Estimating Technology Readiness Level Coefficients

Conrow, Edmund H.

doi:10.2514/1.46753

Cited by 71 publications

(40 citation statements)

References 4 publications

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“…As the resource constraint is tightened past a critical value of the resource cost, the performance across the Pareto frontier decreases, causing regression in all three axes, and distinctive features begin to break down, as seen by Fig. 8 Ordinal TRL values and cardinal TRL cost coefficients (source: [43]). comparison between solutions with R C 195, R C 145, and R C 95.…”

Section: Results For Resource Constrained Relative-valued Objectivmentioning

confidence: 99%

“…As expected, the ordinal TRL values exhibit a linear trend when plotted. Conrow's [43] estimated cardinal coefficients suggest that for a given technology fewer resources are required to progress from a low TRL to the next, compared to advancement from a high TRL to the next. The relative magnitude between cardinal coefficients is very desirable because it addresses the otherwise implied uniformity of required resource investment for TRL advancement.…”

Section: Multi-objective Optimization With Resource Constraint Amentioning

confidence: 99%

“…However, it is characterized by an ordinal scale and thus is not conducive to meaningful mathematical operations. Conrow [43] elaborates on this issue and proposes a cardinal scale of TRL coefficients that is suitable for mathematical operations because they preserve relative comparisons between each other and relative to an absolute datum. Figure 8 illustrates the cardinal coefficients and the TRL values they approximate using this method.…”

Section: Multi-objective Optimization With Resource Constraint Amentioning

confidence: 99%

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Pareto-Optimal Aircraft Technology Study for Environmental Benefits with Multi-Objective Optimization

Jiménez

Mavris

2017

Journal of Aircraft

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The composition of an aircraft technology portfolio in response to environmental impact goals is of paramount importance for present and future aeronautics. Characteristics of the portfolio selection problem are ideally addressed via multi-objective genetic algorithm optimization. Methodological and practical considerations of this approach are examined while generating meaningful insight specific to a set of aircraft technologies expected to mature over the coming decade. Results allow for a detailed characterization of the set of Pareto-optimal technology combinations in terms of its corners, underlying performance tradeoffs, and salient topological features. High-impact technologies are resolved in terms of their pervasiveness across solutions in regions of interest. Because relativevalued environmental objectives can be exploited by the optimizer, the analysis is repeated with absolute-valued analogs to examine how the choice of objectives in this respect can affect the selection of technologies. The effect of resource costs associated with each technology, additively compounded for technology combination solutions, is also examined in this context by expanding the method to include a resource constraint. Accordingly, general features of the Pareto frontier in the objective space are characterized for varying degrees of resource constraint stringency.

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Section: Results For Resource Constrained Relative-valued Objectivmentioning

confidence: 99%

Section: Multi-objective Optimization With Resource Constraint Amentioning

confidence: 99%

Section: Multi-objective Optimization With Resource Constraint Amentioning

confidence: 99%

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Pareto-Optimal Aircraft Technology Study for Environmental Benefits with Multi-Objective Optimization

Jiménez

Mavris

2017

Journal of Aircraft

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“…TRL can also be adapted to support understanding of capabilities and resources required to develop technologies at different stages of development. Conrow (2011) provides description of the TRL stages in terms of the development adopted in NASA. The TRL stages are summarised in Table 1. There were two allocation stages to the TRL framework.…”

Section: Trl Scale Assessmentmentioning

confidence: 99%

Technology readiness level assessment of composites recycling technologies

Rybicka

Tiwari

Leeke

2016

Journal of Cleaner Production

222

114

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a b s t r a c tComposite materials made of glass and carbon fibres have revolutionised many industries. Demand for composites is experiencing rapid growth and global demand is expected to double. As demand for composites grows it is clear that waste management will become an important issue for businesses. Technically composite materials evoke difficult recycling challenges due to the heterogeneity of their composition. As current waste management practices in composites are dominated by landfilling, governments and businesses themselves foresee that this will need to change in the future. The recycling of composites will play a vital role in the future especially for the aerospace, automotive, construction and marine sectors. These industries will require different recycling options for their products based on compliance with current legislation, the business model as well as cost effectiveness. In order to be able to evaluate waste management strategies for composites, a review of recycling technologies has been conducted based on technology readiness levels and waste management hierarchy. This paper analyses 56 research projects to identify growing trends in composite recycling technologies with pyrolysis, solvolysis and mechanical grinding as the most prominent technologies. These recycling technologies attained high scores on the waste management hierarchy (either recycling or reuse applications) suggesting potential development as future viable alternatives to composite landfilling. The research concluded that recycling as a waste management strategy is most popular exploration area. It was found mechanical grinding to be most mature for glass fibre applications while pyrolysis has been most mature in the context of carbon fibre. The paper also highlights the need to understand the use of reclaimed material as important assessment element of recycling efforts. This paper contributes to the widening and systematising knowledge on maturity and understanding composites recycling technologies.

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“…In the quote GAO connects TRL and residual risk that will be carried into the program or project. US Department of Defense (DoD) have considered a TRL equal to or greater than level 6 to be a mature technology; ref (Conrow, 2009), the Science technology objective (STO), among other matures technology up to TRL 6 for further implementation in US. DoD programs (Graettinger, et al, 2002).…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Use of TRL in the systems engineering toolbox

Bakke

Haskins²

2018

INCOSE International Symp

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Technology Readiness Level (TRL) is used to evaluate the maturity of the Critical Technology Elements (CTE) in a project or program and indicates an assumed level of the remaining technical risks for each independent technology. This paper presents results of a literature review exploring the diversity of definitions applied to TRL. Survey results explore whether and how TRLs are used. Based on these results the authors assess to what degree TRL evaluations are suitable for organizations without separately trained and skilled readiness assessment personnel.

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Estimating Technology Readiness Level Coefficients

Cited by 71 publications

References 4 publications

Pareto-Optimal Aircraft Technology Study for Environmental Benefits with Multi-Objective Optimization

Pareto-Optimal Aircraft Technology Study for Environmental Benefits with Multi-Objective Optimization

Technology readiness level assessment of composites recycling technologies

Use of TRL in the systems engineering toolbox

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