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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 901 records · Page 50
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Mapping nanocrystal orientations via scanning Laue diffraction microscopy for multi-peak Bragg coherent diffraction imaging

The recent commissioning of a movable monochromator at the 34-ID-C endstation of the Advanced Photon Source has vastly simplified the collection of Bragg coherent diffraction imaging (BCDI) data from multiple Bragg peaks of sub-micrometre scale samples. Laue patterns arising from the scattering of a polychromatic beam by arbitrarily oriented nanocrystals permit their crystal orientations to be computed, which are then used for locating and collecting several non-co-linear Bragg reflections. The volumetric six-component strain tensor is then constructed by combining the projected displacement fields that are imaged using each of the measured reflections via iterative phase retrieval algorithms. Complications arise when the sample is heterogeneous in composition and/or when multiple grains of a given lattice structure are simultaneously illuminated by the polychromatic beam. Here, a workflow is established for orienting and mapping nanocrystals on a substrate of a different material using scanning Laue diffraction microscopy. The capabilities of the developed algorithms and procedures with both synthetic and experimental data are demonstrated. The robustness is verified by comparing experimental texture maps obtained with Laue diffraction microscopy at the beamline with maps obtained from electron back-scattering diffraction measurements on the same patch of gold nanocrystals. Such tools provide reliable indexing for both isolated and densely distributed nanocrystals, which are challenging to image in three dimensions with other techniques.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Structure of the SPRY domain of the human RNA helicase DDX1, a putative interaction platform within a DEAD-box protein

The structure of the SPRY domain of the human RNA helicase DDX1 was determined at 2.0 Å resolution. The SPRY domain provides a putative protein–protein interaction platform within DDX1 that differs from other SPRY domains in its structure and conserved regions. The human RNA helicase DDX1 in the DEAD-box family plays an important role in RNA processing and has been associated with HIV-1 replication and tumour progression. Whereas previously described DEAD-box proteins have a structurally conserved core, DDX1 shows a unique structural feature: a large SPRY-domain insertion in its RecA-like consensus fold. SPRY domains are known to function as protein–protein interaction platforms. Here, the crystal structure of the SPRY domain of human DDX1 (hDSPRY) is reported at 2.0 Å resolution. The structure reveals two layers of concave, antiparallel β-sheets that stack onto each other and a third β-sheet beneath the β-sandwich. A comparison with SPRY-domain structures from other eukaryotic proteins showed that the general β-sandwich fold is conserved; however, differences were detected in the loop regions, which were identified in other SPRY domains to be essential for interaction with cognate partners. In contrast, in hDSPRY these loop regions are not strictly conserved across species. Interestingly, though, a conserved patch of positive surface charge is found that may replace the connecting loops as a protein–protein interaction surface. The data presented here comprise the first structural information on DDX1 and provide insights into the unique domain architecture of this DEAD-box protein. By providing the structure of a putative interaction domain of DDX1, this work will serve as a basis for further studies of the interaction network within the hetero-oligomeric complexes of DDX1 and of its recruitment to the HIV-1 Rev protein as a viral replication factor.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Structure of the human histone chaperone FACT Spt16 N-terminal domain

The Spt16–SSRP1 heterodimer is a histone chaperone that plays an important role in regulating chromatin assembly. Here, a crystal structure of the N-terminal domain of human Spt16 is presented and it is shown that this domain may contribute to histone binding. The histone chaperone FACT plays an important role in facilitating nucleosome assembly and disassembly during transcription. FACT is a heterodimeric complex consisting of Spt16 and SSRP1. The N-terminal domain of Spt16 resembles an inactive aminopeptidase. How this domain contributes to the histone chaperone activity of FACT remains elusive. Here, the crystal structure of the N-terminal domain (NTD) of human Spt16 is reported at a resolution of 1.84 Å. The structure adopts an aminopeptidase-like fold similar to those of the Saccharomyces cerevisiae and Schizosaccharomyces pombe Spt16 NTDs. Isothermal titration calorimetry analyses show that human Spt16 NTD binds histones H3/H4 with low-micromolar affinity, suggesting that Spt16 NTD may contribute to histone binding in the FACT complex. Surface-residue conservation and electrostatic analysis reveal a conserved acidic patch that may be involved in histone binding.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

