Recently, machining has been exploited as a means for producing ultra-fine grained (UFG) and nano... more Recently, machining has been exploited as a means for producing ultra-fine grained (UFG) and nanocrystalline microstructures for various metal materials, such as aluminum alloys, copper, stainless steel, titanium and nickel-based super alloys, etc. However, no predictive, analytical or numerical work has ever been presented to quantitatively predict the change of grain sizes during machining. In this paper, a dislocation density-based viscoplastic model is adapted for modeling the grain size refinement mechanism during machining by means of a finite element based numerical framework. A novel Coupled Eulerian-Lagrangian (CEL) finite element model embedded with the dislocation density subroutine is developed to model the severe plastic deformation and grain refinement during a steady-state cutting process. The orthogonal cutting tests of a commercially pure titanium (CP Ti) material are simulated in order to assess the validity of the numerical solution through comparison with experiments. The dislocation density-based material model is calibrated to reproduce the observed material constitutive mechanical behavior of CP Ti under various strains, strain rates and temperatures in the cutting process. It is shown that the developed model captures the essential features of the material mechanical behavior and predicts a grain size of 100-160 nm in the chips of CP Ti at a cutting speed of 10 mm/s.
A novel approach to build a Takagi-Sugeno (T-S) fuzzy model of an unknown nonlinear system from e... more A novel approach to build a Takagi-Sugeno (T-S) fuzzy model of an unknown nonlinear system from experimental data is presented in the paper. The neuro-fuzzy models or, more specifically, fuzzy basis function networks (FBFNs) are trained from input-output data to approximate the nonlinear systems for which analytical mathematical models are not available. Then, the T-S fuzzy models are derived from the direct linearization of the neuro-fuzzy models. The operating points for linearization are chosen using the evolutionary strategy to minimize the global approximation error so that the T-S fuzzy models can closely approximate the original unknown nonlinear system with a reduced number of linearizations. Based on T-S fuzzy models, optimal controllers are designed and implemented for a nonlinear two-link flexible joint robot, which demonstrates the possibility of implementing the well-established model-based optimal control method onto unknown nonlinear dynamic systems.
The International Journal of Advanced Manufacturing Technology, Feb 18, 2022
Using an efficient hybrid Cellular Automata/Phase Field (CA-PF) dendrite growth modeling in combi... more Using an efficient hybrid Cellular Automata/Phase Field (CA-PF) dendrite growth modeling in combination with a solid phase transformation model, microstructure evolution and solid-phase transformation were predicted during laser direct deposition (LDD) of H13 tool steel powder across multiple tracks and layers. Temperature and surface geometry data were provided by a comprehensive physics-based laser deposition model. The computational efficiency of the CA-PF model allows for simulating domains large enough to capture dendrite growth across an entire molten pool and into neighboring LDD tracks. The microstructure of the target track is strongly affected by heat from neighboring tracks including re-melting and re-solidification, and martensite tempering. Dendrite size and growth direction across the entire fusion zone, as well as predicted hardness values, are found to be in good agreement with experimental results.
Journal of Manufacturing Science and Engineering-transactions of The Asme, Jul 5, 2018
Previous investigations on "double-pulse" nanosecond (ns) laser drilling reported in the literatu... more Previous investigations on "double-pulse" nanosecond (ns) laser drilling reported in the literature typically utilize double pulses of equal or similar pulse energies. In this paper, "double-pulse" ns laser drilling using double pulses with energies differing by more than ten times has been studied, where both postprocess workpiece characterizations and in situ time-resolved shadowgraph imaging observations have been performed. A very interesting physical phenomenon has been discovered under the studied conditions: the "double-pulse" ns laser ablation process, where the low-energy pulse precedes the highenergy pulse (called "low-high double-pulse" laser ablation) by a suitable amount of time, can produce significantly higher ablation rates than "high-low double-pulse" or "single-pulse" laser ablation under a similar laser energy input. In particular, "low-high double-pulse" laser ablation at a suitable interpulse separation time can drill through a $0.93 mm thick aluminum 7075 workpiece in less than 200 pulse pairs, while "high-low double-pulse" or "single-pulse" laser ablation cannot drill through the workpiece even using 1000 pulse pairs or pulses, respectively. This indicates that "low-high doublepulse" laser ablation has led to a significantly enhanced average ablation rate that is more than five times those for "single-pulse" or "high-low double-pulse" laser ablation. The fundamental physical mechanism for the ablation rate enhancement has been discussed, and a hypothesized explanation has been given.
