Improve Design Efficiency Research Articles

A universal algorithm for linear and quadratic programming in the problems of contact deformation of cable-stayed structures with one-way connections

Problems in production activities that require optimization problems are extremely numerous and very diverse. Optimization approaches are most often associated with the search for the best version of a structure or building. Mathematical methods for solving such problems are developing rapidly and are widely used. They actively and productively penetrate into many areas of scientific research, into engineering and design developments, are an important tool for improving design efficiency throughout the entire process of creating structures. The search for the best design solution is reduced to the selection of a set of parameters that provide a stationary value of the objective function. A wide range of extreme problems of practical orientation, as a rule, in mathematical models contains restrictions on design parameters of the equality-inequality type. In general, their set makes up the content of such a section of mathematics as Mathematical Programming. Due to the fact that there is no single solution method, diversity in research approaches has formed, which divides them into groups, classes, etc. Linear programming (LP), as one of the sections, with a linear objective function and constraints is well studied and successfully applied. Methods of solving problems of nonlinear programming, which includes quadratic programming, are more complex. Therefore, the development of convenient computational schemes is relevant. The essence of this work is that the statements of 2 optimization problems are formalized in a single and convenient form of a symmetric matrix dependence, which makes it possible to obtain an effective (in our opinion) algorithm for their implementation. Namely, a unified scheme for solving both LP and KP problems based on matrix algebra operations is proposed. Quadratic programming (QP), as the second section, also has wide possibilities, in particular, it allows considering the practical tasks of calculating VAT in the mechanics of a deformed solid body under the conditions of contact interaction. Such problems, in particular, include cable-stayed structures with one-way connections and span lengths that can reach tens or hundreds of meters. As an example, the behavior of a model cable-stayed span structure under varying wind loads is considered. The given results may be of interest.

Design Principle of RF Stealth Anti-Sorting Signal Based on Multi-Dimensional Compound Modulation with Pseudo-Center Width Agility

Anti-sorting signal design is an important direction of radio frequency (RF) stealth signal design. The RF stealth signal design is based on the anti-sorting signal design principle, which is essentially the failure principle of the radar signal sorting algorithm. Cluster pre-sorting, the key to radar signal sorting, has the advantages of fast sorting, simultaneous sorting of multiple sources, and greatly reduced computational pressure of the main sorting. However, a unified and widely applicable cluster-sorting failure principle guiding the anti-sorting signal design has not been formally reported in RF stealth anti-sorting signal design. In this paper, the principles of the data field-based K-means clustering algorithm and the fuzzy C-means clustering algorithm are first studied. Aiming at the key step of data similarity measurement in the clustering algorithm, the failure principle of cluster sorting based on pseudo-center wide-agile multi-dimensional compound modulation is proposed. This principle can correctly guide the design of the anti-clustering sorting signal, so it is also called the design principle of the RF stealth anti-sorting signal based on pseudo-center wide-agile multi-dimensional compound modulation. The correctness of the principle is proved by formula derivation, signal simulation, and a sorting experiment. Through a signal comparison simulation with random interference pulse anti-sorting signals, it is strongly proved that the anti-sorting performance of signals designed under the guidance of the anti-clustering signal design principle proposed in this paper is stronger than that of random interference pulse signals. This study provides theoretical support for designing RF stealth anti-sorting signals. Using the signal design principle proposed in this paper, the anti-sorting performance of the RF stealth signal is improved by 10%. The principle of signal design helps to improve design efficiency.

Knowledge Modelling for the Smart Design of Aluminium Profile Extrusion Dies

Aluminium profiles are widely used in distinct fields since their excellent physical properties, and the quality and efficiency of producing aluminium profiles are largely depending on the extrusion dies. Therefore, the design of the aluminium extrusion die is the most significant part. However, the extrusion die design is a complex process, which includes plenty of data, information, and knowledge. In production, reusing part of the previous design information and knowledge can improve design efficiency. In this case, this study has explored the way to systematically model the design knowledge generated during the aluminium extrusion die design process. Firstly, knowledge representation models have been created, acting as the schema layer of the domain knowledge graph for the aluminium extrusion die design. This knowledge graph is subsequently used as the repository of a Web-based smart design system. By providing the three key functionalities of knowledge representation, semantic retrieval and intelligent recommendation, the smart design system can help engineers effectively reuse previous design knowledge to improve design efficiency and quality.

