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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Sensitivity and Uncertainty Analysis of Plutonium and Cesium Isotopes in Modeling of BR3 Reactor Spent Fuel

Nuclear forensics has a broad task to characterize recovered nuclear or radiological material and interpret the results of investigation. One approach to isotopic characterization of nuclear material obtained from a reactor is to chemically separate and perform isotopic measurements on the sample and verify the results with modeling of the sample history, for example, operation of a nuclear reactor. The major actinide plutonium and fission product cesium are commonly measured signatures of the fuel history in a reactor core. This study investigates the uncertainty of the plutonium and cesium isotope ratios of a fuel rod discharged from a research pressurized water reactor when the location of the sample is not known a priori. A sensitivity analysis showed overpredicted values for the 240 Pu/ 239 Pu ratio toward the axial center of the rod and revealed a lower probability of the rod of interest (ROI) being on the periphery of the assembly. The uncertainty analysis found the relative errors due to only the rod position and boron concentration to be 17% to 36% and 7% to 15% for the 240 Pu/ 239 Pu and 137 Cs/ 135 Cs ratios, respectively. Lastly, this study provides a method for uncertainty quantification of isotope concentrations due to the location of the ROI. Similar analyses can be performed to verify future chemical and isotopic analyses.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Condition monitoring and anomaly detection in cyber-physical systems

The modern industrial environment is equipping myriads of smart manufacturing machines where the state of each device can be monitored continuously. Such monitoring can help identify possible future failures and develop a cost-effective maintenance plan. However, it is a daunting task to perform early detection with low false positives and negatives from the huge volume of collected data. This requires developing a holistic machine learning framework to address the issues in condition monitoring of high priority components and develop efficient techniques to detect anomalies that can detect and possibly localize the faulty components. This paper presents a comparative analysis of recent machine learning approaches for robust, cost-effective anomaly detection in cyber-physical systems. While detection has been extensively studied, very few researchers have analyzed the localization of the anomalies. We show that supervised learning outperforms unsupervised algorithms. For supervised cases, we achieve near-perfect accuracy of 98% (specifically for tree-based algorithms). In contrast, the best-case accuracy in the unsupervised cases was 63%—the area under the receiver operating characteristic curve (AUC) exhibits similar outcomes as an additional metric.

Marfo, William↗
DOE OSTI2016

SU-F-P-33: Combining Research and Professional Practice in the Clinical Setting: A Medical Physicist Personal Experience

Purpose: To initiate a discussion on the current and evolving role of Medical Physicists based on author’s professional and research experience in patient safety and quality control. Methods: Several professionals of the departments of Medical Physics and Radiation Oncology, chiefly devoted to clinical tasks, began a research program on patient safety and quality control in a framework provided by the implementation of intraoperative radiotherapy (IORT). We performed studies on virtual simulation for IORT, in vivo dosimetry, failure mode and effect analysis (FMEA), statistical process control (SPC), and receiver operating characteristics of dosimetric equipment. This was done with the support of our research foundation and different grants while continuing with our departmental clinical routine involving about 1600 annual treatments with two linacs and different brachytherapy techniques. Results: We published 5 papers in international journals in the last two years. This author conducted a doctoral research which resulted in a dissertation in 2015. The extra time spent after treatments was essential to succeed. Funding and support achieved via our foundation played a crucial role; but this would have not been possible without punctual external mentoring and partnership. FMEA conclusions were able to be implemented only with staff commitment; however, conclusions concerning equipment cannot be easily communicated to manufacturers. These tasks required extra training in the appropriated methods. Conclusion: Research needed the support of a dedicated foundation, which would have been very difficult to obtain with the sole participation of our departments. FMEA and SPC results may need engagement of staff and manufacturers, respectively, hard to achieve without strong recommendations or even a regulatory framework. All these fields need evolution of Medical Physicists’ roles and additional training. Devotion to both clinical tasks and research could be unfeasible for Medical Physicists in the clinical setting without the appropriate rearrangement of their schedules and tasks. Supported by grants IPT-300000-2010-3 and PI11/01659. ERDF funds and Spanish Government.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Exponentially Reduced Circuit Depths Using Trotter Error Mitigation

