Browse Topic: Augmented / virtual reality

Items (663)
Corrosion critically damages structural strength and affects the structural safety, so there is an urgent need for a method that can accurately model and predict corrosion. Digital twin technology offers new methodologies for corrosion research. This study develops a digital twin-enabled virtual-reality mapping model for simulating aluminum alloy pitting corrosion. The model accounts for the effect of temperature on corrosion and establishes temporal correlations between field conditions and simulations through damage factor (DF) analysis coupled with detailed fatigue rating (DFR) methodology. Experimental validation using 7A04 aluminum specimens confirms the model’s reliability, with maturity analysis demonstrating its applicability in aircraft corrosion research. Through numerical simulation methods, this study simulates the evolutionary law of pitting corrosion development, reflecting the level of structural pitting corrosion damage. This investigation establishes a fundamental theoretical framework for condition monitoring and lifetime prediction of aircraft components affected by pitting corrosion.
Lv, ShengliLiu, ChenglongSun, Jingjue
Hybrid electric vehicles rely heavily on battery pack power capability, which is often compromised by non-uniform aging and thermal gradients. Conventional battery models typically use bulk state-of-health metrics, failing to capture localized degradation that leads to current imbalances and reduced pack utility. This paper presents a multi-scale modelling framework that integrates Electrochemical Impedance Spectroscopy data into a fractional-order equivalent circuit model to simulate localized degradation in Lithium Iron Phosphate cells. Results show that the terminal voltage of LFP cells can be accurately modelled using the proposed fractional-order equivalent circuit with a discrete transfer-function implementation, maintaining root-mean-square errors below 20 mV across most state-of-health and state-of-charge conditions. The validated cell model is then extended to a degradation-aware battery pack representation. The battery pack in this work utilizes a 200-kWh, 800 V architecture consisting of five modules connected in parallel, each module composed of 13 parallel strings of 250 series cells, evaluated under multiple degradation scenarios. By integrating this pack model into a Class-8 series hybrid powertrain simulation, this study quantifies how cell-to-cell heterogeneity impacts vehicle performance under the VECTO regional delivery drive cycle. At the vehicle level, these battery constraints influence engine duty cycles and battery pack stress metrics. When localized degradation reaches up to 40% in one module while the remaining modules degrade up to 20% to 30%, such inhomogeneous degradation reduces the minimum pack terminal voltage by approximately 27% and increases peak discharge current by more than 30%, resulting in more rapid degradation. These battery-level limitations translate into higher fuel consumption by up to 6% in a charge-sustaining scenario.
Safavi, Seyed RezaHomayouni, HoomanShoa, TinaWang, JasonMcTaggart-Cowan, Gordon
Augmented Reality (AR) and multimodal human–machine interfaces (MMI)— combining visual overlays, voice, gesture, eye- tracking, and biometric sensing—are maturing into flight-relevant technologies capable of transforming astronaut training and in-orbit operations. These interfaces can reduce task time, lower procedural errors, and mitigate cognitive workload, thereby strengthening crew autonomy and mission safety. Global operational experiences from International Space Station (ISS) augmented- reality trials and related international programs are synthesized to inform the proposed system architecture and validation framework: (i) an overview of India’s current AR/MMI-related ecosystem relevant to human spaceflight, including astronaut training pipelines and research collaborations; (ii) a mission-grade AR/MMI system architecture and multimodal fusion/decision logic suitable for human-rated operations; (iii) algorithms and programming examples for AR-driven finite-state-machine (FSM) procedures and workload-sensitive adaptation; and (iv) simulation-backed datasets across representative procedures indicating approximately 20 to 30 percent task-time reduction and approximately 40 to 50 percent error- rate reduction under controlled conditions (based on ten procedures and twenty-four simulated sessions for workload analysis). The findings reinforce that AR/MMI deployment can improve training throughput, reduce crew fatigue, and increase safety margins when designed with evidence gating, conservative confidence thresholds, and robust fallback modes. Recommendations include establishing a Human Space Flight Centre (HSFC) AR/MMI laboratory, conducting structured A/B validation trials, and committing resources for progressive demonstrations aligned with future in-orbit operations.
Yadav, Anoop Singh
This paper investigates the use of full-body vibrotactile cueing to augment operator perception during swarm teleoperation tasks. Piloted simulations are conducted in a virtual reality (VR) flight simulation environment using a quadcopter swarm model and a nonlinear dynamic inversion (NDI) flight control architecture. A scaled version of the ADS-33 slalom Mission Task Element (MTE) is implemented to evaluate swarm formation maintenance and obstacle avoidance under four experimental conditions: Good Visual Environment (GVE), Degraded Visual Environment (DVE), and each of these conditions augmented with haptic feedback. Haptic cues are delivered through vibrotactile vests and sleeves to convey information on formation deformation and gate proximity. Experimental results involving human participants indicate that haptic feedback improves formation maintenance and increases operators’ situational awareness of follower drone positions without increasing perceived mental workload. While haptic cues provided modest assistance in gate localization, visual conditions remained the dominant factor influencing obstacle avoidance performance. Overall, the results indicate that full-body haptic feedback provides an effective modality for augmenting operator perception and supporting swarm supervision tasks, particularly in visually degraded environments.
Morcos, MichaelCrane, CliftonBreed, AdamKubik, StephenGeiger, DerekLuzzani, GabrieleGary, EvanSaetti, Umberto
For Urban Air Mobility taxis, passengers will experience different levels of heave motion during flight. Researchers at NASA Armstrong Flight Research Center conducted two studies in which passengers were exposed to varying levels of heave motion in the Armstrong Virtual Reality Passenger Ride Quality Laboratory. In the first study, twenty-three volunteers from the Armstrong workforce evaluated the motions on a five-point rating scale and a binary comfort scale; in the second study, fifty volunteers evaluated a flight experience with varying levels of stimuli using a five-point comfort scale and a five-point passenger acceptance scale. This paper combines the results of these two studies to observe the relationship between heave motion and passenger rider quality and acceptance. Both passenger comfort and acceptance were found to decrease with increasing heave acceleration The statistically significant relationship between the magnitude of heave acceleration and passenger comfort for individual studies and combined results are discussed.
Ramia, SaravanakumaarTzarnotzky, UriHendrickson, CoryRoss, JeremyGuy, ColetteHanson, Curtis
A team of researchers at Penn State have devised a new, streamlined approach to design metasurfaces, a class of engineered materials that can manipulate light and other forms of electromagnetic radiation with just their structures. This rapid optimization process could help manufacture advanced optical systems like camera lenses, virtual reality headsets, holographic imagers and more, the team said.
A new system that brings together real-world sensing and virtual reality would make it easier for building maintenance personnel to identify and fix issues in commercial buildings that are in operation. The system was developed by computer scientists at the University of California San Diego and Carnegie Mellon University.
