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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Workflows Community Summit 2022: A Roadmap Revolution

Scientific workflows have become integral tools in broad scientific computing use cases. Science discovery is increasingly dependent on workflows to orchestrate large and complex scientific experiments that range from the execution of a cloud-based data preprocessing pipeline to multi-facility instrument-to-edge-to-HPC computational workflows. Given the changing landscape of scientific computing (often referred to as a computing continuum) and the evolving needs of emerging scientific applications, it is paramount that the development of novel scientific workflows and system functionalities seek to increase the efficiency, resilience, and pervasiveness of existing systems and applications. Specifically, the proliferation of machine learning/artificial intelligence (ML/AI) workflows, need for processing large-scale datasets produced by instruments at the edge, intensification of near real-time data processing, support for long-term experiment campaigns, and emergence of quantum computing as an adjunct to HPC, have significantly changed the functional and operational requirements of workflow systems. Workflow systems now need to, for example, support data streams from the edge-to-cloud-to-HPC, enable the management of many small-sized files, allow data reduction while ensuring high accuracy, orchestrate distributed services (workflows, instruments, data movement, provenance, publication, etc.) across computing and user facilities, among others. Further, to accelerate science, it is also necessary that these systems implement specifications/standards and APIs for seamless (horizontal and vertical) integration between systems and applications, as well as enable the publication of workflows and their associated products according to the FAIR principles.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

TU-AB-BRC-07: Efficiency of An IAEA Phase-Space Source for a Low Energy X-Ray Tube Using Egs++

Purpose: To extend the capability of the EGSnrc C++ class library (egs++) to write and read IAEA phase-space files as a particle source, and to assess the relative efficiency gain in dose calculation using an IAEA phase-space source for modelling a miniature low energy x-ray source. Methods: We created a new ausgab object to score particles exiting a user-defined geometry and write them to an IAEA phase-space file. A new particle source was created to read from IAEA phase-space data. With these tools, a phase-space file was generated for particles exiting a miniature 50 kVp x-ray tube (The INTRABEAM System, Carl Zeiss). The phase-space source was validated by comparing calculated PDDs with a full electron source simulation of the INTRABEAM. The dose calculation efficiency gain of the phase-space source was determined relative to the full simulation. The efficiency gain as a function of i) depth in water, and ii) job parallelization was investigated. Results: The phase-space and electron source PDDs were found to agree to 0.5% RMS, comparable to statistical uncertainties. The use of a phase-space source for the INTRABEAM led to a relative efficiency gain of greater than 20 over the full electron source simulation, with an increase of up to a factor of 196. The efficiency gain was found to decrease with depth in water, due to the influence of scattering. Job parallelization (across 2 to 256 cores) was not found to have any detrimental effect on efficiency gain. Conclusion: A set of tools has been developed for writing and reading IAEA phase-space files, which can be used with any egs++ user code. For simulation of a low energy x-ray tube, the use of a phase-space source was found to increase the relative dose calculation efficiency by factor of up to 196. The authors acknowledge partial support by the CREATE Medical Physics Research Training Network grant of the Natural Sciences and Engineering Research Council (Grant No. 432290).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Ground Water Levels for NGEE Areas A, B, C and D, Utqiagvik (Barrow), Alaska, 2012-2014

Ice wedge polygonal tundra water levels were measured at a total of 45 locations representing polygon centers and troughs during three summers. Early season water levels, which were still affected by ice and snow, are represented by manual measurements only. Continuous (less than hourly) measurements followed through early fall (~mid-Sep). The data set contains inundation depth (cm), absolute water level and local ground surface elevation (masl). There are a total of 209 files in this dataset. The data were originally provided in Excel workbooks and these files have been preserved within the zip "Original_Files." The workbooks were also transformed and separated by well ID, year, and/or area into 205 extracted files. The Excel files were transformed for archiving with images pulled out into JPEGs, data preserved as CSV files and some methodological information preserved as TXT files. Some functions, features, and formatting were lost during the transformation. Missing data were defined with blank cells. Additional documentation can be found in files labelled with "information.txt" file endings.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Use of treatment log files in spot scanning proton therapy as part of patient-specific quality assurance

