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All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Isolation of Resistance-Bearing Microorganisms

To better exploit the principles of gas transport and mass transport during the processes of cell seeding of 3D scaffolds and in vitro culture of 3D tissue engineered constructs, the oscillatory cell culture bioreactor provides a flow of cell suspensions and culture media directly through a porous 3D scaffold (during cell seeding) and a 3D construct (during subsequent cultivation) within a highly gas-permeable closed-loop tube. This design is simple, modular, and flexible, and its component parts are easy to assemble and operate, and are inexpensive. Chamber volume can be very low, but can be easily scaled up. This innovation is well suited to work with different biological specimens, particularly with cells having high oxygen requirements and/or shear sensitivity, and different scaffold structures and dimensions. The closed-loop changer is highly gas permeable to allow efficient gas exchange during the cell seeding/culturing process. A porous scaffold, which may be seeded with cells, is fixed by means of a scaffold holder to the chamber wall with scaffold/construct orientation with respect to the chamber determined by the geometry of the scaffold holder. A fluid, with/without biological specimens, is added to the chamber such that all, or most, of the air is displaced (i.e., with or without an enclosed air bubble). Motion is applied to the chamber within a controlled environment (e.g., oscillatory motion within a humidified 37 C incubator). Movement of the chamber induces relative motion of the scaffold/construct with respect to the fluid. In case the fluid is a cell suspension, cells will come into contact with the scaffold and eventually adhere to it. Alternatively, cells can be seeded on scaffolds by gel entrapment prior to bioreactor cultivation. Subsequently, the oscillatory cell culture bioreactor will provide efficient gas exchange (i.e., of oxygen and carbon dioxide, as required for viability of metabolically active cells) and controlled levels of fluid dynamic shear (i.e., as required for viability of shear-sensitive cells) to the developing engineered tissue construct. This bioreactor was recently utilized to show independent and interactive effects of a growth factor (IGF-I) and slow bidirectional perfusion on the survival, differentiation, and contractile performance of 3D tissue engineering cardiac constructs. The main application of this system is within the tissue engineering industry. The ideal final application is within the automated mass production of tissue- engineered constructs. Target industries could be both life sciences companies as well as bioreactor device producing companies.

Venkateswaran, Kasthuri, J.↗
NASA NTRS2010

Oscillating Cell Culture Bioreactor

To better exploit the principles of gas transport and mass transport during the processes of cell seeding of 3D scaffolds and in vitro culture of 3D tissue engineered constructs, the oscillatory cell culture bioreactor provides a flow of cell suspensions and culture media directly through a porous 3D scaffold (during cell seeding) and a 3D construct (during subsequent cultivation) within a highly gas-permeable closed-loop tube. This design is simple, modular, and flexible, and its component parts are easy to assemble and operate, and are inexpensive. Chamber volume can be very low, but can be easily scaled up. This innovation is well suited to work with different biological specimens, particularly with cells having high oxygen requirements and/or shear sensitivity, and different scaffold structures and dimensions. The closed-loop changer is highly gas permeable to allow efficient gas exchange during the cell seeding/culturing process. A porous scaffold, which may be seeded with cells, is fixed by means of a scaffold holder to the chamber wall with scaffold/construct orientation with respect to the chamber determined by the geometry of the scaffold holder. A fluid, with/without biological specimens, is added to the chamber such that all, or most, of the air is displaced (i.e., with or without an enclosed air bubble). Motion is applied to the chamber within a controlled environment (e.g., oscillatory motion within a humidified 37 C incubator). Movement of the chamber induces relative motion of the scaffold/construct with respect to the fluid. In case the fluid is a cell suspension, cells will come into contact with the scaffold and eventually adhere to it. Alternatively, cells can be seeded on scaffolds by gel entrapment prior to bioreactor cultivation. Subsequently, the oscillatory cell culture bioreactor will provide efficient gas exchange (i.e., of oxygen and carbon dioxide, as required for viability of metabolically active cells) and controlled levels of fluid dynamic shear (i.e., as required for viability of shear-sensitive cells) to the developing engineered tissue construct. This bioreactor was recently utilized to show independent and interactive effects of a growth factor (IGF-I) and slow bidirectional perfusion on the survival, differentiation, and contractile performance of 3D tissue engineering cardiac constructs. The main application of this system is within the tissue engineering industry. The ideal final application is within the automated mass production of tissue- engineered constructs. Target industries could be both life sciences companies as well as bioreactor device producing companies.