As vehicles evolve toward increased automation and comfort, Power Operated Tailgate (POT) have become a common feature, especially in premium and mid-segment vehicles. These systems, although user-friendly on the surface, involve complex interactions between electronic control units (ECUs), sensors, actuators, and mechanical systems. Ensuring the reliability, safety, and robustness of these features under diverse operating conditions presents a significant validation challenge. Traditional testing methods, which rely heavily on physical prototypes and manual interaction, are often time-consuming, expensive, and prone to human error. Moreover, testing certain safety [3] features, such as anti-pinch or stall protection, under real physical conditions poses inherent risks and limitations. This paper presents a Hardware-in-Loop (HiL)[1] based testing approach for POT [2] systems, offering a safer, faster, and more comprehensive alternative to conventional validation methods. The HiL platform is built around a real-time test environment using Real Time Software, framework, integrated with MATLAB/Simulink [5] based plant models representing motor behaviour, hall sensors, and tailgate dynamics. The ECU under test communicates via CAN [4] and other physical I/Os, while the plant models simulate realistic vehicle responses in real time. The HiL approach enables full automation of functional, diagnostic, and safety validation of the tailgate system including open/close commands, fault injections (open circuit, short faults), latch and sensor logic, and anti-pinch scenarios. This methodology significantly reduces prototype dependence, accelerates ECU software validation, and increases overall test coverage. Results show substantial improvements in fault detection, regression testing efficiency. The proposed solution demonstrates how HiL [1] testing is not only a cost-effective validation method but also a strategic enabler for scalable and safe development of automotive mechatronic systems. This paper concludes by discussing the long-term benefits and future scope of enhancing the HiL setup with remote diagnostics, and seamless integration with other systems. The automotive industry is undergoing a transformation with a growing emphasis on comfort, convenience, and automation. Power Operated Tailgate (POT) have become an integral part of modern vehicles, offering hands-free access, anti-pinch
More, ShwetaGhanwat, HemantShetti, SurajJape, AkshayKulkarni, ShraddhaJagdale, Nitin
Driver-in-the-Loop (DIL) simulators have become crucial tools across automotive, aerospace, and maritime industries in enabling the evaluation of design concepts, testing of critical scenarios and provision of effective training in virtual environments. With the diverse applications of DIL simulators highlighting their significance in vehicle dynamics assessment, Advanced Driver Assistance Systems (ADAS) and autonomous vehicle development, testing of complex control systems is crucial for vehicle safety. By examining the current landscape of DIL simulator use cases, this paper critically focuses on Virtual Validation of ADAS algorithms by testing of repeatable scenarios and effect on driver response time through virtual stimuli of acoustic and optical warnings generated during simulation. To receive appropriate feedback from the driver, industrial grade actuators were integrated with a real-time controller, a high-performance workstation and simulation software called Virtual Test Drive (VTD). By developing an integrated solution for acquiring driver response, creation of scenarios and evaluation of control systems, this paper focuses on virtual validation of systems in a time saving and cost-effective manner.
Sharma, ChinmayaBhagat, AjinkyaKale, Jyoti GaneshKarle, Ujjwala
The integration of Advanced Driver Assistance Systems (ADAS) into modern vehicles necessitates innovative solutions for interior packaging that balance out safety, performance, and ergonomic considerations. This paper introduces an inverted U-shaped steel tube cross car beam (CCB) as a superior alternative to traditional straight tube designs, tailored for premium vehicle instrument panels. The U-shaped geometry overcomes the limitations of straight tube beams by creating additional packaging space for components such as AR-HUDs, steering columns, HVAC systems, and electronic control units (ECUs). This geometry supports efficient crunch packaging while accommodating ergonomic requirements like H-point, eyeball trajectory, and cockpit depth for optimal ADAS component placement. The vertical alignment of the steering column within the U-shaped design further enhances space utilization and structural integrity. This study demonstrates that the inverted U-shaped CCB is a transformative solution for ADAS packaging, providing superior durability, crash performance, and knee injury mitigation compared to traditional straight tube designs. By addressing challenges such as crunch packaging, structural stiffness, and manufacturing efficiency, the U-shaped beam sets a new standard for global automotive platforms. The findings underscore its potential to revolutionize vehicle interiors, enabling advanced technology integration while maintaining safety and efficiency.
Mahajan, Ajay SenuRegatte, GaneshNagarjuna, KamisettiSahoo, SandeepUdugu, KumaraswamyJC, Sudheera
The road infrastructure in India has complex navigational challenges with most of the road unstructured especially in rural areas. Decision-making becomes a challenge for drivers in unpredictable environments such as narrow roads, flooded roads and heavy traffic. In this paper, an Augmented Reality based ML-Algorithm for Driver Assistance (ARMADA) has been proposed that improves awareness to safely maneuver in these conditions. The methodology for development and validation of this Augmented Reality (AR) based algorithm contains multiple steps. Firstly, extensive data collection is conducted using real time recording and benchmark datasets like Berkeley Deep Drive (BDD) and Indian Driving Dataset (IDD). Secondly, collected data are annotated and trained using an optimal machine learning (ML) model to accurately identify the complex scenario. In third step, an ARMADA algorithm is developed, integrating these models to estimate road widths, detect floods and provide seamless driver assistance in a Human Machine Interface (HMI). Finally, proposed algorithm undergoes validation to ensure its effectiveness and accuracy in real-world practical scenarios. The result of this study concludes significant improvements in driver decision making and safety of the driver in complex maneuvering.
Anandaraj, Prem RajSivakumar, VishnuThanikachalam, GaneshL, RadhakrishnanMotoki, YaginumaSelvam, Dinesh Kumar
Virtual Reality technology is emerging as a transformative solution in the manufacturing industry. It offers significant advantages over traditional tools like Tecnomatix Process Simulate in assembly & ergonomic simulations. Analysis using PS is time-consuming and lacks real-time human interaction as it relies on detailed modelling and sequential workflows, which will delay the identification of assembly no-build conditions and ergonomic issues. This paper evaluates the time and the cost-saving potential of VR in assembly processes and explores its role in minimizing the need for physical prototypes across various stages of vehicle development. VR provides interactive environments, enabling interaction with 3D models and real-time collaboration with various teams across the globe. This leads to faster identification of assembly process flaws, quicker iteration cycles, and a reduced need for physical prototypes in the station development process for the lines. VR allows individuals to experience realistic simulations of assembly processes with multiple scenarios, without the risk of real-world safety consequences. This simulation approach through VR technology facilitates real-time ergonomic predictions, quick and accurate simulation of various assembly scenarios during the station development process before the production with minimal iterations which will ensure the assembly processes are getting optimized in the early stages of product development. It proves to be a superior alternative for validating assembly feasibility, reducing time in process sequence building, and achieving faster time to market in manufacturing. By minimizing iterations in physical prototyping and extensive validation and testing of assembly processes, VR significantly impacts time & cost.
