Research on complementary dispatch based on multiobjective optimization model in wind-solar group coordinated control

The utilization of additive manufacturing in producing tubular honeycomb (THC) structures, leveraging capabilities of fused filament fabrication, enables the introduction of attributes, such as buckling initiators, to augment energy absorption characteristics. Increasing crush efficiency and/or energy absorption efficiency of THC structures bolsters payload and occupant protection in vehicular systems during impact scenarios such as collisions for ground vehicles or harsh landings for aircraft. In this investigation, THC structures composed of acrylonitrile butadiene styrene (ABS) plastic were additively manufactured so that buckling initiators (BIs) could be efficiently incorporated in the THC structure and readily positioned at the top, 3/4 height, or half height of the samples. Each configuration was subjected to quasi-static (0.03 mm/s) and constant (0.5 m/s) velocity testing employing an MTS machine, with three specimens manufactured for each test condition. Results demonstrated a notable 12.60% increase in energy absorption efficiency and a 15.75% increase in crush efficiency for specimens featuring BIs at the top of the sample as compared to those without BIs under quasi-static conditions. Furthermore, substantial improvements were also observed under constant velocity testing, indicating the efficacy of BIs at the top of the sample in promoting structural folding and progressive collapse, thereby increasing crush energy absorption and crush efficiency.

Crashworthiness design draws considerable attention and interest in energy absorption systems. An optimal design of circular stepped tubes based on free inversion is presented in the current work to improve and enhance the crashworthiness characteristics under axial impact loading. Circular tubes have been known to be efficient energy absorbers per unit weight, and may be considered as the main part of energy absorbing devices even for frequently impact operation like landing gear or for sudden accidents like other vehicles. The precise choice of the circular tubes' material, shape, and mechanism may save a person life or save a valuable equipment from damage. Adaptive Multiple-Objective Optimization (AMO) can obtain more light and efficient section. An optimization of variable parameters, which represent the shape of a stepped tube under axial impact, is performed using the platform of ANSYS-DESIGN-EXPLORATION linked with LSDYNA code. The analysis leads to 16% reducing in mass with corresponding 31% improving in energy absorption.

Renewable energy systems, exemplified by solar and wind power, are increasingly integrated into modern power grids to mitigate environmental impact and reduce reliance on fossil fuels. However, the inherent intermittency and unpredictability of renewable energy sources pose challenges to grid stability and reliability. Energy Storage Systems (ESS) offer a promising solution to address these challenges by smoothing out power fluctuations and ensuring a consistent power supply. Among various ESS technologies, Flywheel Energy Storage Systems (FESS) have emerged as a noteworthy contender due to their rapid response times, low operating costs, and extended lifespan. This paper focuses on investigating the operation of a novel unit comprising a solar power system integrated with a Flywheel Energy Storage System (PV-FESS). The aim is to develop an effective control algorithm utilizing adaptive fuzzy neural networks and model predictive control (ANFIS-MPC) to manage power fluctuations stemming from renewable energy sources within the grid. The proposed control strategy aims to optimize the operation of the PV-FESS system by dynamically adjusting the energy absorption or release of the flywheel to maintain grid stability. Simulation studies conducted using Matlab-Simulink/Simcape software validate the efficacy of the ANFIS-MPC algorithm in mitigating abnormal fluctuations from renewable energy sources. The results demonstrate that the PV-FESS system effectively balances power fluctuations, ensuring a stable and reliable power output to the grid.

