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392 records · Page 22

OVERFLOW Analysis of Supersonic Retropropulsion Testing on a Blunt Mars Entry Vehicle Concept

Supersonic retropropulsion (SRP) flow over a Hypersonic Inflatable Aerodynamic Decelerator (HIAD) blunt-body vehicle was simulated using the Overflow Computational Fluid Dynamics (CFD) solver. Two nozzle configurations were tested (1E and 1F) as a subset of the seven total configurations in the Descent System Study (DSS) testing campaign. A generalized, Adaptive Mesh Refinement (AMR) shock capturing and plume refinement technique was developed and calibrated for producing automatic and unique grid systems optimized for any given testing condition. Solution independence from grid resolution was determined by successively increasing grid refinement until asymptotic convergence of the mean aerodynamic loads was observed. Overflow Reynolds-averaged Navier-Stokes (RANS) solutions produced realistic SRP flow phenomena, including Mach disk normal shocks contained in high-thrust plumes and bow shock triple-points. Solutions for the 1E nozzle configuration were steady. Conversely, a subset of the 1F test conditions were unsteady and exhibited periodic, non-sinusoidal expansions and contractions of the streamwise-oriented plume, resulting in unsteady aerodynamic loads on the vehicle. Initial investigations into the effect of turbulence modeling fidelity demonstrated significant differences between the aerodynamic loads simulated with RANS and Detached Eddy Simulation (DES). Multiple flow mechanisms were identified as root causes of these differences, including bow shock shape augmentation and reduced entrainment due to reduced turbulence in the DES simulations. Initial comparisons of pitching moment control authority and aerodynamic drag performance between the tested nozzle configurations demonstrated that the 1E configuration may be more advantageous for the Mars Entry, Descent, and Landing (EDL) task.

Supersonic Retropropulsion↗

OVERFLOW Analysis of Supersonic Retropropulsion Testing on a Blunt Mars Entry Vehicle Concept

Supersonic retropropulsion (SRP) flow over a Hypersonic Inflatable Aerodynamic Decelerator (HIAD) blunt-body vehicle was simulated using the Overflow Computational Fluid Dynamics (CFD) solver. Two nozzle configurations were tested (1E and 1F) as a subset of the seven total configurations in the Descent System Study (DSS) testing campaign. A generalized, Adaptive Mesh Refinement (AMR) shock capturing and plume refinement technique was developed and calibrated for producing automatic and unique grid systems optimized for any given testing condition. Solution independence from grid resolution was determined by successively increasing grid refinement until asymptotic convergence of the mean aerodynamic loads was observed. Overflow Reynolds-averaged Navier-Stokes (RANS) solutions produced realistic SRP flow phenomena, including Mach disk normal shocks contained in high-thrust plumes and bow shock triple-points. Solutions for the 1E nozzle configuration were steady. Conversely, a subset of the 1F test conditions were unsteady and exhibited periodic, non-sinusoidal expansions and contractions of the streamwise-oriented plume, resulting in unsteady aerodynamic loads on the vehicle. Initial investigations into the effect of turbulence modeling fidelity demonstrated significant differences between the aerodynamic loads simulated with RANS and Detached Eddy Simulation (DES). Multiple flow mechanisms were identified as root causes of these differences, including bow shock shape augmentation and reduced entrainment due to reduced turbulence in the DES simulations. Initial comparisons of pitching moment control authority and aerodynamic drag performance between the tested nozzle configurations demonstrated that the 1E configuration may be more advantageous for the Mars Entry, Descent, and Landing (EDL) task.

