Adaptive Load-Balancing Algorithms using Symmetric Broadcast Networks

NASA Technical Reports Server (NTRS)

Das, Sajal K.; Harvey, Daniel J.; Biswas, Rupak; Biegel, Bryan A. (Technical Monitor)

2002-01-01

In a distributed computing environment, it is important to ensure that the processor workloads are adequately balanced, Among numerous load-balancing algorithms, a unique approach due to Das and Prasad defines a symmetric broadcast network (SBN) that provides a robust communication pattern among the processors in a topology-independent manner. In this paper, we propose and analyze three efficient SBN-based dynamic load-balancing algorithms, and implement them on an SGI Origin2000. A thorough experimental study with Poisson distributed synthetic loads demonstrates that our algorithms are effective in balancing system load. By optimizing completion time and idle time, the proposed algorithms are shown to compare favorably with several existing approaches.

Loads Bias Genetic and Signaling Switches in Synthetic and Natural Systems

PubMed Central

Medford, June; Prasad, Ashok

2014-01-01

Biological protein interactions networks such as signal transduction or gene transcription networks are often treated as modular, allowing motifs to be analyzed in isolation from the rest of the network. Modularity is also a key assumption in synthetic biology, where it is similarly expected that when network motifs are combined together, they do not lose their essential characteristics. However, the interactions that a network module has with downstream elements change the dynamical equations describing the upstream module and thus may change the dynamic and static properties of the upstream circuit even without explicit feedback. In this work we analyze the behavior of a ubiquitous motif in gene transcription and signal transduction circuits: the switch. We show that adding an additional downstream component to the simple genetic toggle switch changes its dynamical properties by changing the underlying potential energy landscape, and skewing it in favor of the unloaded side, and in some situations adding loads to the genetic switch can also abrogate bistable behavior. We find that an additional positive feedback motif found in naturally occurring toggle switches could tune the potential energy landscape in a desirable manner. We also analyze autocatalytic signal transduction switches and show that a ubiquitous positive feedback switch can lose its switch-like properties when connected to a downstream load. Our analysis underscores the necessity of incorporating the effects of downstream components when understanding the physics of biochemical network motifs, and raises the question as to how these effects are managed in real biological systems. This analysis is particularly important when scaling synthetic networks to more complex organisms. PMID:24676102

Dynamic waste management (DWM): towards an evolutionary decision-making approach.

PubMed

Rojo, Gabriel; Glaus, Mathias; Laforest, Valerie; Laforest, Valérie; Bourgois, Jacques; Bourgeois, Jacques; Hausler, Robert

2013-12-01

To guarantee sustainable and dynamic waste management, the dynamic waste management approach (DWM) suggests an evolutionary new approach that maintains a constant flow towards the most favourable waste treatment processes (facilities) within a system. To that end, DWM is based on the law of conservation of energy, which allows the balancing of a network, while considering the constraints of incoming (h1 ) and outgoing (h2 ) loads, as well as the distribution network (ΔH) characteristics. The developed approach lies on the identification of the prioritization index (PI) for waste generators (analogy to h1 ), a global allocation index for each of the treatment processes (analogy to h2 ) and the linear index load loss (ΔH) associated with waste transport. To demonstrate the scope of DWM, we outline this approach, and then present an example of its application. The case study shows that the variable monthly waste from the three considered sources is dynamically distributed in priority to the more favourable processes. Moreover, the reserve (stock) helps temporarily store waste in order to ease the global load of the network and favour a constant feeding of the treatment processes. The DWM approach serves as a decision-making tool by evaluating new waste treatment processes, as well as their location and new means of transport for waste.

DGs for Service Restoration to Critical Loads in a Secondary Network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Yin; Liu, Chen-Ching; Wang, Zhiwen

During a major outage in a secondary network distribution system, distributed generators (DGs) connected to the primary feeders as well as the secondary network can be used to serve critical loads. This paper proposed a resilience-oriented method to determine restoration strategies for secondary network distribution systems after a major disaster. Technical issues associated with the restoration process are analyzed, including the operation of network protectors, inrush currents caused by the energization of network transformers, synchronization of DGs to the network, and circulating currents among DGs. A look-ahead load restoration framework is proposed, incorporating technical issues associated with secondary networks, limitsmore » on DG capacity and generation resources, dynamic constraints, and operational limits. The entire outage duration is divided into a sequence of periods. Restoration strategies can be adjusted at the beginning of each period using the latest information. Finally, numerical simulation of the modified IEEE 342-node low voltage networked test system is performed to validate the effectiveness of the proposed method.« less

DGs for Service Restoration to Critical Loads in a Secondary Network

DOE PAGES

Xu, Yin; Liu, Chen-Ching; Wang, Zhiwen; ...

2017-08-25

During a major outage in a secondary network distribution system, distributed generators (DGs) connected to the primary feeders as well as the secondary network can be used to serve critical loads. This paper proposed a resilience-oriented method to determine restoration strategies for secondary network distribution systems after a major disaster. Technical issues associated with the restoration process are analyzed, including the operation of network protectors, inrush currents caused by the energization of network transformers, synchronization of DGs to the network, and circulating currents among DGs. A look-ahead load restoration framework is proposed, incorporating technical issues associated with secondary networks, limitsmore » on DG capacity and generation resources, dynamic constraints, and operational limits. The entire outage duration is divided into a sequence of periods. Restoration strategies can be adjusted at the beginning of each period using the latest information. Finally, numerical simulation of the modified IEEE 342-node low voltage networked test system is performed to validate the effectiveness of the proposed method.« less

Load-adaptive practical multi-channel communications in wireless sensor networks.

PubMed

Islam, Md Shariful; Alam, Muhammad Mahbub; Hong, Choong Seon; Lee, Sungwon

2010-01-01

In recent years, a significant number of sensor node prototypes have been designed that provide communications in multiple channels. This multi-channel feature can be effectively exploited to increase the overall capacity and performance of wireless sensor networks (WSNs). In this paper, we present a multi-channel communications system for WSNs that is referred to as load-adaptive practical multi-channel communications (LPMC). LPMC estimates the active load of a channel at the sink since it has a more comprehensive view of the network behavior, and dynamically adds or removes channels based on the estimated load. LPMC updates the routing path to balance the loads of the channels. The nodes in a path use the same channel; therefore, they do not need to switch channels to receive or forward packets. LPMC has been evaluated through extensive simulations, and the results demonstrate that it can effectively increase the delivery ratio, network throughput, and channel utilization, and that it can decrease the end-to-end delay and energy consumption.

The prediction of nonlinear dynamic loads on helicopters from flight variables using artificial neural networks

NASA Technical Reports Server (NTRS)

Cook, A. B.; Fuller, C. R.; O'Brien, W. F.; Cabell, R. H.

1992-01-01

A method of indirectly monitoring component loads through common flight variables is proposed which requires an accurate model of the underlying nonlinear relationships. An artificial neural network (ANN) model learns relationships through exposure to a database of flight variable records and corresponding load histories from an instrumented military helicopter undergoing standard maneuvers. The ANN model, utilizing eight standard flight variables as inputs, is trained to predict normalized time-varying mean and oscillatory loads on two critical components over a range of seven maneuvers. Both interpolative and extrapolative capabilities are demonstrated with agreement between predicted and measured loads on the order of 90 percent to 95 percent. This work justifies pursuing the ANN method of predicting loads from flight variables.

Adaptive Load-Balancing Algorithms Using Symmetric Broadcast Networks

NASA Technical Reports Server (NTRS)

Das, Sajal K.; Biswas, Rupak; Chancellor, Marisa K. (Technical Monitor)

1997-01-01

In a distributed-computing environment, it is important to ensure that the processor workloads are adequately balanced. Among numerous load-balancing algorithms, a unique approach due to Dam and Prasad defines a symmetric broadcast network (SBN) that provides a robust communication pattern among the processors in a topology-independent manner. In this paper, we propose and analyze three novel SBN-based load-balancing algorithms, and implement them on an SP2. A thorough experimental study with Poisson-distributed synthetic loads demonstrates that these algorithms are very effective in balancing system load while minimizing processor idle time. They also compare favorably with several other existing load-balancing techniques. Additional experiments performed with real data demonstrate that the SBN approach is effective in adaptive computational science and engineering applications where dynamic load balancing is extremely crucial.

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

NASA Astrophysics Data System (ADS)

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.

Coseismic Damage Generation in Fault Zones by Successive High Strain Rate Loading Experiments

NASA Astrophysics Data System (ADS)

Aben, F. M.; Doan, M. L.; Renard, F.; Toussaint, R.; Reuschlé, T.; Gratier, J. P.

2014-12-01

Damage zones of active faults control both resistance to rupture and transport properties of the fault. Hence, knowing the rock damage's origin is important to constrain its properties. Here we study experimentally the damage generated by a succession of dynamic loadings, a process mimicking the stress history of a rock sample located next to an active fault. A propagating rupture generates high frequency stress perturbations next to its tip. This dynamic loading creates pervasive damage (pulverization), as multiple fractures initiate and grow simultaneously. Previous single loading experiments have shown a strain rate threshold for pulverization. Here, we focus on conditions below this threshold and the dynamic peak stress to constrain: 1) if there is dynamic fracturing at these conditions and 2) if successive loadings (cumulative seismic events) result in pervasive fracturing, effectively reducing the pulverization threshold to milder conditions. Monzonite samples were dynamically loaded (strain rate > 50 s-1) several times below the dynamic peak strength, using a Split Hopkinson Pressure Bar apparatus. Several quasi-static experiments were conducted as well (strain rate < 10-5-s). Samples loaded up to stresses above the quasi-static uniaxial compressive strength (qsUCS) systematically fragmented or pulverized after four successive loadings. We measured several damage proxies (P-wave velocity, porosity), that show a systematic increase in damage with each load. In addition, micro-computed tomography acquisition on several damage samples revealed the growth of a pervasive fracture network between ensuing loadings. Samples loaded dynamically below the qsUCS failed along one fracture after a variable amount of loadings and damage proxies do not show any a systematic trend. Our conclusions is that milder dynamic loading conditions, below the dynamic peak strength, result in pervasive dynamic fracturing. Also, successive loadings effectively lower the pulverization threshold of the rock. However, the peak loading stress must exceed the qsUCS of the rock, otherwise quasi-static fracturing occurs. Pulverized rocks found in the field are therefore witnesses of previous large earthquakes.

Population-based learning of load balancing policies for a distributed computer system

NASA Technical Reports Server (NTRS)

Mehra, Pankaj; Wah, Benjamin W.

1993-01-01

Effective load-balancing policies use dynamic resource information to schedule tasks in a distributed computer system. We present a novel method for automatically learning such policies. At each site in our system, we use a comparator neural network to predict the relative speedup of an incoming task using only the resource-utilization patterns obtained prior to the task's arrival. Outputs of these comparator networks are broadcast periodically over the distributed system, and the resource schedulers at each site use these values to determine the best site for executing an incoming task. The delays incurred in propagating workload information and tasks from one site to another, as well as the dynamic and unpredictable nature of workloads in multiprogrammed multiprocessors, may cause the workload pattern at the time of execution to differ from patterns prevailing at the times of load-index computation and decision making. Our load-balancing policy accommodates this uncertainty by using certain tunable parameters. We present a population-based machine-learning algorithm that adjusts these parameters in order to achieve high average speedups with respect to local execution. Our results show that our load-balancing policy, when combined with the comparator neural network for workload characterization, is effective in exploiting idle resources in a distributed computer system.

Dynamics Behaviors of Scale-Free Networks with Elastic Demand

NASA Astrophysics Data System (ADS)

Li, Yan-Lai; Sun, Hui-Jun; Wu, Jian-Jun

Many real-world networks, such as transportation networks and Internet, have the scale-free properties. It is important to study the bearing capacity of such networks. Considering the elastic demand condition, we analyze load distributions and bearing capacities with different parameters through artificially created scale-free networks. The simulation results show that the load distribution follows a power-law form, which means some ordered pairs, playing the dominant role in the transportation network, have higher demand than other pairs. We found that, with the decrease of perceptual error, the total and average ordered pair demand will decrease and then stay in a steady state. However, with the increase of the network size, the average demand of each ordered pair will decrease, which is particularly interesting for the network design problem.

User Access Management Based on Network Pricing for Social Network Applications

PubMed Central

Ma, Xingmin; Gu, Qing

2018-01-01

Social applications play a very important role in people’s lives, as users communicate with each other through social networks on a daily basis. This presents a challenge: How does one receive high-quality service from social networks at a low cost? Users can access different kinds of wireless networks from various locations. This paper proposes a user access management strategy based on network pricing such that networks can increase its income and improve service quality. Firstly, network price is treated as an optimizing access parameter, and an unascertained membership algorithm is used to make pricing decisions. Secondly, network price is adjusted dynamically in real time according to network load. Finally, selecting a network is managed and controlled in terms of the market economy. Simulation results show that the proposed scheme can effectively balance network load, reduce network congestion, improve the user's quality of service (QoS) requirements, and increase the network’s income. PMID:29495252

Universal resilience patterns in cascading load model: More capacity is not always better

NASA Astrophysics Data System (ADS)

Wang, Jianwei; Wang, Xue; Cai, Lin; Ni, Chengzhang; Xie, Wei; Xu, Bo

We study the problem of universal resilience patterns in complex networks against cascading failures. We revise the classical betweenness method and overcome its limitation of quantifying the load in cascading model. Considering that the generated load by all nodes should be equal to the transported one by all edges in the whole network, we propose a new method to quantify the load on an edge and construct a simple cascading model. By attacking the edge with the highest load, we show that, if the flow between two nodes is transported along the shortest paths between them, then the resilience of some networks against cascading failures inversely decreases with the enhancement of the capacity of every edge, i.e. the more capacity is not always better. We also observe the abnormal fluctuation of the additional load that exceeds the capacity of each edge. By a simple graph, we analyze the propagation of cascading failures step by step, and give a reasonable explanation of the abnormal fluctuation of cascading dynamics.

Neural networks for self-learning control systems

NASA Technical Reports Server (NTRS)

Nguyen, Derrick H.; Widrow, Bernard

1990-01-01

It is shown how a neural network can learn of its own accord to control a nonlinear dynamic system. An emulator, a multilayered neural network, learns to identify the system's dynamic characteristics. The controller, another multilayered neural network, next learns to control the emulator. The self-trained controller is then used to control the actual dynamic system. The learning process continues as the emulator and controller improve and track the physical process. An example is given to illustrate these ideas. The 'truck backer-upper,' a neural network controller that steers a trailer truck while the truck is backing up to a loading dock, is demonstrated. The controller is able to guide the truck to the dock from almost any initial position. The technique explored should be applicable to a wide variety of nonlinear control problems.

Adaptive MANET multipath routing algorithm based on the simulated annealing approach.

PubMed

Kim, Sungwook

2014-01-01

Mobile ad hoc network represents a system of wireless mobile nodes that can freely and dynamically self-organize network topologies without any preexisting communication infrastructure. Due to characteristics like temporary topology and absence of centralized authority, routing is one of the major issues in ad hoc networks. In this paper, a new multipath routing scheme is proposed by employing simulated annealing approach. The proposed metaheuristic approach can achieve greater and reciprocal advantages in a hostile dynamic real world network situation. Therefore, the proposed routing scheme is a powerful method for finding an effective solution into the conflict mobile ad hoc network routing problem. Simulation results indicate that the proposed paradigm adapts best to the variation of dynamic network situations. The average remaining energy, network throughput, packet loss probability, and traffic load distribution are improved by about 10%, 10%, 5%, and 10%, respectively, more than the existing schemes.

Shock waves on complex networks

NASA Astrophysics Data System (ADS)

Mones, Enys; Araújo, Nuno A. M.; Vicsek, Tamás; Herrmann, Hans J.

2014-05-01

Power grids, road maps, and river streams are examples of infrastructural networks which are highly vulnerable to external perturbations. An abrupt local change of load (voltage, traffic density, or water level) might propagate in a cascading way and affect a significant fraction of the network. Almost discontinuous perturbations can be modeled by shock waves which can eventually interfere constructively and endanger the normal functionality of the infrastructure. We study their dynamics by solving the Burgers equation under random perturbations on several real and artificial directed graphs. Even for graphs with a narrow distribution of node properties (e.g., degree or betweenness), a steady state is reached exhibiting a heterogeneous load distribution, having a difference of one order of magnitude between the highest and average loads. Unexpectedly we find for the European power grid and for finite Watts-Strogatz networks a broad pronounced bimodal distribution for the loads. To identify the most vulnerable nodes, we introduce the concept of node-basin size, a purely topological property which we show to be strongly correlated to the average load of a node.

Load Adaptation of Lamellipodial Actin Networks.

PubMed

Mueller, Jan; Szep, Gregory; Nemethova, Maria; de Vries, Ingrid; Lieber, Arnon D; Winkler, Christoph; Kruse, Karsten; Small, J Victor; Schmeiser, Christian; Keren, Kinneret; Hauschild, Robert; Sixt, Michael

2017-09-21

Actin filaments polymerizing against membranes power endocytosis, vesicular traffic, and cell motility. In vitro reconstitution studies suggest that the structure and the dynamics of actin networks respond to mechanical forces. We demonstrate that lamellipodial actin of migrating cells responds to mechanical load when membrane tension is modulated. In a steady state, migrating cell filaments assume the canonical dendritic geometry, defined by Arp2/3-generated 70° branch points. Increased tension triggers a dense network with a broadened range of angles, whereas decreased tension causes a shift to a sparse configuration dominated by filaments growing perpendicularly to the plasma membrane. We show that these responses emerge from the geometry of branched actin: when load per filament decreases, elongation speed increases and perpendicular filaments gradually outcompete others because they polymerize the shortest distance to the membrane, where they are protected from capping. This network-intrinsic geometrical adaptation mechanism tunes protrusive force in response to mechanical load. Copyright © 2017 Elsevier Inc. All rights reserved.

Dynamic functional connectivity and individual differences in emotions during social stress.

PubMed

Tobia, Michael J; Hayashi, Koby; Ballard, Grey; Gotlib, Ian H; Waugh, Christian E

2017-12-01

Exposure to acute stress induces multiple emotional responses, each with their own unique temporal dynamics. Dynamic functional connectivity (dFC) measures the temporal variability of network synchrony and captures individual differences in network neurodynamics. This study investigated the relationship between dFC and individual differences in emotions induced by an acute psychosocial stressor. Sixteen healthy adult women underwent fMRI scanning during a social evaluative threat (SET) task, and retrospectively completed questionnaires that assessed individual differences in subjectively experienced positive and negative emotions about stress and stress relief during the task. Group dFC was decomposed with parallel factor analysis (PARAFAC) into 10 components, each with a temporal signature, spatial network of functionally connected regions, and vector of participant loadings that captures individual differences in dFC. Participant loadings of two networks were positively correlated with stress-related emotions, indicating the existence of networks for positive and negative emotions. The emotion-related networks involved the ventromedial prefrontal cortex, cingulate cortex, anterior insula, and amygdala, among other distributed brain regions, and time signatures for these emotion-related networks were uncorrelated. These findings demonstrate that individual differences in stress-induced positive and negative emotions are each uniquely associated with large-scale brain networks, and suggest that dFC is a mechanism that generates individual differences in the emotional components of the stress response. Hum Brain Mapp 38:6185-6205, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Framework for cascade size calculations on random networks

NASA Astrophysics Data System (ADS)

Burkholz, Rebekka; Schweitzer, Frank

2018-04-01

We present a framework to calculate the cascade size evolution for a large class of cascade models on random network ensembles in the limit of infinite network size. Our method is exact and applies to network ensembles with almost arbitrary degree distribution, degree-degree correlations, and, in case of threshold models, for arbitrary threshold distribution. With our approach, we shift the perspective from the known branching process approximations to the iterative update of suitable probability distributions. Such distributions are key to capture cascade dynamics that involve possibly continuous quantities and that depend on the cascade history, e.g., if load is accumulated over time. As a proof of concept, we provide two examples: (a) Constant load models that cover many of the analytically tractable casacade models, and, as a highlight, (b) a fiber bundle model that was not tractable by branching process approximations before. Our derivations cover the whole cascade dynamics, not only their steady state. This allows us to include interventions in time or further model complexity in the analysis.

Stress-enhanced gelation: a dynamic nonlinearity of elasticity.

PubMed

Yao, Norman Y; Broedersz, Chase P; Depken, Martin; Becker, Daniel J; Pollak, Martin R; Mackintosh, Frederick C; Weitz, David A

2013-01-04

A hallmark of biopolymer networks is their sensitivity to stress, reflected by pronounced nonlinear elastic stiffening. Here, we demonstrate a distinct dynamical nonlinearity in biopolymer networks consisting of filamentous actin cross-linked by α-actinin-4. Applied stress delays the onset of relaxation and flow, markedly enhancing gelation and extending the regime of solidlike behavior to much lower frequencies. We show that this macroscopic network response can be accounted for at the single molecule level by the increased binding affinity of the cross-linker under load, characteristic of catch-bond-like behavior.

Redundant Design in Interdependent Networks

PubMed Central

2016-01-01

Modern infrastructure networks are often coupled together and thus could be modeled as interdependent networks. Overload and interdependent effect make interdependent networks more fragile when suffering from attacks. Existing research has primarily concentrated on the cascading failure process of interdependent networks without load, or the robustness of isolated network with load. Only limited research has been done on the cascading failure process caused by overload in interdependent networks. Redundant design is a primary approach to enhance the reliability and robustness of the system. In this paper, we propose two redundant methods, node back-up and dependency redundancy, and the experiment results indicate that two measures are effective and costless. Two detailed models about redundant design are introduced based on the non-linear load-capacity model. Based on the attributes and historical failure distribution of nodes, we introduce three static selecting strategies-Random-based, Degree-based, Initial load-based and a dynamic strategy-HFD (historical failure distribution) to identify which nodes could have a back-up with priority. In addition, we consider the cost and efficiency of different redundant proportions to determine the best proportion with maximal enhancement and minimal cost. Experiments on interdependent networks demonstrate that the combination of HFD and dependency redundancy is an effective and preferred measure to implement redundant design on interdependent networks. The results suggest that the redundant design proposed in this paper can permit construction of highly robust interactive networked systems. PMID:27764174

Dynamic Load-Balancing for Distributed Heterogeneous Computing of Parallel CFD Problems

NASA Technical Reports Server (NTRS)

Ecer, A.; Chien, Y. P.; Boenisch, T.; Akay, H. U.

2000-01-01

The developed methodology is aimed at improving the efficiency of executing block-structured algorithms on parallel, distributed, heterogeneous computers. The basic approach of these algorithms is to divide the flow domain into many sub- domains called blocks, and solve the governing equations over these blocks. Dynamic load balancing problem is defined as the efficient distribution of the blocks among the available processors over a period of several hours of computations. In environments with computers of different architecture, operating systems, CPU speed, memory size, load, and network speed, balancing the loads and managing the communication between processors becomes crucial. Load balancing software tools for mutually dependent parallel processes have been created to efficiently utilize an advanced computation environment and algorithms. These tools are dynamic in nature because of the chances in the computer environment during execution time. More recently, these tools were extended to a second operating system: NT. In this paper, the problems associated with this application will be discussed. Also, the developed algorithms were combined with the load sharing capability of LSF to efficiently utilize workstation clusters for parallel computing. Finally, results will be presented on running a NASA based code ADPAC to demonstrate the developed tools for dynamic load balancing.

A survey on investigating the need for intelligent power-aware load balanced routing protocols for handling critical links in MANETs.

PubMed

Sivakumar, B; Bhalaji, N; Sivakumar, D

2014-01-01

In mobile ad hoc networks connectivity is always an issue of concern. Due to dynamism in the behavior of mobile nodes, efficiency shall be achieved only with the assumption of good network infrastructure. Presence of critical links results in deterioration which should be detected in advance to retain the prevailing communication setup. This paper discusses a short survey on the specialized algorithms and protocols related to energy efficient load balancing for critical link detection in the recent literature. This paper also suggests a machine learning based hybrid power-aware approach for handling critical nodes via load balancing.

A Survey on Investigating the Need for Intelligent Power-Aware Load Balanced Routing Protocols for Handling Critical Links in MANETs

PubMed Central

Sivakumar, B.; Bhalaji, N.; Sivakumar, D.

