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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Scheduling message processing for reducing rollback propagation

Traditional checkpointing and rollback recovery techniques for parallel systems have typically assumed the communication pattern is specified by program behavior. In this paper we exploit the property that the communication pattern can often be changed at run-time without affecting program correctness. A scheduling algorithm for message processing and its implementation for reducing rollback propagation are described. The algorithm incorporates a user-transparent prioritized scheme based upon the run-time communication and checkpointing history. Communication trace-driven simulation for several parallel programs written in the Chare Kernel language demonstrates that the probability of rollback propagation can be reduced at the cost of slight additional performance degradation.

Wang, Yi-Min↗
NASA NTRS2023

Comparison of Clouds and Cloud Feedback between AMIP5 and AMIP6

We examine the changes in clouds and cloud feedback between Phase 5 (AMIP5) and Phase 6 (AMIP6) of the Atmospheric Model Intercomparison Project. Each model is perturbed by uniformly increasing the sea surface temperature by 4 K. The simulated cloud fraction, the perturbed states and cloud radiative kernels are used to derive cloud feedback in the shortwave (SW), longwave (LW) and their sum (Net). Compared to AMIP5, the cloud fraction in AMIP6 increases by 9.1%, while the perturbation leads to a 0.25% decrease. The Net cloud feedback at the top of the atmosphere (TOA) is almost double (174%). Statistical tests support that this change is mainly due to an increase in the surface SW cloud feedback caused by optically thick, middle and low clouds. The contribution of the atmospheric Net component (12%) stems from the increase in the atmospheric LW cloud feedback, likely to play a role in weakening (strengthening) the northward (southward) meridional atmospheric energy transport, while the opposite is true for the surface LW and Net cloud feedback in the meridional oceanic energy transport. The substantial increase in cloud feedback at the TOA primarily contributes to the higher climate sensitivity. The cloud feedback spread in AMIP6 is comparable to that in AMIP5.

Clouds↗
DOE OSTI2016

Modeling thermochemistry of fuel and coupling to fuel performance codes

A thermochemical library, Thermochimica, utilizes new algorithms and solvers designed for calculating equilibria of multicomponent and multiphase systems and has been coupled to the nuclear fuel performance code BISON. Thermochimica utilizes a generalized thermochemical database for urania-based fuels that has been under development for a number of years and continues to be expanded. One of the key motivations for use of thermodynamic models is that they can better represent the physics of oxygen migration. The coupling of the BISON code with Thermochimica and examples of its use in representing fuel phenomena are described. In the current implementation in BISON, fluxes are driven by the elemental concentration gradient. However, equilibrium is characterized by the absence of spatial variations of chemical potentials of the system species/components. The driving force to equilibrium (species flux) is proportional to the deviation from equilibrium, i.e., the gradient in chemical potential. It is therefore necessary to integrate chemical potential driven diffusion in the BISON representation of oxygen transport. The diffusion kernels based on thermodynamic models have been developed to simulate multicomponent transport in light water reactor (LWR) materials. The Thermochimica library was used to calculate various thermodynamics properties needed for transport calculations. The library also can calculate properties that are specific to various transport mechanisms for different fuel materials. For example, it can calculate defect site fractions among the sublattices in oxide fuels as a function of temperature, burnup, and stoichiometry. The transport and thermodynamic models are being integrated with other simulation efforts such as calculation of mobility functions that couple fluxes and chemical gradients. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Exponential concentration in quantum kernel methods

Kernel methods in Quantum Machine Learning (QML) have recently gained significant attention as a potential candidate for achieving a quantum advantage in data analysis. Among other attractive properties, when training a kernel-based model one is guaranteed to find the optimal model’s parameters due to the convexity of the training landscape. However, this is based on the assumption that the quantum kernel can be efficiently obtained from quantum hardware. In this work we study the performance of quantum kernel models from the perspective of the resources needed to accurately estimate kernel values. We show that, under certain conditions, values of quantum kernels over different input data can be exponentially concentrated (in the number of qubits) towards some fixed value. Thus on training with a polynomial number of measurements, one ends up with a trivial model where the predictions on unseen inputs are independent of the input data. We identify four sources that can lead to concentration including expressivity of data embedding, global measurements, entanglement and noise. For each source, an associated concentration bound of quantum kernels is analytically derived. Lastly, we show that when dealing with classical data, training a parametrized data embedding with a kernel alignment method is also susceptible to exponential concentration. Our results are verified through numerical simulations for several QML tasks. Altogether, we provide guidelines indicating that certain features should be avoided to ensure the efficient evaluation of quantum kernels and so the performance of quantum kernel methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Ab initio generalized Langevin equation

