Advancements in machine learning for material design and process optimization in the field of additive manufacturing

Additive manufacturing technology is highly regarded due to its advantages,such as high precision and the ability to address complex geometric challenges.However,the development of additive manufacturing process is constrained by issues like unclear fundamental principles,complex experimental cycles,and high costs.Machine learning,as a novel artificial intelligence technology,has the potential to deeply engage in the development of additive manufacturing process,assisting engineers in learning and developing new techniques.This paper provides a comprehensive overview of the research and applications of machine learning in the field of additive manufacturing,particularly in model design and process development.Firstly,it introduces the background and significance of machine learning-assisted design in additive manufacturing process.It then further delves into the application of machine learning in additive manufacturing,focusing on model design and process guidance.Finally,it concludes by summarizing and forecasting the development trends of machine learning technology in the field of additive manufacturing.

Flexible Fixture Design for the Top and End Surface Processing of NP2_NP4 Cylinder Heads

This paper focuses on the design of fixtures for NP2 and NP4 cylinder heads on a horizontal machining center of flexible machining automatic lines.It began with an analysis of the diagrams of part processing and working procedure which formed the basis for the design of the processing technology scheme,a selection of suitable machine tools,and the setting of processing parameters.Fixtures tailored to the chosen machine tools were then designed to meet the processing requirements.Additional aspects of the project included the design of part drawings,calculation of working time quota,design of auxiliary guides,support clamping,and hydraulic circuits,all aimed at fulfilling practical production requirements.

UNIFORM PACKING DIMENSION RESULTS FOR MULTIPARAMETER STABLE PROCESSES

In this article, authors discuss the problem of uniform packing dimension of the image set of multiparameter stochastic processes without random uniform Holder condition, and obtain the uniform packing dimension of multiparameter stable processes. If Z is a stable （N, d, α）-process and αN ≤ d, then the following holds with probability 1 Dim Z（E）=α Dim E for any Borel setE ∈B（R ＋^N）, where Z（E）={x：E←t∈E,Z（t）=x}, Dim （E） denotes the packing dimension of E.

Review of Design of Process Parameters for Squeeze Casting

Squeeze casting(SC)is an advanced net manufacturing process with many advantages for which the quality and properties of the manufactured parts depend strongly on the process parameters.Unfortunately,a universal efficient method for the determination of optimal process parameters is still unavailable.In view of the shortcomings and development needs of the current research methods for the setting of SC process parameters,by consulting and analyzing the recent research literature on SC process parameters and using the CiteSpace literature analysis software,manual reading and statistical analysis,the current state and characteristics of the research methods used for the determination of SC process parameters are summarized.The literature data show that the number of pub-lications in the literature related to the design of SC process parameters generally trends upward albeit with signifi-cant fluctuations.Analysis of the research focus shows that both“mechanical properties”and“microstructure”are the two main subjects in the studies of SC process parameters.With regard to materials,aluminum alloys have been extensively studied.Five methods have been used to obtain SC process parameters:Physical experiments,numeri-cal simulation,modeling optimization,formula calculation,and the use of empirical values.Physical experiments are the main research methods.The main methods for designing SC process parameters are divided into three categories:Fully experimental methods,optimization methods that involve modeling based on experimental data,and theoreti-cal calculation methods that involve establishing an analytical formula.The research characteristics and shortcomings of each method were analyzed.Numerical simulations and model-based optimization have become the new required methods.Considering the development needs and data-driven trends of the SC process,suggestions for the develop-ment of SC process parameter research have been proposed.

Process design and intensification of multicomponent azeotropes special distillation separation via molecular simulation and system optimization

This work provides an overview of distillation processes,including process design for different distillation processes,selection of entrainers for special distillation processes,system integration and intensification of distillation processes,optimization of process parameters for distillation processes and recent research progress in dynamic control strategies.Firstly,the feasibility of using thermodynamic topological theories such as residual curve,phase equilibrium line and distillation boundary line to analyze different separation regions is discussed,and the rationality of distillation process design is discussed by using its feasibility.Secondly,the application of molecular simulation methods such as molecular dynamics simulation and quantum chemical calculation in the screening of entrainer is discussed for the extractive distillation process.The thermal coupling mechanism of different distillation processes is used to explore the process of different process intensifications.Next,a mixed integer nonlinear optimization strategy for the distillation process based on different algorithms is introduced.Finally,the improvement of dynamic control strategies for different distillation processes in recent years is summarized.This work focuses on the application of process intensification and system optimization in the design of distillation process,and analyzes the challenges,prospects,and development trends of distillation technology in the separation of multicomponent azeotropes.

