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Articles 1 - 11 of 11
Full-Text Articles in Engineering
Investment Casting With Ice Patterns Made By Rapid Freeze Prototyping, Wei Zhang, Ming-Chuan Leu, Chao Feng, Rong Ren, Renjie Zhang, Qingping Lu, Jubu Jiang, Yongnian Yan
Investment Casting With Ice Patterns Made By Rapid Freeze Prototyping, Wei Zhang, Ming-Chuan Leu, Chao Feng, Rong Ren, Renjie Zhang, Qingping Lu, Jubu Jiang, Yongnian Yan
Mechanical and Aerospace Engineering Faculty Research & Creative Works
One of the most promising applications of rapid freeze prototyping (RFP) is making metal parts by investment casting with the built ice parts. The integration of RFP and investment casting allows fast creation of complex net-shape metal parts directly from their CAD models. The advantages of doing so include no part geometric complexity limitation, no experience of parting line design and assembling needed, clean and low-cost of process operation, and good performance. In this paper, we will present our recent study on binder selection, slurry making, ceramic shell making, and the casting results of the metal parts.
Study On Water Deposit In Rapid Freeze Prototyping Process, Guanghua Sui, Weihan Zhang, Ming-Chuan Leu
Study On Water Deposit In Rapid Freeze Prototyping Process, Guanghua Sui, Weihan Zhang, Ming-Chuan Leu
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Rapid Freeze Prototyping (RFP) builds a three-dimensional ice part according to its CAD model by depositing and rapidly freezing water in a layer-by-layer manner. To study the water deposit in RFP, assumptions are made based on the deformation of water droplet impinging on a flat substrate, the thermal analysis of a new layer of water deposit, and the characteristics of solidification of a water drop. The equations governing the cross-sectional profile of the water deposit are then established. A model of water deposit is proposed by simplifying the equations under our experimental conditions in RFP. By using this model, equations …
Determination And Improvement Of Building Speed In Rapid Freeze Prototyping, Wei Zhang, Guanghua Sui, Ming-Chuan Leu
Determination And Improvement Of Building Speed In Rapid Freeze Prototyping, Wei Zhang, Guanghua Sui, Ming-Chuan Leu
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Rapid freeze prototyping (RFP) is a solid freeform fabrication process that builds an ice part by rapidly freezing water in a layer by layer manner. One advantage of this process is the ability to build ice parts faster than other SFF processes. The factors that affect the speed of contour building and interior filling in RFP are identified. The influence of these factors is analyzed through heat transfer and material flow analyses. A model based on heat transfer analysis is proposed to determine the maximum achievable speed of contour building under stable conditions. Experiments are conducted to validate the performance …
Laser Additive Manufacturing Process Planning And Automation, Jun Zhang, Jianzhong Ruan, Frank W. Liou
Laser Additive Manufacturing Process Planning And Automation, Jun Zhang, Jianzhong Ruan, Frank W. Liou
Mechanical and Aerospace Engineering Faculty Research & Creative Works
This paper presents a Laser Additive Manufacturing Process Planning (LAMPP) being developed at the University of Missouri-Rolla. The off-line planning recognizes difficult-to-build features from an STL file, selects optimal part orientation and building directions based on the skeleton information of the object geometry, and optimizes the sub-process sequences for deposition and machining. During the optimization of the subpart building processes, collaboration between the deposition process planner and the machining process planner is needed to check the deposition availability and machinability. As a result, tool paths for both the laser head and the machining head are automatically generated.
Process Modeling, Monitoring And Control Of Laser Metal Forming, N. Munjuluri, Sanjeev Agarwal, Frank W. Liou
Process Modeling, Monitoring And Control Of Laser Metal Forming, N. Munjuluri, Sanjeev Agarwal, Frank W. Liou
Electrical and Computer Engineering Faculty Research & Creative Works
Laser Metal Forming (LMF) process is one of the prominent Rapid Prototyping (RP) process that can be used to develop functional and fully dense metal parts. This paper addresses process modeling, monitoring and control of a laser metal forming system currently under development at Laser Aided Manufacturing Processes (LAMP) laboratory at University of Missouri--Rolla. This LMF system is based on a 2.5kW Nd:YAG laser as energy source and integrates five axis metal deposition and five axis machining. The current paper is aimed at characterization of effects of operating parameters such as traverse speed, mass flow-rate and laser power on the …
High-Temperature Characteristics Of 1.3 Μm Ingaasn:Sb/Gaas Multiple-Quantum-Well Lasers Grown By Molecular-Beam Epitaxy, Xiaodong Yang, J. B. Heroux, M. J. Jurkovic, W. I. Wang
High-Temperature Characteristics Of 1.3 Μm Ingaasn:Sb/Gaas Multiple-Quantum-Well Lasers Grown By Molecular-Beam Epitaxy, Xiaodong Yang, J. B. Heroux, M. J. Jurkovic, W. I. Wang
Mechanical and Aerospace Engineering Faculty Research & Creative Works
1.3 μm InGaAsN:Sb/GaAs multiple-quantum-well laser diodes have been grown by solid-source molecular-beam epitaxy using Sb as a surfactant. A low threshold of 1.1 kA/cm² was achieved for broad-area laser diodes under pulsed operation at room temperature. High-temperature device characterization revealed characteristic temperatures (T₀) of 92 and 54 K for operating temperatures below and above 75°C, respectively, as well as a lasing-wavelength temperature dependence of 0.36 nm/°C.
