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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

High Performance Iterative Tomography Reconstructions on GPU and Intel Xeon Phi Coprocessor (Final CRADA Report)

The objective of this project is to (1) implement an open source high performance software toolkit of representative iterative tomographic reconstruction algorithms executing on both GPU and coprocessor, (2) perform benchmark testing for associated applications and make the architecture recommendation with consideration of budget plan and programming capability, and (3) engage research publications on designing and developing new acceleration algorithms on the aforementioned HPC architectures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Asynchronous Iterative Solvers for Extreme-Scale Computing

The Asynchronous Iterative Solvers for Extreme-Scale Computing (AsyncIS) project aims to explore more efficient numerical algorithms by decreasing their overhead. AsyncIS does this by replacing the outer Krylov subspace solver with an asynchronous optimized Schwarz method, thereby removing the global synchronization and bulk synchronous operations typically used in numerical codes. AsyncIS—a U.S. Department of Energy (DOE)-funded collaboration between Georgia Tech, the University of Tennessee, Knoxville, Temple University, and Sandia National Laboratories—also focuses on the development and optimization of asynchronous preconditioners (i.e., preconditioners that are generated and/or applied in an asynchronous fashion). The novel preconditioning algorithms that provide fine-grained parallelism enable preconditioned Krylov solvers to run efficiently on large-scale distributed systems and manycore accelerators like GPUs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

SOLPS-ITER modeling of drift effects in DIII-D double-null AT configurations (Final Report)

At the DIII-D tokamak, our collaborative research program supported divertor development. Specifically, we focused on slot-type divertors called SAS divertors. Modeling of conceptual SAS configurations with SOLPS-ITER, including full drifts, has provided insights that can guide future modeling and experimental research related to tightly baffled slot divertors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

An Iterative Approach for Solving the SCOPF Problem Applying LP, SOCP, and NLP Subproblems

We propose to develop efficient algorithms and software for the SCOPF problem. We will employ an iterative approach that will: a) use linear subproblems and other active set filtering techniques to identify the most important contingencies and drastically reduce the SCOPF model size; b) solve SOCP relaxations of the reduced SCOPF to converge to the neighborhood of the global optimal solution and establish a lower bound on the solution, and; c) use a non-convex, nonlinear interior-point solver, Artelys Knitro, to converge quickly to the optimal solution. To identify the most effective approach, we will experiment with several techniques to identify the tradeoffs between contingency subproblem complexity and fast solvability.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

An Iterative Machine Learning Framework for Event Classification and Monte Carlo Tuning in SpinQuest

The E1039/SpinQuest experiment at Fermi National Accelerator Laboratory uses a 120~GeV proton beam from the Main Injector incident on transversely polarized proton and deuteron targets, using $NH_3$ and $ND_3$, respectively. In addition to measuring the Sivers asymmetry in Drell--Yan $pp$ and $pd$ scattering from sea quarks, SpinQuest will study transverse-spin effects, particularly the transverse single-spin asymmetry (TSSA) in $J/\psi$ production. The angular distributions from the $J/\psi$ decay could play an important role in understanding the gluon contribution to the proton spin structure. However, before extracting these angular distributions, it is necessary to isolate signal events originating from the target from events produced by other sources and from the combinatorial background. To effectively and accurately classify the target events, it is important to ensure that the simulated events are properly tuned to the experimental physics channels. We have introduced an iterative technique to match simulated and experimental events and to classify the physics channels using deep neural networks and a generative model based on normalizing flows.

Hossain, Forhad [Virginia U. (main)] (ORCID:000000↗
DOE OSTI2018

Ultrasonic Model-Based Iterative Reconstruction with Spatially Variant Regularization for One-Sided Non-Destructive Evaluation

One-sided ultrasonic non-destructive evaluation (UNDE) uses ultrasound signals to investigate and inspect structures that are only accessible from one side. A widely used reconstruction technique in UNDE is the synthetic aperture focusing technique (SAFT). SAFT produces fast reconstruction and reasonable images for simple structures. However, for large complex structures, SAFT reconstructions suffer from noise and artifacts. To resolve some of the drawbacks of SAFT, an ultrasonic model-based iterative reconstruction (MBIR) algorithm, a method based on Bayesian estimation, was proposed that showed significant enhancement over SAFT in reducing noise and artifacts. In this paper, we build on previous investigations of the use of MBIR reconstruction on ultrasound data by proposing a spatially varying prior-model to account for artifacts from deeper regions and a 3D regularizer to account for correlations between scans from adjacent regions. We demonstrate that the use of the new prior model in MBIR can significantly improve reconstructions compared to SAFT and the previously proposed MBIR technique.

