Search NASA⌕ Search

SEARCH · Search NASA

Results for “proliferation detection”

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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Quantum Devices for Neutrino and Rare Particle Detection (Final Report)

This report summarizes the technical work completed under the DOE-QuanISED program. This grant allowed the MIT group --and associated groups on the project, including UMass Amherst and Argonne National Laboratory -- to explore the use of superconducting bolometers for the purpose of neutrino and low mass dark matter detection. These low threshold bolometric detection techniques have wide applicability in nuclear and particle physics, including searching for low mass weakly-interacting dark matter; detecting neutrinos via coherent neutrino scattering; searching for axions and nuclear non-proliferation. In addition, we explored how using techniques readily used by the quantum computing community–such as multiplexed microwave resonators and quantum amplifiers—could be used as a low noise readout scheme for an array of superconducting detectors. We briefly summarized the accomplishments under the project, and what future research directions have spawned from this research.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Parallel Multi-Omics in High-Risk Subjects for the Identification of Integrated Biomarker Signatures of Type 1 Diabetes

Background: Biomarkers are crucial for detecting early type-1 diabetes (T1D) and preventing significant β-cell loss before the onset of clinical symptoms. Here, we present proof-of-concept studies to demonstrate the potential for identifying integrated biomarker signature(s) of T1D using parallel multi-omics. Methods: Blood from human subjects at high risk for T1D (and healthy controls; n = 4 + 4) was subjected to parallel unlabeled proteomics, metabolomics, lipidomics, and transcriptomics. The integrated dataset was analyzed using Ingenuity Pathway Analysis (IPA) software for disturbances in the at-risk subjects compared to controls. Results: The final quadra-omics dataset contained 2292 proteins, 328 miRNAs, 75 metabolites, and 41 lipids that were detected in all samples without exception. Disease/function enrichment analyses consistently indicated increased activation, proliferation, and migration of CD4 T-lymphocytes and macrophages. Integrated molecular network predictions highlighted central involvement and activation of NF-κB, TGF-β, VEGF, arachidonic acid, and arginase, and inhibition of miRNA Let-7a-5p. IPA-predicted candidate biomarkers were used to construct a putative integrated signature containing several miRNAs and metabolite/lipid features in the at-risk subjects. Conclusions: Preliminary parallel quadra-omics provided a comprehensive picture of disturbances in high-risk T1D subjects and highlighted the potential for identifying associated integrated biomarker signatures. With further development and validation in larger cohorts, parallel multi-omics could ultimately facilitate the classification of T1D progressors from non-progressors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

SVM-Based Synchronized Fault Detection for 100% Renewable Microgrids: Preprint

Traditional protection schemes face significant challenges when applied to microgrids with high penetrations of renewables with inverter-based resources (IBRs). The proliferation of advanced sensing and communication technologies has generated copious data, offering an opportunity to overcome these limitations using data-driven machine learning approaches. This work proposes a novel approach based on a support vector machine (SVM) for detecting faults within a 100% renewable microgrid. The approach encompasses a systematic offline training stage for the development of a linear SVM-based fault detection algorithm. This process covers offline data collection from the microgrid under study, the extraction of features such as positive- and negative-sequence components and the total harmonic distortion of the voltage and current measurements of the relays, and the design of the linear SVM-based classifier. During the online implementation, however, different classifiers can exhibit asynchronicity in detecting the fault inception at different subcycle-to-cycle period-level delays. To circumvent this asynchronicity issue, a separate algorithm is developed for each relay to estimate the fault inception time as close to the real fault time. The performance of the proposed SVM-based synchronized fault detection method is evaluated using online time-domain simulation studies on a microgrid test system. The results corroborate the reliability of the fault detection scheme when tested under various fault cases (fault types, locations, and impedances) and non-fault cases during both grid-tied and islanded operation modes.

100% microgrid↗
DOE OSTI2020

Innovation in Radiological Security, Part 1 of 2 – Using a Cloud Solution to Compress the Timely Detection Model

