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Dynamic Data (dynamic + data)

Distribution by Scientific Domains
Chemistry40%

Terms modified by Dynamic Data

  • dynamic data reconciliation
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    Selected Abstracts

    Dynamic Sampling and Rendering of Algebraic Point Set Surfaces

    COMPUTER GRAPHICS FORUM, Issue 2 2008
    Gaël Guennebaud
    Abstract Algebraic Point Set Surfaces (APSS) define a smooth surface from a set of points using local moving least-squares (MLS) fitting of algebraic spheres. In this paper we first revisit the spherical fitting problem and provide a new, more generic solution that includes intuitive parameters for curvature control of the fitted spheres. As a second contribution we present a novel real-time rendering system of such surfaces using a dynamic up-sampling strategy combined with a conventional splatting algorithm for high quality rendering. Our approach also includes a new view dependent geometric error tailored to efficient and adaptive up-sampling of the surface. One of the key features of our system is its high degree of flexibility that enables us to achieve high performance even for highly dynamic data or complex models by exploiting temporal coherence at the primitive level. We also address the issue of efficient spatial search data structures with respect to construction, access and GPU friendliness. Finally, we present an efficient parallel GPU implementation of the algorithms and search structures. [source]

    Chemisorption of carbon dioxide on sodium oxide promoted alumina

    AICHE JOURNAL, Issue 11 2007
    K. B. Lee
    Abstract New equilibrium and column dynamic data for chemisorption of carbon dioxide from inert nitrogen at 250, 350, and 450°C were measured on a sample of sodium oxide promoted alumina, which was found to be a reversible chemisorbent for CO2. The equilibrium chemisorption isotherms were Langmuirian in the low pressure region (p <2.0 kPa) with a large gas,solid interaction parameter. The isotherms deviated from the Langmuirian behavior in the higher pressure region. A new analytical model which simultaneously accounted for Langmuirian chemisorption of CO2 on the adsorbent surface and additional reaction between the gaseous and sorbed CO2 molecules was used to describe the measured equilibrium data. The heats of CO2 chemisorption and the additional surface reaction were, respectively, 64.9 and 37.5 kJ/mol. The column breakthrough curves for CO2 sorption from inert N2 on the chemisorbent as well as the desorption of CO2 from the chemisorbent by N2 purge at 350°C could be described by the linear driving force (LDF) model in conjunction with the new sorption isotherm. The same LDF mass transfer coefficients can be used to describe both sorption and desorption processes. The CO2 mass transfer coefficients were (i) independent of feed gas CO2 concentration in the range of the data at a given temperature, and (ii) a weak function of temperature. The ratio of the mass transfer zone length to the column length was very small due to highly favorable CO2 sorption equilibrium. Several sequential cyclic CO2 sorption,desorption column dynamic tests were conducted to demonstrate the apparent stability of the material. © 2007 American Institute of Chemical Engineers AIChE J, 2007 [source]

