Browse Topic: Optics

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Experimental Validation of Frame-Dependent Gyroscopic Frequency Splitting in a Freely Rotating Tire Using Wireless MEMS Accelerometers and Scanning Laser Doppler Vibrometer2026-01-0700To be published on 06/20/2026
Gyroscopic effects split circumferential traveling-wave resonances of rotating structures into forward and backward branches. This work first analyzes the splitting in the co-rotating (Lagrangian) frame to provide physical intuition for the evolution of the two branches with spin speed. A transformation to the inertial (Eulerian) frame is then derived, showing that the observed frequencies are shifted by a kinematic Doppler-like term that acts with opposite sign on the forward and backward waves, leading to different Campbell-diagram slopes depending on the observation frame. The resulting framework is validated experimentally on a freely rotating, unloaded tire using two complementary sensing modalities: wireless on-tire accelerometers (co-rotating view) and a scanning laser Doppler vibrometer (inertial view). A frequency-domain SVD-based identification (FDD/ODS-SVD) is used to extract poles and deformation patterns over a range of spin speeds, enabling Campbell diagrams in both
del Fresno Zarza, Javier, Naets, Frank
Lightweight Magnesium Nanocomposites with Enhanced Wear Resistance for Landing Gear Application2026-26-0751To be published on 06/01/2026
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
Senthilkumar, N.
Mitigating Cracking in COP Optics through Annealing and Step-Torquing2026-26-0764To be published on 06/01/2026
Polymeric optical materials such as Cyclo Olefin Polymer (COP) are adopted in aerospace lighting systems due to their excellent optical clarity, dimensional stability, moldability and weight saving advantages over glass. However, their relatively low toughness and the presence of residual molding stress make them prone to crack initiation during mechanical fastening. During its installation, crack formation was consistently observed around self-tapping screw interfaces, raising concerns over reliability, maintainability, and compliance with durability requirements. A structured Design of Experiments (DOE) was performed to identify root causes and evaluate potential mitigation methods. The investigation revealed that residual stresses in the COP material, combined with localized stress concentrations during screw tightening, were the primary drivers of crack initiation. Two complementary process improvements were identified and validated as part of mitigation plan: (i) annealing of the
S, Nikhil, Singh, Abhimanyu Kumar, Katageri, Praveen, SP, Pradeep, Chandra, Praveen
Design Optimization of Aircraft Light Optics: Eliminating Fasteners by Flexure-Based Clamp to Mitigate the Crack Formation and Validation through HALT2026-26-0750To be published on 06/01/2026
Aircraft lighting systems play a vital role in ensuring operational safety, visibility, and regulatory compliance. Exterior lighting systems are essential for aircraft identification, navigation, collision avoidance, and ground operations under varying environmental conditions. These systems typically include navigation lights, anti-collision lights, landing and taxi lights. An aircraft lighting system comprises light sources, optical elements, electronic control units, power interfaces, wiring harnesses, and mechanical mounting structures. Among these components, optics are critical as they control light distribution, intensity, color accuracy, and efficiency while withstanding harsh aerospace environments such as vibration, thermal cycling, and aerodynamic loads. Aircraft exterior lights are subjected to severe thermo-mechanical stresses due to aerodynamic loading, vibration, and thermal cycling. The use of high-performance optical polymers such as Cyclo Olefin Polymers (COP
Vialta, Frederico, S, Nikhil, Katageri, Praveen, SP, Pradeep, Singh, Abhimanyu Kumar
Zero-Shot Classification of Additive Manufacturing Anomalies2026-26-0721To be published on 06/01/2026
Additive Manufacturing (AM) process involves building part layer by layer. Some of the AM processes ( Laser and Electron beam based) generate a melt pool during printing process. This melt pool can be captured periodically during AM process using special optical arrangements. These images capture high intensity melted zone, heat affected zone, splattered molten metal particles and overall shape of the melt pool. These images carry similar characteristics for good AM processes within a range. When there is an anomaly the above said characteristics of the melt pool changes, for example a low intensity melted zone signifies low energy condition which can lead to defects like balling etc. Hence the captured image at this condition appears significantly different from other images. The common defects which can be detected by analyzing melt pool images are porosity, spatter, lack of fusion, cracks, balling and keyhole instability. There are many machine learning methods available to quantify
Kuppusamy, Balasundar
Development of Graphene Filled Polypropylene Nanocomposite for Aerospace Application2026-26-0739To be published on 06/01/2026
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
Govindaraju, Parthasarathy
Automating Compliance Workflows in Aerospace Systems: A Scalable Framework for Specification Review and Requirement Mapping2026-26-0714To be published on 06/01/2026
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
Mirani, Harsh, Baviskar, Yash G.
