Simulation Modeling Approach Research Articles

Role of Canal Lining on Groundwater Fluctuations: A Modeling Simulation Approach for Jaalwala Distributary, Bahawalnagar

Jaalwala Distributary was selected to see the consequences of concrete lining on the underlying saline groundwater table. Its middle and tail portions were concrete lined whereas the head portion was still unlined. Visual MODFLOW 2011.1 was used to simulate the effects of concrete lining on saline groundwater in two-dimensional format. Simulation results showed a gradual rise of electrical conductivity (EC) up to 7000 μS/cm and decline in water table depth to nine feet (2.74 m). It observed negligible inflows from the distributary through its western boundary due to formation of a permanent barrier in the way of seepage of any kind. Results have further predicted that freshwater layer available beneath the Jaalwala Distributary (before its lining) will finish ultimately and the below present saline water also move upward to take this vacated place. Hence it was concluded to line the canals of saline water areas from their sides which will not only protect them from erosion but canal water theft as well.

Conformity checking of LPG Transportation Trucks by Modelling and Simulation

LPG Loading /unloading site is considered as a dangerous environment of significant risk, especially during LPG transfer operations. These risks may cause catastrophic dangers such as BLEVE (Boiling Liquid Expanding Vapour Explosion), UVCE (Unconfined Vapour Cloud Explosion), etc. The site consists of a tank (RST) containing LPG and threetransfer posts. Two posts allow loading of small carrier tankers 6 tons. The other one transfer post transfer LPG contained injumbo tankers 20 tons inside the tank. The industrial site at risks chooses to demonstrate the need for a modelling-simulation approach. The aim is to check first compliance and authorization of the truck when it enters the site for loading /unloading, to verify the authorization to make the transfer, and then, to identify the driver and his training to ensure that the transfer operations are going to take place without incident. Sometimes, it may happen that Consignment Operator (CO) is busy orabsent and thus the driver operates alone without being authorized, in this case the site risks a loss of control due to a lack of resources. The modelling-simulation will be done using multi-agent systems that will present the drivers, trucks, PO and loading unloading posts as agents in order to have a model facilitating this checking.

A hybrid finite element and surrogate modelling approach for simulation and monitoring supported TBM steering

The paper proposes a novel computational method for real-time simulation and monitoring-based predictions during the construction of machine-driven tunnels to support decisions concerning the steering of tunnel boring machines (TBMs). The proposed technique combines the capacity of a process-oriented 3D simulation model for mechanized tunnelling to accurately describe the complex geological and mechanical interactions of the tunnelling process with the computational efficiency of surrogate (or meta) models based on artificial neural networks. The process-oriented 3D simulation model with updated model parameters based on acquired monitoring data during the advancement process is used in combination with surrogate models to determine optimal tunnel machine-related parameters such that tunnelling-induced settlements are kept below a tolerated level within the forthcoming process steps. The performance of the proposed strategy is applied to the Wehrhahn-line metro project in Düsseldorf, Germany and compared with a recently developed approach for real-time steering of TBMs, in which only surrogate models are used.

Hybrid Reynolds-Averaged/Large-Eddy Simulation of a Scramjet Cavity Flameholder

Steady-state and scale-resolving simulations have been performed for flow in and around a model scramjet combustor flameholder. Experimental data available for this configuration include velocity statistics obtained from particle image velocimetry as well as a limited number of scalar measurements using laser-induced breakdown spectroscopy. Several turbulence models were used for the steady-state Reynolds-averaged simulations, which included both linear and nonlinear eddy viscosity models. The scale-resolving simulations used a hybrid Reynolds-averaged/large-eddy simulation strategy that is designed to be a large-eddy simulation everywhere except in the inner portion (log layer and below) of the boundary layer. Hence, this formulation can be regarded as a wall-modeled large-eddy simulation. This effort was undertaken to not only assess the performance of the hybrid Reynolds-averaged/large-eddy simulation modeling approach in a flowfield of interest to the scramjet research community but also to begin to understand how this capability can best be used to augment standard Reynolds-averaged simulations. The numerical errors were quantified for the steady-state simulations and at least qualitatively assessed for the scale-resolving simulations before making any claims of predictive accuracy relative to the measurements. The steady-state Reynolds-averaged results displayed a high degree of variability when comparing the flameholder fuel distributions obtained from each turbulence model. This prompted the consideration of applying the higher-fidelity scale-resolving simulations as a surrogate “truth” model to calibrate the Reynolds-averaged closures in a nonreacting setting before their use for the combusting simulations. In general, the Reynolds-averaged velocity profile predictions at the lowest fueling level matched the particle imaging measurements almost as well as was observed for the nonreacting condition. However, the velocity field predictions proved to be more sensitive to the flameholder fueling rate than was indicated in the measurements.

