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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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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Automated Reconstruction, Signal Processing and Particle Identification in DUNE

Liquid Argon TPC (LArTPC) technology is increasingly prevalent in large-scale detectors designed to observe neutrino scattering events induced by accelerators or by natural sources. LArTPCs consist of a very high fraction of active detector material with spatial resolutions on the order of a few millimeters. Three-dimensional interactions are imaged in multiple two-dimensional views by the process of projection onto planes of wires. The goal of automated reconstruction is to correctly classify each neutrino scattering event by the flavor of the incoming neutrino, to separate charged-current events from neutral-current and other backgrounds, and to measure the energies of the incoming neutrinos. Detection of neutrinos from supernova bursts and also seaching for nucleon decay are important uses of automated reconstruction algorithms. Because the amount of spatial detail is high and the amount of scattering is high, this reconstruction presents many challenges that are now being investigated with sophisticated techniques.Signal processing, track and shower identification, particle identification, and event classification by a variety of innovative algorithms are reviewed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Automated Reconstruction, Signal Processing and Particle Identification in DUNE

Liquid Argon TPC (LArTPC) technology is increasingly prevalent in large-scale detectors de- signed to observe neutrino scattering events induced by accelerators or by natural sources. LArTPCs consist of a very high fraction of active detector material with spatial resolutions on the order of a few millimeters. Three-dimensional interactions are imaged in multiple two- dimensional views by the process of projection onto planes of wires. The goal of automated reconstruction is to correctly classify each neutrino scattering event by the flavor of the incoming neutrino, to separate charged-current events from neutral-current and other backgrounds, and to measure the energies of the incoming neutrinos. Detection of neutrinos from supernova bursts and also searching for nucleon decay are important uses of automated reconstruction algorithms. Be- cause the amount of spatial detail is high and the amount of scattering is high, this reconstruction presents many challenges that are now being investigated with sophisticated techniques. Signal processing, track and shower identification, particle identification, and event classification by a variety of innovative algorithms are reviewed

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Automated detection of mild cognitive impairment and dementia from voice recordings: A natural language processing approach

Automated computational assessment of neuropsychological tests would enable widespread, cost-effective screening for dementia. A novel natural language processing approach is developed and validated to identify different stages of dementia based on automated transcription of digital voice recordings of subjects’ neuropsychological tests conducted by the Framingham Heart Study (n = 1084). Transcribed sentences from the test were encoded into quantitative data and several models were trained and tested using these data and the participants’ demographic characteristics. Average area under the curve (AUC) on the held-out test data reached 92.6%, 88.0%, and 74.4% for differentiating Normal cognition from Dementia, Normal or Mild Cognitive Impairment (MCI) from Dementia, and Normal from MCI, respectively. The proposed approach offers a fully automated identification of MCI and dementia based on a recorded neuropsychological test, providing an opportunity to develop a remote screening tool that could be adapted easily to any language.

neuropsychological↗
DOE OSTI2017

Hanford Site Composite Analysis Technical Approach Description: Automated Quality Assurance Process Design.

The U.S. Department of Energy (DOE) in DOE O 435.1 Chg. 1, Radioactive Waste Management, requires the preparation and maintenance of a composite analysis (CA). The primary purpose of the CA is to provide a reasonable expectation that the primary public dose limit is not likely to be exceeded by multiple source terms that may significantly interact with plumes originating at a low-level waste disposal facility. The CA is used to facilitate planning and land use decisions that help assure disposal facility authorization will not result in long-term compliance problems; or, to determine management alternatives, corrective actions, or assessment needs if potential problems are identified.

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

Automation of Nanoparticle Synthesis Processes in a Plasma Environment Using LabVIEW

