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All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Management, Analysis, and Visualization of Experimental and Observational Data – The Convergence of Data and Computing

Scientific user facilities—particle accelerators, telescopes, colliders, supercomputers, light sources, sequencing facilities, and more—operated by the U.S. Department of Energy (DOE) Office of Science (SC) generate ever increasing volumes of data at unprecedented rates from experiments, observations, and simulations. At the same time there is a growing community of experimentalists that require real-time data analysis feedback, to enable them to steer their complex experimental instruments to optimized scientific outcomes and new discoveries. Recent efforts in DOE-SC have focused on articulating the data-centric challenges and opportunities facing these science communities. Key challenges include difficulties coping with data size, rate, and complexity in the context of both real-time and post-experiment data analysis and interpretation. Solutions will require algorithmic and mathematical advances, as well as hardware and software infrastructures that adequately support data-intensive scientific workloads. This paper presents the summary findings of a workshop held by DOE-SC in September 2015, convened to identify the major challenges and the research that is needed to meet those challenges.

Bethel, E. Wes↗
DOE OSTI2016

Management, Analysis, and Visualization of Experimental and Observational Data -- The Convergence of Data and Computing

Scientific user facilities---particle accelerators, telescopes, colliders, supercomputers, light sources, sequencing facilities, and more---operated by the U.S. Department of Energy (DOE) Office of Science (SC) generate ever increasing volumes of data at unprecedented rates from experiments, observations, and simulations. At the same time there is a growing community of experimentalists that require real-time data analysis feedback, to enable them to steer their complex experimental instruments to optimized scientific outcomes and new discoveries. Recent efforts in DOE-SC have focused on articulating the data-centric challenges and opportunities facing these science communities. Key challenges include difficulties coping with data size, rate, and complexity in the context of both real-time and post-experiment data analysis and interpretation. Solutions will require algorithmic and mathematical advances, as well as hardware and software infrastructures that adequately support data-intensive scientific workloads. This paper presents the summary findings of a workshop held by DOE-SC in September 2015, convened to identify the major challenges and the research that is needed to meet those challenges.

Bethel, E. Wes↗
DOE OSTI2023

The solenoidal large intensity device (SoLID) for JLab 12 GeV

The solenoidal large intensity device (SoLID) is a new experimental apparatus planned for Hall A at the Thomas Jefferson National Accelerator Facility (JLab). SoLID will combine large angular and momentum acceptance with the capability to handle very high data rates at high luminosity. With a slate of approved high-impact physics experiments, SoLID will push JLab to a new limit at the QCD intensity frontier that will exploit the full potential of its 12 GeV electron beam. In this paper, we present an overview of the rich physics program that can be realized with SoLID, which encompasses the tomography of the nucleon in 3D momentum space from semi-inclusive deep inelastic scattering, expanding the phase space in the search for new physics and novel hadronic effects in parity-violating DIS, a precision measurement of J/ψ production at threshold that probes the gluon field and its contribution to the proton mass, tomography of the nucleon in combined coordinate and momentum space with deep exclusive reactions, and more. To meet the challenging requirements, the design of SoLID described here takes full advantage of recent progress in detector, data acquisition and computing technologies. In addition, we outline potential experiments beyond the currently approved program and discuss the physics that could be explored should upgrades of CEBAF become a reality in the future.

3D imaging↗
DOE OSTI2025

On the minimum number of radiation field parameters to specify gas cooling and heating functions

