Challenges With Measuring Supercritical CO2 Compressor Performance When Approaching the Liquid-Vapor Dome

A team led by General Electric Research (GER) and Southwest Research Institute (SwRI) was tasked to design, build and test an advanced 4MW CO2 compressor that would operate near the liquid-vapor dome for Carbon Dioxide (CO2). The US Department of Energy (DoE) Solar Technologies Office (SETO) funded program was targeted towards a Concentrated Solar Power (CSP) plant where optimum power cycle efficiency can be obtained when operated close to the liquid-vapor dome where CO2 is a supercritical fluid (sCO2) as compression power is reduced in the main compressor. However, the CSP cycle and other related supercritical CO2 cycles (fossil, nuclear, waste heat recovery) have considerable compression challenges both mechanically and aerodynamically when operating with a high density fluid that exceeds 70% the density of water. The subject of this paper is highlighting the challenge in determining compressor performance using industry standard measurements. This application is the highest density industrial-scale centrifugal compressor in the world at 720 kg/m3. This paper will investigate the uncertainty when measuring compressor efficiency using ASME PTC-10 instrumentation and the effect of the strong CO2 property variation when operating as a supercritical fluid, near the fluid-vapor dome. Prior work in this area by Wahl will be summarized and compared with the current compressor test program uncertainty. It will be shown that Wahl predicted high uncertainty as well although, the current testing program is even closer to the liquid-vapor dome than the test program under Wahl. The uncertainty analysis has shown that traditional PTC-10 temperature measurements lead to high levels of uncertainty for sCO2 compression near the liquid-vapor dome. The uncertainty is driven by the large changes in thermodynamic properties of sCO2. These property changes are affected by the measured pressure and temperature; however, temperature measurement error is the primary contributor to uncertainty. Because of this, looking at alternate sCO2 property measurements was investigated. Higher quality localized pressure calibration, improving flow measurement accuracy, and measuring density in addition to temperature all significantly improved efficiency uncertainty. The authors confirmed the most significant measurement change is to measure pressure and density through either a densitometer or a Coriolis flow meter which provides a density measurement in conjunction with flow rate accuracy.

Design of 1 MW Direct-Fired Combustor for an sCO2 Power Cycle

Direct-fired super-critical carbon dioxide (sCO2) power cycles, are a potential method for efficiently capturing nearly all of the CO2 emissions from burning fossil fuels. Direct-fired sCO2 cycles require a very high degree of recuperation, which in turn means that the inlet temperature to the combustor is significantly higher than would typically be seen in a similar gas turbine combustors. Previous efforts have shown that combustor inlet temperatures of around 700 °C are to be expected for a cycle with around 1200 °C combustor exit temperatures [1]. This high inlet temperature means that bypass gasses are extremely hot, which poses some difficulties for the design of the combustion system, especially thermal management of the combustor liner and injectors in the 200 bar sCO2 environment. The project team led by Southwest Research Institute (SwRI) is in the process of building a 1 MW scale direct-fired combustor. This paper will detail some of the design challenges and obstacles associated with designing a direct-fired sCO2 combustor. These obstacles include thermal management of fuel and oxygen streams, oxygen safety, and combustor cooling. This paper will focus on many of the design questions necessary for the design of a direct-fired sCO2 combustor. This work presents computational modeling details of the actual 1 MW geometry currently being built.

Modeling and Testing of a Novel Ultra-Low Temperature sCO2 Opposing Piston Expander

Southwest Research Institute (SwRI) along with Thermal Tech Holdings (TTH) have modeled, built, and tested a piston expander for generating power from low temperature heat sources. The piston was developed with the goal of creating an engine that operates as a recuperated sCO2 Ericsson cycle. A cycle model based on fluid properties from REFPROP is applied for various hot and cold temperatures to demonstrate the potential of the novel expander to improve cycle efficiency. Cycle modeling results demonstrate the potential improvements in cycle efficiency when compared to the sCO2 Brayton cycle. Small-scale bench testing is used to validate the novel piston concept for achieving a sCO2 Ericsson cycle. The concept is scaled up to a full-sized, opposing piston cylinder that acts as an expander in the theoretical Ericsson cycle. Testing is performed on the full-scale piston cylinder for a variety of inlet temperatures and pressures. The full-scale tests are run continuously to track the transient effects. The results of the full-scale test are discussed. The expander piston cylinder test results show high temperatures at the outlet, better than the ideal sCO2 Brayton cycle, but less than an ideal recuperated sCO2 Ericsson cycle. Comparisons are made to demonstrate the projected cycle efficiency improvements over a sCO2 Brayton cycle.