Hybrid Reynolds-Averaged/Large-Eddy Simulation of a Cavity Flameholder: Modeling Sensitivities

Steady-state and scale-resolving simulations have been performed for flow in and around a model scramjet combustor flameholder. The cases simulated corresponded to those used to examine this flowfield experimentally using particle image velocimetry. A variety of turbulence models were used for the steady-state Reynolds-averaged simulations, which included both linear and nonlinear eddy viscosity models. The scale-resolving simulations used a hybrid Reynolds-averaged/large-eddy simulation strategy that is designed to be a large-eddy simulation everywhere except in the inner portion (log layer and below) of the boundary layer. Hence, this formulation can be regarded as a wall-modeled large-eddy simulation. This effort was undertaken to formally assess the performance of the hybrid Reynolds-averaged/large-eddy simulation modeling approach in a flowfield of interest to the scramjet research community. The numerical errors were quantified for both the steady-state and scale-resolving simulations before making any claims of predictive accuracy relative to the measurements. The hybrid Reynolds-averaged/large-eddy simulation results were also carefully scrutinized to ensure that even the coarsest grid had an acceptable level of resolution to meet accepted guidelines for large-eddy simulation and that the time-averaged statistics were acceptably accurate. The autocorrelation and its Fourier transform were the primary tools used for this assessment. Both simulation strategies accurately predicted the mean streamwise velocity distribution within the cavity, although the Reynolds-averaged simulations that used a linear eddy viscosity model tended to overpredict the strength of the primary cavity recirculation zone. Second-order moments of the velocity field were found to be highly sensitive to the turbulence model chosen for the Reynolds-averaged simulations, with all models overpredicting the intensity of the velocity fluctuations within the cavity flameholder. The hybrid Reynolds-averaged/large-eddy simulation results also overpredicted the velocity variances and covariances, unless a filtering operation was applied using a filter size that matched the control volume used to process the particle image velocimetry measurements. This observation suggests that a significant fraction of the turbulence energy was not resolved by the measurements. Taking this uncertainty into account, the second-order statistics extracted from the hybrid simulation strategy could not be shown to be any more accurate than the “best” Reynolds-averaged result.

A combined treatment of UV-assisted TiO2 photocatalysis and high hydrostatic pressure to inactivate internalized murine norovirus

Abstract Human norovirus (HuNoV) is a major cause of foodborne illness associated with shellfish consumption. A solidified agar matrix (SAM) was experimentally prepared using agar solution for inactivation of murine norovirus (MNV-1) as a surrogate for HuNoV in a simulation model approach. MNV-1 was injected inside the SAM for virus internalization, and the effects of single and combined UV-assisted TiO 2 photocatalysis (UVTP) and high hydrostatic pressure (HHP) treatments were determined. The internalized MNV-1 were reduced by 2.9-log 10 and 3.5-log 10 , respectively, after single treatments of UVTP (4.5 mW/cm 2 , 10 min) and HHP (500 MPa, 5 min, ambient temperature). However, the internalized MNV-1 was reduced by 5.5-log 10 (below the detection limit) when UVTP was followed by HHP, indicating a synergistic inactivation effect. Analysis of viral morphology, proteins, and genomic RNA allowed elucidation of mechanisms involved in the synergistic antiviral activity of combined treatments, which appeared to disrupt the MNV-1 structure and damage both the capsid protein and genomic RNA. Industrial relevance HHP treatment of raw oysters has proved commercially successful, but there is a less evidence available regarding the potential of HHP for inactivation of localized viruses present inside foods. A sequential combination of UV-assisted TiO 2 photocatalysis (UVTP) and high hydrostatic pressure (HHP) achieved significantly higher inactivation of localized virus compared to individual treatments due to a synergistic mechanism. An experimentally prepared model food system was found useful to simulate foods with morphological variations and unpredictable viral internalization patterns. This UVTP-HHP combined treatment for inactivation of localized MNV-1 can be useful for disinfection of raw oysters and other similar foods.

