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Articles 1 - 6 of 6
Full-Text Articles in Engineering
S-Net: A Multiple Cross Aggregation Convolutional Architecture For Automatic Segmentation Of Small/Thin Structures For Cardiovascular Applications, Nan Mu, Zonghan Lyu, Mostafa Rezaeitaleshmahalleh, Cassie Bonifas, Jordan Gosnell, Marcus Haw, Joseph Vettukattil, Jingfeng Jiang
S-Net: A Multiple Cross Aggregation Convolutional Architecture For Automatic Segmentation Of Small/Thin Structures For Cardiovascular Applications, Nan Mu, Zonghan Lyu, Mostafa Rezaeitaleshmahalleh, Cassie Bonifas, Jordan Gosnell, Marcus Haw, Joseph Vettukattil, Jingfeng Jiang
Michigan Tech Publications, Part 2
With the success of U-Net or its variants in automatic medical image segmentation, building a fully convolutional network (FCN) based on an encoder-decoder structure has become an effective end-to-end learning approach. However, the intrinsic property of FCNs is that as the encoder deepens, higher-level features are learned, and the receptive field size of the network increases, which results in unsatisfactory performance for detecting low-level small/thin structures such as atrial walls and small arteries. To address this issue, we propose to keep the different encoding layer features at their original sizes to constrain the receptive field from increasing as the network …
Evolution Of Glassy Carbon Derived From Pyrolysis Of Furan Resin, Josh Kemppainen, Ivan Gallegos, Aaron Krieg, Jacob R. Gissinger, Kristopher E. Wise, Margaret Kowalik, Julia A. King, S. Gowtham, Adri Van Duin, Gregory Odegard
Evolution Of Glassy Carbon Derived From Pyrolysis Of Furan Resin, Josh Kemppainen, Ivan Gallegos, Aaron Krieg, Jacob R. Gissinger, Kristopher E. Wise, Margaret Kowalik, Julia A. King, S. Gowtham, Adri Van Duin, Gregory Odegard
Michigan Tech Publications, Part 2
Glassy carbon (GC) material derived from pyrolyzed furan resin was modeled by using reactive molecular dynamics (MD) simulations. The MD polymerization simulation protocols to cure the furan resin precursor material are validated via comparison of the predicted density and Young's modulus with experimental values. The MD pyrolysis simulations protocols to pyrolyze the furan resin precursor is validated by comparison of calculated density, Young's modulus, carbon content, sp carbon content, the in-plane crystallite size, out-of-plane crystallite stacking height, and interplanar crystallite spacing with experimental results from the literature for furan resin derived GC. The modeling methodology established in this work can …
Establishing Physical And Chemical Mechanisms Of Polymerization And Pyrolysis Of Phenolic Resins For Carbon-Carbon Composites, Ivan Gallegos, Josh Kemppainen, Jacob R. Gissinger, Malgorzata Kowalik, Adri Van Duin, Kristopher E. Wise, S. Gowtham, Gregory Odegard
Establishing Physical And Chemical Mechanisms Of Polymerization And Pyrolysis Of Phenolic Resins For Carbon-Carbon Composites, Ivan Gallegos, Josh Kemppainen, Jacob R. Gissinger, Malgorzata Kowalik, Adri Van Duin, Kristopher E. Wise, S. Gowtham, Gregory Odegard
Michigan Tech Publications, Part 2
The complex structural and chemical changes that occur during polymerization and pyrolysis critically affect material properties but are difficult to characterize in situ. This work presents a novel, experimentally validated methodology for modeling the complete polymerization and pyrolysis processes for phenolic resin using reactive molecular dynamics. The polymerization simulations produced polymerized structures with mass densities of 1.24 ± 0.01 g/cm3 and Young's moduli of 3.50 ± 0.64 GPa, which are in good agreement with experimental values. The structural properties of the subsequently pyrolyzed structures were also found to be in good agreement with experimental X-ray data for the phenolic-derived carbon …
Reconstructing 42 Years (1979–2020) Of Great Lakes Surface Temperature Through A Deep Learning Approach, Miraj Kayastha, Tao Liu, Daniel Titze, Timothy C. Havens, Chenfu Huang, Pengfei Xue
Reconstructing 42 Years (1979–2020) Of Great Lakes Surface Temperature Through A Deep Learning Approach, Miraj Kayastha, Tao Liu, Daniel Titze, Timothy C. Havens, Chenfu Huang, Pengfei Xue
Michigan Tech Publications, Part 2
Accurate estimates for the lake surface temperature (LST) of the Great Lakes are critical to understanding the regional climate. Dedicated lake models of various complexity have been used to simulate LST but they suffer from noticeable biases and can be computationally expensive. Additionally, the available historical LST datasets are limited by either short temporal coverage (<30 >years) or lower spatial resolution (0.25° × 0.25°). Therefore, in this study, we employed a deep learning model based on Long Short-Term Memory (LSTM) neural networks to produce a daily LST dataset for the Great Lakes that spans an unparalleled 42 years (1979–2020) at …
Coordinating Tethered Autonomous Underwater Vehicles Towards Entanglement-Free Navigation, Abhishek Patil, Myoungkuk Park, Jungyun Bae
Coordinating Tethered Autonomous Underwater Vehicles Towards Entanglement-Free Navigation, Abhishek Patil, Myoungkuk Park, Jungyun Bae
Michigan Tech Publications
This paper proposes an algorithm that provides operational strategies for multiple tethered autonomous underwater vehicle (T-AUV) systems for entanglement-free navigation. T-AUVs can perform underwater tasks under reliable communication and power supply, which is the most substantial benefit of their operation. Thus, if one can overcome the entanglement issues while utilizing multiple tethered vehicles, the potential applications of the system increase including ecosystem exploration, infrastructure inspection, maintenance, search and rescue, underwater construction, and surveillance. In this study, we focus on developing strategies for task allocation, path planning, and scheduling that ensure entanglement-free operations while considering workload balancing among the vehicles. We …
Neuroevolution Application To Collaborative And Heuristics-Based Connected And Autonomous Vehicle Cohort Simulation At Uncontrolled Intersection, Frederic Jacquelin, Jungyun Bae, Bo Chen, Darrell Robinette
Neuroevolution Application To Collaborative And Heuristics-Based Connected And Autonomous Vehicle Cohort Simulation At Uncontrolled Intersection, Frederic Jacquelin, Jungyun Bae, Bo Chen, Darrell Robinette
Michigan Tech Publications, Part 2
Artificial intelligence is gaining tremendous attractiveness and showing great success in solving various problems, such as simplifying optimal control derivation. This work focuses on the application of Neuroevolution to the control of Connected and Autonomous Vehicle (CAV) cohorts operating at uncontrolled intersections. The proposed method implementation’s simplicity, thanks to the inclusion of heuristics and effective real-time performance are demonstrated. The resulting architecture achieves nearly ideal operating conditions in keeping the average speeds close to the speed limit. It achieves twice as high mean speed throughput as a controlled intersection, hence enabling lower travel time and mitigating energy inefficiencies from stop-and-go …