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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Safe and Precise Landing Integrated Capabilities Evolution (SPLICE)

NASA needs for entry, descent, and landing call for improved Precision Landing and Hazard Avoidance (PL&HA) technologies. SPLICE continues to develop, mature, demonstrate, and infuse these technologies as a portfolio. SPLICE will achieve TRL 5 on a hazard detection lidar mapping sensor and TRL 6 on two key flight software libraries for advanced guidance and hazard detection. A High-Performance Space Computing surrogate multiprocessor (ARM A53) integrates sensors and FSW. This portfolio of technologies may be infused separately or fully integrated.

Guidance Navigation and Control↗
NASA NTRSDate not supplied

Exercising Prediction Validation Methods for Analysis of Quiet Supersonic Overflight

En route noise certification procedures for quiet supersonic aircraft are in development under the International Civil Aviation Organization for a proposed standard that could enable civil supersonic overland flight. While these quiet supersonic aircraft do not exist yet, methods are being developed and evaluated using existing N-wave empirical datasets and low-boom simulation datasets. One potential aspect of future certification methods is the ability to use a validated prediction model to predict the certification noise level under reference day weather conditions. Methods to validate predictions, such as the two-sample t-test, Fisher’s combined probability test, two-sample Kolmogorov-Smirnov test, and equivalence testing, have been exercised and modified for this application. While some methods compare mean values, others compare values across the distribution, and a combination of methods can be used. The methods were applied to a subset of an N-wave dataset to demonstrate the applicability and identify potential areas for improvement. Atmospheric turbulence variability was included as a factor in these analyses through KZKFourier propagation simulations with parameters matching actual flights and weather conditions. Results are presented for six noise metrics (PL, ASEL, BSEL, DSEL, ESEL, and ISBAP), and plans to expand the analyses are discussed.

sonic boom↗
NASA NTRS2023

A System to Provide Deterministic Flight Software Operation and Maximize Multicore Processing Performance: The Safe and Precise Landing – Integrated Capabilities Evolution (SPLICE) Datapath

A method and design are described for a system that processes multiple data streams, utilizing a multicore asymmetric processing architecture, that eliminates data interrupts to the application processors. The design supports a deterministic environment for flight software in NASA’s Safe and Precise Landing – Integrated Capabilities Evolution (SPLICE) project. The SPLICE project develops sensor, algorithm, and compute technologies for Precision Landing and Hazard Avoidance (PL&HA) capabilities. The compute technology for SPLICE is the Descent and Landing Computer (DLC). The DLC hosts several SPLICE algorithms with high computational resource requirements that must be executed in a real-time and deterministic manner. The software runs on a custom Single Board Computer (SBC), with a Xilinx Ultrascale+ Multiprocessor System-on-a-Chip (MPSoC). Input data for the flight software is from a variety of sensors, unique with respect to data rate and packet size. A data path between the SPLICE sensors and algorithms is designed to efficiently deliver this data to the flight software using the MPSoC asymmetric processing cores and Field Programmable Gate Array (FPGA) fabric. This is implemented in a manner that isolates the application processors running the flight software from interrupts associated with the input data. By leveraging real-time processors on the MPSoC, and a structure with the appropriate interfaces in the shared memory on the SBC, the flight software can use the full set of application processors. The available utilization for each processor in this set is also maximized for the SPLICE applications, providing a sufficiently deterministic execution environment without the cost and overhead of a real-time operating system.

David K. Rutishauser↗
NASA NTRSDate not supplied

Efficient and Accurate Terrain Integration & Application to Modeling and Simulation of Planetary Landing Systems

As planetary spacecraft landing system complexity increases, pre-flight performance assessments include correspondingly more detailed and complex models that represent the various environmental elements and vehicle subsystems. Specifically, the relevance and criticality of planetary terrain modeling in the context of precision landing and hazard avoidance (PL&HA) has become evident as both commercial and national agencies return to the Lunar surface and beyond.

Terrain↗
NASA NTRSDate not supplied

Space Technology Mission Directorate Game Changing Development Program

SPLICE project annual program review presentation. SPLICE Precision Landing and Hazard Avoidance (PL&HA) technologies will improve landing precision by an order of magnitude and enable high-resolution real-time 3-D mapping for hazard detection and avoidance during descent.

