Browse Topic: Test facilities

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This paper will revisit an area of Short Take-Off and Landing (STOL) operations and powered-lift aircraft design that has been limited in scope, and at best, very specialized when it comes to research, aircraft built, and experimentation: The Upper Surface Blowing (or USB) aircraft configuration. Five aircraft have been flown successfully using the Upper Surface Blowing powered-lift concept: The Boeing YC-14, the Ball-Bartoe Jetwing, the Antonov An-72, the NASA QSRA experimental aircraft, and the National Aerospace Laboratory (NAL) Aska or Quiet STOL Research aircraft. Only the Antonov An-72 (and its commercial follow-on, the An-74) reached any significant degree of production. This fact illustrates the uniqueness of the USB technology as applied to powered-lift. A background of the technology will be given, what connects them as far as the USB configuration, discuss the main lessons learned, and briefly dwell on other configurations that are close relatives of aircraft using the USB as a source of powered-lift. An extensive review of the existing literature has been fundamental for the development of this paper since many years have passed since the last USB configured aircraft design has flown (the last new USB design to take to the air did so in 1985). Although all the unclassified USB projects that have been constructed and flown will be mentioned in this paper (production and experimental), the main thrust of the paper will be the Boeing YC-14 prototypes and the Ball-Bartoe Jetwing. With respect to NASA’s QSRA demonstrator, the Antonov An-72 series, and the NAL Aska demonstrator, references will be listed for those readers wishing to review the technology and advances made by those aircraft. Their detailed review is beyond the scope of this paper; but the contributions of these aircraft to the state-of-the-art of USB powered-lift configuration is well established.
Pinero, Erasmo
As automation advances and occupants transition from active drivers to passive passengers, understanding how automated driving behavior is evaluated becomes increasingly important. While longitudinal and lateral vehicle dynamics are known to influence perceived comfort and safety, it remains unclear to what extent motion–perception relationships remain stable across urban traffic contexts. This study compares two real-world investigations of automated driving: a left-turn maneuver at a signalized intersection on a test track and a roundabout maneuver with a shuttle in public traffic. Both datasets include high-resolution vehicle dynamics and structured subjective ratings. A consistent objectification approach was applied to examine the transferability of motion–perception relationships across contexts. However, differences in vehicle platform, automation level, trajectory characteristics, and study design limit direct comparability and require cautious interpretation. Despite partially overlapping ranges in selected peak-based dynamic parameters, such as longitudinal acceleration, subjective comfort and safety ratings were consistently higher in the roundabout scenario. Furthermore, strong associations were observed between motion parameters and subjective evaluations in the intersection context (adj. R2 up to 0.891), whereas objective parameters showed only limited explanatory power in the roundabout scenario (adj. R2 ≤ 0.06). The results indicate that motion–perception relationships derived within a specific context may not be directly transferable across different traffic scenarios. The findings highlight limitations of globally derived motion-based evaluation models and underline the importance of validating objectification approaches across diverse operational environments.
Panzer, AnnaStrenge, EmmaIatropoulos, JannesHenze, Roman
SAE TOMORROW TODAY - What Baja SAE Teaches That College Can?t135746/26/2026
What does it really take to engineer under pressure? From mud-soaked vehicles and broken suspensions to team dynamics and split-second decisions, Baja SAE has become a proving ground for the next generation of engineering leaders. By challenging engineering students to design, build, and race single-seat off-road vehicles capable of surviving extreme terrain, Baja SAE requires every team to use the same 14 hp Kohler engine -- creating an even playing field and putting the focus on innovation, durability, and teamwork. Listen in as Honda's Adam Hussemann and TTX Company's Jason Rounds pull back the curtain on the intense, unpredictable world of Baja SAE competitions and how they prepare students for careers in manufacturing, mobility, and beyond. After hearing this conversation, you'll understand why more and more companies value Baja experience just as much as a perfect GPA. We'd love to hear from you. Share your comments, questions and ideas for future topics and guests to podcast@sae.org. Don't forget to take a moment to follow SAE Tomorrow Today--a podcast where we discuss emerging technology and trends in mobility with the leaders, innovators and strategists making it all happen--and give us a review on your preferred podcasting platform. Follow SAE on LinkedIn, Instagram, Facebook, X, and YouTube. Follow host Grayson Brulte on LinkedIn, X, and Instagram.
Patterson, Lori
When developing a vehicle, the overall body stiffness is an important parameter to be estimated for several automotive attributes. As a complement to the traditional experimental and computational static torsional stiffness assessment, an improved method has been developed to evaluate the body stiffness when driving the vehicle on a test track. This method, valid for both test and simulation, is called Opening Distortion Fingerprint (ODF) and uses the so-called Multi Stethoscope (MSS) to measure the dynamic distortion in each body closure opening and cross section. For evaluating the distortion, from both test and Multi Body Dynamics (MBD) simulation data, the Evaluation-line (E-line) method is used. The E-line method is a linear approach. Consequently, it is only valid in the absence of large rigid body rotations of the vehicle body. Therefore, to assess the validity of the ODF method, it is crucial to identify the frequency at which the distortion results become invalid due to rigid body rotations. To identify this frequency range, in an MBD simulation the total distance output parameter can be requested and used. But for a dynamic full vehicle test, it is a major challenge to measure the total distance. Several tests have been performed without success. To calculate this frequency range from test data, this paper presents a new approach. In this methodology two different signal processing methods (E-line and Diagonal) are combined. To check the validity of the new approach, full vehicle test data has been evaluated. In addition, a simplified beam lab experiment is presented, highlighting the difference between test and MBD simulation when measuring the distortion at large rotations.
Olger, EmmaLindkvist, LisaPiiroinen, PetriKarypidis, JohnPena, MiltonBäcklund, JesperAppelgren, PeterMarberg, HenrikUgale, PravinWeber, Jens
This SAE Aerospace Information Report (AIR) has been written for individuals associated with ground level testing of turbofan and turbojet engines, and particularly for those who might be interested in investigating steady-state performance characteristics of a new test cell design or of proposed modifications to an existing test cell by means of numerical modeling and simulation. It is not the intent of this standard to provide specific test cell design recommendations, which are covered in the reference documentation.
EG-1E Gas Turbine Test Facilities and Equipment
It is a general practice to test aero engines to evaluate their performance in specially designed indoor test facilities after assembly, repaired or overhaul. Acoustic features are provided in the test facility to attenuate the noise level to a comfortable and acceptable level. Design of these features specially air intake and exhaust silencers are a challenging task in a flow field like aero-engine test facility considering the very high sound pressure level generated by them during test containing a very wide frequency band. Moreover, growing population and location of these facilities in the vicinity of residential areas has added this challenge in multifold. Also, the capital investment in building these facilities is huge due to their large size and longer construction time. Hence, the correct execution at first shot including design, fabrication and commissioning is very important. An attempt has been made to reduce design errors or improve the accuracy in the design stage by using commercially available acoustics analysis tools followed by laboratory measurement of sample features, which will reduce the lead time and cost of the project in design and implementation of the acoustic features for aero engine test facilities used for military application. This paper outlines the design of acoustics features such as air intake silencers, air cooled exhaust silencer, acoustic panels, sound proof doors and bullet resistant view window, which has produced significant improvement of noise level in and around the test facility.
