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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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The Second Target Station (STS) is a proposed upgrade for SNS. It includes a doubling of the accelerator power and an additional instrument hall. The new instrument hall will receive a 467 kW 10 Hz beam. The parameters and preliminary design aspects of the STS are presented for the accelerator, target systems, instrument hall, instruments and civil construction aspects.
During the report period, we continued the work as outlined in the original proposal. We have analyzed potential optical designs of Wolter mirrors for the neutron-imaging instrument VENUS, which is under construction at SNS. In parallel, we have conducted the initial polarized imaging experiment at Helmholtz Zentrum, Berlin, one of very few of currently available polarized-imaging facilities worldwide.
A summary of the activities and of the scientific production of the “NSTD/C-AD ADS-Reactor Think-Tank” collaboration, over the period May 2013 - May 2015.
The heaviest metals found in stars in most ultra-faint dwarf (UFD) galaxies in the Milky Way halo are generally underabundant by an order of magnitude or more when compared with stars in the halo field. Among the heavy elements produced by n -capture reactions, only Sr and Ba can be detected in red giant stars in most UFD galaxies. This limited chemical information is unable to identify the nucleosynthesis process(es) responsible for producing the heavy elements in UFD galaxies. Similar [Sr/Ba] and [Ba/Fe] ratios are found in three bright halo field stars, BD−18°5550, CS 22185–007, and CS 22891–200. Previous studies of high-quality spectra of these stars report detections of additional n -capture elements, including Eu. The [Eu/Ba] ratios in these stars span +0.41 to +0.86. These ratios and others among elements in the rare Earth domain indicate an r -process origin. These stars have some of the lowest levels of r -process enhancement known, with [Eu/H] spanning −3.95 to −3.32, and they may be considered nearby proxies for faint stars in UFD galaxies. Direct confirmation, however, must await future observations of additional heavy elements in stars in the UFD galaxies themselves.
We present a new method for inferring photometric redshifts in deep galaxy and quasar surveys, based on a data-driven model of latent spectral energy distributions (SEDs) and a physical model of photometric fluxes as a function of redshift. This conceptually novel approach combines the advantages of both machine learning methods and template fitting methods by building template SEDs directly from the spectroscopic training data. This is made computationally tractable with Gaussian processes operating in flux–redshift space, encoding the physics of redshifts and the projection of galaxy SEDs onto photometric bandpasses. This method alleviates the need to acquire representative training data or to construct detailed galaxy SED models; it requires only that the photometric bandpasses and calibrations be known or have parameterized unknowns. The training data can consist of a combination of spectroscopic and deep many-band photometric data with reliable redshifts, which do not need to entirely spatially overlap with the target survey of interest or even involve the same photometric bands. We showcase the method on the i -magnitude-selected, spectroscopically confirmed galaxies in the COSMOS field. The model is trained on the deepest bands (from SUBARU and HST ) and photometric redshifts are derived using the shallower SDSS optical bands only. We demonstrate that we obtain accurate redshift point estimates and probability distributions despite the training and target sets having very different redshift distributions, noise properties, and even photometric bands. Our model can also be used to predict missing photometric fluxes or to simulate populations of galaxies with realistic fluxes and redshifts, for example.
NEREIDS (NEutron REsonance Imaging Diagnostic Suite) is a research-grade toolkit for neutron resonance imaging, providing a Rust physics core, Python bindings, and NeXus/HDF5-compliant data I/O, with a path to fast, standalone GUI workflows for VENUS/MARS.
Code to place polarized neutron reflectivity into bins of constant Qz with regard for Zeeman energy change to the spin-flip channel. The code is written as a Jupyter notebook. Example data are included as separate files (spin_down.txt and spin_up.txt). As a first step, run all cells in the notebook. Opportunities are identified for users to make their own choices for analysis of the data. The code is written to be a stand-alone operation on data collected from a pulse neutron source that have been previously normalized to the wavelength dependence of the incident beam spectrum, background subtracted, etc. The constant Qz binning (this code) is the last step to perform in the analysis (reduction) workflow. This step yields the the reflectivities for the four neutron spin cross-sections. A future intention is to create a version of this code that will be one module of many in the data analysis workflow.
This work describes the development of a model that accounts for the additional surface recession in Thermal Protection Systems (TPS) materials as a result of mechanical erosion due to high shear conditions during atmospheric entry. A computational solid mechanics module was integrated within the Porous material Analysis Toolbox (PATO) based on OpenFOAM. The mechanical erosion was modeled in three steps: first, the implemented stress analysis solver computes the stress and the displacement fields for orthotropic materials using the wall shear stress tensor as a boundary condition; then, regions on the surface where the stress meets the failure criteria are identified; and last, the mesh is moved accordingly to remove the failed material. The outcome is a model capable to predict the total recession of the material due to surface chemistry and mechanical erosion. Results will be included in the final paper after verifying and completing the study.
