Proposta de método para avaliação do desempenho térmico de residências unifamiliares em clima quente e úmido

Nowadays, evaluation methods to measure thermal performance of buildings have been developed in order to improve thermal comfort in buildings and reduce the use of energy with active cooling and heating systems. However, in developed countries, the criteria used in rating systems to asses the thermal and energy performance of buildings have demonstrated some limitations when applied to naturally ventilated building in tropical climates. The present research has as its main objective to propose a method to evaluate the thermal performance of low-rise residential buildings in warm humid climates, through computational simulation. The method was developed in order to conceive a suitable rating system for the athermal performance assessment of such buildings using as criteria the indoor air temperature and a thermal comfort adaptive model. The research made use of the software VisualDOE 4.1 in two simulations runs of a base case modeled for two basic types of occupancies: living room and bedroom. In the first simulation run, sensitive analyses were made to identify the variables with the higher impact over the cases´ thermal performance. Besides that, the results also allowed the formulation of design recommendations to warm humid climates toward an improvement on the thermal performance of residential building in similar situations. The results of the second simulation run was used to identify the named Thermal Performance Spectrum (TPS) of both occupancies types, which reflect the variations on the thermal performance considering the local climate, building typology, chosen construction material and studied occupancies. This analysis generates an index named IDTR Thermal Performance Resultant Index, which was configured as a thermal performance rating system. It correlates the thermal performance with the number of hours that the indoor air temperature was on each of the six thermal comfort bands pre-defined that received weights to measure the discomfort intensity. The use of this rating system showed to be appropriated when used in one of the simulated cases, presenting advantages in relation to other evaluation methods and becoming a tool for the understanding of building thermal behavior

Simulação computacional como ferramenta de auxílio ao projeto: aplicação em edifícios naturalmente ventilados no clima de Natal/RN

Natural air ventilation is the most import passive strategy to provide thermal comfort in hot and humid climates and a significant low energy strategy. However, the natural ventilated building requires more attention with the architectural design than a conventional building with air conditioning systems, and the results are less reliable. Therefore, this thesis focuses on softwares and methods to predict the natural ventilation performance from the point of view of the architect, with limited resource and knowledge of fluid mechanics. A typical prefabricated building was modelled due to its simplified geometry, low cost and occurrence at the local campus. Firstly, the study emphasized the use of computational fluid dynamics (CFD) software, to simulate the air flow outside and inside the building. A series of approaches were developed to make the simulations possible, compromising the results fidelity. Secondly, the results of CFD simulations were used as the input of an energy tool, to simulate the thermal performance under different rates of air renew. Thirdly, the results of temperature were assessed in terms of thermal comfort. Complementary simulations were carried out to detail the analyses. The results show the potentialities of these tools. However the discussions concerning the simplifications of the approaches, the limitations of the tools and the level of knowledge of the average architect are the major contribution of this study

