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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Ensemble voting-based fault classification and location identification for a distribution system with microgrids using smart meter measurements

This study presents an ensemble learning approach for fault classification and location identification in a smart distribution network containing photovoltaics (PV)-based microgrid. Lack of available data points and the unbalanced nature of the distribution system make fault handling a challenging task for utilities. The proposed method uses event-driven voltage data from smart meters to classify and locate faults. The ensemble voting classifier is composed of three base learners; random forest, k-nearest neighbours, and artificial neural network. The fault location (FL) task has been formulated as a classification problem where the fault type is classified in the first step and based on the fault type, the faulty bus is identified. The method is tested on IEEE-123 bus system modified with added PV-based microgrid along with dynamic loading conditions and varying fault resistances from 0 to 20 Ω for both unbalanced and balanced fault types. A further sensitivity analysis has been done to test the robustness of the proposed method under various noise levels and data loss errors in the smart meter measurements. The ensemble method shows improved performance and robustness compared to some previously proposed FL methods. Finally, the proposed method has been experimentally validated on a real-time simulation-based testbed using a state-of-the-art digital real-time simulator, industry standard DNP3 communication protocol and a cpu-based control centre running the FL algorithm.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Improved uncertainty quantification in nondestructive assay for nonproliferation

This paper illustrates methods to improve uncertainty quantification (UQ) for non-destructive assay (NDA) measurements used in nuclear nonproliferation. First, it is shown that current bottom-up UQ applied to calibration data is not always adequate, for three main reasons: (1) Because there are errors in both the predictors and the response, calibration involves a ratio of random quantities, and calibration data sets in NDA usually consist of only a modest number of samples (3–10); therefore, asymptotic approximations involving quantities needed for UQ such as means and variances are often not sufficiently accurate; (2) Common practice overlooks that calibration implies a partitioning of total error into random and systematic error, and (3) In many NDA applications, test items exhibit non-negligible departures in physical properties from calibration items, so model-based adjustments are used, but item-specific bias remains in some data. Therefore, improved bottom-up UQ using calibration data should predict the typical magnitude of item-specific bias, and the suggestion is to do so by including sources of item-specific bias in synthetic calibration data that is generated using a combination of modeling and real calibration data. Second, for measurements of the same nuclear material item by both the facility operator and international inspectors, current empirical (top-down) UQ is described for estimating operator and inspector systematic and random error variance components. A Bayesian alternative is introduced that easily accommodates constraints on variance components, and is more robust than current top-down methods to the underlying measurement error distributions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Molecular organization in MAPLE-deposited conjugated polymer thin films and the implications for carrier transport characteristics

The morphological structure of poly(3-hexylthiophene) (P3HT) thin films deposited by both Matrix Assisted Pulsed Laser Evaporation (MAPLE) and solution spin-casting methods are investigated. We found that the MAPLE samples possessed a higher degree of disorder, with random orientations of polymer crystallites along the side-chain stacking, π-π stacking, and conjugated backbone directions. Furthermore, the average molecular orientations and relative degrees of crystallinity of MAPLE-deposited polymer films are insensitive to the chemistries of the substrates onto which they were deposited; this is in stark contrast to the films prepared by the conventional spin-casting technique. In spite of the seemingly unfavorable molecular orientations and the highly disordered morphologies, the in-plane charge carrier transport characteristics of the MAPLE samples are comparable to those of spin-cast samples, exhibiting similar transport activation energies (56 meV versus 54 meV) to those reported in the literature for high mobility polymers.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Giant Wilson loops and AdS 2 /dCFT 1

