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527 records · Page 30

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NASA NTRS2003

Flame Synthesis Of Single-Walled Carbon Nanotubes And Nanofibers

Carbon nanotubes are widely sought for a variety of applications including gas storage, intercalation media, catalyst support and composite reinforcing material [1]. Each of these applications will require large scale quantities of CNTs. A second consideration is that some of these applications may require redispersal of the collected CNTs and attachment to a support structure. If the CNTs could be synthesized directly upon the support to be used in the end application, a tremendous savings in post-synthesis processing could be realized. Therein we have pursued both aerosol and supported catalyst synthesis of CNTs. Given space limitations, only the aerosol portion of the work is outlined here though results from both thrusts will be presented during the talk. Aerosol methods of SWNT, MWNT or nanofiber synthesis hold promise of large-scale production to supply the tonnage quantities these applications will require. Aerosol methods may potentially permit control of the catalyst particle size, offer continuous processing, provide highest product purity and most importantly, are scaleable. Only via economy of scale will the cost of CNTs be sufficient to realize the large-scale structural and power applications on both earth and in space. Present aerosol methods for SWNT synthesis include laser ablation of composite metalgraphite targets or thermal decomposition/pyrolysis of a sublimed or vaporized organometallic [2]. Both approaches, conducted within a high temperature furnace, have produced single-walled nanotubes (SWNTs). The former method requires sophisticated hardware and is inherently limited by the energy deposition that can be realized using pulsed laser light. The latter method, using expensive organometallics is difficult to control for SWNT synthesis given a range of gasparticle mixing conditions along variable temperature gradients; multi-walled nanotubes (MWNTs) are a far more likely end products. Both approaches require large energy expenditures and produce CNTs at prohibitive costs, around $500 per gram. Moreover these approaches do not possess demonstrated scalability. In contrast to these approaches, flame synthesis can be a very energy efficient, low-cost process [3]; a portion of the fuel serves as the heating source while the remainder serves as reactant. Moreover, flame systems are geometrically versatile as illustrated by innumerable boiler and furnace designs. Addressing scalability, flame systems are commercially used for producing megatonnage quantities of carbon black [4]. Although it presents a complex chemically reacting flow, a flame also offers many variables for control, e.g. temperature, chemical environment and residence times [5]. Despite these advantages, there are challenges to scaling flame synthesis as well.

Wal, Randy L. Vander↗

NASA NTRS2011

Should Pruning be a Pre-Processor of any Linear System?

There are many real-world problems whose mathematical models turn out to be linear systems Ax = b , where A is an m by x n matrix. Each equation of the linear system is an information. An information, in a physical problem, such as 4 mangoes, 6 bananas, and 5 oranges cost $10, is mathematically modeled as 4x(sub 1) + 6x(sub 2) + 5x (sub 3) = 10, where x(sub 1), x(sub 2), x(sub 3) are each cost of one mango, that of one banana, and that of one orange, respectively. All the information put together in a specified context, constitutes the physical problem and need not be all distinct. Some of these could be redundant, which cannot be readily identified by inspection. The resulting mathematical model will thus have equations corresponding to this redundant information and hence are linearly dependent and thus superfluous. Consequently, these equations once identified should be better pruned in the process of solving the system. The benefits are (i) less computation and hence less error and consequently a better quality of solution and (ii) reduced storage requirements. In literature, the pruning concept is not in vogue so far although it is most desirable. In a numerical linear system, the system could be slightly inconsistent or inconsistent of varying degree. If the system is too inconsistent, then we should fall back on to the physical problem (PP), check the correctness of the PP derived from the material universe, modify it, if necessary, and then check the corresponding mathematical model (MM) and correct it. In nature/material universe, inconsistency is completely nonexistent. If the MM becomes inconsistent, it could be due to error introduced by the concerned measuring device and/or due to assumptions made on the PP to obtain an MM which is relatively easily solvable or simply due to human error. No measuring device can usually measure a quantity with an accuracy greater that 0.005% or, equivalently with a relative error less than 0.005%. Hence measurement error is unavoidable in a numerical linear system when the quantities are continuous (or even discrete with extremely large number). Assumptions, though not desirable, are usually made when we find the problem sufficiently difficult to be solved within the available means/tools/resources and hence distort the PP and the corresponding MM. The error thus introduced in the system could (not always necessarily though) make the system somewhat inconsistent. If the inconsistency (contradiction) is too much then one should definitely not proceed to solve the system in terms of getting a least-squares solution or a minimum norm solution or the minimum-norm least-squares solution. All these solutions will be invariably of no real-world use. If, on the other hand, inconsistency is reasonably low, i.e. the system is near-consistent or, equivalently, has near-linearly-dependent rows, then the foregoing solutions are useful. Pruning in such a near-consistent system should be performed based on the desired accuracy and on the definition of near-linear dependence. In this article, we discuss pruning over various kinds of linear systems and strongly suggest its use as a pre-processor or as a part of an algorithm. Ideally pruning should (i) be a part of the solution process (algorithm) of the system, (ii) reduce both computational error and complexity of the process, and (iii) take into account the numerical zero defined in the context. These are precisely what we achieve through our proposed O(mn2) algorithm presented in Matlab, that uses a subprogram of solving a single linear equation and that has embedded in it the pruning.

