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At least 793 records · Page 44

OpenSAMPL: An Open Source Library for Timing and Synchronization Measurements and Analytics

Today's power grid operators are implementing timing and synchronization solutions that provide resilience to Global Navigation Satellite System (GNSS) vulnerabilities. These vendor-specific solutions often come with additional software applications that are designed to monitor that vendor's synchronization performance data. However, resilient timing architectures often resulting in multi-vendor solutions, including approaches that blend terrestrial clocks with space-based subscription services. In such an environment, collecting, analyzing, and visualizing data from a variety of sources within a single platform was heretofore not possible. To address this need, the US Department of Energy's Center for Alternative Synchronization and Timing (CAST) developed OpenSAMPL, the Open Synchronized Analytics and Monitoring Platform, an open-source Python framework for processing, loading, and observing clock measurement data from distributed devices. OpenSAMPL enables the ingestion of diverse clock-probe sources into a scalable time-series database and applies robust analytics. OpenSAMPL currently supports two vendor data pipelines, and will be extended to more in the near future, enabling seamless monitoring of a variety of timing and synchronization devices in a common environment.

Grant, Josh [ORNL] (ORCID:0000000163475060)↗

Reducing Uncertainty of Fielded Photovoltaic Performance (Final Technical Report)

Improved analysis and reporting of photovoltaic (PV) field performance increases the certainty of owners and financiers that systems will perform as expected. Advanced module technologies (e.g., PERC, HJT, and bifacial) introduce new degradation mechanisms and performance characteristics. The FY19-21 Reducing Uncertainty project leveraged data from the ever-increasing PV fleet to develop models and understanding of the field performance of existing and new technologies. Specifically, we accomplished: report on field performance and degradation rates for high-efficiency silicon (HJT, PERC, IBC) and more conventional technologies; developed automated analysis techniques to quantify system performance (performance ratio, energy yield) and production shortfalls (soiling, degradation, availability); refined the RdTools software toolkit to bring standard, validated analysis techniques to bear on third-party data; analyzed and reported on large datasets including Treasury data and Lawrence Berkeley National Laboratory's Utility-Scale dataset to expand the high-quality degradation-rate histogram published previously; worked with industry partners and the DuraMAT data hub to enable private parties to share and aggregate PV production data anonymously, leveraging cloud-based data analysis infrastructure and publishing on US fleet-scale performance comprising over 7GW of operating systems. (https://www.nrel.gov/pv/fleet-performance-data-initiative.html). Through our industry collaborations we have engaged in NDA-covered data transfer with twelve PV fleet owners as of January 2022, with more agreements in negotiation. Our scalable cloud-based time series database contains over 30 billion rows (20TB) of PV time series data, representing over 1700 commercial and utility-scale systems, and over 7.2 GW of DC capacity (Fig 1). Initial field performance results have been distributed in several public reports. Because our fleet composition and data quality methods are continually improving, annual updates to these results are published to our PV Fleet webpage [ https://www.nrel.gov/pv/fleet-performance-data-initiative.html ] and DuraMAT data hub [DOI: 10.21948/1842958]. Another existing dissemination channel used for observed soiling losses is a map we maintain for soiling losses. Additional products developed include a report detailing fleet-wide performance index, availability, startup loss and snow loss factors, a detailed report on the 1603 grant dataset comprising over 100,000 PV systems with failure and performance details and a utility-scale report coauthored with LBNL on 31 GW of system performance.

14 SOLAR ENERGY↗

HIPPO – A Software Platform for Electricity Market Research and Development

The goal of this project is to provide Regional transmission organizations (RTOs) and independent system operators (ISOs) a market design and prototyping software, High-Performance Power-Grid Optimization (HIPPO), that they can evaluate electricity market design options, calculate market planning strategies and operational performance. With the high standards and strict reliability requirements for operating power systems, impacts of new technologies need to be fully investigated prior to any consideration for adoption. A market design and prototyping software tool which can be used to prototype electricity market design options, to calculate market planning strategies and operational performance with high precision, and to investigate the impacts for integrating future power grid technologies will be valuable to RTOs/ISOs who operate power systems, to vendors like GE and ABB who provide the market solvers, and to market participants and researchers who are actively doing market research. HIPPO is a such tool that can be used to improve the current market operations and provide capabilities for rigorous forward-looking design and prototyping of next-generation energy markets. HIPPO has a high-resolution model for the day-ahead SCUC, which was validated with MISO and GE-Grid Solutions. HIPPO is built with parallel and distributed computing capabilities and can be executed in both multi-thread and high-performance computing (HPC) settings. This capability provides fast solution speed necessary to handle the larger and more complex SCUC problems of real-world cases and the potentially growing size and complexity of future scenarios. In addition, HIPPO has a concurrent optimizer (CO) which manages multiple algorithm executions simultaneously and leverages the advantages from different algorithms. This structure provides flexibility to better benchmark competing approaches. Highly accurate market model, fast solution technologies and flexible model and algorithm control are the features which will make HIPPO an extensible platform for developing and testing multiple approaches to meet a wide range of future market needs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

