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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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At least 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Determining Stability Margins in Adiabatic Superconducting Magnets with 3-D Finite Element Analysis

Superconducting magnets play a key role in the development of experiments at Fermilab; understanding the operating stability of these can allow us to utilize more potent magnets for future experiments (like the proposed Muon Collider), optimize the design of magnets in more immediate experiments (like Mu2e), and research the future use of more exotic materials (like high-temperature superconductors). This summer, I developed a 3-D parametric FEA program in ANSYS Mechanical APDL that simulates quench in superconducting magnets, and I also developed a parametric MATLAB program that predicts thermal behavior in magnet quench using the MIITS method. These programs can provide useful quenching parameters (like minimum quench energy and normal zone propagation velocity) for different cases of quench, leading to the previously mentioned objective of magnet design optimization. To test the programs, preliminary cases were run and the data produced was compared and analyzed. The results of these analyses, as well as the program operating methods, are discussed in this project.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Recovery Act - Measurement of Parity Violation in Deep Inelastic Scattering and Studies of the Nucleon Spin Structure at JLab 6 and 11 GeV

The program proposed contains two ingredients which aim to address aspects of two of the three research frontiers of nuclear science as identified in the 2007 NSAC Long Range Plan. The first topic, a test of the current Standard Model, is an ongoing project focusing on measurements of the parity-violating asymmetry in ~e-2H deep inelastic scattering (PVDIS). The PVDIS measurement is complementary to other completed or ongoing low- to medium-energy tests of the Standard Model. As the first, exploratory, step, an experiment using a 6 GeV electron beam will be carried out from October to December 2009 at the Thomas Jefferson National Accelerator Facility (JLab). Meanwhile, a program using the upgraded JLab 11 GeV beam is being planned. The PVDIS program as a whole will provide the first precision data on the axial quark neutral-weak coupling constants. This will either put the current Standard Model to a test that has never been done before, or reveal information on where to look for New Physics beyond the current Standard Model. The PVDIS program will also provide results on hadronic physics effects such as charge symmetry violation. The second part of the proposed program uses spin observables to address the research frontier concerning QCD and structure of the nucleon. An experiment using the JLab 6 GeV beam in 2001 showed that, contrary to predictions from perturbative quantum chromodynamics (pQCD), while the valence up quark’s spin is parallel to the nucleon’s spin, the valence down quark’s spin is not. In order to test the limit of QCD in describing the nucleon spin structure to a region beyond the 6 GeV kinematics, this measurement will be extended to a more energetic, “deeper” valence quark region using the upgraded JLab 11 GeV beam with a polarized 3 He target. Although the two topics of the proposed program appear to focus on different physics, for the upgraded JLab 11 GeV beam, both will utilize a new, yet-to-be-built large acceptance spectrometer, called “SoLID”. Once built, SoLID can be used for other topics such as using PVDIS on a proton target to measure the valence quark distributions, using PVDIS on a polarized target to measure new electro-weak interference structure functions of the nucleon, and semi-inclusive deep inelastic scattering experiments. SoLID will greatly enhance the exploration potential of JLab. The proposed program will first focus on completion of the 6 GeV PVDIS experiment, its data analysis and publishing physics results. This 6 GeV experiment will explore whether precision PVDIS measurements are feasible, will set limits on the hadronic physics effects, and will improve our knowledge on the quark neutral weak couplings, optimally by a factor of six. Starting early 2010, efforts will be spent on preparation for the 11 GeV program, focusing on simulations of SoLID, optimization and construction of the SoLID detector package, and studies of the polarized 3 He target and its improvements. Funding support for the whole program is requested here.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

A Parallel Computing Framework for Finding the Supported Solutions to a Biobjective Network Optimization Problem

