Motion Parameters Research Articles

Significance of magnetic field and Darcy–Forchheimer law on dynamics of non-Newtonian hybrid nanofluid flow over a spinning disc with Arrhenius activation energy and shape factor

Purpose The purpose of the study is to explore the three-dimensional heat and mass transport dynamics of the magneto-hydrodynamic non-Newtonian (Casson fluid) hybrid nanofluid flow comprised of − as nanoparticles suspended in base liquid water as it passes through a flexible spinning disc. The influence of a magnetic field, rotation parameter, porosity, Darcy−Forchheimer, Arrhenius’s activation energy, chemical reaction, Schmidt number and nanoparticle shape effects are substantial physical features of the investigation. Furthermore, the influence of hybrid nanofluid on Brownian motion and thermophoresis features has been represented using the Buongiorno model. The novelty of the work is intended to contribute to a better understanding of Casson non-Newtonian fluid boundary layer flow. Design/methodology/approach The governing mathematical equations that explain the flow and heat and mass transport phenomena for fluid domains include the Navier−Stokes equation, the thermal energy equation and the solutal concentration equations. The governing equations are expressed as partial differential equations, which are then converted into a suitable set of non-linear ordinary differential equations by using the necessary similarity variables. The ordinary differential equations are computed by combining the shooting operation with the three-stage Lobatto BVP4c technique. Findings Graphs and tables are used in the process of analysing the characteristics of velocity distributions, temperature profiles and solutal curves at varying values of the parameters, along with friction drag, heat transfer rate and Sherwood number. It has been revealed that the radial and axial velocities decrease when the Casson parameter value increases and that the rate of heat transmission is higher in hybrid nanofluids with nanoparticles in the shape of a blade. The increase in Brownian motion and thermophoresis parameters causes a rise in the temperature profile. Also, an increase in the activation energy parameter improves the solutal curve. The use of nanoparticles was shown to improve extrusion properties, the rotary heat process and biofuel generation. Originality/value All results are presented graphically and all physical quantities are computed and tabulated. The current results are compared to previous investigations and found to agree significantly with them.

Radiative MHD Casson Non-Newtonian Nanofluid Slip Flow Induced by Stretching Cylinder: A Numerical Approach

Objectives: This article investigates the continuous magnetohydrodynamics slip flow across an extending cylinder, including heat radiation and free stream velocity. The proposed model incorporated the Brownian motion parameter and thermophoresis. Methods: Applying the similarity transformation to a system of partial differential equations yields an ordinary differential equation of first order. Since, there is the nonlinear nature of the modified equations, these ordinary differential equations are addressed by employing mathematical modeling. The shooting process has been embraced to solve changed equations by implementing the following Runge-Kutta Fehlberg method. Findings: Graphical representations are used to show how several fluid factors, such as Casson fluid parameter, free stream velocity, thermophoresis, magnetic parameter, Brownian motion parameter, heat generation parameter, Lewis number, radiation parameter, chemical reaction and curvature parameter affect concentration, temperature and velocity. Results for physical quantity of interest are also computed and reported in tabular form. The study's main findings showed that nanoparticle temperatures rise with greater Brownian motion parameter values, whereas nanoparticle concentration falls with higher heat radiation parameter values. Additionally, it is found that with rise in Lewis number rises as 0.1, 0.4, 0.7, 1.0, 1.3, heat transfer rate falls down by 21.19%. The outcomes are calculated using the MATLAB software. Novelty: This technique's validity is defended by comparing its most recent findings to previously published results and successfully meeting the convergence criteria. The present work emphasizes the analysis of free stream flow in the cylindrical area, specifically in the existence of partial slip and heat radiation, under convective circumstances. This study has significant implications for electronic devices such as processors as well as many businesses and the field of biological and medical sciences. The present investigation aims to support production businesses in achieving the desired level of quality of their products by effectively managing the transport phenomena. Keywords: Stretching cylinder, Heat radiation, Brownian motion, Thermophoresis, Non-Newtonian nanofluid, Shooting technique

