(127b) Enhancing the Safety and Efficiency of Liquid Hydrogen Operations through Advanced Simulations

In the global quest to ensure a sustainable future with greener energy, a greener economy and decarbonization, hydrogen and natural gas have garnered immense attention. Hydrogen is the most abundant element in our universe and produces almost no pollution. This makes it an excellent candidate as a green energy source alternative to fossil fuels and can assist in decarbonizing high-emission sectors like transportation and shipping. It can play a major role in achieving a more sustainable future. As scientists, engineers and companies around the globe endeavor to incorporate hydrogen fuel into their designs, commercial simulation tools have been used to simulate the production, transportation, storage, utilization and safety issues.

Hydrogen is highly flammable (4-75% LFL-HFL). It is important to predict any potential accident scenario that can happen during operation such as boundary layer flashback or within the storage systems. In addition, its transport in pipes can cause hydrogen embrittlement of the steel pipes. These challenging issues are addressed by simulating the inherent processes. In this paper, we will showcase examples of all these issues resolved by simulations.

Finally, liquid hydrogen and more broadly cryogenic liquid field operations, such as storage tank filling, draining, and transportation, involve complex physics of phase change. Computational fluid dynamics (CFD) has been an indispensable tool to investigate and assist in optimization of these processes to ensure safety, maximize fill mass and minimize boil-off losses. However, CFD simulations for these operations have been very time-consuming and demanding on computing resources. For these cryogenic applications, the “time to solution” may become a serious roadblock, especially during the fast-paced initial design exploration phase. To meet fast-action demands, a speedy solution pointing to correct behavior trends with big-picture input-output results is required. This paper will also showcase an approach that is orders of magnitude faster to simulate these long transient field operations. It solves in minutes on a single CPU core while producing good trend predictions. This approach is equally applicable to any cryogenic liquid, such as liquid oxygen (LOX), and various refrigerants — R410a, R-32, and R-454B, to name a few.