Nagendran, Rakesh Kumar
The increasing adoption of electric vehicles (EVs), efficient and accurate battery modeling has become crucial for reliable performance evaluation and control system design. However, maintaining high accuracy in simulations generally requires complex computations, which can limit real-time applicability and scalability. High-fidelity battery models often require significant computational time, making them unsuitable for real-time simulations and large-scale system integration. This paper presents the application of Simulink Reduced Order Models (ROM) to simplify the simulation of EV batteries while maintaining acceptable levels of accuracy. The EV simulation environment has been developed in MATLAB/Simulink to analyze Battery Management System (BMS) control system design and assess EV system level performance. This simulation platform consists of BMS and other important EV controller models and high-fidelity plant models for battery and powertrain systems. While these high-fidelity models enable accurate virtual testing and control logic development, they also impose substantial computational requirements, leading to slower simulation performance. This paper addresses these challenges by proposing a Reduced-Order Modeling (ROM) approach, leveraging Artificial Intelligence (AI) techniques to significantly improve system-level simulation efficiency. In this study, a computationally intensive high-fidelity EV battery pack plant model, which was originally modelled using Simscape battery library was replaced with trained Neural State Space (NSS) ROM model using MATLAB/Simulink tool. A low-order nonlinear ROM based on the Neural State Space (NSS) architecture is developed using deep learning methods, effectively acting as a surrogate for the computationally intensive high-fidelity battery model. The trained ROM was integrated into the Simulink system-level simulation platform and benchmarked against the original high-fidelity model. Simulation results demonstrate that the ROM effectively captures the essential dynamic behavior of the battery while significantly reducing computational costs compared to the baseline high-fidelity Simscape model. The proposed approach achieves a notable reduction in simulation time while maintaining acceptable accuracy under the evaluated drive cycle and operating conditions. This work demonstrates the practicality of ROM-based modeling as a key facilitator for efficient EV battery analysis, design optimization, and control strategy development.
Vernekar, Kiran
The automotive industry faces increasing challenges in managing vehicle lifecycle complexity, including inefficiencies in design, manufacturing, and maintenance. Traditional reactive maintenance approaches often lead to unexpected downtimes, increased costs, and diminished customer experience. Moreover, rapidly evolving technologies demand agile and adaptive development processes. The Digital Twin (DT) concept which involves leveraging advanced technologies to create virtual representations of physical systems offers a promising solution by enabling real-time simulation, prediction, and optimization throughout the vehicle lifecycle. By bridging physical and digital realms, Digital Twins provide a powerful tool for improving system efficiency, adaptability, and quality. This paper highlights the benefits of applying Digital Twin principles at the systems engineering level, offering a solution for more resilient, innovative, and customer-centric vehicle systems. This study explores the integration of Digital Twin technology within a Model-Based Systems Engineering (MBSE) framework, focusing on system-level applications. Using the example of a feature within Seating Systems, we demonstrate how Digital Twin can streamline feature development, improve integration across component-level designs, and proactively identify potential issues. The proposed approach aims to reduce development iterations, enhance feature robustness, and improve user experience.
Agarwal, UjjwalSabharwal, Shambhavi
This paper presents a bidirectional digital twin developed for the Fischertechnik Smart Factory Kit, enabling real-time simulation and validation of production line modifications prior to actual deployment. The digital twin integrates with a Siemens Programmable Logic Controller (PLC) to mirror real-world operations, capturing live production data and visualizing key factory parameters, such as product, process, and resource metrics within a 3D environment. Engineers can test various optimization scenarios by adjusting robot speed and path, conveyor speeds, part & process sequences, and modifying equipment layout sizes to enhance efficiency. Based on the optimization scenarios, the best-performing configurations are identified using metrics such as throughput, cycle time, and resource utilization. Once validated, these changes are directly deployed to the PLC, ensuring seamless implementation. Beyond capacity optimization, this solution enhances overall production efficiency by minimizing idle time and parts waiting time, balancing workloads, and reducing unplanned disruptions. Additionally, by virtually simulating product variations and process changes, the digital twin helps identify design simplifications, reduce product complexity, and streamline manufacturing workflows. A digital twin of the manufacturing system serves as an integrated solution, unifying capabilities such as predictive maintenance, efficiency monitoring, simulation, and analytics in real time. By bridging technology gaps and offering a comprehensive view of the entire production process, it enhances decision-making, maximizes resource utilization, and facilitates seamless technology adoption across the factory. This approach significantly reduces downtime, accelerates response times, and boosts automation, demonstrating the transformative potential of digital twins in optimizing manufacturing operations [1].
Kumar, RahulSingh, Randhir
Advanced Driver Assistance Systems (ADAS) are instrumental in improving road safety and minimizing traffic-related incidents. However, their development and validation processes are resource-intensive, requiring substantial time, cost, and domain-specific expertise. Moreover, real-world testing introduces significant safety challenges. To address these issues, virtual simulation platforms offer high-fidelity environments for the secure and efficient testing of ADAS functions. This research presents a virtual validation framework for a Traffic Jam Pilot (TJP) algorithm utilizing such simulators. The framework features detailed models of camera and radar sensors, capturing essential parameters like detection range and field of view, alongside a vehicle plant model and road infrastructure modeling that includes elements such as curvature, slope, banking angles, and varying lane widths. A perception stack is developed using synthetic sensor data and is integrated with the TJP control algorithm to manage the Ego vehicle in dynamic traffic scenarios, including stop-and-go and cut-in maneuvers. The approach enables comprehensive system evaluation in a risk-free environment, significantly reducing development complexity and cost. A key contribution of this work is the generation of virtual test scenarios derived from real-world driving data, allowing for direct, scenario-specific comparisons between simulation outputs and physical-world behavior. The findings underscore the potential of simulation-based validation as a scalable and reliable pathway toward deploying ADAS functions with improved safety and efficiency.
Agrawal, MridulIthape, AvinashSharma, PrashantTrivedi, Abhishek
Power electronics switching applications are essential for energy management and conversion in automotive electric vehicles (EVs). This paper focuses on DC-DC converters, particularly the integration of 48V DC-DC converters in modern automotive systems. These converters are crucial for efficient power delivery to auxiliary systems such as infotainment, lighting, safety electronics, and thermal management units. In mild hybrid electric vehicles (MHEVs), 48V systems support advanced features like regenerative braking, electric turbocharging, and start-stop functionality. To ensure the reliability, safety, and performance of these converters, Hardware-in-the-Loop (HIL) testing has emerged as a powerful validation technique. HIL enables real-time simulation of the converter’s electrical environment and load conditions, allowing comprehensive testing of the control system without high-level voltage, significantly reducing development time, cost, and risk. The methodology involves utilizing HIL testing to simulate the electrical environment and load conditions of 48V DC-DC converters in real-time. Various control algorithms, such as Voltage Mode Control, Current Mode Control, Digital PID, and Model Predictive Control (MPC), are employed to ensure voltage regulation, load response, and system stability under dynamic operating conditions. Key parameters simulated using HIL for software closed-loop operation include output voltage and current regulation, efficiency, and power loss, switching frequency behavior, closed-loop stability and dynamic response, power quality, ripple, diagnostic and fault-handling capabilities by adhering to ISO26262 safety standards. By simulating various conditions, potential software issues dependent on hardware can be identified and addressed early in the development cycle, ensuring seamless integration of hardware and software components. The advantages of HIL testing include safe and repeatable fault injection, real-time performance analysis, early-stage software validation, and the ability to simulate complex load profiles and environmental conditions. As automotive systems become more electrified and software-driven, HIL testing is indispensable for accelerating innovation while ensuring compliance with safety and performance standards.
