Optimal Design Parameters Research Articles

Design and optimization of inertial amplifier for enhanced vibration control of bridges under moving loads

This paper introduces a vibration control strategy for bridges that involves the implementation of an inertial amplifier to mitigate train-induced vibrations. The study comprehensively evaluates the effectiveness of two types of vibration absorbers, namely spring-mass resonator (SMR) and inertial amplifiers (IA), using a non-dimensional mechanics-based framework. The study further employs a heuristic search adaptive genetic algorithm (GA) to determine the optimal design parameters for the proposed vibration absorbers. The aim is to minimize the mid-span displacement of the bridge through the optimization process. The theoretical non-dimensional framework and the optimization technique are first validated with existing literature, and further, the efficiency of the optimized IA over the SMR of the same static mass is estimated. The comparative studies elucidate that with a lower mass ratio and higher values of the speed parameter (η) and inter-spatial distance between loads (ϵ), the IA system is more effective in reducing the vibration amplitude due to significant mass amplification. However, for lower values of η and ϵ, the SMR seems effective with a higher mass ratio, consequently resulting in amplified static deflection.

Mathematical modelling and optimizing design of heliostat field

The heliostat field is a form of solar thermal power plant, The heliostat field is a crucial component of solar thermal power plants and establishing a heliostat field is of great significance for reducing carbon emissions. and is of great significance in reducing carbon emissions This paper focuses on the mathematical modeling and optimization design problem of the heliostat field. For three different design scenarios, firstly, based on the data provided by the China Undergraduate Mathematical Contest in Modeling 2023, a geometric optical efficiency model is proposed to determine the annual average optical efficiency and output thermal power under specific heliostat field design parameters. Secondly, aiming at the optimal design parameters of the solar furnace field under the condition of rated annual average output thermal power is 60 MW\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext{MW}$$\\end{document}, Particle Swarm Optimization (PSO) combing with efficiency model is utilized to determine the optimal design parameters of the heliostat field. Finally, this paper uses Quasi-Monte Carlo ray tracing (QMCRT) model to perform simulations, exploring how to obtain the optimal design parameters of the heliostat field with the goals of maximizing the output thermal power and ensuring high efficiency. Furthermore, the influence of normal disturbances on the annual average annual average thermal output power is investigated.

Optimisation of Parameters and Application of Green Recyclable Precast Hollow Steel Pipe Concrete Supports

Underground space development is a crucial approach to addressing traffic congestion in China’s cities, especially through underground construction. However, the traditional pit internal support system, particularly the concrete internal support system, has significant drawbacks. These include high energy consumption and carbon emissions, which are increasingly prominent issues. In this paper, a hollow precast concrete-filled steel tube (H-CFST) internal support system is proposed and a node connection scheme is designed. Through numerical simulation, the load-bearing characteristics of H-CFST with different aspect ratios, hollow ratios, hoop thicknesses, and hoop lengths are investigated, and the optimal design parameters are obtained. Finally, following a field application, monitoring data reveal that the precast H-CFST internal support demonstrates superior load-bearing capacity compared to the concrete internal support, successfully meeting the criteria for replacement of the concrete support.

Parametric Analysis and Numerical Optimization of Root-Cutting Shovel of Cotton Stalk Harvester Using Discrete Element Method

Aiming at solving the problems of the high cost of manual pulling, the low reliability of existing pulling devices, and the high breaking rates and high leakage rates in the process of cotton stalk reuse after removal from the field in the Xinjiang cotton area, a soil-loosening and root-cutting cotton stalk pulling and gathering machine was researched and designed; a root-cutting force model was established; the key parameters of the V-shaped root-cutting knife were calculated and optimized; and the ranges of the slide cutting angle, the cutting-edge angle, and the soil entry angle were determined. A shoveling process simulation of the V-shaped root-cutting knife and the root–soil complex was constructed, and the working mechanism of the V-shaped root-cutting knife was clarified. In order to verify the reliability and operation performance of the V-shaped root-cutting knife, the slide cutting angle, the cutting-edge angle, and the soil entry angle were used as the test factors, and a response surface test with three factors and three levels was carried out with the root-breaking force and the mean value of the cutting resistance as the test indices. The test results were analyzed by variance analysis, and the significant factors influencing the root-breaking force in descending order were the slide cutting angle, cutting-edge angle, and soil entry angle. The degrees of influence on the mean value of the cutting resistance were ordered as follows: slide cutting angle, soil entry angle, and cutting-edge angle. In order to make the V-shaped root-cutting knife achieve the optimal working state, the parameters of the test indices were optimized, and the optimal design parameters of the V-shaped root-cutting knife were set as follows: the slide cutting angle was 48.3°, the cutting-edge angle was 43.4°, and the soil entry angle was 26.2°. The field uprooting test showed that the average pass rate of root breakage was 94.8% and the average pull-out rate of cotton stalks was 93.2%. This study provides theoretical guidance for the development of a root-breaking mechanism for cotton straw harvesters.

