SA Models Research Articles

Improving modeling of submerged canopy flows with a vortex-based Spalart–Allmaras model

Accurately modeling the hydrodynamics of submerged canopies is crucial for predicting sediment dynamics and geomorphodynamics. This paper introduces vortex-based Spalart–Allmaras (VBSA) models, considering the spatial structure of canopy-scale vortices and stem wakes. The VBSA models are innovative in incorporating the physics of canopy-overflow interaction. They were validated using experimental data across a wide range of velocities and canopy densities, and their performance was compared with other turbulence models (i.e., previous SA models and k-ε model). Despite lacking high-order numerical schemes, the VBSA models outperform other turbulence models, exhibiting less numerical dissipation and better replication of mean velocity and Reynolds shear stress profiles in the vortex penetration space and below the surface. A sensitivity analysis was conducted to identify optimal values for new model parameters. Analyses suggest that the porous canopy layer suppresses the mixing efficiency by reducing the turbulence length scale. The analysis of eddy viscosity flux balance reveals that the eddy viscosity is transferred to the canopy layer from the overflow by the canopy-scale vortices and is destructed in the canopy, with production being less important, particularly in large submergence scenarios.

Numerical Simulation of Transonic Compressors with Different Turbulence Models

One of the most commonly used techniques in aerospace engineering is the RANS (Reynolds average Navier–Stokes) approach for calculating the transonic compressor flow field, where the accuracy of the computation is significantly affected by the turbulence model used. In this work, we use SA, SST, k-ɛ, and the PAFV turbulence model developed based on the side-biased mean fluctuations velocity and the mean strain rate tensor to numerically simulate the transonic compressor NASA Rotor 67 to evaluate the accuracy of turbulence modeling in numerical calculations of transonic compressors. The simulation results demonstrate that the four turbulence models are generally superior in the numerical computation of NASA Rotor 67, which essentially satisfies the requirements of the accuracy of engineering calculations; by comparing and analyzing the ability of the four turbulence models to predict the aerodynamic performance of transonic compressors and to capture the details of the flow inside the rotor. The errors of the Rotor 67 clogging flow rate calculated by the SA, SST, k-ɛ, and PAFV turbulence models with the experimental data are 0.9%, 0.8%, 0.7%, and 0.6%, respectively. The errors of the calculated peak efficiencies are 2.2%, 1.6%, 0.9%, and 4.9%. The SA and SST turbulence models were developed for the computational characteristics of the aerospace industry. Their computational stability is better and their outputs for Rotor 67 are comparable. The k-ɛ turbulence model calculates the pressure ratio and efficiency that are closest to the experimental data, but the computation of its details of the flow field near the wall surface is not ideal because the k-ɛ turbulence model cannot accurately capture the flow characteristics of the region of high shear stresses. The PAFV turbulence model has a better prediction of complex phenomena such as rotor internal shock wave location, shock–boundary layer interaction, etc., due to the use of a turbulent velocity scale in vector form, but the calculated rotor efficiency is small.

Numerical simulation of subsonic flow around oscillating airfoil based on the Navier–Stokes equations

ABSTRACT Unsteady Reynolds-averaged Navier–Stokes equations of an incompressible fluid are used to numerically simulate the flow around an oscillating airfoil. A comparison is made between two differential one-equation turbulence models SA and SALSA on the problems of subcritical and supercritical turbulent incompressible flow around an oscillating NACA 0015 airfoil. The numerical algorithm utilized for solving the governing equations is founded upon a three-layer implicit scheme, which exhibits second-order integration accuracy in time, third order of upwind approximation of convective terms, and second-order symmetric approximation of the diffusion terms. Pressure and velocity field coupling is achieved through the implementation of the artificial compressibility approach, which is employed for the computation of unsteady problems. The system of initial equations is numerically integrated using the control volume method. The resulting system of algebraic equations has been solved by the GMRES method with ILU(k) preconditioning. The obtained instantaneous streamlines, vorticity contours, and hysteresis curves of unsteady airfoil aerodynamic loads are analyzed for cases of weak ( α 0 = 4 ° ), developed ( α 0 = 11 ° ) and massive ( α 0 = 15 ° ) flow separation at Reynolds number Re = 1.95 × 10 6 . In the case of weak flow separation, the values of the lift coefficient obtained using the SA and SALSA models differ from the experimental data by 10% and 5%, respectively. With a developed separation, these values are already equal to 10–20% for the SA model and 6–8% for the SALSA model. The average values of the lift coefficient, which are obtained using the SA and SALSA models, in the case of massive flow separation, differ from the experimental data by 50–60% and 10–15%, respectively. Comparing the calculation results with both known experimental and calculated data demonstrates that in flows with developed and massive flow separation, which are characterized by unsteady effects in turbulence, the SALSA turbulence model performs better than other tested models. The aerodynamic coefficients obtained with the SALSA turbulence model are in 10–15% better agreement with experimental data than those obtained with other turbulence models.

