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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

SDN-Based Smart Cyber Switching (SCS) for Cyber Restoration of a Digital Substation

In recent years, critical infrastructure and power grids have increasingly been targets of cyber-attacks, causing widespread and extended blackouts. Digital substations are particularly vulnerable to such cyber incursions, jeopardizing grid stability. This paper addresses these risks by proposing a cybersecurity framework that leverages software-defined networking (SDN) to bolster the resilience of substations based on the IEC- 61850 standard. The research introduces a strategy involving smart cyber switching (SCS) for mitigation and concurrent intelligent electronic device (CIED) for restoration, ensuring ongoing operational integrity and cybersecurity within a substation. The SCS framework improves the physical network’s behavior (i.e., leveraging commercial SDN capabilities) by incorporating an adaptive port controller (APC) module for dynamic port management and an intrusion detection system (IDS) to detect and counteract malicious IEC-61850-based sampled value (SV) and generic object-oriented system event (GOOSE) messages within the substation’s communication network. The framework’s effectiveness is validated through comprehensive simulations and a hardware-in-the-loop (HIL) testbed, demonstrating its ability to sustain substation operations during cyber-attacks and significantly improve the overall resilience of the power grid.

Liu, Chen-Ching (ORCID:0000000289417958)↗
DOE OSTI2024

Proton Quenching in Rare-Earth Inorganic Scintillators: GAGG:Ce and YSO:Ce

Scintillator detectors are an integral component of radiation detection systems for a variety of applications such as medical imaging, accelerator diagnostics, and space science. Typically, a scintillator detector’s response is characterized using gamma sources to understand the detection response to different types of radiation, including charged particle detection. However, there exists a nonlinearity of the amount of light produced from an incident gamma ray of specific energy and the light produced from an incident charged particle of the same energy. This important effect, known as quenching, must be accounted for to interpret energies from charged particles incident on detectors. In this article, we present results of quenching parameterization for two types of cerium-doped inorganic scintillators, Y2SiO5:Ce (YSO:Ce) and Gd3Al2Ga3O12:Ce (GAGG:Ce). We measured the light output from incident proton energies from 1 to 25 MeV using a 3-MV tandem accelerator and two reactions: Au(p,p)Au and 3He(d,p)⁴He. Using gamma-ray sources to calibrate the detectors, we compared the measured electron-equivalent energy versus the incident energy expected. Using an adaptation of the Birks semi-empirical formula, we extracted the Birks parameter (kB) to understand quenching. For one of the GAGG:Ce samples, the kB parameter of 0.0072 [g cm-2 MeV-1] is comparable to a similar study where the value of kB was 0.0065 [g cm-2 MeV-1]. For YSO:Ce, no other kB values were found in the literature. Three different types of GAGG:Ce were used to collect measurements of kB as a function of dopant concentration.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Effect of biochanin A on the rumen microbial community of Holstein steers consuming a high fiber diet and subjected to a subacute acidosis challenge

Subacute rumen acidosis (SARA) occurs when highly fermentable carbohydrates are introduced into the diet, decreasing pH and disturbing the microbial ecology of the rumen. Rumen amylolytic bacteria rapidly catabolize starch, fermentation acids accumulate in the rumen and reduce environmental pH. Historically, antibiotics ( e . g ., monensin, MON) have been used in the prevention and treatment of SARA. Biochanin A (BCA), an isoflavone produced by red clover ( Trifolium pratense ), mitigates changes associated with starch fermentation ex vivo . The objective of the study was to determine the effect of BCA on amylolytic bacteria and rumen pH during a SARA challenge. Twelve rumen fistulated steers were assigned to 1 of 4 treatments: HF CON (high fiber control), SARA CON, MON (200 mg d -1 ), or BCA (6 g d -1 ). The basal diet consisted of corn silage and dried distiller’s grains ad libitum . The study consisted of a 2-wk adaptation, a 1-wk HF period, and an 8-d SARA challenge (d 1–4: 40% corn; d 5–8: 70% cracked corn). Samples for pH and enumeration were taken on the last day of each period (4 h). Amylolytic, cellulolytic, and amino acid/peptide-fermenting bacteria (APB) were enumerated. Enumeration data were normalized by log transformation and data were analyzed by repeated measures ANOVA using the MIXED procedure of SAS. The SARA challenge increased total amylolytics and APB, but decreased pH, cellulolytics, and in situ DMD of hay (P < 0.05). BCA treatment counteracted the pH, microbiological, and fermentative changes associated with SARA challenge (P < 0.05). Similar results were also observed with MON (P < 0.05). These results indicate that BCA may be an effective alternative to antibiotics for mitigating SARA in cattle production systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Application of Buckmaster Electrolyte Ion Leakage Test to Woody Biofuel Feedstocks

