Load balancing in integrated optical wireless networks

DEFF Research Database (Denmark)

Yan, Ying; Dittmann, Lars; Wong, S-W.

2010-01-01

In this paper, we tackle the load balancing problem in Integrated Optical Wireless Networks, where cell breathing technique is used to solve congestion by changing the coverage area of a fully loaded cell tower. Our objective is to design a load balancing mechanism which works closely...... with the integrated control scheme so as to maximize overall network throughput in the integrated network architecture. To the best of our knowledge no load balancing mechanisms, especially based on the Multi-Point Control Protocol (MPCP) defined in the IEEE 802.3ah, have been proposed so far. The major research...... issues are outlined and a cost function based optimization model is developed for power management. In particularly, two alternative feedback schemes are proposed to report wireless network status. Simulation results show that our proposed load balancing mechanism improves network performances....

Two Stage Secure Dynamic Load Balancing Architecture for SIP Server Clusters

Directory of Open Access Journals (Sweden)

G. Vennila

2014-08-01

Full Text Available Session Initiation Protocol (SIP is a signaling protocol emerged with an aim to enhance the IP network capabilities in terms of complex service provision. SIP server scalability with load balancing has a greater concern due to the dramatic increase in SIP service demand. Load balancing of session method (request/response and security measures optimizes the SIP server to regulate of network traffic in Voice over Internet Protocol (VoIP. Establishing a honeywall prior to the load balancer significantly reduces SIP traffic and drops inbound malicious load. In this paper, we propose Active Least Call in SIP Server (ALC_Server algorithm fulfills objectives like congestion avoidance, improved response times, throughput, resource utilization, reducing server faults, scalability and protection of SIP call from DoS attacks. From the test bed, the proposed two-tier architecture demonstrates that the ALC_Server method dynamically controls the overload and provides robust security, uniform load distribution for SIP servers.

Dynamic optical resource allocation for mobile core networks with software defined elastic optical networking.

Science.gov (United States)

Zhao, Yongli; Chen, Zhendong; Zhang, Jie; Wang, Xinbo

2016-07-25

Driven by the forthcoming of 5G mobile communications, the all-IP architecture of mobile core networks, i.e. evolved packet core (EPC) proposed by 3GPP, has been greatly challenged by the users' demands for higher data rate and more reliable end-to-end connection, as well as operators' demands for low operational cost. These challenges can be potentially met by software defined optical networking (SDON), which enables dynamic resource allocation according to the users' requirement. In this article, a novel network architecture for mobile core network is proposed based on SDON. A software defined network (SDN) controller is designed to realize the coordinated control over different entities in EPC networks. We analyze the requirement of EPC-lightpath (EPCL) in data plane and propose an optical switch load balancing (OSLB) algorithm for resource allocation in optical layer. The procedure of establishment and adjustment of EPCLs is demonstrated on a SDON-based EPC testbed with extended OpenFlow protocol. We also evaluate the OSLB algorithm through simulation in terms of bandwidth blocking ratio, traffic load distribution, and resource utilization ratio compared with link-based load balancing (LLB) and MinHops algorithms.

Insights and issues with simulating terrestrial DOC loading of Arctic river networks.

Science.gov (United States)

Kicklighter, David W; Hayes, Daniel J; McClelland, James W; Peterson, Bruce J; McGuire, A David; Melillo, Jerry M

2013-12-01

Terrestrial carbon dynamics influence the contribution of dissolved organic carbon (DOC) to river networks in addition to hydrology. In this study, we use a biogeochemical process model to simulate the lateral transfer of DOC from land to the Arctic Ocean via riverine transport. We estimate that, over the 20th century, the pan-Arctic watershed has contributed, on average, 32 Tg C/yr of DOC to river networks emptying into the Arctic Ocean with most of the DOC coming from the extensive area of boreal deciduous needle-leaved forests and forested wetlands in Eurasian watersheds. We also estimate that the rate of terrestrial DOC loading has been increasing by 0.037 Tg C/yr2 over the 20th century primarily as a result of climate-induced increases in water yield. These increases have been offset by decreases in terrestrial DOC loading caused by wildfires. Other environmental factors (CO2 fertilization, ozone pollution, atmospheric nitrogen deposition, timber harvest, agriculture) are estimated to have relatively small effects on terrestrial DOC loading to Arctic rivers. The effects of the various environmental factors on terrestrial carbon dynamics have both offset and enhanced concurrent effects on hydrology to influence terrestrial DOC loading and may be changing the relative importance of terrestrial carbon dynamics on this carbon flux. Improvements in simulating terrestrial DOC loading to pan-Arctic rivers in the future will require better information on the production and consumption of DOC within the soil profile, the transfer of DOC from land to headwater streams, the spatial distribution of precipitation and its temporal trends, carbon dynamics of larch-dominated ecosystems in eastern Siberia, and the role of industrial organic effluents on carbon budgets of rivers in western Russia.

Insights and issues with simulating terrestrial DOC loading of Arctic river networks

Science.gov (United States)

Kicklighter, David W.; Hayes, Daniel J.; McClelland, James W.; Peterson, Bruce J.; McGuire, A. David; Melillo, Jerry M.

2013-01-01

Terrestrial carbon dynamics influence the contribution of dissolved organic carbon (DOC) to river networks in addition to hydrology. In this study, we use a biogeochemical process model to simulate the lateral transfer of DOC from land to the Arctic Ocean via riverine transport. We estimate that, over the 20th century, the pan-Arctic watershed has contributed, on average, 32 Tg C/yr of DOC to river networks emptying into the Arctic Ocean with most of the DOC coming from the extensive area of boreal deciduous needle-leaved forests and forested wetlands in Eurasian watersheds. We also estimate that the rate of terrestrial DOC loading has been increasing by 0.037 Tg C/yr2 over the 20th century primarily as a result of climate-induced increases in water yield. These increases have been offset by decreases in terrestrial DOC loading caused by wildfires. Other environmental factors (CO2 fertilization, ozone pollution, atmospheric nitrogen deposition, timber harvest, agriculture) are estimated to have relatively small effects on terrestrial DOC loading to Arctic rivers. The effects of the various environmental factors on terrestrial carbon dynamics have both offset and enhanced concurrent effects on hydrology to influence terrestrial DOC loading and may be changing the relative importance of terrestrial carbon dynamics on this carbon flux. Improvements in simulating terrestrial DOC loading to pan-Arctic rivers in the future will require better information on the production and consumption of DOC within the soil profile, the transfer of DOC from land to headwater streams, the spatial distribution of precipitation and its temporal trends, carbon dynamics of larch-dominated ecosystems in eastern Siberia, and the role of industrial organic effluents on carbon budgets of rivers in western Russia.

Dynamics of the cell-cycle network under genome-rewiring perturbations

International Nuclear Information System (INIS)

Katzir, Yair; Elhanati, Yuval; Braun, Erez; Averbukh, Inna

2013-01-01

The cell-cycle progression is regulated by a specific network enabling its ordered dynamics. Recent experiments supported by computational models have shown that a core of genes ensures this robust cycle dynamics. However, much less is known about the direct interaction of the cell-cycle regulators with genes outside of the cell-cycle network, in particular those of the metabolic system. Following our recent experimental work, we present here a model focusing on the dynamics of the cell-cycle core network under rewiring perturbations. Rewiring is achieved by placing an essential metabolic gene exclusively under the regulation of a cell-cycle's promoter, forcing the cell-cycle network to function under a multitasking challenging condition; operating in parallel the cell-cycle progression and a metabolic essential gene. Our model relies on simple rate equations that capture the dynamics of the relevant protein–DNA and protein–protein interactions, while making a clear distinction between these two different types of processes. In particular, we treat the cell-cycle transcription factors as limited ‘resources’ and focus on the redistribution of resources in the network during its dynamics. This elucidates the sensitivity of its various nodes to rewiring interactions. The basic model produces the correct cycle dynamics for a wide range of parameters. The simplicity of the model enables us to study the interface between the cell-cycle regulation and other cellular processes. Rewiring a promoter of the network to regulate a foreign gene, forces a multitasking regulatory load. The higher the load on the promoter, the longer is the cell-cycle period. Moreover, in agreement with our experimental results, the model shows that different nodes of the network exhibit variable susceptibilities to the rewiring perturbations. Our model suggests that the topology of the cell-cycle core network ensures its plasticity and flexible interface with other cellular processes

Short-Term Load Forecasting Model Based on Quantum Elman Neural Networks

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Zhisheng Zhang

2016-01-01

Full Text Available Short-term load forecasting model based on quantum Elman neural networks was constructed in this paper. The quantum computation and Elman feedback mechanism were integrated into quantum Elman neural networks. Quantum computation can effectively improve the approximation capability and the information processing ability of the neural networks. Quantum Elman neural networks have not only the feedforward connection but also the feedback connection. The feedback connection between the hidden nodes and the context nodes belongs to the state feedback in the internal system, which has formed specific dynamic memory performance. Phase space reconstruction theory is the theoretical basis of constructing the forecasting model. The training samples are formed by means of K-nearest neighbor approach. Through the example simulation, the testing results show that the model based on quantum Elman neural networks is better than the model based on the quantum feedforward neural network, the model based on the conventional Elman neural network, and the model based on the conventional feedforward neural network. So the proposed model can effectively improve the prediction accuracy. The research in the paper makes a theoretical foundation for the practical engineering application of the short-term load forecasting model based on quantum Elman neural networks.

Failure cascade in interdependent network with traffic loads

International Nuclear Information System (INIS)

Hong, Sheng; Wang, Baoqing; Wang, Jianghui; Zhao, Tingdi; Ma, Xiaomin

2015-01-01

Complex networks have been widely studied recent years, but most researches focus on the single, non-interacting networks. With the development of modern systems, many infrastructure networks are coupled together and therefore should be modeled as interdependent networks. For interdependent networks, failure of nodes in one network may lead to failure of dependent nodes in the other networks. This may happen recursively and lead to a failure cascade. In the real world, different networks carry different traffic loads. Overload and load redistribution may lead to more nodes’ failure. Considering the dependency between the interdependent networks and the traffic load, a small fraction of fault nodes may lead to complete fragmentation of a system. Based on the robust analysis of interdependent networks, we propose a costless defense strategy to suppress the failure cascade. Our findings highlight the need to consider the load and coupling preference when designing robust interdependent networks. And it is necessary to take actions in the early stage of the failure cascade to decrease the losses caused by the large-scale breakdown of infrastructure networks. (paper)

Wavelength converter placement in optical networks with dynamic traffic

DEFF Research Database (Denmark)

Buron, Jakob Due; Ruepp, Sarah Renée; Wessing, Henrik

2008-01-01

We evaluate the connection provisioning performance of GMPLS-controlled wavelength routed networks under dynamic traffic load and using three different wavelength converter placement heuristics. Results show that a simple uniform placement heuristic matches the performance of complex heuristics...

Load balancing in 5G Networks

Directory of Open Access Journals (Sweden)

Tsirakis Christos

2017-01-01

Full Text Available The expected huge increase of mobile devices and user data demand by 2020 will stress the current mobile network in an unprecedented way. The future mobile networks must meet several strong requirements regarding the data rate, latency, quality of service and experience, mobility, spectrum and energy efficiency. Therefore, efforts for more efficient mobile network solutions have been recently initiated. To this direction, load balancing has attracted much attention as a promising solution for higher resource utilization, improved system performance and decreased operational cost. It is an effective method for balancing the traffic and alleviating the congestion among heterogeneous networks in the upcoming 5G networks. In this paper, we focus on an offloading scenario for load balancing among LTE and Wi-Fi networks. Additionally, network graphs methodology and its abstracted parameters are investigated in order to better manage wireless resource allocation among multiple connections. The COHERENT architectural framework, which consists of two main control components, makes use of such abstracted network graphs for controlling or managing various tasks such as traffic steering, load balancing, spectrum sharing and RAN sharing. As a result, the COHERENT project eventually develops a unified programmable control framework used to efficiently coordinate the underlying heterogeneous mobile networks as a whole.

Dynamic Connectivity between Brain Networks Supports Working Memory: Relationships to Dopamine Release and Schizophrenia

Science.gov (United States)

Van Snellenberg, Jared X.; Benavides, Caridad; Slifstein, Mark; Wang, Zhishun; Moore, Holly; Abi-Dargham, Anissa

2016-01-01

Connectivity between brain networks may adapt flexibly to cognitive demand, a process that could underlie adaptive behaviors and cognitive deficits, such as those observed in neuropsychiatric conditions like schizophrenia. Dopamine signaling is critical for working memory but its influence on internetwork connectivity is relatively unknown. We addressed these questions in healthy humans using functional magnetic resonance imaging (during an n-back working-memory task) and positron emission tomography using the radiotracer [11C]FLB457 before and after amphetamine to measure the capacity for dopamine release in extrastriatal brain regions. Brain networks were defined by spatial independent component analysis (ICA) and working-memory-load-dependent connectivity between task-relevant pairs of networks was determined via a modified psychophysiological interaction analysis. For most pairs of task-relevant networks, connectivity significantly changed as a function of working-memory load. Moreover, load-dependent changes in connectivity between left and right frontoparietal networks (Δ connectivity lFPN-rFPN) predicted interindividual differences in task performance more accurately than other fMRI and PET imaging measures. Δ Connectivity lFPN-rFPN was not related to cortical dopamine release capacity. A second study in unmedicated patients with schizophrenia showed no abnormalities in load-dependent connectivity but showed a weaker relationship between Δ connectivity lFPN-rFPN and working memory performance in patients compared with matched healthy individuals. Poor working memory performance in patients was, in contrast, related to deficient cortical dopamine release. Our findings indicate that interactions between brain networks dynamically adapt to fluctuating environmental demands. These dynamic adaptations underlie successful working memory performance in healthy individuals and are not well predicted by amphetamine-induced dopamine release capacity. SIGNIFICANCE

Dynamic Connectivity between Brain Networks Supports Working Memory: Relationships to Dopamine Release and Schizophrenia.

Science.gov (United States)

Cassidy, Clifford M; Van Snellenberg, Jared X; Benavides, Caridad; Slifstein, Mark; Wang, Zhishun; Moore, Holly; Abi-Dargham, Anissa; Horga, Guillermo

2016-04-13

Connectivity between brain networks may adapt flexibly to cognitive demand, a process that could underlie adaptive behaviors and cognitive deficits, such as those observed in neuropsychiatric conditions like schizophrenia. Dopamine signaling is critical for working memory but its influence on internetwork connectivity is relatively unknown. We addressed these questions in healthy humans using functional magnetic resonance imaging (during ann-back working-memory task) and positron emission tomography using the radiotracer [(11)C]FLB457 before and after amphetamine to measure the capacity for dopamine release in extrastriatal brain regions. Brain networks were defined by spatial independent component analysis (ICA) and working-memory-load-dependent connectivity between task-relevant pairs of networks was determined via a modified psychophysiological interaction analysis. For most pairs of task-relevant networks, connectivity significantly changed as a function of working-memory load. Moreover, load-dependent changes in connectivity between left and right frontoparietal networks (Δ connectivity lFPN-rFPN) predicted interindividual differences in task performance more accurately than other fMRI and PET imaging measures. Δ Connectivity lFPN-rFPN was not related to cortical dopamine release capacity. A second study in unmedicated patients with schizophrenia showed no abnormalities in load-dependent connectivity but showed a weaker relationship between Δ connectivity lFPN-rFPN and working memory performance in patients compared with matched healthy individuals. Poor working memory performance in patients was, in contrast, related to deficient cortical dopamine release. Our findings indicate that interactions between brain networks dynamically adapt to fluctuating environmental demands. These dynamic adaptations underlie successful working memory performance in healthy individuals and are not well predicted by amphetamine-induced dopamine release capacity. It is unclear

Neural Network Based Load Frequency Control for Restructuring ...

African Journals Online (AJOL)

Neural Network Based Load Frequency Control for Restructuring Power Industry. ... an artificial neural network (ANN) application of load frequency control (LFC) of a Multi-Area power system by using a neural network controller is presented.

Peak load-impulse characterization of critical pulse loads in structural dynamics

International Nuclear Information System (INIS)

Abrahamson, G.R.; Lindberg, H.E.

1975-01-01

In presenting the characterization scheme, some general features are described first. A detailed analysis is given for the rigid-plastic system of one degree of freedom to illustrate the calculation of critical load curves in terms of peak load and impulse. This is followed by the presentation of critical load curves for uniformly loaded rigid-plastic beams and plates and for dynamic buckling of cylindrical shells under uniform lateral loads. The peak load-impulse characterization of critical pulse loads is compared with the dynamic load factor characterization, and some aspects of the history of the peak load-pulse scheme are presented. (orig./HP) [de

Efficiency Evaluation of Strategies for Dynamic Management of Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Andrea Verônica González

2017-01-01

Full Text Available This paper presents and evaluates dynamic management strategies to improve efficiency in event-triggered wireless sensor networks. We are considering mobility, where nodes move themselves to maximize the coverage, and load balancing state-of-the-art techniques, by which the number of nodes sensing the same area is reduced. To explore mobility, we present a simple method by which nodes can dynamically reorganize themselves based on the force fields approach of mobile robotics. Firstly, the strategies are evaluated separately through experiments with different network configurations and, afterwards, a joint evaluation has been conducted to observe the impact of mobility on the efficiency of load balancing techniques. We show that mobile nodes significantly contribute to keeping the coverage as nodes die in mesh and powerfully improving it in random deployments. Load balancing techniques achieve important results, increasing lifetime and the number of sensed events. However, in random deployments, these techniques lose efficiency and become unsuitable strategies. Combining these strategies with mobility, we observe that PS-based technique keeps its contribution in mesh and random deployments, as well as improving its performance for not so dense networks. Ant-based technique when combined with mobile nodes loses performance significantly in mesh and keeps its good performance in random deployed and less dense networks.

A dynamic allocation mechanism of delivering capacity in coupled networks

International Nuclear Information System (INIS)

Du, Wen-Bo; Zhou, Xing-Lian; Zhu, Yan-Bo; Zheng, Zheng

2015-01-01

Traffic process is ubiquitous in many critical infrastructures. In this paper, we introduce a mechanism to dynamically allocate the delivering capacity into the data-packet traffic model on the coupled Internet autonomous-system-level network of South Korea and Japan, and focus on its effect on the transport efficiency. In this mechanism, the total delivering capacity is constant and the lowest-load node will give one unit delivering capacity to the highest-load node at each time step. It is found that the delivering capacity of busy nodes and non-busy nodes can be well balanced and the effective betweenness of busy nodes with interconnections is significantly reduced. Consequently, the transport efficiency such as average traveling time and packet arrival rate is remarkably improved. Our work may shed some light on the traffic dynamics in coupled networks.

Short term load forecasting using neuro-fuzzy networks

Energy Technology Data Exchange (ETDEWEB)

Hoffman, M.; Hassan, A. [South Dakota School of Mines and Technology, Rapid City, SD (United States); Martinez, D. [Black Hills Power and Light, Rapid City, SD (United States)

2005-07-01

Details of a neuro-fuzzy network-based short term load forecasting system for power utilities were presented. The fuzzy logic controller was used to fuzzify inputs representing historical temperature and load curves. The fuzzified inputs were then used to develop the fuzzy rules matrix. Output membership function values were determined by evaluating the fuzzified inputs with the fuzzy rules. Output membership function values were used as inputs for the neural network portion of the system. The training process used a back propagation gradient descent algorithm to adjust the weight values of the neural network in order to reduce the error between the neural network output and the desired output. The neural network was then used to predict future load values. Sample data were taken from a local power company's daily load curve to validate the system. A 10 per cent forecast error was introduced in the temperature values to determine the effect on load prediction. Results of the study suggest that the combined use of fuzzy logic and neural networks provide greater accuracy than studies where either approach is used alone. 6 refs., 6 figs.

Adaptive dynamic capacity borrowing in road-covering mobile networks

NARCIS (Netherlands)

Ule, A.; Boucherie, Richardus J.; Li, W.; Pan, Y.

2006-01-01

This paper introduces adaptive dynamic capacity borrowing strategies for wireless networks covering a road. In a F/TDMA-based model, road traffic prediction models are used to characterise the movement of hot spots, such as traffic jams, and subsequently to predict the teletraffic load offered to

Daily Nigerian peak load forecasting using artificial neural network ...

African Journals Online (AJOL)

A daily peak load forecasting technique that uses artificial neural network with seasonal indices is presented in this paper. A neural network of relatively smaller size than the main prediction network is used to predict the daily peak load for a period of one year over which the actual daily load data are available using one ...

On Prolonging Network Lifetime through Load-Similar Node Deployment in Wireless Sensor Networks

Science.gov (United States)

Li, Qiao-Qin; Gong, Haigang; Liu, Ming; Yang, Mei; Zheng, Jun

2011-01-01

This paper is focused on the study of the energy hole problem in the Progressive Multi-hop Rotational Clustered (PMRC)-structure, a highly scalable wireless sensor network (WSN) architecture. Based on an analysis on the traffic load distribution in PMRC-based WSNs, we propose a novel load-similar node distribution strategy combined with the Minimum Overlapping Layers (MOL) scheme to address the energy hole problem in PMRC-based WSNs. In this strategy, sensor nodes are deployed in the network area according to the load distribution. That is, more nodes shall be deployed in the range where the average load is higher, and then the loads among different areas in the sensor network tend to be balanced. Simulation results demonstrate that the load-similar node distribution strategy prolongs network lifetime and reduces the average packet latency in comparison with existing nonuniform node distribution and uniform node distribution strategies. Note that, besides the PMRC structure, the analysis model and the proposed load-similar node distribution strategy are also applicable to other multi-hop WSN structures. PMID:22163809

Dynamic state estimation for distribution networks with renewable energy integration

NARCIS (Netherlands)

Nguyen, P.H.; Venayagamoorthy, G.K.; Kling, W.L.; Ribeiro, P.F.

2013-01-01

The massive integration of variable and unpredictable Renewable Energy Sources (RES) and new types of load consumptions increases the dynamic and uncertain nature of the electricity grid. Emerging interests have focused on improving the monitoring capabilities of network operators so that they can

A Scalable Distribution Network Risk Evaluation Framework via Symbolic Dynamics

Science.gov (United States)

Yuan, Kai; Liu, Jian; Liu, Kaipei; Tan, Tianyuan

2015-01-01

Background Evaluations of electric power distribution network risks must address the problems of incomplete information and changing dynamics. A risk evaluation framework should be adaptable to a specific situation and an evolving understanding of risk. Methods This study investigates the use of symbolic dynamics to abstract raw data. After introducing symbolic dynamics operators, Kolmogorov-Sinai entropy and Kullback-Leibler relative entropy are used to quantitatively evaluate relationships between risk sub-factors and main factors. For layered risk indicators, where the factors are categorized into four main factors – device, structure, load and special operation – a merging algorithm using operators to calculate the risk factors is discussed. Finally, an example from the Sanya Power Company is given to demonstrate the feasibility of the proposed method. Conclusion Distribution networks are exposed and can be affected by many things. The topology and the operating mode of a distribution network are dynamic, so the faults and their consequences are probabilistic. PMID:25789859

DYNAMIC LOAD DAMPER MODELING

Directory of Open Access Journals (Sweden)

Loktev Aleksey Alekseevich

2013-01-01

Full Text Available The authors present their findings associated with their modeling of a dynamic load damper. According to the authors, the damper is to be installed onto a structure or its element that may be exposed to impact, vibration or any other dynamic loading. The damper is composed of paralleled or consecutively connected viscous and elastic elements. The authors study the influence of viscosity and elasticity parameters of the damper produced onto the regular displacement of points of the structure to be protected and onto the regular acceleration transmitted immediately from the damper to the elements positioned below it.

Local Dynamic Stability Associated with Load Carrying

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Jian Liu

2013-03-01

Conclusion: Current study confirmed the sensitivity of local dynamic stability measure in load carrying situation. It was concluded that load carrying tasks were associated with declined local dynamic stability, which may result in increased risk of fall accident. This finding has implications in preventing fall accidents associated with occupational load carrying.

An Initial Load-Based Green Software Defined Network

Directory of Open Access Journals (Sweden)

Ying Hu

2017-05-01

Full Text Available Software defined network (SDN is a new network architecture in which the control function is decoupled from the data forwarding plane, that is attracting wide attentions from both research and industry sectors. However, SDN still faces the energy waste problem as do traditional networks. At present, research on energy saving in SDN is mainly focused on the static optimization of the network with zero load when new traffic arrives, changing the transmission path of the uncompleted traffic which arrived before the optimization, possibly resulting in route oscillation and other deleterious effects. To avoid this, a dynamical energy saving optimization scheme in which the paths of the uncompleted flows will not be changed when new traffic arrives is designed. To find the optimal solution for energy saving, the problem is modeled as a mixed integer linear programming (MILP problem. As the high complexity of the problem prohibits the optimal solution, an improved heuristic routing algorithm called improved constant weight greedy algorithm (ICWGA is proposed to find a sub-optimal solution. Simulation results show that the energy saving capacity of ICWGA is close to that of the optimal solution, offering desirable improvement in the energy efficiency of the network.

Three-phase Power Flow Calculation of Low Voltage Distribution Network Considering Characteristics of Residents Load

Science.gov (United States)

Wang, Yaping; Lin, Shunjiang; Yang, Zhibin

2017-05-01

In the traditional three-phase power flow calculation of the low voltage distribution network, the load model is described as constant power. Since this model cannot reflect the characteristics of actual loads, the result of the traditional calculation is always different from the actual situation. In this paper, the load model in which dynamic load represented by air conditioners parallel with static load represented by lighting loads is used to describe characteristics of residents load, and the three-phase power flow calculation model is proposed. The power flow calculation model includes the power balance equations of three-phase (A,B,C), the current balance equations of phase 0, and the torque balancing equations of induction motors in air conditioners. And then an alternating iterative algorithm of induction motor torque balance equations with each node balance equations is proposed to solve the three-phase power flow model. This method is applied to an actual low voltage distribution network of residents load, and by the calculation of three different operating states of air conditioners, the result demonstrates the effectiveness of the proposed model and the algorithm.

Quantum load balancing in ad hoc networks

Science.gov (United States)

Hasanpour, M.; Shariat, S.; Barnaghi, P.; Hoseinitabatabaei, S. A.; Vahid, S.; Tafazolli, R.

2017-06-01

This paper presents a novel approach in targeting load balancing in ad hoc networks utilizing the properties of quantum game theory. This approach benefits from the instantaneous and information-less capability of entangled particles to synchronize the load balancing strategies in ad hoc networks. The quantum load balancing (QLB) algorithm proposed by this work is implemented on top of OLSR as the baseline routing protocol; its performance is analyzed against the baseline OLSR, and considerable gain is reported regarding some of the main QoS metrics such as delay and jitter. Furthermore, it is shown that QLB algorithm supports a solid stability gain in terms of throughput which stands a proof of concept for the load balancing properties of the proposed theory.

An Investigation of dynamic characteristics of structures subjected to dynamic load from the viewpoint of design

International Nuclear Information System (INIS)

Lee, Hyun Ah; Kim, Yong Il; Park, Gyung Jin; Kang, Byung Soo; Kim, Joo Sung

2006-01-01

All the loads in the real world are dynamic loads and structural optimization under dynamic loads is very difficult. Thus the dynamic loads are often transformed to static loads by dynamic factors, which are believed equivalent to the dynamic loads. However, due to the difference of load characteristics, there can be considerable differences between the results from static and dynamic analyses. When the natural frequency of a structure is high, the dynamic analysis result is similar to that of static analysis due to the small inertia effect on the behavior of the structure. However, if the natural frequency of the structure is low, the inertia effect should not be ignored. then, the behavior of the dynamic system is different from that of the static system. The difference of the two cases can be explained from the relationship between the homogeneous and the particular solutions of the differential equation that governs the behavior of the structure. Through various examples, the difference between the dynamic analysis and the static analysis are shown. Also dynamic response optimization results are compared with the results with static loads transformed from dynamic loads by dynamic factors, which show the necessity of the design considering dynamic loads

Peak loads and network investments in sustainable energy transitions

Energy Technology Data Exchange (ETDEWEB)

Blokhuis, Erik, E-mail: e.g.j.blokhuis@tue.nl [Eindhoven University of Technology, Department of Architecture, Building and Planning, Vertigo 8.11, P.O. Box 513, 5600MB Eindhoven (Netherlands); Brouwers, Bart [Eindhoven University of Technology, Department of Architecture, Building and Planning, Vertigo 8.11, P.O. Box 513, 5600MB Eindhoven (Netherlands); Putten, Eric van der [Endinet, Gas and Electricity Network Operations, P.O. Box 2005, 5600CA Eindhoven (Netherlands); Schaefer, Wim [Eindhoven University of Technology, Department of Architecture, Building and Planning, Vertigo 8.11, P.O. Box 513, 5600MB Eindhoven (Netherlands)

2011-10-15

Current energy distribution networks are often not equipped for facilitating expected sustainable transitions. Major concerns for future electricity networks are the possibility of peak load increases and the expected growth of decentralized energy generation. In this article, we focus on peak load increases; the effects of possible future developments on peak loads are studied, together with the consequences for the network. The city of Eindhoven (the Netherlands) is used as reference city, for which a scenario is developed in which the assumed future developments adversely influence the maximum peak loads on the network. In this scenario, the total electricity peak load in Eindhoven is expected to increase from 198 MVA in 2009 to 591-633 MVA in 2040. The necessary investments for facilitating the expected increased peak loads are estimated at 305-375 million Euros. Based upon these projections, it is advocated that - contrary to current Dutch policy - choices regarding sustainable transitions should be made from the viewpoint of integral energy systems, evaluating economic implications of changes to generation, grid development, and consumption. Recently applied and finished policies on energy demand reduction showed to be effective; however, additional and connecting policies on energy generation and distribution should be considered on short term. - Highlights: > Sustainable energy transitions can result in major electricity peak load increases. > Introduction of heat pumps and electrical vehicles requires network expansion. > Under worst case assumptions, peak loads in Eindhoven increase with 200% until 2040. > The necessary investment for facilitating this 2040 peak demand is Euro 305-375 million. > Future policy choices should be made from the viewpoint of the integral energy system.

Peak loads and network investments in sustainable energy transitions

International Nuclear Information System (INIS)

Blokhuis, Erik; Brouwers, Bart; Putten, Eric van der; Schaefer, Wim

2011-01-01

Current energy distribution networks are often not equipped for facilitating expected sustainable transitions. Major concerns for future electricity networks are the possibility of peak load increases and the expected growth of decentralized energy generation. In this article, we focus on peak load increases; the effects of possible future developments on peak loads are studied, together with the consequences for the network. The city of Eindhoven (the Netherlands) is used as reference city, for which a scenario is developed in which the assumed future developments adversely influence the maximum peak loads on the network. In this scenario, the total electricity peak load in Eindhoven is expected to increase from 198 MVA in 2009 to 591-633 MVA in 2040. The necessary investments for facilitating the expected increased peak loads are estimated at 305-375 million Euros. Based upon these projections, it is advocated that - contrary to current Dutch policy - choices regarding sustainable transitions should be made from the viewpoint of integral energy systems, evaluating economic implications of changes to generation, grid development, and consumption. Recently applied and finished policies on energy demand reduction showed to be effective; however, additional and connecting policies on energy generation and distribution should be considered on short term. - Highlights: → Sustainable energy transitions can result in major electricity peak load increases. → Introduction of heat pumps and electrical vehicles requires network expansion. → Under worst case assumptions, peak loads in Eindhoven increase with 200% until 2040. → The necessary investment for facilitating this 2040 peak demand is Euro 305-375 million. → Future policy choices should be made from the viewpoint of the integral energy system.

An adaptive clustering approach to dynamic load balancing and energy efficiency in wireless sensor networks

International Nuclear Information System (INIS)

Gherbi, Chirihane; Aliouat, Zibouda; Benmohammed, Mohamed

2016-01-01

Clustering is a well known approach to cope with large nodes density and efficiently conserving energy in Wireless Sensor Networks (WSN). Load balancing is an effective approach for optimizing resources like channel bandwidth, the main objective of this paper is to combine these two valuable approaches in order to significantly improve the main WSN service such as information routing. So, our proposal is a routing protocol in which load traffic is shared among cluster members in order to reduce the dropping probability due to queue overflow at some nodes. To this end, a novel hierarchical approach, called Hierarchical Energy-Balancing Multipath routing protocol for Wireless Sensor Networks (HEBM) is proposed. The HEBM approach aims to fulfill the following purposes: decreasing the overall network energy consumption, balancing the energy dissipation among the sensor nodes and as direct consequence: extending the lifetime of the network. In fact, the cluster-heads are optimally determined and suitably distributed over the area of interest allowing the member nodes reaching them with adequate energy dissipation and appropriate load balancing utilization. In addition, nodes radio are turned off for fixed time duration according to sleeping control rules optimizing so their energy consumption. The performance evaluation of the proposed protocol is carried out through the well-known NS2 simulator and the exhibited results are convincing. Like this, the residual energy of sensor nodes was measured every 20 s throughout the duration of simulation, in order to calculate the total number of alive nodes. Based on the simulation results, we concluded that our proposed HEBM protocol increases the profit of energy, and prolongs the network lifetime duration from 32% to 40% compared to DEEAC reference protocol and from 25% to 28% compared to FEMCHRP protocol. The authors also note that the proposed protocol is 41.7% better than DEEAC with respect to FND (Fist node die), and 25

Neural Network Algorithm for Particle Loading

International Nuclear Information System (INIS)

Lewandowski, J.L.V.

2003-01-01

An artificial neural network algorithm for continuous minimization is developed and applied to the case of numerical particle loading. It is shown that higher-order moments of the probability distribution function can be efficiently renormalized using this technique. A general neural network for the renormalization of an arbitrary number of moments is given

Dynamic Gust Load Analysis for Rotors

Directory of Open Access Journals (Sweden)

Yuting Dai

2016-01-01

Full Text Available Dynamic load of helicopter rotors due to gust directly affects the structural stress and flight performance for helicopters. Based on a large deflection beam theory, an aeroelastic model for isolated helicopter rotors in the time domain is constructed. The dynamic response and structural load for a rotor under the impulse gust and slope-shape gust are calculated, respectively. First, a nonlinear Euler beam model with 36 degrees-of-freedoms per element is applied to depict the structural dynamics for an isolated rotor. The generalized dynamic wake model and Leishman-Beddoes dynamic stall model are applied to calculate the nonlinear unsteady aerodynamic forces on rotors. Then, we transformed the differential aeroelastic governing equation to an algebraic one. Hence, the widely used Newton-Raphson iteration algorithm is employed to simulate the dynamic gust load. An isolated helicopter rotor with four blades is studied to validate the structural model and the aeroelastic model. The modal frequencies based on the Euler beam model agree well with published ones by CAMRAD. The flap deflection due to impulse gust with the speed of 2m/s increases twice to the one without gust. In this numerical example, results indicate that the bending moment at the blade root is alleviated due to elastic effect.

Dynamic QoS management in Differentiated Services using bandwidth brokers, RSVP aggregation and load control protocols

NARCIS (Netherlands)

Westberg, Lars; Eriksson, Anders; Karagiannis, Georgios; Heijenk, Geert; Rexhepi, Vlora; Partain, David

2001-01-01

A method and network subsystem for providing on demand end to end Quality of Service (Qos) in a dynamic manner, use a combination of Resource Reservation Protocol (RSVP), load control protocol (and its successors) and Bandwidth Brokers (BBs)(1106) which communicate using a predetermined protocol.

Dynamic QoS management in Differentiated Services using bandwidth brokers, RSVP aggregation and load control protocols

NARCIS (Netherlands)

Westberg, Lars; Eriksson, Anders; Karagiannis, Georgios; Heijenk, Geert; Rexhepi, Vlora; Partain, David

2009-01-01

A method and network subsystem for providing on demand end to end Quality of Service (Qos) in a dynamic manner, use a combination of Resource Reservation Protocol (RSVP), load control protocol (and its successors) and Bandwidth Brokers (BBs)(1106) which communicate using a predetermined protocol.

Modeling Networks and Dynamics in Complex Systems: from Nano-Composites to Opinion Formation

Science.gov (United States)

Shi, Feng

Complex networks are ubiquitous in systems of physical, biological, social or technological origin. Components in those systems range from as large as cities in power grids, to as small as molecules in metabolic networks. Since the dawn of network science, significant attention has focused on the implications of dynamics in establishing network structure and the impact of structural properties on dynamics on those networks. The first part of the thesis follows this direction, studying the network formed by conductive nanorods in nano-materials, and focuses on the electrical response of the composite to the structure change of the network. New scaling laws for the shear-induced anisotropic percolation are introduced and a robust exponential tail of the current distribution across the network is identified. These results are relevant especially to "active" composite materials where materials are exposed to mechanical loading and strain deformations. However, in many real-world networks the evolution of the network topology is tied to the states of the vertices and vice versa. Networks that exhibit such a feedback are called adaptive or coevolutionary networks. The second part of the thesis examines two closely related variants of a simple, abstract model for coevolution of a network and the opinions of its members. As a representative model for adaptive networks, it displays the feature of self-organization of the system into a stable configuration due to the interplay between the network topology and the dynamics on the network. This simple model yields interesting dynamics and the slight change in the rewiring strategy results in qualitatively different behaviors of the system. In conclusion, the dissertation aims to develop new network models and tools which enable insights into the structure and dynamics of various systems, and seeks to advance network algorithms which provide approaches to coherently articulated questions in real-world complex systems such as

Dynamic response analysis of an aircraft structure under thermal-acoustic loads

International Nuclear Information System (INIS)

Cheng, H; Li, H B; Zhang, W; Wu, Z Q; Liu, B R

2016-01-01

Future hypersonic aircraft will be exposed to extreme combined environments includes large magnitude thermal and acoustic loads. It presents a significant challenge for the integrity of these vehicles. Thermal-acoustic test is used to test structures for dynamic response and sonic fatigue due to combined loads. In this research, the numerical simulation process for the thermal acoustic test is presented, and the effects of thermal loads on vibro-acoustic response are investigated. To simulate the radiation heating system, Monte Carlo theory and thermal network theory was used to calculate the temperature distribution. Considering the thermal stress, the high temperature modal parameters are obtained with structural finite element methods. Based on acoustic finite element, modal-based vibro-acoustic analysis is carried out to compute structural responses. These researches are very vital to optimum thermal-acoustic test and structure designs for future hypersonic vehicles structure (paper)

In Situ Test Study of Characteristics of Coal Mining Dynamic Load

Directory of Open Access Journals (Sweden)

Jiang He

2015-01-01

Full Text Available Combination of coal mining dynamic load and high static stress can easily induce such dynamic disasters as rock burst, coal and gas outburst, roof fall, and water inrush. In order to obtain the characteristic parameters of mining dynamic load and dynamic mechanism of coal and rock, the stress wave theory is applied to derive the relation of mining dynamic load strain rate and stress wave parameters. The in situ test was applied to study the stress wave propagation law of coal mine dynamic load by using the SOS microseismic monitoring system. An evaluation method for mining dynamic load strain rate was proposed, and the statistical evaluation was carried out for the range of strain rate. The research results show that the loading strain rate of mining dynamic load is in direct proportion to the seismic frequency of coal-rock mass and particle peak vibration velocity and is in inverse proportion to wave velocity. The high-frequency component damps faster than the low-frequency component in the shockwave propagating process; and the peak particle vibration velocity has a power functional relationship with the transmitting distance. The loading strain rate of mining dynamic load is generally less than class 10−1/s.

Wavelet neural network load frequency controller

International Nuclear Information System (INIS)

Hemeida, Ashraf Mohamed

2005-01-01

This paper presents the feasibility of applying a wavelet neural network (WNN) approach for the load frequency controller (LFC) to damp the frequency oscillations of two area power systems due to load disturbances. The present intelligent control system trained the wavelet neural network (WNN) controller on line with adaptive learning rates, which are derived in the sense of a discrete type Lyapunov stability theorem. The present WNN controller is designed individually for each area. The proposed technique is applied successfully for a wide range of operating conditions. The time simulation results indicate its superiority and effectiveness over the conventional approach. The effects of consideration of the governor dead zone on the system performance are studied using the proposed controller and the conventional one

Load management in electrical networks. Objectives, methods, prospects

International Nuclear Information System (INIS)

Gabioud, D.

2008-01-01

This illustrated article takes up the problems related to the variation of the load in electricity networks. How to handle the peak load? Different solutions in the energy demand management are discussed. Method based on the price, method based on the reduction of the load by electric utilities. Information systems are presented which gives the consumer the needed data to participate in the local load management.

A network dynamics approach to chemical reaction networks

NARCIS (Netherlands)

van der Schaft, Abraham; Rao, S.; Jayawardhana, B.

2016-01-01

A treatment of chemical reaction network theory is given from the perspective of nonlinear network dynamics, in particular of consensus dynamics. By starting from the complex-balanced assumption the reaction dynamics governed by mass action kinetics can be rewritten into a form which allows for a

Dynamic-ETL: a hybrid approach for health data extraction, transformation and loading.

