Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Distributed computation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Material Protection, Accounting and Control Technologies (MPACT) Implementation Plan: Lab-Scale Demonstration of Advanced Safeguard and Security Systems

The Materials Protection, Accounting, and Control Technologies (MPACT) campaign is working towards the goal of developing and demonstrating the next generation of nuclear materials management for the peaceful use of civilian nuclear energy. A major milestone of the campaign is the “Lab-scale demonstration of an advanced safeguards and security system,” due in 2020. This implementation plan describes how tools developed in the MPACT campaign will be used to meet this milestone. These tools consist of instrumentation and devices as well as computer software for modelling, simulation and integration of data and information for safeguard and security analysis. The plan is focused on demonstrating an advanced safeguard and security systems for electrochemical processing plants, but also identifies activities needed to address advanced reactor, aqueous processing and other advanced fuel cycle facilities. A key component to achieving the 2020 milestone is the development of a virtual distributed test bed that incorporates the instruments, data, analysis tools, and models currently under development and provides a framework to link and normalize the data in a way that simulates a facility, including uncertainty quantification. This virtual distributed test bed will integrate computer simulated facilities that make up a fuel cycle of interest, with distributed test beds located in actual operating facilities and laboratories. The MPACT campaign recently issued roadmaps for both Modelling & Simulation and Advanced Integration which address this component, and activities necessary to achieve the 2020 milestone. Research, development and testing of specific technologies have been supported by the MPACT campaign in coordination with other DOE-NE and DOE-NNSA programs. These technologies provide the essential data needed by the safeguard and security systems, and feed into the data analysis and facility models. This plan will identify these technologies, their current status and activities needed to demonstrate the technologies at the laboratory scale. Wherever possible, test of technologies in field conditions using suitable nuclear materials will be used to define performance. Where necessary, surrogate materials and/or simulation will be used to provide useful information for the demonstration. When completed, the 2020 milestone will provide a demonstration of advanced safeguard and security technologies, including advanced modelling, simulation and analysis approaches, applied to electrochemical processing. It will also identify applications of the technology and approaches in other advanced fuel cycle and reactor concepts.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2021

X-ray computed tomography-based porosity analysis: Algorithms and application for porous woody biomass

The properties of lignocellulosic biomass, such as bulk physical, thermal, and mechanical properties, as well as the mobility of enzymes or catalysts, are largely affected by porosity, pore structures, and pore size distribution. While X-ray computed tomography (CT) has been introduced to effectively produce 3D volumetric images of material microstructure, a quantitative porosity analysis from the 3D images has never been done. This work introduces a first-of-its-kind X-ray CT-based quantitative porosity analysis method and applies the developed toolkit to characterize the internal porosity distribution of loblolly pine. A sample loblolly pine chip was scanned by a nano-resolution X-ray CT system and digitally reconstructed after a sequence of image processing operations. Here, a comprehensive porosity analysis was then performed to quantify the envelope porosity, the spatial distribution of local porosity, and the directional porosity. Solutions to the various challenges in image processing, porosity calculation, and large data handling are provided.

42 ENGINEERING↗
DOE OSTI2012

Development of Large-Dimension Configuration-Interaction Shell-Model Code

The project period was devoted to several developments in the technical capabilities of the BIGSTIC large-dimension configuration-interaction shell-model code, written in Fortran 90. The specific computational goals for the project period were: (1) store Lanczos vectors on core in RAM to minimize I/O; (2) rewrite reorthogonalization with Lanczos vectors stored in core, consult with personnel at LLNL, LBL, ORNL, Iowa State University to maximize performance; (3) restrict creation of N-body jumps to those needed by an individual node; and (4) distribute 3-body interaction over many cores. Significant progress was made towards these goals, especially (1) and (2), although in the process they discovered intermediate tasks that had to be accomplished first. The achievements were as follows - I put into place structures and algorithms to facility fragmenting very large-dimension Lanczos intermediate vectors. Only by fragmenting the vectors can we carry out (1) and (2). In addition, I reorganized the action of the Hamiltonian matrix and created a new division of operations for MPI. Based upon earlier work, I made plans of a revised algorithm for distribution of work with MPI, with a particular eye towards breaking up the Lanczos vectors. I introduce a new derived type (opbundles) which collects the parameters for the Hamiltonian, and rewrote the application routines to use it. It has been validated and verified. I made progress towards revised MPI parallelization. Using the opbundles, I was able to compute a distribution of work over compute nodes, which should be very efficient. This new distribution is easier to derive and more efficient, in principle, than the old distribution. Furthermore, it should make applications with fragmented Lanczos vectors easier. Implementation is still in progress.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2012

