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Internal audits are a requirement of the AS9100, AS 13100 and RM 13005 and are intended to verify the compliance and effectiveness of an organization's quality management system. The methods and techniques for performing internal audits have significantly changed in the aviation, space and defense industries, and internal auditors must be knowledgeable of these requirements and the expectations as identified in the standard.

Crash reconstruction is a scientific process that utilizes principles of physics and empirical data to analyze the physical, electronic, video, audio, and testimonial evidence from a crash to determine how and why the crash occurred. This course will introduce this reconstruction process as it gets applied to various crash types - in-line and intersection collisions, pedestrian collisions, motorcycle crashes, rollover crashes, and heavy truck crashes. Methods of evidence documentation will be covered. Analysis methods will also be presented for electronic data from event data recorders and for video.

Investigating human driver behavior enhances the acceptance of the autonomous driving and increases road safety in heterogeneous environments with human-operated and autonomous vehicles. The previously established driver fingerprint model, focuses on the classification of driving style based on CAN bus signals. However, driving styles are inherently complex and influenced by multiple factors, including changing driving environments and driver states. To comprehensively create a driver profile, an in-car measurement system based on the Driver-Driven vehicle-Driving environment (3D) framework is developed. The measurement system records emotional and physiological signals from the driver, including ECG signal and heart rate. A Raspberry Pi camera is utilized on the dashboard to capture the driver's facial expressions and a trained convolutional neural network (CNN) recognizes emotion. To conduct unobtrusive ECG measurements, an ECG sensor is integrated into the steering wheel.

Evolving to MedDev provides a new opportunity for executives in aerospace, automotive and medical devices companies to connect and develop long-term growth strategies and find ways to meet the increased short-term demand for medical supplies

Evolving to MedDev provides a new opportunity for executives in aerospace, automotive and medical devices companies to connect and develop long-term growth strategies and find ways to meet the increased short-term demand for medical supplies

Evolving to MedDev provides a new opportunity for executives in aerospace, automotive and medical devices companies to connect and develop long-term growth strategies and find ways to meet the increased short-term demand for medical supplies

Evolving to MedDev provides a new opportunity for executives in aerospace, automotive and medical devices companies to connect and develop long-term growth strategies and find ways to meet the increased short-term demand for medical supplies

Evolving to MedDev provides a new opportunity for executives in aerospace, automotive and medical devices companies to connect and develop long-term growth strategies and find ways to meet the increased short-term demand for medical supplies

Evolving to MedDev provides a new opportunity for executives in aerospace, automotive and medical devices companies to connect and develop long-term growth strategies and find ways to meet the increased short-term demand for medical supplies

Evolving to MedDev provides a new opportunity for executives in aerospace, automotive and medical devices companies to connect and develop long-term growth strategies and find ways to meet the increased short-term demand for medical supplies

Evolving to MedDev provides a new opportunity for executives in aerospace, automotive and medical devices companies to connect and develop long-term growth strategies and find ways to meet the increased short-term demand for medical supplies

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

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.

Heavy Vehicle Event Data Recorders (HVEDRs) have the ability to capture important data surrounding an event such as a crash or near crash. Efforts by many researchers to analyze the capabilities and performance of these complex systems can be problematic, in part, due to the challenges of obtaining a heavy truck, the necessary space to safely test systems, the inherent unpredictability in testing, and the costs associated with this research. In this paper, a method for simulating vehicle speed sensor (VSS) inputs to HVEDRs to trigger events is introduced and validated. Full-scale instrumented testing is conducted to capture raw VSS signals during steady state and braking conditions. The recorded steady state VSS signals are injected into the HVEDR along with synthesized signals to evaluate the response of the HVEDR. Brake testing VSS signals are similarly captured and injected into the HVEDR to trigger an event record.

The IncQuery AUTOSAR-UML Bridge is an innovative solution for Assisted Documentation Creation and Automated Handover, aiming at driving a paradigm shift in integrated digital engineering in the automotive domain. The AUTOSAR-UML Bridge is addressing a well-known gap in the engineering ecosystem of automotive design, where the co-design of AUTOSAR models and other model-based artifacts is often hampered by tedious workflows involving manual syncing of model contents between AUTOSAR and UML/SysML tools. The Bridge is aiming at streamlining the workflow by generating high-quality UML models from AUTOSAR projects, with built-in ISO26262 and ASPICE compliance. Automotive software architects and systems engineers spend a lot of time with creating ISO26262-compliant documentation, by creating UML models from AUTOSAR architecture designs, or establishing traceability between requirements captured in SysML and design artefacts that exist in both modeling languages.

The author has developed UV based photocatalytic air purification system (Mathur, 2021, 2122, 2023) that can eliminate all pathogens from the cabin air including COVID-19. In this study, the focus is to determine the risk of infection due to pathogens/germs in the cabin of an automobile. Author has determined the risk of infection by using Wells-Riley model and conducted CFD analysis to determine propagation of virus in cabin as a function of: 1 Cabin Volume & Number of Occupants (Wells-Riley Model in OSA mode): (i) Cabin volume from: Small Sedan, Large Sedan and a SUV; with 4 occupants (males & females); Number of infector 1; Air flowrate (m3/min); (ii) A 15-seater minibus – with 10 occupants (males); Number of infectors 1 & 2; Air flowrate (m3/min) 2 CFD to simulate 4 occupants and 1 infector in an automotive cabin – Current investigation is for talking, coughing and sneezing with blower off in Recirc mode wit (i) Infector in the front seat; (ii) Infector in the rear seat.