Design and Improvement of Digital Communication System Based on EDA Platform

The design of digital circuit systems based on EDA tools can greatly improve design efficiency. In this paper, a multi-mode communication signal modulation and demodulation system are designed with FPGA as the hardware carrier. Furthermore, this paper puts forward a teaching and experimental scheme of communication circuits, that is, using the EDA platform to realize different modulation and demodulation modes. The advantage of this scheme is that it can not only be realized in hardware, but also can analyze the performance accurately and that the waveform is intuitive. This scheme can make students feel the advantages of EDA Technology in complex logic circuit design. Students can understand new communication modes deeply by using EDA technology.

RISE-based adaptive tracking control for Euler–Lagrange mechanical systems with matched disturbances

The core idea of traditional adaptive control is to reconstruct parameter estimation errors with known signals and damping injection based on tracking error, while the formulation of desired damping in controller designs is usually a nontrivial task. The main contribution of this paper lies in the development of the classic RISE result and a constructive damping injection procedure for the adaptive tracking control of Euler–Lagrange mechanical systems. By utilizing generalized dynamic scaling function, scalar filtering, the improved RISE method and analyzing the existence of finite escape time of the closed-loop system, a globally asymptotically stable result is obtained with facilitative damping injection, significant order reduction and improved design efficiency when compared with the existing results. Simulations on a fully actuated 2-DOF planar robot manipulator model demonstrate the effectiveness of the proposed methods.

A product design method for form and color matching based on aesthetic theory

Form and color matching design are vital links in product design. Recently, many scholars have focused on quantifying visual aesthetics to improve design efficiency in form or color matching design activities. However, few scholars have considered both form and color matching. Therefore, we propose a more comprehensive and practical design model based on the aesthetics theory of form and color matching. This model includes 3 phases: preparation (Phase I), form design (Phase II), and color matching design (Phase III). In Phase I, the target product's functional system and design objectives are clarified. In Phase II, the spatial layouts of the target product are analysed, and several reasonable layouts are designed in detail. Finally, the form with the highest aesthetic measurement is selected from alternatives using the modified equilibrium formula and questionnaire. In Phase III, a group of colors conforming to the target imagery is selected from a color palette. Meanwhile, a set of appropriate observation angles are chosen using an expert questionnaire. Subsequently, three-color combinations with higher color harmony are filled into images with different observation angles. Finally, the aesthetics of color matching schemes are obtained using the formula of color matching, and the scheme with a higher average value of the aesthetic measurement from all observation angles is considered the best scheme. This paper takes the fresh food vehicle and leafless fan as the cases. The best form and color matching scheme are obtained using the formula of aesthetic measurement and verified with an expert questionnaire. The result shows consistency between the results of the quantization formula and the expert questionnaire, which confirms the effectiveness of this design model. The proposed design model could improve the design efficiency and ensure the products' visual aesthetics.

Application Model Construction of Traditional Cultural Elements in Illustration Design under Artificial Intelligence Background

The sustainable development of modern illustration art needs to dig deep into traditional culture in content and, on the basis of spreading cultural forms and improving cultural influence, supplement its own creative forms. The influence of AI (artificial intelligence) on illustration design not only is manifested in the optimization of illustration design tools and the improvement of design efficiency, but also makes the illustration design methods more diverse and promotes new breakthroughs in the illustration design concept under the influence of new technologies. In this paper, combining the advantages of two activation functions, SoftSign and ReLU, a new activation function, SReLU, is constructed and applied to CNN (Convolutional Neural Network). The multimode property of color prediction is modeled by quantifying ab color channels in Lab color space, and the introduction of GAN (Generative Adversarial Network) structure can make the whole model show better generation effect and improve the generation ability of image style conversion network. Results. The experiment proves the effectiveness of the method with high-quality image visual effect.

BIM-based automated design of drainage systems for panelized residential buildings

The development of building information modelling has facilitated the improvement of cost and time management in panelized construction. This research proposes an automated method to design and draft drainage systems in the BIM environment. The proposed method can improve design efficiency, eliminate design errors, and reduce material waste. In order to improve production efficiency at the panelized construction plant, the drainage pipe network is separated into smaller components at the geometric boundaries of the plumbing panel which is a floor or wall panel through which pipes pass. Meanwhile, a bill of materials for each plumbing panel is generated for the purpose of further cutting optimization. A prototyped BIM extension application, an add-on to Autodesk Revit, is developed as a proof of concept. A case study of residential drainage system design and optimization is presented to illustrate the feasibility of the proposed framework. As the key contribution of this research, the integration of the BIM model with the automated design system, rule-based pipe route planning approach, and optimal cutting stock algorithm achieves the automation in drainage system design in the context of panelized construction to improve design and production efficiency.

