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Full-Text Articles in Engineering
Stochastic Modeling Of Physical Drag Coefficient – Its Impact On Orbit Prediction And Space Traffic Management, Smriti Nandan Paul, Phillip Logan Sheridan, Richard J. Licata, Piyush M. Mehta
Stochastic Modeling Of Physical Drag Coefficient – Its Impact On Orbit Prediction And Space Traffic Management, Smriti Nandan Paul, Phillip Logan Sheridan, Richard J. Licata, Piyush M. Mehta
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Ambitious satellite constellation projects by commercial entities and the ease of access to space in recent times have led to a dramatic proliferation of low-Earth space traffic. It jeopardizes space safety and long-term sustainability, necessitating better space domain awareness (SDA). Correct modeling of uncertainties in force models and orbital states, among other things, is an essential part of SDA. For objects in the low-Earth orbit (LEO) region, the uncertainty in the orbital dynamics mainly emanate from limited knowledge of the atmospheric drag-related parameters and variables. In this paper, which extends the work by Paul et al. (2021), we develop a …
Artificial Neural Network For Predicting Heat Transfer Rates In Supercritical Carbon Dioxide, Vinusha Dasarla Giri Babu
Artificial Neural Network For Predicting Heat Transfer Rates In Supercritical Carbon Dioxide, Vinusha Dasarla Giri Babu
Doctoral Dissertations and Master's Theses
Supercritical carbon dioxide as a working fluid in a closed Brayton cycle is proving to be more efficient than a conventional steam-based Rankine engine. Understanding the heat transfer properties of supercritical fluids is important for the design of a working engine cycle. The thermophysical properties of supercritical fluids tend to vary non-linearly near the pseudo-critical region. Traditionally, empirical correlations are used to calculate the heat transfer coefficient. It has been shown in the literature and within our own studies that these correlations provide inaccurate predictions near the pseudo-critical line, where heat transfer may be deteriorated or enhanced, resulting from strong …
In-Situ Infrared Thermographic Inspection For Local Powder Layer Thickness Measurement In Laser Powder Bed Fusion, Tao Liu, Cody S. Lough, Hossein Sehhat, Yi Ming Ren, Panagiotis D. Christofides, Edward C. Kinzel, Ming-Chuan Leu
In-Situ Infrared Thermographic Inspection For Local Powder Layer Thickness Measurement In Laser Powder Bed Fusion, Tao Liu, Cody S. Lough, Hossein Sehhat, Yi Ming Ren, Panagiotis D. Christofides, Edward C. Kinzel, Ming-Chuan Leu
Mechanical and Aerospace Engineering Faculty Research & Creative Works
The laser powder bed fusion (LPBF) process is strongly influenced by the characteristics of the powder layer, including its thickness and thermal transport properties. This paper investigates in-situ characterization of the powder layer using thermographic inspection. A thermal camera monitors the temperature history of the powder surface immediately after a layer of new powder is deposited by the recoating system. During this process, thermal energy diffuses from the underlying solid part, eventually raising the temperature of the above powder layer. Guided by 1D modeling of this heat-up process, experiments show how the parameterized thermal history can be correlated with powder …
Guiding A Human Follower With Interaction Forces: Implications On Physical Human-Robot Interaction, George L. Holmes, Keyri Moreno Bonnett, Amy Costa, Devin Michael Burns, Yun Seong Song
Guiding A Human Follower With Interaction Forces: Implications On Physical Human-Robot Interaction, George L. Holmes, Keyri Moreno Bonnett, Amy Costa, Devin Michael Burns, Yun Seong Song
Psychological Science Faculty Research & Creative Works
This work challenges the common assumption in physical human-robot interaction (pHRI) that the movement intention of a human user can be simply modeled with dynamic equations relating forces to movements, regardless of the user. Studies in physical human-human interaction (pHHI) suggest that interaction forces carry sophisticated information that reveals motor skills and roles in the partnership and even promotes adaptation and motor learning. In this view, simple force-displacement equations often used in pHRI studies may not be sufficient. To test this, this work measured and analyzed the interaction forces (F) between two humans as the leader guided the blindfolded follower …
Nonlinear Intelligent Model Predictive Control Of Mobile Robots, Benjamin Albia
Nonlinear Intelligent Model Predictive Control Of Mobile Robots, Benjamin Albia
Theses and Dissertations
This thesis presents a framework for an artificial neural network (ANN) model-based nonlinear model predictive control of mobile ground robots. A computer vision analysis module was first developed to extract quantitative position information from onboard camera feed with respect to a prescribed path. Various strategies were developed to construct nonlinear physical plant models for model predictive control (MPC), including the physics-based model (PBM), the ANN trained on PBM-generated data, the ANN trained on test-captured data, and the ANN initially trained on PBM-generated data and then retrained with captured data. All the models predict physical states and positions of the robot …
Fdm Machine Learning: An Investigation Into The Utility Of Neural Networks As A Predictive Analytic Tool For Go Around Decision Making, John Bro
ASA Multidisciplinary Research Symposium
FDM MACHINE LEARNING: An investigation into the utility of neural networks as a predictive analytic tool for go around decision making.
