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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Phonon-Assisted Ballistic Current from First-Principles Calculations

The bulk photovoltaic effect (BPVE) refers to current generation due to illumination by light in a homogeneous bulk material lacking inversion symmetry. In addition to the intensively studied shift current, the ballistic current, which originates from asymmetric carrier generation due to scattering processes, also constitutes an important contribution to the overall kinetic model of the BPVE. In this Letter, we use a perturbative approach to derive a formula for the ballistic current resulting from the intrinsic electron-phonon scattering in a form amenable to first-principles calculation. We then implement the theory and calculate the ballistic current of the prototypical BPVE material BaTiO 3 using quantum-mechanical density functional theory. The magnitude of the ballistic current is comparable to that of the shift current, and the total spectrum (shift plus ballistic) agrees well with the experimentally measured photocurrents. Furthermore, we show that the ballistic current is sensitive to structural change, which could benefit future photovoltaic materials design.

14 SOLAR ENERGY↗
DOE OSTI2020

RODeO (Revenue Operation and Device Optimization Model) [SWR 20-67]

The Revenue, Operation, and Device Optimization (RODeO) model explores optimal system design and operation considering different levels of grid integration, equipment cost, operating limitations, financing, and credits and incentives. RODeO is a price-taker model formulated as a mixed-integer linear programming (MILP) model in the GAMS modeling platform. The objective is to maximizes the net revenue for a collection of equipment at a given site. The equipment includes generators (e.g., gas turbine, steam turbine, solar, wind, hydro, fuel cells, etc.), storage systems (batteries, pumped hydro, gas-fired compressed air energy storage, long-duration systems, hydrogen), and flexible loads (e.g., electric vehicles, electrolyzers, flexible building loads). The input data required by RODeO can be classified into three bins: 1) utility service data, which refers to retail utility rate information (meter cost, energy and demand charges), 2) electricity market data, which include energy and reserve prices, 3) other inputs, which refer to additional electrical demand, product output demand, technological assumptions, financial properties, and operational parameters.

Guerra Fernandez, Omar Jose↗
DOE OSTI2023

DEEPEN 3D PFA Favorability Models and 2D Favorability Maps at Newberry Volcano

DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments. Part of the DEEPEN project involved developing and testing a methodology for a 3D play fairway analysis (PFA) for multiple play types (conventional hydrothermal, superhot EGS, and supercritical). This was tested using new and existing geoscientific exploration datasets at Newberry Volcano. This GDR submission includes images, data, and models related to the 3D favorability and uncertainty models and the 2D favorability and uncertainty maps. The DEEPEN PFA Methodology is based on the method proposed by Poux et al. (2020), which uses the Leapfrog Geothermal software with the Edge extension to conduct PFA in 3D. This method uses all available data to build a 3D geodata model which can be broken down into smaller blocks and analyzed with advanced geostatistical methods. Each data set is imported into a 3D model in Leapfrog and divided into smaller blocks. Conditional queries can then be used to assign each block an index value which conditionally ranks each block's favorability, from 0-5 with 5 being most favorable, for each model (e.g., lithologic, seismic, magnetic, structural). The values between 0-5 assigned to each block are referred to as index values. The final step of the process is to combine all the index models to create a favorability index. This involves multiplying each index model by a given weight and then summing the resulting values. The DEEPEN PFA Methodology follows this approach, but split up by the specific geologic components of each play type. These components are defined as follows for each magmatic play type: 1. Conventional hydrothermal plays in magmatic environments: Heat, fluid, and permeability 2. Superhot EGS plays: Heat, thermal insulation, and producibility (the ability to create and sustain fractures suitable for and EGS reservoir) 3. Supercritical plays: Heat, supercritical fluid, pressure seal, and producibility (the proper permeability and pressure conditions to allow production of supercritical fluid) More information on these components and their development can be found in Kolker et al., 2022. For the purposes of subsurface imaging, it is easier to detect a permeable fluid-filled reservoir than it is to detect separate fluid and permeability components. Therefore, in this analysis, we combine fluid and permeability for conventional hydrothermal plays, and supercritical fluid and producibility for supercritical plays. More information on this process is described in the following sections. We also project the 3D favorability volumes onto 2D surfaces for simplified joint interpretation, and we incorporate an uncertainty component. Uncertainty was modeled using the best approach for the dataset in question, for the datasets where we had enough information to do so. Identifying which subsurface parameters are the least resolved can help qualify current PFA results and focus future efforts in data collection. Where possible, the resulting uncertainty models/indices were weighted using the same weights applied to the respective datasets, and summed, following the PFA methodology above, but for uncertainty. There are two different versions of the Leapfrog model and associated favorability models: - v1.0: The first release in June 2023 - v2.1: The second release, with improvements made to the earthquake catalog (included additional identified events, removed duplicate events), to the temperature model (fixed a deep BHT), and to the index models (updated the seismicity-heat source index models for supercritical and EGS, and the resistivity-insulation index models for all three play types). Also uses the jet color map rather than the magma color map for improved interpretability. - v2.1.1: Updated to include v2.0 uncertainty results (see below for uncertainty model versions) There are two different versions of the associated uncertainty models: - v1.0: The first release in June 2023 - v2.0: The se...

