International Journal of Modeling, Simulation, and Scientific Computing

In order to improve the simulation accuracy for free-fall lifeboat in ship life-saving training system, this paper analyzes and models the motion of boat’s launching from the skid. The whole launching is divided into four phases, namely: sliding down, rotation, free fall and water entry. According to the theory of momentum and strip theory, hydrodynamic forces of the boat at water entry are calculated under the effect of waves. The method of interpolation is used for calculating the half width and added mass of cross-sections at water entry. The model is used for numerical investigation about the boat launching from skid under different conditions and applied to ship life-saving simulation training system. The following conclusions are finally obtained: (1) When the initial inclination angle is 30${}^{\circ }$, the horizontal distance between the point of water entry of the boat and the lower end of the slide is about 7.2m. The horizontal distance will be smaller, when the initial inclination angle increases. There is no obvious law between forward distance and waves. (2) When the initial inclination angle is 45${}^{\circ }$, the setback may occur after the boat entering the wave. When the initial angle is 60${}^{\circ }$, the setback occurs after the boat entering the water. (3) When the center of gravity is 1.5m in front of the midship of the boat, the boat will turn over.

The road damage coefficient $\beta$ is a significant indicator to estimate the degree of the road damage caused by vehicles. The existing calculation method of $\beta$ is not convenient for the engineering application. To effectively evaluate the damage degree and facilitate the engineering application, this paper studied the simple and reliable analytical calculation method of $\beta$. Firstly, a dynamic model of the vehicle–road system was created. The tire pressure and the tire damping were considered in the model. Moreover, the relationship between the tire vertical stiffness and the tire pressure is approximated as a linear function. Secondly, based on the dynamic model, according to the definition of $\beta$, a concise analytical formula of $\beta$ was derived and verified by numerical simulations. The relative errors of the analytical calculation results are all less than 0.1%. Thirdly, the influences of the tire pressure $p$, the damping ratio ${\xi }_s$ of the suspension system, and the damping ratio ${\xi }_t$ of the wheel system on $\beta$ were analyzed. Moreover, based on the analytical formula of $\beta$, a mathematical model of the optimal damping matching for the suspension system was established and a case study was also given. The research results show that the larger the tire pressure $p$, the larger the value of $\beta$ is. For each $p$, there is an optimal damping ratio ${\xi }_s$. If the tire damping is ignored, it will lead to the design error for ${\xi }_s$. Finally, some important conclusions were drawn. The analytical formula of $\beta$ and the conclusions can provide valuable references for the analysis of the road damage and the initial design of vehicle suspensions.

Cloud computing is the distributed computing paradigm continually exposed to different attacks and threats of various origins. The data stored in the cloud framework is easier for external and internal intruders, as access to the cloud framework is done through internet services. Various intrusion detection (ID) methods are developed to detect network intruders in the cloud, but these methods are not primarily effective in generating accurate detection results. Hence, an effective intrusion detection system (IDS) is designed to solve the security issues that unfavorably influence the sustainable development of the cloud and enhance the protection of the cloud from malicious attacks. The IDS is modeled using the proposed Feedback Deer Hunting Optimization (FDHO)-based Deep Residual network to detect network intrusions. However, the proposed FDHO algorithm is designed by integrating Feedback Artificial Tree (FAT) with Deer Hunting Optimization (DHOA), respectively. Moreover, the detection of malicious attacks is carried out using a Deep Residual network that significantly increases the training speed, reduces the computational complexity, and generates effective detection results. The performance of the proposed method is comparatively analyzed with the existing techniques, such as Stacked Contractive Auto-Encoder and Support Vector Machine (SCAE+SVM), Artificial Neural Network with ant bee colony optimization algorithm+fuzzy clustering (ANN+ABC+fuzzy clustering), Improved dynamic immune algorithm (IDIA), and Normalized K-means (NK) clustering algorithm with RNN named, (NK-RNN), FAT-based Deep Residual network, and DHOA-based Deep Residual network using the BoT-IoT dataset and KDD cup-99 dataset. The proposed method achieved outstanding performance by considering the metrics, like specificity, accuracy, and sensitivity, with the values of 0.9526, 0.9498, and 0.9214 using the BoT-IoT dataset.

In this paper, we construct an SIR epidemic model with a modified Beddington–De Angelis type incidence rate and saturated treatment rate. We modify the incidence rate to incorporate the isolation of infected individuals after detection, and separation of some susceptible individuals from the rest to avoid the infection, without an increase in the number of classes. We find that the system has a unique disease-free equilibrium (DFE) which is locally asymptotically stable when the reproduction number is less than unity. The multiple endemic equilibria may exist irrespective of the basic reproduction number. The existence of bistability is encountered. Supercritical transcritical (forward), as well as subcritical transcritical (backward) bifurcation, may occur at ${\Re }_0=1$ where contact rate, $\beta ={\beta }^{\ast }$ acts as the bifurcation parameter. Therefore, DFE need not be globally stable. The conditions for the existence of Andronov–Hopf bifurcation are deduced with maximum treatment capacity, $c=c_0$ as the bifurcation parameter. The impacts of isolation of confirmed infected cases and separation of some susceptible from rest are studied numerically as well as the effect of saturation in treatment. The existence of chaotic behavior is deduced by showing the maximum Lyapunov exponent to be positive as well as the sensitivity to initial conditions. The computation of the Kalpan–Yorke dimension to be fractional confirms the existence of fractal-type strange attractor. The positive Kolmogorov–Sinai entropy further strengthens the claim of the existence of chaos.

