NDMAS Overview
Overview of the Nuclear Data Management and Analysis System detailed as: Overview of NDMAS System, NDMAS NQA-1 process, Data in NDMAS, and Future work and new additions.
11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
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Results for “process data”
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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DUNE Software and Computing Challenges
The DUNE experiment will begin running in the late 2020's. The goals of the experiment include 1) studying neutrino oscillations using a beam of neutrinos from Fermilab in Illinois to the Sanford Underground Research Facility, 2) studying astrophysical neutrino sources and rare processes and 3) understanding the physics of neutrino interactions in matter. The DUNE Far Detector, consisting of four 17 kt LArTPC modules, will produce "events" rang-ing in size from 6 GBs to more than 100 TBs, posing unique challenges for DUNE software and computing. The data processing algorithms, particularly for raw data, drive the requirements for the future DUNE software framework documented here.
97 MATHEMATICS AND COMPUTING↗
Data-driven simultaneous process optimization and adsorbent selection for vacuum pressure swing adsorption
Technologies for post-combustion carbon capture are essential for the reduction of greenhouse gas emissions to the atmosphere. However, they are still associated with high costs and energy consumption. Intensified processes for carbon capture have the potential to overcome these challenges due to their higher efficiency, lower capital cost, and increased operational flexibility. Here, this work investigates simultaneous optimization of process conditions and adsorbent selection for a modular Vacuum Pressure-Swing Adsorption system designed for CO 2 capture. Both surrogate-based Nonlinear Programming and Mixed-Integer Nonlinear Programming approaches are applied and compared in terms of computational efficiency and solution accuracy. Moreover, process performance results are examined by applying several data analytics techniques to gain insights into the material-process correlations. Data-driven classifiers and neural networks can accurately predict whether a material is likely to satisfy purity, recovery, and energy constraints when operated at optimal process conditions.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
The integrated miniaturized electrostatic analyzer: A space plasma environment sensor
The integrated Miniaturized Electrostatic Analyzer (iMESA) was a satellite-based ionospheric sensor that operated on NASA’s Space Test Program Satellite (STPSat-3) from December 2013 to July 2019. The instrument’s scientific objective was to (1) measure the plasma density in low Earth orbit, (2) measure the plasma temperature in low Earth orbit, and (3) quantify the spacecraft potential with respect to the ambient plasma potential in the ionosphere. iMESA sampled the ionosphere every 10 s by measuring the ion current density through the ESA as a result of the motion of the spacecraft through the plasma. Current density spectra were transmitted to the ground where they were post-processed into ion density spectra and then analyzed numerically to determine the ion density, ion temperature, and spacecraft potential. This article discusses the instrument design and simulation, the determination of a geometric factor, and data processing procedures and evaluates the final data product with regard to the mission success criteria. Here, the ion density and ion temperature captured by the iMESA instrument are on the same order and range as the values predicted in the literature. The spacecraft potential was also quantified. The conclusion after the evaluation of the instrument’s data product is that the scientific mission is successful on all three points.
