Optimization Of Design Parameters Research Articles

Configuration and Parameter Optimization Design of a Novel RBR-2RRR Spherical Hybrid Bionic Shoulder Joint

To improve the workspace, linear displacement stiffness, and driving torque utilization of humanoid robot shoulder joint mechanisms, an offset-designed RBR-2RRR (R represents the revolute pair, and B represents the ball cage joint) spherical hybrid bionic shoulder joint configuration (SHBSJC) is proposed and its structural parameters are optimized. Firstly, the shoulder joint’s physiological structure is biomimetically designed, a prototype mechanism of RBR-2RRR SHBSJC is proposed, and its kinematics are solved. The deformation response of RBR-2RRR and 3-RRR under the same load is compared to verify the obtained configuration can improve the linear displacement stiffness. Considering the workspace and singularity, using the GCI and GDCI as optimization functions, the recommended and adopted values of structural parameters are obtained. The distribution diagrams of the LCI and LDCI demonstrate that the configuration meets performance expectations. To further increase the prototype mechanism’s workspace and match the human shoulder joint’s motion range, an offset-designed RBR-2RRR SHBSJC is proposed, and the offset angle, installation posture angle, and spatial mapping relationship of the mechanism are determined. The results of workspace comparison and virtual model machine action simulation indicate that the final configuration meets the workspace expectations. This work enriches the shoulder joint configuration types and has engineering application value.

Research on performance optimization of electrolytic cell: Non-parameter topology and parameter optimization

The technology of water electrolysis for hydrogen production converts renewable energy into hydrogen, enabling efficient storage and utilization of clean energy. The key to enabling the large-scale development of water electrolysis technology lies in enhancing the performance of electrolytic cells and minimizing energy consumption. The mastoid process structure obviously influences the electrolytic cell's flow and electrochemical performance. Therefore, this paper studied the sensitivity of the mastoid process structure to the optimization target, designed the shape topology and the parameter optimization structure, and further analyzed the influence of the two optimization methods on the flow and electrochemical performance of the electrolytic cell based on the multi-physics coupling model. The results show that under the same deformation area, the pressure drop of the topology and the parameter optimization structure is reduced by 17.17 % and 11.89 % compared with that of the original structure. The electrochemical properties were almost unaffected, and the change value was less than 0.1 %. Topology optimization design can achieve optimal performance within limited deformation constraints, and parameter optimization design is more conducive to industrial processing.

The SG‐Climbot: An Adaptable, Efficient, Inspection and Repair Robot for Steam Generator Heat Transfer Tube Sheet

ABSTRACTThe steam generator plays a crucial role as a safety component and protective barrier in nuclear power plants. Regular inspection and repair of heat transfer tubes, which operate in high‐temperature, high‐pressure, corrosive, and abrasive environments for extended periods, are essential. Inspection and repair robots move inside the steam generator to conduct comprehensive inspections and evaluations of the heat transfer tubes. However, existing robots have relatively simple execution devices and fixed movement methods, resulting in poor adaptability to different specifications of tube sheets and limited flexibility in handling maintenance tasks. In response to these limitations, the SG‐Climbot, a quadruped crawling tube sheet inspection and repair robot, has been proposed. This robot is designed to adapt to full‐specification tube sheets and operate efficiently by conducting inspections while moving. By comparing different motion modes, a robot configuration with a quadruped parallel structure was suggested. Kinematic and static analyses were conducted, resulting in the development of both forward and inverse kinematic models, along with the identification of conditions leading to tipping. Using parametric modeling and optimization design, optimized design parameters were obtained. Finite element simulation analysis was performed on the overall structure and main components, leading to an optimized structural model. Finally, based on the design model and computational analysis, a prototype was developed and tested. The experimental results indicate that the robot has achieved the expected functionality and performance targets. Its efficient maintenance operation mode of conducting inspections while moving provides a basis for the autonomous and intelligent development of steam generators.

