SEARCH · Search NASA
Results for “background radiation estimation”
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.
Estimating radiological background using imaging spectroscopy
Optical imaging spectroscopy is investigated as a method to estimate radiological background by spectral identification of soils, sediments, rocks, minerals and building materials derived from natural materials and assigning tabulated radiological emission values to these materials. Radiological airborne surveys are undertaken by local, state and federal agencies to identify the presence of radiological materials out of regulatory compliance. Detection performance in such surveys is determined by (among other factors) the uncertainty in the radiation background; increased knowledge of the expected radiation background will improve the ability to detect low-activity radiological materials. Radiological background due to naturally occurring radiological materials (NORM) can be estimated by reference to previous survey results, use of global 40K, 238U, and 232Th (KUT) values, reference to existing USGS radiation background maps, or by a moving average of the data as it is acquired. Each of these methods has its drawbacks: previous survey results may not include recent changes, the global average provides only a zero-order estimate, the USGS background radiation map resolutions are coarse and are accurate only to 1 km – 25 km sampling intervals depending on locale, and a moving average may essentially low pass filter the data to obscure small changes in radiation counts. Imaging spectroscopy from airborne or spaceborne platforms can offer higher resolution identification of materials and background, as well as provide imaging context information. AVIRIS hyperspectral image data is analyzed using commercial exploitation software to determine the usefulness of imaging spectroscopy to identify qualitative radiological background emissions when compared to airborne radiological survey data.
A hierarchical Bayesian model for background variation in radiation source localization
In this paper, we apply a new model to account for varying background radiation in radiological source localization. We present a hierarchical Bayesian model that simultaneously infers background and source location parameters without requiring separate estimation of the background radiation at each detector location. We employ a simplified photon transport model to reduce the computational expense of Bayesian model calibration. Furthermore, we demonstrate the model accuracy by localizing a cesium-137 source in a simulated city block, and we analyze experimental field measurements with varying background. In both cases, the model provides sufficient fidelity that we can locate the source while simultaneously estimating background radiation.
miniTimeCube as a neutron scatter camera
We present Monte Carlo (MC) simulation results from a study of a compact plastic-scintillator detector suitable for imaging fast neutrons in the 1 – 10 MeV energy range: the miniTimeCube (mTC). Originally designed for antineutrino detection, the mTC consists of 24 MultiChannel Plate (MCP) photodetectors surrounding a 13 cm cube of boron-doped plastic scintillator. Our simulation results show that waveform digitization of 1536 optically sensitive channels surrounding the scintillator should allow for spatiotemporal determination of individual neutron-proton scatters in the detector volume to ~ 100 picoseconds and ~5 mm. A Bayesian estimation framework is presented for multiple-scatter reconstruction, and is used to estimate the incoming direction and energy of simulated individual neutrons. Finally, we show how populations of reconstructed neutrons can be used to estimate the direction and energy spectrum of nearby simulated neutron sources.
Background Conditions Influence the Estimated Cloud Radiative Effects of Anthropogenic Aerosol Emissions From Different Source Regions
Abstract Using the Community Earth System Model, with the Community Atmosphere Model version 5.3, we investigate the cloud radiative effects of anthropogenic aerosols emitted from different source regions and global shipping. We also analyze aerosol burdens, cloud condensation nuclei concentration, liquid water path, and ice water path. Due to transboundary transport and sublinearity in the response of clouds to aerosols, the cloud radiative effects of emissions from a given source region are influenced by emissions from other source regions. For example, the shortwave cloud radiative effect of shipping is −0.39 ± 0.03 W/m 2 when other anthropogenic emissions sources are present (the “present‐day background” assumption) compared with −0.60 ± 0.03 W/m 2 when other anthropogenic emissions sources are absent (the “natural background” assumption). In general, the cloud radiative effects are weaker if present‐day background conditions are assumed compared with if natural background conditions are assumed. Assumptions about background conditions should be carefully considered when investigating the climate impacts of aerosol emissions from a given source region.