A case study of take away restaurant using simulation modelling approach

A model is proposed here for The Take away Restaurant. The model is developed under the assumption that there is no limit for the number of customer’s arrival and there is limited number of servers who will attend customers. At the time of heavy rush that is at dinner time, overcrowding is major problem, which may effect profit as well as goodwill of restaurant. Studying and analyzing such type of restaurants from long period of time, we have noticed continuous increase in number of customers as well as in number of restaurants. So it is a big question in front of management how to provide best service in lesser time so that their customer could not move to other options. Long waiting queues is a big issue for a customer as he is not ready to wait for a long time. When we asked to many customers the reason for switching to other restaurants from a particular restaurant, they pointed on issues like insufficient personnel and long waiting time. To overcome these situations, we will use queuing model which can provide reasonably accurate evaluations of our system’s performance in the light of Simulation modeling.

Flow and contaminant dispersion analysis around a model building using non-linear eddy viscosity model and large eddy simulation

In the present paper, the analysis of concentration and flow fields around a model building was performed using two different approaches in turbulence modeling. In the first approach, the non-linear model of Ehrhard and Moussiopoulos was employed as one of the best cubic non-linear eddy viscosity models, and large eddy simulation was utilized in the second approach. The obtained results suggest that although the non-linear model has the ability to predict the anisotropic normal components of Reynolds stress tensor, due to time-averaged nature of its governing equations, it is incapable of estimating the correct values of Reynolds stress components and turbulent characteristics in the wake region of the model building. So the predicted turbulence kinetic energy values by the non-linear model are 45% smaller than those of large eddy simulation approach in the wake region behind the model building. Also different predictions of the wake region structure by the non-linear model and large eddy simulation approach revealed that elongation of iso-surface for \(\left\langle K \right\rangle\) = 1.5 in non-linear model is 56% more than that of large eddy simulation approach. The large eddy simulation approach shows much consistent behavior to the physics governing the flow compared to the non-linear model. Also good agreement observed between the results obtained through this approach and the experimental data. However, the disadvantage of large eddy simulation approach is the high computational costs.

Modeling and data assessment of longitudinal salinity in a low-gradient estuarine river

Continuous data of vertical-profile salinity were analyzed for four stations located successively upriver in a macrotidal estuary, the lower St. Johns River (Northeast Florida, USA). The data analysis confirmed well-mixed salinity conditions in the river with at most 1.3 ppt of vertical variability at Dames Point (river km 20), where the main variations of salinity are along the longitudinal axis of the river. Given the well-mixed salinity conditions and dominant horizontal structure of salinity variations in the river, we present and apply a barotropic, two-dimensional modeling approach for hydrodynamic-salinity transport simulation in the lower St. Johns River. When properly forced by offshore surge, high-resolution wind fields and freshwater river inflows, the model replicated the salinity measurements remarkably well, including the separation into tidal and sub-tidal components. The data and model results show that, at times, offshore winds and surge can be more influential on longitudinal salinity variations than local winds over the river. We demonstrate the importance of using proper boundary conditions to force the model relative to the minimal sensitivity of the model to parameter adjustment of horizontal mixing and uncertainty-based perturbation of wind and inflow forcings.

Experimental Simulation: Using Generative Modeling and Palaeoecological Data to Understand Human-Environment Interactions

The amount of palaeoecological information available continues to grow rapidly, providing improved descriptions of the dynamics of past ecosystems and enabling them to be seen from new perspectives. At the same time, there has been concern over whether palaeoecological enquiry needs to move beyond descriptive inference to a more hypothesis-focussed or experimental approach; however, the extent to which conventional hypothesis-driven scientific frameworks can be applied to historical contexts (i.e., the past) is the subject of ongoing debate. In other disciplines concerned with human-environment interactions, including physical geography and archaeology, there has been growing use of generative simulation models, typified by agent-based approaches. Generative modelling encourages counter-factual questioning (“what if…?”), a mode of argument that is particularly important in systems and time-periods, such as the Holocene and now the Anthropocene, where the effects of humans and other biophysical processes are deeply intertwined. However, palaeoecologically focused simulation of the dynamics of the ecosystems of the past either seems to be conducted to assess the applicability of some model to the future or treats humans simplistically as external forcing factors. In this review we consider how generative simulation-modelling approaches could contribute to our understanding of past human-environment interactions. We consider two key issues: the need for null models for understanding past dynamics and the need to be able learn more from pattern-based analysis. In this light, we argue that there is considerable scope for palaeocology to benefit from developments in generative models and their evaluation. We discuss the view that simulation is a form of experiment and, by using case studies, consider how the many patterns available to palaeoecologists can support model evaluation in a way that moves beyond simplistic pattern-matching and how such models might also inform us about the data themselves and the processes generating them. Our emphasis is on how generative simulation might complement traditional palaeoecological methods and proxies rather than on a detailed overview of the modelling methods themselves.

