Optimal Design Methods Research Articles

Uniform Accuracy Lifetime Principle and Optimal Design Methods for Measurement Systems

The accuracy of measurement instruments, as well as that of their components, gradually declines as time goes on. Due to different loss mechanisms and the allowable accuracy loss values, the accuracy lifetimes of a whole system and its components are generally nonuniform, which lead to the waste of resources and costs. In this paper, a novel design method based on the uniform accuracy lifetime principle is presented to avoid the waste of resources. After giving and determining the uniformity and accuracy loss weights, optimal design models are established, and the sequential quadratic programming (SQP) method is employed to solve the models. A design example is presented to verify the effectiveness of the design model and the solution method. Using this method, the minimum accuracy lifetime of the whole system extends from 73.07 weeks to 200 weeks, and the uniformity improves from 0.75 to 0.96. The proposed method can be used in practice to achieve the target of uniform accuracy lifetimes for measurement systems because it is easy for manufacturers to obtain the average loss velocities of different components. The implementation of the optimization method will greatly help to save resources and improve the utilization efficiency of instruments or equipment.

A Synchronous Auxiliary Resonant Commutated Pole Soft-Switching Inverter With Improved Load Adaptability

To realize a soft-switching inverter with small volume and high efficiency, a synchronous auxiliary resonant commutated pole (SARCP) soft-switching inverter with improved load adaptability is proposed, which only contains two auxiliary inductors. In one switching cycle, all commutation processes can be synchronously assisted by an auxiliary inductor. Soft switching is achievable for all switches of the SARCP inverter. Compared with the auxiliary resonant commutated pole (ARCP) inverter, the SARCP inverter has improved load adaptability, especially in the light load current condition, which is beneficial to reduce the total power loss and the dc-link capacitance. The equivalent circuits of the SARCP inverter are given under different operation modes. The operation principle, soft-switching implementation conditions, parameter optimization design methods, and the characteristics of the SARCP inverter are analyzed. Finally, simulation and experimental results verify the effectiveness of the SARCP inverter.

Quality characteristic extraction for complex products with multi-granular fuzzy language based on the triple bottom lines of sustainability

Advanced product optimization design methods can greatly improve the market competitiveness of enterprises in manufacturing industry and promote the sustainable development of economy, society and environment. Quality characteristic is the carrier of product quality and closely related to sustainable product design. To manage reasonably the environmental, economic and social goals in actual product design, this paper proposes a quality characteristic extraction method for complex products with multi-granular fuzzy language based on the triple bottom lines of sustainability. Satisfaction evaluation of a customer group expressed in multi-granular fuzzy language is given full consideration with the adoption of dominant granular structures. Interval rough number (IRN) is employed for product quality function development (QFD) to fully retain the calculation simplicity of rough sets and expression flexibility of interval numbers in the correlation transformation between customer requirements and quality characteristics. A multi-objective optimization model for the quality characteristic extraction of complex products is established according to the triple bottom lines of sustainability, and an improved fruit fly optimization algorithm with the segmented variable step size is designed to solve it efficiently. Lastly, the rationality and effectiveness of the proposed method are demonstrated by the case study of a computer numerical control (CNC) machine tool.

Co-optimization of a novel distributed energy system integrated with hybrid energy storage in different nearly zero energy community scenarios

Many countries have proposed plans on distributed energy systems. However, distributed energy systems still can be improved in system optimization design methods, new-type load, and application scenarios. Therefore, a novel distributed energy system is developed combining solar energy utilization with hybrid energy storage technology, i.e., heat storage and electricity storage. Secondly, with primary energy saving rate, carbon dioxide equivalent emission reduction rate, and annual cost per unit supply area as objectives, an integration optimization method considering equipment configuration and operation strategy is adopted. Then, considering different community types and scales, 12 nearly zero energy community scenarios with electric vehicles as a new-type load are designed. Comparative analysis is conducted on the proposed system, comparing with separated production system and in different scenarios. The results show the scenario with 50% public buildings possesses considerable energy saving (53.1%), environmentally protection (56.4%), and economy (50.1 CNY/m2). The proportion of public buildings mainly influences primary energy saving rate (21.0%), followed by annual cost per unit supply area 17.7 (CNY/m2), finally carbon emission reduction (9.1%). The residential community with 196800 m2 building scale perform brilliantly. These findings worth popularization and application in the developing nearly zero energy communities.

