| 1. |
- Alyami, Mana, et al.
(författare)
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Application of metaheuristic optimization algorithms in predicting the compressive strength of 3D-printed fiber-reinforced concrete
- 2024
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Ingår i: Developments in the Built Environment. - 2666-1659. ; 17
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Tidskriftsartikel (refereegranskat)abstract
- In recent years, the construction industry has been striving to make production faster and handle more complex architectural designs. Waste reduction, geometric freedom, lower construction costs, and speedy construction make the 3D-printed fiber-reinforced concrete (3DPFRC) alternative for future construction. However, achieving the optimum mixture composition for 3DPFRC remains a daunting task, entailing the consideration of multiple variables and necessitating an extensive trial-and-error experimental process. Therefore, this study investigated the application of different metaheuristic optimization algorithms to predict the compressive strength (CS) of 3DPFRC. A database of 299 data samples with 16 different input features was compiled from the experimental studies in the literature. Six metaheuristic algorithms, such as human felicity algorithm (HFA), differential evolution algorithm (DEA), nuclear reaction optimization (NRO), Harris hawks optimization (HHO), lightning search algorithm (LSA), and tunicate swarm algorithm (TSA) were applied to identify the optimal hyperparameter combination for the random forest (RF) model in predicting the CS of 3DPFRC. Different statistical metrics and 10-fold cross-validation were used to evaluate the accuracy of the models. The TSA-RF model exhibited superior performance compared to other models, achieving correlation (R), mean absolute error (MAE), and root mean square error (RMSE) values of 0.99, 2.10 MPa, and 3.59 MPa, respectively. The LSA-RF model also performed well, with R, MAE, and RMSE values of 0.99, 2.93 MPa, and 6.23 MPa, respectively. SHapley Additive exPlanation (SHAP) interpretability elucidates the intricate relationships between features and their effects on the CS, thereby offering invaluable insights for the performance-based mix proportion design of 3DPFRC.
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| 2. |
- Andersen, Sarah Cecilie, et al.
(författare)
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Environmental impacts of circularity in the built environment: How do system boundaries affect decision support?
- 2024
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Ingår i: Developments in the Built Environment. - 2666-1659. ; 18
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Tidskriftsartikel (refereegranskat)abstract
- Life-Cycle Assessments (LCA) have become a common tool of decision support in the built environment regarding environmental impacts. The goal of this study is to investigate the influence of different LCA approaches and system boundaries on decision support regarding circular design strategies. Three different ways of applying attributional LCA (ALCA) and one consequential LCA (CLCA) are assessed using a case study of a wooden beam with either virgin or reclaimed timber. While the conclusions are not readily scalable, the case study's results indicate that using reclaimed material is environmentally beneficial when applying ALCA. However, when applying CLCA the reclaimed material performs worse than the virgin material. This highlights the potential pitfalls of scaling up solutions based on LCA results without considering the broader consequences. While the current ALCA approach is useful for declarations, it may not provide comprehensive decision support for driving a transition in the built environment.
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| 3. |
- Bäcklund, Katarina, 1982-, et al.
(författare)
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Implementing digital innovations : Overcoming organizational challenges
- 2024
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Ingår i: Developments in the Built Environment. - : Elsevier BV. - 2666-1659. ; 18
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Tidskriftsartikel (refereegranskat)abstract
- While real estate owners play a significant role in advancing digitalization and sustainability within the sector, there's limited understanding of their innovation processes. This article aims to increase understanding on the innovation processes and dynamic capabilities in real estate owner organizations. The article examines a longitudinal case study within a prominent Swedish real estate owner known for significant investments in smart building technologies. Despite these investments, practical benefits face hurdles, reflecting broader challenges in real estate sector digitalization projects. These obstacles include top-down innovation focus, limited cross-functional and user-centric innovation, innovation process discontinuities, ambiguous innovator roles, hierarchical communication, resource constraints, and uncertainties in technology implementation. The study emphasizes the inclusion of diverse perspectives in innovation processes and suggests further research on organizational and user-centric aspects. It contributes to real estate and facility management literature by proposing potential solutions to innovation processes, offering valuable insights for industry practitioners and researchers alike.
