Effects Of Parameter Variations Research Articles

Evaluating energy harvesting UAV-NOMA network with random user pairing in the finite blocklength regime

This study proposes an integrated system that combines energy harvesting (EH) enabled unmanned aerial vehicles (UAVs) with non-orthogonal multiple access (NOMA) to enhance communication system performance within a cellular network. Addressing the limitations of existing analyses that often assume an infinite blocklength scenario, we explore EH-enabled UAV-NOMA systems within a cellular framework under a finite blocklength (FBL) scenario. The study investigates the complex interactions and advantages resulting from the integration of EH, NOMA, and UAV technologies, aiming to assess whether EH can sustain communication within this framework. The network model considers base stations (BSs), UAVs, and terrestrial devices distributed with independent Poisson point processes (PPPs) over a large area. In this network, BSs employ NOMA to serve cell center devices directly, while cell edge devices, which are nor in direct contact with BS, are served via simultaneous wireless information and power transfer (SWIPT) enabled UAVs. The study derives metrics including joint harvesting and decoding probability for a randomly selected UAV, coverage probability (CP) for cell devices, and end-to-end block error rate (BLER) probabilities for typical device pairs. The findings demonstrate that the proposed scheme effectively supplies all the necessary transmit power for communication purposes through EH, achieving reasonable reliability. Additionally, the study highlights the importance of considering a combination of blocklengths from different phases to achieve optimal performance, rather than solely relying on an increment in blocklength. Finally, the effects of parameter variations on network performance are examined.

Sustainable nitrogen fixation by bubble discharge plasma: Performance optimization and mechanism

Sustainable nitrogen fixation driven by renewable energy sources under mild conditions has been widely sought to replace the industrial Haber-Bosch process. The fixation of nitrogen in the form of NOx− and NH4+ into aqueous solutions using electricity-driven gas–liquid discharge plasma is considered a promising prescription. In this paper, a scalable bubble discharge excited by nanosecond pulse power is employed for nitrogen fixation in the liquid phase. The nitrogen fixation performance and the mechanisms are analyzed by varying the power supply parameters, working gas flow rate and composition. The results show that an increase in voltage and frequency can result in an enhanced NO3− yield. Increases in the gas flow rate can result in inadequate activation of the working gas, which together with more inefficient mass transfer efficiencies can reduce the yield. The addition of O2 effectively elevates NO3− production while simultaneously inhibiting NH4+ production. The addition of H2O vapor increases the production of OH and H, thereby promoting the generation of reactive nitrogen and enhancing the yield of nitrogen fixation. However, the excessive addition of O2 and H2O vapor results in negative effect on the yield of nitrogen fixation, due to the significant weakening of the discharge intensity. The optimal nitrogen fixation yield was up to 16.5 μmol/min, while the optimal energy consumption was approximately 21.3 MJ/mol in this study. Finally, the mechanism related to nitrogen fixation is discussed through the optical emission spectral (OES) information in conjunction with the simulation of energy loss paths in the plasma by BOLSIG + . The work advances knowledge of the effect of parameter variations on nitrogen fixation by gas–liquid discharge for higher yield and energy production.

A study on production of hydrogen using Al scrap feedstock.

A sustainable future, concerning the energy transformation of a country, heavily relies on the availability of energy resources, particularly renewables such as solar, wind, hydropower, and clean hydrogen. Among these, hydrogen is the most promising energy source due to its high calorific value, ranging between 120 and 140MJ/kg. It has the potential to lead the market in various industries such as power generation, steel, chemical, petrochemical, and automotive. Significant research has been going on in hydrogen production technologies to reduce costs and improve competitiveness with fossil fuels. One such potential approach includes the use of metal-water reactions, which offer unique opportunities for producing clean hydrogen and other valuable byproducts. However, the quantity of hydrogen produced varies depending on the metal feedstock, type of electrolyte, and the activator or catalyst, used in combination with water. This latest work discusses recent progress on hydrogen production and the effects of variations in different parameters on the process, with a focus on aluminum (Al)-water reactions. Investigations have been conducted and reported on the effect of various activators with different concentrations, the quantity of aluminum scrap feedstock, and the volume of the electrolyte on the kinetics of the metal-water reactions and hydrogen production. Sodium hydroxide (NaOH) was observed to be more effective than potassium hydroxide (KOH) in promoting metal-water reactions. These activator-assisted metal-water reactions help produce clean hydrogen, along with other value-added products such as hydroxides. This work clearly sheds light on the potential utilization of industrial aluminum scrap as feedstock for producing clean hydrogen.

