9762 papers found
The paper presents the solution of damped nonlinear oscillator with the use of different numerical procedures in Prime 3.0 environment. As a technical example the case of ferroresonant circuit was used. The presented results demonstrate both possibilities of the environment Prime 3.0 and difficulties in achieving convergence of solutions for considered extreme nonlinear example.
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.
This paper deals with evaluation of inconsistent data of key comparison. The paper considers evaluation of key comparison value and degree of equivalence of measurement standards as well as the methods for confirmation of calibration and measurement capabilities, which are based on measurement uncertainties declared by participants and key comparison results.
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 present a fast non-rigorous method for the analysis of stochastic line edge roughness (LER) with amplitudes in the range of a few nanometers, based on a 2D Fourier transform method. LER has an significant impact on the light diffraction patterns measured by scatterometry. Scatterometry is a fast, non-destructive optical method used in wafer metrology to determine the geometry parameters of periodic surface structures from scattered light intensities.
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 discusses the analysis of interlaboratory comparison data where there may be some doubt about the validity of the uncertainty statements. The analysis of repeated measurements drawn from a Gaussian distribution with unknown variance provides a model for the posterior adjustment of the input distribution associated with each participant. Importantly, the shapes of the input distributions are adjusted, not just their standard deviations.
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.
Flow conditions in industrial pipe and district heating systems are not ideal. Moreover nearly all types of flow measurement devices are sensitive to flow conditions at their inlet section. In this contribution the generalized polynomial chaos method (gPC) is used to study the influence of a disturbed inlet profile with swirl and asymmetry components through a single beam ultrasonic flow meter. This approach allows to estimate the expected variations of the measured volume flow as a function of the position and orientation of the modeled meter in an efficient way.
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.