Capabilities and constraints of NASA's ground-based reduced gravity facilities

The ground-based reduced gravity facilities of NASA have been utilized to support numerous investigations addressing various processes and phenomina in several disciplines for the past 30 years. These facilities, which include drop towers, drop tubes, aircraft, and sounding rockets are able to provide a low gravity environment (gravitational levels that range from 10(exp -2)g to 10(exp -6)g) by creating a free fall or semi-free fall condition where the force of gravity on an experiment is offset by its linear acceleration during the 'fall' (drop or parabola). The low gravity condition obtained on the ground is the same as that of an orbiting spacecraft which is in a state of perpetual free fall. The gravitational levels and associated duration times associated with the full spectrum of reduced gravity facilities including spaced-based facilities are summarized. Even though ground-based facilities offer a relatively short experiment time, this available test time has been found to be sufficient to advance the scientific understanding of many phenomena and to provide meaningful hardware tests during the flight experiment development process. Also, since experiments can be quickly repeated in these facilities, multistep phenomena that have longer characteristic times associated with them can sometimes be examined in a step-by-step process. There is a large body of literature which has reported the study results achieved through using reduced-gravity data obtained from the facilities

Performance of a parallel code for the Euler equations on hypercube computers

The performance of hypercubes were evaluated on a computational fluid dynamics problem and the parallel environment issues were considered that must be addressed, such as algorithm changes, implementation choices, programming effort, and programming environment. The evaluation focuses on a widely used fluid dynamics code, FLO52, which solves the two dimensional steady Euler equations describing flow around the airfoil. The code development experience is described, including interacting with the operating system, utilizing the message-passing communication system, and code modifications necessary to increase parallel efficiency. Results from two hypercube parallel computers (a 16-node iPSC/2, and a 512-node NCUBE/ten) are discussed and compared. In addition, a mathematical model of the execution time was developed as a function of several machine and algorithm parameters. This model accurately predicts the actual run times obtained and is used to explore the performance of the code in interesting but yet physically realizable regions of the parameter space. Based on this model, predictions about future hypercubes are made

Attachment of lead wires to thin film thermocouples mounted on high temperature materials using the parallel gap welding process

Parallel gap resistance welding was used to attach lead wires to sputtered thin film sensors. Ranges of optimum welding parameters to produce an acceptable weld were determined. The thin film sensors were Pt13Rh/Pt thermocouples; they were mounted on substrates of MCrAlY-coated superalloys, aluminum oxide, silicon carbide and silicon nitride. The entire sensor system is designed to be used on aircraft engine parts. These sensor systems, including the thin-film-to-lead-wire connectors, were tested to 1000 C

Extranodal Natural-Killer/T-Cell Lymphoma, Nasal Type

The World Health Organization (WHO) classification recognizes 2 main categories of natural killer (NK) cell-derived neoplasms, namely, extranodal NK/T-cell lymphoma, nasal type, and aggressive NK-cell leukaemia. Extranodal nasal NK/T-cell lymphoma is more frequent in the Far East and Latin America. Histopathological and immunophenotypical hallmarks include angiocentricity, angiodestruction, expression of cytoplasmic CD3 epsilon (ε), CD56, and cytotoxic molecules and evidence of Epstein-Barr virus (EBV) infection. Early stage disease, in particular for localized lesion in the nasal region, is treated with chemotherapy and involved-field radiotherapy. On the other hand, multiagent chemotherapy is the mainstay of treatment for advanced or disseminated disease. L-asparaginase-containing regimens have shown promise in treating this condition. The role of autologous hematopoietic stem cell transplantation is yet to be clearly defined. Allogeneic hematopoietic stem cell transplantation, with the putative graft-versus-lymphoma effect, offers a potentially curative option in patients with advanced disease

