arXiv subjects

James E. McClure

Publications and source records attributed to James E. McClure.

At least 19 recordsLinked to original sources

arXiv2024

Commutativity properties of Quinn spectra

We give a simple sufficient condition for Quinn's "bordism-type" spectra to be weakly equivalent to commutative symmetric ring spectra. We also show that the symmetric signature is (up to weak equivalence) a monoidal transformation between symmetric monoidal functors, which implies that the Sullivan-Ranicki orientation of topological bundles is represented by a ring map between commutative symmetric ring spectra. In the course of proving these statements we give a new description of symmetric L theory which may be of independent interest.

math.AT↗

arXiv2024

Local interactions in active matter are reinforced by spatial structure

The flocking of self-propelled particles in heterogeneous environments is relevant to both natural and artificial systems. The Vicsek model is a canonical choice to investigate such systems due to the minimal number of parameters required to define flocking. Prior research on the Vicsek model has investigated the effects of interaction rules, particle speed, and obstacle packing on the flocking behavior, but the effect of interaction radius remains an open question. Unlike obstacle-free domains, the locality of interactions not only affects how quickly the system can become polarized, but also how well the flocks can align or realign after colliding with obstacles. In this letter, we delve into this subtle relationship that exists in the scale of the perception of Vicsek particles in the presence of obstacles. We demonstrate that the presence of obstacles impacts group density, which provides the basis to identify distinct phases for collective behavior. This leads to the counter-intuitive result that obstacles, while generally confounding for macroscopic order, may enable global order even as noise in the system increases.

physics.comp-ph↗

arXiv2023

The impact of wettability on the co-moving velocity of two-fluid flow in porous media

The impact of wettability on the co-moving velocity of two-fluid flow in porous media is analyzed herein. The co-moving velocity, developed by Roy et al. (2022), is a novel representation of the flow behavior of two fluids through porous media. Our study aims to better understand the behavior of the co-moving velocity by analyzing simulation data under various wetting conditions. The simulations were conducted using the Lattice-Boltzmann color-fluid model and evaluated the relative permeability for different wetting conditions on the same rock. The analysis of the simulation data followed the methodology proposed by Roy et al. (2022) to reconstruct a constitutive equation for the co-moving velocity. Surprisingly, it was found that the coefficients of the constitutive equation were nearly the same for all wetting conditions. Based on these results, a simple approach was proposed to reconstruct the oil phase relative permeability using only the co-moving velocity relationship and water phase relative permeability. This proposed method provides new insights into the dependency of relative permeability curves, which has implications for the history matching of production data and solving the associated inverse problem. The research findings contribute to a better understanding of the impact of wettability on fluid flow in porous media and provide a practical approach for estimating relative permeability based on the co-moving velocity relationship, which has never been shown before.

physics.flu-dyn↗

arXiv2023

Effective permeability of an immiscible fluid in porous media determined from its geometric state

Based on the phenomenological extension of Darcy's law, two-fluid flow is dependent on a relative permeability function of saturation only that is process/path dependent with an underlying dependency on pore structure. For applications, fuel cells to underground $CO_2$ storage, it is imperative to determine the effective phase permeability relationships where the traditional approach is based on the inverse modelling of time-consuming experiments. The underlying reason is that the fundamental upscaling step from pore to Darcy scale, which links the pore structure of the porous medium to the continuum hydraulic conductivities, is not solved. Herein, we develop an Artificial Neural Network (ANN) that relies on fundamental geometrical relationships to determine the mechanical energy dissipation during creeping immiscible two-fluid flow. The developed ANN is based on a prescribed set of state variables based on physical insights that predicts the effective permeability of 4,500 unseen pore-scale geometrical states with $R^2 = 0.98$.

physics.flu-dyn↗

arXiv2023

Simulating Noisy Quantum Circuits for Cryptographic Algorithms

The emergence of noisy intermediate-scale quantum (NISQ) computers has important consequences for cryptographic algorithms. It is theoretically well-established that key algorithms used in cybersecurity are vulnerable to quantum computers due to the fact that theoretical security guarantees, designed based on algorithmic complexity for classical computers, are not sufficient for quantum circuits. Many different quantum algorithms have been developed, which have potentially broad applications on future computing systems. However, this potential depends on the continued maturation of quantum hardware, which remains an area of active research and development. Theoretical limits provide an upper bound on the performance for algorithms. In practice, threats to encryption can only be accurately be assessed in the context of the rapidly evolving hardware and software landscape. Software co-design refers to the concurrent design of software and hardware as a way to understand the limitations of current capabilities and develop effective strategies to advance the state of the art. Since the capabilities for classical computation currently exceed quantum capabilities, quantum emulation techniques can play an important role in the co-design process. In this paper, we describe how the {\em cuQuantum} environment can support quantum algorithm co-design activities using widely-available commodity hardware. We describe how emulation techniques can be used to assess the impact of noise on algorithms of interest, and identify limitations associated with current hardware. We present our analysis in the context of areas of priority for cybersecurity and cryptography in particular since these algorithms are extraordinarily consequential for securing information in the digital world.

