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Optimizing X-ray Computed Tomography Settings for Dimensional Metrology Using 2D Image Analysis
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Multi-core and many-core shared-memory parallel raycasting volume rendering optimization and tuning
Given the computing industry trend of increasing processing capacity by adding more cores to a chip, the focus of this work is tuning the performance of a staple visualization algorithm, raycasting volume rendering, for shared-memory parallelism on multi-core CPUs and many-core GPUs. Our approach is to vary tunable algorithmic settings, along with known algorithmic optimizations and two different memory layouts, and measure performance in terms of absolute runtime and L2 memory cache misses. Our results indicate there is a wide variation in runtime performance on all platforms, as much as 254% for the tunable parameters we test on multi-core CPUs and 265% on many-core GPUs, and the optimal configurations vary across platforms, often in a non-obvious way. For example, our results indicate the optimal configurations on the GPU occur at a crossover point between those that maintain good cache utilization and those that saturate computational throughput. This result is likely to be extremely difficult to predict with an empirical performance model for this particular algorithm because it has an unstructured memory access pattern that varies locally for individual rays and globally for the selected viewpoint. Our results also show that optimal parameters on modern architectures are markedly different from those in previous studies run on older architectures. In addition, given the dramatic performance variation across platforms for both optimal algorithm settings and performance results, there is a clear benefit for production visualization and analysis codes to adopt a strategy for performance optimization through auto-tuning. These benefits will likely become more pronounced in the future as the number of cores per chip and the cost of moving data through the memory hierarchy both increase.
Multi-core and Many-core Shared-memory Parallel Raycasting Volume Rendering Optimization and Tuning
Given the computing industry trend of increasing processing capacity by adding more cores to a chip, the focus of this work is tuning the performance of a staple visualization algorithm, raycasting volume rendering, for shared-memory parallelism on multi-core CPUs and many-core GPUs. Our approach is to vary tunable algorithmic settings, along with known algorithmic optimizations and two different memory layouts, and measure performance in terms of absolute runtime and L2 memory cache misses. Our results indicate there is a wide variation in runtime performance on all platforms, as much as 254% for the tunable parameters we test on multi-core CPUs and 265% on many-core GPUs, and the optimal configurations vary across platforms, often in a non-obvious way. For example, our results indicate the optimal configurations on the GPU occur at a crossover point between those that maintain good cache utilization and those that saturate computational throughput. This result is likely to be extremely difficult to predict with an empirical performance model for this particular algorithm because it has an unstructured memory access pattern that varies locally for individual rays and globally for the selected viewpoint. Our results also show that optimal parameters on modern architectures are markedly different from those in previous studies run on older architectures. And, given the dramatic performance variation across platforms for both optimal algorithm settings and performance results, there is a clear benefit for production visualization and analysis codes to adopt a strategy for performance optimization through auto-tuning. These benefits will likely become more pronounced in the future as the number of cores per chip and the cost of moving data through the memory hierarchy both increase.
Assessment of verification and validation status - RELAP5-3D and RAVEN
The United States nuclear industry is facing a strong challenge to ensure maximum safety while enhancing economic benefit. Safety is a key parameter to all aspects related to light water reactor (LWR) nuclear power plants (NPPs), especially cost savings. Since the goal is to extend the lifetimes of these NPPs, the traditional deterministic safety concept may not guarantee a current economic asset. The Light Water Reactor Sustainability (LWRS) Program has been promoting a wide range of research and development (R&D) in this field to maximize the safety, economics, and performance of these NPPs through improved scientific understanding. One of the best practices to achieve this goal is to identify and optimize safety margins, which can lead to cost reduction. To do this, under the LWRS framework, the Risk-Informed Systems Analysis (RISA) Pathway will focus on the optimization of safety margin and minimization of uncertainties to ensure both safety and economics at the highest level. The RISA Pathway will provide enhanced capabilities for analyzing and characterizing LWR systems performance by developing and demonstrating methods, tools, and data to enable risk-informed margins management (RIMM). The goals of the RISA Pathway are twofold: (1) deploy the risk-informed tools and methods that enable better representation of safety margins and factors that contribute to cost and safety; and (2) conduct advanced risk assessment applications with industry to support margin management strategies that enable more cost-effective plant operation. The tools and methods provided by the RISA Pathway will support effective margin management for both active and passive safety systems, structures, and components (SSC) of an NPP. The tools and methods used in the RISA Pathway should have high confidence and highest technical maturity for and implementation to industry at its current setting. They should also have a capability to support risk-informed decision making for both probabilistic and deterministic elements of safety. The RISA Pathway will, therefore, perform a comprehensive assessment of verification and validation (V&V) status of RISA Toolkit to enhance credibility RISA Toolkit which be used by industry. This report summarizes assessment technical maturity of RISA thermal-hydraulics accident analysis code RELAP5-3D and multi-purpose probabilistic risk analysis tool RAVEN V&V status including specific information of the tool such as capability and features, quality assurance program, developer/independent V&V record, separation/integral tests history, user documents, and feedback.
