Evidence of residual entropy in the cubic spinel Zn2TiO4

The standard free energies of formation of Zn2Ti04 and ZnTi03 have been determined in the temperature range 930° to i ioo'x from electromotive force measurements on reversible solid oxide galvanic cells;Ag-5at%znll I Pt, + CaO-Zr02 ZnO I II Ag-5at%Zn Y20r Th02 CaO-Zr02 + ,Pt Zn2Ti04+ ZnTi03 and II Ag-5at%Zn CaO-Zr02 + ,Pt ZnTi03+ Ti02 The values may be expressed by the equations,2ZnO (wurtz) + Ti02(rut) -> Zn2Ti04(sp), f:!:.Go = -750-2-46T (±75)cal;ZnO(wurtz) +Ti02(rut) -> ZnTi03(ilmen) ,f:!:.Co = -]600-0·]99T(±50)cal.Combination of the free energy values with the calorimetric heat of formation, and low-temperature and high-temperature heat capacity of Zn2Ti04 reported in literature, suggests a residual entropy of ],9 (±0·6) cal K-1 mol ? for the cubic spinel. Ideal mixing of Zn2+ and Ti4+ ions on the octahedral sites would result in a configurational contribution to the entropy of 2· 75 cal K-1 rnol ".The difference is indicative of short-range ordering of cations on octahedral sites.

Analysis of residual tropical cemented soil behaviour

In -situ soils in gee-material spectrum might arise due to sedimentation or could be non-sedimentary residual formations. The inherent nature and diversity of geological processes involved in the soil formation stage itself are responsible for a wide variability in the in-situ state of the soil. In this paper the possibility of analyses to arrive at engineering parameters of residual soils with varied degrees of residual or acquired cementation by the use of physical and in-situ parameters normally determined in routine investigations, are examined. An Intrinsic State Line,(ISL), with reference to an intrinsic state parameter (e/e(L)) and its variation with effective stress for reconstituted clays has been developed for residual tropical soils of non-sedimentary origin. In relation to the Intrinsic State Line (ISL), the undisturbed state, e, the potential parameter, e(L), along with the overburden pressure data has been analyzed to identify the dominance of cementation or stress history or both in controlling the compressibility and strength behaviour of natural residual soil. The location of yield stress point in relation to the ISL, pre-, and post- yield stress, compression indices along the e- log sigma(v) path provide a simple means to the analysis of the compressibility characteristics of cemented soils for analysis.

Residual strength of hot pressed zirconium diboride (ZrB2) after exposure to high temperatures

ZrB2 with different amounts of B4C additive (0-5 wt.%) has been hot pressed at 2000 degrees C and 25 MPa for 1 h. By addition of B4C, density as well as micro-hardness increased. For lower B4C content (0.5 and 1 wt.%), hot pressed ZrB2 shows considerable improvement in flexural strength after exposure in air at 1000 C for 5 h, while higher B4C content (3 and 5 wt.%) leads to marginal or no improvement. For any content of B4C, flexural strength after exposure in air at 1500 degrees C for 5 h is lower than as-hot pressed ZrB2. (C) 2011 Elsevier B.V. All rights reserved.

Residual strength evaluation of concrete structural components under fatigue loading

This paper presents methodologies for residual strength evaluation of concrete structural components using linear elastic and nonlinear fracture mechanics principles. The effect of cohesive forces due to aggregate bridging has been represented mathematically by employing tension softening models. Various tension softening models such as linear, bilinear, trilinear, exponential and power curve have been described with appropriate expressions. These models have been validated by predicting the remaining life of concrete structural components and comparing with the corresponding experimental values available in the literature. It is observed that the predicted remaining life by using power model and modified bi-linear model is in good agreement with the corresponding experimental values. Residual strength has also been predicted using these tension softening models and observed that the predicted residual strength is in good agreement with the corresponding analytical values in the literature. In general, it is observed that the variation of predicted residual moment with the chosen tension softening model follows the similar trend as in the case of remaining life. Linear model predicts large residual moments followed by trilinear, bilinear and power models.

A Linear S-N Curve with Load Dependent Variance and Explicit Failure Probability

We reconsider standard uniaxial fatigue test data obtained from handbooks. Many S-N curve fits to such data represent the median life and exclude load-dependent variance in life. Presently available approaches for incorporating probabilistic aspects explicitly within the S-N curves have some shortcomings, which we discuss. We propose a new linear S-N fit with a prespecified failure probability, load-dependent variance, and reasonable behavior at extreme loads. We fit our parameters using maximum likelihood, show the reasonableness of the fit using Q-Q plots, and obtain standard error estimates via Monte Carlo simulations. The proposed fitting method may be used for obtaining S-N curves from the same data as already available, with the same mathematical form, but in cases in which the failure probability is smaller, say, 10 % instead of 50 %, and in which the fitted line is not parallel to the 50 % (median) line.