The 1/2-BPS Wilson loop in N = 4 supersymmetric Yang-Mills theory is an important and well-studied example of conformal defect. In particular, much work has been done for the correlation functions of operator insertions on the Wilson loop in the fundamental representation. In this paper, we extend such analyses to Wilson loops in the large-rank symmetric and antisymmetric representations, which correspond to probe D3 and D5 branes with AdS 2 × S 2 and AdS 2 × S 4 worldvolume geometries, ending at the AdS 5 boundary along a one-dimensional contour. We first compute the correlation functions of protected scalar insertions from supersymmetric localization, and obtain a representation in terms of multiple integrals that are similar to the eigenvalue integrals of the random matrix, but with important differences. Using ideas from the Fermi Gas formalism and the Clustering method, we evaluate their large N limit exactly as a function of the ’t Hooft coupling. The results are given by simple integrals of polynomials that resemble the Q-functions of the Quantum Spectral Curve, with integration measures depending on the number of insertions. Next, we study the correlation functions of fluctuations on the probe D3 and D5 branes in AdS. We compute a selection of three- and four-point functions from perturbation theory on the D-branes, and show that they agree with the results of localization when restricted to supersymmetric kinematics. We also explain how the difference of the internal geometries of the D3 and D5 branes manifests itself in the localization computation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

Caffeine improves reaction time, vigilance and logical reasoning during extended periods with restricted opportunities for sleep

Rationale Various occupational groups are required to maintain optimal physical and cognitive function during overnight periods of wakefulness, often with less than optimal sleep. Strategies are required to help mitigate the impairments in cognitive function to help sustain workplace safety and productivity. Objectives To test the effectiveness of repeated 200 mg doses of caffeine on cognitive function and live-fire marksmanship with soldiers during three successive nights of sustained wakefulness followed by 4-h afternoon sleep periods. Methods Twenty Special Forces personnel (28.6±4.7 years, 177.6±7.5 cm and 81.2±8.0 kg) were randomly assigned to receive four 200-mg doses of caffeine (n=10) or placebo (n= 10) during the late evening and early morning hours during three successive days. An afternoon 4-h sleep period followed. The psychomotor (PVT) and field (FVT) vigilance, logical reasoning (LRT) tests and a vigilance monitor assessed cognitive function throughout the study. Live-fire marksmanship requiring friend–foe discrimination was assessed. Results Caffeine maintained speed on the PVT (p<0.02), improved detection of events during FVT (p<0.001), increased number of correct responses to stimuli as assessed by the vigilance monitor (p<0.001) and increased response speed during the LRT (p<0.001) throughout the three overnight testing periods. Live-fire marksmanship was not altered by caffeine. Conclusions A total daily dose of 800 mg caffeine during successive overnight periods of wakefulness is an effective strategy to maintain cognitive function when optimal sleep periods during the day are not available.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Machine learning for graph-based representations of three-dimensional discrete fracture networks

Structural and topological information play a key role in modeling flow and transport through fractured rock in the subsurface. Discrete fracture network (DFN) computational suites such as dfnWorks (Hyman et al. Comput. Geosci. 84, 10–19 2015) are designed to simulate flow and transport in such porous media. Flow and transport calculations reveal that a small backbone of fractures exists, where most flow and transport occurs. Restricting the flowing fracture network to this backbone provides a significant reduction in the network’s effective size. However, the particle-tracking simulations needed to determine this reduction are computationally intensive. Such methods may be impractical for large systems or for robust uncertainty quantification of fracture networks, where thousands of forward simulations are needed to bound system behavior. In this paper, we develop an alternative network reduction approach to characterizing transport in DFNs, by combining graph theoretical and machine learning methods. We consider a graph representation where nodes signify fractures and edges denote their intersections. Using random forest and support vector machines, we rapidly identify a subnetwork that captures the flow patterns of the full DFN, based primarily on node centrality features in the graph. Our supervised learning techniques train on particle-tracking backbone paths found by dfnWorks, but run in negligible time compared to those simulations. In conclusion, we find that our predictions can reduce the network to approximately 20% of its original size, while still generating breakthrough curves consistent with those of the original network.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Exponential number of equilibria and depinning threshold for a directed polymer in a random potential

