The Experts below are selected from a list of 315 Experts worldwide ranked by ideXlab platform
S.s. Banda - One of the best experts on this subject based on the ideXlab platform.
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Optimal Control of Metal Forging
Optimal Design and Control, 1995Co-Authors: Jordan M. Berg, R.j. Adams, J.c. Malas, S.s. BandaAbstract:The development of good material models, accurate nonlinear finite element codes, and computer- controlled presses makes practical the application of control techniques to metal Forging. This paper considers the problem of selecting a ram velocity profile to produce a desired microstructure, given a specified die and preform geometry and Forging Temperature. Two approaches for doing so are successfully applied to a simple but representative problem. The first is based on classical numerical optimization techniques. The second is based on inverse neural networks, and offers potential savings in critical computations. A method for choosing the Forging Temperature is also presented.
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Nonlinear optimization-based design of ram velocity profiles for isothermal Forging
IEEE Transactions on Control Systems Technology, 1995Co-Authors: Jordan M. Berg, R.j. Adams, J.c. Malas, S.s. BandaAbstract:The development of good material models, accurate nonlinear finite element codes, and computer-controlled presses make practical the application of control techniques to metal Forging. This paper considers the open-loop problem of selecting a nominal ram velocity profile to produce a desired microstructure, given a specified die and preform geometry and Forging Temperature. Two approaches for doing so are applied to a simple, but representative problem. The first is based on classical numerical optimization techniques. The second is based on inverse neural networks and offers potential savings in critical computations. Simulation studies for the two methods show good results.
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Design of ram velocity profiles for isothermal Forging via nonlinear optimization
Proceedings of 1994 American Control Conference - ACC '94, 1994Co-Authors: J.n. Berg, R.j. Adams, J.c. Malas, S.s. BandaAbstract:The development of realistic material behavior models, accurate nonlinear finite element codes, and computer-controlled presses makes practical the application of control techniques to metal Forging. This paper considers the problem of selecting a ram velocity profile to produce a desired microstructure, given a specified die and preform geometry and Forging Temperature. Two approaches for doing so are successfully applied to a simple but representative problem. The first is based on classical numerical optimization techniques. The second is based on inverse neural networks, and offers potential savings in critical computations. A method for choosing the Forging Temperature is also presented.
Yu Zhao - One of the best experts on this subject based on the ideXlab platform.
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effect of semi solid Forging Temperature on microstructure and mechanical properties of ti14 alloy
Journal of Alloys and Compounds, 2009Co-Authors: Yu Chen, Yu ZhaoAbstract:Abstract The influence of the semi-solid Forging Temperature between 1000 and 1100 °C on the microstructure and mechanical properties of a new α+Ti 2 Cu alloy was investigated. The results indicated that more Ti 2 Cu tended to precipitate on grain boundaries at a higher Forging Temperature, and finally formed a network structure after Forging at 1100 °C. The precipitation was found to be controlled by both peritectic and eutectoid reactions. The elevated Temperatures resulted in more liquid along the prior grain boundaries, which increased the peritectic precipitation in this region and formation of precipitation zones during re-solidification. In addition, the liquid served to relax the stress concentrations caused by dislocation pile-ups within the grains and provided more nucleation sites for eutectoid Ti 2 Cu precipitates on grain boundaries. Hardness and room Temperature tensile properties decreased as the Forging Temperature increased, and intergranular fractures were observed after semi-solid Forging at 1050 and 1100 °C, which is also attributed to the grain boundary network obtained by semi-solid Forging.
Yu Chen - One of the best experts on this subject based on the ideXlab platform.
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effect of semi solid Forging Temperature on microstructure and mechanical properties of ti14 alloy
Journal of Alloys and Compounds, 2009Co-Authors: Yu Chen, Yu ZhaoAbstract:Abstract The influence of the semi-solid Forging Temperature between 1000 and 1100 °C on the microstructure and mechanical properties of a new α+Ti 2 Cu alloy was investigated. The results indicated that more Ti 2 Cu tended to precipitate on grain boundaries at a higher Forging Temperature, and finally formed a network structure after Forging at 1100 °C. The precipitation was found to be controlled by both peritectic and eutectoid reactions. The elevated Temperatures resulted in more liquid along the prior grain boundaries, which increased the peritectic precipitation in this region and formation of precipitation zones during re-solidification. In addition, the liquid served to relax the stress concentrations caused by dislocation pile-ups within the grains and provided more nucleation sites for eutectoid Ti 2 Cu precipitates on grain boundaries. Hardness and room Temperature tensile properties decreased as the Forging Temperature increased, and intergranular fractures were observed after semi-solid Forging at 1050 and 1100 °C, which is also attributed to the grain boundary network obtained by semi-solid Forging.
