Browse Topic: Documentation
The useability of development processes in the automotive sector has decreased in the past years to a level at which their application and true benefit to is being questioned. Such degradation can be attributed to new additions to the processes and introduction of FuSa and Cybersecurity standards. The processes try to keep up with the shift from the traditional ‘plan–implement–test–roll-out' methodology to more agile methods. In addition, process departments typically in charge of these processes, focus on compliance to the letter of the standard to achieve certification, often with little thought to the actual implementation and the process they will be used by their engineering teams. Process growth to meet the needs of new and more complex technologies often mandates the use of new tools, which if implemented incorrectly can lead to unnecessary bureaucracy and additional overheads. Furthermore, the language of these new processes is in a form from assessor, making it difficult for an engineer to understand, interpret and implement. As a result, engineers become annoyed, losing productivity and motivation when working with what they perceive as burdensome standards, that simply exist to slow development. This has a huge impact on the competitiveness of companies especially in markets that are facing existential threats from internal and external pressures such as the automotive industry. Against popular belief, the application of generative AI (and large language models) will not solve the problem. On the contrary, it risks automating complex processes in the same unfamiliar language and creating documents to serve process overhead, rather than engineering development. This paper presents inefficiencies in the current state-of-the art processes used in the automotive sector and proposes a structured approach that increases the efficiency of automotive software development. It does so by documenting and implementing development processes based on how engineers actually perform their work. In the second step the adjustments that are necessary to ensure compliance of the product with industry standards are made. Such an approach produces efficient, compact and compliant process definition.
Simulation-driven product development involves numerous computer aided engineering (CAE) model iterations, where each version represents a critical difference. Usually, these multiple model versions are generated by hundreds of simulation engineers working in teams distributed across the globe, making functional collaboration a key to effective product development. To manage vast amounts of CAE data generated by engineers working simultaneously on a project, it is imperative to have a robust version management system to track changes in the CAE data. A robust version management is the backbone of an effective simulation data management (SDM) system. It involves capturing and documenting model changes at every design iteration. Accurate documentation of the model changes is crucial as it helps in understanding the model evolution and collaboration among engineers. However, documenting is usually considered a boring and tedious task by many engineers. This often leads to bad change documentation, which in turn reduces data discoverability and causes knowledge loss. With the onset of artificial intelligence (AI) in engineering simulations, engineers can now learn even more from their simulation data. In this paper, authors have explored an AI-assisted approach for facilitating the change documentation by augmenting the change comments via automatically extracted details, as studied in the SAFECAR-ML research project. The project is funded by the German Federal Ministry of Education and Research (BMBF) under the “KI4KMU” initiative (Research, Development, and Use of AI Methods in SMEs). The main goal of SAFECAR-ML is to develop an AI model that understands the nature of design changes and automatically generates change descriptions. When a detailed and informative change documentation is available, large language model (LLM)-based generative AI can be used for discovering and creating simulation-related content in an SDM system, for example by using retrieval augmented generation (RAG) approaches. A long-term outlook is to build an AI-assisted capability to perform complex tasks in an SDM system, like search and summarization of the data, automatic evaluation of simulation results, and thinking models for researching the available simulation data making recommendations on further model changes.
This investigation reveals many DoD contractors do not treat integration as a stand-alone activity. Instead, integration is an inherent part of the development process. The contractors did not have a specific documented process for integration beyond calling out integration as an activity in the development process. Integration is an integrator unique step within the development process to meet functional and performance requirements. Identification of the interfaces and engineering to match the interfaces requires substantial individual expertise and heuristics for each integration effort resulting in inconsistent non-repeatable integrations. This increases risk, and limits third party integration effectiveness and utility. This paper identifies steps that can be taken to increase the speed and effectiveness of integration while decreasing the effort and dependency on individual expertise.
As part of a human factors research project aimed at optimizing technical documentation used in helicopter maintenance with multimedia elements, we compared different instruction formats to observe their effects on the performance of an assembly task. This task offers us the opportunity to test procedures that call for similar actions as a maintenance task (e.g., localization, action sequencing, assembly). Static (i.e., image and image with text) and dynamic instruction formats (i.e., video, video with text and video with audio) were compared to determine if dynamic formats allowed a better motor performance of the task for assembly reaction time (time needed to complete the assembly) and accuracy. We were also interested in how the use of the text instructions interacted with both visual dynamic and static instructions. Reaction times were recorded and measured with eye tracking data. Subjective data was collected in questionnaires during and after the experiment. Results showed significant differences in the time spent on the instructions and the time spent on the assembly, depending on the format of instructions. Overall, assembly time is shorter with video instruction formats, but videos took longer to be consulted than static formats. Results also showed a difference in the number of actions required to do the assembly. Videos facilitated the right path of action sequence in comparison with static formats. With the analysis of both subjective and objective data, the results give us a better idea of the advantages and drawbacks of using dynamic formats in technical documentation.
