This thesis deals with internal shading devices and their influence on the thermal stability of the room. Furthermore, compares the differences in the behavior of different materials. Finally, compares the measured values with the computational models.

This thesis deals the internal shielding elements and their influence on the thermal stability of the room and compares the differences in their characteristics.

This master’s thesis deals with the strain-stress analyses of the pig femoral bone in physiological and pathological condition. Pathological condition is determined by a significant defect in diaphysis of the bone fixed by using direct angular stable locking plate with screws. The thesis describes the creation of computational models with special focus on bone tissues models of material, which are based on analysis of digital images from computed tomography (CT). There are created and analyzed three types of computational models: the first one corresponds to physiological condition of femur, the second one to femur with significant defect and fixation plate and the third one to femur with significant defect, fixation plate and rod. Every model is loaded in three ways: the first of them simulating the experimental conditions of pressure testing of the femur, the second one bone stress in the sagittal plane and the third one stress by using load determined from probational release of the pig hind limb. Strain-stress states are determined by finite element method using Ansys computational system. Gained results of stress and strain are compared with experimental measurements. The thesis presents a basic idea of the mechanical behavior of porcine femur and porcine femur with significant bone defect.

Master's thesis focuses on the simulation engine transients. The model of single-cylinder engine was constructed in simulation software Lotus Engine Simulation. Then was made simulation of transients. The thesis try to describe the influence of moment of inertia of the engine, the engine starting speed and process of throttle opening during the transients. For all modes also compare two methods of fuel control.

The subject of this thesis is the computational model of existing KWH boiler. There is a short research in the introduction, which deals with combustion heat of considered boiler.  The stoichiometric and balance calculations of gasification chamber ZKG are performed first. The Balance calculations are based on the boiler thermal loss calculations, the losses were determined experimentally. The entire calculation is processed in a computational program for purposses of debugging and manipulation with partial calculations. The computational model that is proposed in this thesis provide better boiler proces understandig. The real boiler measurement is performed for evaluation. The next point is the result analyses, that shows potential boiler efficiency improvements.

The goal of this model is to create and to implement qualitative model of the signal track of olfactory sensory neuron, including the feedback with a focus on diffusion of substances that allows to conduct more simulations for the better understanding of dynamics of the signal track. This model is expected to be used for the simulation of influencing during the activation of two receptors in firstly defined distance. Model was created and therefore implemented in a programming language Python with the use of library STEPS. Then I have conducted sensitivity analysis by a method Morris OAT on the model, together with an optimization with the usage of change of individual parameters with a great importance on the output of the model. Model is conducting good and biologically comparable results when there are from 10 to 100 active receptors at the beginning of the track. Unfortunately with a lower numbers, the results are not valid and therefore not to be used for the simulation of influencing of two activated receptors. Despite this is a main benefit of the work the model of signal transduction for the whole signal track with an included feedback and emphasis on diffusion. Another benefit is a set of scripts for the sensitivity analysis by a method Morris OAT and optimization.

Plasma turbulence associated with the creation of an artificial dust layer in the earth's ionosphere is investigated. The Charged Aerosol Release Experiment (CARE) aims to understand the mechanisms for enhanced radar scatter from plasma irregularities embedded in dusty plasmas in space. Plasma irregularities embedded in a artificial dusty plasma in space may shed light on understanding the mechanism for enhanced radar scatter in Noctilucent Clouds (NLCs) and Polar Mesospheric Summer Echoes (PMSEs) in the earth's mesosphere. Artificially created, charged-particulate layers also have strong impact on radar scatter as well as radio signal propagation in communication and surveillance systems. The sounding rocket experiment was designed to develop theories of radar scatter from artificially created plasma turbulence in charged dust particle environment. Understanding plasma irregularities embedded in a artificial dusty plasma in space will also contribute to addressing possible effects of combustion products in rocket/space shuttle exhaust in the ionosphere. In dusty space plasmas, plasma irregularities and instabilities can be generated during active dust aerosol release experiments. Small scale irregularities (several tens of centimeter to meters) and low frequency waves (in the ion/dust scale time in the order of second) are studied in this work, which can be measured by High Frequency (HF), Very High Frequency (VHF) and Ultra High Frequency (UHF) radars. The existence of dust aerosol particles makes computational modeling of plasma irregularities extremely challenging not only because of multiple spatial and temporal scale issue but also due to complexity of dust aerosol particles. This work will provide theoretical and computational models to study plasma irregularities driven by dust aerosol release for the purpose of designing future experiments with combined ground radar, optical and in-situ measurement. In accordance with linear analysis, feasible hybrid computational models are developed to study nonlinear evolution of plasma instabilities in artificially created dusty space plasmas. First of all, the ion acoustic (IA) instability and dust acoustic (DA) instability in homogenous unmagnetized plasmas are investigated by a computational model using a Boltzmann electron assumption. Such acoustic-type instabilities are attributed to the charged dust and ion streaming along the geomagnetic field. Secondly, in a homogenous magnetized dusty plasma, lower-hybrid (LH) streaming instability will be generated by dust streaming perpendicular to the background geomagnetic field. The magnetic field effect on lower-hybrid streaming instabilities is investigated by including the ratio of electron plasma frequency and electron gyro frequency in this model. The instability in weakly magnetized circumstances agree well with that for the ion acoustic (IA) instability by a Boltzmann model. Finally, in an inhomogeneous unmagnetized/magnetized dust boundary layer, possible instabilities will be addressed, including dust acoustic (DA) wave due to flow along the boundary and lower-hybrid (LH) sheared instability due to flow cross the boundary. With applications to active rocket experiments, plasma irregularity features in a linear/nonlinear saturated stage are characterized and predicted. Important parameters of the dust aerosol clouds that impact the evolution of waves will be also discussed for upcoming dust payload generator design. These computational models, with the advantage of following nonlinear wave-particle interaction, could be used for space dusty plasmas as well as laboratory dusty plasmas. / Ph. D.

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Categorization is a complex decision-making process that requires observers to collect information about stimuli using their senses. While research on visual or auditory categorization is extensive, there has been little attention given to tactile categorization. Here we developed a paradigm for studying tactile categorization using 3D-printed objects. Furthermore, we derived a categorization model using Bayesian inference and tested its performance against human participants in our categorization task. This model accurately predicted participant performance in our task but consistently outperformed them, even after extending the learning period for our participants. Through theoretical exploration and simulations, we demonstrated that the presence of sensory measurement noise could account for this performance gap, which we determined was a present factor in participants undergoing our task through a follow-up experiment. Including measurement noise led to a better-fitting model that was able to match the performance of our participants much more closely. Overall, the work in this thesis provides evidence for the efficacy of a tactile categorization experimental paradigm, demonstrates that a Bayesian model is a good fit and predictor for human categorization performance, and underscores the importance of accounting for sensory measurement noise in categorization models. / Dissertation / Doctor of Philosophy (PhD) / The process of categorization is an essential part of our daily life as we encounter various things in the world. Here we explore a model that attempts to explain this process. This model is derived using Bayesian inference and was applied to human behavioural data in a categorization task. We found that the model accounted for most of the performance of our participants but consistently outperformed them. We conducted simulations to explore and demonstrate that this difference is primarily due to the presence of sensory noise in participants. Once we accounted for this noise, we found that our model predicted human performance even more accurately. The work in this thesis demonstrates that a Bayesian Categorization Model which accounts for sensory noise is a good fit and predictor for human performance on categorization tasks.

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