Integrated water resource management in the Segura Hydrographic Basin: An artificial intelligence approach.

Managing resources effectively in uncertain demand, variable availability, and complex governance policies is a significant challenge. This paper presents a paradigmatic framework for addressing these issues in water management scenarios by integrating advanced physical modelling, remote sensing techniques, and Artificial Intelligence algorithms. The proposed approach accurately predicts water availability, estimates demand, and optimizes resource allocation on both short- and long-term basis, combining a comprehensive hydrological model, agronomic crop models for precise demand estimation, and Mixed-Integer Linear Programming for efficient resource distribution.

A Cyber-Physical Data Collection System Integrating Remote Sensing and Wireless Sensor Networks for Coffee Leaf Rust Diagnosis.

Coffee Leaf Rust (CLR) is a fungal epidemic disease that has been affecting coffee trees around the world since the 1980s. The early diagnosis of CLR would contribute strategically to minimize the impact on the crops and, therefore, protect the farmers' profitability. In this research, a cyber-physical data-collection system was developed, by integrating Remote Sensing and Wireless Sensor Networks, to gather data, during the development of the CLR, on a test bench coffee-crop.

Multiscale Simulation Platform Linking Lithium Ion Battery Electrode Fabrication Process with Performance at the Cell Level.

A novel multiscale modeling platform is proposed to demonstrate the importance of particle assembly during battery electrode fabrication by showing its effect on battery performance. For the first time, a discretized three-dimensional (3D) electrode resulting from the simulation of its fabrication has been incorporated within a 3D continuum performance model. The study used LiNiCoMnO as active material, and the effect of changes of electrode formulation is explored for three cases, namely 85:15, 90:10, and 95:5 ratios between active material and carbon-binder domains.

Diagnosis and optimization of WWTPs using the PWM library: full-scale experiences.

Given the shift in perception of wastewater treatment plants as water resource recovery facilities, conventional mathematical models need to be updated. The resource recovery perspective should be applied to new processes, technologies and plant layouts. The number and level of models proposed to date give an overview of the complexity of the new plant configurations and provides a wide range of possibilities and process combinations in order to construct plant layouts.

Lessons learnt from the application of a multi-variable controller for nitrogen removal in the Mekolalde wastewater treatment plant: good simulation practices in control.

Although often perceived as tools for use by scientists, mathematical modelling and simulation become indispensable when control engineers have to design controllers for real-life wastewater treatment plants (WWTPs). Nonetheless, the design of effective controllers in the wastewater domain using simulations requires effects, such as the nonlinearity of actuators, the time response of sensors, plant model uncertainties, etc. to have been reproduced beforehand.