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Description of general purpose digital computer program /NASTRAN/ for analysis of elastic structures under various loading conditions using finite element method approach
The Landau damping of electrostatic Langmuir waves and ion-acoustic waves in a hot, isotropic, nonmagnetized, generalized Lorentzian plasma is analyzed using the modified plasma dispersion function. Numerical solutions for the real and imaginary parts of the wave frequency omega sub 0 - (i)(gamma) have been obtained as a function of the normalized wave number (k)(lambda sub D), where lambda sub D is the electron Debye length. For both particle distributions the electrostatic modes are found to be strongly damped at short wavelengths. At long wavelengths, this damping becomes less severe, but the attenuation of Langmuir waves is much stronger for a generalized Lorentzian plasma than for a Maxwellian plasma. It is concluded that Landau damping of ion-acoustic waves is only slightly affected by the presence of a high energy tail, but is strongly dependent on the ion temperature.
A general method described by Hermann and Martin (1976) for the study of the feedback invariants of linear systems is considered. It is shown that this method, which makes use of ideas of topology and algebraic geometry, is very useful in the investigation of feedback problems for which the classical methods are not suitable. The transfer function as a curve in the Grassmanian is examined. The general concepts studied in the context of specific systems and applications are organized in terms of the theory of Lie groups and algebraic geometry. Attention is given to linear systems which have a structure group, linear mechanical systems, and feedback invariants. The investigation shows that Lie group techniques are powerful and useful tools for analysis of the feedback structure of linear systems.
A difficult aspect of system optimization is the choice of a single cost function relating system parameters to the quality of the design; there are generally conflicting criteria by which the system can be evaluated. This paper discusses the problem of optimization with respect to multiple criteria, i.e., with a vector-valued cost function, without prespecifying constraints or the weighting of the criteria. The paper discusses theoretical results concerning the set of non-inferior solutions so generated and a computational algorithm for obtaining a characteristic set of non-inferior solutions.
A Miniature Embedded Reconfigurable Computer and Logic (MERCAL) module has been developed and verified. MERCAL was designed to be a general-purpose, universal module that that can provide significant hardware and software resources to meet the requirements of many of today's complex embedded applications. This is accomplished in the MERCAL module by combining a sub credit card size PC in a DIMM form factor with a XILINX Spartan I1 FPGA. The PC has the ability to download program files to the FPGA to configure it for different hardware functions and to transfer data to and from the FPGA via the PC's ISA bus during run time. The MERCAL module combines, in a compact package, the computational power of a 133 MHz PC with up to 150,000 gate equivalents of digital logic that can be reconfigured by software. The general architecture and functionality of the MERCAL hardware and system software are described.
Modelling of protein-protein interactions in signal transduction is receiving increased attention in computational biology. This paper describes recent research in the application of Maude, a symbolic language founded on rewriting logic, to the modelling of functional domains within signalling proteins. Protein functional domains (PFDs) are a critical focus of modern signal transduction research. In general, Maude models can simulate biological signalling networks and produce specific testable hypotheses at various levels of abstraction. Developing symbolic models of signalling proteins containing functional domains is important because of the potential to generate analyses of complex signalling networks based on structure-function relationships.
This paper presents experimental work conducted in the Icing Research Tunnel at NASA Glenn Research Center to characterize the velocity of large drops in the test section. Some icing spray clouds with large drops were generated with Mod1 nozzles at low nozzle air pressure of 2 to 4 psig for various tunnel air speeds. Drop diameters and drop velocities were measured via high-resolution imaging with a Particle Imaging Particle Tracking Velocimetry probe developed by Artium Technologies. The probe was mounted at four different locations aligned with the centerline of the test section from near the end of the contraction to the constant height test section part of the tunnel. CFD analyses were performed. It showed that the probe head geometry affects the local air flow in the measurement area of the probe between the prongs and in front of the probe. Initial analysis of the air velocity data during the test also indicated that the probe mounting stand has blockage effect on the local tunnel air velocity measurement by a pitot-static probe affixed on the mounting plate next to the stand. Those findings were later verified in the Icing Research Tunnel using a new pitot-static probe design with a linear motion system to measure the local tunnel air velocity with and without the probe. As a result, additional drop trajectory simulations were performed with the airflow moving towards the probe head with a Langmuir-D 7-bin distribution cloud containing large drops. The simulation results helped identify a critical drop-size threshold of 300 μm above which the velocities of larger drops are negligibly affected by the adverse pressure gradient generated by the probe head due to their large drop inertia. From the dimensional analysis of the drop velocity measurement data obtained, it showed that at the tunnel test section reference location a generalized empirical correlation was developed for the non-dimensional drop velocity as a function of the non-dimensional corrected drop diameter independent of the actual spraybar pressure settings and the tunnel air speeds. The generalized curve-fit correlation showed that the drop velocity was universally asymptotic to about 86 percent of the corresponding tunnel air speed at the test section reference location for the largest drop diameter captured by the probe. Further evaluation of this correlation is recommended to assess its applicability for Supercooled Large Drop icing scaling applications in the Icing Research Tunnel.