Computational Analysis of Platform Motion and Wave Effects on the Aerodynamics and Wake of the IEA 22 MW Floating Wind Turbine2026-99-17355/22/2026
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
Xie, Bin, Sun, Haiying, Chen, Ye
Design and Research of an Elderly Mobility Assist System Based on Intelligent Power-Assistance Device2026-99-07375/15/2026
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
Yu, Chenxi, Wang, Longyi, Zhu, Huayun, Dong, Yan, Mi, Ruixue, Zhu, Lihong
Design and Implementation of an Intelligent Mobile Waste Classification and Collection Robot System2026-99-07025/15/2026
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
Xia, Ying, Zhu, Huabing, Jia, Ruitong, He, Yifan, Hou, Wentao, Fu, Shaozao, Lin, Jiaoyang
Design of a Novel Intelligent Monitoring Platform for Low and Medium Altitudes2026-99-07395/15/2026
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
Song, Ziang, Gao, Wenxuan, Cao, Xiaochuan, Zheng, Xing, Zhao, Chong
Cabbage Cleaning Device Based on Fischertechnik Model2026-99-07345/15/2026
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
Chen, Yuhui, Zhang, Yixuan, Ruan, Jia, Zhu, Huayun, He, Lianzheng, Zhao, Ping
Adaptive Speed-Regulated Impedance Control for Robotic Ultrasound Scanning: Reducing Constant-Force Tracking Errors2026-99-07515/15/2026
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
Min, Kang, Zhang, Le, Shi, Yudong, Fang, Jin, Mo, Hangjie, Li, Xiaojian
Diffusion Framework with Cross-Modality Fusion Perception for Autonomous Driving in Urban Traffic2026-99-07495/15/2026
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
Qu, Yanwei, Mo, Hangjie
Design of a Modular High-Power High-Repetition-Rate Semiconductor Pulsed Laser Power Supply2026-99-07165/15/2026
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Huang, De, Lu, Jiawei, Yang, Zhiqing, Xv, Ziyi, Xing, Hui
A Comparison between Leica RTC360 and Recon-3D Scan Data in Pre- and Post-Collision Vehicle Documentation2026-01-50304/22/2026
Documenting and mapping using three-dimensional (3D) technologies have become essential in crime- and crash-scene investigations in recent years. Traditionally, this has been accomplished using terrestrial laser scanners (TLS), which often come with significant upfront costs. In contrast, Recon-3D, launched in 2022, leverages the capabilities of Apple’s light detection and ranging (LiDAR) sensor, available in Pro and Pro Max models since 2020. This study aims to evaluate the relative accuracy of documenting vehicles in both pre- and post-collision conditions using these technologies. A deviation analysis was conducted utilizing CloudCompare software to compare point cloud data collected from the Leica RTC360 laser scanner with that obtained from Recon-3D for 7 vehicles in a pre- and post-impact condition for a total of n = 14 vehicles. At the 1, 2, and 3 cm deviation thresholds, the average percent of points which fell below each threshold level for all vehicles was 66%, 91%, and 97
Lim, Jihwa, Liscio, Eugene
Camera Monitor Systems Test Protocols and Performance RequirementsJ3155_202604 (Current)4/13/2026
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
Reconstruction of Pedestrian-Vehicle Collisions Using 3D Skeletal Estimation from Vehicle-Mounted Camera Video2026-01-05754/7/2026
Pedestrian fatalities in traffic accidents continue to rise, with severe injuries often resulting from both vehicle impact and subsequent ground contact, frequently occurring outside the field of view of vehicle-mounted cameras. This study presents a proof-of-concept (PoC) approach for reconstructing three-dimensional pedestrian motion—including occluded regions—using dashcam video. The method integrates 2D human pose estimation (MMPose) and monocular depth estimation (Depth Anything V2),the latter was fine-tuned on a custom dataset, to generate 3D skeletal coordinates.To evaluate motion matching, the reconstructed pedestrian poses were quantitatively compared with a database of vehicle collision simulations using the THUMS human body model and skeletal data representing real-world crash scenarios generated in PC-Crash. Composite similarity indices based on thoracic center of gravity trajectory and torso orientation vectors were employed for this comparison. Preliminary results
Onishi, Koji, Wang, Kewang, Uno, Eriko, Ichikawa, Koji, Tanase, Noboru, Ando, Takahiro
A Dataset for Visual Classification of Flat Tires2026-01-01524/7/2026
Flat tires represent a common yet serious issue in vehicle safety, leading to compromised control, increased braking distance, and potential rim or structural damage when undetected. Conventional tire pressure monitoring systems (TPMS) rely on embedded sensors that can fail, incur high replacement costs, and are not always equipped in older or low-cost vehicles. To address these limitations, this study presents a comprehensive visual dataset for flat-tire classification using computer vision and machine learning techniques. The dataset comprises 600 labeled images—300 flat-tire and 300 non-flat-tire samples—collected from diverse vehicle types, lighting conditions, and viewpoints. This dataset is designed to support the training and benchmarking of lightweight edge-AI models suitable for real-time deployment on embedded platforms. A set of supervised learning models were evaluated. Results demonstrate that visual-based classification provides a cost-effective and scalable pathway
Gunasekaran, Aswin, Govilesh, Vidarshana, Challa, Karthikeya, Maxim, Bruce, Shen, Jie
Self-Supervised Gaussian-Based Framework for Robust Static-Dynamic Decomposition and Real-Time Urban Scene Reconstruction2026-01-00104/7/2026
