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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

An open source analysis framework for large-scale building energy modeling

Full integration of building energy modelling into the design and retrofit process has long been a goal of building scientists and practitioners. However, significant barriers still exist. Among them are the lack of available: (1) configurable technology stacks for performing both small- and large-scale analyses, (2) different classes of algorithms compatible with common design workflows, and (3) analysis tools for effectively visualizing large-scale simulation results. This article discusses the OpenStudio® Analysis Framework: a scalable analysis framework for building energy modelling that was developed to overcome the three barriers listed above. The framework is open-source and scalable to facilitate wider adoption and has a clearly defined application programming interface upon which other applications can be built. It runs on high-performance computing systems, within cloud infrastructure, and on laptops, and uses a common workflow to enable different classes of algorithms. Lessons learned from previous development efforts are also discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

The mobility of small vacancy/helium complexes in tungsten and its impact on retention in fusion-relevant conditions

Tungsten is a promising plasma facing material for fusion reactors. Despite many favorable properties, helium ions incoming from the plasma are known to dramatically affect the microstructure of tungsten, leading to bubble growth, blistering, and/or to the formation of fuzz. In order to develop mitigation strategies, it is essential to understand the atomistic processes that lead to bubble formation and subsequent microstructural changes. In this work, we use large-scale Accelerated Molecular Dynamics simulations to investigate small (N=1,2) V N He M vacancy/helium complexes, which serve as the nuclei for larger helium bubble growth, over timescales reaching into the milliseconds under conditions typical of the operation of fusion reactors. These complexes can interconvert between different I L V N+L He M variants via Frenkel pair nucleation (leading to the creation of a additional vacancy/interstitial pair) and annihilation events; sequences of these events can lead to net migration of these embryonic bubbles. The competition between nucleation and annihilation produces a very complex dependence of the diffusivity on the number of heliums. Finally, through cluster dynamics simulations, we show that diffusion of these complexes provides an efficient pathway for helium release at fluxes expected in fusion reactors, and hence that accounting for the mobility of these complexes is crucial.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Incorporation of metal nanoparticles into wood substrate and methods

Metal nanoparticles were incorporated into wood. Ionic liquids were used to expand the wood cell wall structure for nanoparticle incorporation into the cell wall structure. Nanoparticles of elemental gold or silver were found to be effective surface enhanced Raman spectroscopy (SERS) imaging contrast or sensing agents. Nanoparticles of elemental iron were found to be efficient microwave absorbers and caused localized heating for disrupting the integrity of the lignocellulosic matrix. Controls suggest that the localized heating around the iron nanoparticles reduces losses of cellulose in the form of water, volatiles and CO.sub.2. The ionic liquid is needed during the incorporation process at room temperature. The use of small amounts of ionic liquid combined with the absence of an ionic liquid purification step and a lower energy and water use are expected to reduce costs in an up-scaled pretreatment process.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2018

Hi-C2.1 Observations of Solar Jetlets at Edges of Network Lanes

We present high resolution (0.2”) high cadence (5s) extreme ultraviolet (EUV) observations of small-­scale jetlet-­like features and spicule-­like features observed with NASA’s High-­resolution Coronal Imager2.1 (Hi-C) during its 5‐min observing span. We investigate the magnetic setting of 4 on-disk jetlets and 2 on-­disk spicules by using high resolution 172A images from Hi-­‐C and EUV images from Solar Dynamics Observatory (SDO)/Atmospheric Imaging Assembly (AIA) and line-­of-­sight magnetograms from SDO/Helioseismic and Magnetic Imager (HMI). The jetlets and spicules are at edges of magnetic network lanes. From magnetograms co-­aligned with the Hi-­C and AIA images, we find that the jetlets stem from sites of likely flux cancelation between merging majority-polarity and weaker minority-­polarity flux, but in contrast to larger jetlets observed by IRIS some do not show obvious enhanced brightenings at their base. Based on the similarity of these observations of approx. 4 obvious Hi-­C small jetlets with our previous observations of 10 IRIS larger jetlets and approx. 30 coronal jets in quiet regions and coronal holes, we infer that flux cancelation is probably the essential process in the buildup and triggering of jetlets. Our observations suggest that network jetlet eruptions, large and small, are small-scale analogs of both larger-­scale coronal jet eruptions and the still-­larger-­scale eruptions that makemajor CMEs. For simplicitywe will use termjetlets for jetlet-­like features and spicules for spicule-­like features.

