We examine which capabilities technologies provide to support collaborative process modeling. We develop a model that explains how technology capabilities impact cognitive group processes, and how they lead to improved modeling outcomes and positive technology beliefs. We test this model through a free simulation experiment of collaborative process modelers structured around a set of modeling tasks. With our study, we provide an understanding of the process of collaborative process modeling, and detail implications for research and guidelines for the practical design of collaborative process modeling.

Made available in DSpace on 2018-08-02T00:04:06Z (GMT). No. of bitstreams: 1 tese_10529_foundations_for_ontology_based_multi_level_conceptual_modeling_2012 - victorio.pdf: 6142526 bytes, checksum: 3e3483b04f4e9b86ab648e66104ac1e2 (MD5) Previous issue date: 2016-12-16 / Considerando que modelos conceituais são produzidos com o objetivo de representar certos aspectos do mundo físico e social de acordo com uma conceituação específica e que ontologias buscam descrever conceituações, tem havido crescente interesse no uso de ontologias para fornecer uma base teórica sólida para a disciplina de modelagem conceitual. Esse interesse deu origem a uma área de pesquisa denominada modelagem conceitual baseada em ontologias, com avanços significativos na modelagem conceitual nas últimas décadas. Apesar desses avanços, a modelagem baseada em ontologias não provê suporte adequado à modelagem de domínios que exigem a representação de categorias de indivíduos e de categorias de categorias (ou tipos de tipos). A representação de entidades de vários "níveis" de classificação tem sido o foco de uma área de pesquisa distinta denominada modelagem multi-nível. As iniciativas em modelagem multi-nível visam a contornar as limitações impostas pelo paradigma convencional de modelagem em dois níveis. Apesar das contribuições relevantes das áreas de modelagem multi-nível e de modelagem conceitual baseada em ontologias, a combinação dessas duas áreas ainda não recebeu a devida atenção. Este trabalho explora essa lacuna propondo o uso combinado de teorias formais para a modelagem multi-nível e de ontologias de fundamentação para apoiar o que chamamos de modelagem conceitual multi-nível baseada em ontologias. Para fornecer uma abordagem bem fundamentada à modelagem conceitual multi-nível, desenvolvemos uma teoria chamada MLT. MLT caracteriza formalmente a natureza dos níveis de classificação e define precisamente as relações que podem ocorrer entre elementos de diferentes níveis de classificação. A fim de aproveitar os benefícios do uso de ontologias de fundamentação na modelagem de domínios que abrangem vários níveis de classificação, combinamos MLT com uma ontologia de fundamentação. Essa combinação resulta em uma abordagem de modelagem que apoia a construção de modelos conceituais multi-níveis em um espectro de níveis de especificidade, desde ontologias de fundamentação até modelos conceituas de domínios específicos. Para demonstrar a aplicabilidade da nossa abordagem de modelagem conceitual multi-nível baseada em ontologias, a empregamos para desenvolver uma ontologia núcleo para estruturas organizacionais, um domínio que abrange vários níveis de classificação. Além disso, mostramos como MLT pode ser usada como uma teoria de referência para esclarecer a semântica e aumentar a expressividade de UML no que diz respeito à representação de modelos de multi-níveis. O perfil UML produzido viabiliza a aplicação prática de MLT pela comunidade de modelagem conceitual.