By extending the Kac–Rice approach to manifolds of finite internal dimension, we show that the mean number &lang;N{sub tot}&rang; of all possible equilibria (i.e. force-free configurations, a.k.a. equilibrium points) of an elastic line (directed polymer), confined in a harmonic well and submitted to a quenched random Gaussian potential in dimension d=1+1, grows exponentially &lang;N{sub tot}&rang; ~exp(r L) with its length L. The growth rate r is found to be directly related to the generalized Lyapunov exponent (GLE) which is a moment-generating function characterizing the large-deviation type fluctuations of the solution to the initial value problem associated with the random Schrödinger operator of the 1D Anderson localization problem. For strong confinement, the rate r is small and given by a non-perturbative (instanton, Lifshitz tail-like) contribution to GLE. For weak confinement, the rate r is found to be proportional to the inverse Larkin length of the pinning theory. As an application, identifying the depinning with a landscape “topology trivialization” phenomenon, we obtain an upper bound for the depinning threshold f{sub c}, in the presence of an applied force, for elastic lines and d-dimensional manifolds, expressed through the mean modulus of the spectral determinant of the Laplace operators with a random potential. We also discuss the question of counting of stable equilibria. Finally, we extend the method to calculate the asymptotic number of equilibria at fixed energy (elastic, potential and total), and obtain the (annealed) distribution of the energy density over these equilibria (i.e. force-free configurations). Some connections with the Larkin model are also established.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Fusion of Laboratory and Textual Data for Investigative Bioforensics

Chemical and biological forensic programs focus on the identification of a threat and acquisition of laboratory measurements to determine how a threat agent may have been produced. However, to generate investigative leads, it might also be useful to identify institutions where the same agent has been produced by the same or a very similar process, since the producer of the agent may have learned methods at a university or similar institution. We have developed a Bayesian network framework that fuses hard and soft data sources to assign probability to production practices. It combines the results of laboratory measurements with an automatic text reader to scan scientific literature and rank institutions that had published papers on the agent of interest in order of the probability that the institution has the capability to generate the sample of interest based on laboratory data. We demonstrate the Bayesian network on an example case from microbial forensics, predicting the methods used to produce Bacillus anthracis spores based on mass spectrometric measurements and identifying institutions that have a history of growing Bacillus spores using the same or highly similar methods. We illustrate that the network model can assign a higher posterior probability than expected by random chance to appropriate institutions when trained using only a small set of manually analyzed documents. This is the first example of an automated methodology to integrate experimental and textual data for the purpose of investigative forensics.

Webb-Robertson, Bobbie-Jo M.↗
DOE OSTI2012

Patient Preferences and Physician Practice Patterns Regarding Breast Radiotherapy

Purpose: There are multiple current strategies for breast radiotherapy (RT). The alignment of physician practice patterns with best evidence and patient preferences will enhance patient autonomy and improve cancer care. However, there is little information describing patient preferences for breast RT and physician practice patterns. Methods and Materials: Using a reliable and valid instrument, we assessed the preferences of 5,000 randomly selected women (with or without cancer) undergoing mammography. To assess practice patterns, 2,150 randomly selected physician-members of American Society for Radiation Oncology were surveyed. Results: A total of 1,807 women (36%) and 363 physicians (17%) provided usable responses. The 95% confidence interval is < {+-}2.3% for patients and < {+-}5.3% for physicians. Patient preferences were hypofractionated whole breast irradiation (HF-WBI) 62%, partial breast irradiation (PBI) 28%, and conventionally fractionated whole breast irradiation (CF-WBI) 10%. By comparison, 82% of physicians use CF-WBI for more than 2/3 of women and 56% never use HF-WBI. With respect to PBI, 62% of women preferred three-dimensional (3D)-PBI and 38% favor brachytherapy-PBI, whereas 36% of physicians offer 3D-PBI and 66% offer brachytherapy-PBI. 70% of women prefer once-daily RT over 10 days vs. twice-daily RT over 5 days. 55% of physicians who use PBI do not offer PBI on clinical trial. Conclusions: HF-WBI, while preferred by patients and supported by evidence, falls behind the unproven and less preferred strategy of PBI in clinical practice. There is a discrepancy between women's preferences for PBI modality and type of PBI offered by physicians. Further alignment is needed between practice patterns, patient preferences, and clinical evidence.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2012

