For nearly all turbomachinery applications, operators prefer to utilize a direct-driven configuration and avoid gear units. But there are special cases where gear units should be used.

Following an initial evaluation such as a driver speed match analysis, vendors or consultants sometimes inform operators or purchasers that there is no way to avoid the use of a gear unit in a specific turbomachinery train. In high-speed turbomachinery applications, some vendors offer a conventional electric motor with a gear unit. This has been the case particularly for high-speed centrifugal compressors. This is considered by some as an unjustified bias against high-speed, direct-drive electric motors. The use of such motors should be evaluated more closely. The risk and possible operational issues of modern high-speed, direct-drive electric motors are usually less than the problems and issues associated with gear units.

For low-speed turbomachinery trains, the use for a gear unit can easily be avoided. Proper driver types could be selected for machinery options to avoid high-speed drivers for low-speed driven equipment. Steam turbine drivers, though, should usually be limited to direct drive applications. For example, a high-speed steam turbine driver for a low-speed compressor or pump using a gear unit for speed-match is usually a poor decision. Such a complicated configuration can potentially cause many torsional, dynamic and operational issues.

Gas turbine models should be selected to facilitate the direct drive turbomachinery arrangement. Aeroderivative gas turbines usually offer direct-drive trains compared to frame type gas turbines which could only be used in limited speed ranges.

There are tens of thousands of gear units that operate over long periods of time in a wide range of sizes and power-ratings. There are also many gear units for high-gear ratios (above 10), and high-speed applications such as high-speed drivers. Risks, operational issues, and high capital/operational costs associated with gear units have been accepted as fact in many plants. But operators have experienced operational issues, painful installation/commissioning procedures, delays in commission/start-up, numerous unscheduled shutdowns, high cost, and other risks associated with gear units. Because of these issues, there is a growing feeling that gear units should be avoided, if possible.

What is the optimum turbomachinery configuration? It is always best to minimize the number of machinery pieces mounted on a turbomachinery train. That means, eliminating gear units if possible. Doing so, reduces capital, operational, and maintenance costs.

Some gear-unit manufacturers and supporters blame poor application engineering or inadequate maintenance as the reason operators have problems with their gear units. But this does little to lower the relatively high failure rates and issues being experienced with gear units.

Here are a couple of examples from my own experience. They concern integrally geared compressors driven by high-speed steam turbines using intermediate gear units for speed reduction. In such a train, the speed of high-speed steam turbine is first reduced in the intermediate gear reduction. This is used to drive the main input shaft of the compressor. The speed is then increased in the integrally geared train for each compressor casing.

Such a configuration presents inefficient and problematic operation. The speed reduction followed by a speed increase presents considerable losses in the train. It also leads to constant wear and other problems. Such a configuration mandates fixed speed operation of the steam turbine. Instead, this arrangement can be replaced with a more efficient variable-speed steam turbine, direct-driven compressor configuration. This raises the efficiency, reliability, and operational flexibility of the train.

It is true that gear units are needed for many turbomachinery trains. They should be used in cases where other options are not available. But the risks and potential problems associated with gear units should always be considered. Gear units can be eliminated in many turbomachinery trains. Gear units should only be used in turbomachinery trains that other direct drive solutions cannot be employed. 

Amin Almasi is a Chartered Professional Engineer in Australia and U.K. (M.Sc. and B.Sc. in mechanical engineering). He is a senior consultant specializing in rotating equipment, condition monitoring and reliability.

Should Gear Units Be Used Or Avoided?

Applying Stonewall Control to a Turboexpander 

BY TARIQ H. AL-ALSHAIKH & TALAL AL-RASHIDI

A turboexpander is a high-speed centrifugal rotating equipment item that chills an expanding gas and converts the gas’s pressure energy into mechanical work. The turboexpander can also drive a brake compressor or an electric generator. Turboexpanders are used in NGL Plants to liquefy all the ethane from the sales gas and recover most of the throttled poten-tial energy as work.

Gas expansion in a turboexpander produces more liquefaction due to its ability to reach a lower chilling temperature, as the process is almost isentropic. Then the gas enters a demethanizer column, which separates the methane from the other heavy hydrocarbon ends such as ethane, propane, and butane. This design is provided to recover all the propane and heavier components while achieving an optimum ethane recovery of 99+%. 

The overhead product of the demethanizer is cold residue gas, which is routed to a cold box heat exchanger, before the gas is compressed by the compressor end of the expander/compressor, where the gas is boosted in pressure. It then flows to the battery limits, before feeding the sales gas compressors. 

While in either ethane recovery or ethane rejection mode, the process can be run in what is known as Joule-Thompson (J-T) mode, as well through the use of a bypass line, which is usually used during startup and shutdown of the machine. In this mode, the expander/compressor is completely bypassed. Instead, vapor feed to the demethanizer is routed through a bypass valve around the expander. Due to the expander being bypassed, the compressor must also be bypassed as no power is supplied to it. Rather than flowing through the compressor to the battery limits, the stream flows through a bypass line fitted with a check valve to prevent backflow. While operating in this mode, it is possi-ble to adjust the operating conditions, such as increasing the operating pressure of the demetha-nizer column to maintain the desired product quality. However, a loss in product recovery should be expected. 

Normal natural gas liquids (NGL) recovery plants use an inlet flow to control the gas being depres-surized to the demethanizer operating pressure, using the expanders or partial/full J-T bypass valve. The inlet flow is controlled by two separate flow controllers, one for the expander inlet guide vanes and one for the J-T valves. While operating parallel turboexpander-compressor trains, one train may trip out of operation due to a fault. If the plant’s production needs to be kept high while one turboexpander-compressor is down, this is usually accomplished by operating with one turboexpander-compressor and one JT-valve. The speed override controller and low select is usually included by a compressor control vendor to take control of the inlet guide vanes to prevent unnecessary overspeed trips due to flow controller action. During this event, the compressor side of the turboexpander will go to the stonewall region as the flow from the demethanizer overhead will be directed to one compressor instead of two as the other one tripped. The compressor operation in stonewall will be sustained unless back pressure is created downstream of the compressor outlet. 

Note: The stonewall region is when a compressor operating point moved to the right of the per-formance curve at its minimum head in which any additional flow or system resistance reduction will not cause any flow increase. Moreover, the com-pressor will experience stonewall when the gas velocity increased until it reaches the sonic veloc-ity of Mach 1. 

Applying stonewall control to compressors is rare and not as prevalent as it is for surge control. However, it is advisable for high-speed compressors to control their operation in the stonewall region. If the compressor is operated in the choke region, it generates turbulence and vibration that can excite the natural frequency of the impeller and a sudden increase in axial thrust that the magnetic bearings will not be able to counterbalance, resulting in possible damage to the compressor, thus trip-ping the unit. Therefore, it is advisable to control the compressor away from the stonewall region by applying corrective control action to move the operating point out of the choke very quickly. 

An NGL plant that has two turboexpanders operat-ing in parallel, faced a reduction in production. Management decided to switch to a different oper-ating mode that used one turboexpander-compressor train operating along a JT-valve. The turboexpander tripped due to high radial vibration (unbalance). The other turboexpander was started and ran alongside the JT-valve. After running for approximately 12 hours, the second turboexpander train also tripped on high radial vibration. Neither turboexpander could run at normal operating speed, as they tripped on high unbalance vibration if the speed slightly exceeded the minimum. 