Guidance Navigation and Control↗
NASA NTRS2025

Uncertainty Quantification for Empirical X-59 Sonic Boom Loudness Levels

Estimates of the total uncertainty for empirically determined loudness levels are documented when GRS (Ground Recording System) noise monitors are used to record X 59 sonic boom waveforms. The total uncertainty is characterized by combining nine different sources of uncertainty that may affect the apparent gain of the measurement chain. These uncertainty estimates are presented as expected measurement error relative to the true loudness level, and separate error estimates are provided for eight different noise metrics in which NASA has interest. The behavior of the Perceived Level (PL) metric is studied within the report body, while the total uncertainties for the seven other noise metrics are summarized in appendices for brevity. The effects of four sources of uncertainty are estimated simply from information found on hardware specification sheets provided by the manufacturer. However, mock acoustic recordings are created to estimate the effects of other sources because those effects are expected to induce spectral coloration, so they may vary with noise metric type and sound level. These sources are not well modeled by simple gain adjustments. Importantly, measurement error is computable when processing mock recordings since the true levels are knowable, which is not the case when processing data recorded in the field. Specifically, the true levels are knowable because the components of the mock recordings are separable – e.g., loudness levels of booms can be computed with or without superimposed background noise. Mock acoustic recordings also have the benefit of allowing analysis of sonic booms from vehicles that are not yet flying, like the X-59, since the mock recordings are created by combining vehicle-specific predicted waveforms with other audio sources. The estimates of total measurement error are documented as a function of the signal-to-noise ratio (SNR) of the loudness level, where the corrected SNR is computed while accounting for the effects of the method that is used to correct for background noise contamination when computing the noise metric values. The corrected SNR calculations used here can be applied to both mock recordings and in-field measurements, so the uncertainty of in-field recordings can be found using pre-computed lookup tables that identify the relationship between metric type, corrected SNR, and the expected measurement error.

Sonic Boom↗
NASA NTRS2003

Flight Test of an Intelligent Flight-Control System

The F-15 Advanced Controls Technology for Integrated Vehicles (ACTIVE) airplane (see figure) was the test bed for a flight test of an intelligent flight control system (IFCS). This IFCS utilizes a neural network to determine critical stability and control derivatives for a control law, the real-time gains of which are computed by an algorithm that solves the Riccati equation. These derivatives are also used to identify the parameters of a dynamic model of the airplane. The model is used in a model-following portion of the control law, in order to provide specific vehicle handling characteristics. The flight test of the IFCS marks the initiation of the Intelligent Flight Control System Advanced Concept Program (IFCS ACP), which is a collaboration between NASA and Boeing Phantom Works. The goals of the IFCS ACP are to (1) develop the concept of a flight-control system that uses neural-network technology to identify aircraft characteristics to provide optimal aircraft performance, (2) develop a self-training neural network to update estimates of aircraft properties in flight, and (3) demonstrate the aforementioned concepts on the F-15 ACTIVE airplane in flight. The activities of the initial IFCS ACP were divided into three Phases, each devoted to the attainment of a different objective. The objective of Phase I was to develop a pre-trained neural network to store and recall the wind-tunnel-based stability and control derivatives of the vehicle. The objective of Phase II was to develop a neural network that can learn how to adjust the stability and control derivatives to account for failures or modeling deficiencies. The objective of Phase III was to develop a flight control system that uses the neural network outputs as a basis for controlling the aircraft. The flight test of the IFCS was performed in stages. In the first stage, the Phase I version of the pre-trained neural network was flown in a passive mode. The neural network software was running using flight data inputs with the outputs provided to instrumentation only. The IFCS was not used to control the airplane. In another stage of the flight test, the Phase I pre-trained neural network was integrated into a Phase III version of the flight control system. The Phase I pretrained neural network provided realtime stability and control derivatives to a Phase III controller that was based on a stochastic optimal feedforward and feedback technique (SOFFT). This combined Phase I/III system was operated together with the research flight-control system (RFCS) of the F-15 ACTIVE during the flight test. The RFCS enables the pilot to switch quickly from the experimental- research flight mode back to the safe conventional mode. These initial IFCS ACP flight tests were completed in April 1999. The Phase I/III flight test milestone was to demonstrate, across a range of subsonic and supersonic flight conditions, that the pre-trained neural network could be used to supply real-time aerodynamic stability and control derivatives to the closed-loop optimal SOFFT flight controller. Additional objectives attained in the flight test included (1) flight qualification of a neural-network-based control system; (2) the use of a combined neural-network/closed-loop optimal flight-control system to obtain level-one handling qualities; and (3) demonstration, through variation of control gains, that different handling qualities can be achieved by setting new target parameters. In addition, data for the Phase-II (on-line-learning) neural network were collected, during the use of stacked-frequency- sweep excitation, for post-flight analysis. Initial analysis of these data showed the potential for future flight tests that will incorporate the real-time identification and on-line learning aspects of the IFCS.

