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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Integrated Model of the Eye/Optic Nerve Head Biomechanical Environment

Visual Impairment and Intracranial Pressure (VIIP) syndrome is a concern for long-duration space flight. Previously, it has been suggested that ocular changes observed in VIIP syndrome are related to the cephalad fluid shift that results in altered fluid pressures [1]. We are investigating the impact of changes in intracranial pressure (ICP) using a combination of numerical models, which simulate the effects of various environment conditions, including finite element (FE) models of the posterior eye. The specific interest is to understand how altered pressures due to gravitational changes affect the biomechanical environment of tissues of the posterior eye and optic nerve sheath. METHODS: Additional description of the numerical modeling is provided in the IWS abstract by Nelson et al. In brief, to simulate the effects of a cephalad fluid shift on the cardiovascular and ocular systems, we utilized a lumped-parameter compartment model of these systems. The outputs of this lumped-parameter model then inform boundary conditions (pressures) for a finite element model of the optic nerve head (Figure 1). As an example, we show here a simulation of postural change from supine to 15 degree head-down tilt (HDT), with primary outcomes being the predicted change in strains at the optic nerve head (ONH) region, specifically in the lamina cribrosa (LC), retrolaminar optic nerve, and prelaminar neural tissue (PLNT). The strain field can be decomposed into three orthogonal components, denoted as the first, second and third principal strains. We compare the peak tensile (first principal) and compressive (third principal) strains, since elevated strain alters cell phenotype and induces tissue remodeling. RESULTS AND CONCLUSIONS: Our lumped-parameter model predicted an IOP increase of c. 7 mmHg after 21 minutes of 15 degree HDT, which agreed with previous reports of IOP in HDT [1]. The corresponding FEM simulations predicted a relative increase in the magnitudes of the peak tensile and compressive strains in the lamina cribrosa of 42 and 43, respectively (Fig. 2). The corresponding changes in the optic nerve strains were 17 and 39, while in the PLNT they were 47 and 43. These magnitudes of relative elevations in peak strains may induce a phenotypic response in resident mechano-responsive resident cells [2]. This approach may be expanded to investigate other environmental changes (e.g. parabolic flight). Through our VIIP SCHOLAR project, we will validate and improve these integrated models by measuring patient-specific changes in optic nerve sheath geometry in patients with idiopathic intracranial hypertension before and after lumbar puncture and CSF removal.

biomechanics↗
NASA NTRS2005

New Integrated Modeling Capabilities: MIDAS' Recent Behavioral Enhancements

The Man-machine Integration Design and Analysis System (MIDAS) is an integrated human performance modeling software tool that is based on mechanisms that underlie and cause human behavior. A PC-Windows version of MIDAS has been created that integrates the anthropometric character "Jack (TM)" with MIDAS' validated perceptual and attention mechanisms. MIDAS now models multiple simulated humans engaging in goal-related behaviors. New capabilities include the ability to predict situations in which errors and/or performance decrements are likely due to a variety of factors including concurrent workload and performance influencing factors (PIFs). This paper describes a new model that predicts the effects of microgravity on a mission specialist's performance, and its first application to simulating the task of conducting a Life Sciences experiment in space according to a sequential or parallel schedule of performance.

Gore, Brian F.↗
DOE OSTI2017

An integrated modelling framework to assess long-term impacts of water management strategies steering soil subsidence in peatlands

Around the world many peatlands are managed unsustainably. Drainage of the peat causes soil subsidence and a range of negative societal impacts. Integrated strategies are required to ensure more sustainable long-term settings, based on impact assessment models that simulate the interrelated dynamics of water management and soil subsidence, and determine the spatial and temporal range of societal impacts. This paper presents an integrated modelling framework that meets these requirements. We used the framework to assess the impacts of a range of water management strategies in Dutch peatlands. Average soil subsidence rates were shown to range from 0.6 to 4.5 mm·y{sup −1}, resulting in marked differences in societal impacts that affect stakeholders unequally. Moreover, the impacts on real estate damage and water system maintenance revealed inverse trends that result in increasingly unbalanced cost-benefit ratios. The generated insights led the regional water authority to change their current water management strategy, preventing unsustainable future developments. We find the results relevant for improving stakeholders' awareness of long-term impacts of management strategies, and making negotiation processes on goals, means, and possible future pathways more transparent. - Highlights: •We developed an integrated modelling framework to support peatland management. •We used the case of Dutch peatlands to illustrate the added value of the framework. •Spatial patterns and temporal trends show how stakeholders are affected unequally. •The results were used to improve water management strategies.

