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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Pair production of charged IDM scalars at high energy CLIC

The Compact Linear Collider (CLIC) was proposed as the next energy-frontier infrastructure at CERN, to study e ^+ + e ^- − collisions at three centre-of-mass energy stages: 380,GeV, 1.5,TeV and 3,TeV. The main goal of its high-energy stages is to search for the new physics beyond the Standard Model (SM). The Inert Doublet Model (IDM) is one of the simplest SM extensions and introduces four new scalar particles: H ^\pm ± , A and H; the lightest, H, is stable and hence a natural dark matter (DM) candidate. A set of benchmark points is considered, which are consistent with current theoretical and experimental constraints and promise detectable signals at future colliders. Prospects for observing pair-production of the IDM scalars at CLIC were previously studied using signatures with two leptons in the final state. In the current study, discovery reach for the IDM charged scalar pair-production is considered for the semi-leptonic final state at the two high-energy CLIC stages. Full simulation analysis, based on the current CLIC detector model, is presented for five selected IDM scenarios. Results are then extended to the larger set of benchmarks using the Delphes fast simulation framework. The CLIC detector model for Delphes has been modified to take pile-up contribution from the beam-induced \gamma\gamma γ γ interactions into account, which is crucial for the presented analysis. Results of the study indicate that heavy, charged IDM scalars can be discovered at CLIC for most of the proposed benchmark scenarios, with very high statistical significance.

Klamka, Jan↗
DOE OSTI2025

Destructive Analysis of TRISO Particles: Crush/Burn/Leach Followed by Davies-Gray Titration and IDMS

The accurate accounting of nuclear materials is a cornerstone of international nuclear safeguards. One emerging challenge in this domain is the fabrication of TRIstructural ISOtropic (TRISO) particle fuels. Although these innovative fuel forms are critical for advanced reactor applications, their robust refractory ceramics and coating compositions present significant obstacles to destructive analysis (DA) methods. Ensuring full and quantitative recovery from these particles is essential for accurate mass accountancy. The current study was initiated to address these challenges, first by validating a previously established destructive method developed by Oak Ridge National Laboratory (ORNL) for the quantitative recovery of uranium from TRISO particles and then following that process with uranium content determination through isotope dilution mass spectrometry (IDMS) and Davies-Gray titration. This study expands on the scope of a digestive method that was developed under the Advanced Gas Reactor Fuel Development and Qualification program and is currently implemented in both the Coated Particle Fuel Development Laboratory and Irradiated Fuels Examination Laboratory at ORNL. The success of the previous Advanced Gas Reactor work relied on developing a DA method to evaluate the fabrication process and reactor experiments. The methodology described in this report was designed to rigorously investigate the efficacy of the crush/burn/leach sample preparation of TRISO particles; it aims to quantify uranium recovery while also assessing the effects of TRISO constituents (e.g., silicon and zirconium) on analytical precision and accuracy. By comparing the results from the titration method and IDMS, we sought to determine whether existing analytical procedures accepted by the International Atomic Energy Agency (IAEA) could be effectively translated to TRISO fuel forms. The team employed an approach that involved processing replicate TRISO samples, optimizing the milling (i.e., crushing) step and performing serial leaches. The elemental composition of the analytical samples was examined to prepare for interference studies in the second year of this project. The integration of gamma spectrometry to verify residual uranium activity further strengthened the validation. Statistical methods were applied to the collected data to evaluate the uncertainties arising from sampling, sample preparation and uranium quantification. These uncertainties were then compared to the IAEA’s international target values (ITVs). Additional data collected in upcoming project work will strengthen the uncertainty estimates. Ultimately, it is hoped that this project will contribute materially to the body of work related to characterization of TRISO based fuels for the purpose of material accountancy and its applications to international safeguards.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Demonstration of a Rapid HPLC-ICPMS Direct Coupling Technique Using IDMS- Project Report: Part II

