The dissertation thesis is focused on non-transparent ventilated façade constructions, airflow in the ventilated cavity and the building envelope temperatures in relation with the different parameters of the construction and the ventilated cavity. The aim of this work is to optimize the temperature behavior of the building envelope during the summer season when the overheating is the most distinctive. The numerical and experimental methods with many different variants of façade constructions were used to investigation. The variants were compared and evaluated by the measured values of airflow speed in the ventilated cavity, temperature in the ventilated cavity and on the surfaces of constructions around the cavity. The result of the investigation is the evaluation of the influence of the airflow resistances or the reflectance of the surfaces around the ventilated cavity. Part of the thesis was formulated in relation with the project of MPPF - Multifunctional Plug & Play Facade during the internship at TU Graz. The efficiency of some parts of the energy active façade in this project depends on the temperature. The part of the results is the patented passive system for ventilation of building envelope and the patented cavity panel for ventilated facades.

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Traditional HPC scientific workloads are tightly coupled, while emerging scientific workflows exhibit even more complex patterns, consisting of multiple characteristically different stages that may be IO-intensive, compute-intensive, or memory-intensive. New high-performance computer systems are evolving to adapt to these new requirements and are motivated by the need for performance and efficiency in resource usage. On the other hand, cloud workloads are loosely coupled, and their systems have matured technologies under different constraints from HPC. In this thesis, the use of cloud technologies designed for loosely coupled dynamic and elastic workloads is explored, repurposed, and examined in the landscape of HPC in three major parts. The first part deals with the deployment of HPC workloads in cloud-native environments through the use of containers and analyses the feasibility and trade-offs of elastic scaling. The second part relates to the use of workflow management systems in HPC workflows; in particular, a molecular docking workflow executed through Airflow is discussed. Finally, object storage systems, a cost-effective and scalable solution widely used in the cloud, and their usage in HPC applications through MPI I/O are discussed in the third part of this thesis. / Framväxande vetenskapliga applikationer är mycket datatunga och starkt kopplade. Nya högpresterande datorsystem anpassar sig till dessa nya krav och motiveras av behovet av prestanda och effektivitet i resursanvändningen. Å andra sidan är moln-applikationer löst kopplade och deras system har mogna teknologier som utvecklats under andra begränsningar än HPC. I den här avhandlingen diskuteras användningen av moln-teknologier som har mognat under löst kopplade applikationer i HPC-landskapet i tre huvuddelar. Den första delen handlar om implementeringen av HPC-applikationer i molnmiljöer genom användning av containrar och analyserar genomförbarheten och avvägningarna av elastisk skalning. Den andra delen handlar om användningen av arbetsflödeshanteringsystem i HPC-arbetsflöden; särskilt diskuteras ett molekylär dockningsarbetsflöde som utförs genom Airflow. Objektlagringssystem och deras användning inom HPC, tillsammans med ett gränssnitt mellan S3-standard och MPI I/O, diskuteras i den tredje delen av denna avhandling / <p>QC 20231122</p>