Multichannel Approach for Sentiment Analysis Using Stack of Neural Network with Lexicon Based Padding and Attention Mechanism

Abstract Sentiment analysis (SA) has been an important focus of study in the fields of computational linguistics and data analysis for a decade. Recently, promising results have been achieved when applying DNN models to sentiment analysis tasks. Long short-term memory (LSTM) models, as well as its derivatives like gated recurrent unit (GRU), are becoming increasingly popular in neural architecture used for sentiment analysis. Using these models in the feature extraction layer of a DNN results in a high dimensional feature space, despite the fact that the models can handle sequences of arbitrary length. Another problem with these models is that they weight each feature equally. Natural language processing (NLP) makes use of word embeddings created with word2vec. For many NLP jobs, deep neural networks have become the method of choice. Traditional deep networks are not dependable in storing contextual information, so dealing with sequential data like text and sound was a nightmare for such networks. This research proposes multichannel word embedding and employing stack of neural networks with lexicon-based padding and attention mechanism (MCSNNLA) method for SA. Using convolution neural network (CNN), Bi-LSTM, and the attention process in mind, this approach to sentiment analysis is described. One embedding layer, two convolution layers with max-pooling, one LSTM layer, and two fully connected (FC) layers make up the proposed technique, which is tailored for sentence-level SA. To address the shortcomings of prior SA models for product reviews, the MCSNNLA model integrates the aforementioned sentiment lexicon with deep learning technologies. The MCSNNLA model combines the strengths of emotion lexicons with those of deep learning. To begin, the reviews are processed with the sentiment lexicon in order to enhance the sentiment features. The experimental findings show that the model has the potential to greatly improve text SA performance.

Exploiting the co-crystal ligands shape, features and structure-based approaches for identification of SARS-CoV-2 Mpro inhibitors

SARS-CoV-2 enters the host cell through the ACE2 receptor and replicates its genome using an RNA-Dependent RNA Polymerase (RDRP). The functional RDRP is released from pro-protein pp1ab by the proteolytic activity of Main protease (Mpro) which is encoded within the viral genome. Due to its vital role in proteolysis of viral polyprotein chains, it has become an attractive potential drug target. We employed a hierarchical virtual screening approach to identify small synthetic protease inhibitors. Statistically optimized molecular shape and color-based features (various functional groups) from co-crystal ligands were used to screen different databases through various scoring schemes. Then, the electrostatic complementarity of screened compounds was matched with the most active molecule to further reduce the hit molecules’ size. Finally, five hundred eighty-seven molecules were docked in Mpro catalytic binding site, out of which 29 common best hits were selected based on Glide and FRED scores. Five best-fitting compounds in complex with Mpro were subjected to MD simulations to analyze their structural stability and binding affinities with Mpro using MM/GB(PB)SA models. Modeling results suggest that identified hits can act as the lead compounds for designing better active Mpro inhibitors to enhance the chemical space to combat COVID-19.Communicated by Ramaswamy H. Sarma

Численное моделирование течения в плоском внезапно расширяющемся канале на основе новой двужидкостной модели турбулентности

