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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Cross-correlation of CMB Polarization Lensing with High-$z$ Submillimeter $Herschel$-ATLAS Galaxies

Herein we report a 4.8σ measurement of the cross-correlation signal between the cosmic microwave background (CMB) lensing convergence reconstructed from measurements of the CMB polarization made by the P OLARBEAR experiment and the infrared-selected galaxies of the $Herschel$-ATLAS survey. This is the first measurement of its kind. We infer a best-fit galaxy bias of $b$ = 5.76 ± 1.25, corresponding to a host halo mass of log 10 (M h /M ⊙ ). =13.5$^{+0.2}_{-0.3}$ at an effective redshift of $z$ ~ 2 from the cross-correlation power spectrum. Residual uncertainties in the redshift distribution of the submillimeter galaxies are subdominant with respect to the statistical precision. We perform a suite of systematic tests, finding that instrumental and astrophysical contaminations are small compared to the statistical error. This cross-correlation measurement only relies on CMB polarization information that, differently from CMB temperature maps, is less contaminated by galactic and extragalactic foregrounds, providing a clearer view of the projected matter distribution. This result demonstrates the feasibility and robustness of this approach for future high-sensitivity CMB polarization experiments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Deep Learning of Dark Energy Spectroscopic Instrument Mock Spectra to Find Damped Lyα Systems

We have updated and applied a convolutional neural network (CNN) machine-learning model to discover and characterize damped Ly α systems (DLAs) based on Dark Energy Spectroscopic Instrument (DESI) mock spectra. We have optimized the training process and constructed a CNN model that yields a DLA classification accuracy above 99% for spectra that have signal-to-noise ratios (S/N) above 5 per pixel. The classification accuracy is the rate of correct classifications. This accuracy remains above 97% for lower S/N ≈1 spectra. This CNN model provides estimations for redshift and H i column density with standard deviations of 0.002 and 0.17 dex for spectra with S/N above 3 pixel -1 . Also, this DLA finder is able to identify overlapping DLAs and sub-DLAs. Further, the impact of different DLA catalogs on the measurement of baryon acoustic oscillations (BAO) is investigated. The cosmological fitting parameter result for BAO has less than 0.61% difference compared to analysis of the mock results with perfect knowledge of DLAs. This difference is lower than the statistical error for the first year estimated from the mock spectra: above 1.7%. We also compared the performances of the CNN and Gaussian Process (GP) models. Our improved CNN model has moderately 14% higher purity and 7% higher completeness than an older version of the GP code, for S/N > 3. Both codes provide good DLA redshift estimates, but the GP produces a better column density estimate by 24% less standard deviation. A credible DLA catalog for the DESI main survey can be provided by combining these two algorithms.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

INTEGRAL Detection of the First Prompt Gamma-Ray Signal Coincident with the Gravitational-wave Event GW170817

We report the INTernational Gamma-ray Astrophysics Laboratory ( INTEGRAL ) detection of the short gamma-ray burst GRB 170817A (discovered by Fermi -GBM) with a signal-to-noise ratio of 4.6, and, for the first time, its association with the gravitational waves (GWs) from binary neutron star (BNS) merging event GW170817 detected by the LIGO and Virgo observatories. The significance of association between the gamma-ray burst observed by INTEGRAL and GW170817 is 3.2σ, while the association between the Fermi -GBM and INTEGRAL detections is 4.2σ. GRB 170817A was detected by the SPI-ACS instrument about 2 s after the end of the GW event. We measure a fluence of (1.4 ± 0.4 ± 0.6) × 10{sup −7} erg cm{sup −2} (75–2000 keV), where, respectively, the statistical error is given at the 1σ confidence level, and the systematic error corresponds to the uncertainty in the spectral model and instrument response. We also report on the pointed follow-up observations carried out by INTEGRAL , starting 19.5 hr after the event, and lasting for 5.4 days. We provide a stringent upper limit on any electromagnetic signal in a very broad energy range, from 3 keV to 8 MeV, constraining the soft gamma-ray afterglow flux to <7.1 × 10{sup −11} erg cm{sup −2} s{sup −1} (80–300 keV). Exploiting the unique capabilities of INTEGRAL , we constrained the gamma-ray line emission from radioactive decays that are expected to be the principal source of the energy behind a kilonova event following a BNS coalescence. Finally, we put a stringent upper limit on any delayed bursting activity, for example, from a newly formed magnetar.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Characterizing and Mitigating Intraday Variability: Reconstructing Source Structure in Accreting Black Holes with mm-VLBI