Influence of process variations on clinch joint characteristics considering the effect of the nominal tool design

Focusing on upcoming challenges in lightweight design, such as increasing emission targets or novel multimaterial connections, versatile applicable and environmentally friendly production technologies are crucial. In this context, mechanical joining technology clinching offers a fast and energy-efficient procedure for assembling sheet metals, being a proper alternative to established joining methods, such as spot welding. However, the design of clinch points is a challenge, which is partly supported by numerical or data-based approaches for optimal tool dimensions assuring proper joint characteristics. While this is usually done for an ideal environment, real joining processes are characterized by multiple inevitably varying parameters, e.g. of the material, which have a significant impact on the quality of clinch points. Therefore, this contribution addresses the current gap by analyzing the effect of parameter variations or uncertainties on the resulting joint characteristics and studying the impact of the nominal tool design. Thus, an efficient meta-model-based variation simulation procedure is proposed and used for analyzing the effect of different tool design configurations and variation scenarios. Based on the results, it was found that varying process parameters have a strong impact on the resulting joint characteristics, whereby the effect significantly depends on the nominal tool design. This reveals the potential for a robust tool design and implies that the nominal tool design and the tolerancing of parameters should be done simultaneously for a reliable virtual joining point design without extensive iterations and physical tests.

Understanding the Manufacturing Process of Lipid Nanoparticles for mRNA Delivery Using Machine Learning.

Lipid nanoparticles (LNPs), used for mRNA vaccines against severe acute respiratory syndrome coronavirus 2, protect mRNA and deliver it into cells, making them an essential delivery technology for RNA medicine. The LNPs manufacturing process consists of two steps, the upstream process of preparing LNPs and the downstream process of removing ethyl alcohol (EtOH) and exchanging buffers. Generally, a microfluidic device is used in the upstream process, and a dialysis membrane is used in the downstream process. However, there are many parameters in the upstream and downstream processes, and it is difficult to determine the effects of variations in the manufacturing parameters on the quality of the LNPs and establish a manufacturing process to obtain high-quality LNPs. This study focused on manufacturing mRNA-LNPs using a microfluidic device. Extreme gradient boosting (XGBoost), which is a machine learning technique, identified EtOH concentration (flow rate ratio), buffer pH, and total flow rate as the process parameters that significantly affected the particle size and encapsulation efficiency. Based on these results, we derived the manufacturing conditions for different particle sizes (approximately 80 and 200 nm) of LNPs using Bayesian optimization. In addition, the particle size of the LNPs significantly affected the protein expression level of mRNA in cells. The findings of this study are expected to provide useful information that will enable the rapid and efficient development of mRNA-LNPs manufacturing processes using microfluidic devices.

TRENDS IN THE DEVELOPMENT OF REACTIVE POWER COMPENSATION SYSTEMS

This paper surveys current trends and developments in reactive power compensation systems, elucidating their significance in enhancing system capacity and flexibility. By analyzing the capacity factor enhancement enabled by reactive power compensation, the study underscores its role in optimizing electricity delivery, thus conserving energy resources and facilitating the integration of renewable energy sources. It explores the key models and concepts driving advancements in reactive power compensation within power grids. As modern electrical systems grow in complexity, ongoing research into improving compensation methods becomes imperative to ensure the reliability and efficiency of industrial power grids. Future endeavors will involve developing a model utilizing real-world enterprise data to investigate the effects of technological variations in filter parameters on the performance of complex reactive power compensation schemes, encompassing both filters and capacitor banks. Keywords: reactive power, compensation systems, filter-compensating circuit, industrial power grid, electric power. Context. The paper considers the current trends used in the field of reactive power compensation, and the main directions of development of modern methods of reactive power compensation. Objective. The purpose of the work is to overview of current trends in the development of reactive power compensation systems, as well as an overview of possible ways of their effective application in various industrial networks. Methods. The paper presents a key aspect of reactive power compensation is its ability to increase system capacity and flexibility. By improving the capacity factor, utilities can deliver electricity more efficiently, reducing the need for excess capacity and thus conserving energy resources. In addition, this process plays an important role in supporting the integration of renewable energy sources such as wind and solar power, which often introduce volatility into electricity generation schemes. Results. The paper presents the main models and concepts in the field of reactive power compensation in power grids. Conclusions. Given the growing complexity of modern electrical systems, it is important to continue research into improving methods and means of reactive power compensation to ensure the reliability and efficiency of industrial power grids. In further research, it is planned to develop a model using a real enterprise as an example and investigate the impact of technological deviations of filter parameters on the steady-state and transient performance of complex reactive power compensation schemes, including not only filters but also capacitor banks.

