Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “active 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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Graph-theoretical KMC Framework for Calculating Effective Diffusivity in TPBAR Components: Effective Diffusivity of Tritium in α-Zr Grain Boundaries

We report the development of a computer simulation tool based on the Graph-theoretical kinetic Monte Carlo (GT-KMC) approach that can be used to simulate diffusion and derive effective diffusivity of species in complex structures of TPBAR components. The GT-KMC framework was implemented in AKSOME, an on-lattice self-learning kinetic Monte Carlo tool developed at PNNL and was previously used to study solute diffusion in metal alloys. This newly developed tool will be helpful in simulating atom diffusion and extracting their effective diffusivities in grain boundaries and interfaces in various TPBAR components. Once benchmarked, the tool will be used to simulate the diffusion of tritium (hydrogen) along grain boundaries in α-Zr using the activation energy barrier data previously obtained from Density Functional Theory calculations.

36 MATERIALS SCIENCE↗
DOE OSTI2025

FracML: A Machine Learning Based Tool to Quantify Reservoir Scale Fracture Network for CO2 Storage

Poster on “FRACML: A Machine Learning Based Tool to Quantify Reservoir Scale Fracture Network for CO2 Storage” for the CCUS 2025 conference held in Houston, Texas March 3-5, 2025. The accurate characterization of subsurface fracture networks is essential for the secure operation of carbon capture, utilization, and storage (CCUS) projects. A thorough understanding of the spatial distribution of subsurface faults and fractures is crucial for predicting CO2 plume evolution and minimizing risks such as potential leakage into overlying formations or induced seismicity. In this context, robust fracture network quantification plays a pivotal role in reservoir management, providing the data necessary to fine-tune operational parameters, and ensure the environmental and economic viability of CCUS projects. As part of the U.S. Department of Energy’s SMART (Science-informed Machine Learning for Accelerating Real-time Decisions in Subsurface Applications) initiative, we focused on the development and application of a machine learning-based tool (FRACML) designed to quantify and map fracture networks using real-world (non-synthetic) data from an active CO2 injection site. Our objective is to demonstrate the utility of this tool in improving operational efficiency and safety across CCUS sites.

artifical intelligence / machine learning (AI/ML)↗
DOE OSTI2025

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↗
DOE OSTI2026

Wasserstein Normalized Autoencoder for Anomaly Detection in ProtoDUNE Vertical-Drift Detector

ProtoDUNE Vertical Drift needs a selective triggering algorithm. The detector sits on Earth's surface, so cosmic activity dominates its data. Our goal in this paper is to trigger on neutrino events more robustly than the current deployed Analog-to-Digital Converter Simple Window (ADCSW) model and, eventually, search for signals of Beyond Standard Model (BSM) physics at DUNE as our ultimate North Star objective. As a step towards this goal, we evaluate a Wasserstein Normalized Autoencoder (WNAE) on simulated collection-plane only windows of shape $1\times10\times10$ where Neutrinos act as our BSM-proxy and Cosmic-ray Muons serve as our learned background. The network parameters are fitted using only cosmic-ray muon events as background in order to maintain an unsupervised pipeline. Training uses finite-step Langevin $x^-$ samples, positive-sample reconstruction energy, and an empirical sliced $2$-Wasserstein objective to learn a normalized Boltzmann energy model. We then calibrate on a nominal $5\,\mathrm{Hz}$ operating threshold calculated from cosmic validation data. Both WNAE and ADCSW accept 311 of 194,083 held-out cosmic background events at this $5\,\mathrm{Hz}$ threshold. We found that WNAE accepts 9,677 of 34,634 neutrino-proxy events $(27.9\pm0.24)\%$, compared with 10,076 $(29.1\pm0.24)\%$ for ADCSW, an observed WNAE-minus-ADCSW difference of $-1.15\%$. At another nominal $2\,\mathrm{Hz}$ target threshold, the corresponding efficiencies are $(20.5\pm0.22)\%$ and $(22.6\pm0.22)\%$, respectively. Of the WNAE-selected neutrino proxies at $5\,\mathrm{Hz}$, $(20.8\pm0.4)\%$ of the classified neutrino-proxy events are unique to WNAE, where the uncertainty is an absolute binomial standard error of $0.4\%$.

