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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

An adjoint method for a high-order discretization of deforming domain conservation laws for optimization of flow problems

We report the fully discrete adjoint equations and the corresponding adjoint method are derived for a globally high-order accurate discretization of conservation laws on parametrized, deforming domains. The conservation law on the deforming domain is transformed into one on a fixed reference domain by the introduction of a time-dependent mapping that encapsulates the domain deformation and parametrization, resulting in an Arbitrary Lagrangian–Eulerian form of the governing equations. A high-order discontinuous Galerkin method is used to discretize the transformed equation in space and a high-order diagonally implicit Runge–Kutta scheme is used for the temporal discretization. Quantities of interest that take the form of space–time integrals are discretized in a solver-consistent manner. The corresponding fully discrete adjoint method is used to compute exact gradients of quantities of interest along the manifold of solutions of the fully discrete conservation law. These quantities of interest and their gradients are used in the context of gradient-based PDE-constrained optimization. The adjoint method is used to solve two optimal shape and control problems governed by the isentropic, compressible Navier–Stokes equations. The first optimization problem seeks the energetically optimal trajectory of a 2D airfoil given a required initial and final spatial position. The optimization solver, driven by gradients computed via the adjoint method, reduced the total energy required to complete the specified mission nearly an order of magnitude. The second optimization problem seeks the energetically optimal flapping motion and time-morphed geometry of a 2D airfoil given an equality constraint on the x-directed impulse generated on the airfoil. The optimization solver satisfied the impulse constraint to greater than 8 digits of accuracy and reduced the required energy between a factor of 2 and 10, depending on the value of the impulse constraint, as compared to the nominal configuration.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Establishing Malware Attribution and Binary Provenance Using Multicompilation Techniques

Malware is a serious problem for computer systems and costs businesses and customers billions of dollars a year in addition to compromising their private information. Detecting malware is particularly difficult because malware source code can be compiled in many different ways and generate many different digital signatures, which causes problems for most anti-malware programs that rely on static signature detection. Our project uses a convolutional neural network to identify malware programs but these require large amounts of data to be effective. Towards that end, we gather thousands of source code files from publicly available programming contest sites and compile them with several different compilers and flags. Building upon current research, we then transform these binary files into image representations and use them to train a long-term recurrent convolutional neural network that will eventually be used to identify how a malware binary was compiled. This information will include the compiler, version of the compiler and the options used in compilation, information which can be critical in determining where a malware program came from and even who authored it.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Benchmarking highly entangled states on a 60-atom analogue quantum simulator

Abstract Quantum systems have entered a competitive regime in which classical computers must make approximations to represent highly entangled quantum states 1,2 . However, in this beyond-classically-exact regime, fidelity comparisons between quantum and classical systems have so far been limited to digital quantum devices 2–5 , and it remains unsolved how to estimate the actual entanglement content of experiments 6 . Here, we perform fidelity benchmarking and mixed-state entanglement estimation with a 60-atom analogue Rydberg quantum simulator, reaching a high-entanglement entropy regime in which exact classical simulation becomes impractical. Our benchmarking protocol involves extrapolation from comparisons against an approximate classical algorithm, introduced here, with varying entanglement limits. We then develop and demonstrate an estimator of the experimental mixed-state entanglement 6 , finding our experiment is competitive with state-of-the-art digital quantum devices performing random circuit evolution 2–5 . Finally, we compare the experimental fidelity against that achieved by various approximate classical algorithms, and find that only the algorithm we introduce is able to keep pace with the experiment on the classical hardware we use. Our results enable a new model for evaluating the ability of both analogue and digital quantum devices to generate entanglement in the beyond-classically-exact regime, and highlight the evolving divide between quantum and classical systems.