Bending the carbon curve: fire management for carbon resilience under climate change

Forest landscapes are increasingly managed for fire resilience, particularly in the western US which has recently experienced drought and widespread, high-severity wildfires. Fuel reduction treatments have been effective where fires coincide with treated areas. Fuel treatments also have the potential to reduce drought-mortality if tree density is uncharacteristically high, and to increase long-term carbon storage by reducing high-severity fire probability. Assess whether fuel treatments reduce fire intensity and spread and increase carbon storage under climate change. We used a simulation modeling approach that couples a landscape model of forest disturbance and succession with an ecosystem model of carbon dynamics (Century), to quantify the interacting effects of climate change, fuel treatments and wildfire for carbon storage potential in a mixed-conifer forest in the western USA. Our results suggest that fuel treatments have the potential to ‘bend the C curve’, maintaining carbon resilience despite climate change and climate-related changes to the fire regime. Simulated fuel treatments resulted in reduced fire spread and severity. There was partial compensation of C lost during fuel treatments with increased growth of residual stock due to greater available soil water, as well as a shift in species composition to more drought- and fire-tolerant Pinus jeffreyi at the expense of shade-tolerant, fire-susceptible Abies concolor. Forest resilience to global change can be achieved through management that reduces drought stress and supports the establishment and dominance of tree species that are more fire- and drought-resistant, however, achieving a net C gain from fuel treatments may take decades.

Reliability of SAC 105 and SAC1205N under Drop Tests

Abstract In this paper, the solder joint failure and the solder joint fatigue life in the Thin-profile Fine-pitch Ball Grid Array (TFBGA) Package was investigated by performing the drop test, and implementing a simulation model. Owing to the need to meet the increasing demands for functionality, microelectronic package reliability can be compromised and has become the key issue when executing drop tests. During impact in drop test, the deformation of PCB due to bending and mechanical shocks can cause solder joint crack. While this is a well-known issue, observing the solder joint responses during the test execution can be a challenge. Therefore, in this work, a simulation model approach has been developed to investigate the stress and strain of the solder joint during the drop test. In this research, the JEDEC Condition B drop test was simulated, characterized by 1500G peak acceleration and 0.5 ms duration. The drop test simulation model was successful in predicting the solder joint fatigue life with different solder joint materials, such as SAC105 and SAC1205N, while also facilitating result comparison to identify the most optimal structure.

Simulation modelling as a tool for knowledge mobilisation in health policy settings: a case study protocol.

BackgroundEvidence-informed decision-making is essential to ensure that health programs and services are effective and offer value for money; however, barriers to the use of evidence persist. Emerging systems science approaches and advances in technology are providing new methods and tools to facilitate evidence-based decision-making. Simulation modelling offers a unique tool for synthesising and leveraging existing evidence, data and expert local knowledge to examine, in a robust, low risk and low cost way, the likely impact of alternative policy and service provision scenarios. This case study will evaluate participatory simulation modelling to inform the prevention and management of gestational diabetes mellitus (GDM). The risks associated with GDM are well recognised; however, debate remains regarding diagnostic thresholds and whether screening and treatment to reduce maternal glucose levels reduce the associated risks. A diagnosis of GDM may provide a leverage point for multidisciplinary lifestyle modification interventions. This research will apply and evaluate a simulation modelling approach to understand the complex interrelation of factors that drive GDM rates, test options for screening and interventions, and optimise the use of evidence to inform policy and program decision-making.Methods/DesignThe study design will use mixed methods to achieve the objectives. Policy, clinical practice and research experts will work collaboratively to develop, test and validate a simulation model of GDM in the Australian Capital Territory (ACT). The model will be applied to support evidence-informed policy dialogues with diverse stakeholders for the management of GDM in the ACT. Qualitative methods will be used to evaluate simulation modelling as an evidence synthesis tool to support evidence-based decision-making. Interviews and analysis of workshop recordings will focus on the participants’ engagement in the modelling process; perceived value of the participatory process, perceived commitment, influence and confidence of stakeholders in implementing policy and program decisions identified in the modelling process; and the impact of the process in terms of policy and program change.DiscussionThe study will generate empirical evidence on the feasibility and potential value of simulation modelling to support knowledge mobilisation and consensus building in health settings.

