The process of model generation is key to the realization of a Simulation Model Development Environment. Model generation is facilitated in the environment via the Model Generator - a software utility that assists a modeler in the development of a simulation model specification. Since modeling is inherently creative, the correct assistance provided to a modeler can neither be derived algorithmically, nor proved mathematically. Only through experimentation with prototypical assistance forms can we begin to understand the meaning of correctness. This thesis describes the development of a Model Generator prototype for the Simulation Model Development Environment. A review of the literature indicates the need for more extensive questioning of the model generation process to identify the proper foundational support than 1s available in applications designed under the program generation approach. The Conical Methodology provides the Conceptual Framework, and the Condition Specification provides the target specification form for the Model Generator prototype. A set of algorithms to derive a condition specification via a series of interactive dialogues is presented, and the results of early prototype experimentation are discussed. New questions are raised as to the role of relational attributes in the Conical Methodology and the extent and types of model analysis provided by a Model Generator. Finally, an analysis of the Model Generator as a platform for the assessment of the Conical Methodology/Condition Specification is given and directions for future research outlined. / Master of Science

In this study, a new engineering model is presented which treats the motions of a rigid body to ground shock. A rigid body is defined as one whose deformations are small compared to the deformations of the surrounding media. The new model treats non-planar normal loads on the structure, tensile cut-off constraints at the upstream and downstream faces of the structure, and shear forces on the lateral surfaces of the structure. It assumes linear elastic material properties for all materials, and collinearity between reflected and transmitted particle velocities and stresses. An important feature of the model is that it incorporates the effects of wave diffraction around the rigid body through simple bounding arguments on the conditions which prevail in the shadow zone of the structure at early-times, intermediate-times, and late-times after the wave has engulfed the rigid body. The resulting expressions are uncomplicated, and provide bounds on the structure’s motion. The model was tested against a series of linear elastic finite element calculations and was found to be accurate, and able to explain the velocity overshoot which, while not widely known, accompanies the motions of rigid bodies under certain circumstances. The model was also tested against the results of a high-explosive test in sand, and a high explosive test in a competent shale, by treating the ground motion instrument canisters on the tests as rigid bodies. Again the model was found to be accurate, and accounted for the differences observed between finite difference predictions of the flow fields and the measured canisters’ responses. The model is expected to find application in aiding in the interpretation of ground motion measurements from explosion tests, in the design of ground motion transducers, and as an aid in the vulnerability analysis of underground Structures to the effects from large explosions. / Ph. D.

Economic viability of fish production in recirculating aquaculture system (RAS) facility depends on minimizing the energy requirements of operating such facilities. The fish growth and water quality aspects of RAS have been studied in considerable details. However, the understanding of the thermal environment of RAS lags behind. A step-wise steady-state thermal model was developed to simulate the daily heating, ventilation, water pumping, biofilter operation, and lighting energy requirements over a production cycle. The model was validated using temperature and energy data collected from RAS facility of Virginia Tech during 1992. Model simulations were performed with various production scenarios. The energy cost of fish production ($/kg) was used to evaluate different scenarios with and without heat recovery from discharged system water. Building heating required the most (40 % - 70 % of total) energy followed by water pumping, biofilter operation, lighting, and ventilation. Water replacement was the most dominant factor in determining the facility’s heating energy requirement. Heat recovery from discharged system water indicated significant drop (up to 40 %) in energy cost of fish production. / Master of Science

M.S.

In recent years, the requirements engineering community has proposed a number of models for the generation of a well-formulated, complete set of requirements. However, these models are often highly abstract or narrowly focused, providing only pieces of structure and parts of guidance to the requirements generation process. Furthermore, many of the models fail to identify methods that can be employed to achieve the activity objectives. As a consequence of these problems, the requirements engineer lacks the necessary guidance to effectively apply the requirements generation process, and thus, resulting in the production of an inadequate set of requirements. To address these concerns, we propose the expanded Requirements Generation Model (x-RGM), which consists of activities at a more appropriate level of abstraction. This decomposition of the model ensures that the requirements engineer has a clear understanding of the activities involved in the requirements generation process. In addition, the objectives of all the activities defined by the x-RGM are identified and explicitly stated so that no assumptions are made about the goals of the activities involved in the generation of requirements. We also identify sets of methods that can be used during each activity to effectively achieve its objectives. The mapping of methods to activities guides the requirements engineer in selecting the appropriate techniques for a particular activity in the requirements engineering process. Furthermore, we prescribe small subsets of methods for each activity based on commonly used selection criteria such that the chosen criterion is optimized. This list of methods is created with the intention of simplifying the task of choosing methods for the activities defined by the x-RGM that best meet the selection criterion goal / Master of Science

Na engenharia de software há os modelos tradicionais e os modelos ágeis. Porém, não há um consenso sobre quais são as práticas necessárias para se obter sucesso em um projeto de engenharia de software. O presente trabalho propõe a análise do modelo SEMAT através de um estudo de caso usando esse modelo para a concepção e o levantamento de requisitos de um software para e-learning, na área de ensino de banco de dados. A partir desse estudo de caso foi possível verificar a aplicabilidade do modelo para a aplicação, além de demonstrar algumas restrições e adaptações necessárias para o uso nessa área específica. / In software engineering there are traditional and agile models. However, there is no consensus on what practices are required for a successful software engineering project. This work proposes to analyze the SEMAT model through a study case for the conception and requirements elicitation of an e-learning database education software. From this study case it was possible to verify the model applicability for the application, as well as to understand some restrictions and adjustments required for this specific area.