Informative Spectral Bands For Remote Green Lai Estimation In C3 And C4 Crops, Oz Kira, Anthony L. Nguy-Robertson, Timothy J. Arkebauer, Raphael Linker, Anatoly A. Gitelson
Informative Spectral Bands For Remote Green Lai Estimation In C3 And C4 Crops, Oz Kira, Anthony L. Nguy-Robertson, Timothy J. Arkebauer, Raphael Linker, Anatoly A. Gitelson
School of Natural Resources: Faculty Publications
Green leaf area index (LAI) provides insight into the productivity, physiological and phenological status of vegetation. Measurement of spectral reflectance offers a fast and nondestructive estimation of green LAI. A number of methods have been used for the estimation of green LAI; however, the specific spectral bands employed varied widely among the methods and data used. Our objectives were (i) to find informative spectral bands retained in three types of methods, neural network (NN), partial least squares (PLS) regression and vegetation indices (VI), for estimating green LAI in maize (a C4 species) and soybean (a C3 species); (ii) to assess …
A Systematic Approach For Real-Time Operator Functional State Assessment, Guangfan Zhang, Wei Wang, Aaron Pepe, Roger Xu, Tom Schnell, Nick Anderson, Dean Heitkamp, Jiang Li, Feng Li, Frederick Mckenzie
A Systematic Approach For Real-Time Operator Functional State Assessment, Guangfan Zhang, Wei Wang, Aaron Pepe, Roger Xu, Tom Schnell, Nick Anderson, Dean Heitkamp, Jiang Li, Feng Li, Frederick Mckenzie
Electrical & Computer Engineering Faculty Publications
A task overload condition often leads to high stress for an operator, causing performance degradation and possibly disastrous consequences. Just as dangerous, with automated flight systems, an operator may experience a task underload condition (during the en-route flight phase, for example), becoming easily bored and finding it difficult to maintain sustained attention. When an unexpected event occurs, either internal or external to the automated system, the disengaged operator may neglect, misunderstand, or respond slowly/inappropriately to the situation. In this paper, we discuss an approach for Operator Functional State (OFS) monitoring in a typical aviation environment. A systematic ground truth finding …
State Dependent Riccati Equation Based Spacecraft Attitude Control, Ming Xin, S. N. Balakrishnan
State Dependent Riccati Equation Based Spacecraft Attitude Control, Ming Xin, S. N. Balakrishnan
Mechanical and Aerospace Engineering Faculty Research & Creative Works
We present a new optimal control approach to the robust spacecraft attitude control in the framework of State Dependent Riccati Equation (SDRE) technique. To treat this highly nonlinear control system, we formulate it as a nonlinear optimal regulator problem. SDRE technique was well applied to this class of attitude control problem. We also synthesize a neural network based extra controller to achieve the robustness in the presence of the parameter uncertainties. A general spacecraft attitude regulation problem was studied to show the effectiveness of SDRE approach and robust extra control design. © 2002. Published by the American Institute of Aeronautics …