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DOE OSTI2024

Power System Waveform Datasets for Machine Learning

The desire for increased visibility across the electricity grid will necessarily increase the deployment of sensing and measurement devices and associated data management needs to unprecedented levels. For the existing sensing and measurement infrastructure, there remains a great amount of “value” yet to be extracted through advanced data management and analytics. Availability of more data will not, by itself, lead to changes in grid visibility, security, and resiliency. To create the predictive and prescriptive environment required to enable new markets and transactions for customer revenue and a reliable grid, the data must be collected, organized, evaluated, and analyzed using sophisticated algorithms to provide actionable information allowing operators and customers to reliably manage an increasingly complex grid. Progress in artificial intelligence (AI) has been largely driven by large, publicly available datasets that can be used to train AI algorithms such as MNIST, a database of handwritten images of digits, and ImageNet, an image database of everyday objects. These types of publicly available databases of real-world training datasets have been largely credited for advancement of image processing, computer vision, and deep learning algorithms that these use cases deploy. However, in the power systems industry to date, there are few databases with proper event labeling, and data access to a publicly available collection of power system event waveforms that will allow users to interact with grid signature data. Publicly available datasets of power system event waveforms, such as the DOE/EPRI dataset, often lack critical metadata or contain limited examples of each event type, and data formats vary widely across these datasets.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Adaptation of Temperature Dependent Thermal Neutron Libraries for Fast On-The-Fly Monte Carlo Sampling at Arbitrary Temperatures

Thermal neutron scattering data is necessary for reactor simulations of thermal reactors, but the data storage required can be unwieldy. This is exacerbated when simulations require a large temperature range, as is the case for accident scenarios and reactor start-up. Previous work conducted at RPI has explored and demonstrated a proof of concept of On-The-Fly (OTF) data storage with light water and crystalline graphite based on ENDF/B-VII.1. This provides an updated data storage paradigm for incoherent inelastic cross-sections that allow the data to be used to generate necessary sampling Cumulative Density Functions (CDFs) for any desired temperature. The work presented in this paper extends the previous work by implementing the proof of concept based on ENDF/B-VIII.0, instead of ENDF/B-VII.1, and to include additional materials, such as beryllium and oxygen in beryllium oxide and the new reactor grades of porous graphite. Completion of this work allows a single thermal data file to represent any thermal scattering event for a given material OTF for the temperature of interest, which greatly reduces the data storage needed with only a marginal cost in the calculation of the CDFs OTF. This paper will review the basic methodologies in generating the OTF data, as well as present the updates and improvements made in the generation process. Application of the methodologies covered in this paper show a significant reduction in the storage requirements for inelastic incoherent scattering events. In which, the evaluated ENDF/B-VIII.0 thermal scattering library can be reduced from 563.1 MB to 10.9 MB for light water and 339.3 MB to 13.6 MB for Be in BeO.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS2000

Development and Implementation of Real-Time Information Delivery Systems for Emergency Management

The disaster management community has an on-going need for real-time data and information, especially during catastrophic events. Currently, twin engine or jet aircraft with limited altitude and duration capabilities collect much of the data. Flight safety is also an issue. Clearly, much of the needed data could be delivered via over-the-horizon transfer through a uninhabited aerial vehicles (UAV) platform to mission managers at various locations on the ground. In fact, because of the ability to stay aloft for long periods of time, and to fly above dangerous situations, UAV's are ideally suited for disaster missions. There are numerous situations that can be considered disastrous for the human population. Some, such as fire or flood, can continue over a period of days. Disaster management officials rely on data from the site to respond in an optimum way with warnings, evacuations, rescue, relief, and to the extent possible, damage control. Although different types of disasters call for different types of response, most situations can be improved by having visual images and other remotely sensed data available. "Disaster Management" is actually made up of a number of activities, including: - Disaster Prevention and Mitigation - Emergency Response Planning - Disaster Management (real-time deployment of resources, during an event) - Disaster / Risk Modeling All of these activities could benefit from real-time information, but a major focus for UAV-based technology is in real-time deployment of resources (i.e., emergency response teams), based on changing conditions at the location of the event. With all these potential benefits, it is desirable to demonstrate to user agencies the ability to perform disaster management missions as described. The following demonstration project is the first in a program designed to prove the feasibility of supporting disaster missions with UAV technology and suitable communications packages on-board. A several-year program is envisioned, in which a broad range of disaster-related activities are demonstrated to the appropriate user communities.

