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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Implementation and evaluation of multi-dual mode counter-current chromatography in the CUP Modeler software

Counter-current chromatography (CCC) is a separation technique that utilizes immiscible solvent pairs as stationary and mobile phases, which imparts numerous benefits compared to solid-liquid chromatography including the ability to treat either the more-dense or less-dense solvent layer as the mobile phase. Multi-dual mode (MDM) is a CCC elution mode capable of improving the separation of closely eluting compounds by alternating upper- and lower-layer solvent flows in opposing directions within the same separation. While some effort has been made to model MDM, implementation of these models in experimental design has yet to be widely adopted. Accordingly, we further developed our previously published cell utilized partitioning (CUP) model to include MDM predictions with CCC and packaged the full suite of CUP modeling capabilities into a user-friendly, open-source tool called the CUP Modeler. The mathematical model for MDM CCC was derived and validated with experimental separation of ethyl guaiacol (EG) and ethyl phenol (EP), two compounds that co-elute in our previously demonstrated reductive catalytic fractionation (RCF) lignin monomer isolation method. The developed MDM model provided insights into the effect of multiple operating parameters - including stationary phase retention, flow rate, column efficiency, feed concentration ratio, selectivity factor, and solute distribution ratios - on the separation yields, productivity, and purities. Our model agreed with prevailing understanding of MDM but also revealed new insights including that the ideal distribution ratios for co-eluting solutes to be separated by MDM is between 1.1 and 1.5, with the lower value ideally close to 1.25. Overall, this work provides fundamental insights for MDM process design and enables broader adoption of general liquid-liquid chromatography with a new, open-source user-friendly interface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

SimCCS: An open-source tool for optimizing CO 2 capture, transport, and storage infrastructure

Commercial-scale carbon capture and storage (CCS) technology will involve deploying infrastructure on a massive and costly scale. This effort will require careful and comprehensive planning to ensure that capture locations, storage sites, and the dedicated CO 2 distribution pipelines are selected in a robust and cost-effective manner. Presented in 2009, SimCCS is an optimization model for integrated system design that enables researchers, stakeholders, and policy makers to design CCS infrastructure networks. SimCCS 2.0 is a complete, ground-up redesign that is now a portable software package, useable and shareable by the CCS research, industrial, policy, and public communities. SimCCS 2.0 integrates multiple new capabilities including a refined optimization model, novel candidate network generation techniques, and optional integration with high-performance computing platforms. Accessing user-provided CO 2 source, sink, and transportation data, SimCCS 2.0 creates candidate transportation routes and formalizes an optimization problem that determines the most cost-effective CCS system design. This optimization problem is further solved either through a high-performance computing interface, or through third-party software on a local desktop computing platform. Finally, SimCCS 2.0 employs an open-access geographic information system framework to enable analysis and visualization capabilities. SimCCS 2.0 is written in Java and is publicly available via GitHub to encourage collaboration, modification, and community development.