The extraordinary physical resolution afforded by the Event Horizon Telescope has opened a window onto the astrophysical phenomena unfolding on horizon scales in two known black holes, M87* and Sgr A*. However, with this leap in resolution has come a new set of practical complications. Sgr A* exhibits intraday variability that violates the assumptions underlying Earth aperture synthesis, limiting traditional image reconstruction methods to short timescales and data sets with very sparse (u, v) coverage. We present a new set of tools to detect and mitigate this variability. We develop a data-driven, model-agnostic procedure to detect and characterize the spatial structure of intraday variability. This method is calibrated against a large set of mock data sets, producing an empirical estimator of the spatial power spectrum of the brightness fluctuations. We present a novel Bayesian noise modeling algorithm that simultaneously reconstructs an average image and statistical measure of the fluctuations about it using a parameterized form for the excess variance in the complex visibilities not otherwise explained by the statistical errors. These methods are validated using a variety of simulated data, including general relativistic magnetohydrodynamic simulations appropriate for Sgr A* and M87*. We find that the reconstructed source structure and variability are robust to changes in the underlying image model. We apply these methods to the 2017 EHT observations of M87*, finding evidence for variability across the EHT observing campaign. The variability mitigation strategies presented are widely applicable to very long baseline interferometry observations of variable sources generally, for which they provide a data-informed averaging procedure and natural characterization of inter-epoch image consistency.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

An automated integrated web-based smart tool for open stope design

The Stability Graph is a widely used tool for the design of open stopes in underground mining. Many users of the Stability Graph still apply this design method manually. Although the manual approach has benefits, using multiple graphs and stability number computation charts for each stope surface is time-consuming, even for the experienced mining engineer. Current practice in the use of the method also limits data sharing. This paper presents a StopeSoft web-based tool for open stope stability prediction that is developed on the basis of the Stability Graph method and is available at openstope.com. StopeSoft incorporates flexibility in terms of Stability Graph options and incorporates additional critical factors often overlooked. As a web-based tool, StopeSoft encourages and makes data sharing possible globally, focused on expanding the database and improving the current limitations of the Stability Graph to provide practical, reliable solutions for mining engineers, consultants, and academics. The StopeSoft automated process facilitates the process of open stope stability prediction, saving time and minimizing potential human errors. Statistical treatment of the data accounts for the variability of input parameters to emphasize the probabilistic nature of the Stability Graph method. The probabilistic interpretation of the stability states of stope surfaces eliminates the false feeling of absolute stope performance based on its location on the Stability Graph , as implied by the deterministic approach.

58 GEOSCIENCES↗
DOE OSTI2018

Regional evapotranspiration from an image-based implementation of the Surface Temperature Initiated Closure (STIC1.2) model and its validation across an aridity gradient in the conterminous US

Recent studies have highlighted the need for improved characterizations of aerodynamic conductance and temperature (g A and T 0 ) in thermal remote-sensing-based surface energy balance (SEB) models to reduce uncertainties in regional-scale evapotranspiration (ET) mapping. By integrating radiometric surface temperature (TR) into the Penman–Monteith (PM) equation and finding analytical solutions of gA and T0, this need was recently addressed by the Surface Temperature Initiated Closure (STIC) model. However, previous implementations of STIC were confined to the ecosystem-scale using flux tower observations of infrared temperature. This study demonstrates the first regional-scale implementation of the most recent version of the STIC model (STIC1.2) that integrates the Moderate Resolution Imaging Spectroradiometer (MODIS) derived TR and ancillary land surface variables in conjunction with NLDAS (North American Land Data Assimilation System) atmospheric variables into a combined structure of the PM and Shuttleworth–Wallace (SW) framework for estimating ET at 1 km × 1 km spatial resolution. Evaluation of STIC1.2 at 13 core AmeriFlux sites covering a broad spectrum of climates and biomes across an aridity gradient in the conterminous US suggests that STIC1.2 can provide spatially explicit ET maps with reliable accuracies from dry to wet extremes. When observed ET from one wet, one dry, and one normal precipitation year from all sites were combined, STIC1.2 explained 66 % of the variability in observed 8-day cumulative ET with a root mean square error (RMSE) of 7.4 mm/8-day, mean absolute error (MAE) of 5 mm/8-day, and percent bias (PBIAS) of -4 %. These error statistics showed relatively better accuracies than a widely used but previous version of the SEB-based Surface Energy Balance System (SEBS) model, which utilized a simple NDVI-based parameterization of surface roughness (z OM ), and the PM-based MOD16 ET. SEBS was found to overestimate (PBIAS = 28 %) and MOD16 was found to underestimate ET (PBIAS =-26 %). The performance of STIC1.2 was better in forest and grassland ecosystems as compared to cropland (20 % underestimation) and woody savanna (40 % overestimation). Model inter-comparison suggested that ET differences between the models are robustly correlated with g A and associated roughness length estimation uncertainties which are intrinsically connected to T R uncertainties, vapor pressure deficit (D A ), and vegetation cover. A consistent performance of STIC1.2 in a broad range of hydrological and biome categories, as well as the capacity to capture spatio-temporal ET signatures across an aridity gradient, points to the potential for this simplified analytical model for near-real-time ET mapping from regional to continental scales.

