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At least 1,495 records · Page 83

Comparative Analysis for EMU Fleet Latent Loading Characterization in Support of US EVA 80 Failure

During United States Extravehicular Activity 80 (US EVA 80), water was observed in the helmet of an Extravehicular Mobility Unit (EMU) during cabin repressurization. One of the primary mechanisms that can cause water in the helmet of an EMU is integrated performance induced sublimator carryover. The sublimator is a heat exchanger that removes heat and humidity from the ventilation loop. Water vapor is condensed from the gas and removed by slurper holes in the sublimator. Sublimator carryover is caused by the inability of the EMU sublimator to remove all of the condensed water vapor, resulting in liquid water entering the helmet. To determine if sublimator carryover was a likely cause of the US EVA 80 failure, a comparative analysis of numerous historical EVAs was conducted to calculate the total latent load (total water vapor generated by the crewmember) for numerous historical EVAs and ground tests using the Systems Improved Numerical Differencing Analyzer EMU (SINDA EMU) model. The analysis showed that US EVA 80 was associated with a comparatively high latent load when compared to other EVAs that did not present water in the helmet. Further, this analysis showed that other historical EVAs which had visible water in the helmet were also associated with higher latent loads. This analysis provides evidence that the likely cause of the US EVA 80 water in the helmet event was not the failure of an individual component, but rather sublimator carryover caused by excessive production of water vapor by the crewmember. The evidence from this analysis agrees with results from the Test, Teardown, and Evaluation (TT&E) of the EMU which did not show any failure of individual components of the EMU that would lead to water in the helmet.

Noah Andersen↗

Computer analysis of large structural systems.

Numerical procedure for structural systems analysis, discussing computer application to hydrodynamic, electric, magnetic, thermodynamic, elastostatic and elastodynamic problems

NUMERICAL ANALYSIS↗

Direct numerical simulations of a high Karlovitz number laboratory premixed jet flame – an analysis of flame stretch and flame thickening [Direct numerical simulations of a high Ka laboratory premixed jet flame - an analysis of flame stretch and flame thickening]

This article reports an analysis of the first detailed chemistry direct numerical simulation (DNS) of a high Karlovitz number laboratory premixed flame. The DNS results are first compared with those from laser-based diagnostics with good agreement. The subsequent analysis focuses on a detailed investigation of the flame area, its local thickness and their rates of change in isosurface following reference frames, quantities that are intimately connected. The net flame stretch is demonstrated to be a small residual of large competing terms: the positive tangential strain term and the negative curvature stretch term. The latter is found to be driven by flame speed–curvature correlations and dominated in net by low probability highly curved regions. Flame thickening is demonstrated to be substantial on average, while local regions of flame thinning are also observed. The rate of change of the flame thickness (as measured by the scalar gradient magnitude) is demonstrated, analogously to flame stretch, to be a competition between straining tending to increase gradients and flame speed variations in the normal direction tending to decrease them. The flame stretch and flame thickness analyses are connected by the observation that high positive tangential strain rate regions generally correspond with low curvature regions; these regions tend to be positively stretched in net and are relatively thinner compared with other regions. Finally, high curvature magnitude regions (both positive and negative) generally correspond with lower tangential strain; these regions are in net negatively stretched and thickened substantially.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Investigation of the Seasonal Freeze/Thaw Cycle of Soils in the GAPP Regions

The objective of this project is to understand the current and future impacts and feedbacks of seasonally frozen ground on the regional and global climate system and the ecosystem as a whole. More specifically, we proposed to: investigate the dynamics of the seasonally freezing and thawing processes and their relations to current climatic conditions through in situ data analysis and numerical modeling; develop a comprehensive algorithm to detect surface soil freeze/thaw status for snow-free land surface using passive microwave remote sensing data and for snow-covered land surface using numerical modeling, and validate the algorithm and numerical model using available ground-based measurements; investigate seasonal and inter-annual variations of frozen soils in the GAPP regions using data generated from the new validated algorithm and their relations to the environmental factors such as air temperature, snow cover, surface morphology, soil type and soil moisture; generate a frozen soil data set which describes the timing, duration, thickness, and area extent of seasonally frozen ground for the period from 1978 to present. The proposed research will be accomplished through data analysis, remote sensing, and numerical modeling.