Sen, Syamal K.↗

NASA NTRS2011

Should Pruning be a Pre-Processor of any Linear System?

There are many real-world problems whose mathematical models turn out to be linear systems Ax = b, where A is an m x n matrix. Each equation of the linear system is an information. An information, in a physical problem, such as 4 mangoes, 6 bananas, and 5 oranges cost $10, is mathematically modeled as an equation 4x(sub 1) + 6x(sub 2) + 5x(sub 3) = 10 , where x(sub 1), x(sub 2), x(sub 3) are each cost of one mango, that of one banana, and that of one orange, respectively. All the information put together in a specified context, constitutes the physical problem and need not be all distinct. Some of these could be redundant, which cannot be readily identified by inspection. The resulting mathematical model will thus have equations corresponding to this redundant information and hence are linearly dependent and thus superfluous. Consequently, these equations once identified should be better pruned in the process of solving the system. The benefits are (i) less computation and hence less error and consequently a better quality of solution and (ii) reduced storage requirements. In literature, the pruning concept is not in vogue so far although it is most desirable. It is assumed that at least one information, i.e. one equation is known to be correct and which will be our first equation. In a numerical linear system, the system could be slightly inconsistent or inconsistent of varying degree. If the system is too inconsistent, then we should fall back on to the physical problem (PP), check the correctness of the PP derived from the material universe, modify it, if necessary, and then check the corresponding mathematical model (MM) and correct it. In nature/material universe, inconsistency is completely nonexistent. If the MM becomes inconsistent, it could be due to error introduced by the concerned measuring device and/or due to assumptions made on the PP to obtain an MM which is relatively easily solvable or simply due to human error. No measuring device can usually measure a quantity with an accuracy greater that 0.005% or, equivalently with a relative error less than 0.005%. Hence measurement error is unavoidable in a numerical linear system when the quantities are continuous (or even discrete with extremely large number). Assumptions, though not desirable, are usually made when we find the problem sufficiently difficult to be solved within the available means/tools/resources and hence distort the PP and the corresponding MM. The . error thus introduced in the system could (not always necessarily though) make the system somewhat inconsistent. If the inconsistency (contradiction) is too much then one should definitely not proceed to solve the system in terms of getting a least-squares solution or the minimum-norm least-squares solution. All these solutions will be invariably of no real-world use. If, on the other hand, inconsistency is reasonably low, i.e. the system is near-consistent or, equivalently, has near-linearly-dependent rows, then the foregoing solutions are useful. Pruning in such a near-consistent system should be performed based on the desired accuracy and on the definition of near-linear dependence. In this article, we discuss pruning over various kinds of linear systems and strongly suggest its use as a pre-processor or as a part of an algorithm. Ideally pruning should (i) be a part of the solution process (algorithm) of the system, (ii) reduce both computational error and complexity of the process, and (iii) take into account the numerical zero defined in the context. These are precisely what we achieve through our proposed O(mn2) algorithm presented in Matlab, that uses a subprogram of solving a single linear equation and that has embedded in it the pruning.

Sen, Syamal K.↗

NASA NTRS1998

Measuring Thermal Conductivity and Moisture Absorption of Cryo-Insulation Materials

