International Journal of Engineering Systems Modelling and Simulation (13 papers in press)

Regular Issues

• Advancing breast cancer detection: a comprehensive investigation of advanced classification techniques  
  by Shilpa Choudhary, Sivaneasan Bala Krishnan, Prasun Chakrabarti 
  Abstract: As the most prevalent cancer in women worldwide, breast cancer requires early detection to have the best possible treatment results. However, conventional screening techniques, like mammography and clinical examinations, can take time and effort. In this paper, we proposed a predictive model for the identification of breast cancer by combining state-of-the-art model BERT with machine learning approaches. Several machine learning algorithms, such as K-nearest neighbours, decision tree, random forest, neural network, and BERT, were tested on the Breast Cancer Wisconsin (Diagnostic) Dataset for early prediction of the diseases. The BERT models accuracy was improved by using hyperparameter optimisation techniques. For the proposed works evaluation, we used metrics like accuracy, F1-score, precision, and recall on the standard publically available datasets. With an accuracy of 0.98 across various splits and an area under the curve (AUC) of 0.98 in receiver operating characteristic (ROC) curves, our results show that BERT consistently works better than other models. These findings highlight the value of early and reliable identification in improving patient outcomes, highlighting the promise of machine learning algorithms, notably BERT, inaccurate breast cancer prediction.
  Keywords: breast cancer prediction; K-nearest neighbours; KNNs; decision tree; neural networks; random forest; BERT; classification.
  DOI: 10.1504/IJESMS.2025.10072165
   
  
• Cost effective biomass supply chain optimisation for the bio-energy industry  
  by Prajwal Panwar, Anand Chauhan, Anubhav Pratap Singh, Ritu Arora 
  Abstract: Increasing energy needs and environmental concerns require sustainable solutions. A promising alternative to fossil fuels is biodiesel, generated from easily accessible macro-algae such as Ulva fasciata, Cystoseira indica and Gracilaria corticata. A cost-effective macroalgal biodiesel supply chain is proposed using optimisation methodology. Utilising an advanced algorithm, the model optimises biodiesel production from macroalgae procurement to bio-refinery and depot placement. The framework incorporates expenses, biorefinery site, biodiesel storage and strategic macroalgae extraction centres. The model is optimised using a genetic algorithm, factoring in the expenses of installing biodiesel manufacturing plants. The sensitivity analysis demonstrates that these initial expenditures considerably impact the supply chains economic burden. Sensitivity analysis confirms the frameworks usefulness, making it valuable for stakeholders such as traders and policymakers promoting the biofuel business. This study sets forth the foundation for the manufacture of biodiesel from macroalgae on a massive scale, ensuring its sustainability.
  Keywords: macro-algae; sustainable energy; supply chain; bio-diesel; genetic algorithm; optimisation.
  DOI: 10.1504/IJESMS.2025.10073145
   
  
• Design and performance analysis of flexible 2 x 2 linear planar array MIMO antennas with beam steering for on-body and WLAN applications  
  by M. Ribitha Elizabeth, M. Vadivel 
  Abstract: This paper introduces an on-body simulation and WLAN low-cost flexible linear planar array four-port MIMO antenna with 9.46 dBi gain and 2.41 GHz operating frequency. Compactness, body closeness, and high gain have been the main design requirements, which are of exceedingly high use in WLAN, WBAN, and Wi-Fi wearable devices. The antenna is fabricated using 0.25 mm thick polyimide of low loss tangent of 0.004 and a 3.8 dielectric constant to offer the electrical performance without compromising structural stiffness. The two-port elements are fed into a linear planar array by a corporate feedline network to ensure maximum directivity and prevent signal loss in body-centric environments. To further improve the characteristics of the radiation, an electromagnetic bandgap (EBG) structure is used for effective main lobe radiation and beam forming in the x-axis plane. The structure is designed from a simulation model of 10 g human tissue, and the SAR is 1.09 W/kg, which meets IEEE C95.1 and ICNIRP wearable device safety standards. The antennas free-space reflection coefficient is -20 dB and -45 dB with EBG at the operational frequency. The antennas diversity gain is approximately 10 dBi with an envelope correlation coefficient (ECC) value of less than 0.003, making it effective for element-to-element isolation and MIMO-based on-body communication system compatibility.
  Keywords: linear planar array; four-port MIMO; EBG reflector; beam steering; wireless body area network; microstrip patch antennas; MPA; liquid crystal polymers; LCP; polydimethylsiloxane; PDMS; polyethene; PE; polyethene terephthalate; PET.
  DOI: 10.1504/IJESMS.2025.10073554
   
