Characterization of granite matrix porosity and pore-space geometry by in situ and laboratory methods

Most available studies of interconnected matrix porosity of crystalline rocks are based on laboratory investigations; that is, work on samples that have undergone stress relaxation and were affected by drilling and sample preparation. The extrapolation of the results to in situ conditions is therefore associated with considerable uncertainty, and this was the motivation to conduct the ‘in situ Connected Porosity’ experiment at the Grimsel Test Site (Central Swiss Alps). An acrylic resin doped with fluorescent agents was used to impregnate the microporous granitic matrix in situ around an injection borehole, and samples were obtained by overcoring. The 3-D structure of the porespace, represented by microcracks, was studied by U-stage fluorescence microscopy. Petrophysical methods, including the determination of porosity, permeability and P -wave velocity, were also applied. Investigations were conducted both on samples that were impregnated in situ and on non-impregnated samples, so that natural features could be distinguished from artefacts. The investigated deformed granites display complex microcrack populations representing a polyphase deformation at varying conditions. The crack population is dominated by open cleavage cracks in mica and grain boundary cracks. The porosity of non-impregnated samples lies slightly above 1 per cent, which is 2–2.5 times higher than the in situ porosity obtained for impregnated samples. Measurements of seismic velocities (Vp ) on spherical rock samples as a function of confining pressure, spatial direction and water saturation for both non-impregnated and impregnated samples provide further constraints on the distinction between natural and induced crack types. The main conclusions are that (1) an interconnected network of microcracks exists in the whole granitic matrix, irrespective of the distance to ductile and brittle shear zones, and (2) conventional laboratory methods overestimate the matrix porosity. Calculations of contaminant transport through fractured media often rely on matrix diffusion as a retardation mechanism.

The Effects Of Reinforcement Inclusions On Wear Tolerance, Playing Quality And Physical Properties In A Silt Loam And Sand Rootzone Matrix

Reinforcement inclusions have been advocated to alleviate wear, compaction, and unstable surfaces in sports fields, but little research on the effects of these materials has been conducted in the USA. Experiments were established on a native silt loam and a sand rootzone matrix, seeded with a Kentucky bluegrass (Poa pratensis L.) blend, at the Joseph Troll Turf Research Center, University of Massachusetts, Amherst, USA to determine the effects of reinforcement inclusions on wear, surface hardness, traction, ball roll, ball bounce resilience, water infiltration rate, soil bulk density, air porosity, total porosity, and root weights. Three types of reinforcement inclusions (Sportgrass, Netlon, Turfgrids) were tested along with a non-reinforced control in a three year study. The treatments were set out in a randomized complete block design with four replications in both soils. No inclusion provided less wear or greater infiltration or air-filled porosity relative to the control. Reinforcement inclusions showed significant differences, however, in surface hardness, traction, and ball roll relative to the control, although this varied with the time of year. Infiltration rates, airfilled porosity, total pore space, bulk density, hardness, traction, ball roll, and ball rebound were greater on the sand rootzone than on the silt loam. Significant correlations were present between soil bulk density, surface hardness, traction, and ball roll. Based on our study, the use of reinforcement inclusions to provide better wear tolerance for sand or native soil athletic fields is not warranted. Certain playing surface characteristics, however, may be slightly improved with the use of reinforcement inclusions. The use of sands for sports surfaces is justified based upon the improvement in playing quality characteristics and soil physical properties important to a good playing surface.

The PSE-3D instability analysis methodology for flows depending strongly on two and weakly on the third spatial dimension

The present contribution discusses the development of a PSE-3D instability analysis algorithm, in which a matrix forming and storing approach is followed. Alternatively to the typically used in stability calculations spectral methods, new stable high-order finitedifference-based numerical schemes for spatial discretization 1 are employed. Attention is paid to the issue of efficiency, which is critical for the success of the overall algorithm. To this end, use is made of a parallelizable sparse matrix linear algebra package which takes advantage of the sparsity offered by the finite-difference scheme and, as expected, is shown to perform substantially more efficiently than when spectral collocation methods are used. The building blocks of the algorithm have been implemented and extensively validated, focusing on classic PSE analysis of instability on the flow-plate boundary layer, temporal and spatial BiGlobal EVP solutions (the latter necessary for the initialization of the PSE-3D), as well as standard PSE in a cylindrical coordinates using the nonparallel Batchelor vortex basic flow model, such that comparisons between PSE and PSE-3D be possible; excellent agreement is shown in all aforementioned comparisons. Finally, the linear PSE-3D instability analysis is applied to a fully three-dimensional flow composed of a counter-rotating pair of nonparallel Batchelor vortices.

