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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Membrane-based carbon capture process optimization using CFD modeling

Carbon capture is a promising option to mitigate CO2 emissions from existing coal-fired power plants, cement and steel industries, and petrochemical complexes. Among the available technologies, membrane-based carbon capture presents the lowest energy consumption, operating costs, and carbon footprint. In addition, membrane processes have important operational flexibility and response times. On the other hand, the major challenges to widespread application of this technology are related to reducing capital costs and improving membrane stability and durability. To upscale the technology into stacked flat sheet configurations, high fidelity computational fluid dynamics (CFD) that describes the separation process accurately are required. High fidelity simulations have been shown to be effective in studying the complex transport phenomena in membrane systems. In addition, obtaining high CO2 recovery percentages and product purity requires a multi-stage membrane process, where the optimal network configuration of the membrane modules must be studied in a systematic way. In order to address the design problem at process scale, we formulate a superstructure for the membrane-based carbon capture, including up to three separation stages. In the formulation of the optimization problem, we include reduced models, based on rigorous CFD simulations of the membrane modules. Numerical results indicate that the optimal design includes three membrane stages, and the capture cost is 45.4 $/t-CO2.

Pedrozo, Hector A.↗
DOE OSTI2022

Porting a fast-running wildfire plume model for use in national security and climate applications

In this project, the code for the fast-running Freitas wildfire plume model was successfully ported into the NARAC system, creating an operations-ready capability for predicting the transport of hazardous smoke from large wildfires. “Porting” refers to copying a section of code from one software package to another while accounting for unique dependencies in each software package. In this case, the code was ported from the Weather Research and Forecasting (WRF) Model, which is used extensively by the project team. To verify correct implementation, model results from the updated NARAC system were compared to those from WRF and the High-Resolution Rapid Refresh (HRRR) forecast model, which also employs the Freitas scheme. The NARAC User Interface (UI) and code documentation were also updated to include the new wildfire plume option, and a wildfire case was added to the NARAC test suite. The code was used in a real-time, semi-operational setup to predict smoke transport during the Cerro Pelado fire near Los Alamos National Laboratory in May 2022. The Freitas plume model was also tested for LLNL climate applications. Although the code was not ported into the Energy Exascale Earth System Model (E3SM), it was tested offline using E3SM atmospheric inputs, and results were compared to existing high-resolution plume predictions from large-eddy simulations in WRF. The code implementation and testing completed during this project will enable future work predicting smoke transport from large wildfires in LLNL national security and climate mission spaces.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2015

Environment Modeling Using Runtime Values for JPF-Android

Software applications are developed to be executed in a specific environment. This environment includes external native libraries to add functionality to the application and drivers to fire the application execution. For testing and verification, the environment of an application is simplified abstracted using models or stubs. Empty stubs, returning default values, are simple to generate automatically, but they do not perform well when the application expects specific return values. Symbolic execution is used to find input parameters for drivers and return values for library stubs, but it struggles to detect the values of complex objects. In this work-in-progress paper, we explore an approach to generate drivers and stubs based on values collected during runtime instead of using default values. Entry-points and methods that need to be modeled are instrumented to log their parameters and return values. The instrumented applications are then executed using a driver and instrumented libraries. The values collected during runtime are used to generate driver and stub values on- the-fly that improve coverage during verification by enabling the execution of code that previously crashed or was missed. We are implementing this approach to improve the environment model of JPF-Android, our model checking and analysis tool for Android applications.

