Browse Topic: Terminology
The detection of free space plays a fundamental role in ensuring the safe and efficient operation of heavy-duty vehicles, particularly in environments where the available area to maneuver is severely constrained, such as construction zones, rest areas, or loading docks. An accurate estimation of free space is essential to prevent collisions, maintaining operational continuity and minimizing vehicle downtime. As observed from the reviewed literature, despite the large number of proposed free-space detection methods, there is no concise and established definition about how free space should be determined, represented, and inferred, nor agreement on the semantic classes to be considered. This heterogeneity complicates systematic comparison and benchmarking across approaches. This paper presents a structured survey and methodological analysis of recent free-space detection and semantic segmentation approaches across automotive LiDAR-, camera-, and radar-based perception systems, as well as multimodal sensor fusion. The review spans classical geometric and occupancy-based techniques together with deep-learning methods, along with datasets commonly used for evaluation. The main contributions are (i) a structured taxonomy and comparative analysis of existing free-space definitions and detection strategies, categorized by their assumptions, representation forms, and sensing modalities; and (ii) a unified and application-independent definition of free space together with the required semantic classes. These contributions aim to provide a consistent conceptual foundation to support future research and to aid the systematic evaluation of upcoming free-space detection systems.
Despite advances in CFD, wind tunnel testing remains indispensable for aerodynamic validation, correlation, and homologation. Increasing configuration complexity, shortened development cycles, and stringent result robustness and documentation requirements demand a shift from isolated facilities to integrated, data-driven ecosystems within the overall development and company-wide test processes. We present a software-centric approach integrating wind tunnel operations into a strategic element of the Digital Thread. By orchestrating test planning, execution, data acquisition, and documentation within a unified framework, experimental data becomes reusable across projects and traceable for compliance and homologation. The interaction between CFD and physical testing is important. Such approach systematically improves simulation models with wind tunnel tests. And CFD results guide efficient test matrix definition. Extended measurement methodologies include automated actuation of active aerodynamic components in test sequences, while BEVs introduce further aerodynamic and thermal aspects for range and efficiency. Thus, extended and automated test definition down to the step-level of test sequences is introduced. Within such integrated environment, AI can be a supporting engineering tool to enhance testing. AI-based methods can assist in identifying relevant test points within complex parameter spaces and in correlating experimental and simulated results, assisting but not replacing established engineering judgment. Also, for the operating department, analyzing process data for maintenance predictions and efficiency optimizations can be assisted by AI-based methods and supporting AI-agents. The approach boosts efficiency by reducing test effort and tedious manual tasks, leading to shorter development cycles, supporting improved time-to-market. Structured workflows and standardized data handling enhance data quality, improve comparability of results, and ensure robust documentation for reliable audit trails. By combining physical testing, simulation, and intelligent processing, the wind tunnel becomes a reproducible, innovation-enabling element in modern product development, positioning software as the backbone of efficient, future-proof aerodynamic testing.
This study investigates the post-failure flight dynamics of a 1200 lb classical octocopter under single motor inoperative condition using nonlinear time-domain simulations with a baseline feedback controller. A physics based propulsion sizing strategy is developed using IEC duty cycle definitions where continuous requirements are derived from nominal hover with margin and short time capability is used to accommodate elevated post failure loads. The selected motor satisfies both regimes and enables transient overdrive without excessive weight penalty. Simulation results in hover and forward flight at the best range speed showing that the vehicle can recover from any single motor failure and retrim using inherent redundancy without fault identification. However, recovery involves significant transient attitude excursions and altitude loss, and requires substantial increases in motor power, with multiple motors exceeding S1 power limits. Post-failure maneuver simulations indicate retained controllability with some degradation and increased coupling. These simulations demonstrate that the proposed motor sizing enables necessary operation post-failure while avoiding unnecessary oversizing.
A common-open data exchange standard for rotorcraft health and usage monitoring systems (CODEX-HUMS), SAE Aerospace Standard AS7140, was issued in September 2025. This standard provides a definition for the CODEX-HUMS open data format produced or used by an on-board or off-board system. The centerpiece of the standard is the data model. This paper describes how the two main data types, stream and batch data, are defined and modeled distinctly by AS7140. The batch data model, targeted at high-frequency, short-duration recorded data, features and delineates a "source", an "indicator", and a "status" element. The streaming data model, intended for lower-frequency, longer-duration HUMS data, covers events and parametric data. The data model is structured by defined data collections to describe the data collected or supporting metadata specifying details about the system or underlying data. In particular, there are definition-type entities and recorded data-type entities. This data model is designed to be flexible and efficient in order to accommodate existing HUMS as well as future HUMS development that support legacy and new rotorcraft platforms.
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.
This paper presents an in-depth study on configuration management for civil aircraft electromechanical systems, grounded in process methodologies and practical experience of configuration management. Beginning with the definition and significance of configuration management, the study analyzes existing configuration management practices in domestic and international aviation enterprises. It systematically examines the requirements and frameworks for configuration management in civil aircraft electromechanical systems, refining critical elements through two primary dimensions: the establishment, refinement and implementation of configuration management processes. Critical refined elements are highlighted to offer actionable insights for civil aviation enterprises in advancing their configuration management practices.
