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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Progress on Generic Phase-Field Method Development

In this report, we summarize our current collaborative efforts, involving three national laboratories: Idaho National Laboratory (INL), Pacific Northwest National Laboratory (PNNL) and Los Alamos National Laboratory (LANL), to develop a computational framework for homogenous and heterogenous nucleation mechanisms into the generic phase-field model. During the studies, the Fe-Cr system was chosen as a model system due to its simplicity and availability of reliable thermodynamic and kinetic data, as well as the range of applications of low-chromium ferritic steels in nuclear reactors. For homogenous nucleation, the relevant parameters determined from atomistic studies were used directly to determine the energy functional and parameters in the phase-field model. Interfacial energy, critical nucleus size, nucleation rate, and coarsening kinetics were systematically examined in two- and three- dimensional models. For the heterogeneous nucleation mechanism, we studied the nucleation and growth behavior of chromium precipitates due to the presence of dislocations. The results demonstrate that both nucleation schemes can be introduced to a phase-field modeling algorithm with the desired accuracy and computational efficiency.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Sepsis reconsidered: Identifying novel metrics for behavioral landscape characterization with a high-performance computing implementation of an agent-based model

Objectives: Sepsis affects nearly 1 million people in the United States per year, has a mortality rate of 28–50% and requires more than $20 billion a year in hospital costs. Over a quarter century of research has not yielded a single reliable diagnostic test or a directed therapeutic agent for sepsis. Central to this insufficiency is the fact that sepsis remains a clinical/physiological diagnosis representing a multitude of molecularly heterogeneous pathological trajectories. Advances in computational capabilities offered by High Peformance Computing (HPC) platforms call for an evolution in the investigation of sepsis to attempt to define the boundaries of traditional research (bench, clinical and computational) through the use of computational proxy models. We present a novel investigatory and analytical approach, derived from how HPC resources and simulation are used in the physical sciences, to identify the epistemic boundary con- ditions of the study of clinical sepsis via the use of a proxy agent-based model of systemic inflammation. Design: Current predictive models for sepsis use correlative methods that are limited by patient heterogeneity and data sparseness. We address this issue by using an HPC version of a system-level validated agent-based model of sepsis, the Innate Immune Response ABM (IIRBM), as a proxy system in order to identify boundary conditions for the possible behavioral space for sepsis. We then apply advanced analysis derived from the study of Random Dynamical Systems (RDS) to identify novel means for characterizing system behavior and providing insight into the tractability of traditional investigatory methods. Results: The behavior space of the IIRABM was examined by simulating over 70 million sepsis patients for up to 90 days in a sweep across the following parameters: cardio-respiratory-metabolic resilience; microbial invasiveness; microbial toxigenesis; and degree of nosocomial exposure. In addition to using established methods for describing parameter space, we developed two novel methods for characterizing the behavior of a RDS: Probabilistic Basins of Attraction (PBoA) and Stochastic Trajectory Analysis (STA). Computationally generated behavioral landscapes demonstrated attractor structures around stochastic re- gions of behavior that could be described in a complementary fashion through use of PBoA and STA. The stochasticity of the boundaries of the attractors highlights the challenge for correlative attempts to characterize and classify clinical sepsis. Conclusions: HPC simulations of models like the IIRABM can be used to generate approximations of the behavior space of sepsis to both establish “boundaries of futility” with respect to existing investi- gatory approaches and apply system engineering principles to investigate the general dynamic properties of sepsis to provide a pathway for developing control strategies. Here, the issues that bedevil the study and treatment of sepsis, namely clinical data sparseness and inadequate experimental sampling of system behavior space, are fundamental to nearly all biomedical research, manifesting in the “Crisis of Reproducibility” at all levels. HPC-augmented simulation-based research offers an investigatory strategy more consistent with that seen in the physical sciences (which combine experiment, theory and simulation), and an opportunity to utilize the leading advances in HPC, namely deep machine learning and evolutionary computing, to form the basis of an iterative scientific process to meet the full promise of Precision Medicine (right drug, right patient, right time).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Filters for Improvement of Multiscale Data from Atomistic Simulations

