Accurate Simulation Research Articles

Underwater acoustic propagation and scattering from a dynamic rough sea surface using the Finite-Difference Time-Domain method.

Models for underwater acoustic propagation typically assume that the sea surface is smooth or rough but frozen in time. Long-duration transmissions on the order of tens of seconds are being considered for next-generation SONAR. These types of signals improve target resolution and tracking. However, they can interact with the sea surface at many different wave displacements during transmission. This violates the "frozen" boundary assumption and causes additional transmission losses and Doppler effects on the received signal. Full-wave propagation models can be used to better understand the mechanisms behind these phenomena. This understanding leads to better system design without having to perform expensive at-sea experiments. In this paper, a finite-difference time-domain (FDTD) method is implemented to model the impact of roughness and motion on the sea surface. The FDTD method is a full-wave numeric technique that allows an arbitrary function to define the boundary points. Surface motion is accomplished by modifying these boundary points at each time step. A variable subgrid sea surface boundary technique is developed to improve the accuracy of these FDTD simulations. The rough, time-evolving sea surface is modeled using a Pierson-Moskowitz frequency spectrum, which is simple to implement and fully defined by wind speed and direction.

Weighted compact nonlinear scheme based on smooth scale separation for self-adaptive turbulence eddy simulations

Multiscale compressible turbulent flow is widely present in the aerospace field, and the co-existence of shock wave discontinuities and multi-scale turbulence in the flow field poses significant challenges for high-fidelity numerical simulation. To design high-order nonlinear scheme to improve the accuracy of complex turbulence simulation with stable shock wave capture, a weighted compact nonlinear scheme – targeted essentially non-oscillatory (WCNS-T) scheme is developed based on targeted essentially non-oscillatory scheme within the WCNS framework. Also, an improved variant of WCNS-T with smooth scale separation (denoted as WCNS-ST) is proposed from the perspective of both numerical convergence and accuracy. The numerical properties of different nonlinear weights are discussed in classical numerical problems, including spectral properties analysis, and two-dimensional Riemann problem. Then, the newly developed WCNS-ST scheme based on smooth scale separation was used to combine a unified turbulence model called Self-Adaptive Turbulence Eddy Simulation (SATES), which is applied to simulate subsonic flow past a 30P30N airfoil and supersonic base flow. The good convergence and numerical results are obtained using the newly developed WCNS-ST scheme, whereas WCNS-T shows worse convergence. In addition, adaptive dissipation control is further introduced for the WCNS-ST scheme, and the new variant (denoted as WCNS-STA) still shows good residual convergence and predicts more accurate results due to low numerical dissipation. The above results indicate that the proposed smooth scale separation and its WCNS-STA scheme have a good performance in SATES simulations of multiscale flow problems, making it more potential for complex engineering applications.

Deformable-boundary integral formulation for the solution of arbitrarily-forced acoustic wave equation

The propagation of perturbations in fluids is governed by an acoustic wave equation. This paper, first, introduces an arbitrarily-forced wave equation which, properly adapted, gives rise to equations describing specific phenomena of signal perturbation propagation in fluids (like, for instance, the Lighthill and Ffowcs-Williams and Hawkings equations for radiation and scattering). Then, its solution is determined through a novel boundary integral formulation based on the free-space Green function, which is applicable to fluid domains bounded by solid or porous deformable surfaces. Different versions of the proposed boundary integral formulation can be derived, depending on the frame of reference in which they are expressed. The numerical investigation begins with the comparison of the results obtained by the presented formulation against analytical solutions concerning both a pulsating solid sphere and a deformable porous surface that encloses pulsating sources. Then, the equivalence of the formulations expressed in different frames is examined for a bending and twisting non-lifting wing translating at different Mach numbers. Finally, the aeroacoustic field generated by a helicopter rotor model in forward flight is examined to assess the effect of the body deformation on the radiated noise and the accuracy of the numerical simulations by comparison with experimental data. The results of the numerical investigation have provided a comprehensive validation of the deformable-boundary integral formulation presented for the analysis of wave propagation in fluids, and confirmed its capability to study problems of engineering interest.

