A stabilization approach for mesh-free simulations of systems developing shocks or extreme strain localizations

A new stabilization scheme, based on a stochastic representation of the discretized field variables, is proposed with a view to reduce or even eliminate unphysical oscillations in the mesh-free numerical simulations of systems developing shocks or exhibiting localized bands of extreme deformation in the response. The origin of the stabilization scheme may be traced to nonlinear stochastic filtering and, consistent with a class of such filters, gain-based additive correction terms are applied to the simulated solution of the system, herein achieved through the element-free Galerkin method, in order to impose a set of constraints that help arresting the spurious oscillations. The method is numerically illustrated through its Applications to inviscid Burgers' equations, wherein shocks may develop as a result of intersections of the characteristics, and to a gradient plasticity model whose response is often characterized by a developing shear band as the external load is gradually increased. The potential of the method in stabilized yet accurate numerical simulations of such systems involving extreme gradient variations in the response is thus brought forth. (C) 2014 Elsevier Ltd. All rights reserved.

Joint Channel Estimation and Data Detection in MIMO-OFDM Systems: A Sparse Bayesian Learning Approach

The impulse response of wireless channels between the N-t transmit and N-r receive antennas of a MIMO-OFDM system are group approximately sparse (ga-sparse), i.e., NtNt the channels have a small number of significant paths relative to the channel delay spread and the time-lags of the significant paths between transmit and receive antenna pairs coincide. Often, wireless channels are also group approximately cluster-sparse (gac-sparse), i.e., every ga-sparse channel consists of clusters, where a few clusters have all strong components while most clusters have all weak components. In this paper, we cast the problem of estimating the ga-sparse and gac-sparse block-fading and time-varying channels in the sparse Bayesian learning (SBL) framework and propose a bouquet of novel algorithms for pilot-based channel estimation, and joint channel estimation and data detection, in MIMO-OFDM systems. The proposed algorithms are capable of estimating the sparse wireless channels even when the measurement matrix is only partially known. Further, we employ a first-order autoregressive modeling of the temporal variation of the ga-sparse and gac-sparse channels and propose a recursive Kalman filtering and smoothing (KFS) technique for joint channel estimation, tracking, and data detection. We also propose novel, parallel-implementation based, low-complexity techniques for estimating gac-sparse channels. Monte Carlo simulations illustrate the benefit of exploiting the gac-sparse structure in the wireless channel in terms of the mean square error (MSE) and coded bit error rate (BER) performance.

Renormalization group approach on nanostructured systems

The electronic spectra of one-dimensional nanostructured systems are calculated within the pure hopping model on the tight-binding Hamiltonian. By means of the renormalization group Green's function method, the dependence of the density of states on the distributions of nanoscaled grains and the changes of values of hopping integrals in nanostructured systems are studied. It is found that the frequency shifts are dependent rather on the changes of the hopping integrals at nanoscaled grains than the distribution of nanoscaled grains.

An approach to valuing ponds within farming systems for aquaculture

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A complex systems modelling approach for decentralized simulation of electrical microgrids

ICECCS 2010

Commercial aquaculture in Nigeria: a vertically integrated approach in the commercial freshwater farming of tilapia in floating bamboo net-hapas and cages systems

Tilapia once termed "poor man's" fish, still remains as the highly-priced food fish in many developing countries. The good attributes of this fish prompt its use in intensive aquaculture vertically integrated systems (VIS) which embrace broodstock development, hatchery/nursery and growout phase. Based on the series of studies carried out at Kainji Lake Research Institute, in New Bussa, Nigeria using Oreochromis (Tilapia niloticus) in floating bamboo hapas/cages, the recommended intensive modular systems were estimated to be capable of producing 4 million Tilapia fingerlings and 729 tons fish (Market-size) annually. Cost-benefit analysis showed the venture to have high prospects. It is recommended that priority be given to Tilapia cage culture at the national level in order to contribute immensely towards increased fish production