Panesar, Navdeep K.↗
DOE OSTI2026

A fast and robust computational modeling approach for density and shape predictions in powder metallurgy hot isostatic pressing

Powder metallurgy hot isostatic pressing (PM-HIP) is an advanced manufacturing process that produces near-net-shape parts with high material utilization and uniform microstructures. PM-HIP is frequently used for producing small-scale parts with complicated geometries and is potentially economical for producing large-scale parts. However, excessive post-HIP shape distortions can reduce its effectiveness and economic advantage, especially for larger parts. A PM-HIP computational model can predict and help mitigate these distortions. However, due to complex deformation mechanisms and thermo-mechanical coupling present in PM-HIP processes, these non-linear computational models sometimes become numerically unstable. The numerical instabilities in these models can lead to very slow convergence or no convergence at all, which often translates to slow and unreliable models. These limitations are more pronounced in large models with complicated geometries. Hence, in this work, an alternative modeling approach is presented that improves numerical stability and computational performance. The presented approach achieves these improvements through approximating the fully coupled thermo-mechanical PM-HIP model as a decoupled model and adding inertial damping to the model’s mechanical part. In conclusion, a comparison with the fully coupled model indicated a slight dip in prediction accuracy (<5% error) but significant improvements in numerical stability (>20 times larger time step size) and computational performance (5-10 times speed-up with less computational resource usage) when using the presented approach.

Hot isostatic pressing↗
NASA NTRS1993

Impact damage in filament wound composite bottles

Increasingly, composite materials are being used in advanced structural applications because of the significant weight savings they offer when compared to more traditional engineering materials. The higher cost of composites must be offset by the increased performance that results from reduced structural weight if these new materials are to be used effectively. At present, there is considerable interest in fabricating solid rocket motor cases out of composite materials, and capitalizing on the reduced structural weight to increase rocket performance. However, one of the difficulties that arises when composite materials are used is that composites can develop significant amounts of internal damage during low velocity impacts. Such low velocity impacts may be encountered in routine handling of a structural component like a rocket motor case. The ability to assess the reduction in structural integrity of composite motor cases that experience accidental impacts is essential if composite rocket motor cases are to be certified for manned flight. While experimental studies of the post-impact performance of filament wound composite motor cases haven been proven performed (2,3), scaling impact data from small specimens to full scale structures has proven difficult. If such a scaling methodology is to be achieved, an increased understanding of the damage processes which influence residual strength is required. The study described herein was part of an ongoing investigation of damage development and reduction of tensile strength in filament wound composites subjected to low velocity impacts. The present study, which focused on documenting the damage that develops in filament wound composites as a result of such impacts, included two distinct tasks. The first task was to experimentally assess impact damage in small, filament wound pressure bottles using x-ray radiography. The second task was to study the feasibility of using digital image processing techniques to assist in determining the 3-D distribution of damage from stereo x-ray pairs.

Highsmith, Alton L.↗
DOE OSTI2020

Stable Methane Isotopologues From Northern Lakes Suggest That Ebullition Is Dominated by Sub‐Lake Scale Processes