The design and implementation of new security technologies must account for numerous and complex operational challenges. For example, traditionally isolated systems must now survive amid the proliferation of network connectivity and endure the dynamic environments created by organizations tolerating bring-your-own-device policies. When evaluating the cyber, physical, or cyber-physical security of an asset, a common practice in the security industry is to apply the Timely Detection Model (TDM)—a versatile concept that relates the security functions of detection, delay, and response to the progression of an oppositional force’s attack timeline. If implemented correctly, security enhancements can compress the TDM to offer efficiencies to the stakeholders responsible for adjudicating threat scenarios. The efficiencies gained by the response force allow for more effective protection strategies to be realized. One such enhancement, deployed within the radiological security domain—the Sentry-Remote Monitoring System (Sentry-RMS)—is a stand-alone security system that detects, assesses, and communicates priority alarms as a means of thwarting internal and external threats. The SEntry-RMS CommUnications and REsponse (Sentry-SECURE) platform—an optional feature of the Sentry-RMS—is being developed to facilitate more efficient alarm adjudication by site stakeholders and, if necessary, a faster response by law enforcement. This Cloud-hosted platform receives protected information from deployed Sentry-RMS units and relays it to stakeholders that have vested interests in maintaining an elevated level of situational awareness. Operationally, this enables real-time delivery of high-priority alarm and video imagery directly to an identified response stakeholder, such as local law enforcement or site management, via natively developed mobile applications or full platform integration. The Sentry-SECURE platform, as implemented by the U.S. Department of Energy’s Office of Radiological Security, is an example of an innovative security technology that compresses the TDM by (1) enabling a more efficient time to target and (2) better informing a response force’s predetermined tactics, techniques, and procedures. This paper explores the platform’s operational roles, highlights its principal functions, and presents a use case that demonstrates how the platform provides enhanced situational awareness when adjudicating priority alarms.

Sentry-RMS, Timely Detection Model, Sentry-SECURE↗
DOE OSTI2024

Utilizing a Virtual Sodium-Cooled Fast Reactor Digital Twin to Aid in Diversion Pathway Analysis for International Safeguards Applications

We report digital twin technology has the potential to improve the effectiveness of international safeguards inspectors by providing a tool which can: first, perform an accurate diversion path analysis, identify their indicators, and required sensors to detect them; and second, monitor facilities in real-time using critical data streams that benefit from this safeguards-by-design approach. Safeguards inspectors are required to visit facilities and verify the nuclear material to ensure no diversion has taken place and detect misuse of the facility; however, this analysis and verification effort is time consuming, and with limited funding it is imperative that time spent at a nuclear facility is focused on key areas. A virtual digital twin of three prototypic sodium fast reactors was developed, where diversion and misuse scenarios were explored to determine how a digital twin could provide inspectors with an understanding of how proliferation may occur and where the most likely areas for proliferation would be. For each of the three reactors, an optimization algorithm was able to find core designs which would be difficult to detect via sensors alone; however, the use of a machine learning adapter provided by the digital twin was able to show general trends in where proliferation as likely to take place.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Radiation Detection Data Competition Report

In FY2018 through FY2020, NA-22, the Defense Nuclear Nonproliferation Research and Development Program, funded a Data Science project to develop and implement statistical methodology to effectively host data competitions with the goal of leveraging the opportunity provided by crowdsourcing. By accessing and engaging expertise from a broader research community, there is an opportunity to attract innovative solutions from a variety of different research disciplines to advance the ability to solve important non-proliferation problems. This report summarizes the key results of this project after hosting two data competitions focused on urban radiation detection. The first competition was focused on attracting participants from the U.S. national laboratories, while the second, hosted by TopCoder, was open to the broader international community and awarded prize money to the top 10 competitors. At the start of the project, there was strong interest from NA-22 to explore and develop the capability to host data competitions as a means of leveraging the broader community to solve important nuclear nonproliferation problems. Having a standard data set on which to compare different approaches based on clearly defined criteria was desirable to be able to evaluate the state of solutions for important problems. Initially, it was not clear that it would even be possible logistically and bureaucratically to host a competition with an international field of competitors and to award the prize money needed to attract solutions from top competitors. Happily, a path to host the competitions was ultimately found that allowed this powerful accelerator of improvements to be leveraged.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2020

Gene Expression Thresholds Derived From Short-term Exposures Identify Rat Liver Tumorigens

Abstract Traditional methods for cancer risk assessment are resource-intensive, retrospective, and not feasible for the vast majority of environmental chemicals. In this study, we investigated whether quantitative genomic data from short-term studies may be used to set protective thresholds for potential tumorigenic effects. We hypothesized that gene expression biomarkers measuring activation of the key early events in established pathways for rodent liver cancer exhibit cross-chemical thresholds for tumorigenesis predictive for liver cancer risk. We defined biomarker thresholds for 6 major liver cancer pathways using training sets of chemicals with short-term genomic data (3–29 days of exposure) from the TG-GATES (n = 77 chemicals) and DrugMatrix (n = 86 chemicals) databases and then tested these thresholds within and between datasets. The 6 pathway biomarkers represented genotoxicity, cytotoxicity, and activation of xenobiotic, steroid, and lipid receptors (aryl hydrocarbon receptor, constitutive activated receptor, estrogen receptor, and peroxisome proliferator-activated receptor α). Thresholds were calculated as the maximum values derived from exposures without detectable liver tumor outcomes. We identified clear response values that were consistent across training and test sets. Thresholds derived from the TG-GATES training set were highly predictive (97%) in a test set of independent chemicals, whereas thresholds derived from the DrugMatrix study were 96%–97% predictive for the TG-GATES study. Threshold values derived from an abridged gene list (2/biomarker) also exhibited high predictive accuracy (91%–94%). These findings support the idea that early genomic changes can be used to establish threshold estimates or “molecular tipping points” that are predictive of later-life health outcomes.

