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The goals of this research are two-fold: to study effective means of growing ZnSe crystals of good optical quality and to determine the advantages of growing such crystals in microgravity. As of this date the optimal conditions for crystal growth have not been determined. However, successful growth runs were made in two furnances and the results are given.
It is argued that the bioreactor being developed at NASA will allow researchers to determine the optimal conditions (e.g., pH, O sub 2, CO sub 2, nutrients) for growth of hybridoma cells, and to determine whether cell growth and antibody production are enhanced in the microgravity of space.
The development presented introduces a general form of mixed formulation for the optimal shape design problem. The associated optimality conditions are easily obtained without resorting to highly elaborate mathematical developments. Also, the physical significance of the adjoint problem is clearly defined with this formulation.
Optimization problems are typically solved by starting with an initial estimate and proceeding iteratively to improve it until the optimum is found. The design points along the path from the initial estimate to the optimum are usually of no value. The present work proposes a strategy for tracing a path of optimum solutions parameterized by the amount of available resources. The paper specifically treats the optimum design of a structure to maximize its buckling load. Equations for the optimum path are obtained using Lagrange multipliers, and solved by a homotopy method. The solution path has several transitions from unimodal to bimodal solutions. The Lagrange multipliers and second-order optimality conditions are used to detect branching points and to switch to the optimum solution path. The procedure is applied to the design of a foundation which supports a column for maximum buckling load. Using the total available foundation stiffness as a homotopy parameter, a set of optimum foundation designs is obtained.
Estimation of the sensitivity of problem functions with respect to problem variables forms the basis for many of our modern day algorithms for engineering optimization. The most common application of problem sensitivities has been in the calculation of objective function and constraint partial derivatives for determining search directions and optimality conditions. A second form of sensitivity analysis, parameter sensitivity, has also become an important topic in recent years. By parameter sensitivity, researchers refer to the estimation of changes in the modeling functions and current design point due to small changes in the fixed parameters of the formulation. Methods for calculating these derivatives have been proposed by several authors (Armacost and Fiacco 1974, Sobieski et al 1981, Schmit and Chang 1984, and Vanderplaats and Yoshida 1985). Two drawbacks to estimating parameter sensitivities by current methods have been: (1) the need for second order information about the Lagrangian at the current point, and (2) the estimates assume no change in the active set of constraints. The first of these two problems is addressed here and a new algorithm is proposed that does not require explicit calculation of second order information.
There are three major habitats involving ice and snow, and the microorganisms studied from these habitats are most eukaryotic. Sea ice is inhabited by algae called diatoms, glacial ice has sparse populations of green algai cal desmids, and the temporary and permanent snows in mountainous regions and high latitudes are inhabited mostly by green algal flagellates. The life cycle of green algal flagellates is summarized by discussing the effects of light, temperature, nutrients, and snow melts. Specific examples of optimal conditions and environmental effects for various snow algae are given. It is not likely that the eukaryotic snow algae presented are candidated for life on the planet Mars. Evolutionally, eukaryotic cells as know on Earth may not have had the opportunity to develop on Mars (if life evolved at all on Mars) since eukaryotes did not appear on Earth until almost two billion years after the first prokaryotic organisms. However, the snow/ice ecosystems on Earth present themselves as extreme habitats were there is evidence of prokaryotic life (eubacteria and cyanbacteria) of which literally nothing is known. Any future surveillances of extant and/or extinct life on Mars should include probes (if not landing sites) to investigate sites of concentrations of ice water. The possibility of signs of life in Martian polar regions should not be overlooked.
Perfusion bioreactor module, self-contained, closed-loop cell-culture system that operates in microgravity or on Earth. Equipment supports growth or long-term maintenance of cultures of human or other fragile cells for experiments in basic cell biology or process technology. Designed to support proliferation (initially at exponential rates of growth) of cells in complex growth medium and to maintain confluent cells in defined medium under conditions optimized to permit or encourage selected functions of cells, including secretion of products of cells into medium.
A theory of microemulsions developed previously is extended to include the effect of a gravitational field. It predicts variation with position of drop size, drop volume fraction, and area per molecule in the surfactant films within a microemulsion phase. Variation in volume fraction is greatest and occurs in such a way that oil content increases with increasing elevation, as has been found experimentally. Large composition variations are predicted within a middle phase microemulsion near optimal conditions because inversion from the water-continuous to the oil-continuous arrangement occurs with increasing elevation. Generally speaking, gravity reduces solubilization within microemulsions and promotes separation of excess phases.
