Browse Topic: Systems engineering
Traditional safe-life methodologies for rotorcraft structural components rely on deterministic safety factors to account for uncertainty in loads, material properties, and operational usage. While effective for ensuring safety, these approaches lead to early retirement lives and reduced aircraft availability. This paper presents an updated digital twin-based probabilistic framework for rotorcraft component fatigue life assessment that integrates a probabilistic stress–life (S-N) material model, machine learning-based load estimation from flight data, and Monte Carlo uncertainty propagation. The approach is demonstrated for a critical location on the CH-146 Griffon main rotor yoke. Compared with earlier work, the present study advances the framework through independent validation of the load-estimation model and application to available in-service flight data from multiple mission categories. A probabilistic sensitivity analysis is used to examine the separate and combined effects of material variability and load-estimation uncertainty on fatigue life, cumulative probability of failure, and hazard rate. For the CH-146 demonstration case, the results indicate that the material fatigue strength uncertainty has a major impact on the lower tail of the life distribution and the corresponding reliability-based life, whereas load-estimation accuracy uncertainty has a secondary influence on risk metrics. The application of the digital twin framework to operational, search and rescue, and training mission data further shows that mission-specific usage variability plays an important role in the evolution of fatigue damage accumulation and structural risk. Overall, the proposed framework provides a more informative basis for risk-based rotorcraft life assessment by explicitly quantifying uncertainty and incorporating aircraft-specific operational data. The study is intended as a step toward validation of the framework rather than a completed operational deployment.
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 reduction enroute to technical feasibility is addressed with a methodology that applies predictive analytics aided by artificial intelligence that will accelerate prototype fabrication by 2030 and fast track market incentives for multiple aviation technologies.
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 and enable rapid process tailoring for reduced distortion, we have developed and validated a digital twin-based Quenching Laboratory Software (QLAB) tool. QLAB integrates a thermal multi-phase computational fluid dynamics (CFD) model, sequentially coupled with a Mechanical Threshold Stress (MTS) model and a precipitation model. The thermal CFD component captures turbulent flow, multi-phase transformations, and the complex heat transfer stages of quenching including vapor blanket formation, nucleate boiling, and convection—to accurately predict temperature evolution. The MTS-precipitation model quantifies the effects of microstructural precipitates on the material's mechanical response under thermal loading. QLAB has been thoroughly validated using representative aluminum airframe components, including aluminum bars with pockets and Lcorner parts. We demonstrate the tool's predictive accuracy by comparing its output against experimentally measured temperature and distortion fields. Finally, we apply the validated QLAB to conduct a virtual quenching test on a simplified aluminum airframe structure, showcasing its potential for performance-informed process optimization.
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, with a promotion to VP Engineering upon Lynn's retirement in the next few years. This was one of the most challenging decisions of his life for Dr. Schrage and his family, as they had to move from their home in O'Fallon, IL - a great town and home for his growing family.. In addition, his wife Nancy's parents and his mother and sisters, all lived within a half hour from his home. His father, Albin, had passed away while we were moving to the St. Louis Area following his MSAE graduation from Georgia Tech in May 1974. When he arrived at Georgia Tech in January 1974, he started teaching the Rotorcraft Design Courses, which were similar in content to what he had developed in AVRADCOM and to what Dr. Dick Carlson taught at Stanford U. He also developed and taught design courses in his two weeks each year in the Department of Mechanics at USMA West Point during his reserve duty from 1978-1983. He continued in the U.S. Army Reserves and taught two weeks at USMA until 1996. He then retired as Colonel in the USAR in 2004. He used a computer-integrated environment and the top-down design decision support process taught at West Point. This provided a Framework for using Systems Engineering Methods for Product Design Driven and Quality Engineering Methods for Process Design Driven, as illustrated in Figure 1. Value-based Acquisition decision-making is a lost art in Digital Engineering and other attempts to produce effective and affordable systems. The Army FARA Contract termination in 2022 was primarily due to lack of Development Assurance Value Based Acquisition (DAVBA) (Ref. 1).
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 Model-Based Systems Engineering (MBSE), will streamline future avionics upgrades while maintaining compatibility with existing and future fleet assets. This transformation positions the Black Hawk for sustained operational effectiveness in multi-domain operations, reinforcing the Army's aviation modernization objectives.
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 model utilizes the residual dynamics via a data-driven approach to correct the physics-based model. Using the measured vehicle states and control inputs, a deep neural network (DNNs) was trained to learn the residual forces and torques. The resulting hybrid model reduced prediction errors by 55% on average compared to the RCAS model based on pure physics.
