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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Measuring uncertainty by extracting fuzzy rules using rough sets and extracting fuzzy rules under uncertainty and measuring definability using rough sets

Computers are not designed to handle terms where uncertainty is present. To deal with uncertainty, techniques other than classical logic must be developed. This paper examines the concepts of statistical analysis, the Dempster-Shafer theory, rough set theory, and fuzzy set theory to solve this problem. The fundamentals of these theories are combined to provide the possible optimal solution. By incorporating principles from these theories, a decision-making process may be simulated by extracting two sets of fuzzy rules: certain rules and possible rules. From these rules a corresponding measure of how much we believe these rules is constructed. From this, the idea of how much a fuzzy diagnosis is definable in terms of its fuzzy attributes is studied.

Worm, Jeffrey A.↗
NASA NTRS2018

The Number of Support Constraints for Overlapping Set Optimization with Nested Admissible Sets Is Equal to One

This paper reports on the formalization of a recent result by Crespo, et al., as found in the references. The formalized result bounds the number of support constraints in a particular type of optimization problem. The problem involves discovering an optimal member of a family of sets that overlaps each member of a constraining collection of sets. The particular case addressed here concerns optimizations in which the family of sets is nested. The primary results were formalized in the interactive theorem prover PVS and support the claim that a single support constraint exists in very general circumstances.

Siratt, John↗
DOE OSTI2019

Delineating Facies Spatial Distribution by Integrating Ensemble Data Assimilation and Indicator Geostatistics with Level-Set Transformation

The facies-based approach has been widely adopted to delineate an aquifer into distinct geological units with unique distributions of hydraulic, physical, and/or chemical properties. The recent development in ensemble-based data assimilation methods allows both the direct and indirect data to be used to improve facies delineation. A major difficulty in those applications is to honor the spatial continuity and avoid overfitting after data assimilation. We introduce a new facies delineation framework to integrate ensemble data assimilation with traditional transition probability-based geostatistics. A level-set concept is used to parametrize discrete facies indicators and for updating facies shape. During the iterative data assimilation process, we impose spatial continuity by conditioning facies field generation on points selected adaptively based on their sensitivity to observation data. This reconditioning step is a key step to maintain spatial continuity and overcome over-fitting problems in inversion. We selected two examples to evaluate the performance of the new framework in estimating facies-based permeability field. The first example is a two-dimensional synthetic system with transient head data induced by pumping tests used for delineating two facies. The second example is a three-dimensional case with three facies, conceptualized from a field tracer experiment within the Columbia River corridor in Washington State, USA. Both examples demonstrate that the new method can adequately capture the spatial pattern of hydrofacies with reconditioning, which leads to the improved prediction of system behaviors.

Song, Xuehang↗
DOE OSTI2022

Intersections of Disadvantaged Communities and Renewable Energy Potential: Data Set and Analysis to Inform Equitable Investment Prioritization in the United States

Renewable energy development can bolster local economies through job creation, local tax revenues, and reduced energy costs; however, communities most in need of economic development and employment opportunities often see lower levels of renewable energy deployment. We sought to identify areas where disadvantaged community indicators and high generation potential from cost-effective renewable energy opportunities intersect and deployment could lead to economic development and job creation. This presentation will highlight several of our findings. This research and the associated county-level data set are intended to inform national- and state-level energy-related assistance programs, economic development efforts, and infrastructure programs seeking to prioritize investments in disadvantaged communities.

community energy planning↗
DOE OSTI2021

Validation of the Community Land Model Version 5 over the Contiguous United States (CONUS) using in situ and remote sensing data sets

The Community Land Model (CLM) is an effective tool to simulate the biophysical and biogeochemical processes and their interactions with the atmosphere. Although CLM Version 5 (CLM5) constitutes various updates in these processes, its performance in simulating energy, water and carbon cycles over the Contiguous United States (CONUS) at scales which land surface changes and hydrometeorological and hydroclimatological applications are more locally relevant is yet to be assessed. In this study, we conducted three simulations at 0.125? during 1979-2018 over the CONUS using different configurations of CLM, namely CLM5-biogeochemistry (CLM5BGC), CLM4.5BGC, and CLM5-satellite phenology (CLM5SP). We validated and compared their simulations against multiple remote-sensed and in-situ datasets. Overall, the parametric and structural updates (e.g., carbon cost for nitrogen uptake, variable soil thickness, dry surface layer) in CLM5 improve its ability in capturing terrestrial biogeochemical dynamics. The low evapotranspiration in CLM5BGC is associated with biases in simulating vegetation phenological characteristics rather than soil water limitations. The mismatch between CLM5BGC-simulated peak leaf area index and reference data can be attributed to CLM5BGC's inability in simulating phenology of trees and grasses. The differences between CLM-simulated irrigation and reference estimates can be attributed to differences between processes represented in models and in reality, and uncertainties in input and validation datasets. Evaluation against observations at small catchments suggest that hydrologic parameters needed to be calibrated to improve simulations of runoff, especially subsurface runoff. Additional efforts are needed to incorporate spatially-distributed plant phenology and physiology parameters and regional-specific agricultural management practices (e.g., planting, harvest).