Abstract Stable isotopes have emerged as popular study targets when investigating emission of methane (CH 4 ) from lakes. Yet little is known on how isotopic patterns conform to variations in emission magnitudes—a highly relevant question. Here, we present a large multiyear data set on stable isotopes of CH 4 ebullition (bubbling) from three small adjacent subarctic lakes. The δ 13 C‐CH 4 and δD‐CH 4 range from −78.4‰ to −53.1‰ and from −369.8‰ to −218.8‰, respectively, and vary greatly among the lakes. The signatures suggest dominant hydrogenotrophic methanogenesis, particularly in the deep zones, but there are also signals of seemingly acetoclastic production in some high fluxing shallow areas, possibly fueled by in situ vegetation, but in‐sediment anaerobic CH 4 oxidation cannot be ruled out as an alternative cause. The observed patterns, however, are not consistent across the lakes. Neither do they correspond to the spatiotemporal variations in the measured bubble CH 4 fluxes. Patterns of acetoclastic and hydrogenotrophic production plus oxidation demonstrate that gains and losses of sediment CH 4 are dominated by sub‐lake scale processes. The δD‐CH 4 in the bubbles was significantly different depending on measurement month, likely due to evaporation effects. On a larger scale, our isotopic data, combined with those from other lakes, show a significant difference in bubble δD‐CH 4 between postglacial and thermokarst lakes, an important result for emission inventories. Although this characteristic theoretically assists in source partitioning studies, most hypothetical future shifts in δD‐CH 4 due to high‐latitude lake area or production pathway are too small to lead to atmospheric changes detectable with current technology.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

Polar stratospheric cloud processed air and potential vorticity in the Northern Hemisphere lower stratosphere at mid-latitudes during winter

The present study compares small-scale (less than 100 km) features in ER-2 measurements of ClO, O3, H2O, N2O, and NO(y) outside the lower stratospheric Arctic vortex of 1988-1989 with features on potential vorticity maps from ECMWF. The potential vorticity maps are obtained from T106 analyses and forecasts. Some of the plots were truncated to lower resolution (T63 or T42) which smooths out the finer-scale structure. Comparison of these lower resolution plots shows how much detail is lost by excessive smoothing. It is also evident that the forecast plots lose fine-scale structure due to dissipation in the model resulting mainly from horizontal diffusion. It is concluded that blobs of air on the maps at latitudes between the vortex edge and 25 deg N having potential vorticities characteristic of the vortex did indeed originate from the vortex, but that the real atmosphere is more sharply differentiated than the meteorological analyses, implying that the potential vorticity maps underestimate the amount of peeled-off material.

Tuck, A. F.↗
DOE OSTI2020

Development of neural network force fields for corrosion studies

To fully understand the chemistry and physics of corrosion, novel methods of simulation must be developed. One approach is designing machine learning (ML) algorithms integrated with density functional theory to develop adaptive force fields to gain insight into corrosion behavior namely at the surface of metal oxides. Current methods of modeling corrosion are slow due to the computational cost of resolving both reaction mechanics and mass transport processes. Machine learning methods can be implemented to obtain structure-activity relationships at both the molecular and bulk scale while still retaining the accuracy of density functional theory (DFT) and significantly decreasing the time needed for simulations of complex chemical processes in the various environments of corrosion. Multiscale models are needed for corrosion studies to fully understand its processes not only at the atomic length scale (chemical bonding, energies, and forces), but also at the nano and meso length scales (solid-state physics and material science processes). Current methods of study include DFT, molecular dynamics, and Monte Carlo. The limitation of DFT is that only a small number of atoms or molecules can be simulated at that level of theory. Density functional theory is used to study the electronic structure of atoms and molecules, and calculate the force component of each atom. However, these calculations are limited to about 1000 atoms. Custom periodic boundary conditions (PBC) can be used to describe the various environments and defects that affect the atomic forces to produce a large data set from which a training set can be derived. Machine learning can be utilized to overcome the barrier of modeling macroscopic and multi-scale processes from ab initio calculations through the development of adaptive force fields. Local environments determine the atomic forces of a given system, therefore adaptive force fields must be created to produce reliable quantum mechanical calculations. This can be achieved by developing a learning algorithm that uses the mapped atomic forces or fingerprint as an input to produce energies and magnetic moments as output. A systematic approach was used to begin to build a data set in order to accurately describe the atomic forces in various environments. In Figure 4 below, a simple PBC cell of Fe{sub 2}O{sub 3} was first optimized. A surface optimization was performed next, followed by a hydroxylated surface optimization. Once this calculation has converged, the adsorption of halide species to the hydroxylated surface will be investigated. TensorFlow is an open source platform for machine learning developed by Google. Using a high level application program interface (API) such as Keras allows for building and training ML models easily in a number of different environments and languages. For this project, a neural network was developed within Anaconda in Python. Future Work: Further development of reference data set; Refining neural network and learning algorithm; Fingerprinting atomic environment to enable mapping of atomic force components; Choosing appropriate training set from reference data; Learning from training set and enabling non-linear mapping of training set fingerprints and the atomic forces; Estimation of uncertainty to identify ranges of outside applicability; Testing and analysis of molecular dynamic simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2017

