CFD-modeling of insulation debris transport phenomena in water flow

The investigation of insulation debris generation, transport and sedimentation becomes important with regard to reactor safety research for PWR and BWR, when considering the long-term behavior of emergency core cooling systems during all types of loss of coolant accidents (LOCA). The insulation debris released near the break during a LOCA incident consists of a mixture of disparate particle population that varies with size, shape, consistency and other properties. Some fractions of the released insulation debris can be transported into the reactor sump, where it may perturb/impinge on the emergency core cooling systems. Open questions of generic interest are the sedimentation of the insulation debris in a water pool, its possible re-suspension and transport in the sump water flow and the particle load on strainers and corresponding pressure drop. A joint research project on such questions is being performed in cooperation between the University of Applied Sciences Zittau/Görlitz and the Forschungszentrum Dresden-Rossendorf. The project deals with the experimental investigation of particle transport phenomena in coolant flow and the development of CFD models for its description. While the experiments are performed at the University at Zittau/Görlitz, the theoretical modeling efforts are concentrated at Forschungszentrum Dresden-Rossendorf. In the current paper the basic concepts for CFD-modeling are described and feasibility studies including the conceptual design of the experiments are presented. © 2009 Elsevier B.V. All rights reserved.

CFD-modeling and Experiments of insulation debris transport phenomena in water flow

The investigation of insulation debris generation, transport and sedimentation becomes important with regard to reactor safety research for PWR and BWR, when considering the long-term behavior of emergency core cooling systems during all types of loss of coolant accidents (LOCA). The insulation debris released near the break during a LOCA incident consists of a mixture of disparate particle population that varies with size, shape, consistency and other properties. Some fractions of the released insulation debris can be transported into the reactor sump, where it may perturb/impinge on the emergency core cooling systems. Open questions of generic interest are the sedimentation of the insulation debris in a water pool, its possible re-suspension and transport in the sump water flow and the particle load on strainers and corresponding pressure drop. A joint research project on such questions is being performed in cooperation between the University of Applied Sciences Zittau/Görlitz and the Forschungszentrum Dresden-Rossendorf. The project deals with the experimental investigation of particle transport phenomena in coolant flow and the development of CFD models for its description. While the experiments are performed at the University at Zittau/Görlitz, the theoretical modeling efforts are concentrated at Forschungszentrum Dresden-Rossendorf. In the current paper the basic concepts for CFD modeling are described and feasibility studies including the conceptual design of the experiments are presented.

A nested Petri net framework for modeling and analyzing multi-agent systems

In the past two decades, multi-agent systems (MAS) have emerged as a new paradigm for conceptualizing large and complex distributed software systems. A multi-agent system view provides a natural abstraction for both the structure and the behavior of modern-day software systems. Although there were many conceptual frameworks for using multi-agent systems, there was no well established and widely accepted method for modeling multi-agent systems. This dissertation research addressed the representation and analysis of multi-agent systems based on model-oriented formal methods. The objective was to provide a systematic approach for studying MAS at an early stage of system development to ensure the quality of design. ^ Given that there was no well-defined formal model directly supporting agent-oriented modeling, this study was centered on three main topics: (1) adapting a well-known formal model, predicate transition nets (PrT nets), to support MAS modeling; (2) formulating a modeling methodology to ease the construction of formal MAS models; and (3) developing a technique to support machine analysis of formal MAS models using model checking technology. PrT nets were extended to include the notions of dynamic structure, agent communication and coordination to support agent-oriented modeling. An aspect-oriented technique was developed to address the modularity of agent models and compositionality of incremental analysis. A set of translation rules were defined to systematically translate formal MAS models to concrete models that can be verified through the model checker SPIN (Simple Promela Interpreter). ^ This dissertation presents the framework developed for modeling and analyzing MAS, including a well-defined process model based on nested PrT nets, and a comprehensive methodology to guide the construction and analysis of formal MAS models.^

Toward equity through participation in Modeling Instruction in introductory university physics

