Optimization Of Design Parameters Research Articles

Nature-Based Solutions for Landscape Performance Evaluation—Handan Garden Expo Park’s “Clear as a Drain” Artificial Wetland as an Example

As a technology for water landscape performance that considers landscape, ecological, and social effects, nature-based solutions play a crucial role in enhancing the functionality of integrated ecosystem services on the micro-scale. This study conducted a systematic investigation into the landscape performance of the “Clear as a Drain” composite sponge facility at Handan Garden Expo Park. The following conclusions were drawn: (1) In terms of ecological restoration support services, the “Clear as a Drain” artificial wetland exhibited diverse habitat types, a rich variety of plant species specific to the site’s region, and high plant diversity indices for shrubs (1.776) and herbaceous aquatic plants (3.352). Reclaimed water reused in the artificial terraced wetland promoted plant growth and diversity while contributing to site self-rehabilitation; plants also significantly contributed to carbon fixation, oxygen release, and carbon emission reduction. (2) Regarding ecological restoration regulation services, the artificial wetland effectively purified reclaimed water with substantial improvements observed in incoming water quality during spring, summer, and autumn—particularly notable purification effects were observed during the summer months. Pollutant reduction rates for COD, BOD5 ammonia nitrogen, TP, and TN reached 75.8%, 72.1%, 93.8%, 96.7%, and 90.3%, respectively; different independent subsystems within the wetland demonstrated distinct advantages in pollutant removal; park plants displayed strong air purification capabilities; annual energy savings from park plants could fully cover daily energy consumption for nearby residents. This case could serve as guidance for scientific management and design parameter optimization of other composite sponge facilities.

Optimization design of voltage regulation ring parameters for 1100 kV DC voltage ratio standard equipment based on FCC neural network

Optimization design of voltage regulation ring parameters for 1100 kV DC voltage ratio standard equipment based on FCC neural network

New Solid-State Acoustic Motion Sensors: Sensing Potential Estimation for Different Piezo Plate Materials.

The present paper discusses the scientific and technical problem of optimizing the design and characteristics of a new type of solid-state sensors for motion parameters on bulk acoustic waves in order to increase the signal-to-noise ratio and the detectability of an informative signal against the background of its own noise and interference. Criteria for choosing materials for structural elements, including piezoelectric transducers of the sensitive element, were identified; a corresponding numerical simulation was performed using the developed program; and experimental studies according to the suggested method were carried out to validate the obtained analytical and calculated positions. The experimental results revealed the correctness of the chosen criteria for the optimization of design parameters and characteristics, demonstrated the high correlation between the results of modeling and field studies, and, thus, confirmed the prospects of using this new type of solid-state acoustic sensors of motion parameters in the navigation and control systems of highly dynamic objects.

Nonlinear dynamics of planetary roller screw mechanism.

The synchronous meshing of the gear pair and the screw pair is a typical feature of the planetary roller screw mechanism. In order to fully derive and analyze the nonlinear dynamic characteristics of the system, this paper creatively incorporates the time-varying meshing stiffness of gear pair and the comprehensive transmission error into the research content. Combined with the thread contact force and friction force between the roller and the screw and between the roller and the nut, the nonlinear dynamic model of the planetary roller screw mechanism considering the meshing excitation of the gear pair is established. According to the time domain diagram, frequency domain diagram, phase plane diagram, Poincaré section diagram, three-dimensional spectrum diagram, and spatial phase diagram, the nonlinear behavior of the system is described in detail, and the bifurcation evolution process of the system under the excitation frequency parameters of the external load is revealed. In addition, based on the theory of multi-scale method and considering the variables such as meshing stiffness, meshing damping, and load fluctuation, the stability equation of the primary resonance of the system is derived. The analysis of the stability of the system under different working conditions shows that the parameters are selected within a reasonable range, which effectively reduces the primary common amplitude value and enhances the overall stability of the system. The research content improves the previous system dynamics modeling method and provides a theoretical basis for the nonlinear dynamics modeling method and parameter optimization design of the planetary roller screw mechanism.