Na engenharia de software há os modelos tradicionais e os modelos ágeis. Porém, não há um consenso sobre quais são as práticas necessárias para se obter sucesso em um projeto de engenharia de software. O presente trabalho propõe a análise do modelo SEMAT através de um estudo de caso usando esse modelo para a concepção e o levantamento de requisitos de um software para e-learning, na área de ensino de banco de dados. A partir desse estudo de caso foi possível verificar a aplicabilidade do modelo para a aplicação, além de demonstrar algumas restrições e adaptações necessárias para o uso nessa área específica. / In software engineering there are traditional and agile models. However, there is no consensus on what practices are required for a successful software engineering project. This work proposes to analyze the SEMAT model through a study case for the conception and requirements elicitation of an e-learning database education software. From this study case it was possible to verify the model applicability for the application, as well as to understand some restrictions and adjustments required for this specific area.

Models which describe the performance of physical process are essential for quality prediction, experimental planning, process control and optimization. Engineering models developed based on the underlying physics/mechanics of the process such as analytic models or finite element models are widely used to capture the deterministic trend of the process. However, there usually exists stochastic randomness in the system which may introduce the discrepancy between physics-based model predictions and observations in reality. Alternatively, statistical models can be used to develop models to obtain predictions purely based on the data generated from the process. However, such models tend to perform poorly when predictions are made away from the observed data points. This dissertation contributes to model enhancement research by integrating physics-based model and statistical model to mitigate the individual drawbacks and provide models with better accuracy by combining the strengths of both models. The proposed model enhancement methodologies including the following two streams: (1) data-driven enhancement approach and (2) engineering-driven enhancement approach. Through these efforts, more adequate models are obtained, which leads to better performance in system forecasting, process monitoring and decision optimization. Among different data-driven enhancement approaches, Gaussian Process (GP) model provides a powerful methodology for calibrating a physical model in the presence of model uncertainties. However, if the data contain systematic experimental errors, the GP model can lead to an unnecessarily complex adjustment of the physical model. In Chapter 2, we proposed a novel enhancement procedure, named as "Minimal Adjustment", which brings the physical model closer to the data by making minimal changes to it. This is achieved by approximating the GP model by a linear regression model and then applying a simultaneous variable selection of the model and experimental bias terms. Two real examples and simulations are presented to demonstrate the advantages of the proposed approach. Different from enhancing the model based on data-driven perspective, an alternative approach is to focus on adjusting the model by incorporating the additional domain or engineering knowledge when available. This often leads to models that are very simple and easy to interpret. The concepts of engineering-driven enhancement are carried out through two applications to demonstrate the proposed methodologies. In the first application where polymer composite quality is focused, nanoparticle dispersion has been identified as a crucial factor affecting the mechanical properties. Transmission Electron Microscopy (TEM) images are commonly used to represent nanoparticle dispersion without further quantifications on its characteristics. In Chapter 3, we developed the engineering-driven nonhomogeneous Poisson random field modeling strategy to characterize nanoparticle dispersion status of nanocomposite polymer, which quantitatively represents the nanomaterial quality presented through image data. The model parameters are estimated through the Bayesian MCMC technique to overcome the challenge of limited amount of accessible data due to the time consuming sampling schemes. The second application is to calibrate the engineering-driven force models of laser-assisted micro milling (LAMM) process statistically, which facilitates a systematic understanding and optimization of targeted processes. In Chapter 4, the force prediction interval has been derived by incorporating the variability in the runout parameters as well as the variability in the measured cutting forces. The experimental results indicate that the model predicts the cutting force profile with good accuracy using a 95% confidence interval. To conclude, this dissertation is the research drawing attention to model enhancement, which has considerable impacts on modeling, design, and optimization of various processes and systems. The fundamental methodologies of model enhancement are developed and further applied to various applications. These research activities developed engineering compliant models for adequate system predictions based on observational data with complex variable relationships and uncertainty, which facilitate process planning, monitoring, and real-time control.

Early systems engineering and requirements definition requires quantitative information about potential solutions prior to having sufficient information or time to develop detailed models. This research develops and demonstrates a transparent and repeatable process for rapidly creating quantitative models that leverage existing expert knowledge. This process is built upon established modeling frameworks and current literature for low fidelity modeling and hierarchical expert-based methods. The process includes system definition using interactive morphological analysis and gathering information from subject-matter experts with computer-based interfaces in order to create a series of linear performance models. Available volunteers provided data for a relevant aerospace design to test the process as a whole and several hypotheses about specific methodological decisions made during the development. The collected data was analyzed for similarity among participants and for similarity to model parameters of an existing trusted truth model. The results of the analysis demonstrated the ability for expert-based models to accurately match the behavior of the truth models and of historical data.

