A Novel Method for Handicrafts Design Based on Fusion of Multi-Intelligent Decision Algorithm

Background Cardiovascular diseases are the leading cause of death throughout the developed world, attributed to approximately 17.8 million deaths worldwide in 2017 with increasing prevalence due to the aging population. Cardiovascular diseases generally result in heart failure. While the best treatment option for heart failure patients is heart transplantation, there is a severe deficiency in the availability of donor hearts. Rotary Blood Pumps (RBPs) utilised as Ventricular Assist Devices (VADs) provide an alternative treatment option. These devices are small implantable pumps that support the failing heart by providing power to augment circulation. The development of RBPs generally begins with initial designs obtained using traditional pump design methods (such as that developed by Stepanoff). However, studies have shown that this approach produces RBP prototypes far from optimal in design. Traditional theory relies on design constants derived empirically for large industrial pumps and these do not scale down well when applied to the much smaller RBPs. The initial designs are therefore generally quite poor and require an iterative build-and-test approach to obtain suitable pump prototypes – a process that is expensive and time consuming. Therefore, by improving the methodology for obtaining initial designs to better reflect the final product, development time can be greatly reduced. A popular avenue for analysing the effect of design variations and to further develop early prototypes of RBPs is to employ Computational Fluid Dynamics (CFD) simulations. These numerical simulations provide detailed data regarding the flow fields within these devices. However, a range of simulation options is available, leading to a wide range of potential predictions. In an attempt to provide a benchmark case, the FDA presented a challenge in which a pump design and test conditions were defined, allowing for direct comparison amongst different simulation approaches from a number of labs/RBP developers. The purpose of this thesis was to produce a gross design tool to provide a good starting point in RBP prototyping and a CFD simulation approach for verification that can also be used as a design refinement tool. Methods Formulating a design method for pumps requires the generation of empirical data. A number of pump design variables was identified as having an impact on pump performance, and a large number of experimental tests would have been needed to test the influence of each. Instead, a Design of Experiments (DOE) was utilised to streamline the process. The DOE outputs a relatively small number of tests required to fit a statistical model. Each design specified by the DOE was examined experimentally using a custom-built automated pump test platform to generate a number of performance measures. The obtained results were used to formulate a Response Surface Method (RSM) statistical model that showed acceptable fit to the input data. Coupled with desirability functions, the RSM model allowed for design optimisation. This tool essentially replaces Stepanoff’s traditional design methodology. The RSM model provides a robust tool that allows the user flexibility in design optimisation goals. The FDA pump was investigated in this thesis and a wide variety of simulation approaches was examined to determine which was most accurate. A range of factors were considered which included: mesh density, interface position between the rotating and stationary zones, steady vs. transient simulations, discretisation schemes, time step size and choice of turbulence model. The most appropriate option from each investigative study was selected to determine a recommended simulation approach. Final simulations were performed using these recommendations and were compared to the FDA experimental results to confirm the suitability of the suggested settings. Determination of Centrifugal Blood Pump Characteristics using CFD and Experimental Analysis iii The statistical model developed was used to design two different impellers as validation test cases. The first impeller was designed to optimise the maximum efficiency, P – Q curve slope and efficiency consistency. The second impeller was designed to mimic the approach used in traditional design methods for RBPs in setting a target design point as the primary objective and the aforementioned factors (from the first impeller) as secondary objectives. These two case studies underwent statistical performance predictions, CFD simulations, PIV analysis and experimental hydraulic testing to validate the statistical and CFD models. Results From the initial CFD study, a hybrid SBES turbulence model with full transient simulation on a fine grid with small time steps proved to be the most suitable both in terms of pressure rise generated by the FDA pump and resulting velocity fields when compared to published experimental results. From these findings the CFD modelling strategy was established. CFD results for the two validation pumps showed pressure rises matching the experimental data (8% and 1% difference for each impeller) within an acceptable range (<10% from the mean). The simulated velocity fields also closely replicated the PIV data for the majority of the flow domain. The statistical performance predictions well reflected those measured experimentally with the majority of data points falling within its confidence intervals. The hydraulic results also supported the main goal of this thesis, whereby an impeller generated using the statistical model, operated far closer to the target design point than that of a blood pump designed following Stepanoff’s methodology. Overall, both the statistical model and CFD approach provided accurate predictions and the purpose of the thesis was achieved. Final Remarks The statistical and CFD models developed in this thesis yield an effective design tool and verification methodology and show improvement over the current traditional design methods and accuracy in simulated results. Ultimately, the utilisation of these tools will lead to a reduction in the development time for new RBPs and provide a good understanding of the flow dynamics within these pumps, leading to improved pump designs reaching patients sooner. These tools are readily generalizable and could be adopted as design tools now.