Design parameter optimization method for a prestressed steel structure driven by multi-factor coupling

Design parameter optimization method for a prestressed steel structure driven by multi-factor coupling

Stability Analysis of Gravity Dam using Matlab Programming

Gravity dams are critical structures in civil engineering, designed to withstand the immense forces exerted by water pressure and gravity. Ensuring their stability is paramount to prevent catastrophic failures that could result in significant economic and environmental consequences. This study presents a comprehensive stability analysis of a gravity dam using MATLAB programming. The analysis focuses on evaluating the structural integrity and safety factors of the dam under various loading conditions, including hydrostatic pressure and seismic forces. MATLAB's computational capabilities are utilized to perform rigorous numerical simulations, incorporating finite element analysis (FEA) and stability criteria assessments. Key aspects of the stability analysis include the determination of critical failure modes such as sliding, overturning, and base pressure distribution. Through MATLAB programming, the study explores different dam geometries and material properties to assess their influence on overall stability. Furthermore, sensitivity analyses are conducted to investigate the impact of uncertainties in input parameters on the dam's stability margins. This provides insights into potential weak points and allows for optimization of design parameters to enhance dam safety.

Optimization Design of Hydraulic Fracturing Fracture Parameters of Horizontal Wells in Algal Limestone Reservoir

The algal limestone reservoir has extremely low permeability, developed dissolution pores and weak structural planes, and has heterogeneity. There is a problem of significant differences in single-well production after fracturing in oilfield sites. It is crucial to clarify the matching relationship between hydraulic fracture parameters and production. This article establishes a triple medium seepage mathematical model of “fracture—dissolution pore—matrix pore” considering the lithological characteristics of algal limestone, which is used to predict the cumulative production of horizontal wells after fracturing, and its reliability is verified through example well production data. The influence of fracture parameters on the production of horizontal wells was revealed through numerical simulation, filling the gap in the study of parameters for the stimulation of algal limestone reservoirs. The results indicate that the proposed triple medium model can accurately characterize the characteristics of algal limestone and is suitable for simulating the production capacity of algal limestone reservoirs. The production of horizontal wells is influenced by various hydraulic fracture parameters. The length, conductivity, and height of hydraulic fractures are positively correlated with production, while the spacing between fractures is negatively correlated with production. Taking the overall production of the platform horizontal well group as the optimization objective, and the change in production increase as the discrimination criterion, the optimal values of various fracture parameters are determined. At the same time, simulation results show that using the staggered fracture pattern is beneficial for improving the overall production. The research results have reference significance for the development of algal limestone reservoirs

Multi-objective optimization of efficient liquid cooling-based battery thermal management system using hybrid manifold channels

Maintaining a battery cell at an optimal temperature improves both its performance and lifespan. This study proposes a cold plate equipped with hybrid manifold channels, positioned at the bottom of a high-capacity 280 Ah LiFeO4 battery pack. Based on the developed whole battery pack model, the response surface method elucidates the functional relationship between design parameters (i.e., the width of parallel channels, the width of manifold channels, the height of parallel channels, and the inlet velocity) and responses (i.e., the flow pressure drop, the temperature difference of the entire battery modules, and the temperature difference of the cold plate). Multi-objective optimization of design parameters is performed to search the Pareto front to maximize thermal performance and minimize flow pressure drop, employing the NSGA-II algorithm. Results reveal that the maximum battery temperature can be limited to 30.73–33.78 °C with a coolant pressure drop ranging from 7.66 kPa to 1.76 kPa, at a heating power of 10 kW/m3 for the battery cell. The optimal design configuration, identified through TOPSIS, limits the maximum battery temperature to an acceptable temperature of 45 °C at a discharging rate of 3C, with a pressure drop below 4.2 kPa. Compared to the 280 Ah LiFeO4 battery with natural air cooling and forced flow immersion cooling systems, the maximum battery temperature with a discharging rate of 1C is reduced by 17.6 °C and 11.7 °C, respectively.

