Prediction of pollutants dispersion patterns around two adjacent urban road tunnels

Road tunnels have recently become prevalent in urban areas of China. In areas adjacent to these tunnels, air quality and human health are important public health concerns. As such, assessing pollutant dispersion and decay rates around tunnel portals in the surrounding environment is an important field of study. This study established a three-dimensional computational fluid dynamics (CFD) model containing two adjacent urban road tunnels, to estimate pollution dispersion characteristics outside the tunnels. The results indicate that, when pollutants were exhausted from the portals only, crossflow between the two adjacent tunnels was quite severe. The highest carbon monoxide (CO) concentration was nearly 50?ppm, exceeding the 10?ppm limit National Standard in China for 1?h exposure when exhaust shafts are absent. When shafts exhausted 80% of the pollutants from the tunnel portal, crossflow between the adjacent tunnels decreased to 10-50% of that without shafts. The simulation results demonstrate that the combination of shafts and portals was an effective and energy-saving strategy to exhaust pollution from adjacent super-long urban road tunnels. These findings increase our fundamental understanding and provide guidelines for evaluating pollutant exposure risk around tunnel portals, the design of tunnel exhaust shafts, and environmental planning purposes in urban environments.     

Atmospheric Pressure Ion Source Development: Experimental Validation of Simulated Ion Trajectories within Complex Flow and Electrical Fields

Three-dimensionally (3D) resolved ion trajectory calculations within the complex viscous flow field of an atmospheric pressure ion source are presented. The model calculations are validated with spatially resolved measurements of the relative sensitivity distribution within the source enclosure, referred to as the distribution of ion acceptance (DIA) of the mass analyzer. In previous work, we have shown that the DIA shapes as well as the maximum signal strengths strongly depend on ion source operational parameters such as gas flows and temperatures, as well as electrical field gradients established by various source electrode potentials (e.g., capillary inlet port potential and spray shield potential). In all cases studied, distinct, reproducible, and, to some extent, surprising DIA patterns were observed. We have thus attempted to model selected experimental operational source modes (called operational points) using a validated computational flow dynamics derived 3D-velocity field as an input parameter set for SIMION/SDS, along with a suite of custom software for data analysis and parameter set processing. Despite the complexity of the system, the modeling results reproduce the experimentally derived DIA unexpectedly well. It is concluded that SIMION/SDS in combination with accurate computational fluid dynamics (CFD) input data and adequate analysis software is capable of successfully modeling operational points of an atmospheric pressure ion (API) source. This approach should be very useful in the computer-aided design of future API sources.

Adapting the DeepSARM approach for dual-target ligand design

The structure–activity relationship (SAR) matrix (SARM) methodology and data structure was originally developed to extract structurally related compound series from data sets of any composition, organize these series in matrices reminiscent of R-group tables, and visualize SAR patterns. The SARM approach combines the identification of structural relationships between series of active compounds with analog design, which is facilitated by systematically exploring combinations of core structures and substituents that have not been synthesized. The SARM methodology was extended through the introduction of DeepSARM, which added deep learning and generative modeling to target-based analog design by taking compound information from related targets into account to further increase structural novelty. Herein, we present the foundations of the SARM methodology and discuss how DeepSARM modeling can be adapted for the design of compounds with dual-target activity. Generating dual-target compounds represents an equally attractive and challenging task for polypharmacology-oriented drug discovery. The DeepSARM-based approach is illustrated using a computational proof-of-concept application focusing on the design of candidate inhibitors for two prominent anti-cancer targets.

     

Modeling the Kinetics of Complex Systems: Enzymatic Hydrolysis of Lignocellulosic Substrates

Lignocellulosic biomass is mainly composed of cellulose, hemicellulose, and lignin. Fuzzy logic, in turn, is a branch of many-valued logic based on the paradigm of inference under vagueness. This paper presents a methodology, based on computational intelligence, for modeling the kinetics of a complex reactional system. The design of a fuzzy interpolator to model cellulose hydrolysis is reported, within the perspective of applying kinetic models in bioreactor engineering. Experimental data for various types of lignocellulosic materials were used to develop the interpolator. New experimental data from the enzymatic hydrolysis of a synthetic substrate, on the other hand, were used to validate the methodology. The accuracy of the results indicates that this is a promising approach to extend the application of models fitted for specific situations to different cases, thus enhancing their generality.     

