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Efficient machine learning for strength prediction of ready-mix concrete production (prolonged mixing)
(2026-01-19)
Tuvayanond, Wiput
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Kamchoom, Viroon
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Prasittisopin, Lapyote
Purpose – This paper aims to clarify the efficient process of the machine learning algorithms implemented in the ready-mix concrete (RMC) onsite. It proposes innovative machine learning algorithms in terms of preciseness and computation time for the RMC strength prediction. Design/methodology/approach – This paper presents an investigation of five different machine learning algorithms, namely, multilinear regression, support vector regression, k-nearest neighbors, extreme gradient boosting (XGBOOST) and deep neural network (DNN), that can be used to predict the 28- and 56-day compressive strengths of nine mix designs and four mixing conditions. Two algorithms were designated for fitting the actual and predicted 28- and 56-day compressive strength data. Moreover, the 28-day compressive strength data were implemented to predict 56-day compressive strength. Findings – The efficacy of the compressive strength data was predicted by DNN and XGBOOST algorithms. The computation time of the XGBOOST algorithm was apparently faster than the DNN, offering it to be the most suitable strength prediction tool for RMC. Research limitations/implications – Since none has been practically adopted the machine learning for strength prediction for RMC, the scope of this work focuses on the commercially available algorithms. The adoption of the modified methods to fit with the RMC data should be determined thereafter. Practical implications – The selected algorithms offer efficient prediction for promoting sustainability to the RMC industries. The standard adopting such algorithms can be established, excluding the traditional labor testing. The manufacturers can implement research to introduce machine learning in the quality controcl process of their plants. Originality/value – Regarding literature review, machine learning has been assessed regarding the laboratory concrete mix design and concrete performance. A study conducted based on the on-site production and prolonged mixing parameters is lacking.
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Corrigendum to “Microplastics in construction and built environment” [Dev. Built Environ. 15 (2023) 100188] (Developments in the Built Environment (2023) 15, (S2666165923000704), (10.1016/j.dibe.2023.100188))
(2023-12-01)
Prasittisopin, Lapyote
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Ferdous, Wahid
;
Kamchoom, Viroon
The authors regret that in the original publication, the affiliation of the last author was incomplete. The correct affiliation should have been ‘Bangkok 10520, Thailand’. The authors would like to apologise for any inconvenience caused.
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Microplastics in construction and built environment
(2023-10-01)
Prasittisopin, Lapyote
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Ferdous, Wahid
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Kamchoom, Viroon
Plastics have been extensively used in the building and construction industries for decades. However, the more plastics are utilised, the more microplastics are released. This review and analysis article summarises and organises the knowledge from 211 current related publications published in 2014–2022. The review and analysis explain the kinds of plastics employed in construction and built environment. Fabrics or textiles, fibres and plastics in cementitious systems, paints, tyres and roads are discussed. The entry points of microplastics into the human body are reviewed next, followed by the management of recycled wastes. The important research gaps and possible solutions include using high-strength concretes and surface-hardening agents is suggested to encapsulate the microplastics inside the matrix; DPSIR model analysis can be holistically adopted for each composite; innovative bio-chemical technology like self-healing concrete and bio-degradable plastics can be a viable choice; and social science, law and urban planning can support awareness and comprehension.
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Investigating the Impacts of Biochar Amendment and Soil Compaction on Unsaturated Hydraulic Properties of Silty Sand
(2023-07-01)
Chen, Zhongkui
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Kamchoom, Viroon
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Chen, Rui
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Prasittisopin, Lapyote
The application of biochar as an environmentally friendly additive for agricultural soils has recently gained significant attention. However, the influence of biochar addition on unsaturated hydraulic behavior at high suction ranges (i.e., exceeding 100 kPa) remains largely understudied. This study investigates the impact of biochar addition on the unsaturated hydraulic properties of biochar amended soil (BAS). The effects of biochar content, particle size, and soil compaction on the unsaturated hydraulic properties of BAS were also considered. Peanut shell biochar was utilized in this investigation and was amended into a compacted silty sand with distinct particle size groups. Soil water retention curves and unsaturated permeability were measured through a series of evaporation tests. Results demonstrate that the impact of soil compaction on the unsaturated hydraulic properties of BAS diminishes at high suction range, regardless of biochar particle size and content. A high degree of compaction reduces the saturated permeability of BAS by minimising soil macropores. On the other hand, incorporating high biochar contents with fine particles into the soil enhances the reduction of unsaturated permeability and the improvement of water holding capacity, thereby making biochar an effective application in soil for sustainability of the agroecological environment.

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