Dynamic reliability assessment for high CFRDs incorporating ground motion and material parameter variability via GPDEM

The randomness of earthquake and material parameters significantly impacts the seismic response and dynamic reliability of geotechnical engineering structures. In this study, a dynamic reliability analysis method for high concrete face rockfill dams (CFRDs) under the influence of random factors is proposed by combining random sample generation methods with the generalized probability density evolution method (GPDEM). Firstly, the spectral representation-random function method is employed to achieve dimensionality reduction expression for intensity-frequency non-stationary ground motion. Sensitivity analysis is then used to identify the random variables of the rockfill constitutive model, and the improved generalized F-discrepancy (GF-discrepancy) method is utilized to generate random material parameters. Then, the random samples of earthquake and material parameter are introduced into the finite element calculation of CFRD, conducting a series of dynamic finite element calculations. Finally, GPDEM is used to derive probability information and dynamic reliability from the deterministic time history responses. The results indicate that random factors contribute to the variability of seismic response and dynamic reliability. Stochastic ground motion significantly affects extreme values, while variability in material parameters has a more pronounced influence on the overall process of seismic response. These findings provide valuable references for the seismic design of CFRDs.

Research on the multitarget 3D trajectory tracking method of Thalassodes immissaria in the thermal infrared region based on YOLOX-GMM and SORT-Pest.

Studying the behavioral responses and movement trajectories of insects under different stimuli is crucial for developing more effective biological control measures. Therefore, accurately obtaining the movement trajectories and behavioral parameters of insects in three-dimensional space is essential. This study used the litchi pest Thalassodes immissaria as the research object. A special binocular vision observation system was designed for nighttime movement. A thermal infrared camera was used for video recording of T. immissaria in a lightless environment. Moreover, a multi-object tracking method based on the YOLOX-GMM and SORT-Pest algorithms was proposed for tracking T. immissaria in thermal infrared images. By obtaining the central coordinates of the two T. immissaria in the video, target matching and 3D trajectory reconstruction in the parallel binocular system were achieved. Error analysis of the T. immissaria detection and tracking model, as well as the 3D reconstruction model, showed that the average accuracy of T. immissaria detection reached 89.6%, tracking accuracy was 96.9%, and the average error of the reconstructed 3D spatial coordinates was 15 mm. These results indicate that the method can accurately obtain the 3D trajectory and motion parameters of T. immissaria. Such data can greatly contribute to researchers' comprehensive understanding of insect behavioral patterns and habits, providing important support for more targeted control strategies.

PID Controller Based on Improved DDPG for Trajectory Tracking Control of USV

When navigating dynamic ocean environments characterized by significant wave and wind disturbances, USVs encounter time-varying external interferences and underactuated limitations. This results in reduced navigational stability and increased difficulty in trajectory tracking. Controllers based on deterministic models or non-adaptive control parameters often fail to achieve the desired performance. To enhance the adaptability of USV motion controllers, this paper proposes a trajectory tracking control algorithm that calculates PID control parameters using an improved Deep Deterministic Policy Gradient (DDPG) algorithm. Firstly, the maneuvering motion model and parameters for USVs are introduced, along with the guidance law for path tracking and the PID control algorithm. Secondly, a detailed explanation of the proposed method is provided, including the state, action, and reward settings for training the Reinforcement Learning (RL) model. Thirdly, the simulations of various algorithms, including the proposed controller, are presented and analyzed for comparison, demonstrating the superiority of the proposed algorithm. Finally, a maneuvering experiment under wave conditions was conducted in a marine tank using the proposed algorithm, proving its feasibility and effectiveness. This research contributes to the intelligent navigation of USVs in real ocean environments and facilitates the execution of subsequent specific tasks.