Multiscale computational models strive to produce accurate and efficient numerical simulations of systems involving interactions across multiple spatial and temporal scales that typically differ by several orders of magnitude. Some such models utilize a hybrid continuum-atomistic approach combining continuum approximations with first-principles-based atomistic models to capture multiscale behavior. By following the heterogeneous multiscale method framework for developing multiscale computational models, unknown continuum scale data can be computed from an atomistic model. Concurrently coupling the two models requires performing numerous atomistic simulations which can dominate the computational cost of the method. Furthermore, when the resulting continuum data is noisy due to sampling error, stochasticity in the model, or randomness in the initial conditions, filtering can result in significant accuracy gains in the computed multiscale data without increasing the size or duration of the atomistic simulations. In this work, we demonstrate the effectiveness of spectral filtering for increasing the accuracy of noisy multiscale data obtained from atomistic simulations. Moreover, we present a robust and automatic method for closely approximating the optimum level of filtering in the case of additive white noise. By improving the accuracy of this filtered simulation data, it leads to a dramatic computational savings by allowing for shorter and smaller atomistic simulations to achieve the same desired multiscale simulation precision.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Comparison of Homogeneous and Heterogeneous CFD Fuel Models for Phase I of the IAEA CRP on HTR Uncertainties Benchmark

Computational Fluid Dynamics (CFD) evaluation of homogeneous and heterogeneous fuel models was performed as part of the Phase I calculations of the International Atomic Energy Agency (IAEA) Coordinate Research Program (CRP) on High Temperature Reactor (HTR) Uncertainties in Modeling (UAM). This study was focused on the nominal localized stand-alone fuel thermal response, as defined in Ex. I-3 and I-4 of the HTR UAM. The aim of the stand-alone thermal unit-cell simulation is to isolate the effect of material and boundary input uncertainties on a very simplified problem, before propagation of these uncertainties are performed in subsequent coupled neutronics/thermal fluids phases on the benchmark. In many of the previous studies for high temperature gas cooled reactors, the volume-averaged homogeneous mixture model of a single fuel compact has been applied. In the homogeneous model, the Tristructural Isotropic (TRISO) fuel particles in the fuel compact were not modeled directly and an effective thermal conductivity was employed for the thermo-physical properties of the fuel compact. On the contrary, in the heterogeneous model, the uranium carbide (UCO), inner and outer pyrolytic carbon (IPyC/OPyC) and silicon carbide (SiC) layers of the TRISO fuel particles are explicitly modeled. The fuel compact is modeled as a heterogeneous mixture of TRISO fuel kernels embedded in H-451 matrix graphite. In this study, a steady-state and transient CFD simulations were performed with both homogeneous and heterogeneous models to compare the thermal characteristics. The nominal values of the input parameters are used for this CFD analysis. In a future study, the effects of input uncertainties in the material properties and boundary parameters will be investigated and reported.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

A dosimetric comparison of whole-lung treatment techniques in the pediatric population

