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NASA NTRS2020

An Overview of NASA’s Learn-to-Fly Technology Development

“Learn-to-Fly” (L2F) is an advanced technology development effort within the Modeling and Control for Agile Aircraft Development (MCAAD) group, a part of the NASA Transformative Aeronautics Concepts Program’s (TACP) Transformational Tools and Technologies (TTT) project. The goal of L2F is to develop technologies for enabling self-learning flight vehicles, using both ground- and flight-test approaches. Specifically, research has been conducted to demonstrate the potential to merge two enabling technologies, real-time aerodynamic modeling and adaptive flight controls, to substantially reduce the typical ground- and flight-testing time requirements for air vehicle design. This effort involved development of real-time, on-board algorithms to demonstrate key L2F technologies including aerodynamic modeling and control for an aircraft with minimal a priori knowledge. This research included both ground-based wind tunnel experiments utilizing modern design of experiments (DOE) techniques, as well as a flight test campaign, and was intended to rapidly advance these technologies and demonstrate key capabilities of the L2F approach. This paper presents the overview of the methods used to develop L2F technologies in NASA Langley Research Center’s 12-Foot Low Speed Tunnel, as well as in flight experiments. These methods include efficient wind tunnel data collection, real-time global nonlinear aerodynamic modeling in both the time and frequency domains, and the integration of the modeling techniques with adaptive flight controls, all of which were demonstrated using experimental validation.

Stephen E Riddick↗

NASA NTRS2020

Wind Tunnel Investigation of the Supersonic Stage Separation Aerodynamics of a Generic 0.0175-Scale Bimese Two-Stage-to-Orbit Reusable Launch Vehicle Configuration

A wind tunnel investigation was conducted of the supersonic stage separation aerodynamics of a generic two-stage-to-orbit bimese wingbody configuration in the NASA Langley Research Center Unitary Plan Wind Tunnel. Proximity and isolated model testing was conducted at Mach numbers of 2.3, 3.0, and 4.5 and a unit Reynolds number of 2.0 million per foot using 0.0175-scale models of the Langley Glide-Back Booster concept designated as the orbiter and booster in belly-to-belly and back-to-belly configurations. Longitudinal forces and moments were obtained on both models and surface static pressure measurements were obtained on the orbiter model at 328 relative proximity locations and at relative angles of attack of 0 degrees and 5 degrees. The test results supported a larger effort to develop and validate experimental and computational tools applicable to the design and simulation of stage separation and abort procedures for reusable launch vehicles composed of multiple bodies, including winged bodies. An initial proof-of-concept experiment featuring low-cost uninstrumented models was conducted to verify an emerging automated model control system and new support system hardware, and to identify potential model and support system blockage and unsteady aerodynamics/model dynamics prior to committing to higher-fidelity instrumented models. This investigation led to upgrades in the facility stage separation hardware, calibration and testing techniques and capabilities, and data analysis and documentation methodologies that have been extended to the more recent NASA Constellation and Space Launch System crew and cargo launch vehicle programs. A virtual diagnostics interface methodology was used to facilitate the design of the stage separation support hardware, to position the models in the test section, and to define the experimental test space. Advances in the facility automated model positioning system established a foundation for the development of a continuous-sweep data acquisition technique that is responsible for significant productivity improvements to the current NASA Space Launch System test program. The automated model positioning capability was leveraged to conduct a companion statistically-designed stage separation experiment requiring randomization of the relative proximity positions of the orbiter and booster models. The respective zones of influence and interference effects of the orbiter and booster were identified from three-dimensional scatter plots, contour and influence maps, and two-dimensional plotting methods. The highly-nonlinear, shock-dominated aerodynamic characteristics of the orbiter and booster in the Unitary Plan Wind Tunnel exhibited good agreement with independent test data obtained in a NASA Marshall Space Flight Center wind tunnel and with computational fluid dynamics predictions using a compressible, three-dimensional flow solver and an inviscid, unstructured Cartesian method.

Erickson, Gary E.↗

NASA NTRSDate not supplied

TPSAS-NF1676L-14336-DND

Problem Statement: Develop robust CFD-based methods for rapid design and analysis of supersonic cruise aircraft that are highly efficient, and have a low sonic boom. What is our approach? - Advanced Efficient Analysis / Design Methods - Develop computational algorithms and techniques for rapid high fidelity analysis of supersonic fluid flow phenomena, which will also contribute to multi-fidelity analysis / design tools. - Experimental Validation - Validate concepts for design optimization of both high aerodynamic efficiency and low sonic boom.