Cheng, Yanyan↗
DOE OSTI2014

Narrowing the error in electron correlation calculations by basis set re-hierarchization and use of the unified singlet and triplet electron-pair extrapolation scheme: Application to a test set of 106 systems

A method previously suggested to calculate the correlation energy at the complete one-electron basis set limit by reassignment of the basis hierarchical numbers and use of the unified singlet- and triplet-pair extrapolation scheme is applied to a test set of 106 systems, some with up to 48 electrons. The approach is utilized to obtain extrapolated correlation energies from raw values calculated with second-order Møller-Plesset perturbation theory and the coupled-cluster singles and doubles excitations method, some of the latter also with the perturbative triples corrections. The calculated correlation energies have also been used to predict atomization energies within an additive scheme. Good agreement is obtained with the best available estimates even when the (d, t) pair of hierarchical numbers is utilized to perform the extrapolations. This conceivably justifies that there is no strong reason to exclude double-zeta energies in extrapolations, especially if the basis is calibrated to comply with the theoretical model.

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

Minimizing Optimal Transport for Functions with Fixed-Size Nodal Sets

Consider the class of zero-mean functions with fixed L ∞ and L 1 norms and exactly N ϵ N nodal points. Which functions f minimize W p (f + ,f – ), the Wasserstein distance between the measures whose densities are the positive and negative parts? We provide a complete solution to this minimization problem on the line and the circle, which provides sharp constants for previously proven “uncertainty principle”-type inequalities, i.e., lower bounds on N • W p (f + ,f – ). We further show that, while such inequalities hold in many metric measure spaces, they are no longer sharp when the non-branching assumption is violated; indeed, for metric star-graphs, the optimal lower bound on W p (f + ,f – ) is not inversely proportional to the size of the nodal set, N. Here, based on similar reductions, we make connections between the analogous problem of minimizing W p (f + ,f – ) for f defined on Ω C R d with an equivalent optimal domain partition problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Setting and stiffening of cementitious components in Cast Stone waste form for disposal of secondary wastes from the Hanford waste treatment and immobilization plant

Cast Stone is a cementitious waste form, a viable option to immobilize secondary nuclear liquid wastes generated from the Hanford Waste Treatment and Immobilization Plant. However, no study has been performed to understand the flow and stiffening behavior, which is essential to ensure proper workability and is important to safety in a nuclear waste field-scale application. X-ray diffraction, rheology, and ultrasonic wave reflection methods were used to understand the specific phase formation and stiffening of Cast Stone. Our results showed a good correlation between rheological properties of the fresh mixture and phase formation in Cast Stone. Secondary gypsum formation was observed with low concentration simulants, and the formation of gypsum was suppressed in high concentration simulants. A threshold concentration for the drastic change in stiffening was found at 1.56 M Na concentration. It was found that the stiffening of Cast Stone was strongly dependent on the concentration of simulant. Highlights: • A combination of XRD, UWR, and rheology gives a better understanding of Cast Stone. • Stiffening of Cast Stone was strongly dependent on the concentration of simulant. • A drastic change in stiffening of Cast Stone was found at 1.56 M Na concentration.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Dimensional reduction in manifoldlike causal sets

We investigate the behavior of small subsets of causal sets that approximate Minkowski space in three, four, and five dimensions, and show that their effective dimension decreases smoothly at small distances. The details of the short distance behavior depend on a choice of dimensional estimator, but for a reasonable version of the Myrheim-Meyer dimension, the minimum dimension is d ≈ 2 , reproducing results that have been seen in other approaches to quantum gravity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Automated detection of photovoltaic cleaning events: A performance comparison of techniques as applied to a broad set of labeled photovoltaic data sets

