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At least 1,279 records · Page 71

COMPASS-FME Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) Experiment Level 1 Sensor Data v2-1

This is the version 2-1 Level 1 (L1) data release for COMPASS-FME environmental sensors located at our Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) experimental site. This manipulative, ecosystem-scale TEMPEST experiment addresses the potential for freshwater and estuarine-water disturbance events to alter tree function, species composition, and ecosystem processes in a deciduous coastal forest in MD, USA. The experiment uses a large-unit (2000 m2), un-replicated experimental design, with three 50 m × 40 m plots serving as control, freshwater, and estuarine-water treatments. L1 data are close to raw, but are units-transformed and have out-of-instrument-bounds, out-of-service, and outlier flags added. Duplicates and missing data are removed but otherwise these data are not filtered, and have not been subject to any additional algorithmic or human QA/QC. Any scientific analyses of L1 data should be performed with care. **This dataset will be updated quarterly with new data for the duration of the project** This dataset includes: - An overall dataset README file that describes the current version, gives citation and contact information, etc. - Site- and year-specific folders, each holding variable-specific CSV (comma separated value) data files for each site and plot in that year. - Metadata files within each site-year folder provide full information on data units, expected ranges, contact information, detailed flood times, as well as a general description of the site. - Environmental sensor types that appear in the data files include weather (ClimaVUE50, CS, RM Young, and LI instruments in the graphs below); soil conditions (TEROS12); soil redox state (Redox); groundwater variables (AquaTROLL200 and AquaTROLL600); open water sondes (Exo); tree sap velocity (Sapflow); and system voltage and state (Datalogger). Data are normally logged every 15 minutes. Please see v2-1 TEMPEST L1 Sensor Package Quick Start.pdf for detailed information on data package structure, temporal coverage, and versioning. The TEMPEST flood events occurred on the following dates. They lasted for ~10 hours each day and delivered ~80,000 gallons to each plot; many data streams are available at 1 or 5 minute frequency during these periods. * Tests: Aug 25 (fresh plot) and Sep 9 (salt plot), 2021 * TEMPEST 1: June 22, 2022 * TEMPEST 2: June 6-7, 2023 * TEMPEST 3: June 11-13, 2024 This dataset was updated 2026-03-12: (i) data now go through 2025-12-31 (previous end was 2025-06-30) and (ii) dataset and file names updated to “…v2-1” (previously was “v2-0”).

54 ENVIRONMENTAL SCIENCES↗

SU-C-BRD-03: Closing the Loop On Virtual IMRT QA

Purpose: To develop an algorithm that predicts a priori IMRT QA passing rates. Methods: 416 IMRT plans from all treatment sites were planned in Eclipse version 11 and delivered using a dynamic sliding window technique on Clinac iX or TrueBeam linacs (Varian Medical Systems, Palo Alto, CA). The 3%/3mm and 2%/2mm local distance to agreement (DTA) were recorded during clinical operations using a commercial 2D diode array (MapCHECK 2, Sun Nuclear, Melbourne, FL). Each plan was characterized by 37 metrics that describe different failure modes between the calculated and measured dose. Machine-learning algorithms (MLAs) were trained to learn the relation between the plan characteristics and each passing rate. Minimization of the cross validated error, together with maximum a posteriori estimation (MAP), were used to choose the model parameters. Results: 3%/3mm local DTA can be predicted with an error smaller than 3% for 98% of the plans. For the remaining 2% of plans, the residual error was within 5%. For 2%/2mm local DTA passing rates, 96% percent of the plans were successfully predicted with an error smaller than 5%. All high-risk plans that failed the 2%/2mm local criteria were correctly identified by the algorithm. The most important metric to describe the passing rates was determined to be the MU per Gray (modulation factor). Conclusions: Logs files and independent dose calculations have been suggested as possible substitutes for measurement based IMRT QA. However, none of these methods answer the fundamental question of whether a plan can be delivered with a clinically acceptable error given the limitations of the linacs and the treatment planning system. Predicting the IMRT QA passing rates a priori closes that loop. For additional robustness, virtual IMRT QA can be combined with Linac QA and log file analysis to confirm appropriate delivery.

