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At least 163 records · Page 9

Jas4pp — A data-analysis framework for physics and detector studies

This paper describes the Jas4pp framework for exploring physics cases and for detector-performance studies of future particle collision experiments. Jas4pp is a multi-platform Java program for numeric calculations, scientific visualization in 2D and 3D, storing data in various file formats and displaying collision events and detector geometries. It also includes complex data-analysis algorithms for function minimization, regression analysis, event reconstruction (such as jet reconstruction), limit settings and other libraries widely used in particle physics. The framework can be used with several scripting languages, such as Python/Jython, Groovy and JShell. Several benchmark tests discussed in the paper illustrate significant improvements in the performance of the Groovy and JShell scripting languages compared to the standard Python implementation in C. Furthermore, the improvements for numeric computations in Java are attributed to recent enhancements in the Java Virtual Machine.

97 MATHEMATICS AND COMPUTING↗

Data Analysis for DNA Stable Isotope Probing Experiments Using Multiple Window High-Resolution SIP

DNA stable isotope probing (DNA-SIP) allows for the identification of microbes that assimilate isotopically labeled substrates into DNA. Here we describe the analysis of sequencing data using the multiple window high-resolution DNA-SIP method (MW-HR-SIP). MW-HR-SIP has improved accuracy over other methods and is easily implemented on the statistical platform R. Here, we also discuss key experimental parameters to consider when designing DNA-SIP experiments and how these parameters affect accuracy of analysis.

59 BASIC BIOLOGICAL SCIENCES↗

py4DSTEM: A Software Package for Four-Dimensional Scanning Transmission Electron Microscopy Data Analysis

Scanning transmission electron microscopy (STEM) allows for imaging, diffraction, and spectroscopy of materials on length scales ranging from microns to atoms. By using a high-speed, direct electron detector, it is now possible to record a full two-dimensional (2D) image of the diffracted electron beam at each probe position, typically a 2D grid of probe positions. These 4D-STEM datasets are rich in information, including signatures of the local structure, orientation, deformation, electromagnetic fields, and other sample-dependent properties. However, extracting this information requires complex analysis pipelines that include data wrangling, calibration, analysis, and visualization, all while maintaining robustness against imaging distortions and artifacts. In this paper, we present py4DSTEM, an analysis toolkit for measuring material properties from 4D-STEM datasets, written in the Python language and released with an open-source license. We describe the algorithmic steps for dataset calibration and various 4D-STEM property measurements in detail and present results from several experimental datasets. We also implement a simple and universal file format appropriate for electron microscopy data in py4DSTEM, which uses the open-source HDF5 standard. We hope this tool will benefit the research community and help improve the standards for data and computational methods in electron microscopy, and we invite the community to contribute to this ongoing project.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Active multi-mode data analysis to improve fault diagnosis in AHUs

Faults in heating, ventilation and air conditioning systems can lead to increased energy consumption, occupant comfort issues, and reduced equipment lifetime. Commercial fault detection and diagnosis (FDD) tools has been increasingly deployed in U.S. commercial buildings. While they are helping to achieve energy efficiency and operational reliability, there remain gaps in their fault diagnostic capabilities. The diagnostic results often contain multiple distinct candidate root causes (CRCs) or offer no insight into CRCs. This study developed a novel active rule-based multi-mode data analysis method to enhance diagnostic resolution by applying proven rule sets and additional new rules to data from multiple known operational modes. The proposed method was demonstrated using enhanced air handling unit performance assessment rule sets and validated with the simulated data of two air handling units. New metrics, namely, reduced number of CRCs and improvement ratio, were developed to quantify the improvement of fault diagnostic resolution. The validation results showed that the proposed method effectively reduced the number of CRCs in contrast to analyzing data solely for a single mode of operation. It achieved a median improvement ratio of 80% in 19 test cases.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Ambient Mass Spectrometer Data Analysis Pipeline Development

The ability to detect chemical + isotopic information for trace actinide samples is currently not available at SRNL. This negatively impacts our ability to explore, develop, and characterize signatures of nonproliferation interest. Paper spray ionization mass spectrometry (PSIMS) is a novel ambient mass spectrometry technique that promises to rectify this issue. PSI-MS produces copious amounts of data; thus, a data analysis pipeline is necessary to quickly extract meaningful results.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Visualization and Data Analysis for High-Performance Computing

This is a set of slides from a guest lecture for a class at the University of Texas, El Paso on visualization and data analysis for high-performance computing. The topics covered are the following: trends in high-performance computing; scientific visualization, such as OpenGL, ray tracing and volume rendering, VTK, and ParaView; data science at scale, such as in-situ visualization, image databases, distributed memory parallelism, shared memory parallelism, VTK-m, "big data", and then an analysis example.

