This paper describes an experimental study on the flexural ductility of lightweight-aggregate concrete beams in­cluding concretes with compressive strengths between 22.0 and 60.4 MPa and dry densities between 1651 and 1953 kg/m3. Nineteen simply supported beams were tested until failure. Two symmetrical concentrated loads were applied at approxi­mately one third of the span. Ductility was studied by defining ductility indexes. The main variables are the concrete compressive strength and the longitudinal tensile reinforcement ratio. It is shown that the parameter with higher influ­ence on ductility is the longitudinal tensile reinforcement ratio. The test results are also compared with the requirements from some codes of practice. It is shown that ACI Code requirements give more guaranties as far as ductility is con­cerned, when compared with European codes.

This study aims to develop a reliable method for predicting power plant construction costs during the early planning stages using ensemble machine learning techniques. Accurate cost predictions are essential for project feasibility, and this research highlights the strength of ensemble methods in improving prediction accuracy by combining the advantages of multiple models, offering a significant improvement over traditional approaches. This investigation employed the Random Forest (RF) algorithm to estimate the overall construction cost of a power plant. The RF algorithm was contrasted with single-learner machine learning models: Support Vector Regression (SVR) and k-Nearest Neighbors (KNN). Performance measures, comprising the coefficient of determination ($R^2$), Mean Absolute Error (MAE), and Root Mean Squared Error (RMSE), were used to evaluate and contrast the performance of the implemented models. Statistical measures demonstrated that the RF approach surpassed alternative models, demonstrating the highest coefficient of determination for testing ($R^2=0.956$) and the lowest Root Mean Square Error (RMSE = 29.27) for the testing dataset. The Shapley Additive Explanation (SHAP) technique was implemented to explain the significance and impact of predictor factors affecting power plant construction costs. The outcomes of this investigation provide crucial information for project decision-makers, allowing them to reduce discrepancies in projected costs and make informed decisions at the beginning of the construction phase.

The presence of filler in asphalt concrete may improve the properties of the mixture. This study investigates the mechanical and volumetric properties of such a mixture using walnut shell ash as a filler in various replacement ratios. The mixtures were mixed with various proportions of limestone (0%, 10%, 20%, 30%, 40%, 50%, 60%, 80%, and 100%) in addition to WSA as a replacement filler. Tests were subsequently carried out, including tests of Marshall’s stability and flow, voids in mineral aggregates, air voids, and theoretical maximum specific gravity. The results revealed that increasing the replacement percentage resulted in a considerable improvement in the performance of the asphalt–concrete mixtures. The results revealed that the mixture with a 60% replacement ratio achieved the best Marshall stability, achieving an improvement of 15.02% compared to the conventional sample, alongside good flow properties. This improvement was accompanied by high conformity with the other physical properties of the asphalt mixture, including a 3.55% air void percentage, which is within the permissible limits for the surface layer, as well as a 21.80% increase in the percentage of voids in the mineral aggregate, which is considered an ideal value. These results paved the way for further study and adjustments to other requirements of the asphalt mixture, as there were no issues with the availability or production costs of the filler material, given the abundance of raw materials. However, it is important to note that, as is evident from the results, a complete 100% replacement led to undesirable outcomes, resulting in a 10.68% decrease in Marshall strength compared to that of the conventional sample. This decrease indicates that the mixture was unable to provide its most important property. Although improving the other properties with complete replacement is not beneficial, a detailed investigation into this ineffective percentage revealed that, according to the results, the ideal replacement ratio is 60% walnut shells and 40% limestone, which results in optimal performance.

This article presents an experimental study on the evolution of the neutral axis depth at failure in the critical section with the flexural ductility and plastic rotation capacity of reinforced concrete (RC) lightweight-aggregate concrete (LWAC) beams. For this, the results of a previous experimental program involving RC LWAC beams tested in flexure until failure are used. The variable studies were the concrete compressive strength (between 22.0 and 60.4 MPa and dry density between 1651 and 1953 kg/m³) and the longitudinal tensile reinforcement ratio (between 0.13% and 2.69%). The flexural ductility and the plastic rotation capacity of the RC LWAC beams are characterized by a ductility index and a plastic trend parameter, respectively. The influence of the variable studies, as well as the relation of the flexural ductility and plastic rotation capacity with the values for the neutral axis depth at failure are analyzed and discussed. Some conclusions are drawn which can be useful for the design of RC LWAC beams for flexure. In particular, it is shown that the practical rule of limiting the neutral axis depth at failure to ensure ductile behavior, as used in normal-weight aggregate concrete beams, is also valid for RC LWAC beams.

This article describes a study on the plastic behaviour of lightweight-aggregate concrete beams. the experimental results of nineteen simply supported beams previously tested by the authors were used in this study. the experimental plastic rotation capacity of the tested beams was characterized by a parameter called plastic trend parameter (ΡΤΡ). the main variables studied were the concrete compressive strength and the longitudinal tensile reinforcement ratio. it was found that plastic rotation capacity slightly increases as the concrete compressive strength increases. An appropriate range for the longitudinal tensile reinforcement ratio to ensure plastic rotation capacity is proposed. the results of this study were also compared with the requirements from some codes of practice. From this analysis, it was shown that ACi Code requirements give more guaranties as far as plastic rotation capacity is concerned, when compared with european codes.

The global drive toward energy transition and carbon neutrality requires integrated and data-driven approaches for managing buildings and smart cities. Existing urban energy assessment frameworks remain fragmented and often lack multiscale interoperability between building-level models and territorial datasets. At the same time, shallow geothermal energy is emerging as an efficient and renewable solution for sustainable heating and cooling. To address these gaps, this study examines the potential of GeoBIM, the integration of Building Information Modeling (BIM) and Geographic Information Systems (GIS), as a unified framework for multiscale energy analysis and for supporting shallow geothermal applications. A systematic literature review was conducted based on the PRISMA framework, combining a systematic literature review using the Scopus database with the critical examination of representative case studies. The results show that GeoBIM-based modeling improves data quality, enhances thermal performance assessments, and supports the implementation of shallow geothermal systems, including energy piles and district-scale ground-coupled networks. Reported applications demonstrate energy consumption reductions exceeding 40% in certain urban contexts. Several research gaps and challenges were identified, particularly data interoperability issues, lack of standardization, computational complexity, and the need for specialized training. Overall, the review indicates that GeoBIM offers a promising pathway for optimizing resources, supporting informed decision-making, and advancing resilient and sustainable smart buildings and cities.