Copernicus satellites for supporting irrigation and water management in Australia: the COALA H2020 Project.

<p>COALA is a project funded by the Horizon 2020 program of the European Union with the aim of developing Copernicus Earth Observation-based information services for irrigation and nutrient management in Australia, building on consolidated experience of past EU projects and existing operational irrigation advisory services. Earth Observation-based services can provide “diagnostic” data and information relevant for integrated input management of irrigation water and nutrients, from subplot level to irrigation scheme or river basin levels.</p><p>COALA, started on January 2020, is developing Copernicus-based information service for the Australian agricultural systems, based on strong collaboration with Academic Australian institutions and business players. COALA services will provide to farmers, irrigation organisation and basin authorities information about crops development, water and nutrient status, irrigated areas by means of innovative algorithms based on Sentinel Earth Observation data, which will be accessed by means of the new cloud platforms (DIAS) of Copernicus. In-situ and other source of data, such as ground soil moisture probes, meteorological stations and Numerical Weather Prediction models, will be used to improve the information provided to the final users.</p><p>The advancements beyond the state of art of COALA methodologies for managing irrigation are:</p><p>COALA will demonstrate that Copernicus data and new DIAS infrastructure can greatly improve the availability of a multi-scale information product shared by the different levels of users. The innovative approach achieves a "converging loop procedure" between water authority, irrigation infrastructure operation and farmers, enabling transparency in all the decision taken at all levels and improving the accuracy of estimation of actual water use.</p><p><strong>https://www.coalaproject.eu/</strong></p>

0352 A Large-Scale EEG Study at Home to Objectivise Effects of Ageing on Slow Wave Sleep and Process S

Introduction Several studies have shown slow wave sleep (SWS) is altered with ageing. However, most of these studies have been conducted in-lab and usually over a single night. In this study, we assessed the evolution of process S with ageing by analysing the dynamics of endogenous and auditory-evoked slow waves in a large population. Methods 300 participants (200 M, 20 - 70 y.o.) were selected from volunteers users wearing a sleep headband for at least 3 nights, meeting the criteria of high signal quality and having no subjective sleep complaints nor being shift-workers. The Dreem headband is a connected device able to monitor EEG signals as well as pulse and movement and performs sleep staging in real-time automatically. Slow waves were detected as large negative deflections on the filtered EEG signals during NREM sleep. The auditory evoked slow waves were done using a previously validated closed-loop procedure. Results In our study, age was strongly correlated with N3 sleep duration (r=-0.34, p<0.0001), slow wave amplitude (r=-0.25, p<0.0001), and slow wave density (r=-0.40, p<0.0001). The slope of the slow wave activity, representing the process S here, was significantly decreased (r=-0.32, p<0.0001). This effect was mainly due to changes in the density of slow waves in the first 2 hours of sleep (r=-0.41, p<0.0001). Finally, our results show a decrease in the probability of auditory evoked slow waves (r=-0.43, p<0.0001). Conclusion These results confirmed the in-lab studies showing a heterogeneous alteration of homoeostatic process S with age, as well as a general decrease of slow wave occurrences, that is observed in parallel of a decrease of the probability of evoking slow waves, suggesting a global change in the system responsible for slow wave generation. Support This study was supported by Dreem sas and ANR, FLAG ERA 2015, HPB SLOW-Dyn

MODEL PREDICTIVE CONTROL OF A HYDRAULIC ACTUATOR IN TORQUE APPLYING SYSTEM OF A MECHANICALLY CLOSED-LOOP TEST RIG FOR THE HELICOPTER GEARBOX

