Browse Topic: Systems engineering
This digital data model for the AS9100D aerospace quality management standard provides a structured, machine‑readable representation of the requirements, definitions, and industry‑specific enhancements that distinguish AS9100D from its ISO 9001:2015 foundation. Designed to support interoperability across aviation, space, and defense organizations, the model encapsulates the standard’s clause hierarchy, terminology, and compliance attributes in a format optimized for automated processing, validation, and lifecycle management. The model incorporates the revised clause structure introduced with ISO 9001:2015 and extends it with aerospace‑specific obligations, risk‑based considerations, and supply‑chain expectations defined by the International Aerospace Quality Group (IAQG). It captures the relationships between core quality management system elements—such as leadership, planning, operational control, and performance evaluation—while embedding additional AS9100D requirements related to
The H-60 Black Hawk remains a cornerstone of U.S. Army Aviation, but its legacy avionics architecture presents modernization challenges. To ensure long-term operational relevance and interoperability with future platforms like the Future Long Range Assault Aircraft (FLRAA), the Army is implementing a Modular Open Systems Approach (MOSA). This strategy facilitates rapid technology integration, enhances sustainment efficiency, and mitigates obsolescence. The Army's MOSA adoption aligns with regulatory mandates such as the National Defense Authorization Act and Department of Defense (DoD) acquisition policies, ensuring modularity, scalability, and interoperability across aviation systems. The application of modern open standards, such as the Future Airborne Capability Environment (FACE®), within the Black Hawk supports software reuse and hardware commonality, reducing lifecycle costs and vendor lock. A phased modernization approach, including a Digital Backbone architecture supported by
Traditional safe-life methodologies for rotorcraft structural components often result in overly conservative life estimates, increasing maintenance costs and reducing aircraft availability. This study explores the integration of digital twin concepts with probabilistic modeling and machine learning to enhance structural life assessment, demonstrated through a practical case involving the Royal Canadian Air Force CH-146 Griffon helicopter. A probabilistic fatigue model determines a fatigue life distribution by incorporating material variability and uncertain operational loads inferred directly from flight data. Unlike conventional approaches, this method dynamically estimates load spectra, including uncertainty instead of relying on conservative assumptions. Monte Carlo simulations are used to quantify structural risk and assess the impact of load and material uncertainties. Sensitivity analyses highlight these uncertainties’ contributions to failure probability. The proposed approach
Quenching is the most critical step in the sequence of heat-treating operations, aiming to preserve the solid solution formed at the solution heat-treating temperature by rapidly cooling the material to near room temperature. Currently, there is no reliable, performance-informed quenching process that can consistently reduce the high scrap rate of airframe aluminum forging parts, which often suffer from significant residual stress and distortion. This limitation stems from the complex interactions between temperature, phase transformations, and stress/strain behavior—each influenced by the evolving temperature distribution and microstructural state of the workpiece. Conventional modeling techniques for quenching processes typically lump these multiscale, multi-physics phenomena into a simplified heat transfer coefficient (HTC). However, determining the spatial and temporal variations of HTC through experiments is both prohibitively time-consuming and costly. To address this challenge
Commercial viability for new unmanned aircraft in markets such as the European Union (EU) requires moving closer to population centers, flying Beyond Visual Line of Sight (BVLOS), and operating in busier airspaces – transitioning to medium-risk SORA SAIL III and SAIL IV operations. This requires a paradigm shift from primarily startup-style, minimalist system architecture modeling, documentation, and safety analyses–if any–towards the rigor expected in classical certification processes (e.g. ARP4754 and ARP4761). Model-based systems engineering (MBSE) and safety analysis (MBSA) methodologies have the potential to greatly aid in this transition: central models can more efficiently capture technical complexity, leverage component redundancy, and allow for easier sharing and re-use of system elements among specialized engineering tools. Larger all-encompassing MBSE/MBSA tools are expected to be particularly useful for their flexibility–providing for current and future needs, as more