This presentation presents experimental work conducted in the Icing Research Tunnel at NASA Glenn Research Center to characterize the velocity of large drops in the tunnel test section. Some icing spray clouds with large-sized drops were generated with Mod1 nozzles at low nozzle air pressure of 2 to 4 psig for various tunnel air speeds. Drop diameters and drop velocities were measured via high-resolution imaging with a Particle Imaging Particle Tracking Velocimetry probe developed by Artium Technologies. The probe was mounted at four different locations aligned with the centerline of the test section from near the end of the contraction to the constant height test section part of the tunnel. CFD analyses were performed. It showed that the probe head geometry affects the local air flow between the prongs and in front of the probe. Initial analysis of the air velocity data during the test also indicated that the probe mounting stand has blockage effect on the local tunnel air velocity measurement by a Pitot static probe affixed on the mounting plate. Those findings were later verified in the Icing Research Tunnel using a new Pitot probe design with a linear motion system to measure the local tunnel air velocity with and without the probe. As a result, additional drop trajectory simulations as airflow moving towards the probe head were run for a Langmuir-D 7-bin drop size distribution of a spray cloud with a nominally large value of medium volumetric diameter. The simulation results helped identify a critical drop-size threshold of 300 µm above which the velocities of larger drops are not affected by the adverse pressure gradient generated by the probe head due to their large drop inertia. From the dimensional analysis of the drop velocity measurement data obtained, it showed that at the tunnel test section reference location a generalized empirical correlation was developed for the non-dimensional drop velocity as a function of the non-dimensional corrected drop diameter independent of the actual spraybar pressure settings and the tunnel air speeds. The generalized curve-fit correlation showed that the drop velocity was universally asymptotic to about 86 percent of the corresponding tunnel air speed at the test section reference location for the largest drop diameter captured by the probe. Further evaluation of this correlation is recommended to assess its applicability for Supercooled Large Drop icing scaling applications in the Icing Research Tunnel.
A number of reasoning problems involving the manipulation of temporal information can naturally be viewed as implicitly inducing an ordering of potential local decisions involving time (specifically, associated with durations or orderings of events) on the basis of preferences. For example. a pair of events might be constrained to occur in a certain order, and, in addition. it might be preferable that the delay between them be as large, or as small, as possible. This paper explores problems in which a set of temporal constraints is specified, where each constraint is associated with preference criteria for making local decisions about the events involved in the constraint, and a reasoner must infer a complete solution to the problem such that, to the extent possible, these local preferences are met in the best way. A constraint framework for reasoning about time is generalized to allow for preferences over event distances and durations, and we study the complexity of solving problems in the resulting formalism. It is shown that while in general such problems are NP-hard, some restrictions on the shape of the preference functions, and on the structure of the preference set, can be enforced to achieve tractability. In these cases, a simple generalization of a single-source shortest path algorithm can be used to compute a globally preferred solution in polynomial time.
The Skylab Program consists of three low-earth-orbit missions of the Orbital Assembly (OA) (figure 1.0-1), extending over.an a-month period. The OA consists of the CSM docked to the Saturn Workshop.(SWS). This handbook describes the systems for three of the four major components of the SWS (OWS, AM, and MDA), and also discusses significant interfaces with the Instrument Unit (IU), ATM, and CSM. The other major component of the SWS, the ATM, is treated separately in its own handbook. The OWS, AM, MDA, ATM Deployment Assembly (ATM-DA), Fixed Airlock Shroud (FAS), Payload Shroud (PS), and IU are addressed throughout this document as individual modules from a structural standpoint only. Although normally considered a part of the launch vehicle, the IU is treated in this document as part of the SWS because of its function in preparing the SWS for orbital operation. Section 1.0 describes vehicle and mission configurations of the Skylab program and provides general descriptions of the various systems. Section 2.0 provides detailed systems data covering system interfaces, functional description, subsystems and major components description, component operation, failure modes, performance and design data, operational limitations and restrictions, and instrumentation, and briefly outlines the experiments. Section 3.0 contains illustrations of all panels and identifies the controls and displays, panels, reference designators, nomenclature, functions, circuit breakers, and power sources. The Table of Contents lists in order of appearance all sections, subsections, major paragraphs, illustrations, and tables and provides their respective page locations. Appendix A defines the abbreviations and acronyms employed throughout this handbook, and Appendix B explains the symbols used. Appendix C is a locator index that references component controls contained in Section 3.0. Appendix D is an alphabetical index of paragraph headings, illustrations, and tables, according to the key word, with applicable page numbers. Additional items of significance to the user have been included in the index. The technical level to which this document is written assumes the reader to have general knowledge of engineering terms and principles.
The lattice sums for the bcc lattice are recalculated using the method of Flax and Raich to obtain more general expressions, valid for all temperatures, in terms of a Langevin function and its derivatives. Formulas are presented which enable easy numerical evaluation. A comparison with well-known low-temperature expansions and with the results of direct numerical integration demonstrates the validity at low temperatures of the more general expressions calculated here.