To demonstrate the dosimetric advantages and disadvantages of standard anteroposterior-posteroanterior (S-AP/PA{sub AAA}), inverse-planned AP/PA (IP-AP/PA) and volumetry-modulated arc (VMAT) radiotherapies in the treatment of children undergoing whole-lung irradiation. Each technique was evaluated by means of target coverage and normal tissue sparing, including data regarding low doses. A historical approach with and without tissue heterogeneity corrections is also demonstrated. Computed tomography (CT) scans of 10 children scanned from the neck to the reproductive organs were used. For each scan, 6 plans were created: (1) S-AP/PA{sub AAA} using the anisotropic analytical algorithm (AAA), (2) IP-AP/PA, (3) VMAT, (4) S-AP/PA{sub NONE} without heterogeneity corrections, (5) S-AP/PA{sub PB} using the Pencil-Beam algorithm and enforcing monitor units from technique 4, and (6) S-AP/PA{sub AAA[FM]} using AAA and forcing fixed monitor units. The first 3 plans compare modern methods and were evaluated based on target coverage and normal tissue sparing. Body maximum and lower body doses (50% and 30%) were also analyzed. Plans 4 to 6 provide a historic view on the progression of heterogeneity algorithms and elucidate what was actually delivered in the past. Averages of each comparison parameter were calculated for all techniques. The S-AP/PA{sub AAA} technique resulted in superior target coverage but had the highest maximum dose to every normal tissue structure. The IP-AP/PA technique provided the lowest dose to the esophagus, stomach, and lower body doses. VMAT excelled at body maximum dose and maximum doses to the heart, spine, and spleen, but resulted in the highest dose in the 30% body range. It was, however, superior to the S-AP/PA{sub AAA} approach in the 50% range. Each approach has strengths and weaknesses thus associated. Techniques may be selected on a case-by-case basis and by physician preference of target coverage vs normal tissue sparing.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

Histogram Analysis of CT Perfusion of Hepatocellular Carcinoma for Predicting Response to Transarterial Radioembolization: Value of Tumor Heterogeneity Assessment

PurposeTo evaluate in patients with hepatocellular carcinoma (HCC), whether assessment of tumor heterogeneity by histogram analysis of computed tomography (CT) perfusion helps predicting response to transarterial radioembolization (TARE).Materials and MethodsSixteen patients (15 male; mean age 65 years; age range 47–80 years) with HCC underwent CT liver perfusion for treatment planning prior to TARE with Yttrium-90 microspheres. Arterial perfusion (AP) derived from CT perfusion was measured in the entire tumor volume, and heterogeneity was analyzed voxel-wise by histogram analysis. Response to TARE was evaluated on follow-up imaging (median follow-up, 129 days) based on modified Response Evaluation Criteria in Solid Tumors (mRECIST). Results of histogram analysis and mean AP values of the tumor were compared between responders and non-responders. Receiver operating characteristics were calculated to determine the parameters’ ability to discriminate responders from non-responders.ResultsAccording to mRECIST, 8 patients (50 %) were responders and 8 (50 %) non-responders. Comparing responders and non-responders, the 50th and 75th percentile of AP derived from histogram analysis was significantly different [AP 43.8/54.3 vs. 27.6/34.3 mL min{sup −1} 100 mL{sup −1}); p < 0.05], while the mean AP of HCCs (43.5 vs. 27.9 mL min{sup −1} 100 mL{sup −1}; p > 0.05) was not. Further heterogeneity parameters from histogram analysis (skewness, coefficient of variation, and 25th percentile) did not differ between responders and non-responders (p > 0.05). If the cut-off for the 75th percentile was set to an AP of 37.5 mL min{sup −1} 100 mL{sup −1}, therapy response could be predicted with a sensitivity of 88 % (7/8) and specificity of 75 % (6/8).ConclusionVoxel-wise histogram analysis of pretreatment CT perfusion indicating tumor heterogeneity of HCC improves the pretreatment prediction of response to TARE.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Uncertainty analyses of CO2 plume expansion subsequent to wellbore CO2 leakage into aquifers

In this study, we apply an uncertainty quantification (UQ) framework to CO2 sequestration problems. In one scenario, we look at the risk of wellbore leakage of CO2 into a shallow unconfined aquifer in an urban area; in another scenario, we study the effects of reservoir heterogeneity on CO2 migration. We combine various sampling approaches (quasi-Monte Carlo, probabilistic collocation, and adaptive sampling) in order to reduce the number of forward calculations while trying to fully explore the input parameter space and quantify the input uncertainty. The CO2 migration is simulated using the PNNL-developed simulator STOMP-CO2e (the water-salt-CO2 module). For computationally demanding simulations with 3D heterogeneity fields, we combined the framework with a scalable version module, eSTOMP, as the forward modeling simulator. We built response curves and response surfaces of model outputs with respect to input parameters, to look at the individual and combined effects, and identify and rank the significance of the input parameters.