Data-driven approach for design and optimization of rotor–stator mixers for miscible fluids with different viscosities

Rotor–stator mixers (RSMs) are essential equipment used in the food, pharmaceutical, and cosmetic industries. The performance of RSMs is conventionally analyzed using three approaches based on empirical correlations and experimental and numerical analyses. This paper introduces a new approach based on a multifidelity data-driven framework for designing and optimizing RSMs that systematically combines elements of experimental and high-resolution computational fluid dynamics (CFD) models to train a machine learning model to predict RSM performance. It was subsequently coupled to an optimization solver based on a genetic algorithm. The developed framework was applied to a small-scale RSM with variable rotor blade radius, rotor speed, stator mesh width, and mass flow rate that is operated to mix two miscible fluids with different viscosities. The RSM was optimized at two regimes of low and high viscosities to achieve the best performance in terms of shaft power and mixing indices. The results demonstrate the successful application of the developed frameworks. The optimization of the mixing of high-viscosity fluids yielded a higher improvement than that for low-viscosity fluids. A decrease in shaft power of approximately 50% was obtained for the high-viscosity fluids, whereas the mixing indices increased up to 20% by the optimization of the geometrical input design parameters. The proposed framework can be advantageous for designers and operators at the industrial scale.

Design and analysis of a single-stage supersonic turbine with partial admission

Supersonic impulse turbines are commonly used to harvest waste heat from systems based on organic Rankine cycles, automotive applications, and gas-generator liquid rocket engines. This research aims to design and analyze a single-stage supersonic turbine with a rated power of approximately 440 KW. We present a comprehensive preliminary design roadmap followed by design parameters optimization. The preliminary sizing is carried out using one-dimensional flow analysis, while the blade geometrical design is performed using the two-dimensional method of characteristics. The turbine performance is then analyzed through numerical simulations on three-dimensional models. Comprehensive parametric analyses are conducted to examine the turbine performance sensitivity to changes in partial admission (PA), mean radius, and turbine blade height using three-dimensional sliding mesh techniques (SMT). The current analysis simulates the full turbine to capture PA effects, rather than focusing on a single periodic sector as is common in turbomachinery simulation practices. Different PA scenarios are investigated, emphasizing a single rotor passage over a complete rotor cycle in a partially admitted turbine, and examining its charging and discharging mechanisms. Flow tracking over such a blade shows that the turbine rotor exhibits compressor-like behavior over most of the unadmitted zone, contributing to efficiency drops and severe transients.

Simulation optimization of the key design parameters of the deodorization system in municipal solid waste transfer station

Simulation optimization of the key design parameters of the deodorization system in municipal solid waste transfer station

An Improved Artificial Electric Field Algorithm for Determining the Maximum Length of Gravel Packing in Deep-Water Horizontal Well

Gravel packing in deep-water horizontal wells is an effective and practical sand control method, which is a key technical method to ensure efficient exploitation of deep-water oil and gas. To ensure the successful implementation of gravel packing in deep water horizontal wells, it is crucial to carry out effective optimization design of packing parameters. This paper proposes a novel optimization design approach for gravel packing in deep-water horizontal wells. In the proposed approach, an optimization model is proposed for gravel packing in deep-water horizontal wells, in which the gravel packing length is regarded as the objective function. Then, an improved artificial electric field algorithm (IAEFA) is introduced for optimizing the key gravel packing parameters so as to determine the maximum gravel packing length. For a specific case study, we conducted optimization calculations for gravel packing in a deep-water horizontal well. Results of the case study demonstrate that the optimization design approach based on the IAEFA algorithm can effectively address the parameter optimization problem of deep-water horizontal well gravel packing. For the target well of the case study, the maximum packing length obtained by the IAEFA algorithm could reach 1000.22 m, and the corresponding 3 sets of optimal packing parameters were also obtained. In the scenario of optimal packing parameters, the total time of gravel packing in target well is 566.6 min, and the total amount of sand consumption is 54,050.94 lbs. The bottom hole pressure during the injection stage remains stable with about 9780 psi, then slowly rises from 9788 psi to 9837 psi in the α-wave packing stage, and rapidly increases from 9837 psi to 9986 psi in the β-wave packing stage. The proposed approach provides an efficient and practical optimization tool for the optimal design of gravel packing in deep water horizontal wells.