We describe practical improvements for parallel BWT-based lossless compressors frequently utilized in modern day big data applications. We propose a clustering-based data permutation approach for improving compression ratio for data with significant alphabet variation along with a faster string sorting approach based on the application of the $O(n)$ complexity counting sort with permutation reindexing.

In an attempt to improve the current low efficiency and high consumption situation of vibration mills, this paper analyses the chaotic motion characteristics of the system and the movement of vibration mill. The complex stiffness-dispersion coupling of the system is also studied, so as to investigate the effect of the system’s chaotic motion characteristics on the efficiency improvement and energy consumption reduction. Based on the ADAMS software, this paper establishes a simplified vibration mill mechanical model, analyzes the singularity and stability of the system, and determines the critical speed at which the vibration motor becomes chaotic according to the bifurcation diagram. Then the chaotic state of the grinding machine with sinusoidal variation in its motor speed is studied based on the Poincaré principle, singular attractor and maximum Lyapunov exponent. Lastly, a 200h vibration test on diamond powder with an average particle size of 10 $\mu$m was carried out. Test results under the two operating conditions of variable and constant speeds are compared and analyzed. Our results show that with variable speed the vibration mill achieved higher grinding efficiency but smaller particle grain size. The research elaborated in this paper provides a valuable reference for the engineering application of the chaotic characteristics of vibration mill.

Smoothed Particle Hydrodynamics (SPH) is fast emerging as a practically useful computational simulation tool for a wide variety of engineering problems. SPH is also gaining popularity as the back bone for fast and realistic animations in graphics and video games. The Lagrangian and mesh-free nature of the method facilitates fast and accurate simulation of material deformation, interface capture, etc. Typically, particle-based methods would necessitate particle search and locate algorithms to be implemented efficiently, as continuous creation of neighbor particle lists is a computationally expensive step. Hence, it is advantageous to implement SPH, on modern multi-core platforms with the help of High-Performance Computing (HPC) tools. In this work, the computational performance of an SPH algorithm is assessed on multi-core Central Processing Unit (CPU) as well as massively parallel General Purpose Graphical Processing Units (GP-GPU). Parallelizing SPH faces several challenges such as, scalability of the neighbor search process, force calculations, minimizing thread divergence, achieving coalesced memory access patterns, balancing workload, ensuring optimum use of computational resources, etc. While addressing some of these challenges, detailed analysis of performance metrics such as speedup, global load efficiency, global store efficiency, warp execution efficiency, occupancy, etc. is evaluated. The OpenMP and Compute Unified Device Architecture$(CUDA)$ parallel programming models have been used for parallel computing on Intel Xeon$(R)$ E5-$2630$ multi-core CPU and NVIDIA Quadro M$4000$ and NVIDIA Tesla p$100$ massively parallel GPU architectures. Standard benchmark problems from the Computational Fluid Dynamics (CFD) literature are chosen for the validation. The key concern of how to identify a suitable architecture for mesh-less methods which essentially require heavy workload of neighbor search and evaluation of local force fields from neighbor interactions is addressed.

In some of the previous decades, we have observed that mathematical modeling has become one of the most interesting research fields and has attracted many researchers. In this regard, thousands of researchers have proposed different varieties of mathematical models to study the dynamics of a number of real-world problems. This research work is framed to analyzing the structure of the well-known Lassa hemorrhagic epidemic; a dangerous epidemic for pregnant women, via new generalized Caputo type noninteger order derivative with the help of a modified Predictor–Corrector scheme. Lassa hemorrhagic disease is an epidemical and biocidal fever, whose negative impacts were initially recognized in the countries of Africa. This virus has killed many pregnant women as compared to the Ebola epidemic. It was noticed that Lassa virus was isolated in Vero cell cultures from a blood pattern, and after 12 days it was ejective, after the climb of the sickness. In this research study, necessary theorems and lemmas are reminded to prove the existence of a unique solution and stability of given fractional approximation scheme. All necessary results are reminded to confirm the effectiveness of the proposed approximation algorithm by graphical observations for various fractional-order values. In our practical calculations, we plotted the graphs for two different values of natural death rate along with various values of given fractional-order operator. Our major target is to show the importance of the proposed modified version of the Predictor–Corrector algorithm in epidemic studies by exploring the given Lassa hemorrhagic fever dynamics.