42 ENGINEERING↗
DOE OSTI2013

3D tomodosimetry using long scintillating fibers: A feasibility study

Purpose: 3D dosimetry is recognized as an ideal for patient-specific quality assurance (QA) of highly conformal radiotherapy treatments. However, existing 3D dosimeters are not straightforward to implement in the clinic, as their read-out procedure is often tedious and their accuracy, precision, and/or sample size exhibit limitations. The purpose of this work is to develop a 3D dosimeter based on the concept of tomodosimetry inside concentric cylindrical planes using long scintillating fibers for the QA of modern radiotherapy techniques such as intensity-modulated radiation therapy (IMRT) or intensity-modulated arc therapy (IMAT).Methods: Using a model-based simulation, scintillating fibers were modeled on three concentric cylindrical planes of radii 2.5, 5.0, and 7.5 cm, inside a 10 cm radius water-equivalent cylinder phantom. The phantom was set to rotate around its central axis, made parallel to the linac gantry axis of rotation. Light acquisitions were simulated using the calculated dose from the treatment planning software and reconstructed in each cylindrical plane at a resolution of 1 mm{sup 2} using a total-variation minimization iterative reconstruction algorithm. The 3D dose was then interpolated from the reconstructed cylindrical plane doses at a resolution of 1 mm{sup 3}. Different scintillating fiber patterns were compared by varying the angle of each fiber in its cylindrical plane and introducing a light-tight cut in each fiber. The precision of the reconstructed cylindrical dose distribution was evaluated using a Poisson modeling of the acquired light signals and the accuracy of the interpolated 3D dose was evaluated using an IMRT clinical plan for a prostate case.Results: Straight scintillating fiber patterns with light-tight cuts were the most accurate in cylindrical dose reconstruction, showing less than 0.5 mm distance-to-agreement in dose gradients and a mean local dose difference of less than 0.2% in the high dose region for a 10 × 10 cm{sup 2} field. The precision attained with this fiber configuration was less than 0.9% in the high dose, low gradient region of an IMRT segment for light acquisitions of 0.1 MU over a 360 degree rotation of the cylinder phantom. 3D dose interpolation for the IMRT clinical plan yielded an overall dose difference with the reference input of less than 1%, except in high dose gradients.Conclusions: Using long scintillating fibers inside rotating, concentric cylindrical planes, the authors demonstrate that their tomodosimetry method has the potential for high resolution, precise, and accurate 3D dosimetry. Moreover, because of its water-equivalence and rotational symmetry, this design should find interesting application for both treatment QA and machine commissioning.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

TU-H-BRA-05: A System Design for Integration of An Interior MRI and a Linear Accelerator

Purpose: MRI is a highly desirable modality to guide radiation therapy but it is difficult to combine a conventional MRI scanner directly with a linear accelerator (linac). An interior MRI (iMRI) concept has been proposed to acquire MRI images within a small field of view only covering targets and immediate surrounding tissues. The objective of this project is to design an interior MRI system to work with a linac using a magnet to provide a field around 0.2T in a cube of 20cm per side, and perform image reconstruction with a slightly inhomogeneous static magnetic fields. Methods: All the results are simulated using a commercially available software package, FARADY. In our design, a ring structure holds the iMRI system and also imbeds a linac treatment head. The ring is synchronized to the linac gantry rotation. Half of the ring is made of steel and becomes a magnetic flux return path (yoke) so that a strong magnetic field will be limited inside the iron circuit and fringe fields will be very weak. In order to increase the static magnetic field homogeneity, special steel magnet boots or tips were simulated. Three curved boots were designed based on two-dimensional curves: arc, parabola and hyperbola. Results: Different boot surfaces modify magnetic field distributions differently. With the same pair of neodymium-iron-boron (NdFeB) magnets, the magnetic induction at the centers are 0.217T, 0.201T, 0.204T, and 0.212T for flat, arc, parabola and hyperbola boots, respectively. The hyperbola boots lead to the most homogeneous results, the static magnetic field deviations are within 0.5% in a cube of 20cm, and can be further improved using shimming techniques. Conclusion: This study supports the concept of an iMRI design. Successful development of iMRI will provide crucial information for tumor delineation in radiation therapy.

43 PARTICLE ACCELERATORS↗
DOE OSTI2015

Validation of continuous energy sensitivity coefficients calculations in the MORET 5 code - 14269

A continuous-energy sensitivity coefficients calculation capability has been developed in the MORET 5 Monte Carlo code recently. As discussed in this paper, it relies on the differential operator method, an adjoint weighting model (to avoid calculating the fission source derivatives) and a constrained sensitivity coefficient model for sensitivity profiles to distributions such as, for instance, the fission spectrum. For now, the coefficients are provided per medium, per isotope, per reaction on an energy binning defined by the user. The sensitivity coefficients are currently available for the following quantities: total, elastic scattering, total inelastic scattering, fission, total capture and radiative capture cross sections, average neutron produced by fission and fission spectrum. This paper deals with the validation of this new feature in the MORET code on several benchmarks and applications with various energy spectra and geometrical configurations. This validation is performed through the UACSA expert group and the Jezebel ICSBEP benchmarks, but also thanks to calculations performed in the frame of experimental program design in the STACY facility. Comparisons are made using the MCNP6.1 code and the SCALE6.1 package as references. Preliminary results show a pretty good agreement between the different software. (authors)