Researchers working on chemical separations and inductively coupled plasma mass spectrometry have developed a rapid separation–direct analysis scheme to determine both concentration and isotopics of a suite of elements down to the low picogram level, with the ultimate goal of performing rapid analysis of postdetonation nuclear materials. The second phase in method development has shown that both the sensitivity and stability to achieve the precise, low-level analyses required can be maintained even when present in complex silicon- and uranium-based matrices. The methods analyte list has been expanded to incorporate a number of new analytes, notably the actinides plutonium, americium, curium, neptunium, and thorium and the key fission product zirconium. Key nonnatural fission product isotopic ratios in irradiated highly enriched uranium targets have been successfully measured at the low picogram level. The accuracy of these ratios was confirmed using an isotopic depletion and decay modeling software to within 1–2%.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2017

Demonstration of a Rapid HPLC-ICPMS Direct Coupling Technique Using IDMS-Project Report: Part I

Staff members working in chemical separations and inductively coupled plasma mass spectrometry have developed a rapid separation-direct analysis scheme to determine both concentration and isotopics of a suite of elements down to the low picogram level. To reach the goal of rapid analysis of post-detonation nuclear materials, this first phase in method development has shown both the sensitivity and stability to achieve the precise, low-level analyses required. By coupling a high pressure ion chromatography system to an inductively coupled plasma mass spectrometer, researchers can achieve online analysis of the separated components of the sample directly. Using theT hermo Scientific™ Qtegra™ analysis software, the data has been processed automatically to yield precise isotopic composition and concentrations.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2015

Production of highly-enriched 134Ba for a reference material for isotope dilution mass spectrometry measurements

Isotope dilution mass spectrometry (IDMS) is an analytical technique capable of providing accurate and precise quantitation of trace isotope abundance and assay providing measurement uncertainties below 1 %. To achieve these low uncertainties, the IDMS method ideally utilizes chemically pure “spike” solutions that consist of a single highly enriched isotope that is well-characterized relating to the abundance of companion isotopes and concentration in solution. To address a current demand for accurate 137Cs/137Ba ratio measurements for “age” determination of radioactive 137Cs sources, Idaho National Laboratory (INL) is producing enriched 134Ba isotopes that are tobe used for IDMS spikes to accurately determine 137Ba accumulation from the decay of 137Cs. The final objective of this work it to provide a homogenous set of reference materials that the National Institute of Standards and Technology can certify as standard reference materials used for IDMS. The process that was developed at INL for the separation and isolation of Ba isotopes, chemical purification of the isotopes in solution, and the encapsulation of the materials will be described.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2015

The electroweak phase transition in the Inert Doublet Model

We study the strength of a first-order electroweak phase transition in the Inert Doublet Model (IDM), where particle dark matter (DM) is comprised of the lightest neutral inert Higgs boson. We improve over previous studies in the description and treatment of the finite-temperature effective potential and of the electroweak phase transition. We focus on a set of benchmark models inspired by the key mechanisms in the IDM leading to a viable dark matter particle candidate, and illustrate how to enhance the strength of the electroweak phase transition by adjusting the masses of the yet undiscovered IDM Higgs states. We argue that across a variety of DM masses, obtaining a strong enough first-order phase transition is a generic possibility in the IDM. We find that due to direct dark matter searches and collider constraints, a sufficiently strong transition and a thermal relic density matching the universal DM abundance is possible only in the Higgs funnel regime.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Lake Bacterial Assemblage Composition Is Sensitive to Biological Disturbance Caused by an Invasive Filter Feeder

One approach to improve forecasts of how global change will affect ecosystem processes is to better understand how anthropogenic disturbances alter bacterial assemblages that drive biogeochemical cycles. Species invasions are important contributors to global change, but their impacts on bacterial community ecology are rarely investigated. Here, we studied direct impacts of invasive dreissenid mussels (IDMs), one of many invasive filter feeders, on freshwater lake bacterioplankton. We demonstrated that direct effects of IDMs reduced bacterial abundance and altered assemblage composition by preferentially removing larger and particle-associated bacteria. While this increased the relative abundances of many free-living bacterial taxa, some were susceptible to filter feeding, in line with efficient removal of phytoplankton cells of <2 μm. This selective removal of particle-associated and larger bacteria by IDMs altered inferred bacterial functional group representation, defined by carbon and energy source utilization. Specifically, we inferred an increased relative abundance of chemoorganoheterotrophs predicted to be capable of rhodopsin-dependent energy generation. In contrast to the few previous studies that have focused on the longer-term combined direct and indirect effects of IDMs on bacterioplankton, our study showed that IDMs act directly as a biological disturbance to which freshwater bacterial assemblages are sensitive. The negative impacts on particle-associated bacteria, which have been shown to be more active than free-living bacteria, and the inferred shifts in functional group representation raise the possibility that IDMs may directly alter bacterially mediated ecosystem functions.Freshwater bacteria play fundamental roles in global elemental cycling and are an intrinsic part of local food webs. Human activities are altering freshwater environments, and much has been learned regarding the sensitivity of bacterial assemblages to a variety of these disturbances. Yet, relatively few studies have focused on how species invasion, which is one of the most important aspects of anthropogenic global change, affects freshwater bacterial assemblages. This study focuses on the impact of invasive dreissenid mussels (IDMs), a globally distributed group of invasive species with large impacts on freshwater phyto- and zooplankton assemblages. Here, we show that IDMs have direct effects on lake bacterioplankton abundance, taxonomic composition, and inferred bacterial functional group representation.

