Smarter Defrost Modeling for Heat Pump and Refrigeration Systems
July 6, 2026
New Modelon research to be shared at the 2026 Herrick Conferences at Purdue University For simulation and thermal engineers working on heat pumps, refrigeration systems, HVAC&R equipment, and thermal management for energy-intensive facilities, frost is more than an operating nuisance. It is a system-level performance problem. When frost builds on a coil, it changes heat […]
Introducing the Data Center Library for Modelon Impact
July 1, 2026
See how reference system designs and calibrated vendor components help data center teams move faster and engineer with greater confidence. As AI workloads drive unprecedented increases in rack density, power consumption, and thermal complexity, data center teams are under pressure to evaluate new cooling technologies, reduce risk, and deliver infrastructure faster than ever before. Today, […]
From AI Guidance to Agentic Simulation in Modelon Impact
June 24, 2026
Modelon’s enhanced AI Assistant now helps engineers analyze models, launch simulations, and accelerate engineering workflows directly within the Modelon Impact platform. ▶️ Watch how it works! When we introduced the AI Assistant in Modelon Impact, the goal was simple: help engineers get answers faster, troubleshoot issues more easily, and reduce the friction that often slows […]
From Spec to Simulation: An AI Agent Builds a Data Center Cooling Model
June 10, 2026
Start from a vendor PDF. End with a validated, simulation-ready Modelica model in a single working session. No manual coding at any step. That is the capability we want to show in this post, and it is a current capability, not a future one. Data center infrastructure is changing fast. AI compute is pushing facilities […]
The Token Economics of Engineering AI
June 4, 2026
A Question Worth Putting Numbers On Engineering AI workflows incur cost in how they acquire knowledge during a session. In 5 Questions to Ask Before Trusting AI-Related Simulation Results, the fourth question was: Does the AI spend its effort on engineering or on infrastructure? It is the most consequential of the five, and the hardest […]
Why Two‑Phase Direct‑to‑Chip Cooling is Reaching a Tipping Point
May 19, 2026
Modelon & University of Maryland Researchers to Present Findings at Upcoming Conference Artificial intelligence and high-performance computing (HPC) are fundamentally reshaping the way data centers are designed. Power densities continue to rise, thermal margins are tightening, and workloads are becoming more dynamic and less predictable. HGX H100 racks introduced in 2022 consumed around 40–60 kW, […]
How to Do Weather File Sweeps in Modelon Impact
May 12, 2026
A customer told us something recently that stuck with me. They were evaluating how a data center design would perform across climates. Hot and humid. Cold and dry. Different cities, different weather years. The kind of analysis you have to do if uptime, efficiency, and resilience matter. Technically, they were getting it done. Practically, it […]
Engineering AI that Supports Real Decisions
April 23, 2026
Executive Summary Engineering teams rarely struggle because they lack possible answers. They struggle because getting from a question to a trustworthy answer takes work: choosing the right model, deciding which assumptions are acceptable, configuring a study that can actually run, understanding why a run failed, and turning results into something that supports a real decision. […]
AI Assisted Simulation Now in Modelon Impact
April 21, 2026
Editors Note: Looking for the latest updates? Read how the Modelon Impact AI Assistant now supports agentic simulation workflows, model analysis, and experiment execution in our newest announcement. Modelon’s new AI Assistant helps engineers get started faster, troubleshoot more easily, and move through simulation work with greater confidence. ▶️ Watch how it works! Simulation software […]
5 Questions to Ask Before Trusting AI-Related Simulation Results
April 16, 2026
AI can now generate simulation models from natural language prompts. It can derive equations, write code, configure experiments, and produce results. For engineers evaluating these capabilities, the interesting question is no longer, “Can AI do it?” It almost always can. The harder question is: “Should I trust the result enough to make a decision?” That […]