Verification↗
DOE OSTI2024

Membrane-based Carbon Capture Process Optimization using CFD Modeling

Carbon capture is a promising option to mitigate CO2 emissions from existing coal-fired power plants, cement and steel industries, and petrochemical complexes. Among the available technologies, membrane-based carbon capture presents the lowest energy consumption, operating costs, and carbon footprint. In addition, membrane processes have important operational flexibility and response times. On the other hand, the major challenges to widespread application of this technology are related to reducing capital costs and improving membrane stability and durability. To upscale the technology into stacked flat sheet configurations, high fidelity computational fluid dynamics (CFD) that describes the separation process accurately are required. High fidelity simulations have been shown to be effective in studying the complex transport phenomena in membrane systems. In addition, obtaining high CO2 recovery percentages and product purity re-quires a multi-stage membrane process, where the optimal network configuration of the mem-brane modules must be studied in a systematic way. In order to address the design problem at process scale, we formulate a superstructure for the membrane-based carbon capture, including up to three separation stages. In the formulation of the optimization problem, we include reduced models, based on rigorous CFD simulations of the membrane modules.

Pedrozo, Hector A.↗
DOE OSTI2014

Land-Use History and Contemporary Management Inform an Ecological Reference Model for Longleaf Pine Woodland Understory Plant Communities.

Ecological restoration is frequently guided by reference conditions describing a successfully restored ecosystem; however, the causes and magnitude of ecosystem degradation vary, making simple knowledge of reference conditions insufficient for prioritizing and guiding restoration. Ecological reference models provide further guidance by quantifying reference conditions, as well as conditions at degraded states that deviate from reference conditions. Many reference models remain qualitative, however, limiting their utility. We quantified and evaluated a reference model for southeastern U.S. longleaf pine woodland understory plant communities. We used regression trees to classify 232 longleaf pine woodland sites at three locations along the Atlantic coastal plain based on relationships between understory plant community composition, soils lol(which broadly structure these communities), and factors associated with understory degradation, including fire frequency, agricultural history, and tree basal area. To understand the spatial generality of this model, we classified all sites together. and for each of three study locations separately. Both the regional and location-specific models produced quantifiable degradation gradients–i.e., progressive deviation from conditions at 38 reference sites, based on understory species composition, diversity and total cover, litter depth, and other attributes. Regionally, fire suppression was the most important degrading factor, followed by agricultural history, but at individual locations, agricultural history or tree basal area was most important. At one location, the influence of a degrading factor depended on soil attributes. We suggest that our regional model can help prioritize longleaf pine woodland restoration across our study region; however, due to substantial landscape-to-landscape variation, local management decisions should take into account additional factors (e.g., soil attributes). Our study demonstrates the utility of quantifying degraded states and provides a series of hypotheses for future experimental restoration work. More broadly, our work provides a framework for developing and evaluating reference models that incorporate multiple, interactive anthropogenic drivers of ecosystem degradation.

Ecological Reference Models↗
DOE OSTI2024

Explaining Neural Spike Activity for Simulated Bio-plausible Network through Deep Sequence Learning

With significant improvements in large-scale simulations of brain models, there is a growing need to develop tools for rapid analysis and interpreting the simulation results. In this work, we explore the potential of sequential deep learning models to understand and explain the network dynamics among the neurons extracted from a large-scale neural simulation in STACS (Simulation Tool for Asynchronous Cortical Stream). Our method employs a representative neuroscience model that abstracts the cortical dynamics with a reservoir of randomly connected spiking neurons with a low stable spike firing rate throughout the simulation duration. We subsequently analyze the spike dynamics of the simulated spiking neural network through an autoencoder model and an attention-based mechanism.

Kulkarni, Shruti↗
DOE OSTI2016

A comparison of simple global kinetic models for coal devolatilization with the CPD model

Simulations of coal combustors and gasifiers generally cannot incorporate the complexities of advanced pyrolysis models, and hence there is interest in evaluating simpler models over ranges of temperature and heating rate that are applicable to the furnace of interest. In this paper, six different simple model forms are compared to predictions made by the Chemical Percolation Devolatilization (CPD) model. The model forms included three modified one-step models, a simple two-step model, and two new modified two-step models. These simple model forms were compared over a wide range of heating rates (5 × 10 3 to 10 6 K/s) at final temperatures up to 1600 K. Comparisons were made of total volatiles yield as a function of temperature, as well as the ultimate volatiles yield. Advantages and disadvantages for each simple model form are discussed. In conclusion, a modified two-step model with distributed activation energies seems to give the best agreement with CPD model predictions (with the fewest tunable parameters).