2014-01-01

In mobile ad hoc networks connectivity is always an issue of concern. Due to dynamism in the behavior of mobile nodes, efficiency shall be achieved only with the assumption of good network infrastructure. Presence of critical links results in deterioration which should be detected in advance to retain the prevailing communication setup. This paper discusses a short survey on the specialized algorithms and protocols related to energy efficient load balancing for critical link detection in the recent literature. This paper also suggests a machine learning based hybrid power-aware approach for handling critical nodes via load balancing. PMID:24790546

Dynamic bandwidth allocation based on multiservice in software-defined wavelength-division multiplexing time-division multiplexing passive optical network

NASA Astrophysics Data System (ADS)

Wang, Fu; Liu, Bo; Zhang, Lijia; Jin, Feifei; Zhang, Qi; Tian, Qinghua; Tian, Feng; Rao, Lan; Xin, Xiangjun

2017-03-01

The wavelength-division multiplexing passive optical network (WDM-PON) is a potential technology to carry multiple services in an optical access network. However, it has the disadvantages of high cost and an immature technique for users. A software-defined WDM/time-division multiplexing PON was proposed to meet the requirements of high bandwidth, high performance, and multiple services. A reasonable and effective uplink dynamic bandwidth allocation algorithm was proposed. A controller with dynamic wavelength and slot assignment was introduced, and a different optical dynamic bandwidth management strategy was formulated flexibly for services of different priorities according to the network loading. The simulation compares the proposed algorithm with the interleaved polling with adaptive cycle time algorithm. The algorithm shows better performance in average delay, throughput, and bandwidth utilization. The results show that the delay is reduced to 62% and the throughput is improved by 35%.

Fair Energy Scheduling for Vehicle-to-Grid Networks Using Adaptive Dynamic Programming.

PubMed

Xie, Shengli; Zhong, Weifeng; Xie, Kan; Yu, Rong; Zhang, Yan

2016-08-01

Research on the smart grid is being given enormous supports worldwide due to its great significance in solving environmental and energy crises. Electric vehicles (EVs), which are powered by clean energy, are adopted increasingly year by year. It is predictable that the huge charge load caused by high EV penetration will have a considerable impact on the reliability of the smart grid. Therefore, fair energy scheduling for EV charge and discharge is proposed in this paper. By using the vehicle-to-grid technology, the scheduler controls the electricity loads of EVs considering fairness in the residential distribution network. We propose contribution-based fairness, in which EVs with high contributions have high priorities to obtain charge energy. The contribution value is defined by both the charge/discharge energy and the timing of the action. EVs can achieve higher contribution values when discharging during the load peak hours. However, charging during this time will decrease the contribution values seriously. We formulate the fair energy scheduling problem as an infinite-horizon Markov decision process. The methodology of adaptive dynamic programming is employed to maximize the long-term fairness by processing online network training. The numerical results illustrate that the proposed EV energy scheduling is able to mitigate and flatten the peak load in the distribution network. Furthermore, contribution-based fairness achieves a fast recovery of EV batteries that have deeply discharged and guarantee fairness in the full charge time of all EVs.

A Distributed Dynamic Programming-Based Solution for Load Management in Smart Grids

NASA Astrophysics Data System (ADS)

Zhang, Wei; Xu, Yinliang; Li, Sisi; Zhou, MengChu; Liu, Wenxin; Xu, Ying

2018-03-01

Load management is being recognized as an important option for active user participation in the energy market. Traditional load management methods usually require a centralized powerful control center and a two-way communication network between the system operators and energy end-users. The increasing user participation in smart grids may limit their applications. In this paper, a distributed solution for load management in emerging smart grids is proposed. The load management problem is formulated as a constrained optimization problem aiming at maximizing the overall utility of users while meeting the requirement for load reduction requested by the system operator, and is solved by using a distributed dynamic programming algorithm. The algorithm is implemented via a distributed framework and thus can deliver a highly desired distributed solution. It avoids the required use of a centralized coordinator or control center, and can achieve satisfactory outcomes for load management. Simulation results with various test systems demonstrate its effectiveness.

Parallel Processing of Adaptive Meshes with Load Balancing

NASA Technical Reports Server (NTRS)

Das, Sajal K.; Harvey, Daniel J.; Biswas, Rupak; Biegel, Bryan (Technical Monitor)

2001-01-01

Many scientific applications involve grids that lack a uniform underlying structure. These applications are often also dynamic in nature in that the grid structure significantly changes between successive phases of execution. In parallel computing environments, mesh adaptation of unstructured grids through selective refinement/coarsening has proven to be an effective approach. However, achieving load balance while minimizing interprocessor communication and redistribution costs is a difficult problem. Traditional dynamic load balancers are mostly inadequate because they lack a global view of system loads across processors. In this paper, we propose a novel and general-purpose load balancer that utilizes symmetric broadcast networks (SBN) as the underlying communication topology, and compare its performance with a successful global load balancing environment, called PLUM, specifically created to handle adaptive unstructured applications. Our experimental results on an IBM SP2 demonstrate that the SBN-based load balancer achieves lower redistribution costs than that under PLUM by overlapping processing and data migration.

System Impact Study of the Eastern Grid of Sumba Island, Indonesia: Steady-State and Dynamic System Modeling for the Integration of One and Two 850-kW Wind Turbine Generators

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oswal, R.; Jain, P.; Muljadi, Eduard

2016-01-01

The goal of this project was to study the impact of integrating one and two 850-kW wind turbine generators into the eastern power system network of Sumba Island, Indonesia. A model was created for the 20-kV distribution network as it existed in the first quarter of 2015 with a peak load of 5.682 MW. Detailed data were collected for each element of the network. Load flow, short-circuit, and transient analyses were performed using DIgSILENT PowerFactory 15.2.1.

Force-velocity relation for actin-polymerization-driven motility from Brownian dynamics simulations.

PubMed

Lee, Kun-Chun; Liu, Andrea J

2009-09-02

We report numerical simulation results for the force-velocity relation for actin-polymerization-driven motility. We use Brownian dynamics to solve a physically consistent formulation of the dendritic nucleation model with semiflexible filaments that self-assemble and push a disk. We find that at small loads, the disk speed is independent of load, whereas at high loads, the speed decreases and vanishes at a characteristic stall pressure. Our results demonstrate that at small loads, the velocity is controlled by the reaction rates, whereas at high loads the stall pressure is determined by the mechanical properties of the branched actin network. The behavior is consistent with experiments and with our recently proposed self-diffusiophoretic mechanism for actin-polymerization-driven motility. New in vitro experiments to measure the force-velocity relation are proposed.

A Scalable Distribution Network Risk Evaluation Framework via Symbolic Dynamics

PubMed Central

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

An efficient routing strategy for traffic dynamics on two-layer complex networks

NASA Astrophysics Data System (ADS)

Ma, Jinlong; Wang, Huiling; Zhang, Zhuxi; Zhang, Yi; Duan, Congwen; Qi, Zhaohui; Liu, Yu

2018-05-01

In order to alleviate traffic congestion on multilayer networks, designing an efficient routing strategy is one of the most important ways. In this paper, a novel routing strategy is proposed to reduce traffic congestion on two-layer networks. In the proposed strategy, the optimal paths in the physical layer are chosen by comprehensively considering the roles of nodes’ degrees of the two layers. Both numerical and analytical results indicate that our routing strategy can reasonably redistribute the traffic load of the physical layer, and thus the traffic capacity of two-layer complex networks are significantly enhanced compared with the shortest path routing (SPR) and the global awareness routing (GAR) strategies. This study may shed some light on the optimization of networked traffic dynamics.

FIBER OPTICS: Role of point defects in the photosensitivity of hydrogen-loaded phosphosilicate glass

NASA Astrophysics Data System (ADS)

Larionov, Yu V.

2010-08-01

It is shown that point defect modifications in hydrogen-loaded phosphosilicate glass (PSG) do not play a central role in determining its photosensitivity. Photochemical reactions that involve a two-step point defect modification and pre-exposure effect are incapable of accounting for photoinduced refractive index changes. It seems likely that a key role in UV-induced refractive index modifications is played by structural changes in the PSG network. Experimental data are presented that demonstrate intricate network rearrangement dynamics during UV exposure of PSG.

A continually online-trained neural network controller for brushless DC motor drives

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rubaai, A.; Kotaru, R.; Kankam, M.D.

2000-04-01

In this paper, a high-performance controller with simultaneous online identification and control is designed for brushless dc motor drives. The dynamics of the motor/load are modeled online, and controlled using two different neural network based identification and control schemes, as the system is in operation. In the first scheme, an attempt is made to control the rotor angular speed, utilizing a single three-hidden-layer network. The second scheme attempts to control the stator currents, using a predetermined control law as a function of the estimated states. This schemes incorporates three multilayered feedforward neural networks that are online trained, using the Levenburg-Marquadtmore » training algorithm. The control of the direct and quadrature components of the stator current successfully tracked a wide variety of trajectories after relatively short online training periods. The control strategy adapts to the uncertainties of the motor/load dynamics and, in addition, learns their inherent nonlinearities. Simulation results illustrated that a neurocontroller used in conjunction with adaptive control schemes can result in a flexible control device which may be utilized in a wide range of environments.« less

Extended shortest path selection for package routing of complex networks

NASA Astrophysics Data System (ADS)

Ye, Fan; Zhang, Lei; Wang, Bing-Hong; Liu, Lu; Zhang, Xing-Yi

The routing strategy plays a very important role in complex networks such as Internet system and Peer-to-Peer networks. However, most of the previous work concentrates only on the path selection, e.g. Flooding and Random Walk, or finding the shortest path (SP) and rarely considering the local load information such as SP and Distance Vector Routing. Flow-based Routing mainly considers load balance and still cannot achieve best optimization. Thus, in this paper, we propose a novel dynamic routing strategy on complex network by incorporating the local load information into SP algorithm to enhance the traffic flow routing optimization. It was found that the flow in a network is greatly affected by the waiting time of the network, so we should not consider only choosing optimized path for package transformation but also consider node congestion. As a result, the packages should be transmitted with a global optimized path with smaller congestion and relatively short distance. Analysis work and simulation experiments show that the proposed algorithm can largely enhance the network flow with the maximum throughput within an acceptable calculating time. The detailed analysis of the algorithm will also be provided for explaining the efficiency.

Simple measurement-based admission control for DiffServ access networks

NASA Astrophysics Data System (ADS)

Lakkakorpi, Jani

2002-07-01

In order to provide good Quality of Service (QoS) in a Differentiated Services (DiffServ) network, a dynamic admission control scheme is definitely needed as an alternative to overprovisioning. In this paper, we present a simple measurement-based admission control (MBAC) mechanism for DiffServ-based access networks. Instead of using active measurements only or doing purely static bookkeeping with parameter-based admission control (PBAC), the admission control decisions are based on bandwidth reservations and periodically measured & exponentially averaged link loads. If any link load on the path between two endpoints is over the applicable threshold, access is denied. Link loads are periodically sent to Bandwidth Broker (BB) of the routing domain, which makes the admission control decisions. The information needed in calculating the link loads is retrieved from the router statistics. The proposed admission control mechanism is verified through simulations. Our results prove that it is possible to achieve very high bottleneck link utilization levels and still maintain good QoS.

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

PubMed

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 barriers that prevent data partners from participating in research data networks, and therefore, promotes the advancement of comparative effectiveness research using secondary electronic health data.

Historical data learning based dynamic LSP routing for overlay IP/MPLS over WDM networks

NASA Astrophysics Data System (ADS)

Yu, Xiaojun; Xiao, Gaoxi; Cheng, Tee Hiang

2013-08-01

Overlay IP/MPLS over WDM network is a promising network architecture starting to gain wide deployments recently. A desirable feature of such a network is to achieve efficient routing with limited information exchanges between the IP/MPLS and the WDM layers. This paper studies dynamic label switched path (LSP) routing in the overlay IP/MPLS over WDM networks. To enhance network performance while maintaining its simplicity, we propose to learn from the historical data of lightpath setup costs maintained by the IP-layer integrated service provider (ISP) when making routing decisions. Using a novel historical data learning scheme for logical link cost estimation, we develop a new dynamic LSP routing method named Existing Link First (ELF) algorithm. Simulation results show that the proposed algorithm significantly outperforms the existing ones under different traffic loads, with either limited or unlimited numbers of optical ports. Effects of the number of candidate routes, add/drop ratio and the amount of historical data are also evaluated.

Latency Hiding in Dynamic Partitioning and Load Balancing of Grid Computing Applications

NASA Technical Reports Server (NTRS)

Das, Sajal K.; Harvey, Daniel J.; Biswas, Rupak

2001-01-01

The Information Power Grid (IPG) concept developed by NASA is aimed to provide a metacomputing platform for large-scale distributed computations, by hiding the intricacies of highly heterogeneous environment and yet maintaining adequate security. In this paper, we propose a latency-tolerant partitioning scheme that dynamically balances processor workloads on the.IPG, and minimizes data movement and runtime communication. By simulating an unsteady adaptive mesh application on a wide area network, we study the performance of our load balancer under the Globus environment. The number of IPG nodes, the number of processors per node, and the interconnected speeds are parameterized to derive conditions under which the IPG would be suitable for parallel distributed processing of such applications. Experimental results demonstrate that effective solution are achieved when the IPG nodes are connected by a high-speed asynchronous interconnection network.

Neural Network based Control of SG based Standalone Generating System with Energy Storage for Power Quality Enhancement

NASA Astrophysics Data System (ADS)

Nayar, Priya; Singh, Bhim; Mishra, Sukumar

2017-08-01

An artificial intelligence based control algorithm is used in solving power quality problems of a diesel engine driven synchronous generator with automatic voltage regulator and governor based standalone system. A voltage source converter integrated with a battery energy storage system is employed to mitigate the power quality problems. An adaptive neural network based signed regressor control algorithm is used for the estimation of the fundamental component of load currents for control of a standalone system with load leveling as an integral feature. The developed model of the system performs accurately under varying load conditions and provides good dynamic response to the step changes in loads. The real time performance is achieved using MATLAB along with simulink/simpower system toolboxes and results adhere to an IEEE-519 standard for power quality enhancement.

Dynamic modeling and optimization for space logistics using time-expanded networks

NASA Astrophysics Data System (ADS)

Ho, Koki; de Weck, Olivier L.; Hoffman, Jeffrey A.; Shishko, Robert

2014-12-01

This research develops a dynamic logistics network formulation for lifecycle optimization of mission sequences as a system-level integrated method to find an optimal combination of technologies to be used at each stage of the campaign. This formulation can find the optimal transportation architecture considering its technology trades over time. The proposed methodologies are inspired by the ground logistics analysis techniques based on linear programming network optimization. Particularly, the time-expanded network and its extension are developed for dynamic space logistics network optimization trading the quality of the solution with the computational load. In this paper, the methodologies are applied to a human Mars exploration architecture design problem. The results reveal multiple dynamic system-level trades over time and give recommendation of the optimal strategy for the human Mars exploration architecture. The considered trades include those between In-Situ Resource Utilization (ISRU) and propulsion technologies as well as the orbit and depot location selections over time. This research serves as a precursor for eventual permanent settlement and colonization of other planets by humans and us becoming a multi-planet species.

From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks

PubMed Central

Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming

2016-01-01

The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains. PMID:26972968

From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks.

PubMed

Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming

2016-03-14

The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains.

Data analysis-based autonomic bandwidth adjustment in software defined multi-vendor optical transport networks.

PubMed

Li, Yajie; Zhao, Yongli; Zhang, Jie; Yu, Xiaosong; Jing, Ruiquan

2017-11-27

Network operators generally provide dedicated lightpaths for customers to meet the demand for high-quality transmission. Considering the variation of traffic load, customers usually rent peak bandwidth that exceeds the practical average traffic requirement. In this case, bandwidth provisioning is unmetered and customers have to pay according to peak bandwidth. Supposing that network operators could keep track of traffic load and allocate bandwidth dynamically, bandwidth can be provided as a metered service and customers would pay for the bandwidth that they actually use. To achieve cost-effective bandwidth provisioning, this paper proposes an autonomic bandwidth adjustment scheme based on data analysis of traffic load. The scheme is implemented in a software defined networking (SDN) controller and is demonstrated in the field trial of multi-vendor optical transport networks. The field trial shows that the proposed scheme can track traffic load and realize autonomic bandwidth adjustment. In addition, a simulation experiment is conducted to evaluate the performance of the proposed scheme. We also investigate the impact of different parameters on autonomic bandwidth adjustment. Simulation results show that the step size and adjustment period have significant influences on bandwidth savings and packet loss. A small value of step size and adjustment period can bring more benefits by tracking traffic variation with high accuracy. For network operators, the scheme can serve as technical support of realizing bandwidth as metered service in the future.

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

NASA Astrophysics Data System (ADS)

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.

An adaptive density-based routing protocol for flying Ad Hoc networks

NASA Astrophysics Data System (ADS)

Zheng, Xueli; Qi, Qian; Wang, Qingwen; Li, Yongqiang

2017-10-01

An Adaptive Density-based Routing Protocol (ADRP) for Flying Ad Hoc Networks (FANETs) is proposed in this paper. The main objective is to calculate forwarding probability adaptively in order to increase the efficiency of forwarding in FANETs. ADRP dynamically fine-tunes the rebroadcasting probability of a node for routing request packets according to the number of neighbour nodes. Indeed, it is more interesting to privilege the retransmission by nodes with little neighbour nodes. We describe the protocol, implement it and evaluate its performance using NS-2 network simulator. Simulation results reveal that ADRP achieves better performance in terms of the packet delivery fraction, average end-to-end delay, normalized routing load, normalized MAC load and throughput, which is respectively compared with AODV.

An intelligent switch with back-propagation neural network based hybrid power system

NASA Astrophysics Data System (ADS)

Perdana, R. H. Y.; Fibriana, F.

2018-03-01

The consumption of conventional energy such as fossil fuels plays the critical role in the global warming issues. The carbon dioxide, methane, nitrous oxide, etc. could lead the greenhouse effects and change the climate pattern. In fact, 77% of the electrical energy is generated from fossil fuels combustion. Therefore, it is necessary to use the renewable energy sources for reducing the conventional energy consumption regarding electricity generation. This paper presents an intelligent switch to combine both energy resources, i.e., the solar panels as the renewable energy with the conventional energy from the State Electricity Enterprise (PLN). The artificial intelligence technology with the back-propagation neural network was designed to control the flow of energy that is distributed dynamically based on renewable energy generation. By the continuous monitoring on each load and source, the dynamic pattern of the intelligent switch was better than the conventional switching method. The first experimental results for 60 W solar panels showed the standard deviation of the trial at 0.7 and standard deviation of the experiment at 0.28. The second operation for a 900 W of solar panel obtained the standard deviation of the trial at 0.05 and 0.18 for the standard deviation of the experiment. Moreover, the accuracy reached 83% using this method. By the combination of the back-propagation neural network with the observation of energy usage of the load using wireless sensor network, each load can be evenly distributed and will impact on the reduction of conventional energy usage.

Markov Task Network: A Framework for Service Composition under Uncertainty in Cyber-Physical Systems.

PubMed

Mohammed, Abdul-Wahid; Xu, Yang; Hu, Haixiao; Agyemang, Brighter

2016-09-21

In novel collaborative systems, cooperative entities collaborate services to achieve local and global objectives. With the growing pervasiveness of cyber-physical systems, however, such collaboration is hampered by differences in the operations of the cyber and physical objects, and the need for the dynamic formation of collaborative functionality given high-level system goals has become practical. In this paper, we propose a cross-layer automation and management model for cyber-physical systems. This models the dynamic formation of collaborative services pursuing laid-down system goals as an ontology-oriented hierarchical task network. Ontological intelligence provides the semantic technology of this model, and through semantic reasoning, primitive tasks can be dynamically composed from high-level system goals. In dealing with uncertainty, we further propose a novel bridge between hierarchical task networks and Markov logic networks, called the Markov task network. This leverages the efficient inference algorithms of Markov logic networks to reduce both computational and inferential loads in task decomposition. From the results of our experiments, high-precision service composition under uncertainty can be achieved using this approach.

Load-induced modulation of signal transduction networks.

PubMed

Jiang, Peng; Ventura, Alejandra C; Sontag, Eduardo D; Merajver, Sofia D; Ninfa, Alexander J; Del Vecchio, Domitilla

2011-10-11

Biological signal transduction networks are commonly viewed as circuits that pass along information--in the process amplifying signals, enhancing sensitivity, or performing other signal-processing tasks--to transcriptional and other components. Here, we report on a "reverse-causality" phenomenon, which we call load-induced modulation. Through a combination of analytical and experimental tools, we discovered that signaling was modulated, in a surprising way, by downstream targets that receive the signal and, in doing so, apply what in physics is called a load. Specifically, we found that non-intuitive changes in response dynamics occurred for a covalent modification cycle when load was present. Loading altered the response time of a system, depending on whether the activity of one of the enzymes was maximal and the other was operating at its minimal rate or whether both enzymes were operating at submaximal rates. These two conditions, which we call "limit regime" and "intermediate regime," were associated with increased or decreased response times, respectively. The bandwidth, the range of frequency in which the system can process information, decreased in the presence of load, suggesting that downstream targets participate in establishing a balance between noise-filtering capabilities and a circuit's ability to process high-frequency stimulation. Nodes in a signaling network are not independent relay devices, but rather are modulated by their downstream targets.

Optimization of an electromagnetic linear actuator using a network and a finite element model

NASA Astrophysics Data System (ADS)

Neubert, Holger; Kamusella, Alfred; Lienig, Jens

2011-03-01

Model based design optimization leads to robust solutions only if the statistical deviations of design, load and ambient parameters from nominal values are considered. We describe an optimization methodology that involves these deviations as stochastic variables for an exemplary electromagnetic actuator used to drive a Braille printer. A combined model simulates the dynamic behavior of the actuator and its non-linear load. It consists of a dynamic network model and a stationary magnetic finite element (FE) model. The network model utilizes lookup tables of the magnetic force and the flux linkage computed by the FE model. After a sensitivity analysis using design of experiment (DoE) methods and a nominal optimization based on gradient methods, a robust design optimization is performed. Selected design variables are involved in form of their density functions. In order to reduce the computational effort we use response surfaces instead of the combined system model obtained in all stochastic analysis steps. Thus, Monte-Carlo simulations can be applied. As a result we found an optimum system design meeting our requirements with regard to function and reliability.

High performance computing in biology: multimillion atom simulations of nanoscale systems

PubMed Central

Sanbonmatsu, K. Y.; Tung, C.-S.

2007-01-01

Computational methods have been used in biology for sequence analysis (bioinformatics), all-atom simulation (molecular dynamics and quantum calculations), and more recently for modeling biological networks (systems biology). Of these three techniques, all-atom simulation is currently the most computationally demanding, in terms of compute load, communication speed, and memory load. Breakthroughs in electrostatic force calculation and dynamic load balancing have enabled molecular dynamics simulations of large biomolecular complexes. Here, we report simulation results for the ribosome, using approximately 2.64 million atoms, the largest all-atom biomolecular simulation published to date. Several other nanoscale systems with different numbers of atoms were studied to measure the performance of the NAMD molecular dynamics simulation program on the Los Alamos National Laboratory Q Machine. We demonstrate that multimillion atom systems represent a 'sweet spot' for the NAMD code on large supercomputers. NAMD displays an unprecedented 85% parallel scaling efficiency for the ribosome system on 1024 CPUs. We also review recent targeted molecular dynamics simulations of the ribosome that prove useful for studying conformational changes of this large biomolecular complex in atomic detail. PMID:17187988

The default mode network and the working memory network are not anti-correlated during all phases of a working memory task.

PubMed

Piccoli, Tommaso; Valente, Giancarlo; Linden, David E J; Re, Marta; Esposito, Fabrizio; Sack, Alexander T; Di Salle, Francesco

2015-01-01

The default mode network and the working memory network are known to be anti-correlated during sustained cognitive processing, in a load-dependent manner. We hypothesized that functional connectivity among nodes of the two networks could be dynamically modulated by task phases across time. To address the dynamic links between default mode network and the working memory network, we used a delayed visuo-spatial working memory paradigm, which allowed us to separate three different phases of working memory (encoding, maintenance, and retrieval), and analyzed the functional connectivity during each phase within and between the default mode network and the working memory network networks. We found that the two networks are anti-correlated only during the maintenance phase of working memory, i.e. when attention is focused on a memorized stimulus in the absence of external input. Conversely, during the encoding and retrieval phases, when the external stimulation is present, the default mode network is positively coupled with the working memory network, suggesting the existence of a dynamically switching of functional connectivity between "task-positive" and "task-negative" brain networks. Our results demonstrate that the well-established dichotomy of the human brain (anti-correlated networks during rest and balanced activation-deactivation during cognition) has a more nuanced organization than previously thought and engages in different patterns of correlation and anti-correlation during specific sub-phases of a cognitive task. This nuanced organization reinforces the hypothesis of a direct involvement of the default mode network in cognitive functions, as represented by a dynamic rather than static interaction with specific task-positive networks, such as the working memory network.

