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DOE OSTI2025

SAXS Assistant: Automated SAXS analysis for structural discovery in biologics and polymeric nanoparticles

Small-angle x-ray scattering (SAXS) is a powerful technique for assessing macromolecular structure. High-throughput SAXS is limited by the time-consuming and, at times, subjective nature of SAXS data interpretation. Here, we present SAXS Assistant, a Python-based script that streamlines SAXS data analysis to extract features for machine learning (ML) and key structural parameters, including the Guinier radius of gyration (R g ), pair distance distribution function (PDDF)-derived R g , maximum particle dimension (D max ), and Kratky plots. The script builds upon BioXTAS RAW and validates reliability via Guinier/PDDF R g agreement, an important indicator of well-measured data sets. For assistance in D max estimation, a multilayer perceptron regressor was trained with 1940 data files from the Small Angle Scattering Biological Data Bank. The model achieved a test set performance R 2 = 0.90 and mean absolute error = 11.7 Å. Training exclusively with experimental data translates analyses from researchers, including experts in the field, to the ML model, which helps assess D max estimations from PDDF. Gaussian mixture model clustering was implemented to classify profiles into structural classes based on entries in the Small Angle Scattering Biological Data Bank. Users may therefore assess the similarity between experimental samples and known biomolecular shapes within the mapped repository entries. This probabilistic clustering aids in quantifying information from Kratky and generating shape-descriptive features. SAXS Assistant accelerates SAXS data analysis through enforced quality control, ML-ready outputs, and flags for low-confidence results. In addition to providing the ability to analyze large data sets at high throughput, this tool is versatile and may serve researchers in both biological and synthetic polymer research fields.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Thermal and magnetic evolution of a crystallizing basal magma ocean in Earth's mantle

We present the thermochemical evolution of a downward crystallizing basal magma ocean (BMO) overlying the liquid outer core and probe its capability to dissipate enough power to generate and sustain an early dynamo. Furthermore, a total of 61 out of 112 scenarios for a BMO with imposed, present-day heat flux, Q BMO , values of 15, 18, and 21 TW and radiogenic heat, Q r , values of 4, 8, and 12 TW fully crystallized during the age of the Earth. Most of these models are energetically capable of inducing magnetic activity for the first 1.5 Gyrs, at least, with durations extending to 2.5 Gyrs; with final core-mantle boundary (CMB) temperatures of 4400 ±500 K-well within current best estimates for inferred temperatures. None of the models with Q BMO = 12 TW achieved a fully crystallized state, which may reflect a lower bound on the present-day heat flux across the CMB. BMO-powered dynamos exhibit strong dependence on the partition coefficient of iron into the liquid layer and its associated melting-point depression for a lower mantle composition at near-CMB conditions-parameters which are poorly constrained to date. Nonetheless, we show that a crystallizing BMO is a plausible mechanism to sustain an early magnetic field.

58 GEOSCIENCES↗

DOE OSTI2016

SU-F-T-367: Using PRIMO, a PENELOPE-Based Software, to Improve the Small Field Dosimetry of Linear Accelerators

Purpose: To calculate output correction factors for Varian Clinac 2100iX beams for seven small field detectors and use the values to determine the small field output factors for the linacs at Karolinska university hospital. Methods: Phase space files (psf) for square fields between 0.25cm and 10cm were calculated using the PENELOPE-based PRIMO software. The linac MC-model was tuned by comparing PRIMO-estimated and experimentally determined depth doses and lateral dose-profiles for 40cmx40cm fields. The calculated psf were used as radiation sources to calculate the correction factors of IBA and PTW detectors with the code penEasy/PENELOPE. Results: The optimal tuning parameters of the MClinac model in PRIMO were 5.4 MeV incident electron energy and zero energy spread, focal spot size and beam divergence. Correction factors obtained for the liquid ion chamber (PTW-T31018) are within 1% down to 0.5 cm fields. For unshielded diodes (IBA-EFD, IBA-SFD, PTW-T60017 and PTW-T60018) the corrections are up to 2% at intermediate fields (>1cm side), becoming down to −11% for fields smaller than 1cm. The shielded diode (IBA-PFD and PTW-T60016) corrections vary with field size from 0 to −4%. Volume averaging effects are found for most detectors in the presence of 0.25cm fields. Conclusion: Good agreement was found between correction factors based on PRIMO-generated psf and those from other publications. The calculated factors will be implemented in output factor measurements (using several detectors) in the clinic. PRIMO is a userfriendly general code capable of generating small field psf and can be used without having to code own linac geometries. It can therefore be used to improve the clinical dosimetry, especially in the commissioning of linear accelerators. Important dosimetry data, such as dose-profiles and output factors can be determined more accurately for a specific machine, geometry and setup by using PRIMO and having a MC-model of the detector used.