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

DEEPEN: Final 3D PFA Favorability Models and 2D Favorability Maps at Newberry Volcano

Part of the DEEPEN (DE-risking Exploration of geothermal Plays in magmatic ENvironments) project involved developing and testing a methodology for a 3D play fairway analysis (PFA) for multiple play types (conventional hydrothermal, superhot EGS, and supercritical). This was tested using new and existing geoscientific exploration datasets at Newberry Volcano. This GDR submission includes images, data, and models related to the 3D favorability and uncertainty models and the 2D favorability and uncertainty maps. The DEEPEN PFA Methodology, detailed in the journal article below, is based on the method proposed by Poux & O'brien (2020), which uses the Leapfrog Geothermal software with the Edge extension to conduct PFA in 3D. This method uses all available data to build a 3D geodata model which can be broken down into smaller blocks and analyzed with advanced geostatistical methods. Each data set is imported into a 3D model in Leapfrog and divided into smaller blocks. Conditional queries can then be used to assign each block an index value which conditionally ranks each block's favorability, from 0-5 with 5 being most favorable, for each model (e.g., lithologic, seismic, magnetic, structural). The values between 0-5 assigned to each block are referred to as index values. The final step of the process is to combine all the index models to create a favorability index. This involves multiplying each index model by a given weight and then summing the resulting values. The DEEPEN PFA Methodology follows this approach, but split up by the specific geologic components of each play type. These components are defined as follows for each magmatic play type: 1. Conventional hydrothermal plays in magmatic environments: Heat, fluid, and permeability 2. Superhot EGS plays: Heat, thermal insulation, and producibility (the ability to create and sustain fractures suitable for and EGS reservoir) 3. Supercritical plays: Heat, supercritical fluid, pressure seal, and producibility (the proper permeability and pressure conditions to allow production of supercritical fluid) More information on these components and their development can be found in Kolker et al., (2022). For the purposes of subsurface imaging, it is easier to detect a permeable fluid-filled reservoir than it is to detect separate fluid and permeability components. Therefore, in this analysis, we combine fluid and permeability for conventional hydrothermal plays, and supercritical fluid and producibility for supercritical plays. We also project the 3D favorability volumes onto 2D surfaces for simplified joint interpretation, and we incorporate an uncertainty component. Uncertainty was modeled using the best approach for the dataset in question, for the datasets where we had enough information to do so. Identifying which subsurface parameters are the least resolved can help qualify current PFA results and focus future efforts in data collection. Where possible, the resulting uncertainty models/indices were weighted using the same weights applied to the respective datasets, and summed, following the PFA methodology above, but for uncertainty.

15 GEOTHERMAL ENERGY↗
DOE OSTI2018

Effects of Exhaust Gas Recirculation (EGR) on Turbulent Combustion and Emissions in Advanced Gas Turbine Combustors with High-Hydrogen-Content (HHC) Fuels (Final Report)

This Final Report documents the entire four years of the Cooperative Agreement DE-FE0011822, from October 1, 2013 through September 30, 2017, that was competitively awarded under Funding Opportunity Announcement DE-FOA-0000795 in support of the U.S. Department of Energy’s (DOE) National Energy Technology Laboratory (NETL) University Turbine Systems Research (UTSR) Program. Under the UTSR Program, DOE typically issues Funding Opportunity Announcement (FOA) solicitations every 1-2 years so that U.S. colleges/universities may propose research & development (R&D) projects in specific technical topic areas (e.g., combustion, aerodynamics/heat transfer, advanced materials) that have been identified as both scientifically and industrially relevant to the gas turbine industry. The primary objectives of this Purdue University project (in collaboration with Princeton University through a sub-award) was to develop experimental methods, kinetic models, and numerical tools to help quantify and predict the impact of exhaust gas recirculation (EGR) on NOx and CO emissions, combustion kinetics, radiation heat transfer, turbulent combustion, and combustion instabilities for natural gas and high hydrogen content (HHC) fuels by using laminar and turbulent flow reactors and gas turbine combustors operating at high temperatures and pressures. This project has obtained detailed data for improving chemical kinetic models to study EGR effects and provide insight into the effects of EGR on flame speeds and turbulent flame structure, as well as assessing the impact of EGR on emissions in a high-pressure combustion test rig. The project was divided into six primary tasks: 1) Project Management and Program Planning; 2) Flow Reactor Investigation of EGR Chemical Kinetics; 3) Combustion Bomb Investigation of EGR Effects on Flame Speed; 4) Investigation of EGR Effects on Turbulent Flame Structure in Reactor-Assisted Turbulent Slot (RATS) Burner; 5) Investigation of EGR Effects in Purdue Staged Combustion Test Rig; and 6) Development and Validation of a Large Eddy Simulation (LES) Tool for Gas Turbine Combustion and Emission Modeling using HHC Fuels. Details on the execution and results of each of these tasks are provided in the main report. To assist the reader, each task is described in a chapter-like format with its own separate listing of tables, figures, and references so that the results of each task/subtask (i.e., technical sections covering various experiments and modeling work focused on a specific area) can be quickly obtained while also getting an overall feel of the project execution. This chapter-like format also allows for acknowledgement of support from other programs relative to specific tasks. In this manner, the reader can more conveniently digest the R&D results in the various task/subtask sections that may be of most interest to the reader. In addition to this Final Report, the Purdue/Princeton team was able to publish 7 journal articles and provide 7 presentations at national scientific meetings/conferences to disseminate results. A listing of these journal articles and presentations is provided at the end of this report

