The permeability of hot mix asphalt (HMA) is of special interest to engineers and researchers due to the effects that water has on asphalt pavement performance. Significant research has been done to study HMA permeability. However, most of the studies primarily focused on relating permeability to the average percent air voids in the mix. Such relationships cannot predict permeability accurately due to the different distributions of air void structures at a given average percent of air voids. Air void distribution is a function of many factors such as mix design, compaction method, and aggregate properties. Recent advances in X-ray computed tomography and image analysis techniques offer a unique opportunity to better quantify the air void structure and, consequently, predict HMA permeability. This study is focused on portraying permeability as a function of air void size distribution by using a probabilistic approach that was previously developed by Garcia Bengochea for soils. This approach expresses permeability as a function of the probability density function (pdf) of the air void size distribution. Equations are derived in this thesis to describe this relationship for laboratory specimens compacted using the linear kneading compactor (LKC) and Superave^TM gyratory compactor (SGC) as well as for field cores (labeled as MS). A good correlation exists between permeability and the pdf of the air voids that formed the flow paths (i.e. connected voids). The relationship between moisture damage, air void structure, and cohesive and adhesive bond energy is also investigated in this study. Moisture damage is evaluated by monitoring changes in mechanical properties due to moisture conditioning. The influence of air void structure on pore pressure is studied using a recently developed program at Texas A&M University that simulates fluid flow and pore pressure in a porous medium. The surface free energy of the aggregates and asphalt are calculated from laboratory measurements using the Universal Sorption Device (USD) and the Wilhelmy Plate method, respectively, in order to test the compatibility of the aggregates with the asphalt in the presence of water.

<p>This thesis concerns the modelling of acoustical and vibrational properties of open cell porous foams in multi-layered structures, especially multi-layered panels. The object is to enable optimisation of the microscopic geometry of the foam with respect to macroscopic quantities such as sound pressure level, surface velocity, total mass or cost. The developed method is based on numerical solutions to Biot's equations were scaling laws has been used to connect the microscopic geometry of the foam to macroscopic properties such as density, flow resistivity and characteristic length. Efforts have also been made to establish a scaling law for tortuosity that allows for adaptation to different strut shapes.</p>

Ph.D.

Thesis (M.A.)--University of Texas at Austin, 1990. / Vita. Includes bibliographical references (leaves 96-101).

Thesis (Ph. D.)--Institute of Paper Chemistry, 1963. / Includes bibliographical references (p. 181-184).

Thesis (Ph. D.)--Institute of Paper Chemistry, 1975. / Includes bibliographical references (p. 102-104).

Thesis (Ph. D.)--University of Washington, 2003. / Vita. Includes bibliographical references (leaves 96-104).

Relative permeabilities for three-phase flow are commonly predicted from two-phase flow measurements using empirical models. These models are usually tested against available steady state data. However, the oil flow is unsteady state during various production stages such as gas injection after water flood. Accurate measurement of oil permeability([subscript ro]) during unsteady tertiary gas flood is necessary to study macroscopic oil displacement rate under micro scale events including double drainage, coalescence and reconnection, bulk flow and film drainage. We measure the three-phase oil relative permeability by conducting unsteady-state drainage experiments in a 0.8m water-wet sandpack. We find that when starting from capillary-trapped oil, k[subscript ro] starts high and decreases with a small change in oil saturation, and shows a strong dependence on both the flow of water and the water saturation, contrary to most models. The observed flow coupling between water and oil is stronger in three-phase flow than two-phase flow, and cannot be observed in steady-state measurements. The results suggest that the oil is transported through moving gas/oil/water interfaces (form drag) or momentum transport across stationary interfaces (friction drag). We present a simple model of friction drag which compares favorably to the experimental data. We also solve the creeping flow approximation of the Navier-Stokes equation for stable wetting and intermediate layers in the corner of angular capillaries by using a continuity boundary condition at the layer interface. We find significant coupling between the condensed phases and calculate the generalized mobilities by solving co-current and counter-current flow of wetting and intermediate layers. Finally, we present a simple heuristic model for the generalized mobilities as a function of the geometry and viscosity ratio. To identify the key parameter controlling the measured excess oil flow during tertiary gasflood, we also conduct simultaneous water-gas flood tests where we control water relative permeability and let water saturation develop naturally. The measured data and pore scale calculations indicate that viscous coupling can not explain completely the observed flow coupling between oil and water. We conclude that the rate of water saturation decrease, which controls the pore scale mechanisms including double drainage, reconnection, and film drainage significantly influences the rate of oil drainage during tertiary gas flood. Finally, we present a simple heuristic model for oil relative permeability during tertiary gas flood, and also explain how Stone I and saturation-weighted interpolation should be used to predict the permeability of mobilized oil during transient tertiary gasflood. / text

