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NASA NTRS1992

Domain decomposition: A bridge between nature and parallel computers

Domain decomposition is an intuitive organizing principle for a partial differential equation (PDE) computation, both physically and architecturally. However, its significance extends beyond the readily apparent issues of geometry and discretization, on one hand, and of modular software and distributed hardware, on the other. Engineering and computer science aspects are bridged by an old but recently enriched mathematical theory that offers the subject not only unity, but also tools for analysis and generalization. Domain decomposition induces function-space and operator decompositions with valuable properties. Function-space bases and operator splittings that are not derived from domain decompositions generally lack one or more of these properties. The evolution of domain decomposition methods for elliptically dominated problems has linked two major algorithmic developments of the last 15 years: multilevel and Krylov methods. Domain decomposition methods may be considered descendants of both classes with an inheritance from each: they are nearly optimal and at the same time efficiently parallelizable. Many computationally driven application areas are ripe for these developments. A progression is made from a mathematically informal motivation for domain decomposition methods to a specific focus on fluid dynamics applications. To be introductory rather than comprehensive, simple examples are provided while convergence proofs and algorithmic details are left to the original references; however, an attempt is made to convey their most salient features, especially where this leads to algorithmic insight.

Keyes, David E.↗

NASA NTRS2004

Einstein Inflationary Probe (EIP)

I will discuss plans to develop a concept for the Einstein Inflation Probe: a mission to detect gravity waves from inflation via the unique signature they impart to the cosmic microwave background (CMB) polarization. A sensitive CMB polarization satellite may be the only way to probe physics at the grand-unified theory (GUT) scale, exceeding by 12 orders of magnitude the energies studied at the Large Hadron Collider. A detection of gravity waves would represent a remarkable confirmation of the inflationary paradigm and set the energy scale at which inflation occurred when the universe was a fraction of a second old. Even a strong upper limit to the gravity wave amplitude would be significant, ruling out many common models of inflation, and pointing to inflation occurring at much lower energy, if at all. Measuring gravity waves via the CMB polarization will be challenging. We will undertake a comprehensive study to identify the critical scientific requirements for the mission and their derived instrumental performance requirements. At the core of the study will be an assessment of what is scientifically and experimentally optimal within the scope and purpose of the Einstein Inflation Probe.

Hinshaw, Gary↗

NASA NTRS1997

Heterogeneous Combustion of Porous Graphite Particles in Microgravity

Recent theoretical investigations on graphite particle combustion have employed several levels of heterogeneous reaction models, ranging from global to elementary models, to describe the oxidation of carbon to gaseous products. Unlike the counterpart homogeneous reaction models, these heterogeneous reaction models are not well developed because of the difficulties associated with decoupling the physical characteristics of the solid (e.g. surface area taking part in combustion) from the chemical kinetic data. This is certainly true for porous graphite particle combustion, where heterogeneous and homogeneous reactions occur within the pores and play an important role in the overall oxidation process. As a result, there are considerable uncertainties of physical phenomena predicted using different heterogeneous kinetic models available in the literature. A good example, discussed later in this paper, is the predicted critical particle size below which the mass burning rate becomes exponentially small. The main goal of this study is to understand the basic mechanism controlling such rapid changes in burning rates, by developing a model where physical contributions are decoupled from chemical rate constants in a consistent manner. Another important goal of the proposed study is to develop a truly intrinsic, detailed heterogeneous reaction model for porous graphite combustion at high-temperatures, and to derive a systematically reduced heterogeneous reaction model in terms of the elementary reaction rate constants of the detailed model. The validation of chemical kinetic models describing the heterogeneous and homogeneous combustion in and around a spherically symmetric porous graphite particle can be considerably simplified by experimental measurements obtained under microgravity conditions. A vital component of this study is to conduct such supporting experiments on particle burning rate and surface temperature using NASA microgravity facilities, in close coordination with the theoretical effort. The basic understanding obtained and models developed as part of this project will be useful for optimal design of coal combustion devices. These models can also be extended to investigate the role of heterogeneous chemistry on pollutant formation pathways in combustion devices. The theoretical approach developed here, with pore diffusion effects decoupled from the chemical effects, can also be extended to understand the heterogeneous combustion of other porous fuels, for example, combustion of magnesium in a CO2 environment for propulsion in the Martian atmosphere.