Purpose: The purpose of this work was to assess the monitor unit (MU) values and position accuracy of spot scanning proton beams as recorded by the daily treatment logs of the treatment control system, and furthermore establish the feasibility of using the delivered spot positions and MU values to calculate and evaluate delivered doses to patients. Methods: To validate the accuracy of the recorded spot positions, the authors generated and executed a test treatment plan containing nine spot positions, to which the authors delivered ten MU each. The spot positions were measured with radiographic films and Matrixx 2D ion-chambers array placed at the isocenter plane and compared for displacements from the planned and recorded positions. Treatment logs for 14 patients were then used to determine the spot MU values and position accuracy of the scanning proton beam delivery system. Univariate analysis was used to detect any systematic error or large variation between patients, treatment dates, proton energies, gantry angles, and planned spot positions. The recorded patient spot positions and MU values were then used to replace the spot positions and MU values in the plan, and the treatment planning system was used to calculate the delivered doses to patients. The results were compared with the treatment plan. Results: Within a treatment session, spot positions were reproducible within {+-}0.2 mm. The spot positions measured by film agreed with the planned positions within {+-}1 mm and with the recorded positions within {+-}0.5 mm. The maximum day-to-day variation for any given spot position was within {+-}1 mm. For all 14 patients, with {approx}1 500 000 spots recorded, the total MU accuracy was within 0.1% of the planned MU values, the mean (x, y) spot displacement from the planned value was (-0.03 mm, -0.01 mm), the maximum (x, y) displacement was (1.68 mm, 2.27 mm), and the (x, y) standard deviation was (0.26 mm, 0.42 mm). The maximum dose difference between calculated dose to the patient based on the plan and recorded data was within 2%. Conclusions: The authors have shown that the treatment log file in a spot scanning proton beam delivery system is precise enough to serve as a quality assurance tool to monitor variation in spot position and MU value, as well as the delivered dose uncertainty from the treatment delivery system. The analysis tool developed here could be useful for assessing spot position uncertainty and thus dose uncertainty for any patient receiving spot scanning proton beam therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Performance regression manager for large scale systems

Methods comprising generating, based on a first output generated by a first execution instance of a command, a first output file specifying a value of at least one performance metric, wherein the first output file is formatted according to a predefined format, comparing the value of the at least one performance metric in the first output file to a value of the performance metric in a second output file, the second output file having been generated based on a second output generated by a second execution instance of the command, and outputting for display an indication of a result of the comparison of the value of the at least one performance metric of the first output file to the value of the at least one performance metric of the second output file.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

SU-E-T-69: Cloud-Based Monte Carlo Patient-Specific Quality Assurance (QA) Method for Volumetric Modulated Arc Therapy (VMAT)

Purpose: Patient-specific QA for VMAT is incapable of providing full 3D dosimetric information and is labor intensive in the case of severe heterogeneities or small-aperture beams. A cloud-based Monte Carlo dose reconstruction method described here can perform the evaluation in entire 3D space and rapidly reveal the source of discrepancies between measured and planned dose. Methods: This QA technique consists of two integral parts: measurement using a phantom containing array of dosimeters, and a cloud-based voxel Monte Carlo algorithm (cVMC). After a VMAT plan was approved by a physician, a dose verification plan was created and delivered to the phantom using our Varian Trilogy or TrueBeam system. Actual delivery parameters (i.e., dose fraction, gantry angle, and MLC at control points) were extracted from Dynalog or trajectory files. Based on the delivery parameters, the 3D dose distribution in the phantom containing detector were recomputed using Eclipse dose calculation algorithms (AAA and AXB) and cVMC. Comparison and Gamma analysis is then conducted to evaluate the agreement between measured, recomputed, and planned dose distributions. To test the robustness of this method, we examined several representative VMAT treatments. Results: (1) The accuracy of cVMC dose calculation was validated via comparative studies. For cases that succeeded the patient specific QAs using commercial dosimetry systems such as Delta- 4, MAPCheck, and PTW Seven29 array, agreement between cVMC-recomputed, Eclipse-planned and measured doses was obtained with >90% of the points satisfying the 3%-and-3mm gamma index criteria. (2) The cVMC method incorporating Dynalog files was effective to reveal the root causes of the dosimetric discrepancies between Eclipse-planned and measured doses and provide a basis for solutions. Conclusion: The proposed method offers a highly robust and streamlined patient specific QA tool and provides a feasible solution for the rapidly increasing use of VMAT treatments in the clinic.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Compare Energy Use in Variable Refrigerant Flow Heat Pumps Field Demonstration and Computer Model

