The objective of this study was to evaluate the bond behaviour of concrete-filled steel tubes (CFSTs) where waste chipped rubber, sourced from scrap tyres, partially replaces natural coarse aggregate. A series of push-out tests on 112 circular and square CFST specimens were investigated with the main parameters considered in the tests being: (a) cross-sectional type (circular and square); (b) cross-sectional dimensions; (c) concrete type (normal and rubberised concretes); (d) replacement ratio of recycled chipped rubber; and (e) concrete age (28–365 days). Four rubber chip replacement ratios (0, 10, 20 and 30%) by volume of coarse aggregate were used. The experimental results indicated that cross-sectional type and dimensions have a high impact on the interfacial bond strength. The bond strength in larger circular tubes was about 60% more than the bond strength in smaller circular tubes, and about 127% and 42% more than the bond strength in large and small square tubes, respectively. It was also found that CFSTs incorporating chipped rubber shared a generally similar interface bond behaviour between the concrete core and steel tubes with conventional CFSTs. Moreover, the bond strength decreased remarkably with the increase of concrete age.
Glass waste, which is dumped around the world in huge amounts, can be used as a partial replacement of mineral aggregate in concrete industry. This would not only contribute to reducing pollution extent but also enhancing physical properties and durability of concrete. This article reports the mechanical performance of concrete with different replacement percentages of crushed glass waste of cement or fine aggregates before and after being subjected to standard cycles of freezing and thawing. Mechanical performance was evaluated in terms of compressive and flexural strengths. Furthermore, internal damage extent was evaluated using ultrasonic pulse velocity and dynamic modulus of elasticity. The results (average of six specimens for each test) revealed the feasibility of incorporating glass waste in concrete mixtures for the purpose of improving strength and durability; especially in environments where concrete is being exposed to an effective freezing and thawing cycles.
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.
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.
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