Abstract Solving multi‐objective combinatorial optimization problems can quickly become computationally challenging when applied to large networks generated from big data. Present‐day first‐rate Mixed Integer Programming (MIP) solvers have parallelism built‐in to take advantage of multicore architectures; but specialized network optimization algorithms that can often solve graph problems more efficiently than a general MIP solver are typically programmed serially. Thus, these network algorithm implementations do not take full advantage of modern multicore computer capabilities. Many parallel computing languages include a fork/join framework into their concurrency packages that allow for simple conversion of recursive serial algorithms to operate in parallel without having to use complicated low‐level message‐passing interfaces. Fork/join is particularly well suited to divide and conquer algorithms such as Non‐Inferior Set Estimation (NISE) method for computing the supported Pareto front of a multi‐objective optimization problem. This work develops a simple general parallel NISE (pNISE) implementation using the Java 7 concurrency tools, and then offers results from a specific implementation of solving a bi‐objective shortest path problem. The results indicate that this method is capable of sizeable speed‐ups on both small‐scale personal computers as well as large‐scale shared memory supercomputers. Finally, other network problems suitable to this method are discussed, including multi‐objective variants of the minimum spanning tree problem, transportation problem, assignment problem, maximum flow problem, and the minimum‐cost flow problem. Copyright © 2015 John Wiley & Sons, Ltd.

Medrano, Fernando Antonio↗
DOE OSTI2025

Capacitated p -hub approach for park-and-ride facility location problem under nested logit demand function: polyhedral approaches

By generalizing the unconstrained p-hub approach for the park-and-ride (P&R) facility location problem under the multinomial logit demand function, the capacitated p-hub approach for the problem under the nested logit demand function captures a broader range of real-world cases. To solve this problem optimally, we introduce a mixed-integer linear program and accelerate its solution by enhancing the branch-and-cut procedure. To address the problem at a large scale, we introduce two other polyhedral approaches: variable neighborhood search (VNS) and adaptive randomized rounding (ARR). Downtown areas in Seoul have a high modal share of public transportation and congested road traffic, yet P&R has not been widely implemented. Therefore, we apply the ARR procedure to solve a real-world problem using traffic and geographic data from the Seoul metropolitan area. ARR performs better than VNS and addresses real-world cases. The solutions obtained by ARR present a phased expansion plan that encourages policymakers to start installing a small number of P&Rs immediately.

Capacitated p-hub approach↗
DOE OSTI2018

A centralized-based method to determine the local voltage control strategies of distributed generator operation in active distribution networks

The increasing penetration of distributed generators (DGs) exacerbates the risk of voltage violations in active distribution networks (ADNs). The var capacity provided by DG inverters is a potential solution for voltage regulation. The conventional centralized control strategies limited by computation and communication burdens are difficult to meet the requirement of rapid voltage control. However, the local control strategies based on real-time measurements have a fast response to the frequent fluctuations of DG outputs. The performance of these local controllers depends on the tuning of the control parameters. This paper proposes a centralized-based method to determine the local voltage control strategies for DGs. A centralized parameter tuning model of control curves is built, in which and curves of DG inverters are mathematically formulated based on piecewise linearization. The original mixed-integer nonlinear programming (MINLP) model is converted into an effectively solved mixed-integer second-order cone programming (MISOCP) model using convex relaxation. The potential benefits of DG inverters are explored to regulate both reactive and curtailed active power, based on local voltage measurements. Case studies on a modified PG&E 69-node distribution system are carried out to verify the effectiveness of the proposed method. Results show that power losses of ADNs are significantly reduced and voltage profiles are also improved.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Extended convex hull-based distributed optimal energy flow of integrated electricity-gas systems

Integrated electricity and gas systems are constructed to facilitate the gas-fired generation, and the distributed operation of these integrated systems have received much attention due to the increased emphasis on data security and privacy between different agencies. This paper proposes an extended convex hull based method to address optimal energy flow problems for the integrated electricity and gas systems in a distributed manner. First, a multi-block electricity-gas system model is constructed by dividing the whole system into N blocks considering both physical and regional differences. This multi-block model is then convexified by replacing the nonconvex gas transmission equation with the extended convex hull-based constraints. The Jacobi-Proximal alternating direction method of multipliers algorithm is adopted to solve the convexified model and minimize its operation cost. Finally, the feasibility of the optimal solution for the convexified model is checked, and a sufficient condition is developed. If the sufficient condition is satisfied, the optimal solution for the original nonconvex problem can be recovered from that for the convexified problem. Simulation results demonstrate that the proposed method is tractable and effective in obtaining feasible optimal solutions for multi-block optimal energy flow problems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Vehicle-to-manufacturing (V2M) system: A novel approach to improve energy demand flexibility for demand response towards sustainable manufacturing

