Technology readiness levels for advanced nuclear fuels and materials development

Carmack, Jon; Braase, Lori; Wigeland, R. A.; Todosow, M.

doi:10.1016/j.nucengdes.2016.11.024

Cited by 30 publications

(27 citation statements)

References 8 publications

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“…Adaptions to other technology fields have been presented, yet they mostly cover altered titles and descriptions without providing further details of the TRLs (e.g. 3,12,18 , also see Table 1). This paper targets more accurate and comprehensible TRL rating by presenting specific criteria and indicators.…”

Section: Introductionmentioning

confidence: 99%

Specifying Technology Readiness Levels for the Chemical Industry

Buchner

Stepputat

Zimmermann

et al. 2019

Ind. Eng. Chem. Res.

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Technology readiness levels (TRL) have received increasing recognition throughout academia, industry and policy-making as a tool for evaluating and communicating a technology's maturity.Conventional scales are unspecific to technologies as they aim at evaluating and comparing technologies combining different fields. Hence, they present vague descriptions which leave considerable room for interpretation and subjective choices. For the chemical industry, adaptions and specific criteria are needed for more comprehensible TRL ratings. This paper specifies the nine conventional TRLs for the chemical industry as: Idea, Concept, Proof of concept, Preliminary process development, Detailed process development, Pilot trials, Demonstration and full-scale engineering, Commissioning, and Production. Adjusted descriptions and additional criteria with detailed indicators are presented, depicting the logical progression of a typical chemical innovation in the phases of applied research, development and deployment. The specified TRLs facilitate evaluation and communication of a technology's maturity and substantially improve the basis for data availability-based assessment.Issuing institution Purpose and background of the scale US National Aeronautics and Space Administration (NASA) 2,6,7 Space technology planning as a measurement system that "supports assessments of the maturity of a particular technology and the consistent comparison of maturity between different types of technology" 2 US Department of Defense (US DoD) 13 Focus on "critical technologies" 13 , used in 'Major Defense Acquisition Programs', evaluates the degree of risk associated with each TRL and recommends mitigation measures US Department of Energy (US DoE) 8 Based on NASA and US DoD, adapted to DoE needs, incorporates scale of testing, system fidelity and environment (waste) as criteria in the description, provides appendix with questions for general TRL rating and detailed questions for critical technical elements US Department of Health and Human Services (US HHS) 9Biomedical adaption: designed for evaluating the maturity of medical countermeasure products (drugs and biologics)European Commission, horizon 2020 framework

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Section: Introductionmentioning

confidence: 99%

Specifying Technology Readiness Levels for the Chemical Industry

Buchner

Stepputat

Zimmermann

et al. 2019

Ind. Eng. Chem. Res.

View full text Add to dashboard Cite

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“…EM Class (t), CT Class (t), and UL Class (t) are separately affected by the related coefficient of technology development TD EM (t), TD CT (t), and TD UL (t). The function of technology maturity shows regularity [49]. Thus, the improvement percent of EM Class (t), CT Class (t), and UL Class (t) are separately driven by TD EM (t), TD CT (t), and TD UL (t).…”

Section: Ev Preference Factor Modulementioning

confidence: 96%

“…Thus, the improvement percent of EM Class (t), CT Class (t), and UL Class (t) are separately driven by TD EM (t), TD CT (t), and TD UL (t). TD EM (t), TD CT (t), and TD UL (t) are all set to 7% in each year [49].…”

Section: Ev Preference Factor Modulementioning

confidence: 99%

An Improved Differential Evolution Algorithm for Optimal Location of Battery Swapping Stations Considering Multi-Type Electric Vehicle Scale Evolution