    GEOLOGICAL MODEL EVALUATION THROUGH WELL TEST SIMULATION: A CASE STUDY FROM THE WYTCH FARM OILFIELD, SOUTHERN ENGLAND

    JOURNAL OF PETROLEUM GEOLOGY, Issue 1 2007
    S.Y. Zheng
    This paper presents an approach to the evaluation of reservoir models using transient pressure data. Braided fluvial sandstones exposed in cliffs in SW England were studied as the surface equivalent of the Triassic Sherwood Sandstone, a reservoir unit at the nearby Wytch Farm oilfield. Three reservoir models were built; each used a different modelling approach ranging in complexity from stochastic pixel-based modelling using commercially available software, to a spreadsheet random number generator. In order to test these models, numerical well test simulations were conducted using sector models extracted from the geological models constructed. The simulation results were then evaluated against the actual well test data in order to find the model which best represented the field geology. Two wells at Wytch Farm field were studied. The results suggested that for one of the sampled wells, the model built using the spreadsheet random number generator gave the best match to the well test data. In the well, the permeability from the test interpretation matched the geometric average permeability. This average is the "correct" upscaled permeability for a random system, and this was consistent with the random nature of the geological model. For the second well investigated, a more complex "channel object" model appeared to fit the dynamic data better. All the models were built with stationary properties. However, the well test data suggested that some parts of the field have different statistical properties and hence show non-stationarity. These differences would have to be built into the model representing the local geology. This study presents a workflow that is not yet considered standard in the oil industry, and the use of dynamic data to evaluate geological models requires further development. The study highlights the fact that the comparison or matching of results from reservoir models and well-test analyses is not always straightforward in that different models may match different wells. The study emphasises the need for integrated analyses of geological and engineering data. The methods and procedures presented are intended to form a feedback loop which can be used to evaluate the representivity of a geological model. [source]

    Dynameomics: Large-scale assessment of native protein flexibility

    PROTEIN SCIENCE, Issue 12 2008
    Noah C. Benson
    Abstract Structure is only the first step in understanding the interactions and functions of proteins. In this paper, we explore the flexibility of proteins across a broad database of over 250 solvated protein molecular dynamics simulations in water for an aggregate simulation time of ,6 ,s. These simulations are from our Dynameomics project, and these proteins represent approximately 75% of all known protein structures. We employ principal component analysis of the atomic coordinates over time to determine the primary axis and magnitude of the flexibility of each atom in a simulation. This technique gives us both a database of flexibility for many protein fold families and a compact visual representation of a particular protein's native-state conformational space, neither of which are available using experimental methods alone. These tools allow us to better understand the nature of protein motion and to describe its relationship to other structural and dynamical characteristics. In addition to reporting general properties of protein flexibility and detailing many dynamic motifs, we characterize the relationship between protein native-state flexibility and early events in thermal unfolding and show that flexibility predicts how a protein will begin to unfold. We provide evidence that fold families have conserved flexibility patterns, and family members who deviate from the conserved patterns have very low sequence identity. Finally, we examine novel aspects of highly inflexible loops that are as important to structural integrity as conventional secondary structure. These loops, which are difficult if not impossible to locate without dynamic data, may constitute new structural motifs. [source]

    Modeling the partial nitrification in sequencing batch reactor for biomass adapted to high ammonia concentrations

    BIOTECHNOLOGY & BIOENGINEERING, Issue 1 2006
    V. Pambrun
    Abstract Partial nitrification has proven to be an economic way for treatment of industrial N-rich effluent, reducing oxygen and external COD requirements during nitrification/denitrification process. One of the key issues of this system is the intermediate nitrite accumulation stability. This work presents a control strategy and a modeling tool for maintaining nitrite build-up. Partial nitrification process has been carried out in a sequencing batch reactor at 30°C, maintaining strong changing ammonia concentration in the reactor (sequencing feed). Stable nitrite accumulation has been obtained with the help of an on-line oxygen uptake rate (OUR)-based control system, with removal rate of 2 kg NH -N,·,m,3/day and 90%,95% of conversion of ammonium into nitrite. A mathematical model, identified through the occurring biological reactions, is proposed to optimize the process (preventing nitrate production). Most of the kinetic parameters have been estimated from specific respirometric tests on biomass and validated on pilot-scale experiments of one-cycle duration. Comparison of dynamic data at different pH confirms that NH3 and NO should be considered as the true substrate of nitritation and nitratation, respectively. The proposed model represents major features: the inhibition of ammonia-oxidizing bacteria by its substrate (NH3) and product (HNO2), the inhibition of nitrite-oxidizing bacteria by free ammonia (NH3), the INFluence of pH. It appears that the model correctly describes the short-term dynamics of nitrogenous compounds in SBR, when both ammonia oxidizers and nitrite oxidizers are present and active in the reactor. The model proposed represents a useful tool for process design and optimization. © 2006 Wiley Periodicals, Inc. [source]