43 PARTICLE ACCELERATORS↗

NASA NTRS1987

Density fluctuations induced by nonlinear Alfven waves

The generation of plasma density fluctuations by nonlinear Alfven waves is considered. Of particular interest is the modification to the 'static approximation', describing the relationship between wave intensity and plasma density, when the Alfven wave packet is rapidly steepening. The study concentrates on a forced wave equation for the plasma density, which yields the static approximation in a select approximnation. An analytic solution to this equation is obtained for a reasonable model of a steeping wave packet. The principal results are: (1) the static approximation should give a surprisingly robust description of the coupling between Alfven wave intensity and plasma density; (2) departures of the plasma density perturbation from the static approximation result are determined by a parameter that is a simple function of the wave amplitude and plasma beta; (3) for rapidly evolving wave packets, the position of maximum density change is displaced from that of maximum wave intensity, and (4) the magnitude of the density fluctuation will not be much different than the static approximation estimate.

Spangler, Steven R.↗

DOE OSTI2026

Unbiased primordial gravitational wave inference from the CMB with SMICA

The detection of primordial gravitational waves in Cosmic Microwave Background B-mode polarization observations requires accurate and robust subtraction of astrophysical contamination. We show, using a blind Spectral Matching Independent Component Analysis, that it is possible to infer unbiased estimates of the primordial B-mode signal from ground-based observations of a small patch of sky even for highly complex foreground contamination. This work, originally performed in the context of configuration studies for a future CMB-S4 observatory, is highly relevant for the analysis of observations by the current generation of CMB experiments.

cosmological parameters from CMBR↗

DOE OSTI2022

Calibration and Commissioning of the LSST

Understanding the nature of dark energy and dark matter remains one of the fundamental questions in physics today; impacting our understanding of particle physics, cosmology, and possibly theories of gravity. Given the scale and complexity of the next generation of cosmology experiments (e.g., the Rubin Observatory, the Euclid satellite mission, and the Roman space telescope) we are entering an era where statistical noise no longer determines the accuracy to which we can measure cosmological parameters. Our ability to control and correct for systematics will ultimately determine the scientific impact of these experiments. This award addressed the challenge of how we determine what limits the accuracy of our cosmological measures, what techniques are appropriate for measuring and calibrating the properties of galaxies to best constrain cosmological models, how to develop statistical techniques that are insensitive to systematic errors, and how to optimize survey strategies in order to minimize systematics while maximizing the speed at which an experiment can achieve its science objectives. In this final technical report for award DE-SC0011635 we describe a set of open-source frameworks that simulate the characteristics and properties of current and planned cosmology surveys and the application of these frameworks to the development of new methodologies for estimating the properties and distances to galaxies that are robust to noisy and incomplete data.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1989

Estimations of ABL fluxes and other turbulence parameters from Doppler lidar data

Techniques for extraction boundary layer parameters from measurements of a short-pulse CO2 Doppler lidar are described. The measurements are those collected during the First International Satellites Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE). By continuously operating the lidar for about an hour, stable statistics of the radial velocities can be extracted. Assuming that the turbulence is horizontally homogeneous, the mean wind, its standard deviations, and the momentum fluxes were estimated. Spectral analysis of the radial velocities is also performed from which, by examining the amplitude of the power spectrum at the inertial range, the kinetic energy dissipation was deduced. Finally, using the statistical form of the Navier-Stokes equations, the surface heat flux is derived as the residual balance between the vertical gradient of the third moment of the vertical velocity and the kinetic energy dissipation. Combining many measurements would normally reduce the error provided that, it is unbiased and uncorrelated. The nature of some of the algorithms however, is such that, biased and correlated errors may be generated even though the raw measurements are not. Data processing procedures were developed that eliminate bias and minimize error correlation. Once bias and error correlations are accounted for, the large sample size is shown to reduce the errors substantially. The principal features of the derived turbulence statistics for two case studied are presented.