High-fidelity 3D reconstruction of large-scale urban scenes is critical for autonomous driving perception and simulation. Existing neural rendering methods, including NeRF and Gaussian-based variants, often face challenges like unstable geometry, noisy motion segmentation, and poor performance under sparse viewpoints or varying illumination. This paper presents a self-supervised Gaussian-based framework to address these challenges, enabling robust static–dynamic decomposition and real-time scene reconstruction. The proposed method introduces three innovations: (1) a semantic–geometric feature fusion module that combines semantic context and geometric cues for reliable motion prior estimation; (2) a cross-sequence geometric consistency constraint that enforces depth and surface continuity across time and viewpoints; (3) an efficient Gaussian parameter optimization strategy that stabilizes geometry by jointly constraining scale and normal updates. Experiments on the Waymo Open Dataset
Feng, Runlei, Wang, Ning, Zhang, Zhihao
Investigation of CDI and TCI Ignition Characteristics for Lean Hydrogen-Air Mixtures in a Constant Volume Combustion Chamber2026-01-03274/7/2026
The discharge characteristics of ignition systems critically influence flame kernel formation and ignition stability under lean-burn conditions. This study experimentally compares a transistor coil ignition (TCI) and a capacitor discharge ignition (CDI) system in a constant-volume combustion chamber using hydrogen–air mixtures. The electrical behavior of both systems was first characterized through synchronized measurements of voltage, current, and high-speed imaging under various operating conditions with a resistive spark plug. The CDI system exhibited high-current (≈750 mA), short-duration (≈250 μs) discharges with strong instantaneous power but limited total spark-gap energy (≈5 mJ), while the TCI system produced lower-current, longer-duration (≈3 ms) discharges with higher cumulative energy (≈30 mJ). Flow-field tests revealed that the TCI discharge duration and energy release were strongly influenced by airflow, whereas CDI discharge behavior remained largely unchanged at flow
Cong, Binghao, Jin, Long, Yu, Xiao, Zhou, Qing, Tjong, Jimi, Zheng, Ming
Accelerated Computed Tomography for Spray Characterization2026-01-03414/7/2026
Computed tomography (CT) is a valuable diagnostic technique for visualizing spray plume direction and assessing mixture quality within combustion chambers under engine-relevant conditions. High-speed extinction imaging followed by tomographic reconstruction enables temporally and spatially resolved measurements of liquid volume fraction and plume evolution in multi-plume sprays. Traditionally, tomographic reconstruction requires capturing multiple angular views by rotating the injector and averaging over numerous injections to ensure statistical convergence. This process is time-intensive, particularly due to the large volume of data acquisition and the corresponding delays in data saving, particularly when acquiring many injections per view angle. In this study, we investigate the minimum number of injections required to achieve sufficient CT image quality, thereby significantly reducing experimental time. Two injectors are evaluated: a symmetric 8-hole Spray M injector from the
Yi, Junghwa, Wan, Kevin, Pickett, Lyle
Evaluating Cloud Platforms for Real-Time Cooperative Perception Systems Using RSU Cameras: A Comparative Study of Google Colab, Azure, and AWS2026-01-00184/7/2026
This paper presents a comparative study of three widely used cloud platforms, Google Colab, Microsoft Azure, and Amazon Web Services (AWS), for running a real-time cooperative perception system based on roadside unit (RSU) cameras. The goal is to evaluate the performance, scalability, and cost-efficiency of each platform when handling high-volume video data for object detection, a key task in autonomous driving. A unified perception pipeline using the YOLOv8 Small model was deployed on all platforms, with the same dataset and settings to ensure fair comparison. The evaluation focused on key metrics such as latency, frame processing rate, detection accuracy, cost, scalability, and reliability. The results show that Google Colab is a cost-effective starting point but has limitations in uptime and scalability. Azure offers stable performance and balanced cost, making it suitable for medium-scale applications. AWS delivers the best scalability and speed but at a higher cost. This study
Alkharabsheh, Ekhlass, Alawneh, Shadi, Rawashdeh, Osamah
Temporal Knowledge Distillation for Sparse Stream DETR 3D Object Detection2026-01-00234/7/2026
Sparse Stream DETR 3D object detection has become pivotal in autonomous driving, and previous methods achieve remarkable performance by aggregating temporal information, which also face a balance problem of precision and efficiency. Knowledge distillation offers a promising solution to enhance the efficiency of a small model without incurring computational overhead; however, previous methods lack the exploration of the Temporal Distillation knowledge for the DETR detector. This paper designs a novel Temporal DETR Query Guidance paradigm to impart temporal relation knowledge from a powerful teacher model to enable the student to associate object states across time, leverage historical context. The teacher’s queries grasp the temporal knowledge through self-attention, and the backbone uses the EVA-02 large-scale image model. The student utilizes the teacher's self-attention layer and its own learnable queries to compute the attention as its guidance and mimics the feature interaction
Yan, Yixiong
Ensemble of Experts for Generating Digital Parking Maps from Remote Sensing Images2026-01-01074/7/2026
A digital parking map with precise parking spot geospatial information is crucial for tasks such as automatic valet parking, parking spot recommendations, and parking route optimization. This paper presents a parking map generation scheme that extracts high-definition parking spot geometry from remote sensing images. These images often suffer from occlusion, inconsistent resolution, and varying luminosity conditions. The proposed scheme utilizes a model ensemble paradigm, integrating multiple machine learning models to enhance the accuracy and quality of the generation of parking maps. The experiments demonstrate that the proposed scheme achieves an 80.5% parking spot detection precision and a center-to-center geometric representation error of 0.93 meters.