Synthetic unit hydrographs, which assume uniform rainfall excess distribution and static watershed conditions, are frequently used to estimate hydrograph characteristics when observed data are unavailable. The objective of this research was to develop a spatially distributed unit hydrograph (SDUH) model that directly reflects spatial variation in the watershed in generating runoff hydrographs. The SDUH model is a time-area unit hydrograph technique that uses a geographic information system (GIS) to develop a cumulative travel time map of the watershed based on cell by cell estimates of overland and channel flow velocities. The model considers slope, land use, watershed position, channel characteristics, and rainfall excess intensity in determining flow velocities. The cumulative travel time map is divided into isochrones which are used to generate a time-area curve and the resulting unit hydrograph. Predictions of the SDUH model along with the Snyder, SCS, and Clark synthetic unit hydrographs were compared with forty observed storm events from an 1153-ha Virginia Piedmont watershed. The SDUH model predictions were comparable or slightly better than those from the other models, with the lowest relative error in the peak flow rate prediction for 12 of the 40 storms, and a model efficiency of at least 0.90 for 21 of the storms. Despite the good predictions of the hydrograph peak flow rate and shape, the time to peak was underpredicted for 34 of the 40 storms. Runoff from the 40 storms was also generated for two subwatersheds (C: 462 ha; D: 328 ha) in Owl Run to assess the effect of scale on the SDUH model. Peak flow rate predictions were more accurate for the entire watershed than for either subwatershed. The time to peak prediction and model efficiency statistics were comparable for the entire watershed and subwatershed D. Subwatershed C had poorer predictions, which were attributed to a large pond in the main channel, rather than to scale effects. The SDUH model provides a framework for predicting runoff hydrographs for ungauged watersheds that can reflect the spatially distributed nature of the rainfall-runoff process. Predictions were comparable to the other synthetic unit hydrograph techniques. Because the time to peak and model efficiency statistics were similar for the 1153-ha watershed and a 328-ha subwatershed, scale does not have a major impact on the accuracy of the SDUH model. / Master of Science

Full-motion driving simulators require efficient real-time high fidelity vehicle models in order to provide a more realistic vehicle response. Typically, multi-body models are used to represent the vehicle dynamics, but these have the unfortunate drawback of requiring the solution of a set of coupled differential algebraic equations (DAE). DAE's are not conducive to real-time implementation such as in a driving simulator, without a very expensive processing capability. The primary objective of this thesis is to show that multi-body models constructed from DAE's can be reasonably approximated with linear models using suspension elements that have nonlinear constitutive relationships. Three models were compared in this research, an experimental quarter-car test rig, a multi-body dynamics differential algebraic equation model, and a linear model with nonlinear suspension elements. Models constructed from differential algebraic equations are computationally expensive to compute and are difficult to realize for real-time simulations. Instead, a linear model with nonlinear elements was proposed for a more computationally efficient solution that would retain the nonlinearities of the suspension. Simplifications were made to the linear model with nonlinear elements to further reduce computation time for real-time simulation. The development process of each model is fully described in this thesis. Each model was excited with the same input and their outputs were compared. It was found that the linear model with nonlinear elements provides a reasonably good approximation of actual model with the differential algebraic equations. / Master of Science

The Virginia Department of Environmental Quality (VADEQ) under the direction of the United States Environmental Protection Agency (USEPA) has listed the lower Appomattox River as impaired because it violates current water quality standards for fecal coliforms. To advance the analytical process by which various scenarios for improving water quality within the estuary are examined, an array of computer-based hydrodynamic and water quality models were investigated. The Dynamic Estuary Model (DYNHYD5), developed by USEPA, was used to simulate hydrodynamics within the lower Appomattox River. The Water Quality Analysis Simulation Program (WASP6.1), also developed by USEPA, was employed to perform water quality simulations of fecal coliforms. Also, a detailed literature review examined DYNHYD5 and WASP6.1 model theory, computer-based model solution techniques, and background hydrodynamic theory. DYNHYD5 sensitivity analysis showed that the model was most responsive to tidal heights (seaward boundary conditions) both upstream and downstream within the model network. Specific model parameters were varied during calibration until modeled water surface elevations converged on observed water surface elevations. A goodness-of-fit value of 0.749 was determined with linear regression analysis for model calibration. DYNHYD5 input parameter validation was performed with additional observations and a goodness-of-fit value of 0.829 was calculated. Through sensitivity analysis, WASP6.1 proved to be most responsive to coliform loading rates in the downstream direction and boundary concentrations in the upstream direction. With these results, WASP6.1 input parameters were calibrated against observed fecal coliform concentrations. A goodness-of-fit value of 0.573 was determined with linear regression analysis for model calibration. WASP6.1 input parameter validation was performed with additional observations and a goodness-of-fit value of 0.0002 was calculated. Model results suggest that hydrodynamic model calibration and validation can be improved with additional tidal height observations at the downstream seaward boundary. Similarly, water quality model calibration and validation can possibly be improved with the aid of detailed, time-variable coliform concentrations at the downstream seaward boundary. Therefore, it is recommended that a water quality sampling station and tidal stage recorder be installed at the confluence of the Appomattox and James Rivers to provide for further testing of estuary hydrodynamic and water quality models. / Master of Science