Radiation Therapy Oncology Group Consensus Panel Guidelines for the Delineation of the Clinical Target Volume in the Postoperative Treatment of Pancreatic Head Cancer

Purpose: To develop contouring guidelines to be used in the Radiation Therapy Oncology Group protocol 0848, a Phase III randomized trial evaluating the benefit of adjuvant chemoradiation in patients with resected head of pancreas cancer. Methods and Materials: A consensus committee of six radiation oncologists with expertise in gastrointestinal radiotherapy developed stepwise contouring guidelines and an atlas for the delineation of the clinical target volume (CTV) in the postoperative treatment of pancreas cancer, based on identifiable regions of interest and margin expansions. Areas at risk for subclinical disease to be included in the CTV were defined, including nodal regions, anastomoses, and the preoperative primary tumor location. Regions of interest that could be reproducibly contoured on postoperative imaging after a pancreaticoduodenectomy were identified. Standardized expansion margins to encompass areas at risk were developed after multiple iterations to determine the optimal margin expansions. Results: New contouring recommendations based on CT anatomy were established. Written guidelines for the delineation of the postoperative CTV and normal tissues, as well as a Web-based atlas, were developed. Conclusions: The postoperative abdomen has been a difficult area for effective radiotherapy. These new guidelines will help physicians create fields that better encompass areas at risk and minimize dose to normal tissues.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

A 2-Stage Genome-Wide Association Study to Identify Single Nucleotide Polymorphisms Associated With Development of Erectile Dysfunction Following Radiation Therapy for Prostate Cancer

Purpose: To identify single nucleotide polymorphisms (SNPs) associated with development of erectile dysfunction (ED) among prostate cancer patients treated with radiation therapy. Methods and Materials: A 2-stage genome-wide association study was performed. Patients were split randomly into a stage I discovery cohort (132 cases, 103 controls) and a stage II replication cohort (128 cases, 102 controls). The discovery cohort was genotyped using Affymetrix 6.0 genome-wide arrays. The 940 top ranking SNPs selected from the discovery cohort were genotyped in the replication cohort using Illumina iSelect custom SNP arrays. Results: Twelve SNPs identified in the discovery cohort and validated in the replication cohort were associated with development of ED following radiation therapy (Fisher combined P values 2.1 Multiplication-Sign 10{sup -5} to 6.2 Multiplication-Sign 10{sup -4}). Notably, these 12 SNPs lie in or near genes involved in erectile function or other normal cellular functions (adhesion and signaling) rather than DNA damage repair. In a multivariable model including nongenetic risk factors, the odds ratios for these SNPs ranged from 1.6 to 5.6 in the pooled cohort. There was a striking relationship between the cumulative number of SNP risk alleles an individual possessed and ED status (Sommers' D P value = 1.7 Multiplication-Sign 10{sup -29}). A 1-allele increase in cumulative SNP score increased the odds for developing ED by a factor of 2.2 (P value = 2.1 Multiplication-Sign 10{sup -19}). The cumulative SNP score model had a sensitivity of 84% and specificity of 75% for prediction of developing ED at the radiation therapy planning stage. Conclusions: This genome-wide association study identified a set of SNPs that are associated with development of ED following radiation therapy. These candidate genetic predictors warrant more definitive validation in an independent cohort.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Is Pilocarpine Effective in Preventing Radiation-Induced Xerostomia? A Systematic Review and Meta-analysis