Product formulas are a popular class of digital quantum simulation algorithms due to their conceptual simplicity, low overhead, and performance, which often exceeds theoretical expectations. Recently, Richardson extrapolation and polynomial interpolation have been proposed to mitigate the Trotter error incurred by the use of these formulas. This work provides a rigorous, general analysis of these techniques for computing time-evolved observables, simplifying the interpolation algorithm in the process, and shows that extrapolation generically improves the performance of product formulas for this task. We demonstrate that, to achieve error 𝜖 in a simulation of time 𝑇 using a 𝑝 ⁢th-order product formula with extrapolation, circuit depths of 𝑂⁡(𝑇 1+1/𝑝 ⁢polylog (1/𝜖)) are sufficient—an exponential improvement in the precision over product formulas alone. Furthermore, we prove that these algorithms achieve commutator scaling, and improve the 𝑇 complexity for the interpolation algorithm. By relaxing the requirement of performing exact Chebyshev interpolation, our simplified algorithm eliminates the need for fractional implementations of Trotter steps, reducing computational overhead. Finally, we show these techniques can be combined with the classical shadows method to estimate many time-evolved local observables. Taken together, our findings provide the strongest evidence yet for the utility of Trotter error-mitigation techniques in algorithmic applications.

quantum algorithms & computation↗
DOE OSTI2014

INITIATORS AND TRIGGERING CONDITIONS FOR ADAPTIVE AUTOMATION IN ADVANCED SMALL MODULAR REACTORS

It is anticipated that Advanced Small Modular Reactors (AdvSMRs) will employ high degrees of automation. High levels of automation can enhance system performance, but often at the cost of reduced human performance. Automation can lead to human out-of the loop issues, unbalanced workload, complacency, and other problems if it is not designed properly. Researchers have proposed adaptive automation (defined as dynamic or flexible allocation of functions) as a way to get the benefits of higher levels of automation without the human performance costs. Adaptive automation has the potential to balance operator workload and enhance operator situation awareness by allocating functions to the operators in a way that is sensitive to overall workload and capabilities at the time of operation. However, there still a number of questions regarding how to effectively design adaptive automation to achieve that potential. One of those questions is related to how to initiate (or trigger) a shift in automation in order to provide maximal sensitivity to operator needs without introducing undesirable consequences (such as unpredictable mode changes). Several triggering mechanisms for shifts in adaptive automation have been proposed including: operator initiated, critical events, performance-based, physiological measurement, model-based, and hybrid methods. As part of a larger project to develop design guidance for human-automation collaboration in AdvSMRs, researchers at Idaho National Laboratory have investigated the effectiveness and applicability of each of these triggering mechanisms in the context of AdvSMR. Researchers reviewed the empirical literature on adaptive automation and assessed each triggering mechanism based on the human-system performance consequences of employing that mechanism. Researchers also assessed the practicality and feasibility of using the mechanism in the context of an AdvSMR control room. Results indicate that there are tradeoffs associated with each mechanism, but that some are more applicable to the AdvSMR domain. The two mechanisms that consistently improve performance in laboratory studies are operator initiated adaptive automation based on hierarchical task delegation and the Electroencephalogram(EEG) –based measure of engagement. Current EEG methods are intrusive and require intensive analysis; therefore it is not recommended for an AdvSMR control rooms at this time. Researchers also discuss limitations in the existing empirical literature and make recommendations for further research.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

2024 Workshop - Remote Sensing and Fluxes Upscaling for Real-world Impact - Tutorial v1

The software-tutorial was developed within the 2024 Remote Sensing and Fluxes Upscaling for Real-world Impact workshop as part of the hands-on session. The workshop was supported by AmeriFlux, National Ecological Observatory Network (NEON) and CarbonDew. The software provides basic tools to perform the following tasks: - gather remote sensing images using Google Earth Engine API; - gather flux data; - perform basic functions, such as plotting time-series, perform QA of the data, compute vegetation indices; - perform correlation analysis between flux data and remote sensing data; - perform flux predictions based on remote sensing data integrated in different modalities.