Almansouri, Hani↗
DOE OSTI2022

Evaluating the Performance of Random Forest and Iterative Random Forest Based Methods when Applied to Gene Expression Data

Gene-to-gene networks, such as Gene Regulatory Networks (GRN) and Predictive Expression Networks (PEN) capture relationships between genes and are beneficial for use in downstream biological analyses. There exists multiple network inference tools to produce these gene-to-gene networks from matrices of gene expression data. Random Forest-Leave One Out Prediction (RF-LOOP) is a method that has been shown to be efficient at producing these gene-to-gene networks, frequently known as GEne Network Inference with Ensemble of trees (GENIE3). Here we validate that iterative Random Forest-Leave One Out Prediction (iRF-LOOP) produces higher quality networks than GENIE3. We use both synthetic and empirical networks from the Dialogue for Reverse Engineering Assessment and Methods (DREAM) Challenges by Sage Bionetworks, as well as two additional empirical networks created from Arabidopsis thaliana and Populus trichocarpa expression data.

iRF-Loop, expression network, Populus Trichocarpa↗
DOE OSTI2023

Using iterative random forest to find geospatial environmental and Sociodemographic predictors of suicide attempts

Despite a recent global decrease in suicide rates, death by suicide has increased in the United States. It is therefore imperative to identify the risk factors associated with suicide attempts to combat this growing epidemic. In this study, we aim to identify potential risk factors of suicide attempt using geospatial features in an Artificial intelligence framework. We use iterative Random Forest, an explainable artificial intelligence method, to predict suicide attempts using data from the Million Veteran Program. This cohort incorporated 405,540 patients with 391,409 controls and 14,131 attempts. Our predictive model incorporates multiple climatic features at ZIP-code-level geospatial resolution. We additionally consider demographic features from the American Community Survey as well as the number of firearms and alcohol vendors per 10,000 people to assess the contributions of proximal environment, access to means, and restraint decrease to suicide attempts. In total 1,784 features were included in the predictive model. Our results show that geographic areas with higher concentrations of married males living with spouses are predictive of lower rates of suicide attempts, whereas geographic areas where males are more likely to live alone and to rent housing are predictive of higher rates of suicide attempts. We also identified climatic features that were associated with suicide attempt risk by age group. Additionally, we observed that firearms and alcohol vendors were associated with increased risk for suicide attempts irrespective of the age group examined, but that their effects were small in comparison to the top features. Taken together, our findings highlight the importance of social determinants and environmental factors in understanding suicide risk among veterans.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Locating Partial Discharges in Power Transformers with Convolutional Iterative Filtering

The most common source of transformer failure is in the insulation, and the most prevalent warning signal for insulation weakness is partial discharge (PD). Locating the positions of these partial discharges would help repair the transformer to prevent failures. This work investigates algorithms that could be deployed to locate the position of a PD event using data from ultra-high frequency (UHF) sensors inside the transformer. These algorithms typically proceed in two steps: first determining the signal arrival time, and then locating the position based on time differences. This paper reviews available methods for each task and then propose new algorithms: a convolutional iterative filter with thresholding (CIFT) to determine the signal arrival time and a reference table of travel times to resolve the source location. The effectiveness of these algorithms are tested with a set of laboratory-triggered PD events and two sets of simulated PD events inside transformers in production use. Tests show the new approach provides more accurate locations than the best-known data analysis algorithms, and the difference is particularly large, 3.7X, when the signal sources are far from sensors.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Iterative and Self-Consistent Estimation of Degradation and Soiling Loss in PV Systems - A Case Study

In many parts of the world, soiling is a significant loss mechanism for PV energy production. Methods for accurately quantifying historical and current soiling losses are needed. Furthermore, state-of-the-art methods to estimate degradation rates based on production data do not handle soiling in a satisfactory manner. In order to accurately estimate either of these quantities, it is in many cases helpful to consider their combined effect on PV system performance. In this work we make use of the Combined Degradation and Soiling (CODS) algorithm, which iteratively decomposes time series of daily normalized energy yield into four components: a soiling ratio, a degradation trend, seasonal variations, and noise. We demonstrate the use of the model on field performance data from a utility-scale power plant in a high-soiling environment in the Middle East. We apply the algorithm to the temperature-corrected performance index of the DC power on inverter level, quantifying how soiling varies over time and through the plant. The irradiation-weighted average soiling loss in this plant is 2.3 %, with a median soiling rate of -0.086 %/day. Between the inverters in the site in study, estimated degradation rates range between -0.86 %/year and -0.15 %/year, with a mean rate of -0.48 %/year.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2023

Retrieval of temperature and humidity profiles from ground-based high-resolution infrared observations using an adaptive fast iterative algorithm

