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Start date: 2024Subject: search.filters.subject.Compressive strength

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Now showing 1 - 5 of 5
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    PublicationOpen Access
    Sustainable Alternatives to Clay Bricks: A Review on PET-Based Masonry Units for Green Construction
    (Ontario International Development Agency, 2026) Wijesundara H; Perera S.V.T.J
    The rapid escalation of global plastic consumption, particularly polyethylene terephthalate (PET), has created severe environmental challenges, while the conventional clay brick industry continues to generate significant greenhouse gas emissions and deplete nonrenewable resources. This paper reviews existing literature on two sustainable construction approaches aimed at addressing these dual issues: (i) the incorporation of melted PET in masonry blocks and (ii) the embedding of sand-filled PET bottles in masonry units. Findings indicate that melted PET-sand composite bricks, particularly at an optimal 1:3 plastic-to-sand ratio, exhibit superior performance compared to conventional clay bricks. These composites achieve compressive strength improvements of over 44% and reduce water absorption by up to 94.93%. They also demonstrate enhanced durability, with less than 2% strength loss under acid exposure, compared to over 15% in traditional bricks. Additionally, their production requires 79% less energy and reduces CO₂ emissions by a similar margin, underscoring their environmental advantages. The review also highlights the effectiveness of sand-filled PET bottles as structural masonry elements. Sand is a superior filler since it can hold up to 38.34 N/mm² of pressure, which is far more than bottles filled with dirt (8.99 N/mm²) or plastic bags (2.72 N/mm²). The review shows that both melted PET-sand bricks and sand-filled PET bottle masonry are good, eco-friendly substitutes for regular clay bricks. These methods have two benefits: they reduce plastic waste and encourage building techniques that are good for the environment. The results give an excellent justification to use PET-based masonry technologies as we shift toward building materials that are better for the environment.
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    PublicationEmbargo
    Uniaxial compressive response of cement mortar with waste aluminium fibre sourced from electrical distribution cables
    (Springer Science and Business Media, 2025-01) Perera K.D.Y.G.; Ahamed Y.L.F; Somarathna H.M.C.C; Jayasekara D.A.B.P.M; Mohotti D; Raman S.N
    Electrical distribution and communication cables cease to function for transmission when their length is insufficient, and it is considered as it approaches the end of their useful lives. Further, the disposal techniques are not eco-friendly. This study aimed to evaluate the feasibility of cement mortar systems with the inclusion of aluminium fibre extracted from electrical distribution cables. Two diameters of 1.35 mm and 1.70 mm and two lengths of 10 mm and 15 mm fibres were used while incorporating four volume ratios, particularly 0.5%, 1.0%, 1.5%, and 2.0% to evaluate the effect of the length, diameter and volume ratios. The compression test and density test were performed to study the behaviour of Metal Fibre Reinforced Mortar (MFRM) systems under both dry and wet states. Compared to conventional mortar, the ultimate compressive strength of MFRM systems was increased up to 39.4% in 1.5% of fibre addition under the 28-day dry state, where the 1.5% volume ratio showed the best performance under compressive loads. Strain at ultimate strength, modulus of elasticity and strain energy also showed improvements with the fibre inclusion up to 74.4%, 87.3%, and 106.6% respectively. Fibres with higher aspect ratios showed significant effectiveness among the aforementioned fibre variations. The overall results highlighted that the MFRM with 1.5% of fibres performed expertly with 15 mm length and 1.35 mm diameter under compression loads
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    PublicationEmbargo
    Mechanical and durability analysis of eco-friendly light weight cement blocks using raw rice husk as a partial replacement for manufactured sand
    (Elsevier Ltd, 2025-03-08) Thavarajah, L; Sundaralingam, K; Tharmarajah, G
    The study investigates the mechanical and durability properties of cement blocks made by partially replacing manufactured sand (M-sand) with raw rice husk (RRH). The rising demand for sand in construction, coupled with the environmental impact of its extraction, has prompted the exploration of alternative materials. RRH, a byproduct of rice milling, offers an eco-friendly substitute for sand. The research examines blocks containing varying proportions of RRH (20 %, 40 %, and 60 %) and compares treated and untreated husks. Key parameters, including compressive strength, tensile strength, density, performance when exposed to heat, and water absorption, were analyzed. The results show that up to 40 % of RRH can be used to replace sand without compromising the blocks' structural integrity. Treated RRH blocks demonstrated better bonding with cement, leading to higher compressive and tensile strengths compared to untreated ones. A 40 % RRH replacement achieved an average compressive strength of 3.57 MPa, surpassing the minimum requirements for non-load-bearing masonry units as per Sri Lankan and Australian standards. However, increasing RRH content to 60 % significantly reduced strength and durability. Additionally, RRH blocks exhibited a decrease in density, offering advantages in terms of transportation and handling. Water absorption increased with higher RRH content due to its porous nature yet remained within acceptable limits for treated blocks. These findings suggest that RRH can be a sustainable alternative to sand in masonry applications, especially in rural and eco-conscious construction.
