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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Design Strategy for a Formally Verified Reliable Computing Platform

This paper presents a high-level design for a reliable computing platform for real-time control applications. The design tradeoffs and analyses related to the development of a formally verified reliable computing platform are discussed. The design strategy advocated in this paper requires the use of techniques that can be completely characterized mathematically as opposed to more powerful or more flexible algorithms whose performance properties can only be analyzed by simulation and testing. The need for accurate reliability models that can be related to the behavior models is also stressed. Tradeoffs between reliability and voting complexity are explored. In particular, the transient recovery properties of the system are found to be fundamental to both the reliability analysis as well as the "correctness" models.

Butler, Ricky W.↗
DOE OSTI2024

Airborne LiDAR to Improve Canopy Fuels Mapping for Wildfire Modeling

Increasing conflict between wildfire and the built environment has increased the need for more up-to-date and finer resolution canopy fuels data to improve wildfire modeling and associated risk forecasts. The US Forest Service and US Department of the Interior’s LANDFIRE product, which provides 30-m resolution canopy fuels data for the entire US, is one of the most widely used sources of fuels data. However, the last complete mapping effort for LANDFIRE is based on 2016 conditions, and subsequent updates reflect disturbances 1-2 years behind the release year. Airborne systems equipped with Light Detection and Ranging (LiDAR) sensors can be deployed to actively sense canopy structure and estimate canopy fuels data (cover, height, base height, bulk density) at finer resolutions. Canopy base height (CBH) and canopy bulk density (CBD) are difficult to measure both in the field and in LiDAR point clouds. Still, they are important for accurately modeling crown fires, which are often intense and difficult to contain. Additionally, point cloud datasets are large, and calculations require efficient utilization of computational resources. To address these challenges, we are working on an approach that uses openly available National Ecological Observatory Network (NEON) airborne LiDAR data, with calculations processed in the R programming language and parallelized through the lidR package. CBH and CBD are often derived from tree height, diameter at breast height, and species-specific allometries using the Fire and Fuels Extension of the Forest Vegetation Simulator (FFE-FVS). We aim to test if airborne LiDAR can estimate CBH and CBD without the use of empirical equations. Reliable estimates of canopy fuels data directly from airborne LiDAR could streamline quick, fine-resolution updates for use in wildfire behavior models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

DOE ART Graphite Program Intro Status 2023

General description of the ART Graphite Program with Status for 2023. This includes list of staff members, and brief description of behavior models, licensing & code, graphite R&D, As-Fab'd Properties, Machanism and Analysis, Irradiation. Also detail FY23 Activites, with AGC Update, Oxidation Activiteis, Baseline STatus, ASME Code Development, VIC Project Update, Molten salt studies. Slide included to highlight each employee contributions for work and papers and NEUPs.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2010

DEM Solutions Develops Answers to Modeling Lunar Dust and Regolith

With the proposed return to the Moon, scientists like NASA-KSC's Dr. Calle are concerned for a number of reasons. We will be staying longer on the planet's surface, future missions may include dust-raising activities, such as excavation and handling of lunar soil and rock, and we will be sending robotic instruments to do much of the work for us. Understanding more about the chemical and physical properties of lunar dust, how dust particles interact with each other and with equipment surfaces and the role of static electricity build-up on dust particles in the low-humidity lunar environment is imperative to the development of technologies for removing and preventing dust accumulation, and successfully handling lunar regolith. Dr. Calle is currently working on the problems of the electrostatic phenomena of granular and bulk materials as they apply to planetary surfaces, particularly to those of Mars and the Moon, and is heavily involved in developing instrumentation for future planetary missions. With this end in view, the NASA Kennedy Space Center's Innovative Partnerships Program Office partnered with OEM Solutions, Inc. OEM Solutions is a global leader in particle dynamics simulation software, providing custom solutions for use in tackling tough design and process problems related to bulk solids handling. Customers in industries such as pharmaceutical, chemical, mineral, and materials processing as well as oil and gas production, agricultural and construction, and geo-technical engineering use OEM Solutions' EDEM(TradeMark) software to improve the design and operation of their equipment while reducing development costs, time-to-market and operational risk. EDEM is the world's first general-purpose computer-aided engineering (CAE) tool to use state-of-the-art discrete element modeling technology for the simulation and analysis of particle handling and manufacturing operations. With EDEM you'can quickly and easily create a parameterized model of your granular solids system. Computer-aided design (CAD) models of real particles can be imported to obtain an accurate representation of their shape. EDEM(TradeMark) uses particle-scale behavior models to simulate bulk solids behavior. In addition to particle size and shape, the models can account for physical properties of particles along with interaction between particles and with equipment surfaces and surrounding media, as needed to define the physics of a particular process.

