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At least 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Microstructure optimization with constrained design objectives using machine learning-based feedback-aware data-generation

Microstructure sensitive design has a critical impact on the performance of engineering materials. The safety and performance requirements of critical components, as well as the cost of material and machining of Titanium components, make dovetailing of the microstructure imperative. This paper addresses the optimization of several microstructure design problems for Titanium components under specific design constraints using a feedback-aware data-driven solution methodology. In this study, the microstructure is modeled with an orientation distribution function (ODF) that measures the volumes of different crystallographic orientations. Two algorithms are used to sample the entire microstructure space followed by machine learning-aided identification of a minimal subset of ODF dimensions which is subsequently explored by targeted sampling. Conventional optimization methods lead to a unique microstructure rather than yielding a comprehensive space of optimal or near-optimal microstructures. Multiple solutions are crucial for the deployment of materials design for manufacturing as traditional manufacturing processes can only generate a limited set of microstructures. Our data sampling-based methodology not only outperforms or is on par with other optimization techniques in terms of the optimal property value, but also provides numerous near-optimal solutions, 3–4 orders of magnitude more than previous methods. Consequently, the proposed framework delivers a spectrum of optimal solutions in the microstructure space which can accelerate materials development and reduce manufacturing costs.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Flexible and Transferable ab Initio Force Field for Zeolitic Imidazolate Frameworks: ZIF-FF

We have developed a transferable ab initio intramolecular force field for zeolitic imidazolate frameworks (ZIFs), “ZIF-FF”, that is capable of quantitatively describing the structural properties and relative stabilities of ZIFs. In contrast to nearly all prior force fields, ZIF-FF properly describes the relative stability of ZIF polymorphs, a crucial element in ZIF nucleation and crystal growth. Beginning with a general Amber force field (GAFF), Zn-related force field parameters were optimized against dispersion-corrected DFT-calculated properties using a genetic algorithm. We validated the resulting force field by examining bond and angle distributions, phonon density of states, mechanical properties, diffusion properties and via modeling a ZIF amorphization process. Moreover, we find that ZIF-FF is transferable, successfully describing relative stability of various ZIF surface structures, as well as the densities of ZIFs with diverse functionalized linkers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

An Observationally Trained Markov Model for MJO Propagation

A Markovian stochastic model is developed for studying the propagation of the Madden-Julian Oscillation (MJO). This model represents the daily changes in real time multivariate MJO (RMM) indices as random functions of their current state and background conditions. The probability distribution function of the RMM changes is obtained using a machine learning algorithm trained to maximize MJO forecast skills using observed daily indices of RMM and different modes of variability. Skillful forecasts are obtained for lead times between 8 and 27 days. Large ensemble simulations by the stochastic model show that with monsoonal changes in the background state, MJO propagation across the Maritime Continent (MC) is most likely to be disrupted in boreal spring and summer when MJO events propagate from favorable conditions over the Indian Ocean to unfavorable ones over the MC, and predictability is higher during spring and summer when MJO activity is away from the MC region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Three-dimensional imaging of grain boundaries via quantitative fluorescence X-ray tomography analysis

Abstract Three-dimensional visualization of material composition within multiple grains and across complex networks of grain boundaries at nanoscales can provide new insight into the structure evolution and emerging functional properties of the material for diverse applications. Here, using nanoscale scanning X-ray fluorescence tomography, coupled with an advanced self-absorption correction algorithm developed in this work, we analyze the three-dimensional gain distributions and compositions in a Ce 0.8 Gd 0.2 O 2-δ -CoFe 2 O 4 mixed ionic-electronic conductor system with high accuracy and statistical significance. Our systematic investigation reveals an additional emergent phase and uncovers highly intriguing composition stability ranges for the multiple material phases within this system. The presented visualization of composition variations across complex interfaces, supported by our quantitative composition analysis, discloses mechanistic pathways of the diverse phase transformations occurring in the material synthesis, providing insights for the optimization of transport properties in the mixed ionic-electronic conductor system.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Data-Driven Benchmarking of Building Energy Efficiency Utilizing Statistical Frontier Models

