International Journal of Modeling, Simulation, and Scientific Computing

In distribution simulation based on High-level architecture (HLA), data distribution management (DDM) is one of HLA services for the purpose of filtering the unnecessary data transferring over the network. DDM admits the sending federates and the receiving federates to express their interest using update regions and subscription regions in a multidimensional routing space. There are several matching algorithms to obtain overlap information between the update regions and subscription regions. When the number of regions increase sharply, the matching process is time consuming. However, the existing algorithms is hard to be parallelized to take advantage of the computing capabilities of multi-core processors. To reduce the computational overhead of region matching, we propose a parallel algorithm based on order relation to accelerate the matching process. The new matching algorithm adopts divide-and-conquer approach to divide the regions into multiple region bound sublists, each of which comprises parts of region bounds. To calculate the intersection inside and amongst the region bound sublists, two matching rules are presented. This approach has good performance since it performs region matching on the sublists parallel and does not require unnecessary comparisons within regions in different sublists. Theoretical analysis has been carried out for the proposed algorithm and experimental result shows that the proposed algorithm has better performance than major existing DDM matching algorithms.

In order to provide a simple and efficient approach to perform the real-time interactive motion control of virtual human in virtual maintenance environment (VME), the motion control method of virtual human based on limited input information is proposed. With the space position tracking system with only one sensor the action sequences and motion models of virtual human, the human motions and hand actions in VME are driven by the sensor data in stages and in real time through the transmission condition control in the process of maintenance operation. And the input data and information is processed based on the method of Kalman filtering and wavelet transforming to improve the control effects. An experimental VME is also established to validate the control efficiency, and the experiment results show that the space motion control of virtual human in VME can be performed based on limited information with proposed control strategy.

The numerical simulation of 2D simple square lattice of Ising superspins, that interact via the Ruderman–Kittel–Kasuya–Yosida (RKKY) exchange interaction is performed. It is found, that at low temperatures in the researched systems predominantly realized labyrinth domain structure. The modeled image of magnetization distribution does not coincide with the image of energy distribution. Hysteresis loops of the samples and labyrinth domain structures similarly obtained by Monte Carlo method, are also observed in physical experiments.

In this paper, we propose to study four meteorological and seasonal time series (TS) coupled with a multi-layer perceptron (MLP) modeling. We chose to combine two transfer functions for the nodes of the hidden layer, and to use a temporal indicator (time index as input) in order to take into account the seasonal aspect of the studied TS. The results of the prediction concern two years of measurements and the learning step, eight independent years. We show that this methodology can improve the accuracy of meteorological data estimation compared to a classical MLP modeling with a homogenous transfer function.

To better utilize the potential of system simulation models and simulators, industrially applicable methods for Verification, Validation and Uncertainty Quantification (VV&UQ) are crucial. This paper presents an exploratory case study of VV&UQ techniques applied on models integrated in aircraft system simulators at Saab Aeronautics and in driving simulators at the Swedish National Road and Transport Research Institute (VTI). Results show that a large number of Verification and Validation (V&V) techniques are applied, some of which are promising for further development and use in simulator credibility assessment. Regarding the application of UQ, a large gap between academia and this part of industry has been identified, and simplified methods are needed. The applicability of the NASA Credibility Assessment Scale (CAS) at the studied organizations is also evaluated and it can be concluded that the CAS is considered to be a usable tool for achieving a uniform level of V&V for all models included in a simulator, although its implementation at the studied organizations requires tailoring and coordination.

Online anomaly detection for stream data has been explored recently, where the detector is supposed to be able to perform an accurate and timely judgment for the upcoming observation. However, due to the inherent complex characteristics of stream data, such as quick generation, tremendous volume and dynamic evolution distribution, how to develop an effective online anomaly detection method is a challenge. The main objective of this paper is to propose an adaptive online anomaly detection method for stream data. This is achieved by combining isolation principle with online ensemble learning, which is then optimized by statistic histogram. Three main algorithms are developed, i.e., online detector building algorithm, anomaly detecting algorithm and adaptive detector updating algorithm. To evaluate our proposed method, four massive datasets from the UCI machine learning repository recorded from real events were adopted. Extensive simulations based on these datasets show that our method is effective and robust against different scenarios.

