The pattern determination of sea surface temperature distribution and chlorophyll a in the southern Caspian Sea using SOM model

Remote sensing has changed modern oceanography by proving synoptic periodic data which can be processed. Since the satellite data are usually too much and nonlinear, in most cases, it is difficult to distinguish the patterns from these images. In fact, SOM (Self-Organizing Maps) model is a type of ANN (Artificial Neural Network) that has the ability to distinguish the efficient patterns from the vast complex of satellite data. In this study, the sea surface temperature data and chlorophyll a related to a part of south Caspian Sea were investigated weekly by NOAA satellite for three years (2003–2005) and the annual and seasonal patterns were extracted (elicited) with their relative frequency using the SOM model. In all patterns the Caspian Sea coast has the highest chl-a and when you go away from the shore the rate decreases and when you approach to the middle parts the chl-a is of the least proportion on the sea surface

Re-analysis of the “Akron” Airship Pressure Data to Design Pressure Measurement Experiments on an Underwater Vehicle

Pressure experimental data from NACA tests on the airship “Akron” were reanalysed in this study. The pressure distribution over the bare hull of the airship were presented by using 3D pressure surfaces and 2D pressure contours for different pitch angles. By integration of the normal pressures at each panel over the bare hull of the airship, the axial and normal forces and the pitching moment exerted on the hull were derived. The paper has a brief introduction on how to use this re-analysis of the old experiment data to plan pressure-measurement experiments on an underwater vehicle

Response surface models for the hydrodynamic loads measured on slender underwater vehicles during pure yaw manoeuvres

Experiments were performed at the NRC-IOT with the bare hull of a full-scale, slender, body-of-revolution underwater vehicle of five different lengths, using an internal three-component balance and a planar motion mechanism (PMM). The experiments included resistance, static yaw, dynamic sway and yaw, and, circular arc runs. The data from the pure yaw (zigzag) captive manoeuvring tests were used to develop regression equations in the form of Response Surface Models (RSMs) for the hydrodynamic loads versus manoeuvre inputs. A sample application of the RSMs is illustrated in comparison with sea-trials data from the underwater vehicle ?MUN Explorer?.NRC publication: Ye

Resistance and static yaw experiments on the underwater vehicle Phoenix: modelling and analysis, utilizing statistical design of experiments methodology

This research is focused on the hydrodynamic behaviour of a series of hull forms for an underwater vehicle, which includes a range of length-to-diameter ratios. Experimental data were gathered for several standard manoeuvring experiments and a reverse Design Of Experiment (DOE) was applied to the available data. From the DOE point of view, the effects of the main factors in each type of experiment were studied and an appropriate Response Surface Model (RSM) was fitted to the data. The developed empirical model is very useful in predicting the non-dimensional hydrodynamic force and moment coefficients, which is a major step in simulating the motion of an underwater vehicle.Peer reviewed: YesNRC publication: Ye