Highly parameterized model calibration with cloud computing: an example of regional flow model calibration in northeast Alberta,Canada

Expanding groundwater datasets collected by automated sensors, and improved groundwater databases, have caused a rapid increase in calibration data available for groundwater modeling projects. Improved methods of subsurface characterization have increased the need for model complexity to represent geological and hydrogeological interpretations. The larger calibration datasets and the need for meaningful predictive uncertainty analysis have both increased the degree of parameterization necessary during model calibration. Due to these competing demands, modern groundwater modeling efforts require a massive degree of parallelization in order to remain computationally tractable. A methodology for the calibration of highly parameterized, computationally expensive models using the Amazon EC2 cloud computing service is presented. The calibration of a regional-scale model of groundwater flow in Alberta, Canada, is provided as an example. The model covers a 30,865-km² domain and includes 28 hydrostratigraphic units. Aquifer properties were calibrated to more than 1,500 static hydraulic head measurements and 10 years of measurements during industrial groundwater use. Three regionally extensive aquifers were parameterized (with spatially variable hydraulic conductivity fields), as was the aerial recharge boundary condition, leading to 450 adjustable parameters in total. The PEST-based model calibration was parallelized on up to 250 computing nodes located on Amazon’s EC2 servers.     

The Deep X-Ray Radio Blazar Survey (DXRBS) – II. New identifications

We have searched the archived, pointed ROSAT Position Sensitive Proportional Counter data for blazars by correlating the WGACAT X-ray data base with several publicly available radio catalogues, restricting our candidate list to serendipitous X-ray sources with a flat radio spectrum ( α _r≤0.70, where S _ν ∝ ν ^{− α} ). This makes up the Deep X-ray Radio Blazar Survey (DXRBS). Here we present new identifications and spectra for 106 sources, including 86 radio-loud quasars, 11 BL Lacertae objects, and nine narrow-line radio galaxies. Together with our previously published objects and already-known sources, our sample now contains 298 identified objects: 234 radio-loud quasars [181 flat-spectrum quasars: FSRQ ( α _r≤0.50) and 53 steep-spectrum quasars: SSRQ], 36 BL Lacs and 28 narrow-line radio galaxies. Redshift information is available for 96 per cent of these. Thus our selection technique is ∼90 per cent efficient at finding radio-loud quasars and BL Lacs. Reaching 5-GHz radio fluxes ∼50 mJy and 0.1–2.0 keV X-ray fluxes a few ×10⁻¹⁴ erg cm⁻² s⁻¹, DXRBS is the faintest and largest flat-spectrum radio sample with nearly complete (∼85 per cent) identification. We review the properties of the DXRBS blazar sample, including redshift distribution and coverage of the X-ray-radio–power plane for quasars and BL Lacs. Additionally, we touch upon the expanded multiwavelength view of blazars provided by DXRBS. By sampling for the first time the faint end of the radio and X-ray luminosity functions, this sample will allow us to investigate the blazar phenomenon and the validity of unified schemes down to relatively low powers.     

Examples of extreme intraday variability

We present results of the ATCA IDV Survey of southern extragalactic radio sources. We discuss briefly the properties of the 22 new intraday variable sources discovered in the Survey. The follow-up observations of a few extreme examples of strong intraday variability are presented. We find that the characteristics of the total flux density fluctuations at different wavelengths are consistent with intersteller scintillations (ISS) of the microarcsecondsize soorten components. However, the scintillating components of a few extreme IDVs are characterized by the brightness temperatures far exceeding the T _B=10¹² K limit. The relativistic beaming invoked in such sources would require Doppler factors up to as high as δ∼ 10³. This revised version was published online in July 2006 with corrections to the Cover Date.     

Volume contents

Volume Contents

Volume contents     

Simultaneous time-lapse electrical resistivity inversion

Time-lapse monitoring is a powerful tool for observing dynamic changes in the subsurface. In particular it offers the potential for achieving inversion results with increased fidelity through the inclusion of complementary information from multiple time-steps. This inclusion of complementary information can reduce the need for spatial smoothing, without adding inversion artifacts to the resulting images. Commonly used time-lapse inversion methods include the ratio method, cascaded time-lapse inversion, difference inversion and differencing independent inversions. We introduce two additional methods in which both time-lapse data sets are inverted simultaneously. In the first, called temporally constrained time-lapse inversion, inversion of both datasets is done under a single optimization procedure and constraints are added to the regularization to ensure that the changes from one time to another are smooth. In the second method, called simultaneous time-lapse inversion, the inversions at time 1 and time 2 are performed simultaneously and constraints of smoothness and closeness to a reference model are applied to the difference image produced at each iteration, and subsequently, the constraints are updated at each iteration. Through both a numerical and a field example we compare the results of common time-lapse inversion methods as well as the introduced approaches. We found that of the commonly used time-lapse inversion methods the difference inversion method produced the best resolution of time-lapse changes and was the most robust in the presence of noise. However, we found that the alternative approach of simultaneous time-lapse inversion produced the best reconstruction of modeled EC changes in the numerical example and easily interpretable high resolution difference images in the field example. Moreover, there was less tailoring of regularization parameters with our simultaneous time-lapse approach, suggesting that it will lend itself well to an automated inversion code.     

Radio Intra-Day Variability: Answers and Questions

Intra-day variability (IDV) of active galactic nuclei (AGN) has been detected from gamma-ray energies to radio wavelengths. At high energies, such variability appears to be intrinsic to the sources themselves. However, at radio wavelengths, brightness temperatures as high as10¹⁸ to 10²¹ K are encountered if the IDV is intrinsic to the source. We discuss here the accumulating evidence showing that, at radio wavelengths where the highest brightness temperatures are encountered, interstellar scintillation (ISS) is the principal mechanism causing IDV. While ISS reduces the implied brightness temperatures, they still remain uncomfortably high. This revised version was published online in July 2006 with corrections to the Cover Date.     

基于颗粒组构特性的散体材料本构模型研究

通过散体介质材料单元颗粒排列组构表达的细观结构力学关系,建立了用颗粒密集度、颗粒排列组构关系和颗粒间摩擦特性等非连续介质材料特性参数描述的散体介质材料本构模型,从而实现散体介质材料宏观连续介质描述的等效应力表达.通过该模型可采用数值方法进行散体介质材料准静态情况下的力学特性分析.文中最后基于有限元软件ABAQUS,进行了该本构模型的二次开发.数值算例结果验证了所建立散体介质材料本构模型的适用性.