Computational Challenges for Power System Operation

As the power grid technology evolution and information technology revolution converge, power grids are witnessing a revolutionary transition, represented by emerging grid technologies and large scale deployment of new sensors and meters in networks. This transition brings opportunities, as well as computational challenges in the field of power grid analysis and operation. This paper presents some research outcomes in the areas of parallel state estimation using the preconditioned conjugated gradient method, parallel contingency analysis with a dynamic load balancing scheme and distributed system architecture. Based on this research, three types of computational challenges are identified: highly coupled applications, loosely coupled applications, and centralized and distributed applications. Recommendations for future work for power grid applications are also presented.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Control of Ionomer Distribution and Porosity in Roll-to-Roll Coated Fuel Cell Catalyst Layers

As fuel cells transition from the laboratory to industrial production for vehicles and other applications there is a need to understand how manufacturing processes impact the properties and, ultimately, the performance of materials. Roll-to-roll coating enables processing at meters per second speeds with physics that can be quite different from common laboratory coating methods. In this work, we have focused on the coating of catalyst layers for proton exchange membrane fuel cells. Commonly, laboratory samples are prepared using spray coating or hand painting, which effectively coat many thin layers to achieve the desired catalyst layer thickness. This creates catalyst layers with uniform distributions of materials throughout the thickness of the full catalyst layer. In contrast, roll-to-roll methods, like slot die and gravure, coat the catalyst layer as a single wet film. As the film dries, ink constituents are able to segregate, leading to a heterogeneous distribution of materials through the thickness of the layer. It is also known that solvent and drying rate can affect the morphology of the catalyst layer. Thus, there is a need to understand how ink formulation and the drying process influence the distribution of materials and catalyst layer morphology. Here, we have explored the influence of solvent and drying rate on morphology of roll-to-roll coated catalyst layers. We show the development of the Kelvin probe method as a rapid screening technique for qualitative analysis of ionomer distribution. We also utilize nano X-ray computed tomography to visualize electrode structure and to quantify particle-size and pore-size distributions, thickness-dependent ionomer distribution, tortuosity, and effective transport properties. We find that solvent has a strong influence on ionomer distribution, with less of an effect on porosity. Conversely, drying temperature has a strong influence on porosity, but less influence on ionomer distribution. Finally, we utilize in situ fuel cell performance testing and other advanced diagnostics to quantify the impact of catalyst layer properties on fuel cell performance and demonstrate that roll-to-roll coating is capable of coating high performance catalyst layers in multi-meter lengths. have focused on the coating of catalyst layers for proton exchange membrane fuel cells. Commonly, laboratory samples are prepared using spray coating or hand painting, which effectively coat many thin layers to achieve the desired catalyst layer thickness. This creates catalyst layers with uniform distributions of materials throughout the thickness of the full catalyst layer. In contrast, roll-to-roll methods, like slot die and gravure, coat the catalyst layer as a single wet film. As the film dries, ink constituents are able to segregate, leading to a heterogeneous distribution of materials through the thickness of the layer. It is also known that solvent and drying rate can affect the morphology of the catalyst layer. Thus, there is a need to understand how ink formulation and the drying process influence the distribution of materials and catalyst layer morphology. Here, we have explored the influence of solvent and drying rate on morphology of roll-to-roll coated catalyst layers. We show the development of the Kelvin probe method as a rapid screening technique for qualitative analysis of ionomer distribution. We also utilize nano X-ray computed tomography to visualize electrode structure and to quantify particle-size and pore-size distributions, thickness-dependent ionomer distribution, tortuosity, and effective transport properties. We find that solvent has a strong influence on ionomer distribution, with less of an effect on porosity. Conversely, drying temperature has a strong influence on porosity, but less influence on ionomer distribution. Finally, we utilize in situ fuel cell performance testing and other advanced diagnostics to quantify the impact of catalyst layer properties on fuel cell performance and demonstrate that roll-to-roll coating is capable of coating high performance catalyst layers in multi-meter lengths.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2025

EJFAT Scientific Perspective

Presented new computing model to the test by deploying the EJFAT system alongside a data-stream processing framework running the production-level CLAS12 event reconstruction application. In this experiment, a continuous stream of CLAS12 Level-1 identified events was processed in real-time using the EJFAT load balancer, distributing the workload across 90 computing nodes located across the U.S. This marks the first-ever large-scale, real-time distributed data stream processing experiment, demonstrating that scientific data-streaming pipelines can efficiently scale across four dimensions, thanks to EJFAT’s advanced hardware and software capabilities.