Hill, III,, Thomas↗
DOE OSTI2020

Integrating Data Sources for Improved Safeguards and Accountancy of Electrochemical Fuel Reprocessing Systems. Final Report

Electrochemical reprocessing (also commonly known as “pyroprocessing”) of used nuclear fuel is an alternative to aqueous reprocessing that confers a number of advantages, including the ability to process more recently-discharged fuel, smaller resultant waste volumes, and the lack of isolation of plutonium in the product stream. While electrochemical reprocessing systems have seen a significant research and development effort, nuclear safeguards and security of these systems remains under-developed, particularly given the significant differences in operating environment and process flowsheet compared with established aqueous methods. Objective 4 of DOE’s nuclear energy research and development activities in Nuclear Energy Research and Development Roadmap is: “Understand and minimize the risks of nuclear proliferation and terrorism.” Material Control & Accountancy (MC&A) programs at nuclear processing plants deter and detect theft and diversion of nuclear material by both outside and inside adversaries. Empirical modeling and data analytics of online measurements and state indicators can improve the timeliness of detection and reduce the uncertainty in accountancy measures. To support the development and demonstration of such methods, data are needed that capture expected measurement values collected throughout electrochemical reprocessing facilities. A review of the available literature of current research in measurements for electrochemical reprocessing systems identified twenty-two candidate measurement methodologies, which characterize fuel/salt composition, concentrations of various isotopes and elements, and operational parameters throughout the reprocessing facility. Four primary measurement methodologies have been simulated based on either physical simulations or empirical correlations: gamma emissions, neutron emissions, hybrid k-edge densitometry (HKED), and cyclic voltammetry. Initial investigation into the use of these measures for process monitoring and detection suggests the approach is viable and worthy of further investigation. This report summarizes efforts to generate signatures of key measurements during operation of electrochemical reprocessing facilities and initial investigation of data analytics to support process monitoring, diversion detection, and accountancy.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Challenges in Automated Detection of COVID-19 Misinformation

The COVID-19 pandemic has made the dangers of the spread of misinformation obvious but despite much global effort to curbing its spread, fake information about the pandemic keeps proliferating. In this paper, we address the development of automated methods for verification of claims about COVID-19 and discuss the challenges associated with this task. We focus on labeled data collection, limitations of existing models, and difficulties of applying misinformation detection models in practical applications. Our initial analysis indicates label imbalance may be a particular challenge for developing claim verification models and we discuss options for alleviating this issue.

Herrmannova, Dasha↗
DOE OSTI2026

Sensor Reduction for Diversion Detection in a Realistic Heat Pipe Microreactor Using Supervised Machine Learning

Microreactors are designed as a smaller, cheaper, and safer alternative to traditional nuclear power plants. Their non-traditional characteristics and prospect of mass production and deployment will likely require new approaches to nuclear safeguards. The primary proliferation concern with microreactors is the diversion of fuel material. Such diversion may produce measurable defects in key physical attributes like neutron flux, which may in turn be detectable using machine learning models. Preliminary work has demonstrated this ability for modeled nominal and diversion scenarios using large quantities of energy integrated neutron flux data. In practice, the number of available sensors for such measurements will be limited and energy integrated flux information will not be available. This work explores the ability of tree-based gradient boosted ensemble models to classify a given microreactor core is nominal or diversion, and determine the number of fuel pins diverted in the case of diversion with reduced numbers of sensors and more realistic detector responses. Classification accuracy of greater than 98% and regression errors as low as 5% of the total number of fuel pins were achieved with as few as 15 sensors, compared to 99% and 4.1% with a maximum of 240 sensors.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Demonstration of active neutron interrogation of special nuclear materials using a high-intensity short-pulse-laser-driven neutron source