Wegener, Steve↗

DOE OSTI2024

Performance Analysis of Data Processing in Distributed File Systems with Near Data Processing

In the era of big data, the escalating volume and velocity of data generation pose significant challenges in data processing. Traditional systems like Spark and Hadoop manage the increasing amount and velocity of data by improving data placement and processing speeds. However, they face inherent limitations due to the essential data movement required for processing. In this paper, we explore the Skyhook framework, a novel extension of the Ceph distributed system, which significantly reduces the need for data movement. We present an extensive case study using the Skyhook framework, applying it with the TPC-H and K-means clustering algorithms. More specifically, we leverage the TPC-H benchmark to distinguish between CPU-intensive and I/O-intensive tasks. We explore the integration of K-means clustering into SQL, coupled with a near-data processing system to offload the computational burden of the K-means clustering algorithm to storage nodes. We conduct a comprehensive performance evaluation of distributed data processing applications across three processing approaches: traditional layout (baseline), optimized layout, and near-data processing. Additionally, we introduce the use of the FIO tool to simulate real-world system workloads, enabling the measurement of performance metrics such as average latency and CPU utilization. Our research is a significant advance in understanding how to optimize data processing systems to meet the demands of the modern data landscape.

Hou, Shiyue↗

DOE OSTI2022

CEAZ: Accelerating Parallel I/O Via Hardware-Algorithm Co-Designed Adaptive Lossy Compression

As supercomputers continue to grow to exa-scale, the amount of data that needs to be saved or transmitted is exploding. To this end, many previous works have studied using error-bounded lossy compressors to reduce the data size and improve the I/O performance. However, little work has been done for effectively offloading lossy compression onto FPGA-based SmartNICs to reduce the compression overhead. In this paper, we propose a hardware-algorithm co-design of efficient and adaptive lossy compressor for scientific data on FPGAs (called CEAZ) to accelerate parallel I/O. Our contribution is fourfold: (1) We propose an efficient Huffman coding approach that can adaptively update Huffman codewords online based on codewords generated offline (from a variety of representative scientific datasets). (2) We derive a theoretical analysis to support a precise control of compression ratio under an error-bounded compression mode, enabling accurate offline Huffman codewords generation. This also help us create a fixed-ratio compression mode for consistent throughput. (3) We develop an efficient compression pipeline by adopting cuSZ’s dual-quantization algorithm to our hardware use case. (4) We evaluate CEAC on five real-world datasets with both a single FPGA board and 256 nodes from Bridges2 supercomputer. Experiments show that CEAZ outperforms the second-best FPGA-based lossy compressor by 2× of throughput and 9.6× of compression ratio. It also improves MPI_File_write and MPI_Gather throughputs by up to 32.7× and 31.4×, respectively.

Zhang, Chengming↗

DOE OSTI2026

Image processing workflow yielding high contrast synchrotron nanoscale computed tomography data from Ni-YSZ electrodes