Molecular dynamics (MD) simulations were carried out to study the bulk polycrystalline properties... more Molecular dynamics (MD) simulations were carried out to study the bulk polycrystalline properties of NiTi. Thermally driven phase transitions of NiTi between martensite and austenitewere simulated using single crystalline simulation domains. With external stress boundary conditions, MD simulation successfully predicted experimentally observed phase transformation temperatures of bulk polycrystalline. Elastic characteristics of NiTi martensite were simulated using polycrystalline simulation domains that consist of realistic disorientations and grain boundary structures. The existence of grain disorientation and grain boundary lowered the potential energy of the simulation domain, which led to more realistic elastic modulus prediction. Analysis of simulation domains that predicted realistic bulk polycrystalline properties showed that the major difference between single crystalline and polycrystalline structures is atomic stress distribution.
Powder capture efficiency is indicative of the amount of material that is added to the substrate ... more Powder capture efficiency is indicative of the amount of material that is added to the substrate during laser additive manufacturing processes, and thus, being able to predict capture efficiency provides capability of predictive modeling during such processes. The focus of the work presented in this paper is to create a numerical model to understand particle trajectories and velocities, which in turn allows for the prediction of capture efficiency. To validate the numerical model, particle tracking velocimetry experiments at two powder flow rates were conducted on free stream particle spray to track individual particles such that particle concentration and velocity fields could be obtained. Results from the free stream comparison showed good agreement to the trends observed in experimental data and were subsequently used in a direct laser deposition simulation to assess capture efficiency and temperature profile at steady-state. The simulation was validated against a single track deposition experiment and showed proper correlation of the free surface geometry, molten pool boundary, heat affected zone boundary and capture efficiency.
Molecular dynamics (MD) simulations were carried out to study the bulk polycrystalline properties... more Molecular dynamics (MD) simulations were carried out to study the bulk polycrystalline properties of NiTi. Thermally driven phase transitions of NiTi between martensite and austenitewere simulated using single crystalline simulation domains. With external stress boundary conditions, MD simulation successfully predicted experimentally observed phase transformation temperatures of bulk polycrystalline. Elastic characteristics of NiTi martensite were simulated using polycrystalline simulation domains that consist of realistic disorientations and grain boundary structures. The existence of grain disorientation and grain boundary lowered the potential energy of the simulation domain, which led to more realistic elastic modulus prediction. Analysis of simulation domains that predicted realistic bulk polycrystalline properties showed that the major difference between single crystalline and polycrystalline structures is atomic stress distribution.
Under the concept of "Industry 4.0", production processes will be pushed to be increasingly inter... more Under the concept of "Industry 4.0", production processes will be pushed to be increasingly interconnected, information based on a real time basis and, necessarily, much more efficient. In this context, capacity optimization goes beyond the traditional aim of capacity maximization, contributing also for organization's profitability and value. Indeed, lean management and continuous improvement approaches suggest capacity optimization instead of maximization. The study of capacity optimization and costing models is an important research topic that deserves contributions from both the practical and theoretical perspectives. This paper presents and discusses a mathematical model for capacity management based on different costing models (ABC and TDABC). A generic model has been developed and it was used to analyze idle capacity and to design strategies towards the maximization of organization's value. The trade-off capacity maximization vs operational efficiency is highlighted and it is shown that capacity optimization might hide operational inefficiency.
Human Factors and Ergonomics in Manufacturing & Service Industries, 2013
The purpose of this article is to review the key emerging innovations in laser and photonics syst... more The purpose of this article is to review the key emerging innovations in laser and photonics systems as well as their design and integration, focusing on challenges and opportunities for solutions of societal challenges. Developments, their significance, and frontier challenges are explained in advanced manufacturing, biomedicine and healthcare, and communication. Systems, networks, and integration issues and challenges are then discussed, and an integration framework for networking laser-and photonic-based services and products is proposed. The article concludes with implications and an agenda for education, research and development, and policy needs, with a focus on human, society, science, and technology integration.