Gyurjyan, Vardan [Thomas Jefferson National Accele↗
DOE OSTI2019

MCNP AND CFD MODELING OF A SODIUM FAST REACTOR SUB-ASSEMBLY CHANNEL TO CAPTURE LOCALIZED TEMPERATURE PEAKING

Typical evaluation tools for sodium-cooled fast reactors (SFR) use simplified neutronic/thermal models to efficiently compute the power and temperature distributions within the core. However, their modeling capability can be limited in extreme cases such as when sharp inter-assembly power gradients occur, or for non-standard SFR assembly geometries. Higher fidelity tools that rely on Monte Carlo methods for neutron transport, and Computational Fluid Dynamics (CFD) for thermal analysis, are better suited in these instances. The higher accuracy comes at the cost of higher computational expense. MCNP and STAR CCM+ were selected for this analysis. While MCNP is capable of generating pin-level power distributions for a whole-core SFR model, it is prohibitively expensive to then conduct CFD analysis for every single assembly. A semi-empirical model was therefore developed to rapidly estimate pin temperature distributions throughout the whole core. It relies on a geometric correction factor for turbulent flow-mixing. The correction factor is obtained from a CFD simulation of a single fuel assembly with a uniform power distribution and an adiabatic boundary condition. Without using CFD, each sub-channel outlet temperature is calculated separately using 1-D heat-balance and Nusselt number correlations and the MCNP calculated pin-powers. The rudimentary 1-D model is then corrected for the flow-mixing effect based on the CFD data. The temperature calculation is performed by a code written in the Python language called CFD Monte-Carlo Developed Reconstruction of Sub-channel at a Quasi-Representative Level (CMDR-SQRL). CMDR-SQRL was shown to adequately predict CFD evaluated temperature distribution for a wide range of SFR configurations, including an extreme case with fuel assemblies nearby containing moderating material. The agreement demonstrates how geometric and power-driven effects can be decoupled within an SFR assembly. CMDR-SQRL is intended to be mainly used for scoping studies to provide core-wide evaluations efficiently.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Automated Integration of Continental-Scale Observations in Near-Real Time for Simulation and Analysis of Biosphere–Atmosphere Interactions

The National Ecological Observatory Network (NEON) is a continental-scale observatory with sites across the US collecting standardized ecological observations that will operate for multiple decades. To maximize the utility of NEON data, we envision edge computing systems that gather, calibrate, aggregate, and ingest measurements in an integrated fashion. Edge systems will employ machine learning methods to cross-calibrate, gap-fill and provision data in near-real time to the NEON Data Portal and to High Performance Computing (HPC) systems, running ensembles of Earth system models (ESMs) that assimilate the data. For the first time gridded EC data products and response functions promise to offset pervasive observational biases through evaluating, benchmarking, optimizing parameters, and training new machine learning parameterizations within ESMs all at the same model-grid scale. Leveraging open-source software for EC data analysis, we are already building software infrastructure for integration of near-real time data streams into the International Land Model Benchmarking (ILAMB) package for use by the wider research community. We will present a perspective on the design and integration of end-to-end infrastructure for data acquisition, edge computing, HPC simulation, analysis, and validation, where Artificial Intelligence (AI) approaches are used throughout the distributed workflow to improve accuracy and computational performance.

Durden, David J.↗
DOE OSTI2017

EpiK: A Knowledge Base for Epidemiological Modeling and Analytics of Infectious Diseases