Davidson, Ron↗
NASA NTRS2011

The Atacama Cosmology Telescope: ACT-CL J0102-4215 "El Gordo," a Massive Merging Cluster at Redshift 0.87

We present a detailed analysis from new multi-wavelength observations of the exceptional galaxy cluster ACT-CL J0102-4915, likely the most massive, hottest, most X-ray luminous and brightest Sunyaev-Zel'dovich (SZ) effect cluster known at redshifts greater than 0.6. The Atacama Cosmology Telescope (ACT) collaboration discovered ACT-CL J0102-4915 as the most significant Sunyaev-Zeldovich (SZ) decrement in a sky survey area of 755 square degrees. Our VLT/FORS2 spectra of 89 member galaxies yield a cluster redshift, z = 0.870, and velocity dispersion, sigma(gal) +/- 1321 106 km s-1. Our Chandra observations reveal a hot and X-ray luminous system with an integrated temperature of T(X) = 14:5 +/- 0:1 keV and 0.5 2.0 keV band luminosity of L(X) = (2:19 0:11) 1045 h(exp -2)70erg s-1. We obtain several statistically consistent cluster mass estimates; using empirical mass scaling relations with velocity dispersion, X-ray Y(X) , and integrated SZ distortion, we estimate a cluster mass of M(200) = (2:16 +/- 0:32) 10(exp 15) h(exp-1) 70M compared to the Sun. We constrain the stellar content of the cluster to be less than 1% of the total mass, using Spitzer IRAC and optical imaging. The Chandra and VLT/FORS2 optical data also reveal that ACT-CL J0102-4915 is undergoing a major merger between components with a mass ratio of approximately 2 to 1. The X-ray data show significant temperature variations from a low of 6:6 +/- 0:7 keV at the merging low-entropy, high-metallicity, cool core to a high of 22 +/- 6 keV. We also see a wake in the X-ray surface brightness and deprojected gas density caused by the passage of one cluster through the other from which we estimate a merger speed of around 1300 km s(exp -1) for an assumed merger timescale of 1 Gyr. ACTCL J0102-4915 is possibly a high-redshift analog of the famous Bullet Cluster. Such a massive cluster at this redshift is rare, although consistent with the standard CDM cosmology in the lower part of its allowed mass range. Massive, high-redshift mergers like ACT-CL J0102-4915 are unlikely to be reproduced in the current generation of numerical N-body cosmological simulations.

Menanteau, Felipe↗
NASA NTRS2006

The Effect of Air Density on Atmospheric Electric Fields Required for Lightning Initiation from a Long Airborne Object

The purpose of the work was to determine minimum atmospheric electric fields required for lightning initiation from an airborne vehicle at various altitudes up to 10 km. The problem was reduced to the determination of a condition for initiation of a viable positive leader from a conductive object in an ambient electric field. It was shown that, depending on air density and shape and dimensions of the object, critical atmospheric fields are governed by the condition for leader viability or that for corona onset. To establish quantitative criteria for reduced air densities, available observations of spark discharges in long laboratory gaps were analyzed, the effect of air density on leader velocity was discussed and evolution in time of the properties of plasma in the leader channel was numerically simulated. The results obtained were used to evaluate the effect of pressure on the quantitative relationships between the potential difference near the leader tip, leader current and its velocity; based on these relationships, criteria for steady development of a leader were determined for various air pressures. Atmospheric electric fields required for lightning initiation from rods and ellipsoidal objects of various dimensions were calculated at different air densities. It was shown that there is no simple way to extend critical ambient fields obtained for some given objects and pressures to other objects and pressures.

