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Though modal analysis is a common tool to evaluate the dynamic properties of a structure, there are still many individual decisions to be made during the process which are often based on experience and make it difficult for occasional users to gain reliable and correct results. One of those experience-based choices is the correct number and placement of reference points. This decision is especially important, because it must be made right in the beginning of the process and a wrong choice is only noticeable in the very end of the process. Picking the wrong reference points could result in incomplete modal analysis outcomes, as it might make certain modes undetectable, compounded by the user's lack of awareness about these missing modes. In the paper an innovative approach will be presented to choose the minimal number of mandatory reference points and their placement.

For automotive engineers involved in crash reconstruction and analysis, a knowledge of basic accident reconstruction principles and techniques is essential, but often insufficient to answer all of the questions posed by design engineers, regulators, and lawyers. This course takes participants beyond the basics of accident reconstruction to physical models and analysis techniques that are unique to the reconstruction of single-vehicle rollover crashes.

The evaluation of aircraft characteristics through flight test maneuvers is fundamental to aviation safety and understanding flight attributes. This research project proposes a comprehensive methodology to detect and analyze aircraft maneuvers using full flight data, combining signal processing and machine learning techniques. Leveraging the Wavelet Transform, we unveil intricate temporal details within flight data, uncovering critical time-frequency insights essential for aviation safety. The integration of Long Short-Term Memory (LSTM) models enhances our ability to capture temporal dependencies, surpassing the capabilities of machine learning in isolation. These extracted maneuvers not only aid in safety but also find practical applications in system identification, air-data calibration, and performance analysis, significantly reducing pre-processing time for analysts.

The paper presents a theoretical framework for the detection and first-level preliminary identification of potential defects on aero-structure components while employing ultrasonic guided wave based structural health monitoring strategies, systems and tools. In particular, we focus our study on ground inspection using laser-Doppler scan of surface velocity field, which can also be partly reconstructed or monitored using point sensors and actuators on-board structurally integrated. Using direct wave field data, we first question the detectability of potential defects of unknown location, size, and detailed features. Defects could be manufacturing defects or variations, which may be acceptable from design and qualification standpoint; however, those may cause significant background signal artifacts in differentiating structure progressive damage or sudden failure like impact-induced damage and fracture.

To investigate the rollover phenomena experienced by all-terrain vehicles (ATVs) during their motion caused by input from the road surface, a combined simulation using CarSim and Simulink has been employed to validate an active anti-rollover control strategy based on differential braking for ATVs, followed by vehicle testing. In the research process, a nonlinear three-degrees-of-freedom vehicle model has been developed. By utilizing a zero-moment point index as a rollover warning indicator, this approach could accurately detect the rollover status of the vehicle, particularly in scenarios involving low road adhesion on unpaved surfaces, which are characteristic of ATV operation. The differential braking, generating a roll moment by adjusting the amount of lateral force each braked tire can generate, was proved as an effective method to enhance rolling stability.

This specification covers a titanium alloy in the form of welding wire (see 8.5).

This procurement specification covers aircraft-quality solid rivets made from a corrosion resistant nickel-copper alloy of the type identified under the Unified Numbering System as UNS N04400 and of 46 ksi minimum shear strength.

This procurement specification covers tubular, blind rivets fabricated from a corrosion resistant nickel-copper alloy of the type identified under the Unified Numbering System as UNS N04405, and of 52 ksi minimum shear strength for self-plugging style rivets.

This procurement specification covers solid rivets and hollow end rivets made from a corrosion and heat resistant steel of the type identified under the Unified Numbering System as UNS S66286 and of 80 ksi single shear strength at room temperature.

THOR-AV 5F, a modified THOR-5F dummy, was designed to represent both upright and reclined occupants in vehicle crashworthiness studies. The dummy was evaluated in four test conditions: a) 25° seatback, 15 km/h, b) 25° seatback, 32 km/h, c) 45° seatback, 15 km/h, d) 45° seatback, 32 km/h. The dummy’s biomechanical responses were compared against those of postmortem human subjects (PMHS) tested in the same test conditions. The latest National Highway Traffic Safety Administration (NHTSA) BioRank method was used to provide a biofidelity ranking score (BRS) for each data channel in the tests to assess the dummy’s biofidelity objectively. The evaluation was categorized into two groups: restraint system and dummy. In the four test conditions, the restraint system showed good biofidelity with BRS scores of 1.49, 1.47, 1.15, and 1.79, respectively.