Bhattarai, Nishan (ORCID:0000000327493549)↗
DOE OSTI2017

Systematic Biases in Weak Lensing Cosmology with the Dark Energy Survey

This thesis sets out a practical guide to applying shear measurements as a cosmological tool. We first present one of two science-ready galaxy shape catalogues from Year 1 of the Dark Energy Survey (DES Y1), which covers 1500 square degrees in four bands $griz$, with a median redshift of $0.59$. We describe the shape measurement process implemented by the DES Y1 imshape catalogue, which contains 21.9 million high-quality $r$-band bulge/disc fits. In Chapter 3 a new suite of image simulations, referred to as Hoopoe, are presented. The Hoopoe dataset is tailored to DES Y1 and includes realistic blending, spatial masks and variation in the point spread function. We derive shear corrections, which we show are robust to changes in calibration method, galaxy binning and variance within the simulated dataset. Sources of systematic uncertainty in the simulation-based shear calibration are discussed, leading to a final estimate of the $1\sigma$ uncertainties in the residual multiplica tive bias after calibration of 0.025. Chapter 4 describes an extension of the analysis on the Hoopoe simulations into a detailed investigation of the impact of galaxy neighbours on shape measurement and shear cosmology. Four mechanisms by which neighbours can have a non-negligible influence on shear measurement are identified. These effects, if ignored, would contribute a net multiplicative bias of $m \sim 0.03 - 0.09$ in DES Y1, though the precise impact will depend on both the measurement code and the selection cuts applied. We use the cosmological inference pipeline of DES Y1 to explore the cosmological implications of neighbour bias and show that omitting blending from the calibration simulation for DES Y1 would bias the inferred clustering amplitude $S_8 \equiv \sigma_8 (\omegam /0.3)^{0.5}$ by $1.5 \sigma$ towards low values. Finally, we use the Hoopoe simulations to test the effect of neighbour-induced spatial correlations in the multiplicative bias. We find the cosmo logical impact to be subdominant to statistical error at the! current level of precision. Another major uncertainity in shear cosmology is the accuracy of our ensemble redshift distributions. Chapter 5 presents a numerical investigation into the combined constraining power of cosmic shear, galaxy clustering and their cross-correlation in DES Y1, and the potential for internal calibration of redshift errors. Introducing a moderate uniform bias into the redshift distributions used to model the weak lensing (WL) galaxies is shown to produce a $> 2\sigma$ bias in $S_8$. We demonstrate that this cosmological bias can be eliminated by marginalising over redshift error nuisance parameters. Strikingly, the cosmological constraint of the combined dataset is largely undiminished by the loss of prior information on the WL distributions. We demonstrate that this implicit self-calibration is the result of complementary degeneracy directions in the combined data. In Chapter 6 we present the preliminary results of an investigation into galaxy intrin sic alignments. Using the DES Y1 data, we show a clear dependence in alignment amplitude on galaxy type, in agreement with previous results. We subject these findings to a series of initial robustness tests. We conclude with a short overview of the work presented, and discuss prospects for the future.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Nucleon Form Factors with 2+1 Flavors of Domain Wall Fermions and All-Mode-Averaging

