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Results for “iterative analysis”

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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Integration of the Full Tokamak Reference Model with the Complex Model for ITER Neutronic Analysis

The ITER International Organization has developed a number of reference Monte Carlo N-Particle (MCNP) models including the tokamak machine C-model, the Tokamak Complex model, and the neutral beam injection (NBI) systems model. The Tokamak Complex model primarily describes building structures beyond the bioshield. Representation of the tokamak and its systems are not included in this model. The Oak Ridge National Laboratory Radiation Transport Group has conducted two ITER neutronic analysis model integrations: (1) integration of the tokamak C-model with the Tokamak Complex model for shutdown dose rate characterization in Port Cell 16 at level B1, and (2) integration of the NBI model with the Tokamak Complex model for estimating the spatial distribution of biological dose rate at levels L1, L2, and L3 of the Tokamak Complex. The integrated models were further extended to include models of system components that are essential to the neutronic analyses. Furthermore, this paper presents the approach and computer tools used to integrate existing reference models, describes the additional design details implemented in the integrated models, and provides representative neutronic calculations based on the extended models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Non-iterative characteristics analysis for high-pressure ramp loading

Here in the canonical ramp compression experiment, a smoothly increasing load is applied to the surface of the sample, and the particle velocity history is measured at two or more different distances into the sample, at interfaces where the surface of the sample can be probed. The velocity histories are used to deduce a stress-density relation, usually using iterative Lagrangian analysis to account for the perturbing effect of the impedance mismatch at the interface. In that technique, a stress-density relation is assumed in order to correct for the perturbation and is adjusted until it becomes consistent with the deduced stress-density relation. This process is subject to the usual difficulties of nonlinear optimization, such as the existence of local minima (sensitivity to the initial guess), possible failure to converge, and relatively large computational effort. We show that, by considering the interaction of successive characteristics reaching a free surface, the stress-density relation can be deduced directly by recursion rather than iteration. This calculation is orders of magnitude faster than iterative analysis and does not require an initial guess. Direct recursion may be less suitable for very noisy data, but it was robust when applied to trial data. The stress-density relation deduced was identical to the result from iterative Lagrangian analysis.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Investigations into alternative radiation transport codes for ITER neutronics analysis

As radiation transport models for ITER become increasingly complex, the use of traditional constructive solid geometry (CSG) modelling approaches such as MCWNP presents significant disadvantages during model creation and integration. Studies were performed to assess the capabilities of alternative mesh-based neutronics workflows offered by the MCNP, DAG-MCNP and Serpent-2 codes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Neutronics Analysis for ITER Diagnostic Generic Upper Port Plug

This paper presents new results of neutronics analysis performed for the updated design of the ITER Diagnostic Generic Upper Port Plug (DGUPP). Such analysis is performed regularly during the development of the ITER Ports design. Neutronics analysis is an important step in support of the development of ITER components irradiated by 14 MeV neutrons generated in D-T fusion thermonuclear reactions. The neutrons are born in the ITER tokamak plasma chamber and then impinge on the surrounding blanket and port plugs, after that they diffuse through shielding material of vacuum vessel components or could stream through the diagnostic channels and assembly gaps far away from plasma up to the bio-shield and in a small amount beyond it. While ITER machine is in operation it is inaccessible, after the shut-down it is planned to provide personnel access to the Upper Port Inter-Space Structure (UP ISS) behind the Port Plug via the corridors. Neutrons activate the ITER materials and those radioactive materials emit decay gammas during the shut-down causing a Shut-Down Dose Rate (SDDR) field distributed all around the activated materials. Decay gammas could also stream through the void channels. That emphasizes the need for calculation of decay gamma transport in evaluations of SDDR, which is reflected in the use of transport - activation interface code described in Section of Computational Modelling. The assessment of radiation environment (fluxes and SDDR) at DGUPP was focused on the port back-side area of UP ISS, where personnel access is planned along the ISS maintenance corridors. Minimization of SDDR at the front part of the ISS maintenance corridors was the target value for optimization of the DGUPP shielding and analysis of related neutronics effects. Following the dose ALARA (As Low As Reasonably Achievable) principle, every possibility to reduce SDDR should be investigated, emphasizing the importance of this analysis. The challenges of such analysis are inextricably connected with the engineering complexity of the ITER machine, with integration of many diagnostics systems having channels and gaps inside the ITER ports. Those gaps result in radiation streaming and negatively affect the shielding performance of the port plugs. The computational complication is caused by the need to model precisely the ITER geometry and then to run deep penetrating radiation transport in the substantially heterogenic toroidal geometry of ITER large-size tokamak, with 30 m height and diameter of its bio-shield. The whole mass of Upper Port Plug (UPP) could be up to 25 tons and it must be very precisely positioned inside the port opening in blanket and Vacuum Vessel. Facing the engineering challenges for the assembly of DGUPP, there were proposed two Project Change Requests (PCRs) No. 439 and 709 concerning the design updates of UPP/blanket interface and its remote handling.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2017