High-resolution crystal structures of Escherichia coli FtsZ bound to GDP and GTP

Bacterial cytokinesis is mediated by the Z-ring, which is formed by the prokaryotic tubulin homolog FtsZ. Recent data indicate that the Z-ring is composed of small patches of FtsZ protofilaments that travel around the bacterial cell by treadmilling. Treadmilling involves a switch from a relaxed (R) state, favored for monomers, to a tense (T) conformation, which is favored upon association into filaments. The R conformation has been observed in numerous monomeric FtsZ crystal structures and the T conformation in Staphylococcus aureus FtsZ crystallized as assembled filaments. However, while Escherichia coli has served as a main model system for the study of the Z-ring and the associated divisome, a structure has not yet been reported for E. coli FtsZ. To address this gap, structures were determined of the E. coli FtsZ mutant FtsZ(L178E) with GDP and GTP bound to 1.35 and 1.40 Å resolution, respectively. The E. coli FtsZ(L178E) structures both crystallized as straight filaments with subunits in the R conformation. These high-resolution structures can be employed to facilitate experimental cell-division studies and their interpretation in E. coli .

protofilaments↗
DOE OSTI2015

Geant4 simulation of clinical proton and carbon ion beams for the treatment of ocular melanomas with the full 3-D pencil beam scanning system

This work investigates the possibility to use carbon ion beams delivered with active scanning modality, for the treatment of ocular melanomas at the Centro Nazionale di Adroterapia Oncologica (CNAO) in Pavia. The radiotherapy with carbon ions offers many advantages with respect to the radiotherapy with protons or photons, such as a higher relative radio-biological effectiveness (RBE) and a dose release better localized to the tumor. The Monte Carlo (MC) Geant4 10.00 patch-03 toolkit is used to reproduce the complete CNAO extraction beam line, including all the active and passive components characterizing it. The simulation of proton and carbon ion beams and radiation scanned field is validated against CNAO experimental data. For the irradiation study of the ocular melanoma an eye-detector, representing a model of a human eye, is implemented in the simulation. Each element of the eye is reproduced with its chemical and physical properties. Inside the eye-detector a realistic tumor volume is placed and used as the irradiation target. A comparison between protons and carbon ions eye irradiations allows to study possible treatment benefits if carbon ions are used instead of protons. (authors)

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Model-driven Deception for Control System Environments

Deception techniques are a useful defensive mechanism that could be very valuable in control systems where updates and patches can be difficult. However, to deceive a motivated and targeted attacker it is necessary to enhance deception platforms with capabilities to model and simulate physical processes to achieve necessary fidelity. In this paper, attributes of cyberphysical decoys are discussed and design of a system with these attributes is presented. A boiler model use case is provided to demonstrate how this novel deception capability can be integrated into and used to defend a system.

Hofer, William J.↗
DOE OSTI2019

Convolutional Dictionary Regularizers for Tomographic Inversion

There has been a growing interest in the use of data-driven regularizers to solve inverse problems associated with computational imaging systems. The convolutional sparse representation model has recently gained attention, driven by the development of fast algorithms for solving the dictionary learning and sparse coding problems for sufficiently large images and data sets. Nevertheless, this model has seen very limited application to tomographic reconstruction problems. In this paper, we present a model-based tomographic reconstruction algorithm using a learnt convolutional dictionary as a regularizer. The key contribution is the use of a data-dependent weighting scheme for the l 1 regularization to construct an effective denoising method that is integrated into the inversion using the Plug-and-Play reconstruction framework. Using simulated data sets we demonstrate that our approach can improve performance over traditional regularizers based on a Markov random field model and a patch-based sparse representation model for sparse and limited-view tomographic data sets.