Chelliah, Harsha K.↗

NASA NTRS2004

Multivariate Error Covariance Estimates by Monte-Carlo Simulation for Assimilation Studies in the Pacific Ocean

One of the most difficult aspects of ocean state estimation is the prescription of the model forecast error covariances. The paucity of ocean observations limits our ability to estimate the covariance structures from model-observation differences. In most practical applications, simple covariances are usually prescribed. Rarely are cross-covariances between different model variables used. Here a comparison is made between a univariate Optimal Interpolation (UOI) scheme and a multivariate OI algorithm (MvOI) in the assimilation of ocean temperature. In the UOI case only temperature is updated using a Gaussian covariance function and in the MvOI salinity, zonal and meridional velocities as well as temperature, are updated using an empirically estimated multivariate covariance matrix. Earlier studies have shown that a univariate OI has a detrimental effect on the salinity and velocity fields of the model. Apparently, in a sequential framework it is important to analyze temperature and salinity together. For the MvOI an estimation of the model error statistics is made by Monte-Carlo techniques from an ensemble of model integrations. An important advantage of using an ensemble of ocean states is that it provides a natural way to estimate cross-covariances between the fields of different physical variables constituting the model state vector, at the same time incorporating the model's dynamical and thermodynamical constraints as well as the effects of physical boundaries. Only temperature observations from the Tropical Atmosphere-Ocean array have been assimilated in this study. In order to investigate the efficacy of the multivariate scheme two data assimilation experiments are validated with a large independent set of recently published subsurface observations of salinity, zonal velocity and temperature. For reference, a third control run with no data assimilation is used to check how the data assimilation affects systematic model errors. While the performance of the UOI and MvOI is similar with respect to the temperature field, the salinity and velocity fields are greatly improved when multivariate correction is used, as evident from the analyses of the rms differences of these fields and independent observations. The MvOI assimilation is found to improve upon the control run in generating the water masses with properties close to the observed, while the UOI failed to maintain the temperature and salinity structure.

Borovikov, Anna↗

NASA NTRS2008

Sensor Selection and Data Validation for Reliable Integrated System Health Management

For new access to space systems with challenging mission requirements, effective implementation of integrated system health management (ISHM) must be available early in the program to support the design of systems that are safe, reliable, highly autonomous. Early ISHM availability is also needed to promote design for affordable operations; increased knowledge of functional health provided by ISHM supports construction of more efficient operations infrastructure. Lack of early ISHM inclusion in the system design process could result in retrofitting health management systems to augment and expand operational and safety requirements; thereby increasing program cost and risk due to increased instrumentation and computational complexity. Having the right sensors generating the required data to perform condition assessment, such as fault detection and isolation, with a high degree of confidence is critical to reliable operation of ISHM. Also, the data being generated by the sensors needs to be qualified to ensure that the assessments made by the ISHM is not based on faulty data. NASA Glenn Research Center has been developing technologies for sensor selection and data validation as part of the FDDR (Fault Detection, Diagnosis, and Response) element of the Upper Stage project of the Ares 1 launch vehicle development. This presentation will provide an overview of the GRC approach to sensor selection and data quality validation and will present recent results from applications that are representative of the complexity of propulsion systems for access to space vehicles. A brief overview of the sensor selection and data quality validation approaches is provided below. The NASA GRC developed Systematic Sensor Selection Strategy (S4) is a model-based procedure for systematically and quantitatively selecting an optimal sensor suite to provide overall health assessment of a host system. S4 can be logically partitioned into three major subdivisions: the knowledge base, the down-select iteration, and the final selection analysis. The knowledge base required for productive use of S4 consists of system design information and heritage experience together with a focus on components with health implications. The sensor suite down-selection is an iterative process for identifying a group of sensors that provide good fault detection and isolation for targeted fault scenarios. In the final selection analysis, a statistical evaluation algorithm provides the final robustness test for each down-selected sensor suite. NASA GRC has developed an approach to sensor data qualification that applies empirical relationships, threshold detection techniques, and Bayesian belief theory to a network of sensors related by physics (i.e., analytical redundancy) in order to identify the failure of a given sensor within the network. This data quality validation approach extends the state-of-the-art, from red-lines and reasonableness checks that flag a sensor after it fails, to include analytical redundancy-based methods that can identify a sensor in the process of failing. The focus of this effort is on understanding the proper application of analytical redundancy-based data qualification methods for onboard use in monitoring Upper Stage sensors.