60 APPLIED LIFE SCIENCES↗

Tidal Turbine Test, Downeast Turbines, July 12, 2021

Downeast Turbines tested a tidal turbine prototype with novel rotor/channel system and lateral effluent discharge apparatus (LEDA), during five days of testing in the flume at Alden Lab. Three days of testing (July 12-14, 2021) focused on turbine power metrics of torque and rpm, which were low, and then two days of follow-up testing (July 27-28, 2021) focused on LEDA performance metrics of pressure differential and rates of volumetric flow, with encouraging results. Next step is to to characterize, and even optimize, configurations of the LEDA, using 3D-CFD as a helpful tool, to refine its shape and explore its limits of performance as a means of effluent discharge that augments performance of an instream turbine. An improved configuration of the LEDA will be re-combined with the rotor/channel system of the turbine prototype, and ultimately, the rotor will be re-sized (enlarged), to better match the LEDA's performance capabilities in drawing through a rate of volumetric flow. This submission is Downeast Turbines' Post Access Report for the test event. It includes the files described here (next below), and several reference links. "Downeast TEAMER-Post-Access-Report...docx" is a document file containing the report. "Appendices A, B, and C" are included in this file, and so are "Figures #1-7." "Appendix D - Test Data Workbooks.zip" is an archive file containing all post access data (raw data tables, calculating tables, and graphs), presented in fourteen Excel workbooks as described in the report. "Appendix E - Post Access Figures.zip" is an archive file containing "Figures #8-52," of the report.

16 TIDAL AND WAVE POWER↗

SU-E-T-241: Design and Implement of An Information Management System for Radiation Workers in a Hospital

Purpose: To meet the special needs of Medical Administration Division, an information management system for radiation workers in a hospital(IMSRWH) has been developed. Methods: There are about 200 radiation workers in 20 departments, such as department of radiology, department of radiation oncology, department of nuclear medicine, and so on. An IMSRWH server was used to run a database and web service of Apache+PHP+MySQL. The IMSRWH web service could be accessed with Internet Explorer(IE) to input, search, count, and print the radiation workers’ data. Every worker’s data information includes the following tables: registration, personal dose monitoring records, personnel certificate, training certificate, personnel license, medical examination, etc, and each table includes more optional detail information. Results: In the past year, the IMSRWH has been successfully developed and implemented in the hospital. According to the needs, the user rights are divided into: the system administrator, office manager, department manager and radiation worker. The different users have the different interfaces, and the appropriate authority permissions mean corresponding operations. The administrator and office manager could manage all personnel information, department manager could manage the staff information of his department, and the workers could view or modify their own information. Because information updates, involving hundreds of each entry and modification are complicated, each table information of all workers can be batch import from or export to a Microsoft Excel CSV format file, to update all together. However, it has only Chinese version now. Conclusion: It was demonstrated to be user-friendly and was proven to significantly improve the efficiency of the hospital management. Since it is an in-house developed system, more functions can be added or modified to further enhance its potentials in research and clinical practice.

60 APPLIED LIFE SCIENCES↗

MO-G-BRE-03: Automated Continuous Monitoring of Patient Setup with Second-Check Independent Image Registration

Purpose: To create a non-supervised quality assurance program to monitor image-based patient setup. The system acts a secondary check by independently computing shifts and rotations and interfaces with Varian's database to verify therapist's work and warn against sub-optimal setups. Methods: Temporary digitally-reconstructed radiographs (DRRs) and OBI radiographic image files created by Varian's treatment console during patient setup are intercepted and used as input in an independent registration module customized for accuracy that determines the optimal rotations and shifts. To deal with the poor quality of OBI images, a histogram equalization of the live images to the DDR counterparts is performed as a pre-processing step. A search for the most sensitive metric was performed by plotting search spaces subject to various translations and convergence analysis was applied to ensure the optimizer finds the global minima. Final system configuration uses the NCC metric with 150 histogram bins and a one plus one optimizer running for 2000 iterations with customized scales for translations and rotations in a multi-stage optimization setup that first corrects and translations and subsequently rotations. Results: The system was installed clinically to monitor and provide almost real-time feedback on patient positioning. On a 2 month-basis uncorrected pitch values were of a mean 0.016° with standard deviation of 1.692°, and couch rotations of − 0.090°± 1.547°. The couch shifts were −0.157°±0.466° cm for the vertical, 0.045°±0.286 laterally and 0.084°± 0.501° longitudinally. Uncorrected pitch angles were the most common source of discrepancies. Large variations in the pitch angles were correlated with patient motion inside the mask. Conclusion: A system for automated quality assurance of therapist's registration was designed and tested in clinical practice. The approach complements the clinical software's automated registration in terms of algorithm configuration and performance and constitutes a practical approach to implement safe and cost-effective radiotherapy.