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2015

Evidence for the role of hydrogen in the stabilization of minority carrier lifetime in boron-doped Czochralski silicon

This study demonstrates that the presence of a hydrogen source during fast-firing is critical to the regeneration of B-O defects and that is it not a pure thermally based mechanism or due to plasma exposure. Boron-doped p-type wafers were fired with and without hydrogen-rich silicon nitride (SiN{sub x}:H) films present during the fast-firing process. After an initial light-induced degradation step, only wafers fired with the SiN{sub x}:H films present were found to undergo permanent and complete recovery of lifetime during subsequent illuminated annealing. In comparison, wafers fired bare, i.e., without SiN{sub x}:H films present during firing, were found to demonstrate no permanent recovery in lifetime. Further, prior exposure to hydrogen-rich plasma processing was found to have no impact on permanent lifetime recovery in bare-fired wafers. This lends weight to a hydrogen-based model for B-O defect passivation and casts doubt on the role of non-hydrogen species in the permanent passivation of B-O defects in commercial-grade p-type Czochralski silicon wafers.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Boosts in leaf-level photosynthetic capacity aid Pinus ponderosa recovery from wildfire

Forests mitigate climate change by sequestering massive amounts of carbon, but recent increases in wildfire activity are threatening carbon storage. Currently, our understanding of wildfire impacts on forest resilience and the mechanisms controlling post-fire recovery remains unresolved due to a lack of empirical data on mature trees in natural settings. Here, we quantify the physiological mechanisms controlling carbon uptake immediately following wildfire in mature individuals of ponderosa pine (Pinus ponderosa), a wide-spread and canopy-dominant tree species in fire-prone forests. While photosynthetic capacity was lower in burned than unburned trees due to an overall depletion of resources, we show that within the burned trees, photosynthetic capacity increases with the severity of damage. Our data reveal that boosts in the efficiency of carbon uptake at the leaf-level may compensate for whole-tree damage, including the loss of leaf area and roots. We further show that heightened photosynthetic capacity in remaining needles on burned trees may be linked with reduced water stress and leaf nitrogen content, providing pivotal information about post-fire physiological processes. Our results have implications for Earth system modeling efforts because measurements of species-level physiological parameters are used in models to predict ecosystem and landscape-level carbon trajectories. Finally, current land management practices do not account for physiological resilience and recovery of severely burned trees. Our results suggest premature harvest may remove individuals that may otherwise survive, irrevocably altering forest carbon balance.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Improved Biomass Cooking Stoves and Improved Stove Emission Equipment

