Optimal predictive control of water transport systems: Arrêt-Darré/Arros case study

This paper proposes the use of predictive optimal control as a suitable methodology to manage efficiently transport water networks. The predictive optimal controller is implemented using MPC control techniques. The Arrêt-Darré/Arros dam-river system located in the Southwest region of France is proposed as case study. A high-fidelity dynamic simulator based on the full Saint-Venant equations and able to reproduce this system is developed in MATLAB/SIMULINK to validate the performance of the developed predictive optimal control system. The control objective in the Arrêt-Darré/Arros dam-river system is to guarantee an ecological flow rate at a control point downstream of the Arrêt-Darré dam by controlling the outflow of this dam in spite of the unmeasured disturbances introduced by rainfalls incomings and farmer withdrawals

Applying rotorcraft modelling technology to renewable energy research

The perceived need to reduce mankind's impact on the global climate motivates towards a future society in which a significant proportion of its energy needs will be extracted from the winds and the tides of the planet. This paper shows several examples of the application of Brown's Vorticity Transport Model, originally developed to perform simulations of helicopter aeromechanics and wake dynamics, to the analysis of the performance of renewable energy devices and their possible impact on the environment. Prediction of the loading on wind turbines introduces significant additional challenges to such a model, including the need to account fully for the effects of radial flow on blade stall. The wake-mediated aerodynamic interactions that occur within a wind farm can reduce its power output significantly, but this problem is very similar to that where the aerodynamic unsteadiness of the coupled wake of the main and tail rotors of a helicopter can result in significantly increased pilot workload. The helicopter-related problem of brownout, encountered during operations in desert conditions, has its analogue in the entrainment of sediment into the wakes of tidal turbines. In both cases it may be possible to ameliorate the influence of the rotor on its environment by careful and well-informed design. Finally, calculations of the distortion and dispersal of the exhaust plumes of a helicopter by the wake of its rotor allow insight into how wind turbines might interfere with the dispersal of pollutants from nearby industrial sites. These examples show how cross-disciplinary information transfer between the rotorcraft field and the renewable energy community is helping to develop the technologies that will be required by our future society, as well as helping to understand the environmental issues that might need to be faced as these technologies become more prevalent

A high-performance computing framework for Monte Carlo ocean color simulations

This paper presents a high-performance computing (HPC) framework for Monte Carlo (MC) simulations in the ocean color (OC) application domain. The objective is to optimize a parallel MC radiative transfer code named MOX, developed by the authors to create a virtual marine environment for investigating the quality of OC data products derived from in situ measurements of in-water radiometric quantities. A consolidated set of solutions for performance modeling, prediction, and optimization is implemented to enhance the efficiency of MC OC simulations on HPC run-time infrastructures. HPC, machine learning, and adaptive computing techniques are applied taking into account a clear separation and systematic treatment of accuracy and precision requirements for large-scale MC OC simulations. The added value of the work is the integration of computational methods and tools for MC OC simulations in the form of an HPC-oriented problem-solving environment specifically tailored to investigate data acquisition and reduction methods for OC field measurements. Study results highlight the benefit of close collaboration between HPC and application domain researchers to improve the efficiency and flexibility of computer simulations in the marine optics application domain. (C) 2016 The Authors. Concurrency and Computation: Practice and Experience Published by John Wiley & Sons Ltd.Portuguese Foundation for Science and Technology (FCT/MEC) [PEst-OE/EEI/UI0527/2011]; ESA [22576/09/I-OL, ARG/003-025/1406/CIMA]; NOVA LINCS [UID/CEC/04516/2013]info:eu-repo/semantics/publishedVersio

An acoustic view of ocean mixing

Knowledge of the parameter K (turbulent diffusivity/"mixing intensity") is a key to understand transport processes of matter and energy in the ocean. Especially the almost vertical component of K across the ocean stratification (diapycnal diffusivity) is vital for research on biogeochemical cycles or greenhouse gas budgets. Recent boost in precision of water velocity data that can be obtained from vessel-mounted acoustic instruments (vmADCP) allows identifying ocean regions of elevated diapycnal diffusivity during research cruises - in high horizontal resolution and without extra ship time needed. This contribution relates acoustic data from two cruises in the Tropical North East Atlantic Oxygen Minimum Zone to simultaneous field observations of diapycnal diffusivity: pointwise measurements by a microstructure profiler as well as one integrative value from a large scale Tracer Release Experiment