This chapter focuses on recent development of direct probability-based designmethods, including the expanded reliability-based design (expanded RBD) method, reliabilitybased robust geotechnical design (RGD) method, and the new safety standards for flood defenses in the Netherlands which is the first ever national standard that adopts direct (or full) probability-based design methods. One major criticism to the simplified semi-probabilistic RBD format is displacement of sound engineering judgment and lack of flexibility for practitioners. Because the simplified semi-probabilistic RBD format adopts the same trial-and-error approach as traditional allowable stress design (ASD) methods and it is developed to circumvent the need for practitioners to perform probabilistic analysis, these compromises seem unavoidable. An alternative solution to this dilemma is to maintain the engineering judgment and flexibility similar to ASD methods, but at the expense of performing probabilistic analysis using direct probability-based designmethods. It is shown that, with the aid of commonly available computers and widely used computer software such as Microsoft Excel, performing Monte Carlo Simulation (MCS)-based probabilistic analysis and design are becoming more and more straightforward and convenient. MCS is already available in some commercial geotechnical software programs. MCS can be comprehended easily as a repetitive computer execution of traditional ASD design calculation, and the reliability analysis background required for performing MCS is substantially reduced. A gravity retaining wall design example is used in this chapter to illustrate theMCS-based design method in Excel.

The product design theory and methods based on “the Scientific Outlook on Development” have been set up by our group in recent 10 years, The new progress concerning Research of product design theory and methods include: 1) QCTES was instead of IQCTES including six requirements of product design; 2) traditional design stages were replaced with four new stages including investigation, planning, implement and inspection; 3) green design was replaced with harmonious design; 4) traditional design method was replaced with deep-layer design method; 5) concept and connotation of product top-layer design were proposed; 6) more detailed contents of product synthesis design method were advanced. We got good effects to apply above product design methodology on many product designs recent years.

The use of flexible roof diaphragms is very common in the United States, both for residential buildings and large-scale commercial buildings. Due to its simplicity, the traditional diaphragm design method is commonly used in diaphragm design, in particular for the design of diaphragms with relatively small dimensions. The traditional diaphragm design method assumes the axial chord forces developed in framing members under in-plane loading are carried only by the perimeter elements. The traditional diaphragm design method has always been thought to be a conservative design method, especially when applied to large diaphragms. In recent years, the engineering community began to question the applicability of the traditional diaphragm design method. A new design approach known as the collective chord design method was proposed to analyze the chord forces for very large flexible roof diaphragms. This method utilizes strain compatibility of a simple beam to estimate the axial forces in chord members. This paper evaluates the applicability of the traditional and collective chord design methods by modeling the behavior of large panelized roof diaphragms numerically.

After hundreds of years of changes, due to the development of chemistry, the development of human life has undergone tremendous changes. People have used chemical science to manufacture many supplies, such as various medicines and various types of cosmetics. In recent decades, electronic components and computer software technology have developed rapidly, and the fourth round of technological revolution is underway, which has a favorable impact on the development of various industries. Traditional paper‐cut and cosmetic bag design methods should also take into account the advantages of wireless communication and artificial intelligence technology and combine other types of traditional industries to carry out technological reforms to help traditional craftsmanship pass down. In modern life, due to the vigorous promotion of cosmetics, there are more and more cosmetics on the market, and the traditional paper‐cut art itself is an artistic design method similar to cosmetic design. Both industries will grow rapidly after the use of artificial intelligence and wireless communication technology for the update of both industries. Therefore, the purpose of this paper is to combine wireless communication technology with artificial intelligence technology to transform the traditional paper‐cut art and cosmetic packaging design. After consulting the reasons for the decline of the traditional handicraft industry and the reasons for the turmoil caused by modern technology, this paper conducts a combined design of artificial intelligence technology, wireless communication technology, and cosmetic packaging and then performs wireless communication and artificial intelligence on the cutting of traditional paper design elements. The design of the technical matching system is also designed for traditional paper‐cut art and cosmetic packaging. And find professional practitioners for research and discussion and multiple transformations and obtain experimental analysis results data. After many experiments, it can be seen that the combination of wireless communication and artificial intelligence technology can transform the traditional paper‐cut art and cosmetic packaging design, improve their relevance, continue the inheritance of paper‐cut art, and possibly improve the efficacy of cosmetics.

