International Journal of Simulation and Process Modelling (8 papers in press)

Regular Issues

• Generic inter-task communication paradigm in a business process and its modeling and simulation with extended Petri nets  
  by Alexander Kostin 
  Abstract: A model of inter-task communication in a business process (BP) is described and investigated in a long series of simulation experiments It is assumed that BP consists of a set of dynamic and communicating tasks that, for a given project instantiation, try to implement the related project under some predefined system parameters Thus, the BP is implemented as a project consisting of an ordered set of involved tasks The developed model includes not only tasks of the project, but also the components that continuously generate requests for projects, analyze the reports from involved tasks and collect and evaluate the statistics for each project These components are called requesters After the generation of a request for a new project, the requester randomly chooses, among a set of available tasks, the first task and initiates it This task, after performing a part of the requested project, activates the next task.
  Keywords: simulation modelling; business processes; performance metrics; extended Petri nets.
  DOI: 10.1504/IJSPM.2024.10068361
   
  
• Gene regulatory networks optimisation method based on joint evaluation of network structure and node attribute  
  by Luxuan Qu, Junchang Xin, Yinghui Xiang, Mingcan Wang, Zhiqiong Wang 
  Abstract: Accurately modelling gene regulatory networks (GRNs) is essential for revealing the mechanisms of disease development. However, existing methods often include false positive edges, reducing model accuracy. Current optimization algorithms, primarily focusing on removing triangular structure edges, tend to ignore many redundant edges and sometimes delete correct ones due to improper parameter settings. This paper introduces a GRNs optimization based on joint evaluation of network structure and node attribute. The approach addresses redundancy in both triangular and mutual structures, allowing for the identification of more redundant edges. By incorporating global node attribute, the method limits the removal of correct regulatory edges. This joint evaluation ensures that only the truly redundant relationships are deleted. Experimental results demonstrated that NSNA achieved an overall nearly 7\% improvement both in F1-score and AUC compared to modeling method without optimization. The approach offers potential benefits for advancing disease research and improving network modelling.
  Keywords: gene regulatory networks; joint evaluation; network structure; node attribute; redundancy relationships.
  DOI: 10.1504/IJSPM.2024.10068608
   
  
• Agent based smart insulin pump for autonomous diabetes management  
  by Asma Bouaita, Yacine Kissoum, Smaine Mazouzi 
  Abstract: Advancements in computing technology have paved the way for ambient intelligence, enabling smart objects to better serve users through adaptability and reactivity. This paper introduces the Agent-based Cooperating Smart Objects (ACOSO) model, a multi-agent system (MAS) approach for designing and implementing a smart insulin pump for elderly persons suffering from diabetes. Unlike conventional centralized systems, the ACOSO model facilitates decentralized, proactive, and reactive interactions between smart objects, ensuring enhanced adaptability to the user’s health status and environment. The key contribution is the application of this agent-oriented paradigm to healthcare, demonstrating how the model supports real-time health monitoring, effective blood glucose management, and integration with smart home ecosystems, all while maintaining user privacy and safety. This approach offers a scalable and intelligent solution for chronic disease management, improving significantly the autonomy and quality of life for elderly peoples, thus addressing the growing socioeconomic challenges of aging populations.
  Keywords: smart insulin pump; agent based systems; cooperating smart objects; CSOs; internet of things in healthcare; autonomous diabetes management; real-time decision making.
  DOI: 10.1504/IJSPM.2025.10069212
   
  
• Effect of pin shapes on temperature distribution in friction stir lap joint of AA6061 with AZ31 using numerical simulation  
  by Amit Yadav, Ajai Jain, Rajiv Verma 
  Abstract: The assessment of weld quality in friction stir welding relies on selecting the appropriate weld parameters, with the shape of the tool pin being one such crucial parameter. This study employs a computational fluid dynamics model to investigate the impact of various pin shapes namely straight cylindrical, hexagonal, square, and triangular on temperature distribution. The workpieces selected for dissimilar friction stir lap welding are aluminium alloy 6061 and magnesium alloy AZ31, with a convex shoulder used to help accommodate minor variations in workpiece thickness. It was observed that the maximum temperature generation occurs with a cylindrical pin-shaped tool, followed by hexagonal, square, and triangular shapes, respectively. This study will assist in selecting the optimal tool shape for the given workpiece setup and will benefit several industries, including aerospace (wings, fuselages, etc.), automotive (rims, chassis, frames, etc.), railway (container bodies, wagons, carriages, etc.), and shipbuilding and marine (structures, platforms, panels, etc.).
  Keywords: friction stir weld; FSW; computational fluid-dynamics; CFD; Ansys-Fluent; finite-volume approach; numerical simulation.
  DOI: 10.1504/IJSPM.2025.10069656
   