03 NATURAL GAS↗
NASA NTRS1992

User's manual for three dimensional FDTD version D code for scattering from frequency-dependent dielectric and magnetic materials

The Penn State Finite Difference Time Domain Electromagnetic Scattering Code version D is a 3-D numerical electromagnetic scattering code based upon the finite difference time domain technique (FDTD). The manual provides a description of the code and corresponding results for several scattering problems. The manual is organized into 14 sections: introduction; description of the FDTD method; operation; resource requirements; version D code capabilities; a brief description of the default scattering geometry; a brief description of each subroutine; a description of the include file; a section briefly discussing Radar Cross Section computations; a section discussing some scattering results; a sample problem setup section; a new problem checklist; references and figure titles. The FDTD technique models transient electromagnetic scattering and interactions with objects of arbitrary shape and/or material composition. In the FDTD method, Maxwell's curl equations are discretized in time-space and all derivatives (temporal and spatial) are approximated by central differences.

Beggs, John H.↗
NASA NTRS1995

Magnetospheric space plasma investigations

Topics and investigations covering this period of this semiannual report period (August 1994 - January 1995) are as follows: (1) Generalized SemiKinetic (GSK) modeling of the synergistic interaction of transverse heating of ionospheric ions and magnetospheric plasma-driven electric potentials on the auroral plasma transport. Also, presentations of GSK modeling of auroral electron precipitation effects on ionospheric plasma outflows, of ExB effects on such outflow, and on warm plasma thermalization and other effects during refilling with pre-existing warm plasmas; (2) Referees' reports received on the statistical study of the latitudinal distributions of core plasmas along the L = 4.6 field line using DE-1/RIMS data. Other work is concerned in the same field, field-aligned flows and trapped ion distributions; and (3) A short study has been carried out on heating processes in low density flux tubes in the outer plasmasphere. The purpose was to determine whether the high ion temperatures observed in these flux tubes were due to heat sources operating through the thermal electrons or directly to the ions. Other investigations center along the same area of plasmasphere-ionosphere coupling. The empirical techniques and model, the listing of hardware calibrated, and/or tested, and a description of notable meetings attended is included in this report, along with a list of all present publication in submission or accepted and those reference papers that have resulted from this work thus far.

Comfort, Richard H.↗
NASA NTRS2000

Capacity of Pulse-Position Modulation (PPM) on Gaussian and Webb Channels

This article computes the capacity of various idealized soft-decision channels modeling an optical channel using an avalanche photodiode detector (APD) and pulse-position modulation (PPM). The capacity of this optical channel depends in a complicated way on the physical parameters of the APD and the constraints imposed by the PPM orthogonal signaling set. This article attempts to identify and separate the effects of several fundamental parameters on the capacity of the APD-detected optical PPM channel. First, an overall signal-to-noise ratio (SNR) parameter is de ned such that the capacity as a function of a bit-normalized version of this SNR drops precipitously toward zero at quasi-brick-wall limits on bit SNR that are numerically the same as the well-understood brick-wall limits for the standard additive white Gaussian noise (AWGN) channel. A second parameter is used to quantify the effects on capacity of one unique facet of the optical PPM channel (as compared with the standard AWGN channel) that causes the noise variance to be higher in signal slots than in nonsignal slots. This nonuniform noise variance yields interesting capacity effects even when the channel model is AWGN. A third parameter is used to measure the effects on capacity of the difference between an AWGN model and a non-Gaussian model proposed by Webb (see reference in [2]) for approximating the statistics of the APD-detected optical channel. Finally, a fourth parameter is used to quantify the blending of a Webb model with a pure AWGN model to account for thermal noise. Numerical results show that the capacity of M-ary orthogonal signaling on the Webb channel exhibits the same brick-wall Shannon limit, (M ln 2)=(M 1), as on the AWGN channel ( 1:59 dB for large M). Results also compare the capacity obtained by hard- and soft-output channels and indicate that soft-output channels o er a 3-dB advantage.

