Eyelet particle tracing - steady visualization of unsteady flow

It is a challenging task to visualize the behavior of time-dependent 3D vector fields. Most of the time an overview of unsteady fields is provided via animations, but, unfortunately, animations provide only transient impressions of momentary flow. In this paper we present two approaches to visualize time varying fields with fixed geometry. Path lines and streak lines represent such a steady visualization of unsteady vector fields, but because of occlusion and visual clutter it is useless to draw them all over the spatial domain. A selection is needed. We show how bundles of streak lines and path lines, running at different times through one point in space, like through an eyelet, yield an insightful visualization of flow structure ('eyelet lines'). To provide a more intuitive and appealing visualization we also explain how to construct a surface from these lines. As second approach, we use a simple measurement of local changes of a field over time to determine regions with strong changes. We visualize these regions with isosurfaces to give an overview of the activity in the dataset. Finally we use the regions as a guide for placing eyelets

Topology Based Flow Analysis and Superposition Effects

Using topology for feature analysis in flow fields faces several problems. First of all, not all features can be detected using topology based methods. Second, while in flow feature analysis the user is interested in a quantification of feature parameters like position, size, shape, radial velocity and other parameters of feature models, many of these parameters can not be determined using topology based methods alone. Additionally, in some applications it is advantageous to regard the vector field as a superposition of several, possibly simple, features. As topology based methods are quite sensitive to superposition effects, their precision and usability is limited in these cases. In this paper, topology based analysis and visualization of flow fields is estimated and compared to other feature based approaches demonstrating these problems

Fault and fracture zone detection based on soil gas mapping and gamma ray survey at the extension site of an open pit coal mine

Identification of open active faults and fracture zones is a part of exploration study prior to mining operation. However, detailed mapping of geological discontinuities in an otherwise low permeable overburden is rarely carried out in the mining area. To develop a rapid and feasible survey method, a field campaign was conducted to examine different soil gas survey methods along three transects at the Carrington West Wing extension site of a coal mine, Hunter River Valley, NSW, Australia. Coal seam gas together with Uranium-238 (present in the gas-bearing coal seam) increases the soil gas signal which can be detected with suitable soil gas mapping methods. Three techniques associated with four parameters were tested at the field site. A conventional active soil gas sampling method was applied with the samples analysed off-site in the lab by gas chromatography for carbon dioxide and methane concentrations. Radon was measured on site by means of radon detector. It was expected that high soil gas concentration anomalies, if detected, could then be related to the locations of permeable fault/ fracture zones. A rapid and simple technique was used to determine the relative counts of Bismuth-214 in the soil surface by employing a gamma ray spectrometer. As a decay product of the 222Rn, 214Bi is also expected to exhibit relatively higher activities in the soil over faults and fracture zones

Spatial and Temporal Evolution of Particle Migration in Gap-Graded Granular Soils: Insights from Experimental Observations

This study presents physical observations and insights into particle migration characteristics throughout the suffusion process. Using a purpose-built coaxial permeameter cell, suffusion experiments were conducted on idealised internally unstable gap-graded granular soils at varying fines content and hydraulic loading conditions. The specimens were prepared with a mixture layer comprising finer and coarser fractions underlying a coarse layer composed of the coarser fraction alone. This enabled the finer fraction within the mixture layer to migrate through the coarse layer with upward seepage flow. The local porosity profile along the specimen was determined using spatial time domain reflectometry and an inversion algorithm, which enabled the development of a novel field map of the difference in porosity from the initial condition. This field map provided a visual guide of the spatial and temporal variation in porosity and enabled particle migration internally within the specimen to be quantitatively characterised from onset to progression to washout. The limiting onset condition identified from the field map was shown to be comparable to that obtained using conventional approaches, thereby providing strong validation for the application of porosity-based field maps. As suffusion progressed, the height of infiltrating finer particles into the coarse layer increased linearly with time, while the overall rate of particle migration from the mixture layer to the coarse layer evolved in a non-linear manner with the rate of migration increasing as the specimen reached a complete mixture condition, where the finer fraction infiltrated the entire coarse layer. The attainment of a complete mixture condition was dependent on the fabric of the gap-graded soil ... (see PDF for full abstract).Comment: 28 pages, 20 figures. Article published in Journal of Geotechnical and Geoenvironmental Engineering 2023 (see https://ascelibrary.org/doi/10.1061/JGGEFK.GTENG-11094

An improved ontological representation of dendritic cells as a paradigm for all cell types

