Reduce Design Cost Research Articles

Broadband metamaterial linear polarization converter designed by a hybrid neural network with data augmentation

Deep learning techniques provide a new approach to the design and optimization of electromagnetic metamaterials. This study used a convolutional neural network and long short-term memory (CNN–LSTM) hybrid network to design and optimize a broadband metamaterial reflective linear polarization converter. The data augmentation method was also employed in few-shot learning to reduce optimization costs and improve model prediction performance. With the inverse prediction, a linear polarization converter that perfectly covers the Ku-band was obtained and fabricated with flexible printed circuit technology. Both simulation and experimental results indicate that this network can accurately predict the structural parameters. The polarization converter not only achieves remarkable broadband polarization conversion efficiency spanning the 2.2–18 GHz range but also maintains precise cross-polarization control across the entire Ku-band. The mean polarization conversion ratio in the Ku-band was calculated to be an impressive 99.69%. Finally, the mechanism of polarization conversion and the influence of each structural parameter on its performance further verify the optimality of the inverse design model. The use of CNN–LSTM deep learning methods significantly simplified the design process of electromagnetic metamaterials, reducing design costs while ensuring high design precision and excellent performance.

Utilization and potentials of digital twins – application examples

ABSTRACT In response to global geopolitical challenges and technological advancements, systems of the German Armed Forces are undergoing redesign or adaptation to enhance combat capabilities while prioritizing soldier and civilian protection. Digital twins, virtual representations of reality, offer a systematic and efficient means to explore various factors affecting military systems. Specifically in the naval domain, digital twins can significantly improve applications, reduce design cost, and facilitate user involvement in early phases of the design process. In this paper we use the infantry fighting vehicle PUMA as an example to highlight the importance of leveraging digital twins in virtual reality to address ergonomic and operational challenges, enhance situational awareness, and optimize interaction concepts for improved military effectiveness.

Commutation torque ripple suppression method for brushless DC motors with minimum phase shift angle

SummaryCommutation torque ripple occurs when brushless DC (BLDC) motor runs in the high‐speed range, which degrades operation performance. To overcome the problem, this paper presents a commutation torque ripple suppression method based on the minimum phase shift angle (MPSA) of hall signals. In the paper, the effect of the phase shift angle (PSA) of hall signals on phase current is analyzed, and the MPSA is deduced on the basis of the unit duty cycle of the incoming and non‐commutation phase. With the proposed method, two‐phase conduction mode is used in the full speed range, commutation period and non‐commutation period, which avoids switching modulation mode and enhances system reliability. The proposed method is implemented through shifting hall signals by the MPSA, and it is simple and feasible without the requirement to redesign a controller. Moreover, no additional power devices and precise sensors are required, which reduces design cost and volume size. The proposed method is experimentally compared with different methods under steady operation condition, and the results show superior performance on suppressing commutation torque ripple. The loading experiment demonstrates that the proposed method exhibits good dynamic response. The frequency spectrum of the electromagnetic torque is analyzed, and it is verified that the 6nf harmonics are diminished with the proposed method.

Research on design methodology for railway freight service combination plans to meet diverse demands

PurposeFacing the diverse needs of large-scale customers, based on available railway service resources and service capabilities, this paper aims to research the design method of railway freight service portfolio, select optimal service solutions and provide customers with comprehensive and customized freight services.Design/methodology/approachBased on the characteristics of railway freight services throughout the entire process, the service system is decomposed into independent units of service functions, and a railway freight service combination model is constructed with the goal of minimizing response time, service cost and service time. A model solving algorithm based on adaptive genetic algorithm is proposed.FindingsUsing the computational model, an empirical analysis was conducted on the entire process freight service plan for starch sold from Xi'an to Chengdu as an example. The results showed that the proposed optimization model and algorithm can effectively guide the design of freight plans and provide technical support for real-time response to customers' diversified entire process freight service needs.Originality/valueWith the continuous optimization and upgrading of railway freight source structure, customer demands are becoming increasingly diverse and personalized. Studying and designing a reasonable railway freight service plan throughout the entire process is of great significance for timely response to customer needs, improving service efficiency and reducing design costs.

