993 resultados para LABORATORY MODELS


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In the laboratory of Dr. Dieter Jaeger at Emory University, we use computer simulations to study how the biophysical properties of neurons—including their three-dimensional structure, passive membrane resistance and capacitance, and active membrane conductances generated by ion channels—affect the way that the neurons transfer synaptic inputs into the action potential streams that represent their output. Because our ultimate goal is to understand how neurons process and relay information in a living animal, we try to make our computer simulations as realistic as possible. As such, the computer models reflect the detailed morphology and all of the ion channels known to exist in the particular neuron types being simulated, and the model neurons are tested with synaptic input patterns that are intended to approximate the inputs that real neurons receive in vivo. The purpose of this workshop tutorial was to explain what we mean by ‘in vivo-like’ synaptic input patterns, and how we introduce these input patterns into our computer simulations using the freely available GENESIS software package (http://www.genesis-sim.org/GENESIS). The presentation was divided into four sections: first, an explanation of what we are talking about when we refer to in vivo-like synaptic input patterns

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Field soils show rather different spreading behavior at different water saturations, frequently caused by layering of the soil material. We performed tracer experiments in a laboratory sand tank. Such experiments complement and help comprehension of field investigations. We estimated, by image analysis, the first two moments of small plumes traveling through a two-dimensional, heterogeneous medium with strongly anisotropic correlation structure. Three steady state regimes were analyzed. Two main conclusions were drawn. First, low saturation led to very large heterogeneity and to strong preferential flow. Thus the description of the flow paths and the prediction of the solute arrival times require, in this case, more accurate knowledge about the topological structure. Second, saturation-dependent macroscopic anisotropy is an essential element of transport in unsaturated media. For this reason, small structural soil features should be properly upscaled to give appropriate effective soil parameters to be input in transport models.

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The diffusion of radionuclides is an important safety aspect for nuclear waste disposal in argillaceous host rocks. A long-term diffusion experiment, termed DI-A, is being carried out at the Mont Terri Rock Laboratory in the Opalinus Clay formation. The aim of this experiment is the understanding of the migration and sorption behaviour of cationic and anionic species in consolidated clays. This study reports on the experimental layout and the first results obtained from the DI-A experiment, which include the investigation of HTO, Na-22(+), Cs+, and I- migration during a period of 1 year by analysing these tracers in the water circulating in the borehole. In addition, results obtained from through-diffusion experiments on small-sized samples with HTO, I-, and Cl-36(-) are presented. The decrease of tracer concentrations in the borehole is fastest for Cs+, followed by Na-22(+), HTO, and finally I-. The chemical composition of the artificial pore water in the borehole shows very little variation with time, thus indicating almost no chemical disturbance around the borehole. Through-diffusion experiments in the laboratory that were performed parallel to the bedding plane with two different methods yielded effective diffusion coefficients for HTO of 4-5 X 10(-11) m(2) s(-1) and significantly lower ones for anions Cl- and I- (0.7-1.6 X 10(-11) m(2) s(-1)). The results indicate the importance of anion exclusion effects arising from the negatively charged clay surfaces. Furthermore, they demonstrate the anisotropic diffusion properties of the clay formation with significantly increased diffusion rates parallel to bedding relative to the perpendicular direction. The tracer data of the in situ experiment were successfully described with 2D diffusion models using diffusion and sorption parameters obtained from the above mentioned and other laboratory studies. The modelling results indicate that HTO and I- diffused with no retardation. The retardation of Na+ and Cs+ could be described by empirical sorption expressions from previously derived batch sorption (Cs+) or diffusion (Na+) experiments. Overall, the obtained results demonstrate the feasibility of the technical concept to study the diffusion of nonsorbing and sorbing tracers in consolidated clays. (C) 2004 Elsevier B.V. All rights reserved.

