59,268 research outputs found

    A lattice Boltzmann model for natural convection in cavities

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    We study a multiple relaxation time lattice Boltzmann model for natural convection with moment–based boundary conditions. The unknown primary variables of the algorithm at a boundary are found by imposing conditions directly upon hydrodynamic moments, which are then translated into conditions for the discrete velocity distribution functions. The method is formulated so that it is consistent with the second–order implementation of the discrete velocity Boltzmann equations for fluid flow and temperature. Natural convection in square cavities is studied for Rayleigh numbers ranging from 103 to 106. An excellent agreement with benchmark data is observed and the flow fields are shown to converge with second order accuracy

    A U.S. Navy Precise Time and Time Interval (PTTI) program update

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    The review presents a brief history of the program, its management organization, and current and projected requirements, capabilities and program efforts. The overall program growth since September 1975 is presented. The Navy's areas of concern regarding future PTTI development are described

    DC motor proportional control system for orthotic devices

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    Multi-channel proportional control system for operation of dc motors for use with externally-powered orthotic arm braces is described. Components of circuitry and principles of operation are described. Schematic diagram of control circuit is provided

    The role of Computer Aided Process Engineering in physiology and clinical medicine

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    This paper discusses the potential role for Computer Aided Process Engineering (CAPE) in developing engineering analysis and design approaches to biological systems across multiple levels—cell signalling networks, gene, protein and metabolic networks, cellular systems, through to physiological systems. The 21st Century challenge in the Life Sciences is to bring together widely dispersed models and knowledge in order to enable a system-wide understanding of these complex systems. This systems level understanding should have broad clinical benefits. Computer Aided Process Engineering can bring systems approaches to (i) improving understanding of these complex chemical and physical (particularly molecular transport in complex flow regimes) interactions at multiple scales in living systems, (ii) analysis of these models to help to identify critical missing information and to explore the consequences on major output variables resulting from disturbances to the system, and (iii) ‘design’ potential interventions in in vivo systems which can have significant beneficial, or potentially harmful, effects which need to be understood. This paper develops these three themes drawing on recent projects at UCL. The first project has modeled the effects of blood flow on endothelial cells lining arteries, taking into account cell shape change resulting in changes in the cell skeleton which cause consequent chemical changes. A second is a project which is building an in silico model of the human liver, tieing together models from the molecular level to the liver. The composite model models glucose regulation in the liver and associated organs. Both projects involve molecular transport, chemical reactions, and complex multiscale systems, tackled by approaches from CAPE. Chemical Engineers solve multiple scale problems in manufacturing processes – from molecular scale through unit operations scale to plant-wide and enterprise wide systems – so have an appropriate skill set for tackling problems in physiology and clinical medicine, in collaboration with life and clinical scientists

    Quasar broad absorption line variability measurements using reconstructions of un-absorbed spectra

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    We present a two-epoch Sloan Digital Sky Survey and Gemini/GMOS+William Herschel Telescope/ISIS variability study of 50 broad absorption line quasars of redshift range 1.9 < z < 4.2, containing 38 Si IV and 59 C IV BALs and spanning rest-frame time intervals of approximately 10 months to 3.7 years. We find that 35/50 quasars exhibit one or more variable BALs, with 58% of Si IV and 46% of C IV BALs showing variability across the entire sample. On average, Si IV BALs show larger fractional change in BAL pseudo equivalent width than C IV BALs, as referenced to an unabsorbed continuum+emission-line spectrum constructed using non-negative matrix factorisation. No correlation is found between BAL variability and quasar luminosity, suggesting that ionizing continuum changes do not play a significant role in BAL variability (assuming the gas is in photoionization equilibrium with the ionizing continuum). A subset of 14 quasars have one variable BAL from each of Si IV and C IV with significant overlap in velocity space and for which variations are in the same sense (strengthening or weakening) and which appear to be correlated (98% confidence). We find examples of both appearing and disappearing BALs in weaker/shallower lines with disappearance rates of 2.3% for C IV and 5.3% for Si IV, suggesting average lifetimes of 142 and 43 years respectively. We identify 5 objects in which the BAL is coincident with the broad emission-line, but appears to cover only the continuum source. Assuming a clumpy inhomogeneous absorber model and a typical size for the continuum source, we infer a maximum cloud radius of 10^13 to 10^14 cm, assuming Eddington limited accretion.Comment: Accepted for publication in MNRAS. 22 pages, 12 figures, 7 table