Falco, Nicola [Lawrence Berkeley National Laborato↗
DOE OSTI2018

MaDaTS: Managing Data on Tiered Storage for Scientific Workflows

Scientific workflows are processing large amounts of data through complex simulation and analysis tasks. Meanwhile, the need to minimize I/O costs on next generation systems and the evolution of new technologies (NVRAMs, SSDs etc.) is resulting in deeper storage hierarchies on High Performance Computing (HPC) systems. A multi-tiered storage hierarchy introduces complexities in workflow and data management. There is need for simple and flexible data abstractions that can allow users to seamlessly manage workflow data and tasks on HPC systems with multiple storage tiers. MaDaTS (Managing Data on Tiered Storage for Scientific Workflows) provides an API and a command-line tool that allows users to manage their workflows and data on tiered storage (Ghoshal & Ramakrishnan (2017)).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Fusion Advanced Design Studies

During the January 1, 2013 – December 31, 2015 contract period, the UW Fusion Technology Institute personnel have actively participated in the ARIES-ACT and FESS-FNSF projects, led the nuclear and thermostructural tasks, attended several project meetings, and participated in all conference calls. The main areas of effort and technical achievements include updating and documenting the nuclear analysis for ARIES-ACT1, performing nuclear analysis for ARIES-ACT2, performing thermostructural analysis for ARIES divertor, performing disruption analysis for ARIES vacuum vessel, and developing blanket testing strategy and Materials Test Module for FNSF.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Realizing the Power of Near-Term Quantum Technologies

This the final report of the LDRD project entitled "Realizing the Power of Near-Term Quantum Technologies", which was tasked with laying a theoretical foundation and computational framework for quantum simulation on quantum devices, to support both future Sandia efforts and the broader academic research effort in this area. The unifying theme of the project has been the desire to delineate more clearly the interface between existent classical computing resources that are vast and reliable with emerging quantum computing resources that will be scarce and unreliable for the foreseeable future. We seek to utilize classical computing resources to judge the efficacy of quantum devices for quantum simulation tasks and determine when they exceed the performance of classical devices, thereby achieving "quantum supremacy". This task was initially pursued by adapting the general concept of "parameter space compression" to quantum simulation. An inability to scale this analysis efficiently to large-scale simulations precipitated a shift in focus to assessing quantum supremacy of a specific quantum device, a 1D Bose gas trapped in an optical lattice, that was more amenable to large-scale analysis. We also seek to reconstruct unobserved information from limited observations of a quantum device to enhance their utility. This task was initially pursued as an application of maximum entropy reconstruction. Initial attempts to improve entropy approximations for direct reconstruction by free energy minimization proved to be more difficult than expected, and the focus shifted to the development of a quantum thermostat to facilitate indirect reconstruction by evolving a quantum Markov process. An efficient quantum thermostat is broadly useful for quantum state preparation in almost any quantum simulation task. In the middle of the project, a small opportunistic investment was made in a high-risk experiment to build an analog quantum simulator out of hole quantum dots in Ge/SiGe heterostructures. While a useful simulator was not produced, hole quantum dots at a Ge/SiGe interface have been successfully observed for the first time.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Similar Exposure Group [Stick Welding without LEV - Manganese - RiskLevel 4]

This memorandum is presented to summarize quantitative worker exposure data collected while performing shielded metal arc welding (“SMAW” or “stick”) without local exhaust ventilation (LEV) and to validate if the appropriate risk level has been assigned to this task using Bayesian Decision Analysis (BDA). The purpose of this exposure assessment is to determine if it can be stated with at least 75% certainty that the true exposure profile (i.e., 95 th percentile) of the SEG is at or below the risk level currently assigned to this SEG.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2022

Low-Cost Recyclable Oxygen Carrier and Novel Process for Chemical Looping Combustion