Freed, Lisa E.↗
NASA NTRS1993

Al-26 production profile and model comparisons in Canyon Diablo

The large preatmospheric size of the Canyon Diablo meteorite, a radius of about 15 m, makes it especially suitable for systematic studies of cosmogenic nuclide production rates of iron objects in a 2 pi geometry. To reconstruct the exposure history of the meteoroid, Heymann et al. investigated several fragments recovered from known geographic locations around the crater for their shock features and cosmogenic nobel gases. They applied the Signer-Nier noble gas production rate model to establish the preatmospheric depth of the specimens in the meteoroid. Cosmic ray exposure ages suggested a multi-episodic irradiation, with 170 or 540 Ma being inferred for most of the samples studied while two anomalous specimens indicated a possible third exposure age at 940 Ma. Be-10 and Cl-36 have been measured in a number of these same samples by accelerator mass spectrometry (AMS), with use being made of the preatmospheric depths determined in Heymann et al. to construct production profiles. The present study extends the cosmogenic radionuclide data to Al-26 and compares the results with both the production rate model of Reedy and Arnold and production rates determined from the cross sections used by the Reedy-Arnold model (for the major nuclear reactions making Al-26) in combination with differential fluxes calculated using the Los Alamos High Energy Transport (LAHET) Code System. Model calculations for Be-10 and Cl-36 have also been obtained.

Michlovich, E.↗
NASA NTRS2009

T-Slide Linear Actuators

T-slide linear actuators use gear bearing differential epicyclical transmissions (GBDETs) to directly drive a linear rack, which, in turn, performs the actuation. Conventional systems use a rotary power source in conjunction with a nut and screw to provide linear motion. Non-back-drive properties of GBDETs make the new actuator more direct and simpler. Versions of this approach will serve as a long-stroke, ultra-precision, position actuator for NASA science instruments, and as a rugged, linear actuator for NASA deployment duties. The T slide can operate effectively in the presence of side forces and torques. Versions of the actuator can perform ultra-precision positioning. A basic T-slide actuator is a long-stroke, rack-and-pinion linear actuator that, typically, consists of a T-slide, several idlers, a transmission to drive the slide (powered by an electric motor) and a housing that holds the entire assembly. The actuator is driven by gear action on its top surface, and is guided and constrained by gear-bearing idlers on its other two parallel surfaces. The geometry, implemented with gear-bearing technology, is particularly effective. An electronic motor operating through a GBDET can directly drive the T slide against large loads, as a rack and pinion linear actuator, with no break and no danger of back driving. The actuator drives the slide into position and stops. The slide holes position with power off and no brake, regardless of load. With the T slide configuration, this GBDET has an entire T-gear surface on which to operate. The GB idlers coupling the other two T slide parallel surfaces to their housing counterpart surfaces provide constraints in five degrees-of-freedom and rolling friction in the direction of actuation. Multiple GB idlers provide roller bearing strength sufficient to support efficient, rolling friction movement, even in the presence of large, resisting forces. T-slide actuators can be controlled using the combination of an off-the-shelf, electric servomotor, a motor angle resolution sensor (typically an encoder or resolver), and microprocessor-based intelligent software. In applications requiring precision positioning, it may be necessary to add strain gauges to the T-slide housing. Existing sensory- interactive motion control art will work for T slides. For open-loop positioning, a stepping motor emulation technique can be used.

