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.

Sustainable campuses have a substantial role to play in achieving the Sustainable Development Goals (SDGs). Worldwide, there are many rating schemes to assess universities’ sustainability; UI GreenMetric is one of the most common global rating schemes aimed at encouraging green campuses and university sustainability worldwide. However, none of the existing rating schemes quantitatively measure the contributions of the implementation of its assessment indicators to achieve SDGs. There is a shortage of information on how sustainable campuses contribute to achieving SDGs. Thus, this research aimed to develop a novel index to assess and manage the contributions of sustainable campuses certified by UI GreenMetric to achieve SDGs. This article proposes novel indices, the GreenMetric Indicator Contribution Index (GMICI) and the GreenMetric Sustainable Campus Index (GMSCI), to evaluate the contributions of implementing UI GreenMetric indicators for achieving the SDGs. By implementing questionnaire surveys, we collected the relevant data. Structured questionnaire surveys yielded 35 responses from experts. The contributions of UI GreenMetric indicators to achieving SDGs were evaluated using the Relative Importance Index (RII). The results indicated an important relationship between the GreenMetric indicator and SDGs 3, 4, 6, 7, 8, 9,11, 12, 13 and 15. This research concludes that the proposed GMICI and GMSCI are a rigorous means for evaluating the contribution of UI GreenMetric indicators to UN-SDGs’ achievement.

Purpose: The purpose of this paper is to investigate the main causes of delay in public construction projects. This is motivated by feedback from public construction experts concerning substantive delays during the last decade. The study thus seeks to help decision makers in Jordan and elsewhere identify problems and develop mitigating strategies. Design/methodology/approach: Causes of delay were identified from previous related studies and then augmented after consultation with experts. This resulted in 56 delay factors classified into eight groups. The sampling frame for the study was defined in terms of public construction projects (mostly related to roads) owned by the Ministry of Public Works and Housing in Jordan. A survey was conducted with engineers working as representatives of the owner, contractors or consultants to elicit and evaluate the importance of the 56 delay factors. Findings: Overall, 113 completed questionnaire responses were returned and analyzed to rank the causes of delay using the relative importance index method. Owners and consultants showed more interest in factors related to themselves, while contractors showed highest interest in an external factor related to the owner of services. Four recommendations are put forward for decision makers to mitigate against delays. Originality/value: This research investigates a relatively large number of delay factors compared to other studies and these are categorized into groups to facilitate thematic understanding. Further, compared to previous related research, this research fills a gap by exploring the opinions of different contract parties.

Sustainable buildings contribute significantly to achieving sustainable development and provide many benefits. However, sustainable building construction projects are riskier than traditional construction projects. Thus, this research aimed to identify and assess the risks in sustainable construction projects in Jordan based on their probabilities of occurrence and impacts on time and cost. For this purpose, a literature review and structured interviews were performed to identify the risks. Additionally, questionnaire surveys were conducted, and the relative relevance index and analytic hierarchy process were utilized to assess the probabilities and impacts of these risks on time and cost. After that, a focus group discussion was conducted. According to the the risks’ probability and impacts on time and cost, the top-scoring risks include changes to the original design, budgeting inaccuracies owing to a lack of experience with sustainable building projects, additional costs incurred as a result of the use of sustainable building construction materials and equipment, inadequate or inaccurate sustainable design information, insufficient funds from clients, inadequate project planning for a sustainable building project, a tight project schedule for a sustainable building project, and insufficient identification of sustainable construction’s scope. This research contributes to the body of knowledge and practice by providing a novel integrated method for assessing risks in sustainable building construction projects in Jordan.

In general, construction projects are vulnerable to various risks during their life cycle. These risks may negatively affect the project cost and duration, in addition to other factors, including environmental impact, health and safety, and quality of construction work. The COVID-19 pandemic has brought more challenges to construction projects. This study presents an assessment of 47 major risks affecting construction projects. The research investigates and assesses the risk factors associated with a special type of construction project, namely, projects funded by external sources, due to their importance, characteristics, and sensitivity. Furthermore, the study was carried out under the impact of the special conditions and constraints associated with the COVID-19 health pandemic. These conditions provided specific types of risks, results of risk assessment, and recommended responses to the risks. The studied risks were categorized using the PESTLE technique, an external factor analysis technique, which includes six groups of Political, Economic, Social, Technological, Legal, and Environmental risks. A questionnaire survey was conducted on 34 construction organizations that implemented or supervised projects funded by external sources. The aim of the survey was to assess the risks affecting the construction projects in terms of probability of occurrence and severity on the projects’ cost and time schedule. Then, the importance of each risk was calculated, and the risks were ranked according to their importance. The results showed the high importance of environmental and legal risks and indicated that the most important risk factors are the difficulty of issuing licenses and permits and the inappropriate definition of the scope of work. This study would help managers and fund providers make decisions regarding risks during uncontrolled pandemic or disastrous circumstances. Although the current study was conducted in Jordan, its procedures and results can be useful in other locations with different properties and conditions.