An Optimization Method for Optimal Engineering Structure Design Combining Intelligent Optimization Algorithm and CAE Code

Short-term load forecasting is generally applied in power system real-time dispatching and day-ahead generation planning, which is of great significance for power system economic dispatching and safe operation of the system. Much research on short-term load forecasting using neural networks has been carried out at home and abroad. However, how to obtain the optimal network and structure evolution accurately and quickly has evolved into a key challenge for short-term load forecasting, because the prediction effect of the neural network method is more easily affected by the existing network structure and parameters, and the personality difference of the prediction object itself makes it difficult for the parameters to be reused. Aiming at this problem, this paper proposes a TPE-based neural network structure design and parameter optimization method for short-term load forecasting. This method realizes fast optimization of parameters of different types, structures, parameters, and input and output of deep neural networks, and is widely applied in Guangxi power grid. It is verified by an actual example that the method can effectively improve prediction accuracy.

COMBINED IDENTIFICATION AND CONTROL: ANOTHER WAY

In order to save project investment and reduce project quantity, the optimal design of aqueduct is the main problem in the project therefore, carrying out the optimal design and simulation analysis of U-shaped thin-walled aqueduct has important engineering application value. The paper takes Sha River aqueduct as the research object and adopts the direct search and point checking method of mixed discrete variable optimisation design. It also adopts the structural optimisation design method based on genetic algorithm and gives the optimal design scheme of U-shaped aqueduct. The optimisation design method has the advantages of fast convergence speed, high convergence efficiency and strong global search ability. The results show that, U-shape aqueduct structure is smooth, it has good mechanical properties, and the structural stress is small and can meet the strength requirement. The maximum vertical displacement of the aqueduct occurs in the middle of the span, the vertical displacement value is small, which can meet the requirement of stiffness.

With the rapid development of technology, motors have drawn increasing attention in aviation applications, especially in the more electrical aircraft and all electrical aircraft concepts. Power weight ratio and reliability are key parameters for evaluating the performance of equipment applied in aircraft. The temperature rise of the motor is closely related to the reliability of the motor. Therefore, based on Taguchi, a novel multi-objective optimization method for the heat dissipation structural design of an electro-hydrostatic actuator (EHA) drive motor was proposed in this paper. First, the thermal network model of the EHA drive motor was established. Second, a sensitivity analysis of the key parameters affecting the cooling performance of the motor was conducted, such as the thickness of fins, the height of fins, the space of fins, the potting materials and the slot fill factor. Third, taking the average temperature of the windings and the power weight ratio as the optimization goal, the multi-objective optimal design of the heat dissipation structure of the motor was carried out by applying Taguchi. Then, a 3-D finite element model of the motor was established and the steady state thermal analysis was carried out. Furthermore, a prototype of the optimal motor was manufactured, and the temperature rise under full load condition tested. The result indicated that the motor with the optimized heat dissipating structure presented a low temperature rise and high power weight ratio, therefore validating the proposed optimization method.

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.

To achieve the optimal feasible force density vector of a given geometry configuration tensegrity grid structure, an efficient procedure is presented for optimal initial self-stress design of tensegrity grid structures by consecutively solving two linear homogeneous systems in conjunction with a minimization problem. The nonlinear constrained optimization algorithm, known as the Interior-Point Method (I-PM), is utilized to obtain the minimal solution, leading to a set of force densities which guarantee the non-degeneracy condition of the force density matrix. The evaluation of the eigenvalues of tangent stiffness matrix is also introduced to check the geometric stability of the tensegrity grid structures. Finally, three numerical examples have been investigated comprehensively to prove the capability of the proposed method in optimal initial self-stress design of tensegrities. Furthermore, division of number of member group has been discussed in detail for the purpose of demonstrating the efficiency of the proposed method in seeking initial force densities of tensegrity grid structures.

This article proposes an efficient parameterized level set method (PLSM) for structural topology optimization design with minimum compliance as the objective function and volume fraction as the constraint condition. In the stage of establishing the optimization model, the level set function (LSF) is interpolated using compactly-supported radial basis functions (CS-RBFs) to transform the Hamilton-Jacobi partial differential equation (PDE) into ordinary differential equations (ODEs), thereby making the evolution of the LSF more convenient and efficient, and ensuring the smoothness of the optimization result boundary. The method of moving asymptotes (MMA) is used for solving the established optimization model, and meanwhile the shape sensitivity constraint factor is added to improve computational efficiency. During the evolution of the LSF, an approximate re-initialization scheme is employed to prevent the gradient of the LSF boundary from being too large or too small, thereby improving the numerical stability and the convergence speed of structural topology optimization process. Furthermore, the proposed method is also extensible and applicable to topology optimization of multi-material structures. The feasibility and effectiveness of this method have been verified through several typical numerical examples involving topology optimization of single-material structures and multi-material structures within the framework of minimum compliance design. HIGHLIGHTS An efficient parameterized level set method using the approximate re-initialization scheme is proposed for structural topology optimization. The approximate re-initialization scheme is employed when solving the parameterized level set function via the MMA algorithm. This scheme can prevents the gradient of the level set function boundary from being too large or too small, making the level set function update more stable and accelerating the convergence speed of structural topology optimization. The effectiveness and feasibility of the proposed method are demonstrated through examples of single-material and multi-material structural topology optimization.