Research on aerodynamic optimization design method and flow mechanism of a high-subsonic compressor cascade

Designing the high-performance, high-subsonic airfoils suitable for different Reynolds number flow is the major challenge for high-altitude long-endurance drones and ultra-high altitude solar aircraft. To overcome the difficulties, this paper proposed a set of aerodynamic optimization design methods that combine the improved category shape function transformation method, parallel computational fluid dynamics, and an improved whale optimization algorithm. This approach achieves high modeling accuracy, computational efficiency, and strong optimization ability. Verification using single-peak, multi-peak, and fixed-dimensional test functions demonstrates that the improved whale optimization algorithm has significantly enhanced optimization capabilities compared with the conventional whale optimization, particle swarm optimization, and gravity search algorithms. Numerical simulations are used to analyze the internal flow mechanisms before and after airfoil optimization under different Reynolds numbers. The results show that, compared with the original airfoil, the optimized airfoil has front loading characteristics that effectively reduce the adverse pressure gradient of the rear part of suction surface, promoting the transition in this region. The reduced adverse pressure gradient also inhibits the development and growth of laminar separation bubbles and slows down the growth of the boundary layer displacement thickness, thereby reducing wake mixing loss and improving the aerodynamic performance.

Trust-Region RB Methods for PDE-Constrained Optimization and Optimal Input Design

In this paper we propose an algorithm for the bi-level optimal input design involving a parameter-dependent evolution problem. In the inner cycle a control is fixed and the parameter is optimized in order to minimize a cost function that measure the discrepancy from some data. In the outer cycle the found parameter is fixed and the control is now optimized in order to minimize a suitable measure of uncertainty of the parameters. The inner cycle uses a trust-region reduced basis approximation of the model with creation and enrichment of the reduced basis on-the-fly. Numerical examples illustrate the efficiency of the proposed approach.

Improving the load capacity of cylindrical gears and transmissions by parametric optimal design with CAD/CAM systems

Gears are an essential component of modern drives and systems. Cylindrical gears with involute profile have established themselves as one of the most widely used. Recent years have seen intensive research of both their profiling, as well as methodologies for improving their load carrying capacity. One way to increase productivity in the manufacture of cylindrical gears is the use of automated design systems. This paper presents an approach for optimal gear selection by applying the methods of parametric optimal design, modeling and study of gears with involute profile and study of their load carrying capacity.

Level set-based multi-material topology optimization considering material and joint cost

In vehicle body structural design, weight reduction is one of the most important issues for improving both dynamic performance and fuel efficiency. Therefore, structural design using multi-materials has been attracting attention in order to achieve weight reduction while maintaining the stiffness of the vehicle body. By employing multi-materials with different physical properties, superior designs can be obtained in various aspects such as stiffness, mass, and cost. However, these are trade-offs with each other. Therefore, it is important to develop a multi-material design method that can improve these aspects. On the other hand, multi-material design has some challenges that single-material design does not have. One of them is how to evaluate the joints of multi-material structures. The boundary between dissimilar materials must be joined by means of adhesion or welding. However, few optimal design methods exist that refer to joints. In this study, we propose a design method for optimal structures based on multi-material topology optimization. This takes into account not only the cost dependent on the quantity of materials, but also the cost of joining different materials. To evaluate this joining cost, level set method is used, since it requires a clear representation of the material boundary area. We applied the MM-LS (Multi-Material Level Set) method, which can represent the shapes of multi-materials. Numerical examples for the cost minimization problem and the cost-mass multi-objective optimization problem are presented.

