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Noise reduction for manufacturing enterprises is favorable for workers because it relieves occupational diseases and improves productivity. An acoustic metamaterial with parallel, unequal cavities is proposed and optimized, aiming to achieve an optimal broadband sound absorber in the low–frequency range with a limited total thickness. A theoretical model for the acoustic metamaterial of a hexagonal column with 6 triangular cavities and 12 right–angled trapezoidal cavities was established. The lengths of these embedded apertures were optimized using the particle swarm optimization algorithm, with initial parameters obtained from acoustic finite element simulation. Additionally, the impacts of manufacturing errors on different regions were analyzed. The experimental results prove that the proposed acoustic metamaterials can achieve an average absorption coefficient of 0.87 from 384 Hz to 667 Hz with a thickness of 50 mm, 0.83 from 265 Hz to 525 Hz with a thickness of 70 mm, and 0.82 from 156 Hz to 250 Hz with a thickness of 100 mm. The experimental validation demonstrates the accuracy of the finite element model and the effectiveness of the optimization algorithm. This extensible acoustic metamaterial, with excellent sound absorption performance in the low-frequency range, can be mass-produced and widely applied for noise control in industries.

In today’s data-driven age, the thermal properties of computer transistors play an important role. In this research, finite element simulation is employed to construct the structural model of the primary components within a computer chassis, and the thermal performance is evaluated based on ambient temperature, thermal conductivity, and heat dissipation rate. By combining the particle swarm optimization algorithm with numerical simulation for joint simulation and structural optimization, the component layout was optimized to reduce the working temperature. The results show that when the background temperature, that is, the ambient temperature, rises from −20 °C to 60 °C, the maximum operating temperature of the computer is approximately 88 °C. The maximum temperature is mainly in the transistor core and the minimum temperature is in the intake grille, and the operating temperature of the optimized structure decreases by approximately 10 °C. The research shows that the operating temperature is most sensitive to the change of background temperature, and the transistor core is the main heating source. The maximum temperature can be reduced by rationally adjusting the position of the components. This study provides a reference for analyzing the thermal performance of computers and optimizing structures.

The combination structure of a porous metal and microperforated panel was optimized to develop a low frequency sound absorber. Theoretical models were constructed by the transfer matrix method based on the Johnson—Champoux—Allard model and Maa’s theory. Parameter optimizations of the sound absorbers were conducted by Cuckoo search algorithm. The sound absorption coefficients of the combination structures were verified by finite element simulation and validated by standing wave tube measurement. The experimental data was consistent with the theoretical and simulation data, which proved the efficiency, reliability, and accuracy of the constructed theoretical sound absorption model and finite element model. The actual average sound absorption coefficient of the microperforated panel + cavity + porous metal + cavity sound absorber in the 100–1800 Hz range reached 62.9615% and 73.5923%, respectively, when the limited total thickness was 30 mm and 50 mm. The excellent low frequency sound absorbers obtained can be used in the fields of acoustic environmental protection and industrial noise reduction.

The braking energy can be recovered and recycled by the regenerative braking system, which is significant to improve economics and environmental effect of the hydraulic hybrid vehicle. Influencing factors for the energy recovery rate of regenerative braking system in hydraulic hybrid vehicle were investigated in this study. Based on the theoretical analysis of accumulator and energy recovery rate, modeling of the regenerative braking system and its energy management strategy was conducted in the simulation platform of LMS Imagine Lab AMESim. The simulation results indicated that the influencing factors included braking intensity, initial pressure of the accumulator, and initial braking speed, and the optimal energy recovery rate of 87.61% was achieved when the parameters were 0.4, 19 MPa, and 300 rpm, respectively. Experimental bench was constructed and a series of experiments on energy recovery rate with different parameters were conducted, which aimed to validate the simulation results. It could be found, that with the optimal parameters obtained in the simulation process, the actual energy recovery rate achieved in the experiment was 83.33%, which was almost consistent with the simulation result. The obtained high energy recovery rate would promote the application of regenerative braking system in the hydraulic hybrid vehicle.

Rubber is widely applied in the field of electrical engineering due to its high elasticity. However, its poor thermal conductivity can cause localized overheating and eventual failure. This issue can be addressed through adding fillers with high thermal conductivity. In this study, natural rubber is selected as the matrix, while braided carbon fiber (B-CF), known for its excellent thermal conductivity, serves as the reinforcing phase. This research defines cubic Bessel curves, establishes a curvilinear coordinate system, and examines the orthogonal anisotropic thermal conductivity of B-CF bundles. It has been verified that eight cycles of fiber accurately represent the finite element simulation model. Based on this, the impact of the cross-sectional shape and area of the fiber bundle on heat dissipation was studied. The results show that the cross-sectional shape has minimal impact on heat dissipation, with temperature differences between the heat source center and the end of the cross-section line remaining within 1 °C. In contrast, the cross-sectional area significantly affects the reduction of the temperature, achieving reductions of up to 32.6% at the heat source center and 40.4% at the opposite side, respectively. This study provides valuable guidance for improving the thermal performance of braided fiber-reinforced rubber products.