Detecting shielded special nuclear material, such as nuclear explosives, is a difficult challenge pursued by non-proliferation, anti-terrorism, and nuclear security programs worldwide. Interrogation with intense fast-neutron pulses is a promising method to characterize concealed nuclear material rapidly but is limited by suitable source availability and proven instrumentation. In this study we have pioneered a demonstration of such an interrogation method using a high-intensity, short-pulse, laser-driven neutron source that offers potential benefits compared to conventional neutron sources. The measurement results reported here represent the first experimental demonstration of this interrogation approach on enriched uranium items and demonstrate the feasibility of a precise measurement using realistic nuclear materials, representative of field scenarios, even with just a single laser-driven neutron pulse. Bright pulsed sources can overcome the nuisance background of items with strong internal neutron sources, improving analytical power, while single-shot assay is attractive in high-throughput situations where time is at a premium. The science and technology of this type of neutron production is developing rapidly, and we anticipate that practical mobile interrogation systems will become available based on the detection concepts demonstrated here to meet the growing measurement needs.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2023

Keeping LANL at the forefront of list mode capability for safeguards and MC&A [Slides]

Neutron based detection forms key capability to enable and support international and domestic nuclear safeguards and non-proliferation missions. Key stakeholders include International Atomic Energy Agency (IAEA), European Atomic Energy Community (EURATOM), regional safeguards inspectorates, domestic stakeholders. LANL has been historically a leader in development of Non-destructive Assay (NDA) instruments and associated data acquisition hardware and software.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2021

High expression of Notch2 drives tongue squamous cell carcinoma carcinogenesis

Tongue squamous cell carcinoma (TSCC) is one of the most common cancers in the oral cavity. Notch signaling is frequently dysregulated in cancer. However, the role of Notch2 in TSCC is not well understood. The aim of this study was to investigate the effect of abnormal expression of Notch2 in TSCC. The expression of Notch2 was tested in 47 pairs of tissues from tongue cancer and normal samples by using immunohistochemical staining. Tongue cancer cells were transfected with siRNA or plasmid. The proliferation of the cells was tested by the CCK8 assay and colony formation assay. Subcutaneous tumor model was established to observe tumor growth. Transwell assay was used to detect the changes of cell migration and invasion ability. A humanized anti-Notch2 antibody was used to TSCC cells. We found that Notch2 was upregulated in tongue carcinoma tissues. Knocking down the expression of Notch2 by siRNA in the TSCC cell lines decreased proliferation ability both in vitro and in vivo. In addition, migration and invasion abilities were inhibited by knockdown of Notch2 in the TSCC cells. However, overexpression of Notch2 increased tongue cancer cell proliferation, invasion and migration. The humanized anti-Notch2 antibody inhibited TSCC cell growth. The results indicated that Notch2 is an oncogene in tongue squamous cell carcinoma and may become the target of a new approach for treating TSCC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Electrical sensing, tracking, and actuation of droplets

Devices, techniques, and processes are disclosed that use electrical impedance to detect of the presence and contents of droplets including cells, nucleic acids, proteins, or solute concentrations in an array of retrievable, trackable, trapped droplets in a fluidic system. Electrodes may be positioned underneath individual droplet traps in a microchannel to assay droplet contents and/or actuating droplets for the release of the droplets from corresponding traps. The disclosed technology may be used for detection of the results of solvent extraction processes including time-dependent quantification of metal ion concentration in the aqueous and organic phases, for wastewater treatment, heavy metal detection, pharmaceutical industry, and/or biotechnology, or for environmental monitoring of wastewater for toxic metal, monitoring of biological cell viability and proliferation, monitoring of extraction processes used in heavy metal mining, monitoring of extraction processes used in nuclear fuel processing, monitoring kinetics of enzyme processes, and/or assessing pharmacodynamics and drug efficacy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Model predictive control for voltage restoration in microgrids using temporal logic specifications

Power system operation will encounter numerous voltage variabilities as the proliferation of renewable energy continues. Real-time monitoring and communication technologies can potentially improve voltage stability by enabling the rapid detection of voltage deviations and the implementation of corrective actions. These corrective actions will only be effective in restoring stability if they are chosen in a timely and scalable manner. This paper considers the problem of power systems’ load voltage control in order to simultaneously address both magnitude and time voltage specifications. In order to comply with grid codes and avoid unnecessary relay protection actions, a model predictive control (MPC)-based control strategy employing temporal logic specifications (TLSs) is proposed. The TLSs strategy is introduced as a formalism to control the voltage variation at a critical load bus against operational bounds over time. The control objective is to schedule optimal control input signals from the available supportive energy storage systems, which provide reactive power injections, leading to satisfying the specified finite-time restoration described by the TLSs with minimal control efforts. The simulation results display that the TLSs strategy for power systems’ voltage control synthesis is extremely significant.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Evaluation of material accountancy techniques for 233 Pa from thorium nuclear fuels