Gouda, Bansidhar
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 SAE Aerospace Information Report (AIR) developed by a broad cross section of personnel from the aviation industry and government agencies is offered to provide state-of-the-art information for the use of individuals and organizations designing new or upgraded turboshaft engine test facilities. This document is also applicable to turboprop engines tested with a dynamometer as load absorption device, as they are basically tested as turboshaft engines. For propeller-equipped turbofan testing facilities design considerations, see 2.1.7.
EG-1E Gas Turbine Test Facilities and Equipment
This SAE standard establishes the requirement for suppliers to plan a reliability program that satisfies the following three requirements: a The supplier shall ascertain customer requirements b The supplier shall meet customer requirements c The supplier shall assure that customer requirements have been met
G-41 Reliability
This work presents the development of an interconnected gearbox drive system for a tandem rotor unmanned aerial vehicle (UAV) designed for a power rating of 20 kW per rotor. Development of the facility for dynamic testing of the interconnecting drive system is also presented. Tandem rotor configurations offer superior payload capacity and aerodynamic efficiency but pose challenges in transmission design due to the need for synchronized power distribution between counter-rotating rotors. The proposed gearbox employs a simple two-stage reduction system combining bevel and planetary gears to achieve compactness, high torque transmission, and ease of fabrication. A dedicated test rig is concurrently being developed to evaluate gearbox performance under variable torque and speed conditions for the first stage with the mechanical interconnection. The test set-up integrates a variable-speed drive, torque and vibration sensors, and a data acquisition system to measure efficiency, losses, and thermal characteristics. While fabrication and assembly are ongoing, this work lays the foundation for experimental validation and optimization of drivetrain performance. The project contributes toward developing reliable, lightweight, and scalable transmission solutions for heavy payload multi-rotor vertical lift UAVs. The drive system dynamics, in particular, the torque transmission through the cross shaft during maneuvers will be the investigated using the current test rig configuration.
Mathur, TanmayNayak, AshishSingh, Sriansh
This paper presents the contributions of the Royal Netherlands Aerospace Centre (NLR) to a Leonardo-led consortium participating in NATO Next-Generation Rotorcraft Capability (NGRC) Study #5, which is aimed at the development of Integrated Platform Concepts (IPC) to fulfill the NATO NGRC 2035+ Capability Development needs. NLR contributed to this industry effort by providing an independent evaluation of the high-speed tiltrotor concept proposed by the consortium led by Leonardo, considering aspects such as handling qualities, rotorcraft-ship compatibility, as well as a broader operational Battle Lab assessment. The handling qualities assessment and related control law development considered predictive metrics from ADS-33E and MIL-1797A, and yielded Level 1 handling for the baseline tiltrotor concept along with an evaluation of design sensitivities. The ship compatibility assessment, based on in-airwake trim and simulated lateral approach procedures, offered early insight into tentative limits for tiltrotor shipboard operations on Frigate-class navy vessels. The Battle Lab simulations provided an early holistic evaluation of operational effectiveness of the proposed IPC in the Air Assault mission scenario that is part of the NGRC Concept of Operations (CONOPS).
van 't Hoff, StefanVasileiadis, EmmanouilMamino, MatteoBakker, RichardPfeifle, Ole
This organizational process survey provides insight into the technical aspects of approved airworthy aircraft modifications applied in government organization vertical lift flight test. The publication reviews processes applied by the National Research Council of Canada's Flight Research Laboratory (NRC-FRL) and its Airworthiness Control System to enable research flight testing. Dominated by the need for integrating experimental payloads, the NRC-FRL embeds a Design and Fabrication Service organization for modification of internal and external client projects and flight test aircraft. In context of experimental flight testing, this work reviews technical information on process, facilities, and methodology for airworthy integration of flight test payloads. Information is used to synthesize recommendations in experimental vertical lift flight testing that satisfy both formal (regulated compliance) and informal (compliance intent) airworthiness requirements.
Alexander, MarcLong, TerryLebrun, CamileDay, JamesMelnik, HarleyThomas, Jeffrey
Army researchers recently developed a 3D-printable, easy-to-assemble drone designed to enhance intelligence, surveillance and reconnaissance capabilities. Army Research Laboratory, Adelphi, MD Researchers at the U.S. Army Combat Capabilities Development Command, or DEVCOM, Army Research Laboratory (ARL) harnessed bottom-up Soldier innovation to develop an experimental 3D-printed small unmanned aerial system, or drone, that was demonstrated at the inaugural U.S. Army Best Drone Warfighter Competition in Huntsville, Alabama. Known as the Soldier Portable Autonomous Reconnaissance Transitioning Aircraft, or SPARTA, the drone was developed at DEVCOM ARL in collaboration with Soldiers. By incorporating Soldier feedback early in the design process and leveraging ARL's world-class research facilities, researchers developed a 3D-printable, easy-to-assemble drone designed to enhance intelligence, surveillance and reconnaissance capabilities. ARL is actively working to partner the technology with industry to get into the hands of the warfighter.
Machina Labs recently closed its latest round of financing with $124 million, enough to develop a facility featuring up to 50 of its RoboCraftsman cells capable of producing thousands of complex structural assemblies for aerospace and defense customers - a list that already includes Lockheed Martin and the U.S. Air Force, among others. Founded in 2019, Machina Labs is a California-based company that seeks to reinvent metal manufacturing with a robot that uses artificial intelligence (AI) to rapidly form and assemble complex military grade structures directly from digital design files. RoboCraftsman is the company's manufacturing robot that leverages its proprietary “RoboForming” process to integrate multiple manufacturing processes - including metal forming, trimming, scanning, and heat treating - into a single containerized machine.
This specification covers a synthetic rubber in the form of sheet, strip, tubing, extrusions, and molded shapes. This specification should not be used for molded rings, compression seals, O-ring cords, and molded in place gaskets for aeronautical and aerospace applications without complete consideration of the end use prior to the selection this material.