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This paper reports a comparison of three modeling strategies for the analysis of hospital mortality in a sample of general medicine inpatients in a Department of Veterans Affairs medical center. Logistic regression, a Markov chain model, and longitudinal logistic regression were evaluated on predictive performance as measured by the c-index and on accuracy of expected numbers of deaths compared to observed. The logistic regression used patient information collected at admission; the Markov model was comprised of two absorbing states for discharge and death and three transient states reflecting increasing severity of illness as measured by laboratory data collected during the hospital stay; longitudinal regression employed Generalized Estimating Equations (GEE) to model covariance structure for the repeated binary outcome. Results showed that the logistic regression predicted hospital mortality as well as the alternative methods but was limited in scope of application. The Markov chain provides insights into how day to day changes of illness severity lead to discharge or death. The longitudinal logistic regression showed that increasing illness trajectory is associated with hospital mortality. The conclusion is reached that for standard applications in modeling hospital mortality, logistic regression is adequate, but for new challenges facing health services research today, alternative methods are equally predictive, practical, and can provide new insights. ^

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INTRODUCTION This paper focuses exclusively on experimental models with ultra high dilutions (i.e. beyond 10(-23)) that have been submitted to replication scrutiny. It updates previous surveys, considers suggestions made by the research community and compares the state of replication in 1994 with that in 2015. METHODS Following literature research, biochemical, immunological, botanical, cell biological and zoological studies on ultra high dilutions (potencies) were included. Reports were grouped into initial studies, laboratory-internal, multicentre and external replications. Repetition could yield either comparable, or zero, or opposite results. The null-hypothesis was that test and control groups would not be distinguishable (zero effect). RESULTS A total of 126 studies were found. From these, 28 were initial studies. When all 98 replicative studies were considered, 70.4% (i.e. 69) reported a result comparable to that of the initial study, 20.4% (20) zero effect and 9.2% (9) an opposite result. Both for the studies until 1994 and the studies 1995-2015 the null-hypothesis (dominance of zero results) should be rejected. Furthermore, the odds of finding a comparable result are generally higher than of finding an opposite result. Although this is true for all three types of replication studies, the fraction of comparable studies diminishes from laboratory-internal (total 82.9%) to multicentre (total 75%) to external (total 48.3%), while the fraction of opposite results was 4.9%, 10.7% and 13.8%. Furthermore, it became obvious that the probability of an external replication producing comparable results is bigger for models that had already been further scrutinized by the initial researchers. CONCLUSIONS We found 28 experimental models which underwent replication. In total, 24 models were replicated with comparable results, 12 models with zero effect, and 6 models with opposite results. Five models were externally reproduced with comparable results. We encourage further replications of studies in order to learn more about the model systems used.

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We present recent improvements of the modeling of the disruption of strength dominated bodies using the Smooth Particle Hydrodynamics (SPH) technique. The improvements include an updated strength model and a friction model, which are successfully tested by a comparison with laboratory experiments. In the modeling of catastrophic disruptions of asteroids, a comparison between old and new strength models shows no significant deviation in the case of targets which are initially non-porous, fully intact and have a homogeneous structure (such as the targets used in the study by Benz and Asphaug, 1999). However, for many cases (e.g. initially partly or fully damaged targets and rubble-pile structures) we find that it is crucial that friction is taken into account and the material has a pressure dependent shear strength. Our investigations of the catastrophic disruption threshold (27, as a function of target properties and target sizes up to a few 100 km show that a fully damaged target modeled without friction has a Q(D)*:, which is significantly (5-10 times) smaller than in the case where friction is included. When the effect of the energy dissipation due to compaction (pore crushing) is taken into account as well, the targets become even stronger (Q(D)*; is increased by a factor of 2-3). On the other hand, cohesion is found to have an negligible effect at large scales and is only important at scales less than or similar to 1 km. Our results show the relative effects of strength, friction and porosity on the outcome of collisions among small (less than or similar to 1000 km) bodies. These results will be used in a future study to improve existing scaling laws for the outcome of collisions (e.g. Leinhardt and Stewart, 2012). (C) 2014 Elsevier Ltd. All rights reserved.

