Browse Topic: Imaging and visualization

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In view of the problems that it is difficult to accurately control the spraying area of the mining sprinkler, and the resource waste caused by the mis-spraying material stacking area, as well as the failure of traditional radar monitoring in the complex electromagnetic environment, this paper proposes an anti-splashing system for the mining sprinkler. By combining millimeter wave radar and visual recognition fusion technology, the overall scheme of the anti-splash system is proposed. Then the control simulation of the whole system is carried out. The results show that the problem of poor control in traditional sprinkler operation can be effectively solved, and the sprinkler area can be adjusted intelligently. Finally, in order to verify the accuracy of the algorithm used in this paper, different algorithms are used for comparative experimental verification. The results show that the Modified YOLOv4 algorithm has a high accuracy of 98.75 %, which has good applicability and provides a theoretical basis for subsequent research.
Hou, Lin
g-C₃N₄, a metal-free semiconductor photocatalyst, demonstrates remarkable potential, but its practical application in pollutant degradation is significantly limited by the rapid recombination of photogenerated electron-hole pairs and low photocatalytic efficiency. To address this, a series of magnetic recyclable g-C₃N₄/CoFe₂O₄ composite photocatalysts with different CoFe₂O₄ doping ratios were innovatively designed and prepared via thermal polymerization, sol- gel, and combined with ultrasonic and heat treatment processes. The novelty of this composite design lies in the effective integration of magnetic CoFe₂O₄ with g-C₃N₄ through a heterojunction structure. It substantially boosts the absorption of visible light. Concurrently, it effectively fosters the separation and mobility of photo-induced charge carriers. The composite materials were systematically characterized by X-ray diffraction, thermogravimetric analysis, scanning electron microscopy with energy-dispersive X-ray spectroscopy, photoluminescence spectroscopy, and ultraviolet-visible diffuse reflectance spectroscopy. Using tetracycline hydrochloride as the target pollutant, the photocatalytic activity of the composites was evaluated under visible light irradiation, and the effects of initial concentration, catalyst dosage, and the influence of solution pH on degradation efficiency were also examined. The results indicated that the composite with a CoFe₂O₄ to g-C₃N₄ mass ratio of 1:3 (denoted as 3-CN/CFO) exhibited the optimal performance: a TCH degradation rate of 80.29 % within 105 minutes and a total organic carbon removal rate of 61.63 %. After five consecutive cycling experiments, the degradation efficiency remained above 70 %, demonstrating good reusability and stability. The performance improvement is attributed to the formation of heterojunctions in the composite, which effectively facilitates charge separation, inhibits carrier recombination, and enhances visible light absorption. Furthermore, the inherent magnetism of the composite permits efficient recovery, streamlining its integration into practical applications. Toward the purification of antibiotic-contaminated water, this research proposes a viable method for fabricating highly effective and recyclable photocatalysts.
Hua, LongjunChai, TianWang, YimingZhang, JingHe, Ting
Fatigue design is a key common quality technology for improving the quality control capability of China’s automotive products. The fatigue of materials is a multi-scale damage evolution process. Characterizing and processing the large number of three-dimensional defects inside the material, which have different shapes and distributions, and predicting the material’s lifespan based on the cross-scale damage evolution mechanism, is one of the key technologies for fatigue optimization design. This paper discusses the research methods for the fatigue life of aluminum alloy materials. Firstly, based on the staged fatigue damage experiments, the three-dimensional defect features are obtained through CT scanning and reconstruction, and a defect characterization and processing method based on k-d tree and multi-scale feature pyramid is established to accurately represent the topological and geometric relationships of non-uniformly distributed three-dimensional defects. Secondly, a mathematical model for the evolution of micro-damage and macro-cracks is constructed, and the cross-scale transformation of defects is achieved through hierarchical and recursive methods, revealing the cross-scale evolution mechanism of fatigue damage in aluminum alloy materials. Finally, a remaining life prediction model based on defect information and feature weights is established through the support vector regression algorithm (SVR). This research method can provide technical support for the fatigue life optimization design application of lightweight materials such as aluminum alloys.
Zhang, LiangxiaNiu, ZhijunCheng, FangfangChen, HaoYang, Yali
The distribution of contact stress in roller bearings has a significant impact on operational performance and safety. Firstly, we established a bearing clearance change model that combines interference fit and thermal expansion effects. Then, we studied the clearance changes of key parameters’ influence under different operating conditions. Using Hertz contact theory, we analyze the nonlinear coupling relationship between clearance changes, load distribution, and contact stress. Through MATLAB analytical calculations, load and stress distribution contour maps were obtained under typical operating conditions, which provided theoretical support for bearing optimization design and reliability analysis. The result depicts that an increase in interference fit and temperature difference leads to clearance decrease, triggering a redistribution of contact stress. As clearance decreases, the maximum contact stress exhibits a nonlinear growth trend. To further enhance engineering practicality, this paper uses the MATLAB platform to develop a visualization of digital image processing software. The software enables interactive analysis throughout the entire process of clearance input, stress calculation, and graphical display.
Pang, YiqingCai, HongbinRen, Siyang
The driving cycle is the basic model of certification of vehicle fuel consumption and emissions, or calibration of powertrains. Standard regulatory driving cycles, such as WLTC, in general assume flat roads during their generation and fail to take into account the strong effect that road gradients have on vehicle operation and driving energy consumption. Such a shortcoming, then, leads to gross mismatches in adaptability when used for urban environments with typical hilly topography. To solve this problem, in this paper, we proposed a method for building driving cycles that consider the impact of slope with actual driving data. Initially, high-precision onboard data collectors were used to generate a total sum of 21, 350 km of driving data from the Munich area, thus creating a diversified driving data set with details such as vehicle speed, slope, and environmental information. Subsequently, joint probability distributions of “speed-acceleration” and “slope-slope change rate” are proposed by using the Micro-trip Method, and a novel chi-squared test algorithm is used to obtain a higher fidelity of urban driving cycle representative of typical conditions. Results of the driving cycle results show that the driving cycle built was close to the actual kinematics, indicating a deviation of less than 5%, and can capture the average uphill characteristic of 1.7%, which is quite well represented. Finally, in fact, validation of whole vehicle environmental chamber tests further demonstrates that the energy consumption prediction error of the developed driving cycle is just 2.2%, much lower than 19.1% error of WLTC. It highlights the importance of considering slope parameters in improving the accuracy of energy consumption calibration for an EV operating on complex slope terrains. Furthermore, it underscores that converting the real-world driving data into lab-based driving cycles can reduce the cost and time of actual road tests for Chinese companies going to the overseas markets, thereby offering support for the international marketing strategy of a global database.
