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NASA’s Urban Air Mobility (UAM) Sub-Project is engaged in research to support the introduction of air taxis into the National Airspace System. An important aspect of system development is to consider the human factors aspects of aircraft design. This presentation gives a background on human factors and suggests some important human factors issues for UAM and Advanced Air Mobility.
In-flight icing is an important consideration that affects aircraft design, performance and safety. Newer regulations combined with increasing demand to reduce fuel burn, emissions and noise are driving a need for improvements in icing simulation capability. To that end, this paper presents the results of ice accretion testing conducted in the NASA Icing Research Tunnel on a large swept wing section typical of a modern commercial transport. The model was based upon a section of the Common Research Model wing at the 64% semispan station with a streamwise chord length of 136 in. The test conditions were developed with an icing scaling analysis to generate similar conditions for a small MVD = 25 μm and a large MVD = 110 μm. A series of tests were conducted over a range of total temperature from -23.8 ˚C to -1.4 ˚C with all other conditions held constant. The results for the small MVD cloud conditions were consistent with previous work and showed the changing ice morphology from rime ice at colder temperatures to highly 3D scallop ice in the range of -8.7 ˚C to -3.8 ˚C. The results for the large MVD cloud conditions exhibited some differences in the ice accretion morphology from the small MVD conditions. Scallop-like ice features were observed at total temperature of -3.8˚C. The large MVD ice accretion at lower temperatures tended to be smoother than the corresponding ice accretion for small MVD. The thickness of the main ice shape tended to be larger for the small MVD conditions compared to the corresponding large MVD ice shape while the latter had more ice farther downstream. The measured ice mass was approximately equal between the corresponding small and large MVD ice shapes up to a freezing fraction of 0.6. For higher freezing fraction, the large MVD ice shapes weighed more. Cloud MVD variation from 50 μm to 230 μm while holding the scaling parameters constant resulted in very minor differences in the ice shapes, mostly in the upper and lower surface chordwise extents. Ice volume was computed from 3D scan data and used to calculate a ratio of ice mass to volume. The resulting values were in the range of 240 to 455 Kg/m3. While this is consistent with analogous values previously reported in the literature, more data are needed to determine a specific trend in this ratio as a function of freezing fraction and the corresponding governing physical phenomena. This work has resulted in a significant experimental database of ice accretion for small and large MVD conditions applicable to large-scale swept wings.
In-flight icing is an important consideration that affects aircraft design, performance and safety. Newer regulations combined with increasing demand to reduce fuel burn, emissions and noise are driving a need for improvements in icing simulation capability. To that end, this paper presents the results of ice accretion testing conducted in the NASA Icing Research Tunnel on a large swept wing typical of a modern commercial transport. The model was based upon a section of the Common Research Model wing at the 64% semispan station with a streamwise chord length of 136 in. The test conditions were developed with an icing scaling analysis to generate similar conditions for a small MVD = 25 μm and a large MVD = 110 μm. A series of tests were conducted over a range of total temperature from -23.8 ˚C to -1.4 ˚C with all other conditions held constant. The results for the small MVD cloud conditions were consistent with previous work and showed the changing ice morphology from rime ice at colder temperatures to highly 3D scallop ice in the range of -8.7 ˚C to -3.8 ˚C. The results for the large MVD cloud conditions exhibited some differences in the ice accretion morphology. Scallop-like ice features were observed at total temperature of -3.8˚C. The large MVD ice accretion at lower temperatures tended to be smoother than the corresponding ice accretion for small MVD. The thickness of the main ice shape tended to be larger for the small MVD conditions compared to the corresponding large MVD ice shape while the latter had more ice farther downstream. The measured ice mass was approximately equal between the corresponding small and large MVD ice shapes up to a freezing fraction of 0.6. For higher freezing fraction, the large MVD ice shapes weighed more. Cloud MVD variation from 50 μm to 230 μm while holding the scaling parameters constant resulted in very minor differences in the ice shapes, mostly in the upper and lower surface chordwise extents. Ice volume was computed from 3D scan data and used to calculate a ratio of ice mass to volume. The resulting values were in the range of 240 to 455 Kg/m3. While this is consistent with analogous values previously reported in the literature, more data are needed to determine a specific trend in this ratio as a function of freezing fraction and the corresponding governing physical phenomena. This work has resulted in a significant experimental database of ice accretion for small and large MVD conditions applicable to large-scale swept wings.
