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The unstretched laminar flame speed (LFS) plays a key role in engine models and predictions of flame propagation. It is also an essential parameter in the study of turbulent combustion and can be directly used in many turbulent combustion models. Therefore, it is important to predict the laminar flame speed accurately and efficiently. Two improved correlations for the unstretched laminar flame speed, namely improved power law and improved Arrhenius form correlations, are proposed for iso-octane/air mixtures in this study, using simulated results for typical operating conditions for spark-ignition engines: unburned temperatures of 300-950 K, pressures of 1-120 bar, and equivalence ratios of 0.6-1.5. The original data points used to develop the new correlations were obtained using the detailed combustion kinetics for iso-octane from Lawrence Livermore National Laboratory (LLNL). The three coefficients in the improved power law correlation were determined using a methodology different from previous approaches. The improved Arrhenius form correlation employs a function of unburned gas temperature to replace the flame temperature, making the expression briefer and making the coefficients easier to calculate. The improved Arrhenius method is able to predict the trends and the values of laminar flame speed with improved accuracy over a larger range of operating conditions. The improved power law method also works well but for a relatively narrow range of predictions. The improved Arrhenius method is recommended, considering its overall fitting error was only half of that using the improved power law correlation and it was closer to the experimental measurements. Even though ϕm, the equivalence ratio at which the laminar flame speed reaches its maximum, is not monotonic with pressure, this dependence is still included, since it produces least-rich best torque (LBT). The comparisons between the improved correlations in this study and the experimental measurements and the other correlations from various researchers are shown as well. 

Two improved correlations for the laminar flame speed, an improved power law correlation and an improved Arrhenius form correlation, are proposed for iso-octane in this study based on CONVERGE one-dimensional simulation results using the LLNL reaction mechanism. The typical working conditions for a spark-ignition engine, 300-950 K for unburned temperature, 1-120 bar for pressure, and 0.6-1.5 for equivalence ratio, were chosen to generate the results. Each of the two improved correlations has three parameters to be determined and these parameters are all shown as simple functions of equivalence ratio. The predicted unstretched laminar flame speeds using these two correlations were compared with the experimental measurements and with correlations from other researchers. In summary, both improved correlations, using simple and workable expressions, were able to predict the trends and the values of the unstretched laminar flame speed with improved accuracy. The improved Arrhenius form was more accurate and presented good predictions over a large range of operating conditions, and therefore is recommended for practical calculations and predictions. 

This poster presents our first steps to define a roadmap to robust science for high-throughput applications used in scientific discovery. These applications combine multiple components into increasingly complex multi-modal workflows that are often executed in concert on heterogeneous systems. The increasing complexity hinders the ability of scientists to generate robust science (i.e., ensuring performance scalability in space and time; trust in technology, people, and infrastructures; and reproducible or confirmable research). Scientists must withstand and overcome adverse conditions such as heterogeneous and unreliable architectures at all scales (including extreme scale), rigorous testing under uncertainties, unexplainable algorithms in machine learning, and black-box methods. This poster presents findings and recommendations to build a roadmap to overcome these challenges and enable robust science. The data was collected from an international community of scientists during a virtual world cafe in February 2021 

Scientists using the high-throughput computing (HTC) paradigm for scientific discovery rely on complex software systems and heterogeneous architectures that must deliver robust science (i.e., ensuring performance scalability in space and time; trust in technology, people, and infrastructures; and reproducible or confirmable research). Developers must overcome a variety of obstacles to pursue workflow interoperability, identify tools and libraries for robust science, port codes across different architectures, and establish trust in non-deterministic results. This poster presents recommendations to build a roadmap to overcome these challenges and enable robust science for HTC applications and workflows. The findings were collected from an international community of software developers during a Virtual World Cafe in May 2021. 

Neurological difficulties commonly accompany individuals suffering from congenital disorders of glycosylation, resulting from defects in the N-glycosylation pathway. Vacant N-glycosylation sites (N220 and N229) of Kv3, voltage-gated K+ channels of high-firing neurons, deeply perturb channel activity in neuroblastoma (NB) cells. Here we examined neuron development, localization, and activity of Kv3 channels in wildtype AB zebrafish and CRISPR/Cas9 engineered NB cells, due to perturbations in N-glycosylation processing of Kv3.1b. We showed that caudal primary (CaP) motor neurons of zebrafish spinal cord transiently expressing fully glycosylated (WT) Kv3.1b have stereotypical morphology, while CaP neurons expressing partially glycosylated (N220Q) Kv3.1b showed severe maldevelopment with incomplete axonal branching and extension around the ventral musculature. Consequently, larvae expressing N220Q in CaP neurons had impaired swimming locomotor activity. We showed that replacement of complex N-glycans with oligomannose attached to Kv3.1b and at cell surface lessened Kv3.1b dispersal to outgrowths by altering the number, size, and density of Kv3.1b-containing particles in membranes of rat neuroblastoma cells. Opening and closing rates were slowed in Kv3 channels containing Kv3.1b with oligomannose, instead of complex N-glycans, which suggested a reduction in the intrinsic dynamics of the Kv3.1b α-subunit. Thus, N-glycosylation processing of Kv3.1b regulates neuronal development and excitability, thereby controlling motor activity.