Thorium is a promising alternative to uranium as nuclear fuel with advantages such as higher abundance, lower production of long-lived transuranic elements, and potentially better proliferation resistance. However, thorium presents a potential pathway for proliferation where produced 233 Pa can be diverted for the clandestine production of safeguarded 233 U. To prevent this, the ability to detect and measure 233 Pa must be assessed. This paper reviews several nuclear material accountancy techniques to determine their suitability for detecting 233 Pa extracted from irradiated thorium fuel. Hybrid K-edge densitometry and passive gamma spectroscopy have been found to be the best options based on technology maturity, cost, accuracy, and acquisition time. Thorium can be used in various reactor designs such as pressurized water reactors (PWRs), Canada deuterium uranium (CANDU) reactors, and molten salt reactors (MSRs). Therefore, thorium-uranium oxide fueling was modeled for three representative reactors (PWR, CANDU, MSR), burning the fuel to 47 GWd/MTHM for PWR, 19 GWd/MTHM for CANDU, and at a steady power of 52.711 MW/MTHM for MSR. Within each model, the protactinium element in the used fuel was extracted and its isotopic content analyzed. Simulated results indicated that 233 Pa can be detected using passive gamma spectroscopy in each fuel type at all decay times (0–300 days) following separation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Incomplete radiofrequency ablation induced chemoresistance by up-regulating heat shock protein 70 in hepatocellular carcinoma

Highlights: • iRFA treatment inhibited cisplatin-induced pyroptosis of HCC cells. • Heat shock protein 70 was involved in the suppression of NLRP3 activation. • iRFA treatment decreased the cisplatin sensitivity of HCC through regulating HSP70. Radiofrequency ablation (RFA) is a common minimally invasive treatment for hepatocellular carcinoma (HCC). Incomplete RFA (iRFA) due to the sub-lethal heat shock challenge of some cell populations leads to the generation of transformed survivor cells with enhanced chemoresistance. However, the underlying mechanism of iRFA on HCCs chemoresistance remains unknown. In the present study, we investigated the effect of iRFA on HCCs sensitivity to cisplatin. Cells treated with the sub-lethal heat shock challenge were used to mimic iRFA treatment in vitro. An orthotopic implantation HCC model was established and also performed iRFA treatment. Flow cytometry, transwell assay, and cell counting kit-8 assay were used to determine the effect of iRFA treatment on cisplatin-induced HCC cell apoptosis, invasion, and cell viability. ELISA and Western blot were used to detect the effect of iRFA treatment on cisplatin-induced HCC cell pyroptosis. We found that iRFA treatment increased the HCC cell proliferation and invasion ability, and inhibited cisplatin-induced pyroptosis. Further experiments showed that iRFA treatment induced upregulation of HSP70, which inhibited the cisplatin-induced NLRP3 inflammasome activation, leading to inhibition of pyroptosis. HSP70 knockdown or NLRP3 overexpression could reverse the effect of iRFA treatment in vitro. In vivo, HSP70 knockdown reversed the chemosensitivity of HCC to cisplatin, which was decreased by iRFA. In conclusion, we demonstrated that iRFA induced drug resistance by HSP70-mediated inhibition of cell pyroptosis in HCC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Optimizing the sensitivity of high repetition rate broadband transient optical spectroscopy with modified shot-to-shot detection

A major limitation of transient optical spectroscopy is that relatively high laser fluences are required to enable broadband, multichannel detection with acceptable signal-to-noise levels. Under typical experimental conditions, many condensed phase and nanoscale materials exhibit fluence-dependent dynamics, including higher order effects such as carrier–carrier annihilation. With the proliferation of commercial laser systems, offering both high repetition rates and high pulse energies, have come new opportunities for high sensitivity pump-probe measurements at low pump fluences. However, experimental considerations needed to fully leverage the statistical advantage of these laser systems have not been fully described. Here, we demonstrate a high repetition rate, broadband transient spectrometer capable of multichannel shot-to-shot detection at 90 kHz. Importantly, we find that several high-speed cameras exhibit a time-domain fixed pattern noise resulting from interleaved analog-to-digital converters, which is particularly detrimental to the conventional “ON/OFF” modulation scheme used in pump-probe spectroscopy. Using a modified modulation and data processing scheme, we achieve a noise level of 10−5 in 4 s for differential transmission, an order of magnitude lower than for commercial 1 kHz transient spectrometers for the same acquisition time. We leverage the high sensitivity of this system to measure the differential transmission of monolayer graphene at low pump fluence. We show that signals on the order of 10−6 OD can be measured, enabling a new data acquisition regime for low-dimensional materials.

47 OTHER INSTRUMENTATION↗