Yadav, VikaskumarWakure, Vinod
Distributed drive steer-by-wire chassis has significant potential for enhancing vehicle dynamics performance, while also presenting great challenges to vehicle dynamics control. To address the coordination among multiple chassis subsystems and the coupled control allocation of longitudinal and lateral tire forces, this paper proposes a centralized control framework based on optimal yaw moment control. By analyzing the impact of longitudinal and lateral tire forces on vehicle yaw moments, a method for allocating longitudinal and lateral forces with maximum yaw moment as the objective is proposed. On this basis, a hierarchical control architecture is designed, including the driver control layer, motion control layer, tire force allocation layer, and actuator execution layer, to achieve centralized domain control of longitudinal and lateral dynamics in distributed drive steer-by-wire chassis. Finally, the proposed centralized controller is validated using offline simulation and real-time simulation. The results show that the proposed centralized controller enables precise trajectory tracking with a longitudinal error below 0.2 m and a lateral error constrained within 0.1 m, while reducing the average tire adhesion coefficient by 13% compared to decentralized control. The controller effectively maintains tire forces within a stable operational region, thereby significantly enhancing vehicle stability.
Wu, DongmeiGuo, ChunzhiLiu, ChangshengXia, XinLi, MiaoLiu, Wei
The integration of sensory stimuli in Virtual Reality remains a challenge in the automotive industry, especially regarding consumer perception and immersive experience. This study aims to examine the applications of virtual reality in the automotive industry, analyzing how the integration of sensory stimuli can impact consumer perception, the technological challenges involved, and the opportunities for innovation in the sector, contributing to the advancement of immersive automotive experiences. We adopted a literature-based analytical approach, involving the review of VR technologies applied to product design, consumer interaction, and sensory integration, with a focus on tactile, visual, and olfactory stimuli. The analysis considered technological, cultural, and market factors, ensuring a comprehensive understanding of the current state and challenges of VR adoption in the automotive context. As a result, we identified key benefits of VR in improving design, testing, training, and marketing processes, as well as challenges related to stimulus synchronization, sensory latency, device precision, and cultural sensory preferences. These findings demonstrate the significant potential of multisensory VR to enhance user experience and strengthen consumer-brand relationships in the automotive industry. The study provides a critical reflection on the technological and cultural barriers to Virtual Reality sensory integration, with potential implications for product development and customer engagement in automotive and immersive experience fields. Future work will focus on empirical validation and technological advancements to overcome existing limitations and further consolidate the use of multisensory solutions.
Ramos, CatharinaThasla, YasmimRodrigues, DanielaAlfonso, MarcioLeite, RodrigoRibeiro, EuláliaWinkler, Ingrid
Warranty claims function as primary source of characterizing field failures across industries, wherein appropriate classification of these claims is critical for further analysis. The classification of warranty claims is a highly laborious effort, involving significant man-hours of warranty analysts. This can be highly optimized and made efficient using direct interpretation of the claim data on 3D model using unity game engine. Additionally, the color perception technique using immersive technology (AR/VR) can help to identify the vital few & drive prioritization of the field failures leading to faster problem resolution. The capabilities of UI/UX & advanced visualization are integrated to develop novel methods to classify the warranty claims & interpret it on a 3D model using immersive technology which is novel and one of its kind in industry. Unique characteristics of this tool is it focuses on the warranty claim classification by claim cost & count of claims and presents the heat map (Red-High, Yellow- Moderate, Green- Low, Gray – No claims) which helps in faster visualization of the claims on actual product. We have also integrated the respective corrective action associated for a failure mode which can help us to understand the status of actions plan to be deployed / closed and track for its future effectiveness. The NLP algorithm has been trained through a multi-representative training dataset which covers all the failure categories based on experiential knowledge. Cross-validation technique is used for optimizing the machine learning algorithm parameters. The test datasets consisting of different mix of warranty claims were then fed into the model wherein the prediction accuracy of more than 90% achieved over multiple runs consistently.
Nankery, Viveksavadatti, SandeepShete, AtulApkare, SanketGanapathi, Poongundran
Virtual reality (VR), Augmented Reality (AR) and Mixed reality (MR) are advanced engineering techniques that coalesces physical and digital world to showcase better perceiving. There are various complex physics which may not be feasible to visualize using conventional post processing methods. Various industrial experts are already exploring implementation of VR for product development. Traditional computational power is improving day-by-day with new additional features to reduce the discrepancy between test and CFD. There has been an increase in demand to replace actual tests with accurate simulation approaches. Post processing and data analysis are key to understand complex physics and resolving critical failure modes. Analysts spend a considerable amount of time analyzing results and provide directions, design changes and recommendations. There is a scope to utilize advanced features of VR, AR and MR in CFD post process to find out the root cause of any failures occurred with advanced visualization. This paper focusses on how VR can be used for 3D CFD detailed result analysis. Various physics such as Conjugate heat transfer (both steady state and transient), Discrete phase model, and Flow analysis have been integrated with VR in this study. Few case studies are also discussed, demonstrating how VR helped in understanding complex physics and provided directions for product development. After treatment systems have complex multi physics involved. Using VR, droplet interaction with exhaust gases inside the system helped in better understanding of complex physics. Steady state thermal simulation is another area where VR visualization helps to understand high temperature plume in proximity regions. This paper also focusses on the challenges experienced during integration and usage of VR. ANSYS FLUENT with Ensight are primary tools which have integrated with VR setup to utilize benefit of VR. Automated scripts have been created for ease of VR hand tools usage. Analyst issues in current post processing methods and solutions to it through VR are also discussed in this paper. Advance level implementation of AR is demonstrated in this study.
Savitha, BhuduriSharma, SachinShree, Deepa
Off-highway vehicles (OHVs) are vital for India’s construction, mining, agriculture, and infrastructure sectors. With growing demand for productivity and sustainability, the need for efficient customer support and precise diagnostic techniques has become paramount. This paper presents a comprehensive study of challenges faced in India, current and emerging diagnostic technologies, troubleshooting techniques, and strategies for effective customer support. Case studies, tables, and diagrams illustrate practical solutions.
