An LES turbulent inflow generator using a recycling and rescaling method

The present paper describes a recycling and rescaling method for generating turbulent inflow conditions for Large Eddy Simulation. The method is first validated by simulating a turbulent boundary layer and a turbulent mixing layer. It is demonstrated that, with input specification of mean velocities and turbulence rms levels (normal stresses) only, it can produce realistic and self-consistent turbulence structures. Comparison of shear stress and integral length scale indicates the success of the method in generating turbulent 1-point and 2-point correlations not specified in the input data. With the turbulent inlet conditions generated by this method, the growth rate of the turbulent boundary/mixing layer is properly predicted. Furthermore, the method can be used for the more complex inlet boundary flow types commonly found in industrial applications, which is demonstrated by generating non-equilibrium turbulent inflow and spanwise inhomogeneous inflow. As a final illustration of the benefits brought by this approach, a droplet-laden mixing layer is simulated. The dispersion of droplets in the near-field immediately downstream of the splitter plate trailing edge where the turbulent mixing layer begins is accurately reproduced due to the realistic turbulent structures captured by the recycling/rescaling method

Prediction Enhancement of Residue Real-Value Relative Accessible Surface Area in Transmembrane Helical Proteins by Solving the Output Preference Problem of Machine Learning-Based Predictors

The α-helical transmembrane proteins constitute 25% of the entire human proteome space and are difficult targets in high-resolution wet-lab structural studies, calling for accurate computational predictors. We present a novel sequence-based method called MemBrain-Rasa to predict relative solvent accessibility surface area (rASA) from primary sequences. MemBrain-Rasa features by an ensemble prediction protocol composed of a statistical machine-learning engine, which is trained in the sequential feature space, and a segment template similarity-based engine, which is constructed with solved structures and sequence alignment. We locally constructed a comprehensive database of residue relative solvent accessibility surface area from the solved protein 3D structures in the PDB database. It is searched against for segment templates that are expected to be structurally similar to the query sequence’s segments. The segment template-based prediction is then fused with the support vector regression outputs using knowledge rules. Our experiments show that pure machine learning output cannot cover the entire rASA solution space and will have a serious prediction preference problem due to the relatively small size of membrane protein structures that can be used as the training samples. The template-based engine solves this problem very well, resulting in significant improvement of the prediction performance. MemBrain-Rasa achieves a Pearson correlation coefficient of 0.733 and mean absolute error of 13.593 on the benchmark dataset, which are 26.4% and 26.1% better than existing predictors. MemBrain-Rasa represents a new progress in structure modeling of α-helical transmembrane proteins. MemBrain-Rasa is available at www.csbio.sjtu.edu.cn/bioinf/MemBrain/

π⁺–π Interactions between (Hetero)aromatic Amine Cations and the Graphitic Surfaces of Pyrogenic Carbonaceous Materials

Many organic compounds of environmental concern contain amine groups that are positively charged at environmental pH. Here we present evidence that (hetero)­aromatic amine cations can act as π acceptors in forming π⁺–π electron donor–acceptor (EDA) interactions with the π electron-rich, polyaromatic surface of pyrogenic carbonaceous materials (PCMs) (i.e., biochar, black carbon, and graphene). The π⁺–π EDA interactions combine a cation−π force with a π–π EDA force resulting from charge polarization of the ring’s quadrupole. Adsorption on a biochar and reference adsorbent graphite was conducted of triazine herbicides, substituted anilines, heterocyclic aromatic amines, and other amines whose charge is insulated from the aromatic ring. When normalized for the hydrophobic effect, the adsorption increased with decreasing pH as the amines became ionized, even on graphite that had no significant fixed or variable charge. The cationic π acceptor (quinolinium ion) was competitively displaced more effectively by the π acceptor 2,4-dinitrobenzene than by the π donor naphthalene. The maximum electrostatic potential of organocations computed with density functional theory was found to be a strong predictor of the π⁺–π EDA interaction. The π⁺–π EDA interaction was disfavored by electropositive alkyl substituents and by charge delocalization into additional rings. Amines whose charge was insulated from the ring fell far out of the correlation (more positive free energy of adsorption). Identifying and characterizing this novel π⁺–π EDA interaction on PCMs will help in predicting the fate of organocations in both natural and engineered systems

Effect of Adsorption Nonlinearity on the pH–Adsorption Profile of Ionizable Organic Compounds

Solution pH is an important factor in the adsorptive behavior of ionizable organic compounds (IOCs) in many industrial, commercial, and environmental contexts. A linear speciation model (LSM) that assumes the concentration-independent adsorption of charged and neutral species is often employed to model the pH–adsorption profile (edge). Deviations from that modelincluding the shift of the adsorption edge from its expected inflection point at pH = p<i>K</i>_a and the appearance of an adsorption maximum (“hump”) near the p<i>K</i>_aare sometimes used to infer the mechanism. We investigated the adsorption of six organic acids and bases on the nonfunctionalized, extremely low variable-charge surface of graphite. Isotherms at constant pH of both charged and neutral species were usually highly nonlinear, and the adsorption edges typically showed a shift, hump, or both. We postulate that this behavior is due to the gradual extinction of the dissolved neutral or charged species as the pH approaches and then crosses the p<i>K</i>_a. This leads to an increase in the affinity of that species for the solid resulting from the inherent nonlinearity of its isotherm. The extinction of the more strongly adsorbing species mainly causes the shift, whereas the extinction of the less strongly adsorbing species gives rise to the hump. A nonlinear speciation model (NSM) based on Freundlich or Langmuir equations was employed to fit the adsorption edge. The NSM captured both the shift and the hump and was superior to the LSM. Increasing adsorption nonlinearity of the neutral species shifts the adsorption edge in the acidic direction (organic bases) or alkaline direction (organic acids), whereas increasing nonlinearity of the charged species increases the hump size. Both the shift and hump size increase as the difference in adsorption affinity between neutral and charged species decreases. The results show that the concentration dependence alone can strongly affect the shape of pH–adsorption curve and should be taken into account in future modeling

