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Full-Text Articles in Engineering

Optimal Sampling Paths For Autonomous Vehicles In Uncertain Ocean Flows, Andrew J. De Stefan Aug 2019

Optimal Sampling Paths For Autonomous Vehicles In Uncertain Ocean Flows, Andrew J. De Stefan

Dissertations

Despite an extensive history of oceanic observation, researchers have only begun to build a complete picture of oceanic currents. Sparsity of instrumentation has created the need to maximize the information extracted from every source of data in building this picture. Within the last few decades, autonomous vehicles, or AVs, have been employed as tools to aid in this research initiative. Unmanned and self-propelled, AVs are capable of spending weeks, if not months, exploring and monitoring the oceans. However, the quality of data acquired by these vehicles is highly dependent on the paths along which they collect their observational data. The ...


Principal Component Neural Networks For Modeling, Prediction, And Optimization Of Hot Mix Asphalt Dynamics Modulus, Parnian Ghasemi, Mohamad Aslani, Derrick K. Rollins, R. Christopher Williams Aug 2019

Principal Component Neural Networks For Modeling, Prediction, And Optimization Of Hot Mix Asphalt Dynamics Modulus, Parnian Ghasemi, Mohamad Aslani, Derrick K. Rollins, R. Christopher Williams

Derrick K Rollins, Sr.

The dynamic modulus of hot mix asphalt (HMA) is a fundamental material property that defines the stress-strain relationship based on viscoelastic principles and is a function of HMA properties, loading rate, and temperature. Because of the large number of efficacious predictors (factors) and their nonlinear interrelationships, developing predictive models for dynamic modulus can be a challenging task. In this research, results obtained from a series of laboratory tests including mixture dynamic modulus, aggregate gradation, dynamic shear rheometer (on asphalt binder), and mixture volumetric are used to create a database. The created database is used to develop a model for estimating ...


Principal Component Neural Networks For Modeling, Prediction, And Optimization Of Hot Mix Asphalt Dynamics Modulus, Parnian Ghasemi, Mohamad Aslani, Derrick K. Rollins, R. Christopher Williams Aug 2019

Principal Component Neural Networks For Modeling, Prediction, And Optimization Of Hot Mix Asphalt Dynamics Modulus, Parnian Ghasemi, Mohamad Aslani, Derrick K. Rollins, R. Christopher Williams

Chemical and Biological Engineering Publications

The dynamic modulus of hot mix asphalt (HMA) is a fundamental material property that defines the stress-strain relationship based on viscoelastic principles and is a function of HMA properties, loading rate, and temperature. Because of the large number of efficacious predictors (factors) and their nonlinear interrelationships, developing predictive models for dynamic modulus can be a challenging task. In this research, results obtained from a series of laboratory tests including mixture dynamic modulus, aggregate gradation, dynamic shear rheometer (on asphalt binder), and mixture volumetric are used to create a database. The created database is used to develop a model for estimating ...


Two-On-One Pursuit With A Non-Zero Capture Radius, Patrick J. Wasz Mar 2019

Two-On-One Pursuit With A Non-Zero Capture Radius, Patrick J. Wasz

Theses and Dissertations

In this paper, we revisit the "Two Cutters and Fugitive Ship" differential game that was addressed by Isaacs, but move away from point capture. We consider a two-on-one pursuit-evasion differential game with simple motion and pursuers endowed with circular capture sets of radius l > 0. The regions in the state space where only one pursuer effects the capture and the region in the state space where both pursuers cooperatively and isochronously capture the evader are characterized, thus solving the Game of Kind. Concerning the Game of Degree, the algorithm for the synthesis of the optimal state feedback strategies of the ...


A Data-Driven Toolchain For The Operational Performance Analysis And Optimization Of Buildings, Anthony Reed Florita Jan 2019

A Data-Driven Toolchain For The Operational Performance Analysis And Optimization Of Buildings, Anthony Reed Florita

Civil Engineering Graduate Theses & Dissertations

Automation has proven indispensable to advancing human endeavors. Within the built environment its evolution and sophistication are on the cusp of moving beyond automatic control into automated prediction and diagnosis. A data-driven toolchain is developed so human efforts can be focused on high-value concerns. The research examines smart buildings as a cyberphysical construct and places the Bayesian perspective as paramount. Prior knowledge is leveraged through common building energy modeling and simulation tools, which are utilized and extended. An iterative, three-step process is developed to 1) classify building energy performance scenarios, 2) forecast dynamics over a planning horizon of interest, and ...


Applications Of Fixed Point Theory To Distributed Optimization, Robust Convex Optimization, And Stability Of Stochastic Systems, Seyyed Shaho Alaviani Jan 2019

Applications Of Fixed Point Theory To Distributed Optimization, Robust Convex Optimization, And Stability Of Stochastic Systems, Seyyed Shaho Alaviani

Graduate Theses and Dissertations

Large-scale multi-agent networked systems are becoming more and more popular due to applications in robotics, machine learning, and signal processing. Although distributed algorithms have been proposed for efficient computations rather than centralized computations for large data optimization, existing algorithms are still suffering from some disadvantages such as distribution dependency or B-connectivity assumption of switching communication graphs. This study applies fixed point theory to analyze distributed optimization problems and to overcome existing difficulties such as distribution dependency or B-connectivity assumption of switching communication graphs. In this study, a new mathematical terminology and a new mathematical optimization problem are defined. It is ...