4
Additional Considerations
This chapter addresses additional key issues considered by the committee, as follows:
- State of Development Achievable by 2030
- Interrelationship Among Goals, Research Areas, and Research Topics
- Research Consortia
- Development Process
- Future Vision
STATE OF DEVELOPMENT ACHIEVABLE BY 2030
The discussion of each research topic in Chapter 2 describes the estimated state of development that could be achieved by 2030. As is the case with some other federal agencies involved in research and development (R&D), the Department of Energy (DOE) has defined technology readiness levels (TRLs) as a parameter to describe the state of development of advanced technologies and systems. DOE has defined TRLs as shown in Table 4.1.
DOE typically sponsors research through TRL 6 or, in some cases, TRL 7. It is expected that R&D of a technology through TRL 9 will not proceed unless industry funds further development as part of a product development program. Research and technology development funded by DOE is conducted primarily by DOE laboratories, industry, and academia.
As described in Chapter 3, the projected TRL for each research area would likely advance as indicated in Table 4.2 if the research were to be supported by a moderate level of funding. In some cases, a TRL is not applicable (N/A) because the research topic is focused on advancing the understanding of phenomena (e.g., combustion properties) rather than the development of technologies and systems.
TABLE 4.1 Department of Energy Technology Readiness Levels
| Relative Level of Technology Development | TRL | TRL Definition | Description |
|---|---|---|---|
| System Operations | 9 | Actual system operated over the full range of expected mission conditions | The technology is in its final form and operated under the full range of operating mission conditions. Examples include using the actual system with the full range of wastes in hot operations. |
| System Commissioning | 8 | Actual system completed and qualified through test and demonstration | The technology has been proven to work in its final form and under expected conditions. In almost all cases, this TRL represents the end of true system development. Examples include developmental testing and evaluation of the system with actual waste in hot commissioning. Supporting information includes operational procedures that are virtually complete. An Operational Readiness Review (ORR) has been successfully completed prior to the start of hot testing. |
| 7 | Full-scale, similar (prototypical) system demonstrated in relevant environment | This represents a major step up from TRL 6, requiring demonstration of an actual system prototype in a relevant environment. Examples include testing full-scale prototype in the field with a range of simulants in cold commissioning.a Supporting information includes results from the full-scale testing and analysis of the differences between the test environment, and analysis of what the experimental results mean for the eventual operating system/environment. Final design is virtually complete. | |
| Technology Demonstration | 6 | Engineering/pilot-scale, similar (prototypical) system validation in relevant environment | Engineering-scale models or prototypes are tested in a relevant environment. This represents a major step up in a technology’s demonstrated readiness. Examples include testing an engineering-scale prototypical system with a range of simulants.a Supporting information includes results from the engineering-scale testing and analysis of the differences between the engineering scale, prototypical system/environment, and analysis of what the experimental results mean for the eventual operating system/environment. TRL 6 begins true engineering development of the technology as an operational system. The major difference between TRL 5 and 6 is the step up from laboratory scale to engineering scale and the determination of scaling factors that will enable design of the operating system. The prototype should be capable of performing all the functions that will be required of the operational system. The operating environment for the testing should closely represent the actual operating environment. |
| Technology Development | 5 | Laboratory scale, similar system validation in relevant environment | The basic technological components are integrated so that the system configuration is similar to (matches) the final application in almost all respects. Examples include testing a high-fidelity, laboratory-scale system in a simulated environment with a range of simulantsa and actual waste.b Supporting information includes results from the laboratory-scale testing, analysis of the differences between the laboratory and eventual operating system/environment, and analysis of what the experimental results mean for the eventual operating system/environment. The major difference between TRL 4 and 5 is the increase in the fidelity of the system and environment to the actual application. The system tested is almost prototypical. |
| 4 | Component or system validation in laboratory environment | The basic technological components are integrated to establish that the pieces will work together. This is relatively “low fidelity” compared with the eventual system. Examples include integration of ad hoc hardware in a laboratory and testing with a range of simulants and small-scale tests on actual waste.b Supporting information includes the results of the integrated experiments and estimates of how the experimental components and experimental test results differ from the expected system performance goals. TRLs 4 to 6 represent the bridge from scientific research to engineering. TRL 4 is the first step in determining whether the individual components will work together as a system. The laboratory system will probably be a mix of on-hand equipment and a few special-purpose components that may require special handling, calibration, or alignment to get them to function. |
