Hasil untuk "Hydraulic engineering"

Yaneth Coromoto Azuaje de Rodríguez , Lázaro Osvaldo Rodríguez Montes de Oca , Daylon Fundora Caballero

El Gran Humedal del Norte de Ciego de Ávila es un ecosistema estratégico por su biodiversidad, regulación hídrica y función como amortiguador ante fenómenos ambientales extremos. Este frágil entorno enfrenta crecientes amenazas debido al cambio climático, incluyendo sequías prolongadas, aumento de temperaturas, intrusión salina en acuíferos y alteración de los patrones de lluvia. Mediante datos georreferenciados, se establecen correlaciones entre fluctuaciones ambientales y la salud del humedal. La cartografía climática es una herramienta indispensable para abordar estos desafíos, permitiendo la visualización espacial y temporal de variables críticas como precipitación, temperatura, humedad, salinidad y dirección del viento. Integra datos satelitales, estaciones meteorológicas y modelos predictivos, contribuyendo a diseñar respuestas adaptativas. Su aplicación prioriza la protección de servicios ecosistémicos y garantiza la sostenibilidad a largo plazo de este patrimonio natural

Behzad Ghanbarian, Andres Patrignani

In soil physics, saturated hydraulic conductivity, K_sat, is among the most important hydraulic properties with broad applications to modeling flow and transport under saturated conditions. Its accurate estimation, however, is challenging and requires precise characterization of pore space. In this study, we applied concepts of critical path analysis (CPA) to estimate K_sat from soil water retention curve. To evaluate the CPA, we used 313 undisturbed soil samples from the Kansas Mesonet database in which the value of K_sat spans over five orders of magnitude in variation. We found that the CPA estimated K_sat reasonably well with root mean square log-transformed error RMSLE = 0.87. For most samples, the predicted values were around the 1:1 line within a factor of 10 of the measurements. We also estimated K_sat using five other methods but none was more accurate than the CPA.

Diego Firmenich, Leandro Antonelli, Bruno Pazos et al.

User stories are one of the most widely used artifacts in the software industry to define functional requirements. In parallel, the use of high-fidelity mockups facilitates end-user participation in defining their needs. In this work, we explore how combining these techniques with large language models (LLMs) enables agile and automated generation of user stories from mockups. To this end, we present a case study that analyzes the ability of LLMs to extract user stories from high-fidelity mockups, both with and without the inclusion of a glossary of the Language Extended Lexicon (LEL) in the prompts. Our results demonstrate that incorporating the LEL significantly enhances the accuracy and suitability of the generated user stories. This approach represents a step forward in the integration of AI into requirements engineering, with the potential to improve communication between users and developers.

CAO Ruizhe, QIN Anzhen

【Objective】Accurate estimation of reference crop evapotranspiration (ET0) is essential for determining crop water requirements, improving irrigation efficiency and supporting sustainable water resource management, especially in regions facing water scarcity. The objective of this paper is to identify a reliable and practical model for estimating ET0 in Northern Henan Province.【Method】Daily meteorological data measured from 2021 to 2022 and numerical weather forecasts from 2023 for Xinxiang City, Henan Province, were used to develop and evaluate the following ET0 models: the Prophet model, the autoregressive integrated moving average model (ARIMA), the extreme learning machine (ELM) model, and their hybrid combinations. ET0 calculated using these models were compared with that calculated using the FAO-56 Penman-Monteith method.【Result】ET0 calculated in all models were correlated with maximum temperature, minimum temperature, solar radiation, and wind speed 2 m above the ground surface. They factors were thus selected as inputs to the models. The time-series models (Prophet and ARIMA) effectively captured seasonal variation in ET0 but gave rise to notable errors when ET0 exceeded 5.5 mm/d. The ELM model better captured the nonlinear relationship between ET0 and these meteorological factors, achieving an increase of R2 value by 11%, compared with the time-series models. The ELM-ARIMA hybrid model was more accurate than other models for calculating ET0 in medium-term (1-10 day), with its MAE, RMSE and MBE reduced by 64.5%, 72.9% and 65.6%, respectively, compared to those in the non-hybrid model; its correlation with observed ET0 was R2=0.945, the highest among all models.【Conclusion】The ELM-ARIMA hybrid model is most accurate and reliable for calculating ET0 and is recommended for use in water resource management and agricultural planning in Northern Henan Province.