Fast and accurate approximations of gas cooling and heating functions are needed for hydrodynamic galaxy simulations. We use machine learning to analyze atomic gas cooling and heating functions computed by Cloudy in the presence of a generalized incident local radiation field. We characterize the radiation field through binned radiation field intensities instead of the photoionization rates used in our previous work. We find a set of 6 energy bins whose intensities exhibit relatively low correlation. We use these bins as features to train machine learning models to predict Cloudy cooling and heating functions at fixed metallicity. We compare the relative SHapley Additive exPlanation (SHAP) value importance of the features. From the SHAP analysis, we identify a feature subset of 3 energy bins ($0.5-1, 1-4$, and $13-16 \, \mathrm{Ry}$) with the largest importance and train additional models on this subset. We compare the mean squared errors and distribution of errors on both the entire training data table and a randomly selected 20% test set withheld from model training. The machine learning models trained with 3 and 6 bins, as well as 3 and 4 photoionization rates, have comparable accuracy everywhere, with errors $\gtrsim 10$ times smaller than for the interpolation table of Gnedin and Hollon (2012). We conclude that 3 energy bins (or 3 analogous photoionization rates: molecular hydrogen photodissociation, neutral hydrogen HI, and fully ionized carbon CVI) are sufficient to characterize the dependence of the gas cooling and heating functions on our assumed incident radiation field model.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Determining X-ray source intensity and confidence bounds in crowded fields

We present a rigorous description of the general problem of aperture photometry in high-energy astrophysics photon-count images, in which the statistical noise model is Poisson, not Gaussian. We compute the full posterior probability density function for the expected source intensity for various cases of interest, including the important cases in which both source and background apertures contain contributions from the source, and when multiple source apertures partially overlap. A Bayesian approach offers the advantages of allowing one to (1) include explicit prior information on source intensities, (2) propagate posterior distributions as priors for future observations, and (3) use Poisson likelihoods, making the treatment valid in the low-counts regime. Elements of this approach have been implemented in the Chandra Source Catalog.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Halted-pendulum Relaxation: Application to White Dwarf Binary Initial Data

Studying compact-star binaries and their mergers is integral to determining progenitors for observable transients. Today, compact-star mergers are typically studied via state-of-the-art computational fluid dynamics codes. One such numerical technique, smoothed particle hydrodynamics (SPH), is frequently chosen for its excellent mass, energy, and momentum conservation. The natural treatment of vacuum and the ability to represent highly irregular morphologies make SPH an excellent tool for the study of compact-star binaries and mergers. For many scenarios, including binary systems, the outcome of simulations is only as accurate as the initial conditions. For SPH, it is essential to ensure that the particles are distributed regularly, representing the initial density profile but without long-range correlations. Particle noise in the form of high-frequency local motion and low-frequency global dynamics must be damped out. Damping the latter can be as computationally intensive as the actual simulation. We discuss a new and straightforward relaxation method, halted-pendulum relaxation (HPR), to remove global oscillation modes of SPH particle configurations. In combination with effective external potentials representing gravitational and orbital forces, we show that HPR has an excellent performance in efficiently relaxing SPH particles to the desired density distribution and removing global oscillation modes. We compare the method to frequently used relaxation approaches and test it on a white dwarf binary model at its Roche-lobe overflow limit. We highlight the importance of our method in achieving accurate initial conditions and its effect on achieving circular orbits and realistic accretion rates when compared with other general relaxation methods.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Grizzly: A Multi-scale and Multi-Physics Tool to Model Aging of Nuclear Power Plant Components

