Search NASA⌕ Search

SEARCH · Search NASA

Results for “enumerators”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Effect of Image Classification Accuracy on Dasymetric Population Estimation

Dasymetric mapping involves the disaggregation of count data, usually relating to population/demographics, from census enumeration areas to smaller target zones with the aid of an ancillary layer related to population density. The ancillary layer is often a binary classification such as developed versus undeveloped, building versus non-building, and residential versus non-residential, in which one class is treated as populated and the other as unpopulated. While dasymetric mapping relies heavily on ancillary data, little research has been done to address the error in ancillary data and its effects on dasymetric mapping accuracy. This chapter reports our research effort to investigate the effect of image classification accuracy on dasymetric population estimates by developing a binomial classification of buildings from high-resolution remote sensor imagery. The classifier was systematically and iteratively manipulated to generate a series of outputs with variegated accuracy characteristics. Lastly, we generated a corresponding series of population estimates based on the mapped building area from each iteration to investigate the relationship between the accuracy of classification and population estimation.

McKee, Jacob↗
DOE OSTI2023

Materials Design Directions for Solar Thermochemical Water Splitting

The sustainable, economical production of molecular hydrogen is a crucial component of a net zero-greenhouse-gas-emissions future. Solar thermochemical water splitting (STWS) offers a renewable route to hydrogen with the potential to help decarbonize several industries, including transportation, manufacturing, mining, metals processing, and electricity generation, as well as provide sustainable hydrogen as a chemical feedstock. STWS uses high temperatures generated from concentrated sunlight or other sustainable means for high-temperature heat to produce hydrogen and oxygen from steam. For example, in its simplest form of a two-step thermochemical cycle, a redox-active metal oxide is heated to ≈1700-2000 K, driving off molecular oxygen while producing oxygen vacancies in the material. The reduced metal oxide then cools (ideally with the extracted heat recuperated for re-use) and, in a separate step, comes into contact with steam, which reacts with oxygen vacancies to produce molecular hydrogen while recovering the original state of the metal oxide. Despite its promising use of the entire solar spectrum to split water thermochemically, the current estimated cost of hydrogen produced via STWS is ≈4-6× the U.S. Department of Energy (DOE) Hydrogen Shot target value of $1/kg. One contributing approach to bridging this cost gap is the design of new materials with improved thermodynamic properties to enable higher efficiencies. The state-of-the-art (SOA) redox-active metal oxide for STWS is ceria (CeO 2 ), due to its close to optimal, although too high, oxygen vacancy formation enthalpy and large configurational and electronic entropy of reduction. However, ceria requires high operating temperatures and its efficiency is insufficient. Therefore, efforts to increase the efficiency of STWS cycles have focused on further optimizing oxygen vacancy formation enthalpies and augmenting the reduction entropy via substitution or doping and materials discovery schemes. Examples of the latter include the perovskites BaCe 0.25 Mn 0.75 O 3 and (Ca,Ce)(Ti,Mn)O 3 . These efforts and others have revealed intuitive chemical principles for the efficient and systematic design of more effective materials, such as the strong correlation between the enthalpies of crystal bond dissociation and solid-state cation reduction with the enthalpy of oxygen vacancy formation, as well as configurational entropy augmentation via the coexistence of two or more redox-active cation sublattices. The purpose of this chapter is to prepare the reader with an up-to-date account of STWS redox-active materials, both the SOA and promising newcomers, as well as to provide chemically intuitive strategies for improving their cycle efficiencies through materials design – in conjunction with ongoing efforts in reactor engineering and gas separations – to reach the cost points for commercial viability. First, we will introduce the thermodynamics of STWS using a two-step, metal-oxide, thermochemical cycle with economics in mind. We also will compare the pros and cons of processes that do or do not involve phase changes. Second, we will describe the qualities that make ceria the SOA STWS redox-active material, as well as its limitations. Third, we will survey some of the most promising candidates to date in the search for materials to supplant ceria, emphasizing the post-ternary, metal-oxide-perovskite alloys. Lastly, we will enumerate and discuss the following materials design directions for STWS redox-active materials: crystal reduction potentials as a proxy for oxygen vacancy formation enthalpies, engineering the electronic and configurational entropy of reduction via f-shells and simultaneous redox, and vetting materials stability via temperature-dependent phase diagrams and melting-point prediction.

