Direct tests of the entropic model of quasicrystals

Assuming an entropic origin for phason elasticity in quasicrystals, we derive predictions for the temperature dependence of grain-boundary structure and free energy, the nature of the elastic instability in these systems, and the behavior of sound damping near the instability. We believe that these will provide decisive tests of the entropic model for quasicrystals.

Continuity of plastic strain rate in stress relaxation tests

Stress relaxation testing is often utilised for determining whether athermal straining contributes to plastic flow; if plastic strain rate is continuous across the transition from tension to relaxation then plastic strain is fully thermally activated. This method was applied to an aged type 316 stainless steel tested in the temperature range 973–1123 K and to a high purity Al in the recrystallised annealed condition tested in the temperature range 274–417 K. The results indicated that plastic strain is thermally activated in these materials at these corresponding test temperatures. For Al, because of its high strain rate sensitivity, it was necessary to adopt a back extrapolation procedure to correct for the finite period that the crosshead requires to decelerate from the constant speed during tension to a dead stop for stress relaxation.

A new cryptic rock-dwelling Hemidactylus (Squamata: Gekkonidae) from south India

A new species of gecko, Hemidactylus graniticolus sp. nov. is described from Karnataka state, south India. This large-sized (SVL to at least 110.6 mm), rupicolous gecko differs from congeners in having 16-18 longitudinal rows of fairly regularly arranged, subtrihedral, weakly keeled, striated tubercles at midbody; 9-11 and 12-13 subdigital lamellae on the first and fourth digits, respectively, of both manus and pes; tail with transverse series of four enlarged tubercles on each tail segment; 23-28 femoral pores on each side separated by 1-3 poreless scales; 12-14 supralabials and 9-11 infralabials. Molecular data support the distinctiveness of the new species and its affinities with large-bodied, tuberculate Hemidactylus spp. from India and Sri Lanka.

On generating optimal signal probabilities for random tests: A genetic approach

Genetic Algorithms are robust search and optimization techniques. A Genetic Algorithm based approach for determining the optimal input distributions for generating random test vectors is proposed in the paper. A cost function based on the COP testability measure for determining the efficacy of the input distributions is discussed, A brief overview of Genetic Algorithms (GAs) and the specific details of our implementation are described. Experimental results based on ISCAS-85 benchmark circuits are presented. The performance pf our GA-based approach is compared with previous results. While the GA generates more efficient input distributions than the previous methods which are based on gradient descent search, the overheads of the GA in computing the input distributions are larger. To account for the relatively quick convergence of the gradient descent methods, we analyze the landscape of the COP-based cost function. We prove that the cost function is unimodal in the search space. This feature makes the cost function amenable to optimization by gradient-descent techniques as compared to random search methods such as Genetic Algorithms.

Repeated drop weight impacts and post-impact ILSS tests on glass-epoxy composite

E glass epoxy laminates of thicknesses in the range 2-5 mm were subjected to repeated impacts. For each thickness the number of hits to cause tup penetration was determined and the value of this number was higher the larger the thickness of the laminate tested. The C-scan, before and after impact, was done to obtain information regarding flaw distribution. Short beam shear test samples were made from locations at fixed distances from impact point and tested. The samples closer to the zone of impact showed lower strength values. Scanning fractography revealed shear deformation features for these samples and brittle fracture features for the region near the zone of impact.

Maintaining dynamic sequences under equality tests in polylogarithmic time

We present a randomized and a deterministic data structure for maintaining a dynamic family of sequences under equality tests of pairs of sequences and creations of new sequences by joining or splitting existing sequences. Both data structures support equality tests in O(1) time. The randomized version supports new sequence creations in O(log(2) n) expected time where n is the length of the sequence created. The deterministic solution supports sequence creations in O(log n (log m log* m + log n)) time for the mth operation.

Validation of processing maps for a 15Cr-15Ni-2.2Mo-0.3Ti austenitic stainless steel using hot forging and rolling tests

The processing maps are being developed for use in optimising hot workability and controlling the microstructure of the product. The present investigation deals with the examination to assess the prediction of the processing maps for a 15Cr-15Ni-2.2Mo-0.3Ti austenitic stainless steel using forging and rolling tests at different temperatures in the range of 600-1200 degreesC. The tensile properties of these deformed products were evaluated at room temperature. The influence of the processing conditions, i.e. strain rate and temperature on the tensile properties of the deformed product were analysed to identify the optimum processing parameters. The results have shown good agreement between the regimes exhibited by the map and the properties of the rolled or forged product. The optimum parameters for processing of this steel were identified as rolling or press forging at temperatures above 1050 degreesC to obtain optimum product properties. (C) 2002 Elsevier Science B.V. All rights reserved.

Stress-Strain Prediction of Jointed Rocks using Artificial Neural Networks

The applicability of Artificial Neural Networks for predicting the stress-strain response of jointed rocks at varied confining pressures, strength properties and joint properties (frequency, orientation and strength of joints) has been studied in the present paper. The database is formed from the triaxial compression tests on different jointed rocks with different confining pressures and different joint properties reported by various researchers. This input data covers a wide range of rock strengths, varying from very soft to very hard. The network was trained using a 3 layered network with feed forward back propagation algorithm. About 85% of the data was used for training and remaining15% for testing the predicting capabilities of the network. Results from the analyses were very encouraging and demonstrated that the neural network approach is efficient in capturing the complex stress-strain behaviour of jointed rocks. A single neural network is demonstrated to be capable of predicting the stress-strain response of different rocks, whose intact strength vary from 11.32 MPa to 123 MPa and spacing of joints vary from 10 cm to 100 cm for confining pressures ranging from 0 to 13.8 MPa.

A comparative study of ordinary kriging and support vector machine models for the spatial variability of rock depth in Bangalore

In this paper, reduced level of rock at Bangalore, India is arrived from the 652 boreholes data in the area covering 220 sq.km. In the context of prediction of reduced level of rock in the subsurface of Bangalore and to study the spatial variability of the rock depth, ordinary kriging and Support Vector Machine (SVM) models have been developed. In ordinary kriging, the knowledge of the semivariogram of the reduced level of rock from 652 points in Bangalore is used to predict the reduced level of rock at any point in the subsurface of Bangalore, where field measurements are not available. A cross validation (Q1 and Q2) analysis is also done for the developed ordinary kriging model. The SVM is a novel type of learning machine based on statistical learning theory, uses regression technique by introducing e-insensitive loss function has been used to predict the reduced level of rock from a large set of data. A comparison between ordinary kriging and SVM model demonstrates that the SVM is superior to ordinary kriging in predicting rock depth.

The Behaviour of Two-Phase Flow of DNAPL and Water through a Fractured Rock under Confining Pressure

This study presents the characterization of DNAPL and water flow in a fracture under confining pressure. A comprehensive mathematical model and the conditions under which DNAPL will enter an initially water-saturated deforming rock fracture are discussed. A numerical model with which to predict the quantity of each phase in terms of their saturations in deforming rock joint is developed. The effect of varying confining stresses on the traverse time of DNAPL across a fractured aquitard is studied. The sensitivity analysis for physical and hydraulic properties like initial fracture apertures, fracture dips, equivalent fracture aperture and confining pressures are performed and discussed.