Regional empirical algorithm for an improved retrieval of chlorophyll a concentrations in the Black Sea using Sentinel 3 ocean color data

<p>The Black Sea is an extraordinarily complex water body for ocean color remote sensing, as it belong to Case 2 waters, which are characterized by relatively high absorption by Colored Dissolved Organic Matter (CDOM) while the concentration of non-pigmented particulate matter does not co-vary in a predictable manner with chlorophyll <em>a</em> . The optical complexity of the Black Sea is the reason why the standard bio-optical algorithms developed for Case 1 waters, are the source of large uncertainties (of the order of hundreds of percent) of chlorophyll <em>a</em> concentration in the coastal and shelf regions. In the framework of ESA contract “BIO-OPTICS FOR OCEAN COLOR REMOTE SENSING OF THE BLACK SEA - Black Sea Color” we developed empirical ocean color algorithm for chlorophyll<em> a </em>retrieval from Sentinel 3A/OLCI primary ocean color products using the <em>in situ </em>reference bio-optical datasets collected in the Black Sea in the period 2012-2019. Results obtained from the assessment of operational S3A/OLCI chlorophyll products, highlighted and confirmed that the specific regional algorithm is essential for the Black Sea. The coefficients of the regional algorithm were derived from the regression of log-transformed pigment concentrations and remote sensing reflectance ratio at 490nm and 560 nm with determination coefficient R<sup>2</sup> =0.88 and number of samples N=186. The algorithm predicts chlorophyll a values using a cubic polynomial formulation. The result of assessment of the regional chlorophyll <em>a</em> product against independent in situ measurements from the data utilized for algorithm development, showed relatively high accuracy (31.7%), fewer underestimations (MPD=-9.2%) and a good agreement (R<sup>2</sup>=0.66) between datasets indicating that the regional algorithm is more effective in reproducing the  pigment concentration in the Black Sea waters in comparison to the standard Sentinel 3A/OLCI algorithms. Our analysis revealed the importance of providing regional algorithms strictly required to suit the peculiar bio-optical properties featuring this basin. However, this requires collection of accurate<em> in situ </em>measurements in the different parts of the Black Sea. The validity of the reported empirical algorithm obviously depends on the size of the dataset used for its development. The Black Sea waters vary at a basin level due to the sub-regional features, environmental factors and seasonal variability, consequently the presented regional algorithm might have a limited generalization capability. Clearly, more<em> in situ</em> data with improved spatial and temporal coverage are critically needed for further calibration and validation of the ocean color products in the Black Sea.</p>

A Bayesian Approach for the Identification of Cascade Loss Model Strategy

A Bayesian method has been used to identify the best model strategy to describe the profile losses of low pressure turbine (LPT) cascades operating under unsteady inflow. The model has been tuned with experimental data measured in a large scale cascade facility, equipped with a moving bar system. Tests have been carried out on two different cascades, investigating three different reduced frequencies, three mass flow coefficients and several Reynolds numbers (up to eight) per condition, accounting for an overall amount of 51 different combinations of these parameters for each cascade. The predictor functions included into the model have been varied starting from a classic polynomial formulation for each influencing parameter, and then with functional relationships mimicking physical constrains and loss tendencies. Different combinations of the predictors, also including different types and orders of the cross-terms, have been evaluated by means of a Bayesian model selection method searching for the maximum probability of the model in fitting the cloud of experimental data. In particular, the evaluation of the Model Evidence (ME) using the Bayesian Information Criterion approximation (BIC) has allowed obtaining sufficient accuracy and avoiding overfitting at the same time. The best model here identified will be shown to be able to well reproduce the loss surface of a third different cascade that does not participate to the model selection. Realistic profile loss evolutions outside of the design space tested are provided, thus also allowing for a generalization of the structure of the model for other applications and future works.

Design and Analysis of a Monolithic Compliant Dwell Mechanism

A novel, monolithic flexible translational dwell mechanism that is driven by a DC motor is designed in this study. Mechanism consists of an initially straight, large deflecting pinned-pinned buckling beam as a coupler, semi-circular compliant arc as a follower, rigid crank and a slider. An approximate dwell motion is created since the slider doesn’t move until the critical buckling load of the flexible coupler is achieved and then snaps to its maximum displacement by pushing the follower arc beam. As the maximum bending on the arc is reached, slider moves back to its initial as the crank follows a full rotation. Dynamical lumped model of the mechanism is obtained by integrating first and second kind of elliptic integral solution of pinned-pinned beam with polynomial formulation method. Optimal dimensions and geometric positions are explored using commercially available FEA program (ADAMs). Mechanism is built by 3D printing the entire mechanism as a single piece using polyethylene terephthalate glycol (PETG). Mathematical model of the mechanism is validated through experimental setup and ADAMs simulations.

A Polynomial Formulation of Inverse Kinematics of Rolling Contact

Rolling contact has been used by robotic devices to drive between configurations. The degrees of freedom (DOFs) of rolling contact pairs can be one, two, or three, depending on the geometry of the objects. This paper aimed to derive three kinematic inputs required for the moving object to follow a trajectory described by its velocity profile when the moving object has three rotational DOFs and thus can rotate about any axis through the contact point with respect to the fixed object. We obtained three contact equations in the form of a system of three nonlinear algebraic equations by applying the curvature theory in differential geometry and simplified the three nonlinear algebraic equations to a univariate polynomial of degree six. Differing from the existing solution that requires solving a system of nonlinear ordinary differential equations, this polynomial is suitable for fast and accurate numerical root approximations. The contact equations further revealed the two essential parts of the spin velocity: The induced spin velocity governed by the geometry and the compensatory spin velocity provided externally to realize the desired spin velocity.