The Default Mode Network and the Working Memory Network Are Not Anti-Correlated during All Phases of a Working Memory Task

PubMed Central

Piccoli, Tommaso; Valente, Giancarlo; Linden, David E. J.; Re, Marta; Esposito, Fabrizio; Sack, Alexander T.; Salle, Francesco Di

2015-01-01

Introduction The default mode network and the working memory network are known to be anti-correlated during sustained cognitive processing, in a load-dependent manner. We hypothesized that functional connectivity among nodes of the two networks could be dynamically modulated by task phases across time. Methods To address the dynamic links between default mode network and the working memory network, we used a delayed visuo-spatial working memory paradigm, which allowed us to separate three different phases of working memory (encoding, maintenance, and retrieval), and analyzed the functional connectivity during each phase within and between the default mode network and the working memory network networks. Results We found that the two networks are anti-correlated only during the maintenance phase of working memory, i.e. when attention is focused on a memorized stimulus in the absence of external input. Conversely, during the encoding and retrieval phases, when the external stimulation is present, the default mode network is positively coupled with the working memory network, suggesting the existence of a dynamically switching of functional connectivity between “task-positive” and “task-negative” brain networks. Conclusions Our results demonstrate that the well-established dichotomy of the human brain (anti-correlated networks during rest and balanced activation-deactivation during cognition) has a more nuanced organization than previously thought and engages in different patterns of correlation and anti-correlation during specific sub-phases of a cognitive task. This nuanced organization reinforces the hypothesis of a direct involvement of the default mode network in cognitive functions, as represented by a dynamic rather than static interaction with specific task-positive networks, such as the working memory network. PMID:25848951

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

PubMed

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.

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

NASA Technical Reports Server (NTRS)

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.

Solar Dynamic Power System Stability Analysis and Control

NASA Technical Reports Server (NTRS)

Momoh, James A.; Wang, Yanchun

1996-01-01

The objective of this research is to conduct dynamic analysis, control design, and control performance test of solar power system. Solar power system consists of generation system and distribution network system. A bench mark system is used in this research, which includes a generator with excitation system and governor, an ac/dc converter, six DDCU's and forty-eight loads. A detailed model is used for modeling generator. Excitation system is represented by a third order model. DDCU is represented by a seventh order system. The load is modeled by the combination of constant power and constant impedance. Eigen-analysis and eigen-sensitivity analysis are used for system dynamic analysis. The effects of excitation system, governor, ac/dc converter control, and the type of load on system stability are discussed. In order to improve system transient stability, nonlinear ac/dc converter control is introduced. The direct linearization method is used for control design. The dynamic analysis results show that these controls affect system stability in different ways. The parameter coordination of controllers are recommended based on the dynamic analysis. It is concluded from the present studies that system stability is improved by the coordination of control parameters and the nonlinear ac/dc converter control stabilize system oscillation caused by the load change and system fault efficiently.

Efficient, Decentralized Detection of Qualitative Spatial Events in a Dynamic Scalar Field

PubMed Central

Jeong, Myeong-Hun; Duckham, Matt

2015-01-01

This paper describes an efficient, decentralized algorithm to monitor qualitative spatial events in a dynamic scalar field. The events of interest involve changes to the critical points (i.e., peak, pits and passes) and edges of the surface network derived from the field. Four fundamental types of event (appearance, disappearance, movement and switch) are defined. Our algorithm is designed to rely purely on qualitative information about the neighborhoods of nodes in the sensor network and does not require information about nodes’ coordinate positions. Experimental investigations confirm that our algorithm is efficient, with O(n) overall communication complexity (where n is the number of nodes in the sensor network), an even load balance and low operational latency. The accuracy of event detection is comparable to established centralized algorithms for the identification of critical points of a surface network. Our algorithm is relevant to a broad range of environmental monitoring applications of sensor networks. PMID:26343672

Efficient, Decentralized Detection of Qualitative Spatial Events in a Dynamic Scalar Field.

PubMed

Jeong, Myeong-Hun; Duckham, Matt

2015-08-28

This paper describes an efficient, decentralized algorithm to monitor qualitative spatial events in a dynamic scalar field. The events of interest involve changes to the critical points (i.e., peak, pits and passes) and edges of the surface network derived from the field. Four fundamental types of event (appearance, disappearance, movement and switch) are defined. Our algorithm is designed to rely purely on qualitative information about the neighborhoods of nodes in the sensor network and does not require information about nodes' coordinate positions. Experimental investigations confirm that our algorithm is efficient, with O(n) overall communication complexity (where n is the number of nodes in the sensor network), an even load balance and low operational latency. The accuracy of event detection is comparable to established centralized algorithms for the identification of critical points of a surface network. Our algorithm is relevant to a broad range of environmental monitoring applications of sensor networks.

Community Microgrid Scheduling Considering Network Operational Constraints and Building Thermal Dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Guodong; Ollis, Thomas B.; Xiao, Bailu

Here, this paper proposes a Mixed Integer Conic Programming (MICP) model for community microgrids considering the network operational constraints and building thermal dynamics. The proposed optimization model optimizes not only the operating cost, including fuel cost, purchasing cost, battery degradation cost, voluntary load shedding cost and the cost associated with customer discomfort due to room temperature deviation from the set point, but also several performance indices, including voltage deviation, network power loss and power factor at the Point of Common Coupling (PCC). In particular, the detailed thermal dynamic model of buildings is integrated into the distribution optimal power flow (D-OPF)more » model for the optimal operation of community microgrids. The heating, ventilation and air-conditioning (HVAC) systems can be scheduled intelligently to reduce the electricity cost while maintaining the indoor temperature in the comfort range set by customers. Numerical simulation results show the effectiveness of the proposed model and significant saving in electricity cost could be achieved with network operational constraints satisfied.« less

Community Microgrid Scheduling Considering Network Operational Constraints and Building Thermal Dynamics

DOE PAGES

Liu, Guodong; Ollis, Thomas B.; Xiao, Bailu; ...

2017-10-10

Here, this paper proposes a Mixed Integer Conic Programming (MICP) model for community microgrids considering the network operational constraints and building thermal dynamics. The proposed optimization model optimizes not only the operating cost, including fuel cost, purchasing cost, battery degradation cost, voluntary load shedding cost and the cost associated with customer discomfort due to room temperature deviation from the set point, but also several performance indices, including voltage deviation, network power loss and power factor at the Point of Common Coupling (PCC). In particular, the detailed thermal dynamic model of buildings is integrated into the distribution optimal power flow (D-OPF)more » model for the optimal operation of community microgrids. The heating, ventilation and air-conditioning (HVAC) systems can be scheduled intelligently to reduce the electricity cost while maintaining the indoor temperature in the comfort range set by customers. Numerical simulation results show the effectiveness of the proposed model and significant saving in electricity cost could be achieved with network operational constraints satisfied.« less

Energy-efficient orthogonal frequency division multiplexing-based passive optical network based on adaptive sleep-mode control and dynamic bandwidth allocation

NASA Astrophysics Data System (ADS)

Zhang, Chongfu; Xiao, Nengwu; Chen, Chen; Yuan, Weicheng; Qiu, Kun

2016-02-01

We propose an energy-efficient orthogonal frequency division multiplexing-based passive optical network (OFDM-PON) using adaptive sleep-mode control and dynamic bandwidth allocation. In this scheme, a bidirectional-centralized algorithm named the receiver and transmitter accurate sleep control and dynamic bandwidth allocation (RTASC-DBA), which has an overall bandwidth scheduling policy, is employed to enhance the energy efficiency of the OFDM-PON. The RTASC-DBA algorithm is used in an optical line terminal (OLT) to control the sleep mode of an optical network unit (ONU) sleep and guarantee the quality of service of different services of the OFDM-PON. The obtained results show that, by using the proposed scheme, the average power consumption of the ONU is reduced by ˜40% when the normalized ONU load is less than 80%, compared with the average power consumption without using the proposed scheme.

Attention supports verbal short-term memory via competition between dorsal and ventral attention networks.

PubMed

Majerus, Steve; Attout, Lucie; D'Argembeau, Arnaud; Degueldre, Christian; Fias, Wim; Maquet, Pierre; Martinez Perez, Trecy; Stawarczyk, David; Salmon, Eric; Van der Linden, Martial; Phillips, Christophe; Balteau, Evelyne

2012-05-01

Interactions between the neural correlates of short-term memory (STM) and attention have been actively studied in the visual STM domain but much less in the verbal STM domain. Here we show that the same attention mechanisms that have been shown to shape the neural networks of visual STM also shape those of verbal STM. Based on previous research in visual STM, we contrasted the involvement of a dorsal attention network centered on the intraparietal sulcus supporting task-related attention and a ventral attention network centered on the temporoparietal junction supporting stimulus-related attention. We observed that, with increasing STM load, the dorsal attention network was activated while the ventral attention network was deactivated, especially during early maintenance. Importantly, activation in the ventral attention network increased in response to task-irrelevant stimuli briefly presented during the maintenance phase of the STM trials but only during low-load STM conditions, which were associated with the lowest levels of activity in the dorsal attention network during encoding and early maintenance. By demonstrating a trade-off between task-related and stimulus-related attention networks during verbal STM, this study highlights the dynamics of attentional processes involved in verbal STM.

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

NASA Astrophysics Data System (ADS)

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.

Power conditioning using dynamic voltage restorers under different voltage sag types.

PubMed

Saeed, Ahmed M; Abdel Aleem, Shady H E; Ibrahim, Ahmed M; Balci, Murat E; El-Zahab, Essam E A

2016-01-01

Voltage sags can be symmetrical or unsymmetrical depending on the causes of the sag. At the present time, one of the most common procedures for mitigating voltage sags is by the use of dynamic voltage restorers (DVRs). By definition, a DVR is a controlled voltage source inserted between the network and a sensitive load through a booster transformer injecting voltage into the network in order to correct any disturbance affecting a sensitive load voltage. In this paper, modelling of DVR for voltage correction using MatLab software is presented. The performance of the device under different voltage sag types is described, where the voltage sag types are introduced using the different types of short-circuit faults included in the environment of the MatLab/Simulink package. The robustness of the proposed device is evaluated using the common voltage sag indices, while taking into account voltage and current unbalance percentages, where maintaining the total harmonic distortion percentage of the load voltage within a specified range is desired. Finally, several simulation results are shown in order to highlight that the DVR is capable of effective correction of the voltage sag while minimizing the grid voltage unbalance and distortion, regardless of the fault type.

Power conditioning using dynamic voltage restorers under different voltage sag types

PubMed Central

Saeed, Ahmed M.; Abdel Aleem, Shady H.E.; Ibrahim, Ahmed M.; Balci, Murat E.; El-Zahab, Essam E.A.

2015-01-01

Voltage sags can be symmetrical or unsymmetrical depending on the causes of the sag. At the present time, one of the most common procedures for mitigating voltage sags is by the use of dynamic voltage restorers (DVRs). By definition, a DVR is a controlled voltage source inserted between the network and a sensitive load through a booster transformer injecting voltage into the network in order to correct any disturbance affecting a sensitive load voltage. In this paper, modelling of DVR for voltage correction using MatLab software is presented. The performance of the device under different voltage sag types is described, where the voltage sag types are introduced using the different types of short-circuit faults included in the environment of the MatLab/Simulink package. The robustness of the proposed device is evaluated using the common voltage sag indices, while taking into account voltage and current unbalance percentages, where maintaining the total harmonic distortion percentage of the load voltage within a specified range is desired. Finally, several simulation results are shown in order to highlight that the DVR is capable of effective correction of the voltage sag while minimizing the grid voltage unbalance and distortion, regardless of the fault type. PMID:26843975

An Effective Hybrid Routing Algorithm in WSN: Ant Colony Optimization in combination with Hop Count Minimization.

PubMed

Jiang, Ailian; Zheng, Lihong

2018-03-29

Low cost, high reliability and easy maintenance are key criteria in the design of routing protocols for wireless sensor networks (WSNs). This paper investigates the existing ant colony optimization (ACO)-based WSN routing algorithms and the minimum hop count WSN routing algorithms by reviewing their strengths and weaknesses. We also consider the critical factors of WSNs, such as energy constraint of sensor nodes, network load balancing and dynamic network topology. Then we propose a hybrid routing algorithm that integrates ACO and a minimum hop count scheme. The proposed algorithm is able to find the optimal routing path with minimal total energy consumption and balanced energy consumption on each node. The algorithm has unique superiority in terms of searching for the optimal path, balancing the network load and the network topology maintenance. The WSN model and the proposed algorithm have been implemented using C++. Extensive simulation experimental results have shown that our algorithm outperforms several other WSN routing algorithms on such aspects that include the rate of convergence, the success rate in searching for global optimal solution, and the network lifetime.

An Effective Hybrid Routing Algorithm in WSN: Ant Colony Optimization in combination with Hop Count Minimization

PubMed Central

2018-01-01

Low cost, high reliability and easy maintenance are key criteria in the design of routing protocols for wireless sensor networks (WSNs). This paper investigates the existing ant colony optimization (ACO)-based WSN routing algorithms and the minimum hop count WSN routing algorithms by reviewing their strengths and weaknesses. We also consider the critical factors of WSNs, such as energy constraint of sensor nodes, network load balancing and dynamic network topology. Then we propose a hybrid routing algorithm that integrates ACO and a minimum hop count scheme. The proposed algorithm is able to find the optimal routing path with minimal total energy consumption and balanced energy consumption on each node. The algorithm has unique superiority in terms of searching for the optimal path, balancing the network load and the network topology maintenance. The WSN model and the proposed algorithm have been implemented using C++. Extensive simulation experimental results have shown that our algorithm outperforms several other WSN routing algorithms on such aspects that include the rate of convergence, the success rate in searching for global optimal solution, and the network lifetime. PMID:29596336

Relative importance of multiple factors on terrestrial loading of DOC to Arctic river networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kicklighter, David W.; Hayes, Daniel J; Mcclelland, James W

2014-01-01

Terrestrial carbon dynamics influence the contribution of dissolved organic carbon (DOC) to river networks in addition to controlling carbon fluxes between the land surface and the atmosphere. 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 the pan-arctic watershed has contributed, on average, 32 Tg C/yr of DOC to the Arctic Ocean over the 20th century with most coming from the extensive area of boreal deciduous needle-leaved forests and forested wetlands in Eurasian watersheds. We also estimate that the rate ofmore » terrestrial DOC loading has been increasing by 0.037 Tg C/yr2 over the 20th century primarily as a result of increases in air temperatures and precipitation. These increases have been partially compensated 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 compensated and enhanced concurrent effects on hydrology to influence terrestrial DOC loading. Future increases in riverine DOC concentrations and export may occur from warming-induced increases in terrestrial DOC production associated with enhanced microbial metabolism and the exposure of additional organic matter from permafrost degradation along with decreases in water yield associated with warming-induced increases in evapotranspiration. Improvements in simulating terrestrial DOC loading to pan-arctic rivers in the future will require better information on 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.« less

Performance of a Dynamically Controlled Inverter in a Photovoltaic System Interconnected with a Secondary Network Distribution System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coddington, M. H.; Kroposki, B. D.; Basso, T.

In 2008, a 300 kW{sub peak} photovoltaic (PV) system was installed on the rooftop of the Colorado Convention Center (CCC). The installation was unique for the electric utility, Xcel Energy, as it had not previously permitted a PV system to be interconnected on a building served by the local secondary network distribution system (network). The PV system was installed with several provisions; one to prevent reverse power flow, another called a dynamically controlled inverter (DCI), that curtails the output of the PV inverters to maintain an amount of load supplied by Xcel Energy at the CCC. The DCI system utilizesmore » current transformers (CTs) to sense power flow to insure that a minimum threshold is maintained from Xcel Energy through the network transformers. The inverters are set to track the load on each of the three phases and curtail power from the PV system when the generated PV system current reaches 95% of the current on any phase. This is achieved by the DCI, which gathers inputs from current transformers measuring the current from the PV array, Xcel, and the spot network load. Preventing reverse power flow is a critical technical requirement for the spot network which serve this part of the CCC. The PV system was designed with the expectation that the DCI system would not curtail the PV system, as the expected minimum load consumption was historically higher than the designed PV system size. However, the DCI system has operated many days during the course of a year, and the performance has been excellent. The DCI system at the CCC was installed as a secondary measure to insure that a minimum level of power flows to the CCC from the Xcel Energy network. While this DCI system was intended for localized control, the system could also reduce output percent if an external smart grid control signal was employed. This paper specifically focuses on the performance of the innovative design at this installation; however, the DCI system could also be used for new s- art grid-enabled distribution systems where renewables power contributions at certain conditions or times may need to be curtailed.« less

Dynamic load balancing for petascale quantum Monte Carlo applications: The Alias method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sudheer, C. D.; Krishnan, S.; Srinivasan, A.

Diffusion Monte Carlo is the most accurate widely used Quantum Monte Carlo method for the electronic structure of materials, but it requires frequent load balancing or population redistribution steps to maintain efficiency and avoid accumulation of systematic errors on parallel machines. The load balancing step can be a significant factor affecting performance, and will become more important as the number of processing elements increases. We propose a new dynamic load balancing algorithm, the Alias Method, and evaluate it theoretically and empirically. An important feature of the new algorithm is that the load can be perfectly balanced with each process receivingmore » at most one message. It is also optimal in the maximum size of messages received by any process. We also optimize its implementation to reduce network contention, a process facilitated by the low messaging requirement of the algorithm. Empirical results on the petaflop Cray XT Jaguar supercomputer at ORNL showing up to 30% improvement in performance on 120,000 cores. The load balancing algorithm may be straightforwardly implemented in existing codes. The algorithm may also be employed by any method with many near identical computational tasks that requires load balancing.« less

Capacity allocation mechanism based on differentiated QoS in 60 GHz radio-over-fiber local access network

NASA Astrophysics Data System (ADS)

Kou, Yanbin; Liu, Siming; Zhang, Weiheng; Shen, Guansheng; Tian, Huiping

2017-03-01

We present a dynamic capacity allocation mechanism based on the Quality of Service (QoS) for different mobile users (MU) in 60 GHz radio-over-fiber (RoF) local access networks. The proposed mechanism is capable for collecting the request information of MUs to build a full list of MU capacity demands and service types at the Central Office (CO). A hybrid algorithm is introduced to implement the capacity allocation which can satisfy the requirements of different MUs at different network traffic loads. Compared with the weight dynamic frames assignment (WDFA) scheme, the Hybrid scheme can keep high priority MUs in low delay and maintain the packet loss rate less than 1% simultaneously. At the same time, low priority MUs have a relatively better performance.

Heuristic approaches for energy-efficient shared restoration in WDM networks

NASA Astrophysics Data System (ADS)

Alilou, Shahab

In recent years, there has been ongoing research on the design of energy-efficient Wavelength Division Multiplexing (WDM) networks. The explosive growth of Internet traffic has led to increased power consumption of network components. Network survivability has also been a relevant research topic, as it plays a crucial role in assuring continuity of service with no disruption, regardless of network component failure. Network survivability mechanisms tend to utilize considerable resources such as spare capacity in order to protect and restore information. This thesis investigates techniques for reducing energy demand and enhancing energy efficiency in the context of network survivability. We propose two novel heuristic energy-efficient shared protection approaches for WDM networks. These approaches intend to save energy by setting on sleep mode devices that are not being used while providing shared backup paths to satisfy network survivability. The first approach exploits properties of a math series in order to assign weight to the network links. It aims at reducing power consumption at the network indirectly by aggregating traffic on a set of nodes and links with high traffic load level. Routing traffic on links and nodes that are already under utilization makes it possible for the links and nodes with no load to be set on sleep mode. The second approach is intended to dynamically route traffic through nodes and links with high traffic load level. Similar to the first approach, this approach computes a pair of paths for every newly arrived demand. It computes these paths for every new demand by comparing the power consumption of nodes and links in the network before the demand arrives with their potential power consumption if they are chosen along the paths of this demand. Simulations of two different networks were used to compare the total network power consumption obtained using the proposed techniques against a standard shared-path restoration scheme. Shared-path restoration is a network survivability method in which a link-disjoint backup path and wavelength is reserved at the time of call setup for a working path. However, in order to reduce spare capacity consumption, this reserved backup path and wavelength may be shared with other backup paths. Pool Sharing Scheme (PSS) is employed to implement shared-path restoration scheme [1]. In an optical network, the failure of a single link leads to the failure of all the lightpaths that pass through that particular link. PSS ensures that the amount of backup bandwidth required on a link to restore the failed connections will not be more than the total amount of reserved backup bandwidth on that link. Simulation results indicate that the proposed approaches lead to up to 35% power savings in WDM networks when traffic load is low. However, power saving decreases to 14% at high traffic load level. Furthermore, in terms of the total capacity consumption for working paths, PSS outperforms the two proposed approaches, as expected. In terms of total capacity consumption all the approaches behave similarly. In general, at low traffic load level, the two proposed approaches behave similar to PSS in terms of average link load, and the ratio of block demands. Nevertheless, at high traffic load, the proposed approaches result in higher ratio of blocked demands than PSS. They also lead to higher average link load than PSS for the equal number of generated demands.

Living with a large reduction in permited loading by using a hydrograph-controlled release scheme

USGS Publications Warehouse

Conrads, P.A.; Martello, W.P.; Sullins, N.R.

2003-01-01

The Total Maximum Daily Load (TMDL) for ammonia and biochemical oxygen demand for the Pee Dee, Waccamaw, and Atlantic Intracoastal Waterway system near Myrtle Beach, South Carolina, mandated a 60-percent reduction in point-source loading. For waters with a naturally low background dissolved-oxygen concentrations, South Carolina anti-degradation rules in the water-quality regulations allows a permitted discharger a reduction of dissolved oxygen of 0.1 milligrams per liter (mg/L). This is known as the "0.1 rule." Permitted dischargers within this region of the State operate under the "0.1 rule" and cannot cause a cumulative impact greater than 0.1 mg/L on dissolved-oxygen concentrations. For municipal water-reclamation facilities to serve the rapidly growing resort and retirement community near Myrtle Beach, a variable loading scheme was developed to allow dischargers to utilize increased assimilative capacity during higher streamflow conditions while still meeting the requirements of a recently established TMDL. As part of the TMDL development, an extensive real-time data-collection network was established in the lower Waccamaw and Pee Dee River watershed where continuous measurements of streamflow, water level, dissolved oxygen, temperature, and specific conductance are collected. In addition, the dynamic BRANCH/BLTM models were calibrated and validated to simulate the water quality and tidal dynamics of the system. The assimilative capacities for various streamflows were also analyzed. The variable-loading scheme established total loadings for three streamflow levels. Model simulations show the results from the additional loading to be less than a 0.1 mg/L reduction in dissolved oxygen. As part of the loading scheme, the real-time network was redesigned to monitor streamflow entering the study area and water-quality conditions in the location of dissolved-oxygen "sags." The study reveals how one group of permit holders used a variable-loading scheme to implement restrictive permit limits without experiencing prohibitive capital expenditures or initiating a lengthy appeals process.

Energy efficient flexible hybrid wavelength division multiplexing-time division multiplexing passive optical network with pay as you grow deployment

NASA Astrophysics Data System (ADS)

Garg, Amit Kumar; Madavi, Amresh Ashok; Janyani, Vijay

2017-02-01

A flexible hybrid wavelength division multiplexing-time division multiplexing passive optical network architecture that allows dual rate signals to be sent at 1 and 10 Gbps to each optical networking unit depending upon the traffic load is proposed. The proposed design allows dynamic wavelength allocation with pay-as-you-grow deployment capability. This architecture is capable of providing up to 40 Gbps of equal data rates to all optical distribution networks (ODNs) and up to 70 Gbps of a asymmetrical data rate to the specific ODN. The proposed design handles broadcasting capability with simultaneous point-to-point transmission, which further reduces energy consumption. In this architecture, each module sends a wavelength to each ODN, thus making the architecture fully flexible; this flexibility allows network providers to use only required OLT components and switch off others. The design is also reliable to any module or TRx failure and provides services without any service disruption. Dynamic wavelength allocation and pay-as-you-grow deployment support network extensibility and bandwidth scalability to handle future generation access networks.