Study on trifluoromethanesulfonic acid-promoted synthesis of daidzein: Process optimization and reaction mechanism

Daidzein has been widely used in pharmaceuticals,nutraceuticals,cosmetics,feed additives,etc.Its preparation process and related reaction mechanism need to be further investigated.A cost-effective process for synthesizing daidzein was developed in this work.In this article,a two-step synthesis of daidzein(Friedel–Crafts acylation and[5+1]cyclization)was developed via the employment of trifluoromethanesulfonic acid(TfOH)as an effective promoting reagent.The effect of reaction conditions such as solvent,the amount of TfOH,reaction temperature,and reactant ratio on the conversion rate and the yield of the reaction,respectively,was systematically investigated,and daidzein was obtained in 74.0%isolated yield under optimal conditions.Due to the facilitating effect of TfOH,the Friedel–Crafts acylation was completed within 10 min at 90℃ and the[5+1]cyclization was completed within 180 min at 25℃.In addition,a possible reaction mechanism for this process was proposed.The results of the study may provide useful guidance for industrial production of daidzein on a large scale.

Combining reinforcement learning with mathematical programming:An approach for optimal design of heat exchanger networks

Heat integration is important for energy-saving in the process industry.It is linked to the persistently challenging task of optimal design of heat exchanger networks(HEN).Due to the inherent highly nonconvex nonlinear and combinatorial nature of the HEN problem,it is not easy to find solutions of high quality for large-scale problems.The reinforcement learning(RL)method,which learns strategies through ongoing exploration and exploitation,reveals advantages in such area.However,due to the complexity of the HEN design problem,the RL method for HEN should be dedicated and designed.A hybrid strategy combining RL with mathematical programming is proposed to take better advantage of both methods.An insightful state representation of the HEN structure as well as a customized reward function is introduced.A Q-learning algorithm is applied to update the HEN structure using theε-greedy strategy.Better results are obtained from three literature cases of different scales.

DIMENSION RESULTS FORORNSTEIN-UHLENBECK TYPE MARKOVPROCESS

Let {X-t, t greater than or equal to 0} be an Ornstein-Uhlenbeck type Markov process with Levy process A(t), the authors consider the fractal properties of its ranges, give the upper and lower bounds of the Hausdorff dimensions of the ranges and the estimate of the dimensions of the level sets for the process. The existence of local times and occupation times of X-t are considered in some special situations.

Evaluating Methods of Visual Assistance for Workers to Improve Quality and Usability in Individualized Kitchen Cabinet Assembly

In times of digitalisation, visual assistance systems in assembly are increasingly important. The design of these assembly systems needs to be highly complex to meet the requirements. Due to the increasing number of variants in production processes, as well as shorter innovation and product life cycles, assistance systems should improve quality and reduce complexity of assembly processes. However, many large kitchen manufacturers still assemble kitchen cabinets manually, due to the high variety of components, such as rails and fittings. This paper focuses on the analysis and evaluation of virtual assistance systems to improve quality and usability in individualised kitchen cabinet assembly processes at a large German manufacturer. A solution is identified and detailed.

Attributes of Domestic Spaces for Contemporary Habitation-A Secondary Publication

The domestic space can be defined as the sphere that articulates the needs for subjective containment and contextual stimuli.In this sense,questions arise about the indispensable attributes that spaces must possess for this articulation to take place adequately.Architecture,as the discipline in charge of satisfying the specific spatial needs of those who inhabit these spaces and,in a broader sense,as a concrete contribution to society,must address this relationship in all its complexity and generate concrete responses that incorporate the appropriate spatial attributes during the design processes.The design processes that shape living spaces confront this dialectic,and the manner in which they do so brings identity and character to them.It is believed that the higher the level of variables that are contemplated and weighted,the greater the adequacy of spaces to the changing dynamics of the people who inhabit them.This article focuses on a thorough analysis of these spatial attributes,in parallel to the definition of each one as a particular condition for design,based on their conceptualization,breakdown,and articulation.Conceptually,the following attributes are addressed:flexibility,adaptability,variability,versatility,multiplicity,plurality,integrality,gradualness,incrementality,progressiveness,independence,connectivity,intimacy,and privacy.Each of these attributes is valued as a contribution to creating adequate habitability in contextual terms,with consideration to possible integrations and combinations.

A Feature Definition Hierarchy for Supporting Design Process

特征定义的适应性是特征技术在设计过程成功应用的关键和核心问题．本文基于提出了面向设计过程的特征定义层次结构及特征定义方法，将特征定义用应用特征、形状特征和几何表示３个相对独立的层次来表示，并分别利用特征语义解释器和改进的几何关联图实现层次间的有效连接和相互转换，这不仅消弱了特征定义对应用的依赖性而更具广泛性，也为基于特征的并行设计过程模型的建立提供了基础．

PREPROCESSING AND POSTPROCESSING SYSTEM FOR FINITE ELEMENT COMPUTATION

研究了有限元计算中的单元自动划分、曲线处理、节点疏密处理、载荷自动分布、与优化设计的衔接和等应力线绘制等方面的技术问题，阐述了有限元平面八节点单元前后置处理软件的设计过程。

QUALITY FUNCTION DEPLOYMENT IN BOTTOM-UP PROCESS FOR DESIGN REUSE

To deal with a bottom up process model for design reuses a specific extended house of quality(EHOQ)is proposed Two kinds of supported functions,basic supported functions and new supported functions,are defined.Two processes to determine two kinds of functions are presented A kind of EHOQ matrix for a company is given and its management steps are studied.

