International Journal of Engineering Systems Modelling and Simulation (23 papers in press)

Regular Issues

• FPGA implementation of low complexity super resolution scaling architecture for UHD display systems  
  by Chidadala Janardhan, K.Venkata Ramanaiah, K. Babulu 
  Abstract: Ultra high definition (UHD) technology has been changing the entertainment industry significantly and its content is severely short of supply due to limited content creators or hard to access due to insufficient network bandwidth. Recent improvements in CMOS image sensor technology, multimedia applications traditional standard display (SD) systems are not sufficient to display high-quality images. Conventional FPGA-based SR methods will exhibit more complexity and requires more hardware resources to perform. This paper describes low complexity super resolution scaling architecture (SRSA) for UHD systems. In our proposed method, bi-cubic interpolation is used for reconstruction the low-frequency image to high-frequency images, these bi-cubic interpolations will have the capability to interpolate sixteen nearest neighbours of a pixel. In addition to that high-frequency patches are overlapped to construct super resolutions images with using kernel algorithm. The proposed system generates the output image at 1,600 x 1,600 sizes from 800 x 800 image size. The proposed SRSA super-resolution technique is modelled in Verilog HDL and synthesised in Xilinx Zynq-7000 series FPGA and shown the comparison of area, delay, and power. From the simulation results, the performance of the proposed method can compete over the state of the art methods.
  Keywords: image interpolation; super resolution; image resolution; field programmable gate arrays; image restoration.
  DOI: 10.1504/IJESMS.2024.10063207
   
  
• Analysis of hole expansion test of aluminium alloy using finite element method simulation  
  by Yogesh Dewang, Vipin Sharma, Shashi Ranjan Mohan, Riyan Cyriac Jose 
  Abstract: The major problems associated with forming operations of metal sheets are edge failures often associated with the stretch flangeability of the material. Several ferrous and non-ferrous metals and their alloys have been studied in the recent decade to address the above mentioned issue. Stretch flangeability of a materials used in automotive applications is determined by several tests, the prominent ones being hole expansion test and uniaxial tensile test along with bending tests. The stretch flangeability of AA6016 was studied by finite element method hole expansion test. It is developed on ABAQUS/CAE 2020with implicit simulation. A finite element model is developed with appropriate material model for understanding the significance of physical parameters affecting the stretch flangeability. Simulation results provide a greater access to analyse mechanical properties acting under deformation.
  Keywords: automobile; sheet forming; hole expansion; FEM simulation; flanging; stretch frangibility.
  
  
• Rayleigh wave in rotating thermoelastic half-space under impedance boundary conditions, two-temperature, diffusion  
  by Heena Sharma, Sangeeta Kumari, Bharti Thakur 
  Abstract: In the present work, the governing equation of Rayleigh wave is considered with rotation, diffusion, and two-temperature under impedance boundary conditions for generalised thermoelastic half-space. The surface wave technique is used to solve the governing equation of Rayleigh wave to obtain the frequency equation. It also satisfies radiation conditions. Impact of rotation, initial stress, two-temperature, magnetic field, and diffusion with impedance boundary conditions numerically calculated. The effect of different parameters against dimensionless speed is presented graphically.
  Keywords: Rayleigh wave; frequency equation; generalised thermoelasticity; relaxation time; initial stress; two-temperature; magnetic field; rotation; diffusion; impedance boundary conditions; IBCs.
  DOI: 10.1504/IJESMS.2024.10063678
   
  
• DBPF pre-processing based improved ECG signal analysis in medical engineering applications  
  by Varun Gupta 
  Abstract: Bioinformatics is the essential field to capture and interpret the biomedical datasets. Among these datasets, heart is main organ which is responsible for circulation of the blood and appears in the form of electrocardiogram (ECG) signal. Unfortunately, the heart’s conduction is nonlinear in nature requiring utilisation of technological advancements. The activity of heart is signified by various small waves, viz., P-wave, QRS wave (complex), and T-wave. In this paper combination of three efficient techniques, viz., digital bandpass filtering (DBPF), Hilbert envelope, and factor analysis is used for ECG signal analysis. The analysis of ECG signal is done by estimating position of R-peaks in MIT-BIH Arrhythmia (MIT-BIH Arr) database and MIT-BIH Long-Term ECG database. The proposed technique is definitely important for medical engineering applications in estimating correct health condition.
  Keywords: bioinformatics; electrocardiogram; ECG; digital bandpass filter; Hilbert envelope; factor analysis; R-peaks.
  DOI: 10.1504/IJESMS.2024.10063747
   