Dunn, Carol Anne↗
NASA NTRS2015

Improved Dynamic Modeling of the Cascade Distillation Subsystem and Integration with Models of Other Water Recovery Subsystems

The Cascade Distillation Subsystem (CDS) is a rotary multistage distiller being developed to serve as the primary processor for wastewater recovery during long-duration space missions. The CDS could be integrated with a system similar to the International Space Station (ISS) Water Processor Assembly (WPA) to form a complete Water Recovery System (WRS) for future missions. Independent chemical process simulations with varying levels of detail have previously been developed using Aspen Custom Modeler (ACM) to aid in the analysis of the CDS and several WPA components. The existing CDS simulation could not model behavior during thermal startup and lacked detailed analysis of several key internal processes, including heat transfer between stages. The first part of this paper describes modifications to the ACM model of the CDS that improve its capabilities and the accuracy of its predictions. Notably, the modified version of the model can accurately predict behavior during thermal startup for both NaCl solution and pretreated urine feeds. The model is used to predict how changing operating parameters and design features of the CDS affects its performance, and conclusions from these predictions are discussed. The second part of this paper describes the integration of the modified CDS model and the existing WPA component models into a single WRS model. The integrated model is used to demonstrate the effects that changes to one component can have on the dynamic behavior of the system as a whole.

Perry, Bruce↗
NASA NTRS1995

Mathematical Model Of Curing Behavior Of A Polymer

Mathematical model predicts selected aspects of chemical, thermal and mechanical responses of polymeric liner and propellant materials during curing process. Predictions made both prior to processing and during process in quasi-real time. Developed specifically for use in designing and analyzing process in which bondline materials (including polymeric liners) and propellant cast and cured in rocket motor. With modifications, model applicable to curing of other polymeric materials. Further development may provide direct "in-line" program for calculations, including comparisons, in real time. This will constitute basis for more sophisticated control of process.

Loomis, Willard C.↗
NASA NTRS1999

Porous Media and Mixture Models for Hygrothermal Behavior of Phenolic Composites

Theoretical models are proposed to describe the interaction of water with phenolic polymer. The theoretical models involve the study of the flow of a viscous fluid through a porous media and the thermodynamic theory of mixtures. From the theory, a set of mathematical relations are developed to simulate the effect of water on the thermostructural response of phenolic composites. The expressions are applied to simulate the measured effect of water in a series of experiments conducted on carbon phenolic composites.

Sullivan, Roy M.↗
DOE OSTI2024

Versatile stochastic model for predictive KMC simulation of fcc metal nanostructure evolution with realistic kinetics

Stochastic lattice-gas models provide the natural framework for analysis of the surface diffusion-mediated evolution of crystalline metal nanostructures on the appropriate time scale (often 10 1 –10 4 s) and length scale. Model behavior can be precisely assessed by kinetic Monte Carlo simulation, typically incorporating a rejection-free algorithm to efficiently handle the broad range of Arrhenius rates for hopping of surface atoms. The model should realistically prescribe these rates, or the associated barriers, for a diversity of local surface environments. However, commonly used generic choices for barriers fail, even qualitatively, to simultaneously describe diffusion for different low-index facets, for terrace vs step edge diffusion, etc. We introduce an alternative Unconventional Interaction–Conventional Interaction formalism to prescribe these barriers, which, even with few parameters, can realistically capture most aspects of behavior. Here, the model is illustrated for single-component fcc metal systems, mainly for the case of Ag. It is quite versatile and can be applied to describe both the post-deposition evolution of 2D nanostructures in homoepitaxial thin films (e.g., reshaping and coalescence of 2D islands) and the post-synthesis evolution of 3D nanocrystals (e.g., reshaping of nanocrystals synthesized with various faceted non-equilibrium shapes back to 3D equilibrium Wulff shapes).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1999

