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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Knowledge-Based Aircraft Automation: Managers Guide on the use of Artificial Intelligence for Aircraft Automation and Verification and Validation Approach for a Neural-Based Flight Controller

The ultimate goal of this report was to integrate the powerful tools of artificial intelligence into the traditional process of software development. To maintain the US aerospace competitive advantage, traditional aerospace and software engineers need to more easily incorporate the technology of artificial intelligence into the advanced aerospace systems being designed today. The future goal was to transition artificial intelligence from an emerging technology to a standard technology that is considered early in the life cycle process to develop state-of-the-art aircraft automation systems. This report addressed the future goal in two ways. First, it provided a matrix that identified typical aircraft automation applications conducive to various artificial intelligence methods. The purpose of this matrix was to provide top-level guidance to managers contemplating the possible use of artificial intelligence in the development of aircraft automation. Second, the report provided a methodology to formally evaluate neural networks as part of the traditional process of software development. The matrix was developed by organizing the discipline of artificial intelligence into the following six methods: logical, object representation-based, distributed, uncertainty management, temporal and neurocomputing. Next, a study of existing aircraft automation applications that have been conducive to artificial intelligence implementation resulted in the following five categories: pilot-vehicle interface, system status and diagnosis, situation assessment, automatic flight planning, and aircraft flight control. The resulting matrix provided management guidance to understand artificial intelligence as it applied to aircraft automation. The approach taken to develop a methodology to formally evaluate neural networks as part of the software engineering life cycle was to start with the existing software quality assurance standards and to change these standards to include neural network development. The changes were to include evaluation tools that can be applied to neural networks at each phase of the software engineering life cycle. The result was a formal evaluation approach to increase the product quality of systems that use neural networks for their implementation.

Broderick, Ron↗
NASA NTRS2002

System Level Uncertainty Assessment for Collaborative RLV Design

A collaborative design process utilizing Probabilistic Data Assessment (PDA) is showcased. Given the limitation of financial resources by both the government and industry, strategic decision makers need more than just traditional point designs, they need to be aware of the likelihood of these future designs to meet their objectives. This uncertainty, an ever-present character in the design process, can be embraced through a probabilistic design environment. A conceptual design process is presented that encapsulates the major engineering disciplines for a Third Generation Reusable Launch Vehicle (RLV). Toolsets consist of aerospace industry standard tools in disciplines such as trajectory, propulsion, mass properties, cost, operations, safety, and economics. Variations of the design process are presented that use different fidelities of tools. The disciplinary engineering models are used in a collaborative engineering framework utilizing Phoenix Integration's ModelCenter and AnalysisServer environment. These tools allow the designer to join disparate models and simulations together in a unified environment wherein each discipline can interact with any other discipline. The design process also uses probabilistic methods to generate the system level output metrics of interest for a RLV conceptual design. The specific system being examined is the Advanced Concept Rocket Engine 92 (ACRE-92) RLV. Previous experience and knowledge (in terms of input uncertainty distributions from experts and modeling and simulation codes) can be coupled with Monte Carlo processes to best predict the chances of program success.

Charania, A. C.↗
NASA NTRS2011

Exploring the Model Design Space for Battery Health Management

Battery Health Management (BHM) is a core enabling technology for the success and widespread adoption of the emerging electric vehicles of today. Although battery chemistries have been studied in detail in literature, an accurate run-time battery life prediction algorithm has eluded us. Current reliability-based techniques are insufficient to manage the use of such batteries when they are an active power source with frequently varying loads in uncertain environments. The amount of usable charge of a battery for a given discharge profile is not only dependent on the starting state-of-charge (SOC), but also other factors like battery health and the discharge or load profile imposed. This paper presents a Particle Filter (PF) based BHM framework with plug-and-play modules for battery models and uncertainty management. The batteries are modeled at three different levels of granularity with associated uncertainty distributions, encoding the basic electrochemical processes of a Lithium-polymer battery. The effects of different choices in the model design space are explored in the context of prediction performance in an electric unmanned aerial vehicle (UAV) application with emulated flight profiles.

