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Articles 1 - 3 of 3
Full-Text Articles in Mechanical Engineering
2nd Annual Undergraduate Research Conference Abstract Book, University Of Missouri--Rolla
2nd Annual Undergraduate Research Conference Abstract Book, University Of Missouri--Rolla
Undergraduate Research Conference at Missouri S&T
No abstract provided.
An Internet Based Intelligent Argumentation System For Collaborative Engineering Design, Xiaoqing Frank Liu, Samir Raorane, Man Zheng, Ming-Chuan Leu
An Internet Based Intelligent Argumentation System For Collaborative Engineering Design, Xiaoqing Frank Liu, Samir Raorane, Man Zheng, Ming-Chuan Leu
Computer Science Faculty Research & Creative Works
Modern product design is a very complicated process which involves groups of designers, manufacturers, suppliers, and customer representatives. Conflicts are unavoidable in collaboration among multiple stakeholders, who have different objectives, requirements, and priorities. Unfortunately, current web-based collaborative engineering design systems do not support collaborative conflict resolution. In this paper, we will develop an intelligent computational argumentation model to enable management of a large scale argumentation network, and resolution of conflicts based on argumentation from many participants. A web-based intelligent argumentation tool is developed as a part of a web-based collaborative engineering design system based on the above model to resolve …
Neural Network-Based Output Feedback Controller For Lean Operation Of Spark Ignition Engines, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier, Jonathan B. Vance, Pingan He
Neural Network-Based Output Feedback Controller For Lean Operation Of Spark Ignition Engines, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier, Jonathan B. Vance, Pingan He
Electrical and Computer Engineering Faculty Research & Creative Works
Spark ignition (SI) engines running at very lean conditions demonstrate significant nonlinear behavior by exhibiting cycle-to-cycle dispersion of heat release even though such operation can significantly reduce NOx emissions and improve fuel efficiency by as much as 5-10%. A suite of neural network (NN) controller without and with reinforcement learning employing output feedback has shown ability to reduce the nonlinear cyclic dispersion observed under lean operating conditions. The neural network controllers consists of three NN: a) A NN observer to estimate the states of the engine such as total fuel and air; b) a second NN for generating virtual input; …