The STEP 10 MWe sCO2 Pilot Demonstration Status Update

The Gas Technology Institute (GTI®), Southwest Research Institute® (SwRI®) and General Electric Global Research (GEGR) are executing the “STEP” [Supercritical Transformational Electric Power] project, to design, construct, commission, and operate an integrated and reconfigurable 10 MWe sCO2 [supercritical CO2] pilot plant test facility. The $122* million project is funded $84 million by the US DOE’s National Energy Technology Laboratory (NETL Award Number DE-FE0028979) and $38* million (*including building investment) by the team members, component suppliers and others interested in sCO2 technology. This paper provides an update on the project’s progress. The pilot facility is currently under construction at SwRI’s San Antonio, Texas, USA campus. Now well into Phase 2, a ground-breaking was held in October of 2018, and civil work and the construction of a dedicated 22,000 ft2 building is complete. Most major equipment is in fabrication or delivered to site. Efforts have already provided valuable project learnings for technology commercialization. This project is a significant step toward sCO2 cycle based power generation commercialization and is informing the performance, operability, and scale-up to commercial plants.

Momentum Enhancement Simulations for Hypervelocity Impacts on Sandstone

<p>Two NASA missions that will be launched in 2022 have spun renewed interest in hypervelocity impact of  rocks and metals. This work focuses on the prediction of the momentum enhancement effect, i.e. the extra momentum acquired by the target due to the ejecta flying off the target in the direction of the impactor. Predicting the momentum enhancement with simulations has been elusive, probably because the target material is rarely well characterized. This presentation shows that, given a good knowledge of the properties of the target material and, by adding two essential pieces of the physics (strength of failed material and bulking after failure), the computer simulations can provide good predictions of the momentum enhancement for hypervelocity impact tests performed at Southwest Research Institute.</p>

Development and Testing of Connected Vehicle Wrong-Way Driving Applications

The Texas A&M Transportation Institute (TTI) and Southwest Research Institute (SwRI) recently developed connected vehicle (CV) applications that detect wrong-way vehicles, warn wrong-way drivers, notify traffic management agencies and law enforcement, and alert affected travelers. The research team reviewed the state of the practice regarding intelligent transportation systems (ITS) and CV technologies being applied as wrong-way driving (WWD) countermeasures. Next, the research team identified user needs associated with the implementation of CV WWD applications, and developed a concept of operations and functional requirements for CV WWD applications. The research team then built, tested, and successfully conducted a proof-of-concept demonstration of the CV WWD applications at the Texas A&M University RELLIS Campus.

Planning for Successful Transients and Trips in a 1 MWe-Scale High-Temperature sCO2 Test Loop

Supercritical CO2 power cycles incorporate a unique combination of high fluid pressure, temperature, and density as well as limited component availability (e.g., high-temperature trip valves) that can result in operational challenges, particularly during off-design and transient operation. These conditions and various failure scenarios must be considered and addressed during the facility, component, and control system design phase in order to ensure machinery health and safety during operation. This paper discusses significant findings and resulting design/control requirements from a detailed failure modes and effects analysis (FMEA) that was performed for the 1 MWe-scale supercritical CO2 test loop at Southwest Research Institute, providing insight into design and control requirements for future test facilities and applications. The test loop incorporates a centrifugal pump, axial turboexpander, gas-fired primary heat exchanger, and microchannel recuperator for testing in a simple recuperated cycle configuration at pressures and temperatures up to 255 bar and 715 °C, respectively. The analysis considered off-design operation as well as high-impact failures of turbomachinery and loop components that may require fast shutdowns and blowdowns. The balance between fast shutdowns/blowdowns and the need to manage thermal stresses in the turbomachinery resulted in staged shutdown sequences and impacted the design/control strategies for major loop components and ancillary systems including the fill, vent, and seal supply systems.