Influence of Stator/Rotor Torque Ratio on Torque Performance in External-Rotor Dual-Armature Flux-Switching PM Machines

External-rotor dual-armature flux-switching PM (ER-DA-FSPM) machines have high torque density and decent fault tolerance, making them promising candidates for in-wheel machine applications in electric vehicles. The torque output and optimal design parameters of ER-DA-FSPM machines are affected by the stator/rotor torque ratio, which is the focus of this paper. Firstly, this paper analyzes airgap flux density harmonics of ER-DA-FSPM to provide a clear insight into the torque-generation mechanism. Then, this paper investigates the influence of torque ratio on average torque under the same copper loss. It is found that the average torque decreases with torque ratio increasing due to the reduction of the positive torque component generated by the sixth airgap field harmonics and the rise in the negative torque component from the eighth harmonics. Moreover, this paper also provides the optimal parameter recommendation to guide the machine design. The split ratio should increase, and the arc of PMs should decrease for a larger torque ratio, whilst the other parameters are hardly influenced. Next, this paper makes a comparison among the ER-DA-FSPM machine, external rotor flux-switching PM (ER-FSPM) machine, and surface-mounted PM (ER-SPM) machines. It shows that the ER-DA-FSPM machine, with the torque ratio being 2, can lead to a much larger total torque. In addition, in the event of rotor winding failure, which is more possible due to the existence of slip rings than stator winding failure, the stator can still provide an average torque larger than that of ER-SPM machine and 92.0% that of the ER-FSPM machine, respectively. Finally, the theoretical analysis is verified by the experiments.

Comparative assessment and optimization among several plenum shapes and positions for the forced air-cooled battery thermal management system

Plenum shape and position play a significant impact on the heat dissipation performance of battery pack with air-cooled structure. However, the existed plenum shape and position are simple. In this work, four different plenum shapes (slanted, convex, concave and stepped) of the battery thermal management system (BTMS) are designed. Then the influences of plenum shapes and positions (at the inlet, outlet, and inlet & outlet) on the heat dissipation performance of the battery are investigated, respectively. Subsequently, a single factor analysis is performed to obtain the range of the design parameters (Hin, Hout, Rin and Rout) in Design 6. Finally, a multi-objective optimization of Design 6 is carried out to further improve the thermal performance of BTMS. Numerical results demonstrate that: 1) For the significant improvement of the cooling ability, convex plenum is at the inlet & outlet whereas other shape ones are all at the inlet. 2) No matter where it is at the inlet, outlet, or inlet & outlet, the convex plenum achieves the excellent cooling effect in Z- and U-type air-cooled structures. 3) Design 6 (convex plenum at the inlet & outlet) exhibits the best cooling ability among all plenum shapes and positions. 4) The design parameters of the optimized Design 6 are Hin = 17.9 mm, Hout = 19 mm, Rin = 2100 mm and Rout = 2000 mm, and the maximum temperature and temperature difference respectively achieve a 35.06 % (18.921 K) and 76.98 % (19.923 K) reduction under such optimized design parameter settings in comparison with those of the benchmark (Design 9).

An improved multi-island genetic algorithm and its utilization in the optimal design of a micropositioning stage

An improved multi-island genetic algorithm (IMIGA) by integrating various common improvement methods, optimized through D-optimal and analysis of variance (ANOVA) techniques. IMIGA’s performance is validated against various state-of-the-art algorithms across CEC2020 test suite and classic engineering problems, affirming its superiority. IMIGA’s potential in industrial applications is demonstrated by employing it for optimal design in a micropositioning stage, leveraging machine learning (ML) for parameter optimization. With the optimal design parameters, driven by IMIGA and a surrogate ML model, the proposed stage attained a first natural frequency of 55 Hz and maximum strokes of 266.7 μm, 110.9 μm, and 0.7552 mrad in the x-, y-, and θ-directions, respectively. These experimental results closely align with the predicted outcomes from the design phase, highlighting the accuracy and reliability of the employed methodology. Such consistency between experimental measurements and predicted values underscores the efficacy of the design approach in achieving desired performance metrics.

