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Learn how the ATD-2 analytical team has used various sources and metrics to verify that the operational system follows a do no harm mandate while also providing efficiency and predictability benefits.
Airspace Technology Demonstration 2 (ATD-2) sub-project conducted a Human-in-the-Loop (HITL) simulation to assess Ramp Controllers ability to deliver aircraft to the spot within the compliance window (+/- 5 min) under various metering conditions. Compliance at the spot was similar between the different metering conditions ranging between 83% - 85% and increased to 92% - 99% when aircraft were initially compliant with gate advisories. Metering benefits that exist in the field did not appear in the simulation due to simulation artifacts such as gate holding departures in Baseline, which effectively metered the demand. The combined Target Off-Block Time (TOBT) +Target Movement Area entry Time (TMAT) condition resulted in higher workload on the Workload Assessment Keypad (WAK) than the Baseline and TOBT alone conditions, and lower situation awareness than the Baseline condition. Metering at Dallas/Fort Worth International Airport (DFW) with TOBT only or TMAT only could be equally effective, and either would be a better option than TOBT + TMAT due to increased workload and reduced situation awareness.
High-level overview of capability and evaluation of a NASA ATD-2 prototype system that enables Flight Operators and Air Traffic Management to manage reroute of departures in Dallas, TX.
Overview of developments and results of a NASA ATD-2 prototype system that enables Flight Operators and Air Traffic Management to manage reroute of departures in Dallas, TX.
This briefing discusses how machine learning could be applied to large aviation data problems, using TBFM SWIM data elements and data analytics lessons learned from ATD-2.
In June 2019, a full-scale crash test of a Fokker F28 Fellowship aircraft was conducted as part of a joint National Aeronautics and Space Administration/Federal Aviation Administration (NASA/FAA) project to investigate the performance of transport aircraft under realistic crash conditions. The test objectives were to provide data for assessment of transport aircraft crash worthiness and to generate test data for model validation. The test article was loaded with transport aircraft seats in a 3+2 configuration. A total of 24 instrumented Anthropomorphic Test Devices (ATDs) were placed in the seats and restrained. The test article weighed 33,306-lb. and, during the crash test, impacted a 2-ft. high soil bed at 65.3-ft/s forward and 31.8-ft/s vertical velocity. The full-scale crash test was simulated using the commercial nonlinear explicit transient dynamic finite element code, LSDYNA®. This paper will provide a description of the test article and the crash test conditions, document the F28 full-scale model development, and present test-analysis comparisons in several categories including inertial properties, kinematic responses, structural acceleration responses, and airframe deformation and failure. In addition, test-analysis results will be quantified based on the International Organization for Standardization (ISO) 16250 curve comparison methodology.
In this report, the capability of component fuselage testing and finite element models (FEMs) to predict occupant injury risk when applied to full-scale aircraft crash testing was evaluated. Component level and full-scale crash tests of a Fokker-F28 aircraft were performed in conjunction with representative FEM simulations. Lumbar spine injury risk, calculated through Anthropomorphic Test Device (ATD) outputs measured in the full-scale test, was compared with predictions made by component level testing and simulations. A quantitative assessment of FEM prediction accuracy was made using the International Organization for Standardization (ISO) Technical Report (TR) 16250 curve comparison methodology. Lumbar load injury risk measured in the full-scale test configuration was found to be significantly higher than in the component tests performed. The FEM provided a closer prediction of occupant injury risk than component testing but exhibited limitations in the multi-axis load environment. This work will help inform the application of component testing and FEM simulation when used to evaluate aircraft crashworthiness.
Unique facility allows for the testing of items from coupons to airframes: - Composites, metals, honeycombs, foams, struts, ATDs, - MD-500, CH 46, Orion Boilerplates, Orion Pallets, “Iron Birds”.
In June 2019, a full-scale crash test of a Fokker F28 Fellowship aircraft was conducted as part of a joint National Aeronautics and Space Administration/Federal Aviation Administration (NASA/FAA) project to investigate the performance of transport aircraft under realistic crash conditions. The test objectives were to provide data for assessment of transport aircraft crashworthiness under realistic impact conditions and to generate test data for model validation. The test article was loaded with transport aircraft seats in a 3+2 configuration. A total of 24 instrumented ATDs were placed in the seats and restrained. The test article weighed 33,306-lb. (15,107.3-kg) and, during the crash test, impacted a 2-ft. (0.61-m) high soil bed at 65.3-ft/s (19.9-m/s) forward and 31.8-ft/s (9.7-m/s) vertical velocity. The full-scale aircraft crash test was simulated using the commercial nonlinear explicit transient dynamic finite element code, LS-DYNA. This paper will provide a description of the test article and the crash test conditions, document the F28 full-scale model development, and present test-analysis comparisons. The test-analysis comparisons include inertial properties, kinematic responses, structural acceleration responses, and structural deformation and failure.
The presentation discusses goals for real-time metrics, new fields available in the ATD-2 System for displaying metrics to users, and analyses on delay prediction accuracy and delay savings.
Runway assignments at major airports are made by air traffic controllers subject to various constraints, and to achieve various objectives. In this research, we describe our efforts training machine learning (ML) models to predict both departure and arrival runway assignments using an entirely data-driven approach. This approach is compared to existing rule-based approaches developed in previous research using input from Subject Matter Experts. The models have features derived from various FAA data feeds, and leverage multiple machine learning algorithms. Results for models trained for nine major U.S. airports are described and compared to one another across various important dimensions. Particular attention was paid to developing a repeatable framework for training these models so the approach could be scaled to other airports, and to developing models that are useful in a real-time environment. In addition, the models were designed to be functional in a real-time environment to support NASA’s ATD-2 project, as part of an ML-powered shadow system to compare against the performance of the fielded system.