NASA is seeking to develop thermal insulation material systems suitable for withstanding both extremely high temperatures encountered during atmospheric re-entry heating and aero- braking maneuvers, as well as extremely low temperatures existing in liquid fuel storage tanks. Currently, materials used for the high temperature insulation or Thermal Protection System (TPS) are different from the low temperature, or cryogenic insulation. Dual purpose materials are necessary to the development of reusable launch vehicles (RLV). The present Space Shuttle (or Space Transportation System, STS) employs TPS materials on the orbiter and cryo-insulation materials on the large fuel tank slung under the orbiter. The expensive fuel tank is jettisoned just before orbit is achieved and it burns up while re-entering over the Indian Ocean. A truly completely reusable launch vehicle must store aR cryogenic fuel internally. The fuel tanks will be located close to the outer surface. In fact the outer skin of the craft will probably also serve as the fuel tank enclosure, as in jet airliners. During a normal launch the combined TPS/cryo-insulation system will serve only as a low temperature insulator, since aerodynamic heating is relatively minimal during ascent to orbit. During re-entry, the combined TPS/cryo-insulation system will serve only as a high temperature insulator, since all the cryogenic fuel will have been expended in orbit. However, in the event of an.aborted launch or a forced/emergency early re-entry, the tanks will still contain fuel, and the TPS/cryo-insulation will have to serve as both low and high temperature insulation. Also, on long duration missions, such as to Mars, very effective cryo-insulation materials are needed to reduce bod off of liquid propellants, thereby reducing necessary tankage volume, weight, and cost. The conventional approach to obtaining both low and high temperature insulation, such as is employed for the X-33 and X-34 spacecraft, is to use separate TPS and cryo-insulation materials, which are connected by means of adhesives or stand-offs (spacers). Three concepts are being considered: (1) the TPS is bonded directly to the cryo-insulation which, in turn, is bonded to the exterior of the tank, (2) stand-offs are used to make a gap between the TPS and the cryo-insulation, which is bonded externally to the tank, (3) TPS is applied directly or with stand-offs to the exterior so the tank, and cryo-insulation is applied directly to the interior of the tank. Many potential problems are inherent in these approaches. For example, mismatch between coefficients of thermal expansion of the TPS and cryo-insulation, as well as aerodynamic loads, could lead to failure of the bond. Internal cryo-insulation must be prevent from entering the sump of the fuel turbo-pump. The mechanical integrity of the stand-off structure (if used) must withstand multiple missions. During ground hold (i.e., prior to launch) moisture condensation must be minimized in the gap between the cryo-insulation and the TPS. The longer term solution requires the development of a single material to act as cryo- insulation during ground hold and as TPS during re-entry. Such a material minimizes complexity and weight while improving reliability and reducing cost.

Lambert, Michael A.↗

NASA NTRSDate not supplied

Some Aeronautical Communications Experiments

Classically there has existed an asymmetry between the computing and communicating sides of aerospace systems. Over the past few decades, this asymmetry has shifted to favoring communication link technologies, meaning that advancements in available central processing units (CPUs), storage devices, and internal data buses have stagnated. Indeed, the increased emphasis placed on refining subsystem performance such as with antenna bandwidth in phased arrays, amplifier power efficiency, software defined radio (SDR) flexibility and encoding for data compression and error correction has given rise to successful debuts of multi-gigabit-per-second data return from long space-link distances. These accomplishments are easily quantifiable through link budgets and illustrate what is possible, but also reveal the deficiencies in overall communications capabilities. In particular, the ever-accelerating presence of aerospace vehicles gives rise to newer and larger classes of challenges to address the needs of 21st century systems. Furthermore remote sensing and imaging capabilities have far outpaced our ability to transmit their products to the ground, so we are increasingly dependent on pre-processing and downselection to contend with the communications bottleneck. No longer may we depend upon the constrained logistics in delivering end-to-end data delivery through manual reconfigurations, static event scheduling and execution on a per-vehicle basis, for these methods do not scale and therefore must give way to dynamic, networked approaches with an overall systems view in mind. Emerging mission requirements exhibit a trend toward multiple smaller-scale vehicles working together to perform dissimilar observations. Such operations necessitate sensor fusion across a constellation, and where data processing may be distributed throughout a fairly disconnected network whose topology changes over time in non-deterministic manners. Individual communications link performance is still very relevant to deploying an effective communications system, but now must be embedded within a greater architecture of capability to optimally utilize the bandwidth available from each link to generate an ultimate end-to-end quality of service. The deleterious effects of timing uncertainty across the arrangement presents a challenge to measurement synchronization and delivery, so a successful deployed system needs to be tolerant to the delays inherent in time-of-light between elements and digital processing latencies existing at each node. In this presentation we share the flight test results from a high performance Gbps laser communications terminal evaluated with a suite of store and forward capabilities called High-rate Delay Tolerant Networking (HDTN). The communications payload is operated over Lake Erie across a range of configurations including several convergence layers, and is evaluated to determine recovery time after link disruptions, information loss, efficiency and speed. The effectiveness of utilizing a flying laboratory to increase the Technology Readiness Level (TRL) of an integrated system in relevant environments is discussed, as well as the value of conducting aeronautics experiments to retire risk for technology infusion into space missions. Upcoming flight campaigns will be presented, including opportunities to demonstrate secure command and control, data intensive hyperspectral imaging, quantum link characterization, 4k High Definition (HD) video streaming and internetworked space-ground-aero relay operations. These experiments will pave the way for future missions which will depend upon interoperability across disparate government and privately owned networks, involve contention with uncertain and dynamic timing, and require agility to autonomously configure optimal parameters across networks of ever-increasing size and complexity to ensure data delivery. https://www1.grc.nasa.gov/space/scan/acs/tech-studies/dtn/

Daniel Raible↗