Optimization Method for Hot Air Reflow Soldering Process Based on Robust Design

The process design of hot air reflow soldering is one of the key factors affecting the quality of PCBA (Printed Circuit Board Assembly) component products. In order to improve the product quality during the design process, this paper proposes a robust optimization-based finite element simulation analysis method including significant influencing factor screening, robustness evaluation, robust optimization, and reliability verification for the reflow soldering process. The simulation model of the reflow soldering process temperature field based on experiments is constructed and validated. Sensitivity analysis is used to select important influencing factors, such as the last five set temperature zones (T5 to T9) in the reflow oven and the thermal properties of materials such as PCBs (printed circuit boards), BGAs (ball grid arrays), and solder paste, as well as noise factors like the heating environment during the soldering process. Several surrogate models are used to construct the response surface, and the optimal fitting scheme is selected to effectively avoid poor fitting caused by inappropriate surrogate models. The 6σ robust optimization approach is introduced to evaluate and optimize the robustness of the process design parameter where the heating factor is chosen as the optimization target. The reliability analysis method is employed to validate the product quality. This paper establishes a comprehensive robustness analysis method for hot air reflow soldering, effectively reducing design costs and addressing the lack of robustness analysis in the current hot air reflow soldering process design.

High nonlinearity of BEV's stepped automatic transmission design objectives and its optimal solution by a novel ISA-RSA

The battery electric vehicle's (BEV's) stepped automatic transmission (SAT) has a significant influence on the power and economic performance of the new-energy vehicle system dynamics. The SAT entails a complex design process, where the transmission ratio parameter and the control strategy are interactively coupled, causing a difficulty in achieving a globally optimal solution. The actual design process involves multiple design objectives and incurs high design costs. The purpose of this study is to explore the variation characteristics of the design objectives of BEV's SAT and propose a transmission parameter optimization design method with reduced design costs. The paper investigates the interactive coupling property of the transmission ratio parameter and the control strategy, analyzing the high nonlinearity of SAT design objectives using the example of two-gear transmission. It proposes a design method that combines a heuristic optimization algorithm and an estimation model (Method Ⅲ), and a design method that utilizes an improved simulated annealing algorithm and a region search algorithm (ISA-RSA, Method Ⅳ). These methods are compared with a design method based on combination tests using the traversing method (Method Ⅰ) and a design method based on the heuristic optimization algorithm (Method Ⅱ). The results indicate that Method I incurs high design costs with limited effectiveness, while Method II exhibits unstable economic performance and integrated design objectives with fluctuations. Method III is highly dependent on the accuracy of the estimated model and performs poorly in optimizing acceleration time. However, Method Ⅳ, with low design costs, demonstrates remarkable optimization ability to solve high nonlinearity problems and exhibits a high probability of converging to the area near the globally optimal solution. This paper also aims to provide a direct solution to high design cost and highly nonlinear design objective problems in other engineering fields.

Can We Miniaturize CT Technology for a Successful Mobile Stroke Unit Roll-Out?

Mortality from stroke remains high in Australia, especially for patients located outside the metropolitan cities. This is because they have limited access to specialized stroke facilities for optimal stroke treatment. Mobile stroke units have the capability to take CT scanners out to the patient however current CT commercial scanner designs are large and heavy. As such, this paper aims to design and develop a lightweight CT scanner for use in a mobile stroke unit (either road-based or air-based ambulance) to bring healthcare solution to patients in the rural and remote areas. We used the engineering design optimization approach to redesign and reduce the weight of the existing CT scanner with without compromised it structural performance. We managed to reduce the weight the CT scanner by three-fold while reducing design costs by allowing numerous simulations to be performed using computer software to achieve our design goals. The results are not only useful to optimize CT scanner structure to retrofit on a mobile stroke unit, but also bring the medical device solution to the market and support scalable solution to the larger community. Such an advance will allow for improved equity in healthcare whereby patients can be treated irrespective of location.

Automated Optimum Design of Light Steel Frame Structures in Chinese Rural Areas Using Building Information Modeling and Simulated Annealing Algorithm

Many manual calculations and repeated modeling are required during the traditional structural design process. However, due to the high cost, rural buildings in China cannot be professionally designed and verified by designers as urban buildings, and their safety and economy cannot easily meet the requirements. Building Information Modeling (BIM) technology and intelligent optimization algorithms can effectively improve the structural design process and reduce design costs, but their applications in the field of rural residential buildings in China are limited. Therefore, this paper presents an innovative framework that realizes the structural design of rural light steel frame structures on the BIMBase platform (widely used BIM software in China, BIMBase 2023R1.3). Based on the parametric library of structural components built on standardized component coding, the framework completes the rapid modeling of rural light steel frame structures and the interaction between the BIMBase platform and structural analysis software, SATWE. The improved two-stage simulated annealing (SA) algorithm is applied to the structural design of rural buildings to obtain a design scheme that meets the design requirements and reduces the material consumption as much as possible. Two prefabricated rural light steel frame structures were analyzed to evaluate the efficiency of the proposed framework. The results show the feasibility of the proposed framework. Compared with traditional manual design methods, the design period can be reduced by six times while maintaining comparable levels of material consumption and structural design indicators.