The Cell Ontology (CL) is designed to provide a standardized representation of cell types for data annotation. Currently, the CL employs multiple is_a relations, defining cell types in terms of histological, functional, and lineage properties, and the majority of definitions are written with sufficient generality to hold across multiple species. This approach limits the CL’s utility for cross-species data integration. To address this problem, we developed a method for the ontological representation of cells and applied this method to develop a dendritic cell ontology (DC-CL). DC-CL subtypes are delineated on the basis of surface protein expression, systematically including both species-general and species-specific types and optimizing DC-CL for the analysis of flow cytometry data. This approach brings benefits in the form of increased accuracy, support for reasoning, and interoperability with other ontology resources. 104. Barry Smith, “Toward a Realistic Science of Environments”, Ecological Psychology, 2009, 21 (2), April-June, 121-130. Abstract: The perceptual psychologist J. J. Gibson embraces a radically externalistic view of mind and action. We have, for Gibson, not a Cartesian mind or soul, with its interior theater of contents and the consequent problem of explaining how this mind or soul and its psychological environment can succeed in grasping physical objects external to itself. Rather, we have a perceiving, acting organism, whose perceptions and actions are always already tuned to the parts and moments, the things and surfaces, of its external environment. We describe how on this basis Gibson sought to develop a realist science of environments which will be ‘consistent with physics, mechanics, optics, acoustics, and chemistry’

Characterisation of geomechanical properties of bentonite clay used for plug and abandonment operations of coal seam gas wells

Compressed bentonite in the form of pellets or plugs is used for the abandonment of production wells for the oil and gas industry. The design of the abandonment systems is based on the hydro-mechanical behaviour of the compressed bentonite defined by mechanical parameters that are used from published data rather than quantified for the used material by laboratory investigations. This paper presents an experimental study on characterising the swelling and shear strength behaviour of raw and polymer (polyvinylpyrrolidone, PVP) treated bentonite. Dislodgement tests consist of three hydrated bentonite plugs inserted in steel casings with the failure mechanism characterised. The bentonite used comes from a local mine (in Queensland, Australia) and is comparable to other bentonites usually used for the abandonment of wells or for other problems where mineral sealing is required (e.g. basal clay barriers of landfills). The experiments have shown that polymer treated bentonite shows significantly larger shear strengths than raw bentonite with simultaneously less swelling. More compressed samples also showed higher shear strengths and less swelling. The dislodgement tests have characterised for the first time the cascaded failure mechanism of a series of plugs forming an abandonment system. This investigation is the first step towards the development of an improved design for abandonment systems for wells using bentonite plugs

Efficient Construction of Flow Structures

Visualizing flow structures according to the users’ interests provides insight to scientists and engineers. In previous work, a flow structure based on streamline predicates, that examine, whether a streamline has a given property, was defined. Evaluating all streamlines results in characteristic sets grouping all streamlines with similar behavior with respect to a given predicate. Since there are infinitely many streamlines, the algorithm chooses a finite subset for the computation of an approximated discrete version of the characteristic sets. However, even the construction of characteristic sets based on a finite set of streamlines tends to be computationally expensive. Based on a thorough analysis of all processing steps, we present and compare different acceleration approaches. The techniques are based on simplifications that result in characteristic set boundaries deviating from the correct but computational expensive boundaries. We developmeasures for objective comparison of the introduced errors. An adaptive refinement approach turns out to be the best compromise between computation time and quality

Localized Flow and Analysis of 2D and 3D Vector Fields

In this paper we present an approach to the analysis of the contribution of a small subregion in a dataset to the global flow. To this purpose, we subtract the potential flow that is induced by the boundary of the sub-domain from the original flow. Since the potential flow is free of both divergence and rotation, the localized flow field retains the original features. In contrast to similar approaches, by making explicit use of the boundary flow of the subregion, we manage to isolate the region-specific flow that contains exactly the local contribution of the considered subdomain to the global flow. In the remainder of the paper, we describe an implementation on unstructured grids in both two and three dimensions. We discuss the application of several widely used feature extraction methods on the localized flow, with an emphasis on topological schemes

Computation of Localized Flow for Steady and Unsteady Vector Fields and its Applications

We present, extend, and apply a method to extract the contribution of a subregion of a data set to the global flow. To isolate this contribution, we decompose the flow in the subregion into a potential flow that is induced by the original flow on the boundary and a localized flow. The localized flow is obtained by subtracting the potential flow from the original flow. Since the potential flow is free of both divergence and rotation, the localized flow retains the original features and captures the region-specific flow that contains the local contribution of the considered subdomain to the global flow. In the remainder of the paper, we describe an implementation on unstructured grids in both two and three dimensions for steady and unsteady flow fields. We discuss the application of some widely used feature extraction methods on the localized flow and describe applications like reverse-flow detection using the potential flow. Finally, we show that our algorithm is robust and scalable by applying it to various flow data sets and giving performance figures