Mechanism design optimization through CAD-based Bayesian optimization and quantified constraints

This study addresses the challenge of mechanism design optimization, particularly focusing on the energy efficiency and design space of reciprocating mechanisms. The research question centers on how to effectively utilize Computer-Aided Design (CAD) simulations alongside Bayesian optimization (BO) and a constrained design space to streamline the design optimization process, overcoming the limitations of traditional kinematic and dynamic analysis methods. The objective is to investigate and develop a novel optimization framework that integrates CAD-based simulations with a BO approach. To achieve this, the study employs a methodological approach. At first, the feasibility of a chosen mechanism design is evaluated through a sequence of CAD-motion simulations to quantify the (in)feasibility of this design. When this design appears to be feasible, a CAD-based design evaluation method is started, in which the objective value is extracted by a sequence of CAD-motion simulations. In this paper, we advocate the use of non-parametric Gaussian processes to build a surrogate model of the objective function and the feasible design space constrained by static and dynamic constraints. The main research results demonstrate that the proposed CAD-based Bayesian optimization framework can effectively identify optimal design parameters that minimize the root mean square (RMS) torque while adhering to specified static and dynamic constraints. This optimization approach significantly reduces the complexity associated with analytic methods, making it scalable to more complex mechanisms and implementable by machine builders. In conclusion, the study successfully develops a novel optimization framework that leverages CAD-based simulations and Bayesian optimization to streamline the design process of mechanisms. The results of an emergency ventilator case study with three design parameters show a reduction of the RMS torque with 71% after 255 CAD-based design evaluations. Moreover, the results demonstrate the effectiveness of incorporating constraints into the design optimization process and the usage of Bayesian optimization (BO), providing insights into the obtained optimum. This approach offers probabilistic insights into the expected improvement of the optimum, highlighting that the full optimization potential is utilized in a computationally efficient manner.

Computer-aided design and optimization of a multi-level fruit catching system for fresh-market fruit harvesting

Tree fruit harvesting is a labor-intensive operation. Multi-level fruit catching and retrieval (MFCR) systems have been proposed for the mass harvesting of soft fruits using trunk shaking. However, overcoming excessive fruit damage as fruits fall through the canopy is very challenging and requires optimization of several aspects of an MFCR’s design. In this work, we present a novel computer-aided design approach for optimizing design parameters of MFCR systems. A simplified index that utilizes geometry and simple mechanics is developed to quantify the interference between an MFCR’s catching booms and tree branches. Also, an index is introduced that utilizes geometry and simplified collision kinematics to represent accumulated damage on fruits falling through the canopy. These two indices are used in a case study to determine the optimal solution – and its sensitivity – for the number of layers of an MFCR system that maximizes marketable fruit collection over twenty digitized pear trees. In conjunction with more elaborate machine-tree-fruit interaction models, the proposed methodology can be used to optimize the design of fresh-fruit mass harvesters that utilize multi-level catching and retrieval systems.

Room-Temperature Creep Deformation of a Pressure-Resistant Cylindrical Structure Made of Dissimilar Titanium Alloys

The long-term safety of pressure-resistant structures used in deep-sea equipment may be threatened by creep deformation. The creep deformation behavior of a pressure-resistant structure made of different titanium alloys, Ti-6Al-4V and Ti-4Al-2V, at room temperature is investigated in this research. The kinetics and mechanisms underlying creep deformation in these materials is explained by proposing an improved constitutive model considering the effects of stress level, loading rate and environmental temperature field, offering crucial information for optimizing design parameters and guaranteeing the lifespan of the structure. Model parameters are determined for the two types of titanium alloys based on tensile creep testing results and validated through a simulation of the experimental process. In this study, a material creep model was used to predict the long-term deformation of large pressure-resistant titanium structures to ensure safe long-term operation. The safety factor used in the model is 1.5. Finite element analyses are conducted for the creep behavior of the pressure-resistant structure under real operating circumstances based on the creep constitutive model. The simulation predicts stress distribution, strain evolution, and deformation size over long periods of time by integrating complicated geometries, boundary conditions, and material characteristics. The present research can provide basic information for the local impacts of creep deformation on the inside of facilities, which helps refine design strategies to reduce possible damage risks.