The International Journal of Advanced Manufacturing Technology, 2022
Using an efficient hybrid Cellular Automata/Phase Field (CA-PF) dendrite growth modeling in combi... more Using an efficient hybrid Cellular Automata/Phase Field (CA-PF) dendrite growth modeling in combination with a solid phase transformation model, microstructure evolution and solid-phase transformation were predicted during laser direct deposition (LDD) of H13 tool steel powder across multiple tracks and layers. Temperature and surface geometry data were provided by a comprehensive physics-based laser deposition model. The computational efficiency of the CA-PF model allows for simulating domains large enough to capture dendrite growth across an entire molten pool and into neighboring LDD tracks. The microstructure of the target track is strongly affected by heat from neighboring tracks including re-melting and re-solidification, and martensite tempering. Dendrite size and growth direction across the entire fusion zone, as well as predicted hardness values, are found to be in good agreement with experimental results.
Mechanisms of energy transport during ultrashort laser pulses ͑USLPs͒ ablation are investigated i... more Mechanisms of energy transport during ultrashort laser pulses ͑USLPs͒ ablation are investigated in this paper. Nonequilibrium electron-transport, material ionization, as well as density change effects, are studied using atomistic models-the molecular dynamics ͑MD͒ and Monte Carlo ͑MC͒ methods, in addition to the previously studied laser absorption, heat conduction, and stress wave propagation. The target material is treated as consisting of two subsystems: valence-electron system and lattice system. MD method is applied to analyze the motion of atoms while MC method is applied for simulating electron dynamics and multiscattering events between particles. Early-time laser-energy absorption and redistribution as well as later-time material ablation and expansion processes are analyzed. This model is validated in terms of ablation depth, lattice/electron temperature distribution as well as evolution, and plume front velocity, through comparisons with experimental or theoretical results in literature. It is generally believed that the hydrodynamic motion of the ablated material is negligible for USLP but this study shows it is true only for its effect on laser-energy deposition. This study shows that the consideration of hydrodynamic expansion and fast density change in both electron and lattice systems is important for obtaining a reliable energy transport mechanism in the locally heated zone.
A novel approach to build a Takagi-Sugeno (T-S) fuzzy model of an unknown nonlinear system from e... more A novel approach to build a Takagi-Sugeno (T-S) fuzzy model of an unknown nonlinear system from experimental data is presented in the paper. The neuro-fuzzy models or, more specifically, fuzzy basis function networks (FBFNs) are trained from input–output data to approximate the nonlinear systems for which analytical mathematical models are not available. Then, the T-S fuzzy models are derived from the direct linearization of the neuro-fuzzy models. The operating points for linearization are chosen using the evolutionary strategy to minimize the global approximation error so that the T-S fuzzy models can closely approximate the original unknown nonlinear system with a reduced number of linearizations. Based on T-S fuzzy models, optimal controllers are designed and implemented for a nonlinear two-link flexible joint robot, which demonstrates the possibility of implementing the well-established model-based optimal control method onto unknown nonlinear dynamic systems.
Using an efficient hybrid Cellular Automata/Phase Field (CA-PF) dendrite growth modeling in combi... more Using an efficient hybrid Cellular Automata/Phase Field (CA-PF) dendrite growth modeling in combination with a solid phase transformation model, microstructure evolution and solid-phase transformation were predicted during laser direct deposition (LDD) of H13 tool steel powder across multiple tracks and layers. Temperature and surface geometry data were provided by a comprehensive physics-based laser deposition model. The computational efficiency of the CA-PF model allows for simulating domains large enough to capture dendrite growth across an entire molten pool and into neighboring LDD tracks. The microstructure of the target track is strongly affected by heat from neighboring tracks including re-melting and re-solidification, and martensite tempering. Dendrite size and growth direction across the entire fusion zone, as well as predicted hardness values, are found to be in good agreement with experimental results.