Shukla, Ajitesh, Cao, Xiaofei, Liu, Yongkang, Takeuchi, Yusuke, Sisbot, Akin
Numerical Framework for Predicting Power Loss and Oil Flow Dynamics in Dip-Lubricated Gear Systems2026-01-04114/7/2026
Oil churning and windage power losses in dip-lubricated gearboxes can significantly affect overall transmission efficiency, particularly at high rotational speeds. As modern gearbox systems are pushed toward higher efficiency and reliability, understanding and predicting these losses becomes increasingly important. In addition to energy dissipation, the associated multiphase flow phenomena—such as oil splashing, thin film formation along gear surfaces, and aeration of the sump—strongly influence lubrication effectiveness, heat transfer, and component durability. Capturing these effects requires a robust numerical strategy that can resolve both power loss mechanisms and multiphase flow dynamics with sufficient accuracy. In this study, a single spur gear is numerically analyzed under varying oil depths and rotational speeds to quantify total power loss and investigate oil flow patterns. The computational approach employs a volume-of-fluid multiphase framework, and the predictions are
Mahyawansi, Pratik J., Haria, Hiral, Pandey, Ashutosh, Khajeh Hosseini D, Navvab
A Comparison of Road Grade Preview Signals from Lidar and Maps2026-01-00264/7/2026
Road grade can impact the energy efficiency, safety, and comfort associated with automated vehicle control systems. Currently, control systems that attempt to compensate for road grade are designed with one of two assumptions. Either the grade is only known once the vehicle is driving over the road segment through proprioception, or complete knowledge of the oncoming road grade is known from a pre-made map. Both assumptions limit the performance of a control system, as not having a preview signal prevents proactive grade compensation, whereas relying only on map data potentially subjects the control system to missing or outdated information. These limits can be avoided by measuring the oncoming grade in real-time using on-board lidar sensors. In this work, we use point returns accumulated during travel to estimate the grade at each waypoint along a path. The estimated grade is defined as the difference in height between the front and rear wheelbase at a given waypoint. Kalman filtering
Schexnaydre, Logan, Poovalappil, Aman, Robinette, Darrell, Bos, Jeremy
An Enhanced Canny-Based Vision System for Vanishing Point Detection in Camera Calibration and Sun Glare Mitigation for ADAS2026-01-00164/7/2026
Edge detection is fundamental for intelligent vehicle applications, directly supporting ADAS functions such as lane detection, obstacle recognition, and scene understanding. The conventional Canny edge detection method exhibits notable shortcomings, especially in color-image processing, adaptive threshold selection, and preserving edge integrity under noisy conditions. In this study, we present an enhanced Canny edge detection framework tailored for ADAS-oriented intelligent vehicle systems, incorporating a quaternion-based weighted averaging scheme for color preservation, adaptive thresholds derived from gradient-amplitude histograms, multiscale edge localization via scale multiplication, and a novel gravitational-field-intensity operator for improved gradient robustness. Moreover, we extend the method to vanishing-point estimation an essential ADAS capability by performing precise intersection calculations combined with clustering techniques such as DBSCAN and RANSAC. Experimental
Uppala, Rohit Raj, Kaye, Murali, Zadeh, Mehrdad, Tan, Teik-Khoon
AI-Driven Data Consistency and Relationship Inference System for Agile Component Library Management2026-01-01094/7/2026
Reliable component libraries are the foundation of the engineering process and the starting point for all intelligence within CAD tools. In practice, however, libraries created and maintained by librarians often contain incomplete, inconsistent, or outdated data. This paper introduces the component data consistency and relationship inference AI system, developed within Amoeba software, which addresses these challenges by improving component library quality. The system uses AI to infer component attributes such as component type, gender, color, material, etc. Moreover, it can identify relationships such as the family a connector is associated with based on its attributes and geometry. The system improves data consistency in areas such as resolving mismatched wire size constraints imposed by the connector and cavity components. It also utilizes computer vision to identify common connector footprints, cavity sizes, and 2D symbol geometries. Deployed within Amoeba software, the system has
Phan, Dung, Horvat, Bryan
Enhancing LiDAR Performance under Fog with Adaptive Multi-Echo and Feature-Based Filtering2026-01-00114/7/2026
LiDAR (Light Detection and Ranging) systems are essential for autonomous driving (AD) and advanced driver-assistance systems (ADAS), providing accurate 3D perception of the surrounding environment. However, their performance significantly deteriorates under adverse weather conditions such as fog, where laser pulses are scattered by airborne particles, resulting in substantial noise and reduced ranging accuracy. This scattering effect makes it difficult to detect objects within or behind particulate matter, posing a serious challenge for reliable perception in real-world driving scenarios. To address this issue, we propose an algorithm that combines adaptive multi-echo signal processing with a feature-integrated, rule-based denoising framework to enhance LiDAR performance in noisy environments. The multi-echo approach selectively utilizes meaningful signal returns by evaluating both intensity and relative echo positions. Based on predefined rules, the algorithm identifies the echo most