Variable Refrigerant Flow (VRF) heat pumps are often regarded as energy efficient air-conditioning systems which offer electricity savings as well as reduction in peak electric demand while providing improved individual zone setpoint control. One of the key advantages of VRF systems is minimal duct losses which provide significant reduction in energy use and duct space. However, there is limited data available to show their actual performance in the field. Since VRF systems are increasingly gaining market share in the US, it is highly desirable to have more actual field performance data of these systems. An effort was made in this direction to monitor VRF system performance over an extended period of time in a US national lab test facility. Due to increasing demand by the energy modeling community, an empirical model to simulate VRF systems was implemented in the building simulation program EnergyPlus. This paper presents the comparison of energy consumption as measured in the national lab and as predicted by the program. For increased accuracy in the comparison, a customized weather file was created by using measured outdoor temperature and relative humidity at the test facility. Other inputs to the model included building construction, VRF system model based on lab measured performance, occupancy of the building, lighting/plug loads, and thermostat set-points etc. Infiltration model inputs were adjusted in the beginning to tune the computer model and then subsequent field measurements were compared to the simulation results. Differences between the computer model results and actual field measurements are discussed. The computer generated VRF performance closely resembled the field measurements.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Continuous Snow Depth, Intensive Site 1, Utqiagvik (Barrow), Alaska, 2012-2014

Continuous Snow depth data were collected at several points within four intensive study areas in near Utqiagvik (Barrow), Alaska. All sites were located on polygonal permafrost and co-located with micromet surface measurements and subsurface measurements. These data assist in the calculation of the energy balance at the land surface and will also be useful as inputs into modeling activities. Included are 18 CSV data files and one file level metadata CSV file. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

NGEE Arctic Tram: Overview of Tram-mounted Instruments, Co-located Data, Measurement Position, Elevation and Polygon Characterization, Utqiagvik (Barrow), Alaska, 2014-2018

The NGEE-Arctic Tram operated from 2014 - 2018. It was installed on the Barrow Environmental Observatory in Barrow, Alaska in late May of 2014 and operated through mid-November 2014. The subsequent 2015 through 2018 years followed a similar schedule, but with different deployment dates and data gaps, with the goal always to capture the surface dynamics of the snow melt, growing, and freeze-up seasons. This Tram overview dataset has three objectives: (1) provide new data users with a brief description of the Tram system and its research purposes; (2) provide generally useful Tram site characterization details, including measurement position ground surface elevation, characteristics of the Arctic polygonal tundra under the Tram, vegetation community composition (future), and derived image products; and (3) reference all of the data products and archived datasets that were collected with the Tram-mounted sensors and co-located instruments. This dataset contains two csv files, two zipped files, one tif file, and one pdf file. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Utilization Analysis in Low-Temperature Geothermal Play Fairway Analysis for the Appalachian Basin (GPFA-AB)

This submission of Utilization Analysis data to the Geothermal Data Repository (GDR) node of the National Geothermal Data System (NGDS) is in support of Phase 1 Low Temperature Geothermal Play Fairway Analysis for the Appalachian Basin. The submission includes data pertinent to the methods and results of an analysis of the Surface Levelized Cost of Heat (SLCOH) for US Census Bureau Places within the study area. This was calculated using a modification of a program called GEOPHIRES, available at http://koenraadbeckers.net/geophires/index.php. The MATLAB modules used in conjunction with GEOPHIRES, the MATLAB data input file, the GEOPHIRES output data file, and an explanation of the software components have been provided. Results of the SLCOH analysis appear on 4 .png image files as mapped risk of heat utilization. For each of the 4 image (.png) files, there is an accompanying georeferenced TIF (.tif) file by the same name. In addition to calculating SLCOH, this Task 4 also identified many sites that may be prospects for use of a geothermal district heating system, based on their size and industry, rather than on the SLCOH. An industry sorted listing of the sites (.xlsx) and a map of these sites plotted as a layer onto different iterations of maps combining the three geological risk factors (Thermal Quality, Natural Reservoir Quality, and Risk of Seismicity) has been provided. In addition to the 6 image (.png) files of the maps in this series, a shape (.shp) file and 7 associated files are included as well. Finally, supporting files (.pdf) describing the utilization analysis methodology and summarizing the anticipated permitting for a deep district heating system are supplied. UPDATE: Newer version of the Utilization Analysis has been added here: https://gdr.openei.org/submissions/878

