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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 OSTI2013

DarkLight radiation backgrounds

We report measurements of photon and neutron radiation levels observed while transmitting a 0.43 MW electron beam through millimeter-sized apertures and during beam-on, but accelerating gradient RF-on, operation. These measurements were conducted at the Free-Electron Laser (FEL) facility of the Jefferson National Accelerator Laboratory (JLab) using a 100 MeV electron beam from an energy-recovery linear accelerator. The beam was directed successively through 6 mm, 4 mm, and 2 mm diameter apertures of length 127 mm in aluminum at a maximum current of 4.3 mA (430 kW beam power). This study was conducted to characterize radiation levels for experiments that need to operate in this environment, such as the proposed DarkLight Experiment. We find that sustained transmission of a 430 kW CW beam through a 2 mm aperture is feasible with manageable beam-related backgrounds. We also find that during beam-off, RF-on operation, field emission inside the niobium cavities of the accelerator cryomodules is the primary source of ambient radiation.

43 PARTICLE ACCELERATORS↗
DOE OSTI2013

PROBING THE COSMIC X-RAY AND MeV GAMMA-RAY BACKGROUND RADIATION THROUGH THE ANISOTROPY

While the cosmic soft X-ray background is very likely to originate from individual Seyfert galaxies, the origin of the cosmic hard X-ray and MeV gamma-ray background is not fully understood. It is expected that Seyferts including Compton thick population may explain the cosmic hard X-ray background. At MeV energy range, Seyferts having non-thermal electrons in coronae above accretion disks or MeV blazars may explain the background radiation. We propose that future measurements of the angular power spectra of anisotropy of the cosmic X-ray and MeV gamma-ray backgrounds will be key to deciphering these backgrounds and the evolution of active galactic nuclei (AGNs). As AGNs trace the cosmic large-scale structure, spatial clustering of AGNs exists. We show that e-ROSITA will clearly detect the correlation signal of unresolved Seyferts at 0.5-2 keV and 2-10 keV bands and will be able to measure the bias parameter of AGNs at both bands. Once future hard X-ray all sky satellites achieve a sensitivity better than 10{sup –12} erg cm{sup –2} s{sup –1} at 10-30 keV or 30-50 keV—although this is beyond the sensitivities of current hard X-ray all sky monitors—angular power spectra will allow us to independently investigate the fraction of Compton-thick AGNs in all Seyferts. We also find that the expected angular power spectra of Seyferts and blazars in the MeV range are different by about an order of magnitude, where the Poisson term, so-called shot noise, is dominant. Current and future MeV instruments will clearly disentangle the origin of the MeV gamma-ray background through the angular power spectrum.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Effect of natural gamma background radiation on portal monitor radioisotope unmixing

It is well known that national security relies on several layers of protection. One of the most important is the traffic control at borders and ports that exploits Radiation Portal Monitors (RPMs) to detect and deter potential smuggling attempts. Most portal monitors rely on plastic scintillators to detect gamma rays. Despite their poor energy resolution, their cost effectiveness and the possibility of growing them in large sizes make them the gamma-ray detector of choice in RPMs. Unmixing algorithms applied to organic scintillator spectra can be used to reliably identify the bare and unshielded radionuclides that triggered an alarm, even with fewer than 1000 detected counts and in the presence of two or three nuclides at the same time. In this work, we experimentally studied the robustness of a state-of-the-art unmixing algorithm to different radiation background spectra, due to varying atmospheric conditions, in the 16 °C to 28 °C temperature range. In the presence of background, the algorithm is able to identify the nuclides present in unknown radionuclide mixtures of three nuclides, when at least 1000 counts from the sources are detected. With fewer counts available, we found larger differences of approximately 35.9% between estimated nuclide fractions and actual ones. In these low count rate regimes, the uncertainty associated by our algorithm with the identified fractions could be an additional valuable tool to determine whether the identification is reliable or a longer measurement to increase the signal-to-noise ratio is needed. Moreover, the algorithm identification performances are consistent throughout different data sets, with negligible differences in the presence of background types of different intensity and spectral shape.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2017