Vranish, John↗
NASA NTRS2001

The Role of Convection and Growth Competition in Phase Selection in Microgravity: Controlled Convection in the Containerless Processing of Steel Alloys

Containerless processing using electromagnetic levitation (EML) is a powerful technique in the investigation of reactive molten metal systems. On ground, the power required to overcome the weight of the sample is sufficient to cause significant heating and induce substantial melt convection. In microgravity, the heating and positioning fields may be decoupled and the field strength may be varied to achieve the desired level of convection within the limits set by the geometry of the levitation coil and the sample size. From high-speed digital images of the double recalescence behavior of Fe-Cr-Ni alloys in ground-based testing and in reduced-gravity aboard the NASA KC-135 parabolic aircraft, we have shown that phase selection can be predicted based on a growth competition model. An important parameter in this model is the delay time between primary nucleation and subsequent nucleation of the stable solid within the liquid/metastable solid array. This delay time is a strong function of composition and a weak function of the undercooling of the melt below the metastable liquidus. From the results obtained during the first Microgravity Sciences Laboratory (MSL-1) mission, we also know that convection may significantly influence the delay time, especially at low undercoolings. Currently, it is unclear what mechanism controls the formation of a heterogeneous site that allows nucleation of the austenitic phase on the pre-existing ferrite skeleton. By examining the behavior of the delay time under different convective conditions, we hypothesize that we can differentiate between several of these mechanisms to gain an understanding of how to control microstructural. evolution. We will anchor these predictions by examining samples quenched at different times following primary recalescence in microgravity. A second important parameter in the growth competition model is the identification of the growth rate of the stable phase into the semi-solid array that formed during primary recalescence. Current dendritic growth theory is inadequate in predicting solidification behavior under these conditions as metallographic analyses show that stable phase growth proceeds along the interface between the metastable solid and residual liquid. Since growth velocity is independent of the initial undercooling relative to the metastable liquidus, we hypothesize that purely thermal effects can be separated from other important growth model parameters by careful selection of the liquid composition in a ternary system.

Matson, D. M.↗
NASA NTRS1996

Comparative Study of Advanced Turbulence Models for Turbomachinery

A computational study has been undertaken to study the performance of advanced phenomenological turbulence models coded in a modular form to describe incompressible turbulent flow behavior in two dimensional/axisymmetric and three dimensional complex geometry. The models include a variety of two equation models (single and multi-scale k-epsilon models with different near wall treatments) and second moment algebraic and full Reynolds stress closure models. These models were systematically assessed to evaluate their performance in complex flows with rotation, curvature and separation. The models are coded as self contained modules that can be interfaced with a number of flow solvers. These modules are stand alone satellite programs that come with their own formulation, finite-volume discretization scheme, solver and boundary condition implementation. They will take as input (from any generic Navier-Stokes solver) the velocity field, grid (structured H-type grid) and computational domain specification (boundary conditions), and will deliver, depending on the model used, turbulent viscosity, or the components of the Reynolds stress tensor. There are separate 2D/axisymmetric and/or 3D decks for each module considered. The modules are tested using Rocketdyn's proprietary code REACT. The code utilizes an efficient solution procedure to solve Navier-Stokes equations in a non-orthogonal body-fitted coordinate system. The differential equations are discretized over a finite-volume grid using a non-staggered variable arrangement and an efficient solution procedure based on the SIMPLE algorithm for the velocity-pressure coupling is used. The modules developed have been interfaced and tested using finite-volume, pressure-correction CFD solvers which are widely used in the CFD community. Other solvers can also be used to test these modules since they are independently structured with their own discretization scheme and solver methodology. Many of these modules have been independently tested by Professor C.P. Chen and his group at the University of Alabama at Huntsville (UAH) by interfacing them with own flow solver (MAST).

Hadid, Ali H.↗
NASA NTRS1987

Damage growth in composite laminates with interleaves

The influence of placing interleaves between fiber reinforced plies in multilayered composite laminates is investigated. The geometry of the composite is idealized as two dimensional, isotropic, linearly elastic media made of a damaged layer bonded between two half planes and separated by thin interleaves of low extensional and shear moduli. The damage in the layer is taken in the form of a symmetric crack perpendicular to the interface and may extend up to the interface. The case of an H-shaped crack in the form of a broken layer with delamination along the interface is also analyzed. The interleaves are modeled as distributed shear and tension springs. Fourier integral transform techniques are used to develop solutions in terms of singular integral equations. An asymptotic analysis of the integral equations based on Muskhelishvili's techniques reveals logarithmically singular axial stresses in the half plane at the crack tips for the broken layer. For the H shaped crack, similar singularities are found to exist in the axial stresses at the interface crack tips in the layer and the half plane. The solution of the equations is found numerically for the stresses and displacements by using the Hadamard's concept of direct differentiation of Cauchy integrals as well as Gaussian integration techniques.