Mulla, TosifThakur, AnilTripathi, Ashish
Virtual Reality (VR) systems are increasingly integrating haptic feedback to increase the level of immersion in virtual environments. This study is designed to investigate the impact of varying fidelity levels on the user experience when interacting with a tablet touchscreen User Interface (UI) in a virtual environment. Participants take part in touchscreen gesture-based tasks in different haptic fidelity levels, including no gloves, low haptic fidelity vibrotactile gloves, high haptic fidelity pneumatic gloves, and a real-world control condition. This study was designed to measure the user experience, which includes presence, embodiment, and system usability using qualitative surveys along with quantitative performance metrics. This study aims to understand how haptic feedback impacts the user experience to facilitate more informed employment of VR technology in training, simulation, and rapid prototyping.
Al-Shubeilat, FaresAthamnah, SolafAlJundi, Abdel RahmanBrudnak, MarkWood, RyanLouie, Wing Yue GeoffreyRawashdeh, Osamah
Navigation in off-road terrains is a well-studied problem for self-driving and autonomous vehicles. Frequently cited concerns include features like soft soil, rough terrain, and steep slopes. In this paper, we present the important but less studied aspect of negotiating vegetation in off-road terrain. Using recent field measurements, we develop a fast running model for the resistance on a ground vehicle overriding both small vegetation like grass and larger vegetation like bamboo and trees. We implement of our override model into a 3D simulation environment, the MSU Autonomous Vehicle Simulator (MAVS), and demonstrate how this model can be incorporated into real-time simulation of autonomous ground vehicles (AGV) operating in off-road terrain. Finally, we show how this model can be used to simulate autonomous navigation through a variety of vegetation with a PID speed controller and measuring the effect of navigation through vegetation on the vehicle speed.
Goodin, ChristopherMoore, Marc N.Hudson, Christopher R.Carruth, Daniel W.Salmon, EthanCole, Michael P.Jayakumar, ParamsothyEnglish, Brittney
Navigation in off-road terrains is a well-studied problem for self-driving and autonomous vehicles. Frequently cited concerns include features like soft soil, rough terrain, and steep slopes. In this paper, we present the important but less studied aspect of negotiating vegetation in off-road terrain. Using recent field measurements, we develop a fast running model for the resistance on a ground vehicle overriding both small vegetation like grass and larger vegetation like bamboo and trees. We implement of our override model into a 3D simulation environment, the MSU Autonomous Vehicle Simulator (MAVS), and demonstrate how this model can be incorporated into real-time simulation of autonomous ground vehicles (AGV) operating in off-road terrain. Finally, we show how this model can be used to simulate autonomous navigation through a variety of vegetation with a PID speed controller and measuring the effect of navigation through vegetation on the vehicle speed.
Goodin, ChristopherMoore, Marc N.Hudson, Christopher R.Carruth, Daniel W.Salmon, EthanCole, Michael P.Jayakumar, ParamsothyEnglish, Brittney
Virtual reality (VR) video games that combine screen time with exercise are a great way to get fit, but game designers face a major challenge — adherence to ‘exergames’ is low, with most users dropping out once they start to feel uncomfortable or bored.
EPFL researchers have developed a customizable soft robotic system that uses compressed air to produce shape changes, vibrations, and other haptic, or tactile, feedback in a variety of configurations. The device holds significant promise for applications in virtual reality, physical therapy, and rehabilitation.
While semi-autonomous driving (SAE level 3 & 4) is already partially a reality, the driver still needs to take over driving upon notice. Hence, the cockpit cannot be designed freely to accommodate spaces for non-driving related activities. In the following use case, a mobile workplace is created by integrating a translucent acrylic glass pane into the cockpit and introducing joystick steering of the car. By using the technology Virtual Desktop 1, which is a software layer, any desktop application can be represented freely transformable on arbitrary physical and virtual surfaces. Thus, a complete Windows environment can be distributed across all curved and flat surfaces of an interior. The concept is further enhanced by a voice-driven generative AI which helps to summarize documents. A physical and a virtual demonstrator are created to experience and assess the mobile workspace, the well-being of the driver, external influences, and psychological aspects. The physical demonstrator is a 1:1 partial interior mockup with projection-based interactive surfaces. The virtual demonstrator represents the same interior model using the simulation technology TRONIS® and is perceptible through virtual reality (Apple Vision Pro). The demonstrators enable a user-centered design process and facilitate the creation of innovative designs that can be experienced realistically. The technological concepts can also be adapted for other non-driving related activities such as relaxation and entertainment, allowing for the application of many use cases and a broad variety of potential users.
Beutenmüller, FrankReining, NineRosenstiel, RetoSchmidt, MaximilianLayer, SelinaBues, MatthiasMendonca, Daisy
This paper presents a coupled electromagnetic and thermal simulation of Permanently Excited Synchronous Machines (PMSM) in the context of virtual prototyping in a real-time Hardware-in-the-Loop (HiL) environment. Particularly in real-time simulations, thermal influences are often neglected due to the increased complexity of a coupled simulation. This results in inaccurate simulations and incomplete design optimizations. The objective of this contribution is to enable a precise and realistic real-time simulation that represents the electromagnetic as well as the thermal behavior. The electromagnetic simulation is executed used a Field-Programmable Gate Array (FPGA) and parameterized by Finite Element Analysis (FEA) results. The thermal model is based on a Lumped-Parameter-Thermal-Network (LPTN), which is based on physical laws, geometry parameters and material specifications. The simulation results are validated with testbench measurements to ensure the accuracy of the overall model. By combining electromagnetic and thermal models, design changes and thermal management can be evaluated simultaneously in real time. Compared to simulations that consider the thermal behavior separately, this coupled analysis enables more accurate evaluation and optimization. Embedding real-time thermal simulation into the virtual prototyping process not only allows frontloading of the electric machine development process, but also enables a direct interaction between machine design and controller development. This approach leads to improved predictions of temperature distributions and thermal losses under transient operating conditions, helping to identify and correct potential design errors at an early stage.
Jonczyk, FabianKara, OnurBergheim, YannickLee, Sung-YongStrop, MalteProchotta, FabianAndert, Jakob
The complex and turbulent ship airwakes make shipboard rotorcraft launch and recovery difficult for even the most seasoned pilots. One of the main challenges to using flight simulation to train pilots is the real-time accurate prediction of the ship airwake. A real-time, accurate methodology that is able to operate on personal computers without computational meshing is being developed for Advanced Air Mobility (AAM) applications. The early success of this novel approach indicates that it may be well-suited to meet the challenge of dynamic interface (DI) applications as well. To explore this, a novel reduced-order model (ROM) to represent unsteady airwakes for shipboard operations is underway. This ROM will be integrated into an ocean-based representative environment model (REM) to close the gap in real-time simulations without significant computational investment. The ROM effort presented here specifically investigates which superstructure wake characteristics are dominant in different regions where flight operations are conducted. Canonical ship geometries that have been significantly studied experimentally and computationally provide the substantiation of this approach. Evaluation of the accuracy of the approach is presented, correlated with Lattice-Boltzmann simulations, theoretical and experimental data.