Waste consumption of bio-degradable products through a secondary supply chain

Food and agriculture organization estimates that 33% of the food is wasted in the world. It is essential to optimize the food supply chains to mitigate the economic and environmental impacts of this large amount of food waste. The targets of food waste reduction can be achieved by increasing lifetime and consuming the inevitably produced food waste for producing secondary products. This research proposes a primary and secondary supply chain model, where effective preservation policy increases lifetime of food items, and the yet produced food waste is converted into secondary products. This way, the waste from the system is removed and it is converted into a sustainable zero-waste system. A nonlinear mathematical model is proposed to set the objective function of the research, which best determines the production plan, inventory schedule and investment in preservation technology while maximizing profit. The model is solved using the Kuhn-Tucker method, and the model optimality is obtained by proposing an algorithm. Numerical analysis is carried out to validate the presented model, and sensitivity analysis is performed to demonstrate the effects of variation in cost parameters on the profit. The outcome of the analysis shows that the proposed secondary supply chain increases profit by 35% and the preservation policy increases the profit by 17.9%. Besides, the proposed policies minimize and remove the food waste from system. Managerial implications are provided for the practitioners to apply the proposed model in food supply chains.

Nonlinear combination resonance analysis of parametric-forced excitation for an axially moving piezoelectric rectangular thin plate in thermal- electromechanical coupling field

In this paper, the combination resonance of parametric-forced excitation characteristics for an axially moving rectangular piezoelectric plate under a thermal-electromechanical field is studied. Based on Kirchhoff-Love plate theory and Von Karman theory, the transverse vibration governing equations are derived from Hamilton's principle. The equations are discretized to ordinary differential equations by the Galerkin method. Then, the multiple scales method is applied to solve the system combination resonance equation, two different resonance states and corresponding amplitude-frequency response equations are obtained by eliminating the secular term, respectively. Additionally, the stability of the steady-state responses is analyzed by Lyapunov stability. Based on the numerical analysis, the influence of axial velocity, external voltage, central temperature difference, structural damping, and other parameters on nonlinear combination resonance response are investigated. The effect of parameter variation on period-doubling bifurcation and the chaotic motion of the system are also discussed by the system global bifurcation diagram.

Optimization of Welding Parameters for Minimizing Defects and Porosity in Electric Arc Welding of Mild Steel Grade Fe 500 Using of Taguchi Method

Abstract: Electric arc welding is a widely used technique in industrial applications for joining metals, including mild steel grade Fe 500. However, the process is susceptible to defects such as porosity, which can compromise the integrity and quality of welds. In this study, we investigate the optimization of welding parameters to minimize defects and porosity in electric arc welding of mild steel grade Fe 500, utilizing the Taguchi method. The Taguchi method, known for its efficiency in optimization studies, is employed to systematically identify the most influential welding parameters and their optimal levels. Through a series of experiments based on the Taguchi orthogonal array design, we vary parameters such as current amperage, voltage, and electrode size to explore their effects on weld quality. The experimental results reveal significant insights into the relationship between welding parameters and defect formation. By analyzing signal-to-noise ratios and ultimate tensile strength, we quantify the effects of parameter variations on weld quality. The Taguchi analysis enables us to identify the optimal combination of welding parameters that minimizes defects and porosity while maximizing weld strength.

Design of power efficient and reliable hybrid inverter approach based 11 T SRAM design using GNRFET technology

Designing a power efficient and high-speed static random-access memory (SRAM) cell with improved noise stability using traditional complementary metal oxide semiconductor (CMOS) devices is an arduous task. Owing to balanced electrical properties of graphene nanoribbon field-effect transistor (GNRFET), its capability to realize high performance SRAM cells need a keen exploration. This article proposes an 11-transistor GNRFET SRAM cell which deploys hybrid inverter scheme. The hybrid inverter scheme encompasses two distinct inverters, based on stacked transistors and Schmitt trigger (ST) techniques. The simulations conducted using 16 nm GNRFET model in HSPICE simulator show that proposed SRAM cell has write power, hold power, read power, write static noise margin, hold static noise margin, read static noise margin, write delay and read delay of 0.445 nW, 0.978 µW, 1.8 nW, 225 mV, 222.8 mV, 225.1 mV, 24 pS and 49.6 pS, respectively. The results obtained for proposed SRAM cell have been found to be encouraging in contrast to previously reported SRAM cells implemented using 16 nm GNRFET model. Besides this, the effect of variation in various parameters of GNRFET on performance of proposed SRAM cell has been investigated in this article. The outstanding performance results of SRAM makes its suitable for developing high performance memories devices for biomedical digital gadgets, internet of things (IoT), artificial intelligence (AI) and smart agricultural applications.