Extracting waterline and inverting tidal flats topography based on Sentinel-2 remote sensing images: A case study of the northern part of the North Jiangsu radial sand ridges

Muddy tidal flats with landforms vary widely over space and time. The evolution of tidal flats topography has had a significant impact on the region. Therefore, there is a need to develop methods for rapidly and accurately characterizing tidal flats topography. This study applied thresholding segmentation (TS), machine learning, and two image classification methods to Sentinel-2 remote sensing images to extract the instantaneous waterline of the northern part of the North Jiangsu Radial sand Ridges (NJRSR). Tidal level data at specific time intervals were obtained using the Delft3D and TPXO9 models, after which tidal flats topography inversion was conducted. As a result, varied among the different classification methods, with the K-Nearest Neighbors (KNN) algorithm producing the optimal waterline extraction. Furthermore, the accuracy of tidal level simulation was improved by employing Delft3D software and constructing a scaled-down model of the study area. Comparisons with Delft3D model simulations of tidal levels with observations at three tide gauge stations yielded accuracies of 17.5 cm, 18.5 cm and 17.9 cm, this result showed that the establishment of the tidal level model can enhance the accuracy of tidal flats Digital Elevation Model (DEM) inversion. In fact, the combined application of the KNN algorithm and Delft3D model within retrieval of tidal level provided the most accurate topographic inversion, with an average error of 0.297 m, which was reduced to 0.292 m after median filtering, and the results indicated a trend of southward erosion in the tidal flats in the study area, with a turning point roughly located in the southern part of Doulong Port. The results of this study can help improve the future monitoring of dynamic changes in intertidal wetland topography and the conservation and development of tidal flats areas.

Research on Multi-type and Multi-level Real-time Simulation and Optimization of New Power System

Abstract Aiming at the problem that the current real-time simulation algorithm is difficult to improve the performance and accuracy of multi-type and multi-level real-time simulation when dealing with new power systems, we propose a new multi-type and multi-level real-time simulation and optimization algorithm for power systems. Firstly, the efficiency and accuracy of the solution are improved by directly updating the conductance nodes (Gnodes) and current nodes (Inodes) on power system components, and the updating of Gnodes and Inodes is replaced by the prior calculation based on the inverse matrix (Ginv) of admittance matrix, thus further optimizing the simulation solution process and reducing the computational complexity. Then, the efficient numerical method, data structure optimization, and parallel computing technology are used to optimize the construction process of the inverse matrix (Ginv) of the admittance matrix to reduce the computational complexity and memory consumption of electromagnetic transient simulation. Finally, the idea of the sparse matrix is introduced to optimize the operation process of Gstruct and improve the calculation speed of the simulation solution. The research proves that the multi-type and multi-level real-time simulation solution and its optimization method of new power systems can be studied more systematically through the above technical route, which can improve the efficiency and accuracy of power system simulation solutions and provide strong support for practical application.

Calibration of discrete element method simulation parameters for lunar rover using simulated lunar soil

Abstract To ensure the accuracy and scientific validity of simulation results in discrete element simulation of simulated lunar soil and sieve wheels for lunar surface probes, a method for calibrating the simulation parameters of an analog lunar soil simulation using a box-Behnken experimental design is proposed. First, the particle model and particle size distribution of the discrete element simulation were calibrated based on the determination of the intrinsic parameters, shape parameters, and particle size parameters of this simulated lunar soil. A Box-Behnken experimental design is employed to conduct response surface simulation experiments for the pile angle, obtaining optimal parameter values. The optimal parameter values are applied in the simulation validation, revealing a relative error of only 3% compared to the actual pile angle. This indicates that the obtained results can serve as calibrated values.

Cooling performance study of a new cooling system in subway tunnel based on field measurement and CFD simulation

Abstract Some cities’ subways were constructed early and have been in operation for a long time. A large amount of heat accumulates in the rocks around the subway tunnels, causing the phenomenon of heat accumulation. This situation leads to the inadequate cooling capability of train air-conditioning systems, which, may even cease to function under extreme conditions. Currently, few solutions are available to address this issue. Therefore, this study proposes a new cooling system in subway tunnel. Considering the dusty environment inside the tunnel, the terminal equipment mainly consists of natural convection copper tube finless heat exchangers and a self-flushing device without fans, which cool using piston wind. By comparing field measurements of two tunnels with and without the cooling system in similar locations, the results show that the air temperature in the tunnels is reduced after the cooling system is installed. The results indicate that the average temperature in the tunnels decreases from 30.93 °C to 19.80 °C, marking a reduction of 11.13 °C after the cooling system runs for 24 hours. The temperature change in the tunnel is a long-term process, and actual measurements require significant time consumption. In this study, the long-term effect is predicted using CFD simulation in tunnels. The accuracy and credibility of the CFD simulation have been confirmed through its reasonable agreement with experimental data, with the final temperature after 24 hours achieving a relative error of less than 0.26%. Through the simulation, the temperature at a depth of 10 cm inside the tunnel wall after 24 hours is determined to be 27.56 °C, indicating a reduction of 3.44 °C compared to the initial temperature of 31 °C. This study can provide a reference for other subway tunnel cooling systems and serves as a basis for CFD simulations to verify cooling effects.

