RWater – A Cyber Enabled Tool For Hydrologic Modeling And Analysis

Existing distributed hydrologic models are complex and computationally demanding for using as a rapid-forecasting policy-decision tool, or even as a class-room educational tool. In addition, platform dependence, specific input/output data structures and non-dynamic data-interaction with pluggable software components inside the existing proprietary frameworks make these models restrictive only to the specialized user groups. RWater is a web-based hydrologic analysis and modeling framework that utilizes the commonly used R software within the HUBzero cyber infrastructure of Purdue University. RWater is designed as an integrated framework for distributed hydrologic simulation, along with subsequent parameter optimization and visualization schemes. RWater provides platform independent web-based interface, flexible data integration capacity, grid-based simulations, and user-extensibility. RWater uses RStudio to simulate hydrologic processes on raster based data obtained through conventional GIS pre-processing. The program integrates Shuffled Complex Evolution (SCE) algorithm for parameter optimization. Moreover, RWater enables users to produce different descriptive statistics and visualization of the outputs at different temporal resolutions. The applicability of RWater will be demonstrated by application on two watersheds in Indiana for multiple rainfall events.

A Modular and digitally programmable interface based on band-pass sigma-delta modulator for mixed-signal systems-on-chip

The focus of this thesis is to discuss the development and modeling of an interface architecture to be employed for interfacing analog signals in mixed-signal SOC. We claim that the approach that is going to be presented is able to achieve wide frequency range, and covers a large range of applications with constant performance, allied to digital configuration compatibility. Our primary assumptions are to use a fixed analog block and to promote application configurability in the digital domain, which leads to a mixed-signal interface. The use of a fixed analog block avoids the performance loss common to configurable analog blocks. The usage of configurability on the digital domain makes possible the use of all existing tools for high level design, simulation and synthesis to implement the target application, with very good performance prediction. The proposed approach utilizes the concept of frequency translation (mixing) of the input signal followed by its conversion to the ΣΔ domain, which makes possible the use of a fairly constant analog block, and also, a uniform treatment of input signal from DC to high frequencies. The programmability is performed in the ΣΔ digital domain where performance can be closely achieved according to application specification. The interface performance theoretical and simulation model are developed for design space exploration and for physical design support. Two prototypes are built and characterized to validate the proposed model and to implement some application examples. The usage of this interface as a multi-band parametric ADC and as a two channels analog multiplier and adder are shown. The multi-channel analog interface architecture is also presented. The characterization measurements support the main advantages of the approach proposed.

On developing efficient applications using conservative distributed simulation paradigm

This paper aims to present, using a set of guidelines, how to apply the conservative distributed simulation paradigm (CMB protocol) to develop efficient applications. Using these guidelines, even a user with little experience on distributed simulation and computer architecture can have good performance on distributed simulations using conservative synchronization protocols for parallel processes.The set of guidelines is focus on a specific application domain, the performance evaluation of computer systems, considering models with coarse granularity and few logical processes and running over two platforms: parallel (high performance communication environment) and distributed (low performance communication environment).

Langevin simulation of scalar fields: Additive and multiplicative noises and lattice renormalization

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

New integrated Zeta and Cuk inverters intended for standalone and grid-connected applications

This paper presents new inverter topologies based on the integration of a DC to DC Zeta or Cuk converter with a voltage source inverter (VSI). The proposed integration procedure aims to reduce the amount of components, meaning lower volume, weight and costs. In this context, new families of single-phase and three-phase integrated inverters are also presented. Therefore, considering the novelty for Zeta and Cuk integrated inverters structures, the proposed single-phase and three-phase inverters versions are analyzed for grid-tied and stand-alone applications. Furthermore, in order to demonstrate the feasibility of the proposal, the main simulation and experimental results are presented. © 2011 IEEE.

iSPD: An iconic-based modeling simulator for distributed grids

Simulation of large and complex systems, such as computing grids, is a difficult task. Current simulators, despite providing accurate results, are significantly hard to use. They usually demand a strong knowledge of programming, what is not a standard pattern in today's users of grids and high performance computing. The need for computer expertise prevents these users from simulating how the environment will respond to their applications, what may imply in large loss of efficiency, wasting precious computational resources. In this paper we introduce iSPD, iconic Simulator of Parallel and Distributed Systems, which is a simulator where grid models are produced through an iconic interface. We describe the simulator and its intermediate model languages. Results presented here provide an insight in its easy-of-use and accuracy.