Science.gov (United States)

Ong, Toan C; Kahn, Michael G; Kwan, Bethany M; Yamashita, Traci; Brandt, Elias; Hosokawa, Patrick; Uhrich, Chris; Schilling, Lisa M

2017-09-13

Electronic health records (EHRs) contain detailed clinical data stored in proprietary formats with non-standard codes and structures. Participating in multi-site clinical research networks requires EHR data to be restructured and transformed into a common format and standard terminologies, and optimally linked to other data sources. The expertise and scalable solutions needed to transform data to conform to network requirements are beyond the scope of many health care organizations and there is a need for practical tools that lower the barriers of data contribution to clinical research networks. We designed and implemented a health data transformation and loading approach, which we refer to as Dynamic ETL (Extraction, Transformation and Loading) (D-ETL), that automates part of the process through use of scalable, reusable and customizable code, while retaining manual aspects of the process that requires knowledge of complex coding syntax. This approach provides the flexibility required for the ETL of heterogeneous data, variations in semantic expertise, and transparency of transformation logic that are essential to implement ETL conventions across clinical research sharing networks. Processing workflows are directed by the ETL specifications guideline, developed by ETL designers with extensive knowledge of the structure and semantics of health data (i.e., "health data domain experts") and target common data model. D-ETL was implemented to perform ETL operations that load data from various sources with different database schema structures into the Observational Medical Outcome Partnership (OMOP) common data model. The results showed that ETL rule composition methods and the D-ETL engine offer a scalable solution for health data transformation via automatic query generation to harmonize source datasets. D-ETL supports a flexible and transparent process to transform and load health data into a target data model. This approach offers a solution that lowers technical

Software defined network architecture based research on load balancing strategy

Science.gov (United States)

You, Xiaoqian; Wu, Yang

2018-05-01

As a new type network architecture, software defined network has the key idea of separating the control place of the network from the transmission plane, to manage and control the network in a concentrated way; in addition, the network interface is opened on the control layer and the data layer, so as to achieve programmable control of the network. Considering that only the single shortest route is taken into the calculation of traditional network data flow transmission, and congestion and resource consumption caused by excessive load of link circuits are ignored, a link circuit load based flow media business QoS gurantee system is proposed in this article to divide the flow in the network into ordinary data flow and QoS flow. In this way, it supervises the link circuit load with the controller so as to calculate reasonable route rapidly and issue the flow table to the exchanger, to finish rapid data transmission. In addition, it establishes a simulation platform to acquire optimized result through simulation experiment.

Entropy of dynamical social networks

Science.gov (United States)

Zhao, Kun; Karsai, Marton; Bianconi, Ginestra

2012-02-01

Dynamical social networks are evolving rapidly and are highly adaptive. Characterizing the information encoded in social networks is essential to gain insight into the structure, evolution, adaptability and dynamics. Recently entropy measures have been used to quantify the information in email correspondence, static networks and mobility patterns. Nevertheless, we still lack methods to quantify the information encoded in time-varying dynamical social networks. In this talk we present a model to quantify the entropy of dynamical social networks and use this model to analyze the data of phone-call communication. We show evidence that the entropy of the phone-call interaction network changes according to circadian rhythms. Moreover we show that social networks are extremely adaptive and are modified by the use of technologies such as mobile phone communication. Indeed the statistics of duration of phone-call is described by a Weibull distribution and is significantly different from the distribution of duration of face-to-face interactions in a conference. Finally we investigate how much the entropy of dynamical social networks changes in realistic models of phone-call or face-to face interactions characterizing in this way different type human social behavior.

Overload cascading failure on complex networks with heterogeneous load redistribution

Science.gov (United States)

Hou, Yueyi; Xing, Xiaoyun; Li, Menghui; Zeng, An; Wang, Yougui

2017-09-01

Many real systems including the Internet, power-grid and financial networks experience rare but large overload cascading failures triggered by small initial shocks. Many models on complex networks have been developed to investigate this phenomenon. Most of these models are based on the load redistribution process and assume that the load on a failed node shifts to nearby nodes in the networks either evenly or according to the load distribution rule before the cascade. Inspired by the fact that real power-grid tends to place the excess load on the nodes with high remaining capacities, we study a heterogeneous load redistribution mechanism in a simplified sandpile model in this paper. We find that weak heterogeneity in load redistribution can effectively mitigate the cascade while strong heterogeneity in load redistribution may even enlarge the size of the final failure. With a parameter θ to control the degree of the redistribution heterogeneity, we identify a rather robust optimal θ∗ = 1. Finally, we find that θ∗ tends to shift to a larger value if the initial sand distribution is homogeneous.

Evaluation of dynamic loads induced by transient regimes of fluid flows in the pipe systems and devices of reducing the loads and their effects

International Nuclear Information System (INIS)

Serban, Viorel; Chirita, Alexandru Mihai; Androne, Marian; Alexandru, Constantin; Ciuca, Camelia; Badara, Janina; Alexandru, Carmen

1995-01-01

The paper presents the analytic methods for estimating the dynamic effects induced in pipe systems in transient regimes. They are based on computation programs developed in order to check the behaviour of ECCS and EWS under 'water hammer effect' and the behaviour of the primary circuit system under stresses caused by pipe cracks. Computation examples are presented in order to emphasize the capabilities of the programs to model transient phenomena in complex pipe networks. The overpressure induced by the water hammer effect, as revealed by comparing several transient regimes, depends on the fluid viscosity, the initial speed, the duration of starting the transient regime, the system rigidity, etc. Values several ten times higher that the initial one could be thus reached. An overview of new types of devices designed for damping the effect of water hammer phenomenon, as well as of sustaining supports for pipe systems and equipment able to damp the vibrations produced by the transient regimes of fluid flows and seismic movements is presented. These devices have also to cope with the high shocks produced by pipe breakage as well as high static loads. The paper contains the following sections: 1. Introduction; 2. Evaluating dynamic loads associated to the water hammer phenomenon; 3. Determining loads associated to the water hammer phenomenon for the ECC system of the Cernavoda NPP Unit 1; 4. Device for reducing the water hammer effects; 5. Evaluating dynamic loads associated to pipe cracks; 6. Determining loads associated to pipe cracks in the Cernavoda NPP primary circuit; 7. Devices for absorbing and damping the dynamic loads in pipe systems and equipment; 8. Conclusions. (authors)

Artificial Neural Networks for SCADA Data based Load Reconstruction (poster)

NARCIS (Netherlands)

Hofemann, C.; Van Bussel, G.J.W.; Veldkamp, H.

2011-01-01

If at least one reference wind turbine is available, which provides sufficient information about the wind turbine loads, the loads acting on the neighbouring wind turbines can be predicted via an artificial neural network (ANN). This research explores the possibilities to apply such a network not

Optimizing the Quality of Dynamic Context Subscriptions for Scarce Network Resources

DEFF Research Database (Denmark)

Shawky, Ahmed; Olsen, Rasmus Løvenstein; Pedersen, Jens Myrup

2012-01-01

Scalable access to dynamic context information is a key challenge for future context-sensitive systems. When increasing the access frequency, the information accuracy can improve but at the same time the additional context management traffic may reduce network performance, which creates...... the opposite effect on information reliability. In order to understand and control this trade-off, this paper develops a model that allows to calculate context reliability, captured by the so-called mismatch probability, in relation to the network load. The model is subsequently used for a real time algorithm...

REDISTRIBUTION OF BASE STATIONS LOAD IN MOBILE COMMUNICATION NETWORKS

Directory of Open Access Journals (Sweden)

Igor Ruban

2017-09-01

Full Text Available The subject matter of the article is the processes of load distribution in mobile communication networks. The object of research is the handover. The goal is to develop a method for redistributing the load between neighboring areas for mobile nodes. The considered base stations are supposed to have the signal-to-noise ratios that are equal or close. The methods that are used: methods of system analysis, methods of digital signal processing. The following results are obtained. The method that allows mobile nodes, whose signal-to-noise ratios are equal or close, to switch to a less loaded base station. This method allows the base station to launch the handover process enabling more even distribution of the load from mobile nodes among neighboring base stations in wireless and mobile networks. In the suggested modification of the method, the function assessing the bandwidth of the uplink channel is added to the base stations, as well a threshold value for using its bandwidth. Thus, when the current value of bandwidth reaches the threshold, the base station starts sending out a message to all mobile nodes and verifies free neighboring areas for switching over mobile nodes. If there are adjacent areas with a lower load, the base station notifies all potential candidates about the necessity of their switching over. The handover process is launched when the available bandwidth of the base station decreases below a certain threshold. Therefore, it is possible to optimize the operation of the WiMAX network with respect to the criterion of the total bandwidth capacity of the base stations. Besides, the results of the comparative analysis of the handover process in networks based on the WiMAX technology that are obtained using the OpNet simulation environment are presented. Conclusions.The suggested approach can be used to improve the basic software of mobile communication networks. When moving a node from one area to another one in access servers, the

Dynamic loads on the primary system

International Nuclear Information System (INIS)

Rohde, J.

1980-01-01

As a result of pipe breaks f.ex. in the primary system of a PWR-plant dynamic forces act on the components of the system as well as on their support-structures and internals. The design basis must guarantee that LOCA or system-transient generated loads cannot produce deformations or fractures that endanger the coolability of the reactor, the emergency feedwater supply to the core-region and a safe shut-down of the reactor. In this lecture the first part of a LOCA will be discussed, where the highest dynamic loads on the primary system are expected. In this connection comments are given on the main assumptions and boundary conditions, the related regulations and guide-lines, as well as the possible consequences of an accident. Next, a review is presented of the analytical methods being used for the determination of thermohydraulic generated loads. The stress-calculations on the basis of these load-functions are discussed in the following lectures. The application of the analytical methods, i.e. the different computer codes, and the verification on the basis of the experimental results are described together with a discussion of the theoretical results. In addition a survey will be given of the research work done in connection with the problems of the dynamic loads under accident conditions. Finally, the problems of the fluid-structure interaction will be explained and comments made on computer code development now under way regarding this problem. A short film will be presented to provide a better understanding of fast transient phenomena. (orig./RW)

Dynamic behavior of the interaction between epidemics and cascades on heterogeneous networks

Science.gov (United States)

Jiang, Lurong; Jin, Xinyu; Xia, Yongxiang; Ouyang, Bo; Wu, Duanpo

2014-12-01

Epidemic spreading and cascading failure are two important dynamical processes on complex networks. They have been investigated separately for a long time. But in the real world, these two dynamics sometimes may interact with each other. In this paper, we explore a model combined with the SIR epidemic spreading model and a local load sharing cascading failure model. There exists a critical value of the tolerance parameter for which the epidemic with high infection probability can spread out and infect a fraction of the network in this model. When the tolerance parameter is smaller than the critical value, the cascading failure cuts off the abundance of paths and blocks the spreading of the epidemic locally. While the tolerance parameter is larger than the critical value, the epidemic spreads out and infects a fraction of the network. A method for estimating the critical value is proposed. In simulations, we verify the effectiveness of this method in the uncorrelated configuration model (UCM) scale-free networks.

Portable Parallel Programming for the Dynamic Load Balancing of Unstructured Grid Applications

Science.gov (United States)

Biswas, Rupak; Das, Sajal K.; Harvey, Daniel; Oliker, Leonid

1999-01-01

The ability to dynamically adapt an unstructured -rid (or mesh) is a powerful tool for solving computational problems with evolving physical features; however, an efficient parallel implementation is rather difficult, particularly from the view point of portability on various multiprocessor platforms We address this problem by developing PLUM, tin automatic anti architecture-independent framework for adaptive numerical computations in a message-passing environment. Portability is demonstrated by comparing performance on an SP2, an Origin2000, and a T3E, without any code modifications. We also present a general-purpose load balancer that utilizes symmetric broadcast networks (SBN) as the underlying communication pattern, with a goal to providing a global view of system loads across processors. Experiments on, an SP2 and an Origin2000 demonstrate the portability of our approach which achieves superb load balance at the cost of minimal extra overhead.

Reduction of Dynamic Loads in Mine Lifting Installations

Science.gov (United States)

Kuznetsov, N. K.; Eliseev, S. V.; Perelygina, A. Yu

2018-01-01

Article is devoted to a problem of decrease in the dynamic loadings arising in transitional operating modes of the mine lifting installations leading to heavy oscillating motions of lifting vessels and decrease in efficiency and reliability of work. The known methods and means of decrease in dynamic loadings and oscillating motions of the similar equipment are analysed. It is shown that an approach based on the concept of the inverse problems of dynamics can be effective method of the solution of this problem. The article describes the design model of a one-ended lifting installation in the form of a two-mass oscillation system, in which the inertial elements are the mass of the lifting vessel and the reduced mass of the engine, reducer, drum and pulley. The simplified mathematical model of this system and results of an efficiency research of an active way of reduction of dynamic loadings of lifting installation on the basis of the concept of the inverse problems of dynamics are given.

Radial basis function neural network for power system load-flow

International Nuclear Information System (INIS)

Karami, A.; Mohammadi, M.S.

2008-01-01

This paper presents a method for solving the load-flow problem of the electric power systems using radial basis function (RBF) neural network with a fast hybrid training method. The main idea is that some operating conditions (values) are needed to solve the set of non-linear algebraic equations of load-flow by employing an iterative numerical technique. Therefore, we may view the outputs of a load-flow program as functions of the operating conditions. Indeed, we are faced with a function approximation problem and this can be done by an RBF neural network. The proposed approach has been successfully applied to the 10-machine and 39-bus New England test system. In addition, this method has been compared with that of a multi-layer perceptron (MLP) neural network model. The simulation results show that the RBF neural network is a simpler method to implement and requires less training time to converge than the MLP neural network. (author)

Sparse dynamical Boltzmann machine for reconstructing complex networks with binary dynamics

Science.gov (United States)

Chen, Yu-Zhong; Lai, Ying-Cheng

2018-03-01

Revealing the structure and dynamics of complex networked systems from observed data is a problem of current interest. Is it possible to develop a completely data-driven framework to decipher the network structure and different types of dynamical processes on complex networks? We develop a model named sparse dynamical Boltzmann machine (SDBM) as a structural estimator for complex networks that host binary dynamical processes. The SDBM attains its topology according to that of the original system and is capable of simulating the original binary dynamical process. We develop a fully automated method based on compressive sensing and a clustering algorithm to construct the SDBM. We demonstrate, for a variety of representative dynamical processes on model and real world complex networks, that the equivalent SDBM can recover the network structure of the original system and simulates its dynamical behavior with high precision.

Dynamic sink assignment for efficient energy consumption in wireless sensor networks

KAUST Repository

Oikonomou, Konstantinos N.

2012-04-01

Efficient energy consumption is a challenging problem in wireless sensor networks (WSNs) and closely related to extending network lifetime. The usual way of tackling this issue for topologies with fixed link weight and fixed sink location, has been shown to be severely affected by the energy hole problem. In this paper, the energy consumption problem is initially studied for WSNs with fixed sink assignment and it is analytically shown that energy consumption is minimized when the sink is assigned to the node that is the solution of a suitably formulated 1-median problem. This motivates the introduction of a dynamic environment where link weights change based on the energy level and the aggregate traffic load of the adjacent nodes. Then, the sink is adaptively allowed to move among neighbor nodes, according to a scalable sink migration strategy. Simulation results support the analytical claims demonstrating energy consumption reduction and an additional network lifetime increment when migration is employed in the dynamic environment. © 2012 IEEE.

A network dynamics approach to chemical reaction networks

Science.gov (United States)

van der Schaft, A. J.; Rao, S.; Jayawardhana, B.

2016-04-01

A treatment of a chemical reaction network theory is given from the perspective of nonlinear network dynamics, in particular of consensus dynamics. By starting from the complex-balanced assumption, the reaction dynamics governed by mass action kinetics can be rewritten into a form which allows for a very simple derivation of a number of key results in the chemical reaction network theory, and which directly relates to the thermodynamics and port-Hamiltonian formulation of the system. Central in this formulation is the definition of a balanced Laplacian matrix on the graph of chemical complexes together with a resulting fundamental inequality. This immediately leads to the characterisation of the set of equilibria and their stability. Furthermore, the assumption of complex balancedness is revisited from the point of view of Kirchhoff's matrix tree theorem. Both the form of the dynamics and the deduced behaviour are very similar to consensus dynamics, and provide additional perspectives to the latter. Finally, using the classical idea of extending the graph of chemical complexes by a 'zero' complex, a complete steady-state stability analysis of mass action kinetics reaction networks with constant inflows and mass action kinetics outflows is given, and a unified framework is provided for structure-preserving model reduction of this important class of open reaction networks.

Inferring network topology from complex dynamics

International Nuclear Information System (INIS)

Shandilya, Srinivas Gorur; Timme, Marc

2011-01-01

Inferring the network topology from dynamical observations is a fundamental problem pervading research on complex systems. Here, we present a simple, direct method for inferring the structural connection topology of a network, given an observation of one collective dynamical trajectory. The general theoretical framework is applicable to arbitrary network dynamical systems described by ordinary differential equations. No interference (external driving) is required and the type of dynamics is hardly restricted in any way. In particular, the observed dynamics may be arbitrarily complex; stationary, invariant or transient; synchronous or asynchronous and chaotic or periodic. Presupposing a knowledge of the functional form of the dynamical units and of the coupling functions between them, we present an analytical solution to the inverse problem of finding the network topology from observing a time series of state variables only. Robust reconstruction is achieved in any sufficiently long generic observation of the system. We extend our method to simultaneously reconstructing both the entire network topology and all parameters appearing linear in the system's equations of motion. Reconstruction of network topology and system parameters is viable even in the presence of external noise that distorts the original dynamics substantially. The method provides a conceptually new step towards reconstructing a variety of real-world networks, including gene and protein interaction networks and neuronal circuits.

Rapidly exploring structural and dynamic properties of signaling networks using PathwayOracle

Directory of Open Access Journals (Sweden)

Ram Prahlad T

2008-08-01

Full Text Available Abstract Background In systems biology the experimentalist is presented with a selection of software for analyzing dynamic properties of signaling networks. These tools either assume that the network is in steady-state or require highly parameterized models of the network of interest. For biologists interested in assessing how signal propagates through a network under specific conditions, the first class of methods does not provide sufficiently detailed results and the second class requires models which may not be easily and accurately constructed. A tool that is able to characterize the dynamics of a signaling network using an unparameterized model of the network would allow biologists to quickly obtain insights into a signaling network's behavior. Results We introduce PathwayOracle, an integrated suite of software tools for computationally inferring and analyzing structural and dynamic properties of a signaling network. The feature which differentiates PathwayOracle from other tools is a method that can predict the response of a signaling network to various experimental conditions and stimuli using only the connectivity of the signaling network. Thus signaling models are relatively easy to build. The method allows for tracking signal flow in a network and comparison of signal flows under different experimental conditions. In addition, PathwayOracle includes tools for the enumeration and visualization of coherent and incoherent signaling paths between proteins, and for experimental analysis – loading and superimposing experimental data, such as microarray intensities, on the network model. Conclusion PathwayOracle provides an integrated environment in which both structural and dynamic analysis of a signaling network can be quickly conducted and visualized along side experimental results. By using the signaling network connectivity, analyses and predictions can be performed quickly using relatively easily constructed signaling network models

Dynamic Load Balancing of Parallel Monte Carlo Transport Calculations

International Nuclear Information System (INIS)

O'Brien, M; Taylor, J; Procassini, R

2004-01-01

The performance of parallel Monte Carlo transport calculations which use both spatial and particle parallelism is increased by dynamically assigning processors to the most worked domains. Since the particle work load varies over the course of the simulation, this algorithm determines each cycle if dynamic load balancing would speed up the calculation. If load balancing is required, a small number of particle communications are initiated in order to achieve load balance. This method has decreased the parallel run time by more than a factor of three for certain criticality calculations

LAMAN: Load Adaptable MAC for Ad Hoc Networks

Directory of Open Access Journals (Sweden)

Realp Marc

2005-01-01

Full Text Available In mobile ad hoc radio networks, mechanisms on how to access the radio channel are extremely important in order to improve network efficiency. In this paper, the load adaptable medium access control for ad hoc networks (LAMAN protocol is described. LAMAN is a novel decentralized multipacket MAC protocol designed following a cross-layer approach. Basically, this protocol is a hybrid CDMA-TDMA-based protocol that aims at throughput maximization in multipacket communication environments by efficiently combining contention and conflict-free protocol components. Such combination of components is used to adapt the nodes' access priority to changes on the traffic load while, at the same time, accounting for the multipacket reception (MPR capability of the receivers. A theoretical analysis of the system is developed presenting closed expressions of network throughput and packet delay. By simulations the validity of our analysis is shown and the performances of a LAMAN-based system and an Aloha-CDMA-based one are compared.

Tourism-planning network knowledge dynamics

DEFF Research Database (Denmark)

Dredge, Dianne

2014-01-01

This chapter explores the characteristics and functions of tourism networks as a first step in understanding how networks facilitate and reproduce knowledge. A framework to progress understandings of knowledge dynamics in tourism networks is presented that includes four key dimensions: context......, network agents, network boundaries and network resources. A case study of the development of the Next Generation Tourism Handbook (Queensland, Australia), a policy initiative that sought to bring tourism and land use planning knowledge closer together is presented. The case study illustrates...... that the tourism policy and land use planning networks operate in very different spheres and that context, network agents, network boundaries and network resources have a significant influence not only on knowledge dynamics but also on the capacity of network agents to overcome barriers to learning and to innovate....

Purinergic responses of chondrogenic stem cells to dynamic loading

Directory of Open Access Journals (Sweden)

Gađanski Ivana

2013-01-01

Full Text Available In habitually loaded tissues, dynamic loading can trigger ATP (adenosine 5’- triphosphate release to extracellular environment, and result in calcium signaling via ATP binding to purine P2 receptors1. In the current study we have compared purinergic responses (ATP release of two types of cells: bovine chondrocytes (bCHs and human mesenchymal stem cells (hMSC that were encapsulated in agarose and subjected to dynamic loading. Both cell types were cultured under chondrogenic conditions, and their responses to loading were evaluated by ATP release assay in combination with connexin (Cx-sensitive fluorescent dye (Lucifer Yellow - LY and a Cx-hemichannel blocker (Flufenamic acid - FFA. In response to dynamic loading, chondrogenic hMSCs released significantly higher amounts of ATP (5-fold in comparison to the bCHs early in culture (day 2. Triggering of LY uptake in the bCHs and hMSCs by dynamic loading implies opening of the Cx-hemichannels. However, the number of LY-positive cells in hMSC-constructs was 2.5-fold lower compared to the loaded bCH-constructs, suggesting utilization of additional mechanisms of ATP release. Cx-reactive sites were detected in both bCHs and hMSCs-constructs. FFA application led to reduced ATP release both in bCHs and hMSCs, which confirms the involvement of connexin hemichannels, with more prominent effects in bCHs than in hMSCs, further implying the existence of additional mechanism of ATP release in chondrogenic hMSCs. Taken together, these results indicate stronger purinergic response to dynamic loading of chondrogenic hMSCs than primary chondrocytes, by activation of connexin hemichannels and additional mechanisms of ATP release. [Projekat Ministrastva nauke Republike Srbije, ON174028 i br. III41007

Dynamic queuing transmission model for dynamic network loading

DEFF Research Database (Denmark)

Raovic, Nevena; Nielsen, Otto Anker; Prato, Carlo Giacomo

2017-01-01

and allowing for the representation of multiple vehicle classes, queue spillbacks and shock waves. The model assumes that a link is split into a moving part plus a queuing part, and p that traffic dynamics are given by a triangular fundamental diagram. A case-study is investigated and the DQTM is compared...

Quantitative analysis of impact measurements using dynamic load cells

Directory of Open Access Journals (Sweden)

Brent J. Maranzano

2016-03-01

Full Text Available A mathematical model is used to estimate material properties from a short duration transient impact force measured by dropping spheres onto rectangular coupons fixed to a dynamic load cell. The contact stress between the dynamic load cell surface and the projectile are modeled using Hertzian contact mechanics. Due to the short impact time relative to the load cell dynamics, an additional Kelvin–Voigt element is included in the model to account for the finite response time of the piezoelectric crystal. Calculations with and without the Kelvin–Voigt element are compared to experimental data collected from combinations of polymeric spheres and polymeric and metallic surfaces. The results illustrate that the inclusion of the Kelvin–Voigt element qualitatively captures the post impact resonance and non-linear behavior of the load cell signal and quantitatively improves the estimation of the Young's elastic modulus and Poisson's ratio. Mathematically, the additional KV element couples one additional differential equation to the Hertzian spring-dashpot equation. The model can be numerically integrated in seconds using standard numerical techniques allowing for its use as a rapid technique for the estimation of material properties. Keywords: Young's modulus, Poisson's ratio, Dynamic load cell

Conflict and convention in dynamic networks.

Science.gov (United States)

Foley, Michael; Forber, Patrick; Smead, Rory; Riedl, Christoph

2018-03-01

An important way to resolve games of conflict (snowdrift, hawk-dove, chicken) involves adopting a convention: a correlated equilibrium that avoids any conflict between aggressive strategies. Dynamic networks allow individuals to resolve conflict via their network connections rather than changing their strategy. Exploring how behavioural strategies coevolve with social networks reveals new dynamics that can help explain the origins and robustness of conventions. Here, we model the emergence of conventions as correlated equilibria in dynamic networks. Our results show that networks have the tendency to break the symmetry between the two conventional solutions in a strongly biased way. Rather than the correlated equilibrium associated with ownership norms (play aggressive at home, not away), we usually see the opposite host-guest norm (play aggressive away, not at home) evolve on dynamic networks, a phenomenon common to human interaction. We also show that learning to avoid conflict can produce realistic network structures in a way different than preferential attachment models. © 2017 The Author(s).

Dynamic strength of rock with single planar joint under various loading rates at various angles of loads applied

Directory of Open Access Journals (Sweden)

Pei-Yun Shu

2018-06-01

Full Text Available Intact rock-like specimens and specimens that include a single, smooth planar joint at various angles are prepared for split Hopkinson pressure bar (SHPB testing. A buffer pad between the striker bar and the incident bar of an SHPB apparatus is used to absorb some of the shock energy. This can generate loading rates of 20.2–4627.3 GPa/s, enabling dynamic peak stresses/strengths and associated failure patterns of the specimens to be investigated. The effects of the loading rate and angle of load applied on the dynamic peak stresses/strengths of the specimens are examined. Relevant experimental results demonstrate that the failure pattern of each specimen can be classified as four types: Type A, integrated with or without tiny flake-off; Type B, slide failure; Type C, fracture failure; and Type D, crushing failure. The dynamic peak stresses/strengths of the specimens that have similar failure patterns increase linearly with the loading rate, yielding high correlations that are evident on semi-logarithmic plots. The slope of the failure envelope is the smallest for slide failure, followed by crushing failure, and that of fracture failure is the largest. The magnitude of the plot slope of the dynamic peak stress against the loading rate for the specimens that are still integrated after testing is between that of slide failure and crushing failure. The angle of application has a limited effect on the dynamic peak stresses/strengths of the specimens regardless of the failure pattern, but it affects the bounds of the loading rates that yield each failure pattern, and thus influences the dynamic responses of the single jointed specimen. Slide failure occurs at the lowest loading rate of any failure, but can only occur in single jointed specimen that allows sliding. Crushing failure is typically associated with the largest loading rate, and fracture failure may occur when the loading rate is between the boundaries for slide failure and crushing

Activating and inhibiting connections in biological network dynamics

Directory of Open Access Journals (Sweden)

Knight Rob

2008-12-01

Full Text Available Abstract Background Many studies of biochemical networks have analyzed network topology. Such work has suggested that specific types of network wiring may increase network robustness and therefore confer a selective advantage. However, knowledge of network topology does not allow one to predict network dynamical behavior – for example, whether deleting a protein from a signaling network would maintain the network's dynamical behavior, or induce oscillations or chaos. Results Here we report that the balance between activating and inhibiting connections is important in determining whether network dynamics reach steady state or oscillate. We use a simple dynamical model of a network of interacting genes or proteins. Using the model, we study random networks, networks selected for robust dynamics, and examples of biological network topologies. The fraction of activating connections influences whether the network dynamics reach steady state or oscillate. Conclusion The activating fraction may predispose a network to oscillate or reach steady state, and neutral evolution or selection of this parameter may affect the behavior of biological networks. This principle may unify the dynamics of a wide range of cellular networks. Reviewers Reviewed by Sergei Maslov, Eugene Koonin, and Yu (Brandon Xia (nominated by Mark Gerstein. For the full reviews, please go to the Reviewers' comments section.

Asynchronous networks: modularization of dynamics theorem

Science.gov (United States)

Bick, Christian; Field, Michael

2017-02-01

Building on the first part of this paper, we develop the theory of functional asynchronous networks. We show that a large class of functional asynchronous networks can be (uniquely) represented as feedforward networks connecting events or dynamical modules. For these networks we can give a complete description of the network function in terms of the function of the events comprising the network: the modularization of dynamics theorem. We give examples to illustrate the main results.

Periodic dynamics in queuing networks

Energy Technology Data Exchange (ETDEWEB)

Addabbo, Tommaso [Information Engineering Department, University of Siena, Via Roma 56, 53100 Siena (Italy)], E-mail: addabbo@dii.unisi.it; Kocarev, Ljupco [Macedonian Academy of Sciences and Arts, bul. Krste Misirkov 2, P.O. Box 428, 1000 Skopje, Republic of Macedonia (Macedonia, The Former Yugoslav Republic of)], E-mail: lkocarev@ucsd.edu

2009-08-30

This paper deals with state-dependent open Markovian (or exponential) queuing networks, for which arrival and service rates, as well as routing probabilities, may depend on the queue lengths. For a network of this kind, following Mandelbaum and Pats, we provide a formal definition of its associated fluid model, and we focus on the relationships which may occur between the network stochastic dynamics and the deterministic dynamics of its corresponding fluid model, particularly focusing on queuing networks whose fluid models have global periodic attractors.

Psychology and social networks: a dynamic network theory perspective.

Science.gov (United States)

Westaby, James D; Pfaff, Danielle L; Redding, Nicholas

2014-04-01

Research on social networks has grown exponentially in recent years. However, despite its relevance, the field of psychology has been relatively slow to explain the underlying goal pursuit and resistance processes influencing social networks in the first place. In this vein, this article aims to demonstrate how a dynamic network theory perspective explains the way in which social networks influence these processes and related outcomes, such as goal achievement, performance, learning, and emotional contagion at the interpersonal level of analysis. The theory integrates goal pursuit, motivation, and conflict conceptualizations from psychology with social network concepts from sociology and organizational science to provide a taxonomy of social network role behaviors, such as goal striving, system supporting, goal preventing, system negating, and observing. This theoretical perspective provides psychologists with new tools to map social networks (e.g., dynamic network charts), which can help inform the development of change interventions. Implications for social, industrial-organizational, and counseling psychology as well as conflict resolution are discussed, and new opportunities for research are highlighted, such as those related to dynamic network intelligence (also known as cognitive accuracy), levels of analysis, methodological/ethical issues, and the need to theoretically broaden the study of social networking and social media behavior. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Impact evaluation of conducted UWB transients on loads in power-line networks

Science.gov (United States)

Li, Bing; Månsson, Daniel

2017-09-01

Nowadays, faced with the ever-increasing dependence on diverse electronic devices and systems, the proliferation of potential electromagnetic interference (EMI) becomes a critical threat for reliable operation. A typical issue is the electronics working reliably in power-line networks when exposed to electromagnetic environment. In this paper, we consider a conducted ultra-wideband (UWB) disturbance, as an example of intentional electromagnetic interference (IEMI) source, and perform the impact evaluation at the loads in a network. With the aid of fast Fourier transform (FFT), the UWB transient is characterized in the frequency domain. Based on a modified Baum-Liu-Tesche (BLT) method, the EMI received at the loads, with complex impedance, is computed. Through inverse FFT (IFFT), we obtain time-domain responses of the loads. To evaluate the impact on loads, we employ five common, but important quantifiers, i.e., time-domain peak, total signal energy, peak signal power, peak time rate of change and peak time integral of the pulse. Moreover, to perform a comprehensive analysis, we also investigate the effects of the attributes (capacitive, resistive, or inductive) of other loads connected to the network, the rise time and pulse width of the UWB transient, and the lengths of power lines. It is seen that, for the loads distributed in a network, the impact evaluation of IEMI should be based on the characteristics of the IEMI source, and the network features, such as load impedances, layout, and characteristics of cables.

Three-Phase Unbalanced Load Flow Tool for Distribution Networks

DEFF Research Database (Denmark)

Demirok, Erhan; Kjær, Søren Bækhøj; Sera, Dezso

2012-01-01

This work develops a three-phase unbalanced load flow tool tailored for radial distribution networks based on Matlab®. The tool can be used to assess steady-state voltage variations, thermal limits of grid components and power losses in radial MV-LV networks with photovoltaic (PV) generators where...... most of the systems are single phase. New ancillary service such as static reactive power support by PV inverters can be also merged together with the load flow solution tool and thus, the impact of the various reactive power control strategies on the steady-state grid operation can be simply...... investigated. Performance of the load flow solution tool in the sense of resulting bus voltage magnitudes is compared and validated with IEEE 13-bus test feeder....

Revealing networks from dynamics: an introduction

International Nuclear Information System (INIS)

Timme, Marc; Casadiego, Jose

2014-01-01

What can we learn from the collective dynamics of a complex network about its interaction topology? Taking the perspective from nonlinear dynamics, we briefly review recent progress on how to infer structural connectivity (direct interactions) from accessing the dynamics of the units. Potential applications range from interaction networks in physics, to chemical and metabolic reactions, protein and gene regulatory networks as well as neural circuits in biology and electric power grids or wireless sensor networks in engineering. Moreover, we briefly mention some standard ways of inferring effective or functional connectivity. (topical review)

Dynamic and interacting complex networks

Science.gov (United States)

Dickison, Mark E.

This thesis employs methods of statistical mechanics and numerical simulations to study some aspects of dynamic and interacting complex networks. The mapping of various social and physical phenomena to complex networks has been a rich field in the past few decades. Subjects as broad as petroleum engineering, scientific collaborations, and the structure of the internet have all been analyzed in a network physics context, with useful and universal results. In the first chapter we introduce basic concepts in networks, including the two types of network configurations that are studied and the statistical physics and epidemiological models that form the framework of the network research, as well as covering various previously-derived results in network theory that are used in the work in the following chapters. In the second chapter we introduce a model for dynamic networks, where the links or the strengths of the links change over time. We solve the model by mapping dynamic networks to the problem of directed percolation, where the direction corresponds to the time evolution of the network. We show that the dynamic network undergoes a percolation phase transition at a critical concentration pc, that decreases with the rate r at which the network links are changed. The behavior near criticality is universal and independent of r. We find that for dynamic random networks fundamental laws are changed: i) The size of the giant component at criticality scales with the network size N for all values of r, rather than as N2/3 in static network, ii) In the presence of a broad distribution of disorder, the optimal path length between two nodes in a dynamic network scales as N1/2, compared to N1/3 in a static network. The third chapter consists of a study of the effect of quarantine on the propagation of epidemics on an adaptive network of social contacts. For this purpose, we analyze the susceptible-infected-recovered model in the presence of quarantine, where susceptible

Dynamically-Loaded Hardware Libraries (HLL) Technology for Audio Applications

DEFF Research Database (Denmark)

Esposito, A.; Lomuscio, A.; Nunzio, L. Di

2016-01-01

In this work, we apply hardware acceleration to embedded systems running audio applications. We present a new framework, Dynamically-Loaded Hardware Libraries or HLL, to dynamically load hardware libraries on reconfigurable platforms (FPGAs). Provided a library of application-specific processors......, we load on-the-fly the specific processor in the FPGA, and we transfer the execution from the CPU to the FPGA-based accelerator. The proposed architecture provides excellent flexibility with respect to the different audio applications implemented, high quality audio, and an energy efficient solution....

Dynamic response of infrastructure to environmentally induced loads analysis, measurements, testing, and design

CERN Document Server

Manolis, George

2017-01-01

This book provides state of the art coverage of important current issues in the analysis, measurement, and monitoring of the dynamic response of infrastructure to environmental loads, including those induced by earthquake motion and differential soil settlement. The coverage is in five parts that address numerical methods in structural dynamics, soil–structure interaction analysis, instrumentation and structural health monitoring, hybrid experimental mechanics, and structural health monitoring for bridges. Examples that give an impression of the scope of the topics discussed include the seismic analysis of bridges, soft computing in earthquake engineering, use of hybrid methods for soil–structure interaction analysis, effects of local site conditions on the inelastic dynamic analysis of bridges, embedded models in wireless sensor networks for structural health monitoring, recent developments in seismic simulation methods, and seismic performance assessment and retrofit of structures. Throughout, the empha...

The dynamics of transmission and the dynamics of networks.

Science.gov (United States)

Farine, Damien

2017-05-01

A toy example depicted here highlighting the results of a study in this issue of the Journal of Animal Ecology that investigates the impact of network dynamics on potential disease outbreaks. Infections (stars) that spread by contact only (left) reduce the predicted outbreak size compared to situations where individuals can become infected by moving through areas that previously contained infected individuals (right). This is potentially important in species where individuals, or in this case groups, have overlapping ranges (as depicted on the top right). Incorporating network dynamics that maintain information about the ordering of contacts (central blocks; including the ordering of spatial overlap as noted by the arrows that highlight the blue group arriving after the red group in top-right of the figure) is important for capturing how a disease might not have the opportunity to spread to all individuals. By contrast, a static or 'average' network (lower blocks) does not capture any of these dynamics. Interestingly, although static networks generally predict larger outbreak sizes, the authors find that in cases when transmission probability is low, this prediction can switch as a result of changes in the estimated intensity of contacts among individuals. [Colour figure can be viewed at wileyonlinelibrary.com]. Springer, A., Kappeler, P.M. & Nunn, C.L. (2017) Dynamic vs. static social networks in models of parasite transmission: Predicting Cryptosporidium spread in wild lemurs. Journal of Animal Ecology, 86, 419-433. The spread of disease or information through networks can be affected by several factors. Whether and how these factors are accounted for can fundamentally change the predicted impact of a spreading epidemic. Springer, Kappeler & Nunn () investigate the role of different modes of transmission and network dynamics on the predicted size of a disease outbreak across several groups of Verreaux's sifakas, a group-living species of lemur. While some factors

Application of high-resolution domestic electricity load profiles in network modelling

DEFF Research Database (Denmark)

Marszal, Anna Joanna; Mendaza, Iker Diaz de Cerio; Heiselberg, Per Kvols

2016-01-01

the generated profiles are inputted in a low-voltage network model created in DIgSILENT PowerFactory. By means of employing 1 hour based demand and generation profiles in during dynamic studies, the representation of the local power system performance might sometimes not be as accurate as needed. In the test...... with modeling when 1-minute domestic electricity demand and generation profiles are used as inputs. The analysis is done with a case study of low-voltage network located in Northern Denmark. The analysis includes two parts. The first part focuses on modeling the domestic demands and on-site generation in 1......-minute resolution. The load profiles of the household appliances are created using a bottom-up model, which uses the 1-minute cycle power use characteristics of a single appliance as the main building block. The profiles of heavy electric appliances, such as heat pump, are not included in the above...

Immune networks: multi-tasking capabilities at medium load

International Nuclear Information System (INIS)

Agliari, E; Annibale, A; Barra, A; Coolen, A C C; Tantari, D

2013-01-01

Associative network models featuring multi-tasking properties have been introduced recently and studied in the low-load regime, where the number P of simultaneously retrievable patterns scales with the number N of nodes as P ∼ log N. In addition to their relevance in artificial intelligence, these models are increasingly important in immunology, where stored patterns represent strategies to fight pathogens and nodes represent lymphocyte clones. They allow us to understand the crucial ability of the immune system to respond simultaneously to multiple distinct antigen invasions. Here we develop further the statistical mechanical analysis of such systems, by studying the medium-load regime, P ∼ N δ with δ ∈ (0, 1]. We derive three main results. First, we reveal the nontrivial architecture of these networks: they exhibit a high degree of modularity and clustering, which is linked to their retrieval abilities. Second, by solving the model we demonstrate for δ < 1 the existence of large regions in the phase diagram where the network can retrieve all stored patterns simultaneously. Finally, in the high-load regime δ = 1 we find that the system behaves as a spin-glass, suggesting that finite-connectivity frameworks are required to achieve effective retrieval. (paper)

Impact evaluation of conducted UWB transients on loads in power-line networks

Directory of Open Access Journals (Sweden)

B. Li

2017-09-01

Full Text Available Nowadays, faced with the ever-increasing dependence on diverse electronic devices and systems, the proliferation of potential electromagnetic interference (EMI becomes a critical threat for reliable operation. A typical issue is the electronics working reliably in power-line networks when exposed to electromagnetic environment. In this paper, we consider a conducted ultra-wideband (UWB disturbance, as an example of intentional electromagnetic interference (IEMI source, and perform the impact evaluation at the loads in a network. With the aid of fast Fourier transform (FFT, the UWB transient is characterized in the frequency domain. Based on a modified Baum–Liu–Tesche (BLT method, the EMI received at the loads, with complex impedance, is computed. Through inverse FFT (IFFT, we obtain time-domain responses of the loads. To evaluate the impact on loads, we employ five common, but important quantifiers, i.e., time-domain peak, total signal energy, peak signal power, peak time rate of change and peak time integral of the pulse. Moreover, to perform a comprehensive analysis, we also investigate the effects of the attributes (capacitive, resistive, or inductive of other loads connected to the network, the rise time and pulse width of the UWB transient, and the lengths of power lines. It is seen that, for the loads distributed in a network, the impact evaluation of IEMI should be based on the characteristics of the IEMI source, and the network features, such as load impedances, layout, and characteristics of cables.

Dynamics of High-Resolution Networks

DEFF Research Database (Denmark)

Sekara, Vedran

the unprecedented amounts of information collected by mobile phones to gain detailed insight into the dynamics of social systems. This dissertation presents an unparalleled data collection campaign, collecting highly detailed traces for approximately 1000 people over the course of multiple years. The availability...... are we all affected by an ever changing network structure? Answering these questions will enrich our understanding of ourselves, our organizations, and our societies. Yet, mapping the dynamics of social networks has traditionally been an arduous undertaking. Today, however, it is possible to use...... of such dynamic maps allows us to probe the underlying social network and understand how individuals interact and form lasting friendships. More importantly, these highly detailed dynamic maps provide us new perspectives at traditional problems and allow us to quantify and predict human life....

