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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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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

An evidential approach to model-based satellite diagnosis

The paper presents an approach to the implementation of an automated satellite diagnosis capability which emphasizes techniques offering flexibility in the application of diagnostic strategies. The system utilizes a structural and behavioral model of the satellite; it uses a form of spreading activation to perform the diagnostic procedures on the model. A Dempster-Shafer evidential framework was implemented, making it possible to integrate evidence from the multiple sources necessary for building useful systems.

Bickmore, Timothy W.↗
NASA NTRS2015

The GEWEX Process Evaluation Study: GEWEX-PROES

Progress in realistically simulating the energy and water cycles in weather and climate models has been slower than desirable. Climate models submitted to the Coupled Model Intercomparison Project Phase-5 (CMIP-5), while more comprehensive than their predecessors, have shown little to no improvement in their biases in simulating key features of the climate system. As a result, uncertainties in global climate and hydrological sensitivities, and in the simulation of regional climate change, have not been reduced significantly. It is time to make use of these opportunities to significantly advance our understanding of key energy and water cycle processes at a wide range of space and time scales, and to provide a more insightful evaluation of the representation of these processes within models. This will require new ways of both analyzing the observations and diagnosing model behavior. The keys to success will be in skillfully combining different data sets and exploring relationships between them, as well as in the ability of models to reproduce those relationships correctly. In response to this challenge, a new GEWEX-wide activity, the GEWEX Process Evaluation Study, will take advantage of the opportunities that the combination of many of the existing data sets provide.

climate models↗
NASA NTRS1989

Minimal modeling of the extratropical general circulation

The ability of low-order, two-layer models to reproduce basic features of the mid-latitude general circulation is investigated. Changes in model behavior with increased spectral resolution are examined in detail. Qualitatively correct time-mean heat and momentum balances are achieved in a beta-plane channel model which includes the first and third meridional modes. This minimal resolution also reproduces qualitatively realistic surface and upper-level winds and mean meridional circulations. Higher meridional resolution does not result in substantial changes in the latitudinal structure of the circulation. A qualitatively correct kinetic energy spectrum is produced when the resolution is high enough to include several linearly stable modes. A model with three zonal waves and the first three meridional modes has a reasonable energy spectrum and energy conversion cycle, while also satisfying heat and momentum budget requirements. This truncation reproduces the basic mechanisms and zonal circulation features that are obtained at higher resolution. The model performance improves gradually with higher resolution and is smoothly dependent on changes in external parameters.

O'Brien, Enda↗
DOE OSTI2024

A protocol for model intercomparison of impacts of marine cloud brightening climate intervention

A modeling protocol (defined by a series of climate model simulations with specified model output) is introduced. Studies using these simulations are designed to improve the understanding of climate impacts using a strategy for climate intervention (CI) known as marine cloud brightening (MCB) in specific regions; therefore, the protocol is called MCB-REG (where REG stands for region). The model simulations are not intended to assess consequences of a realistic MCB deployment intended to achieve specific climate targets but instead to expose responses to interventions in six regions with pervasive cloud systems that are often considered candidates for such a deployment. A calibration step involving simulations with fixed sea surface temperatures (SSTs) is first used to identify a common forcing, and then coupled simulations with forcing in individual regions and combinations of regions are used to examine climate impacts. Synthetic estimates constructed by superposing responses from simulations with forcing in individual regions are considered a means of approximating the climate impacts produced when MCB interventions are introduced in multiple regions. A few results comparing simulations from three modern climate models (CESM2, E3SMv2, and UKESM1) are used to illustrate the similarities and differences between model behavior and the utility of estimates of MCB climate responses that were synthesized by summing responses introduced in individual regions. Cloud responses to aerosol injections differ substantially between models (CESM2 clouds appear much more susceptible to aerosol emissions than the other models), but patterns in precipitation and surface temperature responses were similar when forcing is imposed with similar amplitudes in the same regions. A previously identified La Niña-like response to forcing introduced in the Southeast Pacific is evident in this study, but the amplitude of the response was shown to markedly differ across the three models. Other common response patterns were also found and are discussed. Forcing in the Southeast Atlantic consistently (across all three models) produces weaker global cooling than that in other regions, and the Southeast Pacific and South Pacific show the strongest cooling. This indicates that the efficiency of a given intervention depends on not only the susceptibility of the clouds to aerosol perturbations, but also the strength of the underlying radiative feedbacks and ocean responses operating within each region. These responses were generally robust across models, but more studies and an examination of responses with ensembles would be beneficial.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