An intermediate-scale model for thermal hydrology in low-relief permafrost-affected landscapes

Integrated surface/subsurface models for simulating the thermal hydrology of permafrost-affected regions in a warming climate have recently become available, but computational demands of those new process-rich simu- lation tools have thus far limited their applications to one-dimensional or small two-dimensional simulations. We present a mixed-dimensional model structure for efficiently simulating surface/subsurface thermal hydrology in low-relief permafrost regions at watershed scales. The approach replaces a full three-dimensional system with a two-dimensional overland thermal hydrology system and a family of one-dimensional vertical columns, where each column represents a fully coupled surface/subsurface thermal hydrology system without lateral flow. The system is then operator split, sequentially updating the overland flow system without sources and the one-dimensional columns without lateral flows. We show that the app- roach is highly scalable, supports subcycling of different processes, and compares well with the corresponding fully three-dimensional representation at significantly less computational cost. Those advances enable recently developed representations of freezing soil physics to be coupled with thermal overland flow and surface energy balance at scales of 100s of meters. Furthermore developed and demonstrated for permafrost thermal hydrology, the mixed-dimensional model structure is applicable to integrated surface/subsurface thermal hydrology in general.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Innovative Polyhydroxyalkanoates (PHA) Production with Microbial Electrochemical Technology (MET)

The project “Innovative Polyhydroxyalkanoates (PHA) Production with Microbial Electrochemical Technology (MET)” addressed food waste disposal challenges by successfully converting food waste to bioplastics (known as PHAs). The novel process created by our team of researchers from universities, national labs, and industry substantially enhanced overall carbon conversion efficiency of food waste processing (> 50%), while reducing disposal costs (> 25%). The project showed economic viability potential at community scale through pilot-scale demonstration at a relevant scale (50 L reactor volume) with more than 100 hours of PHA production using realistic conditions. The project goal was to valorize food waste by shunting traditional anaerobic digestion processing and creating a value-added PHA processing route that improves the economics and sustainability of local, community-scale, wet organic waste treatment. First, the food waste undergoes microbial-based, dark fermentation to break down the food to small carbon chains known as volatile fatty acids (VFAs). Instead of microorganisms converting the VFAs into methane using normal anaerobic digestion processing, our innovative process inhibits methane production. This preserves the produced VFAs for extraction and use by a novel Haloferax mediterranei (HM) archaea, which effectively converts the VFAs to bioplastics. The project added microbial electrochemical cells (MEC) to the dark fermentation process to enhance the VFAs produced and optimize the type of bioplastics formed.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Topology, landscapes, and biomolecular energy transport

While ubiquitous, energy redistribution remains a poorly understood facet of the nonequilibrium thermodynamics of biomolecules. At the molecular level, finite-size effects, pronounced nonlinearities, and ballistic processes produce behavior that diverges from the macroscale. Here, we show that transient thermal transport reflects macromolecular energy landscape architecture through the topological characteristics of molecular contacts and the nonlinear processes that mediate dynamics. While the former determines transport pathways via pairwise interactions, the latter reflects frustration within the landscape for local conformational rearrangements. Unlike transport through small-molecule systems, such as alkanes, nonlinearity dominates over coherent processes at even quite short time- and length-scales. Our exhaustive all-atom simulations and novel local-in-time and space analysis, applicable to both theory and experiment, permit dissection of energy migration in biomolecules. The approach demonstrates that vibrational energy transport can probe otherwise inaccessible aspects of macromolecular dynamics and interactions that underly biological function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Scalable edge clustering of dynamic graphs via weighted line graphs