Secure and Cost-Effective Distributed Aggregation for Mobile Sensor Networks

PubMed Central

Guo, Kehua; Zhang, Ping; Ma, Jianhua

2016-01-01

Secure data aggregation (SDA) schemes are widely used in distributed applications, such as mobile sensor networks, to reduce communication cost, prolong the network life cycle and provide security. However, most SDA are only suited for a single type of statistics (i.e., summation-based or comparison-based statistics) and are not applicable to obtaining multiple statistic results. Most SDA are also inefficient for dynamic networks. This paper presents multi-functional secure data aggregation (MFSDA), in which the mapping step and coding step are introduced to provide value-preserving and order-preserving and, later, to enable arbitrary statistics support in the same query. MFSDA is suited for dynamic networks because these active nodes can be counted directly from aggregation data. The proposed scheme is tolerant to many types of attacks. The network load of the proposed scheme is balanced, and no significant bottleneck exists. The MFSDA includes two versions: MFSDA-I and MFSDA-II. The first one can obtain accurate results, while the second one is a more generalized version that can significantly reduce network traffic at the expense of less accuracy loss. PMID:27120599

A spectral profile multiplexed FBG sensor network with application to strain measurement in a Kevlar woven fabric

NASA Astrophysics Data System (ADS)

Guo, Guodong; Hackney, Drew; Pankow, Mark; Peters, Kara

2017-04-01

A spectral profile division multiplexed fiber Bragg grating (FBG) sensor network is described in this paper. The unique spectral profile of each sensor in the network is identified as a distinct feature to be interrogated. Spectrum overlap is allowed under working conditions. Thus, a specific wavelength window does not need to be allocated to each sensor as in a wavelength division multiplexed (WDM) network. When the sensors are serially connected in the network, the spectrum output is expressed through a truncated series. To track the wavelength shift of each sensor, the identification problem is transformed to a nonlinear optimization problem, which is then solved by a modified dynamic multi-swarm particle swarm optimizer (DMS-PSO). To demonstrate the application of the developed network, a network consisting of four FBGs was integrated into a Kevlar woven fabric, which was under a quasi-static load imposed by an impactor head. Due to the substantial radial strain in the fabric, the spectrums of different FBGs were found to overlap during the loading process. With the developed interrogating method, the overlapped spectrum would be distinguished thus the wavelength shift of each sensor can be monitored.

Neural Network for Positioning Space Station Solar Arrays

NASA Technical Reports Server (NTRS)

Graham, Ronald E.; Lin, Paul P.

1994-01-01

As a shuttle approaches the Space Station Freedom for a rendezvous, the shuttle's reaction control jet firings pose a risk of excessive plume impingement loads on Freedom solar arrays. The current solution to this problem, in which the arrays are locked in a feathered position prior to the approach, may be neither accurate nor robust, and is also expensive. An alternative solution is proposed here: the active control of Freedom's beta gimbals during the approach, positioning the arrays dynamically in such a way that they remain feathered relative to the shuttle jet most likely to cause an impingement load. An artificial neural network is proposed as a means of determining the gimbal angles that would drive plume angle of attack to zero. Such a network would be both accurate and robust, and could be less expensive to implement than the current solution. A network was trained via backpropagation, and results, which compare favorably to the current solution as well as to some other alternatives, are presented. Other training options are currently being evaluated.

Stochastic dynamics of small ensembles of non-processive molecular motors: The parallel cluster model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Erdmann, Thorsten; Albert, Philipp J.; Schwarz, Ulrich S.

2013-11-07

Non-processive molecular motors have to work together in ensembles in order to generate appreciable levels of force or movement. In skeletal muscle, for example, hundreds of myosin II molecules cooperate in thick filaments. In non-muscle cells, by contrast, small groups with few tens of non-muscle myosin II motors contribute to essential cellular processes such as transport, shape changes, or mechanosensing. Here we introduce a detailed and analytically tractable model for this important situation. Using a three-state crossbridge model for the myosin II motor cycle and exploiting the assumptions of fast power stroke kinetics and equal load sharing between motors inmore » equivalent states, we reduce the stochastic reaction network to a one-step master equation for the binding and unbinding dynamics (parallel cluster model) and derive the rules for ensemble movement. We find that for constant external load, ensemble dynamics is strongly shaped by the catch bond character of myosin II, which leads to an increase of the fraction of bound motors under load and thus to firm attachment even for small ensembles. This adaptation to load results in a concave force-velocity relation described by a Hill relation. For external load provided by a linear spring, myosin II ensembles dynamically adjust themselves towards an isometric state with constant average position and load. The dynamics of the ensembles is now determined mainly by the distribution of motors over the different kinds of bound states. For increasing stiffness of the external spring, there is a sharp transition beyond which myosin II can no longer perform the power stroke. Slow unbinding from the pre-power-stroke state protects the ensembles against detachment.« less

Accounting for heterogeneity of nutrient dynamics in riverscapes through spatially distributed models

NASA Astrophysics Data System (ADS)

Wollheim, W. M.; Stewart, R. J.

2011-12-01

Numerous types of heterogeneity exist within river systems, leading to hotspots of nutrient sources, sinks, and impacts embedded within an underlying gradient defined by river size. This heterogeneity influences the downstream propagation of anthropogenic impacts across flow conditions. We applied a river network model to explore how nitrogen saturation at river network scales is influenced by the abundance and distribution of potential nutrient processing hotspots (lakes, beaver ponds, tributary junctions, hyporheic zones) under different flow conditions. We determined that under low flow conditions, whole network nutrient removal is relatively insensitive to the number of hotspots because the underlying river network structure has sufficient nutrient processing capacity. However, hotspots become more important at higher flows and greatly influence the spatial distribution of removal within the network at all flows, suggesting that identification of heterogeneity is critical to develop predictive understanding of nutrient removal processes under changing loading and climate conditions. New temporally intensive data from in situ sensors can potentially help to better understand and constrain these dynamics.

The Distributed Diagonal Force Decomposition Method for Parallelizing Molecular Dynamics Simulations

PubMed Central

Boršnik, Urban; Miller, Benjamin T.; Brooks, Bernard R.; Janežič, Dušanka

2011-01-01

Parallelization is an effective way to reduce the computational time needed for molecular dynamics simulations. We describe a new parallelization method, the distributed-diagonal force decomposition method, with which we extend and improve the existing force decomposition methods. Our new method requires less data communication during molecular dynamics simulations than replicated data and current force decomposition methods, increasing the parallel efficiency. It also dynamically load-balances the processors' computational load throughout the simulation. The method is readily implemented in existing molecular dynamics codes and it has been incorporated into the CHARMM program, allowing its immediate use in conjunction with the many molecular dynamics simulation techniques that are already present in the program. We also present the design of the Force Decomposition Machine, a cluster of personal computers and networks that is tailored to running molecular dynamics simulations using the distributed diagonal force decomposition method. The design is expandable and provides various degrees of fault resilience. This approach is easily adaptable to computers with Graphics Processing Units because it is independent of the processor type being used. PMID:21793007

Embarked electrical network robust control based on singular perturbation model.

PubMed

Abdeljalil Belhaj, Lamya; Ait-Ahmed, Mourad; Benkhoris, Mohamed Fouad

2014-07-01

This paper deals with an approach of modelling in view of control for embarked networks which can be described as strongly coupled multi-sources, multi-loads systems with nonlinear and badly known characteristics. This model has to be representative of the system behaviour and easy to handle for easy regulators synthesis. As a first step, each alternator is modelled and linearized around an operating point and then it is subdivided into two lower order systems according to the singular perturbation theory. RST regulators are designed for each subsystem and tested by means of a software test-bench which allows predicting network behaviour in both steady and transient states. Finally, the designed controllers are implanted on an experimental benchmark constituted by two alternators supplying loads in order to test the dynamic performances in realistic conditions. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Characterization of SWNT based Polystyrene Nanocomposites

NASA Astrophysics Data System (ADS)

Mitchell, Cynthia; Bahr, Jeffrey; Tour, James; Arepalli, Sivaram; Krishnamoorti, Ramanan

2003-03-01

Polystyrene nanocomposites with functionalized single walled carbon nanotubes (SWNTs), prepared by the in-situ generation and addition of organic diazonium compounds, were characterized using a range of structural and dynamic methods. These were contrasted to the properties of polystyrene composites prepared with unfunctionalized SWNTs at the same loadings. The functionalized nanocomposites demonstrated a percolated SWNT network structure at concentrations of 1 vol SWNT based composites at similar loadings of SWNT exhibited behavior comparable to that of the unfilled polymer. This formation of the SWNT network structure is because of the improved compatibility between the SWNTs and the polymer matrix due to the functionalization. Further structural evidence for the compatibility of the modified SWNTs and the polymer matrix will be discussed in the presentation.

Data processing of high-rate low-voltage distribution grid recordings for smart grid monitoring and analysis

NASA Astrophysics Data System (ADS)

Maaß, Heiko; Cakmak, Hüseyin Kemal; Bach, Felix; Mikut, Ralf; Harrabi, Aymen; Süß, Wolfgang; Jakob, Wilfried; Stucky, Karl-Uwe; Kühnapfel, Uwe G.; Hagenmeyer, Veit

2015-12-01

Power networks will change from a rigid hierarchic architecture to dynamic interconnected smart grids. In traditional power grids, the frequency is the controlled quantity to maintain supply and load power balance. Thereby, high rotating mass inertia ensures for stability. In the future, system stability will have to rely more on real-time measurements and sophisticated control, especially when integrating fluctuating renewable power sources or high-load consumers like electrical vehicles to the low-voltage distribution grid.

Achieving Congestion Mitigation Using Distributed Power Control for Spectrum Sensor Nodes in Sensor Network-Aided Cognitive Radio Ad Hoc Networks

PubMed Central

Zhuo, Fan; Duan, Hucai

2017-01-01

The data sequence of spectrum sensing results injected from dedicated spectrum sensor nodes (SSNs) and the data traffic from upstream secondary users (SUs) lead to unpredictable data loads in a sensor network-aided cognitive radio ad hoc network (SN-CRN). As a result, network congestion may occur at a SU acting as fusion center when the offered data load exceeds its available capacity, which degrades network performance. In this paper, we present an effective approach to mitigate congestion of bottlenecked SUs via a proposed distributed power control framework for SSNs over a rectangular grid based SN-CRN, aiming to balance resource load and avoid excessive congestion. To achieve this goal, a distributed power control framework for SSNs from interior tier (IT) and middle tier (MT) is proposed to achieve the tradeoff between channel capacity and energy consumption. In particular, we firstly devise two pricing factors by considering stability of local spectrum sensing and spectrum sensing quality for SSNs. By the aid of pricing factors, the utility function of this power control problem is formulated by jointly taking into account the revenue of power reduction and the cost of energy consumption for IT or MT SSN. By bearing in mind the utility function maximization and linear differential equation constraint of energy consumption, we further formulate the power control problem as a differential game model under a cooperation or noncooperation scenario, and rigorously obtain the optimal solutions to this game model by employing dynamic programming. Then the congestion mitigation for bottlenecked SUs is derived by alleviating the buffer load over their internal buffers. Simulation results are presented to show the effectiveness of the proposed approach under the rectangular grid based SN-CRN scenario. PMID:28914803

An Efficient Framework Model for Optimizing Routing Performance in VANETs.

PubMed

Al-Kharasani, Nori M; Zulkarnain, Zuriati Ahmad; Subramaniam, Shamala; Hanapi, Zurina Mohd

2018-02-15

Routing in Vehicular Ad hoc Networks (VANET) is a bit complicated because of the nature of the high dynamic mobility. The efficiency of routing protocol is influenced by a number of factors such as network density, bandwidth constraints, traffic load, and mobility patterns resulting in frequency changes in network topology. Therefore, Quality of Service (QoS) is strongly needed to enhance the capability of the routing protocol and improve the overall network performance. In this paper, we introduce a statistical framework model to address the problem of optimizing routing configuration parameters in Vehicle-to-Vehicle (V2V) communication. Our framework solution is based on the utilization of the network resources to further reflect the current state of the network and to balance the trade-off between frequent changes in network topology and the QoS requirements. It consists of three stages: simulation network stage used to execute different urban scenarios, the function stage used as a competitive approach to aggregate the weighted cost of the factors in a single value, and optimization stage used to evaluate the communication cost and to obtain the optimal configuration based on the competitive cost. The simulation results show significant performance improvement in terms of the Packet Delivery Ratio (PDR), Normalized Routing Load (NRL), Packet loss (PL), and End-to-End Delay (E2ED).

Analysis of Online DBA Algorithm with Adaptive Sleep Cycle in WDM EPON

NASA Astrophysics Data System (ADS)

Pajčin, Bojan; Matavulj, Petar; Radivojević, Mirjana

2018-05-01

In order to manage Quality of Service (QoS) and energy efficiency in the optical access network, an online Dynamic Bandwidth Allocation (DBA) algorithm with adaptive sleep cycle is presented. This DBA algorithm has the ability to allocate an additional bandwidth to the end user within a single sleep cycle whose duration changes depending on the current buffers occupancy. The purpose of this DBA algorithm is to tune the duration of the sleep cycle depending on the network load in order to provide service to the end user without violating strict QoS requests in all network operating conditions.

Scandinavia studies of recent crustal movements and the space geodetic baseline network

NASA Technical Reports Server (NTRS)

Anderson, A. J.

1980-01-01

A brief review of crustal movements within the Fenno-Scandia shield is given. Results from postglacial studies, projects for measuring active fault regions, and dynamic ocean loading experiments are presented. The 1979 Scandinavian Doppler Campaign Network is discussed. This network includes Doppler translocation baseline determination of future very long baseline interferometry baselines to be measured in Scandinavia. Intercomparison of earlier Doppler translocation measurements with a high precision terrestrial geodetic baseline in Scandinavia has yielded internal agreement of 6 cm over 887 km. This is a precision of better than 1 part in to the 7th power.

Seismic response of rock slopes: Numerical investigations on the role of internal structure

NASA Astrophysics Data System (ADS)

Arnold, L.; Applegate, K.; Gibson, M.; Wartman, J.; Adams, S.; Maclaughlin, M.; Smith, S.; Keefer, D. K.

2013-12-01

The stability of rock slopes is significantly influenced and often controlled by the internal structure of the slope created by such discontinuities as joints, shear zones, and faults. Under seismic conditions, these discontinuities influence both the resistance of a slope to failure and its response to dynamic loading. The dynamic response, which can be characterized by the slope's natural frequency and amplification of ground motion, governs the loading experienced by the slope in a seismic event and, therefore, influences the slope's stability. In support of the Network for Earthquake Engineering Simulation (NEES) project Seismically-Induced Rock Slope Failure: Mechanisms and Prediction (NEESROCK), we conducted a 2D numerical investigation using the discrete element method (DEM) coupled with simple discrete fracture networks (DFNs). The intact rock mass is simulated with a bonded assembly of discrete particles, commonly referred to as the bonded-particle model (BPM) for rock. Discontinuities in the BPM are formed by the insertion of smooth, unbonded contacts along specified planes. The influence of discontinuity spacing, orientation, and stiffness on slope natural frequency and amplification was investigated with the commercially available Particle Flow Code (PFC2D). Numerical results indicate that increased discontinuity spacing has a non-linear effect in decreasing the amplification and increasing the natural frequency of the slope. As discontinuity dip changes from sub-horizontal to sub-vertical, the slope's level of amplification increases while the natural frequency of the slope decreases. Increased joint stiffness decreases amplification and increases natural frequency. The results reveal that internal structure has a strong influence on rock slope dynamics that can significantly change the system's dynamic response and stability during seismic loading. Financial support for this research was provided by the United States National Science Foundation (NSF) under grant CMMI-1156413.

Load estimation from photoelastic fringe patterns under combined normal and shear forces

NASA Astrophysics Data System (ADS)

Dubey, V. N.; Grewal, G. S.

2009-08-01

Recently there has been some spurt of interests to use photoelastic materials for sensing applications. This has been successfully applied for designing a number of signal-based sensors, however, there have been limited efforts to design image-based sensors on photoelasticity which can have wider applications in term of actual loading and visualisation. The main difficulty in achieving this is the infinite loading conditions that may generate same image on the material surface. This, however, can be useful for known loading situations as this can provide dynamic and actual conditions of loading in real time. This is particularly useful for separating components of forces in and out of the loading plane. One such application is the separation of normal and shear forces acting on the plantar surface of foot of diabetic patients for predicting ulceration. In our earlier work we have used neural networks to extract normal force information from the fringe patterns using image intensity. This paper considers geometric and various other statistical parameters in addition to the image intensity to extract normal as well as shear force information from the fringe pattern in a controlled experimental environment. The results of neural network output with the above parameters and their combinations are compared and discussed. The aim is to generalise the technique for a range of loading conditions that can be exploited for whole-field load visualisation and sensing applications in biomedical field.

Elan4/SPARC V9 Cross Loader and Dynamic Linker

DOE Office of Scientific and Technical Information (OSTI.GOV)

anf Fabien Lebaillif-Delamare, Fabrizio Petrini

2004-10-25

The Elan4/Sparc V9 Croos Loader and Liner is a part of the Linux system software that allows the dynamic loading and linking of user code in the network interface Quadrics QsNETII, also called as Elan4 Quadrics. Elan44 uses a thread processor that is based on the assembly instruction set of the Sparc V9. All this software is integrated as a Linux kernel module in the Linux 2.6.5 release.

Structure and Transport Anomalies in Soft Colloids

NASA Astrophysics Data System (ADS)

Srivastava, Samanvaya; Archer, Lynden A.; Narayanan, Suresh

2013-04-01

Anomalous trends in nanoparticle correlation and motion are reported in soft nanoparticle suspensions using static and dynamic x-ray scattering measurements. Contrary to normal expectations, we find that particle-particle correlations decrease and particle dynamics become faster as volume fraction rises above a critical particle loading associated with overlap. Our observations bear many similarities to the cascade of structural and transport anomalies reported for complex, network forming molecular fluids such as water, and are argued to share similar physical origins.

Distributed plug-and-play optimal generator and load control for power system frequency regulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

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

A distributed control scheme, which can be implemented on generators and controllable loads in a plug-and-play manner, is proposed for power system frequency regulation. The proposed scheme is based on local measurements, local computation, and neighborhood information exchanges over a communication network with an arbitrary (but connected) topology. In the event of a sudden change in generation or load, the proposed scheme can restore the nominal frequency and the reference inter-area power flows, while minimizing the total cost of control for participating generators and loads. Power network stability under the proposed control is proved with a relatively realistic model whichmore » includes nonlinear power flow and a generic (potentially nonlinear or high-order) turbine-governor model, and further with first- and second-order turbine-governor models as special cases. Finally, in simulations, the proposed control scheme shows a comparable performance to the existing automatic generation control (AGC) when implemented only on the generator side, and demonstrates better dynamic characteristics than AGC when each scheme is implemented on both generators and controllable loads. Simulation results also show robustness of the proposed scheme to communication link failure.« less

Distributed plug-and-play optimal generator and load control for power system frequency regulation

DOE PAGES

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

2018-03-14

A distributed control scheme, which can be implemented on generators and controllable loads in a plug-and-play manner, is proposed for power system frequency regulation. The proposed scheme is based on local measurements, local computation, and neighborhood information exchanges over a communication network with an arbitrary (but connected) topology. In the event of a sudden change in generation or load, the proposed scheme can restore the nominal frequency and the reference inter-area power flows, while minimizing the total cost of control for participating generators and loads. Power network stability under the proposed control is proved with a relatively realistic model whichmore » includes nonlinear power flow and a generic (potentially nonlinear or high-order) turbine-governor model, and further with first- and second-order turbine-governor models as special cases. Finally, in simulations, the proposed control scheme shows a comparable performance to the existing automatic generation control (AGC) when implemented only on the generator side, and demonstrates better dynamic characteristics than AGC when each scheme is implemented on both generators and controllable loads. Simulation results also show robustness of the proposed scheme to communication link failure.« less

Artificial neural network and SARIMA based models for power load forecasting in Turkish electricity market

PubMed Central

2017-01-01

Load information plays an important role in deregulated electricity markets, since it is the primary factor to make critical decisions on production planning, day-to-day operations, unit commitment and economic dispatch. Being able to predict the load for a short term, which covers one hour to a few days, equips power generation facilities and traders with an advantage. With the deregulation of electricity markets, a variety of short term load forecasting models are developed. Deregulation in Turkish Electricity Market has started in 2001 and liberalization is still in progress with rules being effective in its predefined schedule. However, there is a very limited number of studies for Turkish Market. In this study, we introduce two different models for current Turkish Market using Seasonal Autoregressive Integrated Moving Average (SARIMA) and Artificial Neural Network (ANN) and present their comparative performances. Building models that cope with the dynamic nature of deregulated market and are able to run in real-time is the main contribution of this study. We also use our ANN based model to evaluate the effect of several factors, which are claimed to have effect on electrical load. PMID:28426739

Artificial neural network and SARIMA based models for power load forecasting in Turkish electricity market.

PubMed

Bozkurt, Ömer Özgür; Biricik, Göksel; Tayşi, Ziya Cihan

2017-01-01

Load information plays an important role in deregulated electricity markets, since it is the primary factor to make critical decisions on production planning, day-to-day operations, unit commitment and economic dispatch. Being able to predict the load for a short term, which covers one hour to a few days, equips power generation facilities and traders with an advantage. With the deregulation of electricity markets, a variety of short term load forecasting models are developed. Deregulation in Turkish Electricity Market has started in 2001 and liberalization is still in progress with rules being effective in its predefined schedule. However, there is a very limited number of studies for Turkish Market. In this study, we introduce two different models for current Turkish Market using Seasonal Autoregressive Integrated Moving Average (SARIMA) and Artificial Neural Network (ANN) and present their comparative performances. Building models that cope with the dynamic nature of deregulated market and are able to run in real-time is the main contribution of this study. We also use our ANN based model to evaluate the effect of several factors, which are claimed to have effect on electrical load.

Many Body Effects on Particle Diffusion in Polymer Nanocomposites

NASA Astrophysics Data System (ADS)

Dell, Zachary E.; Schweizer, Kenneth S.

2014-03-01

Recent statistical mechanical theories of nanoparticle motion in polymer melts and networks have focused on the dilute particle limit. By combining PRISM theory predictions for microscopic structural correlations, and a new formulation of self-consistent dynamical mode coupling theory, we extend dilute theories to finite filler loading. As a minimalist model, the polymer dynamics are first assumed to be unperturbed by the presence of the nanoparticles. The long time particle diffusivity in unentangled and entangled melts is determined as a function of polymer tube diameter and radius of gyration, nanoparticle diameter, and polymer-filler attraction strength under both constant volume and constant pressure situations. The influence of nanocomposite statistical structure (depletion, steric stabilization, bridging) on dynamics is also investigated. Using recent theoretical developments for predicting tube diameters in nanocomposites, the consequences of filler-induced tube dilation on nanoparticle motion is established. In entangled melts, increasing filler loading first modestly speeds up diffusion, and then dramatically when the inter-filler separation becomes smaller than the tube diameter. At very high loadings, a filler glass transition is generically predicted.

Working memory load modulation of parieto-frontal connections: evidence from dynamic causal modeling

PubMed Central

Ma, Liangsuo; Steinberg, Joel L.; Hasan, Khader M.; Narayana, Ponnada A.; Kramer, Larry A.; Moeller, F. Gerard

2011-01-01

Previous neuroimaging studies have shown that working memory load has marked effects on regional neural activation. However, the mechanism through which working memory load modulates brain connectivity is still unclear. In this study, this issue was addressed using dynamic causal modeling (DCM) based on functional magnetic resonance imaging (fMRI) data. Eighteen normal healthy subjects were scanned while they performed a working memory task with variable memory load, as parameterized by two levels of memory delay and three levels of digit load (number of digits presented in each visual stimulus). Eight regions of interest, i.e., bilateral middle frontal gyrus (MFG), anterior cingulate cortex (ACC), inferior frontal cortex (IFC), and posterior parietal cortex (PPC), were chosen for DCM analyses. Analysis of the behavioral data during the fMRI scan revealed that accuracy decreased as digit load increased. Bayesian inference on model structure indicated that a bilinear DCM in which memory delay was the driving input to bilateral PPC and in which digit load modulated several parieto-frontal connections was the optimal model. Analysis of model parameters showed that higher digit load enhanced connection from L PPC to L IFC, and lower digit load inhibited connection from R PPC to L ACC. These findings suggest that working memory load modulates brain connectivity in a parieto-frontal network, and may reflect altered neuronal processes, e.g., information processing or error monitoring, with the change in working memory load. PMID:21692148

Neural joint control for Space Shuttle Remote Manipulator System

NASA Technical Reports Server (NTRS)

Atkins, Mark A.; Cox, Chadwick J.; Lothers, Michael D.; Pap, Robert M.; Thomas, Charles R.

1992-01-01

Neural networks are being used to control a robot arm in a telerobotic operation. The concept uses neural networks for both joint and inverse kinematics in a robotic control application. An upper level neural network is trained to learn inverse kinematic mappings. The output, a trajectory, is then fed to the Decentralized Adaptive Joint Controllers. This neural network implementation has shown that the controlled arm recovers from unexpected payload changes while following the reference trajectory. The neural network-based decentralized joint controller is faster, more robust and efficient than conventional approaches. Implementations of this architecture are discussed that would relax assumptions about dynamics, obstacles, and heavy loads. This system is being developed to use with the Space Shuttle Remote Manipulator System.

