The HyRAM+ software is an open-source toolkit that provides publicly available models and default input values to enable straightforward and consistent safety assessments for hydrogen and other alternative fuel systems, such as natural gas and propane. The HyRAM+ quantitative risk assessment calculation incorporates annual likelihood of leaks or failures for both compressed gaseous and liquefied flammable fuels, as well as probabilistic models for the effects of heat flux and overpressure. HyRAM
Hydrogen Extremely Low Probability of Rupture (HELPR) is a modular probabilistic fracture mechanics modeling platform developed to assess structural integrity of pipelines for transmission and distribution of hydrogen. HELPR couples fatigue and fracture engineering models with probabilistic methods to generate fast predictions and enables quantification of prediction uncertainty and sensitivity. This user manual serves as a guide through the various analysis features HELPR contains.
Hydrogen fuel sources offer alternatives to conventional fuels in the rail transportation industry. Hydrogen powered locomotive designs utilizing either a fuel cell or an internal combustion engine can make migration to alternative fuels possible for rail transportation. Codes and standards are still in development for rail application of hydrogen and safety risks must be assessed for hydrogen locomotive applications. This report utilizes a failure mode & effects analysis framework to help qualitatively understand possible risks from a hydrogen locomotive system. Findings illustrate how a combination of three mitigations greatly reduces the risks from a hydrogen locomotive system.
Typical QRAs provide deterministic estimates and understanding of risks posed but are constructed using significant assumptions and uncertainties due to limited data availability and historical momentum of using nominal estimates. This report presents a hydrogen QRA analysis using HyRAM+ that incorporates uncertainty with Latin hypercube sampling and sensitivity analysis using linear regression.
Leaks in a hydrogen system can have destructive effects on other components within the system, leading to cascading leaks. The risk of cascading leaks is not currently quantified in many existing risk frameworks, but the prevalence of cascading failures in historical hydrogen facility accidents necessitates further study. A method for quantifying the probability, frequency, and risk of cascaded leaks is proposed. The method provides example scenarios of metrics that would set off cascading failures from each physical effect, including a jet fire melting the O-ring of another component, and an overpressure event from an initial explosion shearing off another component from the system. Cascading leak frequencies and individual risk are calculated for an example hypothetical system. While cascading leaks are quantitatively demonstrated to add to the overall risk, their contributions are small and may not add value to a risk assessment when analyzed in this rigorous quantitative framework.
As hydrogen storage facilities increase in size and capacity, it may be necessary to evaluate codes and standards that regulate hydrogen, especially in relation to allowable aggregate quantities. Existing regulations for other substances with comparable hazards such as oxygen, natural gas, and petroleum were reviewed; most fuels do not have aggregate quantity limits despite sometimes having individual tank capacity restrictions or limits for certain non-industrial, indoor, or small-scale applications. This precedent suggests that specifying a hydrogen quantity limit may not be necessary. Several possible methods for identifying an appropriate limit are presented to illustrate different approaches for a limit basis. These methods are based on overall risk, or the specific consequences inflicted by a jet fire or an explosion on people and infrastructure. However, these example metrics tend to require assumptions about potential leak sizes, suggesting that a general aggregate quantity limit would be difficult to justify without more system-specific requirements.
An analysis was performed to determine whether a hydrogen jet flame impinging on a tunnel ceiling composed of multiple prestressed steel reinforced concrete box beams could result in permanent damage to the tunnel. The lower layer of the concrete box beam was modeled to determine whether heat reaches the steel reinforcing bars and whether spalling could occur. Heat transfer analysis shows that the temperature remains constant at the location of the steel reinforcing bars after 1.3 minutes of impingement and reaches a maximum of 130°C after 5 minutes. However, assuming a constant impingement for 5 minutes is an over estimation due the existing fire model which includes conservative assumptions. Explosive spalling may occur at a thin layer (~0.05 in. at 50 seconds, 0.1 in. at 5 minutes) at the bottom surface of the concrete box beam, but the steel reinforcing bars will not be exposed to the hydrogen flame.
Gaseous hydrogen is known to embrittle most steels, including the steels used in natural gas pipelines. As injection of hydrogen into the existing natural gas infrastructure is considered globally by the pipeline industry, the structural integrity of pipelines transporting gaseous hydrogen must be investigated. Hydrogen Extremely Low Probability of Rupture (HELPR) is a publicly available and open-source probabilistic fatigue and fracture mechanics toolkit recently developed at Sandia National Laboratories. HELPR is intended to incorporate the influence of hydrogen into structural integrity assessments of natural gas transmission and distribution infrastructure. HELPR utilizes engineering models, such as those specified in ASME B31.12 and API 579, with relatively low computational costs to perform large sample ensembles, enabling estimation of performance distributions including low probability tail estimates. Leveraging the probabilistic capabilities built into HELPR, the sensitivity of fatigue and fracture calculations to specific modeling parameters on performance margins can be quantified. Through applying HELPR’s probabilistic capabilities to realistic scenarios, the impact of uncertainty in specific model parameter descriptions on performance margins, such as cycles to unstable crack growth or rupture in gaseous hydrogen, can be characterized; this same approach can then be used to assess the impact of reducing uncertainty sources on the resulting performance metrics, margins, and associated risks. A few industry-motivated scenarios are used to demonstrate this approach.