Runway assignments at major airports are made by air traffic controllers subject to various constraints, and to achieve various objectives. In this research, we describe our efforts training machine learning (ML) models to predict both departure and arrival runway assignments using an entirely data-driven approach. This approach is compared to existing rule-based approaches developed in previous research using input from Subject Matter Experts. The models have features derived from various FAA data feeds, and leverage multiple machine learning algorithms. Results for models trained for nine major U.S. airports are described and compared to one another across various important dimensions. Particular attention was paid to developing a repeatable framework for training these models so the approach could be scaled to other airports, and to developing models that are useful in a real-time environment. In addition, the models were designed to be functional in a real-time environment to support NASA’s ATD-2 project, as part of an ML-powered shadow system to compare against the performance of the fielded system.
A brief overview of the ATD-3 DRAW tool for assisting Traffic Management Coordinators with rerouting flights impacted by convective weather in a arrival- metered air traffic environment.
We report the results of X-ray (CXO) and radio (ATCA) observations of the pulsar wind nebula(PWN) powered by the young pulsar PSR J1016–5857, which we dub “the Goose” PWN. In bothbands the images reveal a tail-like PWN morphology which can be attributed to pulsar’s motion. Bycomparing archival and newCXOobservations, we measure the pulsar’s proper motionμ= 28.8±7.3mas yr−1, yielding a projected pulsar velocityv≈440±110 km s−1(atd= 3.2 kpc); its direction isconsistent with the PWN shape. Radio emission from the PWN is polarized, with the magnetic fieldoriented along the pulsar tail. The radio tail connects to a larger radio structure (not seen in X-rays)which we interpret as a relic PWN (also known as a plerion). The spectral analysis of theCXOdatashows that the PWN spectrum softens from Γ = 1.7 to Γ≈2.3−2.5 with increasing distance fromthe pulsar. The softening can be attributed to the rapid synchrotron burn-off, which would explainthe lack of X-ray emission from the older relic PWN. In addition to non-thermal PWN emission, wedetected thermal emission from a hot plasma which we attribute to the host SNR. The radio PWNmorphology and the proper motion of the pulsar suggest that the reverse shock passed through thepulsar’s vicinity and pushed the PWN to one side.
Introduction: Recent data show a landing-attributed injury rate among Soyuz crew members to be higher than predicted in original certification analysis. New vehicles being developed for NASA are being certified using analytical tools to quantify injury risk. This assessment will provide data to allow the Agency to evaluate whether these tools are able to capture true injury risk and allow a comparison between Soyuz landings and upcoming vehicles. Methods: A finite element model (FEM) of the Soyuz descent module (DM) and its landing environment were developed to recreate Soyuz landing conditions. Occupant breakout models composed of the Soyuz seat and Sokol helmet were then developed to evaluate occupant response. These models included both anthropomorphic test device (ATD) and human body model (HBM) surrogates in three anthropometric sizes. A generalized distribution analysis of the Soyuz landing environment was performed using landing variable distributions from available literature. Results were used to identify trends in vehicle landing acceleration with landing conditions and to compare landing model injury risk predictions with those estimated in vehicle certification analysis. Next, historic Soyuz landings identified as inducing occupant injury during were reconstructed using the developed landing model and estimated landing conditions. Results and Discussion: This assessment demonstrated the capability of certification metrics, which include a combination of vehicle- and occupant-level injury risk analysis, to identify elevated injury risk landing conditions. However, the developed landing load predictions were limited by available vehicle and landing condition data. Additional data, particularly landing acceleration data specific to historic Soyuz landing conditions, would greatly enhance this assessment’s findings.
The National Aeronautics and Space Administration (NASA) will perform a full-scale crash test of a representative electric vertical take-off and landing (eVTOL) fuselage in November 2022. The test article is a carbon-composite fuselage cabin section of the six-passenger lift plus cruise (LPC) eVTOL design concept which was created by NASA to advance understanding of eVTOL propulsion, noise, and safety. The test will consist of impacting the fuselage cabin section onto a concrete surface with a combined horizontal and vertical velocity approximating a severe but survivable crash landing for this vehicle design. Data generated from this test will be used to inform eVTOL crashworthiness regulation development, evaluate the use of energy absorbing concepts within vehicle design, and validate finite element model (FEM) techniques used in crashworthiness predictions. The cabin section response will be evaluated using structural instrumentation, anthropometric test devices (ATDs), and high-speed photogrammetry. This study will compare pre-test FEM predictions to test results to quantify the capability of these tools to predict crashworthiness of the carbon-composite eVTOL airframe.
The National Aeronautics and Space Administration (NASA) will perform a full-scale crash test of a representative electric vertical take-off and landing (eVTOL) fuselage in November 2022. The test article is a carbon-composite fuselage cabin section of the six-passenger lift plus cruise (LPC) eVTOL design concept which was created by NASA to advance understanding of eVTOL propulsion, noise, and safety. The test will consist of impacting the fuselage cabin section onto a concrete surface with a combined horizontal and vertical velocity approximating a severe but survivable crash landing for this vehicle design. Data generated from this test will be used to inform eVTOL crashworthiness regulation development, evaluate the use of energy absorbing concepts within vehicle design, and validate finite element model (FEM) techniques used in crashworthiness predictions. The cabin section response will be evaluated using structural instrumentation, anthropometric test devices (ATDs), and high-speed photogrammetry. This study will compare pre-test FEM predictions to test results to quantify the capability of these tools to predict crashworthiness of the carbon-composite eVTOL airframe.
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.