The mechanics of structure genome was used to predict the mechanical behavior of Ti6Al4V built by... more The mechanics of structure genome was used to predict the mechanical behavior of Ti6Al4V built by additive manufacturing. • The structure genome included the basic representative heterogeneous microstructure of the fabricated parts. • The MSG based simulations provided a very good agreement with the experiments in the mechanical behaviors. • The MSG based method was computationally superior to RVE based simulations.
Journal of Manufacturing Science and Engineering, 1999
This paper involves development of an algorithm to predict stability lobes in face milling operat... more This paper involves development of an algorithm to predict stability lobes in face milling operation. The modeling is based on frequency domain analysis and is an extension of Budak and Altintas to a three dimensional case. It considers the effects of insert and cutter geometry, cutting conditions, process nonlinearity, entry and exit angles and the fully dimensional structural dynamics of both the machine tool and workpiece, including axial dynamics which are often neglected by many researchers. In addition, the predictive capability of stability lobes by the presented models is compared with those results obtained by time domain simulations.
Using high-speed picosecond laser pulse irradiation, low-reflectance laser-induced periodic surfa... more Using high-speed picosecond laser pulse irradiation, low-reflectance laser-induced periodic surface structures (LIPSS) have been created on polycrystalline silicon. The effects of laser fluence, scan speed, overlapping ratio and polarization angle on the formation of LIPSS are reported. The anti-reflective properties of periodic structures are discussed, and the ideal LIPSS for low surface reflectance is presented. A decrease of 35.7 % in average reflectance of the silicon wafer was achieved over the wavelength range of 400-860 nm when it was textured with LIPSS at high scan speeds of 4000 mm/s. Experimental results of broadband reflectance of silicon wafers textured with LIPSS have been compared with finite difference time domain simulations and are in good agreement, showing high predictability in reflectance values for different structures. The effects of changing the LIPSS profile, fill factor and valley depth on the surface reflectance were also analyzed through simulations.
Microholes with diameters varying with the hole depth have promising applications in important ap... more Microholes with diameters varying with the hole depth have promising applications in important applications, but their manufacturing is difficult when the diameter of the hole is very small and/or varies complicatedly with the depth. In the authors' previous work (Dabir-Moghaddam et al., 2016), physics-based modeling study has been carried out on the interaction of a short laser pulse with a plasma plume that pre-exists in a microhole and the resulted effect on the sidewall of the hole. The model calculations have implied that a novel dual-pulse laser ablation and plasma amplification (LAPA) technique is potentially feasible for drilling microholes with diameters that are different at different hole depths. In this paper, further model calculations have been performed to study the effect of different initial plasma temperatures. Under the studied conditions, it has been found that laser amplification of a plasma plume with a higher initial temperature can lead to a larger heat flux to the hole sidewall surface and a larger surface vaporization depth in the sidewall, which indicates that more significant material removal will be expected. On the other hand, a lower initial plasma temperature can lead to more non-uniform vaporization depths at different sidewall locations, indicating that a spatially more selective material removal will be expected.
The International Journal of Advanced Manufacturing Technology, 2015
In keyhole welding, welding quality is closely related to the stability of the keyhole, which is ... more In keyhole welding, welding quality is closely related to the stability of the keyhole, which is primarily determined by keyhole geometry during the welding process. Three essential attributes to describe the simplified threedimensional keyhole shape include keyhole size, penetration depth, and keyhole inclination angle. However, when using traditional measurement techniques, it is very challenging to take in-process measurements of penetration depth and inclination angle, even if the keyhole size can be detected by using a visual monitoring system. To realize the on-line estimation of keyhole dynamics and welding defects, a data-based radial basis function neural network state observer is adopted for estimating penetration depth and inclination angle in the transient state when welding parameters change suddenly. First, a static neural network is trained in advance to establish a correlation between the welding parameters and unobservable keyhole geometry. The dynamic state observer is trained based on the transient welding conditions predicted by a numerical model and then used to estimate the time-varying keyhole geometry. Meanwhile, a coaxial monitoring system is used to observe the keyhole shape from the top side in real time, which not only provides input to the neural network but also indicates the potential welding porosities. The predicted results are validated by experimental data obtained by welding of stainless steel 304 and magnesium alloy AZ31B.