Numerical study on heat transfer of two-phase fluid in helical coil pipe under ocean condition

The thermal hydraulic characteristics and heat transfer of two-phase fluid in helical coil once-through steam generator under ocean conditions like rolling and heaving motions are studied numerically. A CFD model is established to analyze the effects of motion parameters like amplitude, period and rolling radius and the heat flux distribution are discussed. The analysis shows that the overall heat transfer decreases under ocean conditions, but the overall deterioration is limited, indicting the helical coil pipe has the stability for ocean conditions. The additional forces like Coriolis, centrifugal and inertial forces introduced by rolling motion are analyzed theoretically and the result shows it detorts the original two main vortexes responsible for high heat transfer due to its spiral geometry, making heat transfer fluctuates up and down periodically near the steady state value. As rolling height increases, the heat transfer is nonlinear due to the competition between Coriolis force and centrifugal and inertial forces. As rolling amplitude increases, the heat transfer variation increases and the local heat transfer deterioration is severely aggravated, indicating high rolling amplitude should be avoided as possible. Increasing rolling period makes heat transfer behavior more approximate to static case as gravity and centrifugal force due to spiral geometry is dominate. Under heaving motion, the overall heat transfer decreases, and increasing heaving amplitude and decreasing period make the fluctuation more severe.

Impact of Drawing Machine Parameters on Force and Energy Consumption in Borosilicate Glass Tube Production

Middle borosilicate glass tubes are critical materials for medical packaging, with the drawing machine playing a pivotal role in their production process. However, the effects of the drawing wheel’s motion parameters on the glass tube remain underexplored. Therefore, based on the finite element method simulation and validation experiment, the effects of experimental factors (angle of upper and lower drawing wheel, AUD; friction factor of glass and rubber, FFGR; and distance of upper and lower drawing wheel, DUD) on experimental indexes (maximum effective stress of glass tube, MES; rotational speed of glass tube, RSG; maximum and average forward driving force, MFDF and AFDF; maximum and average rotational driving force, MRDF and ARDF; total energy consumption and power, TEC and TPD; maximum and average forward driving power, MFDP and AFDP; and maximum and average rotational driving power, MRDP and ARDP) were analyzed. The results indicated that compared to FFGR and AUD, the influence of DUD on experimental indexes was the highest. The positive influence of AUD on RSG, ARDP, and MRDP, the positive influence of FFGR and the negative influence of DUD on MRDF, ARDF, TEC, TPD, ARDP, and MRDP were found, respectively. These findings will provide a theoretical reference for the optimization of drawing machines.

Study on the attenuation relationship of the acceleration envelope parameters for the Wenchuan earthquake aftershocks

The seismic attenuation relationship between ground motion parameters (such as peak acceleration and response spectra value) and seismic parameters (such as magnitude and epicentral distance) is an important foundation for seismic hazard analysis and the core of determining seismic input parameters for seismic resistance engineering. The acceleration envelope parameters, which describe the relationship between ground motion intensity and time variation, are primarily used for artificially synthesizing seismic motion. At present, little research has been performed on the attenuation relationship of acceleration envelope parameters in the Longmenshan fault zone on the eastern side of the Tibetan Plateau in China. Therefore, this study selected the Mw4-6 aftershock records of the 2008 Wenchuan earthquake that occurred on the Longmenshan fault zone and established a commonly used three segment envelope model parameter attenuation relationship. We classified aftershock records based on their source mechanisms and obtained attenuation relationship models for thrust slip aftershocks, thrust and strike slip aftershocks, and strike slip aftershocks. The results are as follows: (1) The thrust slip aftershock records had the longest rising stage which is the time difference from the arrival of P-waves to the beginning of the stable sustained stage of seismic motion. Thrust and strike slip aftershocks records had the longest stable sustained stage period and the slowest attenuation at the tail of the record. (2) The attenuation relationship of the acceleration envelope parameters commonly used in Chinese engineering for artificially synthesizing seismic motion is based on the strong earthquake records in the western United States. But, compared to the attenuation characteristics of the acceleration envelope function in the western United States, the Mw4-6 earthquake records on the Longmenshan fault zone had a slower attenuation rate at the tail of the record. So, accurately artificially synthesizing seismic motion through envelope parameter attenuation model requires the use of attenuation model established by earthquake records in this region.