Saha, Bhaskar↗
NASA NTRS2016

Extraction and Capture of Water from Martian Regolith Experimental Proof-of-Concept

Mars Design Reference Architecture 5.0:Lists in-situ resource utilization (ISRU) as enabling for robust human Mars missionsLO2LCH4 ascent propulsion 25,000 kg oxygen from atmosphere for ascent and life support Atmospheric based ISRU processes less operationally complex than surface based limited concept evaluation to date and Mars surface water property and distribution uncertainty would not allow [Mars soil water processing] to be base lined at this time Limited Concept Evaluation to Date Lunar regolith O2 extraction processing experience Lunar regolith is fluidized and heated to high temperatures with H2 to produce H2O from iron-bearing minerals Mars similarity concept: Soil placed in fluidized bed reactor Heated to moderate temperatures Inert gas flow used to fluidize the bed and help with water desorption Challenges: High-temperature dusty seals Working gas requires downstream separation and recycling to reduce consumables loss Batch process heating thermally inefficient.

in situ resource utilization↗
NASA NTRS2017

Early Results from the Advanced Radiation Protection Thick GCR Shielding Project

The Advanced Radiation Protection Thick Galactic Cosmic Ray (GCR) Shielding Project leverages experimental and modeling approaches to validate a predicted minimum in the radiation exposure versus shielding depth curve. Preliminary results of space radiation models indicate that a minimum in the dose equivalent versus aluminum shielding thickness may exist in the 20-30 g/cm2 region. For greater shield thickness, dose equivalent increases due to secondary neutron and light particle production. This result goes against the long held belief in the space radiation shielding community that increasing shielding thickness will decrease risk to crew health. A comprehensive modeling effort was undertaken to verify the preliminary modeling results using multiple Monte Carlo and deterministic space radiation transport codes. These results verified the preliminary findings of a minimum and helped drive the design of the experimental component of the project. In first-of-their-kind experiments performed at the NASA Space Radiation Laboratory, neutrons and light ions were measured between large thicknesses of aluminum shielding. Both an upstream and a downstream shield were incorporated into the experiment to represent the radiation environment inside a spacecraft. These measurements are used to validate the Monte Carlo codes and derive uncertainty distributions for exposure estimates behind thick shielding similar to that provided by spacecraft on a Mars mission. Preliminary results for all aspects of the project will be presented.

Norman, Ryan B.↗
NASA NTRS2014

Numerical Uncertainty Analysis for Computational Fluid Dynamics using Student T Distribution -- Application of CFD Uncertainty Analysis Compared to Exact Analytical Solution

Computational Fluid Dynamics (CFD) is the standard numerical tool used by Fluid Dynamists to estimate solutions to many problems in academia, government, and industry. CFD is known to have errors and uncertainties and there is no universally adopted method to estimate such quantities. This paper describes an approach to estimate CFD uncertainties strictly numerically using inputs and the Student-T distribution. The approach is compared to an exact analytical solution of fully developed, laminar flow between infinite, stationary plates. It is shown that treating all CFD input parameters as oscillatory uncertainty terms coupled with the Student-T distribution can encompass the exact solution.

Groves, Curtis E.↗
NASA NTRS2020

How emissions uncertainty influences the distribution and radiative impacts of smoke from fires in North America