Failure mitigation in software defined networking employing load type prediction

KAUST Repository

Bouacida, Nader

2017-07-31

The controller is a critical piece of the SDN architecture, where it is considered as the mastermind of SDN networks. Thus, its failure will cause a significant portion of the network to fail. Overload is one of the common causes of failure since the controller is frequently invoked by new flows. Even through SDN controllers are often replicated, the significant recovery time can be an overkill for the availability of the entire network. In order to overcome the problem of the overloaded controller failure in SDN, this paper proposes a novel controller offload solution for failure mitigation based on a prediction module that anticipates the presence of a harmful long-term load. In fact, the long-standing load would eventually overwhelm the controller leading to a possible failure. To predict whether the load in the controller is short-term or long-term load, we used three different classification algorithms: Support Vector Machine, k-Nearest Neighbors, and Naive Bayes. Our evaluation results demonstrate that Support Vector Machine algorithm is applicable for detecting the type of load with an accuracy of 97.93% in a real-time scenario. Besides, our scheme succeeded to offload the controller by switching between the reactive and proactive mode in response to the prediction module output.

Predicting Dynamic Response of Structures under Earthquake Loads Using Logical Analysis of Data

Directory of Open Access Journals (Sweden)

Ayman Abd-Elhamed

2018-04-01

Full Text Available In this paper, logical analysis of data (LAD is used to predict the seismic response of building structures employing the captured dynamic responses. In order to prepare the data, computational simulations using a single degree of freedom (SDOF building model under different ground motion records are carried out. The selected excitation records are real and of different peak ground accelerations (PGA. The sensitivity of the seismic response in terms of displacements of floors to the variation in earthquake characteristics, such as soil class, characteristic period, and time step of records, peak ground displacement, and peak ground velocity, have also been considered. The dynamic equation of motion describing the building model and the applied earthquake load are presented and solved incrementally using the Runge-Kutta method. LAD then finds the characteristic patterns which lead to forecast the seismic response of building structures. The accuracy of LAD is compared to that of an artificial neural network (ANN, since the latter is the most known machine learning technique. Based on the conducted study, the proposed LAD model has been proven to be an efficient technique to learn, simulate, and blindly predict the dynamic response behaviour of building structures subjected to earthquake loads.

Impact of Electric Vehicle Charging Station Load on Distribution Network

Directory of Open Access Journals (Sweden)

Sanchari Deb

2018-01-01

Full Text Available Recent concerns about environmental pollution and escalating energy consumption accompanied by the advancements in battery technology have initiated the electrification of the transportation sector. With the universal resurgence of Electric Vehicles (EVs the adverse impact of the EV charging loads on the operating parameters of the power system has been noticed. The detrimental impact of EV charging station loads on the electricity distribution network cannot be neglected. The high charging loads of the fast charging stations results in increased peak load demand, reduced reserve margins, voltage instability, and reliability problems. Further, the penalty paid by the utility for the degrading performance of the power system cannot be neglected. This work aims to investigate the impact of the EV charging station loads on the voltage stability, power losses, reliability indices, as well as economic losses of the distribution network. The entire analysis is performed on the IEEE 33 bus test system representing a standard radial distribution network for six different cases of EV charging station placement. It is observed that the system can withstand placement of fast charging stations at the strong buses up to a certain level, but the placement of fast charging stations at the weak buses of the system hampers the smooth operation of the power system. Further, a strategy for the placement of the EV charging stations on the distribution network is proposed based on a novel Voltage stability, Reliability, and Power loss (VRP index. The results obtained indicate the efficacy of the VRP index.

CDMA coverage under mobile heterogeneous network load

NARCIS (Netherlands)

Saban, D.; van den Berg, Hans Leo; Boucherie, Richardus J.; Endrayanto, A.I.

2002-01-01

We analytically investigate coverage (determined by the uplink) under non-homogeneous and moving traffic load of third generation UMTS mobile networks. In particular, for different call assignment policies, we investigate cell breathing and the movement of the coverage gap occurring between cells

Fibre optical measuring network based on quasi-distributed amplitude sensors for detecting deformation loads

International Nuclear Information System (INIS)

Kul'chin, Yurii N; Kolchinskiy, V A; Kamenev, O T; Petrov, Yu S

2013-01-01

A new design of a sensitive element for a fibre optical sensor of deformation loads is proposed. A distributed fibre optical measuring network, aimed at determining both the load application point and the load mass, has been developed based on these elements. It is shown that neural network methods of data processing make it possible to combine quasi-distributed amplitude sensors of different types into a unified network. The results of the experimental study of a breadboard of a fibre optical measuring network are reported, which demonstrate successful reconstruction of the trajectory of a moving object (load) with a spatial resolution of 8 cm, as well as the load mass in the range of 1 – 10 kg with a sensitivity of 0.043 kg -1 . (laser optics 2012)

A new evolutionary solution method for dynamic expansion planning of DG-integrated primary distribution networks

International Nuclear Information System (INIS)

Ahmadigorji, Masoud; Amjady, Nima

2014-01-01

Highlights: • A new dynamic distribution network expansion planning model is presented. • A Binary Enhanced Particle Swarm Optimization (BEPSO) algorithm is proposed. • A Modified Differential Evolution (MDE) algorithm is proposed. • A new bi-level optimization approach composed of BEPSO and MDE is presented. • The effectiveness of the proposed optimization approach is extensively illustrated. - Abstract: Reconstruction in the power system and appearing of new technologies for generation capacity of electrical energy has led to significant innovation in Distribution Network Expansion Planning (DNEP). Distributed Generation (DG) includes the application of small/medium generation units located in power distribution networks and/or near the load centers. Appropriate utilization of DG can affect the various technical and operational indices of the distribution network such as the feeder loading, energy losses and voltage profile. In addition, application of DG in proper size is an essential tool to achieve the DG maximum potential benefits. In this paper, a time-based (dynamic) model for DNEP is proposed to determine the optimal size, location and installation year of DG in distribution system. Also, in this model, the Optimal Power Flow (OPF) is exerted to determine the optimal generation of DGs for every potential solution in order to minimize the investment and operation costs following the load growth in a specified planning period. Besides, the reinforcement requirements of existing distribution feeders are considered, simultaneously. The proposed optimization problem is solved by the combination of evolutionary methods of a new Binary Enhanced Particle Swarm Optimization (BEPSO) and Modified Differential Evolution (MDE) to find the optimal expansion strategy and solve OPF, respectively. The proposed planning approach is applied to two typical primary distribution networks and compared with several other methods. These comparisons illustrate the

When are network coding based dynamic multi-homing techniques beneficial?

DEFF Research Database (Denmark)

Pereira, Carlos; Aguiar, Ana; Roetter, Daniel Enrique Lucani

2016-01-01

Mechanisms that can cope with unreliable wireless channels in an efficient manner are required due to the increasing number of resource constrained devices. Concurrent use of multiple communications technologies can be instrumental towards improving services to mobile devices in heterogeneous...... networks. In our previous work, we developed an optimization framework to generate channel-aware transmission policies for multi-homed devices under different cost criteria. Our formulation considers network coding as a key technique that simplifies load allocation across multiple channels and provides...... high resiliency under time-varying channel conditions. This paper seeks to explore the parameter space and identify the operating regions where dynamic coded policies offer most improvement over static ones in terms of energy consumption and channel utilization. We leverage meta-heuristics to find...

PPOOLEX experiments on dynamic loading with pressure feedback

International Nuclear Information System (INIS)

Puustinen, M.; Laine, J.; Raesaenen, A.

2011-01-01

This report summarizes the results of the dynamic loading experiments (DYN series) carried out with the scaled down, two compartment PPOOLEX test facility designed and constructed at LUT. Steam was blown into the dry well compartment and from there through the DN200 vertical blowdown pipe to the condensation pool filled with sub-cooled water. The main purpose of the experiments was to study dynamic loads caused by different condensation modes. Particularly, the effect of counterpressure on loads due to pressure oscillations induced by chugging was of interest. Before the experiments the condensation pool was filled with isothermal water so that the blowdown pipe outlet was submerged by 1.03-1.11 m. The initial temperature of the pool water varied from 11 deg. C to 63 deg. C, the steam flow rate from 290 g/s to 1220 g/s and the temperature of incoming steam from 132 deg. C to 182 deg. C. Non-condensables were pushed from the dry well into the gas space of the wet well with a short discharge of steam before the recorded period of the experiments. As a result of this procedure, the system pressure was at an elevated level in the beginning of the actual experiments. An increased counterpressure was used in the last experiment of the series. The diminishing effect of increased system pressure on chugging intensity and on measured loads is evident from the results of the last experiment. The highest pressure pulses both inside the blowdown pipe and in the condensation pool were about half of those measured with a lower system pressure but otherwise with similar test parameters. The experiments on dynamic loading gave expected results. The loads experienced by pool structures depended strongly on the steam mass flow rate, pool water temperature and system pressure. The DYN experiments indicated that chugging and condensation within the blowdown pipe cause significant dynamic loads in case of strongly sub-cooled pool water. The level of pool water temperature is decisive

PPOOLEX experiments on dynamic loading with pressure feedback

Energy Technology Data Exchange (ETDEWEB)

Puustinen, M.; Laine, J.; Raesaenen, A. (Lappeenranta Univ. of Technology, Nuclear Safety Research Unit (Finland))

2011-01-15

This report summarizes the results of the dynamic loading experiments (DYN series) carried out with the scaled down, two compartment PPOOLEX test facility designed and constructed at LUT. Steam was blown into the dry well compartment and from there through the DN200 vertical blowdown pipe to the condensation pool filled with sub-cooled water. The main purpose of the experiments was to study dynamic loads caused by different condensation modes. Particularly, the effect of counterpressure on loads due to pressure oscillations induced by chugging was of interest. Before the experiments the condensation pool was filled with isothermal water so that the blowdown pipe outlet was submerged by 1.03-1.11 m. The initial temperature of the pool water varied from 11 deg. C to 63 deg. C, the steam flow rate from 290 g/s to 1220 g/s and the temperature of incoming steam from 132 deg. C to 182 deg. C. Non-condensables were pushed from the dry well into the gas space of the wet well with a short discharge of steam before the recorded period of the experiments. As a result of this procedure, the system pressure was at an elevated level in the beginning of the actual experiments. An increased counterpressure was used in the last experiment of the series. The diminishing effect of increased system pressure on chugging intensity and on measured loads is evident from the results of the last experiment. The highest pressure pulses both inside the blowdown pipe and in the condensation pool were about half of those measured with a lower system pressure but otherwise with similar test parameters. The experiments on dynamic loading gave expected results. The loads experienced by pool structures depended strongly on the steam mass flow rate, pool water temperature and system pressure. The DYN experiments indicated that chugging and condensation within the blowdown pipe cause significant dynamic loads in case of strongly sub-cooled pool water. The level of pool water temperature is decisive

Cascading failures with local load redistribution in interdependent Watts-Strogatz networks

Science.gov (United States)

Hong, Chen; Zhang, Jun; Du, Wen-Bo; Sallan, Jose Maria; Lordan, Oriol

2016-05-01

Cascading failures of loads in isolated networks have been studied extensively over the last decade. Since 2010, such research has extended to interdependent networks. In this paper, we study cascading failures with local load redistribution in interdependent Watts-Strogatz (WS) networks. The effects of rewiring probability and coupling strength on the resilience of interdependent WS networks have been extensively investigated. It has been found that, for small values of the tolerance parameter, interdependent networks are more vulnerable as rewiring probability increases. For larger values of the tolerance parameter, the robustness of interdependent networks firstly decreases and then increases as rewiring probability increases. Coupling strength has a different impact on robustness. For low values of coupling strength, the resilience of interdependent networks decreases with the increment of the coupling strength until it reaches a certain threshold value. For values of coupling strength above this threshold, the opposite effect is observed. Our results are helpful to understand and design resilient interdependent networks.

Information governance in dynamic networked business process management

NARCIS (Netherlands)

Rasouli, M.; Eshuis, H.; Grefen, P.W.P.J.; Trienekens, J.J.M.; Kusters, R.J.

2016-01-01

Competition in today’s globalized markets forces organizations to collaborate within dynamic business networks to provide mass-customized integrated solutions for customers. The collaboration within dynamic business networks necessitates forming dynamic networked business processes (DNBPs).

Short term and medium term power distribution load forecasting by neural networks

International Nuclear Information System (INIS)

Yalcinoz, T.; Eminoglu, U.

2005-01-01

Load forecasting is an important subject for power distribution systems and has been studied from different points of view. In general, load forecasts should be performed over a broad spectrum of time intervals, which could be classified into short term, medium term and long term forecasts. Several research groups have proposed various techniques for either short term load forecasting or medium term load forecasting or long term load forecasting. This paper presents a neural network (NN) model for short term peak load forecasting, short term total load forecasting and medium term monthly load forecasting in power distribution systems. The NN is used to learn the relationships among past, current and future temperatures and loads. The neural network was trained to recognize the peak load of the day, total load of the day and monthly electricity consumption. The suitability of the proposed approach is illustrated through an application to real load shapes from the Turkish Electricity Distribution Corporation (TEDAS) in Nigde. The data represents the daily and monthly electricity consumption in Nigde, Turkey

Fundamental structures of dynamic social networks

DEFF Research Database (Denmark)

Sekara, Vedran; Stopczynski, Arkadiusz; Jørgensen, Sune Lehmann

2016-01-01

Social systems are in a constant state of flux, with dynamics spanning from minute-by-minute changes to patterns present on the timescale of years. Accurate models of social dynamics are important for understanding the spreading of influence or diseases, formation of friendships...... and their interactions in the network of real-world person-to-person proximity measured via Bluetooth, as well as their telecommunication networks, online social media contacts, geolocation, and demographic data. These high-resolution data allow us to observe social groups directly, rendering community detection......, and the productivity of teams. Although there has been much progress on understanding complex networks over the past decade, little is known about the regularities governing the microdynamics of social networks. Here, we explore the dynamic social network of a densely-connected population of ∼1,000 individuals...

Dynamic modeling and analysis of load sharing characteristics of wind turbine gearbox

Directory of Open Access Journals (Sweden)

Pengxing Yi

2015-03-01

Full Text Available A coupled dynamic model, which contains helical gears-shafts-bearings for a wind turbine gearbox transmission system, was built considering nonlinear factors of the time-varying mesh stiffness, the external varying load, and the dynamic transmission error at first. The model is confirmed to be right after comparing the theoretical data with the experimental load sharing values, and also it is found that the static load sharing is conservative to evaluate the non-equilibrium effect of a planetary gear system. Besides, the analyzing results of the influence of average error and amplitude error on the load sharing show that the load sharing could be decreased if the error goes up a little. Then, by means of treating the static tracing point as the dynamic initial values, we analyzed the initial position’s influence on the load sharing of transmission system to provide a theoretical basis of load sharing control. Furthermore, we explored the influence of high-speed shaft position angle on the load sharing and the dynamic load factor of gears fixed on the parallel shafts. The results provide useful theoretical guidelines for the design of parallel shaft gear system in the wind turbines.

Studying Dynamics in Business Networks

DEFF Research Database (Denmark)

Andersen, Poul Houman; Anderson, Helen; Havila, Virpi

1998-01-01

This paper develops a theory on network dynamics using the concepts of role and position from sociological theory. Moreover, the theory is further tested using case studies from Denmark and Finland......This paper develops a theory on network dynamics using the concepts of role and position from sociological theory. Moreover, the theory is further tested using case studies from Denmark and Finland...

How complex a dynamical network can be?

International Nuclear Information System (INIS)

Baptista, M.S.; Kakmeni, F. Moukam; Del Magno, Gianluigi; Hussein, M.S.

2011-01-01

Positive Lyapunov exponents measure the asymptotic exponential divergence of nearby trajectories of a dynamical system. Not only they quantify how chaotic a dynamical system is, but since their sum is an upper bound for the rate of information production, they also provide a convenient way to quantify the complexity of a dynamical network. We conjecture based on numerical evidences that for a large class of dynamical networks composed by equal nodes, the sum of the positive Lyapunov exponents is bounded by the sum of all the positive Lyapunov exponents of both the synchronization manifold and its transversal directions, the last quantity being in principle easier to compute than the latter. As applications of our conjecture we: (i) show that a dynamical network composed of equal nodes and whose nodes are fully linearly connected produces more information than similar networks but whose nodes are connected with any other possible connecting topology; (ii) show how one can calculate upper bounds for the information production of realistic networks whose nodes have parameter mismatches, randomly chosen; (iii) discuss how to predict the behavior of a large dynamical network by knowing the information provided by a system composed of only two coupled nodes.

Complex Dynamical Network Control for Trajectory Tracking Using Delayed Recurrent Neural Networks

Directory of Open Access Journals (Sweden)

Jose P. Perez

2014-01-01

Full Text Available In this paper, the problem of trajectory tracking is studied. Based on the V-stability and Lyapunov theory, a control law that achieves the global asymptotic stability of the tracking error between a delayed recurrent neural network and a complex dynamical network is obtained. To illustrate the analytic results, we present a tracking simulation of a dynamical network with each node being just one Lorenz’s dynamical system and three identical Chen’s dynamical systems.

Markovian dynamics on complex reaction networks

Energy Technology Data Exchange (ETDEWEB)

Goutsias, J., E-mail: goutsias@jhu.edu; Jenkinson, G., E-mail: jenkinson@jhu.edu

2013-08-10

Complex networks, comprised of individual elements that interact with each other through reaction channels, are ubiquitous across many scientific and engineering disciplines. Examples include biochemical, pharmacokinetic, epidemiological, ecological, social, neural, and multi-agent networks. A common approach to modeling such networks is by a master equation that governs the dynamic evolution of the joint probability mass function of the underlying population process and naturally leads to Markovian dynamics for such process. Due however to the nonlinear nature of most reactions and the large size of the underlying state-spaces, computation and analysis of the resulting stochastic population dynamics is a difficult task. This review article provides a coherent and comprehensive coverage of recently developed approaches and methods to tackle this problem. After reviewing a general framework for modeling Markovian reaction networks and giving specific examples, the authors present numerical and computational techniques capable of evaluating or approximating the solution of the master equation, discuss a recently developed approach for studying the stationary behavior of Markovian reaction networks using a potential energy landscape perspective, and provide an introduction to the emerging theory of thermodynamic analysis of such networks. Three representative problems of opinion formation, transcription regulation, and neural network dynamics are used as illustrative examples.

Markovian dynamics on complex reaction networks

International Nuclear Information System (INIS)

Goutsias, J.; Jenkinson, G.

2013-01-01

Complex networks, comprised of individual elements that interact with each other through reaction channels, are ubiquitous across many scientific and engineering disciplines. Examples include biochemical, pharmacokinetic, epidemiological, ecological, social, neural, and multi-agent networks. A common approach to modeling such networks is by a master equation that governs the dynamic evolution of the joint probability mass function of the underlying population process and naturally leads to Markovian dynamics for such process. Due however to the nonlinear nature of most reactions and the large size of the underlying state-spaces, computation and analysis of the resulting stochastic population dynamics is a difficult task. This review article provides a coherent and comprehensive coverage of recently developed approaches and methods to tackle this problem. After reviewing a general framework for modeling Markovian reaction networks and giving specific examples, the authors present numerical and computational techniques capable of evaluating or approximating the solution of the master equation, discuss a recently developed approach for studying the stationary behavior of Markovian reaction networks using a potential energy landscape perspective, and provide an introduction to the emerging theory of thermodynamic analysis of such networks. Three representative problems of opinion formation, transcription regulation, and neural network dynamics are used as illustrative examples

An Adaptive Learning Based Network Selection Approach for 5G Dynamic Environments

Directory of Open Access Journals (Sweden)

Xiaohong Li

2018-03-01

Full Text Available Networks will continue to become increasingly heterogeneous as we move toward 5G. Meanwhile, the intelligent programming of the core network makes the available radio resource be more changeable rather than static. In such a dynamic and heterogeneous network environment, how to help terminal users select optimal networks to access is challenging. Prior implementations of network selection are usually applicable for the environment with static radio resources, while they cannot handle the unpredictable dynamics in 5G network environments. To this end, this paper considers both the fluctuation of radio resources and the variation of user demand. We model the access network selection scenario as a multiagent coordination problem, in which a bunch of rationally terminal users compete to maximize their benefits with incomplete information about the environment (no prior knowledge of network resource and other users’ choices. Then, an adaptive learning based strategy is proposed, which enables users to adaptively adjust their selections in response to the gradually or abruptly changing environment. The system is experimentally shown to converge to Nash equilibrium, which also turns out to be both Pareto optimal and socially optimal. Extensive simulation results show that our approach achieves significantly better performance compared with two learning and non-learning based approaches in terms of load balancing, user payoff and the overall bandwidth utilization efficiency. In addition, the system has a good robustness performance under the condition with non-compliant terminal users.

Dynamics of Number of Packets in Transit in Free Flow State of Data Network

International Nuclear Information System (INIS)

Shengkun Xie; Lawniczak, A.T.

2011-01-01

We study how the dynamics of Number of Packets in Transit (NPT) is affected by the coupling of a routing type with a volume of incoming packet traffic in a data network model of packet switching type. The NPT is a network performance indicator of an aggregate type that measures in '' real time '', how many packets are in the network on their routes to their destinations. We conduct our investigation using a time-discrete simulation model that is an abstraction of the Network Layer of the ISO OSI Seven Layer Reference Model. This model focuses on packets and their routing. We consider a static routing and two different types of dynamic routings coupled with different volumes of incoming packet traffic in the network free flow state. Our study shows that the order of the values of the NPT mean value time series depends on the coupling of a routing type with a volume of incoming packet traffic and changes when the volume of incoming packet traffic increases and is closed to the critical source load values, i.e. when it is closed to the phase transition points from the network free flow state to its congested states. (authors)

Disruptions, loads, and dynamic response of ITER

International Nuclear Information System (INIS)

Nelson, B.; Riemer, B.; Sayer, R.; Strickler, D.; Barabaschi, P.; Ioki, K.; Johnson, G.; Shimizu, K.; Williamson, D.

1995-01-01

Plasma disruptions and the resulting electromagnetic loads are critical to the design of the vacuum vessel and in-vessel components of the International Thermonuclear Experimental Reactor (ITER). This paper describes the status of plasma disruption simulations and related analysis, including the dynamic response of the vacuum vessel and in-vessel components, stresses and deflections in the vacuum vessel, and reaction loads in the support structures

Incorporating moving dynamic tyre loads in pavement design and analysis

CSIR Research Space (South Africa)

Steyn, WJvdM

2000-07-01

Full Text Available at the University of Pretoria. 4 REAL LIFE TYRE LOADS Characterisation Pavement loading has been shown by various authors to be a dynamic (time-dependent) phenomenon (Divine, 1997; Cebon, 1999). A pavement experiences a vehicle as a moving, time-varying set... frequencies. Body bounce generally dominates the dynamic loading, and is mainly caused by the response of the sprung mass of the vehicle to the pavement roughness. Axle hop becomes more significant at higher vehicle speeds and higher pavement roughnesses...

Development of Fast-Running Simulation Methodology Using Neural Networks for Load Follow Operation

International Nuclear Information System (INIS)

Seong, Seung-Hwan; Park, Heui-Youn; Kim, Dong-Hoon; Suh, Yong-Suk; Hur, Seop; Koo, In-Soo; Lee, Un-Chul; Jang, Jin-Wook; Shin, Yong-Chul

2002-01-01

A new fast-running analytic model has been developed for analyzing the load follow operation. The new model was based on the neural network theory, which has the capability of modeling the input/output relationships of a nonlinear system. The new model is made up of two error back-propagation neural networks and procedures to calculate core parameters, such as the distributions and density of xenon in a quasi-steady-state core like load follow operation. One neural network is designed to retrieve the axial offset of power distribution, and the other is for reactivity corresponding to a given core condition. The training data sets for learning the neural networks in the new model are generated with a three-dimensional nodal code and, also, the measured data of the first-day test of load follow operation. Using the new model, the simulation results of the 5-day load follow test in a pressurized water reactor show a good agreement between the simulation data and the actual measured data. Required computing time for simulating a load follow operation is comparable to that of a fast-running lumped model. Moreover, the new model does not require additional engineering factors to compensate for the difference between the actual measurements and analysis results because the neural network has the inherent learning capability of neural networks to new situations

The Pneumatic Actuators As Vertical Dynamic Load Simulators On Medium Weighted Wheel Suspension Mechanism

Science.gov (United States)

Ka'ka, Simon; Himran, Syukri; Renreng, Ilyas; Sutresman, Onny

2018-02-01

Almost all of road damage can be caused by dynamic loads of vehicles that fluctuate according to the type of vehicle that passes through. This study aims to calculate the vertical dynamic load of the vehicle actually occurs on road construction by the mechanism of vehicle wheel suspension. Pneumatic cylinders driven by pressurized air directly load the spring and shock absorber installed on the wheels of the vehicle. The load fluctuations of the medium weight categorized vehicles are determined by the regulation of the amount of pressurized air that enters into the pneumatic cylinder chamber, pushing the piston and connecting rods. The displacement that occurs during compression on the spring and shock absorber, is substituted into the equation of vehicle dynamic load while taking into account the spring stiffness constant, and the fluid or damper gas coefficient. The results show that the magnitude of the displacement when the compression force works has significant influences to the amount of vertical dynamic load of the vehicle that overlies the road construction. The presence of dynamic load of vehicles that fluctuates and repeats, also affects on the reduction of road ability to receive the load. Experimental results using pneumatic actuators instead of real dynamic vehicle loads illustrate the characteristics of the relationship between work pressure and dynamic load. If the working pressure of P2 (bar) is greater, the vertical dynamic load Ft (N) that overloads the road structure is also greater. The associate graphs show that the shock absorber has a greater ability to reduce dynamic load vertically that burden the road structure when compared with the ability of screw spring.

Effect of loading rate on dynamic fracture of reaction bonded silicon nitride

Science.gov (United States)

Liaw, B. M.; Kobayashi, A. S.; Emery, A. F.

1986-01-01

Wedge-loaded, modified tapered double cantilever beam (WL-MTDCB) specimens under impact loading were used to determine the room temperature dynamic fracture response of reaction bonded silicon nitride (RBSN). The crack extension history, with the exception of the terminal phase, was similar to that obtained under static loading. Like its static counterpart, a distinct crack acceleration phase, which was not observed in dynamic fracture of steel and brittle polymers, was noted. Unlike its static counterpart, the crack continued to propagate at nearly its terminal velocity under a low dynamic stress intensity factor during the terminal phase of crack propagation. These and previously obtained results for glass and RBSN show that dynamic crack arrest under a positive dynamic stress intensity factor is unlikely in static and impact loaded structural ceramics.

Local Dynamics in Trained Recurrent Neural Networks.

Science.gov (United States)

Rivkind, Alexander; Barak, Omri

2017-06-23

Learning a task induces connectivity changes in neural circuits, thereby changing their dynamics. To elucidate task-related neural dynamics, we study trained recurrent neural networks. We develop a mean field theory for reservoir computing networks trained to have multiple fixed point attractors. Our main result is that the dynamics of the network's output in the vicinity of attractors is governed by a low-order linear ordinary differential equation. The stability of the resulting equation can be assessed, predicting training success or failure. As a consequence, networks of rectified linear units and of sigmoidal nonlinearities are shown to have diametrically different properties when it comes to learning attractors. Furthermore, a characteristic time constant, which remains finite at the edge of chaos, offers an explanation of the network's output robustness in the presence of variability of the internal neural dynamics. Finally, the proposed theory predicts state-dependent frequency selectivity in the network response.

Local Dynamics in Trained Recurrent Neural Networks

Science.gov (United States)

Rivkind, Alexander; Barak, Omri

2017-06-01

Learning a task induces connectivity changes in neural circuits, thereby changing their dynamics. To elucidate task-related neural dynamics, we study trained recurrent neural networks. We develop a mean field theory for reservoir computing networks trained to have multiple fixed point attractors. Our main result is that the dynamics of the network's output in the vicinity of attractors is governed by a low-order linear ordinary differential equation. The stability of the resulting equation can be assessed, predicting training success or failure. As a consequence, networks of rectified linear units and of sigmoidal nonlinearities are shown to have diametrically different properties when it comes to learning attractors. Furthermore, a characteristic time constant, which remains finite at the edge of chaos, offers an explanation of the network's output robustness in the presence of variability of the internal neural dynamics. Finally, the proposed theory predicts state-dependent frequency selectivity in the network response.

Insensitivity of proportional fairness in critically loaded bandwidth sharing networks

NARCIS (Netherlands)

Vlasiou, M.; Zhang, J.; Zwart, B.

2014-01-01

Proportional fairness is a popular service allocation mechanism to describe and analyze the performance of data networks at flow level. Recently, several authors have shown that the invariant distribution of such networks admits a product form distribution under critical loading. Assuming

Software defined networks reactive flow programming and load balance switching

OpenAIRE

Καλλιανιώτης, Νικόλαος; Kallianiotis, Nikolaos

2017-01-01

This project serves as a Master Thesis as the requirements of the master’s programme Master of Digital Communications and Networks. It proposes load balancing algorithms applied to Software-Defined Networks to achieve the best possible resource utilisation of each of the links present in a network. The open-sources Opendaylight project and Floodlight project are used as SDN controllers, and the network is emulated using Mininet software

Investigation of Load Sharing in Hybrid (2G/3G) Mobile Networks

OpenAIRE

Martynas Stirbys; Karolis Žvinys

2015-01-01

The main purpose of this work is to investigate load sharing methods for 2G/3G cellular networks in order to determine their impact on the network and users. One of the study aims is to analyze the performance of the methods. Moreover the paper provides an overview of the methods circumstances, limitations. Directed Retry and Load Based Handover methods were chosen. Data was obtained from real Lithuanian mobile operator’s network. The paper also discusses the changes in Key Performance Indica...

Effects of static pre-loading on the dynamic stability of a column on ...

African Journals Online (AJOL)

This paper presents, from strictly analytical consideration, the dynamic analysis of a finite column stressed by a step load but in the presence of a previously imposed static load. The results show that (a) the dynamic buckling load for this type of loading is relatively higher than that of a similar column stressed by a step load ...

Temporal fidelity in dynamic social networks

DEFF Research Database (Denmark)

Stopczynski, Arkadiusz; Sapiezynski, Piotr; Pentland, Alex ‘Sandy’

2015-01-01

of the network dynamics can be used to inform the process of measuring social networks. The details of measurement are of particular importance when considering dynamic processes where minute-to-minute details are important, because collection of physical proximity interactions with high temporal resolution...

Behavior of Brittle Materials Under Dynamic Loading

National Research Council Canada - National Science Library

Kanel, G

2000-01-01

Dynamic loading of brittle materials is related to many applications, including explosive excavation of rocks, design of ceramic armor, meteor impact on spacecraft windows, particle damage to turbine blades, etc...

Pinning Synchronization of Switched Complex Dynamical Networks

Directory of Open Access Journals (Sweden)

Liming Du

2015-01-01

Full Text Available Network topology and node dynamics play a key role in forming synchronization of complex networks. Unfortunately there is no effective synchronization criterion for pinning synchronization of complex dynamical networks with switching topology. In this paper, pinning synchronization of complex dynamical networks with switching topology is studied. Two basic problems are considered: one is pinning synchronization of switched complex networks under arbitrary switching; the other is pinning synchronization of switched complex networks by design of switching when synchronization cannot achieved by using any individual connection topology alone. For the two problems, common Lyapunov function method and single Lyapunov function method are used respectively, some global synchronization criteria are proposed and the designed switching law is given. Finally, simulation results verify the validity of the results.

Interestingness-Driven Diffusion Process Summarization in Dynamic Networks

DEFF Research Database (Denmark)

Qu, Qiang; Liu, Siyuan; Jensen, Christian S.

2014-01-01

The widespread use of social networks enables the rapid diffusion of information, e.g., news, among users in very large communities. It is a substantial challenge to be able to observe and understand such diffusion processes, which may be modeled as networks that are both large and dynamic. A key...... tool in this regard is data summarization. However, few existing studies aim to summarize graphs/networks for dynamics. Dynamic networks raise new challenges not found in static settings, including time sensitivity and the needs for online interestingness evaluation and summary traceability, which...... render existing techniques inapplicable. We study the topic of dynamic network summarization: how to summarize dynamic networks with millions of nodes by only capturing the few most interesting nodes or edges over time, and we address the problem by finding interestingness-driven diffusion processes...

Investigation of Load Sharing in Hybrid (2G/3G Mobile Networks

Directory of Open Access Journals (Sweden)

Martynas Stirbys

2015-07-01

Full Text Available The main purpose of this work is to investigate load sharing methods for 2G/3G cellular networks in order to determine their impact on the network and users. One of the study aims is to analyze the performance of the methods. Moreover the paper provides an overview of the methods circumstances, limitations. Directed Retry and Load Based Handover methods were chosen. Data was obtained from real Lithuanian mobile operator’s network. The paper also discusses the changes in Key Performance Indicators.

Insensitive versus efficient dynamic load balancing in networks without blocking

NARCIS (Netherlands)

Jonckheere, M.

2006-01-01

So-called Whittle networks have recently been shown to give tight approximations for the performance of non-locally balanced networks with blocking, including practical routing policies such as joining the shortest queue. In the present paper, we turn the attention to networks without blocking. To

Dynamic characteristics of motor-gear system under load saltations and voltage transients

Science.gov (United States)

Bai, Wenyu; Qin, Datong; Wang, Yawen; Lim, Teik C.

2018-02-01

In this paper, a dynamic model of a motor-gear system is proposed. The model combines a nonlinear permeance network model (PNM) of a squirrel-cage induction motor and a coupled lateral-torsional dynamic model of a planetary geared rotor system. The external excitations including voltage transients and load saltations, as well as the internal excitations such as spatial effects, magnetic circuits topology and material nonlinearity in the motor, and time-varying mesh stiffness and damping in the planetary gear system are considered in the proposed model. Then, the simulation results are compared with those predicted by the electromechanical model containing a dynamic motor model with constant inductances. The comparison showed that the electromechanical system model with the PNM motor model yields more reasonable results than the electromechanical system model with the lumped-parameter electric machine. It is observed that electromechanical coupling effect can induce additional and severe gear vibrations. In addition, the external conditions, especially the voltage transients, will dramatically affect the dynamic characteristics of the electromechanical system. Finally, some suggestions are offered based on this analysis for improving the performance and reliability of the electromechanical system.

Dynamic training algorithm for dynamic neural networks

International Nuclear Information System (INIS)

Tan, Y.; Van Cauwenberghe, A.; Liu, Z.

1996-01-01

The widely used backpropagation algorithm for training neural networks based on the gradient descent has a significant drawback of slow convergence. A Gauss-Newton method based recursive least squares (RLS) type algorithm with dynamic error backpropagation is presented to speed-up the learning procedure of neural networks with local recurrent terms. Finally, simulation examples concerning the applications of the RLS type algorithm to identification of nonlinear processes using a local recurrent neural network are also included in this paper

Node Load Balance Multi-flow Opportunistic Routing in Wireless Mesh Networks

Directory of Open Access Journals (Sweden)

Wang Tao

2014-04-01

Full Text Available Opportunistic routing (OR has been proposed to improve the performance of wireless networks by exploiting the multi-user diversity and broadcast nature of the wireless medium. It involves multiple candidate forwarders to relay packets every hop. The existing OR doesn’t take account of the traffic load and load balance, therefore some nodes may be overloaded while the others may not, leading to network performance decline. In this paper, we focus on opportunities routing selection with node load balance which is described as a convex optimization problem. To solve the problem, by combining primal-dual and sub-gradient methods, a fully distributed Node load balance Multi-flow Opportunistic Routing algorithm (NMOR is proposed. With node load balance constraint, NMOR allocates the flow rate iteratively and the rate allocation decides the candidate forwarder selection of opportunities routing. The simulation results show that NMOR algorithm improves 100 %, 62 % of the aggregative throughput than ETX and EAX, respectively.

Complex networks under dynamic repair model

Science.gov (United States)

Chaoqi, Fu; Ying, Wang; Kun, Zhao; Yangjun, Gao

2018-01-01

Invulnerability is not the only factor of importance when considering complex networks' security. It is also critical to have an effective and reasonable repair strategy. Existing research on network repair is confined to the static model. The dynamic model makes better use of the redundant capacity of repaired nodes and repairs the damaged network more efficiently than the static model; however, the dynamic repair model is complex and polytropic. In this paper, we construct a dynamic repair model and systematically describe the energy-transfer relationships between nodes in the repair process of the failure network. Nodes are divided into three types, corresponding to three structures. We find that the strong coupling structure is responsible for secondary failure of the repaired nodes and propose an algorithm that can select the most suitable targets (nodes or links) to repair the failure network with minimal cost. Two types of repair strategies are identified, with different effects under the two energy-transfer rules. The research results enable a more flexible approach to network repair.

Applied Knowledge Management to Mitigate Cognitive Load in Network-Enabled Mission Command

Science.gov (United States)

2017-11-22

ARL-TN-0859 ● NOV 2017 US Army Research Laboratory Applied Knowledge Management to Mitigate Cognitive Load in Network-Enabled...Applied Knowledge Management to Mitigate Cognitive Load in Network-Enabled Mission Command by John K Hawley Human Research and Engineering...REPORT TYPE Technical Note 3. DATES COVERED (From - To) 1 May 2016–20 April 2017 4. TITLE AND SUBTITLE Applied Knowledge Management to Mitigate

Organization of excitable dynamics in hierarchical biological networks.

Directory of Open Access Journals (Sweden)

Mark Müller-Linow

Full Text Available This study investigates the contributions of network topology features to the dynamic behavior of hierarchically organized excitable networks. Representatives of different types of hierarchical networks as well as two biological neural networks are explored with a three-state model of node activation for systematically varying levels of random background network stimulation. The results demonstrate that two principal topological aspects of hierarchical networks, node centrality and network modularity, correlate with the network activity patterns at different levels of spontaneous network activation. The approach also shows that the dynamic behavior of the cerebral cortical systems network in the cat is dominated by the network's modular organization, while the activation behavior of the cellular neuronal network of Caenorhabditis elegans is strongly influenced by hub nodes. These findings indicate the interaction of multiple topological features and dynamic states in the function of complex biological networks.

Current scaling of axially radiated power in dynamic hohlraums and dynamic hohlraum load design for ZR

International Nuclear Information System (INIS)

Mock, Raymond Cecil; Nash, Thomas J.; Sanford, Thomas W. L.

2007-01-01

We present designs for dynamic hohlraum z-pinch loads on the 28 MA, 140 ns driver ZR. The scaling of axially radiated power with current in dynamic hohlraums is reviewed. With adequate stability on ZR this scaling indicates that 30 TW of axially radiated power should be possible. The performance of the dynamic hohlraum load on the 20 MA, 100 ns driver Z is extensively reviewed. The baseline z-pinch load on Z is a nested tungsten wire array imploding onto on-axis foam. Data from a variety of x-ray diagnostics fielded on Z are presented. These diagnostics include x-ray diodes, bolometers, fast x-ray imaging cameras, and crystal spectrometers. Analysis of these data indicates that the peak dynamic radiation temperature on Z is between 250 and 300 eV from a diameter less than 1 mm. Radiation from the dynamic hohlraum itself or from a radiatively driven pellet within the dynamic hohlraum has been used to probe a variety of matter associated with the dynamic hohlraum: the tungsten z-pinch itself, tungsten sliding across the end-on apertures, a titanium foil over the end aperture, and a silicon aerogel end cap. Data showing the existence of asymmetry in radiation emanating from the two ends of the dynamic hohlraum is presented, along with data showing load configurations that mitigate this asymmetry. 1D simulations of the dynamic hohlraum implosion are presented and compared to experimental data. The simulations provide insight into the dynamic hohlraum behavior but are not necessarily a reliable design tool because of the inherently 3D behavior of the imploding nested tungsten wire arrays

Material properties under intensive dynamic loading

CERN Document Server

Cherne, Frank J; Zhernokletov, Mikhail V; Glushak, B L; Zocher, Marvin A

2007-01-01

Understanding the physical and thermomechanical response of materials subjected to intensive dynamic loading is a challenge of great significance in engineering today. This volume assumes the task of gathering both experimental and diagnostic methods in one place, since not much information has been previously disseminated in the scientific literature.

Numerical evaluation of cracked pipes under dynamic loading

International Nuclear Information System (INIS)

Petit, M.; Jamet, P.

1989-01-01

In order to apply the leak-before-break concept to piping systems, the behavior of cracked pipes under dynamic, and especially seismic, loadings must be studied. A simple finite element model of a cracked pipe has been developed and implemented in the general purpose computer code CASTEM 2000. The model is a generalization of the approach proposed by Paris and Tada (1). Considered loads are bending moment and axial force (representing thermal expansion and internal pressure.) The elastic characteristics of the model are determined using the Zahoor formulae for the geometry-dependent factors. Owing to the material behabior plasticity must be taken into account. To represent the crack growth, the material is defined by two characteristic values: J 1c which is the level of energy corresponding to crack initiation and the tearing modulus, T, which governs the length of propagation of the crack. For dynamic loads, unilateral conditions are imposed to represent crack closure. The model has been used for the design of dynamic tests to be conducted on shaking tables. Test principle is briefly described and numerical results are presented. Finally evaluation of margin, due to plasticity, in comparison with the standard design procedure is made

Network dynamics and its relationships to topology and coupling structure in excitable complex networks

International Nuclear Information System (INIS)

Zhang Li-Sheng; Mi Yuan-Yuan; Gu Wei-Feng; Hu Gang

2014-01-01

All dynamic complex networks have two important aspects, pattern dynamics and network topology. Discovering different types of pattern dynamics and exploring how these dynamics depend on network topologies are tasks of both great theoretical importance and broad practical significance. In this paper we study the oscillatory behaviors of excitable complex networks (ECNs) and find some interesting dynamic behaviors of ECNs in oscillatory probability, the multiplicity of oscillatory attractors, period distribution, and different types of oscillatory patterns (e.g., periodic, quasiperiodic, and chaotic). In these aspects, we further explore strikingly sharp differences among network dynamics induced by different topologies (random or scale-free topologies) and different interaction structures (symmetric or asymmetric couplings). The mechanisms behind these differences are explained physically. (interdisciplinary physics and related areas of science and technology)

Robust adaptive synchronization of general dynamical networks ...