Extracting accurate soiling loss information from photovoltaic (PV) production data first requires segmenting the time series data per natural or manually occurring cleaning events. Maintenance logs are often incomplete, rain data are often unavailable, and the debate on rain thresholds for cleaning and dew or wind cleanings is still ongoing. The present work aims to overtake these issues by improving automated methods to detect these cleaning events and therefore improve extraction of soiling loss information. Time series power production data from 22 PV inverters were labeled for natural or manually occurring cleaning events. The data sets were carefully selected to include varying degrees of soiling, cleaning events, and noise. Several algorithms, including filtering logic and change point detection, were examined for efficacy at detecting the labeled cleanings. All the methods introduced except for changepoint detection showed significant improvement at detecting the labeled cleaning events per the mean F 1 score. Furthermore, the highest performing cleaning detection algorithm achieved an absolute increase in the mean F 1 score of 43% over the default version of the RdTools stochastic rate and recovery (SRR) algorithm. The highest performing algorithm included irradiance filtering and a cleaning detection threshold, adjusted based on the 40-day centered rolling median of the absolute day-to-day deviations in the daily performance index (PI). Furthermore, these improvements are promising as cleaning detection is an essential step in the automated analysis of PV soiling.

14 SOLAR ENERGY↗
DOE OSTI2017

Identifying the minor set cover of dense connected bipartite graphs via random matching edge sets

Using quantum annealing to solve an optimization problem requires minor embedding a logic graph into a known hardware graph. We introduce the minor set cover (MSC) of a known graph GG : a subset of graph minors which contain any remaining minor of the graph as a subgraph, in an effort to reduce the complexity of the minor embedding problem. Any graph that can be embedded into GG will be embeddable into a member of the MSC. Focusing on embedding into the hardware graph of commercially available quantum annealers, we establish the MSC for a particular known virtual hardware, which is a complete bipartite graph. Furthermore, we show that the complete bipartite graph K N,N has a MSC of N minors, from which K N+1 is identified as the largest clique minor of K N,N . In the case of determining the largest clique minor of hardware with faults we briefly discussed this open question.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Constraints on models of the Higgs boson with exotic spin and parity using decays to bottom-antibottom quarks in the full CDF data set

In this study, a search for particles with the same mass and couplings as those of the standard model Higgs boson but different spin and parity quantum numbers is presented. We test two specific alternative Higgs boson hypotheses: a pseudoscalar Higgs boson with spin-parity J P = 0 – and a gravitonlike Higgs boson with J P = 2 + , assuming for both a mass of 125 GeV/c 2 . We search for these exotic states produced in association with a vector boson and decaying into a bottom-antibottom quark pair. The vector boson is reconstructed through its decay into an electron or muon pair, or an electron or muon and a neutrino, or it is inferred from an imbalance in total transverse momentum. We use expected kinematic differences between events containing exotic Higgs bosons and those containing standard model Higgs bosons. The data were collected by the CDF experiment at the Tevatron proton-antiproton collider, operating at a center-of-mass energy of √s = 1.96 TeV, and correspond to an integrated luminosity of 9.45 fb –1 . We exclude deviations from the predictions of the standard model with a Higgs boson of mass 125 GeV/c 2 at the level of 5 standard deviations, assuming signal strengths for exotic boson production equal to the prediction for the standard model Higgs boson, and set upper limits of approximately 30% relative to the standard model rate on the possible rate of production of each exotic state.

Aaltonen, Timo Antero↗
DOE OSTI2016

Identification of the core set of carbon-associated genes in a bioenergy grassland soil

Despite the central role of soil microbial communities in global carbon (C) cycling, little is known about soil microbial community structure and even less about their metabolic pathways. Efforts to characterize soil communities often focus on identifying differences in gene content across environmental gradients, but an alternative question is what genes are similar in soils. These genes may indicate critical species or potential functions that are required in all soils. Here we identified the “core” set of C cycling sequences widely present in multiple soil metagenomes from a fertilized prairie (FP). Of 226,887 sequences associated with known enzymes involved in the synthesis, metabolism, and transport of carbohydrates, 843 were identified to be consistently prevalent across four replicate soil metagenomes. This core metagenome was functionally and taxonomically diverse, representing five enzyme classes and 99 enzyme families within the CAZy database. Though it only comprised 0.4% of all CAZy-associated genes identified in FP metagenomes, the core was found to be comprised of functions similar to those within cumulative soils. The FP CAZy-associated core sequences were present in multiple publicly available soil metagenomes and most similar to soils sharing geographic proximity. In soil ecosystems, where high diversity remains a key challenge for metagenomic investigations, these core genes represent a subset of critical functions necessary for carbohydrate metabolism, which can be targeted to evaluate important C fluxes in these and other similar soils.

Howe, Adina↗