The University of North Dakota, through its Institute for Energy Studies and Energy & Environmental Research Center, partnered with Envergex LLC, Barr Engineering and Microbeam Technologies to develop a transformational enabling technology for advancement of Chemical Looping Combustion technology. Industrial support was provided by Carbontec Energy Corporation. The project targeted the two biggest challenges to chemical looping combustion: (1) High costs of oxygen carrier replacement/loss due to expensive manufacturing and high replacement rates from physical attrition and/or decrease in reactivity, and (2) Inherently slow fuel char conversion which represents the rate-limiting step for chemical looping combustion and results in very large equipment sizes, and overall lower carbon dioxide capture efficiency. The project activities were addressed in a series of seven tasks. Task 1 extended throughout the entire project and oversaw project management and execution. Task 2 and 3 focused on development and evaluation of the novel oxygen carrier. Task 4 to 7 focused on design of the novel reactor, testing with the novel oxygen carrier and a techno-economic assessment of the process. The list of tasks are: Task 1 – Project management and planning, Task 2 – Laboratory scale oxygen carrier manufacturing and assessment, Task 3 – Modeling and laboratory-scale evaluation of oxygen carrier performance with coal, Task 4 – 10-kilowatt thermal integrated system installation, Task 5 – Scaled-up oxygen carrier manufacturing, Task 6 – 10-kilowatt testing, and Task 7 – Process design and techno-economic analysis.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Data Efficiency Assessment of Generative Adversarial Networks for Critical Heat Flux Synthetic Data Generation

This study investigates the application of generative artificial intelligence techniques, particularly conditional generative adversarial networks (cGAN), in real-world engineering contexts, with a specific focus on synthetic data generation for critical heat flux (CHF). Utilizing a dataset comprising more than 20,000 real experimental CHF measurements, we conduct a series of experiments to examine cGAN’s behavior. These experiments encompass varying sizes of the training dataset, training cGAN on data from diverse experimental sources to generate new data on unseen experimental setups, and assessing the impact of excluding various input features on cGAN’s data generation accuracy. Our findings underscore the pronounced data dependency of cGAN for reliable performance, with decreased efficacy observed with smaller training dataset sizes. Notably, cGAN exhibits varying performance when trained on data from different experiments, with superior predictive capabilities observed for certain experiment sources compared to others. For instance, when cGAN was trained on data from Smolin et al.’s experiments or Zenkevich et al., it exhibited relatively good performance in generating the data from Becker et al., Kirillov et al., and Alekseev et al. experiments. In contrast, when trained with Alekseev et al.’s data and tasked with generating other experimental setups, cGAN showed notably poor performance. In both scenarios, cGAN’s performance was inferior compared to training on samples from all experiments concurrently. A feature importance analysis highlights the significant influence of parameters such as mass flux and heated length on accurate CHF generation, while other parameters like diameter and pressure have less impact. Inlet temperature is identified as a moderating factor by cGAN.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

An Experimental Investigation of Human Performance Differences Depending on Simulator Complexity

As a different approach to collect human reliability analysis (HRA) data compared to the full-scope simulator studies, Idaho National Laboratory (INL) has attempted to collect HRA data based on Simplified Human Error Experimental Program (SHEEP), which uses a simplified simulator and student participants. To date, INL has considered the SHEEP approach using simplified simulators such as Rancor Microworld and Compact Nuclear Simulator to complement – not replace – full-scope studies as well as to mainly collect HRA data for estimating nominal/basic human error probabilities (HEPs) needed in the HRA quantification process. This study is a part of the project aiming to suggest how to support full-scope data collection studies based on SHEEP. This paper first introduces major tasks within the SHEEP framework. Then, as one of the major tasks, why and how we have planned to experimentally investigate human performance differences depending on simulator complexity are mainly introduced in this paper.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2016

Fire compartment partitioning approaches for fire probabilistic safety analysis of a high-temperature gas-cooled reactor - 18545

Fire compartment partitioning is the foundational task in Fire Probabilistic Safety Analysis (FPSA), that requires approaches able to balance analytical accuracy and computational burden. In this work, two fire compartment partitioning approaches are illustrated and applied to an electric building of a High-Temperature Gas-Cooled Reactor (HTGR, e.g., HTR-PM), and the quantified risks of the compartments obtained with the two approaches are compared. The results show that risk is insensitive to the utilized fire compartment partitioning approach, making the FPSA tasks easier to be performed. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Meta‐Analysis and Regression Modeling of the Impacts of Four Indoor Environmental Quality Metrics on Office Performance