02 PETROLEUM↗
NASA NTRS2012

NASA Integrated Model Centric Architecture (NIMA) Model Use and Re-Use

This whitepaper accepts the goals, needs and objectives of NASA's Integrated Model-centric Architecture (NIMA); adds experience and expertise from the Constellation program as well as NASA's architecture development efforts; and provides suggested concepts, practices and norms that nurture and enable model use and re-use across programs, projects and other complex endeavors. Key components include the ability to effectively move relevant information through a large community, process patterns that support model reuse and the identification of the necessary meta-information (ex. history, credibility, and provenance) to safely use and re-use that information. In order to successfully Use and Re-Use Models and Simulations we must define and meet key organizational and structural needs: 1. We must understand and acknowledge all the roles and players involved from the initial need identification through to the final product, as well as how they change across the lifecycle. 2. We must create the necessary structural elements to store and share NIMA-enabled information throughout the Program or Project lifecycle. 3. We must create the necessary organizational processes to stand up and execute a NIMA-enabled Program or Project throughout its lifecycle. NASA must meet all three of these needs to successfully use and re-use models. The ability to Reuse Models a key component of NIMA and the capabilities inherent in NIMA are key to accomplishing NASA's space exploration goals. 11

Conroy, Mike↗
NASA NTRS2008

Integrated Modeling Framework

This document is a chart showing the inputs to and outputs from various parts of the integrated climate model.

Luvall, Jeffrey C.↗
DOE OSTI2020

Mitigating energy demand sector emissions: The integrated modelling perspective

Mitigating carbon emissions in the current energy system will require fundamental changes of both the energy supply and the energy demand sectors. Previous global model-based analyses, however, have focused mostly on energy supply transformations, while the energy demand sector changes are less well understood. In this study, this knowledge gap is addressed by analysing in detail the projected future energy demand projections, and the required demand-side changes to reach stringent mitigation targets using a suite of integrated assessment models. We examine industry, transport and buildings sector pathways across four models and three different reference scenarios from the Shared-Socioeconomic Pathway framework which is used as a set of common future perspectives by the climate research community. The demand side mitigation efforts are compared to a more detailed, sector-specific, technology-oriented assessments of abatement potential based on a literature review for the year 2030. The results indicate that strong emission growth in the industry and transport sector can be attributed to increasing final energy per capita and population growth. In the stringent mitigation scenarios energy efficiency, electrification and switching to low carbon fuel are all required in the short term. In the green growth SSP1 scenario the required emission reduction is significantly less than other scenarios showing that the demand growth and the technology development largely affects the sectors’ mitigation challenge. The technology assessment estimates that in particular in the transport and buildings sector there is a higher potential to reduce demand-side emissions through energy efficiency improvements than currently envisioned in the integrated assessment models.

Edelenbosch, Oreane Y.↗
DOE OSTI2018

Integrated Model, Batch and Domain Parallelism in Training Neural Networks

We propose a new integrated method of exploiting model, batch and domain parallelism for the training of deep neural networks (DNNs) on large distributed-memory computers using minibatch stochastic gradient descent (SGD). Our goal is to find an efficient parallelization strategy for a fixed batch size using $P$ processes. Our method is inspired by the communication-avoiding algorithms in numerical linear algebra. We see $P$ processes as logically divided into a $P_r \times P_c$ grid where the $P_r$ dimension is implicitly responsible for model/domain parallelism and the $P_c$ dimension is implicitly responsible for batch parallelism. In practice, the integrated matrix-based parallel algorithm encapsulates these types of parallelism automatically. We analyze the communication complexity and analytically demonstrate that the lowest communication costs are often achieved neither with pure model nor with pure data parallelism. We also show how the domain parallel approach can help in extending the theoretical scaling limit of the typical batch parallel method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Setting the System Boundaries of “Energy for Water” for Integrated Modeling