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    PublicationOpen Access
    Eco-friendly mix design of slag-ash-based geopolymer concrete using explainable deep learning
    (Elsevier, 2024-09) Ranasinghe, R.S.S.; Kulasooriya, W.K.V.J.B; Perera, U.S; Ekanayake, I.U.; Meddage, D.P.P.; Mohotti, D; Rathanayake, U
    Geopolymer concrete is a sustainable and eco-friendly substitute for traditional OPC (Ordinary Portland Cement) based concrete, as it reduces greenhouse gas emissions. With various supplementary cementitious materials, the compressive strength of geopolymer concrete should be accurately predicted. Recent studies have applied deep learning techniques to predict the compressive strength of geopolymer concrete yet its hidden decision-making criteria diminish the end-users’ trust in predictions. To bridge this gap, the authors first developed three deep learning models: an artificial neural network (ANN), a deep neural network (DNN), and a 1D convolution neural network (CNN) to predict the compressive strength of slag ash-based geopolymer concrete. The performance indices for accuracy revealed that the DNN model outperforms the other two models. Subsequently, Shapley additive explanations (SHAP) were used to explain the best-performed deep learning model, DNN, and its compressive strength predictions. SHAP exhibited how the importance of each feature and its relationship contributes to the compressive strength prediction of the DNN model. Finally, the authors developed a novel DNN-based open-source software interface to predict the mix design proportions for a given target compressive strength (using inverse modeling technique) for slag ash-based geopolymer concrete. Additionally, the software calculates the Global Warming Potential (kg CO2 equivalent) for each mix design to select the mix designs with low greenhouse emissions.
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    PublicationOpen Access
    Eco-friendly mix design of slag-ash-based geopolymer concrete using explainable deep learning
    (Elsevier, 2024-09) Ranasinghe, R.S.S.; Kulasooriya, W.K.V.J.B.; Perera, U S; Ekanayake, I.U.; Meddage, D.P.P.; Mohotti, D; Rathanayake, U
    Geopolymer concrete is a sustainable and eco-friendly substitute for traditional OPC (Ordinary Portland Cement) based concrete, as it reduces greenhouse gas emissions. With various supplementary cementitious materials, the compressive strength of geopolymer concrete should be accurately predicted. Recent studies have applied deep learning techniques to predict the compressive strength of geopolymer concrete yet its hidden decision-making criteria diminish the end-users’ trust in predictions. To bridge this gap, the authors first developed three deep learning models: an artificial neural network (ANN), a deep neural network (DNN), and a 1D convolution neural network (CNN) to predict the compressive strength of slag ash-based geopolymer concrete. The performance indices for accuracy revealed that the DNN model outperforms the other two models. Subsequently, Shapley additive explanations (SHAP) were used to explain the best-performed deep learning model, DNN, and its compressive strength predictions. SHAP exhibited how the importance of each feature and its relationship contributes to the compressive strength prediction of the DNN model. Finally, the authors developed a novel DNN-based open-source software interface to predict the mix design proportions for a given target compressive strength (using inverse modeling technique) for slag ash-based geopolymer concrete. Additionally, the software calculates the Global Warming Potential (kg CO2 equivalent) for each mix design to select the mix designs with low greenhouse emissions.