查看更多>>摘要：Balancing between simulation performance and simulation accuracy is difficult. Most simulators focus on optimizing only one of these two aspects. Which comes at the cost of the other. In this work we demonstrate a framework to dynamically balance between computational performance and simulation accuracy based on the context of the simulation. This allows to maximize both performance and accuracy when possible during the execution of the simulation. To do this, we present a method to apply adaptive abstraction in a large-scale agent-based traffic simulation. This method uses the concept of experimental frames for simulation models in order to keep track of model validity given the current simulation context. Furthermore, we present a custom developed state-of-the-art multi-level traffic simulator that includes adaptive abstraction in the core of its simulation architecture. We validate the proposed methods in a realistic multi-level traffic simulation use case executed in an urban environment.
查看更多>>摘要：City-scale simulation modelling of active modes of transportation (i.e., walking and cycling) is becoming increasingly popular in recent years. The heterogeneous and complex behaviour of these transportation modes, however, indicates the need for a shift from the traditional car and public transport centred modelling approaches towards incorporating the requirements for walking and cycling behaviour, while maintaining the run-time efficiency of the models. In this paper, we introduce and test our algorithm to create road network representations, designed and optimised to be used in city-scale active transportation modelling. The algorithm relies on open and universal data. In addition to the major roads and attributes typically used in transport modelling (e.g., speed limit, number of lanes, permitted travel modes), the algorithm also captures minor roads usually favoured by pedestrians and cyclists, along with road attributes such as bicycle-specific infrastructure, traffic signals, road gradient and road surface type. Furthermore, it simplifies the complex geometries of the network and merges parallel roads, if applicable, to make it suitable for large-scale simulations. To examine the utility and performance of the algorithm, we used it to create a network representation for Greater Melbourne, Australia, and compared the output with a network created using an existing simulation toolkit along with another network from an existing city-scale transport model from the Victorian government. Through simulation experiments with these networks, we illustrated that for routed trips on our network for walking and cycling, it is of comparable accuracy to the common network conversion tools in terms of travel distance of the shortest paths while being more than two times faster when used for simulating different sample sizes. Therefore, our algorithm offers a flexible and adjustable solution for users to create road networks for city-scale active transport modelling while balancing between their desired simulation accuracy and run-time.
查看更多>>摘要：This paper presents a comparative assessment of two-dimensional convolutional neural networks (2DCNN) and boosting methods for regression-based textile whiteness estimation, applied to high resolution images of textiles of an industrial cotton textiles producer, labeled with whiteness values, thus enabling supervised learning. The images were taken under various lighting conditions. Concerning the machine learning methods, Random Forest and XGBoost were the selected and tested boosting techniques on which model hyper-parameter tuning was applied, whereas regarding the 2DCNN architectures, the known from literature ColorNet architecture was selected and a more shallow one, called WERegNet, was introduced. Data augmentation was applied during pre-processing, due to the limited amount of available data. Based on the simulation results, the WERegNet architecture surpasses ColorNet and XGBoost in terms of performance, while it is comparable with Random Forest on test set, based on model selection measure Normalized Root Mean Squared Error.
查看更多>>摘要：Recently, a great development has occurred in the communication networks, in which the trend of development is towards automation and flexible network structure. In addition, the stages of telecommunication development are conventionally divided from manual switching to flexible virtualized architecture, to which telecommunications operators have resorted. Furthermore, in the context of the 3rd generation partnership project (3GPP) standards framework, the network function virtualization (NFV) with might and main has been evaluated by telecom operators and shows that the efficiency of the topology can be significantly improved. However, it is difficult to organize ultra-reliable low-latency communication (URLLC) and massive machine type communications (mMTC) services within 5G, due to the topology centralization. Moreover, network monitoring, in particular of carrier-class equipment, reveals that there is no ideal static network topology in which the network and its elements have been uniformly loaded over a long service time. Therefore, in this study, a dynamic network topology and service placement is proposed to analyze and predict services, in which Genetic Algorithm (GA) is utilized. In addition, an efficient forecasting and live migration methods of service as an application to edge computing systems are introduced, where this approach can be used in the systems with an intelligent allocation of operator equipment resources for providing flexibility and high-quality topological organization. Finally, simulation results proved that the network equipment efficiency can significantly be increased by more than 30%.