The U.S. manufacturing sector accounts for 77% of the industrial energy consumption, but its participation in demand response (DR) programs is largely lagged behind. The limited flexibility in production scheduling under high capacity utilization and the lack of DR schemes that incorporate energy demand flexibility measures are deemed as major barriers. In this study, a framework of the interactive vehicles-to-manufacturing (V2M) energy sharing system is proposed to improve the energy demand flexibility of the aggregated system and enhance the DR effectiveness for manufacturers. The V2M-based DR scheme aims to reduce the energy cost by load shifting through joint production and energy sharing control, which can eventually promote manufacturing DR implementation even under high capacity utilization requirements and dynamic real-time electricity prices. The V2M system is modeled based on a discrete-Markov chain considering the complex interconnections among various manufacturing resources and multi-directional energy flows among manufacturing facilities, electric vehicles, and the power grid. Based on the system model, a mixed-integer nonlinear programming (MINLP) problem is formulated to identify the optimal DR scheme. The effectiveness of the proposed approach is validated through comparisons with traditional manufacturing DR schemes. Finally, the results show that a 2.1 to 6.5 times energy demand flexibility improvement and an additional 4.7% to 6.9% energy cost reduction can be achieved by the proposed approach.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Improving operational flexibility of integrated energy system with uncertain renewable generations considering thermal inertia of buildings

Insufficient flexibility in system operation caused by traditional "heat-set" operating modes of combined heat and power (CHP) units in winter heating periods is a key issue that limits renewable energy consumption. In order to reduce the curtailment of renewable energy resources through improving the operational flexibility, a novel optimal scheduling model based on chance-constrained programming (CCP), aiming at minimizing the lowest generation cost, is proposed for a small-scale integrated energy system (IES) with CHP units, thermal power units, renewable generations and representative auxiliary equipments. In this model, due to the uncertainties of renewable generations including wind turbines and photovoltaic units, the probabilistic spinning reserves are supplied in the form of chance-constrained; from the perspective of user experience, a heating load model is built with consideration of heat comfort and inertia in buildings. To solve the model, a solution approach based on sequence operation theory (SOT) is developed, where the original CCP-based scheduling model is tackled into a solvable mixed-integer linear programming (MILP) formulation by converting a chance constraint into its deterministic equivalence class, and thereby is solved via the CPLEX solver. We report the simulation results on the modified IEEE 30-bus system demonstrate that the presented method manages to improve operational flexibility of the IES with uncertain renewable generations by comprehensively leveraging thermal inertia of buildings and different kinds of auxiliary equipments, which provides a fundamental way for promoting renewable energy consumption.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2019

Co-optima fuels combustion: A comprehensive experimental investigation of prenol isomers

Carbon monoxide time-histories, ignition delay times, and laminar burning velocity measurements are reported for the oxidation of 3-methyl-2-buten-1-ol (prenol) and 3-methyl-3-buten-1-ol (isoprenol). These prenols are fuel candidates outlined by the U.S. Department of Energy’s Co-Optimization of Fuels and Engines (Co-Optima) program. The laminar burning velocity measurements were conducted for two fuels with synthetic air within a constant-volume spherical combustion chamber at initial conditions of 428 K and 1 atm for a range of equivalence ratios from 0.75 to 1.50. The laminar burning velocities of the two fuels were found to be similar, and the maximum value occurred at an equivalence ratio near 1.0. Carbon monoxide time-histories and ignition delay times were recorded behind reflected shockwaves in a double-diaphragm, heated shock tube over the temperature range 1269–1472 K near 9.4 atm with a mixture of 0.05% fuel/0.35% O 2 /99.6% Ar. Comparisons with predictions of a detailed chemical kinetic mechanism from the literature were provided. Current model predictions overpredicted both the ignition delay time and the max CO yield; however, the model captured the profile of CO formation well. Detailed uncertainty and sensitivity analyses were carried out to identify important reactions that need attention for accurate prediction of these fuel’s chemistry. Further investigation into the rate of C 3 H 3 + O 2 = CH 2 CO + HCO reaction was suggested based on current experiments. In conclusion, the experimental data and analysis presented here is critical in the development, validation and improvement of kinetic models of these promising Co-Optima fuels.