Modeling the formation and propagation of desiccation cracks in soils

The problem of desiccation cracks in soils has received increasing attention in the last few years, in both experimental investigations and modeling. Experimental research has been mainly focused on the behavior of slurries subjected to drying in plates of different shapes, sizes and thickness. The main objectives of these studies were to learn about the process of crack formation under controlled environmental conditions, and also to better understand the effect of different factors (e.g. soil type, boundary conditions, soil thickness) on the morphology of the crack network. As for the numerical modeling, different approaches have been suggested lately to describe the behavior of drying cracks in soils. One aspect that it is still difficult to describe properly is the crack pattern observed in desiccated soils. This work presents a novel technique to model the behavior of drying soils. The crack patter observed in desiccation tests on circular plates are simulated with the main objective of predicting the effect of soil thickness on crack pattern. Good agreement between experimental results and model prediction are observed.

Distance software: design and analysis of distance sampling surveys for estimating population size

1. Distance sampling is a widely used technique for estimating the size or density of biological populations. Many distance sampling designs and most analyses use the software Distance. 2. We briefly review distance sampling and its assumptions, outline the history, structure and capabilities of Distance, and provide hints on its use. 3. Good survey design is a crucial prerequisite for obtaining reliable results. Distance has a survey design engine, with a built-in geographic information system, that allows properties of different proposed designs to be examined via simulation, and survey plans to be generated. 4. A first step in analysis of distance sampling data is modeling the probability of detection. Distance contains three increasingly sophisticated analysis engines for this: conventional distance sampling, which models detection probability as a function of distance from the transect and assumes all objects at zero distance are detected; multiple-covariate distance sampling, which allows covariates in addition to distance; and mark–recapture distance sampling, which relaxes the assumption of certain detection at zero distance. 5. All three engines allow estimation of density or abundance, stratified if required, with associated measures of precision calculated either analytically or via the bootstrap. 6. Advanced analysis topics covered include the use of multipliers to allow analysis of indirect surveys (such as dung or nest surveys), the density surface modeling analysis engine for spatial and habitat-modeling, and information about accessing the analysis engines directly from other software. 7. Synthesis and applications. Distance sampling is a key method for producing abundance and density estimates in challenging field conditions. The theory underlying the methods continues to expand to cope with realistic estimation situations. In step with theoretical developments, state-of- the-art software that implements these methods is described that makes the methods accessible to practicing ecologists.

A novel set of ss-N-biaryl ether sulfonamide hydroxamates as potential MMPs inhibitors: Molecular dynamics simulations and molecular properties evaluation

Matrix metalloproteinases (MMPs) constitute a family of zinc-dependent proteases involved in the extracellular matrix degradation. MMP-2 and MMP9 are overexpressed in several human cancer types, including melanoma, thus the development of new compounds to inhibit MMPs' activity is desirable. Molecular dynamic simulation and molecular properties calculations were performed on a set of novel beta-N-biaryl ether sulfonamide-based hydroxamates, reported as MMP-2 and MMP-9 inhibitors, for providing data to develop an exploratory analysis. Thermodynamic, electronic, and steric descriptors have significantly discriminated highly active from moderately and less active inhibitors of MMP-2 whereas apparent partition coefficient at pH 1.5 was also significant for the MMP-9 data set. Compound 47 was considered an outlier in all analysis, indicating the presence of a bulky substituent group in R3 is crucial to this set of inhibitors for the establishment of molecular interactions with the S1 subsite of both enzymes, but there is a limit. (C) 2012 Wiley Periodicals, Inc.

