Input Angle Research Articles

Optimizing Heat Transfer in Heat Pipes Using Hybrid Nanofluids With Multi‐Walled Carbon Nanotubes and Alumina

ABSTRACTThis study investigates the thermal performance of heat pipes using hybrid nanofluids composed of multi‐walled carbon nanotubes (MWCNT) and aluminum oxide (Al2O3) nanoparticles. The aim was to assess the effects of nanoparticle concentration (0.1%–0.5%), filling ratio (60%–90%), heat input (50–80 W), and inclination angle (0°–90°) on thermal resistance and heat transfer coefficient (HTC). Hybrid nanofluids were prepared using ultrasonic homogenization, and their stability was confirmed by zeta potential analysis, showing a reduction from −60 to −48 mV over 30 days. Experimental results revealed that the thermal resistance decreased with increasing filling ratio and inclination angle, reaching a minimum of 0.80 K/W at a 90° angle, 90% filling ratio, and 80 W heat input. Similarly, the overall HTC increased with these parameters, peaking at 2250 W/m2 K under the same conditions. At a 0.5% nanoparticle concentration, the HTC improved by up to 40% compared with conventional fluids. The thermal conductivity of the hybrid nanofluid also rose significantly, from 0.7 W/m K at 30°C to 1.5 W/m K at 90°C, outperforming distilled water. These findings highlight the potential of hybrid nanofluids to enhance heat pipe efficiency, particularly in high‐power applications, by optimizing nanoparticle concentration, filling ratio, and inclination angle.

Reentry vehicle fixed-time terminal guidance and attitude control with impact angle constraints

The motivation of this paper is to handle the terminal guidance and attitude control problem for the unpowered reentry vehicle in the diving phase, which is crucial for interception to the target. The most important objectives of this study are to intercept the maneuvering target with the miss distance and impact angle error as small as possible. First, the second-order derivatives of the aerodynamic angles are derived with the fin deflections as control input, which is objective to avoid the tracking of reentry vehicle body angle rate command in the traditional methods. Second, a novel fixed-time time-varying parameter nonsingular terminal sliding mode guidance law is proposed to improve the convergence speed of line-of-sight angle rate, which can avoid control input singularity without switching to the polynomial form when the error approaches the origin. Thirdly, a new global time-varying sliding mode is developed to design the attitude controller, with the predefined fixed convergence time and analytical solution. The system states are proved to be fixed-time convergence based on the Lyapunov stability theory. Six-degree-of-freedom flight simulations are conducted to validate the superiority of the proposed algorithm in terms of miss distance, impact angle error, intercepting time and control input energy.

Dispersion-free characterization of terahertz slab–waveguide modal confinement based on a metal Bragg grating structure

Photonic waveguide structures that use periodic metal grooves and periodically perforated metal slits (PPMSs) can laterally confine Sommerfeld and Zenneck surface waves of metals with the electric field accumulation among metal interspaces in the terahertz (THz) region, instead of the total internal reflection principle of dielectric slab media. For the efficiency enhancements of THz-wave coupling and slab–waveguide confinement, specific integrators with high refractive indices or specified for input angles of transverse magnetic polarized waves, such as prisms, metal blades, and waveguides, are requested to excite spoof surface plasmons in the THz region. However, the integrator-assembled slab–waveguides encounter challenges of THz pulse-wave communication in compact and low-distortion systems. A resonant waveguide grating structure based on PPMSs is experimentally demonstrated to confine THz lateral waves from the plane-wave radiation in free space. The open frame and periodic metal cavities of PPMSs can work as a slab–waveguide to transmit structural confined waveguide modes with forwarding evanescent waves of Fabry–Pérot resonance. For 0.1–1 THz waves, the short wavelengths that are both less than half the metal slit width and 3.75 times the metal thickness can lead to zero dispersion and the highest confinement factor in a slab–waveguide for PPMS-confined THz waves. This behavior is opposite to the high structural dispersion in confined THz waves of surface plasmonic devices.