Fires and the aerosols that they emit impact air quality, health, and climate, but the abundance and properties of carbonaceous aerosol (both black carbon and organic carbon) from biomass burning (BB) remain uncertain and poorly constrained. We aim to explore the uncertainties associated with fire emissions and their air quality and radiative impacts from underlying dry matter consumed and emissions factors. To investigate this, we compare model simulations from a global chemical transport model, GEOS-Chem, driven by a variety of fire emission inventories with surface and airborne observations of black carbon (BC) and organic aerosol (OA) concentrations and satellite-derived aerosol optical depth (AOD). We focus on two fire-detection-based and/or burned-area-based (FD-BA) inventories using burned area and active fire counts, respectively, i.e., the Global Fire Emissions Database version 4 (GFED4s) with small fires and the Fire INventory from NCAR version 1.5 (FINN1.5), and two fire radiative power (FRP)-based approaches, i.e., the Quick Fire Emission Dataset version 2.4 (QFED2.4) and the Global Fire Assimilation System version 1.2 (GFAS1.2). We show that, across the inventories, emissions of BB aerosol (BBA) differ by a factor of 4 to 7 over North America and that dry matter differences, not emissions factors, drive this spread. We find that simulations driven by QFED2.4 generally overestimate BC and, to a lesser extent, OA concentrations observations from two fire-influenced aircraft campaigns in North America (ARCTAS and DC3) and from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network, while simulations driven by FINN1.5 substantially underestimate concentrations. The GFED4s and GFAS1.2-driven simulations provide the best agreement with OA and BC mass concentrations at the surface (IMPROVE), BC observed aloft (DC3 and ARCTAS), and AOD observed by MODIS over North America. We also show that a sensitivity simulation including an enhanced source of secondary organic aerosol (SOA) from fires, based on the NOAA Fire Lab 2016 experiments, produces substantial additional OA; however, the spread in the primary emissions estimates implies that this magnitude of SOA can be neither confirmed nor ruled out when comparing the simulations against the observations explored here. Given the substantial uncertainty in fire emissions, as represented by these four emission inventories, we find a sizeable range in 2012 annual BBA PM2.5 population-weighted exposure over Canada and the contiguous US (0.5 to 1.6 µg/cu. m). We also show that the range in the estimated global direct radiative effect of carbonaceous aerosol from fires (−0.11 to −0.048 W/sq. m) is large and comparable to the direct radiative forcing of OA (−0.09 W/sq. m) estimated in the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC). Our analysis suggests that fire emissions uncertainty challenges our ability to accurately characterize the impact of smoke on air quality and climate.

North America↗
NASA NTRS1993

Effects of location uncertainties on the observed distribution of gamma-ray bursts detected by BATSE

The Burst and Transient Source Experiment (BATSE) on NASA's Compton Gamma-Ray Observatory has shown that the sources of gamma-ray bursts have an angular distribution consistent with isotropy, yet the bursts are spatially inhomogeneous. Detection of a statistically significant deviation from isotropy in the burst distribution would provide a clue to the distance of the burst sources. BATSE's ability to detect slight deviations of the angular distribution from isotropy is, in part, dependent on the accuracy of the computed burst locations. Using bursts whose locations have been determined accurately and independently, we estimate BATSE's location uncertainties and incorporate them into 3D Monte Carlo simulations of the burst distributions to show that, despite individual burst location uncertainties of about 5 deg, the ability of BATSE to place stringent limits on the anisotropy present in the angular distribution of the gamma-ray bursts is not significantly degraded. Observational effects of possible galactic halo distributions of the burst sources are noted.

Horack, J. M.↗
NASA NTRSDate not supplied

Quantifying Uncertainty in Particle Size Distribution Parameters Inferred from SAGE III/ISS Extinction Spectra