Parametric Optimization Problem Formulation for Connected Hybrid Electric Vehicles using Neural Network based Equivalent Model
The dynamics of powertrain control systems are complicated and involve both nonlinear plant model and control functionalities, albeit they are well defined and formulated using first principle approaches. This constitutes difficulties in exploring implementable optimal tuning rules for some selected control parameters using vehicle-to-vehicle (V2V) communications. This paper presents a way to use neural networks (NN) to represent the problem of parameter tuning for optimizing fuel consumption. For this purpose, physical modelling and validation have been firstly performed for the closed loop powertrain system of the concerned vehicle for some given driving cycles. This is then followed by the sensitivity analysis that selects most influential control parameters to optimize. Using the data generated from the obtained physical models, an equivalent NN formulation has finally been obtained that gives simple yet unified objectives and constraints ready to be used to solve the optimization problem that produces optimal tuning rules for the selected control parameters to minimize fuel consumption.
Commercialization of Medium Voltage HTS Triax™ Cable Systems
The original project scope that was established in 2007 aimed to install a 1,700 meter (1.1 mile) medium voltage HTS Triax™ cable system into the utility grid in New Orleans, LA. In 2010, however, the utility partner withdrew from the project, so the 1,700 meter cable installation was cancelled and the scope of work was reduced. The work then concentrated on the specific barriers to commercialization of HTS cable technology. The modified scope included long-length HTS cable design and testing, high voltage factory test development, optimized cooling system development, and HTS cable life-cycle analysis. In 2012, Southwire again analyzed the market for HTS cables and deemed the near term market acceptance to be low. The scope of work was further reduced to the completion of tasks already started and to testing of the existing HTS cable system in Columbus, OH. The work completed under the project included: • Long-length cable modeling and analysis • HTS wire evaluation and testing • Cable testing for AC losses • Optimized cooling system design • Life cycle testing of the HTS cable in Columbus, OH • Project management. The 200 meter long HTS Triax™ cable in Columbus, OH was incorporated into the project under the initial scope changes as a test bed for life cycle testing as well as the site for an optimized HTS cable cooling system. The Columbus cable utilizes the HTS Triax™ design, so it provided an economical tool for these of the project tasks.
Computationally Guided Investigation of the Optical Spectra of Pure β-UO 3
Single-phase β-UO 3 is synthesized by flash heating UO 2 (NO 3 )·6H 2 O in air to 450 °C and annealing for 60 h under the same conditions. For the first time, we report the Raman spectra of pure β-UO 3 . To facilitate the assignment of Raman and infrared vibrational modes, we use density functional theory with density functional perturbation theory. By employing a novel analysis scheme that includes the mode frequencies as well as a quantitative analysis of the mode eigenvectors, we assign the observed spectral features to individual chemical modes. In particular, the density functional theory optimized structure, observed Raman spectrum, and eigenvector analysis suggest the presence of four crystallographically distinct uranyl ions, one more than has previously been suggested.