47 OTHER INSTRUMENTATION↗
Characterization of Delayed-Particle Emission Signatures for Pyroprocessing, Part 1: Fuel Assembly
An initial study was conducted with nondestructive assay analysis using the MCNP6 Monte Carlo radiation-transport code to calculate delayed-neutron and delayed- gamma emission signature monitors to characterize burnup and isotopic composition for pyroprocessing. The study consists of five parts. In Part 1, a generic Westinghouse fuel assembly model was modified to create models with 3% and 5% 235 U enrichments, 20, 30, 40, and 50 GWd/MTU burnups, and 3-, 5-, 10-, 20-, and 30-year cooling times. MCNP6 was used to create detail-rich delayed-particle source terms for fuel assembly. Delayed-gamma activity ratios were then developed for conventional 134 Cs/ 137 Cs, 134 Cs/ 154 Eu, and 154 Eu/ 137 Cs markers as a function of burnup and of actinide mass for elemental uranium, neptunium, plutonium, americium, and curium. In addition, data mining using photon tally data was employed to discover potential new delayed-gamma activity ratios. The data mining effort was streamlined by the creation and use of several utility codes to extract and process data. The study confirms behavior for burnup dependence of 134 Cs/ 137 Cs, 134 Cs/ 154 Eu, and 154 Eu/ 137 Cs markers. A process for the discovery of potential new delayed-gamma markers has been developed, and results are presented. The actinide and nonactinide inventories for the fuel assembly models are used as source materials for the electrorefining models. Parts 2–5 contain analysis of a pyrochemical separations model that includes an MCNP6 mockup of the INL Mark IV electrorefiner (see companion documents). Part 2 focuses on delayed-particle emissions from the electrorefiner with loaded fuel dissolution baskets before electrorefining. Part 3 investigates delayed-particle emissions from the electrorefiner following electrorefining. Part 4 presents delayed-particle emissions from other pyroprocessing units that contain material developed by the electrorefining process in Part 3. Part 5 parallels Part 4, except for a 10 wt% plutonium reduction.
98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
IOTA : integration optimization, triage and analysis tool for the processing of XFEL diffraction images
Serial femtosecond crystallography (SFX) uses an X-ray free-electron laser to extract diffraction data from crystals not amenable to conventional X-ray light sources owing to their small size or radiation sensitivity. However, a limitation of SFX is the high variability of the diffraction images that are obtained. As a result, it is often difficult to determine optimal indexing and integration parameters for the individual diffraction images. Presented here is a software package, called IOTA , which uses a grid-search technique to determine optimal spot-finding parameters that can in turn affect the success of indexing and the quality of integration on an image-by-image basis. Integration results can be filtered using a priori information about the Bravais lattice and unit-cell dimensions and analyzed for unit-cell isomorphism, facilitating an improvement in subsequent data-processing steps.
Chemistry↗
Retrieving Historical Electrorefining Data
Pyrochemical Operations began at Los Alamos National Laboratory (LANL) during 1962 (1). Electrorefining (ER) has been implemented as a routine process since the 1980’s. The process data that went through the ER operation was recorded but had never been logged in an online database. Without a database new staff members are hindered in their work by the lack of information. To combat the issue a database in Access was created to collect the historical data. The years from 2000 onward were entered and queries were created to analyze trends. These trends will aid engineering and operations staff to reach optimal performance for the startup of the new lines.
38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
Metabolomic data streaming for biology-dependent data acquisition
During the last 10 years, metabolomics has emerged as a powerful technology to interrogate cellular biochemistry at the global level. Although much of the success has been driven by advances in mass spectrometry, developments in bioinformatic resources for data processing have been equally important. Additionally, the widely used metabolomic software XCMS, in particular, has undergone substantial improvements since its first introduction in 2005 (ref. 1). In addition to improved algorithms for peak picking, retention time alignment and data visualization, XCMS has transitioned from a command-line interface requiring expertise with the R programming language, to a web-based platform with a graphical user interface2. This web-based platform, which we call XCMS Online, enables thousands of users to upload their metabolomic data and perform cloud-based processing.
59 BASIC BIOLOGICAL SCIENCES↗
Geophysical and Environmental Monitoring Data, Lower Watershed, Teller Road Mile Marker 27, Seward Peninsula, Alaska, 2017-2019
This data set contains geophysical and environmental monitoring data acquired between September 2017 and 2019 at the lower Teller watershed, Seward Peninsula, Alaska. Geophysical data comprises processed resistivity data, acquired daily between Spring and Fall of 2018 and 2019, and a baseline measurement of Fall 2017. The environmental monitoring data comprises depth resolved, distributed soil moisture and soil temperature data. These measurements were obtained used Decagon 5TE sensors placed at 0.1 m, 0.2 m , 0.3 m, and 0.4 m depth. In addition, temperature data at 0.5 m, 1.0 m, and 1.5 m were acquired using Hobo temperature sensors. Data were collected to improve our understanding of the hydrological response of discontinuous permafrost systems, in particular focusing on multi-annual dynamics and short term disturbances, such as snowmelt or precipitation events. The electrical resistivity tomography (ERT) monitoring data are included as processed resistivity models, with model cells x dimension equal to the distance along the profile, and model z dimension being elevation. The start and end point of the transect are (UTM Zone 3N): E 454881.66 m, N 7178949.45 m, and E 454772.60, N 7178885.81. Locations of the soil moisture and temperature sensors are provided in the data package. This dataset is discussed in detail in the Uhlemann, S. et al 2021 paper listed in the references. This dataset includes one *.pdf user guide and 315 *.csv data files included within four zipped files.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).
