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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Propagating uncertainties in large-scale hemodynamics models via network uncertainty quantification and reduced-order modeling

Numerical simulations of the cardiovascular system are affected by uncertainties arising from a substantial lack of data related to the boundary conditions and the physical parameters of the mathematical models. Quantifying the impact of this uncertainty on the numerical results along the circulatory network is challenged by the complexity of both the morphology of the domain and the local dynamics. Here, we propose to integrate (i) the Transverse Enriched Pipe Element Methods (TEPEM) as a reduced-order model for effectively computing the 3D local hemodynamics; and (ii) a combination of uncertainty quantification via Polynomial Chaos Expansion and classical relaxation methods – called network uncertainty quantification (NetUQ) – for effectively propagating random variables that encode uncertainties throughout the networks. The findings demonstrate the computational effectiveness of computing the propagation of uncertainties in networks with nontrivial topology, including portions of the cerebral and the coronary systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Block copolymer self-assembly to pattern gold nanodots for site-specific placement of DNA origami and attachment of nanomaterials

Directed placement of DNA origami could play a key role in future integrated nanoelectronic devices. Here we demonstrated the site-selective attachment of DNA origami on gold dots formed using a pattern transfer method through block copolymer self-assembly. First, a random copolymer brush layer is grafted on the Si surface and then poly (styrene-b-methylmethacrylate) block copolymer is spin-coated to give a hexagonal nanoarray after annealing. UV irradiation followed by acetic acid etching is used to remove the PMMA, creating cylindrical holes and then oxygen plasma etching removes the random copolymer layer inside those holes. Next, metal evaporation, followed by lift-off creates a gold dot array. We evaluated different ligand functionalization of Au dots, as well as DNA hybridization to attach DNA origami to the nanodots. DNA-coated Au nanorods are assembled on the DNA origami as a step towards creating nanowires and to facilitate electron microscopy characterization of the attachment of DNA origami on these Au nanodots. The DNA hybridization approach showed better DNA attachment to Au nanodots than localization by electrostatic interaction. Here, this work contributes to the understanding of DNA-templated assembly, nanomaterials, and block copolymer nanolithography. Furthermore, the work shows potential for creating DNA-templated nanodevices and their placement in ordered arrays in future nanoelectronics.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Monte Carlo evaluation of the semiclassical multi-step direct reaction series

We show how the multi-step direct reaction series can be evaluated using Monte Carlo methods. Nucleon-nucleon collisions occur according to the random selection of a nucleon’s attenuation factor along its classical trajectory. The particles and hole excited in a collision are selected from a local Fermi distribution. We assume that the particles continue to propagate and possibly collide again before leaving the nucleus. We assume that holes collide in place, to possibly produce other particles and holes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

An investigation of high entropy alloy conductivity using first-principles calculations

The Kubo–Greenwood equation, in combination with the first-principles Korringa–Kohn–Rostoker coherent potential approximation (KKR-CPA) can be used to calculate the DC residual resistivity of random alloys at T = 0 K. We implemented this method in a multiple scattering theory based ab initio package, MuST, and applied it to the ab initio study of the residual resistivity of the high entropy alloy Al x CoCrFeNi as a function of x. The calculated resistivities are compared with experimental data. We also predict the residual resistivity of refractory high entropy alloy MoNbTaV x W. Furthermore, the calculated resistivity trends are also explained using theoretical arguments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Propagation of priors for more accurate and efficient spectroscopic functional fits and their application to ferroelectric hysteresis

Multi-dimensional spectral-imaging is a mainstay of the scanning probe and electron microscopies, micro-Raman, and various forms of chemical imaging. In many cases, individual spectra can be fit to a specific functional form, with the model parameter maps, providing direct insight into material properties. Since spectra are often acquired across a spatial grid of points, spatially adjacent spectra are likely to be similar to one another; yet, this fact is almost never used when considering parameter estimation for functional fits. On datasets tried here, we show that by utilizing proximal information, whether it be in the spatial or spectral domains, it is possible to improve the reliability and increase the speed of such functional fits by ~2-3x, as compared to random priors. We explore and compare three distinct new methods: (1) spatially averaging neighborhood spectra, and propagating priors based on functional fits to the averaged case, (2) hierarchical clustering-based methods where spectra are grouped hierarchically based on response, with the priors propagated progressively down the hierarchy, and (3) regular clustering without hierarchical methods with priors propagated from fits to cluster means. Our results highlight that utilizing spatial and spectral neighborhood information is often critical for accurate parameter estimation in noisy environments, which we show for ferroelectric hysteresis loops acquired on a prototypical PbTiO3 thin film with piezoresponse spectroscopy. This method is general and applicable to any spatially measured spectra where functional forms are available. Examples include exploring the superconducting gap with tunneling spectroscopy, using the Dynes formula, or current-voltage curve fits in conductive atomic force microscopy mapping. Here we explore the problem for ferroelectric hysteresis, which, given its large parameter space, constitutes a more difficult task than, for example, fitting current-voltage curves with a Schottky emission formula.