09 BIOMASS FUELS↗
DOE OSTI2013

OpenMSI: A High-Performance Web-Based Platform for Mass Spectrometry Imaging

Mass spectrometry imaging (MSI) enables researchers to directly probe endogenous molecules directly within the architecture of the biological matrix. Unfortunately, efficient access, management, and analysis of the data generated by MSI approaches remain major challenges to this rapidly developing field. Despite the availability of numerous dedicated file formats and software packages, it is a widely held viewpoint that the biggest challenge is simply opening, sharing, and analyzing a file without loss of information. Here we present OpenMSI, a software framework and platform that addresses these challenges via an advanced, high-performance, extensible file format and Web API for remote data access (http://openmsi.nersc.gov). The OpenMSI file format supports storage of raw MSI data, metadata, and derived analyses in a single, self-describing format based on HDF5 and is supported by a large range of analysis software (e.g., Matlab and R) and programming languages (e.g., C++, Fortran, and Python). Careful optimization of the storage layout of MSI data sets using chunking, compression, and data replication accelerates common, selective data access operations while minimizing data storage requirements and are critical enablers of rapid data I/O. The OpenMSI file format has shown to provide >2000-fold improvement for image access operations, enabling spectrum and image retrieval in less than 0.3 s across the Internet even for 50 GB MSI data sets. To make remote high-performance compute resources accessible for analysis and to facilitate data sharing and collaboration, we describe an easy-to-use yet powerful Web API, enabling fast and convenient access to MSI data, metadata, and derived analysis results stored remotely to facilitate high-performance data analysis and enable implementation of Web based data sharing, visualization, and analysis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Catalytic Resonance Theory: The Catalytic Mechanics of Programmable Ratchets

Catalytic reaction networks of multiple elementary steps operating under dynamic conditions via a programmed input oscillation are difficult to interpret and optimize due to reaction system complexity. To understand these dynamic systems, individual elementary catalytic reactions oscillating between catalyst states were evaluated to identify their three fundamental characteristics that define their ability to promote reactions away from equilibrium. First, elementary catalytic reactions exhibit directionality to promote reactions forward or backward from equilibrium as determined by a ratchet directionality metric comprised of the input oscillation duty cycle and the reaction rate constants. Second, catalytic ratchets are defined by the catalyst state of strong or weak binding that permit reactants to proceed through the transition state. Third, elementary catalytic ratchets exhibit a cutoff frequency which defines the transition in applied frequency for which the catalytic ratchet functions to promote chemistry away from equilibrium. All three ratchet characteristics are calculated from chemical reaction parameters including rate constants derived from linear scaling parameters, reaction conditions, and catalyst state. The characteristics of the reaction network’s constituent elementary catalytic reactions provided an interpretation of complex reaction networks and a method of predicting the behavior of dynamic surface chemistry on oscillating catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Mathematical model of the metal mould surface temperature optimization

The article is focused on the problem of generating a uniform temperature field on the inner surface of shell metal moulds. Such moulds are used e.g. in the automotive industry for artificial leather production. To produce artificial leather with uniform surface structure and colour shade the temperature on the inner surface of the mould has to be as homogeneous as possible. The heating of the mould is realized by infrared heaters located above the outer mould surface. The conceived mathematical model allows us to optimize the locations of infrared heaters over the mould, so that approximately uniform heat radiation intensity is generated. A version of differential evolution algorithm programmed in Matlab development environment was created by the authors for the optimization process. For temperate calculations software system ANSYS was used. A practical example of optimization of heaters locations and calculation of the temperature of the mould is included at the end of the article.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

RANGE: A robust adaptive nature-inspired global explorer of potential energy surfaces

With the growing demand for realistic representations of chemical structures and the advent of exascale computing, the intelligent sampling of potential energy surfaces and efficient identification of global minima have become more essential but also more feasible. Building on prior studies demonstrating the efficiency of the Artificial Bee Colony (ABC) swarm intelligence algorithm, we report a hybrid metaheuristic framework that integrates the adaptive exploration capabilities of ABC coupled with the exploitation strengths of genetic algorithms (GA) in a scalable, Python-based implementation. The resulting tool, RANGE (Robust Adaptive Nature-inspired Global Explorer), provides seamless interfaces to multiple potential energy evaluators, either directly or via widely used Python libraries, and is designed for high-performance computing environments. We describe the implementation details of RANGE and evaluate its performance, relative to ABC- or GA-alone based algorithms, on a variety of chemical systems, including molecular clusters and heterogeneous surfaces. In conclusion, our results demonstrate RANGE’s efficiency, robustness, and broad applicability in addressing challenging global optimization problems in computational chemistry and materials science.