Science & Technology - Other Topics↗
DOE OSTI2018

Network Reduction Algorithm for Developing Distribution Feeders for Real-Time Simulators

As advanced grid-support functions (AGF) become more widely used in grid-connected photovoltaic (PV) inverters, utilities are increasingly interested in their impacts when implemented in the field. These effects can be understood by modeling feeders in real-time simulators and test PV inverters using power hardware-in-the-loop (PHIL) techniques. This paper presents a novel feeder model reduction algorithm using a ruin & reconstruct methodology that enables large feeders to be solved and operated on real-time computing platforms. Two Hawaiian Electric feeder models in Synergi Electric's load flow software were converted to reduced order models in OpenDSS, and subsequently implemented in the OPAL-RT real-time digital testing platform. Smart PV inverters were added to the realtime model with AGF responses modeled after characterizing commercially available hardware inverters. Finally, hardware inverters were tested in conjunction with the real-time model using PHIL techniques so that the effects of AGFs on the feeders could be analyzed.

14 SOLAR ENERGY↗
DOE OSTI2015

Fast, automatic, and accurate catheter reconstruction in HDR brachytherapy using an electromagnetic 3D tracking system

Purpose: In high dose rate brachytherapy (HDR-B), current catheter reconstruction protocols are relatively slow and error prone. The purpose of this technical note is to evaluate the accuracy and the robustness of an electromagnetic (EM) tracking system for automated and real-time catheter reconstruction. Methods: For this preclinical study, a total of ten catheters were inserted in gelatin phantoms with different trajectories. Catheters were reconstructed using a 18G biopsy needle, used as an EM stylet and equipped with a miniaturized sensor, and the second generation Aurora{sup ®} Planar Field Generator from Northern Digital Inc. The Aurora EM system provides position and orientation value with precisions of 0.7 mm and 0.2°, respectively. Phantoms were also scanned using a μCT (GE Healthcare) and Philips Big Bore clinical computed tomography (CT) system with a spatial resolution of 89 μm and 2 mm, respectively. Reconstructions using the EM stylet were compared to μCT and CT. To assess the robustness of the EM reconstruction, five catheters were reconstructed twice and compared. Results: Reconstruction time for one catheter was 10 s, leading to a total reconstruction time inferior to 3 min for a typical 17-catheter implant. When compared to the μCT, the mean EM tip identification error was 0.69 ± 0.29 mm while the CT error was 1.08 ± 0.67 mm. The mean 3D distance error was found to be 0.66 ± 0.33 mm and 1.08 ± 0.72 mm for the EM and CT, respectively. EM 3D catheter trajectories were found to be more accurate. A maximum difference of less than 0.6 mm was found between successive EM reconstructions. Conclusions: The EM reconstruction was found to be more accurate and precise than the conventional methods used for catheter reconstruction in HDR-B. This approach can be applied to any type of catheters and applicators.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-C-207-06: In Vivo Quantification of Gold Nanoparticles Using K-Edge Imaging Via Spectrum Shaping by Gold Filter

Purpose: Gold nanoparticles (AuNP) are multifunctional platforms ideal for drug delivery, targeted imaging and radiosensitization. We have investigated quantitative imaging of AuNPs using on board imager (OBI) cone beam computed tomography (CBCT). To this end, we also present, for the first time, a novel method for k-edge imaging of AuNP by filter-based spectral shaping. Methods: We used a digital 25 cm diameter water phantom, embedded with 3 cm spheres filled with AuNPs of different concentrations (0 mg/ml – 16 mg/ml). A poly-energetic X-ray spectrum of 140 kVp from a conventional X-ray tube is shaped by balanced K-edge filters to create an excess of photons right above the K-edge of gold at 80.7 keV. The filters consist of gold, tin, copper and aluminum foils. The phantom with appropriately assigned attenuation coefficients is forward projected onto a detector for each energy bin and then integrated. FKD reconstruction is performed on the integrated projections. Scatter, detector efficiency and noise are included. Results: We found that subtracting the results of two filter sets (Filter A:127 µm gold foil with 254 µm tin, 330 µm copper and 1 mm aluminum, and Filter B: 635 µm tin with 264 µm copper and 1 mm aluminum), provides substantial image contrast. The resulting filtered spectra match well below 80.7 keV, while maintaining sufficient X-ray quanta just above that. Voxel intensities of AuNP containing spheres increase linearly with AuNP concentration. K-edge imaging provides 18% more sensitivity than the tin filter alone, and 38% more sensitivity than the gold filter alone. Conclusion: We have shown that it is feasible to quantitatively detect AuNP distributions in a patient-sized phantom using clinical CBCT and K-edge spectral shaping.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-D-204-06: Dose and Image Quality Evaluation of a Low-Dose Slot-Scanning X-Ray System for Pediatric Orthopedic Studies

