An experimentally validated thermo-mechanical model for the prediction of thermal contact conductance

A predictive model for estimating thermal contact conductance between two nominally flat metallic rough surfaces has been developed and experimentally validated. The predictive model consists of two complementary parts, the first of which is a surface deformation analysis to calculate the actual area of contact for each contact spot, while the second accounts for the effects of constriction resistance and gas gap conductance between the contacting surfaces. A surface characterization technique is developed which generates an equivalent 3-D surface profile from multiple 2-D profiles and determines the unique wavelengths of importance for the surface deformation and constriction resistance models. For given surface profiles and material properties of two contacting surfaces, and a specified contact pressure, the surface characterization technique filters out non-essential wavelengths on the surface, after which the surface deformation analysis calculates the deformation and contact area of each contacting asperity by considering three different modes of deformation, namely, elastic, elastic–plastic, and plastic. The constriction resistance model is then used to calculate the constriction resistance for each contacting asperity based on the area of contact and radius of curvature of the asperity. The constriction resistance values for all the contacting asperities are then used to calculate the total thermal contact conductance. An experimental facility has also been constructed to measure thermal contact conductance of interfaces to verify the results of the predictive model. Good agreement has been found between the model predictions and experimental measurements, validating the modeling approach.     

Simple modelling of the effects of exploitation on hot springs, Geyser Valley, Wairakei, New Zealand

Many hot springs in Geyser Valley declined and ceased flowing during well testing (1950–1958) or the early stages of development (1958–1964) of the Wairakei field, North Island, New Zealand. A simple model that considers mixing, geothermal reservoir pressure, and Darcy flow is applied to analyse the changes in flow rate and chemistry of spring SP18. The model suggests that prior to the testing the observed flow rate of 3 l/s was comprised of about 2.1 l/s of water from the deep reservoir and about 0.9 l/s from shallow groundwater. As the pressure in the reservoir decreased as a result of exploitation, the reservoir component declined but the groundwater component remained near constant until the spring had nearly ceased flowing. The model reasonably predicts the flow cessation date for four other springs (Group A) but poorly predicts that for seven other springs (Group B). These two groups of springs do not appear to be clustered at the ground surface. The pressure–elevation relationship suggests that the Group A springs feed from within the shallower Waiora Formation and Group B springs from within the deeper Wairakei Ignimbrite Formation. The observation that declines of chloride concentrations in Group A springs occurred at least three years before those in springs of Group B is consistent with the finding that Group A springs have a shallower feeder depth.     

The effect of light on the vitamin B2 and the vitamin A content of cheese

Edam type cheese was exposed to sunlight at ambient temperature and to fluorescent light at 5 °C. The loss of vitamin B₂ (riboflavin) and vitamin A was monitored in both the surface and inner layers of the cheese and the results compared with control samples kept in the dark. The loss of riboflavin when exposed to sunlight was shown to be primarily a surface effect but losses of vitamin A were similar throughout the cheese. When exposed to fluorescent light at 5 °C and monitored at intervals for 10 days the loss of riboflavin was still greatest at the surface but a trend to lower values than the control was evident throughout the cheese. Vitamin A losses followed a different pattern in both sunlight and fluorescent light. There was a heavy initial loss throughout the cheese. Under fluorescent light this was followed by a period in which further loss was mainly in the surface layer. Vacuum packaging reduced the loss of riboflavin but had no effect on the loss of vitamin A.     

Quantized Feedback Adaptive Reliable $$H_{\infty }$$ Control for Linear Time-Varying Delayed Systems

Based on an improved \(H_\infty \) performance index, the method of designing a reliable adaptive \(H_\infty \) controller with quantized state is addressed for the time-varying delayed system in this paper. On the basis of online estimates of actuator faults, the controller parameters are updated automatically to compensate the influence of actuator faults on the system while the desired improved \(H_\infty \) performance is preserved. A Lyapunov function candidate is constructed to prove that the closed-loop system is asymptotically stable. And the existing sufficient conditions of the controller are proved to be less conservative. The gains of the controller and the parameters of the adaptive law are co-designed and obtained in terms of solutions to a set of linear matrix inequalities. Finally, two numerical examples are given to illustrate that the proposed method is more effective than the previous methods for time-varying delayed systems.     