Implementation of demand response strategies in a multi-purpose commercial building using a whole-building simulation model approach

This paper exploits a whole-building energy simulation approach to develop and evaluate demand response strategies for commercial buildings. The research is motivated by the increasing penetration of renewable energy sources such as wind and solar, which owing to their stochastic nature, means that enhanced integration of demand response measures in buildings is becoming more challenging and complex. Using EnergyPlus, a simulation model of a multi-purpose commercial building was developed and calibrated. Demand response strategies are evaluated for a number of building zones, which utilise different heating, cooling and ventilation equipment. The results show that for events of varying demand response durations, different strategies should be selected for each zone based on their thermal and usage profiles. Overall, a maximum reduction of 14.7% in electrical power demand was recorded when targeting a centralised chiller load, with smaller reductions for other decentralised building loads.

Insights into the structural perturbations of spliced variants of CD44: a modeling and simulation approach

Transient interactions between cancer stem cells and components of the tumor microenvironment initiate various signaling pathways crucial for carcinogenesis. Predominant hyaluronan (HA) receptor, CD44 is structurally and functionally one of the most variable cell surface receptors having the potential to generate a diverse repertory of CD44 isoforms by alternative splicing of variant exons and post-translational modifications. A structurally distinctive variant of CD44, CD44v10, has an inevitable role in malignant progression, invasion, and metastasis. This can be attributed to the binding of HA with CD44v10, which demonstrates a completely different behavioral pattern as compared to the other spliced variants of CD44 molecule. Absence of a comprehensively predicted crystal structure of human CD44s and CD44v10 is an impediment in understanding the resultant structural alterations caused by the binding of HA. Thus, in this study, we aim to predict the CD44s and CD44v10 structures to their closest native confirmation and study the HA binding-induced structural perturbations using homology modeling, molecular docking, and MD simulation approach. The results depicted that modeled 3D structures of CD44s and CD44v10 isoforms were found to be stable throughout MD simulations; however, a substantial decrease was observed in the binding affinity of HA with CD44v10 (−5.355 kcal/mol) as compared to CD44s. Furthermore, loss and gain of several H-bonds and hydrophobic interactions in CD44v10–HA complex during the simulation process not only elucidated the reason for decreased binding affinity for HA but also prompted toward the plausible role of HA-induced structural perturbations in occurrence and progression of carcinogenesis.

Using Simulation Modeling Approach to Predict USMLE Steps 1 and 2 Performances

Using Simulation Modeling Approach to Predict USMLE Steps 1 and 2 Performances

Bicycle-Bicycle Accidents Emerge from Encounters: An Agent-Based Approach

Traditional accident risk prediction models need adequate data on explanatory variables, most importantly data on traffic flows. However, in the case of accidents between bicycles the availability of such data is often limited. Therefore, alternative bottom-up simulation modelling approaches are expected to complement traditional equation-based models. In this paper we present an agent-based approach to explore bicycle-bicycle accidents. Specifically, we hypothesise that (1) bicycle-bicycle accidents are based on the population of encounters between cyclists rather than on bicycle flows and (2) that encounters have a non-linear relationship with flows. Bicycle flows and encounters are simulated by means of an agent-based model that is implemented for the road network of the city of Salzburg. Simulation results are tested against a 10-year dataset of police records on bicycle-bicycle accidents. The results affirm both hypotheses: First, cyclist encounters exhibit a linear relationship to accidents and thus suggest being the true population of bicycle-bicycle accidents. Second, flows show a relationship in the form of a second-order polynomial function with encounters as well as accidents.

