Model reduction for nonlinear aerodynamics and aeroelasticity using a Discrete Empirical Interpolation Method

A novel surrogate model is proposed in lieu of Computational Fluid Dynamics (CFD) solvers, for fast nonlinear aerodynamic and aeroelastic modeling. A nonlinear function is identified on selected interpolation points by
a discrete empirical interpolation method (DEIM). The flow field is then reconstructed using a least square approximation of the flow modes extracted
by proper orthogonal decomposition (POD). The aeroelastic reduce order
model (ROM) is completed by introducing a nonlinear mapping function
between displacements and the DEIM points. The proposed model is investigated to predict the aerodynamic forces due to forced motions using
a N ACA 0012 airfoil undergoing a prescribed pitching oscillation. To investigate aeroelastic problems at transonic conditions, a pitch/plunge airfoil
and a cropped delta wing aeroelastic models are built using linear structural models. The presence of shock-waves triggers the appearance of limit
cycle oscillations (LCO), which the model is able to predict. For all cases
tested, the new ROM shows the ability to replicate the nonlinear aerodynamic forces, structural displacements and reconstruct the complete flow
field with sufficient accuracy at a fraction of the cost of full order CFD
model.

Fast and sensitive aflatoxin B1 and total aflatoxins ELISAs for analysis of peanuts, maize and feed ingredients

Aflatoxins are a group of carcinogenic compounds produced by Aspergillus fungi that can grow on different agricultural crops. Both acute and chronic exposure to these mycotoxins can cause serious illness. Due to the high occurrence of aflatoxins in crops worldwide fast and cost-effective analytical methods are required for the identification of contaminated agricultural commodities before they are processed into final products and placed on the market. In order to provide new tools for aflatoxin screening two prototype fast ELISA methods: one for the detection of aflatoxin B₁ and the other for total aflatoxins were developed. Seven monoclonal antibodies with unique high sensitivity and at the same time good cross-reactivity profiles were produced. The monoclonal antibodies were characterized and two antibodies showing IC₅₀ of 0.037 ng/mL and 0.031 ng/mL for aflatoxin B₁ were applied in simple and fast direct competitive ELISA tests. The methods were validated for peanut matrix as this crop is one of the most affected by aflatoxin contamination. The detection capabilities of aflatoxin B₁ and total aflatoxins ELISAs were 0.4 μg/kg and 0.3 μg/kg for aflatoxin B₁, respectively, which are one of the lowest reported values. Total aflatoxins ELISA was also validated for the detection of aflatoxins B₂, G₁ and G₂. The application of the developed tests was demonstrated by screening 32 peanut samples collected from the UK retailers. Total aflatoxins ELISA was further applied to analyse naturally contaminated maize porridge and distiller's dried grain with solubles samples and the results were correlated with these obtained by UHPLC-MS/MS method.

Model reduction for nonlinear aeroelasticity using the Discrete Empirical Interpolation Method

A novel surrogate model is proposed in lieu of computational fluid dynamic (CFD) code for fast nonlinear aerodynamic modeling. First, a nonlinear function is identified on selected interpolation points defined by discrete empirical interpolation method (DEIM). The flow field is then reconstructed by a least square approximation of flow modes extracted by proper orthogonal decomposition (POD). The proposed model is applied in the prediction of limit cycle oscillation for a plunge/pitch airfoil and a delta wing with linear structural model, results are validate against a time accurate CFD-FEM code. The results show the model is able to replicate the aerodynamic forces and flow fields with sufficient accuracy while requiring a fraction of CFD cost.