From observation to replication: machine-learning-driven quantification and replication of fine-scale fish kinematics and behavior

Long-term quantification of fish behavior is essential for aquatic ecology, wildlife telemetry, and biomechanical device development. However, the observation duration required to obtain reliable behavioral and kinematic metrics remains unclear, and few tools exist to physically reproduce natural swimming motion for controlled experimentation. We address these challenges by developing a generalizable framework that models behavioral reliability (Spearman–Brown reliability index) as a function of observation duration and derives metric-specific monitoring thresholds. Using juvenile white sturgeon (Acipenser transmontanus) as a case study, we demonstrate that the minimum duration needed for reliable estimates varies substantially across kinematic features: to exceed a reliability of 0.8, total distance traveled requires 12 days, average curvature (mm?¹) 15 days, tail-beat frequency (Hz) 8 days, and average speed (body length/s) 17 days. We further bridge digital analysis and physical testing by developing a hardware-in-the-loop simulator that reconstructs machine-learning-derived swimming kinematics with high fidelity (correlation coefficient 0.98–0.99, RMSE 1.22–1.27 mm over a 5-minute segment). This platform enables realistic, repeatable motion stimuli for evaluating aquatic sensing technologies and bio-integrated devices under controlled conditions. Together, these contributions provide a scalable approach for designing long-term behavioral studies and a data-driven connection between ecological observation and robotic experimentation.

Hwang, SungJoo↗
DOE OSTI2022

Evaluating Tropical Precipitation Relations in CMIP6 Models with ARM Data

Abstract A set of diagnostics based on simple, statistical relationships between precipitation and the thermodynamic environment in observations is implemented to assess phase 6 of the Coupled Model Intercomparison Project (CMIP6) model behavior with respect to precipitation. Observational data from the Atmospheric Radiation Measurement (ARM) permanent field observational sites are augmented with satellite observations of precipitation and temperature as an observational baseline. A robust relationship across observational datasets between column water vapor (CWV) and precipitation, in which conditionally averaged precipitation exhibits a sharp pickup at some critical CWV value, provides a useful convective onset diagnostic for climate model comparison. While a few models reproduce an appropriate precipitation pickup, most models begin their pickup at too low CWV and the increase in precipitation with increasing CWV is too weak. Convective transition statistics compiled in column relative humidity (CRH) partially compensate for model temperature biases—although imperfectly since the temperature dependence is more complex than that of column saturation. Significant errors remain in individual models and weak pickups are generally not improved. The conditional-average precipitation as a function of CRH can be decomposed into the product of the probability of raining and mean precipitation during raining times (conditional intensity). The pickup behavior is primarily dependent on the probability of raining near the transition and on the conditional intensity at higher CRH. Most models roughly capture the CRH dependence of these two factors. However, compensating biases often occur: model conditional intensity that is too low at a given CRH is compensated in part by excessive probability of precipitation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2012

Emergent Capabilities Converging into M and S 2.0

The continued operational environment complexity faced by the Department of Defense, despite a restricted resource environment, is a mandate for greater adaptability and availability in joint training. To address these constraints, this paper proposes a model for the potential integration of adaptability training, virtual world capabilities and immersive training into the wider Joint Live Virtual and Constructive (JLVC) Federation, supported by human, social, cultural and behavior modeling, and measurement and assessment. By fusing those capabilities and modeling and simulation enhancements into the JLVC federation, it will create a force who is more apt to arrive at and implement correct decisions, and more able to appropriately seize initiative in the field. The model would allow for the testing and training of capabilities and TTPs that cannot be reasonably explored to their logical conclusions in a 'live' environment, as well as enhance training fidelity for all echelons and tasks.

Reitz, Emilie↗
NASA NTRS2014

Robust Informatics Infrastructure Required For ICME: Combining Virtual and Experimental Data

With the increased emphasis on reducing the cost and time to market of new materials, the need for robust automated materials information management system(s) enabling sophisticated data mining tools is increasing, as evidenced by the emphasis on Integrated Computational Materials Engineering (ICME) and the recent establishment of the Materials Genome Initiative (MGI). This need is also fueled by the demands for higher efficiency in material testing; consistency, quality and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. Further, the use of increasingly sophisticated nonlinear, anisotropic and or multi-scale models requires both the processing of large volumes of test data and complex materials data necessary to establish processing-microstructure-property-performance relationships. Fortunately, material information management systems have kept pace with the growing user demands and evolved to enable: (i) the capture of both point wise data and full spectra of raw data curves, (ii) data management functions such as access, version, and quality controls;(iii) a wide range of data import, export and analysis capabilities; (iv) data pedigree traceability mechanisms; (v) data searching, reporting and viewing tools; and (vi) access to the information via a wide range of interfaces. This paper discusses key principles for the development of a robust materials information management system to enable the connections at various length scales to be made between experimental data and corresponding multiscale modeling toolsets to enable ICME. In particular, NASA Glenn's efforts towards establishing such a database for capturing constitutive modeling behavior for both monolithic and composites materials