Estimating Public Dose Along Hypothetical Spent Nuclear Fuel Transportation Routes
In the future, it will be necessary to transport large quantities of spent nuclear fuel (SNF) from nuclear power plant sites to an interim storage facility (ISF) or a repository when such a facility is available. Because it is impossible to shield all of the radiation from this material, the general public will receive a very small, but quantifiable, dose from this transportation campaign. This paper describes the estimated collective effective radiation dose to the public due to SNF shipments under routine conditions and compares the estimated dose figures to the natural background radiation dose. To determine the estimated collective effective dose to the public, this analysis uses the US Department of Energy's (DOE) Stakeholder Tool for Assessing Radioactive Transportation (START), a geographic information system (GIS) routing tool, and a set of unit dose factors (UDFs) which were developed to calculate the estimated dose to the public along transportation routes. The estimated doses of radiation to which the public would be exposed during shipments of SNF is expected to be a consideration, along with many other factors, when making routing decisions. In all cases studied in this paper, estimated doses to the public will be orders of magnitude lower than the natural background radiation dose and will meet all US federal regulatory requirements for radiation dose/exposure to members of the public. The sample routes analyzed in this paper are expected to be representative of future SNF shipment routes in terms of length and mode of transportation, although they do not represent actual routes or destinations. This paper considers four routes from two shutdown reactor sites to two destinations. It must be noted that the specified origin sites are not necessarily the first sites under consideration for a de-inventory process. Further, the destination sites reviewed in this report are only to illustrate estimated dose figures along different routes and should not be taken as potential sites for an ISF or repository. For illustrative purposes only, the shortest distance rail route was found between each origin and destination point, and the collective effective dose to the public from the SNF cask was estimated along each route. This paper is not intended to make recommendations for routing decisions, but rather is intended to inform further discussion about the transportation of SNF and other radioactive materials.
Engineering a modular 44 Ti/ 44 Sc generator: eluate evaluation in preclinical models and estimation of human radiation dosimetry
Background: 44 Sc/ 47 Sc is an attractive theranostic pair for targeted in vivo positron emission tomographic (PET) imaging and beta-particle treatment of cancer. The 44 Ti/ 44 Sc generator allows daily onsite production of this diagnostic isotope, which may provide an attractive alternative for PET facilities that lack in-house irradiation capabilities. Early animal and patient studies have demonstrated the utility of 44 Sc. In our current study, we built and evaluated a novel clinical-scale 44 Ti/ 44 Sc generator, explored the pharmacokinetic profiles of 44 ScCl 3 , [ 44 Sc]-citrate and [ 44 Sc]-NODAGA (1,4,7-triazacyclononane,1-glutaric acid-4,7-acetic acid) in naïve mice, and estimated the radiation burden of 44 ScCl 3 in humans. Methods: 44 Ti/ 44 Sc (101.2 MBq) in 6 M HCl solution was utilized to assemble a modular ZR resin containing generator. After assembly, 44 Sc was eluted with 0.05 M HCl for further PET imaging and biodistribution studies in female Swiss Webster mice. Based on the biodistribution data, absorbed doses of 44 / 47 ScCl 3 in human adults were calculated for 18 organs and tissues using the IDAC-Dose software. Results: 44 Ti in 6 M HCl was loaded onto the organic resin generator with a yield of 99.97%. After loading and initial stabilization, 44 ScCl 3 was eluted with 0.05 M HCl in typical yields of 82.9 ± 5.3% (N = 16), which was normalized to the estimated generator capacity. Estimated generator capacity was computed based on elution time interval and the total amount of 44 Ti loaded on the generator. Run in forward and reverse directions, the 44 Sc/ 44 Ti ratio from a primary column was significantly improved from 1038 ± 440 to 3557 ± 680 (Bq/Bq) when a secondary, replaceable, ZR resin cartridge was employed at the flow outlet. In vivo imaging and ex vivo distribution studies of the reversible modular generator for 44 ScCl 3 , [ 44 Sc]-citrate and [ 44 Sc]-NODAGA show that free 44 Sc remained in the circulation significantly longer than the chelated 44 Sc. The dose estimation of 44 ScCl 3 reveals that the radiation burden is 0.146 mSv/MBq for a 70 kg adult male and 0.179 mSv/MBq for a 57 kg adult female. Liver, spleen and heart wall will receive the highest absorbed dose: 0.524, 0.502, and 0.303 mGy/MBq, respectively, for the adult male. Conclusions: A clinical-scale 44 Ti/ 44 Sc generator system with a modular design was developed to supply 44 ScCl 3 in 0.05 M HCl, which is suitable for further radiolabeling and in vivo use. Our data demonstrated that free 44 ScCl 3 remained in the circulation for extended periods, which resulted in approximately 10 times greater radiation burden than stably chelated 44 Sc. Stable 44 Sc/ 47 Sc-complexation will be more favorable for in vivo use and for clinical utility.