Effects of Post-Pyrolysis Air Oxidation of Biomass Chars on Adsorption of Neutral and Ionizable Compounds

This study was conducted to understand the effects of thermal air oxidation of biomass chars experienced during formation or production on their adsorptive properties toward various compounds, including five neutral nonpolar and polar compounds and seven weak acids and bases (p<i>K</i>_a = 3–5.2) selected from among industrial chemicals and the triazine and phenoxyacetic acid herbicide classes. Post-pyrolysis air oxidation (PPAO) at 400 °C of anoxically prepared wood and pecan shell chars for up to 40 min enhanced the mass-normalized adsorption at pH ∼ 7.4 of all test compounds, especially the weak acids and bases, by up to 100-fold. Both general and specific effects were identified. The general effect results from “reaming” of pores by the oxidative removal of pore wall matter and/or tarry deposits generated during the pyrolysis step. Reaming creates new surface area and enlarges nanopores, which helps relieve steric hindrance to adsorption. The specific effect results from creation of new acidic functionality that provides sites for the formation of very strong, charge-assisted hydrogen bonds (CAHB) with solutes having comparable p<i>K</i>_a. The CAHB hypothesis was supported by competition experiments and the finding that weak acid anion adsorption increased with surface carboxyl content, despite electrostatic repulsion from the growing negative charge. The results provide insight into the effects of air oxidation on pollutant retention

Supplementary Methods and Materials from Background complexity and the detectability of camouflaged targets by birds and humans

Remaining undetected is often key to survival, and camouflage is a widespread solution. However, extrinsic to the animal itself, the complexity of the background may be important. This has been shown in laboratory experiments using artificially patterned prey and backgrounds, but the mechanism remains obscure (not least because ‘complexity’ is a multifaceted concept). In this study, we determined the best predictors of detection by wild birds and human participants searching for the same cryptic targets on trees in the field. We compared detection success to metrics of background complexity and ‘visual clutter’ adapted from the human visual salience literature. For both birds and humans, the factor that explained most of the variation in detectability was the textural complexity of the tree bark as measured by a metric of feature congestion (specifically, many nearby edges in the background). For birds, this swamped any effects of colour match to the local surround, although, for humans, local luminance disparities between the target and tree became important. For both taxa, a more abstract measure of complexity, entropy, was a poorer predictor. Our results point to the common features of background complexity that affect visual search in birds and humans, and how to quantify them

An LES turbulent inflow generator using a recycling and rescaling method

The present paper describes a recycling and rescaling method for generating turbulent inflow conditions for Large Eddy Simulation. The method is first validated by simulating a turbulent boundary layer and a turbulent mixing layer. It is demonstrated that, with input specification of mean velocities and turbulence rms levels (normal stresses) only, it can produce realistic and self-consistent turbulence structures. Comparison of shear stress and integral length scale indicates the success of the method in generating turbulent 1-point and 2-point correlations not specified in the input data. With the turbulent inlet conditions generated by this method, the growth rate of the turbulent boundary/mixing layer is properly predicted. Furthermore, the method can be used for the more complex inlet boundary flow types commonly found in industrial applications, which is demonstrated by generating non-equilibrium turbulent inflow and spanwise inhomogeneous inflow. As a final illustration of the benefits brought by this approach, a droplet-laden mixing layer is simulated. The dispersion of droplets in the near-field immediately downstream of the splitter plate trailing edge where the turbulent mixing layer begins is accurately reproduced due to the realistic turbulent structures captured by the recycling/rescaling method

A robust interface method for drop formation and breakup simulation at high density ratio using an extrapolated liquid velocity

© 2016 The Authors. A two-phase flow formulation for atomisation modelling is presented, with a Coupled Level Set/Volume Of Fluid (CLSVOF) technique adopted for interface-tracking. In order to achieve stable numerical solution at high density ratios, an extrapolated liquid velocity field is constructed and used in discretisation of the momentum equations. Solution accuracy is also improved when this field is also used in the scalar (VOF and Level Set) advection equations. A divergence-free algorithm is proposed to ensure satisfaction of the continuity condition for the extrapolated liquid velocity. The density and viscosity across the interface are treated sharply as a function of the Level Set to maintain the physical discontinuity. The developed method is shown to accurately predict drop formation in low Re liquid jets and the deformation and breakup morphology of a single droplet in uniform air flow at different Weber numbers (from 3.4 to 96). The mechanism for droplet breakup is determined based on an analysis of the simulation results. The computed Rayleigh–Taylor instability wavelength extracted from the acceleration of the simulated liquid droplet agrees well with experimental measurements and theoretical analysis, confirming that Rayleigh–Taylor instability dominates single drop breakup in the Weber number range studied. Finally, the influence of liquid viscosity on droplet breakup is numerically investigated; the critical Weber number separating deformation and breakup regimes is well predicted at different Ohnesorge numbers in comparison with the experimental data