Simulations of Surfactant Driven Thin Film Flow

This thesis is intended to fulfill the requirements of the Math and Physics departments at Harvey Mudd College. We begin with a brief introduction to the study of surfactant dynamics followed by some background on the experimental framework our work is related to. We then go through a derivation of the model we use, and explore in depth the nature of the Equation of State (EoS), the relationship between the surface tension on a fluid and the surfactant concentration. We consider the effect of using an empirical equation of state on the results of the simulations and compare the new results against the results produced using a multilayer (EoS) as well as experimental observations. We find that the empirical EoS leads to two new behaviors - preserving of large gradients of surfactant concentration and the occurrence of dynamics in distinct regimes. These behaviors suggest that the empirical EoS improves the agreement of the model’s prediction with experiment

Connectivity-Aware Pheromone Mobility Model for Autonomous UAV Networks

UAV networks consisting of reduced size, weight, and power (low SWaP) fixed-wing UAVs are used for civilian and military applications such as search and rescue, surveillance, and tracking. To carry out these operations efficiently, there is a need to develop scalable, decentralized autonomous UAV network architectures with high network connectivity. However, the area coverage and the network connectivity requirements exhibit a fundamental trade-off. In this paper, a connectivity-aware pheromone mobility (CAP) model is designed for search and rescue operations, which is capable of maintaining connectivity among UAVs in the network. We use stigmergy-based digital pheromone maps along with distance-based local connectivity information to autonomously coordinate the UAV movements, in order to improve its map coverage efficiency while maintaining high network connectivity

Decentralized and stable matching in Peer-to-Peer energy trading

In peer-to-peer (P2P) energy trading, a secured infrastructure is required to manage trade and record monetary transactions. A central server/authority can be used for this. But there is a risk of central authority influencing the energy price. So blockchain technology is being preferred as a secured infrastructure in P2P trading. Blockchain provides a distributed repository along with smart contracts for trade management. This reduces the influence of central authority in trading. However, these blockchain-based systems still rely on a central authority to pair/match sellers with consumers for trading energy. The central authority can interfere with the matching process to profit a selected set of users. Further, a centralized authority also charges for its services, thereby increasing the cost of energy. We propose two distributed mechanisms to match sellers with consumers. The first mechanism doesn't allow for price negotiations between sellers and consumers, whereas the second does. We also calculate the time complexity and the stability of the matching process for both mechanisms. Using simulation, we compare the influence of centralized control and energy prices between the proposed and the existing mechanisms. The overall work strives to promote the free market and reduce energy prices

Patterns in the daily diary of the 41st president, George Bush

This thesis explores interfaces for locating and comprehending patterns among time-based materials in digital libraries. Time-based digital library materials are like other digital library materials in that they are comprised of data and metadata. In addition, they have a time or period of time attached to each data item. The specific focus of this thesis is on fine-granularity items-items that have relatively little data and cover brief periods of time. In such a context, people often are left to discern patterns of activity by retrospectively making sense of the collection or parts thereof. The specific domain chosen for the implementation is the daily diary of President George Bush, the 41st president of the USA. This project developed a searching and browsing interface, which allows people to study the relationship between activities and people in the library data. As part of this thesis, a corpus of the Presidential daily diary was digitized. Two interfaces were provided to this corpus, one based on a standard information retrieval engine (Greenstone) and another presenting time-based visualizations of data items. An evaluation was conducted to explore the relative strengths and weaknesses of these two interfaces

A Deep Q-Learning based, Base-Station Connectivity-Aware, Decentralized Pheromone Mobility Model for Autonomous UAV Networks

UAV networks consisting of low SWaP (size, weight, and power), fixed-wing UAVs are used in many applications, including area monitoring, search and rescue, surveillance, and tracking. Performing these operations efficiently requires a scalable, decentralized, autonomous UAV network architecture with high network connectivity. Whereas fast area coverage is needed for quickly sensing the area, strong node degree and base station (BS) connectivity are needed for UAV control and coordination and for transmitting sensed information to the BS in real time. However, the area coverage and connectivity exhibit a fundamental trade-off: maintaining connectivity restricts the UAVs' ability to explore. In this paper, we first present a node degree and BS connectivity-aware distributed pheromone (BS-CAP) mobility model to autonomously coordinate the UAV movements in a decentralized UAV network. This model maintains a desired connectivity among 1-hop neighbors and to the BS while achieving fast area coverage. Next, we propose a deep Q-learning policy based BS-CAP model (BSCAP-DQN) to further tune and improve the coverage and connectivity trade-off. Since it is not practical to know the complete topology of such a network in real time, the proposed mobility models work online, are fully distributed, and rely on neighborhood information. Our simulations demonstrate that both proposed models achieve efficient area coverage and desired node degree and BS connectivity, improving significantly over existing schemes

DAISIM: A Computational Simulator for the MakerDAO Stablecoin

We present a computational simulation of the single-collateral DAI stablecoin launched by the MakerDAO project in 2017. At the core of the simulation is a model of cryptocurrency investors acting as rational Markowitz mean-variance portfolio optimizers, with heterogeneous risk tolerance. The simulator, called DAISIM, incorporates automated order matching and price update mechanisms to determine the DAI price. We use the simulator to evaluate how the single-collateral DAI price, as well as portfolio allocations, vary for a given population of investors as a function of exogenous parameters such as the price of ETH and various system parameters including stability rate and transaction fee. DAISIM is being made available as open-source and may be useful in evaluating other similar projects