In developing countries, there is an urgent need for access to safe, efficient, and more affordable cooking technologies. Nearly 2.5 billion people currently use an open fire or traditional cookstove to prepare their meals, and recent models predict that use of biomass for cooking will continue to be the dominant energy use in rural, resource-poor households through 2030. For these families, cooking poses serious risks to health, safety, and income. An alarming 4 million people, primarily women and children, die prematurely each year from indoor and outdoor exposure to the harmful emissions released by solid fuel combustion. Use of traditional stoves can also have a significant impact on deforestation and climate change. This dire situation creates a critical need for cookstoves that significantly and verifiably reduce fuel use and emissions in order to reach protective levels for human health and the environment. Additionally, advances in the scientific equipment needed to measure and monitor stove fuel use and emissions have not kept pace with the significant need within the industry. While several testing centers in the developed world may have hundred thousand-dollar emissions testing systems, organizations in the field have had little more than a thermometer, a scale, and subjective observations to quantify the performance of stove designs. There is an urgent need for easy-to-use, inexpensive, accurate, and robust stove testing equipment for use by laboratory and field researchers around the world. ASAT and their research partner, Aprovecho Research Center (ARC), have over thirty years of experience addressing these two needs, improved cookstoves and emissions monitoring equipment, with expertise spanning the full spectrum of development from conceptual design to product manufacturing and dissemination. This includes: 1) research, design, and verification of clean biomass cookstove technology and emissions monitoring equipment; 2) mass production of quality-controlled stove and emissions equipment at levels scalable to meet global demand; and 3) global distribution through a variety of channels and partners. ARC has been instrumental in designing and improving more than 100 stove designs over the past thirty years. In the last four years, ASAT and ARC have played a key role in the production and sales of over 200,000 improved stoves in the developed and developing world. The ARC-designed emissions equipment is currently used by researchers in laboratories and field studies on five continents. During Phase I of the DOE STTR grant, ASAT and ARC worked together to apply their wealth of product development experience towards creating the next generation of improved cookstoves and emissions monitoring equipment. Highlights of Phase I for the biomass cookstove project include 1) the development of several new stove technologies that reached the DOE 50/90 benchmark; 2) fabrication of new stove prototypes by ASAT’s manufacturing partner, Shengzhou Stove Manufacturing (SSM); 3) field testing of prototype stoves with consumers in Puerto Rico and the US; and 4) the selection of three stove prototypes for further development and commercialization during Phase II. Highlights of Phase I for the emissions monitoring equipment project include: 1) creation of a new emissions monitoring equipment product, the Laboratory Emissions Monitoring System (LEMS 2) the addition of gravimetric PM measurements to the stove testing systems to meet International Standards Organization criteria; 3) the addition of a CO{sub 2} sensor and wireless 3G capability to the IAP Meter; and 4) and the improvement of sensors and signal quality on all systems. Twelve Regional Testing and Knowledge Centers purchased this equipment during the Phase I project period.

09 BIOMASS FUELS↗
DOE OSTI2016

Techno-Economic Analysis of Integration of Low-Temperature Geothermal Resources for Coal-Fired Power Plants

Presented here are the results of a techno-economic (TEA) study of the potential for coupling low-grade geothermal resources to boost the electrical output from coal-fired power plants. This study includes identification of candidate 500 MW subcritical coal-fired power plants in the continental United States, followed by down-selection and characterization of the North Valmy generating station, a Nevada coal-fired plant. Based on site and plant characteristics, ASPEN Plus models were designed to evaluate options to integrate geothermal resources directly into existing processes at North Valmy. Energy outputs and capital costing are presented for numerous hybrid strategies, including integration with Organic Rankine Cycles (ORCs), which currently represent the primary technology for baseload geothermal power generation.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2019

Quantifying neural information content: a case study of the impact of hippocampal adult neurogenesis

Neural networks have an intrinsic information content encapsulated by neural firing behaviors and constituted by their neural encoding. Shannon entropy is a fundamental method to quantize the amount of information in a variety of sources such as communication channels. Many approaches have been devised to apply this sort of information measure to neurons with mixed success. However, doing so typically requires knowledge of the firing behavior probability distributions for the neurons of interest (whether modeled or recordings), and furthermore often is only applicable for single neurons and not ensembles. We have observed that conventional compression methods may help overcome some of the limiting factors of standard techniques and allows us to approximate information in neural data. To do so we have used compressibility as a measure of complexity in order to estimate entropy to quantitatively assess information content of neural ensembles.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Advancing coupled fire-atmosphere research with HIGRAD/FIRETEC (w20_firetec) (CY 2021 Institutional Computing Annual Progress Report) [Slides]

LANL’s HIGRAD and FIRETEC models were used in a multi-scale simulation framework to investigate impacts of small-scale fuel heterogeneities on large-scale Pyro-Cb formation. Forest structural diversity is found to increase canopy fire spread, and thus risk of tree mortality in FIRETEC simulations. Structural diversity is associated with an increase in ladder fuels, which facilitate fire spread into the canopy. Low-intensity fire burning in marginal conditions is highly sensitive to small perturbation in atmospheric turbulence. These results highlight predictive limitations of individual fire simulations, and emphasize the need for ensemble simulations, especially for low-intensity, prescribed fire.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Hydrogen Plus Other Alternative Fuels Risk Assessment Models (HyRAM+) Version 4.1 Technical Reference Manual