The Aircraft Working Group enables the Advanced Air Mobility (AAM) ecosystem through vehicle development and production as well as individual vehicle management and operations. Aircraft design and operations management develop AAM-inspired concepts and technologies to help define requirements and standards addressing key challenges such as safety, integration, noise, automation, and scalability. This presentation focuses on RVLT electronic Vertical Takeoff Landing Propulsion overview.
NASA’s Advanced Air Transport Technology (AATT) project is breaching the boundaries of aircraft design in pursuit of eco-friendly solutions that are compatible with urban noise comfort levels. Boundary layer ingesting (BLI) propulsion systems promise to reduce fuel burn with additional potential benefits in noise reduction. Type-II BLI systems of the STARC-ABL type are the subject of a test campaign planned for fiscal year 2022 in the National Transonic Facility (NTF), for which a CRM-based model with a retrofitted tail cone thruster (TCT) has been designed. The present work is a precursor to the NTF test, where the 240 cases planned for the experiment were simulated using the Launch, Ascent and Vehicle Aerodynamics (LAVA)computational framework. Solution sensitivity to angle of attack, engine operating conditions, and the presence of the supporting structure (sting) in the wind tunnel test are analyzed in the extensive dataset. The main flow features contributing to the inlet distortion are identified as the vertical tail wake, wing downwash and fuselage upsweep vortices, with the latter two experiencing the greatest sensitivity to angle of attack. Finally, results from an inlet-guide-vane(IGV) design/integration study are presented. The LAVA team and the turbomachinery design team at NASA’s Ames and Glenn Research Centers are collaborating in an effort to reduce flow distortion upstream of the fan by means of integrating an IGV system into the CRM-TCT model. A significant improvement in flow distortion metrics has been achieved since the initial design iteration. Results employing an actuator zone model with realistic radially-varying thrust profiles to simulate first-order fan effects within LAVA are presented.
This paper presents an assessment of the airframe noise prediction capability in the research version of the NASA Aircraft Noise Prediction Program (ANOPP) with the objective of validating the accuracy of the current prediction methods, and more importantly, identifying the potential improvements to update the methods. The assessment compares predictions of the individual noise components currently implemented in ANOPP, including the landing gear, the slat, the flap, and the trailing edge noise, with the data from the Propulsion Airframe Aeroacoustics and Aircraft System Noise flight test conducted as part of the Boeing 2020 ecoDemonstrator program on a Boeing 787-10 Etihad Airways aircraft. For each component, prediction errors and discussions are presented for the noise characteristics, covering not only the source features but also the installation effects. It is shown that the predictions by the research level methods in ANOPP capture the major noise features, but improvement potential is identified in two main categories. The first includes minor features that have not been sufficiently modeled in the current methods, the noise due to interactions of the landing gear wake with the flaps and the slat bracket noise, for example. The second is related to changes in modern aircraft designs, which may alter the noise source mechanisms, and thus, calls for major improvements and updates on the current prediction models, examples including the flap side edge noise for modern flap systems and the trailing edge noise for realistic wings with taper and sweep. To illustrate the progress of the method development, previous generations of airframe noise models in ANOPP are also compared with the flight test data.
The results of an ongoing assessment of the transition modeling capability in NASA's OVERFLOW and FUN3D programs are presented, with a focus on the Langtry-Menter γ-Reθt transition model in combination with the shear-stress transport (SST) turbulence model. While the effect of numerics and boundary conditions on the accuracy and iterative convergence of RANS solutions for fully turbulent flows has been well documented, especially in the context of canonical flow configurations, the same cannot be said for transport-equation-based transition models coupled with RANS-based turbulence models. Given the criticality of transition modeling for new aircraft design and optimization, there has been a renewed focus on the accuracy of such transition models and their inconsistent implementation across different flow solvers as seen from the AIAA and NATO-AVT workshops. In this work, we aim to establish the verification of such models via these two well established CFD codes with different numerics. The goal is to produce high-quality data, such as grids, solutions, and other auxiliary data, that may be utilized for code verification by others in the CFD community. As a first step, the work reported here is focused on the Langtry-Menter transition model as applied to two simple 2D configurations, namely the flat plate, and the NLF-0416, respectively. The paper also highlights how the boundary conditions and baseline turbulence model can affect the solutions from the SST-based Langtry-Menter transition model. A preliminary evaluation of the automatic mesh adaption capabilities of these solvers and potential benefits for flow configurations involving a mix of laminar, transitional, and fully turbulent flows is also reported.
