Browse Topic: Safety testing and procedures
Deep learning (DL) models have attained state-of-the-art performance in numerous fields. Nevertheless, for certain real-world applications, existing models encounter diverse challenges, ranging from a lack of generability to new data to issues of scalability and overfitting. In this context, integrating information extracted from different modalities holds promise as a potential solution to alleviate these challenges. This paper introduces MAVEN, a multimodal deep-learning framework for long-range atmospheric visibility estimation. Using multimodal deep learning, MAVEN fuses various modalities to estimate long-range atmospheric visibility. These modalities include RGB imagery, Edge Map, Entropy Map, Depth Map, and Normal Surface Map. Results show that in contrast to single-modality RGB, which achieves only 87.92% accuracy, multimodal deep learning models achieve an accuracy of over 96%. This significant improvement highlights the potential of multimodal approaches to enhance the accuracy and reliability of atmospheric visibility estimation, which is crucial for improving safety in applications such as aviation, maritime navigation, and autonomous vehicles. By addressing challenges such as data variability, environmental factors, and the inherent complexity of atmospheric conditions, MAVEN contributes to more reliable and robust visibility estimation systems, thereby enhancing safety and operational efficiency in critical environments.
Several efforts have been made to develop Flight Test Maneuvers for Handling Qualities evaluations, aimed at quantifying the effects of vehicle characteristics and assistance systems on a Helicopter Air-to-Air Refueling mission profile. However, these Flight Test Maneuvers have not achieved widespread adoption, likely due to the substantial logistical challenges associated with tanker deployment. Depending on a tanker aircraft not only incurs significant costs but also requires extensive organizational effort and prior testing, before Handling Qualities can be evaluated for the aerial refueling capabilities of a new rotorcraft design. Additionally, these available Flight Test Maneuver setups are not standardized or widely applied to the same degree as Mission Task Elements of the Aeronautical Design Standard, which limits repeatability and comparability. A new approach is proposed to address these limitations by introducing a repeatable, standardized method to reveal Handling Qualities deficiencies considering a worst-case situation of Helicopter Air-to-Air Refueling. This approach involves analyzing drogue motion to create a synthetic, deterministic target forcing function, based on the summation of several sine waves. Resulting laws of motion are applied to a target tracking task replicating a drogue chasing scenario by projecting all required references into the pilots' field of view. Piloted simulator studies conducted at the Air Vehicle Simulator (AVES) of the German Aerospace Center (DLR) demonstrate a high degree of similarity in pilot control behavior between the proposed Flight Test Maneuver and actual simulated Helicopter Air-to-Air Refueling.
Accurate simulation of fluid-structure interactions (FSI) is critical for designing aircraft systems, particularly for applications involving fuel tank sloshing and large deformations. Traditional added mass methods often fail to capture the nonlinear and frequency-dependent behavior of these coupled systems. This study applies the Finite Pointset Method (FPM), a mesh-free computational fluid dynamics (CFD) technique, coupled with an explicit finite element solver, to predict complex FSI phenomena. Validation is performed using benchmark experiments, including a harmonic tank sloshing test and a guided plate ditching scenario, with results demonstrating strong agreement with measured pressures and structural responses. Additional validation on a composite fuel tank drop impact test confirms FPM's ability to model large deformations and rupture under dynamic loading. The findings highlight FPM's robustness and adaptability for aerospace FSI problems, offering a powerful alternative for virtual prototyping and certification workflows where conventional methods are insufficient.
To validate simulation work towards the design of the Dragonfly rotorcraft lander, a process of extracting a modal model from impact test data is described in this paper. Through a curve-fitting process using Siemens Testlab software, modal frequencies, damping, and mode shapes are extracted and mass-normalized to be imported as a modal model into the Rotorcraft Comprehensive Analysis System (RCAS) to represent the dynamics of the underlying structure more accurately. Wind tunnel conditions were simulated to compare to hub loads measured during wind tunnel testing. An initial comparison of RCAS with VVPM inflow and RCAS coupled with HELIOS show similar hub loads but also show the importance of modeling the rotational degrees of freedom of the structure properly. Additional modeling comparisons between modeling the hubs and the load cell locations further illustrate that by capturing rotational mode shapes based on test data, in-plane hub loads are predicted more accurately.