Pattern Discovery in Internet Background Radiation

Internet Background Radiation (IBR) is observed in empty network address spaces. No traffic should arrive there, but it does in overwhelming quantities, gathering evidences of attacks, malwares and misconfigurations. The study of IBR helps to detect spreading network problems, common vulnerabilities and attack trends. However, network traffic data evolves quickly and is of high volume and diversity, i.e., an outstanding big data challenge. When used to assist network security, it also requires the online classification of dynamic streaming data. In this paper, we introduce an AGgregation & Mode (AGM) vector to represent network traffic. The AGM format characterizes IP hosts by extracting aggregated and mode values of IP header fields, and without inspecting payloads. We performed clustering and statistical analysis to explore six months of IBR from 2012 with the AGM mapping. The discovered patterns allow building a classification of IBR, which identifies phenomena that have been actively polluting the Internet for years. The AGM representation is light and tailored for monitoring and pattern discovery. We show that AGM vectors are suitable to analyze large volumes of network traffic: they capture permanent operations, such as long term scanning, as well as bursty events from targeted attacks and short term incidents.

Iglesias, Felix↗
DOE OSTI2020

Development of Gamma Background Radiation Digital Twin with Machine Learning Algorithms: Application of Unsupervised Machine Learning to Detection of Anomalies and Nuisances in Gamma Background Radiation Environmental Screening Data

Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. The measurement data is a 2D matrix, where one dimension is gamma ray energy, and the other dimension is the number of measurements or total time. In principle, gamma radiation sources can be detected and identified from the measured data by their unique spectral lines. Detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. The objective of this work is to explore unsupervised machine learning (ML) algorithms for development of a digital twin of gamma radiation background, and for detection and identification of weak nuisances and anomalies events in the presence of highly fluctuating background. In one segment of work, we developed a gamma background estimation model using a Longshort term memory (LSTM) network for one-step CPS time series prediction. The LSTM model was validated with two data sets of measurements from two independent NaI detectors positioned on a mobile platform. The data sets contained background radiation only and no orphan isotope sources. The LSTM model was constructed and tested using data from one of the detectors. Performance of the LSTM model was validate through one-step prediction of CPS time series of another NaI detector without re-training. This approach allows to create a digital twin for nuclear background estimation. Using LSTM, it could be possible to detect a source through subtraction of the estimated counts from the measured background. In another segment of work, we investigated detection of gamma emitting sources in the presence of complex background using unsupervised machine learning. Spectral lines of isotopes are difficult to observe in one-second measurements. Averaging over the entire measurement campaign data set reveals spectral lines of most common background isotopes. Spectral lines of orphan sources, which might appear only in a few measurements during the campaign, will be washed out if averaging is performed over the entire measurement data set. The approach we have explored consists of extracting one-second measurements containing weak spectral features through data clustering. Averaging one-second spectra in a cluster should reveal the presence of anomaly sources. We created two ML models using K-means clustering and Neural Network Self-organizing Map (SOM). Performance of these ML models was benchmarked using search data. One data set contained 137 Cs source, and another dataset contained 131 I source.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

A shallow underground laboratory for low-background radiation measurements and materials development

Pacific Northwest National Laboratory recently commissioned a new shallow underground laboratory, located at a depth of approximately 30 meters-water-equivalent. This new addition to the small class of radiation measurement laboratories located at modest underground depths houses the latest generation of custom-made, high-efficiency, low-background gamma-ray spectrometers and gas proportional counters. This paper describes the unique capabilities present in the shallow underground laboratory; these include large-scale ultra-pure materials production and a suite of radiation detection systems. Reported data characterize the degree of background reduction achieved through a combination of underground location, graded shielding, and rejection of cosmic-ray events. We conclude by presenting measurement targets and future opportunities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Radiation Backgrounds at Cosmic Dawn: X-Rays from Compact Binaries