42 ENGINEERING↗
DOE OSTI2012

Probability-Based Software for Grid Optimization: Improved Power System Operations Using Advanced Stochastic Optimization

GENI Project: Sandia National Laboratories is working with several commercial and university partners to develop software for market management systems (MMSs) that enable greater use of renewable energy sources throughout the grid. MMSs are used to securely and optimally determine which energy resources should be used to service energy demand across the country. Contributions of electricity to the grid from renewable energy sources such as wind and solar are intermittent, introducing complications for MMSs, which have trouble accommodating the multiple sources of price and supply uncertainties associated with bringing these new types of energy into the grid. Sandia’s software will bring a new, probability-based formulation to account for these uncertainties. By factoring in various probability scenarios for electricity production from renewable energy sources in real time, Sandia’s formula can reduce the risk of inefficient electricity transmission, save ratepayers money, conserve power, and support the future use of renewable energy.

ARPA-E↗
DOE OSTI2016

SU-F-T-468: Efficient Scanning Data Analysis for TomoTherapy

Purpose: The standard TomoTherapy 2D scanning system requires manual analysis using spreadsheets or similar software. Manual analysis is time consuming and does not allow efficient use of the medical physicist or timely results that may indicate issues during the acquisition of data. The purpose of this study is to determine if an in-house solution can provide timely analysis of TomoTherapy scan data. Methods: A custom MATLAB program utilizing a streamlined graphical interface was developed to interpret the native scanning data acquired by the TomoTherapy Electrometer Measurement System (TEMS). The gold beam data provided by the manufacturer was used as a baseline for the acquired data. Two separate sets of scan data were used including longitudinal, transverse, and percent depth dose (PDD). The scan data were compared visually in an overlay and analytically for each beam width using the full width half max (FWHM) for longitudinal profiles and difference inside the field core for the transverse profiles as recommended by TG-148. A plot of the PDD percent error at each point along the curve was generated to show agreement. The time to analysis was measured on a laptop running an Intel i5 processor with 8GB of RAM. Results: The software program required on average less than 5 seconds to load and analyze the results. No conversion or reformatting of the data was required. This allowed real-time visualization of the comparison to the gold beam data as well as the parameters recommended by TG-148. The average percent difference was 0.3% for the longitudinal profiles and 0.1% for the transverse profiles. All PDD data was less than 1% different beyond dmax. Conclusion: We have developed a tool to analyze TomoTherapy scan data in real-time. This allows an efficient method to perform beam commissioning, annual QA, and adjust the beam parameters if necessary.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2019

PV Cyber Security Research (Final Report)

Extensive deployment of interoperable distributed energy resources (DER) on power systems is increasing the power system cyber security attack surface. National and jurisdictional interconnection standards require DER to include a range of autonomous and commanded grid support functions which can drastically influence power quality, voltage, and bulk system frequency. This project was split into two phases. The first provided a survey and roadmap of the cybersecurity for the solar industry. The second investigated multiple PV cybersecurity research and development (R&D) concepts identified in the first phase. In the first year, the team created a roadmap for improving cybersecurity for distributed solar energy resources. This roadmap was intended to provide direction for the nation over the next five years and focused on the intersection of industry and government and recommends activities in four related areas: stakeholder engagement, cyber security research and development, standards development, and industry best practices. At the same time, the team produced a primer for DER vendors, aggregators, and grid operators to establish a common taxonomy and describe basic principles of cyber security, encryption, communication protocols, DER cyber security recommendations and requirements, and device-, aggregator-, and utility-level security best practices to ensure data confidentiality, integrity, and availability. This material was motivated by the need to assist the broader PV industry with cybersecurity resilience and describe the state-of-the-art for securing DER communications. Lastly, an adversary-based assessment of multiple PV devices was completed at the Distributed Energy Technologies Laboratory at Sandia National Laboratories to determine the status of industry cybersecurity practices. The team found multiple deficiencies in the security features of the assessed devices. In the second year, a set of recommendations was created for DER communication protocols— especially with respect to the state-of-the-art requirements in IEEE 2030.5. Additionally, several cybersecurity R&D technologies related to communications-enabled photovoltaic systems were studied to harden DER communication networks. Specifically, the team investigated (a) using software defined networking to create a moving target defense system for DER communications, and (b) engineering controls that prevent misprogramming or adversary action on DER devices/networks by disallowing setpoints that will generate unstable power system operations.