Triple-Helix Structured Model Based on Problem-Knowledge-Solution Co-evolution for Innovative Product Design Process

A design problem with deficient information is generally described as wicked or ill-defined.The information insufficiency leaves designers with loose settings,free environments,and a lack of strict boundaries,which provides them with more opportunities to facilitate innovation.Therefore,to capture the opportunity behind the uncertainty of a design problem,this study models an innovative design as a composite solving process,where the problem is clarified and resolved from fuzziness to satisfying solutions by interplay among design problems,knowledge,and solutions.Additionally,a triple-helix structured model for the innovative product design process is proposed based on the co-evolution of the problem,solution,and knowledge spaces,to provide designers with a distinct design strategy and method for innovative design.The three spaces interact and co-evolve through iterative mappings,including problem structuring,knowledge expansion,and solution generation.The mappings carry the information processing and decision-making activities of the design,and create the path to satisfying solutions.Finally,a case study of a reactor coolant flow distribution device is presented to demonstrate the practicability of this model and the method for innovative product design.

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.

Study on preparation of fast curing novolaks for the shell process

To save energy and raise molding and coremaking productivity, the synthetic procedure of novolaks for the shell process was investigated. The study indicated that it was difficult to obtain fast curing novolaks under strongly acidic conditions alone. A novel synthetic procedure was proposed for preparing novolaks in a two-step manner, a divalent metal salt catalyzed novolak preparation followed by a strong acid catalyzed novolak preparation. The optimum conditions for the two-step procedure were determined by orthogonal experiment design. The results showed that it was easy to prepare fast curing novolaks with cure time in the range of 20 s to 30 s and softening point in the range of 80℃ to 90℃ under complex catalysis conditions.

Process design for gas condensate desulfurization and synthesis of nano-13X zeolite adsorbent: equilibrium and dynamic studies

This paper summarizes the results of a study of adsorption of sulfur compounds from a high-sulfur feed on improved spherical-shaped nano-AgX zeolite. For this purpose, the nano-AgX zeolite was initially synthesized and improved with silver compounds such as silver nitrate, and then it was utilized in the adsorption process. In order to investigate the equilibrium and dynamics of the adsorption process, adsorptive desulfurization of real feed(i.e., sour gas condensate from the South Pars gas field) was carried out in batch and continuous processes under several operating conditions; a temperature-dependent Langmuir isotherm model was used to fit the equilibrium data. The value of monolayer adsorption capacity(q_m) and adsorption enthalpy(ΔH) were calculated to be 1.044 mmol/g and 16.8 kJ/mol, respectively. Furthermore, a detailed theoretical model was employed in order to model the breakthrough experiments. The results revealed that an increase in the feed flow rate and 1/T values will cause linear and exponential increase in the total mass transfer coefficient(ks). Isotherm and dynamic breakthrough models were found to be in agreement with the experimental data.

ON THE HITTING PROBABILITY AND POLARITY FOR A CLASS OF SELF-SIMILAR MARKOV PROCESSES

The anthem investigate the hitting probability, polarity and the relationship between the polarity and Hausdorff dimension for self-similar Markov processes with state space (0, infinity) and increasing path.

基于Processing的何香凝艺术参与式创新转化应用研究

以何香凝艺术为对象,分析了其在创造性转化中存在的问题。通过研究运用Processing技术和参与式设计对创造性转化的潜力,发现Processing技术和参与式设计相互协作,可以成为何香凝艺术发展的双重推动力。基于这一发现,提出了一种基于Processing的何香凝艺术参与式创新转化应用策略,旨在促进何香凝艺术的创新转化。该策略将Processing技术与参与式设计相结合,提供了一种新的途径,以增加公众对何香凝艺术的参与度和认知度,进而推动其在当代社会中的发展和扩大影响力。

Computer‑aided CT image processing and modeling method for tibia microstructure

We present a method for computed tomography(CT)image processing and modeling for tibia microstructure,achieved by using computer graphics and fractal theory.Given the large-scale image data of tibia species with DICOM standard for clinical applications,we take advantage of algorithms such as image binarization,hot pixel removing and close operation to obtain visually clear image for tibia microstructure.All of these images are based on 20 CT scanning images with 30μm slice thickness and 30μm interval and continuous changes in pores.For each pore,we determine its profile by using an improved algorithm for edge detection.Then,to calculate its three-dimensional fractal dimension,we measure the circumference perimeter and area of the pores of bone microstructure using a line fitting method based on the least squares.Subsequently,we put forward an algorithm for the pore profiles through ellipse fitting.The results show that the pores have significant fractal characteristics because of the good linear correlation between the perimeter and the area parameters in log–log scale coordinates system,and the ratio of the elliptical short axis to the long axis through ellipse fitting tends to 0.6501.Based on support vector machine and structural risk minimization principle,we put forward a mapping database theory of structure parameters among the pores of CT images and fractal dimension,Poisson’s ratios,porosity and equivalent aperture.On this basis,we put forward a new concept for 3D modeling called precision-measuring digital expressing to reconstruct tibia microstructure for human hard tissue.