In today’s electric age, the definition of ‘high-performance’ is being rewritten, courtesy of electric sports cars, supercars, and hypercars pushing limits that were once thought impossible to reach. Even Formula 1, quite surprisingly to many, has embraced electrification by integrating hybrid electric systems at the pinnacle of motorsport. Every jaw-dropping 0 to 60 mph time or record-breaking lap is backed by a battery system engineered with precision. Increasingly that precision is driven by simulation technology.
Problem definition: Battery-electric commercial vehicles in particular have large battery capacities with several hundred kilowatt hours, some of which do not have enough energy for an entire working day, which is why they need to be recharged if necessary. High charging power with correspondingly high charging currents is required to recharge the electrical energy storage in an acceptable time. Due to the electrical losses, waste heat is generated, which places a thermal load on the charging components. In particular, the CCS charging inlet is subject to high thermal loads and, for safety reasons, must not exceed the maximum temperature of 90°C according to DIN EN IEC 62196-1. Depending on the ambient temperature, the charging inlet in the charging path often represents a thermally limiting component, as the charging current must be reduced before the maximum temperature is reached. Solution: Three general solution approaches are used to investigate how the CCS charging inlet can be improved for the thermal challenge: 1 Heat reduction 2 Heat absorption 3 Heat transmission Objective: The CCS charging inlet is represented by a detailed Matlab thermal simulation model. A specific optimisation approach is derived for each of the three general solution approaches with the aim in the smallest possible component changes. Target realisation: The general solution approach: “Heat reduction”, is investigated by the optimisation approach: “Reduction of contact resistance”. The general solution approach: “Heat absorption”, is investigated by the optimisation approach: “Increase of thermal mass”. The general solution approach: “Heat transmission”, is investigated by the optimisation approach: “Different insulator material”. Finally, the thermal simulation of the CCS charging inlet shows the effects of all optimisation approaches together compared to the initial state.
The scope of this SAE Aerospace Recommended Practice (ARP) is to establish the procedure for creating titles of aerospace tubing and clamp installation documents generated by SAE Subcommittee G-3E.
Axial velocity measurements were performed in the wake of a hovering rotor with constant and sinusoidal cyclic pitch inputs ranging from 0.05/rev to 0.4/rev using a fixed, 2D-3C PIV system. Measurements were taken at 36 azimuths of the rotor with a constant cyclic input producing a pitching moment of CM = -0.00037. Using a Pitt-Peters definition, a longitudinal inflow state of λ1c = 0.0059 was extracted from the velocity measurements. A phase-resolved, undersampling approach was used to reconstruct the time history of the wake for the dynamic inputs. Simultaneous rotor hub loads measurements were used to obtain the frequency response of the longitudinal inflow state to pitching moment perturbations. The pitching moment perturbations ranged from ΔCM = 0.00027 at f=0.05/rev to 0.00046 at f=0.4/rev. The inflow perturbations ranged from Δλ1c = 0.0085 at f=0.1/rev to 0.0085 at f=0.4/rev. A first order transfer function was fit to the frequency response to compute Pitt-Peters dynamic inflow model parameters, but the low signal strength of λ1c produced high uncertainties in the model parameters.
Airworthiness certification of aircraft requires an Airworthiness Security Process (AWSP) to ensure safe operation under potential unauthorized interactions, particularly in the context of growing cyber threats. Regulatory authorities mandate the consideration of Intentional Unauthorized Electronic Interactions (IUEI) in the development of aircraft, airborne software, and equipment. As the industry increasingly adopts Model-Based Systems Engineering (MBSE) to accelerate development, we aim to enhance this effort by focusing on security scope definitions – a critical step within the AWSP for security risk assessment that establishes the boundaries and extent of security measures. However, our findings indicate that, despite the increasing use of model-based tools in development, these security scope definitions often remain either document-based or, when modeled, are presented at overly abstract levels, both of which limit their utility. Furthermore, we found that these definitions frequently lack alignment with airworthiness security regulations. To address these two distinct gaps, this paper presents a model-based approach for detailed security scope definitions using the Systems Modelling Language (SysML). Our approach aligns with airworthiness security regulations ED-202A / DO-326A and ED-203A / DO-356A and incorporates a SysML profile based on the CORAS language for accurate modeling of security scopes. This facilitates a model-based security risk assessment by creating unambiguously system models that represent assets through model elements, document entry points to the assets and determine their environment. This SysML-based approach supports certification related activities by ensuring that security scope definitions are comprehensive and aligned with airworthiness regulations, directly addressing the identified gaps. The approach's applicability and effectiveness are demonstrated through an illustrative example in the domain of aircraft cabin system development. Moreover, the approach provides valuable inputs that assist operators in deriving guidance for the safe operation and maintenance of the aircraft, complementing existing methods and practices.
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