AMS CE Elastomers Committee
The Stellantis North America Aero-Acoustic Wind Tunnel (AAWT) has been upgraded with a cutting-edge 5-belt Moving Ground Plane (MGP) system, featuring an 8.5-meter center belt and four Wheel Spinning Unit (WSU) belts with advanced coatings for durability and visibility. The expanded 9.4-meter turntable enables ±90° yaw and supports vehicles with wheelbases from 1800 mm to 4500 mm and weights up to 5000 kg, accommodating the full Stellantis North America product range. The original 2-stage boundary layer control system was retained, with new tertiary slots added for improved flow quality. A high-stiffness, six-component Horiba balance with integrated calibration weights and tractive force measurement ensures accurate and precise measurements. Facility enhancements include a 550 m2 building addition for equipment and vehicle prep, a dedicated compressor container for clean air supply, and a vehicle underbody wash booth for efficient cleaning. Commissioning confirmed that flow quality, axial static pressure distribution, and acoustic background noise meet or exceed system specifications. Operational since October 2024, the upgraded AAWT now delivers world-class aerodynamic and acoustic testing capabilities, with enhanced automation, safety, and efficiency.
Lounsberry, ToddLadouceur, BrentFadler, Gregory
At the U.S. Environmental Protection Agency’s National Vehicle and Fuel Emissions Laboratory, a development project was implemented to compare various test methods for benchmarking the operation of vehicle electric drive units (EDUs). In earlier research, several test methods were identified, of which two were used to test a Chevrolet Bolt EDU: (a) in-vehicle testing of the complete EDU on a chassis hub dynamometer and (b) stand-alone testing of the EDU’s electric motor and inverter in a dedicated test cell after removal from the vehicle. The resulting data sets were compared with each other and with similar data previously published by GM. In this paper, additional EDU test methods are explored. First, the stand-alone testing of the EDU and its subcomponents is expanded to include testing both with and without the EDU gearing. This testing allows the electric motor, inverter, and gearbox to be characterized separately and the EDU to be characterized as a complete unit. Second, in-vehicle testing of the complete EDU is performed on a roll dynamometer. EDU efficiency and losses are determined using data obtained from wheel hub torque sensors; these results are compared to estimated values based on the force and speed data collected by the roll dynamometer. Finally, the relative difficulty of implementation and the robustness of the resulting data for each of the benchmarking methods developed is analyzed and compared to methods developed and described in earlier research. Metrics used for comparison include the cost and level of effort of the implementation, complexity of the setup, repeatability of the test conditions, safety considerations, ability to separate EDU components, completeness of the data set produced, and the variability, quality and accuracy of the resulting data.
Moskalik, AndrewSchauer, EthanBarba, Daniel
As automotive aerodynamic testing facilities evolve to capture more real-world behavior, updating the correlation between old and new technologies is essential. Recently, the three-member consortium of the United States Council for Automotive Research (USCAR) - General Motors, Ford Motor Company, and FCA US LLC - transitioned from full-size static ground plane facilities to 5-belt moving ground plane wind tunnel facilities. The primary objective of this study was to update the correlation data sets to maintain consistent and robust data sharing among companies, which is the cornerstone of USCAR efforts. To achieve this, a set of updated correlation data sets were calculated to replace the original correlation study results from 2008. Additionally, the methodology for applying correlation equations was revised from using averaged wind tunnel data to employing direct wind tunnel-to-wind tunnel correlation equations. In a two-phase correlation effort conducted in 2022 and 2025, the three companies exchanged and evaluated six vehicles of varying size and proportions across the three rolling road wind tunnels. To ensure the updated correlation data sets capture the bounds of current and future vehicle aerodynamic performance, the tested bandwidth of coefficient of drag area (CDA) data ranged from 0.37 m2 to 1.45 m2 (CD from 0.17 to 0.48). Despite the unique challenges of each wind tunnel project, the outcome of the updated correlation efforts demonstrated excellent correlation (R2 > 99.8%) across direct tunnel-to-tunnel comparisons, mirroring the success of the original 2008 correlation efforts. These findings validate the accuracy and reliability of aerodynamic data collection in each of the three rolling road facilities, thereby supporting consistent and robust data sharing among USCAR partners.
Nastov, AlexanderLounsberry, ToddMadin, TrevorLangmeyer, GregoryFadler, GregorySkinner, ShaunHorton, Damien
As the utilization of lithium-ion batteries in electric vehicles expands, monitoring the usable cell capacity (UCC) is essential for ensuring accurate state-of-health (SOH) estimation. Battery performance degradation is influenced by temperature and constraints. Capacity tests in laboratory settings are typically conducted at low C-rates to approximate equilibrium conditions, whereas in real vehicle applications, charging currents are often much higher. This discrepancy in rates frequently results in deviations between laboratory characterization and on-board Battery Management Systems (BMS) capacity estimation. To investigate how C-rate of diagnostic Reference Performance Test (RPT) modulates aging effects under temperature and mechanical loading, we conducted long-term cycling tests on lithium iron phosphate/graphite pouch cells at 25°C and 45°C under different constrained conditions. The cycling protocol is a tiered multi-rate protocol. Cells were aged at Block1 under 1C, and UCC evolution was quantified after each block. The result shows battery aging can be divided into three stages: a decelerated, steady, and accelerated aging stage. The degradation of LFP cells is dominated by loss of lithium inventory (LLI), and elevated temperature accelerates the degradation. By combining differential voltage analysis (DVA), direct current internal resistance, electrochemical impedance spectroscopy, and ultrasonic testing, we found that under 45°C free condition, accelerated aging is consistent with intensified SEI growth and electrolyte decomposition, accompanied by increased LLI, gas-generation, and increased resistance. These signals emerge earlier than the apparent capacity divergence and may serve as early indicators for predicting the onset of rapid degradation. Appropriate constrain mitigates aging, and its influence becomes more pronounced when using higher-rate RPTs. At 25°C, high-rate RPTs exhibit an apparent capacity recovery. DVA analyses indicate the recovery originates from gradual activation of lithium. Overall, these findings illustrate and explain the degradation characteristics and capacity recovery phenomenon, providing a reference for connecting laboratory standard tests with on-board BMS capacity estimation.
Zhang, ShanNiu, ZhiceXia, Yong
Design for durability in the automotive industry depends on a clear understanding of how road surfaces and driving characteristics affect structural road loads and fatigue. Traditionally, road surface classification has been subjective (e.g., city, highway, rural), and done through driving instrumented vehicles over a small selection of roads. The variations in driving characteristics that are often consequent to the road surface quality are rarely accounted for in designing vehicle level durability tests. This makes it difficult to establish targets for durability testing that accurately match the wide variations in real-world roads and driving. This paper presents a data-driven approach to objectively classify road surface and driving characteristics using metrics derived from existing road response metrics like Vibration Dose Value (VDV) and statistical estimates of vehicle speed and acceleration. Data collected at the proving grounds on gravel roads, smooth roads, city-like roads, etc., is used to identify classifiers that categorize road-driving combinations into groups correlating with structural fatigue damage. This correlation between fatigue damage and road-driving classification is developed using Wheel Force Transducer (WFT) measurements from instrumented vehicles. This method shows promise to develop structural fatigue estimates directly from telemetry data. The method provides a path to replacing subjective road classification with a vehicle-sensor and signal-based, objective classification for developing durability targets and tests. This method is also scalable in terms of application on vehicle fleet data in uncontrolled environments, to develop an accurate understanding of real-world use of vehicles by customers.