A Quantitative Study of Oxygen as a Metabolic Regulator

An acute reduction in oxygen (O2) delivery to a tissue is generally associated with a decrease in phosphocreatine, increases in ADP, NADH/NAD, and inorganic phosphate, increased rates of glycolysis and lactate production, and reduced rates of pyruvate and fatty acid oxidation. However, given the complexity of the human bioenergetic system and its components, it is difficult to determine quantitatively how cellular metabolic processes interact to maintain ATP homeostasis during stress (e.g., hypoxia, ischemia, and exercise). Of special interest is the determination of mechanisms relating tissue oxygenation to observed metabolic responses at the tissue, organ, and whole body levels and the quantification of how changes in tissue O2 availability affect the pathways of ATP synthesis and the metabolites that control these pathways. In this study, we extend a previously developed mathematical model of human bioenergetics to provide a physicochemical framework that permits quantitative understanding of O2 as a metabolic regulator. Specifically, the enhancement permits studying the effects of variations in tissue oxygenation and in parameters controlling the rate of cellular respiration on glycolysis, lactate production, and pyruvate oxidation. The whole body is described as a bioenergetic system consisting of metabolically distinct tissue/organ subsystems that exchange materials with the blood. In order to study the dynamic response of each subsystem to stimuli, we solve the ordinary differential equations describing the temporal evolution of metabolite levels, given the initial concentrations. The solver used in the present study is the packaged code LSODE, as implemented in the NASA Lewis kinetics and sensitivity analysis code, LSENS. A major advantage of LSENS is the efficient procedures supporting systematic sensitivity analysis, which provides the basic methods for studying parameter sensitivities (i.e., changes in model behavior due to parameter variation). Sensitivity analysis establishes relationships between model predictions and problem parameters (i.e., initial concentrations, rate coefficients, etc). It helps determine the effects of uncertainties or changes in these input parameters on the predictions, which ultimately are compared with experimental observations in order to validate the model. Sensitivity analysis can identify parameters that must be determined accurately because of their large effect on the model predictions and parameters that need not be known with great precision because they have little or no effect on the solution. This capability may prove to be important in optimizing the design of experiments, thereby reducing the use of animals. This approach can be applied to study the metabolic effects of reduced oxygen delivery to cardiac muscle due to local myocardial ischemia and the effects of acute hypoxia on brain metabolism. Other important applications of sensitivity analysis include identification of quantitatively relevant pathways and biochemical species within an overall mechanism, when examining the effects of a genetic anomaly or pathological state on energetic system components and whole system behavior.

Radhakrishnan, Krishnan↗
DOE OSTI2024

Quantum Drude oscillators coupled with Coulomb potential as an efficient model for bonded and non-covalent interactions in atomic dimers

The quantum Drude oscillator (QDO) model has been widely used as an efficient surrogate to describe the electric response properties of matter as well as long-range interactions in molecules and materials. Most commonly, QDOs are coupled within the dipole approximation so that the Hamiltonian can be exactly diagonalized, which forms the basis for the many-body dispersion method [Phys. Rev. Lett. 108, 236402 (2012)]. The dipole coupling is efficient and allows us to study non-covalent many-body effects in systems with thousands of atoms. However, there are two limitations: (i) the need to regularize the interaction at short distances with empirical damping functions and (ii) the lack of multipolar effects in the coupling potential. In this work, we convincingly address both limitations of the dipole-coupled QDO model by presenting a numerically exact solution of the Coulomb-coupled QDO model by means of quantum Monte Carlo methods. We calculate the potential-energy surfaces of homogeneous QDO dimers, analyzing their properties as a function of the three tunable parameters: frequency, reduced mass, and charge. We study the coupled-QDO model behavior at short distances and show how to parameterize this model to enable an effective description of chemical bonds, such as the covalent bond in the H2 molecule.

Chemistry↗
NASA NTRS1992

Symbolic discrete event system specification

Extending discrete event modeling formalisms to facilitate greater symbol manipulation capabilities is important to further their use in intelligent control and design of high autonomy systems. An extension to the DEVS formalism that facilitates symbolic expression of event times by extending the time base from the real numbers to the field of linear polynomials over the reals is defined. A simulation algorithm is developed to generate the branching trajectories resulting from the underlying nondeterminism. To efficiently manage symbolic constraints, a consistency checking algorithm for linear polynomial constraints based on feasibility checking algorithms borrowed from linear programming has been developed. The extended formalism offers a convenient means to conduct multiple, simultaneous explorations of model behaviors. Examples of application are given with concentration on fault model analysis.

Zeigler, Bernard P.↗
DOE OSTI2023

On the applicability of various levels of detail for occupant behavior representation and modeling in building performance simulation

Occupant behavior (OB) is one of the significant sources of uncertainty in building performance simulation. While OB modeling has received increased attention in the past decade, research on the degree of granularity or level of detail (LoD) required for representing occupants is still in the nascent stages. This paper analyzes the modeling and applicability of three LoDs to represent occupants in building performance assessment. A medium-sized prototype office building located in Chicago, Illinois is used as the simulation case study. Ten occupant-centric attributes are adopted to develop the LoDs for OB representation. We first demonstrate the different modeling approaches required for simulating the three fidelity levels. Later, we illustrate the suitability of the developed LoDs in supporting six building performance use cases across different lifecycle stages. Furthermore, this study intends to provide guidance for the building simulation community on appropriate OB representation to support various use cases.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Functionally Assembled Terrestrial Ecosystem Simulator (FATES) for Hurricane Disturbance and Recovery