Design of Infinite Impulse Response Filters Based on Multi-Objective Particle Swarm Optimization

The goal of this study is to explore the effectiveness of applying multi-objective particle swarm optimization (MOPSO) algorithms in the design of infinite impulse response (IIR) filters. Given the widespread application of IIR filters in digital signal processing, the precision of their design plays a significant role in the system’s performance. Traditional design methods often encounter the problem of local optima, which limits further enhancement of the filter’s performance. This research proposes a method based on multi-objective particle swarm optimization algorithms, aiming not just to find the local optima but to identify the optimal global design parameters for the filters. The design methodology section will provide a detailed introduction to the application of multi-objective particle swarm optimization algorithms in the IIR filter design process, including particle initialization, velocity and position updates, and the definition of objective functions. Through multiple experiments using Butterworth and Chebyshev Type I filters as prototypes, as well as examining the differences in the performance among these filters in low-pass, high-pass, and band-pass configurations, this study compares their efficiencies. The minimum mean square error (MMSE) of this study reached 1.83, the mean error (ME) reached 2.34, and the standard deviation (SD) reached 0.03, which is better than the references. In summary, this research demonstrates that multi-objective particle swarm optimization algorithms are an effective and practical approach in the design of IIR filters.

Topology optimization of smart structures to enhance the performances of vibration control and energy harvesting

Abstract With the growing interest in smart materials, the utilization of shunted piezoceramics for dynamic vibration control has gained significant attention due to their unique characteristics, such as the ability to absorb strain energy from vibrating systems and convert it into electrical energy. Designing and analyzing the behavior of structures in hybrid mitigation/harvesting conditions, considering both reliability and performance, pose challenges. This paper aims to achieve optimal design parameters for the structure by employing a multiobjective optimization approach that strikes a compromise between maximizing harvested power and minimizing structural damage. To evaluate the effectiveness of the design, topology optimization was conducted in three different cases to compare the results. By systematically exploring the design space, these cases provide insights into the influence of various parameters on the structural performance. In addition, to enhance computational efficiency, the structure was represented as a metamodel using neural networks. This approach enables rapid evaluation and prediction of the structure’s behavior, facilitating the optimization process. By integrating multiobjective optimization, topology optimization, and metamodeling techniques, this study aims to provide valuable insights into the optimal design of structures that simultaneously incorporate shunt circuitry for vibration control and energy harvesting, leading to improved performance and reliability.

Designing Stable Nanoparticles for Deforming Silicon Anodes in Lithium Ion Batteries

Silicon anodes in lithium-ion batteries are a promising next-generation battery technology offering ten times higher theoretical capacity than commercial graphite anodes. However, substantial volume changes (around 300%) associated with silicon anodes pose a significant challenge to the cycle life of these batteries. To understand the effect of the interaction between lithiation (diffusion) and mechanics (volume expansion, stress generation) on cycle life, a theoretical chemo-mechanical model of an isolated deforming silicon anode nanospherical particle is proposed in this study. Existing models, designed for low-capacity electrode materials, ignore the effect of deforming volume in the model formulation. Deforming volume, critical for high-capacity electrodes like silicon, is accounted for in the proposed model. Galvanostatic and potentiostatic operating conditions are considered. Simulations of the model help explain the importance of smaller particle sizes in observed longer cycle lives of silicon anodes. These enable mathematically accurate calibration of the partial molar volume of the material and determination of the developed mechanical stresses. Simulations of the proposed model help us optimize design parameters like particle size, particle thickness, and the charge rate/ applied voltage for elastic operation to ensure longer cycle lives of these batteries. Figure 1

Prediction of Optimal Design Parameters for Reinforced Soil Embankments with Wrapped Faces Using a GA–BP Neural Network