Linda Bangert↗

NASA NTRS2020

High Contrast Integral Field Spectrograph (HCIFS): Multi-Spectral Wavefront Control and Reduced-Dimensional System Identification

Any High-contrast imaging instrument in a future large ground-based or space-based telescopes will include an integral field spectrograph (IFS) for measuring broadband starlight residuals and characterizing the exoplanet's atmospheric spectrum. In this paper, we report the development of a high-contrast integral field spectrograph (HCIFS) at Princeton University and demonstrate its application in multi-spectral wavefront control. Moreover, we propose and experimentally validate a new reduced-dimensional system identification algorithm for an IFS imaging system, which improves the system's wavefront control speed, contrast and computational and data storage efficiency.

He Sun↗

NASA NTRSDate not supplied

Characterization of CO 4th Positive Radiation in CO2-Ar Mixtures

This paper presents measurements and simulations of CO 4th Positive spectra obtained in NASA Ames Research Center's Electric Arc Shock Tube (EAST) and CentraleSupelec's Plasma Torch. The experiments were aimed at measuring optically thin emission for the main band features of CO 4th Positive by using test gas mixtures of CO2 and Ar. By using mixtures of CO2 and Ar, the temperature of the flow (and consequently black-body curve) is increased compared to using pure CO2 (or CO2 / N2 mixtures). This temperature increase allows for emission spectroscopy of features that would nominally be black-body limited for conditions relevant to Mars entry. The CO 4th Positive system is the focus of this study as it accounts for a large percentage of the emitted radiation for Martian entry, and also due to the difficulties of obtaining experimental validation data due to the emission appearing in the Vacuum Ultraviolet (VUV) spectral range. The focus of this paper is to provide a comprehensive comparison between the EAST and plasma torch data along with various CO 4th Positive databases available in the literature. Previously reported VUV CO2 / N2 EAST data required a larger temperature than would be predicted based upon equilibrium shock relations. The need for the temperature increase implies that the EAST experiment did not fully equilibrate. Thus, it is presumed that the EAST data did not obtain an equilibrium condition. The plasma torch data, on the other hand, is very consistent with equilibrium assumptions. Thus, the equilibrium data obtained in the plasma torch is utilized to construct the CO 4th Positive emission model, which is then applied to the EAST data with a non-equilibrium interpretation.

A. M. Brandis↗

NASA NTRSDate not supplied

Design of a Crossflow Attenuated Natural Laminar Flow Flight Test Article

This abstract includes preliminary information on the computational design and analysis of a flight test article. The flight test aims to experimentally validate the new Crossflow Attenuated Natural Laminar Flow (CATNLF) design method in a flight environment. The CATNLF design method uses geometry shaping to produce specific pressure distributions that enable laminar flow on vehicle components with high sweep and high Reynolds numbers by attenuating the crossflow growth that typically leads to premature transition on such components. The flight test article design is scheduled to be completed at the end of 2019, with model fabrication beginning in early 2020.Design results presented in this abstract are representative of the final test article. The final paper will be updated to include the finalized test article geometry and analysis.

Michelle N. Lynde↗

NASA NTRSDate not supplied

Design of a Crossflow Attenuated Natural Laminar Flow Flight Test Article

A natural laminar flow test article has been designed and analyzed for a flight test at the NASA Armstrong Flight Research Center using the F-15 aircraft with Centerline Instrument Pylon (CLIP) testbed. The flight test aims to experimentally validate the new Crossflow Attenuated Natural Laminar Flow (CATNLF) design method in a flight environment. The CATNLF design method uses geometry shaping to produce specific pressure distributions that enable laminar flow on vehicle components with high sweep and high Reynolds numbers by attenuating the crossflow growth that typically leads to premature transition on such components. The CATNLF test article, which will be mounted vertically below the F-15 for flight testing, is designed to be representative of a transonic transport wing and accounts for transition mechanisms due to crossflow, Tollmien-Schlichting, and attachment line transition instabilities. The test article is predicted to support 53% surface area of laminar flow on the suction-side at the design point and maintains significant laminar flow extents at near-cruise, off-design conditions. The design was performed, flight matrix selected, and instrumentation chosen with two primary test goals in mind: to confirm the effectiveness of the CATNLF method in attenuating crossflow growth on a representative transonic transport wing, and to investigate surface requirements needed for laminar flow applications.