Estimation of the full-field dynamic response of a floating bridge using Kalman-type filtering algorithms

NASA Astrophysics Data System (ADS)

Petersen, Ø. W.; Øiseth, O.; Nord, T. S.; Lourens, E.

2018-07-01

Numerical predictions of the dynamic response of complex structures are often uncertain due to uncertainties inherited from the assumed load effects. Inverse methods can estimate the true dynamic response of a structure through system inversion, combining measured acceleration data with a system model. This article presents a case study of full-field dynamic response estimation of a long-span floating bridge: the Bergøysund Bridge in Norway. This bridge is instrumented with a network of 14 triaxial accelerometers. The system model consists of 27 vibration modes with natural frequencies below 2 Hz, obtained from a tuned finite element model that takes the fluid-structure interaction with the surrounding water into account. Two methods, a joint input-state estimation algorithm and a dual Kalman filter, are applied to estimate the full-field response of the bridge. The results demonstrate that the displacements and the accelerations can be estimated at unmeasured locations with reasonable accuracy when the wave loads are the dominant source of excitation.

Multi-PON access network using a coarse AWG for smooth migration from TDM to WDM PON

NASA Astrophysics Data System (ADS)

Shachaf, Y.; Chang, C.-H.; Kourtessis, P.; Senior, J. M.

2007-06-01

An interoperable access network architecture based on a coarse array waveguide grating (AWG) is described, displaying dynamic wavelength assignment to manage the network load across multiple PONs. The multi-PON architecture utilizes coarse Gaussian channels of an AWG to facilitate scalability and smooth migration path between TDM and WDM PONs. Network simulations of a cross-operational protocol platform confirmed successful routing of individual PON clusters through 7 nm-wide passband windows of the AWG. Furthermore, polarization-dependent wavelength shift and phase errors of the device proved not to impose restrain on the routing performance. Optical transmission tests at 2.5 Gbit/s for distances up to 20 km are demonstrated.

A comparison of two types of neural network for weld quality prediction in small scale resistance spot welding

NASA Astrophysics Data System (ADS)

Wan, Xiaodong; Wang, Yuanxun; Zhao, Dawei; Huang, YongAn

2017-09-01

Our study aims at developing an effective quality monitoring system in small scale resistance spot welding of titanium alloy. The measured electrical signals were interpreted in combination with the nugget development. Features were extracted from the dynamic resistance and electrode voltage curve. A higher welding current generally indicated a lower overall dynamic resistance level. A larger electrode voltage peak and higher change rate of electrode voltage could be detected under a smaller electrode force or higher welding current condition. Variation of the extracted features and weld quality was found more sensitive to the change of welding current than electrode force. Different neural network model were proposed for weld quality prediction. The back propagation neural network was more proper in failure load estimation. The probabilistic neural network model was more appropriate to be applied in quality level classification. A real-time and on-line weld quality monitoring system may be developed by taking advantages of both methods.

Stability analysis of spacecraft power systems

NASA Technical Reports Server (NTRS)

Halpin, S. M.; Grigsby, L. L.; Sheble, G. B.; Nelms, R. M.

1990-01-01

The problems in applying standard electric utility models, analyses, and algorithms to the study of the stability of spacecraft power conditioning and distribution systems are discussed. Both single-phase and three-phase systems are considered. Of particular concern are the load and generator models that are used in terrestrial power system studies, as well as the standard assumptions of load and topological balance that lead to the use of the positive sequence network. The standard assumptions regarding relative speeds of subsystem dynamic responses that are made in the classical transient stability algorithm, which forms the backbone of utility-based studies, are examined. The applicability of these assumptions to a spacecraft power system stability study is discussed in detail. In addition to the classical indirect method, the applicability of Liapunov's direct methods to the stability determination of spacecraft power systems is discussed. It is pointed out that while the proposed method uses a solution process similar to the classical algorithm, the models used for the sources, loads, and networks are, in general, more accurate. Some preliminary results are given for a linear-graph, state-variable-based modeling approach to the study of the stability of space-based power distribution networks.

Towards Smart Grid Dynamic Ratings

NASA Astrophysics Data System (ADS)

Cheema, Jamal; Clark, Adrian; Kilimnik, Justin; Pavlovski, Chris; Redman, David; Vu, Maria

2011-08-01

The energy distribution industry is giving greater attention to smart grid solutions as a means for increasing the capabilities, efficiency and reliability of the electrical power network. The smart grid makes use of intelligent monitoring and control devices throughout the distribution network to report on electrical properties such as voltage, current and power, as well as raising network alarms and events. A further aspect of the smart grid embodies the dynamic rating of electrical assets of the network. This fundamentally involves a rating of the load current capacity of electrical assets including feeders, transformers and switches. The mainstream approach to rate assets is to apply the vendor plate rating, which often under utilizes assets, or in some cases over utilizes when environmental conditions reduce the effective rated capacity, potentially reducing lifetime. Using active intelligence we have developed a rating system that rates assets in real time based upon several events. This allows for a far more efficient and reliable electrical grid that is able to extend further the life and reliability of the electrical network. In this paper we describe our architecture, the observations made during development and live deployment of the solution into operation. We also illustrate how this solution blends with the smart grid by proposing a dynamic rating system for the smart grid.

Dynamic modeling of nitrogen losses in river networks unravels the coupled effects of hydrological and biogeochemical processes

USGS Publications Warehouse

Alexander, Richard B.; Böhlke, John Karl; Boyer, Elizabeth W.; David, Mark B.; Harvey, Judson W.; Mulholland, Patrick J.; Seitzinger, Sybil P.; Tobias, Craig R.; Tonitto, Christina; Wollheim, Wilfred M.

2009-01-01

The importance of lotic systems as sinks for nitrogen inputs is well recognized. A fraction of nitrogen in streamflow is removed to the atmosphere via denitrification with the remainder exported in streamflow as nitrogen loads. At the watershed scale, there is a keen interest in understanding the factors that control the fate of nitrogen throughout the stream channel network, with particular attention to the processes that deliver large nitrogen loads to sensitive coastal ecosystems. We use a dynamic stream transport model to assess biogeochemical (nitrate loadings, concentration, temperature) and hydrological (discharge, depth, velocity) effects on reach-scale denitrification and nitrate removal in the river networks of two watersheds having widely differing levels of nitrate enrichment but nearly identical discharges. Stream denitrification is estimated by regression as a nonlinear function of nitrate concentration, streamflow, and temperature, using more than 300 published measurements from a variety of US streams. These relations are used in the stream transport model to characterize nitrate dynamics related to denitrification at a monthly time scale in the stream reaches of the two watersheds. Results indicate that the nitrate removal efficiency of streams, as measured by the percentage of the stream nitrate flux removed via denitrification per unit length of channel, is appreciably reduced during months with high discharge and nitrate flux and increases during months of low-discharge and flux. Biogeochemical factors, including land use, nitrate inputs, and stream concentrations, are a major control on reach-scale denitrification, evidenced by the disproportionately lower nitrate removal efficiency in streams of the highly nitrate-enriched watershed as compared with that in similarly sized streams in the less nitrate-enriched watershed. Sensitivity analyses reveal that these important biogeochemical factors and physical hydrological factors contribute nearly equally to seasonal and stream-size related variations in the percentage of the stream nitrate flux removed in each watershed.

A neural network approach for determining gait modifications to reduce the contact force in knee joint implant.

PubMed

Ardestani, Marzieh Mostafavizadeh; Chen, Zhenxian; Wang, Ling; Lian, Qin; Liu, Yaxiong; He, Jiankang; Li, Dichen; Jin, Zhongmin

2014-10-01

There is a growing interest in non-surgical gait rehabilitation treatments to reduce the loading in the knee joint. In particular, synergetic kinematic changes required for joint offloading should be determined individually for each subject. Previous studies for gait rehabilitation designs are typically relied on a "trial-and-error" approach, using multi-body dynamic (MBD) analysis. However MBD is fairly time demanding which prevents it to be used iteratively for each subject. This study employed an artificial neural network to develop a cost-effective computational framework for designing gait rehabilitation patterns. A feed forward artificial neural network (FFANN) was trained based on a number of experimental gait trials obtained from literature. The trained network was then hired to calculate the appropriate kinematic waveforms (output) needed to achieve desired knee joint loading patterns (input). An auxiliary neural network was also developed to update the ground reaction force and moment profiles with respect to the predicted kinematic waveforms. The feasibility and efficiency of the predicted kinematic patterns were then evaluated through MBD analysis. Results showed that FFANN-based predicted kinematics could effectively decrease the total knee joint reaction forces. Peak values of the resultant knee joint forces, with respect to the bodyweight (BW), were reduced by 20% BW and 25% BW in the midstance and the terminal stance phases. Impulse values of the knee joint loading patterns were also decreased by 17% BW*s and 24%BW*s in the corresponding phases. The FFANN-based framework suggested a cost-effective forward solution which directly calculated the kinematic variations needed to implement a given desired knee joint loading pattern. It is therefore expected that this approach provides potential advantages and further insights into knee rehabilitation designs. Copyright © 2014 IPEM. Published by Elsevier Ltd. All rights reserved.

Neural network-based adaptive dynamic surface control for permanent magnet synchronous motors.

PubMed

Yu, Jinpeng; Shi, Peng; Dong, Wenjie; Chen, Bing; Lin, Chong

2015-03-01

This brief considers the problem of neural networks (NNs)-based adaptive dynamic surface control (DSC) for permanent magnet synchronous motors (PMSMs) with parameter uncertainties and load torque disturbance. First, NNs are used to approximate the unknown and nonlinear functions of PMSM drive system and a novel adaptive DSC is constructed to avoid the explosion of complexity in the backstepping design. Next, under the proposed adaptive neural DSC, the number of adaptive parameters required is reduced to only one, and the designed neural controllers structure is much simpler than some existing results in literature, which can guarantee that the tracking error converges to a small neighborhood of the origin. Then, simulations are given to illustrate the effectiveness and potential of the new design technique.

Molecular dynamics study on the evolution of interfacial dislocation network and mechanical properties of Ni-based single crystal superalloys

NASA Astrophysics Data System (ADS)

Li, Nan-Lin; Wu, Wen-Ping; Nie, Kai

2018-05-01

The evolution of misfit dislocation network at γ /γ‧ phase interface and tensile mechanical properties of Ni-based single crystal superalloys at various temperatures and strain rates are studied by using molecular dynamics (MD) simulations. From the simulations, it is found that with the increase of loading, the dislocation network effectively inhibits dislocations emitted in the γ matrix cutting into the γ‧ phase and absorbs the matrix dislocations to strengthen itself which increases the stability of structure. Under the influence of the temperature, the initial mosaic structure of dislocation network gradually becomes irregular, and the initial misfit stress and the elastic modulus slowly decline as temperature increasing. On the other hand, with the increase of the strain rate, it almost has no effect on the elastic modulus and the way of evolution of dislocation network, but contributes to the increases of the yield stress and tensile strength. Moreover, tension-compression asymmetry of Ni-based single crystal superalloys is also presented based on MD simulations.

Coupled dynamics analysis of wind energy systems

NASA Technical Reports Server (NTRS)

Hoffman, J. A.

1977-01-01

A qualitative description of all key elements of a complete wind energy system computer analysis code is presented. The analysis system addresses the coupled dynamics characteristics of wind energy systems, including the interactions of the rotor, tower, nacelle, power train, control system, and electrical network. The coupled dynamics are analyzed in both the frequency and time domain to provide the basic motions and loads data required for design, performance verification and operations analysis activities. Elements of the coupled analysis code were used to design and analyze candidate rotor articulation concepts. Fundamental results and conclusions derived from these studies are presented.

Non-dimensional physics of pulsatile cardiovascular networks and energy efficiency.

PubMed

Yigit, Berk; Pekkan, Kerem

2016-01-01

In Nature, there exist a variety of cardiovascular circulation networks in which the energetic ventricular load has both steady and pulsatile components. Steady load is related to the mean cardiac output (CO) and the haemodynamic resistance of the peripheral vascular system. On the other hand, the pulsatile load is determined by the simultaneous pressure and flow waveforms at the ventricular outlet, which in turn are governed through arterial wave dynamics (transmission) and pulse decay characteristics (windkessel effect). Both the steady and pulsatile contributions of the haemodynamic power load are critical for characterizing/comparing disease states and for predicting the performance of cardiovascular devices. However, haemodynamic performance parameters vary significantly from subject to subject because of body size, heart rate and subject-specific CO. Therefore, a 'normalized' energy dissipation index, as a function of the 'non-dimensional' physical parameters that govern the circulation networks, is needed for comparative/integrative biological studies and clinical decision-making. In this paper, a complete network-independent non-dimensional formulation that incorporates pulsatile flow regimes is developed. Mechanical design variables of cardiovascular flow systems are identified and the Buckingham Pi theorem is formally applied to obtain the corresponding non-dimensional scaling parameter sets. Two scaling approaches are considered to address both the lumped parameter networks and the distributed circulation components. The validity of these non-dimensional number sets is tested extensively through the existing empirical allometric scaling laws of circulation systems. Additional validation studies are performed using a parametric numerical arterial model that represents the transmission and windkessel characteristics, which are adjusted to represent different body sizes and non-dimensional haemodynamic states. Simulations demonstrate that the proposed non-dimensional indices are independent of body size for healthy conditions, but are sensitive to deviations caused by off-design disease states that alter the energetic load. Sensitivity simulations are used to identify the relationship between pulsatile power loss and non-dimensional characteristics, and optimal operational states are computed. © 2016 The Author(s).

Based on records of Three Gorge Telemetric Seismic Network to analyze Vibration process of micro fracture of rock landslide

NASA Astrophysics Data System (ADS)

WANG, Q.

2017-12-01

Used the finite element analysis software GeoStudio to establish vibration analysis model of Qianjiangping landslide, which locates at the Three Gorges Reservoir area. In QUAKE/W module, we chosen proper Dynamic elasticity modulus and Poisson's ratio of soil layer and rock stratum. When loading, we selected the waveform data record of Three Gorge Telemetric Seismic Network as input ground motion, which includes five rupture events recorded of Lujiashan seismic station. In dynamic simulating, we mainly focused on sliding process when the earthquake date record was applied. The simulation result shows that Qianjiangping landslide wasn't not only affected by its own static force, but also experienced the dynamic process of micro fracture-creep-slip rupture-creep-slip.it provides a new approach for the early warning feasibility of rock landslide in future research.

An Efficient Framework Model for Optimizing Routing Performance in VANETs

PubMed Central

Zulkarnain, Zuriati Ahmad; Subramaniam, Shamala

2018-01-01

Routing in Vehicular Ad hoc Networks (VANET) is a bit complicated because of the nature of the high dynamic mobility. The efficiency of routing protocol is influenced by a number of factors such as network density, bandwidth constraints, traffic load, and mobility patterns resulting in frequency changes in network topology. Therefore, Quality of Service (QoS) is strongly needed to enhance the capability of the routing protocol and improve the overall network performance. In this paper, we introduce a statistical framework model to address the problem of optimizing routing configuration parameters in Vehicle-to-Vehicle (V2V) communication. Our framework solution is based on the utilization of the network resources to further reflect the current state of the network and to balance the trade-off between frequent changes in network topology and the QoS requirements. It consists of three stages: simulation network stage used to execute different urban scenarios, the function stage used as a competitive approach to aggregate the weighted cost of the factors in a single value, and optimization stage used to evaluate the communication cost and to obtain the optimal configuration based on the competitive cost. The simulation results show significant performance improvement in terms of the Packet Delivery Ratio (PDR), Normalized Routing Load (NRL), Packet loss (PL), and End-to-End Delay (E2ED). PMID:29462884

Indirect adaptive fuzzy wavelet neural network with self- recurrent consequent part for AC servo system.

PubMed

Hou, Runmin; Wang, Li; Gao, Qiang; Hou, Yuanglong; Wang, Chao

2017-09-01

This paper proposes a novel indirect adaptive fuzzy wavelet neural network (IAFWNN) to control the nonlinearity, wide variations in loads, time-variation and uncertain disturbance of the ac servo system. In the proposed approach, the self-recurrent wavelet neural network (SRWNN) is employed to construct an adaptive self-recurrent consequent part for each fuzzy rule of TSK fuzzy model. For the IAFWNN controller, the online learning algorithm is based on back propagation (BP) algorithm. Moreover, an improved particle swarm optimization (IPSO) is used to adapt the learning rate. The aid of an adaptive SRWNN identifier offers the real-time gradient information to the adaptive fuzzy wavelet neural controller to overcome the impact of parameter variations, load disturbances and other uncertainties effectively, and has a good dynamic. The asymptotical stability of the system is guaranteed by using the Lyapunov method. The result of the simulation and the prototype test prove that the proposed are effective and suitable. Copyright © 2017. Published by Elsevier Ltd.

Angular default mode network connectivity across working memory load.

PubMed

Vatansever, D; Manktelow, A E; Sahakian, B J; Menon, D K; Stamatakis, E A

2017-01-01

Initially identified during no-task, baseline conditions, it has now been suggested that the default mode network (DMN) engages during a variety of working memory paradigms through its flexible interactions with other large-scale brain networks. Nevertheless, its contribution to whole-brain connectivity dynamics across increasing working memory load has not been explicitly assessed. The aim of our study was to determine which DMN hubs relate to working memory task performance during an fMRI-based n-back paradigm with parametric increases in difficulty. Using a voxel-wise metric, termed the intrinsic connectivity contrast (ICC), we found that the bilateral angular gyri (core DMN hubs) displayed the greatest change in global connectivity across three levels of n-back task load. Subsequent seed-based functional connectivity analysis revealed that the angular DMN regions robustly interact with other large-scale brain networks, suggesting a potential involvement in the global integration of information. Further support for this hypothesis comes from the significant correlations we found between angular gyri connectivity and reaction times to correct responses. The implication from our study is that the DMN is actively involved during the n-back task and thus plays an important role related to working memory, with its core angular regions contributing to the changes in global brain connectivity in response to increasing environmental demands. Hum Brain Mapp 38:41-52, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Network control processor for a TDMA system

NASA Astrophysics Data System (ADS)

Suryadevara, Omkarmurthy; Debettencourt, Thomas J.; Shulman, R. B.

Two unique aspects of designing a network control processor (NCP) to monitor and control a demand-assigned, time-division multiple-access (TDMA) network are described. The first involves the implementation of redundancy by synchronizing the databases of two geographically remote NCPs. The two sets of databases are kept in synchronization by collecting data on both systems, transferring databases, sending incremental updates, and the parallel updating of databases. A periodic audit compares the checksums of the databases to ensure synchronization. The second aspect involves the use of a tracking algorithm to dynamically reallocate TDMA frame space. This algorithm detects and tracks current and long-term load changes in the network. When some portions of the network are overloaded while others have excess capacity, the algorithm automatically calculates and implements a new burst time plan.

Transmission Loss Calculation using A and B Loss Coefficients in Dynamic Economic Dispatch Problem

NASA Astrophysics Data System (ADS)

Jethmalani, C. H. Ram; Dumpa, Poornima; Simon, Sishaj P.; Sundareswaran, K.

2016-04-01

This paper analyzes the performance of A-loss coefficients while evaluating transmission losses in a Dynamic Economic Dispatch (DED) Problem. The performance analysis is carried out by comparing the losses computed using nominal A loss coefficients and nominal B loss coefficients in reference with load flow solution obtained by standard Newton-Raphson (NR) method. Density based clustering method based on connected regions with sufficiently high density (DBSCAN) is employed in identifying the best regions of A and B loss coefficients. Based on the results obtained through cluster analysis, a novel approach in improving the accuracy of network loss calculation is proposed. Here, based on the change in per unit load values between the load intervals, loss coefficients are updated for calculating the transmission losses. The proposed algorithm is tested and validated on IEEE 6 bus system, IEEE 14 bus, system IEEE 30 bus system and IEEE 118 bus system. All simulations are carried out using SCILAB 5.4 (www.scilab.org) which is an open source software.

Traffic placement policies for a multi-band network

NASA Technical Reports Server (NTRS)

Maly, Kurt J.; Foudriat, E. C.; Game, David; Mukkamala, R.; Overstreet, C. Michael

1990-01-01

Recently protocols were introduced that enable the integration of synchronous traffic (voice or video) and asynchronous traffic (data) and extend the size of local area networks without loss in speed or capacity. One of these is DRAMA, a multiband protocol based on broadband technology. It provides dynamic allocation of bandwidth among clusters of nodes in the total network. A number of traffic placement policies for such networks are proposed and evaluated. Metrics used for performance evaluation include average network access delay, degree of fairness of access among the nodes, and network throughput. The feasibility of the DRAMA protocol is established through simulation studies. DRAMA provides effective integration of synchronous and asychronous traffic due to its ability to separate traffic types. Under the suggested traffic placement policies, the DRAMA protocol is shown to handle diverse loads, mixes of traffic types, and numbers of nodes, as well as modifications to the network structure and momentary traffic overloads.

Conducted noise analysis and protection of 45 kJ/s, ±50 kV capacitor charging power supply when interfaced with repetitive Marx based pulse power system.

PubMed

Naresh, P; Patel, Ankur; Sharma, Archana

2015-09-01

Pulse power systems with highly dynamic loads like klystron, backward wave oscillator (BWO), and magnetron generate highly dynamic noise. This noise leads to frequent failure of controlled switches in the inverter stage of charging power supply. Designing a reliable and compatible power supply for pulse power applications is always a tricky job when charging rate is in multiples of 10 kJ/s. A ±50 kV and 45 kJ/s capacitor charging power supply based on 4th order LCLC resonant topology has been developed for a 10 Hz repetitive Marx based system. Conditions for load independent constant current and zero current switching (ZCS) are derived mathematically. Noise generated at load end due to dynamic load is tackled effectively and reduction in magnitude noise voltage is achieved by providing shielding between primary and secondary of high voltage high frequency transformer and with LCLC low pass filter. Shielding scales down the ratio between coupling capacitance (Cc) and the collector-emitter capacitance of insulated gate bi-polar transistor switch, which in turn reduces the common mode noise voltage magnitude. The proposed 4th order LCLC resonant network acts as a low pass filter for differential mode noise in the reverse direction (from load to source). Power supply has been tested repeatedly with 5 Hz repetition rate with repetitive Marx based system connected with BWO load working fine without failure of single switch in the inverter stage.

Conducted noise analysis and protection of 45 kJ/s, ±50 kV capacitor charging power supply when interfaced with repetitive Marx based pulse power system

NASA Astrophysics Data System (ADS)

Naresh, P.; Patel, Ankur; Sharma, Archana

2015-09-01

Pulse power systems with highly dynamic loads like klystron, backward wave oscillator (BWO), and magnetron generate highly dynamic noise. This noise leads to frequent failure of controlled switches in the inverter stage of charging power supply. Designing a reliable and compatible power supply for pulse power applications is always a tricky job when charging rate is in multiples of 10 kJ/s. A ±50 kV and 45 kJ/s capacitor charging power supply based on 4th order LCLC resonant topology has been developed for a 10 Hz repetitive Marx based system. Conditions for load independent constant current and zero current switching (ZCS) are derived mathematically. Noise generated at load end due to dynamic load is tackled effectively and reduction in magnitude noise voltage is achieved by providing shielding between primary and secondary of high voltage high frequency transformer and with LCLC low pass filter. Shielding scales down the ratio between coupling capacitance (Cc) and the collector-emitter capacitance of insulated gate bi-polar transistor switch, which in turn reduces the common mode noise voltage magnitude. The proposed 4th order LCLC resonant network acts as a low pass filter for differential mode noise in the reverse direction (from load to source). Power supply has been tested repeatedly with 5 Hz repetition rate with repetitive Marx based system connected with BWO load working fine without failure of single switch in the inverter stage.

Modeling Aircraft Wing Loads from Flight Data Using Neural Networks

NASA Technical Reports Server (NTRS)

Allen, Michael J.; Dibley, Ryan P.

2003-01-01

Neural networks were used to model wing bending-moment loads, torsion loads, and control surface hinge-moments of the Active Aeroelastic Wing (AAW) aircraft. Accurate loads models are required for the development of control laws designed to increase roll performance through wing twist while not exceeding load limits. Inputs to the model include aircraft rates, accelerations, and control surface positions. Neural networks were chosen to model aircraft loads because they can account for uncharacterized nonlinear effects while retaining the capability to generalize. The accuracy of the neural network models was improved by first developing linear loads models to use as starting points for network training. Neural networks were then trained with flight data for rolls, loaded reversals, wind-up-turns, and individual control surface doublets for load excitation. Generalization was improved by using gain weighting and early stopping. Results are presented for neural network loads models of four wing loads and four control surface hinge moments at Mach 0.90 and an altitude of 15,000 ft. An average model prediction error reduction of 18.6 percent was calculated for the neural network models when compared to the linear models. This paper documents the input data conditioning, input parameter selection, structure, training, and validation of the neural network models.