Mutli-scale models↗
NASA NTRS2017

Near Earth Asteroid Characterization for Threat Assessment

Physical characteristics of NEAs are an essential input to modeling behavior during atmospheric entry and to assess the risk of impact but determining these properties requires a non-trivial investment of time and resources. The characteristics relevant to these models include size, density, strength and ablation coefficient. Some of these characteristics cannot be directly measured, but rather must be inferred from related measurements of asteroids and/or meteorites. Furthermore, for the majority of NEAs, only the basic measurements exist so often properties must be inferred from statistics of the population of more completely characterized objects. The Asteroid Threat Assessment Project at NASA Ames Research Center has developed a probabilistic asteroid impact risk (PAIR) model in order to assess the risk of asteroid impact. Our PAIR model and its use to develop probability distributions of impact risk are discussed in other contributions to PDC 2017 (e.g., Mathias et al.). Here we utilize PAIR to investigate which NEA characteristics are important for assessing the impact threat by investigating how changes in these characteristics alter the damage predicted by PAIR. We will also provide an assessment of the current state of knowledge of the NEA characteristics of importance for asteroid threat assessment. The relative importance of different properties as identified using PAIR will be combined with our assessment of the current state of knowledge to identify potential high impact investigations. In addition, we will discuss an ongoing effort to collate the existing measurements of NEA properties of interest to the planetary defense community into a readily accessible database.

Asteroid characterization↗
NASA NTRS2011

Highlights of Transient Plume Impingement Model Validation and Applications

This paper describes highlights of an ongoing validation effort conducted to assess the viability of applying a set of analytic point source transient free molecule equations to model behavior ranging from molecular effusion to rocket plumes. The validation effort includes encouraging comparisons to both steady and transient studies involving experimental data and direct simulation Monte Carlo results. Finally, this model is applied to describe features of two exotic transient scenarios involving NASA Goddard Space Flight Center satellite programs.

Woronowicz, Michael↗
NASA NTRS1998

Modeling with Livingstone

MPL is the language with which a modeler describes a system to be diagnosed or controlled by Livingstone. MPL is used to specify what are the components of the system, how they are interconnected, and how they behave both nominally and when failed. Component behavioral models used by Livingstone are described by a set of propositional, well-formed formula (wff). An understanding of well-formed formula, primitive component types specified through defcomponent, and device structure specified by defmodule, is essential to understanding of MPL, This document describes: welI-formed formula (wff): The basis for describing the behavior of a component in a system defvalues: Specifies the domain (legal values) of a variable defcomponent: Defines the modes, behaviors and mode transitions for primitive components deftnodule: Defines composite devices, consisting of interconnected components defrelation: A macro mechanism for expanding a complex wff according to the value of an argument forall: An iteration construct used to expand a wff or relation on a set of arguments defsymbol-expansion: A mechanism for naming a collection of symbols (eg the name of all valves in the system)

Kurien, J.↗
DOE OSTI2022

Classification of Nuclear Reactor Operations Using Spatial Importance and Multisensor Networks

Distributed multisensor networks record multiple data streams that can be used as inputs to machine learning models designed to classify operations relevant to proliferation at nuclear reactors. The goal of this work is to demonstrate methods to assess the importance of each node (a single multisensor) and region (a group of proximate multisensors) to machine learning model performance in a reactor monitoring scenario. This, in turn, provides insight into model behavior, a critical requirement of data-driven applications in nuclear security. Using data collected at the High Flux Isotope Reactor at Oak Ridge National Laboratory via a network of Merlyn multisensors, two different models were trained to classify the reactor’s operational state: a hidden Markov model (HMM), which is simpler and more transparent, and a feed-forward neural network, which is less inherently interpretable. Traditional wrapper methods for feature importance were extended to identify nodes and regions in the multisensor network with strong positive and negative impacts on the classification problem. These spatial-importance algorithms were evaluated on the two different classifiers. The classification accuracy was then improved relative to baseline models via feature selection from 0.583 to 0.839 and from 0.811 ± 0.005 to 0.884 ± 0.004 for the HMM and feed-forward neural network, respectively. While some differences in node and region importance were observed when using different classifiers and wrapper methods, the nodes near the facility’s cooling tower were consistently identified as important—a conclusion further supported by studies on feature importance in decision trees. Node and region importance methods are model-agnostic, inform feature selection for improved model performance, and can provide insight into opaque classification models in the nuclear security domain.