Their operation was shifted back to two turbo-expander trains operating in parallel, but at minimum speed to avoid tripping. When time allowed to inspect the machines, it was found that both compressors had broken a piece of the leading edge of one of the vanes. After investigation it was concluded that both turboexpander compressors ran in the stonewall region, which caused over-loading that excited impeller natural frequency and high vibration. Subsequently, this led to fatigue failure at the leading edge of the compressor vanes causing the severe unbalance and tripping of the train. The conclusion was to modify the control system setup to keep the turboexpander-compressor away from the stonewall region. 

Although some control system suppliers utilize a suction anti-choke valve at the compressor suction side, this control scheme did not work effectively. When the suction anti-choke valve tried to prevent the compressor flow from pushing it to stonewall, the suction anti-choke valve was counteracted by the demethanizer controller trying to maintain constant pressure. As a result, the compressor anti-choke valve was bypassed, and hence did not protect the compressor from operating in the stonewall region. 

A proposed control modification requires a dis-charge anti-choke valve as it will provide the proper control by increasing the speed of the turboex-pander and decreasing the J-T-valve flow. Preventing the turboexpander compressor from going into the stonewall region is achieved by creat-ing back pressure on the compressor discharge that is already preset at a certain flow in the compressor control system. The rest of the flow coming out of the demethanizer overhead will be directed to the inlet of the sales gas compressors through a bypass line upstream of the suction side of the compressors. This yields to a slight increase in the demethanizer pressure, which is within its design. Moreover, the turboexpander speed is increased to its maxi-mum possible setting, to allow for the brake com-pressor to stay within its designed operating range and keep it away from the stonewall region. 

Any turboexpander control strategy to avoid operation in stonewall region should include the following: 

1. Monitor the brake compressor flow, pressure ratio, discharge pressure, and expander inlet pres-sure and speed. 

2. Monitor the demethanizer pressure changes for possible flow upsets. 

3. Replace the compressor inlet anti-choke valve with a discharge anti-choke valve, thus increasing the head required and keeping some of the load on the turboexpander. The discharge valve will allow increasing turboexpander speed while keeping the compressor away from the stonewall region. 

4. Control the Q (Flow)/N (Speed) ratio to keep it over 110% of surge Q/N value to avoid oper-ating in surge, and also keep it under 95% of stonewall Q/N value to avoid operating in the stonewall region. 

5. If the flow gets close to surge, open the compressor recycle valve. It is also advisable that the recycle line is equipped with a light duty cooler that can be used to eliminate any overheating if recycling continuous for an extended period. This prevents overloading of sales gas compressors. 

6. If the flow reaches the stonewall region, increase the turboexpander to maximum speed (approximately 105% of rated speed) by adjusting the variable inlet guide vanes. This change limits the tendency to move into the choke region and pushes the compressor away from the stonewall region. It also maximizes the flow through the tur-boexpander and thus minimizes the flow through the J-T valve. 

7. If additional flow is required, partially open the JT-valves while monitoring the flow in the compressor, this must be done gradually under close monitoring of compressor Q/N and speed. And open the flow control valve to flare on the inlet of the brake compressor, to reduce the flow to the compressor, preventing it from reaching the choke limit. Employing a discharge anti-choke valve — in the turboexpander-compressors operating in parallel — is an essential safeguard against inevitable operation in the stonewall region upon the trip of one of the turboexpanders. 

■Tariq H. Al-Alshaikh is a Senior Engineering Consultant on compressors, expanders and steam turbines for Saudi Aramco. He holds an M.S. degree in fluid dynamics from the University of Southern California. 

Talal Al-Rashidi is a Compressor and Steam Turbine Engineer. He holds an M.S. degree in Mechanical Engineering from Drexel University, USA. For more information, visit Aramco.com

Turboexpander Protection

Invented in the mid-20th century and typically equipped in process gas centrifugal, dry gas screw compressors and expanders, dry gas seals (DGS) are the preferred gas lubricated dry seal solutions available on the market. They have become the standard for new machines. 

DGS are robust, simple, consumes less power, and are more efficient in reducing leakage than their predecessor. Various configurations such as tandem with and without an intermediate labyrinth, single, and double are available & shall be selected based on process requirements. In this article, we discuss the various DGS failure modes and how they should be addressed: 

Pressurized hold, also called settle-out condition, occurs when the compressor remains at a standstill, but the casing is pressurized. If an alternate process gas lacks sufficient pressure and flow, process gas enters the seal cavity through the process labyrinth and contaminates the primary seal. This causes seal damage when the compressor is restarted. Minimum ambient site temperature also must be considered as the seal will be at the same temperature during standstill condition, which will cause the process gas to condense and deposit on seal face grooves.

To avoid this kind of failure, the seal gas must be supplied with the required pressure even during a blackout. An alternate supply of seal gas should be consid-ered when gas is not available from the compressor discharge. But it should not change the composition of the process gas. A seal gas booster should be considered when alternate gas is unavailable.

The cause of the majority of DGS failures is contamination. This happens mostly during commissioning by not following OEM recommendations and best practices. Seal gas panel components including piping are properly cleaned and flushed with air, end connections are blinded and dispatched to the site. However, site situations are always different. The piping upstream of the console must also be cleaned thoroughly including interconnecting pip-ing between the console and the compressor. Corrosion inhibitors must be removed. The seal gas supply tem-perature dew point margin must be higher than or equal to the recom-mended value as per API. Failure to do any of the above will lead to contamination followed by degradation of the lift-off effect, friction between the static and rotating faces, parts deformation, O-ring extrusion, heat generation causing thermal shock on the rotating seat, and eventually failure of the rotating and or static rings.

Although a DGS is less susceptible to failure during continuous normal operation, it may happen due to upset conditions leading to contaminated seal gas supply or condensate forma-tion as a result of pressure drop across conditioning equipment. The flow velocity requirement across the pro-cess labyrinth varies depending on the process gas, usually 5 m/s. High velocity must be considered for some processes. If available pressure is not enough, consider installing a seal gas booster which will keep pressure at the seal cavity higher than on the process side. Ensure that a properly sized coalesc-ing seal gas filter is installed which will filter out particles above 3μm. The gap between rotating faces is 3-5μm (a human hair is 70μm). Additional requirements, as per the recent API 692 code, should be considered as necessary.

A separation seal, also known as a barrier or tertiary seal, is located in between the DGS and the bearing box. Its purpose is to avoid lube oil ingress from the bearing to DGS side during normal operation and minimize process gas flow to the bearing side in the event of DGS failure.Flow consumption is much less than the secondary side. But depending on the type of seal applied, enough flow is neces-sary to avoid oil ingress to the DGS side. Nitrogen is typically used but dry air can also be supplied if the process allows it and does not create an explosive mixture. On the other side, high flow is not desir-able as it may over-pressurize the lube oil reservoir. The vent line must be checked regularly and any oil traces should be drained and rectified.

Reverse pressure occurs when down-stream pressure is higher than the upstream supply pressure. If specified, a seal should be designed for reverse differ-ential pressure as recommended by API. This must be confirmed by the DGS vendor as well. During reverse pressuriza-tion, contaminated gas or liquid droplets can travel from the flare vent line back to seal faces resulting in O-ring dislodging, loss of performance, and subsequent risk of seal damage. A differential pressure control valve with PDIT can be applied to avoid these issues. If not, necessary arrangements should be implemented so as not to reverse pressurize the DGS. Confirm flare line minimum, normal, and maxi-mum pressure with the customer. Ensure DGS leakage gas does not create an explosive mixture with other hazardous gases in the flare.

The compressor casing may be depres-surized after shutdown in case of over-haul, emergency shutdown, planned maintenance, or as per process require-ments. DGS O-ring material must be chosen based on depressurization rate. Consult with seal vendors if the decom-pression rate is different a standard application. If special considerations aren’t given to the selection of O-rings, they can be subject to explosive decompression due to rapid depressurization. Additionally, the decompression rate must be selected right at the basic design stage. Special attention must be given to avoid the Joule Thompson effect based on gas composition. This can lead to condensation of the gas and the process side may be exposed to Minimum Design Metal Temperature (MDMT). If material is not selected according to MDMT, the subject material may fail.