Novel Active Snubbers for SSCBs to Improve Switch Voltage Utilization Rate

This paper proposes two novel active snubbers for direct current (dc) solid-state circuit breakers (SSCBs): metal-oxide-varistor with resistor-capacitor-switch (MOV-RCS) and active-MOV with resistor-capacitor-diode (AMOV-RCD). In the snubber branch, either half- or full-controlled switch can be applicable, leading to four novel topologies. There are two main contributions: 1) MOV is disconnected from the power line during SSCB OFF-state, which enhances reliability as neither voltage nor power appears on MOV; 2) voltage utilization rate η <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>v</i></sub> of the main switch is remarkably increased, which improves efficiency and power density, and reduces design cost. Experiments of five prototypes are conducted including four proposed snubbers and a comparison with conventional MOV-RCD snubber. Results show that, for 1.2 kV MOSFETs as the main switch, new snubbers can enhance η <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>v</i></sub> from 37.5% to 60%, achieving 183 A dc current interruption under 720 V dc bus voltage within 2.4 μs. Meanwhile, the voltage peak is limited to 1.112 kV.

Modeling and performance analysis of underwater gliders based on the virtual prototype technology

An underwater glider often comprises a buoyancy propulsion system, attitude regulation system, control system, hydrodynamic shape, etc. Numerous dynamic models based on rigid body dynamics have been established to study the motion performance of underwater gliders, which often neglect their attitude regulation and control systems. In this paper, a virtual prototype model of underwater gliders is developed based on the virtual prototype technology and verified by sea trials. Using the virtual model developed, the effects of three different control strategies and passive accumulators on underwater glider motion performance are discussed. The results demonstrate the feasibility of the virtual prototype model for motion performance analysis and control strategy optimization instead of the physical prototype. Thus, the proposed model could cut down the research and design time and reduce design costs.

Active disturbance rejection control of three-phase LCL power conversion system under non-ideal grid conditions

Under non-ideal grid operating conditions such as unbalanced grid voltage and harmonic grid that are commonly found in microgrid conditions, the negative sequence components of the microgrid voltage interfere with the active and reactive current controls in the power conversion system, leading to an increase in the harmonic content of the grid-side current and affecting the power quality of the microgrid system. To solve these problems, firstly, the mathematical model of the LCL-type power conversion system is analyzed, and a linear active disturbance rejection control based on model compensation is designed. Secondly, the influence of non-ideal power grid conditions on the control of the LCL-type power conversion system is analyzed, and the active disturbance rejection control strategy of the LCL-type power conversion system based on frequency-locked loops with harmonic cancellation modules (HCM-FLL) is proposed, which speeds up the system, improves the system’s robustness, and reduces the harmonic content of the network measurement current under the condition of power grid voltage unbalance and harmonic power grid. Finally, by using the verification of MATLAB/Simulink simulation, the current power quality obviously under the condition of voltage unbalance and harmonic power grid is evidently improved by the proposed control strategy. When compared to the traditional control methods, the control strategy proposed in this study features a simple control structure, making it easy to implement in engineering without requiring high controller performance or additional circuits. This reduces design costs and provides a wide range of controller parameters, ensuring strong anti-interference performance without the need for frequent controller parameter adjustments.

DFMA-oriented modular and parametric design and secondary splitting of vertical PC components

The design and production of assembled buildings are difficult to standardise, which limits their extensive application. In this paper, the design for manufacture and assembly (DFMA) concept is applied to the design of vertical precast concrete (PC) components for assembled buildings. Taking vertical PC components as an example, the rapid modelling and whole life-cycle application of DFMA-oriented PC components for assembled buildings are investigated. Firstly, the modular design method is introduced. By combining parametric design and building information modelling (BIM), we propose a modular, parametric design method and process of PC components based on DFMA. Secondly, the design of standard modules after secondary splitting is introduced for a better DFMA-oriented parametric design of PC components. We explored the secondary development process of DFMA and BIM and the module creation process of the parametric standard based on family templates and DFMA. Thirdly, based on the parametric standard module, the application of the optimised whole life cycle of design, manufacture and assembly of PC components is introduced. Finally, the feasibility of this method is verified by practical cases. The design process for PC components is fast, accurate and standardised. The integrated application of BIM is accelerated, and digital collaboration in assembly construction is strengthened. The study results are conducive to establishing a standardised design and production system for PC components, reducing design costs, improving design efficiency and the comprehensive benefits of assembled buildings.

