AIMC Topic: Water Movements

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A biomimetic underwater vehicle actuated by waves with ionic polymer-metal composite soft sensors.

Bioinspiration & biomimetics
The ionic polymer-metal composite (IPMC) is a soft material based actuator and sensor and has a promising potential in underwater application. This paper describes a hybrid biomimetic underwater vehicle that uses IPMCs as sensors. Propelled by the en...

Modeling total phosphorus removal in an aquatic environment restoring horizontal subsurface flow constructed wetland based on artificial neural networks.

Environmental science and pollution research international
A horizontal subsurface flow constructed wetland (HSSF-CW) was designed to improve the water quality of an artificial lake in Beijing Wildlife Rescue and Rehabilitation Center, Beijing, China. Artificial neural networks (ANNs), including multilayer p...

Fish locomotion: recent advances and new directions.

Annual review of marine science
Research on fish locomotion has expanded greatly in recent years as new approaches have been brought to bear on a classical field of study. Detailed analyses of patterns of body and fin motion and the effects of these movements on water flow patterns...

Spatiotemporal variations in Pearl River plume dispersion over the last decade based on VIIRS-derived sea surface salinity.

Marine pollution bulletin
A river plume indicates the dispersion and transport path of pollutants from runoff, monitoring the spatiotemporal variation of river plume distribution from space is crucial for marine environmental governance. This study focuses on the Pearl River ...

Spectral physics-informed neural network for transient pipe flow simulation.

Water research
Accurate wave propagation models are essential for effective monitoring and automated localization in water supply pipelines. The recently-established Physics-Informed Neural Networks (PINNs) can enhance the wave analysis and reduce uncertainties by ...

A fuzzy TOPSIS-based approach for prioritizing low-impact development methods in high-density residential areas.

Water science and technology : a journal of the International Association on Water Pollution Research
The study successfully implemented six low-impact development (LID) methods to manage surface runoff in urban areas: green roof, infiltration trench, bio retention cell, rain barrel, green roof combined with infiltration trench, and rain barrel combi...

Enhancing rainfall-runoff model accuracy with machine learning models by using soil water index to reflect runoff characteristics.

Water science and technology : a journal of the International Association on Water Pollution Research
The advancement of data-driven models contributes to the improvement of estimating rainfall-runoff models due to their advantages in terms of data requirements and high performance. However, data-driven models that rely solely on rainfall data have l...

Machine learning approaches for adequate prediction of flow resistance in alluvial channels with bedforms.

Water science and technology : a journal of the International Association on Water Pollution Research
In natural rivers, flow conditions are mainly dependent on flow resistance and type of roughness. The interactions among flow and bedforms are complex in nature as bedform dynamics primarily regulate the flow resistance. Manning's equation is the mos...

Hybrid wavelet-gene expression programming and wavelet-support vector machine models for rainfall-runoff modeling.

Water science and technology : a journal of the International Association on Water Pollution Research
It is critical to use research methods to collect and regulate surface water to provide water while avoiding damage. Following accurate runoff prediction, principled planning for optimal runoff is implemented. In recent years, there has been an incre...

Predictive models for wastewater flow forecasting based on time series analysis and artificial neural network.

Water science and technology : a journal of the International Association on Water Pollution Research
Wastewater flow forecasting is key for proper management of wastewater treatment plants (WWTPs). However, to predict the amount of incoming wastewater in WWTPs, wastewater engineers face challenges arising from numerous complexities and uncertainties...