Predictive analysis of tensile strength ratios in laminated bamboo composites: Unraveling the stochastic impact of ply angle variations through machine learning model

Laminated bamboo composites (LBC), made by sandwiching bamboo strips, offer promising alternatives to traditional construction materials, especially for housing. However, subjection to the continuous static loading makes these materials initiate cracks inside their various ply. This study uses classical laminate theory (CLT) to determine the strength ratio (SR) of the LBC at different ply orientations by applying Tsai-Wu and Tsai-Hill failure criteria using MATLAB. The study aims to calculate the SRs for LBCs using CLT, employing an ANN model and stochastic finite element (FE) modeling to investigate SRs of five-layered LBCs with varying ply orientations. Applying CLT, the highest SR was determined to be 1.5375 × 107 N/m for the [0°/0°/0°/0°/0°] laminate, as per both failure theories. The study reveals substantial SR variations depending on ply orientation, consistently showing higher SR predictions with the Tsai-Wu theory compared to the Tsai-Hill theory. Next, the study emphasizes the deterministic methodologies to account for the stochastic effects of ply angle on the obtained SR of LBCs. Monte Carlo simulation (MCS) was utilized to model 10,000 randomly generated ply angle inputs and their associated SRs. By incorporating MCS to introduce ±1% variations in ply angles and utilizing normally distributed data, this research effectively captures uncertainties associated with ply orientation. Finally, to forecast the random SR of LBC with various ply orientations, an artificial neural network (ANN) surrogate model is employed. The stochastic analysis confirms the need to quantify the associated uncertainties. The findings of this study are crucial for advancing the application of LBC in sustainable construction, providing valuable insights into their mechanical behavior under different ply orientations, considering the stochastic effect in properties.

Radial Basis Function Neural Network and Feedforward Active Disturbance Rejection Control of Permanent Magnet Synchronous Motor

A composite control strategy is proposed to improve the position-tracking performance and anti-interference capabilities of permanent magnet synchronous motors (PMSMs). This strategy integrates an active disturbance rejection controller (ADRC) and a radial basis function neural network (RBFNN) with feedforward control. Initially, the flexibility and robustness of the ADRC are utilized in the position loop control. Subsequently, the parameters of the extended state observer (ESO) within the ADRC are optimized, benefiting from the fast convergence speed and optimal approximation provided by the RBFNN. To further enhance the dynamic tracking performance, a differential feedforward link is introduced between the desired speed and the output signal. The simulation and experimental results demonstrate that when the expected electrical angle inputs are sinusoidal and pulse signals, the incorporation of the feedforward link and the adjustment of parameters in the ADRC lead to improved position-tracking capabilities and greater adaptability to load disturbances.

A comprehensive study on active mixer performance using liquid metal droplets: an experimental approach

In this experimental study, we delve into the performance of an active mixer that utilizes liquid metal droplets. Our mixer configuration follows an innovative Y-type design, where two liquid metal-based pumping mechanisms operate within the minichannel inlet branches. By applying alternating current voltage to both sides of the liquid metal, we induce a surface tension gradient, propelling the fluid from the reservoirs toward the minichannel. Notably, the two entering liquids are distinctly colored, allowing us to quantify mixing using a Mixing Index (MI) definition and image processing techniques. Our investigation centers on four key variables governing mixer performance: applied voltage, liquid metal droplet diameter, input angle between the branches, and minichannel width. Given the experimental nature of our research, we employ a central composite design method within the framework of design of experiments (DoE). From our obtained experimental results, we establish correlations between MI and the other variables. Our examination of the four mentioned parameters revealed that liquid metal droplet diameter exerts the most significant influence on the mixing index. Following this, in descending order of impact, we find applied voltage, input angle, and channel width. In the optimal dimensions of our mixer, we achieve a remarkable maximum MI of 0.867.

Pointer Meter Reading Method Based on YOLOv8 and Improved LinkNet.