We compute the expected X-ray diffuse background and radiative feedback on the intergalactic medium (IGM) from X-ray binaries prior to and during the epoch of reionization. The cosmic evolution of compact binaries is followed using a population synthesis technique that treats separately neutron stars and black hole binaries in different spectral states and is calibrated to reproduce the observed X-ray properties of galaxies at z ≲ 4. Together with an updated empirical determination of the cosmic history of star formation, recent modeling of the stellar mass–metallicity relation, and a scheme for absorption by the IGM that accounts for the presence of ionized H ii bubbles during the epoch of reionization, our detailed calculations provide refined predictions of the X-ray volume emissivity and filtered radiation background from “normal” galaxies at z ≳ 6. Radiative transfer effects modulate the background spectrum, which shows a characteristic peak between 1 and 2 keV. Because of the energy dependence of photoabsorption, soft X-ray photons are produced by local sources, while more energetic radiation arrives unattenuated from larger cosmological volumes. While the filtering of X-ray radiation through the IGM slightly increases the mean excess energy per photoionization, it also weakens the radiation intensity below 1 keV, lowering the mean photoionization and heating rates. Numerical integration of the rate and energy equations shows that the contribution of X-ray binaries to the ionization of the bulk IGM is negligible, with the electron fraction never exceeding 1%. Direct He i photoionizations are the main source of IGM heating, and the temperature of the largely neutral medium in between H ii cavities increases above the temperature of the cosmic microwave background (CMB) only at z ≲ 10, when the volume filling factor of H ii bubbles is already ≳0.1. Therefore, in this scenario, it is only at relatively late epochs that neutral intergalactic hydrogen may be observable in 21 cm emission against the CMB.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

THE MYSTERY OF THE COSMIC DIFFUSE ULTRAVIOLET BACKGROUND RADIATION

The diffuse cosmic background radiation in the Galaxy Evolution Explorer far-ultraviolet (FUV, 1300-1700 Å) is deduced to originate only partially in the dust-scattered radiation of FUV-emitting stars: the source of a substantial fraction of the FUV background radiation remains a mystery. The radiation is remarkably uniform at both far northern and far southern Galactic latitudes and increases toward lower Galactic latitudes at all Galactic longitudes. We examine speculation that this might be due to interaction of the dark matter with the nuclei of the interstellar medium, but we are unable to point to a plausible mechanism for an effective interaction. We also explore the possibility that we are seeing radiation from bright FUV-emitting stars scattering from a ''second population'' of interstellar grains—grains that are small compared with FUV wavelengths. Such grains are known to exist, and they scatter with very high albedo, with an isotropic scattering pattern. However, comparison with the observed distribution (deduced from their 100 μm emission) of grains at high Galactic latitudes shows no correlation between the grains' location and the observed FUV emission. Our modeling of the FUV scattering by small grains also shows that there must be remarkably few such ''smaller'' grains at high Galactic latitudes, both north and south; this likely means simply that there is very little interstellar dust of any kind at the Galactic poles, in agreement with Perry and Johnston. We also review our limited knowledge of the cosmic diffuse background at ultraviolet wavelengths shortward of Lyα—it could be that our ''second component'' of the diffuse FUV background persists shortward of the Lyman limit and is the cause of the reionization of the universe.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Radiation portal monitor data file format for comprehensive background radiation monitoring