60 APPLIED LIFE SCIENCES↗

Merged Observatory Data Files (MODFs): an integrated observational data product supporting process-oriented investigations and diagnostics

A large and ever-growing body of geophysical information is measured in campaigns and at specialized observatories as a part of scientific expeditions and experiments. These collections of observed data include many essential climate variables (as defined by the Global Climate Observing System) but are often distinguished by a wide range of additional non-routine measurements that are designed to not only document the state of the environment but also the drivers that contribute to that state. These field data are used not only to further understand environmental processes through observation-based studies but also to provide baseline data to test model performance and to codify understanding to improve predictive capabilities. To address the considerable barriers and difficulty in utilizing these diverse and complex data for observation–model research, the Merged Observatory Data File (MODF) concept has been developed. A MODF combines measurements from multiple instruments into a single file that complies with well-established data format and metadata practices and has been designed to parallel the development of corresponding Merged Model Data Files (MMDFs). Using the MODF and MMDF protocols will facilitate the evolution of model intercomparison projects into model intercomparison and improvement projects by putting observation and model data “on the same page” in a timely manner. The MODF concept was developed especially for weather forecast model studies in the Arctic. The surprisingly complex process of implementing MODFs in that context refined the concept itself. Thus, this article explains the concept of MODFs by providing details on the issues that were revealed and resolved during that first specific implementation. Detailed instructions are provided on how to make MODFs, and this article can be considered a MODF creation manual.

54 ENVIRONMENTAL SCIENCES↗

Parallel Event Selection on HPC Systems

In their recent measurement of the neutrino oscillation parameters,NOvA uses a sample of approximately 25 million reconstructed spills to searchfor electron-neutrino appearance events. These events are stored in an n-tupleformat, in 250 thousand ROOT files. File sizes range from a few hundred KiB toa few MiB; the full dataset is approximately 1.4 TiB. These millions of eventsare reduced to a few tens of events by the application of strict event selectioncriteria, and then summarized by a handful of numbers each, which are used inthe extraction of the neutrino oscillation parameters.The NOvA event selection code is currently a serial C++ program that readsthese n-tuples. The current table data format and organization and the selection/reduction processing involved provides us with an opportunity to explorealternate approaches to represent the data and implement the processing. Werepresent our n-tuple data in HDF5 format that is optimized for the HPC environmentand which allows us to use the machine’s high-performance parallelI/O capabilities. We use MPI, numpy and h5py to implement our approach andcompare the performance with the existing approach. We study the performanceimplications of using thousands of small files of different sizes as comparedwith one large file using HPC resources. This work has been done as part of theSciDAC project, “HEP analytics on HPC” in collaboration with the ASCR teamsat ANL and LBNL.

Paterno, Marc↗

WE-D-BRA-05: Pseudo In Vivo Patient Dosimetry Using a 3D-Printed Patient-Specific Phantom

Purpose: To test the feasibility of using 3D-printed patient-specific phantoms for intensity-modulated radiation therapy (IMRT) quality assurance (QA). Methods: We created a patient-specific whole-head phantom using a 3D printer. The printer data file was created from high-resolution DICOM computed tomography (CT) images of 3-year old child treated at our institution for medulloblastoma. A custom-modified extruder system was used to create tissue-equivalent materials. For the printing process, the Hounsfield Units from the CT images were converted to proportional volumetric densities. A 5-field IMRT plan was created from the patient CT and delivered to the 3D- phantom. Dose was measured by an ion chamber placed through the eye. The ion chamber was placed at the posterior edge of the planning target volume in a high dose gradient region. CT scans of the patient and 3D-phantom were fused by using commercial treatment planning software (TPS). The patient’s plan was calculated on the phantom CT images. The ion chamber’s active volume was delineated in the TPS; dose per field and total dose were obtained. Measured and calculated doses were compared. Results: The 3D-phantom dimensions and tissue densities were in good agreement with the patient. However, because of a printing error, there was a large discrepancy in the density in the frontal cortex. The calculated and measured treatment plan doses were 1.74 Gy and 1.72 Gy, respectively. For individual fields, the absolute dose difference between measured and calculated values was on average 3.50%. Conclusion: This study demonstrated the feasibility of using 3D-printed patient-specific phantoms for IMRT QA. Such phantoms would be particularly advantageous for complex IMRT treatment plans featuring high dose gradients and/or for anatomical sites with high variation in tissue densities. Our preliminary findings are promising. We anticipate that, once the printing process is further refined, the agreement between measured and calculated doses will improve.