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

NASA Astrophysics Data System (ADS)

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.

Intelligent voltage control strategy for three-phase UPS inverters with output LC filter

NASA Astrophysics Data System (ADS)

Jung, J. W.; Leu, V. Q.; Dang, D. Q.; Do, T. D.; Mwasilu, F.; Choi, H. H.

2015-08-01

This paper presents a supervisory fuzzy neural network control (SFNNC) method for a three-phase inverter of uninterruptible power supplies (UPSs). The proposed voltage controller is comprised of a fuzzy neural network control (FNNC) term and a supervisory control term. The FNNC term is deliberately employed to estimate the uncertain terms, and the supervisory control term is designed based on the sliding mode technique to stabilise the system dynamic errors. To improve the learning capability, the FNNC term incorporates an online parameter training methodology, using the gradient descent method and Lyapunov stability theory. Besides, a linear load current observer that estimates the load currents is used to exclude the load current sensors. The proposed SFNN controller and the observer are robust to the filter inductance variations, and their stability analyses are described in detail. The experimental results obtained on a prototype UPS test bed with a TMS320F28335 DSP are presented to validate the feasibility of the proposed scheme. Verification results demonstrate that the proposed control strategy can achieve smaller steady-state error and lower total harmonic distortion when subjected to nonlinear or unbalanced loads compared to the conventional sliding mode control method.

Wireless Sensor Network Quality of Service Improvement on Flooding Attack Condition

NASA Astrophysics Data System (ADS)

Hartono, R.; Widyawan; Wibowo, S. B.; Purnomo, A.; Hartatik

2018-03-01

There are two methods of building communication using wireless media. The first method is building a base infrastructure as an intermediary between users. Problems that arise on this type of network infrastructure is limited space to build any network physical infrastructure and also the cost factor. The second method is to build an ad hoc network between users who will communicate. On ad hoc network, each user must be willing to send data from source to destination for the occurrence of a communication. One of network protocol in Ad Hoc, Ad hoc on demand Distance Vector (AODV), has the smallest overhead value, easier to adapt to dynamic network and has small control message. One AODV protocol’s drawback is route finding process’ security for sending the data. In this research, AODV protocol is optimized by determining Expanding Ring Search (ERS) best value. Random topology is used with variation in the number of nodes: 25, 50, 75, 100, 125 and 150 with node’s speed of 10m/s in the area of 1000m x 1000m on flooding network condition. Parameters measured are Throughput, Packet Delivery Ratio, Average Delay and Normalized Routing Load. From the test results of AODV protocol optimization with best value of Expanding Ring Search (ERS), throughput increased by 5.67%, packet delivery ratio increased by 5.73%, and as for Normalized Routing Load decreased by 4.66%. ERS optimal value for each node’s condition depending on the number of nodes on the network.

Construction of a stochastic model of track geometry irregularities and validation through experimental measurements of dynamic loading

NASA Astrophysics Data System (ADS)

Panunzio, Alfonso M.; Puel, G.; Cottereau, R.; Simon, S.; Quost, X.

2017-03-01

This paper describes the construction of a stochastic model of urban railway track geometry irregularities, based on experimental data. The considered irregularities are track gauge, superelevation, horizontal and vertical curvatures. They are modelled as random fields whose statistical properties are extracted from a large set of on-track measurements of the geometry of an urban railway network. About 300-1000 terms are used in the Karhunen-Loève/Polynomial Chaos expansions to represent the random fields with appropriate accuracy. The construction of the random fields is then validated by comparing on-track measurements of the contact forces and numerical dynamics simulations for different operational conditions (train velocity and car load) and horizontal layouts (alignment, curve). The dynamics simulations are performed both with and without randomly generated geometrical irregularities for the track. The power spectrum densities obtained from the dynamics simulations with the model of geometrical irregularities compare extremely well with those obtained from the experimental contact forces. Without irregularities, the spectrum is 10-50 dB too low.

AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, 34th and AIAA/ASME Adaptive Structures Forum, La Jolla, CA, Apr. 19-22, 1993, Technical Papers. Pts. 1-6

NASA Astrophysics Data System (ADS)

Topics addressed include the prediction of helicopter component loads using neural networks, spacecraft on-orbit coupled loads analysis, hypersonic flutter of a curved shallow panel with aerodynamic heating, thermal-acoustic fatigue of ceramic matrix composite materials, transition elements based on transfinite interpolation, damage progression in stiffened composite panels, a direct treatment of min-max dynamic response optimization problems, and sources of helicopter rotor hub inplane shears. Also discussed are dynamics of a layered elastic system, confidence bounds on structural reliability, mixed triangular space-time finite elements, advanced transparency development for USAF aircraft, a low-velocity impact on a graphite/PEEK, an automated mode-tracking strategy, transonic flutter suppression by a passive flap, a nonlinear response of composite panels to random excitation, an optimal placement of elastic supports on a simply supported plate, a probabilistic assessment of composite structures, a model for mode I failure of laminated composites, a residual flexibility approach to multibody dynamics,and multilayer piezoelectric actuators.

Research on virtual network load balancing based on OpenFlow

NASA Astrophysics Data System (ADS)

Peng, Rong; Ding, Lei

2017-08-01

The Network based on OpenFlow technology separate the control module and data forwarding module. Global deployment of load balancing strategy through network view of control plane is fast and of high efficiency. This paper proposes a Weighted Round-Robin Scheduling algorithm for virtual network and a load balancing plan for server load based on OpenFlow. Load of service nodes and load balancing tasks distribution algorithm will be taken into account.

Effects of riparian buffer width on wood loading in headwater streams after repeated forest thinning

Treesearch

Julia I. Burton; Deanna H. Olson; Klaus J. Puettmann

2016-01-01

Forested riparian buffer zones are used in conjunction with upland forest management, in part, to provide for the recruitment for large wood to streams. Small headwater streams account for the majority of stream networks in many forested regions. Yet, our understanding of how riparian buffer width influences wood dynamics in headwater streams is relatively less...

Distributed Decision Making in a Dynamic Network Environment

DTIC Science & Technology

1990-01-01

protocols, particularly when traffic arrival statistics are varying or unknown, and loads are high. Both nonpreemptive and preemptive repeat disciplines are...The simulation model allows general value functions, continuous time operation, and preemptive or nonpreemptive service. For reasons of tractability... nonpreemptive LIFO, (4) nonpreemptive LIFO with discarding, (5) nonpreemptive HOL, (6) nonpreemp- tive HOL with discarding, (7) preemptive repeat HOL, (8

Flight Test of an Adaptive Controller and Simulated Failure/Damage on the NASA NF-15B

NASA Technical Reports Server (NTRS)

Buschbacher, Mark; Maliska, Heather

2006-01-01

The method of flight-testing the Intelligent Flight Control System (IFCS) Second Generation (Gen-2) project on the NASA NF-15B is herein described. The Gen-2 project objective includes flight-testing a dynamic inversion controller augmented by a direct adaptive neural network to demonstrate performance improvements in the presence of simulated failure/damage. The Gen-2 objectives as implemented on the NASA NF-15B created challenges for software design, structural loading limitations, and flight test operations. Simulated failure/damage is introduced by modifying control surface commands, therefore requiring structural loads measurements. Flight-testing began with the validation of a structural loads model. Flight-testing of the Gen-2 controller continued, using test maneuvers designed in a sequenced approach. Success would clear the new controller with respect to dynamic response, simulated failure/damage, and with adaptation on and off. A handling qualities evaluation was conducted on the capability of the Gen-2 controller to restore aircraft response in the presence of a simulated failure/damage. Control room monitoring of loads sensors, flight dynamics, and controller adaptation, in addition to postflight data comparison to the simulation, ensured a safe methodology of buildup testing. Flight-testing continued without major incident to accomplish the project objectives, successfully uncovering strengths and weaknesses of the Gen-2 control approach in flight.

Elastic deformation and failure in protein filament bundles: Atomistic simulations and coarse-grained modeling.

PubMed

Hammond, Nathan A; Kamm, Roger D

2008-07-01

The synthetic peptide RAD16-II has shown promise in tissue engineering and drug delivery. It has been studied as a vehicle for cell delivery and controlled release of IGF-1 to repair infarcted cardiac tissue, and as a scaffold to promote capillary formation for an in vitro model of angiogenesis. The structure of RAD16-II is hierarchical, with monomers forming long beta-sheets that pair together to form filaments; filaments form bundles approximately 30-60 nm in diameter; branching networks of filament bundles form macroscopic gels. We investigate the mechanics of shearing between the two beta-sheets constituting one filament, and between cohered filaments of RAD16-II. This shear loading is found in filament bundle bending or in tensile loading of fibers composed of partial-length filaments. Molecular dynamics simulations show that time to failure is a stochastic function of applied shear stress, and that for a given loading time behavior is elastic for sufficiently small shear loads. We propose a coarse-grained model based on Langevin dynamics that matches molecular dynamics results and facilities extending simulations in space and time. The model treats a filament as an elastic string of particles, each having potential energy that is a periodic function of its position relative to the neighboring filament. With insight from these simulations, we discuss strategies for strengthening RAD16-II and similar materials.

Intelligent Resource Management for Local Area Networks: Approach and Evolution

NASA Technical Reports Server (NTRS)

Meike, Roger

1988-01-01

The Data Management System network is a complex and important part of manned space platforms. Its efficient operation is vital to crew, subsystems and experiments. AI is being considered to aid in the initial design of the network and to augment the management of its operation. The Intelligent Resource Management for Local Area Networks (IRMA-LAN) project is concerned with the application of AI techniques to network configuration and management. A network simulation was constructed employing real time process scheduling for realistic loads, and utilizing the IEEE 802.4 token passing scheme. This simulation is an integral part of the construction of the IRMA-LAN system. From it, a causal model is being constructed for use in prediction and deep reasoning about the system configuration. An AI network design advisor is being added to help in the design of an efficient network. The AI portion of the system is planned to evolve into a dynamic network management aid. The approach, the integrated simulation, project evolution, and some initial results are described.

Impact Capacity Reduction in Railway Prestressed Concrete Sleepers with Surface Abrasions

NASA Astrophysics Data System (ADS)

Ngamkhanong, Chayut; Li, Dan; Kaewunruen, Sakdirat

2017-10-01

Railway sleepers (also called ‘railroad tie’ in North America) embedded in ballasted railway tracks are a main part of railway track structures. Its important role is to transfer the loads evenly from the rails to a wider area of ballast bed and to secure rail gauge and enable safe passages of rolling stocks. By nature, railway infrastructure is nonlinear, evidenced by its behaviours, geometry and alignment, wheel-rail contact and operational parameters such as tractive efforts. Based on our critical review, the dynamic behaviour of railway sleepers has not been fully investigated, especially when the sleepers are deteriorated by excessive wears. In fact, the ballast angularity causes differential abrasions on the soffit or bottom surface of sleepers (especially at railseat zone). Furthermore, in sharp curves and rapid gradient change, longitudinal and lateral dynamics of rails increase the likelihood of railseat abrasions in concrete sleepers due to the unbalanced loading conditions. This paper presents a structural capacity of concrete sleepers under dynamic transient loading. The modified compression field theory for ultimate strength design of concrete sleepers under impact loading will be highlighted in this study. The influences of surface abrasions, including surface abrasion and soffit abrasion, on the dynamic behaviour of prestressed concrete sleepers, are firstly highlighted. The outcome of this study will improve the rail maintenance and inspection criteria in order to establish appropriate and sensible remote track condition monitoring network in practice. Moreover, this study will also improve the understanding of the fundamental dynamic behaviour of prestressed concrete sleepers with surface abrasions. The insight into these behaviours will not only improve safety and reliability of railway infrastructure but will enhance the structural safety of other concrete structures.

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

NASA Astrophysics Data System (ADS)

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.

Automated wind load characterization of wind turbine structures by embedded model updating

NASA Astrophysics Data System (ADS)

Swartz, R. Andrew; Zimmerman, Andrew T.; Lynch, Jerome P.

2010-04-01

The continued development of renewable energy resources is for the nation to limit its carbon footprint and to enjoy independence in energy production. Key to that effort are reliable generators of renewable energy sources that are economically competitive with legacy sources. In the area of wind energy, a major contributor to the cost of implementation is large uncertainty regarding the condition of wind turbines in the field due to lack of information about loading, dynamic response, and fatigue life of the structure expended. Under favorable circumstances, this uncertainty leads to overly conservative designs and maintenance schedules. Under unfavorable circumstances, it leads to inadequate maintenance schedules, damage to electrical systems, or even structural failure. Low-cost wireless sensors can provide more certainty for stakeholders by measuring the dynamic response of the structure to loading, estimating the fatigue state of the structure, and extracting loading information from the structural response without the need of an upwind instrumentation tower. This study presents a method for using wireless sensor networks to estimate the spectral properties of a wind turbine tower loading based on its measured response and some rudimentary knowledge of its structure. Structural parameters are estimated via model-updating in the frequency domain to produce an identification of the system. The updated structural model and the measured output spectra are then used to estimate the input spectra. Laboratory results are presented indicating accurate load characterization.

Controlling toughness and dynamics of polymer networks via mussel-inspired dynamical bonds

NASA Astrophysics Data System (ADS)

Filippidi, Emmanouela

For dry, thermoset, polymer systems increasing the degree of cross-linking increases the elastic modulus. However, it simultaneously compromises the elongation under tension, usually reducing the overall total energy dissipated before fracture (toughness). Dynamic reformable bonds and complex network topologies have been used to circumnavigate this issue with moderate success, mainly in hydrated network systems. Hydration, however, which swells these networks limits how far one could increase the modulus, while their chemistry prevents improvement of the mechanics upon drying. Employing the mussel byssus-inspired strategy of iron-catechol coordination bonds, we have synthesized and studied epoxy networks comprising covalently attached catechol moieties capable of forming additional iron-catechol complex cross-links that still function in dry conditions. In such a fashion, we create a high modulus, high elongation, high toughness material. The iron-catechol coordination bonds play multiple roles that enhance the mechanical performance of the system: at low strain and fast strain rates, they act like permanent cross-links with bonding strength similar to covalent bonds, but start disassociating at high elongation. They are also reformable, enabling material self-healing in a matter of minutes in the absence of load. Finally, the dissociative crosslink cleavage alters the local chain topology, creating length scales that unfold upon elongation. The elegance of this system lies on its general versatility. Both the polymer and metal ion can be used as control parameters to study the interplay of covalent and dynamical bonds as well as explore the limits of the design of elastomers with enhanced toughness. MRSEC of NSF Award No. DMR-1121053.

A Hybrid Demand Response Simulator Version 1.0

DOE Office of Scientific and Technical Information (OSTI.GOV)

2012-05-02

A hybrid demand response simulator is developed to test different control algorithms for centralized and distributed demand response (DR) programs in a small distribution power grid. The HDRS is designed to model a wide variety of DR services such as peak having, load shifting, arbitrage, spinning reserves, load following, regulation, emergency load shedding, etc. The HDRS does not model the dynamic behaviors of the loads, rather, it simulates the load scheduling and dispatch process. The load models include TCAs (water heaters, air conditioners, refrigerators, freezers, etc) and non-TCAs (lighting, washer, dishwasher, etc.) The ambient temperature changes, thermal resistance, capacitance, andmore » the unit control logics can be modeled for TCA loads. The use patterns of the non-TCA can be modeled by probability of use and probabilistic durations. Some of the communication network characteristics, such as delays and errors, can also be modeled. Most importantly, because the simulator is modular and greatly simplified the thermal models for TCA loads, it is very easy and fast to be used to test and validate different control algorithms in a simulated environment.« less

On-Line Tracking Controller for Brushless DC Motor Drives Using Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Rubaai, Ahmed

1996-01-01

A real-time control architecture is developed for time-varying nonlinear brushless dc motors operating in a high performance drives environment. The developed control architecture possesses the capabilities of simultaneous on-line identification and control. The dynamics of the motor are modeled on-line and controlled using an artificial neural network, as the system runs. The control architecture combines the experience and dependability of adaptive tracking systems with potential and promise of the neural computing technology. The sensitivity of real-time controller to parametric changes that occur during training is investigated. Such changes are usually manifested by rapid changes in the load of the brushless motor drives. This sudden change in the external load is simulated for the sigmoidal and sinusoidal reference tracks. The ability of the neuro-controller to maintain reasonable tracking accuracy in the presence of external noise is also verified for a number of desired reference trajectories.

Overload Control for Signaling Congestion of Machine Type Communications in 3GPP Networks

PubMed Central

Lu, Zhaoming; Pan, Qi; Wang, Luhan; Wen, Xiangming

2016-01-01

Because of the limited resources on radio access channels of third generation partnership projection (3GPP) network, one of the most challenging tasks posted by 3GPP cellular-based machine type communications (MTC) is congestion due to massive requests for connection to radio access network (RAN). In this paper, an overload control algorithm in 3GPP RAN is proposed, which proactively disperses the simultaneous access attempts in evenly distributed time window. Through periodic reservation strategy, massive access requests of MTC devices are dispersed in time, which reduces the probability of confliction of signaling. By the compensation and prediction mechanism, each device can communicate with MTC server with dynamic load of air interface. Numerical results prove that proposed method makes MTC applications friendly to 3GPP cellular network. PMID:27936011

Overload Control for Signaling Congestion of Machine Type Communications in 3GPP Networks.

PubMed

Lu, Zhaoming; Pan, Qi; Wang, Luhan; Wen, Xiangming

2016-01-01

Because of the limited resources on radio access channels of third generation partnership projection (3GPP) network, one of the most challenging tasks posted by 3GPP cellular-based machine type communications (MTC) is congestion due to massive requests for connection to radio access network (RAN). In this paper, an overload control algorithm in 3GPP RAN is proposed, which proactively disperses the simultaneous access attempts in evenly distributed time window. Through periodic reservation strategy, massive access requests of MTC devices are dispersed in time, which reduces the probability of confliction of signaling. By the compensation and prediction mechanism, each device can communicate with MTC server with dynamic load of air interface. Numerical results prove that proposed method makes MTC applications friendly to 3GPP cellular network.

Statistical modeling of the Internet traffic dynamics: To which extent do we need long-term correlations?

NASA Astrophysics Data System (ADS)

Markelov, Oleg; Nguyen Duc, Viet; Bogachev, Mikhail

2017-11-01

Recently we have suggested a universal superstatistical model of user access patterns and aggregated network traffic. The model takes into account the irregular character of end user access patterns on the web via the non-exponential distributions of the local access rates, but neglects the long-term correlations between these rates. While the model is accurate for quasi-stationary traffic records, its performance under highly variable and especially non-stationary access dynamics remains questionable. In this paper, using an example of the traffic patterns from a highly loaded network cluster hosting the website of the 1998 FIFA World Cup, we suggest a generalization of the previously suggested superstatistical model by introducing long-term correlations between access rates. Using queueing system simulations, we show explicitly that this generalization is essential for modeling network nodes with highly non-stationary access patterns, where neglecting long-term correlations leads to the underestimation of the empirical average sojourn time by several decades under high throughput utilization.

Traffic sharing algorithms for hybrid mobile networks

NASA Technical Reports Server (NTRS)

Arcand, S.; Murthy, K. M. S.; Hafez, R.

1995-01-01

In a hybrid (terrestrial + satellite) mobile personal communications networks environment, a large size satellite footprint (supercell) overlays on a large number of smaller size, contiguous terrestrial cells. We assume that the users have either a terrestrial only single mode terminal (SMT) or a terrestrial/satellite dual mode terminal (DMT) and the ratio of DMT to the total terminals is defined gamma. It is assumed that the call assignments to and handovers between terrestrial cells and satellite supercells take place in a dynamic fashion when necessary. The objectives of this paper are twofold, (1) to propose and define a class of traffic sharing algorithms to manage terrestrial and satellite network resources efficiently by handling call handovers dynamically, and (2) to analyze and evaluate the algorithms by maximizing the traffic load handling capability (defined in erl/cell) over a wide range of terminal ratios (gamma) given an acceptable range of blocking probabilities. Two of the algorithms (G & S) in the proposed class perform extremely well for a wide range of gamma.

Advanced diagnostic system for piston slap faults in IC engines, based on the non-stationary characteristics of the vibration signals

NASA Astrophysics Data System (ADS)

Chen, Jian; Randall, Robert Bond; Peeters, Bart

2016-06-01

Artificial Neural Networks (ANNs) have the potential to solve the problem of automated diagnostics of piston slap faults, but the critical issue for the successful application of ANN is the training of the network by a large amount of data in various engine conditions (different speed/load conditions in normal condition, and with different locations/levels of faults). On the other hand, the latest simulation technology provides a useful alternative in that the effect of clearance changes may readily be explored without recourse to cutting metal, in order to create enough training data for the ANNs. In this paper, based on some existing simplified models of piston slap, an advanced multi-body dynamic simulation software was used to simulate piston slap faults with different speeds/loads and clearance conditions. Meanwhile, the simulation models were validated and updated by a series of experiments. Three-stage network systems are proposed to diagnose piston faults: fault detection, fault localisation and fault severity identification. Multi Layer Perceptron (MLP) networks were used in the detection stage and severity/prognosis stage and a Probabilistic Neural Network (PNN) was used to identify which cylinder has faults. Finally, it was demonstrated that the networks trained purely on simulated data can efficiently detect piston slap faults in real tests and identify the location and severity of the faults as well.

Molecular mechanics of silk nanostructures under varied mechanical loading.

PubMed

Bratzel, Graham; Buehler, Markus J

2012-06-01

Spider dragline silk is a self-assembling tunable protein composite fiber that rivals many engineering fibers in tensile strength, extensibility, and toughness, making it one of the most versatile biocompatible materials and most inviting for synthetic mimicry. While experimental studies have shown that the peptide sequence and molecular structure of silk have a direct influence on the stiffness, toughness, and failure strength of silk, few molecular-level analyses of the nanostructure of silk assemblies, in particular, under variations of genetic sequences have been reported. In this study, atomistic-level structures of wildtype as well as modified MaSp1 protein from the Nephila clavipes spider dragline silk sequences, obtained using an in silico approach based on replica exchange molecular dynamics and explicit water molecular dynamics, are subjected to simulated nanomechanical testing using different force-control loading conditions including stretch, pull-out, and peel. The authors have explored the effects of the poly-alanine length of the N. clavipes MaSp1 peptide sequence and identify differences in nanomechanical loading conditions on the behavior of a unit cell of 15 strands with 840-990 total residues used to represent a cross-linking β-sheet crystal node in the network within a fibril of the dragline silk thread. The specific loading condition used, representing concepts derived from the protein network connectivity at larger scales, have a significant effect on the mechanical behavior. Our analysis incorporates stretching, pull-out, and peel testing to connect biochemical features to mechanical behavior. The method used in this study could find broad applications in de novo design of silk-like tunable materials for an array of applications. Copyright © 2011 Wiley Periodicals, Inc.

Predictive functional control for active queue management in congested TCP/IP networks.

PubMed

Bigdeli, N; Haeri, M

2009-01-01

Predictive functional control (PFC) as a new active queue management (AQM) method in dynamic TCP networks supporting explicit congestion notification (ECN) is proposed. The ability of the controller in handling system delay along with its simplicity and low computational load makes PFC a privileged AQM method in the high speed networks. Besides, considering the disturbance term (which represents model/process mismatches, external disturbances, and existing noise) in the control formulation adds some level of robustness into the PFC-AQM controller. This is an important and desired property in the control of dynamically-varying computer networks. In this paper, the controller is designed based on a small signal linearized fluid-flow model of the TCP/AQM networks. Then, closed-loop transfer function representation of the system is derived to analyze the robustness with respect to the network and controller parameters. The analytical as well as the packet-level ns-2 simulation results show the out-performance of the developed controller for both queue regulation and resource utilization. Fast response, low queue fluctuations (and consequently low delay jitter), high link utilization, good disturbance rejection, scalability, and low packet marking probability are other features of the developed method with respect to other well-known AQM methods such as RED, PI, and REM which are also simulated for comparison.

A distributed computing approach to mission operations support. [for spacecraft

NASA Technical Reports Server (NTRS)

Larsen, R. L.

