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Full-Text Articles in Engineering
Challenges To Levulinic Acid And Humins Valuation In The Sugarcane Bagasse Biorefinery Concept, Emília Savioli Lopes, Jean Felipe Leal Silva, Elmer Ccopa Rivera, Alana Petrina Gomes, Melina Savioli Lopes, Rubens Maciel Filho, Laura Plazas Tovar
Challenges To Levulinic Acid And Humins Valuation In The Sugarcane Bagasse Biorefinery Concept, Emília Savioli Lopes, Jean Felipe Leal Silva, Elmer Ccopa Rivera, Alana Petrina Gomes, Melina Savioli Lopes, Rubens Maciel Filho, Laura Plazas Tovar
Faculty Publications
© 2020, Springer Science+Business Media, LLC, part of Springer Nature. Levulinic acid (LA) is currently one of the most promising chemicals derived from biomass. However, its large-scale production is hampered by the challenges in biomass hydrolysis and the poor selectivity due to the formation of humins (HUs). This study addresses these challenges using the biorefinery concept of biomass fractionation. A three-step process (pretreatment, delignification, and acid-catalyzed conversion) was optimized to produce LA from SCB considering the yield (YLA), efficiency (ELA), and concentration of LA (CLA) as functions of temperature, reaction time, acid concentration, and solids loading. By means of a …
Survey Of 8 Uav Set-Covering Algorithms For Terrain Photogrammetry, Joshua Hammond, Cory Vernon, Trent Okeson, Benjamin Barrett, Samuel Arce, Valerie Newell, Joseph Janson, Kevin Franke, John Hedengren
Survey Of 8 Uav Set-Covering Algorithms For Terrain Photogrammetry, Joshua Hammond, Cory Vernon, Trent Okeson, Benjamin Barrett, Samuel Arce, Valerie Newell, Joseph Janson, Kevin Franke, John Hedengren
Faculty Publications
Remote sensing with unmanned aerial vehicles (UAVs) facilitates photogrammetry for environmental and infrastructural monitoring. Models are created with less computational cost by reducing the number of photos required. Optimal camera locations for reducing the number of photos needed for structure-from-motion (SfM) are determined through eight mathematical set-covering algorithms as constrained by solve time. The algorithms examined are: traditional greedy, reverse greedy, carousel greedy (CG), linear programming, particle swarm optimization, simulated annealing, genetic, and ant colony optimization. Coverage and solve time are investigated for these algorithms. CG is the best method for choosing optimal camera locations as it balances number of …
Model Predictive Automatic Control Of Sucker Rod Pump System With Simulation Case Study, Brigham Hansen, Brandon Tolbert, Cory Vernon, John Hedengren
Model Predictive Automatic Control Of Sucker Rod Pump System With Simulation Case Study, Brigham Hansen, Brandon Tolbert, Cory Vernon, John Hedengren
Faculty Publications
This work enables accelerated fluid recovery in oil and gas reservoirs by automatically controlling fluid height and bottomhole pressure in wells. Several literature studies show significant increase in recovered oil by determining a target bottomhole pressure but rarely consider how to control to that value. This work enables those benefits by maintaining bottomhole pressure or fluid height. Moving Horizon Estimation (MHE) determines uncertain well parameters using only common surface measurements. A Model Predictive Controller (MPC) adjusts the stroking speed of a sucker rod pump to maintain fluid height. Pump boundary conditions are simulated with Mathematical Programs with Complementarity Constraints (MPCCs) …
Gekko Optimization Suite, Logan Beal, Daniel Hill, Ronald Abraham Martin, John Hedengren
Gekko Optimization Suite, Logan Beal, Daniel Hill, Ronald Abraham Martin, John Hedengren
Faculty Publications
This paper introduces GEKKO as an optimization suite for Python. GEKKO specializes in dynamic optimization problems for mixed-integer, nonlinear, and differential algebraic equations (DAE) problems. By blending the approaches of typical algebraic modeling languages (AML) and optimal control packages, GEKKO greatly facilitates the development and application of tools such as nonlinear model predicative control (NMPC), real-time optimization (RTO), moving horizon estimation (MHE), and dynamic simulation. GEKKO is an object-oriented Python library that offers model construction, analysis tools, and visualization of simulation and optimization. In a single package, GEKKO provides model reduction, an object-oriented library for data reconciliation/model predictive control, and …
Optimal Trajectory Generation Using Model Predictive Control For Aerially Towed Cable Systems, Liang Sun, John Hedengren, Randal W. Beard
Optimal Trajectory Generation Using Model Predictive Control For Aerially Towed Cable Systems, Liang Sun, John Hedengren, Randal W. Beard
Faculty Publications
This paper studies trajectory generation for a mothership that tows a drogue using a flexible cable. The contributions of this paper include model validation for the towed cable system described by a lumped mass extensible cable using flight data, and optimal trajectory generation for the towed cable system with tension constraints using model predictive control. The optimization problem is formulated using a combination of the squared error and l1-norm objective functions. Different desired circular trajectories of the towed body are used to calculate optimal trajectories for the towing vehicle subject to performance limits and wind disturbances. Trajectory generation for transitions …
Constrained Control And Optimization Of Tubular Solid Oxide Fuel Cells For Extending Cell Lifetime, Ben Spivey, John Hedengren, Thomas F. Edgar
Constrained Control And Optimization Of Tubular Solid Oxide Fuel Cells For Extending Cell Lifetime, Ben Spivey, John Hedengren, Thomas F. Edgar
Faculty Publications
Extending fuel cell lifetime is a necessary objective for reducing fuel cell power generation cost of electricity. Capital costs comprise the most significant fraction of the cost of electricity. Reducing the frequency of fuel cell replacement can be achieved by implementing a control strategy that prevents excursions into operating regions causing failure. In this paper we implement a constrained MIMO model predictive controller (MPC) to avoid the failure modes relevant for a high-temperature tubular solid oxide fuel cell (SOFC) system while performing load-following. The primary causes of failure are catalyst poisoning, fuel or air starvation, carbon deposition, and microcracking. Prior …