This study determined the elastic properties of composites and concretes reinforced with oil shale ash (OSA) particles, a byproduct of oil shale combustion in an electric power plant in Estonia (Auvere). Since 2018, OSA has no longer been classified as hazardous waste in the EU, enabling its reuse in sustainable materials. The present research examined the effect of OSA on the elastic properties of epoxy–OSA and concrete–OSA composites. The experimental results show that the elastic modulus of epoxy resin increases with an increase in the ash concentration, while it decreases in concrete with a higher OSA content. Theoretical models, including the rule of mixtures, finite element method (FEM), Mori–Tanaka method, and Halpin–Tsai method, were used to predict these properties numerically. The rule of mixtures and FEM generally overestimated the modulus for epoxy–OSA, whereas the Mori–Tanaka and Halpin–Tsai methods provided closer predictions. For concrete–OSA, the compressive strength tests followed the LVS EN 12390-3:2019 standards, with elastic modulus conversions being made via IS 456:2000 Clause 6.2.3.1, which showed a variable decrease across different strength classes. The findings highlight the potential of OSA as a reinforcing filler in construction materials, promoting environmental sustainability by repurposing industrial waste while offering mechanical benefits.

This study determined the elastic properties of “green” concrete with cement partially replaced by oil shale ash (OSA) and reinforced with short basalt integral fibers (BIFs). Commercially available Deutsche Basalt Faser (DBF) GmbH Turbobuild Integral basalt fibers were used. There is currently a high demand both for strengthening concrete and applying ecological approaches with respect to circular economy. Oil shale ash is the byproduct of oil shale combustion. Basalt fiber is produced by melting basalt rock. Both BIF and OSA are used as additives in concrete. Cement replacement by OSA non-linearly changes the concrete’s strength properties, and the addition of BIF improves them. An experimental investigation was conducted using four-point bending tests and cube sample compression tests. Theoretical methods such as Voigt and Reuss boundaries, the Halpin–Tsai method, and the Mori–Tanaka method were used to predict the elastic properties of the fabricated samples. The theoretical models can provide useful information, although they may not fully capture the real properties observed experimentally. The results show that BIFs protect against instant brittle destruction. The experiments demonstrated an optimal OSA concentration for a fixed amount of BIF, resulting in the highest load-bearing capacity of the concrete. The addition of either 15% OSA only or 20% OSA and CBF can increase the stiffness of the concrete. This article provides guidance to the construction sector on using OSA and CBF together.

Computational fluid dynamics (CFD) simulations generate huge datasets with many variables such as Velocity and Pressure at nodes, elements, and time steps. It is challenging and expensive to analysis large datasets and storage, developing applications over the large datasets required additional computational resources and storage volume. To addresses this problem, we have employed data reduction technique for the reduction of the complexity and utilize its computational resources. Reduced Order Modelling emerged technique leading dimensional reduction yet preserving dominant features, patterns and discarding less significant features. Focusing on developing the Reduced Order Models (ROM) for data compression, we implemented Proper Orthogonal Decomposition (POD) technique for dimensionality reduction. Proper Orthogonal Decomposition (POD) is widely used for building efficient Reduced Order Model (ROM) in CFD simulations, enabling effective dimensionality reduction while preserving key flow characteristics. POD extracts the high-energy structures from the flow field, representing dominant patterns through POD modes that contributes to the overall dynamics. Dimensional reduction is achieved by truncating lower-energy modes based on rank, retaining only the most significant features. In this paper we conducted numerical simulation flow over the convex shape object cantered in the flow path, with parametric velocity ranging 25 -300 m/s and density 900 - 2000 kg/m2 of the water. The solution matrix is extracted and total volume was 8.83 MB. After computing POD modes and captured five most energetic modes (Rank = 5) and truncated other modes. The resulting ROM took 4.42 MB achieving a data volume saving of 4.41 MB (8.83 - 4.42 MB). when compared with volume consumptions over the single full numerical simulation (482 MB) to ROM (4.2 MB) is 477.8 MB and percentage occupation for the ROM is only 0.87% which is less than 1% of the original size of full simulation. This study also explores effective techniques for generating and truncating POD-based ROM. It also demonstrates the use of EZyRB-based ROM combined with Radial Basis Function (RBF) interpolation is applied to the POD coefficients using EZyRB library allows fast reconstruction of flow fields without running Full Order Model (FOM) to predict system responses for new parameter values, density 1232 kg/m2 and velocity 152 m/s we successfully reconstructed the flow field using ROM without conducting FOM. These new parameter values were projecting onto the original spatial domain for the visualization and comparing results with Ansys Fluent FOM. Highlighting the efficiency and effectiveness of ROM in parametric interpolation with lower dimensions and provides an intuitive approach for developing digital models that accurately represent physical systems with significantly reduced the computational volume and resources.