Visual Multimedia Intelligent Computing System for Seismic Performance of Bridge Structure Based on Object-Oriented Technology.

In order to further promote the standardization of seismic performance design of bridge structures, one must ensure the quality of bridge design and improve design efficiency. First, based on the basic principle of the probabilistic pushover method, the randomness of the structural pushover curve is attributed to the randomness of plastic hinges. Second, the visualization of seismic performance of bridge structures based on the object-oriented technology is adopted. So that the randomness of seismic action can be considered in the analysis of seismic performance. Finally, the limit state equation of the seismic performance of the structure is used to evaluate the reliability of the seismic performance of the bridge in each limit state conveniently. The results show that the failure probability of the structure in each limit state is less than 0.5 under different basic accelerations from 0 to 0.4 g. The software method is simple in calculation and has a strong adaptability, avoiding the difficulty of seismic reliability analysis caused by large-scale simulation and large amount of calculation of traditional structures. Therefore, this method can be easily applied to the probabilistic analysis of seismic behavior of bridge structures under large earthquakes without evaporative deformation failure criterion.

Application of Graphic Design with Computer Graphics and Image Processing: Taking Packaging Design of Agricultural Products as an Example

With development of economy, all industries have undergone earthshaking changes. Various new technologies are starting to be employed in all aspects of life, and graphic design is no exception. The use of computer graphics and image processing technologies in graphic design can substantially improve design efficiency and make graphic design job more convenient to develop. The requirements for the quality of graphic design are higher. Quality inspection has become a necessary step in the production process, in which the detection of graphic design defects is an indispensable and important link. The traditional graphic design defect detection adopts the method of manual visual inspection, which has the disadvantages of poor stability, long consumption time, and high labor cost. As an efficient computer graphics and image processing technology, convolutional neural network has received extensive attention in graphic design defect detection because of its advantages of high speed, efficiency, and high degree of automation. Taking agricultural product packaging as an example, this paper studies application technology for graphic design defect detection with convolutional neural network (CNN). The main contents are as follows: construct the original YOLOv3 network model, input the graphic design images of agricultural product packaging into the network model in batches according to the computing power of the hardware equipment, train the YOLOv3 network, and deeply study and analyze the experimental results. The related improvement techniques are then given, based on the characteristics of agricultural product packaging design faults. The backbone network, multiscale feature map, a priori frame, and activation function of YOLOv3 are improved, and then performance of the improved model is verified by experiments.

Coupling Matrix-Based Co-Design of Filter-Oscillators

This letter presents a methodology of designing integrated filter-oscillators using the coupling matrix technique. The <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$N + 4$ </tex-math></inline-formula> coupling matrix is developed for the first time to describe the filter-oscillator topology. Accordingly, the corresponding group delay, loop gain, loop phase, and complex quality factor of the feedback filter can be calculated using the matrix. This helps rapidly predict oscillating frequencies at group delay or complex quality factor peak frequencies to achieve lower phase noise. Moreover, since the transistor and the transmission line (TL) entries are incorporated in the coupling matrix, the physical geometries can be directly determined, resulting in improved design efficiency. Two third-order filter-oscillators are implemented at 2.91 GHz (group delay peak) and 3.15 GHz (complex quality factor peak) frequencies, respectively. The developed filter-oscillators are measured with −121 and −145 dBc/Hz phase noise at 1-MHz offset frequency, validating this coupling matrix-based co-design approach.

High temperature creep strength design and optimization of solid oxide fuel cell

In order to improve product design efficiency and guarantee the high temperature structural integrity during the long-term creep of solid oxide fuel cell (SOFC), the creep strength design method is studied by using the finite element method (FEM) and the response surface method (RSM) with considering the interaction between the geometric parameters. A multi-regression model representing the correlation between the sealant failure probability and the geometric parameters is established for rapid estimation of creep strength and optimization design of geometric dimensions. The sealant failure probability is decreased from 0.994 to 0.015 by the optimization of SOFC geometrical size. And the error between results predicted by the FEM and results predicted by the multi-regression model is less than 10%. Therefore, the multi-regression model is proven to be an excellent tool for creep failure prediction and structural design optimization, reducing research costs and time, and improving design efficiency.