15 GEOTHERMAL ENERGY↗
DOE OSTI2015

GPFA-AB_Phase1UtilizationTask4DataUpload

This submission of Utilization Analysis data to the Geothermal Data Repository (GDR) node of the National Geothermal Data System (NGDS) is in support of Phase 1 Low Temperature Geothermal Play Fairway Analysis for the Appalachian Basin (project DE-EE0006726). The submission includes data pertinent to the methods and results of an analysis of the Surface Levelized Cost of Heat (SLCOH) for US Census Bureau ‘Places’ within the study area. This was calculated using a modification of a program called GEOPHIRES, available at http://koenraadbeckers.net/geophires/index.php. The MATLAB modules used in conjunction with GEOPHIRES, the MATLAB data input file, the GEOPHIRES output data file, and an explanation of the software components have been provided. Results of the SLCOH analysis appear on 4 .png image files as mapped ‘risk’ of heat utilization. For each of the 4 image (.png) files, there is an accompanying georeferenced TIF (.tif) file by the same name. In addition to calculating SLCOH, this Task 4 also identified many sites that may be prospects for use of a geothermal district heating system, based on their size and industry, rather than on the SLCOH. An industry sorted listing of the sites (.xlsx) and a map of these sites plotted as a layer onto different iterations of maps combining the three geological risk factors (Thermal Quality, Natural Reservoir Quality, and Risk of Seismicity) has been provided. In addition to the 6 image (.png) files of the maps in this series, a shape (.shp) file and 7 associated files are included as well. Finally, supporting files (.pdf) describing the utilization analysis methodology and summarizing the anticipated permitting for a deep district heating system are supplied.

15 GEOTHERMAL ENERGY↗
DOE OSTI2016

SU-G-BRA-12: Development of An Intra-Fractional Motion Tracking and Dose Reconstruction System for Adaptive Stereotactic Body Radiation Therapy in High-Risk Prostate Cancer

Purpose: A clinical trial on stereotactic body radiation therapy (SBRT) for high-risk prostate cancer is undergoing at our institution. In addition to escalating dose to the prostate, we have increased dose to intra-prostatic lesions. Intra-fractional prostate motion deteriorates well planned radiation dose, especially for the small intra-prostatic lesions. To solve this problem, we have developed a motion tracking and 4D dose-reconstruction system to facilitate adaptive re-planning. Methods: Patients in the clinical trial were treated with VMAT using four arcs and 10 FFF beam. KV triggered x-ray projections were taken every 3 sec during delivery to acquire 2D projections of 3D anatomy at the direction orthogonal to the therapeutic beam. Each patient had three implanted prostate markers. Our developed system first determined 2D projection locations of these markers and then 3D prostate translation and rotation via 2D/3D registration of the markers. Using delivery log files, our GPU-based Monte Carlo tool (goMC) reconstructed dose corresponding to each triggered image. The calculated 4D dose distributions were further aggregated to yield the delivered dose. Results: We first tested each module in our system. MC dose engine were commissioned to our treatment planning system with dose difference of <0.5%. For motion tracking, 1789 kV projections from 7 patients were acquired. The 2D marker location error was <1 mm. For 3D motion tracking, root mean square (RMS) errors along LR, AP, and CC directions were 0.26mm, 0.36mm, and 0.01mm respectively in simulation studies and 1.99mm, 1.37mm, and 0.22mm in phantom studies. We also tested the entire system workflow. Our system was able to reconstruct delivered dose. Conclusion: We have developed a functional intra-fractional motion tracking and 4D dose re-construction system to support our clinical trial on adaptive high-risk prostate cancer SBRT. Comprehensive evaluations have shown the capability and accuracy of our system.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Initial experience of ArcCHECK and 3DVH software for RapidArc treatment plan verification