Purpose: To evaluate the efficacy of concomitant administration of pilocarpine on radiation-induced xerostomia in patients with head and neck cancers. Methods and Materials: The PubMed, Web of Science, Cochrane Library, and ClinicalTrials were searched to identify randomized, controlled trials studying the effect of concomitant administration of pilocarpine for radiation-induced xerostomia. Included trials were systematically reviewed, and quantifiable outcomes were pooled for meta-analysis. Outcomes of interest included salivary flow, clinician-rated xerostomia grade, patient-reported xerostomia scoring, quality of life, and adverse effects. Results: Six prospective, randomized, controlled trials in 8 articles were included in this systematic review. The total number of patients was 369 in the pilocarpine group and 367 in the control group. Concomitant administration of pilocarpine during radiation could increase the unstimulated salivary flow rate in a period of 3 to 6 months after treatment, and also reduce the clinician-rated xerostomia grade. Patient-reported xerostomia was not significantly impacted by pilocarpine in the initial 3 months but was superior at 6 months. No significant difference of stimulated salivary flow rate could be confirmed between the 2 arms. Adverse effects of pilocarpine were mild and tolerable. Conclusions: The concomitant administration of pilocarpine during radiation increases unstimulated salivary flow rate and reduces clinician-rated xerostomia grade after radiation. It also relieves patients' xerostomia at 6 months and possibly at 12 months. However, pilocarpine has no effect on stimulated salivary flow rate.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Time domain probabilistic seismic risk analysis using ground motion prediction equations of Fourier amplitude spectra

Modeling of Fourier amplitude spectra (FAS) of seismic motions has gained much attention in engineering seismology. In the past few years, several ground motion prediction equations (GMPEs) and inter-frequency correlation structure of FAS have been established. Due to many preferable characteristics of FAS, probabilistic seismic hazard/risk analysis is rapidly changing from ergodic, spectrum acceleration Sa(T 0 )-based approach to non-ergodic, site-specific, FAS-based approach. This paper presents time domain intrusive framework for probabilistic seismic risk analysis using GMPE of FAS. Herein, methodology for time domain stochastic ground motion modeling based on GMPEs of FAS is presented in some detail. The simulated uncertain motions are modeled as a random process and represented by polynomial chaos Karhunen-Loève expansion. The random process excitations are further propagated into the uncertain structural system using Galerkin stochastic finite element method (SFEM). Probabilistic evolution of structural response is solved, and such solution is used to develop seismic risk for any damage state. The presented framework is illustrated through seismic risk analysis of a four-story building subjected to possible earthquakes from two strike slip faults. The influences of the epistemic uncertainties in source stress drop Δσ and site attenuation κ0 on seismic risk are investigated. The need for non-ergodic seismic risk analysis with source-specific and site specific characterizations is emphasized.

58 GEOSCIENCES↗
DOE OSTI2024

Extending the computational reach of a superconducting qutrit processor

Quantum computing with qudits is an emerging approach that exploits a larger, more connected computational space, providing advantages for many applications, including quantum simulation and quantum error correction. Nonetheless, qudits are typically afflicted by more complex errors and suffer greater noise sensitivity which renders their scaling difficult. In this work, we introduce techniques to tailor arbitrary qudit Markovian noise to stochastic Weyl–Heisenberg channels and mitigate noise that commutes with our Clifford and universal two-qudit gate in generic qudit circuits. We experimentally demonstrate these methods on a superconducting transmon qutrit processor, and benchmark their effectiveness for multipartite qutrit entanglement and random circuit sampling, obtaining up to 3× improvement in our results. To the best of our knowledge, this constitutes the first-ever error mitigation experiment performed on qutrits. Our work shows that despite the intrinsic complexity of manipulating higher-dimensional quantum systems, noise tailoring and error mitigation can significantly extend the computational reach of today’s qudit processors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

The persistence of memory in ionic conduction probed by nonlinear optics

Predicting practical rates of transport in condensed phases enables the rational design of materials, devices and processes. This is especially critical to developing low-carbon energy technologies such as rechargeable batteries. For ionic conduction, the collective mechanisms, variation of conductivity with timescales and confinement, and ambiguity in the phononic origin of translation, call for a direct probe of the fundamental steps of ionic diffusion: ion hops. However, such hops are rare-event large-amplitude translations, and are challenging to excite and detect. Here we use single-cycle terahertz pumps to impulsively trigger ionic hopping in battery solid electrolytes. This is visualized by an induced transient birefringence, enabling direct probing of anisotropy in ionic hopping on the picosecond timescale. The relaxation of the transient signal measures the decay of orientational memory, and the production of entropy in diffusion. We extend experimental results using in silico transient birefringence to identify vibrational attempt frequencies for ion hopping. Using nonlinear optical methods, we probe ion transport at its fastest limit, distinguish correlated conduction mechanisms from a true random walk at the atomic scale, and demonstrate the connection between activated transport and the thermodynamics of information.

