Exploring Digital Visualization Methods in Urban Public Building Space Design

Digital technology has driven the innovation of architectural design methods and tools,applying digital techniques to allow greater possibilities for more innovative and scientific design of public building spaces.This article first analyzes the characteristics of digital visualization and its advantages in the design of urban public building spaces,including aspects such as visualizing three-dimensional expression,rational analysis of building space,Virtual Reality Experience,and integration of design and construction processes.Subsequently,by introducing digital design methods such as parametric design,algorithmic generation,nonlinear design,and artificial intelligence-assisted design,it explores the methods and implementation approaches of digital visualization in the design of public building spaces.The aim is to offer insights and references for the deeper integration of digital technology into architectural design practices.

Analysis of Urban Public Building Space Design Strategies in the Digital Age

Urban public building spaces involve various aspects of people’s daily activities and interactions,making the rationality and scientific nature of the design of these spaces crucial.This article first discusses the role and impact of digitization in the design of public building spaces,covering aspects such as digital design methods,visual expression and presentation,augmented reality’s spatial interaction experience,and integrated design and construction.Following that,it analyzes the process of digitized urban public building space design by exploring topics like digital space design and modeling,visual representation of digital spaces,digital performance analysis of spaces,and the integration of digital projects.This article aims to provide insights and references for urban public building space design in the digital era.

Research on the Application and Development of Digital Media Art in Urban Public Space Design

Digital media art is an emerging art form that combines digital technology and media art.It has huge potential to bring innovation to urban public spaces and provide them with vibrant artistic experiences.This article analyzes the design significance and value of digital media art in urban public space,its various forms of application in urban public space design,and the innovative ideas and paths that digital media art can take in urban public space to guide the future.The application and innovative methods of digital media art in urban public space design provide certain theoretical and practical references for urban planners and designers.

Design space exploration of neural network accelerator based on transfer learning

With the increasing demand of computational power in artificial intelligence(AI)algorithms,dedicated accelerators have become a necessity.However,the complexity of hardware architectures,vast design search space,and complex tasks of accelerators have posed significant challenges.Tra-ditional search methods can become prohibitively slow if the search space continues to be expanded.A design space exploration(DSE)method is proposed based on transfer learning,which reduces the time for repeated training and uses multi-task models for different tasks on the same processor.The proposed method accurately predicts the latency and energy consumption associated with neural net-work accelerator design parameters,enabling faster identification of optimal outcomes compared with traditional methods.And compared with other DSE methods by using multilayer perceptron(MLP),the required training time is shorter.Comparative experiments with other methods demonstrate that the proposed method improves the efficiency of DSE without compromising the accuracy of the re-sults.

The Application and Prospects of Digital Visualization in Urban Public Building Space Design

With the development and innovation of digital information technology, digital visualization plays an increasingly important role in the design of urban public building spaces. This paper explores the application of digital visualization technology in the design of urban public building spaces and looks ahead to future trends. Firstly, it analyzes the challenges in the design of urban public building spaces, including extensive professional involvement, complex functional layout requirements, rational emergency evacuation routes, multidimensional analysis of architectural spatial environments, and appropriate selection of decorative materials. Next, it introduces the applications of digital visualization technology in showcasing visual design and expression, optimizing spatial functional layouts, enhancing the rationality of evacuation routes, analyzing dynamic environmental impacts and energy consumption, and improving the effectiveness of material selection in the design of urban public building spaces. Lastly, it discusses the prospects of extended reality (XR) technology, interactive design using data platforms, and AI technology in the design of public building spaces. It is hoped that this paper provides inspiration and reference for the deeper application of digital information technology in the field of architecture. .

Metamodel-based Global Optimization Using Fuzzy Clustering for Design Space Reduction