Otimização dos parâmetros de maquinagem no processo de fresagem

Cada vez mais, os principais objetivos na indústria é a produção a baixo custo, com a máxima qualidade e com o tempo de fabrico o mais curto possível. Para atingir esta meta, a indústria recorre, frequentemente, às máquinas de comando numérico (CNC), uma vez que com esta tecnologia torna se capaz alcançar uma elevada precisão e um tempo de processamento mais baixo. As máquinas ferramentas CNC podem ser aplicadas em diferentes processos de maquinagem, tais como: torneamento, fresagem, furação, entre outros. De todos estes processos, o mais utilizado é a fresagem devido à sua versatilidade. Utiliza-se normalmente este processo para maquinar materiais metálicos como é o caso do aço e dos ferros fundidos. Neste trabalho, são analisados os efeitos da variação de quatro parâmetros no processo de fresagem (velocidade de corte, velocidade de avanço, penetração radial e penetração axial), individualmente e a interação entre alguns deles, na variação da rugosidade num aço endurecido (aço 12738). Para essa análise são utilizados dois métodos de otimização: o método de Taguchi e o método das superfícies. O primeiro método foi utilizado para diminuir o número de combinações possíveis e, consequentemente, o número de ensaios a realizar é denominado por método de Taguchi. O método das superfícies ou método das superfícies de resposta (RSM) foi utilizado com o intuito de comparar os resultados obtidos com o método de Taguchi, de acordo com alguns trabalhos referidos na bibliografia especializada, o RSM converge mais rapidamente para um valor ótimo. O método de Taguchi é muito conhecido no setor industrial onde é utilizado para o controlo de qualidade. Apresenta conceitos interessantes, tais como robustez e perda de qualidade, sendo bastante útil para identificar variações do sistema de produção, durante o processo industrial, quantificando a variação e permitindo eliminar os fatores indesejáveis. Com este método foi vi construída uma matriz ortogonal L16 e para cada parâmetro foram definidos dois níveis diferentes e realizados dezasseis ensaios. Após cada ensaio, faz-se a medição superficial da rugosidade da peça. Com base nos resultados obtidos das medições da rugosidade é feito um tratamento estatístico dos dados através da análise de variância (Anova) a fim de determinar a influência de cada um dos parâmetros na rugosidade superficial. Verificou-se que a rugosidade mínima medida foi de 1,05m. Neste estudo foi também determinada a contribuição de cada um dos parâmetros de maquinagem e a sua interação. A análise dos valores de “F-ratio” (Anova) revela que os fatores mais importantes são a profundidade de corte radial e da interação entre profundidade de corte radial e profundidade de corte axial para minimizar a rugosidade da superfície. Estes têm contribuições de cerca de 30% e 24%, respetivamente. Numa segunda etapa este mesmo estudo foi realizado pelo método das superfícies, a fim de comparar os resultados por estes dois métodos e verificar qual o melhor método de otimização para minimizar a rugosidade. A metodologia das superfícies de resposta é baseada num conjunto de técnicas matemáticas e estatísticas úteis para modelar e analisar problemas em que a resposta de interesse é influenciada por diversas variáveis e cujo objetivo é otimizar essa resposta. Para este método apenas foram realizados cinco ensaios, ao contrário de Taguchi, uma vez que apenas em cinco ensaios consegue-se valores de rugosidade mais baixos do que a média da rugosidade no método de Taguchi. O valor mais baixo por este método foi de 1,03μm. Assim, conclui-se que RSM é um método de otimização mais adequado do que Taguchi para os ensaios realizados. Foram obtidos melhores resultados num menor número de ensaios, o que implica menos desgaste da ferramenta, menor tempo de processamento e uma redução significativa do material utilizado.

Sparse time-frequency data analysis : a multi-scale approach

In this work, we further extend the recently developed adaptive data analysis method, the Sparse Time-Frequency Representation (STFR) method. This method is based on the assumption that many physical signals inherently contain AM-FM representations. We propose a sparse optimization method to extract the AM-FM representations of such signals. We prove the convergence of the method for periodic signals under certain assumptions and provide practical algorithms specifically for the non-periodic STFR, which extends the method to tackle problems that former STFR methods could not handle, including stability to noise and non-periodic data analysis. This is a significant improvement since many adaptive and non-adaptive signal processing methods are not fully capable of handling non-periodic signals. Moreover, we propose a new STFR algorithm to study intrawave signals with strong frequency modulation and analyze the convergence of this new algorithm for periodic signals. Such signals have previously remained a bottleneck for all signal processing methods. Furthermore, we propose a modified version of STFR that facilitates the extraction of intrawaves that have overlaping frequency content. We show that the STFR methods can be applied to the realm of dynamical systems and cardiovascular signals. In particular, we present a simplified and modified version of the STFR algorithm that is potentially useful for the diagnosis of some cardiovascular diseases. We further explain some preliminary work on the nature of Intrinsic Mode Functions (IMFs) and how they can have different representations in different phase coordinates. This analysis shows that the uncertainty principle is fundamental to all oscillating signals.