| Relative Level of Technology Development | TRL | TRL Definition | Description |
|---|---|---|---|
| Research to Prove Feasibility | 3 | Analytical and experimental critical function and/or characteristic proof of concept | Active research and development is initiated. This includes analytical studies and laboratory-scale studies to physically validate the analytical predictions of separate elements of the technology. Examples include components that are not yet integrated or representative tested with simulants.a Supporting information includes results of laboratory tests performed to measure parameters of interest and comparison to analytical predictions for critical subsystems. At TRL 3 the work has moved beyond the paper phase to experimental work that verifies that the concept works as expected on simulants. Components of the technology are validated, but there is no attempt to integrate the components into a complete system. Modeling and simulation may be used to complement physical experiments. |
| Basic Technology Research | 2 | Technology concept and/or application formulated | Once basic principles are observed, practical applications can be invented. Applications are speculative, and there may be no proof or detailed analysis to support the assumptions. Examples are still limited to analytic studies. Supporting information includes publications or other references that outline the application being considered and that provide analysis to support the concept. The step up from TRL 1 to TRL 2 moves the ideas from pure to applied research. Most of the work is analytical or paper studies with the emphasis on understanding the science better. Experimental work is designed to corroborate the basic scientific observations made during TRL 1 work. |
| 1 | Basic principles observed and reported | This is the lowest level of technology readiness. Scientific research begins to be translated into applied research and development. Examples might include paper studies of a technology’s basic properties or experimental work that consists mainly of observations of the physical world. Supporting information includes published research or other references that identify the principles that underlie the technology. |
a Simulants should match relevant chemical and physical properties.
b Testing with as wide a range of actual waste as practicable and consistent with waste availability, safety, as low as reasonably achievable (ALARA), cost, and area risk is highly desirable.
SOURCE: Department of Energy, 2011, Technology Readiness Assessment Guide, Office of Management, Washington, D.C., https://www.directives.doe.gov/directives-documents/400-series/0413.3-EGuide-04a/@@images/file.
INTERRELATIONSHIPS AMONG GOALS, RESEARCH AREAS, AND RESEARCH TOPICS
As noted in the Chapter 1 description of the prioritization process, the committee prioritized the goals and research topics using three selection criteria for each:
- Goals
- Performance improvement
- Technical risk
- Breadth of application
- Research topics
- Benefit
- Technical risk
- Breadth of application
The interrelationships among the goals and research topics are indicative of their breadth of application. Interrelationships among the goals are illustrated at the end of Chapter 2. Interrelationships among the research areas are illustrated in Chapter 3 in the discussion of each research area, and they are summarized at the end of Chapter 3. The key interrelationships between the goals and the research topics (and, by implication, the research areas) are shown in Table 4.3.
TABLE 4.2 Advances in Technology Readiness Level
| Research Areas and Topics | Change in TRL |
|---|---|
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N/A |
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TRL 1 to TRL 6 |
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TRL 2 to TRL 7 |
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TRL 3 to TRL 6 |
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TRL 3 to TRL 6 |
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TRL 1–3 to TRL 4–9b |
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TRL 4 to TRL 6 |
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TRL 3 to TRL 6 |
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TRL 4 to TRL 7 |
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TRL 1 to TRL 6 |
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N/A |
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N/A |
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TRL 2 to TRL 6 |
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TRL 2 to TRL 6 |
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TRL 4 to TRL 7 |
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TRL 3 to TRL 6 |
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TRL 1 to TRL 3 |
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TRL 3 to TRL 6 |
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TRL 3 to TRL 6 |
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TRL 3 to TRL 7 |
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TRL 3 to TRL 7 |
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TRL 3 to TRL 8 |
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TRL 3 to TRL 6 |
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TRL 1 to TRL 8 |
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TRL 3 to TRL 6 |
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TRL 3 to TRL 7 |
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TRL 3 to TRL 8a |
a TRL 8 is achievable for fuel mixtures with up to 50 percent hydrogen. For fuel mixtures substantially in excess of 50 percent hydrogen, TRL 6 is a more realistic goal.
b The change in TRL level for research topic 2.3 varies for different alloys and applications. For more information see the Chapter 3 section, “Research Topic 2.3: Advanced Alloy Technologies.”
