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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

An ab initio electronic transport database for inorganic materials

Electronic transport in materials is governed by a series of tensorial properties such as conductivity, Seebeck coefficient, and effective mass. These quantities are paramount to the understanding of materials in many fields from thermoelectrics to electronics and photovoltaics. Transport properties can be calculated from a material’s band structure using the Boltzmann transport theory framework. We present here the largest computational database of electronic transport properties based on a large set of 48,000 materials originating from the Materials Project database. Our results were obtained through the interpolation approach developed in the BoltzTraP software, assuming a constant relaxation time. We present the workflow to generate the data, the data validation procedure, and the database structure. In conclusion, our aim is to target the large community of scientists developing materials selection strategies and performing studies involving transport properties.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Procedure of recovery of pin-by-pin fields of energy release in the core of VVER-type reactor for the BIPR-8 code

The procedure of recovery of pin-by-pin energy-release fields for the BIPR-8 code and the algorithm of the BIPR-8 code which is used in nodal computation of the reactor core and on which the recovery of pin-by-pin fields of energy release is based are briefly described. The description and results of the verification using the module of recovery of pin-by-pin energy-release fields and the TVS-M program are given.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Enabling Highly Efficient Capsule Networks Processing Through A PIM-Based Architecture Design

In recent years, the CNNs have achieved great successes in the image processing tasks, e.g., image recognition and object detection. Unfortunately, traditional CNN's classication is found to be easily misled by increasingly complex image features due to the usage of pooling operations, hence unable to preserve accurate position and pose information of the objects. To address this challenge, a novel neural network structure called Capsule Network has been proposed, which introduces equivariance through capsules to signicantly enhance the learning ability for image segmentation and object detection. Due to its requirement of performing a high volume of matrix operations, CapsNets have been generally accelerated on modern GPU platforms that provide highly optimized software library for common deep learning tasks. However, based on our performance characterization on modern GPUs, CapsNets exhibit low effciency due to the special program and execution features of their routing procedure, including massive unshareable intermediate variables and intensive syn- chronizations, which are very dicult to optimize at software level. To address these challenges, we propose a hybrid computing architecture design named PIM-CapsNet. It preserves GPU's on-chip computing capability for accelerating CNN types of layers in CapsNet, while pipelining with an off-chip in-memory acceleration solution that effectively tackles routing procedure's ineffciency by leveraging the processing-in-memory capability of today's 3D stacked memory. Using routing procedure's inherent parallellization feature, our design enables hierarchical improvements on CapsNet inference effciency through minimizing data movement and maximizing parallel processing in memory. Evaluation results demonstrate that our proposed design can achieve substantial improvement on both performance and energy savings for CapsNet inference, with almost zero accuracy loss. The results also suggest good performance scalability in optimizing the routing procedure with increasing network size.

Zhang, Xingyao↗
DOE OSTI2021

Domain knowledge-informed, process-mapping AI graph for designing Fe-based alloys

<span style="font-family: Calibri, sans-serif; font-size: 12pt;">Continuous improvement in efficiency of a power plant relies on designing materials for use at increasingly higher temperature and/or pressure, for 100,000s hours of operation. Due to complexity, non-linearity and high-dimensionality of the problem, traditional Machine Learning (ML) approaches require unreasonably large datasets for the data-driven model development. Science-based material and process engineering complements hard data with, sometimes soft and intuitive, empirical domain knowledge. Artificial Intelligence (AI) was used in this study to incorporate such knowledge into computational graph architecture (process-mimicking artificial neuron design, causal layer and graph structures, ensemble modeling of latent states) and learning procedures (variable transformation, fuzzy physics pre-training and freezing of deep layers, virtual microstructure representation, and adversarial multi-objective optimization). The first alloys design pathways suggested by the AI tool (pyroMind) passed a preliminary engineering review on soundness and transparency.</span>

Romanov, Vyacheslav↗
DOE OSTI2018

Real-time data analysis for medical diagnosis using FPGA-accelerated neural networks