Over the past 30 years from the end of the 20th century to the present, service robotics technology has made great progress, and many important results have been achieved in the broad interdisciplinary fields of robot mechanical structure, information transmission and interaction, material science, automation control, sensor technology, etc. . Every breakthrough in key technologies has enabled service robots to develop rapidly in the direction that people expect. With the in-depth development of Internet technology, the comprehensive popularization and promotion of the Internet of Things technology led by 5G. Coupled with the continuous breakthrough of new developments in the field of artificial intelligence, the development of service robots has encountered an unprecedented technological dividend period, and will surely usher in considerable development, becoming an important driving force for the promotion of human civilization and economic development.The rapid development of many advanced technologies such as artificial intelligence, big data, and 5G communications has directly promoted the rapid development of the robotics industry. Under the impetus of new technologies, service robots closely related to humans are developing rapidly. Service robots are becoming more and more intelligent. In this context, the design principles of service robots, interaction design, service mode design and other related fields are in urgent need of intelligent transformation, and the concept of intelligent design with artificial intelligence as the core has begun to be paid attention to by the academic community.The research on intelligent design in academia is currently mainly in the review stage, and the field of discussion is mainly focused on graphic design. This article hopes to broaden the research field of intelligent design by studying the intelligent design of service robots. At the same time, it provides new ideas and new paradigms for the innovative design of service robots to improve the user experience and service quality of service robots. This research mainly studies the design principles, design goals, interaction design, service mode and design process of existing service robots based on the perspective of intelligent design. This article mainly uses the literature analysis method and the desktop survey method to sort out related theories and design methods and combines specific practical case analysis to make a bold outlook on the intelligent design of service robots to help the intelligent transformation of service robots.In the era of intelligent design, the design principles of service robots are also changing and iterating. First of all, service robots must adapt to their service scenarios. Different service scenarios have different requirements for the function and existence of the product; secondly, Secondly, the interaction design of service robots should be carried out based on user experience, and technology serves as a tool to enhance users’ experience ; the last is the discussion of appearance design principles of service robots. This article takes the LeoBots Scrub Singapore sweeping robot as an example to propose that the appearance design of service robots needs to be developed around safety, emotion and bionics. Intelligent design is guided by traditional design thinking and methods, and conducts big data analysis and intelligent research on the essence, process, thinking and other aspects of industrial design through related design methodology, as the basis for intelligent design to simulate artificial design. The core technical means of intelligent design is artificial intelligence, which is based on big data analysis, combined with artificial intelligence technologies such as machine learning, artificial neural networks, genetic algorithms, and deep learning to achieve the intelligent development of the entire process design.The change of service robot design principles and the addition of intelligent design have changed the design process of service robots. Based on the practical cases of Haier U-BOT robots, this article actively explores the service robot design process under the development trend of intelligent transformation based on intelligent design in order to provide new ideas for the intelligent design of service robots. The intelligent transformation of service robots promotes the development of intelligent design, and intelligent design drives the intelligent transformation of service robots.

The floor plan layout of museum exhibition spaces is the skeleton network of the museum, which determines the internal circulation and spatial form of the museum. This paper studies the method and practice of using artificial intelligence technology to assist in the space design of exhibition halls in urban cultural museums. First, it introduces the limitations of traditional space design methods for exhibition halls in urban cultural museums and the superiority and application prospects of the CGAN (conditional generative adversarial network) model in space design. Second, the principle and training process of the CGAN model are explained in detail, and the experimental results and analysis are given. By learning 100 floor plans of exhibition halls of urban culture museums, the CGAN model can generate a new floor plan design for an exhibition hall, which provides a new idea and innovative method for this design task. Finally, the limitations and future research directions of the CGAN model in the space design of urban cultural museum exhibition halls are discussed. The study shows that using the CGAN model to learn the floor plans of exhibition halls of urban cultural museums can effectively improve the innovation and practicability of space design and has the following advantages: (1) It can quickly generate a large number of exhibition hall floor plans, shorten the design cycle, and improve design efficiency. (2) The generated floor plan designs of the exhibition hall are diverse and personalized, meeting the design requirements of different scenarios and needs. (3) The method promotes the deep integration of space design and artificial intelligence technology and provides new possibilities and ideas for space design. These conclusions provide new ideas and methods for the space design of exhibition halls of urban cultural museums and provide a reference and inspiration for space design and intelligent applications in other fields, such as office space design, home decoration space design, landscape space design, and historical arcade and building renovation design.