Purpose: Children in early teens with scoliosis require repeated radiographic exams over a number of years. The EOS (EOS imaging S.A., Paris, France) is a novel low-dose slot-scanning digital radiographic system designed to produce full-spine images of a free-standing patient. The radiation dose and image quality characteristics of the EOS were evaluated relative to those of a Computed Radiography (CR) system for scoliosis imaging. Methods: For dose evaluation, a full-torso anthropomorphic phantom was scanned five times using the default standard clinical protocols for both the EOS and a CR system, which include both posteroanterior and lateral full-spine views. Optically stimulated luminescent dosimeters (OSLDs), also known as nanoDots™ (Landauer, Inc., Glenwood, IL), were placed on the phantom’s surface to measure entrance skin dose. To assess image quality, MTF curves were generated from sampling the noise levels within the high-contrast regions of a line-pair phantom. Vertical and horizontal distortions were measured for the square line-pair phantom with the EOS system to evaluate the effects of geometric magnification and misalignment with the indicated imaging plane. Results: The entrance skin dose was measured to be 0.4 to 1.1 mGy for the EOS, and 0.7 to 3.6 mGy for the CR study. MTF comparison shows that CR greatly outperforms the EOS, despite both systems having a limiting resolution at 1.8 line-pairs per mm. Vertical distortion was unaffected by phantom positioning, because of the EOS slot-scanning geometry. Horizontal distortion increased linearly with miscentering distance. Conclusion: The EOS system resulted in approximately 70% lower radiation dose than CR for full-spine images. Image quality was found to be inferior to CR. Further investigation is required to see if EOS system is an acceptable modality for performing clinically diagnostic scoliosis examinations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Human-System Interface Design Review Guidelines

The U.S. Nuclear Regulatory Commission (NRC) staff reviews the human factors engineering (HFE) aspects of nuclear power plants in accordance with the Standard Review Plan (NUREG-0800, Standard Review Plan for the Review of Safety Analysis Reports for Nuclear Power Plants: LWR Edition). The Human Factors Engineering Program Review Model (NUREG-0711, Revision 3, issued November 2012) contains detailed design review procedures. As part of the review process, the interfaces between plant personnel and the plant's systems and components are evaluated for conformance with HFE guidelines. This document, Human-System Interface Design Review Guidelines (NUREG-0700, Revision 3), provides the guidelines necessary to perform this evaluation. The review guidelines address the physical and functional characteristics of human-system interfaces (HSIs). Because these guidelines only address the HFE aspects of design and not other related considerations, such as instrumentation and control and structural design, they are referred to as HFE guidelines. In addition to the review of actual HSIs, the NRC staff can use the NUREG-0700 guidelines to evaluate a design-specific HFE guidelines document or style guide. The HFE guidelines are organized into four basic parts, which are divided into sections. Part I contains guidelines for the basic HSI elements: information displays, user-interface interaction and management, and analog displays and controls. These elements are used as building blocks to develop HSI systems to serve specific functions. Part II contains the guidelines for reviewing the following HSI systems: alarm system, safety parameter display system, group-view display system, soft control system, computer-based procedure system, automation system, and communication system. Part III provides guidelines for the review of workstations and workplaces. Part IV provides guidelines for the review of HSI support (i.e., maintainability of digital systems and degraded HSI and instrumentation and control conditions).