25 ENERGY STORAGE↗
DOE OSTI2023

The Covariance of PFNS Results from the Chi-Nu Experiment

The prompt fission neutron spectrum (PFNS) from neutron-induced fission is a fundamental quantity for the behavior of nuclear reactors, and has been measured many times on a wide variety of nuclei and covering different ranges of incident and emitted neutron energies. However, results from past measurements are frequently called into question in modern nuclear data evaluations because of a lack of thorough experimental documentation and incomplete uncertainty analyses. The Chi-Nu experiment at Los Alamos National Laboratory was designed to produce high-precision measurements of the PFNS of major actinides over a wide range of incident and emitted neutron energies, and with the documentation and covariance analysis required to ensure that the results of this experiment maintain their impact long into the future, thereby avoiding this pitfall of past measurements. In this work we describe the Chi-Nu experiment along with summaries of the treatment of and methods developed to address two important components of the analysis of Chi-Nu data: random-coincidence backgrounds and MCNP simulations. Furthermore, we describe the first results for correlations not just between all data points collected on a single target nucleus, but also between all data points from separate Chi-Nu measurements on 235 U and 239 Pu. These correlations are important for accurately calculating ratios of the PFNS from one actinide to another, which are rare and can be informative for nuclear data evaluation efforts.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Cooper minima in high-Z atoms: effects of correlation and relativity on np photoionization

Abstract Photoionization dipole transition matrix elements pass through a zero or attain a minimum that leaves imprints on photoionization parameters like the cross-section, angular distribution asymmetry parameter, phase shift, and photoionization time delay. This minimum is commonly known as the ‘Cooper minimum’ (CM). The CM, in general, is strongly affected by relativistic and correlation effects. Previous works investigated CM in the 6pand 5psubshell photoionization up toZ= 100 using the single-particle Dirac-Slater (DS) method. The present work extends the earlier work toZup to 120 using more accurate methods; Dirac–Hartree–Fock (DHF) which includes the relativistic effects and exchange correlations, and the relativistic random phase approximation (RRPA) which includes both initial and final state electron-electron correlations along with relativistic effects. In addition to the study of photoionization from the 6pand 5psubshells, the 4psubshell has also been investigated in the present work. To demonstrate the prominent effects in the high-Z atoms, Rn (Z= 86), Ra (Z= 88), No (Z= 102), Cn (Z = 112), Og (Z= 118), and Ubn (Z= 120) are investigated.

Optics↗
DOE OSTI2024

Machine learning materials properties with accurate predictions, uncertainty estimates, domain guidance, and persistent online accessibility

One compelling vision of the future of materials discovery and design involves the use of machine learning (ML) models to predict materials properties and then rapidly find materials tailored for specific applications. However, realizing this vision requires both providing detailed uncertainty quantification (model prediction errors and domain of applicability) and making models readily usable. At present, it is common practice in the community to assess ML model performance only in terms of prediction accuracy (e.g. mean absolute error), while neglecting detailed uncertainty quantification and robust model accessibility and usability. Here, we demonstrate a practical method for realizing both uncertainty and accessibility features with a large set of models. We develop random forest ML models for 33 materials properties spanning an array of data sources (computational and experimental) and property types (electrical, mechanical, thermodynamic, etc). All models have calibrated ensemble error bars to quantify prediction uncertainty and domain of applicability guidance enabled by kernel-density-estimate-based feature distance measures. All data and models are publicly hosted on the Garden-AI infrastructure, which provides an easy-to-use, persistent interface for model dissemination that permits models to be invoked with only a few lines of Python code. We demonstrate the power of this approach by using our models to conduct a fully ML-based materials discovery exercise to search for new stable, highly active perovskite oxide catalyst materials.

domain of applicability↗