Bazelyan, E. M.↗
NASA NTRS2012

JPL Innovation Foundry

NASA supports the community of mission principal investigators by helping them ideate, mature, and propose concepts for new missions. As NASA's Federally Funded Research and Development Center (FFRDC), JPL is a primary resource for providing this service. The environmental context for the formulation lifecycle evolves continuously. Contemporary trends include: more competitors; more-complex mission ideas; scarcer formulation resources; and higher standards for technical evaluation. Derived requirements for formulation support include: stable, clear, reliable methods tailored for each stage of the formulation lifecycle; on-demand access to standout technical and programmatic subject-matter experts; optimized, outfitted facilities; smart access to learning embodied in a vast oeuvre of prior formulation work; hands-on method coaching. JPL has retooled its provision of integrated formulation lifecycle support to PIs, teams, and program offices in response to this need. This mission formulation enterprise is the JPL Innovation Foundry.

foundry↗
NASA NTRSDate not supplied

Estimating the Noise Floor of Sonic Boom Metrics Across the USA

NASA is building the X-59 Quiet Supersonic Technology aircraft to produce low noise sonic booms for a series of community noise surveys across the USA. Survey participants will rate their perception of the low booms from supersonic X-59 flyovers. Several noise metrics are proposed to quantify the noise dose: A-, B-, D-, E-weighted Sound Exposure Level, Stevens Perceived Level, and Indoor Sonic Boom Annoyance Predictor. Sparse measurements across the survey area will be used to estimate community noise exposure. The level of these low booms may be comparable to the ambient noise level in some locations, leading to uncertainty in noise exposure estimations. This uncertainty may necessitate increased reliance on sonic boom propagation predictions for exposure estimation. Low-boom signal to ambient noise ratio is one way to quantify uncertainty in measured sonic boom levels. An empirical relationship between A-weighted ambient level and sonic boom metric levels is used in conjunction with the National Park Service’s L50 SPL map to estimate sonic boom metric ambient levels across the USA. The estimate of ambient sonic boom metric levels will aid in X-59 test planning and execution.

sonic boom↗
NASA NTRS2021

Estimated Ambient Sonic Boom Metric Levels and X-59 Signal-to-Noise Ratios across the USA

NASA is building the X-59 Quiet Supersonic Technology aircraft to produce low noise sonic booms for a series of community noise surveys across the USA. Survey participants will rate their perception of the low-booms from supersonic X-59 flyovers. Several noise metrics are proposed to quantify the noise dose: A-, B-, D-, and E-weighted Sound Exposure Level, Stevens Perceived Level, and Indoor Sonic Boom Annoyance Predictor. Sparse measurements across the survey area will be used to estimate community noise exposure. The level of these low-booms may be comparable to the ambient noise level in some locations, leading to uncertainty in noise exposure estimations. This uncertainty may necessitate increased reliance on sonic boom propagation predictions for exposure estimation. Low-boom signal to ambient noise ratio is one way to quantify uncertainty in measured sonic boom levels. An empirical relationship between A-weighted ambient level and sonic boom metric levels is used in conjunction with the National Park Service’s L50 SPL map to estimate ambient noise levels expressed in terms of sonic boom noise metrics across the USA. These estimates of ambient levels will aid in X-59 community test planning and execution. The signal-to-noise ratio for the undertrack X-59 sonic boom is also estimated, and an example application of these data is presented for comparing potential noise monitor sites prior to a community noise test.

X-59↗
NASA NTRSDate not supplied

The effect of modeling dose uncertainty on low-boom community noise dose-response curves

In logistic dose-response modeling, failing to account for uncertainty in estimated doses can cause an artificial flattening or attenuation of the slope of the summary curve. In Lee et al. [J. Acoust. Soc. Am. 147(4), pp. 2222-2234 (2020)], data from two NASA low-amplitude sonic boom community noise survey tests were modeled using a Bayesian multilevel logistic regression (MLR) statistical model that assumed there was no uncertainty in the noise dose estimates. However, in these community tests, the noise dose uncertainty was estimated by Page et al. [NASA/CR-2014-218180 and NASA/CR-2020-220589/Volume I] using a leave-one-out method. In the current work, a term was added to extend the Bayesian MLR model to account for the estimated noise dose uncertainty quantified in the Page et al. analyses. This uncertainty term was included in two ways, either as classical or as Berkson uncertainty, and yield similar results. When the uncertainty is accounted for in the Bayesian MLR model, the dose-response curves become 5-10% steeper, but the difference in the noise dose that elicits a 5% highly annoyed response is small (less than 1 dB). This result is encouraging for future X-59 community tests whose survey area will be sparsely populated with noise monitors.

