Category Archives: SPS

Natural Gas Pipeline Operations with Increased Hydrogen

Problem Statement

Decarbonization has become a politicized issue in recent years.  As engineers our mandate is to examine problems and provide solutions, not necessarily to pontificate on the validity of the problems posed or the priorities that should be placed on these problems.  In this blog post, we will examine said problems and discuss methodologies to arrive at solutions. A full technical description of this work is available in the paper PSIG 2216.

One such solution is increasing the use of hydrogen (H2) as a fuel source.  Is H2 the hero that we have been waiting for to cancel carbon and lead us to a bright future?  Maybe.  But it will take a lot of smart work and human ingenuity to cross the “carbon chasm”.  H2 will need help to become the super-hero that saves the day, year, millennium…

Engineers, like most humans, tend to be negative as the cost of failure often outweighs benefits.  But let’s put our pessimism aside and look at some of the positive aspects of hydrogen as an additive to existing fuel streams.

  • Hydrogen fuel consumption produces no carbon dioxide (CO2)
  • There are vast existing networks of natural gas pipelines and processing infrastructure

So that is the good, let’s take a look at the bad (and ugly).  While our heroic H2 is not the villainous carbon, it is also perhaps not the workhorse that modern society has come to rely on.  Actually, H2 poses some new problems to consider.  These include;

  • Reduction in transportation efficiency
  • Hydrogen embrittlement of steel
  • Change in combustion effects
  • Eventual separation of hydrogen from natural gas
  • Changes in pipeline operations

Addressing these problems requires a methodical analysis of the systems involved.  An overarching question one may begin with would be, how to start to characterize and understand the impacts of a hydrogen-rich gas stream?  A comparison of the accuracy of various equations of state (EoS) for modelling fluids containing H2 would be a good start.  Ultimately, it would be useful to quantify the impact of increasing the H2 content to the hydraulics of natural gas systems.  We should examine steady state scenarios, such as the line capacity.  Additionally, we should examine transient operations, such as linepack.

Equation of State Investigation

To evaluate the feasibility of hydrogen utilization a high-accuracy EoS is crucial. Perhaps the most impactful fluid property from a hydraulic perspective is density. To better understand the accuracy of various EoS, we will compare density predictions to measured data.

The Hernandez-Gomez [1] et al data set from 2018 measured the density of methane-hydrogen binary mixtures over a range of compositions, pressures, and temperatures relevant to transport of H2 in natural gas pipelines.

The best known and most widely used EoS is that of Peng-Robinson (PR) from 1973. PR is a cubic EoS, which makes the job of coding up this EoS in simulators easy for software developers but does not provide the best physical description of fluids. More modern takes on EoS are complex models such as Groupe Européen de Recherches Gazières (GERG) 2008 and American Gas Association (AGA) 8. It should be noted that AGA8D is a composition-based method for predicting fluid properties, while AGA8P utilizes bulk properties of the gas to predict fluid properties. AGA8P utilized CO2 content, specific gravity, and heat content as inputs, while AGA8D uses a more detailed approach.

Gas densities predictions from GERG, AGA8, and PR EoS are compared to the measured data from Hernandez-Gomez 2018 in Figures 1-3.

Figure1: Comparison for 5/95 H2 CH4 @ 80.3 °F over a range of pressures; Left) Density measured and predicted; Right) Density error percentage (predicted – measured)/measured
Figure2: Comparison for 10/90 H2 CH4 @ 80.3 °F over a range of pressures; Left) Density measured and predicted; Right) Density error percentage (predicted – measured)/measured
Figure3: Comparison for 50/50 H2 CH4 @ 125.3 °F over a range of pressures; Left) Density measured and predicted; Right) Density error percentage (predicted – measured)/measured

From the figures above we noted that while PR may be acceptable for quick screenings, the error is larger than should be acceptable for a realistic analysis of natural gas systems. GERG or AGA8 are recommended for modelling hydrogen blends in transport and processing. Furthermore, the error or PR increases with increased H2 concentration. It should be noted that the figures above were generated using the Multiflash thermodynamic simulation software, which does not support the AGA8P EoS. Thus, AGA8D was used for this analysis. Results for AGA8P would be expected to be worse than those of AGA8D.   A summary of the findings from Figure 1, Figure 2 and Figure 3 are provided in Table 1.