08 HYDROGEN↗
DOE OSTI2023

Computational Investigation of MAX as Intercalation Host for Rechargeable Aluminum‐Ion Battery

Abstract Layered carbides and their analogs with MAX phase (general formula AM n+1 X n ) have emerged as promising candidates for energy storage and conversion applications. One frontier for energy storage is using MAX as an Al‐ion intercalation electrode. Given that many MAXs have Al as the A sites, the structure can potentially serve as a stable host for Al intercalation. Here in this work, 425 ternary MAX Al‐ion battery electrodes are computationally enumerated. Specifically, first principal phase diagram calculations are performed on the combinatorial space of 17 types of typical transition metals, five types of anions (C, N, B, Si, and P), three types of stoichiometries (n = 1, 2, and 3) and two types of layered stackings (α and β). Among all the ternary MAX materials, 44 candidates show reasonable synthetic accessibility, and six with extraordinary performance are predicted to be promising Al‐ion battery electrodes. With the phase stability, and electrochemical performance (average voltage, theoretical capacity, energy density, and Al diffusion barrier), the work provides a comprehensive computational assessment of the great opportunities behind MAX‐based Al‐ion batteries.

Chemistry↗
DOE OSTI2018

Minimum Energy of Multicomponent Distillation Systems Using Minimum Additional Heat and Mass Integration Sections

Heat and mass integration to consolidate distillation columns in a multicomponent distillation configuration can lead to a number of new energy efficient and cost effective configurations. In this paper, we identify a powerful and simple-to-use fact about heat and mass integration. The newly developed heat and mass integrated configurations, which we call as HMP configurations, involve first introducing thermal couplings to all intermediate transfer streams, followed by consolidating columns associated with a lighter pure product reboiler and a heavier pure product condenser. A systematic method of enumerating all HMP configurations is introduced. We compare the energy savings of HMP configurations with the well-known fully thermally coupled (FTC) configurations. We demonstrate that HMP configurations can have very similar and sometimes even the same minimum total vapor duty requirement as the FTC configuration, while using far less number of column sections, intermediate transfer streams, and thermal couplings than the FTC configurations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

A Comprehensive Comparative Study of Active Learning Schemes for Nanophotonics Design

We present a benchmarking study of active learning (AL) schemes for designing planar multilayer nanophotonic metamaterials, where the design tasks are formulated as binary optimization problems. Different surrogate models, including factorization machine (FM), Gaussian process regression (GPR), and convolutional neural network (CNN), combined with different optimization methods, including exhaustive enumeration, discrete particle swarm optimization (DPSO), quantum annealing (QA), hybrid QA, and simulated annealing are studied. The benchmark cases investigated range from small problems with short binary lengths (N = 25) to large problems with N up to 100, focusing on the design of two classes of photonic structures, including antireflective coatings for the long-wavelength infrared region and transparent radiative coolers. For small problems, CNN coupled with DPSO in AL achieves the best performance. As N increases, FM with QA outperforms GPR and CNN. For FM-based AL, hybrid QA yields the best optimization results, particularly in high-dimensional cases (N = 100). These results demonstrate that the optimization method can significantly affect in AL performance as N increases, and that QA-based optimization can provide practical routes for mitigating the optimization bottleneck in high-dimensional problems.