Gal-Chen, Tzvi↗

NASA NTRSDate not supplied

Green Aviation: Review, Aspirations, and Operational Improvements

Air traffic affects the environment locally, regionally and globally. Estimates show that aviation is responsible for 13% of transportation-related fossil fuel consumption and 2% of all anthropogenic CO2 emissions. Although there is considerable decline in air traffic due to COVID pandemic, Federal Aviation Administration (FAA) expects domestic air traffic to grow at an annual rate of 2.0 % over the next 20 years. Global air traffic is expected to grow more rapidly than domestic air traffic at an annual rate of 4.8% from 2011 to 2030. The desire to accommodate growing air traffic needs while limiting the impact of aviation on the environment has led to research in green aviation with the goals of better scientific understanding, utilization of alternative fuels, introduction of new aircraft technology, and rapid operational changes. Greenhouse gases, nitrogen oxides, and contrails generated by air traffic affect the climate in different and uncertain ways. Understanding the changes requires a hierarchy of models to deal with multiple disciplines, time scales ranging from few minutes to few hundred years and uncertainties in modeling parameters affecting both science and policy. This talk reviews earlier work at Ames on the modeling approach and an integrated capability to design aircraft operations based on a trade-off between fuel consumption, environmental goals and stakeholder values.

Green Aviation↗

DOE OSTI2020

Performance estimation of resonance-enhanced dual-buoy wave energy converter using coupled time-domain simulation

This article presents the modeling methodology and performance evaluation of the resonance-enhanced dual-buoy WEC (Wave Energy Converter) by HEM (hydrodynamic & electro-magnetic) fully-coupled-dynamics time-domain-simulation program. The numerical results are systematically compared with the authors’ 1/6-scale experiment. With a direct-drive linear generator, the WEC consists of dual floating cylinders and a moon-pool between the cylinders, which can utilize three resonance phenomena from moon-pool dynamics as well as heave motions of inner and outer buoys. The contact and friction between the two buoys observed in the experiment are also properly modeled in the time-domain simulation by the Coulomb-friction model. Moon-pool resonance peaks significantly exaggerated in linear potential theory are empirically adjusted through comparisons with measured values. A systematic comparative study between the simulations and experiments with and without PTO (power-take-off) is conducted, and the relative heave displacements/velocities and power outputs are well matched. Then, parametric studies are carried out with the simulation program to determine optimum generator parameters. The performance with various wave conditions is also assessed.

16 TIDAL AND WAVE POWER↗

DOE OSTI2017

On a carbon nanostructure-based thermoelectric converter with record parameters

There is a new idea to enhance the Seebeck coefficient using electron drag by a heat flux and decrease the thermal conductivity by heat dissipation at the interfaces between graphite- and diamond-like areas in a composite formed from carbon nanostructures. The proposed thermoelectric converter is based on a thin (20–50 nm) graphite-like layer located at an ultra-short distance from the diamond-like area. According to estimation, a thermoelectric power higher than in the case of diffusion by a factor of 10{sup 3} can be attained. Under ideal conditions, this allows a room-temperature thermoelectric efficiency of 150 to be obtained. The results of investigations within project no. 16-19-00075 of the Russian Science Foundation are substantiated.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Automated shaker placement and regularized input estimation for MIMO testing.

Multi-input, multi-output (MIMO) testing is used in component qualification to reproduce operational responses in the laboratory. It is often preferred to single-input and base-shake testing because of the potential for equivalent or better tests using smaller actuators and shorter test suites. Given a target response, two key steps in MIMO test design are selecting actuator locations and solving for input loads. Actuator locations are often manually selected using expert judgment. If an automatic method is used, locations are usually determined by simulating the vibration control problem and minimizing a combination of the input energy and control residuals. To select a configuration, the relative importance of input energy and residuals must be specified. Specifying relative weights is, in general, a manual and subjective process. This paper develops an objective function that compares actuator configurations based on control accuracy and required input energy without any manual parameter tuning. The objective function uses an optimally selected tradeoff parameter for each candidate configuration. To choose actuator locations using the new objective function, a pivoting algorithm for integer programming problems is developed. Starting with an initial configuration (such as the one generated by a greedy algorithm), the pivoting algorithm guarantees an objective function decrease in each iteration until convergence is reached. In a simulation featuring a structure excited by a diffuse acoustic field, electrodynamic shaker locations and regularized inputs are solved for without any analyst-specified parameters. Simulations are performed in MIMO configurations where the number of target responses is less than, equal to, and greater than the number of actuators.