Evaluation and Optimization of Snow Albedo Scheme in Noah-MP Land Surface Model Using In Situ Spectral Observations in the Colorado Rockies
The Biosphere-Atmosphere Transfer Scheme (BATS) ground snow albedo algorithm is commonly used in land-surface models (LSM), weather forecasting and research applications. This study addresses key uncertainties in BATS simulated ground snow albedo within the Noah-MP LSM framework through evaluation and optimization of the Noah-MP BATS ground snow albedo formulation using 2-band (visible and near-infrared (NIR)) in situ albedo observations at Rocky Mountain field stations. The Noah-MP BATS ground snow albedo scheme is extremely sensitive to its input parameters. Namely, an ensemble generated by varying BATS input parameters within potentially plausible ranges provides an average daily range (maximum ensemble member minus minimum ensemble member) of ground snow albedo exceeding 0.45 in visible and NIR bands. Parameter optimization improves agreement between simulated and in situ observed ground snow albedo in visible, NIR and broadband spectrums. Importantly, optimized parameters result in reduced biases relative to observed fresh-snow albedo and better agreement with observed albedo decay. Our analysis across different sites supports that the optimized BATS ground snow albedo parameters are appropriate to transfer in space and time, at least within the region studied (the central-southern Rocky Mountains). The primary error source remaining after parameter optimization is that observed fresh-snow albedo is highly variable, particularly in the NIR spectrum, whereas BATS fresh-snow albedo is constant, an issue which requires further investigation. This study shows significant correlations between observed fresh-snow albedo and surface meteorological conditions (e.g., downward shortwave radiation and temperature) which can support future model development that attempts to include a time-varying formulation for fresh-snow albedo.
Post-assembly magnetization of a 100 kW high speed permanent magnet rotor
A post-assembly magnetizing fixture has been designed and successfully used to magnetize the rotor of a 100 kW high speed permanent magnet synchronous motor. The rotor is a solid cylinder with outer diameter of 80 mm and total length of 515 mm. The permanent magnet material is samarium-cobalt (Sm{sub 2}Co{sub 17}) with saturation magnetizing field of 6 T. The mechanical stability of the magnetizing fixture has been studied as well as the general design methodology. The magnetizing coil is subdivided in order to reduce the electromagnetic force, and the coils are separately reinforced in different ways. The electromagnetic and structural optimization is performed by finite element analysis and verified by experiments.
Risk-Informed MultiPphysics BestEestimate Plus Uncertainties (BEPU) Application Development of RELAP5-3D Perturbation Model
The United States nuclear industry is facing a strong challenge to ensure maximum safety while enhancing economic benefit. Safety is a key parameter to all aspects related to light water reactor (LWR) nuclear power plants (NPPs), especially cost savings. Since the goal is to extend the lifetimes of these NPPs, the traditional deterministic safety concept may not guarantee a current economic asset. The Light Water Reactor Sustainability (LWRS) Program has been promoting a wide range of research and development (R&D) in this field to maximize the safety, economics, and performance of these NPPs through improved scientific understanding. One of the best practices to achieve this goal is to identify and optimize safety margins, which can lead to cost reduction. To do this, under the LWRS framework, the Risk-Informed Systems Analysis (RISA) Pathway will focus on the optimization of safety margin and minimization of uncertainties to ensure both safety and economics at the highest level. The RISA Pathway will provide enhanced capabilities for analyzing and characterizing LWR systems performance by developing and demonstrating methods, tools, and data to enable risk-informed margins management (RIMM). The goals of the RISA Pathway are twofold: (1) deploy the risk-informed tools and methods that enable better representation of safety margins and factors that contribute to cost and safety; and (2) conduct advanced risk assessment applications with industry to support margin management strategies that enable more cost-effective plant operation. The tools and methods provided by the RISA Pathway will support effective margin management for both active and passive safety systems, structures, and components (SSC) of an NPP. The tools and methods used in the RISA Pathway should have high confidence and highest technical maturity for and implementation to industry at its current setting. They should also have a capability to support risk-informed decision making for both probabilistic and deterministic elements of safety. The RISA Pathway will, therefore, perform a comprehensive assessment of verification and validation (V&V) status of RISA Toolkit to enhance credibility RISA Toolkit which be used by industry. This report summarizes RELAP5-3D development activities for best estimated and uncertainty (BEPU) capability to support ongoing RISA Pathway pilot projects for risk informed uncertainty quantification applications. Work scope includes (1) development of initial perturbation model for selected closure laws and (2) testing of suitable probability distribution functions (PDF) for the selected correlations. Developed BEPU modules are tested with selected separate effect cases and compared with conventional thermal-hydraulics model.
Flow rate optimization for a small liquid argon system at Fermilab.
This analysis highlights the dominant role of pressure loss in filter disks, emphasizing its crucial consideration during the design phase to ensure optimal fluid flow. Additionally, the significance of vapor quality at the transfer line inlet is identified as a key factor impacting the fill rate. Reducing inlet vapor quality and exploring the use of subcooled liquid are recommended approaches to enhance system performance.