cs.CR↗

arXiv2023

Computing cohomology groups that classify bundles of strongly self-absorbing $C^*$-algebras

Locally trivial bundles of $C^*$-algebras with fibre $D \otimes \mathcal{K}$ for a strongly self-absorbing $C^*$-algebra $D$ over a finite CW-complex $X$ form a group $E^1_D(X)$ that is the first group of a cohomology theory $E^*_D(X)$. In this paper we compute these groups by expressing them in terms of ordinary cohomology and connective $K$-theory. To compare the $C^*$-algebraic version of $gl_1(KU)$ with its classical counterpart we also develop a uniqueness result for the unit spectrum of complex periodic topological $K$-theory.

math.OA↗

arXiv2022

Capturing membrane structure and function in lattice Boltzmann models

We develop a mesoscopic approach to model the non-equilibrium behavior of membranes at the cellular scale. Relying on lattice Boltzmann methods, we develop a solution procedure to recover the Nernst-Planck equations and Gauss's law. A general closure rule is developed to describe mass transport across the membrane, which is able to account for protein-mediated diffusion based on a coarse-grained representation. We demonstrate that our model is able to recover the Goldman equation from first principles and show that hyper-polarization occurs when membrane charging dynamics are controlled by multiple relaxation timescales. The approach provides a promising way to characterize non-equilibrium behaviors that arise due to the role of membranes in mediating transport based on realistic three-dimensional cell geometries.

cond-mat.mes-hall↗

arXiv2022

Relative permeability as a stationary process: energy fluctuations in immiscible displacement

Relative permeability is commonly used to model immiscible fluid flow through porous materials. In this work we derive the relative permeability relationship from conservation of energy, assuming that the system to be non-ergodic at large length scales and relying on averaging in both space and time to homogenize the behavior. Explicit criteria are obtained to define stationary conditions: (1) there can be no net change for extensive measures of the system state over the time averaging interval; (2) the net energy inputs into the system are zero, meaning that the net rate of work done on the system must balance with the heat removed; and (3) there is no net work performed due to the contribution of internal energy fluctuations. Results are then evaluated based on direct numerical simulation. Dynamic connectivity is observed during steady-state flow, which is quantitatively assessed based the Euler characteristic. We show that even during steady-state flow at low capillary number ($\mathsf{Ca}\sim1\times10^5$), typical flow processes will explore multiple connectivity states. The residence time for each connectivity state is captured based on the time-and-space average. The distribution for energy fluctuations is shown to be multi-modal and non-Gaussian when terms are considered independently. However, we demonstrate that their sum is zero. Given an appropriate choice of the thermodynamic driving force, we show that the conventional relative permeability relationship is sufficient to model the energy dissipation in systems with complex pore-scale dynamics that routinely alter the structure of fluid connected pathways.

physics.flu-dyn↗

arXiv2022

Neural Network Based Pore Flow Field Prediction in Porous Media Using Super Resolution

Direct pore-scale simulations of fluid flow through porous media are computationally expensive to perform for realistic systems. Previous works have demonstrated using the geometry of the microstructure of porous media to predict the velocity fields therein based on neural networks. However, such trained neural networks do not perform well for unseen porous media with a large degree of heterogeneity. In this study we propose that incorporating a coarse velocity field in the input of neural networks is an effective way to improve the prediction performance. The coarse velocity field can be simulated with a low computational cost and provides global information to regularize the ill-posedness of the learning problem, which is usually caused by the use of local geometries due to the computational resource constraints. We show that incorporating the coarse-mesh velocity field significantly improves the prediction accuracy of the fine-mesh velocity field by comparison to the prediction that relies on geometric information alone, especially for the porous medium with a large interior vuggy pore space. We also show the flexibility of training the network in using coarse velocity fields with various resolutions. The results suggest that even using coarse velocity field with a very low resolution, the predictions are still enhanced and close to the ground truths. The feasibility of the method is further demonstrated by testing the trained network on real rocks. This study highlights the merits of incorporating a coarse-mesh velocity field into the input for neural networks, which provides global, physics-based information for the model, thereby improving the model's generalization capability.

