Experimental study on shrinkage behaviour and prediction of shrinkage magnitudes of residual soils

The present study examines the shrinkage behaviour of residually derived black cotton (BC) soil and red soil compacted specimens that were subjected to air-drying from the swollen state. The soil specimens were compacted at varying dry density and moisture contents to simulate varied field conditions. The void ratio and moisture content of the swollen specimens were monitored during the drying process and relationship between them is analyzed. Shrinkage is represented as reduction in void ratio with decrease in water content of soil specimens. It is found to occur in three distinct stages. Total shrinkage magnitude depends on the type of clay mineral present. Variation in compaction conditions effect marginally total shrinkage magnitudes of BC soil specimens but have relatively more effect on red soil specimens. A linear relation is obtained between total shrinkage magnitude and volumetric water content of soil specimens in swollen state and can be used to predict the shrinkage magnitude of soils.

Parametric finite element analyses of geocellsupported embankments

This paper presents the results from parametric finite element analyses of geocell-supported embankments constructed on weak foundation soils. A composite model is used to numerically simulate the improvement in the strength and stiffness of the soil as a result of geocell confinement. The shear strength of the geocell-encased soil is obtained as a function of the additional confining pressure due to the geocell encasement considering it as a thin cylinder subjected to internal pressure. The stiffness of the geocell-encased soil is obtained from the stiffness of the unreinforced soil and the tensile modulus of the geocell material using an empirical equation. The validity of the model is verified by simulating the laboratory experiments on model geocell-supported embankments. Parametric finite element analyses of the geocell-supported embankments are carried out by varying the dimensions of the geocell layer, the tensile strength of the material used for fabricating the geocell layer, the properties of the infill soil, and the depth of the foundation layer. Some important guidelines for selecting the geocell reinforcement to support embankments on weak foundation soils are established through these numerical studies.

Hybrid moving block bootstrap for stochastic simulation of multi-site multi-season streamflows

The Hybrid approach introduced by the authors for at-site modeling of annual and periodic streamflows in earlier works is extended to simulate multi-site multi-season streamflows. It bears significance in integrated river basin planning studies. This hybrid model involves: (i) partial pre-whitening of standardized multi-season streamflows at each site using a parsimonious linear periodic model; (ii) contemporaneous resampling of the resulting residuals with an appropriate block size, using moving block bootstrap (non-parametric, NP) technique; and (iii) post-blackening the bootstrapped innovation series at each site, by adding the corresponding parametric model component for the site, to obtain generated streamflows at each of the sites. It gains significantly by effectively utilizing the merits of both parametric and NP models. It is able to reproduce various statistics, including the dependence relationships at both spatial and temporal levels without using any normalizing transformations and/or adjustment procedures. The potential of the hybrid model in reproducing a wide variety of statistics including the run characteristics, is demonstrated through an application for multi-site streamflow generation in the Upper Cauvery river basin, Southern India. (C) 2004 Elsevier B.V. All rights reserved.

Strong shock with radiation near the surface of a star

The propagation of a shock wave, originating in a stellar interior, is considered when it approaches the surface of the star and assumes a self-similar character, "forgetting" its initial conditions. The flow behind the shock is assumed to be spatially isothermal rather than adiabatic to simulate the conditions of large radiative transfer near the stellar surface. The adiabatic and isothermal flows behind such a shock are compared. The exact shock-propagation laws, obtained by solving the equations in similarity variables, for different values of the parameter δ in the undisturbed density law, ρ0 ∝ xδ, and γ, the ratio of specific heats, are compared with the approximate values calculated by Whitham's characteristic rule and the two show a generally good agreement.