TU-AB-BRC-12: Optimized Parallel MonteCarlo Dose Calculations for Secondary MU Checks

Purpose: Secondary MU checks are an important tool used during a physics review of a treatment plan. Commercial software packages offer varying degrees of theoretical dose calculation accuracy, depending on the modality involved. Dose calculations of VMAT plans are especially prone to error due to the large approximations involved. Monte Carlo (MC) methods are not commonly used due to their long run times. We investigated two methods to increase the computational efficiency of MC dose simulations with the BEAMnrc code. Distributed computing resources, along with optimized code compilation, will allow for accurate and efficient VMAT dose calculations. Methods: The BEAMnrc package was installed on a high performance computing cluster accessible to our clinic. MATLAB and PYTHON scripts were developed to convert a clinical VMAT DICOM plan into BEAMnrc input files. The BEAMnrc installation was optimized by running the VMAT simulations through profiling tools which indicated the behavior of the constituent routines in the code, e.g. the bremsstrahlung splitting routine, and the specified random number generator. This information aided in determining the most efficient compiling parallel configuration for the specific CPU’s available on our cluster, resulting in the fastest VMAT simulation times. Our method was evaluated with calculations involving 10{sup 8} – 10{sup 9} particle histories which are sufficient to verify patient dose using VMAT. Results: Parallelization allowed the calculation of patient dose on the order of 10 – 15 hours with 100 parallel jobs. Due to the compiler optimization process, further speed increases of 23% were achieved when compared with the open-source compiler BEAMnrc packages. Conclusion: Analysis of the BEAMnrc code allowed us to optimize the compiler configuration for VMAT dose calculations. In future work, the optimized MC code, in conjunction with the parallel processing capabilities of BEAMnrc, will be applied to provide accurate and efficient secondary MU checks.

60 APPLIED LIFE SCIENCES↗

GridOPTICS Software System

GridOPTICS Software System (GOSS) is a middleware that facilitates creation of new, modular and flexible operational and planning platforms that can meet the challenges of the next generation power grid. GOSS enables Department of Energy, power system utilities, and vendors to build better tools faster. GOSS makes it possible to integrate Future Power Grid Initiative software products/prototypes into existing power grid software systems, including the PNNL PowerNet and EIOC environments. GOSS is designed to allow power grid applications developed for different underlying software platforms installed in different utilities to communicate with ease. This can be done in compliance with existing security and data sharing policies between the utilities. GOSS not only supports one-to-one data transfer between applications, but also publisher/subscriber scheme. To support interoperability requirements of future EMS, GOSS is designed for CIM compliance. In addition to this, it supports authentication and authorization capabilities to protect the system from cyber threats. In summary, the contributions of the GOSS middleware are as follows: A platform to support future EMS development. A middleware that promotes interoperability between power grid applications. A distributed architecture that separates data sources from power grid applications. Support for data exchange with either one-to-one or publisher/subscriber interfaces. An authentication and authorization scheme for limiting the access to data between utilities.