Efficient approximate Bayesian inference for quantifying uncertainty in multiscale animal movement models

It is becoming increasingly important for wildlife managers and conservation ecologists to understand which resources are selected or avoided by an animal and how to best predict future spatial distributions of animal populations in the long term. However, inferring the patterns of space use by animals is a challenging multiscale inference problem, and formal uncertainty quantification of parameter estimates is an essential component of models that provide useful predictions across scales. In this study, we develop an approximate Bayesian inference framework for step selection models of animal movement which quantifies the uncertainty in estimates of resource selection and avoidance parameters within the Bayesian paradigm. The framework allows joint inference of movement and resource selection parameters of animals and is multiscale in that parameters inferred from fine scale movement steps scale to produce predictions of long-term patterns of space use. Our analysis focuses on simulated movement data in which we test the performance of our framework by altering movement parameters in the data-generating process. In our simulations, individuals respond to two environmental covariates and we employ all combinations of positive and negative selection coefficients corresponding to attraction to an environmental feature and avoidance of an environmental feature, respectively. In all scenarios, we recover the movement parameters used for the simulation of synthetic movement data using variational inference, an approximate Bayesian method, allowing us to formally quantify the uncertainty associated with each parameter for varying data set sizes. Our framework successfully recovered all combinations of movement parameters of the simulated data and accurately captured their posterior distributions given the available data suggesting that the framework is reliable and suitable for inferring how animals select resources and move on a landscape.Notably, our analysis shows that even for reasonably large data sets (circa 10,000 observations) there can still be considerable uncertainty associated with resource selection parameters which can in turn lead to inaccurate predictions of long term space use if not properly incorporated into the modelling approach. To further illustrate the utility of our approach, we also present a case study of its application to an example data set consisting of GPS locations of a fisher (Martes pennanti) Our approach will be of interest to ecologists looking to address conservation questions such as when and where animals are likely to spend most of their time. Furthermore, the approach could be used to predict new suitable areas for conservation based on how GPS collared animal use or avoid resources while including uncertainty around the predictions, thereby helping to make informed management decisions.

Research on Target Position and Motion Parameters Based on Azimuth Wave Number of Echo Signal

Abstract The circular synthetic aperture radar (CSAR) system by a small rotor unmanned aerial vehicle, being capable of three-dimensional target imaging, is one of the research hotspots in SAR imaging. In this paper, for the frequency modulated continuous wave CSAR system, the geometric structure and wavenumber spectrum are derived, and then the relationship between the azimuth wavenumber and system parameters as well as flight motion conditions is analyzed. Through simulation analysis, it is verified that the azimuth wavenumber of the echo signal is affected by the position and motion parameters of the imaging target, laying a theoretical foundation for the development and application of the wavenumber domain imaging algorithm of CSAR.

EKF-based parameter estimation method for radar maneuvering target with unknown time information

Moving target detection (MTD) is a research hotspot in radar signal processing. Generally, the time information of non-cooperative moving targets entering and leaving a radar coverage area is unknown, which would lead to severe performance loss for target parameter estimation, detection, and imaging. Unlike our previous research work, this paper addresses the motion parameters estimation and refocusing problem for a radar maneuvering target with unknown entry and departure time. A computationally efficient method that utilizes extended Kalman filtering (EKF) for phase tracking is proposed to estimate the entry and departure times. The proposed method first performs range cell migration correction (RCMC) on the pulse compression echo signal. Then, the maneuvering target signal is modeled as a polynomial phase signal (PPS) and utilizes the EKF to construct a binary state-space equation for polynomial phase tracking. Finally, by comparing the phase tracking results of the noise cell and the signal cell, one can derive estimates for the entry/departure time and motion parameters. Compared with existing methods, the proposed method avoids multi-dimension searching on the parameter space, so it has a prominent advantage in computational complexity. Moreover, the core of the proposed method lies in tracking the polynomial phase, which is not constrained by the order of target motion, and has wider applicability in practice. Both simulated and public radar data are used to validate the effectiveness of the proposed method.