Gases and air have dew points which vary based on pressure, temperature, and type of gas. The gas used as a seal gas from the compressor discharge undergoes reduction in pressure and temperature which causes condensation. Similarly, when the dew point temperature is achieved, condensate forms. Eventually, droplets travel through the rotating and stationery seal faces where they will create a blistering effect resulting in failure of the seals faces.

The solution is to follow the rule of chemistry and perform a dew point analysis. The designer should check gas properties from the compressor datasheet and reconfirm these with the client as smaller changes in composition can affect the dew point. Plot the dew point line for possible cases, calculate the dew point, and check its margin from the supplied temperature. The delta T should be equal to or higher than that recommended in API. If the margin is less, gas conditioning will be necessary to keep the gas dry as it passes through the seal gas system. Only the most likely failure scenarios are addressed here. But DGS failure can be caused by various factors depending on the site situation. 

■ Bhushan Nikam is a Project Engineer for a major turbomachinery equip-ment manufacturing organization. He holds bachelor’s degree in Mechan- ical Engineering from university of Pune, IN. He can be reached at nikambb007@gmail.com

Disclaimer: These views are solely those of the author based on personal experience. He assumes no liability or responsibility for any use of this information. Users should always reach out to OEMs and industry professionals as needed.

Dry Gas Seal Failure Modes

Impact of Thermodynamic Property Accuracy on Compressor Performance

Figure 1: Multi-Section Compressor on Factory Test Stand

Knowledge of centrifugal compressor thermodynamic performance is critical to initial acceptance and, once installed, periodic or continuous health monitoring to ensure that the operation is consistent with the original design expectations. The accurate determination of this performance is dependent upon a number of factors. These include uncertainties associated with measured parameters of pressures and temperatures, composition of gas mixtures, and the calculated thermodynamic properties that are derived from these parameter measurements. 

Industry standards, ASME PTC 10 and the ISO equivalent, ISO 5389, define some fundamental compressor performance measures that are universally accepted to describe their thermodynamic behavior. The polytropic work (or poly-tropic head) represents the useful work that is applied to the gas to raise its pressure from suction to discharge conditions. It is expressed by the following equation based upon the work of Schultz and the definition of a polytropic process for an ideal gas:

This equation shows that the polytropic work (Wp) is only dependent upon the compressor suction and discharge values of pressure (P), temperature (T), specific volume (v), and the gas molecular weight (MW). The average polytropic exponent, n, included in these relations is also derived from these parameters. These properties are all available from some equations of state for the gas. However, the polytropic work (useful work) does not represent the total amount of work required by the compression process. 

An additional amount of work known as the lost work is consumed to raise the gas from suction to discharge pressure. Lost work manifests itself as an increase in the thermodynamic property of entropy of the gas or gas mixture and an additional increase in temperature above what would be expected for only the useful work also known as an isentropic process. The combined useful and lost work result in an increase in the total energy of the gas, also referred to as the increase in the thermodynamic property of enthalpy. Thus, the ratio of the polytropic work to the total enthalpy increase of the gas defines the polytropic efficiency of the compression process.

All thermodynamic properties needed to calculate compressor performance can be derived from three progressively complex thermodynamic models. The simplest, a perfect gas, requires only the pressure, temperature and gas molecular weight to obtain the specific volume, or its reciprocal the gas density, and the polytropic work. The enthalpy and entropy are calculated using constant values of the specific heat for a given gas or gas mixture and the temperature differential from suction to discharge of the compressor.

As the gas behavior becomes more complex, the perfect gas model needs to be modified with the addition of the specific heats becoming a func-tion of the temperature. This results in a more involved functional relationship with temperature needed to calculate the enthalpies and entropies required. An added parameter, the gas compressibility factor Z, is also introduced but its value is held at unity with the specific volume derived being equal to that of the perfect gas relation.

The most complex thermodynamic model is the real gas model. There is a compressibility factor, Z, which is a function of both the pressure and temperature with a more complex calculation of the specific volume than the simpler models. Additionally, the specific heat parameters are also functions of both pressure and temperature, resulting in more difficult relations needed to calculate the resulting enthalpies and entropies.

Figure 2: Pressure-Enthalpy Diagram for Methane

A more visual comparison of the enthalpy behavior of a gas is available through the examination of a pressure versus enthalpy diagram for a substance. Figure 2 is such a diagram for pure methane. The red isotherms which display near vertical linear characteristics at low pressures and higher temperature values reflect ideal gas behavior. These isotherms demonstrate increasing curvature at higher pressures which indicates progressive real gas performance with influences of both temperature and pressure present. A perfect gas would display consistent deviations in enthalpy for equal deviations in temperature and this is approximately noted at the lowest pressure levels and moderate temperatures where the changes in specific heat with temperature are minimal.

Although perfect and ideal gas relations may be limited in their application to given pressure and temperature conditions, it is assumed that real gas relations are valid across a broad range of con-ditions including ideal gas conditions. The corresponding values of specific volume (compressibility factor), enthalpy and entropy are more generally applicable when compared to the sim-pler perfect and ideal gas thermodynamic models.

A substantial number of equations of state (EOS) have been developed over the past century to describe the thermodynamic behavior of substances, including several particularly focused on the vapor phase. The ideal gas EOS is generally applicable to simple molecules at low pressures due to the limited interactions between the particles that are relatively sparsely distributed in relation to one another within an arbitrary volume. As pressures increase and the gas molecules become more populated within a fixed volume and complex in both geometry and electro-magnetic polarity, the resulting attractive and repul-sive forces impact the ability of the ideal gas EOS to accurately describe the thermodynamic behavior. Under these more challenging conditions, more complicated relations are needed to ade-quately predict the gas properties. Although generally expressed as a single compressibility factor, Z, applied to the ideal gas EOS, the equations behind the determination of the compressibility factor and other, associated properties can be quite complicated. 

Six selected real gas equations of state will be included in the following comparisons due to their typical application with gas compression. They can be separated into the four major categories provided below along with some historical perspective:

The van der Waals EOS was one of the first proposed beyond the ideal gas EOS. Subsequent improvements to the van der Waals equation included the Redlich-Kwong (R-K), Soave, and the Peng-Robinson (P-R) EOSs, including a number of others. These became known as cubic equations of state due to the fact that they expressed the pressure in terms of a cubic relationship to the specific volume. Alternatively, the compressibility factor could also be expressed as a third-degree polynomial which could be solved explicitly. The R-K EOS included only two com-ponent specific parameters that were derived from the critical pressure and temperature of that component. The Soave and P-R EOSs included a third parameter that was named the Pitzer acentric factor which was experimentally determined and further accounted for molecular polarity and non-sphericity.

Observations demonstrated that the cubic equations of state provided estimations of the compressibility factor that were offset from experimental values across a wide range of pressure and temperature conditions. Peneloux initially proposed a volume-translation method for the Soave equation of state that addressed this shift. Several other volume translation methods have been pro-posed for cubic equations of state. The method proposed by Jhaveri and Youngren has been included here as applied to the P-R EOS and is designated as the VTPR EOS for comparison.

A more complex equation of state was proposed by Beattie-Bridgeman that included higher order specific volume terms and was considered to be more accurate than the cubic equations of state at the time. Benedict, Webb and Rubin proposed an expansion of this relation and Starling added additional terms which resulted in the BWRS EOS with a total of eleven empirically derived constants for each gas component, three more than its predecessor. Although significantly more complicated than the cubic equations of state, these thermodynamic models claim increased accuracy.

