Dust acoustic solitary and shock waves in coupled dusty plasmas with variable dust charge and vortex-like ion distribution

The modified Kodomtsev-Petviashvili-Burger (mKP-Burger) and Kodomtsev-Petviashvili-Burger equations are derived in strongly coupled dusty plasmas containing iso-nonthermal ions; Boltzmann distributed electrons and variable dust charge. We use reductive perturbation method and discuss on solitary waves and shock waves solutions of these equations.     

Some aspects of entropic gravity in the presence of a noncommutative Schwarzschild-deSitter black hole

We study some features of entropic force approach in the presence of a noncommutative Schwarzschild-deSitter black hole. In this setup, there exists a similarity between the small and large scales. There are two finite cut-off in very short and long distances wherein the force and energy graph stop abruptly at those scales. We find that the existence of a deSitter core around the origin, induced by noncommutativity, in addition to a standard deSitter background at large scale may lead to a violation of the equivalence principle. Finally in order to directly observe the finite cut-off at short-scale gravity, caused by noncommutativity quantum fluctuations, we derive an effective gravitational constant.     

Conventional vs. modified pseudo-dynamic seismic analyses in the shallow strip footing bearing capacity problem

The conventional pseudo-dynamic(CPD) and modified pseudo-dynamic(MPD) methods are invoked to obtain the seismic bearing capacity of strip foundations using the limit equilibrium method, with a two-wedge failure mechanism.A spectral version of the conventional pseudo-dynamic method(SPD) is also invoked by considering the ground motion amplification factor, to be a function of the non-dimensional frequency λ/B and soil damping. Numeric analyses show that bearing capacity results obtained by the MPD and SPD methods are generally consistent. Both experience the same general reduction in bearing capacity with the increase of λ/B, with successive ups and downs corresponding to soil′s natural frequencies. For 5λ/B10, SPD and MPD results fluctuated between falling above and below CPD results. For λ/B2.5, SPD and MPD results were consistent with attenuation of the shear wave, while for 10λ/B, amplification was exhibited. Results obtained by the CPD method monotonically decrease, due to the fact that CPD fails to inherently consider site effects and damping, and instead and relies on a single factor to consider the ground motion amplification.     

Preparation of frost atlas using different interpolation methods in a semiarid region of south of Iran

In this research, suitability of different kriging and inverse distance weighted (IDW) methods in estimating occurrence date of frost was evaluated. Data included minimum daily air temperature values from 27 meteorological stations of Fars province in southern Iran from 18 to 45 years. Data ranges of 0 to ?1.5, ?1.5 to ?3 and below ?3°C were considered as mild, moderate and severe frost intensities, respectively. Starting with the first day of autumn, iso-occurrence days for the frost intensities and occurrence probabilities (25%, 50%, 75% and 90%) were estimated using ordinary kriging, cokriging, residual kriging type 1 (RK1), residual kriging type 2 (RK2), universal kriging and IDW methods. In these models, the errors of estimated frost intensities at different probabilities were lowest in the RK2 model, but lack of establishment of spatial structure due to long distance between stations caused the predictions not to be acceptable in some cases. In a proposed method (modified inverse distance weighted, MIDW), the trend between the first and last days of frost occurrence with earth elevation was removed, and the reminder values were estimated by (IDW) method. Although, the errors for estimated frost dates by MIDW and RK2 methods were the same, but the MIDW method did not have the spatial establishment shortcoming. Furthermore, the simplicity and practicality of the MIDW method makes it a reasonable selection.     

Annual precipitation forecast for west, southwest, and south provinces of Iran using artificial neural networks

Rainfed agriculture plays an important role in the agricultural production of the southern and western provinces of Iran. In rainfed agriculture, the adequacy of annual precipitation is considered as an important factor for dryland field and supplemental irrigation management. Different methods can be used for predicting the annual precipitation based on climatic and non-climatic inputs. Among which artificial neural networks (ANN) is one of these methods. The purpose of this research was to predict the annual precipitation amount (millimeters) in the west, southwest, and south of Islamic Republic of Iran with the total area of 394,259?km², by applying non-climatic inputs according to the long-time average precipitation in each station (millimeters), 47.5?mm precipitation since the first of autumn (day), t _47.5, and other effective parameters like coordinate and altitude of the stations, by using the artificial neural networks. In order to intelligently estimate the annual amount of precipitation in the study regions (ten provinces), feedforward backpropagation artificial neural network model has been used (method I). To predict the annual precipitation amount more accurately, the region under study was divided into three sub-regions, according to the precipitation mapping, and for each sub-region, the neural networks were developed using t _47.5 and long-time average annual precipitation in each station (method II). It is concluded that neural networks did not significantly increase the prediction accuracy in the study area compared with multiple regression model proposed by other investigators. However, in case of ANN, it is better to use a structure of 2–6–6–10–1 and Levenberg–Marquardt learning algorithm and sigmoid logistic activation function for prediction of annual precipitation.     