54 ENVIRONMENTAL SCIENCES↗
TEAMER: Twin Ocean Power Wave Energy Converter Comprehensive Overview
These files collectively provide a comprehensive overview of the testing process, data analysis, and validation for the Twin Ocean Power device tested at the O.H. Hinsdale Wave Research Laboratory, supported by TEAMER funding. This resource includes an overview of power results for a series of 7 trials. The files included in this comprehensive overview include a comprehensive log sheet for each trial, a summary of all trials, and processing scripts for the raw data. It includes all raw data in .tsv and MATLAB compatible formats, an average power chart, angular velocity charts for each trial, trial metrics, and power output files. This resource includes images of the Twin Ocean Power Wave Energy Converter device components and movement during testing and video recordings of each trial.
16 TIDAL AND WAVE POWER↗
ISRM Suggested Method: Determining Deformation and Failure Characteristics of Rocks Subjected to True Triaxial Compression
The purpose of this ISRM Suggested Method is to introduce a guideline on determining deformation and failure characteristics of rocks subjected to true triaxial compression on different stress path. Here, the true triaxial testing apparatus was reviewed by means of the function and engineering application. Some key techniques, such as stress and strain measurements, and reduction of end effect between specimen and metal platens, preventing metal platens interference, were stated and suggested in detail. Methodology of specimen processing, specimen shape, and testing procedure are characterized. There is an explanation of the experimental data processing on stress–strain curves, strength, and fracture mode.
42 ENGINEERING↗
Performance of Julia for High Energy Physics Analyses
We argue that the Julia programming language is a compelling alternative to currently more common implementations in Python and C++ for common data analysis workflows in high energy physics. We compare the speed of implementations of different workflows in Julia with those in Python and C++. Furthermore, our studies show that the Julia implementations are competitive for tasks that are dominated by computational load rather than data access. For work that is dominated by data access, we demonstrate an application with concurrent file reading and parallel data processing.
97 MATHEMATICS AND COMPUTING↗
Nanoscale Probing of Electrical Memory Effects in van der Waals Layered PdSe 2
Tunable electronic materials that can be switched between different impedance states are fundamental to the hardware elements for neuromorphic computing architectures. This “brain-like” computing paradigm uses highly paralleled and colocated data processing, leading to greatly improved energy efficiency and performance compared to traditional architectures in which data have to be frequently transferred between processor and memory. In this work, we use scanning microwave impedance microscopy for nanoscale electrical and electronic characterization of two-dimensional layered semiconductor PdSe 2 to probe neuromorphic properties. The local resolution of tens of nanometers reveals significant differences in electronic behavior between and within PdSe 2 nanosheets (NSs). In particular, we detected both n-type and p-type behaviors, although previous reports only point to ambipolar n-type dominating characteristics. Nanoscale capacitance–voltage curves and subsequent calculation of characteristic maps revealed a hysteretic behavior originating from the creation and erasure of Se vacancies as well as the switching of defect charge states. In addition, stacks consisting of two NSs show enhanced resistive and capacitive switching, which is attributed to trapped charge carriers at the interfaces between the stacked NSs. Stacking n- and p-type NSs results in a combined behavior that allows one to tune electrical characteristics. In conclusion, as local inhomogeneities of electrical and electronic behavior can have a significant impact on the overall device performance, the demonstrated nanoscale characterization and analysis will be applicable to a wide range of semiconducting materials.