  
• Heat transfer performance analysis of steam boilers-fin and tube heat exchangers under varying geometric dimensions  
  by Samson Kolawole Fasogbon, Ibrahim Ademola Fetuga, Ayodele Temitope Oyeniran, Mishael Alelume, John Temitope Onafowokan, Opeyemi Samuel Eso, Tochukwu Anthony Ndokwu, Samuel Olabode Afolabi, Victor Blessed Bassey, Rufus Seyi Oluwadare, Olabode Thomas Olakoyejo 
  Abstract: This study analyses the heat transfer performance of fin and tube heat exchangers in steam boilers, focusing on the impact of geometrical parameters such as the number of tube rows, tube diameter, fin pitch, fin thickness, and fin surface area on thermal efficiency. Flue gases typically exit at temperatures between 298K and 523K, resulting in energy losses of 10-30% in industrial boiler systems. The analysis employed COMSOL Multiphysics to model flue gas flow using three approaches: laminar flow modeling and two turbulence models (k-epsilon and k omega), all based on Reynolds-averaged Navier-Stokes equations. The k-omega model provided the best alignment with experimental data (Wang et al., 2006), enhancing heat transfer predictions. The results show that heat transfer stabilises beyond six tube rows, with Nusselt numbers ranging from 10.97 to 21.16 and effectiveness reaching 0.54. Three parameters proved critical for maximising heat transfer performance: fin surface area, fin thickness, and tube diameter. The optimal flue gas flow rate was determined to be within the range of 0.02 to 0.2 kg/s. These findings guide the design of efficient heat exchangers for waste heat recovery, minimising energy losses in industrial applications.
  Keywords: waste heat recovery; flue gases; thermal performance; fin and tube heat exchangers; tube rows; fin pitch; fin thickness; fin surface area.
  DOI: 10.1504/IJESMS.2025.10073555
   
  
• Hybrid relay protocol design based on NOMA  
  by Sankarsan Panda, M. Karthikeyan, S. Palanikumar, Sheshang Degadwala 
  Abstract: In this paper, there is a mixed access method that links many things to the narrowband internet of things (NB-IoT). It uses both non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA). Working together in a single decode-and-forward (DF) or amplify-and-forward (AF) way loses a lot of time and space. It also suggests a new Hybrid NOMA gearbox plan with relay-adaptively chosen teamwork. The steady-state probability is used to find the closed formulas for the output and the chance that the system will break down. We improve the process above even more by letting the parent node send the failed received overlay signals more than once. It is less likely that there will be an outage when there are more than one resends that can be made. The suggested adaptable joint hybrid NOMA transmission strategy is better than the pure OMA transmission mode in a number of ways.
  Keywords: NOMA; system throughput; OMA transmission mode; protocol design.
  DOI: 10.1504/IJESMS.2025.10073678
   
  
• Circularly polarised compact square dielectric resonator antenna for web applications  
  by Madhusmita C. Sahoo, Aswin Patani, Nitinkumar Jivarajbhai Bathani 
  Abstract: The dielectric resonator antenna (DRA) is utilised for ultra wide band (UWB) applications due to low conducting losses, better flexibility and better radiation efficiency. However, achieving compact geometry with circular polarisation (CP) while suppressing interference from existing wireless services remains a challenge. Moreover, mutual coupling between ports in multi-port UWB DRAs can significantly degrade performance. Considering these, this work presents a CP-based square DRA (SDRA) for UWB applications with the dimension of 10 mm x 10 mm x 0.508 mm. This design achieves a triple notch of 3.2-3.9 GHz (Wi-MAX), 4-6 GHz (WLAN) and 8-12 GHz (X-band) applications. The antenna is implemented on an FR4 substrate and incorporates a defected ground structure (DGS) to reduce mutual coupling between the two ports. Then, a microstrip feed line is provided, and the parasitic patch is placed between the two ports for better reflection coefficient for UWB applications. The proposed design achieves gains of 13.3, 2.7, and 22 dBic with corresponding VSWR values of 1.10, 1.31 and 1.26 for the three respective notched bands.
  Keywords: dielectric resonator antenna; DRA; ultra wide band; UWB; circular polarisation; triple notches; parasitic patch; defected ground structure.
  DOI: 10.1504/IJESMS.2025.10073816
   