Frontal-crash sled tests were conducted to assess submarining protection and abdominal injury risk for midsized male occupants in the rear seat of modern vehicles. Twelve sled tests were conducted in four rear-seat vehicle-bucks with twelve post-mortem human surrogates (PMHS). Select kinematic responses and submarining incidence were compared to previously observed performance of the Hybrid III 50th-percentile male and THOR-50M ATDs (Anthropomorphic Test Devices) in matched sled tests conducted as part of a previous study. Abdominal pressure was measured in the PMHS near each ASIS (Anterior Superior Iliac Spine), in the inferior vena cava, and in the abdominal aorta. Damage to the abdomen, pelvis, and lumbar spine of the PMHS was also identified. In total, five PMHS underwent submarining. Four PMHS, none of which submarined, sustained pelvis fractures and represented the heaviest of the PMHS tested. Submarining of the PMHS occurred in two out of four vehicles.

With the current trend of including the evaluation of the risk of brain injuries in vehicle crashes due to rotational kinematics of the head, two injury criteria have been introduced since 2013 – BrIC and DAMAGE. BrIC was developed by NHTSA in 2013 and was suggested for inclusion in the US NCAP for frontal and side crashes. DAMAGE has been developed by UVa under the sponsorship of JAMA and JARI and has been accepted tentatively by the EuroNCAP. Although BrIC in US crash testing is known and reported, DAMAGE in tests of the US fleet is relatively unknown. The current paper will report on DAMAGE in NCAP-like tests and potential future frontal crash tests involving substantial rotation about the three axes of occupant heads. Distribution of DAMAGE of three-point belted occupants without airbags will also be discussed. Prediction of brain injury risks from the tests have been compared to the risks in the real world.

In this paper, experimental studies were conducted to examine the mechanical behavior of a polymer composite material called polyamide with glass fiber (PA6-GF), which was fabricated using the three-dimensional (3D) fusion deposition modeling (FDM) technique. FDM is one of the most well-liked low-cost 3D printing techniques for facilitating the adhesion and hot melting of thermoplastic materials. PA6 exhibits an exceptionally significant overall performance in the families of engineering thermoplastic polymer materials. By using twin-screw extrusion, a PA6-GF mixed particles made of PA6 and 20% glass fiber was produced as filament. Based on literature review, the samples have been fabricated for tensile, hardness, and flexural with different layer thickness of 0.08 mm, 0.16 mm, and 0.24 mm, respectively. The composite PA6-GF behavior is characterized through an experimental test employing a variety of test samples made in the x and z axes.

The Bendix Wingman Fusion – a radar and camera collision mitigation system (CMS) available on commercial vehicles – was evaluated in two separate test series to determine its performance in simulated rear collision scenarios. In the first series of tests, evaluations were conducted in daytime, nighttime, and rainy conditions between 15 to 58 miles per hour (mph) to evaluate the performance of the audible and visual forward collision warning (FCW) system in a first-generation Bendix Wingman Fusion CMS while approaching a stationary live vehicle target (SLVT) in a 2017 Kenworth T680. A second test series was conducted with a 2017 Kenworth T680 traveling at 50 mph in daytime conditions approaching a decelerating vehicle to evaluate the Bendix Wingman Fusion CMS on the truck. Both test series sought to determine the maximum distance the system would warn prior to the test driver swerving around the SLVT or moving vehicle target.

Verification and validation (V&V) of autonomous vehicles (AVs) is a challenging task. AVs must be thoroughly tested, to ensure their safe functionality in complex traffic situations including rare but safety-relevant events. Furthermore, AVs must mitigate risks and hazards that result from functional insufficiencies, as described in the Safety of the Intended Functionality (SOTIF) standard. SOTIF analysis includes iterative identification of driving scenarios that are not only unsafe, but also unknown. However, identifying SOTIF’s unknown-unsafe scenarios is an open challenge. In this paper we proposed a systematic optimization-based approach for identification of unknown-unsafe scenarios. The proposed approach consists of three main steps including data collection, feature extraction and optimization towards unknown unsafe scenarios.

Highway safety remains a significant concern, especially in mixed traffic scenarios involving heavy-duty vehicles (HDV) and smaller passenger cars. The vulnerability of HDVs following closely behind smaller cars is evident in incidents involving the lead vehicle, potentially leading to catastrophic rear-end collisions. This paper explores how automatic speed enforcement systems, using speed cameras, can mitigate risks for HDVs in such critical situations. While historical crash data consistently demonstrates the reduction of accidents near speed cameras, this paper goes beyond the conventional notion of crash occurrence reduction. Instead, it investigates the profound impact of driver behavior changes within desired travel speed distribution, especially around speed cameras, and their contribution to the safety of trailing vehicles, with a specific focus on heavy-duty trucks in accident-prone scenarios.