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. This paper describes how Model-Based Systems Engineering tools and Digital Engineering ecosystems can support the M&S VV&A Process. The model-based construct facilitates creating metrics dashboards, leveraging model-based artifacts for improved communication of M&S VV&A status, quality, maturity, and completeness.
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 sophisticated details or analyses can be derived from simpler starting points and existing model elements. This project developed proof-of-concept examples within the Ansys SAM and medini analyze tools to demonstrate their usefulness for supporting SORA SAIL III and IV applications. This team included colleagues from the automotive domain to showcase the relative ease of producing the required evidence within just two Ansys tools–which is otherwise a time-consuming and confusing ordeal, typically using several disconnected programs. UAS designers and operators are encouraged to start with the information and examples produced by this project to accelerate their transition towards SAIL III and IV applications.
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 provides probabilistic life predictions, supporting risk-based maintenance strategies to potentially optimize operational efficiency. The long-term goal is to develop an adaptive digital twin model that continuously updates with new operational flight data, enhancing predictive accuracy for helicopter fleet management.
ABSTRACT Today’s combat vehicle designs are largely constrained by traditional manufacturing processes, such as machining, welding, casting, and forging. Recent advancements in 3D-Printing technology offer tremendous potential to provide economical, optimized components by eliminating fundamental process limitations. The ability to re-design suitable components for 3D-printing has potential to significantly reduce cost, weight, and lead-time in a variety of Defense & Aerospace applications. 3D-printing will not completely replace traditional processes, but instead represents a new tool in our toolbox - from both a design and a manufacturing standpoint.
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 discovered novel out-of-plane regime.
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 comprised of the aircraft manufacturer, the vertiport provider and the operator. It reviews the different business processes on electric vertical take-off and landing (eVTOL) vehicle design and manufacturing, vertiport design, and operations, and highlights the associated benefits of such approach. Through these processes, we will see how the virtual twin experiences shape the future of product design, manufacturing, and operations. It changes the way in which stakeholders collaborate in a complex system of systems context. The paper concludes on the ways that the virtual twin experience provides organizations enhanced visualization and understanding, expanded trade-space exploration, and improved decision-making, and how it enables innovators and enterprises alike with greater visibility, efficiency, flexibility, and compliance.
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 for different weights and altitudes combinations. Sensitivity analyses on the parameters that affect the manoeuvres the most have been performed and the effects of the assumptions and requirements at touchdown on the HV avoid region investigated.
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 control system. Level 1 performance is achieved with both control systems and dynamic tail rotor drivetrain loads are reduced up to 58% by the nonlinear element.
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.
This paper describes both technology and methods when integrated into a holistic acquisition approach stands to affect acquisition success. Mission engineering, drives the ability to use innovation-driven outcome approaches with an end-effects delivery focus; crafting the necessary mission capabilities working back into the development of systems and technologies. Developing product line-centric products enables improved system engineering of more holistic product line scope against Business, Mission, and Stakeholder needs, applying product line scoping against both Market and Mission Segmentation. Organizational operational effectiveness in shifting to a product line approach to product development.
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 turbulence-induced heat transfer coefficient (HTC) imposed through one-way coupling determines the thermo-mechanical response in composite parts. Using the developed digital twin tool (SMARTCLAVE), HTC's spatial and temporal variation can be generated digitally without invoking an expensive and time-consuming experimental approach. The predicted local boundary conditions are used in SMARTCLAVE to determine the cure kinetics, temperature distribution, and thermal-mechanical response that drives the residual stress and distortion of composite parts after curing. The accuracy of the digital twin for autoclaving is demonstrated first using a benchmark problem followed by the capability demonstration with a single-part L-beam assembly. The benefits of using the digital twin tool are illustrated via the optimal placement of multiple parts in an autoclave to balance the throughput and quality.