We report recent progress in the calculations of the isovector nucleon electromagnetic form factors using 2+1 flavors of domain wall fermions at pion masses of 170 MeV and 250 MeV. The lattice size is fixed at 323 ×64 with a lattice cutoff scale of 1.37(1) GeV. For the calculations with Mp = 170 MeV, we employed the All-Mode-Averaging (AMA) technique, which led to roughly a factor of 20 improvement in computational efficiency and has reduced the statistical errors in our results significantly. We were also able to do calculations at two different source-sink separations, at roughly 1.3 fm and 1.0 fm, without much additional cost by reusing the low eigenmodes stored for the AMA calculations. We will present results for the isovector form factors and their derived quantities, including the Dirac and Pauli radii, anomalous magnetic moment and discuss the effects of possible excited-state contaminations. Connected contributions to the isoscalar Dirac and Pauli form factors will also be shown.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Total Measurement Uncertainty in Neutron Coincidence Multiplicity Analysis

Neutron multiplicity analysis is a widely used technique in international safeguards and is most commonly applied to the assay of product and scrap materials in the production of mixed oxide fuel. The typical neutron multiplicity analysis applies only a crude, almost cursory, uncertainty analysis limited to propagation of statistical errors in the derived singles, doubles, and triples count rates through the point source model. While these analyses do not account for uncertainties in basic detector parameters (e.g., efficiency or gate utilization factors), nuclear data, or covariances between any of these values, measurement uncertainties are often quoted in the range of 1–2% of the resulting mass values. In this work, we examined the impact of the nuclear data and instrumentation uncertainties on the multiplicity assay result for various counting regimes using the point-model equations as the basis for discussion. Potential biases introduced by the current nuclear data set on the measurement and the need for a more complete error treatment when we progress beyond empirical calibrations based on highly representative items will be discussed.

Mcelroy Jr, Robert↗
DOE OSTI2020

Simulation of Particle-Material Interactions

This paper gives an overview of the particle transport theory essentials, the basics of particle-material interaction simulation, physical quantities needed to simulate particle transport and interactions in materials, Monte Carlo simulation flow, response of additive detectors, statistical weights and other techniques to minimize statistical errors. Effects in materials under irradiation, materials response related to component lifetime and performance are considered with a focus on high-energy and high-power accelerator applications. Implementation of simulation of particle-material interactions in the modern Monte Carlo codes along with the code s main features and results of recent benchmarking are described.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

A High-resolution Regional Wave Resource Characterization For The U.S. West Coast

Objectives/Scope: Wave resource characterization is a critical step for wave energy converter deployment in the coastal ocean and relies on long-term, high-resolution wave datasets. This study presents a detailed modeling study of the wave resource along the U.S. West Coast (Washington, Oregon, and California), a coastal region that was identified with high wave energy potential in earlier studies. Methods, Procedures, Process: The wave hindcast covers a 32-year period from 1979 to 2010 and is based on a multi-resolution, unstructured-grid SWAN model framework. Model configuration closely follows and meets the requirements recommended by the International Electrotechnical Commission Technical Specification (IEC TS) for wave energy resource assessment and characterization (Class 2 - feasibility study). The model domain covers the entire U.S. Exclusive Economic Zone (EEZ) in the West Coast and has a spatial resolution varying from ~300 m in the nearshore region (20 km from the shoreline) to ~2500 m within the EEZ and ~5000 m at the open boundary, which extends beyond the EEZ. The model was forced by hourly 2-D wave spectra produced by a two-way nested WaveWatch III model, which covers the global ocean domain and the broader U.S. West Coast region domain with spatial resolutions of 0.5 degree and 10 arc-minutes, respectively. Both wave models are forced by hourly, 0.5-degree wind forcing obtained from NCEP’s Climate Forecast System Reanalysis (CFSR) product. Results, Observations, Conclusions: The standard model output for the SWAN model includes 3-hourly output for the six IEC wave resource parameters (e.g., omnidirectional wave power) at each grid point and hourly 2-D spectra at more than 50 NDBC buoys. Extensive model validation was achieved by comparing the six model-predicted IEC parameters with those derived from field observations at representative NDBC buoys. The error statistics indicated the model’s satisfactory performance. Further analyses were conducted to systematically evaluate the temporal and spatial distributions of wave energy potential and wave climate along the U.S. West Coast. Results suggest that Washington and Oregon coasts have similar nearshore wave resource, which is significantly higher than resources in Southern California. Strong seasonal variations are also observed, e.g., high wave energy tends to occur in the winter months. In summary, this study produced the first high-resolution, comprehensive dataset on wave energy distribution along the U.S. West Coast. Novel/Additive Information: The results are being used by the National Renewable Energy Laboratory to update the MHK Atlas, which was originally derived from NOAA’s 4-arc-minute WaveWatch III model output. In addition, the monthly averaged wave energy climatology dataset can be readily shared to support a variety of research and application efforts within the EEZ of the U.S. West Coast.

