Orientador: Antonio Carlos Luz Lisboa / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Quimica / Made available in DSpace on 2018-08-21T22:08:42Z (GMT). No. of bitstreams: 1 Melo_LilianePimentade_M.pdf: 2065230 bytes, checksum: 66e96790b65d4144223056979c84a2f7 (MD5) Previous issue date: 2013 / Resumo: O xisto é uma rocha betuminosa sedimentar rica em querogênio, a qual pode ser extraída sob a forma de óleo e gás, hidrocarbonetos com aplicação similares a dos produtos derivados do petróleo. A etapa industrial do processamento do xisto que demanda maiores investimentos é a extração da matéria orgânica da rocha por aquecimento (pirólise) em um equipamento denominado retorta, contendo o gás de pirólise. A descrição das trocas de calor entre as partículas de rocha e o gás leito de pirólise pode ser avaliada por modelos matemáticos e numéricos. Nesse contexto, a proposta do trabalho foi elaborar e solucionar um modelo matemático que descreve o gradiente térmico no interior das partículas de xisto e do gás nas fases de troca de calor dentro da retorta. Os dados para a elaboração do modelo foram obtidos na usina comercial de xisto da Petrobrás. Consideram-se as propriedades físicas da partícula, tais como calor específico, condutividade térmica e o coeficiente de transferência de calor. Verificam-se também os balanços de energia no reator. Com o resultado do modelo para o balanço térmico no reator considerando gradiente de temperatura no interior das partículas foi possível observar como ocorre a influência da temperatura do gás no perfil de temperatura da partícula / Abstract: Shale is a sedimentary rock rich in kerogen, organic complex mixture which can be extracted in the form of oil and gas. Industrial shale processing description is based models representing the heat transfer in drying, heating and pyrolysis. The extraction of organic matter from rock by heating (pyrolysis) is a great investment on industrial process. The condition of the rock particles along the retort, which occurs the extraction, can be assessed by mathematical and numerical models. In this context, the purpose of this study was to develop and solve a mathematical model that describes the thermal gradient inside the particles of shale and gas in the retort. Data for developing the model were obtained from Petrobras. It was considered the physical properties of the particle, such as specific heat, density, thermal conductivity and coefficient of heat transfer. There are also the energy balances in the reactor. Model results for the heat balance in the reactor considering temperature gradient within the particles shows the influence of the gas temperature in the temperature profile of the particle / Mestrado / Engenharia de Processos / Mestre em Engenharia Química

This thesis deals with analysis, design and implementation of database in telecommunication company. The thesis consists of existing data structures analysis, functional requirements analysis, new data structures design, data consolidation and migration into new data structures and application implementation. Primary goal is monitoring of budget.

Orientadores: Elaine Cristina Catapani Poletti, Francisco José Arnold / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Tecnologia / Made available in DSpace on 2018-08-26T21:52:10Z (GMT). No. of bitstreams: 1 Alves_LauraBeatriz_M.pdf: 609137 bytes, checksum: 0a1fee66bd832bbad382627190ace320 (MD5) Previous issue date: 2015 / Resumo: A presente pesquisa propõe um modelo de avaliação e classificação de amostras de leite cru no tocante à sua regularidade, tendo em vista que, frequentemente, são constatadas alterações em amostras do produto comprometendo sua qualidade e sua composição. Sabido que tais adulterações, além de outras consequências, têm reflexos à saúde humana, objetivou-se desenvolver uma técnica de análise do leite sem riscos e sem interferência em suas propriedades físico-químicas. Assim, através de um equipamento de ultrassom e de um sistema de apoio à decisão, avaliou-se o coeficiente de atenuação e a velocidade de propagação de ondas do produto sob diversas diluições. Tais resultados alimentaram um sistema de apoio à decisão baseado em regras fuzzy que possibilitam o desenvolvimento de um método alternativo de análise e verificação de regularidade do produto. Com isso, foi possível confirmar a eficiência da técnica ao identificar que, com a adulteração progressiva da amostra, o coeficiente de atenuação aumenta e a velocidade de propagação diminui, desde que a amostra de referência seja a de leite cru puro / Abstract: This research proposes an evaluation and classification model of samples of raw milk in regarding its regularity, taking into consideration that frequently found changes in product samples, affecting its quality and composition. Known that such adulteration, among other consequences, have an effect on human health, it was aimed to develop a technique milk analysis without risk and without interference in their physicochemical properties. Thus, through an ultrasound equipment and a system for decision support, the attenuation coefficient and the velocity of wave propagation of the product were evaluated in different dilutions. These results supplied a system of decision support based on fuzzy rules that enable the development an alternative method of analysis and product regularly check. Thus, it was possible confirm the efficiency technique to identify, with the sample progressive adulteration, the attenuation coefficient increases and the propagation speed decreases once the reference sample is a pure raw milk / Mestrado / Tecnologia e Inovação / Mestra em Tecnologia

In this workshop, participants engaged with and reflected on authentic artifacts from data modeling projects related to the solar system and to deforestation that were completed by elementary students in grade 5 (average age 11). These authentic examples were used to ground a discussion of using a data modeling approach to help elementary students make sense of and meaningful integrated use of mathematics and science concepts and tools. School-based ways of helping teachers understand this approach in order to be able to use it in their classrooms were also discussed.