14 SOLAR ENERGY↗
DOE OSTI2021

WOMBAT (Windfarm Operations and Maintenance cost-Benefit Analysis Tool) WISDEM® [SWR-21-68]

The windfarm operations and maintenance cost-benefit analysis tool (WOMBAT) is software to simulate the operations and maintenance phase of either onshore or offshore windfarms. WOMBAT is a medium-fidelity tool that is designed to model turbine, cable, and substation failures at the subassembly level, but is flexible enough that individual component or asset-level modeling can also be performed. WOMBAT enables users to model technological improvements, the use of a wide range of service equipment from drone repairs and remote resets to heavy lift vessels and crawler cranes, to analyze cost trends with varying trade-offs in conjunction with energy production, availability and a growing range of metrics. This library provides a tool to simulate the operation and maintenance phase (O&M) of distributed, land-based, and offshore windfarms using a discrete event simulation framework. WOMBAT is written around the SimPy discrete event simulation framework. Additionally, this is supported using a flexible and modular object-oriented code base, which enables the modeling of arbitrarily large (or small) windfarms with as many or as few failure and maintenance tasks that can be encoded. Please note that this is still heavily under development, so you may find some functionality to be incomplete at the current moment, but rest assured the functionality is expanding. With that said, it would be greatly appreciated for issues or PRs to be submitted for any improvements at all, from fixing typos (guaranteed to be a few) to features to testing. Also available at: https://pypi.org/project/wombat/

Cooperman, Aubryn↗
DOE OSTI2015

Design & Implementation of MACSio

We are proposing to develop “MACSio” (pronounced “max-ee-oh”), a Multi-purpose, Application-Centric, Scalable I/O proxy application. It is being proposed to fill a long existing void in co-design proxy applications that allow for I/O performance testing and evaluation of tradeoffs in data model interfaces and parallel I/O paradigms for multi-physics, HPC applications. Two key design features of MACSio will set it apart from existing I/O benchmarking tools. The first is the level of abstraction (LOA) at which MACSio is being designed to operate. The second is the degree of flexibility MACSio is being designed to provide in driving an HPC I/O workload through parameterized, user-defined data objects and a variety of parallel I/O paradigms and I/O interfaces. Combined, these features will allow MACSio to closely mimic I/O workloads for a wide variety of real applications and, in particular, multi-physics applications where data object distribution and composition vary dramatically both within and across parallel tasks. These data objects can then be marshaled using one or more I/O interfaces and parallel I/O paradigms, allowing for direct comparisons of software interfaces, parallel I/O paradigms, and filesystem technologies with the same set of customizable data objects.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Application of Advanced Metering Infrastructure Data to Advanced Utility System Operations: Cooperative Research and Development, CRADA Number CRD-17-00712 (Final Report)

The primary objective of the proposed project is to evaluate the capabilities of Advanced Metering Infrastructure (AMI) based controls for grid operations. This includes monitoring and control at the secondary transformer level using existing AMI infrastructure. In addition, some of the challenges of using a model-less control will also be identified. The lessons learned will be disseminated to other utilities around the country through peer-reviewed publications with the consent of SDG&E. The scope of the work includes using data from SDG&E's existing AMI infrastructure and working with third party vendors selected by SDG&E. The grid edge monitoring systems and controls provided by the selected vendors will perform grid operations using AMI data. The National Renewable Energy Laboratory (NREL) will perform a software and controller-based evaluation of the grid edge controller, intelligent devices and sensors, at the Energy System Integration Facility (ESIF) laboratory.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

The Kokkos Ecosystem [Brief]

