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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 OSTI2024

e RPCA : Robust Principal Component Analysis for Exponential Family Distributions

Abstract Robust principal component analysis (RPCA) is a widely used method for recovering low‐rank structure from data matrices corrupted by significant and sparse outliers. These corruptions may arise from occlusions, malicious tampering, or other causes for anomalies, and the joint identification of such corruptions with low‐rank background is critical for process monitoring and diagnosis. However, existing RPCA methods and their extensions largely do not account for the underlying probabilistic distribution for the data matrices, which in many applications are known and can be highly non‐Gaussian. We thus propose a new method called RPCA for exponential family distributions (), which can perform the desired decomposition into low‐rank and sparse matrices when such a distribution falls within the exponential family. We present a novel alternating direction method of multiplier optimization algorithm for efficient decomposition, under either its natural or canonical parametrization. The effectiveness of is then demonstrated in two applications: the first for steel sheet defect detection and the second for crime activity monitoring in the Atlanta metropolitan area.

Zheng, Xiaojun↗
DOE OSTI2021

Local structure of Mott insulating iron oxychalcogenides La 2 O 2 Fe 2 OM2(M=S,Se)

Here, we describe the local structural properties of the iron oxychalcogenides, La 2 O 2 Fe 2 OM 2 (M=S,Se), by using pair distribution function analysis applied to total scattering data. Our results from neutron powder diffraction show that M = S and Se possess similar nuclear structures at low and room temperatures. The local crystal structures were studied by investigating deviations in atomic positions and the extent of the formation of orthorhombicity. Analysis of the total scattering data suggests that buckling of the Fe 2 O plane occurs below 100 K. The buckling may occur concomitantly with a change in octahedral height. Furthermore, within a typical range of 1-2 nm, we observed a short-range orthorhombiclike structure suggestive of nematic fluctuations in both of these materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

A Probabilistic Reasoner Based on Bayes Risk for Damage Detection in Structural Systems

Structural health monitoring (SHM) systems are used to inform operation of structural systems subject to loads and environments that may affect their integrity. SHM systems rely on continuous monitoring of the structure to determine its health state. These systems are often coupled with a model of the deployed structure to determine the consequences of changes in the system by forecasting the response to future states. These models, which may be thought of as digital twins, need to be updated to reflect the latest state of the structural system. This work makes use of an uncertainty-aware machine learning model that enforces distance preservation of the original input space to determine deviations from the training data input space distributions. This workflow enables domain shift detection to determine whether damage is present in the structure. The uncertainty metrics generated by this network are then used in a Bayes risk framework to design an optimal damage detector given cost and risk considerations. The approach is demonstrated on a computational example with simulated damage.

Najera-Flores, David [ATA Engineering, Inc.]↗
DOE OSTI2018

Environmental impact assessment follow-up for projects in China: Institution and practice

Highlights: • As an essential part of the environmental management system required by the EIA Law, the EIA follow-up was poorly executed. • The effectiveness of the EIA follow-up could be greatly elevated by enhancing monitoring and public participation. • Environmental information disclosure plays the essential role in promoting the EIA follow-up. - Abstract: The Environmental Impact Assessment (EIA) is one of the important means of environmental management worldwide, and the EIA follow-up is one of the crucial measures to ensure the concrete implementation of the EIA. In this research, systematic reviews of EIA follow-up for projects in China were conducted to comprehensively appraise the implementation of the EIA follow-up and to identify the potential to improve the practice of an EIA follow-up. First, the EIA follow-up reports were collected through various sources. In total, there were 74 EIA follow-up reports that were identified and acquired. Second, a reviewing framework, containing 16 different indicators, was developed to systematically document and classify these EIA follow-up reports. Third, these EIA follow-up reports were grouped into several categories according to various indicators and then were analyzed to recognize their key features, including sources of data, analytic tools adopted, spatial-temporal distribution, industrial distribution, triggering causes, content, structure and effectiveness. The results showed that there were considerable disparities in the quality and the rigor of EIA follow-ups conducted. These features, along with some existing deficiencies of EIA follow-up, such as the lack of corresponding monitoring and management, can greatly limit the overall application and effectiveness of EIA follow-up in China. However, a number of good practices were identified. For example, a list of projects subject to mandatory EIA follow-up was promulgated, and the conditions for projects subject to EIA follow-up were explicitly stipulated in regulations. These good practices would be very helpful for the international EIA community to advance the practice of EIA follow-up, to reduce the disparities in the quality and the rigor of EIA follow-up, to improve the overall effectiveness of EIA follow-up and to promote the future implementation and development of EIA follow-up.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Nondestructive Modular Leak Detection in 3D Printed 316L Stainless Steel Pipes via Laser Powder Bed Fusion