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In many US homes, 15% of the energy that can be saved is hidden beneath complex mathematical calculations. Hidden energy savings can be revealed by converting mathematical calculations to data visualizations, creating a story for residents to see how they are consuming energy. Cloud-based data visualization platforms offer the ability to appropriately communicate complex building energy data to a broad set of stakeholders. Unfortunately, proprietary solutions are too expensive and open-source options lack standardization for cloud-based energy monitoring. This study aims to create a comprehensive energy dashboard display to increase residents' energy awareness of how energy is consumed throughout their homes. But before energy dashboards can be created, a content analysis of current visualization chart types used on utility bills and energy monitoring devices were discovered to see how energy data has been visualized in the energy domain. Next, a literature review was conducted to reveal other visualization chart types outside of the energy domain that could be used to visualize energy data. The content analysis results identified eight visualization chart types that are used on utility bills and energy monitoring devices. In addition, the literature review uncovered eight additional visualization chart types that have the functionality to visualize energy data. Next, the visualization chart types were combined with data modeling design techniques to create prototype energy dashboard displays to communicate energy insights to residents. Soon utility companies will begin to provide data visualizations for the majority of their customers. The insights from this study can help to inform and lead the development of commercially used data visualizations. In addition, this research can provide utility companies with a blueprint on how to share energy consumption data with customers. / Master of Science / For residents to live an energy-efficient lifestyle, they must first begin by learning about one's energy consumption behaviors in the home. Unfortunately, utility bills miss out on communicating energy insights to customers based on how the energy data appears on the utility bill. Graphs on utility bills that display aggregate monthly energy consumption do not provide enough information for residents to comprehend how energy is consumed through their homes or provide information on how to lower energy consumption. There are commercial energy consumption devices on the market such as CURB and eGauge that provide an energy dashboard display, but the visuals are too complex to draw conclusions. This study aims to create an energy dashboard display that allows residents to see how energy is consumed throughout their homes. But before energy dashboards can be created, a content analysis of current visualization chart types used on utility bills and energy monitoring devices were discovered to see how energy data has been visualized in the energy domain. Next, a literature review was conducted to reveal other visualization chart types outside of the energy domain that could be used to visualize energy data. The content analysis results identified eight chart types used of utility bills and energy monitoring devices. In addition, the literature review results uncovered eight additional chart types not used on utility bills and energy monitoring devices that have the potential to visualize energy data. Next, the identified and uncovered chart types were combined with data modeling design techniques to create example energy dashboard displays. Changing the way energy data is displayed to residents, can educate residents on how energy is consumed throughout their home. In addition, the insights from this study can provide utility companies with a model for displaying energy data to increase their customers' energy awareness. Living an energy-efficient lifestyle, first began by understanding how energy is consumed throughout one's home.

Sustainable demolition waste management is rarely practiced within the construction industry. This is mainly due to the fact that the decision-making process for sustainable demolition waste management is a very resource-demanding and time-consuming task in terms of data collection and data management. The decision-making process includes multiple analyses of possible demolition waste management alternatives from economic, environmental, and social perspectives. Such analyses require waste managers to capture and manage huge amounts of data scattered within fragmented data sources at the end-of-life of a building. The process of capturing and managing this information for the building end-of-life would be time-consuming and costly. Therefore, the waste managers are reluctant to pursue sustainable demolition waste management practices in order to prevent potential delays and incurred costs. This research identified information that is required to conduct sustainable demolition waste management analyses. The identified information was then classified based on information sources. An object-oriented data model (OODM) was proposed to allow the waste managers to more efficiently store and manage the information at the end-of-life phase. Furthermore, a sustainable demolition waste management prototype application was developed to demonstrate how the required information is captured from different sources of data, stored within OODM classes, and retrieved from the integrated database. Finally, the proposed OODM was verified in terms of its scope, flexibility, and implementability. The goal of the research is to offer a method for storing and managing end-of-life information in an efficient and effective manner to support sustainable demolition waste management decision making. To achieve the goal, this dissertation outlines the objectives of the research, the methodologies used in developing the object-oriented data model, conclusions, limitations, and potential future research work. / Ph. D.