Measurement method of flexible component pose based on discrete motion actuators

Abstract In order to address the limitations of traditional large discrete motion actuator mechanisms in realizing high-precision inter-axis relationship calibration in manufacturing environments, this paper proposes a new convolutional neural network-based attitude mapping estimation method, component pose using convolutional neural network (CPCNN). The method implicitly encodes the inter-axis relation matrix into the weight parameters of the training neural network, which results in a high degree of integration with existing large discrete motion actuator mechanisms. The CPCNN-based method directly obtains the attitude change of the adjustment cabin by reading the change of each axis of the current motion actuator mechanism in its own coordinate system. This method can overcome the limitations of the experimental process in the traditional calibration methods and improve the accuracy of attitude mapping under the influence of self-weight by selecting better motion parameters through redundant degrees of freedom. The application of this new method will provide an effective solution for the high-precision inter-axis relationship calibration of large discrete motion actuator mechanisms in manufacturing environments, offering new possibilities for improving production efficiency and product quality.

Joint reaction and simulated muscle forces during squatting and walking in persons with hemophilia

BackgroundPersons with hemophilia experience joint bleeding that can lead to debilitating arthropathy, most commonly seen in ankles, knees, and elbows. Arthropathy can hinder participation in daily and athletic activities. We explored how hemophilic arthropathy impacts movement patterns in walking and bilateral squatting tasks in persons with hemophilia compared to healthy controls. MethodsPersons with hemophilia and healthy controls completed walking and squatting tasks while kinematic and kinetic motion capture data were collected. The Hemophilia Joint Health Score exam was performed to measure hemophiliac arthropathy. OpenSim was used to model muscle and joint reaction forces and calculate moments and angles. Peak values were compared using Cohen's d to estimate effect sizes of hemophilia on movement parameters. FindingsNine persons with hemophilia and eight age-matched controls were analyzed. Temporal-spatial metrics were similar between hemophilia and control groups in both tasks. In walking, persons with hemophilia had higher peak ankle dorsiflexion angles, vertical ground reaction force weight acceptance peaks, and hip extension and flexion moments compared to controls. In squatting, persons with hemophilia had lower knee extension moments, ankle joint reaction force, and knee extensor forces, but had higher hip extension moments. InterpretationTemporal-spatial metric similarity between hemophilia and controls suggests that kinetic and kinematic analyses are needed to identify movement pattern differences. These data identify potential compensatory strategies at the hip that may be used by persons with hemophilia to mitigate impact on the knee and ankle. Future work will confirm these data in a larger sample size and be used to develop physical therapy strategies.

Effect of thin film thickness of ferrofluid on inclined bioconvective flow

This research examines the effect of variable thin film thickness on the bioconvective ferrofluid flow through a rotating sloped surface when a magnetic field (dipole) is present. Similarity transformation is used to standardize the current model's governing equations. By using a finite element method, the normalized nonlinear differential equations are numerically solved. Variable thickness of ferrofluid thin film and bioconvective parameters (bioconvective Lewis number, bioconvective Peclet number, and micro-organism concentration difference) yield the following results: velocity profiles (radial, tangential, and axial), gravity flow (drainage velocity and induced velocity), temperature profile, concentration profile and microorganism profile. In addition, this investigation examines the density of moving microorganisms as well as local heat and mass transport. The temperature, concentration, radial, axial, drainage, induced, and motile microbe velocity are all improved with increasing film thickness. Variable thickness increases local heat transfer whereas increasing Brownian motion and thermophoresis parameters decreases it. This study could be helpful for self-sterilizing applications and biomedical engineering.

Behavioural responses of common dolphins to naval sonar.