This paper presents a design optimization method for all-wood concrete-slab forms. This procedure was formulated to provide for a safe slab-form design with minimum cost. It considers in its design process the cost of each slab-form component (sheathing, joist, stringer, and wood shore) and all available combinations of slab-form components. The performance of the optimum design method is compared to that of the traditional design method, which uses design charts/tables. The optimum design method was found to have a potential cost savings over the traditional design method. A study was conducted to confirm these cost savings. The results of the study show that cost savings as high as 9.9% were achieved by using the design optimization method.

Research on multidisciplinary fatigue optimization design method in structural design of high speed train

A simultaneous optimization method for the aerodynamic design of rotor and wind-lens for wind-lens turbine has been developed. The present optimal design method is based on a genetic algorithm (GA), and optimizes simultaneously blade loading distribution and wind-lens shape. Three-dimensional Reynolds averaged Navier-Stokes (RANS) simulation for the wind-lens turbine designed by the optimal design method has been conducted on the off-designed conditions. The result shows that the wind-lens turbine designed by the optimal design method is superior to the conventional one in the total performance, because of the suppression of flow separation on the inside of wind-lens, the lower stall point, and the smaller difference between design and actual attack angles. The analysis indicates also that the more suppression of flow separation and the less difference between design and actual attack angles raise the performance of wind-lens turbines.

Under high gravity loads, steel double-beam floor systems need to be reinforced by beam-end concrete panels to reduce the material quantity since rotational constraints from the concrete panel can decrease the moment demand by inducing a negative moment at the ends of the beams. However, the optimal design process for the material quantity of steel beams requires a time-consuming iterative analysis for the entire floor system while especially keeping in consideration the rotational constraints in composite connections between the concrete panel and steel beams. This study aimed to develop an optimal design method with the LM (Length-Moment) index for the steel double-beam floor system to minimize material quantity without the iterative design process. The LM index is an indicator that can select a minimum cross-section of the steel beams in consideration of the flexural strength by lateral-torsional buckling. To verify the proposed design method, the material quantities between the proposed and code-based design methods were compared at various gravity loads. The proposed design method successfully optimized the material quantity of the steel double-beam floor systems without the iterative analysis by simply choosing the LM index of the steel beams that can minimize objective function while satisfying the safety-related constraint conditions. In particular, under the high gravity loads, the proposed design method was superb at providing a quantity-optimized design option. Thus, the proposed optimal design method can be an alternative for designing the steel double-beam floor system.

A general method for optimal elastic design of indeterminate structures by decomposition of the structure into separate subproblems is proposed. Both stiffness and flexibility method formulations are presented. The iterative two-level approach that is mainly intended for large systems consists of dividing the structure into smaller substructures, optimized independently at a first level. Forces and displacements along the intersections of the substructures are held constant during the first-level solutions but are optimized at a second level. All intermediate solutions of the first-level problem are feasible and thus the optimization iteration can always be terminated with a feasible solution. In general, decomposition can be performed in different ways. Criteria for successful formulation are established, for which simple and efficient solutions are obtained. The method might prove useful in different optimal design problems of trusses, frames, and beams. Numerical examples demonstrate the application of the method to a variety of problems.

The cutting head is the core working mechanism of the roadheader for coal-rock materials cutting. The efficient and high performance design of cutting head is the key to improve the road head digging and mining technology. In this paper, based on cutting head design theory and virtual prototype technology, we propose a computer-aided structure design and performance optimization method for cutting head. We compile the calculation code and realize the reading and storing of relevant data through Excel. In particular, to obtain more realistic cutting performance data of the cutting head, we construct a coupling model of cutting head cutting rock wall based on virtual prototype technology, and then establish a database matching structural parameters, working parameters, coal-rock properties and cutting performance through extensive simulations. Based on the method, we complete the design of EBZ220 roadheader cutting head. We show that our method can realize the fast and efficient design of cutting head, and the designed cutting head has good working performance.

Improving parameter estimation with an efficient sequential probabilistic collocation-based optimal design method

<p>This paper defines basic operations of neutrosophic numbers and neutrosophic number functions for objective functions and constraints in optimization models. Then, we propose a general neutrosophic number optimization model for the optimal design of truss structures. The application and effectiveness of the neutrosophic number optimization method are demonstrated through the design example of a two-bar truss structure under indeterminate environment to achieve the minimum weight objective under stress and stability constraints. The comparison of the neutrosophic number optimal design method with traditional optimal design methods proves the usability and suitability of the presented neutrosophic number optimization design method under an indeterminate / neutrosophic number environment.</p>