Proposta de método para avaliação do desempenho térmico de residências unifamiliares em clima quente e úmido

Nowadays, evaluation methods to measure thermal performance of buildings have been developed in order to improve thermal comfort in buildings and reduce the use of energy with active cooling and heating systems. However, in developed countries, the criteria used in rating systems to asses the thermal and energy performance of buildings have demonstrated some limitations when applied to naturally ventilated building in tropical climates. The present research has as its main objective to propose a method to evaluate the thermal performance of low-rise residential buildings in warm humid climates, through computational simulation. The method was developed in order to conceive a suitable rating system for the athermal performance assessment of such buildings using as criteria the indoor air temperature and a thermal comfort adaptive model. The research made use of the software VisualDOE 4.1 in two simulations runs of a base case modeled for two basic types of occupancies: living room and bedroom. In the first simulation run, sensitive analyses were made to identify the variables with the higher impact over the cases´ thermal performance. Besides that, the results also allowed the formulation of design recommendations to warm humid climates toward an improvement on the thermal performance of residential building in similar situations. The results of the second simulation run was used to identify the named Thermal Performance Spectrum (TPS) of both occupancies types, which reflect the variations on the thermal performance considering the local climate, building typology, chosen construction material and studied occupancies. This analysis generates an index named IDTR Thermal Performance Resultant Index, which was configured as a thermal performance rating system. It correlates the thermal performance with the number of hours that the indoor air temperature was on each of the six thermal comfort bands pre-defined that received weights to measure the discomfort intensity. The use of this rating system showed to be appropriated when used in one of the simulated cases, presenting advantages in relation to other evaluation methods and becoming a tool for the understanding of building thermal behavior

Development of Planning And Evaluation Models For Superstreets

Despite the extensive implementation of Superstreets on congested arterials, reliable methodologies for such designs remain unavailable. The purpose of this research is to fill the information gap by offering reliable tools to assist traffic professionals in the design of Superstreets with and without signal control. The entire tool developed in this thesis consists of three models. The first model is used to determine the minimum U-turn offset length for an Un-signalized Superstreet, given the arterial headway distribution of the traffic flows and the distribution of critical gaps among drivers. The second model is designed to estimate the queue size and its variation on each critical link in a signalized Superstreet, based on the given signal plan and the range of observed volumes. Recognizing that the operational performance of a Superstreet cannot be achieved without an effective signal plan, the third model is developed to produce a signal optimization method that can generate progression offsets for heavy arterial flows moving into and out of such an intersection design.

Simulação computacional como ferramenta de auxílio ao projeto: aplicação em edifícios naturalmente ventilados no clima de Natal/RN

Natural air ventilation is the most import passive strategy to provide thermal comfort in hot and humid climates and a significant low energy strategy. However, the natural ventilated building requires more attention with the architectural design than a conventional building with air conditioning systems, and the results are less reliable. Therefore, this thesis focuses on softwares and methods to predict the natural ventilation performance from the point of view of the architect, with limited resource and knowledge of fluid mechanics. A typical prefabricated building was modelled due to its simplified geometry, low cost and occurrence at the local campus. Firstly, the study emphasized the use of computational fluid dynamics (CFD) software, to simulate the air flow outside and inside the building. A series of approaches were developed to make the simulations possible, compromising the results fidelity. Secondly, the results of CFD simulations were used as the input of an energy tool, to simulate the thermal performance under different rates of air renew. Thirdly, the results of temperature were assessed in terms of thermal comfort. Complementary simulations were carried out to detail the analyses. The results show the potentialities of these tools. However the discussions concerning the simplifications of the approaches, the limitations of the tools and the level of knowledge of the average architect are the major contribution of this study

Interrelated product design activities sequencing with efficient tabu search algorithms

This paper proposes and investigates a metaheuristic tabu search algorithm (TSA) that generates optimal or near optimal solutions sequences for the feedback length minimization problem (FLMP) associated to a design structure matrix (DSM). The FLMP is a non-linear combinatorial optimization problem, belonging to the NP-hard class, and therefore finding an exact optimal solution is very hard and time consuming, especially on medium and large problem instances. First, we introduce the subject and provide a review of the related literature and problem definitions. Using the tabu search method (TSM) paradigm, this paper presents a new tabu search algorithm that generates optimal or sub-optimal solutions for the feedback length minimization problem, using two different neighborhoods based on swaps of two activities and shifting an activity to a different position. Furthermore, this paper includes numerical results for analyzing the performance of the proposed TSA and for fixing the proper values of its parameters. Then we compare our results on benchmarked problems with those already published in the literature. We conclude that the proposed tabu search algorithm is very promising because it outperforms the existing methods, and because no other tabu search method for the FLMP is reported in the literature. The proposed tabu search algorithm applied to the process layer of the multidimensional design structure matrices proves to be a key optimization method for an optimal product development.

