Solving chemical dynamic optimization problems with ranking-based differential evolution algorithms

Dynamic optimization problems(DOPs) described by differential equations are often encountered in chemical engineering. Deterministic techniques based on mathematic programming become invalid when the models are non-differentiable or explicit mathematical descriptions do not exist. Recently, evolutionary algorithms are gaining popularity for DOPs as they can be used as robust alternatives when the deterministic techniques are invalid. In this article, a technology named ranking-based mutation operator(RMO) is presented to enhance the previous differential evolution(DE) algorithms to solve DOPs using control vector parameterization. In the RMO, better individuals have higher probabilities to produce offspring, which is helpful for the performance enhancement of DE algorithms. Three DE-RMO algorithms are designed by incorporating the RMO. The three DE-RMO algorithms and their three original DE algorithms are applied to solve four constrained DOPs from the literature. Our simulation results indicate that DE-RMO algorithms exhibit better performance than previous non-ranking DE algorithms and other four evolutionary algorithms.

An experimental study on fracture mechanical behavior of rock-like materials containing two unparallel fissures under uniaxial compression

Strength and deformability characteristics of rock with pre-existing fissures are governed by cracking behavior. To further research the effects of pre-existing fissures on the mechanical properties and crack coalescence process, a series of uniaxial compression tests were carried out for rock-like material with two unparallel fissures.In the present study, cement, quartz sand, and water were used to fabricate a kind of brittle rock-like material cylindrical model specimen. The mechanical properties of rock-like material specimen used in this research were all in good agreement with the brittle rock materials. Two unparallel fissures（a horizontal fissure and an inclined fissure） were created by inserting steel during molding the model specimen.Then all the pre-fissured rock-like specimens were tested under uniaxial compression by a rock mechanics servocontrolled testing system. The peak strength and Young＇s modulus of pre-fissured specimen all first decreased and then increased when the fissure angle increased from 0？to 75？.In order to investigate the crack initiation, propagation and coalescence process, photographic monitoring was adopted to capture images during the entire deformation process.Moreover, acoustic emission（AE） monitoring technique was also used to obtain the AE evolution characteristic of prefissured specimen. The relationship between axial stress, AE events, and the crack coalescence process was set up： when a new crack was initiated or a crack coalescence occurred, thecorresponding axial stress dropped in the axial stress–time curve and a big AE event could be observed simultaneously.Finally, the mechanism of crack propagation under microscopic observation was discussed. These experimental results are expected to increase the understanding of the strength failure behavior and the cracking mechanism of rock containing unparallel fissures.

Morphology and structure of extremely red objects at z ～ 1 in the CANDELS-COSMOS field

Using high-resolution HST/Wide Field Camera 3 F125W imaging from the CANDELS-COSMOS field, we report the structural and morphological properties of extremely red objects （EROs） at -z 1. Based on the UVJ color criteria, we sepa- rate EROs into two types： old passive galaxies （OGs） and dusty star-forming galaxies （DGs）. For a given stellar mass, we find that the mean size of OGs （DGs） is smaller by a factor of - 2 （1.5） than that of present-day early-type （late-type） galaxies at a rest-frame optical wavelength. We derive the average effective radii of OGs and DGs, corresponding to 2.09 ± 1.13 kpc and 3.27± 1.14 kpc, respectively. Generally, the DGs are heterogeneous, with mixed features including bulges, disks and irregular structures, with relatively high M20, large size and low G. By contrast, OGs have elliptical-like compact morphologies with lower M20, smaller size and higher G, indicating a more concentrated and symmetric spatial extent of the stellar population distribution in OGs than DGs. These findings imply that OGs and DGs have different evolutionary processes, and that the minor merger scenario is the most likely mechanism for the structural properties of OGs. However, the size evolution of DGs is possibly due to the secular evolution of galaxies.