Indian Academy of Sciences (India)

Robust adaptive synchronization; dynamical network; multiple delays; multiple uncertainties. ... Networks such as neural networks, communication transmission networks, social rela- tionship networks etc. ..... a very good effect. Pramana – J.

Physical Proximity and Spreading in Dynamic Social Networks

OpenAIRE

Stopczynski, Arkadiusz; Pentland, Alex Sandy; Lehmann, Sune

2015-01-01

Most infectious diseases spread on a dynamic network of human interactions. Recent studies of social dynamics have provided evidence that spreading patterns may depend strongly on detailed micro-dynamics of the social system. We have recorded every single interaction within a large population, mapping out---for the first time at scale---the complete proximity network for a densely-connected system. Here we show the striking impact of interaction-distance on the network structure and dynamics ...

Dynamical prediction and pattern mapping in short-term load forecasting

Energy Technology Data Exchange (ETDEWEB)

Aguirre, Luis Antonio; Rodrigues, Daniela D.; Lima, Silvio T. [Departamento de Engenharia Eletronica, Universidade Federal de Minas Gerais, Av. Antonio Carlos, 6627, 31270-901 Belo Horizonte, MG (Brazil); Martinez, Carlos Barreira [Departamento de Engenharia Hidraulica e Recursos Hidricos, Universidade Federal de Minas Gerais, Av. Antonio Carlos, 6627, 31270-901 Belo Horizonte, MG (Brazil)

2008-01-15

This work will not put forward yet another scheme for short-term load forecasting but rather will provide evidences that may improve our understanding about fundamental issues which underlay load forecasting problems. In particular, load forecasting will be decomposed into two main problems, namely dynamical prediction and pattern mapping. It is argued that whereas the latter is essentially static and becomes nonlinear when weekly features in the data are taken into account, the former might not be deterministic at all. In such cases there is no determinism (serial correlations) in the data apart from the average cycle and the best a model can do is to perform pattern mapping. Moreover, when there is determinism in addition to the average cycle, the underlying dynamics are sometimes linear, in which case there is no need to resort to nonlinear models to perform dynamical prediction. Such conclusions were confirmed using real load data and surrogate data analysis. In a sense, the paper details and organizes some general beliefs found in the literature on load forecasting. This sheds some light on real model-building and forecasting problems and helps understand some apparently conflicting results reported in the literature. (author)

Decoding network dynamics in cancer

DEFF Research Database (Denmark)

Linding, Rune

2014-01-01

Biological systems are composed of highly dynamic and interconnected molecular networks that drive biological decision processes. The goal of network biology is to describe, quantify and predict the information flow and functional behaviour of living systems in a formal language and with an accur......Biological systems are composed of highly dynamic and interconnected molecular networks that drive biological decision processes. The goal of network biology is to describe, quantify and predict the information flow and functional behaviour of living systems in a formal language...... and with an accuracy that parallels our characterisation of other physical systems such as Jumbo-jets. Decades of targeted molecular and biological studies have led to numerous pathway models of developmental and disease related processes. However, so far no global models have been derived from pathways, capable...

Transitions from Trees to Cycles in Adaptive Flow Networks

DEFF Research Database (Denmark)

Martens, Erik Andreas; Klemm, Konstantin

2017-01-01

-world transport networks exhibit both tree-like motifs and cycles. When the network is subject to load fluctuations, the presence of cyclic motifs may help to reduce flow fluctuations and, thus, render supply in the network more robust. While previous studies considered network topology via optimization...... principles, here, we take a dynamical systems approach and study a simple model of a flow network with dynamically adapting weights (conductances). We assume a spatially non-uniform distribution of rapidly fluctuating loads in the sinks and investigate what network configurations are dynamically stable......Transport networks are crucial to the functioning of natural and technological systems. Nature features transport networks that are adaptive over a vast range of parameters, thus providing an impressive level of robustness in supply. Theoretical and experimental studies have found that real...

Decrease of dynamic loads in mobile energy means

Science.gov (United States)

Polivaev, O. I.; Gorban, L. K.; Vorohobin, A. V.; Vedrinsky, O. S.

2018-03-01

The increase in the productivity of machine and tractor units is possible due to the increase in operating speeds, this leads to the emergence of increased dynamic loads in the system “engine-transmission-propulsion unit-soil”, which worsens the performance of machine-tractor aggregates. To reduce fluctuations in the “engine-transmission” system, special vibration dampers are used, which installed in close proximity to the engine and protect well the transmission from uneven engine operation; however, such dampers practically do not eliminate the oscillations of external loads. Reducing dynamic loads on the transmission and the mobile power engine (MPE) is an important issue directly related to improving the performance, reliability and durability of the tractor, as well as reducing the slippage of the drive wheels. In order to reduce effectively dynamic loads on the transmission and on the MPE, it is necessary to introduce resilient damping elements closer to the sources of oscillations, namely, to the driving wheels. At the same time, the elastic-damping element should provide accumulation of vibration energy caused by external influences and have a large energy capacity. The installation of an elastic-damping element in the final link of the tractor transmission ensures a reduction in the magnitude of external influences, thereby protecting the engine and transmission from large dynamic loads, and allows one to reduce the slippage of the propellers, which has a positive effect on the traction and energy characteristics of the tractor. Traction tests of the LTP-55 tractor on a concrete road showed that the use of an elasto-damping drive makes it possible to increase the maximum tractive power from 33.5 to 35.3 kW and to reduce the slipping of propellers by 12-30%, the specific fuel consumption by 6-10%. When driving on stubble, the use of an elastic-damping drive increases the maximum tractive power from 25 to 26 kW, reduces the skidding of propellers by

SDN-Enabled Dynamic Feedback Control and Sensing in Agile Optical Networks

Science.gov (United States)

Lin, Likun

Fiber optic networks are no longer just pipelines for transporting data in the long haul backbone. Exponential growth in traffic in metro-regional areas has pushed higher capacity fiber toward the edge of the network, and highly dynamic patterns of heterogeneous traffic have emerged that are often bursty, severely stressing the historical "fat and dumb pipe" static optical network, which would need to be massively over-provisioned to deal with these loads. What is required is a more intelligent network with a span of control over the optical as well as electrical transport mechanisms which enables handling of service requests in a fast and efficient way that guarantees quality of service (QoS) while optimizing capacity efficiency. An "agile" optical network is a reconfigurable optical network comprised of high speed intelligent control system fed by real-time in situ network sensing. It provides fast response in the control and switching of optical signals in response to changing traffic demands and network conditions. This agile control of optical signals is enabled by pushing switching decisions downward in the network stack to the physical layer. Implementing such agility is challenging due to the response dynamics and interactions of signals in the physical layer. Control schemes must deal with issues such as dynamic power equalization, EDFA transients and cascaded noise effects, impairments due to self-phase modulation and dispersion, and channel-to-channel cross talk. If these issues are not properly predicted and mitigated, attempts at dynamic control can drive the optical network into an unstable state. In order to enable high speed actuation of signal modulators and switches, the network controller must be able to make decisions based on predictive models. In this thesis, we consider how to take advantage of Software Defined Networking (SDN) capabilities for network reconfiguration, combined with embedded models that access updates from deployed network

Convergent dynamics for multistable delayed neural networks

International Nuclear Information System (INIS)

Shih, Chih-Wen; Tseng, Jui-Pin

2008-01-01

This investigation aims at developing a methodology to establish convergence of dynamics for delayed neural network systems with multiple stable equilibria. The present approach is general and can be applied to several network models. We take the Hopfield-type neural networks with both instantaneous and delayed feedbacks to illustrate the idea. We shall construct the complete dynamical scenario which comprises exactly 2 n stable equilibria and exactly (3 n − 2 n ) unstable equilibria for the n-neuron network. In addition, it is shown that every solution of the system converges to one of the equilibria as time tends to infinity. The approach is based on employing the geometrical structure of the network system. Positively invariant sets and componentwise dynamical properties are derived under the geometrical configuration. An iteration scheme is subsequently designed to confirm the convergence of dynamics for the system. Two examples with numerical simulations are arranged to illustrate the present theory

Design of dynamic loading support on high temperature pipe

International Nuclear Information System (INIS)

Sitandung, Y.B.; Bandriyana, B.

2002-01-01

As a follow up to pipe stress analysis result caused by high temperature operation loading, a design of dynamic loading support was made. The type of variable and constant support as acceptable choosing are applicated for reduce of over stress and over load on piping system. Analysis line schedule of AP600 as an example with apply three dynamic loading support (two type variable and one type constant support). The pre-design of the third support above are based on analysis result with follow the support catalog and field condition wherein its supports are installed. To guarantee the performance and accurate of the support, checking is performed for spring working rate tolerance, support variability and swing angle. The design results of variable spring are loads, size, working rate, type tolerance, spring rate, variability, long and sway angle with each values 5000; 15; 1,25; VM; 0.655; 1080; 0.114; 114,5; 0,48 for S1 and 2045; 12; 0,583; VS; 0,237; 900; 0,132; 130; 0,34 for S3

Dynamic Evolution Model Based on Social Network Services

Science.gov (United States)

Xiong, Xi; Gou, Zhi-Jian; Zhang, Shi-Bin; Zhao, Wen

2013-11-01

Based on the analysis of evolutionary characteristics of public opinion in social networking services (SNS), in the paper we propose a dynamic evolution model, in which opinions are coupled with topology. This model shows the clustering phenomenon of opinions in dynamic network evolution. The simulation results show that the model can fit the data from a social network site. The dynamic evolution of networks accelerates the opinion, separation and aggregation. The scale and the number of clusters are influenced by confidence limit and rewiring probability. Dynamic changes of the topology reduce the number of isolated nodes, while the increased confidence limit allows nodes to communicate more sufficiently. The two effects make the distribution of opinion more neutral. The dynamic evolution of networks generates central clusters with high connectivity and high betweenness, which make it difficult to control public opinions in SNS.

Traffic Dynamics on Complex Networks: A Survey

Directory of Open Access Journals (Sweden)

Shengyong Chen

2012-01-01

Full Text Available Traffic dynamics on complex networks are intriguing in recent years due to their practical implications in real communication networks. In this survey, we give a brief review of studies on traffic routing dynamics on complex networks. Strategies for improving transport efficiency, including designing efficient routing strategies and making appropriate adjustments to the underlying network structure, are introduced in this survey. Finally, a few open problems are discussed in this survey.

Analysis of recurrent neural networks for short-term energy load forecasting

Science.gov (United States)

Di Persio, Luca; Honchar, Oleksandr

2017-11-01

Short-term forecasts have recently gained an increasing attention because of the rise of competitive electricity markets. In fact, short-terms forecast of possible future loads turn out to be fundamental to build efficient energy management strategies as well as to avoid energy wastage. Such type of challenges are difficult to tackle both from a theoretical and applied point of view. Latter tasks require sophisticated methods to manage multidimensional time series related to stochastic phenomena which are often highly interconnected. In the present work we first review novel approaches to energy load forecasting based on recurrent neural network, focusing our attention on long/short term memory architectures (LSTMs). Such type of artificial neural networks have been widely applied to problems dealing with sequential data such it happens, e.g., in socio-economics settings, for text recognition purposes, concerning video signals, etc., always showing their effectiveness to model complex temporal data. Moreover, we consider different novel variations of basic LSTMs, such as sequence-to-sequence approach and bidirectional LSTMs, aiming at providing effective models for energy load data. Last but not least, we test all the described algorithms on real energy load data showing not only that deep recurrent networks can be successfully applied to energy load forecasting, but also that this approach can be extended to other problems based on time series prediction.

A study on the evolution of crack networks under thermal fatigue loading

International Nuclear Information System (INIS)

Kamaya, Masayuki; Taheri, Said

2008-01-01

The crack network is a typical cracking morphology caused by thermal fatigue loading. It was pointed out that the crack network appeared under relatively small temperature fluctuations and did not grow deeply. In this study, the mechanism of evolution of crack network and its influence on crack growth was examined by numerical calculation. First, the stress field near two interacting cracks was investigated. It was shown that there are stress-concentration and stress-shielding zones around interacting cracks, and that cracks can form a network under the bi-axial stress condition. Secondly, a Monte Carlo simulation was developed in order to simulate the initiation and growth of cracks under thermal fatigue loading and the evolution of the crack network. The local stress field formed by pre-existing cracks was evaluated by the body force method and its role in the initiation and growth of cracks was considered. The simulation could simulate the evolution of the crack network and change in number of cracks observed in the experiments. It was revealed that reduction in the stress intensity factor due to stress feature in the depth direction under high cycle thermal fatigue loading plays an important role in the evolution of the crack network and that mechanical interaction between cracks in the network affects initiation rather than growth of cracks. The crack network appears only when the crack growth in the depth direction is interrupted. It was concluded that the emergence of the crack network is preferable for the structural integrity of cracked components

Characterization of dynamic loads on the LMFBR rotating shield

International Nuclear Information System (INIS)

Morris, E.

1979-01-01

The rotating shields structure is a potential weak point of some current designs of primary containment against postulated whole core explosions. The calculation of the effect of transient loads on this structure, resulting from such an explosion, is therefore important in developing a safety case. The transient loads are usually calculated by computer codes such as ASTARTE, SEURBNUK, REXCO or ICECO and the effect of these loads on the structure by a suitable finite element code. Such procedure can be lengthly and costly. The present paper proposed a procedure which allows the consequences of changes in the transient loads, resulting from design changes for example, to be quickly and simply gauged. The load-impulse method of characterizing dynamic response of a structural system is well established. Provided loads with a similar temporal variation are compared, it can be shown that the dynamic response depends on only two features of the load, an average load and a time intregrated load or impulse. The scope of this approach has been extended by Youngdahl who has shown, for structures which deform in a rigid-plastic manner, that complex laoding histories can be equated to a rectangular form of loading, in a precise manner for simple structures and in an approximate manner for more complicated structures. This paper proposes that the failure characteristics of the rotating shields for which extensive plastic deformation is involved, be calculated for rectangular type loadings. The complex transient loadings calculated for various explosions and various changes in the primary vessel design can then be reduced to an equivalent rectangular form and the consequencial response of the shields structure deduced. (orig.)

Using Network Dynamical Influence to Drive Consensus

Science.gov (United States)

Punzo, Giuliano; Young, George F.; MacDonald, Malcolm; Leonard, Naomi E.

2016-05-01

Consensus and decision-making are often analysed in the context of networks, with many studies focusing attention on ranking the nodes of a network depending on their relative importance to information routing. Dynamical influence ranks the nodes with respect to their ability to influence the evolution of the associated network dynamical system. In this study it is shown that dynamical influence not only ranks the nodes, but also provides a naturally optimised distribution of effort to steer a network from one state to another. An example is provided where the “steering” refers to the physical change in velocity of self-propelled agents interacting through a network. Distinct from other works on this subject, this study looks at directed and hence more general graphs. The findings are presented with a theoretical angle, without targeting particular applications or networked systems; however, the framework and results offer parallels with biological flocks and swarms and opportunities for design of technological networks.

Features wear nodes mechanization wing aircraft operating under dynamic loads

Directory of Open Access Journals (Sweden)

А.М. Хімко

2009-03-01

Full Text Available  The conducted researches of titanic alloy ВТ-22 at dynamic loading with cycled sliding and dynamic loading in conditions of rolling with slipping. It is established that roller jamming in the carriage increases wear of rod of mechanization of a wing to twenty times. The optimum covering for strengthening wearied sites and restoration of working surfaces of wing’s mechanization rod is defined.

LOGISTIC NETWORK REGRESSION FOR SCALABLE ANALYSIS OF NETWORKS WITH JOINT EDGE/VERTEX DYNAMICS.

Science.gov (United States)

Almquist, Zack W; Butts, Carter T

2014-08-01

Change in group size and composition has long been an important area of research in the social sciences. Similarly, interest in interaction dynamics has a long history in sociology and social psychology. However, the effects of endogenous group change on interaction dynamics are a surprisingly understudied area. One way to explore these relationships is through social network models. Network dynamics may be viewed as a process of change in the edge structure of a network, in the vertex set on which edges are defined, or in both simultaneously. Although early studies of such processes were primarily descriptive, recent work on this topic has increasingly turned to formal statistical models. Although showing great promise, many of these modern dynamic models are computationally intensive and scale very poorly in the size of the network under study and/or the number of time points considered. Likewise, currently used models focus on edge dynamics, with little support for endogenously changing vertex sets. Here, the authors show how an existing approach based on logistic network regression can be extended to serve as a highly scalable framework for modeling large networks with dynamic vertex sets. The authors place this approach within a general dynamic exponential family (exponential-family random graph modeling) context, clarifying the assumptions underlying the framework (and providing a clear path for extensions), and they show how model assessment methods for cross-sectional networks can be extended to the dynamic case. Finally, the authors illustrate this approach on a classic data set involving interactions among windsurfers on a California beach.

A STUDY ON DYNAMIC LOAD HISTORY RECONSTRUCTION USING PSEUDO-INVERSE METHODS

OpenAIRE

Santos, Ariane Rebelato Silva dos; Marczak, Rogério José

2017-01-01

Considering that the vibratory forces generally cannot be measured directly at the interface of two bodies, an inverse method is studied in the present work to recover the load history in such cases. The proposed technique attempts to reconstruct the dynamic loads history by using a frequency domain analysis and Moore-Penrose pseudo-inverses of the frequency response function (FRF) of the system. The methodology consists in applying discrete dynamic loads on a finite element model in the time...

Learning State Space Dynamics in Recurrent Networks

Science.gov (United States)

Simard, Patrice Yvon

Fully recurrent (asymmetrical) networks can be used to learn temporal trajectories. The network is unfolded in time, and backpropagation is used to train the weights. The presence of recurrent connections creates internal states in the system which vary as a function of time. The resulting dynamics can provide interesting additional computing power but learning is made more difficult by the existence of internal memories. This study first exhibits the properties of recurrent networks in terms of convergence when the internal states of the system are unknown. A new energy functional is provided to change the weights of the units in order to the control the stability of the fixed points of the network's dynamics. The power of the resultant algorithm is illustrated with the simulation of a content addressable memory. Next, the more general case of time trajectories on a recurrent network is studied. An application is proposed in which trajectories are generated to draw letters as a function of an input. In another application of recurrent systems, a neural network certain temporal properties observed in human callosally sectioned brains. Finally the proposed algorithm for stabilizing dynamics around fixed points is extended to one for stabilizing dynamics around time trajectories. Its effects are illustrated on a network which generates Lisajous curves.

Controlling the dynamics of multi-state neural networks

International Nuclear Information System (INIS)

Jin, Tao; Zhao, Hong

2008-01-01

In this paper, we first analyze the distribution of local fields (DLF) which is induced by the memory patterns in the Q-Ising model. It is found that the structure of the DLF is closely correlated with the network dynamics and the system performance. However, the design rule adopted in the Q-Ising model, like the other rules adopted for multi-state neural networks with associative memories, cannot be applied to directly control the DLF for a given set of memory patterns, and thus cannot be applied to further study the relationships between the structure of the DLF and the dynamics of the network. We then extend a design rule, which was presented recently for designing binary-state neural networks, to make it suitable for designing general multi-state neural networks. This rule is able to control the structure of the DLF as expected. We show that controlling the DLF not only can affect the dynamic behaviors of the multi-state neural networks for a given set of memory patterns, but also can improve the storage capacity. With the change of the DLF, the network shows very rich dynamic behaviors, such as the 'chaos phase', the 'memory phase', and the 'mixture phase'. These dynamic behaviors are also observed in the binary-state neural networks; therefore, our results imply that they may be the universal behaviors of feedback neural networks

A Dynamic Model for Load Balancing in Cloud Infrastructure

Directory of Open Access Journals (Sweden)

Jitendra Bhagwandas Bhatia

2015-08-01

Full Text Available This paper analysis various challenges faced in optimizing computing resource utilization via load balancing and presents a platform-independent model for load balancing which targets high availability of resources, low SLA (Service Level agreement violations and saves power. To achieve this, incoming requests are monitored for sudden burst, a prediction model is employed to maintain high availability and a power-aware algorithm is applied for choosing a suitable physical node for a virtual host. The proposed dynamic load balancing model provides a way to conflicting goals of saving power and maintaining high resource availability.For anyone building a private, public or hybrid IaaS cloud infrastructure, load balancing of virtual hosts on a limited number of physical nodes, becomes a crucial aspect. This paper analysis various challenges faced in optimizing computing resource utilization via load balancing and presents a platform independent model for load balancing which targets high availability of resources, low SLA (Service Level agreement violations and saves power. To achieve this, incoming requests are monitored for sudden burst, prediction model is employed to maintain high availability and power aware algorithm is applied for choosing a suitable physical node for virtual host. The proposed dynamic load balancing model provides a way to conflicting goals of saving power and maintaining high resource availability.

Intelligent harmonic load model based on neural networks

Science.gov (United States)

Ji, Pyeong-Shik; Lee, Dae-Jong; Lee, Jong-Pil; Park, Jae-Won; Lim, Jae-Yoon

2007-12-01

In this study, we developed a RBFNs(Radial Basis Function Networks) based load modeling method with harmonic components. The developed method implemented by using harmonic information as well as fundamental frequency and voltage which are essential input factors in conventional method. Thus, the proposed method makes it possible to effectively estimate load characteristics in power lines with harmonics. The RBFNs have certain advantage such as simple structure and rapid computation ability compared with multilayer perceptron which is extensively applied for load modeling. To show the effectiveness, the proposed method has been intensively tested with various dataset acquired under the different frequency and voltage and compared it with conventional methods such as polynominal 2nd equation method, MLP and RBF without considering harmonic components.

Immune networks: multi-tasking capabilities at medium load

Science.gov (United States)

Agliari, E.; Annibale, A.; Barra, A.; Coolen, A. C. C.; Tantari, D.

2013-08-01

Associative network models featuring multi-tasking properties have been introduced recently and studied in the low-load regime, where the number P of simultaneously retrievable patterns scales with the number N of nodes as P ˜ log N. In addition to their relevance in artificial intelligence, these models are increasingly important in immunology, where stored patterns represent strategies to fight pathogens and nodes represent lymphocyte clones. They allow us to understand the crucial ability of the immune system to respond simultaneously to multiple distinct antigen invasions. Here we develop further the statistical mechanical analysis of such systems, by studying the medium-load regime, P ˜ Nδ with δ ∈ (0, 1]. We derive three main results. First, we reveal the nontrivial architecture of these networks: they exhibit a high degree of modularity and clustering, which is linked to their retrieval abilities. Second, by solving the model we demonstrate for δ frameworks are required to achieve effective retrieval.

Loading dynamics of a sliding DNA clamp.

KAUST Repository

Cho, Won-Ki; Jergic, Slobodan; Kim, Daehyung; Dixon, Nicholas E; Lee, Jong-Bong

2014-01-01

8° during clamp closure. The single-molecule polarization and FRET studies thus revealed the real-time dynamics of the ATP-hydrolysis-dependent 3D conformational change of the β clamp during loading at a ss/dsDNA junction.

Dynamic Intelligent Feedback Scheduling in Networked Control Systems

Directory of Open Access Journals (Sweden)

Hui-ying Chen

2013-01-01

Full Text Available For the networked control system with limited bandwidth and flexible workload, a dynamic intelligent feedback scheduling strategy is proposed. Firstly, a monitor is used to acquire the current available network bandwidth. Then, the new available bandwidth in the next interval is predicted by using LS_SVM approach. At the same time, the dynamic performance indices of all control loops are obtained with a two-dimensional fuzzy logic modulator. Finally, the predicted network bandwidth is dynamically allocated by the bandwidth manager and the priority allocator in terms of the loops' dynamic performance indices. Simulation results show that the sampling periods and priorities of control loops are adjusted timely according to the network workload condition and the dynamic performance of control loops, which make the system running in the optimal state all the time.

Dynamic Trust Management for Mobile Networks and Its Applications

Science.gov (United States)

Bao, Fenye

2013-01-01

Trust management in mobile networks is challenging due to dynamically changing network environments and the lack of a centralized trusted authority. In this dissertation research, we "design" and "validate" a class of dynamic trust management protocols for mobile networks, and demonstrate the utility of dynamic trust management…

Using adaptive network based fuzzy inference system to forecast regional electricity loads

International Nuclear Information System (INIS)

Ying, L.-C.; Pan, M.-C.

2008-01-01

Since accurate regional load forecasting is very important for improvement of the management performance of the electric industry, various regional load forecasting methods have been developed. The purpose of this study is to apply the adaptive network based fuzzy inference system (ANFIS) model to forecast the regional electricity loads in Taiwan and demonstrate the forecasting performance of this model. Based on the mean absolute percentage errors and statistical results, we can see that the ANFIS model has better forecasting performance than the regression model, artificial neural network (ANN) model, support vector machines with genetic algorithms (SVMG) model, recurrent support vector machines with genetic algorithms (RSVMG) model and hybrid ellipsoidal fuzzy systems for time series forecasting (HEFST) model. Thus, the ANFIS model is a promising alternative for forecasting regional electricity loads

Using adaptive network based fuzzy inference system to forecast regional electricity loads

Energy Technology Data Exchange (ETDEWEB)

Ying, Li-Chih [Department of Marketing Management, Central Taiwan University of Science and Technology, 11, Pu-tzu Lane, Peitun, Taichung City 406 (China); Pan, Mei-Chiu [Graduate Institute of Management Sciences, Nanhua University, 32, Chung Keng Li, Dalin, Chiayi 622 (China)

2008-02-15

Since accurate regional load forecasting is very important for improvement of the management performance of the electric industry, various regional load forecasting methods have been developed. The purpose of this study is to apply the adaptive network based fuzzy inference system (ANFIS) model to forecast the regional electricity loads in Taiwan and demonstrate the forecasting performance of this model. Based on the mean absolute percentage errors and statistical results, we can see that the ANFIS model has better forecasting performance than the regression model, artificial neural network (ANN) model, support vector machines with genetic algorithms (SVMG) model, recurrent support vector machines with genetic algorithms (RSVMG) model and hybrid ellipsoidal fuzzy systems for time series forecasting (HEFST) model. Thus, the ANFIS model is a promising alternative for forecasting regional electricity loads. (author)

Analysis of pile foundations under dynamic loads

International Nuclear Information System (INIS)

Waas, G.; Hartmann, H.G.

1981-01-01

A method is presented for the analysis of pile foundations which are subjected to horizontal dynamic loads from earthquakes, airplane impact, gas explosion or other sources. The motion of the pile cap and the pile forces are computed. - The loads may be applied to the pile cap or directly to the piles (e.g. by earthquake wave motion). The soil may be stratified and is considered to be an elastic or visco-elastic medium. The piles are assumed vertical. The method makes use of an approximate fundamental solution for displacements caused by a dynamic point load in a layered visco-elastic medium. The approximation involves a discretization of the medium in the vertical direction. In horizontal directions the medium is treated by continuum theory. The soil medium supports each pile at about 10 to 20 nodes. A dynamic flexiblity matrix for the soil is derived which relates the elastic, damping and inertial forces of the soil to the displacements at each node. It includes effects of radiation damping. All piles are coupled through the soil flexibility matrix. The piles are modelled by beam elements. Transient response is computed using fast discrete Fourier transforms. The arrangement of the piles is arbitrary. However, simple and double symmetry can be accounted for by the computer program. When the pile arrangement is axisymmetric, the degrees of freedom can be reduced to only those of two piles per ring. The influence of the number of piles and the influence of the pile spacing on group stiffness and on pile forces is presented for two soil profiles. Dynamic effects on pile forces of a foundation for a reactor building are studied. They are significant when soils are soft. (orig.)

Adaptive-network models of collective dynamics

Science.gov (United States)

Zschaler, G.

2012-09-01

Complex systems can often be modelled as networks, in which their basic units are represented by abstract nodes and the interactions among them by abstract links. This network of interactions is the key to understanding emergent collective phenomena in such systems. In most cases, it is an adaptive network, which is defined by a feedback loop between the local dynamics of the individual units and the dynamical changes of the network structure itself. This feedback loop gives rise to many novel phenomena. Adaptive networks are a promising concept for the investigation of collective phenomena in different systems. However, they also present a challenge to existing modelling approaches and analytical descriptions due to the tight coupling between local and topological degrees of freedom. In this work, which is essentially my PhD thesis, I present a simple rule-based framework for the investigation of adaptive networks, using which a wide range of collective phenomena can be modelled and analysed from a common perspective. In this framework, a microscopic model is defined by the local interaction rules of small network motifs, which can be implemented in stochastic simulations straightforwardly. Moreover, an approximate emergent-level description in terms of macroscopic variables can be derived from the microscopic rules, which we use to analyse the system's collective and long-term behaviour by applying tools from dynamical systems theory. We discuss three adaptive-network models for different collective phenomena within our common framework. First, we propose a novel approach to collective motion in insect swarms, in which we consider the insects' adaptive interaction network instead of explicitly tracking their positions and velocities. We capture the experimentally observed onset of collective motion qualitatively in terms of a bifurcation in this non-spatial model. We find that three-body interactions are an essential ingredient for collective motion to emerge

Deep Constrained Siamese Hash Coding Network and Load-Balanced Locality-Sensitive Hashing for Near Duplicate Image Detection.

Science.gov (United States)

Hu, Weiming; Fan, Yabo; Xing, Junliang; Sun, Liang; Cai, Zhaoquan; Maybank, Stephen

2018-09-01

We construct a new efficient near duplicate image detection method using a hierarchical hash code learning neural network and load-balanced locality-sensitive hashing (LSH) indexing. We propose a deep constrained siamese hash coding neural network combined with deep feature learning. Our neural network is able to extract effective features for near duplicate image detection. The extracted features are used to construct a LSH-based index. We propose a load-balanced LSH method to produce load-balanced buckets in the hashing process. The load-balanced LSH significantly reduces the query time. Based on the proposed load-balanced LSH, we design an effective and feasible algorithm for near duplicate image detection. Extensive experiments on three benchmark data sets demonstrate the effectiveness of our deep siamese hash encoding network and load-balanced LSH.

Discrete dynamic modeling of cellular signaling networks.

Science.gov (United States)

Albert, Réka; Wang, Rui-Sheng

2009-01-01

Understanding signal transduction in cellular systems is a central issue in systems biology. Numerous experiments from different laboratories generate an abundance of individual components and causal interactions mediating environmental and developmental signals. However, for many signal transduction systems there is insufficient information on the overall structure and the molecular mechanisms involved in the signaling network. Moreover, lack of kinetic and temporal information makes it difficult to construct quantitative models of signal transduction pathways. Discrete dynamic modeling, combined with network analysis, provides an effective way to integrate fragmentary knowledge of regulatory interactions into a predictive mathematical model which is able to describe the time evolution of the system without the requirement for kinetic parameters. This chapter introduces the fundamental concepts of discrete dynamic modeling, particularly focusing on Boolean dynamic models. We describe this method step-by-step in the context of cellular signaling networks. Several variants of Boolean dynamic models including threshold Boolean networks and piecewise linear systems are also covered, followed by two examples of successful application of discrete dynamic modeling in cell biology.

Solving Dynamic Battlespace Movement Problems Using Dynamic Distributed Computer Networks

National Research Council Canada - National Science Library

Bradford, Robert

2000-01-01

.... The thesis designs a system using this architecture that invokes operations research network optimization algorithms to solve problems involving movement of people and equipment over dynamic road networks...

Functional asynchronous networks: Factorization of dynamics and function

Directory of Open Access Journals (Sweden)

Bick Christian

2016-01-01

Full Text Available In this note we describe the theory of functional asynchronous networks and one of the main results, the Modularization of Dynamics Theorem, which for a large class of functional asynchronous networks gives a factorization of dynamics in terms of constituent subnetworks. For these networks we can give a complete description of the network function in terms of the function of the events comprising the network and thereby answer a question originally raised by Alon in the context of biological networks.

Competing dynamic phases of active polymer networks

Science.gov (United States)

Freedman, Simon; Banerjee, Shiladitya; Dinner, Aaron R.

Recent experiments on in-vitro reconstituted assemblies of F-actin, myosin-II motors, and cross-linking proteins show that tuning local network properties can changes the fundamental biomechanical behavior of the system. For example, by varying cross-linker density and actin bundle rigidity, one can switch between contractile networks useful for reshaping cells, polarity sorted networks ideal for directed molecular transport, and frustrated networks with robust structural properties. To efficiently investigate the dynamic phases of actomyosin networks, we developed a coarse grained non-equilibrium molecular dynamics simulation of model semiflexible filaments, molecular motors, and cross-linkers with phenomenologically defined interactions. The simulation's accuracy was verified by benchmarking the mechanical properties of its individual components and collective behavior against experimental results at the molecular and network scales. By adjusting the model's parameters, we can reproduce the qualitative phases observed in experiment and predict the protein characteristics where phase crossovers could occur in collective network dynamics. Our model provides a framework for understanding cells' multiple uses of actomyosin networks and their applicability in materials research. Supported by the Department of Defense (DoD) through the National Defense Science & Engineering Graduate Fellowship (NDSEG) Program.

Effects of moving dynamic tyre loads on tyre-pavement contact stresses

CSIR Research Space (South Africa)

Steyn, WJvdM

2002-01-01

Full Text Available The purpose of this paper is to indicate the effect that moving dynamic tyre loads has on the tyre-pavement contact stresses used in pavement analysis. Traditionally tyre loads (in pavement analysis) are modelled as constant loads applied through...

Green IGP Link Weights for Energy-efficiency and Load-balancing in IP Backbone Networks

OpenAIRE

Francois, Frederic; Wang, Ning; Moessner, Klaus; Georgoulas, Stylianos; Xu, Ke

2013-01-01

The energy consumption of backbone networks has become a primary concern for network operators and regulators due to the pervasive deployment of wired backbone networks to meet the requirements of bandwidth-hungry applications. While traditional optimization of IGP link weights has been used in IP based load-balancing operations, in this paper we introduce a novel link weight setting algorithm, the Green Load-balancing Algorithm (GLA), which is able to jointly optimize both energy efficiency ...

DYNAMIC TIME HISTORY ANALYSIS OF BLAST RESISTANT DOOR USING BLAST LOAD MODELED AS IMPACT LOAD

Directory of Open Access Journals (Sweden)

Y. A. Pranata

2012-06-01

Full Text Available A blast resistant single door was designed to withstand a 0.91 bar blast pressure and 44 ms blast duration. The analysis was done using Dynamic Time History Analysis using Blast Load modeled as Impact Load for given duration. The material properties used have been modified to accommodate dynamic effects. The analysis was done using dynamic finite element method (fem for time of the blast duration, and the maximum/minimum internal forces and displacement were taken from the time history output, in order to know the behavior under blast load and estimate the safety margin of the door. Results obtained from this research indicated that the maximum z-displacement is 1.709 mm, while in the term of serviceability, the permitted is 25 mm. The maximum reaction force is 73,960 N, while the maximum anchor capacity is 82,069 N. On blast condition, the maximum frame stress is 71.71 MPa, the maximum hinge shear stress is 45.28 MPa. While on rebound condition, the maximum frame stress is 172.11 MPa, the maximum hinge shear stress is 29.46 MPa. The maximum door edge rotation is 0.44 degree, which is not exceed the permitted boundary (1.2 degree. Keywords: Dynamic time history, blast resistant door, single door, finite element method.

Dynamic behaviors in directed networks

International Nuclear Information System (INIS)

Park, Sung Min; Kim, Beom Jun

2006-01-01

Motivated by the abundance of directed synaptic couplings in a real biological neuronal network, we investigate the synchronization behavior of the Hodgkin-Huxley model in a directed network. We start from the standard model of the Watts-Strogatz undirected network and then change undirected edges to directed arcs with a given probability, still preserving the connectivity of the network. A generalized clustering coefficient for directed networks is defined and used to investigate the interplay between the synchronization behavior and underlying structural properties of directed networks. We observe that the directedness of complex networks plays an important role in emerging dynamical behaviors, which is also confirmed by a numerical study of the sociological game theoretic voter model on directed networks

Power Quality Improvement Using an Enhanced Network-Side-Shunt-Connected Dynamic Voltage Restorer

Science.gov (United States)

Fereidouni, Alireza; Masoum, Mohammad A. S.; Moghbel, Moayed

2015-10-01

Among the four basic dynamic voltage restorer (DVR) topologies, the network-side shunt-connected DVR (NSSC-DVR) has a relatively poor performance and is investigated in this paper. A new configuration is proposed and implemented for NSSC-DVR to enhance its performance in compensating (un)symmetrical deep and long voltage sags and mitigate voltage harmonics. The enhanced NSSC-DVR model includes a three-phase half-bridge semi-controlled network-side-shunt-connected rectifier and a three-phase full-bridge series-connected inverter implemented with a back-to-back configuration through a bidirectional buck-boost converter. The network-side-shunt-connected rectifier is employed to inject/draw the required energy by NSSC-DVR to restore the load voltage to its pre-fault value under sag/swell conditions. The buck-boost converter is responsible for maintaining the DC-link voltage of the series-connected inverter at its designated value in order to improve the NSSC-DVR capability in compensating deep and long voltage sags/swells. The full-bridge series-connected inverter permits to compensate unbalance voltage sags containing zero-sequence component. The harmonic compensation of the load voltage is achieved by extracting harmonics from the distorted network voltage using an artificial neural network (ANN) method called adaptive linear neuron (Adaline) strategy. Detailed simulations are performed by SIMULINK/MATLAB software for six case studies to verify the highly robustness of the proposed NSSC-DVR model under various conditions.

Identify Dynamic Network Modules with Temporal and Spatial Constraints

Energy Technology Data Exchange (ETDEWEB)

Jin, R; McCallen, S; Liu, C; Almaas, E; Zhou, X J

2007-09-24

Despite the rapid accumulation of systems-level biological data, understanding the dynamic nature of cellular activity remains a difficult task. The reason is that most biological data are static, or only correspond to snapshots of cellular activity. In this study, we explicitly attempt to detangle the temporal complexity of biological networks by using compilations of time-series gene expression profiling data.We define a dynamic network module to be a set of proteins satisfying two conditions: (1) they form a connected component in the protein-protein interaction (PPI) network; and (2) their expression profiles form certain structures in the temporal domain. We develop the first efficient mining algorithm to discover dynamic modules in a temporal network, as well as frequently occurring dynamic modules across many temporal networks. Using yeast as a model system, we demonstrate that the majority of the identified dynamic modules are functionally homogeneous. Additionally, many of them provide insight into the sequential ordering of molecular events in cellular systems. We further demonstrate that identifying frequent dynamic network modules can significantly increase the signal to noise separation, despite the fact that most dynamic network modules are highly condition-specific. Finally, we note that the applicability of our algorithm is not limited to the study of PPI systems, instead it is generally applicable to the combination of any type of network and time-series data.

Dynamic Sensor Network Reprogramming using SensorScheme

NARCIS (Netherlands)

Evers, L.; Havinga, Paul J.M.; Kuper, Jan

2007-01-01

Building wireless sensor network applications is a challenging task, and it has become apparent that it is crucial for many sensor networks to be able to load or update the application after deployment. Since communication is a scarce resource and costly in terms of energy, it is important to

Deep Neural Network Based Demand Side Short Term Load Forecasting

Directory of Open Access Journals (Sweden)

Seunghyoung Ryu

2016-12-01

Full Text Available In the smart grid, one of the most important research areas is load forecasting; it spans from traditional time series analyses to recent machine learning approaches and mostly focuses on forecasting aggregated electricity consumption. However, the importance of demand side energy management, including individual load forecasting, is becoming critical. In this paper, we propose deep neural network (DNN-based load forecasting models and apply them to a demand side empirical load database. DNNs are trained in two different ways: a pre-training restricted Boltzmann machine and using the rectified linear unit without pre-training. DNN forecasting models are trained by individual customer’s electricity consumption data and regional meteorological elements. To verify the performance of DNNs, forecasting results are compared with a shallow neural network (SNN, a double seasonal Holt–Winters (DSHW model and the autoregressive integrated moving average (ARIMA. The mean absolute percentage error (MAPE and relative root mean square error (RRMSE are used for verification. Our results show that DNNs exhibit accurate and robust predictions compared to other forecasting models, e.g., MAPE and RRMSE are reduced by up to 17% and 22% compared to SNN and 9% and 29% compared to DSHW.

Network Physiology: How Organ Systems Dynamically Interact

Science.gov (United States)

Bartsch, Ronny P.; Liu, Kang K. L.; Bashan, Amir; Ivanov, Plamen Ch.

2015-01-01

We systematically study how diverse physiologic systems in the human organism dynamically interact and collectively behave to produce distinct physiologic states and functions. This is a fundamental question in the new interdisciplinary field of Network Physiology, and has not been previously explored. Introducing the novel concept of Time Delay Stability (TDS), we develop a computational approach to identify and quantify networks of physiologic interactions from long-term continuous, multi-channel physiological recordings. We also develop a physiologically-motivated visualization framework to map networks of dynamical organ interactions to graphical objects encoded with information about the coupling strength of network links quantified using the TDS measure. Applying a system-wide integrative approach, we identify distinct patterns in the network structure of organ interactions, as well as the frequency bands through which these interactions are mediated. We establish first maps representing physiologic organ network interactions and discover basic rules underlying the complex hierarchical reorganization in physiologic networks with transitions across physiologic states. Our findings demonstrate a direct association between network topology and physiologic function, and provide new insights into understanding how health and distinct physiologic states emerge from networked interactions among nonlinear multi-component complex systems. The presented here investigations are initial steps in building a first atlas of dynamic interactions among organ systems. PMID:26555073

Network Physiology: How Organ Systems Dynamically Interact.