To prevent noise pollution, a hexagonal acoustic metamaterial cell combining multiple parallel Helmholtz resonators with optional apertures is proposed. There were 6 trapezoidal chambers and 6 triangular chambers, and each front panel had 6 different apertures, which meant that there were 6 12 = 2176782336 possible permutations. The distribution of sound pressures obtained by acoustic finite element simulation revealed the acoustic absorption mechanism, which provided effective guidance to alter the absorption capacity. For certain scenarios, the acoustic absorption performance was optimized by the joint combination of artificial neural network and acoustic finite element simulation. Through manufacturing and testing the sample, actual average acoustic absorption coefficients were achieved at 0.6733, 0.7296, 0.8785 and 0.7065 for the target frequency ranges 350–950 Hz, 400–1000 Hz, 500–800 Hz and 350–700 Hz, respectively, with total thickness 40 mm. The tunable acoustic absorption property proved that the hexagonal acoustic metamaterial cell was appropriate for noise reduction with variable frequency ranges.

Porous metal is widely used in the fields of sound absorption and noise reduction, and it is a critical procedure to identify acoustic characteristic parameters and to improve sound absorption performances. Based on the constructed theoretical sound absorption model and experimental data, acoustic characteristic parameters of the porous metal were identified through the cuckoo search identification algorithm, and their reliabilities were certified through comparing with these labeled parameters and further experimental validation. By adding the microperforated metal panel in front of the porous metal, a composite sound-absorbing structure was formed, which aimed to improve the sound absorption performance of the original porous metal by optimizing the parameters. Finite element simulation and a standing wave tube measurement were conducted to validate the effectiveness and practicability of the optimal composite sound-absorbing structure. Consistencies among theoretical predictions, simulation results, and experimental data proved the effectiveness of the identification and optimization method. When the target frequency ranges were 100–1000 Hz, 100–2000 Hz, 100–3000 Hz, and 100–4000 Hz. Actual average sound absorption coefficients of the optimal composite structures were 0.5154, 0.6369, 0.6770, and 0.7378, respectively, which exhibited the obvious improvements with a tiny increase in the occupied space and a small addition in weight.

Sound absorption performance of polyurethane foam could be improved by adding a prepositive microperforated polymethyl methacrylate panel to form a composite sound-absorbing structure. A theoretical sound absorption model of polyurethane foam and that of the composite structure were constructed by the transfer matrix method based on the Johnson–Champoux–Allard model and Maa’s theory. Acoustic parameter identification of the polyurethane foam and structural parameter optimization of the composite structures were obtained by the cuckoo search algorithm. The identified porosity and static flow resistivity were 0.958 and 13078 Pa·s/m2 respectively, and their accuracies were proved by the experimental validation. Sound absorption characteristics of the composite structures were verified by finite element simulation in virtual acoustic laboratory and validated through standing wave tube measurement in AWA6128A detector. Consistencies among the theoretical data, simulation data, and experimental data of sound absorption coefficients of the composite structures proved the effectiveness of the theoretical sound absorption model, cuckoo search algorithm, and finite element simulation method. Comparisons of actual average sound absorption coefficients of the optimal composite structure with those of the original polyurethane foam proved the practicability of this identification and optimization method, which was propitious to promote its practical application in noise reduction.

The composite structure of a microperforated panel and porous metal is a promising sound absorber for industrial noise reduction, sound absorption performance of which can be improved through parameter optimization. A theoretical model is constructed for the composite structure of a microperforated panel and porous metal based on Maa’s theory and the Johnson–Champoux–Allard model. When the limited total thickness is 30 mm, 50 mm, and 100 mm respectively, dimensional optimization of structural parameters of the proposed composite structure is conducted for the optimal average sound absorption coefficient in the frequency range (2000 Hz, 6000 Hz) through a cuckoo search algorithm. Simulation models of the composite structures with optimal structural parameters are constructed based on the finite element method. Validations of the optimal composite structures are conducted based on the standing wave tube method. Comparative analysis of the theoretical data, simulation data, and experimental data validates feasibility and effectiveness of the parameter optimization. The optimal sandwich structure with an actual total thickness of 36.8 mm can obtain the average sound absorption coefficient of 97.65% in the frequency range (2000 Hz, 6000 Hz), which is favorable to promote practical application of the composite structures in the fields of sound absorption and noise reduction.

Sound absorption performance of a porous metal can be improved by compression and optimal permutation, which is favorable to promote its application in noise reduction. The 10-layer gradient compressed porous metal was proposed to obtain optimal sound absorption performance. A theoretical model of the sound absorption coefficient of the multilayer gradient compressed porous metal was constructed according to the Johnson-Champoux-Allard model. Optimal parameters for the best sound absorption performance of the 10-layer gradient compressed porous metal were achieved by a cuckoo search algorithm with the varied constraint conditions. Preliminary verification of the optimal sound absorber was conducted by the finite element simulation, and further experimental validation was obtained through the standing wave tube measurement. Consistencies among the theoretical data, the simulation data, and the experimental data proved accuracies of the theoretical sound absorption model, the cuckoo search optimization algorithm, and the finite element simulation method. For the investigated frequency ranges of 100–1000 Hz, 100–2000 Hz, 100–4000 Hz, and 100–6000 Hz, actual average sound absorption coefficients of optimal 10-layer gradient compressed porous metal were 0.3325, 0.5412, 0.7461, and 0.7617, respectively, which exhibited the larger sound absorption coefficients relative to those of the original porous metals and uniform 10-layer compressed porous metal with the same thickness of 20 mm.