Stratospheric aerosols play key roles in the chemistry and radiation balance of the atmosphere and are a key input parameter for global chemistry and climate models. The degree to which aerosols impact chemistry and radiation balance depends primarily on their microphysical properties such as particle size distribution (PSD). The PSD is a mathematical description of the relative abundance of different sized particles within a sampling volume. If the PSD is accurately known then other key modeling parameters (e.g., surface area density) can be derived. Occultation observations from orbital instruments such as SAGE III/ISS have been used to infer these PSD parameters by inverting the extinction coefficient spectra. However, past efforts failed to address two key issues with this methodology: 1. The measurement uncertainty was not accounted for; 2. They assumed the PSDs to be single-mode only, while “real-world” PSDs are predominantly bi-modal. Accounting for both issues in the retrieval will yield an expanded solution space to the inferred PSD parameters; the question is “by how much?” To address this knowledge gap, we propose to carry out a series of simulations and, for every valid SAGE III/ISS data point, determine the range of PSD parameters that yield extinction spectra that are indistinguishable from the SAGE III/ISS data, within the limits of the reported uncertainty. Further, we will expand the solution space, for the first time, to include bimodal distributions. The results of this work will advance Earth system modeling/prediction capability through identifying the uncertainty of PSD parameter estimates using SAGE III/ISS data. The key benefits of this study over previous studies are twofold: 1. we will provide PSD estimates that include bimodal distributions in the solution space, 2. we will provide an uncertainty estimate for these parameters. The results of this study may be used directly in current and future climate and chemistry models.

SAGE III/ISS↗
NASA NTRS2011

Chance-Constrained Guidance With Non-Convex Constraints

Missions to small bodies, such as comets or asteroids, require autonomous guidance for descent to these small bodies. Such guidance is made challenging by uncertainty in the position and velocity of the spacecraft, as well as the uncertainty in the gravitational field around the small body. In addition, the requirement to avoid collision with the asteroid represents a non-convex constraint that means finding the optimal guidance trajectory, in general, is intractable. In this innovation, a new approach is proposed for chance-constrained optimal guidance with non-convex constraints. Chance-constrained guidance takes into account uncertainty so that the probability of collision is below a specified threshold. In this approach, a new bounding method has been developed to obtain a set of decomposed chance constraints that is a sufficient condition of the original chance constraint. The decomposition of the chance constraint enables its efficient evaluation, as well as the application of the branch and bound method. Branch and bound enables non-convex problems to be solved efficiently to global optimality. Considering the problem of finite-horizon robust optimal control of dynamic systems under Gaussian-distributed stochastic uncertainty, with state and control constraints, a discrete-time, continuous-state linear dynamics model is assumed. Gaussian-distributed stochastic uncertainty is a more natural model for exogenous disturbances such as wind gusts and turbulence than the previously studied set-bounded models. However, with stochastic uncertainty, it is often impossible to guarantee that state constraints are satisfied, because there is typically a non-zero probability of having a disturbance that is large enough to push the state out of the feasible region. An effective framework to address robustness with stochastic uncertainty is optimization with chance constraints. These require that the probability of violating the state constraints (i.e., the probability of failure) is below a user-specified bound known as the risk bound. An example problem is to drive a car to a destination as fast as possible while limiting the probability of an accident to 10(exp -7). This framework allows users to trade conservatism against performance by choosing the risk bound. The more risk the user accepts, the better performance they can expect.

FROM↗
NASA NTRSDate not supplied

Distribution of SLS Integrated Load Uncertainty to Surface Pressures and Sectional Loads

Aerodynamic loads that are important to launch vehicle programs such as NASA’s Space Launch System (SLS) include both integrated loads such as the force & moment on the entire vehicle and distributed loads. In this work two examples of distributed loads are considered: the pressure field on the surface of the vehicle and sectional loads, which are one-dimensional distributions along the axis of the launch vehicle. In some modern flight programs, the integrated loads, such as lift and drag, used to design the guidance and control laws for the vehicle come from wind tunnel testing, while distributed loads are produced using Computational Fluid Dynamics(CFD). The first task that is addressed in this paper, then, is to provide a formal method to adjust the distributed loads so that integrating them matches the prescribed integrated load. In addition, the integrated loads in a launch vehicle typically include an uncertainty estimate. The second task is to distribute this prescribed integrated uncertainty to each point in a distributed load. Both tasks are addressed using the same technique, which is to create distributed load profiles that isolate adjustments to one integrated load while leaving the others unaffected. These adjustments are informed by Proper Orthogonal Decomposition (POD) of the entire CFD-based distributed load database. Once applied, the adjusted distributed loads can be used to evaluate any scalar quantity of interest that might be needed by downstream users such as structural analysis or trajectory modelers.