Quenching is a heat treatment process for the rapid cooling of a metallic workpiece in water, oil, or air to obtain certain desired material properties. It is the most critical step in the sequence of heat-treating operations to preserve the solid solution formed at the solution heat-treating temperature by rapidly cooling to near room temperature. Because of the complex interaction between temperature, phase-transformation, and stress/strain relation that depends on the temperature distribution and the microstructure of the workpiece, there is no performance-informed quenching process that can be applied reliably to reduce the high scrap rate of airframe aluminum forging parts with a significant amount of residual stress and distortion. Since large aluminum forging parts are increasingly used in aerospace structures to enable structural unitization, it is important to construct a digital twin modeling approach to mirror the physical quenching process for minimizing scrap rate, increasing production efficiency, and engineers and machine operators' handling of variances in forging operations. A high-fidelity modeling of the coupling of thermal, metallurgical, and mechanical interactions is a key component to creating a digital twin of the physical quenching process. A high-fidelity thermal multi-phase computational fluid dynamics (CFD) model is applied to simulate fluid dynamics and temperature fields in the quenchant tank. The developed immersogeometric modeling approach is used next for an efficient model generation of a 3D workpiece with various dipping orientations. Given the temperature and pressure profiles predicted from the CFD-based heat transfer module, residual stress and distortion prediction modules are developed by including temperature and pressure fields mapping and temperature and strain rate dependent property evolution via Abaqus' user-defined subroutines. Verification and demonstration studies are performed using aluminum coupons dipped into a quenching tank with different orientations. Time histories of the temperature and residual stress fields were predicted to explore the relationship between the process and performance.
Today's world of engineering is moving faster with a goal of producing more, in less time. This leads to the question that every engineer faces, "do I take the time to develop requirements or jump straight into the design effort?" This question is easily answered when the engineer understands the role of requirements and how they fit into the product life cycle. Once the role of requirements is understood the next step is to understand what requirements are and how they work. The goal is to produce efficient, precise, and professional requirements that describe one system or a system of multiple systems for the project that is in work. When requirements are done right, the project will be completed on time, on budget, with a happy customer that is receiving the product they paid for. This paper is intended to train engineers to understand what requirements are and how to develop them. The paper will cover the basic reasoning for requirements, where requirements fit into the product design lifecycle, and rules for writing good requirements.
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 take into account uncertainties of complex systems are needed and have driven updates to the boundary condition and design of experiments (DOE) generation within the workflow. Vehicle sub-system design can be highly iterative, performed by a large number of participants in multidisciplinary groups. To ensure traceability across the digital thread, a provenance and metadata storage methodology has been implemented to capture information about CFD simulations and construct a query able database while a model-based systems engineering (MBSE) framework provides a structured and integrated approach to managing information throughout the product lifecycle. The SIM-FIX-SIM approach enabled with a robust analysis framework for digital flight assessment prior to first flight will contribute to the overall goal of reducing development timelines and achieving cost reduction goals for cutting-edge rotorcraft development programs.
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As embedded electronic control systems are increasingly penetrating vehicle subsystems, the designers are faced with a dilemma of providing state of art vehicle features on one hand and ensuring frugal implementation of the same to meet competitive pressures on the other. For embedded software and hardware systems this means adoption of judicious and innovative design choices with reusable building blocks. This paper dwells upon various design aspects of control and monitoring which are frequently used for automotive applications such as feed-forward and proportional integral control, diagnostics for sensor boundary conditions, handling of intermittent faults without causing nuisance to the vehicle users etc.
The aerospace ecosystem is a complex system of systems comprising of many stakeholders in exchanging technical, design, development, certification, operational, and maintenance data across the different lifecycle stages of an aircraft from concept, engineering, manufacturing, operations, and maintenance to its disposal. Many standards have been developed to standardize and improve the effectiveness, efficiency, and security of the data transfer processes in the aerospace ecosystem. There are still challenges in data transfer due to the lack of standards in certain areas and lack of awareness and implementation of some standards. G-31 standards committee of SAE International has conducted a study on the available digital data standards in aircraft asset life cycle to understand the current and future landscapes of the needed digital data standards and identify gaps. This technical paper presents the study conducted by the G-31 technical committee. This paper reviews the data being exchanged between various stakeholders in the aerospace asset lifecycle and the availability of standards for the data transfer within the aerospace ecosystem. It identifies gaps based on the list of currently available data standards, and then creates a future landscape to address the needed digital data standards. This paper focuses on aircraft operations, maintenance, transfer, disposal processes, and post-build stage, and does not address the detailed interactions during the aircraft design, development and manufacturing phases. Its scope is also limited to key stakeholder interactions throughout the different stages of the aircraft operations, maintenance, and retirement.