Many studies over the last two decades have addressed the “water-energy nexus,” generally defined as the inter-dependency between water and energy in their supply, processing, distribution, and use. The research community currently disaggregates the water-energy nexus into two components: “water for energy” and “energy for water.” While there seems to be clear consensus on the definition of “water for energy”—that is, water required for the extraction, processing, and transformation of energy as well as the irrigation of bioenergy—there has been less agreement on the definition and system boundaries of “energy for water.” Here we represent six integrated assessment modeling teams presently incorporating the hydrologic system and water demands into existing global models of energy, agriculture, land use, and climate. In this article, we propose system boundaries of “energy for water” that are appropriate for integrated energy and water modeling, and introduce a third category of processes that are relevant for the water-energy nexus, but that are not logically classified as either “water for energy” or “energy for water.”

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Modeling Integrated Electricity and Natural Gas Systems Using Co-Simulation

One approach for modeling natural gas and electricity networks as integrated systems is co-simulation, which involves separating a single model into subproblems that are solved iteratively, with coupling information passed between then. Although a fully integrated problem might be more direct, co-simulation offers advantages in that it can sometimes be more computationally tractable, and can also leverage existing simulation tools to represent the subproblems. Here we present a framework for co-simulation of natural gas and electricity networks using the HELICS tool. We provide validation of the co-simulation approach by comparing results with a fully integrated approach that uses the same simulation tool, finding that the two approaches provide identical results for a range of test cases. We then present results from natural gas and electricity network co-simulation case study of the Colorado Front Range, with an evaluation of the present-day system and also a future system with higher shares of renewable power. The presentation will close with a discussion on future avenues of work for co-simulation of gas and power networks.

co-simulation↗
DOE OSTI2025

Integrated Modeling Driven Evaluation of Opportunities for Climate‐Resilient Perennial Biomass Crop Plantings in Flood‐Prone Agricultural Landscapes

Adapting to future climate change in flood-prone landscapes will require climate-resilient agricultural systems. Planting perennial crops, like switchgrass and willow, along river corridors can mitigate future flooding while supporting bioenergy markets. We developed an integrated assessment linking climate, hydrologic, and inundation model results to assess future flood risk to river-adjacent agricultural lands in the Mid-Atlantic Region (MAR) and explore this opportunity. We produced ensemble streamflow projections for every MAR stream using a hydrologic model driven by a suite of downscaled and bias-corrected Coupled Model Intercomparison Project Phase 6 climate projections. We then conducted high-resolution inundation mapping based on projected flood frequencies for baseline and future periods. Results show that in the near-term future, at least two-thirds of the streams will experience 100-year floods more severe than the baseline 200-year floods. Riparian zones are projected to face a median rise of inundation by 9.5%–24.1%. Results show that there is an opportunity to mitigate flooding in over half of MAR's counties with the quantities of switchgrass and willow plantings anticipated for mature bioenergy markets, even under the most extreme (200-year) flood events. Our integrated modeling framework can guide similar regions to evaluate opportunities for flood-resilient agricultural systems under climate change.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2014

Using Ensemble Short-Term Initialized Coupled NASA GEOS5 Climate Model Integrations to Study Convective Bias Growth

The representation of convective processes, particularly deep convection in the tropics, remains a persistent problem in climate models. In fact structural biases in the distribution of tropical rainfall in the CMIP5 models is hardly different than that of the CMIP3 versions. Given that regional climate change at higher latitudes is sensitive to the configuration of tropical forcing, this persistent bias is a major issue for the credibility of climate change projections. In this study we use model output from integrations of the NASA Global Earth Observing System Five (GEOS5) climate modeling system to study the evolution of biases in the location and intensity of convective processes. We take advantage of a series of hindcast experiments done in support of the US North American Multi-Model Ensemble (NMME) initiative. For these experiments a nine-month forecast using a coupled model configuration is made approximately every five days over the past 30 years. Each forecast is started with an updated analysis of the ocean, atmosphere and land states. For a given calendar month we have approximately 180 forecasts with daily means of various quantities. These forecasts can be averaged to essentially remove "weather scales" and highlight systematic errors as they evolve. Our primary question is to ask how the spatial structure of daily mean precipitation over the tropics evolves from the initial state and what physical processes are involved. Errors in parameterized convection, various water and energy fluxes and the divergent circulation are found to set up on fast time scales (order five days) compared to errors in the ocean, although SST changes can be non-negligible over that time. For the month of June the difference between forecast day five versus day zero precipitation looks quite similar to the difference between the June precipitation climatology and that from the Global Precipitation Climatology Project (GPCP). We focus much of our analysis on the influence of SST gradients, associated PBL baroclinicity enabled by turbulent mixing, the ensuing PBL moisture convergence, and how changes in these processes relate to convective precipitation bias growth over this short period.