More recent variations of this class of equations of state offer additional accuracy but include more than thirty empirically derived constants for indi-vidual gas components. The actual Virial Equation of State is a similar power series expansion with constants that are a function of temperature.

3. Corresponding States Principle Equations of StateThe Corresponding States Principle (CSP) is based upon the fact that different gases demon-strate similar thermodynamic characteristics when the pressure and temperature are normalized with their respective critical values. A number of alternate versions of various equations of state have also been developed using the normalized (reduced) pressure and temperature as variables. 

Probably the most accurate of these was devel-oped by Lee and Kesler and later modified by Plöcker, known as the Lee-Kesler-Plöcker (LKP) EOS. It is based upon the BWRS EOS using “simple” fluid and “reference” fluids combined with the Pitzer acentric factor for the selected gas or gas mixture.

While not being included in this comparison, there are some notable generalized CSP equations of state that can be utilized with reasonable expected accuracies. A generalized equation of state is one that does not require a detailed gas mixture composition but rather simply a presumed hydrocarbon mixture molecular weight and mole fraction compositions of the sour/acid gas components of nitrogen, carbon dioxide and hydrogen sulfide. The hydrocarbon mixture molecular weight is used to calculate values of pseudo-reduced values of pressure and temperature. Two of the more accurate generalized CSP equations of state are those developed by Dranchuk-Purvis-Robinson and Dranchuk-Abou-Kassem. These are typically used in oil and gas production applications where detailed gas mixture compositions are not known or variations are expected.

A recent and stated highly accurate new form of an equation of state is the one developed by the Groupe Européen de Recherches Gazières (GERG). It is based upon the Helmholtz free energy which is a function of the internal energy and entropy of a substance and one of the fundamental thermodynamic energy functions. Similar to the virial family of equations of state, it is dependent upon a large number of empirically obtained constants for each of the included gas components. 

Figure 3: Equation of State Comparison for Typical Natural Gas.

Figure 4: Equation of State Comparison for Carbon Dioxide.

The accuracy of any equation of state for a given single component gas or gas mixture can be validated by comparing its predicted compressibility factor (or specific volume) over a range of pressures and temperatures against laboratory measured values. There is a substantial amount of this laboratory generated PvT data available in the public technical literature. Usually, it is in the form of specific measured data points along isotherms across a range of pressures. This existing data may be utilized to verify the accuracy of a given equation of state proposed to evaluate a compressor application with the same or comparable single component gas or gas mixture. However, unique gas compositions may benefit from the generation of more specific experimental PvT data for the intended range of operating con-ditions. A number of laboratories exist that are capable of generating this data.

One example of an accuracy evaluation is provided in Figure 3 for a typical natural gas mixture. It is approximately 90% methane, 3% ethane, 1.5% propane, 1.7% carbon dioxide, and 1.7% nitrogen by volume. The experimental data was collected along a 170oF (76.7C) isotherm and a pressure range from atmospheric to 6000 psia (413.7 Bara). The experimental data points are provided as black triangles. Curves for the six different equations of state evaluated are included and designated in the legend.

The cubic equations of state display the largest deviations from the measured data. It should be noted that the volume-translated Peng-Robinson, VTPR EOS, shows improved agreement. The remaining equations of state demonstrate very good agreement with the experimental data. One final observation that should be highlighted is the good agreement with all equations of state. The exception is the R-K EOS at pressures below approximately 500 psia (34.5 Bara) along this isotherm. This is due to the behavior of this mixture at the lower pressures approaching those of an ideal gas at this relatively moderate temperature.

A second example is presented in Figure 4 for pure carbon dioxide across an increased pressure range up to a maximum of over 18,000 psia (1241 Bara). Good agreement is once again demonstrated for most of the equations of state evaluated with the largest deviations evident for the simpler, cubic equations of state.

These two figures are fairly representative for a large number of gas mixtures. But it is prudent to have a discussion between the equipment manufacturer and end user concerning the most appropriate equation of state to utilize for a specific application. As noted previously, if there is not ade-quate shared experience for unique gas mixtures, it may require the development of a program to empirically determine PvT data for the mixture and evaluation against a number of different equations of state to determine the most accurate.

The volumetric behavior of the gas is demonstrated through a comparison of PvT data and an equation of state. However, it is not obvious how this translates to other thermodynamic properties such as the internal energy, enthalpy and entropy. The perfect and ideal gas models described above state that these properties are related to the specific heats with the ideal gas model having the specific heats also being a function of the temperature. Experimental determination of specific heats is achieved through the use of a calorimeter, where an amount of energy is added to a thermally isolated gas sample and the increase in temperature is measured. A perfect gas would result in constant values of the measured specific heats over successive tests at different initial temperatures. But an ideal gas would reflect a temperature dependent value.

The real gas thermodynamic model is based upon the assumption that the specific heats are functions of both temperature and pressure. Although calorimeters exist that can measure specific heats at elevated pressures, most of this data has been derived from equipment that is designed to operate at relatively low pressures. Analyses of these real gas thermodynamic functions show that they can be expressed as the sum of the ideal gas value and an isothermal term that is a function of the pressure. This additive pressure dependent term is often referred to as the departure, or residual, function. Further mathematical evaluation can express these departure functions in terms of the compressibility factor which relates the value of the departure function to the value and accuracy of the compressibility factor. A few investigations into the accuracy of the departure functions as related to the predicted accuracy of the compress-ibility factor have confirmed this relationship. It is therefore plausible to assume that equation of state accuracy in the prediction of the compress-ibility factor can be extended to these additional thermodynamic parameters.

EQUATION OF STATE IMPACTS ON COMPRESSOR PERFORMANCE

It follows that equation of state differences in prediction of compressibility factor and the associated thermodynamic parameters may also influence the calculation of compressor thermodynamic performance parameters. These differences can readily be illustrated by comparing calculated polytropic work and efficiency for the various example equations of state based upon a common set of suction and discharge pressures and temperatures. Representative performance curves are first selected from actual applications with comparable gas compositions and suction conditions. 

One of the evaluated equations of state is designated as the baseline and discharge pressures and temperatures are calculated for defined suction conditions at a number of points along the baseline performance curves. These sets of suction and discharge pres-sures and temperatures are then utilized to calculate polytropic work and efficiency for each of the equations of state. They are also used to plot performance curves, essentially in the same fashion as would occur in the case of acquired test data.

Baseline data included in the following comparisons was determined using the GERG EOS due to its demonstrated minimal deviation from published PvT data. Two examples are presented with both based upon the typical natural gas com-position defined previously. The first example addresses the comparative performance of a low-pressure case with a common suction pressure of 100 psia (6.89 Bara) and temperature of 100oF (37.8C). Discharge pres-sures range from approximately 208 psia (14.34 Bara) at higher inlet volumetric flows to 273 psia (18.82 Bara) at low flows near surge. Seven spe-cific operating points were evaluated and are presented in Figures 5 and 6. Polytropic work is plotted in Figure 5 versus an arbitrary range of inlet volumetric flow rates. Good agreement is displayed between the various equations of state.

Figure 5: Polytropic Work for Low Pressure Natural Gas.

Figure 6: Polytropic Efficiency For Low Pressure Natural Gas.

Although there appears to be more deviation in the polytropic efficiency than the polytropic work, a closer look at the scaling in Figure 6 also confirms good agreement between the different equations of state. These results could lead one to believe that there are insignificant differences based upon the choice of an equation of state. However, it should be recognized that there was little deviation in predicted compressibility factor in this range of pressures in Figure 3. Gas properties within this range of pressures and temperatures are near ideal with compressibility factor values near unity and with minimal differences between suction and discharge conditions between the equations of state. 