Timestamped relational datasets consisting of records (or connections) between pairs of entities are ubiquitous in network science. For applications like peer-to-peer communication, email, various social network interactions, and computer network security, it is useful to organize these records into groups based on how and when they are occurring. Weighted line graphs offer a natural way to model how records are related in such datasets but for large real-world graph topologies, building and utilizing the line graph is prohibitively expensive. Here, we present the framework to cluster the edges of a dynamic graph via the associated line graph that contains two major contributions. The first is a method to work with the line graph implicitly and the second is a distributed scale implementation of an agglomerative hierarchical graph clustering algorithm. We outline a novel hierarchical dynamic graph edge clustering approach that efficiently breaks massive relational datasets into small sets of edges containing events at various timescales. This is in stark contrast to traditional graph clustering algorithms that prioritize highly connected (clique-like) community structures. Our approach relies on constructing a sufficient subgraph of a weighted line graph and applying a hierarchical agglomerative clustering. This approach is related to scalable techniques from spatial clustering, nonlinear-dimension reduction, topological data analysis, and draws particular inspiration from HDBSCAN. As an edge clustering, this method yields an overlapping node clustering. Our algorithm is parallelizable and we demonstrate efficient clustering of a billion-scale, real-world dynamic graph into small edge sets that correlate in topology and time. The entire clustering process for a graph with tens of billions of edges takes just a few minutes of run time on 256 nodes of a distributed compute environment. We argue how the output of the edge clustering is useful for a multitude of data visualization and powerful machine learning tasks, both involving the original massive dynamic graph data and metadata associated with the nodes and edges. Finally, we describe how this approach can be extended to dynamic hypergraphs and dynamic graphs/hypergraphs with unstructured data living on vertices and edges.

Data Analysis↗
DOE OSTI2015

Small-Scale Coal-Biomass to Liquids Production Using Highly Selective Fischer-Tropsch Synthesis

The research project advanced coal-to-liquids (CTL) and coal-biomass to liquids (CBTL) processes by testing and validating Chevron’s highly selective and active cobalt-zeolite hybrid Fischer-Tropsch (FT) catalyst to convert gasifier syngas predominantly to gasoline, jet fuel and diesel range hydrocarbon liquids, thereby eliminating expensive wax upgrading operations The National Carbon Capture Center (NCCC) operated by Southern Company (SC) at Wilsonville, Alabama served as the host site for the gasifier slip-stream testing/demonstration. Southern Research designed, installed and commissioned a bench scale skid mounted FT reactor system (SR-CBTL test rig) that was fully integrated with a slip stream from SC/NCCC’s transport integrated gasifier (TRIG TM ). The test-rig was designed to receive up to 5 lb/h raw syngas augmented with bottled syngas to adjust the H 2 /CO molar ratio to 2, clean it to cobalt FT catalyst specifications, and produce liquid FT products at the design capacity of 2 to 4 L/day. It employed a 2-inch diameter boiling water jacketed fixed-bed heat-exchange FT reactor incorporating Chevron’s catalyst in Intramicron’s high thermal conductivity micro-fibrous entrapped catalyst (MFEC) packing to efficiently remove heat produced by the highly exothermic FT reaction.