  
• Role of biomedical devices on surgical applications - an outlook  
  by Md. Abdul Raheem Junaidi, Ram Chandra Murthy Kalluri, Y. V. Daseswara Rao 
  Abstract: The research mainly focuses on the three different types of laparoscopic instruments such as grasping, laparoscopic forceps, and suction irrigation devices with their design modifications and robot assistance activities. Some mechanical components such as links, sliders, gears, pivots, etc. are assisted in the working mechanism of the laparoscopic instruments. Despite of its potential demand, certain complexities are faced by surgeons due to its design characteristics. From the analysis, it is clear that several researchers are focused for optimise the design of forceps and handles in laparoscopic surgery. The process of suction and irrigation contributes well to laparoscopic surgery; however, the interest toward such a process is limited by the researchers. The existing researches of laparoscopic instrumental enhancement between the year 2011 and 2020 are symbolised in this work. This research promotes direction to several surgical device designers by adopting the additional innovative methodology for designing the novel laparoscopic instruments.
  Keywords: robotic device; laparoscopic instruments; minimal invasive surgery; Grasper; suction and irrigation medical device; CFD perspectives.
  DOI: 10.1504/IJESMS.2025.10064595
   
  
• Induction motor speed control performance enhancement using fractional order filters  
  by Saida Hassainia, Samir Ladaci, Sihem Kechida, Khaled Khelil 
  Abstract: This paper proposes a novel methodology for performance enhancement of simple feedback control by means of fractional order filters applied to the speed drive of an induction machine. Three performance indexes are used for this aim namely the integral square error (ISE), integral absolute error (IAE) and integral time absolute error (ITAE). A first order filter in different positions of the control loop is considered in presence of a noise source in order to design the filter configuration. Then, an optimisation of the fractional order filter is realised. Comparative simulation results are given to illustrate the superiority and robustness of the proposed control scheme with regard to integer order filters and unfiltered controllers.
  Keywords: fractional order filter; fractional order systems; induction machine; pi controller; performance index; speed control.
  DOI: 10.1504/IJESMS.2024.10064607
   
  
• A versatile biomedical device employed for diverse applications in minimally invasive surgical procedures  
  by Md. Abdul Raheem Junaidi 
  Abstract: The research revolutionises to introduce a new design of an instrument that combines the functionality of Maryland forceps with that of a suction irrigation device. Currently, the above two operations have to be carried out sequentially, which adds to the amount of time and effort spent by the surgeon. Integrating both these features within the same device can ensure that both processes can take place simultaneously or one after the other as many times as required, without unnecessary removal of the device from the incision. Thus the article has modelled the instrument which can potentially benefit in all other various laparoscopic procedures.
  Keywords: laparoscopic instruments; irrigation; suction; forceps; mechanism; multi-functional.
  DOI: 10.1504/IJESMS.2024.10064909
   
  
• A global thermal node model for analysing the effect of glass cover geometric parameters for no-load indirect solar dryer  
  by Ernest Léontin Lemoubou, Carine Pamela Aghogue Donchi, Hervé Thierry Tagne Kamdem, René Tchinda 
  Abstract: In this paper, a global thermal node model is developed for describing no-load indirect solar dryer with double-glass collector. The dryer is formed with drying unit and double air pass collector mounted with two absorber plates separated by confined air. The nodal model takes into account the time variations of solar flux, convection heat losses to the ambient and radiated flux from the soil surface. The mathematical model describing the transient heat transfer process is derived from the node theory, while the surface soil fluxes are approximated using the boundary layer similarity theory. The resulted equations are solved numerically using the iterative finite difference method. The results obtained indicate excellent agreement of the global node model proposed when compared predictions to experimental values of the literature. The simulation reveals significant effect of glass cover thickness and glass covers confined air thickness on the thermal behaviour of the dryer.
  Keywords: global node model; indirect solar dryer; numerical simulation; glass cover geometric parameters; boundary layer theory; dynamic conditions; thermal behaviour.
  DOI: 10.1504/IJESMS.2025.10065108
   