Novel multiplexer circuit design in quantum-dot cellular automata technology

The QCA technology is a strong contender for replacing CMOS technology in the design of nanoscale digital circuits. The goal of this paper’s design is to increase the performance of the multiplexer (MUX) circuit. The design strategy is using a cost-effective architecture and path-planning design, which can reduce design costs. This paper presents an efficient circuit for 2-to-1 QCA MUX. Then, two circuits including 4-to-1 and 8-to-1 QCA MUX circuits are developed using this 2-to-1 QCA MUX circuit. The functionality of these circuits is investigated using QCADesigner tool version 2.0.3. The designed 2-to-1 QCA MUX circuit has 0.5 clock cycles delay, 0.01μm2 area and 15 cells. Moreover, the suggested 4-to-1 (8-to-1) QCA MUX circuit has 53 (163) cells, 0.06 (0.18) μm2 area and 1 (3.75) clock cycles delay. The energy dissipation (Area-delay cost) of the proposed 2-to-1, 4-to-1, and 8-to-1 MUX at 1oK is 8.91 mev (0.04), 17.9 mev (0.96), and 39.3 mev (8.82), respectively. The comparison results demonstrate that the designed circuits provide benefits compared to other MUX circuits.

The use of artificial intelligence and time characteristics in the optimization of the structure of the volumetric percentage detection system independent of the scale value inside the pipe

ABSTRACT When scale builds up in a transmission pipeline, it narrows the pipe’s interior and causes losses in both power and efficiency. A noninvasive instrument based on gamma-ray attenuation is one of the most reliable diagnostic procedures for determining volumetric percentages in a variety of circumstances. A system with a NaI detector and dual-energy gamma generator simulations (241Am and 133 Ba radioisotopes) is recommended for simulating a volume percentage detection system utilizing Monte Carlo N particle (MCNP). Three-phase flow consisting of oil, water, and gas moves through a scaled pipe of variable wall thicknesses in a stratified flow regime with changing volume percentages. After gamma rays are emitted from one end of the pipe, a detector take in the photons coming from the other end. Four temporal features, including kurtosis and mean value of the square root (MSR), skewness, and waveform length (WL) picked up by the detector, were thus obtained. By training two GMDH neural networks with the aforementioned inputs, it is possible to forecast volumetric percentages with an RMSE of less than 0.90 and independently of scale thickness. The low error value, simplicity of the system, and reduction of design costs ensures the effectiveness of the suggested method and the advantages of employing this approach in the petroleum and petrochemical industries.

A new product development study using intelligent data analysis algorithm based on KE theory

The Artificial Neural Networks (ANN) are more widely used in the New Product Development (NPD) process in recent years. The product data generation process is a prerequisite for the application of the ANN algorithm. In the development of new products, the Kansei Engineering (KE) method is an effective emotion-based data generation method. The Semantic Difference (SD) method is usually used to obtain data to apply to design idea generation. Facing the data demand of product creativity, it is important to establish the relationship between consumer perception and product expression. Numerical relationships are not linear and several methods are required for solving these problems. The method of the Back Propagation (BP) neural network is simple and effective to be used in this case. This paper proposes an innovative data modeling method using digital coding and KE. This model explores a rational design method of perceptual intention and builds an intelligent model. Compared with traditional method, the modified model can quickly and accurately reflect the users’ perceptual needs, make the design more scientific, improve the design efficiency, and reduce design costs. This method is used in the design of electric welding machines, and this process can effectively provide technical support for NPD process in small and medium-sized enterprises.

A Simple Mthod for Building Orientation Definition of Standardized Preschool Design in Brazilian Climatic Zones

Introduction: Brazilian Government's Proinfância Program developed Standardized Preschool Designs (SPDs) to ensure children's access to preschool while reducing design costs and shortening bidding and construction processes. Local administrations are expected to define the SPD’s building orientation in an available site, Proinfância provides no information regarding the SPDs' building orientation definition. Methods: This study proposes a simple method to help local administrations to define an adequate building orientation of SPDs in the eight Brazilian climatic zones aiming for thermal performance and thermal comfort. This method combines the ABNT NBR 15.575:2013 simulation method for thermal performance assessment and the ASHRAE Standard 55-2017 Adaptive Model for thermal comfort assessment. The SPD Type 2 was chosen for the method validation, and a decision-support framework was developed to solve divergences among conflicting results. Results: Thermal performance and thermal comfort assessments demonstrated that Type 2 is more suitable for warmer CZs. In some CZs, the thermal comfort results showed significant variations with the building orientation shift. The proposed method proved to be adequate to indicate building orientation to Proinfância Program’ Type 2. Conclusion: In addition, this study allowed the elaboration of a building orientation’s recommendations’ list for each Brazilian climatic zone. Municipal administrations might use the results to guarantee thermally qualified indoor spaces based in cientific evidences. The data collected contribute to the advancement of knowledge in the field of thermal comfort regarding naturally conditioned preschool buildings.