Jung, Serang [Kyung Hee University, Korea]↗
DOE OSTI2015

Value Modeling for Enterprise Resilience

Abstract. The idea that resilience is a tangible, measureable, and desirable system attribute has grown rapidly over the last decade beyond is origins in explaining ecological, physiological, psychological, and social systems. Operational enterprise resilience requires two types of measurement. First, the system must monitor various operational conditions in order to respond to disruptions. These measurements are part of one or more observation, orientation, decision, and action (OODA) loops The OODA control processes that implement a resilience strategy use these measurements to provide robustness, rapid recovery and reconstitution. In order to assess the effectiveness of the resilience strategy, a different class of measurements is necessary. This second type consists of measurements about how well the OODA processes cover critical enterprise functions and the hazards to which the enterprise is exposed. They allow assessment of how well enterprise management processes anticipate, mitigate, and adapt to a changing environment and the degree to which the system is fault tolerant. This paper nominates a theoretical framework, in the form of definitions, a model, and a syntax, that accounts for this important distinction, and in so doing provides a mechanism for bridging resilience management process models and the many proposed cyber-defense metric enumerations.

Henderson, Dale L.↗
DOE OSTI2022

Retracted: Monitoring Hatchery Broodstock Composition and Genetic Variation of Spring/Summer Chinook Salmon in the Columbia River Basin with Multigeneration Pedigrees

Abstract Hatchery production of Chinook Salmon Oncorhynchus tshawytscha in the Columbia River basin comprises most of the anadromous salmonid production in this region. Hatchery facilities and programs serve to mitigate for impacts to salmonids due to the construction and operation of hydropower dams and habitat impacts from development in addition to the conservation and restoration of natural populations. A genetic method referred to as parentage-based tagging (PBT) enables highly reliable detection of hatchery-origin fish and inference of multigeneration pedigrees. This study compiles 11 years of PBT data from nearly 125,000 interior stream-type Chinook Salmon from 24 spawning hatcheries located in tributaries of the mid- and upper Columbia River as well as the Salmon, Clearwater, and Grande Ronde River subbasins. Multigenerational pedigrees allowed investigation of the proportion of natural- and hatchery-origin broodstock (pNOB and pHOB, respectively) for each hatchery and enumeration of the scale of production between segregated and integrated programs. We then compared how pHOB and the scale of production influenced the number of stray fish observed, genetic diversity, relatedness, and age-class compositions within broodstocks. Over 91.0% of hatchery broodstock could be assigned back to their parents, and there was an overall rate of less than 1.0% of broodstock that were unintentionally incorporated into nonnatal hatchery programs. We evaluated 14 segregated programs with 0.0–10.0% pNOB, 7 intermediate programs (10.1–50.0% pNOB), and 3 integrated programs (>50.0% pNOB). There was no correlation between the scale of production or pNOB with the level of genetic diversity, but as production size increased, so did the effective number of breeders. This study demonstrates the utility of PBT as a monitoring tool for hatchery broodstocks, and results suggest that segregated and integrated programs have tradeoffs that generally align with their intended broodstock management purpose of providing fish for harvest and/or fish for supplementation or reintroduction.

Horn, Rebekah L.↗
DOE OSTI2023

Multigeneration Pedigrees to Monitor Hatchery Broodstock Composition and Genetic Variation of Spring/Summer Chinook Salmon in the Columbia River Basin

Abstract Hatchery production of Chinook Salmon Oncorhynchus tshawytscha in the Columbia River basin comprises most of the anadromous salmonid production in this region. Hatchery facilities and programs serve to mitigate for impacts to salmonids due to the construction and operation of hydropower dams and habitat impacts from development in addition to the conservation and restoration of natural populations. A genetic method referred to as parentage-based tagging (PBT) enables highly reliable detection of hatchery-origin fish and inference of multigeneration pedigrees. This study compiles 11 years of PBT data from nearly 125,000 interior stream-type Chinook Salmon from 24 spawning hatcheries located on tributaries of the mid- and upper Columbia River and in the Salmon, Clearwater, and Grande Ronde River subbasins. Multigenerational pedigrees allowed for investigation of the proportions of natural- and hatchery-origin broodstock (pNOB and pHOB, respectively) for each hatchery and enumeration of the scale of production between segregated and integrated programs. We then compared how pHOB and the scale of production influenced the number of stray fish observed, genetic diversity, relatedness, and age-class compositions within broodstocks. Over 91.0% of hatchery broodstock could be assigned back to their parents, and overall less than 1.0% of broodstock consisted of fish that were unintentionally incorporated into nonnatal hatchery programs. We evaluated 11 segregated programs with 0.0–10.0% pNOB, 9 intermediate programs (10.1–50.0% pNOB), and 3 integrated programs (>50.0% pNOB). There was no correlation between the scale of production or pNOB with the level of genetic diversity, but as production size increased, so did the effective number of breeders. This study demonstrates the utility of PBT as a monitoring tool for hatchery broodstocks, and results suggest that segregated and integrated programs have tradeoffs that generally align with their intended broodstock management purpose of providing fish for harvest and/or fish for supplementation or reintroduction.