Various retrieval algorithms have been developed for retrieving temperature and water vapor profiles from Atmospheric Emitted Radiance Interferometer (AERI) observations. The physical retrieval algorithm, named AERI Optimal Estimation (AERIoe), outperforms other retrieval algorithms in many aspects except the retrieval time, which is significantly increased due to the complex radiative transfer process. The calculation of the Jacobian matrix is the most computationally intensive step of the physical retrieval algorithm. Interestingly, an analysis of the change in AERI observations' information content with respect to Jacobians revealed that the AERIoe algorithm's performance presents negligible dependence on these metrics. Thus, the Jacobian matrix could remain unchanged when the variation in the atmospheric state is small in the retrieval process to reduce the most time-consuming computation. On the basis of the above findings, a fast physical–iterative retrieval algorithm was proposed by adaptively recalculating Jacobians in keeping with the changes in the atmospheric state. Experiments with synthetic observations demonstrate that the proposed method experiences an average reduction in retrieval time by an impressive 59 % compared to the original AERIoe algorithm while achieving maximum root-mean-square errors of less than 0.95 K and 0.22 log(ppmv) for heights below 3 km for the temperature and water vapor profile, respectively. Further analyses revealed that the fast-retrieval algorithm reached an acceptable convergence rate of 98.7 %, marginally lower than AERIoe's 99.9 % convergence rate for the 826 cases used in this study.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Lyapunov-Based Iterative Learning of the Region of Attraction for Autonomous Systems

This presentation introduces a novel algorithm for estimating the region of attraction of equilibrium points for nonlinear discrete-time autonomous systems. The method iteratively expands an initial estimate of the region of attraction by constructing unions of sublevel sets of learned functions parametrized as neural networks. Unlike conventional techniques that rely on a single global Lyapunov function, the proposed approach provides a collection of local Lyapunov-like functions, enabling richer representations and potentially larger region of attraction estimates. These functions are trained using sampled state-space data, and their Lipschitz continuity ensures that desirable properties extend beyond the training samples. The devised strategy is tested via numerical simulations, demonstrating the effectiveness of the proposed approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Mode Conversion Losses in Expansion Units for ITER ECH Transmission Lines

The ITER electron cyclotron heating transmission lines will consist of 63.5 mm diameter corrugated waveguides, each carrying 1 MW of 170 GHz microwaves. These transmission lines must include expansion units to accommodate expansion and contraction along the path from the gyrotron microwave sources to the tokamak. A numerical mode matching code has been developed to calculate power losses due to mode conversion of the operating mode, HE11, to higher order modes as a result of the radial discontinuities in a sliding joint. Two expansion unit designs were evaluated, a simple gap expansion unit and a more complex tapered expansion unit. The gap expansion unit demonstrated loss that oscillated rapidly with expansion length, due to trapped modes within the unit. The tapered expansion unit has been shown to effectively suppress these trapped modes at the expense of increased fabrication complexity. In a gap expansion unit, for a waveguide step size of 2.5 mm, loss can be kept below 0.1% to a maximum expansion length of 17 mm. Expansion units without corrugation on interior walls were also evaluated. Expansion units that lack corrugations are found to increase mode trapping within the units, though not beyond useful application. The mode matching code developed in this paper was also used to estimate mode conversion loss in vacuum pumpouts for the ECH lines; the estimated loss was found to be negligibly small.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Reassessing energy deposition for the ITER 5 MA vertical displacement event with an improved DINA model

The beryllium (Be) main chamber wall interaction during a 5 MA/1.8 T upward, unmitigated VDE scenario, first analysed in [J. Coburn et al., Phys. Scr. T171 (2020) 014076] for ITER, has been re-evaluated using the latest energy deposition analysis software. Updates to the DINA disruption model are summarized, including an improved numerical convergence for the 0D power balance, limitations on the safety factor within the plasma core, and the choice to maintain a constant plasma +halo poloidal cross-section. Such updates result in a broad halo region and higher radiated power fractions compared to previous models. The new scenario lasts for ~75 ms and deposits ~29 MJ of energy, with the radial distribution of parallel heat flux q‖(r)resembling an exponential falloff with an effective λ_q=75-198 mm. A maximum halo width w_h of 0.52 m at the outboard midplane is observed. SMITER field line tracing and energy deposition simulations calculate a q_{⊥,max} of ~83 MW/m^2 on the upper first wall panels (FWP). Heat transfer calculations with the MEMOS-U code show that the FWP surface temperature reaches ~1000 K, well below the Be melt threshold. Variations of this 5 MA scenario with Be im-purity densities from 0 to 3∙10^19 m^-3 also remain below the melt threshold despite differences in energy deposition and duration. These results are in contrast to the early study which predicted melt damage to the first wall [J. Coburn et al., Phys. Scr. T171 (2020) 014076], and emphasize the importance of accurate models for the halo width w_h and the heat flux distribution q‖(r)within that halo width. The 2020 halo model in DINA has been compared with halo current experiments on COMPASS, JET, and Alcator C-Mod, and the preliminary results build confidence in the broad halo width predictions. Results for the 5 MA VDE are compared with those for a 15 MA equivalent, generated using the new DINA model. At the higher current, significant melting of the upper FWP is to be expected.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