In this paper, symplectic schemes and symmetric schemes are presented to simulate Nonlinear Schrödinger Equation (NLSE) in case of dark soliton motion. Firstly, by Ablowitz–Ladik model (A–L model), the NLSE is discretized into a non-canonical Hamiltonian system. Then, different kinds of coordinate transformations can be used to standardize the non-canonical Hamiltonian system. Therefore, the symplectic schemes and symmetric schemes can be employed to simulate the solitons motion and test the preservation of the invariants of the A–L model and the conserved quantities approximations of the original NLSE. The numerical experiments show that symplectic schemes and symmetric schemes have similar simulation effect, and own significant superiority over non-symplectic and non-symmetric schemes in long-term tracking the motion of solitons, preserving the invariants and the approximations of conserved quantities. Moreover, it is obvious that coordinate transformations with more symmetry have a better simulation effect.

In this study, we developed a SEIR model, including social interactions and individual human mobility in everyday activities. For this purpose, daily mobility of people was considered by using the molecular dynamic method and the virus spreading was modeled employing the ordinary SEIR scheme. Utilizing this model, the variation of population size, density, and health strategy as well as the effect of busy places such as malls, were considered. The results show that our flexible model is able to consider the effects of different parameters such as distance between peoples, local population density and health strategy in the outbreak.

In this paper, the atomization characteristics of Si₃N₄ ceramic dry granulation affect the performance of Si₃N₄ ceramic bearing balls. In order to improve the dry granulation characteristics and the comprehensive performance of Si₃N₄ ceramic bearing balls, the atomization mechanism of the spinning nozzle used for Si₃N₄ dry granulation was studied in detail. The interaction between air and binder in the pressure-swirl nozzle is analyzed based on VOF method, the modified realizable $k-𝜀$ turbulence model is used to simulate the flow field inside and outside the pressure-swirl nozzle, the effects of nozzle inlet parameters including the number of tangential inlets and the deflection angle of tangential inlets on the binder volume fraction, velocity distribution and pressure distribution are analyzed. The results show that when the number of tangential inlets increases from 1 to 4, the swirl strength of gas–liquid two-phase in the nozzle increases, the mean diameter of air core increases from 1.51mm to 2.01mm, and the spray cone angle increases from 18.5${}^{\circ }$ to 26.4${}^{\circ }$. Besides, when the deflection angle of tangential inlet increases from 0${}^{\circ }$ to 15${}^{\circ }$, the swirl strength of gas–liquid two-phase in the nozzle with the deflection angle of tangential inlet of 10${}^{\circ }$ is the largest, and the mean diameter of air core and spray cone angle is 3.04mm and 30.7${}^{\circ }$, respectively. Based on the atomization experiment platform of the electric control fuel system, the mean diameter of air core and spray cone angle are measured, the micromorphology of Si₃N₄ particles is observed, which verifies the correctness of numerical simulation. When the Si₃N₄ particles are prepared by dry granulation, taking the atomization performance of nozzle into consideration, the pressure-swirl nozzle with 4 tangential inlets and 10${}^{\circ }$ deflection angle should be selected.

This work provides a new fuzzy variable fractional COVID-19 model and uses a variable fractional operator, namely, the fuzzy variable Atangana–Baleanu fractional derivatives in the Caputo sense. Next, we explore the proposed fuzzy variable fractional COVID-19 model using the fixed point theory approach and determine the solution’s existence and uniqueness conditions. We choose an appropriate mapping and with the help of the upper/lower solutions method. We prove the existence of a positive solution for the proposed fuzzy variable fractional COVID-19 model and also obtain the result on the existence of a unique positive solution. Moreover, we discuss the generalized Hyers–Ulam stability and generalized Hyers–Ulam–Rassias stability. Further, we investigate the results on maximum and minimum solutions for the fuzzy variable fractional COVID-19 model.

The product of high complex profile, high strength, high productivity and excellent material properties with infinite length can be produced by Continuous Extrusion (CE) process. The numerical simulation of Aluminum (AA 1100) feedstock material at different wheel velocities, product diameter, feedstock temperature, die temperature and friction condition has been carried out using 3D simulation tool Design Environment for Forming (DEFORM-3D) in this paper. The development of mathematical model is carried out to investigate the influence of wheel velocity, extrusion ratio, feedstock temperature, die temperature and friction conditions on total load required for the deformation and extrusion of feedstock material through Response Surface Methodology (RSM). The statistical significance of mathematical model is verified through analysis of variance (ANOVA). The most optimum value of extrusion load has been found to be 136.4kN through iterative process of Genetic Algorithm (GA) using Artificial Neural Network (ANN). The optimized value of input process variables for minimum value of extrusion load obtained has been found to be 13 Revolutions per Minute (RPM) as wheel velocity, 5mm as product diameter, 0.95 as friction condition, 650${}^{\circ }$C as feedstock temperature and 550${}^{\circ }$C as die temperature. This paper with proposed methodology will be helpful for industries working in the area of CE in terms of minimizing energy consumption during production process of bus bars, tubes, wires, cables, sheets, plates, strips, etc.