Orientadores: Rubens Maciel Filho, Dailton de Freitas Rezende / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Quimica / Made available in DSpace on 2018-08-04T02:31:08Z (GMT). No. of bitstreams: 1 Custodio_AlineFerrao_M.pdf: 1962631 bytes, checksum: 51b733d6a4d5cc5f583e63880f05a9eb (MD5) Previous issue date: 2003 / Resumo: Até as duas primeiras décadas do século XX, a extração industrial de oleaginosas se fazia, exclusivamente pelo uso de prensas. As prensas, embora extraíssem um óleo de muito boa qualidade, deixavam resíduos no material sólido (torta) superiores, por exemplo a 5% para grãos como o de soja. Tais resíduos além de implicarem em perda de óleo, afetavam a qualidade da torta, que é também um dos produtos efluentes do extrator. A extração por solvente, por outro lado, é capaz de retirar o óleo, deixando resíduos inferiores a 1%. Após a extração, os sólidos são encaminhados ao dessolventizador e a micela (mistura óleo-solvente) ao sistema de destilação, composto por dois evaporadores em série e uma coluna de dessorção (stripping). A unidade de evaporação é uma das que mais demandam energia em uma planta de processamento. Assim, a modelagem matemática dinâmica deste processo com vistas à otimização do consumo energético e à avaliação do desempenho de políticas de controle torna-se um requisito decisivo para operação economicamente viável. O objetivo geral deste trabalho é desenvolver um modelo dinâmico efetuando análises de sensibilidade paramétrica para um evaporador típico da indústria de extração de óleos vegetais, visando a otimização deste processo, ou seja, a recuperação máxima de solvente e o consumo mínimo de energia. A fim de analisar as condições de operação do sistema, propôs-se um modelo matemático do sistema de evaporação com base no de TONELLI et al. (1990), consistindo em balanços mássicos global e de óleo e de balanço energético em torno do sistema de evaporação. O programa simulador foi construído em linguagem FORTRAN. Este programa, a partir de informações tais como temperatura, pressão e concentração de alimentação, assim como de quais são os componentes envolvidos, calcula propriedades termodinâmicas tais como temperaturas de ebulição, capacidades térmicas e entalpias de misturas. Desse modo, um mínimo de informações são requeridas, permitindo simulações rápidas do processo de evaporação. O programa computacional elaborado permitiu simulações rápidas e com baixos erros numéricos para o processo de evaporação do solvente em uma unidade de dessolventização do óleo após extração convencional. Este programa permitiu ainda avaliações de efeitos para os fatores influentes na evaporação. Considerando-se a intensidade das perturbações realizadas e o nível central dos fatores, o fator fração mássica de óleo na entrada foi o que apresentou o maior efeito. Já a velocidade de escoamento do vapor de água de aquecimento foi o fator com o menor efeito no teor de óleo da micela efluente / Abstract: Until the two first decades of century XX, the industrial extraction of oleaginosas were carried out exclusively by mechanical process. This process allow to extracted oil of very good quality, but it leads the left residues in the solid material (pie) to be very high, for example 5% for grains as of soy. Such residues besides implying in loss of oil, affected the quality of the pie, that is also one of the effluent products of the extractor. The extraction for solvent, on the other hand, is capable to remove the oil, leaving residues to be smaller (1%). After the extraction, the solids are directed to the dessolventizador and miscella (oil-solvent mixture) to the distillation system. Witch is composed by two evaporators in series and a stripping column. The unit of evaporation is one that demands for high energy consumption in a processing plant. Thus, the dynamic mathematical modeling of this process with sights to the reduction of the energy consumption and to the evaluation of the performance of control politics becomes a decisive requirement for economically viable operation. The general objective of this work is to develop a dynamic model of the process witch allow for parametric sensitivity analyze for a typical evaporator for the vegetal oil industry extraction. The aim is to have a tool for either process optimization or maximum recovery of solvent. The deterministic mathematical model is developed through mass and energy balance equation together with heat and mass transfer parameter correlations. The simulator was build up in FORTRAN. The software uses operational information as feed temperature, concentration and pressure witch allows for the calculation of the thermodynamic properties such as thermal temperatures of boiling, capacities and enthalpies of mixtures. In this way, a minimum of information is required, allowing fast simulations of the evaporation process. Through experimental design procedure applied to the deterministic model was possible to identify the main operational variables effects as well as the impact of the extraction array variables has on the process behaviors. The mass oil fraction in the feed was found to have the largest effect. The speed of the water vapor draining for the heating zone was the factor with the loweit effect in the oil miscella effluent / Mestrado / Desenvolvimento de Processos Químicos / Mestre em Engenharia Química