Michelle N. Lynde↗

NASA NTRSDate not supplied

CMC Research at NASA Glenn in 2021: Recent Progress and Plans

As part of NASA’s Aeronautics research, Glenn Research Center has developed SiC/SiC Ceramic Matrix Composites for 2700°F turbine engine applications in the next generation of ultra-efficient aircraft. In this presentation, the development and characterization of constituents and fabrication processes that enabled this advancement will be reviewed, and the resulting improvements in CMC mechanical properties and durability will be summarized. Progress toward the development and experimental validation of analytical models predicting the effects of engine operating conditions on the durability of Ceramic Matrix Composites with Environmental Barrier Coatings will be summarized. Results from current collaborative research with industry, universities and other government agencies will be reviewed. Research plans for 2021 and opportunities for future collaborations with NASA will also be summarized.

Ceramic Matrix Composites↗

NASA NTRS2024

Test and Analysis of the 8-foot Diameter Cylindrical Sandwich Composite Test Article CTA8.2B: As part of the NASA Engineering and Safety Center Shell Buckling Knockdown Factor Project

The buckling response of thin-walled cylindrical structures have long been shown to be sensitive to various imperfections. That is, imperfections related to load introduction, boundary conditions, material property variation, and geometric deviations can all contribute to experimentally obtained buckling loads being lower than the buckling loads predicted for perfect representations of the same thin-walled cylindrical structure. To account for the influence of geometry-based imperfections of a thin-walled cylindrical structure on buckling response, a design factor (also known as a buckling knockdown factor) is used during the design phase. Guidelines for buckling knockdown factors are readily available in NASA SP-8007, Buckling of Thin Walled Circular Cylinders, which was updated in 2020. Prior to this recent update, NASA SP-8007 had not been updated since 1969, and since that time, computational analysis, experimental testing, and manufacturing methods have significantly improved. The NASA Engineering and Safety Center (NESC) Shell Buckling Knockdown Factor Project (SBKF, NESC Assessment 07-010-E) had the goal of developing buckling design recommendations for select classes of metallic and composite launch-vehicle structures [3]. Specifically, the test and analysis results from the fourth SBKF composite test article SBKF-P3-CYL-CTA8.2B, which is referred to as CTA8.2B, are described in this paper. This test was the fourth in a series of four tests on sandwich composite cylinders that will be used to experimentally validate analysis methods, which in turn can be used to develop new analysis-based shell buckling design guidelines for typical sandwich composite launch vehicle cylindrical structures. Publications describing previous test validation with analysis are available in Refs. CTA8.2B was designed to occupy one corner of the design space with approximately equal bending stiffnesses in the axial and transverse directions and have a larger ratio of radius to effective shell thickness. Each test article had a unique design and was designed to occupy a specific region of the design space. CTA8.2B was an 8-foot diameter honeycomb-core sandwich cylinder that was fabricated and tested at the NASA Marshall Space Flight Center (MSFC). The primary objectives of this test were to interrogate the structural capability of a composite test article, and to verify the test article design and analysis approach for cylinders subjected to axial compression and combined axial and bending loads. First, descriptions of the test article design and test are given in Section 2.0, and modeling and analysis methods used in support of the test article design and testing activities are described briefly in Section 3.0. Then, select test results are presented and compared to predicted results in Section 4.0, and concluding remarks are presented in Section 5.0. Finally, drawings of CTA8.2B and references used to support the test and analysis are provided in the Appendix.

Nonlinear analysis↗

NASA NTRS2022

Buckling Test and Analysis of the 8-Foot-Diameter Sandwich Composite Cylinder Test Article CTA8.2 as Part of the Shell Buckling Knockdown Factor Project: Test Dates 5-7 December 2017

It is well known that the buckling response of thin shell structures can be sensitive to small imperfections in the geometry and loading. The NASA Engineering and Safety Center (NESC) Shell Buckling Knockdown Factor Project (SBKF) has the goal of developing buckling design recommendations for select classes of metallic and composite shells. Part of completed SBKF work is described in this report. In particular, the test and analysis results from the second SBKF composite test article, CTA8.2, are described. This test was the second in a series of tests on sandwich composite cylinders that can be used to experimentally validate analysis methods, which in turn can be used to develop analysis-based shell buckling design guidelines for sandwich composite launch-vehicle cylindrical structures. CTA8.2 was an 8-foot diameter honeycomb-core sandwich cylinder that was fabricated and tested at the Marshall Space Flight Center (MSFC). The primary objectives of this test were to interrogate the structural capability of the composite test article, and to verify the test-article design and analysis approach for cylinders subjected to axial compression loads. This report contains the descriptions of the test-article design, fabrication, and test. The pre-test modeling and analysis methods, and corresponding results used in support of the test-article design and test planning, are also described. Additional post-test modeling and analysis efforts and results follow. Selected test results are compared to pre-test predictions and post-test analyses.