Statistical analysis and simulation techniques in wall-bounded turbulence

The present work is devoted to the assessment of the energy fluxes physics in the space of scales and physical space of wall-turbulent flows. The generalized Kolmogorov equation will be applied to DNS data of a turbulent channel flow in order to describe the energy fluxes paths from production to dissipation in the augmented space of wall-turbulent flows. This multidimensional description will be shown to be crucial to understand the formation and sustainment of the turbulent fluctuations fed by the energy fluxes coming from the near-wall production region. An unexpected behavior of the energy fluxes comes out from this analysis consisting of spiral-like paths in the combined physical/scale space where the controversial reverse energy cascade plays a central role. The observed behavior conflicts with the classical notion of the Richardson/Kolmogorov energy cascade and may have strong repercussions on both theoretical and modeling approaches to wall-turbulence. To this aim a new relation stating the leading physical processes governing the energy transfer in wall-turbulence is suggested and shown able to capture most of the rich dynamics of the shear dominated region of the flow. Two dynamical processes are identified as driving mechanisms for the fluxes, one in the near wall region and a second one further away from the wall. The former, stronger one is related to the dynamics involved in the near-wall turbulence regeneration cycle. The second suggests an outer self-sustaining mechanism which is asymptotically expected to take place in the log-layer and could explain the debated mixed inner/outer scaling of the near-wall statistics. The same approach is applied for the first time to a filtered velocity field. A generalized Kolmogorov equation specialized for filtered velocity field is derived and discussed. The results will show what effects the subgrid scales have on the resolved motion in both physical and scale space, singling out the prominent role of the filter length compared to the cross-over scale between production dominated scales and inertial range, lc, and the reverse energy cascade region lb. The systematic characterization of the resolved and subgrid physics as function of the filter scale and of the wall-distance will be shown instrumental for a correct use of LES models in the simulation of wall turbulent flows. Taking inspiration from the new relation for the energy transfer in wall turbulence, a new class of LES models will be also proposed. Finally, the generalized Kolmogorov equation specialized for filtered velocity fields will be shown to be an helpful statistical tool for the assessment of LES models and for the development of new ones. As example, some classical purely dissipative eddy viscosity models are analyzed via an a priori procedure.

Interactive simulation of flexible parts

Computer simulations play an ever growing role for the development of automotive products. Assembly simulation, as well as many other processes, are used systematically even before the first physical prototype of a vehicle is built in order to check whether particular components can be assembled easily or whether another part is in the way. Usually, this kind of simulation is limited to rigid bodies. However, a vehicle contains a multitude of flexible parts of various types: cables, hoses, carpets, seat surfaces, insulations, weatherstrips... Since most of the problems using these simulations concern one-dimensional components and since an intuitive tool for cable routing is still needed, we have chosen to concentrate on this category, which includes cables, hoses and wiring harnesses. In this thesis, we present a system for simulating one dimensional flexible parts such as cables or hoses. The modeling of bending and torsion follows the Cosserat model. For this purpose we use a generalized spring-mass system and describe its configuration by a carefully chosen set of coordinates. Gravity and contact forces as well as the forces responsible for length conservation are expressed in Cartesian coordinates. But bending and torsion effects can be dealt with more effectively by using quaternions to represent the orientation of the segments joining two neighboring mass points. This augmented system allows an easy formulation of all interactions with the best appropriate coordinate type and yields a strongly banded Hessian matrix. An energy minimizing process accounts for a solution exempt from the oscillations that are typical of spring-mass systems. The use of integral forces, similar to an integral controller, allows to enforce exactly the constraints. The whole system is numerically stable and can be solved at interactive frame rates. It is integrated in the DaimlerChrysler in-house Virtual Reality Software veo for use in applications such as cable routing and assembly simulation and has been well received by users. Parts of this work have been published at the ACM Solid and Physical Modeling Conference 2006 and have been selected for the special issue of the Computer-Aided-Design Journal to the conference.