Sensitivity analysis of paediatric knee kinematics to the graft surgical parameters during anterior cruciate ligament reconstruction: A sequentially linked neuromusculoskeletal-finite element analysis

Background and objectiveIncidence of paediatric anterior cruciate ligament (ACL) rupture has increased substantially over recent decades. Following ACL rupture, ACL reconstruction (ACLR) surgery is typically performed to restore passive knee stability. This surgery involves replacing the failed ACL with a graft, however, surgeons must select from range of surgical parameters (e.g., type, size, insertion, and pre-tension) with no robust evidence guiding these decisions. This study presents a systemmatic computational approach to study effects of surgical parameter variation on kinematics of paediatric knees. MethodsThis study used sequentially-linked neuromusculoskeletal (NMSK) finite element (FE) models of three paediatric knees to estimate the: (i) sensitivity of post-operative knee kinematics to four surgical parameters (type, size, insertion, and pre-tension) through multi-input multi-output sensitivity analysis; (ii) influence of motion and loading conditions throughout stance phase of walking gait on sensitivity indices; and (iii) influence of subject-specific anatomy (i.e., knee size) on sensitivivty indices. A previously validated FE model of the intact knee for each subject served as a reference against which ACLR knee kinematics were compared. ResultsSensitivity analyses revealed significant influences of surgical parameters on ACLR knee kinematics, albeit without discernible trend favouring any one parameter. Graft size and pre-tension were primary drivers of variation in knee translations and rotations, however, their effects fluctuated across stance indicating motion and loading conditions affect system sensitivity to surgical parameters. Importantly, the sensitivity of knee kinematics to surgical parameter varied across subjects, indicating geometry (i.e., knee size) influenced system sensitivity. Notably, alterations in graft parameters yielded substantial effects on kinematics (normalized root-mean-square-error > 10 %) compared to intact knee models, indicating surgical parameters vary post-operative knee kinematics. ConclusionsOverall, this initial study highlights the importance of surgical parameter selection on post-operative kinematics in the paediatric ACLR knee, and provides evidence of the need for personalized surgical planning to ultimately enhance patient outcomes.

Pengaruh Variasi Parameter Filter Terhadap Harmonisa Pada Operasi PLTS Terintegrasi Sistem Tenaga Listrik

This paper provides a comprehensive harmonic picture of Photovoltaic operations integrated with the Electric Power System (Photovoltaic on-grid). Harmonics in Photovoltaic on-grid are generated from the inverter. One way to reduce harmonics is by installing a filter. Apart from reducing harmonics, filters can improve the system power factor value. This research examines the effect of variations in Photovoltaic on-grid filter parameters on inverter power capacity using Simulink/Matlab simulation. The FFT (Fast Fourier Transform) method is used to determine the harmonic order and THD of the current and voltage of the system on the side before and after the filter. The simulation results show changes in filter parameter variations for Qc (Var) values ​​giving THDi and THDv values ​​before and after filter installation using the FFT approach.

Role of ultrasensitivity in biomolecular circuitry for achieving homeostasis

Living systems have developed control mechanisms for achieving homeostasis. Here, we propose a plausible biological feedback architecture that exploits ultrasensitivity and shows adaptive responses without requiring error detection mechanism (i.e., by measuring an external reference signal and deviation from this). While standard engineering control systems are usually based on error measurements, this is not the case for biological systems. We find that a two-state negative feedback control system, without explicit error measurements, is able to track a reference signal that is implicitly determined by the tunable threshold and slope characterizing the sigmoidal ultrasensitive relationship implemented by the control system. We design different ultrasensitive control functions (ultrasensitive up- or down-regulation, or both) and, by performing sensitivity analysis, show that increasing the sensitivity level of the control allows achieving robust adaptive responses to the effects of parameter variations and step disturbances. Finally, we show that the devised control system architecture without error detection is implemented within the yeast osmoregulatory response network and allows achieving adaptive responses to osmotic stress, by exploiting the ubiquitous ultrasensitive features of the involved biomolecular circuitry.