physics.flu-dyn↗

arXiv2021

Thermodynamics of fluctuations based on time-and-space averages

We develop non-equilibrium theory by using averages in time and space as a generalized way to upscale thermodynamics in non-ergodic systems. The approach offers a classical perspective on the energy dynamics in fluctuating systems. The rate of entropy production is shown to be explicitly scale dependent when considered in this context. We show that while any stationary process can be represented as having zero entropy production, second law constraints due to the Clausius theorem are preserved due to the fact that heat and work are related based on conservation of energy. As a demonstration we consider the energy dynamics for the Carnot cycle and for Maxwell's demon. We then consider non-stationary processes, applying time-and-space averages to characterize non-ergodic effects in heterogeneous systems where energy barriers such as compositional gradients are present. We show that the derived theory can be used to understand the origins of anomalous diffusion phenomena in systems where Fick's law applies at small length scales but not at large length scales. We then characterize fluctuations in capillary-dominated systems, which are non-stationary due to the irreversibility of cooperative events.

cond-mat.soft↗

arXiv2021

Capillary fluctuations and energy dynamics for flow in porous media

Capillary energy barriers have important consequences for immiscible fluid flow in porous media. We derive time-and-space averaging theory to account for non-equilibrium behavior and understand the role of athermal capillary fluctuations in the context of their relationship to larger scale phenomenological equations. The formulation resolves several key challenges associated with two-fluid flow in porous media: (1) geometric and thermodynamic quantities are constructed as smooth functions of time based on time-and space averages; (2) averaged thermodynamics are developed for films; (3) multi-scale fluctuation terms are identified, which account for transient behaviours of interfaces and films that occur due to pore-scale events; (4) geometric constraints are derived and imposed on the averaged thermodynamics; (5) a new constitutive model is proposed for capillary pressure dynamics that includes contributions from films; and (6) a time-and-space criterion for representative elementary volume (REV) is established based on capillary fluctuations. Capillary fluctuations are assessed quantitatively based on pore-scale simulations and experimental core-flooding data.

physics.flu-dyn↗

arXiv2020

Intersection homology duality and pairings: singular, PL, and sheaf-theoretic

We compare the sheaf-theoretic and singular chain versions of Poincare duality for intersection homology, showing that they are isomorphic via naturally defined maps. Similarly, we demonstrate the existence of canonical isomorphisms between the singular intersection cohomology cup product, the hypercohomology product induced by the Goresky-MacPherson sheaf pairing, and, for PL pseudomanifolds, the Goresky-MacPherson PL intersection product. We also show that the de Rham isomorphism of Brasselet, Hector, and Saralegi preserves product structures.

math.GT↗

arXiv2020

The LBPM software package for simulating multiphase flow on digital images of porous rocks

Direct pore scale simulations of two-fluid flow on digital rock images provide a promising tool to understand the role of surface wetting phenomena on flow and transport in geologic reservoirs. We present computational protocols that mimic conventional special core analysis laboratory (SCAL) experiments, which are implemented within the open source LBPM software package. Protocols are described to simulate unsteady displacement, steady-state flow at fixed saturation, and to mimic centrifuge experiments. These methods can be used to infer relative permeability and capillary curves, and otherwise understand two-fluid flow behavior based on first principles. Morphological tools are applied to assess image resolution, establish initial conditions, and instantiate surface wetting maps based on the distribution of fluids. Internal analysis tools are described that measure essential aspects of two-fluid flow, including fluid connectivity and surface measures, which are used to track transient aspects of the flow behavior as they occur during simulation. Computationally efficient workflows are developed by combining these components with a two-fluid lattice Boltzmann model to define hybrid methods that can accelerate computations by using morphological tools to incrementally evolve the pore-scale fluid distribution. We show that the described methods can be applied to recover expected trends due to the surface wetting properties based on flow simulation in Benntheimer sandstone.