Tian, LichenJiang, PingGao, WangLiang, YongkaiMa, KunqiYu, Hanzhengnan
To address the challenges of binocular vision ranging under complex environmental conditions—such as illumination variations, occlusion, and textureless regions, which result in unreliable and non-robust performance—this paper proposes a multi-source heterogeneous sensor fusion ranging method integrating 4D millimeter-wave radar with the YOLOv5-Monster framework. This method is capable of overcoming the issue of limited ranging accuracy in monocular or binocular vision algorithms under non-ideal imaging conditions. This study achieves high-precision spatial perception through the following specific pipeline: First, Zhang’s calibration method is used to obtain the intrinsic and extrinsic parameters of the binocular camera, and stereo rectification is performed on the raw images. Next, a lightweight YOLOv5 network is employed for object detection, while a high-performance Monster network is utilized to generate dense disparity maps, thereby accomplishing initial depth estimation. To mitigate the inherent depth estimation errors of vision-only systems, 3D point cloud data from a 4D millimeter-wave radar is further introduced. By applying a Kalman filter algorithm, the millimeter-wave radar point cloud and visual outputs are fused, achieving spatiotemporal synchronization and optimal state estimation across modalities and effectively correcting biases in visual ranging. Experimental results show that within the full range of 4 to 150 meters, the relative error of the proposed method remains below 5%. Specifically, the relative errors are 1.25% (absolute error: 0.05 m) at 4 meters, 1.40% at 5 meters, 2.99% at 75 meters, and 4.91% at 150 meters. Compared with the vision-only Monster-YOLOv5 baseline method, the relative error at 150 meters is reduced from 13.16% to 4.91%, representing an accuracy improvement of over 60%. Meanwhile, in terms of long-distance error control, the proposed method significantly outperforms traditional stereo matching approaches such as SGBM+YOLOv5 and BM+YOLOv5, reducing errors by more than 20 percentage points. These results verify that deep multi-modal fusion can enhance environmental adaptability and measurement reliability, providing a high-precision and highly robust solution for distance estimation in intelligent perception systems, which holds important theoretical and engineering significance.
Li, FugaiXie, YuwenSu, HaoLiu, DongleiWu, Qiong
This study aims to verify the accuracy and stability of a system used for measuring and analyzing the welding deformation of vehicle bodies under different welding parameters. A 3D laser scanner was employed to capture the surface topography data of the vehicle’s front deck before and after welding. In order to determine the welding deformation, PolyWorks software was utilized for deformation analysis, which processed the 3D scanning data and compared the post-welding data set. A dedicated vehicle body welding deformation measurement system was developed, including hardware configuration and software development. The BP neural network algorithm was adopted to predict the welding deformation, and the results indicated that the deviation between the predicted values and the average experimental measurements was less than 10%. This confirmed the practicality of the BP neural network in predicting welding deformation and highlighted its effectiveness in technical support for the optimization of welding parameters and deformation control in automotive manufacturing.
Li, LinaZhang, YiqiSun, HongchangWei, Xiezhen
The primary mirror support truss of large-aperture segmented telescopes, serving as a critical load-bearing component of the optical system, has its structural stability directly determining the optical imaging quality. This paper adopts a collaborative design method integrating topology optimization and size optimization to address issues, including excessive weight and unreasonable stiffness distribution in traditional support truss designs. First, based on the topology optimization theory of the Solid Isotropic Material with Penalization variable density method, topology optimization was performed on the initial truss structure using finite element simulation software, with the volume fraction as a constraint and the objective of maximizing structural stiffness to determine the optimal material distribution model. Subsequently, the truss structure was reconfigured based on the topology optimization results. Finally, the cross-sectional dimensions of the truss members were selected as optimization variables, and size optimization was performed using the NSGA-II multi-objective optimization algorithm with the objectives of minimizing structural weight and minimizing weighted compliance, while considering constraints such as stress and displacement. The results show that the optimized support truss achieves a 3.9% reduction in weight and a 35.47% decrease in elastic strain energy. This effectively meets the high-precision and lightweight design requirements for telescope support structures and provides a feasible technical solution for the design of large-aperture telescope support trusses.
Tan, DeliGuo, LiquanGao, DedongLiu, ChuanjieDai, XiaodongHuang, Lei
Craters are the primary landmarks used for visual navigation in missions exploring small celestial bodies. However, obtaining high-quality, annotated crater data is often challenging due to limited imaging conditions and strict mission constraints. Conventional semantic segmentation models struggle with limited data and are challenging to train effectively. To overcome this limitation, this study introduces a few-shot segmentation approach for crater detection on small celestial bodies. Our method includes a prototype representation module that constructs class-level prototypes to quickly associate crater regions with their semantic features. This paper also designs an iterative learning module that gradually improves the segmentation output, helping the model better capture detailed edges and structures. Tests on a simulated few-shot dataset demonstrate that our method provides reliable and accurate crater segmentation, achieving a mean intersection-over-union (mIoU) of 88.7, outperforming traditional fully supervised methods.
Li, ShuaiZhu, Shengying
To address the challenges faced by micro flapping-wing flying robots in visual navigation—specifically, the large volume of visual information and the difficulty in transforming it into usable intelligent visual data—this paper proposes a clustering-based data-driven approach for directional and image perception. The aim is to enable intelligent visual navigation for flapping-wing robots. The proposed method performs clustering analysis on gyroscope data from the flapping-wing robot to extract directional features. Simultaneously, it applies clustering techniques to visual images captured by the robot to identify intelligent features such as edges. This approach enables the robot to acquire multiple optimized perceptual data types, thereby enhancing the behavior control system. Through the use of clustering analysis, the method not only improves the effectiveness of visual navigation but also extracts features related to visual targets and environmental information, providing technical support for visual target tracking. The experimental platform consists of a flapping-wing robot equipped with an onboard camera, and the proposed clustering-driven visual image perception approach has been experimentally validated. Experimental results demonstrate the high feasibility and effectiveness of the method in practical applications. The main contributions of this study lie in two aspects: (1) a clustering-driven visual image perception method for flapping-wing robots, and (2) a clustering-based approach for identifying posture and behavioral patterns of flapping-wing flying robots.
Li, ZixuanDing, WeiZhang, FengSong, MinLiu, ZhaomingMiao, LeiLiu, HaotianBai, NingTian, ShenCui, LongWang, Hongwei
Autonomous optical navigation is one of the important navigation methods for the small bodies approach phase. To improve optical navigation performance during the approach phase to a small body, this paper presents a method for extracting the target centroid from sequential optical images. The process begins with fitting a minimum enclosing ellipse to the detected contours in each frame to obtain an initial estimate of the centroid. Building upon this, edge corner points across adjacent images are matched using normalized cross-correlation, and their displacement is tracked using optical flow techniques. The observed pixel trajectories are analyzed, and a predictive model of pixel motion is formulated based on the geometric relationship between the detector and the small body. By combining the directly extracted centroids with the predicted motion of key pixels, a fusion strategy is developed to improve the reliability of the centroid estimation. Finally, numerical simulation results demonstrate that the method significantly improves the accuracy of centroid extraction, thereby enhancing the overall performance of optical navigation during approach operations.