FREEZE-THAW TESTS↗

Enabling Re-executable Workflows with Near-realtime Visualization, Provenance Capture and Advanced Querying for Mass Spectrometry Data

Mass spectrometry imaging (MSI) enables simultaneous spatially-resolved analysis of numerous ionizable molecules on a sample surface. The current analysis pipeline involves analyzing the data coming off the instrument using a tool called MSI Quickview and saving the results onto a storage drive before moving on to the next experiment. While this works well for single datasets, there is a demand for more scalable, flexible workflows that are re-executable across datasets, support extensive querying and ease collaboration. Here, we present a workflow that moves data analysis from a mere desktop application for single experiments to a more general capability

Re-executable workflow↗

Multi-Variate Factorisation of Numerical Simulations

Factorisation (also known as “factor separation”) is widely used in the analysis of numerical simulations. It allows changes in properties of a system to be attributed to changes in multiple variables associated with that system. There are many possible factorisation methods; here we discuss three previously proposed factorisations that have been applied in the field of climate modelling: the linear factorisation, the Stein and Alpert (1993) factorisation, and the Lunt et al. (2012) factorisation. We show that, when more than two variables are being considered, none of these three methods possess all four properties of “uniqueness”, “symmetry”, “completeness”, and “purity”. Here, we extend each of these factorisations so that they do possess these properties for any number of variables, resulting in three factorisations – the “linear-sum” factorisation, the “shared-interaction” factorisation, and the “scaled-residual” factorisation. We show that the linear-sum factorisation and the shared-interaction factorisation reduce to be identical in the case of four or fewer variables, and we conjecture that this holds for any number of variables. We present the results of the factorisations in the context of three past studies that used the previously proposed factorisations.

Numerical simulations↗

Transient dynamics of terrestrial carbon storage: Mathematical foundation and numeric examples

Terrestrial ecosystems absorb roughly 30% of anthropogenic CO 2 emissions since preindustrial era, but it is unclear whether this carbon (C) sink will endure into the future. Despite extensive modeling, experimental, and observational studies, what fundamentally determines transient dynamics of terrestrial C storage under climate change is still not very clear. Here we develop a new framework for understanding transient dynamics of terrestrial C storage through mathematical analysis and numerical experiments. Our analysis indicates that the ultimate force driving ecosystem C storage change is the C storage capacity, which is jointly determined by ecosystem C input (e.g., net primary production, NPP) and residence time. Since both C input and residence time vary with time, the C storage capacity is time-dependent and acts as a moving attractor that actual C storage chases. The rate of change in C storage is proportional to the C storage potential, the difference between the current storage and the storage capacity. The C storage capacity represents instantaneous responses of the land C cycle to external forcing, whereas the C storage potential represents the internal capability of the land C cycle to influence the C change trajectory in the next time step. The influence happens through redistribution of net C pool changes in a network of pools with different residence times. Furthermore, this and our other studies have demonstrated that one matrix equation can exactly replicate simulations of most land C cycle models (i.e., physical emulators). As a result, simulation outputs of those models can be placed into a three-dimensional (3D) parameter space to measure their differences. The latter can be decomposed into traceable components to track the origins of model uncertainty. Moreover, the emulators make data assimilation computationally feasible so that both C flux- and pool-related datasets can be used to better constrain model predictions of land C sequestration. We also propose that the C storage potential be the targeted variable for research, market trading, and government negotiation for C credits.

54 ENVIRONMENTAL SCIENCES↗

Numerical discreteness errors in multispecies cosmological N -body simulations

ABSTRACT We present a detailed analysis of numerical discreteness errors in two-species, gravity-only, cosmological simulations using the density power spectrum as a diagnostic probe. In a simple set-up where both species are initialized with the same total matter transfer function, biased growth of power forms on small scales when the solver force resolution is finer than the mean interparticle separation. The artificial bias is more severe when individual density and velocity transfer functions are applied. In particular, significant large-scale offsets in power are measured between simulations with conventional offset grid initial conditions when compared against converged high-resolution results where the force resolution scale is matched to the interparticle separation. These offsets persist even when the cosmology is chosen so that the two particle species have the same mass, indicating that the error is sourced from discreteness in the total matter field as opposed to unequal particle mass. We further investigate two mitigation strategies to address discreteness errors: the frozen potential method and softened interspecies short-range forces. The former evolves particles under the approximately ‘frozen’ total matter potential in linear theory at early times, while the latter filters cross-species gravitational interactions on small scales in low-density regions. By modelling closer to the continuum limit, both mitigation strategies demonstrate considerable reductions in large-scale power spectrum offsets.