Dolinar, S.↗
NASA NTRS2009

Modeling Guidelines for Code Generation in the Railway Signaling Context

Modeling guidelines constitute one of the fundamental cornerstones for Model Based Development. Their relevance is essential when dealing with code generation in the safety-critical domain. This article presents the experience of a railway signaling systems manufacturer on this issue. Introduction of Model-Based Development (MBD) and code generation in the industrial safety-critical sector created a crucial paradigm shift in the development process of dependable systems. While traditional software development focuses on the code, with MBD practices the focus shifts to model abstractions. The change has fundamental implications for safety-critical systems, which still need to guarantee a high degree of confidence also at code level. Usage of the Simulink/Stateflow platform for modeling, which is a de facto standard in control software development, does not ensure by itself production of high-quality dependable code. This issue has been addressed by companies through the definition of modeling rules imposing restrictions on the usage of design tools components, in order to enable production of qualified code. The MAAB Control Algorithm Modeling Guidelines (MathWorks Automotive Advisory Board)[3] is a well established set of publicly available rules for modeling with Simulink/Stateflow. This set of recommendations has been developed by a group of OEMs and suppliers of the automotive sector with the objective of enforcing and easing the usage of the MathWorks tools within the automotive industry. The guidelines have been published in 2001 and afterwords revisited in 2007 in order to integrate some additional rules developed by the Japanese division of MAAB [5]. The scope of the current edition of the guidelines ranges from model maintainability and readability to code generation issues. The rules are conceived as a reference baseline and therefore they need to be tailored to comply with the characteristics of each industrial context. Customization of these recommendations has been performed for the automotive control systems domain in order to enforce code generation [7]. The MAAB guidelines have been found profitable also in the aerospace/avionics sector [1] and they have been adopted by the MathWorks Aerospace Leadership Council (MALC). General Electric Transportation Systems (GETS) is a well known railway signaling systems manufacturer leading in Automatic Train Protection (ATP) systems technology. Inside an effort of adopting formal methods within its own development process, GETS decided to introduce system modeling by means of the MathWorks tools [2], and in 2008 chose to move to code generation. This article reports the experience performed by GETS in developing its own modeling standard through customizing the MAAB rules for the railway signaling domain and shows the result of this experience with a successful product development story.

Ferrari, Alessio↗
NASA NTRSDate not supplied

A Transmission Electron Microscopy Study of a Refractory Metal Grain from a Calcium-Aluminum-Rich Inclusion in the Leoville CV3 Chondrite

Introduction: Calcium-aluminum-rich inclusions (CAIs) are an important component of chondritic meteorites. They can contain materials that are thermodynamically predicted and isotopically age dated to be among the first-formed solids in our solar system [1-5]. Observed in some CAIs are micron to sub-micron sized inclusions rich in Fe, Ni, and high-Z elements such as Pt, Os, Ir and W, in the form of refractory metal nuggets (RMNs), fremdlinges, and ‘nugget like objects’ (NLOs) [1,6]. Refractory siderophile elements such as Os, Ir and Ru are thermodynamically predicted to condense at temperatures well in excess of the major CAI phases such as melilite, perovskite, spinel and hibonite [2,7-9]. These refractory metal inclusions in CAIs can therefore serve as probes into the thermodynamic landscape of the early solar protoplanetary disk. Here we report on a refractory grain identified in a CAI of the Leoville CV3 chondrite. This work is part of an ongoing effort to gain insight into the thermochemistry of the early solar system through systematic analyses of the structure and chemistry of various components in CAIs [10-13]. Sample and Analytical Techniques: A fluffy type A CAI (Fig. 1A) was identified in a section of the Leoville, CV3 chondrite (Center for Meteorite Studies, Arizona State University collection, #821_C_3) using a JOEL-JXA 8530F electron microprobe at Arizona State University. Backscattered electron (BSE) imaging and energy-dispersive X-ray spectroscopy (EDS) were used to identify refractory metal grains in the CAI using a Thermo Fisher (formerly FEI) Helios NanoLab 660 G3 focused-ion-beam scanning-electron microscope (FIBSEM) located at the Kuiper Materials Imaging and Characterization Facility (KMICF) at the Lunar and Planetary Laboratory, University of Arizona. The FIB is equipped with an EDAX EDS system. We selected one of the larger (micron-sized) refractory metal grains, designated as ‘Spud’ (Fig. 1B) for further analysis. ‘Spud’ was extracted and thinned to electron transparency (<100 nm) using the FIB-SEM located in KMICF, following methods described by [14- 15]. The FIB section was analyzed using a 200 keV Hitachi HF5000 scanning transmission electron microscope (S/TEM) located at KMICF. The HF5000 is equipped with cold-field emission gun, 3rd-order spherical aberration corrector for STEM imaging, and an Oxford Instruments X-Max N 100 TLE energydispersive spectroscopy (EDS) system with dual 100 mm2 windowless silicon-drift detectors (Ω = 2.0 sr). Selected-area electron-diffraction (SAED) patterns were acquired to aid in determination of crystallinity and phase. Results: The mineralogy, texture, and morphology of the CAI are consistent with that of a fluffy type A (FTA) CAI [16]. BSE imaging at high magnifications revealed grains with high contrast, indicative of compositions rich in elements of higher atomic number relative to surrounding material. These high-Z grains have sizes that range from ∼250 nm to 4 µm. EDS analyses confirm that the bright grains are metal-rich inclusions. A minor fraction of the grains are composed of only Fe and Ni, but the majority (∼60%) of the identified inclusions also contained various refractory siderophiles including Os, Ru, Zr, Ir and Mo. EDS analysis on the FIB-SEM of Spud shows that it contains Fe, Ni, Mo and Ru. High-angle annular dark-field (HAAFD) imaging and EDS mapping in the TEM (Fig. 2) show that Spud occurs in melilite (Ca1.9Al1.99Si1.06O7). Spud contains a subhedral to anhedral morphology and is compositionally heterogenous (polyphasic, Fig. 2). Local spatial correlation occurs among Fe, Ni, and Pt, and also among Os, Ru, and Mo. SAED patterns show that the Fe-Ni-Pt, Fe-Os-Mo-Ru and Fe-Pt regions are crystalline. Discussion: CAIs can contain various types of inclusions rich in Fe, Ni and refractory siderophiles such as Os, Ru, W and Pt [1]. RMNs are micron-sized, single phase alloy grains and can contain Os, Ir, Ru and Rh [1,7,17]. NLOs are also micron-sized inclusions, but contain two phases, a refractory metal, and an oxide [6]. Fremdlinge are the largest of such inclusions (tens of microns in size) and are complex aggregates of Fe-Ni alloy, silicates, oxides, and sulfides [1,17]. While the size of Spud matches previous descriptions of RMNs and NLOs, Spud is neither a single-phase alloy like RMNs, nor does it contain one metal phase and one oxide like NLOs. Spud does not match the above described categories of refractory metal inclusions. The presence of refractory siderophiles such as Mo, Os, Ru, and Pt suggests a high-temperature origin. Thermodynamic modelling by [7] indicates condensation temperatures of 1917 K, 1693 K, 1613 K and 1415 K for Os, Mo, Ru and Pt respectively. These models also show that following the initial condensation of a refractory metal, alloying of solutes such as Fe, Ni and W, occurs in levels proportional to their partial pressures in the surrounding gas. Such alloying occurs at temperatures above the condensation temperatures of common CAI phases such as melilite (1529 K), perovskite (1441 K), spinel (197 K) and forsterite (1354 K) [2]. The polyphasic nature of Spud could be the result of such high-temperature alloying, possibly shortly after the condensation of Mo and Ru at 1693 K and 1613 K respectively. That Spud occurs as an inclusion is consistent with it having formed prior to and at temperature above that of its host melilite in this FTA CAI, which is qualitatively consistent with such prior thermodynamic modeling. Further, the polyphasic nature of Spud is similar to refractory grains from a FTA CAI in the Northwest Africa (NWA) 8323, CV3 chondrite [11-13]. These data suggest that such refractory metal grains could have been widespread in the inner and early solar protoplanetary disk and represent some of the earliest formed solids to have condensed. Acknowledgments: Research and instrumentation supported by NASA grants #NNX12AL47G, #NNX15AJ22G and #80NSSC19K0509, and NSF grants #1531243 and #0619599. Fig 2. STEM data on ‘Spud’. HAADF Image (Top) False-color EDS Maps (Bottom) References: [1] MacPherson G. J. (2014) T. of Geochem. Vol I: Met. And Cosmochem. Processes, 139-179. [2] Lodders K. (2003) ApJ, 591, 1220-1247. [3] Ebel D. S. (2006) Met. & the Early S. Sys. II., 253- 277. [4] Amelin Y. (2002) Science, 297, 1678-1683. [5] Connelly J.N. et.al. (2012) Science, 338, 651-655. [6] Schwander D. et al. (2015) GCA, 18, 70-87. [7] Palme H. and Wlotzka F. (1976) EPSL, 33, 45-60. [8] Berg T. et al. (2009) ApJ, 702, 172-176. [9] Liffman K. et al. (2021) Icarus, 221, 89-105. [10] Zega T.J. et al. (2021) PSJ, 2, 115. [11] Ramprasad T. et al. (2020) LPSC LI, Abstract #2472. [12] Ramprasad T. et al. (2021) Microscopy & Microanalysis, S1, 2792-2794. [13] Ramprasad T. et al. (2021) 84th MetSoc, Abstract #6123. [14] Zega T.J. et al. (2007) MAPS, 42, 1373-1386. [15] Ramprasad T. et al. (2022) MAPS, in revision. [16] Grossman L. (1975), GCA, 39, 433-454. [17] El Goresy A. et al. (1978) LPSC IX, Abstract#1100