42 ENGINEERING↗
DOE OSTI2021

Safety and Security Defense-in-Depth for Nuclear Power Plants

This report describes the risk-informed technical elements that will contribute to a defense-in-depth assessment for cybersecurity. Risk-informed cybersecurity must leverage the technical elements of a risk-informed approach appropriately in order to evaluate cybersecurity risk insights. HAZCADS and HAZOP+ are suitable methodologies to model the connection between digital harm and process hazards. Risk assessment modeling needs to be expanded beyond HAZCADS and HAZOP+ to consider the sequence of events that lead to plant consequences. Leveraging current practices in PRA can lead to categorization of digital assets and prioritizing digital assets commensurate with the risk. Ultimately, the culmination of cyber hazard methodologies, event sequence modeling, and digital asset categorization will facilitate a defense-in-depth assessment of cybersecurity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Reference Site Conditions for Floating Wind Arrays in the United States

Floating offshore wind farm design is highly site-specific, requiring detailed information about the specific conditions of a project area for realistic design studies. Unfortunately, publicly available site condition data for potential floating offshore wind project sites in the United States is scarce. To support U.S. offshore wind research, we developed reference site condition datasets, including metocean and seabed information, for four potential floating wind project areas in the U.S.: Humboldt Bay, Morro Bay, the Gulf of Maine, and the Gulf of Mexico. These datasets were compiled using publicly available data. Our metocean analysis, covering wind, waves, and surface currents, utilized measurement data from 2000 to 2020. Sources included the National Renewable Energy Laboratory’s National Offshore Wind Dataset for wind data, National Data Buoy Center buoys for wave data, and the High Frequency Radar Network for surface currents. These data were integrated into hourly time series used to compute extreme return periods up to 500 years, monthly statistics, and joint probability clusters for fatigue analysis. Soil conditions were evaluated using the usSEABED database and bathymetry grids were interpolated from the NCEI Digital Elevation Model Global Mosaic. In addition to providing curated reference site condition datasets for four U.S. areas, our assessment highlights the need for more publicly available metocean and soil condition data.

17 WIND ENERGY↗
DOE OSTI2024

Zero-Power Analog Optical Processing

The motivation behind this research is the growing challenge of handling the massive amounts of data generated by modern imaging systems. Conventional digital image processing techniques are struggling to keep pace with the demands of high-resolution and high-speed imaging systems for remote sensing due to their high-power consumption and data storage requirements. We present a novel approach based on analog photonics to address this challenge. The proposed system utilizes a silicon-photonics-based image encoder positioned after image formation and initial optical-to-electrical conversion. The photonic encoder compresses image data using a passive disordered photonic structure to perform kernel-type random projections of the raw data. The compressed data is then processed by a back-end neural network, which reconstructs the original image with high fidelity (structural similarity exceeding 90%). Our proposed approach has the potential to compress images with ~ 1000X lower power consumption compared to digital approaches with data rates exceeding 1 terapixel/second.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Using Numba for GPU acceleration of Neutron Beamline Digital Twins

Digital twins of neutron instruments using Monte Carlo ray tracing have proven to be useful in neutron data analysis and verifying instrument and sample designs. However, these simulations can become quite complex and computationally demanding with tens of billions of neutrons. In this paper, we present a GPU accelerated version of MCViNE using Python and Numba to balance user extensibility with performance. Numba is an open-source just-in-time (JIT) compiler for Python using LLVM to generate efficient machine code for CPUs and GPUs with NVIDIA CUDA. The JIT nature of Numba allowed complex instrument kernels to be generated easily. Initial simulations have shown a speedup between 200-1000x over the original CPU implementation. The performance gain with Numba enables more sophisticated data analysis and impacts neutron scattering science and instrument design.