Goree, James G.↗
NASA NTRS1998

Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes

A code trellis is a graphical representation of a code, block or convolutional, in which every path represents a codeword (or a code sequence for a convolutional code). This representation makes it possible to implement Maximum Likelihood Decoding (MLD) of a code with reduced decoding complexity. The most well known trellis-based MLD algorithm is the Viterbi algorithm. The trellis representation was first introduced and used for convolutional codes [23]. This representation, together with the Viterbi decoding algorithm, has resulted in a wide range of applications of convolutional codes for error control in digital communications over the last two decades. There are two major reasons for this inactive period of research in this area. First, most coding theorists at that time believed that block codes did not have simple trellis structure like convolutional codes and maximum likelihood decoding of linear block codes using the Viterbi algorithm was practically impossible, except for very short block codes. Second, since almost all of the linear block codes are constructed algebraically or based on finite geometries, it was the belief of many coding theorists that algebraic decoding was the only way to decode these codes. These two reasons seriously hindered the development of efficient soft-decision decoding methods for linear block codes and their applications to error control in digital communications. This led to a general belief that block codes are inferior to convolutional codes and hence, that they were not useful. Chapter 2 gives a brief review of linear block codes. The goal is to provide the essential background material for the development of trellis structure and trellis-based decoding algorithms for linear block codes in the later chapters. Chapters 3 through 6 present the fundamental concepts, finite-state machine model, state space formulation, basic structural properties, state labeling, construction procedures, complexity, minimality, and sectionalization of trellises. Chapter 7 discusses trellis decomposition and subtrellises for low-weight codewords. Chapter 8 first presents well known methods for constructing long powerful codes from short component codes or component codes of smaller dimensions, and then provides methods for constructing their trellises which include Shannon and Cartesian product techniques. Chapter 9 deals with convolutional codes, puncturing, zero-tail termination and tail-biting.Chapters 10 through 13 present various trellis-based decoding algorithms, old and new. Chapter 10 first discusses the application of the well known Viterbi decoding algorithm to linear block codes, optimum sectionalization of a code trellis to minimize computation complexity, and design issues for IC (integrated circuit) implementation of a Viterbi decoder. Then it presents a new decoding algorithm for convolutional codes, named Differential Trellis Decoding (DTD) algorithm. Chapter 12 presents a suboptimum reliability-based iterative decoding algorithm with a low-weight trellis search for the most likely codeword. This decoding algorithm provides a good trade-off between error performance and decoding complexity. All the decoding algorithms presented in Chapters 10 through 12 are devised to minimize word error probability. Chapter 13 presents decoding algorithms that minimize bit error probability and provide the corresponding soft (reliability) information at the output of the decoder. Decoding algorithms presented are the MAP (maximum a posteriori probability) decoding algorithm and the Soft-Output Viterbi Algorithm (SOVA) algorithm. Finally, the minimization of bit error probability in trellis-based MLD is discussed.

Lin, Shu↗
NASA NTRS1993

Structured adaptive grid generation using algebraic methods

The accuracy of the numerical algorithm depends not only on the formal order of approximation but also on the distribution of grid points in the computational domain. Grid adaptation is a procedure which allows optimal grid redistribution as the solution progresses. It offers the prospect of accurate flow field simulations without the use of an excessively timely, computationally expensive, grid. Grid adaptive schemes are divided into two basic categories: differential and algebraic. The differential method is based on a variational approach where a function which contains a measure of grid smoothness, orthogonality and volume variation is minimized by using a variational principle. This approach provided a solid mathematical basis for the adaptive method, but the Euler-Lagrange equations must be solved in addition to the original governing equations. On the other hand, the algebraic method requires much less computational effort, but the grid may not be smooth. The algebraic techniques are based on devising an algorithm where the grid movement is governed by estimates of the local error in the numerical solution. This is achieved by requiring the points in the large error regions to attract other points and points in the low error region to repel other points. The development of a fast, efficient, and robust algebraic adaptive algorithm for structured flow simulation applications is presented. This development is accomplished in a three step process. The first step is to define an adaptive weighting mesh (distribution mesh) on the basis of the equidistribution law applied to the flow field solution. The second, and probably the most crucial step, is to redistribute grid points in the computational domain according to the aforementioned weighting mesh. The third and the last step is to reevaluate the flow property by an appropriate search/interpolate scheme at the new grid locations. The adaptive weighting mesh provides the information on the desired concentration of points to the grid redistribution scheme. The evaluation of the weighting mesh is accomplished by utilizing the weight function representing the solution variation and the equidistribution law. The selection of the weight function plays a key role in grid adaptation. A new weight function utilizing a properly weighted boolean sum of various flowfield characteristics is defined. The redistribution scheme is developed utilizing Non-Uniform Rational B-Splines (NURBS) representation. The application of NURBS representation results in a well distributed smooth grid by maintaining the fidelity of the geometry associated with boundary curves. Several algebraic methods are applied to smooth and/or nearly orthogonalize the grid lines. An elliptic solver is utilized to smooth the grid lines if there are grid crossings. Various computational examples of practical interest are presented to demonstrate the success of these methods.