Inspired by the foraging behavior of E. coli bacteria, bacterial foraging optimization (BFO) has emerged as a powerful technique for solving optimization problems. However, BFO shows poor performance on complex and high-dimensional optimization problems. In order to improve the performance of BFO, a new dynamic bacterial foraging optimization based on clonal selection (DBFO-CS) is proposed. Instead of fixed step size in the chemotaxis operator, a new piecewise strategy adjusts the step size dynamically by regulatory factor in order to balance between exploration and exploitation during optimization process, which can improve convergence speed. Furthermore, reproduction operator based on clonal selection can add excellent genes to bacterial populations in order to improve bacterial natural selection and help good individuals to be protected, which can enhance convergence precision. Then, a set of benchmark functions have been used to test the proposed algorithm. The results show that DBFO-CS offers significant improvements than BFO on convergence, accuracy and robustness. A complex optimization problem of model reduction on stable and unstable linear systems based on DBFO-CS is presented. Results show that the proposed algorithm can efficiently approximate the systems.

Unmanned Underwater Vehicle (UUV) formation system has an important role in the utilization of marine resource. In order to provide an efficient method to research modeling and simulation of UUV formation in the marine environment, the novel approach based on Multi-Agent Interaction Chain was proposed for the UUV formation system. Firstly, Multi-Agent Interaction Chain was analyzed, which mainly considered task and role of UUV in the formation, and the overall modeling process of UUV formation system based on Multi-Agent Interaction Chain was established. Then, the static structure of Multi-Agent Interaction Chain was researched focusing on Hybrid UUV-Agent model structure from the UUV-Agent State-Set and UUV-Agent Rule-Base which were the two aspects to strengthen reliability of interaction chain; the dynamic mechanism of Multi-Agent Interaction Chain was designed, which was focused on collaboration model and communication model through the Adaptive Dynamic Contract Net Protocol and KQML/XML/RTI. Finally, three experiments were established to verify the validity and effectiveness of proposed modeling approach for UUV formation system. Simulation results show the proposed model has good performance, which has important theoretical innovation and application prospects.

A new treatment is presented for land use planning problems by means of extremal optimization (EO) in conjunction to cell-based neighborhood local search. EO, inspired by self-organized critical models of evolution has been applied mainly to the solution of classical combinatorial optimization problems. Cell-based local search has been employed by the author elsewhere in problems of spatial resource allocation in combination with genetic algorithms and simulated annealing. In this paper, it complements EO in order to enhance its capacity for a spatial optimization problem. The hybrid method thus formed is compared to methods of the literature on a specific resource allocation problem by taking into account both the development and the transportation cost. It yields better results both in terms of objective function values and in terms of compactness. The latter is an important quantity for spatial planning and its meaning is discussed. The appearance of significant compactness values as emergent results is investigated.

In this paper, a method of 3D reconstruction from two images acquired by two panoramic cameras is presented. Firstly, the features of the reconstruction object detected in each image are matched through the DP matching method. Secondly, optical correction is carried out on two cameras, and the internal parameters of panoramic cameras can be calculated. Finally, according to the calibration method, the geometric relationship between corresponding points in space and in two panoramic images is deduced. The results indicate that the method of 3D reconstruction based on two panoramic cameras is simple, and the accuracy can reach 98.82%.

A finite element model for piezoelectric smart beam in extension mode based on First-order Shear Deformation Theory (FSDT) with an appropriate through-thickness distribution of electric potential is presented. Accuracy of piezoelectric finite element formulations depends on the selection of assumed mechanical and electrical fields. Most of the conventional FSDT-based piezoelectric beam formulations available in the literature use linear through-thickness distribution of electric potential which is actually nonlinear. Here, a novel quadratic profile of the through-thickness electric potential is proposed to include the nonlinear effects. The results obtained show that the accuracy of conventional formulations with linear through-thickness potential approximation is affected by the material configuration, especially when the piezoelectric material dominates the beam cross section. It is shown that the present formulation gives the same level of accuracy for all regimes of material configurations in the beam cross section. Also, a modified form of the FSDT displacements is employed, which utilizes the shear angle as a degree of freedom instead of section rotation. Such a FSDT displacement field shows improved performance compared to the conventional field. The present formulation is validated by comparing the results with ANSYS 2D simulation. The comparison of results proves the improved efficiency and accuracy of the present formulation over the conventional formulations.

With severe overload on transmission lines, further exchange of power flow is affected due to congestion on power transmission lines. This paper investigates the effect of Flexible AC Transmission System (FACTS) devices like TCSC and UPFC in congestion mitigation. The proposal uses multiple FACTS devices of similar type and investigates their effect on congestion mitigation in high voltage transmission lines. This proposal is tested on IEEE-14 bus system.