This paper discusses the development of a flight dynamics model (or digital twin) of a compact and re-configurable coaxial-propeller-based micro air vehicle (MAV) in hover, edgewise, and maneuvering flight using a hybrid physics-based plus data-driven approach. The MAV has a mass of 366 grams (0.81 lb), and features a 52 mm (2.05 in) diameter cylindrical fuselage, foldable propellers, and a two-axis gimbal thrust vectoring mechanism for pitch and roll control. The aircraft has been successfully launched from a pneumatic cannon and has achieved stable and controlled flight. A physics-based flight dynamics model of this novel MAV has been developed using Rotorcraft Comprehensive Analysis System (RCAS). RCAS is able to predict the translational dynamics near hover reasonably well; however, the accuracy decreases for rotational dynamics in edgewise flight resulting in significant differences between predicted dynamics and flight test data, known as residual dynamics. The current hybrid
In January 1984, the Georgia Tech School of Aerospace Engineering (AE) hired Dr. Daniel P. Schrage as the Rotorcraft Design Professor and the Associate Director of the Georgia Tech Center of Excellence in Rotary Wing Aircraft Technology (CERWAT), one of the Army-sponsored Rotorcraft Centers of Excellence (RCOE). Dr. Schrage left St. Louis, MO at the end of 1983 as the Director for Advanced Systems (DAS) and the Associate Director of Army Aviation Science and Technology in the Aviation Research and Development Command (AVRADCOM). His departure was a tough decision for Dr. Schrage as he was designated to become the Technical Director of the new Aviation Systems Command (AVSCOM). However, the new AVSCOM motto was "Readiness Immediate and Development Eventual," which, as it turned out, meant that new Army Aviation Systems would not be developed for the next 35 years. Dr. Schrage was also recruited by Bob Lynn, Bell Helicopters VP Engineering, as the Bell Helicopters Director of Technology
Ever-increasing modeling and simulation capabilities and the desire to use simulations in support of system qualification, regulatory compliance, and other critical decision-making roles, raises the bar on the need for rigorous V&V of all aspects of the models used to create the simulation data. US Department of Defense Directives and Instructions, and emerging regulatory and industry standards on Modeling and Simulation in a Digital Engineering context require rigorous M&S Verification, Validation, and Accreditation (M&S VV&A). These specifications aim to create trusted and credible simulation data that can be used in critical decision-making roles on complex systems. Implementing a well-defined, structured, model-based and standards-based M&S VV&A Process early in the program lifecycle facilitates collaboration and documented buy-in on M&S VV&A for program with customers and/or regulatory agencies. This collaboration increases acceptance throughout the program and product lifecycles
Research into the feasibility of a scaled rim-drive propulsion product to enable ultra-heavy vertical lift (UHVL) is ongoing at the University of South Carolina in partnership with KRyanCreative, LLC, a start-up aerospace small business. The research team is advancing a superconductive design concept for a rotor system that delivers significant performance gains and flight envelope expansion disruptive to the vertical lift transportation sector. The team has conceived a novel electric tip-driven ducted propulsor to guide architectural and engineering investigations that improve hover and acoustic performance over current practice without penalty to weight and cost. This paper summarizes the data and assumptions that emerge from the systems engineering process of requirements decomposition for product realization. Requirements are categorized as to whether they are explicit (programs of record) or implied (comparable business case or as an alternative to a program of record). Risk
ABSTRACT The authors studied the effects of different types of armor on the performance of spin-torque microwave detectors (STMD). Working prototypes of novel nano-sized spintronic sensors of microwave radiation for battlefield anti-radar and wireless communications applications are being integrated into Sensor Enhanced Armor (SEA) and Multifunctional Armor (MFA) and tested in SEA-NDE Lab at TARDEC. The preliminary theoretical estimations have shown that STMD based on the spin-torque effect in magnetic tunnel junctions (MTJ), when placed in the external electromagnetic field of a microwave frequency, can work as diode detectors with the maximum theoretical sensitivity of 1000 V/W. These STNO detectors could be scaled to sub-micron size, are frequency-selective and tunable, and are tolerant to ionizing radiation. We studied the performance of a STMD in two different dynamical regimes of detector operation: in well-known traditional in-plane regime of STMD operation and in recently
Developing and operating an advanced air mobility service is challenging in many ways. The technical complexity of the task, the lack of available supporting infrastructure, the regulatory environment, and the necessity of collaboration among all stakeholders are barriers to a wide-spread implementation. Digital tools are now available to the whole industry to tackle those challenges, one of them being the virtual twin experience technology. The virtual twin experience is generated by the digital twin technology applied to a certain domain of application. It is a system of systems designed to provide users with a unique and immersive experience of reality, without physically being present in the real-world environment. It offers capabilities that go beyond traditional means, enabling organizations and users to achieve tasks and insights that were previously not possible. This paper describes how the virtual twin experience is adopted within the advanced air mobility ecosystem, that is