Lifecycle Analysis For Environmentally Conscious Solid Freeform Manufacturing, Yanchun Luo, Ji Zhiming, Ming-Chuan Leu, R. J. Caudill
Lifecycle Analysis For Environmentally Conscious Solid Freeform Manufacturing, Yanchun Luo, Ji Zhiming, Ming-Chuan Leu, R. J. Caudill
Mechanical and Aerospace Engineering Faculty Research & Creative Works
A lifecycle based process model for analyzing the environmental performance of SFM processes and SFM based rapid tooling processes is presented in this paper. The process environmental performance assessment model considers material, energy and disposal scenarios. The material use, process parameters (e.g. scanning speed) and power use can affect the environmental consequence of a process when material resource, energy, human health and environmental damage are taken into account. The presented method is applied to the SLA process and two SLA based rapid tooling processes. The method can be used to compare different rapid prototyping (RP) and RT processes in terms …
A Neural Network Methodology For Path Planning And Coordination Of Car-Like Robots, Prasanna Venkatesan Sadagopan
A Neural Network Methodology For Path Planning And Coordination Of Car-Like Robots, Prasanna Venkatesan Sadagopan
Masters Theses
"A car-like indoor mobile robot is a kinematically constrained robot that can be modeled as a 2D object translating and rotating in the horizontal plane among well- defined obstacles. The kinematic constraints impose that the linear velocity of the robot is along its main axis (no sideways motion is possible) and restrict the range of admissible values for the steering angle. The goal of this study is to combine neural network techniques and motion planning algorithms to create a new methodology for coordinating the motion of multiple car-like robots avoiding collision with polygonal obstacles in a work environment. An incremental …
Convergence Analysis Of Adaptive Critic Based Optimal Control, S. N. Balakrishnan, Xin Liu
Convergence Analysis Of Adaptive Critic Based Optimal Control, S. N. Balakrishnan, Xin Liu
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Adaptive critic based neural networks have been found to be powerful tools in solving various optimal control problems. The adaptive critic approach consists of two neural networks which output the control values and the Lagrangian multipliers associated with optimal control. These networks are trained successively and when the outputs of the two networks are mutually consistent and satisfy the differential constraints, the controller network output produces optimal control. In this paper, we analyze the mechanics of convergence of the network solutions. We establish the necessary conditions for the network solutions to converge and show that the converged solution is optimal.
Infinite Time Optimal Neuro Control For Distributed Parameter Systems, S. N. Balakrishnan, Radhakant Padhi
Infinite Time Optimal Neuro Control For Distributed Parameter Systems, S. N. Balakrishnan, Radhakant Padhi
Mechanical and Aerospace Engineering Faculty Research & Creative Works
The conventional dynamic programming methodology for the solution of optimal control, despite having many desirable features, is severely restricted by its computational requirements. However, in recent times, an alternate formulation, known as the adaptive-critic synthesis, has given it a new perspective. In this paper, we have attempted to use the philosophy of adaptive-critic design to the optimal control of distributed parameter systems. An important contribution of this study is the derivation of the necessary conditions of optimality for distributed parameter systems, described in discrete domain, following the principle of approximate dynamic programming. Then the derived necessary conditions of optimality are …
Robust Adaptive Critic Based Neurocontrollers For Systems With Input Uncertainties, S. N. Balakrishnan, Zhongwu Huang
Robust Adaptive Critic Based Neurocontrollers For Systems With Input Uncertainties, S. N. Balakrishnan, Zhongwu Huang
Mechanical and Aerospace Engineering Faculty Research & Creative Works
A two-neural network approach to solving optimal control problems is described in this study. This approach called the adaptive critic method consists of two neural networks: one is called the supervisor or critic, and the other is called an action network or controller. The inputs to both these networks are the current states of the system to be controlled. Each network is trained through an output of the other network and the conditions for optimal control. When their outputs are mutually consistent, the controller network output is optimal. The optimality is limited to the underlying model. Hence, we develop a …