The operating lifetime of Ni-YSZ fuel electrodes used in solid oxide electrolysis cells and fuel cells (SOECs and SOFCs) is limited by Ni redistribution, one of the primary degradation mechanisms that must be overcome to extend the longevity and maximize the performance of SOECs and SOFCs. To achieve this, 3D microstructural data is needed to relate both initial performance and performance loss over time to microstructural properties and their evolution throughout operation under various conditions. However, 3D microstructure data remains relatively scarce within the literature due to multiple challenges in acquiring and analyzing such data reliably. This work presents a workflow for acquiring and processing synchrotron X-ray nanoscale computed tomography (nano-CT) data from Ni-YSZ electrodes. Parameters for each step in the nano-CT workflow are described up to the final result (a 3D reconstruction), with particular emphasis on image alignment using freely available software. Following the results of a parametric sweep of the image alignment step, high contrast, low signal-to-noise 3D nano-CT data is obtained with relatively short compute times. While the exact methods best suited to samples with different microstructural qualities, or similar Ni-YSZ nano-CT data obtained from other sources may deviate from the solution found herein, this work also generalizes the decision points and evaluation of each step to provide a starting point to adapt this workflow to other datasets.

08 HYDROGEN↗

NASA NTRS2013

Minimal Power Latch for Single-Slope ADCs

Column-parallel analog-to-digital converters (ADCs) for imagers involve simultaneous operation of many ADCs. Single-slope ADCs are well adapted to this use because of their simplicity. Each ADC contains a comparator, comparing its input signal level to an increasing reference signal (ramp). When the ramp is equal to the input, the comparator triggers a latch that captures an encoded counter value (code). Knowing the captured code, the ramp value and hence the input signal are determined. In a column-parallel ADC, each column contains only the comparator and the latches; the ramp and code generation are shared. In conventional latch or flip-flop circuits, there is an input stage that tracks the input signal, and this stage consumes switching current every time the input changes. With many columns, many bits, and high code rates, this switching current can be substantial. It will also generate noise that may corrupt the analog signals. A latch was designed that does not track the input, and consumes power only at the instant of latching the data value. The circuit consists of two S-R (set-reset) latches, gated by the comparator. One is set by high data values and the other by low data values. The latches are cross-coupled so that the first one to set blocks the other. In order that the input data not need an inversion, which would consume power, the two latches are made in complementary polarity. This requires complementary gates from the comparator, instead of complementary data values, but the comparator only triggers once per conversion, and usually has complementary outputs to begin with. An efficient CMOS (complementary metal oxide semiconductor) implementation of this circuit is shown in the figure, where C is the comparator output, D is the data (code), and Q0 and Q1 are the outputs indicating the capture of a zero or one value. The latch for Q0 has a negative-true set signal and output, and is implemented using OR-AND-INVERT logic, while the latch for Q1 uses positive- true signals and is implemented using AND-OR-INVERT logic. In this implementation, both latches are cleared when the comparator is reset. Two redundant transistors are removed from the reset side of each latch, making for a compact layout. CMOS imagers with column-parallel ADCs have demonstrated high performance for remote sensing applications. With this latch circuit, the power consumption and noise can be further reduced. This innovation can be used in CMOS imagers and very-low-power electronics

Hancock, Bruce R.↗

NASA NTRS2014

Climate Analytics as a Service

Climate science is a big data domain that is experiencing unprecedented growth. In our efforts to address the big data challenges of climate science, we are moving toward a notion of Climate Analytics-as-a-Service (CAaaS). CAaaS combines high-performance computing and data-proximal analytics with scalable data management, cloud computing virtualization, the notion of adaptive analytics, and a domain-harmonized API to improve the accessibility and usability of large collections of climate data. MERRA Analytic Services (MERRA/AS) provides an example of CAaaS. MERRA/AS enables MapReduce analytics over NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) data collection. The MERRA reanalysis integrates observational data with numerical models to produce a global temporally and spatially consistent synthesis of key climate variables. The effectiveness of MERRA/AS has been demonstrated in several applications. In our experience, CAaaS is providing the agility required to meet our customers' increasing and changing data management and data analysis needs.

big data↗

DOE OSTI2022

Approach to using 3D laser-induced breakdown spectroscopy (LIBS) data to explore the interaction of FLiNaK and FLiBe molten salts with nuclear-grade graphite