Garg, Sanjay↗

NASA NTRS1994

Optimizing tertiary storage organization and access for spatio-temporal datasets

We address in this paper data management techniques for efficiently retrieving requested subsets of large datasets stored on mass storage devices. This problem represents a major bottleneck that can negate the benefits of fast networks, because the time to access a subset from a large dataset stored on a mass storage system is much greater that the time to transmit that subset over a network. This paper focuses on very large spatial and temporal datasets generated by simulation programs in the area of climate modeling, but the techniques developed can be applied to other applications that deal with large multidimensional datasets. The main requirement we have addressed is the efficient access of subsets of information contained within much larger datasets, for the purpose of analysis and interactive visualization. We have developed data partitioning techniques that partition datasets into 'clusters' based on analysis of data access patterns and storage device characteristics. The goal is to minimize the number of clusters read from mass storage systems when subsets are requested. We emphasize in this paper proposed enhancements to current storage server protocols to permit control over physical placement of data on storage devices. We also discuss in some detail the aspects of the interface between the application programs and the mass storage system, as well as a workbench to help scientists to design the best reorganization of a dataset for anticipated access patterns.

Chen, Ling Tony↗

NASA NTRS2004

Uncertainties in estimates of the risks of late effects from space radiation

Methods used to project risks in low-Earth orbit are of questionable merit for exploration missions because of the limited radiobiology data and knowledge of galactic cosmic ray (GCR) heavy ions, which causes estimates of the risk of late effects to be highly uncertain. Risk projections involve a product of many biological and physical factors, each of which has a differential range of uncertainty due to lack of data and knowledge. Using the linear-additivity model for radiation risks, we use Monte-Carlo sampling from subjective uncertainty distributions in each factor to obtain an estimate of the overall uncertainty in risk projections. The resulting methodology is applied to several human space exploration mission scenarios including a deep space outpost and Mars missions of duration of 360, 660, and 1000 days. The major results are the quantification of the uncertainties in current risk estimates, the identification of factors that dominate risk projection uncertainties, and the development of a method to quantify candidate approaches to reduce uncertainties or mitigate risks. The large uncertainties in GCR risk projections lead to probability distributions of risk that mask any potential risk reduction using the "optimization" of shielding materials or configurations. In contrast, the design of shielding optimization approaches for solar particle events and trapped protons can be made at this time and promising technologies can be shown to have merit using our approach. The methods used also make it possible to express risk management objectives in terms of quantitative metrics, e.g., the number of days in space without exceeding a given risk level within well-defined confidence limits. Published by Elsevier Ltd on behalf of COSPAR.

Non-NASA Center↗

NASA NTRS1997

Error Analysis System for Spacecraft Navigation Using the Global Positioning System (GPS)

The Flight Dynamics Division (FDD) at the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) is currently developing improved space-navigation filtering algorithms to use the Global Positioning System (GPS) for autonomous real-time onboard orbit determination. In connection with a GPS technology demonstration on the Small Satellite Technology Initiative (SSTI)/Lewis spacecraft, FDD analysts and programmers have teamed with the GSFC Guidance, Navigation, and Control Branch to develop the GPS Enhanced Orbit Determination Experiment (GEODE) system. The GEODE system consists of a Kalman filter operating as a navigation tool for estimating the position, velocity, and additional states required to accurately navigate the orbiting Lewis spacecraft by using astrodynamic modeling and GPS measurements from the receiver. A parallel effort at the FDD is the development of a GPS Error Analysis System (GEAS) that will be used to analyze and improve navigation filtering algorithms during development phases and during in-flight calibration. For GEAS, the Kalman filter theory is extended to estimate the errors in position, velocity, and other error states of interest. The estimation of errors in physical variables at regular intervals will allow the time, cause, and effect of navigation system weaknesses to be identified. In addition, by modeling a sufficient set of navigation system errors, a system failure that causes an observed error anomaly can be traced and accounted for. The GEAS software is formulated using Object Oriented Design (OOD) techniques implemented in the C++ programming language on a Sun SPARC workstation. The Phase 1 of this effort is the development of a basic system to be used to evaluate navigation algorithms implemented in the GEODE system. This paper presents the GEAS mathematical methodology, systems and operations concepts, and software design and implementation. Results from the use of the basic system to evaluate navigation algorithms implemented on GEODE are also discussed. In addition, recommendations for generalization of GEAS functions and for new techniques to optimize the accuracy and control of the GPS autonomous onboard navigation are presented.