Neutron imaging with coded sources: new challenges and the implementation of a simultaneous iterative reconstruction technique

The limitations in neutron flux and resolution (L/D) of current neutron imaging systems can be addressed with a Coded Source Imaging system with magnification (xCSI). More precisely, the multiple sources in an xCSI system can exceed the flux of a single pinhole system for several orders of magnitude, while maintaining a higher L/D with the small sources. Moreover, designing for an xCSI system reduces noise from neutron scattering, because the object is placed away from the detector to achieve magnification. However, xCSI systems are adversely affected by correlated noise such as non-uniform illumination of the neutron source, incorrect sampling of the coded radiograph, misalignment of the coded masks, mask transparency, and the imperfection of the system Point Spread Function (PSF). We argue that a model-based reconstruction algorithm can overcome these problems and describe the implementation of a Simultaneous Iterative Reconstruction Technique algorithm for coded sources. Design pitfalls that preclude a satisfactory reconstruction are documented.

Santos-Villalobos, Hector J↗
DOE OSTI2013

Time parallelization of advanced operation scenario simulations of ITER plasma

This work demonstrates that simulations of advanced burning plasma operation scenarios can be successfully parallelized in time using the parareal algorithm. CORSICA - an advanced operation scenario code for tokamak plasmas is used as a test case. This is a unique application since the parareal algorithm has so far been applied to relatively much simpler systems except for the case of turbulence. In the present application, a computational gain of an order of magnitude has been achieved which is extremely promising. A successful implementation of the Parareal algorithm to codes like CORSICA ushers in the possibility of time efficient simulations of ITER plasmas.

Samaddar, D.↗
DOE OSTI2014

Normal operation and maintenance safety lessons from the ITER US PbLi test blanket module program for a US FNSF and DEMO

A leading power reactor breeding blanket candidate for a fusion demonstration power plant (DEMO) being pursued by the US Fusion Community is the Dual Coolant Lead Lithium (DCLL) concept. The safety hazards associated with the DCLL concept as a reactor blanket have been examined in several US design studies. These studies identify the largest radiological hazards as those associated with the dust generation by plasma erosion of plasma blanket module first walls, oxidation of blanket structures at high temperature in air or steam, inventories of tritium bred in or permeating through the ferritic steel structures of the blanket module and blanket support systems, and the 210Po and 203Hg produced in the PbLi breeder/coolant. What these studies lack is the scrutiny associated with a licensing review of the DCLL concept. An insight into this process was gained during the US participation in the International Thermonuclear Experimental Reactor (ITER) Test Blanket Module (TBM) Program. In this paper we discuss the lessons learned during this activity and make safety proposals for the design of a Fusion Nuclear Science Facility (FNSF) or a DEMO that employs a lead lithium breeding blanket.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Development of Acoustic Model-Based Iterative Reconstruction Technique for Thick-Concrete Imaging

Ultrasound signals have been used extensively for non-destructive evaluation (NDE). However, typical reconstruction techniques, such as the synthetic aperture focusing technique (SAFT), are limited to quasi-homogenous thin media. New ultrasonic systems and reconstruction algorithms are in need for one-sided NDE of non-homogenous thick objects. An application example space is imaging of reinforced concrete structures for commercial nuclear power plants (NPPs). These structures provide important foundation, support, shielding, and containment functions. Identification and management of aging and degradation of concrete structures is fundamental to the proposed long-term operation of NPPs. Another example is geothermal and oil/gas production wells. These multi-layered structures are composed of steel, cement, and several types of soil and rocks. Ultrasound systems with greater penetration range and image quality will allow for better monitoring of the well s health and prediction of high-pressure hydraulic fracturing of the rock. These application challenges need to be addressed with an integrated imaging approach, where the application, hardware, and reconstruction software are highly integrated and optimized. Therefore, we are developing an ultrasonic system with Model-Based Iterative Reconstruction (MBIR) as the image reconstruction backbone. As the first implementation of MBIR for ultrasonic signals, this paper document the first implementation of the algorithm and show reconstruction results for synthetically generated data.

Almansouri, Hani↗