Liu, JingZhu, Shengying
This paper proposes a multi-source dynamic error compensation algorithm for the transfer alignment of airborne optoelectronic payloads. This method addresses performance limitations of micro-inertial navigation systems (micro-INS) in complex dynamic environments, specifically those arising from accumulated device noise and the inability to perform static alignment due to installation errors. The algorithm’s core is the Extended Kalman Filter (EKF) technology. By constructing a “velocity + attitude” matching model between the UAV’s master inertial navigation system (MINS) and the optoelectronic payload’s slave inertial navigation system (SINS), it leverages high-precision MINS navigation information to correct SINS errors. Utilizing a 21-dimensional state space equation and measurement equation, the algorithm achieves real-time estimation and compensation of various errors, including attitude misalignment angles, sensor biases, installation errors, and flexure deformation. Simulation results demonstrate significant alignment accuracy improvement. Post-lever arm effect compensation, velocity errors are stably controlled within 0.01 m/s. Concurrently, flexure deformation angle compensation substantially reduces misalignment angle fluctuations across all directions, enhancing system stability and maintaining low misalignment angles. These findings validate the proposed error compensation strategy’s effectiveness.
Zhang, LuLi, MaoWang, ShiyongLei, Chao
This paper presents an innovative study in exploring, evaluating, and implementing deep-learning architectures for the calibration of multimodal sensor systems. The aim of this paper is to leverage the use of sensor fusion to achieve dynamic, real-time alignment between 3D LiDAR and 2D camera sensors. Static calibration methods are tedious and time-consuming, which is why we propose utilizing conventional neural networks (CNNs) coupled with geometrically informed learning to solve this issue. We leverage the foundational principles of extrinsic LiDAR–camera calibration tools such as RegNet, CalibNet, and LCCNet by exploring open-source models that are available online and compare our results with their corresponding research papers. Requirements for extracting these visual and measurable outputs involved tweaking source code, fine-tuning, training, validation, and testing of each of these frameworks for equal comparisons. This approach aims to investigate which of these advanced networks produces the most accurate and consistent predictions. Through a series of experiments, we reveal some of their shortcomings and areas for potential improvements. We find that LCCNet yields the best results among all the models that we validated.
Karramreddy, Venkat Sai RaxitMitchell, Liam
In this study, high-speed back-illuminated imaging and laser-induced fluorescence (LIF) methods were employed to investigate the impingement behavior of millimeter-sized single isooctane drops on a dry solid wall and various liquid films, including isooctane and glycerol solution films of different concentrations. Various fuel spray impingement scenarios in gasoline direct injection engines were examined. High-speed back-illuminated imaging was primarily used to examine the impact of fuel drops on a dry wall and a fuel film of the same composition as the drops. The LIF method was used to examine the impact of fuel drops on the glycerol solution film, allowing for the distinction between fuel drops and the glycerol solution film. The impingement behavior varied depending on the Weber number of the incident drop and the wall condition. When fuel drops impacted the solid dry wall vertically, they spread into a circular liquid film. The outer edge of the liquid film folded and bulged, and upon reaching the maximum spreading diameter, it maintained equilibrium and did not retract. When isooctane fuel drops impacted the isooctane film, they broke and splashed, with thinner films producing stronger splashes. Additionally, the Weber number of the fuel drops significantly influenced the crown shape and splashing after impact. The impingement behavior of fuel drops on the glycerol solution film was also investigated, focusing on the liquid film morphology after impact. Based on the experimental data, empirical correlations were established between the critical Weber numbers for transitions among different crown morphologies and the dimensionless film thickness under varying film viscosities.
Yang, TianLu, LiliGuo, ZongweiSong, EnzheYao, ChongNing, YilinKe, Yun
This paper presents a monocular vision-based system for high-precision missile pose measurement using ArUco markers and Perspective-n-Point (PnP) algorithms. By deploying 6 × 6 ArUco markers on a cylindrical missile mock-up, the system establishes 3D-2D correspondences between structured-light-scanned models and camera images to solve the PnP problem. The proposed approach integrates optimized ArUco marker recognition — leveraging adaptive thresholding, contour simplification, and grid-based validation — with the Efficient PnP (EPnP) algorithm to achieve real-time pose estimation. Experimental validation demonstrates angular accuracy of ± 0.3° in roll/pitch/yaw and positional accuracy of ± 2 mm within a 2 m range under controlled conditions. The system exhibits robustness against partial occlusions and motion blur, with degraded performance (± 1.2°, ± 5 mm) in extreme scenarios. Key innovations include a streamlined marker detection pipeline and adaptive pose refinement using Levenberg-Marquardt optimization. This work provides a cost-effective, non-contact solution for flight tests, with potential applications in weapon separation testing.
Wang, RuiyangZhang, Chaofan
In order to reduce traffic accidents caused by cars straying from lanes, a lane line recognition and deviation warning system based on machine vision is designed. It mainly includes image preprocessing, lane line detection, and the design of a deviation warning model. “In this study, an ROS-based intelligent vehicle-mounted camera is adopted for road image collection. To reduce the computational load of data processing while guaranteeing the algorithm’s accuracy and reliability, grayscale conversion and region of interest (ROI) extraction are implemented to finish the image preprocessing stage. Additionally, a fusion strategy of global and local thresholds is introduced to enhance both the operational speed and detection accuracy of the algorithm” use the Canny operator for the edge feature extraction; and complete the fitted lane lines with the improved Hough transform. Finally, based on the Kalman filter and camera viewpoint conversion coefficient algorithm, the lane line offset is detected in real time, and the deviation is judged in combination with the monitoring interface. Simulation experiments show that the system is able to effectively recognize the lane line and judge the deviation status under the condition of setting the offset threshold of 70 pixels, which significantly improves the accuracy and real-time performance of the lane deviation warning and provides effective technical support for reducing traffic accidents.
Wang, XufengZhang, ChunshuWang, YanChen, YihuiJi, Rui
Compliance verification in aerospace systems often relies on labor-intensive workflows that demand extensive manual effort to produce structured review documentation and requirement matrices. These processes can span dozens of hours per review, are vulnerable to inconsistencies due to non-standardized annotations, and depend heavily on individual interpretation of fragmented technical sources. With a growing backlog of review tasks and a steady influx of new requests, the need for scalable automation has become increasingly important. This study presents a modular automation framework designed to streamline compliance assessments through intelligent document parsing, requirement extraction, and matrix generation. The system integrates optical character recognition, computer vision, and natural language processing techniques to process both scanned and digital documents. By digitizing data across multiple hardware configurations and automating extraction from diverse technical records, the framework enables consistent evaluation across a broad spectrum of requirement categories. Automation scripts and standardized templates facilitate rapid population of compliance matrices, reducing manual hand-offs and minimizing reliance on specialized expertise. Implementation led to a 39% reduction in turnaround time and a 62% increase in monthly throughput, demonstrating measurable efficiency gains in the compliance review process. This framework exemplifies how intelligent automation can drive operational efficiency, deliver measurable cost savings, and pioneer data-driven and scalable innovation in aerospace compliance engineering.
Mirani, HarshBaviskar, Yash G.
Under a microscope, a bouquet of lollipop-like structures, each smaller than a grain of sand, waves gently in a petri dish of liquid. Suddenly, they snap together, like the jaws of a Venus flytrap, as a scientist waves a small magnet over the dish. What was previously an assemblage of tiny passive structures has transformed instantly into an active robotic gripper.