Science.gov (United States)

Bartsch, Ronny P; Liu, Kang K L; Bashan, Amir; Ivanov, Plamen Ch

2015-01-01

We systematically study how diverse physiologic systems in the human organism dynamically interact and collectively behave to produce distinct physiologic states and functions. This is a fundamental question in the new interdisciplinary field of Network Physiology, and has not been previously explored. Introducing the novel concept of Time Delay Stability (TDS), we develop a computational approach to identify and quantify networks of physiologic interactions from long-term continuous, multi-channel physiological recordings. We also develop a physiologically-motivated visualization framework to map networks of dynamical organ interactions to graphical objects encoded with information about the coupling strength of network links quantified using the TDS measure. Applying a system-wide integrative approach, we identify distinct patterns in the network structure of organ interactions, as well as the frequency bands through which these interactions are mediated. We establish first maps representing physiologic organ network interactions and discover basic rules underlying the complex hierarchical reorganization in physiologic networks with transitions across physiologic states. Our findings demonstrate a direct association between network topology and physiologic function, and provide new insights into understanding how health and distinct physiologic states emerge from networked interactions among nonlinear multi-component complex systems. The presented here investigations are initial steps in building a first atlas of dynamic interactions among organ systems.

Dynamical Networks Characterization of Space Weather Events

Science.gov (United States)

Orr, L.; Chapman, S. C.; Dods, J.; Gjerloev, J. W.

2017-12-01

Space weather can cause disturbances to satellite systems, impacting navigation technology and telecommunications; it can cause power loss and aviation disruption. A central aspect of the earth's magnetospheric response to space weather events are large scale and rapid changes in ionospheric current patterns. Space weather is highly dynamic and there are still many controversies about how the current system evolves in time. The recent SuperMAG initiative, collates ground-based vector magnetic field time series from over 200 magnetometers with 1-minute temporal resolution. In principle this combined dataset is an ideal candidate for quantification using dynamical networks. Network properties and parameters allow us to characterize the time dynamics of the full spatiotemporal pattern of the ionospheric current system. However, applying network methodologies to physical data presents new challenges. We establish whether a given pair of magnetometers are connected in the network by calculating their canonical cross correlation. The magnetometers are connected if their cross correlation exceeds a threshold. In our physical time series this threshold needs to be both station specific, as it varies with (non-linear) individual station sensitivity and location, and able to vary with season, which affects ground conductivity. Additionally, the earth rotates and therefore the ground stations move significantly on the timescales of geomagnetic disturbances. The magnetometers are non-uniformly spatially distributed. We will present new methodology which addresses these problems and in particular achieves dynamic normalization of the physical time series in order to form the network. Correlated disturbances across the magnetometers capture transient currents. Once the dynamical network has been obtained [1][2] from the full magnetometer data set it can be used to directly identify detailed inferred transient ionospheric current patterns and track their dynamics. We will show

Dynamic analysis of solid propellant grains subjected to ignition pressurization loading

Science.gov (United States)

Chyuan, Shiang-Woei

2003-11-01

Traditionally, the transient analysis of solid propellant grains subjected to ignition pressurization loading was not considered, and quasi-elastic-static analysis was widely adopted for structural integrity because the analytical task gets simplified. But it does not mean that the dynamic effect is not useful and could be neglected arbitrarily, and this effect usually plays a very important role for some critical design. In order to simulate the dynamic response for solid rocket motor, a transient finite element model, accompanied by concepts of time-temperature shift principle, reduced integration and thermorheologically simple material assumption, was used. For studying the dynamic response, diverse ignition pressurization loading cases were used and investigated in the present paper. Results show that the dynamic effect is important for structural integrity of solid propellant grains under ignition pressurization loading. Comparing the effective stress of transient analysis and of quasi-elastic-static analysis, one can see that there is an obvious difference between them because of the dynamic effect. From the work of quasi-elastic-static and transient analyses, the dynamic analysis highlighted several areas of interest and a more accurate and reasonable result could be obtained for the engineer.

Complex networks: Dynamics and security

Indian Academy of Sciences (India)

This paper presents a perspective in the study of complex networks by focusing on how dynamics may affect network security under attacks. ... Department of Mathematics and Statistics, Arizona State University, Tempe, Arizona 85287, USA; Institute of Mathematics and Computer Science, University of Sao Paulo, Brazil ...

Learning dynamic Bayesian networks with mixed variables

DEFF Research Database (Denmark)

Bøttcher, Susanne Gammelgaard

This paper considers dynamic Bayesian networks for discrete and continuous variables. We only treat the case, where the distribution of the variables is conditional Gaussian. We show how to learn the parameters and structure of a dynamic Bayesian network and also how the Markov order can be learned...

On delay adjustment for dynamic load balancing in distributed virtual environments.

Science.gov (United States)

Deng, Yunhua; Lau, Rynson W H

2012-04-01

Distributed virtual environments (DVEs) are becoming very popular in recent years, due to the rapid growing of applications, such as massive multiplayer online games (MMOGs). As the number of concurrent users increases, scalability becomes one of the major challenges in designing an interactive DVE system. One solution to address this scalability problem is to adopt a multi-server architecture. While some methods focus on the quality of partitioning the load among the servers, others focus on the efficiency of the partitioning process itself. However, all these methods neglect the effect of network delay among the servers on the accuracy of the load balancing solutions. As we show in this paper, the change in the load of the servers due to network delay would affect the performance of the load balancing algorithm. In this work, we conduct a formal analysis of this problem and discuss two efficient delay adjustment schemes to address the problem. Our experimental results show that our proposed schemes can significantly improve the performance of the load balancing algorithm with neglectable computation overhead.

Mechanical behavior of ultrafine-grained materials under combined static and dynamic loadings

Directory of Open Access Journals (Sweden)

Guo Y.Z.

2015-01-01

Full Text Available Ultrafine-grained (UFG materials have extensive prospects for engineering application due to their excellent mechanical properties. However, the grain size decrease reduces their strain hardening ability and makes UFG materials more susceptible to deformation instability such as shear localization. In most cases, critical shear strain is taken as the criterion for formation of shear localization under impact loading or adiabatic shear band (ASB. Recently, some researchers found that the formation of ASB was determined only by the dynamic loading process and had nothing to do with its static loading history. They proposed for coarse-grained metals a dynamic stored energy-based criterion for ASB and verified it by some experiments. In this study, we will focus on the shear localization behavior of UFG metals such as UFG titanium and magnesium alloy AZ31. Quasi-static loading and dynamic loading will be applied on the same specimen alternately. The shear localization behavior will be analyzed and the criterion of its formation will be evaluated.

Mobility-Aware and Load Balancing Based Clustering Algorithm for Energy Conservation in MANET

Institute of Scientific and Technical Information of China (English)

XU Li; ZHENG Bao-yu; GUO Gong-de

2005-01-01

Mobile ad hoc network (MANET) is one of wireless communication network architecture that has received a lot of attention. MANET is characterized by dynamic network topology and limited energy. With mobility-aware and load balancing based clustering algorithm (MLCA), this paper proposes a new topology management strategy to conserve energy. Performance simulation results show that the proposed MLCA strategy can balances the traffic load inside the whole network, so as to prolong the network lifetime, meanly, at the same time, achieve higher throughput ratio and network stability.

Feasibility of Applying Controllable Lubrication to Dynamically Loaded Journal Bearings

DEFF Research Database (Denmark)

Estupinan, Edgar Alberto; Santos, Ilmar

2009-01-01

A multibody dynamic model of the main mechanical components of a hermetic reciprocating compressor is presented in this work. Considering that some of the mechanical elements are interconnected via thin fluid films, the multibody dynamic model is coupled to the equations from the dynamics...... of the fluid films, based on fluid film theory. For a dynamically loaded journal bearing, the fluid film pressure distribution can be computed by numerically solving the Reynolds equation, by means of finite-difference method. Particularly, in this study the main focus is on the lubrication behavior...... and reaction forces in a reciprocating compressor have a cyclic behavior, periodic oil pressure injection rules based on the instantaneous crank angle and load bearing condition can be established. In this paper, several bearing configurations working under different oil pressure injection rules conditions...

Sensitivity Analysis of Dynamic Tariff Method for Congestion Management in Distribution Networks

DEFF Research Database (Denmark)

Huang, Shaojun; Wu, Qiuwei; Liu, Zhaoxi

2015-01-01

The dynamic tariff (DT) method is designed for the distribution system operator (DSO) to alleviate the congestions that might occur in a distribution network with high penetration of distribute energy resources (DERs). Sensitivity analysis of the DT method is crucial because of its decentralized...... control manner. The sensitivity analysis can obtain the changes of the optimal energy planning and thereby the line loading profiles over the infinitely small changes of parameters by differentiating the KKT conditions of the convex quadratic programming, over which the DT method is formed. Three case...

Dynamic defense and network randomization for computer systems

Science.gov (United States)

Chavez, Adrian R.; Stout, William M. S.; Hamlet, Jason R.; Lee, Erik James; Martin, Mitchell Tyler

2018-05-29

The various technologies presented herein relate to determining a network attack is taking place, and further to adjust one or more network parameters such that the network becomes dynamically configured. A plurality of machine learning algorithms are configured to recognize an active attack pattern. Notification of the attack can be generated, and knowledge gained from the detected attack pattern can be utilized to improve the knowledge of the algorithms to detect a subsequent attack vector(s). Further, network settings and application communications can be dynamically randomized, wherein artificial diversity converts control systems into moving targets that help mitigate the early reconnaissance stages of an attack. An attack(s) based upon a known static address(es) of a critical infrastructure network device(s) can be mitigated by the dynamic randomization. Network parameters that can be randomized include IP addresses, application port numbers, paths data packets navigate through the network, application randomization, etc.

Working memory load improves early stages of independent visual processing

OpenAIRE

Cocchi, Luca; Toepel, Ulrike; De Lucia, Marzia; Martuzzi, Roberto; Wood, Stephen J.; Carter, Olivia; Murray, Micah M.

2010-01-01

Increasing evidence suggests that working memory and perceptual processes are dynamically interrelated due to modulating activity in overlapping brain networks. However, the direct influence of working memory on the spatio-temporal brain dynamics of behaviorally relevant intervening information remains unclear. To investigate this issue, subjects performed a visual proximity grid perception task under three different visual-spatial working memory (VSWM) load conditions. VSWM load was manipula...

LOAD FORECASTING FOR POWER SYSTEM PLANNING AND OPERATION USING ARTIFICIAL NEURAL NETWORK AT AL BATINAH REGION OMAN

Directory of Open Access Journals (Sweden)

HUSSEIN A. ABDULQADER

2012-08-01

Full Text Available Load forecasting is essential part for the power system planning and operation. In this paper the modeling and design of artificial neural network for load forecasting is carried out in a particular region of Oman. Neural network approach helps to reduce the problem associated with conventional method and has the advantage of learning directly from the historical data. The neural network here uses data such as past load; weather information like humidity and temperatures. Once the neural network is trained for the past set of data it can give a prediction of future load. This reduces the capital investment reducing the equipments to be installed. The actual data are taken from the Mazoon Electrical Company, Oman. The data of load for the year 2007, 2008 and 2009 are collected for a particular region called Al Batinah in Oman and trained using neural networks to forecast the future. The main objective is to forecast the amount of electricity needed for better load distribution in the areas of this region in Oman. The load forecasting is done for the year 2010 and is validated for the accuracy.

Self-organization of complex networks as a dynamical system.

Science.gov (United States)

Aoki, Takaaki; Yawata, Koichiro; Aoyagi, Toshio

2015-01-01

To understand the dynamics of real-world networks, we investigate a mathematical model of the interplay between the dynamics of random walkers on a weighted network and the link weights driven by a resource carried by the walkers. Our numerical studies reveal that, under suitable conditions, the co-evolving dynamics lead to the emergence of stationary power-law distributions of the resource and link weights, while the resource quantity at each node ceaselessly changes with time. We analyze the network organization as a deterministic dynamical system and find that the system exhibits multistability, with numerous fixed points, limit cycles, and chaotic states. The chaotic behavior of the system leads to the continual changes in the microscopic network dynamics in the absence of any external random noises. We conclude that the intrinsic interplay between the states of the nodes and network reformation constitutes a major factor in the vicissitudes of real-world networks.

Transitions from Trees to Cycles in Adaptive Flow Networks

Directory of Open Access Journals (Sweden)

Erik A. Martens

2017-11-01

Full Text Available Transport networks are crucial to the functioning of natural and technological systems. Nature features transport networks that are adaptive over a vast range of parameters, thus providing an impressive level of robustness in supply. Theoretical and experimental studies have found that real-world transport networks exhibit both tree-like motifs and cycles. When the network is subject to load fluctuations, the presence of cyclic motifs may help to reduce flow fluctuations and, thus, render supply in the network more robust. While previous studies considered network topology via optimization principles, here, we take a dynamical systems approach and study a simple model of a flow network with dynamically adapting weights (conductances. We assume a spatially non-uniform distribution of rapidly fluctuating loads in the sinks and investigate what network configurations are dynamically stable. The network converges to a spatially non-uniform stable configuration composed of both cyclic and tree-like structures. Cyclic structures emerge locally in a transcritical bifurcation as the amplitude of the load fluctuations is increased. The resulting adaptive dynamics thus partitions the network into two distinct regions with cyclic and tree-like structures. The location of the boundary between these two regions is determined by the amplitude of the fluctuations. These findings may explain why natural transport networks display cyclic structures in the micro-vascular regions near terminal nodes, but tree-like features in the regions with larger veins.

Nonlinear Dynamics on Interconnected Networks

Science.gov (United States)

Arenas, Alex; De Domenico, Manlio

2016-06-01

Networks of dynamical interacting units can represent many complex systems, from the human brain to transportation systems and societies. The study of these complex networks, when accounting for different types of interactions has become a subject of interest in the last few years, especially because its representational power in the description of users' interactions in diverse online social platforms (Facebook, Twitter, Instagram, etc.) [1], or in representing different transportation modes in urban networks [2,3]. The general name coined for these networks is multilayer networks, where each layer accounts for a type of interaction (see Fig. 1).

Dynamic Loading of Carrara Marble in a Heated State

Science.gov (United States)

Wong, Louis Ngai Yuen; Li, Zhihuan; Kang, Hyeong Min; Teh, Cee Ing

2017-06-01

Useable land is a finite space, and with a growing global population, countries have been exploring the use of underground space as a strategic resource to sustain the growth of their society and economy. However, the effects of impact loading on rocks that have been heated, and hence the integrity of the underground structure, are still not fully understood and has not been included in current design standards. Such scenarios include traffic accidents and explosions during an underground fire. This study aims to provide a better understanding of the dynamic load capacity of Carrara marble at elevated temperatures. Dynamic uniaxial compression tests are performed on Carrara marble held at various temperatures using a split-Hopkinson Pressure Bar (SHPB) setup with varying input force. A customized oven is included in the SHPB setup to allow for testing of the marble specimens in a heated state. After the loading test, a three-wave analysis is performed to obtain the dynamic stress-strain curve of the specimen under loading. The fragments of the failed specimens were also collected and dry-sieved to obtain the particle size distribution. The results reveal that the peak stress of specimens that have been heated is negatively correlated with the heating temperature. However, the energy absorbed by the specimens at peak stress at all temperatures is similar, indicating that a significant amount of energy is dissipated via plastic deformation. Generally, fragment size is also found to show a negative correlation with heating temperature and loading pressure. However, in some cases this relationship does not hold true, probably due to the occurrence of stress shadowing. Linear Elastic Fracture Mechanics has been found to be generally applicable to specimens tested at low temperatures; but at higher temperatures, Elastic-Plastic Fracture Mechanics will give a more accurate prediction. Another contribution of this study is to show that other than the peak stress of the

Dynamic Response and Failure Mechanism of Brittle Rocks Under Combined Compression-Shear Loading Experiments

Science.gov (United States)

Xu, Yuan; Dai, Feng

2018-03-01

A novel method is developed for characterizing the mechanical response and failure mechanism of brittle rocks under dynamic compression-shear loading: an inclined cylinder specimen using a modified split Hopkinson pressure bar (SHPB) system. With the specimen axis inclining to the loading direction of SHPB, a shear component can be introduced into the specimen. Both static and dynamic experiments are conducted on sandstone specimens. Given carefully pulse shaping, the dynamic equilibrium of the inclined specimens can be satisfied, and thus the quasi-static data reduction is employed. The normal and shear stress-strain relationships of specimens are subsequently established. The progressive failure process of the specimen illustrated via high-speed photographs manifests a mixed failure mode accommodating both the shear-dominated failure and the localized tensile damage. The elastic and shear moduli exhibit certain loading-path dependence under quasi-static loading but loading-path insensitivity under high loading rates. Loading rate dependence is evidently demonstrated through the failure characteristics involving fragmentation, compression and shear strength and failure surfaces based on Drucker-Prager criterion. Our proposed method is convenient and reliable to study the dynamic response and failure mechanism of rocks under combined compression-shear loading.

Short-Term Forecasting of Electric Loads Using Nonlinear Autoregressive Artificial Neural Networks with Exogenous Vector Inputs

Directory of Open Access Journals (Sweden)

Jaime Buitrago

2017-01-01

Full Text Available Short-term load forecasting is crucial for the operations planning of an electrical grid. Forecasting the next 24 h of electrical load in a grid allows operators to plan and optimize their resources. The purpose of this study is to develop a more accurate short-term load forecasting method utilizing non-linear autoregressive artificial neural networks (ANN with exogenous multi-variable input (NARX. The proposed implementation of the network is new: the neural network is trained in open-loop using actual load and weather data, and then, the network is placed in closed-loop to generate a forecast using the predicted load as the feedback input. Unlike the existing short-term load forecasting methods using ANNs, the proposed method uses its own output as the input in order to improve the accuracy, thus effectively implementing a feedback loop for the load, making it less dependent on external data. Using the proposed framework, mean absolute percent errors in the forecast in the order of 1% have been achieved, which is a 30% improvement on the average error using feedforward ANNs, ARMAX and state space methods, which can result in large savings by avoiding commissioning of unnecessary power plants. The New England electrical load data are used to train and validate the forecast prediction.

Alternative approach to automated management of load flow in engineering networks considering functional reliability

Directory of Open Access Journals (Sweden)

Ирина Александровна Гавриленко

2016-02-01

Full Text Available The approach to automated management of load flow in engineering networks considering functional reliability was proposed in the article. The improvement of the concept of operational and strategic management of load flow in engineering networks was considered. The verbal statement of the problem for thesis research is defined, namely, the problem of development of information technology for exact calculation of the functional reliability of the network, or the risk of short delivery of purpose-oriented product for consumers

Dynamic Load Balancing for PIC code using Eulerian/Lagrangian partitioning

OpenAIRE

Sauget, Marc; Latu, Guillaume

2017-01-01

This document presents an analysis of different load balance strategies for a Plasma physics code that models high energy particle beams with PIC method. A comparison of different load balancing algorithms is given: static or dynamic ones. Lagrangian and Eulerian partitioning techniques have been investigated.

A network flow model for load balancing in circuit-switched multicomputers

Science.gov (United States)

Bokhari, Shahid H.

1990-01-01

In multicomputers that utilize circuit switching or wormhole routing, communication overhead depends largely on link contention - the variation due to distance between nodes is negligible. This has a major impact on the load balancing problem. In this case, there are some nodes with excess load (sources) and others with deficit load (sinks) and it is required to find a matching of sources to sinks that avoids contention. The problem is made complex by the hardwired routing on currently available machines: the user can control only which nodes communicate but not how the messages are routed. Network flow models of message flow in the mesh and the hypercube were developed to solve this problem. The crucial property of these models is the correspondence between minimum cost flows and correctly routed messages. To solve a given load balancing problem, a minimum cost flow algorithm is applied to the network. This permits one to determine efficiently a maximum contention free matching of sources to sinks which, in turn, tells one how much of the given imbalance can be eliminated without contention.

The Effect of the Loading on Dynamic Stability and Scapular Asymmetry

Directory of Open Access Journals (Sweden)

Mohammad Hassan Azarsa

2014-03-01

Full Text Available Background: Scapular stabilization and neuromuscular control provide an important parameter to characterize shoulder function during dynamic activities. Many studies have confirmed the effect of the loading on scapular position and scapulohumeral rhythm. Therefore, the evaluation of stabilizer muscles involvement in scapular asymmetry may assist in the development of clinical examination and rehabilitation program. The aim of this study was to evaluate the effect of loading on dynamic stability and scapular asymmetry in basketball players. Methods: Thirty healthy male basketball players aged between 20 to 31 years old were tested. The linear distance between scapular inferior angle and T7 spinous process was measured using a caliper in 90 degrees of unloaded scaption and with 1, 2 and 4 kg loading. The difference of distances of two sides in the above 4 positions was analyzed. Results: The amount of distances difference in two sides with 1 kg loading was minimal (9.36 mm. This difference increased to 10.19 mm and 12.22 mm, with increasing the loading to 2 and 4 kg respectively; although the 4 positions of the test did not show significant differences in distances difference (P>0.05. Conclusion: This study shows that dynamic stability of the scapula is dependent on the role of muscles, so that with increasing load on the muscles, the scapular asymmetry is more pronounced.

Dynamic capabilities and network benefits

Directory of Open Access Journals (Sweden)

Helge Svare

2017-01-01

Full Text Available The number of publicly funded initiatives to establish or strengthen networks and clusters, in order to enhance innovation, has been increasing. Returns on such investments vary, and the aim of this study is to explore to what extent the variation in benefits for firms participating in networks or clusters can be explained by their dynamic capabilities (DC. Based on survey data from five Norwegian networks, the results suggest that firms with higher DC are more successful in harvesting the potential benefits of being member of a network.

Incremental Centrality Algorithms for Dynamic Network Analysis

Science.gov (United States)

2013-08-01

literature.   7.1.3 Small World Networks In 1998, Watts and Strogatz introduced a model that starts with a regular lattice (ring) of n nodes and...and S. Strogatz , "Collective Dynamics of ‘Small-World’ Networks," Nature, vol. 393, pp. 440-442, 1998. [13] T. Opsahl, "Structure and Evolution of...34On Random Graphs," Publicationes Mathematicae, vol. 6, 1959. [167] D.J. Watts and S.H. Strogatz , "Collective Dynamics of ‘Small-World’ Networks

Using Gait Dynamics to Estimate Load from a Body-Worn Accelerometer

Science.gov (United States)

2016-02-05

dynamics, ambulation, correlation structure, musculoskeletal injury I. INTRODUCTION ilitary personnel commonly engage in training and operational...according to their load estimation accuracy, which is defined by the Pearson correlation , r, of its load estimates with the true loads (see Tables...method. In Table IV are shown the mean absolute error, MAE, and Pearson correlation , r, of the load estimates using estimates from GS alone, PLS alone

Dynamic analysis of a pumped-storage hydropower plant with random power load

Science.gov (United States)

Zhang, Hao; Chen, Diyi; Xu, Beibei; Patelli, Edoardo; Tolo, Silvia

2018-02-01

This paper analyzes the dynamic response of a pumped-storage hydropower plant in generating mode. Considering the elastic water column effects in the penstock, a linearized reduced order dynamic model of the pumped-storage hydropower plant is used in this paper. As the power load is always random, a set of random generator electric power output is introduced to research the dynamic behaviors of the pumped-storage hydropower plant. Then, the influences of the PI gains on the dynamic characteristics of the pumped-storage hydropower plant with the random power load are analyzed. In addition, the effects of initial power load and PI parameters on the stability of the pumped-storage hydropower plant are studied in depth. All of the above results will provide theoretical guidance for the study and analysis of the pumped-storage hydropower plant.

Salience network dynamics underlying successful resistance of temptation

Science.gov (United States)

Nomi, Jason S; Calhoun, Vince D; Stelzel, Christine; Paschke, Lena M; Gaschler, Robert; Goschke, Thomas; Walter, Henrik; Uddin, Lucina Q

2017-01-01

Abstract Self-control and the ability to resist temptation are critical for successful completion of long-term goals. Contemporary models in cognitive neuroscience emphasize the primary role of prefrontal cognitive control networks in aligning behavior with such goals. Here, we use gaze pattern analysis and dynamic functional connectivity fMRI data to explore how individual differences in the ability to resist temptation are related to intrinsic brain dynamics of the cognitive control and salience networks. Behaviorally, individuals exhibit greater gaze distance from target location (e.g. higher distractibility) during presentation of tempting erotic images compared with neutral images. Individuals whose intrinsic dynamic functional connectivity patterns gravitate toward configurations in which salience detection systems are less strongly coupled with visual systems resist tempting distractors more effectively. The ability to resist tempting distractors was not significantly related to intrinsic dynamics of the cognitive control network. These results suggest that susceptibility to temptation is governed in part by individual differences in salience network dynamics and provide novel evidence for involvement of brain systems outside canonical cognitive control networks in contributing to individual differences in self-control. PMID:29048582

Agent Based Modeling on Organizational Dynamics of Terrorist Network

OpenAIRE

Bo Li; Duoyong Sun; Renqi Zhu; Ze Li

2015-01-01

Modeling organizational dynamics of terrorist network is a critical issue in computational analysis of terrorism research. The first step for effective counterterrorism and strategic intervention is to investigate how the terrorists operate with the relational network and what affects the performance. In this paper, we investigate the organizational dynamics by employing a computational experimentation methodology. The hierarchical cellular network model and the organizational dynamics model ...

An Efficient SDN Load Balancing Scheme Based on Variance Analysis for Massive Mobile Users

Directory of Open Access Journals (Sweden)

Hong Zhong

2015-01-01

Full Text Available In a traditional network, server load balancing is used to satisfy the demand for high data volumes. The technique requires large capital investment while offering poor scalability and flexibility, which difficultly supports highly dynamic workload demands from massive mobile users. To solve these problems, this paper analyses the principle of software-defined networking (SDN and presents a new probabilistic method of load balancing based on variance analysis. The method can be used to dynamically manage traffic flows for supporting massive mobile users in SDN networks. The paper proposes a solution using the OpenFlow virtual switching technology instead of the traditional hardware switching technology. A SDN controller monitors data traffic of each port by means of variance analysis and provides a probability-based selection algorithm to redirect traffic dynamically with the OpenFlow technology. Compared with the existing load balancing methods which were designed to support traditional networks, this solution has lower cost, higher reliability, and greater scalability which satisfy the needs of mobile users.

Complex systems and networks dynamics, controls and applications

CERN Document Server

Yu, Xinghuo; Chen, Guanrong; Yu, Wenwu

2016-01-01

This elementary book provides some state-of-the-art research results on broad disciplinary sciences on complex networks. It presents an in-depth study with detailed description of dynamics, controls and applications of complex networks. The contents of this book can be summarized as follows. First, the dynamics of complex networks, for example, the cluster dynamic analysis by using kernel spectral methods, community detection algorithms in bipartite networks, epidemiological modeling with demographics and epidemic spreading on multi-layer networks, are studied. Second, the controls of complex networks are investigated including topics like distributed finite-time cooperative control of multi-agent systems by applying homogenous-degree and Lyapunov methods, composite finite-time containment control for disturbed second-order multi-agent systems, fractional-order observer design of multi-agent systems, chaos control and anticontrol of complex systems via Parrondos game and many more. Third, the applications of ...

Loading Processes Dynamics Modelling Taking into Account the Bucket-Soil Interaction

Directory of Open Access Journals (Sweden)

Carmen Debeleac

2007-10-01

Full Text Available The author propose three dynamic models specialized for the vibrations and resistive forces analysis that appear at the loading process with different construction equipment like frontal loaders and excavators.The models used putting into evidence the components of digging: penetration, cutting, and loading.The conclusions of this study consist by evidentiate the dynamic overloads that appear on the working state and that induced the self-oscillations into the equipment structure.

Structural network heterogeneities and network dynamics: a possible dynamical mechanism for hippocampal memory reactivation.

Science.gov (United States)

Jablonski, Piotr; Poe, Gina; Zochowski, Michal

2007-03-01

The hippocampus has the capacity for reactivating recently acquired memories and it is hypothesized that one of the functions of sleep reactivation is the facilitation of consolidation of novel memory traces. The dynamic and network processes underlying such a reactivation remain, however, unknown. We show that such a reactivation characterized by local, self-sustained activity of a network region may be an inherent property of the recurrent excitatory-inhibitory network with a heterogeneous structure. The entry into the reactivation phase is mediated through a physiologically feasible regulation of global excitability and external input sources, while the reactivated component of the network is formed through induced network heterogeneities during learning. We show that structural changes needed for robust reactivation of a given network region are well within known physiological parameters.

Quantifying the dynamics of coupled networks of switches and oscillators.

Directory of Open Access Journals (Sweden)

Matthew R Francis

Full Text Available Complex network dynamics have been analyzed with models of systems of coupled switches or systems of coupled oscillators. However, many complex systems are composed of components with diverse dynamics whose interactions drive the system's evolution. We, therefore, introduce a new modeling framework that describes the dynamics of networks composed of both oscillators and switches. Both oscillator synchronization and switch stability are preserved in these heterogeneous, coupled networks. Furthermore, this model recapitulates the qualitative dynamics for the yeast cell cycle consistent with the hypothesized dynamics resulting from decomposition of the regulatory network into dynamic motifs. Introducing feedback into the cell-cycle network induces qualitative dynamics analogous to limitless replicative potential that is a hallmark of cancer. As a result, the proposed model of switch and oscillator coupling provides the ability to incorporate mechanisms that underlie the synchronized stimulus response ubiquitous in biochemical systems.

Synthesis of recurrent neural networks for dynamical system simulation.

Science.gov (United States)

Trischler, Adam P; D'Eleuterio, Gabriele M T

2016-08-01

We review several of the most widely used techniques for training recurrent neural networks to approximate dynamical systems, then describe a novel algorithm for this task. The algorithm is based on an earlier theoretical result that guarantees the quality of the network approximation. We show that a feedforward neural network can be trained on the vector-field representation of a given dynamical system using backpropagation, then recast it as a recurrent network that replicates the original system's dynamics. After detailing this algorithm and its relation to earlier approaches, we present numerical examples that demonstrate its capabilities. One of the distinguishing features of our approach is that both the original dynamical systems and the recurrent networks that simulate them operate in continuous time. Copyright © 2016 Elsevier Ltd. All rights reserved.

Effect of dynamic monotonic and cyclic loading on fracture behavior for Japanese carbon steel pipe STS410

Energy Technology Data Exchange (ETDEWEB)

Kinoshita, Kanji; Murayama, Kouichi; Ogata, Hiroyuki [and others

1997-04-01

The fracture behavior for Japanese carbon steel pipe STS410 was examined under dynamic monotonic and cyclic loading through a research program of International Piping Integrity Research Group (EPIRG-2), in order to evaluate the strength of pipe during the seismic event The tensile test and the fracture toughness test were conducted for base metal and TIG weld metal. Three base metal pipe specimens, 1,500mm in length and 6-inch diameter sch.120, were employed for a quasi-static monotonic, a dynamic monotonic and a dynamic cyclic loading pipe fracture tests. One weld joint pipe specimen was also employed for a dynamic cyclic loading test In the dynamic cyclic loading test, the displacement was controlled as applying the fully reversed load (R=-1). The pipe specimens with a circumferential through-wall crack were subjected four point bending load at 300C in air. Japanese STS410 carbon steel pipe material was found to have high toughness under dynamic loading condition through the CT fracture toughness test. As the results of pipe fracture tests, the maximum moment to pipe fracture under dynamic monotonic and cyclic loading condition, could be estimated by plastic collapse criterion and the effect of dynamic monotonic loading and cyclic loading was a little on the maximum moment to pipe fracture of the STS410 carbon steel pipe. The STS410 carbon steel pipe seemed to be less sensitive to dynamic and cyclic loading effects than the A106Gr.B carbon steel pipe evaluated in IPIRG-1 program.

Effect of dynamic monotonic and cyclic loading on fracture behavior for Japanese carbon steel pipe STS410

International Nuclear Information System (INIS)

Kinoshita, Kanji; Murayama, Kouichi; Ogata, Hiroyuki

1997-01-01

The fracture behavior for Japanese carbon steel pipe STS410 was examined under dynamic monotonic and cyclic loading through a research program of International Piping Integrity Research Group (EPIRG-2), in order to evaluate the strength of pipe during the seismic event The tensile test and the fracture toughness test were conducted for base metal and TIG weld metal. Three base metal pipe specimens, 1,500mm in length and 6-inch diameter sch.120, were employed for a quasi-static monotonic, a dynamic monotonic and a dynamic cyclic loading pipe fracture tests. One weld joint pipe specimen was also employed for a dynamic cyclic loading test In the dynamic cyclic loading test, the displacement was controlled as applying the fully reversed load (R=-1). The pipe specimens with a circumferential through-wall crack were subjected four point bending load at 300C in air. Japanese STS410 carbon steel pipe material was found to have high toughness under dynamic loading condition through the CT fracture toughness test. As the results of pipe fracture tests, the maximum moment to pipe fracture under dynamic monotonic and cyclic loading condition, could be estimated by plastic collapse criterion and the effect of dynamic monotonic loading and cyclic loading was a little on the maximum moment to pipe fracture of the STS410 carbon steel pipe. The STS410 carbon steel pipe seemed to be less sensitive to dynamic and cyclic loading effects than the A106Gr.B carbon steel pipe evaluated in IPIRG-1 program

Major component analysis of dynamic networks of physiologic organ interactions

International Nuclear Information System (INIS)

Liu, Kang K L; Ma, Qianli D Y; Ivanov, Plamen Ch; Bartsch, Ronny P

2015-01-01

The human organism is a complex network of interconnected organ systems, where the behavior of one system affects the dynamics of other systems. Identifying and quantifying dynamical networks of diverse physiologic systems under varied conditions is a challenge due to the complexity in the output dynamics of the individual systems and the transient and nonlinear characteristics of their coupling. We introduce a novel computational method based on the concept of time delay stability and major component analysis to investigate how organ systems interact as a network to coordinate their functions. We analyze a large database of continuously recorded multi-channel physiologic signals from healthy young subjects during night-time sleep. We identify a network of dynamic interactions between key physiologic systems in the human organism. Further, we find that each physiologic state is characterized by a distinct network structure with different relative contribution from individual organ systems to the global network dynamics. Specifically, we observe a gradual decrease in the strength of coupling of heart and respiration to the rest of the network with transition from wake to deep sleep, and in contrast, an increased relative contribution to network dynamics from chin and leg muscle tone and eye movement, demonstrating a robust association between network topology and physiologic function. (paper)

The dynamic behavior of mortar under impact-loading

Science.gov (United States)

Kawai, Nobuaki; Inoue, Kenji; Misawa, Satoshi; Tanaka, Kyoji; Hayashi, Shizuo; Kondo, Ken-Ichi; Riedel, Werner

2007-06-01

Concrete and mortar are the most fundamental structural material. Therefore, considerable interest in characterizing the dynamic behavior of them under impact-loading exists. In this study, plate impact experiments have been performed to determine the dynamic behavior of mortar. Longitudinal and lateral stresses have been directly measured by means of embedded polyvinylidene fluoride (PVDF) gauges up to 1 GPa. A 200 mm-cal. powder gun enable us to measure longitudinal and lateral stresses at several point from the impact surface, simultaneously. The shear strength under impact-loading has been obtained from measured longitudinal and lateral stresses. The longitudinal stress profile shows a two-wave structure. It is indicated that this structure is associated with the onset of pore compaction and failure of mortar by comparing with hydrocode simulations using an elastic-plastic damage model for concrete.

Dynamic fracture initiation in brittle materials under combined mode I/II loading

International Nuclear Information System (INIS)

Nakano, M.; Kishida, K.; Yamauchi, Y.; Sogabe, Y.

1994-01-01

A new test method has been developed to measure the resistance of dynamic fracture initiation in brittle materials under combined mode I/II loadings. The Brazilian disks with center-cracks have been fractured under oblique impact loadings in diametral-compression. The dynamic stress intensity factors of mode I and II are evaluated from the superposition integrals of the step response functions for the cracked disk. The experimental results are presented to elucidate the influence of loading rate on the combined mode fracture toughness for ceramics and glasses. (orig.)

Recovery time after localized perturbations in complex dynamical networks

International Nuclear Information System (INIS)

Mitra, Chiranjit; Kittel, Tim; Kurths, Jürgen; Donner, Reik V; Choudhary, Anshul

2017-01-01

Maintaining the synchronous motion of dynamical systems interacting on complex networks is often critical to their functionality. However, real-world networked dynamical systems operating synchronously are prone to random perturbations driving the system to arbitrary states within the corresponding basin of attraction, thereby leading to epochs of desynchronized dynamics with a priori unknown durations. Thus, it is highly relevant to have an estimate of the duration of such transient phases before the system returns to synchrony, following a random perturbation to the dynamical state of any particular node of the network. We address this issue here by proposing the framework of single-node recovery time (SNRT) which provides an estimate of the relative time scales underlying the transient dynamics of the nodes of a network during its restoration to synchrony. We utilize this in differentiating the particularly slow nodes of the network from the relatively fast nodes, thus identifying the critical nodes which when perturbed lead to significantly enlarged recovery time of the system before resuming synchronized operation. Further, we reveal explicit relationships between the SNRT values of a network, and its global relaxation time when starting all the nodes from random initial conditions. Earlier work on relaxation time generally focused on investigating its dependence on macroscopic topological properties of the respective network. However, we employ the proposed concept for deducing microscopic relationships between topological features of nodes and their respective SNRT values. The framework of SNRT is further extended to a measure of resilience of the different nodes of a networked dynamical system. We demonstrate the potential of SNRT in networks of Rössler oscillators on paradigmatic topologies and a model of the power grid of the United Kingdom with second-order Kuramoto-type nodal dynamics illustrating the conceivable practical applicability of the proposed

Recovery time after localized perturbations in complex dynamical networks

Science.gov (United States)

Mitra, Chiranjit; Kittel, Tim; Choudhary, Anshul; Kurths, Jürgen; Donner, Reik V.

2017-10-01

Maintaining the synchronous motion of dynamical systems interacting on complex networks is often critical to their functionality. However, real-world networked dynamical systems operating synchronously are prone to random perturbations driving the system to arbitrary states within the corresponding basin of attraction, thereby leading to epochs of desynchronized dynamics with a priori unknown durations. Thus, it is highly relevant to have an estimate of the duration of such transient phases before the system returns to synchrony, following a random perturbation to the dynamical state of any particular node of the network. We address this issue here by proposing the framework of single-node recovery time (SNRT) which provides an estimate of the relative time scales underlying the transient dynamics of the nodes of a network during its restoration to synchrony. We utilize this in differentiating the particularly slow nodes of the network from the relatively fast nodes, thus identifying the critical nodes which when perturbed lead to significantly enlarged recovery time of the system before resuming synchronized operation. Further, we reveal explicit relationships between the SNRT values of a network, and its global relaxation time when starting all the nodes from random initial conditions. Earlier work on relaxation time generally focused on investigating its dependence on macroscopic topological properties of the respective network. However, we employ the proposed concept for deducing microscopic relationships between topological features of nodes and their respective SNRT values. The framework of SNRT is further extended to a measure of resilience of the different nodes of a networked dynamical system. We demonstrate the potential of SNRT in networks of Rössler oscillators on paradigmatic topologies and a model of the power grid of the United Kingdom with second-order Kuramoto-type nodal dynamics illustrating the conceivable practical applicability of the proposed

PLATON: Peer-to-Peer load adjusting tree overlay networks

NARCIS (Netherlands)

Lymberopoulos, L.; Pittaras, C.; Grammatikou, M.; Papavassiliou, S.; Maglaris, V.

2011-01-01

Peer-to-Peer systems supporting multi attribute and range queries use a number of techniques to partition the multi dimensional data space among participating peers. Load-balancing of data accross peer partitions is necessary in order to avoid the presence of network hotspots which may cause

An efficient approach for electric load forecasting using distributed ART (adaptive resonance theory) and HS-ARTMAP (Hyper-spherical ARTMAP network) neural network

International Nuclear Information System (INIS)

Cai, Yuan; Wang, Jian-zhou; Tang, Yun; Yang, Yu-chen

2011-01-01

This paper presents a neural network based on adaptive resonance theory, named distributed ART (adaptive resonance theory) and HS-ARTMAP (Hyper-spherical ARTMAP network), applied to the electric load forecasting problem. The distributed ART combines the stable fast learning capabilities of winner-take-all ART systems with the noise tolerance and code compression capabilities of multi-layer perceptions. The HS-ARTMAP, a hybrid of an RBF (Radial Basis Function)-network-like module which uses hyper-sphere basis function substitute the Gaussian basis function and an ART-like module, performs incremental learning capabilities in function approximation problem. The HS-ARTMAP only receives the compressed distributed coding processed by distributed ART to deal with the proliferation problem which ARTMAP (adaptive resonance theory map) architecture often encounters and still performs well in electric load forecasting. To demonstrate the performance of the methodology, data from New South Wales and Victoria in Australia are illustrated. Results show that the developed method is much better than the traditional BP and single HS-ARTMAP neural network. -- Research highlights: → The processing of the presented network is based on compressed distributed data. It's an innovation among the adaptive resonance theory architecture. → The presented network decreases the proliferation the Fuzzy ARTMAP architectures usually encounter. → The network on-line forecasts electrical load accurately, stably. → Both one-period and multi-period load forecasting are executed using data of different cities.

Cognitive radio networks dynamic resource allocation schemes

CERN Document Server

Wang, Shaowei

2014-01-01

This SpringerBrief presents a survey of dynamic resource allocation schemes in Cognitive Radio (CR) Systems, focusing on the spectral-efficiency and energy-efficiency in wireless networks. It also introduces a variety of dynamic resource allocation schemes for CR networks and provides a concise introduction of the landscape of CR technology. The author covers in detail the dynamic resource allocation problem for the motivations and challenges in CR systems. The Spectral- and Energy-Efficient resource allocation schemes are comprehensively investigated, including new insights into the trade-off

Towards building a neural network model for predicting pile static load test curves

Directory of Open Access Journals (Sweden)

Alzo’ubi A. K.

