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At least 433 records · Page 24

Multi-terabyte image storage and distribution for NASA's Hubble Space Telescope

The modular architecture, functionality, and key components of the Hubble Space Telescope Data Archive Distribution Service (DADS) are presented. DADS functions comprise archive management, catalog management, and user interface. The distributed modular architecture utilized is made up of four subsystems, including the archive, host, catalog, and the Science Operations ground System/DADS Interface Processor. All data generated by the HST are archived in DADS on 12-in. optical disks. DADS is a permanent archive with a data capacity of 30 terabytes that can be expanded to 68 terabytes. Supplementary information and stellar observations will be instantly accessible through DADS, which can collect and archive more than 3 gigabytes per day of image and support data over the lifetime of the HST. Electronic and physical media will be accessible through 140 network connections, with a catalogue to assist in data set selection.

Weller, H. W., Jr.↗

Program for User-Friendly Management of Input and Output Data Sets

A computer program manages large, hierarchical sets of input and output (I/O) parameters (typically, sequences of alphanumeric data) involved in computational simulations in a variety of technological disciplines. This program represents sets of parameters as structures coded in object-oriented but otherwise standard American National Standards Institute C language. Each structure contains a group of I/O parameters that make sense as a unit in the simulation program with which this program is used. The addition of options and/or elements to sets of parameters amounts to the addition of new elements to data structures. By association of child data generated in response to a particular user input, a hierarchical ordering of input parameters can be achieved. Associated with child data structures are the creation and description mechanisms within the parent data structures. Child data structures can spawn further child data structures. In this program, the creation and representation of a sequence of data structures is effected by one line of code that looks for children of a sequence of structures until there are no more children to be found. A linked list of structures is created dynamically and is completely represented in the data structures themselves. Such hierarchical data presentation can guide users through otherwise complex setup procedures and it can be integrated within a variety of graphical representations.

Klimeck, Gerhard↗

Revamping Spacecraft Operational Intelligence

The EPOXI flight mission has been testing a new commercial system, Splunk, which employs data mining techniques to organize and present spacecraft telemetry data in a high-level manner. By abstracting away data-source specific details, Splunk unifies arbitrary data formats into one uniform system. This not only reduces the time and effort for retrieving relevant data, but it also increases operational visibility by allowing a spacecraft team to correlate data across many different sources. Splunk's scalable architecture coupled with its graphing modules also provide a solid toolset for generating data visualizations and building real-time applications such as browser-based telemetry displays.

Hwang, Victor↗

Recent Metallic Fuel Data Recovery in FIPD

The Metallic Fuels Irradiation and Physics Database (FIPD) [1] is an organized collection of metallic fuel test pin data (U-xPu-yZr, = 0 ~ 28; y = 2 ~ 10) and documentation available to industry. FIPD mainly contains three types of data: (1) Fuel pin fabrication data, including fuel slug diameter, fuel slug length, cladding diameter, smear density, etc. (2) Fuel pin operation conditions, including axial distributions for power, temperatures, fluences, burnup, and isotopic densities, etc. and (3) Fuel pin post-irradiation examination (PIE) data, including fission gas release and gas chemistry, profilometry, and neutron radiography, etc. The operating conditions for pins with PIE data available in FIPD span significant ranges across key parameters. The fuel peak burnup extends from less than 5% up to 20 at%. The cladding peak temperature varies from about 490°C to 660°C. Finally, the cladding peak DPA shows a wide range from less than 5 to 120. These broad ranges reflect the diverse testing conditions and operational parameters captured in the available PIE data. More detail about FIPD can be found in ref. [2]. The database development is an ongoing effort covering metallic fuel experiments from the Experimental Breeder Reactor II (EBR-II) and the Fast Flux Test Facility (FFTF). As reported in the ref. [3, 4], most of the PIE data generated during the IFR program [5] has been collected, reviewed, processed, and integrated into FIPD. The most recently added PIE data can be found in ref. [4], which shows the collection of over 95% of the PIE data by the time of this paper. The recent improvements to the database are summarized in this paper.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Stochastic Ensemble Generation for Improved Characterization of Representing Geologic Variability in a Reservoir: IBDP Case Study for SMART Initiative