The use of best management practices or BMPs to treat urban stormwater runoff has been pervasive for many years. Extensive research has been conducted to evaluate the performance of individual BMPs at specific locations; however, little research has been published that seeks to evaluate the impacts of small, distributed BMPs throughout a watershed at the regional level. To address this, a model is developed using EPA SWMM 5.0 for the Duck Pond watershed, which is located in Blacksburg, Virginia and encompasses much of the Virginia Polytechnic and State Institute's campus and much of the town of Blacksburg as well. A variety of BMPs are designed and placed within the model. Several variations of the model are created in order to test different aspects of BMP design and to test the BMP modeling abilities of EPA SWMM 5.0. Simulations are performed using one-hour design storms and yearlong hourly rainfall traces. From these simulations, small water quality benefits are observed at the system level. This is seen as encouraging, given that a relatively small amount of the total drainage area is controlled by BMPs and that the BMPs are not sited in optimal locations. As expected, increasing the number of BMPs in the watershed generally increases the level of treatment. The use of the half-inch rule in determining the required water quality volume is examined and found to provide reasonable results. The design storm approach to designing detention structures is also examined for a two-pond system located within the model. The pond performances are examined under continuous simulation and found to be generally adequate for the simulated rainfall conditions, although they do under-perform somewhat in comparison to the original design criteria. The usefulness of EPA SWMM 5.0 as a BMP modeling tool is called into question. Many useful features are identified, but so are many limitations. Key abilities such as infiltration from nodes or treatment in conduit flow are found to be lacking. Pollutant mass continuity issues are also encountered, making specific removal rates difficult to define. / Master of Science