TABLE 4.3 Interrelationships Among the Research Topics and Goals
| Research Areas and Topics | Power Generation Goals | Aviation Goal | Oil and Gas Goals | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Efficiency | Compatibility with Renewable Energy Sources | CO2 Emissions | Fuel Flexibility | Levelized Cost of Electricity | Fuel Burn | Fuel Flexibility | CBOM | Flexible Power Demand and Efficiency | |
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X | X | X | O | X | X | |||
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X | X | X | O | X | X | X | ||
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X | X | X | X | X | X | X | X | |
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X | X | X | O | |||||
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O | O | X | O | X | ||||
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X | X | X | ||||||
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X | X | |||||||
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X | O | X | X | |||||
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X | O | O | X | X | ||||
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X | X | X | O | |||||
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X | X | X | O | |||||
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X | X | X | ||||||
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X | O | X | X | |||||
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X | X | X | X | X | X | |||
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O | O | X | O | X | ||||
| Research Areas and Topics | Power Generation Goals | Aviation Goal | Oil and Gas Goals | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Efficiency | Compatibility with Renewable Energy Sources | CO2 Emissions | Fuel Flexibility | Levelized Cost of Electricity | Fuel Burn | Fuel Flexibility | CBOM | Flexible Power Demand and Efficiency | |
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X | X | |||||||
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O | X | X | X | X | X | X | ||
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O | X | X | ||||||
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X | X | X | O | |||||
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X | X | |||||||
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X | O | O | O | O | O | |||
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O | O | O | O | X | ||||
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O | X | O | O | |||||
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O | X | O | X | O | ||||
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O | X | O | ||||||
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O | X | X | X | |||||
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X | X | X | ||||||
NOTE: Goals in green are most closely related to efficiency, and the goals in blue are most closely related to fuel flexibility. An “X” indicates that the accomplishment of a particular research area would make a major contribution to achieving the indicated goal. An “O” indicates that a research area would make a less important but still substantial contribution.
RESEARCH CONSORTIA
A few of the high-priority research areas identified by the study committee would benefit from consortia that include efforts from academia, industry, and government. These consortia could (1) address precompetitive research and (2) collaborate on the development of complex or expensive facilities that would be difficult to reproduce at many laboratories. Complex issues that are best addressed by researchers with a wide range of expertise include the development of sensors that would be precompetitive, high-fidelity simulations for operations in particle-laden environments that would require complex facilities, development of advanced high-temperature structural material and coatings that require a range of expertise, and coordination of experiments to inform unresolved physics models in numerical simulations that would range from precompetitive research to that needing complex facilities. Areas that would benefit from coordination on complex or expensive facilities would include combustion and heat transfer.
As noted in Chapter 3, in the section “Research Area 8: Condition-Based Operations and Maintenance,” sensor development for gas turbines must meet demanding temperature and pressure constraints associated with the harsh internal environments of gas turbines. There is an existing group of experts working on precompetitive research known as the Propulsion Instrumentation Working Group. This group provides a forum for all organizations involved with gas turbines to collaboratively discuss instrumentation, sensors, measurement systems, and standards. Domestic original equipment manufacturers (OEMs) of gas turbines for aviation and power generation work together through a teaming arrangement to advance sensors. Continuing and even strengthening the research portfolio of this group could potentially create new opportunities to embed wireless sensors in gas turbines.
The cleanliness of the environment in which gas turbines operate has a large impact on their performance. As discussed in Chapter 3, in the section “Research Topic 4.3: Fundamental Physics and Modeling in Particle-Laden Flows,” a range of contaminates are of interest. Existing models are unable to predict how particle-laden environments affect turbine operations or to identify those designs that are less sensitive to particle-laden environments. Even the simplest of test cases do not exist, which also causes a wide divide between experimental test cases matched with numerical predictions that could lead to reasonable predictions of particle deposition under harsh conditions. A consortium composed of experimentalists, modelers, and turbine manufacturers is needed to define test cases ranging from simple to complex. A closely coordinated effort is needed to fully understand the relevant parameters and physics of particle ingestion.