  
• Investigation of the behaviour of double corrugated steel shear walls with internal stiffeners  
  by Wentao Qin 
  Abstract: The double corrugated steel shear wall (DCSSW) system has been introduced recently, in which identical and parallel trapezoidal corrugated plates (CPs) are connected through high-strength bolts. In this paper, the lateral behaviour of internally stiffened DCSSWs is investigated under monotonic loading using the finite element method in the ABAQUS software. To make comparisons, the non-connected DCSSWs were also considered in the current paper. The results indicated that the maximum lateral strengths of the non-connected DCSSWs are less than those of linked DCSSWs. The maximum strength of the non-connected DCSSWs with a corrugation angle of 30, 45, and 60 is less than that of connected DCSSWs by 34%, 14%, and 10%, respectively. Additionally, this study demonstrated that the maximum strength of the internally stiffened DCSSWs is 3.4% to 39.8% greater than that of non-connected DCSSWs. Nevertheless, the maximum strength of the DCSSWs with internal stiffeners is ultimately 4.5% greater than that of linked DCSSWs. Furthermore, a thicker, stiffer material results in higher maximum strength.
  Keywords: double corrugated steel shear wall; DCSSW; strength and initial stiffness; IS; pushover curve; corrugated plates; hysteresis curve; flat plate; elastic buckling.
  DOI: 10.1504/IJESMS.2025.10073914
   
  
• Min-path based PTM approach to system reliability: failure rate analysis and MTTF  
  by Sadiya Naaz, Mangey Ram, Akshay Kumar 
  Abstract: Prioritising reliability in the planning, installing, and upkeep of traffic signal management systems is crucial for traffic authorities and structure functions. The reliability of these networks can be increased, resulting in more effective and safer traffic control, by implementing sturdy technology, periodic repair procedures, redundancy initiatives, cybersecurity procedures, as well as successful surveillance. This study presents and modelled a traffic signal management system with the goal of assessing its reliability, when the travellers and arrivals are unpredictable. The systems primary functions are to optimise flows of traffic, increase safety, and reduce congestion at crossings, all of that contribute to increased effectiveness of the network. The failure rate study of the suggested traffic signal management System is established second. In order to investigate the reliability assessment, the extremely well-known matrix-based min-path path tracing method procedure is applied instead of u-function approach. Thirdly, the models variation is shown using the exponential decay curve. In order to quantify the deterioration intensities or hazard rate of an entire system or component over a period of time, we lastly assess the breakdown intensity index for the proposed system. Finally, the recommended systems cumulative signature has been assessed.
  Keywords: traffic signal management system; min-path based matrix methodology; path tracing method; MTTF; hazard intensity index.
  DOI: 10.1504/IJESMS.2025.10075000
   
  
• Spectrum sharing using deep learning: multi-agent reinforcement learning  
  by B.V. Santhosh Krishna, A. Bharathidhasan, N. Ashokkumar, K. Periyar Selvam 
  Abstract: The number of people using cell phones and the requirement for the radio band has increased over the last few years. The fast rise of 5G networks for wireless communication and wireless communication has met this need. There is reason to believe that the issue of improper use of the wireless spectrum could be resolved with the progress of cognitive radio and its spectrum-sensing technology. Deep learning technology is known for being able to learn and change amazingly quickly. The purpose of this research is to provide a brief summary of the approach used in cognitive radio spectrum-sensing technology and deep learning technology. The first part of this study talks about the common spectrum-sensing methods to give a big picture of the benefits of deep learning-based spectrum-sensing algorithms. We find that our method can increase the accuracy of previous work and conventional learning strategies by as much as 83%.
  Keywords: cognitive radio; spectrum sensing; wireless communication; cooperative spectrum sensing.
  DOI: 10.1504/IJESMS.2025.10071409
   
  
• Excitation effects of arc grounding fault on PT ferroresonance of distribution networks connected to photovoltaic in high-altitude areas  
  by Jinpeng Yuan, Jingwen Sun, Zibin Li, Wande Lin, Zile Wang, Jianwu Li 
  Abstract: Power distribution network systems in high-altitude areas with low air pressure are prone to arc grounding fault, and abundant solar resources lead to the access of numerous distributed new energy sources, which further increases the risk of potential transformer (PT) ferroresonance excited by arc grounding fault. This study designed a device simulating the arcing characteristics in high altitude environment, established a Mayr arc model for simulating arc grounding fault, analysed the fault characteristics of PT ferroresonance overvoltage caused by arc grounding, metallic grounding and accessing to new energy in high altitude areas, and compared the effects of connecting damping resistor at the open delta of PT secondary winding and connecting single-phase PT at the neutral of primary winding to suppress ferroresonance under different conditions, which may provide a reference for suppressing ferroresonance caused by new energy access in high altitude areas.
  Keywords: ferroresonance; overvoltage; potential transformer; arc grounding fault.
  DOI: 10.1504/IJESMS.2025.10071011
   