As the pressure range of the compression application increases, differences in predicted compressibility factors become more evident. Using a similar procedure to predict discharge pressure and temperatures from defined suction conditions and a selected baseline polytropic work and efficiency curves, a comparison of calculated polytropic work and efficiency character-istics can be developed for the chosen set of equations of state. 

Figure 7: Polytropic Work For High Pressure Natural Gas.

Figure 7 provides these curves using a common suction conditions of 2000 psia (137.9 Bara) and 100oF (37.8C) with discharge pressures ranging from 4349 psia (299.8 Bara) to 5553 psia (382.9 Bara) as determined with the GERG EOS.

Good agreement is evident among the more complex, virial type equations of state in comparison to obvious deviations with the cubic based equations of state. Significant deviations are noted for the R-K EOS across the entire inlet volumetric flow range, whereas the amount of deviation is decreased for the P-R EOS and minimized further for the VTPR EOS. This behavior lends credibility to the proposition that equation of state compressibility factor accuracy also translates to reduced uncertainty in the prediction of compressor performance.

An equivalent evaluation of the polytropic efficiency is presented in Figure 8 for the higher-pressure case. Once again, greater deviation from the baseline is evident for the cubic equations of state. However, it is noted that the VTPR EOS displays greater deviation than the P-R EOS. This apparent shift in efficiency is due to the differences in the prediction of the enthalpy of the gas mixture at suction and discharge conditions, specifically the departure enthalpy term which is also a function of the compressibility factor. 

Recall that the efficiency is the ratio of the polytropic work to the enthalpy rise from suction to discharge conditions.

Figure 8: Polytropic Efficiency For High Pressure Natural Gas.

These examples demonstrate that the choice of equation of state used to estimate the thermodynamic properties can impact the calculation of recognized compressor performance parameters, particularly as gas conditions progressively depart from ideal gas behavior. A robust equation of state should adequately predict both ideal and real gas conditions. While these examples address a representative gas composition and set  of operating conditions, the results may not apply to all potential applications. An evaluation of the most accurate equation of state for a specific application should be com-pleted to ensure the most accurate estimates of compressor performance parameters are obtained. It should be noted that the gas power required for the different equations of state at a common inlet volumetric flow rate shows less deviation across the wide range of conditions. This is due to a cancelation of compressibility factors between the polytropic head and flow rate relations, but does relate to a difference in mass flow rate for a common value of volumetric flow rate. 

The information provided in this article leads to the following recommendations with respect to the application of a given equation of state in the evalu-ation of compressor thermodynamic performance.

1. Equipment supplier and user, or user’s representative, should discuss and agree upon the most appropriate equation of state for a specific application. This should be determined prior to equipment purchase commitment and utilized for both compressor and compression facility design activities.

2. If adequate information is not available to support the use of a specific equation of state, a program should be initiated to collect PvT data for the spe-cific gas/gas mixture across the anticipated pressure and temperature range of the application. This should be followed by an analysis of various equations of state to establish the most accurate.

3. Consistent use of a common equation of state should be utilized for initial compressor design and performance prediction, any planned ASME PTC 10 Type 1 (full pressure, similar gas composition) factory testing, field testing, and longer term operational compressor per-formance monitoring.

4. Given that factory ASME PTC 10 Type 2 testing is normally performed with inert gases at near ideal gas conditions, use of a common equation of state may not be necessary due to minimal deviations in thermodynamic properties. 

◦Mark R. Sandberg, P.E. is the owner of Sandberg Turbomachinery Consulting. For more information, read the paper“A More Comprehensive Evaluation of Equation of State Influences on Compressor Performance Determination,” at https://oaktrust.library.tamu.edu/bitstream/handle/1969.1/166804. 

Compressor performance and thermodynamics

Control systems for gas turbines, steam tur-bines and compressors have become more complex. They now incorporate emis-sions-based algorithms (such as DLE and DLN), model-specific diagnostic routines, safety certified protection logic, and cybersecure firewall programs in recent years. This increased complexity is part of the reason why more turbomachinery owners are asking control manufacturers to provide long-term support services for their installed control systems. This is becoming an emerging trend in the market. Plant owners are requiring turbomachinery control manufacturers to provide long-term support for installed contol systems.

The outsourcing of the management of turbomachinery controls is becoming more common. 

High employee turnover coupled with increased control system complexity is forcing turbomachinery owners to question how best to support their plants and turbomachinery long term. Some refinery and petrochemical owners, for example, demand that control manufacturers sign long-term service contracts before allowing the control system to be installed.

A long-term service contract with the turbomachinery control manufacture is seen as a way for plant owners to reduce yearly personnel training expenses, ensure they have access to control system specialists and the latest versions of hardware, software, and cyber-security protection. It eliminates the need to train plant personnel on control systems. Long-term service contracts for turbomachinery controls typically include requirements for many dif-ferent levels of support, including emergency phone support, email support, remote computer support, local technician services, revision control support, and plant personnel training services.

Depending on the plant’s network security requirements and applicable regulations, remote support can be as simple as plant personnel sharing their computer screen via Teams or Zoom. Alternatively, it can be as sophisticated as a secure remote link where a remote support team can log into a system, monitor, troubleshoot, and perform software patch updates as required. In such an environment, plants need cybersecurity expertise and protection. With these types of OEM-provided services, the plant is assured that service engineers are routinely trained on the lat-est system algorithms, network configurations, and cybersecurity patches. They also have access to factory experts to resolve system problems. 

Most turbomachinery owners also require the control manufacturer to provide some level of local support to ensure quick response in the case of system failure or emergency event as well as provide periodic training to plant operators and engineers. 

Woodward offers long-term support services for installed control systems. 

Where turbomachinery availability is key for critical processes and plants, 24/7 access and response time by a local service engineer is a usual require-ment. Depending on the plant the local service engineer(s) may be required to spend a certain number of days in the plant and to be on-call. As control manufacturers are continually making improvements to their products, many plants are now including hardware, software, and cyber security revision control within long-term service contracts. This inclusion ensures that the control manufacture is routinely updating the control system with the latest version of control components, software programs, and security logic.

Responding to this emerging trend, Woodward provides long-term support services to turbomachinery owners globally, assisting them to keep plants operational and control systems up to date. Woodward offers a range of remote and site-based services, for all of its turbomachinery product lines. It is open to customizing service contracts for each plant’s support requirements. 

■Rich Kamphaus is Global Sales Director for Steam Turbine and Compressor Markets at Woodward, a provider of control systems for the turbomachinery, aerospace, industrial, military, power generation, and transporta-tion markets. For more information, visit woodward.com 

Direct turbomachinery controls 

Design and engineering software lies back of every aspect of turbomachinery and facility layout. These tools are used to figure out how to increase efficiency, heighten performance, lower costs, decrease emissions, and find the best way to arrange and integrate equipment and systems. 

There are a great many trends and influences impacting this slice of the market. And the vendor community has risen to the challenge. Let’s hear from the experts: 

Concepts NREC offers a suite of software tools starting from preliminary design through full 3D computational fluid dynamics (CFD), finite element analysis (FEA) and 5-axis machining of turbomachinery. Together, the software is called the Agile Engineering Design System. New for 2022 is CyCAL, which allows the design of turbomachinery within a larger system and includes thermodynamic cycle analysis. CyCAL will be a new platform to bring together all tools in a single user environment.