Horn, Rebekah L.↗
DOE OSTI2024

Computational tools and algorithms for ion mobility spectrometry-mass spectrometry

Ion mobility spectrometry-mass spectrometry (IMS-MS or IM-MS) is a powerful analytical technique that combines the gas-phase separation capabilities of IM with the identification and quantification capabilities of MS. IM-MS can differentiate molecules with indistinguishable masses but different structures (e.g., isomers, isobars, molecular classes, and contaminant ions). The importance of this analytical technique is reflected by a staged increase in the number of applications for molecular characterization across a variety of fields, from different MS-based omics (proteomics, metabolomics, lipidomics, etc.) to the structural characterization of glycans, organic matter, proteins, and macromolecular complexes. With the increasing application of IM-MS there is a pressing need for effective and accessible computational tools. This article presents an overview of the most recent free and open-source software tools specifically tailored for the analysis and interpretation of data derived from IM-MS instrumentation. This review enumerates these tools and outlines their main algorithmic approaches, while highlighting representative applications across different fields. Finally, a discussion of current limitations and expectable improvements is presented.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Accounting for nonuniformity of bulk‐solvent: A mosaic model

Abstract A flat mask‐based model is almost universally used in macromolecular crystallography to account for disordered (bulk) solvent. This model assumes any voxel of the crystal unit cell that is not occupied by the atomic model is occupied by the solvent. The properties of this solvent are assumed to be exactly the same across the whole volume of the unit cell. While this is a reasonable approximation in practice, there are a number of scenarios where this model becomes suboptimal. In this work, we enumerate several of these scenarios and describe a new generalized approach to modeling the bulk‐solvent which we refer to as mosaic bulk‐solvent model. The mosaic bulk‐solvent model allows nonuniform features of the solvent in the crystal to be accounted for in a computationally efficient way. It is implemented in the computational crystallography toolbox and the Phenix software.

Afonine, Pavel V.↗
DOE OSTI2014

Wedge sampling for computing clustering coefficients and triangle counts on large graphs

Graphs are used to model interactions in a variety of contexts, and there is a growing need to quickly assess the structure of such graphs. Some of the most useful graph metrics are based on triangles, such as those measuring social cohesion. Despite the importance of these triadic measures, algorithms to compute them can be extremely expensive. We discuss the method of wedge sampling. This versatile technique allows for the fast and accurate approximation of various types of clustering coefficients and triangle counts. Furthermore, these techniques are extensible to counting directed triangles in digraphs. Our methods come with provable and practical time-approximation tradeoffs for all computations. We provide extensive results that show our methods are orders of magnitude faster than the state of the art, while providing nearly the accuracy of full enumeration.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Making machine learning a useful tool in the accelerated discovery of transition metal complexes