  
• Rule representation and a switchable pattern matching model for hot-rolled steel production scheduling system with rule engine  
  by Yanguang Sun, Zhiqiang Geng, Jinxiang Chen, Jiachen Gu, Gang Sheng 
  Abstract: Rule representation and a switchable pattern matching model for hot-rolled steel production (HRSP) scheduling system with rule engine are presented in this paper. Six features of scheduling rules for HRSP are described by mathematical models, respectively, which help to construct the rule engine of HRSP scheduling system. A pattern matching model switched between Decision Pattern Network (DPN) and Rete module is presented to solve the complex and changeable problems of scheduling rules. The above approaches are verified by applying a dataset from a steel plant. The results show that the proposed approaches greatly improve the flexibility and responsiveness of HRSP scheduling system with rule engine.
  Keywords: rule engine; pattern matching model; scheduling rule representation; hot-rolled steel production.
  DOI: 10.1504/IJSPM.2024.10069788
   
  
• Simulation-driven optimisation of neural radiance fields for 3D traffic scene reconstruction  
  by Dan Shan, Yaohui Sun, Xiangdong Meng, Yan Xing 
  Abstract: Accurate 3D scene reconstruction is essential for applications like autonomous driving and traffic management, but current methods often suffer from aliasing and blurring in complex multi-view scenes. To address these challenges, we propose a novel deep learning algorithm that integrates feature meshes into multi-scale neural radiance fields. This approach enhances both the quality and computational efficiency of 3D scene reconstruction, allowing for detailed views and scalability to larger scenes. By optimizing the projection of 3D rays and minimizing the error between observed and rendered colors, our method significantly reduces training time and improves key image quality metrics. Experimental results show a 43% reduction in training time and improvements in PSNR (6.3%), SSIM (4.5%), and LPIPS (20%) compared to existing techniques, making it a practical solution for real-world traffic scene reconstruction.
  Keywords: neural radiance fields; NeRFs; 3D traffic scene reconstruction; anti-aliasing; rendering optimisation; autonomous driving; deep learning; multi-scale rendering; performance metrics.
  DOI: 10.1504/IJSPM.2024.10070381
   
  
• Impact of atmospheric propagation impairments on submillimetre airborne radar performance  
  by Bedilu Ababu Teka, Demissie Gelmecha, Ram Singh, Rajeev Shakya, Bijay Kumar Paikaray, Satyasis Mishra 
  Abstract: This research presents the performance of submillimetre airborne radar systems in the presence of various atmospheric propagation impairments. The study aims to assess the effects of environmental factors such as rain, fog, clouds, atmospheric turbulence, and atmospheric attenuation on radar performance using computational methods such as Friis-transmission, ecological factors and radiation model. The simulated results have shown that the free space path loss significantly increases with distance and frequency and highlights the importance of accounting for phase differences in radar performance. The rise in the Earths potential leads to greater angles of incidence and refraction, lowers reflection coefficients, and enhances the output signal-to-noise ratio. This underscores the critical need to optimise transmit power. This research has been provided to extract valuable insights into the performance dynamics of submillimetre airborne radar systems amidst atmospheric propagation impairments, providing essential considerations for radar system design and operation in critical environment.
  Keywords: Atmospheric Propagation Impairments; Airborne radar systems; Atmospheric attenuation; Environmental factors; Atmospheric turbulence.
  DOI: 10.1504/IJSPM.2024.10070435
   
  
• Simulation-based modelling of circular economy challenges in the food industry: an ISM approach for process optimisation and sustainability  
  by Rakesh Kumar, Bijay Kumar Paikaray, Girija Nandini, Swarna Prabha Jena, V.S. Damodharan 
  Abstract: The circular economy is the recycling of processes. Food products involve various aspects, such as processing, packing, and waste management. The study delves into the circular economy adoption challenges in the food industry. This research explores 15 challenges for the sustainable food industry. The expert opinion and previous literature reviews guided the selection of these challenges. The study collected data from industrial experts engaged in the food industry. The study employed the Interpretive Structure Modelling method to identify the most influential and least challenging factors. The study found that the most significant obstacles to adopting a sustainable food industry in the circular economy are government incentives, insufficient knowledge about sustainable food industry processes, awareness of CSR activities, corporate governance, and performance indicators. The study is limited to the food industry in the Indian region.
  Keywords: circular economy; sustainability; food industry; packaging; Industry 4.0.
  DOI: 10.1504/IJSPM.2024.10070534