Frontier methods quantify the energy efficiency of buildings by forming an efficient frontier (best-practice technology) and by comparing all buildings against that frontier. Because energy consumption fluctuates over time, the efficiency scores are stochastic random variables. Existing applications of frontier methods in energy efficiency either treat efficiency scores as deterministic values or estimate their uncertainty by resampling from one set of measurements. Availability of smart meter data (repeated measurements of energy consumption of buildings) enables using actual data to estimate the uncertainty in efficiency scores. Additionally, existing applications assume a linear form for an efficient frontier; i.e.,they assume that the best-practice technology scales up and down proportionally with building characteristics. However, previous research shows that buildings are nonlinear systems. This paper proposes a statistical method called stochastic energy efficiency frontier (SEEF) to estimate a bias-corrected efficiency score and its confidence intervals from measured data. The paper proposes an algorithm to specify the functional form of the frontier, identify the probability distribution of the efficiency score of each building using measured data, and rank buildings based on their energy efficiency. To illustrate the power of SEEF, this paper presents the results from applying SEEF on a smart meter data set of 307 residential buildings in the United States. SEEF efficiency scores are used to rank individual buildings based on energy efficiency, to compare subpopulations of buildings, and to identify irregular behavior of buildings across different time-of-use periods. SEEF is an improvement to the energy-intensity method (comparing kWh/sq.ft.): whereas SEEF identifies efficient buildings across the entire spectrum of building sizes, the energy-intensity method showed bias toward smaller buildings. The results of this research are expected to assist researchers and practitioners compare and rank (i.e.,benchmark) buildings more robustly and over a wider range of building types and sizes. Eventually, doing so is expected to result in improved resource allocation in energy-efficiency programs.

Kavousian, A↗
DOE OSTI2020

ReaxFF molecular dynamics simulations of electrolyte–water systems at supercritical temperature

We have performed ReaxFF molecular dynamics simulations of alkali metal–chlorine pairs in different water densities at supercritical temperature (700 K) to elucidate the structural and dynamical properties of the system. The radial distribution function and the angular distribution function explain the inter-ionic structural and orientational arrangements of atoms during the simulation. The coordination number of water molecules in the solvation shell of ions increases with an increase in the radius of ions. We find that the self-diffusion coefficient of metal ions increases with a decrease in density under supercritical conditions due to the formation of voids within the system. The hydrogen bond dynamics has been interpreted by the residence time distribution of various ions, which shows Li+ having the highest water retaining capability. The void distribution within the system has been analyzed by using the Voronoi polyhedra algorithm providing an estimation of void formation within the system at high temperatures. We observe the formation of salt clusters of Na+ and K+ at low densities due to the loss of dielectric constants of ions. The diffusion of ions gets altered dramatically due to the formation of voids and nucleation of ions in the system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Time-dependent saturation and physics-based nonlinear model of cross-beam energy transfer

The nonlinear physics of cross-beam energy transfer (CBET) for multi-speckled laser beams is examined using large-scale particle-in-cell simulations for a range of laser and plasma conditions relevant to indirect-drive inertial confinement fusion (ICF) experiments. The time-dependent growth and saturation of CBET involve complex, nonlinear ion and electron dynamics, including ion trapping-induced enhancement and detuning, ion acoustic wave (IAW) nonlinearity, oblique forward stimulated Raman scattering (FSRS), and backward stimulated Brillouin scattering (BSBS) in a CBET-amplified seed beam. Ion-trapping-induced detuning of CBET is captured in the kinetic linear response by a new δf-Gaussian-mixture algorithm, enabling an accurate characterization of trapping-induced non-Maxwellian distributions. Ion trapping induces nonlinear processes, such as changes to the IAW dispersion and nonlinearities (e.g., bowing and self-focusing), which, together with pump depletion, FSRS, and BSBS, determine the time-dependent nature and level of CBET gain as the system approaches a steady state. Using VPIC simulations at intensities at and above the onset threshold for ion trapping and the insight from the time-dependent saturation analyses, we construct a nonlinear CBET model from local laser and plasma conditions that predicts the CBET gain and the energy deposition into the plasma. This model is intended to provide a more accurate, physics-based description of CBET saturation over a wide range of conditions encountered in ICF hohlraums compared with linear CBET gain models with ad hoc saturation clamps often used in laser ray-based methods in multi-physics codes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Nonlinear models for coupling the effects of stimulated Raman scattering to inertial confinement fusion codes