As the adoption of Electric Vehicles (EV) and Plug-in Hybrid Electric Vehicles (PHEV) continues to rise, more individuals are encountering these quieter vehicles in their daily lives. While topics such as propulsion sound via Active Sound Design (ASD) and bystander safety through Acoustic Vehicle Alerting Systems (AVAS) have been extensively discussed, charging noise remains relatively unexplored. Most EV/PHEV owners charge their vehicles at home, typically overnight, leading to a lack of awareness about charging noise. However, those who have charged their cars overnight often report a variety of sounds emanating from the vehicle and the electric vehicle supply equipment (EVSE). This paper presents data from several production EVs measured during their normal charging cycles. Binaural recordings made inside and outside the vehicles are analyzed using psychoacoustic metrics to identify sounds that may concern EV/PHEV owners or their neighbors.
Large eddy simulations (LES) of two HVAC duct configurations at different vent blade angles are performed with the GPU-accelerated low-Mach (Helmholtz) solver for comparison with aeroacoustics measurements conducted at Toyota Motor Europe facilities. The sound pressure level (SPL) at four near-field experimental microphones are predicted both directly in the simulation by recording the LES pressure time history at the microphone locations, and through the use of a frequency-domain Ffowcs Williams-Hawking (FW-H) formulation. The A-weighted 1/3 octave band delta SPL between the two vent blades angle configurations is also computed and compared to experimental data. Overall, the simulations capture the experimental trend of increased radiated noise with the rotated vent blades, and both LES and FW-H spectra show good agreement with the measurements over most of the frequency range of interest, up to 5,000Hz. For the present O(30) million cell mesh and relatively long noise data collection of 0.5s, the simulation results can be obtained in about 6 hours on 8 standard GPUs. Accurate and efficient numerical predictions of the SPL from HVAC ducts would allow automotive manufacturers to assess different duct configurations in the early design cycles and avoid the costly countermeasures necessary when excessive noise is observed in the experimental phase of the final design.
Demonstrating deadline adherence for real-time tasks is a common requirement in all safety norms. Timing verification has to address two levels: the code level (worst-case execution time) and the scheduling level (worst-case response time). Determining which methodology is suited best depends on the characteristics of the target processor. All contemporary microprocessors try to maximize the instruction-level parallelism by sophisticated performance-enhancing features that make the execution time of a particular instruction dependent on the execution history. On multi-core systems, the execution time additionally is influenced by interference effects on shared resources caused by concurrent activities on the different cores, which are not controlled by the scheduling algorithm. In the avionics domain, the new FAA AC 20-193 / EASA AMC 20-193 guidance documents formalize predictability aspects of multi-core systems and derive adequate measures for timing verification. Timing verification is a long standing and still very challenging topic. Established techniques include response time analysis, worst-case execution time analysis and real-time tracing. The goal of this article is to summarize the aspects relevant for timing verification, and give an overview of the available techniques. We also explicitly address multi-core considerations, focusing on the latest certification authorities’ publications from the avionics domain.
Artificial intelligence (AI) systems promise transformative advancements, yet their growth has been limited by energy inefficiencies and bottlenecks in data transfer. Researchers at Columbia Engineering have unveiled a groundbreaking solution: a 3D photonic-electronic platform that achieves unprecedented energy efficiency and bandwidth density, paving the way for next-generation AI hardware.
Video analysis plays a major role in many forensic fields. Many articles, publications, and presentations have covered the importance and difficulty in properly establishing frame timing. In many cases, the analyst is given video files that do not contain native metadata. In other cases, the files contain video recordings of the surveillance playback monitor which eliminates all original metadata from the video recording. These “video of video” recordings prevent an analyst from determining frame timing using metadata from the original file. However, within many of these video files, timestamp information is visually imprinted onto each frame. Analyses that rely on timing of events captured in video may benefit from these imprinted timestamps, but for forensic purposes, it is important to establish the accuracy and reliability of these timestamps. The purpose of this research is to examine the accuracy of these timestamps and to establish if they can be used to determine the timing between frames. Four recording devices and six cameras were utilized with varying configurations. All videos recorded the Axon VFR Lightboard as the control measurement. Videos were recorded with each device and each camera configuration at 30, 15, and 4 frames per second. Once recorded, each video was processed using Axon Investigate’s “VFR Lightboard Calculator” to establish the actual timing between each frame. Subsequently, ten timestamp seconds within each video were compared to the actual elapsed time reported by the Lightboard. In total, 54 videos were recorded across all configurations. This study demonstrates the timestamp is not always accurate from second to second. However, a pattern was observed, and a methodology was developed. The average error between the theoretical time and the actual time reported by the Lightboard was 2.99 milliseconds (approximately 0.3%). The maximum error between theoretical and actual time for any timestamp second was 22 milliseconds (approximately 2.2%).
