МЕТАЭВРИСТИЧЕСКИЙ МЕТОД ОПТИМИЗАЦИИ НА ОСНОВЕ МОДЕЛИ ПОВЕДЕНИЯ СТВОЛОВЫХ КЛЕТОК

In the calibration process of industrial robots, selecting the optimal measurement position configuration can improve calibration accuracy. However, existing research on the optimal measurement configurations selection mainly focuses on open-loop measurement methods using laser trackers. The exploration of the optimal measurement configuration selection for closed-loop measurement methods has not been developed to a large extent. This research introduces a measurement configurations selection observability index based on the position difference error equation, as well as an optimization method based on this index. Initially, we establish an error model for the kinematic parameters of industrial robots, which is based on the position difference of measurement configurations. Subsequently, by minimizing the relative error of the measurement, we proposed an observability index, denoted as <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\boldsymbol{O}_{\boldsymbol{e}}$</tex-math></inline-formula>. Using this index, construct a fitness function and use particle swarm optimization (PSO) algorithm to optimize the selection of robot measurement configuration set. The effectiveness of the proposed optimization method has been demonstrated through experiments conducted on CRP RA07 and JAKA Zu seven robots. The experimental results show that using the observability index <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\boldsymbol{O}_{\boldsymbol{e}}$</tex-math></inline-formula> to select the optimal configuration set can improve the calibration accuracy of the robot by 25.8% and 37.0%, respectively. The verification experiment using a laser tracker confirms that our optimal configuration set selection method can effectively improve calibration accuracy. This research fills the gap in the selection of optimal measurement configurations for constrained measurement. It is of great significance for field calibration research of robots.

In optimal design of a permanent magnet (PM) motor, many design variables are required to consider some device properties. These variables are, for example, the shape of core and magnet, the tooth length, the number of turns, and the winding radius. Moreover, many restrictions must be considered in practical PM motor design. These restrictions are, for example, the slot space factor and the cogging torque. However, the optimization problem, which has many design variables by the finite element method (FEM), has not been reported. In this paper, the efficiency of PM motor under the considerations given above is optimized by using FEM and optimization algorithm. In this problem, an objective function has many local minima and it is difficult to calculate its gradient. For these reasons, the genetic algorithm (GA) and simulated annealing method (SA), which are stochastic methods, are used for optimization method, because of the possibility of global range search and because gradient calculation is not required. Adding to both optimization methods, in this paper, SA combined with GA is used for one of the optimization methods. It is found that the solutions optimized by these methods are reasonable from an engineering point of view. © 2001 Scripta Technica, Electr Eng Jpn, 138(3): 72–79, 2002

This paper designs and optimizes a new structure hybrid material B‐pillar assembly. Establish a finite element analysis model for the side impact test of an electric vehicle to verify the model's accuracy. Construct a finite element model of the hybrid material B‐pillar assembly. Combined with the static performance analysis of the B‐pillar, the laminate design of the carbon fiber composite B‐pillar reinforcement plate and optimization. For the outer and inner panels of the B‐pillar, the surrogate model method and the multiobjective optimization method are combined to set 11 design variables and 13 responses. The optimal Latin hypercube design method was used to randomly sample each design variable and fit the radial basis function (RBF) approximate model. The modified second‐generation non‐dominated sorting genetic algorithm (MNSGA‐II) was used to carry out multiobjective optimization of the mixed material B‐pillar assembly, and the multicriteria decision‐making method was used to obtain the optimal solution for the Pareto solution set. A drop weight impact test was performed on the hybrid material B‐pillar assembly. The results showed that the peak collision force of the hybrid material B‐pillar was reduced by 43.7% compared with the original steel B‐pillar, the specific energy absorption was increased by 17.5%, and the side impact safety performance was better. After optimization, the weight of the mixed material B‐column was reduced by 26.44%. The improvement rates of the intrusion amount at P2 and the intrusion speed at P1 were 23.99% and 0.63%, respectively, and the lightweight effect and side impact safety were significantly improved.Highlights The finite element analysis parameters of carbon fiber composite materials were constructed through experiments, and the basis for simulation analysis under various working conditions of the B‐pillar based on performance‐driven optimization was established. A hybrid material B‐pillar design method is proposed, which consists of a variable‐thickness high‐strength steel B‐pillar outer plate, a variable‐thickness high‐strength steel B‐pillar inner plate, and a carbon fiber composite B‐pillar reinforcement plate. The super layer of the carbon fiber composite B‐pillar reinforcement plate was optimized and the laying plan of the carbon fiber composite B‐pillar reinforcement plate was determined. Performance‐driven optimization is adopted to realize the collaboration of multilevel design and optimization methods such as B‐pillar conceptual design, detailed design, and multiobjective optimization. A modified NSGA‐II algorithm was proposed and combined with the multicriteria decision‐making method and the entropy‐weighted gray relation analysis method to determine the Pareto optimal solution and the optimal design scheme for the mixed material B‐pillar.

