Morrow1 Model - with Capillary Pressure
Farnsworth Unit (FWU) CO2EOR Eclipse compositional model: Morrow1 model uses the Morrow1 relative permeability curve with capillary pressure assigned homogeneously
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Farnsworth Unit (FWU) CO2EOR Eclipse compositional model: Morrow1 model uses the Morrow1 relative permeability curve with capillary pressure assigned homogeneously
Battery performance is strongly correlated with electrode microstructural properties. To account for its impact, lithium-ion battery (LIB) models either abstract the microstructural heterogeneity of composite electrodes using effective macroscopic properties (macro- or meso- scale models) or directly solve the system of equations on the microstructure geometry or mesh (microstructure-scale models). Therefore, to be adequate, both families of models require information from the microstructure geometry, which can be provided by the numerical tool presented in this work. MATBOX is a MATLAB open-source application [1] developed by NREL for performing various microstructure-related tasks including microstructure numerical generation, image filtering and microstructure segmentation, microstructure characterization and correlation, visualization, and microstructure meshing. MATBOX was originally developed for the analysis of LIB electrode microstructures; however, the algorithms provided by the toolbox are widely applicable to other heterogeneous materials. The toolbox provides a user-friendly experience thanks to a Graphical-User Interface, requires no coding by the user, and is well documented. This presentation will illustrate various MATBOX features for the characterization of a LIB electrode, including a fully automated Representative Volume Element (RVE) analysis, the numerical generation of complex 'virtual' microstructure, including dual-layer electrodes and carbon-binder additive phase, and the meshing of a complex NMC/graphite full cell microstructure suitable for 3D finite-element modeling. Other modules (segmentation, visualization, and correlation) will be briefly presented. Thanks to its modular, open-source approach, MATBOX can easily incorporate third-party algorithms to eventually build a standard in the field that will benefit the whole scientific community. Effective diffusion coefficient [2], additive phase numerical generation [3], and meshing [4] third-party algorithms have been already integrated in the toolbox with more to come.
Surface tension affects all aspects of fluid flow in porous media. Through measurements of surface tension interaction under multiphase conditions, a relative permeability curve can be determined. Relative permeability is a numerical description of the interaction between two or more fluids and the porous media. It is a critical parameter for various tools that characterize subsurface multiphase flow systems, such as numerical simulation for carbon sequestration, oil and gas development, and groundwater contamination remediation. Therefore, it is critical to get a good statistical distribution of relative permeability in the porous media under study. Empirical formula for determining relative permeability from capillary pressure are already well established but do not provide the needed flexibility that is required to match laboratory-derived relative permeability curves. By expanding the existing methods for calculating relative permeability from capillary pressure data, it is possible to create both two and three-phase relative permeability curves. Mercury intrusion capillary pressure (MICP) data from the Morrow 'B' Sandstone coupled with interfacial tension and contact angle measurements were used to create a suite of relative permeability curves. Furthermore, these curves were then calibrated to a small sample of existing laboratory curves to elucidate common fitting parameters for the formation that were then used to create relative permeability curves from MICP data that does not have an associated laboratory-measured relative permeability curve.
Farnsworth Unit (FWU) CO2EOR Eclipse compositional model: Hydrostratigraphic Region 4 model uses the Morrow2 (UNOCAL) relative permeability curve with HSU5 capillary pressure assigned homogeneously
Farnsworth Unit (FWU) CO2EOR Eclipse compositional model: Hydrostratigraphic Region 4 model uses the Morrow2 (UNOCAL) relative permeability curve with HSU6 capillary pressure assigned homogeneously
Surface tension affects all aspects of fluid flow in porous media. Through measurements of surface tension interaction under multiphase conditions, a relative permeability relationship can be determined. Relative permeability is a numerical description of the interplay between two or more fluids and the porous media they flow through. It is a critical parameter for various tools used to characterized subsurface multiphase flow systems, such as numerical simulation for oil and gas development, carbon sequestration, and groundwater contamination remediation. Therefore, it is critical to get a good statistic distribution of relative permeability in the porous media under study. Empirical relationships for determining relative permeability from capillary pressure are already well established but do not provide the needed flexibility required to match laboratory derive relative permeability relationships. By expanding the existing methods for calculating relative permeability from capillary pressure data, it is possible to create both two and three-phase relative permeability relationships. Existing laboratory-measured relative permeability data along with mercury intrusion capillary (MICP) data coupled with interfacial tension and contact angle measurements were used to determine the efficacy of this approach to relative permeability curve creation. The relative permeability relationships determined with this method were fit to existing laboratory data to elucidate common fitting parameters that were then used to create relative permeability relationships from MICP data that does not have an associated laboratory-measured relative permeability relationship.