Grizzly is a multi-scale multi-physics tool being developed at Idaho National Laboratory (INL) as part of the US Department of Energy's Light Water Reactor Sustainability program to provide improved safety assessments of systems, components, and structures in nuclear power plants subjected to age-related degradation. Its goal is to provide an improved scientific basis for decisions surrounding license renewal, which would permit operation of commercial nuclear power plants beyond 60 years. Grizzly is based on INL's MOOSE framework, which enables multi-physics simulations in a massively parallel computing environment. The reactor pressure vessel (RPV) has been chosen as the initial application for Grizzly. The primary concern for the RPV is that it becomes increasingly susceptible to fracture initiation at the sites of pre-existing flaws over time. This is because exposure to irradiation and high temperatures embrittles the steel. Assessing the safety of an RPV under transient conditions involves simulations at multiple scales. At the engineering scale, strongly coupled equations of heat conduction and solid mechanics are solved to simulate the global response of the RPV to accident conditions. Sub-models are used to represent regions with pre-existing flaws and the stress intensity factors are evaluated from the domain integrals. Crack propagation is then determined using a model that provides the temperature and neutron fluence dependent fracture toughness of the RPV steel. The ability of Grizzly to provide accurate engineering scale estimates of RPV safety beyond 60 years of operation strongly relies on the predictability of the embrittlement model. Multiple models for embrittlement have been proposed, and the physically based empirical model is implemented in Grizzly. However, the formation of late blooming phases greatly reduces the confidence on the extrapolated values obtained from embrittlement model, which is further exacerbated by the absence of real field data for validation. Experimentally validated lower length scale models can significantly improve the predictability of the embrittlement model beyond the calibrated range and the development of such models is another ongoing effort in Grizzly. The modeling activity in Grizzly spans across different length scales, and can be divided into: (i) Irradiation induced microstructure evolution at the atomistic and single crystal length scale using molecular dynamics, atomistic kinetic Monte-Carlo, phase-field and rate theory; (ii) Effect of the irradiation induced defects on the flow stress and fracture processes at the polycrystalline scale using crystal plasticity. Subsequently, the prediction from these models can be used to obtain irradiation induced ductile-to-brittle transition temperature (DBTT) shifts from specimen-scale simulations; (iii) Global thermo-mechanical response of the RPV under normal and accident scenarios, and probabilistic risk analyses at the engineering scale using the DBTT shifts obtained from the lower length scale models. The item (i) has been discussed in a previous report. In this extended abstract an overview of items (ii) and (iii) is provided. The extended abstract summarizes the current status of the modeling effort under Grizzly. At the engineering scale, reduced order model development is underway using the statistical tool RAVEN. This will allow probabilistic analysis considering a wide range of flaw topologies in a computationally efficient manner. Coupling the irradiation induced defect growth predictions to crystal plasticity is also in progress. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Assessing Historical Variability of South Asian Monsoon Lows and Depressions With an Optimized Tracking Algorithm

Abstract Cyclonic low‐pressure systems (LPS) produce abundant rainfall in South Asia, where they are traditionally categorized as monsoon lows, monsoon depressions, and more intense cyclonic storms. The India Meteorological Department (IMD) has tracked monsoon depressions for over a century, finding a large decline in their number in recent decades, but their methods have changed over time and do not include monsoon lows. This study presents a fast, objective algorithm for identifying monsoon LPS and uses it to assess interannual variability and trends in reanalyses. Variables and thresholds used in the algorithm are selected to best match a subjectively analyzed LPS data set while minimizing disagreement between four reanalyses in a training period. The stream function of 850 hPa horizontal wind is found to be optimal in this sense; it is less noisy than vorticity and represents the complete nondivergent wind, even when flow is not geostrophic. Using this algorithm, LPS statistics are computed for five reanalyses, and none show a detectable trend in monsoon depression counts since 1979. Both the Japanese 55‐year Reanalysis (JRA‐55) and the IMD data set show a step‐like reduction in depression counts when they began using geostationary satellite data, in 1979 and 1982, respectively; the 1958–2018 linear trend in JRA‐55, however, is smaller than in the IMD data set, and its error bar includes 0. There are more LPS in seasons with above‐average monsoon rainfall and in La Niña years, but few other large‐scale modes of interannual variability are found to modulate LPS counts, lifetimes, or track length consistently across reanalyses.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Accurate small and wide angle x-ray scattering profiles from atomic models of proteins and nucleic acids