Optimization of Design Parameters of Press Wheel Attached Straw Cutting Mechanism for Rice Residue in Simulated Field Condition

Optimization of Design Parameters of Press Wheel Attached Straw Cutting Mechanism for Rice Residue in Simulated Field Condition

Online control parameter optimization design for multi-machine coordinated loading system of hazardous substances

To address the parameter instability issues in hazardous materials handling during multi-machine loading and unloading operations, we propose a Full-Scale Smart Parameter Optimization Control (FSPOC) system specifically designed for multi-machine coordination. This system leverages a novel fish scale prediction algorithm tailored for cooperative multi-machine environments. Initially, the fish scale prediction algorithm, inspired by bionic fish scales, is developed to predict future system behavior by analyzing historical data. Building on this algorithm, we introduce a disturbance cancellation control theorem and design a parameter optimization controller to enhance stability in high-dimensional nonlinear spaces. The FSPOC method is then applied to a multi-machine cooperative system, enabling online distributed parameter optimization for complex systems with multiple degrees of freedom. The effectiveness of the proposed method was validated through simulations, where it was compared with two other optimization techniques: Genetic Algorithm-based PID (GAPID) and Chaotic Atomic Search Algorithm-based PID (CHASO). The simulation results confirm the superiority of the FSPOC method.

Multi-Objective Optimization of Building Design Parameters for Cost Reduction and CO2 Emission Control Using Four Different Algorithms

Multi-Objective Optimization of Building Design Parameters for Cost Reduction and CO2 Emission Control Using Four Different Algorithms

An experimental parametric analysis of the acoustic response in dielectric elastomer loudspeakers

This article presents an experimental parametric analysis of dielectric elastomer (DE) loudspeakers, which generate sound by means of soft lightweight electroactive polymer membranes, with no need for electromagnetic actuators. Attention is set on a simple topology, which consists of a DE actuator membrane deformed out-of-plane in a conical shape between fixed frames. Different scaled replicas of the system were built, featuring different diameters and elastomer membrane thickness, with the aim of highlighting the dependence of the acoustic response on the design parameters. An experimental analysis of the effect of different electrical and mechanical pre-loads was also carried out. Results suggest that the acoustic response is affected by both geometrical factors, possible effects of aero-elastic interactions, and the level of mechanical stress acting on the DE membrane. These findings provide valuable insights for the optimisation of DE loudspeaker design and operational parameters.

Study on the Effect of Thermal Characteristics of Grease-Lubricated High-Speed Silicon Nitride Full Ceramic Ball Bearings in Motorized Spindles

Grease lubrication is cost-effective and low-maintenance for motorized spindles, but standard steel bearings can fail at high speeds. This study focuses on high-speed full ceramic ball bearings lubricated with grease. The coefficient of friction torque in the empirical formula is corrected by establishing the heat generation model of full ceramic ball bearing and combining it with experiments. A simulation model of grease flow is established to study the influence of grease filling amount on grease distribution. The simulation model of the temperature field of a full ceramic ball bearing is established to analyze the influence of rotating speed on bearing heat generation, and experiments verify the calculation results of the theoretical model. The results show that an optimal grease filling amount of 15~25% ensures even distribution without accumulation. Additionally, when the amount of grease is constant, the outer ring temperature increases with higher rotating speeds. The test results show that when the grease filling is 0.9~1.2 g, it accounts for about 9~12% of the volume of the bearing cavity, and the temperature of the outer ring is the lowest. At a rotation speed of 24,000 rpm, the outer ring temperature of the grease-lubricated bearing is 50.1 °C, indicating a reasonable range for use in motorized spindles. It provides a theoretical basis for the optimization design of macro-structural parameters of full ceramic ball bearings in the future, which can minimize heat generation and maximize bearing capacity.

Lithium Battery Shell Mould Design and Process Parameter Optimization Method Based on Digital Technology

Lithium Battery Shell Mould Design and Process Parameter Optimization Method Based on Digital Technology

Improved control strategy and designed control parameters of pitch system for wind turbine considering blade load reduction

