Fabrication of a sandwich panel by integrating coconut husk with polyurethane foam and optimization using R2

Sharma, Prerna; Prasath Kumar, V.R.

doi:10.1016/j.conbuildmat.2023.133929

Cited by 9 publications

(1 citation statement)

References 63 publications

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“…This study details the findings of an experiment conducted to examine the impact of partially replacing cement with PC waste ash 16 . This study examined the workability and density of fresh concrete, as well as the compressive strength of hardened concrete after 7 and 28 days 28 . However, these wastes can be successfully utilized in the manufacturing of concrete, thereby decreasing the demand for land to dispose of PC waste ash and protecting the environment by reducing the consumption and production of cement 6 …”

Section: Introductionmentioning

confidence: 99%

Modelling the mechanical properties of concrete produced with polycarbonate waste ash by machine learning

Sathvik,

Kumar,

Ulloa

et al. 2024

Sci Rep

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India’s cement industry is the second largest in the world, generating 6.9% of the global cement output. Polycarbonate waste ash is a major problem in India and around the globe. Approximately 370,000 tons of scientific waste are generated annually from fitness care facilities in India. Polycarbonate waste helps reduce the environmental burden associated with disposal and decreases the need for new raw materials. The primary variable in this study is the quantity of polycarbonate waste ash (5, 10, 15, 20 and 25% of the weight of cement), partial replacement of cement, water-cement ratio and aggregates. The mechanical properties, such as compressive strength, split tensile strength and flexural test results, of the mixtures with the polycarbonate waste ash were superior at 7, 14 and 28 days compared to those of the control mix. The water absorption rate is less than that of standard concrete. Compared with those of conventional concrete, polycarbonate waste concrete mixtures undergo minimal weight loss under acid curing conditions. Polycarbonate waste is utilized in the construction industry to reduce pollution and improve the economy. This study further simulated the strength characteristics of concrete made with waste polycarbonate ash using least absolute shrinkage and selection operator regression and decision trees. Cement, polycarbonate waste, slump, water absorption, and the ratio of water to cement were the main components that were considered input variables. The suggested decision tree model was successful with unparalleled predictive accuracy across important metrics. Its outstanding predictive ability for split tensile strength (R2 = 0.879403), flexural strength (R2 = 0.91197), and compressive strength (R2 = 0.853683) confirmed that this method was the preferred choice for these strength predictions.

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Section: Introductionmentioning

confidence: 99%

Modelling the mechanical properties of concrete produced with polycarbonate waste ash by machine learning

Sathvik,

Kumar,

Ulloa

et al. 2024

Sci Rep

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Buckling analysis of hybrid fiber‐reinforced composite sandwich panels with varying numbers of polyurethane cores

Wang,

Qiao,

Song

et al. 2024

Polymer Composites

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Hybrid fiber‐reinforced composite sandwich panels with multi‐layer polyurethane cores are widely applied in aerospace, automotive, construction, and shipbuilding industries. This study aims to investigate the buckling performance of composite structures with varying numbers of polyurethane cores. To achieve this, the buckling loads of these structures are determined using an energy method, microscopic mechanics method, and the first‐order zigzag kinematic model. The accuracy of the equation employed in the algorithm is validated using the finite element method. Additionally, we conduct a parametric analysis to examine the influence of various parameters on the buckling performance of the structures. The results indicate that an effective strategy for improving the critical buckling loads of the hybrid fiber‐reinforced composite sandwich plate involves strategically placing fibers and matrix materials with higher elastic modulus on the skin layer. Moreover, the critical buckling load is notably influenced by the number and positioning of polyurethane layers, as well as the fiber content.Highlights An analytical model is established to predict the buckling behavior. The correctness of the model was verified using the finite element method. Effects of structural parameters on buckling performance were investigated.

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A step towards sustainability to optimize the performance of self-compacting concrete by incorporating fish scale powder: A response surface methodology approach

Ujwal,

Shiva Kumar

2024

emergent mater.

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Fabrication of a sandwich panel by integrating coconut husk with polyurethane foam and optimization using R2

Cited by 9 publications

References 63 publications

Modelling the mechanical properties of concrete produced with polycarbonate waste ash by machine learning

Modelling the mechanical properties of concrete produced with polycarbonate waste ash by machine learning

Buckling analysis of hybrid fiber‐reinforced composite sandwich panels with varying numbers of polyurethane cores

A step towards sustainability to optimize the performance of self-compacting concrete by incorporating fish scale powder: A response surface methodology approach

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