Investigation on laser shock peening capability by FE simulation

Laser shock peening is a technique similar to shot peening that imparts compressive residual stresses in materials for improving fatigue resistance. The ability to use a high energy laser pulse to generate shock waves, inducing a compressive residual stress field in metallic materials, has applications in multiple fields such as turbo-machinery, airframe structures, and medical appliances. The transient nature of the LSP phenomenon and the high rate of the laser's dynamic make real time in-situ measurement of laser/material interaction very challenging. For this reason and for the high cost of the experimental tests, reliable analytical methods for predicting detailed effects of LSP are needed to understand the potential of the process. Aim of this work has been the prediction of residual stress field after Laser Peening process by means of Finite Element Modeling. The work has been carried out in the Stress Methods department of Airbus Operations GmbH (Hamburg) and it includes investigation on compressive residual stresses induced by Laser Shock Peening, study on mesh sensitivity, optimization and tuning of the model by using physical and numerical parameters, validation of the model by comparing it with experimental results. The model has been realized with Abaqus/Explicit commercial software starting from considerations done on previous works. FE analyses are “Mesh Sensitive”: by increasing the number of elements and by decreasing their size, the software is able to probe even the details of the real phenomenon. However, these details, could be only an amplification of real phenomenon. For this reason it was necessary to optimize the mesh elements' size and number. A new model has been created with a more fine mesh in the trough thickness direction because it is the most involved in the process deformations. This increment of the global number of elements has been paid with an "in plane" size reduction of the elements far from the peened area in order to avoid too high computational costs. Efficiency and stability of the analyses has been improved by using bulk viscosity coefficients, a merely numerical parameter available in Abaqus/Explicit. A plastic rate sensitivity study has been also carried out and a new set of Johnson Cook's model coefficient has been chosen. These investigations led to a more controllable and reliable model, valid even for more complex geometries. Moreover the study about the material properties highlighted a gap of the model about the simulation of the surface conditions. Modeling of the ablative layer employed during the real process has been used to fill this gap. In the real process ablative layer is a super thin sheet of pure aluminum stuck on the masterpiece. In the simulation it has been simply reproduced as a 100µm layer made by a material with a yield point of 10MPa. All those new settings has been applied to a set of analyses made with different geometry models to verify the robustness of the model. The calibration of the model with the experimental results was based on stress and displacement measurements carried out on the surface and in depth as well. The good correlation between the simulation and experimental tests results proved this model to be reliable.

Modeling, characterization and microalgal cultivation in an airlift panel photobioreactors.

Microalgae cultures are attracting great attentions in many industrial applications. However, one of the technical challenges is to cut down the capital and operational costs of microalgae production systems, with special difficulty in reactor design and scale-up. The thesis work open with an overview on the microalgae cultures as a possible answer to solve some of the upcoming planet issues and their applications in several fields. After the work offers a general outline on the state of the art of microalgae culture systems, taking a special look to the enclosed photobioreactors (PBRs). The overall objective of this study is to advance the knowledge of PBRs design and lead to innovative large scale processes of microalgae cultivation. An airlift flat panel photobioreactor was designed, modeled and experimentally characterized. The gas holdup, liquid flow velocity and oxygen mass transfer of the reactor were experimentally determined and mathematically modeled, and the performance of the reactor was tested by cultivation of microalgae. The model predicted data correlated well with experimental data, and the high concentration of suspension cell culture could be achieved with controlled conditions. The reactor was inoculated with the algal strain Scenedesmus obliquus sp. first and with Chlorella sp. later and sparged with air. The reactor was operated in batch mode and daily monitored for pH, temperature, and biomass concentration and activity. The productivity of the novel device was determined, suggesting the proposed design can be effectively and economically used in carbon dioxide mitigation technologies and in the production of algal biomass for biofuel and other bioproducts. Those research results favored the possibility of scaling the reactor up into industrial scales based on the models employed, and the potential advantages and disadvantages were discussed for this novel industrial design.