This research investigates the leak detection features of 316L Stainless Steel pipe structures manufactured via Laser Powder Bed Fusion (LPBF). This work involves the design of a modular sensor system integrating nondestructive evaluation (NDE) methods, including thermal imaging and ultrasonic frequency detection to detect and characterize leaks in components. This aims to improve leak detection sensitivity within medium-pressure gas systems, during continuous operation without halting flow or introducing safety risks. The system could be adaptable for use on unmanned aerial vehicles (UAVs), enabling remote leak detection in active environments. A custom pneumatic system incorporating temperature and pressure sensors was assembled to detect leaks in LPBF-printed 316L SS tee pipes. Experimental results and simulations confirm the system’s effectiveness in leak detection and material evaluation. This research program also integrated a Python-based image recognition platform based on a metallography and optical microscopy to assess the porosity and complement the leak detection data on the printed structures. This allows a detailed analysis of pore distribution and internal leak paths, which could compromise structural integrity, critical for quality control during manufacturing. Findings suggest that the investigated approach holds potential for enhancing leak detection technologies and adapt them for advanced manufactured parts.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Scaling Subspace-Driven Approaches Using Information Fusion

In this work, we seek to exploit the deep structure of multi-modal data to robustly exploit the group subspace distribution of the information using the Convolutional Neural Networks (CNNs) formalism. Upon unfolding the set of subspaces constituting each data modality, and learning their corresponding encoders, an optimized integration of the generated inherent information is carried out to yield a characterization of various classes. Referred to as deep Multimodal Robust Group Subspace Clustering (DRoGSuRe), this approach is compared against the independently developed state-of-the-art approach named Deep Multimodal Subspace Clustering (DMSC). Experiments on different multimodal datasets show that our approach is competitive and more robust in the presence of noise.

Ghanem, Sally↗
DOE OSTI2019

Co-location Pattern Mining of Geosocial Data to Characterize Urban Functional Spaces

Spatial Co-location Pattern (SCP) mining continues to play a critical role in understanding the morphology of urban functional spaces of world cities. It requires a large amount of fine-granular data and computing efficiency to handle the combinatorial explosion of co-location patterns. To this end, this work has two main contributions - i) We showcase a novel approach to perform SCP mining to characterize intra-city scale structure of urban functionality or co-located activity patterns using geosocial Points-of-Interest (POI) vector data. ii) We present a generalized and optimized parallel/distributed SCP mining algorithm implemented on a Hadoop MapReduce system and demonstrate the utility of our approach using the city of Berlin (Germany) as an example. The SCPs tend to vary across Berlin's municipal boroughs and at different spatial scales. Our findings on Berlin's functional structure conform to existing urban geography models. Such a data-driven exploration of massive urban POIs using distributed computing is first of its kind and can help better understand the changing dynamics of urban functionality, as well as physical, and social network structure around the world.

Masrur, Arif↗
DOE OSTI2020

TriC: Distributed-memory Triangle Counting by Exploiting the Graph Structure

Graph analytics has emerged as an important tool in the analysis of large scale data from diverse application domains such as social networks, cyber security and bioinformatics. Counting the number of triangles in a graph is a fundamental kernel with several applications such as detecting the community structure of a graph or in identifying important vertices in a graph. The ubiquity of massive datasets is driving the need to scale graph analytics on parallel systems. However, numerous challenges exist in efficiently parallelizing graph algorithms, especially on distributed-memory systems. Irregular memory accesses and communication patterns, low computation to communication ratios, and the need for frequent synchronization are some of the leading challenges. In this paper, we present TriC, our distributed-memory implementation of triangle counting in graphs using the Message Passing Interface (MPI), as a submission to the 2020 GraphChallenge competition. Using a set of synthetic and real-world inputs from the challenge, we demonstrate a speedup of up to 90x relative to previous work on 32 processor-cores of a NERSC Cori node. We also provide details from distributed runs with up to8192 processes along with strong scaling results. The observations presented in this work provide an understanding of the system-level bottlenecks at scale that specifically impact sparse-irregular workloads and will therefore benefit other efforts to parallelize graph algorithms.