In 2016/2017, the field of High-Performance Computing (HPC) entered a new era driven by fundamental physics challenges to produce ever more energy and cost-efficient processors. Since the convergence on the Message-Passing Interface (MPI) standard in the mid-1990s, application developers enjoyed a seemingly static view of the underlying machine — that of a distributed collection of homogeneous nodes executing in collaboration. However, after almost two decades of dominance, the sole use of MPI to derive parallelism acted as a limiter to improved future performance. While MPI is widely expected to continue to function as the basic mechanism for communication between compute nodes for the immediate future, additional parallelism is required on the computing node itself if high performance and efficiency goals are to be realized. When reviewing the architectures of the top HPC systems today, the change in paradigm is clear: the compute nodes of the leading machines in the world are either powered by many-core chips with a few dozen cores each, or use heterogeneous designs, where traditional CPUs marshal work to massively parallel compute accelerators which has as many as 200,000 processing threads in flight simultaneously. Complicating matters further for application developers, each processor vendor has its own preferred way of writing code for their architecture.The Kokkos EcoSystem was released by Sandia in 2017 to address this new era in HPC system design by providing a vendor independent performance portable programming system for scientific, engineering, and mathematical software applications written in the C++ programming language. Using Kokkos, application developers can be more productive because they will not have to create and maintain separate versions of their software for each architecture, nor will they have to be experts in each architecture's peculiar requirements. Instead, they will have a single method of programming for the diverse set of modern HPC architectures. While Kokkos started in 2011 as a programming model only, it soon became clear that complex applications needed more. It is also critical to have a portable mathematical functions and developers need tools to debug their applications, gain insight into the performance characteristics of their codes and tune algorithm performance parameters through automated processes. The Kokkos EcoSystem addresses those needs through its three main components: the Kokkos Core programming model, the Kokkos Kernels math library, and the Kokkos Tools project.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

COWALKER:EFFECTIVE TRANSPORT PROPERTIES OF COMPOSITE MATERIALS

SF-23-026 This software computes effective transport properties of composite materials involving fibers and nanoparticles using a random-walk algorithm that efficiently scales to an arbitrary number of processes and cores. Effective transport properties (thermal, electrical) are key to bridge the microstructure of complex materials with its macroscopic behavior. Traditional approaches either use effective medium approximations (closed mathematical expressions that are approximation for certain conditions) or continuum simulation models such as finite element or finite volume, which require the generation of a mesh for each configuration explored. cowalker leverages the equivalence between laplacian or heat equation-based models and random walks to compute the asymptotic transport properties from an ensemble of first sojourn times of a random walker moving through the composite material. This allows us to directly define a composite material as a collection of particles and use algorithms developed for molecular dynamics to quickly compute the intersection of the walker with the different interfaces in the material. cowalker is developed in C++, and it relies on the GNU Scientific Library for random generation. cowalker is currently delivered as source code, so the GSL library is not included in cowalker's distribution. A more userfriendly version, cowalker.jl is currently in development and will be released as part of cowalker.

YANGUAS-GIL, ANGEL↗
DOE OSTI2019

Future SDN-HPON Control Plane Architecture and Protocol for On-Demand Terabit End-to-End Extreme-Scale Science Applications