Under the same geological conditions, the thickness and length of the reinforced strip, the slope ratio of the reinforced embankment, the modulus of elasticity of the fill and the reinforced strip, and the friction angle at the interface between the reinforcement and the soil, are the main design parameters that have an important influence on the stress, deformation, and stability of the encompassing reinforced soil embankment. To quickly and accurately determine the optimal design parameters for reinforced soil embankments with wrapped faces, ensuring minimal cost, while maintaining structural safety, we propose a design parameter prediction model based on a GA–BP neural network. This model evaluates parameters within their specified ranges, using maximum lateral displacement, maximum vertical displacement, maximum stress in the XZ direction, the maximum shear strain increment, and the safety factor, as assessment criteria. The primary objective is to minimize the overall cost of the embankment. A comparison with five machine learning algorithms shows that the model has high prediction accuracy, and the optimal design parameter combinations obtained from the optimization search can significantly reduce the cost of the embankment, while controlling the displacement and stability of the embankment. Therefore, the GA–BP network is suitable for predicting the optimal design parameters of reinforced soil embankments with wrapped faces.

Electrokinetic Remediation of Cu- and Zn-Contaminated Soft Clay with Electrolytes Situated above Soil Surfaces.

Electrokinetic remediation (EKR) has shown great potential for the remediation of in situ contaminated soils. For heavy metal-contaminated soft clay with high moisture content and low permeability, an electrokinetic remediation method with electrolytes placed above the ground surface is used to avoid issues such as electrolyte leakage and secondary contamination that may arise from directly injecting electrolytes into the soil. In this context, using this novel experimental device, a set of citric acid (CA)-enhanced EKR tests were conducted to investigate the optimal design parameters for Cu- and Zn-contaminated soft clay. The average removal rates of heavy metals Cu and Zn in these tests were in the range of 27.9-85.5% and 63.9-83.5%, respectively. The results indicate that the Zn removal was efficient. This was determined by the migration intensity of the electro-osmotic flow, particularly the volume reduction of the anolyte. The main factors affecting the Cu removal efficiency in sequence were the effective electric potential of the contaminated soft clay and the electrolyte concentration. Designing experimental parameters based on these parameters will help remove Cu and Zn. Moreover, the shear strength of the contaminated soil was improved; however, the degree of improvement was limited. Low-concentration CA can effectively control the contact resistance between the anode and soil, the contact resistance between the cathode and soil, and the soil resistance by increasing the amount of electrolyte and the contact area between the electrolyte and soil.

Optical analysis and design of a novel solar beam down concentrator for indoor cooking

This investigation provides the design and optical analysis of an innovative solar beam-down configuration, which can be a promising passive solution for indoor solar-based cooking, offering an eco-friendly and sustainable approach. The system uses a beam-down parabolic dish concentrator to concentrate the solar radiation onto a ground-mounted receiver module, which has a secondary optical module consisting of a secondary reflector-light pipe system. The receiver module is a well-insulated tank consisting of a receiver in contact with a primary heat transfer fluid. The thermal energy stored in the receiver module is transported via a secondary heat transfer fluid to and from the cooktop via a tube-in-tube arrangement, which induces a thermosyphon effect. A multi-variable optical analysis through an efficient ray tracing methodology has been adopted to identify optimal design values of optical components such as parabolic dish concentrators, secondary reflectors, and light pipe-receiver assemblies. The optimal optical design parameters and their corresponding ray trace analysis results are elaborated. It was found that the designed beam-down parabolic dish concentrator system provides an ideal thermal energy of 10.3 kWh per day at an average DNI of 650 W/m2. Further, this investigation provides a design for a beam-down parabolic dish concentrating system that may be used for efficient and sustainable solar energy solutions.

Multi-Objective Optimization of the Ultrasonic Scalpel Rod and Tip with Improved Performance: Vibration Frequency, Amplitude, and Service Life

Ultrasonic scalpel design for minimally invasive surgical procedures is mainly focused on optimizing cutting performance. However, an important issue is the low fatigue life of traditional ultrasonic scalpels, which affects their long-term reliability and effectiveness and creates hidden dangers for surgery. In this study, a multi-objective optimal design for the cutting performance and fatigue life of ultrasonic scalpels was proposed using finite element analysis and fatigue simulation. The optimal design parameters of resonance frequency and amplitude were determined. By setting the transition fillet and keeping the gain structure away from the node position to enable the scalpel to have a high service life with excellent cutting performance. The frequency modulation method of setting the vibration node bosses at the node position and setting the vibration antinode grooves at the antinode position was compared. Then, the mechanism of the influence of various design elements, such as tip, shank, node position, and antinode position, on the resonance frequency, amplitude, and fatigue life of the ultrasonic scalpel was analyzed, and the optimal design principles of the ultrasonic scalpel were obtained. The proposed ultrasonic scalpel design was confirmed by simulations, impedance measurements, and liver tissue cutting experiments, demonstrating its feasibility and enhanced performance. This research introduces innovative design strategies to improve the fatigue life and performance of ultrasonic scalpels to address an important issue in minimally invasive surgery.