In order to improve the reading efficiency of pointer meter, this paper proposes a reading method based on LinkNet. Firstly, the meter dial area is detected using YOLOv8. Subsequently, the detected images are fed into the improved LinkNet segmentation network. In this network, we replace traditional convolution with partial convolution, which reduces the number of model parameters while ensuring accuracy is not affected. Remove one pair of encoding and decoding modules to further compress the model size. In the feature fusion part of the model, the CBAM (Convolutional Block Attention Module) attention module is added and the direct summing operation is replaced by the AFF (Attention Feature Fusion) module, which enhances the feature extraction capability of the model for the segmented target. In the subsequent rotation correction section, this paper effectively addresses the issue of inaccurate prediction by CNN networks for axisymmetric images within the 0-360° range, by dividing the rotation angle prediction into classification and regression steps. It ensures that the final reading part receives the correct angle of image input, thereby improving the accuracy of the overall reading algorithm. The final experimental results indicate that our proposed reading method has a mean absolute error of 0.20 and a frame rate of 15.

Experimental study of the effect of the input and output key angles on the discharge coefficient and efficiency of the PKWs

ABSTRACT The results showed that Cd, Ra, and, consequently, the increase in the passing flow discharge have a direct relationship with the inclination angle of the input and output keys, and for this reason, the weir of the piano key weir (PKW) with an angle of 90° has the highest Cd and Ra. An increase in the HT/P ratio in all angles leads to a decrease in Cd and Ra. However, the decrease rate of these parameters is less for a 15° angle compared to other threshold angles of the input and output keys. In the PKWs with different input and output key angles and at low HT/P ratios , the dropping flow nappe needs aeration due to its bonding. However, by increasing this ratio to the submergence condition and transforming into a linear weir, the dropping flow nappe is aerated. At low ratios of HT/P, the dropping flow nappes do not interfere, and the highest discharge coefficient and the highest weir efficiency are obtained. While by increasing the HT/P ratio, the dropping flow nappes start to collide and interfere with each other in the output keys, causing the flow rise and the weir submergence, and consequently, the discharge coefficient is decreased.

Finite-Time Disturbance Observer-Based Adaptive Course Control for Surface Ships.

In this paper, a finite-time disturbance observer-based adaptive control strategy is proposed for the ship course control system subject to input saturation and external disturbances. Based on the Gaussian error function, a smooth saturation model is designed to avoid the input saturation of the system and reduce steering engine vibrations, and an auxiliary dynamic system is introduced to compensate for the effect of the rudder angle input inconsistency on the system. By constructing an auxiliary dynamic, a finite-time disturbance observer is designed to approximate the external disturbance of the system; an adaptive updating law is also constructed to estimate the upper bound of the derivative of the external disturbance. Combining the finite-time disturbance observer with the auxiliary dynamic system, a novel adaptive ship course control law is proposed by using the hyperbolic tangent function. Moreover, according to LaSalle's Invariance Principle, a system stability analysis method with loose stability conditions and easy realizations is designed, while the stability of the closed-loop system and the ultimately uniformly boundedness of all its signals are proven. Finally, the course control simulation analysis of a surface ship is carried out. The results show that the proposed control law has a strong resistance to external disturbances and a strong non-fragility to system parameter perturbations, which ensure that the course control system has great control performance.

Dimensional synthesis of motion generation of a planar four-bar mechanism

A motion generation method for a planar four-bar mechanism without prescribed timing is proposed in this article. A characteristic of coupler points is found: for the coupler points of a four-bar mechanism in a standard installation position rotated by the corresponding input angle clockwise around the origin of the Cartesian coordinate system xOy, the generated points lie on the feature coupler circles. Next, based on this, the design process is divided into three steps. In the first step, the relative input angles, the relative coupler angles and five geometric parameters of the desired four-bar mechanism are optimized. In the second step, the basic dimensional types and initial input angle are determined, and then, the input angles are obtained. In the third step, the real size of the desired linkage mechanism is calculated. Because the dimension of the design variables in each step is exceptionally small, the motion synthesis method can yield design solutions with high precision in a short time. Six comparison examples are presented to demonstrate the efficacy of the proposed method. In addition, the method is used to design a robot for lower limb rehabilitation for application to the human foot.