Kaito, Seiya, Zheng, Shengchao, Fujioka, Ibuki, Beppu, Taro
Development of Technology to Distinguish Contaminants using LiDAR Near-Field Point Cloud based on Real-Field Data2026-01-00204/7/2026
Reliable environmental perception under adverse and contaminated conditions is a critical requirement for autonomous driving systems. Although LiDAR sensors play a central role in such perception, their performance is significantly degraded by surface contamination caused by environmental factors such as rain, snow, dust, anti-icing materials, and bug splatter impacts. However, most existing public datasets and prior studies rely on simulated or laboratory-generated contamination scenarios, which limit their applicability to real-world autonomous driving. To address this gap, we construct a large-scale real-world dataset collected from approximately 22,000 km of on-road driving across diverse regions of the United States, covering a wide range of naturally occurring environmental contamination conditions. The dataset was acquired using a multimodal sensing platform integrating LiDAR, perception RGB cameras, infrared camera sensors, and external monitoring systems, enabling
Kim, Hunjae
Investigation of In-Cylinder Cycle-to-Cycle Variation Using PIV, LIF and RANS Simulation2026-01-02994/7/2026
Cycle-to-cycle variation (CCV) of combustion is an issue that inevitably arises in internal combustion engines. There is a need to clarify and improve the situation, as well as predict it using computational fluid dynamics (CFD). This study involved carrying out experimental analyses of the factors that cause combustion cycle fluctuations, as well as predicting the CCV of gas flow using RANS. To elucidate the CCV in gas flow and combustion within gasoline engine, simultaneous TR-PIV, PLIF and direct-photography of flame propagation were performed using an optical single-cylinder engine, CCV prediction model for gas flow using RANS was verified. The results revealed the following: The variation in the equivalence ratio per cycle has little effect on initial combustion but does influence IMEP. Evaluating the laminar flame speed, SL and turbulent flame speed, ST as factors determining initial combustion revealed almost no correlation with SL, while moderate correlations were observed
Hokimoto, Satoshi, Moriyoshi, Yasuo, Kuboyama, Tatsuya
Investigation on Microstructure and Mechanical Properties in the Dissimilar Joining of WE43 to AA7075 Alloy using FSW2026-01-02294/7/2026
This research investigates the alterations in microstructure, microhardness, and joint strength resulting from the dissimilar friction stir welding (FSW) of WE43 magnesium alloy to AA7075 aluminium alloy. The study specifically analyses the role of FSW process parameters in the formation of intermetallic compounds (IMCs), the evolution of grain structure, the resultant microhardness distribution across the weld zone, and the joint tensile strength. A comprehensive microstructural characterization was performed utilizing optical microscopy (OM), field emission scanning electron microscopy with energy-dispersive X-ray spectroscopy (FESEM-EDS), electron backscatter diffraction (EBSD), and X-ray diffraction (XRD). These analyses confirmed significant grain refinement in the stir zone and the identification of various IMCs at the weld interface. Microhardness mapping indicated a gradient profile, with the weld nugget exhibiting superior hardness attributed to its dynamically recrystallized
Ahmad, Tariq, Khan, Noor Zaman, Ahmad, Babar, Siddiquee, Arshad Noor
Defect Depth Characterization via Thermally and Pneumatically Induced Shearography for Component Inspection in the Automotive Sector2026-01-02054/7/2026
The following approach introduces a novel method for defect depth characterization using digital Shearography, which is a non-contact, full-field, and material-independent optical interferometric method that enables fast and nondestructive testing (NDT) of components, especially in industrial environments such as the automotive sector. While traditional techniques like computed-tomography, ultrasonic-testing, or thermography can offer depth approximations but they often involve high costs, longer testing times, or limited accessibility. In contrast, the method introduced utilizes various excitation methods in combination with shearographic evaluation to derive procedures for depth estimation of subsurface defects. Recent developments in Shearography have enhanced the method’s robustness and industrial applicability. By detecting the surface deformation behavior in the nanometer range under defined loading, depth-related characteristics of hidden defects can be extracted. Loading can be
Bastgen, Valentin, Plaßmann, Jessica, Petry, Christopher, von Freymann, Georg, Schuth, Michael
A Helical Compression Spring Fracture under Impact Velocity in Pump Operation by Theoretical Study and FEA2026-01-02714/7/2026
Helical compression springs have been used widely in various industries from automotive, aerospace and construction to electronics and medical devices. In the automotive industry, they appear in many places such as suspension, valvetrain, etc., as well in the discharge check valve of Gasoline Direct Injection (GDI) pump, which is the subject of study due to a recent fracture in lab testing. A theoretical study is conducted first to establish the equation governing spring dynamic motion under impact velocity, which can be in high magnitude with surging shock wave along spring axis. A new spring shock wave equation is developed for spring axial motion coupled with coil torsional effect. This newly derived shock wave equation has a broader term than the classic spring formula found in most engineering books. In this paper, it shows that the classic spring shock wave equation is only a special case for the general wave equation newly discovered. Then, a theoretical formula on spring shock