97 MATHEMATICS AND COMPUTING↗

Federal Metering Data Analysis Needs and Existing Tools

Agencies have been working to improve their metering data collection, management, and analysis efforts over the last decade (since EPAct 2005) and will continue to address these challenges as new requirements and data needs come into place. Unfortunately there is no “one-size-fits-all” solution. As agencies continue to expand their capabilities to use metered consumption data to reducing resource use and improve operations, the hope is that shared knowledge will empower others to follow suit. This paper discusses the Federal metering data analysis needs and some existing tools.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A Study of the Trade-off Between Reducing Precision and Reducing Resolution for Data Analysis and Visualization

There presently exist two dominant strategies to reduce data sizes in analysis and visualization: reducing the precision of the data, e.g., through quantization, or reducing its resolution, e.g., by subsampling. Both have advantages and disadvantages and both face fundamental limits at which the reduced information ceases to be useful. The paper explores the additional gains that could be achieved by combining both strategies. In particular, we present a common framework that allows us to study the trade-off in reducing precision and/or resolution in a principled manner. We represent data reduction schemes as progressive streams of bits and study how various bit orderings such as by resolution, by precision, etc., impact the resulting approximation error across a variety of data sets as well as analysis tasks. Additionally, we compute streams that are optimized for different tasks to serve as lower bounds on the achievable error. Scientific data management systems can use the results proposed in this paper as guidance on how to store and stream data to make efficient use of the limited storage and bandwidth in practice.

97 MATHEMATICS AND COMPUTING↗

UNESE Data Analysis - Disko Elm Gas Transport Characteristics (NA-22 Quarterly Report)

Two research papers describing gas transport studies in subsurface containment environments appropriate for underground nuclear explosions were revised and accepted for publication in the peer-reviewed journals, Nature – Scientific Reports and Journal of Geophysical Research. The Nature – Scientific Reports paper is a primary deliverable and describes the gas-transport experiment performed in P Tunnel (NNSS) and 1) subsequent analysis of field data as part of the UNESE program. The Journal of Geophysical Research paper describes an experiment, supported mainly by DARPA and led by researchers at Weston Geophysical and New Mexico Tech., with 2) analyses supported by this project to evaluate the ability of SF6 gas tracer to track xenon gas migration under conditions related to a previous UNESE experiment. Two new tasks consider 3) evaluation of detonation heating and multiphase flow on arrival of xenon at the surface and 4) the impact of surface or Langmuir adsorption of gases being transported through pores and along fractures.

58 GEOSCIENCES↗

HDG-1 Fiber Bragg grating data analysis

The main goal of the High dose graphite 1 Advanced test reactor experiment was to study nuclear grade graphite at high fluences. Additional supplementary optical fiber instrumentation was added to this long duration experiment for instrumentation development purposes. The supplementary instrumentation consisted of two pure silica core, fluorine doped cladding optical fibers each etched with 9 fiber Bragg gratings, one fiber being heat treated for 9 hours at 750 C and 16 hours at 750 C, the other being heat treated for 24 hours at 550 C and 48 hours at 650 C. Fiber Bragg gratings are known to have issues of measurement drift when in high temperature and high radiation environments like what is encountered in the Advanced test reactor. At the culmination of this experiment, the optical fibers saw ~1.3E21 n/cm2 total fluence, which is at the highest fluences that fiber Bragg gratings have been studied to date. Reported here is the analysis of this data including radiation induced shift and changes in sensitivity.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

Near Real-time Data Analysis of Core-collapse Supernova Simulations with Bellerophon

We present an overview of a software system, Bellerophon, built to support a production-level HPC application called CHIMERA, which simulates core-collapse supernova events at the petascale. Developed over the last four years, Bellerophon enables CHIMERA's geographically dispersed team of collaborators to perform data analysis in near real-time. Its n-tier architecture provides an encapsulated, end-to-end software solution that enables the CHIMERA team to quickly and easily access highly customizable animated and static views of results from anywhere in the world via a web- deliverable, cross-platform desktop application. In addition, Bellerophon addresses software engineering tasks for the CHIMERA team by providing an automated mechanism for performing regression testing on a variety of supercomputing platforms. Elements of the team's workflow management needs are met with software tools that dynamically generate code repository statistics, access important online resources, and monitor the current status of several supercomputing resources.

97 MATHEMATICS AND COMPUTING↗

Probabilistic Error Bounds for Low-Rank Tensor Decompositions Used in Large-Scale Data Analysis Applications (LDRD Final Report)

This report documents a research project on analyzing low-rank tensor models for data analysis that took place at Sandia National Laboratories from October 2023–September 2025. The focus of this work was to extend theoretical frameworks from statistics and probability theory for use with models for scalar, vector, and matrix data to models with tensor, or general multi-dimensional array, data. Through this work, we have provided a new set of tools for bounding errors on low-rank tensor models of both complete and sampled data. The remainder of this report is organized as follows. In Section 1, we describe the proposed work at the start of the project. Section 2 describes the research advances made as part of the project. Other research contributions in the form of conference presentations and software development is provided in Section 3. Workforce development at Sandia and Florida Atlantic University (via a subcontract on this project) is provided in Section 4.