Graph Neural Networks and Applied Linear Algebra

Sparse matrix computations are ubiquitous in scientific computing. With the recent interest in scientific machine learning, it is natural to ask how sparse matrix computations can leverage neural networks (NN). Unfortunately, multi-layer perceptron (MLP) neural networks are typically not natural for either graph or sparse matrix computations. The issue lies with the fact that MLPs require fixed-sized inputs while scientific applications generally generate sparse matrices with arbitrary dimensions and a wide range of nonzero patterns (or matrix graph vertex interconnections). While convolutional NNs could possibly address matrix graphs where all vertices have the same number of nearest neighbors, a more general approach is needed for arbitrary sparse matrices, e.g. arising from discretized partial differential equations on unstructured meshes. Graph neural networks (GNNs) are one approach suitable to sparse matrices. GNNs define aggregation functions (e.g., summations) that operate on variable size input data to produce data of a fixed output size so that MLPs can be applied. The goal of this paper is to provide an introduction to GNNs for a numerical linear algebra audience. Concrete examples are provided to illustrate how many common linear algebra tasks can be accomplished using GNNs. We focus on iterative methods that employ computational kernels such as matrix-vector products, interpolation, relaxation methods, and strength-of-connection measures. Our GNN examples include cases where parameters are determined a-priori as well as cases where parameters must be learned. The intent with this article is to help computational scientists understand how GNNs can be used to adapt machine learning concepts to computational tasks associated with sparse matrices. It is hoped that this understanding will stimulate data-driven extensions of classical sparse linear algebra tasks

Optical Polarization and Spectral Variability in the M87 Jet

During the last decade, M87's jet has been the site of an extraordinary variability event, with one knot (HST-1) increasing by over a factor 100 in brightness. Variability was also seen on timescales of months in the nuclear flux. Here we discuss the optical-UV polarization and spectral variability of these components, which show vastly different behavior. HST-1 shows a highly significant correlation between flux and polarization, with P increasing from $\sim 20$ at minimum to >40% at maximum, while the orientation of its electric vector stayed constant. HST-1's optical-UV spectrum is very hard ($\alpha_{UV-O}\sim0.5$, $F_\nu\propto\nu^{-\alpha}$), and displays "hard lags" during epochs 2004.9-2005.5, including the peak of the flare, with soft lags at later epochs. We interpret the behavior of HST-1 as enhanced particle acceleration in a shock, with cooling from both particle aging and the relaxation of the compression. We set 2$\sigma$ upper limits of $0.5 \delta$ parsecs and 1.02$c$ on the size and advance speed of the flaring region. The slight deviation of the electric vector orientation from the jet PA, makes it likely that on smaller scales the flaring region has either a double or twisted structure. By contrast, the nucleus displays much more rapid variability, with a highly variable electric vector orientation and 'looping' in the $(I,P)$ plane. The nucleus has a much steeper spectrum ($\alpha_{UV-O} \sim 1.5$) but does not show UV-optical spectral variability. Its behavior can be interpreted as either a helical distortion to a steady jet or a shock propagating through a helical jet.Comment: 14 pages, 7 figures, ApJ, in pres

Mass transport phenomena between bubbles and dissolved gases in liquids under reduced gravity conditions

The experimental and analytical work that was done to establish justification and feasibility for a shuttle middeck experiment involving mass transfer between a gas bubble and a liquid is described. The experiment involves the observation and measurement of the dissolution of an isolated immobile gas bubble of specified size and composition in a thermostatted solvent liquid of known concentration in the reduced gravity environment of earth orbit. Methods to generate and deploy the bubble were successful both in normal gravity using mutually buoyant fluids and under reduced gravity conditions in the NASA Lear Jet. Initialization of the experiment with a bubble of a prescribed size and composition in a liquid of known concentration was accomplished using the concept of unstable equilibrium. Subsequent bubble dissolution or growth is obtained by a step increase or decrease in the liquid pressure. A numerical model was developed which simulates the bubble dynamics and can be used to determine molecular parameters by comparison with the experimental data. The primary objective of the experiment is the elimination of convective effects that occur in normal gravity