A new method is introduced to compute X-ray solution scattering profiles from atomic models of macromolecules. The three-dimensional version of the Reference Interaction Site Model (RISM) from liquid-state statistical mechanics is employed to compute the solvent distribution around the solute, including both water and ions. X-ray scattering profiles are computed from this distribution together with the solute geometry. We describe an efficient procedure for performing this calculation employing a Lebedev grid for the angular averaging. The intensity profiles (which involve no adjustable parameters) match experiment and molecular dynamics simulations up to wide angle for two proteins (lysozyme and myoglobin) in water, as well as the small-angle profiles for a dozen biomolecules taken from the BioIsis.net database. The RISM model is especially well-suited for studies of nucleic acids in salt solution. Use of fiber-diffraction models for the structure of duplex DNA in solution yields close agreement with the observed scattering profiles in both the small and wide angle scattering (SAXS and WAXS) regimes. In addition, computed profiles of anomalous SAXS signals (for Rb{sup +} and Sr{sup 2+}) emphasize the ionic contribution to scattering and are in reasonable agreement with experiment. In cases where an absolute calibration of the experimental data at q = 0 is available, one can extract a count of the excess number of waters and ions; computed values depend on the closure that is assumed in the solution of the Ornstein–Zernike equations, with results from the Kovalenko–Hirata closure being closest to experiment for the cases studied here.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

INTENSITY MAPPING OF THE [C II] FINE STRUCTURE LINE DURING THE EPOCH OF REIONIZATION

The atomic C II fine-structure line is one of the brightest lines in a typical star-forming galaxy spectrum with a luminosity {approx}0.1%-1% of the bolometric luminosity. It is potentially a reliable tracer of the dense gas distribution at high redshifts and could provide an additional probe to the era of reionization. By taking into account the spontaneous, stimulated, and collisional emission of the C II line, we calculate the spin temperature and the mean intensity as a function of the redshift. When averaged over a cosmologically large volume, we find that the C II emission from ionized carbon in individual galaxies is larger than the signal generated by carbon in the intergalactic medium. Assuming that the C II luminosity is proportional to the carbon mass in dark matter halos, we also compute the power spectrum of the C II line intensity at various redshifts. In order to avoid the contamination from CO rotational lines at low redshift when targeting a C II survey at high redshifts, we propose the cross-correlation of C II and 21 cm line emission from high redshifts. To explore the detectability of the C II signal from reionization, we also evaluate the expected errors on the C II power spectrum and C II-21 cm cross power spectrum based on the design of the future millimeter surveys. We note that the C II-21 cm cross power spectrum contains interesting features that capture physics during reionization, including the ionized bubble sizes and the mean ionization fraction, which are challenging to measure from 21 cm data alone. We propose an instrumental concept for the reionization C II experiment targeting the frequency range of {approx}200-300 GHz with 1, 3, and 10 m apertures and a bolometric spectrometer array with 64 independent spectral pixels with about 20,000 bolometers.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Minimizing CGYRO HPC Communication Costs in Ensembles with XGYRO by Sharing the Collisional Constant Tensor Structure

First-principles fusion plasma simulations are both compute and memory intensive, and CGYRO is no exception. The use of many HPC nodes to fit the problem in the available memory thus results in significant communication overhead, which is hard to avoid for any single simulation. That said, most fusion studies are composed of ensembles of simulations, so we developed a new tool, named XGYRO, that executes a whole ensemble of CGYRO simulations as a single HPC job. By treating the ensemble as a unit, XGYRO can alter the global buffer distribution logic and apply optimizations that are not feasible on any single simulation, but only on the ensemble as a whole. The main saving comes from the sharing of the collisional constant tensor structure, since its values are typically identical between parameter-sweep simulations. This data structure dominates the memory consumption of CGYRO simulations, so distributing it among the whole ensemble results in drastic memory savings for each simulation, which in turn results in overall lower communication overhead.