The purpose of the research was to numerically study the structure of the flow in a flat channel in the zone of its sudden step-like expansion. The results of the study are given in the paper. The calculations are carried out with the use of a new two-fluid turbulence model and are based on the numerical solution of a system of nonstationary equations. The profiles of axial velocity and turbulent stress in various sections of the channel before and after the step were obtained, as well as the dependence of the friction coefficient for the lower wall of the channel on the distance after the step. For the difference approximation of the initial equations, the control volume approach was applied; the relationship between the velocities and pressure was found using the SIMPLEC procedure. Meanwhile, the viscosity terms were approximated by the central difference, and for the convective terms the QUICK second-order accuracy scheme was used. To confirm the correctness of the numerical results, we compared them with the experimental data taken from the NASA database for the Reynolds number Re = 36,000. The results obtained using the SA and SST models are also given in the paper. Despite the coarse grid used for numerical calculations, the results based on the new two-fluid turbulence model are not less accurate than the results determined by the RANS models for predicting separated flows in the flat channel in the zone of its sudden backward-facing step expansion

Age estimation based on Willems method versus country specific model in Saudi Arabia children and adolescents

BackgroundThe aims of this study were to create a method for estimation of dental age in Saudi children and adolescents based on the Willems model developed using the Belgian Caucasian (BC) reference data and to compare the ability of the two models to predict age in Saudi children.MethodsDevelopment of the seven lower left permanent mandibular teeth was staged in 1146 panoramic radiographs from healthy Saudi children (605 male, 541 female) without missing permanent teeth and without all permanent teeth fully developed (except third molars). The data were used to validate the Willems BC model and to construct a Saudi Arabian-specific (Willems SA) model. The mean error, mean absolute error, and root mean square error obtained from both validations were compared to quantify the variance in errors in the sample.ResultsThe overall mean error for the Willems SA method was 0.023 years (standard deviation, ± 0.55), indicating no systematic underestimation or overestimation of age. For girls, the error using the Willems SA method was significantly lower but still negligible at 0.06 years. A small but statistically significant difference in total mean absolute error (11 days) was found between the Willems BC and Willems SA models when the data were compared independent of sex. The overall mean absolute error for girls was slightly lower for the Willems BC method than for the Willems SA method (1.33 years vs. 1.37 years).ConclusionsThe difference in ability to predict dental age between the Willems BC and Willems SA methods is very small, indicating that the data from the BC population can be used as a reference in the Saudi population.

PNS9 Estimating Incidence Progressed Patients in Partitioned Survival Models - a Comparison of Three Methodologies

Partitioned survival analysis (Part SA) is a useful modelling technique for assessing cost-effectiveness of interventions that impact survival. Part SA models typically comprise of three mutually exclusive health states: progression-free survival (PFS), progressed disease (PD) and death. Incident progression in Part SA models is defined as “proportion of patients who progressed from PFS to PD state during a model cycle”. The current study explores three different methods of estimating incident progression and their implications on cost effectiveness models.

Designation of the Troposphere Radio Refractivity for the Area of the Military Aerodrome in Dęblin

Abstract The radio refractivity is one of major parameters in troposphere monitoring over a selected military aerodrome. The paper makes an in-depth analysis and description of the results of radio refractivity of the troposphere zone. The radio refractivity of the troposphere zone was estimated for the area of the military aerodrome EPDE in Dęblin, Poland. The radio refractivity of the troposphere zone was calculated using empirical troposphere models for the GNSS satellite technique as well as real meteorological data from the SYNOP message. In the paper, the authors demonstrate the results of wet, hydrostatic and total radio refractivity of the troposphere zone for EPDE military aerodrome. The SA and UNB3m models were applied in numerical computations of troposphere refractivity in an annual period.

Estimating non-native plant richness with a species-accumulation model along roads.

Monitoring non-native plant richness is important for biodiversity conservation and scientific research. The species-area model (SA model) has been used frequently to estimate the total species richness within a region. However, the conventional SA model may not provide robust estimations of non-native plant richness because the ecological processes associated with the accumulation of exotic and native plants may differ. Because roads strongly dictate the distributions of exotic plants, we propose a species-accumulation model along roads (SR model), rather than an SA model, to estimate the non-native plant richness within a region. Using 270 simulated data sets, we compared the differences in performance between the SR and SA models. A decision tree based on prediction accuracy was created to guide model application, which was validated using field data from 3 national nature reserves in 3 different provinces in China. The SR model significantly outperformed the SA model when non-native species were restricted to the roadsides and the proportion of uncommon exotic species was small. More importantly, the SR model accurately estimated the non-native plant richness in all field sites with an error of <1 species per site. We believe our new model meets the practical need to efficiently and robustly estimate non-native plant richness, which may facilitate effective biodiversity conservations and promote research on non-native plant invasion and vegetation dynamics.

