Online Supplement to ‘Myopic Allocation Policy with Asymptotically Optimal Sampling Rate’

This document is the Online Supplement to ‘Myopic Allocation Policy with Asymptotically Optimal Sampling Rate,’ to be published in the IEEE Transactions of Automatic Control in 2017.

Computational Analysis of Intelligent Agents: Social and Strategic Settings

The central motif of this work is prediction and optimization in presence of multiple interacting intelligent agents. We use the phrase `intelligent agents' to imply in some sense, a `bounded rationality', the exact meaning of which varies depending on the setting. Our agents may not be `rational' in the classical game theoretic sense, in that they don't always optimize a global objective. Rather, they rely on heuristics, as is natural for human agents or even software agents operating in the real-world. Within this broad framework we study the problem of influence maximization in social networks where behavior of agents is myopic, but complication stems from the structure of interaction networks. In this setting, we generalize two well-known models and give new algorithms and hardness results for our models. Then we move on to models where the agents reason strategically but are faced with considerable uncertainty. For such games, we give a new solution concept and analyze a real-world game using out techniques. Finally, the richest model we consider is that of Network Cournot Competition which deals with strategic resource allocation in hypergraphs, where agents reason strategically and their interaction is specified indirectly via player's utility functions. For this model, we give the first equilibrium computability results. In all of the above problems, we assume that payoffs for the agents are known. However, for real-world games, getting the payoffs can be quite challenging. To this end, we also study the inverse problem of inferring payoffs, given game history. We propose and evaluate a data analytic framework and we show that it is fast and performant.

Evolution of strength and physical properties of ultramafic and carbonate rocks under hydrothermal conditions

Interaction of rocks with fluids can significantly change mineral assemblage and structure. This so-called hydrothermal alteration is ubiquitous in the Earth’s crust. Though the behavior of hydrothermally altered rocks can have planet-scale consequences, such as facilitating oceanic spreading along slow ridge segments and recycling volatiles into the mantle at subduction zones, the mechanisms involved in the hydrothermal alteration are often microscopic. Fluid-rock interactions take place where the fluid and rock meet. Fluid distribution, flux rate and reactive surface area control the efficiency and extent of hydrothermal alteration. Fluid-rock interactions, such as dissolution, precipitation and fluid mediated fracture and frictional sliding lead to changes in porosity and pore structure that feed back into the hydraulic and mechanical behavior of the bulk rock. Examining the nature of this highly coupled system involves coordinating observations of the mineralogy and structure of naturally altered rocks and laboratory investigation of the fine scale mechanisms of transformation under controlled conditions. In this study, I focus on fluid-rock interactions involving two common lithologies, carbonates and ultramafics, in order to elucidate the coupling between mechanical, hydraulic and chemical processes in these rocks. I perform constant strain-rate triaxial deformation and constant-stress creep tests on several suites of samples while monitoring the evolution of sample strain, permeability and physical properties. Subsequent microstructures are analyzed using optical and scanning electron microscopy. This work yields laboratory-based constraints on the extent and mechanisms of water weakening in carbonates and carbonation reactions in ultramafic rocks. I find that inundation with pore fluid thereby reducing permeability. This effect is sensitive to pore fluid saturation with respect to calcium carbonate. Fluid inundation weakens dunites as well. The addition of carbon dioxide to pore fluid enhances compaction and partial recovery of strength compared to pure water samples. Enhanced compaction in CO2-rich fluid samples is not accompanied by enhanced permeability reduction. Analysis of sample microstructures indicates that precipitation of carbonates along fracture surfaces is responsible for the partial restrengthening and channelized dissolution of olivine is responsible for permeability maintenance.

DEVELOPMENT OF AN OFF-LINE RAINFLOW COUNTING ALGORITHM WITH TEMPORAL PARAMETERS AND DATA REDUCTION

Rainflow counting methods convert a complex load time history into a set of load reversals for use in fatigue damage modeling. Rainflow counting methods were originally developed to assess fatigue damage associated with mechanical cycling where creep of the material under load was not considered to be a significant contributor to failure. However, creep is a significant factor in some cyclic loading cases such as solder interconnects under temperature cycling. In this case, fatigue life models require the dwell time to account for stress relaxation and creep. This study develops a new version of the multi-parameter rainflow counting algorithm that provides a range-based dwell time estimation for use with time-dependent fatigue damage models. To show the applicability, the method is used to calculate the life of solder joints under a complex thermal cycling regime and is verified by experimental testing. An additional algorithm is developed in this study to provide data reduction in the results of the rainflow counting. This algorithm uses a damage model and a statistical test to determine which of the resultant cycles are statistically insignificant to a given confidence level. This makes the resulting data file to be smaller, and for a simplified load history to be reconstructed.