Detection of Tsunami Wave Generation and Propagation Using Fiber Bragg Grating Sensors

This paper describes the design and development of a Fiber Bragg Grating (FBG) sensor system for monitoring tsunami waves generated in the deep ocean. An experimental setup was designed and fabricated to simulate the generation and propagation of a tsunami wave. The characteristics and efficiency of the developed FBG sensor was evaluated with a standard commercial Digiquartz sensor. For real time monitoring of tsunami waves, FBG sensors bonded to a cantilever is used and the wavelength shifts (Delta lambda(B)) in the reflected spectra resulting from the strain/pressure imparted on the FBGs have been recorded using a high-speed Micron Optics FBG interrogation system. The parameters sensed are the signal burst during tsunami generation and pressure variations at different places as the tsunami wave propagates away from the source of generation. The results obtained were compared with the standard commercial sensor used in tsunami detection. The observations suggest that the FBG sensor was highly sensitive and free from many of the constraints associated with the commercial tsunameter.

Slip line field analysis of a simple plane strain closed‐die forging

A slip line field is proposed for symmetrical single‐cavity closed‐die forging by rough dies. A compatible velocity field is shown to exist. Experiments were conducted using lead workpiece and rough dies. Experimentally observed flow and load were used to validate the proposed slip line field. The slip line field was used to simulate the process in the computer with the objective of studying the influence of flash geometry on cavity filling.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications. (C) 2005 Elsevier B. V. All rights reserved.

Effect of process variables on die-billet temperature history in a slow speed hot coining type process

A computer code is developed as a part of an ongoing project on computer aided process modelling of forging operation, to simulate heat transfer in a die-billet system. The code developed on a stage-by-stage technique is based on an Alternating Direction Implicit scheme. The experimentally validated code is used to study the effect of process specifics such as preheat die temperature, machine ascent time, rate of deformation, and dwell time on the thermal characteristics in a batch coining operation where deformation is restricted to surface level only.

Inelastic response of beams under sinusoidal and random loads

A new analytical model has been suggested for the hysteretic behaviour of beams. The model can be directly used in a response analysis without bothering to locate the precise point where the unloading commences. The model can efficiently simulate several types of realistic softening hysteretic loops. This is demonstrated by computing the response of cantilever beams under sinusoidal and random loadings. Results are presented in the form of graphs for maximum deflection, bending moment and shear

The 26 July 2005 heavy rainfall event over Mumbai: numerical modeling aspects

The performance of the Advanced Regional Prediction System (ARPS) in simulating an extreme rainfall event is evaluated, and subsequently the physical mechanisms leading to its initiation and sustenance are explored. As a case study, the heavy precipitation event that led to 65 cm of rainfall accumulation in a span of around 6 h (1430 LT-2030 LT) over Santacruz (Mumbai, India), on 26 July, 2005, is selected. Three sets of numerical experiments have been conducted. The first set of experiments (EXP1) consisted of a four-member ensemble, and was carried out in an idealized mode with a model grid spacing of 1 km. In spite of the idealized framework, signatures of heavy rainfall were seen in two of the ensemble members. The second set (EXP2) consisted of a five-member ensemble, with a four-level one-way nested integration and grid spacing of 54, 18, 6 and 1 km. The model was able to simulate a realistic spatial structure with the 54, 18, and 6 km grids; however, with the 1 km grid, the simulations were dominated by the prescribed boundary conditions. The third and final set of experiments (EXP3) consisted of a five-member ensemble, with a four-level one-way nesting and grid spacing of 54, 18, 6, and 2 km. The Scaled Lagged Average Forecasting (SLAF) methodology was employed to construct the ensemble members. The model simulations in this case were closer to observations, as compared to EXP2. Specifically, among all experiments, the timing of maximum rainfall, the abrupt increase in rainfall intensities, which was a major feature of this event, and the rainfall intensities simulated in EXP3 (at 6 km resolution) were closest to observations. Analysis of the physical mechanisms causing the initiation and sustenance of the event reveals some interesting aspects. Deep convection was found to be initiated by mid-tropospheric convergence that extended to lower levels during the later stage. In addition, there was a high negative vertical gradient of equivalent potential temperature suggesting strong atmospheric instability prior to and during the occurrence of the event. Finally, the presence of a conducive vertical wind shear in the lower and mid-troposphere is thought to be one of the major factors influencing the longevity of the event.