Adam Przekop↗

NASA NTRS2022

Buckling Test and Analysis of the 8-foot-diameter Sandwich Composite Cylinder Test Article CTA8.3 as Part of the Shell Buckling Knockdown Factor Project: Test Dates 16~19 December 2019

This report describes work that is part of SBKF-the test and analysis results from the third SBKF cylindrical sandwich composite test article, which was designated SBKF-P3-CYL-CTA8.3. This test was the third in a series of tests on sandwich composite cylinders that can be used to experimentally validate analysis methods, which in turn can be used to develop analysis-based shell buckling design guidelines for sandwich composite launch-vehicle cylindrical structures. The primary objectives of this test were to interrogate the structural capability of the composite test article, and to verify the test-article design and analysis approach for cylinders subjected to axial compression and combined compression and bending loads.

Sandwich composite cylinder↗

NASA NTRSDate not supplied

Shock-Layer Radiation Insights Available Through Flowfield Property Binning

This paper introduces a method for assessing similarity between available shock-layer radiation measurements and the radiative heating to a vehicle of interest. This method will be referred to as the flowfield property binning (FPB) approach. The challenge in developing this approach is that radiometer measurements from a surface normal line of sight, observed radiation measurements of the entire shock-layer from a distance, or measured shock-tube nonequilibrium profiles are notably different geometrically than the radiative flux to a vehicle surface. Therefore, the relative contributions of various regions of the shock-layer to the measurement, and how these relative contributions compare with the radiative heating to a vehicle of interest, are unclear. By tracking the radiation contribution from each flowfield location, and then grouping this contribution based on two local flowfield properties, these geometric differences are removed. This provide a two dimensional group, or bin, distribution that represents the radiation environment in the same format for various types of radiation simulations, such as observed radiation or radiative flux to a vehicle surface. In the limits of optically-thin radiation transport and thermochemical equilibrium flow, the choice of pressure and temperature as the binning flowfield properties is shown to provide a bin distribution that uniquely defines the radiation simulation. This concept is found to be sufficient for establishing similarity between two cases even when the optically-thin radiation transport and thermochemical equilibrium assumptions are not satisfied. A simple metric of comparison between bin distributions from different cases is provided by the histogram intersection algorithm. This algorithm results in a histogram intersection factor (H) between 0 and 1, which represents the fraction of the radiation that is similar between the two cases. Therefore, if H evaluated between bin distributions for two completely different radiation problems is near 1, then they represent essentially the same radiation problem. This means that they depend on the same weighting of various radiation modeling parameters evaluated at the same pressure and temperature. If one of these cases agrees well with a radiation measurement, then the matching bin distributions provide justification for applying this experimental validation to the other case. Even for H values as low as 0.2, the measurement case could be considered relevant if there are no other useful measurements. This approach allows observed radiation measurements to directly inform radiative heating simulations, which allows NASA’s past and future investments in observed radiation measurements to directly inform the radiative heating uncertainty or margins for future vehicle design. This FPB approach is also used to determine shock-tube conditions for informing backshell radiative heating simulations, where the normal shock velocity and Lagrangian time from the shock is used for the binning variables instead of pressure and temperature.

Shock Layer Radiation↗

NASA NTRSDate not supplied

BRAINSTACK – A Platform for Artificial Intelligence & Machine Learning Collaborative Experiments on a Nano-Satellite