Singanallur Vaidyanathan, Venkatakrishnan↗
DOE OSTI2012

Miniaturized Multi-Band Antenna via Element Collocation

Although much research has been performed on a driven element parasitically loaded by another element shorted to ground for dual frequency operation, the novel concept of two or more coplanar-driven elements in close proximity designed for multiple frequency operation has not been represented in the literature. Since each higher frequency antenna is built into the lower frequency elements, the largest element controls the structure’s total size. Furthermore, by using the self-resonant frequency inherent in reactive elements due to device packaging, the aperture of each antenna, due to a low insertion loss path at the frequency of the larger element, will include that of all smaller radiators. This configuration provides a large standing wave ratio at the shorter wavelengths via several series capacitive-inductive connections. Therefore, each antenna element provides the required surface area for the frequency of operation while being isolated from the larger radiators. For this study, a dual 2.45/5.8 GHz microstrip patch encompasses a small surface area of 9 square inches and provides circularly polarized electromagnetic radiation in excess of 6 dBi. This concept can be extrapolated to include additional radiators or may be scaled to other frequencies of interest.

42 ENGINEERING↗
DOE OSTI2018

Multilevel Semantic Labeling of Mobile Homes from Overhead Imagery

Finding where people live and the vulnerabilities of man-made facilities during natural disasters, is not only critical for rescue efforts, but also essential for damage assessment in the aftermath. Leveraging on the availability of high resolution satellite imagery, advances in machine learning and high performance computing hardware, it is now possible to generate geographical maps for man-made facilities at scale. Mapping from satellite imagery can be a daunting task due to the enormous amount of data to be processed over large areas. In this short paper we take advantage of annotated satellite imagery and automate the semantic labeling of mobile home parks using an efficient framework rooted in patch-based and pixel-level classification. This multilevel labeling effort is a precursor to our future goal for deploying very large scale deep convolutional neural networks toward both broad and finer characterization of man-made structures from one-meter resolution NAIP images.

Lunga, Dalton↗
DOE OSTI2021

A Review of Cyber-Physical Security for Photovoltaic Systems

In this paper, the challenges and a future vision of the cyber-physical security of photovoltaic (PV) systems are discussed from a firmware, network, PV converter controls, and grid security perspective. The vulnerabilities of PV systems are investigated under a variety of cyber-attacks, ranging from data integrity attacks to software-based attacks. A success rate metric is designed to evaluate the impact and facilitate decision making. Model-based and data-driven methods for threat detection and mitigation are summarized. In addition, the blockchain technology that addresses cyber-attacks in software and cyber networks is described. Simulation and experimental results that show the impact of cyber-attacks at the converter (device) and grid (system) levels are presented. Finally, potential research opportunities are discussed for next-generation, cyber-secure power electronics systems. These opportunities include multi-scale controllability, self-/event-triggering control, artificial intelligence/machine learning, hot patching, and online security. As of today, this study will be one of the few comprehensive studies in this emerging and fast-growing area.

14 SOLAR ENERGY↗
DOE OSTI2021

Security Vulnerability and Mitigation in Photovoltaic Systems

Software and firmware vulnerabilities pose security threats to photovoltaic (PV) systems. When patches are not available or cannot be timely applied to fix vulnerabilities, it is important to mitigate vulnerabilities such that they cannot be exploited by attackers or their impacts will be limited when exploited. However, the vulnerability mitigation problem for PV systems has received little attention. This paper analyzes known security vulnerabilities in PV systems, proposes a multi-level mitigation framework and various mitigation strategies including neural network-based attack detection inside inverters, and develops a prototype system as a proof-of-concept for building vulnerability mitigation into PV system design.