Transmission health is an important factor in safety and maintenance costs in industries, so construction of test rigs for testing high-powered gearboxes under different operating conditions of helicopters is required. The studied test rig, which is developed at Sharif University of Technology branch of ACECR (Academic Centre of Education, Culture and Research) is mainly used for testing high-powered gearboxes through a mechanically closed-loop procedure. For providing a variety of speeds and torques in test rigs, torque applying system is required. According to generation of higher forces, reduced size of equipment and accurate positioning, electro hydraulic actuators (EHAs) are used for applying torques for planetary gearboxes of this test rig. Due to the importance of applying accurate torques in evaluation of the gearbox performance, first an accurate model of EHA is derived, which captures the system dynamics using system identification method with low consumed time and simple relations. After that, a type of model predictive controller called dynamic matrix controller is proposed for controlling EHA under determined requirements. Then, the performance of proposed controller under normal conditions as well as in presence of disturbance is investigated. The results show a good tracking of controller for various reference inputs in different conditions. Moreover, the performance of the proposed controller is compared with the performance of classical proportional-integral-derivative (PID) controller and superior characteristics of the proposed controller is concluded.

Design and Implementation of Cuk Converter for Power Factor Correction of PMBLDC Motor Drive

The present project relates to designing of a cuk converter for improving power factor at AC main supply for the PMBLDC motor. In the work an electronic communication technique is used as the motor requires a distortion less controlled DC voltage served to Voltage Source Inverter. The main reason to implement the project is to achieve betterment in the performance of the motor. The work overcomes the problems associated with less power factor of AC main supply. The project helps in eliminating current harmonics generally appears at source input supply by employing a closed loop procedure. A converter called cuk converter and DBR are used for DC to DC and for AC to DC conversion respectively. The analysis of power quality is observed by using a software MATLAB/Simulink and implementation on hardware is also done to verify the analysis

Uncertainty Analysis for Time- and Space-Dependent Responses With Random Variables

The performance of a product varies with respect to time and space if the associated limit-state function involves time and space. This study develops an uncertainty analysis method that quantifies the effect of random input variables on the performance (response) over time and space. The combination of the first order reliability method (FORM) and the second-order reliability method (SORM) is used to approximate the extreme value of the response with respect to space at discretized instants of time. Then the response becomes a Gaussian stochastic process that is fully defined by the mean, variance, and autocorrelation functions obtained from FORM and SORM, and a sequential single loop procedure is performed for spatial and random variables. The method is successfully applied to the reliability analysis of a crank-slider mechanism, which operates in a specified period of time and space.

Uncertainty Analysis for Time- and Space-Dependent Responses With Random Variables

The performance of a product varies with respect to time and space if the associated limit-state function is a function of time and space. This study develops an uncertainty analysis method that quantifies the effect of random input variables on the performance (response) over time and space. The first order reliability method (FORM) is used to approximate the extreme value of the response with respect to space at discretized instants of time. Then the response becomes a Gaussian stochastic process that is fully defined by the mean, variance, and autocorrelation functions obtained from FORM, where a sequential single loop procedure is performed for spatial and random variables. The method is successfully applied to the reliability analysis of a crank-slider mechanism, which operates in a specified period of time and space.

A Single-Loop Kriging Surrogate Modeling for Time-Dependent Reliability Analysis

Current surrogate modeling methods for time-dependent reliability analysis implement a double-loop procedure, with the computation of extreme value response in the outer loop and optimization in the inner loop. The computational effort of the double-loop procedure is quite high even though improvements have been made to improve the efficiency of the inner loop. This paper proposes a single-loop Kriging (SILK) surrogate modeling method for time-dependent reliability analysis. The optimization loop used in current methods is completely removed in the proposed method. A single surrogate model is built for the purpose of time-dependent reliability assessment. Training points of random variables and over time are generated at the same level instead of at two separate levels. The surrogate model is refined adaptively based on a learning function modified from time-independent reliability analysis and a newly developed convergence criterion. Strategies for building the surrogate model are investigated for problems with and without stochastic processes. Results of three numerical examples show that the proposed single-loop procedure significantly increases the efficiency of time-dependent reliability analysis without sacrificing the accuracy.