Computational epidemiology seeks to develop computational methods to study the distribution and determinants of health-related states or events (including disease), and the application of this study to the control of diseases and other health problems. Recent advances in computing and data sciences have led to the development of innovative modeling environments to support this important goal. The datasets used to drive the dynamic models as well as the data produced by these models presents unique challenges owing to their size, heterogeneity and diversity. These datasets form the basis of effective and easy to use decision support and analytical environments. As a result, it is important to develop scalable data management systems to store, manage and integrate these datasets. In this paper, we develop EpiK —a knowledge base that facilitates the development of decision support and analytical environments to support epidemic science. An important goal is to develop a framework that links the input as well as output datasets to facilitate effective spatio-temporal and social reasoning that is critical in planning and intervention analysis before and during an epidemic. The data management framework links modeling workflow data and its metadata using a controlled vocabulary. The metadata captures information about storage, the mapping between the linked model and the physical layout, and relationships to support services. EpiK is designed to support agent-based modeling and analytics frameworks—aggregate models can be seen as special cases and are thus supported. We use semantic web technologies to create a representation of the datasets that encapsulates both the location and the schema heterogeneity. The choice of RDF as a representation language is motivated by the diversity and growth of the datasets that need to be integrated. A query bank is developed—the queries capture a broad range of questions that can be posed and answered during a typical case study pertaining to disease outbreaks. The queries are constructed using SPARQL Protocol and RDF Query Language (SPARQL) over the EpiK. EpiK can hide schema and location heterogeneity while efficiently supporting queries that span the computational epidemiology modeling pipeline: from model construction to simulation output. As a result, we show that the performance of benchmark queries varies significantly with respect to the choice of hardware underlying the database and resource description framework (RDF) engine.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Layered Coordination Architecture for Resilient Restoration of Power Distribution Systems

The current practices for restoring critical services in the distribution system during a disaster, align with the traditional centralized ideology of distribution systems operations. A central processor evaluates the distribution system after a disruption and attains a restoration plan. However, the centralized operational paradigm is susceptible to single-point failures, requires full situational awareness of the distribution system, and poses scalability challenges for large multifeeder distribution systems. This motivates a distributed decision-making paradigm where multiple agents solve smaller subproblems and jointly coordinate their individual decisions to achieve the global/network-level objective. Toward this goal, we propose a layered architecture for distributed algorithms for resilience and a two-stage distributed algorithm for distribution system restoration. The proposed distributed decision-making framework enables the bottom-up restoration of the distribution system using all available resources, including distributed generation, while only requiring local awareness and limited communications with neighboring connected regions. The proposed framework is robust to single-point failures, enables autonomy using distributed algorithms, and had reduced computational cost compared to centralized optimization solutions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Implementation of Parallel Dynamic Simulation on Shared-Memory vs. Distributed-Memory Environments

Power system dynamic simulation computes the system response to a sequence of large disturbance, such as sudden changes in generation or load, or a network short circuit followed by protective branch switching operation. It consists of a large set of differential and algebraic equations, which is computational intensive and challenging to solve using single-processor based dynamic simulation solution. High-performance computing (HPC) based parallel computing is a very promising technology to speed up the computation and facilitate the simulation process. This paper presents two different parallel implementations of power grid dynamic simulation using Open Multi-processing (OpenMP) on shared-memory platform, and Message Passing Interface (MPI) on distributed-memory clusters, respectively. The difference of the parallel simulation algorithms and architectures of the two HPC technologies are illustrated, and their performances for running parallel dynamic simulation are compared and demonstrated.

dynamic simulation↗
DOE OSTI2016

SE2-ANL Subchannel Analysis with New Heating Calculation Based on VARIANT Transport Code

The multi-assembly, steady-state sub-channel analysis code SE2-ANL has been widely used in thermal-hydraulic analysis of sodium cooled fast reactors (SFR). It is used to compute the core-wide temperature profiles for a given flow distribution and to determine the assembly flow rates yielding a desired (assembly-wise) peak temperature distribution. It is a modified version of SUPERENERGY-2 coupled with the DIF3D/GAMSOR/DIF3D procedure for coupled neutron and gamma heating calculations, developed at Argonne National Laboratory (ANL). In the current version of SE2-ANL, the neutron and gamma fluxes are calculated using the finite-difference diffusion theory option of the DIF3D code with six triangular meshes per hexagonal assembly. In addition, the pin power distributions are estimated by assuming that the power distribution within an assembly is separable in the radial and axial directions. Furthermore, the total heat generation rate in an assembly duct wall is simply determined by a user-specified fraction of the total gamma heating within that assembly. In order to determine the pin power distributions more accurately by eliminating these limitations, a new coupled heating calculation procedure has recently developed based on the neutron and gamma transport calculations with the VARIANT code. For this, the GAMSOR code has been extended to generate the intra-nodal gamma source distribution to be consistent with the trial functions of VARIANT. Using the computed neutron and gamma flux distributions, the power distribution in each fuel pin and duct wall is determined using a new utility code CURVE, which has been developed to evaluate the VARIANT flux solution at the center of each fuel pin and along the duct mid-wall. For each pin segment contained in a VARIANT node, the axial power shape is represented as a quadratic profile. The SE2-ANL code has been modified to interface with the new, coupled neutron and gamma heating calculation scheme. In addition, several improvements have been made on the computational methods and models of SE2-ANL. To eliminate the limit on the axial mesh size due to the numerical instability problem of the current explicit scheme, the numerical scheme for discretizing the energy equation in the axial direction has been changed to the {theta}-method of the SLTHEN code. An automated flow allocation scheme has also been implemented in SE2-ANL to determine assembly flow rates such that the peak cladding mid-wall temperatures of individual orifice zones are equalized over the burn cycle. The impacts of the new heating calculation scheme based on VARIANT transport solutions on the cladding and fuel temperatures have been tested against the existing method of SE2-ANL. Using the existing and new heating calculation schemes, full-core subchannel analyses were performed for the metal core design of the 1000 MWt Advanced Burner Reactor (ABR-1000), and the resulting coolant, cladding and fuel temperatures were compared. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2019