H2 content (mol%)Average Error (%)Average Absolute Error (%)
Table1:  Summary of Results for Comparison of EoS Models to Measured H2/CH4 Densities

Hydraulic Model Basis and Steady State Analysis

As many of us learned at some point in our academic or professional careers; all models are wrong, but some are useful. In order to analyze cases on a like for like basis, special care must be taken when asking, “compared to what?”.  For this analysis we aimed at modelling a real-life system as a basis, and then creating comparison cases where flow rate was equivalent but H2 content increased, and where the total caloric value of the fluid was held constant while the H2 content increased (equivalent energy).

The system in question was a pipeline with three compression stations spaced more or less equidistantly between the inlet and outlet. This pipeline system included multiple parallel pipelines, with several delivery points along the lines. An idealized schematic is given in Figure 4.


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Figure4: Pipelines with compression stations and approximate segment lengths

Each compressor station had a minimum suction pressure of 500 psig. The compressor station nearest to the inlet (Station A) had a discharge pressor that varied below the maximum allowable operating pressure (MAOP). The middle station (Station B) had a discharge pressure controller that was set at 894 psig. The station closest to the outlet (Station C) had a discharge pressure controller that was set at 936 psig.

The composition was varied with H2 at a baseline value of 0.02 mol%, then additional cases were considered with 5, 10 and 20 mol% H2, while the concentration of other components was held in proportion to the baseline case. This resulted in the gas compositions considered for this analysis, given in Table 2.

ComponentFluid 1Fluid 2Fluid 3Fluid 4
Table 2: Gas compositions considered in this analysis on a molar percentage basis

Steady state simulations were run as a parametric study to investigate the total power usage and suction pressures for the system. This study included an analysis of 32 cases with the parameter variations given in Table 3.

Equation of StateAGA8P AGA8D Peng-Robinson (PR) Benedict Webb Rubin Starling (BWRS)4
H2 Content0.02% (base) 5% 10% 20%4
EquivalenceFlow Rates Maintained Energy Maintained2
Table3: Parametric study parameters, conditions and variations considered

Before jumping to findings, we should clarify why two flowrates were considered for this analysis. This speaks to one of the challenges with H2 as an energy source, namely that H2 is less energy dense than natural gas. The result is that to maintain demand on a like for like basis, i.e., to keep customers happy, higher overall flowrates are required as H2 content increases. This poses another question, “will the H2 rich fluid flowing at or below MAOP provide sufficient energy to meet demand”? If so, what would be the added operational cost for compression, i.e., power requirements, as H2 content increases?

Power requirements for compression stations A, B, and C were calculated for the four fluid compositions and several EoS considered in this analysis. It should be noted that the simulator used for these scenarios included options for AGA8D and AGA8P, along with the more rigorous Benedict-Webb-Rubin-Starling (BWRS) EoS. Power requirements for each station as a function of H2 content with various EoS are depicted in Figure 5.

Figure5: Power requirements for each station over a range of H2 contents from steady state simulations for equivalent flowrate with varying EoS assumptions

The AGA8P results are inconsistent. The overarching trend was a decrease in power usage as H2 content increased.  The power usage for Stations A and C are essentially constant (note the scales on the y-axis are not the same), while that of Station B was responsible for the overall inverse relationship for the system.  This was the expected result, as pressure drop was expected to decrease with increasing H2 content as the volumetric flowrate remained unchanged.

The suction pressures at each station are provided in Figure 6 as a function of H2 content.

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Figure6: Suction pressure for each station over a range of H2 contents from steady state simulations for equivalent flowrate with varying EoS assumptions

This is the result one would expect with the lower pressure drop discussed above with increased H2 content.  As in the previous charts, the AGA8P results are inconsistent, and are considered to be erroneous compared with those of the more rigorous models.

An analysis of this system with the volumetric flowrate held constant would be only part of the picture.  The customer’s concern is with their energy demand, not so much with the volume of gas required to deliver said energy.  For this reason we evaluated cases whereby the total caloric content of the gas stream was equivalent to that of natural gas.  Due to the lower energy density of H2, a greater volume of gas would be required to deliver equivalent energy to customers.  The power usages and suction pressures are given in Figure 7 and Figure 8, respectively.