Kendrick, Coleman↗
DOE OSTI2024

Reference Site Condition Datasets for Floating Wind Arrays in the United States

Floating offshore wind farm design is highly site-specific, requiring detailed information about the specific conditions of a project area for realistic design studies. Unfortunately, publicly available site condition data for potential floating offshore wind project sites in the United States is scarce. To support U.S. offshore wind research, we developed reference site condition datasets, including metocean and seabed information, for four potential floating wind project areas in the U.S.: Humboldt Bay, Morro Bay, the Gulf of Maine, and the Gulf of Mexico. These datasets were compiled using publicly available data. Our metocean analysis, covering wind, waves, and surface currents, utilized measurement data from 2000 to 2020. Sources included the National Renewable Energy Laboratory’s National Offshore Wind Dataset for wind data, National Data Buoy Center buoys for wave data, and the High Frequency Radar Network for surface currents. These data were integrated into hourly time series used to compute extreme return periods up to 500 years, monthly statistics, and joint probability clusters for fatigue analysis. Soil conditions were evaluated using the usSEABED database and bathymetry grids were interpolated from the NCEI Digital Elevation Model Global Mosaic. Further information on the datasets and how they were created can be found in: Biglu, M., M. Hall, E. Lozon, S. Housner. 2024. Reference Site Conditions for Floating Wind Arrays in the United States. Golden, CO: National Renewable Energy Laboratory (NREL). NREL/TP-5000-89897. The data are also available at: https://github.com/FloatingArrayDesign/SiteConditions The content of each dataset is as follows: _NOW23_wind.txt: Hourly NOW-23 wind data up to a height of 400 meter. _metocean_1hr.txt: Hourly time series including wind, wave, surface current and temperature data. _Summary.xlsx: Metocean data, including extreme values, joint probability distributions and monthly statistics. _usSEABED_soil.csv: Extract of the usSEABED database for this specific site. _bathymetry_200m.txt (and 500m, 1000m): Gridded seabed depth data.

16 TIDAL AND WAVE POWER↗
DOE OSTI2017

Network Reduction Algorithm for Developing Distribution Feeders for Real-Time Simulators: Preprint

As advanced grid-support functions (AGF) become more widely used in grid-connected photovoltaic (PV) inverters, utilities are increasingly interested in their impacts when implemented in the field. These effects can be understood by modeling feeders in real-time systems and testing PV inverters using power hardware-in-the-loop (PHIL) techniques. This paper presents a novel feeder model reduction algorithm using a Monte Carlo method that enables large feeders to be solved and operated on real-time computing platforms. Two Hawaiian Electric feeder models in Synergi Electric's load flow software were converted to reduced order models in OpenDSS, and subsequently implemented in the OPAL-RT real-time digital testing platform. Smart PV inverters were added to the real-time model with AGF responses modeled after characterizing commercially available hardware inverters. Finally, hardware inverters were tested in conjunction with the real-time model using PHIL techniques so that the effects of AGFs on the choice feeders could be analyzed.

14 SOLAR ENERGY↗
DOE OSTI2026

Energy Systems Integration Facility Stewardship Summary: Fiscal Year 2025

A summary of NLR's stewardship of the nationally unique Energy Systems Integration Facility (ESIF) highlighting performance metrics, capability upgrades, and examples of R&D impact. 2025 brought a national focus on energy and ESIF is meeting the moment. All eyes are on data centers and domestic manufacturing and bringing the benefits of artificial intelligence to power system planning and operations. In step with national priorities, ESIF is building out capabilities that advance secure, reliable, and affordable power. ESIF hosted 190 multidisciplinary research projects, 855 high-performance computer users, and collaborated with 81 partners from industry, academia, research, and federal agencies. These research projects resulted in an AI method for detecting high-impedance faults with 90% accuracy, a grid controls demonstration in Connecticut, power quality validation of CorePower's flagship inductor, and a cybersecurity assessment of potential rogue capabilities in digitally connected energy devices. Facility infrastructure improvements enhanced the thermal research network, the SCADA system, the cyber range, power hardware-in-the-loop testing, and more. With support from the U.S Department of Energy (DOE), the ESIF laboratories continue to deliver leading solutions for secure, reliable, and affordable power.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Automatic Organ Segmentation for CT Scans Based on Super-Pixel and Convolutional Neural Networks