SLS↗
NASA NTRS2007

Impact of Uncertainty in the Drop Size Distribution on Oceanic Rainfall Retrievals From Passive Microwave Observations

The variability of the drop size distribution (DSD) is one of the factors that must be considered in understanding the uncertainties in the retrieval of oceanic precipitation from passive microwave observations. Here, we have used observations from the Precipitation Radar on the Tropical Rainfall Measuring Mission spacecraft to infer the relationship between the DSD and the rain rate and the variability in this relationship. The impact on passive microwave rain rate retrievals varies with the frequency and rain rate. The total uncertainty for a given pixel can be slightly larger than 10% at the low end (ca. 10 GHz) of frequencies commonly used for this purpose and smaller at higher frequencies (up to 37 GHz). Since the error is not totally random, averaging many pixels, as in a monthly rainfall total, should roughly halve this uncertainty. The uncertainty may be lower at rain rates less than about 30 mm/h, but the lack of sensitivity of the surface reference technique to low rain rates makes it impossible to tell from the present data set.

Wilheit, Thomas T.↗
NASA NTRSDate not supplied

Simulation of Vacuum Chamber Pressure Distribution with Surrogate Modeling and Uncertainty Quantification

A major challenge in understanding differences in electric propulsion performance in ground tests and in space operations concerns the pressure distribution within the test vacuum chamber. The chamber backpressure is much higher than experienced in space, modifying thruster performance and plume dynamics. Numerical simulation is a key element to determining the background conditions in non-ideal vacuum chamber environments. An important parameter for the accurate simulation of chamber backpressure is the probability that an atom will stick to a cryogenic panel used to pump away the plume gases. This quantity can be used to model vacuum pumps in particle-based kinetic numerical methods. In this work, a three-dimensional direct simulation Monte Carlo code is used to model neutral xenon atoms flowing from the anode of the H9 Hall Effect Thruster within the University of Michigan’s Large Vacuum Test Facility. Simulated pressures are compared with ion gauge pressure measurements to infer the effective sticking coefficient of the chamber’s vacuum pumps. A pressure predicting surrogate model is developed for inference of pump sticking coefficients and for uncertainty quantification. This information enables accurate and useful kinetic simulations of electric propulsion thruster plasma plumes in vacuum chambers.

DSMC↗
NASA NTRS2002

Visualizing 2D Probability Distributions from Satellite Image-Derived Data

Creating maps of biophysical and geophysical variables using Earth Observing System (EOS) satellite image data is an important component of Earth science. These 2D maps have a single value at every location and standard techniques are used to visualize them. Current tools fall short, however, when it is necessary to describe a distribution of values at each location. Distributions may represent a frequency of occurrence over time, frequency of occurrence from multiple runs of an ensemble forecast or possible values from an uncertainty model. 'Distribution data sets' are described, then a case study is presented to visualize such 2D distributions. Distribution data sets are different from multivariate data sets in the sense that the values are for a single variable instead of multiple variables. Our case study data consists of multiple realizations of percent forest cover, generated using a geostatistical technique that combines ground measurements and satellite imagery to model uncertainty about forest cover. We present several approaches for analyzing and visualizing such data sets. The first is a pixel-wise analysis of the probability density functions for the 2D image while the second is an analysis of features identified within the image. Such pixel-wise and feature-wise views will give Earth scientists a more complete understanding of distribution data sets.

Kao, David↗
NASA NTRS2011

Uncertainty Analysis via Failure Domain Characterization: Unrestricted Requirement Functions

This paper proposes an uncertainty analysis framework based on the characterization of the uncertain parameter space. This characterization enables the identification of worst-case uncertainty combinations and the approximation of the failure and safe domains with a high level of accuracy. Because these approximations are comprised of subsets of readily computable probability, they enable the calculation of arbitrarily tight upper and lower bounds to the failure probability. The methods developed herein, which are based on nonlinear constrained optimization, are applicable to requirement functions whose functional dependency on the uncertainty is arbitrary and whose explicit form may even be unknown. Some of the most prominent features of the methodology are the substantial desensitization of the calculations from the assumed uncertainty model (i.e., the probability distribution describing the uncertainty) as well as the accommodation for changes in such a model with a practically insignificant amount of computational effort.