Impact of process parameters variation on noise and linearity performances of GC-JL-GAA MOSFET

ABSTRACT The short channel effects are improved in GC-JL-GAA MOSFETs by raising the channel’s graded doping level. The noise and linearity of the device plays a crucial role in RFIC circuit applications. Therefore, this article presents a comprehensive analysis of noise and linearity parameters of graded channel junction-less-gate-all-around (GC-JL-GAA) MOSFET with process parameter variations through 3D Silvaco ATLAS device simulator. This paper investigates the noise parameters such as Noise Conductance (NC), minimum noise figure (NFmin), and optimum source impedance (Z0). To comprehend the performance of GC-JL-GAA MOSFETs, the noise characteristics with changes in channel thickness, channel length, high-k gate oxide, and oxide thickness are examined and compared. Moreover, the effect of process parameter variation on linearity FOMs such as gm2, gm3, IIP3, IMD3, VIP2, VIP3, and 1-db compression point are also examined. The GC-JL-GAA device, however, provides improved noise and linearity performance parameters for lower channel length of the device as per the performance evaluation. Furthermore, it has been observed that high-k gate oxide deteriorates noise and linearity performance of GC-JL-GAA MOSFETs. Based on the results of the performance evaluation, it has been revealed that the GC-JL-GAA devices are suitable to be employed in Radio Frequency (RF) applications.

Exploration of optimal control based surrogate modeling as a basis for fuel efficient 4D aircraft routing on graphs

AbstractFuel efficient coordination of aircraft operations in the Terminal Maneuvering Area of large airports can contribute to the reduction of the environmental impact of air traffic. To exploit the full potential of the air traffic system, coordinated routing in the Terminal Maneuvering Area, runway assignment and scheduling need to be optimized considering detailed models of the aircraft dynamics and performance. Due to the inhomogeneous nature and level of detail of these combined discrete and continuous decision problems, the optimization of the overall operations poses significant challenges. As part of an integrated approach to the solution of this hybrid problem, this work explores the generation of surrogate models for the fuel consumption of individual aircraft using optimal control methods to exploit the physical capability of the aircraft within an operationally permissible envelope. The surrogate models approximate the predicted fuel consumption of a given point-mass aircraft model on short generic trajectory segments. The trade-off between flight duration and fuel consumption on such segments is analyzed, focusing on the influences of initial aircraft mass, altitude, distance, mean climb angle, along-track wind velocity and linear wind shear. An extensive description of the optimal control-based data generation and surrogate modeling methodology is followed by a discussion of the effects of parameter variation. Based on an illustrative case study, the applicability of the approach is critically analyzed.

Design and compressive behaviors of the gradient re-entrant origami honeycomb metamaterials

In recent years, origami honeycomb metamaterials have garnered extensive attention from researchers. Re-entrant origami honeycomb metamaterials exhibit excellent mechanical performances by virtue of lightweight, high-energy-absorbing characteristics and diverse configurations. In this study, the gradient re-entrant origami honeycomb metamaterials are designed by changing significant geometric parameters. To investigate the effects of geometric parameters variations on compressive behaviors, the theoretical analysis model of the re-entrant origami honeycomb is built to predict the compression stress under low-velocity and high-velocity impact. Subsequently, the energy absorption of the uniform re-entrant origami honeycomb (UROH), the gradient-thickness re-entrant origami honeycombs (GTROHs) and the gradient-angle re-entrant origami honeycomb (GAROHs)are investigated under different compression velocities. The impact resistances of UROH, GTROHs and GAROHs are discussed systematically. By adjusting the gradient distribution of thickness, the deformation modes and Poisson’s ratio curves of the structure could be altered. Furthermore, under the high-velocity impact, the specific energy absorption (SEA) of the unidirectionally negative GTROH is increased by 36% than that of UROH at the strain of 0.29. The SEA of the unidirectionally positive GTROH is higher by 14.4% than that of UROH at the strain of 0.8. In addition, the unidirectionally positive GTROH exhibits better impact resistance performance than UROH by comparing the peak stress and SEA value under different compression velocities. This study is expected to provide the new route for designing advanced origami-inspired honeycomb structures and improving buffer protection devices.