2D material↗
BeyondPlanck: V. Minimal ADC Corrections for Planck LFI
We describe the correction procedure for Analog-to-Digital Converter (ADC) differential non-linearities (DNL) adopted in the Bayesian end-to-end BEYONDPLANCK analysis framework. This method is nearly identical to that developed for the official Planck Low Frequency Instrument (LFI) Data Processing Center (DPC) analysis, and relies on the binned rms noise profile of each detector data stream. However, rather than building the correction profile directly from the raw rms profile, we first fit a Gaussian to each significant ADC-induced rms decrement, and then derive the corresponding correction model from this smooth model. The main advantage of this approach is that only samples which are significantly affected by ADC DNLs are corrected, as opposed to the DPC approach in which the correction is applied to all samples, filtering out signals not associated with ADC DNLs. The new corrections are only applied to data for which there is a clear detection of the non-linearities, and for which they perform at least comparably with the DPC corrections. Out of a total of 88 LFI data streams (sky and reference load for each of the 44 detectors) we apply the new minimal ADC corrections in 25 cases, and maintain the DPC corrections in 8 cases. All these corrections are applied to 44 or 70 GHz channels, while, as in previous analyses, none of the 30 GHz ADCs show significant evidence of non-linearity. By comparing the BEYONDPLANCK and DPC ADC correction methods, we estimate that the residual ADC uncertainty is about two orders of magnitude below the total noise of both the 44 and 70 GHz channels, and their impact on current cosmological parameter estimation is small. However, we also show that non-idealities in the ADC corrections can generate sharp stripes in the final frequency maps, and these could be important for future joint analyses with the Planck High Frequency Instrument (HFI), Wilkinson Microwave Anisotropy Probe (WMAP), or other datasets. We therefore conclude that, although the existing corrections are adequate for LFI-based cosmological parameter analysis, further work on LFI ADC corrections is still warranted.
79 ASTRONOMY AND ASTROPHYSICS↗
Advances in utilizing event based data structures for neutron scattering experiments
This article strives to expand on existing work to demonstrate advancements in data processing made available using event mode measurements. Most spallation neutron sources in the world have data acquisition systems that provide event recording. The new science that is enabled by utilizing event mode has only begun to be explored. In the past, these studies were difficult to perform because histograms forced dealing with either large chunks of time or a large number of files. With event based data collection, data can be explored and rebinned long after the measurement has completed. This article will review some of the principles of event data and how the method opens up new possibilities for in situ measurements, highlighting techniques that can be used to explore changes in the data. We also demonstrate the statistical basis for determining data quality and address the challenge of determining how long to measure mid-measurement. Lastly, we demonstrate a model independent method of grouping data via hierarchical clustering methods that can be used to improve calibration, reduction, and data exploration.
