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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 development of efficient techniques for calculating sensitivity derivatives is studied. The objective is to present a computational procedure for calculating sensitivity derivatives as part of performing structural reanalysis for large-scale problems. The scope is limited to framed type structures. Both linear static analysis and free-vibration eigenvalue problems are considered.
Savannah River Remediation (SRR) is planning to remove a buildup of sodium aluminosilicate scale from the 2H-evaporator pot by loading and soaking the pot with heated 1.5 M nitric acid solution. Sampling and analysis of the scale material has been performed so that uranium and plutonium isotopic analysis can be input into a Nuclear Criticality Safety Assessment (NCSA) for scale removal by chemical cleaning. Historically, since the operation of the Defense Waste Processing Facility (DWPF), silicon in the DWPF recycle stream combines with aluminum in the typical tank farm supernate to form sodium aluminosilicate scale mineral deposits in the 2Hevaporator pot and gravity drain line. The 2H-evaporator scale samples analyzed by Savannah River National Laboratory (SRNL) came from the bottom cone sections of the 2H-evaporator pot [Sample HTF-13-77] and the wall 2H-evaporator [sample HTF-13-82]. X-ray diffraction analysis (XRD) confirmed that both the 2H-evaporator pot scale and the wall samples consist of nitrated cancrinite (a crystalline sodium aluminosilicate solid) and clarkeite (a uranium oxy-hydroxide mineral). On “as received” basis, the bottom pot section scale sample contained an average of 2.59E+00 ± 1.40E-01 wt % total uranium with a U-235 enrichment of 6.12E-01 ± 1.48E-02 %, while the wall sample contained an average of 4.03E+00 ± 9.79E-01 wt % total uranium with a U-235 enrichment of 6.03E-01% ± 1.66E-02 wt %. The bottom pot section scale sample analyses results for Pu-238, Pu-239, and Pu-241 are 3.16E- 05 ± 5.40E-06 wt %, 3.28E-04 ± 1.45E-05 wt %, and <8.80E-07 wt %, respectively. The evaporator wall scale samples analysis values for Pu-238, Pu-239, and Pu-241 averages 3.74E-05 ± 6.01E-06 wt %, 4.38E-04 ± 5.08E-05 wt %, and <1.38E-06 wt %, respectively. The Pu-241 analyses results, as presented, are upper limit values. These results are provided so that SRR can calculate the equivalent uranium-235 concentrations for the NCSA. Results confirm that the uranium contained in the scale remains depleted with respect to natural uranium. SRNL did not calculate an equivalent U-235 enrichment, which takes into account other fissionable isotopes U-233, Pu-239 and Pu-241. The applicable method for calculation of equivalent U-235 will be determined in the NCSA.
In this paper, a techno-economic model / cost reduction analysis of a low-cost, dispatchable / scalable, efficient Ground-Level Integrated Diverse Energy Storage (GLIDES) system is analyzed, along with a review of existing state-of-the-art energy storage technologies. The introduced technology, GLIDES, which was invented at the Oak Ridge National Laboratory (ORNL), stores energy by compression and expansion of air using water as a liquid piston inside high-pressure reservoirs. GLIDES is introduced by combining Pumped Hydroelectric Storage (PHS) and Compressed Air Energy Storage (CAES) technologies. Here, by replacing inefficient gas compressor and turbine with higher efficiency liquid turbomachines for liquid-piston compression/expansion, GLIDES achieves higher roundtrip efficiency than other gas compression-based energy storage technologies and is a scalable energy storage system. For cost reduction purposes, various pressure reservoirs including steel vessels, carbon fiber vessels, pipe segments, and underground pressure reservoirs are analyzed in this paper. Based on the analyzed data using the models discussed in this paper, energy storage costs as low as ~$14/kWh and ~346/kWh (roundtrip efficiency (RTE) ~80%) can be achieved for a grid-scale GLIDES using depleted oil/gas reservoirs and high-pressure pipe segments respectively.