Pang, Michael L., Gunturu, Srinu, Norkin, Eugene
Radar-Based Dynamic Pixel Activation in Camera Sensors for Optimized Image Processing, Power Efficiency, and Thermal Management2026-01-00474/7/2026
The increased integration of radar and vision sensors in modern vehicles has significantly improved environmental perception, safety, and automation. Nevertheless, conventional camera modules capture images in fixed, continuous frames, leading to unnecessary data processing, power consumption, and heat generation in the limited space of small sensors. The paper discusses the technology of Radar Based Dynamic Pixel Activation (RDPA); whereby radar data can be used to dynamically activate specific pixels on the camera sensor, optimizing image capture and processing. Through a systematic literature review of peer-reviewed articles published between 2021 and 2025, we examined the literature on radar-camera fusion, adaptive imaging, and sensor design that is efficient in power consumption. The review indicates a research gap that there is no current paradigm that dynamically activates sensor pixels at the hardware level using radar data. We aggregated ten topical studies and proposed a
Kasarla, Nagender Reddy
Analysis of In-Cylinder Flow for Hybrid Gasoline Engine using High-Speed Particle Image Velocimetry2026-01-02984/7/2026
To increase the thermal efficiency of a hybrid inline 4-cylinder direct injection engine, combustion promotion was carried out by enhancing the in-cylinder flow. The intake port and piston top shape were optimized using CFD. In-cylinder flow analysis in steady flow showed that the mean steady flow tumble ratio with the in-cylinder flow enhancement specification increased to 1.7 compared to 1.0 with the previous model and 1.4 with the early development specification. The limit engine speed, which is the engine speed at when the mean flow coefficient decreases due to the choke, and the mean steady flow tumble ratio with the in-cylinder flow enhancement specification were positioned on the trade-off line between the NA and the TC engine. In-cylinder flow analysis on the single-cylinder optical engine showed that the in-cylinder flow entering the cylinder smoothly flowed to the exhaust side, and the in-cylinder flow descending on the exhaust side was smoothly converted to the upward flow
Okura, Yasuhiro, Urata, Yasuhiro
Monocular 3D Perception and Lane-Aware Bird’s-Eye-View Mapping for Autonomous Driving2026-01-00124/7/2026
Accurate perception of the surrounding environment is fundamental and essential to safe and reliable autonomous driving. This work presents an integrated vision-based framework that com bines object detection, 3D spatial localization, and lane segmentation to construct a unified bird’s-eye-view (BEV) representation of the driving scene. The pipeline provides geometric information on object position and orientation by employing Omni3D to infer 3D bounding boxes of objects from monocular camera frames. Detections are subsequently projected onto a 2D BEV canvas, where object instances are represented with respect to the ground plane for enhanced interpretability. To complement the object-level perception, we utilized YOLOPv2 to perform lane segmentation, producing both lane masks and lane line masks in the image domain for future coordinate transformation. By adopting a pinhole camera model, the coordinate transformation of these masks from the perspective image plane into the BEV canvas
Tan, Lin, Arjmanzdadeh, Ziba, Wang, Hanchen, Li, Taozhe, Hajnorouzali, Yasaman, Burch, Collin, Lee, Victoria, Xu, Bin
In-Situ Raman Measurements of Fuel Dilution of Lubricant Films in a Direct-Injection Spark-Ignition Engine2026-01-03554/7/2026
To measure the fuel proportion within the lubricant film, an in-situ Raman spectroscopy technique was employed in a specially modified single-cylinder direct-injection spark-ignition engine. The engine block was engineered for optical access with a fused silica window, enabling a focused laser beam to probe the lubricant film on the engine liner under motoring conditions. The lubricant used was GTL8 base oil with ZDDP additive, and iso-octane was injected as a model fuel to study fuel-lubricant mixing. A calibration curve was established by recording Raman spectra of known mixtures of GTL8 oil and iso-octane. The Raman intensity ratio of the iso-octane peak to the oil peak was used as a quantitative indicator of fuel concentration. During engine operation, Raman spectra were acquired in real time, on a cycle-by-cycle basis, through the optical window. Upon iso-octane injection, its characteristic Raman peak appeared in the spectrum, and the intensity ratio was referenced against the
Bolle, Bastien, Augoye, Kobi, Wong, Janet, Aleiferis, Pavlos, Hall, Jonathan, Bassett, Mike, Cracknell, Roger
Night Vision Goggles (NVG) Compatible Lighting for Civil AircraftAS5452C (Current)3/13/2026
This SAE Aerospace Standard (AS) will specify what type of NVGs are required and minimum requirements for compatible crew station lighting, aircraft exterior lighting such as anti-collision lights, and position/navigation lights that are “NVG compatible.” Also, this document is intended to set standards for NVG utilization for aircraft so that special use aircraft such as the Coast Guard, Border Patrol, Air Rescue, Police Department, Medivacs, etc., will be better equipped to chase drug smugglers and catch illegal immigrants, rescue people in distress, reduce high-speed chases through city streets by police, etc. Test programs and pilot operator programs are required. For those people designing or modifying civil aircraft to be NVG compatible, the documents listed in 2.1.3 are essential.