CGYRO↗
DOE OSTI2025

Results and lessons learned from accelerating radio frequency modeling using machine learning [slides]

The “advanced tokamak” reactor concept is a leading candidate for a steady state fusion pilot plant. An advanced tokamak (AT) sustains a majority of the required plasma current with effects resulting from maintenance of the peaked pressure at the device center. This current is augmented by auxiliary current drive sources. These auxiliary actuators may consist of neutral particle beams and/or radio frequency (RF) systems such as lower hybrid current drive (LHCD) and high harmonic fast wave (HHFW) current drive using radio and microwaves from antennas. The primary focus of this work is to develop models of RF current profile control suitable for use in integrated modeling frameworks and for real-time control in experiments. Direct physics models of RF current drive can be computationally intensive. In order to achieve predictive times appropriate for the thousands of calls needed in real-time control of experiments and for use in integrated models, we will apply modern machine learning (ML) techniques to accelerate these models and interpolate their results. To generate the fast and accurate models for use in control level algorithms and integrated modeling we need to replace present models with high dimensional interpolation of their results. We will perform additional simulations across a broader parameter range for EAST and other tokamaks in different physics regimes (Alcator C-Mod, DIII-D, WEST, CFETR, ARC, ITER) and combine them into a larger database for training and testing of the ML models. Further testing of the control level models with experimental current profile data from EAST and C-Mod tokamaks will provide additional confirmation of the control level model before integration in a tokamak control system or integrated modeling suite. ML will be used to optimize the selection of training data consisting of RF current driven at different values of density profile, temperature profile, plasma current, and wavenumber. ML will also be used to facilitate classification of current drive from these input data. The output of this effort will be a validated classifier capable of determining the current drive profiles for HHFW CD and LHCD on a mille-second timescale. This will provide a breakthrough capability enabling real-time control of RF driven current profiles in experiments including ITER ICRF and use integrated modeling frameworks requiring thousands of current profile calculations in discharge simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

WarpIV: In situ visualization and analysis of ion accelerator simulations

The generation of short pulses of ion beams through the interaction of an intense laser with a plasma sheath offers the possibility of compact and cheaper ion sources for many applications--from fast ignition and radiography of dense targets to hadron therapy and injection into conventional accelerators. To enable the efficient analysis of large-scale, high-fidelity particle accelerator simulations using the Warp simulation suite, the authors introduce the Warp In situ Visualization Toolkit (WarpIV). WarpIV integrates state-of-the-art in situ visualization and analysis using VisIt with Warp, supports management and control of complex in situ visualization and analysis workflows, and implements integrated analytics to facilitate query- and feature-based data analytics and efficient large-scale data analysis. WarpIV enables for the first time distributed parallel, in situ visualization of the full simulation data using high-performance compute resources as the data is being generated by Warp. The authors describe the application of WarpIV to study and compare large 2D and 3D ion accelerator simulations, demonstrating significant differences in the acceleration process in 2D and 3D simulations. WarpIV is available to the public via https://bitbucket.org/berkeleylab/warpiv. The Warp In situ Visualization Toolkit (WarpIV) supports large-scale, parallel, in situ visualization and analysis and facilitates query- and feature-based analytics, enabling for the first time high-performance analysis of large-scale, high-fidelity particle accelerator simulations while the data is being generated by the Warp simulation suite. Furthermore, this supplemental material https://extras.computer.org/extra/mcg2016030022s1.pdf provides more details regarding the memory profiling and optimization and the Yee grid recentering optimization results discussed in the main article.