Recently, machining has been exploited as a means for producing ultra-fine grained (UFG) and nano... more Recently, machining has been exploited as a means for producing ultra-fine grained (UFG) and nanocrystalline microstructures for various metal materials, such as aluminum alloys, copper, stainless steel, titanium and nickel-based super alloys, etc. However, no predictive, analytical or numerical work has ever been presented to quantitatively predict the change of grain sizes during machining. In this paper, a dislocation density-based viscoplastic model is adapted for modeling the grain size refinement mechanism during machining by means of a finite element based numerical framework. A novel Coupled Eulerian-Lagrangian (CEL) finite element model embedded with the dislocation density subroutine is developed to model the severe plastic deformation and grain refinement during a steady-state cutting process. The orthogonal cutting tests of a commercially pure titanium (CP Ti) material are simulated in order to assess the validity of the numerical solution through comparison with experiments. The dislocation density-based material model is calibrated to reproduce the observed material constitutive mechanical behavior of CP Ti under various strains, strain rates and temperatures in the cutting process. It is shown that the developed model captures the essential features of the material mechanical behavior and predicts a grain size of 100-160 nm in the chips of CP Ti at a cutting speed of 10 mm/s.
A novel approach to build a Takagi-Sugeno (T-S) fuzzy model of an unknown nonlinear system from e... more A novel approach to build a Takagi-Sugeno (T-S) fuzzy model of an unknown nonlinear system from experimental data is presented in the paper. The neuro-fuzzy models or, more specifically, fuzzy basis function networks (FBFNs) are trained from input-output data to approximate the nonlinear systems for which analytical mathematical models are not available. Then, the T-S fuzzy models are derived from the direct linearization of the neuro-fuzzy models. The operating points for linearization are chosen using the evolutionary strategy to minimize the global approximation error so that the T-S fuzzy models can closely approximate the original unknown nonlinear system with a reduced number of linearizations. Based on T-S fuzzy models, optimal controllers are designed and implemented for a nonlinear two-link flexible joint robot, which demonstrates the possibility of implementing the well-established model-based optimal control method onto unknown nonlinear dynamic systems.
The International Journal of Advanced Manufacturing Technology, Feb 18, 2022
Using an efficient hybrid Cellular Automata/Phase Field (CA-PF) dendrite growth modeling in combi... more Using an efficient hybrid Cellular Automata/Phase Field (CA-PF) dendrite growth modeling in combination with a solid phase transformation model, microstructure evolution and solid-phase transformation were predicted during laser direct deposition (LDD) of H13 tool steel powder across multiple tracks and layers. Temperature and surface geometry data were provided by a comprehensive physics-based laser deposition model. The computational efficiency of the CA-PF model allows for simulating domains large enough to capture dendrite growth across an entire molten pool and into neighboring LDD tracks. The microstructure of the target track is strongly affected by heat from neighboring tracks including re-melting and re-solidification, and martensite tempering. Dendrite size and growth direction across the entire fusion zone, as well as predicted hardness values, are found to be in good agreement with experimental results.
Journal of Manufacturing Science and Engineering-transactions of The Asme, Jul 5, 2018
Previous investigations on "double-pulse" nanosecond (ns) laser drilling reported in the literatu... more Previous investigations on "double-pulse" nanosecond (ns) laser drilling reported in the literature typically utilize double pulses of equal or similar pulse energies. In this paper, "double-pulse" ns laser drilling using double pulses with energies differing by more than ten times has been studied, where both postprocess workpiece characterizations and in situ time-resolved shadowgraph imaging observations have been performed. A very interesting physical phenomenon has been discovered under the studied conditions: the "double-pulse" ns laser ablation process, where the low-energy pulse precedes the highenergy pulse (called "low-high double-pulse" laser ablation) by a suitable amount of time, can produce significantly higher ablation rates than "high-low double-pulse" or "single-pulse" laser ablation under a similar laser energy input. In particular, "low-high double-pulse" laser ablation at a suitable interpulse separation time can drill through a $0.93 mm thick aluminum 7075 workpiece in less than 200 pulse pairs, while "high-low double-pulse" or "single-pulse" laser ablation cannot drill through the workpiece even using 1000 pulse pairs or pulses, respectively. This indicates that "low-high doublepulse" laser ablation has led to a significantly enhanced average ablation rate that is more than five times those for "single-pulse" or "high-low double-pulse" laser ablation. The fundamental physical mechanism for the ablation rate enhancement has been discussed, and a hypothesized explanation has been given.