“Engineers need to look at many aspects of a design in addition to the aero/hydrodynamic performance of the primary flow path,” said Peter Weitzman, President, Software Division of Concepts NREC. “A successful designer needs to simultaneously consider off-design performance, secondary (leakage, bleed, injection) flow, rotordy-namics, and product life.” 

In addition, it is not enough to look at the turbo components in isolation. Every piece of turbomachinery sits inside some larger system to accomplish a specific thermodynamic cycle. If the cycle/system layout is decided first and imposed on the turbomachinery designer, then optimal system performance may not be achieved. The turbomachinery needs to be designed concur-rently with the cycle/system to achieve competitive product performance.

Design trends are receiving a lot of impetus lately from the launch industry. The most critical part of a rocket engine is the turbopump, and designers of engines needs to design the engine cycle and turbopumps as a single system. Customers in the rocket industry want better software to accommodate engine cycle and turbopump design, and these improvements are becoming available to anyone designing turbomachinery.

“Our latest software releases have really been about moving beyond design point performance of the primary flow path,” said Weitzman. “We have added capabilities to design and analyze secondary flow in leakage paths for all classes of turbomachinery. CyCAL provides optimized cycle/system design and analysis capability.” 

The SoftInWay AxSTREAM platform is a fully integrated design, analysis, and optimization soft-ware solution for turbomachinery propulsion and power generation systems. The software includes advanced meanline/streamline, CFD, and FEA solvers, as well as thermodynamic cycle and hydraulic network modeling, rotor dynamics analysis and AI capabilities. Additionally, users can do true clean-sheet design through its generative design solver which can automatically create a design space and narrow down the design intent without introducing too much designer bias into the equation. This can help engineers make decisions about how many stages a machine should have, what the optimal configuration is, and other key thermodynamic and geometric decisions before having to go through meanline analysis or later stages in the design process. 

Valentine Moroz. Chief Operating Officer, SoftInWay has observed some definite trends on the simulation side. “We’re seeing a push towards integrated end-to-end solutions both by means of internal development and through partnerships/acquisitions between small software venders and large companies,” he said. “We’re also seeing the industry trend towards use of digital twins, AI, and high-performance computing (HPC).” 

Within the turbomachinery industry, Moroz added, there are three main development strategies: 

1. Complete clean-sheet design for novel applications (especially in areas such as hydrogen, fuel cells, electric vehicles, etc.) where there is no in-house expertise.

2. Trimming and scaling to adjust existing designs to fit into a new design application (the focus here being a reduction in development time, cost, and risk). 

3. Throwing as much computing power as possible at older designs to try and maximize optimization.It is important to fully understand the objec-tives of a design project before beginning.

“When a project kicks off without a clear understanding of the engineering intent across all teams, it often will lead to conflicting ideas about the project requirements across management, the technical team, and the financial team,” said Moroz. “It is important to establish the engi-neering intent early on to understand what tools you actually need to make your project a success.” 

The TURBOdesign Suite by ADT is an integrated platform for the development of turbomachinery systems, starting from meanline design and covering 3D blade design using inverse design technology with automatic optimization capabili-ties. Inverse design is a unique design method to:

• Satisfy the turbomachinery requirements from the first iterations (e.g., compressors pressure ratio, head in pumps or pressure rise in fans);

• To rapidly develop high efficiency blades, using blade loading as an aerodynamic design input parameters which correlates with performances;

• Accurate surrogate models with small design matrix, requiring up to two orders of magni-tude less computational costs compared to conventional direct optimization methods;

• Develop general design know-how by under-standing the blade loading requirements for product series and similar applications;

• A three-dimensional design approach ideally suited for additive manufacturing.

Over the past few years ADT has enhanced its software to facilitate design exploration and opti-mization at various stages of the design workflow and across all turbomachinery applications. This includes development of integrated design explo-ration, optimization and ML/AI loops starting from a handful of basic requirements such an engine log line for example, and development of automated design, analysis and optimization workflows for 3D blade design/volutes linked with 3D CFD/FEA and multiphysics. In addition, direct interfaces and couplings with major CAE systems are available for integration within existing design environments and facilitating data transfer across programs. Finally, interactive, machine learning-driven user guidance during the design process provides feedback based on live user input parameters.

Maturing turbomachinery components and systems efficiency levels combined with tougher competition and stricter regulatory requirements are driving the search for designs that offer higher efficiency, particularly across multiple areas of the operating conditions that coincide with the lifecycle operations of the system. Smaller and more compact turbomachinery packages, too, are required to reduce weight and material costs in electrification and high-volume productions. 

“Some of the main market drivers are an overall lack of skilled turbomachinery design engineers in the industry compared to a growing demand,” said Professor Mehrdad Zangeneh, Managing Director of Advanced Design Technology. “In addition, development of new products required for decar-bonization which asks for novel system cycles and product configurations.”

Southwest Research Institute (SwRI) manages the Numerical Propulsion System Simulation (NPSS) Consortium. The NPSS software is an engineering simulation and design environment that enables engineers to develop customizable system models. Applications primarily include aerospace systems, engine models for aircraft propulsion applications, thermal management systems, liquid rocket propulsion systems, and energy generation systems. It comes with a library of standard models and components. SwRI manages the licensing and sales of the NPSS software. Additionally, its engineers provide engineering services for developing custom NPSS models, or designing engineering systems for a wide portfolio of propulsion and energy related systems.

Charles Krouse, NPSS Consortium Manager at Southwest Research Institute (SwRI) said that customers, these days, are increasingly interested in (1) electric/hybrid-electric propulsion systems, (2) high-speed propulsions applications, and (3) interfaces between modeling tools. The trend towards electric and hybrid-electric propulsion systems, for example, is being driven primarily by environmental concerns. Although aircraft propulsion only accounts for a small percentage of total carbon emissions (2-3%), emissions reduction targets are approaching quickly, especially for the slow-changing aircraft industry. Furthermore, as the general population sees significant progress in industries such as renewable energy and electric cars, they are beginning to point fingers at the aircraft industry for not adopting environmentally friendly technologies. 

The market for high-speed propulsion applications is being driven by factors such as the hyper-sonic arms race, supersonic business jet startups, and the billionaire space race. With the threat of hypersonic weapons from potential adversaries, the U.S. government is investing in hypersonic weapons. Supersonic jet companies, on the other hand, are being funded by private investors. There seems to be a convergence of technologies that has promised to make supersonic flight affordable, and startups such as Boom Supersonic, Hermeus, Spike Aerospace, and others are racing to beat the incumbents such as Lockheed Martin. 

Krouse added that the trend towards robust interfaces is being driven by the growing number of specialized engineering tools, increasing computational capabilities, and requirements for a heavier focus on model-based design practices. 

“As computational capabilities increase, engineers are able link multiple subsystem models together and simulate more complex models of whole aircraft systems,” said Krouse. “However, linking subsystems models together  between tools requires signif icant computer science expertise to understand the underlying computer architectures.”

NPSS software was traditionally modelled turbomachinery systems. Since turbomachinery applications are now commonly coupled with electric/ hybrid-electric systems, the organization has added the capability to model electric systems in NPSS software, including components such as motors, generators, inverters, and resistors. This capability will be available in its next release. 

SwRI has also developed a supersonic propul-sion model as part of an internal research and development effort. The purpose of this project was to develop improved capabilities for modeling critical components, such as the combustor, inlet, and isolator in high-speed air-breathing propul-sion applications. Additionally, the organization developed a system to demonstrate the transition from subsonic flight to supersonic flight, using a turbine-based combined cycle (TBCC). 

Advances have been made, too, in the area of interfaces. Recently, SwRI developed APIs for NPSS to interface with python and java computer languages, which are in addition to the existing interfaces to standard languages such as C/C++ and Fortran. This allows NPSS users to complete their development work in their preferred programming language and communicate with the NPSS simulation environment. 

