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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 NTRS2010

LRN, ERN:, & BERN @ Wireless Integrating the Sciences (WITS) Theatre

In order to develop a call to action for a learning tool that would work to best teach Science Technology Engineering and Math (STEM), the NASA Goddard team will partner with the inventor of Bop It!, an interactive game of verbs and following instructions; and Global Imagination, the developers of Magic Planet. In this paper Decision-making Orbital Health! (DOH!) will be described as a game derived from the basic functions necessary for Bop lt!, a familiar game. that will ask the educational audience to respond to changing commands to Bop It!, Twist It!, and Squeeze It! The success of the new version of the game, will be that the Earth will be making these commands from Dynamic Planet, and the crowd assembled can play wirelessly. Wireless Integrating The Sciences (WITS) Theatre : A balanced approach will describe how the communities local to Goddard and perhaps San Francisco will develop curriculum that helps kids teach kids with an engaging game and a STEM message. The performing arts will be employed to make it entertaining and appropriate to the size of the gathering, and the students educational level.

Hilliard, L.↗
NASA NTRS1990

Aircraft en route noise annoyance

Results are reported from a laboratory experiment conducted in order to quantify the annoyance experienced by people on the ground in response to en route noise (ERN) generated by aircraft at cruise conditions. Objectives included the comparison of annoyance responses to ERN with the annoyance responses to takeoff and landing noise; the comparison of the annoyance responses to advanced turboprop aircraft ERN with those of the turbofan ERN; and also the ability of aircraft noise measurement procedures and corrections to predict annoyance to ERN. Tests were conducted at the Langley Acoustics Research Laboratory on 32 human subjects selected at random. Subjects judged the annoyance level of 24 Propfan Test Assessment advanced turboprop ERN stimuli, 18 conventional turbofan ERN stimuli, and 60 conventional turboprop and turbofan takeoff and landing noise stimuli. Analysis of resulting data compared annoyance responses to different aircraft types and operations, examined the ability of current noise measurement and correction procedures to predict annoyance ERN, and calculated optimum duration correction magnitudes for ERN.

Mccurdy, David A.↗
NASA NTRS2006

Secondary Electron Emission and the Exploration of Space

The emission of secondary electrons from surfaces exposed to the space plasma and radiation environment is a process of great importance to space system engineering design and operations. A spacecraft will collect charge until it reaches an equilibrium potential gov,erned by the balance of incoming electron and ion currents from the space environment with outgoing secondary, backscattered, and photoelectron currents. Laboratory measurements of secondary electron yields are an important parameter for use in spacecraft charging analyses because the magnitude and sign of the equilibrium potential depends on both the energy spectrum of electrons and ions in the space environment and the electrical properties of the surface materials (including the energy dependent secondary electron yields). Typical benign equilibrium potentials range &om a few tens of volts positive in interplanetary space to a few volts negative in low Earth orbit. However, spacecraft are known to charge to negative potentials exceeding one to ten kilovolts in some environments and anomalies or system failures due to electrostatic discharges originating from highly charged surfaces becomes a serious concern. This presentation will provide a review of the spacecraft charging process with special emphasis on the role of secondary electrons in controlling the current balance process. Charging examples will include spacecraft in Earth orbit and interplanetary space as well as dust charging on the lunar surface, a phenomenon of importance to future lunar surface operations.

Minow, Joseph I.↗
NASA NTRS2022

Landslide Likelihood Prediction using Machine Learning Algorithms

The supply of electricity via power plants is criticalto the operation of many critical infrastructure systems in mod-ern society. Natural hazards can disrupt the power supply, causepower outages that can halt economic growth, and impede emer-gency response until power is restored. The proposed work aimsto predict the landslides likelihood in these critical infrastructurelocations in the Northeastern USA using integrated databases ofexplanatory variables and machine learning algorithms. First,data related to landslides are obtained and merged, includingtopographic, soil moisture, and precipitation-related data. Fiveregression algorithms, namely: Random Forest, Extreme Gradi-ent Boosting (XGBoost), K-Nearest Neighbor regression (KNN),Linear Support Vector Regressor (SVR), and Linear regression,are utilized to predict the landslide probability and evaluatedon the dataset. The accuracy of the models is assessed by usingstatistical metrics such as mean absolute error (MAE), meansquared error (MSE), and root mean squared error (RMSE).The study results show that Random Forest outperformed othermodels with the mutual information feature selection method.It achieved an MSE of 0.0011 with mutual information-basedfeature selection and an MSE of 0.00157 without feature selection.KNN regressor outperformed the other models with an MSEof 0.00139 with correlation-based information selection. Theproposed landslide identification model with Random Forestalgorithm shows outstanding robustness and great potential intackling the landslide likelihood prediction by employing MLalgorithms.

Vasundhara Acharya↗
NASA NTRSDate not supplied

Curating AI-Ready Datasets for Equity and Environmental Justice: A Data-Centric AI Case Study

An equitable and environmentally just community is essentialin order to avoid disproportionate burden borne by vulnerablecommunities. This need becomes pressing in the aftermathof an extreme event such as disaster or hazard when it is diffi-cult for the governing bodies to implement resource allocationas per the need. Artificial Intelligence (AI) algorithms canhelp surface Equity and Environmental Justice (EEJ) issueswhen trained on EEJ datasets. However, curating AI-readyEEJ training datasets is challenging due to differences in fac-tors such as heterogeneity, resolution, modality, and level ofexpertise in labeling. Additionally, EEJ issues involve sensi-tive information where uncertainties and errors could degradethe performance of AI algorithms. For eg. Error in seasonalcrop yield information can highly affect the prediction of an-nual crop yield. To address these challenges, Data-centricAI (DCAI) methods are employed, which enhance AI algo-rithm performance even with limited training samples. DCAIprioritizes data quality, thereby reducing the adverse effectsof uncertainties and errors during the model training process.This research proposes a novel dataset and benchmark for an-alyzing the effect of the Maui Wildfire of 2023 for Equityand Environmental Justice (EEJ) issues. The proposed datasetaligns with the concepts of DCAI such as annotation quality,data preprocessing, privacy, feature engineering, governanceand provenance. We firmly believe that the proposed datasetwould lay a foundation to implement robust and reliable mod-ern AI algorithms for addressing EEJ issues.