The XFaster Power Spectrum and Likelihood Estimator for the Analysis of Cosmic Microwave Background Maps
We present the XFaster analysis package, XFaster is a fast, iterative angular power spectrum estimator based on a diagonal approximation to the quadratic Fisher matrix estimator. XFaster uses Monte Carlo simulations to compute noise biases and filter transfer functions and is thus a hybrid of both Monte Carlo and quadratic estimator methods. In contrast to conventional pseudo-C ℓ based methods, the algorithm described here requires a minimal number of simulations, and does not require them to be precisely representative of the data to estimate accurate covariance matrices for the bandpowers. The formalism works with polarization-sensitive observations and also data sets with identical, partially overlapping, or independent survey regions. The method was first implemented for the analysis of BOOMERanG data (Netterfield et al. 2002; Jones et al. 2006), and also used as part of the Planck analysis (Rocha et al. 2011). Here, we describe the full, publicly available analysis package, written in Python, as developed for the analysis of data from the 2015 flight of the SPIDER instrument (SPIDER Collaboration 2021). The package includes extensions for self-consistently estimating null spectra and for estimating fits for Galactic foreground contributions. We show results from the extensive validation of XFaster using simulations, and its application to the SPIDER data set.
Investigation of the effect of noise parameters of a 3D lidar on the error in estimating relief signatures of distant objects from 2D field intensity distributions of reflected radiation
We consider the influence of noise parameters of a 3D lidar and external background radiation on the error in estimating the relief signatures of distant objects from 2D field intensity distributions of the reflected radiation. A physical and mathematical model is developed to analyse the effect of noise. The dependence of the error in estimating the relief signatures at various signal-to-noise ratios is investigated taking into account the parameters of real multi-element photodetectors (MEPDs). The obtained results indicate the possibility of evaluating relief signatures of distant objects with high accuracy based on standard MEPDs simultaneously for a large number of points on the object’s surface with a signal-to-noise ratio of more than 4. (paper)
Misclassification of primary liver cancer in the Life Span Study of atomic bomb survivors
Primary liver cancer is difficult to diagnose accurately at death, due to metastases from nearby organs and to concomitant diseases, such as chronic hepatitis and cirrhosis. Trends in diagnostic accuracy could affect radiation risk estimates for incident liver cancer by altering background rates or by impacting risk modification by sex and age. We quantified the potential impact of death‐certificate inaccuracies on radiation risk estimates for liver cancer in the Life Span Study of atomic bomb survivors. True‐positive and false‐negative rates were obtained from a previous study that compared death‐certificate causes of death with those based on pathological review, from 1958 to 1987. We assumed various scenarios for misclassification rates after 1987. We obtained estimated true positives and estimated false negatives by stratified sampling from binomial distributions with probabilities given by the true‐positive and false‐negative rates, respectively. Poisson regression methods were applied to highly stratified person‐year tables of corrected case counts and accrued person years. During the study period (1958–2009), there were 1,885 cases of liver cancer, which included 383 death‐certificate‐only (DCO) cases; 1,283 cases with chronic liver disease as the underlying cause of death; and 150 DCO cases of pancreatic cancer among 105,444 study participants. Across the range of scenarios considered, radiation risk estimates based on corrected case counts were attenuated, on average, by 13–30%. Our results indicated that radiation risk estimates for liver cancer were potentially sensitive to death‐certificate inaccuracies. Additional data are needed to inform misclassification rates in recent years.
