Exploring cryogenic storage with Simcenter Amesim: Why it matters in engineering
- Alvaro Filho
- Sep 16
- 5 min read
Cryogenic storage and distribution — handling substances at extremely low temperatures — might sound like something out of science fiction, yet it plays a crucial role in many engineering applications. From aerospace rockets to medical preservation, superconducting technologies or liquified natural gas (LNG) in ships, cryogenic systems are everywhere. But how do we design these systems to be efficient with a maximum level of safety? Using thermofluid system simulation can help do just that .
In this blog post, we will explore how Simcenter Amesim, a top-tier simulation platform, empowers engineers and enthusiasts alike to model and optimize cryogenic storage systems efficiently using a simulation example inspired by a very well-known NASA experiment of cryogenic tank self-pressurization.
Challenges of cryogenic storage
Cryogenic storage involves storing fluids (hydrogen, nitrogen, natural gas) that are gaseous in ambient conditions. Decreasing their temperature below a certain point changes them into very cold liquids, critical in certain applications. The storage of these cryogenic liquids requires specialized insulated containers, like dewars or cryogenic tanks, to maintain low temperatures, prevent heat transfer, and ensure safety. But with low temperatures come unique challenges such as thermal management, pressure buildup and boil-off. Dealing with challenges requires advanced simulation capabilities to frontload any safety issues that might occur during the product life cycle.
Simulating cryogenic storage in Simcenter Amesim
Simcenter Amesim offers comprehensive tools for modeling and analyzing cryogenic storage systems. It comes with a set of key components such as cryogenic tanks that enable simulations that closely represent real-world conditions, including factors like gas-liquid interaction and thermal exchange.
Core capabilities:
Heat and mass exchange at the liquid/gas interface
Simulate the liquid and gas phases within a storage tank
Model scenarios including filling and emptying, self-pressurization and boil-off
Why Use Simcenter Amesim for cryogenic storage?
Simcenter Amesim comes with a library of fuel cell and cryogenic fluid storage libraries. Compatibility between these multiple thermofluid libraries and the possibility to couple with detailed lumped thermal model facilitates system-wide integration, enhancing a holistic evaluation in engineering projects.
With these capabilities, from the beginning of the design phase, the user can easily estimate the effect in terms of pressure buildup and temperature caused by possible heat ingress in a cryogenic tank. Thanks to the addition of a film layer at the free surface of the tank, pressures and temperatures are captured with increased precision to allow engineers to better size insulation systems. This results in 3-node cryogenic tank model – bulk, film and ullage.
Three-node cryogenic tank in Simcenter Amesim
As for the tank geometry, it can be of any 3D shape – thanks to the Simcenter Amesim tank CAD mapping tool, we can generate the tank liquid height as a function of volume.
A practical example: NASA’s experiments of self-pressurization in a liquid hydrogen tank
With the capabilities explained above, a Simcenter Amesim model can be built focusing on boil-off and self-pressurization in a cryogenic tank. This demo is based on experiments at NASA’s Lewis Research Center, exploring liquid hydrogen (LH₂) storage in a 4.89 m³ spherical tank subject to a constant heat ingress —findings published by Hasan et al.
As for the setup of the experiments, the LH₂ tank was enclosed in a cylindrical cryoshroud. The shroud may be cooled with liquid nitrogen or heated above ambient with electrical resistances to maintain a certain temperature around the tank that we call Tamb in this demo.
Understanding boil-off rates
Three boil-off test cases were performed at 83 K, 294 K, and 350 K of ambient temperature. To cool the upper section, the tank is filled with LH₂ to 95 % capacity. The vent pressure is then gradually reduced to the backpressure control system’s operating pressure of 117 kPa. The boil-off rate is monitored until it stabilizes.
The Simcenter Amesim model used to perform this test case is shown below:
Hydrogen boil-off model
In the above model, GH2 is vented from the tank through a relief valve. Heat is also transferred from the exterior to the vapor on one side, and from the exterior to the liquid on the other side. For each case, a heat transfer coefficient is set using a variable thermal conductance to fit the average heat flux values absorbed, as shown in the table below. The thermal conductances are piloted with the wet and dry areas to compute the heat flows.]
Experiment | Ambient temperature [K] | Heat flux [W/m²] |
Exp 1 | 83 | 0,35 |
Exp 2 | 294 | 2.0 |
Exp 3 | 350 | 3,5 |
The final values of the boil-off rates (expressed in SCMH) from the model, after 50 h of simulation, are pretty close, as shown below next to the steady-state boil off rates of the experiment.
Boil-off rates (simulation vs experiments)
Exploring self-pressurization dynamics
Self-pressurization in a cryogenic tank is basically when you leave the tank sitting in “hotter” environment, LH₂ will evaporate and increase the tank pressure – which may cause a safety issue at some point, so it’s important to assess this pressure buildup in the cryogenic tank.
Self-pressurization tests were conducted at different ambient temperatures: 83 K, 294 K and 350 K. The tank initial fill level was 84%, the initial pressure was 103 kPa. The goal here is to set up the model to match the time-series values of tank pressure and check whether time-series values of temperatures are within the correct ranges.
Self-pressurization model
In the model above, there’s no venting. LH₂ is stored and the variable thermal conductances are set to match the average heat fluxes exchanged with the ambient.
Just like the boil-off tests, there are 3 self-pressurization tests, lasting respectively 20 h, 18 h and 14 h. Pressure values are shown below.
Pressure values (simulation vs experiments)
It can be observed above that for the pressurization tests, the pressures computed by the model exhibit a similar pattern to the tests. They deviate from the experiment by an absolute maximum ranging from 1.5 to 6 %.
Conclusion
As seen in the current demonstration, with a cryogenic tank model divided into three nodes — ullage, film and bulk, we can capture important phenomena such as boil-off rate and self-pressurization. For enhanced temperature predictions in ullage where different temperature layers can exist, further discretization of the upper part could prove beneficial.
Cryogenic storage is a pivotal technology shaping the future of industries relying on hydrogen and other low-temperature applications. Simcenter Amesim offers not just a platform, but a comprehensive toolset to visualize, model, and optimize these systems. By leveraging its capabilities, you can significantly advance your understanding and design of cryogenic storage solutions.
Ensure your cryogenic projects are more efficient and safer with the power of Simcenter Amesim. Schedule a meeting with CAEXPERTS now and discover how our expertise can help your team model, predict, and optimize cryogenic storage systems with precision and confidence.
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