Paridhi Parajuli↗
NASA NTRS1993

Numerical solution of flame sheet problems with and without multigrid methods

Flame sheet problems are on the natural route to the numerical solution of multidimensional flames, which, in turn, are important in many engineering applications. In order to model the structure of flames more accurately, we use the vorticity-velocity formulation of the fluid flow equations, as opposed to the streamfunction-vorticity approach. The numerical solution of the resulting nonlinear coupled elliptic partial differential equations involves a pseudo transient process and a steady state Newton iteration. Rather than working with dimensionless variables, we introduce scale factors that can yield significant savings in the execution time. In this context, we also investigate the applicability and performance of several multigrid methods, focusing on nonlinear damped Newton multigrid, using either one way or correction schemes.

Douglas, Craig C.↗
NASA NTRS1995

Numerical modeling of flame-balls in fuel-air mixtures

At low gravity, when buoyancy effects are small, flame-balls can be generated. These are stationary spherical structures whose existence appears to require a near-limit mixture, a small Lewis number and heat losses from radiation. It is our goal to combine computational modeling with existing experimental and theoretical studies (NASA) of these structures so that an improved understanding of flammability limits and near-limit phenomena will occur. The question of flammability limits is of fundamental importance and has long been examined. It is of great practical importance to predict, from first principles, a limit mixture strength that agrees with experimental values for the configuration at hand. Flame-balls provide an excellent configuration in which convective losses can be eliminated and the resulting stable solutions are produced from a diffusive, reactive and radiative balance. Although analytical modeling provides convincing evidence that the key physical ingredients of flame-balls have been identified, quantitative confirmation can only come from detailed numerical simulations. Our goal is to predict theoretically the mass fractions of the species and the temperature as functions of the independent coordinate r.

Smooke, Mitchell D.↗
NASA NTRS2011

International Space Station Water Balance Operations

In November 2008, the Water Regenerative System racks were launched aboard Space Shuttle flight, STS-126 (ULF2) and installed and activated on the International Space Station (ISS). These racks, consisting of the Water Processor Assembly (WPA) and Urine Processor Assembly (UPA), completed the installation of the Regenerative (Regen) Environmental Control and Life Support Systems (ECLSS), which includes the Oxygen Generation Assembly (OGA) that was launched 2 years prior. With the onset of active water management on the US segment of the ISS, a new operational concept was required, that of water balance . In November of 2010, the Sabatier system, which converts H2 and CO2 into water and methane, was brought on line. The Regen ECLSS systems accept condensation from the atmosphere, urine from crew, and processes that fluid via various means into potable water, which is used for crew drinking, building up skip-cycle water inventory, and water for electrolysis to produce oxygen. Specification (spec) rates of crew urine output, condensate output, O2 requirements, toilet flush water, and drinking needs are well documented and used as the best guess planning rates when Regen ECLSS came online. Spec rates are useful in long term planning, however, daily or weekly rates are dependent upon a number of variables. The constantly changing rates created a new challenge for the ECLSS flight controllers, who are responsible for operating the ECLSS systems onboard ISS from Mission Control in Houston. This paper reviews the various inputs to water planning, rate changes, and dynamic events, including but not limited to: crew personnel makeup, Regen ECLSS system operability, vehicle traffic, water storage availability, and Carbon Dioxide Removal Assembly (CDRA), Sabatier, and OGA capability. Along with the inputs that change the various rates, the paper will review the different systems, their constraints, and finally the operational challenges and means by which flight controllers manage this new concept of "water balance."

Tobias, Barry↗
NASA NTRS2013

A Comparison Between Gravity Wave Momentum Fluxes in Observations and Climate Models

For the first time, a formal comparison is made between gravity wave momentum fluxes in models and those derived from observations. Although gravity waves occur over a wide range of spatial and temporal scales, the focus of this paper is on scales that are being parameterized in present climate models, sub-1000-km scales. Only observational methods that permit derivation of gravity wave momentum fluxes over large geographical areas are discussed, and these are from satellite temperature measurements, constant-density long-duration balloons, and high-vertical-resolution radiosonde data. The models discussed include two high-resolution models in which gravity waves are explicitly modeled, Kanto and the Community Atmosphere Model, version 5 (CAM5), and three climate models containing gravity wave parameterizations,MAECHAM5, Hadley Centre Global Environmental Model 3 (HadGEM3), and the Goddard Institute for Space Studies (GISS) model. Measurements generally show similar flux magnitudes as in models, except that the fluxes derived from satellite measurements fall off more rapidly with height. This is likely due to limitations on the observable range of wavelengths, although other factors may contribute. When one accounts for this more rapid fall off, the geographical distribution of the fluxes from observations and models compare reasonably well, except for certain features that depend on the specification of the nonorographic gravity wave source functions in the climate models. For instance, both the observed fluxes and those in the high-resolution models are very small at summer high latitudes, but this is not the case for some of the climate models. This comparison between gravity wave fluxes from climate models, high-resolution models, and fluxes derived from observations indicates that such efforts offer a promising path toward improving specifications of gravity wave sources in climate models.

mathematical models↗