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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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Use of Artificial Intelligence in Human Resource Management

The integration of Artificial Intelligence into Human Resource Management processes presents an evolving domain of exploration and practical application. The widespread adoption of AI technologies presents the potential for significant transformations in products, innovation processes and business models. The research aim is to develop a framework for effective use of AI in Human Resource Management. The subject of the research is AI-based solutions in Human Resource Management. The object of the research is Human Resource Management processes in an enterprise.A multifaceted research approach was used to scrutinize the effective utilization of AI in HRM: Literature review, Case Studies, Employee Surveys, Interviews with HR experts.During this research, the author highlighted aspects of contemporary HRM that can be improved using AI technologies; made a list of the recommended practices for integrating AI-based solutions into HRM; developed a framework for AI tools implementation and found out that HR experts’ and employees’ overall perspective on AI within HRM appears optimistic.This research holds both theoretical and practical significance, driving advancements in theoretical knowledge, informing organizational practices, and shaping the future of work in the digital age.

Author: Ana Enache

Supervisor: Yulia Stukalina

Degree: Master

Year: 2024

Work Language: English

Study programme: Business and Management

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Development of Decision Support Tool for Transport Forwarding Company Operating within Netherlands and Italy

This paper investigates the development of a decision support tool for a Latvian transportation company operating in the Dutch and Italian markets. Models and algorithms for optimizing freight routes using Excel and Python are included. Digitalization of logistics processes is recognized as a key to improve efficiency and reduce costs. Two methods for solving the traveling salesman problem were examined and compared: Excel with Solver and Python with the NetworkX library.The methodology involved collecting data from Google My Maps, creating Excel spreadsheets, and developing Python software to automate route optimization. The results showed that both methods improved route planning, reducing time and cost, as well as reducing carbon footprint.The study emphasizes the importance of integrating technologies such as machine learning and big data into logistics to increase flexibility and adaptability. Recommendations were offered to further improve and implement these technologies for sustainable business development and increased competitiveness in international markets.

Author: Anastasija Škaduna

Supervisor: Berdymyrat Ovezmyradov

Degree: Professional Bachelor

Year: 2024

Work Language: English

Estimating Generalised Transport Costs of Road Freight Transportation in the Baltic Sea Region

This problem of estimating road transport costs in the Baltic Sea region is important for optimising cargo delivery expenses in local transportation and manufacturing sectors. The study incorporates a wider range of economic and logistical factors beyond the usual metrics of physical distance and travel time by using Generalised Transport Costs (GTC). Important factors like geodesic and road distances, travel times, fuel consumption, labor costs, tolls, and other overheads are identified. We utilise a unique dataset that analyses trips between centroids within each NUTS-2 region.The study confirms the GTC model by comparing calculated costs with established database values. Regression analysis uncovers key factors affecting transport costs, such as road distance, travel time, and tolls.Network analysis is used to map the routes in the region, focusing on finding paths that are both cost-effective and time-efficient. The analysis shows how small changes in routes can have a big impact on costs and efficiency.In conclusion, this thesis contributes to the knowledge of road freight transport costs in the Baltic Sea region, offering valuable insights for policymakers and logistics companies.

Author: Angelīna Ņekļudova

Supervisor: Francesco Maria Turno

Degree: Professional Bachelor

Year: 2024

Work Language: English

Factors affecting customer loyalty in the logistics service
industry

In this study the author conducted a survey among 68 employees of different companies, 31 of them representing logistics companies and 37 employees of companies that are users of these services in order to analyze the obtained data using the PLS-SEM method and to identify the key factors affecting the formation of customer loyalty. Based on the identified factors the author proposes a concept of measures to increase customer loyalty of small road freight transportation companies in Latvia.Chapter 1 provides theoretical information on the process of selecting a logistics service provider and a description of the factors used in this process. The basics of the creation of customer loyalty and measures to increase it were also considered.Chapter 2 includes the analysis of the freight transportation market in Latvia, analysis of logistics companies in Latvia and analysis of the data obtained from the survey.Chapter 3 contains a statistical model showing the most important factors affecting customer loyalty of logistic companies. Based on the statistical model, a concept of measures to increase customer loyalty of small logistics companies is proposed.

Author: Artūrs Emīls Zelčs

Supervisor: Jeļena Popova

Degree: Bachelor

Year: 2024

Work Language: English

Study programme: Business and Management

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