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Figure 7: Power requirements for each station over a range of H2 contents from steady state simulations for equivalent energy with varying EoS assumptions
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Figure8: Suction pressure for each station over a range of H2 contents from steady state simulations for equivalent energy with varying EoS assumptions

Under equivalent energy conditions, the power usage for Stations A and B are nearly constant, while Station C required a significant increase in power as H2 content increased.  The power requirements of Station C are eventually constrained by the minimum suction pressure requirement.  In fact, the Station C discharge pressure was not able to be maintained under these conditions.  The limiting factor at high H2 content is the minimum suction pressure, which was maintained at 500 psig, and constrained the power usage.  Station B saw decreasing suction pressure with increasing H2 content, as power and minimum suction pressure constraints drove the response.  For Station A, power was the limiting constraint.

Transient Analysis

A key factor for operability of a natural gas asset is the degree to which the volume of the system can be leveraged to safely compress fluids for a brief time, and then later utilized.  Adding H2 to natural gas fluids tended to increase the mass of gas that could be packed into the pipeline while the outlet boundary was closed.

Linepack transient simulations were run from initial conditions or each of the steady state simulations (4 EoS x 4 compositions = 16 cases). However, due to the low accuracy of PR and AGA8P only results for AGA8D and BWRS EoS will be discussed. The linepack scenarios assumed a real consumption profile (from actual field data) with a constant inlet flowrate. Simulations were run for 24 hours under these conditions. Results for simulations with the inlet flowrate for all compositions held equal are provided in Figure 9.

Figure9: Linepack for Left) AGA8D and Right) BWRS EoS over a 24hour period from transient simulations for equivalent flowrate with varying H2 contents

The important findings from these results are that the BWRS and AGA8D EoS produce outputs of similar tendencies, albeit varying magnitudes.  Additionally, linepack increases as H2 content increase.  This means that adding H2 to the natural gas fluid actually increases the operability of the system.

As in the steady state analysis, we must ultimately ensure that the customer’s demands are met; thus, the more relevant results are of the scenario whereby equivalent energy is delivered.  These scenarios were also simulated, with the flowrate adjusted to result in an equivalent amount of energy entering the pipeline system during linepack.  Given the approximate similarity of AGA8D and BWRS EoS results, we shall only examine the AGA8D results in Figure 10.

Figure 10: Linepack for AGA8D EoS over a 24hour period from transient simulations for equivalent energy with varying H2 contents

Contrary to the equivalent flowrate case, with equivalent energy inflow we observe decreased linepack with increased H2 content.  This means that on an energy delivery equivalency basis that the pipeline system has less operational flexibility when H2 is present.  In comparing linepack of the base case natural gas composition to that of the highest H2 content (20 mol% H2) the change in linepack was greater when greater H2 content was present.  In this case the linepack difference (initial – final) was 29% greater for the highest H2 content as compared to the base case.  The reason for decreased linepack is that to maintain equivalent energy content additional mass must be added, as H2 is less energy dense than hydrocarbon gases.

Next Steps and Conclusions

To summarize findings from the three studies that were conducted (EoS comparison, steady state power usage and hydraulic analysis, transient line pack analysis) we will now mention a few key takeaways.

EoS Formulation Conclusions

  • GERG and AGA8D rendered extremely high accuracy in gas density predictions as compared to measurements.  Accuracy of the BWRS EoS was slightly less, but still within the bounds of acceptability.
  • Results from using the AGA8P EoS were erratic. Linepack was over-predicted for some mixtures, while under-predicted for others.
  • PR consistently over-predicted gas densities, leading to excessive linepack predictions. Comparable results would be expected from other cubic EoS.  Thus, PR and its cubic brethren are not recommended for such analyses.

Steady State Analysis Conclusions

  • H2 decreases pressure drop and power usage for the same flow rate.
  • This comes at a “cost” of less energy for equivalent flowrates. When considering equivalent energy H2 increases pressure drop and power usage requirements.

Transient Analysis Conclusions

  • The decreased pressure drop associated with increased H2 content on an equivalent flowrate basis results in greater linepack and more flexibility in operations.
  • When equivalent energy content is assumed, H2 decrease linepack.

Next Steps

This line of inquiry will be of increasing importance as the industry moves toward hydrocarbon alternatives. Additional research and investigation will be required to better understand the viability of H2 as a fuel source or additive. The smaller molecular size of H2 poses containment issues that must be addressed from an operational and material science basis.

Topics for further investigation include, pigging, leak detection and depressurization operations. Additionally, it would be useful to better understand burn tip efficiency, process equipment requirements, storage requirements, reservoir-fluid interactions, and metallurgy issues for increased H2 fluid streams.