An accurate and robust method for intensification of wastewater sludge pipe flow

Globally, environmental impacts and population growth are driving the process intensification of wastewater treatment plants (WWTPs) via transition from conventional (2–3 wt% solids) to highly concentrated (4–6 wt% solids) wastewater sludges (HCWS). This presents an industrial challenge as HCWS are complex, non-Newtonian materials whose viscosity increases nonlinearly with solids concentration. This viscosity increase is particularly relevant for sludge pipe flow as it leads to considerable pumping pressure that ultimately limits the feasibility of pipe flow transportation. Hence, process intensification demands accurate prediction of HCWS turbulent pipe flow to design and optimise pumping infrastructure and piping systems. Such prediction requires accurate rheological characterisation of HCWS and numerical prediction of HCWS turbulent pipe flow, neither of which has been achieved to date due to respective limitations associated with benchtop rheometry and numerical turbulence models. We address these challenges by first developing accurate methods for rheological characterisation of HCWS via laminar flow of digested sludge at various solids concentrations (2–5 %) in a fully instrumented pipe loop facility at a large-scale WWTP. These rheological parameters are used in direct numerical simulation (DNS) computations (that avoid turbulence models) of turbulent pipe flow of HCWS. These predictions are then validated against turbulent flow pipe loop data. This method yields accurate (2–15 % error) predictions of HCWS turbulent pipe flow, compared with up to ∼75 % error for conventional pipe flow correlations. This validation highlights the need for accurate rheological characterisation and numerical simulation to predict HCWS pipe flow and provides a sound basis for the intensification and optimisation of WWTP pipeline systems.

How numerical simulations helped to achieve breakeven on the NIF

The inertial confinement fusion program relies upon detailed simulations with inertial confinement fusion (ICF) codes to design targets and to interpret the experimental results. These simulations treat as much physics from essential principles as is practical, including laser deposition, cross beam energy transfer, x-ray production and transport, nonlocal thermal equilibrium kinetics, thermal transport, hydrodynamic instabilities, thermonuclear burn, and transport of reaction products. Improvements in radiation hydrodynamic code capabilities and vast increases in computing power have enabled more realistic, accurate 3D simulations that treat all known asymmetry sources. We describe how numerical simulations helped to guide the program, assess the impediments to breakeven, and optimize every aspect of target design. A preshot simulation of the first National Ignition Facility experiment that surpassed breakeven predicted an increased yield that matches the experimental result, within the preshot predicted uncertainty, with a target gain of 1.5. We will cover the key developments in Lawrence Livermore National Laboratory ICF codes that enabled these simulations and give specific examples of how they helped to guide the program.

Numerical simulation and experimental investigation on friction stir welding of AZ31 magnesium alloy

Integrated numerical simulations and experimental investigations were employed to scrutinize the thermal, mechanical, and microstructural transformations of the AZ31 magnesium alloy during the friction stir welding (FSW) process. Especially, the primary focus was on the influence of process parameters such as rotational speed and welding speed on the temperature distribution, grain refinement, and mechanical properties of welded joints in alloys. By employing Deform-3D coupled with the integration of constitutive equations and dynamic recrystallization (DRX) models, the FSW process was investigated. The investigation revealed a significant increase in temperature when the tool’s shoulder made contact with the weld, resulting in the substantial accumulation of heat during FSW. Distinctions became apparent between the advancing side (AS) and the receding side (RS), with the AS exhibiting slightly elevated levels of temperature, equivalent stress, strain, and grain size. Specifically, adjustments in the rotational speed of the stirring tool and a reduction in welding speed resulted in larger grain sizes within the alloy. For example, when the rotational speed was set at 1200 rpm and the travel rate was 200 mm min−1, the initial grain size of the weld experienced a substantial decrease from 57.8 μm to 8.2 μm. Subsequent experimental verification, considering grain size and microhardness, was carried out to optimize FSW parameters for achieving the desired material properties. The accuracy of simulation results was validated through a meticulous comparison with experimental findings, underscoring the potential of numerical simulation in comprehending and predicting FSW processes.