Shaurya, ShubhamRamakrishnan, SankaranDemiri, AlbionKhapane, Prashant
The automotive industry faces several challenges requiring faster product development, where numerical simulations and digitalization are key enablers to reduce time to market and development costs. Numerical methods require both short turnaround times and high-fidelity results. Capturing small differences across vehicle designs, by accurately predicting complex flow phenomena is crucial for aerodynamics optimization. The disruptive and fast development of GPGPU computing hardware, promising accelerated turnaround times at lower costs, found its natural position in this landscape. This paper describes simulation approaches with increasing fidelity applied to a set of variants of a Stellantis estate production car: these include geometrical, yaw angle and ride height changes, and all were tested in wind tunnel test facilities. Correlation between aerodynamics CFD simulations using Simcenter STAR-CCM+ and wind tunnel measurements is verified by comparing drag trends, pressure probes and wake visualizations. From a numerical perspective, several simulation approaches are analyzed with increasing complexity. First, all design variants were simulated in an open road domain, using both steady state RANS and transient, scale-resolving DDES. The same approaches were applied in a digital wind tunnel domain corresponding to the real-world test conditions. Domain and modeling strategy impacts are analyzed and correlated to test results. All simulations were run on both CPU and GPU computing facilities, providing an answer in terms of price/performance differences and results consistency. To confirm the validity of the highest fidelity approach identified, an additional SUV model was simulated in a different wind tunnel environment and drag deltas were compared to test.
Landi, SimoneAltmann, PeterCannavacciuolo, CiroJohannesson, ManiBorowiec, GrzegorzRibes, CharlesGuzman, ArturoMiretti, Luca
This paper reports on the Catesby Aero Research Facility (CARF), which began commercial operation in 2019, and summarizes facility characteristics and associated measurement technologies, with an emphasis on vehicle-mounted component-force measurement devices. CARF is a proving ground converted from a former railway tunnel approximately 2.74 km in length and surfaced with high-quality tarmac. The road-surface quality was specified to be comparable to that of SUBARU's proving ground and was achieved using established construction methods. The course is approximately straight with a small longitudinal grade. Key course specifications include an approximately 40 m2 blockage area, a 6 m road width (maximum 8.4 m), flatness σ < 0.5 mm, and a gradient of 0.57%. Relative to outdoor coast-down testing, the tunnel length enables continuous measurement to very low speeds, thereby improving repeatability. A six-component force sensor integrated into the hub unit enables on-road measurement of aerodynamic loads during driving and provides a dynamic range exceeding that of conventional stationary tire-testing equipment. Flow visualization was conducted using stationary particle image velocimetry (PIV), providing correlation data for computational fluid dynamics (CFD).
Shimoyama, Hiroshi
This paper describes Waymo's Collision Avoidance Testing (CAT) methodology: a scenario-based testing method that evaluates the safety of the Waymo Driver Automated Driving Systems' (ADS) intended functionality in conflict situations initiated by other road users that require urgent evasive maneuvers. Because SAE Level 4 ADS are responsible for the dynamic driving task (DDT), when engaged, without immediate human intervention, evaluating a Level 4 ADS using scenario-based testing is difficult due to the potentially infinite number of operational scenarios in which hazardous situations may unfold. To that end, in this paper we first describe the safety test objectives for the CAT methodology, including the collision and serious injury metrics and the reference behavior model representing a non-impaired eyes on conflict human driver used to form an acceptance criterion. Afterward, we introduce the process for identifying potentially hazardous situations from a combination of human data, ADS testing data, and expert knowledge about the product design and associated Operational Design Domain (ODD). The test allocation and execution strategy is presented next, which exclusively utilize simulations constructed from sensor data collected on a test track, real-world driving, or from simulated sensor data. The paper concludes with the presentation of results from applying CAT to the fully autonomous ride-hailing service that Waymo operates in San Francisco, California and Phoenix, Arizona. The iterative nature of scenario identification, combined with over ten years of experience of on-road testing, results in a scenario database that converges to a representative set of responder role scenarios for a given ODD. Using Waymo's virtual test platform, which is calibrated to data collected as part of many years of ADS development, the CAT methodology provides a robust and scalable safety evaluation.
Kusano, KristoferBeatty, KurtSchnelle, ScottFavaro, FrancescaCrary, CamVictor, Trent
Leonardo DRS has opened a new naval power and propulsion manufacturing and testing facility in Charleston, South Carolina, expanding its role in delivering next generation electric propulsion, integrated power systems, and high energy payload support for U.S. Navy surface and undersea platforms. The 140,000 square foot site consolidates advanced manufacturing, final assembly, and high fidelity testing for electric power conversion and propulsion systems, while also supporting naval steam turbine design, production, and subsystem integration for programs including the Columbia class ballistic missile submarine. A representative for Leonardo's Naval Power Systems business unit provided emailed statements with details about the type of advanced manufacturing the company will deploy at the new facility.
In the automotive industry, increasing noise regulations are influencing product sales and passenger comfort, creating a need for more effective noise testing methods. Hardware-in-Loop (HiL) based virtual acoustic testing serves as a critical step before Driver-in-Loop testing, allowing for the assessment of vehicle performance and noise levels inside and outside the vehicle under various conditions before physical prototype testing is performed. The Hardware-in-the-Loop (HiL) simulator setup is equipped with joystick control that requires a physical representation of the vehicle dynamics model provided as a Functional Mock-up Unit (FMU) in real-time format. In contrast, the vehicle control logic is implemented in C++ code. The simulator incorporates both lateral and longitudinal dynamics. Additional interfaces are integrated to support joystick input and virtual road visualization enabling realistic vehicle maneuvering and dynamic performance evaluation. However, performing all test protocols directly on the HiL setup can be time-consuming and costly. To address this limitation of full HiL testing, in this study, an offline Software-in-the-Loop (SiL) Co-simulation framework was developed as an alternative. This method replicates the HiL environment within MATLAB/Simulink, where joystick actions are simulated according to predefined driving protocols. The dynamic behavior of the vehicle during a reverse driving protocol, involving a 540° constant steering angle and 0–100% acceleration pedal input, was analyzed and compared between Offline SiL and HiL environments. Results demonstrated that 85% of key parameters exhibited strong correlation (R2 > 0.9), confirming that the offline SiL-based approach effectively replicates HiL performance. The remaining parameters also showed acceptable consistency. These findings indicate that the proposed Offline Co-simulation method is a promising, cost-effective, and scalable alternative for accurately predicting vehicle dynamic behavior, aligning well with current automotive industry needs for early-stage validation and optimization.