Zheng, Jake [U. Chicago (main)] (ORCID:00090002189↗
DOE OSTI2019

Dynamic color mapping with a multi-scale histogram: A design study with physical scientists

Many research and development activities for scientific data analysis have focused on scalability challenges and data-driven features. Conversely, data visualization that focus on models requiring human interaction rarely involve practical and largescale scientific data analysis. Therefore, a gap exists between interactive data visualization and scientific data analysis applications. In this paper, we present a design study of interactive data visualization to support scientists who visually analyze data from neutron scattering experiments. This study was conducted in multiple phases: 1) problem characterization; 2) initial design and formative evaluation; and 3) iterative design. We characterize the problems and the design requirements for the analysis of the specific physical science data. We discuss the design, development, evaluation of our visual analytics tool and as well as our iterative developments with physical scientists. We show how to bridge the gap between the two disciplines uncovering new potential to solve their challenges in this design study. We focus on a specific challenge, finding an optimal color mapping, which plays a critical role in neutron scattering science and is broadly applicable to other scientific domains. To address the challenge, we propose two interactive visualization techniques: a dynamic color scale bar (DCSB) and a multi-scale histogram (MSH).

Chae, Junghoon↗
DOE OSTI2023

Substrate-independent expression of key functional genes in Cycloclasticus pugetii strain PS-1 limits their use as markers for PAH biodegradation

Microbial degradation of petroleum hydrocarbons is a crucial process for the clean-up of oil-contaminated environments. Cycloclasticus spp. are well-known polycyclic aromatic hydrocarbon (PAH) degraders that possess PAH-degradation marker genes including rhd3α, rhd2α, and pahE. However, it remains unknown if the expression of these genes can serve as an indicator for active PAH degradation. Here, we determined transcript-to-gene (TtG) ratios with (reverse transcription) qPCR in cultures of Cycloclasticus pugetii strain PS-1 grown with naphthalene, phenanthrene, a mixture of these PAHs, or alternate substrates (i.e., no PAHs). Mean TtG ratios of 1.99 × 10 −2 , 1.80 × 10 −3 , and 3.20 × 10 −3 for rhd3α, rhd2α, and pahE, respectively, were measured in the presence or absence of PAHs. The TtG values suggested that marker-gene expression is independent of PAH degradation. Measurement of TtG ratios in Arctic seawater microcosms amended with water-accommodated crude oil fractions, and incubated under in situ temperature conditions (i.e., 1.5°C), only detected Cycloclasticus spp. rhd2α genes and transcripts (mean TtG ratio of 4.15 × 10 −1 ). The other marker genes—rhd3α and pahE—were not detected, suggesting that not all Cycloclasticus spp. carry these genes and a broader yet-to-be-identified repertoire of PAH-degradation genes exists. The results indicate that the expression of PAH marker genes may not correlate with PAH-degradation activity, and transcription data should be interpreted cautiously.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Magnetic Flux Emergence and Decay Rates for Preceder and Follower Sunspots Observed with HMI

We quantify the emergence and decay rates of preceder (p) and follower (f) sunspots within 10 active regions from 2010 to 2014 using Space-weather Helioseismic Magnetic Imager Active Region Patch data. The sunspots are small to mid-sized regions and contain a signed flux within a single polarity sunspot of (1.1--6.5)×10{sup 21} Mx. The net unsigned flux within the regions, including plage, ranges from (5.1--20)×10{sup 21} Mx. Rates are calculated with and without intensity contours to differentiate between sunspot formation and flux emergence. Signed flux emergence rates, calculated with intensity contours, for the p (f) spots average 6.8(4.9)×10{sup 19} Mx hr{sup −1}, while decay rates are −1.9(−3.4)×10{sup 19} Mx hr{sup −1}. The mean, signed flux emergence rate of the regions, including plage, is 7.1×10{sup 19} Mx hr{sup −1}, for a mean peak flux of 5.9×10{sup 21} Mx. Using a synthesis of these results and others reported previously, there is a clear trend for larger flux regions to emerge faster than smaller ones. Observed emergence rates (dϕ/dt, Mx hr{sup −1}) scale with total signed peak flux, ϕ-tilde {sub max}, as a power law with an exponent of 0.36, i.e., dϕ/dt=A ϕ-tilde {sub max}{sup 0.36}. The observed rates may assist in constraining the boundary and initial conditions in simulations which already demonstrate increased rates for flux tubes with higher buoyancy and twist, or in the presence of a strong upflow. Overall, the observed emergence rates are smaller than those in simulations, which may indicate a slower rise of the flux in the interior than what is captured in simulations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

