ScholarWorks@Hanyang University: Lee, Seung Hwan

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Lee, Seung Hwan (이승환)

COLLEGE OF ENGINEERING (SCHOOL OF MECHANICAL ENGINEERING)

Research Area: Metal 3D printing

Tel 02-2220-0455
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Laser welding:5||Inconel 718:3||Deep learning:3||Aluminum alloy:3||Hardness:3||316L stainless steel:2||Gas tungsten arc welding:2||Aluminum  alloy:2||microstructure:2||heat accumulation:2||Induction heating:2||Coaxial dualbeam:2||hotwire:2||finite element analysis:2||Stress corrosion cracking:2||wire arc additive manufacturing (WAAM):2||Additive manufacturing:2||optimization:2||cold metal transfer (CMT):2||machine learning:2||Carbon Nanofiber:1||Carbon equivalent:1||Characterization:1||Chemical  properties:1||Classification:1||Cobaltmanganese oxide:1||Cold metal transfer:1||Cold metal transfer (CMT):1||Cold spray:1||Computational modeling:1||Continuous cooling transformation diagram:1||Convolution Neural Network(CNN):1||Convolutional  neural network (CNN):1||Convolutional Neural Network (CNN):1||Cooperative adaptive cruise control:1||Corrosion test:1||Cranfield test:1||Creep:1||Deep  learning:1||Deflection in droplet transfer:1||Delamination:1||Deltaferrite:1||Dielectric layer:1||Diffusion:1||Dissimilar materials joining:1||Dissimilar materials welding:1||Dissolution:1||Drop weight test:1||Droplet transfer:1||Dynamic resistance:1||ERNiCr3:1||Electrocatalyst:1||Electrodeposition:1||Emission spectroscopy:1||Energy  absorption:1||Energy Storage:1||Excavator side door:1||Exterior quality:1||Extruded alloy:1||Fatigue life prediction model:1||Feature extraction:1||Fisher&apos:1||Flow drilling screw:1||Fluxcored arc welding:1||Force:1||Friction:1||Fuels:1||Full  penetration:1||GMAW:1||GMAW process:1||Gap:1||Gas  metal  arc  welding  (GMAW):1||Gas  metal arc welding:1||Gaussian process regression:1||Gaussian process regression (GPR):1||Genetic algorithm:1||Grain growth:1||Halbach array:1||Heat treatment:1||High  Mg  weight:1||Homogenization:1||Hot Press Forming (HPF):1||Hot cracking:1||Hot wire:1||Hotcracking resistivity:1||Hotwire:1||Hybrid model:1||Insitu monitoring indicator:1||Inconel 52:1||Indentation depth:1||Interfacial strength:1||Intergranular Corrosion:1||Intermetallic compound:1||Iron Phosphate:1||Joint quality prediction:1||Knearest neighbors (kNN):1||Keyhole behavior:1||Laser directed energy deposition:1||Laser material processing:1||Laser spallation test:1||Laser vision:1||Laser welding with filler wire:1||Laves phase:1||Levelset method:1||Light Water Reactors:1||Long ShortTerm Memory (LSTM):1||Lorentz&apos:1||MAXWELL:1||Machine learning:1||Magnesium:1||Magnetohydrodynamics:1||Mathematical models:1||Maximum hardness:1||Mechanical  properties:1||Mechanical properties:1||Mechanical property prediction:1||Melt pool behavior prediction:1||Michelson interferometer:1||Microstructural tailoring:1||Misalignment:1||Molten pool:1||Multilevel metallization:1||Multiscale Simulation:1||Negative temperature coefficient:1||Ni superalloy:1||Nickel alloys:1||Nondestructive test:1||Nonpenetration stress corrosion cracking:1||Nugget size:1||Numerical models:1||Numerical simulation:1||Optimization:1||Oxides:1||Oxygen evolution reaction:1||Phase transformation kinetics:1||Physicsinformed Gaussian process regression:1||Physicsinformed neural network:1||Plasma/plume:1||Porosity ratio:1||Precontact process:1||Precipitation:1||Precipitation hardening:1||Precipitation kinetics:1||Predictive models:1||ReaxFF:1||ResNet:1||Resistance  spot  welding:1||Resistance element welding:1||Resistance spot welding:1||Ring beamdriven flow:1||Roads:1||Root  pass:1||SN 490C:1||STS 316L:1||Secondary phases:1||SelfPiercing Rivet(SPR):1||Sensor:1||Sliding:1||Smartphone:1||Solidification crack:1||Solidification