Over the last decade or more there has been a concerted push to move from on condition to predictive maintenance to improve rotorcraft availability and cost competitiveness of sustainment (Ref. 1-2). The US Army, along with industry partners, have been working on the development of prognostics for complete rotorcraft coverage. It has been identified that accurately capturing maintenance actions is needed to improve the accuracy of prognostics for better component health state awareness. Further to achieve the Army's vision for Zero Maintenance rotorcraft and meet the Maintenance Free Operating Period (MFOP) (Ref. 3) requirements for the Future Vertical Lift (FVL) program, it's essential to have an automated configuration management system. To help meet these objectives, the Army and Honeywell are working on the Rotorcraft Automated Component Tracking (RACT) Science and Technology (S&T) development program. This paper discusses the research being conducted to enable the Army's RACT concept done by the Honeywell team and the CCDC AvMC. It identifies the current state of RACT technologies and challenges of integrating such technologies into the rotorcraft environment.
This paper reports on the current state of experimentation and deployment of the PMM method within the Design Office of Airbus Helicopters (AH). It shows that it is possible to efficiently carry out a system engineering process based on modeling and simulation (MS4SE). It is based on simulation tools that are widely available and known to engineers in the practice of their disciplines. The PMM method has not yet been used at AH on a complete helicopter program. This is owed in part to the too recent emergence of PMM. However, PMM has gone through several qualification stages in the form of Proofs of Concept (POCs) and pilot projects conducted directly in relation with operational teams and engineering disciplines interested to PMM for the greatest benefit of end users. The paper presents results for each stage of the development cycle paying a particular attention on both ends of this cycle: from the development of the operational concept and the validation of the top-level specification to the final verification of a helicopter function on an integrated helicopter test laboratory.
This research sought to distill and define the fundamentals of system and software architecture analysis and form the basis by which a design can be tested and analyzed prior to its implementation. In short, the question "can a design be measured against the business-level objectives and quality-of-use architectural requirements. The research focuses on building a body of knowledge that supports an analysis, built on fundamentals which scales and can serve as the basis by which we can transform when and how architecture validation can occur. This research supports ongoing work towards developing a strategic comprehensive architecture approach and extends the analysis and documentation of the Key Business Drivers (KBDs) and architectural drivers supporting the efficient development and sustainment of interoperable aviation mission systems. A prototype process that leverages the discovered relationships and weights for use by current Architects and Senior Systems Engineers is shown. Programs implementing this approach are expected to benefit from the planned reuse of architectural artifacts for follow up systems engineering products supporting the development of reusable component product lines avoiding the long-term challenges of unrealized architectural objectives.
Several electrical vertical take-off and landing (eVTOL) concepts have emerged from startups, to propose new sustainable mobility experiences. As opposed to traditional players in aircraft manufacturing, these "shakers" are innovating around first-of-a-kind, novel configurations of fully electric air taxis with distributed propulsion and tilt rotors. While the eVTOL development is itself a challenge, being a startup builds upon additional challenges to be successful: they need to be first on the market and reach a functioning prototype as soon as possible, they need to be agile, be unique and propose a mobility experience. Lastly, they need to reach type certificate for their vehicle - something not yet achieved and with few months-old regulatory guidance. The tools to be used by the startups and the associated business processes to be implemented are of critical importance to tackle the engineering challenges and to answer the ambition of the startups. Systems engineering and simulation are on the path for reinventing the sky, around a single business platform on the cloud.
The digital twin (DT) refers to a digital replica or virtual model of actual physical product or process that can be applicable for various purposes. In this study, a digital reproduction of the next generation active twist blade, meeting superior durability characteristics and high strength requirements under severe operating environments of a helicopter rotor, is attempted using the up-to-date computed tomography (CT) scheme combined with modern digital image processing technique. The CT scan covers much portion of the blade root, transition, and tip regions where substantial variations in external geometries and/or interior structural layouts are present while limited zones in the airfoil blade region being considered as nonuniform. A three-dimensional (3D) finite element-based DT simulation model is constructed using the high-resolution CT-scan images. The detailed lamination geometries and sequences of layered composites in the blade skin and spar are implemented in the DT model which can be exploited further for durability study or strength analysis. The reconstructed 3D analysis model is used to determine the structural properties of the blade. In parallel, either mechanical or optical measurement methods along with two-dimensional (2D) blade sectional analysis are carried out to cross validate their predictions. Overall, fair to good correlation is obtained between the different set of results. The agreement is good for mass, elastic axis, and flap bending while less satisfactory results are obtained with the torsion rigidity. A sensitivity analysis is also conducted to clarify the impact of modeling cables, nose weight, and manufacturing imperfections on the structural property evaluation of the blade.