Network Algorithms for Detection of Radiation Sources
In support of national defense, Domestic Nuclear Detection Office’s (DNDO) Intelligent Radiation Sensor Systems (IRSS) program supported the development of networks of radiation counters for detecting, localizing and identifying low-level, hazardous radiation sources. Industry teams developed the first generation of such networks with tens of counters, and demonstrated several of their capabilities in indoor and outdoor characterization tests. Subsequently, these test measurements have been used in algorithm replays using various sub-networks of counters. Test measurements combined with algorithm outputs are used to extract Key Measurements and Benchmark (KMB) datasets. We present two selective analyses of these datasets: (a) a notional border monitoring scenario that highlights the benefits of a network of counters compared to individual detectors, and (b) new insights into the Sequential Probability Ratio Test (SPRT) detection method, which lead to its adaptations for improved detection. Using KMB datasets from an outdoor test, we construct a notional border monitoring scenario, wherein twelve 2”*2” NaI detectors are deployed on the periphery of 21*21meter square region. A Cs-137 (175 uCi) source is moved across this region, starting several meters from outside and finally moving away. The measurements from individual counters and the network were processed using replays of a particle filter algorithm developed under IRSS program. The algorithm outputs from KMB datasets clearly illustrate the benefits of combining measurements from all networked counters: the source was detected before it entered the region, during its trajectory inside, and until it moved several meters away. When individual counters are used for detection, the source was detected for much shorter durations, and sometimes was missed in the interior region. The application of SPRT for detecting radiation sources requires choosing the detection threshold, which in turn requires a source strength estimate, typically specified as a multiplier of the background radiation level. A judicious selection of this source multiplier is essential to achieve optimal detection probability at a specified false alarm rate. Typically, this threshold is chosen from the Receiver Operating Characteristic (ROC) by varying the source multiplier estimate. ROC is expected to have a monotonically increasing profile between the detection probability and false alarm rate. We derived ROCs for multiple indoor tests using KMB datasets, which revealed an unexpected loop shape: as the multiplier increases, detection probability and false alarm rate both increase until a limit, and then both contract. Consequently, two detection probabilities correspond to the same false alarm rate, and the higher is achieved at a lower multiplier, which is the desired operating point. Using the Chebyshev’s inequality we analytically confirm this shape. Then, we present two improved network-SPRT methods by (a) using the threshold off-set as a weighting factor for the binary decisions from individual detectors in a weighted majority voting fusion rule, and (b) applying a composite SPRT derived using measurements from all counters.
A New Approach to Reduce Uncertainties in Space Radiation Cancer Risk Predictions
The prediction of space radiation induced cancer risk carries large uncertainties with two of the largest uncertainties being radiation quality and dose-rate effects. In risk models the ratio of the quality factor (QF) to the dose and dose-rate reduction effectiveness factor (DDREF) parameter is used to scale organ doses for cosmic ray proton and high charge and energy (HZE) particles to a hazard rate for γ-rays derived from human epidemiology data. In previous work, particle track structure concepts were used to formulate a space radiation QF function that is dependent on particle charge number Z, and kinetic energy per atomic mass unit, E. QF uncertainties where represented by subjective probability distribution functions (PDF) for the three QF parameters that described its maximum value and shape parameters for Z and E dependences. Here I report on an analysis of a maximum QF parameter and its uncertainty using mouse tumor induction data. Because experimental data for risks at low doses of γ-rays are highly uncertain which impacts estimates of maximum values of relative biological effectiveness (RBE max ), I developed an alternate QF model, denoted QF γAcute where QFs are defined relative to higher acute γ-ray doses (0.5 to 3 Gy). The alternate model reduces the dependence of risk projections on the DDREF, however a DDREF is still needed for risk estimates for high-energy protons and other primary or secondary sparsely ionizing space radiation components. Risk projections (upper confidence levels (CL)) for space missions show a reduction of about 40% (CL~50%) using the QF γAcute model compared the QFs based on RBE max and about 25% (CL~35%) compared to previous estimates. In addition, I discuss how a possible qualitative difference leading to increased tumor lethality for HZE particles compared to low LET radiation and background tumors remains a large uncertainty in risk estimates.
