Cost overruns are common on long-term construction projects. This is mostly because of inaccurate early estimates and unexpected changes in the economy and finances. In Egypt, the costs of materials like steel, cement, bricks, sand, and aggregates make up a large part of the cost of building. These costs are greatly affected by the state of the economy and the financial markets. Even though the Construction Cost Index (CCI) is a widely used economic indicator around the world, Egypt has not yet made its own CCI official. This study creates a predictive model just for Egypt’s construction industry that aims to predict a localized CCI to improve financial planning and lower risk. The framework uses two deep learning models, Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), to make predictions about Egypt’s CCI. The models include a wide range of macroeconomic, monetary, foreign exchange market, commodity/energy market and equity market indicators, as well as technical indicators. In Python, advanced statistical methods like correlation analysis, multicollinearity, and stepwise regression are used to make sure that the best features are chosen. The GRU is better at keeping things in balance because it wins on the calibration (Weighted Absolute Percentage Error (WAPE), Bias (mean error)), the absolute error metrics (Mean Absolute Error, Mean Absolute Percentage Error, Symmetric Mean Absolute Percentage Error, and median error), while LSTM is better at squared-loss/association and turning points (Root Mean Squared Error, Mean Squared Error, Coefficient of determination, Directional Accuracy) because it has a slightly tighter variance fit and sign tracking. There is a permutation feature importance analysis for six features in both the GRU Model and the LSTM Model that shows that oil is the most important thing that affects the construction cost index (CCI). The study shows that deep learning models can accurately predict economic indicators. This gives Egypt’s construction industry a useful, data-driven tool for estimating costs ahead of time. They make a big difference in Egypt’s construction industry and meet the need for localized forecasting models in markets.

A 3D finite element model (FEM) for predicting the distribution of lateral pressure in a square flexible walled steel silo during the filling phase was analyzed in this study. The numerical approach, developed using Abaqus software, predicts the stress state in bulk solids, as well as the pressures exerted on the silo walls. An elasto-plastic model using the Drucker–Prager criterion was employed to simulate the behavior of the granular materials. The FEM simulates the behavior of the bulk solid and its interaction with the silo’s wall and base using a surface-to-surface discretization model. The model’s predictions were validated by previous experimental measurements. The results revealed good agreement between the FEM predictions and the experimental measurements. The research confirms that the lateral pressure distribution is not uniform at any silo level. This highlights the fact that many available theories and current design codes are not accurate for flexible steel walls. As a result of the wall’s deformability, pressure regimes on the silo wall change significantly in the horizontal direction at any level. The results showed that the horizontal variations of lateral pressure change drastically with regard to wall stiffness. The FEM has been used to investigate the effect of critical parameters on wall pressure distribution, such as properties of bulk solids, wall thickness, and silo type, whether deep or flat.

This study proposes a modification for the current design approach for square and rectangular silos that accounts for silos’ wall flexibility. First, the authors investigated the effect of wall stiffness symbolized by the wall width-to-thickness ratio (a/t) and silo’s dimensions, on the wall-filling pressure using a recently validated 3D finite element model (FEM). The model was then employed to predict the pressures acting on silos’ walls accounting for the stress state in stored granular materials. Most design formulas and guidelines assume silos’ walls to be rigid. This assumption is acceptable for the case of rigid wall concrete silos; however, it is questionable for semi-rigid, flexible wall metal silos. Consequentially, it is crucial to determine the minimum wall stiffness necessary to secure the applicability of the current design rigid wall assumptions and to propose a way to deal with semi-rigid and flexible walls. To this end, several wall pressure distributions that correspond to filling steel silos with varied wall thicknesses were studied. A new adjustment to the Janssen technique was proposed for a better estimate of the wall-filling pressures for square and rectangular silos. In the case of prismatic silos, the Eurocode uses the Janssen equation together with an equivalent radius of a corresponding circular silo (with the same hydraulic radius) to determine the wall pressure. This method predicts pressure values that are practically accurate for rigid-wall silos, but its accuracy decreases for semi-rigid and flexible-wall silos. As an enhancement, the Janssen equation was modified in this research to generate more accurate pressure estimates based on the equivalent volume concept. The finite element results of several developed models with the same granular material were compared to the estimations of the newly established approach to verify the broad range of its applicability.

This study develops and validates a 3-D finite-element model for lateral pressures in square, flat-bottomed steel silos, challenging the applicability of conventional design methods. The model, using Mohr–Coulomb for wheat and surface-to-surface contact, closely matches observed pressures and demonstrates that slenderness h/a determines the pressure regime: Janssen-type asymptotic profiles in slender silos (h/a ≥ 7.5) change to Rankine-type linear profiles in squat silos (h/a ≤ 1.5). Therefore, using slender-silo formulae for squat designs may lead to inaccurate estimations of base pressures. A parametric study evaluates material influences: lateral pressure is significantly affected by Poisson’s ratio (raising from 0.28 to 0.45 more than doubles base pressure, + 110%) and wall friction µ, while it shows little sensitivity to Young’s modulus and cohesion. These results provide design-oriented recommendations for the safe and cost-effective sizing of silos across various geometries and granular materials.

This study proposes a modification for the current design approach for rectangular silos that accounts of silos’ wall flexibility. First, the authors investigated the effect of wall stiffness, symbolized by the wall width-to-thickness ratio (a/t), on the wall-filling pressure using a recently validated 3D finite element model (F.E.M.). The model was then employed to predict the pressures acting on flexible-wall silos accounting for the stress state in stored granular materials. Most design formulas and guidelines assume silos’ walls to be rigid. This assumption is acceptable for the case of thick-wall concrete silos; it is questionable for thin-wall, metal silos, however. Consequentially, it is crucial to determine the minimum wall stiffness necessary to secure the applicability of the current design rigid wall assumption, and to propose a way to deal with more flexible walls. To this end, several wall pressure distributions that correspond to filling steel silos with varied wall thicknesses were studied. A new adjustment to the Janssen technique was proposed for a better estimate of the wall-filling pressures for square or rectangular silos. In the case of square silos, the Eurocode uses the Janssen equation together with an equivalent radius of a corresponding circular silo (with the same hydraulic radius) to determine the wall pressure. This method predicts pressure values that are practically accurate for rigid-wall silos, but its accuracy decreases for flexible-wall silos. As a remedy, the Janssen equation was modified in this research to generate more accurate pressure estimates based on the equivalent volume concept. The finite element results of several developed models with the same granular material were compared to the estimations of the newly established approach to verify the broad range of its applicability.