The purpose of this study was to perform delivery quality assurance with ArcCHECK and 3DVH system (Sun Nuclear, FL) and to evaluate the suitability of this system for volumetric-modulated arc therapy (VMAT) (RapidArc [RA]) verification. This software calculates the delivered dose distributions in patients by perturbing the calculated dose using errors detected in fluence or planar dose measurements. The device is tested to correlate the gamma passing rate (%GP) and the composite dose predicted by 3DVH software. A total of 28 patients with prostate cancer who were treated with RA were analyzed. RA treatments were delivered to a diode array phantom (ArcCHECK), which was used to create a planned dose perturbation (PDP) file. The 3DVH analysis used the dose differences derived from comparing the measured dose with the treatment planning system (TPS)-calculated doses to perturb the initial TPS-calculated dose. The 3DVH then overlays the resultant dose on the patient's structures using the resultant “PDP” beams. Measured dose distributions were compared with the calculated ones using the gamma index (GI) method by applying the global (Van Dyk) normalization and acceptance criteria, i.e., 3%/3 mm. Paired differences tests were used to estimate statistical significance of the differences between the composite dose calculated using 3DVH and %GP. Also, statistical correlation by means of logistic regression analysis has been analyzed. Dose-volume histogram (DVH) analysis for patient plans revealed small differences between treatment plan calculations and 3DVH results for organ at risk (OAR), whereas planning target volume (PTV) of the measured plan was systematically higher than that predicted by the TPS. The t-test results between the planned and the estimated DVH values showed that mean values were incomparable (p < 0.05). The quality assurance (QA) gamma analysis 3%/3 mm showed that in all cases there were only weak-to-moderate correlations (Pearson r: 0.12 to 0.74). Moreover, clinically relevant differences increased with increasing QA passing rate, indicating that some of the largest dose differences occurred in the cases of high QA passing rates, which may be called “false negatives.” The clinical importance of any disagreement between the measured and the calculated dose is often difficult to interpret; however, beam errors (either in delivery or in TPS calculation) can affect the effectiveness of the patient dose. Further research is needed to determinate the role of a PDP-type algorithm to accurately estimate patient dose effect.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2022

L0 Data from the 2018 NGEE Arctic LiDAR and Imagery Unoccupied Aerial System Campaign at the Teller 47 Field Site, Seward Peninsula, Alaska

Airborne remote sensing data collected from Los Alamos National Laboratory's (LANL) heavy-lift unoccupied aerial system (UAS) hexacopter platform operated by NGEE Arctic scientists from EES-14 (Earth System Observations group) at Los Alamos National Laboratory. These data were collected in July 2018 at a field site near mile marker 47 along the Teller road between Nome, Alaska and Teller, Alaska. A DJI Matrice 600 Pro Airframe and Routescene UAV LiDARSystem was used to collect LiDAR data, and DJI Phantom 4 Advanced was used to collect optical red/green/blue (RGB) imagery at regular intervals along 11 flight paths. This data package contains unprocessed data products (processing level 0) including flight paths, raw photos, and raw lidar data files (*.kml, *.jpg, and *.lpd formats). Ancillary aircraft data, flight mission parameters, and general flight conditions are also included (see Supplemental Files, *.rinex, and *.rtcm3 files). The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

CHARMM-GUI Drude prepper for molecular dynamics simulation using the classical Drude polarizable force field

Explicit treatment of electronic polarizability in empirical force fields (FFs) represents an extension over a traditional additive or pairwise FF and provides a more realistic model of the variations in electronic structure in condensed phase, macromolecular simulations. To facilitate utilization of the polarizable FF based on the classical Drude oscillator model, Drude Prepper has been developed in CHARMM-GUI. Drude Prepper ingests additive CHARMM protein structures file (PSF) and pre-equilibrated coordinates in CHARMM, PDB, or NAMD format, from which the molecular components of the system are identified. These include all residues and patches connecting those residues along with water, ions, and other solute molecules. This information is then used to construct the Drude FF-based PSF using molecular generation capabilities in CHARMM, followed by minimization and equilibration. In addition, inputs are generated for molecular dynamics (MD) simulations using CHARMM, GROMACS, NAMD, and OpenMM. Validation of the Drude Prepper protocol and inputs is performed through conversion and MD simulations of various heterogeneous systems that include proteins, nucleic acids, lipids, polysaccharides, and atomic ions using the aforementioned simulation packages. Stable simulations are obtained in all studied systems, including 5 μs simulation of ubiquitin, verifying the integrity of the generated Drude PSFs. Additionally, the ability of the Drude FF to model variations in electronic structure is shown through dipole moment analysis in selected systems. Finally, the capabilities and availability of Drude Prepper in CHARMM-GUI is anticipated to greatly facilitate the application of the Drude FF to a range of condensed phase, macromolecular systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