Tibbetts, Jake↗
NASA NTRS1983

Evaluation of Three Constitutive Models for the Prediction of Hastelloy X Elevated Temperature Cyclic Response

The approach for the method development assumes that, for a thermally loaded structure, the overall strain history is defined by linear elastic analysis. The local stress history at a fatigue critical location is then determined from a one dimensional material behavior model and the local strain and temperature conditions. Three material models are currently being evaluated to assess their ability to predict relevant high temperature cyclic material response characteristics. They are: a time independent classical plasticity and creep representation, a time dependent viscoplastic model capable of predicting combined creep and plasticity effects, and an approximate elastic analysis approach that uses a series of stress-strain curves and a cyclic hardening model to determine reverse plasticity.

Moreno, V.↗
DOE OSTI2023

Region and cloud regime dependence of parametric sensitivity in E3SM atmosphere model

Abstract The Department of Energy (DOE)’s Energy Exascale Earth System Model (E3SM), including its atmosphere model (EAM), has many relatively new features. In a previous study we conducted a systematic parametric sensitivity analysis for EAM based on short, perturbed parameter ensemble (PPE) simulations, mainly focusing on global mean climate features and metrics. While parameter values in global climate models are generally invariant in space and time, model response to parameters perturbation may vary by regions and climate regimes, which motivates the need to better understand the EAM model behaviors and physics at regional scale and process level. In this study, using the same set of PPE simulations and a similar sensitivity analysis framework, we identify parameters that cause largest sensitivities over different regions and compare model responses in fast atmospheric processes to the parameters across different cloud regimes for several important cloud-related fidelity metrics. We find that cloud forcing has opposite response to some parameters over mid-latitude vs. tropical land. We also analyze how the parametric sensitivity varies as stratocumulus transitions to shallow convection and to deep convection over ocean. Low cloud forcing and shortwave cloud forcing in the subtropical eastern Pacific are most sensitive to the parameters controlling the width of the probability density function (PDF) of the subgrid vertical velocity ( w’ ) ( gamma ) and the damping of the w’ skewness ( c8 ) near the coast but become more sensitive to the parameter affecting the damping of the w’ variance ( c1 ) further offshore. Detailed interpretation of the spatial dependence of parametric sensitivity is provided. We also investigate how the parametric sensitivity evolves with prediction duration. This study improves our process-level understanding of cloud physics and parameterization and provides insights for developing more advanced regime-aware parameterization schemes in global climate model.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

HDL to verification logic translator

The increasingly higher number of transistors possible in VLSI circuits compounds the difficulty in insuring correct designs. As the number of possible test cases required to exhaustively simulate a circuit design explodes, a better method is required to confirm the absence of design faults. Formal verification methods provide a way to prove, using logic, that a circuit structure correctly implements its specification. Before verification is accepted by VLSI design engineers, the stand alone verification tools that are in use in the research community must be integrated with the CAD tools used by the designers. One problem facing the acceptance of formal verification into circuit design methodology is that the structural circuit descriptions used by the designers are not appropriate for verification work and those required for verification lack some of the features needed for design. We offer a solution to this dilemma: an automatic translation from the designers' HDL models into definitions for the higher-ordered logic (HOL) verification system. The translated definitions become the low level basis of circuit verification which in turn increases the designer's confidence in the correctness of higher level behavioral models.