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Dissolved organic matter (DOM) in the oceans constitutes a major carbon pool involved in global biogeochemical cycles. More than 96% of the marine DOM resists microbial degradation for thousands of years. The composition of this refractory DOM (RDOM) exhibits a molecular signature which is ubiquitously detected in the deep oceans. Surprisingly efficient microbial transformation of labile into RDOM was shown experimentally, implying that microorganisms produce far more RDOM than needed to sustain the global pool. By assessing the microbial formation and transformation of DOM in unprecedented molecular detail for 3 years, we show that most of the newly formed RDOM is molecularly different from deep sea RDOM. Only <0.4% of the net community production was channeled into RDOM molecularly undistinguishable from deep sea DOM. Our study provides novel experimentally derived molecular evidence and data for global models on the production, turnover and accumulation of marine DOM.

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We introduce two probabilistic, data-driven models that predict a ship's speed and the situations where a ship is probable to get stuck in ice based on the joint effect of ice features such as the thickness and concentration of level ice, ice ridges, rafted ice, moreover ice compression is considered. To develop the models to datasets were utilized. First, the data from the Automatic Identification System about the performance of a selected ship was used. Second, a numerical ice model HELMI, developed in the Finnish Meteorological Institute, provided information about the ice field. The relations between the ice conditions and ship movements were established using Bayesian learning algorithms. The case study presented in this paper considers a single and unassisted trip of an ice-strengthened bulk carrier between two Finnish ports in the presence of challenging ice conditions, which varied in time and space. The obtained results show good prediction power of the models. This means, on average 80% for predicting the ship's speed within specified bins, and above 90% for predicting cases where a ship may get stuck in ice. We expect this new approach to facilitate the safe and effective route selection problem for ice-covered waters where the ship performance is reflected in the objective function.

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Independent Components Analysis is a Blind Source Separation method that aims to find the pure source signals mixed together in unknown proportions in the observed signals under study. It does this by searching for factors which are mutually statistically independent. It can thus be classified among the latent-variable based methods. Like other methods based on latent variables, a careful investigation has to be carried out to find out which factors are significant and which are not. Therefore, it is important to dispose of a validation procedure to decide on the optimal number of independent components to include in the final model. This can be made complicated by the fact that two consecutive models may differ in the order and signs of similarly-indexed ICs. As well, the structure of the extracted sources can change as a function of the number of factors calculated. Two methods for determining the optimal number of ICs are proposed in this article and applied to simulated and real datasets to demonstrate their performance.

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Fundamental research and modelling in plasma atomic physics continue to be essential for providing basic understanding of many different topics relevant to high-energy-density plasmas. The Atomic Physics Group at the Institute of Nuclear Fusion has accumulated experience over the years in developing a collection of computational models and tools for determining the atomic energy structure, ionization balance and radiative properties of, mainly, inertial fusion and laser-produced plasmas in a variety of conditions. In this work, we discuss some of the latest advances and results of our research, with emphasis on inertial fusion and laboratory-astrophysical applications.

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Stochastic model updating must be considered for quantifying uncertainties inherently existing in real-world engineering structures. By this means the statistical properties,instead of deterministic values, of structural parameters can be sought indicating the parameter variability. However, the implementation of stochastic model updating is much more complicated than that of deterministic methods particularly in the aspects of theoretical complexity and low computational efficiency. This study attempts to propose a simple and cost-efficient method by decomposing a stochastic updating process into a series of deterministic ones with the aid of response surface models and Monte Carlo simulation. The response surface models are used as surrogates for original FE models in the interest of programming simplification, fast response computation and easy inverse optimization. Monte Carlo simulation is adopted for generating samples from the assumed or measured probability distributions of responses. Each sample corresponds to an individual deterministic inverse process predicting the deterministic values of parameters. Then the parameter means and variances can be statistically estimated based on all the parameter predictions by running all the samples. Meanwhile, the analysis of variance approach is employed for the evaluation of parameter variability significance. The proposed method has been demonstrated firstly on a numerical beam and then a set of nominally identical steel plates tested in the laboratory. It is found that compared with the existing stochastic model updating methods, the proposed method presents similar accuracy while its primary merits consist in its simple implementation and cost efficiency in response computation and inverse optimization.