Medical imaging technology is advancing rapidly, bringing new opportunities and challenges for machine designers. Systems that once required dedicated hospital rooms and significant floor space are becoming more compact, faster, mobile and capable of delivering increasingly detailed clinical insight. From advanced CT scanners to imaging platforms integrated with surgical robotics, imaging equipment is evolving toward more point-of-care (POC) solutions to meet rising expectations for diagnostic accuracy, procedural guidance and operational efficiency.
Polypropylene, a commodity plastic, is the semi-crystalline thermoplastics widely used in high volume for general purpose application. Polypropylene is the macro molecules of soft and weak backbone, which by reinforcement of fillers in different forms such as fiber, spheroids, nanotubes, flakes, etc., can influence its mechanical, thermal, electrical, creep resistance, and flame resistance properties for use in aerospace applications. Currently, polycarbonate and nylon plastics are used in aerospace applications, however, they are expensive compared with polypropylene. In this thesis, efforts are put to study the effect of reinforcement fillers in the properties of polypropylene composite, primarily the mechanical and flammability properties. The matrix element, polypropylene co polymer and reprocessed polypropylene blended in equal ratio, are coupled with the dispersing phases such as graphene, mica, fumed silica, and polydimethylsiloxane polymer. Effect of graphene as reinforcing filler at different weight % to polypropylene composite’s properties are studied and compared with that of the neat polypropylene. Effect of coupling agent, Aminopropyltriethoxysilane (APTES), on mineral fillers and Polydimethylsiloxane polymer (PDMS) used for crosslinking with the polypropylene matrix is also studied and compared using Fourier Transform Infrared Spectroscopy (FTIR) and Scanning Electron Microscope (SEM) techniques.
Govindaraju, Parthasarathy
This study systematically evaluated the wear resilient performance of AZ61 magnesium alloy reinforced with 15 wt.% SiC and diverse amounts of multi-walled carbon nanotubes (MWCNTs) under dry sliding circumstances adopting pin-on-disc apparatus (ASTM G99). To identify the influence of factors like sliding speed (SS) (1-3 m/s), axial load (AL) (10-30 N), and MWCNT concentration (0-3 wt.%) that affect tribological performance, experiments were developed using a Central Composite Design (CCD) under Response Surface Methodology (RSM). SEM micrographs revealed a dispersion optimum near 2 wt.% MWCNT, where CNTs anchor to SiC and bridge the α-Mg matrix, while 3 wt.% shows agglomerates and micro-voids. Findings showed that wear loss (WL) and friction coefficient (CoF) was greatly amplified by increasing AL owing to localized heating and contact stresses. A compacted tribolayer was formed by increasing SS, which decreased WL but marginally raised the CoF. At low AL (10 N), SS (2.09 m/s), and 2.12 wt.% MWCNT, the wear resistance was significantly improved by improving load transfer and creating a lubricating carbon-rich coating, resulting in a decreased WL of 0.006 g. The CoF persisted within the range of 0.19 to 0.28. Agglomeration of MWCNTs caused increased WL and CoF when the MWCNT content is increased above 2 wt.%. Worn-surface microscopy at the optimum showed fine wear tracks and a continuous carbon/oxide glaze, evidencing a lubricious CNT-rich third-body film, whereas high AL/low MWCNT produced deep grooves and delamination.
Senthilkumar, N.
Space vehicle and satellite development programs are driving demand for new small- and medium-sized satellites across commercial and defense imaging, data collection, and other space-based applications.
As satellites take on more onboard processing - from Earth imaging to autonomy - spacecraft computing designers are pushing for higher performance under tight thermal and radiation constraints. Here's how suppliers are approaching heat removal, radiation mitigation and production-scale space-grade computing for LEO and beyond.
This study investigates the unsteady aerodynamic response, wake evolution, and vortex dynamics of an ultra-large floating offshore wind turbine (FOWT) under coupled motion–wave conditions. A high-fidelity aero–hydrodynamic CFD model is employed for the IEA 22 MW reference turbine. Platform pitch and surge motions are prescribed via sinusoidal functions, and wave conditions are independently introduced by considering two representative sea states (H = 4 m and 7 m) and a no-wave case. Results show that pitch and combined pitch–surge motions significantly amplify unsteady aerodynamic effects, increasing peak power from 81.1 MW (P5S0) to 92.6 MW (P5S5), with periodic negative power output and severe dynamic stall. Under strong motion, waves further raise peak power to 93.4 MW (H7P5S5), indicating a coupled amplification effect. Dynamic stall is mainly triggered by pitch motion, expanding in scope and duration with motion amplitude; wave effects on stall remain limited. Platform motion also enhances wake recovery by increasing inflow shear and turbulence, leading to higher turbulent kinetic energy (TKE) and a reduced velocity deficit (ΔŪ). Waves compress the low-speed wake core and reduce ΔŪ from 0.248 (no-wave case) to 0.204 under H7 conditions at x/D = 3.0, with the effect being particularly evident under combined motion. Vortex visualization reveals that platform movement leads to vortex merging, ring thickening, and deflection, with combined motion creating the strongest mixing. Wave-generated vortices interact with tip vortices near the surface, becoming more intense under larger wave heights. In general, platform motion is the main factor in FOWT unsteady aerodynamics, while waves have secondary but cooperative effects by changing inflow structures and aiding wake recovery. This study offers theoretical support and engineering guidance for aerodynamic design optimization and wind farm layout of next-generation ultra-large floating offshore wind turbines.
Xie, BinSun, HaiyingChen, Ye
Robotic ultrasound scanning technology is a research hotspot in the field of medical imaging, and can achieve standardized and high-precision data acquisition. However, large force tracking errors occur during scanning, especially in complex human tissues, which can severely degrade image quality and diagnostic accuracy. Therefore, we propose an adaptive speed-regulated impedance control strategy to address this challenge, which innovatively combines the spline real-time interpolation and impedance control for constant force tracking. Firstly, the discrete ultrasound scanning paths are fitted to generate a smooth and synchronized interpolation trajectory. Then, the speed of the reference trajectory is adjusted in real time based on the Taylor formula to reduce the force tracking error. Experimental verification was conducted, and the results showed that the force tracking error increases with the increase of trajectory speed. In addition, at high speeds (e.g., 10 mm/s), the mean/variance of the force tracking error of the proposed method (0.3067N/0.2784) is reduced by 31.1%/37.4% respectively compared with the mean/variance of the traditional impedance control (0.4452N/0.4448), fully demonstrating the effectiveness of the proposed control strategy.