T. Ramprasad↗
DOE OSTI2025

Assessing the Performance of Exchange‐Correlation Density Functionals in Describing the Iron‐Catalyzed Ammonia Synthesis System

Density functional theory (DFT) has been widely employed for elucidating mechanistic aspects of heterogeneous catalysis. However, the accuracy of DFT calculations relies heavily on selecting an exchange-correlation (XC) functional that correctly describes the electronic structure of materials involved in the reactions. This study assesses the accuracy of several XC density functionals for modeling the iron-catalyzed ammonia synthesis system. In the assessment of functional accuracy, experimental references are compared to DFT-calculated values for the formation energy of gas-phase ammonia and nitrogen, bulk Fe/Fe-nitride (γ′-Fe 4 N) lattice constants and cohesive/formation energies, and nitrogen and ammonia binding energies on Fe(100), Fe(111), Fe(110), and γ′-Fe 4 N(111). It is observed that the experimental value for each of these descriptors is accurately modeled by at least one functional. RPBE alone provides reliable estimates for both the lattice constant and cohesive energy of Fe and γ′-Fe 4 N. Temperature-programmed desorption experiments led to estimates for N and NH 3 adsorption across several Fe-based facets that are best captured by RPBE. These results highlight the importance of choosing an appropriate XC functional that accurately describes experimental systems and offer insights into effectively modeling the interactions between nitrogen and ammonia on Fe-based surfaces.