As space missions continue to become more ambitious, complex, and distant to Earth, the need for advanced on-board intelligent decision making to guide everything from mission operations to fault detection and recovery has become a major front of space research. While the prevalence of research on such Artificial Intelligence / Machine Learning (AI/ML) modules has exploded, the capacity to experimentally validate such modules in space in a rapid and inexpensive format has not. To this end, the Nano Orbital Workshop (NOW) group at NASA Ames Research Center has been at the forefront of performing initial flight evaluation tests of ‘commercially’ available AI/ML computational platforms via the TechEdSat (TES-n) flight series as part of what is programmatically referred to as the BRAINSTACK. BRAINSTACK will provide an orbital AI/ML evaluation laboratory where computational experiments are pre-loaded into memory prior to launch, and then executed as desired during the mission, with results reported back and program tweaks or new data sets uploaded as needed. Processors selected as part of the BRAINSTACK are of ideal size, packaging, and power consumption for easy integration into a cube satellite structure. These experiments have included the evaluation of small, high-performance GPUs and more recently, neuromorphic processors in LEO operations. Neuromorphic processors are of particular interest due to their superior computational power efficiency over GPUs. The first TES-n flight test of an Intel first-generation Loihi neuromorphic processor launched on January 13, 2022 and continues to operate in orbit despite almost no space environment modifications. The Intel Loihi Gen-1 is characterized by a 14nm 128-core Spiking Neural Network (SNN) able to support on-chip training. This experiment utilized a Loihi packaged in the ‘Kapoho Bay’ USB module, providing a relatively straight-forward interface to the bus avionics system. The Kapoho Bay was in turn managed by a host Intel Pentium single-board computer to handle scheduling of the AI/ML application payloads, and communications with the satellite vehicle manager. The recently released Intel Loihi Gen-2, able to support integer-valued spike payloads and produced using 7nm process, will form part of the basis of the evolving BRAINSTACK in the upcoming three TES-n/NOW flights. Additionally, it is planned to measure the radiation environment these processors experience to understand any degradation or computational artifacts caused by long term space radiation exposure on these novel architectures. This evolving flexible and collaborative environment involving various research teams across NASA and other organizations is intended to be a convenient orbital test platform from which many anticipated future space AI/ML applications may be initially tested.

Artificial Intelligence↗

NASA NTRSDate not supplied

BRAINSTACK – A Platform for Artificial Intelligence & Machine Learning Collaborative Experiments on a Nano-Satellite

Artificial Intelligence↗

NASA NTRS2023

Development of a Computational Fluid Dynamics Model for a High-Speed Centrifugal Compressor

Computational fluid dynamics (CFD) has become widely used in the design and analysis of turbomachinery components such as centrifugal compressors. However, CFD is only a limited representation of experimental cases and struggles to model complex flows or can lack small model details to increase computation speed. To make advancements in compressor technology, designers need tools like CFD that can help them predict flow behavior in new designs. The High Efficiency Centrifugal Compressor (HECC) was designed by United Technologies Research Center (UTRC) for NASA to investigate the difficulties behind improving centrifugal compressor technology and to provide an open case to the turbomachinery research community. CFD analysis was completed by UTRC to aid in the design process. The pre-test study significantly overpredicted the compressor’s performance, and while post-test analysis was more representative, its results have yet to be publicly available. CFD technology has also since improved in recent years. In this study, a high-fidelity computational model for the vaneless configuration of HECC operating at its design point was developed and compared to an equivalent experimental case. This model incorporated GPU versions of mesh generation and solver codes from AeroDynamic Solutions, Inc. The development of such a model is significant since there has yet to be a published numerical simulation of HECC’s vaneless configuration. Additionally, the use of GPU codes decreases computation times for the model, which has allowed for the inclusion of impeller blade fillets. Initial results showed a general overprediction of compressor performance by the model. Predictions were more accurate for the impeller compared to predictions for the full compressor stage. Spanwise analyses showed that the model tended to follow flow behavior patterns exhibited in the experiment. Beyond this study, this model will be iterated upon and experimentally validated to further examine HECC performance.

centrifugal compressor↗

NASA NTRSDate not supplied

Design of Electrostatic Dust Lofting Suborbital Flight Experiment Examining Photoionization under Lunar Gravity

Dust on the lunar surface electrostatically charges due to the plasma environment surrounding the Moon, causing grains to become lofted and adhere to nearby surfaces including landers and astronauts. Studying the behaviors of these charged particles in the lunar environment is essential to plan around the deleterious effects of dust to future Moon missions. Models attempt to predict the amount of dust loading that can be expected in many of these scenarios, but they require experimental validation to be predictive. This physics cannot be fully studied on Earth due to the six times larger gravitational force obscuring the electrostatic interactions, so it is necessary to run experiments in a more relevant environment, including vacuum and near-lunar gravitational effects. An experiment has been designed to fly on the Lunar Gravity Acceleration (LGA) mission aboard the Blue Origin New Shepard suborbital rocket. This experiment will perform photoionization charging of lunar regolith simulant grains under the illumination of an ultraviolet (UV) source. As a result, the charged grains will then electrostatically repel one another and loft in the reduced gravity environment; their trajectories will be imaged via a high-speed camera. Preliminary laboratory results influencing the design of this experiment will be presented, including characterization of several UV sources, measurements of photoionization currents under various vacuum conditions, and examination of lunar simulant dust lofting under terrestrial gravity. Results from this flight will be compared with ground-based testing and the laboratory results outlined above to examine the dependence on gravity and will be fed into the dust charging and lofting models currently under development.

