Neural networks for prediction of acoustical properties of polyurethane foams

This paper presents a study of neural networks for prediction of acoustical properties of polyurethane foams. The proposed neural network model of the foam uses easily measured parameters such as frequency, airflow resistivity and density to predict multiple acoustical properties including the sound absorption coefficient and the surface impedance. Such a model is quite robust in the sense that it can be used to develop models for many different classes of materials with different sets of input and output parameters. The current neural network model of the foam is empirical and provides a useful complement to the existing analytical and numerical approaches.     

Advantages of Odd Random Phase Multisine Electrochemical Impedance Measurements

Electrochemical impedance spectroscopy (EIS) is a powerful technique to study electrochemical processes and to perform screening tasks. Recently an integrated measuring and modeling methodology for EIS based on a multisine excitation signal was developed. A key issue in this methodology is the data analysis, allowing us to rapidly quantify the reliability of the measured data. In this paper, a comparison is made between classical single‐sine and the proposed multisine measurements on the same system. The fitting of the impedance data obtained by single‐or multisine excitation and using different weighting factors is also discussed. In addition to the advantages reported in earlier work, it is concluded that, of all investigated frequencies, the odd random phase multisine excitation yields the highest quality data in the shortest measurement time.     

Wind effects on noise propagation for complicated geographical and road configurations

Outdoor propagation from roads is influenced by wind, temperature and humidity. It is necessary to predict wind effects to simulate long-term environmental noise accurately. Noise levels have been measured in conjunction with wind speed and wind direction measurements. These noise levels showed noticeable daily changes. Excess attenuations of noise levels were found to depend on the vector wind (U_vec). By relating the vector wind and observed sound attenuations under all wind conditions, the influence of wind can be more accurately predicted for purposes of simulating noise propagation.     

Noise-induced dynamic bistability of front propagation

We study noise-induced front propagation in a bistable system of the activator–inhibitor type. By varying the intensity of the multiplicative noise, the velocity of the front exhibits a transition to a bistable regime, where the actual velocity and direction of front motion depends mainly on the (random) initial conditions.     

‘Best-case’ noise performance of feedback interferometers, potential for micromachine applications

We present a theoretical analysis of the noise performance of phase measuring feedback interferometers. We first analyse the operation of this kind of instrument and note that under certain circumstances bistability can occur. The bistable region should be avoided if possible when using feedback interferometry for high-accuracy measurement with low-input powers, as it can give rise to very high-noise levels. We then go on to investigate the effects of shot noise (on the interferometer output signal) and thermal noise (in the feedback loop), and relate these to the phase measurement accuracy of the interferometer. A ‘best-case’ calculation indicates that phase noise of about 0.005λ is possible at input powers in the nanowatt region. In practice, we expect that noise levels will be higher than predicted (particularly at high-input powers) due to the effects of vibration and air turbulence.     

Simulated annealing in the presence of noise

In many practical optimization problems, evaluation of a solution is subject to noise, e.g., due to stochastic simulations or measuring errors. Therefore, heuristics are needed that are capable of handling such noise. This paper first reviews the state-of-the-art in applying simulated annealing to noisy optimization problems. Then, two new algorithmic variants are proposed: an improved version of stochastic annealing that allows for arbitrary annealing schedules, and a new approach called simulated annealing in noisy environments (SANE). The latter integrates ideas from statistical sequential selection in order to reduce the number of samples required for making an acceptance decision with sufficient statistical confidence. Finally, SANE is shown to significantly outperform other state-of-the-art simulated annealing techniques on a stochastic travelling salesperson problem.     

Validation of a complex urban noise model close to a road

The adequacy of a model for the sound level close to a road is investigated by comparing resulting predictions for the sound level over a building façade with measurements. The road model involves the road geometry (the number and positions of traffic lanes), the traffic structure (vehicle flow rates and their average speeds in each lane) and equivalent omnidirectional point sources representing the vehicles. It is found that the assumed road traffic noise source model is adequate only for predicting levels over the higher part of the façade. However the investigation has allowed definition of what improvements are needed in the road source modelling to enable adequate predictions over the whole of the building façade.     

Noise map validation by continuous noise monitoring

This paper presents a comparison of two noise assessments in the Gdansk agglomeration in Poland. One is based on the noise map produced by computational method for the city in 2007, the second one is based on real data from continuous measurements acquired by a noise monitoring network operating in the city since 2008. Differences are shown and analyzed. Additionally, seasonal and weekday influence on noise indicators (L_DEN, L_D, L_E and L_N) is analyzed and discussed in this paper.     

Noise reduction by dynamic signal preemphasis

In this work we propose an approach to reduce the digitization noise for a given dynamic range, i.e., the number of bits, of an analog to digital converter used in an NMR receiver. In this approach, the receiver gain is dynamically increased so that the free induction decay is recorded in such an emphasized way that the decaying signal is digitized using as many number of bits as possible, and at the stage of data processing, the original signal profile is restored by applying the apodization that compensates the effect of the preemphasis. This approach, which we call APodization after Receiver gain InCrement during Ongoing sequence with Time (APRICOT), is performed in a solid-state system containing a pair of (13)C spins, one of which is fully isotopically labeled and the other is naturally abundant. It is demonstrated that the exceedingly smaller peak buried in the digitization noise in the conventional approach can be revealed by employing APRICOT.     

Varistor behavior study in undoped tungsten trioxide ceramic

In this paper, varistor property and mechanism of undoped tungsten trioxide (WO₃) ceramic have been studied. Experimental results revealed that pure WO₃ ceramic could exhibit a nonohmic behavior which was formed in the cooling process of ceramic, and very sensitive to heat treatment in different atmospheres. By comparison with the reported SnO₂ and ZnO varistor systems, it is supposed that the surface of WO₃ grain is more ready to adsorb oxygen and form high enough barriers at grain boundaries responsible for varistor behavior. The influences of heat treatments on the varistor properties of WO₃ ceramic have been investigated.