A combined CFD modeling with population balance equation to predict pressure drop in venturi scrubbers

A venturi scrubber is one of the most important devices for air pollution control. Although there are different models for predicting the pressure drop in venturi scrubbers, most of them have some defects and cannot predict the pressure drop correctly. In this study, for the first time, an Eulerian–Eulerian computational fluid dynamics (CFD) model is combined with a population balance equation to predict the pressure drop in venturi scrubbers. This simulation takes into account a multiple size group model for droplet dispersion and droplet size distribution, which is based on a population balance equation. Flow field has been calculated by solving the time averaged continuity and Navier–Stokes equations along with the standard k–ε turbulence model. The equations included drag, turbulent dispersion, and buoyancy forces. The calculated pressure drop with and without considering the population balance equation was compared with the experimental data to evaluate the accuracy of the CFD modeling. The size distribution of droplets in the venturi scrubber was studied at different points for different liquid to gas ratios and throat gas velocities. The results show that the maximum break-up of droplets happens at the liquid injection point. Finally, the effects of nozzle diameter and nozzle arrangement on pressure drop in venturi scrubbers were investigated.     

Simulation of Polymer Reactors Using the Compartment Modeling Approach

A compartment modeling approach based on computational fluid dynamics (CFD) simulations is applied to a simplified static mixer geometry. Compartments are derived from velocity fields obtained from cold CFD simulations. This methodology is based on the definition of periodic flow zones (PFZ) derived from the recurrent flow profile within the static mixer. In general, PFZ can be characterized by two different compartments: flow zones with hydrodynamic behavior of a tubular reactor and dead zones exhibiting a more continuous stirred tank reactor‐like characteristic. In CFD studies the influence of changing fluid properties, for example viscosity, on flow profile due to polymerization progress is considered. In the deterministic compartment model, the continuous flow profile within the static mixer is transformed to basic reactor models interconnected via an exchange stream. To reduce model complexity and the number of model parameters, constant volumes of compartments are assumed. Changes in hydrodynamics are considered by a variable exchange flow rate as a function of Re manipulating residence time in compartments. Simulation studies show the influence of decreasing exchange flow rates with polymerization progress, as Re decreases, resulting in a greater increase of viscosity in dead zones. The reactor performance is qualitatively represented by the simulation results.     

Two-body Reduced Density Matrix Reconstruction for Van der Waals Systems

A method for the calculation of the electronic energy of a correlated system is presented. This approach is based on the reconstruction of the total two-body reduced density matrix by doing separate configurations interaction calculations on fragments. The method has been tested on Van der Waals systems and has been implemented by considering restrictive N-representability conditions. It is shown that the computational strategy presented in this work can describe with good accuracy weak dispersion interactions, and considerably lowers the size-consistency error of a classical configuration interaction calculation.     

The boundary element method: applications to steady-state voltammetric simulations within domains extending to infinity

Application of the boundary element method (BEM) to the simulation of diffusion limited electrolysis reactions occurring within an infinite domain is outlined. This article focuses on the development of procedures that permit electrolysis simulations to be performed, where only an element mesh over the electrode region is required. This approach provides significant benefits over the traditional application of BEM simulations for electrochemical-based problems. In particular the reduction in mesh points to regions only over the electrode results in simpler grid generation procedures and significantly reduced computational times. The paper describes the theory and numerical details required to develop steady-state two-dimensional diffusional models for voltammetric simulations. The accuracy and versatility of the numerical procedures are tested by examining the current density at a range of well-defined electrode geometries.     

Multiple-quantum relaxation dispersion NMR spectroscopy probing millisecond time-scale dynamics in proteins: theory and application

New relaxation dispersion experiments are presented that probe millisecond time-scale dynamical processes in proteins. The experiments measure the relaxation of (1)H-(15)N multiple-quantum coherence as a function of the rate of application of either (1)H or (15)N refocusing pulses during a constant time relaxation interval. In contrast to the dispersion profiles generated from more conventional (15)N((1)H) single-quantum relaxation experiments that depend on changes in (15)N((1)H) chemical shifts between exchanging states, (1)H-(15)N multiple-quantum dispersions are sensitive to changes in the chemical environments of both (1)H and (15)N spins. The resulting multiple-quantum relaxation dispersion profiles can, therefore, be quite different from those generated by single-quantum experiments, so that an analysis of both single- and multiple-quantum profiles together provides a powerful approach for obtaining robust measures of exchange parameters. This is particularly the case in applications to protonated proteins where other methods for studying exchange involving amide proton spins are negatively influenced by contributions from neighboring protons. The methodology is demonstrated on protonated and perdeuterated samples of a G48M mutant of the Fyn SH3 domain that exchanges between folded and unfolded states in solution.     

Third-order rate constants of atmospheric importance

Input data and results are presented for the calculation of a number of third-order rate constants of atmospheric interest using Troe′s approximate method. A comparison with experimental data indicates that this approach provides a reliable method for predicting unknown rate constants and estimating temperature dependences. These calculations form the basis of the recommendations of the NASA review panel for third-order rate constants to be used in atmospheric modeling.     