Low-velocity impact analysis and multi-objective optimization of hybrid carbon/basalt fibre reinforced composite laminate

Three-dimensional in-plane progressive damage model was developed for carbon/basalt fibre interlayer hybrid composites in this study, and cohesive element model was employed to simulate interlaminar damage. Numerical simulation of low-velocity progressive impact damage of hybrid composite laminate was carried out, and its accuracy was verified by physical impact test, with the maximum error of the maximum contact force, maximum displacement and energy absorption not exceeding 6.1% and the maximum error in damage area size within 4.8%. The effects of lay-up structure and angle on the impact properties of hybrid laminate were investigated through simulation. Finally, real number coding strategy was proposed for the parametric representation of the lay-up material and angle of each layer. Multi-objective optimization of hybrid laminate based on Kriging surrogate model and hybrid algorithm composed of elitist non-dominated sorting genetic (NSGA2) algorithm and multi-objective particle swarm (MPSO) algorithm was conducted. The optimal trade-off solution was selected from the Pareto solutions using technique for ordering preferences by similarity to ideal solution (TOPSIS) coupled with principal component analysis (PCA) methods. The coefficient of variance between peak force and maximum displacement of the optimized laminate was 49.3%, 44.9% and 31.4% lower than those of the pure CFRP laminate, pure BFRP laminate, and hybrid laminate before optimization, respectively, indicating that the balance degree of impact displacement and force has been substantially improved. The progressive impact damage simulation and parametric optimization design methodology proposed in this study provide useful guidance for the design of hybrid composite laminate.

Multi-objective optimization and performance improvement of CD nozzle design parameters for cold spray coating process using RSM, ANN and GA

This study presents the multi-objective optimization of the convergent-divergent (CD) nozzle for the cold spray (CS) process and investigates the impact of five key nozzle design parameters. A 2D axisymmetric baseline nozzle was optimized through face central composite design (FCCD), computational fluid dynamics (CFD) simulations, response surface methodology (RSM), artificial neural networks (ANN), and genetic algorithms (GA). The nozzle performance in the CS process advances the manufacturing technologies by significantly optimizing the four response variables. Comparative analysis shows that RSM models (R² = 0.9893) were more accurate on average than ANN models (R² = 0.9848), although ANN provided a deeper understanding of complex interactions with an overall correlation coefficient of 0.99191. Sensitivity analysis suggested that increasing convergent length (Lc) increases particle velocity (PV) before it stabilizes while particle temperature (PT) decreases due to cooling effects. Divergent length (Ld) increases PV to an optimal range, but reduces PT, indicating energy loss. Smaller injector inner diameter (Did) enhances PV but reduces PT. Injector length (Li) increases PV to a certain limit, beyond which benefits stabilizes, and also increases surface pressure (SP). Expanding the exit diameter (De) increases PV, drops PT and heat flux (HF), and reduces SP, indicating decreased flow resistance. Optimization with RSM coupled with numerical simulation (RSM-DF) improved PV, PT, HF, and SP by 9.1 %, 4.4 %, 17.9 %, and 27.6 % respectively. Further optimization with a 5–6–4 ANN and GA (NSGA-II) improved PV by 5 %, PT by 5.4 %, HF by 15.7 %, and reduced SP by 20.9 %. Integrating CFD, RSM, ANN, and GA provides an effective approach for optimizing CD nozzle parameters.

Modeling and Design Parameter Optimization to Improve the Sensitivity of a Bimorph Polysilicon-Based MEMS Sensor for Helium Detection.

Helium is integral in several industries, including nuclear waste management and semiconductors. Thus, developing a sensing method for detecting helium is essential to ensure the proper operation of such facilities. Several approaches can be used for helium detection, including based on the high thermal conductivity of helium, which is several times higher than air. This work utilizes the high thermal conductivity of helium to design and analyze a bimorph MEMS sensor for helium sensing applications. COMSOL Multiphysics software (version 6.2) is used to carry out this investigation. The sensor is constructed from poly-silicon and SiO2 materials with a trenched cantilever beam configuration. The sensor is electrically heated, and its morphed displacement depends on the surrounding gas's composition, which decreases in the presence of helium. Several factors were investigated to probe their effect on the sensor's sensitivity to helium, including the thickness of the poly-silicon layer, the configuration of the trench, and the thickness and location of SiO2 layer. The simulations showed that the best performance, up to 2 ppm helium detection level, can be achieved with thinner beams and medium trench lengths.