Will H2 be our gallant champion, a dragon to be slain, or a complex mixture of both that can be harnessed? If nature provides free lunches, it does not send invitations our way often. Tackling de-carbonization is no different. It will require significant amounts of additional work to be viable, but the value of reaching a hydrogen powered future is certainly worth further investment.

  1. Hernandez-Gomez, R.; Tuma, D.; Perez, E.; and Chamorro, C. R. “Accurate Experimental (P, rho, and T) Data for the Introduction of Hydrogen into the Natural Gas Grid (II): Thermodynamic Characterization of the Methane-Hydrogen Binary System from 240 to 350 K and Pressures up to 20 MPa.” J. Chem. Eng. Data 2018, 63, 1613-1630

Calculation of Transient Piping Loads Caused by Pressure


Piping and pipeline design engineers are familiar with the dangers of pressure surges (commonly referred to as “water hammer”) in liquid-filled pipes/pipelines.  Pressure surges can be caused by transient events, such as valve closures and pump trips, that cause a pressure wave to move through the piping system at a high speed.  The magnitude and speed of the pressure wave are determined primarily by the nature of the transient event (for instance, how fast the valve closes) and the speed of sound of the fluid, but also depend on the pipe material, diameter, wall thickness, and conditions of whether/how the pipe is constrained from moving.  Pressure surges can burst the pipe or produce a vacuum, which may lead to collapse of the pipe.

A problem associated with pressure surges, transient piping loads, is also important, but less well understood by most engineers.  This discussion examines the fundamentals of transient piping load analysis, the tools that are used to perform the analysis, and how evoleap can add value with this type of analysis.

Consider pipe segment that contains a straight horizontal section, with two vertical sections; each with a 90° bend connecting the vertical sections to the horizontal section as shown in Figure 1.  The fluid exerts four forces on the pipe:  gravity, friction, the downstream pressure force (F2), and upstream pressure force (F1).  At steady-state conditions the pipe is static, so the sum of the forces in the horizontal and vertical directions must be zero.  In the horizontal direction the friction force (Ffric) balances the difference in the pressure forces (F1 and F2).  In the vertical direction the gravitational force (Fgrav) is balanced by upward forces exerted by pipe supports and/or the pipe segments at the bends.

Figure 1:  Forces on Pipe Segment with 90° Bends on Each End at Steady Flow

In almost all cases, the frictional force, as we will show, is small and can be ignored.  Also, the gravity force, provided the pipe remains full of liquid, is effectively constant, so it is irrelevant to a transient analysis.  The pressure forces are equal to the product of the pressure at the specified location and the inner pipe wall surface area.  With 90° bends, the direction of the force is along the pipe axis of the pipe segment.  The sum of the forces in the horizontal direction is given in the equations below.

Equation 1: Sum of Forces in the Horizontal Direction

When a valve is closed downstream of the segment, the behavior is different.  The valve closure will generate a pressure surge that will propagate backwards through the piping system.  At some point, shortly after the valve is fully closed, the pressure wave will reach the pipe segment of interest as illustrated in Figure 2.  At that time, the pressure at the downstream bend is much greater than the pressure at the upstream end, resulting in a large, net force in the direction of flow, which can cause damage to the pipe and/or supports or cause the pipe to jump off its supports.  For a long pipe segment (~1000 ft), the pressure wave will traverse the entire segment in roughly 0.3 s.

Figure 2:  Pressure Profile During a Transient Event

Synergi Pipeline Simulator (SPS) is the industry-leading, transient, single-phase, pipeline simulator and is well-suited for this type of problem.  In plants and terminals there are hundreds or thousands of pipe segments.  Calculating and extracting the piping loads for different transient cases is a tedious, but important task.  This has led evoleap to develop automated techniques for setting up, calculating, and extracting the piping loads from transient simulations for complex piping systems. 

The piping load calculations are done via SPS’s application development language, intran, using macros.  Macros can be thought of as subroutines that are invoked via a single statement that passes the necessary arguments.  Thus, one macro can be used to calculate all the pipe forces where the macro is invoked for each pipe segment.  The code to invoke the macros is generated automatically using Excel.  SPS calculates the piping load for each segment at every time step in the simulation.  The results, piping loads as a function of time and extreme piping loads, are extracted and analyzed automatically with evoleap’s inhouse tools.