Over the past several years, Urban Air Mobility (UAM) has galvanized enthusiasm from investors and researchers, marrying expertise in aircraft design, transportation, logistics, artificial intelligence, battery chemistry, and broader policymaking. However, two significant questions remain unexplored: (1) What is the value of UAM in a region’s transportation network? and (2) How can UAM be effectively deployed to realize and maximize this value to all stakeholders, including riders and local economies? To adequately understand the value proposition of UAM for metropolitan areas, the authors develop a holistic multi-modal toolchain, SimUAM, to model and simulate UAM and its impacts on travel behavior. This toolchain has several components: (1) Microsimulation Analysis for Network Traffic Assignment (MANTA): A fast, high-fidelity regional-scale traffic microsimulator, (2) VertiSim: Agranular, discrete-event vertiport and pedestrian simulator, (3) Flexible Engine for Fast-time Evaluation of Flight Environments (Fe3): A high-fidelity, trajectory-based aerial microsimulation. SimUAM, rooted in granular, GPU-based microsimulation, models millions of trips and their movements in the street network and in the air, producing interpretable and actionable performance metrics for UAM designs and deployments. Once the ground-air interface is modeled, the authors find that the market for UAM decreases across all network designs relative to models with static assumptions about transfer times. However, significant improvements can be made to balance the demand and optimize the networks for transfer time, likely increasing the number of benefited trips. The modularity, extensibility, and speed of the platform will allow for rapid scenario planning and sensitivity analysis, effectively acting as a detailed performance assessment tool.
Over the past several years, Urban Air Mobility (UAM) has galvanized enthusiasm from investors and researchers, marrying expertise in aircraft design, transportation, logistics, artificial intelligence, battery chemistry, and broader policymaking. However, two significant questions remain unexplored: (1) What is the value of UAM in a region’s transportation network?, and (2) How can UAM be effectively deployed to realize and maximize this value to all stakeholders, including riders and local economies? To adequately understand the value proposition of UAM for metropolitan areas, we develop a holistic multi-modal toolchain, SimUAM, to model and simulate UAM and its impacts on travel behavior. This toolchain has several components: (1) MANTA: A fast, high-fidelity regional-scale traffic microsimulator, (2) VertiSim: A granular, discrete-event vertiport and pedestrian, (3) 3: A high-fidelity, trajectory-based aerial microsimulation. SimUAM, rooted in granular, GPU-based microsimulation, models millions of trips and their exact movements in the street network and in the air, producing interpretable and actionable performance metrics for UAM designs and deployments. The modularity, extensibility, and speed of the platform will allow for rapid scenario planning and sensitivity analysis, effectively acting as a detailed performance assessment tool. As a result, stakeholders in UAM can understand the impacts of critical infrastructure, and subsequently define policies, requirements, and investments needed to support UAM as a viable transportation mode.
Researchers at the National Aeronautics and Space Administration (NASA) Armstrong Flight Research Center (Edwards, California); the Federal Aviation Administration (FAA); and Regulus Group, LLC (Atlantic City, New Jersey) collaborated for the flight-test demonstration of an Automatic Dependent Surveillance-Broadcast (ADS-B) system equipped on a high-altitude Earth Resources-2 (ER-2) research airplane. The unique ER-2 airplane is a NASA-owned and operated airborne science version of the United States Air Force / Lockheed Martin Aeronautics (Bethesda, Maryland) U-2S airplane. The FAA has mandated that by the year 2020, aircraft operating within certain sections of the United States National Airspace system be equipped with ADS-B Out technology; the research presented in this paper is the first to show how the NASA ADS-B architecture satisfies the mandate for a unique high-altitude aircraft. An exceptional military aircraft design, security protocols, and the performance envelope of the ER-2 airplane made the avionics integration remarkably challenging. The design required the ADS-B avionics to survive the harsh flight environment of the ER-2 airplane. The most prominent challenge was the functional integration of modern civilian avionics into federated military legacy avionics. Flight-test objectives were to certify an ADS-B Out (1090ES) passive surveillance integrated with a Traffic Alert and Collision Avoidance System (TCAS) I active surveillance system on an ER-2 platform for high-altitude cruise operations. In April 2022, NASA conducted three flights at Edwards Air Force Base (Edwards, California) - each greater than one-hour flight reaching altitudes above 60,000 ft.