In addition, SwRI has been working to resolve some of the challenges connected with additive manufacturing (AM). The AM process can some-times create anomalies such as voids that may lead to fatigue crack formation, growth, and fracture. Customary integrity analysis methods for conven-tional materials have significant limitations for AM applications.

However, a zone-based probabilistic damage tolerance (PDT) methodology is a promising framework for the assessment and certification of AM parts. This approach calculates the probability of fracture due to the formation and growth of fatigue cracks at material or manufacturing anomalies. The component is subdivided into different zones each having different properties, such as material properties, non-destructive inspection (NDI) probability of detection (POD), and anomaly distributions. The Darwin software developed by SwRI provides practical implemen-tation of zone-based PDT methods.

Originally developed to address rogue material anomalies in titanium rotors for aircraft engines, Darwin has expanded to address a range of integ-rity threats. It is used, for example, to ensure the structural integrity of conventional safety-critical components in turbomachinery. NASA and the FAA are actively funding research at SwRI to evaluate the wider use of Darwin for AM applications and to enhance its capabilities towards this goal. 

When asked what trends he had observed, Jeff Erno, Expert Solution Architect, Dassault Systèmes named three: A need for integration between geometry (CAD) and analysis (CAE); home-grown design and analysis solutions (due to lack of commercial off the shelf or COTS software), that were needed in the 1980s and 1990s to be competitive, are needing an upgrade and possibly a rewrite from legacy FORTAN and C programming methods; and demand for collabo-ration and storage for analytical results.

“Innovation is driving legacy home-grown tools to adapt, which is difficult to do with legacy programming methods,” said Erno. “Older more manual methods aren’t cutting it.”

The company has adjusted to these trends via geometry and analysis methods ported into a single, unified platform, promoting fast rerunning of analysis to evaluate performance as the design changes. Such changes are incorporated into Dassalt’s SolidWorks, Catia and Simulia lines. Such tools offer geometry and analysis integrated associatively allowing replay when the design changes. In addition, platform-based collaboration allows designers to work with other designers and with analysts to evaluate performance. 

Rahul Garg, Vice President, Industrial Machinery, Siemens Digital Industries Software, has observed a movement towards improved renewable energy adoption to ensure turbomachinery grows progressively more energy efficient. This includes adopting new fuel types; adjusting their operations for cleaner output; and using inte-grated cloud software to source, manage and store their turbomachinery solutions. 

“Companies are leveraging technology to solve complex issues that arise across the machine lifecycle to continu-ously improve their processes,” said Garg. "For instance, some companies utilize simulation software that leverages a digital twin. This digital twin can help them foresee thermal and dynamic deformations and address the problem before it arises in late-stage development.” 

A major impetus for these trends is digitalization. The benefits include augmented cross-domain collaboration; project data reuse for faster order fulfillment; enhanced machine development via the use of a digital twin; improved lifecycle service maintenance through digital twin and low-code tools; and task automation enabling greater time to devote to functional projects. 

To that end, Siemens developed its cloud-based Xcelerator portfolio to help clients respond to turbomachinery trends and tackle market demands. The company is actively enhancing this cloud approach to simplify adoption through pre-configured industry processes, capturing experience inside templates. Xcelerator offers various design, analysis and engineering solu-tions. Xcelerator products can integrate with other engineering tools.

Design and Engineering Software

The latest buzzword in the turbomachinery industry is the digital twin. It’s being praised as the holy grail for everything from failure prevention and maintenance reduction to life extension, improved operation, and parts fore-casting. While the digital-twin concept offers defi-nite value for machinery operation, some of these claims stretch the truth. It’s worthwhile to discuss what a digital twin really is, what it can do, and where its limitations lie. 

A digital twin is a computer virtual represen-tation and simulation of a real physical object or process. Although the idea has been around for a long time, the basic concept and definition were introduced in 2002 by Michael Grieves, then at the University of Michigan, as a model for Product Lifecycle Management. NASA then coined the term in 2010 in a Roadmap Report. The digital twin consists of three parts: the physical object, the digital or virtual product, and the connections between the two. The concept has branched out into different types, such as the digital-twin aggregate (DTA), where multiple digital twins operate in parallel to simulate a complex system.

Implementing a simple digital twin or a more complex DTA requires data about the real-time status of the real-life object, as well as the ability to operate, maintain, or repair the real system remotely via a parallel digital twin representation. Think of Apollo 13, where the ground-based engineers were able to determine how to rescue the mission remotely by simulating all operations and failure scenarios to identify a viable solution. Thus, “the ultimate vision for a digital twin is to be able to create, test and build [our] equipment in a virtual environment” (John Vickers, NASA, 2010). 

In its purest form, the digital twin is a product and technology development tool. That means it is also an alternative to big data approaches, where correlation is assumed to be a proxy for causation. The digital twin is essentially a computer simulation program that uses real-life data to create simulations that can predict how a physical asset will perform. Artificial intelligence, self-learning, and software data analytics can also be utilized to enhance and refine the output. 

But, to quote Lewis Carroll’s Humpty Dumpty in Through the Looking-Glass, “When I use a word, it means just what I choose it to mean.” So, what does “digital twin” mean in current turbomachinery discussions about condition monitoring, predictive interventions, condition-based repair and process optimization? 

The distinction between a simulation model and a digital twin is not really clear. The basic components of a digital twin are a model and some real-life operational data. That’s nothing new. For decades, we have used performance models — in the form of performance curves or compressor maps, for example — to determine the health of equipment by simply comparing the expected behavior (from the curves) to measured performance data. The difference between a model and a digital twin (i.e., “a digital twin without a physical twin is a model”) does not help because the performance curves actually reflect the behavior of a real machine.

The added feature of a true digital twin versus a simple model is that a digital twin can adapt to changes of the physical object over time. For example, if a machine shows wear or has perfor-mance degradation, a true digital twin can adjust whereas a simple model simulation cannot. The digital twin thus provides added value in that it provides a more accurate representation of the current state of the machine. This can be of significant value when scheduling maintenance and repairs or predicting remaining life since the digital twin’s updated parameters directly relate to known physical failure mechanisms. 

One of the key insights of digital-twin operation is that the simulation model used in the background does not have to be complicated. The use of performance curves noted above can be part of a digital twin. But updating the model to the current state of the machine using measured data is not trivial. Measured data is always subject to condition, measurement, and statistical uncertainties. The digital-twin correction using actual data (from operations, field, and factory testing) must be treated as a statistical process — the more data, the better the model improve-ment. The sourcing of test data from multiple (more or less) identical machines helps signifi-cantly when correcting the model. This means that a manufacturer with a large number of machines in operation (gas turbines, steam turbines, compressors etc.) has an advantage when building a digital twin. 

The minimum requirements for the model used in a digital twin are simply that it is sufficiently physics-based, accurate, and quick to run. The concept of a digital twin, leaving all the hype aside, is based on existing and mature technologies. Overuse of the term may lead to underutilization when potential adopters become cynical of the buzzwords and shiny presentations. Using the concept requires trust in the model, the data, and the algorithms used to update the model. Supervision by human experts is still required for checking the plausi-bility of the model outcomes and digital-twin recommendations. 

■Klaus Brun is the Director of R&D at Elliott Group. He is also the past Chair of the Board of Directors of the ASME International Gas Turbine Institute and the IGTI Oil & Gas applications committee.

Rainer Kurz is the Manager of Gas Compressor Engineering at Solar Turbines Incorporated in San Diego, CA. He is an ASME Fellow since 2003 and the past chair of the IGTI Oil and Gas Applications Committee.