Abstract The operational space and global performance of plasmas with edge-localized modes (ELMs) suppressed by resonant magnetic perturbations (RMPs) are surveyed by comparing AUG, DIII-D, EAST, and KSTAR stationary operating points. RMP-ELM suppression is achieved over a range of plasma currents, toroidal fields, and RMP toroidal mode numbers. Consistent operational windows in edge safety factor are found across devices, while windows in plasma shaping parameters are distinct. Accessed pedestal parameters reveal a quantitatively similar pedestal-top density limit for RMP-ELM suppression in all devices of just over 3 × 10 19 m −3 . This is surprising given the wide variance of many engineering parameters and edge collisionalities, and poses a challenge to extrapolation of the regime. Wide ranges in input power, confinement time, and stored energy are observed, with the achieved triple product found to scale like the product of current, field, and radius. Observed energy confinement scaling with engineering parameters for RMP-ELM suppressed plasmas are presented and compared with expectations from established H and L-mode scalings, including treatment of uncertainty analysis. Different scaling exponents for individual engineering parameters are found as compared to the established scalings. However, extrapolation to next-step tokamaks ITER and SPARC find overall consistency within uncertainties with the established scalings, finding no obvious performance penalty when extrapolating from the assembled multi-device RMP-ELM suppressed database. Overall this work identifies common physics for RMP-ELM suppression and highlights the need to pursue this no-ELM regime at higher magnetic field and different plasma physical size.
Abstract not provided
Abstract- We extend our approach capturing and relating the provenance and performance metrics of computational workflows as a diagnostic tool for runtime optimization and placement. One important challenge is the volume of extracted data, both for performance metrics and provenance, even when specifying filters and focusing on quantities of interest in a simulation. We reduce this data by performing anomaly detection on streaming data and store provenance for the detected anomalies, an approach we call prescriptive provenance. This paper discusses the Chimbuko architecture enabling the approach. We present the use of a protein structure propagation workflow based on NWChemEx. We are testing algorithms for anomaly detection and present preliminary results here obtained with Local Outlier Factor. While scaling remains a challenge, these results show that our robust Chimbuko architecture for streaming analysis with prescriptive provenance is a promising approach.
Ultra-light weight and ultra-thin membrane inflatable antenna concepts are fast evolving to become the state-of-the-art antenna concepts for deep-space applications. NASA Langley Research Center has been involved in the structural dynamics research on antenna structures. One of the goals of the research is to develop structural analysis methodology for prediction of the static and dynamic response characteristics of the inflatable antenna concepts. This research is focused on the computational studies to use nonlinear large deformation finite element analysis to characterize the ultra-thin membrane responses of the antennas. Recently, structural analyses have been performed on a few parabolic reflector antennas of varying size and shape, which are referred in the paper as 0.3 meters subscale, 2 meters half-scale, and 4 meters full-scale antenna. The various aspects studied included nonlinear analysis methodology and solution techniques, ways to speed convergence in iterative methods, the sensitivities of responses with respect to structural loads, such as inflation pressure, gravity, and pretension loads in the ground and in-space conditions, and the ultra-thin membrane wrinkling characteristics. Several such intrinsic aspects studied have provided valuable insight into evaluation of structural characteristics of such antennas. While analyzing these structural characteristics, a quick study was also made to assess the applicability of dynamics scaling of the half-scale antenna. This paper presents the details of the nonlinear structural analysis results, and discusses the insight gained from the studies on the various intrinsic aspects of the analysis methodology. The predicted reflector surface characteristics of the three inflatable ultra-thin membrane parabolic reflector antenna concepts are presented as easily observable displacement fringe patterns with associated maximum values, and normal mode shapes and associated frequencies. Wrinkling patterns are presented to show how surface wrinkle progress with increasing tension loads. Antenna reflector surface accuracies were found to be very much dependent on the type and size of the antenna, the reflector surface curvature, reflector membrane supports in terms of spacing of catenaries, as well as the amount of applied load.
This dataset contains input and result files of computational simulations with the SCALE code system. The simulations cover radionuclide inventory and reactivity analyses of a fluoride salt-cooled high temperature pebble-bed reactor (PB-FHR), specifically the Hermes low-power PB-FHR demonstration reactor. Users wanting to reproduce results from this dataset are required to obtain a license to the SCALE code system for which details on the distribution can be found here: https://www.ornl.gov/scale/releases
With the continuous increase in high performance computing capabilities, simulations are becoming ever larger and more complex, using bigger domains, tracking more variables, and producing more time steps. This increase in the ranges of spatial and temporal simulation scales results in data that presents significant challenges to as well as new opportunities for the visualization and data analysis community. For example, highly-localized, intermittent events (such as the formation of ignition kernels in turbulent combustion) may be caused by interactions between multiple variables across a series of time steps, making both their definition and their extraction difficult, particularly at scale. This paper introduces an intuitive framework to support the identification, characterization, and tracking of such complex, multivariate, temporally evolving events in large-scale simulations. In a pre-processing step, we use topological techniques to create a hierarchical family of feature definitions for each variable of interest. Subsequently, we select a particular set of features for analysis and, using overlap-based metrics, we generate an attributed relational graph (ARG) capturing the relationships between different variables both within one and across multiple time steps. Finally, we leverage subgraph-isomorphism search heuristics to identify patterns in the ARG that characterize interesting events. We demonstrate the power of this approach by analyzing a large-scale turbulent combustion simulation.