79 ASTRONOMY AND ASTROPHYSICS↗

A theoretical study of heterojunction and graded band gap type solar cells

The theory of heterojunction and graded bandgap solar cells was studied to help determine the material compositions and device dimensions needed for high efficiency solar cells. Because of the involved analysis of the fundamental equations describing solar cell operation, a general numerical device analysis program was used. A major part of the initial work was involved in modifying an existing silicon solar cell analysis program to account for the unique features of graded bandgap and heterojunction solar cells. The most successful III-V solar cells have so far been constructed in the GaAs and Gal-xAlxAs material systems; this project was concerned with such solar cells. The most efficient solar cell so far evaluated is an abrupt heterojunction cell with a pure AlAs layer at the surface with a GaAs substrate. The predicted efficiency for this cell is slightly larger than that of a graded bandgap Gal-xAlxAs solar cell.

Hauser, J. R.↗

Stiffness-generated rigid-body mode shapes for Lanczos eigensolution with SUPORT DOF by way of a MSC/NASTRAN DMAP alter

When using all MSC/NASTRAN eigensolution methods except Lanczos, the analyst can replace the coupled system rigid-body modes calculated within DMAP module READ with mass orthogonalized and normalized rigid-body modes generated from the system stiffness. This option is invoked by defining MSC/NASTRAN r-set degrees of freedom via the SUPORT bulk data card. The newly calculated modes are required if the rigid-body modes calculated by the eigensolver are not 'clean' due to numerical roundoffs in the solution. When performing transient structural dynamic load analysis, the numerical roundoffs can result in inaccurate rigid-body accelerations which affect steady-state responses. Unfortunately, when using the Lanczos method and defining r-set degrees of freedom, the rigid-body modes calculated within DMAP module REIGL are retained. To overcome this limitation and to allow MSC/NASTRAN to handle SUPORT degrees of freedom identically for all eigensolvers, a DMAP Alter has been written which replaces Lanczos-calculated rigid-body modes with stiffness-generated rigid-body modes. The newly generated rigid-body modes are normalized with respect to the system mass and orthogonalized using the Gram-Schmidt technique. This algorithm has been implemented as an enhancement to an existing coupled loads methodology.

Abdallah, Ayman A.↗

Numerical and experimental investigation of melting with internal heat generation within cylindrical enclosures

There have been significant efforts by the heat transfer community to investigate the melting phenomenon of materials. These efforts have included the analytical development of equations to represent melting, numerical development of computer codes to assist in modeling the phenomena, and collection of experimental data. The understanding of the melting phenomenon has application in several areas of interest, for example, the melting of a Phase Change Material (PCM) used as a thermal storage medium as well as the melting of the fuel bundle in a nuclear power plant during an accident scenario. The objective of this research is two-fold. First a numerical investigation, using computational fluid dynamics (CFD), of melting with internal heat generation for a vertical cylindrical geometry is presented. Second, to the best of authors knowledge, there are very limited number of engineering experimental results available for the case of melting with Internal Heat Generation (IHG). An experiment was performed to produce such data using resistive, or Joule, heating as the IHG mechanism. The numerical results are compared against the experimental results and showed favorable correlation. Uncertainties in the numerical and experimental analysis are discussed. Based on the numerical and experimental analysis, recommendations are made for future work.

99 GENERAL AND MISCELLANEOUS↗

Study for the analysis of the observations, and numerical data representing the planets as far-infrared calibration sources

The existing radiative transfer and inversion programs will be modified for application to the atmospheres of Uranus, Neptune, and Jupiter. The programs will be employed for analysis of KAO planetary observations in order to develop far infrared photometric calibration standards. This work will be carried out on MSFC computers. The expected end product of this task is a working program for analysis of the observations, and numerical data representing the planets as far-infrared calibration sources.