Soares do Amaral J.V.Montevechi J.A.B.Miranda R.D.C.Junior W.T.D.S....
21页
查看更多>>摘要：Over the past few decades, modeling, simulation, and optimization tools have received attention for their ability to represent and improve complex systems. The use of metamodeling techniques in optimization via simulation problems has grown considerably in recent years to promote more robust and agile decision-making, determining the best scenario in the solution space. The objective of this article is to conduct a systematic literature review of metamodeling-based simulation optimization (MBSO). The main contributions of this paper are related to systematically gather, analyze, and discuss the knowledge disseminated in this area, support future research and expand the literature related to MBSO techniques. Research questions were planned to assist MBSO researchers and practitioners, by presenting the most frequent contexts, applications, methods, tools, and metrics found in metamodeling studies in optimization via simulation problems. We considered papers published in scientific journals and listed in the Web of Science, Scopus, ACM Digital Library, IEEE Xplore, and Science Direct databases. The conclusion related the gaps, opportunities, and future perspectives found during the development of this research, suggesting that this research area is growing in the past 15 years.
查看更多>>摘要：Martensitic stainless steel is widely used where there is a need for strength, hardness, and corrosion resistance. But the machinability of this steel is difficult because of its poor thermal conductivity, as it leads to high tool wear. Application of coating on the cutting tool is one of the sustainable techniques utilized in improving the machinability of work material. But the problem in the application of the coated tool is the determination of different coating materials and the thickness of coatings, and it usually requires extensive experimental tests. Therefore finite element modelling has proved to be one of the important techniques which can be employed in evaluating the machining performance of coated cutting tools. In the current work, oblique cutting experiments, 2D, and 3D FEM simulations have been performed while machining the martensitic AISI 420 steel using the multi-layered (TiN-TiCN-Al2O3-TiN, TiN-Al2O3-TiCN-TiN) coated carbide tools and uncoated carbide tool. A tabular data material model has been utilized to model the work material. Initially, the simulation results of tangential forces obtained using 2D FE and 3D FE machining models are validated with the experimental tangential forces at a feed rate (f) of 0.14 mm/rev, depth (d) of 0.3 mm, and cutting velocity (V) of 230 m/min. It has been observed that a maximum error of 59.10% in the tangential force has been observed using the 2D FE machining model and experimental results, while a maximum error of 4.05% has been observed using the 3D machining model and experimental results. Thus it indicates that the 3D FE machining model is more suitable in the prediction of machining responses. The 3D FE machining model has been further validated with the experimental results in terms of tangential force and feeds force using the different coated and uncoated cutting tools at varying feed rates of 0.14, 0.18, 0.224, and 0.25 mm/rev and at depth d = 0.3 mm, cutting speed V = 230 m/min. A maximum error of 13.97% in the tangential force and 5% in the feed force is observed at different cutting conditions. The validated model has been further utilized to examine the influence of tool coatings and cutting parameters on the effective stress, cutting temperature, cutting power, and tool temperature. The developed 3D FE model indicates that the better machinability of martensitic AISI 420 steel can be achieved using the multi-layer TiN-TiCN-Al2O3-TiN coated tool in terms of reduction in cutting temperature, effective stress, and power consumption.
查看更多>>摘要：In this paper,1 we describe LUNES-Blockchain, an agent-based simulator of blockchains that relies on Parallel and Distributed Simulation (PADS) techniques to obtain high scalability. The software is organized as a multi-level simulator that permits to simulate a virtual environment, made of many nodes running the protocol of a specific Distributed Ledger Technology (DLT), such as the Bitcoin or the Ethereum blockchains. This virtual environment is executed on top of a lower-level Peer-to-Peer (P2P) network overlay, which can be structured based on different topologies and with a given number of nodes and edges. Functionalities at different levels of abstraction are managed separately, by different software modules and with different time granularity. This allows for accurate simulations, where (and when) it is needed, and enhances the simulation performance. Using LUNES-Blockchain, it is possible to simulate different types of attacks on the DLT. In this paper, we specifically focus on the P2P layer, considering the selfish mining, the 51% attack and the Sybil attack. For which concerns selfish mining and the 51% attack, our aim is to understand how much the hash-rate (i.e. a general measure of the processing power in the blockchain network) of the attacker can influence the outcome of the misbehavior. On the other hand, in the filtering denial of service (i.e. Sybil Attack), we investigate which dissemination protocol in the underlying P2P network makes the system more resilient to a varying number of nodes that drop the messages. The results confirm the viability of the simulation-based techniques for the investigation of security aspects of DLTs.