74 ATOMIC AND MOLECULAR PHYSICS↗
Review of Enabling Technologies to Facilitate Secure Compute Customization
High performance computing environments are often used for a wide variety of workloads ranging from simulation, data transformation and analysis, and complex workflows to name just a few. These systems may process data for a variety of users, often requiring strong separation between job allocations. There are many challenges to establishing these secure enclaves within the shared infrastructure of high-performance computing (HPC) environments. The isolation mechanisms in the system software are the basic building blocks for enabling secure compute enclaves. There are a variety of approaches and the focus of this report is to review the different virtualization technologies that facilitate the creation of secure compute enclaves. The report reviews current operating system (OS) protection mechanisms and modern virtualization technologies to better understand the performance/isolation properties. We also examine the feasibility of running ``virtualized'' computing resources as non-privileged users, and providing controlled administrative permissions for standard users running within a virtualized context. Our examination includes technologies such as Linux containers (LXC [32], Docker [15]) and full virtualization (KVM [26], Xen [5]). We categorize these different approaches to virtualization into two broad groups: OS-level virtualization and system-level virtualization. The OS-level virtualization uses containers to allow a single OS kernel to be partitioned to create Virtual Environments (VE), e.g., LXC. The resources within the host's kernel are only virtualized in the sense of separate namespaces. In contrast, system-level virtualization uses hypervisors to manage multiple OS kernels and virtualize the physical resources (hardware) to create Virtual Machines (VM), e.g., Xen, KVM. This terminology of VE and VM, detailed in Section 2, is used throughout the report to distinguish between the two different approaches to providing virtualized execution environments. As part of our technology review we analyzed several current virtualization solutions to assess their vulnerabilities. This included a review of common vulnerabilities and exposures (CVEs) for Xen, KVM, LXC and Docker to gauge their susceptibility to different attacks. The complete details are provided in Section 5 on page 33. Based on this review we concluded that system-level virtualization solutions have many more vulnerabilities than OS level virtualization solutions. As such, security mechanisms like sVirt (Section 3.3) should be considered when using system-level virtualization solutions in order to protect the host against exploits. The majority of vulnerabilities related to KVM, LXC, and Docker are in specific regions of the system. Therefore, future "zero day attacks" are likely to be in the same regions, which suggests that protecting these areas can simplify the protection of the host and maintain the isolation between users. The evaluations of virtualization technologies done thus far are discussed in Section 4. This includes experiments with 'user' namespaces in VEs, which provides the ability to isolate user privileges and allow a user to run with different UIDs within the container while mapping them to non-privileged UIDs in the host. We have identified Linux namespaces as a promising mechanism to isolate shared resources, while maintaining good performance. In Section 4.1 we describe our tests with LXC as a non-root user and leveraging namespaces to control UID/GID mappings and support controlled sharing of parallel file-systems. We highlight several of these namespace capabilities in Section 6.2.3. The other evaluations that were performed during this initial phase of work provide baseline performance data for comparing VEs and VMs to purely native execution. In Section 4.2 we performed tests using the High-Performance Computing Conjugate Gradient (HPCCG) benchmark to establish baseline performance for a scientific application when run on the Native (host) machine in contrast with execution under Docker and KVM. Our tests verified prior studies showing roughly 2-4% overheads in application execution time & MFlops when running in hypervisor-base environments (VMs) as compared to near native performance with VEs. For more details, see Figures 4.5 (page 28), 4.6 (page 28), and 4.7 (page 29). Additionally, in Section 4.3 we include network measurements for TCP bandwidth performance over the 10GigE interface in our testbed. The Native and Docker based tests achieved >= ~9Gbits/sec, while the KVM configuration only achieved 2.5Gbits/sec (Table 4.6 on page 32). This may be a configuration issue with our KVM installation, and is a point for further testing as we refine the network settings in the testbed. The initial network tests were done using a bridged networking configuration. The report outline is as follows: - Section 1 introduces the report and clarifies the scope of the proj...
Aderholdt, Ferrol↗
Unlimited Release of non-proprietary experimental data from the Scaled Wind Farm Technology (SWiFT) Facility
Each year Wind Energy Technologies Dept. 08821 submits a memo through the Sandia National Labs Review and Approval (R&A) system to facilitate the release of the Scaled Wind Farm Technology (SWiFT) Facility raw logged data. This release of data explicitly does not cover specialized instruments, or guest researcher instruments (i.e. SpiDAR, SpinnerLidar), nor processed data.
17 WIND ENERGY↗
Watchmen 3.0.0 Users Guide: Revision 6
Watchmen is a research software application developed by Pacific Northwest National Laboratory (PNNL) that incorporates the scientific and operational expertise for reviewing data from treaty monitoring radionuclide stations. The radionuclide stations are part of the International Monitoring System (IMS), a worldwide network to monitor for nuclear explosions. The data the IMS produces are critical to determine if a radionuclide release event is from a nuclear explosion. Stations deliver their measurements and system status to the International Data Centre (IDC), which forwards it via email to all subscribers. Watchmen is capable of processing data from several radioxenon station types.
97 MATHEMATICS AND COMPUTING↗