The floor plan layout of museum exhibition spaces is the skeleton network of the museum, which determines the internal circulation and spatial form of the museum. This paper studies the method and practice of using artificial intelligence technology to assist in the space design of exhibition halls in urban cultural museums. First, it introduces the limitations of traditional space design methods for exhibition halls in urban cultural museums and the superiority and application prospects of the CGAN (conditional generative adversarial network) model in space design. Second, the principle and training process of the CGAN model are explained in detail, and the experimental results and analysis are given. By learning 100 floor plans of exhibition halls of urban culture museums, the CGAN model can generate a new floor plan design for an exhibition hall, which provides a new idea and innovative method for this design task. Finally, the limitations and future research directions of the CGAN model in the space design of urban cultural museum exhibition halls are discussed. The study shows that using the CGAN model to learn the floor plans of exhibition halls of urban cultural museums can effectively improve the innovation and practicability of space design and has the following advantages: (1) It can quickly generate a large number of exhibition hall floor plans, shorten the design cycle, and improve design efficiency. (2) The generated floor plan designs of the exhibition hall are diverse and personalized, meeting the design requirements of different scenarios and needs. (3) The method promotes the deep integration of space design and artificial intelligence technology and provides new possibilities and ideas for space design. These conclusions provide new ideas and methods for the space design of exhibition halls of urban cultural museums and provide a reference and inspiration for space design and intelligent applications in other fields, such as office space design, home decoration space design, landscape space design, and historical arcade and building renovation design.

Machine-learning-accelerated design of functional structural components in deep-sea soft robots

LCL filter has been widely used in grid-connected inverter system because of its excellent high-frequency harmonic suppression ability. However, the parameter design of LCL filter involves many mutually restrictive factors, such as THD, filter volume, power loss, cost and system stability, and it is difficult for traditional empirical design methods to achieve the best balance among these performance indicators. To solve this problem, this paper proposes an optimal design method of LCL filter based on multi-objective genetic algorithm (MOGA). Firstly, the mathematical model of LCL filter is established, and the optimization objectives are defined from frequency domain and time domain, including harmonic suppression effect, loss and the influence of filter parameters on system stability. The effectiveness of the proposed method is verified by MATLAB/Simulink analysis, and compared with the traditional design method. The results show that the optimization strategy can effectively reduce the grid-side current THD, optimize the filter volume and power loss, improve the stability and adaptability of the system, and help to improve the overall performance and engineering application value of the grid-connected inverter system.

MGSE [1] (Mechanical Ground Support Equipment) is necessary equipment for spacecraft research and development. The traditional MGSE design method requires repeated modeling, analysis and drawing, so the traditional design method is inefficient for the design of stereotyped MGSE. This paper introduces a new parameter-based fast design MGSE method. This method extracts the key parameters to drive the establishment of the model. Parametric analysis can be carried out in the system. Compared with traditional design methods, the efficiency can be at least double.

The paper describes the mergence of traditional architectural design processes with approaches that rely on digital media and software for the creation of architectural space. The depicted projects are part of a ‘work in progress’ process, with a recent studio that is set up to apply the so far accumulated experiences. Within the projects, focus is on those design phases where the applied media and methodology is changed and where the back and forth between different media and the depth of their implementation is perceptible in, and / or has a significant influence on the design itself. Through a line of successive experiments, the paper explains the development of a possible method that utilizes a variety of today’s accessible tools in architecture, making use of phenomena that appear when changing from one tool to another. Goal is to avoid limitations that are existent by the solely employment of one media or method, and to understand the fusion between different media as an inspiring momentum to develop the design further. The paper draws a line from an initially experienced and analyzed design method over several projects in practice and academia to conclude with a possible design method that could be established successfully in both fields of architectural teaching and practice. Initial experiences had been drawn from professional practice, in which the digital realm was limited to a support device of the design process. The first project that is described in the paper, explored the employment of digital media as a possible tool to drive the design process in a broader sense. The studio setting was organized as a laboratory for the exploration of the change of applied media. Focus was on the influence on the design progress. The design method required of the studios participants was not exclusively based on an architectural program, but on an initial, very conceptual process with an artistic approach, based on personal experiences of each participant. This was meant to detach the students entirely from architectural processes and mindsets they had picked up so far. Parallel to that kind of an intellectual process, studio participants learned to handle Maya as the 3D modeling software of their choice. Both the technical knowledge and the artistic projects were merged in a second project phase, in which participants had to further develop their work by applying a very effective mix of various design tools. Using digital media as a parametric design generator, subsequent projects were developed. The task for the designers here were to decide what kind of algorithm could be applied to which process and when it was to be stopped for the best result. Applying such an automatism successfully to the design process, the employment of traditional media and methodology remained, to adapt the digital driven schemes to the required design task. The diverse design experiments demonstrate important aspects when merging complex design and animation software with traditional design processes. To achieve good architectural design results, all examined projects showed that traditional design methods with its physical models are hardly replaceable to its full extent by other media, but digital media are able to strengthen design processes and invite designers to explore new means of design work.