Systematic Review of Computational Fluid Dynamics Modelling and Simulation Techniques Employed in Vertical Axis Hydrokinetic Turbines

At present, Computational Fluid Dynamics (CFD) is being utilized to explore tidal and hydrokinetic turbine systems, advancing comprehension of turbulent flow phenomena and raising the accuracy of performance predictions for these fluid-driven turbines. Consequently, this utilization of CFD contributes to the optimization of efficiency in these devices. Turbines are subject to variations from the best design point due to the influence of fluctuating flow rates, despite the findings of recent research that have identified the ideal design points. In contrast to conventional literature reviews, systematic analysis offers numerous advantages. The methodological strategy applied in this study entailed cross-referencing the findings obtained from Web of Science (WOS) and Scopus databases to establish the comprehensiveness as well as reliability of researcher data. Improving the review process, elevating the prominence of the field of study, and establishing critical priorities to mitigate research bias are all potential strategies for enhancing the quality of these evaluations. This research divides its findings into three core themes: (1) Performance assessment for practical implications, (2) Numerical analysis for theoretical insights, and (3) Design parameter optimization for engineering relevance. These themes collectively provide a well-rounded examination of the research outcomes across practical, theoretical, and engineering dimensions. Finally, the research findings have the potential to act as a significant point of reference for informing the best design considerations pertaining to vertical axis turbines.

Optimization of pellet design parameters to achieve deep fueling depth in EAST plasma with PAM code

Deep pellet fueling depth is necessary to achieve a high-density high confinement operation and to conduct some pellet-related researches in current devices, such as trigger of internal transport barrier, and to achieve high fusion power and tritium burn-up fraction in future fusion devices. The newly developed PAM code which can make a fast evaluation on pellet ablation and deposition is applied to optimize injection parameters to achieve deep pellet fueling. Systematic scans on pellet injection parameters including pellet injection positions, injection angles, sizes and speeds are performed for optimization purpose, while at the same time demonstrating flexibility and time efficiency of the PAM code. Dependences of the pellet fueling depth on these injection parameters are revealed by simulation results and analyzed. Simulation results indicate that pellet penetration contributes more to the deep pellet deposition than the ∇B -induced plasmoid drifts in low temperature plasmas, while deep pellet fueling in reactor relevant high temperature plasmas has to rely on plasmoid drifts. Though a shallow penetration is expected in high temperature plasmas, the ∇B -induced plasmoid drift is expected to be larger than that in relatively low temperature plasmas.

Optimization of Ship Design for the Effect of Wind Propulsion

International regulations as well as strong market demand for zero-emission transport call for a radical change in the shipping industry. One very promising zero-emission propulsion system for shipping is wind propulsion. In this context, the EU-funded Orcelle Wind project (https://cordis.europa.eu/project/id/101096673) aims at using wind as the main source of ship propulsion and to demonstrate the effectiveness and viability of Wind Assisted Propulsion Systems (WAPS) by a retrofitting and new building demonstrator. In this paper, we explore the effect of wing sails on the concept design of a VLCC tanker in the frame of a newly parametric ship design optimization procedure.

Response Surface Optimization Design of G20CrMo Composite Surface Cylinder Texture Parameters and Analysis of Tribological Performance

Response Surface Optimization Design of G20CrMo Composite Surface Cylinder Texture Parameters and Analysis of Tribological Performance

Optimization design of heliostat field parameters based on gray Wolf algorithm

Optimization design of heliostat field parameters based on gray Wolf algorithm

Composite effects of residual stress and hardness gradient on contact fatigue performance of rough tooth surfaces and optimization design of detailed characteristic parameters

Residual stress and hardness gradient significantly affect the contact fatigue failure process of rough tooth surfaces, and the meticulous design of their characteristic parameters can help improve the fatigue resistance of gears. In this paper, an efficient computational method for rough tooth surface contact is established based on the reconstruction modeling of asperities and mixed lubrication analysis. By comprehensively considering the effects of residual stress and hardness gradient, the Dangvan multiaxial fatigue criterion is adopted to predict and analyze the contact fatigue life of the gear surface. The correlation between the surface residual stress, maximum residual stress depth, surface hardness, and effective hardening layer depth, among other characteristic parameters, and the contact fatigue performance of tooth surfaces is established. The results show that: (1) Increasing the magnitude of surface residual compressive stress and surface hardness can significantly reduce the risk of fatigue failure in the near-surface layer of the gear. To achieve the same fatigue performance, there is a linear negative correlation between the design values of the two parameters. (2) Affected by the double stress peaks in the rough tooth surface stress field, the maximum residual stress depth significantly affects the depth at which the highest failure risk occurs. With changes in roughness, the optimal design value of the maximum residual compressive stress depth changes from about 0.5 times the Hertzian contact half-width depth in the subsurface layer (Sa < 0.2 μm) to about 15 μm in the near-surface layer (Sa > 0.4 μm). (3) Considering both process cost and gear surface fatigue resistance, the design threshold for the effective hardening layer depth should be greater than the Hertzian contact half-width. This paper establishes a composite correlation between the meticulous characteristic parameters of residual stress, hardness gradient, and the contact fatigue performance of tooth surfaces, providing theoretical support for optimal design of tooth surface anti-fatigue performance.