Halappanavar, Mahantesh↗
DOE OSTI2018

Crystal and Magnetic Structures of Granular Powder Spinel Mn–Zn and Ni–Zn Ferrites

Some specific features of the crystal and magnetic structures of granular powder spinel-like ferrites Mn{sub 0.160}Mg{sub 0.404}Zn{sub 0.448}Fe{sub 2}O{sub 4}, Mn{sub 0.676}Zn{sub 0.227}Fe{sub 0.09}Fe{sub 2}O{sub 4}, Mn{sub 0.5792}Zn{sub 0.2597}Fe{sub 0.1612}Fe{sub 2}O{sub 4}, and Ni{sub 0.32}Zn{sub 0.68}Fe{sub 2}O{sub 4} have been studied by neutron diffraction. It has been established that the crystal structure of all the studied compounds has a cubic symmetry with space group Fd3̄m. Ferrimagnetic ordering is observed in all the studied structures. Based on the experimental data, the unit cell parameters and interatomic bond lengths of the studied compounds are determined alongside with the distribution of cations between octahedral and tetrahedral crystallographic positions in their cubic crystal structure. Corresponding average magnetic moments are calculated for different positions in their cubic structure. Some structural mechanisms of the formation of magnetic properties depending on the level of doping and the size of powder grains are discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Search for heavy pseudoscalar and scalar bosons decaying to a top quark pair in proton–proton collisions at $\sqrt{s}$ = 13 TeV

A search for pseudoscalar or scalar bosons decaying to a top quark pair ($\textrm{t}$$\bar{\textrm{t}}$) in final states with one or two charged leptons is presented. The analyzed proton–proton collision data was recorded at $\sqrt{s}$ = 13 TeV by the CMS experiment at the CERN LHC and corresponds to an integrated luminosity of 138 fb -1 . The invariant mass $m_{{\textrm{t}}{\bar{\textrm{t}}}}$ of the reconstructed $\textrm{t}$$\bar{\textrm{t}}$ system and variables sensitive to its spin and parity are used to discriminate against the standard model background. Interference between pseudoscalar or scalar boson production and the standard model $\textrm{t}$$\bar{\textrm{t}}$ continuum is included, leading to peak-dip structures in the $m_{{\textrm{t}}{\bar{\textrm{t}}}}$ distribution. An excess of the data above the background prediction, based on perturbative quantum chromodynamics (QCD) calculations, is observed near the kinematic $\textrm{t}$$\bar{\textrm{t}}$ production threshold, while good agreement is found for high $m_{{\textrm{t}}{\bar{\textrm{t}}}}$. The data are consistent with the background prediction if the contribution from a simplified model of a color-singlet $^1\textrm{S}^{|1|}_0$ ${{\textrm{t}}{\bar{\textrm{t}}}}$ quasi-bound state $η_{\textrm{t}}$, inspired by nonrelativistic QCD, is added. Upper limits at 95% confidence level are set on the coupling between the pseudoscalar or scalar bosons and the top quark for boson masses in the range 365–1000 GeV, relative widths between 0.5% and 25%, and two background scenarios with or without $η_{\textrm{t}}$ contribution.

CMS↗
DOE OSTI2021

Joint Matrix Completion and Compressed Sensing for State Estimation in Low-observable Distribution System

Limited measurement availability at the distribution grid presents challenges for state estimation and situational awareness. This paper combines the advantages of two sparsity-based state estimation approaches (matrix completion and compressive sensing) that have been proposed recently to address the challenge of unobservability. The proposed approach exploits both the low rank structure and a suitable transform domain representation to leverage the correlation structure of the spatio-temporal data matrix while incorporating the powerflow constraints of the distribution grid. Simulations are carried out on three phase unbalanced IEEE 37 test system to verify the effectiveness of the proposed approach. The performance results reveal - (1) the superiority over traditional matrix completion and (2) very low state estimation errors for high compression ratios representing very low observability.

