Discrete element method investigation on thermally-induced shakedown of granular materials

Temperature change, as a common kind of internal perturbation performed on granular materials, has a significant effect on the bulk properties of granular materials. However, few studies on thermally-induced shakedown under a long-term thermal cycling were reported. In this work, the discrete element method was used to give insight into the thermally-induced shakedown on the fabric and stress states within non-cohesive, frictional granular assemblies. Assemblies were submitted to thermal cycling at a stationary boundary condition after experiencing a one-dimensional compression. Evolution of coordination number, entropy and anisotropy was investigated as well as boundary forces and contact forces. At the same time, effects of the heating rate, the initial vertical load and the magnitude of temperature change were examined. It demonstrates that thermal cycling induces a significant force relaxation within granular materials, while the corresponding granular fabric has a small change. In addition, the entropy and anisotropy decreases with thermal cycling. Moreover, the initial vertical load can constrain the development of thermally-induced fabric change, thereby limiting force relaxation to some degree. Both high heating rate and larger magnitudes of temperature change contribute to more significant force relaxation. However, they cause smaller fabric changes even though they provide larger perturbations.     

Modifying continuous-time random walks to model finite-size particle diffusion in granular porous media

The continuous-time random walk (CTRW) model is useful for alleviating the computational burden of simulating diffusion in actual media. In principle, isotropic CTRW only requires knowledge of the step-size, \(P_l\), and waiting-time, \(P_t\), distributions of the random walk in the medium and it then generates presumably equivalent walks in free space, which are much faster. Here we test the usefulness of CTRW to modelling diffusion of finite-size particles in porous medium generated by loose granular packs. This is done by first simulating the diffusion process in a model porous medium of mean coordination number, which corresponds to marginal rigidity (the loosest possible structure), computing the resulting distributions \(P_l\) and \(P_t\) as functions of the particle size, and then using these as input for a free space CTRW. The CTRW walks are then compared to the ones simulated in the actual media. In particular, we study the normal-to-anomalous transition of the diffusion as a function of increasing particle size. We find that, given the same \(P_l\) and \(P_t\) for the simulation and the CTRW, the latter predicts incorrectly the size at which the transition occurs. We show that the discrepancy is related to the dependence of the effective connectivity of the porous media on the diffusing particle size, which is not captured simply by these distributions. We propose a correcting modification to the CTRW model—adding anisotropy—and show that it yields good agreement with the simulated diffusion process. We also present a method to obtain \(P_l\) and \(P_t\) directly from the porous sample, without having to simulate an actual diffusion process. This extends the use of CTRW, with all its advantages, to modelling diffusion processes of finite-size particles in such confined geometries.     

Models of Ballistic Propagation of Heat at Low Temperatures

Heat conduction at low temperatures shows several effects that cannot be described by the Fourier law. In this paper, the performance of various theories is compared in case of wave-like and ballistic propagation of heat pulses in NaF.     

Dynamics of Plug Formation in a Circular Cylinder Under Low Bond Number Conditions: Experiment and Simulation

The goal of the current study is to investigate the dynamics of two phase interface under a low Bond number condition. Silicone oil is injected into a cylinder under a Bond number of about 0.47 via a side tube forming a T-junction with the former. The time evolution of the interface of silicon oil in a cylinder is captured using a high speed camera. The volume at which the plug is formed is then determined using an image processing tool to analyze the captured images. A numerical simulation is carried out where fluid is injected into a cylinder, under a less than unity Bond number condition, via a side tube. Numerical and experimental results are then compared.     

A superhydrophilic titanium implant functionalized by ozone gas modulates bone marrow cell and macrophage responses

Bone-forming cells and M? play key roles in bone tissue repair. In this study, we prepared a superhydrophilic titanium implant functionalized by ozone gas to modulate osteoconductivity and inhibit inflammatory response towards titanium implants. After 24 h of ozone gas treatment, the water contact angle of the titanium surface became zero. XPS analysis revealed that hydroxyl groups were greatly increased, but carbon contaminants were largely decreased 24 h after ozone gas functionalization. Also, ozone gas functionalization did not alter titanium surface topography. Superhydrophilic titanium (O₃–Ti) largely increased the aspect ratio, size and perimeter of cells when compared with untreated titanium (unTi). In addition, O₃–Ti facilitated rat bone marrow derived MSCs differentiation and mineralization evidenced by greater ALP activity and bone-like nodule formation. Interestingly, O₃–Ti did not affect RAW264.7 M? proliferation. However, naive RAW264.7 M? cultured on unTi produced a two-fold larger amount of TNFα than that on O₃–Ti. Furthermore, O₃–Ti greatly mitigated proinflammatory cytokine production, including TNFα and IL-6 from LSP-stimulated RAW264.7 M?. These results demonstrated that a superhydrophilic titanium prepared by simple ozone gas functionalization successfully increased MSCs proliferation and differentiation, and mitigated proinflammatory cytokine production from both naive and LPS-stimulated M?. This superhydrophilic surface would be useful as an endosseous implantable biomaterials and as a biomaterial for implantation into other tissues.     