Visualization of Babble–Speech Interactions Using Andrews Curves

Visualizing multidimensional data such as the mel frequency cepstral coefficients (MFCCs) proves difficult, especially when the number of dimensions is greater than 3. As a result, it becomes extremely difficult to spot trends in high-dimensional signal interactions. Andrews curves seam to aid in the process of performing graphical analysis of high-dimensional data. This study examines the properties of the babble in the feature domain as well as the effect of the babble noise on the MFCCs of clean speech. Experiments have been conducted using two babble models: the overlapping conversation model and the overlapping speaker model. The purpose of this paper was to provide an insight into the effect of the babble noise on the first thirteen MFCCs of clean speech through the use of Andrews curves. The investigations of this paper give a visual comparison of the signals to expose trends, which the conventional visualization methods do not. The use of Andrews curves not only allows the signal to be observed, but also allows for a statistical comparisons between signals. With a better understanding of the difference between the models, it would be possible to develop systems, which are more robust in babble-corrupted environment.     

Stabilization of Discrete-time Fuzzy Systems Via Delta Operators and its Application to Truck–Trailer Model

This paper addresses the problem of robust \(L_2{-}L_\infty \) control in delta domain for a class of Takagi–Sugeno (TS) fuzzy systems with interval time-varying delays and disturbance input. In particular, the system under study involves state time delay, uncertainties and fast sampling period \(\mathcal {T}\). The main aim of this work was to design a \(L_2{-}L_\infty \) controller such that the proposed TS fuzzy system is robustly asymptotically stable with a \(L_2{-}L_\infty \) prescribed performance level \(\gamma >0\). Based on the proper Lyapunov–Krasovskii functional (LKF) involving lower and upper bound of time delay and free-weighting technique, a new set of delay-dependent sufficient conditions in terms of linear matrix inequalities (LMIs) are established for obtaining the required result. The result reveals that the asymptotic stability is achieved quickly when the sampling frequency is high. Finally, a numerical example based on the truck–trailer model is given to demonstrate the effectiveness and potential of the proposed design technique.     

IGCC for PAPR Reduction in OFDM Systems Over the Nonlinearity of SSPA and Wireless Fading Channels

High peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) systems seriously impacts power efficiency in radio frequency section due to the nonlinearity of high-power amplifiers. In this article, an improved gamma correction companding (IGCC) is proposed for PAPR reduction and investigated under multipath fading channels. It is shown that the proposed IGCC provides a significant PAPR reduction while improving power spectral levels and error performances when compared with the previous gamma correction companding. IGCC outperforms existing companding methods when a nonlinear solid-state power amplifier (SSPA) is considered. Additionally, with the introduction of \(\alpha , \beta , \gamma \), and \(\varDelta \) parameters, the improved companding can offer more flexibility in the PAPR reduction and therefore achieves a better trade-off among the PAPR gain, bit error rate (BER), and power spectral density (PSD) performance. Moreover, IGCC improves the BER and PSD performances by minimizing the nonlinear companding distortion. Further, IGCC improves signal-to-noise ratio (SNR) degradation (\(\varDelta _{\mathrm{SNR}}\)) and total degradation performances by 12.2 and 12.8 dB, respectively, considering an SSPA with input power back-off of 3.0 dB. Computer simulation reveals that the performances of IGCC are independent of the modulation schemes and works with arbitrary number of subcarriers (N), while it does not increase computational complexity when compared with the existing companding schemes used for PAPR reduction in OFDM systems.     

Adaptive Filtering Techniques using Cyclic Prefix in OFDM Systems for Multipath Fading Channel Prediction

This paper presents adaptive channel prediction techniques for wireless orthogonal frequency division multiplexing (OFDM) systems using cyclic prefix (CP). The CP not only combats intersymbol interference, but also precludes requirement of additional training symbols. The proposed adaptive algorithms exploit the channel state information contained in CP of received OFDM symbol, under the time-invariant and time-variant wireless multipath Rayleigh fading channels. For channel prediction, the convergence and tracking characteristics of conventional recursive least squares (RLS) algorithm, numeric variable forgetting factor RLS (NVFF-RLS) algorithm, Kalman filtering (KF) algorithm and reduced Kalman least mean squares (RK-LMS) algorithm are compared. The simulation results are presented to demonstrate that KF algorithm is the best available technique as compared to RK-LMS, RLS and NVFF-RLS algorithms by providing low mean square channel prediction error. But RK-LMS and NVFF-RLS algorithms exhibit lower computational complexity than KF algorithm. Under typical conditions, the tracking performance of RK-LMS is comparable to RLS algorithm. However, RK-LMS algorithm fails to perform well in convergence mode. For time-variant multipath fading channel prediction, the presented NVFF-RLS algorithm supersedes RLS algorithm in the channel tracking mode under moderately high fade rate conditions. However, under appropriate parameter setting in \(2\times 1\) space–time block-coded OFDM system, NVFF-RLS algorithm bestows enhanced channel tracking performance than RLS algorithm under static as well as dynamic environment, which leads to significant reduction in symbol error rate.