An Advanced Surge Dynamic Model for Simulating Emergency Shutdown Events and Comparing Different Antisurge Strategies

The compressor surge is a phenomenon which has to be avoided since it implies the deterioration of performance and leads to mechanical damage to the compressor and system components. As a consequence, compression system models have a crucial role in predicting the phenomena which can occur in the compressor and pipelines during operation. In this paper, a dynamic model, developed in the matlab/simulink environment, is further implemented to allow the study of surge events caused by rapid transients, such as emergency shutdown events (ESD). The aim is to validate the model using the experimental data obtained in a single-stage centrifugal compressor installed in the test facility at Southwest Research Institute. The test facility consists of a closed loop system and is characterized by a recycling circuit, and thus a recycling valve, which is opened in case of surge or driver shutdown. Simulations were carried out at 17,800 and 19,800 rpm; the comparison with experimental data showed the accuracy of the model in simulating different opening rates and different sizes of the recycle valve, at both low and high suction pressure (HSP). Moreover, different actions for recovering/preventing surge were simulated by controlling different valves along the piping system and by adding a check valve immediately downstream the compressor. The results demonstrated the fidelity of the model and its capability of simulating piping systems with different configurations and components, also showing, qualitatively, the different effects of some alternative actions which can be taken after surge onset.

The Comparison of Aerodynamic Performance Data Acquired From Thermal Measurements and a Torquemeter on a Compressor Impeller

Full-thermal heat-soak of machinery is vital for acquiring accurate aerodynamic performance data, but this process often requires significant testing time to allow all facility components to reach a steady-state temperature. Even still, there is the potential for heat loss in a well-insulated facility, and this can lead to inaccurate results. The implementation of a torquemeter to calculate performance metrics, such as isentropic efficiency, has two potential advantages: (1) the method is not susceptible to effects due to thermal heat loss in the facility, and (2) a torquemeter directly measures actual torque, and thus work, input, which eliminates the need to fully heat-soak to measure the actual enthalpy rise of the gas. This paper presents a comparison of aerodynamic performance metrics calculated both from data acquired with thermal measurements as well as from a torquemeter. These tests were conducted over five speedlines for a shrouded impeller in the Southwest Research Institute Single Stage Test Rig facility. Isentropic efficiency calculated from the torquemeter was approximately 1–2 efficiency points lower than the isentropic efficiency based on thermal measurements. This corresponds to approximately 0.5–1 °C in heat loss in the discharge collector and piping. Furthermore, observations from three full-thermal heat-soak points indicate the significant difference in time required to reach steady-state performance within measurement uncertainty tolerances between the torque-based and thermal-based methods. This comparison, while largely suspected, has not yet been studied in previous publications.

Evaluating Optimization Strategies for Engine Simulations Using Machine Learning Emulators

This work evaluates different optimization algorithms for Computational Fluid Dynamics (CFD) simulations of engine combustion. Due to the computational expense of CFD simulations, emulators built with machine learning algorithms were used as surrogates for the optimizers. Two types of emulators were used: a Gaussian Process (GP) and a weighted variety of machine learning methods called SuperLearner (SL). The emulators were trained using a dataset of 2048 CFD simulations that were run concurrently on a supercomputer. The Design of Experiments (DOE) for the CFD runs was obtained by perturbing nine input parameters using a Monte Carlo method. The CFD simulations were of a heavy duty engine running with a low octane gasoline-like fuel at a partially premixed compression ignition mode. Ten optimization algorithms were tested, including types typically used in research applications. Each optimizer was allowed 800 function evaluations and was randomly tested 100 times. The optimizers were evaluated for the median, minimum, and maximum merits obtained in the 100 attempts. Some optimizers required more sequential evaluations, thereby resulting in longer wall clock times to reach an optimum. The best performing optimization methods were particle swarm optimization (PSO), differential evolution (DE), GENOUD (an evolutionary algorithm), and Micro-Genetic Algorithm (GA). These methods found a high median optimum as well as a reasonable minimum optimum of the 100 trials. Moreover, all of these methods were able to operate with less than 100 successive iterations, which reduced the wall clock time required in practice. Two methods were found to be effective but required a much larger number of successive iterations: the DIRECT and MALSCHAINS algorithms. A random search method that completed in a single iteration performed poorly in finding 1 Currently at Southwest Research Institute, San Antonio, Texas optimum designs, but was included to illustrate the limitation of highly concurrent search methods. The last three methods, Nelder-Mead, BOBYQA, and COBYLA, did not perform as well.