Abstract As machine learning (ML) has matured, it has opened a new frontier in theoretical and computational chemistry by offering the promise of simultaneous paradigm shifts in accuracy and efficiency. Nowhere is this advance more needed, but also more challenging to achieve, than in the discovery of open‐shell transition metal complexes. Here, localized d or f electrons exhibit variable bonding that is challenging to capture even with the most computationally demanding methods. Thus, despite great promise, clear obstacles remain in constructing ML models that can supplement or even replace explicit electronic structure calculations. In this article, I outline the recent advances in building ML models in transition metal chemistry, including the ability to approach sub‐kcal/mol accuracy on a range of properties with tailored representations, to discover and enumerate complexes in large chemical spaces, and to reveal opportunities for design through analysis of feature importance. I discuss unique considerations that have been essential to enabling ML in open‐shell transition metal chemistry, including (a) the relationship of data set size/diversity, model complexity, and representation choice, (b) the importance of quantitative assessments of both theory and model domain of applicability, and (c) the need to enable autonomous generation of reliable, large data sets both for ML model training and in active learning or discovery contexts. Finally, I summarize the next steps toward making ML a mainstream tool in the accelerated discovery of transition metal complexes. This article is categorized under: Electronic Structure Theory > Density Functional Theory Software > Molecular Modeling Computer and Information Science > Chemoinformatics

Kulik, Heather J.↗
DOE OSTI2024

The role of stereochemistry in combustion processes

Stereochemical effects significantly influence chemical processes, yet it is not well understood if they are a leading source of uncertainty in combustion modeling. Stereochemistry influences a combustion model (i) at the earliest stage of its construction when mapping the reaction network, (ii) in the computation of individual thermochemical and rate parameters, and (iii) in the prediction of combustion observables. The present work reviews the importance of enumerating stereochemical species and reactions at each of these steps. Further, it analyzes the separate influence of several types of stereochemistry, including geometric, optical, and fleeting transition state diastereomers. Three reaction networks serve to examine which stages of low-temperature oxidation are most affected by stereochemistry, including the first and second oxidation of n-butane, the third oxidation of n-pentane, and the early stages of pyrolysis of 1- and 2-pentene. The 149 reactions in the n-butane mechanism are expanded to 183 reactions when accounting for diastereomerism. Each of these 183 reactions is parameterized with ab initio kinetics computations to determine that, for the n-butane mechanism, the median factor of diastereomeric deviation is 3.5 at 360 K for rate constants and as high as 1.6 for mechanism reactivity, in terms of ignition delay times, as opposed to a mechanism without stereochemical expansion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

The Zintl Concept Applied to Intergrowth Structures: Electron‐Hole Matching, Stacking Preferences, and Chemical Pressures in Pd 5 InAs

Abstract Enumerating the potential stacking sequences of layers is a fundamental way to account for the structure diversity of solid state compounds. In many cases, these stacking variations represent polymorphs with only small energetic differences. Here, we examine a compound for which the preferred stacking pattern instead reveals key aspects about its chemical bonding: Pd 5 InAs. Its structure is based on the intergrowth of slabs of the AuCu 3 and PtHg 2 (or alternatively, fluorite) structure types. Two basic stacking arrangements are available to this compound, represented by the Pd 5 TlAs and HoCoGa 5 structure types. DFT total energy calculations reveal that the former outcompetes the latter by a staggering 0.65 eV/formula unit. Through a combination of DFT‐reversed approximation Molecular Orbital (DFT‐raMO) and DFT‐Chemical Pressure (DFT‐CP) analysis we trace this preference to two factors. First, with DFT‐raMO analysis, we derive a Zintl‐like bonding scheme of Pd 5 InAs. This scheme, along with the inspection of selected crystal orbitals, is then connected to preferred stacking through the coordination environments of the Pd atoms at the interface between the Pd−In and Pd−As layers. In the hypothetical HoCoGa 5 ‐type and observed Pd 5 InAs‐type structures, different Pd coordination environments arise at the interfaces. The hypothetical structure features square planar PdIn 2 As 2 units, in each of which the same 4d‐orbital serves in the Pd sublattice's role as both Lewis acid (for interactions with the As) and Lewis base (for interactions with the In). In the observed structure, tetrahedral PdIn 2 As 2 units occur instead, so that these contradictory roles are distributed to separate 4d‐orbitals, leading to more effective bonding. DFT‐CP analysis illustrates that this driving force for the Pd 5 TlAs‐type arrangement is supplemented by a favorable alignment of the packing tensions in the parent structures. Altogether, the resulting picture demonstrates how the reaction of simple intermetallic structures to form intergrowths can be guided by recognizable chemical interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