43 PARTICLE ACCELERATORS↗
DOE OSTI2014

SU-E-T-278: Realization of Dose Verification Tool for IMRT Plan Based On DPM

Purpose: To build a Monte Carlo dose verification tool for IMRT Plan by implementing a irradiation source model into DPM code. Extend the ability of DPM to calculate any incident angles and irregular-inhomogeneous fields. Methods: With the virtual source and the energy spectrum which unfolded from the accelerator measurement data,combined with optimized intensity maps to calculate the dose distribution of the irradiation irregular-inhomogeneous field. The irradiation source model of accelerator was substituted by a grid-based surface source. The contour and the intensity distribution of the surface source were optimized by ARTS (Accurate/Advanced Radiotherapy System) optimization module based on the tumor configuration. The weight of the emitter was decided by the grid intensity. The direction of the emitter was decided by the combination of the virtual source and the emitter emitting position. The photon energy spectrum unfolded from the accelerator measurement data was adjusted by compensating the contaminated electron source. For verification, measured data and realistic clinical IMRT plan were compared with DPM dose calculation. Results: The regular field was verified by comparing with the measured data. It was illustrated that the differences were acceptable (<2% inside the field, 2–3mm in the penumbra). The dose calculation of irregular field by DPM simulation was also compared with that of FSPB (Finite Size Pencil Beam) and the passing rate of gamma analysis was 95.1% for peripheral lung cancer. The regular field and the irregular rotational field were all within the range of permitting error. The computing time of regular fields were less than 2h, and the test of peripheral lung cancer was 160min. Through parallel processing, the adapted DPM could complete the calculation of IMRT plan within half an hour. Conclusion: The adapted parallelized DPM code with irradiation source model is faster than classic Monte Carlo codes. Its computational accuracy and speed satisfy the clinical requirement, and it is expectable to be a Monte Carlo dose verification tool for IMRT Plan. Strategic Priority Research Program of the China Academy of Science(XDA03040000); National Natural Science Foundation of China (81101132)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Measurement of the photon electroproduction cross section at JLAB with the goal of performing a Rosenbluth separation of the DVCS contribution

The study of the inner structure of hadrons allows us to understand the nature of the interactions between partons, quarks and gluons, described by Quantum Chromodynamics. The elastic scattering reactions, which have been studied in order to measure the nucleon form factors, are included in this frame. The inelastic scattering reactions are also included in this frame, they allow us to obtain information about the nucleon structure thanks to the development of the parton distribution functions (PDFs). While through elastic scattering we can obtain information about the charge distribution of the nucleon, and hence, about the spatial distribution of the partons, through inelastic scattering we obtain information about the momentum distributions of partons, by employing the PDFs. However, we can study the exclusive inelastic scattering reactions, such as the Deeply Virtual Compton Scattering (DVCS), wich allow us to access to the spatial and momentum distributions simultaneously. This is possible thanks to the generalized parton distributions (GPDs), which allow us to correlate both types of distributions. The process known as DVCS is the easiest way to access the GPDs. This process can be expressed as the scattering of an electron by a proton by means of a virtual photon with the result of the scattered initial particles plus a real photon. We find a process competing with DVCS known as Bethe-Heitler (BH), in which the real photon is radiated by the lepton rather than the quark. Due to the small cross section of DVCS, of the order of nb, in order to conduct these kind of experiments it is necessary to make use of facilities capable of providing high beam intensities. One of these facilities is the Thomas Jefferson National Accelerator Facility , where the experiment JLab E07-007, "Complete Separation of Virtual Photon and π⁰ Electroproduction Observables of Unpolarized Protons", took place during the months of October to December of 2010. The main goal of this experiment is the isolation of the contribution from the term coming form the DVCS from the interference term, resulting from the BH contribution. This isolation is known as "Rosenbluth Separation". The work presented in this thesis focuses on the analysis of the data stored by the electromagnetic calorimeter, employed for the detection of real photons. There is also a a theoretical introduction to the study of the nucleon structure, reviewing the concepts of form factors and parton distributions through elastic and inelastic processes. The computation of the photon leptoproduction cross section is described in detail, as well as the goals of experiment E07-007. This thesis also describes the analysis of the data stored by the electromagnetic calorimeter, with the purpose of obtaining the kinematic variables of the real photons resulting from DVCS reactions. Finally, it describes the selection of events from stored data, the applied cuts to kinematical variables and the background subtraction. Also, the process of extraction of the necessary observables for computing the photon leptoproduction cross section is described, along with the main steps followed to perform the Monte Carlo simulation used in this computation. The resulting cross sections are shown at the end of this thesis.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