Algorithms and data structure↗
DOE OSTI2019

Resolution of the ATLAS muon spectrometer monitored drift tubes in LHC Run 2

The momentum measurement capability of the ATLAS muon spectrometer relies fundamentally on the intrinsic single-hit spatial resolution of the monitored drift tube precision tracking chambers. Optimal resolution is achieved with a dedicated calibration program that addresses the specific operating conditions of the 354 000 high-pressure drift tubes in the spectrometer. The calibrations consist of a set of timing offsets and drift time to drift distance transfer relations, and result in chamber resolution functions. This paper describes novel algorithms to obtain precision calibrations from data collected by ATLAS in LHC Run 2 and from a gas monitoring chamber, deployed in a dedicated gas facility. The algorithm output consists of a pair of correction constants per chamber which are applied to baseline calibrations, and determined to be valid for the entire ATLAS Run 2. The final single-hit spatial resolution, averaged over 1172 monitored drift tube chambers, is $81.7 \pm 2.2 \mu$m.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Optimal Sizing and Operation of a Hybrid Clean Energy Center

In this paper, we consider the deployment of battery energy storage systems (BESSs) paired with photovoltaics (PV) to form a hybrid clean energy center (HCEC), where the BESS is equipped for two main purposes: i) reducing the volatility of PV output and ii) shifting energy to meet an export limit. We develop a linear dynamical model to characterize the output of an HCEC and express the volatility and export power as functions of the battery's dispatch operations. We also propose an optimal sizing method via second-order cone programming (SOCP) to maximize the net benefits of the HCEC. Numerical studies are performed to illustrate and validate the proposed method.

Battery energy storage systems, photovoltaics, sec↗
DOE OSTI2017

Integrating External Resources with a Task-Based Programming Model

Accessing external resources (e.g., loading input data, checkpointing snapshots, and out-of-core processing) can have a significant impact on the performance of supercomputer applications. However, no existing programming systems for high-performance computing directly manage and optimize these external accesses. As a result, users must explicitly manage external accesses alongside their computation at the application level, which can result in both correctness and performance issues. We address this limitation by introducing Iris, a task-based programming model with semantics for external resources. Iris allows applications to describe their access requirements to external resources and the relationship of those accesses to the computation. Iris incorporates external I/O into a deferred execution model, reschedules external I/O to overlap I/O with computation, and reduces external I/O when possible. We evaluate Iris on three microbenchmarks representative of important workloads in HPC and a full combustion simulation, S3D. We demonstrate that the Iris implementation of S3D reduces the external I/O overhead by up to 20×, compared to the Legion and the Fortran implementations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

A Probabilistic Risk Mitigation Model for Cyber-Attacks to PMU Networks

The power grid is becoming more dependent on information and communication technologies. Complex networks of advanced sensors such as phasor measurement units (PMUs) are used to collect real time data to improve the observability of the power system. Recent studies have shown that the power grid has significant cyber vulnerabilities which could increase when PMUs are used extensively. Therefore, recognizing and responding to vulnerabilities are critical to the security of the power grid. This paper proposes a risk mitigation model for optimal response to cyber-attacks to PMU networks. We model the optimal response action as a mixed integer linear programming (MILP) problem to prevent propagation of the cyber-attacks and maintain the observability of the power system.