Carbon sequestration, uncertainty quantification, ↗
DOE OSTI2020

Heterogeneous data-processing optimization with CLARA’s adaptive workflow orchestrator

The hardware landscape used in HEP and NP is changing from homogeneous multi-core systems towards heterogeneous systems with many different computing units, each with their own characteristics. To achieve maximum performance with data processing, the main challenge is to place the right computing on the right hardware. In this paper, we discuss CLAS12 charge particle tracking workflow orchestration that allows us to utilize both CPU and GPU to improve the performance. The tracking application algorithm was decomposed into micro-services that are deployed on CPU and GPU processing units, where the best features of both are intelligently combined to achieve maximum performance. In this heterogeneous environment, CLARA aims to match the requirements of each micro-service to the strength of a CPU or a GPU architecture. A predefined execution of a micro-service on a CPU or a GPU may not be the most optimal solution due to the streaming data-quantum size and the data-quantum transfer latency between CPU and GPU. So, the CLARA workflow orchestrator is designed to dynamically assign micro-service execution to a CPU or a GPU, based on the online benchmark results analyzed for a period of real-time data-processing.

Gyurjyan, Vardan↗
DOE OSTI2012

A first-principles theoretical approach to heterogeneous nanocatalysis

A theoretical approach to heterogeneous catalysis by sub-nanometre supported metal clusters and alloys is presented and discussed. Its goal is to perform a computational sampling of the reaction paths in nanocatalysis via a global search in the phase space of structures and stoichiometry combined with filtering which takes into account the given experimental conditions (catalytically relevant temperature and reactant pressure), and corresponds to an incremental exploration of the disconnectivity diagram of the system. The approach is implemented and applied to the study of propylene partial oxidation by Ag3 supported on MgO(100). First-principles density-functional theory calculations coupled with a Reactive Global Optimization algorithm are performed, finding that: (1) the presence of an oxide support drastically changes the potential energy landscape of the system with respect to the gas phase, favoring configurations which interact positively with the electrostatic field generated by the surface; (2) the reaction energy barriers for the various mechanisms are crucial in the competition between thermodynamically and kinetically favored reaction products; (3) a topological database of structures and saddle points is produced which has general validity and can serve for future studies or for deriving general trends; (4) the MgO(100) surface captures some major features of the effect of an oxide support and appears to be a good model of a simple oxide substrate; (5) strong cooperative effects are found in the co-adsorption of O2 and other ligands on small metal clusters. The proposed approach appears as a viable route to advance the role of predictive computational science in the field of heterogeneous nanocatalysis.

Chemistry↗
DOE OSTI2018

Strain heterogeneity in sheared colloids revealed by neutron scattering

Recent computational and theoretical studies have shown that the deformation of colloidal suspensions under a steady shear is highly heterogeneous at the particle level and demonstrate a critical influence on the macroscopic deformation behavior. Despite its relevance to a wide variety of industrial applications of colloidal suspensions, scattering studies focusing on addressing the heterogeneity of the non-equilibrium colloidal structure are scarce thus far. Here in this paper, we report the first experimental result using small-angle neutron scattering. From the evolution of strain heterogeneity, we conclude that the shear-induced deformation transforms from nearly affine behavior at low shear rates, to plastic rearrangements when the shear rate is high.

36 MATERIALS SCIENCE↗
DOE OSTI2015

WE-EF-303-10: Single- Detector Proton Radiography as a Portal Imaging Equivalent for Proton Therapy