Real-time analysis of patient data during medical procedures can provide vital diagnostic feedback that significantly improves chances of success. With sensors becoming increasingly fast, frameworks such as Deep Neural Networks are required to perform calculations within the strict timing constraints for real-time operation. However, traditional computing platforms responsible for running these algorithms incur a large overhead due to communication protocols, memory accesses, and static (often generic) architectures. In this work, we implement a low-latency Multi-Layer Perceptron (MLP) processor using Field Programmable Gate Arrays (FPGAs). Unlike CPUs and Graphics Processing Units (GPUs), our FPGA-based design can directly interface sensors, storage devices, display devices and even actuators, thus reducing the delays of data movement between ports and compute pipelines. Moreover, the compute pipelines themselves are tailored specifically to the application, improving resource utilization and reducing idle cycles. We demonstrate the effectiveness of our approach using mass-spectrometry data sets for real-time cancer detection. We demonstrate that correct parameter sizing, based on the application, can reduce latency by 20% on average. Furthermore, we show that in an application with tightly coupled data-path and latency constraints, having a large amount of computing resources can actually reduce performance. Using mass-spectrometry benchmarks, we show that our proposed FPGA design outperforms both CPU and GPU implementations, with an average speedup of 144x and 21x, respectively. In our work, we demonstrate the importance of application-specific optimizations in order to minimize latency and maximize resource utilization for MLP inference. By directly interfacing and processing sensor data with ultra-low latency, FPGAs can perform real-time analysis during procedures and provide diagnostic feedback that can be critical to achieving higher percentages of successful patient outcomes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Fast Hyperspectral Neutron Tomography

Hyperspectral neutron computed tomography is a tomographic imaging technique in which thousands of wavelength-specific neutron radiographs are measured for each tomographic view. In conventional hyperspectral reconstruction, data from each neutron wavelength bin are reconstructed separately, which is extremely time-consuming. These reconstructions often suffer from poor quality due to low signal-to-noise ratios. Consequently, material decomposition based on these reconstructions tends to produce inaccurate estimates of the material spectra and erroneous volumetric material separation. In this paper, we present two novel algorithms for processing hyperspectral neutron data: fast hyperspectral reconstruction and fast material decomposition. Both algorithms rely on a subspace decomposition procedure that transforms hyperspectral views into low-dimensional projection views within an intermediate subspace, where tomographic reconstruction is performed. The use of subspace decomposition dramatically reduces reconstruction time while reducing both noise and reconstruction artifacts. We apply our algorithms to both simulated and measured neutron data and demonstrate that they reduce computation and improve the quality of the results relative to conventional methods.

Chowdhury, Mohammad Samin Nur [Purdue University]↗
DOE OSTI2015

Computationally-efficient stochastic cluster dynamics method for modeling damage accumulation in irradiated materials

An improved version of a recently developed stochastic cluster dynamics (SCD) method (Marian and Bulatov, 2012) [6] is introduced as an alternative to rate theory (RT) methods for solving coupled ordinary differential equation (ODE) systems for irradiation damage simulations. SCD circumvents by design the curse of dimensionality of the variable space that renders traditional ODE-based RT approaches inefficient when handling complex defect population comprised of multiple (more than two) defect species. Several improvements introduced here enable efficient and accurate simulations of irradiated materials up to realistic (high) damage doses characteristic of next-generation nuclear systems. The first improvement is a procedure for efficiently updating the defect reaction-network and event selection in the context of a dynamically expanding reaction-network. Next is a novel implementation of the τ-leaping method that speeds up SCD simulations by advancing the state of the reaction network in large time increments when appropriate. Lastly, a volume rescaling procedure is introduced to control the computational complexity of the expanding reaction-network through occasional reductions of the defect population while maintaining accurate statistics. The enhanced SCD method is then applied to model defect cluster accumulation in iron thin films subjected to triple ion-beam (Fe{sup 3+}, He{sup +} and H{sup +}) irradiations, for which standard RT or spatially-resolved kinetic Monte Carlo simulations are prohibitively expensive.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Digestive Tract Complications of Renal Cryoablation

We report a case each of duodenorenal and colorenal fistula that arose after computed tomography-guided percutaneous cryoablation (PCA) for renal cell carcinoma and use imaging and endoscopic findings to analyze their causes and mechanisms. Both complications occurred though the edge of the iceball did not touch the intestinal wall, and patients’ symptoms and fistula formation occurred several days after the PCA procedure. Based on imaging and endoscopy findings, we suspected the colorenal fistula resulted from bowel injury caused by ischemia from the occlusion of small vessels at the procedure’s low temperature. Both cases were resolved conservatively without surgical intervention.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

A fast band–Krylov eigensolver for macromolecular functional motion simulation on multicore architectures and graphics processors