Akyol, BoraA↗

The MCDB System for Management and Analysis of Petabyte-Scale Uncertain Data

Analysts working with very large data sets often use statistical models to “guess” at unknown, inaccurate, or missing information associated with the data. For example, a distant object viewed through an optical lens will have its position slightly shifted by imperfections in the lens. Thus, rather than considering the object’s observed position to be absolutely correct, it makes sense to take into account the lens’s imperfections to obtain a probabilistic guess as to the object’s true position. For another example, it might be important to associate some sort of error distribution with each of the individual sensors in an array of magnetometers. This error distribution may be complex and include spatially-driven covariances, because errors in nearby sensors are likely to be correlated (caused, for example, by the presence of some nearby, fixed metal object). This project is concerned with the design and implementation of a prototype data management system called the Monte Carlo Database System, or MCDB for short. MCDB allows an expert-level analyst or statistician to attach arbitrary stochastic models to very large data sets in order to “guess” the values for unknown or inaccurate data, such as the actual position of the observed object in the lens example above. When the resulting data set is analyzed, the underlying stochastic models are used to generate hundreds or thousands of possible data set instances, and each of those possible instances is analyzed separately by MCDB. Thus, MCDB does not just give a single answer to the analysis, but it actually gives an empirical distribution of query results that embody the underlying uncertainty, and can in turn be analyzed using standard statistical techniques. The stochastic models in MCDB are implemented as user-defined, external C++ libraries called Variable Generation functions (VG functions for short). Because the VG function interface is exceedingly general, it allows MCDB to be used in a very wide variety of application domains, in conjunction with virtually any stochastic model. Ultimately, we ended up calling the system that we developed over the course of the project SimSQL, to denote the fact that it allowed for stochastic simulation of data. The software developed during the lifetime of the project is available for download from the SimSQL project website: http://cmj4.web.rice.edu/SimSQL/SimSQL.html.

42 ENGINEERING↗

A High-Throughput Computing Infrastructure to Generate Custom, Open Community Geothermal Datasets

The most significant challenge facing geothermal research, development, and deployment is a lack of comprehensive datasets describing the geological and economical properties of North America. Automated knowledge base construction, the process of designing algorithms to analyze text and images to programmatically build new datasets, is one possible solution to this problem. The xDD library of full-text scientific articles (https://xdd.wisc.edu) is one of the largest collections of open and controlled-access scientific documents available for knowledge base construction in the world, but it has been underutilized by experts in geothermal research. The xDD development team attributed the lack of engagement by software developers and geothermal researchers to two perceived shortcomings of the system. First, the workflow for obtaining data from xDD for local development and testing of data mining applications was unnecessarily abstruse and required significant manual intervention by xDD systems administrators. Second, although xDD already held articles from a broad cross-section of scientific literature with an emphasis on the geosciences, it did not have an explicit set of geothermal research documents that could serve as the nucleus of a geothermal data mining application. To address these issues, the Automated Data Extraction PlaTform (ADEPT) was proposed to extend the data distribution capabilities of the xDD system. The ADEPT extension added the following four key features to xDD: 1) integration of National Geothermal Data System (NGDS) documents into the xDD library to provide an explicitly geothermally-themed collection; 2) improved RESTful (i.e., https-protocol driven) web services for external partners to access xDD data for machine learning application development; 3) a web platform for end-users and xDD administrators to coordinate the development of data mining applications from the initial step of browsing available documents to the final stage of deploying a production-quality machine learning application on high-throughput computing infrastructure; and 4) the development of demonstration data mining applications to illustrate the new workflow to potential collaborators. A total of 21,674 geothermal documents from NGDS were fully ingested into the xDD library and the associated metadata is publicly available through the xDD web services; furthermore, the ADEPT web platform is now publicly accessible and fully live at https://xdd.wisc.edu/adept/.

15 GEOTHERMAL ENERGY↗

GridOPTICS Software System

GridOPTICS Software System (GOSS) is a middleware that facilitates creation of new, modular and flexible operational and planning platforms that can meet the challenges of the next generation power grid. GOSS enables Department of Energy, power system utilities, and vendors to build better tools faster. GOSS makes it possible to integrate Future Power Grid Initiative software products/prototypes into existing power grid software systems, including the PNNL PowerNet and EIOC environments. GOSS is designed to allow power grid applications developed for different underlying software platforms installed in different utilities to communicate with ease. This can be done in compliance with existing security and data sharing policies between the utilities. GOSS not only supports one-to-one data transfer between applications, but also publisher/subscriber scheme. To support interoperability requirements of future EMS, GOSS is designed for CIM compliance. In addition to this, it supports authentication and authorization capabilities to protect the system from cyber threats. In summary, the contributions of the GOSS middleware are as follows: A platform to support future EMS development. A middleware that promotes interoperability between power grid applications. A distributed architecture that separates data sources from power grid applications. Support for data exchange with either one-to-one or publisher/subscriber interfaces. An authentication and authorization scheme for limiting the access to data between utilities.

