The increasing demand for clean energy and the global shift towards renewable sources necessitate reliable solar radiation forecasting for the effective integration of solar energy into the energy system. Reliable solar radiation forecasting has become crucial for the design, planning, and operational management of energy systems, especially in the context of ambitious greenhouse gas emission goals. This paper presents a study on the application of auto-regressive integrated moving average (ARIMA) models for the seasonal forecasting of solar radiation in different climatic conditions. The performance and prediction capacity of ARIMA models are evaluated using data from Jordan and Poland. The essence of ARIMA modeling and analysis of the use of ARIMA models both as a reference model for evaluating other approaches and as a basic forecasting model for forecasting renewable energy generation are presented. The current state of renewable energy source utilization in selected countries and the adopted transition strategies to a more sustainable energy system are investigated. ARIMA models of two time series (for monthly and hourly data) are built for two locations and a forecast is developed. The research findings demonstrate that ARIMA models are suitable for solar radiation forecasting and can contribute to the stable long-term integration of solar energy into countries’ systems. However, it is crucial to develop location-specific models due to the variability of solar radiation characteristics. This study provides insights into the use of ARIMA models for solar radiation forecasting and highlights their potential for supporting the planning and operation of energy systems.

Numerous existing formulas predicted the ultimate interfacial bond strength in concrete-filled steel tubes (CFST) between steel tubes and concrete core without investigating the whole response under push-out load. In this research, four models are proposed to predict the interfacial behavior in CFST including the post-peak branch under the push-out loading test based on 157 circular specimens and 105 squared specimens from the literature. Two models (one for circular and one for squared CFST) are developed and calibrated using artificial neural network (ANN) and two models (one for circular and one for squared CFST) are developed based on multivariable regression analysis, analysis of variance (ANOVA). The shape of the specimen (circular or squared), diameter of the tube, thickness of the tube, concrete compressive strength, age at the time of testing, and length of the specimen are the main factors considered. These models are then compared to other existing formulas to verify their capability to better predict the ultimate interfacial bond strength. It is found that the ANN model gives better results for most of the considered data. It is also found that ANN models can predict the overall bond-slip response for the considered dataset. In order to simulate the response of any CFST column using finite element (FE) method, it is vital to have sufficient input data on the overall bond-slip behavior between the interior face of the steel tube and the exterior surface of the concrete core including the post-peak branch. Accordingly, the suggested ANN model is used to generate the required input data related to the cohesive behavior and damage along the interface in ABAQUS model to simulate the response of two circular and two squared CFST columns under concentric compressive load. The results are in good agreement with experimental outcomes. The cohesive criterion and damage interface that are used based on ANN models in FE are found to be sufficient and can be adopted to model CFST columns.

Sand is one of the most abundant, naturally occurring materials in many parts of the world, which is used in local rural areas in infrastructure projects such as in the construction of low volume paved and unpaved road layers due to their availability at low cost and scarcity of other suitable construction materials. Several geotechnical solutions for sand stabilization have been undertaken to improve their properties in order to overcome erosion, failure of pavements under traffic loading, embankments, cuts and excavations caused by failures of sand structure. In this investigation, bentonite clay–water slurry was used due to its cohesive and eco-friendly nature to improve sand strength by the means of manual injection in the laboratory and pilot scales. Sand was stabilized using variation of bentonite clay contents, 0%, 1%, 2%, 3%, and 4% (by weight of dry sand), at different curing times: 0 days, 1 day, 2 days, and 3 days. Direct shear tests were conducted to determine shear strength parameters for sand before and after stabilization process. Furthermore, a transparent polypropylene box (60 cm × 40 cm × 30 cm) was used in this study as a larger scale for sand stabilization technique by applying manual grouting of bentonite clay–water slurry to the sand mass. A mechanical shaker was used at 100, 200, 300, and 400 rpm for 10 min at each stage to test the stability of sand in addition to using a Scanning Electron Microscope (SEM) to obtain images for stabilized sand and Ground Penetrating Radar (GPR) to scan soil mass before and after stabilization. The test results showed that a slurry composed of 3% of bentonite clay additive with 10.3% added water by weight of dry sand mass are the optimum amounts for the stabilization process, which provides a substantial resistance to shear forces.

This study aimed to investigate the effect of freeze and thaw (FT) cycles on the performance of asphalt concrete (AC) mixtures modified by partial replacement of mineral filler of the aggregate with natural bentonite clay (NBC) in order to reduce damage that occurs due to rapid FT cycles within the pavement structure. After exposure to FT cycles, AC mixture stability is reduced and becomes lower than minimum requirements, which leads to earlier damage of pavement. In order to enhance the AC mixture’s abilities to sustain severe FT cycles, this study used NBC amounts as a substitute for mineral filler by weight of its portion of the total aggregate: 5%, 10%, 15%, and 20%. Marshall stability, flow, and FT cycles were tested, and interior damage degree was assessed by a nondestructive test called ultrasonic pulse velocity (UPV). The results revealed the viability of combining NBC with asphalt mixtures for the purpose of improving the mixtures’ properties, particularly in environments where asphalt pavement is exposed to alternating FT cycles. The results also revealed that replacement of filler with NBC by 5% in AC mixtures reduced the damage caused over 8 continuous weeks of rapid FT cycles by 13%, which, in future applications, would reduce maintenance cost and prolong the pavement’s service life.

This study aimed to investigate the performance of asphalt mixtures after natural bentonite clay partial replacement of mineral filler portion of aggregates. Different bentonite contents were used to replace the mineral filler by total weight of its portion of total aggregates, namely, 5, 10, 15, and 20%; additional bentonite contents were conducted for the stability test, namely, 25 and 30%. Marshall stability, flow, bulk density, hydraulic conductivity, and indirect tensile strength (ITS) tests were performed. Results showed that replacing mineral filler by natural bentonite clay in asphalt mixtures leads to the increase of density and stability, which increased to 11.57 kN for mixtures containing 15% bentonite (compared with 9.17 kN for the control specimen), with 23% loss when soaked with water for 24 h. Results indicate an increase in both flow and ITS values and reduction in hydraulic conductivity of the modified mixtures compared with control specimens.