Awareness of how buildings interact with the occupant experience—especially human performance—is becoming more prevalent, as seen by increasing interest and investment in healthy built environments. However, there is a need to synthesize the wide array of existing indoor environmental assessment and performance research in a way that can translate directly to building design and operation. Existing research in this area typically focuses on a single isolated metric and has not focused on making the results utilizable by building practitioners. The aim of this research is to investigate existing office performance literature through meta‐analyses and produce regression models for four indoor environmental quality (IEQ) metrics to support critical decision‐making for building operation and renovation. To reach this aim, a literature review was conducted to identify studies that measure the impact of changing ventilation rate, temperature, horizontal illuminance, and noise level in offices on occupant task performance. This repository of field and laboratory studies was analyzed to visualize the trends between the selected IEQ metrics and task performance. The temperature, ventilation rate, and horizontal illuminance regression models showed clear improvement potential when modifying indoor conditions toward the defined high‐performance range, while the regression model for noise level was inconclusive. The discussion notes the importance of designing holistically for all components of these IEQ categories to utilize the results, for example, good filtration on outdoor air for quantifying ventilation impact and uniform overhead lighting with low contrast for quantifying horizontal illuminance impact. The novelty of this work is in considering multiple facets of the indoor environment under a single, unified analysis schema and producing IEQ‐based performance gains that can directly inform cost‐benefit analyses of building design and renovation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

BAD2matrix: Phylogenomic matrix concatenation, indel coding, and more

Common steps in phylogenomic matrix production include biological sequence concatenation, morphological data concatenation, insertion/deletion (indel) coding, gene content (presence/absence) coding, removing uninformative characters for parsimony analysis, recording with reduced amino acid alphabets, and occupancy filtering. Existing software does not accomplish these tasks on a phylogenomic scale using a single program. BAD2matrix is a Python script that performs the above-mentioned steps in phylogenomic matrix construction for DNA or amino acid sequences as well as morphological data. The script works in UNIX-like environments (e.g., LINUX, MacOS, Windows Subsystem for LINUX).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Deeplynx Dag Repository

The DeepLynx DAG repository will contain several Airflow DAGs (Directed Acyclic Graphs) which will be used in the context of DeepLynx's deployed Apache Airflow instance. These DAGs will be used for multiple data management tasks for DeepLynx data, including but not limited to: - bringing data from various sources and tools into DeepLynx - managing sequential data workflows, such as running Python scripts on data to perform analysis and returning the results to DeepLynx - performing any necessary transformation or pre-processing on data coming into DeepLynx from external sources or out of DeepLynx to go to external applications

Brownlee, JarenM.↗
DOE OSTI2014

SNS Sample Activation Calculator Experimental Validation - Paper 79

The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) uses the Sample Activation Calculator (SAC) to calculate the activation of all samples after they have been exposed to the neutron beam in any of the neutron scattering instruments at the SNS beamlines. The SAC web page takes user inputs (choice of beamline, the mass, composition and area of the sample, irradiation time, decay time, etc.) and then calculates the activation for the sample. In recent years, the SAC has been incorporated into the user proposal and sample handling process, and beamline scientists and users have noticed discrepancies in the predicted activation of their samples. As a part of the Neutronics Analysis Group at SNS, we were tasked with validating the SAC tool and diagnosing the origin of the discrepancies seen by the beamline scientists and the users. In the process of performing these measurements, we additionally found that several aspects of realistic neutron scattering operations, and thus sample exposure, cannot be captured with current configuration of the SAC tool. Typical neutron scattering samples are irradiated for multiple periods with different neutron energy ranges; the realities of accelerator operation indicate that not all of those periods will be at the same accelerator power, and scattering samples are frequently not fully illuminated by the well-collimated neutron beam. Finally, we will explore whether neutron beams, as modified by neutron guide systems with energy-dependent intensity modifications and by precise energy-band defining mechanical choppers, are suitably analyzed with multigroup cross section libraries in which there are typically very few energy groups below one eV. (authors)

43 PARTICLE ACCELERATORS↗