1975-01-01

Computing mission operation support includes orbit determination, attitude processing, maneuver computation, resource scheduling, etc. The large-scale third-generation distributed computer network discussed is capable of fulfilling these dynamic requirements. It is shown that distribution of resources and control leads to increased reliability, and exhibits potential for incremental growth. Through functional specialization, a distributed system may be tuned to very specific operational requirements. Fundamental to the approach is the notion of process-to-process communication, which is effected through a high-bandwidth communications network. Both resource-sharing and load-sharing may be realized in the system.

Emergence of ultrafast sparsely synchronized rhythms and their responses to external stimuli in an inhomogeneous small-world complex neuronal network.

PubMed

Kim, Sang-Yoon; Lim, Woochang

2017-09-01

We consider an inhomogeneous small-world network (SWN) composed of inhibitory short-range (SR) and long-range (LR) interneurons, and investigate the effect of network architecture on emergence of synchronized brain rhythms by varying the fraction of LR interneurons p long . The betweenness centralities of the LR and SR interneurons (characterizing the potentiality in controlling communication between other interneurons) are distinctly different. Hence, in view of the betweenness, SWNs we consider are inhomogeneous, unlike the "canonical" Watts-Strogatz SWN with nearly the same betweenness centralities. For small p long , the load of communication traffic is much concentrated on a few LR interneurons. However, as p long is increased, the number of LR connections (coming from LR interneurons) increases, and then the load of communication traffic is less concentrated on LR interneurons, which leads to better efficiency of global communication between interneurons. Sparsely synchronized rhythms are thus found to emerge when passing a small critical value p long (c) (≃0.16). The population frequency of the sparsely synchronized rhythm is ultrafast (higher than 100 Hz), while the mean firing rate of individual interneurons is much lower (∼30 Hz) due to stochastic and intermittent neural discharges. These dynamical behaviors in the inhomogeneous SWN are also compared with those in the homogeneous Watts-Strogatz SWN, in connection with their network topologies. Particularly, we note that the main difference between the two types of SWNs lies in the distribution of betweenness centralities. Unlike the case of the Watts-Strogatz SWN, dynamical responses to external stimuli vary depending on the type of stimulated interneurons in the inhomogeneous SWN. We consider two cases of external time-periodic stimuli applied to sub-populations of the LR and SR interneurons, respectively. Dynamical responses (such as synchronization suppression and enhancement) to these two cases of stimuli are studied and discussed in relation to the betweenness centralities of stimulated interneurons, representing the effectiveness for transfer of stimulation effect in the whole network. Copyright © 2017 Elsevier Ltd. All rights reserved.

Optimization and resilience of complex supply-demand networks

NASA Astrophysics Data System (ADS)

Zhang, Si-Ping; Huang, Zi-Gang; Dong, Jia-Qi; Eisenberg, Daniel; Seager, Thomas P.; Lai, Ying-Cheng

2015-06-01

Supply-demand processes take place on a large variety of real-world networked systems ranging from power grids and the internet to social networking and urban systems. In a modern infrastructure, supply-demand systems are constantly expanding, leading to constant increase in load requirement for resources and consequently, to problems such as low efficiency, resource scarcity, and partial system failures. Under certain conditions global catastrophe on the scale of the whole system can occur through the dynamical process of cascading failures. We investigate optimization and resilience of time-varying supply-demand systems by constructing network models of such systems, where resources are transported from the supplier sites to users through various links. Here by optimization we mean minimization of the maximum load on links, and system resilience can be characterized using the cascading failure size of users who fail to connect with suppliers. We consider two representative classes of supply schemes: load driven supply and fix fraction supply. Our findings are: (1) optimized systems are more robust since relatively smaller cascading failures occur when triggered by external perturbation to the links; (2) a large fraction of links can be free of load if resources are directed to transport through the shortest paths; (3) redundant links in the performance of the system can help to reroute the traffic but may undesirably transmit and enlarge the failure size of the system; (4) the patterns of cascading failures depend strongly upon the capacity of links; (5) the specific location of the trigger determines the specific route of cascading failure, but has little effect on the final cascading size; (6) system expansion typically reduces the efficiency; and (7) when the locations of the suppliers are optimized over a long expanding period, fewer suppliers are required. These results hold for heterogeneous networks in general, providing insights into designing optimal and resilient complex supply-demand systems that expand constantly in time.

Use of model calibration to achieve high accuracy in analysis of computer networks

DOEpatents

Frogner, Bjorn; Guarro, Sergio; Scharf, Guy

2004-05-11

A system and method are provided for creating a network performance prediction model, and calibrating the prediction model, through application of network load statistical analyses. The method includes characterizing the measured load on the network, which may include background load data obtained over time, and may further include directed load data representative of a transaction-level event. Probabilistic representations of load data are derived to characterize the statistical persistence of the network performance variability and to determine delays throughout the network. The probabilistic representations are applied to the network performance prediction model to adapt the model for accurate prediction of network performance. Certain embodiments of the method and system may be used for analysis of the performance of a distributed application characterized as data packet streams.

Contextualizing Wetlands Within a River Network to Assess Nitrate Removal and Inform Watershed Management

NASA Astrophysics Data System (ADS)

Czuba, Jonathan A.; Hansen, Amy T.; Foufoula-Georgiou, Efi; Finlay, Jacques C.

2018-02-01

Aquatic nitrate removal depends on interactions throughout an interconnected network of lakes, wetlands, and river channels. Herein, we present a network-based model that quantifies nitrate-nitrogen and organic carbon concentrations through a wetland-river network and estimates nitrate export from the watershed. This model dynamically accounts for multiple competing limitations on nitrate removal, explicitly incorporates wetlands in the network, and captures hierarchical network effects and spatial interactions. We apply the model to the Le Sueur Basin, a data-rich 2,880 km2 agricultural landscape in southern Minnesota and validate the model using synoptic field measurements during June for years 2013-2015. Using the model, we show that the overall limits to nitrate removal rate via denitrification shift between nitrate concentration, organic carbon availability, and residence time depending on discharge, characteristics of the waterbody, and location in the network. Our model results show that the spatial context of wetland restorations is an important but often overlooked factor because nonlinearities in the system, e.g., deriving from switching of resource limitation on denitrification rate, can lead to unexpected changes in downstream biogeochemistry. Our results demonstrate that reduction of watershed-scale nitrate concentrations and downstream loads in the Le Sueur Basin can be most effectively achieved by increasing water residence time (by slowing the flow) rather than by increasing organic carbon concentrations (which may limit denitrification). This framework can be used toward assessing where and how to restore wetlands for reducing nitrate concentrations and loads from agricultural watersheds.

Adaptation to a cortex controlled robot attached at the pelvis and engaged during locomotion in rats

PubMed Central

Song, Weiguo; Giszter, Simon F.

2011-01-01

Brain Machine Interfaces (BMIs) should ideally show robust adaptation of the BMI across different tasks and daily activities. Most BMIs have used over-practiced tasks. Little is known about BMIs in dynamic environments. How are mechanically body-coupled BMIs integrated into ongoing rhythmic dynamics, e.g., in locomotion? To examine this we designed a novel BMI using neural discharge in the hindlimb/trunk motor cortex in rats during locomotion to control a robot attached at the pelvis. We tested neural adaptation when rats experienced (a) control locomotion, (b) ‘simple elastic load’ (a robot load on locomotion without any BMI neural control) and (c) ‘BMI with elastic load’ (in which the robot loaded locomotion and a BMI neural control could counter this load). Rats significantly offset applied loads with the BMI while preserving more normal pelvic height compared to load alone. Adaptation occurred over about 100–200 step cycles in a trial. Firing rates increased in both the loaded conditions compared to baseline. Mean phases of cells’ discharge in the step cycle shifted significantly between BMI and the simple load condition. Over time more BMI cells became positively correlated with the external force and modulated more deeply, and neurons’ network correlations on a 100ms timescale increased. Loading alone showed none of these effects. The BMI neural changes of rate and force correlations persisted or increased over repeated trials. Our results show that rats have the capacity to use motor adaptation and motor learning to fairly rapidly engage hindlimb/trunk coupled BMIs in their locomotion. PMID:21414932

Performance analysis of dynamic time-slot allocation system

NASA Astrophysics Data System (ADS)

Kong, Hongwei; Ruan, Fang; Feng, Chongxi

2001-10-01

Multi-service Access on the narrow-band DDN (Digital Data Network) leased lines to use the bandwidth more efficiently and reduce the cost has attracted much interest. In this paper, one novel multi-service multiplexing scheme based on DTSA (Dynamic Time-Slot Allocation) is given. This scheme can guarantee the QoS of the multiplexed services such as FAX, Voice and data and adapt to different link rates (64kb/s, 128kb/s, 256kb/s), A model is given in this paper to analyze the data behavior under this scheme. The simulation result and the model result have shown that the QoS guarantee to voice and FAX doesn't compromise the QoS of data service much in the meaning of delay and delay variance when the data load is not too high. The simulation result agrees with the model well when data load is not too high.

Ultrastable cellulosome-adhesion complex tightens under load.

PubMed

Schoeler, Constantin; Malinowska, Klara H; Bernardi, Rafael C; Milles, Lukas F; Jobst, Markus A; Durner, Ellis; Ott, Wolfgang; Fried, Daniel B; Bayer, Edward A; Schulten, Klaus; Gaub, Hermann E; Nash, Michael A

2014-12-08

Challenging environments have guided nature in the development of ultrastable protein complexes. Specialized bacteria produce discrete multi-component protein networks called cellulosomes to effectively digest lignocellulosic biomass. While network assembly is enabled by protein interactions with commonplace affinities, we show that certain cellulosomal ligand-receptor interactions exhibit extreme resistance to applied force. Here, we characterize the ligand-receptor complex responsible for substrate anchoring in the Ruminococcus flavefaciens cellulosome using single-molecule force spectroscopy and steered molecular dynamics simulations. The complex withstands forces of 600-750 pN, making it one of the strongest bimolecular interactions reported, equivalent to half the mechanical strength of a covalent bond. Our findings demonstrate force activation and inter-domain stabilization of the complex, and suggest that certain network components serve as mechanical effectors for maintaining network integrity. This detailed understanding of cellulosomal network components may help in the development of biocatalysts for production of fuels and chemicals from renewable plant-derived biomass.

Multi-layer service function chaining scheduling based on auxiliary graph in IP over optical network

NASA Astrophysics Data System (ADS)

Li, Yixuan; Li, Hui; Liu, Yuze; Ji, Yuefeng

2017-10-01

Software Defined Optical Network (SDON) can be considered as extension of Software Defined Network (SDN) in optical networks. SDON offers a unified control plane and makes optical network an intelligent transport network with dynamic flexibility and service adaptability. For this reason, a comprehensive optical transmission service, able to achieve service differentiation all the way down to the optical transport layer, can be provided to service function chaining (SFC). IP over optical network, as a promising networking architecture to interconnect data centers, is the most widely used scenarios of SFC. In this paper, we offer a flexible and dynamic resource allocation method for diverse SFC service requests in the IP over optical network. To do so, we firstly propose the concept of optical service function (OSF) and a multi-layer SFC model. OSF represents the comprehensive optical transmission service (e.g., multicast, low latency, quality of service, etc.), which can be achieved in multi-layer SFC model. OSF can also be considered as a special SF. Secondly, we design a resource allocation algorithm, which we call OSF-oriented optical service scheduling algorithm. It is able to address multi-layer SFC optical service scheduling and provide comprehensive optical transmission service, while meeting multiple optical transmission requirements (e.g., bandwidth, latency, availability). Moreover, the algorithm exploits the concept of Auxiliary Graph. Finally, we compare our algorithm with the Baseline algorithm in simulation. And simulation results show that our algorithm achieves superior performance than Baseline algorithm in low traffic load condition.

Dynamic Hierarchical Energy-Efficient Method Based on Combinatorial Optimization for Wireless Sensor Networks.

PubMed

Chang, Yuchao; Tang, Hongying; Cheng, Yongbo; Zhao, Qin; Yuan, Baoqing Li andXiaobing

2017-07-19

Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN routing protocols, we propose a dynamic hierarchical protocol based on combinatorial optimization (DHCO) to balance energy consumption of sensor nodes and to improve WSN longevity. For each sensor node, the DHCO algorithm obtains the optimal route by establishing a feasible routing set instead of selecting the cluster head or the next hop node. The process of obtaining the optimal route can be formulated as a combinatorial optimization problem. Specifically, the DHCO algorithm is carried out by the following procedures. It employs a hierarchy-based connection mechanism to construct a hierarchical network structure in which each sensor node is assigned to a special hierarchical subset; it utilizes the combinatorial optimization theory to establish the feasible routing set for each sensor node, and takes advantage of the maximum-minimum criterion to obtain their optimal routes to the base station. Various results of simulation experiments show effectiveness and superiority of the DHCO algorithm in comparison with state-of-the-art WSN routing algorithms, including low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), genetic protocol-based self-organizing network clustering (GASONeC), and double cost function-based routing (DCFR) algorithms.

A single network adaptive critic (SNAC) architecture for optimal control synthesis for a class of nonlinear systems.

PubMed

Padhi, Radhakant; Unnikrishnan, Nishant; Wang, Xiaohua; Balakrishnan, S N

2006-12-01

Even though dynamic programming offers an optimal control solution in a state feedback form, the method is overwhelmed by computational and storage requirements. Approximate dynamic programming implemented with an Adaptive Critic (AC) neural network structure has evolved as a powerful alternative technique that obviates the need for excessive computations and storage requirements in solving optimal control problems. In this paper, an improvement to the AC architecture, called the "Single Network Adaptive Critic (SNAC)" is presented. This approach is applicable to a wide class of nonlinear systems where the optimal control (stationary) equation can be explicitly expressed in terms of the state and costate variables. The selection of this terminology is guided by the fact that it eliminates the use of one neural network (namely the action network) that is part of a typical dual network AC setup. As a consequence, the SNAC architecture offers three potential advantages: a simpler architecture, lesser computational load and elimination of the approximation error associated with the eliminated network. In order to demonstrate these benefits and the control synthesis technique using SNAC, two problems have been solved with the AC and SNAC approaches and their computational performances are compared. One of these problems is a real-life Micro-Electro-Mechanical-system (MEMS) problem, which demonstrates that the SNAC technique is applicable to complex engineering systems.

Evaluation and prediction of solar radiation for energy management based on neural networks

NASA Astrophysics Data System (ADS)

Aldoshina, O. V.; Van Tai, Dinh

2017-08-01

Currently, there is a high rate of distribution of renewable energy sources and distributed power generation based on intelligent networks; therefore, meteorological forecasts are particularly useful for planning and managing the energy system in order to increase its overall efficiency and productivity. The application of artificial neural networks (ANN) in the field of photovoltaic energy is presented in this article. Implemented in this study, two periodically repeating dynamic ANS, that are the concentration of the time delay of a neural network (CTDNN) and the non-linear autoregression of a network with exogenous inputs of the NAEI, are used in the development of a model for estimating and daily forecasting of solar radiation. ANN show good productivity, as reliable and accurate models of daily solar radiation are obtained. This allows to successfully predict the photovoltaic output power for this installation. The potential of the proposed method for controlling the energy of the electrical network is shown using the example of the application of the NAEI network for predicting the electric load.

Maximum and minimum return losses from a passive two-port network terminated with a mismatched load

NASA Technical Reports Server (NTRS)

Otoshi, T. Y.

1993-01-01

This article presents an analytical method for determining the exact distance a load is required to be offset from a passive two-port network to obtain maximum or minimum return losses from the terminated two-port network. Equations are derived in terms of two-port network S-parameters and load reflection coefficient. The equations are useful for predicting worst-case performances of some types of networks that are terminated with offset short-circuit loads.

Aeroelasticity of morphing wings using neural networks

NASA Astrophysics Data System (ADS)

Natarajan, Anand

In this dissertation, neural networks are designed to effectively model static non-linear aeroelastic problems in adaptive structures and linear dynamic aeroelastic systems with time varying stiffness. The use of adaptive materials in aircraft wings allows for the change of the contour or the configuration of a wing (morphing) in flight. The use of smart materials, to accomplish these deformations, can imply that the stiffness of the wing with a morphing contour changes as the contour changes. For a rapidly oscillating body in a fluid field, continuously adapting structural parameters may render the wing to behave as a time variant system. Even the internal spars/ribs of the aircraft wing which define the wing stiffness can be made adaptive, that is, their stiffness can be made to vary with time. The immediate effect on the structural dynamics of the wing, is that, the wing motion is governed by a differential equation with time varying coefficients. The study of this concept of a time varying torsional stiffness, made possible by the use of active materials and adaptive spars, in the dynamic aeroelastic behavior of an adaptable airfoil is performed here. Another type of aeroelastic problem of an adaptive structure that is investigated here, is the shape control of an adaptive bump situated on the leading edge of an airfoil. Such a bump is useful in achieving flow separation control for lateral directional maneuverability of the aircraft. Since actuators are being used to create this bump on the wing surface, the energy required to do so needs to be minimized. The adverse pressure drag as a result of this bump needs to be controlled so that the loss in lift over the wing is made minimal. The design of such a "spoiler bump" on the surface of the airfoil is an optimization problem of maximizing pressure drag due to flow separation while minimizing the loss in lift and energy required to deform the bump. One neural network is trained using the CFD code FLUENT to represent the aerodynamic loading over the bump. A second neural network is trained for calculating the actuator loads, bump displacement and lift, drag forces over the airfoil using the finite element solver, ANSYS and the previously trained neural network. This non-linear aeroelastic model of the deforming bump on an airfoil surface using neural networks can serve as a fore-runner for other non-linear aeroelastic problems.

Behavioral and Neural Correlates of Executive Function: Interplay between Inhibition and Updating Processes.

PubMed

Kim, Na Young; Wittenberg, Ellen; Nam, Chang S

2017-01-01

This study investigated the interaction between two executive function processes, inhibition and updating, through analyses of behavioral, neurophysiological, and effective connectivity metrics. Although, many studies have focused on behavioral effects of executive function processes individually, few studies have examined the dynamic causal interactions between these two functions. A total of twenty participants from a local university performed a dual task combing flanker and n-back experimental paradigms, and completed the Operation Span Task designed to measure working memory capacity. We found that both behavioral (accuracy and reaction time) and neurophysiological (P300 amplitude and alpha band power) metrics on the inhibition task (i.e., flanker task) were influenced by the updating load (n-back level) and modulated by working memory capacity. Using independent component analysis, source localization (DIPFIT), and Granger Causality analysis of the EEG time-series data, the present study demonstrated that manipulation of cognitive demand in a dual executive function task influenced the causal neural network. We compared connectivity across three updating loads (n-back levels) and found that experimental manipulation of working memory load enhanced causal connectivity of a large-scale neurocognitive network. This network contains the prefrontal and parietal cortices, which are associated with inhibition and updating executive function processes. This study has potential applications in human performance modeling and assessment of mental workload, such as the design of training materials and interfaces for those performing complex multitasking under stress.

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

PubMed

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.

Multi-load Groups Coordinated Load Control Strategy Considering Power Network Constraints

NASA Astrophysics Data System (ADS)

Liu, Meng; Zhao, Binchao; Wang, Jun; Zhang, Guohui; Wang, Xin

2017-05-01

Loads with energy storage property can actively participate in power balance for power systems, this paper takes air conditioner as a controllable load example, proposing a multi-load groups coordinated load control strategy considering power network constraints. Firstly, two load control modes considering recovery of load diversity are designed, blocking power oscillation of aggregated air conditioners. As the same time, air conditioner temperature setpoint recovery control strategy is presented to avoid power recovery peak. Considering inherent characteristics of two load control modes, an coordinated load control mode is designed by combining the both. Basing on this, a multi-load groups coordinated load control strategy is proposed. During the implementing of load control, power network constraints should be satisfied. An indice which can reflect the security of power system operating is defined. By minimizing its value through optimization, the change of air conditioning loads’ aggregated power on each load bus can be calculated. Simulations are conducted on an air conditioners group and New England 10-generator 39-bus system, verifying the effectiveness of the proposed multi-load groups coordinated load control strategy considering power network constraints.

Fast packet switching algorithms for dynamic resource control over ATM networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tsang, R.P.; Keattihananant, P.; Chang, T.

1996-12-01

Real-time continuous media traffic, such as digital video and audio, is expected to comprise a large percentage of the network load on future high speed packet switch networks such as ATM. A major feature which distinguishes high speed networks from traditional slower speed networks is the large amount of data the network must process very quickly. For efficient network usage, traffic control mechanisms are essential. Currently, most mechanisms for traffic control (such as flow control) have centered on the support of Available Bit Rate (ABR), i.e., non real-time, traffic. With regard to ATM, for ABR traffic, two major types ofmore » schemes which have been proposed are rate- control and credit-control schemes. Neither of these schemes are directly applicable to Real-time Variable Bit Rate (VBR) traffic such as continuous media traffic. Traffic control for continuous media traffic is an inherently difficult problem due to the time- sensitive nature of the traffic and its unpredictable burstiness. In this study, we present a scheme which controls traffic by dynamically allocating/de- allocating resources among competing VCs based upon their real-time requirements. This scheme incorporates a form of rate- control, real-time burst-level scheduling and link-link flow control. We show analytically potential performance improvements of our rate- control scheme and present a scheme for buffer dimensioning. We also present simulation results of our schemes and discuss the tradeoffs inherent in maintaining high network utilization and statistically guaranteeing many users` Quality of Service.« less

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

PubMed Central

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

Theory of Cooperative Activated Structural Relaxation in Polymer Nanocomposites Composed of Small and Sticky Particles

NASA Astrophysics Data System (ADS)

Xie, Shijie; Schweizer, Kenneth

Recently, Cheng, Sokolov and coworkers have discovered qualitatively new dynamic behavior (exceptionally large Tg and fragility increases, unusual thermal and viscoelastic responses) in polymer nanocomposites composed of nanoparticles comparable in size to a polymer segment which form physical bonds with both themselves and segments. We generalize the Elastically Collective Nonlinear Langevin Equation theory of deeply supercooled molecular and polymer liquids to study the cooperative activated hopping dynamics of this system based on the dynamic free energy surface concept. The theoretical calculations are consistent with segmental relaxation time measurements as a function of temperature and nanoparticle volume fraction, and also the nearly linear growth of Tg with NP loading; predictions are made for the influence of nonuniversal chemical effects. The theory suggests the alpha process involves strongly coupled activated motion of segments and nanoparticles, consistent with the observed negligible change of the heat capacity jump with filler loading. Based on cohesive energy calculations and transient network ideas, full structural relaxation is suggested to involve a second, slower bond dissociation process with distinctive features and implications.

Assembly of the MHC I peptide-loading complex determined by a conserved ionic lock-switch

PubMed Central

Blees, Andreas; Reichel, Katrin; Trowitzsch, Simon; Fisette, Olivier; Bock, Christoph; Abele, Rupert; Hummer, Gerhard; Schäfer, Lars V.; Tampé, Robert

2015-01-01

Salt bridges in lipid bilayers play a decisive role in the dynamic assembly and downstream signaling of the natural killer and T-cell receptors. Here, we describe the identification of an inter-subunit salt bridge in the membrane within yet another key component of the immune system, the peptide-loading complex (PLC). The PLC regulates cell surface presentation of self-antigens and antigenic peptides via molecules of the major histocompatibility complex class I. We demonstrate that a single salt bridge in the membrane between the transporter associated with antigen processing TAP and the MHC I-specific chaperone tapasin is essential for the assembly of the PLC and for efficient MHC I antigen presentation. Molecular modeling and all-atom molecular dynamics simulations suggest an ionic lock-switch mechanism for the binding of TAP to tapasin, in which an unfavorable uncompensated charge in the ER-membrane is prevented through complex formation. Our findings not only deepen the understanding of the interaction network within the PLC, but also provide evidence for a general interaction principle of dynamic multiprotein membrane complexes in immunity. PMID:26611325

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dall'Anese, Emiliano

Past works that focused on addressing power-quality and reliability concerns related to renewable energy resources (RESs) operating with business-as-usual practices have looked at the design of Volt/VAr and Volt/Watt strategies to regulate real or reactive powers based on local voltage measurements, so that terminal voltages are within acceptable levels. These control strategies have the potential of operating at the same time scale of distribution-system dynamics, and can therefore mitigate disturbances precipitated fast time-varying loads and ambient conditions; however, they do not necessarily guarantee system-level optimality, and stability claims are mainly based on empirical evidences. On a different time scale, centralizedmore » and distributed optimal power flow (OPF) algorithms have been proposed to compute optimal steady-state inverter setpoints, so that power losses and voltage deviations are minimized and economic benefits to end-users providing ancillary services are maximized. However, traditional OPF schemes may offer decision making capabilities that do not match the dynamics of distribution systems. Particularly, during the time required to collect data from all the nodes of the network (e.g., loads), solve the OPF, and subsequently dispatch setpoints, the underlying load, ambient, and network conditions may have already changed; in this case, the DER output powers would be consistently regulated around outdated setpoints, leading to suboptimal system operation and violation of relevant electrical limits. The present work focuses on the synthesis of distributed RES-inverter controllers that leverage the opportunities for fast feedback offered by power-electronics interfaced RESs. The overarching objective is to bridge the temporal gap between long-term system optimization and real-time control, to enable seamless RES integration in large scale with stability and efficiency guarantees, while congruently pursuing system-level optimization objectives. The design of the control framework is based on suitable linear approximations of the AC power-flow equations as well as Lagrangian regularization methods. The proposed controllers enable an update of the power outputs at a time scale that is compatible with the underlying dynamics of loads and ambient conditions, and continuously drive the system operation towards OPF-based solutions.« less

A micro-mechanical model to determine changes of collagen fibrils under cyclic loading

NASA Astrophysics Data System (ADS)

Chen, Michelle L.; Susilo, Monica E.; Ruberti, Jeffrey A.; Nguyen, Thao D.