High fidelity analysis are utilized in modern engineering design optimization problems which involve expensive black-box models.For computation-intensive engineering design problems,efficient global optimization methods must be developed to relieve the computational burden.A new metamodel-based global optimization method using fuzzy clustering for design space reduction(MGO-FCR) is presented.The uniformly distributed initial sample points are generated by Latin hypercube design to construct the radial basis function metamodel,whose accuracy is improved with increasing number of sample points gradually.Fuzzy c-mean method and Gath-Geva clustering method are applied to divide the design space into several small interesting cluster spaces for low and high dimensional problems respectively.Modeling efficiency and accuracy are directly related to the design space,so unconcerned spaces are eliminated by the proposed reduction principle and two pseudo reduction algorithms.The reduction principle is developed to determine whether the current design space should be reduced and which space is eliminated.The first pseudo reduction algorithm improves the speed of clustering,while the second pseudo reduction algorithm ensures the design space to be reduced.Through several numerical benchmark functions,comparative studies with adaptive response surface method,approximated unimodal region elimination method and mode-pursuing sampling are carried out.The optimization results reveal that this method captures the real global optimum for all the numerical benchmark functions.And the number of function evaluations show that the efficiency of this method is favorable especially for high dimensional problems.Based on this global design optimization method,a design optimization of a lifting surface in high speed flow is carried out and this method saves about 10 h compared with genetic algorithms.This method possesses favorable performance on efficiency,robustness and capability of global convergence and gives a new optimization strategy for engineering design optimization problems involving expensive black box models.

Reliable Space Pursuing for Reliability-based Design Optimization with Black-box Performance Functions

Reliability-based design optimization （RBDO） is intrinsically a double-loop procedure since it involves an overall optimization and an iterative reliability assessment at each search point. Due to the double-loop procedure, the computational expense of RBDO is normally very high. Current RBDO research focuses on problems with explicitly expressed performance functions and readily available gradients. This paper addresses a more challenging type of RBDO problem in which the performance functions are computation intensive. These computation intensive functions are often considered as a ＂black-box＂ and their gradients are not available or not reliable. On the basis of the reliable design space （RDS） concept proposed earlier by the authors, this paper proposes a Reliable Space Pursuing （RSP） approach, in which RDS is first identified and then gradually refined while optimization is performed. It fundamentally avoids the nested optimization and probabilistic assessment loop. Three well known RBDO problems from the literature are used for testing and demonstrating the effectiveness of the proposed RSP method.

Minimax designs for linear regression models with bias in a reproducing kernel Hilbert space in a discrete set

Consider the design problem for estimation and extrapolation in approximately linear regression models with possible misspecification. The design space is a discrete set consisting of finitely many points, and the model bias comes from a reproducing kernel Hilbert space. Two different design criteria are proposed by applying the minimax approach for estimating the parameters of the regression response and extrapolating the regression response to points outside of the design space. A simulated annealing algorithm is applied to construct the minimax designs. These minimax designs are compared with the classical D-optimal designs and all-bias extrapolation designs. Numerical results indicate that the simulated annealing algorithm is feasible and the minimax designs are robust against bias caused by model misspecification.

Analysis of Space Design of a Campus Square from the Perspective of Humanity:A Case Study of Sanjiacun Square in Xiamen University

The behavior styles of students which are the main service groups of Sanjiacun Square in Xiamen University were surveyed and analyzed firstly from the aspects of their perception,use and assessment of the square space,and then strategies to design the square space in the campus from the perspective of humanity were summarized to provide scientific references for the design of a square space in an university campus.

A structural topological optimization method for multi-displacement constraints and any initial topology configuration

In density-based topological design, one expects that the final result consists of elements either black （solid material） or white （void）, without any grey areas. Moreover, one also expects that the optimal topology can be obtained by starting from any initial topology configuration. An improved structural topological optimization method for multidisplacement constraints is proposed in this paper. In the proposed method, the whole optimization process is divided into two optimization adjustment phases and a phase transferring step. Firstly, an optimization model is built to deal with the varied displacement limits, design space adjustments, and reasonable relations between the element stiffness matrix and mass and its element topology variable. Secondly, a procedure is proposed to solve the optimization problem formulated in the first optimization adjustment phase, by starting with a small design space and advancing to a larger deign space. The design space adjustments are automatic when the design domain needs expansions, in which the convergence of the proposed method will not be affected. The final topology obtained by the proposed procedure in the first optimization phase, can approach to the vicinity of the optimum topology. Then, a heuristic algorithm is given to improve the efficiency and make the designed structural topology black/white in both the phase transferring step and the second optimization adjustment phase. And the optimum topology can finally be obtained by the second phase optimization adjustments. Two examples are presented to show that the topologies obtained by the proposed method are of very good 0/1 design distribution property, and the computational efficiency is enhanced by reducing the element number of the design structural finite model during two optimization adjustment phases. And the examples also show that this method is robust and practicable.