Truong, S. H.↗

NASA NTRS1999

Parallel Tetrahedral Mesh Adaptation with Dynamic Load Balancing

The ability to dynamically adapt an unstructured grid is a powerful tool for efficiently solving computational problems with evolving physical features. In this paper, we report on our experience parallelizing an edge-based adaptation scheme, called 3D_TAG. using message passing. Results show excellent speedup when a realistic helicopter rotor mesh is randomly refined. However. performance deteriorates when the mesh is refined using a solution-based error indicator since mesh adaptation for practical problems occurs in a localized region., creating a severe load imbalance. To address this problem, we have developed PLUM, a global dynamic load balancing framework for adaptive numerical computations. Even though PLUM primarily balances processor workloads for the solution phase, it reduces the load imbalance problem within mesh adaptation by repartitioning the mesh after targeting edges for refinement but before the actual subdivision. This dramatically improves the performance of parallel 3D_TAG since refinement occurs in a more load balanced fashion. We also present optimal and heuristic algorithms that, when applied to the default mapping of a parallel repartitioner, significantly reduce the data redistribution overhead. Finally, portability is examined by comparing performance on three state-of-the-art parallel machines.

Oliker, Leonid↗

NASA NTRS2002

Uncertainties in Estimates of the Risks of Late Effects from Space Radiation

The health risks faced by astronauts from space radiation include cancer, cataracts, hereditary effects, and non-cancer morbidity and mortality risks related to the diseases of the old age. Methods used to project risks in low-Earth orbit are of questionable merit for exploration missions because of the limited radiobiology data and knowledge of galactic cosmic ray (GCR) heavy ions, which causes estimates of the risk of late effects to be highly uncertain. Risk projections involve a product of many biological and physical factors, each of which has a differential range of uncertainty due to lack of data and knowledge. Within the linear-additivity model, we use Monte-Carlo sampling from subjective uncertainty distributions in each factor to obtain a Maximum Likelihood estimate of the overall uncertainty in risk projections. The resulting methodology is applied to several human space exploration mission scenarios including ISS, lunar station, deep space outpost, and Mar's missions of duration of 360, 660, and 1000 days. The major results are the quantification of the uncertainties in current risk estimates, the identification of factors that dominate risk projection uncertainties, and the development of a method to quantify candidate approaches to reduce uncertainties or mitigate risks. The large uncertainties in GCR risk projections lead to probability distributions of risk that mask any potential risk reduction using the "optimization" of shielding materials or configurations. In contrast, the design of shielding optimization approaches for solar particle events and trapped protons can be made at this time, and promising technologies can be shown to have merit using our approach. The methods used also make it possible to express risk management objectives in terms of quantitative objective's, i.e., the number of days in space without exceeding a given risk level within well defined confidence limits.

Cucinotta, F. A.↗

NASA NTRS2014

Transition-Edge Hot-Electron Microbolometers for Millimeter and Submillimeter Astrophysics

