OpenClaw AI Agent + TriboSolver: Running Simulations from Telegram and Building Custom Reports

By Aydar Akchurin

OpenClaw AI agent + TriboSolver turned out to be a useful combination for a practical tribology workflow. I used TriboSolver as the calculation tool and controlled the whole experiment from a Telegram chat through an OpenClaw agent.

OpenClaw is an agent runtime that connects chat, browser automation, files, and local tools. In this case it worked as a Telegram-controlled engineering assistant: I gave short instructions in the TriboSolver Telegram topic, and the OpenClaw AI agent operated the TriboSolver web UI, extracted result data, created plots, and compiled PDF reports.

Simulation setup

The test case was a dry point contact solved in TriboSolver with the Boundary Element Method. I used a 64 × 64 × 32 grid over a 6e-5 m domain and enabled subsurface stress for Body 1.

• Simulation: Dry Contact Simulation
• Model: Boundary Element Method
• Loads: 1 N and 0.1 N
• Body 1: E = 200 GPa, ν = 0.30, H = 2.0 GPa
• Body 2: E = 160 GPa, ν = 0.27, H = 9.5 GPa
• Geometry: point contact, radii 1e-2 m for both bodies
• Friction: none

For the 1 N case, the average contact pressure was about 303 MPa and the real contact area was about 3.30e-9 m². For the 0.1 N case, the average contact pressure was about 128.6 MPa and the real contact area was about 7.78e-10 m².

What changed in the workflow

The solver remained TriboSolver. The OpenClaw AI agent did not replace it with a backend script or a simplified calculation. It used the actual web interface, loaded the result files, selected result variables, and pulled data from the Results tab.

The report was generated outside the original reporting capabilities of the tool. The agent used the calculated pressure and stress fields, then compiled its own graphs:

• contact pressure maps,
• pressure profiles through the center,
• Body 1 Von Mises stress cross-sections,
• X-Z stress sections at y = 0,
• centerline stress curves through depth.

Pros compared with a usual GUI workflow

• Faster iteration after the calculation. I could ask for another cross-section or centerline curve directly in Telegram.
• Repeatable reporting. Once the 1 N report structure existed, the 0.1 N report followed the same pattern.
• Custom plots. The final PDF was not limited to predefined report layouts.
• Solver transparency. The calculation still came from TriboSolver, so the GUI remained the source of truth.

Cons and rough edges

• Browser control sometimes required manual approval from the remote desktop.
• Web UI automation is more fragile than a clean result API.
• The agent can automate plotting, but the engineer still needs to judge whether the model and results make sense.

Report generation

The reports were assembled from TriboSolver result data, not from a built-in reporting button.

Future of calculation tools like TriboSolver

I do not think the future is “AI instead of solvers.” The useful direction is trusted solvers with better automation around them.

The ideal stack is simple: a reliable solver core, a clear GUI for setup and verification, and an automation layer that can extract results, compare cases, build custom plots, and generate reports. OpenClaw acted as that automation layer in this experiment.

For tribology this matters because a contact calculation produces many useful fields: pressure, displacement, contact area, gap, plastic deformation, and subsurface stress. The calculation is only part of the job. The other part is turning those fields into insight quickly.

Takeaway

This workflow made the post-processing conversational. I asked for a pressure profile, then a subsurface section, then a centerline curve, then a second load case. TriboSolver did the calculation; OpenClaw handled the repetitive UI and reporting work.

That feels like a practical future for engineering software: less time formatting reports, more time asking the next engineering question.