Scaling Behavior for the Susceptibility of the Vacuum

Using the two-component superfluid model of Winterberg for space, two models for the susceptibility of the cosmic vacuum as a function of the cosmic scale parameter, a, are presented. We also consider the possibility that Newton’s constant can scale, i.e., G-1=G-1(a), to form the most general scaling laws for polarization of the vacuum. The positive and negative values for the Planckion mass, which form the basis of the Winterberg model, are inextricably linked to the value of G, and as such, both G and Planck mass are intrinsic properties of the vacuum. Scaling laws for the non-local, smeared, cosmic susceptibility, , the cosmic polarization, , the cosmic macroscopic gravitational field, , and the cosmic gravitational field mass density, , are worked out, with specific examples. At the end of recombination, i.e., the era of last scattering, using the polarization to explain dark matter, and the gravitational field mass density to explain dark energy, we find that, . While this is an unconventional assignment, differing from the ΛCDM model, we believe this is correct, as localized dark matter (LDM) contributions can be much higher in this epoch than cosmic smeared values for susceptibility. All density parameter assignments in Friedmanns’ equation are cosmic averages, valid for distance scales in excess of 100 Mpc in the current epoch. We also evaluate the transition from ordinary matter dominance, to dark matter dominance, for the cosmos as a whole. We obtain for the transition points, z=1.66, for susceptibility model I, and, z=2.53 , for susceptibility model II.

Shear failure behaviors and degradation mechanical model of rockmass under true triaxial multi-level loading and unloading shear tests OA

The redistribution of three-dimensional(3D)geostress during underground tunnel excavation can easily induce to shear failure along rockmass structural plane,potentially resulting in engineering disasters.However,the current understanding of rockmass shear behavior is mainly based on shear tests under2D stress without lateral stress,the shear fracture under 3D stress is unclear,and the relevant 3D shear fracture theory research is deficient.Therefore,this study conducted true triaxial cyclic loading and unloading shear tests on intact and bedded limestone under different normal stressσnand lateral stressσpto investigate the shear strength,deformation,and failure characteristics.The results indicate that under differentσnandσp,the stress–strain hysteresis loop area gradually increases from nearly zero in the pre-peak stage,becomes most significant in the post-peak stage,and then becomes very small in the residual stage as the number of shear test cycles increases.The shear peak strength and failure surface roughness almost linearly increase with the increase inσn,while they first increase and then gradually decrease asσpincreases,with the maximum increases of 12.9%for strength and 15.1%for roughness.The shear residual strength almost linearly increases withσn,but shows no significant change withσp.Based on the acoustic emission characteristic parameters during the test process,the shear fracture process and microscopic failure mechanism were analyzed.As the shear stressτincreases,the acoustic emission activity,main frequency,and amplitude gradually increase,showing a significant rise during the cycle near the peak strength,while remaining almost unchanged in the residual stage.The true triaxial shear fracture process presents tensile-shear mixture failure characteristics dominated by microscopic tensile failure.Based on the test results,a 3D shear strength criterion considering the lateral stress effect was proposed,and the determination methods and evolution of the shear modulus G,cohesion cjp,friction angleφjp,and dilation angleψjpduring rockmass shear fracture process were studied.Under differentσnandσp,G first rapidly decreases and then tends to stabilize;cjp,φjp,andψjpfirst increase rapidly to the maximum value,then decrease slowly,and finally remain basically unchanged.A 3D shear mechanics model considering the effects of lateral stress and shear parameter degradation was further established,and a corresponding numerical calculation program was developed based on3D discrete element software.The proposed model effectively simulates the shear failure evolution process of rockmass under true triaxial shear test,and is further applied to successfully reveal the failure characteristics of surrounding rocks with structural planes under different combinations of tunnel axis and geostress direction.

Multi-objective optimization of feature selection using hybrid cat swarm optimization

With the pervasive generation of information from a wide range of sensors and devices,there always exist a large number of input features in databases,thus complicating machine learning problem formulation.However,certain features are relatively impertinent to specific problems,which may degrade the performances of classifiers in terms of prediction accuracy,sensitivity,specificity,and recall rate.The main goal of a multi-objective optimization problem is to identify the subsets of the given features.To this end,a hybrid cat swarm optimization(HCSO)algorithm is proposed in our paper for performance improvement of the basic cat swarm optimization(CSO)that incorporates guided and competitive&inherent characteristics into the original CSO.The performance of HCSO has been tested by finding the optimal feature subset for 15 benchmark datasets.The number of class labels for these datasets varies between 2 and 40.The time complexity analysis of both CSO and HCSO has also been evaluated.Moreover,the performance of the proposed algorithm has been compared with that of simple CSO and other state-ofthe-art techniques.The performances obtained by HCSO have an average 2.68%improvement with a standard deviation of 2.91.The maximum performance improvement is up to 10.09%in prediction accuracy.Tested on the same datasets,CSO has yielded improvements within the range of-7.27%to 8.51%with an average improvement 0.9%and standard deviation 3.96.The statistical tests carried out in the experiments prove that HCSO manifests a moderately better feature selection capacity than that of its counterparts.