Improving the CFD modelling of cross-ventilation in highly-packed urban areas

Computational Fluid Dynamics (CFD) simulations are widely used in many wind-related urban morphology studies in urban areas, including cross-ventilation. The accuracy of the CFD models, however, is still a challenging issue for accurate prediction of the complex flow behavior around and inside the buildings. The RANS models, although broadly preferred, provide poor results in predicting the cross-ventilation in street canyons.Thus, this study aims to understand and quantify limitations of the steady RANS models for cross-ventilation applications in highly-packed urban areas. To this end, a series of experimentally validated CFD simulations were conducted for a group of buildings, which were arranged in regular and staggered orders with different urban area densities. The improvement possibility of the RANS model accuracy was investigated using a parametric sensitivity study over the closure coefficients, and consequently a series of new closure coefficients were found for urban area densities between 0.25 and 0.4. Furthermore, as an interesting finding of this study, CFD results for urban area densities above 0.4 showed a high discrepancy compared to the expected measurement ranges for surface wind pressure; this implies that the CFD modelling of higher density urban areas should be treated with more caution and thus further studies are required to develop a guideline for such applications

A Detailed Cutaneous Manifestations Evaluation in Patients with Polycystic Ovary Syndrome

Background and Aim: Polycystic ovary syndrome (PCOS) is the most common endocrine disorder among women of reproductive age. The hypothalamus-pituitary-ovary axis dysregulates in PCOS, ultimately leading to hyperandrogenisms. Consequently, it is associated with hirsutism, dyslipidemia, obesity, infertility, menstrual disturbance, and insulin resistance. To our knowledge, there is no detailed investigation of these manifestations. That is why, this study aimed to evaluate manifestations of hyperandrogenism, hirsutism in particular. Methods: This study was performed on 39 women with an initial diagnosis of polycystic ovary syndrome. Rotterdam criteria including Oligo- or anovulation, hyperandrogenism clinical and/or biochemical signs, and ultrasound appearance of polycystic ovaries used as diagnostic criteria. Hirsutism scoring was carried out according to Freeman-Gallwey’s definition of hirsutism. The patients were analyzed for other skin problems including male pattern baldness, acanthosis nigricans, and acne as well as demographic features. Results: Hirsutism was observed in the majority of our patients (91%) ranging from mild to severe. Concerning the distribution of hirsutism on various parts of the body, severe hirsutism was observed more on the groin, abdominal area, and chin respectively. Male pattern baldness, acanthosis nigricans, and acne, and dysregulated menstruation were reported in these patients. Conclusion: This investigation found that skin manifestations, especially hirsutism, are highly frequent in patients with PCOS. *Corresponding Author: Hashem Nayeri; Email: [email protected]; [email protected] Please cite this article as: Masaeli A, Nayeri H, Mirzaei M. A Detailed Cutaneous Manifestations Evaluation in Patients with Polycystic Ovary Syndrome. Arch Med Lab Sci. 2021;7:1-6 (e10). https://doi.org/10.22037/amls.v7.3082

Experimental and Steady-RANS CFD Modelling of Cross-ventilation in Moderately-dense Urban Areas

Computational fluid dynamics (CFD) models based on the steady Reynolds-averaged Navier Stokes (SRANS) equations are vastly used for calculation of airflow field inside and around cross-ventilated buildings. However, most of the developed CFD guidelines ignore CFD challenges related to cross-ventilation modeling in terms of flow unsteadiness, high level of gradients of airflow parameters, and complex interactions between the indoor and outdoor flows.Hence, a systematic parametric study was performed in this study for a generic cross-ventilated building model with a planar area ratio of 0.25 against different wind angles while effects of different CFD parameters, including advection and diffusion terms discretization methods, mesh generation techniques, and turbulence models on prediction accuracy and convergence behavior of CFD solver were comprehensively studied.Results show that a particularly generated unstructured tetrahedral mesh configuration with significantly lower mesh numbers can provide comparable results with structured hexahedral mesh configuration. Furthermore, second-order discretization scheme for advection terms encounters convergence issues against the normal wind angle, but generally presents more accurate results against oblique wind angles. Moreover, two-equation turbulence models showed very low accuracy in the case of normal wind angle, but acceptable results were found for oblique wind angles

Developing a framework for improvement of building thermal performance modeling under urban microclimate interactions