Akyol, Bora A↗

Measurement and control system for cryogenic helium gas bearing turbo-expander experimental platform based on Siemens PLC S7-300

An experimental platform for cryogenic Helium gas bearing turbo-expanders is established at the Technical Institute of Physics and Chemistry, Chinese Academy of Sciences. This turbo-expander experimental platform is designed for performance testing and experimental research on Helium turbo-expanders with different sizes from the liquid hydrogen temperature to the room temperature region. A measurement and control system based on Siemens PLC S7-300 for this turbo-expander experimental platform is developed. Proper sensors are selected to measure such parameters as temperature, pressure, rotation speed and air flow rate. All the collected data to be processed are transformed and transmitted to S7-300 CPU. Siemens S7-300 series PLC CPU315-2PN/DP is as master station and two sets of ET200M DP remote expand I/O is as slave station. Profibus-DP field communication is established between master station and slave stations. The upper computer Human Machine Interface (HMI) is compiled using Siemens configuration software WinCC V6.2. The upper computer communicates with PLC by means of industrial Ethernet. Centralized monitoring and distributed control is achieved. Experimental results show that this measurement and control system has fulfilled the test requirement for the turbo-expander experimental platform.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Quantum Networks for Resilient Power Grids: Theory and Simulated Evaluation

Quantum networks are considered the future of secure communication in the coming quantum era. Yet there lack significant efforts on developing practical quantum networks for power grids. Here, in this paper, we establish a quantum network-based power grid (QNetGrid) framework and develops a real-time, reliable, flexible, programmable, and cost-effective QNetGrid software testbed containing repeater-based quantum communication, quantum routing, real software-defined networking (SDN) switches, and real-time networked microgrids (NMs) operations. It makes the following contributions: 1) a repeater and routing based quantum network simulator (QNSim) is developed, 2) repeaters with and without quantum memories are respectively simulated in QNSim, 3) different routing scenarios in QNetGrid are investigated, 4) a real-time QNetGrid software testbed is built in RTDS incorporating QNSim and real SDN switches, and 5) various test cases are designed, and experimental results produced with the QNetGrid testbed provide valuable insights for building quantum networks in power grids.

24 POWER TRANSMISSION AND DISTRIBUTION↗

eDNAjoint: An R package for interpreting paired or semi‐paired environmental DNA and traditional survey data in a Bayesian framework

Abstract Environmental DNA (eDNA) sampling is increasingly used in surveys of species distribution as a potentially sensitive and efficient monitoring method. Yet access to modelling tools designed specifically for interpreting this new data type lags behind its ubiquity. While occupancy modelling software has dominated the analytical landscape for eDNA data analysis of single species, this type of model may not always be the most appropriate. The rate of eDNA detection often corresponds to species density, rather than just occupancy, and researchers often have access to observations from non‐genetic sampling methods at the same sites. To provide users access to a modelling framework designed to maximize the use of all available data, we developed an R package, eDNAjoint . The package provides an easy‐to‐use interface for fitting a ‘joint’ model that integrates data from paired or semi‐paired eDNA and traditional surveys in a Bayesian framework. The model can be used to estimate parameters like the probability of a false positive eDNA detection and mean catch rate at a site, and the package allows access to multiple model variations and Bayesian prior customization. Additional functionality can be used for model selection, summarising posteriors and comparing the relative sensitivities of the two survey methods. We demonstrate the use of eDNAjoint by fitting a variation of the model with site‐level covariates that scale the sensitivity of eDNA sampling relative to traditional sampling. The example workflow uses binary eDNA and seine count data for the endangered tidewater goby ( Eucyclogobius newberryi ) from a study by Schmelzle and Kinziger (2016). This use case includes a prior sensitivity analysis and an evaluation of the relationship between detection rates and environmental variables. eDNAjoint has the potential to greatly increase the range of users who will be able to rigorously analyse eDNA and traditional survey data in a Bayesian framework, understand if and how eDNA can improve monitoring practices, and gain confidence in the interpretability of eDNA data.