Optimal design of near-Earth asteroid sample-return trajectories in the Sun–Earth–Moon system

In the 6th edition of the Chinese Space Trajectory Design Competition held in 2014, a near-Earth asteroid sample-return trajectory design problem was released, in which the motion of the spacecraft is modeled in multi-body dynamics, considering the gravitational forces of the Sun, Earth, and Moon. It is proposed that an electric-propulsion spacecraft initially parking in a circular 200-kin-altitude low Earth orbit is expected to rendezvous with an asteroid and carry as much sample as possible back to the Earth in a 10-year time frame. The team from the Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences has reported a solution with an asteroid sample mass of 328 tons, which is ranked first in the competition. In this article, we will present our design and optimization methods, primarily including overall analysis, target selection, escape from and capture by the Earth-Moon system, and optimization of impulsive and low-thrust trajectories that are modeled in multi-body dynamics. The orbital resonance concept and lunar gravity assists are considered key techniques employed for trajectory design. The reported solution, preliminarily revealing the feasibility of returning a hundreds-of-tons asteroid or asteroid sample, envisions future space missions relating to near-Earth asteroid exploration.

Fluidised bed granulation of two APIs:QbD approach and development of a NIR in-line monitoring method

The study focused on the fluid-bed granulation process of a product with two active pharmaceutical ingredients,intended for coated tablets preparation and further transfer to industrial scale.The work aimed to prove that an accurate control of the critical granulation parameters can level the input material variability and offer a user-friendly process control strategy.Moreover,an in-line Near-Infrared monitoring method was developed,which offered a real time overview of the moisture level along the granulation process,thus a reliable supervision and control process analytical technology(PAT)tool.The experimental design’s results showed that the use of apparently interchangeable active pharmaceutical ingredients(APIs)and filler sorts that comply with pharmacopoeial specifications,lead to different end-product critical attributes.By adapting critical granulation parameters(i.e.binder spray rate and atomising pressure)as a function of material characteristics,led to granules with average sizes comprised in a narrow range of 280–320μm and low nongranulated fraction of under 5%.Therefore,the accurate control of process parameters according to the formulation particularities achieved the maintenance of product within the design space and removed material related variability.To complete the Quality by design(QbD)strategy,despite its limited spectral domain,the microNIR spectrometer was successfully used as a robust PAT monitoring tool that offered a real time overview of the moisture level and allowed the supervision and control of the granulation process.

Optimal design of the link lengths for a planar parallel manipulator

This paper addresses geometry design of a new kind of 2-DOF parallel manipulator actuated horizontally by linear actua- tors. The first step of the optimum design involves developing a non-dimensional structure of the planar 2-DOF parallel manipulator. The global conditioning index, global velocity index, global stiffness index and global payload index of the 2-DOF parallel manipu- lators are investigated, and the geometrical parameters without dimension are determined with respect to the specification on per- formances. Finally, based on the optimum non-dimensional result, the optimum dimensional parameters are achieved which is suit- able for the desired workspace. The optimum methodology of this paper is convenient and can be extended to other parallel mecha-

HYPERSTATIC STRUCTURE MAPPING MODEL BUILDING AND OPTIMIZING DESIGN

Hyperstatic structure plane model being built by structural mechanics is studied. Space model precisely reflected in real stress of the structure is built by finite element method （FEM） analysis commerce software. Mapping model of complex structure system is set up, with convenient calculation just as in plane model and comprehensive information as in space model. Plane model and space model are calculated under the same working condition. Plane model modular construction inner force is considered as input data; Space model modular construction inner force is considered as output data. Thus specimen is built on input data and output dam. Character and affiliation are extracted through training specimen, with the employment of nonlinear mapping capability of the artificial neural network. Mapping model with interpolation and extrpolation is gained, laying the foundation for optimum design. The steel structure of high-layer parking system （SSHLPS） is calculated as an instance. A three-layer back-propagation （BP） net including one hidden layer is constructed with nine input nodes and eight output nodes for a five-layer SSHLPS. The three-layer structure optimization result through the mapping model interpolation contrasts with integrity re-analysis, and seven layers structure through the mapping model extrpulation contrasts with integrity re-analysis. Any layer SSHLPS among 1-8 can be calculated with much accuracy. Amount of calculation can also be reduced if it is appfied into the same topological structure, with reduced distortion and assured precision.

Analysis and design for architecture-based software

The technologies of software architecture are introduced, and the software analysis-and-design process is divided into requirement analysis, software architecture design and system design. Using these technologies, a model of architecture-centric software analysis and design process（ACSADP） is proposed. Meanwhile, with regard to the completeness, consistency and correctness between the software requirements and design results, the theories of function and process control are applied to ACSADP. Finally, a model of integrated development environnment （IDE） for ACSADP is propcsed. It can be demonstrated by the practice that the model of ACSADP can aid developer to manage software process effectively and improve the quality of software analysis and design.

