Transient flows represent a critical topic in the field of hydraulic engineering, one that has witnessed significant progress in recent decades [...]
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This study presents a methodology for the digitalisation process for analysing transient flow phenomena in a U-tube. It comprises several layers, including the characterisation of liquid oscillation dynamics, image segmentation for experimentally determining variations in the meniscus position, and the integration of machine learning techniques with analytical solutions. The position, velocity, and acceleration of the meniscus are obtained using image-processing methods and subsequently compared with the corresponding analytical predictions. The proposed methodology accurately represents the existing hydraulic conditions, incorporating both Newtonian and Ogawa friction models. To assess model performance, the index of agreement was employed to compare analytical and experimental results. The findings indicate a systematic error of 2.2 mm ± 3 pixels when using the Ogawa friction model, which corresponds to the best model for predicting this hydraulic behaviour. Finally, the implementation of machine learning techniques demonstrates considerable potential for predictive analysis, with statistical measures showing coefficients of determination above 0.997 and consistently low Root Mean Square Error values.
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This work considers the behaviour of air inside pipes when the air is expelled through air valves. Generally, the air shows isothermal behaviour. Nevertheless, when the transient is very fast, it shows adiabatic behaviour. In a real installation, an intermediate evolution between these two extreme conditions occurs. Thus, it is verified that the results vary significantly depending on the hypothesis adopted. To determine the pressure of the air pocket, the most unfavourable hypothesis (isothermal behaviour) is typically adopted. Nevertheless, from the perspective of the water hammer that takes place when the water column arrives at the air valve and abruptly closes, the most unfavourable hypothesis is the opposite (adiabatic behaviour). In this case, the residual velocity with which the water arrives at the air valve is higher, and, consequently, the water hammer generated is greater.
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Abstract Mathematical models are a fundamental tool in the learning process of environmental engineering. These models need to be calibrated in order to be used by future engineers as a simulation tool for the represented problems. This paper deals with the concept of computational models calibration applied to higher environmental engineering studies. In this paper, we depict a methodology to calibrate water quality models, as an educational example that represents the environmental problem of dissolved oxygen in a stream. This methodology is based on defining two types of parameters involved in calibration. First, internal parameters appear in the equations from semi‐empirical estimations and can be found within some intervals. Genetic algorithms are proposed to estimate them. Second, experimental measurements enter into equations as external parameters. They affect the accuracy of the final solutions. Therefore, an uncertainty analysis has to be performed. Finally, a termination criterion for calibration has been proposed, based on the overlap between the confidence intervals of predicted and measured values. By developing this methodology, we provide awareness to our students of the importance of calibration of mathematical models so that they can apply them in their future simulation of environmental problems. Students identify the possible sources of uncertainty at each stage of the environmental model performance and apply them in this particular problem, Genetic Algorithm Techniques, as a computational tool to improve the accuracy of their model predictions. © 2009 Wiley Periodicals, Inc. Comput Appl Eng Educ 19: 795–805, 2011
Resumen es: Los sistemas domesticos de aprovechamiento de lluvia se estan recuperando como una opcion alternativa al suministro desde las redes generales de distribu...