Multi-input multi-output↗

DOE OSTI2015

Building a Business Case for Compressed Natural Gas in Fleet Applications

VICE 2.0 is the second generation of the VICE financial model developed by the National Renewable Energy Laboratory for fleet managers to assess the financial soundness of converting their fleets to run on CNG. VICE 2.0 uses a number of variables for infrastructure and vehicles to estimate the business case for decision-makers when considering CNG as a vehicle fuel. Enhancements in version 2.0 include the ability to select the project type (vehicles and infrastructure or vehicle acquisitions only), and to decouple vehicle acquisition from the infrastructure investment, so the two investments may be made independently. Outputs now include graphical presentations of investment cash flow, payback period (simple and discounted), petroleum displacement (annual and cumulative), and annual greenhouse gas reductions. Also, the Vehicle Data are now built around several common conventionally fueled (gasoline and diesel) fleet vehicles. Descriptions of the various model sections and available inputs follow. Each description includes default values for the base-case business model, which was created so economic sensitivities can be investigated by altering various project parameters one at a time.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

Quantifying Thermal Output of Energetic Materials (LDRD Final Report)

We present the results of an LDRD project, funded by the Nuclear Deterrence IA, to develop capabilities for quantitative assessment of pyrotechnic thermal output. The thermal battery igniter is used as an exemplar system. Experimental methodologies for thermal output evaluation are demonstrated here, which can help designers and engineers better specify pyrotechnic components , provide thermal output guidelines for new formulations, and generate new metrics for assessing component performance and margin given a known failure condition. A heat-transfer analysis confirms that the dominant mode of energy transfer from the pyrotechnic output plume to the heat pellet is conduction via deposition of hot titanium particles. A simple lumped-parameter model of titanium particle heat transfer and a detailed multi-phase model of deposition heat transfer are discussed. Pyrotechnic function, as defined by "go/no-go" standoff testing of a heat pellet, is correlated with experimentally measured igniter plume temperature, titanium metal particle temperature, and energy deposition. Three high-speed thermal diagnostics were developed for this task. A three-color imaging pyrometer, acquiring 100k images per second on three color channels, is deployed for measurement of titanium particle temperatures. Complimentary measurements of the overall igniter plume emission ("color") temperature were conducted using a transmission-grating spectrograph in line-imaging mode. Heat flux and energy deposition to a cold wall at the heat-pellet location were estimated using an eroding thermocouple probe, with a frequency response of ~5 kHz. Ultimate "go/no-go" function in the igniter/heat-pellet system was correlated with quantitative thermal metrics, in particular surface energy deposition and plume color temperature. Titanium metal-particle and plume color temperatures both experience an upper bound approximated by the 3245-K boiling point of TiO 2 . Average metal-particle temperatures remained nearly constant for all standoff distances at T = 2850 K, ± 300 K, while plume color temperature and heat flux decay with standoff—suggesting that heat-pellet failure results from a drop in metal-particle flux and not particle temperature. At 50% likelihood of heat-pellet failure, peak time-resolved plume color temperatures drop well below TiO 2 boiling to ~2000 - 2200 K, near the TiO 2 melting point. Estimates of peak heat flux decline from up to 1 GW/m 2 for near-field standoffs to below 320 MW/m 2 at 50% failure likelihood.

