,研究了不同参数对换热器强化结构特征和换热器性能的影响。结果表明,拓扑优化换热器的通道结构呈现多级分叉构型,分叉的数量随着入口Reynolds数、翅片传热效率和流体Prandtl数的增大而增多。在此基础上,采用耗散和边界层理论分析了拓扑优化分叉通道与流体边界层厚度的内在联系,为换热器结构强化设计提供了新的思路。

众包制造环境下协同产品族设计与延迟决策的主从关联优化

针对众包制造环境下产品族设计与延迟决策之间的协同优化问题,建立了以产品族设计为主、延迟决策为从的混合整数非线性双层规划模型。模型上层由制造商设计产品族架构以最大化自身的期望利润,下层由多个分销商优化延迟产品模块的类型以最大化各自的期望利润,且各分销商之间的决策具有相互独立性。考虑到延迟产品模块事先不确定,提出虚拟延迟结构将该优化问题具体化,并证明需要被延迟的产品模块。开发了一个双层嵌套遗传算法对模型进行求解。用智能冰箱产品族延迟案例验证了所提模型和算法的有效性,并对所提延迟偏好参数进行了灵敏度分析。

基于跨界思维下的瑶绣编织技艺与家具设计融合创新

为探讨瑶族刺绣产业的可持续发展模式,共论跨界思维下的民俗文化共生体系。即传统刺绣的空灵美感与现代家具的实用功能相结合。文章首先阐述了跨界思维的定义及在设计等领域的表现,并引入瑶绣这一非物质文化遗产与家具设计结合,以此为契机探索跨界理念在传统技艺传承创新中的应用,继而研究采用KE和FAHP相结合,分别对瑶绣编织技艺办公椅的用户需求和文化需求进行关联映射,最终得出相关用户需求并应用于办公座椅的设计实践中。这一探索体现了跨学科融合的范式,通过跨界思维的哲学将瑶族刺绣图案和技艺完美融入现代家具设计中,这不仅推动了跨文化、跨工艺技术在家具设计中的美学新范式,还给打破传统界限,以促进不同领域之间的融合创新提供了新思路。瑶族刺绣所固有的丰富触感和视觉故事能够增强家具使用的感官体验,以促进传统文化与创新设计的情感共鸣。