The assessment of ceramic and mixed recycled aggregates for high strength and low shrinkage concretes

Very few studies on recycled aggregate concretes (RC) have been extended to the use of recycled ceramic and mixed aggregates in relation with high strength concretes. In the main they concentrate only on the analysis of the physical and mechanical properties. This study deals with the investigation of the influence that different percentages (up to 30% substitution for natural aggregates) of high porous ceramic and mixed recycled aggregates have over the plastic, autogenous and drying shrinkage of the concretes. The physical and mechanical properties as well as the chloride resistance were also determine in order to assess the viability of the use of ceramic and mixed recycled aggregates in high strength concretes. The results revealed that the employment of highly porous recycled aggregates reduced the plastic and autogenous shrinkage values of the concrete with respect to those obtained by conventional concrete (CC). Although the total drying shrinkage of the recycled concrete proved to be 25% higher than that of the CC concrete, the CC concrete had in fact a higher shrinkage value than that of the RC from 7 to 150 days of drying. It can be concluded that the RC concrete produced employing up to 30% of fine ceramic aggregates (FCA, with 12% of absorption capacity) achieved the lowest shrinkage values and higher mechanical and chloride ion resistance. In addition, the concrete produced with low percentage (10–15%) of recycled mixed aggregates also had similar properties to conventional concrete.     

Assessing abrasion performance of self-consolidating concrete containing synthetic fibers using acoustic emission analysis

The key objective of this investigation was to evaluate the abrasion resistance of self-consolidating concrete (SCC) with and without synthetic fibers (SynFs). The abrasion resistance of normal concrete was also investigated in this study for comparison. The abrasion test was performed on concrete specimens according to the rotating-cutter method along with continuous monitoring of acoustic emission (AE) using attached AE sensors. The effects of changing concrete type and incorporating various types (flexible and semi-rigid) and lengths of SynFs on the abrasion behaviour were investigated with the aid of AE analysis. AE signal characteristics such as amplitude, signal strength, number of hits, and duration were gathered during testing. Furthermore, the collected AE data was used to complete b-value analysis as well as intensity analysis resulting in three additional parameters: b-value, severity (S_r), and historic index (H(t)). The results showed that the AE parameters were directly correlated with the abrasion damage in all tested mixtures. Adding SynFs to all SCC mixtures enhanced their abrasion resistance. The flexible fibers variety exhibited better abrasion performance on average than the semi-rigid fibers. Meanwhile, longer fibers showed lower abrasion resistance than the shorter ones with the same type. The results also indicated that AE intensity analysis was able to determine the ranges for H(t) and S_r that identify the extent of damage due to abrasion of SynF-reinforced SCC.     

Dynamic material properties of wood subjected to low-velocity impact

This article studied the effects of low-velocity impact on the failure stresses and stiffness using a pendulum test. The specimens were of variable depth (20, 30, and 40 mm), a width of 50 mm, length of 650 mm, and span-length of 480 mm. The smallest specimen depth was similar to specimen sizes tested in the literature used to create the duration of load curve, while the largest specimen depth are considered structural size specimens. The impact was predicted using a numerical approach with Euler–Bernoulli beam, as well as Timoshenko beam theory, with a plastic contact law. The models were validated for impact from a low release-angle (where the beam remained elastic), but could use improvement for the force prediction at a high incidence velocity. The measured force signals were used as forcing functions to obtain the dynamic failure stresses for all of the evaluated specimens, and the Timoshenko–Goens–Hearmon Method to derive the dynamic E. The resulting strain rates ranged from 9.11?×?10^?5 s^?1 for the quasi-static specimens up to 25 s^?1 for the greatest incidence velocity. The results from this study suggest different duration of load factors than the Madison Curve, influencing the design of structures subjected to dynamic loading.     

Coupled temperature and moisture effects on the tensile behavior of strain hardening cementitious composites (SHCC) reinforced with PVA fibers

This paper reports the experimental findings on the tensile behavior of strain-hardening cement-based composites (SHCC). The composites were subjected to the combined effects of elevated temperatures and internal moisture condition. Uniaxial tensile tests on dumbbell-shaped SHCC specimens with in situ temperature control were performed at 22, 60 and 100 °C. In addition, the effect of the internal humidity of SHCC (95, 50, 20 and 0%) coupled to the elevated temperatures was investigated. It was shown that the tensile strength decreases and the strain capacity increases with an increase in temperature. The influence of the internal moisture conditions was more significant in high temperatures. The strain capacity reduced significantly with a decrease in the humidity level. The crack pattern of the SHCC specimens was determined. Furthermore, single fiber pullout tests were performed under the considered high temperatures condition. Finally, the results are discussed based on the thermogravimetry analysis of the PVA fiber, alterations on its microstructure and surface coating.     