O. V. Zhuravlov, A. P. Shatkovskyi, S. V. Riabkov et al.

The article presents an assessment of the accuracy of meteorological data obtained from the Visual Crossing Weather Data (VWS VCWD) virtual meteorological station and the calculated reference evapotranspiration (ETo) based on these data for the conditions of southern Ukraine. It has been established that the data on air temperature and relative humidity are obtained with high accuracy, with MAPE and RMSE errors of 4,5% and 0,94°C and 9,1% and 7,53%, respectively. Good accuracy is characteristic of dew point temperature and solar radiation, with MAPE and RMSE errors of 20,9% and 1,44 °C and 17,4% and 3,41 MJ/m²·day, respectively. Dew point temperature data can also be obtained with satisfactory accuracy depending on the observation period. The MAPE and RMSE errors for water vapor pressure deficit are 46,2% and 0,21 kPa, respectively, which corresponds to satisfactory accuracy. Depending on the observation period, water vapor pressure deficit data can also be obtained with unsatisfactory accuracy. Wind speed data at a height of 2 m, obtained with unsatisfactory accuracy, have MAPE and RMSE errors of 104,3% and 1,20 m/s, respectively. To improve the accuracy of the meteorological data obtained, correction factors were calculated, and when applied, the accuracy of all meteorological data obtained is improved. The possibility of calculating ET using data from the Visual Crossing Weather Data virtual meteorological station for the period April-September with good accuracy has been confirmed. The MAPE error was 13,7%, and the RMSE was 0.62 mm. To improve the accuracy of ET calculations in southern Ukraine, a  correction factor of 0.95 must be used. Taking this into account, the accuracy of ET calculations for the period May-August increases to 89%, and the RMSE is 0,63 mm.  The use of refined meteorological data reduces the accuracy of ET calculations by 4,8% and increases the RMSE by 0,15 mm. Based on the results of the research, a web application will be developed to calculate ET and ETc using the FAO56-RM methodology with data from VWS Visual Crossing Weather Data.

GUO Chu, WANG Danna, ZHANG Tao et al.

Based on Euler multiphase model, RNG <italic>k</italic>-<italic>ε </italic>turbulence model, and SIMPLEC algorithm, a numerical simulation of solid-liquid two-phase flow in an axial flow pump was carried out to study the pressure fluctuation characteristics of the axial flow pump when transporting a sediment-laden flow. The pressure fluctuation characteristics of the axial flow pump unit at different positions under the condition of clean water were emphasized, and the pressure pulsation characteristics with clean water medium and solid-liquid two-phase flow under the design condition were compared. The results show that the pressure pulsation at the impeller inlet and outlet of the axial flow pump unit presents obvious periodicity under the condition of clear water medium, and the amplitude increases gradually from the hub to the rim; the pulsation amplitude at the impeller outlet is less than that at the impeller inlet. The pulsation amplitude in the middle of the guide vane is smaller than that at the inlet and outlet of the impeller, and the pressure pulsation amplitude decreases first and then increases along the radial direction; the pressure pulsation amplitude at the outlet of the guide vane distributes irregularly along the radial direction. There is no obvious difference between the pressure pulsation amplitudes at the inlet of the impeller under the condition of clean water and solid-liquid two-phase flow, but the pressure pulsation waveform phase under the condition of two-phase flow lags behind about 0.04 s compared with that under the condition of clean water. The distribution law of pressure pulsation in the middle and at the outlet of the guide vane is quite different, and the amplitude of pressure pulsation is relatively large under the condition of solid-liquid two-phase flow. The vortex intensity distribution in the middle section of the guide vane is more complex than that in the clear water condition when the flow is laden with sediment, and the intensity is larger. The research results can provide some reference for the optimal design of axial flow pump units.

