Direct simulation of interface dynamics: linking capillary pressure, interfacial area and surface energy

We perform direct numerical simulations of drainage by solving Navier- Stokes equations in the pore space and employing the Volume Of Fluid (VOF) method to track the evolution of the fluid-fluid interface. After demonstrating that the method is able to deal with large viscosity contrasts and to model the transition from stable flow to viscous fingering, we focus on the definition of macroscopic capillary pressure. When the fluids are at rest, the difference between inlet and outlet pressures and the difference between the intrinsic phase average pressure coincide with the capillary pressure. However, when the fluids are in motion these quantities are dominated by viscous forces. In this case, only a definition based on the variation of the interfacial energy provides an accurate measure of the macroscopic capillary pressure and allows separating the viscous from the capillary pressure components.

Modeling the impact of lesions in the human brain.

Lesions of anatomical brain networks result in functional disturbances of brain systems and behavior which depend sensitively, often unpredictably, on the lesion site. The availability of whole-brain maps of structural connections within the human cerebrum and our increased understanding of the physiology and large-scale dynamics of cortical networks allow us to investigate the functional consequences of focal brain lesions in a computational model. We simulate the dynamic effects of lesions placed in different regions of the cerebral cortex by recording changes in the pattern of endogenous ("resting-state") neural activity. We find that lesions produce specific patterns of altered functional connectivity among distant regions of cortex, often affecting both cortical hemispheres. The magnitude of these dynamic effects depends on the lesion location and is partly predicted by structural network properties of the lesion site. In the model, lesions along the cortical midline and in the vicinity of the temporo-parietal junction result in large and widely distributed changes in functional connectivity, while lesions of primary sensory or motor regions remain more localized. The model suggests that dynamic lesion effects can be predicted on the basis of specific network measures of structural brain networks and that these effects may be related to known behavioral and cognitive consequences of brain lesions.

Numerical simulation of ambient seismic wavefield modification caused by pore-fluid effects in an oil reservoir

We have modeled numerically the seismic response of a poroelastic inclusion with properties applicable to an oil reservoir that interacts with an ambient wavefield. The model includes wave-induced fluid flow caused by pressure differences between mesoscopic-scale (i.e., in the order of centimeters to meters) heterogeneities. We used a viscoelastic approximation on the macroscopic scale to implement the attenuation and dispersion resulting from this mesoscopic-scale theory in numerical simulations of wave propagation on the kilometer scale. This upscaling method includes finite-element modeling of wave-induced fluid flow to determine effective seismic properties of the poroelastic media, such as attenuation of P- and S-waves. The fitted, equivalent, viscoelastic behavior is implemented in finite-difference wave propagation simulations. With this two-stage process, we model numerically the quasi-poroelastic wave-propagation on the kilometer scale and study the impact of fluid properties and fluid saturation on the modeled seismic amplitudes. In particular, we addressed the question of whether poroelastic effects within an oil reservoir may be a plausible explanation for low-frequency ambient wavefield modifications observed at oil fields in recent years. Our results indicate that ambient wavefield modification is expected to occur for oil reservoirs exhibiting high attenuation. Whether or not such modifications can be detected in surface recordings, however, will depend on acquisition design and noise mitigation processing as well as site-specific conditions, such as the geologic complexity of the subsurface, the nature of the ambient wavefield, and the amount of surface noise.

Thermal modeling and management in ultrathin chip stack technology

This paper presents a thermal modeling for power management of a new three-dimensional (3-D) thinned dies stacking process. Besides the high concentration of power dissipating sources, which is the direct consequence of the very interesting integration efficiency increase, this new ultra-compact packaging technology can suffer of the poor thermal conductivity (about 700 times smaller than silicon one) of the benzocyclobutene (BCB) used as both adhesive and planarization layers in each level of the stack. Thermal simulation was conducted using three-dimensional (3-D) FEM tool to analyze the specific behaviors in such stacked structure and to optimize the design rules. This study first describes the heat transfer limitation through the vertical path by examining particularly the case of the high dissipating sources under small area. First results of characterization in transient regime by means of dedicated test device mounted in single level structure are presented. For the design optimization, the thermal draining capabilities of a copper grid or full copper plate embedded in the intermediate layer of stacked structure are evaluated as a function of the technological parameters and the physical properties. It is shown an interest for the transverse heat extraction under the buffer devices dissipating most the power and generally localized in the peripheral zone, and for the temperature uniformization, by heat spreading mechanism, in the localized regions where the attachment of the thin die is altered. Finally, all conclusions of this analysis are used for the quantitative projections of the thermal performance of a first demonstrator based on a three-levels stacking structure for space application.