Phase field method to optimize dielectric devices for electromagnetic wave propagation
We discuss a phase field method for shape optimization in the context of electromagnetic wave propagation. The proposed method has the same functional capabilities as the level set method for shape optimization. The first advantage of the method is the simplicity of computation, since extra operations such as re-initialization of functions are not required. The second is compatibility with the topology optimization method due to the similar domain representation and the sensitivity analysis. Structural shapes are represented by the phase field function defined in the design domain, and this function is optimized by solving a time-dependent reaction diffusion equation. The artificial double-well potential function used in the equation is derived from sensitivity analysis. We study four types of 2D or 2.5D (axisymmetric) optimization problems. Two are the classical problems of photonic crystal design based on the Bloch theory and photonic crystal wave guide design, and two are the recent topics of designing dielectric left-handed metamaterials and dielectric ring resonators.
Risk-averse optimal control of semilinear elliptic PDEs
In this paper, we consider the optimal control of semilinear elliptic PDEs with random inputs. These problems are often nonconvex, infinite-dimensional stochastic optimization problems for which we employ risk measures to quantify the implicit uncertainty in the objective function. In contrast to previous works in uncertainty quantification and stochastic optimization, we provide a rigorous mathematical analysis demonstrating higher solution regularity (in stochastic state space), continuity and differentiability of the control-to-state map, and existence, regularity and continuity properties of the control-to-adjoint map. Our proofs make use of existing techniques from PDE-constrained optimization as well as concepts from the theory of measurable multifunctions. We illustrate our theoretical results with two numerical examples motivated by the optimal doping of semiconductor devices.
Cost- and Risk-Based Seismic Design Optimization of Nuclear Power Plant Safety Systems
Seismic analysis, design, and qualification of systems, structures, and components (SSCs) is a significant contributor to the capital cost of a nuclear power plant. To reduce capital costs of advanced nuclear power plants and make commercial nuclear energy more competitive, innovations are needed in their structural design and construction, and not just in the reactor core and associated systems. Seismic isolation has been identified as an important cost-cutting technology that enables standardization of equipment across various sites. This paper develops and demonstrates a cost- and risk-based seismic design optimization of a representative safety system in a nuclear power plant with the dual goals of minimizing overnight capital cost and meeting safety goals. The design optimization can also include component seismic isolation, in which case, the optimized design includes a set of equipment that needs to be seismically isolated to minimize capital cost. The open-source codes MASTODON and Dakota are used for seismic probabilistic risk assessment and design optimization, respectively. A generic nuclear facility with a safety system comprising SSCs that are common to nuclear power plants is considered for the demonstration of the design optimization and is assumed to be located at the Idaho National Laboratory site. Generic costs and seismic design cost functions are assumed for the SSCs of the safety system. The sum of the costs of the SSCs is minimized in the optimization process, while the risk of failure of the safety system is provided as a constraint. Furthermore, results show that the optimization process reduces capital costs significantly while automatically prioritizing the safety of SSCs that contribute most to the risk of the safety system.
Thermoluminescence glow curve analysis and CGCD method for erbium doped CaZrO{sub 3} phosphor
The manuscript report the synthesis, thermoluminescence study at fixed concentration of Er{sup 3+} (1 mol%) doped CaZrO{sub 3} phosphor. The phosphors were prepared by modified solid state reaction method. The powder sample was characterized by thermoluminescence (TL) glow curve analysis. In TL glow curve the optimized concentration in 1mol% for UV irradiated sample. The kinetic parameters were calculated by computerized glow curve deconvolution (CGCD) techniaue. Trapping parameters gives the information of dosimetry loss in prepared phosphor and its usability in environmental monitoring and for personal monitoring. CGCD is the advance tool for analysis of complicated TL glow curves.
Oxygen Isotope Exponent as a Function of the Numbers of CuO{sub 2} Layers in Optimally Doped Superconductors Bi{sub 2}Sr{sub 2}Ca{sub n−1}Cu{sub n}O{sub 2n+4+δ} (n = 1, 2, 3)
In this study, we carried out an analysis of the oxygen isotope exponent in optimally doped Bi{sub 2}Sr{sub 2}Ca{sub n−1} Cu{sub n}O{sub 2n+4+δ} ( n = 1,2,3). The expression in the strong electron-phonon coupling approach for the isotope exponent taking into account numbers of CuO{sub 2} layers in the unit cell was obtained. It is shown that increasing numbers of CuO{sub 2} layers lead to the decreasing of the isotope exponent, which is in agreement with available experimental data.