J.c. Malas - One of the best experts on this subject based on the ideXlab platform.
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Optimal Control of Metal Forging
Optimal Design and Control, 1995Co-Authors: Jordan M. Berg, R.j. Adams, J.c. Malas, S.s. BandaAbstract:The development of good material models, accurate nonlinear finite element codes, and computer- controlled presses makes practical the application of control techniques to metal Forging. This paper considers the problem of selecting a ram velocity profile to produce a desired microstructure, given a specified die and preform geometry and Forging Temperature. Two approaches for doing so are successfully applied to a simple but representative problem. The first is based on classical numerical optimization techniques. The second is based on inverse neural networks, and offers potential savings in critical computations. A method for choosing the Forging Temperature is also presented.
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Nonlinear optimization-based design of ram velocity profiles for isothermal Forging
IEEE Transactions on Control Systems Technology, 1995Co-Authors: Jordan M. Berg, R.j. Adams, J.c. Malas, S.s. BandaAbstract:The development of good material models, accurate nonlinear finite element codes, and computer-controlled presses make practical the application of control techniques to metal Forging. This paper considers the open-loop problem of selecting a nominal ram velocity profile to produce a desired microstructure, given a specified die and preform geometry and Forging Temperature. Two approaches for doing so are applied to a simple, but representative problem. The first is based on classical numerical optimization techniques. The second is based on inverse neural networks and offers potential savings in critical computations. Simulation studies for the two methods show good results.
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Design of ram velocity profiles for isothermal Forging via nonlinear optimization
Proceedings of 1994 American Control Conference - ACC '94, 1994Co-Authors: J.n. Berg, R.j. Adams, J.c. Malas, S.s. BandaAbstract:The development of realistic material behavior models, accurate nonlinear finite element codes, and computer-controlled presses makes practical the application of control techniques to metal Forging. This paper considers the problem of selecting a ram velocity profile to produce a desired microstructure, given a specified die and preform geometry and Forging Temperature. Two approaches for doing so are successfully applied to a simple but representative problem. The first is based on classical numerical optimization techniques. The second is based on inverse neural networks, and offers potential savings in critical computations. A method for choosing the Forging Temperature is also presented.
R.j. Adams - One of the best experts on this subject based on the ideXlab platform.
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Optimal Control of Metal Forging
Optimal Design and Control, 1995Co-Authors: Jordan M. Berg, R.j. Adams, J.c. Malas, S.s. BandaAbstract:The development of good material models, accurate nonlinear finite element codes, and computer- controlled presses makes practical the application of control techniques to metal Forging. This paper considers the problem of selecting a ram velocity profile to produce a desired microstructure, given a specified die and preform geometry and Forging Temperature. Two approaches for doing so are successfully applied to a simple but representative problem. The first is based on classical numerical optimization techniques. The second is based on inverse neural networks, and offers potential savings in critical computations. A method for choosing the Forging Temperature is also presented.
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Nonlinear optimization-based design of ram velocity profiles for isothermal Forging
IEEE Transactions on Control Systems Technology, 1995Co-Authors: Jordan M. Berg, R.j. Adams, J.c. Malas, S.s. BandaAbstract:The development of good material models, accurate nonlinear finite element codes, and computer-controlled presses make practical the application of control techniques to metal Forging. This paper considers the open-loop problem of selecting a nominal ram velocity profile to produce a desired microstructure, given a specified die and preform geometry and Forging Temperature. Two approaches for doing so are applied to a simple, but representative problem. The first is based on classical numerical optimization techniques. The second is based on inverse neural networks and offers potential savings in critical computations. Simulation studies for the two methods show good results.
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Design of ram velocity profiles for isothermal Forging via nonlinear optimization
Proceedings of 1994 American Control Conference - ACC '94, 1994Co-Authors: J.n. Berg, R.j. Adams, J.c. Malas, S.s. BandaAbstract:The development of realistic material behavior models, accurate nonlinear finite element codes, and computer-controlled presses makes practical the application of control techniques to metal Forging. This paper considers the problem of selecting a ram velocity profile to produce a desired microstructure, given a specified die and preform geometry and Forging Temperature. Two approaches for doing so are successfully applied to a simple but representative problem. The first is based on classical numerical optimization techniques. The second is based on inverse neural networks, and offers potential savings in critical computations. A method for choosing the Forging Temperature is also presented.