The millimeter and the submillimeter wavelengths of the electromagnetic spectrum hold a wealth of information about the evolution of the universe. In particular, cosmic microwave background (CMB) radiation and its polarization carry the oldest information in the universe, and provide the best test of the inflationary paradigm available to astronomy today. Detecting gravity waves through their imprint on the CMB polarization would have extraordinary repercussions for cosmology and physics. A transition-edge hot-electron micro - bolometer (THM) consists of a superconducting bilayer transition-edge sensor (TES) with a thin-film absorber. Unlike traditional monolithic bolometers that make use of micromachined structures, the THM em ploys the decoupling between electrons and phonons at millikelvin temperatures to provide thermal isolation. The devices are fabricated photolithographically and are easily integrated with antennas via microstrip transmission lines, and with SQUID (superconducting quantum interference device) readouts. The small volume of the absorber and TES produces a short thermal time constant that facilitates rapid sky scanning. The THM consists of a thin-film metal absorber overlapping a superconducting TES. The absorber forms the termination of a superconducting microstripline that carries RF power from an antenna. The purpose of forming a separate absorber and TES is to allow flexibility in the optimization of the two components. In particular, the absorbing film's impedance can be chosen to match the antenna, while the TES impedance can be chosen to match to the readout SQUID amplifier. This scheme combines the advantages of the TES with the advantages of planar millimeter-wave transmission line circuits. Antenna-coupling to the detectors via planar transmission lines allows the detector dimensions to be much smaller than a wavelength, so the technique can be extended across the entire microwave, millimeter, and submillimeter wavelength ranges. The circuits are fabricated using standard microlithographic techniques and are compatible with uniform, large array formats. Unlike traditional monolithic bolometers that make use of micromachined structures, the THM employs the decoupling between electrons and phonons at millikelvin temperatures to provide thermal isolation. There is no fragile membrane in the structure for thermal isolation, which improves the fabrication yield.

Hsieh, Wen-Ting↗

NASA NTRSDate not supplied

Using XR for Improving Scientific Discovery With Numerical Weather Models

Earth science (ES) digital twins will help us understand the complex interactions and interrelationships that make up our Earth system and the impacts of earth science phenomena on it. Our work addresses two underdeveloped areas in current ES digital twin work: improving the understanding and interaction with ES model outputs by using Virtual and Mixed Reality (XR) tools and improving the non-intuitive mapping of continuous ES natural phenomena to gridded reference frames in current numerical models. Traditionally, scientists working on ES view and analyze the results of calculated or measured observables with static 1-dimensional (1D), 2D or 3D plots displayed on flat computer screens or paper. Using such limited mediums, it can be very difficult to identify, track and understand the evolution of key features due to poor viewing angles and the nature of flat computer screens. In addition, numerical models, such as the NASA Goddard Earth Observing System (GEOS) ES model, are almost exclusively formulated, visualized and analyzed in an Eulerian reference frame with fixed grid points in space and time. However, ES phenomena such as convective clouds, hurricanes and wildfire smoke plumes are visualized and analyzed in a Lagrangian reference frame: therefore it is often difficult and unnatural to understand these phenomena in relation to each other, visualized either in an Eulerian or Lagrangian context. In 3D visualizations, data generally takes one of three forms: gridded (e.g., voxelized) data, where space is divided into regions; point clouds, where data is represented as a set of points; and meshes, where objects are rendered as surfaces composed of small polygons (usually triangles). A gridded, Eulerian reference frame has been the default representation for the 2D visual analysis of atmospheric data in part because the numerical methods used to generate atmospheric model data in the first place use a gridded approach, with equations defining the relationships between the physical variables in each of a grid's cells across successive timesteps. In our work, we are particularly interested in data from GEOS. Another reason why gridded representations tend to be used for visualizing data from such models is because trajectories are difficult to interpret from representations on 2D surfaces, due to line-of-sight ambiguity. Instead of a fixed grid from GEOS, we embed a trajectory model to simulate particles' movement throughout a GEOS run. We then ingest these particle trajectories as animated point clouds with a NASA open source XR toolkit, the Mixed Reality Exploration Toolkit (MRET), and merge GEOS data with ES phenomena data onto one combined visualization that the user can intuitively interact with. Efficient rendering of arbitrarily large point clouds is an ongoing challenge being addressed by the computer science community, with the GPU-based optimizations and efficient GPU memory utilization a common theme of recent advances, especially for XR, where sustained high frame rate is mandatory to save the user from suffering due to simulation sickness. In this work, we describe and evaluate our progress in choosing and implementing appropriate methods for rendering arbitrarily large point clouds within MRET for XR. While tracking the XR headset enables the immersion of a user within a 3D scene of a data visualization, tracking of XR handheld controllers or user’s hands enables us to implement intuitive user interactions with the visualized datasets. Conventional tools require a user working with an ES visualization to conduct many interactions to commit their intended selections or manipulations with a visualized dataset; for example to specify a set of points in 3D space. Doing so in a 2D flat screen interface has traditionally required specifying a set of points in three distinct 2D coordinate systems (XY, XZ, and YZ), which is cumbersome. In other scientific domains, it has been shown that specifying or selecting a location or volume in XR using handheld controllers or tracked hands allows for greater speed and accuracy. We anticipate the same will hold true for atmospheric data, and we will share initial results of measuring the utility of such an interface. Notably, as the data being visualized is generated by GEOS as a prediction based on initial conditions, an intended application of our tool is to serve as part of an iterative feedback loop. Through XR, a scientist will review and manipulate a GEOS model run, modifying the conditions as needed to do subsequent runs of GEOS. Thereby, XR-based improvements to speed and accuracy of 3D tagging of points minimizes the effort required by both the scientist and the computer cluster conducting the necessary calculations.