electrostatics↗

NASA NTRSDate not supplied

Microstructure Controlled Multi-Layer Porous Material Liner Tested On The Advanced Noise Control Fan

A novel concept of multilayer micro structurally controlled noise mitigation porous material was developed and experimentally validated in the laboratory by normal incidence impedance test. Extensive parametric studies were made to understand various parameters that influence acoustic absorption and transmission loss based on the test specimen size, particle size, porosity, pore size, and its distribution through the thickness. The results were reported in many publications. This work was focused on applying the concept and assessing the validity of the technology to aircraft turbomachine engines. The NASA Glenn Research Center’s Advanced Noise Control Fan (ANCF) low-speed test rig was selected. The liner insert required a 4-ft internal diameter cylinder with a 2-inch thick and 9-inch axial length. The liner was fabricated in eight segments and assembled in an aluminum test rig. The liner was tested for both tonal and broadband noise at the Notre Dame Turbomachinery Lab White Field test facility, where the ANCF is located. The study concludes that: Microstructurally controlled porous material is very effective in dissipating the sound energy; the liner is effective for tonal noise (2 to 13 dB reduction in noise levels) that constitutes the major part of the overall fan noise, especially the blade passing frequency which is generally the dominating component; Also, the liner is effective for broadband noise with reductions in sound pressure level of about 3 dB for the shaft order greater than 20. The proposed two-layer liner model demonstrated the validity of the concept. More studies are required to optimize the design.

Liner↗

NASA NTRS2023

BRAINSTACK – A Platform for Artificial Intelligence & Machine Learning Collaborative Experiments on a Nano-Satellite

As the space economy continues to expand through increasingly easy access to advanced and inexpensive technology, space missions themselves have become more ambitious with exploration targets growing ever distant while simultaneously requiring larger guidance and communication budgets. These conflicting desires of distance and control drive the need for advanced on-board intelligent decision making to reduce communication and control limitations by automating as many mission functions as possible in-situ. While the amount of research on such Artificial Intelligence and Machine Learning (AI/ML) software modules has grown exponentially, the capacity to experimentally validate such software modules in space in a rapid and inexpensive format has not. To this end, the Nano Orbital Workshop (NOW) group at NASA Ames Research Center has been at the forefront of performing initial flight evaluation tests of ‘commercially’ available bleeding-edge computational platforms via what is programmatically referred to as the BrainStack on the TechEdSat (TES-n) flight series. This on-orbit computational platform provides an evaluation laboratory where advanced software experiments are pre-loaded into memory prior to launch, then executed as payloads during mission operations with results reported back and program tweaks or new training sets uploaded as needed. Processors selected as part of the BrainStack are of ideal size, packaging, and power consumption for easy integration into a cube satellite structure. These experiments have included the evaluation of small, high-performance GPUs and, more recently, neuromorphic processors, in LEO operations. Neuromorphic processors are of particular interest due to their superior power efficiency over GPUs in intelligent automation applications. The first TES-n flight test of an Intel first-generation Loihi neuromorphic processor launched on TES-13, January 13, 2022, and continues to operate in orbit despite no significant modifications to harden the processor against the space environment. The Intel Loihi Gen-1 on TES-13 is characterized by a 14nm 128-core Spiking Neural Network (SNN) able to support on-chip training. The processor is packaged in the Kapoho Bay USB module, providing a relatively straight-forward interface to the bus avionics system. The Kapoho Bay was in turn managed by an Intel Pentium single-board computer to handle scheduling of the software application payloads and communications with the satellite’s primary computer. The recently released Intel Loihi Gen-2, able to support integer-valued spike payloads and produced using 7nm process, will form part of the continually evolving BrainStack in the upcoming three TES-n/NOW flights. The Kapoho Point unit will incorporate eight Loihi-2 processors, enabling neural networks of up to one million neurons and one billion synapsis. Additionally, it is planned to measure the radiation environment these processors experience to understand any degradation or computational artifacts caused by long term space radiation exposure on these novel architectures. This evolving flexible and collaborative environment involving various research teams across NASA and other organizations is intended to be a convenient orbital test platform from which many anticipated future space automation applications may be initially tested.

Artificial Intelligence↗