Nonlinear dynamic state estimation in instrumented structures with conditionally linear Gaussian substructures

Many problems of state estimation in structural dynamics permit a partitioning of system states into nonlinear and conditionally linear substructures. This enables a part of the problem to be solved exactly, using the Kalman filter, and the remainder using Monte Carlo simulations. The present study develops an algorithm that combines sequential importance sampling based particle filtering with Kalman filtering to a fairly general form of process equations and demonstrates the application of a substructuring scheme to problems of hidden state estimation in structures with local nonlinearities, response sensitivity model updating in nonlinear systems, and characterization of residual displacements in instrumented inelastic structures. The paper also theoretically demonstrates that the sampling variance associated with the substructuring scheme used does not exceed the sampling variance corresponding to the Monte Carlo filtering without substructuring. (C) 2012 Elsevier Ltd. All rights reserved.

Minimal residual method provides optimal regularization parameter for diffuse optical tomography

The inverse problem in the diffuse optical tomography is known to be nonlinear, ill-posed, and sometimes under-determined, requiring regularization to obtain meaningful results, with Tikhonov-type regularization being the most popular one. The choice of this regularization parameter dictates the reconstructed optical image quality and is typically chosen empirically or based on prior experience. An automated method for optimal selection of regularization parameter that is based on regularized minimal residual method (MRM) is proposed and is compared with the traditional generalized cross-validation method. The results obtained using numerical and gelatin phantom data indicate that the MRM-based method is capable of providing the optimal regularization parameter. (C) 2012 Society of Photo-Optical Instrumentation Engineers (SPIE). DOI: 10.1117/1.JBO.17.10.106015]

A h-Adaptive Algorithm Using Residual Error Estimates for Fluid Flows

Algorithms for adaptive mesh refinement using a residual error estimator are proposed for fluid flow problems in a finite volume framework. The residual error estimator, referred to as the R-parameter is used to derive refinement and coarsening criteria for the adaptive algorithms. An adaptive strategy based on the R-parameter is proposed for continuous flows, while a hybrid adaptive algorithm employing a combination of error indicators and the R-parameter is developed for discontinuous flows. Numerical experiments for inviscid and viscous flows on different grid topologies demonstrate the effectiveness of the proposed algorithms on arbitrary polygonal grids.

Variance-Reduced Particle Filters for Structural System Identification Problems

A few variance reduction schemes are proposed within the broad framework of a particle filter as applied to the problem of structural system identification. Whereas the first scheme uses a directional descent step, possibly of the Newton or quasi-Newton type, within the prediction stage of the filter, the second relies on replacing the more conventional Monte Carlo simulation involving pseudorandom sequence with one using quasi-random sequences along with a Brownian bridge discretization while representing the process noise terms. As evidenced through the derivations and subsequent numerical work on the identification of a shear frame, the combined effect of the proposed approaches in yielding variance-reduced estimates of the model parameters appears to be quite noticeable. DOI: 10.1061/(ASCE)EM.1943-7889.0000480. (C) 2013 American Society of Civil Engineers.

Epoch extraction based on integrated linear prediction residual using plosion index

Epoch is defined as the instant of significant excitation within a pitch period of voiced speech. Epoch extraction continues to attract the interest of researchers because of its significance in speech analysis. Existing high performance epoch extraction algorithms require either dynamic programming techniques or a priori information of the average pitch period. An algorithm without such requirements is proposed based on integrated linear prediction residual (ILPR) which resembles the voice source signal. Half wave rectified and negated ILPR (or Hilbert transform of ILPR) is used as the pre-processed signal. A new non-linear temporal measure named the plosion index (PI) has been proposed for detecting `transients' in speech signal. An extension of PI, called the dynamic plosion index (DPI) is applied on pre-processed signal to estimate the epochs. The proposed DPI algorithm is validated using six large databases which provide simultaneous EGG recordings. Creaky and singing voice samples are also analyzed. The algorithm has been tested for its robustness in the presence of additive white and babble noise and on simulated telephone quality speech. The performance of the DPI algorithm is found to be comparable or better than five state-of-the-art techniques for the experiments considered.

Large-MIMO Receiver based on Linear Regression of MMSE Residual

Multiple input multiple output (MIMO) systems with large number of antennas have been gaining wide attention as they enable very high throughputs. A major impediment is the complexity at the receiver needed to detect the transmitted data. To this end we propose a new receiver, called LRR (Linear Regression of MMSE Residual), which improves the MMSE receiver by learning a linear regression model for the error of the MMSE receiver. The LRR receiver uses pilot data to estimate the channel, and then uses locally generated training data (not transmitted over the channel), to find the linear regression parameters. The proposed receiver is suitable for applications where the channel remains constant for a long period (slow-fading channels) and performs quite well: at a bit error rate (BER) of 10(-3), the SNR gain over MMSE receiver is about 7 dB for a 16 x 16 system; for a 64 x 64 system the gain is about 8.5 dB. For large coherence time, the complexity order of the LRR receiver is the same as that of the MMSE receiver, and in simulations we find that it needs about 4 times as many floating point operations. We also show that further gain of about 4 dB is obtained by local search around the estimate given by the LRR receiver.