60 APPLIED LIFE SCIENCES↗

A Monte Carlo calculation model of electronic portal imaging device for transit dosimetry through heterogeneous media

Purpose: To develop and evaluate a fast Monte Carlo (MC) dose calculation model of electronic portal imaging device (EPID) based on its effective atomic number modeling in the XVMC code. Methods: A previously developed EPID model, based on the XVMC code by density scaling of EPID structures, was modified by additionally considering effective atomic number (Z{sub eff}) of each structure and adopting a phase space file from the EGSnrc code. The model was tested under various homogeneous and heterogeneous phantoms and field sizes by comparing the calculations in the model with measurements in EPID. In order to better evaluate the model, the performance of the XVMC code was separately tested by comparing calculated dose to water with ion chamber (IC) array measurement in the plane of EPID. Results: In the EPID plane, calculated dose to water by the code showed agreement with IC measurements within 1.8%. The difference was averaged across the in-field regions of the acquired profiles for all field sizes and phantoms. The maximum point difference was 2.8%, affected by proximity of the maximum points to penumbra and MC noise. The EPID model showed agreement with measured EPID images within 1.3%. The maximum point difference was 1.9%. The difference dropped from the higher value of the code by employing the calibration that is dependent on field sizes and thicknesses for the conversion of calculated images to measured images. Thanks to the Z{sub eff} correction, the EPID model showed a linear trend of the calibration factors unlike those of the density-only-scaled model. The phase space file from the EGSnrc code sharpened penumbra profiles significantly, improving agreement of calculated profiles with measured profiles. Conclusions: Demonstrating high accuracy, the EPID model with the associated calibration system may be used for in vivo dosimetry of radiation therapy. Through this study, a MC model of EPID has been developed, and their performance has been rigorously investigated for transit dosimetry.

60 APPLIED LIFE SCIENCES↗

SU-F-T-276: Source Modeling and VMAT Quality Assurance Referring to the TrueBeam Representative Beam Data for Eclipse

Purpose: To study quality assurance (QA) of volumetric modulated arc therapy (VMAT) after the 6MV and 10MV photon beam source modeling, referring to the Varian TrueBeam representative beam data for Eclipse. Methods: The source model needs specific measured beam data, such as PDDs and profiles, diagonal profile, output factors (OFs), and MLC transmission factor (TF) and dosimetric leaf gap (DLG), et al. We downloaded the representative data from myVarian website, which includes TrueBeam 4MV-15MV photon beam data and 6MeV-22MeV electron beam data in w2CAD file format for use with Eclipse and in Excel spreadsheet format for use in data comparison. The beam data in W2CAD format can be imported into the Eclipse system and calibrated for use, as appropriate. We used PTW MP3 water tank to measure the beam data in some typical field sizes, and compared the measured data with the representative data. We found that the PDDs, profiles and OFs are similar. However according to some papers and our measurements, we decided that our MLC TF and DLG are 1.58 and 1.33 (6MV), 1.79 and 1.57 (10MV), respectively. After we had configured the anisotropic analytical algorithm (AAA) with the representative data in Eclipse, we also have done dosimetric verification for 88 VMAT plans. Results: The end-to-end test procedures of VMAT were performed for 6MV and 10MV energy modes. The NE Farmer ion chamber mean measurements showed 1.2% (6MV, 38 cases) and 1.2% (10MV, 50 cases) between measurement and calculation; the Sun Nuclear ArcCheck mean measurements demonstrated gamma pass rates are as followings: 98.9%, 93.2%, 61.0% for 6MV, and 98.9%, 91.9%, 59.5% for 10MV, using 3%/3mm, 2%/2mm, 1%/1mm, 10% threshold criteria, respectively. Conclusion: The representative data is applicable to our TrueBeam for the VMAT plan, though our MLC factors are a little different, and its patientspecific QA is good.