36 MATERIALS SCIENCE↗

DOE OSTI2016

TREAT Neutronics Analysis and Design Support, Part II: Multi-SERTTA-CAL

Experiment vehicle design is necessary in preparation for Transient Reactor Test (TREAT) facility restart and the resumption of transient testing to support Accident Tolerant Fuel (ATF) characterization and other future fuels testing requirements. Currently the most mature vehicle design is the Multi-SERTTA (Static Environments Rodlet Transient Test Apparatuses), which can accommodate up to four concurrent rodlet-sized specimens under separate environmental conditions. Robust test vehicle design requires neutronics analyses to support design development, optimization of the power coupling factor (PCF) to efficiently maximize energy generation in the test fuel rodlets, and experiment safety analyses. In integral aspect of prior TREAT transient testing was the incorporation of calibration experiments to experimentally evaluate and validate test conditions in preparation of the actual fuel testing. The calibration experiment package established the test parameter conditions to support fine-tuning of the computational models to deliver the required energy deposition to the fuel samples. The calibration vehicle was designed to be as near neutronically equivalent to the experiment vehicle as possible to minimize errors between the calibration and final tests. The Multi-SERTTA-CAL vehicle was designed to serve as the calibration vehicle supporting Multi-SERTTA experimentation. Models of the Multi-SERTTA-CAL vehicle containing typical PWR-fuel rodlets were prepared and neutronics calculations were performed using MCNP6.1 with ENDF/B-VII.1 nuclear data libraries; these results were then compared against those performed for Multi-SERTTA to determine the similarity and possible design modification necessary prior to construction of these experiment vehicles. The estimated reactivity insertion worth into the TREAT core is very similar between the two vehicle designs, with the primary physical difference being a hollow Inconel tube running down the length of the calibration vehicle. Calculations of PCF indicate that on average there is a reduction of approximately 6.3 and 12.6%, respectively, for PWR fuel rodlets irradiated under wet and dry conditions. Changes to the primary or secondary vessel structure in the calibration vehicle can be performed to offset this discrepancy and maintain neutronic equivalency. Current possible modifications to the calibration vehicle include reduction of the primary vessel wall thickness, swapping Zircaloy-4 for stainless steel 316 in the secondary containment, or slight modification to the temperature and pressure of the water environment within the primary vessel. Removal of some of the instrumentation within the calibration vehicle can also serve to slightly increase the PCF. Future efforts include further modification and optimization of the Multi-SERTTA and Multi-SERTTA-CAL designs in preparation of actual TREAT transient testing. Experimental results from both test vehicles will be compared against calculational results and methods to provide validation and support additional neutronics analyses.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2016

TREAT neutronics analysis and design support, Part II: Multi-SERTTA-CAL

Experiment vehicle design is necessary in preparation for Transient Reactor Test (TREAT) facility restart and the resumption of transient testing to support Accident Tolerant Fuel (ATF) characterization and other future fuels testing requirements. Currently the most mature vehicle design is the Multi-SERTTA (Static Environments Rodlet Transient Test Apparatuses), which can accommodate up to four concurrent rodlet-sized specimens under separate environmental conditions. Robust test vehicle design requires neutronics analyses to support design development, optimization of the power coupling factor (PCF) to efficiently maximize energy generation in the test fuel rodlets, and experiment safety analyses. An integral aspect of prior TREAT transient testing was the incorporation of calibration experiments to experimentally evaluate and validate test conditions in preparation of the actual fuel testing. The calibration experiment package established the test parameter conditions to support fine-tuning of the computational models to deliver the required energy deposition to the fuel samples. The calibration vehicle was designed to be as near neutronically equivalent to the experiment vehicle as possible to minimize errors between the calibration and final tests. The Multi-SERTTA-CAL vehicle was designed to serve as the calibration vehicle supporting Multi-SERTTA experimentation. Models of the Multi-SERTTA-CAL vehicle containing typical PWR-fuel rodlets were prepared and neutronics calculations were performed using MCNP6.1 with ENDF/B-VII.1 nuclear data libraries; these results were then compared against those performed for Multi-SERTTA to determine the similarity and possible design modification necessary prior to construction of these experiment vehicles. The estimated reactivity insertion worth into the TREAT core is very similar between the two vehicle designs, with the primary physical difference being a hollow Inconel tube running down the length of the calibration vehicle. Calculations of PCF indicate that on average there is a reduction of approximately 6 % for PWR fuel rodlets irradiated under both wet and dry conditions. Changes to the primary or secondary vessel structure in the calibration vehicle can be performed to offset this discrepancy and maintain neutronic equivalency. Current possible modifications to the calibration vehicle include reduction of the primary vessel wall thickness, swapping Zircaloy-4 for stainless steel 316 in the secondary containment, or slight modification to the temperature and pressure of the water environment within the primary vessel. Removal of some of the instrumentation within the calibration vehicle can also serve to slightly increase the PCF. Future efforts include further modification and optimization of the Multi-SERTTA and Multi-SERTTA-CAL designs in preparation of actual TREAT transient testing. Experimental results from both test vehicles will be compared against calculational results and methods to provide validation and support additional neutronics analyses. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2017