The vehicle wake region is of high importance when analyzing the aerodynamic performance of a vehicle. It is characterized by turbulent separated flow and large low-pressure regions that contribute significantly to drag. In some cases, the wake region can oscillate between different modes which can pose an engineering challenge during vehicle development. Vehicles that exhibit bimodal wake behavior need to have their drag values recorded over a sufficient time period to take into account the low frequency shift in drag signal, therefore, simulating such vehicle configurations in CFD could consume substantial CPU hours resulting in an expensive and inefficient vehicle design iterations process. As an alternative approach to running simulations for long periods of time, the impact of adding artificial turbulence to the inlet on wake behavior and its potential impact on reduced runtime for design process is investigated in this study. By adding turbulence to the upstream flow, the wake can be prevented from settling into a particular mode and will instead rapidly cycle between modes, which may not only allow the drag to converge to a steady average value in a much shorter simulation time but also prevents bimodal drag behavior from going undetected in the form of early simulation convergence and inconsistent variation across different vehicles. With a more reliable average drag value output from simulations, informed decisions on vehicle configuration can be made during the development phase.
This TIR establishes high-flow fueling protocols, including their process limits for fueling of compressed gaseous hydrogen vehicles at peak flow rates from 60 to 300 g/s with compressed hydrogen storage system (CHSS) volume capacities between 248.6 and 7500 L which have been qualified to UN GTR #13. This document is initially being published as a TIR due to limited field testing of the fueling protocols. Once the fueling protocols have been field tested, the SAE Fuel Cell Standards Committee Interface Task Force intends to publish a revision to this document as an SAE Standard.
Researchers have developed a new soft robot design that engages in three simultaneous behaviors: rolling forward, spinning like a record, and following a path that orbits around a central point. The device, which operates without human or computer control, holds promise for developing soft robotic technologies that can be used to navigate and map unknown environments.
A new aviation supply chain integrity coalition has offered 13 recommended actions to prevent the circulation of non-serialized aircraft parts throughout the global aviation industry. Embry-Riddle Aeronautical University, Daytona Beach, FL In the summer of 2023, a receiving clerk in the procurement department of TAP Air Portugal, a Lisbon-based airline, made a curious discovery: A $65 engine part that should have appeared brand-new showed signs of significant wear. The clerk checked the documentation from the London-based parts supplier and noticed that the submitted documentation was also suspicious. Using his safety training, the employee immediately reported the anomaly to TAP Air Portugal management, which raised the issue with the jet engine's manufacturer. Little did the procurement clerk know at the time, but this escalation led to one of the biggest investigations in the history of the aviation supply chain, as reported by Reuters and the British Broadcasting Corporation in 2023.
In the summer of 2023, a receiving clerk in the procurement department of TAP Air Portugal, a Lisbon-based airline, made a curious discovery: A $65 engine part that should have appeared brandnew showed signs of significant wear. The clerk checked the documentation from the London-based parts supplier and noticed that the submitted documentation was also suspicious.
Researchers have developed a printing process that prints strong nonmetallic materials in record time — five times faster than traditional 3D printing. The process, called SWOMP, which stands for Selective dual-wavelength Olefin metathesis 3D printing, uses dual-wavelength light, unlike the traditional printing process.
Defying engineering challenges in record time, researchers at the University of Maryland developed a machine learning model that eliminates hassles in materials design to yield green technologies used in wearable heaters.
Engineers at the University of California San Diego have developed an ultra-sensitive sensor made with graphene that can detect extraordinarily low concentrations of lead ions in water. The device achieves a record limit of detection of lead down to the femtomolar range, which is one million times more sensitive than previous sensing technologies.
Neurostimulators, also known as brain pacemakers, send electrical impulses to specific areas of the brain via special electrodes. It is estimated that some 200,000 people worldwide are now benefiting from this technology, including those who suffer from Parkinson’s disease or from pathological muscle spasms. According to Mehmet Fatih Yanik, professor of neurotechnology at ETH Zurich, further research will greatly expand the potential applications: instead of using them exclusively to stimulate the brain, the electrodes can also be used to precisely record brain activity and analyze it for anomalies associated with neurological or psychiatric disorders. In a second step, it would be conceivable in future to treat these anomalies and disorders using electrical impulses.
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.
