Non-linear finite element analysis (NLFEA) has been frequently used to assess the ultimate capacity of reinforced concrete (RC) structures under the most complex conditions. Nevertheless, the guidelines using such methods to evaluate RC corbels are limited. In addition, the influence of material modeling options regarding the behavior of such members was not investigated until now. This paper proposes to present a framework for the NLFEAs of RC corbels using the Concrete Damaged Plasticity (CDP) model. the influence of several modeling choices related to this constitutive model also is discussed in detail, including the assumed stress–strain behavior in compression and tension and the parameters related to the yield criterion and flow rule. For this, a first set of test results was used to validate the proposed approach to the NLFEA. Afterwards, the sensibility of the numerical results for several modeling choices was investigated. In the end, the proposed framework for the NLFEA was checked against a database of 36 test results from the literature. The mean ratio between the predicted and experimental test results was 1.015 with a coefficient of variation of only 8.57%. The governing failure mechanism of the tests was predicted correctly in approximately 88% of the simulations. In summary, the proposed approach allows for predicting the ultimate capacity and failure mechanism of RC corbels accurately.

Deep beams do not behave according to classical beam theory. The nonlinearity of strain distribution within these elements requires application of strut and tie models (STM) or other alternatives to evaluate the complex stress field. Although the design of these elements is a common task for structural engineers, limited research is found on assessing effectiveness of the results. The purpose of this work is to compare, in a systematic approach, different design solutions for a deep beam using selected performance metrics which are strain energy, reinforcement ratio, maximum load, structural efficiency, safety factor and cracking behavior. A deep beam (2.85 m of height, 4.20 m of length and 0.2 m of thickness) with a square opening (0.7 m x 0.7 m) close to one of the supports was subjected to a uniform loading at the top surface while resting on supports at both ends. A simplified finite element model (FEM) of this beam was developed simulating concrete with elastic linear stress-strain behavior and disregarding steel reinforcements. This model allowed determination of elastic stress fields necessary to subsequent analyses. Four STM were then developed, supposing the total load respectively represented by one (STM-1), two (STM-2), four (STM-4) or eight (STM-8) concentrated loads equally spaced along the top of the beam. Additionally, an in-plane stress field method (SFM) was applied to the design of the same beam subjected to uniform loading on the top surface. After design and detailing of the reinforcement for each situation, nonlinear FEMs were used to predict the ultimate conditions. The strain energy reduced significantly comparing results from STM-1 to STM-2 and subsequently to STM-4 and remained at a low level in STM-8 and SFM. The reinforcement ratio reduced systematically from STM-1 to STM-8, was minimum with the SFM and the same behavior was followed by maximum load. The structural efficiency (maximum load/reinforcement ratio) increased from STM-1 to STM-8, with maximum efficiency at STM-8 and was slightly below with SFM. The safety factor reduced systematically from STM-1 to STM-8 and was slightly lower with SFM, but in all cases was above acceptable limits found in design codes.

Given the inherent porosity of cementitious materials, fluctuations in temperature disrupt the hygrothermal equilibrium, thereby influencing the accuracy of the coefficient of thermal expansion (CTE) measurements. This results in variations in the observed expansion magnitudes, which are contingent on the material's moisture content. Many existing methodologies for measuring CTE do not adequately control for moisture or consider procedural nuances, leading to inaccuracies and often necessitating expensive equipment. This study evaluates two methodologies for determining the CTE of cementitious mortars, focusing on the influence of moisture and the use of accessible equipment. Among the two methodologies tested, one was recommended for its higher precision in determining the CTE of a prismatic mortar sample by measuring length variations due to temperature changes. In this method, the sample is heated to 80ºC at a fixed relative humidity until hygrothermal equilibrium is reached, after which measurements are taken during cooling to 22 ± 2°C. Adjustments were made to eliminate the influence of studs, and the CTE is calculated using linear regression to correlate strain with temperature variation. The methodology demonstrated a repeatability standard deviation of 0.08×10⁻⁶/ºC, comparable to the precision of AASHTO T 336 (0.12×10⁻⁶/ºC) and superior to ASTM C 531 (1.62×10⁻⁶/ºC). Evaluating CTE at moisture levels of 50%, 75%, 98%, and saturation revealed a parabolic behavior, with a maximum CTE near 75% relative humidity, aligning with existing literature. This methodology offers a promising approach for assessing the CTE of mortars, particularly those exposed to environmental conditions, emphasizing the importance of compatibility between repair mortar and substrate across different moisture levels.

The Belo Monte Hydroelectric Complex, located on the Xingu River in Altamira, Pará, Brazil, includes two powerplants: Pimental, built directly on the riverbed, and Belo Monte, which uses water diverted from an intermediate reservoir. This reservoir is contained by 28 dikes, mostly underlain by migmatite residual soils. During construction and early operation, tubular cavities known as canaliculi and associated resurgence processes were identified downstream of several dikes. However, the spatial controls governing these phenomena remain poorly understood in tropical lateritic environments. This study proposes an integrated geostatistical–machine learning framework for the spatial prediction of resurgence and canaliculi. Ordinary Kriging was applied to model the elevation of the Young Residual Soil (YRS) contact surface using approximately 450 borehole records. The model was subsequently extrapolated to downstream areas lacking direct subsurface data through Support Vector Machine (SVM) regression. A digital terrain model was combined with the modeled YRS contact to identify potential outcrop zones associated with resurgence. Spatial statistical indicators based on minimum-distance metrics were developed to quantify the correspondence between predicted outcrop areas and fieldmapped occurrences. The results show strong spatial agreement between predicted YRS outcrop zones and mapped resurgence and canaliculi points across five representative dikes, with average shortest distance ranging from 4.4 to 50.6 m. Cross-validation indicated satisfactory predictive performance of the YRS digital model, with RMSE values between 4.16 and 9.56 m for kriging and between 3.36 and 10.65 m for SVM. The proposed framework provides a replicable and cost-effective predictive tool for dam safety management, supporting the definition of priority inspection corridors and early detection of anomalous resurgence and canaliculi behavior in tropical dam foundations.