We introduce a new iterative Krylov subspace-based eigensolver for the simulation of macromolecular motions on desktop multithreaded platforms equipped with multicore processors and, possibly, a graphics accelerator (GPU). The method consists of two stages, with the original problem first reduced into a simpler band-structured form by means of a high-performance compute-intensive procedure. This is followed by a memory-intensive but low-cost Krylov iteration, which is off-loaded to be computed on the GPU by means of an efficient data-parallel kernel. The experimental results reveal the performance of the new eigensolver. Concretely, when applied to the simulation of macromolecules with a few thousands degrees of freedom and the number of eigenpairs to be computed is small to moderate, the new solver outperforms other methods implemented as part of high-performance numerical linear algebra packages for multithreaded architectures.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Efficient antisymmetrization algorithm for the partially correlated wave functions in the free complement-local Schrödinger equation method

We propose here fast antisymmetrization procedures for the partially correlated wave functions that appear in the free complement-local Schrödinger equation (FC-LSE) method. Pre-analysis of the correlation diagram, referred to as dot analysis, combined with the determinant update technique based on the Laplace expansion, drastically reduces the orders of the antisymmetrization computations. When the complement functions include only up to single-correlated terms, the order of computations is O(N{sup 3}), which is the same as the non-correlated case. Similar acceleration is obtained for general correlated functions as a result of dot analysis. This algorithm has been successfully used in our laboratory in actual FC-LSE calculations for accurately solving the many-electron Schrödinger equations of atoms and molecules. The proposed method is general and applicable to the sampling-type methodology of other partially correlated wave functions like those in the quantum Monte Carlo and modern Hylleraas-type methods.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Data-driven modeling and control of dynamical systems using Koopman and Perron-Frobenius operators

This dissertation studies the data-driven modeling and control problem of nonlinear systems by exploiting the linear operator theoretic framework involving Koopman and Perro-Frobenius operator. A systematic linear-operator based controller design procedure has been established, which can be used to solve a variety of nonlinear control problems, including feedback stabilization using control Lyapunov functions, optimal quadratic regulation using Koopman eigenfunctions and convex optimization formulation of optimal control problem using P-F and Koopman operator approximation. As the core of data-driven modeling, we first propose a new algorithm for the finite-dimensional approximation of the linear transfer Koopman and Perron-Frobenius operator from time-series data. We argue that the existing approach for the finite-dimensional approximation of these transfer operators such as Dynamic Mode Decomposition (DMD) and Extended Dynamic Mode Decomposition (EDMD) do not capture two important properties of these operators, namely positivity and Markov property. The algorithm we propose preserves these two properties. We call the proposed algorithm as naturally structured DMD (NSDMD) since it retains the inherent properties of these operators. Naturally structured DMD algorithm leads to a better approximation of the steady-state dynamics of the system regarding computing Koopman and Perron- Frobenius operator eigenfunctions and eigenvalues. However, preserving positivity property is critical for capturing the real transient dynamics of the system. This positivity property of the transfer operators and it's finite-dimensional approximation play an important role for controller and estimator design of nonlinear systems. To solve the feedback stabilization problem for nonlinear control systems, we tried to take advantage of the Koopman operator framework. The Koopman operator approach provides a linear representation for a nonlinear dynamical system and a bilinear representation for a nonlinear control system. The problem of feedback stabilization of a nonlinear control system is then transformed to the stabilization of a bilinear control system. We propose a control Lyapunov function (CLF)-based approach for the design of stabilizing feedback controllers for the bilinear system. The search for finding a CLF for the bilinear control system is formulated as a convex optimization problem. This leads to a schematic procedure for designing CLF-based stabilizing feedback controllers for the bilinear system and hence the original nonlinear system. Another advantage of the proposed controller design approach outlined in this dissertation is that it does not require explicit knowledge of system dynamics. In particular, the bilinear representation of a nonlinear control system in the Koopman eigenfunction space can be obtained from time-series data. Next, we study the optimal quadratic regulation problem for nonlinear systems. The linear operator theoretic framework involving the Koopman operator is used to lift the dynamics of nonlinear control system to an infinite-dimensional bilinear system. The optimal quadratic regulation problem for nonlinear system is formulated in terms of the finite-dimensional approximation of the bilinear system. A convex optimization-based approach is proposed for solving the quadratic regulator problem for bilinear system. We applied a variety of examples and compared the simulation results between our framework and conventional LQR control using linearized model. For more general optimal control problems, we provide a density-function based convex formulation for the optimal control problem of the nonlinear system. The convex formulation relies on the duality result in the stability theory of a dynamical system involving density function and Perron-Frobenius operator. The optimal control problem is formulated as an infinite-dimensional convex optimization program. The finite-dimensional approximation of the optimization problem relies on the recent advances made in the data-driven computation of the Koopman operator, which is dual to the Perron-Frobenius operator. Simulation results are presented to demonstrate the application of the developed framework.