Wang, Taiping↗
DOE OSTI2023

Exascale Multiphysics Nuclear Reactor Simulations for Advanced Designs

ENRICO is a coupled application developed under the U.S. Department of Energy's Exascale Computing Project (ECP) targeting the modeling of advanced nuclear reactors. It couples radiation transport with heat and fluid simulation, including the high-fidelity, highresolution Monte-Carlo code Shift and the Computational fluid dynamics code NekRS. NekRS is a highly-performant open-source code for simulation of incompressible and low-Mach fluid flow, heat transfer, and combustion with a particular focus on turbulent flows in complex domains. It is based on rapidly convergent high-order spectral element discretizations that feature minimal numerical dissipation and dispersion. State-of-the-art multilevel preconditioners, efficient high-order time-splitting methods, and runtime-adaptive communication strategies are built on a fast OCCA-based kernel library, libParanumal, to provide scalability and portability across the spectrum of current and future high-performance computing platforms. On Frontier, Nek5000/RS has recently achieved an unprecedented milestone in breaching over 1 billion spectral elements and 350 billion degrees of freedom. Shift has demonstrated the capability to transport upwards of 1 billion particles per second in full core nuclear reactor simulations featuring complete temperature-dependent, continuous-energy physics on Frontier. Shift achieved a weak-scaling efficiency of 97.8% on 8192 nodes of Frontier and calculated 6 reactions in 214,896 fuel pin regions below 1% statistical error yielding first-of-a-kind resolution for a Monte Carlo transport application.

Hamilton, Steven P.↗
DOE OSTI2015

Geant4 simulation for a study of a possible use of carbon ions pencil beam for the treatment of ocular melanomas with the active scanning system at CNAO Centre

The aim of this work is to validate the Geant4 application reproducing the CNAO (National Centre for Oncological Hadrontherapy) beamline and to study of a possible use of carbon ion pencil beams for the treatment of ocular melanomas at the CNAO Centre. The promising aspect of carbon ions radiotherapy for the treatment of this disease lies in its superior relative radiobiological effectiveness (RBE). The Monte Carlo Geant4 toolkit is used to simulate the complete CNAO extraction beamline, with the active and passive components along it. A human eye modeled detector, including a realistic target tumor volume, is used as target. Cross check with previous studies at CNAO using protons allows comparisons on possible benefits on using such a technique with respect to proton beams. Before the eye-detector irradiation a validation of the Geant4 simulation with CNAO experimental data is carried out with both carbon ions and protons. Important beam parameters such as the transverse FWHM and scanned radiation field 's uniformity are tested within the simulation and compared with experimental measurements at CNAO Centre. The physical processes involved in secondary particles generation by carbon ions and protons in the eye-detector are reproduced to take into account the additional dose to the primary beam given to irradiated eye's tissues. A study of beam shaping is carried out to produce a uniform 3D dose distribution (shaped on the tumor) by the use of a spread out Bragg peak. The eye-detector is then irradiated through a two dimensional transverse beam scan at different depths. In the use case the eye-detector is rotated of an angle of 40 deg. in the vertical direction, in order to mis-align the tumor from healthy tissues in front of it. The treatment uniformity on the tumor in the eye-detector is tested. For a more quantitative description of the deposited dose in the eye-detector and for the evaluation of the ratio between the dose deposited in the tumor and the other eye components, proton and carbon DVHs (Dose Volume Histograms) are compared. A high statistics simulated sample is used to minimize statistical errors. In the simulation a new particle generation method is developed in order to reproduce the experimental treatment plan by importing the DICOM RT-PLAN file, which contains all the information on the irradiation geometries and sequences (treatment plan parameters). Conclusions Even further validations must be done, the good results so far obtained by this work point out and confirm the possibility of using carbon ions delivered with active scanning beams to treat the ocular melanoma.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Remote Radiation Sensing Using Aerial and Ground Platforms