Gambles, J. W.↗
NASA NTRSDate not supplied

TPSAS-NF1676L-33873-DND

NOAA's National Air Quality Forecasting Capability (NAQFC) model provides 48-hour forecast of surface ozone and other atmospheric constituents serving as the nation's key tool actively used by regulatory professionals in assessing air quality events and the issuance of public air quality alerts. NAQFC incorporates input meteorology from North American Mesoscale Model (NAM) at 12 km horizontal resolution that is coupled to the Community Multi-scale Air Quality Model (CMAQ) to predict emissions, tropospheric gas and aerosol chemistry, and related deposition and removal processes. The NAQFC forecast simulations contain 35 steps in altitude, with about one third of these in a typical afternoon daytime boundary layer (0-1.5 km). While several studies have been conducted comparing NAQFC predictions to surface observations, investigations comparing the vertical distribution to observations remain limited. Vertical comparisons are needed in order to fully assess forecast model behavior and atmospheric mixing conditions leading to the formation of ozone at the surface. The Tropospheric Ozone Lidar Network (TOLNet) instruments provide a unique observational capability in this regard, as ozone vertical measurements can be directly compared to models, such as NAQFC, and provide additional insight into atmospheric processes and enhance forecast capabilities. In this study, we utilize multiple TOLNet lidar observations obtained during the Ozone Water Land Environmental Transition Studies (OWLETS-2017 & OWLETS-2018) and the Long Island Sound Tropospheric Ozone Study (LISTOS-2018) to compare with NAQFC vertical predictions of ozone. These campaigns took place at different coastal locations along the US East coast with each campaign having multiple TOLNet lidars present, providing a unique opportunity to examine vertical structure of ozone in regions with complex water-land boundaries. Preliminary comparison results will be presented on ozone temporal and vertical differences between NAQFC and the TOLNet lidars along with example case studies to illustrate insights into boundary layer and surface processes of trace gases.

Timothy Berkoff↗
NASA NTRS2010

Reliability Quantification of Advanced Stirling Convertor (ASC) Components

The Advanced Stirling Convertor, is intended to provide power for an unmanned planetary spacecraft and has an operational life requirement of 17 years. Over this 17 year mission, the ASC must provide power with desired performance and efficiency and require no corrective maintenance. Reliability demonstration testing for the ASC was found to be very limited due to schedule and resource constraints. Reliability demonstration must involve the application of analysis, system and component level testing, and simulation models, taken collectively. Therefore, computer simulation with limited test data verification is a viable approach to assess the reliability of ASC components. This approach is based on physics-of-failure mechanisms and involves the relationship among the design variables based on physics, mechanics, material behavior models, interaction of different components and their respective disciplines such as structures, materials, fluid, thermal, mechanical, electrical, etc. In addition, these models are based on the available test data, which can be updated, and analysis refined as more data and information becomes available. The failure mechanisms and causes of failure are included in the analysis, especially in light of the new information, in order to develop guidelines to improve design reliability and better operating controls to reduce the probability of failure. Quantified reliability assessment based on fundamental physical behavior of components and their relationship with other components has demonstrated itself to be a superior technique to conventional reliability approaches based on utilizing failure rates derived from similar equipment or simply expert judgment.

Shah, Ashwin R.↗
DOE OSTI2023

Understanding Changes in Cloud Simulations from E3SM Version 1 to Version 2

This study documents clouds simulated by the Energy Exascale Earth System Model (E3SM) version 2 (E3SMv2) and attempts to understand what causes the model behavior change in clouds relative to E3SMv1. This is done by analyzing the last 30-year (1985–2014) data from the 165-year historical simulations using E3SMv1 and v2 and four sensitivity tests to isolate the impact of changes in model parameter choices in its turbulence, shallow convection, and cloud macrophysics parameterization (CLUBB), microphysical parameterization (MG2), and deep convection scheme (ZM), as well as model physics changes in convective triggering. It is shown that E3SMv2 significantly improves the simulation of subtropical coastal stratocumulus clouds (Sc) and clouds with optical depth larger than 3.6 over the stratocumulus to cumulus transition regimes, where Shortwave Cloud Radiative Effect (SWCRE) is also improved, and the Southern Ocean (SO) while seeing an overall slight degradation in low clouds over other tropical and subtropical oceans. The better performance in E3SMv1 over those regions is partially due to error compensation between its simulated optically thin and intermediate low clouds for which E3SMv2 actually improves simulation of optically intermediate low clouds. Sensitivity tests indicate that the changes in low clouds are primarily due to the tuning made in CLUBB. The impact of the ZM tuning is mainly on optically intermediate and thick high clouds, contributing to improved SWCRE and Longwave Cloud Radiative Effect (LWCRE). The impact of the MG2 tuning and the new convective trigger is primarily on the high latitudes and the Southern Ocean (SO). They have a relatively smaller impact on clouds than do the CLUBB and ZM tunings. This study offers additional insights about clouds simulated in E3SMv2 by utilizing multiple data sets and the COSP diagnostic tool as well as through sensitivity tests. The improved understanding will benefit the future E3SM developments.

54 ENVIRONMENTAL SCIENCES↗