Use of machine learning to optimize actuator configuration on an airfoil

Machine learning was used to optimize the geometric arrangement of a pair of unsteady actuators on flow separation over an efficient low Reynolds number airfoil in post-tall conditions. Large eddy simulation was used to validate the results. Two actuators: one with blowing and the other with suction openings were installed on the top surface of an airfoil at low Reynolds number of 60,000. An SD7003 airfoil at a post stall angle of attack of 13° was utilized. The boundary layer flow of the top surface was manipulated by the actuators to control flow separation. The influence of several actuator parameters: frequency, energy input, opening area, location and orientation angle were considered in an optimization of the dual actuator configuration. A genetic algorithm-based optimization was implemented to find the most effective configuration of this coupling. Since the optimization process is time-consuming, machine learning was used to train artificial neural networks to be coupled with genetic algorithm to reduce the computational cost. The artificial neural networks and their training was constantly upgraded during the optimization cycle. Results for the optimal case indicated an increase in lift coefficient and the objective function in comparison to uncontrolled case by factors of 1.88 and 3.33 respectively. We also found a reduction in drag coefficient. It was also found that using a pair of actuators was more efficient than using a single actuator.

The Effect of Sensor Feature Inputs on Joint Angle Prediction across Simple Movements.

The use of wearable sensors, such as inertial measurement units (IMUs), and machine learning for human intent recognition in health-related areas has grown considerably. However, there is limited research exploring how IMU quantity and placement affect human movement intent prediction (HMIP) at the joint level. The objective of this study was to analyze various combinations of IMU input signals to maximize the machine learning prediction accuracy for multiple simple movements. We trained a Random Forest algorithm to predict future joint angles across these movements using various sensor features. We hypothesized that joint angle prediction accuracy would increase with the addition of IMUs attached to adjacent body segments and that non-adjacent IMUs would not increase the prediction accuracy. The results indicated that the addition of adjacent IMUs to current joint angle inputs did not significantly increase the prediction accuracy (RMSE of 1.92° vs. 3.32° at the ankle, 8.78° vs. 12.54° at the knee, and 5.48° vs. 9.67° at the hip). Additionally, including non-adjacent IMUs did not increase the prediction accuracy (RMSE of 5.35° vs. 5.55° at the ankle, 20.29° vs. 20.71° at the knee, and 14.86° vs. 13.55° at the hip). These results demonstrated how future joint angle prediction during simple movements did not improve with the addition of IMUs alongside current joint angle inputs.

A neural network inverse problem solution for a MIMO magnetic levitation actuator

A multiple-input and multiple-output planar actuator is proposed, which utilizes mechanically driven stator magnet arrays to levitate a permanent magnet mover. A state of levitation and actuation is obtained by mechanically altering the orientation of the stator magnets to control the forces and torques on the mover. A challenge for the design and control of the actuator is inverting the relationship between the force and stator magnet rotation angles, as there is no closed-form analytical solution. In this study, a feed-forward neural network is applied to model the forward relation between stator magnet angle input and a force and torque output to reduce the forward computation time for the design process and for error estimation in real-time applications. Additionally, the neural network is considered for inverting the solution for a motion profile sampled at 1000 Hz. The developed forward model is able to calculate the forces and torques on the mover a factor 10 faster than the equivalent charge or Fourier model with an absolute error of 3 mN and 0.1 mNm for the forces and torques, respectively, and a feed-forward neural network is able to accurately learn an inverse solution for small motion profiles.