Nonlinearity of bituminous mixtures

This paper presents an experimental characterization of the strain dependency of the complex modulus of bituminous mixtures for strain amplitude levels lower than about \(110~\upmu\mbox{m}/\mbox{m}\). A series of strain amplitude sweep tests are performed at different temperatures (8, 10, 12 and 14°C) and frequencies (0.3, 1, 3 and 10 Hz), during which complex modulus is monitored. For each combination of temperature and frequency, four maximum strain amplitudes are targeted (50, 75, 100 and \(110~\upmu\mbox{m}/\mbox{m}\)). For each of them, two series of 50 loading cycles are applied, respectively at decreasing and increasing strain amplitudes. Before each decreasing strain sweep and after each increasing strain sweep, 5 cycles are performed at constant maximum targeted strain amplitude.Experimental results show that the behavior of the studied material is strain dependent. The norm of the complex modulus decreases and phase angle increases with strain amplitude. Results are presented in Black and Cole–Cole plots, where characteristic directions of nonlinearity can be identified. Both the effects of nonlinearity in terms of the complex modulus variation and of the direction of nonlinearity in Black space seem to validate the time–temperature superposition principle with the same shift factors as for linear viscoelasticity.The comparison between results obtained during increasing and decreasing strain sweeps suggests the existence of another phenomenon occurring during cyclic loading, which appears to systematically induce a decrease of the norm of the complex modulus and an increase of the phase angle, regardless of the type of the strain sweep (increasing or decreasing).     

A Minimal Closed-form Solution for the Perspective Three Orthogonal Angles (P3oA) Problem: Application To Visual Odometry

We provide a simple closed-form solution to the Perspective three orthogonal angles (P3oA) problem: given the projection of three orthogonal lines in a calibrated camera, find their 3D directions. Upon this solution, an algorithm for the estimation of the camera relative rotation between two frames is proposed. The key idea is to detect triplets of orthogonal lines in a hypothesize-and-test framework and use all of them to compute the camera rotation in a robust way. This approach is suitable for human-made environments where numerous groups of orthogonal lines exist. We evaluate the numerical stability of the P3oA solution and the estimation of the relative rotation with synthetic and real data, comparing our results to other state-of-the-art approaches.     

Multivariate Median Filters and Partial Differential Equations

Multivariate median filters have been proposed as generalizations of the well-established median filter for gray-value images to multichannel images. As multivariate median, most of the recent approaches use the \(L^1\) median, i.e., the minimizer of an objective function that is the sum of distances to all input points. Many properties of univariate median filters generalize to such a filter. However, the famous result by Guichard and Morel about approximation of the mean curvature motion PDE by median filtering does not have a comparably simple counterpart for \(L^1\) multivariate median filtering. We discuss the affine equivariant Oja median and the affine equivariant transformation–retransformation \(L^1\) median as alternatives to \(L^1\) median filtering. We analyze multivariate median filters in a space-continuous setting, including the formulation of a space-continuous version of the transformation–retransformation \(L^1\) median, and derive PDEs approximated by these filters in the cases of bivariate planar images, three-channel volume images, and three-channel planar images. The PDEs for the affine equivariant filters can be interpreted geometrically as combinations of a diffusion and a principal-component-wise curvature motion contribution with a cross-effect term based on torsions of principal components. Numerical experiments are presented, which demonstrate the validity of the approximation results.     

On negative results when using sentiment analysis tools for software engineering research

Recent years have seen an increasing attention to social aspects of software engineering, including studies of emotions and sentiments experienced and expressed by the software developers. Most of these studies reuse existing sentiment analysis tools such as SentiStrength and NLTK. However, these tools have been trained on product reviews and movie reviews and, therefore, their results might not be applicable in the software engineering domain. In this paper we study whether the sentiment analysis tools agree with the sentiment recognized by human evaluators (as reported in an earlier study) as well as with each other. Furthermore, we evaluate the impact of the choice of a sentiment analysis tool on software engineering studies by conducting a simple study of differences in issue resolution times for positive, negative and neutral texts. We repeat the study for seven datasets (issue trackers and Stack Overflow questions) and different sentiment analysis tools and observe that the disagreement between the tools can lead to diverging conclusions. Finally, we perform two replications of previously published studies and observe that the results of those studies cannot be confirmed when a different sentiment analysis tool is used.     

Top-<Emphasis Type="Italic">k</Emphasis> temporal keyword search over social media data

Social media services have already become main sources for monitoring emerging topics and sensing real-life events. A social media platform manages social stream consisting of a huge volume of timestamped user generated data, including original data and repost data. However, previous research on keyword search over social media data mainly emphasizes on the recency of information. In this paper, we first propose a problem of top-k most significant temporal keyword query to enable more complex query analysis. It returns top-k most popular social items that contain the keywords in the given query time window. Then, we design a temporal inverted index with two-tiers posting list to index social time series and a segment store to compute the exact social significance of social items. Next, we implement a basic query algorithm based on our proposed index structure and give a detailed performance analysis on the query algorithm. From the analysis result, we further refine our query algorithm with a piecewise maximum approximation (PMA) sketch. Finally, extensive empirical studies on a real-life microblog dataset demonstrate the combination of two-tiers posting list and PMA sketch achieves remarkable performance improvement under different query settings.