We take as an example, the flow of Liquified Natural Gas (LNG) through a 30”, horizontal pipe segment 790 ft long, bounded by 90° bends upstream and downstream initially flowing at a standard loading/unloading rate for LNG.  These are typical pipe sizes and segment lengths for LNG loading and receiving terminals.  LNG loading and unloading terminals must be particularly cognizant of pressure surges and the resulting piping loads because they operate at high flow velocities, typically at 15 ft/s or greater and have fast valve closures during Emergency Shutdowns (ESDs). 

The pressure profile at steady state through the pipe segment is shown in Figure 3 where the left axis (~80 ft) is at the upstream 90° bend.  The downstream 90° bend is at the right axis at ~870 ft.  Since the pipe is horizontal the difference in pressure across the pipe segment is accounted for entirely by friction.  The pressure drop is only 2.9 psi, so the frictional force is obviously small.  For instance, the force on each end is P*A = 68.8 psi * 672 in2 = 46.2 kips whereas the frictional force is (P2 – P1) * A = 2.9 psi * 672 in2 = 1.9 kips.  In a surge event the pressure forces will be significantly larger (higher pressures) and frictional force will be smaller because the flow will approach zero.  In fact, when the pressure wave reaches the segment, the flow rate, and the frictional force, will be very close to zero.

Figure 3: Pressure in a Section Similar to Figure 1 at Steady State – 12,000m3/hr – LNG

At time = 5 s, an ESD is initiated, which closes the ESD valves that isolate the loading system from the loading arms/LNG carrier.  The ESD valves close in 18 s, which is within the typical range for LNG loading/unloading systems.  The resulting pressures upstream and downstream of the pipe segment are shown in Figure 4.  Very little happens as the ESD valves are initially closing.  As the ESD valves near closure, pressures rise steadily due to line packing.  The valves are fully closed at 23 s.  In the last second prior to closure the pressure rises rapidly reaching a maximum value of 310 psig. 

Figure 4:  Upstream and Downstream Pressure in a Pipe Segment During ESD Closure

Figure 5 shows the same data but zoomed in on the time when the rapid pressure rises and maximum pressures occur.  At 22 s, the upstream and downstream pressures are 153.5 and 183.6 psig, respectively, giving a net force of (183.6 – 154.5) * 672 = 19.6 kips exerted in the upstream direction.  Such calculations are performed at every time step for every pipe segment across the entire simulation.  The results can be used to compare with rated limits to determine fitness for service. In this case, the Maximum Surge Pressure (MASP) is 440 psig, which is equivalent to 296 kips.  Also, the raw results can be exported and used in standard piping analysis software, such as Caesar II.  In general, if piping loads exceed limits, possible mitigations are:

  • Changes in the closing characteristics of the valves (e.g. faster initially and slower at the end),
  • Changes in the valve closure times,
  • Reduction of the maximum allowable flow rate,
  • Addition of surge relief,
  • Addition of surge tanks,
  • Shorten segments (e.g. expansion loops),
  • Bypasses that divert flow.
Figure 5:  Transient Segment Pressures – Zoomed in on Maximum Surge Between 20s and 25s

Pressure profiles across the pipe segment at 1 s intervals are shown in Figure 6.  The piping load at any time is directly proportional to the difference in pressure across the segment.   The maximum piping load depends on the sharpness of the pressure wave (steeper slope), the length of the pipe segment (bigger pressure difference), and the area of the pipe (larger pipes will experience larger loads).

Figure 6:  Pressure Profiles During Transient Event with Each Line Representing a Second

More complicated geometries also require consideration.  For example, Figure 7 shows a common configuration with a pair of 45° bends.  At a 45° bend, the pressure force is directed at a 45° angle to the pipe axis.  Thus, there is a net force, even under steady-state conditions, on the segments 1-2 and 3-4.  Under steady state conditions, the sum of forces F1, F2, F3 and F4 are effectively zero.  However, as the forces are offset, there is a moment imposed on the system which tends to make the piping system straighten out.  This is the same effect that makes a garden hose straighten out when it is pressurized.

Figure 7: Scenario 2 – Fluid Flowing Through Offset Pipes

Other situations that require special consideration are pipe segments with check valves or valves that may be closed or are actuated in the transient event and pipes with a change in diameter.

For further information, please contact Trent Brown at