Results for “ORIENTATION” — Page 61

DOE OSTI2023

Physically-based control-oriented modeling for turbocharged stoichiometric spark-ignited engine with cooled EGR and flexible VVT systems

Accurate estimation and prediction of engine gas exchange system and in-cylinder conditions are critical for spark-ignited engine control and diagnostic algorithm development. In this paper, a physically-based, control-oriented model for a 2.8 l turbocharged, variable valve timing (VVT) and low pressure (LP) exhaust gas recirculation (EGR)-utilizing SI engine was developed. The model includes the impact of modulation to any combination of 10 actuators, including the throttle valve, compressor bypass valve, fueling rate, waste-gate, LP EGR valve, number of deactivated cylinders, intake valve open (IVO) timing, intake valve close (IVC) timing, exhaust valve open (EVO) timing and exhaust valve close (EVC) timing. The accuracy of the model in capturing engine dynamics was demonstrated by validating it against high-fidelity engine GT-Power simulation results for various drive cycles, particularly emphasizing elevated loads. In comparison to the open literature, novel contributions of the effort described in this paper includes in-cylinder gas composition modeling and turbine-out pressure estimation.

Zhang, Xu↗

DOE OSTI2018

Response induction coil magnetometers to perturbations in orientation

© 1996-2018 Society of Exploration Geophysicists. All rights reserved. We explore the data collected by a 3-component induction coil magnetometer system with respect to motion of the instruments in earths static magnetic field. The sensitivtiy of the inductiuon coil magnetometer leads to unprecediented accuracy on tilt measurements. We model the signals observed during seismic events as being perturbations in coil orientation. In theory, these perturbations can include ground roll, ocean motion, nearby cultural seismicity, or any other field with a tilting effect. Using data from a magnetic observatory near Parkfield CA we invert several time series of coil data during different levels of seismic activity in an attempt to determine the magnitudes of rotation at which our model accurately describes the coil data. Finally, we explore the transfer function between the coils and nearby seismic instruments (accelerometers, tiltmeters, and velocity seismometers).

Kappler, K↗

DOE OSTI2023

Enhanced lightning strike protection using vertically oriented carbon fiber melded with conventional carbon fiber-reinforced composite and its validation through damage analysis

Lightning strike protection (LSP) is one of the prime factors in aerospace and wind industries concerning safety, enhanced service life, and reduced downtime. To ensure better LSP, high electrical conductivity is required to dissipate the current, which is always a challenge for polymer composites due to the inherent insulating nature of the polymer matrix. Conventional carbon fiber-reinforced composites (CFRP) offer electrical conductivity in the planar direction while the vertical i.e. through-thickness conductivity still remains a challenge. Having been motivated by this fact, we have fabricated CFRP interleaved with vertically oriented CF (Z-fiber) for the lightning strike test (100 kA). A paint was applied to mimic the actual service condition of the composite laminates. We have prepared two Z-fiber composites: (a) Z-1 containing one Z-fiber layer on the top along with conventional CF layers and (b) Z-5 containing five interleaved Z-fiber layers and compared the properties with conventional CFRP (Z-0). Interestingly, even a single Z-fiber layer (Z-1) showed lower damage (visual damage diameter 22 mm) than Z-0 (visual damage diameter 26 mm). Z-5 displayed the lowest damage (visual damage diameter 16.7 mm), which was further confirmed by cross-sectional optical microscopy. Improved LSP was attributed to the higher through-thickness electrical conductivity in the case of Z-5 (9 times with respect to Z-0) reflecting a lower electrical anisotropy for Z-fiber composites. The residual mechanical property after the lightning test was analyzed through the flexural test, and the retention of flexural strength and modulus was 66% and 86%, respectively for Z-5 showing a significant improvement in comparison to Z-0 (>40% for both).