Oates, BrendenVera Garcia, BraulioSmith, MarilynRauleder, Juergen
Small, highly maneuverable Urban Air Mobility (UAM) air taxis might exhibit motions during hover and low-speed flight that are unfamiliar to many passengers, and for which there are no established guidelines to predict passenger comfort. Researchers performed a study in the Armstrong Virtual Reality Passenger Ride Quality Laboratory to identify relationships between sudden motion characteristics and UAM passenger comfort and acceptance. Twenty-three volunteer test subjects from the Armstrong workforce each completed a 15-minute experience as a passenger in a virtual air taxi simulation. Subjects evaluated a series of flight maneuvers with varying levels of sudden motion using a five-point rating scale and indicated which motion(s) they found uncomfortable. Researchers then administered a post-test questionnaire to relate the passengers’ ratings to their willingness to fly on a real air taxi with similar levels of motion. The study results relate peak heave acceleration and jerk to passenger acceptance.
Hanson, CurtRamia, SaravanakumaarBarnes, Kyle
This paper investigates the use of multi-modal cueing through full-body haptic feedback to enhance pilot-vehicle system (PVS) performance, reduce mental workload (MWL), and increase situational awareness (SA) in both good and degraded visual environments (GVE/DVE). Piloted simulations were conducted using an H-60-like flight dynamics model in a virtual reality (VR) motion-based simulator, evaluating two ADS-33-like mission task elements (MTEs) – precision hover and slalom – under visual-only and combined visual and haptic feedback conditions in both GVE and DVE. The H-60 flight dynamics were augmented with a dynamic inversion (DI)- based stability augmentation system (SAS), implementing rate-command/attitude hold (RCAH) response type on the roll, pitch, and yaw axes and altitude hold response type on the vertical axis. The SAS was designed to achieve Level 1 handling qualities per ADS-33 standards. The full-body haptic cueing strategy leveraged an outer-loop DI control law, which provided vibrotactile feedback to cue desired roll, pitch, and yaw attitudes to the pilot. Roll cues were delivered via tactors mounted on the upper arms, pitch cues via tactors on the chest and back, and yaw cues via tactors on the calves. Eight test subjects participated in the piloted simulations, including three U.S. Navy test pilots and five subjects with different flying experiences. Results indicated that haptic feedback significantly improved hover performance, reducing MWL and enhancing SA, particularly in DVE. However, in the slalom task, predefined haptic guidance misaligned with pilots’ individual control strategies, leading to performance degradation. This finding highlights the need for pilot-specific adaptive haptic feedback to mitigate inconsistencies in dynamic maneuvering tasks.
Morcos, Michael T.Saetti, UmbertoGeiger, Derek H.Kubik, Stephen T.Breed, Adam R.Crane, Clifton J.Luzzani, GabrieleFischer, Madeline R.Jun, DogyuGary, Evan
We present the flight testing and integration of the Microsoft HoloLens 2 as a head-worn display (HWD) in DLR's research helicopter. Building on its successful use in a helicopter simulator, initial flight tests confirmed its feasibility in a real helicopter. Current tests focused on system optimization, with head tracking identified as the critical component for hologram stability. Since the HoloLens' inside-out tracking fails in moving vehicles, it was fused with an external infrared tracker, automatically calibrated via an optimization approach adaptable to various trackers and mounting positions. A test pilot with HWD experience rated the system as fully functional, enabling the first successful experiments with holographic Mission Task Elements. Beyond the helicopter, the HoloLens was tested in a car and on a high-speed boat, where holograms remained spatially stable despite high-frequency movements, with a maximum low-frequency error of 0.6° in heading. Static errors depended solely on the external tracker's quality. These results demonstrate the HoloLens 2's potential for operational use in dynamic vehicle environments, enhancing immersion. Its mixed-reality features and adaptability proved particularly valuable for rapid research and development across platforms.
Walko, ChristianJusko, TimMaibach, Malte-Jörn
Industrial bearings are critical components in aerospace, industrial, and automotive manufacturing, where their failures can result in costly downtime. Traditional fault diagnosis typically depends on time-consuming on-site inspections conducted by specialized field engineers. This study introduces an automated Artificial Intelligence virtual agent system that functions as a maintenance technician, empowering on-site personnel to perform preliminary diagnoses. By reducing the dependence on specialized engineers, this technology aims to minimize downtime. The Agentic Artificial Intelligence system leverages agents with the backbone of intelligence from Computer Vision and Large Language Models to guide the inspection process, answer queries from a comprehensive knowledge base, analyze defect images, and generate detailed reports with actionable recommendations. Multiple deep learning algorithms are provisioned as backend API tools to support the agentic workflow. This study details the architectural design of the agentic system and provides a real-time simulation of its workflow. In this study, inspection reports previously conducted by live technicians are used as a surrogate for simulating the diagnostic process carried out by agents. Validation of the system is studied by industry standard metrics like RAGAS comparing reports generated by field technicians versus AI agent generated reports. This feasibility study gets a score of 0.72, and it shows good promise for automating the time-consuming defect identification process. The concepts discussed can be extended to other similar problems, demonstrating their potential to enhance operational efficiency across sectors. This AI agentic workflow automation is constantly evolving, and further studies are needed to improve current performance levels and to mitigate the risk factors for productionizing this solution.
Chandrasekaran, Balaji
Augmented reality (AR) has become a hot topic in the entertainment, fashion, and makeup industries. Though a few different technologies exist in these fields, dynamic facial projection mapping (DFPM) is among the most sophisticated and visually stunning ones. Briefly put, DFPM consists of projecting dynamic visuals onto a person’s face in real-time, using advanced facial tracking to ensure projections adapt seamlessly to movements and expressions.
A vital aspect of Ultra-Fast Charging (UFC) Li-Ion battery pack is its thermal management system, which impacts safety, performance, and cell longevity. Immersion cooling technology is more effective compared to indirect cold plate as heat can dissipate much quicker and has a potential to mitigate the thermal runaway propagation, improve pack overall performance, and cell life significantly. For design optimization and getting better insight, high fidelity Multiphysics-Multiscale simulations are required. Equivalent Circuit Model (ECM) based electro-thermally coupled multi-physics CFD simulations are performed to optimize the innovative busbar design, of a recently developed immersion cooled battery pack, which enables the capability to remove individual cell. Further, high fidelity 3D transient flow-thermal simulations have helped in optimizing the coolant flow direction, inlet positions, cell spacing and separator design for efficient flow distribution in the module. While high-fidelity CFD models accurately depict flow and thermal behavior, their computational demands often hinder quick optimizations. Therefore, this study focuses on generating Reduced Order Models (ROM) from high fidelity CFD models, to improve prediction performance of Battery Management System (BMS) using real-time simulations. A detailed methodology for creating a linear parameter variant (LPV) ROM, and multiple linear time in-variant (LTI) matrices, for quicker parametric studies, are being studied. The ROM fully integrates electro-thermal aspects for immersion cooling systems where the dielectric liquid is in direct contact with cells and flows along axial direction of the cells. The required training data for the LPV ROM creation is generated by running transient step response thermal simulations on converged steady-state flow solution for different flow rates. The experimental module setup comprising of 144 cells immersed in the dielectric fluid is also prepared for the model validation. The model validations done against test results confirms ROM's accuracy and robustness, with a tenfold reduction in computational time and minimal loss in solution accuracy.