16S rRNA gene↗
DOE OSTI2016

XSIM Final Report: Modelling the Past and Future of Identity Management for Scientific Collaborations

The eXtreme Science Identity Management (XSIM1) research project: collected and analyzed real world data on virtual organization (VO) identity management (IdM) representing the last 15+ years of collaborative DOE science; constructed a descriptive VO IdM model based on that data; used the model and existing trends to project the direction for IdM in the 2020 timeframe; and provided guidance to scientific collaborations and resource providers that are implementing or seeking to improve IdM functionality. XSIM conducted over 20 semi­structured interviews of representatives from scientific collaborations and resource providers, both in the US and Europe; the interviewees supported diverse set of scientific collaborations and disciplines. We developed a definition of “trust,” a key concept in IdM, to understand how varying trust models affect where IdM functions are performed. The model identifies how key IdM data elements are utilized in collaborative scientific workflows, and it has the flexibility to describe past, present and future trust relationships and IdM implementations. During the funding period, we gave more than two dozen presentations to socialize our work, encourage feedback, and improve the model; we also published four refereed papers. Additionally, we developed, presented, and received favorable feedback on three white papers providing practical advice to collaborations and/or resource providers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Microgrid Energy Management System Integration with Advanced Distribution Management System

The Integrated Distribution Management System (IDMS) project was initiated to demonstrate the interactive operation of microgrid systems and the distribution systems with which they interconnect. The key technologies for this are the microgrid management system and the utility distribution management system. The IDMS project successfully demonstrated that a utility’s advanced distribution management system/distributed energy resources management system (ADMS/DERMS) could effectively manage microgrids to provide visibility and control functionalities as well as use the microgrid as a dispatchable resource to support the utility grid. The DERMS accomplishes this by determining active and reactive power needs at the point of common coupling (PCC) using advanced applications like volt/VAR watt optimization (VVWO) and load relief (LR) with the underlying core applications state estimation (SE) and load flow (LF). The ADMS/DERMS can use the microgrid as a resource to resolve and prevent violations in the grid and to optimize the operational working state of the grid. The IDMS project demonstrated that a utility-operated ADMS with embedded DERMS functionality can flexibly manage a variety of microgrids and other aggregated distributed energy resources (DER) in concert with the wider distribution grid. Microgrids can provide grid services in any number of different ways to meet the operational needs of the distribution utility. The manner of aggregation — microgrid or virtual power plant — is not necessarily relevant to the utility as long as the grid services from the aggregated DER are available and can be managed by its ADMS/DERMS for the stability and reliability of the grid. The IDMS project demonstrated this integrated ADMS concept by combining hardware/software-in-the-loop testing with commercial products from different vendors and a utility’s network model. The project integrated the Schneider Electric EcoStruxure™ ADMS with DERMS with the Schweitzer Engineering Laboratories (SEL) POWERMAX ® Microgrid Control System, and the simulated resources with energy company PECO’s model of a utility-owned microgrid, establishing an operational relationship in which the utility manages the operational functionality of a microgrid at the PCC and that provides the utility with the capability to control the comprehensive power system, inclusive of the macrogrid and microgrid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

An islanding detection methodology combining decision trees and Sandia frequency shift for inverter-based distributed generations

