Computing costs for FEM analysis of foundation engineering problems and possible ways of increasing efficiency

The application of finite element methods (FEM) is often restricted by the available computer capacity and the computing costs. The purpose of this paper, therefore, is, to present test results and to discuss possible ways of achieving a substantial reduction in computing times. Dividing the numerical analysis into the five levels–hardware, software, element-mesh and element-type, iteration technique (approximation of non-linearity) and constitutive model–one can show that the computing time can be reduced by about 20 per cent at every level. In particular, the use of the modified Newton-Raphson method for approximation of non-linearity and the constitutive model–apart from the theoretical concept (elastoplastic, hypoelastic etc.)—must be formulated in a manner which does not produce substantial changes in the coefficients of the material matrix caused by small stress changes. On the whole, computing time can be reduced to about 10 per cent of present computing costs. Thus, it would even be economically viable to solve three-dimensional non-linear problems by FEM.     

IRNSS-1A: signal and clock characterization of the Indian regional navigation system

An initial characterization of the L5 and S-Band navigation signals transmitted by the first satellite of the Indian regional navigation satellite system (IRNSS) is presented. In the absence of a public signal specification, a 30 m high-gain antenna has been used to record the signal spectrum and the modulated chip sequences. For the IRNSS standard positioning service, use of a Gold ranging code is confirmed and relevant shift register parameters for the two frequencies are identified. Based on a prototype receiver, L5 single-frequency code and phase observations of IRNSS-1A have also been collected. The tracking performance is described, and the measurements are used to characterize the short-term clock stability of IRNSS-1A.     

Temperature and precipitation responses to El Niño-Southern Oscillation in a hierarchy of datasets with different levels of observational constraints

Climate Dynamics - El Niño-Southern Oscillation (ENSO) is the dominant mode of climate variability, affecting climate conditions over large areas of the globe. There are, however, substantial...     

New remote sensing techniques for the detection and quantification of earth surface CO2 degassing

Earth degassing specifically of carbon dioxide CO₂ is of increasing interest with respect to the global carbon budget, related climate effects, earthquake and volcano eruption mechanisms, as well as plant physiological reactions in gas-rich environments. Investigations in all of these disciplines require the detection of surface CO₂ degassing structures and quantification of their emissions. We introduce minimal thermal change detection based on infrared imaging as a new remote sensing tool for the detection of earth surface thermal anomalies suiting among others to discover earth degassing locations of any origin. The method allows for seamless areal search and monitoring of degassing structures in any terrain. As proof of concept infrared imaging measurements were performed at the Bossoleto vent on the eastern master fault of the Siena Graben (Tuscany, Italy). It is known for the migration of a large amount of CO₂-rich gas from deep geothermal reservoirs. Field data acquired confirmed the qualification of the method. Detection of CO₂ degassing locations from infrared image time series worked reliably and optimal detection conditions were identified (dry, calm, cloudless weather between dusk and dawn). A simple model of heat exchange processes involved and observed was developed. In a first attempt this model was applied to determine the gas exit temperature, the area of gas thermal reach and the gas flux from recorded image series. It is the first method that allows remote areal survey of mofette fields and the associated CO₂ flux quantification sole from infrared image time series.     

Weathering, dust, and biocycling effects on soil silicon isotope ratios

Silicon isotope ratios (δ³⁰Si) of bulk mineral materials in soil integrate effects from both silicon sources and processing. Here we report δ³⁰Si values from a climate gradient of Hawaiian soils developed on 170 ka basalt and relate them to patterns of soil chemistry and mineralogy. The results demonstrate informative relationships between the mass fraction of soil Si depletion and δ³⁰Si. In upper (<1 m deep) soil horizons along the climate gradient, Si depletion correlates with decreases of residual δ³⁰Si values in low rainfall soils and increases in high rainfall soils. Strong positive correlation between soil δ³⁰Si and dust-derived quartz and mica content show that both trends are largely controlled by the abundance of these weathering-resistant minerals. The data also lend support to the idea that fractionation of Si isotopes in secondary phases is controlled by partitioning of silicon between dissolved and precipitated products during the initial weathering of primary basalt. Secondary mineral δ³⁰Si values from lower (>1 m deep) soil horizons generally correlate with the isotope fractionation predicted by a study of dissolved Si in basalt-watershed rivers and driven by preferential ²⁸Si removal from the dissolved phase during precipitation. In contrast, after correcting for the influence of dust, secondary mineral Si depletion and δ³⁰Si values in shallow (<1 m deep) soil horizons showed evidence of biocycling induced Si redistribution and substantially lower δ³⁰Si values than predicted. Low δ³⁰Si values in shallow soil horizons compared to predictions can be attributed to repeated fractionation as secondary minerals undergo additional cycles of dissolution and precipitation. Primary mineral weathering, secondary mineral weathering, dust accumulation, and biocycling are major processes in terrestrial Si cycling and these results demonstrate that each can be traced by δ³⁰Si values interpreted in conjunction with mineralogy and measures of Si depletion.