Wu, Shi Tsan↗

A method for the analysis of impact systems using numerical continuation

The existence of impacts in mechanical systems inherently makes these systems nonlinear in nature. As a result, these systems can be difficult to thoroughly characterize. Furthermore, the results obtained through the analysis of these systems can be highly dependent on the models used to describe the contact during an impact event. Due to the inherent difficulties in the analysis of systems with impacts, more efficient methods are desired to carry out these analyses and compare the results obtained from different contact models. This report proposes numerical continuation as an efficient method for the analysis of impact systems and presents the results of an analysis of a single degree of freedom impact oscillator. Also, recommendations are given for future improvements to this method in order to make it practical for the analysis of complex systems.

Wallen, Samuel P.↗

Interpretable machine learning models classify minerals via spectroscopy

Developing methods to identify mineral species confidently and rapidly from Raman spectral analysis is critical to numerous fields. Traditionally, analysis relies on pattern matching the Raman spectrum of an unknown dataset with a supporting library of well-characterized spectral data, which may prove difficult for environmental samples that are poorly crystalline or phase mixtures. Here, we developed interpretable machine learning models that can classify uranium minerals by secondary oxyanion chemistry and other physicochemical properties based solely on Raman spectra. This new ML method produces a mineral profile of physical and chemical properties for an unknown sample and can rapidly classify or identify unknown minerals from Raman data, without the need for an exact pattern match in a spectral library. Training models are validated by 1. Strong correlation of high confidence model regions with published spectroscopic assignments and 2. Correct classification of a mineral not present in training data. Training data are from the Compendium of Uranium Raman and Infrared Experimental Spectra and available crystallographic information files within the open-source Smart Spectral Matching scientific framework. Physically meaningful classifier models can rapidly identify key structural and chemical information about unknown uranium minerals and the overall methodology is broadly applicable for mineral phases.

Machine learning↗

Towards Effective Clustering Techniques for the Analysis of Electric Power Grids

Clustering is an important data analysis technique with numerous applications in the analysis of electric power grids. Standard clustering techniques are oblivious to the rich structural and dynamic information available for power grids. Therefore, by exploiting the inherent topological and electrical structure in the power grid data, we propose new methods for clustering with applications to model reduction, locational marginal pricing, phasor measurement unit (PMU or synchrophasor) placement, and power system protection. We focus our attention on model reduction for analysis based on time-series information from synchrophasor measurement devices, and spectral techniques for clustering. By comparing different clustering techniques on two instances of realistic power grids we show that the solutions are related and therefore one could leverage that relationship for a computational advantage. Thus, by contrasting different clustering techniques we make a case for exploiting structure inherent in the data with implications for several domains including power systems.

clustering, k-means, power grid, graphs↗

Development and Validation of High Performance Unshrouded Centrifugal Impeller

The feasibility of using a two-stage unshrouded impeller turbopump to replace the current three-stage reusable launch vehicle engine shrouded impeller hydrogen pump has been evaluated from the standpoint of turbopump weight reduction and overall payload improvement. These advantages are a by-product of the higher tip speeds that an unshrouded impeller can sustain. The issues associated with the effect of unshrouded impeller tip clearance on pump efficiency and head have been evaluated with one-dimensional tools and full three-dimensional rotordynamic fluid reaction forces and coefficients have been established through time dependent computational fluid dynamics (CFD) simulation of the whole 360 degree impeller with different rotor eccentricities and whirling ratios. Unlike the shrouded impeller, the unshrouded impeller forces are evaluated as the sum of the pressure forces on the blade and the pressure forces on the hub using the CFD results. The turbopump axial thrust control has been optimized by adjusting the first stage impeller backend wear ring seal diameter and diverting the second stage backend balance piston flow to the proper location. The structural integrity associated with the high tip speed has been checked by analyzing a 3D-Finite Element Model at maximum design conditions (6% higher than the design speed). This impeller was fabricated and tested in the NASA Marshall Space Flight Center water-test rig. The experimental data will be compared with the analytical predictions and presented in another paper. The experimental data provides validation data for the numerical design and analysis methodology. The validated numerical methodology can be used to help design different unshrouded impeller configurations.

Chen, Wei-Chung↗