With the current technological advancements revolutionizing the concept of Urban Air Mobility (UAM) and package delivery, there is also, a concurrent need to quantify the operational safety of these vehicles in terms of their associated risk. Conducting safe flight operations is critical for UAM vehicles which are electrically Vertical Takeoff and Landing (eVTOL) vehicles, to operate in current Air traffic control. In this paper, a data-driven method for UAM vehicle energy consumption prediction and risk quantification with conditional value-at-risk based on energy consumption distribution is presented. Significant factors affecting energy consumption, such as density altitude, aircraft design, airspeed, and collision avoidance algorithms, are considered in the data-driven based energy consumption prediction of different eVTOL
Auralization of the sound fields within flight vehicle interiors is of interest to aircraft designers considering crew and passenger ride quality. Computer models can be used to predict the filtering effects that the fuselage structure and interior volume have on the exterior sound field in order to simulate the resulting cabin interior noise. However, this can become expensive when a wide frequency range of analysis suitable for passenger auralization is desired. This is particularly the case when using deterministic modeling methods such as finite element analysis (FEA) wherein prohibitively high levels of detail and finite element discretizations are required to resolve the wavelengths at high frequencies. On the contrary, Statistical Energy Analysis (SEA), while not capturing important modal behaviors at low frequencies, is better suited for higher frequency analyses where structural and interior dynamics exhibit high modal overlap and spatially averaged physical quantities suffice. For this reason, a hybrid procedure is considered here that utilizes FE modal solutions at lower frequencies and SEA results at higher frequencies. A transfer function dataset containing the exterior to interior vibroacoustic filtering effect is calculated accordingly and subsequently stored to be used for a variety of exterior dynamic load cases. At low frequencies, the transfer function dataset detail is related to the level of FE model refinement whereas at high frequencies it functions as an equalizer array with a level of detail corresponding to the SEA subsystem partitioning scheme. The above procedure is described herein and demonstrated on a six passenger flight vehicle with eight propulsors in a hover flight condition.
In-flight icing is an important consideration that affects aircraft design, performance, certification and safety. Newer regulations combined with increasing demand to reduce fuel burn, emissions and noise are driving a need for improvements in icing simulation capability. To that end, this paper presents the results of additional ice accretion testing conducted in the NASA Icing Research Tunnel in January 2022 with a large swept wing section typical of a modern commercial transport. The model was based upon a section of the Common Research Model wing at the 64% semispan station with a streamwise chord length of 136 in. The test conditions were developed with an icing scaling analysis to generate similar conditions for a small median volumetric diameter (MVD) = 25 μm cloud and a large MVD = 110 μm cloud. A series of tests were conducted over a range of total temperature from -23.8 ˚C to -1.4 ˚C with all other conditions held constant. Another series of tests explored cloud MVD variations from 50 μm to 230 μm while holding constant certain scaling parameters. The variation in ice mass and scanned ice volume across repeat conditions was approximately 50% lower than the uncertainty in the cloud MVD and liquid water content. The measured ice mass and volume calculated from the 3D scans were used to compute the mass to volume ratio that is sometimes referred to as ice density or void fraction. When the ice volume based on the ice shape maximum combined cross section was used to determine this ratio, the resulting values were in the range of 240 to 455 kg/m 3 . This is consistent with analogous values previously reported in the literature. The ice shape mass and volume increased with MVD from 50 to 230 μm at fixed values of the scaling parameters. The ice mass to volume ratio was approximately constant for all of the cases which showed that the accreted mass and volume increased at approximately the same rate. These results demonstrate the significance of cloud MVD on ice shape mass and volume.