We report the results of a five year evaluation of the reform of introductory calculus-based physics by implementation of Modeling Instruction (MI) at Florida International University (FIU), a Hispanic-serving institution. MI is described in the context of FIU’s overall effort to enhance student participation in physics and science broadly. Our analysis of MI from a “participationist” perspective on learning identifies aspects of MI including conceptually based instruction, culturally sensitive instruction, and cooperative group learning, which are consistent with research on supporting equitable learning and participation by students historically under-represented in physics (i.e., Black, Hispanic, women). This study uses markers of conceptual understanding as measured by the Force Concept Inventory (FCI) and odds of success as measured by the ratio of students completing introductory physics and earning a passing grade (i.e., C− or better) by students historically under-represented in physics to reflect equity and participation in introductory physics. FCI pre and post scores for students in MI are compared with lecture-format taught students. Modeling Instruction students outperform students taught in lecture-format classes on post instruction FCI (61.9% vs 47.9%, p

Modeling instruction: Positive attitudinal shifts in introductory physics measured with CLASS

Among the most surprising findings in Physics Education Research is the lack of positive results on attitudinal measures, such as Colorado Learning Attitudes about Science Survey (CLASS) and Maryland Physics Expectations Survey (MPEX). The uniformity with which physics teaching manages to negatively shift attitudes toward physics learning is striking. Strategies which have been shown to improve conceptual learning, such as interactive engagement and studio-format classes, provide more authentic science experiences for students; yet do not seem to be sufficient to produce positive attitudinal results. Florida International University’s Physics Education Research Group has implemented Modeling Instruction in University Physics classes as part of an overall effort toward building a research and learning community. Modeling Instruction is explicitly designed to engage students in scientific practices that include model building, validation, and revision. Results from a preinstruction/postinstruction CLASS measurement show attitudinal improvements through both semesters of an introductory physics sequence, as well as over the entire two-course sequence. In this Brief Report, we report positive shifts from the CLASS in one section of a modeling-based introductory physics sequence, for both mechanics (N=22) and electricity and magnetism (N=23). Using the CLASS results and follow up interviews, we examine how these results reflect on modeling instruction and the unique student community and population at FIU.

Multilingualism and conceptual modelling

One of the leading motivations behind the multilingual semantic web is to make resources accessible digitally in an online global multilingual context. Consequently, it is fundamental for knowledge bases to find a way to manage multilingualism and thus be equipped with those procedures for its conceptual modelling. In this context, the goal of this paper is to discuss how common-sense knowledge and cultural knowledge are modelled in a multilingual framework. More particularly, multilingualism and conceptual modelling are dealt with from the perspective of FunGramKB, a lexico-conceptual knowledge base for natural language understanding. This project argues for a clear division between the lexical and the conceptual dimensions of knowledge. Moreover, the conceptual layer is organized into three modules, which result from a strong commitment towards capturing semantic knowledge (Ontology), procedural knowledge (Cognicon) and episodic knowledge (Onomasticon). Cultural mismatches are discussed and formally represented at the three conceptual levels of FunGramKB.

Geological realism in hydrogeological and geophysical inverse modeling: A review

Scientific curiosity, exploration of georesources and environmental concerns are pushing the geoscientific research community toward subsurface investigations of ever-increasing complexity. This review explores various approaches to formulate and solve inverse problems in ways that effectively integrate geological concepts with geophysical and hydrogeological data. Modern geostatistical simulation algorithms can produce multiple subsurface realizations that are in agreement with conceptual geological models and statistical rock physics can be used to map these realizations into physical properties that are sensed by the geophysical or hydrogeological data. The inverse problem consists of finding one or an ensemble of such subsurface realizations that are in agreement with the data. The most general inversion frameworks are presently often computationally intractable when applied to large-scale problems and it is necessary to better understand the implications of simplifying (1) the conceptual geological model (e.g., using model compression); (2) the physical forward problem (e.g., using proxy models); and (3) the algorithm used to solve the inverse problem (e.g., Markov chain Monte Carlo or local optimization methods) to reach practical and robust solutions given today's computer resources and knowledge. We also highlight the need to not only use geophysical and hydrogeological data for parameter estimation purposes, but also to use them to falsify or corroborate alternative geological scenarios.