Mechanical Structure Design of Pressure Sensors with Temperature Self-compensation for Invasive Blood Pressure Monitoring

Abstract Invasive blood pressure (IBP) is a fundamental part of basic cardiovascular monitoring. Conventional piezoresistive pressure sensors are limited in usage due to the high cost associated with equipment and intricate fabrication processes. Meanwhile, low-cost strain gauge pressure sensors have poor performance in the gauge factor (GF) and temperature insensitivity. Here, we report a mechanical structure design for diaphragm pressure sensors (DPSs) by introducing a compensation grid to overcome the aforementioned challenges. A simplified model is established to analyze the mechanical deformation and obtain the optimal design parameters of the DPS. By rationally arranging the placement of sensitive grids to eliminate the discrepancy of relative resistance changes within four arms of the Wheatstone full-bridge circuit, the appropriate GF and high temperature insensitivity are simultaneously achieved. The blood pressure sensor with the DPS is then fabricated and characterized experimentally, which demonstrates an appropriate GF (ΔU/U0)/P = 3.56 × 10−5 kPa−1 and low temperature coefficient of voltage (ΔU/U0)/ΔT = 3.4 × 10−7 °C−1. The developed mechanical structure design offers valuable insights for other resistive pressure sensors to improve the GF and temperature insensitivity.

锤片式粉碎机V型锤片设计及试验优化

Low productivity and high electricity consumption are considered problems of the hammer mill, which is widely used in current feed production. In this paper, a folded V-shaped hammer was designed to improve the performance of the hammer mill. To determine the optimal design parameters of the new hammer, the single-factor test and orthogonal tests were carried out with the inclination angle of hammer, the angle of hammer head, and the distance of hammer head as the influencing factors, and the productivity and output per kWh as evaluation indexes. The order of the influence on the productivity and output per kWh were the inclination angle of hammer>the angle of hammer head> the distance of hammer head. The parameters were optimized based on the orthogonal tests with the following results: the angle of hammer head was 160°, inclination angle of hammer was 110°, and the inclination distance of hammer head was 24 mm. The static analysis and modal analysis were carried out on the optimized hammer by using ANSYS software. The results showed that the new hammer satisfies the strength and stiffness requirements during working, does not resonate, and has good dynamic characteristics. The new hammer can effectively improve the performance of the hammer mill, and the research results can provide theoretical basis for the optimization design of the hammer mill.

Computational Fluid Dynamics-Based Optimisation of High-Speed and High-Performance Bearingless Cross-Flow Fan Designs

To enhance the fluid dynamic performance of bearingless cross-flow fans (CFFs), this paper presents a CFD-based optimisation of both rotor and static casing wall modifications. High-performance CFFs are essential in industrial applications such as highly specialised laser modules in the semiconductor industry. The goal for the investigated rotor modifications is to enhance the CFF’s mechanical stiffness by integrating reinforcing shafts, which is expected to increase the limiting bending resonance frequency, thereby permitting higher rotational speeds. Additionally, the effects of these rotor modifications on the fluid dynamic performance are evaluated. For the casing wall modifications, the goal is to optimise design parameters to reduce losses. Optimised bearingless CFFs benefit semiconductor manufacturing by improving the gas circulation system within the laser module. Higher CFF performance is a key enabler for enhancing laser performance, increasing the scanning speed of lithography machines, and ultimately improving chip throughput. Several numerical simulations are conducted and validated using various commissioned prototypes, each measuring 600mm in length and 60mm in outer diameter. The results reveal that integrating a central shaft increases the rotational speed by up to 42%, from 5000rpm to 7100rpm, due to enhanced CFF stiffness. However, the loss in fluid flow amounts to 61% and outweighs the gain in rotational speed. Optimising the casing walls results in a 22% increase in maximum fluid flow reaching 1800m3/h at 5000rpm. It is demonstrated that the performance of bearingless CFFs can be enhanced by modifying the geometry of the casing walls, without requiring changes to the CFF rotor or bearingless motors.