Distributed generations (DGs) for grid-connected applications require an accurate and reliable islanding detection methodology (IDM) for secure system operation. This paper presents an IDM for grid-connected inverter-based DGs. The proposed method is a combination of passive and active islanding detection techniques for aggregation of their advantages and elimination/minimisation of the drawbacks. In the proposed IDM, the passive method utilises critical system attributes extracted from local voltage measurements at target DG locations as well as employs decision tree-based classifiers for characterisation and detection of islanding events. The active method is based on Sandia frequency shift technique and is initiated only when the passive method is unable to differentiate islanding events from other system events. Thus, the power quality degradation introduced into the system by active islanding detection techniques can be minimised. Furthermore, a combination of active and passive techniques allows detection of islanding events under low power mismatch scenarios eliminating the disadvantage associated with the use of passive techniques alone. Finally, detailed case study results demonstrate the effectiveness of the proposed method in detection of islanding events under various power mismatch scenarios, load quality factors and in the presence of single or multiple grid-connected inverter-based DG units.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Pulsed ion hall accelerator for investigation of reactions between light nuclei in the astrophysical energy range

The factors defining the constraints on the current characteristics of the magnetically insulated ion diode (IDM) are considered. The specific current parameters close to the maximum possible ones are obtained for the particular IDM-40 design assigned for acceleration of light ions and investigation of nuclear reactions with small cross sections in the astrophysical energy range (2–40 keV) in the entrance channel. It is experimentally demonstrated that the chosen optimal operation conditions for IDM-40 units provide high stability of the parameters (energy distribution and composition of accelerated particle beams, degree of neutralization) of the accelerated particle flux, which increases during the working pulse.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Real-World Driving Features for Identifying Intelligent Driver Model Parameters

Driver behavior models play a significant role in representing different driving styles and the associated relationships with traffic patterns and vehicle energy consumption in simulation studies. The models often serve as a proxy for baseline human driving when assessing energy-saving strategies that alter vehicle velocity. Such models are especially important in connectivity-enabled energy-saving strategy research because they can easily adapt to changing driving conditions like posted speed limits or change in traffic light state. While numerous driver models exist, parametric driver models provide the flexibility required to represent variability in real-world driving through different combinations of model parameters. These model parameters must be informed by a representative set of parameter values for the driver model to adequately represent a real-world driver. It stands to reason that determining the parameter values from real-world driving data would serve the purpose of representing a real-world driver. Although the published literature is replete with techniques and consequences of using real-world driving data to determine parameter values for parametric driver models, none have explored them in the context of using shorter driving features where the parameter values may change over the course of a single trip for the same driver. In this study we consider the “intelligent driver model” (IDM) as our driver behavior model and use real-world driving data from the Transportation Secure Data Center (TSDC) maintained at the National Renewable Energy Laboratory (NREL). The TSDC includes real-world travel data from across the United States, from which NREL has created a wide range of driving routes consisting of road features such as speed limits, stop locations, and turn locations. The real-world driving data are categorized into different driving regimes and extracted into driving features. The driving features are then used to calibrate the parameter values for the IDM. The distribution of the parameters and the relationships among them are reported. The insights obtained from this study enable judicious usage of IDM or similar parametric driver models to represent baseline human driver behavior in simulations.

27 ARPA - Advanced Research Projects Agency-Energy↗
DOE OSTI2021

Real-World Driving Features for Identifying Intelligent Driver Model Parameters: Preprint

Driver behavior models play a significant role in representing different driving styles and the associated relationships with traffic patterns and vehicle energy consumption in simulation studies. The models often serve as a proxy for baseline human driving when assessing energy-saving strategies that alter vehicle velocity. Such models are especially important in connectivity-enabled energy-saving strategy research because they can easily adapt to changing driving conditions like posted speed limits or change in traffic light state. While numerous driver models exist, parametric driver models provide the flexibility required to represent variability in real-world driving through different combinations of model parameters. These model parameters must be informed by a representative set of parameter values for the driver model to adequately represent a real-world driver. It stands to reason that determining the parameter values from real-world driving data would serve the purpose of representing a real-world driver. While the published literature is replete with techniques and consequences of using real-world driving data to determine parameter values for parametric driver models, none have explored them in the context of using shorter driving features where the parameter values may change over the course of a single trip for the same driver. In this study we consider the “Intelligent Driver Model” (IDM) as the driver behavior model to explore and real-world driving data from the Transportation Secure Data Center (TSDC) maintained at the National Renewable Energy Laboratory (NREL). The TSDC includes real-world travel data from across the United States, from which NREL has created a wide range of driving routes consisting of road features such as speed limits, stop locations and turn locations. The real-world driving data are categorized into different driving regimes and extracted into driving features. The driving features are then used to calibrate the parameter values for the IDM. The distribution of the parameters and the relationships among them are reported. The insights obtained from this study enable judicious usage of IDM or similar parametric driver models to represent baseline human driver behavior in simulations.