Risk Assessment and Management of Uranium Mill Tailings Legacies - 17508

exploitation activities took place at 61 sites. The great majority of these mining sites are located in central-east Portugal, including the Urgeirica mine that was the most important uranium deposit exploited in the country. The mining activities at this site generated 1.6 million m{sup 3} of radioactive wastes disposed in an open air area originating the largest radioactive tailings pile of the country. The environmental remediation of the Urgeirica site was one of the main priorities of the national plan for the rehabilitation of former uranium mining sites. Site remediation, that included the mine industrial area with several support infrastructures and a processing plant, was executed between 2006 and 2008 (1. phase) and between 2008 and 2014 (2. phase). Nevertheless, the environmental rehabilitation of the Portuguese uranium legacies sites is not yet concluded. One of the last largest mining complexes, the Quinta do Bispo open pit, is scheduled to be rehabilitated only in 2020. This work presents a study to evaluate the environmental impacts from the uranium mill tailings legacies before and after the remediation works, focusing on two different approaches: a deterministic methodology for dose assessment and a probabilistic methodology with the Monte Carlo method to estimate the incremental lifetime risk. Probabilistic distributions of the input parameters were used in the risk calculation approach. The methodology for dose and risk assessments may be applied to other sites that are still under intervention and the results may be used to prioritize the remediation stages. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Modern deep neural networks for Direct Normal Irradiance forecasting: A classification approach

The escalating energy demand and the adverse environmental impacts of fossil-fuel use necessitate a shift towards cleaner and renewable alternatives. Concentrated Solar Power (CSP) technology emerges as a promising solution, offering a carbon-free alternative for power generation. The efficiency and profitability of CSP depend on the Direct Normal Irradiance (DNI) component of solar radiation; hence, accurate DNI forecasting can help optimize CSP plants’ operations and performance. The unpredictable nature of weather phenomena, particularly cloud cover, introduces uncertainty into DNI projections. Existing DNI forecasting models use meteorological factors, which are both challenging to estimate numerically over short prediction windows and expensive to model through data at a sufficiently high spatial and temporal resolution. This research addresses the challenge by presenting a novel approach that formulates DNI prediction as a multi-class classification problem, departing from conventional regression-based methods. The primary objective of this classification framework is to identify optimal periods aligning with specific operational thresholds for CSP plants, contributing to enhanced dispatch optimization strategies. We model the DNI classification problem using four advanced deep neural networks – rectified linear unit (ReLU) networks, 1D residual networks (ResNets), bidirectional long short-term memory (BiLSTM) networks, and transformers – achieving accuracies up to 93.5% without requiring meteorological parameters.

14 SOLAR ENERGY↗

DOE OSTI2015

MO-F-CAMPUS-I-01: A System for Automatically Calculating Organ and Effective Dose for Fluoroscopically-Guided Procedures

Purpose: A system was developed that automatically calculates the organ and effective dose for individual fluoroscopically-guided procedures using a log of the clinical exposure parameters. Methods: We have previously developed a dose tracking system (DTS) to provide a real-time color-coded 3D- mapping of skin dose. This software produces a log file of all geometry and exposure parameters for every x-ray pulse during a procedure. The data in the log files is input into PCXMC, a Monte Carlo program that calculates organ and effective dose for projections and exposure parameters set by the user. We developed a MATLAB program to read data from the log files produced by the DTS and to automatically generate the definition files in the format used by PCXMC. The processing is done at the end of a procedure after all exposures are completed. Since there are thousands of exposure pulses with various parameters for fluoroscopy, DA and DSA and at various projections, the data for exposures with similar parameters is grouped prior to entry into PCXMC to reduce the number of Monte Carlo calculations that need to be performed. Results: The software developed automatically transfers data from the DTS log file to PCXMC and runs the program for each grouping of exposure pulses. When the dose from all exposure events are calculated, the doses for each organ and all effective doses are summed to obtain procedure totals. For a complicated interventional procedure, the calculations can be completed on a PC without manual intervention in less than 30 minutes depending on the level of data grouping. Conclusion: This system allows organ dose to be calculated for individual procedures for every patient without tedious calculations or data entry so that estimates of stochastic risk can be obtained in addition to the deterministic risk estimate provided by the DTS. Partial support from NIH grant R01EB002873 and Toshiba Medical Systems Corp.

60 APPLIED LIFE SCIENCES↗