As wind turbines increase in the power, the longer the blade, the more severe the blade load. Traditional control strategies and control parameters do not consider to reduce blade load, which seriously threatens the safe operation of wind turbines. Therefore, this study proposes a pitch control strategy based on blade active damping control and a multistage control parameter design method. Firstly, this study proposes a pitch control strategy based on blade active damping control to reduce the blade load based on the establishment of a mathematical model of the pitch system considering the blade load and a dynamic model of blade active damping control. Secondly, in the control parameter initial values design of Stage Ⅰ, this study proposes a variable forgetting factor recursive least squares to identify a simplified mathematical model of the pitch system and a Low–overshoot Chien–Hrones–Reswisk to solve the proportional integral control parameter initial values. Thirdly, in the control parameter optimal values design of Stage Ⅱ, this study proposes an adaptive genetic algorithm with improved hyperbolic tangent function to optimize control parameter at the equilibrium points and proposes an adaptive control to calculate control parameter at the non–equilibrium points. Finally, based on the Bladed software for 2 MW and 5 MW wind turbines, the superiority of the proposed methods, effectiveness and applicability in improving the control accuracy of the output power and generator speed, and reducing the load situation at the blade root position are verified.

An optimizated additional damping control for suppressing ultra‐low frequency oscillation suppression based on SVC

AbstractThe ultra‐low frequency oscillation (ULFO) imposes an emerging stability challenge to the high proportion of hydropower grids. To suppress ULFO without reducing the primary frequency regulation of the hydro governor, a novel idea to exploit the voltage regulation effect of load is implemented. First, the additional damping controller is designed and configured in static var compensator (SVC), and the frequency analysis model considering the configuration of SVC as well as damping controller is established. Based on the model, the specific influence of SVC and controller on ULFO is analysed through eigenvalue calculation. In addition, the influence of various load models and SVC location on the damping level are further studied. Consequently, a parameter optimization design method for SVC additional damping control is proposed, it is modelled as the optimization problem of damping ratio in ULFO mode under multi‐operation conditions, which is solved by a particle swarm optimization algorithm. Finally, the effectiveness of the designed SVC additional damping controller is verified in the improved four‐machine two‐area power system and the actual power grid in China.

Quantitative evaluation of acid flow behavior in fractures and optimization of design parameters based on acid wormhole filtration losses

The technique of matrix acidification or acid fracturing is commonly utilized to establish communication with natural fractures during reservoir reconstruction. However, this process often encounters limitations due to filtration, which restricts the expansion of the primary acid-etching fracture. To address this issue, a computational model has been developed to simulate the expansion of an acid-etching wormhole by considering various factors such as formation process, injection duration, pressure build-up, and time-varying acid percolation rate. By analyzing the pumping displacement of acid-etching wormholes, this model provides valuable insights into the time-dependent quantities of acid percolation. It has been revealed that the filtration rate of acid-etching wormholes is strongly influenced by pumping displacement, viscosity, and concentration of the acid fluid used in stimulation as well as physical properties of the reservoir itself. Notably, viscosity plays a significant role in determining the effectiveness of acid fracturing especially in low-viscosity conditions. Acid concentration within 15% to 20% exhibits maximum impact on successful acid fracturing while concentrations below 15% or above 20% show no obvious effect. Furthermore, it was found that pumping displacement has a major influence on effective fracturing. However, beyond a certain threshold (> 5.0 m3/min), increased pumping displacement leads to slower etching distance for acids used in construction purposes. The simulation also provides real-time distribution analysis for acidity levels within eroded fractures during matrix-acidification processes and quantifies extent of chemical reactions between acids and rocks within these fractures thereby facilitating optimization efforts for design parameters related to matrix-acidification.

Hydrothermal properties with entropy generation effects on a hybrid nanofluid considering thermal radiation on a stretching/shrinking sheet

Heat transfer efficiency is a significant area of modern research because it is used in a variety of engineering domains, improving the performance of thermal systems such as solar collectors. In this article, a statistical optimization of hybrid nanofluid flow through a stretching/shrinking inclined surface inside the solar-powered ship with entropy generation is investigated by utilizing copper and alumina as a tinny-sized nanomaterial in base fluid water. Copper is also corrosion-resistant with a high thermal conductivity that can be useful in marine environments where salted water and humidity damage the other materials. Coating or a catalyst for solar thermal systems aluminum oxide can be utilized to generate steam or hot water by using the heat coming from the sun. The significance of thermal radiation is considered as the heat source. The developed mathematical model in the form of the partial differential equation is transformed to nonlinear coupled Ordinary Differential Equations (ODEs) by using similarity variables. The reduced equations are solved numerically by applying the shooting algorithm with the bvp4c tool of MATLAB. The surface response methodology is utilized for the statistical optimization of experimental design parameters. The entropy generation rises with the increase of Reynolds number and Brinkmann number. The highest entropy value is found for the Cu-Al2O3/water with λ = 1.0 for Re = 15 and Br = 15. No significant change is reported in the local Nusselt number for changing the Eckert number value. The Response Surface Modeling (RSM) result shows that the experimental input parameter rises with “a factor.”