Saha, Subhabrata↗

DOE OSTI2017

Characterization of local hydride re-orientation in high burn-up PWR fuel rods induced by high pressure at high temperatures

Hydride re-orientation in high burn-up PWR fuel rods was induced by high pressure at high temperatures. The high-burnup specimens were sectioned from PWR rods taken from a 15×15 assembly of the H.B. Robinson (HBR) Unit 2 reactor. Out-of cell benchmark tests performed on unirradiated hydrided Zircaloy-4 specimens were conducted to determine the appropriate temperature, pressure, cooling rate, and number of cooling cycles for the reorientation of the irradiated in-cell specimens. The in-cell hydride reorientation tests were performed using high-burnup fuel specimens under a hoop stress ≈145 MPa at 400°C. The specimens were heated to the target temperature of 400°C, held for 3 hours, cooled at 1°C/min to 170°C,and then heated at 1°C/min to the target temperature again for five cycles. Post test metallographic examinations showed that a significant amount of radial hydrides were induced in the HBR fuel rods. The length of radial hydride was up to 60 μm. For unirradiated materials, the ductility of the radial hydride treated specimens is significantly reduced as compared to the as-hydrided specimens having the same hydrogen concentration (≈300 wppm in this work). The mechanical testing on irradiated fueled samples with hydride reorientation experiments have been performed, and will be reported separately in the near future.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

Deposition and dielectric characterization of highly oriented V 2 O 5 thin films

The possibility of ferroelectricity in orthorhombic V 2 O 5 thin flms was investigated. Films were deposited via either a chemical solution deposition (CSD) route or by RF magnetron sputtering. Highly (001) oriented V 2 O 5 flms were achieved with both deposition routes at temperatures as low as 300°C. No evidence for ferroelectricity was observed, even in flms which had been doped to provide local nuclei for polarization reversal. Loss originated from mid-gap trap states stemming from oxygen vacancies that were observed with photoluminescence, supplemented by piezoresponse force microscopy measurements. Furthermore, these trap states may have helped mimic ferroelectricity in previous reports on V 2 O 5 .

36 MATERIALS SCIENCE↗

DOE OSTI2023

CMakePPLang: An object-oriented extension to CMake

CMakePPLang is an object-oriented extension to the CMake language written entirely using the original CMake language, with the goal of making projects built on CMake easier to create and maintain. That said, CMakePPLang has different coding practices, paradigms, and standards than the original CMake language, much in the same way that C++ coding differs from C coding despite some level of interoperability. Currently, CMakePPLang is used within the CMakePP organization as the foundation for two in-progress projects: CMakeTest and CMaize. CMakeTest provides a solution for unit testing CMake and CMakePPLang code. CMaize is a CMake tool to simplify interoperability between projects and writing their build systems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Pressure Safety Orientation Live #769

Pressure Safety Orientation (course #769) introduces workers at Los Alamos National Laboratory (LANL) to the Laboratory Pressure Safety Program and to pressure-related hazards. This course also affords a hands-on exercise involving the assembly of a simple pressure system. This course is required for all LANL personnel who work on or near pressure systems and are exposed to pressure-related hazards. These personnel include pressure-system engineers, designers, fabricators, installers, operators, inspectors, maintainers, and others who work with pressurized fluids and may be exposed to pressure-related hazards.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2026

ARM Data-Oriented Metrics and Diagnostics Package for Climate Model Evaluation

A Python-based metrics and diagnostics package is currently being developed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Infrastructure Team at Lawrence Livermore National Laboratory (LLNL) to facilitate the use of long-term, high-frequency measurements from the ARM Facility in evaluating the regional climate simulation of clouds, radiation, and precipitation. This metrics and diagnostics package computes climatological means of targeted climate model simulation and generates tables and plots for comparing the model simulation with ARM observational data. The Coupled Model Intercomparison Project (CMIP) model data sets are also included in the package to enable model intercomparison as demonstrated in Zhang et al. (2017). The mean of the CMIP model can serve as a reference for individual models. Basic performance metrics are computed to measure the accuracy of mean state and variability of climate models. The evaluated physical quantities include cloud fraction, temperature, relative humidity, cloud liquid water path, total column water vapor, precipitation, sensible and latent heat fluxes, and radiative fluxes, with plan to extend to more fields, such as aerosol and microphysics properties. Process-oriented diagnostics focusing on individual cloud- and precipitation-related phenomena are also being developed for the evaluation and development of specific model physical parameterizations. The version 1.0 package is designed based on data collected at ARM’s Southern Great Plains (SGP) Research Facility, with the plan to extend to other ARM sites. The metrics and diagnostics package is currently built upon standard Python libraries and additional Python packages developed by DOE (such as CDMS and CDAT). The ARM metrics and diagnostic package is available publicly with the hope that it can serve as an easy entry point for climate modelers to compare their models with ARM data. In this report, we first present the input data, which constitutes the core content of the metrics and diagnostics package in section 2, and a user's guide documenting the workflow/structure of the version 1.0 codes, and including step-by-step instruction for running the package in section 3.