Purpose: In proton therapy, patient alignment is of critical importance due to the sensitivity of the proton range to tissue heterogeneities. Traditionally proton radiography is used for verification of the water-equivalent path length (WEPL), which dictates the depth protons reach. In this work we propose its use for alignment. Additionally, many new proton centers have cone-beam computed tomography in place of beamline X-ray imaging and so proton radiography offers a unique patient alignment verification similar to portal imaging in photon therapy. Method: Proton radiographs of a CIRS head phantom were acquired using the Beam Imaging System (BIS) (IBA, Louvain-la-Neuve) in a horizontal beamline. A scattered beam was produced using a small, dedicated, range modulator (RM) wheel fabricated out of aluminum. The RM wheel was rotated slowly (20 sec/rev) using a stepper motor to compensate for the frame rate of the BIS (120 ms). Dose rate functions (DRFs) over two RM wheel rotations were acquired. Calibration was made with known thicknesses of homogeneous solid water. For each pixel the time width, skewness and kurtosis of the DRFs were computed. The time width was used to compute the object WEPL. In the heterogeneous phantom, the excess skewness and excess kurtosis (i.e. difference from homogeneous cases) were computed and assessed for suitability for patient set up. Results: The technique allowed for the simultaneous production of images that can be used for WEPL verification, showing few internal details, and excess skewness and kurtosis images that can be used for soft tissue alignment. These latter images highlight areas where range mixing has occurred, correlating with phantom heterogeneities. Conclusion: The excess skewness and kurtosis images contain details that are not visible in the WET images. These images, unique to the time-resolved proton radiographic method, could be used for patient set up according to soft tissues.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Recovering the effects of subgrid heterogeneity in simulations of radionuclide transport through fractured media

Groundwater flow and contaminant transport through fractured media can be simulated using Discrete Fracture Network (DFN) models which provide a natural description of structural heterogeneity. However, this approach is computationally expensive, with the large number of intersecting fractures necessitated by many real-world applications requiring modeling simplifications to be made for calculations to be tractable. Upscaling methods commonly used for this purpose can result in some loss of local-scale variability in the groundwater flow velocity field, resulting in underestimation of particle travel times, transport resistance and retention in transport calculations. In this paper, a transport downscaling algorithm to recover the transport effects of heterogeneity is tested on a synthetic Brittle Fault Zone model, motivated by the problem of large safety assessment calculations for geological repositories of spent nuclear fuel. We show that the variability in the local-scale velocity field which is lost by upscaling can be recovered by sampling from a library of DFN transport paths, accurately reproducing DFN transport statistic distributions and radionuclide breakthrough curves in an upscaled model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

The research on meta-job scheduling heuristics in heterogeneous environments

As the core of rational utilization of computing resources, the scheduling algorithm has gained the interest of many researchers. Aimed at meta-job scheduling in heterogeneous environments, this paper puts forward three algorithms: the meta-job scheduling algorithm based on deviation (MaxD-min heuristic), the meta-job scheduling algorithm based on relative deviation (MaxRD-min heuristic), and the Cordwood algorithm (CA). The former two Algorithm are improvements of the classic Min-min algorithm. The latter CA algorithm is a new method that tries to place each building block on the tray with minimal amount of Sufferage. In conclusion, the result of experimenting shows that the three algorithms, in comparison to Min-Min and Max-Min algorithm, can effectively reduce the total span of scheduling (makespan).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

SU-E-J-128: Two-Stage Atlas Selection in Multi-Atlas-Based Image Segmentation

Purpose: In the new era of big data, multi-atlas-based image segmentation is challenged by heterogeneous atlas quality and high computation burden from extensive atlas collection, demanding efficient identification of the most relevant atlases. This study aims to develop a two-stage atlas selection scheme to achieve computational economy with performance guarantee. Methods: We develop a low-cost fusion set selection scheme by introducing a preliminary selection to trim full atlas collection into an augmented subset, alleviating the need for extensive full-fledged registrations. More specifically, fusion set selection is performed in two successive steps: preliminary selection and refinement. An augmented subset is first roughly selected from the whole atlas collection with a simple registration scheme and the corresponding preliminary relevance metric; the augmented subset is further refined into the desired fusion set size, using full-fledged registration and the associated relevance metric. The main novelty of this work is the introduction of an inference model to relate the preliminary and refined relevance metrics, based on which the augmented subset size is rigorously derived to ensure the desired atlases survive the preliminary selection with high probability. Results: The performance and complexity of the proposed two-stage atlas selection method were assessed using a collection of 30 prostate MR images. It achieved comparable segmentation accuracy as the conventional one-stage method with full-fledged registration, but significantly reduced computation time to 1/3 (from 30.82 to 11.04 min per segmentation). Compared with alternative one-stage cost-saving approach, the proposed scheme yielded superior performance with mean and medium DSC of (0.83, 0.85) compared to (0.74, 0.78). Conclusion: This work has developed a model-guided two-stage atlas selection scheme to achieve significant cost reduction while guaranteeing high segmentation accuracy. The benefit in both complexity and performance is expected to be most pronounced with large-scale heterogeneous data.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