The UC Davis team conducted architecture, algorithm and experimental studies for next generation ultra-high-bandwidth optical networks in support of extreme-scale science applications. In particular, over the course of this 3-year project, the UC Davis team achieved the following main accomplishments: Designed a network architecture for automated multi-domain service provisioning: Designed information exchange schemes between autonomous systems (domains) Designed application programming interfaces to orchestrate resource reservation in data centers, high performance computation facilities, and communication networks belonging to different autonomous systems Experimentally assessed the multi-domain network architecture in a distributed field trial set-up connecting premises in three continents Designed a broker-based orchestrated multi-domain optical networking framework supporting observe-analyze-act cycle based cognitive inter-domain service provisioning: Designed an inter-domain operation mechanism, e.g., topology abstraction, for the broker plane and domain managers to collaboratively accomplish inter-domain service provisioning while respecting the autonomy of each administrative domain Designed an alien wavelength monitoring scheme and an artificial neural network based optical signal-to-noise ratio estimator for quality-of-transmission aware inter-domain service provisioning Developed a deep neural network based multi-domain traffic predictor and a cognitive routing and spectrum assignment algorithm to realize knowledge-based autonomous traffic engineering in multi-domain networks Implemented an optical signal-to-noise ratio estimator and traffic predictor with Google’s Tensor flow and assessed their performance using experimental and synthetic data Demonstrated the benefits of the proposed cognitive schemes with experiments ona two-domain elastic optical network testbed and evaluations on a six-domain simulation framework Built a two-domain software-defined networking control plane testbed using the ONOS platform and demonstrated the workflow of broker and domain manager cooperation, including hierarchical performance monitoring, topology abstraction and cognitive resource allocation. Designed self-learning cognitive service provisioning schemes using advanced machine learning technologies: Designed a self-taught anomaly detection framework for optical networks, including an unsupervised data clustering module for pattern recognition, a supervised data regression and classification module for online anomaly detection, and the system operation principle Experimentally validated the effectiveness of the self-taught anomaly detection framework with various failure/anomaly scenarios. Designed a self-learning autonomic routing, modulation and spectrum assignment (RMSA) provisioning framework for elastic optical networks with deep reinforcement learning. Designed effective modeling and training mechanisms for the self-learning RMSA framework Conducted extensive numerical simulations with various traffic patterns and topologies to verify the advantage of the self-learning RMSA framework.

42 ENGINEERING↗
DOE OSTI2016

A Lyapunov Function Based Remedial Action Screening Tool Using Real-Time Data

This report summarizes the outcome of a research project that comprised the development of a Lyapunov function based remedial action screening tool using real-time data (L-RAS). The L-RAS is an advanced computational tool that is intended to assist system operators in making real-time redispatch decisions to preserve power grid stability. The tool relies on screening contingencies using a homotopy method based on Lyapunov functions to avoid, to the extent possible, the use of time domain simulations. This enables transient stability evaluation at real-time speed without the use of massively parallel computational resources. The project combined the following components. 1. Development of a methodology for contingency screening using a homotopy method based on Lyapunov functions and real-time data. 2. Development of a methodology for recommending remedial actions based on the screening results. 3. Development of a visualization and operator interaction interface. 4. Testing of screening tool, validation of control actions, and demonstration of project outcomes on a representative real system simulated on a Real-Time Digital Simulator (RTDS) cluster. The project was led by Michigan State University (MSU), where the theoretical models including homotopy-based screening, trajectory correction using real-time data, and remedial action were developed and implemented in the form of research-grade software. Los Alamos National Laboratory (LANL) contributed to the development of energy margin sensitivity dynamics, which constituted a part of the remedial action portfolio. Florida State University (FSU) and Southern California Edison (SCE) developed a model of the SCE system that was implemented on FSU's RTDS cluster to simulate real-time data that was streamed over the internet to MSU where the L-RAS tool was executed and remedial actions were communicated back to FSU to execute stabilizing controls on the simulated system. LCG Consulting developed the visualization and operator interaction interface, based on specifications provided by MSU. The project was performed from October 2012 to December 2016, at the end of which the L-RAS tool, as described above, was completed and demonstrated. The project resulted in the following innovations and contributions: (a) the L-RAS software prototype, tested on a simulated system, vetted by utility personnel, and potentially ready for wider testing and commercialization; (b) an RTDS-based test bed that can be used for future research in the field; (c) a suite of breakthrough theoretical contributions to the field of power system stability and control; and (d) a new tool for visualization of power system stability margins. While detailed descriptions of the development and implementation of the various project components have been provided in the quarterly reports, this final report provides an overview of the complete project, and is demonstrated using public domain test systems commonly used in the literature. The SCE system, and demonstrations thereon, are not included in this report due to Critical Energy Infrastructure Information (CEII) restrictions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Fast and robust strategies for large-scale mixed-integer SCOPF

This project develops scalable, computationally efficient algorithms to solve realistic large-scale power system optimization problems, including systems with more than 8,000 buses, as part of a larger series of competitions run by ARPA-E. These problems are critical because the secure and reliable operation of the power grid is becoming increasingly challenging, especially under conditions of increased uncertainty and variability. The economic feasibility of our methods is high, given that they are purely software-based solutions designed to operate power grids more efficiently. The technical effectiveness balances heuristics and approximations to provide a trade-off between speed and accuracy.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