Efficient methodologies for system matrix modelling in iterative image reconstruction for rotating high-resolution PET

A fully 3D iterative image reconstruction algorithm has been developed for high-resolution PET cameras composed of pixelated scintillator crystal arrays and rotating planar detectors, based on the ordered subsets approach. The associated system matrix is precalculated with Monte Carlo methods that incorporate physical effects not included in analytical models, such as positron range effects and interaction of the incident gammas with the scintillator material. Custom Monte Carlo methodologies have been developed and optimized for modelling of system matrices for fast iterative image reconstruction adapted to specific scanner geometries, without redundant calculations. According to the methodology proposed here, only one-eighth of the voxels within two central transaxial slices need to be modelled in detail. The rest of the system matrix elements can be obtained with the aid of axial symmetries and redundancies, as well as in-plane symmetries within transaxial slices. Sparse matrix techniques for the non-zero system matrix elements are employed, allowing for fast execution of the image reconstruction process. This 3D image reconstruction scheme has been compared in terms of image quality to a 2D fast implementation of the OSEM algorithm combined with Fourier rebinning approaches. This work confirms the superiority of fully 3D OSEM in terms of spatial resolution, contrast recovery and noise reduction as compared to conventional 2D approaches based on rebinning schemes. At the same time it demonstrates that fully 3D methodologies can be efficiently applied to the image reconstruction problem for high-resolution rotational PET cameras by applying accurate pre-calculated system models and taking advantage of the system's symmetries.

Three dimensional (3D) microstructure-based modeling of interfacial decohesion in particle reinforced metal matrix composites

Modeling and prediction of the overall elastic–plastic response and local damage mechanisms in heterogeneous materials, in particular particle reinforced composites, is a very complex problem. Microstructural complexities such as the inhomogeneous spatial distribution of particles, irregular morphology of the particles, and anisotropy in particle orientation after secondary processing, such as extrusion, significantly affect deformation behavior. We have studied the effect of particle/matrix interface debonding in SiC particle reinforced Al alloy matrix composites with (a) actual microstructure consisting of angular SiC particles and (b) idealized ellipsoidal SiC particles. Tensile deformation in SiC particle reinforced Al matrix composites was modeled using actual microstructures reconstructed from serial sectioning approach. Interfacial debonding was modeled using user-defined cohesive zone elements. Modeling with the actual microstructure (versus idealized ellipsoids) has a significant influence on: (a) localized stresses and strains in particle and matrix, and (b) far-field strain at which localized debonding takes place. The angular particles exhibited higher degree of load transfer and are more sensitive to interfacial debonding. Larger decreases in stress are observed in the angular particles, because of the flat surfaces, normal to the loading axis, which bear load. Furthermore, simplification of particle morphology may lead to erroneous results.

On the Use of Matrix-Free Shift-Invert Strategies For Global Flow Instability Analysis

A novel time-stepping shift-invert algorithm for linear stability analysis of laminar flows in complex geometries is presented. This method, based on a Krylov subspace iteration, enables the solution of complex non-symmetric eigenvalue problems in a matrix-free framework. Validations and comparisons to the classical exponential method have been performed in three different cases: (i) stenotic flow, (ii) backward-facing step and (iii) lid-driven swirling flow. Results show that this new approach speeds up the required Krylov subspace iterations and has the capability of converging to specific parts of the global spectrum. It is shown that, although the exponential method remains the method of choice if leading eigenvalues are sought, the performance of the present method could be dramatically improved with the use of a preconditioner. In addition, as opposed to other methods, this strategy can be directly applied to any time-stepper, regardless of the temporal or spatial discretization of the latter.