Parametric Dynamic Simulation and Bayesian Design Optimization of a Front-Loading Washing Machine

Abstract Objective This paper presents the dynamic modeling and design optimization of a fully parametrized front-loading washing machine. Methods A thorough mathematical analysis is performed to capture the effect of nine design variables (including rotation speed, spring stiffness, weight balancer mass density, damping coefficient, spring and damper angles) on vibrational characteristics of the washing machine. The parametric simulation reveals a complex relationship between the vibrational dynamics and design variables, entailing a computationally efficient optimization approach. A Bayesian Optimization (BO) framework is developed, in which a Gaussian process model and Genetic Algorithm (GA) are utilized along with carefully selected acquisition functions to enable adaptive sampling and search for optimal design values. The objective function is to minimize the maximum amplitude of the tub displacement inside the washing machine body. Two case studies are performed to consider a different number of design variables and choices of various infill methods. Results Results show that the fully parametrized front-loading washing machine model is applicable for parametric simulation and design optimization. The proposed BO is able to successfully find a set of design variable values corresponding to the lowest maximum displacement for vibration reduction. A comparison analysis is also carried out to exhibit the difference in optimization convergence and computational cost caused by the choice of acquisition functions. Conclusion It is shown that the fully parametrized washing machine model yields a lower maximum displacement than the model with fewer design variables. Of the two acquisition functions studied for optimization, the Expected Improvement function converges more rapidly than the Lower Bound criterion.

A review of preparing high-purity metals by vacuum distillation

With the development of science and technology, the high-tech industry has increasingly higher requirements for the purity of metals. However, the presence of trace impurities can have a bad effect on the properties of metals. Vacuum distillation process is widely used to prepare high-purity metals because of its advantages of high metal recovery, good environmental protection and simple equipment. In this paper, the overall progress in the preparation of high-purity metals around the principle and process research of vacuum distillation is systematically summarized. Principles of vacuum distillation, variant design of vacuum distillation, parameter optimization and simulation are covered. Based on the current status of the preparation of high-purity metals by this technology, it is pointed out that mechanistic studies and simulations are indispensable in scientific research. This research has certain reference significance for improving production efficiency, saving production cost and improving metal purity.

Nonlinear impedance characteristics of a gas hydraulic energy absorber and performance prediction for railway transportation of valuable goods

It is meaningful to investigate the nonlinear impedance characteristics of gas hydraulic energy absorbers (GHEAs) and their potential application in modern railway transportation of valuable goods. Fluid-mechanics-based full parametric modelling of a GHEA used in a high-speed train is performed, both simulations with the developed mathematic model and physical experiments are carried out on the static and dynamic characteristics of the GHEA. The agreement between the results of the simulation and the experiment with tolerable deviations validates the nonlinear mathematic model. Longitudinal train dynamics (LTD) modelling and simulation of a Chinese rapid freight train with the validated GHEA model or the conventional MT-2 friction-type energy absorber model is finally conducted. The results show that when the train uses GHEAs instead of MT-2 energy absorbers, the coupler forces and vehicle accelerations of the train are significantly reduced, and the vehicles operate more steadily in situations such as train startup, emergency braking and shunting operations; thus, gas hydraulic energy absorber is protective and would be alternative for equipping rapid freight trains for the transportation of valuable goods. The obtained nonlinear mathematic model in terms of the structural, oil and gas property parameters of the GHEA is useful and meaningful in further parameter design optimization of GHEAs and optimal specification of GHEAs for rapid freight trains.