The layered oxyselenide BiCuSeO system is known as one of the high‐performance thermoelectric materials with intrinsically low thermal conductivity. By employing atomic, nano‐ to mesoscale structural ...optimizations, low thermal conductivity coupled with enhanced electrical transport properties can be readily achieved. Upon partial substitution of Bi3+ by Ca2+ and Pb2+, the thermal conductivity can be reduced to as low as 0.5 W m−1 K−1 at 873 K through dual‐atomic point‐defect scattering, while a high power factor of ≈1 × 10−3 W cm−1 K−2 is realized over a broad temperature range from 300 to 873 K. The synergistically optimized power factor and intrinsically low thermal conductivity result in a high ZT value of ≈1.5 at 873 K for Bi0.88Ca0.06Pb0.06CuSeO, a promising candidate for high‐temperature thermoelectric applications. It is envisioned that the all‐scale structural optimization is critical for optimizing the thermoelectricity of quaternary compounds.
A record‐high ZT value, the figure of merit, of ≈1.5 at 873 K in BiCuSeO is achieved through a Pb and Ca dual‐doping approach. Synergistically, the power factor is optimized by electrical structure tuning with Pb dopants, and the thermal conductivity is reduced by phonon scattering at CaO2 nanoclusters.
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•A hybrid fluid flow MR damper was designed.•The multiphysics field coupled simulation model of the MR damper was established using COMSOL software.•A multi-objective structural ...optimization method based on theoretical computational prediction model was proposed and a genetic algorithm was used to solve the prediction model.•The dynamic performance, current input time, and energy consumption for the proposed MR damper were simulated, and the experimental verification was also carried out.
Magnetorheological (MR) dampers are widely used in industrial applications due to its simple structure, fast response and adjustable damping performance. However, the volume of the MR damper will be limited by the installation space, which hinders the application to some extent. In this paper, a hybrid fluid flow MR damper which can be used in antiseismic building is designed to achieve better damping performance under constrained volume size. The multiphysics coupling simulation model and circuit simulation model are also established. Numerical results show the output damping force is 6.367 kN, the dynamic adjustable range is 50.768, and the current input time is 31 ms under the applied current of 2.0 A. In order to improve the dynamic performance of the designed MR damper under constrained volume size, a multi-objective structural optimization method based on theoretical calculation model is proposed. Experiments are also conducted to investigate the dynamic performance of the initial and optimal MR damper. Compared with the initial MR damper, the output damping force and the dynamic adjustable range of the optimal damper are improved by 6.6 % and 46.3 %, while the energy consumption is reduced by 10.7 %, respectively.
The volume presents a collaboration between internationally recognized experts on anti-optimization and structural optimization, and summarizes various novel ideas, methodologies and results studied ...over 20 years. The book vividly demonstrates how the concept of uncertainty should be incorporated in a rigorous manner during the process of designing real-world structures. The necessity of anti-optimization approach is first demonstrated, then the anti-optimization techniques are applied to static, dynamic and buckling problems, thus covering the broadest possible set of applications. Finally, anti-optimization is fully utilized by a combination of structural optimization to produce the optimal design considering the worst-case scenario. This is currently the only book that covers the combination of optimization and anti-optimization. It shows how various optimization techniques are used in the novel anti-optimization technique, and how the structural optimization can be exponentially enhanced by incorporating the concept of worst-case scenario, thereby increasing the safety of the structures designed in various fields of engineering.
In standard engineering practice, designers often aim to minimize the amount and volume of concrete in reinforced concrete (RC) frames by reducing the size of member cross-sections. This is done ...either for architectural reasons or because it is assumed to drive to more economic and environmentally friendly productions. The present study, for first time, compares the environmental footprint of RC frames designed for minimum concrete volume against designs for minimum embodied carbon. To serve this goal, six realistic 3D RC building frames are optimally designed for parametric values of the carbon factors of concrete and reinforcing steel materials. In this comparison, it is noticed that the carbon factors ratio R of reinforcing steel to concrete plays a key role. More particularly, it is found that for R ≤ 10 the designs for minimum concrete and carbon practically coincide. This is a useful observation since it signals a clear direction to designers to decrease concrete sections to achieve minimum environmental impact. Nevertheless, as R increases from 10, the two designs gradually deviate since the carbon footprint of rebars becomes more important. For high R values, the RC frames with the least amount of concrete produce, on average, up to 40 % more embodied carbon than the most environmentally clean designs.
With the increasing power of wind turbine generators (WTG), the failure rate of rolling bearings in wind turbines due to insufficient bearing capacity increases with the increase of bearing size. To ...overcome these challenges, this paper proposes a design optimization method for the rectangular groove elliptical sliding bearing (RGEB) of the WTG output shaft. This method can maximize the radial bearing capacity under the premise of ensuring that the oil film pressure is large, the end leakage and the temperature rise are small. The multidisciplinary design and modeling of RGEB are carried out according to the structure and working conditions of WTG. Based on computational fluid dynamics (CFD), the influence of the number of rectangular dynamic pressure grooves on the bearing performance is analyzed. The kriging model, BP neural network model, and SSA-BP model are constructed for each performance index of RGEB, to establish a high-precision combined surrogate model based on global error criterion. After establishing the optimization equation, the PSO and SQP combined optimization algorithm is used to optimize the optimal structural parameters. The results show that the bearing capacity of the optimized RGEB is 95.9% higher than that of the ordinary elliptical bearing (EB) without increasing the size and quality of the bearing. In addition, the combined surrogate model can effectively replace the expensive finite element model to deal with the WTG sliding-bearing optimization problem.
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•This review focuses on the structural optimization strategy of cationic chitosan.•Antifungal activities and potential applications of cationic chitosan derivatives are described and ...summarized.•Challenges, shortcomings, and prospect of cationic chitosan derivatives as antifungal therapy are emphasized and commented.
The increasing resistance of pathogen fungi poses a global public concern. There are several limitations in current antifungals, including few available fungicides, severe toxicity of some fungicides, and drug resistance. Therefore, there is an urgent need to develop new antifungals with novel targets. Chitosan has been recognized as a potential antifungal substance due to its good biocompatibility, biodegradability, non-toxicity, and availability in abundance, but its applications are hampered by the low charge density results in low solubility at physiological pH. It is believed that enhancing the positive charge density of chitosan may be the most effective approach to improve both its solubility and antifungal activity. Hence, this review mainly focuses on the structural optimization strategy of cationic chitosan and the potential antifungal applications. This review also assesses and comments on the challenges, shortcomings, and prospect of cationic chitosan derivatives as antifungal therapy.
Using gas lubrication theory and finite difference methods, this study solve the gas film pressure equation in spiral groove dry gas seal and assesses key performance aspects like opening force, ...leakage rate, and gas film stiffness. It examines how structural parameters affect sealing performance and utilizes Latin hypercube sampling with a radial basis neural network, optimized by genetic algorithms, for predictive analysis. The effectiveness of control variable, orthogonal, and genetic algorithm methods in optimizing sealing performance is comparatively analyzed. Findings reveal a substantial impact of structural parameters on sealing performance with intricate interdependencies. The neural network, trained with 400 samples, achieves a prediction error below 3.6%. Genetic algorithm optimization of structural parameters notably enhances seal performance over other methods.
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