Crespo, Luis G.↗
NASA NTRS2008

Temporal Stability of Surface Roughness Effects on Radar Based Soil Moisture Retrieval During the Corn Growth Cycle

A representative soil surface roughness parameterization needed for the retrieval of soil moisture from active microwave satellite observation is difficult to obtain through either in-situ measurements or remote sensing-based inversion techniques. Typically, for the retrieval of soil moisture, temporal variations in surface roughness are assumed to be negligible. Although previous investigations have suggested that this assumption might be reasonable for natural vegetation covers (Moran et al. 2002, Thoma et al. 2006), insitu measurements over plowed agricultural fields (Callens et al. 2006) have shown that the soil surface roughness can change considerably over time. This paper reports on the temporal stability of surface roughness effects on radar observations and soil moisture retrieved from these radar observations collected once a week during a corn growth cycle (May 10th - October 2002). The data set employed was collected during the Optimizing Production Inputs for Economic and Environmental Enhancement (OPE3) field campaign covering this 2002 corn growth cycle and consists of dual-polarized (HH and VV) L-band (1.6 GHz) acquired at view angles of 15, 35, and 55 degrees. Cross-polarized L baud radar data were also collected as part of this experiment, but are not used in the analysis reported on here. After accounting for vegetation effects on radar observations, time-invariant optimum roughness parameters were determined using the Integral Equation Method (IEM) and radar observations acquired over bare soil and cropped conditions (the complete radar data set includes entire corn growth cycle). The optimum roughness parameters, soil moisture retrieval uncertainty, temporal distribution of retrieval errors and its relationship with the weather conditions (e.g. rainfall and wind speed) have been analyzed. It is shown that over the corn growth cycle, temporal roughness variations due to weathering by rain are responsible for almost 50% of soil moisture retrieval uncertainty depending on the sensing configuration. The effects of surface roughness variations are found to be smallest for observations acquired at a view angle of 55 degrees and HH polarization. A possible explanation for this result is that at 55 degrees and HH polarization the effect of vertical surface height changes on the observed radar response are limited because the microwaves travel parallel to the incident plane and as a result will not interact directly with vertically oriented soil structures.

Joseph, A.T.↗
NASA NTRS2017

Improving Photometric Calibration of Meteor Video Camera Systems

We present the results of new calibration tests performed by the NASA Meteoroid Environment Office (MEO) designed to help quantify and minimize systematic uncertainties in meteor photometry from video camera observations. These systematic uncertainties can be categorized by two main sources: an imperfect understanding of the linearity correction for the MEO's Watec 902H2 Ultimate video cameras and uncertainties in meteor magnitudes arising from transformations between the Watec camera's Sony EX-View HAD bandpass and the bandpasses used to determine reference star magnitudes. To address the first point, we have measured the linearity response of the MEO's standard meteor video cameras using two independent laboratory tests on eight cameras. Our empirically determined linearity correction is critical for performing accurate photometry at low camera intensity levels. With regards to the second point, we have calculated synthetic magnitudes in the EX bandpass for reference stars. These synthetic magnitudes enable direct calculations of the meteor's photometric flux within the camera bandpass without requiring any assumptions of its spectral energy distribution. Systematic uncertainties in the synthetic magnitudes of individual reference stars are estimated at approx. 0.20 mag, and are limited by the available spectral information in the reference catalogs. These two improvements allow for zero-points accurate to 0.05 - 0.10 mag in both filtered and unfiltered camera observations with no evidence for lingering systematics. These improvements are essential to accurately measuring photometric masses of individual meteors and source mass indexes.

Steven Ehlert↗