Despite strong interest in how noise affects marine mammals, little is known for the most abundant and commonly exposed taxa. Social delphinids occur in groups of hundreds of individuals that travel quickly, change behaviour ephemerally and are not amenable to conventional tagging methods, posing challenges in quantifying noise impacts. We integrated drone-based photogrammetry, strategically placed acoustic recorders and broad-scale visual observations to provide complementary measurements of different aspects of behaviour for short- and long-beaked common dolphins. We measured behavioural responses during controlled exposure experiments (CEEs) of military mid-frequency (3-4 kHz) active sonar (MFAS) using simulated and actual Navy sonar sources. We used latent-state Bayesian models to evaluate response probability and persistence in exposure and post-exposure phases. Changes in subgroup movement and aggregation parameters were commonly detected during different phases of MFAS CEEs but not control CEEs. Responses were more evident in short-beaked common dolphins (n = 14 CEEs), and a direct relationship between response probability and received level was observed. Long-beaked common dolphins (n = 20) showed less consistent responses, although contextual differences may have limited which movement responses could be detected. These are the first experimental behavioural response data for these abundant dolphins to directly inform impact assessments for military sonars.

A computation analysis with heat and mass transfer for micropolar nanofluid in ciliated microchannel: With application in the ductus efferentes

Inherited heat enhancement capabilities and their significance in the field of medical sciences and industry make nanofluids the focus of research nowadays. Furthermore, due to the remarkable advancements in bionanotechnology and its significance in biomedical fields such as drug delivery systems, cancer tumor therapy, bioimaging, and many others, it has emerged as a key research area. Contribution of cilia for the flow in ductus efferentes of human male reproductive tract is elaborated. A novel mathematical scheme is presented for the heat and mass transfer of MHD micropolar nanofluid transport in an asymmetric channel lined with cilia. The pertinent equations of nanofluid transport are exposed to lubrication approximation theory and solution for the physical problem is examined with efficient bvp4c technique in MATLAB. Fluid rheology is explored with the variations of different transport parameters like Hartmann number, Grashof number, Brownian motion, buoyancy, thermophoresis and Darcy number. It is reported that nanofluid transport is affected with rise in the Lorentz force and show reverse behavior with rising permeability. The temperature of the nanofluid in ciliated microchannel is raised with enhanced value of Hartmann number, Grashof number, Prandtl number, and Darcy number while diffusion phenomenon of nanofluid is slowed down with these parameters. Spinning motion of the nanofluid is enhanced with Grashof number and slow down with nanoparticle Grashof number and different behavior is recorded for Darcy and viscosity parameters in different flow regime. Reported investigation presents crucial findings for ciliary transport of micropolar nanofluid and tackled with appropriate selection of micropolar parameter, Brownian motion parameter, thermophoresis and Grashof number. Moreover, this investigation will be handful for cilia-based actuators which work as micro-mixers in controlling the flow in minute bio-sensors and may prove their worth in micro-pumps employed in various drug-delivery systems.

Numerical simulation on the interaction of median fins for enhancing vortex dynamics and propulsion performance in fish self-propelled swimming

Studies have shown that fish can enhance propulsion performance by utilizing the interaction between median fins (dorsal, anal, and caudal fins), compared to fish with only caudal fin. However, most of the current studies are based on the fish oscillating in-place, and the analysis of median fins interaction to improve swimming propulsion performance is still insufficient, and the mechanism needs further study. This study applied three-dimensional numerical simulation methods to solve the process of grass carp accelerating from a stationary state to cruising state under different body and median fins combination, as well as different motion parameter models. A comparative quantitative analysis of different models was conducted to assess the impact of median fins interactions on enhancing swimming performance, with a detailed analysis of the hydrodynamic mechanisms and their relationship with vortex dynamics. The results indicated that interactions between median fins could generate significant hydrodynamic benefits, with the fish's average swimming speed increasing up to 4.6 times, thrust up to 33.47%, and swimming efficiency up to 25.48%. This study found that the enhancement of propulsion performance was due to the formation of high-intensity and persistent posterior body vortices by the movements of the dorsal and anal fins, which were captured by the leading-edge of the caudal fin, greatly enhancing the strength of the leading-edge vortex. This study elucidates the hydrodynamic mechanisms of the interaction between median fins and could provide new insights into the efficient swimming mechanism of fish in nature.