Min, KangZhang, LeShi, YudongFang, JinMo, HangjieLi, Xiaojian
This paper presents the design of a novel intelligent monitoring platform for low and medium altitudes, aiming to offer a new solution for the development of intelligent equipment operating in this airspace. Current monitoring tasks are primarily performed by fixed-wing and multi-rotor UAVs, but these platforms face significant technical bottlenecks in flight endurance and monitoring precision. This research aims to address these deficiencies. The platform is based on a small-scale unmanned airship featuring a semi-rigid, hybrid lift-body structure. Improvements were made upon the traditional ellipsoidal hull; the hull profile was optimized using a geometric superposition method, introducing an aerodynamic camber line with a maximum camber (m) of 4% to enhance aerodynamic performance at small angles of attack. In terms of its energy system, the platform is powered by a purely electric energy system composed of solar panels and batteries; solar energy is used during the day, while surplus energy is stored in the batteries for night operations, thereby effectively extending flight endurance. For intelligent monitoring, the platform integrates an intelligent recognition and positioning system based on machine vision, which is deployed on a Jetson Nano and utilizes a YOLO11 instance segmentation model. The team has experimentally proven that the platform can effectively achieve intelligent monitoring in low and medium altitude airspace. Furthermore, the structural integrity of the gondola and the aerodynamic advantages of the modified hull have also been verified via simulation analysis. This work provides a new design concept for intelligent monitoring equipment. The platform can also be applied to scenarios such as forest fire prevention, precision agriculture, and long-term ecological monitoring, offering a new solution for the design of unmanned intelligent monitoring equipment.
Song, ZiangGao, WenxuanCao, XiaochuanZheng, XingZhao, Chong
The aging of the population has been a key issue worldwide, with mobility and fall of the elderly an important problem to be solved. In this paper, we propose an elderly mobility assist system based on the intelligent power-assisted device consisting of an assistive cane and an intelligent companion. It has the functions of standing support after falling, daily support and on-site rest. The assistive cane adopts a two-stage expansion mechanism of crank and slider structure, which forms a stable triangular support after unfolding, so that the patient can stand safely. The intelligent companion platform is driven by drive wheels, equipped with pushrod motors and vacuum suction devices, it can automatically approach the user and form an stable support column when the cane is in the out-of reach range; the control system is designed by combining microcontroller, camera object recognition, wristband remote control, to realize automatic steering and autonomous navigation at differential speed. The overall design satisfies the requirements of safety and strength through mechanical verification and stress analysis. The proposed system can help the elderly people to recover from falls better and enhance their independence and safety in their daily walks.
Yu, ChenxiWang, LongyiZhu, HuayunDong, YanMi, RuixueZhu, Lihong
This article focuses on the problem of high labor cost, low processing efficiency and poor automation of the existing equipment in the postharvest processing of Chinese cabbage. It will design and produce an automated Chinese cabbage processing method called Smart Fresh Pack. Root removal, leaf removal, washing, loading, weighing, packaging and labeling functions were integrated, and smart dexterous intelligence was applied to core concepts and this can be used in the bulk production scenario of supermarkets in the city and countryside Compared with traditional assembly line equipment, obvious advantages in terms of structure, function and processing capacity: Key innovations include: Low-pressure air jet cleaning replaces water washing, which prevents a second contamination and weighing error due to surface moisture; pneumatic gripper and multi-DOF robotic arms combine to package and dynamically weigh simultaneously, streamlining these tasks; machine vision relies on an SSD-MobileNetV2 visual model with Sobel edge detection to locate and identify wilted leaves; and pairing with a multi-threaded control structure for millisecond level closed-loop response. I used Fischertechnik models to build and simulate, checking whether the motion logic of this design is reasonable, whether the stresses are safe, and whether the airflow cleaning is effective. This machine finishes the complete processing of one cabbage just within one minute, its modular and its maintainance and scalability aspects are also there, it gives small and medium size agricultural entities a low cost but also very effective clean vegetable processing route, this is truly good for making progress with the auto, standard and green developments within agric prd processing.
Chen, YuhuiZhang, YixuanRuan, JiaZhu, HuayunHe, LianzhengZhao, Ping
End-to-end autonomous driving in urban environments faces three core challenges. First, camera and LiDAR sensor heterogeneity causes cross-modal perception inconsistencies and sensor fusion instability. Second, diffusion models suffer from training instability due to scale variance and distribution changes, which limits generalization. Third, traditional trajectory decoders lack structured interaction with semantic elements, thereby undermining planning rationality. To address these issues, CMFPNet introduces an integrated framework with three key modules. The HGCF-Backbone integrates LiDAR and camera features using channel focus, deformable cross-focus, and state space modeling to enhance semantic alignment. The NST module maps physical trajectories to normalized space, employing truncated diffusion sampling for stable generation in just 2–4 steps. The NDA models trajectory generation as a semantic narrative, utilizing a six-stage semantic attention flow incorporating BEV context, interactive dynamics, and self-states. Experiments on the NAVSIM dataset demonstrate CMFP Net’s superiority over existing baselines, showing outstanding generalization and trajectory stability in challenging scenarios. Notably, the truncated sampling strategy achieves an 8–10× acceleration during inference while maintaining decision accuracy and reducing computational costs. CMFPNet provides a scalable, semantically consistent solution for diffusion-based autonomous driving with significant potential in both research and practical deployment.
Qu, YanweiMo, Hangjie
To address the growing demand for waste management, improve the efficiency and accuracy of waste classification, reduce costs, promote environmental protection and circular economy development, and solve environmental pollution and resource waste problems through technological innovation. This paper proposes an intelligent mobile waste classification and collection robot system. The system consists of a picking mechanical arm subsystem, a waste classification and collection subsystem, a self-moving chassis subsystem, and a solar tracking power generation subsystem. The picking mechanical arm subsystem actively collects waste through a mechanical arm combined with machine vision technology and deposits it into the waste classification device, while the waste classification and collection subsystem completes functions such as classification, compression, collection, and dumping, utilizing a navigation and positioning-driven chassis to achieve autonomous waste collection, simultaneously employing an AI (Artificial Intelligence) interactive voice broadcast device for waste classification promotion. The operation and control of each subsystem are fed back to the client through remote network connection devices, achieving “unified network management.”
Xia, YingZhu, HuabingJia, RuitongHe, YifanHou, WentaoFu, ShaozaoLin, Jiaoyang
The Army requires rotorcraft drive systems to operate for 30 minutes following a loss of lubrication event to make an emergency landing. Coatings research has shown great promise for loss of lubrication, but coating repeatability and quality control is a primary hurdle. The Army partnered with Acree Technologies via a Small Business Innovation Research (SBIR) effort to develop an optimized gear coating for loss of lubrication. The research culminated in a system level transmission experiment that maintained flight relevant torque and speed through a helicopter gearbox without oil for three hours. The authors decided to shutdown the experiment for inspection after three hours of operation without oil because the temperature and vibration signals maintained steady state conditions without signs of failure. Teardown analysis showed the transmission gear surfaces did not scuff, scanning electron microscope analysis showed coating remained on the gear teeth, and cross-sectional SEM analysis showed a measurable coating thickness remaining on the gear teeth after three-hours of operation without oil.