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Some neural bruise prediction models have been implemented in the laboratory, for the most traded fruit species and varieties, allowing the prediction of the acceptability or rejectability for damages, with respect to the EC Standards. Different models have been built for both quasi-static (compression) and dynamic (impact) loads covering the whole commercial ripening period of fruits. A simulation process has been developed gathering the information on laboratory bruise models and load sensor calibrations for different electronic devices (IS-100 and DEA-1, for impact and compression loads respectively). Some evaluation methodology has been designed gathering the information on the mechanical properties of fruits and the loading records of electronic devices. The evaluation system allows to determine the current stage of fruit handling process and machinery.

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This paper presents an overview of depth averaged modelling of fast catastrophic landslides where coupling of solid skeleton and pore fluid (air and water) is important. The first goal is to show how Biot-Zienkiewicz models can be applied to develop depth integrated, coupled models. The second objective of the paper is to consider a link which can be established between rheological and constitutive models. Perzyna´s viscoplasticity can be considered a general framework within which rheological models such as Bingham and cohesive frictional fluids can be derived. Among the several alternative numerical models, we will focus here on SPH which has not been widely applied by engineers to model landslide propagation. We propose an improvement, based on combining Finite Difference meshes associated to SPH nodes to describe pore pressure evolution inside the landslide mass. We devote a Section to analyze the performance of the models, considering three sets of tests and examples which allows to assess the model performance and limitations: (i) Problems having an analytical solution, (ii) Small scale laboratory tests, and (iii) Real cases for which we have had access to reliable information