Carbon dioxide capture and storage (CCS) is considered one of the key technologies for reducing atmospheric emissions of CO₂ from human activities (IPCC, 2005). The scale of potential deployment of CCS is enormous spanning manufacturing, power generation and hydrocarbon extraction worldwide. Uncertainty, cost-benefit challenges, market barriers and failures, and promotion and regulation of infrastructure are the main obstacles for deploying CCS technology in a broad scale. In a CCS project, it is the operator’s responsibility to guarantee the CO₂ containment while complying with environmental regulations and CO₂ contractual requirements with the source emitter. Acquiring new information (e.g. seismic, logs, production data, etc.) about a particular field can reduce the uncertainty about the reservoir properties and can (but not necessarily) influence the decisions affecting the deployment of a CCS project. The main objective of this study is to provide a decision-analysis framework to quantify the Value of Information (VOI) in a CCS project that faces uncertainties about permeability values in the reservoir. This uncertainty translates into risks of CO₂ migration out of the containment zone (or lease zone), non-compliance with contractual requirements on CO₂ storage capacity, and leakage of CO₂ to sources of Underground Source of Drinking Water (USDW). The field under analysis has been idealized based on a real project located in Texas. Subsurface modeling of the upper Frio Formation (injection zone) was conducted using well logs, field-specific GIS data, and other relevant published literature. The idealized model was run for different scenarios with different permeability distributions. The VOI was quantified by defining prior scenarios based on the current knowledge of a reservoir, contractual requirements, and regulatory constraints. The project operator has the option to obtain more reliable estimates of permeability, which will help to reduce the uncertainty of the CO₂ behavior and storage capacity of the formation. The accuracy of the information gathering activities is then applied to the prior probabilities (Bayesian inference) to infer the value of such data. / text

Dispersivity data compiled over many lengths show that values at typical interwell distances are about two to four factors of ten larger than those measured on cores. Such large dispersivities may represent large mixing zones in the reservoir or they may be a result of convective spreading driven by permeability heterogeneity. This dissertation uses the idea of flow reversal (echo tests) to distinguish between convective spreading and dispersive mixing. Spreading is reversible, mixing is not. A zero or small value of echo dispersivity (estimated after flow reversal) implies little or no mixing and convection dominated transport. An echo dispersivity value equal to the transmission value (estimated after forward flow) would imply well mixed transport. A particle tracking code is developed to simulate echo tests for tracer transport in single phase, incompressible flow through three-dimensional, heterogeneous permeable media. Echo dispersivities are estimated for typical heterogeneity realizations and compared with corresponding transmission values at the field scale. The most important observation is that echo dispersivities are significantly larger than core scale values. They also lie on the overall trend of measured dispersivities and corroborate the large echo dispersivities previously inferred from single well tracer test data. This implies that significant mixing occurs in field scale transport. Echo dispersivities increase with permeability heterogeneity (variance and autocorrelation lengths). This is the effect of local (point or pore scale) mixing in the transverse direction, integrated over long and tortuous flow paths. Transport in typical reservoir formations, with significant autocorrelation in permeabilities, is most likely to be in a pre-asymptotic regime and cannot be described by a unique dispersivity value. This is because the Fickian model for dispersion fails to capture the mixing zone growth correctly in this regime. These results highlight the need to develop representative models for dispersion and improve upscaling methodologies. / text