Riggs, MarkPomplon, WilliamFetty, JasonMilligan, RyanWoods, RonWong, KelvinMatzke, CalebJacques, KellyHood, Adrian
This study investigates the aerodynamic response of a small-scale UAV propeller under steady and transient conditions at low Reynolds numbers (104–105;). In this regime, phenomena such as laminar separation, transition, and the formation of recirculation bubbles strongly influence airfoil performance. In addition, the flow response to rapid changes in rotational speed is still poorly understood, as most existing models assume quasi-steady behavior. Experiments were conducted in a low-speed wind tunnel using a commercially available 10-inch class propeller (X500 V2 1045). The propeller was subjected to controlled rotor speed ramps, and phase-locked particle image velocimetry (PIV) was combined with synchronized load measurements to track the flow evolution during acceleration and deceleration. A hysteresis was observed in the thrust response when comparing increasing and decreasing rotational speed at identical operating conditions. At the same time, the PIV measurements reveal that the inflow field and the effective angles of attack at the blade scale evolve dynamically throughout the transient. These findings highlight the importance of transient trajectories in low-Reynolds-number propeller operation and show that quasi-steady models are insufficient to describe the observed aerodynamic behavior.
Ratz, ManuelMendez, Miguel AlfonsoSciacchitano, AndreaSchram, Christophe
This paper presents an experimental investigation of ship airwake-rotor interaction under cruise-only and longitudinal gust conditions (cruise + gust). A model-scale NATO Generic Destroyer and rotorcraft were tested using time-resolved stereoscopic particle image velocimetry, a six-axis force/torque load cell, and flush pressure sensors. Flow structures, pressure distributions, and spectral energy within the pilot workload-relevant frequency bands were analyzed. High-pressure regions on the ship deck surface show the interactions between the ship recirculation region and rotor ground effects from downwash. The reduced forward velocity within the airwake leads to decreased thrust and a nose-down pitching moment across the ship deck. For high-disk-loading rotorcraft, the rotor ground effects are less important than the ship airwake effects. The power spectral densities of CT, CMx, and CMy decrease toward higher frequencies, while the PSDs of CFx and CFy retain comparatively higher energy at the upper end of the full-scale pilot workload frequency band. A maximum increase of 54.3% in the CMy pilot workload factor in the cruise + gust conditions is observed at Ldeck, which denotes a significant rise in the demand of pilot inputs near the ship stern. The overall pilot workload factor in the cruise + gust case increased by 35.6% compared to cruise-only at 1.5Ldeck, and decreases into the deck. Overall, gust-driven airwake dynamics intensify rotor loading and increase pilot workload demands during shipboard helicopter operations.
Yon, StevenLi, Sicheng Kevin
Stacked co-rotating rotors offer a mechanically simple alternative to conventional coaxial counter-rotating systems, but their aerodynamic performance is strongly dependent on both axial and azimuthal blade spacing. This study experimentally and numerically investigates the effects of rotor spacing on the performance and wake structure of model-scale stacked rotors in hover. A dedicated test platform was developed to measure thrust, power, and phase-resolved 2D-3C particle image velocimetry flow fields for two-bladed stacked rotors over axial spacings of Δz/c=0.75 to 5 and azimuthal spacings of ϕ = 0° and 90°. Relative to isolated two- and four-bladed baseline rotors, the stacked configurations exhibited measurable variations in total hub loading and induced flow structure as a function of spacing. The flow field results show that changes in axial spacing alter the relative position of the lower rotor within the convected wake of the upper rotor, producing corresponding changes in inflow, effective angle of attack, and total thrust. Azimuthal spacing further modifies these trends by shifting the phase relationship between upper- and lower-rotor blade passages. To interpret these effects, a coupled blade element momentum theory and Blade Interaction Prediction model was developed. The model captures the primary trends in measured thrust and sectional loading, demonstrating that both wake convection and chordwise blade interaction are required to predict the aerodynamic behavior of closely spaced stacked rotors.
Cotoia, ColbyJohnson, Chloe
Helicopter tail shake constitutes a significant limitation to both passenger comfort and aircraft stability. Under powered descent conditions, elevated Angle of Attack (AoA) cause flow separation around the rotor hub and engine cowling, leading to the development of an unsteady wake dominated by large-scale turbulent structures. To support the helicopter tail shake phenomenon investigation, a dedicated Particle Image Velocimetry (PIV) experimental setup was designed in this work, together with four aerodynamic devices aimed at mitigating tail shake. These components were then tested through a wind tunnel campaign with the PIV setup. The proposed aerodynamic components were conceived to either deflect the hub wake away from the tail empennages or to decrease the Turbulent Kinetic Energy (TKE) within the wake. To achieve these objectives, a dorsal fin, a horse-collar, and two spoiler configurations inspired by automotive applications were designed and experimentally evaluated. The devices were tested both as standalone solutions and in combined arrangements on a scaled helicopter wind tunnel model featuring a rotating hub and blade shanks. The vertical velocity component, was used as an indicator of wake deflection, and the Turbulent Kinetic Energy was used as an indicator of wake turbulence. The Horse Collar and the Large Spoiler showed a reduction in both indicators suggesting possible tail shake mitigating capabilities, and additional improvements were achieved when the two devices were deployed in combination.
Campanardi, Gabriele GiuseppeZanotti, AlexZaccara, MirkoCelada, Luca
This study presents subscale wind tunnel experiments investigating the transient aerodynamic interactions of a rotor during a continuous relative-wind approach toward the landing deck of the NATO Generic Destroyer. Time-resolved rotor loads and stereoscopic particle image velocimetry measurements were used to characterize the interacting ship-rotor flow field under headwind and quartering wind-over-deck conditions. The measurements captured the evolving influence of ship airwake, ground effect, and superstructure-induced recirculation as the rotor moved from downstream to the final hover position over the deck. The results show that rotor thrust, rolling moment, and pitching moment underwent distinct changes throughout the approach, with the loading trends varying significantly with wind-over-deck angle. Time-frequency analysis further reveals that the unsteady rotor response was concentrated in a limited band of frequencies associated with various coherent flow structures shed from the ship superstructure. Spectral proper orthogonal decomposition was used to identify the dominant airwake features responsible for these fluctuations at specific frequencies, including large-scale structures originating from the radar and hangar region. These findings demonstrate that the dynamic approach resolved both slow- and fast-changing transient aerodynamic effects along the approach path that cannot be captured with static hovering measurements.
Chen, Wei-HanRauleder, JuergenJarrad, Dounya
This paper presents a wind tunnel investigation on the interactional aerodynamics of a slowed-rotor lift- and thrust-compounded helicopter model in high-speed forward flight. A systematic configuration study was conducted to isolate the aerodynamic contributions of the main rotor, wings, fuselage, and pusher propeller to the aft flowfield, measured using phase-resolved 2D-3C particle image velocimetry. Measurements were acquired at an advance ratio of 0.5 across multiple rotor thrust levels, lift offset trim states, and propeller rotational speeds. The fuselage induces a streamwise velocity deficit of nearly 50% of the freestream near the tail boom due to oncoming flow blockage. This deficit is modulated by the main rotor and wing configurations. The rotor slipstream partially alleviates the deficit by convecting high-speed freestream flow downwards. Lift offset in the asymmetric half-wing configuration suppresses the rotor wake influence, deepening the velocity deficit relative to a conventional rotor trim state. The pusher propeller partially recovers the streamwise velocity deficit, with propeller performance improving in proportion to the magnitude of the deficit due to reduced climb inflow and increased blade sectional angle of attack. These findings demonstrate that the velocity gradient aft of a compound rotorcraft impacts pusher propeller performance, highlighting the importance of flowfield-informed propeller design for improved performance in high-speed forward flight.