Mechanical Models of Drillstrings with Drag Reduction Oscillators and Optimal Design Methods of Vibration Parameters in Horizontal Drilling

Mechanical Models of Drillstrings with Drag Reduction Oscillators and Optimal Design Methods of Vibration Parameters in Horizontal Drilling

Overview of the Optimal Design of the Electrically Excited Doubly Salient Variable Reluctance Machine

The Electrically Excited Doubly Salient Variable Reluctance Machine (EEDSVRM) is a new type of brushless machine designed according to the principle of air gap reluctance change. There is neither permanent magnet steel nor excitation winding on the rotor. The rotor is made of silicon steel sheets, thus the structure of the variable reluctance machine is very simple. There are many optimization methods for this type of machine optimal design, such as novel machine topology optimization, finite element simulation-based optimization, mathematical analysis-based optimization, intelligent algorithm-based optimization, and multiple fusion-based optimization. Firstly, this article introduces the basic structure and working principle of the EEDSVRM and analyzes both its common regularity and individual difference. Then, the different optimization design methods of EEDSVRM are reviewed, the advantages and disadvantages of the different optimization methods are summarized, and the research interests of the optimization design of variable reluctance machines in the future are prospected.

Optimal spatial monitoring of populations described by reaction–diffusion models

Using spatialised population measurements and related geographic habitat data, it is feasible nowadays to derive parsimonious spatially explicit population models and to carry on their parameter estimation. To achieve such goal, reaction–diffusion models are common in conservation biology and agricultural plant health where they are used, for example, for landscape planning or epidemiological surveillance. Unfortunately, if the mathematical methods and computational power are readily available, biological measurements are not. Despite the high throughput of some habitat related remote sensors, the experimental cost of biological measurements are one of the worst bottleneck against a widespread usage of reaction–diffusion models. Hence we will recall some classical methods for optimal experimental design that we deem useful to spatial ecologist. Using two case studies, one in landscape ecology and one in conservation biology, we will show how to construct a priori experimental design minimizing variance of parameter estimates, enabling optimal experimental setup under constraints.

Improvement on optimal design of dynamic absorber for enhancing seismic performance of nuclear piping using adaptive Kriging method

For improving the seismic performance of the nuclear power plant (NPP) piping system, attempts have been made to apply a dynamic absorber (DA). However, the current piping DA design method is limited because it cannot provide the globally optimum values for the target design seismic loading. Therefore, this study proposes a seismic time history analysis-based DA optimal design method for piping. To this end, the Kriging approach is introduced to reduce the numerical cost required for seismic time history analyses. The appropriate design of the experiment method is used to increase the efficiency in securing response data. A gradient-based method is used to efficiently deal with the multi-dimensional unconstrained optimization problem of the DA optimal design. As a result, the proposed method showed an excellent response reduction effect in several responses compared to other optimal design methods. The proposed method showed that the average response reduction rate was about 9% less at the maximum acceleration, about 5% less at the maximum value of the response spectrum, about 9% less at the maximum relative displacement, and about 4% less at the maximum combined stress compared to existing optimal design methods. Therefore, the proposed method enables an effective optimal DA design method for mitigating seismic response in NPP piping in the future.

Multiobjective optimization design of hybrid composite laminates for vibration using sequential permutation table method

Due to the large variable design space in optimization problems of composite laminates, it remains one of the challenging tasks to develop efficient optimization design methods to improve the design flexibility and efficiency. This work presents a sequential permutation table (SPT) method for the multiobjective optimization design of two-material hybrid composite laminates with simply supported boundary conditions, which maximizes the fundamental frequency and minimizes the cost/weight. Based on the vibration analysis of hybrid composite laminates, the approximate linear regularity of the square of fundamental frequency is derived, and two best ply orientations for the two materials are identified, respectively. By assigning one best ply orientation with maximum fundamental frequency at respective stacking positions, and using another best ply orientation to replace plies in the stacking sequence from the mid-plane to the outermost can lead to the optimum. Two multiobjective optimization problems are employed to verify the SPT method, results are compared with those obtained by heuristic algorithms. The obtained better solutions demonstrate the effectiveness and efficiency of the SPT method and its potentials for optimal design of hybrid composite laminates.

