Strain Virtual Sensing for Structural Health Monitoring under Variable Loads

Virtual sensing is the process of using available data from real sensors in combination with a model of the system to obtain estimated data from unmeasured points. In this article, different strain virtual sensing algorithms are tested using real sensor data, under unmeasured different forces applied in different directions. Stochastic algorithms (Kalman filter and augmented Kalman filter) and deterministic algorithms (least-squares strain estimation) are tested with different input sensor configurations. A wind turbine prototype is used to apply the virtual sensing algorithms and evaluate the obtained estimations. An inertial shaker is installed on the top of the prototype, with a rotational base, to generate different external forces in different directions. The results obtained in the performed tests are analyzed to determine the most efficient sensor configurations capable of obtaining accurate estimates. Results show that it is possible to obtain accurate strain estimations at unmeasured points of a structure under an unknown loading condition, using measured strain data from a set of points and a sufficiently accurate FE model as input and applying the augmented Kalman filter or the least-squares strain estimation in combination with modal truncation and expansion techniques.The research presented in this work has been carried out by Ikerlan Research Center, a center certificated as “Centro de Excelencia Cervera”. This work has been funded by CDTI, dependent on the Spanish Ministerio de Ciencia e Innovación, through the “Ayudas Cervera para centros tecnológicos 2019” program, project MIRAGED with expedient number CER-20190001

Eco-friendly pesticide based on peppermint oil nanoemulsion: preparation, physicochemical properties, and its aphicidal activity against cotton aphid

Using organic insecticides including plant oils, it is possible to design a new perspective for the control of insect pests. In this research, nanoemulsion formulations of Mentha piperita, wild-type essential oil (EO) were prepared utilizing high-energy ultrasonication process. Physicochemical properties of nanoemulsions were precisely studied by measurement various parameters including pH, viscosity, conductivity, and zeta potential. Experimental design by the aid of response surface methodology (RSM) was used to highlight the physicochemical roles of EO percentage (1% to 5% (v/v)) and surfactant concentration (3% to 15% (v/v)) for achieving minimum droplet diameter with high physical stability. The nanoemulsion formulations were then characterized using dynamic light scattering, transmission electron microscopy, and optical clarity. Afterward, an appropriate model between the variable factors (EO percentage and surfactant concentration) and the response (hydrodynamic particle size) was statistically developed. Under the optimum conditions, nanoemulsion with hydrodynamic particle size less than 10 nm with high physical stability is obtainable. Bioassay experiments were carried out to elucidate the effects of nanoemulsion on the cotton aphid. Synthesized nanoemulsion formulations showed relatively high contact toxicity (average value of LC50 was about 3879.5 +/- 16.2 mu l a.i./L) against the pest. On the basis of the obtained results, prepared nanoemulsion using M. piperita is potentially applicable as organic insecticides against cotton aphid

SIMULATION OF LIQUID FUEL ATOMIZATION IN AN INDUSTERIAL SPRAY NOZZLE OF A POWERPLANT BOILER

ABSTRACT In this study, the liquid fuel atomization in the injector nozzle of the combustion chamber of a powerplant boiler is numerically simulated. The atomization of a liquid fuel injector is characterized by drop size distribution of the nozzle. This phenomenon plays an important role in the performance of the combustion chamber such as the combustion efficiency, and the amount of soot and NOx formation inside the boiler. The injector nozzle, considered in this study, belongs to a powerplant boiler where the liquid fuel is atomized using a high pressure steam. First, the geometric characteristics of the injector are carefully analyzed using a wire-cut process and a CAD model of the nozzle is created. Next, one of the nozzle orifices and the atomization zone where the high pressure steam meets the liquid fuel is recognized. The computational domain is extended long enough to cover the whole atomization zone up to the end of the orifice. The flow governing equations are the continuity and Navier-Stokes equations. For tracking the liquid/gas interface, the Volume-ofFluid (VOF) method along with Youngs' algorithm for geometric reconstruction of the free surface is used. The simulation results show the details of the liquid and steam flow inside the nozzle including velocity distribution and shape of the liquid/gas interface. It is found that the liquid breakup to ligaments and the atomization of liquid to droplets do not occur inside the nozzle orifice. A liquid jet with certain cross sectional shape leaves the orifice surrounded by a high speed steam. The numerical model provides the shape of the liquid jet, and the steam and fuel velocity distributions at the exit of the nozzle orifice. These parameters are then correlated to the final drop size distribution using analytical/experimental correlations available in literature