2018-01-01

Full Text Available In the United Arab Emirates, Continuous Flight Auger piles are the most widely used type of deep foundation. To test the pile behaviour, the Static Load Test is routinely conducted in the field by increasing the dead load while monitoring the displacement. Although the test is reliable, it is expensive to conduct. This test is usually conducted in the UAE to verify the pile capacity and displacement as the load increase and decreases in two cycles. In this paper we will utilize the Artificial Neural Network approach to build a model that can predict a complete Static Load Pile test. We will show that by integrating the pile configuration, soil properties, and ground water table in one artificial neural network model, the Static Load Test can be predicted with confidence. We believe that based on this approach, the model is able to predict the entire pile load test from start to end. The suggested approach is an excellent tool to reduce the cost associated with such expensive tests or to predict pile’s performance ahead of the actual test.

Dynamics-based centrality for directed networks.

Science.gov (United States)

Masuda, Naoki; Kori, Hiroshi

2010-11-01

Determining the relative importance of nodes in directed networks is important in, for example, ranking websites, publications, and sports teams, and for understanding signal flows in systems biology. A prevailing centrality measure in this respect is the PageRank. In this work, we focus on another class of centrality derived from the Laplacian of the network. We extend the Laplacian-based centrality, which has mainly been applied to strongly connected networks, to the case of general directed networks such that we can quantitatively compare arbitrary nodes. Toward this end, we adopt the idea used in the PageRank to introduce global connectivity between all the pairs of nodes with a certain strength. Numerical simulations are carried out on some networks. We also offer interpretations of the Laplacian-based centrality for general directed networks in terms of various dynamical and structural properties of networks. Importantly, the Laplacian-based centrality defined as the stationary density of the continuous-time random walk with random jumps is shown to be equivalent to the absorption probability of the random walk with sinks at each node but without random jumps. Similarly, the proposed centrality represents the importance of nodes in dynamics on the original network supplied with sinks but not with random jumps.

RADYBAN: A tool for reliability analysis of dynamic fault trees through conversion into dynamic Bayesian networks

International Nuclear Information System (INIS)

Montani, S.; Portinale, L.; Bobbio, A.; Codetta-Raiteri, D.

2008-01-01

In this paper, we present RADYBAN (Reliability Analysis with DYnamic BAyesian Networks), a software tool which allows to analyze a dynamic fault tree relying on its conversion into a dynamic Bayesian network. The tool implements a modular algorithm for automatically translating a dynamic fault tree into the corresponding dynamic Bayesian network and exploits classical algorithms for the inference on dynamic Bayesian networks, in order to compute reliability measures. After having described the basic features of the tool, we show how it operates on a real world example and we compare the unreliability results it generates with those returned by other methodologies, in order to verify the correctness and the consistency of the results obtained

Critical dynamics in associative memory networks

Directory of Open Access Journals (Sweden)

Maximilian eUhlig

2013-07-01

Full Text Available Critical behavior in neural networks is characterized by scale-free avalanche size distributions and can be explained by self-regulatory mechanisms. Theoretical and experimental evidence indicates that information storage capacity reaches its maximum in the critical regime. We study the effect of structural connectivity formed by Hebbian learning on the criticality of network dynamics. The network endowed with Hebbian learning only does not allow for simultaneous information storage and criticality. However, the critical regime is can be stabilized by short-term synaptic dynamics in the form of synaptic depression and facilitation or, alternatively, by homeostatic adaptation of the synaptic weights. We show that a heterogeneous distribution of maximal synaptic strengths does not preclude criticality if the Hebbian learning is alternated with periods of critical dynamics recovery. We discuss the relevance of these findings for the flexibility of memory in aging and with respect to the recent theory of synaptic plasticity.

Traffic Load on Interconnection Lines of Generalized Double Ring Network Structures

DEFF Research Database (Denmark)

Pedersen, Jens Myrup; Riaz, Muhammad Tahir; Madsen, Ole Brun

2004-01-01

Generalized Double Ring (N2R) network structures possess a number of good properties, but being not planar they are hard to physically embed in communication networks. However, if some of the lines, the interconnection lines, are implemented by wireless technologies, the remaining structure...... consists of two planar rings, which are easily embedded by fiber or other wired solutions. It is shown that for large N2R structures, the interconnection lines carry notably lower loads than the other lines if shortest-path routing is used, and the effects of two other routing schemes are explored, leading...... to lower load on interconnection lines at the price of larger efficient average distance and diameter....

Network dynamics in the healthy and epileptic developing brain

Directory of Open Access Journals (Sweden)

Richard Rosch

2018-03-01

Full Text Available Electroencephalography (EEG allows recording of cortical activity at high temporal resolution. EEG recordings can be summarized along different dimensions using network-level quantitative measures, such as channel-to-channel correlation, or band power distributions across channels. These reveal network patterns that unfold over a range of different timescales and can be tracked dynamically. Here we describe the dynamics of network state transitions in EEG recordings of spontaneous brain activity in normally developing infants and infants with severe early infantile epileptic encephalopathies (n = 8, age: 1–8 months. We describe differences in measures of EEG dynamics derived from band power, and correlation-based summaries of network-wide brain activity. We further show that EEGs from different patient groups and controls may be distinguishable on a small set of the novel quantitative measures introduced here, which describe dynamic network state switching. Quantitative measures related to the sharpness of switching from one correlation pattern to another show the largest differences between groups. These findings reveal that the early epileptic encephalopathies are associated with characteristic dynamic features at the network level. Quantitative network-based analyses like the one presented here may in the future inform the clinical use of quantitative EEG for diagnosis.

Shaft Center Orbit in Dynamically Loaded Bearings

DEFF Research Database (Denmark)

Klit, Peder

2005-01-01

The aim of this work is to demonstrate how to utilize the bearings damping coe±cients to estimate the orbit for a dynamically loaded journal bearing. The classical method for this analysis was developed by Booker in 1965 [1]and described further in 1972 [2]. Several authors have re¯ned this metho...

Applicability of laboratory data to large scale tests under dynamic loading conditions

International Nuclear Information System (INIS)

Kussmaul, K.; Klenk, A.

1993-01-01

The analysis of dynamic loading and subsequent fracture must be based on reliable data for loading and deformation history. This paper describes an investigation to examine the applicability of parameters which are determined by means of small-scale laboratory tests to large-scale tests. The following steps were carried out: (1) Determination of crack initiation by means of strain gauges applied in the crack tip field of compact tension specimens. (2) Determination of dynamic crack resistance curves of CT-specimens using a modified key-curve technique. The key curves are determined by dynamic finite element analyses. (3) Determination of strain-rate-dependent stress-strain relationships for the finite element simulation of small-scale and large-scale tests. (4) Analysis of the loading history for small-scale tests with the aid of experimental data and finite element calculations. (5) Testing of dynamically loaded tensile specimens taken as strips from ferritic steel pipes with a thickness of 13 mm resp. 18 mm. The strips contained slits and surface cracks. (6) Fracture mechanics analyses of the above mentioned tests and of wide plate tests. The wide plates (960x608x40 mm 3 ) had been tested in a propellant-driven 12 MN dynamic testing facility. For calculating the fracture mechanics parameters of both tests, a dynamic finite element simulation considering the dynamic material behaviour was employed. The finite element analyses showed a good agreement with the simulated tests. This prerequisite allowed to gain critical J-integral values. Generally the results of the large-scale tests were conservative. 19 refs., 20 figs., 4 tabs

Dynamic Loads and Wake Prediction for Large Wind Turbines Based on Free Wake Method

Institute of Scientific and Technical Information of China (English)

Cao Jiufa; Wang Tongguang; Long Hui; Ke Shitang; Xu Bofeng

2015-01-01

With large scale wind turbines ,the issue of aerodynamic elastic response is even more significant on dy-namic behaviour of the system .Unsteady free vortex wake method is proposed to calculate the shape of wake and aerodynamic load .Considering the effect of aerodynamic load ,inertial load and gravity load ,the decoupling dy-namic equations are established by using finite element method in conjunction of the modal method and equations are solved numerically by Newmark approach .Finally ,the numerical simulation of a large scale wind turbine is performed through coupling the free vortex wake modelling with structural modelling .The results show that this coupling model can predict the flexible wind turbine dynamic characteristics effectively and efficiently .Under the influence of the gravitational force ,the dynamic response of flapwise direction contributes to the dynamic behavior of edgewise direction under the operational condition of steady wind speed .The difference in dynamic response be-tween the flexible and rigid wind turbines manifests when the aerodynamics/structure coupling effect is of signifi-cance in both wind turbine design and performance calculation .

Design and implementation of dynamic hybrid Honeypot network

Science.gov (United States)

Qiao, Peili; Hu, Shan-Shan; Zhai, Ji-Qiang

2013-05-01

The method of constructing a dynamic and self-adaptive virtual network is suggested to puzzle adversaries, delay and divert attacks, exhaust attacker resources and collect attacking information. The concepts of Honeypot and Honeyd, which is the frame of virtual Honeypot are introduced. The techniques of network scanning including active fingerprint recognition are analyzed. Dynamic virtual network system is designed and implemented. A virtual network similar to real network topology is built according to the collected messages from real environments in this system. By doing this, the system can perplex the attackers when Hackers attack and can further analyze and research the attacks. The tests to this system prove that this design can successfully simulate real network environment and can be used in network security analysis.

Evolutionary dynamics of complex communications networks

CERN Document Server

Karyotis, Vasileios; Papavassiliou, Symeon

2013-01-01

Until recently, most network design techniques employed a bottom-up approach with lower protocol layer mechanisms affecting the development of higher ones. This approach, however, has not yielded fascinating results in the case of wireless distributed networks. Addressing the emerging aspects of modern network analysis and design, Evolutionary Dynamics of Complex Communications Networks introduces and develops a top-bottom approach where elements of the higher layer can be exploited in modifying the lowest physical topology-closing the network design loop in an evolutionary fashion similar to

Dynamic Aftershock Triggering Correlated with Cyclic Loading in the Slip Direction

Science.gov (United States)

Hardebeck, J.

2014-12-01

Dynamic stress changes have been shown to contribute to aftershock triggering, but the physical triggering mechanisms are not fully understood. Some proposed mechanisms are based on dynamic stress loading of the target fault in a direction that encourages earthquake slip (e.g. dynamic Coulomb stress triggering), while other mechanisms are based on fault weakening due to shaking. If dynamic stress loading in the fault slip direction plays a role in aftershock triggering, we would expect to see a relationship between the dynamic stress orientations and the aftershock focal mechanisms. Alternatively, if dynamic stress change triggering functions only through a fault weakening mechanism that is independent of the slip direction of the target fault, no such relationship is expected. I study aftershock sequences of 4 M≥6.7 mainshocks in southern California, and find a small but significant relationship between modeled dynamic stress direction and aftershock focal mechanisms. The mainshock dynamic stress changes have two observed impacts: changing the focal mechanisms in a given location to favor those aligned with the dynamic stress change, and changing the spatial distribution of seismicity to favor locations where the dynamic stress change aligns with the background stress. The aftershock focal mechanisms are significantly more aligned with the dynamic stress changes than the preshock mechanisms for only the first 0.5-1 year following most mainshocks, although for at least 10 years following Hector Mine. Dynamic stress effects on focal mechanisms are best observed at long periods (30-60 sec). Dynamic stress effects are only observed when using metrics based on repeated stress cycling in the same direction, for example considering the dominant stress orientation over the full time series, and not for the peak dynamic stress. These results imply that dynamic aftershock triggering operates at least in part through cyclic loading in the direction of fault slip, although

Application of the dynamically allocated virtual clustering management system to emulated tactical network experimentation

Science.gov (United States)

Marcus, Kelvin

2014-06-01

The U.S Army Research Laboratory (ARL) has built a "Network Science Research Lab" to support research that aims to improve their ability to analyze, predict, design, and govern complex systems that interweave the social/cognitive, information, and communication network genres. Researchers at ARL and the Network Science Collaborative Technology Alliance (NS-CTA), a collaborative research alliance funded by ARL, conducted experimentation to determine if automated network monitoring tools and task-aware agents deployed within an emulated tactical wireless network could potentially increase the retrieval of relevant data from heterogeneous distributed information nodes. ARL and NS-CTA required the capability to perform this experimentation over clusters of heterogeneous nodes with emulated wireless tactical networks where each node could contain different operating systems, application sets, and physical hardware attributes. Researchers utilized the Dynamically Allocated Virtual Clustering Management System (DAVC) to address each of the infrastructure support requirements necessary in conducting their experimentation. The DAVC is an experimentation infrastructure that provides the means to dynamically create, deploy, and manage virtual clusters of heterogeneous nodes within a cloud computing environment based upon resource utilization such as CPU load, available RAM and hard disk space. The DAVC uses 802.1Q Virtual LANs (VLANs) to prevent experimentation crosstalk and to allow for complex private networks. Clusters created by the DAVC system can be utilized for software development, experimentation, and integration with existing hardware and software. The goal of this paper is to explore how ARL and the NS-CTA leveraged the DAVC to create, deploy and manage multiple experimentation clusters to support their experimentation goals.

Exponential Synchronization of Uncertain Complex Dynamical Networks with Delay Coupling

International Nuclear Information System (INIS)

Wang Lifu; Kong Zhi; Jing Yuanwei

2010-01-01

This paper studies the global exponential synchronization of uncertain complex delayed dynamical networks. The network model considered is general dynamical delay networks with unknown network structure and unknown coupling functions but bounded. Novel delay-dependent linear controllers are designed via the Lyapunov stability theory. Especially, it is shown that the controlled networks are globally exponentially synchronized with a given convergence rate. An example of typical dynamical network of this class, having the Lorenz system at each node, has been used to demonstrate and verify the novel design proposed. And, the numerical simulation results show the effectiveness of proposed synchronization approaches. (general)

Concurrency-Induced Transitions in Epidemic Dynamics on Temporal Networks.

Science.gov (United States)

Onaga, Tomokatsu; Gleeson, James P; Masuda, Naoki

2017-09-08

Social contact networks underlying epidemic processes in humans and animals are highly dynamic. The spreading of infections on such temporal networks can differ dramatically from spreading on static networks. We theoretically investigate the effects of concurrency, the number of neighbors that a node has at a given time point, on the epidemic threshold in the stochastic susceptible-infected-susceptible dynamics on temporal network models. We show that network dynamics can suppress epidemics (i.e., yield a higher epidemic threshold) when the node's concurrency is low, but can also enhance epidemics when the concurrency is high. We analytically determine different phases of this concurrency-induced transition, and confirm our results with numerical simulations.

Concurrency-Induced Transitions in Epidemic Dynamics on Temporal Networks

Science.gov (United States)

Onaga, Tomokatsu; Gleeson, James P.; Masuda, Naoki

2017-09-01

Social contact networks underlying epidemic processes in humans and animals are highly dynamic. The spreading of infections on such temporal networks can differ dramatically from spreading on static networks. We theoretically investigate the effects of concurrency, the number of neighbors that a node has at a given time point, on the epidemic threshold in the stochastic susceptible-infected-susceptible dynamics on temporal network models. We show that network dynamics can suppress epidemics (i.e., yield a higher epidemic threshold) when the node's concurrency is low, but can also enhance epidemics when the concurrency is high. We analytically determine different phases of this concurrency-induced transition, and confirm our results with numerical simulations.

The application of backpropagation neural network method to estimate the sediment loads

Directory of Open Access Journals (Sweden)

Ari Gunawan Taufik

2017-01-01

Full Text Available Nearly all formulations of conventional sediment load estimation method were developed based on a review of laboratory data or data field. This approach is generally limited by local so it is only suitable for a particular river typology. From previous studies, the amount of sediment load tends to be non-linear with respect to the hydraulic parameters and parameter that accompanies sediment. The dominant parameter is turbulence, whereas turbulence flow velocity vector direction of x, y and z. They were affected by water bodies in 3D morphology of the cross section of the vertical and horizontal. This study is conducted to address the non-linear nature of the hydraulic parameter data and sediment parameter against sediment load data by applying the artificial neural network (ANN method. The method used is the backpropagation neural network (BPNN schema. This scheme used for projecting the sediment load from the hydraulic parameter data and sediment parameters that used in the conventional estimation of sediment load. The results showed that the BPNN model performs reasonably well on the conventional calculation, indicated by the stability of correlation coefficient (R and the mean square error (MSE.

Modelling self-optimised short term load forecasting for medium voltage loads using tunning fuzzy systems and Artificial Neural Networks

International Nuclear Information System (INIS)

Mahmoud, Thair S.; Habibi, Daryoush; Hassan, Mohammed Y.; Bass, Octavian

2015-01-01

Highlights: • A novel Short Term Medium Voltage (MV) Load Forecasting (STLF) model is presented. • A knowledge-based STLF error control mechanism is implemented. • An Artificial Neural Network (ANN)-based optimum tuning is applied on STLF. • The relationship between load profiles and operational conditions is analysed. - Abstract: This paper presents an intelligent mechanism for Short Term Load Forecasting (STLF) models, which allows self-adaptation with respect to the load operational conditions. Specifically, a knowledge-based FeedBack Tunning Fuzzy System (FBTFS) is proposed to instantaneously correlate the information about the demand profile and its operational conditions to make decisions for controlling the model’s forecasting error rate. To maintain minimum forecasting error under various operational scenarios, the FBTFS adaptation was optimised using a Multi-Layer Perceptron Artificial Neural Network (MLPANN), which was trained using Backpropagation algorithm, based on the information about the amount of error and the operational conditions at time of forecasting. For the sake of comparison and performance testing, this mechanism was added to the conventional forecasting methods, i.e. Nonlinear AutoRegressive eXogenous-Artificial Neural Network (NARXANN), Fuzzy Subtractive Clustering Method-based Adaptive Neuro Fuzzy Inference System (FSCMANFIS) and Gaussian-kernel Support Vector Machine (GSVM), and the measured forecasting error reduction average in a 12 month simulation period was 7.83%, 8.5% and 8.32% respectively. The 3.5 MW variable load profile of Edith Cowan University (ECU) in Joondalup, Australia, was used in the modelling and simulations of this model, and the data was provided by Western Power, the transmission and distribution company of the state of Western Australia.

Dynamics of subway networks based on vehicles operation timetable

Science.gov (United States)

Xiao, Xue-mei; Jia, Li-min; Wang, Yan-hui

2017-05-01

In this paper, a subway network is represented as a dynamic, directed and weighted graph, in which vertices represent subway stations and weights of edges represent the number of vehicles passing through the edges by considering vehicles operation timetable. Meanwhile the definitions of static and dynamic metrics which can represent vertices' and edges' local and global attributes are proposed. Based on the model and metrics, standard deviation is further introduced to study the dynamic properties (heterogeneity and vulnerability) of subway networks. Through a detailed analysis of the Beijing subway network, we conclude that with the existing network structure, the heterogeneity and vulnerability of the Beijing subway network varies over time when the vehicle operation timetable is taken into consideration, and the distribution of edge weights affects the performance of the network. In other words, although the vehicles operation timetable is restrained by the physical structure of the network, it determines the performances and properties of the Beijing subway network.

Optimal Base Station Density of Dense Network: From the Viewpoint of Interference and Load.

Science.gov (United States)

Feng, Jianyuan; Feng, Zhiyong

2017-09-11

Network densification is attracting increasing attention recently due to its ability to improve network capacity by spatial reuse and relieve congestion by offloading. However, excessive densification and aggressive offloading can also cause the degradation of network performance due to problems of interference and load. In this paper, with consideration of load issues, we study the optimal base station density that maximizes the throughput of the network. The expected link rate and the utilization ratio of the contention-based channel are derived as the functions of base station density using the Poisson Point Process (PPP) and Markov Chain. They reveal the rules of deployment. Based on these results, we obtain the throughput of the network and indicate the optimal deployment density under different network conditions. Extensive simulations are conducted to validate our analysis and show the substantial performance gain obtained by the proposed deployment scheme. These results can provide guidance for the network densification.

Effect of Static-Dynamic Coupling Loading on Fracture Toughness and Failure Characteristics in Marble

Directory of Open Access Journals (Sweden)

Z. Q. Yin

2014-03-01

Full Text Available Fracture experiments in a notched semi-circular bend configuration were conducted to test the dynamic fracture toughness of a marble under static-dynamic coupling load using a modified split Hopkinson pressure bar. The fracture process of the specimen was monitored using a high speed (HS camera. Based on digital image correlation (DIC and strain gauges, the full-field strain fields and time-to-fracture of the marble were measured under static-dynamic coupling load. Experimental results show that dynamic fracture toughness was well determined, and the HS-DIC technique provides reliable full-field strain fields in the specimens under static-dynamic coupling loads. The failure characteristics of the marble under external impact were affected obviously by pre-compression stress. Increase of axial pre-compression stress was helpful to improve the crack propagation velocity, and dynamic crack initiation toughness was decreased.

Influence of the implant abutment types and the dynamic loading on initial screw loosening

Science.gov (United States)

Kim, Eun-Sook

2013-01-01

PURPOSE This study examined the effects of the abutment types and dynamic loading on the stability of implant prostheses with three types of implant abutments prepared using different fabrication methods by measuring removal torque both before and after dynamic loading. MATERIALS AND METHODS Three groups of abutments were produced using different types of fabrication methods; stock abutment, gold cast abutment, and CAD/CAM custom abutment. A customized jig was fabricated to apply the load at 30° to the long axis. The implant fixtures were fixed to the jig, and connected to the abutments with a 30 Ncm tightening torque. A sine curved dynamic load was applied for 105 cycles between 25 and 250 N at 14 Hz. Removal torque before loading and after loading were evaluated. The SPSS was used for statistical analysis of the results. A Kruskal-Wallis test was performed to compare screw loosening between the abutment systems. A Wilcoxon signed-rank test was performed to compare screw loosening between before and after loading in each group (α=0.05). RESULTS Removal torque value before loading and after loading was the highest in stock abutment, which was then followed by gold cast abutment and CAD/CAM custom abutment, but there were no significant differences. CONCLUSION The abutment types did not have a significant influence on short term screw loosening. On the other hand, after 105 cycles dynamic loading, CAD/CAM custom abutment affected the initial screw loosening, but stock abutment and gold cast abutment did not. PMID:23509006

Dynamical Model of Rocket Propellant Loading with Liquid Hydrogen

Data.gov (United States)

National Aeronautics and Space Administration — A dynamical model describing the multi-stage process of rocket propellant loading has been developed. It accounts for both the nominal and faulty regimes of...

Modeling Insurgent Network Structure and Dynamics

Science.gov (United States)

Gabbay, Michael; Thirkill-Mackelprang, Ashley

2010-03-01

We present a methodology for mapping insurgent network structure based on their public rhetoric. Indicators of cooperative links between insurgent groups at both the leadership and rank-and-file levels are used, such as joint policy statements or joint operations claims. In addition, a targeting policy measure is constructed on the basis of insurgent targeting claims. Network diagrams which integrate these measures of insurgent cooperation and ideology are generated for different periods of the Iraqi and Afghan insurgencies. The network diagrams exhibit meaningful changes which track the evolution of the strategic environment faced by insurgent groups. Correlations between targeting policy and network structure indicate that insurgent targeting claims are aimed at establishing a group identity among the spectrum of rank-and-file insurgency supporters. A dynamical systems model of insurgent alliance formation and factionalism is presented which evolves the relationship between insurgent group dyads as a function of their ideological differences and their current relationships. The ability of the model to qualitatively and quantitatively capture insurgent network dynamics observed in the data is discussed.

Dynamic motifs in socio-economic networks

Science.gov (United States)

Zhang, Xin; Shao, Shuai; Stanley, H. Eugene; Havlin, Shlomo

2014-12-01

Socio-economic networks are of central importance in economic life. We develop a method of identifying and studying motifs in socio-economic networks by focusing on “dynamic motifs,” i.e., evolutionary connection patterns that, because of “node acquaintances” in the network, occur much more frequently than random patterns. We examine two evolving bi-partite networks: i) the world-wide commercial ship chartering market and ii) the ship build-to-order market. We find similar dynamic motifs in both bipartite networks, even though they describe different economic activities. We also find that “influence” and “persistence” are strong factors in the interaction behavior of organizations. When two companies are doing business with the same customer, it is highly probable that another customer who currently only has business relationship with one of these two companies, will become customer of the second in the future. This is the effect of influence. Persistence means that companies with close business ties to customers tend to maintain their relationships over a long period of time.

Dynamic load balancing algorithm for molecular dynamics based on Voronoi cells domain decompositions

Energy Technology Data Exchange (ETDEWEB)

Fattebert, J.-L. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Richards, D.F. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Glosli, J.N. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2012-12-01

We present a new algorithm for automatic parallel load balancing in classical molecular dynamics. It assumes a spatial domain decomposition of particles into Voronoi cells. It is a gradient method which attempts to minimize a cost function by displacing Voronoi sites associated with each processor/sub-domain along steepest descent directions. Excellent load balance has been obtained for quasi-2D and 3D practical applications, with up to 440·10⁶ particles on 65,536 MPI tasks.

Peak load demand forecasting using two-level discrete wavelet decomposition and neural network algorithm

Science.gov (United States)

Bunnoon, Pituk; Chalermyanont, Kusumal; Limsakul, Chusak

2010-02-01

This paper proposed the discrete transform and neural network algorithms to obtain the monthly peak load demand in mid term load forecasting. The mother wavelet daubechies2 (db2) is employed to decomposed, high pass filter and low pass filter signals from the original signal before using feed forward back propagation neural network to determine the forecasting results. The historical data records in 1997-2007 of Electricity Generating Authority of Thailand (EGAT) is used as reference. In this study, historical information of peak load demand(MW), mean temperature(Tmean), consumer price index (CPI), and industrial index (economic:IDI) are used as feature inputs of the network. The experimental results show that the Mean Absolute Percentage Error (MAPE) is approximately 4.32%. This forecasting results can be used for fuel planning and unit commitment of the power system in the future.

Strength and behavior in shear of reinforced concrete deep beams under dynamic loading conditions

Energy Technology Data Exchange (ETDEWEB)

Adhikary, Satadru Das [School of Civil and Environmental Engineering, Nanyang Technological University, 639798 (Singapore); Li, Bing, E-mail: cbli@ntu.edu.sg [School of Civil and Environmental Engineering, Nanyang Technological University, 639798 (Singapore); Fujikake, Kazunori [Department of Civil and Environmental Engineering, National Defense Academy, Yokosuka 239 8686 (Japan)

2013-06-15

Highlights: ► Effects of wider range of loading rates on dynamic shear behavior of RC deep beams. ► Experimental investigation of RC deep beam with and without shear reinforcements. ► Verification of experimental results with truss model and FE simulation results. ► Empirical equations are proposed to predict the dynamic increase factor of maximum resistance. -- Abstract: Research on reinforced concrete (RC) deep beams has seen considerable headway over the past three decades; however, information on the dynamic shear strength and behavior of RC deep beams under varying rates of loads remains limited. This paper describes the experimental results of 24 RC deep beams with and without shear reinforcements under varying rates of concentrated loading. Results obtained serve as useful data on shear resistance, failure patterns and strain rates corresponding to varying loading rates. An analytical truss model approach proves its efficacy in predicting the dynamic shear resistance under varying loading rates. Furthermore, three-dimensional nonlinear finite element (FE) model is described and the simulation results are verified with the experimental results. A parametric study is then conducted to investigate the influence of longitudinal reinforcement ratio, transverse reinforcement ratio and shear span to effective depth ratio on shear behavior. Subsequently, two empirical equations were proposed by integrating the various parameters to assess the dynamic increase factor (DIF) of maximum resistance under varying rates of concentrated loading.

Dynamic behaviour of TM380 mild steel and Ti6Al4V alloy subjected to blast loading

CSIR Research Space (South Africa)

Shoke, Lerato

2016-10-01

Full Text Available and Base Metals Development Network Conference 2016, 19-20 October 2016, KwaZulu Natal, Maharani Hotel Dynamic behaviour of TM380 mild steel and Ti6Al4V alloy subjected to blast loading L. Shoke,1* K. Mutombo2, I.M. Snyman1 and T. Sono1 1... Landwards Sciences, Defence Peace Safety and Security (DPSS), 2 Material Sciences and Manufacturing (MSM), Council for Scientific and Industrial Research (CSIR), Pretoria, South Africa Lshoke@csir.co.za Abstract This paper deals...

Dynamic Axle Load of an Automotive Vehicle When Driven on a Mobile Measurement Platform

OpenAIRE

Jagiełowicz-Ryznar C.

2014-01-01

An analysis of the dynamic axle load of an automotive vehicle (AV) when it is driven on a mobile measurement platform is presented in this paper. During the ride, the time characteristic of the dynamic force N(t), acting on the axle, was recorded. The effect of the vehicle axle mass on the maximum dynamic force value and the dynamic coefficient were studied. On this basis it was attempted to calculate the total vehicle’s weight. Conclusions concerning the dynamic loads of the vehicle axles in...

Resumption of dynamism in damaged networks of coupled oscillators

Science.gov (United States)

Kundu, Srilena; Majhi, Soumen; Ghosh, Dibakar

2018-05-01

Deterioration in dynamical activities may come up naturally or due to environmental influences in a massive portion of biological and physical systems. Such dynamical degradation may have outright effect on the substantive network performance. This requires us to provide some proper prescriptions to overcome undesired circumstances. In this paper, we present a scheme based on external feedback that can efficiently revive dynamism in damaged networks of active and inactive oscillators and thus enhance the network survivability. Both numerical and analytical investigations are performed in order to verify our claim. We also provide a comparative study on the effectiveness of this mechanism for feedbacks to the inactive group or to the active group only. Most importantly, resurrection of dynamical activity is realized even in time-delayed damaged networks, which are considered to be less persistent against deterioration in the form of inactivity in the oscillators. Furthermore, prominence in our approach is substantiated by providing evidence of enhanced network persistence in complex network topologies taking small-world and scale-free architectures, which makes the proposed remedy quite general. Besides the study in the network of Stuart-Landau oscillators, affirmative influence of external feedback has been justified in the network of chaotic Rössler systems as well.

Energy Efficient Caching in Backhaul-Aware Cellular Networks with Dynamic Content Popularity

Directory of Open Access Journals (Sweden)

Jiequ Ji

2018-01-01

Full Text Available Caching popular contents at base stations (BSs has been regarded as an effective approach to alleviate the backhaul load and to improve the quality of service. To meet the explosive data traffic demand and to save energy consumption, energy efficiency (EE has become an extremely important performance index for the 5th generation (5G cellular networks. In general, there are two ways for improving the EE for caching, that is, improving the cache-hit rate and optimizing the cache size. In this work, we investigate the energy efficient caching problem in backhaul-aware cellular networks jointly considering these two approaches. Note that most existing works are based on the assumption that the content catalog and popularity are static. However, in practice, content popularity is dynamic. To timely estimate the dynamic content popularity, we propose a method based on shot noise model (SNM. Then we propose a distributed caching policy to improve the cache-hit rate in such a dynamic environment. Furthermore, we analyze the tradeoff between energy efficiency and cache capacity for which an optimization is formulated. We prove its convexity and derive a closed-form optimal cache capacity for maximizing the EE. Simulation results validate the proposed scheme and show that EE can be improved with appropriate choice of cache capacity.

Impact of the variation in dynamic vehicle load on flexible pavement responses

Science.gov (United States)

Ahsanuzzaman, Md

The purpose of this research was to evaluate the dynamic variation in asphalt pavement critical responses due to dynamic tire load variations. An attempt was also made to develop generalized regression equations to predict the dynamic response variation in flexible pavement under various dynamic load conditions. The study used an extensive database of computed pavement response histories for five different types of sites (smooth, rough, medium rough, very rough and severely rough), two different asphalt pavement structures (thin and thick) at two temperatures (70 °F and 104 °F), subjected to a tandem axle dual tire at three speeds 25, 37 and 50 mph (40, 60 and 80 km/h). All pavement responses were determined using the 3D-Move Analysis program (Version 1.2) developed by University of Nevada, Reno. A new term called Dynamic Response Coefficient (DRC) was introduced in this study to address the variation in critical pavement responses due to dynamic loads as traditionally measured by the Dynamic Load Coefficient (DLC). While DLC represents the additional varying component of the tire load, DRC represents the additional varying component of the response value (standard deviation divided by mean response). In this study, DRC was compared with DLC for five different sites based on the roughness condition of the sites. Previous studies showed that DLC varies with vehicle speed and suspension types, and assumes a constant value for the whole pavement structure (lateral and vertical directions). On the other hand, in this study, DRC was found to be significantly varied with the asphalt pavement and function of pavement structure, road roughness conditions, temperatures, vehicle speeds, suspension types, and locations of the point of interest in the pavement. A major contribution of the study is that the variation of pavement responses due to dynamic load in a flexible pavement system can be predicted with generalized regression equations. Fitting parameters (R2) in the

Efficient graph-based dynamic load-balancing for parallel large-scale agent-based traffic simulation

NARCIS (Netherlands)

Xu, Y.; Cai, W.; Aydt, H.; Lees, M.; Tolk, A.; Diallo, S.Y.; Ryzhov, I.O.; Yilmaz, L.; Buckley, S.; Miller, J.A.

2014-01-01

One of the issues of parallelizing large-scale agent-based traffic simulations is partitioning and load-balancing. Traffic simulations are dynamic applications where the distribution of workload in the spatial domain constantly changes. Dynamic load-balancing at run-time has shown better efficiency

The Social Dynamics of Innovation Networks

NARCIS (Netherlands)

Rutten, Roel; Benneworth, Paul Stephen; Irawati, Dessy; Boekema, Frans

2014-01-01

The social dynamics of innovation networks captures the important role of trust, social capital, institutions and norms and values in the creation of knowledge in innovation networks. In doing so, this book connects to a long-standing debate on the socio-spatial context of innovation in economic

Dynamical Adaptation in Terrorist Cells/Networks

DEFF Research Database (Denmark)

Hussain, Dil Muhammad Akbar; Ahmed, Zaki

2010-01-01

Typical terrorist cells/networks have dynamical structure as they evolve or adapt to changes which may occur due to capturing or killing of a member of the cell/network. Analytical measures in graph theory like degree centrality, betweenness and closeness centralities are very common and have long...

Abnormal cascading failure spreading on complex networks

International Nuclear Information System (INIS)

Wang, Jianwei; Sun, Enhui; Xu, Bo; Li, Peng; Ni, Chengzhang

2016-01-01

Applying the mechanism of the preferential selection of the flow destination, we develop a new method to quantify the initial load on an edge, of which the flow is transported along the path with the shortest edge weight between two nodes. Considering the node weight, we propose a cascading model on the edge and investigate cascading dynamics induced by the removal of the edge with the largest load. We perform simulated attacks on four types of constructed networks and two actual networks and observe an interesting and counterintuitive phenomenon of the cascading spreading, i.e., gradually improving the capacity of nodes does not lead to the monotonous increase in the robustness of these networks against cascading failures. The non monotonous behavior of cascading dynamics is well explained by the analysis on a simple graph. We additionally study the effect of the parameter of the node weight on cascading dynamics and evaluate the network robustness by a new metric.

Efficient Neural Network Modeling for Flight and Space Dynamics Simulation

Directory of Open Access Journals (Sweden)

Ayman Hamdy Kassem

2011-01-01

Full Text Available This paper represents an efficient technique for neural network modeling of flight and space dynamics simulation. The technique will free the neural network designer from guessing the size and structure for the required neural network model and will help to minimize the number of neurons. For linear flight/space dynamics systems, the technique can find the network weights and biases directly by solving a system of linear equations without the need for training. Nonlinear flight dynamic systems can be easily modeled by training its linearized models keeping the same network structure. The training is fast, as it uses the linear system knowledge to speed up the training process. The technique is tested on different flight/space dynamic models and showed promising results.

Clustering promotes switching dynamics in networks of noisy neurons

Science.gov (United States)

Franović, Igor; Klinshov, Vladimir

2018-02-01

Macroscopic variability is an emergent property of neural networks, typically manifested in spontaneous switching between the episodes of elevated neuronal activity and the quiescent episodes. We investigate the conditions that facilitate switching dynamics, focusing on the interplay between the different sources of noise and heterogeneity of the network topology. We consider clustered networks of rate-based neurons subjected to external and intrinsic noise and derive an effective model where the network dynamics is described by a set of coupled second-order stochastic mean-field systems representing each of the clusters. The model provides an insight into the different contributions to effective macroscopic noise and qualitatively indicates the parameter domains where switching dynamics may occur. By analyzing the mean-field model in the thermodynamic limit, we demonstrate that clustering promotes multistability, which gives rise to switching dynamics in a considerably wider parameter region compared to the case of a non-clustered network with sparse random connection topology.

Modelling flow dynamics in water distribution networks using ...

African Journals Online (AJOL)

One such approach is the Artificial Neural Networks (ANNs) technique. The advantage of ANNs is that they are robust and can be used to model complex linear and non-linear systems without making implicit assumptions. ANNs can be trained to forecast flow dynamics in a water distribution network. Such flow dynamics ...

Advances in dynamic network modeling in complex transportation systems

CERN Document Server

Ukkusuri, Satish V

2013-01-01

This book focuses on the latest in dynamic network modeling, including route guidance and traffic control in transportation systems and other complex infrastructure networks. Covers dynamic traffic assignment, flow modeling, mobile sensor deployment and more.

Higher-Order Synaptic Interactions Coordinate Dynamics in Recurrent Networks.

Directory of Open Access Journals (Sweden)

Brendan Chambers

2016-08-01

Full Text Available Linking synaptic connectivity to dynamics is key to understanding information processing in neocortex. Circuit dynamics emerge from complex interactions of interconnected neurons, necessitating that links between connectivity and dynamics be evaluated at the network level. Here we map propagating activity in large neuronal ensembles from mouse neocortex and compare it to a recurrent network model, where connectivity can be precisely measured and manipulated. We find that a dynamical feature dominates statistical descriptions of propagating activity for both neocortex and the model: convergent clusters comprised of fan-in triangle motifs, where two input neurons are themselves connected. Fan-in triangles coordinate the timing of presynaptic inputs during ongoing activity to effectively generate postsynaptic spiking. As a result, paradoxically, fan-in triangles dominate the statistics of spike propagation even in randomly connected recurrent networks. Interplay between higher-order synaptic connectivity and the integrative properties of neurons constrains the structure of network dynamics and shapes the routing of information in neocortex.

Fatigue behaviour of core-spun yarns containing filament by means of cyclic dynamic loading

Science.gov (United States)

Esin, S.; Osman, B.

2017-10-01

The behaviour of yarns under dynamic loading is important that leads to understand the growth characteristics which is exposed to repetitive loadings during usage of fabric made from these yarns. Fabric growth is undesirable property that originated from low resilience characteristics of fabric. In this study, the effects of the filament fineness and yarn linear density on fatigue behaviour of rigid-core spun yarns were determined. Cotton covered yarns containing different filament fineness of polyester (PET) draw textured yarns (DTY) (100d/36f, 100d/96f, 100d/144f, 100d/192f and 100d/333f) and yarn linear densities (37 tex, 30 tex, 25 tex and 21 tex) were manufactured by using a modified ring spinning system at the same spinning parameters. Repetitive loads were applied for 25 cycles at levels between 0.1 and 3 N. Dynamic modulus and dynamic strain of yarn samples were analyzed statistically. Results showed that filament fineness and yarn linear density have significance effect on dynamic modulus and dynamic strain after cyclic loading.

Load control strategies in 2G mobile network for W-CDMA radio ...

African Journals Online (AJOL)

Network planning requires a faithful analysis of each individual cell's capacity. In this paper, we examine load control equations as a resource allocation tool to analyse cell capacity for the uplink and downlink of Wideband Code Division Multiple Access (W-CDMA) networks. In the uplink, the noise rise is a parameter of ...

Actin dynamics and the elasticity of cytoskeletal networks

Directory of Open Access Journals (Sweden)

2009-09-01

Full Text Available The structural integrity of a cell depends on its cytoskeleton, which includes an actin network. This network is transient and depends upon the continual polymerization and depolymerization of actin. The degradation of an actin network, and a corresponding reduction in cell stiffness, can indicate the presence of disease. Numerical simulations will be invaluable for understanding the physics of these systems and the correlation between actin dynamics and elasticity. Here we develop a model that is capable of generating actin network structures. In particular, we develop a model of actin dynamics which considers the polymerization, depolymerization, nucleation, severing, and capping of actin filaments. The structures obtained are then fed directly into a mechanical model. This allows us to qualitatively assess the effects of changing various parameters associated with actin dynamics on the elasticity of the material.

Dynamic Data-Driven UAV Network for Plume Characterization

Science.gov (United States)

2016-05-23

AFRL-AFOSR-VA-TR-2016-0203 Dynamic Data-Driven UAV Network for Plume Characterization Kamran Mohseni UNIVERSITY OF FLORIDA Final Report 05/23/2016...AND SUBTITLE Dynamic Data-Driven UAV Network for Plume Characterization 5a.  CONTRACT NUMBER 5b.  GRANT NUMBER FA9550-13-1-0090 5c.  PROGRAM ELEMENT...studied a dynamic data driven (DDD) approach to operation of a heterogeneous team of unmanned aerial vehicles ( UAVs ) or micro/miniature aerial

Dynamical graph theory networks techniques for the analysis of sparse connectivity networks in dementia

Science.gov (United States)

Tahmassebi, Amirhessam; Pinker-Domenig, Katja; Wengert, Georg; Lobbes, Marc; Stadlbauer, Andreas; Romero, Francisco J.; Morales, Diego P.; Castillo, Encarnacion; Garcia, Antonio; Botella, Guillermo; Meyer-Bäse, Anke

2017-05-01

Graph network models in dementia have become an important computational technique in neuroscience to study fundamental organizational principles of brain structure and function of neurodegenerative diseases such as dementia. The graph connectivity is reflected in the connectome, the complete set of structural and functional connections of the graph network, which is mostly based on simple Pearson correlation links. In contrast to simple Pearson correlation networks, the partial correlations (PC) only identify direct correlations while indirect associations are eliminated. In addition to this, the state-of-the-art techniques in brain research are based on static graph theory, which is unable to capture the dynamic behavior of the brain connectivity, as it alters with disease evolution. We propose a new research avenue in neuroimaging connectomics based on combining dynamic graph network theory and modeling strategies at different time scales. We present the theoretical framework for area aggregation and time-scale modeling in brain networks as they pertain to disease evolution in dementia. This novel paradigm is extremely powerful, since we can derive both static parameters pertaining to node and area parameters, as well as dynamic parameters, such as system's eigenvalues. By implementing and analyzing dynamically both disease driven PC-networks and regular concentration networks, we reveal differences in the structure of these network that play an important role in the temporal evolution of this disease. The described research is key to advance biomedical research on novel disease prediction trajectories and dementia therapies.