Savannah River National Laboratory previously analyzed scale samples from both the wall and cone sections of the 242-16H Evaporator prior to chemical cleaning. The samples were analyzed for uranium and plutonium isotopes required for a Nuclear Criticality Safety Assessment of the scale removal process. The analysis of the scale samples found the material to contain crystalline nitrated cancrinite and clarkeite and significant amounts of mercury. Savannah River Remediation subsequently requested additional analyses on the samples. Inspection of the sample bottles revealed that no sample remained of the cone scale (HTF-17-56) while approximately 4 g of the wall scale sample (HTF-17-57) remained. The wall sample was subsequently ground with a mortar and pestle, at which time it was discovered that the sample contained a significant amount of liquid, metallic mercury. The portion of the sample that was not mercury was approximately 3 g. This portion of the sample was analyzed to determine the concentrations of selected radionuclides. The following radionuclide concentrations were measured: <9.6E+02 dpm/g H-3, 2.9E+02 dpm/g C-14, 5.6E+03 dpm/g Tc-99, and 1.6E+02 dpm/g I-129. Blank samples were also analyzed to evaluate sample contamination from the Shielded Cells environment. All blank sample results were below detectable limits. Due to the limited sample size and the anticipated low levels of the target radionuclides, no replicate sample analysis was conducted.
An efficient method of calculating the natural bond orbitals (NBOs) based on a truncation of the entire density matrix of a whole system is presented for large-scale density functional theory calculations. The method recovers an orbital picture for O(N) electronic structure methods which directly evaluate the density matrix without using Kohn-Sham orbitals, thus enabling quantitative analysis of chemical reactions in large-scale systems in the language of localized Lewis-type chemical bonds. With the density matrix calculated by either an exact diagonalization or O(N) method, the computational cost is O(1) for the calculation of NBOs associated with a local region where a chemical reaction takes place. As an illustration of the method, we demonstrate how an electronic structure in a local region of interest can be analyzed by NBOs in a large-scale first-principles molecular dynamics simulation for a liquid electrolyte bulk model (propylene carbonate + LiBF{sub 4})
Networks of silicon nanowires possess intriguing electronic properties surpassing the predictions based on quantum confinement of individual nanowires. Employing large-scale atomistic pseudopotential computations, as yet unexplored branched nanostructures are investigated in the subsystem level as well as in full assembly. The end product is a simple but versatile expression for the bandgap and band edge alignments of multiply-crossing Si nanowires for various diameters, number of crossings, and wire orientations. Further progress along this line can potentially topple the bottom-up approach for Si nanowire networks to a top-down design by starting with functionality and leading to an enabling structure.
The objective of this study is to establish a detailed techno-economic analysis to assess the effectiveness of incremental technology improvements needed for solid oxide electrolysis cell (SOEC) technology to achieve the U.S. DOE’s Hydrogen Shot goal of hydrogen production at less than $1 per kilogram. The pathway considers incremental technology improvements to key system parameters, with system performance and cost assessed for each pathway step. Briefly, the steps include cell voltage degradation rate improvements, operational current density increases, operating temperature reduction, improved steam utilization, increased system capacity factor, and reduced cell/stack capital costs. Each step is assessed at both atmospheric and pressurized (8 bar) operating conditions. To supplement assessment at each of these discrete stepwise improvements, sensitivity studies are conducted to understand the relative impact of each parameter and identify avenues for additional cost reductions. System efficiency and levelized costs of hydrogen (LCOH) for each case are presented. For the end-of-pathway case, which includes all the incremental research and development improvements, the cost of hydrogen produced is reduced by 50 percent from the state-of-the-art case.
