Comparison of different numerical methods for the solution of the time-fractional reaction-diffusion equation with variable diffusion coefficient

In this work we perform a comparison of two different numerical schemes for the solution of the time-fractional diffusion equation with variable diffusion coefficient and a nonlinear source term. The two methods are the implicit numerical scheme presented in [M.L. Morgado, M. Rebelo, Numerical approximation of distributed order reaction- diffusion equations, Journal of Computational and Applied Mathematics 275 (2015) 216-227] that is adapted to our type of equation, and a colocation method where Chebyshev polynomials are used to reduce the fractional differential equation to a system of ordinary differential equations

Novel anisotropic magnetoelectric effect on δ-FeO(OH)/P(VDF-TrFE) multiferroic composites

The last decade has witnessed an increased research effort on multi-phase magnetoelectric (ME) composites. In this scope, this paper presents the application of novel materials for the development of anisotropic magnetoelectric (ME) sensors based on δ-FeO(OH)/P(VDF-TrFE) composites. The composite is able to precisely determine the amplitude and direction of the magnetic field. A new ME effect is reported in this study, as it emerges from the magnetic rotation of the δ-FeO(OH) nanosheets inside the piezoelectric P(VDF-TrFE) polymer matrix. δ-FeO(OH)/P(VDF-TrFE) composites with 1, 5, 10 and 20 δ-FeO(OH) filler weigh percentage in three δ-FeO(OH) alignment states (random, transversal and longitudinal) have been developed. Results shown that the modulus of the piezoelectric response (10-24 pC.N-1) is stable at least up to three months, the shape and magnetization maximum value (3 emu.g-1) is dependent on δ-FeO(OH) content and the obtained ME voltage coefficient, with a maximum of ≈0.4 mV.cm-1.Oe-1, is dependent on the incident magnetic field direction and intensity. In this way, the produced materials are suitable for innovative anisotropic sensor and actuator applications.

Random walk forecast of urban water in Iran under uncertainty

There are two significant reasons for the uncertainties of water demand. On one hand, an evolving technological world is plagued with accelerated change in lifestyles and consumption patterns; and on the other hand, intensifying climate change. Therefore, with an uncertain future, what enables policymakers to define the state of water resources, which are affected by withdrawals and demands? Through a case study based on thirteen years of observation data in the Zayandeh Rud River basin in Isfahan province located in Iran, this paper forecasts a wide range of urban water demand possibilities in order to create a portfolio of plans which could be utilized by different water managers. A comparison and contrast of two existing methods are discussed, demonstrating the Random Walk Methodology, which will be referred to as the â On uncertainty pathâ , because it takes the uncertainties into account and can be recommended to managers. This On Uncertainty Path is composed of both dynamic forecasting method and system simulation. The outcomes show the advantage of such methods particularly for places that climate change will aggravate their water scarcity, such as Iran.