An iterative forward analysis technique to determine the equation of state of dynamically compressed materials

Here, we developed an iterative forward analysis (IFA) technique with the ability to use hydrocode simulations as a fitting function for analysis of dynamic compression experiments. The IFA method optimizes over parameterized quantities in the hydrocode simulations, breaking the degeneracy of contributions to the measured material response. Velocity profiles from synthetic data generated using a hydrocode simulation are analyzed as a first-order validation of the technique. We also analyze multiple magnetically driven ramp compression experiments on copper and compare with more conventional techniques. Excellent agreement is obtained in both cases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Parametric Thermal and Flow Analysis of ITER Diagnostic Shield Module

As part of the diagnostic port plug assembly, the ITER Diagnostic Shield Module (DSM) is designed to provide mechanical support and the plasma shielding while allowing access to plasma diagnostics. Thermal and hydraulic analysis of the DSM was performed using a conjugate heat transfer approach, in which heat transfer was resolved in both solid and liquid parts, and simultaneously, fluid dynamics analysis was performed only in the liquid part. ITER Diagnostic First Wall (DFW) and cooling tubing were also included in the analysis. This allowed direct modeling of the interface between DSM and DFW, and also direct assessment of the coolant flow distribution between the parts of DSM and DFW to ensure DSM design meets the DFW cooling requirements. Design of the DSM included voids filled with Boron Carbide pellets, allowing weight reduction while keeping shielding capability of the DSM. These voids were modeled as a continuous solid with smeared material properties using analytical relation for thermal conductivity. Results of the analysis lead to design modifications improving heat transfer efficiency of the DSM. Furthermore, the effect of design modifications on thermal performance as well as effect of Boron Carbide will be presented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Electromagnetic Analysis of ITER Electron Cyclotron Emission Model

The ITER electron cyclotron emission (ECE) diagnostic system is located at diagnostics shielding module 2 (DSM2), equatorial port 9 (EP9), to measure electron temperature profile and electron temperature fluctuations, and also assess nonthermal electron distributions via the oblique view. Therefore, ECE has both radial and oblique views with two hot sources for calibration and two couples of mirrors for two different optical views. It shall receive that the large electromagnetic (EM) loads up to 100-MN/m3 force density due to the eddy currents on the copper mirrors generated by the short transient plasma disruption. The simplified EM analysis model using magnetic field ( B ) data and flux variations (dB/dt) method based on the worst case of plasma disruption, MD_DW_EXP16MS_CATIII, has been developed to calculate the force and moments for each ECE component and support structure for EP9 DSM2 Bay2 and Bay3. The B and dB/dt methods use the constant B and dB/dt assumed for each local bay space, but the real B and dB/dt are basically varied along the radial direction of each bay. The complex global model with the local ECE components and support structure using Maxwell transient has been developed to do EM analysis to compare the results of the B and dB/dt models. The volumetric EM force density of the whole ECE components and support structure can be used for the subsequent structural analysis. In conclusion, combined with the thermal and nuclear loads and seismic and initial loads, the ECE integration analysis can be finalized for the operation case.

Fang, J. [Princeton Plasma Physics Laboratory (PPP↗
DOE OSTI2025

Electromagnetic Analysis of ITER Electron Cyclotron Emission Components and Support Structures for the Preliminary Design Review

The ITER electron cyclotron emission (ECE) diagnostic system is located at Design Shield Module (DSM) 2, Equatorial Port (EP) 9 to measure electron temperature profile and electron temperature fluctuations and also to assess nonthermal electron distributions via the oblique view. Therefore, ECE has both radial and oblique views with two couples of mirrors for two different optical views. This ECE diagnostic system shall be exposed to significant power due to unabsorbed electron cyclotron heating power in the plasma. It shall also receive large electromagnetic (EM) loads up to 100 MN/m 3 force density due to the eddy currents generated by the short 16-ms transient plasma disruption. The global EM models of EP12 and EP11 with the worst case of plasma disruption Major Disruption Downward Exponential 16 ms Category III (MD_DW_EXP16MS_CATIII) have been provided by ITER. However, the support structure for these critical components, including four mirrors, is still under the design and development phase, especially during the period of preliminary design reviews (PDRs). For those small in-vessel components that are not modeled explicitly for the PDRs, we can extract the magnetic field (B) data and flux variations (dB/dt) at those locations from the global model and then use the B and dB/dt method to calculate the eddy currents, EM forces, and torques on those components in the local submodels. In conclusion, this paper will present the detailed PDR EM analysis results of the ECE components and support structures.

