Estimation of modal parameters in structures using multiple time history records

In Operational Modal Analysis of structures we often have multiple time history records of vibrations measured at different time instants. This work presents a procedure for estimating the modal parameters of the structure processing all the records, that is, using all available information to obtain a single estimate of the modal parameters. The method uses Maximum Likelihood Estimation and the Expectation Maximization algorithm. Finally, it has been applied to various problems for both simulated and real structures and the results show the advantage of the joint analysis proposed.

Improving the low-wind performance of the AERMOD atmospheric dispersion model for predicting short-range impacts of livestock ammonia emissions.

Short-range impacts to sensitive ecosystems as a result of ammonia emitted by livestock farms are often assessed using atmospheric dispersion modelling systems such as AERMOD. These assessments evaluate mean annual atmospheric concentrations of ammonia and nitrogen deposition rates at the ecosystem location for comparison with ecosystem damage thresholds. However, predictions of mean annual atmospheric concentrations can be dominated by periods of stable night-time conditions, which can contribute significantly to mean concentrations. AERMOD has been demonstrated to overestimate concentrations in certain stable low-wind conditions and so the model could potentially overestimate the short-range impacts of livestock ammonia emissions. This paper tests several modifications to the parameterisation of AERMOD (v12345) that aim to improve model predictions in low-wind conditions. The modifications are first described and then are applied to three pig farm case studies in the USA, Denmark and Spain to assess whether the modifications improve long-term mean ammonia concentration predictions through improved model performance. For these three case studies, most of the modifications tested improved model performance as a result of reducing the long-term mean concentration predictions, with the largest effect for low- or ground-level sources (e.g. slurry lagoons or naturally ventilated housing).

Joint statistical analysis of multiple measurement setups for the estimation of vibrational modes

Computing the modal parameters of large structures in Operational Modal Analysis often requires to process data from multiple non simultaneously recorded setups of sensors. These setups share some sensors in common, the so-called reference sensors that are fixed for all the measurements, while the other sensors are moved from one setup to the next. One possibility is to process the setups separately what result in different modal parameter estimates for each setup. Then the reference sensors are used to merge or glue the different parts of the mode shapes to obtain global modes, while the natural frequencies and damping ratios are usually averaged. In this paper we present a state space model that can be used to process all setups at once so the global mode shapes are obtained automatically and subsequently only a value for the natural frequency and damping ratio of each mode is computed. We also present how this model can be estimated using maximum likelihood and the Expectation Maximization algorithm. We apply this technique to real data measured at a footbridge.

Using damage from 2010 Haiti earthquake for vulnerability estimation of typical structures in Port-au-Prince (Haiti).

After the 2010 Haiti earthquake, that hits the city of Port-au-Prince, capital city of Haiti, a multidisciplinary working group of specialists (seismologist, geologists, engineers and architects) from different Spanish Universities and also from Haiti, joined effort under the SISMO-HAITI project (financed by the Universidad Politecnica de Madrid), with an objective: Evaluation of seismic hazard and risk in Haiti and its application to the seismic design, urban planning, emergency and resource management. In this paper, as a first step for a structural damage estimation of future earthquakes in the country, a calibration of damage functions has been carried out by means of a two-stage procedure. After compiling a database with observed damage in the city after the earthquake, the exposure model (building stock) has been classified and through an iteratively two-step calibration process, a specific set of damage functions for the country has been proposed. Additionally, Next Generation Attenuation Models (NGA) and Vs30 models have been analysed to choose the most appropriate for the seismic risk estimation in the city. Finally in a next paper, these functions will be used to estimate a seismic risk scenario for a future earthquake.

Linear instability analysis of incompressible flow over a cuboid cavity

Direct numerical simulations are performed to analyze the three-dimensional instability of flows over three-dimensional cavities. The flow structures at different Reynolds numbers are investigated by using the spectral-element solver nek5000. As the Reynolds number increasing, the lateral wall effects become more important, the recirculation zone shrinks, the front vortex increases and the flow structure inside of the cavity becomes more complex. Results show that the flow bifurcates from a steady state to an oscillatory regime beyond a value of Reynolds number Re = 1100.

On the two-dimensional theory of incompressible flow over inlets

The linearized solution for the two-dimensional flow over an inlet of general form has been derived, assuming incompressible potential flow. With this theory suction forces at sharp inlet lips can be estimated and ideal inlets can be designed.

Estimation of Symmetric Channels for Discrete Cosine Transform Type-I Multicarrier Systems: A Compressed Sensing Approach

The problem of channel estimation for multicarrier communications is addressed. We focus on systems employing the Discrete Cosine Transform Type-I (DCT1) even at both the transmitter and the receiver, presenting an algorithm which achieves an accurate estimation of symmetric channel filters using only a small number of training symbols. The solution is obtained by using either matrix inversion or compressed sensing algorithms. We provide the theoretical results which guarantee the validity of the proposed technique for the DCT1. Numerical simulations illustrate the good behaviour of the proposed algorithm.