This document is a poster covering the findings from activities on training data generation, specifically geologic ensemble generation. The generated geologic realizations captured the range of possible permeability distributions of the subsurface at the Illinois Basin - Decatur Project (IBDP) site, based on available well log variabilities. The percentages of reservoirs and baffles in the injection zone and a truncation of baffle permeability led to more variance in the simulations. This will be used to build forward modeling, history matching, and optimization workflows. The geologic realizations were also ranked according to dynamic measures of hydraulic diffusivity, and simulations confirm a greater contrast between the reservoir and the baffles during injection.

stochastic ensemble generation↗

Development of a computer program to generate typical measurement values for various systems on a space station

The elements of a simulation program written in Ada were developed. The program will eventually serve as a data generator of typical readings from various space station equipment involved with Communications and Tracking, and will simulate various scenarios that may arise due to equipment malfunction or failure, power failure, etc. In addition, an evaluation of the Ada language was made from the viewpoint of a FORTRAN programmer learning Ada for the first time. Various strengths and difficulties associated with the learning and use of Ada are considered.

Deacetis, Louis A.↗

The magnetic-field investigation on ISPM

The International Solar Polar Mission (ISPM) onboard instrumentation for the magnetic field experiment to establish, on the basis of in-situ observations, the heliolatitude dependence of the interplanetary magnetic field, is described. The prime output consists of vector measurements, made by two triaxial magnetometers, of the ambient magnetic field along the orbit of the spacecraft. The onboard data processor generates two data streams to be transmitted through the spacecraft telemetry. The low speed, analog data stream consists of averaged and despun vector measurements, digitized in the spacecraft analog to digital converter (ADC). The despinning algorithm used in the analog processor is described. The high speed, digital data stream consists of vector measurements digitized in the instrument ADCs, generating up to two vector samples per sec. Multiple data-path switching is used to increase system reliability and to allow cross calibration of the ADCs. On board facilities for inflight calibration are described.

Balogh, A.↗

Hydropower Capacity Factor Trends & Analytics for the United States

This data repository contains all code, input data, and data generated for Turner et al. (2024)—“Hydropower capacity factors trending down in the United States”. File descriptions: – hydro-cf-trends-inputs.zip: Full set of input data used in this study, organized for direct entry into “/data” directory of hydro-cf-trends data processing pipeline. – hydro-cf-trends.zip: Full data processing pipeline, coded using the R {targets} framework. This is a snapshot release (v1.0) of the code repository stored at https://code.ornl.gov/turnersw/hydro-cf-trends/. – hydro-cf-trends-results.zip: Provides all dam level results required to reproduce results and graphics in Turner et al. (2024). Dams are identified by the “complxID” (root of the hydropower plant ID in the Existing Hydropower Assets Database, inherited from HILARRI). Results include: • dam_CF_trends.csv: Table of long-term trends in annualized capacity factors for 610 dams and modeled annualized capacity factors for 362 modeled dams (naturalized and assimilated flows). • dam_annualized_CF_gen.csv: Annualized time series of the following variables for each of 610 hydropower dams with nameplate > 5MW – Reported nameplate capacity (MW) – Implied maximum annual generation (MWh) – Reported net generation (MWh) – Computed annual capacity factor – Modeled annual capacity factor (362 modeled plants only)

13 HYDRO ENERGY↗

An atomic cluster expansion potential for twisted multilayer graphene

Twisted multilayer graphene, characterized by its moiré patterns arising from inter-layer rotational misalignment, serves as a rich platform for exploring quantum phenomena. Machine learning interatomic potentials (MLIPs) are a promising approach to model such systems. Our work develops a method to generate training and test datasets for fitting MLIPs that capture all possible misalignments but remain small-scale to facilitate efficient data generation and parameter estimation. To achieve this, we generate configurations with periodic boundary conditions suitable for density functional theory calculations, and then introduce an internal twist and shift within those supercell structures. Using this technique, supplemented with an active learning workflow, we fit an Atomic Cluster Expansion potential for simulating twisted multilayer graphene and test it for accuracy and robustness on a range of simulation tasks.