Indoor Localization Systems (ILS), also known as Indoor Positioning Systems (IPS), has been created to determine the position of individuals and other assets inside facilities. Indoor Localization Systems have been implemented for monitoring individuals and objects in a variety of sectors. In addition, ILS could be used for energy and sustainability purposes. Energy management is a complex and important challenge in the Built Environment. The indoor localization market is expected to increase by 33.8 billion in the next 5 years based on the 2016 global survey report (Marketsandmarkets.com). Therefore, this thesis focused on exploring and investigating "depth sensors" application in detecting occupants' indoor positions to be used for smarter management of energy consumption in buildings. An interconnected passive depth-sensor-based system of occupants' positioning was investigated for human-building interaction applications. This research investigates the fundamental requirements for depth-sensing technology to detect, identify and track subjects as they move across different spaces. This depth-based approach is capable of sensing and identifying individuals by accounting for the privacy concerns of users in an indoor environment. The proposed system relies on a fixed depth sensor that detects the skeleton, measures the depth, and further extracts multiple features from the characteristics of the human body to identify them through a classifier. An example application of such a system is to capture an individuals' thermal preferences in an environment and deliver services (targeted air conditioning) accordingly while they move in the building. The outcome of this study will enable the application of cost-effective depth sensors for identification and tracking purposes in indoor environments. This research will contribute to the feasibility of accurate detection of individuals and smarter energy management using depth sensing technologies by proposing new features and creating combinations with typical biometric features. The addition of features such as the area and volume of human body surface was shown to increase the accuracy of the identification of individuals. Depth-sensing imaging could be combined with different ILS approaches and provide reliable information for service delivery in building spaces. The proposed sensing technology could enable the inference of people location and thermal preferences across different indoor spaces, as well as, sustainable operations by detecting unoccupied rooms in buildings. / Master of Science / Although Global Positioning System (GPS) has a satisfactory performance navigating outdoors, it fails in indoor environments due to the line of sight requirements. Physical obstacles such as walls, overhead floors, and roofs weaken GPS functionality in closed environments. This limitation has opened a new direction of studies, technologies, and research efforts to create indoor location sensing capabilities. In this study, we have explored the feasibility of using an indoor positioning system that seeks to detect occupants’ location and preferences accurately without raising privacy concerns. Context-aware systems were created to learn dynamics of interactions between human and buildings, examples are sensing, localizing, and distinguishing individuals. An example application is to enable a responsive air-conditioning system to adapt to personalized thermal preferences of occupants in an indoor environment as they move across spaces. To this end, we have proposed to leverage depth sensing technology, such as Microsoft Kinect sensor, that could provide information on human activities and unique skeletal attributes for identification. The proposed sensing technology could enable the inference of people location and preferences at any time and their activity levels across different indoor spaces. This system could be used for sustainable operations in buildings by detecting unoccupied rooms in buildings to save energy and reduce the cost of heating, lighting or air conditioning equipment by delivering air conditioning according to the preferences of occupants. This thesis has explored the feasibility and challenges of using depth-sensing technology for the aforementioned objectives. In doing so, we have conducted experimental studies, as well as data analyses, using different scenarios for human-environment interactions. The results have shown that we could achieve an acceptable level of accuracy in detecting individuals across different spaces for different actions.

Commercial buildings consume more than 40% of the total energy consumption in the United States. Almost 90% of these buildings are small- and medium-sized buildings that do not have a Building Energy Management (BEM) system. The reasons behind this are – lack of awareness, unavailability of inexpensive packaged solutions, and disincentive to invest in a BEM system if the tenant is not the owner. Several open source tools and technologies have emerged recently that can be used for building automation and energy management. However, none of these systems is turnkey and deployment ready. They also lack consistent and intuitive navigation, security, and performance required for a BEM system. The overall project - of which this thesis research is a part - addresses the design and implementation of an open source secure web based user platform to monitor, schedule, control, and perform functions needed for a BEM system serving small and medium-size buildings. The focus of this work are: principles of intuitive graphical user interface design, abstracting device functions into a comprehensive data model, identifying threats and vulnerabilities, and implementing a security framework for the web platform. Monitor and control solutions for devices such as load controllers and sensors are abstracted and their decentralized control strategies are proposed and implemented using an open source robust scalable user platform accessible locally and remotely. The user platform is open-source, scalable, provides role-based access, dynamic, and modular in design. The comprehensive data model includes a user management model, device model, session model, and a scheduling model. The data model is designed to be flexible, robust and can be extended for any new device type. Security risks are analyzed using a threat model to identify security goals. The proposed security framework includes user authentication, device approval, role-based access, secure information exchange protocols, and web platform security. Performance of the user interface platform is evaluated for responsiveness in different screen sizes, page response times, throughput, and the performance of client side entities. / Master of Science