Construction and optimization methods of spherical hexagonal–pentagonal geodesic grids are investigated. The objective is to compare grid structures on common ground. The distinction between two types of hexagonal–pentagonal grids is made. Three conventional grid optimization methods are summarized. In addition, three new optimization methods are proposed. Six desirable conditions for an ideal grid are described, and the grid optimization methods are organized in view of such conditions. Interval uniformity, area uniformity, isotropy, and bisection of cell faces are systematically investigated for optimized grids. There are compensations of preferable grid features in each optimization method, and an optimal method cannot be decided based only on the research of grid features. It is suggested that grid optimization methods should be selected based on research of numerical schemes.

The limited availability of the recorded rainfall-runoff data for many watersheds restricts the development and management of different activities of water resources. To overcome this limitation, the Natural Resources Conservation Service (NRCS) for estimating storm excess rainfall and momentum and optimization methods were combined in a mathematical model to estimate the optimal parameters of Nash Instantaneous unit hydrograph (IUH) and resulting direct runoff hydrograph (DRH), using a developed computer program in MATLAB. The available recorded data of 14 storms (out of 18) of four watersheds in northern Iraq have been applied in the calibration stage. An empirical relationship was developed between the average of each IUH optimal parameter (obtained by optimization as an optimal method according to the applied tests) and the effective watershed topographical characteristics. The developed empirical relations were used in the verification stage to estimate the IUH parameters and DRH for the verification storms and compare with that resulted from Haan’s empirical relations and optimization method. The statistical tests showed that the developed empirical relations efficiency was better than that of Haan’s method and close to that of the recorded storm by optimization method, where the average value of the Nash-Sutcliffe Efficiency for the four watersheds resulted from applying the optimization method, Haan’s method and the developed empirical relations were 0.925, 0.587, 0.883 respectively. The results indicated the developed model’s ability to estimate the IUH and direct runoff hydrograph for ungauged watersheds in northern Iraq.

The quality of stem cells obtained through serial subcultivation is the pivotal factor determining the therapeutic effectiveness of regenerative medicine. However, an effective quality monitoring system for cell culture is yet to be established. Detailed parameter studies of the migratory behavior of stem cells at different passages may provide insight into the deterioration of stemness. Thus, this study aimed to evaluate the feasibility of quantitative bioimage analysis for monitoring stem cell quality during in vitro culture and to explore the passaging effects on stem cell migration. An image-based analytical tool using cell tracking, cytometric analyses, and gating with time-lapse microscopy was developed to characterize the migratory behavior of human mesenchymal stem cells (hMSCs) isolated from human adipose tissue (hADAS) and placenta (hPDMC) cultured on chitosan membranes. Quantitative analysis was performed for the single cells and assembled spheroids selected from 15 videos of Passages 3, 5, and 11 for hADAS and those from 12 videos of Passages 7, 11, and 16 for hPDMC. These passages were selected to represent the young, matured, and degenerated stem cells, respectively. Migratory behavior varied with cell passages. The mobility of single hMSCs decreased at degenerated passages. In addition, enhancement of mobility, due to transformation from single cells to spheroids, occurred at each passage. The young hMSCs seemed more likely to move as single cells rather than as aggregates. Once matured, they tended to aggregate with strong 3D spheroid formability and increased mobility. However, the spheroid formability and mobility decreased at late passage. The increase in aggregation rate with passaging may be a compensatory mechanism to enhance the declining mobility of hMSCs through cell coordination. Our findings regarding the passaging effects on stem-cell migratory behavior agree with biochemical reports, suggesting that the developed imaging method is capable of monitoring the cell-culture quality effectively. © 2020 International Society for Advancement of Cytometry.

The sixth generation (6G) of mobile networks must support the huge growth of mobile connections and provides various intelligent services in future mobile networks. For that, designing high‐performance network architecture and communication systems (CSs) as well as finding coherent solutions for the determined problems is critical demand that needs to be achieved in 6G networks. Optimal solutions are mainly sought by using modifiable, smart, and perceptive algorithms aimed at optimizing more specific tasks. Therefore, advanced optimization methods are highly required to accommodate the requirements of CSs efficiently. That will be in various parts of the future networks such as advanced mobility management, multi communication links, efficient power consumption, ultra‐lower latency, ultra‐security, high speed, and reliable connectivity. Accordingly, highly accurate and smart functions must be modeled to optimize the required communication parameters in the network. This study provides a comprehensive overview of optimization methods that may need further investigations and developments to be applied in 6G networks at various parts of networks. A detailed theoretical description for each method is presented and discussed to elucidate future research directions for optimizing specific characteristics with multi‐objective optimizations. Moreover, this article illustrates the conceptual and structural viewpoints of reported optimization methods. Also, the capability of various optimization methods that can offer industrial solutions in 6G is discussed. The potential applications of each method are also analyzed. Finally, this article presented the research issues and future directions of optimization technology and research gaps that need to be addressed before the standardization of 6G networks.