查看更多>>摘要：The Feed-Forward and Backpropagation Artificial Neural Networks (FFBP-ANN) are generally employed for cut surfaces quality characteristics predictions. However, the determination of the neurons on the hidden layer and the training parameters’ values are tasks requiring many trials according to the Full-Factorial Approach (FFA). Therefore, in this work, a methodology is presented for the optimization of an FFBP-NN and the application of the Taguchi Design of Experiments (TDE). Nine combinations of four variables were examined, having three levels each, according to the L9 (34) orthogonal array. The number of neurons in the hidden layer (N), the learning rate (mu), the increment factor (mu+) and the decrement factor (mu-) are employed as variables. In addition, Mean Squared Error (MSE) and overall regression index (Rall) was decided as the objective functions. Thus, TDE diminishes the FFBP-ANN arrangements to nine from eighty-one of FFA. The optimized FFBP-ANN predicts the surface roughness in various cut depths during laser cutting of thin thermoplastic plates.
查看更多>>摘要：Sheet metal forming operations are widely used in the industry because of their ability to produce complex shapes at higher production rates. These operations utilize high stresses to plastically deform workpiece in the desired geometry. For reliable performance, punch design and operating parameters can play significant role. To investigate the tool wear finite element (FE) based numerical methodology was developed in this study. Tool wear is one of the main causes of tool failure and process deviation in the punching operation. Research in the past has covered process parameters and effects of wear on the die plate. However, little research focused on the effects of wear on the punch itself. In this paper a full analysis of the punching process was performed, giving an understating of the effects of tool rounding due to wear on various punching parameters, while focusing on the evolution of wear on the punch in all cases. It was found that wear accelerates as the punch's bluntness is increased. It was also identified that most of the wear is expected on the radius on the punch as opposed to its face, and the full punch diameter will be affected by the abrasive wear between the sheet metal and the punch as opposed to only the striking edge. However, it was also seen that in cases of highly worn-out punches, the wear on the side can be decreased due to the increased deformation of the sheet metal which occurs due to the blunt punch.
查看更多>>摘要：Flexible job shop scheduling problem (FJSSP) is a critical operational planning step in manufacturing that ensures on-time delivery of goods leading to customer satisfaction. The process of assigning jobs to machines has a larger solution space and consumes a huge amount of time and effort. This research focuses on solving FJSSP using the discrete event simulation (DES) model and integrates it with Composite Dispatching Rules (CDRs) and multi-criteria decision making (MCDMs) based priority rules. Performance evaluation of the flexible job shop is carried out to minimize the Makespan, mean Flow-Time, mean Tardiness, and maximum Tardiness. Best performing CDRs and hybrid MCDM techniques are employed for minimizing the objectives considered in this study. The proposed solution framework integrates Fuzzy Analytic Hierarchy Process (FAHP) for assigning weights to the criteria and MCDM approaches namely technique for order of preference by similarity to ideal solution (TOPSIS), The Evaluation based on Distance from Average Solution (EDAS), Compromise Programming (CP), and Weighted Average Method (WAM) separately to prioritize the jobs. Benchmark problems of different sizes are tested using the best performing CDRs available in the literature and proposed MCDM approaches. The proposed approach is implemented in a real-world large-scale flexible job shop (FJS) that produces auto components handling 114 job variants with 245 operations using 28 machines. The performance analysis indicates that no single rule outperforms all the objective measures considered in this study. The MCDMs based rules perform better compared to CDRs for large-scale problems by considering realistic criteria such as demand, due date, setup time, process time, customer priority, and number of operations. The methodology proposed in this study can be tailored in terms of the criteria used for ranking and production parameters to be executable for any real-time instance.
NSTL
Elsevier