The interlaminar shear failure characteristics of asphalt pavement coupled heating cables

Nowadays, heating cables are used as heat sources for heating pavements in practical engineering. However, there is a contradiction between the snow melting function and the interlaminar stability of heating pavement. In order to solve the contradiction, the interlaminar failure behavior of asphalt mixture coupled heating cables specimen (AMCS) was researched, through experiments and the finite element method. Under the different conditions of heating cables and rolling times, a series of direct shear tests was performed at the interface of AMCS, to compare the interlaminar stability of three different AMCS. Meanwhile, based on the bilinear cohesive zone model and coulomb friction model a 2D finite element model was established, to simulate this shear failure processes and make up for the limitations of the experiment. According to above test and simulation results, the failure mechanism and the weakest interface in AMCS were found, and the influence of the heating cable’s diameter and embedded spacing on the interlaminar shear strength were found. Then, a modified coulomb theorem model was proposed to predict the shear strength of the AMCS. This research enriches the design theory of the heating pavement and it has great significance for its structural design of heating asphalt pavement.     

On the correspondence from Bayesian log-linear modelling to logistic regression modelling with <Emphasis Type="Italic">g</Emphasis>-priors

Consider a set of categorical variables where at least one of them is binary. The log-linear model that describes the counts in the resulting contingency table implies a specific logistic regression model, with the binary variable as the outcome. Within the Bayesian framework, the g-prior and mixtures of g-priors are commonly assigned to the parameters of a generalized linear model. We prove that assigning a g-prior (or a mixture of g-priors) to the parameters of a certain log-linear model designates a g-prior (or a mixture of g-priors) on the parameters of the corresponding logistic regression. By deriving an asymptotic result, and with numerical illustrations, we demonstrate that when a g-prior is adopted, this correspondence extends to the posterior distribution of the model parameters. Thus, it is valid to translate inferences from fitting a log-linear model to inferences within the logistic regression framework, with regard to the presence of main effects and interaction terms.     

Bootstrap- and permutation-based inference for the Mann–Whitney effect for right-censored and tied data

The Mann–Whitney effect is an intuitive measure for discriminating two survival distributions. Here we analyse various inference techniques for this parameter in a two-sample survival setting with independent right-censoring, where the survival times are even allowed to be discretely distributed. This allows for ties in the data and requires the introduction of normalized versions of Kaplan–Meier estimators from which adequate point estimates are deduced. Asymptotically exact inference procedures based on standard normal, bootstrap, and permutation quantiles are developed and compared in simulations. Here, the asymptotically robust and—under exchangeable data—even finitely exact permutation procedure turned out to be the best. Finally, all procedures are illustrated using a real data set.     

Some recent work on multivariate Gaussian Markov random fields

Some recent work on conditional formulation of multivariate Gaussian Markov random fields is presented. The focus is on model constructions by compatible conditionals and coregionalization. Special attention is given to multivariate generalizations of univariate models. Beginning with univariate model constructions, a survey of key approaches to formulating multivariate extensions is presented. Two challenges in the formulation and implementation of multivariate models are highlighted: (1) entanglement of spatial and non-spatial components, and (2) enforcement for positivity condition. Managing the two challenges by decomposition, separation, and constrained parameterization is discussed. Also highlighted is the challenge of flexible modeling of (conditional) cross-spatial dependencies and, in particular, asymmetric cross-spatial dependencies. Interpretation of asymmetric cross-spatial dependencies is also discussed. A coregionalization framework which connects and unifies the various lines of model development is presented. The framework enables a systematic development of a broad range of models via linear and spatially varying coregionalization, respectively, with extensions to locally adaptive models. Formulation of multivariate models over variable-specific lattices is discussed. Selected models are illustrated with examples of Bayesian multivariate and spatiotemporal disease mapping. Potential applications of coregionalization models in imaging analysis, covariance modeling, dimension reduction, and latent variable analysis are briefly mentioned.     

Rejoinder on: Some recent work on multivariate Gaussian Markov random fields

I thank the discussants, Miguel A. Martinez-Beneito, Fedel Greco, Carlo Trivisano, Stephan R Sain, and Reinhard Furrer, for their insightful and stimulating commentary. The rejoinder is organized in five sections: (1) the M-based models, (2) posterior sensitivity to prior choices for \({\varvec{C}}\) and \({\varvec{\varSigma }}\), (3) stationary and non-stationary (M)GMRFs, (4) various approaches to model formulation and related applications, and (5) statistical computation.