Spatial Layout of Mountainous Elderly Residential Districts

Taking the planning of elderly building for example, this paper explored the spatial layout, entrance/exit design, road space design and landscape design of the elderly residential districts against the background of population aging and increasing demands of ecological residence. In addition, the paper tried to fully use outstanding natural environment in mountainous areas to plan the elderly community, and integrate the characteristics of mountainous community planning and elderly buildings.

Protection and Development of Children's Creativity Based on the Creation of Child-friendly Cities

The present society values the protection and development of children’s creativity,and adopted measures in many aspects,but there are still many children’s ideas that are guided by mechanization,so that their creativity is bound,eventually making less likely to children’s development.Therefore,in the construction of children’s friendly cities,it is necessary to pay special attention to the protection and development of children’s creativity.In this paper,through a large number of cases,the protection and development of children’s creativity under the establishment of child-friendly cities were studied and discussed,and the construction principles and methods for this problem,as well as specific measures were put forward.

Data Mining and Machine Learning Methods Applied to A Numerical Clinching Model

Numerical mechanical models used for design of structures and processes are very complex and high-dimensionally parametrised.The understanding of the model characteristics is of interest for engineering tasks and subsequently for an efficient design.Multiple analysis methods are known and available to gain insight into existing models.In this contribution,selected methods from various fields are applied to a real world mechanical engineering example of a currently developed clinching process.The selection of introduced methods comprises techniques of machine learning and data mining,in which the utilization is aiming at a decreased numerical effort.The methods of choice are basically discussed and references are given as well as challenges in the context of meta-modelling and sensitivities are shown.An incremental knowledge gain is provided by a step-bystep application of the numerical methods,whereas resulting consequences for further applications are highlighted.Furthermore,a visualisation method aiming at an easy design guideline is proposed.These visual decision maps incorporate the uncertainty coming from the reduction of dimensionality and can be applied in early stage of design.

Establishment and reliability evaluation of the design space for HPLC analysis of six alkaloids in Coptis chinensis(Huanglian) using Bayesian approach

Coptis chinensis(Huanglian) is a commonly used traditional Chinese medicine(TCM) herb and alkaloids are the most important chemical constituents in it. In the present study, an isocratic reverse phase high performance liquid chromatography(RP-HPLC) method allowing the separation of six alkaloids in Huanglian was for the first time developed under the quality by design(Qb D) principles. First, five chromatographic parameters were identified to construct a Plackett-Burman experimental design. The critical resolution, analysis time, and peak width were responses modeled by multivariate linear regression. The results showed that the percentage of acetonitrile, concentration of sodium dodecyl sulfate, and concentration of potassium phosphate monobasic were statistically significant parameters(P < 0.05). Then, the Box-Behnken experimental design was applied to further evaluate the interactions between the three parameters on selected responses. Full quadratic models were built and used to establish the analytical design space. Moreover, the reliability of design space was estimated by the Bayesian posterior predictive distribution. The optimal separation was predicted at 40% acetonitrile, 1.7 g·m L-1of sodium dodecyl sulfate and 0.03 mol·m L-1 of potassium phosphate monobasic. Finally, the accuracy profile methodology was used to validate the established HPLC method. The results demonstrated that the Qb D concept could be efficiently used to develop a robust RP-HPLC analytical method for Huanglian.

Variable-fidelity optimization with design space reduction

Advanced engineering systems, like aircraft, are defined by tens or even hundreds of design variables. Building an accurate surrogate model for use in such high-dimensional optimization problems is a difficult task owing to the curse of dimensionality. This paper presents a new algorithm to reduce the size of a design space to a smaller region of interest allowing a more accurate surrogate model to be generated. The framework requires a set of models of different physical or numerical fidelities. The low-fidelity （LF） model provides physics-based approximation of the high-fidelity （HF） model at a fraction of the computational cost. It is also instrumental in identifying the small region of interest in the design space that encloses the high-fidelity optimum. A surrogate model is then constructed to match the low-fidelity model to the high-fidelity model in the identified region of interest. The optimization process is managed by an update strategy to prevent convergence to false optima. The algorithm is applied on mathematical problems and a two-dimen-sional aerodynamic shape optimization problem in a variable-fidelity context. Results obtained are in excellent agreement with high-fidelity results, even with lower-fidelity flow solvers, while showing up to 39% time savings.