We introduce a machine learning–based approach called ab initio generalized Langevin equation (AIGLE) to model the dynamics of slow collective variables (CVs) in materials and molecules. In this scheme, the parameters are learned from atomistic simulations based on ab initio quantum mechanical models. Force field, memory kernel, and noise generator are constructed in the context of the Mori–Zwanzig formalism, under the constraint of the fluctuation–dissipation theorem. Combined with deep potential molecular dynamics and electronic density functional theory, this approach opens the way to multiscale modeling in a variety of situations. Here, we demonstrate this capability with a study of two mesoscale processes in crystalline lead titanate, namely the field-driven dynamics of a planar ferroelectric domain wall, and the dynamics of an extensive lattice of coarse-grained electric dipoles. In the first case, AIGLE extends the reach of ab initio simulations to a regime of noise-driven motions not accessible to molecular dynamics. In the second case, AIGLE deals with an extensive set of CVs by adopting a local approximation for the memory kernel and retaining only short-range noise correlations. The scheme is computationally more efficient than molecular dynamics by several orders of magnitude and mimics the microscopic dynamics at low frequencies where it reproduces accurately the dominant far-infrared absorption frequency.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

SU-E-T-104: An Examination of Dose in the Buildup and Build-Down Regions

Purpose: To examine dose in the buildup and build-down regions and compare measurements made with various models and dosimeters Methods: Dose was examined in a 30×30cm {sup 2} phantom of water-equivalent plastic with 10cm of backscatter for various field sizes. Examination was performed with radiochromic film and optically-stimulated-luminescent-dosimeter (OSLD) chips, and compared against a plane-parallel chamber with a correction factor applied to approximate the response of an extrapolation chamber. For the build-down region, a correction factor to account for table absorption and chamber orientation in the posterior-anterior direction was applied. The measurement depths used for the film were halfway through their sensitive volumes, and a polynomial best fit curve was used to determine the dose to their surfaces. This chamber was also compared with the dose expected in a clinical kernel-based computer model, and a clinical Boltzmann-transport-equation-based (BTE) computer model. The two models were also compared against each other for cases with air gaps in the buildup region. Results: Within 3mm, all dosimeters and models agreed with the chamber within 10% for all field sizes. At the entrance surface, film differed in comparison with the chamber from +90% to +15%, the BTE-model by +140 to +3%, and the kernel-based model by +20% to −25%, decreasing with increasing field size. At the exit surface, film differed in comparison with the chamber from −10% to −15%, the BTE-model by −53% to −50%, the kernel-based model by −55% to −57%, mostly independent of field size. Conclusion: The largest differences compared with the chamber were found at the surface for all field sizes. Differences decreased with increasing field size and increasing depth in phantom. Air gaps in the buildup region cause dose buildup to occur again post-gap, but the effect decreases with increasing phantom thickness prior to the gap.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-I-43: A Software-Based Statistical Method to Compute Low Contrast Detectability in Computed Tomography Images

Purpose: The low contrast detectability (LCD) of a CT scanner is its ability to detect and display faint lesions. The current approach to quantify LCD is achieved using vendor-specific methods and phantoms, typically by subjectively observing the smallest size object at a contrast level above phantom background. However, this approach does not yield clinically applicable values for LCD. The current study proposes a statistical LCD metric using software tools to not only to assess scanner performance, but also to quantify the key factors affecting LCD. This approach was developed using uniform QC phantoms, and its applicability was then extended under simulated clinical conditions. Methods: MATLAB software was developed to compute LCD using a uniform image of a QC phantom. For a given virtual object size, the software randomly samples the image within a selected area, and uses statistical analysis based on Student’s t-distribution to compute the LCD as the minimal Hounsfield Unit’s that can be distinguished from the background at the 95% confidence level. Its validity was assessed by comparison with the behavior of a known QC phantom under various scan protocols and a tissue-mimicking phantom. The contributions of beam quality and scattered radiation upon the computed LCD were quantified by using various external beam-hardening filters and phantom lengths. Results: As expected, the LCD was inversely related to object size under all scan conditions. The type of image reconstruction kernel filter and tissue/organ type strongly influenced the background noise characteristics and therefore, the computed LCD for the associated image. Conclusion: The proposed metric and its associated software tools are vendor-independent and can be used to analyze any LCD scanner performance. Furthermore, the method employed can be used in conjunction with the relationships established in this study between LCD and tissue type to extend these concepts to patients’ clinical CT images.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Examining the microtexture evolution in a hole-edge punched into 780 MPa grade hot-rolled steel