Cyber-attack↗
DOE OSTI2015

WE-AB-201-00: Treatment Planning System Commissioning and QA

Treatment planning systems (TPS) are a cornerstone of modern radiation therapy. Errors in their commissioning or use can have a devastating impact on many patients. To support safe and high quality care, medical physicists must conduct efficient and proper commissioning, good clinical integration, and ongoing quality assurance (QA) of the TPS. AAPM Task Group 53 and related publications have served as seminal benchmarks for TPS commissioning and QA over the past two decades. Over the same time, continuing innovations have made the TPS even more complex and more central to the clinical process. Medical goals are now expressed in terms of the dose and margins around organs and tissues that are delineated from multiple imaging modalities (CT, MR and PET); and even temporally resolved (i.e., 4D) imaging. This information is passed on to optimization algorithms to establish accelerator movements that are programmed directly for IMRT, VMAT and stereotactic treatments. These advances have made commissioning and QA of the TPS much more challenging. This education session reviews up-to-date experience and guidance on this subject; including the recently published AAPM Medical Physics Practice Guideline (MPPG) #5 “Commissioning and QA of Treatment Planning Dose Calculations: Megavoltage Photon and Electron Beams”. Treatment Planning System Commissioning and QA: Challenges and Opportunities (Greg Salomons) This session will provide some key background and review publications describing prominent incidents relating to TPS commissioning and QA. Traditional approaches have been hardware and feature oriented. They aim to establish a functional configuration and establish specifications for regular testing of features (like dose calculation) to assure stable operation and detect failures. With the advent of more complex systems, more patient-specific testing has also been adopted. A number of actual TPS defects will be presented along with heuristics for identifying similar defects in the future. Finally, the Gamma test has become a popular metric for reporting TPS Commissioning and QA results. It simplifies complex testing into a numerical index, but noisy data and casual application can make it misleading. A brief review of the issues around the use of the Gamma test will be presented. TPS commissioning and QA: A process orientation and application of control charts (Michael Sharpe) A framework for commissioning a treatment planning system will be presented, focusing on preparations, practical aspects of configuration, priorities, specifications, and establishing performance. The complexity of the modern TPS make modular testing of features inadequate, and modern QA tools can provide “too much information” about the performance of techniques like IMRT and VMAT. We have adopted a process orientation and quality tools, like control charts, for ongoing TPS QA and assessment of patient-specific tests. The trending nature of these tools reveals the overall performance of the TPS system, and quantifies the variations that arise from individual plans, discrete calculations, and experimentation based on discrete measurements. Examples demonstrating application of these tools to TPS QA will be presented. TPS commissioning and QA: Incorporating the entire planning process (Sasa Mutic) The TPS and its features do not perform in isolation. Instead, the features and modules are key components in a complex process that begins with CT Simulation and extends to treatment delivery, along with image guidance and verification. Most importantly, the TPS is used by people working in a multi-disciplinary environment. It is very difficult to predict the outcomes of human interactions with software. Therefore, an interdisciplinary approach to training, commissioning and QA will be presented, along with an approach to the physics chart check and end-to-end testing as a tool for TPS QA. The role of standardization and automation in QA will also be discussed. The recommendations of MPPG #5 and practical implementation strategies (Jennifer Smilowitz) The recently published recommendations from Task Group No. 244, Medical Physics Practice Guideline on Commissioning and QA of Treatment Planning Dose Calculations: Megavoltage Photon and Electron Beams will be presented. The recommendations focus on the validation of commissioning data and dose calculations. Tolerance values for non-IMRT beam configurations are summarized based on established criteria and data collected by the IROC. More stringent evaluation criteria for IMRT dose calculations are suggested to test the limitations of the TPS dose algorithms for advanced delivery conditions. The MPPG encourages users to create a suite of validation tests for dose calculation for various conditions for static photon beams, heterogeneities, IMRT/VMAT and electron beams. This test suite is intended to be used for subsequent testing, including TPS software upgrades. In the past, the recommendations of some reports have not been widely implemented due to practical limitations. Implementation strategies, tools and processes developed by multiple centers for efficient and “do-able” MPPG # 5 testing will be presented, as well as a discussion on the overall validation experience. Learning Objectives: Identify some of the key documents relevant for TPS commissioning and QA Understand strategies for testing TPS software Gain a practical knowledge of the Gamma test criteria Increase familiarity with the process of commissioning a TPS Learn about the use of Control Charts for TPS QA Review the role of the TPS in the overall planning process Increase awareness of the link between TPS QA and chart checking Gain an increased appreciation for the importance of interdisciplinary communication Understand the new recommendations from MPPG #5 on TPS Dose Algorithm Commissioning and QC/QA Learn practical implementation processes and tools for MPPG #5 validation recommendations.

60 APPLIED LIFE SCIENCES↗