adsorption↗
DOE OSTI2018

Sun Grant/DOE Regional Feedstock Partnership: Final Technical Report

The U.S. Department of Energy (DOE) and the Sun Grant Initiative initiated the Regional Feedstock Partnership (referred to as the Partnership) in 2007 primarily to address information gaps associated with the likelihood for realization of the sustainable and reliable production of a billion-tons of biomass annually to support the U.S. bioenergy industry by the year 2030. Publication of The Technical Feasibility of a Billion-Ton Annual Supply (Perlack et al., 2005) in 2005, with its associated yield assumptions, led to the realization that the yield goals and assumptions utilized in that analysis required careful validation. To achieve the overall goal of validating key yield assumptions, the following objectives were developed: 1. Establishment of replicated field trials across regions to determine the impact of crop residue removal (primarily corn and small grains) on future grain yields and soil health. 2. Establishment of replicated field trials of some of the most promising dedicated energy crops (herbaceous annuals and perennials, as well as woody perennials) to demonstrate the potential performance of these feedstocks across the U.S. 3. Assessment of feedstock resources to be used to estimate a sustainable national supply potential. Teams composed of representatives from Land Grant Universities, USDA ARS, DOE National Laboratories, industry, and other federal agencies were identified and assembled to address each of these objectives. For Objective 1, members of the USDA ARS’ Resilient Economic Agricultural Practices (REAP) team combined with university personnel to leverage on-going work and established new trials to determine sustainable corn residue removal rates. In addition, universities across the continental U.S. conducted surveys of published past research to define parameters for the use of cereal grain residue (primarily wheat) as a biomass feedstock. For Objective 2, and based on input from DOE, USDA, Land Grant university scientists, and others, several herbaceous and woody energy crop species were selected for new or further evaluation across wide geographic areas as cellulosic feedstock sources. Species teams were organized to assess the yield potential of candidate herbaceous feedstocks including sorghum, energycane, Miscanthus x giganteus (hereafter referred to as miscanthus), switchgrass, and mixed perennial species (primarily grasses and some legumes) on Conservation Reserve Program (CRP) land. Woody species will be critical components of the bioenergy sector; therefore, species teams were also organized for shrub willow and hybrid poplar (Populus spp.). Field trials of each species were utilized to determine yield potential across the U.S. For Objective 3, a GIS resource team was organized with representatives from each of the five Sun Grant regions. While some regional assessments were made, the multi-institutional team decided that the group from Oregon State University would utilize their PRISM ELM model to estimate national yield potential of the various species evaluated. The following are key outcomes and impacts • The Partnership demonstrated the production potential of diverse herbaceous and woody feedstocks across much of the U.S. for 5-7 consecutive growing seasons. Long-term studies such as this are not commonly possible due to limitations in funding cycles. • Long-term field trials were valuable in demonstrating the importance of agronomic management practices and genetic resources to yield of sorghum, switchgrass, miscanthus, energycane, CRP mixed perennial grasses, poplar, and willow. • National yield potential maps were developed for all species evaluated in the Partnership. • Sustainable corn stover removal rates were quantified for use by producers, harvesters, and commercial lignocellulosic biorefineries. • Data from the Partnership field trials not only validated initial Billion Ton estimates, but were instrumental in developing both the Billion Ton Update in 2011, and especially the 2016 Billion Ton Report. • The Partnership provided the opportunity to assemble and conserve a poplar germplasm collection that contains more than 20,000 clones for use in breeding programs. New clones resulting from crosses made using this germplasm collection have resulted in significantly improved cultivars that could be scaled up and deployed. • Further validation of improved yields of new varieties/cultivars of biomass sorghum, energycane, hybrid poplars, and shrub willows was produced by the Partnership. • The Partnership demonstrated the potential of energycane in northern parts of the southeastern U.S., particularly in relation to sugarcane varieties. • For certain feedstocks (e.g., CRP mixed grasses, switchgrass, willow, and poplar), production economics were ascertained through Partnership field trials. • Biomass samples collected as part of the Partnership are also being used to populate Idaho National Laboratory’s Bioenergy Feedstock Library. • Because of the size and scope of the Partnership, workforce development was a key component and outcome. Numerous undergraduate students (25), graduate students (15 MS and 8 PhD), and postdoctoral researchers (7) were trained by Partnership participants. This will help to prepare individuals for careers in the emerging fields of plant breeding, biomass production, feedstock supply logistics, and biomass conversion processes. • More than 130 scientific publications have been authored by Partnership team members. Numerous other presentations, outreach publications, book chapters, and websites have also been developed to further the continued development of the bioeconomy.

09 BIOMASS FUELS↗
NASA NTRS1983

Analysis of structural perturbations in systems via cost decomposition methods

It has long been common practice to analyze linear dynamic systems by decomposing the total response in terms of individual contributions which are easier to analyze. Examples of this philosophy include the expansion of transfer functions using: (1) the superposition principle, (2) residue theory and partial fraction expansions, (3) Markov parameters, Hankel matrices, and (4) regular and singular perturbations. This paper summarizes a new and different kind of expansion designed to decompose the norm of the response vector rather than the response vector itself. This is referred to as "cost-decomposition' of the system. The notable advantages of this type of decomposition are: (a) easy application to multi-input, multi-output systems, (b) natural compatibility with Linear Quadratic Gaussian Theory, (c) applicability to the analysis of more general types of structural perturbations involving inputs, outputs, states, parameters. Property (c) makes the method suitable for problems in model reduction, measurement/actuator selections, and sensitivity analysis.