Effect of sulphates and curing period on stress–strain curves and failure modes of soil–lime–natural pozzolana mixtures

Abstract

An experimental investigation was undertaken in order to assess the effect of sodium (Na₂SO₄) and calcium (CaSO₄·2H₂O) sulphates and curing period on stress–strain curves and failure modes of grey (GS) and red (RS) clayey soils stabilised by lime (L), natural pozzolana (NP) and their combinations (L–NP). Several soil–L–NP mixtures were studied to be used as subgrade soils for road pavements. Stress–strain curves were obtained from unconfined compressive strength (UCS) test made on several soil–L–NP specimens after curing for 7 and 120 days. Tests results showed that the use of L or L–NP without sulphates produced a significant increase in peaks stress of both clayey soils and then modified their stress–strain curves from nonlinear to linear behaviour almost up to 70% of peak stress after a longer curing period. However, the presence of 2% Na₂SO₄ or any CaSO₄·2H₂O content provided beneficial effects on peaks stress and stress–strain curves of both stabilised clayey soils and then improved their linearity almost up to 95% of peak stress after curing for 120 days. In contrast, the presence of 6% Na₂SO₄ caused undesirable effects. In addition, both sulphates greatly affected the failure modes of soil–L–NP specimens, particularly at a later stage.     

Ion acoustic shock waves in weakly relativistic and dissipative plasmas with nonthermal electrons and thermal positrons

Propagation of ion acoustic waves in plasmas containing electrons, positrons and high relativistic ions is investigated. It is shown that the Korteweg-de Vries (KdV) equation describes the nonlinear waves in this media. The amplitude and energy of the KdV solitary waves are derived and the effects of relativistic ions on these quantities are discussed.     

Ion acoustic solitons of KdV and modified KdV equations in weakly relativistic plasma containing nonthermal electron,positron and warm ion

In this paper, the ion-acoustic solitons in a weakly relativistic electron-positron-ion plasma have been investigated. Relativistic ions, Maxwell-Boltzmann distributed positrons and nonthermal electrons are considered in collisionless warm plasma. Using a reductive perturbation theory, a Korteweg-de Vries (KdV) equation is derived, and the relativistic effect on the solitons is studied. It is found that the amplitude of solitary waves of the KdV equation diverges at the critical values of plasma parameters. Finally, in this situation, the solitons of a modified KdV (mKdV) equation with finite amplitude is derived.     

Effect of <Emphasis Type="Italic">q</Emphasis>-nonextensive distribution of electrons on electron acoustic solitons

Ion acoustic shock waves (IASWs) are studied in a plasma consisting of electrons, positrons and ions. Boltzmann distributed positrons and superthermal electrons are considered in the plasma. The dissipation is taken into account the kinematic viscosity among the plasma constituents. The Korteweg–de Vries–Burgers (KdV–Burgers) equation is derived by reductive perturbation method. Shock waves are solutions of KdV–Burgers equation. It is observed that an increasing positron concentration decreases the amplitude of the waves. Furthermore, in the existence of the kinematic viscosity among the plasma, the shock wave structure appears. The effects of ion kinematic viscosity (η ₀) and the superthermal parameter (k) on the ion acoustic waves are found.     

Online Multi-step Ahead Prediction of Time-Varying Solar and Geomagnetic Activity Indices via Adaptive Neurofuzzy Modeling and Recursive Spectral Analysis

The time-varying Sun as the main source of space weather affects the Earth??s magnetosphere by emitting hot magnetized plasma in the form of solar wind into interplanetary space. Solar and geomagnetic activity indices and their chaotic characteristics vary abruptly during solar and geomagnetic storms. This variation depicts the difficulties in modeling and long-term prediction of solar and geomagnetic storms. On the other hand, the combination of neurofuzzy models and spectral analysis has been a subject of interest due to their many practical applications in modeling and predicting complex phenomena. However, these approaches should be trained by algorithms that need to be carried out by an offline data set, which influences their performance in online modeling and prediction of time-varying phenomena. This paper proposes an adaptive approach for multi-step ahead prediction of space weather indices by extending the regular singular spectrum analysis and locally linear neurofuzzy models to adaptive approaches. The combination of these recursive approaches fulfills requirements of long-term prediction of solar and geomagnetic activity indices. The results demonstrate the power of the proposed method in online prediction of space weather indices.