This work deals with evaluation of the measurand when results of only three measurements are available. Different algorithms are analyzed and compared according to the methodology of data processing algorithms certification.

Magnetometers are widely used for LEO small satellites attitude determination and control system. In order to estimate satellite dynamics and control attitude accurately, scale factor and bias of magnetometer must be estimated. In this study a Linear Kalman filter (LKF) based algorithm for the estimation of magnetometer biases and scale factors is proposed. Proposed algorithms are simulated through attitude dynamics of a small satellite.

We investigate light scattering from single, randomly or actively orientated red blood cells (RBCs) employing a dedicated flow cytometer. The measured bimodal distributions of cross sections of randomly oriented RBCs can be reproduced numerically applying the discrete dipole approximation (DDA). Our sensitivity analysis of the scattering pattern reveals a significant impact of assumed biconcave shapes and different orientations of the hydrodynamically focused RBCs.

This paper described models and algorithms for analysing data captured by coordinate metrology systems such as laser tracers, laser radar, laser trackers, theodolites and indoor GPS. Algorithms use structure-exploiting techniques to determine estimates of target locations and associated variance matrix efficiently. The calculation of the complete variance matrix enables valid estimates of uncertainties for quantities derived from the solution targets to be evaluated and provides a basis for improving the design of measurement strategies to reduce uncertainties.

The use of computational codes has become common practice when experiments are not feasible or when their number is too parsimonious. The statistical modelling of numerical experiments with kriging models yields a probabilistic decision framework to assess the probability of failure of the system and its associated uncertainty. In this work, fast low-fidelity simulations are combined with costly high-fidelity simulations in a co-kriging model and points are sequentially designed to reduce the number of costly simulations. The methodology is applied to a fire engineering case study.