Tyagi, RamavtarNegro, SergioBaranowski, AlexAtluri, Prasad
State-of-the-art fighter aircraft have a large number of support systems that operate in multiple areas. These systems are continuously optimized to achieve maximum efficiency and performance. Countless sensors monitor the environment and generate important data that helps to understand the areas overflown. But even in life-threatening combat situations, target acquisition systems support pilots and provide additional information that can be decisive with the help of augmented reality (AR) and artificial intelligence (AI). Military aviation is an arena with great potential for the use of technical aids that have transformed the original fighter aircraft into a technological masterpiece. In addition to the high level of complexity, the upcoming generation change from fifth- to sixth-generation fighter jets poses major challenges for component suppliers and accelerates the pace of technological competition. A military fighter jet is already an extremely demanding environment for technical equipment.
State-of-the-art fighter aircraft have a large number of support systems that operate in multiple areas. These systems are continuously optimized to achieve maximum efficiency and performance. Countless sensors monitor the environment and generate important data that helps to understand the areas overflown. But even in life-threatening combat situations, target acquisition systems support pilots and provide additional information that can be decisive with the help of augmented reality (AR) and artificial intelligence (AI). Military aviation is an arena with great potential for the use of technical aids that have transformed the original fighter aircraft into a technological masterpiece.
As the demands for air travel and air cargo continue to grow, airport surface operations are becoming increasingly congested, elevating the operational risks for all entities. Conventional measurement methods in airport traffic scenarios are limited by high temporal and spatial costs, uncontrollable variables, and their inabilities to account for low-probability events. Moreover, current simulation software for airport operations exhibits weak simulation capabilities and poor interactivity. To address these issues, this study developed a virtual reality traffic simulation platform for airport surface operations. The platform integrated 3D modeling technologies, including Blender and Unity, with the Photon Fusion multiplayer platform and Simulation of Urban Mobility (SUMO) traffic simulation software. By incorporating Logitech external devices, the platform enabled real-time human-driven simulations, multiplayer online interactions, and validation of airport traffic flow models. To enhance practical applicability of the platform, a scenario library for vehicle-aircraft-taxiway coordinated operations was designed based on historical data. A stated preference survey was distributed to aviation experts, evaluating scenario risk ratings and occurrence frequencies. Principal component analysis and rank sum ratio were applied to identify key scenarios, which were embedded into the platform. The results of this study simulate the interaction among vehicles, aircraft, and airport taxiways, providing a scenario-driven control strategy verification platform and real-time interactive driving decision support. This approach contributes to the digital transformation of airport surface management, enhancing operational efficiency and safety.
Zhang, YuhengHan, ZhongyiZhang, YuhanYe, Zhirui
The effectiveness of the negative suspension structure (NSS) in isolating the driver’s seat vibrations has been demonstrated based on the seat’s model or vehicle’s one-dimensional dynamic model. To fully assess the effectiveness and stability of the seat’s NSS (S-NSS) on different models of vehicles, the three-dimensional models of the vibratory rollers (VR), heavy trucks (HT), and passenger cars (PC) have been built to assess the effectiveness of S-NSS compared to the seat’s passive suspension (S-PC) and seat’s control suspension (S-CS). The effectiveness of S-NSS is then investigated under all operating conditions of vehicles. The investigation results indicate that under a same simulation condition, S-NSS improves the ride comfort and health of the driver better than both S-PS and S-CS on all VR, HT, and PC. However, the effectiveness of S-NSS on PC is lower than on both VR and HT while the effectiveness of S-CS on PC is better than on both VR and HT. Besides, the effectiveness of S-NSS with VR moving on the poor class of the ground surface is better than on the good class of the ground surface. In addition, under the change of the velocity and seat mass, the effectiveness of S-NSS on VR is not only higher than that on HT and PC but also very stable, conversely, the effectiveness of S-CS on PC is better than that on VR and HT. These results imply that S-NSS should be applied on the seat suspension of VR, HT, and PC to improve the comfort and health of the driver, especially on VR, while S-CS should be applied to PC to achieve its best isolation effectiveness.
Su, BeibeiWang, QiangSong, Fengxiang
Researchers in the emerging field of spatial computing have developed a prototype augmented reality headset that uses holographic imaging to overlay full-color, 3D moving images on the lenses of what would appear to be an ordinary pair of glasses. Unlike the bulky headsets of present-day augmented reality systems, the new approach delivers a visually satisfying 3D viewing experience in a compact, comfortable, and attractive form factor suitable for all-day wear.
This research aimed to explore the integration of Virtual reality technology in ergonomically testing automotive interior designs. This objective was aimed at ensuring that such technology could be used to ameliorate user comfort through controlled simulations. Existing ergonomic testing methods are often limited when it comes to recreating actual driving situations and quickly repeating design improvements. VR could be used as a solution because its ergonomically tested simulation can be used to provide users with the real experience of driving. The users can be observed while they experience it and asked for their feedback. For this research, an interactive VR environment imitating a 10-minute-long trip through traffic and changing road conditions was created. It was populated by ten users, concatenated equally in men and women, both aged 20-35, representing approximate demographics of workers in the automotive production industry. Participants of the research were asked to use assessed metrics, which included subjective comfort rating, control reachability, visibility rating and overall user experience within the VR simulation. The VR environment was overall well-received by the demands of this research. Its uses found it comfortable and easy to use, with average metrics of 7.5, 8.0, and 7.5, respectively for comfort, controls, and visibility. The overall user experience averaged at 7.8. The information obtained through this research proves that VR environments can be used effectively to simulate the interior of cars and ameliorate the ergonomics of their designs. This could potentially be a revolutionary technology, accelerating automotive development by the early detection of design mistakes and facilitating iterative improvements with subsequent iterations.
Natrayan, L.Kaliappan, SeeniappanSwamy Nadh, V.Maranan, RamyaBalaji, V.
