Long-range automaton models of earthquakes: Power-law accelerations, correlation evolution, and mode-switching

We introduce a conceptual model for the in-plane physics of an earthquake fault. The model employs cellular automaton techniques to simulate tectonic loading, earthquake rupture, and strain redistribution. The impact of a hypothetical crustal elastodynamic Green's function is approximated by a long-range strain redistribution law with a r(-p) dependance. We investigate the influence of the effective elastodynamic interaction range upon the dynamical behaviour of the model by conducting experiments with different values of the exponent (p). The results indicate that this model has two distinct, stable modes of behaviour. The first mode produces a characteristic earthquake distribution with moderate to large events preceeded by an interval of time in which the rate of energy release accelerates. A correlation function analysis reveals that accelerating sequences are associated with a systematic, global evolution of strain energy correlations within the system. The second stable mode produces Gutenberg-Richter statistics, with near-linear energy release and no significant global correlation evolution. A model with effectively short-range interactions preferentially displays Gutenberg-Richter behaviour. However, models with long-range interactions appear to switch between the characteristic and GR modes. As the range of elastodynamic interactions is increased, characteristic behaviour begins to dominate GR behaviour. These models demonstrate that evolution of strain energy correlations may occur within systems with a fixed elastodynamic interaction range. Supposing that similar mode-switching dynamical behaviour occurs within earthquake faults then intermediate-term forecasting of large earthquakes may be feasible for some earthquakes but not for others, in alignment with certain empirical seismological observations. Further numerical investigation of dynamical models of this type may lead to advances in earthquake forecasting research and theoretical seismology.

An overview of sequential Monte Carlo methods for parameter estimation in general state-space models

Nonlinear non-Gaussian state-space models arise in numerous applications in control and signal processing. Sequential Monte Carlo (SMC) methods, also known as Particle Filters, are numerical techniques based on Importance Sampling for solving the optimal state estimation problem. The task of calibrating the state-space model is an important problem frequently faced by practitioners and the observed data may be used to estimate the parameters of the model. The aim of this paper is to present a comprehensive overview of SMC methods that have been proposed for this task accompanied with a discussion of their advantages and limitations.

Waverider configurations derived from general conical flowfields

A method based on the computational fluid dynamics (CFD) is presented for a flexible waverider's design. The generating bodies of this method could be any cones. In addition, either the leading edge or the profile of the scramjet's inlet is used as the waverider's definition curve, parameterized by the quadric function, the sigmoid function or the B-spline function. Furthermore, several numerical examples are carried out to validate the method and the relevant codes. The CFD results of the configurations show that all the designs are successful. Moreover, primary suggestions are proposed for practical design by comparing the geometrical and aerodynamic performances of the cone-derived waveriders at Mach 6.

Garci Sánchez de Badajoz y la propulsión del Cancionero General

Integran este número de la revista ponencias presentadas en Studia Hispanica Medievalia VIII : Actas de las X Jornadas Internacionales de Literatura Española Medieval, 2011, y de Homenaje al Quinto Centenario del Cancionero General de Hernando del Castillo.

Fatigue crack-growth rate in ferrite martensite dual-phase steel

An empirical study is made on the fatigue crack growth rate in ferrite-martensite dual-phase (FMDP) steel. Particular attention is given to the effect of ferrite content in the range of 24.2% to 41.5% where good fatigue resistance was found at 33.8%. Variations in ferrite content did not affect the crack growth rate when plotted against the effective stress intensity factor range  which was assumed to follow a linear relation with the crack tip stress intensity factor range ΔK. A high  corresponds to uniformly distributed small size ferrite and martensite. No other appreciable correlation could be ralated to the microstructure morphology of the FMDP steel. The closure stress intensity factor , however, is affected by the ferrite content with  reaching a maximum value of 0.7. In general, crack growth followed the interphase between the martensite and ferrite.

Dividing the fatigue crack growth process into Stage I and II where the former would be highly sensitive to changes in ΔK and the latter would increase with ΔK depending on the  ratio. The same data when correlated with the strain energy density factor range ΔS showed negligible dependence on mean stress or R ratio for Stage I crack growth. A parameter α involving the ratio of ultimate stress to yield stress, percent reduction of area and R is introduced for Stage II crack growth so that the  data for different R would collapse onto a single curve with a narrow scatter band when plotted against αΔS.

A general theory on media with randomly distributed inclusions .1. The average field behaviors

In this paper, a theory is developed to calculate the average strain field in the materials with randomly distributed inclusions. Many previous researches investigating the average field behaviors were based upon Mori and Tanaka's idea. Since they were restricted to studying those materials with uniform distributions of inclusions they did not need detailed statistical information of random microstructures, and could use the volume average to replace the ensemble average. To study more general materials with randomly distributed inclusions, the number density function is introduced in formulating the average field equation in this research. Both uniform and nonuniform distributions of inclusions are taken into account in detail.

A ground hydrologic model with inclusion of a layer of vegetation canopy that can interact with general-circulation model

In this paper, a ground hydrologic model(GHM) is presented in which the vapor, heat and momentum exchanges between ground surface covers (including vegetation canopy) and atmosphere is described more realistically. The model is used to simulate three sets of field data and results from the numerical simulation agree with the field data well. GHM has been tested using input data generated by general circulation model (GCM) runs for both the North American regions and the Chinese regions, The results from GHM are quite different from those of GHMs in GCMs. It shows that a more active concerted effort on the land surface process study to provide a physically realistic GHM for predicting the exchange between land and atmosphere is important and necessary.

Evolution and propagation of density waves on galactic disk .1. General evolution equation of wavelet and discussion of its solution

This paper presents a general self-consistent theory of evolution and propagation of wavelets on the galactic disk. A simplified model for this theory, i. e. the thin transition-layer approximation is proposed.There are three types of solutions to the basic equation governing the evolution of wavelets on the disk: (ⅰ) normal propagating type; (ⅱ) swing type; (ⅲ) general evolving type. The results show that the first two types are applicable to a certain domain on the galactic disk and a certain region of the wave number of wavelets. The third is needed to join the other two types and to yield a coherent total picture of the wave motion. From the present theory, it can be seen that the well-known "swing theory" of the G-L sheet model holds only for a certain class of basic states of galaxies.