A parameterized model for tower crane energy consumption was developed based on theoretical formulation and field data
Abstract As tower cranes (TC) getting more use in the construction process, a reliable TC energy consumption calculation model is increasingly required for construction management. This paper proposed a semi-empirical model, which is based on the division of TC work cycle. For fitting the coefficien...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-03-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-94875-5 |
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| Summary: | Abstract As tower cranes (TC) getting more use in the construction process, a reliable TC energy consumption calculation model is increasingly required for construction management. This paper proposed a semi-empirical model, which is based on the division of TC work cycle. For fitting the coefficients, Partial Least Squares Regression (PLSR) was adopted. To simplify the model, variables with weak regression significance to energy consumption were deleted in turn. The best suitable version achieves a Mean Absolute Percentage Error of 25.55%, a Root Mean Square Error (RMSE) of 1036.19 kJ, and a Coefficient of Determination (R2) of 0.83, with just one independent variable. A comparative analysis showed the proposed model had the highest accuracy and fitting degree among all the models for TC energy consumption calculation. Through physical transformation of the proposed model, several key engineering parameters (i.e., load mass, number of work cycles, and hoisting height) affecting TC energy consumption were extracted. The innovation of this empirical study lies in confirming the feasibility of the stage-based calculation model and the small sample fitting strategy, providing new ideas of constructing and optimizing energy consumption models for other construction machinery. At the same time, the proposed model lays a foundation for research related to TC energy consumption to be more reliable. |
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| ISSN: | 2045-2322 |