Tropical cyclones are an important cause of forest disturbance, and major storms caused severe structural damage and elevated tree mortality in coastal tropical forests. Model capabilities that can be used to understand post-hurricane forest recovery are still limited. We use a vegetation demography model, the Functionally Assembled Terrestrial Ecosystem Simulator, coupled with the Energy Exascale Earth System Model Land Model (ELM-FATES) to study the processes and the key factors regulating post-hurricane forest recovery. We implemented hurricane-induced forest damage, including defoliation, structural biomass reduction, and tree mortality, performed ensemble model simulations, and used random forest feature importance. For the simulation in the Luquillo Experimental Forest, Puerto Rico, we identified factors controlling the post-hurricane forest recovery, and quantified the sensitivity of key model parameters to the post-hurricane forest recovery. The results indicate a tendency for the Bisley forests to shift toward the light demanding plant functional type (PFT) when the pre-hurricane biomass between the light demanding and shade tolerant PFTs is nearly equal and forests experience hurricane disturbance with mortality >60% for both the two PFTs. Under more realistic conditions where the shade tolerant PFT is initially dominant, mortality >80% is required for a shift toward dominance of the light demanding PFT at Bisley. Hurricane mortality and background mortality are the two major factors regulating post-hurricane forest recovery in simulations. This research improves understanding of the ELM-FATES model behavior associated with hurricane disturbance and provides guidance for dynamic vegetation model development in representing hurricane induced forest damage with varied intensities.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2021

Cutting out the Middleman: Calibrating and Validating a Dynamic Vegetation Model (ED2-PROSPECT5) Using Remotely Sensed Surface Reflectance

Canopy radiative transfer is the primary mechanism by which models relate vegetation composition and state to the surface energy balance, which is important to light- and temperature-sensitive plant processes as well as understanding land–atmosphere feedbacks. In addition, certain parameters (e.g., specific leaf area, SLA) that have an outsized influence on vegetation model behavior can be constrained by observations of shortwave reflectance, thus reducing model predictive uncertainty. Importantly, calibrating against radiative transfer outputs allows models to directly use remote sensing reflectance products without relying on highly derived products (such as MODIS leaf area index) whose assumptions may be incompatible with the target vegetation model and whose uncertainties are usually not well quantified. Here, we created the EDR model by coupling the two-stream representation of canopy radiative transfer in the Ecosystem Demography model version 2 (ED2) with a leaf radiative transfer model (PROSPECT-5) and a simple soil reflectance model to predict full-range, high-spectral-resolution surface reflectance that is dependent on the underlying ED2 model state. We then calibrated this model against estimates of hemispherical reflectance (corrected for directional effects) from the NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and survey data from 54 temperate forest plots in the northeastern United States. The calibration significantly reduced uncertainty in model parameters related to leaf biochemistry and morphology and canopy structure for five plant functional types. Using a single common set of parameters across all sites, the calibrated model was able to accurately reproduce surface reflectance for sites with highly varied forest composition and structure. However, the calibrated model's predictions of leaf area index (LAI) were less robust, capturing only 46 % of the variability in the observations. Comparing the ED2 radiative transfer model with another two-stream soil–leaf–canopy radiative transfer model commonly used in remote sensing studies (PRO4SAIL) illustrated structural errors in the ED2 representation of direct radiation backscatter that resulted in systematic underestimation of reflectance. In addition, we also highlight that, to directly compare with a two-stream radiative transfer model like EDR, we had to perform an additional processing step to convert the directional reflectance estimates of AVIRIS to hemispherical reflectance (also known as “albedo”). In future work, we recommend that vegetation models add the capability to predict directional reflectance, to allow them to more directly assimilate a wide range of airborne and satellite reflectance products. We ultimately conclude that despite these challenges, using dynamic vegetation models to predict surface reflectance is a promising avenue for model calibration and validation using remote sensing data.

Alexey N Shiklomanov↗
NASA NTRS2015

Near Earth Asteroid Characteristics for Asteroid Threat Assessment

Information about the physical characteristics of Near Earth Asteroids (NEAs) is needed to model behavior during atmospheric entry, to assess the risk of an impact, and to model possible mitigation techniques. The intrinsic properties of interest to entry and mitigation modelers, however, rarely are directly measureable. Instead we measure other properties and infer the intrinsic physical properties, so determining the complete set of characteristics of interest is far from straightforward. In addition, 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. We will provide an assessment of the current state of knowledge about the physical characteristics of importance to asteroid threat assessment. In addition, an ongoing effort to collate NEA characteristics into a readily accessible database for use by the planetary defense community will be discussed.

Atmospheric↗