Supersonic Retropropulsion↗

Capabilities and Performance of Juno’s Radio Science Instrumentation

The Juno Gravity Science Instrument is a radio science instrument onboard the Juno spacecraft, which entered orbit around Jupiter in 2016. The prime objective of the radio science investigation is to estimate the gravitational field of Jupiter from the Doppler shift on the radio link between the spacecraft and the Earth-based observing antennas of NASA’s Deep Space Network (DSN). The instrument is composed of a ground component at the DSN’s DSS-25 antenna, equipped with simultaneous dual X- and Ka-band transmitters and receivers, and a spacecraft component, which includes X- and Ka-band transponders to relay the transmitted signal back to Earth. The frequencies of these signals are measured using sensitive open-loop and closed-loop receivers of the DSN. Using the unique geometry of Juno’s orbit around Jupiter and the exquisite precision of the radio science instrumentation (~5-10 microns/sec one-way), the gravity field of Jupiter has been probed to unprecedented precision, allowing for discoveries of Jupiter’s core size and depth of the zonal winds. This precision is thanks to a detailed data processing and calibration techniques. An Advanced Water Vapor Radiometer measures the tropospheric delay and a linear combination X- and Ka-band links calibrates for Earth ionosphere, solar plasma, and Jovian plasma. Recent measurements probed the electron content inside Jupiter’s Io Plasma Torus, a doughnut-shaped ring of charged particles caught in Jupiter’s magnetosphere. Results from these measurements not only contributes to the scientific literature but also informs the performance of the instrument itself and can be used in future planning.

Oudrhiri, Kamal↗

DSN Radio Astronomy Spectrometer

The Deep Space Network (DSN) enables NASA to communicate with its deep space spacecraft. By virtue of its large antennas, the DSN can be used as a powerful instrument for radio astronomy. In particular, Deep Space Station (DSS) 43, the 70 m antenna at the Canberra Deep Space Communications Complex (CDSCC) has a K-band radio astronomy system covering a 10 GHz bandwidth at 17 to 27 GHz. This spectral range covers a number of atomic and molecular lines, produced in a rich variety of interstellar gas conditions. A new high-resolution spectrometer was deployed at CDSCC in November 2019 and connected to the K-band downconverter. The system has two different firmware modes: 1) Using a 65k-pt FFT to provide 32,768 spectral channels at ~30.5 kHz (0.45 km/s velocity resolution) and 2) Using a 16k-pt polyphase filterbank (PFB) to provide 8,192 spectral channels with ~122 kHz resolution (1.8 km/s velocity resolution). Previous work extensively described the spectrometer system. In this paper we present added functionality and updates to the commissioned spectrometer. The changes include developments in system timing, metadata, firmware and data products.

Bradford, Brian↗

FY23 Descent Systems Study Annual Review

Previous NASA studies of landing human-scale payloads on Mars have concluded that supersonic retropropulsion (SRP), or using multiple retrorocket engines beginning at supersonic descent conditions, is an enabling technology. DSS is partnering with the Aerosciences Evaluation and Test Capabilities (AETC) office to conduct a SRP test in the Langley Unitary Plan Wind Tunnel (UPWT) to quantify the SRP prediction capabilities of multiple computational fluid dynamics (CFD) solvers for a range of model configurations, thrust magnitudes, and tunnel conditions.

Propulsive Descent↗

Comparison of OVERFLOW Computational and Experimental Results for a Blunt Mars Entry Vehicle Concept During Supersonic Retropropulsion

Simulations of supersonic retropropulsion (SRP) flow over a Hypersonic Inflatable Aerodynamic Decelerator (HIAD) blunt-body vehicle were performed using the Overflow Computational Fluid Dynamics (CFD) solver. Simulation conditions and geometry were designed to match specific test runs in the Descent System Study (DSS) testing campaign. The relative accuracy of simulation predictions are assessed by direct comparison to experimental data. Computational predictions of the SRP flowfield and bow shock shape are compared to experimental schlieren images. Comparisons of the model surface pressure environment are presented for unsteady and static discrete tap data as well as time-averaged Pressure-Sensitive Paint (PSP) data.

Supersonic Retropropulsion↗

Simulating Secure Data Exchange and Storage for Urban Air Mobility Environments

In this paper I give some background on UAM, the need for security in UAM, as well as blockchain. Then I discuss how blockchain can facilitate a secure exchange and storage of data in a UAM environment, focusing on a simulation we developed to that simulates a UAM environment. Specifically, the simulation focuses on the negotiation between UAM operators, PSUs, and the DSS when two operators want to claim the same airspace. We discuss how this process, as well as the subsequent vehicle telemetry data, is captured in the blockchain.