A periodic table of effective field theories

We systematically explore the space of scalar effective field theories (EFTs) consistent with a Lorentz invariant and local S-matrix. To do so we define an EFT classification based on four parameters characterizing 1) the number of derivatives per interaction, 2) the soft properties of amplitudes, 3) the leading valency of the interactions, and 4) the spacetime dimension. Carving out the allowed space of EFTs, we prove that exceptional EFTs like the non-linear sigma model, Dirac-Born-Infeld theory, and the special Galileon lie precisely on the boundary of allowed theory space. Using on-shell momentum shifts and recursion relations, we prove that EFTs with arbitrarily soft behavior are forbidden and EFTs with leading valency much greater than the spacetime dimension cannot have enhanced soft behavior. We then enumerate all single scalar EFTs in d < 6 and verify that they correspond to known theories in the literature. Finally, our results suggest that the exceptional theories are the natural EFT analogs of gauge theory and gravity because they are one-parameter theories whose interactions are strictly dictated by properties of the S-matrix.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Fibers add flavor. Part II. 5d SCFTs, gauge theories, and dualities

In [1, 2] we proposed an approach based on graphs to characterize 5d superconformal field theories (SCFTs), which arise as compactifications of 6d $$ \mathcal{N} $$ N = (1 , 0) SCFTs. The graphs, so-called combined fiber diagrams (CFDs), are derived using the realization of 5d SCFTs via M-theory on a non-compact Calabi-Yau threefold with a canonical singularity. In this paper we complement this geometric approach by connecting the CFD of an SCFT to its weakly coupled gauge theory or quiver descriptions and demonstrate that the CFD as recovered from the gauge theory approach is consistent with that as determined by geometry. To each quiver description we also associate a graph, and the embedding of this graph into the CFD that is associated to an SCFT provides a systematic way to enumerate all possible consistent weakly coupled gauge theory descriptions of this SCFT. Furthermore, different embeddings of gauge theory graphs into a fixed CFD can give rise to new UV-dualities for which we provide evidence through an analysis of the prepotential, and which, for some examples, we substantiate by constructing the M-theory geometry in which the dual quiver descriptions are manifest.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

23, 381, 6242, 103268, 1743183, ...:Hilbert series for CP-violating operators in SMEFT

We introduce a systematic method to classify the Standard Model Effective Field Theory (SMEFT) operators based on their CP properties with the Hilbert series techniques. Our method makes it possible to enumerate operators violating CP symmetry in a few seconds. We present the complete classification of dimension eight operators under CP transformation, and the number of CP-odd or CP-violating operators are listed up to dimension 14. We also provide a companion code in Form that allows anybody to reproduce our results.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

A physical basis for cosmological correlators from cuts

Significant progress has been made in our understanding of the analytic structure of FRW wavefunction coefficients, facilitated by the development of efficient algorithms to derive the differential equations they satisfy. Moreover, recent findings indicate that the twisted cohomology of the associated hyperplane arrangement defining FRW integrals overestimates the number of integrals required to define differential equations for the wave-function coefficient. We demonstrate that the associated dual cohomology is automatically organized in a way that is ideal for understanding and exploiting the cut/residue structure of FRW integrals. Utilizing this understanding, we develop a systematic approach to organize compatible sequential residues, which dictates the physical subspace of FRW integrals for any n -site, ℓ-loop graph. In particular, the physical subspace of tree-level FRW wavefunction coefficients is populated by differential forms associated to cuts/residues that factorize the integrand of the wavefunction coefficient into only flat space amplitudes. After demonstrating the validity of our construction using intersection theory, we develop simple graphical rules for cut tubings that enumerate the space of physical cuts and, consequently, differential forms without any calculation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