Cohen, Charlie↗
DOE OSTI2024

An Open-Source Framework for Characterizing Urban Energy Models: Integrating Top-Down and Bottom-Up Methods to Predict Residential Buildings Characteristics: Preprint

Bottom-up urban energy models are crucial for understanding current energy use patterns and informing design strategies. However, accurately characterizing these models to represent different communities remains a challenge due to the extensive data needed for simulating existing energy use behavior. This data includes information related to human activities and building characteristics, all of which correlate with socioeconomic factors. To overcome this challenge, we developed an automated framework that utilizes both top-down and bottom-up data, to predict unknown building and occupant characteristics that are needed for more accurate and equitable modeling and analytics. Our framework, integrated into the URBANopt district energy modeling platform, uses statistical data models from ResStock. URBANopt models co-located buildings and neighborhoods. At this scale there are data gaps in building characteristic data, such as materials, insulation, occupancy, income, and energy usage of the buildings. To address this data gap, we use ResStock data, representative at the census tract scale, and develop machine-learning and deeplearning techniques to disaggregate it to individual buildings. By mapping unique occupant, building and economic properties to URBANopt energy models, we gain detailed insights into the variability of building energy use across different neighborhoods. This insight helps deploy technologies for co-located buildings and supports targeted upgrades for communities with unique economic and demographic characteristics, ensuring energy equity. Accurate characterization of energy models allows us to develop equitable strategies tailored to diverse neighborhoods, whether underserved or affluent. Our automated framework streamlines energy modeling and provides a reliable tool for building energy characterization.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗
NASA NTRS2009

ARTEMIS: Ares Real Time Environments for Modeling, Integration, and Simulation

This slide presentation reviews the use of ARTEMIS in the development and testing of the ARES launch vehicles. Ares Real Time Environment for Modeling, Simulation and Integration (ARTEMIS) is the real time simulation supporting Ares I hardware-in-the-loop (HWIL) testing. ARTEMIS accurately models all Ares/Orion/Ground subsystems which interact with Ares avionics components from pre-launch through orbit insertion The ARTEMIS System integration Lab, and the STIF architecture is reviewed. The functional components of ARTEMIS are outlined. An overview of the models and a block diagram is presented.

Hughes, Ryan↗
DOE OSTI2019

Integrated model construction for CO2-EOR monitoring via charged-wellbore casing controlled-source electromagnetics

We present a method for the integrated development of 3D electrical conductivity models for CO2-EOR monitoring with charged wellbore casing controlled-source electromagnetics (CWC-CSEM). The model is constructed through the multiphysics integration of reservoir simulation, seismic, borehole resistivity, and transient EM (TEM) data. The process is performed in two stages. First, a large background conductivity model is constructed from the combination of seismic, borehole, and TEM data. Second, a more detailed and dynamic component of the model is created within the production interval by converting the reservoir simulation parameters to conductivity through Archie’s equation. In this presentation, we demonstrate the complete workflow for building these 3D conductivity site models that can be updated throughout production using the Bell Creek oil field as an example. We then show application of the developed site model to simulating the predicted CWC-CSEM data as one step in the larger problem of reservoir imaging and monitoring of injected CO2 during enhanced oil recovery.