Layered Information Modeling and a Knowledge Organization Paradigm: Inherent Classification and the Design of Interoperable Systems

In knowledge technology work, as expressed by the scope of this conference, there are a number of communities, each uncovering new methods, theories, and practices. The Library and Information Science (LIS) community is one such community. This community, through tradition and innovation, theories and practice, organizes knowledge and develops knowledge technologies formed by iterative research hewn to the values of equal access and discovery for all. The Information Modeling community is another contributor to knowledge technologies. It concerns itself with the construction of symbolic models that capture the meaning of information and organize it in ways that are computer-based, but human understandable. A recent paper that examines certain assumptions in information modeling builds a bridge between these two communities, offering a forum for a discussion on common aims from a common perspective. In a June 2000 article, Parsons and Wand separate classes from instances in information modeling in order to free instances from what they call the “tyranny” of classes. They attribute a number of problems in information modeling to inherent classification – or the disregard for the fact that instances can be conceptualized independent of any class assignment. By faceting instances from classes, Parsons and Wand strike a sonorous chord with classification theory as understood in LIS. In the practice community and in the publications of LIS, faceted classification has shifted the paradigm of knowledge organization theory in the twentieth century. Here, with the proposal of inherent classification and the resulting layered information modeling, a clear line joins both the LIS classification theory community and the information modeling community. Both communities have their eyes turned toward networked resource discovery, and with this conceptual conjunction a new paradigmatic conversation can take place. Parsons and Wand propose that the layered information model can facilitate schema integration, schema evolution, and interoperability. These three spheres in information modeling have their own connotation, but are not distant from the aims of classification research in LIS. In this new conceptual conjunction, established by Parsons and Ward, information modeling through the layered information model, can expand the horizons of classification theory beyond LIS, promoting a cross-fertilization of ideas on the interoperability of subject access tools like classification schemes, thesauri, taxonomies, and ontologies. This paper examines the common ground between the layered information model and faceted classification, establishing a vocabulary and outlining some common principles. It then turns to the issue of schema and the horizons of conventional classification and the differences between Information Modeling and Library and Information Science. Finally, a framework is proposed that deploys an interpretation of the layered information modeling approach in a knowledge technologies context. In order to design subject access systems that will integrate, evolve and interoperate in a networked environment, knowledge organization specialists must consider a semantic class independence like Parsons and Wand propose for information modeling.

Graded Meshes In Bio-thermal Problems With Transmission-line Modeling Method.

In this study, the transmission-line modeling (TLM) applied to bio-thermal problems was improved by incorporating several novel computational techniques, which include application of graded meshes which resulted in 9 times faster in computational time and uses only a fraction (16%) of the computational resources used by regular meshes in analyzing heat flow through heterogeneous media. Graded meshes, unlike regular meshes, allow heat sources to be modeled in all segments of the mesh. A new boundary condition that considers thermal properties and thus resulting in a more realistic modeling of complex problems is introduced. Also, a new way of calculating an error parameter is introduced. The calculated temperatures between nodes were compared against the results obtained from the literature and agreed within less than 1% difference. It is reasonable, therefore, to conclude that the improved TLM model described herein has great potential in heat transfer of biological systems.

Variability Modeling Of Rainfall, Deforestation, And Incidence Of American Tegumentary Leishmaniasis In Orán, Argentina, 1985-2007.

American tegumentary leishmaniasis (ATL) is a disease transmitted to humans by the female sandflies of the genus Lutzomyia. Several factors are involved in the disease transmission cycle. In this work only rainfall and deforestation were considered to assess the variability in the incidence of ATL. In order to reach this goal, monthly recorded data of the incidence of ATL in Orán, Salta, Argentina, were used, in the period 1985-2007. The square root of the relative incidence of ATL and the corresponding variance were formulated as time series, and these data were smoothed by moving averages of 12 and 24 months, respectively. The same procedure was applied to the rainfall data. Typical months, which are April, August, and December, were found and allowed us to describe the dynamical behavior of ATL outbreaks. These results were tested at 95% confidence level. We concluded that the variability of rainfall would not be enough to justify the epidemic outbreaks of ATL in the period 1997-2000, but it consistently explains the situation observed in the years 2002 and 2004. Deforestation activities occurred in this region could explain epidemic peaks observed in both years and also during the entire time of observation except in 2005-2007.

Modeling The Effects Of Temperature And Ph On The Resistance Of Alicyclobacillus Acidoterrestris In Conventional Heat-treated Fruit Beverages Through A Meta-analysis Approach.

