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Articles 1 - 4 of 4
Full-Text Articles in Physical Sciences and Mathematics
Particle Swarm Transport In Porous Media, Alison R. Hoe, Laura J Pyrak-Nolte
Particle Swarm Transport In Porous Media, Alison R. Hoe, Laura J Pyrak-Nolte
The Summer Undergraduate Research Fellowship (SURF) Symposium
In recent years, interest in particulate transport in the subsurface has increased with the increased use of micro-particulates in consumer products. In this research, we study particulate swarm transport through porous media that depends on the complexity of the flow paths, on the size and shape of the particles and on the physical interactions among the particles, fluids, and matrix. Specifically, we investigate the effect of pore geometry and grain wettability on swarm evolution under gravity. Swarms were composed of 3 micron polystyrene beads in either water or water with KCL (%). Two types of grains are used to simulate …
Photonicstd-2d: Modeling Light Scattering In Periodic Multilayer Photonic Structures, Alexey Bondarev, Shaimaa Azzam, Zhaxylyk Kudyshev, Alexander V. Kildishev
Photonicstd-2d: Modeling Light Scattering In Periodic Multilayer Photonic Structures, Alexey Bondarev, Shaimaa Azzam, Zhaxylyk Kudyshev, Alexander V. Kildishev
The Summer Undergraduate Research Fellowship (SURF) Symposium
Efficient modeling of electromagnetic processes in optical and plasmonic metamaterials is important for enabling new and exciting ways to manipulate light for advanced applications. In this work, we put together a tool for numerical simulation of propagation of normally incident light through a nanostructured multilayer composite material. The user builds a unit cell of a given material layer-by-layer starting from a substrate up to a superstrate, splitting each layer further into segments. The segments are defined by width and material -- dielectric, metal or active medium. Simulations are performed with the finite difference time domain (FDTD) method. A database of …
Classifying Pattern Formation In Materials Via Machine Learning, Lukasz Burzawa, Shuo Liu, Erica W. Carlson
Classifying Pattern Formation In Materials Via Machine Learning, Lukasz Burzawa, Shuo Liu, Erica W. Carlson
The Summer Undergraduate Research Fellowship (SURF) Symposium
Scanning probe experiments such as scanning tunneling microscopy (STM) and atomic force microscopy (AFM) on strongly correlated materials often reveal complex pattern formation that occurs on multiple length scales. We have shown in two disparate correlated materials that the pattern formation is driven by proximity to a disorder-driven critical point. We developed new analysis concepts and techniques that relate the observed pattern formation to critical exponents by analyzing the geometry and statistics of clusters observed in these experiments and converting that information into critical exponents. Machine learning algorithms can be helpful correlating data from scanning probe experiments to theoretical models …
A Fast Model For The Simulation Of External Gear Pumps, Zechao Lu, Xinran Zhao, Andrea Vacca
A Fast Model For The Simulation Of External Gear Pumps, Zechao Lu, Xinran Zhao, Andrea Vacca
The Summer Undergraduate Research Fellowship (SURF) Symposium
External gear pump is an important category of positive displacement fluid machines used to perform the mechanical–hydraulic energy conversions in many fluid power applications. An efficient numerical simulation program is needed to simulate the system in order to provide a direction for design purpose. The model consists of a lumped parameter fluid dynamic model and a model that simulates the radial micro-motions of the gear’s axes of rotation. The system consists of a set of ordinary differential equations related to the conservation on mass of the internal control volumes of the pump, which are given by the tooth space volumes …