Coupled models developed from the building energy simulation (BES) and computational fluid dynamics (CFD) methods are occasionally used for analyzing the buildings thermal performance. Nevertheless, the large uncertainty in the input parameters of BES models and values of the closure coefficients of Reynolds-averaged Navier-Stokes (RANS) turbulence models restrict the accuracy of coupled BES-CFD models for thermal performance prediction in highly dense urban areas.Thus, a systematic framework for improving the accuracy of the coupled BES-CFD models is proposed in this study, consisting of an approximation technique and a stochastic optimization approach. In this framework, at first, a CFD model is improved with a closure coefficients optimization procedure using experimental data. In the second step, the improved CFD model is utilized to conduct a series of CFD simulations for real-geometry buildings in order to calibrate the BES model with the alteration of parameters such as the adaptive discharge coefficient, local wind profile, and convective heat transfer coefficients over the building façades.The developed framework is then applied to a small cross-ventilated office building surrounded by neighboring buildings. Deviations up to 60% are found in the prediction of the energy saving potential of cross-ventilation strategy by the default and calibrated BES models

Modelling enhancement of cross-ventilation in sheltered buildings using stochastic optimization

Accurate representation of turbulence phenomenon in Computational Fluid Dynamics (CFD) modeling of cross-ventilation around and inside buildings is a challenging and complex problem, especially under the sheltering effect of surrounding buildings. Steady Reynolds Averaged Navier-Stokes (RANS) models are broadly used in many practical applications. However, these models mainly fail to predict accurate distribution of flow characteristics in the cavity formed between the buildings, and hence miscalculate the attributed cross flow and airflow rate through buildings. In this study, a novel and systematic methodology is proposed to enhance the accuracy of the model for the urban study applications such as cross-ventilation in the sheltered buildings.A microclimate CFD model for a case study of a cross-ventilation experimental work by Tominaga and Blocken (2015) was firstly constructed and validated. In the next step, the closure coefficients of themodel were modified using a stochastic optimization and Monte Carlo Sampling techniques. The probability density function (PDF) of all closure coefficients were given to the optimizer and proper objective function defined in terms of different validation metrics. The modified coefficients obtained from the developed systematic method could successfully simulates the cross-ventilation phenomena inside the building with an airflow rate prediction error less than 8% compared to the experiment while other RANS models predicted the airflow rate with up to 70% error. The effectiveness of the optimization technique was also discussed in terms of validation metrics and pressure coefficients

Experimental Study on Cross-ventilation of a Generic Building in Highly-dense Urban Areas: Impact of Planar Area Density and Wind Direction

This study presents the experimental results on cross-ventilation in a generic low-rise building placed in highly-dense urban configurations. Flow visualization studies were conducted by utilization of a smoke generator in order to investigate the nature of the flow pattern inside and around the cross-ventilated building. Moreover, distribution of the wind surface pressure coefficients over windward and leeward façades and internal walls of the target building were measured using a pressure tap system. Furthermore, the airflow rate crossing through the openings was measured using a tracer gas method. Different building configurations, representing highly-dense urban areas, as well as different wind angles were investigated in this study Surprisingly, the experimental results reveal a noticeable difference between the mechanism of cross-ventilation in moderately-dense and highly-dense buildings arrangements. A clear leeward jet with a highly-transient nature can be observed, which is generated due to a leeward vortex formed by the target and downstream buildings. As another novel finding of this study, the cross-ventilation is understood to be highly transient in highly-dense urban areas with a strong periodic fresh air pulsation through the windward and leeward openings. This behavior is fundamentally far from the steady state models considered for such cross-ventilation scenarios in literature

Development of an adaptive discharge coefficient to improve the accuracy of crossventilation airflow calculation in building energy simulation tools

Airflow network (AFN) model embedded in building energy simulation (BES) tools such as EnergyPlus is extensively used for prediction of cross-ventilation in buildings. The noticeable uncertainty in the measurement of the surface pressure, discharge coefficient, and simplifications applied to the orifice-based equation result in considerable discrepancies in the prediction of the cross-ventilation airflow rate values. Computational Fluid Dynamics (CFD) provides more accurate results comparing to the orifice-based equations although with an excessive computational cost. The aim of this study is, therefore, to improve the accuracy of the orifice-based model by development of an adaptive correlation for the discharge coefficient using CFD. Hence, a validated CFD model for the cross-ventilation of an unsheltered building is firstly developed using an experimental study. In the next step, by exploiting Latin hypercube sampling (LHS) approaches, a large CFD dataset of 750 scenarios for different building geometries (i.e. square cube, cuboid and long corridor) is generated; the dataset is then coupled to the AFN crossventilation model to obtain an adaptive correlation for the discharge coefficient as a function of the openings’ geometries and location using response surface (RSM) and radial basis function (RBF) models. Results show that the newly developed adaptive correlation successfully increases the accuracy of AFN model for the cross-ventilation modeling of unsheltered buildings as the relative errors for the airflow rate prediction of different building geometries are significantly decreased up to 28% in comparison with the cases with constant discharge coefficient and surface-averaged and local-surface wind pressure coefficients. Results, also demonstrate the importance of considering the value of the local-surface wind pressure in the AFN model for the square cube and cuboid building models