Molecular dynamics (MD) simulations were carried out to study the bulk polycrystalline properties... more Molecular dynamics (MD) simulations were carried out to study the bulk polycrystalline properties of NiTi. Thermally driven phase transitions of NiTi between martensite and austenitewere simulated using single crystalline simulation domains. With external stress boundary conditions, MD simulation successfully predicted experimentally observed phase transformation temperatures of bulk polycrystalline. Elastic characteristics of NiTi martensite were simulated using polycrystalline simulation domains that consist of realistic disorientations and grain boundary structures. The existence of grain disorientation and grain boundary lowered the potential energy of the simulation domain, which led to more realistic elastic modulus prediction. Analysis of simulation domains that predicted realistic bulk polycrystalline properties showed that the major difference between single crystalline and polycrystalline structures is atomic stress distribution.
Powder capture efficiency is indicative of the amount of material that is added to the substrate ... more Powder capture efficiency is indicative of the amount of material that is added to the substrate during laser additive manufacturing processes, and thus, being able to predict capture efficiency provides capability of predictive modeling during such processes. The focus of the work presented in this paper is to create a numerical model to understand particle trajectories and velocities, which in turn allows for the prediction of capture efficiency. To validate the numerical model, particle tracking velocimetry experiments at two powder flow rates were conducted on free stream particle spray to track individual particles such that particle concentration and velocity fields could be obtained. Results from the free stream comparison showed good agreement to the trends observed in experimental data and were subsequently used in a direct laser deposition simulation to assess capture efficiency and temperature profile at steady-state. The simulation was validated against a single track deposition experiment and showed proper correlation of the free surface geometry, molten pool boundary, heat affected zone boundary and capture efficiency.
Molecular dynamics (MD) simulations were carried out to study the bulk polycrystalline properties... more Molecular dynamics (MD) simulations were carried out to study the bulk polycrystalline properties of NiTi. Thermally driven phase transitions of NiTi between martensite and austenitewere simulated using single crystalline simulation domains. With external stress boundary conditions, MD simulation successfully predicted experimentally observed phase transformation temperatures of bulk polycrystalline. Elastic characteristics of NiTi martensite were simulated using polycrystalline simulation domains that consist of realistic disorientations and grain boundary structures. The existence of grain disorientation and grain boundary lowered the potential energy of the simulation domain, which led to more realistic elastic modulus prediction. Analysis of simulation domains that predicted realistic bulk polycrystalline properties showed that the major difference between single crystalline and polycrystalline structures is atomic stress distribution.
Under the concept of "Industry 4.0", production processes will be pushed to be increasingly inter... more Under the concept of "Industry 4.0", production processes will be pushed to be increasingly interconnected, information based on a real time basis and, necessarily, much more efficient. In this context, capacity optimization goes beyond the traditional aim of capacity maximization, contributing also for organization's profitability and value. Indeed, lean management and continuous improvement approaches suggest capacity optimization instead of maximization. The study of capacity optimization and costing models is an important research topic that deserves contributions from both the practical and theoretical perspectives. This paper presents and discusses a mathematical model for capacity management based on different costing models (ABC and TDABC). A generic model has been developed and it was used to analyze idle capacity and to design strategies towards the maximization of organization's value. The trade-off capacity maximization vs operational efficiency is highlighted and it is shown that capacity optimization might hide operational inefficiency.
Human Factors and Ergonomics in Manufacturing & Service Industries, 2013
The purpose of this article is to review the key emerging innovations in laser and photonics syst... more The purpose of this article is to review the key emerging innovations in laser and photonics systems as well as their design and integration, focusing on challenges and opportunities for solutions of societal challenges. Developments, their significance, and frontier challenges are explained in advanced manufacturing, biomedicine and healthcare, and communication. Systems, networks, and integration issues and challenges are then discussed, and an integration framework for networking laser-and photonic-based services and products is proposed. The article concludes with implications and an agenda for education, research and development, and policy needs, with a focus on human, society, science, and technology integration.