New Drag Force Formula of Bending Stems in Deriving Analytical Solutions of Velocity Profile for Flow Through Flexible Vegetation

AbstractInvestigations of water flow movements affected by vegetation is a research hotspot in vegetation ecological restoration. The theory and equations of the flow velocity distribution under the influence of rigid vegetation are relatively mature. This study proposes a new drag force equation that varies with the vegetation bending angle and a new analytical solution of the velocity profile. Comparisons between the model calculation and experimental data, results showed that this new proposed model produced accurate simulations for flow through flexible vegetation for various deflections. In addition, this analytical model was verified to be applicable to rigid vegetation without a bending angle. Moreover, the features of the parameters adopted in this analytical equation are discussed, and the empirical equation for these parameters are presented. This study further improves the research in the field of environmental fluid mechanics and can serve as a theoretical underpinning for the ecological restoration of river courses.

Real-time seismic damage simulation for urban building portfolio based on basic building information and machine learning

Timely and accurate simulation of seismic damage of the urban building portfolio is essential for pre-earthquake planning and post-earthquake rescue. This study proposes a real-time seismic damage simulation method for the urban building portfolio based on the multiple degree-of-freedom (MDOF) shear and flexural-shear model established by basic building information and machine learning. The formulas for predicting periods of six types of structures are proposed, and the surrogate model-I for predicting the critical inter-story hysteretic parameters are established to optimize the MDOF models. The surrogate model-II is established to rapidly predict the engineering demand parameters and damage states of structures under earthquakes. Regarding the generalization capability, an incremental learning strategy is advised to guarantee the accuracy of the surrogate model-II in predicting the seismic damage of other urban building portfolios. The results in two city-scale cases show that the proposed method can achieve real-time seismic damage simulation of urban building portfolio with acceptable accuracy, and it’s not necessary to retrain or only needs minor additional training on the existing surrogate model when applied to other urban building portfolios.

A unified risk field-based driving behavior model for car-following and lane-changing behaviors simulation

The modeling of driving behavior is pivotal for the accurate simulation of traffic scenarios and for providing human-like decision-making of autonomous driving systems. Car-following (CF) and lane-changing (LC) behaviors are continuous maneuvers within traffic flow, generally modeled separately in the literature. The coherence between these two behaviors may be ignored, leading to unrealistic behavioral simulations. Therefore, this paper establishes a risk field-based driving behavior model for two-dimensional motion, ensuring coherent modeling of CF and LC behaviors under a unified framework. First, a risk quantification method is developed to calculate the risk in two-dimensional scenarios, accounting for risk over the preview time. A cubic polynomial is applied to generate path curves that align with vehicle dynamics. Second, the enhanced behavior model primarily comprises two integral components: path and trajectory planning. These two components aim to identify the path or trajectory that maximizes the benefit while meeting the desired risk. Third, the maximum acceptable risk, representing a higher risk than the desired risk, is defined to facilitate path adjustment and avoid frequent path adjustment. Finally, the proposed model is proved through comparisons with existing models using driving data. Several cases are employed for further analysis to show the model's rationality and potential in various aspects. This study develops the previous risk field-based behavior model from one-dimensional to two-dimensional scenarios, furnishes a unified framework for elucidating driving behavior in various scenarios, and contributes to the progress of behavior modeling.

Research and Simulation of Partial Discharge Phenomenon Sensing Technology for Substation Inspection Robots

Abstract This paper thoroughly investigates the phenomenon of partial discharge in substations and proposes a set of simulation experimental apparatus to replicate various types of partial discharge defects in switchgear. By modifying the switchgear, incorporating models for different types of partial discharge, and equipping various standard partial discharge sensors, accurate simulations of phenomena such as point discharge, suspended discharge, gap discharge, and particle discharge are achieved. Through this system, the effectiveness of different detection methods, such as ultrasonic, high-frequency, and transient voltage methods, is validated for various defect models. Furthermore, utilizing an indoor inspection robot guide rail, the paper simulates the environment of partial discharge in substations, enabling the validation of the robot’s partial discharge detection performance and typical patterns under different conditions. This work is dedicated to providing situational awareness technology for partial discharge phenomenon detection for substation inspection robots, so that the inspection robot can detect various abnormal partial discharge phenomena in transformers or other substation equipment through micro sensors to promote the stable operation of the substation.