Asset Monitoring using Smart Sensing and Advanced Analytics for the Distribution Network

As the electric grid transitions into a highly distributed and intelligent grid, electric utilities are becoming increasingly concerned with monitoring the health and performance of their distribution assets. As Internet of Things technologies and data analytics become inexpensive and ubiquitous, low-cost asset monitoring becomes more feasible. Moreover, using edge analytics, computations can be off-loaded to these intelligent sensors to report only actionable information to the cloud. This needs to be done in a highly distributed manner using non-intrusive sensors and device physics that seamlessly integrates with legacy infrastructure. Here, this paper reviews existing sensor based solutions, identifies t heir issues, proposes a novel solution by exploring the required attributes and proposes an approach for low-cost distribution transformer health monitoring.

Asset monitoring↗
DOE OSTI2022

Phoebe: a high-performance framework for solving phonon and electron Boltzmann transport equations

Understanding the electrical and thermal transport properties of materials is critical to the design of electronics, sensors, and energy conversion devices. Computational modeling can accurately predict material properties but, in order to be reliable, requires accurate descriptions of electron and phonon states and their interactions. While first-principles methods are capable of describing the energy spectrum of each carrier, using them to compute transport properties is still a formidable task, both computationally demanding and memory intensive, requiring integration of fine microscopic scattering details for estimation of macroscopic transport properties. To address this challenge, we present Phoebe—a newly developed software package that includes the effects of electron–phonon, phonon–phonon, boundary, and isotope scattering in computations of electrical and thermal transport properties of materials with a variety of available methods and approximations. This open source C++ code combines MPI-OpenMP hybrid parallelization with GPU acceleration and distributed memory structures to manage computational cost, allowing Phoebe to effectively take advantage of contemporary computing infrastructures. We demonstrate that Phoebe accurately and efficiently predicts a wide range of transport properties, opening avenues for accelerated computational analysis of complex crystals.

36 MATERIALS SCIENCE↗
DOE OSTI2011

Yield, variance and spatial distribution of electron–hole pairs in CsI

A Monte Carlo (MC) method previously developed has been applied to simulate the interaction of photons, with energies ranging from 50 eV to ~ 1 MeV, with CsI and the subsequent electron cascades. The MC model has been employed to compute nano-scale spatial distributions of electron-hole pairs and important intrinsic properties, including W, the mean energy per electron-hole pair, and the Fano factor, F. W exhibits discontinuities at the shell edges that follow the photoionization cross sections and decreases with increasing photon energy (from ~19 to 15 eV), with an asymptotic value of 15.2 eV at high energy. This decrease may contribute the initial rise in relative light yield with incident energy observed experimentally for CsI, thus suggesting that nonlinearity may be associated with intrinsic properties of the material at low energies. F is calculated to increase with increasing energy and has an asymptotic value of 0.28. A significant number of electron-hole pairs are produced through the different ionization channels of core shells and corresponding relaxation processes, which may explain why F is larger for CsI than for Si or Ge. Finally, the calculated spatial distributions show that the electron-hole pairs are primarily distributed along fast electron tracks. These spatial distributions constitute important input for large-scale simulations of electron-hole pair transport.