27 ARPA - Advanced Research Projects Agency-Energy↗
DOE OSTI2019

MR texture analysis: potential imaging biomarker for predicting the chemotherapeutic response of patients with colorectal liver metastases

Purpose: The purpose of the study was to determine whether the pre-treated MR texture features of colorectal liver metastases (CRLMs) are predictive of therapeutic response after chemotherapy. Methods: The study included twenty-six consecutive patients (a total of 193 liver metastasis) with unrespectable CRLMs at our institution from August 2014 to February 2016. Lesions were categorized into either responding group or non-responding group according to changes in size. Texture analysis was quantified on T2-weighted images by two radiologists with consensus on regions of interest which were manually drawn on the largest cross-sectional area of the lesions. Five histogram features (mean, variance, skewness, kurtosis, and entropy{sup 1}) and five gray level co-occurrence matrix features (GLCM; angular second moment (ASM), entropy{sup 2}, contrast, correlation, and inverse difference moment (IDM)) were extracted. The texture parameters were statistically analyzed to identify the differences between the two groups, and the potential predictive parameters to differentiate the responding group from the non-responding group were subsequently tested using multivariable logistic regression analysis. Results: A total of 107 responding and 86 non-responding lesions were evaluated. A higher variance, entropy{sup 1}, contrast, entropy{sup 2} and a lower ASM, correlation, IDM were independently (P < 0.05) associated with a good response to chemotherapy with the areas under the ROC curves (AUCs) of 0.602–0.784. Variance (P < 0.001) and ASM (P = 0.001) remained potential predictive values to discriminate responding lesions from non-responding lesions when tested using multivariable logistic regression analysis. The highest AUC of the predictors from the association of variance and ASM was 0.814. Conclusion: MR texture features on pre-treated T2 images have the potential to predict the therapeutic response of colorectal liver metastases.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

Online collection of LC effluent as droplets for automatic injection into ICP-MS

A sample introduction technique was developed to allow for online, dropwise injection of effluent into a mass spectrometer (MS). This allowed for the coupling of chromatography systems that were not driven by pumps without altering the set-up or separation performance. This capability combined the benefits of coupling separation and measurement while also enabling accurate chromatographic evaluation that would generally be performed offline. The incorporation of a flowing rinse into the system made dropwise resolution possible for any liquid capable of forming drops under ambient conditions. The technique was demonstrated utilizing gas pressurized extraction chromatography (GPEC) and inductively coupled plasma-time-of-flight mass spectrometry (ICP-TOFMS) to illustrate the qualitative applications for rapid separation development and procedure evaluation. This method's quantitative applications were evaluated using single and double isotope dilution mass spectrometry (IDMS) with an external mass bias correction to measure analytes across entire elutions including volumes as small as single drops. In conclusion, the total neodymium values afforded by both single and double IDMS were within the uncertainty of the calculated value for evaluation of full elution peaks and for most of the single drops analyzed that reached above 10k cps Nd-144.

GPEC↗
DOE OSTI2014

A systematic halo-independent analysis of direct detection data within the framework of Inelastic Dark Matter

We present a systematic halo-independent analysis of available Weakly Interacting Massive Particles (WIMP) direct detection data within the framework of Inelastic Dark Matter (IDM). We show that, when the smallest number of assumptions is made on the WIMP velocity distribution in the halo of our Galaxy, it is possible to find values of the WIMP mass and the IDM mass splitting for which compatibility between present constraints and any of the three experiments claiming to see a WIMP excess among DAMA, CDMS-Si and CRESST can be achieved.

79 ASTRONOMY AND ASTROPHYSICS↗