Matching Items (5)

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The Analysis of the Airflow around a Rotating Cylindrical Arrow

Description

This honors thesis explores and models the flow of air around a cylindrical arrow that is rotating as it moves through the air. This model represents the airflow around an archery arrow after it is released from the bow and

This honors thesis explores and models the flow of air around a cylindrical arrow that is rotating as it moves through the air. This model represents the airflow around an archery arrow after it is released from the bow and rotates while it flies through the air. This situation is important in archery because an understanding of the airflow allows archers to predict the flight of the arrow. As a result, archers can improve their accuracy and ability to hit targets. However, not many computational fluid dynamic simulations modeling the airflow around a rotating archery arrow exist. This thesis attempts to further the understanding of the airflow around a rotating archery arrow by creating a mathematical model to numerically simulate the airflow around the arrow in the presence of this rotation. This thesis uses a linearized approximation of the Navier Stokes equations to model the airflow around the arrow and explains the reasoning for using this simplification of the fully nonlinear Navier Stokes equations. This thesis continues to describe the discretization of these linearized equations using the finite difference method and the boundary conditions used for these equations. A MATLAB code solves the resulting system of equations in order to obtain a numerical simulation of this airflow around the rotating arrow. The results of the simulation for each velocity component and the pressure distribution are displayed. This thesis then discusses the results of the simulation, and the MATLAB code is analyzed to verify the convergence of the solution. Appendix A includes the full MATLAB code used for the flow simulation. Finally, this thesis explains potential future research topics, ideas, and improvements to the code that can help further the understanding and create more realistic simulations of the airflow around a flying archery arrow.

Contributors

Created

Date Created
2019-05

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A New Numerical Method Based on Leapfrog for Atmospheric and Ocean Modeling

Description

A semi-implicit, fourth-order time-filtered leapfrog numerical scheme is investigated for accuracy and stability, and applied to several test cases, including one-dimensional advection and diffusion, the anelastic equations to simulate the Kelvin-Helmholtz instability, and the global shallow water spectral model to

A semi-implicit, fourth-order time-filtered leapfrog numerical scheme is investigated for accuracy and stability, and applied to several test cases, including one-dimensional advection and diffusion, the anelastic equations to simulate the Kelvin-Helmholtz instability, and the global shallow water spectral model to simulate the nonlinear evolution of twin tropical cyclones. The leapfrog scheme leads to computational modes in the solutions to highly nonlinear systems, and time-filters are often used to damp these modes. The proposed filter damps the computational modes without appreciably degrading the physical mode. Its performance in these metrics is superior to the second-order time-filtered leapfrog scheme developed by Robert and Asselin.

Contributors

Created

Date Created
2016-05

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Consumer Choice Optimization Methods

Description

This paper is an exploration of numerical optimization as it applies to the consumer choice problem. Suggested algorithms are intended to compute solutions to the Marshallian problem, and some can extend to the dual given the suggested modifications. Each method

This paper is an exploration of numerical optimization as it applies to the consumer choice problem. Suggested algorithms are intended to compute solutions to the Marshallian problem, and some can extend to the dual given the suggested modifications. Each method seeks to either weaken the sufficient conditions for optimization, converge to a solution more efficiently, or describe additional properties of the decision space. The purpose of this paper is to explore constrained quasiconvex programming in a less complicated environment by design of Marshallian constraints.

Contributors

Agent

Created

Date Created
2021-05

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Multi-Agent Coordination and Control under Information Asymmetry with Applications to Collective Load Transport

Description

Coordination and control of Intelligent Agents as a team is considered in this thesis.

Intelligent agents learn from experiences, and in times of uncertainty use the knowl-

edge acquired to make decisions and accomplish their individual or team objectives.

Agent objectives are defined

Coordination and control of Intelligent Agents as a team is considered in this thesis.

Intelligent agents learn from experiences, and in times of uncertainty use the knowl-

edge acquired to make decisions and accomplish their individual or team objectives.