97 MATHEMATICS AND COMPUTING↗

Nuclear Smuggling Detection and Deterrence (FY 2018 Data Analysis Annual Report)

The National Nuclear Security Administration’s Office of Nuclear Smuggling Detection and Deterrence (NSDD) has facilitated the installation of more than 3,728 radiation portal monitors (RPMs) at 660 sites in 63 countries. This collection of RPMs represents the world’s largest network of radiation detectors and provides one element of the defense-in-depth approach that supports the Global Nuclear Detection Architecture. These systems support NSDD’s mission to build partner country capability to deter, detect, and interdict the illicit transport of radiological and fissile material through strategic points of entry and exit at seaports, airports, and border crossings.NSDD works collaboratively with partner countries and international organizations to optimize the operation of these RPMs. The large amount of data provided by NSDD partner countries (summarized in the banner to the right) highlights the close cooperation and partnerships NSDD has built with 63 countries around the world. Thirty-two of these countries shared at least some RPM-related data with NSDD in fiscal year (FY) 2018. This significant level of data sharing is a key element that distinguishes the NSDD office as unique among nuclear nonproliferation programs and initiatives: NSDD can provide specific, objective, data-driven decisions and support for sustaining the radiation detection systems it helped deploy. This data analysis report summarizes and aggregates the RPM data provided to the NSDD office for analysis and review in FY 2018.The data can be used to describe RPM performance and characterize the wide diversity of NSDD deployment sites. For example, NSDD deploys detector systems across sites with natural background radiation levels that can vary by a factor of up to nine from site to site. Some RPM lanes have few occupancies, whereas others have up to approximately 8,000 occupancies per day, and the different types of cargo traveling through a site can result in site-wide alarm rates that range from near 0% at some sites to above 3% at others. Based on the data received, the global average uptime for NSDD RPMs was 97% for FY 2018. NSDD takes all these factors into account in making recommendations to partner countries on how to most effectively manage and maintain site operations. NSDD utilizes reports and other information products created by ORNL Radiation Inspection Systems Team (RIST) data analysts to efficiently allocate the resources needed to detect and ultimately interdict illicit nuclear and radiological material.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

THE GREEN BANK TELESCOPE 350 MHz DRIFT-SCAN SURVEY II: DATA ANALYSIS AND THE TIMING OF 10 NEW PULSARS, INCLUDING A RELATIVISTIC BINARY

We have completed a 350 MHz Drift-scan Survey using the Robert C. Byrd Green Bank Telescope with the goal of finding new radio pulsars, especially millisecond pulsars that can be timed to high precision. This survey covered {approx}10,300 deg{sup 2} and all of the data have now been fully processed. We have discovered a total of 31 new pulsars, 7 of which are recycled pulsars. A companion paper by Boyles et al. describes the survey strategy, sky coverage, and instrumental setup, and presents timing solutions for the first 13 pulsars. Here we describe the data analysis pipeline, survey sensitivity, and follow-up observations of new pulsars, and present timing solutions for 10 other pulsars. We highlight several sources-two interesting nulling pulsars, an isolated millisecond pulsar with a measurement of proper motion, and a partially recycled pulsar, PSR J0348+0432, which has a white dwarf companion in a relativistic orbit. PSR J0348+0432 will enable unprecedented tests of theories of gravity.

79 ASTRONOMY AND ASTROPHYSICS↗

Deep Data Analysis of Conductive Phenomena on Complex Oxide Interfaces: Physics from Data Mining

Spatial variability of electronic transport in BiFeO3-CoFe2O4 (BFO-CFO) self-assembled heterostructures is explored using spatially resolved first order reversal curve (FORC) current voltage (IV) mapping. Multivariate statistical analysis of FORC-IV data classifies statistically significant behaviors and maps characteristic responses spatially. In particular, regions of grain, matrix, and grain boundary responses are clearly identified. K-means and Bayesian demixing analysis suggests the characteristic response be separated into four components, with hysteretic type behavior localized at the BFO-CFO tubular interfaces. The conditions under which Bayesian components allow direct physical interpretation are explored, and transport mechanisms at the grain boundaries and individual phases are analyzed. This approach conjoins multivariate statistical analysis with physics-based interpretation, actualizing a robust, universal, data driven approach to problem solving, which can be applied to exploration of local transport and other functional phenomena in other spatially inhomogeneous systems.

big data↗

Training package 1 for slitting data analysis

This document and accompanying files are intended as a first training package on how to analyze slitting data. The end goal is to have Idaho National Laboratory (INL) personnel trained to analyze future slitting data taken in the INL Hot Cell on clad, Low-Enriched Uranium (LEU) fuel plates. This first data package will cover data analysis for a monolithic material (as compared to a layered material like the clad fuel plates). The additional issues for layered specimens will be covered in a future training package.

42 ENGINEERING↗