As part of a larger project aimed at gaining a better understanding of factors that affect the quality of test results using anthropomorphic test devices (ATDs), the FAA tested the effects of dynamic loading of an ATD pelvis. The ATDs required in the aviation regulations were initially developed for the automotive crash environment, which does not include a vertical testing component. One of the two dynamic tests is a vertical impact, with the principal measurement being the compressive load in the lumbar spinal column, with a regulatory limit of 1500 lb. The lumbar load cell is mounted to the pelvis, and data collected could be affected by the performance of the ATD pelvis. The ability to define a vertical calibration test could be used to determine if the pelvis is acceptable for initial use or to monitor in-service degradation. Three ATD pelvises were compressed in a high-rate load frame. The peak load and loading rate of the pelvis compression were selected to simulate conditions achieved in transport category aircraft vertical seat testing. The primary test objective was to measure changes to the rubber and foam cover of the metallic pelvis during high cyclic loading. Each pelvis was subjected to over 100 cycles. Static dimensional measurements, based on a manufacturing tolerance evaluation, were collected during testing. The high-cycle testing did not deform the foam and rubber covers enough to exceed the total dimensional tolerance of the pelvises (± 0.120 in.). The appearance of visual damage was closely monitored throughout the testing. Similar visual damage was seen for each pelvis and occurred at low cycles — 15 to 30. Results suggest the appearance of damage minimally changed the dynamic response of the pelvis. Force-deflection data were also collected from each test series. These data showed minimal change during testing, with the deflection at 2000 lb. changing approximately 0.100 in. across the 105 cycles. This value is similar to the manufacturer’s tolerance for the height of the pelvis. Based on this, the number of vertical sled tests that would precipitate replacement may be over 100 cycles. Due to the harsh environment of dynamic sled testing, other factors, such as cuts in the foam and rubber due to belt loading, may trigger the removal of an ATD pelvis from service prior to the pelvis reaching a defined number of cycles. Future FAA research will evaluate how this change in pelvis force-deflection affects lumbar load.
Aircraft Certification is a mature and complex bureaucracy that has successfully ensured a very high degree of safety of aircraft design, construction, operation and maintenance. Outside of a very few doing the work, there is a general lack of knowledge of certification details. For novel technologies such as electric power, and innovative configurations such as multi-rotors, the rules are far less mature and still emerging and so also poorly understood. Within the Advanced Air Mobility (AAM) initiative, many new aircraft developments are underway using novel configurations, and the public announcements of regulatory progress toward FAA or EASA Type Certification capitalize on this ignorance by being vague or even misleading. Honeywell conceived the Regulatory Readiness Level (RRL) indicator as an objective measure of certification status to serve the AAM industry and ecosystem, with applicability across aviation. The released RRL Version 1 now enables credible, objective assessment of new aircraft progress toward FAA Type Certification, and Operational Approval for Part 135 operations, to allow consistent apples-to-apples comparisons with other aircraft in development. An emerging complementary version of the rubric for EASA Type Certification is ready for publication to enable RRL determination against the European Union criteria. Future releases will consider other Nation's regulatory authorities, supplemental types certifications (STCs), and risk-based airworthiness assessments such as the Specific Operations Risk Assessments (SORA).
Electric Vertical Takeoff and Landing (eVTOL) aircraft present a series of challenges to traditional aviation infrastructure that was designed for conventional rotorcraft. Questions have arisen within the vertical flight community as to the validity and applicability of applying current heliport markings and symbology to vertiports. Several of these questions were addressed in a previous paper from VFS Forum 80: "A Comparison of Proposed Concepts for Vertiport Markings and Symbology" (Ref. 6). In contrast, this paper extends that work and presents the results of additional research to enhance the visibility of the Federal Aviation Administration’s (FAA) “Broken Wheel” symbology. These notional enhancements to the "Broken Wheel" symbology were evaluated over the course of an experimental study using helicopter-rated pilots in the FAA William J. Hughes Technical Center’s S76-D and Loft Dynamics H125 and R22 rotorcraft flight simulators.
The Crashworthy and Escape Systems Branch at NAWCAD has been developing an integrated restraint harness concept for several years, with the intent of developing a novel method of providing improved occupant protection in a crash scenario. A series of tests was conducted on the Horizontal Accelerator at NAS Patuxent River to evaluate the performance of the prototype integrated-restraint system under MIL-STD-58095 conditions with the 50th percentile male Hybrid III Anthropomorphic Test Device (ATD). While occupant flail was the primary metric being analyzed in this effort, ATD instrumentation was also captured, showing that the integrated restraint system demonstrated a significant reduction in head flail compared to five-point restraints while maintaining injury criteria within acceptable levels.
In this paper, we describe an innovative V&V approach using the SCADE product, enabling significant reduction of effort while preserving compliance with DO-178C/DO-331. This new approach relies on a unique capability: automatic generation of Low-Level Tests. Details about savings will be provided to show how we can reduce costs, speed up certifications, and bring products to the market faster. We will conclude by summarizing the actual benefits and describing ongoing work to bring other savings in the future.