Interface modeling is a critical aspect in any multi-material system modeling. Even a small change in the interface model may lead to significant changes in material behavior of the microscale, and these changes may transfer up to higher scales influencing the strain and stress fields, and damaging behavior in the macroscale material. This work focuses on the effects of different interface models in nanocomposites composed of carbon nanotubes in polymer matrix materials and their applications as nanocomposite binders in energetic materials. These material systems include materials that span multiple scales from nano to macroscale, and thus require a detailed multiscale analysis. A hierarchical multiscale framework is employed here, where the effective material properties from subscales are obtained by solving the subscale boundary value problem. The information obtained from the subscale simulations are transferred up to higher scales to be used as input properties. A nonlocal continuum mechanics framework known as peridynamics is used to perform the computational simulations. Peridynamics uses integro-differential equations for conservation laws instead of partial differential equations as in the classical continuum mechanics. This makes it possible for peridynamics to inherently account for nonlocal effects such as damage initiation, crack growth, and crack branching without any modifications such as element deletion, adaptive mesh refinement, using enrichment functions and so on, which are commonly used in other numerical methods. Peridynamics is a particle-based method where the particles are allowed to interact with other particles within their horizon which serves as a cut-off distance for forming particle-to-particle bonds and therefore defines the extent of nonlocality. Peridynamics has different formulations regarding the bond interactions. A bond-based peridynamics framework is used here. A verified and validated in-house code is used for the simulations. The simulations for the carbon nanotube and nanofiber-based nanocomposites, and for nanocomposite bonded energetic materials start from the microscale and range up to the macroscale. For only the carbon nanotube-polymer nanocomposites, the interfaces include the CNT-polymer interfaces. For the energetic materials, the interfaces consider the CNT-polymer interfaces in the microscale and the grain-nanocomposite binder interfaces in the mesoscale. Peridynamics, being a nonlocal continuum mechanics method, by default will have nonlocal interfaces. The material systems investigated in this work first use different nonlocal interfaces in peridynamics which consider the bond between two particles at the interface to be connected in series or in parallel. The nonlocal interface model in peridynamics makes it challenging to control the interface properties and leads to fuzzy interfaces, i.e. interfaces of finite thickness. In this work, a local cohesive interface model is implemented in the peridynamics framework. Cohesive zones were originally used for modeling the growth of cracks by introducing cohesive forces that hold the crack surfaces together, thereby removing the stress singularity problem in linear elastic fracture mechanics. The idea of cohesive zones are applied to peridynamics interfaces, which introduces locality into the nonlocal framework. This interface model does not only remove the nonlocality at the peridynamics interfaces, but it leads to a higher fidelity interface model that is controllable by the user. The differences between the nonlocal and local interfaces are studied in detail in different scales and for different material systems. Implementing a local model into a nonlocal framework brings some challenges, namely obtaining and calibrating the cohesive interface properties for the materials used, the numerical problems with material interpenetration in extreme compression, and very small time steps that are required to resolve the material response. Some remedies are proposed for the problems encountered. The cohesive zone model used in this work can have different functional forms in normal and tangential direction to reflect differences in opening mode and frictional sliding behaviors. / Doctor of Philosophy / Multi-material systems have interface regions where a transition from one material to another occurs. How the interface region is modeled can change the response of a material to external loads even if the interface model is slightly different. This work focuses on the effect of different interface models in nanocomposites based on carbon nanotubes and in nanocomposite bonded energetic materials. These material systems include materials that span multiple scales from nano to the macroscale, and thus require a detailed multiscale analysis. Multiscale analysis of a material means analyzing the material at each scale that is involved for the given material system separately and passing relevant information between the scales. A hierarchical multiscale framework is employed here which is based on a bottom-up approach, where the material properties are obtained at the smaller scales and passed up to the larger scales to be used as the input properties. A nonlocal continuum mechanics in the form of peridynamics is used to perform the computational simulations. The nonlocality stems from the fact that the particles can interact not only with their closest neighbors, but with other particles within their horizon, which is the cut-off distance that dictates how far a material particle can make bonds with other particles. The main advantage of peridynamics is to be able to model cracks without any a priori knowledge about crack growth directions or patterns. Peridynamics has different formulations for representing the bond interactions. A bond-based peridynamics framework is used here. A verified and validated in-house code is used for the simulations. The simulations for the carbon nanotube-polymer nanocomposites and nanocomposite bonded energetic materials take place starting from the microscale up to the macroscale. For the carbon nanotube nanocomposite scale, the interfaces include the fiber-matrix interfaces. For the nanocomposite bonded energetic materials, the interfaces considered include the fiber-matrix interfaces in the microscale and the grain-binder interfaces in the mesoscale. Peridynamics, being a nonlocal continuum mechanics method, nominally includes nonlocal interfaces. The material systems investigated in this work first use different nonlocal interfaces in peridynamics which consider the bond between two particles at the interface to be connected in series or in parallel. The nonlocal interface model in peridynamics makes it challenging to control the interface properties and leads to fuzzy, or finite thickness interfaces. A local cohesive interface model is implemented in the peridynamics framework. Cohesive zones are originally used for modeling cracks by introducing cohesive forces that hold the crack surfaces together to remove the stress singularity at the crack in classical linear elastic fracture mechanics. The idea of cohesive zones are applied to peridynamics interfaces which introduces locality into the nonlocal framework. This interface model does not only remove the nonlocality at the peridynamics interfaces, but it leads to a higher fidelity interface model that is controllable by the user. The differences between the nonlocal and local interfaces are studied in detail in different scales and for different material systems. Implementing a local model into a nonlocal framework brings some challenges, namely obtaining and calibrating the cohesive interface properties for the materials used, the numerical problems with material interpenetration in extreme compression, and very small time steps that are required to resolve the material response. Some remedies are proposed to address these issues. The cohesive zone model used in this work have different mathematical models in normal and tangential directions. It is therefore capable of modeling mechanical and thermal problems including frictional heating. The mechanical results obtained by using cohesive interfaces show potential for developing similar local interface models for thermal and electrical conduction allowing for the expanded application of the approach to multiphysics problems in multiscale composite materials.