This work presents an automated control system for the synthesis of nanomaterials by plasma-enhanced chemical vapor deposition (PECVD), implemented using the LabVIEW software environment. The main objective of the study is to develop an integrated hardware-software platform that enables sequential control of the key stages of the PECVD process, including vacuum chamber preparation, pressure monitoring, working gas supply, plasma ignition, power matching, cyclic nanomaterial growth, and optical monitoring of nanoparticles in the plasma environment. The use of LabVIEW made it possible to integrate actuator control, experimental parameter acquisition, and realtime process visualization within a single automated system. The automated cycle begins with evacuation of the reaction chamber to a predefined base pressure. Transition to the next stage is permitted only after the specified pressure threshold has been reached, ensuring reproducible initial conditions for each experiment. The program then controls the supply of the working gas through mass flow controllers (MFCs). In this work, two gas-flow control modes were considered: analog control using a 0-5 V voltage signal and digital communication via RS-232 interface. It was shown that the analog approach requires accurate scaling of the control voltage, since applying 5 V corresponds to full-scale opening of the controller and results in the maximum gas flow. In contrast, the RS232 interface enables the gas flow rate to be specified directly in sccm, improving the accuracy, flexibility, and convenience of gas-environment control. After pressure stabilization, LabVIEW initiates RF plasma ignition and executes the RF matching algorithm aimed at minimizing reflected power and improving the stability of the plasma process. A separate software module implements the cyclic nanomaterial growth mode, in which the plasma-on time, plasma duration, and total number of synthesis cycles are predefined. This approach makes it possible to control material accumulation on the substrate and to correlate the process parameters with the morphological characteristics of the resulting nanostructures. The final module of the system is designed for optical monitoring of the nanoparticle cloud density in dusty plasma. For this purpose, the change in the intensity of laser radiation passing through the plasma region is recorded using a photodetector and a Keithley 2401 measuring unit connected to LabVIEW via RS-232 interface. The difference between the initial and modified optical signal intensity is used as a diagnostic parameter characterizing the formation and temporal evolution of nanoparticles. The developed system demonstrates that LabVIEW can be effectively applied not only for the automation of individual instruments, but also for the implementation of a complete digital control cycle for PECVD-based nanomaterial synthesis.

PECVD↗
DOE OSTI2025

stor4build

The EnergyPlus simulation engine supports modeling and simulation of thermal energy storage (TES) systems in several ways, including using the Python-EMS feature, which extends the operation of the engine with custom code written in Python. Creation of models using this feature can be tedious and error prone, with the connection of the model components to the Python code a particularly troublesome area. The stor4build Python package simplifies this process by modifying an input model to add a selected TES technology (implemented with the Python-EMS feature) and runs the simulation. The package leverages the OpenStudio middleware software development kit to automate this process as much as possible, eliminating potential errors and simplifying usage of EnergyPlus. The package provides objects, functions, and OpenStudio measures that implement the necessary operations to automate the creation of EnergyPlus models that integrate TES technologies with building systems. In addition, two user interfaces are provided: a command line interface and a web application programming interface. The automated process implemented by the package greatly simplifies the modeling and simulation process, allowing for parametric studies to be executed much more efficiently and effectively. The OpenStudio-based workflow is also very flexible and will allow for future additions of new technologies.

DeGraw, JasonWilliam [Oak Ridge National Laborator↗
DOE OSTI2016

Automation and Database Collection and Extrapolation

This report highlights overall design consideration regarding automation and database collection and extrapolation prototype for Farmpod, LLC. There are potentially many combinations of software, hardware, and networking which suffices for the requirements. For this report, we suggest a Raspberry Pi 2 Model B for the hardware. We suggest the Mako application server for the user interface and RPIO python modules for automated software processes. At the present moment, security is not a major concern, but should be addressed during the initial design phase. The software stack consists of two primary components: the automated processes and application server to implement a user interface.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Qualification and Quantification of Porosity at the Top of the Fuel Pins in Metallic Fuels Using Image Processing

Approximately 130,000 metal fuel pins were irradiated in the Experimental Breeder Reactor II (EBR-II) during its 30 years of operation to develop and characterize existing and prospective fuels. For many of the metal fuel irradiation experiments, neutron radiography imaging was performed to characterize fuel behavior, such as fuel axial expansion. While several fuel expansion results obtained from neutron radiography imaging have been published, the analysis of neutron radiography for the purpose of describing statistical properties of porous matter formed on top of the fuel pins, also referred to as fluff in previous publications, is significantly less represented in the literature with just a single paper so far. This study aims to validate and augment results reported in previous publications using automated image processing. The paper describes the statistical properties of the porous matter in terms of nine parameters derived from radiography images and correlates those parameters with such fuel properties as composition, expansion, temperature, and burnup. The reported results are based on 1097 fuel pins of eight different fuel compositions. For three major fuel types, U-10Zr, U-8Pu-10Zr, and U-19Pu-10Zr, a clear negative correlation is found between the Pu content and five parameters describing the amount of porous matter generated. The parameters describing granularity properties, however, showed either negative correlation or nonlinear dependency from fuel composition. The parameters describing the amount showed a positive correlation with fuel axial expansion, while granularity parameters showed a negative correlation with axial expansion. The dependency on cladding temperature was found to be weak. A positive correlation is demonstrated for volume parameters and fuel burnup. In general, reported results confirm and validate findings published in previous studies using a much larger number of pins and automated processing techniques, which easily lend themselves to reproducibility, thus avoiding subjective bias.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Deformation Mechanisms at Grain Boundaries in Polycrystals (Final Report)