Modeling water movement in horizontal columns using fractal theory

Fractal mathematics has been used to characterize water and solute transport in porous media and also to characterize and simulate porous media properties. The objective of this study was to evaluate the correlation between the soil infiltration parameters sorptivity (S) and time exponent (n) and the parameters dimension (D) and the Hurst exponent (H). For this purpose, ten horizontal columns with pure (either clay or loam) and heterogeneous porous media (clay and loam distributed in layers in the column) were simulated following the distribution of a deterministic Cantor Bar with fractal dimension H" 0.63. Horizontal water infiltration experiments were then simulated using Hydrus 2D software. The sorptivity (S) and time exponent (n) parameters of the Philip equation were estimated for each simulation, using the nonlinear regression procedure of the statistical software package SAS®. Sorptivity increased in the columns with the loam content, which was attributed to the relation of S with the capillary radius. The time exponent estimated by nonlinear regression was found to be less than the traditional value of 0.5. The fractal dimension estimated from the Hurst exponent was 17.5 % lower than the fractal dimension of the Cantor Bar used to generate the columns.

Determination of hydraulic properties of a tropical soil of Hawaii using column experiments and inverse modeling

A method for determining soil hydraulic properties of a weathered tropical soil (Oxisol) using a medium-sized column with undisturbed soil is presented. The method was used to determine fitting parameters of the water retention curve and hydraulic conductivity functions of a soil column in support of a pesticide leaching study. The soil column was extracted from a continuously-used research plot in Central Oahu (Hawaii, USA) and its internal structure was examined by computed tomography. The experiment was based on tension infiltration into the soil column with free outflow at the lower end. Water flow through the soil core was mathematically modeled using a computer code that numerically solves the one-dimensional Richards equation. Measured soil hydraulic parameters were used for direct simulation, and the retention and soil hydraulic parameters were estimated by inverse modeling. The inverse modeling produced very good agreement between model outputs and measured flux and pressure head data for the relatively homogeneous column. The moisture content at a given pressure from the retention curve measured directly in small soil samples was lower than that obtained through parameter optimization based on experiments using a medium-sized undisturbed soil column.

Use of the swat model for hydro-sedimentologic simulation in a small rural watershed

Mathematical models have great potential to support land use planning, with the goal of improving water and land quality. Before using a model, however, the model must demonstrate that it can correctly simulate the hydrological and erosive processes of a given site. The SWAT model (Soil and Water Assessment Tool) was developed in the United States to evaluate the effects of conservation agriculture on hydrological processes and water quality at the watershed scale. This model was initially proposed for use without calibration, which would eliminate the need for measured hydro-sedimentologic data. In this study, the SWAT model was evaluated in a small rural watershed (1.19 km²) located on the basalt slopes of the state of Rio Grande do Sul in southern Brazil, where farmers have been using cover crops associated with minimum tillage to control soil erosion. Values simulated by the model were compared with measured hydro-sedimentological data. Results for surface and total runoff on a daily basis were considered unsatisfactory (Nash-Sutcliffe efficiency coefficient - NSE < 0.5). However simulation results on monthly and annual scales were significantly better. With regard to the erosion process, the simulated sediment yields for all years of the study were unsatisfactory in comparison with the observed values on a daily and monthly basis (NSE values < -6), and overestimated the annual sediment yield by more than 100 %.