Selecting Pedal Load for Lower-Limb Rehabilitation Based on the Combination of Muscle Synergy and Fourier Series

This paper introduces a new lower-limb rehabilitation machine that meets the rehabilitation needs of hemiplegic patients. First, a left–right independent rotary pedal mechanism was selected to facilitate rehabilitation and adapt to the user’s physical condition. Then, a half model of the lower-limb rehabilitation machine is designed and manufactured with ergonomics in mind. As analytical tools, we combine non-negative matrix factorization and non-negative double singular value decomposition to calculate muscle synergy of the walking muscle surface electromyography (sEMG) signal, and use cosine similarity to evaluate the similarity between walking and pedaling activities. By comparing the results of the walking and pedaling experiments, the effectiveness of pedaling in gait rehabilitation is revealed. To further improve the similarity between walking and pedaling, double integration of the sEMG signal is introduced, and the relationship between load input and rotation angle is described for the first time using Fourier series. The results of the experiment confirmed that more than half of the 10 subjects performed pedaling exercises similar to walking using Fourier series loading compared to pedaling exercises with normal constant loading. This loading parameter may have the potential to improve rehabilitation efficiency for many subjects compared to the usual exercise.

Welding residual stress analysis of the X80 pipeline: simulation and validation

Abstract. In this work, a finite-element welding model of the X80 pipeline is established, and the residual stress is calculated using a direct thermal–mechanical coupling method through the User Material (UMAT) subroutine of the double-ellipsoid moving heat source. The effects of process parameters on the welding residual stress of the X80 pipelines are discussed. The ultrasonic longitudinal critical refraction (LCR) wave-detecting method is adopted to verify the simulation results. The results show that the residual stress at the inner surface is higher than that at the outer surface, and the peak Mises stress at the welding seam approaches the yield stress. With the increase in welding groove angle and heat input, the peak Mises stress increases at the inner surface and decreases at the outer surface, but the high-stress zone at the outer surface broadens. The residual stresses at the outer surface are more sensitive to the welding parameters. The comparison between the simulated results and ultrasonic LCR detection indicates that the finite-element method is feasible, and the simulation results are credible.

Parameter optimization, microstructural and mechanical properties of fiber laser lap welds of DP1200 steel sheets

In this research, the effects of laser power, laser welding speed and laser incidence angle were evaluated in terms of weld geometry, microstructure, microhardness, fracture surfaces and tensile shear load in fiber laser welding joints of DP1200 steel sheets. Response Surface Methodology (RSM) was utilized to derive mathematical relationships between the process parameters and the tensile shear load after the tensile test. The optimum combination of process parameters was a laser power of 2800 W, a laser welding speed of 40 mm/s, and a laser incidence angle of 70°. A thermal camera was used to record the laser welding process, and the cooling rates were evaluated by analyzing this data. The influence of cooling rate upon microstructure phase formation for DP1200 steel is investigated, with continuous cooling transformation (CCT) diagrams. Also, post-welding stress and displacement were simulated by Simufact Welding software. At high heat input (55.79 J/mm) occurred coarse dendritic martensitic lath growth while at low heat input (37.6 J/mm) fine dendritic martensitic structure was observed in the weld zone was obtained owing to the high rate of cooling. The microstructure consists of full martensite at a higher than 10 °C/s cooling rate. The findings reveal that the phases in FZ and HAZ, the morphology and martensite/bainite constituents differed related to the heat input and laser incidence angle, which ultimately affects the joint’s microhardness, fracture dynamics and tensile shear load.

Ice base slope effects on the turbulent ice shelf-ocean boundary current

Abstract Efforts to parameterize ice shelf basal melting within climate models are limited by an incomplete understanding of the influence of ice base slope on the turbulent ice shelf-ocean boundary current (ISOBC). Here we examine the relationship between ice base slope, boundary current dynamics, and melt rate using 3-D, turbulence-permitting large-eddy simulations (LES) of an idealized ice shelf-ocean boundary current forced solely by melt-induced buoyancy. The range of simulated slopes (3-10%) is appropriate to the grounding zone of small Antarctic ice shelves and to the flanks of relatively wide ice base channels, and the initial conditions are representative of warm-cavity ocean conditions. In line with previous studies, the simulations feature the development of an Ekman boundary layer adjacent to the ice, overlaying a broad pycnocline. The time-averaged flow within the pycnocline is in thermal wind balance, with a mean shear that is only weakly dependent on the ice base slope angle α, resulting in a mean gradient Richardson number 〈Rig〉 that decreases approximately linearly with sinα. Combining this inverse relationship with a linear approximation to the density profile, we derive formulations for the friction velocity, thermal forcing, and melt rate in terms of slope angle and total buoyancy input. This theory predicts that melt rate varies like the square root of slope, which is consistent with the LES results and differs from a previously proposed linear trend. The derived scalings provide a potential framework for incorporating slope-dependence into parameterizations of mixing and melting at the base of ice shelves.