60 APPLIED LIFE SCIENCES↗

Cyote-attack Chain Estimator

Attack Chain Estimator (ACE) Application Overview The Attack Chain Estimator (ACE) Application is a sophisticated tool designed for the ingestion, classification, sequencing, and enrichment of cybersecurity threat reports. This application leverages advanced machine learning models and extensive historical data to provide comprehensive insights into cyber threats, specifically targeting Industrial Control Systems (ICS). Purpose The primary functions of the ACE Application include: Ingestion of Cybersecurity Threat Reporting: Capable of ingesting text-based threat reports in markdown or text file format. Supports ingestion of structured data from other sources in STIX/JSON format. Classification of Report’s Text-Based Events: Utilizes a DeBERTa classifier, specifically trained on cybersecurity data, to map the events to MITRE ATT&CK for ICS Tactics and Techniques. Classification is performed using multiple Jupyter notebooks and machine learning workflows hosted as FastAPI microservices: regex_data deberta_base_35_train_hft_classifier_mlflow.ipynb hft_regex_classifier_mlflow.ipynb param_train_hft_classifier_mlflow.ipynb regex_tactic_tech.ipynb Ordering of Tactics, Techniques, and Observable Events: Sequences the identified tactics, techniques, and events to form a coherent attack chain. Enrichment with Historical Attack Chain Details: Enhances the attack chain with details from historical attacks using a Markov model developed from CyOTE Precursor Analysis Report data. The Markov model is available as a FastAPI endpoint for seamless integration. Enrichment with Adversary Emulation Capabilities Data: Integrates adversary emulation capabilities data using MITRE Caldera for OT adversary abilities UUIDs. Export of Output Files: Provides options to export the enriched attack chain in JSON or CSV formats. Routing of Output to Other Applications: Facilitates routing of output to various platforms and applications, including: Threat Intelligence Platforms COREII Scout for Threat Intelligence Analysis COREII Modeling and Simulation for Adversary Emulation Technical Description The ACE Application is an advanced cybersecurity tool designed to provide detailed threat analysis and sequence generation. It is built on a robust architecture that integrates natural language processing, machine learning, and historical data modeling. Key Components: Data Ingestion Module: Handles the input of threat reports and data from various formats, ensuring flexibility in data sources. Classification Engine: Employs DeBERTa-based classifiers hosted as FastAPI microservices to analyze and classify threat report events in accordance with the MITRE ATT&CK framework for ICS. Sequence Generator: Orders the classified events into a logical attack chain, providing clear insight into the sequence of tactics and techniques used in the threat. Enrichment Engine: Integrates historical data and adversary emulation capabilities to enhance the attack chain with valuable context and additional details. The historical data enrichment is powered by a Markov model, which is available as a FastAPI endpoint. Export and Routing Module: Facilitates the export of the enriched attack chain in multiple formats and routes the output to designated applications for further analysis or emulation.

Paul, Tony [Idaho National Laboratory (INL), Idaho↗

EGS Collab Experiment 2: Testbed Well Orientation Data

This dataset contains the north seeking gyro data for each of the 11 boreholes drilled at the Experiment 2 testbed on the 4100 foot level of the SURF (Sanford Underground Research Facility). Each gyro file is in individual folders for each well. A single folder called 'E2 All Well Trajectories' contains the trajectories for all the wells but in the mine coordinate system. An image of the well layout is provided in a PowerPoint.

15 GEOTHERMAL ENERGY↗

Depth and elevation of floodplain fine sediment along the East River near Crested Butte, Colorado measured in 2016 and 2017

The depth of floodplain fine sediment was measured at 1,601 points along the East River near Crested Butte, Colorado spanning a study reach approximately 800 m in length in 2016 and 2017. These depths are being used to estimate the volume of floodplain sediment present along the study reach, converted into mass of sediment using bulk density measurements, and finally used to estimate the mass of organic carbon stored in the floodplain based on elemental analysis of percent organic carbon content. Recorded depths include a minimum of 1 cm, a median of 56 cm, a maximum of 175 cm, and a mean with standard deviation of 61 ± 34 cm. This data include a csv file of the coordinates for each point in NAD 83 UTM zone 13, measured sediment depths, distance from the river channel active during 2015 measured using geographic information systems, the elevation of the floodplain surface derived from 0.5-m resolution lidar, and the elevation of the underlying gravel/bedrock surface, and in some cases the distance from the active channel measured in the field along the sampling transect. Also included is an ESRI ArcMap shapefile of the measurement points complete with the data listed above.