Skelton, R. E.↗
NASA NTRS1993

Mars Global Reference Atmospheric Model (Mars-GRAM): Release No. 2 - Overview and applications

The Mars Global Reference Atmospheric Model (Mars-GRAM), a science and engineering model for empirically parameterizing the temperature, pressure, density, and wind structure of the Martian atmosphere, is described with particular attention to the model's newest version, Mars-GRAM, Release No. 2 and to the improvements incorporated into the Release No. 2 model as compared with the Release No. 1 version. These improvements include (1) an addition of a new capability to simulate local-scale Martian dust storms and the growth and decay of these storms; (2) an addition of the Zurek and Haberle (1988) wave perturbation model, for simulating tidal perturbation effects; and (3) a new modular version of Mars-GRAM, for incorporation as a subroutine into other codes.

James, B.↗
DOE OSTI2020

Development of a Convolutional Neural Network Classifier for Data Starved Spectra - 20199

The Institute for Clean Energy Technology (ICET) at Mississippi State University is exploring the utility of machine learning in augmenting its mobile radiation surveying platforms, which are currently being developed as means to survey depleted uranium contaminated areas in support of remediation and decommissioning efforts. Mobile survey platforms provide a means to efficiently scan large areas of interest while reducing human exposure to radiation and other hazards. The survey platforms can also be used for scanning for any gamma emitting isotope in addition to depleted uranium. The spectral data that the platforms collect may be data starved with relatively low counts and poorly defined spectral features depending on the speed of the platforms and scintillation detector selection. Such data-starved spectra are difficult to use for isotope identification, requiring advanced knowledge of the possible radionuclides that could be present and environmental factors that could attenuate signals or introduce background noise. These factors in combination with the volume of survey data increases the time it takes to perform analysis of survey data when the source type is unknown. There are a number of algorithms in the field of machine learning that can be used to classify data that would be challenging and time-consuming for a human to identify. Supervised machine learning algorithms train models based on extensive amounts of human-labeled training data. Once sufficiently trained, these models can be used to quickly make high-fidelity predictions on new data. Convolutional neural networks are machine learning algorithms that excel in learning representations of 'shapes'. They do this by taking numerical input data and convolving them with spatial feature detectors referred to as filters. These filters are incrementally adjusted to reduce the prediction error on the data during the backpropagation step of training. Discussed in this paper is the development of a convolutional neural network classifier (CNNC) that can utilize spectral survey data for source discrimination and isotope identification. Bench-top laboratory experiments data using LaBr{sub 3}(Ce) scintillation detectors were used to train and evaluate the performance of the developed CNNC. The CNNC is capable of discriminating a variety of gamma emitting source types, differentiating different forms of uranium (depleted vs. natural), and estimating the amount of uranium for a known geometry. The discussed CNNC may be useful in scenarios where survey systems are deployed in situations where hazardous radioactive material maybe present, but the type is unknown. When used in remediation applications the CNNC can be used to screen-out false positives, helping reduce remediation costs. (authors)

07 ISOTOPE AND RADIATION SOURCES↗
NASA NTRSDate not supplied

Mars Entry, Descent, Landing, and Ascent Systems Sensitivities to Landing Site and Atmospheric Dust

Plans for human missions to Mars continue to go through several architectural changes, dating all the way back to the 1950s [1]. The continuous study, reformulation, and refinement of Mars architectures and system concepts is necessary in order to incorporate evolving mission objectives, technology advancements, and growth in the body of knowledge regarding human factors and the various environments of human space travel. This evolution has continued into the 21st century, with architectures concepts such as NASA’s Design Reference Architecture 5.0 in 2009 [2], The Evolvable Mars Campaign in 2016 [3], and as recently as 2020, an architecture focused on a crewed mission as early as the 2030s that aims to minimizing crewed duration and infrastructure investment for the first mission [4]. Within these architectures, numerous studies around the current concept designs for Mars entry, descent, landing, and ascent (EDLA) systems have been performed over the last half a decade [[5], [6], [7], [8], [9], [10]]. Despite the breadth and depth of these studies, landing site, a key design parameter relevant to the design of EDLA systems, has remained nebulous over the years, largely due to the ever evolving mission objectives and architecture concept over the decades. However, the specific landing site has direct impact on the altitude and atmospheric conditions, which subsequently impact the design of EDLA systems. To accommodate the lack of a specific landing site, a baseline reference altitude of 0 km relative to the Mars Orbiter Laser Altimeter (MOLA), which is similar to an Earth sea level reference, has typically been selected and fixed for these past studies. Similarly, a baseline reference atmosphere has typically been utilized in these studies, either the Mars Global Reference Atmospheric Model [11], or a general 1982 standard warm, high pressure atmosphere model derived from Viking lander data [12]. Fig. 1 shows the range of elevations across the surface of Mars. Current architectures are focused on latitudes greater than 30 degrees north in an effort to ensure access to frozen water ice. From the figure, it is quickly evident that elevations over the range of longitudes at or above this latitude are significantly varied between roughly -4 to +4 km MOLA. Based on these observations, initial qualitative assessments of the impacts of landing site elevation on EDLA systems were performed. Fig. 2 depicts the expected trends in EDLA system mass for variations in both land site latitude and elevation. The background coloring is a qualitative evaluation of the current knowledge on ice water availability at the latitudes. Further modeling and simulation was performed to obtain numerical predictions of sensitivities to these parameters. Results indicate up to +2% to -4% mass variation from the current baseline Mars Ascent Vehicle concept, with the potential for greater than 6% mass variation at latitudes greater than 70 degrees north. However, variations in the descent system due to landing site were much more significant with mass variations in the range of -15% to +30% around the current baseline Mars Descent System concept. Additionally, Fig. 3 provides a depiction of potential Mars atmospheric density variations with both dust and Martian season. Though the Martian atmosphere is relatively thin compared to Earth’s atmosphere, it still poses significant impact on the design of EDLA systems. Variations in atmospheric density indicated by this slice of data would have significant impact on the design of EDLA systems. However, due to the highly complex nature of atmospheric flight, a qualitative assessment could not be performed. Rather, sensitivity results relied on modeling and simulation to provide numerical results for sensitivities on the current EDLA design concepts under consideration. Understanding these sensitivities is vital to the overall systems design of a Mars architecture. The resulting mass impacts on EDLA systems, driven by landing site elevation and dust level variations, has rippling impacts throughout the architecture that, ultimately, impact the viability of the architecture. Results showed fairly minor mass impacts to the current Mars Ascent Vehicle baseline configuration, roughly -0.6% to + 0.4% mass variations, while the Mars Descent System say greater variations due to dust, roughly -4% to +6% around the baseline concept.