Laser plasma instabilities (LPI) reduce driver-target coupling, alter implosion symmetry, and therefore can fundamentally limit fusion performance in inertial confinement fusion (ICF). Developing a predictive modeling capability for LPI effects can critically advance the success of the field. We perform vector particle-in-cell simulations of multi-speckled laser beams undergoing stimulated Raman scattering (SRS) at various densities and intensities relevant to mainly indirectly driven and a subset of parameter space for directly driven ICF systems, focusing on the regimes with intensities above the onset of electron trapping. Based on the wavenumber of the SRS daughter electron plasma wave, we identify several regions with underpinning SRS saturation physics: the electron-trapping dominated region with intermediate kλD values, the strong Landau damping region at larger kλD values, and the region where the Langmuir decay instability arises at lower kλD values. We develop a nonlinear SRS reflectivity model that features the base trapping-dominated scaling of (kλD)−4 and its modifications. Electron trapping deforms the initialized electron distribution functions, and we have developed a new δf-Gaussian-mixture algorithm for an accurate characterization of the trapped hot electron population. With this SRS hot electron description, we construct a nonlinear energy deposition model and a hot electron source model—based on a modified Manley–Rowe relation—suitable for including SRS effects as a sub-grid module in a high-fidelity ICF design code.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

A semi-automated algorithm for designing stellarator divertor and limiter plates and application to HSX

We present a semi-automated algorithm for designing three-dimensional divertor or limiter plates targeting low heat loads. The algorithm designs the plates in two stages: firstly, the parallel heat flux distribution is caught on vertically-inclined plates at one or several toroidal locations. Secondly, the power per unit area is reduced by stretching, tilting and bending the plates toroidally. Heat transport is modelled using the EMC3-Lite code, which uses an anisotropic diffusion model. We apply this scheme to HSX, a medium-sized stellarator located at the University of Wisconsin–Madison. Starting from the current machine with an extended vessel wall, we construct plates which are able to effectively catch and spread the heat for three different magnetic configurations. The scheme has a computational cost in the order of tens of CPU-minutes, making it a powerful tool for semi-automated plasma-facing component design in three-dimensional environments.

anisotropic diffusion↗
DOE OSTI2025

Critical fluid dynamics in two and three dimensions

We describe a numerical method for simulating stochastic fluid dynamics near a critical point in the Ising universality class. This theory is known as model H, and is expected to govern the nonequilibrium dynamics of quantum chromodynamics (QCD) near a possible critical endpoint of the phase transition between a hadron liquid and the quark-gluon plasma. The numerical algorithm is based on a Metropolis scheme, and automatically ensures that the distribution function of the hydrodynamic variables in equilibrium is independent of the transport coefficients and only governed by the microscopic free energy. We verify dynamic scaling near the critical point of a two and three-dimensional fluid and extract the associated critical exponent z. Here, we find z≃3 in three dimensions, and z≃2 for a two-dimensional fluid. In a finite system, we observe a crossover between the mean field value z=4 and the true critical exponent z≃3 (z≃2 in d=2). This crossover is governed by the values of the correlation length and the renormalized shear viscosity.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Photoluminescence-Imaging-Based Evaluation of Non-Uniform CdTe Degradation

A control algorithm is designed to smooth the variability of PV power output using distributed batteries. The tradeoff between smoothing and battery size is shown. It is also demonstrated that large numbers of highly distributed current, voltage, and irradiance sensors can be utilized to control the distributed storage in a more optimal manner. It is also demonstrated that centralized energy storage control for PV ramp rate smoothing requires very fast communication, typically less than a 15-second update rate. Finally, advanced inverter dynamic reactive current is shown to provide voltage variability smoothing, hence reducing the number of voltage regulator tap changes without energy storage.