SYSTEM DYNAMICS MODELING AS A QUANTITATIVE-QUALITATIVE FRAMEWORK FOR SUSTAINABLE WATER RESOURCES MANAGEMENT: INSIGHTS FOR WATER QUALITY POLICY IN THE GREAT LAKES REGION

Early water resources modeling efforts were aimed mostly at representing hydrologic processes, but the need for interdisciplinary studies has led to increasing complexity and integration of environmental, social, and economic functions. The gradual shift from merely employing engineering-based simulation models to applying more holistic frameworks is an indicator of promising changes in the traditional paradigm for the application of water resources models, supporting more sustainable management decisions. This dissertation contributes to application of a quantitative-qualitative framework for sustainable water resources management using system dynamics simulation, as well as environmental systems analysis techniques to provide insights for water quality management in the Great Lakes basin. The traditional linear thinking paradigm lacks the mental and organizational framework for sustainable development trajectories, and may lead to quick-fix solutions that fail to address key drivers of water resources problems. To facilitate holistic analysis of water resources systems, systems thinking seeks to understand interactions among the subsystems. System dynamics provides a suitable framework for operationalizing systems thinking and its application to water resources problems by offering useful qualitative tools such as causal loop diagrams (CLD), stock-and-flow diagrams (SFD), and system archetypes. The approach provides a high-level quantitative-qualitative modeling framework for "big-picture" understanding of water resources systems, stakeholder participation, policy analysis, and strategic decision making. While quantitative modeling using extensive computer simulations and optimization is still very important and needed for policy screening, qualitative system dynamics models can improve understanding of general trends and the root causes of problems, and thus promote sustainable water resources decision making. Within the system dynamics framework, a growth and underinvestment (G&U) system archetype governing Lake Allegan's eutrophication problem was hypothesized to explain the system's problematic behavior and identify policy leverage points for mitigation. A system dynamics simulation model was developed to characterize the lake's recovery from its hypereutrophic state and assess a number of proposed total maximum daily load (TMDL) reduction policies, including phosphorus load reductions from point sources (PS) and non-point sources (NPS). It was shown that, for a TMDL plan to be effective, it should be considered a component of a continuous sustainability process, which considers the functionality of dynamic feedback relationships between socio-economic growth, land use change, and environmental conditions. Furthermore, a high-level simulation-optimization framework was developed to guide watershed scale BMP implementation in the Kalamazoo watershed. Agricultural BMPs should be given priority in the watershed in order to facilitate cost-efficient attainment of the Lake Allegan's TP concentration target. However, without adequate support policies, agricultural BMP implementation may adversely affect the agricultural producers. Results from a case study of the Maumee River basin show that coordinated BMP implementation across upstream and downstream watersheds can significantly improve cost efficiency of TP load abatement.

Development of an innovative non rule-based energy management strategy for a Hybrid Electric Vehicle, structured for predictive driving controls based on external information knowledge