A-20A Crew Station Lighting
New MEMS Modulator Offers Significant Advancements in Optical EfficiencyTBMG-547123/1/2026
A new Microelectromechanical system (MEMS) grating modulator has been developed, offering significant advancements in optical efficiency and scalability for communication systems. By integrating a tunable sinusoidal grating with broadside-constrained continuous ribbons, a large-scale aperture of 30 × 30 mm is achieved and supports high-speed modulation up to 250 kHz.
Revealing the Thermal-Gas Stability of Lithium Ion Batteries under Low-Temperature Cyclic Aging2026-01-70282/27/2026
With high energy density and long cycle life, lithium-ion batteries (LIBs) are currently the most promising electrochemical devices for electric vehicles and energy storage. However, the safety and reliability of LIBs can be significantly compromised in low-temperature cyclic due to anode lithium plating and other factors which are still unclear. Therefore, it is essential to reveal the thermal-gas stability of LIBs under low-temperature cyclic. This study investigates the thermal runaway (TR) characteristics and gas production characteristics after TR of 18650-type NCA LIBs across four states of health (SOH), from 100% to 70%. Using Glove box, Electrochemical impedance spectroscopy, Scanning electron microscope, X-ray photoelectron spectroscopy, Accelerating rate calorimetry, and Gas chromatography, the research identifies critical trends in temperature rate, gas composition and explosion risk. After around 150 cycles, there is a significant and rapid decline in capacity. The internal
Wang, Hailong, Wu, Senming, Luan, Weiling, Chen, Haofeng
A Thin-Film Flexible Temperature-Strain Multimodal Sensor for Lithium-Ion Battery Monitoring Based of Laser Direct Writing2026-01-70262/27/2026
Multimodal sensors, capable of simultaneously acquiring multiple physical or chemical signals, have shown broad application potential in fields such as health monitoring, soft robotics, and energy systems. However, current multimodal sensors often suffer from complex fabrication processes and signal decoupling challenges, which limit their practical deployment. To address these issues, this work presents a thin-film temperature–strain multimodal sensor (FTSMS) fabricated via laser processing. The temperature-sensing unit, based on the Seebeck effect, achieves a sensitivity of 9.08 μV/°C, while the strain-sensing unit, utilizing BaTiO₃/AlN@PDMS as the sensitive layer, exhibits a gauge factor (GF) of 43.2. By integrating distinct sensing mechanisms (thermovoltage for temperature and capacitance change for strain), the FTSMS enables self-decoupled measurements over 20–90 °C. Applied in LIB monitoring, it successfully captures real-time temperature and strain variations during charge
Wang, Ziwei, Li, Zhenglin, Gao, Yang, Xuan, Fuzhen
Accidental Dooring Warning and Assist System2026-28-00532/12/2026
Dooring accidents occur when a vehicle door is opened into the path of an approaching cyclist, motorcyclist, or other road user, often causing serious collisions and injuries. These incidents are a major road safety concern, particularly in densely populated urban areas where heavy traffic, narrow roads, and inattentive behavior increase the likelihood of such events. To address this challenge, this project presents an intelligent computer vision based warning system designed to detect approaching vehicles and alert occupants before they open a door. The system can operate using either the existing rear parking camera in a vehicle or a USB webcam in vehicles without such a feature. The captured live video stream is processed by a Raspberry Pi 4 microprocessor, chosen for its compact size, low power consumption, and ability to support machine learning frameworks. The video feed is analyzed in real time using MobileNetSSD, a lightweight deep learning object detection model optimized
C, Jegadheesan, T, Karthi, Gurusamy, Varun Sankar, Balraj, Tharun, Murugaiya, Tamilselvan
Multi-Storey AI Based Parking System2026-28-01292/12/2026
This paper presents a novel AI-based parking management system designed to enhance efficiency, reduce manual intervention, and optimize operational costs in modern parking facilities. By integrating computer vision with infrared (IR) sensors, the system continuously monitors parking areas in real time, accurately detecting vehicle occupancy and dynamically updating the space availability. The hybrid approach minimizes reliance on conventional sensors, improving accuracy and environmental robustness. Additional features include intelligent navigation assistance guiding drivers to available spots and integrated video surveillance for enhanced security through AI-driven suspicious activity detection. The user interface provides real-time updates ensuring a seamless and convenient parking experience. Overall, this system offers a comprehensive solution that advances parking technology through automation, real-time monitoring, and secure, user-friendly operation.