Thomas Grubb↗

NASA NTRS1997

Atomic, Molecular, and Optical Physics: Optical Excitation Function of H(1s-2p) Produced by electron Impact from Threshold to 1.8 keV

The optical excitation function of prompt Lyman-Alpha radiation, produced by electron impact on atomic hydrogen, has been measured over the extended energy range from threshold to 1.8 keV. Measurements were obtained in a crossed-beams experiment using both magnetically confined and electrostatically focused electrons in collision with atomic hydrogen produced by an intense discharge source. A vacuum-ultraviolet mono- chromator system was used to measure the emitted Lyman-Alpha radiation. The absolute H(1s-2p) electron impact excitation cross section was obtained from the experimental optical excitation function by normalizing to the accepted optical oscillator strength, with corrections for polarization and cascade. Statistical and known systematic uncertainties in our data range from +/- 4% near threshold to +/- 2% at 1.8 keV. Multistate coupling affecting the shape of the excitation function up to 1 keV impact energy is apparent in both the present experimental data and present theoretical results obtained with convergent close- coupling (CCC) theory. This shape function effect leads to an uncertainty in absolute cross sections at the 10% level in the analysis of the experimental data. The derived optimized absolute cross sections are within 7% of the CCC calculations over the 14 eV-1.8 keV range. The present CCC calculations converge on the Bethe- Fano profile for H(1s-2p) excitation at high energy. For this reason agreement with the CCC values to within 3% is achieved in a nonoptimal normalization of the experimental data to the Bethe-Fano profile. The fundamental H(1s-2p) electron impact cross section is thereby determined to an unprecedented accuracy over the 14 eV - 1.8 keV energy range.

James, G. K.↗

NASA NTRS1994

A mathematical model for simulating noise suppression of lined ejectors

A mathematical model containing the essential features embodied in the noise suppression of lined ejectors is presented. Although some simplification of the physics is necessary to render the model mathematically tractable, the current model is the most versatile and technologically advanced at the current time. A system of linearized equations and the boundary conditions governing the sound field are derived starting from the equations of fluid dynamics. A nonreflecting boundary condition is developed. In view of the complex nature of the equations, a parametric study requires the use of numerical techniques and modern computers. A finite element algorithm that solves the differential equations coupled with the boundary condition is then introduced. The numerical method results in a matrix equation with several hundred thousand degrees of freedom that is solved efficiently on a supercomputer. The model is validated by comparing results either with exact solutions or with approximate solutions from other works. In each case, excellent correlations are obtained. The usefulness of the model as an optimization tool and the importance of variable impedance liners as a mechanism for achieving broadband suppression within a lined ejector are demonstrated.

Watson, Willie R.↗

NASA NTRS1998

Development of Curved-Plate Elements for the Exact Buckling Analysis of Composite Plate Assemblies Including Transverse Shear Effects

The analytical formulation of curved-plate non-linear equilibrium equations that include transverse-shear-deformation effects is presented. A unified set of non-linear strains that contains terms from both physical and tensorial strain measures is used. Using several simplifying assumptions, linearized, stability equations are derived that describe the response of the plate just after bifurcation buckling occurs. These equations are then modified to allow the plate reference surface to be located a distance z(c), from the centroid surface which is convenient for modeling stiffened-plate assemblies. The implementation of the new theory into the VICONOPT buckling and vibration analysis and optimum design program code is described. Either classical plate theory (CPT) or first-order shear-deformation plate theory (SDPT) may be selected in VICONOPT. Comparisons of numerical results for several example problems with different loading states are made. Results from the new curved-plate analysis compare well with closed-form solution results and with results from known example problems in the literature. Finally, a design-optimization study of two different cylindrical shells subject to uniform axial compression is presented.