The structured singular value, U, is an important linear algebra tool to study a class of matrix perturbation problems. It is useful for analyzing the robustness of stability and performance of uncertain, (nominally) linear systems. Computation of (M) is difficult, and usually, upper and lower bounds are all that can be reliably computed. Upper bounds give conservative estimates of the sizes of allowable perturbations. The maximum singular value of a matrix M is an upper bound for (M). As an upper bound, it can be improved by finding a transformations to the data (i.e. M) which do not change the structured singular value, but do reduce the maximum singular value. Typically, upper bound algorithms involve searches over sets of transformations to yield the tightest bound. Lower bound algorithms are intelligent searches for minimum-norm solutions to multivariable polynomial equations, and are based on various optimality conditions that hold at the global (and, unfortunately, some local) minima. The current methods to compute both of these types of bounds are reviewed. Theoretical justification and extensive numerical experience with the various algorithms are covered.
The design of the Initial Blood Storage Experiment (IBSE) was based upon a carefully controlled comparison between identical sets of human blood cell suspensions - red cells, white cell, and platelets - one set of which was transported aboard the Columbia on a 6 day 11 hour mission, and the other held on the ground. Both sets were carried inside stainless steel dewars within specially fabricated flight hardware. Individual bags of cell suspensions were randomly assigned with respect to ground vs orbit status, dewar chamber, and specific location within the dewar. To foster optimal preservation, each cell type was held under specific optimal conditions of pH, ionic strength, solute concentration, gas tension, and temperature. An added variable in this initial experiment was provided by the use of three different polymer/plasticizer formulations for the sealed bags which held the blood cells. At termination of the experiment, aliquots of the suspensions, identified only by code, were distributed to be assayed. Assays were selected to constitute a broad survey of cellular properties and thereby maximize the chances of detection of gravitational effects. A total of 74 different outcome measurements were reported for statistical analysis. When the measurements were completed, the results were entered into the IBSE data base, at which time the data were matched with the original blood bag numbers to determine their status with respect to polymer/plasticizer type, orbit status (orbit or ground), and storage position within the experimental hardware. The data were studied by analysis of variance. Initially, type of bag and orbital status were main factors; later more detailed analyses were made on specific issues such as position in the hardware and specific plastic. If the analysis of variance indicated a statistical significance at the 5 percent level the corresponding p-value was reported.
Variable angle spectroscopic ellipsometry (VASE) was applied to cubic SiC. This technique gives absolute values of the refractive index (n) and the extinction coefficient (k) of a substrate and/or a thin film of unknown material. The samples were grown by chemical vapor deposition (CVD) on p-type silicon. The substrate was aligned either on the (001) axis or 1 degree of (001). Several growth temperatures and growth durations were used. The samples were divided into two groups: (1) thick films of order 10 microns grown near optimal conditions of temperature, flow, and gas ratio; and (2) thin films of order 100 A grown at various temperatures. The ellipsometric results for samples in group 1 were analyzed using a two-phase model (substrate and ambient). Results show that for wavelengths in the visible, the refractive index of these CVD samples is equal to that reported for single crystal cubic SiC, within the experimental error, which is on the order of 1 percent. However, the extinction coefficient has a relatively large value, even above the band gap. The absorption is sample dependent and has a broad peak in the visible. The results for samples in group 2 were analyzed using a three-phase model (substrate, film, and ambient). The dielectric functions of the film, deducted from the measured n and k, were further analyzed using the effective medium approximation. The results show that the films contain 30 to 40 vol. percent amorphous silicon, i.e., silicon with only short-range order.
Computerized simulation of meshing and bearing contact for spiral bevel gears and hypoid gears is a significant achievement that could substantially improve the technology and the quality of the gears. An approach to the synthesis of face-milled spiral bevel gears and their tooth contact analysis is presented. The proposed approach is based on the following ideas: application of the principle of local synthesis that provides optimal conditions of meshing and contact at the mean contact point, M, and in the neighborhood of M; and application of relations between principle directions and curvatures for surfaces being in line contact or in point contact. The developed local synthesis of gears provides the following: (1) the required gear ratio at M; (2) a localized bearing contact with the desired direction of the tangent to the contact path on gear tooth surface and the desired length of the major axis of contact ellipse at M; (3) a predesigned parabolic function of a controlled level for transmission errors which enables absorption of linear functions of transmission errors caused by misalignment and reduces the level of vibrations. The proposed approach does not require either the tilt of the head-cutter for the process of generation or modified roll for the pinion generation. Improved conditions of meshing and contact of the gears can be achieved without the above mentioned parameters. A computer program for determination of basic machine-tool settings and tooth contact analysis for the designed gears is presented. The approach is illustrated with a numerical example.