In an earlier ASABE paper, Buckmaster reported that ion conductivity of biomass leachate in aqueous solution was directly correlated with activity access to plant nutrients within the biomass materials for subsequent biological or chemical processing. The Buckmaster test involves placing a sample of the particles in a beaker of constant-temperature deionized water and monitoring the change in electrical conductivity over time. We adapted the Buckmaster method to a range of woody biomass and other cellulosic bioenergy feedstocks. Our experimental results suggest differences of electrolyte leakage between differently processed woody biomass particles may be an indicator of their utility for conversion in bioenergy processes. This simple assay appears to be particularly useful to compare different biomass comminution techniques and particle sizes for biochemical preprocessing.

09 BIOMASS FUELS↗
DOE OSTI2014

Properties of the remnant clockwise disk of young stars in the galactic center

We present new kinematic measurements and modeling of a sample of 116 young stars in the central parsec of the Galaxy in order to investigate the properties of the young stellar disk. The measurements were derived from a combination of speckle and laser guide star adaptive optics imaging and integral field spectroscopy from the Keck telescopes. Compared to earlier disk studies, the most important kinematic measurement improvement is in the precision of the accelerations in the plane of the sky, which have a factor of six smaller uncertainties (σ ∼ 10 μas yr{sup –2}). We have also added the first radial velocity measurements for eight young stars, increasing the sample at the largest radii (6''-12'') by 25%. We derive the ensemble properties of the observed stars using Monte Carlo simulations of mock data. There is one highly significant kinematic feature (∼20σ), corresponding to the well-known clockwise disk, and no significant feature is detected at the location of the previously claimed counterclockwise disk. The true disk fraction is estimated to be ∼20%, a factor of ∼2.5 lower than previous claims, suggesting that we may be observing the remnant of what used to be a more densely populated stellar disk. The similarity in the kinematic properties of the B stars and the O/WR stars suggests a common star formation event. The intrinsic eccentricity distribution of the disk stars is unimodal, with an average value of (e) = 0.27 ± 0.07, which we show can be achieved through dynamical relaxation in an initially circular disk with a moderately top-heavy mass function.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

CAMERA: A method for cost-aware, adaptive, multifidelity, efficient reliability analysis

Estimating probability of failure in aerospace systems is a critical requirement for flight certification and qualification. Failure probability estimation involves resolving tails of probability distributions, and Monte Carlo sampling methods are intractable when expensive high-fidelity simulations have to be queried. Here, we propose a method to use models of multiple fidelities that trade accuracy for computational efficiency. Specifically, we propose the use of multifidelity Gaussian process models to efficiently fuse models at multiple fidelity, thereby offering a cheap surrogate model that emulates the original model at all fidelities. Furthermore, we propose a novel sequential acquisition function based experiment design framework that can automatically select samples from appropriate fidelity models to make predictions about quantities of interest at the highest fidelity. We use our proposed approach in an importance sampling setting and demonstrate our method on the failure level set and probability estimation on synthetic test functions and two real-world applications, namely, the reliability analysis of a gas turbine engine blade using a finite element method and a transonic aerodynamic wing test case using Reynolds-averaged Navier-Stokes equations. We show that our method predicts the failure boundary and probability more accurately and at a fraction of the computational cost compared with using just a single expensive high-fidelity model. Finally, we show that our sequential approach is guaranteed to asymptotically converge to the true failure boundary with high probability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

