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Author: Mert Aydogmus

Supervisor: Professor Mikael Rinne

Advisor(s)/Co-supervisors: Prof. Nikolaus A. Sifferlinger, Prof. Bernd Lottermoser

Funding:- 

Abstract:

Financial analysis of earnings and expenditures in mining operations is crucial for the economic evaluation of various commodities, including non-metallic and industrial minerals. The costs associated with mining activities significantly influence the profitability and competitiveness of a company within the same sector. This research aims to identify potential optimisation strategies by conducting a comparative mining cost analysis of a company's European silica sand operations. 

Cost accounting was carried out across thirteen mining sites to categorise expenditures based on their relevance to mining implementation. Cost allocation was performed to determine unit mining costs and operational performance metrics, evaluated on a yearly basis for 2023 and 2024. Three operations were identified as cost outliers in both years. Based on the economies of scale hypothesis, a simple linear regression (SLR) model was applied to investigate the relationship between unit cost and production volume. The statistically significant relationship (p < 0.01) indicated that a 1% increase in production corresponds to a 0.25% decrease in unit cost. Subsequently, a multiple linear regression (MLR) model was employed for enhanced predictive capability. The model demonstrated strong statistical significance (p < 0.0001) across multiple variables for predicting mining costs, with four operations exhibiting higher costs than expected from the regression trend. To assess internal efficiency, data envelopment analysis (DEA) was applied using mining cost as the input and profitability, productivity, and production achievement as outputs. The resulting efficiency scores identified three operations as efficiency frontiers, while another three were found to be inefficient for 2023 and 2024. The results were further compared with technical reports from industrial peers producing silica sand. This benchmarking revealed that cost estimates at three of the company’s operations were higher than those reported by several Australian and an Indian silica sand mining projects.

Based on the findings, four operations were prioritised for optimisation. Strategic optimisation plans include reducing energy consumption, optimising mine planning and pit design, evaluating automation potential, and improving fleet management. In conclusion, this research demonstrates the feasibility of identifying optimisation opportunities through comparative cost analysis.

Author: Nina Mattsson

Title of the thesis:  Development of the Process in Inframodelling through Algorithm-Assisted Design

Supervisor: Prof. Nina Raitanen

Advisor(s): DI Pieta Haukka (A-INS)

Funding: -

Abstract:

Modern infrastructure projects are based on model-based design, where infrastructures are designed and implemented using information modelling. Algorithm-assisted design has become a common method in the field in recent years, where design is based on predefined algorithms or scripts. Algorithm-assisted design enables the automation of the design process by automating regularly recurring structures, thereby enhancing and speeding up the design process. The use of algorithm-assisted design in inframodelling, especially in the creation of planning models, has been studied very little or not at all, so the purpose of this thesis was to study the possibilities of algorithm-assisted design and the use of related software in inframodelling without compromising quality assurance.

The research methods used were literature review, interviews, and case study. The literature review was divided into two parts: the first part covered inframodelling and the associated design model and planning model, as well as the transition process between them, while the second part studied algorithm-assisted design and the selected software in theory. The literature review was utilized in the formulation of interview questions and the compilation of the case study. The interviews aimed to identify potential challenges and limitations of creating planning models and algorithm-assisted design, as well as the suitability of inframodelling for algorithm-assisted design. The goal of the case study was to study how algorithm-assisted design can be utilized in different phases of the planning model process.

The interview study showed that algorithm-assisted design does not cause risks from a quality assurance perspective when models are carefully verified. Trimble Novapoint and Autodesk Civil 3D are promising options for future infrastructure modelling software. In the case study, planning model process charts were created, illustrating the phases of both algorithm-assisted and manual execution. These charts can be utilized in the future to develop various road and street project planning processes. Algorithm-assisted design still requires development, especially in road, street, and roadway design, but by combining algorithm-assisted and manual modelling, the efficiency and accuracy of the process can be improved. Future development should focus on developing algorithms suitable for inframodelling and training personnel.

Author: Bhupendra Basnet 

Supervisor: Prof. Wojchiech Solowski 

Advisor(s): Dr Jouko Lehtonen and  MSc Antti Perälä

Abstract: 

The increasing demand for renewable energy has led to a growing adoption of solar panels as a sustainable power generation solution. However, in soft soil areas, designing and installing foundation systems for solar panels can be challenging due to the low bearing capacity and settlement problems. This master's thesis presents a comprehensive study on the design of various steel profiles as pile foundations for solar panels in soft soil areas, with a focus on addressing the geotechnical challenges associated with such soil conditions, particularly in Nordic countries such as Finland. The research presents the different solutions as steel pile foundation under soft soil. In addition, the study will analyze and present the spans for the superstructure under various loads. 
The research of this thesis begins with an in-depth review of the existing literature on steel pile foundations and soft soil geotechnical behaviour. The research will review existing literature on the analysis of solar footing in various loading conditions, such as wind, snow, and dead loads, and their effects. In this study, we analyze the different load requirements for solar panel footings to better understand their impact on the structural stability. The research presents the results of various foundation methods, including pile foundations that utilize different numbers of piles for different load conditions. It reviews several design methods and guide­lines for steel pile foundations in soft soil and evaluates their relevance and applicability to foundations for solar panels. 
The report presents spans for superstructure resulting from varying load (i.e., uplifting forces due to wind load) acting in soft soil foundation steel profile and checking of design criteria regarding Eurocode. Similarly, the connection detail between the pile Solar frame is checked according to Eurocode, and the Solar frame is checked according to Eurocode, and the Stand­ard detail of connection is presented. The design framework aims to determine the optimal solution by providing guidelines on pile type, pile spacing, pile embedment depth, and estima­tion of pile capacity. The proposed design framework aims to improve the reliability and sus­tainability of solar panel foundation systems in soft soil areas, facilitating the widespread adoption of renewable energy sources in such geotechnically challenging environments. 

Author:  Samuli Kiuru

Supervisor: professor Wojciech Solowski

Advisor:  DI Jyrki Pihlajamäki, KFS Finland Oy

Financing: Väylävirasto

Abstract:

Author: Matilda Lille

Supervisor: Professor Mikael Rinne

Advisor: MSc. Kalle Hollmén

Abstract

The construction of rock tunnels generates carbon dioxide emissions due to explosives, machinery, and materials used in rock reinforcement.  This study examined different possibilities to reduce the carbon footprint of reinforcement structures in rock tunnel projects. The focus was particularly on comparing different design methods for reinforcement structures in terms of their carbon footprint. Material choices and their impact on the carbon footprint was investigated in a litterature review. The thesis also contains a case study, which compares the carbon dioxide emissions and costs of tunnel reinforcement structures designed using three different design methods. The first design method used was the Q-system, which is the most common way to design rock reinforcement in tunnels in Finland currently. Additionally, Unwedge, which is a software based on key block theory, was used to calculate the reinforcement need for the tunnel.  The calculations were performed both deterministically and probabilistically. Results indicated that the Q-method leads to over-reinforcement, especially regarding shotcrete. The study suggests that more accurate calculations and design efforts can reduce both the carbon footprint and costs of a tunnel project.