Visuvamithiran, RishikesanChougule, SourabhSrinivasan, RangarajanLaurent, Nicolas
NASA's Space Communications and Navigation (SCaN) Program and the Johns Hopkins Applied Physics Laboratory in Laurel, Maryland, have successfully tested wideband technology that allows spacecraft to communicate with both government and commercial networks for the first time. Launched July 23, 2025, aboard a SpaceX Falcon 9 rideshare mission, the Polylingual Experimental Terminal (PExT) is demonstrating multilingual wideband terminal technology. Hosted on a satellite from York Space Systems, PExT enhances a spacecraft's communications subsystem, enabling mission controllers to track and exchange data more efficiently across a broad range of networks and frequencies.
This document discusses, in broad and general terms, the subject of acoustical considerations in engine test cells. One of the primary purposes of an engine test cell is to control the noise emanating from the operating engine in order to reduce noise in the surrounding facility and community to acceptable levels. This is done by the design and installation of specialized acoustic elements and features, which need to be fully integrated into the overall test cell design. It should be further noted that the requirements of acoustic control are critical to the proper operation of the engine, safety of plant equipment and personnel, and meeting local and legal noise requirements.
EG-1E Gas Turbine Test Facilities and Equipment
This study examines the capability of medium-fidelity comprehensive analysis models to predict the acoustics for manned and unmanned rotorcraft configurations. Using the automated tool NDARC2RCAS developed at DEVCOM Army Research Laboratory, multiple configurations including a single main rotor, tilt rotor, coaxial and pusher, quadcopter, and hexacopter are evaluated at various mission segments including hover, advancing climb, and forward flight. Each configuration and condition is evaluated using a range of aerodynamic models from lower to higher fidelity, including uniform inflow, dynamic inflow, prescribed wake, free wake, and viscous vortex particle method (VVPM). These evaluations are then used with another automated tool, RCAS Acoustics, to predict noise on a Voronoi observer sphere. A comparison of the results for the single main showed good agreement between all of the aerodynamic models except VVPM. For the tilt rotor in forward flight, the higher-fidelity models produced changes in rotor loads due to the interaction with the wing. With prescribed and free wake models, this change in load is sharp and causes noise increases of up to 40 dB in front of and behind the vehicle, while the VVPM model produced a smoother change that results in a smaller, 20 dB increase in noise. The quadcopter and hexacopter show similar in-plane noise levels for all models, with alternating cancellation and amplification patterns due to rotor phasing, while out-of-plane noise is increased on the hexacopter when using the higher fidelity models.
Smith, BrendanFloros, MatthewAnusonti-Inthra, Phuriwat
Penn State UAS Research Lab (PURL) and Autonomous Robotics Competition Club (ARCC)
Iyer, VenkatakrishnanAxten, RachelSurendran, VidullanValente, VitorJohnson, Eric
In its conventional form, dynamometers typically provide a fixed architecture for measuring torque, speed, and power, with their scope primarily centered on these parameters and only limited emphasis on capturing aggregated real-time performance factors such as battery load and energy flow across the diverse range of emerging electric vehicle (EV) powertrain architectures. The objective of this work is to develop a valid, appropriate, scalable modular test framework that combines a real-time virtual twin of a compact physical dynamometer with world leading real-time mechanical and energy parameters/attributes useful for its virtual validation, as well as the evaluation of other unknown parameters that respectively span iterations of hybrid and electric vehicle configurations, ultimately allowing the assessment of multiple chassis without having to modify the physical testing facility's test bench. This integration enables a blended approach, using a live data source for now, providing a point of calibration and validation for the virtual model(s), as well as using the virtual model capability to determine other unknown/measurable characteristics about the physical model. So, this test framework makes that system's capability, representing an enhancement to its ability, with a virtual twin merging them together to enable virtual evaluation of multiple configurations of the chassis without changing the physical test stand. So, this combined real-world and virtual framework offers a scalable and flexible testing and modelling platform for both early performance characterisation, as well as life cycle-based energy evaluations. In responding to the identified gaps, this work introduces an innovative hybrid chassis dynamometer framework that applies to a real-world test bench in tandem with a concurrently simulated virtual model, offering early-stage validation and optimisation potential using the shift-left development proposition. The result is a reusable and forward-thinking platform supporting efficient EV development by forecasting and drawing informed insights into energy flow, battery performance, and lifecycle behaviour from ahead of typical physical testing boundaries.
Kumar, AkhileshV, Yashvati
Real-world usage subjects two-wheelers to complex and varying dynamic loads, necessitating early-stage durability validation to ensure robust product development. Conducting a full life-cycle durability testing on proving grounds is time-consuming, extremely difficult for the riders involved, and costly, which is why accelerated testing using rigs such as the road simulator system have become a preferred approach. The use of road simulators necessitates, accurately measured inputs and precise simulation to ensure proper actuation of the rig, thereby enabling realistic representation of road undulations. This paper covers two important aspects essential for achieving an accurate and clear representation of road simulation in a 4-DOF road simulator, encompassing both longitudinal and vertical simulations at the front and rear of the vehicle. The first aspect involves the development of an instrumentation strategy for the two-wheeler, with careful identification of directionally sensitive locations on the sprung mass and the unsprung mass, to enable precise simulation of all four degrees of freedom within the road simulator. Secondly, a different simulation method is adapted based on the frequency response of the control inputs, enabling more efficient utilization of the measured parameters and ensuring accurate simulation. This selection has been guided by results from the spectral data analysis of the response channels and the initial road simulator model output. Testing was conducted across different proving ground test track, speeds, and loading conditions.