Y. Navidtehrani, C. Betegón, E. Martínez-Pañeda

We present a novel, generalised formulation to treat coupled structural integrity problems by combining phase field and multi-physics modelling. The approach exploits the versatility of the heat transfer equation and is therefore well suited to be adopted in commercial finite element packages, requiring only integration point-level implementation. This aspect is demonstrated here by implementing coupled, multi-variable phenomena through simple \texttt{UMAT} and \texttt{UMATHT} subroutines in the finite element package \texttt{Abaqus}. The generalised theoretical and computational framework presented is particularised to four problems of engineering and scientific relevance: thermo-mechanical fracture, hydraulic fracture, hydrogen-assisted cracking and metallic corrosion. 2D and 3D problems are considered. The results reveal a very good agreement with experimental data, and existing numerical and analytical solutions.The user subroutines developed are made freely available at https://mechmat.web.ox.ac.uk/codes.

Neagoe Angela, Tică Eliza-Isabela, Popa Bogdan et al.

Evaporation has a major significance in the water balance of a reservoir. Usually, recorded data for the evaporation on the free surface of a reservoir are not available. There are numerous empirical relationships for the assessment of the evaporation that can be implemented into the water balance equation. In this paper, for Vidraru, one of the largest reservoirs in Romania, the Hargreaves method is used to estimate the evaporation values that are compared with recorded data obtained from Meteoblue archive. Recorded precipitation and evaporation data are used in mathematical model for water balance to find the answer to the question: can the evaporation and the directly water surface rainfall be neglected in the monthly/annual water balance of a reservoir? Daily meteorological values for the minimum and maximum temperature, evaporation and precipitation measured in the Vidraru reservoir area are used in this work. The main conclusion of the paper is that although in the summer months, on the surface of the lake, the amount of water lost through the evaporation is greater than the amount of water from the precipitations, on the time horizon of one year, the two components of the water balance of the reservoir have close values. Thus, for an accurate application of the water balance equation for a reservoir, the two variables, evaporation and precipitation, can be both considered or both neglected.

Romulus Mawa Tuzingila, Lingyun Kong, Ruben Koy Kasongo

Understanding the effects of mineral composition on geomechanical characteristics is critical in order to design and optimize the hydraulic fracturing necessary for shale gas reservoir production. Fundamental information is still missing in effects of mineral content and the experimental methodologies used. This paper provided an in-depth assessment of the various experimental methodologies and their applications in the relationship between the mineralogical and geomechanical features of the shale formation. The results revealed that more brittle minerals increase their strength, but chemical reaction that creats pores decrease their strength. High content of carbonate or quartz increases a rock's brittleness, while a high content of clay increases a rock's plasticity and decreases its brittleness. As phyllosilicate content increases, the uniaxial compressive strength decreases, and this could be because phyllosilicate minerals have a weakening effect on the mineral bond. Young's modulus often climb as clay minerals decline and as silica with carbonate concentration rises, however Poisson's ratio increases in relation to an increase in clay minerals, which also increases the ductility of the reservoir shale rock. However, compared to minerals and matrix, does not significantly impact the strength of shale rock. Besides, the benefits and drawbacks of using uniaxial and triaxial compression, ultrasonic testing, and nano-indentation techniques in unconventional reservoirs were described. The findings suggest that, because of the possibility for experimental testing repeatability for increased accuracy, ultrasonic testing is the most appropriate experimental approach in the scenes of assessing static and dynamic geomechanical properties of reservoir shale rock. We suggested that numerically-based simulation of experimental techniques used for shale geomechanical evaluations and numerical modeling of heterogeneous shale rock samples will be necessary in light of the limitations faced in the applications of experimental techniques for shale geomechanical evaluation.