GPU simulation of nonlinear propagation of dual band ultrasound pulse complexes

In a new method of ultrasound imaging, called SURF imaging, dual band pulse complexes composed of overlapping low frequency (LF) and high frequency (HF) pulses are transmitted, where the frequency ratio LF:HF ∼ 1 : 20, and the relative bandwidth of both pulses are ∼ 50 − 70%. The LF pulse length is hence ∼ 20 times the HF pulse length. The LF pulse is used to nonlinearly manipulate the material elasticity observed by the co-propagating HF pulse. This produces nonlinear interaction effects that give more information on the propagation of the pulse complex. Due to the large difference in frequency and pulse length between the LF and the HF pulses, we have developed a dual level simulation where the LF pulse propagation is first simulated independent of the HF pulse, using a temporal sampling frequency matched to the LF pulse. A separate equation for the HF pulse is developed, where the the presimulated LF pulse modifies the propagation velocity. The equations are adapted to parallel processing in a GPU, where nonlinear simulations of a typical HF beam of 10 MHz down to 40 mm is done in ∼ 2 secs in a standard GPU. This simulation is hence very useful for studying the manipulation effect of the LF pulse on the HF pulse.

42 ENGINEERING↗
DOE OSTI2025

Adaptive Uncertainty Quantification for Stochastic Hyperbolic Conservation Laws

Here, we propose a predictor-corrector adaptive method for the study of hyperbolic partial differential equations (PDEs) under uncertainty. Constructed around the framework of stochastic finite volume (SFV) methods, our approach circumvents sampling schemes or simulation ensembles while also preserving fundamental properties, in particular hyperbolicity of the resulting systems and conservation of the discrete solutions. Furthermore, we augment the existing SFV theory with a priori convergence results for statistical quantities, in particular push-forward densities, which we demonstrate through numerical experiments. By linking refinement indicators to regions of the physical and stochastic spaces, we drive anisotropic refinements of the discretizations, introducing new degrees of freedom where deemed profitable. To illustrate our proposed method, we consider a series of numerical examples for nonlinear hyperbolic PDEs based on Burgers’ and Euler’s equations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Considerations and Lessons Learned from the Use of Gamma Spectroscopy Systems at FUSRAP Project Sites - 17459

This paper will discuss the application of gamma spectroscopy systems for analysis of environmental media samples for parents and daughter progeny of the Natural Uranium and Thorium Decay Series radionuclides. The concentrations and relative ratios of naturally occurring isotopes are used to confirm the presence of FUSRAP-related wastes and for understanding the associated potential dose and health risks. Focus will be given to lessons learned from the set-up and operation of onsite gamma spectroscopy laboratories used to provide stakeholders with defensible and timely results to support FUSRAP site investigations and remediation including adaptive survey design implementation, physical remediation and waste transport, and confirmatory final status survey activities. This paper focuses on the potential impacts to gamma spectroscopy measurement accuracy from the following: - Bias caused by sample matrix effects as well as use of different library reference values between performance evaluation study providers and testing laboratories; - Use of calibration sources with limited energy ranges, and; - Selection of available alternative isotopic decay reference data for the input of line energies and their intensities. These lessons learned include discussing how inter-laboratory measurement differences from blind performance evaluation samples are affected by the manufacturer's measurement method, including equilibrium assumptions; the isotope decay information source library used by the study provider and participating laboratories; and calibration source geometry/density variances from actual sample conditions. Any of these factors can significantly impact the accuracy of reported results data. Deepening the reader's understanding of the various factors that impact the accuracy, interpretation, and overall usability of gamma spectroscopy results data from laboratories will help ensure defensible decision-making and cost-effective mission implementation within FUSRAP and similar remediation programs. (authors)