Sex differences in urinary levels of several biological indicators of exposure: a simulation study using a compartmental based toxicokinetic model

Toxicokinetic modeling is a useful tool to describe or predict the behavior of a chemical agent in the human or animal organism. A general model based on four compartments was developed in a previous study in order to quantify the effect of human variability on a wide range of biological exposure indicators. The aim of this study was to adapt this existing general toxicokinetic model to three organic solvents, which were methyl ethyl ketone, 1-methoxy-2-propanol and 1,1,1,-trichloroethane, and to take into account sex differences. We assessed in a previous human volunteer study the impact of sex on different biomarkers of exposure corresponding to the three organic solvents mentioned above. Results from that study suggested that not only physiological differences between men and women but also differences due to sex hormones levels could influence the toxicokinetics of the solvents. In fact the use of hormonal contraceptive had an effect on the urinary levels of several biomarkers, suggesting that exogenous sex hormones could influence CYP2E1 enzyme activity. These experimental data were used to calibrate the toxicokinetic models developed in this study. Our results showed that it was possible to use an existing general toxicokinetic model for other compounds. In fact, most of the simulation results showed good agreement with the experimental data obtained for the studied solvents, with a percentage of model predictions that lies within the 95% confidence interval varying from 44.4 to 90%. Results pointed out that for same exposure conditions, men and women can show important differences in urinary levels of biological indicators of exposure. Moreover, when running the models by simulating industrial working conditions, these differences could even be more pronounced. In conclusion, a general and simple toxicokinetic model, adapted for three well known organic solvents, allowed us to show that metabolic parameters can have an important impact on the urinary levels of the corresponding biomarkers. These observations give evidence of an interindividual variablity, an aspect that should have its place in the approaches for setting limits of occupational exposure.

MORM--a Petri net based model for assessing OH&S risks in industrial processes: modeling qualitative aspects.

Because of the increase in workplace automation and the diversification of industrial processes, workplaces have become more and more complex. The classical approaches used to address workplace hazard concerns, such as checklists or sequence models, are, therefore, of limited use in such complex systems. Moreover, because of the multifaceted nature of workplaces, the use of single-oriented methods, such as AEA (man oriented), FMEA (system oriented), or HAZOP (process oriented), is not satisfactory. The use of a dynamic modeling approach in order to allow multiple-oriented analyses may constitute an alternative to overcome this limitation. The qualitative modeling aspects of the MORM (man-machine occupational risk modeling) model are discussed in this article. The model, realized on an object-oriented Petri net tool (CO-OPN), has been developed to simulate and analyze industrial processes in an OH&S perspective. The industrial process is modeled as a set of interconnected subnets (state spaces), which describe its constitutive machines. Process-related factors are introduced, in an explicit way, through machine interconnections and flow properties. While man-machine interactions are modeled as triggering events for the state spaces of the machines, the CREAM cognitive behavior model is used in order to establish the relevant triggering events. In the CO-OPN formalism, the model is expressed as a set of interconnected CO-OPN objects defined over data types expressing the measure attached to the flow of entities transiting through the machines. Constraints on the measures assigned to these entities are used to determine the state changes in each machine. Interconnecting machines implies the composition of such flow and consequently the interconnection of the measure constraints. This is reflected by the construction of constraint enrichment hierarchies, which can be used for simulation and analysis optimization in a clear mathematical framework. The use of Petri nets to perform multiple-oriented analysis opens perspectives in the field of industrial risk management. It may significantly reduce the duration of the assessment process. But, most of all, it opens perspectives in the field of risk comparisons and integrated risk management. Moreover, because of the generic nature of the model and tool used, the same concepts and patterns may be used to model a wide range of systems and application fields.