2D materials↗

Streaming Compression of Scientific Data via Weak-SINDy

Here, in this paper, a streaming weak-SINDy algorithm is developed specifically for compressing streaming scientific data. The production of scientific data, either via simulation or experiments, is undergoing a stage of exponential growth, which makes data compression important and often necessary for storing and utilizing large scientific data sets. As opposed to classical “offline” compression algorithms that perform compression on a readily available data set, streaming compression algorithms compress data “online” while the data generated from simulation or experiments is still flowing through the system. This feature makes streaming compression algorithms well suited for scientific data compression, where storing the full data set offline is often infeasible. This work proposes a new streaming compression algorithm, streaming weak-SINDy, which takes advantage of the underlying data characteristics during compression. The streaming weak-SINDy algorithm constructs feature matrices and target vectors in the online stage via a streaming integration method in a memory efficient manner. The feature matrices and target vectors are then used in the offline stage to build a model through a regression process that aims to recover equations that govern the evolution of the data. For compressing high-dimensional streaming data, we adopt a streaming proper orthogonal decomposition (POD) process to reduce the data dimension and then use the streaming weak-SINDy algorithm to compress the temporal data of the POD expansion. We propose modifications to the streaming weak-SINDy algorithm to accommodate the dynamically updated POD basis. By combining the built model from the streaming weak-SINDy algorithm and a small amount of data samples, the full data flow could be reconstructed accurately at a low memory cost, as shown in the numerical tests.

97 MATHEMATICS AND COMPUTING↗

Multi-Scale 3D Imaging for Machine Learning Property Upscaling: Mt. Simon Sandstone Case Study

Petrographic properties of principal target reservoirs for carbon sequestration, such as the Mt. Simon Sandstone, are relevant to broad interest groups. The Mt. Simon Sandstone is a deep, saline, regionally extensive Cambrian sandstone, overlain by low permeability sealing formations, making it one of the viable geologic carbon storage reservoirs in the Midwestern US. Its thickness (exceeding 2400 ft in some localities), depth, and lateral extent, combined with high porosity and permeability make it a high-priority target of multiple ongoing geologic carbon sequestration efforts in the United States of America. The National Energy Technology Laboratory in Morgantown, West Virginia, has been engaged in characterization efforts of the Mt. Simon for over a decade, with a strong focus on Computed Tomographic data acquisition. Data generated during this period has been hitherto not accessible to the public. This archival effort focused on preservation of historical CT data and associated metadata, and facilitating their accessibility, culminating with the publication of the entire dataset on NETL’s Energy Data eXchange (EDX) and the associated Gill et. al (2024) paper.

Gill, Magdalena K.↗

Calibration of combined bending-torsion fatigue reliability data reduction

The combined bending-torsion fatigue reliability research machines are described. Three such machines are presently in operation. The calibration of these machines is presented in depth. Fatigue data generated with these machines for SAE 4340 steel grooved specimens subjected to reversed bending and steady torque loading are given. The data reduction procedure is presented. Finally, some comments are made about notch sensitivity and stress concentration as applied to combined fatigue.

Kececioglu, D.↗

Anisotropy of nickel-base superalloy single crystals

The influence of orientation on the tensile and stress rupture behavior of 52 Mar-M247 single crystals was studied. Tensile tests were performed at temperatures between 23 and 1093 C; stress rupture behavior was examined between 760 and 1038 C. The mechanical behavior of the single crystals was rationalized on the basis of the Schmid factor contours for the operative slip systems and the lattice rotations which the crystals underwent during deformation. The tensile properties correlated well with the appropriate Schmid factor contours. The stress rupture lives at lower testing temperatures were greatly influenced by the lattice rotations required to produce cross slip. A unified analysis was attained for the stress rupture life data generated for the Mar-M247 single crystals at 760 and 774 C under a stress of 724 MPa and the data reported for Mar-M200 single crystals tested at 760 C under a stress of 689 MPa. Based on this analysis, the stereographic triangle was divided into several regions which were rank ordered according to stress rupture life for this temperature regime.

Mackay, R. A.↗

Creep fatigue life prediction for engine hot section materials (isotropic)

The Hot Section Technology (HOST) program, creep fatigue life prediction for engine hot section materials (isotropic), is reviewed. The program is aimed at improving the high temperature crack initiation life prediction technology for gas turbine hot section components. Significant results include: (1) cast B1900 and wrought IN 718 selected as the base and alternative materials respectively; (2) fatigue test specimens indicated that measurable surface cracks appear early in the specimen lives, i.e., 15% of total life at 871 C and 50% of life at 538 c; (3) observed crack initiation sites are all surface initiated and are associated with either grain boundary carbides or local porosity, transgrannular cracking is observed at the initiation site for all conditions tested; and (4) an initial evaluation of two life prediction models, representative of macroscopic (Coffin-Mason) and more microscopic (damage rate) approaches, was conducted using limited data generated at 871 C and 538 C. It is found that the microscopic approach provides a more accurate regression of the data used to determine crack initiation model constants, but overpredicts the effect of strain rate on crack initiation life for the conditions tested.