Dahale, Shweta↗
DOE OSTI2019

A new method for in situ structural investigations of nano-sized amorphous and crystalline materials using mixed-flow reactors

Structural investigations of amorphous and nanocrystalline phases forming in solution are historically challenging. Few methods are capable of in situ atomic structural analysis and rigorous control of the system. A mixed-flow reactor (MFR) is used for total X-ray scattering experiments to examine the short- and long-range structure of phases in situ with pair distribution function (PDF) analysis. The adaptable experimental setup enables data collection for a range of different system chemistries, initial supersaturations and residence times. The age of the sample during analysis is controlled by adjusting the flow rate. Faster rates allow for younger samples to be examined, but if flow is too fast not enough data are acquired to average out excess signal noise. Slower flow rates form older samples, but at very slow speeds particles settle and block flow, clogging the system. Proper background collection and subtraction is critical for data optimization. Overall, this MFR method is an ideal scheme for analyzing the in situ structures of phases that form during crystal growth in solution. As a proof of concept, high-resolution total X-ray scattering data of amorphous and crystalline calcium phosphates and amorphous calcium carbonate were collected for PDF analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Local structural behavior of PbZr 0.5 Ti 0.5 O 3 during electric field application via in situ pair distribution function study

Here, the local structural behavior of PbZr 0.5 Ti 0.5 O3 (PZT 50/50) ceramics during application of an electric field was investigated using pair distribution function (PDF) analysis. In situ synchrotron total scattering was conducted, and the PDFs were calculated from the Fourier transform of the total scattering data. The PDF refinement of the zero-field data suggests a local-structure model with [001] Ti-displacement and negligible Zr-displacement. The directional PDFs at different field amplitudes indicate the bond-length distribution of the nearest Pb-B (B = Zr/Ti) pair changes significantly with the field. The radial distribution functions (RDFs) of a model for polarization rotation were calculated. The calculated and the experimental RDFs are consistent. This result suggests the changes in Pb-B bond-length distribution could be dominantly caused by polarization rotation. Peak fitting of the experimental RDFs was also conducted. The peak position trends with increasing field are mostly in agreement with the calculation result of the polarization rotation model. The area ratio of the peaks in the experimental RDFs also changed with field amplitude, indicating that Zr atoms have a detectable displacement driven by the electric field. Our study provides an experimental observation of the behaviors of PZT 50/50 under field at a local scale which supports the polarization rotation mechanism.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Final Scientific/Technical Report, Multi-Sensor Inspection and Robotic Systems for Dry Storage Casks

Once removed from service, fuel rod assemblies are cooled in a pool and then placed in dry storage until they can be transported to a repository for disposal. The extended duration that used nuclear fuel spends in dry storage makes it prudent to be able to nondestructively inspect the dry storage casks. The degradation mechanisms of most concern are chloride-induced stress corrosion cracking of the stainless steel canister that confines the spent fuel and distributed cracking of the concrete in the overpack structure. Multi-sensor inspection and robotic systems were researched, developed, built, and tested. One system operates completely outside the cask to inspect the concrete. The other system, known as the PRINSE system, for Proactive Robotic Inspection of Nuclear Storage Enclosures, enters the cask through an outlet vent and navigates around the outer surface of the stainless steel canister. The PRINSE system delivers sensors for: (i) real-time characterization of the canister surface in order to assess whether chlorides are present, (ii) detecting the presence of cracks using shear-horizontal ultrasonic guided waves, (iii) measuring the temperature of the canister surface, and (iv) a gamma radiation counter. The four sensing modalities are applicable to any cask containing a stainless steel canister, however the robotic delivery system is designed specifically for Holtec’s HI-STORM family of casks. Horizontal axis casks have exposed concrete surfaces. A fully contactless air-coupled scanning ultrasonic test platform and a frequency-wavenumber domain data analysis method are used for these concrete structures. Analysis, numerical simulation and experimental results demonstrate that distributed cracks in concrete can be detected and cracked regions localized within a scanned region of concrete. Vertical axis casks (like the HI-STORM family) have steel-clad concrete overpacks. In a separate effort, a semi-coupled test platform and a guided wave attenuation-based data analysis method are used for disbond detection. Analysis, numerical simulation and experimental results show that the bonding conditions of steel-concrete interfaces can be quantitatively characterized using the guided wave signal analysis scheme. The PRINSE system is designed for vertical axis dry storage casks, specifically the HI-STORM family. The double pulse laser-induced breakdown spectroscopy (LIBS) system takes advantage of an optical fiber to deliver intense light to the canister surface that enables surface composition characterization in-situ in real time. Chlorine concentrations as low as 10 mg/m2 were detected on stainless steel. Additionally, a simpler laser setup was created to detect sodium as a surrogate for chlorine, and sodium was detectable when the chlorine concentration was as low as 0.5 mg/m2. The electromagnetic acoustic transducers (EMATs) enable detection of stress corrosion cracks. The EMATs generate shear-horizontal waves that propagate around the canister and are reflected by cracks enabling 100% of the canister weld lines to be inspected. The EMAT-based crack detection system was tested at the Pacific Northwest National Laboratory on a canister containing blind defects and was shown to detect the crack sizes it was designed to detect. The PRINSE system is a novel marsupial robot. The command center and winch outside the cask control the delivery arm and train of cars that traverse the outside of the canister from the cask ventilation system. The sensors are housed in the cargo bays of three cars that comprise the train, which is lowered to the bottom of the canister by the winch. Encoders on the winch enable the sensors to be delivered to a prescribed location, e.g., for re-inspection of a problem area. The PRINSE system does not mar the canister surface, can be extracted manually in the case of a power failure, and is designed for an elevated temperature and gamma radiation environment, although not all components of the prototype are made from the final materials. The PRINSE system was tested on a full canister that was placed inside a HI-STORM cask at the Holtec Manufacturing Division. It was also demonstrated on a full-height mockup at Penn State to a live audience.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Modification of Quark-Gluon Distributions in Nuclei by Correlated Nucleon Pairs