Design and Implementation of OPC UA-Based VR/AR Collaboration Model Using CPS Server for VR Engineering Process

In order to cope with the changing era of the innovative management paradigm of the manufacturing industry, it is necessary to advance the construction of smart factories in the domestic manufacturing industry, and in particular, the 3D design and manufacturing content sector is highly growthable. In particular, the core technologies that enable digital transformation VR (Virtual Reality)/AR (Augmented Reality) technologies have developed rapidly in recent years, but have not yet achieved any particular results in industrial engineering. In the manufacturing industry, digital threads and collaboration systems are needed to reduce design costs that change over and over again due to the inability to respond to various problems and demands that should be considered when designing products. To this end, we propose a VR/AR collaboration model that increases efficiency of manufacturing environments such as inspection and maintenance as well as design simultaneously with participants through 3D rendering virtualization of facilities or robot 3D designs in VR/AR. We implemented converting programs and middleware CPS (Cyber Physical System) servers that convert to BOM (Bill of Material)-based 3D graphics models and CPS models to test the accuracy of data and optimization of 3D modeling and study their performance through robotic arms in real factories.

A Second Harmonic Current Suppressing Method Based on Negative-Order Capacitor

In microgrid system, current in dc bus may contain a lot of undesired low-order harmonics when converters are employed, especially the second harmonic current (SHC). To address the issue, this article proposes a method based on fractional-order capacitor (FOC) to suppress the SHC. The FOC, of which the order <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">α</i> is “−1,” has the same characteristics of dc blocking and ac conducting as conventional capacitor; while it can resonate with a conventional capacitor like an inductor, which could be called a negative-order capacitor (NOC) as well. The proposed circuit has good SHC suppression performance, faster dynamic response, and soft switching realization. It parallels on the dc side of an inverter instead of the large bus capacitor, increasing power density and reducing design cost and loss.The secondary power will only circuit between the ac side of inverter and the NOC circuit. In addition, the NOC circuit can adjust zero impedance to specific harmonics; so it can be expanded to suppress harmonic current at other frequencies in the system. The simulation and experimental results are presented to validate the feasibility of the proposed method.

Adaptive decoupling planning method for the product crowdsourcing design tasks based on knowledge reuse

Crowdsourcing platforms are an effective way for enterprises to improve innovation abilities, reduce design costs and shorten design cycles during the boom of mass personalized customization. However, the absence of intelligent decoupling planning methods is a decisive reason for the poor intelligent decomposition of design tasks on crowdsourcing platforms. Additionally, their accumulated vast design experience and data, which should have been sufficiently reutilized to bridge that gap, have been neglected. Therefore, an adaptive intelligent decoupling planning method for relatively complex product crowdsourcing design tasks is proposed in this study, simultaneously considering knowledge reuse and bilateral feature matching. First, the requirement-knowledge-resource (RKR) characterization model is established according to the extraction of historical design experience to lay a foundation for the knowledge reuse. Second, based on the knowledge reuse, a hierarchical decoupling solution framework merged with the improved HITS-NetClus hybrid algorithm is built to perform retrieval reuse of knowledge and decoupling planning of tasks. Third, the resource competitiveness feedback strategy is taken to refine the decoupling planning scheme to meet resource competitive conditions. Finally, we demonstrate the intelligence of incorporating the hierarchical decoupling solution framework to achieve automatic decomposition using a real crowdsourcing design task for the personalized sewing machine. Our method also improves the resource adaptation capability of task decomposition schemes in practice.

The use of intelligent search algorithms in the cost optimization of road pavement thickness design

Since road pavements consume a significant portion of the financial resources of construction costs, design engineers aim to find an appropriate pavement thickness design with minimum possible cost. The optimal design can be located using intelligent search algorithms. This study compares the performance of genetic algorithm and particle swarm optimization to determine the efficacy of intelligent algorithms in determining the economically optimal pavement thickness design. The software required to implement the two algorithms for solving the pavement design and the simulation–optimization model were developed. Then, nine completed projects in Khuzestan, in Southwestern Iran, were evaluated using the manual design approach of consulting engineers, and the projects’ capabilities were compared by applying the programs developed for the two algorithms to the projects. The results indicated using GA and PSO reduced design costs by 9–26.5% and 5–25%, respectively compared to the manual design, and GA outperforms PSO by 1–5.5% regarding cost savings.