Copper and human health: biochemistry, genetics, and strategies for modeling dose-response relationships

Copper (Cu) and its alloys are used extensively in domestic and industrial applications. Cu is also an essential element in mammalian nutrition. Since both copper deficiency and copper excess produce adverse health effects, the dose-response curve is U-shaped, although the precise form has not yet been well characterized. Many animal and human studies were conducted on copper to provide a rich database from which data suitable for modeling the dose-response relationship for copper may be extracted. Possible dose-response modeling strategies are considered in this review, including those based on the benchmark dose and categorical regression. The usefulness of biologically based dose-response modeling techniques in understanding copper toxicity was difficult to assess at this time since the mechanisms underlying copper-induced toxicity have yet to be fully elucidated. A dose-response modeling strategy for copper toxicity was proposed associated with both deficiency and excess. This modeling strategy was applied to multiple studies of copper-induced toxicity, standardized with respect to severity of adverse health outcomes and selected on the basis of criteria reflecting the quality and relevance of individual studies. The use of a comprehensive database on copper-induced toxicity is essential for dose-response modeling since there is insufficient information in any single study to adequately characterize copper dose-response relationships. The dose-response modeling strategy envisioned here is designed to determine whether the existing toxicity data for copper excess or deficiency may be effectively utilized in defining the limits of the homeostatic range in humans and other species. By considering alternative techniques for determining a point of departure and low-dose extrapolation (including categorical regression, the benchmark dose, and identification of observed no-effect levels) this strategy will identify which techniques are most suitable for this purpose. This analysis also serves to identify areas in which additional data are needed to better define the characteristics of dose-response relationships for copper-induced toxicity in relation to excess or deficiency.

DEVELOPMENT OF AN OPTIMIZATION MODEL FOR BIOFUEL FACILITY SIZE AND LOCATION AND A SIMULATION MODEL FOR DESIGN OF A BIOFUEL SUPPLY CHAIN

A range of societal issues have been caused by fossil fuel consumption in the transportation sector in the United States (U.S.), including health related air pollution, climate change, the dependence on imported oil, and other oil related national security concerns. Biofuels production from various lignocellulosic biomass types such as wood, forest residues, and agriculture residues have the potential to replace a substantial portion of the total fossil fuel consumption. This research focuses on locating biofuel facilities and designing the biofuel supply chain to minimize the overall cost. For this purpose an integrated methodology was proposed by combining the GIS technology with simulation and optimization modeling methods. The GIS based methodology was used as a precursor for selecting biofuel facility locations by employing a series of decision factors. The resulted candidate sites for biofuel production served as inputs for simulation and optimization modeling. As a precursor to simulation or optimization modeling, the GIS-based methodology was used to preselect potential biofuel facility locations for biofuel production from forest biomass. Candidate locations were selected based on a set of evaluation criteria, including: county boundaries, a railroad transportation network, a state/federal road transportation network, water body (rivers, lakes, etc.) dispersion, city and village dispersion, a population census, biomass production, and no co-location with co-fired power plants. The simulation and optimization models were built around key supply activities including biomass harvesting/forwarding, transportation and storage. The built onsite storage served for spring breakup period where road restrictions were in place and truck transportation on certain roads was limited. Both models were evaluated using multiple performance indicators, including cost (consisting of the delivered feedstock cost, and inventory holding cost), energy consumption, and GHG emissions. The impact of energy consumption and GHG emissions were expressed in monetary terms to keep consistent with cost. Compared with the optimization model, the simulation model represents a more dynamic look at a 20-year operation by considering the impacts associated with building inventory at the biorefinery to address the limited availability of biomass feedstock during the spring breakup period. The number of trucks required per day was estimated and the inventory level all year around was tracked. Through the exchange of information across different procedures (harvesting, transportation, and biomass feedstock processing procedures), a smooth flow of biomass from harvesting areas to a biofuel facility was implemented. The optimization model was developed to address issues related to locating multiple biofuel facilities simultaneously. The size of the potential biofuel facility is set up with an upper bound of 50 MGY and a lower bound of 30 MGY. The optimization model is a static, Mathematical Programming Language (MPL)-based application which allows for sensitivity analysis by changing inputs to evaluate different scenarios. It was found that annual biofuel demand and biomass availability impacts the optimal results of biofuel facility locations and sizes.