The energy absorption control characteristics of Al thin-walled tube under quasi-static axial compression

Investigation on the microstructure and compressive behavior of open-cell copper- Al2O3 composite foams

With the development of excellent software in optimization, there is more and more wishes to use these techniques and make epoch developments in their products. However, most of us know that it costs a lot of time and costs to carry out optimization, because it needs to repeat simulations for the number of times. Therefore, most engineers would like to make mathematical models of design problems just enough to express their needs priori to optimization. Let us call these models as light models, in this paper. However, it is very difficult to make a proper light model in the first trial. Recent optimization will find the global solution, so that it will find some modeling miss and lead light model to some strange results. Such phenomenon is not a fault of optimization, but of the light model. We have to revise the light model but it is way difficult to make it rationally with the information we have had from the light model. We have to think of appropriate values of existed constraints, we have to think of new functions for constraints, and so on. It is almost hopeless to revise the light model at one time. The best thing that we can hope for is to give up the light model and make models complex to express the situation of the products. If we do not know proper values for constraints, treat them as objective functions and just go through trade-off analysis to have their relationships information, so that we can give appropriate values. In this sense, it is very important to make models in multi-objective optimization. In multi-objective optimization, it is quite important to carry out trade-off analysis and which might be a key to find epoch design. We had developed approximate multi-objective optimization method, which is composed by satisficing method, convolute radial basis function network and recommendation of new design variables. In satisficing method, we can handle trade-off analysis much easier than weighting methods. However, scalar function composed by satisficing method is not smooth when it gets close to Pareto solution that is indicated by designer’s requirement. Therefore, it is difficult even for convolute RBF to compose better approximate function although we have better approximation for each objective function. In weighting method, it is quite difficult to give proper weights for designer’s requirement. In approximate optimization, fortunately we have a number of data sets. Thus, it is possible to optimize weights which meet for aspiration level in satisficing method. Then, we can have smooth and better approximation for scalar function. In this paper, we are going to show effectiveness of the proposed method through demonstration of numerical examples.

Thin-walled tubes as energy absorption devices are widely in use for their low cost and high manufacturability. Employing origami technique on a tube enables induction of a predetermined failure mode so as to improve its energy absorption efficiency. Here we study the energy absorption of a hexagonal tubular device named the origami crash box numerically and theoretically. Numerical simulations of the quasi-static axial crushing show that the pattern triggers a diamond-shaped mode, leading to a substantial increase in energy absorption and reduction in initial peak force. The effects of geometric parameters on the performance of the origami crash box are also investigated through a parametric study. Furthermore, a theoretical study on the deformation mode and energy absorption of the origami crash box is carried out, and a good match with numerical results is obtained. The origami crash box shows great promise in the design of energy absorption devices.

Energy absorption of bio-inspired multi-layered graded foam-filled structures under axial crushing

Axial crushing of self-lock multi-cell tubes with foam filler and tube envelope

Lightweight cellular materials are engineered to enhance performance attributes such as energy absorption, specific stiffness, negative Poisson's ratio, negative thermal expansion coefficient, etc. However, self‐sensing functionality of such architected materials is seldom explored. Herein, a combined experimental and numerical study on additive manufacturing (AM)‐enabled self‐sensing cellular composites processed via fused filament fabrication, utilizing in‐house engineered multiwall carbon nanotube (MWCNT)/polypropylene random copolymer (PPR) filament feedstocks, is reported. The tunable self‐sensing and enhanced mechanical performance of PPR/MWCNT lattices are experimentally demonstrated by varying their architectural parameters in addition to the MWCNT content. The lattices reveal strain and damage sensitivity gauge factors of 12 and 1.2, respectively, comparable to bulk materials’ commercial gauge factors. Furthermore, self‐sensing lattices exhibit 200%, 155%, 153%, and 137% increase in stiffness, energy absorption capacity (as high as 4.7 MJ m−3), specific energy absorption (20.5 J g−1), and energy absorption efficiency (90%), respectively, compared with their non‐reinforced counterparts. The tunable multifunctional performance of AM‐enabled cellular composites demonstrated here provides guidelines for the design and development of composite lattices with advantaged structural and functional properties for an array of applications such as patient‐specific biomedical devices capable of measuring comfort in prosthetics.