We extend the QCD Parton Model analysis using a factorized nuclear structure model incorporating individual nucleons and pairs of correlated nucleons. Our analysis of high-energy data from lepton deep-inelastic scattering, Drell-Yan, and W and Z boson production simultaneously extracts the universal effective distribution of quarks and gluons inside correlated nucleon pairs, and their nucleus-specific fractions. Such successful extraction of these universal distributions marks a significant advance in our understanding of nuclear structure properties connecting nucleon- and parton-level quantities. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

β-decay feeding intensity distributions for 103,104m Nb

The β decays of 103,104m Nb were studied with the Summing NaI(Tl) (SuN) detector at the National Superconducting Cyclotron Laboratory. The β-decay feeding intensity distribution I β (E) for each isotope was extracted by measuring γ rays in coincidence with an emitted electron. The I β (E) was extracted via the total absorption spectroscopy technique. The I β (E) for each nucleus was compared to predictions made by the quasiparticle random-phase approximation (QRPA) model which is commonly used to calculate β-decay properties for astrophysical applications. The main goal was to provide experimental data for neutron-rich nuclei, relevant to the astrophysical r process. In addition, the extracted β-decay feeding intensity distributions can lead to a better understanding of nuclear structure in a region of rapid structure changes around A = 100. Finally, experimental data for 104m Nb are also of interest to antineutrino studies of nuclear reactors

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Spatio-Temporal Deep Graph Network for Event Detection, Localization, and Classification in Cyber-Physical Electric Distribution System

This work proposes a deep graph learning framework to identify, locate, and classify power, cyber, and cyber power events at the distribution system level. The proposed algorithm jointly exploits spatial, temporal, and node-level cyber and physical data features. The developed graph neural network, together with a deep autoencoder, utilizes physical measurements from distribution level phasor measurement units and cyber data from communication network logs. The spatial structure of the synchrophasor measurements and network is incorporated through a weighted adjacency matrix. The temporal structure is incorporated by defining a spatial operation in the gated recurrent unit. This spatio-temporal learning element resides inside a power event detection, localization, and classification module that provides the degree of confidence for an event label. To accurately pinpoint the location of an event to the nearest bus equipped with a measurement unit, a combination of squared error and proximity score is utilized. Also included is a cyber event detection module that employs heteroskedasticity to analyze the significance of various cyber features during different types of attacks. Finally, a dual-bit cyber-power decision table determines the nature of the event. The proposed method is validated on two distribution systems modeled in OPAL-RT/Hypersim with limited phasor measurement units for different possible physical and cyber events. Further analyses include comparison with other state-of-the-art methods and validation in the presence of measurement noise. As a result, our method outperforms existing approaches and achieves an average detection accuracy of 97.97%, F1-score of 96.88%, precision of 96.53%, and recall of 98.57%.

24 POWER TRANSMISSION AND DISTRIBUTION↗