Budgeting rockfall and modeling sedimentary delivery in torrent systems

This thesis is a compilation of projects to study sediment processes recharging debris flow channels. These works, conducted during my stay at the University of Lausanne, focus in the geological and morphological implications of torrent catchments to characterize debris supply, a fundamental element to predict debris flows. Other aspects of sediment dynamics are considered, e.g. the coupling headwaters - torrent, as well as the development of a modeling software that simulates sediment transfer in torrent systems. The sediment activity at Manival, an active torrent system of the northern French Alps, was investigated using terrestrial laser scanning and supplemented with geostructural investigations and a survey of sediment transferred in the main torrent. A full year of sediment flux could be observed, which coincided with two debris flows and several bedload transport events. This study revealed that both debris flows generated in the torrent and were preceded in time by recharge of material from the headwaters. Debris production occurred mostly during winter - early spring time and was caused by large slope failures. Sediment transfers were more puzzling, occurring almost exclusively in early spring subordinated to runoffconditions and in autumn during long rainfall. Intense rainstorms in summer did not affect debris storage that seems to rely on the stability of debris deposits. The morpho-geological implication in debris supply was evaluated using DEM and field surveys. A slope angle-based classification of topography could characterize the mode of debris production and transfer. A slope stability analysis derived from the structures in rock mass could assess susceptibility to failure. The modeled rockfall source areas included more than 97% of the recorded events and the sediment budgets appeared to be correlated to the density of potential slope failure. This work showed that the analysis of process-related terrain morphology and of susceptibility to slope failure document the sediment dynamics to quantitatively assess erosion zones leading to debris flow activity. The development of erosional landforms was evaluated by analyzing their geometry with the orientations of potential rock slope failure and with the direction of the maximum joint frequency. Structure in rock mass, but in particular wedge failure and the dominant discontinuities, appear as a first-order control of erosional mechanisms affecting bedrock- dominated catchment. They represent some weaknesses that are exploited primarily by mass wasting processes and erosion, promoting not only the initiation of rock couloirs and gullies, but also their propagation. Incorporating the geological control in geomorphic processes contributes to better understand the landscape evolution of active catchments. A sediment flux algorithm was implemented in a sediment cascade model that discretizes the torrent catchment in channel reaches and individual process-response systems. Each conceptual element includes in simple manner geomorphological and sediment flux information derived from GIS complemented with field mapping. This tool enables to simulate sediment transfers in channels considering evolving debris supply and conveyance, and helps reducing the uncertainty inherent to sediment budget prediction in torrent systems. Cette thèse est un recueil de projets d'études des processus de recharges sédimentaires des chenaux torrentiels. Ces travaux, réalisés lorsque j'étais employé à l'Université de Lausanne, se concentrent sur les implications géologiques et morphologiques des bassins dans l'apport de sédiments, élément fondamental dans la prédiction de laves torrentielles. D'autres aspects de dynamique sédimentaire ont été abordés, p. ex. le couplage torrent - bassin, ainsi qu'un modèle de simulation du transfert sédimentaire en milieu torrentiel. L'activité sédimentaire du Manival, un système torrentiel actif des Alpes françaises, a été étudiée par relevés au laser scanner terrestre et complétée par une étude géostructurale ainsi qu'un suivi du transfert en sédiments du torrent. Une année de flux sédimentaire a pu être observée, coïncidant avec deux laves torrentielles et plusieurs phénomènes de charriages. Cette étude a révélé que les laves s'étaient générées dans le torrent et étaient précédées par une recharge de débris depuis les versants. La production de débris s'est passée principalement en l'hiver - début du printemps, causée par de grandes ruptures de pentes. Le transfert était plus étrange, se produisant presque exclusivement au début du printemps subordonné aux conditions d'écoulement et en automne lors de longues pluies. Les orages d'été n'affectèrent guère les dépôts, qui semblent dépendre de leur stabilité. Les implications morpho-géologiques dans l'apport sédimentaire ont été évaluées à l'aide de MNT et études de terrain. Une classification de la topographie basée sur la pente a permis de charactériser le mode de production et transfert. Une analyse de stabilité de pente à partir des structures de roches a permis d'estimer la susceptibilité à la rupture. Les zones sources modélisées comprennent plus de 97% des chutes de blocs observées et les bilans sédimentaires sont corrélés à la densité de ruptures potentielles. Ce travail d'analyses des morphologies du terrain et de susceptibilité à la rupture documente la dynamique sédimentaire pour l'estimation quantitative des zones érosives induisant l'activité torrentielle. Le développement des formes d'érosion a été évalué par l'analyse de leur géométrie avec celle des ruptures potentielles et avec la direction de la fréquence maximale des joints. Les structures de roches, mais en particulier les dièdres et les discontinuités dominantes, semblent être très influents dans les mécanismes d'érosion affectant les bassins rocheux. Ils représentent des zones de faiblesse exploitées en priorité par les processus de démantèlement et d'érosion, encourageant l'initiation de ravines et couloirs, mais aussi leur propagation. L'incorporation du control géologique dans les processus de surface contribue à une meilleure compréhension de l'évolution topographique de bassins actifs. Un algorithme de flux sédimentaire a été implémenté dans un modèle en cascade, lequel divise le bassin en biefs et en systèmes individuels répondant aux processus. Chaque unité inclut de façon simple les informations géomorpologiques et celles du flux sédimentaire dérivées à partir de SIG et de cartographie de terrain. Cet outil permet la simulation des transferts de masse dans les chenaux, considérants la variabilité de l'apport et son transport, et aide à réduire l'incertitude liée à la prédiction de bilans sédimentaires torrentiels. Ce travail vise très humblement d'éclairer quelques aspects de la dynamique sédimentaire en milieu torrentiel.