The (n, α) Reaction in the s-process Branching Point {sup 59}Ni

The (n, α) reaction in the radioactive {sup 59}Ni is of relevance in nuclear astrophysics as {sup 59}Ni can be considered as the first branching point in the astrophysical s-process. Its relevance in nuclear technology is especially related to material embrittlement in stainless steel. However, there is a discrepancy between available experimental data and the evaluated nuclear data files for this reaction. At the n{sub T}OF facility at CERN, a dedicated system based on sCVD diamond diodes was set up to measure the {sup 59}Ni(n, α){sup 56}Fe cross section. The results of this measurement, with special emphasis on the dominant resonance at 203 eV, are presented here.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

SU-E-T-424: Dosimetric Verification of Modulated Electron Radiation Therapy Delivered Using An Electron Specific Multileaf Collimator for Treatment of Scalp Cases

Purpose: Modulated electron radiotherapy (MERT) has the potential to achieve better treatment outcome for shallow tumors such as those of breast and scalp. In a separate study with scalp lesions, MERT was compared to volumetric modulated arc therapy. Our results showed a reduction in the dose reaching the brain with MERT. However dose calculation accuracy and delivery efficiency challenges remain. Thus in the current study we proceed to add more cases to demonstrate MERT beneficial outcome and its delivery accuracy using an electron specific multileaf collimator (eMLC). Methods: We have used the MCBEAM code for treatment head simulation and for generating phase space files to be used as radiation source input for our Monte Carlo based treatment planning system (MC TPS). MCPLAN code is used for calculation of patient specific dose deposition coefficient and for final MERT plan dose calculation. An in-house developed optimization code is used for the optimization process. MERT plans were generated for real patients and head and neck phantom. Film was used for dosimetric verification. The film was cut following the contour of the curved phantom surface and then sealed with black masking tape. In the measurement, the sealed film packet was sandwiched between two adjacent slabs of the head and neck phantom. The measured 2D dose distribution was then compared with calculations. Results: The eMLC allows effective treatment of scalps with multi-lesions spreading around the patient head, which was usually difficult to plan or very time consuming with conventional applicators. MERT continues to show better reduction in the brain dose. The dosimetric measurements showed slight discrepancy, which was attributed to the film setup. Conclusion: MERT can improve treatment plan quality for patients with scalp cancers. Our in-house MC TPS is capable of performing treatment planning and accurate dose calculation for MERT using the eMLC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-P-36: Evaluation of MLC Positioning Errors in Dynamic IMRT Treatments by Analyzing Dynalog Files

Purpose: To assess the accuracy of MLC positioning in Varian linear accelerator, in dynamic IMRT technique, from the analysis of dynalog files generated by the MLC controller. Methods: In Clinac accelerators (pre-TrueBeam technology), control system has an approximately 50ms delay (one control cycle time). Then, the system compares the measured position to the planned position corresponding to the next control cycle. As it has been confirmed by Varian technical support, this effect causes that measured positions appear in dynalogs one cycle out of phase with respect to the planned positions. Around 9000 dynalogs have been analyzed, coming from the three linear accelerators of our center (one Trilogy and two Clinac 21EX) equipped with a Millennium 120 MLC. In order to compare our results to recent publications, leaf positioning errors (RMS and 95th percentile) are calculated with and without delay effect. Dynalogs have been analyzed using a in-house Matlab software. Results: The RMS errors were 0.341, 0.339 and 0.348mm for each Linac; being the average error 0.343 mm. The 95th percentiles of the error were 0.617, 0.607 and 0.625; with an average of 0.617mm. A recent multi-institution study carried out by Kerns et al. found a mean leaf RMS error of 0.32mm and a 95th percentile error value of 0.64mm.Without delay effect, mean leaf RMS errors obtained were 0.040, 0.042 and 0.038mm for each treatment machine; being the average 0.040mm. The 95th percentile error values obtained were 0.057, 0.058 and 0.054 mm, with an average of 0.056mm. Conclusion: Results obtained for the mean leaf RMS error and the mean 95th percentile were consistent with the multi-institution study. Calculated error statistics with delay effect are significantly larger due to the speed proportional and systematic leaf offset. Consequently it is proposed to correct this effect in dynalogs analysis to determine the MLC performance.

60 APPLIED LIFE SCIENCES↗