54 ENVIRONMENTAL SCIENCES↗

Airborne Imagery Collections, Utqiagvik (Barrow), Alaska, 2013

The data here are orthomosaics, digital surface models (DSMs), and individual frames captured during low altitude airborne flights in 2013 at the Barrow Environmental Observatory. The orthomosaics, thermal IR mosaics, and DSMs were generated from the individual frames using Structure from Motion techniques. Data were collected to characterize the optical and thermal properties of the landscape and how they differ between two points in time with different vegetative and hydrologic conditions. The orthomosaic tiles, thermal IR mosaics, and DSMs are geotiffs in NAD 83 UTM Zone 4 named by their lower-left coordinate. Metadata for the raw imagery are contained in the .exif headers in the files for the optical imagery only. XYZ files contain the IR temperatures at various longitudes and latitudes. Supported by the U.S. DOE Arctic NGEE program and the Alaska Climate Science Center. The LiDAR dataset used for accuracy assessment was provided by Cathy Wilson(cjw@lanl.gov) and Chandana Gangodagamage(chandana@lanl.gov). File types included: *.tif; *.png; *.kmz; *.bmp; *.pgw, *xyz, *.jpg. 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↗

NGEE Arctic Plant Traits: Shrub Transects, Kougarok Road Mile Marker 64, Seward Peninsula, Alaska, 2016-2017

Transect data is from point center quarter (PCQ) surveys for shrub density performed in July 2016 at the Kougarok site and in July 2017 at the Kougarok, Teller, and Council sites. For each sample point along the transects, moving averages for shrub density and shrub basal area are provided along with GPS coordinates. Average shrub height and active layer depth are recorded for each sample point as well. Target shrub species differ across the transects: some surveys targeted a mixture of tall shrub species while others targeted specific species. In 2017 insect damage was also quantified. The dataset contains two *.csv data files and one *.pdf. Missing Values are represented by "NA". 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↗

Performance regression manager for large scale systems

System and computer program product to perform an operation 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↗

Performance regression manager for large scale systems

System and computer program product to perform an operation 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↗

A Grid Intensity Map-Based Source Model for Monte Carlo Modeling of IMRT Field Irradiation - Paper 5

An accurate source model is important for TPS (Treatment Planning System) dose calculation and verification, especially for IMRT (Intensity Modulated Radiotherapy) irregular and inhomogeneous fields. Monte Carlo simulation is the most accurate way to calculate dose distributions in the heterogeneous media like human bodies. A full radiotherapy modeling generally includes Linac modeling and phantom dose calculation. Full Linac modeling is very time-consuming and requires highly detailed knowledge of the accelerator composition and structure, however, which is very difficult to obtain for commercial interests. Often all relevant parameters are not known with sufficient accuracy, and thus a time-consuming tuning of e.g. the electron beam spot size and energy must be performed. A multiple source model (MSM) regards particles coming from different parts of an accelerator as if they are coming from different virtual sources. MSM uses a set of virtual sources representing the treatment beam (e.g. primary photons, head scatter, electron contamination) by a set of analytic functions or histograms with parameters derived from dosimetric measurements or a full MC simulation. Tillikainen et al built a three sub-source model by matching with measurement data using an automatic process to optimize the free model parameters for a Varian 2100 C/D accelerator. Lin et al have built a convenient five-photon-sub-source model for Varian 2300C 6 MV-X beam based on Monte Carlo simulated Linac for ARTS (Accurate Radiotherapy System). The particle generation of MSM is very fast compared to full Linac simulation, and its sampling efficiency is not limited by the size of the phase space file (PSF). However, generally MSM is generated based on regular field PSF and needs an irregular component to form the beam shape meanwhile apt to bringing error Linac modeling and MSM producing from PSF analysis actually both are multi-freedom optimization process by adjusting several parameters (e.g. electron energy and angular divergence). Linac modeling adjusts its parameters from the beginning of electron hitting target through all components to fit the simulation to the measurement. MSM tunes its PSF-derived parameters by optimizing to minimize the deviations between the simulation and the measurement. Since the full Linac modeling and the MSM model both need to fine tune their parameters to match the simulation to the measurement, and sometimes maybe offsets the real accelerator for its multi-parameter optimization process. So, why not fine tune directly all source model parameters just behind all Linac components to fit the simulation to the measurement? A grid intensity-based surface source model was suggested here, which assumed the particle emitting from the bottom surface of Linac last beam trimmer MLC (Multi Leaf Collimator). The particle emitting position is sampled on the grid intensity map optimized by TPS, and the particle weight is adjusted by its original grid intensity. This source model not only takes advantage of the Monte Carlo method in the heterogeneous media, but also avoids effectively the transportation speed shortcoming of Monte Carlo simulation through Linac components. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