A Comprehensive Review of Latent Space Dynamics Identification Algorithms for Intrusive and Non-Intrusive Reduced-Order-Modeling

Numerical solvers of partial differential equations (PDEs) have been widely employed for simulating physical systems. However, the computational cost remains a major bottleneck in various scientific and engineering applications, which has motivated the development of reduced-order models (ROMs). Recently, machine-learning-based ROMs have gained significant popularity and are promising for addressing some limitations of traditional ROM methods, especially for advection dominated systems. In this chapter, we focus on a particular framework known as Latent Space Dynamics Identification (LaSDI), which transforms the high-fidelity data, governed by a PDE, to simpler and low-dimensional latent-space data, governed by ordinary differential equations (ODEs). These ODEs can be learned and subsequently interpolated to make ROM predictions. Each building block of LaSDI can be easily modulated depending on the application, which makes the LaSDI framework highly flexible. In particular, we present strategies to enforce the laws of thermodynamics into LaSDI models (tLaSDI), enhance robustness in the presence of noise through the weak form (WLaSDI), select high-fidelity training data efficiently through active learning (gLaSDI, GPLaSDI), and quantify the ROM prediction uncertainty through Gaussian processes (GPLaSDI). We demonstrate the performance of different LaSDI approaches on Burgers equation, a non-linear heat conduction problem, and a plasma physics problem, showing that LaSDI algorithms can achieve relative errors of less than a few percent and up to thousands of times speed-ups.

Computational Engineering, Finance, and Science (c↗
DOE OSTI2020

Environmental controls on ecosystem-scale cold-season methane and carbon dioxide fluxes in an Arctic tundra ecosystem

Abstract. Understanding the processes that influence and control carbon cycling in Arctic tundra ecosystems is essential for making accurate predictions about what role these ecosystems will play in potential future climate change scenarios. Particularly, air–surface fluxes of methane and carbon dioxide are of interest as recent observations suggest that the vast stores of soil carbon found in the Arctic tundra are becoming more available to release to the atmosphere in the form of these greenhouse gases. Further, harsh wintertime conditions and complex logistics have limited the number of year-round and cold-season studies and hence too our understanding of carbon cycle processes during these periods. We present here a two-year micrometeorological data set of methane and carbon dioxide fluxes, along with supporting soil pore gas profiles, that provide near-continuous data throughout the active summer and cold winter seasons. Net emission of methane and carbon dioxide in one of the study years totalled 3.7 and 89 g C m−2 a−1 respectively, with cold-season methane emission representing 54 % of the annual total. In the other year, net emission totals of methane and carbon dioxide were 4.9 and 485 g C m−2 a−1 respectively, with cold-season methane emission here representing 82 % of the annual total – a larger proportion than has been previously reported in the Arctic tundra. Regression tree analysis suggests that, due to relatively warmer air temperatures and deeper snow depths, deeper soil horizons – where most microbial methanogenic activity takes place – remained warm enough to maintain efficient methane production whilst surface soil temperatures were simultaneously cold enough to limit microbial methanotrophic activity. These results provide valuable insight into how a changing Arctic climate may impact methane emission, and highlight a need to focus on soil temperatures throughout the entire active soil profile, rather than rely on air temperature as a proxy for modelling temperature–methane flux dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

How lamina-associated polypeptide 1 (LAP1) activates Torsin

Lamina-associated polypeptide 1 (LAP1) resides at the nuclear envelope and interacts with Torsins, poorly understood endoplasmic reticulum (ER)-localized AAA + ATPases, through a conserved, perinuclear domain. We determined the crystal structure of the perinuclear domain of human LAP1. LAP1 possesses an atypical AAA + fold. While LAP1 lacks canonical nucleotide binding motifs, its strictly conserved arginine 563 is positioned exactly where the arginine finger of canonical AAA + ATPases is found. Based on modeling and electron microscopic analysis, we propose that LAP1 targets Torsin to the nuclear envelope by forming an alternating, heterohexameric (LAP1-Torsin) 3 ring, in which LAP1 acts as the Torsin activator. The experimental data show that mutation of arginine 563 in LAP1 reduces its ability to stimulate TorsinA ATPase hydrolysis. This knowledge may help scientists understand the etiology of DYT1 primary dystonia, a movement disorder caused by a single glutamate deletion in TorsinA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