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| 4. |
- Johansson, Lisen, et al.
(författare)
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A comprehensive review on properties of tailings-based low-carbon concrete: Mechanical, environmental, and toxicological performances
- 2024
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Ingår i: Developments in the Built Environment. - : Elsevier. - 2666-1659. ; 18
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Tidskriftsartikel (refereegranskat)abstract
- With concrete’s key role in construction and infrastructure, the reduction of its carbon footprint is critical for addressing global carbon emissions. One strategy to reduce environmental impact from concrete production is to replace cement clinker or fine aggregates in concrete with industrial wastes. Mine tailings, being a high-volume under-utilized resource, possess properties making it suitable for use as a partial substitute for cement or fine aggregates. This review article provides an overview of the recent findings within the topic of tailings-based concrete (TBC). Many of the identified publications aimed to describe the mechanical performance of TBC, and to optimize the concrete mix with respect to the strength and durability. The recommended cement replacement ranged from 5 to 25% and the recommended fine aggregate replacement ranged from 20 to 60%. In general, the compressive strength was decreased with increasing use of tailings as a replacement of cement. For the use of tailings as replacement for fine aggregates, the correlation was more complex, normally the mechanical performance enhanced at low replacement levels, until it reached an optimum after which it decreased. CO2 savings for replacing fine aggregate with tailings were up to 12% and for the cement replacement up to 30%. When assessing the environmental performance, most of the publications did not account for the loss of its mechanical performance, which could lead to the risk of underestimating the environmental impact. This review not only provides a basis for understanding the mechanical, toxicological, and environmental performances of TBCs, but also links the perspectives together, unveiling the connections between them. Moreover, this review presents an organized overview of the topic of TBC and points out topics for future research.
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| 5. |
- Najeh, Taoufik, et al.
(författare)
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Forecasting maximum formwork pressure for self-compacting concrete using ARX-Laguerre machine learning model
- 2024
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Ingår i: Developments in the Built Environment. - : Elsevier. - 2666-1659. ; 18
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Tidskriftsartikel (refereegranskat)abstract
- Forecasting the maximum pressure exerted by cast-in-place self-compacting concrete (SCC) is a major concern for formwork designers, researchers, and site engineers to accurately design the bearing capacity of the formwork and control the casting rate for safe and fast construction. This article aims to utilize the ARX-Laguerre model, which is a data-driven model to forecast the maximum form pressure. A laboratory instrumented setup was used to cast a 2-m column using SCC made with two different types of cement. A pressure system consisting of four sensors was used to document the pressure during casting. The data were sent to the cloud at every 1-min interval for real-time monitoring. The data were used to develop the model. The results demonstrated that forecasting with the ARX-Laguerre model is highly accurate. The model can forecast the maximum pressure exerted by SCC with less complexity. The model performance was also found to be consistent with insignificant differences between actual experimental results and predicted results. With a recursive and straightforward representation, the resulting model, known as the ARX-Laguerre model, ensures the parameter number reduction. Providing fast prediction of the maximum pressure. The model enables formwork designers to forecast the form pressure to design safe formwork and also helps to control the casting rate when SCC is used.
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| 6. |
- Wang, Dong, et al.
(författare)
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Comparing the efficacy of GEP and MEP algorithms in predicting concrete strength incorporating waste eggshell and waste glass powder
- 2024
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Ingår i: Developments in the Built Environment. - : Elsevier Ltd. - 2666-1659. ; 17
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Tidskriftsartikel (refereegranskat)abstract
- The present study used the techniques of gene expression programming (GEP) and multi-expression programming (MEP) to assess the compressive strength (CS) and flexural strength (FS) and develop predictive models of sustainable mortar modified with waste eggshell powder (WEP) and waste glass powder (WGP) as a replacement of cement. In order to get more insights into the impact and relation of raw components on the CS and FS of a developed sustainable mortar, a comprehensive study using the SHapley Additive exPlanations (SHAP) methodology was performed. When comparing the efficiency of both employed models, it was seen that the MEP model exhibited superior performance with an R2 value of 0.871 and 0.894 for CS and FS, as compared to the GEP model, which had an R2 value of 0.842 and 0.845 for CS and FS respectively.
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