Design of highly perceptible dual-resonance all-dielectric metasurface colorimetric sensor via deep neural networks

Colorimetric sensing, which provides effective detection of bio-molecular signals with one’s naked eye, is an exceptionally promising sensing technique in that it enables convenient detection and simplification of entire sensing system. Though colorimetric sensors based on all-dielectric nanostructures have potential to exhibit distinct color variations enabling manageable detection due to their trivial intrinsic loss, there is crucial limitation that the sensitivity to environmental changes lags behind their plasmonic counterparts because of relatively small region of near field-analyte interaction of the dielectric Mie-type resonator. To overcome this challenge, we proposed all-dielectric metasurface colorimetric sensor which exhibits dual-resonance in the visible region. Thereafter, we confirmed with simulation that, in the elaborately designed dual-Lorentzian-type spectra, highly perceptible variations of structural color were manifested even in minute change of peripheral refractive index. In addition to verifying physical effectiveness of the superior colorimetric sensing performance appearing in the dual-resonance type sensor, by combining advanced optimization technique utilizing deep neural networks, we attempted to maximize sensing performance while obtaining dramatic improvement of design efficiency. Through well-trained deep neural network that accurately simulates the input target spectrum, we numerically verified that designed colorimetric sensor shows a remarkable sensing resolution distinguishable up to change of refractive index of 0.0086.

Ansys AR: Augmented Reality App Concept to Enhance 3D Design and Simulation Experience

This paper introduces the Ansys AR app, an innovative integration of Augmented Reality (AR) with Ansys Discovery, aimed at revolutionizing the 3D design and simulation process. Anticipating the CAD market’s growth, the study explores the transformative potential of AR in enhancing the capabilities of traditional CAD technologies. The user-centric Ansys AR app offers an immersive, interactive experience, allowing users to visualize and manipulate 3D models in real-world settings. The paper demonstrates the app’s effectiveness in improving design efficiency and communication through comprehensive user research, design conceptualization, and usability studies. It concludes with prospects for future enhancements, highlighting the app’s potential to reshape collaborative engineering and design practices.

Effect of different radial skewed angles of reversed blade-angle slot casing treatment on transonic axial flow compressor stability

Single-channel unsteady numerical simulation was carried out on NASA Rotor 35 to study the influence of radial skewed angle of reversed blade-angle slot casing treatment (RBSCT) on the aerodynamic performance and stall margin of a transonic compressor. Moreover, the influence mechanism is explained by detailed flow field analysis. The radial skewed angles were set to +0°, +30°, +60°, and +75° in the research. The calculated result shows that stall margin improvement (SMI) generated by the slots is increased when the radial skewed angle is gradually increased. The SMI of 17.47% for the slots with +75° radial skewed angle is the biggest among the four RBSCTs. As for the design efficiency improvement (DEI), it is increased first and then decreased with the radial skewed angle increasing. RBSCT with +60°radial skewed angle achieves the greatest DEI of 1.11%. The flow field analysis shows that the radial momentum of the injected and sucked flows is improved with the increasing of radial skewed angle. The improvement can reduce the relative airflow angle of mainstream near the stall condition. Furthermore, the excessive radial skewed angle will increase the flow losses in the slots. Consequently, the design efficiency is reduced at +75°.

Visualization of Railway Transportation Engineering Management Using BIM Technology under the Application of Internet of Things Edge Computing