14 SOLAR ENERGY↗
DOE OSTI2012

pGraph: Efficient Parallel Construction of Large-Scale Protein Sequence Homology Graphs

Detecting sequence homology between protein sequences is a fundamental problem in computational molecular biology, with a pervasive application in nearly all analyses that aim to structurally and functionally characterize protein molecules. While detecting the homology between two protein sequences is relatively inexpensive, detecting pairwise homology for a large number of protein sequences can become computationally prohibitive for modern inputs, often requiring millions of CPU hours. Yet, there is currently no robust support to parallelize this kernel. In this paper, we identify the key characteristics that make this problemparticularly hard to parallelize, and then propose a new parallel algorithm that is suited for detecting homology on large data sets using distributed memory parallel computers. Our method, called pGraph, is a novel hybrid between the hierarchical multiple-master/worker model and producer-consumer model, and is designed to break the irregularities imposed by alignment computation and work generation. Experimental results show that pGraph achieves linear scaling on a 2,048 processor distributed memory cluster for a wide range of inputs ranging from as small as 20,000 sequences to 2,560,000 sequences. In addition to demonstrating strong scaling, we present an extensive report on the performance of the various system components and related parametric studies.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2014

SU-E-T-305: Study of the Eclipse Electron Monte Carlo Algorithm for Patient Specific MU Calculations

Purpose: To evaluate the Eclipse electron Monte Carlo (eMC) algorithm based on patient specific monitor unit (MU) calculations, and to propose a new factor which quantitatively predicts the discrepancy of MUs between the eMC algorithm and hand calculations. Methods: Electron treatments were planned for 61 patients on Eclipse (Version 10.0) using the eMC algorithm for Varian TrueBeam linear accelerators. For each patient, the same treatment beam angle was kept for a point dose calculation at dmax performed with the reference condition, which used an open beam with a 15×15 cm2 size cone and 100 SSD. A patient specific correction factor (PCF) was obtained by getting the ratio between this point dose and the calibration dose, which is 1 cGy per MU delivered at dmax. The hand calculation results were corrected by the PCFs and compared with MUs from the treatment plans. Results: The MU from the treatment plans were in average (7.1±6.1)% higher than the hand calculations. The average MU difference between the corrected hand calculations and the eMC treatment plans was (0.07±3.48)%. A correlation coefficient of 0.8 was found between (1-PCF) and the percentage difference between the treatment plan and hand calculations. Most outliers were treatment plans with small beam opening (< 4 cm) and low energy beams (6 and 9 MeV). Conclusion: For CT-based patient treatment plans, the eMC algorithm tends to generate a larger MU than hand calculations. Caution should be taken for eMC patient plans with small field sizes and low energy beams. We hypothesize that the PCF ratio reflects the influence of patient surface curvature and tissue inhomogeneity to patient specific percent depth dose (PDD) curve and MU calculations in eMC algorithm.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

TH-C-BRD-09: Successes and Limitations of Online Range Adaptive Spot Scanning Proton Therapy for NSCLC