Time-resolved background-oriented schlieren (BOS) data are used to calculate the two-dimensional velocity field in the wake of free-flying full-scale helicopters in ground effect. The calculation is performed based on the density gradient pattern of the helicopter engine exhaust gas passing the BOS field of view. A classical BOS evaluation allows the visualization of density gradients such as vortices and the exhaust plume. The result is the BOS displacement field. Applying the two-dimensional divergence to this data results in a pattern that is constant in shape across multiple BOS images, but convects downstream with the outwash velocity of the helicopter. Using this data as input to a second, timeresolved evaluation, quantitative two-dimensional velocity fields are calculated. Choosing an appropriate strategy for preparing and evaluating the data is critical to reliable velocity estimation. Another important aspect is to distinguish between reliable velocity data and erroneous results in areas of reduced signal intensity due to a lack of thermal structures. The velocity data obtained are compared with an analytical outwash model and constant temperature anemometry data acquired simultaneously with the BOS images. The data show good quantitative agreement in areas of sufficient thermal structures within the field of view.
ABSTRACT In this work, iced rotors are studied to develop insight in the potential of acoustics-based ice detection. Based on the HMB CFD solver, approximate iced shapes are used and results are analyzed using the FW-H method. Several candidate monitoring positions are assessed for acoustic sensors to be placed on the helicopter fuselage. The influence of ice on the aero-acoustic characteristics of a rotor is calculated, and parameters such as the ice amount and the icing position on the blade are quantified.
The paper presents recent and ongoing activities of the German Aerospace Center (DLR) focusing on experimental icing investigations within the nationally funded project InTEnt-H (2018-2022) and progressive activities in continuing internal DLR projects. The aim of InTEnt-H was to investigate innovative de-icing and anti-icing technologies for small and medium-weight helicopters, for which no rotor de-icing technologies exist to date, and to demonstrate the effectiveness of these systems in a suitable test facility. For this purpose, the whirl tower test facility of the DLR in Braunschweig has been converted into an icing test facility that is unique in Europe and will allow for the generation of atmospheric icing conditions. In this facility, de-icing and anti-icing systems for rotor blades can be tested under centrifugal loads and various icing conditions. The paper starts with a short presentation of the retrofitting works at the DLR whirl tower test facility and its major components. Then, the progress of the first test campaigns of the projects are reported. The main focus is on the design and test of the de-icing rotor system, carrying different antiicing/ de-icing technologies. The paper closes with an outlook on the upcoming activities planned to satisfy and verify EASA CS-29 Appendix C icing conditions in the frame of the DLR internal project SAFER2.
ABSTRACT The ability to model and evaluate aircraft performance prior to flight has generated a significant increase in safety margin in the flight testing of experimental aircraft. Prior to the artificial icing campaign for the AW609 aircraft, a flight model of predicted aerodynamic behavior was used to rapidly generate a control margin monitoring and warning system, which was implemented on-board the aircraft during testing to provide awareness of predicted aircraft behavior under icing conditions.
Researchers at the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC) have conducted a series of structural component and seat level tests to improve finite element model (FEM) characterization of a representative vertical take-off and landing (eVTOL) test article developed by NASA. A full-scale dynamic test was conducted on the representative eVTOL test article in November of 2022. The test article represented a high wing, six passenger eVTOL design concept and is referred to as the lift plus cruise (LPC) test article. The full-scale test identified limitations in the analytical models used to predict aircraft structural response, in particular the composite material models did not effectively capture brittle failure of the structure which were measured during dynamic loading. To better understand the mechanism behind the composite material failure mechanisms observed and to improve the FEM, intact sample specimens of the composite airframe structure were recovered from the test article post-test and used in material characterization testing. In addition, the seat configurations used in the LPC test article were further studied using isolated seat and anthropomorphic test device (ATD) drop tower testing. Dynamic compression tests and three-point bend tests, conducted at varied impact speeds, were performed on the recovered frame section specimens. Additional testing was conducted to characterize the material properties of the forming foam, which remained in the frames after fabrication. These tests were used to improve characterization of the damage and failure parameters of the composite material model used in the FE model of the LPC test article. Seat level tests were conducted on the seats used in the LPC test article using acceleration pulses inclusive of current general aviation and rotorcraft certification load levels as well as conditions representative of those measured at the seat base during the LPC test. The structural material models and seat environment models of the LPC test article FEM were calibrated using the generated component test data. The updates made to these models were then integrated into the LPC FEM and simulated in the full-scale test condition. Results demonstrated the effectiveness of component testing to improve predictive capability of composite aerospace structural models within the crash and dynamic loading environments. Demonstration of the LPC FEM response across an accumulation of coupon, component, seat environment, and full-scale test levels provides confidence in the predictive capability of this model for future use in the study of occupant safety within eVTOL relevant crash environments.