Scale-adaptive simulation of liquid mixing in an agitated vessel equipped with eccentric HE 3 impeller

The current study presents the results of a numerical simulation of hydrodynamics in an agitated vessel equipped with an eccentric HE 3 impeller. CFD (computational fluid dynamics) simulations were carried out using ANSYS 14.0 software. Time-dependent simulations of turbulent flow were carried out using the SAS-SST (scale adaptive simulation-shear stress transport) method coupled with the SM (sliding mesh) method. The results of the calculations are presented as contours of velocity in different cross-sections of the agitated vessel, as well as profiles of components of velocity vector and turbulence kinetic energy and its dissipation rate. The iso-surface of vorticity, which shows the region of possible vortex existence, is also presented. A numerically obtained data set of impeller power number was used to calculate the averaged impeller power number. This value was compared with the experimental data with good results. The relationship between impeller position and fluctuation of the impeller power number was also analysed.     

Semicontinuous GC analysis and receptor modelling for source apportionment of ozone precursor hydrocarbons in Bresso, Milan, 2003

The European Ozone Directive 2002/3/EC specifies the analysis of 30 individual C2-C9 hydrocarbons in urban air with the attribution of emission sources to pollution concentrations as a major objective. In the present study, we investigate an approach for source apportionment of these ozone precursor hydrocarbons in urban air based on reliable semi continuous volatile organic compound (VOC) analysis in the field and in vehicle emission laboratory combined with multivariate receptor modeling. The GC system relies on an hourly analytical cycle based on a trap sample enrichment phase followed by a dual column gas chromatographic flame ionisation detector (FID) analysis and has successfully been tested during an air monitoring campaign at an urban site (Milan, Italy, September 2003) and in the vehicle laboratory performing exhaust emission measurements while running driving cycles on a chassis dynamometer (mopeds, gasoline and diesel cars). The receptor modeling relies on two complementary principles. The chemical mass balance (CMB) modeling apportions well characterized source profiles for the 30 individual C2-C9 hydrocarbons in the Ozone Directive to the concentrations in ambient air and produces source contribution estimates (SCE) as output. The positive matrix factorization (PMF) analyses variability in the ambient air concentration data and searches for latent variables consisting of co-varying hydrocarbons and produces profiles as output, which in this study could be attributed to known emission sources. Both CMB and PMF rely on an estimated uncertainty for each input data. A new approach is presented, by which the uncertainty is allowed to float as function of the photochemical reactivity of the atmosphere and the stability of each individual compound.     

A practical guide to the staggered herringbone mixer

An analytical model of mixing in the staggered herringbone mixer (SHM) was derived to estimate mixing parameters and provide practical expressions to guide mixer design and operation for a wide range of possible solutes and flow conditions. Mixing in microfluidic systems has historically been characterized by the mixing of a specific solute system or by the redistribution of flow streams; this approach does not give any insight into the ideal operational parameters of the mixer with an arbitrary real system. For Stokes-flow mixers, mixing can be computed from a relationship between solute diffusivity, flow rate, and mixer length. Confocal microscopy and computational fluid dynamics (CFD) modeling were used to directly determine the extent of mixing for several solutes in the staggered herringbone mixer over a range of Reynolds numbers (Re) and Péclet numbers (Pe); the results were used to develop and evaluate an analytical model of its behavior. Mixing was found to be a function of only Pe and downstream position in the mixer. Required mixer length was proportional to log(Pe); this analytical model matched well with the confocal data and CFD model for Pe<5 x 10(4), at which point the experiments reached the limit of resolution. For particular solutes, required length and mixing time depend upon Re and diffusivity. This analytical model is applicable to other solute systems, and possibly to other embodiments of the mixer, to enable optimal design, operation, and estimation of performance.     

Electro-fluid analysis of a molten-salt electrorefiner with rotating cruciform anode baskets

A computational fluid dynamics (CFD)-based multiphysics model of a molten-salt electrorefiner is presented for the computational electro-fluid analysis. A target model of the electrorefining cell presented here has a structure arranged concentrically with the cathode annulus surrounding a rotating cruciform anode inside it. This comprehensive approach of a multiphysics model solves the convective and diffusive transport of ionic uranium and allows for a prediction of the concentration present in the LiCl–KCl eutectic electrolyte between the electrodes at a current driven condition. The coupling of the local overpotential distribution and uranium concentration gradient makes it possible to predict the local current density distribution at the electrode surfaces.     

A full quantum embedded cluster study of proton siting in chabazite

We propose a computational strategy within the full quantum embedded cluster methodology for modeling reactivity in extended systems. This method takes advantages of the embedded cluster methodology for treating interactions in the active region accurately while allowing interactions with the remaining crystal framework to be treated fully quantum mechanically by using the ab initio tight-binding theory. We have applied this method to study proton siting in chabazite. We found that our calculated relative stability of proton at four different oxygen sites agree well with those from previously periodic calculations, though the computational demand for the present approach is much less.     