The International Journal of Advanced Manufacturing Technology, 2022
Using an efficient hybrid Cellular Automata/Phase Field (CA-PF) dendrite growth modeling in combi... more Using an efficient hybrid Cellular Automata/Phase Field (CA-PF) dendrite growth modeling in combination with a solid phase transformation model, microstructure evolution and solid-phase transformation were predicted during laser direct deposition (LDD) of H13 tool steel powder across multiple tracks and layers. Temperature and surface geometry data were provided by a comprehensive physics-based laser deposition model. The computational efficiency of the CA-PF model allows for simulating domains large enough to capture dendrite growth across an entire molten pool and into neighboring LDD tracks. The microstructure of the target track is strongly affected by heat from neighboring tracks including re-melting and re-solidification, and martensite tempering. Dendrite size and growth direction across the entire fusion zone, as well as predicted hardness values, are found to be in good agreement with experimental results.
Mechanisms of energy transport during ultrashort laser pulses ͑USLPs͒ ablation are investigated i... more Mechanisms of energy transport during ultrashort laser pulses ͑USLPs͒ ablation are investigated in this paper. Nonequilibrium electron-transport, material ionization, as well as density change effects, are studied using atomistic models-the molecular dynamics ͑MD͒ and Monte Carlo ͑MC͒ methods, in addition to the previously studied laser absorption, heat conduction, and stress wave propagation. The target material is treated as consisting of two subsystems: valence-electron system and lattice system. MD method is applied to analyze the motion of atoms while MC method is applied for simulating electron dynamics and multiscattering events between particles. Early-time laser-energy absorption and redistribution as well as later-time material ablation and expansion processes are analyzed. This model is validated in terms of ablation depth, lattice/electron temperature distribution as well as evolution, and plume front velocity, through comparisons with experimental or theoretical results in literature. It is generally believed that the hydrodynamic motion of the ablated material is negligible for USLP but this study shows it is true only for its effect on laser-energy deposition. This study shows that the consideration of hydrodynamic expansion and fast density change in both electron and lattice systems is important for obtaining a reliable energy transport mechanism in the locally heated zone.
A novel approach to build a Takagi-Sugeno (T-S) fuzzy model of an unknown nonlinear system from e... more A novel approach to build a Takagi-Sugeno (T-S) fuzzy model of an unknown nonlinear system from experimental data is presented in the paper. The neuro-fuzzy models or, more specifically, fuzzy basis function networks (FBFNs) are trained from input–output data to approximate the nonlinear systems for which analytical mathematical models are not available. Then, the T-S fuzzy models are derived from the direct linearization of the neuro-fuzzy models. The operating points for linearization are chosen using the evolutionary strategy to minimize the global approximation error so that the T-S fuzzy models can closely approximate the original unknown nonlinear system with a reduced number of linearizations. Based on T-S fuzzy models, optimal controllers are designed and implemented for a nonlinear two-link flexible joint robot, which demonstrates the possibility of implementing the well-established model-based optimal control method onto unknown nonlinear dynamic systems.
Using an efficient hybrid Cellular Automata/Phase Field (CA-PF) dendrite growth modeling in combi... more Using an efficient hybrid Cellular Automata/Phase Field (CA-PF) dendrite growth modeling in combination with a solid phase transformation model, microstructure evolution and solid-phase transformation were predicted during laser direct deposition (LDD) of H13 tool steel powder across multiple tracks and layers. Temperature and surface geometry data were provided by a comprehensive physics-based laser deposition model. The computational efficiency of the CA-PF model allows for simulating domains large enough to capture dendrite growth across an entire molten pool and into neighboring LDD tracks. The microstructure of the target track is strongly affected by heat from neighboring tracks including re-melting and re-solidification, and martensite tempering. Dendrite size and growth direction across the entire fusion zone, as well as predicted hardness values, are found to be in good agreement with experimental results.