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El propósito de esta tesis es estudiar la aproximación a los fenómenos de transporte térmico en edificación acristalada a través de sus réplicas a escala. La tarea central de esta tesis es, por lo tanto, la comparación del comportamiento térmico de modelos a escala con el correspondiente comportamiento térmico del prototipo a escala real. Los datos principales de comparación entre modelo y prototipo serán las temperaturas. En el primer capítulo del Estado del Arte de esta tesis se hará un recorrido histórico por los usos de los modelos a escala desde la antigüedad hasta nuestro días. Dentro de éste, en el Estado de la Técnica, se expondrán los beneficios que tiene su empleo y las dificultades que conllevan. A continuación, en el Estado de la Investigación de los modelos a escala, se analizarán artículos científicos y tesis. Precisamente, nos centraremos en aquellos modelos a escala que son funcionales. Los modelos a escala funcionales son modelos a escala que replican, además, una o algunas de las funciones de sus prototipos. Los modelos a escala pueden estar distorsionados o no. Los modelos a escala distorsionados son aquellos con cambios intencionados en las dimensiones o en las características constructivas para la obtención de una respuesta específica por ejemplo, replicar el comportamiento térmico. Los modelos a escala sin distorsión, o no distorsionados, son aquellos que mantienen, en la medida de lo posible, las proporciones dimensionales y características constructivas de sus prototipos de referencia. Estos modelos a escala funcionales y no distorsionados son especialmente útiles para los arquitectos ya que permiten a la vez ser empleados como elementos funcionales de análisis y como elementos de toma de decisiones en el diseño constructivo. A pesar de su versatilidad, en general, se observará que se han utilizado muy poco estos modelos a escala funcionales sin distorsión para el estudio del comportamiento térmico de la edificación. Posteriormente, se expondrán las teorías para el análisis de los datos térmicos recogidos de los modelos a escala y su aplicabilidad a los correspondientes prototipos a escala real. Se explicarán los experimentos llevados a cabo, tanto en laboratorio como a intemperie. Se han realizado experimentos con modelos sencillos cúbicos a diferentes escalas y sometidos a las mismas condiciones ambientales. De estos modelos sencillos hemos dado el salto a un modelo reducido de una edificación acristalada relativamente sencilla. Los experimentos consisten en ensayos simultáneos a intemperie del prototipo a escala real y su modelo reducido del Taller de Prototipos de la Escuela Técnica Superior de Arquitectura de Madrid (ETSAM). Para el análisis de los datos experimentales hemos aplicado las teorías conocidas, tanto comparaciones directas como el empleo del análisis dimensional. Finalmente, las simulaciones nos permiten comparaciones flexibles con los datos experimentales, por ese motivo, hemos utilizado tanto programas comerciales como un algoritmo de simulación desarrollado ad hoc para esta investigación. Finalmente, exponemos la discusión y las conclusiones de esta investigación. Abstract The purpose of this thesis is to study the approximation to phenomena of heat transfer in glazed buildings through their scale replicas. The central task of this thesis is, therefore, the comparison of the thermal performance of scale models without distortion with the corresponding thermal performance of their full-scale prototypes. Indoor air temperatures of the scale model and the corresponding prototype are the data to be compared. In the first chapter on the State of the Art, it will be shown a broad vision, consisting of a historic review of uses of scale models, from antiquity to our days. In the section State of the Technique, the benefits and difficulties associated with their implementation are presented. Additionally, in the section State of the Research, current scientific papers and theses on scale models are reviewed. Specifically, we focus on functional scale models. Functional scale models are scale models that replicate, additionally, one or some of the functions of their corresponding prototypes. Scale models can be distorted or not. Scale models with distortion are considered scale models with intentional changes, on one hand, in dimensions scaled unevenly and, on the other hand, in constructive characteristics or materials, in order to get a specific performance for instance, a specific thermal performance. Consequently, scale models without distortion, or undistorted scale models scaled evenly, are those replicating, to the extent possible, without distortion, the dimensional proportions and constructive configurations of their prototypes of reference. These undistorted and functional scale models are especially useful for architects because they can be used, simultaneously, as functional elements of analysis and as decision-making elements during the design. Although they are versatile, in general, it is remarkable that these types of models are used very little for the study of the thermal performance of buildings. Subsequently, the theories related to the analysis of the experimental thermal data collected from the scale models and their applicability to the corresponding full-scale prototypes, will be explained. Thereafter, the experiments in laboratory and at outdoor conditions are detailed. Firstly, experiments carried out with simple cube models at different scales are explained. The prototype larger in size and the corresponding undistorted scale model have been subjected to same environmental conditions in every experimental test. Secondly, a step forward is taken carrying out some simultaneous experimental tests of an undistorted scale model, replica of a relatively simple lightweight and glazed building construction. This experiment consists of monitoring the undistorted scale model of the prototype workshop located in the School of Architecture (ETSAM) of the Technical University of Madrid (UPM). For the analysis of experimental data, known related theories and resources are applied, such as, direct comparisons, statistical analyses, Dimensional Analysis and last, but not least important, simulations. Simulations allow us, specifically, flexible comparisons with experimental data. Here, apart the use of the simulation software EnergyPlus, a simulation algorithm is developed ad hoc for this research. Finally, the discussion and conclusions of this research are exposed.

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The friction of rocks in the laboratory is a function of time, velocity of sliding, and displacement. Although the processes responsible for these dependencies are unknown, constitutive equations have been developed that do a reasonable job of describing the laboratory behavior. These constitutive laws have been used to create a model of earthquakes at Parkfield, CA, by using boundary conditions appropriate for the section of the fault that slips in magnitude 6 earthquakes every 20-30 years. The behavior of this model prior to the earthquakes is investigated to determine whether or not the model earthquakes could be predicted in the real world by using realistic instruments and instrument locations. Premonitory slip does occur in the model, but it is relatively restricted in time and space and detecting it from the surface may be difficult. The magnitude of the strain rate at the earth's surface due to this accelerating slip seems lower than the detectability limit of instruments in the presence of earth noise. Although not specifically modeled, microseismicity related to the accelerating creep and to creep events in the model should be detectable. In fact the logarithm of the moment rate on the hypocentral cell of the fault due to slip increases linearly with minus the logarithm of the time to the earthquake. This could conceivably be used to determine when the earthquake was going to occur. An unresolved question is whether this pattern of accelerating slip could be recognized from the microseismicity, given the discrete nature of seismic events. Nevertheless, the model results suggest that the most likely solution to earthquake prediction is to look for a pattern of acceleration in microseismicity and thereby identify the microearthquakes as foreshocks.