Purpose: To determine the ability to adapt discrete spot-scanning proton therapy (SSPT) plans based on geometric changes of anatomy to minimize normal tissue dose and maintain target coverage. Methods: We developed and tested a range-correction algorithm to compensate for anatomy changes in SSPT with correction factors for target lateral size changes and energy scaling. This algorithm adjusts the energy of each spot from the original optimized treatment plan to match the new daily anatomy based on water equivalent path-length. To correct for the lateral target size changes, the peripheral spots were scaled based on phantom studies with variable target size. For energy change corrections, alternative cumulative scaling factor lookup tables were generated based on calculated central-axis and integral depth dose calculations for different energies. These various adaptive algorithms were performed on 7 lung cancer patients that were previously treated with proton therapy and who required at least one adaptive intervention. Single-field optimized SSPT plans were generated for these patients with clinical beam angles. Dose-volume histogram metrics were obtained for these patients for both the non-adaptive and the different adaptive plans applied to the last available weekly CT scan. Results: The doses to normal tissue were largely reduced for the spinal cord (Dmax), total lung (V20Gy), and contralateral lung (V20Gy) for all different methods of adaptive planning. With both corrections applied, the average changes for these metrics were −6.2Gy, −2.7%, and −4.9%, respectively. The same method generated unacceptably high target hot spots with average target V110% increase of 12.3%. Conclusion: Adaptive methods based on direct adjustments to proton range can reduce normal tissue doses under large anatomical changes but are insufficient in achieving clinically acceptable target doses and generate unacceptably sizeable hot spots. Adaptive planning methods for proton therapy will likely necessitate some aspect of reoptimization for acceptable clinical utility.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-I-22: A Comprehensive Investigation of Noise Variations Between the GE Discovery CT750 HD and GE LightSpeed VCT

Purpose: To quantify and compare the noise properties between two GE CT models-the Discovery CT750 HD (aka HD750) and LightSpeed VCT, with the overall goal of assessing the impact in clinical diagnostic practice. Methods: Daily QC data from a fleet of 9 CT scanners currently in clinical use were investigated – 5 HD750 and 4 VCT (over 600 total acquisitions for each scanner). A standard GE QC phantom was scanned daily using two sets of scan parameters with each scanner over 1 year. Water CT number and standard deviation were recorded from the image of water section of the QC phantom. The standard GE QC scan parameters (Pitch = 0.516, 120kVp, 0.4s, 335mA, Small Body SFOV, 5mm thickness) and an in-house developed protocol (Axial, 120kVp, 1.0s, 240mA, Head SFOV, 5mm thickness) were used, with Standard reconstruction algorithm. Noise was measured as the standard deviation in the center of the water phantom image. Inter-model noise distributions and tube output in mR/mAs were compared to assess any relative differences in noise properties. Results: With the in-house protocols, average noise for the five HD750 scanners was ∼9% higher than the VCT scanners (5.8 vs 5.3). For the GE QC protocol, average noise with the HD750 scanners was ∼11% higher than with the VCT scanners (4.8 vs 4.3). This discrepancy in noise between the two models was found despite the tube output in mR/mAs being comparable with the HD750 scanners only having ∼4% lower output (8.0 vs 8.3 mR/mAs). Conclusion: Using identical scan protocols, average noise in images from the HD750 group was higher than that from the VCT group. This confirms feedback from an institutional radiologist’s feedback regarding grainier patient images from HD750 scanners. Further investigation is warranted to assess the noise texture and distribution, as well as clinical impact.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-416: Experimental Evaluation of a Commercial GPU-Based Monte Carlo Dose Calculation Algorithm