A Revised Look at Relativistic Electrons in the Earth's Inner Radiation Zone and Slot Region
We describe a new, more accurate procedure for estimating and removing inner zone background contamination from Van Allen Probes Magnetic Electron Ion Spectrometer (MagEIS) radiation belt measurements. This new procedure is based on the underlying assumption that the primary source of background contamination in the electron measurements at L shells less than three, energetic inner belt protons, is relatively stable. Since a magnetic spectrometer can readily distinguish between foreground electrons and background signals, we are able to exploit the proton stability to construct a model of the background contamination in each MagEIS detector by only considering times when the measurements are known to be background dominated. We demonstrate, for relativistic electron measurements in the inner zone, that the new technique is a significant improvement upon the routine background corrections that are used in the standard MagEIS data processing, which can “overcorrect” and therefore remove real (but small) electron fluxes. As an example, we show that the previously reported 1-MeV injection into the inner zone that occurred in June of 2015 was distributed more broadly in L and persisted in the inner zone longer than suggested by previous estimates. Such differences can have important implications for both scientific studies and spacecraft engineering applications that make use of MagEIS electron data in the inner zone at relativistic energies. We compare these new results with prior work and present more recent observations that also show a 1-MeV electron injection into the inner zone following the September 2017 interplanetary shock passage.
Effects of incomplete residential histories on studies of environmental exposure with application to childhood leukaemia and background radiation
Highlights: • Residential exposures are most important for many environmental carcinogens. • Direct measurement in all occupied homes is the gold standard but may be impractical. • About half of cases of childhood cancer have not moved between birth and diagnosis. • Most house movements are short-range; exposures in successive houses are correlated. • Analyses using exposure estimation from a single address are informative. When evaluating environmental exposures, residential exposures are often most relevant. In most countries, it is impossible to establish full residential histories. In recent publications, childhood leukaemia and background radiation have been studied with and without full residential histories. This paper investigates the consequences of lacking such full data. Data from a nationwide Finnish Case-Control study of Childhood Leukaemia and gamma rays were analysed. This included 1093 children diagnosed with leukaemia in Finland in 1990–2011. Each case was matched by gender and year of birth to three controls. Full residential histories were available. The dose estimates were based on outdoor background radiation measurements. The indoor dose rates were obtained with a dwelling type specific conversion coefficient and the individual time-weighted mean red bone marrow dose rates were calculated using age-specific indoor occupancy and the age and gender of the child. Radiation from Chernobyl fallout was included and a 2-year latency period assumed. The median separation between successive dwellings was 3.4 km and median difference in red bone marrow dose 2.9 nSv/h. The Pearson correlation between the indoor red bone marrow dose rates of successive dwellings was 0.62 (95% CI 0.60, 0.64). The odds ratio for a 10 nSv/h increase in dose rate with full residential histories was 1.01 (95% CI 0.97, 1.05). Similar odds ratios were calculated with dose rates based on only the first dwelling (1.02, 95% CI 0.99, 1.05) and only the last dwelling (1.00, 95% CI 0.98, 1.03) and for subjects who had lived only in a single dwelling (1.05, 95% CI 0.98, 1.10). Knowledge of full residential histories would always be the option of choice. However, due to the strong correlation between exposure estimates in successive dwellings and the uncertainty about the most relevant exposure period, estimation of overall exposure level from a single address is also informative. Error in dose estimation is likely to cause some degree of classical measurement error resulting in bias towards the null.
A neural-network based estimator to search for primordial non-Gaussianity in Planck CMB maps
We present an upgraded combined estimator, based on Minkowski Functionals and Neural Networks, with excellent performance in detecting primordial non-Gaussianity in simulated maps that also contain a weighted mixture of Galactic contaminations, besides real pixel's noise from Planck cosmic microwave background radiation data. We rigorously test the efficiency of our estimator considering several plausible scenarios for residual non-Gaussianities in the foreground-cleaned Planck maps, with the intuition to optimize the training procedure of the Neural Network to discriminate between contaminations with primordial and secondary non-Gaussian signatures. We look for constraints of primordial local non-Gaussianity at large angular scales in the foreground-cleaned Planck maps. For the SMICA map we found f{sub NL} = 33 ± 23, at 1σ confidence level, in excellent agreement with the WMAP-9yr and Planck results. In addition, for the other three Planck maps we obtain similar constraints with values in the interval f{sub NL} element of [33, 41], concomitant with the fact that these maps manifest distinct features in reported analyses, like having different pixel's noise intensities.