Keller, Abigail G. [Department of Environment Scie↗

Finite Element Analysis (FEA) for Water-Foam Fracturing of Granite Rock

In addition to the foam data that were obtained from literature and that were collected from the current study, simulation data was also generated from finite element analysis (FEA) conducted in this study using COMSOL Multiphysics software. The FEA models were built to simulate the experiments conducted at Oak Ridge National Laboratory (ORNL) on cement and granite samples. In these FEA models, temperature was kept at ambient while the pressure profile resembled the loading conditions during the ORNL experiments, where pressure was either monotonically increased or applied cyclically. The cement material was used as a model material and was used to study Von Mises stress and tensile stress distribution for different bore hole length geometry using a parametric sweep with water as fracturing fluid using solid-fluid interaction module. For the granite material, FEA models were developed for stress analysis of cylindrical samples with water or foam fluids. The solid mechanics module in COMSOL was implemented to solve for Von Mises stress and tensile stress. The fluid-structure interaction module was implemented to solve for water-foam interaction on granite cylinder with addition of fluid-loading on structure, i.e., large deformation in solid mechanics with no impact on fluid deformation. Foam was considered as a pseudo single-phase compressible fluid for which material properties were calculated from water and gas (nitrogen) phases. The density of foam is calculated as a function of the densities of water and nitrogen, while viscosity is a function of temperature. Four types of FEA analyses were modelled: 1. Monotonic injection with water 2. Monotonic injection with foam 3. Cyclic injection with water 4. Cyclic injection with foam All the COMSOL files are converted to a zip file which is save in .mph.

15 GEOTHERMAL ENERGY↗

On the multidimensional modeling of fluid flow and heat transfer in SCWRS

The Supercritical Water Reactor (SCWR) has been proposed as one of the six Generation IV reactor design concepts under consideration. The key feature of the SCWR is that water at supercritical pressures is used as the reactor coolant. Although at such pressures, fluids do not undergo phase change as they are heated, the fluid properties experience dramatic variations throughout what is known as the pseudo-critical region. Highly nonuniform temperature and fluid property distributions are expected in the reactor core, which will have a significant impact on turbulence and heat transfer in future SCWRs. The goal of the present work has been to understand and predict the effects of these fluid property variations on turbulence and heat transfer throughout the reactor core. Spline-type property models have been formulated for water at supercritical pressures in order to include the dependence of properties on both temperature and pressure into a numerical solver. New models of turbulence and heat transfer for variable-property fluids have been developed and implemented into the NPHASE-CMFD software. The results for these models have been compared to experimental data from the Korea Atomic Energy Research Inst. (KAERI) for various heat transfer regimes. It is found that the Low-Reynolds {kappa}-{epsilon} model performs best at predicting the experimental data. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

The CMS Data Acquisition - Architectures for the Phase-2 Upgrade

The upgraded High Luminosity LHC, after the third Long Shutdown (LS3), will provide an instantaneous luminosity of 7.5 × 10 34 cm -2 s -1 (levelled), at the price of extreme pileup of up to 200 interactions per crossing. In LS3, the CMS Detector will also undergo a major upgrade to prepare for the phase-2 of the LHC physics program, starting around 2025. The upgraded detector will be read out at an unprecedented data rate of up to 50 Tb/s and an event rate of 750 kHz. Complete events will be analysed by software algorithms running on standard processing nodes, and selected events will be stored permanently at a rate of up to 10 kHz for offline processing and analysis. Here in this paper we discuss the baseline design of the DAQ and HLT systems for the phase-2, taking into account the projected evolution of high speed network fabrics for event building and distribution, and the anticipated performance of general purpose CPU. Implications on hardware and infrastructure requirements for the DAQ “data center” are analysed. Emerging technologies for data reduction are considered. Novel possible approaches to event building and online processing, inspired by trending developments in other areas of computing dealing with large masses of data, are also examined. We conclude by discussing the opportunities offered by reading out and processing parts of the detector, wherever the front-end electronics allows, at the machine clock rate (40 MHz). This idea presents interesting challenges and its physics potential should be studied.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

IDC Reengineering Phase 2 Project Scope

The Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) operates the International Data Centre (IDC) to support treaty verification activities by Member States. The IDC collects, stores, processes, and distributes data from seismic, hydroacoustic, infrasound, and radionuclide stations. A significant component of the IDC is the seismic, hydroacoustic, and infrasound (SHI) processing system. The IDC has recognized the need to reengineer the SHI processing system and has defined a three-phase reengineering effort. IDC Reengineering Phase 1 (RP1) started in 2011 with the goal to significantly modernize SHI automatic and interactive data processing software, focusing on enhancements to individual components of the system. Reengineering Phase 2 (RP2), started in 2014, addresses the task of specifying a unified architecture for all SHI software, across processing stages, to pave the way for further software development and sustainment in the future. A key objective of RP2 is an architecture sufficient to provide a basis for a cost estimate for the development or enhancement of the software components and subsystems. This report provides a brief description of the scope of the IDC Reengineering Phase 2 project. It describes the goals and objectives of reengineering, the system definition, and the technical scope of the system.This report expands upon the “Scope for IDC Reengineering Phase 2”, July 2014, ECS-DIS-WGB-43-PTS-MATERIAL-12-ADD-1, produced by the IDC.