Seoul National University College of Engineering announced that researchers from the Department of Electrical and Computer Engineering’s Optical Engineering and Quantum Electronics Laboratory have developed an optical design technology that dramatically reduces the volume of cameras with a folded lens system utilizing “metasurfaces,” a next-generation nano-optical device. By arranging metasurfaces on the glass substrate so that light can be reflected and moved around in the glass substrate in a folded manner, the researchers have realized a lens system with a thickness of 0.7 mm, which is much thinner than existing refractive lens systems. The research, which was supported by the Samsung Future Technology Development Program and the Institute of Information & Communications Technology Planning & Evaluation (IITP), was published on October 30 in the journal Science Advances. Traditional cameras are designed to stack multiple glass lenses to refract light when capturing images. While this structure provided excellent high-quality images, the thickness of each lens and the wide spacing between lenses increased the overall bulk of the camera, making it difficult to apply to devices that require ultra-compact cameras, such as virtual and augmented reality (VR-AR) devices, smartphones, endoscopes, drones, and more.
A digital twin is a digital representation of a real physical system, product, or process that functions as its practically identical digital counterpart for tasks such as testing, integration, monitoring, and maintenance. Creating digital twins allows the ‘digital system’ or ‘digital product’ to be tested at faster-than-real-time which improves overall program efficiency and shortens the programme duration. The HORIBA Intelligent Lab virtual engineering toolset was used to generate an Empirical Digital Twin (EDT) of a contemporary off-highway diesel Internal Combustion Engine (ICE) from physical testing, accounting for the effects of altitude and combustion air temperature. The EDT was subsequently used to predict engine performance and emissions for several synthetic off-highway machine cycles at sea-level and 3000m altitude. The synthetic agricultural cycles which included ploughing, seeding, spraying, fertilising, and roading were generated using a machine simulation programme created by Soluzioni Ingegneria and IPG Automotive. This combined physical testing and simulation approach to off-highway machine development and calibration is expected to support Original Equipment Manufacturers (OEMs) with In Service Monitoring (ISM) within the Stage V emissions period and supplement powertrain development for future emissions standards. The off-highway simulations were conducted using semi-empirical Magic Formula (MF) tyre models which accounted for the tyre-soil elastoplastic working relationship. These models incorporated the coefficients of longitudinal traction and forward resistance on plastic soil and were developed from ASAE standards and extensive field testing with instrumented vehicles. This new off-highway simulation platform developed by Soluzioni Ingegneria and IPG Automotive allows the generation of complex off-highway scenarios which can be used to estimate loading of machine components such as hydraulics, pneumatics, and accessories and right-sizing of powertrains for given machine applications.
Roberts, PhilBates, LukeWhelan, SteveMaroni, ClaudioLeo, ElisabettaPezzola, Marco EzioChild, Steven
Researchers have developed SPINDLE, a pioneering robotic rehabilitation system. Combining virtual reality (VR) with customized resistance training, SPINDLE offers personalized therapy to enhance strength and dexterity for activities of daily living (ADLs). Its adaptability and potential for home use represent a major advancement in tremor rehabilitation, with broader healthcare implications.
A research team at The University of Texas at Austin created a noninvasive electroencephalogram (EEG) sensor that was installed in a Meta VR headset that can be worn comfortably for long periods. The EEG measures the brain’s electrical activity during the immersive VR interactions.
Researchers worldwide are currently working on the next evolution of communication networks, called “beyond 5G” or 6G networks. To enable the near-instantaneous communication needed for applications like augmented reality or the remote control of surgical robots, ultra-high data speeds will be needed on wireless channels. In a study published recently in IEICE Electronics Express, researchers from Osaka University and IMRA AMERICA have found a way to increase these data speeds by reducing the noise in the system through lasers.
The modern automotive industry is facing challenges of ever-increasing complexity in the electrified powertrain era. On-board diagnostic (OBD) systems must be thoroughly calibrated and validated through many iterations to function effectively and meet the regulation standards. Their development and design process are more complex when prototype hardware is not available and therefore virtual testing is a prominent solution, including Model-in-the-loop (MIL), Software-in-the-loop (SIL) and Hardware-in-the-loop (HIL) simulations. Virtual prototype testing relying on real-time simulation models is necessary to design and test new era’s OBD systems quickly and in scale. The new fuel cell powertrain involves new and previously unexplored fail modes. To make the system robust, simulations are required to be carried out to identify different fails. Thus, it is imminent to build simulation models which can reliably reproduce failures of components like the compressor, recirculation pump, humidifier, or cooling systems. This paper shows the development of high-fidelity fuel cell model which is used as digital twin to reproduce relevant failure modes. As the OBD regulations become more stringent and advanced, it is difficult to keep pace with it and perform comprehensive testing in real world environment. In such scenarios, MIL, SIL and HIL testing becomes more prevalent. MIL and SIL testing provide a quick way for controls engineers to develop new strategies at system level to adhere to new OBD regulations. On the other hand, simulating high fidelity physics based Real Time plant model on HIL systems, allows the engineers to perform fault insertions tests on the software and leave the lab environment with a certain degree of guarantee that the software would fare well in real world conditions. The model used can reproduce failure modes consistently while staying in real time which in turn can be detected by controls and can take action promptly. The viability of this approach is demonstrated by showing MIL and HIL test results.
Pandit, Harshad RajendraDimitrakopoulos, PantelisShenoy, ManishAltenhofen, Christian
In the increasingly connected and digital world, businesses are sprinting to integrate technological advancements into their corporate fabric. This is evident with the emerging concept of “digital twinning.” Digital twins are virtual representations of real-world objects or systems used to digitally model performance, identify inefficiencies, and design solutions. This helps improve the “real world” product, reduces costs, and increases efficiency. However, this replication of a physical entity in the digital space is not without its challenges. One of the challenges that will become increasingly prevalent is the processing, storing, and transmitting of Controlled Unclassified Information (CUI). If CUI is not protected properly, an idea to save time, money, and effort could result in the loss of critical data. The Department of Defense's (DoD) CUI Program website defines CUI as “government-created or owned unclassified information that allows for, or requires, safeguarding and dissemination controls in accordance with laws, regulations, or government-wide policies. It is sensitive information that does not meet the criteria for classification but must still be protected.” In March 2020, DoD published Instruction 5200.48, establishing the official DoD CUI Registry.
The National Research Council of Canada (NRC) has recently developed an Integrated Reality In-flight Simulator (IRIS) that allows helicopter pilots to fly the NRC's Bell 412 Advanced Systems Research Aircraft (ASRA) while wearing a commercial off-the-shelf (COTS) virtual reality headset. IRIS is the first airborne simulator of its kind that combines COTS virtual reality and Fly-By-Wire (FBW) synthetic turbulence for helicopter operations. Simulations are not exact replications of actual environments; therefore, a methodology of comparing pilot workload with respect to an analysis of the differences between the simulated and actual environments is required. During a recent flight trial, NRC validated the effectiveness of IRIS to replicate a pilot's workload during ship landing tasks using these workload scales. During the analysis, NRC took initial steps in developing methodologies to examine environmental characteristics and then correlate them to an associated pilot workload. The work also included the initial development of methodologies to analyze pilot workload and alternative prediction methods that better map subjective or quantitative pilot workload data to DIPES.
Comeau, PerryJennings, SionLaw, AndrewWall, Alanna
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