Modeling Radiation Detection Using a Mixed-Effects Statistical Model for Background Variation
In this paper, we consider radiation source localization in an urban environment as an inverse problem and use Bayesian parameter estimation techniques to infer the source location and intensity. Since parameter estimation generally requires a large number of model evaluations, we employ a simplified photon transport model, as in a 2017 paper by Stefanescu, et al., to reduce computational requirements. However, the model in the 2017 paper does not account for the physical reality that background radiation varies with position within an urban locale. We incorporate statistical mixed-effects modeling into the simplified transport equation from the Stefanescu, et al. paper to reflect individual variation among the background radiation measurements at multiple detector locations. With our new model, we use a Bayesian DRAM-within-Gibbs technique, which incorporates the Delayed Rejection Adaptive Metropolis (DRAM) algorithm, to estimate the mixed-effects parameters. We note that without adequate prior information, we were unable to simultaneously estimate the set of parameters corresponding to the source intensity, source location, and individual background radiation counts. By calibrating the background in the absence of a source, we obtained narrow prior distributions, which permitted us to jointly infer the source intensity and location and the background radiation distribution.
A Parametric Analysis of Factors Affecting Calculations of Estimated Dose Rates from Spent Nuclear Fuel Shipments - 16458
Planning for transportation of SNF requires estimation of the radiation dose to the members of the public associated with the transportation. This dose is expected to be very low compared to natural background radiation because dose rates and exposure durations are minimal. A preliminary investigation was performed to estimate the dose rate from a SNF transportation package as a function of distance and evaluate factors affecting the estimated dose rate, such as local environment modeling. Effects on the dose rate are determined for changes in temperature and relative humidity of the air surrounding a transportation package and for different compositions of the ground underneath it. The impact of different vapor content in air was evaluated to be small, within the statistical uncertainty of the dose rate estimates. The neutron dose rate contributions from scattering interactions within different soil/pavement materials were from approximately 20% to 70% at 25 cm from the ground and from approximately 10% to 40% at 175 cm from the ground. The effect of photon scattering interactions within different soil/pavement materials was an increase in photon dose rate of less than 20% at 25 cm from the ground and less than 10% at 175 cm from the ground. The impact of different ground materials on the total dose rate would depend on the relative contributions of photon and neutron dose rates to the total dose rate. (authors)
Epidemiological research on radiation-induced cancer in atomic bomb survivors
The late effects of exposure to atomic bomb radiation on cancer occurrence have been evaluated by epidemiological studies on three cohorts: a cohort of atomic bomb survivors (Life Span Study; LSS), survivors exposed in utero, and children of atomic bomb survivors (F1). The risk of leukemia among the survivors increased remarkably in the early period after the bombings, especially among children. Increased risks of solid cancers have been evident since around 10 years after the bombings and are still present today. The LSS has clarified the dose– response relationships of radiation exposure and risk of various cancers, taking into account important risk modifiers such as sex, age at exposure, and attained age. Confounding by conventional risk factors including lifestyle differences is not considered substantial because people were non-selectively exposed to the atomic bomb radiation. Uncertainty in risk estimates at low-dose levels is thought to be derived from various sources, including different estimates of risk at background levels, uncertainty in dose estimates, residual confounding and interaction, strong risk factors, and exposure to residual radiation and/or medical radiation. The risk of cancer in subjects exposed in utero is similar to that in LSS subjects who were exposed in childhood. Regarding hereditary effects of radiation exposure, no increased risk of cancers associated with parental exposure to radiation have been observed in the F1 cohort to date. In addition to biological and pathogenetic interpretations of the present results, epidemiological investigations using advanced technology should be used to further analyze these cohorts.