Radiation portal monitors (RPMs) are widely used at border security checkpoints to detect the presence of radioactive materials in people, vehicles, and cargo. Typically, RPM detection systems consist of two pillars equipped with gamma and neutron detectors. To improve detection efficiency, RPMs employ techniques such as a limited energy window, dynamic alarm thresholds, and lead shielding. However, without continuous monitoring of background radiation, signal interpretation can be compromised, because environmental factors and mechanical failures can cause fluctuations. Here, we introduce a daily file format that logs gamma background and neutron background radiation levels continuously over a 24 h period; this format is different from traditional formats that record data only when the RPM is active or occupied. The approach enables RPM operators and analysts to (1) identify and diagnose malfunctioning components, (2) adjust system settings to account for dynamic environmental factors, and (3) use the recorded data to characterize outer space phenomena. Continuous background reporting is essential for identifying issues such as faulty connections, voltage divider failures, and errors in background updates. Continuous background reporting also enables the detection of external influences, including nearby X-ray scanners, temperature fluctuations, rainfall, cosmic radiation, and lunar phase changes. These data files are designed to be easily evaluated and parsed using common tools, and a quick review by an expert is often sufficient for problem diagnosis. We anticipate that continuous background radiation monitoring and these new strategies will significantly improve the accuracy and reliability of RPM systems, reducing the rate of false alarms and enhancing overall system performance.

Background radiation monitoring↗
DOE OSTI2016

Predicting Solar Modulation Potentials for Modeling Cosmic Background Radiation

The modeling of the detectability of special nuclear material (SNM) at ports and border crossings requires accurate knowledge of the background radiation at those locations. Background radiation originates from two main sources, cosmic and terrestrial. Cosmic background is produced by high-energy galactic cosmic rays (GCR) entering the atmosphere inducing a cascade of particles that eventually impact the earth's surface. The solar modulation potential represents one of the primary inputs to modeling cosmic background radiation. Usoskin et al. formally define solar modulation potential as 'the mean energy loss [per unit charge, in units of megavolts (MV),] of a cosmic ray particle inside the heliosphere...'. Modulation potential, a function of elevation, location, and time, shares an inverse relationship with cosmic background radiation. As a result, radiation detector background thresholds require adjustment to account for differing background levels, caused in part by differing solar modulations. Failure to do this can result in higher rates of false positives and failed detection of SNM during low and high levels of solar modulation potential, respectively. This study focuses on solar modulation's time dependence and seeks the best method to predict modulation for future dates. The best method will be incorporated into NINESIM, a discrete event simulator. An in-depth description of NINESIM is beyond the scope and purpose of this paper. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

DNDO Report: Predicting Solar Modulation Potentials for Modeling Cosmic Background Radiation

The modeling of the detectability of special nuclear material (SNM) at ports and border crossings requires accurate knowledge of the background radiation at those locations. Background radiation originates from two main sources, cosmic and terrestrial. Cosmic background is produced by high-energy galactic cosmic rays (GCR) entering the atmosphere and inducing a cascade of particles that eventually impact the earth’s surface. The solar modulation potential represents one of the primary inputs to modeling cosmic background radiation. Usosokin et al. formally define solar modulation potential as “the mean energy loss [per unit charge] of a cosmic ray particle inside the heliosphere…” Modulation potential, a function of elevation, location, and time, shares an inverse relationship with cosmic background radiation. As a result, radiation detector thresholds require adjustment to account for differing background levels, caused partly by differing solar modulations. Failure to do so can result in higher rates of false positives and failed detection of SNM for low and high levels of solar modulation potential, respectively. This study focuses on solar modulation’s time dependence, and seeks the best method to predict modulation for future dates using Python. To address the task of predicting future solar modulation, we utilize both non-linear least squares sinusoidal curve fitting and cubic spline interpolation. This material will be published in transactions of the ANS winter meeting of November, 2016.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Cancer Mortality Among People Living in Areas With Various Levels of Natural Background Radiation

There are many places on the earth, where natural background radiation exposures are elevated significantly above about 2.5 mSv/year. The studies of health effects on populations living in such places are crucially important for understanding the impact of low doses of ionizing radiation. This article critically reviews some recent representative literature that addresses the likelihood of radiation-induced cancer and early childhood death in regions with high natural background radiation. The comparative and Bayesian analysis of the published data shows that the linear no-threshold hypothesis does not likely explain the results of these recent studies, whereas they favor the model of threshold or hormesis. Neither cancers nor early childhood deaths positively correlate with dose rates in regions with elevated natural background radiation.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2016