42 ENGINEERING↗
DOE OSTI2019

Fractional polarization of extragalactic sources in the 500 deg 2 SPTpol survey

In this work, we study the polarization properties of extragalactic sources at 95 and 150 GHz in the SPTpol 500 deg 2 survey. We estimate the polarized power by stacking maps at known source positions, and correct for noise bias by subtracting the mean polarized power at random positions in the maps. We show that the method is unbiased using a set of simulated maps with similar noise properties to the real SPTpol maps. We find a flux-weighted mean-squared polarization fraction $\langle$p 2 $\rangle$ = [8.9 ± 1.1] × 10 -4 at 95 GHz and [6.9 ± 1.1] × 10 -4 at 150 GHz for the full sample. This is consistent with the values obtained for a subsample of active galactic nuclei. For dusty sources, we find 95 percent upper limits of $\langle$p 2 $\rangle$ 95 < 16.9 × 10 -3 and $\langle$p 2 $\rangle$ 150 < 2.6 × 10 -3 . We find no evidence that the polarization fraction depends on the source flux or observing frequency. The 1σ upper limit on measured mean-squared polarization fraction at 150 GHz implies that extragalactic foregrounds will be subdominant to the CMB E and B mode polarization power spectra out to at least ℓ ≲ 5700 (ℓ ≲ 4700) and ℓ ≲ 5300 (ℓ ≲ 3600), respectively, at 95 (150) GHz.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Survey of Image Denoising Methods for Medical Image Classification

Medical imaging devices, such as X-ray machines, inherently produce images that suffer from visual noise. Our objectives were to (i.) determine the effect of image denoising on a medical image classification task, and (ii.) determine if there exists a correlation between image denoising performance and medical image classification performance. We performed the medical image classification task on chest X-rays using the DenseNet-121 convolutional neural network (CNN) and used the peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) metrics as the image denoising performance measures. We first found that different denoising methods can make a statistically significant difference in classification performance for select labels. We also found that denoising methods affect fine-tuned models more than randomly-initialized models and that fine-tuned models have significantly higher and more uniform performance than randomly-initialized models. Lastly, we found that there is no significant correlation between PSNR and SSIM values and classification performance for our task.

Michael, Peter↗
DOE OSTI2022

An improved method to access initial states in relativistic heavy-ion collisions

Abstract Observables in heavy-ion collisions are generally categorized into centralities, which reflect an average over events within a range of impact parameters including a wide variety of initial-state configurations. A multiple binning method using spectator neutrons within each centrality has been shown to provide access to events with rare initial-state conditions. This work suggests an improvement in quantifying the difference between standard centrality and spectator neutron binning towards accessing the initial-state properties. A selection of events with higher initial-state density at a fixed participating nucleon number was observed to result in larger final-state particle production and smaller elliptic flow. The relative difference between observables in centrality and spectator binning shows reduced sensitivity for the observables dominated by impact parameter fluctuations in the initial state, such as triangular flow. This property renders the spectator binning method a good candidate for separating geometric contributions from random fluctuations in the initial state towards final-state observables.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Quantified fracture (joint) clustering in Archean basement, Wyoming: application of the normalized correlation count method

We demonstrate statistically significant self-organized clustering over a length scale range from 10 -2 to 10 1 m for north-striking opening-mode fractures (joints) in Late Archean Mount Owen Quartz Monzonite. Spatial arrangement is a critical fracture network attribute that until recently has only been assessed qualitatively. We use normalized fracture intensity plots and the normalized correlation count (NCC) method of Marrett et al. to discriminate clustered from randomly placed or evenly spaced patterns quantitatively over a wide range of length scales and to test the statistical significance of the resulting patterns. We propose a procedure for interpreting cluster patterns on NCC diagrams generated by the freely available spatial analysis software CorrCount. Results illustrate the efficacy of NCC to measure fracture clustering patterns in texturally homogeneous Archean granitic rock in a setting distant (>2 km) from folds or faults. In their current geological setting, these regional fractures are conduits for water flow and their patterns – and the NCC approach to defining clusters – may be useful guides to the spatial arrangement style and clustering magnitude of conductive fractures in other, less accessible fractured basement rocks.