One of the most significant barriers to adoption of Model-Based Systems Engineering (MBSE) (Ref. 1) and the Modular Open System Approach (MOSA) (Ref. 2) is a cost-effective and commonly understood process that combines the best of both. Such a process must earn its way as a replacement for traditional processes used for the development of embedded software. Most, if not all, developers of embedded flight software have development processes that have evolved over many years. This creates a situation in which the one-time expense of conversion to a new process can be cost prohibitive. As such, adoption of MBSE has been limited and compliance with the intent of MOSA statutory and regulatory requirements has been mainly conformance to an open standard. Systems can be built that are modular but not open. Modularity can be a desirable design objective for quality systems engineering (such as the separation of concerns or encapsulation of functionality) apart from the open systems qualities of portability, reusability, maintainability, and so forth. This results in adoption of closed practices in the use of modeling technology that can be (and often are) done in a monolithic way without regard to the many different tools used in a multi-vendor environment. This paper presents an outline and structure to avoid such pitfalls.
A multidisciplinary approach combining conceptual vehicle sizing, surrogate performance modeling, and affordability analysis is presented as a solution to a system of systems operations problem. The approach is utilized in the design analysis of battery-powered quadcopter drones operating in a rapid package delivery system with time and system cost used as objective functions. To facilitate data flow between the design routine and external simulation tools, a software script is developed for rapid design and performance assessment of quadcopters in the size range between 3 and 9 pounds of gross weight. Beginning with a review of the surrogate modeling procedure, the implementation and operation of the software are demonstrated. The aircraft concepts generated in the routine are considered in a preliminary cost-benefit analysis within the system of systems context. The study concludes with observations on quadcopter capability and effectiveness advantages and limits, along with possible future expansion plans of the software tool to investigate these limits.
The objective of the joint National Research Council of Canada (NRC) and The Boeing Company Technology Development Program (TDP) entitled 'Canadian Vertical Lift Autonomy Demonstration' (CVLAD) is to evaluate automated and supervised autonomous flight systems on NRC Bell 412 Advanced Systems Research Aircraft (ASRA) and Royal Canadian Air Force Boeing CH-147F Chinook demonstrators. Boeing technologies such as Degraded Visual Environment Pilotage System and Advanced Vehicle Management System form the foundation of an autonomy solution that aims to satisfy Royal Canadian Air Force, US Army, and other Armed Service branch end-use objectives for force multiplication, tactical advantage, pilot assistance, reduced crew operations, and enhanced fleet productivity. The Boeing Company engaged NRC under a Cooperative Research Agreement since 2016 as part of a number of strategies to upgrade Medium-Heavy Lift H-47 Chinook capabilities prior to long-term aircraft replacement in the 2030 to 2060 timeframe. A recent achievement of the CVLAD TDP by its Boeing Phantom Works, Boeing Chinook Program, Aurora Flight Sciences, and NRC Flight Research Laboratory team was the development of Automated Flight Guidance methods addressing system safety and performance. Design and evaluation activities occurred in Boeing Software-/Hardware in-loop facilities as well as on the NRC Bell 412 ASRA. The CVLAD team is using a blend of traditional Systems Engineering 'V-Shaped' Life Cycle Model, System of Systems, and Model-Based processes to develop a cyber-physical system that aims to meet end-user concept of operations and requirements. Significant benefits of virtual development tools such as component-vehicle digital twins and surrogate inflight simulation facilities are achieved as they promote effective collaboration, efficient design, and relevant verification/validation methodologies. Business models can be made more robust by phasing the introduction of technology where effective automation provides users with near-term benefits, while providing a foundation for safe, reliable, and trusted autonomous capabilities for long-term production.
One major problem of big cities is the congested traffic situation and the noise pollution generated by the traffic participants, i.e., cars, busses, and trams. Those ground-bound transport systems are already reaching their limits. The use of aerial taxi services has the potential to use the third, vertical dimension. Vertical take-off and landing systems, shortened to VTOL systems, possibly autonomous and electrified, with low noise emission and little ground space requirements are preferred. Applying an MBSE-based approach like our methodology called 'Compositional Unified system-Based Engineering', in short CUBE, enables to control the complexity of the challenge to develop appropriate VTOLs. This methodology has already proven itself in the automotive industry and its system development processes. In this paper the CUBE methodology will be transferred to the aerospace system development process to demonstrate its general usability. The fully systematical and model-based description of the System of Systems (SoS, meaning urban infrastructure here) is used to condense the requirements for the System of Interest (SoI, meaning VTOL) regarding many possibilities and limitations. This concept is a promising approach to create system-based and model-based specifications of requirements for the VTOL systems, which later shall operate seamlessly as part of the SoS.
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