Moreno, V.↗

EOS ground data systems: A description and interface overview

The Earth Observing System (EOS) is planned as a space-based measurement system, earth-science research program, and data and information system (EOSDIS). It will consist of several high data rate spacecraft with multiple earth sensing instruments which provide investigators with a thorough, longterm view of the earth's environment. Up to seven spacecraft may be supported at once, either in operational, checkout, or testing phases; and the average data rate from the EOS satellites in orbit at any one time is expected to be from 18 to 60 Mbps. Providing the data processing and flight operations support for EOS will be the EOSDIS Core System (ECS). The ECS will command and control the spacecraft; process and store the EOS data; provide access to the data for years; and support researchers. The data processing aspects of the ECS consist of a collection of Distributed Active Archive Centers (DAAC's) which perform the product generation, data archive and distribution, and information management services. Flight operations aspects will be provided by the EOS Operations Center, by instrument control centers, and by widely distributed instrument support terminals. The communications and system management aspects will be provided by the EOSDIS Science Network and the System Management Center. In addition to the EOS satellite data, other data sets from earlier earth science missions are also to be added to designated DAAC's. Other ground data systems which will provide support to EOS for acquiring, transporting, processing, and distributing the transformed spacecraft data are currently being defined or are being upgraded for the EOS era. These systems include the Space Network consisting of the Tracking and Data Relay Satellite System (TDRSS), the TDRSS Ground Terminals, and the Network Control Center as well as the night Dynamics Facility, the EOS Data and Operations System, and EOS Communications. This paper briefly describes data handling by the ECS, the support data systems, their interfaces, and their roles.

Smith, Gene↗

Electronic Health Management

Accelerated aging methodologies for electrolytic components have been designed and accelerated aging experiments have been carried out. The methodology is based on imposing electrical and/or thermal overstresses via electrical power cycling in order to mimic the real world operation behavior. Data are collected in-situ and offline in order to periodically characterize the devices' electrical performance as it ages. The data generated through these experiments are meant to provide capability for the validation of prognostic algorithms (both model-based and data-driven). Furthermore, the data allow validation of physics-based and empirical based degradation models for this type of capacitor. A first set of models and algorithms has been designed and tested on the data.

Celaya, Jose R.↗

Unbinned extraction of $γ$ from $B\to DK$ with normalizing flows

We introduce an unbinned method for extracting the CKM angle $γ$ from the decay chain $B^\pm \to (D \to K_S π^+ π^-) K^\pm$ using normalizing flows (NFs). The NFs, trained on $D$ decay data, learn a faithful continuous representation of the amplitude and strong phase variation over the $D\to K_Sπ^+π^-$ Dalitz plot whose fidelity improves with increased data sample sizes. With this input, the $B$ decay data can be used to extract the parameters $r_B$, $δ_B$, and $γ$. We test the method on Monte Carlo generated data, where it successfully recovers the injected value of $γ$ within uncertainties. The present implementation propagates statistical uncertainties from finite training data via an ensemble of independently trained flows, and does not attempt to capture the effects of systematic experimental errors. We explore two versions of the method that differ in how the trigonometric constraint on phase variation is encoded, and comment on the possible extension to Bayesian NFs, which would provide direct uncertainty estimates on the learned densities without requiring ensemble training.

Grossman, Yuval [Cornell U., LEPP]↗

Ultraviolet corona detection sensor study

The feasibility of detecting electrical corona discharge phenomena in a space simulation chamber via emission of ultraviolet light was evaluated. A corona simulator, with a hemispherically capped point to plane electrode geometry, was used to generate corona glows over a wide range of pressure, voltage, current, electrode gap length and electrode point radius. Several ultraviolet detectors, including a copper cathode gas discharge tube and a UV enhanced silicon photodiode detector, were evaluated in the course of the spectral intensity measurements. The performance of both silicon target vidicons and silicon intensified target vidicons was evaluated analytically using the data generated by the spectroradiometer scans and the performance data supplied by the manufacturers.

Schmitt, R. J.↗