McGowan, David M.↗

NASA NTRS2000

Dry Ribbon for Heated Head Automated Fiber Placement

Ply-by-ply in situ processes involving automated heated head deposition are being developed for fabrication of high performance, high temperature composite structures from low volatile content polymer matrices. This technology requires (1) dry carbon fiber towpreg, (2) consolidation of towpreg to quality, placement-grade unidirectional ribbon or tape, and (3) rapid, in situ, accurate, ply-by-ply robotic placement and consolidation of this material to fabricate a composite structure. In this study, the physical properties of a candidate thermoplastic ribbon, PIXA/IM7, were evaluated and screened for suitability in robotic placement. Specifically, towpreg was prepared from PIXA powder. Various conditions (temperatures) were used to convert the powder-coated towpreg to ribbons with varying degrees of processability. Ribbon within preset specifications was fabricated at 3 temperatures: 390, 400 and 410 C. Ribbon was also produced out-of-spec by purposely overheating the material to a processing temperature of 450 C. Automated placement equipment at Cincinnati Milacron and NASA Langley was used to fabricate laminates from these experimental ribbons. Ribbons were placed at 405 and 450 C by both sets of equipment. Double cantilever beam and wedge peel tests were used to determine the quality of the laminates and, especially, the interlaminar bond formed during the placement process. Ribbon made under conditions expected to be non-optimal (overheated) resulted in poor placeability and composites with weak interlaminar bond strengths, regardless of placement conditions. Ribbon made under conditions expected to be ideal showed good processability and produced well-consolidated laminates. Results were consistent from machine to machine and demonstrated the importance of ribbon quality in heated-head placement of dry material forms. Preliminary screening criteria for the development and evaluation of ribbon from new matrix materials were validated.

Hulcher, A. Bruce↗

NASA NTRS2004

Progress of Multicolor Single Detector to Detector Array Development for Remote Sensing

Knowledge of the spatial and temporal distribution of atmospheric species such as CO2, O3, H2O, and CH4 is important for understanding the chemistry and physical cycles involving Earth s atmosphere. Although several remote sensing techniques are suitable for such measurements they are considered high cost techniques involving complicated instrumentation. Therefore, simultaneous measurement of atmospheric species using a single remote sensing instrument is significant for minimizing cost, size and complexity. While maintaining the instrument sensitivity and range, quality of multicolor detector, in terms of high quantum efficiency and low noise are vital for these missions. As the first step for developing multicolor focal plan array, the structure of a single element multicolor detector is presented in this paper. The detector consists of three p-n junction layers of Si, GaSb and InAs wafer bonded to cover the spectral range UV to 900 nm, 800 nm to 1.7 m, and 1.5 m to 3.4 m, respectively. Modeling of the absorption coefficient for each material was carried out for optimizing the layers thicknesses for maximum absorption. The resulted quantum efficiency of each layer has been determined except InAs layer. The optical and electrical characterization of each layer structure is reported including dark current and spectral response measurements of Si pin structure and of GaSb and InAs p-n junctions. The effect of the material processing is discussed.

Abedin, M. Nurul↗

NASA NTRS2001

Extensional Rheology Experiment Developed to Investigate the Rheology of Dilute Polymer Solutions in Microgravity

A fundamental characteristic of fluid is viscosity; that is, the fluid resists forces that cause it to flow. This characteristic, or parameter, is used by manufacturers and end-users to describe the physical properties of a specific material so that they know what to expect when a material, such as a polymer, is processed through an extruder, a film blower, or a fiber-spinning apparatus. Normally, researchers will report a shear viscosity that depends on the rate of an imposed shearing flow. Although this type of characterization is sufficient for some processes, simple shearing experiments do not provide a complete picture of what a processor may expect for all materials. Extensional stretching flows are common in many polymer-processing operations such as extrusion, blow molding, and fiber spinning. Therefore, knowledge of the complete rheological (ability to flow and be deformed) properties of the polymeric fluid being processed is required to accurately predict and account for the flow behavior. In addition, if numerical simulations are ever able to serve as a priori design tools for optimizing polymer processing operations such as those described above, an accurate knowledge of the extensional viscosity of a polymer system and its variation with temperature, concentration, molecular weight, and strain rate is critical.

Logsdon, Kirk A.↗