  
• Optimisation of deep learning-based models for the diagnosis of heart disease through ODTH method  
  by Monali Gulhane, T. Sajana 
  Abstract: In middle- and low-income countries, cardiovascular illnesses (CVDs) constitute the leading cause of death, with heart attacks and strokes accounting for around 80% of CVD-related fatalities. Enabling early intervention and treatment planning, effective cardiac irregularity prediction and the design of trustworthy heart disease prediction systems eventually lower death rates. This research investigated the viability of predicting cardiac disease using tabular data and convolutional neural networks (CNN). We first retrieved pertinent data from the collection of records, which was then abridged to 14 characteristics; each record is converted into heatmaps, and PNG files of the heatmaps are stored for further CNN processing and visualisation to DenseNet121, ResNet50 and VGG19. Using 10-fold cross-validation, we discovered that DenseNet121, in addition to the optimisation method stochastic gradient descent (SGD), performed better with 97% accuracy while the other two VGG19 54.39% and ResNet50is 51.00% models, performed low as compared to DenseNet121 in addition with the use of accuracy of 54.39% and 51.00%, respectively. Our research demonstrates that deep learning models are capable to correctly forecast heart disease from tabular data. In this paper, it is concluded that tabular data can be given as input to deep learning models to achieve better accuracy and good results can be observed for further study in the field of disease prediction.
  Keywords: machine learning; deep learning;DenseNet121; ResNet50; VGG19; optimisation.
  DOI: 10.1504/IJESMS.2024.10066247
   
  
• Modelling an SEIR model using saturated treatment function and analysing its stability: the effect of treating H3N2V affected patients by medicines  
  by A. Joshua Cyril Yagan, D. Jasmine 
  Abstract: Swine flu is a respiratory illness characterised by its intense spread during specific seasons, leading to concerns about the potential challenges caused by limited drug availability. This article presents a susceptible-exposed-infected-recovered (SEIR) model incorporating a saturated treatment function to address these concerns. Emphasising the crucial role of early medication in managing the infection, the model serves as a mathematical representation of the disease’s dynamics, featuring the novel inclusion of a saturated treatment function to better manage swine flu’s transmission challenges. This study emphasises early prescription medicine treatment for infected patients. A thorough methodology verifies the model’s positivity and boundedness to ensure it appropriately represents real-world disease dynamics. To better comprehend disease propagation, calculate the reproduction number and find the model’s equilibrium locations. The Gershgorin Circle theorem is used to test model stability, showing its capacity to capture disease transmission’s complicated dynamics. The essay uses numerical simulations to emphasise the need of timely and proper medicine in preventing illness development. This model-driven technique can avert swine flu pandemics by predicting pharmaceutical needs and reducing supply bottlenecks.
  Keywords: variant influenza; swine flu; H3N2; respiratory infection; pandemic; epidemic; SEIR compartmental model; saturated treatment function; reproduction number; model stability and implications.
  DOI: 10.1504/IJESMS.2024.10065300
   
  
• Multi-period planning of fish breeding chains and investigation of its efficiency under demand uncertainty  
  by Sajad Moradi 
  Abstract: This article studies an issue in the fish farming industry, aiming to find the best multi-period plan for managing various chains, including spawning, breeding, harvesting, and selling trout over a given time horizon. It provides a new mixed integer linear programming model that efficiently finds the optimum solution. In the proposed model, some intermediate stages of the breeding chains that do not affect key decisions are ignored, thereby reducing the size and complexity of the proposed model without compromising the optimality of the answers. When weekly demands are considered uncertain data, by simulating weekly demand, it is shown that using the first-in, first-out policy during the selling season, the schedule provided by the deterministic model, in which average value is considered for the weekly demand, will still be effective relatively. By analysing the obtained results, some approaches are suggested to improve the proposed program.
  Keywords: fishing industry; mathematical modelling; demands uncertainty; sales management; simulation.
  DOI: 10.1504/IJESMS.2024.10066291
   
  
• Fortifying cyber defence: unveiling the power of convolutional neural networks and cutting-edge data preprocessing methods for DDoS attack detection in the digital frontier  
  by Chris Harry Kandikattu, Sam Sangeeth Panguluri, Sandeep Kumar, Suneetha Bulla, Abdul Raheem Shaik 
  Abstract: With a global increase in the frequency of cyberattacks in the internet space, the digital sphere faces a significant upheaval in danger to an individual’s online presence and corporate entities. The work put forward in this paper takes advantage of deep learning techniques to improve security against DDoS attacks. The research paper provides a holistic approach to detecting DDoS attacks using convolutional neural networks (CNNs) combined with advanced data preprocessing methods. The proposed work in this research paper has been evaluated using two widely known and publicly available datasets, namely NSL-KDD and CSE-CIC-IDS208. The proposed work demonstrates that the proposed methodology consistently outperforms both datasets, achieving impressive accuracy scores of 97.46% and 98.53%. These findings underscore the promising potential of the proposed approach in enhancing the accuracy and effectiveness of intrusion detection systems.
  Keywords: distributed denial of service; DDoS; cloud attacks; cloud environment; cloud security.
  