Complex Patterns of Alternative Splicing Mediate the Spatial and Temporal Distribution of Perlecan/UNC-52 in Caenorhabditis elegans

The unc-52 gene encodes the nematode homologue of mammalian perlecan, the major heparan sulfate proteoglycan of the extracellular matrix. This is a large complex protein with regions similar to low-density lipoprotein receptors, laminin, and neural cell adhesion molecules (NCAMs). In this study, we extend our earlier work and demonstrate that a number of complex isoforms of this protein are expressed through alternative splicing. We identified three major classes of perlecan isoforms: a short form lacking the NCAM region and the C-terminal agrin-like region; a medium form containing the NCAM region, but still lacking the agrin-like region; and a newly identified long form that contains all five domains present in mammalian perlecan.  Using region-specific antibodies and unc-52 mutants, we reveal a complex spatial and temporal expression pattern for these UNC-52 isoforms. As well, using a series of mutations affecting different regions and thus different isoforms of UNC-52, we demonstrate that the medium NCAM-containing isoforms are sufficient for myofilament lattice assembly in developing nematode body-wall muscle. Neither short isoforms nor isoforms containing the C-terminal agrin-like region are essential for sarcomere assembly or muscle cell attachment, and their role in development remains unclear.

A way forward for land-use planning to achieve policy goals by using spatial modelling scenarios

This paper investigates how demographic (socioeconomic) and land-use (physical and environmental) data can be integrated within a decision support framework to formulate and evaluate land-use planning scenarios. A case-study approach is undertaken with land-use planning scenarios for a rapidly growing coastal area in Australia, the Shire of Hervey Bay. The town and surrounding area require careful planning of the future urban growth between competing land uses. Three potential urban growth scenarios are put forth to address this issue. Scenario A ('continued growth') is based on existing socioeconomic trends. Scenario B ('maximising rates base') is derived using optimisation modelling of land-valuation data. Scenario C ('sustainable development') is derived using a number of social, economic, and environmental factors and assigning weightings of importance to each factor using a multiple criteria analysis approach. The land-use planning scenarios are presented through the use of maps and tables within a geographical information system, which delineate future possible land-use allocations up until 2021. The planning scenarios are evaluated by using a goal-achievement matrix approach. The matrix is constructed with a number of criteria derived from key policy objectives outlined in the regional growth management framework and town planning schemes. The authors of this paper examine the final efficiency scores calculated for each of the three planning scenarios and discuss the advantages and disadvantages of the three land-use modelling approaches used to formulate the final scenarios.

The evaluation of the spatial and temporal stability of sugarcane farm performance based on yield and commercial cane sugar

In broader catchment scale investigations, there is a need to understand and ultimately exploit the spatial variation of agricultural crops for an improved economic return. In many instances, this spatial variation is temporally unstable and may be different for various crop attributes and crop species. In the Australian sugar industry, the opportunity arose to evaluate the performance of 231 farms in the Tully Mill area in far north Queensland using production information on cane yield (t/ha) and CCS ( a fresh weight measure of sucrose content in the cane) accumulated over a 12-year period. Such an arrangement of data can be expressed as a 3-way array where a farm x attribute x year matrix can be evaluated and interactions considered. Two multivariate techniques, the 3-way mixture method of clustering and the 3-mode principal component analysis, were employed to identify meaningful relationships between farms that performed similarly for both cane yield and CCS. In this context, farm has a spatial component and the aim of this analysis was to determine if systematic patterns in farm performance expressed by cane yield and CCS persisted over time. There was no spatial relationship between cane yield and CCS. However, the analysis revealed that the relationship between farms was remarkably stable from one year to the next for both attributes and there was some spatial aggregation of farm performance in parts of the mill area. This finding is important, since temporally consistent spatial variation may be exploited to improve regional production. Alternatively, the putative causes of the spatial variation may be explored to enhance the understanding of sugarcane production in the wet tropics of Australia.

A wideband array antenna with beam-steering capability using real valued weights

This article presents an array antenna with beam-steering capability in azimuth over a wide frequency band using real-valued weighting coefficients that can be realized in practice by amplifiers or attenuators. The described beamforming scheme relies on a 2D (instead of 1D) array structure in order to make sure that there are enough degrees of freedom to realize a given radiation pattern in both the angular and frequency domains. In the presented approach, weights are determined using an inverse discrete Fourier transform (IDFT) technique by neglecting the mutual coupling between array elements. Because of the presence of mutual coupling, the actual array produces a radiation pattern with increased side-lobe levels. In order to counter this effect, the design aims to realize the initial radiation pattern with a lower side-lobe level. This strategy is demonstrated in the design example of 4 X 4 element array. (C) 2005 Wiley Periodicals. Inc.