The deformation behavior in the hole-edge of 780 MPa grade hot-rolled steel during the punching process was investigated via microstructure characterization and computational simulation. Microstructure characterization was conducted to observe the edges of punched holes through the thickness direction, and electron back-scattered diffraction (EBSD) was used to analyze the heterogeneity of the deformation. Finite element analysis (FEA) that could account for a ductile fracture criterion was conducted to simulate the deformation and fracture behaviors of 780 MPa grade hot-rolled steel during the punching process. Calculation of rotation rate fields at the edges of the punched holes during the punching process revealed that metastable orientations in Euler space were confined to specific orientation groups. Rotation-rate fields effectively explained the stability of the initial texture components in the hole-edge region during the punching process. A visco-plastic self-consistent (VPSC) polycrystal model was used to calculate the microtexture evolution in the hole-edge region during the punching process. FEA revealed that the heterogeneous effective strain was closely related to the heterogeneity of the Kernel average misorientation (KAM) distribution in the hole-edge region. A simulation of the deformation microtexture evolution in the hole-edge region using a VPSC model was in good agreement with the experimental results. - Highlights: •We analyzed the microstructure in a hole-edge punched in HR 780HB steel. •Rotation rate fields revealed the stability of the initial texture components. •Heterogeneous effective stain was closely related to the KAM distribution. •VPSC model successfully simulated the deformation microtexture evolution.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Modeling pre-Exascale AMR Parallel I/O Workloads via Proxy Applications

The present work investigates the modeling of preexascale input/output (I/O) workloads of Adaptive Mesh Refinement (AMR) simulations through a simple proxy application. We collect data from the AMReX Castro framework running on the Summit supercomputer for a wide range of scales and mesh partitions for the hydrodynamic Sedov case as a baseline to provide sufficient coverage to the formulated proxy model. The non-linear analysis data production rates are quantified as a function of a set of input parameters such as output frequency, grid size, number of levels, and the Courant-Friedrichs-Lewy (CFL) condition number for each rank, mesh level and simulation time step. Linear regression is then applied to formulate a simple analytical model which allows to translate AMReX inputs into MACSio proxy I/O application parameters, resulting in a simple “kernel” approximation for data production at each time step. Results show that MACSio can simulate actual AMReX nonlinear “static” I/O workloads to a certain degree of confidence on the Summit supercomputer using the present methodology. The goal is to provide an initial level of understanding of AMR I/O workloads via lightweight proxy applications models to facilitate autotune data management strategies in anticipation of exascale systems.

Godoy, William↗
DOE OSTI2016

The construction of arbitrary order ERKN methods based on group theory for solving oscillatory Hamiltonian systems with applications

In general, extended Runge–Kutta–Nyström (ERKN) methods are more effective than traditional Runge–Kutta–Nyström (RKN) methods in dealing with oscillatory Hamiltonian systems. However, the theoretical analysis for ERKN methods, such as the order conditions, the symplectic conditions and the symmetric conditions, becomes much more complicated than that for RKN methods. Therefore, it is a bottleneck to construct high-order ERKN methods efficiently. In this paper, we first establish the ERKN group Ω for ERKN methods and the RKN group G for RKN methods, respectively. We then rigorously show that ERKN methods are a natural extension of RKN methods, that is, there exists an epimorphism η of the ERKN group Ω onto the RKN group G. This epimorphism gives a global insight into the structure of the ERKN group by the analysis of its kernel and the corresponding RKN group G. Meanwhile, we establish a particular mapping φ of G into Ω so that each image element is an ideal representative element of the congruence class in Ω. Furthermore, an elementary theoretical analysis shows that this map φ can preserve many structure-preserving properties, such as the order, the symmetry and the symplecticity. From the epimorphism η together with its section φ, we may gain knowledge about the structure of the ERKN group Ω via the RKN group G. In light of the theoretical analysis of this paper, we obtain high-order structure-preserving ERKN methods in an effective way for solving oscillatory Hamiltonian systems. Numerical experiments are carried out and the results are very promising, which strongly support our theoretical analysis presented in this paper.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