Mine surveying technique and steel storage tank base deformation removal

Introduction. Vertical steel tanks are extensively used in oil fields to hold crude oil and other liquids. Their construction requires continuous surveying control. However, measurement procedures, data processing, and deviations and documentation correction are not universal and cannot be applied for tanks with a capacity of less than 3000 m3. Moreover, the process of correcting the detected bottom irregularities is poorly substantiated and intuitive. Research objective is to improve the as-built survey accuracy and reliability of the low-capacity steel tank bottom, substantiate the minimum height of its irregularities, increase the objectivity and productivity of measurement processing, develop an unambiguous method for time-predictable correction of bottom irregularities, and substantiate the optimal contents of its relief’s as-built scheme. Methods of research. Geometric leveling for the bottom profile survey failed to provide adequate accuracy and was therefore replaced by the method of trigonometric leveling. A method has been developed for determining the deviations of the existent tank bottom profile from the design position by means of algebraic actions with surfaces of a topographic order. The accuracy of determining the smallest height of bottom irregularities has been estimated under the tacheometric survey. A method has been proposed for controlling the correction of tank bottom irregularities based on evaluation calculations of bottom deformations by the finite element method. Research results. All the development results are exemplified by a specific production example. It was found that for a full completion of work, two iterations of tank bottom irregularities correction are enough. Methods of optimal design for the facility’s as-built schemes are presented. Conclusions. A simple, accurate, low-cost, productive, and time-predictable method of mine surveying, mathematical processing and correction of deviations in the tank bottom profile has been developed. This technique reduces the construction period and increases the operating time of the facility.

Research of Methods of Optimal Design of Special Electric Drives

Problems of optimization of special electrical and electromechanical systems in modeling, creation and design are solved mainly by methods of mathematical programming. The task of mathematical programming is to find extremes of the function of many variables in the presence of restrictions on variables, which creates fundamental difficulties. To solve such problems, the number of methods for solving the general problem of mathematical programming is currently expanding significantly. In this regard, the trend in the development of mathematical programming is following the path of highlighting and studying various subclasses of problems. The use of certain specific features of the tasks of the selected subclass creates opportunities for their more effective investigation and solution. Examples of such subclasses give convex, quadratic, linear programming problems, transport-type problems, and others. Geometric programming is also a section of mathematical programming that research a certain class of optimization problems. However, when using geometric programming, you have to apply linear, nonlinear programming, the concept of convex programming. Using optimization methods will allow you to correctly investigate, design and create special electric drives.

Layout Design and Die Casting Using CAE Simulation for Household Appliances

Due to the development and industrialization of science and technology, aluminum alloys have been developed in various fields. Recently, the government has been pursuing ways to decrease the weight and increase the recyclability of various components in order to conserve resources, energy, and the environmental. In keeping with this trend, cast iron products are being replaced by aluminum products in the foundry industry by using high-pressure die casting (HPDC). Casting layout design, relies on the experience and knowledge of mold designers in the casting industry, which proves insufficient to respond to the rapidly changing needs of the era and to increasing production costs. Designing and producing casting layouts using CAD/CAM/CAE technology has become a critical issue. Computer-Aided Engineering (CAE) technology is rapidly increasing with the development of computer software and hardware. CAE technology not only predicts defects in mass production but also performs filling or solidification analysis during the mold design stage before production, enabling optimal mold design methods. New technologies that combine the emerging casting processes of filling and solidification analysis using computer simulation with existing technology and practical experience in the field are rapidly increasing in the foundry industry. Based on empirical knowledge, the layout and design of casting products has traditionally progressed through trial and error. The solutions achieved through scientific calculation and analysis using CAE technology can save a great deal of money and time in the building of die-casting molds and in their design and fabrication. In this study, numerical analysis of household appliances (cooking grills) quickly and accurately predicts problems arising from the filling and solidification of the melted metal in the casting process, thereby ensuring the quality of the final cast product. These results can be used to quickly establish a sound casting layout with reduced production costs.