  
• Quantum vs. classical methods in information security, computing and machine learning domains: an empirical study  
  by Kriti Srivastava, Akshit Gabhane, Ankit Ladva, Pushkar Waykole, S. Suman Rajest 
  Abstract: The rise in big data has necessitated the development of new computing technologies that can process large volumes of data in a faster and more efficient manner. In recent years, quantum computing has emerged as a promising candidate for this purpose due to its ability to work with high dimensionality data and its potential for solving complex problems that classical computers struggle with. This research work conducts a comparative analysis of quantum computing and classical computing in the fields of information security, computing, and machine learning, which are all critical fields in the modern world. The study uses a variety of methods, including theoretical analysis, simulation, and experimental implementation to demonstrate the benefits of quantum computing. This study serves as a basis for future research in the field of quantum computing and its applications, which could lead to significant advancements in various areas of science and technology.
  Keywords: comparative analysis; Grover’s algorithm; Shor’s algorithm; quantum computing; quantum SVM; quantum CNN; information security.
  
  
• Character classification enhancement through hybrid feature fusion in challenging scripts systems  
  by Sobia Habib, Manoj Kumar Shukla, Rajiv Kapoor 
  Abstract: One of the most intriguing research problems is to achieve high accuracy in character recognition of degraded scripts, which is essential for applications such as document digitisation, language translation, and text-to-speech systems. We aim to recognise two degraded scripts of Devanagari and Urdu languages, which have unique difficulties, mainly due to the presence of broken and merged dots. Traditional character recognition techniques, including template matching and feature-based methods, have been widely used but need to be more efficient to handle the complexities of Urdu and Devanagari scripts. We propose classifying damaged scripts using zone-based power curve fitting and a pre-trained VGG19 model that trains on script degradation patterns. Using 6,250 printed examples with distortions from damaged Devanagari and Urdu manuscripts, we fine-tune the VGG19 model. It helps the proposed model understand these characters’ intricate features and minimises overfitting. Our changes improve accuracy and strengthen the script damage detection system. Our results show that the VGG19 architecture works well across most feature extraction strategies, with accuracy scores ranging from 89.26% to 93.42%, while combining the power curve fitting methodology with VGG19 improves classification accuracy to 97.42%.
  Keywords: power curve fitting; VGG19; challenging scripts systems; broken characters; merged dots characters; deep learning features.
  
  
• Machine learning-driven innovations for energy efficiency engineering systems empower greener technologies  
  by R. Regin, K. Selvamani, S. Kanimozhi, Pallavi Ahire, Swakantik Mishra, Sukhwinder Sharma, Sushma Rani 
  Abstract: The research investigates the role of high-energy electronics as a key player in the strength efficiency and sustainability sector. In addition, we look at recent developments in power electronics, including advanced semiconductor materials and novel topologies with machine learning-enhanced control strategies to bring technological innovations towards climate-smart technology. Our process combines a complete literature research and architectural analysis to illuminate innovative power electronics through machine learning and data-driven optimisation. Where the consequences of this study not only show substantial enhancements in power performance and sustainability, but also strengthen the case for embedding advanced energy electronics across myriad programs perfectly aligned with eco-green tech. The discussion extends to how our results may influence the integration of renewable electricity, industrial strategies, and environmental sustainability through transformational system learning-driven innovations. This paper outlines a scenario where green technology meets machine learning to usher in a new era of energy efficiency for a greener planet, highlighting power electronics’ immense potential and future direction. Current constraints are noted as side comments.
  Keywords: sustainable power systems; machine learning optimisation; advanced power electronics; renewable energy integration; energy efficiency solutions; green technology innovations; smart grid technologies; eco-friendly semiconductor materials.
  