In the past, railway line planning usually required engineers to design based on their own experience after a series of field visits, leading to heavy workload and low efficiency. Moreover, operation and maintenance management is more complicated due to an abundance of railway station equipment. Based on the above problems, this paper first puts forward the railway transportation line planning and design method based on Building Information Modeling (BIM) technology. Besides, LocaSpace Viewer realizes the three-dimensional (3D) visual scene modeling of the railway environment to improve the efficiency of railway line planning and design. Secondly, the railway station’s visual operation and maintenance management system is constructed via BIM Technology. Besides, the Internet of Things (IoT) is combined with edge computing and deep learning technology to build a 3D model of station equipment, collect data in real time, and analyze data efficiently. Finally, the design effect of the model, the performance of the visual management system, and the test results of network transmission delay are displayed and analyzed. The results show that BIM can construct the 3D visualization model with high fidelity for the railway environment. This model can get a reasonable line planning scheme and analyze its feasibility, provide a reliable basis for engineers to plan railway transportation lines, and improve design efficiency. In addition, the GPU occupation rate, CPU occupation rate, and memory occupation rate of the operation and maintenance management system in different operating environments are within the standard range; when multiple clients access the system, the system data access delay is 100% less than 8 ms, which has good performance. Furthermore, the performance of the IoT transmission data real-time scheduling model and the edge computing optimization algorithm applied to this system is better than other popular methods, which can significantly improve the operation efficiency of the system. This study aims to enhance the efficiency of railway transportation line planning and station operation and maintenance management with the help of digital technologies.

Multimedia Vocal Performance Automation Evaluation Model Based on RBF Network

Aiming at the problems of the radial basis network model, this paper proposes a multimedia vocal singing automation evaluation network model, combined with the characteristics of multimedia modeling innovation design, and proposes a two-level comprehensive model. First of all, the theory and algorithm of analytic hierarchy process and radial basis function network are researched and analyzed, and the RBF is predicted for the mature area of multimedia development based on the three indicators of the total amount of classified vocals. The prediction scheme evaluation system is then used to fit the prediction data and influencing factors using the RBF network, and then the classified vocals are adjusted and synthesized hierarchically, and a multimedia vocal classification prediction model is established. Finally, this paper uses an example to verify the feasibility performance and prediction accuracy. Based on the above theory, the experiment uses VC++ 6.0 and Matlab 6.5 combined with database technology to initially realize the evaluation system and achieves a good evaluation effect. The simulation results show that three different algorithms are used to establish RBFO content prediction models. The correlation coefficient limit, root mean square error prediction, and relative analysis error (RED) reached 0.9937, 15.5095, and 8.216, respectively. At the same time, the evaluation results have high accuracy and credibility, which not only provide designers with ideas and improvement basis for innovative designs but also ensure design quality, improve design efficiency, and show that RBF networks have good generalization capabilities.

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

With the rapid development of artificial intelligence, handicraft design has developed from artificial design to artificial intelligence design. Traditional handicraft design has the problems of long time consumption and low output, so it is necessary to improve the process technology. Artificial intelligence technology can provide optimized design steps in handicraft design and improve design efficiency and process level. Handicrafts are regarded as important social products and exist in people’s daily life. In the current society, many people do handicrafts and there are major exhibitions. Furthermore, the display of handicrafts is also very grand and shocking. In the design of handicrafts, the traditional design method cannot completely keep up with the production speed and efficiency of handicrafts. Therefore, this paper adopts the fusion multi-intelligent decision algorithm of multi-node branch design in the design method of handicraft. The algorithm model combination is used to analyze and design the layout of the handicraft, which speeds up the design efficiency and production of the handicraft. In this paper, two intelligent algorithms will be used for fusion; they are genetic algorithm and GA-PSO fusion algorithm obtained by particle swarm optimization and they are embedded in handicraft design method for application through mathematical model construction and function construction. After comparing the performance parameter index data of three intelligent algorithms and GA-PSO fusion algorithm, it is obtained that GA-PSO fusion algorithm is 97% correct and has 82% readability, 72% robustness, and 61% structure, making it have better important indicators. Four algorithms optimize each design problem in all aspects of handicraft design at present. Design efficiency, image distribution rate, image optimization degree, and image clarity are compared by simulation experiments. Compared with three intelligent algorithms, traditional design methods, and manual design methods, GA-PSO fusion algorithm can effectively improve the design method and design effect of handicrafts with 92.1% design efficiency, 82.7% image distribution rate, 94.3% image optimization degree, and 84% layout void rate. Finally, the space complexity experiment of four algorithms shows that GA-PSO algorithm can achieve 9.73 dispersion with 11.42 space complexities, which makes the dimension reduction relatively stable, and the algorithm can maintain stability in the design and application of handicrafts.

電気機器分野における設計効率化に向けた深層学習の活用

電気機器分野における設計効率化に向けた深層学習の活用

Research on Improvement of Design Efficiency of Prefabricated Building Mold under Standardized Process

Research on Improvement of Design Efficiency of Prefabricated Building Mold under Standardized Process