In this work, all publicly-accessible published findings on Alicyclobacillus acidoterrestris heat resistance in fruit beverages as affected by temperature and pH were compiled. Then, study characteristics (protocols, fruit and variety, °Brix, pH, temperature, heating medium, culture medium, inactivation method, strains, etc.) were extracted from the primary studies, and some of them incorporated to a meta-analysis mixed-effects linear model based on the basic Bigelow equation describing the heat resistance parameters of this bacterium. The model estimated mean D* values (time needed for one log reduction at a temperature of 95 °C and a pH of 3.5) of Alicyclobacillus in beverages of different fruits, two different concentration types, with and without bacteriocins, and with and without clarification. The zT (temperature change needed to cause one log reduction in D-values) estimated by the meta-analysis model were compared to those ('observed' zT values) reported in the primary studies, and in all cases they were within the confidence intervals of the model. The model was capable of predicting the heat resistance parameters of Alicyclobacillus in fruit beverages beyond the types available in the meta-analytical data. It is expected that the compilation of the thermal resistance of Alicyclobacillus in fruit beverages, carried out in this study, will be of utility to food quality managers in the determination or validation of the lethality of their current heat treatment processes.

Supercritical CO2 recovery of caffeine from green coffee oil: new experimental solubility data and modeling

The caffeine solubility in supercritical CO2 was studied by assessing the effects of pressure and temperature on the extraction of green coffee oil (GCO). The Peng-Robinson¹ equation of state was used to correlate the solubility of caffeine with a thermodynamic model and two mixing rules were evaluated: the classical mixing rule of van der Waals with two adjustable parameters (PR-VDW) and a density dependent one, proposed by Mohamed and Holder² with two (PR-MH, two parameters adjusted to the attractive term) and three (PR-MH3 two parameters adjusted to the attractive and one to the repulsive term) adjustable parameters. The best results were obtained with the mixing rule of Mohamed and Holder² with three parameters.

Spatial pattern detection modeling of thrips (Thrips tabaci) on onion fields

Onion (Allium cepa) is one of the most cultivated and consumed vegetables in Brazil and its importance is due to the large laborforce involved. One of the main pests that affect this crop is the Onion Thrips (Thrips tabaci), but the spatial distribution of this insect, although important, has not been considered in crop management recommendations, experimental planning or sampling procedures. Our purpose here is to consider statistical tools to detect and model spatial patterns of the occurrence of the onion thrips. In order to characterize the spatial distribution pattern of the Onion Thrips a survey was carried out to record the number of insects in each development phase on onion plant leaves, on different dates and sample locations, in four rural properties with neighboring farms under different infestation levels and planting methods. The Mantel randomization test proved to be a useful tool to test for spatial correlation which, when detected, was described by a mixed spatial Poisson model with a geostatistical random component and parameters allowing for a characterization of the spatial pattern, as well as the production of prediction maps of susceptibility to levels of infestation throughout the area.

Enzyme kinetics, structural analysis and molecular modeling studies on a series of Schistosoma mansoni PNP inhibitors

The enzyme purine nucleoside phosphorylase from Schistosoma mansoni (SmPNP) is an attractive molecular target for the development of novel drugs against schistosomiasis, a neglected tropical disease that affects about 200 million people worldwide. In the present work, enzyme kinetic studies were carried out in order to determine the potency and mechanism of inhibition of a series of SmPNP inhibitors. In addition to the biochemical investigations, crystallographic and molecular modeling studies revealed important molecular features for binding affinity towards the target enzyme, leading to the development of structure-activity relationships (SAR).

Structural and chemical basis for anticancer activity of a series of 'beta'-tubulin ligands: molecular modeling and 3D QSAR studies

An important approach to cancer therapy is the design of small molecule modulators that interfere with microtubule dynamics through their specific binding to the ²-subunit of tubulin. In the present work, comparative molecular field analysis (CoMFA) studies were conducted on a series of discodermolide analogs with antimitotic properties. Significant correlation coefficients were obtained (CoMFA(i), q² =0.68, r²=0.94; CoMFA(ii), q² = 0.63, r²= 0.91), indicating the good internal and external consistency of the models generated using two independent structural alignment strategies. The models were externally validated employing a test set, and the predicted values were in good agreement with the experimental results. The final QSAR models and the 3D contour maps provided important insights into the chemical and structural basis involved in the molecular recognition process of this family of discodermolide analogs, and should be useful for the design of new specific ²-tubulin modulators with potent anticancer activity.