Despite its significance in polycrystalline materials, there have been few experimental investigations of the activity of grain boundary sliding (GBS) and the relationship between GBS and slip transmission at grain boundaries. This work addressed this knowledge gap by an experimental and analytical investigation into the interactions between grain boundary sliding (GBS) and slip transmission plastic deformation mechanisms, and how these are impacted by local microstructure. Polycrystalline columnar aluminum of 99.99% purity was examined as a highly modellable system for characterizing grain boundary-local deformation mechanism interaction. High-resolution, large field-of-view strain fields and grain orientation information were captured and statistically analyzed to identify deformation activity with respect to the local microstructure, using a combination of scanning electron microscopy and digital image correlation (SEM-DIC) with electron backscatter diffraction (EBSD). Alignment between the lower-resolution electron backscatter diffraction (EBSD) data and the higher-resolution strain fields was significantly improved by clustering of strain data within an EBSD-defined boundary mantle. Although this work specifically focuses on characterizing the relationship between grain boundary sliding (GBS) and slip transmission, the developed experimental approach, multimodal data alignment process, and automated displacement discontinuity measurement process can be used to study a variety of mechanism interactions across a broad range of materials. Regarding GBS and slip transmission interaction, significant findings include that (1) grain boundaries that slide easily do not facilitate slip transmission; (2) substantial gradients in GBS magnitude could be found along the length of individual grain boundaries, and these were caused by strain discontinuities across the boundary related to deformation anisotropy between adjacent grains; (3) direct transmission and GBS were anti-compatible and facilitated by opposing boundary types (low misorientation and high energy grain boundaries respectively); (4) increased GBS activity was correlated with decreased indirect transmission behavior; (5) GBS accommodation at triple junctions was enabled by intragranular plasticity; and (6) the local intragranular plastic strain discontinuity between grains determined the magnitude of GBS gradients. The experimental strain fields were compared to that of a tangent crystal plasticity finite element (CPFE) model developed by collaborators (Mr. Ajey Venkataraman and Professor Michael Sangid, Purdue University). Implication of this work for improving CPFE models and deformation prediction are discussed. This work provides insight into the nature of these mechanisms and can be used to identify strain transfer criteria that can lead to improved GBS-sensitive crystal plasticity models.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Sci-Fri PM: Radiation Therapy, Planning, Imaging, and Special Techniques - 08: Retrospective Dose Accumulation Workflow in Head and Neck Cancer Patients Using RayStation 4.5.2

Purpose: We have developed a semi-automated dose accumulation workflow for Head and Neck Cancer (HNC) patients to evaluate volumetric and dosimetric changes that take place during radiotherapy. This work will be used to assess how dosimetric changes affect both toxicity and disease control, hence inform the feasibility and design of a prospective HNC adaptive trial. Methods: RayStation 4.5.2 features deformable image registration (DIR), where structures already defined on the planning CT image set can be deformably mapped onto cone-beam computed tomography (CBCT) images, accounting for daily treatment set-up shifts and changes in patient anatomy. The daily delivered dose can be calculated on each CBCT and mapped back to the planning CT to allow dose accumulation. The process is partially automated using Python scripts developed in collaboration with RaySearch. Results: To date we have performed dose accumulation on 18 HNC patients treated at our institution during 2013–2015 under REB approval. Our semi-automated process establishes clinical feasibility. Generally, dose accumulation for the entire treatment course of one case takes 60–120 minutes: importing all CBCTs requires 20–30 minutes as each patient has 30 to 40 treated fractions; image registration and dose accumulation require 60–90 minutes. This is in contrast to the process without automated scripts where dose accumulation alone would take 3–5 hours. Conclusions: We have developed a reliable workflow for retrospective dose tracking in HNC using RayStation. The process has been validated for HNC patients treated on both Elekta and Varian linacs with CBCTs acquired on XVI and OBI platforms respectively.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Remote operations and maintenance framework for molten salt reactors