  
• Heat transfer and fluid flow analysis in concentric tube heat exchangers  
  by B. Konda Reddy, G. Bhanu Kiran, K. Jayadeep 
  Abstract: This study conducts a detailed parametric analysis of heat transfer and fluid flow in concentric tube heat exchangers using CFD simulations in ANSYS Fluent. Four configurations - bare, continuous finned, slotted, and combined finned-slotted - are evaluated for their thermal performance. The impact of mass flow rates and inlet temperatures on heat transfer, temperature distribution, and pressure drop is examined. Results show improved heat transfer in modified designs compared to the bare tube. Continuous finned tubes enhance performance by 12.68%-20.89%, slotted by 0.52%-3.33%, and the combined configuration by 14.47%-24.63%. Pressure drop changes are minimal for finned and combined designs, with a slight decrease for slotted tubes. Validation against experimental data yields a maximum relative error of just 0.19%, confirming model accuracy. The study highlights the effectiveness of advanced configurations in enhancing thermal performance while maintaining pressure stability, aiding the development of more efficient heat exchangers.
  Keywords: heat transfer; fluid flow; concentric tube heat exchanger; bare; continuous finned; slotted; combined finned-slotted; ANSYS fluent; heat transfer performance; pressure drop performance.
  DOI: 10.1504/IJESMS.2026.10075060
   
  
• Comparative analysis of marine debris simulation using ensemble learning with XGBoost and deep convolutional neural networks  
  by S. Belina V.J. Sara, Gnaneswari Gnanaguru, S. Silvia Priscila 
  Abstract: Marine ecosystems, wildlife, and human activities are seriously threatened by marine garbage. Deep learning-based systems for categorisation can automate classifying distinct types of marine debris from photos or video recordings, allowing for more effective and precise monitoring and assessment of debris levels in different maritime circumstances. DL is a useful tool that can help with environmental conservation efforts by categorising marine waste. To improve classification accuracy, sensitivity, and specificity for different types of marine debris, we investigate the use of ensemble learning approaches in this work and used for execution in Python. We compare three distinct implementations of the powerful gradient boosting method XGBoost with innovative deep convolutional neural networks: XGBoost with Adam and GoogleNet optimiser, XGBoost with VGG19 and Adam optimiser, and XGBoost with ResNet and Adam optimiser. The XGBoost algorithm and feature extraction from three different pre-trained CNN architectures, GoogLeNet, VGG19, and ResNet, are used in this study to examine the effectiveness of classifying maritime debris. We highlight the outstanding results obtained by combining ResNet + Adam with XGBoost, a reliable and effective method for classifying maritime trash and producing an accuracy of 91%, specificity of 0.88, and sensitivity of 0.91, respectively.
  Keywords: marine debris simulation; XGBoost ensemble; convolution neural network; CNN; Adam optimiser; image classification; environmental monitoring; optimisation techniques; sensitivity enhancement; deep learning; DL.
  DOI: 10.1504/IJESMS.2025.10071659
   
  
• Improving cooling load prediction in residential buildings with multi-layer perceptron models  
  by Yang Wu, Lanlan You 
  Abstract: Today, building energy efficiency is prioritised since it affects operational costs. Buildings take a lot of energy to maintain pleasant temperatures. Combining this research's cooling load (CL) forecasting method may optimise building energy use. MLPs forecast household cooling demands. MLP models and regressions generally have linear input-output relationships. This research uses two innovative optimisers, cheetah optimiser (CHO) and adaptive opposition slime mould algorithm, to improve MLP model performance. The data used to train the approaches describes each sample's unique traits. These methods will be tested on a simulated dataset using CLs as neural network output variables and building technical attributes as input factors. During the process testing phase, the MLCO (2) (MLP+CHO in layer 2) gets the lowest RMSE value of 0.672 and the greatest R² value of 0.995. The results demonstrate that the proposed hybrid models - MLCO and MLAO - significantly outperform the standalone MLP and conventional optimisation methods, achieving a minimum error rate. These findings confirm the proposed models' superior predictive accuracy and reliability, underscoring their potential for practical application in enhancing energy efficiency in residential buildings.
  Keywords: cooling load; multi-layer perceptron; MLP; cheetah optimiser; CHO; adaptive opposition slime mould algorithm; artificial intelligence; support vector machines; SVM; artificial neural networks; ANNs.
  DOI: 10.1504/IJESMS.2025.10071781