With the rapid development of artificial intelligence technology, its application in the field of game development is becoming more and more extensive, especially in the design of game character actions. This paper explores how artificial intelligence technology can empower game character action design and improve design efficiency and quality. First, the limitations of traditional game character action design methods are introduced, including time-consuming and labor-intensive, lack of diversity and other issues. Secondly, the current application status of artificial intelligence in game character action design is analyzed, focusing on the application of machine learning, deep learning and reinforcement learning in action generation, optimization and adaptability. Then, the game character action design method based on artificial intelligence is elaborated in detail, including innovative technologies such as data-driven action generation, intelligent action editing system, and adaptive action control. Then, the challenges faced by game character action design under the empowerment of artificial intelligence, such as data quality, computing resource requirements, and artistic style maintenance, are discussed, and corresponding solutions are proposed. Finally, the future development trend of artificial intelligence in the field of game character action design is prospected, including cross-modal learning, real-time action generation, and personalized character actions. This study aims to provide game developers with new perspectives and methods to promote the in-depth application and innovative development of artificial intelligence technology in game character action design.

A fast and efficient multiobjective optimization design method is developed for induction machines, which requires much fewer design iterations than the traditional design methods. In this new method, the number of prime variables that define the optimization is reduced to only six. A canonical particle swarm optimization (PSO) method with penalty function for design constraints is developed to find the optimal solution for a user-defined objective function. After several trial solutions with the PSO, the optimal regions for both the design variables and the performance indexes can be estimated. The results will provide useful information for both a drive system designer and a machine designer at an early stage of the design process. A comparison study of PSO and genetic algorithm (GA) is also performed in this paper, and the comparison shows that PSO is more successful in finding the global optima and also has better computational efficiency than GA. The original contributions of this paper are a novel induction machine design method, consideration of winding turn selection limitation, and a machine-design-focused comparison.

With the increasing demands of health care, the design of hospital buildings has become increasingly demanding and complicated. However, the traditional layout design method for hospital is labor intensive, time consuming and prone to errors. With the development of artificial intelligence (AI), the intelligent design method has become possible and is considered to be suitable for the layout design of hospital buildings. Two intelligent design processes based on healthcare systematic layout planning (HSLP) and generative adversarial network (GAN) are proposed in this paper, which aim to solve the generation problem of the plane functional layout of the operating departments (ODs) of general hospitals. The first design method that is more like a mathematical model with traditional optimization algorithm concerns the following two steps: developing the HSLP model based on the conventional systematic layout planning (SLP) theory, identifying the relationship and flows amongst various departments/units, and arriving at the preliminary plane layout design; establishing mathematical model to optimize the building layout by using the genetic algorithm (GA) to obtain the optimized scheme. The specific process of the second intelligent design based on more than 100 sets of collected OD drawings includes: labelling the corresponding functional layouts of each OD plan; building image-to-image translation with conditional adversarial network (pix2pix) for training OD plane layouts, which is one of the most representative GAN models. Finally, the functions and features of the results generated by the two methods are analyzed and compared from an architectural and algorithmic perspective. Comparison of the two design methods shows that the HSLP and GAN models can autonomously generate new OD plane functional layouts. The HSLP layouts have clear functional area adjacencies and optimization goals, but the layouts are relatively rigid and not specific enough. The GAN outputs are the most innovative layouts with strong applicability, but the dataset has strict constraints. The goal of this paper is to help release the heavy load of architects in the early design stage and present the effectiveness of these intelligent design methods in the field of medical architecture.