Huang, Bowen↗
DOE OSTI2017

Navier–Stokes Characteristic Boundary Conditions Using Ghost Cells

Solution methods for the compressible Navier–Stokes equations based on finite volume discretizations often implement boundary conditions using ghost cells outside of the computational domain. Filling the ghost cells using straightforward zeroth-or first-order extrapolation, although computationally expedient, is well known to fail even for some simple flows, especially when turbulent structures interact with the boundaries or if time-varying inflow conditions are imposed. The Navier–Stokes characteristic boundary condition approach provides more accurate boundary conditions, but requires the use of special discretizations at boundaries. The present paper develops a new technique based on the Navier–Stokes characteristic boundary condition approach to derive values for ghost cells that significantly improve the treatment of boundaries over simple extrapolation, but retain the ghost cell approach. Furthermore, it is demonstrated in the context of a Godunov integration procedure that the new method provides accurate results, while allowing the use of the same stencil and numerical methodology near the boundaries as in the interior.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

A Homotopy-Based Method for Robust Computation of Controlling Unstable Equilibrium Points

This paper proposes a homotopy-based method for efficiently computing and precisely determining controlling unstable equilibrium points (CUEPs) in transient stability analysis and screening using direct methods. The proposed method is intended to overcome potential numerical convergence problems associated with computing CUEPs. These convergence problems are mostly due to irregularities in the region of convergence of CUEPs which make it difficult to determine suitable initial points. The most commonly used initial points in computing CUEPs are minimum gradient points (MGPs) on the stability boundary which in turn rely on the determination of exit points (EPs-points at which sustained-fault trajectories exit system stability boundaries). However, determination of MGPs and EPs are computationally involved and sophisticated numerical methods have been introduced such as stability-boundary-following procedure and shadowing method to correct the solution trajectory. The proposed method does not depend on MGPs and also does not require accurate EPs. The proposed method maps the solution from EPs to the CUEPs. The proposed method is applied on several known systems including the NE 39 bus system and the reduced WECC system and the results are provided. The results are compared with the traditional methods such as Boundary of stability region based CUEP method (BCU method).

42 ENGINEERING↗
DOE OSTI2015

The Use of ExoSeal Vascular Closure Device for Direct Antegrade Superficial Femoral Artery Puncture Site Hemostasis

PurposeThis study was designed to assess the efficacy and safety of the ExoSeal vascular closure device (VCD) to achieve hemostasis in antegrade access of the superficial femoral artery (SFA).MethodsWe retrospectively reviewed the outcome of ExoSeal VCD used for hemostasis in 110 accesses to the SFA in 93 patients between July 2011 and July 2013. All patients had patent proximal SFA based on computer tomography angiography or ultrasound duplex. Arterial calcifications at puncture site were graded using fluoroscopy. The SFA was accessed in an antegrade fashion with ultrasound or fluoroscopic guidance. In all patients, 5–7F vascular sheaths were used. The ExoSeal VCD was applied to achieve hemostasis at the end of the procedure. All patients were clinically examined and had ultrasound duplex exam for any puncture site complications during the 24 h postprocedure.ResultsIn all procedures, the ExoSeal was applied successfully. We did not encounter any device-related technical failure. There were four major complications in four patients (3.6 %): three pseudoaneurysms, which were treated with direct thrombin injection, and one hematoma, which necessitated transfusion of two blood units. All patients with complications were treated with anticoagulation preprocedure or received thrombolytic therapy.ConclusionsThe ExoSeal VCD can be safely used for antegrade puncture of the SFA, with a high procedural success rate (100 %) and a low rate of access site complications (3.6 %)

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Comparing Effective Doses During Image-Guided Core Needle Biopsies with Computed Tomography Versus C-Arm Cone Beam CT Using Adult and Pediatric Phantoms