In-flight icing is an important safety issue and is a factor that affects aircraft design and performance. Newer regulations are driving a need for improvements in airframe and engine icing simulation capability. Experimental data is required for development of icing physics models and simulation validation. To that end, this paper presents the analysis of the supercooled liquid icing data subset from tests conducted in 2022 at the NASA Icing Research Tunnel that studied both supercooled water and ice-crystal icing. The test article that was utilized replicated 3D geometrical features of an inter-compressor duct and strut region of a turbofan engine. The surfaces of the Simulated Inter-compressor Duct Research Model (SIDRM) can be heated to simulate the warm surfaces of the turbofan inter-compressor duct. The test article is instrumented with pressure taps, heaters, heat flux gauges, and thermocouples, while a 3D laser scanner, cameras, and a scale to measure ice mass were utilized to characterize the icing behavior. The aim of these tests was to generate ice accretions on the SIDRM test article under well-characterized supercooled liquid icing and ice crystal icing conditions. This paper discusses measurements related to aerodynamic testing and supercooled liquid icing tests that were conducted. Aerodynamic measurements were analyzed and compared to computational simulations and were found to be in good agreement for the range of airspeeds (50 to 230 knots) and angles of attack (0 to 4°) tested. Various parametric sweeps were conducted during the supercooled liquid icing portion of the test entry (cloud median volumetric diameter ranged from 15 to 90 µm, total air temperature from -3 to -17 °C, angle of attack from 0 to 4°, and accretion time from 5 to 20 min). These sweeps were performed to measure that parameter’s impact on ice accretion size, location (icing extent), characteristics (such as glaze/rime ice and shedding behavior), and test article surface temperature. Analysis of the test data showed that clouds composed of larger drops, colder air temperatures, smaller angles of attack, and longer spray times were the primary parameters that resulted in accretions with greater ice mass. Test article angle of attack and cloud droplet size influenced the location of ice accretion as these two parameters directly impact collection efficiency. With respect to icing characteristics, total air temperature dictated icing type, and smaller cloud drop size along with warmer air temperatures resulted in greater amounts of ice shedding. Surface temperature increased during ice accretion from the release of latent (fusion) heat, where total air temperature and cloud drop size impacted the amount of surface temperature change. The icing measurements collected during the SIDRM tests will be used to develop and validate 3D computational engine icing tools, such as GlennICE, that predictively assesses the onset and growth of ice. One of the goals of the sponsoring NASA project is to develop simulation models and tools that can assist in the design and certification of engines for flight in icing conditions in a cost effective way.
In-flight icing is an important consideration that affects aircraft design, performance, certification and safety. Newer regulations combined with increasing demand to reduce fuel burn, emissions and noise are driving a need for improvements in icing simulation capability. To that end, this paper presents the results of additional ice accretion testing conducted in the NASA Icing Research Tunnel in January 2022 with a large swept wing section typical of a modern commercial transport. The model was based upon a section of the Common Research Model wing at the 64% semispan station with a streamwise chord length of 136 in. The test conditions were developed with an icing scaling analysis to generate similar conditions for a small median volumetric diameter (MVD) = 25 μm cloud and a large MVD = 110 μm cloud. A series of tests were conducted over a range of total temperature from -23.8 ˚C to -1.4 ˚C with all other conditions held constant. Another series of tests explored cloud MVD variations from 50 μm to 230 μm while holding constant certain scaling parameters. The variation in ice mass and scanned ice volume across repeat conditions was approximately 50% lower than the uncertainty in the cloud MVD and liquid water content. The measured ice mass and volume calculated from the 3D scans were used to compute the mass to volume ratio that is sometimes referred to as ice density or void fraction. When the ice volume based on the ice shape maximum combined cross section was used to determine this ratio, the resulting values were in the range of 240 to 455 kg/m3. This is consistent with analogous values previously reported in the literature. The ice shape mass and volume increased with MVD from 50 to 230 μm at fixed values of the scaling parameters. The ice mass to volume ratio was approximately constant for all of the cases which showed that the accreted mass and volume increased at approximately the same rate. These results demonstrate the significance of cloud MVD on ice shape mass and volume.