MatRIS: Addressing the Challenges for Portability and Heterogeneity Using Tasking for Matrix Decomposition (Cholesky)

The ubiquitous in-node heterogeneity of HPC and cloud computing platforms makes software portability and performance optimization extremely challenging. Described here, the MatRIS multilevel math library abstraction framework employs tasking to alleviate these difficulties. MatRIS includes the IRIS task-based runtime on the bottom level and exposes different layers of abstraction to render algorithms architecturally agnostic. MatRIS ensures the decomposition and creation of tasks that represent the necessary encapsulation of the optimized kernels from both vendor and open-source math libraries. Once built, MatRIS can select different combinations of accelerators at runtime, making it portable even on diverse heterogeneous architectures. By leveraging the IRIS runtime’s features for managing heterogeneity, MatRIS deploys algorithms that remove the need to specify orchestration and data transfer. This study describes how the serial task abstraction of a tiled Cholesky factorization is made portable and scalable in the case of multi-device and multi-vendor heterogeneity on a node with NVIDIA and AMD GPUs by using MatRIS. First, we demonstrate that Cholesky in MatRIS provides multi-GPU scalability that offers competitive performance versus cuSolverMG. Then, we present the challenges and opportunities for heterogeneous execution.

Monil, M. A. H.↗
DOE OSTI2018

An approach to quantum-computational hydrologic inverse analysis

Making predictions about flow and transport in an aquifer requires knowledge of the heterogeneous properties of the aquifer such as permeability. Computational methods for inverse analysis are commonly used to infer these properties from quantities that are more readily observable such as hydraulic head. We present a method for computational inverse analysis that utilizes a type of quantum computer called a quantum annealer. While quantum computing is in an early stage compared to classical computing, we demonstrate that it is sufficiently developed that it can be used to solve certain subsurface flow problems. We utilize a D-Wave 2X quantum annealer to solve 1D and 2D hydrologic inverse problems that, while small by modern standards, are similar in size and sometimes larger than hydrologic inverse problems that were solved with early classical computers. Our results and the rapid progress being made with quantum computing hardware indicate that the era of quantum-computational hydrology may not be too far in the future.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Pre-exascale accelerated application development: The ORNL Summit experience

High-performance computing (HPC) increasingly relies on heterogeneous architectures to achieve higher performance. In the Oak Ridge Leadership Facility (OLCF), Oak Ridge, TN, USA, this trend continues as its latest supercomputer, Summit, entered production in early 2019. The combination of IBM POWER9 CPU and NVIDIA V100 GPU, along with a fast NVLink2 interconnect and other latest technologies, pushes system performance to a new height and breaks the exascale barrier by certain measures. Due to Summit's powerful GPUs and much higher GPU–CPU ratio, offloading to accelerators becomes a requirement for any application, which intends to effectively use the system. To facilitate navigating a complex landscape of competing heterogeneous architectures, a collection of applications from a wide spectrum of scientific domains is selected for early adoption on Summit. In this article, the experience and lessons learned are summarized, in the hope of providing useful guidance to address new programming challenges, such as scalability, performance portability, and software maintainability, for future application development efforts on heterogeneous HPC systems.

97 MATHEMATICS AND COMPUTING↗