Yang, Jiann-Cherng↗
NASA NTRS1999

Effects of Melt Processing on Evolution of Structure in PEEK

We report on the effects of melt processing temperature on structure formation in Poly(ether-ether-ketone), PEEK. Real time Small Angle X-ray Scattering, SAXS, and thermal analysis are used to follow the melting behavior after various stages of processing. Assignment of peaks to structural entities within the material, the relative perfection of the crystals, and the possibility of their reorganization, are all influenced by the melt processing history. With the advent of high intensity synchrotron sources of X-radiation, polymer scientists gain a research tool which, when used along with thermal analysis, provides additional structural information about the crystals during growth and subsequent melting. PEEK is an engineering thermoplastic polymer with a very high glass transition temperature (145 C) and crystal melting point (337 C). PEEK has been the subject of recent studies by X-ray scattering in which melt and cold crystallization were followed in real-time. X-ray scattering and thermal studies have been used to address the formation of dual endothermic response which has been variously ascribed to lamellar insertion, dual crystal populations, or melting followed by re-crystallization. Another important issue is whether all of the amorphous phase is located in interlamellar regions, or alternatively whether some is located in "pockets" away from the crystalline lamellar stacks. The interpretation of scattering from lamellar stacks varies depending upon whether such amorphous pockets are formed. Some groups believe all of the amorphous phase is interlamellar. This leads to selection of a smaller thickness for the crystals. Other groups suggest that most amorphous phase is not interlamellar, and this leads to the suggestion that the crystal thickness is larger than the amorphous layer within the stacks. To investigate these ideas, we used SAXS and Differential Scanning Calorimetry to compare results of single and dual stage melt crystallization of PEEK using a treatment scheme involving annealing/crystallization at T(sub a1) followed by annealing at T(sub a2) where either T(sub a1) < T(sub a2) or T(sub a1) > T(sub a2). We proposed a model to explain multiple melting endotherms in PPS, treated according to one or two-stage melt or cold crystallization. Key features of this model are that multiple endotherms: (1) are due to reorganization/recrystallization after cold crystallization; and, (2) are dominated by crystal morphology after melt crystallization at high T. In other words, multiple distinct crystal populations are formed by the latter treatment, leading to observation of multiple melting. PEEK 45OG pellets (ICI Americas) were the starting material for this study. Films were compression molded at 400 C, then quenched to ice water. Samples were heated to 375 C in a Mettler FP80 hot stage and held for three min. to erase crystal seeds before cooling them to T(sub a1) = 280 C . Samples were held at T(sub a2) for a period of time, then immediately heated to 360 C. In the second treatment samples were held at T(sub a1) = 31 C for different crystallization times t(sub c) then cooled to 295 C and held 15 min. In situ (SAXS) experiments were performed at the Brookhaven National Synchrotron Light Source with the sample located inside the Mettler hot stage. The system was equipped with a two-dimensional position sensitive detector. The sample to detector distance was 172.7 cm and the X-ray wavelength was 1.54 Angstroms. SAXS data were taken continuously during the isothermal periods and during the heating to 360 C at 5 C/min. Each SAXS scan was collected for 30 sec. Since the samples were isotropic, circular integration was used to increase the signal to noise ratio. After dual stage melt crystallization with T(sub a1) < T(sub a2) the lower melting endotherm arises from holding at T(sub a1). During cooling a broad distribution of crystals forms, and the low-melting tail is perfected during T(sub al). Heating to T(sub a2) melts these imperfect crystals and allows others with greater average long spacing to form in their place. After dual stage crystallization with T(sub a1) > T(sub a2), the amount of space remaining for additional growth at T(sub a2) depends upon the holding time at T(sub a1). The long period of crystals formed at T(sub a2) is smaller than that formed at T(sub a1) due to growth in a now-restricted geometry. Perfection of crystals is seen as an increase of the intensity of the population scattering at higher s, while the intensity of the population scattering at lower s stays constant. During heating from below to above the minor endotherm, we see rapid decrease of the intensity of the X-ray scattering corresponding to the population of crystals scattering in the shoulder. Another important observation is that after the sample is annealed at 295 C, the shoulder intensity is restored once again. The population scattering at higher s remains longer before it disappears in the sample treated to the second stage of melt crystallization, compared to the sample crystallized with a single stage. This could be interpreted as an effect of continued perfection of the less perfect population, which is also reflected in the increased melting temperature of the smaller endotherm as the holding time at 295 C increases. In the corresponding DSC scans we see a shift in the area and the peak temperature of the lower melting endotherm with an increase of the annealing time.