CsI.↗
DOE OSTI2015

Engineering the CernVM-Filesystem as a High Bandwidth Distributed Filesystem for Auxiliary Physics Data

A common use pattern in the computing models of particle physics experiments is running many distributed applications that read from a shared set of data files. We refer to this data is auxiliary data, to distinguish it from (a) event data from the detector (which tends to be different for every job), and (b) conditions data about the detector (which tends to be the same for each job in a batch of jobs). Relatively speaking, conditions data also tends to be relatively small per job where both event data and auxiliary data are larger per job. Unlike event data, auxiliary data comes from a limited working set of shared files. Since there is spatial locality of the auxiliary data access, the use case appears to be identical to that of the CernVM- Filesystem (CVMFS). However, we show that distributing auxiliary data through CVMFS causes the existing CVMFS infrastructure to perform poorly. We utilize a CVMFS client feature called 'alien cache' to cache data on existing local high-bandwidth data servers that were engineered for storing event data. This cache is shared between the worker nodes at a site and replaces caching CVMFS files on both the worker node local disks and on the site's local squids. We have tested this alien cache with the dCache NFSv4.1 interface, Lustre, and the Hadoop Distributed File System (HDFS) FUSE interface, and measured performance. In addition, we use high-bandwidth data servers at central sites to perform the CVMFS Stratum 1 function instead of the low-bandwidth web servers deployed for the CVMFS software distribution function. We have tested this using the dCache HTTP interface. As a result, we have a design for an end-to-end high-bandwidth distributed caching read-only filesystem, using existing client software already widely deployed to grid worker nodes and existing file servers already widely installed at grid sites. Files are published in a central place and are soon available on demand throughout the grid and cached locally on the site with a convenient POSIX interface. This paper discusses the details of the architecture and reports performance measurements.

Dykstra, D.↗
DOE OSTI2019

Probabilistic Forecast of Single–Phase Flow in Porous Media With Uncertain Properties

Uncertainty about geologic makeup and properties of the subsurface renders inadequate a unique quantitative prediction of flow and transport. Instead, multiple alternative scenarios have to be explored within the probabilistic framework, typically by means of Monte Carlo simulations (MCS). These can be computationally expensive, and often prohibitively so, especially when the goal is to compute the tails of a distribution, i.e., probabilities of rare events, which are necessary for risk assessment and decision making under uncertainty. We deploy the method of distributions to derive a deterministic equation for the cumulative distribution function (CDF) of hydraulic head in an aquifer with uncertain (random) hydraulic conductivity. The CDF equation relies on a self-consistent closure approximation, which ensures that the resulting CDF of hydraulic head has the same mean and variance as those computed with either statistical moment equation (the approach used herein) or MCS. We conduct a series of numerical experiments dealing with steady-state two-dimensional flow driven by either a natural hydraulic head gradient or a pumping well. Furthermore, these experiments reveal that the CDF method remains accurate and robust for highly heterogeneous formations with the variance of log conductivity as large as five. For the same accuracy, it is also up to four orders of magnitude faster than MCS in computing hydraulic head with a required degree of confidence (probability).

42 ENGINEERING↗
DOE OSTI2015

Continuous Monitoring and Intrafraction Target Position Correction During Treatment Improves Target Coverage for Patients Undergoing SBRT Prostate Therapy

Purpose: To compare the potential benefits of continuous monitoring of prostate position and intervention (CMI) using 2-mm displacement thresholds during stereotactic body radiation therapy (SBRT) treatment to those of a conventional image-guided procedure involving single localization prior to treatment. Methods and Materials: Eighty-nine patients accrued to a prostate SBRT dose escalation protocol were implanted with radiofrequency transponder beacons. The planning target volume (PTV) margin was 5 mm in all directions, except for 3 mm in the posterior direction. The prostate was kept within 2 mm of its planned position by the therapists halting dose delivery and, if necessary, correcting the couch position. We computed the number, type, and time required for interventions and where the prostate would have been during dose delivery had there been, instead, a single image-guided setup procedure prior to each treatment. Distributions of prostate displacements were computed as a function of time. Results: After the initial setup, 1.7 interventions per fraction were required, with a concomitant increase in time for dose delivery of approximately 65 seconds. Small systematic drifts in prostate position in the posterior and inferior directions were observed in the study patients. Without CMI, intrafractional motion would have resulted in approximately 10% of patients having a delivered dose that did not meet our clinical coverage requirement, that is, a PTV D95 of >90%. The posterior PTV margin required for 95% of the dose to be delivered with the target positioned within the PTV was computed as a function of time. The margin necessary was found to increase by 2 mm every 5 minutes, starting from the time of the imaging procedure. Conclusions: CMI using a tight 2-mm displacement threshold was not only feasible but was found to deliver superior PTV coverage compared with the conventional image-guided procedure in the SBRT setting.

62 RADIOLOGY AND NUCLEAR MEDICINE↗