MO-G-17A-05: PET Image Deblurring Using Adaptive Dictionary Learning

Purpose: The aim of this work is to deblur PET images while suppressing Poisson noise effects using adaptive dictionary learning (DL) techniques. Methods: The model that relates a blurred and noisy PET image to the desired image is described as a linear transform y=Hm+n where m is the desired image, H is a blur kernel, n is Poisson noise and y is the blurred image. The approach we follow to recover m involves the sparse representation of y over a learned dictionary, since the image has lots of repeated patterns, edges, textures and smooth regions. The recovery is based on an optimization of a cost function having four major terms: adaptive dictionary learning term, sparsity term, regularization term, and MLEM Poisson noise estimation term. The optimization is solved by a variable splitting method that introduces additional variables. We simulated a 128×128 Hoffman brain PET image (baseline) with varying kernel types and sizes (Gaussian 9×9, σ=5.4mm; Uniform 5×5, σ=2.9mm) with additive Poisson noise (Blurred). Image recovery was performed once when the kernel type was included in the model optimization and once with the model blinded to kernel type. The recovered image was compared to the baseline as well as another recovery algorithm PIDSPLIT+ (Setzer et. al.) by calculating PSNR (Peak SNR) and normalized average differences in pixel intensities (NADPI) of line profiles across the images. Results: For known kernel types, the PSNR of the Gaussian (Uniform) was 28.73 (25.1) and 25.18 (23.4) for DL and PIDSPLIT+ respectively. For blinded deblurring the PSNRs were 25.32 and 22.86 for DL and PIDSPLIT+ respectively. NADPI between baseline and DL, and baseline and blurred for the Gaussian kernel was 2.5 and 10.8 respectively. Conclusion: PET image deblurring using dictionary learning seems to be a good approach to restore image resolution in presence of Poisson noise. GE Health Care.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

SU-G-206-15: Effects of Dose Reduction On Emphysema Score

Purpose: The purpose of this study was to investigate the effects of reducing radiation dose levels on emphysema scores from lung cancer screening CT exams. Methods: 52 cases were selected from the National Lung Screening Trial (NLST) patients for which we had both the image series and the raw CT data. All scans were acquired with fixed effective mAs (25 for standard-sized patients, 40 for large patients) on a 64-slice scanner (Sensation 64, Siemens Healthcare) using 120kV, 64×0.6mm collimation and pitch 1.0. All images were reconstructed with 1mm slice thickness, B50 kernel. Based on a previously-published technique, we added noise to the raw data to simulate reduced-dose versions at 50% and 25% of the original dose (approximately 1.0- and 0.5-mGy CTDIvol). Lung segmentations were obtained via region growing from manual seed point at a threshold of 600HU followed by manual removal of trachea and major airways. Lung segmentations were only performed on original dose scans, and mapped to simulated reduced-dose scans. Emphysema scores based on relative area of lung with attenuation values lower than −950HU (RA950) were computed for all cases. Results: Average RA950 of all 50 cases were 31.6 (±5.5), 32.5 (±4.9) and 32.8 (±4.6) for 100%, 50% and 25% dose level respectively. The average absolute difference in RA950 between simulated and original dose scans were 1.0 (±0.7) and 1.4 (±1.1) for 50% and 25% dose level respectively. Conclusion: RA950 is relatively robust to dose level, with a difference of no more than 5 from the original dose scans. The average RA950 of this population was high for a two reasons: This was a high risk population of patients with substantial smoking history; The use of B50 kernel, which may be biased towards high emphysema scores. Further exploration with smoother kernels will be conducted in the future. Institutional research agreement, Siemens Healthcare; Past recipient, research grant support, Siemens Healthcare; Consultant, Toshiba America Medical Systems; Consultant, Samsung Electronics; NIH grant support from U01 CA181156.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Uniform Decay for Solutions of an Axially Moving Viscoelastic Beam

The paper deals with an axially moving viscoelastic structure modeled as an Euler–Bernoulli beam. The aim is to suppress the transversal displacement (transversal vibrations) that occur during the axial motion of the beam. It is assumed that the beam is moving with a constant axial speed and it is subject to a nonlinear force at the right boundary. We prove that when the axial speed of the beam is smaller than a critical value, the dissipation produced by the viscoelastic material is sufficient to suppress the transversal vibrations. It is shown that the rate of decay of the energy depends on the kernel which arise in the viscoelastic term. We consider a general kernel and notice that solutions cannot decay faster than the kernel.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Petascale Orbital-Free Density Functional Theory Enabled by Small-Box Algorithms

Orbital-free density functional theory (OFDFT) is a quantum-mechanics-based method that utilizes electron density as its sole variable. The main computational cost in OFDFT is the ubiquitous use of the fast Fourier transform (FFT), which is mainly adopted to evaluate the kinetic energy density functional (KEDF) and electron–electron Coulomb interaction terms. We design and implement a small-box FFT (SBFFT) algorithm to overcome the parallelization limitations of conventional FFT algorithms. We also propose real-space truncation of the nonlocal Wang–Teter KEDF kernel. The scalability of the SBFFT is demonstrated by efficiently simulating one full optimization step (electron density, energies, forces, and stresses) of 1,024,000 lithium (Li) atoms on up to 65,536 cores. We perform other tests using Li as a test material, including calculations of physical properties of different phases of bulk Li, geometry optimizations of nanocrystalline Li, and molecular dynamics simulations of liquid Li. All of the tests yield excellent agreement with the original OFDFT results, suggesting that the OFDFT-SBFFT algorithm opens the door to efficient first-principles simulations of materials containing millions of atoms.