Georgiev, Georgi↗
NASA NTRS2008

Spiking Neurons for Analysis of Patterns

Artificial neural networks comprising spiking neurons of a novel type have been conceived as improved pattern-analysis and pattern-recognition computational systems. These neurons are represented by a mathematical model denoted the state-variable model (SVM), which among other things, exploits a computational parallelism inherent in spiking-neuron geometry. Networks of SVM neurons offer advantages of speed and computational efficiency, relative to traditional artificial neural networks. The SVM also overcomes some of the limitations of prior spiking-neuron models. There are numerous potential pattern-recognition, tracking, and data-reduction (data preprocessing) applications for these SVM neural networks on Earth and in exploration of remote planets. Spiking neurons imitate biological neurons more closely than do the neurons of traditional artificial neural networks. A spiking neuron includes a central cell body (soma) surrounded by a tree-like interconnection network (dendrites). Spiking neurons are so named because they generate trains of output pulses (spikes) in response to inputs received from sensors or from other neurons. They gain their speed advantage over traditional neural networks by using the timing of individual spikes for computation, whereas traditional artificial neurons use averages of activity levels over time. Moreover, spiking neurons use the delays inherent in dendritic processing in order to efficiently encode the information content of incoming signals. Because traditional artificial neurons fail to capture this encoding, they have less processing capability, and so it is necessary to use more gates when implementing traditional artificial neurons in electronic circuitry. Such higher-order functions as dynamic tasking are effected by use of pools (collections) of spiking neurons interconnected by spike-transmitting fibers. The SVM includes adaptive thresholds and submodels of transport of ions (in imitation of such transport in biological neurons). These features enable the neurons to adapt their responses to high-rate inputs from sensors, and to adapt their firing thresholds to mitigate noise or effects of potential sensor failure. The mathematical derivation of the SVM starts from a prior model, known in the art as the point soma model, which captures all of the salient properties of neuronal response while keeping the computational cost low. The point-soma latency time is modified to be an exponentially decaying function of the strength of the applied potential. Choosing computational efficiency over biological fidelity, the dendrites surrounding a neuron are represented by simplified compartmental submodels and there are no dendritic spines. Updates to the dendritic potential, calcium-ion concentrations and conductances, and potassium-ion conductances are done by use of equations similar to those of the point soma. Diffusion processes in dendrites are modeled by averaging among nearest-neighbor compartments. Inputs to each of the dendritic compartments come from sensors. Alternatively or in addition, when an affected neuron is part of a pool, inputs can come from other spiking neurons. At present, SVM neural networks are implemented by computational simulation, using algorithms that encode the SVM and its submodels. However, it should be possible to implement these neural networks in hardware: The differential equations for the dendritic and cellular processes in the SVM model of spiking neurons map to equivalent circuits that can be implemented directly in analog very-large-scale integrated (VLSI) circuits.

Huntsberger, Terrance↗