Gangwal, Santosh K.↗
DOE OSTI2017

Moving Bed Chemical Looping Combustion Fuel Reactor Modeling and Sensitivity Analysis

Chemical looping combustion (CLC) is a novel, coal-based power generation technology that has currently achieved only small-scale, non-integrated development status, with the fuel reactor being the key developmental component in the CLC process. Both circulating fluidized bed (CFB) and moving bed fuel reactors have been the subjects of ongoing development campaigns. The objective of the effort described in this report is to characterize a moving bed fuel reactor by applying more detailed, reaction kinetics-based models that represent the nature of this reactor with a more fundamental foundation than has previously been reported by developers. This report describes the modeling basis, and a “base” fuel reactor’s design and performance characteristics resulting from the model. A major focus of the evaluation has been placed on studies of the sensitivity of the base moving bed fuel reactor performance, design, and CLC power plant cost implications to the key parameters.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2019

Low-Energy, Low-Cost Ethylene Production by Low-Temperature Oxidative Coupling of Methane

Ethylene, one of the highest volume production chemicals in the U.S. and globally, is an essential chemical building block that is used to manufacture countless products, from packaging to antifreeze to tires. Most ethylene is produced via a process called steam cracking, where the feedstock (mostly ethane, sometimes naphtha or propane) is heated to high temperatures over a catalyst. The naphtha feedstock typically comes from petroleum refineries, while ethane is becoming increasingly used as a feedstock in the U.S. due to the rise in domestic natural gas production from shale resources. However, steam cracking is energy intensive and occurs in large- scale facilities. Low-temperature oxidative coupling of methane (LT-OCM) is an alternative ethylene production method that converts methane (natural gas) and optionally ethane to ethylene in a single-step, energy-producing conversion system using an innovative process. While OCM has been studied for over 30 years due to its potential to reduce ethylene production cost, past efforts did not result in a viable catalyst with performance needed for commercialization. These catalysts, while at times achieving promising yield and selectivity, were hampered by very high operating temperatures, low activities, and short lifetimes on the order of hours to days. Recognizing this, Siluria applied a combination of new innovations in catalyst development and a thorough definition and understanding of the problem to develop unique catalysts that enable commercialization of OCM. The OCM catalysts operate at significantly lower temperature (several hundreds of degrees lower) and practical operating pressures (5-10 atmospheres), have high activities and standard lifetimes of years under said conditions. In addition, the simple process provides excellent scalability and flexibility, especially when compared to today’s mega-scale steam crackers, thus enabling small- volume “distributed scale” reactors for on-demand ethylene production for applications such as on-site conversion of ethylene to high value polymer derivatives.

02 PETROLEUM↗
NASA NTRS1975

CARETS: A prototype regional environmental information system. Volume 13: Utility of CARETS products to local planners; an evaluation

The Metropolitan Washington Council of Governments (MWCOG) in cooperation with and under contract to the U.S. Geological Survey, conducted an evaluation of the utility of remote-sensor derived land use data produced by the USGS Central Atlantic Regional Ecological Test Site (CARETS) project. Investigators invited representatives of Washington, D.C. metropolitan area planning agencies to a workshop, introduced them to the CARETS products, and asked them to evaluate the products. In follow-up interviews, planners from 12 participating agencies reported general support for the fulI spectrum of CARETS products but gave more positive responses towards products with which they had some familiarity. Planners considered some products of limited utility because of (1) insufficient detail, (2) too small a scale, or (3) lack of technical capability to incorporate the information and products into the current planning process. Some planners expressed doubt about the application of CARETS products in most day-to-day planning activities , which involve specific rezoning requests or site development plans requiring highly localized data. The greatest potential of the CARETS products was in the identification of broad development patterns at the county or regional level. An appendix documents the results of an inventory of local government decisions relating to land use.

Land use planning↗
NASA NTRS1988

Modeling of impulsive propellant reorientation

The impulsive propellant reorientation process is modeled using the (Energy Calculations for Liquid Propellants in a Space Environment (ECLIPSE) code. A brief description of the process and the computational model is presented. Code validation is documented via comparison to experimentally derived data for small scale tanks. Predictions of reorientation performance are presented for two tanks designed for use in flight experiments and for a proposed full scale OTV tank. A new dimensionless parameter is developed to correlate reorientation performance in geometrically similar tanks. Its success is demonstrated.

Hochstein, John I.↗