Information-Theoretic Methods for Identifying Relationships among Climate Variables

Information-theoretic quantities, such as entropy, are used to quantify the amount of information a given variable provides. Entropies can be used together to compute the mutual information, which quantifies the amount of information two variables share. However, accurately estimating these quantities from data is extremely challenging. We have developed a set of computational techniques that allow one to accurately compute marginal and joint entropies. These algorithms are probabilistic in nature and thus provide information on the uncertainty in our estimates, which enable us to establish statistical significance of our findings. We demonstrate these methods by identifying relations between cloud data from the International Satellite Cloud Climatology Project (ISCCP) and data from other sources, such as equatorial pacific sea surface temperatures (SST).Comment: Presented at the Earth-Sun System Technology Conference (ESTC 2008), Adelphi, MD. http://esto.nasa.gov/conferences/estc2008/ 3 pages, 3 figures. Appears in the Proceedings of the Earth-Sun System Technology Conference (ESTC 2008), Adelphi, M

High/variable mixture ratio oxygen/hydrogen engines

A LOX/LH2 high/variable mixture ratio booster upper stage is described. The engine has high thrust-weight ratio as a booster and high specific impulse as an upper stage engine. Operation at high mixture ratio utilizes the propellants at high bulk density. The engine may use multiple turbopump-preburners for higher thrust ratings. The engine uses the full flow cycle to obtain minimum turbine inlet temperatures for a given chamber pressure and to avoid interpropellant shaft seals and other single point failure modes. A portion of the liquid hydrogen is used to regeneratively cool the thrust chamber assembly. The warmed hydrogen coolant is then used to drive the fuel boost turbopump. All propellants arrive at the gas-gas injector ready to burn. Shear mixing of the parallel flowing high velocity, low density fuel-rich gases with the high density, low velocity oxidizer-rich gases provides complete combustion with a modest chamber volume. Combustion stability is assured by the injection of the heated fuel-rich gases and the comparatively low volume ratio of the propellants before and after combustion. The high area ratio nozzle skirt is fitted with a low area ratio nozzle skirt insert for optimum low altitude performance. The overall engine characteristics make it a candidate for ALS, Shuttle-C, LRB, and SSTO applications

A Recipe for the Estimation of Information Flow in a Dynamical System

Information-theoretic quantities, such as entropy and mutual information (MI), can be used to quantify the amount of information needed to describe a dataset or the information shared between two datasets. In the case of a dynamical system, the behavior of the relevant variables can be tightly coupled, such that information about one variable at a given instance in time may provide information about other variables at later instances in time. This is often viewed as a flow of information, and tracking such a flow can reveal relationships among the system variables. Since the MI is a symmetric quantity; an asymmetric quantity, called Transfer Entropy (TE), has been proposed to estimate the directionality of the coupling. However, accurate estimation of entropy-based measures is notoriously difficult. Every method has its own free tuning parameter(s) and there is no consensus on an optimal way of estimating the TE from a dataset. We propose a new methodology to estimate TE and apply a set of methods together as an accuracy cross-check to provide a reliable mathematical tool for any given data set. We demonstrate both the variability in TE estimation across techniques as well as the benefits of the proposed methodology to reliably estimate the directionality of coupling among variables

A Recipe for the Estimation of Information Flow in a Dynamical System

Information-theoretic quantities, such as entropy and mutual information (MI), can be used to quantify the amount of information needed to describe a dataset or the information shared between two datasets. In the case of a dynamical system, the behavior of the relevant variables can be tightly coupled, such that information about one variable at a given instance in time may provide information about other variables at later instances in time. This is often viewed as a flow of information, and tracking such a flow can reveal relationships among the system variables. Since the MI is a symmetric quantity; an asymmetric quantity, called Transfer Entropy (TE), has been proposed to estimate the directionality of the coupling. However, accurate estimation of entropy-based measures is notoriously difficult. Every method has its own free tuning parameter(s) and there is no consensus on an optimal way of estimating the TE from a dataset. We propose a new methodology to estimate TE and apply a set of methods together as an accuracy cross-check to provide a reliable mathematical tool for any given data set. We demonstrate both the variability in TE estimation across techniques as well as the benefits of the proposed methodology to reliably estimate the directionality of coupling among variables