Jian-Yu Fu, Xiao Ge, Lei Chen et al.

To investigate the fatigue behaviour of stainless steel (SS) reinforcement, monotonic tensile and cyclic fatigue loading tests on 1.4362 duplex SS bars with diameters of 12 mm, 16 mm, and 20 mm are conducted. To keep the characteristics of reinforcement used in engineering construction, the specimens remain unprocessed. Two loading schemes for cyclic tests are considered in this work: (i) constant strain-amplitude, and (ii) variable strain-amplitude. The Ramberg-Osgood model was used to fit the experimental results. The strain-based and energy-based fatigue life equations are obtained. The strain-based fatigue life equation is compared with the present fatigue life estimation equations. Moreover, the ReinforcingSteel material model in OpenSees is calibrated with the experimental data. The results show that SS bars under cyclic experience hardening followed by softening. The bar diameter does not significantly affect the fatigue life prediction. The modified fatigue life equation suggests that SS bars have better fatigue resistance than conventional steel (CS) bars. The numerical analysis indicates that the calibrated steel material model (i.e. ReinforcingSteel) can produce a good simulation of SS bars under cyclic loading. It can improve the accuracy of numerical models of concrete components reinforced by SS bars.

Filippo A. Spinelli, Pascal Egli, Julian Nubert et al.

The precise and safe control of heavy material handling machines presents numerous challenges due to the hard-to-model hydraulically actuated joints and the need for collision-free trajectory planning with a free-swinging end-effector tool. In this work, we propose an RL-based controller that commands the cabin joint and the arm simultaneously. It is trained in a simulation combining data-driven modeling techniques with first-principles modeling. On the one hand, we employ a neural network model to capture the highly nonlinear dynamics of the upper carriage turn hydraulic motor, incorporating explicit pressure prediction to handle delays better. On the other hand, we model the arm as velocity-controllable and the free-swinging end-effector tool as a damped pendulum using first principles. This combined model enhances our simulation environment, enabling the training of RL controllers that can be directly transferred to the real machine. Designed to reach steady-state Cartesian targets, the RL controller learns to leverage the hydraulic dynamics to improve accuracy, maintain high speeds, and minimize end-effector tool oscillations. Our controller, tested on a mid-size prototype material handler, is more accurate than an inexperienced operator and causes fewer tool oscillations. It demonstrates competitive performance even compared to an experienced professional driver.

Federico Vilaseca, Santiago Narbondo, Christian Chreties et al.

RESUMENUn sólido estudio hidrológico diario es una tarea desafiante en regiones caracterizadas por una alta variabilidad hidro-climática, como Uruguay. Por esta razón, los modelos hidrológicos de base física de diferentes escalas temporales y espaciales (concentrados, semi-distribuidos y distribuidos) han pasado por un largo período de desarrollo y aplicación local. En los últimos años, los modelos basados en datos se están usando con éxito para resolver problemas hidrológicos. Hasta ahora, estos diferentes tipos de modelos se han estudiado individualmente para evaluar su capacidad para simular el proceso diario de precipitación-escorrentía. Este trabajo proporciona una profunda comparación entre un modelo agregado (GR4J), un modelo semi-distribuido (SWAT) y otro basado en datos (Random Forest (RF)) para simular el proceso diario de precipitación-escorrentía de dos cuencas hidrográficas ubicadas en Uruguay (una con reservorio y la otra sin). El rendimiento de cada modelo se analizó comparando numéricamente y gráficamente el caudal observado versus el simulado en términos de correspondencia temporal y cuantiles. En general, RF presenta un mejor rendimiento en comparación con los otros modelos físicamente basados. Sin embargo, carece de la capacidad de generalización que caracterizó a los otros dos enfoques. GR4J y SWAT logran un desempeño similar en nuestros casos de estudio.

