Effectiveness of crystalline admixtures and lime/cement coated granules in engineered self-healing capacity of lime mortars

Recently, the use of lime mortars in the restoration of historic buildings has found a renewed interest because they can guarantee the required mechanical, chemical and physical compatibility with the existing substrate. Spontaneous occurrence of self-healing phenomena in lime-based mortars is well known; the possibility of engineering the self-healing capacity, through tailored additions, is therefore of the utmost interest with the aim of enhancing the durability of the building masonry restoration works. This work proposes a system for the evaluation of the self-healing capacity with reference to traditional and advanced lime mortars. The autogenous healing capacity of a reference lime mortar has been first of all evaluated. Then, the possibility of engineering the aforementioned capacity has also assessed, through both commercial crystalline admixtures and tailored encapsulated additives. These should work according to a twofold mechanism: first, the coated granules envelope a core of lime mortar with purpose of making it inert during the hardening phase. Secondly, once the coated granules rupture upon cracking and damage of the mortar, the reactive binder is released and undergoes a delayed hardening, which is responsible of the healing phenomena. The results show that the mortar is able to heal micro-cracks; moreover, the addition of the crystalline admixture enhances this capacity. The different kinds of employed coated granules were also able to induce a sensible self-healing, but they decrease the instantaneous compressive strength.     

The oxidation of bitumen witnessed in-situ by infrared spectroscopy

During the production and recycling of asphalt concrete, bitumen in contact with inorganic particles is exposed to air at high temperatures. As a result an oxidation of bitumen, also known as aging, occurs. The reaction between bitumen and air at 163 °C was studied insitu with and without the presence of inorganic impurities by means of fourier transform infrared spectroscopy in the attenuated reflectance mode. This oxidation was discovered to be a step-wise reaction facilitated by the oxidation of thiols and creation of peroxides within the system. The rate of reaction was demonstrated to depend on the type of impurity present, of which iron (III) chloride was the strongest catalyst. It was further demonstrated that the oxidation reaction is inhibited by the adsorption of thiol species present in the system on copper particles. Combining copper with the iron (III) chloride-containing system also resulted in the inhibition of signal increase in the sulfoxide region of the spectra. The results of this preliminary research on the bitumen oxidation reaction presented are proposed for further research regarding control of aging of asphalt concrete, especially during the recycling works.     

Experimental modelling of free-surface dry granular flows under a centrifugal acceleration field

We investigate the dynamics of granular flows under the action of a centrifugal acceleration field. The granular flows consist of a monodisperse set of glass beads flowing down an inclined plane. The experiments are performed at variable slope angles \(\zeta \) and equivalent centrifugal accelerations \(a_\text {cf}\equiv Ng\). We study the effect of this parameters on the superficial flow velocity u and flow height h. Two trends are observed, by increasing \(\zeta \) and \(a_\text {cf}\), u increases proportionally, and h decreases asymptotically until a constant height. This relation is analysed in terms of the system potential and kinetic energy, leading to the estimation of equivalent impact forces one order of magnitude larger than those observed in small scale 1g laboratory experiments, with the possibility to reach higher forces by increasing N. Finally, considering the trend of u and h, our results suggest a scaling principle of inertial velocity proportional to \(\sqrt{N}\).     

Generalization of the ordinary state-based peridynamic model for isotropic linear viscoelasticity

This paper presents a generalization of the original ordinary state-based peridynamic model for isotropic linear viscoelasticity. The viscoelastic material response is represented using the thermodynamically acceptable Prony series approach. It can feature as many Prony terms as required and accounts for viscoelastic spherical and deviatoric components. The model was derived from an equivalence between peridynamic viscoelastic parameters and those appearing in classical continuum mechanics, by equating the free energy densities expressed in both frameworks. The model was simplified to a uni-dimensional expression and implemented to simulate a creep-recovery test. This implementation was finally validated by comparing peridynamic predictions to those predicted from classical continuum mechanics. An exact correspondence between peridynamics and the classical continuum approach was shown when the peridynamic horizon becomes small, meaning peridynamics tends toward classical continuum mechanics. This work provides a clear and direct means to researchers dealing with viscoelastic phenomena to tackle their problem within the peridynamic framework.     

Robust and efficient direction identification for groupwise additive multiple-index models and its applications

This paper concerns robust and efficient direction identification for a groupwise additive multiple-index model, in which each additive function has a single-index structure. Interestingly, without involving non-parametric approach, we show that the directions of all the index parameter vectors can be recovered by a simple linear composite quantile regression (CQR). As a specific application, a iterative-free CQR estimation procedure for the partially linear single-index model is proposed. Furthermore, it can also be used to develop a penalized CQR procedure for variable selection in the high-dimensional settings. The new method has superiority in robustness and efficiency by inheriting the advantage of the CQR approach. Simulation results and real-data analysis also confirm our method.     

Honest confidence regions and optimality in high-dimensional precision matrix estimation

We propose methodology for estimation of sparse precision matrices and statistical inference for their low-dimensional parameters in a high-dimensional setting where the number of parameters p can be much larger than the sample size. We show that the novel estimator achieves minimax rates in supremum norm and the low-dimensional components of the estimator have a Gaussian limiting distribution. These results hold uniformly over the class of precision matrices with row sparsity of small order \(\sqrt{n}/\log p\) and spectrum uniformly bounded, under a sub-Gaussian tail assumption on the margins of the true underlying distribution. Consequently, our results lead to uniformly valid confidence regions for low-dimensional parameters of the precision matrix. Thresholding the estimator leads to variable selection without imposing irrepresentability conditions. The performance of the method is demonstrated in a simulation study and on real data.     

Testing the hypothesis of a block compound symmetric covariance matrix for elliptically contoured distributions

In this paper, the authors study the problem of testing the hypothesis of a block compound symmetry covariance matrix with two-level multivariate observations, taken for m variables over u sites or time points. Through the use of a suitable block-diagonalization of the hypothesis matrix, it is possible to obtain a decomposition of the main hypothesis into two sub-hypotheses. Using this decomposition, it is then possible to obtain the likelihood ratio test statistic as well as its exact moments in a much simpler way. The exact distribution of the likelihood ratio test statistic is then analyzed. Because this distribution is quite elaborate, yielding a non-manageable distribution function, a manageable but very precise near-exact distribution is developed. Numerical studies conducted to evaluate the closeness between this near-exact distribution and the exact distribution show the very good performance of this approximation even for very small sample sizes and the approach followed allows us to extend its validity to situations where the population distributions are elliptically contoured. A real-data example is presented and a simulation study is also conducted.     

Bandwidth selection in kernel density estimation for interval-grouped data

When interval-grouped data are available, the classical Parzen–Rosenblatt kernel density estimator has to be modified to get a computable and useful approach in this context. The new nonparametric grouped data estimator needs of the choice of a smoothing parameter. In this paper, two different bandwidth selectors for this estimator are analyzed. A plug-in bandwidth selector is proposed and its relative rate of convergence obtained. Additionally, a bootstrap algorithm to select the bandwidth in this framework is designed. This method is easy to implement and does not require Monte Carlo. Both proposals are compared through simulations in different scenarios. It is observed that when the sample size is medium or large and grouping is not heavy, both bandwidth selection methods have a similar and good performance. However, when the sample size is large and under heavy grouping scenarios, the bootstrap bandwidth selector leads to better results.