An Image Distortion Correction Method Based on Distortion Centre and Parameter Estimation

Abstract We propose a radial distortion correction method based on straight-line feature calibration to address the challenge of image radial distortion when measuring mechanical motion parameters using computer vision technology. This method first independently estimates the distortion center, and then transforms the distortion parameter estimation into an arc fitting problem. The least squares optimization algorithm is applied to quickly and accurately estimate the arc parameter of distorted lines, ultimately achieving precise correction of distortion in wide-angle camera images. This method can reduce lens distortion by 89% to 92%, laying a solid foundation for the application of computer vision technology in the field of mechanical motion parameter measurement.

Enhancing underwater unmanned vehicle efficiency through asymmetric dynamics in manta-like swimming

This study explores the hydrodynamic performance of a National Advisory Committee for Aeronautics 0012 foil using computational fluid dynamics with the unsteady Reynolds-averaged Navier–Stokes (URANS) method and shear stress transport k-ω model to assess the impact of asymmetric motion parameters in manta-like swimming. The angles of attack during the mid-upstroke (αmu), mid-downstroke (αmd), and stroke duration (S) are varied to understand their effect. At low Strouhal numbers (StA = 0.2–0.35), a smaller αmd compensates for thrust loss at the start of the upstroke due to a greater αmu. At high Strouhal numbers (StA = 0.5), a greater αmd reduces negative thrust and compensates for the smaller thrust generated by a small αmu during the upstroke. Shorter stroke durations increase asymmetry, leading to more significant positive thrust peaks during the downstroke. If both the angle of attack and S are large, the slower downward speed extends negative thrust, reducing thrust peaks and lowering average thrust. A smaller stroke duration combined with a large angle of attack enhances efficiency due to a greater thrust-to-power ratio, highlighting the interplay between these parameters. A smaller S and greater αmd and StA maximize thrust and efficiency, suggesting aquatic organisms increase thrust while ensuring propulsion efficiency by using a large angle of attack and an asymmetric stroke duration. This study demonstrates how asymmetric parameters interact, providing insights into designing biomimetic underwater vehicles. The findings suggest that asymmetric dynamics enhance propulsion efficiency.

Multilayer deep-learning intelligent computing for the numerical analysis of unsteady heat and mass transfer in MHD Carreau Nanofluid model

The objective of this article is to investigate the mechanism of unsteady heat and mass transfer (HMT) in a magnetohydrodynamics Carreau nanofluid flow (MHD-CNFF). To accomplish this, we utilized a novel artificial intelligence-based (AI) method, deep learning predictive technique combined with Levenberg-Marquardt scheme (DLPT-LMS). The similarity transformation is applied to convert the partial differential equations (PDEs) into a set of non-linear ordinary differential equations (ODEs). We numerically solved these resulting ODEs using the Adam numerical approach in sophisticated “Mathematica” software. The influence of Brownian motion parameter, thermophoresis parameters, Prandtl number, Lewis number, and mass transfer parameters on the temperature, velocity, and concentration profile is analyzed using a synthetic dataset. This evaluation is conducted across different variation of MHD-CNFF by leveraging DLPT-LMS. The absolute error (AE) across various iteration of MHD-CNFF demonstrated a progressive drop, indicating the accuracy of DLPT-LMS. The outcomes of this investigation revealed that the AE ranged from 10-3 to 10-8 which shows a minimum error between actual and predicted value. Additionally, the MSE confirmed the accuracy of proposed DLPT-LMS in predicting the behavior of velocity, temperature, and concentration profiles, with lower values showing better predictions. The model accuracy was reinforced by performance results, including regression analysis and error histograms. Error values gradually decreased during training, validation, and testing phases, exhibiting a robust convergence and indicating the highly reliability of AI-based algorithm for investigating intricate fluid dynamics in MHD-CNFF systems.