On Multiobjective Evolution Model

Self-Organized Criticality (SOC) phenomena could have a significant effect on the dynamics of ecosystems. The Bak-Sneppen (BS) model is a simple and robust model of biological evolution that exhibits punctuated equilibrium behavior. Here we will introduce random version of BS model. Also we generalize the single objective BS model to a multiobjective one.Comment: 6 pages, 5 figure

A parallel algorithm for Hamiltonian matrix construction in electron-molecule collision calculations: MPI-SCATCI

Construction and diagonalization of the Hamiltonian matrix is the rate-limiting step in most low-energy electron -- molecule collision calculations. Tennyson (J Phys B, 29 (1996) 1817) implemented a novel algorithm for Hamiltonian construction which took advantage of the structure of the wavefunction in such calculations. This algorithm is re-engineered to make use of modern computer architectures and the use of appropriate diagonalizers is considered. Test calculations demonstrate that significant speed-ups can be gained using multiple CPUs. This opens the way to calculations which consider higher collision energies, larger molecules and / or more target states. The methodology, which is implemented as part of the UK molecular R-matrix codes (UKRMol and UKRMol+) can also be used for studies of bound molecular Rydberg states, photoionisation and positron-molecule collisions.Comment: Write up of a computer program MPI-SCATCI Computer Physics Communications, in pres

Sidelobe Control in Collaborative Beamforming via Node Selection

Collaborative beamforming (CB) is a power efficient method for data communications in wireless sensor networks (WSNs) which aims at increasing the transmission range in the network by radiating the power from a cluster of sensor nodes in the directions of the intended base station(s) or access point(s) (BSs/APs). The CB average beampattern expresses a deterministic behavior and can be used for characterizing/controling the transmission at intended direction(s), since the mainlobe of the CB beampattern is independent on the particular random node locations. However, the CB for a cluster formed by a limited number of collaborative nodes results in a sample beampattern with sidelobes that severely depend on the particular node locations. High level sidelobes can cause unacceptable interference when they occur at directions of unintended BSs/APs. Therefore, sidelobe control in CB has a potential to increase the network capacity and wireless channel availability by decreasing the interference. Traditional sidelobe control techniques are proposed for centralized antenna arrays and, therefore, are not suitable for WSNs. In this paper, we show that distributed, scalable, and low-complexity sidelobe control techniques suitable for CB in WSNs can be developed based on node selection technique which make use of the randomness of the node locations. A node selection algorithm with low-rate feedback is developed to search over different node combinations. The performance of the proposed algorithm is analyzed in terms of the average number of trials required to select the collaborative nodes and the resulting interference. Our simulation results approve the theoretical analysis and show that the interference is significantly reduced when node selection is used with CB.Comment: 30 pages, 10 figures, submitted to the IEEE Trans. Signal Processin

Low Momentum Classical Mechanics with Effective Quantum Potentials

A recently introduced effective quantum potential theory is studied in a low momentum region of phase space. This low momentum approximation is used to show that the new effective quantum potential induces a space-dependent mass and a smoothed potential both of them constructed from the classical potential. The exact solution of the approximated theory in one spatial dimension is found. The concept of effective transmission and reflection coefficients for effective quantum potentials is proposed and discussed in comparison with an analogous quantum statistical mixture problem. The results are applied to the case of a square barrier.Comment: 4 figure

Vortex-scalar element calculations of a diffusion flame stabilized on a plane mixing layer

The vortex-scalar element method, a scheme which utilizes vortex elements to discretize the region of high vorticity and scalar elements to represent species or temperature fields, is utilized in the numerical simulations of a two-dimensional reacting mixing layer. Computations are performed for a diffusion flame at high Reynolds and Peclet numbers without resorting to turbulence models. In the nonreacting flow, the mean and fluctuation profiles of a conserved scalar show good agreement with experimental measurements. Results for the reacting flow indicate that for temperature independent kinetics, the chemical reaction begins immediately downstream of the splitter plate where mixing starts. Results for the reacting flow with Arrhenius kinetics show an ignition delay, which depends on reactant temperature, before significant chemical reaction occurs. Harmonic forcing changes the structure of the layer, and concomitantly the rates of mixing and reaction, in accordance with experimental results. Strong stretch within the braids in the nonequilibrium kinetics case causes local flame quenching due to the temperature drop associated with the large convective fluxes

Managing the Uncertainty Associated with Hydrogen Gas Hazards and Operability Issues in Nuclear Chemical Plants

The complex and diverse nature of reprocessing and decommissioning operations in existing nuclear chemical plants within the UK results in a variety of challenges. The challenges relate to the quantified risk from hydrogen explosions and how best to manage the associated uncertainties. Several knowledge gaps in terms of the Quantified Risk Assessment (QRA) of hydrogen hazards have been identified in this research work. These include radiolytic hydrogen explosions in sealed process pipes, the failure of ventilation systems used to dilute radiolytic hydrogen in process vessels, the decision uncertainty in installing additional hydrogen purge systems and the uncertainty associated with hold-up of hydrogen in radioactive sludges. The effect of a subsequent sudden release of the heldup hydrogen gas into a vessel ullage space presents a further knowledge gap. Nuclear decommissioning and reprocessing operations also result in operational risk knowledge gaps including the mixing behaviour of radioactive sludges, the performance of robotics for nuclear waste characterisation and control of nuclear fission products associated with solid wastes. Bayesian Belief Networks (BBNs) and Monte Carlo Simulation (MC) techniques have been deployed in this research work to address the identified knowledge gaps. These techniques provide a powerful means of uncertainty analysis of complex systems involving multiple interdependent variables such as those affecting nuclear decommissioning and reprocessing. Through the application of BBN and MC Simulation methodologies to a series of nuclear chemical plant case studies, new knowledge in decommissioning and reprocessing operations has been generated. This new knowledge relates to establishing a realistic quantified risk from hydrogen explosions and nuclear plant operability issues. New knowledge in terms of the key sensitivities affecting the quantified risk of hydrogen explosions and operability in nuclear environments as well as the optimum improvements necessary to mitigate such risks has also been gained