Protein structure prediction: combining de novo modeling with sparse experimental data

Routine structure prediction of new folds is still a challenging task for computational biology. The challenge is not only in the proper determination of overall fold but also in building models of acceptable resolution, useful for modeling the drug interactions and protein-protein complexes. In this work we propose and test a comprehensive approach to protein structure modeling supported by sparse, and relatively easy to obtain, experimental data. We focus on chemical shift-based restraints from NMR, although other sparse restraints could be easily included. In particular, we demonstrate that combining the typical NMR software with artificial intelligence-based prediction of secondary structure enhances significantly the accuracy of the restraints for molecular modeling. The computational procedure is based on the reduced representation approach implemented in the CABS modeling software, which proved to be a versatile tool for protein structure prediction during the CASP (CASP stands for critical assessment of techniques for protein structure prediction) experiments (see http://predictioncenter/CASP6/org). The method is successfully tested on a small set of representative globular proteins of different size and topology, including the two CASP6 targets, for which the required NMR data already exist. The method is implemented in a semi-automated pipeline applicable to a large scale structural annotation of genomic data. Here, we limit the computations to relatively small set. This enabled, without a loss of generality, a detailed discussion of various factors determining accuracy of the proposed approach to the protein structure prediction.     

Development of Gradient Retention Model in Ion Chromatography. Part I: Conventional QSRR Approach

New retention methodology that integrates the conventional quantitative structure-retention relationship (QSRR) approach and gradient retention modeling based on isocratic retention data is developed and presented in this paper. Such an integrated approach removes the general QSRR limitation of highly predefined application conditions (i.e., QSRR are generally applicable only under the conditions used during model development) and allows the prediction of retentions over a wide range of different elution conditions (practically for any isocratic or gradient elution profile). At the same time, it retains the ability to predict retention of components unknown to the model, i.e., the components that have not been used in modeling. Ion-exchange chromatography (IC) analysis of carbohydrates was selected as modeling environment. Three regression techniques were applied and compared during QSRR modeling, namely: stepwise multiple linear regression, partial least squares (PLS), and uninformative variable elimination–PLS regression. The obtained prediction results of the best QSRR model (root-mean-square error of prediction = 22.69 %) were similar to those found in the literature. The upgrade from QSRR to the integrated model did not diminish the predictive ability of the model, indicating an excellent potential of the developed methodology not only in IC but also in chromatography in general.     

A novel approach to the uniform distribution of liquid in multi-channel (electrochemical) flow-through cells

Four-channel flow-through electrochemical cell working in thin-layer regime was designed, fabricated and characterized experimentally and in computational fluid dynamics (CFD) simulations. The new principle of operation allows reproducible splitting of a stream of liquid into multiple flow channels. Systems comprising of 2-, 3-, 4- and 8-channels were tested. The proper function of the cell is given by the ratio of the cross-sections of the fluidic element collecting chamber and the particular flow paths among which the liquid is distributed. Suitable flow rates providing uniform liquid distribution were evaluated and the results were compared to CFD modeling. The flow-through cells designed according to the proposed principle can be simply incorporated in automated routine analysis as only one inlet and one common outlet are required.     

Probing slow dynamics in high molecular weight proteins by methyl-TROSY NMR spectroscopy: application to a 723-residue enzyme

A new CPMG-based multiple quantum relaxation dispersion experiment is presented for measuring millisecond dynamic processes at side-chain methyl positions in high molecular weight proteins. The experiment benefits from a methyl-TROSY effect in which cancellation of intramethyl dipole fields occurs, leading to methyl (13)C-(1)H correlation spectra of high sensitivity and resolution (Tugarinov, V.; Hwang, P. M.; Ollerenshaw, J. E.; Kay, L. E. J. Am. Chem. Soc. 2003, 125, 10420-10428). The utility of the methodology is illustrated with an application to a highly deuterated, methyl-protonated sample of malate synthase G, an 82 kDa enzyme consisting of a single polypeptide chain. A comparison of the sensitivity obtained using the present approach relative to existing HSQC-type (13)C single quantum dispersion experiments shows a gain of a factor of 5.4 on average, significantly increasing the range of applications for this methodology.     

A new procedure for simultaneous calibration of separation and axial dispersion in SEC

Summary A new computational procedure for the simultaneous calibration of separation and axial dispersion by using SEC coupled with a LALLS detector is presented. Its performance is tested by SEC/LALLS experiments with commercially available samples of broad and narrow polystyrene standards. The peakbroadening parameters were calculated by a novel method which utilizes the different effects of axial dispersion on polymers with narrow and broad molecular weight distribution. The dispersion function was assumed to be gaussian. The variation of the dispersion parameter with molecular weight is in good agreement with reports in the literature. Experimental chromatograms have been corrected for the axial dispersion effect.