The Family Thomas Foundation (Familjen Thomas forskningsstiftelse) is a foundation with the aim to fund research on sustainable concrete construction as the overarching theme. We will give a grant (50 000 SEK per thesis) for the best MSc thesis in any of the following two categories, first one focusing on design and second on material level:

1. Smart, resource-efficient design solutions which increase the competitiveness of concrete from a sustainability perspective
2. Resource-efficient concrete that reduces the concrete's climate footprint, including alternative binders and proportioning to reduce binder or clinker
   
   

Suitable MSc thesis fulfil the following criteria:

• It contributes to new knowledge within one or both of the two categories above
• It is structured and well-written
• It is examined at a university within the Nordic countries
• It is finalized during 2022-09-01 to 2023-08-31
  
  

If your MSc thesis fulfils these criteria, please ask your examiner to nominate it!

The grant amounts to 50 000 SEK per thesis.

Information to examiners:

Examiners of MSc theses at Nordic universities are welcome to nominate theses described above.

Deadline for nomination is 2023-12-01.

The nomination shall include:

• A short statement (3-5 sentences) on why the work is nominated
• A link to the finalized MSc thesis
• Contact details to the students
  
  

Please submit your nomination by an email to information@familythomasfoundation.se

THE WINNING THESIS 2022

We congratulate the authors of the thesis that has won a grant of 50 000 SEK!

Optimization of Cable Placement in Post-Tensioned Continuous Concrete Bridges
Development of Guidelines using Genetic Algorithms to Reduce Cost and Environmental Impact

⇒ Master’s Thesis in Master Program Structural Engineering and Building Technology
⇒ Authors: William Mjörnestål, Benjamin Pettersson
⇒ Examiner: Professor/Head of Division Mario Plos, Department of Architecture and Civil Engineering, Concrete Structures
⇒ Department of Architecture and Civil Engineering CHALMERS UNIVERSITY OF TECHNOLOGY Master’s Thesis ACEX30

Gothenburg, Sweden 2022

Abstract
Design of prestressed concrete bridges is a complex and iterative process and have a lot of influencing factors to consider and requirements to fulfil. Even though some attempts at recommendations, engineering practices and software exists, either computation time, efficiency in design or availability may be an issue. As there is a desire in the industry to find more cost-efficient and environmentally sustainable solutions, a need for simple and efficient guidelines in bridge design exists. The aim of this study was to compile general guidelines that can be applied to a varying set of continuous post-tensioned bridges to minimize the cost and environmental impact. The guidelines have been generated from optimization of a bridge beam with varying span length using a genetic algorithm solver. For the structural analyses, a finite element solver was implemented into the optimization script.

When comparing bridges designed with both the proposed guidelines and the conventional solution, load balancing, it was found that significant improvements in cost and notable reductions in global warming potential (GWP) could be achieved with the guidelines. On average, the cost was reduced by almost 7% and the GWP by 5%for the examined cross-section. Other sections were also tested and similar trends could be observed though it was noted that the improvements were considerably smaller for bridges with a slightly wider section. A case study of the road bridge, Halvors länk, showed again that the guidelines were able to reduce the cost by 5%. Due to constraints in cross-section geometry, greater improvements could not be achieved. However, reductions of 11% in prestressing steel amount were obtained for both the original cross-section and the case study, suggesting a more efficient layout.

The study also showed that the use of genetic algorithms can be beneficial in structural design. Implementation of genetic algorithms could, however, increase the computational effort to unreasonable levels depending on the complexity of the problem. Therefore, it could be recommended to compile guidelines from the results of several optimizations utilizing genetic algorithms to be used for more generic problems. With this method, results like that of the genetic algorithm optimization could be achieved but the need for long computations is reduced.