Wang

Liu

et al. 2019

IEEE Access

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Scientific scale forecasting of multi-type electric vehicles (EVs) is critical to accurately analyze the planning and operation of battery-swapping stations (BSSs) and charging stations (CSs). This paper predicts the proportions of plug-in electric vehicles (PEVs), hybrid electric vehicles (HEVs), and battery-swapping electric vehicles (BSEVs) in the total EV fleet in multi-scenarios via a system dynamics (SD) method. Relying on the predicted evolution scale of the BSEVs and the service demand of BSSs calculated by the service radius (SR) method, an improved differential evolutional algorithm combing with Monte Carlo searching (IDEA-MCS) method is proposed to obtain the optimal location of BSSs in a certain region in Beijing, which achieves an economic optimum of BSSs under the battery-swapping mode (BSM) via centralized charging and unified distribution (CCAUD). The analytical results show that the proportion of the BSEVs in different scenarios is the major driver that impacts the location of BSSs. The distribution of BSSs' BS demand in the optimistic scenario is more inhomogeneous than that in the other scenarios. In addition, a cross-comparison of optimal profits in different scenarios is conducted to verify the optimality of BSS locations for a given scenario. Finally, the proposed IDEA-MCS method is compared with the DEA method and IDEA method to verify its optimality.

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“… Two average burnups at discharge were considered: 3% and 6%. For higher average burnups at discharge, peak burnups may be higher than 10%, which would be outside the preferred Technology Readiness Level (TRL) 8-9 range for the driver fuel [Carmack, 2017]. The number of cycles required to reach these burnups is calculated assuming 100-day cycles.…”

Section: Design Variablesmentioning

confidence: 99%

Scoping Analysis of Sodium Cooled Fast Spectrum Test Reactor Cores

Youinou

Bays

Palmiotti

et al. 2020

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This information was prepared as an account of work sponsored by an agency of the U.S. Government. Neither the U.S. Government nor any agency thereof, nor any of their employees, makes any warranty, expressed or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness, of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. References herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the U.S. Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the U.S. Government or any agency thereof. 9. References Appendix 1. Pressure drop correlation Appendix 2. Impact of the number of fuel pins per assembly on thermal hydraulics Appendix 3. Examples of hot channel thermal calculations Appendix 4. Review of other fast test reactors Appendix 5. Approach to determine the reactivity coefficients Appendix 6. Detailed results from parametric study Fuel (60 to 100 cm) Fission gas plenum (same height as fuel) Reflector (50 cm) Reflector (50 cm) Driver Fuel Control Rod Safety Rod Experiment Reflector Shield 4 2.2 Design Constraints for Normal Operation In order to ensure the reactor is operated safely and efficiently, the design requirements discussed in this section were considered for this trade study. These values are solely used in the scope of the trade study and may be reviewed and adjusted later.  Fuel smeared density: 75% theoretical density  The core reactivity is controlled with six primary control rods and three secondary safety rods. The rod locations are shown in Figure 2.2; these positions were arbitrarily selected to carry out the trade study and will need to be adjusted based on control and safety considerations (see Section 5.1).  Sodium inlet and outlet temperatures: 350C and 500C, i.e., representative values for sodium-cooled fast reactors. These are temperatures assumed only for this trade study. More detailed thermal and safety analyses will be required to converge on optimized values. Increasing this inlet-outlet sodium T could be beneficial to increase the fast flux level by allowing increasing power density without increasing sodium velocity.  Peak cladding temperature  650C. The peak cladding temperature is mostly dependent on the sodium outlet temperature. At this stage, no detailed thermal calculations and no orificing optimization have been performed, but based on experience, it is known that a 500C average sodium outlet temperature will ensure the peak cladding temperature requirement is met, provided the fuel assembly is properly designed.  Peak fuel temperature  1,121C for U-20Pu-10Zr and  1,248C for U-10Zr. The peak linear power assumed for this parametric study (450 W/cm, see below) should be low enough to meet this requirement with some...

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Technology readiness levels for advanced nuclear fuels and materials development

Cited by 30 publications

References 8 publications

Specifying Technology Readiness Levels for the Chemical Industry

Specifying Technology Readiness Levels for the Chemical Industry

An Improved Differential Evolution Algorithm for Optimal Location of Battery Swapping Stations Considering Multi-Type Electric Vehicle Scale Evolution

Scoping Analysis of Sodium Cooled Fast Spectrum Test Reactor Cores

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