02 PETROLEUM↗
DOE OSTI2018

Optimization, Inference and Learning for Advanced Networks

This piece of software aims at providing an implementation of methods to perform efficient optimization, probabilistic inference and model selection and learning for various type of networked systems. The software contains a suite of methods and functions that: 1) perform probabilistic inference and random sampling on networked models 2) select or learn networked models from data 3) solve optimization tasks with a networked structure Network models that are supported by these features include, but are not limited to, factor graphs and Markov random fields such as Ising models, Potts models, p-spins models, Gaussian random fields and restricted Boltzmann machine.

Hijazi, Hassan↗
DOE OSTI2021

Position Papers for the ASCR Workshop on Cybersecurity and Privacy for Scientific Computing Ecosystems

At the request of the Department of Energy's (DOE) Office of Advanced Scientific Computing Research (ASCR), this program committee has been tasked with organizing a workshop to identify basic research needs in cybersecurity and privacy to better support DOE's science and energy mission. As part of the process, the program committee is soliciting community input in the form of position papers to help identify significant use cases, facility issues, and other barriers to enabling verifiably trustworthy computational science while preserving data confidentiality as appropriate for scientific workflows of interest to DOE. The program committee will review these position papers and based on the fit of their area of expertise and interest, selected contributors will have the opportunity to participate in the workshop currently planned as a virtual event November 3-5th, 2021. The thrust areas that will be explored by this workshop are the following: (1) Algorithms for secure, scalable, privacy-enhancing technologies and frameworks, including: Federated AI/ML, Differential privacy, Randomized algorithms, Adversarial modeling & simulation, Graph algorithms, and Formal methods; (2) Platforms to support the entire scientific-computing ecosystem, including edge computing for large-scale experiments, focusing on heterogeneous systems and distributed systems, including: Heterogeneous computing systems, Distributed computing systems, and Secure data architectures; and (3) Data workflows to allow agile use of data while preserving integrity and privacy, making the important properties verifiable either at runtime or post-computation, including: Integrity and provenance and Data management infrastructure. Topics that are out-of-scope for the workshop include discussing specific proposed solutions or areas that are clearly out of DOE's fundamental and applied-sciences mission scope, e.g., cryptography, enterprise security, and general-operations technology.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Securing Grid-interactive Efficient Buildings (GEB) through Cyber Defense and Resilient System (CYDRES)

The DOE CYDRES project is driven by the urgent need to address critical research gaps in the domain of cyber-physical security of smart buildings, including Grid-interactive Efficient Buildings (GEBs). CYDRES, a real-time advanced building resilient platform, aims to enhance the cyber-attack-immune capabilities of buildings through multi-layered prevention, detection, and adaptation mechanisms. CYDRES consists of five key modules: a multi-layer network analyzer, an Automatic Fault Detection, Diagnosis, and Prognosis (AFDDP) framework, an intelligent mode selector, a cyber-resilient control framework, and a situation awareness platform. The Network Analyzer employs a data-driven framework that includes a protocol state learning tool and a CRF (Conditional Random Field) command validator. In Hardware-In-the-Loop (HIL) testbeds, it achieved 100% detection accuracy with a false alarm rate of 3%, validating its efficacy in identifying selected cyber-attacks. The AFDDP framework leverages pattern matching, PCA (Principal Component Analysis)-based strategies, and a DBN (Dynamic Bayesian Network)-based fault diagnosis approach to pinpoint the causes of physical system abnormalities using Building Automation System (BAS) data. In HIL experiments, the AFDDP module attained a detection accuracy of over 95% with a false alarm rate below 7%. Additionally, the fault detector utilized machine learning (Random Forest) and deep learning (Multi-Layer Perceptron) methods with acoustic sensor data to achieve a 100% fault detection accuracy in Heating, Ventilation, and Air-Conditioning (HVAC) equipment. The Mode Selector offered real-time impact analysis, allowing immediate actions to protect BASs in the face of emerging threats. The cyber-resilient control framework included an adaptive Model Predictive Control (MPC) and a measurement compensator, reducing temperature violations by up to 94% and improving the total demand flexibility by up to 70% in HIL experiments. Such HIL experiments covered a cyber-attack case and a physical fault case, showcasing CYDRES’ efficiency in maintaining operational continuity during threats. The situation awareness platform in Grafana enhanced real-time threat detection and response visualization, augmenting the operational awareness for building operators. CYDRES demonstrated high technical effectiveness in various test scenarios, particularly in HIL environments. The project's phased development approach ensured efficient use of resources, highlighting its practical feasibility and readiness for commercialization. By enhancing the security and resilience of building operations, CYDRES represents a significant advance in mitigating risks associated with cyber-physical systems, thereby enhancing public confidence in the safety of modern building infrastructure. Future directions for the project include expanding testing protocols, refining AFDDP methodologies, exploring more comprehensive resilient control strategies, and testing in real commercial buildings.