The mechanics of structure genome was used to predict the mechanical behavior of Ti6Al4V built by... more The mechanics of structure genome was used to predict the mechanical behavior of Ti6Al4V built by additive manufacturing. • The structure genome included the basic representative heterogeneous microstructure of the fabricated parts. • The MSG based simulations provided a very good agreement with the experiments in the mechanical behaviors. • The MSG based method was computationally superior to RVE based simulations.
Journal of Manufacturing Science and Engineering, 1999
This paper involves development of an algorithm to predict stability lobes in face milling operat... more This paper involves development of an algorithm to predict stability lobes in face milling operation. The modeling is based on frequency domain analysis and is an extension of Budak and Altintas to a three dimensional case. It considers the effects of insert and cutter geometry, cutting conditions, process nonlinearity, entry and exit angles and the fully dimensional structural dynamics of both the machine tool and workpiece, including axial dynamics which are often neglected by many researchers. In addition, the predictive capability of stability lobes by the presented models is compared with those results obtained by time domain simulations.
Using high-speed picosecond laser pulse irradiation, low-reflectance laser-induced periodic surfa... more Using high-speed picosecond laser pulse irradiation, low-reflectance laser-induced periodic surface structures (LIPSS) have been created on polycrystalline silicon. The effects of laser fluence, scan speed, overlapping ratio and polarization angle on the formation of LIPSS are reported. The anti-reflective properties of periodic structures are discussed, and the ideal LIPSS for low surface reflectance is presented. A decrease of 35.7 % in average reflectance of the silicon wafer was achieved over the wavelength range of 400-860 nm when it was textured with LIPSS at high scan speeds of 4000 mm/s. Experimental results of broadband reflectance of silicon wafers textured with LIPSS have been compared with finite difference time domain simulations and are in good agreement, showing high predictability in reflectance values for different structures. The effects of changing the LIPSS profile, fill factor and valley depth on the surface reflectance were also analyzed through simulations.
Microholes with diameters varying with the hole depth have promising applications in important ap... more Microholes with diameters varying with the hole depth have promising applications in important applications, but their manufacturing is difficult when the diameter of the hole is very small and/or varies complicatedly with the depth. In the authors' previous work (Dabir-Moghaddam et al., 2016), physics-based modeling study has been carried out on the interaction of a short laser pulse with a plasma plume that pre-exists in a microhole and the resulted effect on the sidewall of the hole. The model calculations have implied that a novel dual-pulse laser ablation and plasma amplification (LAPA) technique is potentially feasible for drilling microholes with diameters that are different at different hole depths. In this paper, further model calculations have been performed to study the effect of different initial plasma temperatures. Under the studied conditions, it has been found that laser amplification of a plasma plume with a higher initial temperature can lead to a larger heat flux to the hole sidewall surface and a larger surface vaporization depth in the sidewall, which indicates that more significant material removal will be expected. On the other hand, a lower initial plasma temperature can lead to more non-uniform vaporization depths at different sidewall locations, indicating that a spatially more selective material removal will be expected.
The International Journal of Advanced Manufacturing Technology, 2015
In keyhole welding, welding quality is closely related to the stability of the keyhole, which is ... more In keyhole welding, welding quality is closely related to the stability of the keyhole, which is primarily determined by keyhole geometry during the welding process. Three essential attributes to describe the simplified threedimensional keyhole shape include keyhole size, penetration depth, and keyhole inclination angle. However, when using traditional measurement techniques, it is very challenging to take in-process measurements of penetration depth and inclination angle, even if the keyhole size can be detected by using a visual monitoring system. To realize the on-line estimation of keyhole dynamics and welding defects, a data-based radial basis function neural network state observer is adopted for estimating penetration depth and inclination angle in the transient state when welding parameters change suddenly. First, a static neural network is trained in advance to establish a correlation between the welding parameters and unobservable keyhole geometry. The dynamic state observer is trained based on the transient welding conditions predicted by a numerical model and then used to estimate the time-varying keyhole geometry. Meanwhile, a coaxial monitoring system is used to observe the keyhole shape from the top side in real time, which not only provides input to the neural network but also indicates the potential welding porosities. The predicted results are validated by experimental data obtained by welding of stainless steel 304 and magnesium alloy AZ31B.
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