Computational Fluid Dynamics (CFD) has emerged as an indispensable tool in various engineering fields, particularly in the design and optimization of HVAC systems in complex environments, such as engine rooms. This paper presents a comprehensive overview of CFD applications and focuses on the engine rooms of the Grange Castle Power Plant in Dublin, Ireland. Sustainable Development Capital LLP (SDCL) is constructing a state-of-the-art power plant at Grange Castle Business Park in Dublin, featuring six MAN 18V51/60DF engine generators and a total net export capacity of 111 MW. The plant uses pioneering dualfuel technology and serves as a contingency facility to stabilize the power grid amidst increasing integration of renewable energy. It functions as a responsive backup power generator and a peak load reducer, aiding the Irish government's goal of sourcing 80% of power from renewables by 2030. The initiative is part of a wider strategy including MAN Energy Solutions and Greener Ideas Limited, contributing to three new power plants in Ireland with a combined capacity of 311 MW.This study utilizes steady-state CFD simulations, employing the widely adopted k-epsilon turbulence model. Known for its robustness and computational efficiency, the k-epsilon turbulence model is utilized to analyse one engine cell at the Grange Castle Power Plant. As a two-equation model, it involves solving two additional transport equations alongside the Navier-Stokes equations to simulate fluid flow.Commonly applied in engineering applications, this model will be utilized to provide predictions of airflow and temperatures within the cell during standby and running states over the course of the year. By leveraging the strengths of the k-epsilon turbulence model, the study seeks to gain valuable insights into the complex fluid dynamics within the engine cell, ultimately helping to optimize its performance and efficiency. The analysis focused on one engine cell, with the setup and geometry for each cell being identical.Specifically, the research investigates maintaining the temperature within the cell, temperature distributions, airflow comparisons to design specifications and requirements, heating load and adequate airflow calculations, and potential benefits of optimizing the design and operation of the engine cell.The dimensions and characteristics of the engine room, along with the engines themselves and the heat they generate, play a significant role in the design process. In this study, there are several essential factors to consider, including a negative pressure ventilation system, as well as combustion and cooling air provided through air intake units that draw air from outside the engine hall and exhaust it using fans mounted on the roof. The ventilation system must be designed to maintain the room temperature within the range of 9 °C to 45°C at different points in the room. Since the engine combustion air will be drawn from inside the engine hall, the ventilation system must provide the required volumes of combustion air at all times, along with the necessary ventilation. The CFD analysis conducted in this study provides the groundwork for designing an effective ventilation system that can maintain optimal temperature conditions in the engine room. Using the simulation results, the ventilation system will be optimized to ensure the required temperature is maintained while also preventing the formation of explosive atmospheres.iiAlso, the simulation study presented in this report showcases the ability of CFD simulations to predict airflow and temperature fields in the engine room of a power plant. It is essential to understand the different scenarios' conditions to design a reliable and efficient engine room system. Furthermore, CFD simulations have proven to be an effective tool for optimizing HVAC installations to meet specific building requirements even before installing any equipment. CFD takes into account all factors influencing airflow and temperature, ensuring finely tuned designs even in confined spaces.To accurately analyse and simulate the environment, a 3D model of the engine and room is created using Inventor and AutoCAD software. However, for complex systems like the engine room, simplifying the geometry is necessary when preparing a CFD model. This is because including every detail can result in an excessive number of mesh elements, leading to longer simulation times and higher computational costs. Therefore, striking a balance between geometric complexity and computational efficiency is important for an optimal CFD model. By creating a simplified model, the CFD simulation can be more computationally efficient while still accurately capturing important flow features. The 3D model allows for seamless integration with the CFD software, enabling accurate representation of the environment for analysis.The study conducted simulations for a high-power diesel &amp; gas engine room under four different scenarios, covering various seasonal and load conditions. The results indicated that a heating coil with a 250 kW capacity is required to preheat the airflow of 25.5 m³/s by 8 °C to maintain the required temperature above 9 °C during winter. Similarly, during summer, fans with an airflow rate of 60 m³/s are necessary to keep the engine room temperature below 45 °C. This analysis is critical for designing an optimal ventilation system in engine rooms, ensuring sufficient airflow and maintaining appropriate engine temperature to prevent engine start failure. The simulation results provide invaluable information for HVAC engineers to design an efficient and reliable engine room system.Through the utilization of CFD simulations, engineers can simulate and analyse the performance of the HVAC system under various conditions, providing them with the necessary information to make well-informed decisions to ensure that the system meets the required performance criteria. Implementing CFD in the early stages of HVAC design provides valuable insights, saving engineers time and money associated with real-life testing and validation. By leveraging CFD simulations, engineers can virtually test and evaluate multiple design alternatives, ventilation strategies, and system configurations prior to actual implementation. This proactive approach helps engineers pinpoint potential issues, optimize system design for enhanced efficiency and effectiveness, and minimize the need for expensive post-installation modifications and adjustments.

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This thesis presents the design, modeling, and control of a fully-actuated multi-rotor unmanned aerial vehicle (UAV). Unlike conventional multi-rotors, which suffer from two degrees of underactuation in their propeller plane, the choice of an unconventional propeller configuration in the new drone leads to an even distribution of actuation across the entire force-torque space. This allows the vehicle to produce any arbitrary combination of forces and torques within a bounded magnitude and hence execute motion trajectories unattainable with conventional multi-rotor designs. This system, referred to as the \omninospace, decouples the position and attitude controllers, simplifying the motion control problem. Position control is achieved using a PID feedback loop with gravity compensation, while attitude control uses a cascade architecture where the inner loop follows an angular rate command set by the outer attitude control loop. A novel model is developed to capture the disturbance effects among interacting actuator airflows of the \omninospace. Given a desired actuator thrust, the model computes the required motor command using the current battery voltage and thrusts of disturbing actuators. A system identification is performed to justify the use of a linear approximation for parameters in the model to reduce its computational footprint in real-time implementation. The \omni benefits from two degrees of actuation redundancy resulting in a control allocation problem where feasible force-torques may be produced through an infinite number of actuator thrust combinations. A novel control allocation approach is formulated as a convex optimization to minimize the \omnis energy consumption subject to the propeller thrust limits. In addition to energy savings, this optimization provides fault tolerance in the scenario of a failed actuator. A functioning prototype of the \omni is built and instrumented. Experiments carried out with this prototype demonstrate the capabilities of the new drone and its control system in following various translational and rotational trajectories, some of which would not be possible with conventional multi-rotors. The proposed optimization-based control allocation helps reduce power consumption by as much as 6\%, while being able to operate the drone in the event of a propeller failure. / Thesis / Master of Applied Science (MASc)

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