Monitoring pavement condition during its service life is paramount in order to antici-pate and optimize the potential maintenance work. For this purpose, different non-destructive techniques (NDT) are used to evaluate the structure distresses condition and to provide necessary information for the maintenance tasks. On their own, they are limited to...
Published in The Science of the total environment
Detection of SARS-CoV-2 in sewage has been employed by several researchers as an alternative early warning indicator of virus spreading in communities, covering both symptomatic and asymptomatic cases. A factor that can seriously mislead the quantitative measurement of viral copies in sewage is the adsorption of virus fragments onto the highly poro...
Published in Biotechnology for Biofuels
BackgroundIncreasing the efficiency of the biogas production process is possible by modifying the technological installations of the biogas plant. In this study, specific solutions based on a mathematical model that lead to favorable results were proposed. Three configurations were considered: classical anaerobic digestion (AD) and its two modifica...
Published in SN Applied Sciences
In engineering design, an issue for using complex simulation models in system analysis are unknown causes for dynamic system behavior, which make parameterization difficult. This paper presents a case study in which a structured system analysis is used for the parameterization of complex dynamic multi-domain models. The dynamic system behavior of a...
Published in Tribology Letters
AbstractZinc dialkyldithiophosphate (ZDDP) is a widely used lubricant additive due to its high effectiveness in reducing wear by forming a tribofilm on sliding surfaces. However, the formation and removal of tribofilm are two competing processes depending on the working conditions, and ZDDP loses its anti-wear function when the removal process prev...
Published in Annals of Forest Science
AbstractKey messageWe modeled 10-year net stand volume growth with four machine learning (ML) methods, i.e., artificial neural networks (ANN), support vector machines (SVM), random forests (RF), and nearest neighbor analysis (NN), and with linear regression analysis. Incorporating interactions of multiple variables, the ML methods ANN and SVM predi...
Published in SN Applied Sciences
Empirical models provide precise and cost-effective information on solar energy assessment. The main objective of this work is to create and examine some regression models (linear, quadratic and logarithmic), for the estimation of the monthly global solar radiation potential in the Jubail Industrial City of Saudi Arabia. The industrial city has mor...
Published in Environmental Earth Sciences
In arid areas, the estimation of evaporation rates plays a considerable role on both water resources management and agricultural activities. Hence, it is of utmost importance to determine the best model to predict these rates. This study investigates the applicability of using quantile regression forest in predicting the pan evaporation. The model ...
Published in Solar Physics
The Effective Acceleration Model (EAM) predicts the Time-of-Arrival (ToA) of the Coronal Mass Ejection (CME) driven shock and the average speed within the sheath at 1 AU. The model is based on the assumption that the ambient solar wind interacts with the interplanetary CME (ICME) resulting in constant acceleration or deceleration. The upgraded vers...
Published in Arabian Journal of Geosciences
Soil wind erodibility is an important soil characteristic controlling soil particle susceptibility to wind erosion. Measurement of soil wind erodibility in the field and wind tunnel is time-consuming and expensive. Therefore, using artificial intelligence techniques to predict soil wind erodibility could be less costly and time-consuming. This stud...