Optimization of RANS turbulence models using genetic algorithms to improve the prediction of wind pressure coefficients on low-rise buildings

Being associated with natural ventilation, the pressure distribution on surfaces is relevant for energy consumption, thermal comfort, and air quality in buildings. The aim of this work is to present a simulation-based optimization methodology to recalibrate the closure coefficients of Reynolds-averaged Navier-Stokes (RANS) turbulence models in order to improve the prediction of wind surface-averaged pressure coefficients on a wide range of isolated low-rise buildings. To accomplish this, genetic algorithms and Computational Fluid Dynamics (CFD) simulations are dynamically coupled to find the closure coefficients set which minimize the CFD prediction error regarding wind-tunnel experimental data. The methodology is applied to two turbulence models, the renormalization group k-epsilon model (RNG) and the Spalart-Allmaras model (SA), considering as target cases buildings with different roof types (flat, gable and hip) and wind incidence angles. In order to show the strength of the novel optimal sets of closure coefficients obtained, an exhaustive validation is performed over other low-rise buildings (52 new cases) which were not calibrated against. Results validate using the optimal sets because the recalibrated RNG and SA models decrease the prediction error between 11-64% and 8–45%, respectively, regarding using the standard ones.

Prediction of separation induced transition on thick airfoil using non-linear URANS based turbulence model

Most of the turbulence models in practice are based on the assumption of a linear relation between Reynolds stresses and mean flow strain rates which generally provides a good approximation in case of attached and fully turbulent flows. However, this is seldom the need in most of the engineering problems; the majority of the engineering problems observe flow separation or flow transition. Recent developments in non-linear turbulence models have proven significant improvement in prediction of separated flow due to better resolution of anisotropy in modeled Reynolds stress. The domain of application of this improved RANS model can be extended to flow transitions as well, where the resolution of anisotropy in Reynolds stress is required. For a validation of such kind, a two-dimensional numerical study has been carried out over NACA 0021 with k-ω SST model with non-linear correction at Re = 120000 for various angles of attack which experiences the formation of a laminar separation bubble (LSB). A correct prediction of LSB requires an accurate resolution of anisotropy in Reynolds stresses. For comparison with other linear models, the simulations are also performed with k-kl-ω (a 3-equation linear transition model), k-ω SST (a 2-equation linear model) and Spalart-Allmaras (a 1-equation model). The performance of these models is assessed through aerodynamic lift, drag, pressure and friction coefficients. It is found that the non-linear k-ω SST and k-kl-ω transition model provide comparable quality of prediction in lift and drag coefficients (in spite of the fact that non-linear k-ω SST involves solving less number of transport equation than the transition model) as observed in the experiments whereas k-ω SST and SA models under predict the drag coefficient value at low angle of attack due to inability to capture the separation induced transition. It is also observed that the location of laminar separation bubble is captured accurately when non-linear or transition model is used as opposed to the SA or linear SST models, which lack in the ability to predict the same.

Suicidal ideation, plan, and attempts and nonmedical prescription opioid use among U.S. adults

ObjectiveThe increase of nonmedical prescription opioid use (NMPOU) in the United States has become a public health concern. The purpose of this study was to examine the relationship between nonmedical prescription opioid misuse and past-year suicidality (suicide ideation-SI, suicide plan-SP, and suicide attempts-SA) among U.S. adults.Method: Secondary data analysis was conducted using the 2016 National Survey on Drug Use and Health with 42,625 respondents. NMPOU was grouped in 4 categories: (1) never used, (2) current user, (3) recent user, and (4) past user. The outcome variables were SI, SP and SA and they were predicted in multivariable logistic regression. ResultsCompared to the never-use of NMPO groups, the current, recent, and past users of NMPO showed significantly higher likelihoods of SI, SP, and SA models adjusting for sociodemographic and mental health-related factors. Presence of a major depressive episode had the significantly highest Odds Ratio of SI, SP, and SA. Suicidality among NMPO users is high, and there are multiple, sociodemographic and mental health related factors associated with this finding. ConclusionPolicy and prevention efforts to improve screening and treatment should focus on the at-risk populations identified in this study.