  
• Transforming electrical simulation and management with smart grid technologies  
  by K. Chitra, S.Silvia Priscila, Edwin Shalom Soji, R. Rajpriya, B. Gayathri, A. Chitra 
  Abstract: Electrical simulation and management are essential for ensuring reliable, efficient, and sustainable power supply to various consumers. However, the traditional power grid faces many challenges, such as ageing infrastructure, increasing demand, integration of renewable energy sources, power quality issues, and cyber-attacks. Smart grid technologies offer a promising solution to overcome these challenges and transform the electrical distribution and management system. Intelligent grid systems encompass sophisticated sensing technology, advanced metering devices, communications infrastructure, control mechanisms, data interpretation tools, and automation components. These elements facilitate two-way information and electrical power exchange between those responsible for grid management and end-users. This article reviews intelligent grid technologies’ impact on electrical distribution and operational management. A case study of a mid-sized urban region informs the article’s organised approach to creating and deploying an intelligent grid network. The findings show that intelligent grid technologies improve electrical distribution system dependability, operational efficiency, environmental sustainability, and security. This article explores the problems and opportunities of intelligent grid systems and provides guidance for future research and technology.
  Keywords: smart grid; electrical simulation; power management; smart meter and microgrid; systems’ reliability; operational efficiency; environmental sustainability; grid management.
  
  
• Modelling and optimisation of structural parameters of main landing gear during touchdown and taxing  
  by Mantesh Basappa Khot, Abhijit Prekash, R. Gopalakrishna, Karan Nanda, Hriday Ghosh 
  Abstract: Runway irregularities induce vibrations in the fuselage of aircraft during take-off, taxiing, and landing, leading to fatigue stresses in the airframe. These vibrations impacts passenger comfort and affect the functioning of instruments. To reduce fuselage vibrations in the Fokker-70 aircraft, an optimisation of parameters is conducted, aiming to lower the peak of the frequency response at resonant conditions and minimise the time difference between the fuselage and tire stabilisation after touchdown. This prevents airframe failure due to excessive vibration at resonance. MATLAB s Nelder-Mead simplex algorithm is used for optimisation. Additionally, a PID controller is implemented in the landing gear model to further mitigate vibrations. The controller s effectiveness is tested using a runway model with various bumps, adhering to Boeing s runway roughness criteria. Results show the controller smoothens fuselage response to runway excitations, reducing vibration and enhancing the airframe s fatigue life.
  Keywords: complex modal analysis; Nelder-Mead simplex method; optimisation; Oleo pneumatic shock absorber; PID controller.
  
  
• Modelling and structural analysis of coconut tree climbing mechanism  
  by Pradip Solanki, Ravi Kumar Mandava 
  Abstract: Due to the shortage of professional climbers for cutting the coconuts, many farmers are looking for coconut tree climbing mechanisms. This article aims to develop the mechanism model and examine the various types of stresses, that is, Von-misses stress and maximum shear stress, and deformation of the various mechanical components of the climbing mechanism. The mechanical parts are required to run the mechanisms are modelled individually in CREO. Further, the analysis has been conducted using ANSYS 2021. The result shows that the stresses acting on each mechanism components are less than the permissible limit of the estimated loading conditions. Therefore, it can be observed that the designed components of the mechanism can effectively withstand the load during operating conditions.
  Keywords: climbing mechanism; mechanical components; coconut tree; CREO; ANSYS.
  DOI: 10.1504/IJESMS.2023.10061187
   
  
• Study of porous fin with temperature-dependent thermal conductivity and internal heat generation  
  by Surjan Singh, Priti Sharma 
  Abstract: In this paper, we consider mathematical model of heat transfer in rectangular porous fin with temperature-dependent thermal conductivity and internal heat generation. Governing equation and boundary conditions are presented in dimensionless form. In this paper, we consider three cases for temperature dependent thermal conductivity namely, constant, linear and exponential function of temperature. We have applied three different methods for solution of the problem, i.e., Legendre wavelet collocation method, finite difference method and moment method. In the particular case, we obtained the exact solution, it is compared with these three methods and found good agreement. Effect of various parameters like thermal conductivity, thermo-geometric properties, porosity, heat transfer rate and internal heat generation are presented in the form of tables and figures. The Legendre wavelet collocation method gives high accuracy. The novelty of the work is that a highly nonlinear problem is solved by a hybrid numerical method.
  Keywords: wavelet collocation method; porous fin; thermal conductivity; internal heat generation; finite; moment.
  DOI: 10.1504/IJESMS.2025.10067661
   
