Engineering / CFD · CAE

Computational engineering is at the center of modern product development. In highly competitive sectors — turbomachinery, automotive, aerospace, and defense — shortening design cycles and improving simulation fidelity directly translates to competitive advantage. The shared prerequisite for all of these: adequate and reliable compute capacity.

CFD Workloads: Software and Requirements

Computational fluid dynamics (CFD) is the most compute-intensive category within engineering simulation.

Common CFD Software and HPC Requirements

LES (Large Eddy Simulation) and DNS (Direct Numerical Simulation) are particularly compute-intensive: a mid-complexity LES run on 512–4,096 cores can take 12–72 hours.

Why Network Latency Matters

CFD solvers operate via domain decomposition with halo exchange at every time step. Inter-node communication latency directly affects solution time. InfiniBand HDR/NDR delivers 25–40% better MPI efficiency than Ethernet at 256+ cores.

CAE / FEM Simulations

Finite element method (FEM) structural and thermal analysis, especially for large models and nonlinear cases, demands significant memory and compute capacity.

Common CAE Software

Memory Requirements

Large FEM models (10M+ elements) may require 256–1,024 GB RAM per node. High-memory nodes are an essential component of engineering HPC clusters.

Industry Application Areas

Turbomachinery and Energy

Aerodynamic and aeroelastic analysis of compressors, turbines, and blade profiles. Multistage turbine simulations using MRF (multiple reference frame) and sliding mesh techniques consume significant resources.

Typical configuration: 128–512 CPU cores + InfiniBand + high-speed scratch storage

Automotive

Typical configuration: 64–256 CPU cores + GPU nodes (ANSYS GPU solver)

Aerospace and Space

FAR/CS certification requirements demand simulation accuracy; high-reliability infrastructure is mandatory.

Defense and Security

Ballistic analysis, radar cross-section (RCS) computation, and blast dynamics involving ITAR/EAR-controlled data require on-premise infrastructure. Cloud solutions are legally non-compliant.

Typical Engineering HPC Cluster

Login / Pre-/Post-Processing Nodes (2×)
├── CPU Compute Nodes (16–64 units)
│   └── 2× AMD EPYC 9654, 512 GB DDR5
├── High-Memory Nodes (2–4 units)
│   └── 2× EPYC, 2 TB DDR5 — large FEM models
├── GPU Nodes (optional, 4–8 units)
│   └── 4× NVIDIA L40S or H100 — GPU solver
└── Scratch Storage
    └── BeeGFS / Lustre, NVMe + SAS, 10+ GB/s

Network: InfiniBand HDR200 or NDR400, fat-tree topology

Mevasis Engineering HPC Solutions

Mevasis provides the following services to CFD and CAE-focused engineering teams:

How many cores are needed for CFD simulation? It depends on the workload. A 5–10M cell RANS simulation typically runs well on 32–64 cores. LES or multistage cases may require 256–1,024 cores. Workload profiling is recommended for accurate sizing.

Can OpenFOAM run cost-effectively on cloud? OpenFOAM is license-free, making cloud viable. However, for high-volume steady-state usage (3,000+ hours/year), on-premise or rental is substantially more economical.

Will my existing commercial licenses (ANSYS, Nastran) work on HPC? Yes, provided your license model (token-based, site license, HPC pack) supports parallel execution. Mevasis provides license optimization consulting.

How is simulation data security ensured? On-premise infrastructure keeps data within your premises. Mevasis managed services include access control, encrypted communications, and audit logging as standard.