High-throughput SELEX SAGE method for quantitative modeling of transcription-factor binding sites.

The ability to determine the location and relative strength of all transcription-factor binding sites in a genome is important both for a comprehensive understanding of gene regulation and for effective promoter engineering in biotechnological applications. Here we present a bioinformatically driven experimental method to accurately define the DNA-binding sequence specificity of transcription factors. A generalized profile was used as a predictive quantitative model for binding sites, and its parameters were estimated from in vitro-selected ligands using standard hidden Markov model training algorithms. Computer simulations showed that several thousand low- to medium-affinity sequences are required to generate a profile of desired accuracy. To produce data on this scale, we applied high-throughput genomics methods to the biochemical problem addressed here. A method combining systematic evolution of ligands by exponential enrichment (SELEX) and serial analysis of gene expression (SAGE) protocols was coupled to an automated quality-controlled sequence extraction procedure based on Phred quality scores. This allowed the sequencing of a database of more than 10,000 potential DNA ligands for the CTF/NFI transcription factor. The resulting binding-site model defines the sequence specificity of this protein with a high degree of accuracy not achieved earlier and thereby makes it possible to identify previously unknown regulatory sequences in genomic DNA. A covariance analysis of the selected sites revealed non-independent base preferences at different nucleotide positions, providing insight into the binding mechanism.

Analysis and spatial modeling of the indoor radon Swiss data

The present research deals with an important public health threat, which is the pollution created by radon gas accumulation inside dwellings. The spatial modeling of indoor radon in Switzerland is particularly complex and challenging because of many influencing factors that should be taken into account. Indoor radon data analysis must be addressed from both a statistical and a spatial point of view. As a multivariate process, it was important at first to define the influence of each factor. In particular, it was important to define the influence of geology as being closely associated to indoor radon. This association was indeed observed for the Swiss data but not probed to be the sole determinant for the spatial modeling. The statistical analysis of data, both at univariate and multivariate level, was followed by an exploratory spatial analysis. Many tools proposed in the literature were tested and adapted, including fractality, declustering and moving windows methods. The use of Quan-tité Morisita Index (QMI) as a procedure to evaluate data clustering in function of the radon level was proposed. The existing methods of declustering were revised and applied in an attempt to approach the global histogram parameters. The exploratory phase comes along with the definition of multiple scales of interest for indoor radon mapping in Switzerland. The analysis was done with a top-to-down resolution approach, from regional to local lev¬els in order to find the appropriate scales for modeling. In this sense, data partition was optimized in order to cope with stationary conditions of geostatistical models. Common methods of spatial modeling such as Κ Nearest Neighbors (KNN), variography and General Regression Neural Networks (GRNN) were proposed as exploratory tools. In the following section, different spatial interpolation methods were applied for a par-ticular dataset. A bottom to top method complexity approach was adopted and the results were analyzed together in order to find common definitions of continuity and neighborhood parameters. Additionally, a data filter based on cross-validation was tested with the purpose of reducing noise at local scale (the CVMF). At the end of the chapter, a series of test for data consistency and methods robustness were performed. This lead to conclude about the importance of data splitting and the limitation of generalization methods for reproducing statistical distributions. The last section was dedicated to modeling methods with probabilistic interpretations. Data transformation and simulations thus allowed the use of multigaussian models and helped take the indoor radon pollution data uncertainty into consideration. The catego-rization transform was presented as a solution for extreme values modeling through clas-sification. Simulation scenarios were proposed, including an alternative proposal for the reproduction of the global histogram based on the sampling domain. The sequential Gaussian simulation (SGS) was presented as the method giving the most complete information, while classification performed in a more robust way. An error measure was defined in relation to the decision function for data classification hardening. Within the classification methods, probabilistic neural networks (PNN) show to be better adapted for modeling of high threshold categorization and for automation. Support vector machines (SVM) on the contrary performed well under balanced category conditions. In general, it was concluded that a particular prediction or estimation method is not better under all conditions of scale and neighborhood definitions. Simulations should be the basis, while other methods can provide complementary information to accomplish an efficient indoor radon decision making.