Remote, highly-automated operations and maintenance is key for economically successful deployment of molten salt reactors (MSRs). Liquid-fueled MSRs will have high dose rates within containment following initial start-up due to the proximity of the fuel salt and gaseous fission products. The challenges of performing O&M in high dose environments has long been recognized and many of the required technology components have been developed for use in similar high radiation environments.Future MSRs will need to have much lower labor costs than existing nuclear power plants to be competitive. The advance of digital technologies provides the opportunity to automate maintenance activities. Advances in modeling and simulation (M&S) may enable shifting the role of the operator from remotely performing tasks to overseeing automated systems. Dynamically updating a plant’s digital twin representation through integrating multiple sensor signals will be key to automating complex process tasks. Complex, highly-automated maintenance in high-radiation areas has not been previously proven and adequate demonstration will be required to validate its performance.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Specialty chemicals production case study: Economic analysis of modular chemical process intensification versus conventional stick‐built approaches

Abstract The beneficial synergies of chemical process intensification and plant modularization present a unique step‐wise advancement opportunity for many chemical manufacturers, but economic case studies are needed to raise awareness of such opportunities. The primary objective of this case study is to better understand the business case economics of a specialty chemical plant using modular chemical process intensification (MCPI), by comparing it with that of a conventional stick‐built (CSB) plant that produces the same product at the same production capacity. When comparing MCPI against CSB approaches for a plant project strategy decision, analysts should thoroughly understand and model the differences and similarities in scope bases. The MCPI approach for this case study benefitted from dramatic reductions in capital expenditures (CAPEX). A sizeable reduction in plant spatial volume likely explains some of these reductions. Sizeable operational expenditure (OPEX) reductions with the MCPI plant appear to be associated with the reduced operator staffing required from converting a labor‐intensive batch process into an automated, continuous flow process. Traditional project investment economic measures strongly favored the MCPI case for the design, construction, and operation of the specialty chemical plant. The net present value for the MCPI case was nearly twice that for the CSB case over a ten‐year period, and the payback period for the CSB case was nearly five times longer than that of the MCPI case. The opinion‐based perspective of the study participant identified significant contributors to superior MCPI economic performance for this case study. With the two conditions of low MCPI CAPEX and high product profit margin, economic analysis indicates that incorporation of a backup MCPI train, for operational redundancy when downtime occurs, is a very beneficial strategy.

O'Connor, James T.↗
DOE OSTI2018

Automation Technologies Impact on the Work Process of Nuclear Power Plants

The current cost associated with the work process of nuclear power plants necessities modernizing the work process by augmenting it with automation technologies. This work was performed to assess various automation technologies and the means by which they assimilate into the work process in order to make gains in cost savings in modern nuclear power plants. The goal was to identify key informational items that would be useful to members of industry who are undertaking the large effort to reduce costs through automation by identifying technology maturity levels, recent research, and an analysis of cost impacts of the work process. The technologies cost saving was categorized into low, medium, and high cost savings. Through this effort, a substantive literature review and analysis of recent technological and market trends was performed. The key areas of cost impact were identified through communication with users in industry from operations and maintenance organizations. The results were assembled into a list of work process steps and technologies that are ready be implemented or researched for the automating aspects of that step. This effort aims to present to utilities opportunities of cost saving that are achievable in the short term, and gaps for research organizations and vendors to consider for further research and development. The results of this effort generated a list of technologies that fit each of the three cost saving categories. Electronic work packages remain a high cost saving technology, but data mining and integration, smart scheduling, and dynamic risk models are also indicated to yield a high cost savings. Video applications, spatial mapping, and image processing and identification technologies appear to provide solid cost savings in the medium category, and rounding out the low cost saving areas are deployable technologies such as bar codes, communication tools, and electronic tags.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Automated Image Segmentation and Processing Pipeline Applied to X–Ray Computed Tomography Studies of Pitting Corrosion in Aluminum Wires

Understanding pitting corrosion is critical, yet its kinetics and morphology remain challenging to study from X-ray computed tomography (XCT) due to manual segmentation barriers. To address this, an automated pipeline leveraging deep learning for efficient large-scale XCT analysis is developed, revealing new corrosion insights. The pipeline enables pit segmentation, 3D reconstruction, statistical characterization, and a topological transformation for visualization. Here, the pipeline is applied to 87 648 XCT images capturing commercial purity aluminum (1100 Al) wire exposed to sodium chloride (NaCl) salt particles over a period of 122 h. The pipeline achieves complete feature extraction and statistical quantification across the entire XCT dataset, leveraging distributed computing environment for high efficiency. Global growth kinetics such as high-level stepwise sigmoidal volume loss patterns and granular individual pit developments are both captured for 36 detected pits. By combining automation, computer vision, and extensive XCT datasets, this research accelerates precise corrosion assessment to enable materials science discoveries at scale.