58 GEOSCIENCES↗

Evaluation of Computational Method of High Reynolds Number Slurry Flow for Caverns Backfilling

The abandonment of salt caverns used for brining or product storage poses a significant environmental and economic risk. Risk mitigation can in part be addressed by the process of backfilling which can improve the cavern geomechanical stability and reduce the risk of fluid loss to the environment. This study evaluates a currently available computational tool, Barracuda, to simulate such processes as slurry flow at high Reynolds number with high particle loading. Using Barracuda software, a parametric sequence of simulations evaluated slurry flow at Reynolds number up to 15000 and loading up to 25%. Limitations come into the long time required to run these simulations due in particular to the mesh size requirement at the jet nozzle. This study has found that slurry-jet width and centerline velocities are functions of Reynolds number and volume fraction. The solid phase was found to spread less than the water-phase with a spreading rate smaller than 1, dependent on the volume fraction. Particle size distribution does seem to have a large influence on the jet flow development. This study constitutes a first step to understand the behavior of highly loaded slurries and their ultimate application to cavern backfilling.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

CalderaCast User Manual Version 1.0

CalderaCast is a user-friendly web-based tool for electrical-load forecast, providing stakeholders with a fully customizable decision-support framework that estimates the likely power draw from a possible future electric-vehicle (EV) charging station at a given location on a given day along an alternative fuel corridor (AFC). These EV charging profiles are accurately modeled in CalderaCast using the Caldera software framework developed by Idaho National Laboratories (INL), reflecting the realistic charging levels observed in actual charge events. This tool was developed as part of the National Electric Vehicle Infrastructure (NEVI) program, which is quickly generating substantial interest from would-be charging station operators (CSO), large and small electric utilities, and state transportation planners, some of whom had not seriously considered EV charging previously. All these entities—with or without background in EV infrastructure—must estimate the electricity load that a proposed charging station will generate. This load forecast is critically important for a utility to properly assess the capacity of their distribution network to support the proposed station or properly size grid upgrades for potential load growth due to future EV adoption, vehicle technology improvements, or station growth. This document describes each aspect of the CalderaCast tool and provides guidance to users who are interested in utilizing the tool for their work.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

SU-E-T-378: Limits and Possibilities of a Simplistic Approach to Whole Breast Radiation Therapy Planning

Purpose: Challenges for radiation therapy in developing countries include unreliable infrastructure and high patient load. We propose a system to treat whole breast in the prone position without computed tomography and/or planning software. Methods: Six parameters are measured using calipers and levels with the patient prone in the treatment position. (1) The largest separation; (2) the angle that separation makes with the horizontal; (3) the separation 2 cm posterior to the nipple; (4) the vertical distance between these two separations; (5) the sup/inf length and (6) angle of the desired posterior field edge. The data in (5) (6) and (2) provide field length, collimator and gantry angles. Isocenter is set to the midpoint of (1), anterior jaw setting is 20cm (half-beam setup), and the dose is prescribed to a point 1.5 cm anterior to isocenter. MUs and wedge angles are calculated using an MU calculator and by requiring 100% dose at that point and 100-105% at the midpoint of (3). Measurements on 30 CT scans were taken to obtain the data 1-6. To test the resulting MU/wedge combinations, they were entered into Eclipse (Varian) and dose distributions were calculated. The MU/wedge combinations were recorded and tabulated. Results: Performing a dose volume histogram analysis, the contoured breast V95 was 90.5%, and the average V90 was 94.1%. The maximum dose never exceeded 114.5%, (average 108%). The lung V20 was <5% for 96.7%, and the heart V5 was <10% for 93.3% of our sample. Conclusion: A method to provide prone whole breast treatment without CT-planning was developed. The method provides reasonable coverage and normal tissue sparing. This approach is not recommended if imaging and planning capabilities are available; it was designed to specifically avoid the need for CT planning and should be reserved to clinics that need to avoid that step.

60 APPLIED LIFE SCIENCES↗