UAM↗

Simulating Secure Data Exchange and Storage for Urban Air Mobility Environments

Urban Air Mobility (UAM) defines an environment for managing operations of vertical takeoff and landing (VTOL) and short takeoff and landing (STOL) vehicles in an urban environment. Within a UAM environment, UAM operators manage fleets of vehicles, relying on Providers of Services for UAM (PSUs) for managing flights in a region of airspace. Flight plan deconfliction is primarily performed by the Discovery and Synchronization Service (DSS), and the Federal Aviation Administration (FAA) maintains control over the UAM space via the FAA-Industry Exchange Protocol (FIDXP). UAM is a federated environment with many different entities owning and operating vehicles, PSUs, and other services. These entities often need to interoperate or access data generated by other organizations. This paper demonstrates the feasibility of using blockchain to facilitate a secure data exchange and storage for this flight information in a UAM environment. In particular, this paper is focused on flight plans and telemetry data. A blockchain network was developed with a set of smart contracts for managing relevant flight data. Hyperledger Fabric was chosen as it is performent, scalable, and allows organizations to reuse existing public key infrastructure (PKI) for identity management. A set of simulated UAM services were also developed. These services propose flight plans and negotiate with other UAM services for airspace access. All interactions between UAM services, as well as vehicle telemetry data, is recorded onto the blockchain. Vehicle telemetry data is generated by a vehicle flight simulation service. This paper successfully demonstrates the feasibility of using blockchain as a secure data exchange and storage mechanism in a UAM environment.

UAM↗

Comparison of OVERFLOW Computational and Experimental Results for a Blunt Mars Entry Vehicle Concept during Supersonic Retropropulsion

Simulations of unsteady supersonic retropropulsion (SRP) flow over a Hypersonic Inflatable Aerodynamic Decelerator (HIAD) blunt-body vehicle were performed using the OVERFLOW Computational Fluid Dynamics (CFD) solver. High-fidelity flow solver techniques, including Detached Eddy Simulation (DES) turbulence modeling and Adaptive Mesh Refinement (AMR), were employed to obtain improved realism in CFD predictions. Simulation conditions and geometry configurations were designed to match specific runs in the Descent System Study (DSS) wind tunnel testing (WTT) campaign. The accuracy of each simulation is assessed by direct comparison to experimental data. Comparisons of computational predictions of the SRP flowfield and bow shock shape to experimental schlieren imaging show reasonable prediction of mean shock shape, with approximately 10% similarity in shock standoff distance for selected conditions, as well as similarity in local, time-varying fluctuations of the shock-plume interaction. Comparisons of discrete measurements of surface pressure coefficient (Cp) indicate CFD accuracy within approximately 10% of the experiment across the majority of the model heatshield, with larger variations at some of the heatshield edge locations with stronger flow unsteadiness. Simulated unsteadiness of these chaotic flows, which were highly dynamic and multi-modal, was shown to be within 20-40% of experimentally-measured pressure standard deviation (SD) for the majority of the sampled locations.

Supersonic Retropropulsion↗

Comparison of OVERFLOW Computational and Experimental Results for a Blunt Mars Entry Vehicle Concept during Supersonic Retropropulsion

Simulations of unsteady supersonic retropropulsion (SRP) flow over a Hypersonic Inflatable Aerodynamic Decelerator (HIAD) blunt-body vehicle were performed using the OVERFLOW Computational Fluid Dynamics (CFD) solver. High-fidelity flow solver techniques, including Detached Eddy Simulation (DES) turbulence modeling and Adaptive Mesh Refinement (AMR), were employed to obtain improved realism in CFD predictions. Simulation conditions and geometry configurations were designed to match specific runs in the Descent System Study (DSS) wind tunnel testing (WTT) campaign. The accuracy of each simulation is assessed by direct comparison to experimental data. Comparisons of computational predictions of the SRP flowfield and bow shock shape to experimental schlieren imaging show reasonable prediction of mean shock shape, with approximately 10% similarity in shock standoff distance for selected conditions, as well as similarity in local, time-varying fluctuations of the shock-plume interaction. Comparisons of discrete measurements of surface pressure coefficient (Cp) indicate CFD accuracy within approximately 10% of the experiment across the majority of the model heatshield, with larger variations at some of the heatshield edge locations with stronger flow unsteadiness. Simulated unsteadiness of these chaotic flows, which were highly dynamic and multi-modal, was shown to be within 20-40% of experimentally-measured pressure standard deviation (SD) for the majority of the sampled locations.