36 MATERIALS SCIENCE↗
DOE OSTI2025

BAMCensus (The Behavior and Advanced Mobility Census Dataset Aggregator) [SWR-25-120]

This software is a high-performance tool developed in Rust for downloading and processing large-scale geospatial datasets, specifically focusing on US Census data. It is designed to address scaling limitations found in existing tools, such as R's [tidycensus](https://walker-data.com/tidycensus/), by providing performant streaming dataset JOIN operations between various US Census datasets (like ACS and LEHD) and their corresponding geometries stored on the TIGER/Lines web server. The tool automates the process of joining these data sources, returning aggregated data to the user based on a specified census GEOID type. The tool automates the process of joining these data sources, returning aggregated data to the user based on a specified census GEOID type. Its primary motivation stems from the need for a high-performance solution to combine spatial datasets with graph traversals within the context of mobility analysis tooling being developed at NREL's Behavior and Advanced Mobility (BAM) group.

Fitzgerald, Robert [National Renewable Energy Labo↗
DOE OSTI2020

Automated pipeline framework for processing of large-scale building energy time series data

Commercial buildings account for one third of the total electricity consumption in the United States and a significant amount of this energy is wasted. Therefore, there is a need for “virtual” energy audits, to identify energy inefficiencies and their associated savings opportunities using methods that can be non-intrusive and automated for application to large populations of buildings. Here we demonstrate virtual energy audits applied to large populations of buildings’ time-series smart-meter data using a systematic approach and a fully automated Building Energy Analytics (BEA) Pipeline that unifies, cleans, stores and analyzes building energy datasets in a non-relational data warehouse for efficient insights and results. This BEA pipeline is based on a custom compute job scheduler for a high performance computing cluster to enable parallel processing of Slurm jobs. Within the analytics pipeline, we introduced a data qualification tool that enhances data quality by fixing common errors, while also detecting abnormalities in a building’s daily operation using hierarchical clustering. We analyze the HVAC scheduling of a population of 816 buildings, using this analytics pipeline, as part of a cross-sectional study. With our approach, this sample of 816 buildings is improved in data quality and is efficiently analyzed in 34 minutes, which is 85 times faster than the time taken by a sequential processing. The analytical results for the HVAC operational hours of these buildings show that among 10 building use types, food sales buildings with 17.75 hours of daily HVAC cooling operation are decent targets for HVAC savings. Overall, this analytics pipeline enables the identification of statistically significant results from population based studies of large numbers of building energy time-series datasets with robust results. These types of BEA studies can explore numerous factors impacting building energy efficiency and virtual building energy audits. This approach enables a new generation of data-driven buildings energy analysis at scale.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Modeling DNP3 Traffic Characteristics of Field Devices in SCADA Systems of the Smart Grid

In the generation, transmission, and distribution sectors of the smart grid, intelligence of field devices is realized by programmable logic controllers (PLCs). Many smart-grid subsystems are essentially cyber-physical energy systems (CPES): For instance, the power system process (i.e., the physical part) within a substation is monitored and controlled by a SCADA network with hosts running miscellaneous applications (i.e., the cyber part). To study the interactions between the cyber and physical components of a CPES, several co-simulation platforms have been proposed. However, the network simulators/emulators of these platforms do not include a detailed traffic model that takes into account the impacts of the execution model of PLCs on traffic characteristics. As a result, network traces generated by co-simulation only reveal the impacts of the physical process on the contents of the traffic generated by SCADA hosts, whereas the distinction between PLCs and computing nodes (e.g., a hardened computer running a process visualization application) has been overlooked. To generate realistic network traces using co-simulation for the design and evaluation of applications relying on accurate traffic profiles, it is necessary to establish a traffic model for PLCs. In this work, we propose a parameterized model for PLCs that can be incorporated into existing co-simulation platforms. We focus on the DNP3 subsystem of slave PLCs, which automates the processing of packets from the DNP3 master. To validate our approach, we extract model parameters from both the configuration and network traces of real PLCs. Simulated network traces are generated and compared against those from PLCs. Our evaluation shows that our proposed model captures the essential traffic characteristics of DNP3 slave PLCs, which can be used to extend existing co-simulation platforms and gain further insights into the behaviors of CPES.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