In this paper, a hybrid thin-walled tube with multiple cells and multiple materials is proposed to achieve lightweight, high energy absorption efficiency, and low cost of structures. Energy absorption characteristics and crushing deformation of the hybrid structures are investigated by experimental testing and numerical analysis. Meanwhile, theoretical prediction models of the mean crushing force for hybrid structures are developed and its accuracy was verified. It is found from the sensitivity analysis that the parameters of the multi-cell structure have significant effects on energy absorption. Furthermore, the multi-objective optimization including surrogate models is performed to obtain optimal crashworthiness of the multi-cell hybrid tube. The same optimal results were obtained using the full factor response mapping optimization algorithm and the non-dominated sorting genetic algorithm with elite strategy algorithm for multi-objective optimization solution. Compared with the original multi-cell hybrid tube and multi-cell pure aluminum (Al) tube, the optimized structure showed an increase of 0.25% and 25.31% in specific energy absorption, an increase of 16% and 77.34% in average crushing force, and an increase of 3.89% and 23.08% in energy absorption efficiency, respectively.

Stabilized and efficient multi-crushing properties via face-centered hierarchical honeycomb

The aim of this study is to numerically investigate the low‐velocity impact behavior of carbon fiber reinforced orthogonal woven fabric composite sandwich structures with five different geometric configurations and four different curve angles. Low velocity impact simulations were performed in LS DYNA finite element program to investigate the effects of core configuration and curve angle on peak contact force, energy absorption efficiency and damage mode. A progressive damage analysis based on the combination of the Hashin damage criterion and the Cohesive Zone Model (CZM) with bilinear traction‐separation law was performed using the MAT‐54 (ENHANCED_COMPOSITE_DAMAGE) material model. Among the five different cores, Trapezoidal core has the highest peak force average of 2.9 kN while Triangular core sandwich structure has the lowest with 1.23 kN. Absorbed energy efficiency average was highest for rectangular core with 0.95 and lowest for sinusoidal core with 0.69. The specific absorbed energy value was highest for Triangular core with 0.312 J/g and lowest for Sinusoidal core with 0.178 J/g. The damage area on the structure increased with increasing curve angle. It was determined that the core structure and curve angle is an effective parameter on peak force and energy absorption efficiency.Highlights Impact behavior of sandwich composite structures was examined. The effects of core type and curve angles on peak force, energy absorption efficiency and specific absorption energy were investigated. Specific absorption energy rates were compared with studies in the literature.

The radiation absorption profiles on the surfaces of TiO2 films in a corrugated‐plate photocatalytic reactor were modeled based on first principles. A new term, the local‐area‐specific rate of energy absorption (LASREA), was adopted to describe the catalyst surface radiation in heterogeneous photoreactors. The LASREA and the energy absorption efficiency were both quite sensitive to the dimensions of the corrugated plates. Due to the multiple photon reflections between the opposing surfaces, corrugated plates possess a superior capability for recapturing longer wavelength photons that would otherwise be reflected out of some reactor designs. This results in higher energy absorption efficiency and more uniform LASREA on the catalyst films. Compared to a flat plate, corrugations are predicted to enhance the energy absorption efficiency by up to 50% for UV‐A fluorescent‐lamp‐powered systems and more than 100% for solar‐powered systems.

To improve the multiple performance indices of practical engineering structures under uncertainties, an interval constrained multiobjective optimization model was constructed with structural performance indices included in objectives and constraints being functions of the interval uncertain parameters. An algorithm integrating radial basis function (RBF), interval analysis, and non-dominated sorting genetic algorithm (NSGA-II) was put forward to locate the Pareto-optimal solutions to the interval multiobjective optimization model. A series of RBFs were constructed based on the Latin hypercube experimental design (LHED) and finite element analysis (FEA), which were then integrated with interval analysis to compute the interval bounds of the objective and constraint functions under the fluctuation of uncertain parameters. Then the fitness of every individual during the NSGA-II-based optimization could be obtained. The case study on the optimization of the mechanical performance of a press slider with uncertain material properties demonstrated the feasibility and validity of the proposed methodology.