Supersonic Retropropulsion↗

Evaluation of Machine Learning and Deep Learning Algorithms for Fire Prediction in Southeast Asia

Vegetation fires are prevalent in South/Southeast Asian countries, making fire prediction crucial due to their potential environmental, economic, and social impacts. Accurate predictions of fires facilitate timely interventions, helping to mitigate uncontrolled fires that can lead to biodiversity loss and air quality issues. In this study, we utilize VIIRS satellite-derived fire data alongside six machine learning and deep learning models—Simple Persistence, Multi-Layer Perceptron (MLP), Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), CNN-LSTM, and ConvLSTM—to determine the most effective fire prediction model, using Root Mean Square Error (RMSE) as the metric. Our results indicate that the CNN model is the most reliable in regions with spatial dependencies, such as Brunei, Indonesia, Malaysia, the Philippines, Timor-Leste, and Thailand. Conversely, the ConvLSTM model excels in countries with complex spatiotemporal dynamics like Laos, Myanmar, and Vietnam. The CNN-LSTM hybrid model also performed well in Cambodia, suggesting a need for a balanced approach in areas requiring both spatial and temporal feature extraction. Furthermore, simpler models like Persistence and MLP showed limitations in capturing dynamic patterns and temporal dependencies. Our findings highlight the importance of evaluating models before implementing any decision support systems (DSS) in fire management. By tailoring models to specific regional fire data, we can enhance prediction accuracy and responsiveness, ultimately improving fire risk management in Southeast Asia and beyond.

Deep learning↗

30-kW SEP Spacecraft as Secondary Payloads for Low-Cost Deep Space Science Missions

The Solar Array System contracts awarded by NASA's Space Technology Mission Directorate are developing solar arrays in the 30 kW to 50 kW power range (beginning of life at 1 AU) that have significantly higher specific powers (W/kg) and much smaller stowed volumes than conventional rigid-panel arrays. The successful development of these solar array technologies has the potential to enable new types of solar electric propulsion (SEP) vehicles and missions. This paper describes a 30-kW electric propulsion vehicle built into an EELV Secondary Payload Adapter (ESPA) ring. The system uses an ESPA ring as the primary structure and packages two 15-kW Megaflex solar array wings, two 14-kW Hall thrusters, a hydrazine Reaction Control Subsystem (RCS), 220 kg of xenon, 26 kg of hydrazine, and an avionics module that contains all of the rest of the spacecraft bus functions and the instrument suite. Direct-drive is used to maximize the propulsion subsystem efficiency and minimize the resulting waste heat and required radiator area. This is critical for packaging a high-power spacecraft into a very small volume. The fully-margined system dry mass would be approximately 1120 kg. This is not a small dry mass for a Discovery-class spacecraft, for example, the Dawn spacecraft dry mass was only about 750 kg. But the Dawn electric propulsion subsystem could process a maximum input power of 2.5 kW, and this spacecraft would process 28 kW, an increase of more than a factor of ten. With direct-drive the specific impulse would be limited to about 2,000 s assuming a nominal solar array output voltage of 300 V. The resulting spacecraft would have a beginning of life acceleration that is more than an order of magnitude greater than the Dawn spacecraft. Since the spacecraft would be built into an ESPA ring it could be launched as a secondary payload to a geosynchronous transfer orbit significantly reducing the launch costs for a planetary spacecraft. The SEP system would perform the escape from Earth and then the heliocentric transfer to the science target.

Dawn spacecraft↗