Fuzzy based models for estimating static contact angle and sliding angle of liquid drops

Prediction of the contact angles and sliding angles of liquid drops is so difficult, because the interaction among the variables, which have impact on the angles, is so complex. Therefore, in this paper fuzzy logic was used to develop prediction models. Experimental sliding angle and contact angles of liquid drops on the metal samples with several surface treatments were divided into training data and testing data. By using the knowledge, which was extracted from the training data and experience of authors, the effective if-then rules were developed. Then, the weight of the rules was optimized by particle swarm optimization. The obtained results for testing data by using proposed Fuzzy_CA and Fuzzy_SA models showed that the regression index for the contact angles and sliding angles were 0.9970 and 0.9980, respectively. It means that the predicted angles are so close to measured angles and the proposed fuzzy based models are so reliable.

The impact of socioeconomic status on the association between biomedical and psychosocial well-being and all-cause mortality in older Spanish adults.

The aim of this paper was to analyze the effect of biomedical and psychosocial well-being, based on distinct successful aging models (SA), on time to mortality, and determine whether this effect was modified by socioeconomic status (SES) in a nationally representative sample of older Spanish adults. Data were taken from a 3-year follow-up study with 2783 participants aged 50 or over. Vital status was ascertained using national registers or asking participants' relatives. Kaplan-Meier curves were used to estimate the time to death by SES, and levels of biomedical and psychosocial SA. Cox proportional hazard regression models were conducted to explore interactions between SES and SA models while adjusting for gender, age, and marital status. Lower levels of SES and biomedical and psychosocial SA were associated with low probability of survival. Only the interaction between SES and biomedical SA was significant. Biomedical SA impacted on mortality rates among individuals with low SES but not on those with medium or high SES, whereas psychosocial SA affected mortality regardless of SES. Promoting equal access to health care system and improved psychosocial well-being could be a protective factor against premature mortality in older Spanish adults with low SES.

Successful aging and frailty: mutually exclusive paradigms or two ends of a shared continuum?

The conceptualization of positive and negative states of aging is contentious at the inter- and intraparadigm level; lack of consensus exists within and between states. Working within their respective paradigms, successful aging and frailty researchers may have lost sight of the larger picture. Are successful aging researchers describing nonfrail individuals? Are frailty researchers describing unsuccessful aging? It is imperative that researchers are cognizant of the ways in which their perspectives are contextualized within the literature and within related paradigms, so as to be able to clearly communicate their research and to ensure they are working within the appropriate paradigm to facilitate desired outcomes. Here we discuss the similarities and differences between successful aging and frailty in terms of the scope and emphasis of their constituent components and functioning: both SA and frailty include biomedical components; SA examines the high end, whilst frailty predominately examines the low end of the functioning spectrum. Frailty models emphasize the biomedical realm, whilst SA models emphasize both the biomedical and the psychosocial.

Numerical Simulation of Unsteady Separated Flow over a Delta Wing Using Cartesian Grids and DES/DDES

Detached-Eddy simulation (DES) and Delayed Detached-Eddy simulation (DDES) based on SA and SST turbulent models were developed by using Cartesian grids. Associating with flexible deformation dynamic grid method on Cartesian grids,unsteady Reynolds-averaged Navier-Stokes (URANS), DES and DDES methods involving moving boundaries wereestablished. URANS, DES and DDES were evaluated for simulating the high angle of attack separated flow over a delta wing of 65 degrees swept and with sharp leading edge, showing that DES and DDES forecast the site of vortex breakdown more accurate, which means these methods are fit for simulating the large separated flow and can be adapted to the engineering applications. The study also simulated the unsteady separated flow around the oscillating delta wing. The results show that the pitching of the wing delays the flow separation and makes the flow field appearing hysteresis. It is meaningful to the design of modernastronauticaland aeronautical vehicles.