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Full-Text Articles in Mechanical Engineering
Comparative Analysis Of Injection Of Pyrolysis Oil From Plastics And Gasoline Into The Engine Cylinder And Atomization By A Direct High-Pressure Injector, Magdalena Szwaja, Jeffrey Naber, David Shonnard, Daniel G. Kulas, Ali Zolghadr, Stanislaw Szwaja
Comparative Analysis Of Injection Of Pyrolysis Oil From Plastics And Gasoline Into The Engine Cylinder And Atomization By A Direct High-Pressure Injector, Magdalena Szwaja, Jeffrey Naber, David Shonnard, Daniel G. Kulas, Ali Zolghadr, Stanislaw Szwaja
Michigan Tech Publications
The article discusses the results of experimental studies on the course of pyrolysis oil injection through the high-pressure injector of a direct-injection engine. The pyrolysis oil used for the tests was derived from waste plastics (mainly high-density polyethylene—HDPE). This oil was then distilled. The article also describes the production technology of this pyrolysis oil on a laboratory scale. It presents the results of the chemical composition of the raw pyrolysis oil and the oil after the distillation process using GC-MS analysis. Fuel injection tests were carried out for the distilled pyrolysis oil and a 91 RON gasoline in order to …
Accurate Predictions Of Thermoset Resin Glass Transition Temperatures From All-Atom Molecular Dynamics Simulation, Gregory Odegard, Sagar Patil, Prashik Gaikwad, Prathamesh Deshpande, Aaron Krieg, Sagar P. Shah, Aspen Reyes, Tarik Dickens, Julia A. King, Marianna Maiaru
Accurate Predictions Of Thermoset Resin Glass Transition Temperatures From All-Atom Molecular Dynamics Simulation, Gregory Odegard, Sagar Patil, Prashik Gaikwad, Prathamesh Deshpande, Aaron Krieg, Sagar P. Shah, Aspen Reyes, Tarik Dickens, Julia A. King, Marianna Maiaru
Michigan Tech Publications
To enable the design and development of the next generation of high-performance composite materials, there is a need to establish improved computational simulation protocols for accurate and efficient prediction of physical, mechanical, and thermal properties of thermoset resins. This is especially true for the prediction of glass transition temperature (Tg), as there are many discrepancies in the literature regarding simulation protocols and the use of cooling rate correction factors for predicting values using molecular dynamics (MD) simulation. The objectives of this study are to demonstrate accurate prediction the Tg with MD without the use of cooling rate correction factors and …
Mechanical Properties And Characterization Of Epoxy Composites Containing Highly Entangled As-Received And Acid Treated Carbon Nanotubes, Aaron Krieg, Julia A. King, Gregory M. Odegard, Timothy Leftwich, Leif K. Odegard, Paul D. Fraley, Ibrahim Miskioglu, Claire Jolowsky, Matthew Lundblad, Jin Gyu Park, Richard Liang
Mechanical Properties And Characterization Of Epoxy Composites Containing Highly Entangled As-Received And Acid Treated Carbon Nanotubes, Aaron Krieg, Julia A. King, Gregory M. Odegard, Timothy Leftwich, Leif K. Odegard, Paul D. Fraley, Ibrahim Miskioglu, Claire Jolowsky, Matthew Lundblad, Jin Gyu Park, Richard Liang
Michigan Tech Publications
Huntsman–Merrimack MIRALON® carbon nanotubes (CNTs) are a novel, highly entan-gled, commercially available, and scalable format of nanotubes. As-received and acid-treated CNTs were added to aerospace grade epoxy (CYCOM® 977-3), and the composites were characterized. The epoxy resin is expected to infiltrate the network of the CNTs and could improve mechanical properties. Epoxy composites were tested for flexural and viscoelastic properties and the as-re-ceived and acid treated CNTs were characterized using Field-Emission Scanning and Transmission Electron Microscopy, X-Ray Photoelectron Spectroscopy, and Thermogravimetric Analysis. Composites containing 0.4 wt% as-received CNTs showed an increase in flexural strength, from 136.9 MPa for neat epoxy …
Early-Stage Gas Identification Using Convolutional Long Short-Term Neural Network With Sensor Array Time Series Data, Kai Zhou, Yixin Liu
Early-Stage Gas Identification Using Convolutional Long Short-Term Neural Network With Sensor Array Time Series Data, Kai Zhou, Yixin Liu
Michigan Tech Publications
Gas identification/classification through pattern recognition techniques based on gas sensor arrays often requires the equilibrium responses or the full traces of time-series data of the sensor array. Leveraging upon the diverse gas sensing kinetics behaviors measured via the sensor array, a computational intelligence-based meta-model is proposed to automatically conduct the feature extraction and subsequent gas identification using time-series data during the transitional phase before reaching equilibrium. The time-series data contains implicit temporal dependency/correlation that is worth being characterized to enhance the gas identification performance and reliability. In this context, a tailored approach so-called convolutional long short-term memory (CLSTM) neural network …