The AW609 tiltrotor features a unique high-mounted wing with rotatable nacelles positioned at the wing tips, it is capable of operating both in airplane and vertical flight mode. To achieve suited protection of the occupants during emergency landing, the wing - which is particularly stiff in order to sustain the heavy weights at the tips, where rotors, engines and transmissions are positioned - implements a controlled failure mechanism at root, so that during emergency landings it breaks and unloads the fuselage of the weight of wingbox and nacelles, thus avoiding catastrophic collapse. As the effectiveness of such mechanism was never demonstrated under impact conditions, certification agencies requested an empirical validation through experimental testing. The test was carried out July 2022 at Polytechnic of Milan, Italy; the present work details the Test activity, from its preliminary phases to the Test Day, to the analyses of its outcomes.
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 rotorcraft community faces significantly higher accident rates compared to fixed-wing commercial aircraft, underscoring the critical need for enhanced safety measures. While Helicopter Flight Data Monitoring programs hold promise in improving safety, their widespread adoption remains limited, partly due to challenges associated with the acquisition and analysis of flight data. This paper proposes a Deep Learning (DL) solution to address safety concerns within the rotorcraft community by efficiently acquiring and analyzing flight data for a more automated and comprehensive safety assessment. Specifically, we leverage data obtained with cost-effective off-the-shelf cameras, and process it through Convolutional Neural Networks for automated detection and classification of gauges from several helicopters' cockpits. Our DL pipeline integrates a classifier for helicopter identification, an object detector for cockpit gauges detection and classification, and a network to infer the reading of each detected gauge. The contribution of this work is two-fold: (1) enhance rotorcraft safety by developing a DL framework capable of detecting, classifying, and inferring gauge readings for different helicopter types, and (2) boost research in the field by constructing a curated dataset valuable for aviation and machine learning communities.
The Advanced Helicopter Seating System (AHSS) was started as an effort to evaluate and improve the current state of military rotorcraft seating. The overall goal of the program has been to improve pilot ergonomics and safety through the integration of advanced energy absorption and vibration reduction mechanisms as well as a broad approach to system integration based around updated occupant anthropometrics. An entirely new seating solution has been developed, with intent to integrate with the AH-64 Apache platform for demonstration purposes. The AH-64 development culminated with a series of static tests and dynamic test events to measure the effectiveness of the safety systems integrated on the seat as compared to the legacy AH-64 seating system. While lumbar load data and seat stroke data was obtained, issues with the anthropomorphic test device (ATD) configuration at the 95th male configuration caused some data to be suspect, and premature failure of several components also caused loss of capturing accurate data. Lessons learned are documented in the conclusions. Data and lessons learned from this effort are being used to support a follow-on effort to develop a pilot seat for the UH-60 Black Hawk Platform.
This paper presents the results of a research and development (R&D) effort focused on fluid structure interactions between airframe structures and bladder type fuel tanks during a crash environment. During this R&D effort, fuel tank and surrounding structure crash impact tests were conducted using an innovative test configuration that allowed low-cost fabrication of test articles which represented several different design architectures. LS-DYNA models of the crash test article configurations were also developed and correlated with the tests data. Good correlation between the test data and LS-DYNA analysis results was achieved. The paper also includes recommendations for design of the airframe structures around the fuel tanks based on the fluid structure interaction insights gained from the crash tests and analyses.
Piloted simulation has been used for decades to support flight test activities at the Naval Air Warfare Center Aircraft Division located at Naval Air Station Patuxent River, MD. Conventional lab stations at the Manned Flight Simulator facility have been used effectively to support a wide range of flight test requirements. However, there were limitations with these conventional lab stations when the purpose was to assess handling qualities and pilot workload while landing rotorcraft aboard a ship. Two critical simulation elements were determined to be necessary: (1) an expanded field of view so the pilot could see the ship deck below the aircraft and (2) a motion system to provide the pilot with vital proprioceptive cueing in the turbulent ship environment. A new Virtual Reality Lab was developed at Patuxent River that included these key features. The primary components of the lab included virtual reality headsets, an Unreal Engine image generator, ocean and ship visual models, a six degree-of-freedom motion platform, and a generic cockpit. This paper describes development of the lab, various issues that were encountered, and plans for future improvements.
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