Ganju, ShubhamV, VijayamirtharajPrasad, SathishR S, Mahenthran
The transition toward zero-carbon propulsion technologies has highlighted the urgent need for specialized test infrastructure to support hydrogen and alternative fuel research. This paper presents the conceptualization, design, and operation of a High-Pressure Direct Injection (HPDI) Hydrogen Internal Combustion Engine (H2 ICE) test facility with integrated ammonia fuel testing capability, marking a significant advancement in India’s sustainable automotive research efforts. Drawing from practical experience, it outlines crucial technical specifications, safety protocols, and best practices for establishing robust, adaptable, and secure testing environments. Addressing the industry’s need for dedicated infrastructure, it is engineered for adaptability across various engine types including heavy-duty, light-duty, and multi-utility vehicles while aligning with global technical standards. Key technical considerations include a transient dynamometer with an advanced automation system for precise control of both hydrogen and ammonia test cycles. Emission measurement systems such as hydrogen analyzer, ammonia-specific FTIR, particle number counter, and particle size distribution analyzer, are essential for analyzing regulated and unregulated emissions that are critical to sustainable fuel development. The hydrogen fuel storage and distribution system support up to 500 bar pressure, incorporating certified components. Three distinct supply lines operating at 350 bar (for HPDI), 100 bar (for Low Pressure Direct Injection), and 20 bar (for Port Fuel Injection) to accommodate diverse engine configurations. A separate ammonia delivery system ensures dual-fuel testing while addressing its specific chemical and safety needs. Safety remains a cornerstone of the facility's design due to hydrogen’s flammability and ammonia’s toxicity. Essential measures include a high-capacity ventilation, ATEX-rated electricals, real-time gas detection, inert-gas fire suppression, remote monitoring using CCTV, thermal imaging and acoustic sensors. The facility serves as a benchmark for hydrogen and ammonia ICE research in emerging markets, providing practical insights, and technical recommendations and guidance for aligned infrastructure development in support of a zero-carbon mobility future.
Dhyani, VipinKurien, CaneonSubramanian, BalajiKhandai, ChinmayanandaMuralidharan, M
The Exhaust Emission Control is a vital part of automotive development aimed at ensuring effective control of pollutants such as NOx, CO, and HC. The traditional method of calibrating emission control strategies is a highly time-consuming process, which requires extensive vehicle testing under a variety of operating conditions. The frequent updates in emission legislation requires a high-efficiency process to achieve a faster time-to-market. The use of Machine Learning (ML) in the domain of emission calibration is the need of the hour to proactively improve the process efficiency and achieve a faster time-to-market. This paper attempts to explores emerging trend of Machine Learning (ML) based data analysis that have improved the overall process efficiency of emission control calibration. The data generated by automated programs could be used directly in data analysis with minimal or no need for data cleaning. The Machine Learning (ML) models could be trained by historical data from relevant engine platforms to predict the output. The integration of Machine Learning (ML) models with automated measurement processes further enhances the process by enabling model-based calibration development. The use of automated programs and machine learning (ML) models could ensure high accuracy of the emission calibration data. This methodology could significantly reduce the need for volumes of measurements required for data analysis and calibration. This could further help in optimized usage of testing facilities, ultimately saving time and resources. A 70% overall savings in time and resources could be expected with the use of automation and machine learning models. This methodology also supports faster calibration development cycles that would be required for adhering to frequent legislative changes and achieving faster time-to-market.
Dhayanidhi, HukumdeenBalasubramanian, KarthickA, Akash
A significant contributor to particle mass (PM) emissions originating from road transport are particles emitted from brakes, which in Europe are considered in the upcoming Euro 7 emission legislation. UN-GTR (United Nations Global Technical Regulation) no. 24 describes the methodology for measuring brake particle emissions in a test cell setting with a dynamometer, both in terms of PM and PN (particle number). A regulation-compliant test fulfills various quality criteria for different control parameters, which can often be met by applying different control strategies. In this study, we evaluate the effects of implementing different control strategies for torque applied to the brake by the dynamometer, as well as for sampling flow. Additionally, we discuss the cost-saving potential of increasing the automation degree of testing, as well as modifying existing testbeds to accommodate brake emission testing. The torque control strategies applied in this study did not influence PN or PM emissions. For mass-based sampling flow control, adjusting the flow according to momentary readings of pressure and temperature will lead to variation in isokinetic ratio. Conversely, setting constant values of pressure and temperature will lead to variation in volume flow through the cyclone. For realizing cost-saving potential, we present two new technical solutions: AVL PM Sampler xChange for automating the PM measurement, and AVL Brake Emission 3rd Party Integration platform for integrating AVL brake emission measurement instruments into already existing testbed infrastructures, that are only missing the instrumentation (e.g., a converted engine dynamometer).
Martikainen, SampsaWeidinger, ChristophHuber, Michael Peter
O-rings play a critical role in ensuring leak-proof seals in a wide range of engineering systems. Accurate prediction of their compression and relaxation behavior under various material and geometric configurations is essential for optimal design and reliability. This study presents an analysis of machine learning techniques to predict two key performance outputs, compression force and relaxation force (after 10 minutes) trained on computer-aided engineering (CAE) simulation data. The experimental setup was represented in CAE simulation and the results were compared with experimental data conducted at ZF test facilities. Simulation results correlated well with the experimental data (deviation was less than the 5%). To create a dataset for training machine learning (ML) models, realistic ranges for the input parameters such as hardness and geometrical parameters were determined, and simulation data were generated using design of experiments (DOE). Multiple ML models were developed and evaluated based on error metrics and diagnostic plots. The objective of this study was to identify the most effective algorithm for capturing complex nonlinear relationships between input parameters and target performance metrics. Neural Network (NN) model performed well in predicting the forces in the considered design space. For new data outside the training set, it was able to predict the forces with minimal error (mean absolute percentage error of 2.5% and R2 of 0.99). A tool was created with this ML model, which helps designers to take a data informed decision and enhance product development process. Using this tool forces can now be obtained instantly, whereas the complete process (design and simulation) requires significant time. This approach shows the feasibility of combining machine learning with engineering simulations to speed up the design cycle and lower development costs.
Kosgi, DurgaprasadAlva, P PanchamDangeti, VenkataKrishna Pavan
The automotive industry is rapidly extending the capabilities of automated systems by incorporating connectivity and cooperation features that enable real-time information exchange between vehicles and road infrastructure. Within the Connected, Cooperative, and Automated Mobility (CCAM) framework, Vehicle-to-Vehicle (V2V) communication is expected to play a key role in improving road safety, traffic efficiency, and driving comfort. This work addresses a practical implementation of the standardized Manoeuvre Coordination Messages (MCMs), as defined in the ongoing ETSI standard (ETSI TS 103 561). The proposed approach is demonstrated through a cooperative cut-in use case in which two vehicles negotiate a lane change manoeuvre. In the considered scenario, the ego vehicle, driven by a Highway Pilot (HWP) system, receives the intention to cut-in from a neighbouring cooperative vehicle through an MCM. In response, the ego vehicle adapts its behaviour by decelerating to generate a safe longitudinal gap, which allows the cooperative vehicle to merge the ego’s lane. The negotiation process relies on the bidirectional exchange of MCMs to coordinate the timing and trajectories, ensuring both vehicles complete the manoeuvre safely. Additionally, the Cooperative Awareness Messages (CAMs) allow the vehicles to share real-time information such as position, speed and heading. This connected-enhanced approach extends the capabilities of local perception systems, enabling an improved performance and reaction time to surround traffic participants. The described use case is implemented and validated in a prototype vehicle equipped with V2V communication capabilities and a Highway Pilot (HWP) SAE level 3 driving automation system. Proving ground tests demonstrate that the system can successfully negotiate cut-in manoeuvres in real time, enhancing both safety and traffic flow. The results confirm the feasibility of deploying standardized V2V coordination mechanisms within operational automated driving functions and lay the groundwork for broader integration into future CCAM applications.