The chemical and physical properties of Martian surface materials are reviewed from the perspective of using these resources to support human settlement. The resource potential of Martian sediments and soils can only be inferred from limited analyses performed by the Viking Landers (VL), from information derived from remote sensing, and from analysis of the SNC meteorites thought to be from Mars. Bulk elemental compositions by the VL inorganic chemical (x ray fluorescence) analysis experiments have been interpreted as evidence for clay minerals (possibly smectites) or mineraloids (palagonite) admixed with sulfate and chloride salts. The materials contained minerals bearing Fe, Ti, Al, Mg and Si. Martian surface materials may be used in many ways. Martian soil, with appropriate preconditioning, can probably be used as a plant growth medium, supplying mechanical support, nutrient elements, and water at optimal conditions to the plants. Loose Martian soils could be used to cover structures and provide radiation shielding for surface habitats. Martian soil could be wetted and formed into abode bricks used for construction. Duricrete bricks, with strength comparable to concrete, can probably be formed using compressed muds made from martian soil.
This paper advances a detailed theory of sunspot visibility based on the physiology of the human eye. It is found that the average person under optimal conditions can detect a sunspot whose penumbral diameter is as small as 27 arcsec. The technique for filtering the sunlight, the observer's diet, age, and amount of close-up reading will not change sunspot visibility in practical cases, so the modern observations and theory are fully comparable with the ancient Chinese observations.
The hypothesis that vestiges of the ancestral RNA-dependent RNA polymerase involved in the replication of RNA genomes of Archean cells are present in the eubacterial RNA-polymerase beta-prime subunit and its homologues is discussed. It is shown that, in the DNA-dependent RNA polymerases from three cellular lineages, a very conserved sequence of eight amino acids, also found in a small RNA-binding site previously described for the E. coli polynucleotide phosphorylase and the S1 ribosomal protein, is present. The optimal conditions for the replicase activity of the avian-myeloblastosis-virus reverse transcriptase are presented. The evolutionary significance of the in vitro modifications of substrate and template specificities of RNA polymerases and reverse transcriptases is discussed.
The problems of determining a feedback controller or estimator that optimizes an H2 performance criterion involving a collection of plant models is considered. The approach is based upon fixed-structure optimization in which the estimator or controller order is fixed prior to the development of optimality conditions. The question of maximal controller order is also investigated.
The Hybrid Air Revitalization System (HARS) closed ecosystem concept presented encompasses electrochemical CO2 and O2 separators, in conjunction with a mechanical condenser/separator for maintaining CO2, O2, and humidity levels in crew and plant habitats at optimal conditions. HARS requires no expendables, and allows flexible process control on the bases of electrochemical cell current, temperature, and airflow rate variations. HARS capacity can be easily increased through the incorporation of additional chemical cells. Detailed system flowcharts are provided.
The design of neural networks and fuzzy systems can involve complex, nonlinear, and ill-conditioned optimization problems. Often, traditional optimization schemes are inadequate or inapplicable for such tasks. Genetic Algorithms (GA's) are a class of optimization procedures whose mechanics are based on those of natural genetics. Mathematical arguments show how GAs bring substantial computational leverage to search problems, without requiring the mathematical characteristics often necessary for traditional optimization schemes (e.g., modality, continuity, availability of derivative information, etc.). GA's have proven effective in a variety of search tasks that arise in neural networks and fuzzy systems. This presentation begins by introducing the mechanism and theoretical underpinnings of GA's. GA's are then related to a class of rule-based machine learning systems called learning classifier systems (LCS's). An LCS implements a low-level production-system that uses a GA as its primary rule discovery mechanism. This presentation illustrates how, despite its rule-based framework, an LCS can be thought of as a competitive neural network. Neural network simulator code for an LCS is presented. In this context, the GA is doing more than optimizing and objective function. It is searching for an ecology of hidden nodes with limited connectivity. The GA attempts to evolve this ecology such that effective neural network performance results. The GA is particularly well adapted to this task, given its naturally-inspired basis. The LCS/neural network analogy extends itself to other, more traditional neural networks. Conclusions to the presentation discuss the implications of using GA's in ecological search problems that arise in neural and fuzzy systems.