Accurate segmentation of specific organ from computed tomography (CT) scans is a basic and crucial task for accurate diagnosis and treatment. To avoid time-consuming manual optimization and to help physicians distinguish diseases, an automatic organ segmentation framework is presented. The framework utilized convolution neural networks (CNN) to classify pixels. To reduce the redundant inputs, the simple linear iterative clustering (SLIC) of super-pixels and the support vector machine (SVM) classifier are introduced. To establish the perfect boundary of organs in one-pixel-level, the pixels need to be classified step-by-step. First, the SLIC is used to cut an image into grids and extract respective digital signatures. Next, the signature is classified by the SVM, and the rough edges are acquired. Finally, a precise boundary is obtained by the CNN, which is based on patches around each pixel-point. The framework is applied to abdominal CT scans of livers and high-resolution computed tomography (HRCT) scans of lungs. The experimental CT scans are derived from two public datasets (Sliver 07 and a Chinese local dataset). Experimental results show that the proposed method can precisely and efficiently detect the organs. This method consumes 38 s/slice for liver segmentation. The Dice coefficient of the liver segmentation results reaches to 97.43%. For lung segmentation, the Dice coefficient is 97.93%. This finding demonstrates that the proposed framework is a favorable method for lung segmentation of HRCT scans.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

DEM simulation of the compression of crushable sand: does the initial particle shape matter?

Advances in DEM modeling, combined with high-resolution X-ray tomography, opened the way for computer models based on virtual replicas of the particles which preserve nearly all facets of their geometry. This leads to simulation advantages, but also high computational costs. Here we tackle a question stemming from this trend: how accurate should particle models be to ensure accuracy? We address this question for the case of the compression of crushable sand. LS-DEM was used to generate three models of Ottawa sand (exact replicas, ellipsoids, and spheres) from digital images of its grains. Compression-induced crushing was simulated for all sets by tracking evolving size and shape distribution. The results confirm that exact replicas provide the closest match of the measurements. However, intermediate degrees of rendering (e.g. ellipsoids preserving volume and aspect ratio of the real grains) led to satisfactory results only marginally different from those of exact replicas. In conclusion, these findings provide an example of the protocols that may be followed to identify the optimal degree of particle approximation which should be regarded as mandatory to achieve a conscious, sustainable use of computational resources.

58 GEOSCIENCES↗
DOE OSTI2022

Design and Challenges of Edge Computing ASICs on Front-End Electronics

In situ or hardware-embedded data processing of raw signals, close to their source, in radiation detectors is expected to provide dramatic improvements in data quality and volumes. However, the implementation of artificial neural networks (ANNs) in the front-end electronics, and the design of custom integrated circuits (ASICs), comes with challenges. In addition, detectors have to operate with limited power budget and implement complex functionalities in a very dense space. They often are exposed to extreme conditions as they work in high-radiation environments and/or cryogenic temperatures. This paper presents examples of applications and design methodologies for in-situ ANNs, along with the challenges of retaining the fidelity of the trained networks. For illustration, we use the problem of estimating the energy deposited by the radiation from digitized waveforms. The proposed implementation starts with an ML algorithm trained in Qkeras and eventually leads to an equivalent ASIC implementation. The associated design challenges in realizing energy and area efficient implementations in CMOS processes are reviewed. Novel approaches that employ hybrid technologies (combination of CMOS with memristors), in-memory computing models, and bio-inspired spiking neural networks are also highlighted

47 OTHER INSTRUMENTATION↗