Casey Doyle

Sandia National Laboratories

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Co-Authors

G. Korniss

Rensselaer Polytechnic Institute

Bolesław K. Szymański

Rensselaer Polytechnic Institute

Asmeret Naugle

Sandia National Laboratories

Stephen Verzi

Sandia National Laboratories

Walter Beyeler

Sandia National Laboratories

Bryan Arguello

Sandia National Laboratories California

Kevin L. Stamber

Sandia National Laboratories

Edward Matteo

Sandia National Laboratories California

David Schoenwald

Sandia National Laboratories

Barry Roberts

Sandia National Laboratories California

Cooperative Institutions

Sandia National Laboratories California

Sandia National Laboratories

University of New Mexico

Rensselaer Polytechnic Institute

National Technical Information Service

Office of Scientific and Technical Information

DEVCOM Army Research Laboratory

United States Army Combat Capabilities Development Command

ORCID

University of Notre Dame

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Impact of Bursty Communication Patterns on Naming Game Competitions

Bulletin of the American Physical Society (2016)

Casey Doyle G. Korniss Bolesław K. Szymański

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Optimal Electric Grid Black Start Restoration Subject to Threats.

OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (2022)

Kevin L. Stamber Bryan Arguello R. Sam Garrett Walter Beyeler Casey Doyle

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Optimal Electric Grid Black Start Restoration Subject to Intentional Threats.

Kevin L. Stamber Bryan Arguello R. Sam Garrett Walter Beyeler Casey Doyle

operators. These assumptions are not guaranteed under some threats. This paper focuses on a novel integration of modeling and analysis capabilities to aid operators during restoration activities. A power flow-informed restoration framework, comprised of a restoration mixed-integer program informed by power flow models to identify restoration alternatives, interacts with a dynamic representation of the grid through a cognitive model of operator decision-making, to identify and prove an optimal restoration path. Application of this integrated approach is illustrated on exemplar systems. Validation of the restoration is performed for one of these exemplars using commercial solvers, and comparison is made between the steps and time involved in the commercial solver, and that required by the restoration optimization in and of itself, and by the operator model in acting on the restoration optimization output. Publications and proposals developed under this work, along with a path forward for additional expansion of the work, and summary of what was achieved, are also documented.

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Operator (biology)

Representation

Black box

10.2172/2002237

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Group formation theory at multiple scales.

Casey Doyle Asmeret Naugle Michael L. Bernard Kiran Lakkaraju Robert Kittinger

10.2172/1831039

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Advanced Detection of Wellbore Failure for Safe and Secure Utilization of Subsurface Infrastructure

Edward Matteo Donald Conley Stephen Verzi Barry Roberts Casey Doyle

The main goal of this project was to create a state-of-the-art predictive capability that screens and identifies wellbores that are at the highest risk of catastrophic failure. This capability is critical to a host of subsurface applications, including gas storage, hydrocarbon extraction and storage, geothermal energy development, and waste disposal, which depend on seal integrity to meet U.S. energy demands in a safe and secure manner. In addition to the screening tool, this project also developed several other supporting capabilities to help understand fundamental processes involved in wellbore failure. This included novel experimental methods to characterize permeability and porosity evolution during compressive failure of cement, as well as methods and capabilities for understanding two-phase flow in damaged wellbore systems, and novel fracture-resistant cements made from recycled fibers.

Wellbore

10.2172/1820250

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Mining Personal Media Thresholds for Opinion Dynamics and Social Influence

2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (2018)

Casey Doyle Alex Meandzija G. Korniss Bolesław K. Szymański Derrik E. Asher

To study the detailed effects of social media consumption on personal opinion dynamics, we gather self reported survey data on the volume of different media types an individual must consume before forming or changing their opinion on a subject. We then use frequent pattern mining to analyze the data for common groupings of responses with respect to various media types, sources, and contexts. We show that in general individuals tend to perceive their behavior to be consistent across many variations in these parameters, while further detail shows various common parameter groupings that indicate response changes as well as small groups of individuals that tend to be consistently more easily swayed than the average participant.

Dynamics

Consumption

10.1109/asonam.2018.8508316

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Network Event Forecasting

Matthew Hoffman Asael Sorensen Bryan Arguello Sarah Simpson Barnett Yang

10.2172/2431793

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Social consensus and tipping points with opinion inertia

Bulletin of the American Physical Society (2015)

Casey Doyle Sameet Sreenivasan Bolesław K. Szymański G. Korniss

Abstract When opinions, behaviors or ideas diffuse within a population, some are invariably more sticky than others. The stickier the opinion, behavior or idea, the greater is an individual’s inertia to replace it with an alternative. Here we study the effect of stickiness of opinions in a two-opinion model, where individuals change their opinion only after a certain number of consecutive encounters with the alternative opinion. Assuming that one opinion has a fixed stickiness, we investigate how the critical size of the competing opinion required to tip over the entire population varies as a function of the competing opinion’s stickiness. We analyze this scenario for the case of a complete-graph topology through simulations, and through a semi-analytical approach which yields an upper bound for the critical minority size. We present analogous simulation results for the case of the Erdős–Renyi random network. Finally, we investigate the coarsening properties of sticky opinion spreading on two-dimensional lattices, and show that the presence of stickiness gives rise to an effective surface tension that causes the coarsening behavior to become curvature-driven.

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Hierarchical effects facilitate spreading processes on synthetic and empirical multilayer networks

PLoS ONE (2021)

Casey Doyle Thushara Gunda Asmeret Naugle

In this paper we consider the effects of corporate hierarchies on innovation spread across multilayer networks, modeled by an elaborated SIR framework. We show that the addition of management layers can significantly improve spreading processes on both random geometric graphs and empirical corporate networks. Additionally, we show that utilizing a more centralized working relationship network rather than a strict administrative network further increases overall innovation reach. In fact, this more centralized structure in conjunction with management layers is essential to both reaching a plurality of nodes and creating a stable adopted community in the long time horizon. Further, we show that the selection of seed nodes affects the final stability of the adopted community, and while the most influential nodes often produce the highest peak adoption, this is not always the case. In some circumstances, seeding nodes near but not in the highest positions in the graph produces larger peak adoption and more stable long-time adoption.

Time horizon

Empirical Research

Network Structure

10.1371/journal.pone.0252266

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4 The Spread of Opinions in Societies

Human factors and ergonomics (2016)

Bolesław K. Szymański Omar Ližardo Casey Doyle Panagiotis D. Karampourniotis Pramesh Singh

10.1201/9781315369587-5

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