    Driver steering dynamics measured in car simulator under a range of visibility and roadmaking conditions

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    A simulation experiment was conducted to determine the effect of reduced visibility on driver lateral (steering) control. The simulator included a real car cab and a single lane road image projected on a screen six feet in front of the driver. Simulated equations of motion controlled apparent car lane position in response to driver steering actions, wind gusts, and road curvature. Six drivers experienced a range of visibility conditions at various speeds with assorted roadmaking configurations (mark and gap lengths). Driver describing functions were measured and detailed parametric model fits were determined. A pursuit model employing a road curvature feedforward was very effective in explaining driver behavior in following randomly curving roads. Sampled-data concepts were also effective in explaining the combined effects of reduced visibility and intermittent road markings on the driver's dynamic time delay. The results indicate the relative importance of various perceptual variables as the visual input to the driver's steering control process is changed

    Unit operations for gas-liquid mass transfer in reduced gravity environments

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    Basic scaling rules are derived for converting Earth-based designs of mass transfer equipment into designs for a reduced gravity environment. Three types of gas-liquid mass transfer operations are considered: bubble columns, spray towers, and packed columns. Application of the scaling rules reveals that the height of a bubble column in lunar- and Mars-based operations would be lower than terrestrial designs by factors of 0.64 and 0.79 respectively. The reduced gravity columns would have greater cross-sectional areas, however, by factors of 2.4 and 1.6 for lunar and Martian settings. Similar results were obtained for spray towers. In contract, packed column height was found to be nearly independent of gravity

    Probabilistic Kernel Support Vector Machines

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    We propose a probabilistic enhancement of standard kernel Support Vector Machines for binary classification, in order to address the case when, along with given data sets, a description of uncertainty (e.g., error bounds) may be available on each datum. In the present paper, we specifically consider Gaussian distributions to model uncertainty. Thereby, our data consist of pairs (xi,Σi)(x_i,\Sigma_i), i∈{1,…,N}i\in\{1,\ldots,N\}, along with an indicator yi∈{−1,1}y_i\in\{-1,1\} to declare membership in one of two categories for each pair. These pairs may be viewed to represent the mean and covariance, respectively, of random vectors ξi\xi_i taking values in a suitable linear space (typically Rn\mathbb R^n). Thus, our setting may also be viewed as a modification of Support Vector Machines to classify distributions, albeit, at present, only Gaussian ones. We outline the formalism that allows computing suitable classifiers via a natural modification of the standard "kernel trick." The main contribution of this work is to point out a suitable kernel function for applying Support Vector techniques to the setting of uncertain data for which a detailed uncertainty description is also available (herein, "Gaussian points").Comment: 6 pages, 6 figure

    A theory of human error

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    Human errors tend to be treated in terms of clinical and anecdotal descriptions, from which remedial measures are difficult to derive. Correction of the sources of human error requires an attempt to reconstruct underlying and contributing causes of error from the circumstantial causes cited in official investigative reports. A comprehensive analytical theory of the cause-effect relationships governing propagation of human error is indispensable to a reconstruction of the underlying and contributing causes. A validated analytical theory of the input-output behavior of human operators involving manual control, communication, supervisory, and monitoring tasks which are relevant to aviation, maritime, automotive, and process control operations is highlighted. This theory of behavior, both appropriate and inappropriate, provides an insightful basis for investigating, classifying, and quantifying the needed cause-effect relationships governing propagation of human error
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