Remote sensing of ionizing radiation has a significant role in waste management, nuclear material management and nonproliferation, and radiation safety. Robotic platforms can surpass the number of tasks that are achieved by humans. With this technique, the operator's radiation exposure can be decreased. Remote sensing allows for the evaluation and monitoring of radiological contamination. Gamma-ray and neutron sensors were integrated onto the robotic platforms. This approach allows for the radiation sensor data to be dynamically tracked and mapped thus enabling further analysis of the radiation flux in temporal and spatial domains. The goal is to complete scheduled tasks while the robot is being irradiated. To achieve this, electronic components must be shielded and radiation hardened. CZT Detector: Cadmium Zinc Telluride (CZT) detector technology has been a promising solution for gamma-ray and x-ray measurements. Detector data is transferred to the Odroid minicomputer that controls and powers the module via the USB. Robot Operating System (ROS) was utilized for data acquisition and data fusion. The Mariscotti method was employed for the spectrum analysis. A function was programmed in ROS for the automatic identification of photopeaks. CLYC Detector: A Cs{sub 2}LiYCl{sub 6}:Ce{sup 3+} (CLYC) detector was used for simultaneous medium-resolution gamma-ray measurements and neutron counting. A 2.54 cm diameter photomultiplier tube (PMT) was equipped with a high voltage supply and a miniature digitizer. Gamma-ray excitation: fast core-to-valence luminescence (CVL) with 1 ns decay constant, and prompt Ce{sup 3+} emission with 50 ns decay constant. Neutron excitation: slow cerium self-trapped excitation (Ce{sup 3+} STE), 1000 ns decay constant. Radiation Source Localization: Maximum Likelihood Estimation (MLE) and gradient-based methods were used to locate the position of a radiation source based on measured radiation intensities. Multi-Particle Transport Code FLUKA: Estimation of radiation damage of the electronic components is important in order to optimize the robot's operational time while it is irradiated. Displacement per atom (DPA) represents the radiation damage in materials exposed to the ionizing radiation. Various shielding layers of different thickness t were analyzed (< 5% statistical error). The model of the controller of the UAS was designed in FLUKA. Conclusion: CZT and CLYC detectors were integrated onto the robotic platforms. Radiation source localization and contour mapping using robotic platforms were studied. Functions for data analysis and fusion were developed in ROS. FLUKA code was utilized to analyze DPA values. Layers of low-density and high-density materials were used to shield the UAS electronics.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Development of ARCHER towards clinical use: modeling and simulation of Varian Linac for radiation therapy dose calculations - 25449

Monte Carlo particle transport methods are well recognized as the most accurate approach to dose calculations for radiation therapy treatment planning. However, the lengthy calculation time has prevented Monte Carlo methods from being applied to dose calculations in the planning of radiation therapy. Recently, the emerging parallel computing hardware accelerators, such as general-purpose Graphics Processing Unit (GPU), have significantly boosted the performance of Monte Carlo codes. The accuracy of a clinical dose engine depends greatly on the accuracy of source term modeling and the methodology of dose calculations. Hence, in this study, an efficient and accurate source model of the Varian TrueBeam{sup R} Linac is developed and integrated with a fast photon-electron transport module of the recently developed high-performance Monte Carlo code, ARCHER. The validity of the source model and the particle transport physics are verified with established dose calculation codes such as EGSnrc and validated with experimental measurements. To demonstrate the capability of the platform in clinical applications, three clinical treatment plans (the lung, breast, and prostate) are simulated and analyzed. From the perspective of performance, the entire simulation of each clinical plan, starting from the source modeling to the end of particle transport within the patient phantom, can be finished in less than one minute using a single Titan X GPU card with 1% statistical error. In comparison, the same cases take the EGSnrc code hundreds of CPU hours to finish. The results suggest that this new version of ARCHER code has been successfully developed and tested as a clinically deployable dose engine for external photon beam IMRT plans in the clinical setting. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2018