Agent objectives are defined using cost functions designed uniquely for the collective

task being performed. Individual agent costs are coupled in such a way that group ob-

jective is attained while minimizing individual costs. Information Asymmetry refers

to situations where interacting agents have no knowledge or partial knowledge of cost

functions of other agents. By virtue of their intelligence, i.e., by learning from past

experiences agents learn cost functions of other agents, predict their responses and

act adaptively to accomplish the team’s goal.

Algorithms that agents use for learning others’ cost functions are called Learn-

ing Algorithms, and algorithms agents use for computing actuation (control) which

drives them towards their goal and minimize their cost functions are called Control

Algorithms. Typically knowledge acquired using learning algorithms is used in con-

trol algorithms for computing control signals. Learning and control algorithms are

designed in such a way that the multi-agent system as a whole remains stable during

learning and later at an equilibrium. An equilibrium is defined as the event/point

where cost functions of all agents are optimized simultaneously. Cost functions are

designed so that the equilibrium coincides with the goal state multi-agent system as

a whole is trying to reach.

In collective load transport, two or more agents (robots) carry a load from point

A to point B in space. Robots could have different control preferences, for example,

different actuation abilities, however, are still required to coordinate and perform

load transport. Control preferences for each robot are characterized using a scalar

parameter θ i unique to the robot being considered and unknown to other robots.

With the aid of state and control input observations, agents learn control preferences

of other agents, optimize individual costs and drive the multi-agent system to a goal

state.

Two learning and Control algorithms are presented. In the first algorithm(LCA-

1), an existing work, each agent optimizes a cost function similar to 1-step receding

horizon optimal control problem for control. LCA-1 uses recursive least squares as

the learning algorithm and guarantees complete learning in two time steps. LCA-1 is

experimentally verified as part of this thesis.

A novel learning and control algorithm (LCA-2) is proposed and verified in sim-

ulations and on hardware. In LCA-2, each agent solves an infinite horizon linear

quadratic regulator (LQR) problem for computing control. LCA-2 uses a learning al-

gorithm similar to line search methods, and guarantees learning convergence to true

values asymptotically.

Simulations and hardware implementation show that the LCA-2 is stable for a

variety of systems. Load transport is demonstrated using both the algorithms. Ex-

periments running algorithm LCA-2 are able to resist disturbances and balance the

assumed load better compared to LCA-1.

Contributors

Agent

Created

Date Created
2018

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Computational Methods for Simulations of Multiphase Compressible Flows for Atomization Applications

Description

Compressible fluid flows involving multiple physical states of matter occur in both nature and technical applications such as underwater explosions and implosions, cavitation-induced bubble collapse in naval applications and Richtmyer-Meshkov type instabilities in inertial confinement fusion. Of particular interest is

Compressible fluid flows involving multiple physical states of matter occur in both nature and technical applications such as underwater explosions and implosions, cavitation-induced bubble collapse in naval applications and Richtmyer-Meshkov type instabilities in inertial confinement fusion. Of particular interest is the atomization of fuels that enable shock-induced mixing of fuel and oxidizer in supersonic combustors. Due to low residence times and varying length scales, providing insight through physical experiments is both technically challenging and sometimes unfeasible. Numerical simulations can help provide detailed insight and aid in the engineering design of devices that can harness these physical phenomena.

In this research, computational methods were developed to accurately simulate phase interfaces in compressible fluid flows with a focus on targeting primary atomization. Novel numerical methods which treat the phase interface as a discontinuity, and as a smeared region were developed using low-dissipation, high-order schemes. The resulting methods account for the effects of compressibility, surface tension and viscosity. To aid with the varying length scales and high-resolution requirements found in atomization applications, an adaptive mesh refinement (AMR) framework is used to provide high-resolution only in regions of interest. The developed methods were verified with test cases involving strong shocks, high density ratios, surface tension effects and jumps in the equations of state, in one-, two- and three dimensions, obtaining good agreement with theoretical and experimental results. An application case of the primary atomization of a liquid jet injected into a Mach 2 supersonic crossflow of air is performed with the methods developed.

Contributors

Agent

Created

Date Created
2020