Projected Adaptive Cubic Regularization Algorithm with Derivative-Free Filter Technique for Box Constrained Optimization

An adaptive projected affine scaling algorithm of cubic regularization method using a filter technique for solving box constrained optimization without derivatives is put forward in the passage. The affine scaling interior-point cubic model is based on the quadratic probabilistic interpolation approach on the objective function. The new iterations are obtained by the solutions of the projected adaptive cubic regularization algorithm with filter technique. We prove the convergence of the proposed algorithm under some assumptions. Finally, experiments results showed that the presented algorithm is effective in detail.

Thermally activated intermittent dynamics of creeping crack fronts along disordered interfaces

We present a subcritical fracture growth model, coupled with the elastic redistribution of the acting mechanical stress along rugous rupture fronts. We show the ability of this model to quantitatively reproduce the intermittent dynamics of cracks propagating along weak disordered interfaces. To this end, we assume that the fracture energy of such interfaces (in the sense of a critical energy release rate) follows a spatially correlated normal distribution. We compare various statistical features from the obtained fracture dynamics to that from cracks propagating in sintered polymethylmethacrylate (PMMA) interfaces. In previous works, it has been demonstrated that such an approach could reproduce the mean advance of fractures and their local front velocity distribution. Here, we go further by showing that the proposed model also quantitatively accounts for the complex self-affine scaling morphology of crack fronts and their temporal evolution, for the spatial and temporal correlations of the local velocity fields and for the avalanches size distribution of the intermittent growth dynamics. We thus provide new evidence that an Arrhenius-like subcritical growth is particularly suitable for the description of creeping cracks.

Permeability Evolution During Shear Zone Initiation in Low-Porosity Rocks

Using an innovative experimental set-up (Punch-Through Shear test), we initiated a shear zone (microfault) in Flechtingen sandstone and Odenwald granite under in situ reservoir conditions while monitoring permeability and fracture dilation evolution. The shear zone, which has a cylindrical geometry, is produced by a self-designed piston assembly that punches down the inner part of the sample. Permeability and fracture dilation were measured for the entire duration of the experiment. After the shear zone generation, the imposed shear displacement was increased to 1.2 mm and pore pressure changes of $$\pm 5$$ ± 5 or $$\pm 10$$ ± 10 MPa were applied cyclically to simulate injection and production scenarios. Thin sections and image analysis tools were used to identify microstructural features of the shear zone. The geometry of the shear zone is shown to follow a self-affine scaling invariance, similar to the fracture surface roughness. The permeability evolution related to the onset of the fracture zone is different for both rocks: almost no enhancement for the Flechtingen sandstone and an increase of more than 2 orders of magnitude for the Odenwald granite. Further shear displacement resulted in a slight increase in permeability. A fault compaction is observed after shear relaxation which is associated to a permeability decrease by a factor more than 3. Permeability changes during pressure cycling are reversible when varying the effective pressure. The difference in permeability enhancement between the sandstone and the granite is related to the larger width of the shear zones.

On the simplex, interior-point and objective space approaches to multiobjective linear programming

Most Multiple Objective Linear Programming (MOLP) algorithms working in the decision variable space, are based on the simplex algorithm or interior-point method of Linear Programming. However, objective space based methods are becoming more and more prominent. This paper investigates three algorithms namely the Extended Multiobjective Simplex Algorithm (EMSA), Arbel’s Affine Scaling Interior-point (ASIMOLP) algorithm and Benson’s objective space Outer Approximation (BOA) algorithm. An extensive review of these algorithms is also included. Numerical results on non-trivial MOLP problems show that EMSA and BOA are at par and superior in terms of the quality of a most preferred nondominated point to ASIMOLP. However, ASIMOLP more than holds its own in terms of computing efficiency.

Radical Embodied Computation: Reproduction of Similarity by Analogy as an Order Generating Mechanism in Complex Systems

About two decades ago, scholars from the scientific disciplines that study human behavior and cognition, suggested an era of post-cognitivism was imminent, in which the computer metaphor, computationalism and representationalism would be discarded as viable theoretical frameworks for explaining phenomena of the body and the mind. In the present paper I argue that explanations of complex adaptive behavior require a theory of meaning mechanics that explains how complex adaptive systems can use semantic information to coordinate their behavior. This calls for a unification of sorts between the insights obtained in ecological psychology and embodied embedded cognition with principles of natural computation (cf. Decastro, 2007) in the context of explaining the behavior and properties of complex adaptive systems and networks (see e.g., Freeman et al., 2001; Chialvo, 2010; Flack, 2017a; Scheffer et al., 2018). I will refer to this framework as Radical Embodied Computation (REC++) and discuss some of the philosophical and theoretical issues that have to be resolved. I conclude by suggesting a mechanism for the emergence of meaning that is based the conception of self-affine scaling as the reproduction of similarity by analogy.