Recent Advances in Mechanoluminescence of Doped Zinc Sulfides

AbstractMechanoluminescence (ML) is the light generation of a material under mechanical stimuli. For more than 400 years, many compounds including inorganic and organic materials present this phenomenon. The general mechanism for the ML emission is the stress‐induced electrification effect combined with the piezoelectric field that lead to trapping and detrapping of the charge carriers. However, an in‐depth investigation and research are required to understand and hypothesize the ML mechanisms and optimum design and synthesis methods for better ML properties. Among the most common materials possessing this phenomenon is the zinc sulfide (ZnS) compounds that show high luminescence intensity and reproducibility. Such properties make them best candidates to be used in potential applications such as light and display devices, stress sensors, and human health monitoring devices. Therefore, this minireview focuses on the recent development and progress in doped ZnS ML compounds, including mechanism, design and synthesis, and the practical applications of such materials.

Optimal design of step-stress accelerated degradation test oriented by nonlinear and distributed degradation process

The Step-stress accelerated degradation test (SSADT) is an efficient tool to assess the reliability of products. To ensure an accurate evaluation of reliability-related indexes with limited cost, the optimal design for SSADTs is widely applied. Conventional optimal design methods ideally assume the degradation process to be linear and distribution-free, which may cause the designed test plans to be drastically different from the optimal one. To overcome the drawbacks of the unreasonable assumption, this paper develops a new optimal design method for SSADTs, including a generalized Wiener process-based degradation model (GWPDM) considering the distribution feature and a corresponding optimization criterion aiming at accurate prediction of degradation distributions. The GWPDM is first discussed, where the influence of the nonlinearity, unit-to-unit variability, measurement error and stress-related temporal variability on the degradation process is clarified. The statistical inference of the developed GWPDM is conducted to deduce the proposed optimization criterion. Thus, the optimization model is established to determine the optimal SSADT plan. The proposed method is used to design a SSADT plan for the metal-film resistor. Finally, the necessity and the robustness of the proposed method are verified.

Feasibility Study of Geometrical Parameters of Wood Transportation Roads Including Prediction of Optimum Terms of Construction and Retrofitting Sequence

The methods of optimum design of road longitudinal profile for various purposes, allowing eliminating subjective decisions, are developed and implemented by various research establishments. These methods are based on a deep theoretical background; they are automated but characterized by certain serious drawbacks. Firstly, the use of the minimum amount of excavation works as a criterion of optimality cannot provide an optimum solution regarding a definite period, because traffic intensity and its annual increase are not taken into account. Secondly, the proposed methods do not stipulate the necessity of stepwise development of road geometrical elements and their comprehensive substantiation. Finally, the optimization programs of design lines of the longitudinal profile are complicated and cannot be always applied in small design bureaus. This work, being based on the presented features of analyzed publications and the necessity of their further development, is aimed at the development of methods and recommendations for a feasibility study of main parameters of transversal and longitudinal profiles of wood transportation roads including prediction of optimum terms of construction and retrofitting sequence. Achievement of the formulated purpose is mainly determined by mutual links and the structure of elements considered in this work. For clear determination of subordination of these elements, their influence on techno-economic calculations, and systematization of the overall process, it is necessary to develop a logical model of the problem. Another step to achieve the goal is a mathematical description of links of the logical scheme, that is, the development of the mathematical model of the solution. Since the solution assumes searching for optimum parameters, the mathematical model should be based on the target function with its extremum corresponding to the required optimum combination of the optimized elements. Several variants and the search area are defined by the required limitations.

Optimal design and integration of multiple-function solar water heating systems based on a co-adaptive matchmaking method

Many existing optimal solar-based hot water system design methods do not quantitatively consider the impact of energy mismatching, which leads to the overestimation of system performance and misleads the optimal design of the system. For addressing such mismatching problems, a solar-based hot water system optimization design method based on real-time energy balancing and co-adaptive matchmaking is proposed. It consists of three main parts: (1) establish a simplified solar hot water system model based on the real-time energy balance to simulate the dynamic energy performance of the system; (2) propose a co-adaptive matchmaking optimization method to minimize the energy mismatch between the supply and demand sides of the system; and (3) identify the scheme with the minimum life-cycle total cost as the optimum design. A multiple-function solar water heating system for the domestic hot water supply, space heating and air conditioning of a kindergarten building in Beijing was optimized based on the proposed optimization method. It was found that the energy mismatch degree between the supply and demand sides can be greatly reduced and leading to a maximum life-cycle saving cost up to 20.13% in the concerned case.