Revealing Relationships among Relevant Climate Variables with Information Theory

A primary objective of the NASA Earth-Sun Exploration Technology Office is to understand the observed Earth climate variability, thus enabling the determination and prediction of the climate's response to both natural and human-induced forcing. We are currently developing a suite of computational tools that will allow researchers to calculate, from data, a variety of information-theoretic quantities such as mutual information, which can be used to identify relationships among climate variables, and transfer entropy, which indicates the possibility of causal interactions. Our tools estimate these quantities along with their associated error bars, the latter of which is critical for describing the degree of uncertainty in the estimates. This work is based upon optimal binning techniques that we have developed for piecewise-constant, histogram-style models of the underlying density functions. Two useful side benefits have already been discovered. The first allows a researcher to determine whether there exist sufficient data to estimate the underlying probability density. The second permits one to determine an acceptable degree of round-off when compressing data for efficient transfer and storage. We also demonstrate how mutual information and transfer entropy can be applied so as to allow researchers not only to identify relations among climate variables, but also to characterize and quantify their possible causal interactions.Comment: 14 pages, 5 figures, Proceedings of the Earth-Sun System Technology Conference (ESTC 2005), Adelphi, M

Thermally-Choked Combustor Technology

A program is underway to demonstrate the practical feasibility of thermally-choked combustor technology with particular emphasis on rocket propulsion applications. Rather than induce subsonic to supersonic flow transition in a geometric throat, the goal is to create a thermal throat by adding combustion heat in a diverging nozzle. Such a device would have certain advantages over conventional flow accelerators assuming that the pressure loss due to heat addition does not severely curtail propulsive efficiency. As an aid to evaluation, a generalized one-dimensional compressible flow analysis tool was constructed. Simplified calculations indicate that the process is fluid dynamically and thermodynamically feasible. Experimental work is also being carried out in an attempt to develop, assuming an array of practical issues are surmountable, a practical bench-scale demonstrator using high flame speed H2/O2 combustibles

Signatures of arithmetic simplicity in metabolic network architecture

Metabolic networks perform some of the most fundamental functions in living cells, including energy transduction and building block biosynthesis. While these are the best characterized networks in living systems, understanding their evolutionary history and complex wiring constitutes one of the most fascinating open questions in biology, intimately related to the enigma of life's origin itself. Is the evolution of metabolism subject to general principles, beyond the unpredictable accumulation of multiple historical accidents? Here we search for such principles by applying to an artificial chemical universe some of the methodologies developed for the study of genome scale models of cellular metabolism. In particular, we use metabolic flux constraint-based models to exhaustively search for artificial chemistry pathways that can optimally perform an array of elementary metabolic functions. Despite the simplicity of the model employed, we find that the ensuing pathways display a surprisingly rich set of properties, including the existence of autocatalytic cycles and hierarchical modules, the appearance of universally preferable metabolites and reactions, and a logarithmic trend of pathway length as a function of input/output molecule size. Some of these properties can be derived analytically, borrowing methods previously used in cryptography. In addition, by mapping biochemical networks onto a simplified carbon atom reaction backbone, we find that several of the properties predicted by the artificial chemistry model hold for real metabolic networks. These findings suggest that optimality principles and arithmetic simplicity might lie beneath some aspects of biochemical complexity

Geothermal energy market potential in industrial processing

Geothermal energy is currently being used for a number of industrial processes in countries throughout the world. Its application in the United States is mainly limited to space heating even though the temperature of the geothermal fluid is sufficient for process uses, and could be sold at attractive prices while maintaining a high return on investment. The temperature span for industrial use ranges from 40 to 275/sup 0/C, thus encompassing both the abundant low temperature and the less available high temperature resources. Hydrothermal fluids can be used either directly or indirectly dependent upon fluid quality and process needs. The barriers facing hydrothermal industrial process development are (a) the development infrastructure does not exist, (b) energy users are not aware of hydrothermal energy and its advantages, (c) federal incentives are limited, (d) resources are not fully defined