Development of a new environmentally friendly and efficient centrifugal variable diameter metering device.

The design of the maize metering device involves centrifugal variable diameter pneumatic and cleaning mechanisms, aiming to enhance the performance and power efficiency of pneumatic maize metering devices. Leveraging the impact of changes in centrifugal diameter and the guidance and positioning of airflow, we optimize the hole insert, seeding plate, seed limit board, and integrated front shell. This optimization facilitates the adjustment of both the quantity and posture of seed filling. As a result, seeds can form a uniform flow within the annular cavity, reducing the wind pressure necessary for regular operation and decreasing power consumption. A quadratic regression orthogonal rotation combination experiment is conducted using a self-made experiment bench, considering ground speed, wind pressure, and seeding rate as the experiment factors. Furthermore, a comparative experiment involving a novel centrifugal variable-diameter type metering device. The results indicate optimal seeding performance when the ground speed is 13.2 km/h, the wind pressure is 1.2 kPa, and the feeding rate is 25 seeds/s. Under these conditions, the quality of feed index reaches 95.20%, the multi-index is 3.87%, and the miss index is 0.93%. Findings reveal that the developed seed metering device achieved a quality of feed index exceeding 93.00% across varying speeds of 12~18 km/h, aligning with the production requirements. Moreover, the actual power consumption of Type B and C is about 85.00% and 98.00% lower than Type A, standing at only 32.90 W at 18 km/h. The COP of Type C is about 86 times and 12 times that of Type A and B, respectively, meeting the demands for efficient production of maize seed metering devices. In comparison to traditional design and structural parameter optimization methods for maize seed metering device, this study is helpful to the sustainable development of maize industry and reduce environmental pollution.

A Novel Dung Beetle Optimization Approach for Automatic CMOS Analog Circuit Design

The main objective of the automated circuit sizing technique is to deal with the challenges of design tradeoffs in analog circuit design with improved accuracy and efficacy. Analog circuit design represents a multi-objective optimization challenge, where designers must properly balance various performance factors such as input and output impedance, power dissipation, area, unity-gain bandwidth, slew rate, and open-loop DC gain. Traditional design equations provide a sizing of differential amplifier MOS transistors, further optimization can be achieved through the application of meta-heuristic search techniques. Meta-heuristic search techniques can be used as local optimizers in a smaller search area to improve the optimization of design parameters. The differential amplifier circuit with current mirror load is optimized through the application of the Dung Beetle Optimization (DBO) algorithm. By using an evolutionary algorithm called DBO, all the required parameters were achieved with the least amount of transistor area and power dissipation when compared to the results of the Seeker Optimization Algorithm (SOA), Opposition based Harmony Search Algorithm (OHS), craziness-based particle swarm optimization (CRPSO), and Cuckoo Search (CS) algorithms.

Optimization of Design Parameters for Improved Buoy Reliability in Wave Energy Converter Systems

Wave energy converters are frequently subjected to cyclic fatigue loads, making them prone to structural failure. This study presents a comprehensive design for reliability analysis of buoy structures used in ocean energy converters. A finite element model (FEM) was developed using ABAQUS to evaluate the effects of different materials—linear low-density polyethylene (LLDPE) versus high-density polyethylene (HDPE)—as well as variations in rib spacing and structural thickness under uniform pressure conditions. The analysis considered configurations with 3, 5, and 7 ribs, and wall thicknesses of 0.5, 0.7, and 1 inch. Results indicated that increasing the number of ribs and wall thickness significantly reduces deflection and von Mises stress, enhancing structural stability. HDPE demonstrated superior strength and lower deflection compared to LLDPE, although with reduced ductility. This study provides critical insights into optimizing buoy design parameters to improve the structural performance and durability of wave energy converter buoys, ensuring their reliability and longevity in harsh marine environments.