Full-scale testing of pipes is costly and requires significant infrastructure investments. Subscale testing offers the potential to substantially reduce experimental costs and provides testing flexibility when transferrable test conditions and specimens can be established. To this end, a subscale pipe testing platform was developed to pressure cycle 60 mm diameter pipes (Nominal Pipe Size 2) to failure with gaseous hydrogen. Engineered defects were machined into the inner surface or outer surface to represent pre-existing flaws. The pipes were pressure cycled to failure with gaseous hydrogen at pressures to match operating stresses in large diameter pipes (e.g., stresses comparable to similar fractions of the specified minimum yield stress in transmission pipelines). Additionally, the pipe specimens were instrumented to identify crack initiation, such that crack growth could be compared to fracture mechanics predictions. Predictions leverage an extensive body of materials testing in gaseous hydrogen (e.g., ASME B31.12 Code Case 220) and the recently developed probabilistic fracture mechanics framework for hydrogen (Hydrogen Extremely Low Probability of Rupture, HELPR). In this work, we evaluate the failure response of these subscale pipe specimens and assess the conservatism of fracture mechanics-based design strategies (e.g., API 579/ASME FFS). This paper describes the subscale hydrogen testing capability, compares experimental outcomes to predictions from the probabilistic hydrogen fracture framework (HELPR), and discusses the complement to full-scale testing.
Gaseous hydrogen is known to embrittle most steels, including the steels used in natural gas pipelines. As injection of hydrogen into the existing natural gas infrastructure is considered globally by the pipeline industry, the structural integrity of pipelines transporting gaseous hydrogen must be investigated. Hydrogen Extremely Low Probability of Rupture (HELPR) is a publicly available and open-source probabilistic fatigue and fracture mechanics toolkit recently developed at Sandia National Laboratories. HELPR is intended to incorporate the influence of hydrogen into structural integrity assessments of natural gas transmission and distribution infrastructure. HELPR utilizes engineering models, such as those specified in ASME B31.12 and API 579, with relatively low computational costs to perform large sample ensembles, enabling estimation of performance distributions including low probability tail estimates. Leveraging the probabilistic capabilities built into HELPR, the sensitivity of fatigue and fracture calculations to specific modeling parameters on performance margins can be quantified. Through applying HELPR’s probabilistic capabilities to realistic scenarios, the impact of uncertainty in specific model parameter descriptions on performance margins, such as cycles to unstable crack growth or rupture in gaseous hydrogen, can be characterized; this same approach can then be used to assess the impact of reducing uncertainty sources on the resulting performance metrics, margins, and associated risks. A few industry-motivated scenarios are used to demonstrate this approach.
In order to impact physical mechanical system design decisions and realize the full promise of high-fidelity computational tools, simulation results must be integrated at the earliest stages of the design process. This is particularly challenging when dealing with uncertainty and optimizing for system-level performance metrics, as full-system models (often notoriously expensive and time-consuming to develop) are generally required to propagate uncertainties to system-level quantities of interest. Methods for propagating parameter and boundary condition uncertainty in networks of interconnected components hold promise for enabling design under uncertainty in real-world applications. These methods avoid the need for time consuming mesh generation of full-system geometries when changes are made to components or subassemblies. Additionally, they explicitly tie full-system model predictions to component/subassembly validation data which is valuable for qualification. These methods work by leveraging the fact that many engineered systems are inherently modular, being comprised of a hierarchy of components and subassemblies that are individually modified or replaced to define new system designs. By doing so, these methods enable rapid model development and the incorporation of uncertainty quantification earlier in the design process. The resulting formulation of the uncertainty propagation problem is iterative. We express the system model as a network of interconnected component models, which exchange solution information at component boundaries. We present a pair of approaches for propagating uncertainty in this type of decomposed system and provide implementations in the form of an open-source software library. We demonstrate these tools on a variety of applications and demonstrate the impact of problem-specific details on the performance and accuracy of the resulting UQ analysis. This work represents the most comprehensive investigation of these network uncertainty propagation methods to date.
The previous separation distances in the National Fire Protection Association (NFPA) Hydrogen Technologies Code (NFPA 2, 2020 Edition) for bulk liquid hydrogen systems lack a well-documented basis and can be onerous. This report describes the technical justifications for revisions of the bulk liquid hydrogen storage setback distances in NFPA 2, 2023 Edition. Distances are calculated based on a leak area that is 5% of the nominal pipe flow area. Models from the open source HyRAM+ toolkit are used to justify the leak size as well as calculate consequence-based separation distances from that leak size. Validation and verification of the numerical models is provided, as well as justification for the harm criteria used for the determination of the setback distances for each exposure type. This report also reviews mitigations that could result in setback distance reduction. The resulting updates to the liquid hydrogen separation distances are well-documented, retrievable, repeatable, revisable, independently verified, and use experimental results to verify the models.