Farnsworth Unit (FWU) CO2EOR Eclipse compositional model: Hydrostratigraphic Region 4 model uses the Morrow2 (UNOCAL) relative permeability curve with HSU3-4 capillary pressure assigned homogeneously
Farnsworth Unit (FWU) CO2EOR Eclipse compositional model: Hydrostratigraphic Region 4 model uses the Morrow2 (UNOCAL) relative permeability curve with HSU7-8 capillary pressure assigned homogeneously
Farnsworth Unit (FWU) CO2EOR Eclipse compositional model: Hydrostratigraphic Region 4 model uses the Morrow2 (UNOCAL) relative permeability curve with capillary pressure assigned heterogeneously by hydrostratigraphic unit
These excel spreadsheets were used to develop the two-phase and three-phase methods for converting capillary pressure to relative permeability. Data was collected by the SWP and literature sources cited in the spreadsheets.
Examining the evolution of the maximum of valence quark distribution, qV, weighted by Bjorken x, h(x,t)≡xqV(x,t), it is observed that h(x,t) at the peak becomes a one-parameter function; h(xp,t)=Φ(xp(t)), where xp is the position of the peak, t=logQ2, and Q2 is the resolution scale. This observation is used to derive a new model-independent relation which connects the partial derivative of the valence parton distribution functions (PDFs) in xp to the quantum chromodynamics (QCD) evolution equation through the xp derivative of the logarithm of the function Φ(xp(t)). A numerical analysis of this relation using empirical PDFs results in an observation of the exponential form of the Φ(xp(t))=h(xp,t)=CeDxp(t) for leading to next-to-next leading order approximations of PDFs for the range of Q2, covering four orders in magnitude. The exponent, D, of the observed “height-position” correlation function converges with the increase in the order of approximation. This result holds for all the PDF sets considered. A similar relation is observed also for the pion valence quark distribution, indicating that the obtained relation may be universal for any non-singlet partonic distribution. The observed “height-position” correlation is used also to indicate that no finite number of exchanges can describe the analytic behavior of the valence quark distribution at the position of the peak at fixed Q2.
Farnsworth Unit (FWU) CO2EOR Eclipse compositional model: Hydrostratigraphic Region 1 model uses the HS1 relative permeability curves assigned heterogeneously by hydrostratigraphic unit. The model with capillary pressure applies the HS1 curves heterogeneously by hydrostratigraphic unit.
Farnsworth Unit (FWU) CO2EOR Eclipse compositional model: Hydrostratigraphic Region 3 model uses the HS3 relative permeability curves assigned heterogeneously by hydrostratigraphic unit. The model with capillary pressure applies the HS3 curves heterogeneously by hydrostratigraphic unit.
One of the frontiers for advancing what is known about dark matter lies in using strong gravitational lenses to characterize the population of the smallest dark matter haloes. There is a large volume of information in strong gravitational lens images – the question we seek to answer is to what extent we can refine this information. To this end, we forecast the detectability of a mixed warm and cold dark matter scenario using the anomalous flux ratio method from strong gravitational lensed images. The halo mass function of the mixed dark matter scenario is suppressed relative to cold dark matter but still predicts numerous low-mass dark matter haloes relative to warm dark matter. Since the strong lensing signal receives a contribution from a range of dark matter halo masses and since the signal is sensitive to the specific configuration of dark matter haloes, not just the halo mass function, degeneracies between different forms of suppression in the halo mass function, relative to cold dark matter, can arise. Here, we find that, with a set of lenses with different configurations of the main deflector and hence different sensitivities to different mass ranges of the halo mass function, the different forms of suppression of the halo mass function between the warm dark matter model and the mixed dark matter model can be distinguished with 40 lenses with Bayesian odds of 30:1.