Leiva Ricart, GiselaDomingo Mateu, Bernat
In the rapidly evolving and highly competitive automotive industry, manufacturers are under immense pressure to bring products to market quickly while meeting customer expectations. As a result, optimizing the product development timeline has become essential. Structural integrity analysis for chassis and suspension systems lies in the accurate acquisition of operational load spectra, conventionally executed through Road Load Data Acquisition (RLDA) on instrumented vehicles subjected to proving ground excitation. At this point, RLDA is mainly used for final validation and fine-tuning. If any performance shortfalls, such as premature component failure or durability issues, are discovered, they often trigger design revisions, prototype rework, and additional testing. This study proposes a Virtual Road Load Data Acquisition (vRLDA) methodology employing a high-fidelity full-vehicle multibody dynamic (MBD) representation developed in Adams Car. The system is parameterized and uses high-resolution F-Tire models to replicate transient tire-road interactions, digital tracks are derived from LIDAR-based topography of durability test tracks. Boundary conditions replicate vehicle drive speed and payload. Attachment point load are extraction and its statistical signal fidelity assessed via RMS error metrics, relative damage and peak amplitude congruence against physical RLDA data. Results demonstrate high correlation across critical load channels, accelerations, LVDT & validating the computational workflow’s capacity to replicate operational durability environments. The vRLDA approach thus provides a flexible, scalable architecture to support pre-validation of suspension modules, enabling the design verification, reduction in prototype, instrumentation dependency, and improved convergence of CAE-based life prediction models with empirical outcomes.
Goli, Naga Aswani KumarPrasad, Tej Pratap
This paper contains theoretical and experimental studies of the measurement accuracies of two methods commonly used by vehicle industries and other stakeholders to determine vehicle center of gravity (CG) height. The two methods, which both appear in international standards, are the Axle Lift method and the Stable Pendulum method. The Stable Pendulum method requires a dedicated swinging platform mechanism*, but it is generally considered to be more accurate than the Axle Lift method. Both methods rely on equations for computing CG height that are based on static balance models of a vehicle tested at various pitch angles. For each method, the accuracy of the resulting CG height computations is a function of the individual measurements needed in the model equations. The individual measurements needed depend on the method used, but they include weights, angles, and distance measurements. A theoretical error analysis study is presented that provides insight into the accuracy of both methods given the uncertainty in the required individual measurements. The theoretical error analysis provides uncertainty bounds on the measurements based on the models and equations used for the measurement methods. However, the uncertainty bounds do not account for potential measurement bias related to not adhering exactly to the test method protocols or related to attributes of the test methods not considered in the models and equations. Discussion of measurement bias for both methods, supported by the measurements made, is also provided. Tests using two vehicles and a calibration fixture with known CG height are conducted using both test methods. These tests provide insight into the repeatability of each method, and the tests done using the calibration fixture augment the theoretical error analyses and support claims made regarding the likely accuracy expectations of each method. The findings presented can guide on-highway and off-road vehicle manufacturers, regulatory agencies, and test laboratories in their decisions regarding which of the two methods is best suited for their needs to determine vehicle CG height.
Heydinger, GaryZagorski, ScottBartholomew, MeredithAndreatta, Dale
The paper aimed to improve the accurate quantification of driver drowsiness and to provide comprehensive, evidence-based validation for a Vision-Based Driver Drowsiness and Alertness Warning System. Advanced quantification of driver drowsiness is designed to enhance distinction of true positive events from False Positive and False Negative events. Methodology to pursue this included assessing inputs such as facial features, driver visibility, dynamic driving tasks, driving patterns, driving course time and vehicle speed. The system is programmed to actively learn Eye Aspect Ratio (EAR) reference and adapt personalised EAR threshold value to process EAR frames against the learnt threshold value. This method optimized the data frames to enhance the evaluation and processing of essential frames, thereby reducing delays in the processor and the Human-Machine Interface (HMI) warning module. Comprehensive validation is systematically conducted within a controlled test track environment to ensure precise execution of protocols, maintaining inputs closely aligned with real-time scenarios. The test methodology comprised the execution of pre-defined protocols that is steering robot and a technology-neutral procedure. Pre-defined protocols are scenarios created using the aforementioned assessing inputs. Cartesian coordinates of the system’s camera and driver eye point relative to the seating reference point (SgRP) are identified using a coordinate measurement machine (CMM) to measure the driver's position within the camera's field of view and mark the visibility zones. The protocols are executed with precision using a global navigation satellite system (GNSS), visual sensor, audio sensor and data logger. Subsequently, the system is tested with number of drivers trained on the Karolinska Sleepiness Scale (KSS) to conduct technology-neutral method for statistical analysis. Detailed analysis of the tested data, concluded with results and explored future prospects for quantifying driver drowsiness are discussed. The paper also discussed observations and challenges associated with the functionality of conventional systems and protocols currently deployed in the market.
Balasubrahmanyan, ChappagaddaAkbar Badusha, A
For regions with cold climate, the range of an electric bus becomes a serious restriction to expanding the use of this type of transport. Increased energy consumption affects not only the autonomous driving range, but also the service life of the batteries, the schedule delays and the load on the charging infrastructure. The aim of the presented research is to experimentally and computationally determine the energy consumption for heating the driver's cabin and passenger compartment of an electric bus during the autumn-winter operation period, as well as to identify and analyze ways to reduce this energy consumption. To determine the air temperature in the passenger compartment, a mathematical model based on heat balance equations was used. This model was validated using data from real-world tests. The research was conducted at a proving ground under two conditions: driving at a constant speed and simulating urban bus operation with stops and door openings. The causes of heat loss in electric bus heating were analyzed. It was found that approximately 35% of heat is lost through the ventilation system operating in fresh air intake mode, around 30% is lost due to door openings at stops, 17% dissipates through the windows, and 18% through the bus walls, floor, and roof. Using the mathematical model, a series of calculations were performed to estimate total energy consumption over the heating season for various heating systems and control system settings.