Recently, the interest of the automotive market for hybrid vehicles has increased due to the more restrictive pollutants emissions legislation and to the necessity of decreasing the fossil fuel consumption, since such solution allows a consistent improvement of the vehicle global efficiency. The term hybridization regards the energy flow in the powertrain of a vehicle: a standard vehicle has, usually, only one energy source and one energy tank; instead, a hybrid vehicle has at least two energy sources. In most cases, the prime mover is an internal combustion engine (ICE) while the auxiliary energy source can be mechanical, electrical, pneumatic or hydraulic. It is expected from the control unit of a hybrid vehicle the use of the ICE in high efficiency working zones and to shut it down when it is more convenient, while using the EMG at partial loads and as a fast torque response during transients. However, the battery state of charge may represent a limitation for such a strategy. That’s the reason why, in most cases, energy management strategies are based on the State Of Charge, or SOC, control. Several studies have been conducted on this topic and many different approaches have been illustrated. The purpose of this dissertation is to develop an online (usable on-board) control strategy in which the operating modes are defined using an instantaneous optimization method that minimizes the equivalent fuel consumption of a hybrid electric vehicle. The equivalent fuel consumption is calculated by taking into account the total energy used by the hybrid powertrain during the propulsion phases. The first section presents the hybrid vehicles characteristics. The second chapter describes the global model, with a particular focus on the energy management strategies usable for the supervisory control of such a powertrain. The third chapter shows the performance of the implemented controller on a NEDC cycle compared with the one obtained with the original control strategy.

Interrelated product design activities sequencing with efficient tabu search algorithms

This paper proposes and investigates a metaheuristic tabu search algorithm (TSA) that generates optimal or near optimal solutions sequences for the feedback length minimization problem (FLMP) associated to a design structure matrix (DSM). The FLMP is a non-linear combinatorial optimization problem, belonging to the NP-hard class, and therefore finding an exact optimal solution is very hard and time consuming, especially on medium and large problem instances. First, we introduce the subject and provide a review of the related literature and problem definitions. Using the tabu search method (TSM) paradigm, this paper presents a new tabu search algorithm that generates optimal or sub-optimal solutions for the feedback length minimization problem, using two different neighborhoods based on swaps of two activities and shifting an activity to a different position. Furthermore, this paper includes numerical results for analyzing the performance of the proposed TSA and for fixing the proper values of its parameters. Then we compare our results on benchmarked problems with those already published in the literature. We conclude that the proposed tabu search algorithm is very promising because it outperforms the existing methods, and because no other tabu search method for the FLMP is reported in the literature. The proposed tabu search algorithm applied to the process layer of the multidimensional design structure matrices proves to be a key optimization method for an optimal product development.

The conjugate gradient partitioned block frequency-domain for multichannel adaptive filtering

The conjugate gradient is the most popular optimization method for solving large systems of linear equations. In a system identification problem, for example, where very large impulse response is involved, it is necessary to apply a particular strategy which diminishes the delay, while improving the convergence time. In this paper we propose a new scheme which combines frequency-domain adaptive filtering with a conjugate gradient technique in order to solve a high order multichannel adaptive filter, while being delayless and guaranteeing a very short convergence time.

Gyrokinetic modelling of plasma transport and investigation on test particle dynamics

Turbulent plasmas inside tokamaks are modeled and studied using guiding center theory, applied to charged test particles, in a Hamiltonian framework. The equations of motion for the guiding center dynamics, under the conditions of a constant and uniform magnetic field and turbulent electrostatic field are derived by averaging over the fast gyroangle, for the first and second order in the guiding center potential, using invertible changes of coordinates such as Lie transforms. The equations of motion are then made dimensionless, exploiting temporal and spatial periodicities of the model chosen for the electrostatic potential. They are implemented numerically in Python. Fast Fourier Transform and its inverse are used. Improvements to the original Python scripts are made, notably the introduction of a power-law curve fitting to account for anomalous diffusion, the possibility to integrate the equations in two steps to save computational time by removing trapped trajectories, and the implementation of multicolored stroboscopic plots to distinguish between trapped and untrapped guiding centers. The post-processing of the results is made in MATLAB. The values and ranges of the parameters chosen for the simulations are selected based on numerous simulations used as feedback tools. In particular, a recurring value for the threshold to detect trapped trajectories is evidenced. Effects of the Larmor radius, the amplitude of the guiding center potential and the intensity of its second order term are studied by analyzing their diffusive regimes, their stroboscopic plots and the shape of guiding center potentials. The main result is the identification of cases anomalous diffusion depending on the values of the parameters (mostly the Larmor radius). The transitions between diffusive regimes are identified. The presence of highways for the super-diffusive trajectories are unveiled. The influence of the charge on these transitions from diffusive to ballistic behaviors is analyzed.