CO2, Sequestration, Monitoring, time-lapse, reserv↗
DOE OSTI2017

The molecular architecture of the yeast spindle pole body core determined by Bayesian integrative modeling

Microtubule-organizing centers (MTOCs) form, anchor, and stabilize the polarized network of microtubules in a cell. The central MTOC is the centrosome that duplicates during the cell cycle and assembles a bipolar spindle during mitosis to capture and segregate sister chromatids. Yet, despite their importance in cell biology, the physical structure of MTOCs is poorly understood. Here we determine the molecular architecture of the core of the yeast spindle pole body (SPB) by Bayesian integrative structure modeling based on in vivo fluorescence resonance energy transfer (FRET), small-angle x-ray scattering (SAXS), x-ray crystallography, electron microscopy, and two-hybrid analysis. The model is validated by several methods that include a genetic analysis of the conserved PACT domain that recruits Spc110, a protein related to pericentrin, to the SPB. The model suggests that calmodulin can act as a protein cross-linker and Spc29 is an extended, flexible protein. The model led to the identification of a single, essential heptad in the coiled-coil of Spc110 and a minimal PACT domain. It also led to a proposed pathway for the integration of Spc110 into the SPB.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2004

Integrated Modeling Approach for the Terrestrial Planet Finder Mission

Because of the complexity of the Terrestrial Planet Finder (TPF) design concepts, the project will rely heavily on the use of engineering and science simulations to predict on-orbit performance. Furthermore, current understanding of these missions indicates that the 3m to 8m class optical systems need to be as stable as picometers in wavefront and sub-milli arcsec in pointing. These extremely small requirements impose on the models a level of predictive accuracy heretofore never achieved, especially in the area of microgravity effects, material property accuracy, thermal solution convergence, and all other second order modeling effects typically ignored. New modeling tools and analysis paradigms are developed which emphasize computational accuracy and fully integrated analytical simulations. The process is demonstrated on sample problems using the TPF Coronagraph design concept. The TPF project is also planning a suite of testbeds through which various aspects of the models and simulations will be verified.

terrestrial planet finder↗
DOE OSTI2026

Integrative Modeling and Analysis of Fungal Central Carbon Metabolism

Over a thousand fungal genomes have been sequenced, yet manually curated genome-scale metabolic models (GEMs) are available for only a limited number of species. Moreover, these models have often been developed independently, leading to inconsistencies in namespaces, compartment definitions, and pathway representations that hinder comparative analysis, the systematic reuse of prior curation efforts, and the integration of consolidated metabolic knowledge. Here, we present the Consolidated Fungal Core Metabolism Model (CFCMM), constructed by integrating thirteen published fungal models spanning Ascomycota, Mucoromycota, and both Crabtree-positive and Crabtree-negative yeasts. We harmonized metabolites and reactions into a non-redundant shared ModelSEED ontological space, standardized compartmentalization, and refined gene–protein–reaction (GPR) rules. Using pathway-level visualization and systematic gap detection, we further improved the integrated network through literature-guided curation to correct stoichiometry, stereospecificity, and pathway architecture. Orthologous protein family reconstruction and functional annotation workflows were used to validate and inform GPR associations, with particular emphasis on ambiguous enzyme superfamilies and membrane-associated components. Using the resulting CFCMM, we built high-quality central carbon core models for each fungus and performed flux balance analysis to quantify ATP-yield variation under aerobic and anaerobic conditions, explicitly evaluating scenarios driven by differences in electron transport chain (ETC) composition. Simulations reproduced the expected fermentative yield of approximately 2 mmol ATP per mmol glucose under anaerobic conditions and separated the thirteen fungi into two bioenergetic groups under aerobic respiration based on Complex I status, with predicted yields of approximately 30 versus 22 mmol ATP per mmol glucose. Forcing flux through the alternative oxidase bypass further reduced ATP yields to approximately 12 and 4 mmol ATP per mmol glucose in Complex I-containing and Complex I-lacking fungi, respectively. Collectively, this work provides a manually curated, ModelSEED-consistent, and extensible fungal core metabolic template, deployed in DOE KBase as a resource for automated reconstruction of central carbon core models from any sequenced fungal genome. In addition, the CFCMM provides modular components for developing GEMs with more accurate energy predictions and enables robust comparative analyses of fungal bioenergetics and core metabolic diversity

59 BASIC BIOLOGICAL SCIENCES↗