Due to the innate extracellular matrix mimicking features, fibrous materials exhibited great application potential in biomedicine. In developing excellent fibrous biomaterial, it is essential to reveal the corresponding inherent fiber features’ effects on cell behaviors. Due to the inevitable ‘interference’ cell adhesions to the background or between adjacent fibers, it is difficult to precisely reveal the inherent fiber diameter effect on cell behaviors by using a traditional fiber mat. A single-layer and parallel-arranged polycaprolactone fiber pattern platform with an excellent non-fouling background is designed and constructed herein. In this unique material platform, the ‘interference’ cell adhesions through interspace between fibers to the environment could be effectively ruled out by the non-fouling background. The ‘interference’ cell adhesions between adjacent fibers could also be excluded from the sparsely arranged (SA) fiber patterns. The influence of fiber diameter on stem cell behaviors is precisely and comprehensively investigated based on eliminating the undesired ‘interference’ cell adhesions in a controllable way. On the SA fiber patterns, small diameter fiber (SA-D1, D1 means 1 μm in diameter) may seriously restrict cell proliferation and osteogenesis when compared to the middle (SA-D8) and large (SA-D56) ones and SA-D8 shows the optimal osteogenesis enhancement effect. At the same time, the cells present similar proliferation ability and even the highest osteogenic ability on the densely arranged (DA) fiber patterns with small diameter fiber (DA-D1) when compared to the middle (DA-D8) and large (DA-D56) ones. The ‘interference’ cell adhesion between adjacent fibers under dense fiber arrangement may be the main reason for inducing these different cell behavior trends along with fiber diameters. Related results and comparisons have illustrated the effects of fiber diameter on stem cell behaviors more precisely and objectively, thus providing valuable reference and guidance for developing effective fibrous biomaterials.

Adaptive optimization strategy of air supply for automotive polymer electrolyte membrane fuel cell in life cycle

Solar photovoltaic energy optimization methods, challenges and issues: A comprehensive review

Based on vehicle collision test, a finite element dummy model (FEM dummy) was built, at the same time the parameter optimization method was proposed in the paper. To improve consistency between the dummy simulation results and results of vehicle collision test, it's necessary to scientifically adjust FEM dummy's material parameters. First, parameter optimal selection applied, the most important parameters were selected. Then, using optimal methods obtained FEM dummy correction result which is similar to that of the real vehicle. Finally, chest pressure result curve of a FEM dummy model in positive collision as an example, main materials parameters of the FEM dummy's chest were selected by parameter optimal selection, then the parameters were modified by optimization method. ensuring simulation dummy' chest pressure peaks and spring rate are more consistent with vehicle collision result. It further found that the proposed method could be used to improve the FEM dummy model to meet the result of the vehicle collision simulation.

Evaluation on the method of reducing CFETR TF ripple generated by WCCB blanket

Modern power engineering is struggling with various problems that have not been observed before or have occurred very rarely. The main cause of these problems results from the increasing number of connected distributed electricity sources, mainly renewable energy sources (RESs). Therefore, energy generation is becoming more and more diverse, both in terms of technology and location. Grids that have so far worked as receiving networks change their original function and become generation networks. The directions of power flow have changed. In the case of distribution networks, this is manifested by power flows towards transformer stations and further to the network with a higher voltage level. As a result of a large number of RESs, their total share in the total generation increases. This has a significant impact on various aspects of the operation of the power system. Voltage profiles, branch loads, power flows and directions of power flows between areas change. As a result of the random nature of RES generation, there are problems with the quality of electricity, source stability issues, branch overloading, voltage exceedances and power balance. The occurrence of various types of problems requires the use of more and more advanced methods to solve them. This review paper, which is an introduction to the Special Issue Advanced Optimisation and Forecasting Methods in Power Engineering, describes and justifies the need to reach for effective and available mathematical and IT methods that are necessary to deal with the existing threats appearing in the operation of modern power systems. It indicates exemplary, current problems and advanced methods to solve them. This article is an introduction and justification for the use of advanced calculation methods and algorithms. Engineering intuition and experience are often not enough due to the size and complexity of power grid operation. Therefore, it becomes necessary to use methods based on artificial intelligence and other advanced solutions that will facilitate and support decision making in practice.

Turnpike Sets in Manufacturing Systems: Some Recent Progress

This project is partly supported by NSFC Grant 51207146, RAEng Research Exchange scheme of UK and EPSRC EP/K01496X/1.Superconducting cable is an emerging technology for electricity power transmission. Since the high power capacity HTS transmission cables are manufactured using a multi-layer conductor structure, the current distribution among the multilayer structure would be nonuniform without proper optimization and hence lead to large transmission losses. Therefore a novel optimization method has been developed to achieve evenly distributed current among different layers considering the HTS cable structure parameters: radius, pitch angle and winding direction which determine the self and mutual inductance. A prototype HTS cable has been built using BSCCO tape and tested to validate the design the optimal design method. A superconductor characterization system has been developed using the Labview and NI data acquisition system. It can be used to measure the AC loss and current distribution of short HTS cables.