Dynamical community structure of populations evolving on genotype networks

International Nuclear Information System (INIS)

Capitán, José A.; Aguirre, Jacobo; Manrubia, Susanna

2015-01-01

Neutral evolutionary dynamics of replicators occurs on large and heterogeneous networks of genotypes. These networks, formed by all genotypes that yield the same phenotype, have a complex architecture that conditions the molecular composition of populations and their movements on genome spaces. Here we consider as an example the case of populations evolving on RNA secondary structure neutral networks and study the community structure of the network revealed through dynamical properties of the population at equilibrium and during adaptive transients. We unveil a rich hierarchical community structure that, eventually, can be traced back to the non-trivial relationship between RNA secondary structure and sequence composition. We demonstrate that usual measures of modularity that only take into account the static, topological structure of networks, cannot identify the community structure disclosed by population dynamics

Structure-based control of complex networks with nonlinear dynamics.

Science.gov (United States)

Zañudo, Jorge Gomez Tejeda; Yang, Gang; Albert, Réka

2017-07-11

What can we learn about controlling a system solely from its underlying network structure? Here we adapt a recently developed framework for control of networks governed by a broad class of nonlinear dynamics that includes the major dynamic models of biological, technological, and social processes. This feedback-based framework provides realizable node overrides that steer a system toward any of its natural long-term dynamic behaviors, regardless of the specific functional forms and system parameters. We use this framework on several real networks, identify the topological characteristics that underlie the predicted node overrides, and compare its predictions to those of structural controllability in control theory. Finally, we demonstrate this framework's applicability in dynamic models of gene regulatory networks and identify nodes whose override is necessary for control in the general case but not in specific model instances.

Load reduction test method of similarity theory and BP neural networks of large cranes

Science.gov (United States)

Yang, Ruigang; Duan, Zhibin; Lu, Yi; Wang, Lei; Xu, Gening

2016-01-01

Static load tests are an important means of supervising and detecting a crane's lift capacity. Due to space restrictions, however, there are difficulties and potential danger when testing large bridge cranes. To solve the loading problems of large-tonnage cranes during testing, an equivalency test is proposed based on the similarity theory and BP neural networks. The maximum stress and displacement of a large bridge crane is tested in small loads, combined with the training neural network of a similar structure crane through stress and displacement data which is collected by a physics simulation progressively loaded to a static load test load within the material scope of work. The maximum stress and displacement of a crane under a static load test load can be predicted through the relationship of stress, displacement, and load. By measuring the stress and displacement of small tonnage weights, the stress and displacement of large loads can be predicted, such as the maximum load capacity, which is 1.25 times the rated capacity. Experimental study shows that the load reduction test method can reflect the lift capacity of large bridge cranes. The load shedding predictive analysis for Sanxia 1200 t bridge crane test data indicates that when the load is 1.25 times the rated lifting capacity, the predicted displacement and actual displacement error is zero. The method solves the problem that lifting capacities are difficult to obtain and testing accidents are easily possible when 1.25 times related weight loads are tested for large tonnage cranes.

On the dynamic stability of shear deformable beams under a tensile load

Science.gov (United States)

Caddemi, S.; Caliò, I.; Cannizzaro, F.

2016-07-01

Loss of stability of beams in a linear static context due to the action of tensile loads has been disclosed only recently in the scientific literature. However, tensile instability in the dynamic regime has been only marginally covered. Several aspects concerning the role of shear deformation on the tensile dynamic instability on continuous and discontinuous beams are still to be addressed. It may appear as a paradox, but also for the case of the universally studied Timoshenko beam model, despite its old origin, frequency-axial load diagrams in the range of negative values of the load (i.e. tensile load) has never been brought to light. In this paper, for the first time, the influence of a conservative tensile axial loads on the dynamic behaviour of the Timoshenko model, according to the Haringx theory, is assessed. It is shown that, under increasing tensile loads, regions of positive/negative fundamental frequency variations can be distinguished. In addition, the beam undergoes eigen-mode changes, from symmetric to anti-symmetric shapes, until tensile instability of divergence type is reached. As a further original contribution on the subject, taking advantage of a new closed form solution, it is shown that the same peculiarities are recovered for an axially loaded Euler-Bernoulli vibrating beam with multiple elastic sliders. This latter model can be considered as the discrete counterpart of the Timoshenko beam-column in which the internal sliders concentrate the shear deformation that in the Timoshenko model is continuously distributed. Original aspects regarding the evolution of the vibration frequencies and the relevant mode shapes with the tensile load value are highlighted.

Enhanced method of fast re-routing with load balancing in software-defined networks

Science.gov (United States)

Lemeshko, Oleksandr; Yeremenko, Oleksandra

2017-11-01

A two-level method of fast re-routing with load balancing in a software-defined network (SDN) is proposed. The novelty of the method consists, firstly, in the introduction of a two-level hierarchy of calculating the routing variables responsible for the formation of the primary and backup paths, and secondly, in ensuring a balanced load of the communication links of the network, which meets the requirements of the traffic engineering concept. The method provides implementation of link, node, path, and bandwidth protection schemes for fast re-routing in SDN. The separation in accordance with the interaction prediction principle along two hierarchical levels of the calculation functions of the primary (lower level) and backup (upper level) routes allowed to abandon the initial sufficiently large and nonlinear optimization problem by transiting to the iterative solution of linear optimization problems of half the dimension. The analysis of the proposed method confirmed its efficiency and effectiveness in terms of obtaining optimal solutions for ensuring balanced load of communication links and implementing the required network element protection schemes for fast re-routing in SDN.

Influence of the implant abutment types and the dynamic loading on initial screw loosening

OpenAIRE

Kim, Eun-Sook; Shin, Soo-Yeon

2013-01-01

PURPOSE This study examined the effects of the abutment types and dynamic loading on the stability of implant prostheses with three types of implant abutments prepared using different fabrication methods by measuring removal torque both before and after dynamic loading. MATERIALS AND METHODS Three groups of abutments were produced using different types of fabrication methods; stock abutment, gold cast abutment, and CAD/CAM custom abutment. A customized jig was fabricated to apply the load at ...

Dynamic social networks based on movement

Science.gov (United States)

Scharf, Henry; Hooten, Mevin B.; Fosdick, Bailey K.; Johnson, Devin S.; London, Joshua M.; Durban, John W.

2016-01-01

Network modeling techniques provide a means for quantifying social structure in populations of individuals. Data used to define social connectivity are often expensive to collect and based on case-specific, ad hoc criteria. Moreover, in applications involving animal social networks, collection of these data is often opportunistic and can be invasive. Frequently, the social network of interest for a given population is closely related to the way individuals move. Thus, telemetry data, which are minimally invasive and relatively inexpensive to collect, present an alternative source of information. We develop a framework for using telemetry data to infer social relationships among animals. To achieve this, we propose a Bayesian hierarchical model with an underlying dynamic social network controlling movement of individuals via two mechanisms: an attractive effect and an aligning effect. We demonstrate the model and its ability to accurately identify complex social behavior in simulation, and apply our model to telemetry data arising from killer whales. Using auxiliary information about the study population, we investigate model validity and find the inferred dynamic social network is consistent with killer whale ecology and expert knowledge.

Dynamic Frequency Control in Power Networks

OpenAIRE

Zhao, Changhong; Mallada Garcia, Enrique; Low, Steven H.

2016-01-01

Node controllers in power distribution networks in accordance with embodiments of the invention enable dynamic frequency control. One embodiment includes a node controller comprising a network interface a processor; and a memory containing a frequency control application; and a plurality of node operating parameters describing the operating parameters of a node, where the node is selected from a group consisting of at least one generator node in a power distribution network wherein the proces...

Network evolution driven by dynamics applied to graph coloring

International Nuclear Information System (INIS)

Wu Jian-She; Li Li-Guang; Yu Xin; Jiao Li-Cheng; Wang Xiao-Hua

2013-01-01

An evolutionary network driven by dynamics is studied and applied to the graph coloring problem. From an initial structure, both the topology and the coupling weights evolve according to the dynamics. On the other hand, the dynamics of the network are determined by the topology and the coupling weights, so an interesting structure-dynamics co-evolutionary scheme appears. By providing two evolutionary strategies, a network described by the complement of a graph will evolve into several clusters of nodes according to their dynamics. The nodes in each cluster can be assigned the same color and nodes in different clusters assigned different colors. In this way, a co-evolution phenomenon is applied to the graph coloring problem. The proposed scheme is tested on several benchmark graphs for graph coloring

Dynamic network expansion, contraction, and connectivity in the river corridor of mountain stream network

Science.gov (United States)

Ward, A. S.; Schmadel, N.; Wondzell, S. M.

2017-12-01

River networks are broadly recognized to expand and contract in response to hydrologic forcing. Additionally, the individual controls on river corridor dynamics of hydrologic forcing and geologic setting are well recognized. However, we currently lack tools to integrate our understanding of process dynamics in the river corridor and make predictions at the scale of river networks. In this study, we develop a perceptual model of the river corridor in mountain river networks, translate this into a reduced-complexity mechanistic model, and implement the model in a well-studied headwater catchment. We found that the river network was most sensitive to hydrologic dynamics under the lowest discharges (Qgauge managers of water resources who need to estimate connectivity and flow initiation location along the river corridor over broad, unstudied catchments.

Applications of flow-networks to opinion-dynamics

Science.gov (United States)

Tupikina, Liubov; Kurths, Jürgen

2015-04-01

Networks were successfully applied to describe complex systems, such as brain, climate, processes in society. Recently a socio-physical problem of opinion-dynamics was studied using network techniques. We present the toy-model of opinion-formation based on the physical model of advection-diffusion. We consider spreading of the opinion on the fixed subject, assuming that opinion on society is binary: if person has opinion then the state of the node in the society-network equals 1, if the person doesn't have opinion state of the node equals 0. Opinion can be spread from one person to another if they know each other, or in the network-terminology, if the nodes are connected. We include into the system governed by advection-diffusion equation the external field to model such effects as for instance influence from media. The assumptions for our model can be formulated as the following: 1.the node-states are influenced by the network structure in such a way, that opinion can be spread only between adjacent nodes (the advective term of the opinion-dynamics), 2.the network evolution can have two scenarios: -network topology is not changing with time; -additional links can appear or disappear each time-step with fixed probability which requires adaptive networks properties. Considering these assumptions for our system we obtain the system of equations describing our model-dynamics which corresponds well to other socio-physics models, for instance, the model of the social cohesion and the famous voter-model. We investigate the behavior of the suggested model studying "waiting time" of the system, time to get to the stable state, stability of the model regimes for different values of model parameters and network topology.

A 3D Lumped Thermal Network Model for Long-term Load Profiles Analysis in High Power IGBT Modules

DEFF Research Database (Denmark)

Bahman, Amir Sajjad; Ma, Ke; Ghimire, Pramod

2016-01-01

)-based simulation is another method which is often used to analyze the steady-state thermal distribution of IGBT modules, but it is not possible to be used for long-term analysis of load profiles of power converter, which is needed for reliability assessments and better thermal design. This paper proposes a novel...... enables both accurate and fast temperature estimation of high power IGBT modules in the real loading conditions of the converter; meanwhile the critical details of the thermal dynamics and thermal distribution are also maintained. The proposed thermal model is verified by both FEM simulation......The conventional RC lumped thermal networks are widely used to estimate the temperature of power devices, but they are lack of accuracy in addressing detailed thermal behaviors/couplings in different locations and layers of the high power IGBT modules. On the other hand, Finite Element (FE...

Shaft centre orbit for dynamically loaded radial bearings

DEFF Research Database (Denmark)

Klit, Peder; Vølund, Anders

2002-01-01

The aim of this work is to demonstrate how to utilize the bearings damping coefficients to estimate the orbit for a dynamically loaded journal bearing. The classical method for this analysis was developed by Booker in 1965 Booker1 and described further in 1972 Booker2. Several authors have refine...

Generalized master equations for non-Poisson dynamics on networks.

Science.gov (United States)

Hoffmann, Till; Porter, Mason A; Lambiotte, Renaud

2012-10-01

The traditional way of studying temporal networks is to aggregate the dynamics of the edges to create a static weighted network. This implicitly assumes that the edges are governed by Poisson processes, which is not typically the case in empirical temporal networks. Accordingly, we examine the effects of non-Poisson inter-event statistics on the dynamics of edges, and we apply the concept of a generalized master equation to the study of continuous-time random walks on networks. We show that this equation reduces to the standard rate equations when the underlying process is Poissonian and that its stationary solution is determined by an effective transition matrix whose leading eigenvector is easy to calculate. We conduct numerical simulations and also derive analytical results for the stationary solution under the assumption that all edges have the same waiting-time distribution. We discuss the implications of our work for dynamical processes on temporal networks and for the construction of network diagnostics that take into account their nontrivial stochastic nature.

Dynamic load effects on gate valve operability

International Nuclear Information System (INIS)

Steele, R. Jr.; MacDonald, P.E.; Arendts, J.G.

1986-01-01

The Idaho National Engineering Laboratory (INEL) participated in an internationally sponsored seismic research program conducted at the decommissioned Heissdampfreaktor (HDR) located in the Federal Republic of Germany. An existing piping system was modified by installation of an 8-in., naturally aged, motor-operated gate valve from a US nuclear power plant and a piping support system of US design. Six other piping support systems of varying flexibility from stiff to flexible were also installed at various times during the tests. Additional valve loadings included internal hydraulic loads and, during one block of tests, elevated temperature. The operability and integrity of the aged gate valve and the dynamic response of the various piping support system were measured during 25 representative seismic events

Dynamic control of a bistable wing under aerodynamic loading

International Nuclear Information System (INIS)

Bilgen, Onur; Arrieta, Andres F; Friswell, Michael I; Hagedorn, Peter

2013-01-01

The aerodynamic evaluation of a dynamic control technique applied to a bistable unsymmetrical cross-ply composite plate with surface bonded piezoelectric actuators is presented. The plate is clamped on one end to form a low-aspect-ratio wing. A previously proposed dynamic control method, utilizing bending resonance in different stable equilibrium positions, is used to induce snap-through between the two equilibrium states. Compared to quasi-static actuation, driving the bistable plate near resonance using surface bonded piezoelectric materials requires, theoretically, a lower peak excitation voltage to achieve snap-through. First, a set of extensive wind tunnel experiments are conducted on the passive bistable wing to understand the change in the dynamic behavior under various aerodynamic conditions. The passive wing demonstrated sufficient bending stiffness to sustain its shape under aerodynamic loading while preserving the desired bistable behavior. Next, by the use of the resonant control technique, the plate is turned into an effectively monostable structure, or alternatively, both stable equilibrium positions can be reached actively from the other stable equilibrium. Dynamic forward and reverse snap-through is demonstrated in the wind tunnel which shows both the effectiveness of the piezoelectric actuation as well as the load carrying capability of both states of the bistable wing. (paper)

Loading technique for dynamic response studies of geological materials

International Nuclear Information System (INIS)

Butler, R.I.; Forrestal, M.J.

1979-04-01

A loading technique to study the dynamic response of tuff was explored. Loading is provided by electrically exploding etched copper mesh patterns with current from a capacitor discharge. Pressure pulses with peak pressures up to 1.25 kbar and 0.10 to 0.20 ms durations were measured with a pressure bar. The upper value of peak pressure was limited by the strength of the experimental apparatus, and higher pressure generation is possible with a redesign of test hardware. 6 figures, 2 tables

Dynamic Response of Coarse Granular Material to Wave Load

DEFF Research Database (Denmark)

Ibsen, Lars Bo

1998-01-01

The soil beneath vertical breakwaters is subjected to a combination of forces induced by the waves. The forces acting on the soil can be characterized as 1) static load due to submerged weight of the structure, 2) quasi-static forces induced by cyclic wave loading, and 3) wave impact from breaking...... waves. The stress conditions in the soil below a foundation exposed to these types of loading are very complex. The key to explain and quantify the soil response beneath a vertical breakwater is to understand the role of the volume changes and to be able to model these correctly. It is shown...... that the volume changes in soil subjected to static and dynamic loading are controlled by the characteristic line. Experiments have been performed to study the factors that influence the location of the characteristic line in drained and undrained tests for various types of sand and various types of loading...

Dynamic stresses in a Francis model turbine at deep part load

Science.gov (United States)

Weber, Wilhelm; von Locquenghien, Florian; Conrad, Philipp; Koutnik, Jiri

2017-04-01

A comparison between numerically obtained dynamic stresses in a Francis model turbine at deep part load with experimental ones is presented. Due to the change in the electrical power mix to more content of new renewable energy sources, Francis turbines are forced to operate at deep part load in order to compensate stochastic nature of wind and solar power and to ensure grid stability. For the extension of the operating range towards deep part load improved understanding of the harsh flow conditions and their impact on material fatigue of hydraulic components is required in order to ensure long life time of the power unit. In this paper pressure loads on a model turbine runner from unsteady two-phase computational fluid dynamics simulation at deep part load are used for calculation of mechanical stresses by finite element analysis. Therewith, stress distribution over time is determined. Since only few runner rotations are simulated due to enormous numerical cost, more effort has to be spent to evaluation procedure in order to obtain objective results. By comparing the numerical results with measured strains accuracy of the whole simulation procedure is verified.

Evaluation of muscle activity for loaded and unloaded dynamic squats during vertical whole-body vibration.

Science.gov (United States)

Hazell, Tom J; Kenno, Kenji A; Jakobi, Jennifer M

2010-07-01

The purpose of this investigation was to examine if the addition of a light external load would enhance whole-body vibration (WBV)-induced increases in muscle activity during dynamic squatting in 4 leg muscles. Thirteen recreationally active male university students performed a series of dynamic squats (unloaded with no WBV, unloaded with WBV, loaded with no WBV, and loaded with WBV). The load was set to 30% of body mass and WBV included 25-, 35-, and 45-Hz frequencies with 4-mm amplitude. Muscle activity was recorded with surface electromyography (EMG) on the vastus lateralis (VL), biceps femoris (BF), tibialis anterior (TA), and gastrocnemius (GC) and is reported as EMGrms (root mean square) normalized to %maximal voluntary exertion. During unloaded dynamic squats, exposure to WBV (45 Hz) significantly (p squat exercise in all muscles but decreased the TA. This loaded level of muscle activity was further increased with WBV (45 Hz) in all muscles. The WBV-induced increases in muscle activity in the loaded condition (approximately 3.5%) were of a similar magnitude to the WBV-induced increases during the unloaded condition (approximately 2.5%) demonstrating the addition of WBV to unloaded or loaded dynamic squatting results in an increase in muscle activity. These results demonstrate the potential effectiveness of using external loads with exposure to WBV.

Multi-Layer Mobility Load Balancing in a Heterogeneous LTE Network

DEFF Research Database (Denmark)

Fotiadis, Panagiotis; Polignano, Michele; Laselva, Daniela

2012-01-01

This paper analyzes the behavior of a distributed Mobility Load Balancing (MLB) scheme in a multi-layer 3GPP (3rd Generation Partnership Project) Long Term Evolution (LTE) deployment with different User Equipment (UE) densities in certain network areas covered with pico cells. Target of the study...

A technique for measuring dynamic friction coefficient under impact loading.

Science.gov (United States)

Lin, Y L; Qin, J G; Chen, R; Zhao, P D; Lu, F Y

2014-09-01

We develop a novel setup based on the split Hopkinson pressure bar technique to test the dynamic friction coefficient under impact loading. In the setup, the major improvement is that the end of the incident bar near the specimen is wedge-shaped, which results in a combined compressive and shear loading applied to the specimen. In fact, the shear loading is caused by the interfacial friction between specimen and bars. Therefore, when the two loading force histories are measured, the friction coefficient histories can be calculated without any assumptions and theoretical derivations. The geometry of the friction pairs is simple, and can be either cuboid or cylindrical. Regarding the measurements, two quartz transducers are used to directly record the force histories, and an optical apparatus is designed to test the interfacial slip movement. By using the setup, the dynamic friction coefficient of PTFE/aluminum 7075 friction pairs was tested. The time resolved dynamic friction coefficient and slip movement histories were achieved. The results show that the friction coefficient changes during the loading process, the average data of the relatively stable flat plateau section of the friction coefficient curves is 0.137, the maximum normal pressure is 52 MPa, the maximum relative slip velocity is 1.5 m/s, and the acceleration is 8400 m(2)/s. Furthermore, the friction test was simulated using an explicit FEM code LS-DYNA. The simulation results showed that the constant pressure and slip velocity can both be obtained with a wide flat plateau incident pulse. For some special friction pairs, normal pressure up to a few hundred MPa, interfacial slip velocities up to 10 m/s, and slip movement up to centimeter-level can be expected.

Response of porous beryllium to static and dynamic loading

Energy Technology Data Exchange (ETDEWEB)

Isbell, W.M.; Walton, O.R.; Ree, F.H.

1977-07-01

Previous investigstions of the mechanical response of porous materials to dynamic loading have been extended to include the shock wave response of a brittle metal. The complex response of berylliums of 85 to 90 percent porosity in two initial conditions has been examined in a theoretical and experimental program to be described. The study has resulted in the development of constitutive relations placed in hydrocodes which are capable of accurately predicting wave propagation in the berylliums. A comprehensive set of static (0 to 4 Gpa) and dynamic (0 to 35 Gpa) experiments was performed to measure the behavior of these brittle, porous materials to imposed loads. The results of the experiments guided a modeling effort which added several new features to previous models, including deviatoric stresses, porosity-dependent relaxation time of pore closure, elastic-plastic reopening of pores, and improved compaction functions.

Response of porous beryllium to static and dynamic loading

International Nuclear Information System (INIS)

Isbell, W.M.; Walton, O.R.; Ree, F.H.

1977-07-01

Previous investigstions of the mechanical response of porous materials to dynamic loading have been extended to include the shock wave response of a brittle metal. The complex response of berylliums of 85 to 90 percent porosity in two initial conditions has been examined in a theoretical and experimental program to be described. The study has resulted in the development of constitutive relations placed in hydrocodes which are capable of accurately predicting wave propagation in the berylliums. A comprehensive set of static (0 to 4 Gpa) and dynamic (0 to 35 Gpa) experiments was performed to measure the behavior of these brittle, porous materials to imposed loads. The results of the experiments guided a modeling effort which added several new features to previous models, including deviatoric stresses, porosity-dependent relaxation time of pore closure, elastic-plastic reopening of pores, and improved compaction functions

NIF ICCS network design and loading analysis

International Nuclear Information System (INIS)

Tietbohl, G; Bryant, R

1998-01-01

The National Ignition Facility (NIF) is housed within a large facility about the size of two football fields. The Integrated Computer Control System (ICCS) is distributed throughout this facility and requires the integration of about 40,000 control points and over 500 video sources. This integration is provided by approximately 700 control computers distributed throughout the NIF facility and a network that provides the communication infrastructure. A main control room houses a set of seven computer consoles providing operator access and control of the various distributed front-end processors (FEPs). There are also remote workstations distributed within the facility that allow provide operator console functions while personnel are testing and troubleshooting throughout the facility. The operator workstations communicate with the FEPs which implement the localized control and monitoring functions. There are different types of FEPs for the various subsystems being controlled. This report describes the design of the NIF ICCS network and how it meets the traffic loads that will are expected and the requirements of the Sub-System Design Requirements (SSDR's). This document supersedes the earlier reports entitled Analysis of the National Ignition Facility Network, dated November 6, 1996 and The National Ignition Facility Digital Video and Control Network, dated July 9, 1996. For an overview of the ICCS, refer to the document NIF Integrated Computer Controls System Description (NIF-3738)

Coarse-grained simulation of a real-time process control network under peak load

International Nuclear Information System (INIS)

George, A.D.; Clapp, N.E. Jr.

1992-01-01

This paper presents a simulation study on the real-time process control network proposed for the new ANS reactor system at ORNL. A background discussion is provided on networks, modeling, and simulation, followed by an overview of the ANS process control network, its three peak-load models, and the results of a series of coarse-grained simulation studies carried out on these models using implementations of 802.3, 802.4, and 802.5 standard local area networks

Individual heterogeneity generating explosive system network dynamics.

Science.gov (United States)

Manrique, Pedro D; Johnson, Neil F

2018-03-01

Individual heterogeneity is a key characteristic of many real-world systems, from organisms to humans. However, its role in determining the system's collective dynamics is not well understood. Here we study how individual heterogeneity impacts the system network dynamics by comparing linking mechanisms that favor similar or dissimilar individuals. We find that this heterogeneity-based evolution drives an unconventional form of explosive network behavior, and it dictates how a polarized population moves toward consensus. Our model shows good agreement with data from both biological and social science domains. We conclude that individual heterogeneity likely plays a key role in the collective development of real-world networks and communities, and it cannot be ignored.

Individual heterogeneity generating explosive system network dynamics

Science.gov (United States)

Manrique, Pedro D.; Johnson, Neil F.

2018-03-01

Individual heterogeneity is a key characteristic of many real-world systems, from organisms to humans. However, its role in determining the system's collective dynamics is not well understood. Here we study how individual heterogeneity impacts the system network dynamics by comparing linking mechanisms that favor similar or dissimilar individuals. We find that this heterogeneity-based evolution drives an unconventional form of explosive network behavior, and it dictates how a polarized population moves toward consensus. Our model shows good agreement with data from both biological and social science domains. We conclude that individual heterogeneity likely plays a key role in the collective development of real-world networks and communities, and it cannot be ignored.

Sync in Complex Dynamical Networks: Stability, Evolution, Control, and Application

OpenAIRE

Li, Xiang

2005-01-01

In the past few years, the discoveries of small-world and scale-free properties of many natural and artificial complex networks have stimulated significant advances in better understanding the relationship between the topology and the collective dynamics of complex networks. This paper reports recent progresses in the literature of synchronization of complex dynamical networks including stability criteria, network synchronizability and uniform synchronous criticality in different topologies, ...

Dynamic Analysis of Helical Planetary Gear Sets under Combined Force and Moment Loading

Directory of Open Access Journals (Sweden)

Yanfang Liu

2017-01-01

Full Text Available The dynamic behavior of a single-stage planetary gear set with helical gears of multishaft automotive automatic transmissions has been studied, in which one component of the planetary gear set is imposed by additional external vertical and axial loading from countershaft gear pair in addition to the moment. Under these combined loading conditions, the contributions of the deflections of the ring gear and the carrier cannot be neglected. A three-dimensional nonlinear time-variant dynamic model considering not only the transverse, torsional, axial, and rotational motions of the gears but also the elasticity of the mounted shafts has been developed by combining the lumped parameter method with finite element method. The natural modes and the forced vibration responses due to static transmission errors have been obtained. The proposed dynamic model is employed to describe the effects of the combined external loading condition and positioning on the dynamic behavior of a four-planet system.

Network Signaling Channel for Improving ZigBee Performance in Dynamic Cluster-Tree Networks

Directory of Open Access Journals (Sweden)

D. Hämäläinen

2008-03-01

Full Text Available ZigBee is one of the most potential standardized technologies for wireless sensor networks (WSNs. Yet, sufficient energy-efficiency for the lowest power WSNs is achieved only in rather static networks. This severely limits the applicability of ZigBee in outdoor and mobile applications, where operation environment is harsh and link failures are common. This paper proposes a network channel beaconing (NCB algorithm for improving ZigBee performance in dynamic cluster-tree networks. NCB reduces the energy consumption of passive scans by dedicating one frequency channel for network beacon transmissions and by energy optimizing their transmission rate. According to an energy analysis, the power consumption of network maintenance operations reduces by 70%–76% in dynamic networks. In static networks, energy overhead is negligible. Moreover, the service time for data routing increases up to 37%. The performance of NCB is validated by ns-2 simulations. NCB can be implemented as an extension on MAC and NWK layers and it is fully compatible with ZigBee.

Dynamic analysis of elastic rubber tired car wheel breaking under variable normal load

Science.gov (United States)

Fedotov, A. I.; Zedgenizov, V. G.; Ovchinnikova, N. I.

2017-10-01

The purpose of the paper is to analyze the dynamics of the braking of the wheel under normal load variations. The paper uses a mathematical simulation method according to which the calculation model of an object as a mechanical system is associated with a dynamically equivalent schematic structure of the automatic control. Transfer function tool analyzing structural and technical characteristics of an object as well as force disturbances were used. It was proved that the analysis of dynamic characteristics of the wheel subjected to external force disturbances has to take into account amplitude and phase-frequency characteristics. Normal load variations impact car wheel braking subjected to disturbances. The closer slip to the critical point is, the higher the impact is. In the super-critical area, load variations cause fast wheel blocking.

46 CFR 154.409 - Dynamic loads from vessel motion.

Science.gov (United States)

2010-10-01

... in length and is an analysis by the following formulae that corresponds to a 10−8 probability level... EC02FE91.086 (d) If a cargo tank is designed to avoid fatigue, the dynamic loads determined under paragraph...

Unscheduled load flow effect due to large variation in the distributed generation in a subtransmission network

Science.gov (United States)

Islam, Mujahidul

from the vast network. A path tracing methodology is developed to identify the power lines that are vulnerable to an unscheduled flow effect in the sub-transmission network. It is much harder to aggregate power system network sensitivity information or data from measuring load flow physically than to simulate in software. System dynamics is one of the key factors to determine an appropriate dynamic control mechanism at an optimum network location. Once a model of deterministic but variable power generator is used, the simulation can be meaningful in justifying this claim. The method used to model the variable generator is named the two-components phase distortion model. The model was validated from the high resolution data collected from three pilot photovoltaic sites in Florida - two in the city of St. Petersburg and one in the city of Tampa. The high resolution data was correlated with weather radar closest to the sites during the design stage of the model. Technically the deterministic model cannot replicate a stochastic model which is more realistically applicable for solar isolation and involves a Markov chain. The author justified the proposition based on the fact that for analysis of the response functions of different systems, the excitation function should be common for comparison. Moreover, there could be many possible simulation scenarios but fewer worst cases. Almost all commercial systems are protected against potential faults and contingencies to a certain extent. Hence, the proposed model for worst case studies was designed within a reasonable limit. The simulation includes steady state and transient mode using multiple software modules including MatlabRTM, PSCADRTM and Paladin Design BaseRTM. It is shown that by identifying vulnerable or sensitive branches in the network, the control mechanisms can be coordinated reliably. In the long run this can save money by preventing unscheduled power flow in the network and eventually stabilizing the energy market.

Dynamic load-sharing characteristic analysis of face gear power-split gear system based on tooth contact characteristics

Science.gov (United States)

Dong, Hao; Hu, Yahui

2018-04-01

The bend-torsion coupling dynamics load-sharing model of the helicopter face gear split torque transmission system is established by using concentrated quality standard, to analyzing the dynamic load-sharing characteristic. The mathematical models include nonlinear support stiffness, time-varying meshing stiffness, damping, gear backlash. The results showed that the errors collectively influenced the load sharing characteristics, only reduce a certain error, it is never fully reached the perfect loading sharing characteristics. The system load-sharing performance can be improved through floating shaft support. The above-method will provide a theoretical basis and data support for its dynamic performance optimization design.

Self-organized dynamics in local load-sharing fiber bundle models.

Science.gov (United States)

Biswas, Soumyajyoti; Chakrabarti, Bikas K

2013-10-01

We study the dynamics of a local load-sharing fiber bundle model in two dimensions under an external load (which increases with time at a fixed slow rate) applied at a single point. Due to the local load-sharing nature, the redistributed load remains localized along the boundary of the broken patch. The system then goes to a self-organized state with a stationary average value of load per fiber along the (increasing) boundary of the broken patch (damaged region) and a scale-free distribution of avalanche sizes and other related quantities are observed. In particular, when the load redistribution is only among nearest surviving fiber(s), the numerical estimates of the exponent values are comparable with those of the Manna model. When the load redistribution is uniform along the patch boundary, the model shows a simple mean-field limit of this self-organizing critical behavior, for which we give analytical estimates of the saturation load per fiber values and avalanche size distribution exponent. These are in good agreement with numerical simulation results.

Robustness of pinning a general complex dynamical network

International Nuclear Information System (INIS)

Wang Lei; Sun Youxian

2010-01-01

This Letter studies the robustness problem of pinning a general complex dynamical network toward an assigned synchronous evolution. Several synchronization criteria are presented to guarantee the convergence of the pinning process locally and globally by construction of Lyapunov functions. In particular, if a pinning strategy has been designed for synchronization of a given complex dynamical network, then no matter what uncertainties occur among the pinned nodes, synchronization can still be guaranteed through the pinning. The analytical results show that pinning control has a certain robustness against perturbations on network architecture: adding, deleting and changing the weights of edges. Numerical simulations illustrated by scale-free complex networks verify the theoretical results above-acquired.

Enabling dynamic network analysis through visualization in TVNViewer

Directory of Open Access Journals (Sweden)

Curtis Ross E

2012-08-01

Full Text Available Abstract Background Many biological processes are context-dependent or temporally specific. As a result, relationships between molecular constituents evolve across time and environments. While cutting-edge machine learning techniques can recover these networks, exploring and interpreting the rewiring behavior is challenging. Information visualization shines in this type of exploratory analysis, motivating the development ofTVNViewer (http://sailing.cs.cmu.edu/tvnviewer, a visualization tool for dynamic network analysis. Results In this paper, we demonstrate visualization techniques for dynamic network analysis by using TVNViewer to analyze yeast cell cycle and breast cancer progression datasets. Conclusions TVNViewer is a powerful new visualization tool for the analysis of biological networks that change across time or space.

Enabling dynamic network analysis through visualization in TVNViewer

Science.gov (United States)

2012-01-01

Background Many biological processes are context-dependent or temporally specific. As a result, relationships between molecular constituents evolve across time and environments. While cutting-edge machine learning techniques can recover these networks, exploring and interpreting the rewiring behavior is challenging. Information visualization shines in this type of exploratory analysis, motivating the development ofTVNViewer (http://sailing.cs.cmu.edu/tvnviewer), a visualization tool for dynamic network analysis. Results In this paper, we demonstrate visualization techniques for dynamic network analysis by using TVNViewer to analyze yeast cell cycle and breast cancer progression datasets. Conclusions TVNViewer is a powerful new visualization tool for the analysis of biological networks that change across time or space. PMID:22897913

Agent-based modeling and network dynamics

CERN Document Server

Namatame, Akira

2016-01-01

The book integrates agent-based modeling and network science. It is divided into three parts, namely, foundations, primary dynamics on and of social networks, and applications. The book begins with the network origin of agent-based models, known as cellular automata, and introduce a number of classic models, such as Schelling’s segregation model and Axelrod’s spatial game. The essence of the foundation part is the network-based agent-based models in which agents follow network-based decision rules. Under the influence of the substantial progress in network science in late 1990s, these models have been extended from using lattices into using small-world networks, scale-free networks, etc. The book also shows that the modern network science mainly driven by game-theorists and sociophysicists has inspired agent-based social scientists to develop alternative formation algorithms, known as agent-based social networks. The book reviews a number of pioneering and representative models in this family. Upon the gi...

Comparison of neural network applications for channel assignment in cellular TDMA networks and dynamically sectored PCS networks

Science.gov (United States)

Hortos, William S.

1997-04-01

The use of artificial neural networks (NNs) to address the channel assignment problem (CAP) for cellular time-division multiple access and code-division multiple access networks has previously been investigated by this author and many others. The investigations to date have been based on a hexagonal cell structure established by omnidirectional antennas at the base stations. No account was taken of the use of spatial isolation enabled by directional antennas to reduce interference between mobiles. Any reduction in interference translates into increased capacity and consequently alters the performance of the NNs. Previous studies have sought to improve the performance of Hopfield- Tank network algorithms and self-organizing feature map algorithms applied primarily to static channel assignment (SCA) for cellular networks that handle uniformly distributed, stationary traffic in each cell for a single type of service. The resulting algorithms minimize energy functions representing interference constraint and ad hoc conditions that promote convergence to optimal solutions. While the structures of the derived neural network algorithms (NNAs) offer the potential advantages of inherent parallelism and adaptability to changing system conditions, this potential has yet to be fulfilled the CAP for emerging mobile networks. The next-generation communication infrastructures must accommodate dynamic operating conditions. Macrocell topologies are being refined to microcells and picocells that can be dynamically sectored by adaptively controlled, directional antennas and programmable transceivers. These networks must support the time-varying demands for personal communication services (PCS) that simultaneously carry voice, data and video and, thus, require new dynamic channel assignment (DCA) algorithms. This paper examines the impact of dynamic cell sectoring and geometric conditioning on NNAs developed for SCA in omnicell networks with stationary traffic to improve the metrics

The architecture of dynamic reservoir in the echo state network

Science.gov (United States)

Cui, Hongyan; Liu, Xiang; Li, Lixiang

2012-09-01

Echo state network (ESN) has recently attracted increasing interests because of its superior capability in modeling nonlinear dynamic systems. In the conventional echo state network model, its dynamic reservoir (DR) has a random and sparse topology, which is far from the real biological neural networks from both structural and functional perspectives. We hereby propose three novel types of echo state networks with new dynamic reservoir topologies based on complex network theory, i.e., with a small-world topology, a scale-free topology, and a mixture of small-world and scale-free topologies, respectively. We then analyze the relationship between the dynamic reservoir structure and its prediction capability. We utilize two commonly used time series to evaluate the prediction performance of the three proposed echo state networks and compare them to the conventional model. We also use independent and identically distributed time series to analyze the short-term memory and prediction precision of these echo state networks. Furthermore, we study the ratio of scale-free topology and the small-world topology in the mixed-topology network, and examine its influence on the performance of the echo state networks. Our simulation results show that the proposed echo state network models have better prediction capabilities, a wider spectral radius, but retain almost the same short-term memory capacity as compared to the conventional echo state network model. We also find that the smaller the ratio of the scale-free topology over the small-world topology, the better the memory capacities.

Congested Link Inference Algorithms in Dynamic Routing IP Network

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Yu Chen

2017-01-01

Full Text Available The performance descending of current congested link inference algorithms is obviously in dynamic routing IP network, such as the most classical algorithm CLINK. To overcome this problem, based on the assumptions of Markov property and time homogeneity, we build a kind of Variable Structure Discrete Dynamic Bayesian (VSDDB network simplified model of dynamic routing IP network. Under the simplified VSDDB model, based on the Bayesian Maximum A Posteriori (BMAP and Rest Bayesian Network Model (RBNM, we proposed an Improved CLINK (ICLINK algorithm. Considering the concurrent phenomenon of multiple link congestion usually happens, we also proposed algorithm CLILRS (Congested Link Inference algorithm based on Lagrangian Relaxation Subgradient to infer the set of congested links. We validated our results by the experiments of analogy, simulation, and actual Internet.

Network Dynamics of Innovation Processes

Science.gov (United States)

Iacopini, Iacopo; Milojević, Staša; Latora, Vito

2018-01-01

We introduce a model for the emergence of innovations, in which cognitive processes are described as random walks on the network of links among ideas or concepts, and an innovation corresponds to the first visit of a node. The transition matrix of the random walk depends on the network weights, while in turn the weight of an edge is reinforced by the passage of a walker. The presence of the network naturally accounts for the mechanism of the "adjacent possible," and the model reproduces both the rate at which novelties emerge and the correlations among them observed empirically. We show this by using synthetic networks and by studying real data sets on the growth of knowledge in different scientific disciplines. Edge-reinforced random walks on complex topologies offer a new modeling framework for the dynamics of correlated novelties and are another example of coevolution of processes and networks.

Long-term dynamic loading improves the mechanical properties of chondrogenic mesenchymal stem cell-laden hydrogel

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AH Huang

2010-02-01

Full Text Available Mesenchymal stem cells (MSCs are an attractive cell source for cartilage tissue engineering given their ability to undergo chondrogenesis in 3D culture systems. Mechanical forces play an important role in regulating both cartilage development and MSC chondrogenic gene expression, however, mechanical stimulation has yet to enhance the mechanical properties of engineered constructs. In this study, we applied long-term dynamic compression to MSC-seeded constructs and assessed whether varying pre-culture duration, loading regimens and inclusion of TGF-beta3 during loading would influence functional outcomes and these phenotypic transitions. Loading initiated before chondrogenesis decreased functional maturation, although chondrogenic gene expression increased. In contrast, loading initiated after chondrogenesis and matrix elaboration further improved the mechanical properties of MSC-based constructs, but only when TGF-beta3 levels were maintained and under specific loading parameters. Although matrix quantity was not affected by dynamic compression, matrix distribution, assessed histologically and by FT-IRIS analysis, was significantly improved on the micro- (pericellular and macro- (construct expanse scales. Further, whole genome expression profiling revealed marked shifts in the molecular topography with dynamic loading. These results demonstrate, for the first time, that dynamic compressive loading initiated after a sufficient period of chondro-induction and with sustained TGF-beta exposure enhances matrix distribution and the mechanical properties of MSC-seeded constructs.

OTDM Networking for Short Range High-Capacity Highly Dynamic Networks

DEFF Research Database (Denmark)

Medhin, Ashenafi Kiros

This PhD thesis aims at investigating the possibility of designing energy-efficient high-capacity (up to Tbit/s) optical network scenarios, leveraging on the effect of collective switching of many bits simultaneously, as is inherent in high bit rate serial optical data signals. The focus...... is on short range highly dynamic networks, catering to data center needs. The investigation concerns optical network scenarios, and experimental implementations of high bit rate serial data packet generation and reception, scalable optical packet labeling, simple optical label extraction and stable ultra...