Generalized quantum master equations can improve the accuracy of semiclassical predictions of multitime correlation functions

Multitime quantum correlation functions are central objects in physical science, offering a direct link between the experimental observables and the dynamics of an underlying model. While experiments such as 2D spectroscopy and quantum control can now measure such quantities, the accurate simulation of such responses remains computationally expensive and sometimes impossible, depending on the system’s complexity. A natural tool to employ is the generalized quantum master equation (GQME), which can offer computational savings by extending reference dynamics at a comparatively trivial cost. However, dynamical methods that can tackle chemical systems with atomistic resolution, such as those in the semiclassical hierarchy, often suffer from poor accuracy, limiting the credence one might lend to their results. By combining work on the accuracy-boosting formulation of semiclassical memory kernels with recent work on the multitime GQME, here we show for the first time that one can exploit a multitime semiclassical GQME to dramatically improve both the accuracy of coarse mean-field Ehrenfest dynamics and obtain orders of magnitude efficiency gains.

HEOM‐QUICK2: A general‐purpose simulator for fermionic many‐body open quantum systems—An update

AbstractMany‐body open quantum systems (OQSs) have a profound impact on various subdisciplines of physics, chemistry, and biology. Thus, the development of a computer program capable of accurately, efficiently, and versatilely simulating many‐body OQSs is highly desirable. In recent years, we have focused on the advancement of numerical algorithms based on the fermionic hierarchical equations of motion (HEOM) theory. Being in‐principle exact, this approach allows for the precise characterization of many‐body correlations, non‐Markovian memory, and non‐equilibrium thermodynamic conditions. These efforts now lead to the establishment of a new computer program, HEOM for QUantum Impurity with a Correlated Kernel, version 2 (HEOM‐QUICK2), which, to the best of our knowledge, is currently the only general‐purpose simulator for fermionic many‐body OQSs. Compared with version 1, the HEOM‐QUICK2 program features more efficient solvers for stationary states, more accurate treatment of non‐Markovian memory, and improved numerical stability for long‐time dissipative dynamics. Integrated with quantum chemistry software, HEOM‐QUICK2 has become a valuable theoretical tool for the precise simulation of realistic many‐body OQSs, particularly the single atomic or molecular junctions. Furthermore, the unprecedented precision achieved by HEOM‐QUICK2 enables accurate simulation of low‐energy spin excitations and coherent spin relaxation. The unique usefulness of HEOM‐QUICK2 is demonstrated through several examples of strongly correlated quantum impurity systems under non‐equilibrium conditions. Thus, the new HEOM‐QUICK2 program offers a powerful and comprehensive tool for studying many‐body OQSs with exotic quantum phenomena and exploring applications in various disciplines.This article is categorized under: Data Science > Computer Algorithms and Programming Software > Simulation Methods Theoretical and Physical Chemistry > Statistical Mechanics

Southern Hemisphere Circumpolar Wavenumber‐4 Pattern Simulated in SINTEX‐F2 Coupled Model

AbstractInterannual sea surface temperature (SST) variations in the subtropical‐midlatitude Southern Hemisphere are often associated with a circumpolar wavenumber‐4 (W4) pattern. This study is the first attempt to successfully simulate the SST‐W4 pattern using a state‐of‐the‐art coupled model called SINTEX‐F2 and clarify the underlying physical processes. It is found that the SST variability in the southwestern subtropical Pacific (SWSP) plays a key role in triggering atmospheric variability and generating the SST‐W4 pattern during austral summer (December‐February). In contrast, the tropical SST variability has a very limited effect. The anomalous convection and associated divergence over the SWSP induce atmospheric Rossby waves confined in the westerly jet. Then, the synoptic disturbances circumnavigate the subtropical Southern Hemisphere, establishing an atmospheric W4 pattern. The atmospheric W4 pattern has an equivalent barotropic structure in the troposphere, and it interacts with the upper ocean, causing variations in mixed layer depth due to latent heat flux (LHF) anomalies. As incoming climatological solar radiation goes into a thinner (thicker) mixed layer, the shallower (deeper) mixed layer promotes surface warming (cooling). This leads to positive (negative) SST anomalies, developing the SST‐W4 pattern during austral summer. Subsequently, anomalous entrainment due to the temperature difference between the mixed layer and the water below the mixed layer, anomalous LHF, and disappearance of the overlying atmospheric W4 pattern cause the decay of the SST‐W4 pattern during austral autumn. These results indicate that accurate simulation of the atmospheric forcing and the associated atmosphere‐ocean interaction is essential to capture the SST‐W4 pattern in coupled models.