54 ENVIRONMENTAL SCIENCES↗

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 6.12 User's 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 user's manual for the Dakota software and provides capability overviews and procedures for software execution, as well as a variety of example studies.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Room Temperature Quasi-static Characterization and Constitutive Model Parametrization of Flexible Polyurethane Foams of Different Densities Loaded in Different Orientations

This report describes the efforts to characterize and model General Plastics TF6070 and EF4000 flexible polyurethane foams under room temperature, large deformation quasi-static cyclic mechanical loading conditions. Densities from three to fifteen pound per cubic foot (PCF) are examined, which correspond to relative densities of approximately 4 to 20%. These foams are open cell structured and flexible at room temperature with a glass transition transition less than -30°C, and they fully recover their original shape when unloaded (at room temperature). Uniaxial compression tests were conducted with accompanying lateral image series for Digital Image Correlation (DIC) analysis with the goal of extracting transverse strain responses. Due to difficulties with DIC analysis at large strains, lateral strains were instead extracted for each test via edge tracking. The experimental results exhibit a nonlinear elastic response and anisotropic material behavior (particularly for the lower densities). Some hysteresis is observed that is different between the first and subsequent cycles of deformation indicating both a small degree of permanent damage (reduced stiffness during reloading) and viscoelasticity. These inelastic mechanisms are not considered in the modeling and calibration in this report. This work considers only the rate independent, room temperature foam behavior. Individual foam densities were calibrated for loading in two directions, parallel and perpendicular to the foam bubble rise direction, since the mechanical behavior is different in these two directions. The Flex Foam constitutive model was used for all parameterizations despite the fact that the model is isotropic. A review of the constitutive model is given as well as necessary data reduction procedures to parameterize it for each foam density and orientation are discussed. Finally, two different parameterizations are developed that take the undeformed foam density as an input that span all densities considered. These two parameterized models represent foams loaded in the rise and transverse directions respectively. We summarize the assumptions and limitations of the parameterizations provided in this report to guide analysis choices with them. All parameterizations presented herein have the following traits, room temperature, rate independent, damage-free, and non-dissipative . Isotropy (even if they are representing anisotropic data). Supplied Sierra Solid Mechanics Flex Foam Model Inputs are in units: pounds, inches, Celsius, and seconds

36 MATERIALS SCIENCE↗

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 (V.6.14) (User's 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 users manual for the Dakota software and provides capability overviews and procedures for software execution, as well as a variety of example studies.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

High-Efficiency, Low-Cost III-V Solar Cells by Dynamic Hydride Vapor Phase Epitaxy Coupled with Rapid, Polishing-Free Wafer Reuse through Orientation-Optimized (110) Spalling

We demonstrated (110) GaAs solar cells grown by D-HVPE with equivalent performance and material quality relative to (100) devices. Also, we developed a procedure for repeatable wafer-scale spalling of (110) GaAs. Spalled surfaces were free of the facets founds in (100) GaAs spalling, the large arrest lines found in (100) Ge spalling, and surface features greater than 3 µm in peak-to-valley height, which can otherwise degrade the efficiency of regrown III-V devices. A sub-µm step-terrace morphology was discovered on the post-spall wafer surface, resulting from the restricted cleavage system of GaAs, but we developed understanding of the factors that determine the resulting morphology, enabling ample opportunity for optimization of morphologies suitable for device growth and spall depth waste minimization on (110) GaAs. Lastly, we demonstrated a device grown on a previously spalled surface with only 8% relative efficiency difference to a cell grown on a new unspalled wafer. Significant optimization of the substrate regrowth conditions are required to enable higher efficiency, but these results highlight the promise of (110)-oriented devices coupled with substrate reuse by spalling as a pathway for low-cost III-V photovoltaics.

14 SOLAR ENERGY↗

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↗

DOE OSTI2020

Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 6.13 User's 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 user’s manual for the Dakota software and provides capability overviews and procedures for software execution, as well as a variety of example studies.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 6.15 User's 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.

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↗