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

System Integration for Remote Systems at DOE Hanford Nuclear Site - 18712

The deployment of remotely operated technology that functions in environments too hazardous for worker entry are often needed at the Hanford Site to perform functions like infrastructure inspection; decommissioning and decontamination; characterization; environmental sampling; and nuclear waste sampling, mobilization, and retrieval. The development and production of Hanford remote systems typically requires the integration of robotic components and sensor technologies that have been engineered or adapted to meet function and performance requirements. Pacific Northwest National Laboratory has led the engineering and integration of robotic and sensor/manipulator technology for several remote system deployments at Hanford and for national security sponsors. This paper describes the system integration process for ensuring that the mechanical, electrical, and software aspects of each component are successfully brought together to produce a remote system that meets function and performance requirements under extreme environments and limited-access operational demands. A brief summary of previous and current remote system projects is also provided. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

MetaBAT 2: an adaptive binning algorithm for robust and efficient genome reconstruction from metagenome assemblies

We previously reported MetaBAT, an automated metagenome binning software tool to reconstruct single genomes from microbial communities for subsequent analyses of uncultivated microbial species. MetaBAT has become one of the most popular binning tools largely due to its computational efficiency and ease of use, especially in binning experiments with a large number of samples and a large assembly. MetaBAT requires users to choose parameters to fine-tune its sensitivity and specificity. If those parameters are not chosen properly, binning accuracy can suffer, especially on assemblies of poor quality. Here we developed MetaBAT 2 to overcome this problem. MetaBAT 2 uses a new adaptive binning algorithm to eliminate manual parameter tuning. We also performed extensive software engineering optimization to increase both computational and memory efficiency. Comparing MetaBAT 2 to alternative software tools on over 100 real world metagenome assemblies shows superior accuracy and computing speed. Binning a typical metagenome assembly takes only a few minutes on a single commodity workstation. We therefore recommend the community adopts MetaBAT 2 for their metagenome binning experiments. MetaBAT 2 is open source software and available at https://bitbucket.org/berkeleylab/metabat .

Kang, Dongwan↗
DOE OSTI2015

Π4U: A high performance computing framework for Bayesian uncertainty quantification of complex models

We present Π4U,{sup 1} an extensible framework, for non-intrusive Bayesian Uncertainty Quantification and Propagation (UQ+P) of complex and computationally demanding physical models, that can exploit massively parallel computer architectures. The framework incorporates Laplace asymptotic approximations as well as stochastic algorithms, along with distributed numerical differentiation and task-based parallelism for heterogeneous clusters. Sampling is based on the Transitional Markov Chain Monte Carlo (TMCMC) algorithm and its variants. The optimization tasks associated with the asymptotic approximations are treated via the Covariance Matrix Adaptation Evolution Strategy (CMA-ES). A modified subset simulation method is used for posterior reliability measurements of rare events. The framework accommodates scheduling of multiple physical model evaluations based on an adaptive load balancing library and shows excellent scalability. In addition to the software framework, we also provide guidelines as to the applicability and efficiency of Bayesian tools when applied to computationally demanding physical models. Theoretical and computational developments are demonstrated with applications drawn from molecular dynamics, structural dynamics and granular flow.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Anatomy of a mega‐radiation: Biogeography and niche evolution in Astragalus