Distinguishing Research Reactor Fuels Using Neutron Multiplicity - 25615

Neutron measurements are one of the reliable means of interrogation of fissile material. Neutron measurements are used for total counting (pure metal fissile samples) or counting coincidence/multiplicity (for impure fissile samples). Various flavors of neutron measurement are used routinely by the IAEA to determine the fissile mass of an unknown sample. The objective of this work is to design an experiment to distinguish the two different fuel types using neutron multiplicity method. The design of experiment is performed using Monte Carlo N- Particle (MCNP) transport code. General Electric (GE) designed 1-MWt pool-type research reactor at UMass Lowell (UMLRR) uses Materials Testing Reactor (MTR) plate-type fuel consisting of 19 full and 2 partial fuel assemblies, controlled by four boron control blades and one regulating control rod. Two different fuel types are available at the UMLRR facility. In 2008, UMass Lowell obtained slightly burnt fuel assemblies from the decommissioned WPI research reactor. The simulation results discussed in this paper show that within the limits of statistical error, the single and double moments for the WPI and UMLRR fuels can be measured. The two fuels have very similar composition and enrichments resulting in very similar neutron multiplicity moments. This implies that neutron multiplicity measurements alone would not be sufficient to distinguish between the two fuel types at low burnups. The change in the observed single-double ratio between each fuel type is less than 6 % which falls below the uncertainty in the efficiency of the JCC71 slab detectors. The neutron signature from low burnup and low enriched uranium fuel are not strong, however, these can be measured under low background and long measurement times. This would be an important consideration in designing the experiments and parallel gamma measurements will also be planned. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

Uncertainty Quantification for Monte Carlo simulations - Paper 18

Uncertainty quantification (UQ) generally speaking refers to a wide variety of specific problems, also pertaining different scientific areas: then studies on Uncertainty Quantification involve many different methodologies, techniques and even terminologies: to be specific we are interested in studying how uncertainties on input physical data needed for Monte Carlo simulations transfer into uncertainties on the physical output of the simulation. We mention that other sources of uncertainty are be present in a simulation environment: they can be ascribed either to model inadequacy (for instance when one neglects atomic lattice at very low energies) or to the numerical procedure involved: for the case of MC simulation the latter corresponds to the statistical error affecting the simulation itself. So in general parameter uncertainties are mixed with other kind of uncertainties. The problem then remains seemingly quite complicated, even in this more specific domain: moreover we should better specify the meaning of the rather undetermined words physical data needed for Monte Carlo simulation. In fact they may refer both those data needed to specify the experimental setup that is going to be simulated - like, e.g., geometrical or composition data, but including also some external conditions applied to the system, like temperature, pressure, electromagnetic fields and so on - and physical data - cross sections or often physical models - required to describe particle transport. All these data are generally affected by uncertainties, which through the process of simulation transfer into uncertainty on its physical outcome. Then, from the MC user's own perspective, input data refers both to those that are under his direct experimental control and to many others, whose values and uncertainties will affect the result of the simulation. In this contribution we will summarize previous results, together with some new ones. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2015

Measurement of neutron and gamma-ray noise in large subcritical condition for criticality safety - 14485

Various experimental methods have been proposed for subcriticality measurement and neutron noise analysis method is one of important experimental techniques for this purpose. The variance to mean value method, called Feynman-alpha method, is one of well-known noise analysis methods. In this method, variation of neutron count rate distribution from the Poisson distribution caused by fission chain reactions, which is called Y-value, is measured, however, it is difficult to measure the Y-value in large subcritical state such as nuclear fuel facility, because number of emitted neutrons by fission chain reaction is small, which causes large statistical error. We developed new experimental technique based on Feynman-alpha method combined with pulsed neutron source, called Delayed Neutron Noise Analysis (DNNA) method, to monitor the change of subcriticality. In this new method, neutron and gamma-ray counts measured only appeared in the delayed neutron region after injection of pulsed neutron are analyzed, and the prompt neutron region is completely ignored. The advantage of DNNA compared with conventional method is that spatial dependency of detector positions on measured results can be greatly decreased, which result in increase of accuracy of measured subcriticality. The validity of the DNNA method was experimentally investigated in the Kyoto University Critical Assembly (KUCA) at Kyoto University Research Reactor Institute. In the experiments, pulsed neutrons by D-T reactions are injected into the core and we used {sup 3}He detectors to measure neutron noise signals and BGO scintillation detectors to measure gamma-ray noise signals, and all data in the delayed neutron region were analyzed based on Feynman-alpha method. From the experimental results, it was found that the Y-values are clearly larger than zero in the case of existence of fuel assemblies and this method can be applied to detection of hidden special nuclear materials for example in a cargo container. (authors)

42 ENGINEERING↗