Long range topography by dispersion unmatched spectral-domain interferometry based on virtually imaged phased array modes.

We propose to realize a long range topography by dispersion unmatched spectral-domain interferometry based on virtually imaged phased array (VIPA) modes. By filtering the continuous spectrum of a supercontinuum source through a side-entrance Fabry-Perot etalon configured at two input angles, two groups of VIPA modes are generated. A method based on unmatched dispersion is proposed for non-aliasing reconstruction of the true depth from the interference spectrum under-sampled at two groups of VIPA modes. With the high spectral resolution provided by the VIPA modes instead of the grating-based spectrometer, only a 10 dB falloff in sensitivity over a range of 10 mm was demonstrated. The feasibility of the proposed method was confirmed by topography of a sample of gauge blocks and a model of three-dimensional (3D) printed tooth. The occlusal surface of the tooth model was further quantitatively evaluated, demonstrating its potential application in long range 3D topography.

Simplified V/f Control Algorithm for Reduction of Current Fluctuations in Variable-Speed Operation of Induction Motors

This paper introduces a straightforward control strategy aimed at the reduction of current fluctuations within the low-frequency domain of open-loop V/f control in induction motor drives. Traditional control techniques necessitate the addition of a current compensator based on motor parameters and the use of digital filters such as band-pass or high-pass filters. These methods, however, rely on precise motor parameters and involve complex filter design and implementation. The proposed control is capable of suppressing current fluctuations without controlling the slip of the induction motor. The proposed control strategy generates the forced rotation angle and command input voltage using the V/f block and outputs the d-axis voltage using a proportional integral controller to keep the d-axis current constant at zero. The difference between the command input voltage and the d-axis voltage is applied as the q-axis voltage and then applied through SVPWM. In order to verify the effectiveness of the proposed control, the proposed control is implemented and analyzed using power simulation based on the results of the analysis of the causes of current fluctuations in the induction motor. Finally, the effect of suppressing current fluctuations of the induction motor is verified through experimental results. In the 10~19 Hz range, where the conventional V/f control method resulted in current fluctuation rates exceeding 10% and peaking at 113.3% at 13 Hz, the proposed method suppressed the fluctuation rate to below 8.6% across all frequencies. This paper validates the effectiveness of the proposed control strategy through these results.

The angle of arrival estimation of frequency-hopping cooperative object based on software-defined radio

The primary objective of this research is to propose and examine a technique for accurately determining the azimuth angle of cooperative objects. The proposed methodology aims were to achieve fast processing, increased precision, and enhanced safety. A transmitter emitting a continuous wave with a hopping frequency was utilized in combination with interferometry techniques to measure the angle of arrival (AOA) between two antennas. The efficient method incorporates a coarse-to-fine strategy that improves processing speed and azimuth angle accuracy and to effectively eliminate any signal interference, a Fourier bandpass filter is utilized. The coarse estimation is performed using the fast Fourier transform (FFT) algorithm, while the fine estimation is achieved using the multiple signal classification (MUSIC) algorithm. The fine estimation involves utilizing coarse angle input and a scan limit of 2.5° that is determined from the largest simulated root mean square error (RMSE) value. Modelling and outdoor testing using software defined radio (SDR) have been carried out to assess the proposed methodology. The results from the analysis indicate that the proposed method produces the desired RMSE estimation of less than 1°, thereby validating its accuracy and effectiveness.