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Optimization of Turbofan Engine Performance through Blade Profile Modification

This thesis reports detailed research performed to optimize the geometries of blade rows in turbofan engines through analysis with computational fluid dynamics. The study was conducted systematically by employing theoretical analysis, along with numerical computation used to evaluate the aerodynamic performance of two different blade types. The methodology consisted of the design of blade geometries in SolidWorks, mesh generation using structured and unstructured elements, and CFD simulations on ANSYS Fluent with a focus on cascade analysis. The study commenced with the development of two designs below: Blade Design 1 having a height of 1300 mm, chord length of 294 mm at the base, and 700 mm at a height of 750 mm; Blade Design 2 at a similar height, differing only in leading edge diameters and chord lengths at different cross-sections. This enables detailed meshing such that near-wall regions and critical flow features are resolved with adequate resolution. Using a pressure-based solver, the CFD simulation was performed using the k-ω SST turbulence model, which is proper for capturing near-wall effects and handling adverse pressure gradients. Inlet velocities were considered between 1 and 40 m/s, thus analyzing performance under different operating conditions.

Author: Ajiksun Kumaradhas

Supervisor: Adham Ahmed Awad Elsayed Elmenshawy

Degree: Bachelor

Year: 2024

Work Language: English

Study programme: Aviation Engineering

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Drone manipulator optimization and integration in affordable quadcopter

This paper explores the development of a drone-attachable manipulator designed to perform construction and maintenance tasks, moving beyond the traditional use of UAVs for monitoring. Our primary objective is to design a manipulator capable of lifting objects weighing up to 300 grams, adhering to principles of low cost, ease of manufacturing, and high quality. We begin with a literature review of UAV types and their suitability for integration with manipulators. The design process involves creating multiple manipulator prototypes using Solidworks for simulations to gather data on performance and structural integrity.Static stress and displacement analyses are conducted to identify areas of high stress and potential deformation. Initial designs demonstrate that the static force required to hold a 300-gram object exceeds the capabilities of our prototypes. The final manipulator design is tested for its lifting capabilities and operational limitations. Re The study concludes with an evaluation of the design process, limitations, and potential for future applications of UAV-integrated manipulators in infrastructure construction and maintenance

Author: Arvis Maiželis

Supervisor: Adham Ahmed Awad Elsayed Elmenshawy

Degree: Bachelor

Year: 2024

Work Language: English

Study programme: Aviation Engineering

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Comparative analysis of RPL protocol objective functions impact on energy consumption in low-power and lossy networks

This bachelor thesis explores the impact of different RPL protocol objective functions on energy consumption in low-power and lossy networks. Given the critical role of low-power and lossy networks in applications like environmental monitoring, industrial automation, and smart cities, optimising energy consumption is paramount. Using the Contiki-NG operating system and the Cooja network simulator, this study conducts a comparative analysis of two primary objective functions: Objective Function Zero and Minimum Rank with Hysteresis Objective Function. Simulations are performed under 18 network scenarios including different node densities (10, 30, 50), node positioning, and receive ratios. The findings indicate that Objective Function Zero generally consumes less energy, particularly in high-density networks and environments with high packet delivery ratios. Conversely, Minimum Rank with Hysteresis Objective Function may be more suitable for dynamic and unpredictable environments despite its higher energy consumption. This research offers practical recommendations for selecting objective functions to optimise the energy consumption of constrained networks, contributing to the development of more sustainable IoT solutions.

Author: Deniss Bogdans

Supervisor: Jeļena Baranova

Degree: Bachelor

Year: 2024

Work Language: English

COMPARATIVE ANALYSIS OF LLM-BASED APPROACHES FOR SQL GENERATION

The rapid development of Large Language Models has unlocked opportunities for restructuring software development processes in general as well as in such cases as converting natural language into SQL queries. This study seeks to experimentally evaluate the effects of four LLM-based methods on the efficiency and quality of SQL generation. Evaluation is being held based on following metrics: Correctness, Completeness and Consistency. Studied LLM-based SQL generation methods include Specific LLMs tailored for SQL code generation like SQL Coder frameworks for generating SQL code (Vanna.ai, 2023; Llamaindex, 2023) and Multi agent collaborative networks for transforming language into SQL.The research utilizes a mix of literature review case studies and simulations. It offers a comprehensive review of the advancements in LLM-driven SQL generation encompassing concepts, technologies, methodologies, strengths, limitations, and ethical considerations.This research successfully bridges the gap between theoretical foundations and practical application of AI-augmented approaches while promoting the integration of LLM-based SQL generation, into automated software development processes.

Author: Maksim Ilin

Supervisor: Dmitry Pavlyuk

Degree: Master

Year: 2024

Work Language: English

Study programme: Computer Sciences

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Optimizing Product Cost in Supply Chain

Optimizing product cost through simulation modeling offers a powerful approach to enhancing cost efficiency and decision-making in product development and manufacturing. Simulation modeling allows businesses to create detailed virtual representations of their processes, enabling them to experiment with different scenarios and strategies without the risks associated with physical trials. Simulation modeling supports iterative testing and optimization, allowing for the refinement of product designs and manufacturing processes. Ultimately, this approach enhances the ability to make informed, data-driven decisions, leading to more effective cost management and improved profitability. This abstract highlights the value of simulation modeling in optimizing product cost, emphasizing its role in providing actionable insights and fostering strategic improvements.

Author: Sofiya Andryuk

Supervisor: Mihails Savrasovs

Degree: Professional Bachelor

Year: 2024

Work Language: English

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