Laboratory Investigation of Active Graphite Nitridation by Atomic Nitrogen

Zhang, Lunig; Pejaković, Dušan A.; Marschall, Jochen; Fletcher, Douglas G.

doi:10.2514/6.2009-4251

Cited by 5 publications

(16 citation statements)

References 17 publications

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“…In this work, we consider an experiment for the nitridation of graphite conducted by Zhang et al (2009). The main objective of the experiment is to measure the reaction rate of the graphite with active nitrogen.…”

Section: Introductionmentioning

confidence: 99%

“…The main parameter of interest is the reaction probability of the graphite nitridation reaction. The values of this quantity presented in the literature (Park and Bogdanoff (2006), Goldstein (1964), Suzuki et al (2008), Zhang et al (2009) In Section 2 the problem of optimal experimental design is described in the Bayesian framework. The experimental setup for the nitridation of graphite is detailed in Section 3, followed by the model description in Section 4.…”

Section: Introductionmentioning

confidence: 99%

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Bayesian experimental design for the active nitridation of graphite by atomic nitrogen

Terejanu

Upadhyay

Miki

2012

Experimental Thermal and Fluid Science

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The problem of optimal data collection to efficiently learn the model parameters of a graphite nitridation experiment is studied in the context of Bayesian analysis using both synthetic and real experimental data. The paper emphasizes that the optimal design can be obtained as a result of an information theoretic sensitivity analysis. Thus, the preferred design is where the statistical dependence between the model parameters and observables is the highest possible. In this paper, the statistical dependence between random variables is quantified by mutual information and estimated using a k nearest neighbor based approximation. It is shown, that by monitoring the inference process via measures such as entropy or Kullback-Leibler divergence, one can determine when to stop the data collection process. The methodology is applied to select the most informative designs on both a simulated data set and on an experimental data set, previously published in the literature. It is also shown that the sequential Bayesian analysis used in the experimental design can also be useful in detecting conflicting information between measurements and model predictions.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Bayesian experimental design for the active nitridation of graphite by atomic nitrogen

Terejanu

Upadhyay

Miki

2012

Experimental Thermal and Fluid Science

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“…The nitridation efficiency was also later measured by Park and Bogdanoff [53] and found to be γ N = 0.3 at both 300 and 1100 K. This value has been contradicted by a number of more recent studies [54][55][56]75] that found the nitridation efficiency to be around 10 −3 with a weak temperature dependence. Due to the importance of the nitridation process on surface heat transfer and ablation, further experiments and model validation are required to reduce uncertainties.…”

Section: Introductionmentioning

confidence: 89%

“…Further measurements at low surface temperatures were made by Zhang et al [56], using a microwave discharge heated flow in a furnace-heated quartz tube. Nitridation efficiency was derived from the graphite mass loss over time and the interpolated N concentration at the sample location, based on the measured concentrations entering and leaving the reactor.…”

Section: Nitridationmentioning

confidence: 99%

“…The measured γ N varied from 3 ×10 −3 at 2140 K to 0.81-1.25 ×10 −3 at 2575 K. To the author's knowledge, this is the highest surface temperature for which nitridation efficiency has been measured. Helber et al [57] created the summary plot shown in Figure 2.6 of all current experimental measurements of γ N , based on a previous plot by Zhang et al [56]. It is clear that there is much discrepancy between the limited number of measurements found in the literature.…”

Section: Nitridationmentioning

confidence: 99%

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Hypervelocity shock layer emission spectroscopy with high temperature ablating models

Lewis¹

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During reentry into the atmosphere, a vehicle can encounter extreme convective and possibly radiative heating loads. Such spacecraft must rely on a carefully designed thermal protection system to maintain the integrity of the underlying structure, thus ensuring the survival of any cargo or crew it may contain. Despite many past developments and research efforts, to this day there remain large uncertainties associated with the prediction of heat shield performance. In particular, accurate modelling of ablation phenomena is critical to minimising uncertainties, reducing excess weight, and increasing safety. This includes thermochemical ablation by oxidation, nitridation, and sublimation, as well as the mechanical removal of material via spallation. Due to the high costs associated with in-flight testing, and the difficulty of mounting precision instruments and advanced diagnostics on flight vehicles, ground-based experiments stand as a cost-effective method for reducing modelling uncertainties.Ablation testing is generally conducted in long-duration facilities such as arc jets, which are well suited to investigating in-depth material response due to their ability to provide representative heating rates for extended periods. They are, however, unable to reproduce a realistic in-flight shock layer due to low Reynolds numbers and, depending on the facility type, a high degree of thermal and chemical nonequilibrium in the free-stream. In contrast, impulse facilities such as shock tubes and their variants are well suited to reproducing realistic flight conditions with free-streams that are a closer match for flows dominated by binary processes in terms of Reynolds number, temperature, and chemical composition. Due to their extremely short test times, however, ranging from the order of 10 µs to several milliseconds, they are unable to aerothermally heat test models up to representative in-flight temperatures, or recreate the quasi-steady heat and mass flux balance of flight. This key limitation of impulse facilities was recently overcome in experiments using the University of Queensland's X2 expansion tunnel by electrically pre-heating samples to temperatures approaching 2500 K immediately prior to a test.In this work, the pre-heating methodology was enhanced to generate maximum surface temperatures approaching 3300 K in order to study sublimation phenomena. It was found that although sublimation-regime temperatures could be achieved, the relevant surface processes themselves were suppressed due to the high pitot pressures of the conditions used. Instead, the nitridation process was studied by observing air shock layer CN emissions with pure graphite models heated to surface temperatures ranging from 1770-3300 K. These results were compared with numerical simulations which predicted a monotonic increase of emissions with surface temperature for all models considered, whereas the experiments showed an initial increase from 1770-2500 K and then remained relatively constant from 2500-3300 K. The simulations also su...

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Uncertainty quantification of a graphite nitridation experiment using a Bayesian approach

Upadhyay

Miki

Ezekoye

et al. 2011

Experimental Thermal and Fluid Science

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Laboratory Investigation of Active Graphite Nitridation by Atomic Nitrogen

Cited by 5 publications

References 17 publications

Bayesian experimental design for the active nitridation of graphite by atomic nitrogen

Bayesian experimental design for the active nitridation of graphite by atomic nitrogen

Hypervelocity shock layer emission spectroscopy with high temperature ablating models

Uncertainty quantification of a graphite nitridation experiment using a Bayesian approach

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