Deep learning accelerated numerical simulation for three-dimensional compressible fluids

Numerical simulation of fluid flow is a long-standing challenge across many physical application domains, including engineering, climate, and the physical science. There has been a surge of interest in high order schemes aimed at improving simulation accuracy on coarse grids. However, for high-dimensional fluids, the computational cost escalates with the number of dimensions involved. In this paper, we propose a deep learning-based approach to accelerate the numerical computation and further improve the accuracy in simulating three-dimensional (3D) compressible fluids which can be described by Eulerian equations. The proposed work utilizes 3D Euler transformer networks to learn the interpolation coefficients for cell boundaries, which are applied to approximate the boundary fluxes of fluid on coarser grids. Benefiting from learning features of high-resolution fluid flow, our learned interpolation method yields finer performance on coarse grids, thereby accelerating the fluid simulations and improving the numerical accuracy. The numerical experiments confirm that the proposed method improves performance in inference of coarse-grained dynamics.

High-fidelity simulations of boundary layer transition on an underwater axisymmetric body with stability theory

During the cruise status of an underwater high-speed vehicle, the flow around the vehicle's head typically transitions from a laminar to a turbulent state, triggering flow noise that can interfere with the normal operation of sonar. In order to accurately investigate this flow noise through numerical simulation, a high-fidelity turbulent flow field solution is essential. Common traditional turbulence numerical simulation methods, such as unsteady Reynolds-averaged simulation and large eddy simulation (LES), struggle to capture high-frequency turbulent fluctuations accurately due to their inability to directly resolve small-scale eddy structures, which results in compromising the simulation accuracy of high-frequency flow noise. To address this issue, this paper employs direct numerical simulation (DNS) to achieve high-fidelity resolution of the turbulent flow field, thereby enabling a more accurate assessment of flow noise distribution on the vehicle's surface. Meanwhile, considering significant computational resources required to solve the entire flow field in an underwater high Reynolds number environment, this study also incorporates the fixed transition modeling method and stability theory to confine the DNS computational domain to the vicinity of the transitional zone to improve simulation efficiency. Comparative analysis of flow noise monitoring results in the laminar, transitional, and turbulent zones revealed that the flow noise source in the laminar zone exhibits the lowest amplitude across all frequencies, while the flow noise source in the transitional zone features the highest amplitude, approximately 10 dB higher than that in the turbulent zone. Moreover, significant amplitudes in high-frequency components (above 30 kHz) are detected in both the transition and turbulent zones. Additionally, this study employs LES with the Smagorinsky model to simulate the flow field within the same computational domain as DNS, demonstrating the limitations of the Smagorinsky model-based LES in capturing high-frequency flow noise.

Improving building natural ventilation simulation accuracy: calibration of standard k − ε closure coefficients using design of experiment

Abstract The objective of this study is to improve the accuracy of the standard k − ε (SKE) turbulence model for natural ventilation simulation, a critical component in the analysis and design of energy-efficient buildings. The methodology involves generating 17 design points for the four closure coefficients (C ɛ 1,C ɛ 2,C µ ,σ k ) for the SKE model using 2k full-factorial design of experiment (DOE) with a centre point. A sheltered single storey-building with windward and leeward openings is modelled and simulated using computational Fluid Dynamics (CFD) to obtain the Root Mean Square Error (RMSE) and Factor of two observation (FAC2) for each design point. Response models for RMSE and FAC2 are then generated, and optimization is employed to maximize FAC2, minimize RMSE, and the combination of both. The results are validated and compared with experimental and simulation data reported in existing literature. The findings indicate that the indoor velocity profiles with closure coefficients obtained by maximizing FAC2 are better aligned with the actual experimental results. Compared with the existing calibration method, the proposed calibration method can yield superior results with fewer sampling points, highlighting the efficiency of the proposed approach. The calibration framework developed in this study can be extended to other simulation scenarios, contributing to the robust and efficient modelling of natural ventilation systems in various contexts. This research presents a novel calibration method for the SKE model in natural ventilation simulation, providing a more accurate and efficient approach compared to existing methods. The results have important implications for researchers and practitioners working in the field of building energy simulation and sustainability.