University of Pittsburgh · Established 2002

Laboratory for Computational Transport Phenomena

Computational modeling for turbulent flows, energy systems, and next-generation scientific computing.

About LCTP

Research grounded in physics, built for real engineering systems

Established at the University of Pittsburgh in 2002, LCTP develops computational models for turbulent reacting flows in engines, gas turbines, propulsion systems, and industrial burners.

The laboratory’s work seeks to improve energy efficiency, reduce emissions, and deepen understanding of the underlying physics through accurate, scalable numerical methods.

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Research

Methods for complex transport phenomena

From classical computational fluid dynamics to emerging quantum algorithms, LCTP develops methods for understanding and predicting transport phenomena.

Computational mesh for turbulent combustion

Computational fluid dynamics

Turbulent Combustion

High-fidelity modeling of turbulent reacting flows for advanced energy and propulsion systems.

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Balanced domain decomposition for high-performance computing

Scalable methods

Data-Driven Modeling & High-Performance Computing

Machine learning, parallel algorithms, and optimized simulation tools for demanding transport problems.

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Tensor-network representations of turbulence structures

Emerging computation

Quantum Computing & Tensor Network Simulations

Compact representations and quantum algorithms for turbulence, partial differential equations, and scientific computing.

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Computing at scale

Large-scale computing is central to LCTP’s work. The Pittsburgh Supercomputing Center (PSC), a joint Pitt–Carnegie Mellon center, provides advanced national-scale systems, while Pitt’s Center for Research Computing and Data (CRCD) offers campus computing clusters, GPUs, research storage, software, and technical expertise.

We use these facilities to develop and benchmark parallel codes, run high-fidelity CFD and turbulent reacting-flow simulations, study tensor-network methods, and analyze large datasets. Their combined capabilities help us move new numerical methods from initial testing to demanding production calculations.

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Meet the researchers behind our work or get in touch with the laboratory at the University of Pittsburgh.