  
• Dynamic modelling of CNTs under multiple moving nanoparticles based on non-local strain gradient theory  
  by Abbes Elmeiche, Mohamed Bouamama, Abdelhak Elhannani, Abdelkader Lousdad 
  Abstract: This paper presents an investigation on the dynamic behaviour of single-walled carbon nano-tubes (SWCNT) crossed by multiple moving nano-particles modelled as mobile loads based on Timoshenko's non-local beam theory, including rotational inertia. The governing equations are derived using Hamilton's principle combined with Galerkin's method. The eigen-frequencies are determined by solving analytically the system of equations which govern the problem of the eigenvalues. Temporal integration of the Newmark's method is adopted to find the dynamic response of single-walled carbon nanotubes (SWCNT). The obtained eigen-frequencies are validated by the results of previous published studies. A detailed parametric study is carried out to analyse the effects of non-local parameters, the slenderness ratio, the displacement speed and the number of moving loads on the vibration characteristics of the model. Type or paste your abstract here as prescribed by the journal's instructions for authors. The obtained results show that above mentioned effects play an important role and have a significant effect on the transitional dynamic behaviour of single-walled carbon nanotubes (SWCNT).
  Keywords: dynamic behaviour; SWCNT; multiple moving nano-particles; Timoshenko's non-local beam theory; displacement speed; eigen-frequencies; dynamic response lower.
  DOI: 10.1504/IJESMS.2025.10067657
   
  
• Influence of geometric properties on the natural frequency of bending vibration of polymethacrylamide sandwich composite  
  by Rilwan Kayode Apalowo 
  Abstract: The influences of fibre orientation and thicknesses of the skin and the core on the natural frequencies of cantilever polymethacrylamide rohacell sandwich composites (PMRCs) were numerically studied in this work, using the FEA approach. The study established that maximum natural frequency is obtained for the sandwich when the fibre orientation of its GFRP skin is either lateral, (i.e., 0°) or longitudinal (90°) due to the comparative higher bending stiffness of the skin at these angles. It was also found that the natural frequency increases with increasing core thickness for all bending modes, increases with increasing skin thickness for the fundamental bending mode, and decreases with increasing skin thickness for higher bending modes. It was further found that higher frequencies of bending vibration are obtained in the PMRC sandwich when the PMRF core has a superior thickness ratio of the entire sandwich thickness compared to the GFRP skin.
  Keywords: vibration analysis; finite element analysis; FEA; natural frequency; sandwich laminate; honeycomb structure.
  DOI: 10.1504/IJESMS.2025.10067650
   
  
• Aerodynamic properties comparison between natural feather, nylon, and synthetic shuttlecocks  
  by Dangsuria Ab Rasid, Muhammad Fairuz Remeli, Baljit Singh, Hazim Moria 
  Abstract: This study compared the aerodynamic properties between the natural feather, nylon, and foam shuttlecocks under various pitch angles, α using computational fluid dynamics (CFD) during steady-state flight conditions. The velocity varied within 10-60 m/s and α = 10°, 20°, 30°. The drag coefficient for feather/foam was approximately constant at 0.56. Other aerodynamic properties including the lift and moment coefficients were also investigated. The lift coefficient obtained for nylon and feather/foam were 0.38 and 0.30 at α = 30° (30 m/s). All models had shown a negative sign for the moment coefficient, which indicates the aerodynamic centre is always behind the centre of gravity. Therefore, it will give stability to the shuttlecock during the flight. The nylon shuttlecock showed a higher drag coefficient compared to others due to its larger gap area and an increased wake behind the shuttlecock.
  Keywords: aerodynamic properties comparison; natural feather shuttlecocks; nylon shuttlecocks; synthetics shuttlecocks; computational fluids dynamics; CFD; drag coefficients; lift coefficients; steady-state flight.
  DOI: 10.1504/IJESMS.2025.10067652
   
  
• Research on numerical simulation of wind load on high-rise buildings along the street based on BIM model  
  by Lianguang Mo, Wenying Lu 
  Abstract: In order to overcome the problems of poor accuracy and low efficiency in the existing numerical simulation methods of building surface wind load, a new numerical simulation method of high-rise street building surface wind load based on BIM model is proposed. This method obtains the data of high-rise buildings along the street based on BIM model, and selects Realisable k-ε model as the turbulence model. The non-equilibrium wall function method is used to deal with the turbulence state on the building surface, the boundary conditions are set, and the turbulence model is calculated and solved by a separate solver to realise the numerical simulation of the surface wind load of high-rise street buildings. The experimental results show that the average error of the wind pressure coefficient of the proposed numerical simulation method is less than 0.4, which fully shows that the proposed numerical simulation method has good performance.
  Keywords: BIM model; high-rise buildings along the street; building surface; wind load; numerical simulation.
  DOI: 10.1504/IJESMS.2025.10067651