LOWER BOUND ON THE COSMIC TeV GAMMA-RAY BACKGROUND RADIATION

The Fermi gamma-ray space telescope has revolutionized our understanding of the cosmic gamma-ray background radiation in the GeV band. However, investigation on the cosmic TeV gamma-ray background radiation still remains sparse. Here, we report the lower bound on the cosmic TeV gamma-ray background spectrum placed by the cumulative flux of individual detected extragalactic TeV sources including blazars, radio galaxies, and starburst galaxies. The current limit on the cosmic TeV gamma-ray background above 0.1 TeV is obtained as 2.8 × 10{sup −8}(E/100 GeV){sup −0.55} exp(−E/2100GeV)[GeV cm{sup −2} s{sup −1} sr{sup −1}] < E{sup 2}dN/dE < 1.1 × 10{sup −7}(E/100 GeV){sup −0.49} [GeV cm{sup −2} s{sup −1} sr{sup −1}], where the upper bound is set by requirement that the cascade flux from the cosmic TeV gamma-ray background radiation can not exceed the measured cosmic GeV gamma-ray background spectrum. Two nearby blazars, Mrk 421 and Mrk 501, explain ∼70% of the cumulative background flux at 0.8–4 TeV, while extreme blazars start to dominate at higher energies. We also provide the cumulative background flux from each population, i.e., blazars, radio galaxies, and starburst galaxies which will be the minimum requirement for their contribution to the cosmic TeV gamma-ray background radiation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

Preliminary Background Radiation Observations Procedure

This procedure will provide guidance concerning the collection of preliminary background radiation data for the Second Line of Defense (SLD) Program. Making preliminary background radiation observations is important during initial visits where radiation portal monitors (RPMs) are being considered for installation to highlight clear problem areas of high radiation that could impact RPM performance. The information collected during initial site surveys is used to document clear problem areas and guide design discussions with the stakeholders during the visit. This information also helps to guide the conceptual design of proposed locations for RPM and secondary inspection sites. This procedure groups the processes of the preliminary background radiation observations into the following steps: 1. previsit preparations and logistics, 2. procedures, and 3. use of data.

Instrumentation Related to Nuclear Science & Techn↗
DOE OSTI2022

An LSTM Deep Learning Network for ¿Background Radiation Prediction

Determination of appropriate background radiation is important in any measurement application. Environmental radiation monitors and monitors used to assess dose to individuals outside of controlled areas are particularly susceptible to changes in readings due to fluctuations in the environmental conditions. These fluctuations (e.g. radon progeny concentrations) lead to changes in the detector response in the actual radiation environment, and they need to be taken into account when extracting the net operational doses. Work has been ongoing to apply advances in Deep Learning and Artificial Intelligence to account for changes in detector responses based on environmental parameters; in particular, a Long-Short Term Memory (LSTM) Deep Learning architecture has been utilized to incorporate time-series data into a prediction model. In this work, we present the current status of the project to predict radiation measurements based on meteorological conditions and air packet trajectories extracted using the National Oceanic and Atmospheric Administration's (NOAA) Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT4) model.

Degtiarenko, Pavel↗
DOE OSTI2020

Evaluating Use of the NASA Nowcastof Atmospheric Ionizing Radiation for Aviation Safety (NAIRAS) System for Verifying/Validating AMS Cosmic Background Radiation Measurements, RSLA-006-20, Year 1

This presentation will be presented at FY 2020 SDRD Annual (Webex) Meeting scheduled for September 23–24, 2020. Evaluating Use of the NASA Nowcastof Atmospheric Ionizing Radiation for Aviation Safety (NAIRAS) System for Verifying/Validating AMS Cosmic Background Radiation Measurements, RSLA-006-20, Year 1

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