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This study investigates the representations of white ethnic identities in Non-Summit, a Korean television show, to disaggregate the generalized perception of homogenous whiteness and argue for a dialectical construction of white power and domination in Korea. Specifically, it focuses on representations of Russianness in Non-Summit in relation to the US Americanness, contextualized within post-Cold War and globalized cultural politics prevalent in Korea. Employing critical textual analysis, this study analyzes verbal and visual discourses constructing Russianness and US Americanness in Non-Summit. The findings suggest, in Non-Summit, Russianness is represented as ideologically and culturally deprived, and it appears as a dispossessed white identity that does not earn hegemony like US Americanness. At times, the marginal representations of Russianness seem to weaken the power of whiteness operating in and through the show. However, an encompassing global white supremacy remains intact when Russianness is fit into the category of whiteness through a re-whitening process. [ABSTRACT FROM AUTHOR]

Designing alternative fuels for advanced compression ignition engines necessitates a predictive model for cetane number (CN). In this study, the physics-informed graph neural networks are introduced for a reliable CN prediction by considering molecular features pertinent to the physical properties of molecules that affect CN. The reliability of measured data is another key factor to consider for improving the predictive model. Various experimental instruments for measuring CN exist, including standard and non-standard methods. In this regard, a systematic data quality analysis was carried out for the total 630 CNs collected from literature and new measurements in this study using Advanced Fuel Ignition Delay Analyzer (AFIDA). The results from this data curation process were reflected in the model by imposing lower sample weights on the data coming from less reliable measurement techniques. This approach effectively maximized the prediction accuracy while incorporating data from all available sources. Using the sample weights decreased the mean absolute error (MAE) up to 0.8 CN units. The accuracy was also improved by introducing the CN-related physical properties (the number of hydrogen bond donors and acceptors); the test set MAE is 5.74 and 7.01 for the model with and without such properties, respectively. Investigating molecular structural effects on CN was also carried out to gain chemical insights into factors used to design new fuel candidates. The dimensionality reduction analysis of feature vectors showed a clear clustering in terms of functional groups and CN and the structural effect derived from the model was consistent with the physicochemical insights. This physics-informed model and data curation would be helpful for accurate CN prediction and inform rational fuel design. [ABSTRACT FROM AUTHOR]

The high ϕ -sensitivity (η) of ignition delay time (τ IDT) is one of the desirable fuel properties for the high-load extension of advanced compression ignition engine. Recent studies revealed the effectiveness of a high dilution rate (x D) for enhancing η at the engine-relevant conditions. This study aims to quantify the effect of dilution on the η of isooctane using a combined experiment-simulation approach. The ignition delay of the isooctane/air mixture was measured with an Advanced Fuel Ignition Delay Analyzer (AFIDA) over the temperature range of 623 – 923 K at 10 bar pressure with global ϕ = 0.3 – 0.6, with and without 28.6% of additional N 2 dilution. For precise evaluation of experimental η , the facility effect of the AFIDA experiment was characterized with three-dimensional computational fluid dynamics (3-D CFD) simulation. The temperature in the combustion chamber from 3-D CFD indicated a substantial temporal dependency, varying up to ∼52 K by charge-cooling of fuel injection and heat transfer from the wall. We introduced the dimensionless number θ(t) for characterizing the temporal profile of chamber temperature. Consideration of the facility effect using θ(t) resulted in better agreement between the experimental η and zero-dimensional (0-D) kinetics simulation. The refined η were then further utilized to quantify the effectiveness of dilution to η. The extent of η enhancement with dilution strategy was maximized at the low-temperature chemistry regime, increasing η by 77% with a 28.6% dilution rate. Further analysis on the dilution effect was carried out using 0-D kinetics simulation, revealing the critical dimensionless numbers relevant to the effectiveness of dilution to η enhancement. This study is the first experiment-simulation combined research to quantify the effect of dilution on η , facilitating the kinetics model refinement for better reproduction of ϕ -sensitivity. [ABSTRACT FROM AUTHOR]