Nuclear graphite has historically been a key component of many nuclear reactor designs and has emerged as key to numerous advanced nuclear reactor design concepts. Molten salt reactors (MSRs) are one broad group of advanced reactor designs currently being pursued by industry for commercialization. Several MSR designs under consideration use graphitic materials that directly interface with a molten salt, whether it is a fuel salt, coolant salt, or both. Therefore, the interaction of graphite materials with molten salts must be understood. To gain this required understanding, a range of data is needed including porosity, strength, and composition as a function of different salt exposure parameters. In this study, a laser-induced breakdown spectroscopy (LIBS) measurement and data analysis methodology was developed to obtain spatially resolved elemental composition information for graphite samples exposed to a molten fluoride salt. Traditional univariate emission line analysis of atomic, ionic, and molecular optical emission signals was coupled via correlation analysis with spectral decomposition of the data using principal component analysis. Elemental depth profiling and elemental mapping were also performed to visualize salt–graphite interactions. LIBS was demonstrated to be useful for measuring key analytes such as fluorine and hydrogen, which are troublesome for other analysis techniques. Evidence for complex behavior was found, thereby demonstrating the usefulness of the developed approach for future systematic studies.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1980

Calculations and measurements in support of the triglycine sulfate zero gravity growth experiment

Two areas of investigation which are required for maximum utilization of the flight experiment results from the solution growth of crystals of triglycine sulfate (TGS) are addressed. The use of an ultramicroscope to characterize structural defects in the grown TGS crystals is discussed. Mie theory is applied to the light scattering expected from idealized crystal defects in order to predict the sensitivity of ultramicroscopy in the detection of small defects. Secondly, the measurement of optical properties of TGS solutions in water is discussed. This data is needed in order to interpret interferometric studies of mass transport through the TGS solution during the growth phase of the flight experiment. In particular, refractive index data is obtained for a wide range of temperatures and concentrations of TGS solutions. Absorbance measurements in the ultraviolet have also been made for the same samples.

Springer, J. M.↗

DOE OSTI2020

Opportunities for an Integrated Web-Based Workbench for Data Access and Analysis - 20244

Management of environmental issues can require integration of multiple types of data and information, conducting data analysis and interpretation, and providing data visualization for effective communications. These data elements are important for site management to support regulator interactions and provide defensibility for remedial decisions. Databases and information repositories are core elements of managing data; however, efficient data access and analysis also enable effective site management. The U.S. Department of Energy (DOE) Hanford Site is an example of a complex site with a voluminous quantity of environmental data and a need for efficient site management. Different tiers of data and information tools have been developed and deployed to address site needs. These tools are configured for ready access via the web site interfaces and meet the rigorous quality requirements for environmental site management. Evolving efforts are focused on an integrated platform to meet site environmental management needs. In this platform, users can access site information at multiple levels of detail based on their need and permissions, so that data and associated analyses are presented within the context of the site mission and the user's management or technical needs. This concept is not only applicable at individual sites like Hanford but also applicable at other sites within the DOE complex. An integrated web-based architecture that links data visualization, data analytics, and management tools can provide holistic access to large data sets, minimize complexity, and maximize interactivity and technical communication. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS2005

A Web-based Collaborative Tool for Mars Analog Data Exploration

Solving today's complex research and modeling challenges are dependent on our ability to discover, access, integrate, and share information from multiple sources. The planetary sciences community is no exception'; over the last few years, the need for data mining and exploration tools that can expedite comparative studies between Martian and terrestrial analogs sites and aid the interpretation of Mars data sets has become evident. Data sharing maximizes scientific return from studies and data sets.

Necsoiu, M.↗

DOE OSTI2022

Recommendations for Radiological Data Assessment Implementation

Since thorough verification, validation, and data quality assessment (DQA) processes may delay incident commanders and elected and appointed officials from making key decisions, the U.S. Department of Homeland Security (DHS) National Urban Security Technology Laboratory (NUSTL) tasked Pacific Northwest National Laboratory (PNNL) to develop tools and guidance for the federal, state, local, tribal, and territorial (FSLTT) responders using research, discussions with select FSLTT responders, and the experiences of subject matter experts in incident response. This report provides NUSTL with recommendations on best practices for verification, validation, and data quality assessment for the data collected by responders during a radiological or nuclear event. The purpose of this report is to inform the development of a DQA toolkit aimed at the needs of data assessors during the response to a radiological incident.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