Riding aboard NASA's Psyche spacecraft, the agency's Deep Space Optical Communications technology demonstration continues to break records. While the asteroid-bound spacecraft doesn't rely on optical communications to send data, the new technology has proven that it's up to the task. After interfacing with the Psyche's radio frequency transmitter, the laser communications demo sent a copy of engineering data from over 140 million miles (226 million kilometers) away, 1. times the distance between Earth and the Sun. This achievement provides a glimpse into how spacecraft could use optical communications in the future, enabling higher-data-rate communications of complex scientific information as well as high-definition imagery and video in support of humanity's next giant leap: sending humans to Mars.
Riding aboard NASA’s Psyche spacecraft, the agency’s Deep Space Optical Communications technology demonstration continues to break records. While the asteroid-bound spacecraft doesn’t rely on optical communications to send data, the new technology has proven that it’s up to the task. After interfacing with the Psyche’s radio frequency transmitter, the laser communications demo sent a copy of engineering data from over 140 million miles (226 million kilometers) away, 1½ times the distance between Earth and the Sun.
Aerospace is an industry where competition is high and the need to ensure safety and security while managing costs is foremost. Stakeholders, who gain the most by working together, do not necessarily trust each other. Changing backbone technologies that drive enterprise systems and secure historical records does not happen quickly (if at all). At best, businesses adapt incrementally, building customized applications on top of legacy systems. The complexity of these legacy systems leads to duplication of efforts and data storage, making them very inefficient. Technology that augments, rather than replaces, is needed to transform these complex systems into efficient, digital processes. Blockchain technology offers collaborative opportunities for solving some of the data problems that have long challenged the aerospace industry. The industry has been slow to adopt the technology even though experts agree that it has real potential to revolutionize the global supply chain—including maintenance, repair, and overhaul (MRO)—driving tremendous cost, excess inventory, and inefficiencies out of the system. This chapter discusses how the adoption of blockchain technology could have a significant impact on the aerospace industry and addresses some of the unsettled concerns surrounding the implementation of the technology.
Emergency personnel and first responders have the opportunity to document crash scenes while evidence is still recent. The growth of the drone market and the efficiency of documentation with drones has led to an increasing prevalence of aerial photography for incident sites. These photographs are generally of high resolution and contain valuable information including roadway evidence such as tire marks, gouge marks, debris fields, and vehicle rest positions. Being able to accurately map the captured evidence visible in the photographs is a key process in creating a scaled crash-scene diagram. Image rectification serves as a quick and straightforward method for producing a scaled diagram. This study evaluates the precision of the photo rectification process under diverse roadway geometry conditions and varying camera incidence angles.
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. However, as a project progresses and the work of engineers diverges, keeping AUTOSAR and UML/SysML in synch can be a tedious, slow, and error-prone task – especially when you are already grappling with tight timelines and limited resources. The AUTOSAR-UML Bridge mitigates these workflow issues, by providing assistance for Automotive Software Architects to expedite documentation creation by generating UML models from AUTOSAR for architecture design. Moreover, it assists Automotive Software Engineers with transitioning to detailed design by adding UML-based internal behavior and interface descriptions to AUTOSAR projects. The IncQuery AUTOSAR-UML Bridge's seamless integration with Sparx Systems Enterprise Architect helps to streamline the overall design process. Furthermore, it can also work with LieberLieber’s LemonTree, to enable agile iterations where collaborating architects and engineers can easily merge changes from AUTOSAR into the corresponding UML model, without having to redo or delete anything.
Major hardware and software upgrades underpin the Indy Autonomous Challenge racecar for 2024, proving self-driving vehicle capabilities at triple-digit speeds. After three years and more than 7,000 miles (11,265 km) of racing, the Indy Autonomous Challenge (IAC) enters year four with an updated platform and embedded software upgrades. Among the highlights for the second-generation open-wheel racecars are pending patents and first-time applications. “We've achieved several impressive milestones since our start in 2020,” IAC President Paul Mitchell said. The achievement list includes setting a speed record for passing in autonomous racing (170 mph [273 km/h]), netting the autonomous vehicle land speed record (192.2 mph [309.3 km/h]) and establishing the fastest lap speed for an autonomous vehicle (180 mph [289.68 km/h]). “More than anything, we consider the IAC an applied-research platform for industry and academia to work together on advancing high-speed autonomy,” Mitchell said.
After hurricanes and other disasters, it is becoming more common for people to fly drones to record the damage and post videos on social media. Those videos are a resource for rapid damage assessment. By using artificial intelligence, researchers are developing a system that can automatically identify buildings and make an initial determination of whether they are damaged and how serious that damage might be.
Researchers have designed a lightweight helmet with tiny LEGO-size sensors that scan the brain while a person moves. The helmet is the first of its kind to accurately record magnetic fields generated by brain activity while people are in motion. This advance could make it easier to conduct brain scans in young children and individuals with neurological disorders who can’t always remain still in conventional scanners.
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