Modeling Hypervelocity-Impact-Induced Shock Waves for Characterizing Orbital Debris-Produced Damage

Hypervelocity impact (HVI) is a scenario involving an impacting velocity in excess of 1 km/s. Ubiquitous in outer space, paradigms of HVI are typified by the collision between orbital debris and spacecraft. HVI features transient, localized, and extreme material deformation under which the induced acoustic emission (AE) signals present unique yet complex features. A dedicated modeling and numerical simulation approach, based on the three-dimensional smooth-particle hydrodynamics (SPH), was developed to gain an insight into characteristics of HVI-induced AE propagation. With the approach, both normal and oblique HVI scenarios were interrogated, and material failure in both cases was predicted. The coincidence in results between simulation and HVI experiment, as observed at a qualitative degree, has demonstrated the effectiveness of the modeling. Signal analysis shows that the shock wave converts to Lamb wave quickly as propagation from HVI spot, with the zeroth-order symmetric wave mode (S0) (i.e., the first-arrival wave) dominating wave signal energy. S0 is observed dispersive in a wide frequency range with majority of it below 1 MHz. In comparison, the antisymmetric wave mode distributes in a range below 200 kHz with a peak value at 30 kHz. S0 was employed to pinpoint the location of HVI, using an enhanced delay-and-sum-based diagnostic imaging algorithm, which was validated by locating orbital debris-induced orifice in space structures, showing precise identification results.

Temporal evolution of the selectivity-permeability relationship during porous membrane filtration of protein solutions

Currently, there is no clear understanding on the effects of membrane properties on temporal evolution of membrane selectivity-permeability relationships during microfiltration or ultrafiltration-based water treatment. In this study, porous polyvinylidene fluoride (PVDF) membrane, polyvinyl chloride membrane, and glass-fiber membrane with distinctive physical and chemical properties were employed to filter bovine serum albumin (BSA) at different pH, coupled with model simulation approaches. Both the experimental results and model prediction showed that, due to the existence of different filtration mechanisms, selectivity of the PVDF membrane and the PVC membrane increase with decreasing permeability, whereas an opposite trend was observed for the glass-fiber membrane. Also, pH strongly affected permeability by changing the zeta potentials of the solutes and the membrane surfaces. Moreover, membrane selectivity was less significantly affected by pH for the polymeric membranes than for the glass-fiber membrane. Practically, high selectivity and permeability may be simultaneously achieved during water treatment by: (1) selection of membranes with suitable pore structure (such as control of solute diameter >1/5 pore diameter); (2) control of feed water condition (such as pH) to suppress intermolecular interactions or solute-membrane interactions, further influence the deposition/adsorption of solute on membrane.

Numerical Investigation of Compound Angle Effusion Cooling Using Differential Reynolds Stress Model and Zonal Detached Eddy Simulation Approaches

Effusion cooling is one of the most effective and widespread techniques to prevent combustor liner from being damaged. However, most recent developments in combustion techniques, resulting from increasingly stricter air pollution regulations, have highlighted the necessity of reducing the amount of air available for effusion cooling while keeping an adequate level of protection. Adoption of compound angles in effusion cooling is increasingly recognized by jet engine manufacturers as a powerful solution to meet new combustor requirements. Therefore, understanding the flow behavior and developing methods able to provide accurate estimates of wall temperatures is of a major importance. This study assesses the capability of a high-level Reynolds-averaged Navier–Stokes (RANS) method, differential Reynolds stress model (DRSM), in conjunction with a generalized gradient diffusion hypothesis (GGDH), and of a hybrid RANS–large eddy simulations (LES) method, zonal detached eddy simulation (ZDES), to predict overall film effectiveness. Both approaches are compared with the experimental data from Zhang et al. (2009, “Cooling Effectiveness of Effusion Walls With Deflection Hole Angles Measured by Infrared Imaging,” Appl. Therm. Eng., 29(5), pp. 966–972) and with a classical well-known RANS model (k–ω shear-stress transport (SST) model). Despite the fact that some discrepancies are found, both approaches have proved suitable and reliable for predicting wall temperatures (relative errors of about 5%). Moreover, a new method to deal with ZDES length scales for unstructured grids is proposed. ZDES applicability and its general advantages and drawbacks are also discussed. Finally, an in-depth analysis of the film structure is carried out on the basis of the ZDES simulations. The principal structures are identified (an asymmetric main vortex (AMV) and a counter rotating vortex pair, CRVP), and the film formation mechanisms are presented. Significant spanwise-homogeneous distributions of surface overall film cooling effectiveness are observed.