In-flight icing is an important safety issue and is a factor that affects aircraft design and performance. Newer regulations are driving a need for improvements in airframe and engine icing simulation capability. Experimental data is required for development of icing physics models and simulation validation. To that end, this paper discusses analyzed data from icing tests conducted with a 3D test article in 2022 at the NASA Icing Research Tunnel. The test article, whose geometry is representative of an inter-compressor duct and strut region of a turbofan engine, has been designed and constructed to study the physics of supercooled water icing and ice crystal icing. The surfaces of the Simulated Inter-compressor Duct Research Model (SIDRM) can be heated to simulate the warm surfaces of the turbofan inter-compressor duct. The test article is instrumented with pressure taps, heaters, heat flux gauges, and thermocouples, while a 3D laser scanner, cameras, and a scale to measure ice mass were utilized to characterize the icing behavior. The aim of these tests was to generate ice accretions on the SIDRM test article under well-characterized supercooled liquid icing and ice crystal icing conditions. This paper discusses measurements related to aerodynamic tests and supercooled liquid icing tests that were conducted. Aerodynamic measurements were analyzed and compared to computational simulations and were found to be in good agreement for the range of airspeeds (50 to 230 knots) and angles of attack (0 to 4°) tested. Various parametric sweeps were conducted during the supercooled liquid icing portion of the test entry (cloud median volumetric diameter ranged from 15 to 90 µm, total air temperature from -3 to -17 °C, angle of attack from 0 to 4°, and accretion time from 5 to 20 min). These sweeps were performed to measure that parameter’s impact on ice accretion size, location, characteristics (such as glaze/rime ice and shedding behavior), and test article surface temperature. Analysis of the test data showed that clouds composed of larger drops, colder air temperatures, smaller angles of attack, and longer spray times were the primary parameters that resulted in accretions with greater ice mass. Test article angle of attack and cloud droplet size influenced the location of ice accretion as these two parameters directly impact collection efficiency. With respect to icing characteristics, total air temperature dictated icing type, and smaller cloud drop size along with warmer air temperatures resulted in greater amounts of ice shedding. Surface temperature increased during ice accretion from the release of latent (fusion) heat, where total air temperature and cloud drop size impacted the amount of surface temperature change. The icing measurements collected during the SIDRM tests will be used to develop and validate 3D computational engine icing tools, such as GlennICE, that predictively assesses the onset and growth of ice. One of the goals of the sponsoring NASA project is to develop simulation models and tools that can assist in the design and certification of engines for flight in icing conditions in a cost‑effective way.
This paper describes an efficient computational approach for aircraft aerodynamic model development intended for use in flight dynamics simulations. A commercial surface-vorticity flow solver called FlightStream is employed to predict performance, stability, and control characteristics for a NASA subscale electric vertical takeoff and landing aircraft in its isolated-airframe configuration. A framework is described to rapidly convert OpenVSP geometry into a form compatible with the FlightStream software. FlightStream predictions for the variation of aerodynamic force and moment coefficients with airflow angles and control surface deflection angles are compared to static wind-tunnel data to illustrate the process and assess the accuracy of FlightStream solutions. The results and approach presented in this paper are encouraging for use in rapid aerodynamic modeling and flight dynamics simulation development early in the aircraft design process.
Auralization of the sound fields within flight vehicle interiors is of interest to aircraft designers considering crew and passenger ride quality. Computer models can be used to predict the filtering effects that the fuselage structure and interior volume have on the exterior sound field in order to simulate the resulting cabin interior noise. However, this can become expensive when a wide frequency range of analysis suitable for passenger auralization is desired. This is particularly the case when using deterministic modeling methods such as finite element analysis (FEA) wherein prohibitively high levels of detail and finite element discretizations are required to resolve the wavelengths at high frequencies. On the contrary, Statistical Energy Analysis (SEA), while not capturing important modal behaviors at low frequencies, is better suited for higher frequency analyses where structural and interior dynamics exhibit high modal overlap and spatially averaged physical quantities suffice. For this reason, a hybrid procedure is considered here that utilizes FE modal solutions at lower frequencies and SEA results at higher frequencies. A transfer function dataset containing the exterior to interior vibroacoustic filtering effect is calculated accordingly and subsequently stored to be used for a variety of exterior dynamic load cases. At low frequencies, the transfer function dataset detail is related to the level of FE model refinement whereas at high frequencies it functions as an equalizer array with a level of detail corresponding to the SEA subsystem partitioning scheme. The above procedure is described herein and demonstrated on a six passenger flight vehicle with eight propulsors in a hover flight condition.