X-59↗
NASA NTRSDate not supplied

Experiment Design and Visualization Techniques for an X-59 Low-boom Variability Study

This presentation outlines the design of experiments approach and data visualization techniques for a simulation study of sonic booms from NASA’s X-59 supersonic aircraft. The X-59 will soon be flown over communities across the contiguous USA as it produces a low-loudness sonic boom, or low-boom. Survey data on human perception of low-booms will be collected to support development of potential future commercial supersonic aircraft noise regulatory standards. The macroscopic atmosphere plays a critical role in the loudness of sonic booms. The extensive sonic boom simulation study presented herein was completed to assess climatological, geographical, and seasonal effects on the variability of the X-59’s low-boom loudness and noise exposure region size in order to inform X-59 community test planning. The loudness and extent of the noise exposure region make up the “sonic boom carpet.” Two spatial and temporal resolutions of atmospheric input data to the simulation were investigated. A Fast Flexible Space-Filling Design was used to select the locations across the USA for the two spatial resolutions. Analysis of simulated X-59 low-boom loudness data within a regional subset of the northeast USA was completed using a bootstrap forest to determine the final spatial and temporal resolution of the countrywide simulation study. Atmospheric profiles from NOAA’s Climate Forecast System Version 2 database were used to generate over one million simulated X-59 carpets at the final selected 138 locations across the USA. Effects of aircraft heading, season, geography, and climate zone on low-boom levels and noise exposure region size were analyzed. Models were developed to estimate loudness metrics throughout the USA for X-59 supersonic cruise overflight, and results were visualized on maps to show geographical and seasonal trends. These results inform regulators and mission planners on expected variations in boom levels and carpet extent from atmospheric variations. Understanding potential carpet variability is important when planning community noise surveys using the X-59.

X-59↗
NASA NTRS2024

Large Interferometer For Exoplanets (LIFE) XIII. The value of Combining Thermal Emission and Reflected Light for the Characterization of Earth Twins

Context. Following the recommendations to NASA (in the Astro2020 Decadal survey) and ESA (through the Voyage2050 process), the search for life on exoplanets will be a priority in the next decades. Two concepts for direct imaging space missions are being developed for this purpose: the Habitable Worlds Observatory (HWO) and the Large Interferometer for Exoplanets (LIFE). These two concepts operate in different spectral regimes: HWO is focused on reflected light spectra in the ultraviolet, visible, and near-infrared (UV/VIS/NIR), while LIFE will operate in the mid-infrared (MIR) to capture the thermal emission of temperate exoplanets. Aims. In this study, we aim to assess the potential of HWO and LIFE to characterize a cloud-free Earth twin orbiting a Sun-like star at a distance of 10 pc, both as separate missions and in synergy with each other. We aim to quantify the increase in information that can be gathered by joint atmospheric retrievals on a habitable planet. Methods. We performed Bayesian retrievals on simulated data obtained by an HWO-like mission and a LIFE-like one separately, then jointly. We considered the baseline spectral resolutions currently assumed for these concepts and used two increasingly complex noise simulations, obtained using state-of-the-art noise simulators. Results. An HWO-like concept would allow one to strongly constrain H 2 O, O 2 , and O 3 in the atmosphere of a cloud-free Earth twin, while the atmospheric temperature profile is not well constrained (with an average uncertainty ≈100 K). LIFE-like observations would strongly constrain CO 2 , H 2 O, and O 3 and provide stronger constraints on the thermal atmospheric structure and surface temperature (down to ≈10 K uncertainty). For all the investigated scenarios, both missions would provide an upper limit on CH 4 . A joint retrieval on HWO and LIFE data would accurately define the atmospheric thermal profile and planetary parameters. It would decisively constrain CO 2 , H 2 O, O 2 , and O 3 and find weak constraints on CO and CH 4 . The significance of the detection is in all cases greater than or equal to the single-instrument retrievals. Conclusions. Both missions provide specific information that is relevant for the characterization of a terrestrial habitable exoplanet, but the scientific yield can be maximized by considering synergistic studies of UV/VIS/NIR+MIR observations. The use of HWO and LIFE together will provide stronger constraints on biosignatures and life indicators, with the potential to be transformative for the search for life in the Universe.

E Alei↗