N, Kalaiarasi, Gupta, Shivansh, Hajarnis, Mihir, Anand, Vikas
SAE Truck & Off-Highway Engineering: February 202626TOFHP022/12/2026
AI influence on ICE design Experts offer their outlook on the future of heavy-duty internal combustion engines, and of course artificial intelligence will play a role. Accelerating down the road to autonomy Commercial success of the autonomous truck may be closer than we think. Digital tech a Las Vegas headliner With the rise of AI and other new digital technologies on the horizon, ACT Expo 2026 will be a crucial intersection for industry leaders to map out the route ahead. Editorial CONEXPO debuts - from micro to massive Rolls-Royce pursues pure methanol for marine engines Integrated architectures reshape the mobile-hydraulic ecosystem A proactive approach to hydraulic health in Class 8 trucks Precast concrete bases pave the way for rapid EV charger deployment CONEXPO 2026: Volvo CE to reveal new articulated hauler and short-swing, compact and wheeled excavators Product Briefs SPOTLIGHTS: Imaging/Cameras; Simulation/Analysis Software Q&A Bosch Rexroth: Hydraulics remain relevant in
SBD-YOLO: An Efficient Speed Bump Detector for Active Suspension Preview Control12-09-03-00181/28/2026
Speed bump detection through computer vision and deep learning is essential for advancing active suspension preview control and intelligent driving. Although substantial progress has been made in this field, there remains a need to enhance detection accuracy while reducing computational demands. This article introduces a novel single-stage speed bump detector, the Speed Bump Detector Based on You Only Look Once (SBD-YOLO), which utilizes the YOLOv9 architecture for speed bump identification. To better capture the deep global features of speed bumps, we propose an innovative convolutional module—specifically, a lightweight building block designed for efficient feature extraction—named the Aggregated-MBConv. Furthermore, we design a new YOLO backbone by stacking Mobile Inverted Bottleneck Convolution (MBConv) and Aggregated-MBConv modules, which reduces computational cost while enhancing detection accuracy. Additionally, we introduce a Squeeze-aggregated Excitation (SaE) attention
Mao, Ruichi, Wu, Jian, Wu, Yukai, Wang, Huiliang, Li, Jun, Wu, Guangqiang
Computer Vision Based Driver Health and Wellness Monitoring System: A) Fatigue Detection, B) Emotional Wellbeing2026-26-06391/16/2026
Computer vision has evolved from a supportive driver-assistance tool into a core technology for intelligent, non-intrusive occupant health monitoring in modern vehicles. Leveraging deep learning, edge optimization, and adaptive image processing, this work presents a dual-module Driver Health and Wellness Monitoring System that simultaneously performs fatigue detection and emotional wellbeing assessment using existing in-cabin RGB cameras without requiring additional sensors or intrusive wearables. The fatigue module employs MediaPipe-based facial and skeletal landmark analysis to track Eye Aspect Ratio (EAR), Mouth Aspect Ratio (MAR), head posture, and gaze dynamics, detecting early drowsiness and postural deviations. Adaptive, driver-specific thresholds combined with CAN-bus data fusion minimize false positives, achieving over 92% detection accuracy even under variable lighting and demographics. The emotional wellbeing module analyzes micro-expressions and facial action units to
Iqbal, Shoaib, Imteyaz, Shahma
Artificial Intelligence in Passenger Cars: Unlocking Intelligent Mobility and Human-Centric Vehicle Innovation2026-26-06721/16/2026
Artificial Intelligence (AI) is radically transforming the automotive industry, particularly in the domain of passenger vehicles where personalization, safety, diagnostics, and efficiency. This paper presents an exploration of AI/ML applications through quadrant of the key pillars: Customer Experience (CX), Vehicle Diagnostics, Lifecycle Management, and Connected Technologies. Through detailed use cases, including AI-powered active suspension systems, intelligent fault code prioritization, and eco-routing strategies, we demonstrate how AI models such as machine learning, deep learning, and computer vision are reshaping both the user experience and engineering workflow of modern electric vehicles (EVs). This paper combines simulations, pseudo-algorithms and data-centric examples of the combined depth of functionality and deployment readiness of these technologies. In addition to technical effectiveness, the paper also discusses the challenges at field level in adopting AI at scale i.e
Hazra, Sandip, Tangadpalliwar, Sonali, Khan, Arkadip
Machine Learning Approach to ISO Road Class Prediction Using Multiple Linear Regression2026-26-06671/16/2026
The inertial profiler methodology is traditionally employed in RLDA (Road Load Data Acquisition) to measure road profiles and classify test routes into ISO road classes. However, this approach demands significant time and effort during instrumentation. Also, during data acquisition, laser height sensor data is affected especially during adverse conditions such as rainy seasons or on surfaces with improper reflectivity. Additionally, substantial resources are required for data processing to convert raw measurements into road classifications. To address these challenges, an initial attempt was made to establish a relationship between axle acceleration responses and road profiles, enabling axle acceleration measurements during RLDA to predict ISO road classes. However, this approach relied on a simple linear model that considered only axle acceleration responses, rendering the predictions susceptible to inaccuracies due to varying parameters such as vehicle speed. To overcome these
P, Praveen Kumar, P, Dayalan, Sriramulu, Yoganandam
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