Kozlov, AndreyTerenchenko, AlexeyStryapunin, Alexander
The precise validation of radar sensor is necessary due to surging demand for reliable Advanced Driver-Assistance Systems (ADAS) and autonomous driving technologies. Over-the-Air (OTA) Hardware-in-the-Loop approach is the optimal solution for the current challenges facing with traditional on road testing. This approach supports productive, controllable and repetitive environment because of its lab-based setup which will eliminates the drawbacks such as high costs, limited repeatability, safety related issues. Key parameters of radar such as accurate detection of objects, analysis of doppler velocity, range estimation, angle of arrival measurement, can be tested dynamically. And this test setup offers wide range of testing scenarios, including varying distance of target, relative speeds, simulation of objects and environmental effects also supported.OTA provides the flexibility to eliminate the physical test tracks or targets so that developers can simulate the errors, by introducing faults into the systems and validate the compliances as per the industry standards, OTA HIL testing completely reduces development time and costs through enhancing test coverages, which will increase radar performance. This paper describes the system architecture, test plans, experimental results, demonstrate the critical role of OTA HIL in advancing automotive radar workflows and ensuring reliable ADAS and autonomous driving functionalities.
Jadhav, TejasKarle, UjjwalaPaul, HarshitSNV, Karthik
Higher road noise is perceived in the cabin when the test vehicle encounters road irregularities like bump or pothole in the public roads. The transfer of transient road inputs inside the body caused objectionable cabin noise. Measurements are conducted at different road surfaces to identify the patch where the objective data well correlated with the noise measured at the public road. Wavelet analysis is carried out to identify the frequency zones since the events are transient in nature. TPA is carried out in time domain to identify the nature of the noise and the dominant path through which the transient road forces are transferring inside the body. Based on the outcome of TPA, various countermeasures like reduction of dynamic stiffness of suspension bushes, TMDs on the path are proposed to reduce the structure borne noise. Criteria which need to be considered for reduction of cabin noise due to transient road inputs is also discussed.
S, Nataraja MoorthyRao, ManchiSelvam, EbinezerRaghavendran, Prasath
In the area of structural durability testing using servo hydraulic actuators, developing drive files for the actuators is a major step. Testing outcomes depend on ensuring the simulation accuracy of each drive file. These drive files are developed in an iterative process for different test track surfaces at different road and load combinations till the time we achieved better correlation. Evaluation of simulation accuracy of the drive files is an extensive manual review process making it time-consuming and resource-intensive. To address this challenge, an application has been develop to automate the comparison of actuator signals with predefined target signal files. This tool enables quick and accurate analysis of each drive file in a test run facilitating a comprehensive review of signal deviations. Each test run is having thousands of drive files based on road-load mix and actuator settings. This application helped us in significantly optimizing the simulation workflow by reducing the manual effort in reviewing thousands of files and statistical evaluation. The developed solution improves productivity and enhances quality in structural durability assessments using servo hydraulic actuators.
Soni, YashKatake, VrishaliMullapudi, DattatreyuduChaskar, Mithun
In Automobile, Gasoline Engines are being used along with electrically operated shut-off valve installed at the roof of bus in case of higher capacity of CNG systems. In order to start/ stop CNG supply from cylinder for running of engine/ safety/ servicing an electrical operated ignition switch/ key controlled CNG Shut-Off Valve is placed just after the cylinders. There have been few failures of these CNG shut-off valves in field application. On investigation, it was observed that the CNG shut-off valve gets failed due to water ingress in coils from the cracks on surface generated due to spray of water (due to daily washing of bus and rain) on heated shut-off valves. In order to validate this field failure and subsequent validation of modified design, a need was felt to use a test rig which can exactly simulate the water spray based thermal shocks. However, there was no low cost facility available to simulate the field service condition for validation. Therefore, a low cost test set-up was designed and developed to simulate the failure in test lab to analyze the failure and root cause analysis and further durability validation of improved design. The designed and developed test rig was very useful to investigate the root cause of failures and validation of improved samples. The test rig has been in operation for 2 years without any failures and has validated more than 30 samples of existing and improved samples. The test rig was designed and developed completely in-house and is a low cost in price as well as low running cost.
Srivastava, Pravin KumarVivekanand, VivekanandKumar, Satish
Highway Pilot (HWP) systems, classified as SAE Level 3 Automated Driving Systems (ADS), represent a potential advancement for safer and more efficient highway drives. In this work, the development of a connected HWP prototype is presented. The HWP system is deployed in a real test vehicle and designed to operate autonomously in highway environments. The implementation presented in this paper covers the complete setup of the vehicle platform, including sensor selection and placement, hardware integration and communication interfaces for both autonomous functionality and Vehicle-to-Everything (V2X) connectivity. The software architecture follows a modular design, composed of modules for perception, decision-making and motion control to operate in real-time. The prototype integrates Vehicle-to-Vehicle (V2V) communication, such as Cooperative Awareness Messages (CAM), to enhance situational awareness and improve the overall system behaviour. The modular structure allows new functionalities to be developed and integrated into the same platform, so it becomes a beta testing platform for the early-stage experimentation of innovative features. To validate the prototype, execution of scenario-based testing on a proving ground is used, which is part of the Safety Assurance Framework (SAF), which provides structured methods to help define test scenarios to cover the system’s Operational Design Domain (ODD). Experimental results demonstrate the prototype’s ability to operate in varied highway scenarios.
Domingo Mateu, BernatLeiva Ricart, GiselaFacerias Pelegri, MarcPerez, Marc
The deployment of autonomous trucks in off-road environments poses significant engineering challenges due to terrain variability and dynamic operating conditions. While recent advancements in perception, planning, and control architectures have improved vehicle autonomy, experimental validations comparing autonomous and manual control particularly regarding propulsion efficiency remain limited. This study addresses this gap by conducting structured field experiments to evaluate the performance of a heavy-duty truck operating in autonomous and manual modes. Tests were performed on a dedicated proving ground using a multi-sensor autonomous system. Key performance indicators included vehicle speed stability, engine speed regulation, and fuel consumption. The results show that autonomous driving achieved a 4.5% reduction in fuel consumption compared to manual operation. This gain is attributed to the system’s ability to maintain lower speed variance and more consistent engine behavior, especially during curved segments. These findings highlight the operational and energy efficiency advantages of autonomous control strategies in off-road logistics and support their broader adoption in agricultural and industrial applications.
Paula Silva, CiriloYoshioka, Leopoldo RidekiKitani, Edson CaoruAndré, Fatec SantoSilva, Nouriandres Liborio
The U.S. Space Force (USSF) Space Systems Command (SSC) achieved a major milestone during a demonstration event in August, showcasing the Joint Antenna Marketplace (JAM) and successfully transferring the U.S. Naval Research Laboratory's (NRL) Transmit/Receive Enterprise (TREx) Service from a research and development project into an SSC operational prototype. During the demonstration, the team demonstrated the use of commercial antennas for real-time contacts between a Space Development Agency's (SDA) satellite operations center and their Tranche 0 satellites using JAM which leveraged the newly integrated TREx system.
Oak Ridge National Laboratory (ORNL) researchers have overcome a barrier to using a more affordable, dry process for manufacturing the Li-ion batteries used in vehicles and electronic devices. The resulting batteries provide greater electricity flow and reduced risk of overheating.
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