Performance of a small solar pond in the tropics

The performance of the 240 m2 solar pond in Bangalore is discussed. The problems of erosion of gradient zone and formation of internal convective zones is highlighted. The technique of passive salt addition is shown to be a viable alternative for salt recycling. Different techniques of heat extraction are discussed and the use of an immersed copper heat exchanger is shown to be most convenient. A two-zone model for prediction of the seasonal structure of the solar pond performance is proposed. The model is shown to simulate the seasonal structure of the observed variation of the temperature in the storage zone.

A simple method for potential flow simulation of cascades

A simple method using a combination of conformal mapping and vortex panel method to simulate potential flow in cascades is presented. The cascade is first transformed to a single body using a conformal mapping, and the potential flow over this body is solved using a simple higher order vortex panel method. The advantage of this method over existing methodologies is that it enables the use of higher order panel methods, as are used to solve flow past an isolated airfoil, to solve the cascade problem without the need for any numerical integrations or iterations. The fluid loading on the blades, such as the normal force and pitching moment, may be easily calculated from the resultant velocity field. The coefficient of pressure on cascade blades calculated with this methodology shows good agreement with previous numerical and experimental results.

Parallel Tempering Simulations of Liquid-Phase Adsorption of n-Alkane Mixtures in Zeolite LTA-5A

Adsorption of n-alkane mixtures in the zeolite LTA-5A under liquid-phase conditions has been studied using grand canonical Monte Carlo (GCMC) simulations combined with parallel tempering. Normal GCMC techniques fail for some of these systems due to the preference of linear molecules to coil within a single cage in the zeolite. The narrow zeolite windows severerly restrict interactions of the molecules, making it difficult to simulate cooperative rearrangements necessary to explore configuration space. Because of these reasons, normal GCMC simulations results show poor reproducibility in some cases. These problems were overcome with parallel tempering techniques. Even with parallel tempering, these are very challenging systems for molecular simulation. Similar problems may arise for other zeolites such as CHA, AFX, ERI, KFI, and RHO having cages connected by narrow windows. The simulations capture the complex selectivity behavior observed in experiments such as selectivity inversion and azeotrope formation.

Seasonal prediction of the Indian monsoon

Under the project `Seasonal Prediction of the Indian Monsoon' (SPIM), the prediction of Indian summer monsoon rainfall by five atmospheric general circulation models (AGCMs) during 1985-2004 was assessed. The project was a collaborative effort of the coordinators and scientists from the different modelling groups across the country. All the runs were made at the Centre for Development of Advanced Computing (CDAC) at Bangalore on the PARAM Padma supercomputing system. Two sets of simulations were made for this purpose. In the first set, the AGCMs were forced by the observed sea surface temperature (SST) for May-September during 1985-2004. In the second set, runs were made for 1987, 1988, 1994, 1997 and 2002 forced by SST which was obtained by assuming that the April anomalies persist during May-September. The results of the first set of runs show, as expected from earlier studies, that none of the models were able to simulate the correct sign of the anomaly of the Indian summer monsoon rainfall for all the years. However, among the five models, one simulated the correct sign in the largest number of years and the second model showed maximum skill in the simulation of the extremes (i.e. droughts or excess rainfall years). The first set of runs showed some common bias which could arise either from an excessive sensitivity of the models to El Nino Southern Oscillation (ENSO) or an inability of the models to simulate the link of the Indian monsoon rainfall to Equatorial Indian Ocean Oscillation (EQUINOO), or both. Analysis of the second set of runs showed that with a weaker ENSO forcing, some models could simulate the link with EQUINOO, suggesting that the errors in the monsoon simulations with observed SST by these models could be attributed to unrealistically high sensitivity to ENSO.