Tao Ni, Francesco Pesavento, Mirco Zaccariotto et al.

This paper presents a hybrid modeling approach for simulating hydraulic fracture propagation in saturated porous media: ordinary state-based peridynamics is used to describe the behavior of the solid phase, including the deformation and crack propagation, while FEM is used to describe the fluid flow and to evaluate the pore pressure. Classical Biot poroelasticity theory is adopted. The proposed approach is first verified by comparing its results with the exact solutions of two examples. Subsequently, a series of pressure- and fluid-driven crack propagation examples are solved and presented. The phenomenon of fluid pressure oscillation is observed in the fluid-driven crack propagation examples, which is consistent with previous experimental and numerical evidences. All the presented examples demonstrate the capability of the proposed approach in solving problems of hydraulic fracture propagation in saturated porous media.

A. Goerlinger, M. Baudoin, F. Zoueshtiagh et al.

We report spontaneous oscillations of circular hydraulic jumps created by the impact of a submillimeter water jet on a solid disk. The jet flow rate is shown to condition the occurrence of the oscillations while their period is independent of this parameter. The period, however, varies linearly with the disk radius. This dependency is rationalized by investigating surface gravity wave modes in the cavity formed by the disk. We show that the jump oscillation frequency systematically matches one of the surface wave disk-cavity eigenfrequencies, leading to the conclusion that the oscillations are self-induced by the interaction between the jump and surface wave eigenmodes.

Yongqi Dong, Kejia Chen, Zhiyuan Ma

Condition-based maintenance is becoming increasingly important in hydraulic systems. However, anomaly detection for these systems remains challenging, especially since that anomalous data is scarce and labeling such data is tedious and even dangerous. Therefore, it is advisable to make use of unsupervised or semi-supervised methods, especially for semi-supervised learning which utilizes unsupervised learning as a feature extraction mechanism to aid the supervised part when only a small number of labels are available. This study systematically compares semi-supervised learning methods applied for anomaly detection in hydraulic condition monitoring systems. Firstly, thorough data analysis and feature learning were carried out to understand the open-sourced hydraulic condition monitoring dataset. Then, various methods were implemented and evaluated including traditional stand-alone semi-supervised learning models (e.g., one-class SVM, Robust Covariance), ensemble models (e.g., Isolation Forest), and deep neural network based models (e.g., autoencoder, Hierarchical Extreme Learning Machine (HELM)). Typically, this study customized and implemented an extreme learning machine based semi-supervised HELM model and verified its superiority over other semi-supervised methods. Extensive experiments show that the customized HELM model obtained state-of-the-art performance with the highest accuracy (99.5%), the lowest false positive rate (0.015), and the best F1-score (0.985) beating other semi-supervised methods.

Masod Sadipour, Mohammad Masoud Momeni, Majid Soltani

In this study, a computational simulation is employed to place two essential parameters, the permeability of vessels and hydraulic conductivity, under assessment. These parameters impact the movement of drug particles through vessels, and normal and tumoral tissue to examine the concentration of nanoparticles, interstitial pressure, and velocity. To provide a geometric model detailing the capillary network under normal and tumoral tissue conditions, the geometry is extracted via real image processing. Subsequently, the real conditions were considered to solve the equations pertaining to drug transport and intravascular and interstitial flows in the tissue. The results showed that an increase in permeability and hydraulic conductivity leads to an increase in drug concentration in the tumor. Finally, Methotrexate drug has the most effect in the treatment of tumors. Overall, the computational model for anti-cancer delivery provides a powerful tool for understanding and optimizing drug delivery strategies for the treatment of cancer.

Yun-zhi Tan, Xun Xu, H. Ming et al.