physics.geo-ph↗

arXiv2020

Characterization of wetting using topological principles

Hypothesis Understanding wetting behavior is of great importance for natural systems and technological applications. The traditional concept of contact angle, a purely geometrical measure related to curvature, is often used for characterizing the wetting state of a system. It can be determined from Young's equation by applying equilibrium thermodynamics. However, whether contact angle is a representative measure of wetting for systems with significant complexity is unclear. Herein, we hypothesize that topological principles based on the Gauss-Bonnet theorem could yield a robust measure to characterize wetting. Theory and Experiments We introduce a macroscopic contact angle based on the deficit curvature of the fluid interfaces that are imposed by contacts with other immiscible phases. We perform sessile droplet simulations followed by multiphase experiments for porous sintered glass and Bentheimer sandstone to assess the sensitivity and robustness of the topological approach and compare the results to other traditional approaches. Findings We show that the presented topological principle is consistent with thermodynamics under the simplest conditions through a variational analysis. Furthermore, we elucidate that at sufficiently high image resolution the proposed topological approach and local contact angle measurements are comparable. While at lower resolutions, the proposed approach provides more accurate results being robust to resolution-based effects. Overall, the presented concepts open new pathways to characterize the wetting state of complex systems and theoretical developments to study multiphase systems.

physics.flu-dyn↗

arXiv2019

Linking continuum-scale state of wetting to pore-scale contact angles in porous media

Wetting phenomena play a key role in flows through porous media. Relative permeability and capillary pressure-saturation functions show a high sensitivity to wettability, which has different definitions at the continuum- and pore-scale. At the continuum-scale, the state of wetting is defined as Amott-Harvey or USBM (United States Bureau of Mines) by capillary pressure drainage and imbibition cycles. At the pore-scale, the concept of contact angle is used, which until recently was not experimentally possible to determine within an opaque porous medium. Recent progress on measurements of pore-scale contact angles by X-ray computed micro-tomography has therefore attracted significant attention in various research communities. In this work, the Gauss-Bonnet theorem is applied to provide a direct link between capillary pressure saturation $P_c(S_w)$ data and measured distributions of pore-scale contact angles. We propose that the wetting state of a porous medium can be described in terms of geometrical arguments that constrain the morphological state of immiscible fluids. The constraint describes the range of possible contact angles and interfacial curvatures that can exist for a given system. We present measurements in a tested sandstone for which the USBM index, $P_c(S_w)$, and pore-scale contact angles are measured. Additional studies are also performed using two-phase Lattice Boltzmann simulations to test a wider range of wetting conditions. We show that mean pore-scale contact angle measurements can be predicted from petrophysical data within a few differences. This provides a general framework on how continuum-scale data can be used to describe the geometrical state of fluids within porous media.

physics.flu-dyn↗

arXiv2019

Geometric evolution as a source of discontinuous behavior in soft condensed matter

Geometric evolution represents a fundamental aspect of many physical phenomena. In this paper we consider the geometric evolution of structures that undergo topological changes. Topological changes occur when the shape of an object evolves such that it either breaks apart or converges back into itself to form a loop. Changes to the topology of an object are fundamentally discrete events. We consider how discontinuities arise during geometric evolution processes by characterizing the possible topological events and analyzing the associated source terms based on evolution equations for geometric invariants. We show that the discrete nature of a topological change leads to discontinuous source terms that propagate to physical variables.

cond-mat.soft↗

arXiv2018

The L-Homology Fundamental Class for IP-Spaces and the Stratified Novikov Conjecture

An IP-space is a pseudomanifold whose defining local properties imply that its middle perversity global intersection homology groups satisfy Poincaré duality integrally. We show that the symmetric signature induces a map of Quinn spectra from IP bordism to the symmetric $L$-spectrum of $\Z$, which is, up to weak equivalence, an $E_\infty$ ring map. Using this map, we construct a fundamental $L$-homology class for IP-spaces, and as a consequence we prove the stratified Novikov conjecture for IP-spaces.

math.AT↗

arXiv2018

An Adaptive Volumetric Flux Boundary Condition for Lattice Boltzmann Methods

This paper presents a spatially and temporally adaptive boundary condition to specify the volumetric flux for lattice Boltzmann methods. The approach differs from standard velocity boundary conditions because it allows the velocity to vary over the boundary region provided that the total flux through the boundary satisfies a prescribed constraint, which is a typical scenario for laboratory experimental studies. This condition allows the boundary pressure to adjust dynamically to yield a specified boundary flow rate as a means to avoid unphysical mismatch between the boundary velocity and the interior flow field that can arise when a constant velocity boundary condition is applied. The method is validated for simulation of one- and two-fluid flow in complex materials, with conditions determined to match typical experiments used to study flow in porous media.

physics.comp-ph↗