In this thesis, the Education System Intervention Modeling Framework (ESIM Framework) is introduced for analyzing interventions in the K-12 education system. This framework is the first of its kind to model interventions in the K-12 school system in the United States. Techniques from systems engineering and operations research, such as agent-based modeling and social network analysis, are used to model the bottom-up mechanisms of intervention implementation in schools. By applying the ESIM framework, an intervention can be better analyzed in terms of the barriers and enablers to intervention implementation and sustainability. The risk of failure of future interventions is thereby reduced through improved allocation of resources towards the system agents and attributes which play key roles in the sustainability of the intervention. Increasing the sustainability of interventions in the school system improves educational outcomes in the school and increases the benefits gained from the millions of dollars being invested in such interventions. In the first part of this thesis, a case study of an Engineers Without Borders chapter is modeled which helped in the development of a more generalized framework, applicable across a broad range of education system interventions. In the second part of this thesis, the ESIM framework is developed. The framework developed is divided into four phases: model definition, model design, model analysis, and model validation. Each of these phases has detailed steps in order to build the agent-based model of the particular intervention. In the third part of this thesis, the ESIM framework is applied to a case study of a curriculum intervention, Science Learning: Integrating Design, Engineering and Robotics, involving the design and implementation of an 8th-grade, inquiry-based physical science curriculum across three demographically varying schools. This case study provides a good comparison of the implementation of the intervention across different school settings because of the varied outcomes at the three schools.

Significant uncertainty surrounds the influence of atmospheric and oceanic forcing on the fluctuations of tidewater glacier outlets of the Greenland ice sheet (GrIS), with the majority of studies focussing on dynamics over the last two decades. Although numerical model based projections exist anticipating the future dynamics of major GrIS outlets, these have been made using temporally limited model calibration periods (<5 years) compared to the centennial timescales that they seek to predict over. The ability of these numerical models to simulate the centennial timescale dynamics of GrIS tidewater glaciers has therefore not been explicitly tested. This thesis seeks to calibrate a well-established one-dimensional tidewater glacier numerical model against post-Little Ice Age maximum (LIAmax) observations of a major tidewater glacier outlet of GrIS. The study site chosen is Kangiata Nunaata Sermia (KNS); the largest tidewater outlet in SW Greenland south of Jakobshavn Isbræ. This glacier is known to have undergone retreat of >20 km since its LIAmax, though the timing of this retreat and response to climate forcing is currently poorly constrained. Utilising a range of source material, it is demonstrated that KNS is likely to have achieved its LIAmax by 1761, experiencing either one, or two multi-kilometre retreats by 1859, and retreats of a similar scale between 1921-1968, and 1997-2012. Terminus fluctuations of KNS were in phase with climate anomalies, where data were available for comparison (1871-2012). To allow accurate comparison to numerical model output, the accuracy of different methods of quantifying glacier terminus change was also evaluated. Two new methods were devised so observations could be matched with greater accuracy than existing methods allowed. Glacier sensitivity to climate forcing was evaluated using the numerical model.

Depending on the material system and machining conditions, the localized strain, strain rate and temperature fields induced to the material during the machining process can be intense. Therefore, a wide variety of microstructural evolutions are likely to occur below the machined surface. These microstructural changes take place at various scales. First of all, due to the severe plastic deformation below the machined surface, the crystallographic orientation of grains can change dramatically. In addition, if the levels of the induced temperature and strain are high enough, recrystallization may occur, new grains may form and subsequently grow. Additionally, contingent upon the duration of the machining process, partial grain growth might also happen. Last but not least, if the material is consisted of more than one phase, the microstructural characteristics of secondary phases will also evolve. The ultimate result of all the aforementioned evolutions produces remarkable changes in the mechanical and thermal (and almost all other) properties of the material, which consequently affect the response of the material during service. A comprehensive modeling framework that reliably captures all the aspects of the above microstructural evolutions in machining is absent in the open literature. This work coalesces concrete and all-inclusive modeling toolsets into a unified scheme to follow the mentioned phenomena in machining of aluminum alloy 7075. The modeling outcomes are verified by experimental results to assure reliability. Finite element analyses were applied to obtain the stress, temperature, strain and strain rate fields developed in the material during machining at different parameters. Kinetic-based models were exploited to determine the possible recrystallization or grain growth. A viscoplastic self-consistent crystal plasticity model was utilized to investigate texture evolution below the machined surface. Also for multi-phase materials, the first steps in developing a totally new constitutive model to yield the extent of the possible refinement in the second phase precipitates, were taken. The main goal of the work was to link the above-mentioned microstructural evolutions to process parameters of machining by mathematical derivation of process path functions. Therefore, prediction of microstructural changes as a result of changing the process parameters became possible; which has significant industrial potential and importance. Additionally, such a direct and complete linkage between machining and microstructure is completely new to the scientific community in manufacturing and design fields.