Competitive Dynamics on Complex Networks

Science.gov (United States)

Zhao, Jiuhua; Liu, Qipeng; Wang, Xiaofan

2014-07-01

We consider a dynamical network model in which two competitors have fixed and different states, and each normal agent adjusts its state according to a distributed consensus protocol. The state of each normal agent converges to a steady value which is a convex combination of the competitors' states, and is independent of the initial states of agents. This implies that the competition result is fully determined by the network structure and positions of competitors in the network. We compute an Influence Matrix (IM) in which each element characterizing the influence of an agent on another agent in the network. We use the IM to predict the bias of each normal agent and thus predict which competitor will win. Furthermore, we compare the IM criterion with seven node centrality measures to predict the winner. We find that the competitor with higher Katz Centrality in an undirected network or higher PageRank in a directed network is most likely to be the winner. These findings may shed new light on the role of network structure in competition and to what extent could competitors adjust network structure so as to win the competition.

Planning Training Loads for the 400 M Hurdles in Three-Month Mesocycles using Artificial Neural Networks.

Science.gov (United States)

Przednowek, Krzysztof; Iskra, Janusz; Wiktorowicz, Krzysztof; Krzeszowski, Tomasz; Maszczyk, Adam

2017-12-01

This paper presents a novel approach to planning training loads in hurdling using artificial neural networks. The neural models performed the task of generating loads for athletes' training for the 400 meters hurdles. All the models were calculated based on the training data of 21 Polish National Team hurdlers, aged 22.25 ± 1.96, competing between 1989 and 2012. The analysis included 144 training plans that represented different stages in the annual training cycle. The main contribution of this paper is to develop neural models for planning training loads for the entire career of a typical hurdler. In the models, 29 variables were used, where four characterized the runner and 25 described the training process. Two artificial neural networks were used: a multi-layer perceptron and a network with radial basis functions. To assess the quality of the models, the leave-one-out cross-validation method was used in which the Normalized Root Mean Squared Error was calculated. The analysis shows that the method generating the smallest error was the radial basis function network with nine neurons in the hidden layer. Most of the calculated training loads demonstrated a non-linear relationship across the entire competitive period. The resulting model can be used as a tool to assist a coach in planning training loads during a selected training period.

Planning Training Loads for The 400 M Hurdles in Three-Month Mesocycles Using Artificial Neural Networks

Directory of Open Access Journals (Sweden)

Przednowek Krzysztof

2017-12-01

Full Text Available This paper presents a novel approach to planning training loads in hurdling using artificial neural networks. The neural models performed the task of generating loads for athletes’ training for the 400 meters hurdles. All the models were calculated based on the training data of 21 Polish National Team hurdlers, aged 22.25 ± 1.96, competing between 1989 and 2012. The analysis included 144 training plans that represented different stages in the annual training cycle. The main contribution of this paper is to develop neural models for planning training loads for the entire career of a typical hurdler. In the models, 29 variables were used, where four characterized the runner and 25 described the training process. Two artificial neural networks were used: a multi-layer perceptron and a network with radial basis functions. To assess the quality of the models, the leave-one-out cross-validation method was used in which the Normalized Root Mean Squared Error was calculated. The analysis shows that the method generating the smallest error was the radial basis function network with nine neurons in the hidden layer. Most of the calculated training loads demonstrated a non-linear relationship across the entire competitive period. The resulting model can be used as a tool to assist a coach in planning training loads during a selected training period.

Active influence in dynamical models of structural balance in social networks

Science.gov (United States)

Summers, Tyler H.; Shames, Iman

2013-07-01

We consider a nonlinear dynamical system on a signed graph, which can be interpreted as a mathematical model of social networks in which the links can have both positive and negative connotations. In accordance with a concept from social psychology called structural balance, the negative links play a key role in both the structure and dynamics of the network. Recent research has shown that in a nonlinear dynamical system modeling the time evolution of “friendliness levels” in the network, two opposing factions emerge from almost any initial condition. Here we study active external influence in this dynamical model and show that any agent in the network can achieve any desired structurally balanced state from any initial condition by perturbing its own local friendliness levels. Based on this result, we also introduce a new network centrality measure for signed networks. The results are illustrated in an international-relations network using United Nations voting record data from 1946 to 2008 to estimate friendliness levels amongst various countries.

Dynamic Regression Intervention Modeling for the Malaysian Daily Load

Directory of Open Access Journals (Sweden)

Fadhilah Abdrazak

2014-05-01

Full Text Available Malaysia is a unique country due to having both fixed and moving holidays.  These moving holidays may overlap with other fixed holidays and therefore, increase the complexity of the load forecasting activities. The errors due to holidays’ effects in the load forecasting are known to be higher than other factors.  If these effects can be estimated and removed, the behavior of the series could be better viewed.  Thus, the aim of this paper is to improve the forecasting errors by using a dynamic regression model with intervention analysis.   Based on the linear transfer function method, a daily load model consists of either peak or average is developed.  The developed model outperformed the seasonal ARIMA model in estimating the fixed and moving holidays’ effects and achieved a smaller Mean Absolute Percentage Error (MAPE in load forecast.

Framework based on communicability and flow to analyze complex network dynamics

Science.gov (United States)

Gilson, M.; Kouvaris, N. E.; Deco, G.; Zamora-López, G.

2018-05-01

Graph theory constitutes a widely used and established field providing powerful tools for the characterization of complex networks. The intricate topology of networks can also be investigated by means of the collective dynamics observed in the interactions of self-sustained oscillations (synchronization patterns) or propagationlike processes such as random walks. However, networks are often inferred from real-data-forming dynamic systems, which are different from those employed to reveal their topological characteristics. This stresses the necessity for a theoretical framework dedicated to the mutual relationship between the structure and dynamics in complex networks, as the two sides of the same coin. Here we propose a rigorous framework based on the network response over time (i.e., Green function) to study interactions between nodes across time. For this purpose we define the flow that describes the interplay between the network connectivity and external inputs. This multivariate measure relates to the concepts of graph communicability and the map equation. We illustrate our theory using the multivariate Ornstein-Uhlenbeck process, which describes stable and non-conservative dynamics, but the formalism can be adapted to other local dynamics for which the Green function is known. We provide applications to classical network examples, such as small-world ring and hierarchical networks. Our theory defines a comprehensive framework that is canonically related to directed and weighted networks, thus paving a way to revise the standards for network analysis, from the pairwise interactions between nodes to the global properties of networks including community detection.

Extracting neuronal functional network dynamics via adaptive Granger causality analysis.

Science.gov (United States)

Sheikhattar, Alireza; Miran, Sina; Liu, Ji; Fritz, Jonathan B; Shamma, Shihab A; Kanold, Patrick O; Babadi, Behtash

2018-04-24

Quantifying the functional relations between the nodes in a network based on local observations is a key challenge in studying complex systems. Most existing time series analysis techniques for this purpose provide static estimates of the network properties, pertain to stationary Gaussian data, or do not take into account the ubiquitous sparsity in the underlying functional networks. When applied to spike recordings from neuronal ensembles undergoing rapid task-dependent dynamics, they thus hinder a precise statistical characterization of the dynamic neuronal functional networks underlying adaptive behavior. We develop a dynamic estimation and inference paradigm for extracting functional neuronal network dynamics in the sense of Granger, by integrating techniques from adaptive filtering, compressed sensing, point process theory, and high-dimensional statistics. We demonstrate the utility of our proposed paradigm through theoretical analysis, algorithm development, and application to synthetic and real data. Application of our techniques to two-photon Ca 2+ imaging experiments from the mouse auditory cortex reveals unique features of the functional neuronal network structures underlying spontaneous activity at unprecedented spatiotemporal resolution. Our analysis of simultaneous recordings from the ferret auditory and prefrontal cortical areas suggests evidence for the role of rapid top-down and bottom-up functional dynamics across these areas involved in robust attentive behavior.

Spatial-temporal-spectral EEG patterns of BOLD functional network connectivity dynamics

Science.gov (United States)

Lamoš, Martin; Mareček, Radek; Slavíček, Tomáš; Mikl, Michal; Rektor, Ivan; Jan, Jiří

2018-06-01

Objective. Growing interest in the examination of large-scale brain network functional connectivity dynamics is accompanied by an effort to find the electrophysiological correlates. The commonly used constraints applied to spatial and spectral domains during electroencephalogram (EEG) data analysis may leave part of the neural activity unrecognized. We propose an approach that blindly reveals multimodal EEG spectral patterns that are related to the dynamics of the BOLD functional network connectivity. Approach. The blind decomposition of EEG spectrogram by parallel factor analysis has been shown to be a useful technique for uncovering patterns of neural activity. The simultaneously acquired BOLD fMRI data were decomposed by independent component analysis. Dynamic functional connectivity was computed on the component’s time series using a sliding window correlation, and between-network connectivity states were then defined based on the values of the correlation coefficients. ANOVA tests were performed to assess the relationships between the dynamics of between-network connectivity states and the fluctuations of EEG spectral patterns. Main results. We found three patterns related to the dynamics of between-network connectivity states. The first pattern has dominant peaks in the alpha, beta, and gamma bands and is related to the dynamics between the auditory, sensorimotor, and attentional networks. The second pattern, with dominant peaks in the theta and low alpha bands, is related to the visual and default mode network. The third pattern, also with peaks in the theta and low alpha bands, is related to the auditory and frontal network. Significance. Our previous findings revealed a relationship between EEG spectral pattern fluctuations and the hemodynamics of large-scale brain networks. In this study, we suggest that the relationship also exists at the level of functional connectivity dynamics among large-scale brain networks when no standard spatial and spectral

Identifying and tracking dynamic processes in social networks

Science.gov (United States)

Chung, Wayne; Savell, Robert; Schütt, Jan-Peter; Cybenko, George

2006-05-01

The detection and tracking of embedded malicious subnets in an active social network can be computationally daunting due to the quantity of transactional data generated in the natural interaction of large numbers of actors comprising a network. In addition, detection of illicit behavior may be further complicated by evasive strategies designed to camouflage the activities of the covert subnet. In this work, we move beyond traditional static methods of social network analysis to develop a set of dynamic process models which encode various modes of behavior in active social networks. These models will serve as the basis for a new application of the Process Query System (PQS) to the identification and tracking of covert dynamic processes in social networks. We present a preliminary result from application of our technique in a real-world data stream-- the Enron email corpus.

The Comprehensive Biomechanics and Load-Sharing of Semirigid PEEK and Semirigid Posterior Dynamic Stabilization Systems

Directory of Open Access Journals (Sweden)

D. K. Sengupta

2013-01-01

Full Text Available Alternatives to conventional rigid fusion have been proposed for several conditions related to degenerative disc disease when nonoperative treatment has failed. Semirigid fixation, in the form of dynamic stabilization or PEEK rods, is expected to provide compression under loading as well as an intermediate level of stabilization. This study systematically examines both the load-sharing characteristics and kinematics of these two devices compared to the standard of internal rigid fixators. Load-sharing was studied by using digital pressure films inserted between an artificially machined disc and two loading fixtures. Rigid rods, PEEK rods, and the dynamic stabilization system were inserted posteriorly for stabilization. The kinematics were quantified on ten, human, cadaver lumbosacral spines (L3-S1 which were tested under a pure bending moment, in flexion-extension, lateral bending, and axial rotation. The magnitude of load transmission through the anterior column was significantly greater with the dynamic device compared to PEEK rods and rigid rods. The contact pressures were distributed more uniformly, throughout the disc with the dynamic stabilization devices, and had smaller maximum point-loading (pressures on any particular point within the disc. Kinematically, the motion was reduced by both semirigid devices similarly in all directions, with slight rigidity imparted by a lateral interbody device.

Dynamic loading of galvanized parts

Directory of Open Access Journals (Sweden)

Michal Černý

2010-01-01

Full Text Available This work is divided into two parts: the theoretical part includes actual knowledge and points of view about degradation processes in construction materials, anticorrosion protection, zinc coat composition and high frequency fatigue. The laboratory part follow-up existing regulations contents Czech standards and formulate specifications for acquisition of objective information from acceleration la­bo­ra­to­ry tests in condensation chests, mechanical high frequency fatigue tests on pulsator machine and possibilities of evaluation of fatigue tests. Laboratory findings declare to fundamental types of damage of constructions with anticorrosion protection in real loading conditions with dynamic high frequency character. Laboratory tests were made in sulphide and chloride environments.

perception of communication network fraud dynamics by network ...

African Journals Online (AJOL)

ES Obe

work fraud dynamics by network administrators and stakeholders. In considering ... cyber crime within the last two years. How- ever, two-thirds of the ... ˆ increased exposure to unpredictable fi- nancial losses ... The intentions of the customers are reflected ..... 'There is a 95% confidence that the differ- ence between the ...

Generalized Load Sharing for Homogeneous Networks of Distributed Environment

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A. Satheesh

2008-01-01

Full Text Available We propose a method for job migration policies by considering effective usage of global memory in addition to CPU load sharing in distributed systems. When a node is identified for lacking sufficient memory space to serve jobs, one or more jobs of the node will be migrated to remote nodes with low memory allocations. If the memory space is sufficiently large, the jobs will be scheduled by a CPU-based load sharing policy. Following the principle of sharing both CPU and memory resources, we present several load sharing alternatives. Our objective is to reduce the number of page faults caused by unbalanced memory allocations for jobs among distributed nodes, so that overall performance of a distributed system can be significantly improved. We have conducted trace-driven simulations to compare CPU-based load sharing policies with our policies. We show that our load sharing policies not only improve performance of memory bound jobs, but also maintain the same load sharing quality as the CPU-based policies for CPU-bound jobs. Regarding remote execution and preemptive migration strategies, our experiments indicate that a strategy selection in load sharing is dependent on the amount of memory demand of jobs, remote execution is more effective for memory-bound jobs, and preemptive migration is more effective for CPU-bound jobs. Our CPU-memory-based policy using either high performance or high throughput approach and using the remote execution strategy performs the best for both CPU-bound and memory-bound job in homogeneous networks of distributed environment.

Complex networks: when random walk dynamics equals synchronization

International Nuclear Information System (INIS)

Kriener, Birgit; Anand, Lishma; Timme, Marc

2012-01-01

Synchrony prevalently emerges from the interactions of coupled dynamical units. For simple systems such as networks of phase oscillators, the asymptotic synchronization process is assumed to be equivalent to a Markov process that models standard diffusion or random walks on the same network topology. In this paper, we analytically derive the conditions for such equivalence for networks of pulse-coupled oscillators, which serve as models for neurons and pacemaker cells interacting by exchanging electric pulses or fireflies interacting via light flashes. We find that the pulse synchronization process is less simple, but there are classes of, e.g., network topologies that ensure equivalence. In particular, local dynamical operators are required to be doubly stochastic. These results provide a natural link between stochastic processes and deterministic synchronization on networks. Tools for analyzing diffusion (or, more generally, Markov processes) may now be transferred to pin down features of synchronization in networks of pulse-coupled units such as neural circuits. (paper)

Dynamical systems on networks a tutorial

CERN Document Server

Porter, Mason A

2016-01-01

This volume is a tutorial for the study of dynamical systems on networks. It discusses both methodology and models, including spreading models for social and biological contagions. The authors focus especially on “simple” situations that are analytically tractable, because they are insightful and provide useful springboards for the study of more complicated scenarios. This tutorial, which also includes key pointers to the literature, should be helpful for junior and senior undergraduate students, graduate students, and researchers from mathematics, physics, and engineering who seek to study dynamical systems on networks but who may not have prior experience with graph theory or networks. Mason A. Porter is Professor of Nonlinear and Complex Systems at the Oxford Centre for Industrial and Applied Mathematics, Mathematical Institute, University of Oxford, UK. He is also a member of the CABDyN Complexity Centre and a Tutorial Fellow of Somerville College. James P. Gleeson is Professor of Industrial and Appli...

Hybrid Bee Ant Colony Algorithm for Effective Load Balancing And ...

African Journals Online (AJOL)

PROF. OLIVER OSUAGWA

Ant Colony algorithm is used in this hybrid Bee Ant Colony algorithm to solve load balancing issues ... Genetic Algorithm (MO-GA) for dynamic job scheduling that .... Information Networking and Applications Workshops. [7]. M. Dorigo & T.

Rumor Diffusion in an Interests-Based Dynamic Social Network

Directory of Open Access Journals (Sweden)

Mingsheng Tang

2013-01-01

Full Text Available To research rumor diffusion in social friend network, based on interests, a dynamic friend network is proposed, which has the characteristics of clustering and community, and a diffusion model is also proposed. With this friend network and rumor diffusion model, based on the zombie-city model, some simulation experiments to analyze the characteristics of rumor diffusion in social friend networks have been conducted. The results show some interesting observations: (1 positive information may evolve to become a rumor through the diffusion process that people may modify the information by word of mouth; (2 with the same average degree, a random social network has a smaller clustering coefficient and is more beneficial for rumor diffusion than the dynamic friend network; (3 a rumor is spread more widely in a social network with a smaller global clustering coefficient than in a social network with a larger global clustering coefficient; and (4 a network with a smaller clustering coefficient has a larger efficiency.

Simulating market dynamics: interactions between consumer psychology and social networks.

Science.gov (United States)

Janssen, Marco A; Jager, Wander

2003-01-01

Markets can show different types of dynamics, from quiet markets dominated by one or a few products, to markets with continual penetration of new and reintroduced products. In a previous article we explored the dynamics of markets from a psychological perspective using a multi-agent simulation model. The main results indicated that the behavioral rules dominating the artificial consumer's decision making determine the resulting market dynamics, such as fashions, lock-in, and unstable renewal. Results also show the importance of psychological variables like social networks, preferences, and the need for identity to explain the dynamics of markets. In this article we extend this work in two directions. First, we will focus on a more systematic investigation of the effects of different network structures. The previous article was based on Watts and Strogatz's approach, which describes the small-world and clustering characteristics in networks. More recent research demonstrated that many large networks display a scale-free power-law distribution for node connectivity. In terms of market dynamics this may imply that a small proportion of consumers may have an exceptional influence on the consumptive behavior of others (hubs, or early adapters). We show that market dynamics is a self-organized property depending on the interaction between the agents' decision-making process (heuristics), the product characteristics (degree of satisfaction of unit of consumption, visibility), and the structure of interactions between agents (size of network and hubs in a social network).

Model-based dynamic control and optimization of gas networks

Energy Technology Data Exchange (ETDEWEB)

Hofsten, Kai

2001-07-01

This work contributes to the research on control, optimization and simulation of gas transmission systems to support the dispatch personnel at gas control centres for the decision makings in the daily operation of the natural gas transportation systems. Different control and optimization strategies have been studied. The focus is on the operation of long distance natural gas transportation systems. Stationary optimization in conjunction with linear model predictive control using state space models is proposed for supply security, the control of quality parameters and minimization of transportation costs for networks offering transportation services. The result from the stationary optimization together with a reformulation of a simplified fluid flow model formulates a linear dynamic optimization model. This model is used in a finite time control and state constrained linear model predictive controller. The deviation from the control and the state reference determined from the stationary optimization is penalized quadratically. Because of the time varying status of infrastructure, the control space is also generally time varying. When the average load is expected to change considerably, a new stationary optimization is performed, giving a new state and control reference together with a new dynamic model that is used for both optimization and state estimation. Another proposed control strategy is a control and output constrained nonlinear model predictive controller for the operation of gas transmission systems. Here, the objective is also the security of the supply, quality control and minimization of transportation costs. An output vector is defined, which together with a control vector are both penalized quadratically from their respective references in the objective function. The nonlinear model predictive controller can be combined with a stationary optimization. At each sampling instant, a non convex nonlinear programming problem is solved giving a local minimum

Ad-hoc Network of Smart Sensors for Mechanical Load Measurement

Directory of Open Access Journals (Sweden)

Manuel A. Vieira

2016-07-01

Full Text Available Strain gauges load cells are transducers devices capable of converting changes in applied mechanical load into an electrical analog signal. Those devices have a large spectrum of applications ranging from domestic to industrial or even medical appliances just to name a few. In this work, they are used in the electronic instrumentation of a force platform that will be used to carry out the analysis and characterization of human biomechanical walking. In this platform, four load cells are installed, each one capable of measuring forces along two different axis. A total of eight strain-gauges per load cell are employed. Hence, analog signal transmission, besides requiring a large number of connection wires, is prone to interference and noise. Moreover, with this solution, scalability requires severe changes in the connection topology. In order to circumvent those problems, an alternative in-situ signal conditioning and digital data transmission system was devised. This approach, as far as investigated, presents an innovative solution to signal conditioning and data transmission for load-cells. In particular, the presented solution allows the creation of an ad-hoc network of load cells, using the I²C protocol with a master interface that allows the users to interact and change the parameters of each load cell. This instrumentation structure has been successfully tested and the obtained results are documented in this article.

State-dependent intrinsic predictability of cortical network dynamics.

Directory of Open Access Journals (Sweden)

Leila Fakhraei

Full Text Available The information encoded in cortical circuit dynamics is fleeting, changing from moment to moment as new input arrives and ongoing intracortical interactions progress. A combination of deterministic and stochastic biophysical mechanisms governs how cortical dynamics at one moment evolve from cortical dynamics in recently preceding moments. Such temporal continuity of cortical dynamics is fundamental to many aspects of cortex function but is not well understood. Here we study temporal continuity by attempting to predict cortical population dynamics (multisite local field potential based on its own recent history in somatosensory cortex of anesthetized rats and in a computational network-level model. We found that the intrinsic predictability of cortical dynamics was dependent on multiple factors including cortical state, synaptic inhibition, and how far into the future the prediction extends. By pharmacologically tuning synaptic inhibition, we obtained a continuum of cortical states with asynchronous population activity at one extreme and stronger, spatially extended synchrony at the other extreme. Intermediate between these extremes we observed evidence for a special regime of population dynamics called criticality. Predictability of the near future (10-100 ms increased as the cortical state was tuned from asynchronous to synchronous. Predictability of the more distant future (>1 s was generally poor, but, surprisingly, was higher for asynchronous states compared to synchronous states. These experimental results were confirmed in a computational network model of spiking excitatory and inhibitory neurons. Our findings demonstrate that determinism and predictability of network dynamics depend on cortical state and the time-scale of the dynamics.

Dynamic properties of epidemic spreading on finite size complex networks

Science.gov (United States)

Li, Ying; Liu, Yang; Shan, Xiu-Ming; Ren, Yong; Jiao, Jian; Qiu, Ben

2005-11-01

The Internet presents a complex topological structure, on which computer viruses can easily spread. By using theoretical analysis and computer simulation methods, the dynamic process of disease spreading on finite size networks with complex topological structure is investigated. On the finite size networks, the spreading process of SIS (susceptible-infected-susceptible) model is a finite Markov chain with an absorbing state. Two parameters, the survival probability and the conditional infecting probability, are introduced to describe the dynamic properties of disease spreading on finite size networks. Our results can help understanding computer virus epidemics and other spreading phenomena on communication and social networks. Also, knowledge about the dynamic character of virus spreading is helpful for adopting immunity policy.

Dynamic Mobile IP routers in ad hoc networks

NARCIS (Netherlands)

Kock, B.A.; Schmidt, J.R.

2005-01-01

This paper describes a concept combining mobile IP and ad hoc routing to create a robust mobile network. In this network all nodes are mobile and globally and locally reachable under the same IP address. Essential for implementing this network are the dynamic mobile IP routers. They act as gateways

The Influence of External Load on Quadriceps Muscle and Tendon Dynamics during Jumping.

Science.gov (United States)

Earp, Jacob E; Newton, Robert U; Cormie, Prue; Blazevich, Anthony J

2017-11-01

Tendons possess both viscous (rate-dependent) and elastic (rate-independent) properties that determine tendon function. During high-speed movements external loading increases both the magnitude (FT) and rate (RFDT) of tendon loading. The influence of external loading on muscle and tendon dynamics during maximal vertical jumping was explored. Ten resistance-trained men performed parallel-depth, countermovement vertical jumps with and without additional load (0%, 30%, 60%, and 90% of maximum squat lift strength), while joint kinetics and kinematics, quadriceps tendon length (LT) and patellar tendon FT and RFDT were estimated using integrated ultrasound, motion analysis and force platform data and muscle tendon modelling. Estimated FT and RFDT, but not peak LT, increased with external loading. Temporal comparisons between 0% and 90% loads revealed that FT was greater with 90% loading throughout the majority of the movement (11%-81% and 87%-95% movement duration). However, RFDT was greater with 90% load only during the early movement initiation phase (8%-15% movement duration) but was greater in the 0% load condition later in the eccentric phase (27%-38% movement duration). LT was longer during the early movement (12%-23% movement duration) but shorter in the late eccentric and early concentric phases (48%-55% movement duration) with 90% load. External loading positively influenced peak FT and RFDT but tendon strain appeared unaffected, suggesting no additive effect of external loading on patellar tendon lengthening during human jumping. Temporal analysis revealed that external loading resulted in a large initial RFDT that may have caused dynamic stiffening of the tendon and attenuated tendon strain throughout the movement. These results suggest that external loading influences tendon lengthening in both a load- and movement-dependent manner.

Complex and unexpected dynamics in simple genetic regulatory networks

Science.gov (United States)

Borg, Yanika; Ullner, Ekkehard; Alagha, Afnan; Alsaedi, Ahmed; Nesbeth, Darren; Zaikin, Alexey

2014-03-01

One aim of synthetic biology is to construct increasingly complex genetic networks from interconnected simpler ones to address challenges in medicine and biotechnology. However, as systems increase in size and complexity, emergent properties lead to unexpected and complex dynamics due to nonlinear and nonequilibrium properties from component interactions. We focus on four different studies of biological systems which exhibit complex and unexpected dynamics. Using simple synthetic genetic networks, small and large populations of phase-coupled quorum sensing repressilators, Goodwin oscillators, and bistable switches, we review how coupled and stochastic components can result in clustering, chaos, noise-induced coherence and speed-dependent decision making. A system of repressilators exhibits oscillations, limit cycles, steady states or chaos depending on the nature and strength of the coupling mechanism. In large repressilator networks, rich dynamics can also be exhibited, such as clustering and chaos. In populations of Goodwin oscillators, noise can induce coherent oscillations. In bistable systems, the speed with which incoming external signals reach steady state can bias the network towards particular attractors. These studies showcase the range of dynamical behavior that simple synthetic genetic networks can exhibit. In addition, they demonstrate the ability of mathematical modeling to analyze nonlinearity and inhomogeneity within these systems.

Control theory of digitally networked dynamic systems

CERN Document Server

Lunze, Jan

2013-01-01

The book gives an introduction to networked control systems and describes new modeling paradigms, analysis methods for event-driven, digitally networked systems, and design methods for distributed estimation and control. Networked model predictive control is developed as a means to tolerate time delays and packet loss brought about by the communication network. In event-based control the traditional periodic sampling is replaced by state-dependent triggering schemes. Novel methods for multi-agent systems ensure complete or clustered synchrony of agents with identical or with individual dynamic

Dynamics of slow and fast systems on complex networks

Indian Academy of Sciences (India)

synchrony in oscillator networks [10]. In power grids and the Internet it has been shown that heterogeneity due to different loads on nodes can cause a cascade ..... from that of the bipartite one even when they start from the same initial conditions. In the network of 3 sys- tems the configurations 3 and 4 exhibited frequency.

Mathematical model for spreading dynamics of social network worms

International Nuclear Information System (INIS)

Sun, Xin; Liu, Yan-Heng; Han, Jia-Wei; Liu, Xue-Jie; Li, Bin; Li, Jin

2012-01-01

In this paper, a mathematical model for social network worm spreading is presented from the viewpoint of social engineering. This model consists of two submodels. Firstly, a human behavior model based on game theory is suggested for modeling and predicting the expected behaviors of a network user encountering malicious messages. The game situation models the actions of a user under the condition that the system may be infected at the time of opening a malicious message. Secondly, a social network accessing model is proposed to characterize the dynamics of network users, by which the number of online susceptible users can be determined at each time step. Several simulation experiments are carried out on artificial social networks. The results show that (1) the proposed mathematical model can well describe the spreading dynamics of social network worms; (2) weighted network topology greatly affects the spread of worms; (3) worms spread even faster on hybrid social networks

Quality of computerized blast load simulation for non-linear dynamic ...

African Journals Online (AJOL)

Quality of computerized blast load simulation for non-linear dynamic response ... commercial software system and a special-purpose, blast-specific software product to ... depend both on the analysis model of choice and the stand-off distances.

Cell fate reprogramming by control of intracellular network dynamics

Science.gov (United States)

Zanudo, Jorge G. T.; Albert, Reka

Identifying control strategies for biological networks is paramount for practical applications that involve reprogramming a cell's fate, such as disease therapeutics and stem cell reprogramming. Although the topic of controlling the dynamics of a system has a long history in control theory, most of this work is not directly applicable to intracellular networks. Here we present a network control method that integrates the structural and functional information available for intracellular networks to predict control targets. Formulated in a logical dynamic scheme, our control method takes advantage of certain function-dependent network components and their relation to steady states in order to identify control targets, which are guaranteed to drive any initial state to the target state with 100% effectiveness and need to be applied only transiently for the system to reach and stay in the desired state. We illustrate our method's potential to find intervention targets for cancer treatment and cell differentiation by applying it to a leukemia signaling network and to the network controlling the differentiation of T cells. We find that the predicted control targets are effective in a broad dynamic framework. Moreover, several of the predicted interventions are supported by experiments. This work was supported by NSF Grant PHY 1205840.

Load Management in District Heating Operation

DEFF Research Database (Denmark)

Li, Hongwei; Wang, Stephen Jia

2015-01-01

Smooth operation of district heating system will avoid installation of expensive peak heat boilers, improve plant partial load performance, increase the system redundancy for further network expansion and improve its resilience to ensure security of supply during severe heating seasons. The peak...... heating load can be reduced through building demand side management. The building thermal mass can be used to shift the heating supply under the circumstance without jeopardizing the consumer thermal comfort. In this paper, the multi-agent framework is applied to a simplified building dynamic model...

Arresting Strategy Based on Dynamic Criminal Networks Changing over Time

Directory of Open Access Journals (Sweden)

Junqing Yuan

2013-01-01

Full Text Available We investigate a sequence of dynamic criminal networks on a time series based on the dynamic network analysis (DNA. According to the change of networks’ structure, networks’ variation trend is analyzed to forecast its future structure. Finally, an optimal arresting time and priority list are designed based on our analysis. Better results can be expected than that based on social network analysis (SNA.

Loading dynamics of a sliding DNA clamp.

KAUST Repository

Cho, Won-Ki

2014-05-22

Sliding DNA clamps are loaded at a ss/dsDNA junction by a clamp loader that depends on ATP binding for clamp opening. Sequential ATP hydrolysis results in closure of the clamp so that it completely encircles and diffuses on dsDNA. We followed events during loading of an E. coli β clamp in real time by using single-molecule FRET (smFRET). Three successive FRET states were retained for 0.3 s, 0.7 s, and 9 min: Hydrolysis of the first ATP molecule by the γ clamp loader resulted in closure of the clamp in 0.3 s, and after 0.7 s in the closed conformation, the clamp was released to diffuse on the dsDNA for at least 9 min. An additional single-molecule polarization study revealed that the interfacial domain of the clamp rotated in plane by approximately 8° during clamp closure. The single-molecule polarization and FRET studies thus revealed the real-time dynamics of the ATP-hydrolysis-dependent 3D conformational change of the β clamp during loading at a ss/dsDNA junction.

DyNet: visualization and analysis of dynamic molecular interaction networks.

Science.gov (United States)

Goenawan, Ivan H; Bryan, Kenneth; Lynn, David J

2016-09-01

: The ability to experimentally determine molecular interactions on an almost proteome-wide scale under different conditions is enabling researchers to move from static to dynamic network analysis, uncovering new insights into how interaction networks are physically rewired in response to different stimuli and in disease. Dynamic interaction data presents a special challenge in network biology. Here, we present DyNet, a Cytoscape application that provides a range of functionalities for the visualization, real-time synchronization and analysis of large multi-state dynamic molecular interaction networks enabling users to quickly identify and analyze the most 'rewired' nodes across many network states. DyNet is available at the Cytoscape (3.2+) App Store (http://apps.cytoscape.org/apps/dynet). david.lynn@sahmri.com Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Dynamic Response and Optimal Design of Curved Metallic Sandwich Panels under Blast Loading

Science.gov (United States)

Yang, Shu; Han, Shou-Hong; Lu, Zhen-Hua

2014-01-01

It is important to understand the effect of curvature on the blast response of curved structures so as to seek the optimal configurations of such structures with improved blast resistance. In this study, the dynamic response and protective performance of a type of curved metallic sandwich panel subjected to air blast loading were examined using LS-DYNA. The numerical methods were validated using experimental data in the literature. The curved panel consisted of an aluminum alloy outer face and a rolled homogeneous armour (RHA) steel inner face in addition to a closed-cell aluminum foam core. The results showed that the configuration of a “soft” outer face and a “hard” inner face worked well for the curved sandwich panel against air blast loading in terms of maximum deflection (MaxD) and energy absorption. The panel curvature was found to have a monotonic effect on the specific energy absorption (SEA) and a nonmonotonic effect on the MaxD of the panel. Based on artificial neural network (ANN) metamodels, multiobjective optimization designs of the panel were carried out. The optimization results revealed the trade-off relationships between the blast-resistant and the lightweight objectives and showed the great use of Pareto front in such design circumstances. PMID:25126606

Dynamic response and optimal design of curved metallic sandwich panels under blast loading.

Science.gov (United States)

Qi, Chang; Yang, Shu; Yang, Li-Jun; Han, Shou-Hong; Lu, Zhen-Hua

2014-01-01

It is important to understand the effect of curvature on the blast response of curved structures so as to seek the optimal configurations of such structures with improved blast resistance. In this study, the dynamic response and protective performance of a type of curved metallic sandwich panel subjected to air blast loading were examined using LS-DYNA. The numerical methods were validated using experimental data in the literature. The curved panel consisted of an aluminum alloy outer face and a rolled homogeneous armour (RHA) steel inner face in addition to a closed-cell aluminum foam core. The results showed that the configuration of a "soft" outer face and a "hard" inner face worked well for the curved sandwich panel against air blast loading in terms of maximum deflection (MaxD) and energy absorption. The panel curvature was found to have a monotonic effect on the specific energy absorption (SEA) and a nonmonotonic effect on the MaxD of the panel. Based on artificial neural network (ANN) metamodels, multiobjective optimization designs of the panel were carried out. The optimization results revealed the trade-off relationships between the blast-resistant and the lightweight objectives and showed the great use of Pareto front in such design circumstances.

Dynamic Response and Optimal Design of Curved Metallic Sandwich Panels under Blast Loading

Directory of Open Access Journals (Sweden)

Chang Qi

2014-01-01

Full Text Available It is important to understand the effect of curvature on the blast response of curved structures so as to seek the optimal configurations of such structures with improved blast resistance. In this study, the dynamic response and protective performance of a type of curved metallic sandwich panel subjected to air blast loading were examined using LS-DYNA. The numerical methods were validated using experimental data in the literature. The curved panel consisted of an aluminum alloy outer face and a rolled homogeneous armour (RHA steel inner face in addition to a closed-cell aluminum foam core. The results showed that the configuration of a “soft” outer face and a “hard” inner face worked well for the curved sandwich panel against air blast loading in terms of maximum deflection (MaxD and energy absorption. The panel curvature was found to have a monotonic effect on the specific energy absorption (SEA and a nonmonotonic effect on the MaxD of the panel. Based on artificial neural network (ANN metamodels, multiobjective optimization designs of the panel were carried out. The optimization results revealed the trade-off relationships between the blast-resistant and the lightweight objectives and showed the great use of Pareto front in such design circumstances.

Dynamics of epidemic diseases on a growing adaptive network.

Science.gov (United States)

Demirel, Güven; Barter, Edmund; Gross, Thilo

2017-02-10

The study of epidemics on static networks has revealed important effects on disease prevalence of network topological features such as the variance of the degree distribution, i.e. the distribution of the number of neighbors of nodes, and the maximum degree. Here, we analyze an adaptive network where the degree distribution is not independent of epidemics but is shaped through disease-induced dynamics and mortality in a complex interplay. We study the dynamics of a network that grows according to a preferential attachment rule, while nodes are simultaneously removed from the network due to disease-induced mortality. We investigate the prevalence of the disease using individual-based simulations and a heterogeneous node approximation. Our results suggest that in this system in the thermodynamic limit no epidemic thresholds exist, while the interplay between network growth and epidemic spreading leads to exponential networks for any finite rate of infectiousness when the disease persists.

Agent Based Modeling on Organizational Dynamics of Terrorist Network

Directory of Open Access Journals (Sweden)

Bo Li

2015-01-01

Full Text Available Modeling organizational dynamics of terrorist network is a critical issue in computational analysis of terrorism research. The first step for effective counterterrorism and strategic intervention is to investigate how the terrorists operate with the relational network and what affects the performance. In this paper, we investigate the organizational dynamics by employing a computational experimentation methodology. The hierarchical cellular network model and the organizational dynamics model are developed for modeling the hybrid relational structure and complex operational processes, respectively. To intuitively elucidate this method, the agent based modeling is used to simulate the terrorist network and test the performance in diverse scenarios. Based on the experimental results, we show how the changes of operational environments affect the development of terrorist organization in terms of its recovery and capacity to perform future tasks. The potential strategies are also discussed, which can be used to restrain the activities of terrorists.

Topology Identification of General Dynamical Network with Distributed Time Delays

International Nuclear Information System (INIS)

Zhao-Yan, Wu; Xin-Chu, Fu

2009-01-01

General dynamical networks with distributed time delays are studied. The topology of the networks are viewed as unknown parameters, which need to be identified. Some auxiliary systems (also called the network estimators) are designed to achieve this goal. Both linear feedback control and adaptive strategy are applied in designing these network estimators. Based on linear matrix inequalities and the Lyapunov function method, the sufficient condition for the achievement of topology identification is obtained. This method can also better monitor the switching topology of dynamical networks. Illustrative examples are provided to show the effectiveness of this method. (general)

Dynamic hydro-climatic networks in pristine and regulated rivers

Science.gov (United States)

Botter, G.; Basso, S.; Lazzaro, G.; Doulatyari, B.; Biswal, B.; Schirmer, M.; Rinaldo, A.

2014-12-01

Flow patterns observed at-a-station are the dynamical byproduct of a cascade of processes involving different compartments of the hydro-climatic network (e.g., climate, rainfall, soil, vegetation) that regulates the transformation of rainfall into streamflows. In complex branching rivers, flow regimes result from the heterogeneous arrangement around the stream network of multiple hydrologic cascades that simultaneously occur within distinct contributing areas. As such, flow regimes are seen as the integrated output of a complex "network of networks", which can be properly characterized by its degree of temporal variability and spatial heterogeneity. Hydrologic networks that generate river flow regimes are dynamic in nature. In pristine rivers, the time-variance naturally emerges at multiple timescales from climate variability (namely, seasonality and inter-annual fluctuations), implying that the magnitude (and the features) of the water flow between two nodes may be highly variable across different seasons and years. Conversely, the spatial distribution of river flow regimes within pristine rivers involves scale-dependent transport features, as well as regional climatic and soil use gradients, which in small and meso-scale catchments (A guarantee quite uniform flow regimes and high spatial correlations. Human-impacted rivers, instead, constitute hybrid networks where observed spatio-temporal patterns are dominated by anthropogenic shifts, such as landscape alterations and river regulation. In regulated rivers, the magnitude and the features of water flows from node to node may change significantly through time due to damming and withdrawals. However, regulation may impact river regimes in a spatially heterogeneous manner (e.g. in localized river reaches), with a significant decrease of spatial correlations and network connectivity. Provided that the spatial and temporal dynamics of flow regimes in complex rivers may strongly impact important biotic processes

Impact of constrained rewiring on network structure and node dynamics

Science.gov (United States)

Rattana, P.; Berthouze, L.; Kiss, I. Z.

2014-11-01

In this paper, we study an adaptive spatial network. We consider a susceptible-infected-susceptible (SIS) epidemic on the network, with a link or contact rewiring process constrained by spatial proximity. In particular, we assume that susceptible nodes break links with infected nodes independently of distance and reconnect at random to susceptible nodes available within a given radius. By systematically manipulating this radius we investigate the impact of rewiring on the structure of the network and characteristics of the epidemic. We adopt a step-by-step approach whereby we first study the impact of rewiring on the network structure in the absence of an epidemic, then with nodes assigned a disease status but without disease dynamics, and finally running network and epidemic dynamics simultaneously. In the case of no labeling and no epidemic dynamics, we provide both analytic and semianalytic formulas for the value of clustering achieved in the network. Our results also show that the rewiring radius and the network's initial structure have a pronounced effect on the endemic equilibrium, with increasingly large rewiring radiuses yielding smaller disease prevalence.

Context-dependent retrieval of information by neural-network dynamics with continuous attractors.

Science.gov (United States)

Tsuboshita, Yukihiro; Okamoto, Hiroshi

2007-08-01

Memory retrieval in neural networks has traditionally been described by dynamic systems with discrete attractors. However, recent neurophysiological findings of graded persistent activity suggest that memory retrieval in the brain is more likely to be described by dynamic systems with continuous attractors. To explore what sort of information processing is achieved by continuous-attractor dynamics, keyword extraction from documents by a network of bistable neurons, which gives robust continuous attractors, is examined. Given an associative network of terms, a continuous attractor led by propagation of neuronal activation in this network appears to represent keywords that express underlying meaning of a document encoded in the initial state of the network-activation pattern. A dominant hypothesis in cognitive psychology is that long-term memory is archived in the network structure, which resembles associative networks of terms. Our results suggest that keyword extraction by the neural-network dynamics with continuous attractors might symbolically represent context-dependent retrieval of short-term memory from long-term memory in the brain.

Discriminating lysosomal membrane protein types using dynamic neural network.

Science.gov (United States)