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Use of Neural Networks for the Stiffness Calculation of a Spur Gear Transmission
Planka, Michal ; Krpalek, David (referee) ; Lošák, Petr (advisor)
The aim of this master's thesis is to build artificial neural network that is able to calculate varying single tooth-pair mesh stiffness of spur gear for given input parameters. The training set for this network was determined by computational modelling by finite element method. Therefore, creating of computational model and mesh stiffness calculating were a partial aim of this thesis. Input parameters for stiffness calculation were number of driving and driven gear teeth and gear loading. Creating of computational model and performing series of simulations was followed by creating artificial neural network. Multilayer neural network with backpropagation training was chosen as a type of the network. Created neural network is sufficiently efficient and can determine varying mesh stiffness in input set range for learned input parameters and for values of parameters that are not included in training set as well. This neural network can be used for varying single tooth-pair mesh stiffness estimation in input set range.
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Determination of HVAC air distribution within a passenger vehicle cabin
Planka, Michal ; Mlkvik, Marek (referee) ; Fojtlín, Miloš (advisor)
The aim of this bachelor´s thesis is to determine proportional coefficients of air distribution provided by heating, ventilating, and air conditioning system (HVAC) within a passenger vehicle cabin. The focus of this paper is to determine air flow rates from the outlets at predefined outside climatic conditions (ambient temperature and solar load). The simulation of outside climatic conditions was executed by placing the car into a climatic chamber. The air flow rates from outlets were determined by measuring air flow velocity method, specifically by determining mean value of air flow velocity profile and area of outlet crosssection. Hot-wire anemometry was used for air flow velocity measurement. The results of this experimental work are presented in a diagrammatic form and will serve as a groundwork for boundary condition setting for computer modeling of thermal load and thermal comfort within a vehicular cabin.
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Use of Neural Networks for the Stiffness Calculation of a Spur Gear Transmission
Planka, Michal ; Krpalek, David (referee) ; Lošák, Petr (advisor)
The aim of this master's thesis is to build artificial neural network that is able to calculate varying single tooth-pair mesh stiffness of spur gear for given input parameters. The training set for this network was determined by computational modelling by finite element method. Therefore, creating of computational model and mesh stiffness calculating were a partial aim of this thesis. Input parameters for stiffness calculation were number of driving and driven gear teeth and gear loading. Creating of computational model and performing series of simulations was followed by creating artificial neural network. Multilayer neural network with backpropagation training was chosen as a type of the network. Created neural network is sufficiently efficient and can determine varying mesh stiffness in input set range for learned input parameters and for values of parameters that are not included in training set as well. This neural network can be used for varying single tooth-pair mesh stiffness estimation in input set range.
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Determination of HVAC air distribution within a passenger vehicle cabin
Planka, Michal ; Mlkvik, Marek (referee) ; Fojtlín, Miloš (advisor)
The aim of this bachelor´s thesis is to determine proportional coefficients of air distribution provided by heating, ventilating, and air conditioning system (HVAC) within a passenger vehicle cabin. The focus of this paper is to determine air flow rates from the outlets at predefined outside climatic conditions (ambient temperature and solar load). The simulation of outside climatic conditions was executed by placing the car into a climatic chamber. The air flow rates from outlets were determined by measuring air flow velocity method, specifically by determining mean value of air flow velocity profile and area of outlet crosssection. Hot-wire anemometry was used for air flow velocity measurement. The results of this experimental work are presented in a diagrammatic form and will serve as a groundwork for boundary condition setting for computer modeling of thermal load and thermal comfort within a vehicular cabin.
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