Previous work has introduced the Planning Coordinator (PCOORD), a coordinator functioning within the hierarchy of the Intelligent Machine Mode. Within the structure of the Planning Coordinator resides the Primitive Structure Database (PSDB) functioning to provide the primitive structures utilized by the Planning Coordinator in the establishing of error recovery or on-line path plans. This report further explores the Primitive Structure Database and establishes the potential of utilizing semantic networks as a means of efficiently storing and retrieving the Generalized Stochastic Colored Petri Nets from which the error recovery plans are derived.
The most studied skeletal muscles which depend on gravity, "antigravity" muscles, are located in the posterior portion of the legs. Antigravity muscles are characterized generally by a different fiber type composition than those which are considered nonpostural. The gravity-dependent function of the antigravity muscles makes them particularly sensitive to weightlessness (unweighting) resulting in a substantial loss of muscle protein, with a relatively greater loss of myofibrillar (structural) proteins. Accordingly alpha-actin mRNA decreases in muscle of rats exposed to microgravity. In the legs, the soleus seems particularly responsive to the lack of weight-bearing associated with space flight. The loss of muscle protein leads to a decreased cross-sectional area of muscle fibers, particularly of the slow-twitch, oxidative (SO) ones compared to fast-twitch glycolytic (FG) or oxidative-glycolytic (FOG) fibers. In some muscles, a shift in fiber composition from SO to FOG has been reported in the adaptation to spaceflight. Changes in muscle composition with spaceflight have been associated with decreased maximal isometric tension (Po) and increased maximal shortening velocity. In terms of fuel metabolism, results varied depending on the pathway considered. Glucose uptake, in the presence of insulin, and activities of glycolytic enzymes are increased by space flight. In contrast, oxidation of fatty acids may be diminished. Oxidation of pyruvate, activity of the citric acid cycle, and ketone metabolism in muscle seem to be unaffected by microgravity.
Data in the literature on heat transfer in the case of nucleate boiling of various liquids in the wicks of heat pipes are reviewed. It is shown that none of the known analytical relationships can be used to generalize, with sufficient accuracy, the experimental data found in the literature. It is further shown that the exponent of the specific heat flux in the heat transfer law changes as a function of the liquid and wick properties. A relationship is obtained which generalizes experimental data for heat transfer agents of moderate temperatures (water, acetone, ethanol, and R-11 and R-113 coolants) and ammonia.
The problem of optimal feedback control of uncertain discrete-time dynamic systems is considered where the uncertain quantities do not have a stochastic description but instead are known to belong to given sets. The problem is converted to a sequential minimax problem and dynamic programming is suggested as a general method for its solution. The notion of a sufficiently informative function, which parallels the notion of a sufficient statistic of stochastic optimal control, is introduced, and conditions under which the optimal controller decomposes into an estimator and an actuator are identified.
Atkins' (1959) basic theory of third sound in thick films of superfluid He-4 is extended here to include a heat source for exciting third sound. A one-dimensional model obeying periodic boundary conditions is developed which can represent a variety of experimentally important configurations. General solutions for the model equations are found which give a complete description of third-sound waves in terms of displacement of the film surface, superfluid velocity, and temperature change as functions of space and time. Algebraic expressions for quantities that occur in general formulas are found for special excitation signals. The structure of third sound is calculated for the first time and the results are found to be inconsistent with previous findings. A direct method for accurately measuring the vaporization coefficient is also presented.
Conventionally programmed digital computers can process numbers with great speed and precision, but do not easily recognize patterns or imprecise or contradictory data. Instead of being programmed in the conventional sense, artificial neural networks are capable of self-learning through exposure to repeated examples. However, the training of an ANN can be a time consuming and unpredictable process. A general method is being developed to mate the adaptability of the ANN with the speed and precision of the digital computer. This method was successful in building feedforward networks that can approximate functions and their partial derivatives from examples in a single iteration. The general method also allows the formation of feedforward networks that can approximate the solution to nonlinear ordinary and partial differential equations to desired accuracy without the need of examples. It is believed that continued research will produce artificial neural networks that can be used with confidence in practical scientific computing and engineering applications.
A general description of cyclotron harmonic resonant pitch-angle scattering is presented. Quasi-linear diffusion coefficients are prescribed in terms of the wave normal distribution of plasma wave energy. Numerical computations are performed for the specific case of relativistic electrons interacting with a band of low frequency whistler-mode turbulence. A parametric treatment of the wave energy distribution permits normalized diffusion coefficients to be presented graphically solely as a function of the electron pitch-angle. The diffusion coefficients generally decrease with increasing cyclotron harmonic number. Higher harmonic diffusion is insignificant at very small electron pitch-angles, but becomes increasingly important as the pitch-angle increases. One thus expected the rate of pitch-angle scattering to decrease with increasing electron energy, since the resonant value of the latter varies proportionately with harmonic number. This indicates that, in mirror-type magnet field geometrics, such as the earth's radiation belts, the diffusion losses of high energy electrons are likely to be appreciably slower than those at low energy.