pattern:1||Spearman's rank correlation coefficient:1||Spinel oxides:1||Stainless steel 308L:1||Strengthening phase:1||Stress Corrosion Cracking:1||Submerged arc welding:1||Sulfide inclusion:1||Supercapacitor:1||Support vector machine (SVM):1||Surface activated bonding:1||Surface machining:1||Tfillet  joint:1||Taguchi  method:1||Tandem flux cored arc welding:1||Tandem welding:1||Temperature field prediction:1||Tensile shear  strength:1||Thermal softening:1||Thermomechanically controlled processed steel:1||Time domain:1||Timedomain analysis:1||Timefrequency domain:1||Timeseries data:1||Transition zone:1||Ultrasonic metal welding:1||VGroove:1||V2O5:1||WAAM:1||Water splitting:1||Wear:1||Weld  quality:1||Weld bead bend test:1||Weld lobe:1||Weld pool:1||Weld quality:1||Weldability:1||Welded joints:1||Welding:1||Welding  parameters:1||Welding process monitoring:1||Wire arc additive manufacturing:1||Wire arc additive manufacturing (WAAM):1||acicular ferrite:1||additional fillerwire:1||adhesion strength:1||analog frontend IC (AFE IC):1||antiseismic steel:1||arc interaction:1||bead contact angle:1||bead on plate:1||burst mode:1||buttering:1||buytofly ratio (BTF):1||capacitive touch sensing system:1||carfollowing problem:1||carbon steel:1||coil gun:1||convolutional neural network:1||cooling performance:1||cooling rate:1||coupled analysis:1||current conveyor II:1||deep learning:1||defect:1||design of experiments:1||design optimization:1||dilution:1||direct energy deposition:1||dissimilar welds:1||droplet transfer:1||electrical signals:1||electromagnetic engine valve actuator:1||electromagnetic forming process analysis (EFPA):1||electromagnetic launcher:1||fast Fourier transform (FFT) processor:1||femtosecond pulse laser:1||fillet welding:1||forming force:1||fraction:1||frame rate:1||fully convolutional network:1||gap monitoring:1||gas diffusion barrier:1||gas diffusion mechanism:1||generator:1||genetic algorithm:1||gradientweighted class activation mapping:1||growth rate:1||hot crack:1||hot stamping:1||hybrid fluxcored arc welding:1||hybrid tandem metal active gas welding:1||interfacial strength:1||knurl depth:1||lamellar tear:1||laser metal deposition (LMD):1||laser spallation test:1||magnetic pulse forming:1||metamodel:1||metal powder:1||microstructures:1||model predictive control:1||modified scalogram:1||monitoring:1||multiaxis laser metal deposition:1||multiobjective optimization:1||304 L SS pipe:1||muzzle velocity:1||nanolaminate structure:1||natural fault diagnosis:1||optimal design:1||oxidization:1||parameter optimisation:1||parameter optimization:1||permanent magnet:1||plasma pretreatment:1||plasmaenhanced atomic layer deposition:1||pore:1||processing conditions:1||processing variable:1||random convolutional kernel transform (ROCKET):1||reference frequency:1||rootpass welding:1||s criterion:1||s force:1||secondary dendrite arm spacing:1||segmentation:1||sensor:1||signaltonoise ratio (SNR):1||silicon oxide:1||single mode:1||slice die:1||solidification map:1||solidification parameters:1||spatial variable:1||support vector machine:1||surface morphology:1||temperature gradient:1||thinfilm:1||through glass vias:1||timeseries:1||tin oxide:1||touch screen panel (TSP):1||weldability:1||window test:1||multiplefrequency driving method (MFDM):1||5xxx  series  aluminum  alloy:1||A106Gr:1||A312 TP316L:1||ANSYS:1||Abnormal process conditions:1||Acoustic emission:1||Active stylus:1||Adaptive method:1||Al/Fe dissimilar welding:1||Arc interaction:1||Arc interference:1||Asymmetric:1||B:1||Backbead:1||Bead geometry:1||Bearing Runtofail (RTF)Natural faultAcoustic sensorFrequency energy shifting method (FESM)Anomaly detectionPrognosis:1||CMT:1||CMTbased wire arc additive manufacturing:1||CNN based deep learning:1||

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