CASL COBRA-TF improvements for PWR DNB analysis

COBRA-TF (CTF) is a thermal hydraulic (T/H) subchannel code using either three-dimensional (3D) Cartesian or subchannel coordinate formulations for two-phase fluid flow and heat transfer solutions. CTF has been improved under the Consortium for Advanced Simulation of Light Water Reactors (CASL) program for Pressurized Water Reactor (PWR) applications, including software optimization, new closure models, pre- and post-processing and parallelization for modeling full reactor core T/H responses under normal operating and accident conditions. As a result of collaboration among CASL partners including the Westinghouse Electric Company, the Oak Ridge National Laboratory (ORNL), and the Sandia National Laboratories, additional modeling improvements were made to CTF specifically for PWR Departure from Nucleate Boiling (DNB) analysis, including a code option to evaluate fuel thermal margin in terms of DNB Ratio (DNBR) and an axial shape factor to account for effect of non-uniform axial power distribution on DNB. Multiple DNB correlations are now linked with CTF for different applications, including the Westinghouse proprietary WRB-1 correlation for fuel designs containing mixing vane grid spacers. The improved CTF code with the WRB-1 correlation (CTF/WRB-1) was validated using the DNB data from the PWR Subchannel Bundle Tests (PSBT). In addition to the comparison with the test data, the CTF/WRB-1 DNBR results and the associated local fluid conditions were compared to the results of the Westinghouse T/H design code, VIPRE-W, which is an enhanced version of the VIPRE-01 code originally developed by the Electric Power Research Institute (EPRI). The comparisons showed that CTF/WRB-1 DNBR predictions are in good agreement with the VIPRE-W results within the applicable range of the DNB correlation. A model sensitivity study was performed to confirm that the CTF void drift model had an insignificant effect on DNBR under the steam line break (SLB) low pressure condition. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

TH-C-12A-09: Planning and Delivery of the Fully Dynamic Trajectory Modulated Arc Therapy: Application to Accelerated Partial Breast Irradiation

Purpose: A novel trajectory modulated arc therapy (TMAT) system was developed that uses source motion trajectory involving synchronized gantry rotation with translational and rotational couch movement. MLC motion and dose rate were fully optimized for dynamic beam delivery. This work presents a platform for planning deliverable TMAT on a collision free coronal trajectory and evaluates its benefit for accelerated partial breast irradiation (APBI) in a prone position. Methods: The TMAT algorithm was built on VMAT with modifications (physical properties on couch movement were defined) and enhancements (pencil beam dose calculation engine to support extended SSDs) to make it feasible for TMAT delivery. A Matlab software environment for TMAT optimization and dose calculation was created to allow any user specified motion axis. TMAT delivery was implemented on Varian TrueBeamTM STx via XML scripts. 10 prone breast irradiation cases were evaluated in VMAT and compared with a 6- field non-coplanar IMRT plan. Patient selection/exclusion criteria and structure contouring followed the guidelines of NSABP B-39/RTOG 0413 protocol. Results: TMAT delivery time was ∼4.5 minutes. 251.5°±7.88° of non-isocentric couch arc was achieved by the optimized trajectory with 180– 210 control points at 1°–2° couch increments. The improved dose distribution by TMAT was most clearly observed by the marked reduction in the volume of irradiated normal breast tissue in the high dose region. The ratios of the normal breast tissue volume receiving more than 50%, 80% and 100% of the prescription dose for TMAT versus IMRT were: V50%(TMAT/IMRT) = 78.38%±13.03%, V80%(TMAT/IMRT) = 44.19%±9.04% and V100% (TMAT/IMRT) = 9.96%±7.55%, all p≤0.01. Conclusion: The study is the first demonstration of planning and delivery implementation of a fully dynamic APBI TMAT system with continuous couch motion. TMAT achieved significantly improved dosimetry over noncoplanar IMRT on dose volume parameters correlated with toxicity and cosmetic outcome of APBI. This project was supported by Varian Research Grant.

60 APPLIED LIFE SCIENCES↗