Premise Astragalus (Fabaceae), with more than 3000 species, represents a globally successful radiation of morphologically highly similar species predominant across the northern hemisphere. It has attracted attention from systematists and biogeographers, who have asked what factors might be behind the extraordinary diversity of this important arid-adapted clade and what sets it apart from close relatives with far less species richness. Methods Here, for the first time using extensive phylogenetic sampling, we asked whether (1) Astragalus is uniquely characterized by bursts of radiation or whether diversification instead is uniform and no different from closely related taxa. Then we tested whether the species diversity of Astragalus is attributable specifically to its predilection for (2) cold and arid habitats, (3) particular soils, or to (4) chromosome evolution. Finally, we tested (5) whether Astragalus originated in central Asia as proposed and (6) whether niche evolutionary shifts were subsequently associated with the colonization of other continents. Results Our results point to the importance of heterogeneity in the diversification of Astragalus, with upshifts associated with the earliest divergences but not strongly tied to any abiotic factor or biogeographic regionalization tested here. The only potential correlate with diversification we identified was chromosome number. Biogeographic shifts have a strong association with the abiotic environment and highlight the importance of central Asia as a biogeographic gateway. Conclusions Our investigation shows the importance of phylogenetic and evolutionary studies of logistically challenging “mega-radiations.” Our findings reject any simple key innovation behind high diversity and underline the often nuanced, multifactorial processes leading to species-rich clades.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Experimental Studies of Boronophenylalanine ({sup 10}BPA) Biodistribution for the Individual Application of Boron Neutron Capture Therapy (BNCT) for Malignant Melanoma Treatment

Purpose: Patients with the same histopathologic diagnosis of cutaneous melanoma treated with identical protocols of boron neutron capture therapy (BNCT) have shown different clinical outcomes. The objective of the present studies was to evaluate the biodistribution of boronophenilalanina ({sup 10}BPA) for the potential application of BNCT for the treatment of melanoma on an individual basis. Methods and Materials: The boronophenilalanine (BPA) uptake was evaluated in 3 human melanoma cell lines: MEL-J, A375, and M8. NIH nude mice were implanted with 4 10{sup 6} MEL-J cells, and biodistribution studies of BPA (350 mg/kg intraperitoneally) were performed. Static infrared imaging using a specially modified infrared camera adapted to measure the body infrared radiance of small animals was used. Proliferation marker, Ki-67, and endothelial marker, CD31, were analyzed in tumor samples. Results: The in vitro studies demonstrated different patterns of BPA uptake for each analyzed cell line (P<.001 for MEL-J and A375 vs M8 cells). The in vivo studies showed a maximum average boron concentration of 25.9 ± 2.6 μg/g in tumor, with individual values ranging between 11.7 and 52.0 μg/g of {sup 10}B 2 hours after the injection of BPA. Tumor temperature always decreased as the tumors increased in size, with values ranging between 37°C and 23°C. A significant correlation between tumor temperature and tumor-to-blood boron concentration ratio was found (R{sup 2} = 0.7, rational function fit). The immunohistochemical studies revealed, in tumors with extensive areas of viability, a high number of positive cells for Ki-67, blood vessels of large diameter evidenced by the marker CD31, and a direct logistic correlation between proliferative status and boron concentration difference between tumor and blood (R{sup 2} = 0.81, logistic function fit). Conclusion: We propose that these methods could be suitable for designing new screening protocols applied before melanoma BNCT treatment for each individual patient and lesion.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2026

Latent space dynamics identification for interface tracking with application to shock-induced pore collapse

Capturing sharp, evolving interfaces remains a central challenge in reduced-order modeling, especially when data is limited and the system exhibits localized nonlinearities or discontinuities. Here, we propose LaSDI-IT (Latent Space Dynamics Identification for Interface Tracking), a data-driven framework that combines low-dimensional latent dynamics learning with explicit interface-aware encoding to enable accurate and efficient modeling of physical systems involving moving material boundaries. At the core of LaSDI-IT is a revised autoencoder architecture that jointly reconstructs the physical field and an indicator function representing material regions or phases, allowing the model to track complex interface evolution without requiring detailed physical models or mesh adaptation. The latent dynamics are learned through linear regression in the encoded space and generalized across parameter regimes using Gaussian process interpolation with greedy sampling. We demonstrate LaSDI-IT on the problem of shock-induced pore collapse in high explosives, a process characterized by sharp temperature gradients and dynamically deforming pore geometries. The method achieves relative prediction errors below 9% across the parameter space, accurately recovers key quantities of interest such as pore area and hot spot formation, and matches the performance of dense training with only half the data. This latent dynamics prediction was 10 6 times faster than the conventional high-fidelity simulation, proving its utility for multi-query applications. These results highlight LaSDI-IT as a general, data-efficient framework for modeling discontinuity-rich systems in computational physics, with potential applications in multiphase flows, fracture mechanics, and phase change problems.