PurposeTo compare the effective doses of needle biopsies based on dose measurements and simulations using adult and pediatric phantoms, between cone beam c-arm CT (CBCT) and CT.MethodEffective doses were calculated and compared based on measurements and Monte Carlo simulations of CT- and CBCT-guided biopsy procedures of the lungs, liver, and kidney using pediatric and adult phantoms.ResultsThe effective doses for pediatric and adult phantoms, using our standard protocols for upper, middle and lower lungs, liver, and kidney biopsies, were significantly lower under CBCT guidance than CT. The average effective dose for a 5-year old for these five biopsies was 0.36 ± 0.05 mSv with the standard CBCT exposure protocols and 2.13 ± 0.26 mSv with CT. The adult average effective dose for the five biopsies was 1.63 ± 0.22 mSv with the standard CBCT protocols and 8.22 ± 1.02 mSv using CT. The CT effective dose was higher than CBCT protocols for child and adult phantoms by 803 and 590 % for upper lung, 639 and 525 % for mid-lung, and 461 and 251 % for lower lung, respectively. Similarly, the effective dose was higher by 691 and 762 % for liver and 513 and 608 % for kidney biopsies.ConclusionsBased on measurements and simulations with pediatric and adult phantoms, radiation effective doses during image-guided needle biopsies of the lung, liver, and kidney are significantly lower with CBCT than with CT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Simulation of radiation damping in rings, using stepwise ray-tracing methods

The ray-tracing code Zgoubi computes particle trajectories in arbitrary magnetic and/or electric field maps or analytical field models. It includes a built-in fitting procedure, spin tracking many Monte Carlo processes. The accuracy of the integration method makes it an efficient tool for multi-turn tracking in periodic machines. Energy loss by synchrotron radiation, based on Monte Carlo techniques, had been introduced in Zgoubi in the early 2000s for studies regarding the linear collider beam delivery system. However, only recently has this Monte Carlo tool been used for systematic beam dynamics and spin diffusion studies in rings, including eRHIC electron-ion collider project at the Brookhaven National Laboratory. Some beam dynamics aspects of this recent use of Zgoubi capabilities, including considerations of accuracy as well as further benchmarking in the presence of synchrotron radiation in rings, are reported here.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Free Energies of Hydrated Halide Anions: High Through-Put Computations on Clusters to Treat Rough Energy-Landscapes

With a longer-term goal of addressing the comparative behavior of the aqueous halides F−, Cl−, Br−, and I− on the basis of quasi-chemical theory (QCT), here we study structures and free energies of hydration clusters for those anions. We confirm that energetically optimal (H2O)nX clusters, with X = Cl−, Br−, and I−, exhibit surface hydration structures. Computed free energies, based on optimized surface hydration structures utilizing a harmonic approximation, typically (but not always) disagree with experimental free energies. To remedy the harmonic approximation, we utilize single-point electronic structure calculations on cluster geometries sampled from an AIMD (ab initio molecular dynamics) simulation stream. This rough-landscape procedure is broadly satisfactory and suggests unfavorable ligand crowding as the physical effect addressed. Nevertheless, this procedure can break down when n≳4, with the characteristic discrepancy resulting from a relaxed definition of clustering in the identification of (H2O)nX clusters, including ramified structures natural in physical cluster theories. With ramified structures, the central equation for the present rough-landscape approach can acquire some inconsistency. Extension of these physical cluster theories in the direction of QCT should remedy that issue, and should be the next step in this research direction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

The effect of support functions in a computerized procedure system on interface management tasks - 235

By adapting digital and computer technology, the design of main control rooms (MCR) in nuclear power plants has been changed. When operators operate a nuclear power plant, the tasks using soft controls in advanced MCRs include primary tasks and secondary tasks. Primary tasks are to control nuclear power plant devices and secondary tasks are to find appropriate screens or devices by screen navigations and selections before performing the primary task. The secondary task including interface management tasks is newly introduced in advanced MCRs. In this paper, the tasks are analyzed based on the simulation data of APR1400 which is one of the digitalized nuclear power plants. For analyzing tasks, the unit tasks are divided into three types: navigation, manipulation, and acknowledgement. The primary task represents the manipulation of devices and the secondary task indicates the navigating screens, opening control panels, closing control panels, and confirming the acknowledging alarms. To analyze the effect of support functions of a computerized procedure system (CPS), one of the functions which is expected to have a significant effect on the secondary tasks was considered, that is 'related screen link button.' Two factors, 'ratio of screen alteration' and 'ratio of using screen link button', were used to see the effect of 'related screen link button'. From the task analysis result, it was observed that the secondary tasks which is one of the unique features in advanced MCRs have a quite much portion than that of the primary tasks. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