Failure in porous granular aggregates

We use a 3D Lattice Element Method, based on the discretization of the particles and binding matrix on a regular lattice, to investigate the particle-scale origins of the strength and failure of porous granular aggregates under tensile loading. Damage growth is analyzed by considering the evolution of stress probability density and the number of broken bonds in the particle phase. We show that the stress probability density functions are increasingly broader for a decreasing matrix volume fraction, the stresses being more and more concentrated in the interparticle contact zones with an exponential distribution as in cohesionless granular media [4]. We carried out a detailed parametric study in order to evaluate the combined influence of the matrix volume fraction and particlematrix adherence. Our findings are in agreement with 2D results previously reported in the literature [6]. Three regimes of crack propagation are evidenced, corresponding to no particle damage, particle abrasion and particle fragmentation, respectively. The crack morphology (tortuosity...) is another important feature that we investigate for different distributions of the particles and pores within porous granular aggregates

Influence of adsorption and anaerobic granular sludge characteristics on long chain fatty acids inhibition process

The impact of LCFA adsorption on the methanogenic activity was evaluated in batch assays for two anaerobic granular sludges in the presence and absence of bentonite as synthetic adsorbent. A clear inhibitory effect at an oleate (C18:1) concentration of 0.5 g(C18:1) L(-1) was observed for both sludges. Palmitate (C16:0) was confirmed to be the main intermediate of C18:1 degradation in not adapted sludge and its accumulation was further evidenced by fluorescence staining and microscopy techniques. LCFA inhibition could be decreased by the addition of bentonite, reducing the lag-phase and accelerating the kinetics of LCFA degradation, concluding in the importance of the adsorptive nature of the LCFA inhibitory process. Granule morphology and molecular profiling of predominant microorganisms revealed that biomass adaptation to LCFA could modify the intermediates accumulation profiles and process rates.This work was funded by the Spanish Ministry of Science and Innovation (projects ENE 2007-65850 and CTM 2010-18212), and was partially supported by a grand from the Department of Universities, Research and Media Society of Catalonia Government (BE-DGR 2008 BE1 00261). We would like to thank Lucia Neves, Ana Nicolau, Madalena Vieira, and Ana Julia Cavaleiro, from University of Minho, for their assistance in microscopic observations and analytical methods. We also thank Miriam Guivernau (IRTA) for assistance in the PCR-DGGE profiling and ribotype sequencing. We are also grateful to David Bedoya (MWH) and Francesc Prenafeta (IRTA) for the revision and critical reading of the manuscript

Multichannel Online Blind Speech Dereverberation with Marginalization of Static Observation Parameters in a Rao-Blackwellized Particle Filter

Room reverberation leads to reduced intelligibility of audio signals and spectral coloration of audio signals. Enhancement of acoustic signals is thus crucial for high-quality audio and scene analysis applications. Multiple sensors can be used to exploit statistical evidence from multiple observations of the same event to improve enhancement. Whilst traditional beamforming techniques suffer from interfering reverberant reflections with the beam path, other approaches to dereverberation often require at least partial knowledge of the room impulse response which is not available in practice, or rely on inverse filtering of a channel estimate to obtain a clean speech estimate, resulting in difficulties with non-minimum phase acoustic impulse responses. This paper proposes a multi-sensor approach to blind dereverberation in which both the source signal and acoustic channel are directly estimated from the distorted observations using their optimal estimators. The remaining model parameters are sampled from hypothesis distributions using a particle filter, thus facilitating real-time dereverberation. This approach was previously successfully applied to single-sensor blind dereverberation. In this paper, the single-channel approach is extended to multiple sensors. Performance improvements due to the use of multiple sensors are demonstrated on synthetic and baseband speech examples

Tensile strength and fracture of cemented granular aggregates

Cemented granular aggregates include a broad class of geomaterials such as sedimentary rocks and some biomaterials such as the wheat endosperm. We present a 3D lattice element method for the simulation of such materials, modeled as a jammed assembly of particles bound together by a matrix partially filling the interstitial space. From extensive simulation data, we analyze the mechanical properties of aggregates subjected to tensile loading as a function of matrix volume fraction and particle-matrix adhesion. We observe a linear elastic behavior followed by a brutal failure along a fracture surface. The effective stiffness before failure increases almost linearly with the matrix volume fraction. We show that the tensile strength of the aggregates increases with both the increasing tensile strength at the particle-matrix interface and decreasing stress concentration as a function of matrix volume fraction. The proportion of broken bonds in the particle phase reveals a range of values of the particle-matrix adhesion and matrix volume fraction for which the cracks bypass the particles and hence no particle damage occurs. This limit is shown to depend on the relative toughness of the particle-matrix interface with respect to the particles

Failure in porous granular aggregates

We use a 3D Lattice Element Method, based on the discretization of the particles and binding matrix on a regular lattice, to investigate the particle-scale origins of the strength and failure of porous granular aggregates under tensile loading. Damage growth is analyzed by considering the evolution of stress probability density and the number of broken bonds in the particle phase. We show that the stress probability density functions are increasingly broader for a decreasing matrix volume fraction, the stresses being more and more concentrated in the interparticle contact zones with an exponential distribution as in cohesionless granular media [4]. We carried out a detailed parametric study in order to evaluate the combined influence of the matrix volume fraction and particlematrix adherence. Our findings are in agreement with 2D results previously reported in the literature [6]. Three regimes of crack propagation are evidenced, corresponding to no particle damage, particle abrasion and particle fragmentation, respectively. The crack morphology (tortuosity...) is another important feature that we investigate for different distributions of the particles and pores within porous granular aggregates

Failure in porous granular aggregates

We use a 3D Lattice Element Method, based on the discretization of the particles and binding matrix on a regular lattice, to investigate the particle-scale origins of the strength and failure of porous granular aggregates under tensile loading. Damage growth is analyzed by considering the evolution of stress probability density and the number of broken bonds in the particle phase. We show that the stress probability density functions are increasingly broader for a decreasing matrix volume fraction, the stresses being more and more concentrated in the interparticle contact zones with an exponential distribution as in cohesionless granular media [4]. We carried out a detailed parametric study in order to evaluate the combined influence of the matrix volume fraction and particlematrix adherence. Our findings are in agreement with 2D results previously reported in the literature [6]. Three regimes of crack propagation are evidenced, corresponding to no particle damage, particle abrasion and particle fragmentation, respectively. The crack morphology (tortuosity...) is another important feature that we investigate for different distributions of the particles and pores within porous granular aggregates