Exploring the rate-limiting steps in visual phototransduction recovery by bottom-up kinetic modeling

Phototransduction in vertebrate photoreceptor cells represents a paradigm of signaling pathways mediated by G-protein-coupled receptors (GPCRs), which share common modules linking the initiation of the cascade to the final response of the cell. In this work, we focused on the recovery phase of the visual photoresponse, which is comprised of several interacting mechanisms. We employed current biochemical knowledge to investigate the response mechanisms of a comprehensive model of the visual phototransduction pathway. In particular, we have improved the model by implementing a more detailed representation of the recoverin (Rec)-mediated calcium feedback on rhodopsin kinase and including a dynamic arrestin (Arr) oligomerization mechanism. The model was successfully employed to investigate the rate limiting steps in the recovery of the rod photoreceptor cell after illumination. Simulation of experimental conditions in which the expression levels of rhodospin kinase (RK), of the regulator of the G-protein signaling (RGS), of Arr and of Rec were altered individually or in combination revealed severe kinetic constraints to the dynamics of the overall network. Our simulations confirm that RGS-mediated effector shutdown is the rate-limiting step in the recovery of the photoreceptor and show that the dynamic formation and dissociation of Arr homodimers and homotetramers at different light intensities significantly affect the timing of rhodopsin shutdown. The transition of Arr from its oligomeric storage forms to its monomeric form serves to temper its availability in the functional state. Our results may explain the puzzling evidence that overexpressing RK does not influence the saturation time of rod cells at bright light stimuli. The approach presented here could be extended to the study of other GPCR signaling pathways.

Biological exposure indicators: quantification of biological variability using toxicokinetic modeling

Compartmental and physiologically based toxicokinetic modeling coupled with Monte Carlo simulation were used to quantify the impact of biological variability (physiological, biochemical, and anatomic parameters) on the values of a series of bio-indicators of metal and organic industrial chemical exposures. A variability extent index and the main parameters affecting biological indicators were identified. Results show a large diversity in interindividual variability for the different categories of biological indicators examined. Measurement of the unchanged substance in blood, alveolar air, or urine is much less variable than the measurement of metabolites, both in blood and urine. In most cases, the alveolar flow and cardiac output were identified as the prime parameters determining biological variability, thus suggesting the importance of workload intensity on absorbed dose for inhaled chemicals.

Simulation and Analysis of Arterial Traffic Operations Along the U.S. 61 Corridor in Burlington, Iowa, 1998

The Center for Transportation Research and Education (CTRE) used the traffic simulation model CORSIM to access proposed capacity and safety improvement strategies for the U.S. 61 corridor through Burlington, Iowa. The comparison between the base and alternative models allow for evaluation of the traffic flow performance under the existing conditions as well as other design scenarios. The models also provide visualization of performance for interpretation by technical staff, public policy makers, and the public. The objectives of this project are to evaluate the use of traffic simulation models for future use by the Iowa Department of Transportation (DOT) and to develop procedures for employing simulation modeling to conduct the analysis of alternative designs. This report presents both the findings of the U.S. 61 evaluation and an overview of model development procedures. The first part of the report includes the simulation modeling development procedures. The simulation analysis is illustrated through the Burlington U.S. 61 corridor case study application. Part I is not intended to be a user manual but simply introductory guidelines for traffic simulation modeling. Part II of the report evaluates the proposed improvement concepts in a side by side comparison of the base and alternative models.