Electromagnetic↗
DOE OSTI2019

Nonlinear Diffusion Acceleration of the Least-Squares Transport Equation in Geometries with Voids

In this paper we show the extension of the Nonlinear-Diffusion Acceleration (NDA) to geometries containing small voids using a weighted least-squares (WLS) high order equation. Even though the WLS equation is well defined in voids, the low-order drift diffusion equation was not defined in materials with a zero cross section. This paper derives the necessary modifications to the NDA algorithm. We show that a small change to the NDA closure term and a non-local definition of the diffusion coefficient solve the problems for voids regions. These changes do not affect the algorithm for optical thick material regions, while making the algorithm well defined in optically thin ones. We use a Fourier analysis to perform an iterative analysis to confirm that the modifications result in a stable and efficient algorithm. Numerical results of our method will be presented in the second part of the paper. We test this formulation with a small, one-dimensional test problem. Additionally we present results for a modified version of the C5G7 benchmark containing voids as a more complex, reactor like problem. We compared our results to PDT, Texas A&M’s transport code, utilizing a first order discontinuous formulation as reference and the self-adjoint angular flux equation with void treatment (SAAFτ ), a different second order form. The results indicate, that the NDA WLS performed comparably or slightly worse then the asymmetric SAAFτ , while maintaining a symmetric discretization matrix.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Ground-Truth Prediction to Accelerate Soft-Error Impact Analysis for Iterative Methods

Understanding the impact of soft errors on applications can be expensive. Often, it requires an extensive error injection campaign involving numerous runs of the full application in the presence of errors. In this paper, we present a novel approach to arriving at the ground truth--the true impact of an error on the final output--for iterative methods by observing a small number of iterations to learn deviations between normal and error-impacted execution. We develop a machine learning based predictor for three iterative methods to generate ground-truth results without running them to completion for every error injected. We demonstrate that this approach achieves greater accuracy than alternative prediction strategies, including three existing soft error detection strategies. We demonstrate the effectiveness of the ground truth prediction model in evaluating vulnerability and the effectiveness of soft error detection strategies in the context of iterative methods.

iterative methods, failure prediction, Soft error ↗
DOE OSTI2021

Dakota A Multilevel Parallel Object-Oriented Framework for Design Optimization Parameter Estimation Uncertainty Quantification and Sensitivity Analysis (V.6.14) (Theory Manual)

The Dakota toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the Dakota toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a theoretical manual for selected algorithms implemented within the Dakota software. It is not intended as a comprehensive theoretical treatment, since a number of existing texts cover general optimization theory, statistical analysis, and other introductory topics. Rather, this manual is intended to summarize a set of Dakota-related research publications in the areas of surrogate-based optimization, uncertainty quantification, and optimization under uncertainty that provide the foundation for many of Dakota's iterative analysis capabilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Theory Manual (V.6.15)

The Dakota toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the Dakota toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a theoretical manual for selected algorithms implemented within the Dakota software. It is not intended as a comprehensive theoretical treatment, since a number of existing texts cover general optimization theory, statistical analysis, and other introductory topics. Rather, this manual is intended to summarize a set of Dakota-related research publications in the areas of surrogate-based optimization, uncertainty quantification, and optimization under uncertainty that provide the foundation for many of Dakota's iterative analysis capabilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Dakota A Multilevel Parallel Object-Oriented Framework for Design Optimization Parameter Estimation Uncertainty Quantification and Sensitivity Analysis: Version 6.12 Theory Manual

The Dakota toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the Dakota toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a theoretical manual for selected algorithms implemented within the Dakota software. It is not intended as a comprehensive theoretical treatment, since a number of existing texts cover general optimization theory, statistical analysis, and other introductory topics. Rather, this manual is intended to summarize a set of Dakota-related research publications in the areas of surrogate-based optimization, uncertainty quantification, and optimization under uncertainty that provide the foundation for many of Dakota's iterative analysis capabilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 6.13 Theory Manual

The Dakota toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the Dakota toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a theoretical manual for selected algorithms implemented within the Dakota software. It is not intended as a comprehensive theoretical treatment, since a number of existing texts cover general optimization theory, statistical analysis, and other introductory topics. Rather, this manual is intended to summarize a set of Dakota-related research publications in the areas of surrogate-based optimization, uncertainty quantification, and optimization under uncertainty that provide the foundation for many of Dakota's iterative analysis capabilities.

97 MATHEMATICS AND COMPUTING↗