The HyRAM+ software toolkit provides a basis for conducting quantitative risk assessment and consequence modeling for hydrogen, methane, and propane systems. HyRAM+ is designed to facilitate the use of state-of-the-art models to conduct robust, repeatable assessments of safety, hazards, and risk. HyRAM+ integrates deterministic and probabilistic models for quantifying accident scenarios, predicting physical effects, characterizing hazards (thermal effects from jet fires, overpressure effects from delayed ignition), and assessing impacts on people. HyRAM+ is developed at Sandia National Laboratories to support the development and revision of national and international codes and standards, and to provide developed models in a publicly-accessible toolkit usable by all stakeholders. This document provides a description of the methodology and models contained in HyRAM+ version 4.1. The two most significant changes for HyRAM+ version 4.1 from HyRAM+ version 4.0 are direct incorporation of unconfined overpressure into the QRA calculations and modification of the models for cryogenic liquid flow through an orifice. In QRA mode, the user no longer needs to input peak overpressure and impulse values that were calculated separately; rather, the unconfined overpressure is estimated for the given system inputs, leak size, and occupant location. The orifice flow model now solves for the maximum mass flux through the orifice at constant entropy while conserving energy, which does not require a direct speed of sound calculation. This does not affect the mass flow for all-gaseous releases; the method results in the same speed of sound for choked flow. However, this method does result in a higher (and more realistic) mass flow rate for a given leak size for liquid releases than was previously calculated.

08 HYDROGEN↗
DOE OSTI2022

Study of Radiative Heat Transfer and Flow Physics from Medium-scale Methanol Pool Fire Simulations [Slides]

Analysis of methanol pool fire conducted as part of validation study for SIERRA/Fuego. Radiation model was effectively calibrated by modifying radiation model parameters for methanol. Computing integrated buoyancy flux, entrainment rate, and turbulent kinetic energy allowed for evaluation of less typical quantities in this validation study. Quantities were compared with experimental data or correlations and generally showed agreement. TKE needed fine mesh to be computed accurately. Predicted flame height less sensitive to variations in mixture fraction than temperature. Mixture fraction is a preferable threshold variable for this application.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Secondary organic aerosol (SOA) yields from NO 3 radical + isoprene based on nighttime aircraft power plant plume transects

Nighttime reaction of nitrate radicals ( NO 3 ) with biogenic volatile organic compounds (BVOC) has been proposed as a potentially important but also highly uncertain source of secondary organic aerosol (SOA). The southeastern United States has both high BVOC and nitrogen oxide ( NO x ) emissions, resulting in a large model-predicted NO 3 -BVOC source of SOA. Coal-fired power plants in this region constitute substantial NO x emissions point sources into a nighttime atmosphere characterized by high regionally widespread concentrations of isoprene. In this paper, we exploit nighttime aircraft observations of these power plant plumes, in which NO 3 radicals rapidly remove isoprene, to obtain field-based estimates of the secondary organic aerosol yield from NO 3 + isoprene. Observed in-plume increases in nitrate aerosol are consistent with organic nitrate aerosol production from NO 3 + isoprene, and these are used to determine molar SOA yields, for which the average over nine plumes is 9 % ( ±5 %). Corresponding mass yields depend on the assumed molecular formula for isoprene- NO 3 -SOA, but the average over nine plumes is 27 %( ±14 %), on average larger than those previously measured in chamber studies (12 %–14 % mass yield as Δ OA / Δ VOC after oxidation of both double bonds). Yields are larger for longer plume ages.This suggests that ambient aging processes lead more effectively to condensable material than typical chamber conditions allow. We discuss potential mechanistic explanations for this difference, including longer ambient peroxy radical lifetimes and heterogeneous reactions of NO 3 -isoprene gas phase products. As a result more in-depth studies are needed to better understand the aerosol yield and oxidation mechanism of NO 3 radical + isoprene, a coupled anthropogenic–biogenic source of SOA that may be regionally significant.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