Abstract Buffer is the main component of the engineering barrier system (EBS) in high-level radioactive waste (HLW) disposal repository. Reliable EBS performance assessment requires the delicate numerical modeling of the buffer layer. This study presents the sensitivity analysis of thermal and hydraulic parameters in the repository by using COMSOL Multiphysics, and proposes a new buffer barrier with double layers consisting of buffer-A with higher heat conductivity closing to the HLW canister and buffer-B with lower hydraulic conductivity closing to surrounding rock. From results of the sensitivity analysis, it is concluded that the thermal conductivity and hydraulic conductivity are high sensitivity parameters, and specific heat capacity, water density and water compressibility are low sensitivity parameters. The increase of the thermal conductivity in buffer-A results in effectively reducing the peak temperature in the buffer. Therefore, the double-layer buffer is advantageous and effective for improving the repository safety.

Hao Li, Xiaohong Ding, Dalei Jing et al.

Abstract In order to study the relationship between the thermal-hydraulic performances and the layout of cooling channels designed by topology optimization from the engineering perspective, two types of topology optimization problems are studied. The first is the flow distribution problem that is to achieve the minimization of power dissipation under the flow rate quality constraints, and the second is the heat exchange maximization problem that is to achieve the optimal thermal performances under the constant input power constraint. Then the optimized heat sinks together with a conventional S-shaped channel heat sinks are manufactured and their thermal-hydraulic performances are investigated both numerically and experimentally. The results reveal that the flow distribution design can provide the lowest hydraulic resistance while the heat exchange maximization design can keep the thermal resistance to a minimum. The proposed design method can be used as a tool to provide cooling solutions to the thermal management of high heat flux electronic components.

Bowen Wei, Liangjie Chen, Huokun Li et al.

Abstract The traditional statistical model of concrete dam's displacement monitoring is used widely in hydraulic engineering. However, the forecasting precision of the conventional calculation model is poor due to the antiquated method of information mining and weak generalization capacity. Furthermore, the uncertain chaos effect implied in residual sequence is also intractable for modeling. In consideration of the nonlinearity, time variation, and unsteadiness of the chaotic characteristics of a dam time series, multiscale wavelet technology is used to decompose and reconstruct the residuals of multiple regression models. The fitting prediction of the low-frequency autocorrelation part is completed through the linear training ability of the autoregressive integrated moving average (ARIMA) model, and the support vector machine (SVM) regression model is constructed to optimize and process the nonlinear high-frequency signal. Then, a combined forecasting model for concrete dam's displacement based on signal residual amendment is established. The analysis of an engineering example indicates that the combined model built in this study can identify the time–frequency nonlinear characteristics of the prototype monitoring signal well, thus improving its fitting precision, antinoise ability, and robustness. In addition, the combined mathematical model established in this study is improved and developed for application to the prediction analysis of the effect quantities of other hydraulic structures.

Dashan Yang, C. Gu, Yantao Zhu et al.

Dams are the main water retaining structures in the hydraulic engineering field. Safe operations of dams are important foundations to ensure the hydraulic functionalities of these engineering structures. Deformation, as the most intuitive feature of the dams’ operation behaviors, can comprehensively reflect the dam structural states. In this case, the analysis of the dam prototype deformation data and the establishment of a real-time prediction model become frontier research contents in the field of dam safety monitoring. Considering the multi-nonlinear relationships between dam deformation and relative influential factors as well as the time lag effect of these influential factors, this article adopts long-short-term memory (LSTM) network algorithm in deep learning to deal with the long-term dependence existing in dam deformation and explore the deformation law. The method proposed in this work can effectively avoid the gradient disappearance and gradient explosion problems by using the recurrent neural network (RNN). In addition, this work adopts the Attention mechanism to screen the information that has significant influence on deformation, combining the Adam optimization algorithm that has high calculation efficiency and low memory requirement to improves the learning accuracy and speed of the LSTM. The model overfitting is avoided by applying the Dropout mechanism. The effectiveness of this proposed model in studing the long time series deformation prediction of concrete dams is confirmed by case studies, whose MSE (mean square error) and other 4 error indexes can be reduced.