NASA NTRS1979

Recommendations of the panels: Panel on in-flight measurements

The attenuation factor for aircraft other than the B-747 in reducing the ambient ozone concentrations which enter the cabin is obtained. The need to continue NASA Global Air Sampling Program measurements was expressed for three main purposes; testing new filters, correlation of complaints with ozone levels, and ambient ozone data. The need to continue cooperation between NASA and industry is indicated. Concern with regard to the correlation of ozone levels and complaints was given. The need to measure the variability of ozone within the aircraft cabin was investigated. The requirement for an onboard ozone monitor on all aircraft is discussed.

Rogers, J.↗

NASA NTRS1987

Comparison of two procedures for predicting rocket engine nozzle performance

Two nozzle performance prediction procedures which are based on the standardized JANNAF methodology are presented and compared for four rocket engine nozzles. The first procedure required operator intercedence to transfer data between the individual performance programs. The second procedure is more automated in that all necessary programs are collected into a single computer code, thereby eliminating the need for data reformatting. Results from both procedures show similar trends but quantitative differences. Agreement was best in the predictions of specific impulse and local skin friction coefficient. Other compared quantities include characteristic velocity, thrust coefficient, thrust decrement, boundary layer displacement thickness, momentum thickness, and heat loss rate to the wall. Effects of wall temperature profile used as an input to the programs was investigated by running three wall temperature profiles. It was found that this change greatly affected the boundary layer displacement thickness and heat loss to the wall. The other quantities, however, were not drastically affected by the wall temperature profile change.

Davidian, Kenneth J.↗

NASA NTRS1987

Comparison of two procedures for predicting rocket engine nozzle performance

Davidian, Kenneth J.↗

NASA NTRS1999

Real-Time Leaky Lamb Wave Spectrum Measurement and Its Application to NDE of Composites

Numerous analytical and theoretical studies of the behavior of leaky Lamb waves (LLW) in composite materials were documented in the literature. One of the key issues that are constraining the application of this method as a practical tool is the amount of data that needs to be acquired and the slow process that is involved with such experiments. Recently, a methodology that allows quasi real-time acquisition of LLW dispersion data was developed. At each angle of incidence the reflection spectrum is available in real time from the experimental setup and it can be used for rapid detection of the defects. This technique can be used to rapidly acquire the various plate wave modes along various angles of incidence for the characterization of the material elastic properties. The experimental method and data acquisition technique will be described in this paper. Experimental data was used to examine a series of flaws including porosity and delaminations and demonstrated the efficiency of the developed technique.

Lih, Shyh-Shiuh↗

NASA NTRSDate not supplied

Design for Manufacturing of Structures with Automated Fiber Placement via Integration of Analysis and Process Planning

Under the Design for Manufacturing (DFM) task in the NASA HiCAM program, significant process has been made towards establishing a fully automated optimization process that spans the structural analysis, design, and manufacturing process planning for Automated Fiber Placement (AFP) structures. Previous efforts in this area established the data formats and mapping processes needed to exchange data between disciplines. The software tools used in the framework are HyperX (structural optimization), CAPP (process planning), and VCP (AFP path generation). The work has culminated with automation of data exchanges and an optimization process that drives the three software toward convergence. Within this framework, HyperX is used to generate mass-optimum composite designs which are iterated with VCP and CAPP to improve manufacturability of the designs. As the ply manufacturing process is adjusted by CAPP and VCP, HyperX continually re-assesses the structural integrity of the part and makes adjustments to the laminate as needed. For example, the position of fiber steering and tow overlaps/gaps can necessitate changes to the laminate design. Once the design converges, the end result is a stack of plies that meets both structural and manufacturing requirements. This paper presents the details of the framework and demonstrations the automated process on several parts with significant double-curvature.

HiCAM↗