Computational Engineering   

Along with theory and experimentation, computer simulation has become the third mode of scientific discovery.  Tools like finite element analysis and uncertainty propagation allow our researchers to explore new frontiers in fluid dynamics, heat transfer, bioengineering, combustion, nanotechnology, materials modeling, design, and so much more.  Using the data from thousands of simulations, they can construct models that will ultimately benefit people in real-world situations.

And there's no better place to explore that science than Purdue.  We hosted the first computer science department in the country in 1962, and today, one of the top research supercomputer clusters in the country allows Purdue researchers to explore any possibility they can imagine.

Faculty in Computational Engineering

  • Fluid dynamics
  • Biofluid dynamics
  • Multiphase flows
  • Non-Newtonian fluid dynamics
  • Microfluidics
  • Complex fluids
  • Uncertainty propagation
  • Inverse problems
  • Propagation of information across scales
  • Optimal learning
  • Materials by design
  • Predictive computational tools for biological adaptation processes
  • Tissue expansion
  • Wound healing
  • Reconstructive surgery optimization
  • Numerical methods for biological membranes
  • Indoor and outdoor airflow modeling by computational fluid dynamics (CFD) and measurements
  • Building ventilation systems
  • Indoor air quality (IAQ)
  • Energy analysis
  • Fluid mechanics
  • Nonlinear dynamics and chaos
  • Granular flow
  • Complex fluids, including particulate and multiphase flows
  • Microfluidics, including fluid--structure interactions
  • Wave phenomena in continuum mechanics
  • Applied mathematics and scientific computing
  • Fluid dynamics
  • Interfacial flows
  • Biological and complex fluids
  • Microfluidics
  • CFD of multiphase flows
  • Turbulent gas-liquid flows
  • Cavitation
  • Heat transfer
  • Modeling and simulation techniques for multiphase and multiphysics problems using the phase-field method.
  • Isogeometric methods with applications in fluid and solid mechanics.
  • Modeling and simulation tools for several biomechanics problems, including tumor growth, cellular migration and blood flow at small scales.
  • Computational methods for fluid-structure interaction, especially when the problem involves complex fluids.
  • Predictive, multi-scale modeling and simulation of microstructure evolution in confined granular systems, with an emphasis in manufacturing processes and the relationship between product fabrication and performance.
  • Application areas of interest include:
  • (i) particulate products and processes (e.g., flow, mixing, segregation, consolidation, and compaction of powders),
  • (ii) continuous manufacturing (e.g., Quality by Design, model predictive control, and reduced order models), and
  • (iii) performance of pharmaceutical solid products (e.g., tensile strength, stiffness, swelling and disintegration), biomaterials (e.g., transport and feeding of corn stover) and energetic materials (e.g., deformation and heat generation under quasi-static, near-resonant and impact conditions, and formation and growth of hot spots) materials.
  • Sustainable energy and environment
  • Combustion and turbulent reacting flows
  • Combustion and heat transfer in materials
  • Biomedical flows and heat transfer
  • Global policy research
  • Thermal sciences as applied to HVAC&R systems and equipment
  • Computational solid mechanics
  • Multiscale modeling of materials
  • Finite Elements
  • Dislocation dynamics
  • Computational modeling of micromechanical systems
  • Reliability of electronic interconnects
  • Nano structured materials
  • Effects of length scales on deformation process
  • Big data analysis and statistical machine learning
  • Predictive modeling and uncertainty quantification
  • Scientific computing and computational fluid dynamics
  • Stochastic multiscale modeling
  • Energy storage and conversion (batteries, fuel cells)
  • Mesoscale physics and stochastics
  • Reactive transport, materials, processing, and microstructure interactions
  • Scalable nanomanufacturing: lithography and imaging
  • Optical and magnetic data storage
  • Nanoscale energy conversion, transfer and storage for alternative energy
  • Compact high speed turbomachinery: Design, analysis (experimental-numerical), cavity and tip flows, flow control
  • High speed propulsion: Novel cycle development, intakes, boundary layer transition, combustion
  • Development of measurement techniques and data processing
  • Human Skill and Augmentation
  • Collaborative and Hybridized Intelligence
  • Deep Learning of Shapes and Computer Vision
  • Human-Robot-Machine Interactions
  • Making to Manufacturing (M2M)
  • Factory of the Future and Robotics
  • Manufacturing Productivity
  • Nanoscale heat transfer and energy conversion
  • Multiscale multiphysics simulations of nanomaterials for energy applications
  • Photovoltaic nanomaterials: simulation, synthesis, and devices
  • Thermoelectric nanomaterials: simulation, synthesis and devices
  • Nanoscale thermal radiation and nano-photonics
  • Structural Health Monitoring
  • Wave propagation
  • Structural dynamics and vibration control
  • Adaptive structures
  • Periodic structures and acoustic metamaterials
  • Energy harvesting
  • Thermoacoustics
  • Laser additive manufacturing
  • Ultrafast laser matter interaction
  • Laser welding
  • Laser assisted machining
  • Laser shock peening
  • Multi-physics, multi-scale modeling
  • Micro-nano manufacturing
  • Solid mechanics, multiscale and multiphysics modeling.
  • Design of engineering material systems.
  • Fracture and fatigue.
  • Microarchitectured materials.
  • Biomechanics of soft and hard tissues.
  • Computational solid mechanics
  • Computational geometry
  • Microelectronics reliability
  • Discrete element method (DEM) modeling for particulate systems
  • -- model development, e.g., fibrous particles, particle breakage, particle shapes
  • -- application to manufacturing, e.g., storage and flow, blending, segregation, drying, coating, wet granulation
  • Finite element method (FEM) modeling of powder compaction
  • -- e.g., roll compaction, tableting, picking and sticking
  • Multi-scale modeling (FEM combined with DEM) of powder dynamics
  • -- model development and application to hopper flow, blending, and segregation
  • Chemomechanics of energy-storage materials, such as lithium-ion batteries.
  • In-situ experimentation.
  • First-principles and molecular dynamics simulations on materials science.
  • Stress corrosion in metal oxides.
  • Mechanics of metallic glasses.

Research Areas