As per certification requirements, for a large rotorcraft that does not meet the Category A requirements, the Height-Velocity (HV) avoid region must be determined in total power failure condition. The development of a digital twin representative of the real rotorcraft behaviour allows to reduce flight testing hours and to increase flight tests safety, especially in such critical conditions, thus decreasing risks and costs. In this work, an extensive simulation activity has been carried out to generate HV charts for a medium twin-engine helicopter in case of loss of both engines. An in-house software that emulates pilot logics has been exploited, coupled with a Flightlab model representative of the rotorcraft and validated against flight data. Manoeuvres performed after a dual engine failure were simulated starting from an all engine operative hover out of ground effect (HOGE) and in ground effect (HIGE) or level flight condition until landing, in a grid of heights and velocities and
Rapid advances in high fidelity modeling and high performance computing capabilities have enabled their routine utilization in support of aircraft design. Analysts are able to generate orders of magnitude more data that must then be turned into actionable intelligence to guide design. Enabling effective application of advanced analysis to design requires a robust end-to-end digital transformation to make the simulation processes reusable, repeatable, traceable, scalable and minimize setup errors. This is achieved through the development of a Computational Fluid Dynamic (CFD) modeling framework where streamlining and automation are inserted within the current CFD workflow that involves model setup, simulation and post processing. Workflow automation techniques have been implemented in simulation pre and post processing that reduce the overall process time or enhance the fidelity of the simulation. To conduct CFD evaluations through flight envelope efficiently, space filling methods that
ABSTRACT A new simulation model to predict tail rotor drivetrain maneuver loads at hover is developed. The model consists of a high fidelity dynamic engine simulation coupled to a multibody dynamics simulation of the main rotor system, tail rotor and drivetrain, including torsional flexibility of drivetrain shafts. Simulations of yaw doublets at hover demonstrate that tail rotor drivetrain loads can be reduced without compromising handling qualities for moderate amplitude heading changes. A full autonomous heave/yaw hover control law is developed with a nonlinear element in the heading feedback loop. The nonlinear element specifies the aggressiveness level (gain) as a function of heading angle change. It allows the flight control system engineer to simultaneously minimize tail rotor drivetrain maneuver loads whilst maintaining level 1 handling qualities. The nonlinear flight control system is evaluated for the ADS-33 hover turn mission task element and compared to a conventional linear
The airframe digital twin analysis framework developed at the National Research of Canada is being transposed to safe life applications for rotorcraft components. A probabilistic safe life prediction approach, consisting of uncertain material property data and uncertain load spectra is used to calculate risk assessment metrics, such as the cumulative probability of failure, the hazard rate, and the average hazard rate as a function of time. A demonstration of this approach is presented for a CH-146 Griffon component, for which the uncertain loads are estimated from a model developed through machine learning. This preliminary assessment shows the feasibility of using digital twin concepts as a viable alternative to traditional deterministic life predictions, with the potential to reduce maintenance costs and increase aircraft availability.
The Autoclave processing is commonly used in manufacturing high-performance fibre-reinforced thermoset composite components in the aerospace industry. Variations in the cure cycle, sometimes even apparently minor deviations from the prescribed cure cycle, can harm the laminate properties. Given the costly and time-consuming autoclave manufacturing process, there is a strong need to cure the maximum number of parts in the shortest possible time without compromising quality. In order to achieve high-rate automated manufacturing with the optimized autoclave process, it is important to construct a digital twin modelling approach to mirror the physical composite curing process in the virtual domain based on the integration of high-fidelity multi-physics models. The resulting digital twin includes a thermal CFD model, a thermo-chemo-mechanical module, and an efficient and accurate block coupling between these two modules. The customized Abaqus driven by local and spatial variation of the
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