USE OF THE AERIAL MEASUREMENT SYSTEM HELICOPTER EMERGENCY RESPONSE ACQUISITION SYSTEMS WITH GEOGRAPHIC INFORMATION SYSTEM FOR RADIOACTIVE SOIL REMEDIATION - [11504]

The Aerial Measurement System (AMS) Helicopter Emergency Response Acquisition System provides a thorough and economical means to identify and characterize the contaminants for large area radiological surveys. The helicopter system can provide a 100-percent survey of an area that qualifies as a scoping survey under the Multi-Agency Radiation Survey and Site Investigation Manual (MARSSIM) methodology. If the sensitivity is adequate when compared to the clean up values, it may also be used for the characterization survey. The data from the helicopter survey can be displayed and manipulated to provide invaluable data during remediation activities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Completion processing for data communications instructions

Completion processing of data communications instructions in a distributed computing environment, including receiving, in an active messaging interface (`AMI`) data communications instructions, at least one instruction specifying a callback function; injecting into an injection FIFO buffer of a data communication adapter, an injection descriptor, each slot in the injection FIFO buffer having a corresponding slot in a pending callback list; listing in the pending callback list any callback function specified by an instruction, incrementing a pending callback counter for each listed callback function; transferring payload data as per each injection descriptor, incrementing a transfer counter upon completion of each transfer; determining from counter values whether the pending callback list presently includes callback functions whose data transfers have been completed; calling by the AMI any such callback functions from the pending callback list, decrementing the pending callback counter for each callback function called.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Completion processing for data communications instructions

Completion processing of data communications instructions in a distributed computing environment, including receiving, in an active messaging interface (`AMI`) data communications instructions, at least one instruction specifying a callback function; injecting into an injection FIFO buffer of a data communication adapter, an injection descriptor, each slot in the injection FIFO buffer having a corresponding slot in a pending callback list; listing in the pending callback list any callback function specified by an instruction, incrementing a pending callback counter for each listed callback function; transferring payload data as per each injection descriptor, incrementing a transfer counter upon completion of each transfer; determining from counter values whether the pending callback list presently includes callback functions whose data transfers have been completed; calling by the AMI any such callback functions from the pending callback list, decrementing the pending callback counter for each callback function called.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

OVERVIEW OF ALUMINUM CLADDING OXIDE PREDICTION MODELS FOR EUROPEAN HIGH POWER RESEARCH REACTORS

UMo/Al dispersion fuel clad with aluminum alloy is a primary candidate fuel form that is being developed for the European high power research reactors (EUHPRR). In BR2 tests, water oxidation of cladding grew thick due to high powers. Excessive cladding oxidation is a cause for serious fuel performance degradation in a test while fuel performance itself may be sound. It is necessary for a fuel designer to have a reliable model to predict cladding oxidation for fuel licensing activities. Using oxide data from BR2 tests, this study reviews the prominent oxide prediction models and cladding-to-coolant heat transfer correlations. Because the oxide growth models were based upon different coolant flow conditions from those of the EUHPRR, the effect of the heat transfer correlations at the cladding-to-coolant interface on the oxide thickness prediction were also examined. The best combination of the oxide prediction model and the heat transfer correlation applicable for the EUHPRR is recommended. Since the existing oxide models were all developed for aluminum alloy types different from those currently considered for the EUHPRR, the effect of cladding alloy type is also discussed.

Research reactor fuel, aluminum oxidation, in-pile↗
DOE OSTI2020

Automated Data Review of Analytical Laboratory Results at Los Alamos National Laboratory - 20299