The Used Nuclear Fuel-Storage, Transportation & Disposal Analysis Resource and Data System (UNF-ST&DARDS) is a software tool that integrates a used nuclear fuel (UNF) or spent nuclear fuel (SNF) relational database and key analysis capabilities to simplify and automate numerous UNF management and fuel cycle–related activities. UNF-ST&DARDS is being developed for the US Department of Energy’s Office of Nuclear Energy Spent Fuel and Waste Disposition program. UNF-ST&DARDS provides an integrated framework that uses advanced modeling and simulation to predict the behavior of SNF over the timescales associated with permanent disposal in a geologic repository. After leaving the spent fuel pool, SNF is transferred to dry storage in a dual-purpose canister (DPC). DPCs are considered “dual purpose” because they are designed for both storage and transportation, removing the need to transfer the fuel to a separate transportation cask. However, much research has been conducted investigating the feasibility of directly disposing of DPCs in geologic repositories. Direct disposal of DPCs could reduce worker exposure during repackaging, reducing the amount of low-level waste from the discarded DPCs and potentially saving billions of dollars. Therefore, direct disposal of as-loaded DPCs is desirable if it can be done safely.
Micromix combustion presents a promising solution for integrating hydrogen into gas turbine combustors, offering rapid and compact air-fuel mixing that effectively shortens the combustion zone and significantly reduces nitrogen oxides (NOX) emissions. A major challenge in hydrogen combustion systems is flashback, which is mitigated through short mixing lengths and high flow velocities. This study investigates three fuel injector designs – zero swirl, low swirl, and high swirl – for a 6-mm inner diameter nozzle, where hydrogen is injected through six 0.3 mm diameter holes in a jet-in-crossflow configuration relative to the airstream. Numerical simulations indicate stable flame formation, moderate peak flame temperatures, and subsequent low NOx potential for all designs. These injectors have been fabricated using additive manufacturing, and upcoming experiments will explore flame structure and NOx behavior across varying fuel injection angles, equivalence ratios and pre-mixer velocities. These efforts aim to advance the development of low-emission hydrogen micromix combustion.
A new method for solving nonlinear heat and mass transfer design tasks was considered. Systems using the Number of Transfer Units (NTU) method are a special type of mathematical model of heat and mass exchangers. It was observed, that the NTU models in a form of differential-algebraic equations (DAEs) cannot be directly solved with higher values of NTU. The requirements for consistent initial conditions, as well as numerical limitations of DAEs solvers, result, that the solution to the considered design problems that cannot be obtained by a classical direct shooting procedure. To overcome the presented difficulties, the αDAE model optimization algorithm was adjusted for solving NTU-based models. The new approach consists of 3 main steps: 1) task discretization by a multiple-shooting approach, 2) design an appropriate function $f_{NTU}$(α) to effectively influence the variability of the state variables described by dynamical relations, 3) the iterative numerical optimization algorithm for the new parametrized system. Moreover, computations can be performed by a chosen numerical optimization approach, which can be communicated with an available outer procedure for solving differential-algebraic equations. The presented algorithm was implemented and applied to solve the design task with the NTU model of a counter-flow exchanger. Here, the new approach was used to modify the system dynamics to influence the difficulty of the considered problem. Finally, the presented method enabled failure-free numerical computations for the higher values of the NTU parameter.
Abstract Motivated by a computer model calibration problem from the oil and gas industry, involving the design of a honeycomb seal, we develop a new Bayesian methodology to cope with limitations in the canonical apparatus stemming from several factors. We propose a new strategy of on‐site design and surrogate modeling for a computer simulator acting on a high‐dimensional input space that, although relatively speedy, is prone to numerical instabilities, missing data, and nonstationary dynamics. Our aim is to strike a balance between data‐faithful modeling and computational tractability in a calibration framework—tailoring the computer model to a limited field experiment. Situating our on‐site surrogates within the canonical calibration apparatus requires updates to that framework. We describe a novel yet intuitive Bayesian setup that carefully decomposes otherwise prohibitively large matrices by exploiting the sparse blockwise structure. Empirical illustrations demonstrate that this approach performs well on toy data and our motivating honeycomb example.