Any views or opinions presented in this article are solely those of the authors and do not necessarily represent those of Solar Turbines Incorporated, Elliott Group, or any of their affiliates

The Digital Twin Knows it All  

Many manufacturers, vendors, engineering firms, and operators have real-ized the importance of lessons learned during different stages of design, devel-opment, and machinery introduction. Too often, those lesson-learned documents have been lists with an overwhelming number of items. Unfortunately, many of the same mistakes are repeated by engineers, vendors, contractors, and operators in subsequent projects. Let’s review a few ways to improve modern turbomachinery. 

The bulk of the design review is done by design experts and engineers. However, there are two groups of people that should be included in each segment of the design review process: the commissioning/start-up team, and the people who will operators operate and maintain the machinery. In many cases a common shortfall is that companies do not select the operations team at the time of machinery selection. It is wise for operating companies to assign operation leads and superin-tendents as soon as possible and have their inputs on all key matters. A similar principle is applicable for the commissioning team. The exchange of data and information between engineering and commissioning is vital. There should be lines of communication estab-lished to help key people communicate each other and transfer vital data, feedback, and experience. 

• High-level requirements by client representatives: It is useful if client representatives establish and explain their high-level requirements and expectations to engineering firms and vendors/manufacturers. Of course, some of the expectations might not be achievable and others might not be reasonable considering technical, budget, or time-schedule constraints. However, it is important to discuss these matters as early as possible. It will be found that while some expectations might not be achievable in the way initially thought, alternatives might be formulated which can achieve those expectations at a reasonable cost and without greatly extending delivery times. It is best to not be in a rush to oppose such expec-tations. It is advisable to spend some time and resources to find a way to achieve them in a more suitable way. 

• Operator feedback: If there was a problem in operation, the best way (and usually the only way) to inform the engineering team (and subsequently vendors/manufacturers) and rectify the problem is via operator feedback. 

• Communication with the commissioning team: The communication between the engineering team (vendors/manufacturers) and commissioning leads is vital. The commis-sioning team need data and documents to plan and prepare for their tasks. Feedback from the commissioning team is also important to consider provisions for smoother and commissioning and start-up practices. Combined with modern monitoring systems, automation provides an opportunity for improved reliability and availability. However, there is such a thing as over-automation. 

Automation is a major trend in plants and facilities. Automated operation is cost effective, efficient, advantageous, productive, and more easy to manage. Combined with modern monitoring systems, automation provides an opportunity for improved reliability and availability. However, there is such a thing as over-automation. 

The basic principle is to leave ordinary, repetitive tasks to control systems and provide operators with tools to do their own tasks better. In an over-automated plant, automation hinders operators from operating efficiently. In some cases, operators cannot intervene and override the automated system when there was a problem. 

A general guideline is to buy new turbomachinery rather than second hand. In many cases, it can cost more to rehabilitate and revamp second-hand turbomachinery that to purchase new equipment. There may also be cracks, corrosion, and erosion that has not been detected. Manufacturer warrantee should be mentioned as a key benefit of new equipment. 

Whatever equipment is used, shop inspection is crucial yet is often overlooked. It should not be left only to third-party inspectors. Such inspectors are beneficial and are nearly always needed. In fact, third-party inspection is often a mandatory requirement. However, inspectors from the oper-ating company, engineer consultants, the main EPC contractor, and others are often needed to inspect machinery at various stages. 

■ Amin Almasi is a Chartered Professional Engineer in Australia and U.K. (M.Sc. and B.Sc. in mechanical engineering). He is a senior consultant specializing in rotating equipment, condition monitoring and reliability

SELECTION, PURCHASE,AND OPERATION OF TURBOMACHINERY

Atlas Copco is adding two new businesses to its portfolio. The purchase price for either is not disclosed.

Associated Compressor Engineers Ltd (ACE) of Stockport, UK specializes in the sale, installation, and service of compressor air systems. ACE will be integrated into Compressor Technique.

National Vacuum Equipment Inc. (NVE) is headquartered in Michigan, USA and is a manufacturer of industrial vacuum pumps and packages for mobile use on tanker trucks. NVE will become part of the Industrial Vacuum Division of Copco’s Vacuum Technique business area.

The acquisition is expected to close during Q3.

Articles

Atlas Copco expands compressor and vacuum areas

Atlas Copco Acquisitions

General Electric (GE) is sending out new LM2500+ aeroderivative turbines to Manildra Group’s cogeneration power plant at Shoalhaven Starches in Bomaderry, New South Wales, Australia. GE is providing two LM2500+ aeroderivative gas turbines and two Heat Recovery Steam Generators (HRSG) to deliver up to 54 MW of electricity and 210 TPH of steam.

The new equipment is part of an effort by Manildra Group to replace their coal-fired boilers with natural gas. Manildra Group produces a range of food and industrial products; wheat flours, bakery mixes, ethanol, starches, syrups, and stockfeed.

The manufacturing process at Shoalhaven Starches uses the entire wheat grain, relying on heat steam production to power the site.

The facility requires availability of large amounts of electricity and steam. Manildra Group turned to GE for both. Currently, electricity is purchased from the national grid.

Australia’s new energy initiatives requires industrial entities in the country to become self-sufficient in power generation.

In addition to providing the technology for the cogeneration power plant, GE is signing an eight-year contractual service agreement.


GE LM2500+ Delivery

IDTechEx, a technology company based out of the United Kingdom, predicts that as the 3D printing technology landscape grows, so too will the variety of compatible materials. Polymer, metal, wax, sand, and concrete are a few examples currently on offer.

The technology is expanding from thermoplastics to others such as metal-matrix composites, bio-ceramics, and recycled plastics. The inventory of usable materials expands as end-users demand higher quality product materials. As knowledge spreads about the value of 3D printing, the increased adoption of additive manufacturing (AM) seems more present.


The 3D Printing Materials Landscape. Source: IDTechEx

Polymers are the face of the AM materials market. They are the most widely used and recognizable materials for 3D printing. This creates the perception that polymer 3D printing is only suitable for applications like prototyping. Newer, higher-performing polymers are changing this view.


One such polymer is fiber-reinforced polymer matrix composites (FRPs). Research into carbon fiber opens the gateway for complex composite parts. Beyond composites are high-temperature thermoplastics. Other polymers garnering interest include foams, recycled plastics, bio-based polymers, and nanocarbons. These developments indicate a shift to the face of AM materials.

Powders are the dominant feedstock in metal AM. One lower-cost alternative is metal wire. Another is metal injection molding pellets, which have more efficient extrusion properties. Lastly, bound metal paste is seeing some traction as a safer alternative to powder. These emerging feedstocks will likely lead to continued growth in 3D printing materials.

To view the full IDTechEx 3D Printing Materials Market 2022-2032 report, please visit: https://www.idtechex.com/en/research-report/3d-printing-materials-market-2022-2032/873

IDTechEx releases 2022-2032 market report

3D Printing Materials Growth

As part of their Digital Proximity System (DPS), Metrix is now offering a new phase trigger once-per-turn marker solution. In installations with a faulty once per turn phase marker, the vibration monitoring system is rendered virtually useless. The recently developed DPS enables the repair of faulty once-per-turn phase markers, without the need to shut down and open up the machine. This helps to avoid unscheduled downtime, or extensions of downtime on startup. 

Operationally, the speed system works at up to four pulses at 100,000 rpm, or 400,000 pulses per minute. The DPS can be used to gain the scale factor, in order to obtain an adequate pulse for the vibration monitoring system to report correct phase and speed values. This speed adjustment feature is included with the free DPS software.

Featured Content