Eastern Pacific Emitted Aerosol Cloud Experiment

Aerosol–cloud–radiation interactions are widely held to be the largest single source of uncertainty in climate model projections of future radiative forcing due to increasing anthropogenic emissions. The underlying causes of this uncertainty among modeled predictions of climate are the gaps in our fundamental understanding of cloud processes. There has been significant progress with both observations and models in addressing these important questions but quantifying them correctly is nontrivial, thus limiting our ability to represent them in global climate models. The Eastern Pacific Emitted Aerosol Cloud Experiment (E-PEACE) 2011 was a targeted aircraft campaign with embedded modeling studies, using the Center for Interdisciplinary Remotely-Piloted Aircraft Studies (CIRPAS) Twin Otter aircraft and the research vessel Point Sur in July and August 2011 off the central coast of California, with a full payload of instruments to measure particle and cloud number, mass, composition, and water uptake distributions. EPEACE used three emitted particle sources to separate particle-induced feedbacks from dynamical variability, namely 1) shipboard smoke-generated particles with 0.05–1-μm diameters (which produced tracks measured by satellite and had drop composition characteristic of organic smoke), 2) combustion particles from container ships with 0.05–0.2-μm diameters (which were measured in a variety of conditions with droplets containing both organic and sulfate components), and 3) aircraft-based milled salt particles with 3–5-μm diameters (which showed enhanced drizzle rates in some clouds). The aircraft observations were consistent with past large-eddy simulations of deeper clouds in ship tracks and aerosol– cloud parcel modeling of cloud drop number and composition, providing quantitative constraints on aerosol effects on warm-cloud microphysics.

The Study of Collaborative Design System Based on Android

With the popularization of the modern smart mobile devices and the embedded graphic program method, co-design in a mobile phone or tablet PC may be a possible technique. Although the embedded modeling software still not very commonly used, 3D graphics processing capabilities of embedded systems provided an environment for viewing 3D product model on mobile devices. In order to make the product of design and manufacture more convenient and meet market demand, the study designed a kind of co-design system software on android intelligent device. This paper is based on the use of intelligent mobile devices into a mechanical and electronic product collaborative design system.

"Scale oriented" embedded modeling of the North-Western Mediterranean in the frame of MFSTEP

An embedded forecasting system was developed for the North-Western Mediterranean including a regional model and a coastal model of the Gulf of Lion. The system is based on the Symphonie hydrodynamic free surface model and on the variational initialization and forcing platform VIFOP. It was shown that a pre-modeling period of 7 days before beginning the forecast allows the growth of the small scales. The embedded forecasts have been compared to the MFS observing system. It was basically found that in the North-Western Mediterranean, the MFS basin-scale model and thus the regional model forecasts are characterized by large negative biases of salinity in the first 100 m under the surface leading thus to too light subsurface waters. The underestimation of temperature by the regional model just below the surface and its overestimation at 30 m deep can be associated to an overestimation of the turbulent mixing. The regional and coastal models allow to represent a number of processes especially those induced by the wind as coastal upwelling under stratified conditions, dense water formation over the Gulf of Lion shelf, deep mixing in the convection zone or influence on the Northern Current penetration in the Gulf of Lion.

Rotor Transverse Crack Detection and Diagnosis Using Embedded Modeling

This study proposes an embedded modeling methodology for identifying the crack-induced local stiffness reduction in a shaft from its horizontal and vertical vibrations. An embedded model integrating a dynamic model of the rotor system, and the unknown local stiffness reduction in the form of a universal function approximator i.e., neural network, is established. As a FEM model, it can describe rotors of complex geometry. A solution method is then established to identify the local stiffness reduction of the shaft due to a crack. Subsequently, a method is then used to find the location and size of the crack along the shaft. Simulated studies were conducted to demonstrate that the crack induced stiffness reduction of a Jeffcott rotor system can be identified, and the location, size and shape of the crack can be estimated by the proposed method with high level of accuracy.

Gear Fatigue Crack Size Estimation Using Embedded Modeling

This paper describes an embedded modeling methodology for identifying gear meshing stiffness from measured gear angular displacement or transmission error (which is the difference between where the gear tooth is physically and where it should be if the gear was perfect). An embedded model integrating a physical based model of the gearbox and a parametric representation, in the form of truncated Fourier series, of meshing stiffness is established. A solution method is then used to find the meshing stiffness that minimizes the discrepancy between model output and the measured output. Furthermore, an algorithm is also developed to estimate the size of tooth crack from identified meshing stiffness. Both simulation and experimental studies were conducted to evaluate if identified tooth meshing stiffness can reveal a tooth crack effectively, and if the crack size can be estimated with adequate level of accuracy.