EDLA↗
DOE OSTI2026

Bio-inspired alula-based winglet design for enhanced heat transfer in high temperature fin-and-tube heat exchangers

Fin-and-tube heat exchangers (FTHEs) are widely used for high-temperature flue-gas heat recovery, but their performance is often limited by wake regions and non-uniform fin-surface temperatures. This study proposes and numerically evaluates four bio-inspired longitudinal vortex generator (VG) configurations in a high-temperature FTHE with flue-gas inlet temperature ∼1230 K: double-delta, curved double-delta, alula, and a new curved-alula geometry. The reference fin is not hydraulically plain; it already incorporates leading-edge separation columns and convex protrusions, so the alula-type winglets are assessed as downstream add-ons acting on a strongly disturbed flow. In a second step, perforations (one, two and three circular holes) are introduced into the curved-alula VGs to further tailor the flow field. Three-dimensional simulations with the Shear Stress Transpor (SST) $k - ω$ model, temperature-dependent flue-gas properties and conjugate conduction are carried out for gas-side Reynolds numbers $Re_g ≈ 8.0$ x $10^2 - 3.6$ x $10^3$ (mass flow rates 0.5 – 2.5 g/s), and the designs are compared in terms of surface heat flux, Nusselt number, friction factor and hydrothermal performance factor (HTPF). For this already-promoted fin, the additional downstream winglets provide moderate, incremental hydrothermal gains. At the highest Reynolds number, the best non-perforated design (curved-alula) increases surface heat flux from 1630.9 to 1794.7 kW/m² (∼ 10 % gain) and the Nusselt number from 227.6 to 242.6 (∼ 7 % gain), while the friction factor rises from 0.26 to about 0.30, yielding HTPF values close to unity (∼ 0.9 – 1.0). Introducing circular perforations into the curved-alula winglets acts mainly as a wake-bleeding refinement: the three-hole configuration provides a heat flux of 1824.7 kW/m² and a pressure drop of 127.9 Pa, with HTPF in the range ∼ 1.03 – 1.14 and a small (∼ 1 – 3 %) improvement over the solid curved-alula design. Flow-field analysis shows that the perforated curved-alula VGs shrink tube-wake regions, thin the thermal boundary layer and homogenize the fin-surface temperature (outlet-gas temperature ∼ 510 – 520 K and fin-surface temperature ∼ 420 – 421 K for the three-hole case). An optimal flue-gas mass flow rate of ∼ 1 g/s ($Re_g ≈ 1.5$ x $10^3$) is identified, beyond which additional heat-transfer gains are offset by rapidly increasing pressure losses. Overall, the results highlight that initial fin geometry and VG placement are as important as VG shape: alula-based winglets are expected to yield larger relative gains on simpler flat-fin layouts or when positioned closer to the fin leading edge and tube

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Investigating 3,4-bis(3-nitrofurazan-4-yl)furoxan detonation with a rapidly tuned density functional tight binding model

In this work, we describe a machine learning approach to rapidly tune density functional tight binding models for the description of detonation chemistry in organic molecular materials. Resulting models enable simulations on the several 10s of ps scales characteristic to these processes, with “quantum-accuracy.” We use this approach to investigate early shock chemistry in 3,4-bis(3-nitrofurazan-4-yl)furoxan, a hydrogen-free energetic material known to form onion-like nanocarbon particulates following detonation. We find that the ensuing chemistry is significantly characterized by the formation of large C x N y O z species, which are likely precursors to the experimentally observed carbon condensates. Beyond utility as a means of investigating detonation chemistry, the present approach can be used to generate quantum-based reference data for the development of full machine-learned interatomic potentials capable of simulation on even greater time and length scales, i.e., for applications where characteristic time scales exceed the reach of methods including Kohn–Sham density functional theory, which are commonly used for reference data generation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