14 SOLAR ENERGY↗
DOE OSTI2022

System Resilience Benefits of Dual-Fuel Capable Generators

The growing dependency on natural gas (NG) for power generation raises challenges for ensuring the resilience of power systems during extreme cold weather. Dual-fuel capable generators that can switch from burning NG to distillate fuel oil during a NG shortage offer one way to alleviate these challenges. In this study, the impacts of gas unavailability on the IEEE 73- bus reliability test system (RTS) with 2019 updated generation mixture are explored. An extension to the standard production cost model formulation of unit commitment and economic dis- patch is proposed to allow representation of dual-fuel capable generators that can switch fuels between NG and distillate oil with a specified oil tank capacity and tank refueling capability. The operation of the system under gas unavailability with 0%, 25%, 50%, 75%, and 100% of combined cycle and combustion turbine generators as dual-fuel capable with a one-day supply of fuel oil are simulated using PLEXOS, a production cost model. The dual-fuel generator performance, unserved energy, and system costs are fully assessed.

duel-fuel generator performance↗
DOE OSTI2013

Real-time performance of commercial Intel-based VME Controllers for the CODA data acquisition system

We have evaluated the performance of several Intel-based VME Controllers for the use in the data acquisition systems (DAQs) at Jefferson Lab. For the 12 GeV upgrade, PPC-based VME controllers running vxWorks will be replaced with those that are Intel-based running Linux. Their task will be facilitated by the use of FPGAs on the VME modules to perform trigger logic and communicating trigger information over serial and fiber connections through the DAQ. The need for a hard realtime operating system on the VME controller is removed from the equation as the readout of the digitized data from the VME modules (using VME-2eSST) is done in a threaded environment with multiple CPU cores while digitization takes place in the buffered, pipelined system. In this paper we brief discuss the 12 GeV Hall D DAQ and the requirements of the VME Controller. We present results from baseline testing of various models from different vendors using different Linux kernels, including results from a kernel compiled with the CONFIG_PREEMPT_RT patch.

Moffit, Bryan↗
DOE OSTI2020

A Radiative Transfer Model for Patchy Landscapes Based on Stochastic Radiative Transfer Theory

The availability of global high-resolution land cover maps provides promising a priori knowledge for characterizing subpixel heterogeneity and improving predictions of directional reflectance of coarse-resolution pixels. Due to mutual shadowing and sheltering effects between the adjacent forest and cropland patches, the spectral nonlinear mixing of patchy ecotones is significant, especially when the sun illuminates the ecotone from the forest side with high solar zenith angle. The spectral linear mixture (SLM) approach leads to overestimation of the bidirectional reflectance factor (BRF) in the red band in the principal plane (PP), with a maximum absolute error (MAE) of 0.0063 and a maximum relative error (MRE) of 52.5%, and to underestimation in the near-infrared band in PP with an MAE of 0.0940 and an MRE of 14.5%. In a scenario with randomly distributed boundary orientations, the overestimation of SLM increases with the degree of fragmentation and the view zenith angle. We propose a Radiative Transfer model for patchy ECotones (RTEC). which improves R² from 0.61 to 0.94 in the red band of Landsat-8 directional reflectance at the validation site. The RTEC model provides an efficient and analytical approach for directional reflectance predictions over heterogeneous patchy landscapes at coarse resolution and will be used for biophysical parameter retrievals [e.g., the leaf area index (LAI)] in future applications.

Zeng, Yelu↗
DOE OSTI2025

A Neural Optimizer With Decision-Focused Learning for Optimal Energy Storage Operation

Here, this article introduces a neural optimizer-based framework for optimizing battery energy storage system (BESS) control for grid services, including demand charge and energy cost reduction. By leveraging decision-focused learning (DFL), the proposed framework ensures seamless integration and adaptation, significantly enhancing control performance. A patch time-series transformer is employed for peak load forecasting, incorporating aleatoric uncertainty quantification to account for forecasting uncertainties within the decision-making process. The framework utilizes a solver-in-the-loop approach to generate optimal BESS actions, which are then used to train the neural optimizer-based agent. By co-optimizing both BESS operational modes and output power within the NN, the system achieves improved performance and robustness. After initial training, the forecasting and control models are jointly fine-tuned to account for forecasting errors, further improving decision precision and efficiency through DFL. Case studies are performed to validate the performance of the framework using multiple real-world datasets, demonstrating superior performance in monthly peak load forecasting compared to state-of-the-art models. In addition, the results are compared against existing decision-making approaches. The results demonstrate a reduction in monthly peak forecasting error by approximately 15% across various performance measures and achieve an optimization gap for BESS operation that is about three times smaller compared to existing methods.