The goal of this presentation is to provide a general overview of the multi-scale modeling formulation to determine if there is additional surface recession in Thermal Protection Systems (TPS) materials as a result of mechanical erosion due to high shear conditions during atmospheric entry. This modeling process is performed at different scales by leveraging two computational frameworks developed at NASA: the Porous Microstructure Analysis (PuMA) software, and the Porous material Analysis Toolbox based on OpenFOAM (PATO). PuMA specializes in computing effective macro-scale material properties by performing material response simulations on 3D digital micro-scale representations of porous micro-structures. The modeling of TPS materials at the micro-scale is essential to understand how they behave as part of a heat shield assembly. The first part of the presentation will detail the implementation of PuMA’s cell-centered finite volume elasticity solver, which allows the computation of macro-scale effective mechanical properties of heterogeneous and anisotropic materials such as fibrous and woven TPS composites. These homogenized mechanical properties are used by PATO’s mechanical erosion model to predict the TPS material’s recession at a larger scale. This work will also provide some examples of multi-scale analysis from the fiber level up to the unit cell. The second part of the presentation will focus on the macro-scale approach to determine if erosion at the heat shield’s surface occurs due to mechanical and thermal loads experienced during atmospheric entry. To accomplish this, a solid mechanics module was integrated within PATO enabling it to model the potential mechanical erosion in three steps: first, after obtaining the effective mechanical properties with PuMA, the implemented stress analysis solver computes the stress and the displacement fields for the TPS material using the wall shear stress tensor, computed using a CFD solver, as boundary conditions; then, regions on the surface where the stress meets the failure criteria are identified; finally, the failed material is removed and the mesh is redistributed accordingly. The outcome is a model capable of predicting the total recession in the material due to surface chemistry and mechanical erosion.
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The goal of this work is to predict the mechanical response of TPS materials, and specifically, to determine if there is additional surface recession in the heat shield’s surface as a result of mechanical erosion due to the mechanical and thermal loads experienced during atmospheric entry. To accomplish this, a solid mechanics module was integrated within the PATO material response code, enabling it to model the potential mechanical erosion in three steps: first, having the effective mechanical properties as function of temperature, the implemented stress analysis solver computes the stress and the displacement fields for the TPS material using the wall shear stress tensor, computed with the DPLR hypersonic CFD code, as boundary conditions; then, regions on the surface where the stress meets the failure criteria are identified; finally, the failed material is removed and the mesh is redistributed accordingly. The outcome is a model capable of predicting the total recession in the TPS material due to surface chemistry and mechanical erosion.
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This work describes the development of a model that accounts for the additional surface recession in Thermal Protection Systems (TPS) materials as a result of mechanical erosion due to high shear conditions during atmospheric entry. A computational solid mechanics module was integrated within the Porous material Analysis Toolbox (PATO) based on OpenFOAM. The mechanical erosion was modeled in three steps: first, the implemented stress analysis solver computes the stress and the displacement fields for orthotropic materials using the wall shear stress tensor as a boundary condition; then, regions on the surface where the stress meets the failure criteria are identified; and last, the mesh is moved accordingly to remove the failed material. The outcome is a model capable to predict the total recession of the material due to surface chemistry and mechanical erosion. Results will be included in the final paper after verifying and completing the study.
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This paper discusses the topology used in the HVCMs at SNS to process power for both the cold and warm linac sections of the klystron gallery in support of extended operations at the megawatt level. In anticipation of a second target station and higher anticipated power levels, an enhancement to the present topology is being investigated. SPICE circuit simulations and preliminary experimental data will be presented.
The SNS at ORNL has been fully operational since 2006 and in September 2009, the design goal of 1MW of sustained beam power on target was achieved. Historically, the high voltage converter modulators (HVCM) have been a known problem area and, in order to reach another SNS milestone of 90% availability, a new gate driver was one of several areas targeted to improve the overall reliability of the HVCM systems. The drive capability and fault protection of the large IGBT modules in the HVCM were specifically addressed to improve IGBT switching characteristics and provide enhanced troubleshooting and monitoring capabilities for the critical IGBT/driver pair. This paper outlines the work involved; the result obtained and documents the driver s long-term performance. Enhanced features, designed to be used in conjunction with a new controller presently under development, will also be discussed.
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