The conceptual design for a scaled truss antenna structures experiment program (STASEP) is presented. The hardware analysis of the scaled truss antenna structure (STAS) was performed by interactive design and evaluation of advanced spacecraft (IDEAS) computer aided, interactive, design and analysis program. Four STAS's were designed to be launched by the Shuttle, tested by using the space technology experiments platform (STEP) and space transportation system (STS), and then free flown in short lifetime orbits. Data were gathered on deployment, structural characteristics, geometric accuracies, thermal performance, and drag and lifetime as an orbiting spacecraft. Structural and thermal properties were determined for the STAS, including mass properties, thermal loading, structural natural frequencies, and mode shapes. The necessary analysis, scaling, and ground testing are discussed.
A computational fluid dynamics (CFD) analysis of a natural gas vehicle experiencing a mechanical failure of a pressure relief device on a full CNG cylinder was completed to determine the resulting amount and location of flammable gas. The resulting overpressure if it were to ignite was also calculated. This study completes what is discussed in Ekoto et al. which covers other related leak scenarios. We are not determining whether or not this is a credible release, rather just showing the result of a possible worst case scenario. The Sandia National Laboratories computational tool Netflow was used to calculate the leak velocity and temperature. The in - house CFD code Fuego was used to determine the flow of the leak into the maintenance garage. A maximum flammable mass of 35 kg collected along the roof of the garage. This would result in an overpressure that could do considerable damage if it were to ignite at the time of this maximum volume. It is up to the code committees to decide whet her this would be a credible leak, but if it were, there should be preventions to keep the flammable mass from igniting.
An investigation was performed to ascertain the feasibility of using IPACS (Integrated Probabilistic Assessment of Composite Structures) for probabilistic analysis of a composite fan blade, the development of which is being pursued by various industries for the next generation of aircraft engines. A model representative of the class of fan blades used in the GE90 engine has been chosen as the structural component to be analyzed with IPACS. In this study, typical uncertainties are assumed in the level, and structural responses for ply stresses and frequencies are evaluated in the form of cumulative probability density functions. Because of the geometric complexity of the blade, the number of plies varies from several hundred at the root to about a hundred at the tip. This represents a extremely complex composites application for the IPACS code. A sensitivity study with respect to various random variables is also performed.
The study of complex turbulent flows by means of large-eddy simulation approaches has become increasingly popular in many scientific and engineering applications. The underlying filtering operation of the approach enables to significantly reduce the spatial and temporal resolution requirements by means of representing only large-scale motions. However, the small-scale stresses and their effects on the resolved flow field are not negligible, and therefore require additional modeling. As a consequence, the assumptions made in the closure formulations become potential sources of model-form uncertainty that can impact the quantities of interest. The objective of this work, thus, is to perform a model-form sensitivity analysis in large-eddy simulations of an axisymmetric turbulent jet following an eigenspace-based strategy recently proposed. The approach relies on introducing perturbations to the decomposed subgrid-scale stress tensor within a range of physically plausible values. These correspond to discrepancy in magnitude (trace), anisotropy (eigenvalues) and orientation (eigenvectors) of the normalized, small-scale stresses with respect to a given tensor state, such that propagation of their effects can be assessed. As a result, the generality of the framework with respect to the six degrees of freedom of the small-scale stress tensor makes it also suitable for its application within data-driven techniques for improved subgrid-scale modeling.
TRIMER, Transcription Regulation Integrated with MEtabolic Regulation, is a genome-scale modeling pipeline targeting at metabolic engineering applications. Using TRIMER, regulated metabolic reactions can be effectively predicted by integrative modeling of metabolic reactions with a Transcription Factor (TF)-gene regulatory network (TRN), which is modeled via a Bayesian network (BN). In this paper, we focus on sensitivity analysis of metabolic flux prediction for uncertainty quantification of BN structures for TRN modeling in TRIMER. We propose a computational strategy to construct the uncertainty class of TRN models based on the inferred regulatory order uncertainty given transcriptomic expression data. With that, we analyze the prediction sensitivity of the TRIMER pipeline for the metabolite yields of interest. The obtained sensitivity analyses can guide Optimal Experimental Design (OED) to help acquire new data that can enhance TRN modeling and achieve specific metabolic engineering objectives, including metabolite yield alterations. Here we have performed small- and large-scale simulated experiments, demonstrating the effectiveness of our developed sensitivity analysis strategy for BN structure learning to quantify the edge importance in terms of metabolic flux prediction uncertainty reduction and its potential to effectively guide OED.