Kim, Hyeonjin [Pacific Northwest National Laborato↗
DOE OSTI2015

Efficient Algorithms for Convolutional Sparse Representations

When applying sparse representation techniques to images, the standard approach is to independently compute the representations for a set of overlapping image patches. This method performs very well in a variety of applications, but results in a representation that is multi-valued and not optimized with respect to the entire image. Additionally, an alternative representation structure is provided by a convolutional sparse representation, in which a sparse representation of an entire image is computed by replacing the linear combination of a set of dictionary vectors by the sum of a set of convolutions with dictionary filters. The resulting representation is both single-valued and jointly optimized over the entire image. While this form of a sparse representation has been applied to a variety of problems in signal and image processing and computer vision, the computational expense of the corresponding optimization problems has restricted application to relatively small signals and images. Here, this paper presents new, efficient algorithms that substantially improve on the performance of other recent methods, contributing to the development of this type of representation as a practical tool for a wider range of problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

NSTX-U In-Vessel Control Coils’ Design Concept

In this paper, a successful conceptual design was completed to develop in-vessel control coils [non-axisymmetric control coils (NCCs)]. The NCCs are a series of saddle coils that are intended to satisfy a number of physics criteria including magnetic breaking, error field control, fast resistive wall mode (RWM) control, and edge-localized-mode stabilization. Customized mineral-insulated cable (MIC) was selected for the conductor material. The MIC was made from oxygen-free copper conductor, high purity magnesium oxide powder insulation, and 304 stainless steel sleeve cover. Sample MIC was purchased from an outside supplier, and various tests were conducted for design and performance verification including high-voltage testing, which necessitated the development of special test terminations. A concept design was also developed for terminating the MIC ends using the nonconductive and vacuum-sealed technique. Two alternative designs were proposed for joints inside the vacuum vessel (VV). The NCCs are designed to be mounted in front of the primary passive plates and underneath the plasma-facing component (PFC) tiles. The passive plates will be modified to accommodate the coils. A new PFC tile design concept was developed using high-Z materials. New designs for the penetrations through the VV wall were developed. One port per coil was planned. Finally, a new power patch panel will be required to provide the ability for various combinations of connections between the NCC, the existing RWM coils, and the existing switching power amplifier power suppliers.

42 ENGINEERING↗
DOE OSTI2023

Load Profile Inpainting for Missing Load Data Restoration and Baseline Estimation

This paper introduces a Generative Adversarial Nets (GAN) based, Load Profile Inpainting Network (Load-PIN) for restoring missing load data segments and estimating the baseline for a demand response event. The inputs are time series load data before and after the inpainting period together with explanatory variables (e.g., weather data). Here, we propose a Generator structure consisting of a coarse network and a fine-tuning network. The coarse network provides an initial estimation of the data segment in the inpainting period. The fine-tuning network consists of self-attention blocks and gated convolution layers for adjusting the initial estimations. Loss functions are specially designed for the fine-tuning and the discriminator networks to enhance both the point-to-point accuracy and realisticness of the results. We test the Load-PIN on three real-world data sets for two applications: patching missing data and deriving baselines of conservation voltage reduction (CVR) events. We benchmark the performance of Load-PIN with five existing deep-learning methods. Our simulation results show that, compared with the state-of-the-art methods, Load-PIN can handle varying-length missing data events and achieve 15-30% accuracy improvement.

14 SOLAR ENERGY↗