42 ENGINEERING↗
DOE OSTI2024

Comparison of venous and pooled capillary hemoglobin levels for the detection of anemia among adolescent girls

Introduction: Blood source is a known preanalytical factor affecting hemoglobin (Hb) concentrations, and there is evidence that capillary and venous blood may yield disparate Hb levels and anemia prevalence. However, data from adolescents are scarce. Objective: To compare Hb and anemia prevalence measured by venous and individual pooled capillary blood among a sample of girls aged 10–19 years from 232 schools in four regions of Ghana in 2022. Methods: Among girls who had venous blood draws, a random subsample was selected for capillary blood. Hb was measured using HemoCue® Hb-301. We used Lin’s concordance correlation coefficient (CCC) to quantify the strength of the bivariate relationship between venous and capillary Hb and a paired t-test for difference in means. We used McNemar’s test for discordance in anemia cases by blood source and weighted Kappa to quantify agreement by anemia severity. A multivariate generalized estimating equation was used to quantify adjusted population anemia prevalence and assess the association between blood source and predicted anemia risk. Results: We found strong concordance between Hb measures (CCC = 0.86). The difference between mean venous Hb (12.8 g/dL, ± 1.1) and capillary Hb (12.9 g/dL, ± 1.2) was not significant (p = 0.26). Crude anemia prevalence by venous and capillary blood was 20.6% and 19.5%, respectively. Adjusted population anemia prevalence was 23.5% for venous blood and 22.5% for capillary ( = 0.45). Blood source was not associated with predicted anemia risk (risk ratio: 0.99, 95% CI: 0.96, 1.02). Discordance in anemia cases by blood source was not significant (McNemar p = 0.46). Weighted Kappa demonstrated moderate agreement by severity (k =0.67). Among those with anemia by either blood source (n = 111), 59% were identified by both sources. Conclusion: In Ghanaian adolescent girls, there was no difference in mean Hb, anemia prevalence, or predicted anemia risk by blood source. However, only 59% of girls with anemia by either blood source were identified as having anemia by both sources. These findings suggest that pooled capillary blood may be useful for estimating Hb and anemia at the population level, but that caution is needed when interpreting individual-level data.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1971

An algorithm for terminal air traffic control

An area-navigation method for automatic control of aircraft arriving in a random fashion from the en-route centers to the near terminal area is proposed. Control is exercised by a ground computer that sequences and schedules the aircraft. Altitude segregation is used to separate aircraft in velocity classes. Merging of all aircraft occurs near the outer marker. The merging region is designed so that no near misses will occur if the aircraft follow the assigned trajectories.

Sarris, A. H.↗
NASA NTRS1976

A methodology for small scale rural land use mapping in semi-arid developing countries using orbital imagery. Part 5: Experimental and operational techniques of mapping land use

The author has identified the following significant results. Scope of the preprocessing techniques was restricted to standard material from the EROS Data Center accompanied by some enlarging procedures and the use of the diazo process. Investigation has shown that the most appropriate sampling strategy for this study is the stratified random technique. A viable sampling procedure, together with a method for determining minimum number of sample points in order to test results of any interpretation are presented.

Vangenderen, J. L.↗
NASA NTRS1976

The Application of Recent Techniques in Flight Flutter Testing

The relative merits of sinusoidal excitation versus random atmospheric turbulence was investigated. The randomdec and autocorrelation methods were used to analyze data from a Learjet flight test. A parameter identification digital program, using least squares approach, was developed to determine the aeroelastic characteristics of a two mode system. The flight test program, computer program, and data reduction procedure is presented. Final results of the two modes of excitation obtained by Randomdec method are discussed.

Abla, M. A.↗