Definition and spatial annotation of the dynamic secretome during early kidney development

The term secretome has been defined as a set of secreted proteins (Grimmond et al. [2003] Genome Res 13:1350-1359). The term secreted protein encompasses all proteins exported from the cell including growth factors, extracellular proteinases, morphogens, and extracellular matrix molecules. Defining the genes encoding secreted proteins that change in expression during organogenesis, the dynamic secretome, is likely to point to key drivers of morphogenesis. Such secreted proteins are involved in the reciprocal interactions between the ureteric bud (UB) and the metanephric mesenchyme (AM) that occur during organogenesis of the metanephros. Some key metanephric secreted proteins have been identified, but many remain to be determined. In this study, microarray expression profiling of E10.5, E11.5, and E13.5 kidney and consensus bioinformatic analysis were used to define a dynamic secretome of early metanephric development. In situ hybridisation was used to confirm microarray results and clarify spatial expression patterns for these genes. Forty-one secreted factors were dynamically expressed between the E10.5 and E13.5 timeframe profiled, and 25 of these factors had not previously been implicated in kidney development. A text-based anatomical ontology was used to spatially annotate the expression pattern of these genes in cultured metanephric explants.

The cost of uniqueness in groundwater model calibration

Calibration of a groundwater model requires that hydraulic properties be estimated throughout a model domain. This generally constitutes an underdetermined inverse problem, for which a Solution can only be found when some kind of regularization device is included in the inversion process. Inclusion of regularization in the calibration process can be implicit, for example through the use of zones of constant parameter value, or explicit, for example through solution of a constrained minimization problem in which parameters are made to respect preferred values, or preferred relationships, to the degree necessary for a unique solution to be obtained. The cost of uniqueness is this: no matter which regularization methodology is employed, the inevitable consequence of its use is a loss of detail in the calibrated field. This, ill turn, can lead to erroneous predictions made by a model that is ostensibly well calibrated. Information made available as a by-product of the regularized inversion process allows the reasons for this loss of detail to be better understood. In particular, it is easily demonstrated that the estimated value for an hydraulic property at any point within a model domain is, in fact, a weighted average of the true hydraulic property over a much larger area. This averaging process causes loss of resolution in the estimated field. Where hydraulic conductivity is the hydraulic property being estimated, high averaging weights exist in areas that are strategically disposed with respect to measurement wells, while other areas may contribute very little to the estimated hydraulic conductivity at any point within the model domain, this possibly making the detection of hydraulic conductivity anomalies in these latter areas almost impossible. A study of the post-calibration parameter field covariance matrix allows further insights into the loss of system detail incurred through the calibration process to be gained. A comparison of pre- and post-calibration parameter covariance matrices shows that the latter often possess a much smaller spectral bandwidth than the former. It is also demonstrated that, as all inevitable consequence of the fact that a calibrated model cannot replicate every detail of the true system, model-to-measurement residuals can show a high degree of spatial correlation, a fact which must be taken into account when assessing these residuals either qualitatively, or quantitatively in the exploration of model predictive uncertainty. These principles are demonstrated using a synthetic case in which spatial parameter definition is based oil pilot points, and calibration is Implemented using both zones of piecewise constancy and constrained minimization regularization. (C) 2005 Elsevier Ltd. All rights reserved.

Accounting for management costs in sensitivity analyses of matrix population models

Traditional sensitivity and elasticity analyses of matrix population models have been used to p inform management decisions, but they ignore the economic costs of manipulating vital rates. For exam le, the growth rate of a population is often most sensitive to changes in adult survival rate, but this does not mean that increasing that rate is the best option for managing the population because it may be much more expensive than other options. To explore how managers should optimize their manipulation of vital rates, we incorporated the cost of changing those rates into matrix population models. We derived analytic expressions for locations in parameter space where managers should shift between management of fecundity and survival, for the balance between fecundity and survival management at those boundaries, and for the allocation of management resources to sustain that optimal balance. For simple matrices, the optimal budget allocation can often be expressed as simple functions of vital rates and the relative costs of changing them. We applied our method to management of the Helmeted Honeyeater (Lichenostomus melanops cassidix; an endangered Australian bird) and the koala (Phascolarctos cinereus) as examples. Our method showed that cost-efficient management of the Helmeted Honeyeater should focus on increasing fecundity via nest protection, whereas optimal koala management should focus on manipulating both fecundity and survival simultaneously, These findings are contrary to the cost-negligent recommendations of elasticity analysis, which would suggest focusing on managing survival in both cases. A further investigation of Helmeted Honeyeater management options, based on an individual-based model incorporating density dependence, spatial structure, and environmental stochasticity, confirmed that fecundity management was the most cost-effective strategy. Our results demonstrate that decisions that ignore economic factors will reduce management efficiency.