Gaussian process↗
DOE OSTI2014

Hidden regularity and universal classification of fast side chain motions in proteins

Proteins display characteristic dynamical signatures that appear to be universal across all proteins regardless of topology and size. Here, we systematically characterize the universal features of fast side chain motions in proteins by examining the conformational energy surfaces of individual residues obtained using enhanced sampling molecular dynamics simulation (618 free energy surfaces obtained from 0.94 s MD simulation). The side chain conformational free energy surfaces obtained using the adaptive biasing force (ABF) method for a set of eight proteins with different molecular weights and secondary structures are used to determine the methyl axial NMR order parameters (O axis 2 ), populations of side chain rotamer states (ρ), conformational entropies (S conf ), probability fluxes, and activation energies for side chain inter-rotameric transitions. The free energy barriers separating side chain rotamer states range from 0.3 to 12 kcal/mol in all proteins and follow a trimodal distribution with an intense peak at ~5 kcal/mol and two shoulders at ~3 and ~7.5 kcal/mol, indicating that some barriers are more favored than others by proteins to maintain a balance between their conformational stability and flexibility. The origin and the influences of the trimodal barrier distribution on the distribution of O axis 2 and the side chain conformational entropy are discussed. A hierarchical grading of rotamer states based on the conformational free energy barriers, entropy, and probability flux reveals three distinct classes of side chains in proteins. A unique nonlinear correlation is established between O axis 2 and the side chain rotamer populations (ρ). In conclusion, the apparent universality in O axis 2 versus correlation, trimodal barrier distribution, and distinct characteristics of three classes of side chains observed among all proteins indicates a hidden regularity (or commonality) in the dynamical heterogeneity of fast side chain motions in proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Emergent Constrained Projections of Mean and Extreme Warming in China

Reliable regional temperature projections including heat extremes are essential for climate change adaptation and mitigation. Taking China as an example, simple averages from Coupled Model Intercomparison Project Phase 6 (CMIP6) models project high warming due to sampling many high climate sensitivities in the ensemble. Here, we develop an emergent constraint (EC) framework to obtain constrained mean and daily maximum temperature (TXx) warming over China by using observed global warming and local residual warming. The constrained annual mean and TXx warming over China (2.33°C [1.61–3.05°C] and 2.31°C [1.21–2.99°C]) are 0.65°C [0.04–1.76°C] and 0.63°C [–0.50–2.39°C], respectively, lower than raw projections (2.98°C [1.85–4.22°C] and 2.94°C [2.04–4.39°C]) for 2080–2099 under the intermediate-emission scenario. Approximately half model uncertainty is reduced after constraint. The land area (population) experiencing temperature extremes in our metric is 78% (85%) of the raw projections. Our results imply a lower impact of extreme heat than implied by current raw CMIP6 projections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

An Edge Alignment-Based Orientation Selection Method for Neutron Tomography

Neutron computed tomography (nCT) is a 3D char-acterization technique used to image the internal morphology or chemical composition of samples in biology and materials sciences. A typical workflow involves placing the sample in the path of a neutron beam, acquiring projection data at a predefined set of orientations, and processing the resulting data using an analytic reconstruction algorithm. Typical nCT scans require hours to days to complete and are then processed using conventional filtered back-projection (FBP), which performs poorly with sparse views or noisy data. Hence, the main methods in order to reduce overall acquisition time are the use of an improved sampling strategy combined with the use of advanced reconstruction methods such as model-based iterative reconstruction (MBIR). In this paper, we propose an adaptive orientation selection method in which an MBIR reconstruction on previously-acquired measurements is used to define an objective function on orientations that balances a data-fitting term promoting edge alignment and a regularization term promoting orientation diversity. Using simulated and experimental data, we demonstrate that our method produces high-quality reconstructions using significantly fewer total measurements than the conventional approach.

Yang, Diyu↗