CFD analysis of cross-ventilation flow in a group of generic buildings: Comparison between steady RANS, LES and wind tunnel experiments

Computational fluid dynamics (CFD) results generated by the steady Reynolds-averaged Navier-Stokes equations (SRANS) model and large eddy simulation (LES) are compared with wind tunnel experiments for investigating a cross-ventilation flow in a group of generic buildings. The mean flow structure and turbulence statistics are compared for SRANS based on different two-equation turbulence models with LES based on the Smagorinsky subgrid-scale turbulence model. The LES results show very close agreement with the experimental results in the prediction of the time-averaged velocity, wind surface pressure around and inside the building, and crossing flow through the openings. In contrast, SRANS fails to predict the most important features of cross-ventilation. LES reproduces well the anisotropic turbulence property around and inside the cross-ventilated building, which is closely related to the transient momentum transfer caused in street canyon flows and has a significant influence on the mean flow structure. In contrast, SRANS could not inherently reproduce such transient fluctuations and anisotropic turbulence property, which results in low accurate predictions for the time-averaged velocity components, wind surface pressure distribution and crossing airflow rate up to 100% error

RANS model calibration using stochastic optimization for accuracy improvement of urban airflow CFD modeling

In this study, a systematic calibration methodology is proposed for enhancing the accuracy of urban airflow simulations using computational fluid dynamics (CFD) models based on the Reynolds-averaged Navier-Stokes (RANS) equations. In the calibration process, high-quality data from different sources are used to define the validation metrics, which are then utilized as the objective function in a stochastic optimization solver to find optimal values for closure coefficients of the RANS turbulence model. The proposed calibration method is applied to three different urban case studies, including an unstable atmospheric boundary layer (ABL) around a high-rise building, a sheltered cross-ventilated low-rise building, and a group of low-rise buildings located in a highly packed urban area.The significant advantage of using the obtained calibrated coefficients is observed over the existing coefficients embedded in CFD tools as well as the ones recommended by other calibration methods in literature. Thus, this study proves the necessity of finding a group of customized optimum closure coefficients for RANS turbulence models suitable for a wide range of urban flow problems

Molecular Identification and Intra-species Variations among Leishmania infantum Isolated from Human and Canine Visceral Leishmaniasis in Iran

Background: In Iran, both forms of cutaneous (CL) and visceral leishmaniasis (VL) have been re-ported; so the accurate species identification of the parasite(s) and the analysis of genetic diversity are necessary. Methods: The investigation was conducted from 2014 to 2015 in the northwest and south of Iran, where VL is endemic (7 provinces). Blood samples of patients and infected dogs were collected and sera separated for serologic examinations (DAT, rK39). Spleen or bone marrow samples from infected dogs were also collected to confirm the infection. DNAs of 70 samples amplified by targeting a partial sequence of ITS (18S rRNA–ITS1–5.8S rRNA–ITS2) gene. All the amplicons were sequenced and analyzed with restriction fragment length polymorphism (RFLP) using the TaqI enzyme. Results: The cause of all 70 VL cases, were L. infantum, so, the dominant specie is L. infantum. The sequencing results of all VL cases and RFLP analysis corroborate each other. Discrimination of Iranian Leishmania isolates using ITS gene gives us this opportunity to detect, identify and construct the phylogenetic relationship of Iranian isolates. In addition, detection and differentiation of Leishmania spp. DNA was confirmed by amplification of variable area of the minicircle kDNA (conserved sequence blocks (CSB)). Conclusion: Low divergence and high likelihood were seen among L. infantum isolates of human and dogs from Iran with a very slight divergence was seen between isolates from northwest and south of Iran, thus grouped in a unique clad. No correlation was observed between intraspecies divergence and geographic distribution of the isolates