SU-F-T-580: New Tumor Modeling Using 3D Gel Dosimeter for Brain Stereoctactic Radiotherpy (SRT)

Purpose: The purpose of this study is to develop new tumor model using 3D printing with 3D dosimeter for brain stereoctactic radiotherpy (SRT). Methods: BANG{sup 3} polymer gel was prepared and the gel-filled glass vials were irradiated with a 6 MV photon beam to acquire the calibration curve that present the change of R2 (1/T{sub 2}) value with dose. Graded doses from 0 to 12 Gy with an interval of 2 Gy were delivered. A kit for calibration of gel dosimeter and an 2 tumor model phantoms with a spherical shape were produced using a 3D printer with a polylactic acid after its 3D images were created using Autodesk software. 3D printed tumor phantoms and EBT3 films were irradiated to compare with treatment plan. After irradiation, vials for calibration and tumor model phantoms were scanned at 9.4T MRI. The spin-spin relaxation times (T{sub 2}) according to the each dose were calculated to evaluate the dose response. Acquired images were analyzed using an ImageJ. Scanned MRI images of tumor models were transferred treatment planning system and these were registered to the CT images. In all treatment plans, two arc plans (CW and CCW) were designed to deliver 50 Gy for 10 fractions. For first PTV, treatment plan was accurately designed that 95% of dose to cover 100% of PTV. But 2nd PTV was not intentionally cover 100% of PTV to evaluate the intensity of delivered tumor phantom with polymer gel. We compared the 3D dose distributions obtained from measurements with the 3D printed phantom and calculated with the TPS. Results: 3D printed phantom with a polymer gel was successfully produced. The dose distributions showed qualitatively good agreement among gel, film, and RTP data. Conclusion: A hybrid phantom represents a useful to validate the 3D dose distributions for patient-specific QA.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Detection of Local/Regional Events in Kuwait Using Next-Generation Detection Algorithms

Seismic networks around the world use conventional triggering algorithms to detect seismic signals in order to locate local/regional seismic events. Kuwait National Seismological Network (KNSN) of Kuwait Institute of Scientific Research (KISR) is operating seven broad-band and short-period three-component stations in Kuwait. The network is equipped with Nanometrics digitizers and uses Antelope and Guralp acquisition software for processing and archiving the data. In this study, we selected 10 days of archived hourly-segmented continuous data of five stations (Figure 1) and 250 days of continuous recording at MIB. For the temporary deployment our selection criteria was based on KNSN catalog intensity for the period of time we test the method. An autonomous event detection and clustering framework is employed to test a more complete catalog of this short period of time. The goal is to illustrate the effectiveness of the technique and pursue the framework for longer period of time.

58 GEOSCIENCES↗
DOE OSTI2022

Journal paper

Laser technology is being widely studied for controlled energy deposition for a range of applications, including flow control, ignition, combustion, and diagnostics. The absorption and scattering of laser radiation by liquid droplets in aerosols affects propagation of the laser beam in the atmosphere, while the ignition and combustion characteristics in combustion chambers are influenced by the evaporation rate of the sprayed fuel. In this work, we present a mathematical model built on OpenFOAM for laser heating and evaporation of a single droplet in the diffusion-dominated regime taking into account absorption of the laser radiation, evaporation process, and vapor flow dynamics. The developed solver is validated against available experimental and numerical data for heating and evaporation of ethanol and water droplets. The two main regimes—continuous and pulsed laser heating—are explored. For continuous laser heating, the peak temperature is higher for larger droplets. For pulsed laser heating, when the peak irradiance is close to transition to the boiling regime, the temporal dynamics of the droplet temperature does not depend on the droplet size. With the empirical normalization of time, the dynamics of the droplet shrinkage and cooling are found to be independent of droplet sizes and peak laser intensities.

42 ENGINEERING↗