Purpose: A new commercial GPU-based Monte Carlo dose calculation algorithm (GPUMCD) developed by the vendor Elekta™ to be used in the Monaco Treatment Planning System (TPS) is capable of modeling dose for both a standard linear accelerator and for an Elekta MRI-Linear accelerator (modeling magnetic field effects). We are evaluating this algorithm in two parts: commissioning the algorithm for an Elekta Agility linear accelerator (the focus of this work) and evaluating the algorithm’s ability to model magnetic field effects for an MRI-linear accelerator. Methods: A beam model was developed in the Monaco TPS (v.5.09.06) using the commissioned beam data for a 6MV Agility linac. A heterogeneous phantom representing tumor-in-lung, lung, bone-in-tissue, and prosthetic was designed/built. Dose calculations in Monaco were done using the current clinical algorithm (XVMC) and the new GPUMCD algorithm (1 mm3 voxel size, 0.5% statistical uncertainty) and in the Pinnacle TPS using the collapsed cone convolution (CCC) algorithm. These were compared with the measured doses using an ionization chamber (A1SL) and Gafchromic EBT3 films for 2×2 cm{sup 2}, 5×5 cm{sup 2}, and 10×10 cm{sup 2} field sizes. Results: The calculated central axis percentage depth doses (PDDs) in homogeneous solid water were within 2% compared to measurements for XVMC and GPUMCD. For tumor-in-lung and lung phantoms, doses calculated by all of the algorithms were within the experimental uncertainty of the measurements (±2% in the homogeneous phantom and ±3% for the tumor-in-lung or lung phantoms), except for 2×2 cm{sup 2} field size where only the CCC algorithm differs from film by 5% in the lung region. The analysis for bone-in-tissue and the prosthetic phantoms are ongoing. Conclusion: The new GPUMCD algorithm calculated dose comparable to both the XVMC algorithm and to measurements in both a homogeneous solid water medium and the heterogeneous phantom representing lung or tumor-in-lung for 2×2 cm{sup 2}-10×10 cm{sup 2} field sizes. Funding support was obtained from Elekta.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Evaluation of a commercial MRI Linac based Monte Carlo dose calculation algorithm with GEANT 4

Purpose: This paper provides a comparison between a fast, commercial, in-patient Monte Carlo dose calculation algorithm (GPUMCD) and GEANT4. It also evaluates the dosimetric impact of the application of an external 1.5 T magnetic field. Methods: A stand-alone version of the Elekta™ GPUMCD algorithm, to be used within the Monaco treatment planning system to model dose for the Elekta™ magnetic resonance imaging (MRI) Linac, was compared against GEANT4 (v10.1). This was done in the presence or absence of a 1.5 T static magnetic field directed orthogonally to the radiation beam axis. Phantoms with material compositions of water, ICRU lung, ICRU compact-bone, and titanium were used for this purpose. Beams with 2 MeV monoenergetic photons as well as a 7 MV histogrammed spectrum representing the MRI Linac spectrum were emitted from a point source using a nominal source-to-surface distance of 142.5 cm. Field sizes ranged from 1.5 × 1.5 to 10 × 10 cm{sup 2}. Dose scoring was performed using a 3D grid comprising 1 mm{sup 3} voxels. The production thresholds were equivalent for both codes. Results were analyzed based upon a voxel by voxel dose difference between the two codes and also using a volumetric gamma analysis. Results: Comparisons were drawn from central axis depth doses, cross beam profiles, and isodose contours. Both in the presence and absence of a 1.5 T static magnetic field the relative differences in doses scored along the beam central axis were less than 1% for the homogeneous water phantom and all results matched within a maximum of ±2% for heterogeneous phantoms. Volumetric gamma analysis indicated that more than 99% of the examined volume passed gamma criteria of 2%—2 mm (dose difference and distance to agreement, respectively). These criteria were chosen because the minimum primary statistical uncertainty in dose scoring voxels was 0.5%. The presence of the magnetic field affects the dose at the interface depending upon the density of the material on either sides of the interface. This effect varies with the field size. For example, at the water-lung interface a 33.94% increase in dose was observed (relative to the D{sub max}), by both GPUMCD and GEANT4 for the field size of 2 × 2 cm{sup 2} (compared to no B-field case), which increased to 47.83% for the field size of 5 × 5 cm{sup 2} in the presence of the magnetic field. Similarly, at the lung-water interface, the dose decreased by 19.21% (relative to D{sub max}) for a field size of 2 × 2 cm{sup 2} and by 30.01% for 5 × 5 cm{sup 2} field size. For more complex combinations of materials the dose deposition also becomes more complex. Conclusions: The GPUMCD algorithm showed good agreement against GEANT4 both in the presence and absence of a 1.5 T external magnetic field. The application of 1.5 T magnetic field significantly alters the dose at the interfaces by either increasing or decreasing the dose depending upon the density of the material on either side of the interfaces.

61 RADIATION PROTECTION AND DOSIMETRY↗