Quantum analysis of a Mach–Zehnder interferometer with propagating a single photon Gaussian wave packet

In this paper, a Mach–Zehnder interferometer is analyzed with a single photon Gaussian wave packet at one of its input ports and vacuum state at the other input port. Various noises arising in the Mach–Zehnder interferometer such as photon flux noise and quadrature noise are mathematically analyzed. The effect of variation in device parameters on the power spectral density at the output ports of the Mach–Zehnder interferometer is studied. It is observed that the power spectral density of photon flux noise autocorrelation at the output ports of a Mach–Zehnder interferometer is a function of phase shift, whereas the power spectral density of quadrature noise autocorrelation at the output ports of a Mach–Zehnder interferometer is a function of frequency of a single photon wave packet and the phase shift. The analysis carried out in this paper will be helpful in understanding the quantum fluctuations in the design of quantum logic devices and circuits where the Mach–Zehnder interferometer is a core building block.

Normalized Error-Based PI Controller and Its Application to the DC–DC Buck Converter

In this article, the structure of the normalized error-based proportional-integral (PI) controller is presented and its application to the DC–DC buck converter is discussed. The main motivation is to overcome the drawbacks of saturation and the limited range of controller gains offered by the traditional PI controller. Initially, the theoretical structure and advantages of an improved PI controller are shown. Next, the problem of regulation of the step-down DC–DC converter is addressed using the proposed controller. The objective is to keep the load voltage constant even when the converter parameters vary. The averaged state-space model of the converter is presented and a detailed stability analysis based on the Lypunov indirect method is carried out. The results show an improved range of controller parameters when the proposed controller is employed. Finally, some simulation results are shown to illustrate the effect of controller parameter variations on the output response. These results also verify the ability of the proposed controller to handle the changes in the load, input voltage, and reference voltage of the converter. Moreover, a comparative simulation study validates the superior transient response of the proposed normalized error-based PI controller over the traditional PI controller.

Approximate contact force model for viscoelastic materials based on generalized Maxwell model

This paper proposes a novel approximate model for estimating the normal contact force between a rigid sphere and a viscoelastic half-space based on the generalized Maxwell model. The relaxation function derived from the generalized Maxwell model is applied to the solution to the elastic contact problem based on the elastic–viscoelastic correspondence to obtain an integral expression of pressure for viscoelastic contact. Using the approximate method on the basis of Taylor series, the integral expression is translated into an explicit function of displacement, velocity, time and material properties. A normal contact force model is established by integrating the pressure over contact area. A relaxation test of Nafion® XL is conducted to capture the viscoelastic parameters, and these parameters are employed to simulate the contact behaviors using the finite element method (FEM) to determine the scale factor in the contact force model. In order to verify the validity of the approximate model, the outcomes obtained from the model are compared with those generated by the FEM. A parametric study is conducted to analyze the effects of variations in parameters on normal contact behaviors. The results indicate that the established model is able to predict the contact responses of the viscoelastic materials with complex mechanical characteristics.

Hydrodynamic Performance of Cycloidal Propellers with Four-Bar and Mixed Four-bar/Five-bar Mechanisms: A Numerical Study

Cycloidal propellers constitute a specialized category of underwater propulsion devices, widely employed in vehicles requiring exceptional maneuverability. The parameters of the blade-driving mechanism directly impact the propeller performance. Hence, the effect of variations in the geometric parameters of the blade-driving mechanism on the hydrodynamic performance of cycloidal propellers must be investigated. In this study, a specific set of four-bar and mixed four-bar/five-bar mechanisms are taken as examples, and the effect of linkage-length variations on the hydrodynamic performance of cycloidal propellers was analyzed using numerical simulation methods. First, we established a physical model of the cycloidal propeller, and then derived the relationship between blade-rotation and revolution angles. Subsequently, by solving the Navier–Stokes equations and employing computational fluid dynamics simulations based on viscosity, an analysis is conducted to reveal the trends in the impact of different linkage-length combinations on the hydrodynamic performance of the cycloidal propeller. Finally, the outcomes of the numerical simulations are interpreted using the wing element theory. In similar blade-driving mechanisms, the effects of varying linkage lengths on propeller hydrodynamic performance are determined through alterations in the blade rotation angle range and equilibrium position. An increase in the range of the blade-rotation angle significantly enhances the hydrodynamic performance of the cycloidal propeller. This research employs a more realistic auto-propulsion mode for numerical simulations, establishing a mapping relationship between the blade-driving mechanism and hydrodynamic performance of the cycloidal propeller, while analyzing the underlying influencing mechanisms. Furthermore, crucial numerical simulations and theoretical foundations are employed for designing the four-bar and mixed four-bar/five-bar mechanism cycloidal propellers. The findings of this study could also be used in similar cycloidal propellers with multilinkage mechanism.