Uppoor, VivekChopra, InderjitJohnson, Chloe
Ultrasonic welding (UW) provides a rapid and efficient method for joining composite components by inducing resin flow through thermally driven diffusion and crystallization at the bonded interface. However, in the absence of a multiphysics modeling framework or a digital twin approach, current practice still depends on extensive trial-and-error testing to determine key welding parameters such as vibration amplitude, weld time, weld pressure, hold time, and downspeed. While in-situ thermal cameras can monitor surface temperatures, the internal temperature at the bonded interface is often significantly higher, introducing the risk of thermal degradation and inconsistent bond quality. To overcome these limitations, GEM developed a high-fidelity multiphysics model to establish a quantitative relationship between process parameters and the evolving temperature field within welded thermoplastic parts. The model integrates coupled mechanical, thermal, and acoustic physics to simulate high-frequency vibrations and static pressure, capture the generation and spatial distribution of heat, and represent the temperature-dependent viscoelastic response that governs bond formation. A validation test matrix was designed by systematically varying weld time and vibration amplitude. Through-thickness temperature distributions were measured using infrared thermal imaging, enabling direct comparison with model predictions. Upon validation, the model was applied for process tailoring, allowing precise control of temperature distribution to achieve target bond strength. This integrated modeling and validation approach demonstrated substantial benefits, including reduced design iterations, accelerated process optimization, and improved quality and performance of welded composite structures.
Walthers, MarkLi, RuiWei, QingxuanLua, Jim
This study examines the aerodynamic interactions between rotors in quadrotor vehicles and their impact on forward-flight stability and performance. Through wind tunnel testing of plus and cross configurations, individual rotor forces and moments were measured across varying hub spacings and advance ratios. Results indicate that rotor-rotor interference significantly alters thrust distribution, inducing unintended rolling and pitching moments. Furthermore, Particle Image Velocimetry (PIV) identified asymmetrical inflow distributions as the primary physical driver of these interactions. While increased hub spacing was found to mitigate aerodynamic coupling. These findings highlight the importance of accounting for aerodynamic interactions in multirotor vehicle design and control, particularly for trimming and optimizing forward-flight performance.
Nunez Garcia, VladimirAtte, AbrahamRauleder, Juergen
A novel airfoil was designed at a Reynolds number (Re) of 50,000 using a multi-objective, multi-fidelity framework based on unsteady Reynolds-averaged Navier-Stokes (URANS) simulations and a gradient-free optimization approach, and compared with the DEA-11 airfoil. Aerodynamic performance and flow physics were investigated through water tunnel experiments, two-dimensional and three-dimensional URANS simulations, and microscopic particle image velocimetry (Micro-PIV), with numerical results validated against experimental data. At Re = 50,000, the optimized airfoil achieves approximately 60% drag reduction at matched lift coefficient, a reduced extent of flow separation, lower pitching moment, with comparable maximum lift coefficient relative to the DAE-11 baseline. In the three-dimensional setting, a classical aspect ratio correction recovers the finite-wing lift closely, while three-dimensional URANS consistently under-predicts drag at positive angles of attack. Measurements and computations confirm that trailing-edge laminar separation bubbles play a significant role in the observed nonlinearity in the lift curve by inducing a virtual camber and effective incidence change. Consequently, airfoil performance in terms of lift-to-drag ratio (L/D) is highly dependent on Reynolds number in the range of Re = 104-105.
Jacob, SnehaMiranda, JuanBenedict, MobleBadrya, CamliJoseph, Cibin
This paper experimentally investigates the effect of positioning of individual blades of a two bladed propeller around the rotor hub on overall noise generated by it. An experimental setup was created to measure noise and performance in an anechoic chamber to carry out parametric study in which axial and azimuthal separations between the two blades were introduced through a custom built rotor hub and balancing weight. The propeller noise that is dominated by tonal components associated with blade passage frequency appears to be influenced by azimuthal separation between individual blades and the broadband components generated by turbulent blade-wake interactions is primarily affected by the axial separation between individual blades. From the present study, it is identified that the rotor configurations with 60° azimuthal and 6 mm (3.2% of rotor radius) axial separation resulted in up to 4.4 dB reduction in Overall Sound Pressure Level (OASPL) and 63.9% reduction in acoustic energy, while the 120° configuration with 6 mm (3.2% of radius) axial separation showed up to 3.8 dB reduction in OASPL and 58.7% reduction in acoustic energy through redistribution in acoustic energy across wider frequency range. Flow-field measurements using Particle Image Velocimetry (PIV) revealed that these improvements are associated with merging of tip vortices, thereby reducing blade-wake interactions, demonstrating that controlled blade spacing through hub modification is an effective passive strategy for reducing UAV propeller noise without affecting the performance significantly.
Mandal, AlakeshMimani, AkhileshAbhishek, AbhishekBaranwal, Saurabh
A wind tunnel investigation to assess the impact of rotor-fuselage spacing on the development of the Vortex Ring State and flow topology is presented. Particle Image Velocimetry was utilised to investigate flow mechanisms across a range of rotor-fuselage spacings and descent ratios, which were compared to that of an isolated rotor configuration. Mean flow data was used to identify coherent flow structures, whilst flow unsteadiness was investigated through statistical analysis of the velocity fluctuations. It was found at cases of Vortex Ring State onset, the presence of the fuselage delays the development of the Vortex Ring State for all rotor-fuselage separation distances tested. Furthermore, certain cases of rotor-fuselage spacings display a rotor-fuselage aerodynamic interaction that results in an increased effective descent ratio.
Croke, AlexanderGreen, RichardWatson, Gwilym
Metal-elastomer bonded components can suffer from manufacturing defects such as porosity and bond-line voids. Nondestructive evaluation (NDE) methods can replace or supplement existing destructive tests; however, implementation can be challenging for manufacturers due to the initial equipment cost, time required per test, and imaging quality. These criteria were used to evaluate shearography, high-resolution ultrasound testing (UT), 2D projection X-ray, computed tomography (CT), and acoustic emission (AE) testing, culminating in trade studies for different sample part types. Experimental work was performed on three samples of varying geometries and sizes with seeded defects, applying feasible NDE methods to each. Shearography succeeded in detecting void defects and flow fronts. X-ray and CT failed to detect flaws in 2 out of 3 part types due to energy and time constraints. UT could not reliably detect defects in parts with complex geometries because of scatter. Acoustic emission reliably detected a seeded knit-line defect.