The DOE University Turbine Systems Research program is an example of an effective federal program that builds tight coupling between academics and industry to research problems of interest for advanced, high-efficiency gas turbine development. Other excellent examples of consortia that have been implemented are funded areas through the Department of Defense (DoD) Multidisciplinary University Research Initiative (MURI) program. The Office of Naval Research has funded a MURI on thermal barrier coatings and on high-temperature corrosion, while the U.S. Air Force has funded a MURI on facilitating access to materials data.
FINDING: Research consortia can be useful in addressing interdisciplinary issues in coordinating the work of multiple academic institutions and other research organizations, each of which working individually cannot together provide the critical mass to address complex problems adequately, especially in cases when expensive research facilities are needed.
DEVELOPMENT PROCESS
The speed of product innovation in many industries is rapidly increasing. Gas turbine development may need to follow the same trends to remain competitive over the long term. Advanced development processes to incorporate new methodologies and technologies to reduce research portfolio risks, improve agility, and develop an environment of fast prototyping are required to increase the speed of gas turbine product innovation.1 Accelerating the development process will involve investing in risky research programs. Such programs could focus on new combustor concepts, new gas turbine architectures, or the validation and economic viability assessments of new
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1 Agility refers to the ability of a research program to change direction as the program proceeds based on interim research results or other factors.
power plant cycles. Validation of research programs as early as possible would facilitate fast learning. Potential solutions include validating new technologies using small-scale microturbines, fast prototyping, and fast scaling. Use of additive manufacturing could be leveraged to validate research. This approach could accelerate the overall development cycle time, produce faster feedback on technical feasibility and economic viability, and reduce development risk of advanced gas turbines.
Gas turbine R&D organizations would benefit by defining an overarching mode of operation for their sponsored research programs similar to that utilized in the electronic industry. This overarching architecture will include software programs from all engineering disciplines (geometry definition, analysis, and manufacturing) that communicate seamlessly across the organization so that developmental hardware can be obtained quickly and cheaply. Utilization of additive manufacturing to produce concept hardware for small gas turbines to validate a technology concept before scaling the technology prototype hardware of the concept to full-size gas turbines would round out this architecture.
Developing new generations of gas turbine designs and hardware will necessarily take longer than developing new generations of computers and other electronic devices. Even so, the same top-down architecture described above and the advent of additive manufacturing for high-temperature alloys can revolutionize the time and cost of developing gas turbine technology and product. Furthermore, this approach would greatly facilitate the coordination and integration of research programs so that they are more agile and can proceed at a faster pace.
FUTURE VISION
If the recommended research is completed successfully, the vision is for 2030 gas turbine technology that enables remarkable advances in electrical power generation, commercial and military aviation, and oil and gas production. Continued investment in gas turbine technologies will ensure that gas turbines remain as the product of choice for applications for which they are well suited (i.e., for applications that demand high operating efficiency, power density, reliability, low levels of harmful emissions, and safety). R&D can also improve capabilities of increasing importance, such as high efficiency at partial load for single and combined cycle gas turbines with a wide range of power ratings; seamless integration into electrical grids with solar, wind, and hydroelectric renewable energy sources and energy storage systems; reliable generation of power over a wide range of transient operating conditions; and the ability to use fuels such as drop-in hydrocarbons and hydrogen that are produced by renewable energy sources. The design cycles for new gas turbines will be accelerated through a combination of advanced physics-based computational modeling capabilities enabled by high-performance computing architectures, advanced sensors, and emerging data science tools. New manufacturing technologies such as laser- and electron-beam-based additive manufacturing will enable new performance-enhancing designs and implementation of high-temperature materials and coatings critical to advanced designs. The expanded suite of gas turbines, supported by their digital twins, will operate predictably over their lifetimes with extended overhaul and maintenance cycles that maximize operational capabilities. Investment at the present is critically important, as those organizations that integrate and leverage emerging computational, experimental, informatics, and additive manufacturing approaches will be the future industry leaders.
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