Chemistry↗
DOE OSTI2014

Proper orthogonal decomposition-based spectral higher-order stochastic estimation

A unique routine, capable of identifying both linear and higher-order coherence in multiple-input/output systems, is presented. The technique combines two well-established methods: Proper Orthogonal Decomposition (POD) and Higher-Order Spectra Analysis. The latter of these is based on known methods for characterizing nonlinear systems by way of Volterra series. In that, both linear and higher-order kernels are formed to quantify the spectral (nonlinear) transfer of energy between the system's input and output. This reduces essentially to spectral Linear Stochastic Estimation when only first-order terms are considered, and is therefore presented in the context of stochastic estimation as spectral Higher-Order Stochastic Estimation (HOSE). The trade-off to seeking higher-order transfer kernels is that the increased complexity restricts the analysis to single-input/output systems. Low-dimensional (POD-based) analysis techniques are inserted to alleviate this void as POD coefficients represent the dynamics of the spatial structures (modes) of a multi-degree-of-freedom system. The mathematical framework behind this POD-based HOSE method is first described. The method is then tested in the context of jet aeroacoustics by modeling acoustically efficient large-scale instabilities as combinations of wave packets. The growth, saturation, and decay of these spatially convecting wave packets are shown to couple both linearly and nonlinearly in the near-field to produce waveforms that propagate acoustically to the far-field for different frequency combinations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

GPU Accelerated Sparse Cholesky Factorization

The solution of sparse symmetric positive definite linear systems is an important computational kernel in large-scale scientific and engineering modeling and simulation. We will solve the linear systems using a direct method, in which a Cholesky factorization of the coefficient matrix is performed using a right-looking approach and the resulting triangular factors are used to compute the solution. Sparse Cholesky factorization is compute intensive. In this work we investigate techniques for reducing the factorization time in sparse Cholesky factorization by offloading some of the dense matrix operations on a GPU. We will describe the techniques we have considered. We achieved up to 4x speedup compared to the CPU-only version.

Karsavuran, M Ozan↗
DOE OSTI2016

SU-F-J-08: Quantitative SPECT Imaging of Ra-223 in a Phantom

Purpose: Ra-223 therapy of prostate cancer bone metastases is being used to treat patients routinely. However, the absorbed dose distribution at the macroscopic and microscopic scales remains elusive, due to the inability to image the small activities injected. Accurate activity quantification through imaging is essential to calculate the absorbed dose in organs and sub-units in radiopharmaceutical therapy, enabling personalized absorbed dose-based treatment planning methodologies and more effective and optimal treatments. Methods: A 22 cm diameter by 20 cm long cylindrical phantom, containing a 3.52 cm diameter sphere, was used. A total of 2.01 MBq of Ra-223 was placed in the phantom with 177.6 kBq in the sphere. Images were acquired on a dual-head Siemens Symbia T16 gamma camera using three 20% full-width energy windows and centered at 84, 154, and 269 keV (120 projections, 360° rotation, 45 s per view). We have implemented reconstruction of Ra-223 SPECT projections using OS-EM (up to 20 iterations of 10 subsets) with compensation for attenuation using CT-based attenuation maps, collimator-detector response (CDR) (including septal penetration, scatter and Pb x-ray modeling), and scatter in the patient using the effective source scatter estimation (ESSE) method. The CDR functions and scatter kernels required for ESSE were computed using the SIMIND MC simulation code. All Ra-223 photon emissions as well as gamma rays from the daughters Rn-219 and Bi-211 were modeled. Results: The sensitivity of the camera in the three combined windows was 107.3 cps/MBq. The visual quality of the SPECT images was reasonably good and the activity in the sphere was 27% smaller than the true activity. This underestimation is likely due to partial volume effect. Conclusion: Absolute quantitative Ra-223 SPECT imaging is achievable with careful attention to compensate for image degrading factors and system calibration.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

BASIC HARTREE-FOCK PROXY APPLICTION

This proxy application simulates the compute load and data-movement of the kernel of the Hartree-Fock method in quantum chemistry. The proxy features a simplified algorithm for computing electron repulsion integrals that is easily offloaded to GPUs.

FLETCHER, GRAHAMD↗