Newport News Nuclear BWXT-Los Alamos, LLC (N3B) collects samples in support of the U.S. Department of Energy's (DOE) Office of Environmental Management (EM) Los Alamos Legacy Cleanup Contract (LLCC). N3B receives and reviews over 1.6 million sample data points annually in support of various ongoing environmental monitoring and remediation projects of the LLCC. N3B must demonstrate and document that reported external analytical laboratory data produced for the LLCC are of sufficient quality to fulfill their intended purpose and to support defensible decision making as described in EPA QA/G4 Guidance for the Data Quality Objectives Process 1994. In 2018, N3B assumed management of the LLCC along with the Environmental Information Management (EIM) database that contains all historical and current environmental data associated with the LLCC. The entire EIM database is shared between N3B, Triad National Security, LLC (Triad), and New Mexico Environment Department (NMED). These three parties jointly manage the database, its configuration, and changes / updates. All environmental data that are entered into EIM are updated and available, on a daily basis, in the linked public database Intellus New Mexico (Intellus). The quality and defensibility of the environmental data generated from sampling activities is a key component of an effective remediation process. Providing quality data is accomplished through a data assessment process that includes examination, verification, and validation. Examination is the assessment of completeness of the deliverables, identification of any reporting errors, and determining the usability of the data based on the laboratory's evaluation of its data as described in the case narrative received with the data. Verification consists of an evaluation of the Electronic Data Deliverables (EDD) data report to determine the extent to which the external analytical laboratories met method and contract-specific quality control and reporting requirements. Validation consists of determining the data quality and the extent to which the external analytical laboratories accurately and completely reported all sample and quality control results and satisfied all contract requirements. EIM contains an automatic Data Validation Module which performs automated data review (DVM ADR). DVM ADR is a tool to assist in the validation process. When DVM ADR is used in conjunction with manual examination of sample data packages, the combination of the two will meet and exceed the requirements of verification. N3B recognized an opportunity for process improvement, focusing on DVM ADR configuration and enhancements in EIM. Testing EIM's configuration provided proof of the DVM ADR's capabilities and flexibility to accurately perform routine data checks based on analytical methods and regulatory requirements. In addition, the DVM ADR module was improved through enhancements for all analytes, particularly upgrades for radiochemistry data. Extensive testing of the DVM ADR module occurred using EDDs from actual laboratory analyses on the EIM testing site. During this process, N3B manipulated EDD information to verify that the actual outcomes matched the expected outcomes. The results of this testing were shared with the database architects, and configuration improvements were identified to address these results. During this process, N3B identified that the radiochemical DVM ADR capabilities were underutilized, and so enhanced the DVM ADR functionality with respect to radioanalytical assessment. N3B environmental data uploads to Intellus on a daily basis from EIM, once the analytical data undergoes examination and verification. As such, it is important to have a high level of confidence in the quality and defensibility of the data. The process of manual examination, along with the DVM ADR, in conjunction with full validation of a percentage the data specified through the Data Quality Objectives greatly increases efficiency of data review and confidence level of the quality of the data, and gives the project managers, governmental offices, and the public expedited access to high-quality data. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Wasserstein Normalized Autoencoder for Anomaly Detection in ProtoDUNE Vertical-Drift Detector

ProtoDUNE Vertical Drift needs a selective triggering algorithm. The detector sits on Earth's surface, so cosmic activity dominates its data. Our goal in this paper is to trigger on neutrino events more robustly than the current deployed Analog-to-Digital Converter Simple Window (ADCSW) model and, eventually, search for signals of Beyond Standard Model (BSM) physics at DUNE as our ultimate North Star objective. As a step towards this goal, we evaluate a Wasserstein Normalized Autoencoder (WNAE) on simulated collection-plane only windows of shape $1\times10\times10$ where Neutrinos act as our BSM-proxy and Cosmic-ray Muons serve as our learned background. The network parameters are fitted using only cosmic-ray muon events as background in order to maintain an unsupervised pipeline. Training uses finite-step Langevin $x^-$ samples, positive-sample reconstruction energy, and an empirical sliced $2$-Wasserstein objective to learn a normalized Boltzmann energy model. We then calibrate on a nominal $5\,\mathrm{Hz}$ operating threshold calculated from cosmic validation data. Both WNAE and ADCSW accept 311 of 194,083 held-out cosmic background events at this $5\,\mathrm{Hz}$ threshold. We found that WNAE accepts 9,677 of 34,634 neutrino-proxy events $(27.9\pm0.24)\%$, compared with 10,076 $(29.1\pm0.24)\%$ for ADCSW, an observed WNAE-minus-ADCSW difference of $-1.15\%$. At another nominal $2\,\mathrm{Hz}$ target threshold, the corresponding efficiencies are $(20.5\pm0.22)\%$ and $(22.6\pm0.22)\%$, respectively. Of the WNAE-selected neutrino proxies at $5\,\mathrm{Hz}$, $(20.8\pm0.4)\%$ of the classified neutrino-proxy events are unique to WNAE, where the uncertainty is an absolute binomial standard error of $0.4\%$.

Zheng, Jake [Chicago U.] (ORCID:0009000218901379)↗