Mullin, HollyGodinez-Azcuaga, ValeryHobart, AndersonPearson, JohnVadella, RobbieMoose, ClarkSmith, Edward
Accurate monitoring of helicopter operational usage relies heavily on robust regime recognition algorithms. How-ever, evaluating these approaches is challenging when they operate as opaque, "black boxes", as in the case of machine learning-based models. This paper introduces a comprehensive evaluation framework designed to assess regime recog-nition models from a number of perspectives and investigate anomalies in the predicted regimes. Centered around a high-fidelity data set derived from scripted flight tests covering a complete usage spectrum, the developed method-ology provides a comparative baseline. The analytical suite includes 3D spatial visualization tools for flight path mapping, sequential anomaly detection, and confusion matrix metrics. While applying the labeled data set to other platforms presents inherent limitations in terms of mapping features and regimes appropriately, the integrated toolset successfully exposes weaknesses in the model and highlights gaps in training data. Ultimately, this evaluation frame-work enhances the interpretability of model outputs and builds confidence in the use of regime recognition algorithms.
Cheung, CatherineFenev, NikitaBoldis, Alexander
The objective of this study is to experimentally determine the effect a compound helicopter fuselage has on the forward flight performance of a pusher propeller through wind tunnel testing in the Glenn L. Martin Wind Tunnel (GLMWT). This systematic test campaign builds off of previous compound helicopter test campaigns at the University of Maryland (UMD) where various vehicle configurations have been tested at high advance ratios. Present wind tunnel tests were carried out with three distinct vehicle configurations: isolated propeller, isolated fuselage, and finally fuselage with propeller. The effects of fuselage placement on propeller performance are investigated through measuring propeller loads along with two-dimensional three-component phase-resolved particle image velocimetry (PIV) measurements. The PIV measurements are used to inform two different climb velocity models used in Blade Element Momentum Theory (BEMT) to predict the effects of the fuselage on the pusher propeller's performance. Flow field measurements showed a reduction in axial flow velocity closer to the propeller root with the addition of the fuselage, whereas at the outboard 20% of the propeller's radius, the flow remained close to freestream velocity. The thrust over power ratio of the propeller increased in this configuration compared with the isolated propeller, while overall propulsive efficiency remained similar when computed with the scaled climb velocity.
Teodorescu, RaduJohnson, ChloeChopra, Inderjit
The aerodynamics of propeller--wing interactions during a dynamic tiltrotor conversion maneuver were experimentally studied. This investigation builds upon previous work studying the conversion maneuver as a series of discrete tilt angles. This study varied the freestream velocity, rotational frequency, number of proprotors, proprotor spacing, and conversion time period. Wing loads, surface pressures, and particle image velocimetry were used to investigate tiltrotor aerodynamics. For the multi-proprotor configuration, as the conversion period decreased, wing performance increasingly deviated from quasi-static measurements. Dynamic effects decreased as the freestream velocity increased. Minimal dynamic effects were observed when only one proprotor was used. The greatest dynamic wing performance effects resulted from proprotor-proprotor interactions in proximity to the wing. Several nondimensional parameters including the Transition Number and reduced frequency were evaluated to assess how the dynamic effects observed in the wind tunnel may scale to full-size aircraft.
Semelka, AndrewRauleder, Juergen
This experimental study showcases the aeroacoustic sources measured on a NACA0012 airfoil subjected to dynamic stall due to sinusoidal plunging motions. The flow fields are measured on the upper surface of the airfoil using time-resolved particle image velocimetry (PIV), and the broadband surface pressure fluctuations were measured using a flush-mounted microphone probe and the reconstructed pressure field from PIV. Boundary layer separation occurs as the plunging airfoil approaches the maximum plunging velocity. A dynamic stall vortex (DSV) forms on the upper surface near the leading edge. Pressure distribution over the upper surface evolves in response to the movement of the DSV, with the lowest surface pressure observed at the DSV location. Full boundary layer separation results in a temporary reversal of the adverse pressure gradient, and the lowest pressure during moments of full detachment is at the trailing edge. The overall magnitude of the power spectral density (PSD) of the surface pressure fluctuations increases during the stages near the maximum plunging speed, with greater increases observed for the downstroke phase where the DSV is proceeding over the surface. The low-frequency tonal peaks observed at both the DSV location during downstroke and the maximum velocity during upstroke. However, high-frequency broadband fluctuations were measured from the DSV passage during downstroke. These variations of the surface pressure and its broadband components indicate significant unsteady loading and broadband noise sources from a plunging wing.
Alm, AndrewLi, Sicheng
This study experimentally examines the effect of forced boundary layer (BL) transition on the aerodynamic and aero-acoustic performance of a low Reynolds number rotor in hover. An APC 15×4E two-bladed rotor was tested in three configurations: clean, upper-surface trip (U.S.T.), and combined upper- and lower-surface trip (U.S.T./L.S.T.). Surface oil flow visualization was used to characterize the BL structure. A hover test rig was used to measure the static thrust and torque. Acoustic measurements were conducted in an anechoic chamber, with tonal and broadband noise components separated during post-processing. Results show that surface trips effectively force BL transition, increasing turbulent attachment over the blade. Tripped configurations reduced thrust and increased torque but mitigated Reynolds-number sensitivity. Forced transition reduced the tonal noise for all but one case. For the broadband noise, the forced transition increased the noise in the frequency range where turbulent boundary layer-trailing edge (TBLTE) mechanisms dominate, while decreasing the noise in the frequency range where laminar boundary layer vortex shedding (LBL-VS) occurs.
Harris, JosephNarsipur, ShreyasDeters, RobertSriram, Akhilesh
Bench-level boundary-lubricated fretting experiments were conducted to compare the relative wear of all-steel and hybrid material pairs. Roller-on-raceway contacts were simulated using both AISI M50 steel and Si3N4 cylindrical rollers on flat AISI M50 steel disks. The rollers were 9 mm long with a 9 mm diameter. Tests were conducted with constant amplitude, oscillation frequency, and load. All tests were boundary-lubricated with 0.1 ml of DOD-PRF-85734, MIL-PRF-32538, MILPRF-23699, or unclassified ISO VG 68 aviation gear oil. Wear volume was calculated from 3D measurements on the roller and disk samples after each test. Wear tracks were inspected with light and scanning electron microscopy. It was concluded that hybrid pairs exhibited less wear than all-steel pairs when boundary-lubricated with three of the four aviation gear oils. Both hybrid and all-steel pairs exhibited similar wear when boundary-lubricated with MIL-PRF-23699 oil.
Hager, CarlCarl, MatthewBenak, Noah
This SAE Recommended Practice provides test protocols with performance requirements for camera monitor systems (CMS) to replace existing statutorily required inside and outside rearview mirrors for U.S. market road vehicles. This practice expands specific technical content while retaining harmonization with the FMVSS 111 rear visibility standard and other international standards. This is accomplished by defining required roadway fields of view as specific fields of view (FOV) displayed inside the vehicle. Specific testing protocols and/or specifications are added to enhance ease of use using straightforward language, and any specifications are intended to be independent of different camera and display technologies unless otherwise explicitly stated.
Driver Vision Standards Committee
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