Dynamic mechanical loading induces growth and remodeling in biological tissues. It can alter the degradation rate and intrinsic mechanical properties of collagen through cellular activity. Experiments showed that repeated cyclic loading of a dense collagen fibril substrate increased collagen stiffness and strength, lengthened the substrate, but did not significantly change the fibril areal fraction or fibril anisotropy (Susilo, et al. ``Collagen Network Hardening Following Cyclic Tensile Loading'', Interface Focus, submitted). We developed a model for the collagen fibril substrate (Tonge, et al. ``A micromechanical modeling study of the mechanical stabilization of enzymatic degradation of collagen tissues'', Biophys J, in press.) to probe whether changes in the fibril morphology and mechanical properties can explain the tissue-level properties observed during cyclic loading. The fibrils were modeled as a continuous distribution of wavy elastica, based on experimental measurements of fibril density and collagen anisotropy, and can experience damage after a critical stress threshold. Other mechanical properties in the model were fit to the stress response measured before and after the extended cyclic loading to determine changes in the strength and stiffness of collagen fibrils.

Design and implementation of streaming media server cluster based on FFMpeg.

PubMed

Zhao, Hong; Zhou, Chun-long; Jin, Bao-zhao

2015-01-01

Poor performance and network congestion are commonly observed in the streaming media single server system. This paper proposes a scheme to construct a streaming media server cluster system based on FFMpeg. In this scheme, different users are distributed to different servers according to their locations and the balance among servers is maintained by the dynamic load-balancing algorithm based on active feedback. Furthermore, a service redirection algorithm is proposed to improve the transmission efficiency of streaming media data. The experiment results show that the server cluster system has significantly alleviated the network congestion and improved the performance in comparison with the single server system.

Design and Implementation of Streaming Media Server Cluster Based on FFMpeg

PubMed Central

Zhao, Hong; Zhou, Chun-long; Jin, Bao-zhao

2015-01-01

Poor performance and network congestion are commonly observed in the streaming media single server system. This paper proposes a scheme to construct a streaming media server cluster system based on FFMpeg. In this scheme, different users are distributed to different servers according to their locations and the balance among servers is maintained by the dynamic load-balancing algorithm based on active feedback. Furthermore, a service redirection algorithm is proposed to improve the transmission efficiency of streaming media data. The experiment results show that the server cluster system has significantly alleviated the network congestion and improved the performance in comparison with the single server system. PMID:25734187

Improving the energy efficiency of telecommunication networks

NASA Astrophysics Data System (ADS)

Lange, Christoph; Gladisch, Andreas

2011-05-01

The energy consumption of telecommunication networks has gained increasing interest throughout the recent past: Besides its environmental implications it has been identified to be a major contributor to operational expenditures of network operators. Targeting at sustainable telecommunication networks, thus, it is important to find appropriate strategies for improving their energy efficiency before the background of rapidly increasing traffic volumes. Besides the obvious benefits of increasing energy efficiency of network elements by leveraging technology progress, load-adaptive network operation is a very promising option, i.e. using network resources only to an extent and for the time they are actually needed. In contrast, current network operation takes almost no advantage of the strongly time-variant behaviour of the network traffic load. Mechanisms for energy-aware load-adaptive network operation can be subdivided in techniques based on local autonomous or per-link decisions and in techniques relying on coordinated decisions incorporating information from several links. For the transformation from current network structures and operation paradigms towards energy-efficient and sustainable networks it will be essential to use energy-optimized network elements as well as including the overall energy consumption in network design and planning phases together with the energy-aware load-adaptive operation. In load-adaptive operation it will be important to establish the optimum balance between local and overarching power management concepts in telecommunication networks.

Network coding based joint signaling and dynamic bandwidth allocation scheme for inter optical network unit communication in passive optical networks

NASA Astrophysics Data System (ADS)

Wei, Pei; Gu, Rentao; Ji, Yuefeng

2014-06-01

As an innovative and promising technology, network coding has been introduced to passive optical networks (PON) in recent years to support inter optical network unit (ONU) communication, yet the signaling process and dynamic bandwidth allocation (DBA) in PON with network coding (NC-PON) still need further study. Thus, we propose a joint signaling and DBA scheme for efficiently supporting differentiated services of inter ONU communication in NC-PON. In the proposed joint scheme, the signaling process lays the foundation to fulfill network coding in PON, and it can not only avoid the potential threat to downstream security in previous schemes but also be suitable for the proposed hybrid dynamic bandwidth allocation (HDBA) scheme. In HDBA, a DBA cycle is divided into two sub-cycles for applying different coding, scheduling and bandwidth allocation strategies to differentiated classes of services. Besides, as network traffic load varies, the entire upstream transmission window for all REPORT messages slides accordingly, leaving the transmission time of one or two sub-cycles to overlap with the bandwidth allocation calculation time at the optical line terminal (the OLT), so that the upstream idle time can be efficiently eliminated. Performance evaluation results validate that compared with the existing two DBA algorithms deployed in NC-PON, HDBA demonstrates the best quality of service (QoS) support in terms of delay for all classes of services, especially guarantees the end-to-end delay bound of high class services. Specifically, HDBA can eliminate queuing delay and scheduling delay of high class services, reduce those of lower class services by at least 20%, and reduce the average end-to-end delay of all services over 50%. Moreover, HDBA also achieves the maximum delay fairness between coded and uncoded lower class services, and medium delay fairness for high class services.

Robustness Elasticity in Complex Networks

PubMed Central

Matisziw, Timothy C.; Grubesic, Tony H.; Guo, Junyu

2012-01-01

Network robustness refers to a network’s resilience to stress or damage. Given that most networks are inherently dynamic, with changing topology, loads, and operational states, their robustness is also likely subject to change. However, in most analyses of network structure, it is assumed that interaction among nodes has no effect on robustness. To investigate the hypothesis that network robustness is not sensitive or elastic to the level of interaction (or flow) among network nodes, this paper explores the impacts of network disruption, namely arc deletion, over a temporal sequence of observed nodal interactions for a large Internet backbone system. In particular, a mathematical programming approach is used to identify exact bounds on robustness to arc deletion for each epoch of nodal interaction. Elasticity of the identified bounds relative to the magnitude of arc deletion is assessed. Results indicate that system robustness can be highly elastic to spatial and temporal variations in nodal interactions within complex systems. Further, the presence of this elasticity provides evidence that a failure to account for nodal interaction can confound characterizations of complex networked systems. PMID:22808060

Adaptive integral dynamic surface control of a hypersonic flight vehicle

NASA Astrophysics Data System (ADS)

Aslam Butt, Waseem; Yan, Lin; Amezquita S., Kendrick

2015-07-01

In this article, non-linear adaptive dynamic surface air speed and flight path angle control designs are presented for the longitudinal dynamics of a flexible hypersonic flight vehicle. The tracking performance of the control design is enhanced by introducing a novel integral term that caters to avoiding a large initial control signal. To ensure feasibility, the design scheme incorporates magnitude and rate constraints on the actuator commands. The uncertain non-linear functions are approximated by an efficient use of the neural networks to reduce the computational load. A detailed stability analysis shows that all closed-loop signals are uniformly ultimately bounded and the ? tracking performance is guaranteed. The robustness of the design scheme is verified through numerical simulations of the flexible flight vehicle model.

Simulation of short-term electric load using an artificial neural network

NASA Astrophysics Data System (ADS)

Ivanin, O. A.

2018-01-01

While solving the task of optimizing operation modes and equipment composition of small energy complexes or other tasks connected with energy planning, it is necessary to have data on energy loads of a consumer. Usually, there is a problem with obtaining real load charts and detailed information about the consumer, because a method of load-charts simulation on the basis of minimal information should be developed. The analysis of work devoted to short-term loads prediction allows choosing artificial neural networks as a most suitable mathematical instrument for solving this problem. The article provides an overview of applied short-term load simulation methods; it describes the advantages of artificial neural networks and offers a neural network structure for electric loads of residential buildings simulation. The results of modeling loads with proposed method and the estimation of its error are presented.

Event-triggered synchronization for reaction-diffusion complex networks via random sampling

NASA Astrophysics Data System (ADS)

Dong, Tao; Wang, Aijuan; Zhu, Huiyun; Liao, Xiaofeng

2018-04-01

In this paper, the synchronization problem of the reaction-diffusion complex networks (RDCNs) with Dirichlet boundary conditions is considered, where the data is sampled randomly. An event-triggered controller based on the sampled data is proposed, which can reduce the number of controller and the communication load. Under this strategy, the synchronization problem of the diffusion complex network is equivalently converted to the stability of a of reaction-diffusion complex dynamical systems with time delay. By using the matrix inequality technique and Lyapunov method, the synchronization conditions of the RDCNs are derived, which are dependent on the diffusion term. Moreover, it is found the proposed control strategy can get rid of the Zeno behavior naturally. Finally, a numerical example is given to verify the obtained results.

Interlayer shear behaviors of graphene-carbon nanotube network

NASA Astrophysics Data System (ADS)

Qin, Huasong; Liu, Yilun

2017-09-01

The interlayer shear resistance plays an important role in graphene related applications, and different mechanisms have been proposed to enhance its interlayer load capacity. In this work, we performed molecular dynamics (MD) simulations and theoretical analysis to study interlayer shear behaviors of three dimensional graphene-carbon (3D-GC) nanotube networks. The shear mechanical properties of carbon nanotubes (CNTs) crosslink with different diameters are obtained which is one order of magnitude larger than that of other types of crosslinks. Under shear loading, 3D-GC exhibits two failure modes, i.e., fracture of graphene sheet and failure of CNT crosslink, determined by the diameter of CNT crosslink, crosslink density, and length of 3D-GC. A modified tension-shear chain model is proposed to predict the shear mechanical properties and failure mode of 3D-GC, which agrees well with MD simulation results. The results presented in this work may provide useful insights for future development of high-performance 3D-GC materials.

Dynamic Hierarchical Energy-Efficient Method Based on Combinatorial Optimization for Wireless Sensor Networks

PubMed Central

Tang, Hongying; Cheng, Yongbo; Zhao, Qin; Li, Baoqing; Yuan, Xiaobing

2017-01-01

Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN routing protocols, we propose a dynamic hierarchical protocol based on combinatorial optimization (DHCO) to balance energy consumption of sensor nodes and to improve WSN longevity. For each sensor node, the DHCO algorithm obtains the optimal route by establishing a feasible routing set instead of selecting the cluster head or the next hop node. The process of obtaining the optimal route can be formulated as a combinatorial optimization problem. Specifically, the DHCO algorithm is carried out by the following procedures. It employs a hierarchy-based connection mechanism to construct a hierarchical network structure in which each sensor node is assigned to a special hierarchical subset; it utilizes the combinatorial optimization theory to establish the feasible routing set for each sensor node, and takes advantage of the maximum–minimum criterion to obtain their optimal routes to the base station. Various results of simulation experiments show effectiveness and superiority of the DHCO algorithm in comparison with state-of-the-art WSN routing algorithms, including low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), genetic protocol-based self-organizing network clustering (GASONeC), and double cost function-based routing (DCFR) algorithms. PMID:28753962

Ongoing activity in temporally coherent networks predicts intra-subject fluctuation of response time to sporadic executive control demands.

PubMed

Nozawa, Takayuki; Sugiura, Motoaki; Yokoyama, Ryoichi; Ihara, Mizuki; Kotozaki, Yuka; Miyauchi, Carlos Makoto; Kanno, Akitake; Kawashima, Ryuta

2014-01-01

Can ongoing fMRI BOLD signals predict fluctuations in swiftness of a person's response to sporadic cognitive demands? This is an important issue because it clarifies whether intrinsic brain dynamics, for which spatio-temporal patterns are expressed as temporally coherent networks (TCNs), have effects not only on sensory or motor processes, but also on cognitive processes. Predictivity has been affirmed, although to a limited extent. Expecting a predictive effect on executive performance for a wider range of TCNs constituting the cingulo-opercular, fronto-parietal, and default mode networks, we conducted an fMRI study using a version of the color-word Stroop task that was specifically designed to put a higher load on executive control, with the aim of making its fluctuations more detectable. We explored the relationships between the fluctuations in ongoing pre-trial activity in TCNs and the task response time (RT). The results revealed the existence of TCNs in which fluctuations in activity several seconds before the onset of the trial predicted RT fluctuations for the subsequent trial. These TCNs were distributed in the cingulo-opercular and fronto-parietal networks, as well as in perceptual and motor networks. Our results suggest that intrinsic brain dynamics in these networks constitute "cognitive readiness," which plays an active role especially in situations where information for anticipatory attention control is unavailable. Fluctuations in these networks lead to fluctuations in executive control performance.

Retrieval Property of Attractor Network with Synaptic Depression

NASA Astrophysics Data System (ADS)

Matsumoto, Narihisa; Ide, Daisuke; Watanabe, Masataka; Okada, Masato

2007-08-01

Synaptic connections are known to change dynamically. High-frequency presynaptic inputs induce decrease of synaptic weights. This process is known as short-term synaptic depression. The synaptic depression controls a gain for presynaptic inputs. However, it remains a controversial issue what are functional roles of this gain control. We propose a new hypothesis that one of the functional roles is to enlarge basins of attraction. To verify this hypothesis, we employ a binary discrete-time associative memory model which consists of excitatory and inhibitory neurons. It is known that the excitatory-inhibitory balance controls an overall activity of the network. The synaptic depression might incorporate an activity control mechanism. Using a mean-field theory and computer simulations, we find that the synaptic depression enlarges the basins at a small loading rate while the excitatory-inhibitory balance enlarges them at a large loading rate. Furthermore the synaptic depression does not affect the steady state of the network if a threshold is set at an appropriate value. These results suggest that the synaptic depression works in addition to the effect of the excitatory-inhibitory balance, and it might improve an error-correcting ability in cortical circuits.

Implementation of Parallel Dynamic Simulation on Shared-Memory vs. Distributed-Memory Environments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jin, Shuangshuang; Chen, Yousu; Wu, Di

2015-12-09

Power system dynamic simulation computes the system response to a sequence of large disturbance, such as sudden changes in generation or load, or a network short circuit followed by protective branch switching operation. It consists of a large set of differential and algebraic equations, which is computational intensive and challenging to solve using single-processor based dynamic simulation solution. High-performance computing (HPC) based parallel computing is a very promising technology to speed up the computation and facilitate the simulation process. This paper presents two different parallel implementations of power grid dynamic simulation using Open Multi-processing (OpenMP) on shared-memory platform, and Messagemore » Passing Interface (MPI) on distributed-memory clusters, respectively. The difference of the parallel simulation algorithms and architectures of the two HPC technologies are illustrated, and their performances for running parallel dynamic simulation are compared and demonstrated.« less

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

NASA Astrophysics Data System (ADS)

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 monitoring sensors. In order to maintain signal quality while optimizing network resources, we find that it is essential to model and update estimates of the physical link impairments in real-time. In this thesis, we consider the key elements required to enable an agile optical network, with contributions as follows: • Control Framework: extended the SDN concept to include the optical transport network through extensions to the OpenFlow (OF) protocol. A unified SDN control plane is built to facilitate control and management capability across the electrical/packet-switched and optical/circuit-switched portions of the network seamlessly. The SDN control plane serves as a platform to abstract the resources of multilayer/multivendor networks. Through this platform, applications can dynamically request the network resources to meet their service requirements. • Use of In-situ Monitors: enabled real-time physical impairment sensing in the control plane using in-situ Optical Performance Monitoring (OPM) and bit error rate (BER) analyzers. OPM and BER values are used as quantitative indicators of the link status and are fed to the control plane through a high-speed data collection interface to form a closed-loop feedback system to enable adaptive resource allocation. • Predictive Network Model: used a network model embedded in the control layer to study the link status. The estimated results of network status is fed into the control decisions to precompute the network resources. The performance of the network model can be enhanced by the sensing results. • Real-Time Control Algorithms: investigated various dynamic resource allocation mechanisms supporting an agile optical network. Intelligent routing and wavelength switching for recovering from traffic impairments is achieved experimentally in the agile optical network within one second. A distance-adaptive spectrum allocation scheme to address transmission impairments caused by cascaded Wavelength Selective Switches (WSS) is proposed and evaluated for improving network spectral efficiency.

An adaptive two-stage energy-efficiency mechanism for the doze mode in EPON

NASA Astrophysics Data System (ADS)

Nikoukar, AliAkbar; Hwang, I.-Shyan; Su, Yu-Min; Liem, Andrew Tanny

2016-07-01

Sleep and doze power-saving modes are the common ways to reduce power consumption of optical network units (ONUs) in Ethernet passive optical network (EPON). The doze mode turns off the ONU transmitter when there is no traffic in the upstream direction while the sleep mode turns off the ONU transmitter and receiver. As the result, the sleep mode is more efficient compared to the doze mode, but it introduces additional complexity of scheduling and signaling, losses the clock synchronization and requires long clock recovery time; furthermore, it requires the cooperation of the optical line terminal (OLT) in the downstream direction to queue frames. To improve the energy-saving in the doze mode, a new two-stage mechanism is introduced that the doze sleep duration is extended for longer time with acceptable quality-of-services (QoS) metrics when ONU is idle in the current cycle. By this way the ONU enters the doze mode even in the high load traffic; moreover, the green dynamic bandwidth allocation (GBA) is proposed to calculate the doze sleep duration based on the ONU queue state and incoming traffic ratio. Simulation results show that the proposed mechanism significantly improves the energy-saving 74% and 54% when traffic load is from the light load to the high load in different traffic situations, and also promises the QoS performance.

Human initiated cascading failures in societal infrastructures.

PubMed

Barrett, Chris; Channakeshava, Karthik; Huang, Fei; Kim, Junwhan; Marathe, Achla; Marathe, Madhav V; Pei, Guanhong; Saha, Sudip; Subbiah, Balaaji S P; Vullikanti, Anil Kumar S

2012-01-01

In this paper, we conduct a systematic study of human-initiated cascading failures in three critical inter-dependent societal infrastructures due to behavioral adaptations in response to a crisis. We focus on three closely coupled socio-technical networks here: (i) cellular and mesh networks, (ii) transportation networks and (iii) mobile call networks. In crises, changes in individual behaviors lead to altered travel, activity and calling patterns, which influence the transport network and the loads on wireless networks. The interaction between these systems and their co-evolution poses significant technical challenges for representing and reasoning about these systems. In contrast to system dynamics models for studying these interacting infrastructures, we develop interaction-based models in which individuals and infrastructure elements are represented in detail and are placed in a common geographic coordinate system. Using the detailed representation, we study the impact of a chemical plume that has been released in a densely populated urban region. Authorities order evacuation of the affected area, and this leads to individual behavioral adaptation wherein individuals drop their scheduled activities and drive to home or pre-specified evacuation shelters as appropriate. They also revise their calling behavior to communicate and coordinate among family members. These two behavioral adaptations cause flash-congestion in the urban transport network and the wireless network. The problem is exacerbated with a few, already occurring, road closures. We analyze how extended periods of unanticipated road congestion can result in failure of infrastructures, starting with the servicing base stations in the congested area. A sensitivity analysis on the compliance rate of evacuees shows non-intuitive effect on the spatial distribution of people and on the loading of the base stations. For example, an evacuation compliance rate of 70% results in higher number of overloaded base stations than the evacuation compliance rate of 90%.

Human Initiated Cascading Failures in Societal Infrastructures

PubMed Central

Barrett, Chris; Channakeshava, Karthik; Huang, Fei; Kim, Junwhan; Marathe, Achla; Marathe, Madhav V.; Pei, Guanhong; Saha, Sudip; Subbiah, Balaaji S. P.; Vullikanti, Anil Kumar S.

2012-01-01

In this paper, we conduct a systematic study of human-initiated cascading failures in three critical inter-dependent societal infrastructures due to behavioral adaptations in response to a crisis. We focus on three closely coupled socio-technical networks here: (i) cellular and mesh networks, (ii) transportation networks and (iii) mobile call networks. In crises, changes in individual behaviors lead to altered travel, activity and calling patterns, which influence the transport network and the loads on wireless networks. The interaction between these systems and their co-evolution poses significant technical challenges for representing and reasoning about these systems. In contrast to system dynamics models for studying these interacting infrastructures, we develop interaction-based models in which individuals and infrastructure elements are represented in detail and are placed in a common geographic coordinate system. Using the detailed representation, we study the impact of a chemical plume that has been released in a densely populated urban region. Authorities order evacuation of the affected area, and this leads to individual behavioral adaptation wherein individuals drop their scheduled activities and drive to home or pre-specified evacuation shelters as appropriate. They also revise their calling behavior to communicate and coordinate among family members. These two behavioral adaptations cause flash-congestion in the urban transport network and the wireless network. The problem is exacerbated with a few, already occurring, road closures. We analyze how extended periods of unanticipated road congestion can result in failure of infrastructures, starting with the servicing base stations in the congested area. A sensitivity analysis on the compliance rate of evacuees shows non-intuitive effect on the spatial distribution of people and on the loading of the base stations. For example, an evacuation compliance rate of 70% results in higher number of overloaded base stations than the evacuation compliance rate of 90%. PMID:23118847

Reduced Nucleus Pulposus Glycosaminoglycan Content Alters Intervertebral Disc Dynamic Viscoelastic Mechanics

PubMed Central

Boxberger, John I.; Orlansky, Amy S.; Sen, Sounok; Elliott, Dawn M.

2009-01-01

The intervertebral disc functions over a range of dynamic loading regimes including axial loads applied across a spectrum of frequencies at varying compressive loads. Biochemical changes occurring in early degeneration, including reduced nucleus pulposus glycosaminoglycan content, may alter disc mechanical behavior and thus may contribute to the progression of degeneration. The objective of this study was to determine disc dynamic viscoelastic properties under several equilibrium loads and loading frequencies, and further, to determine how reduced nucleus glycosaminglycan content alters dynamic mechanics. We hypothesized (1) that dynamic stiffness would be elevated with increasing equilibrium load and increasing frequency, (2) that the disc would behave more elastically at higher frequencies, and finally, (3) that dynamic stiffness would be reduced at low equilibrium loads under all frequencies due to nucleus glycosaminoglycan loss. We mechanically tested control and chondroitinase-ABC injected rat lumbar motion segments at several equilibrium loads using oscillatory loading at frequencies ranging from 0.05 to 5 Hz. The rat lumbar disc behaved non-linearly with higher dynamic stiffness at elevated compressive loads irrespective of frequency. Phase angle was not affected by equilibrium load, although it decreased as frequency was increased. Reduced glycosaminoglycan decreased dynamic stiffness at low loads but not at high equilibrium loads and led to increased phase angle at all loads and frequencies. The findings of this study demonstrate the effect of equilibrium load and loading frequencies on dynamic disc mechanics and indicate possible mechanical mechanisms through which disc degeneration can progress. PMID:19539936

Modeling and distributed gain scheduling strategy for load frequency control in smart grids with communication topology changes.

PubMed

Liu, Shichao; Liu, Xiaoping P; El Saddik, Abdulmotaleb

2014-03-01

In this paper, we investigate the modeling and distributed control problems for the load frequency control (LFC) in a smart grid. In contrast with existing works, we consider more practical and real scenarios, where the communication topology of the smart grid changes because of either link failures or packet losses. These topology changes are modeled as a time-varying communication topology matrix. By using this matrix, a new closed-loop power system model is proposed to integrate the communication topology changes into the dynamics of a physical power system. The globally asymptotical stability of this closed-loop power system is analyzed. A distributed gain scheduling LFC strategy is proposed to compensate for the potential degradation of dynamic performance (mean square errors of state vectors) of the power system under communication topology changes. In comparison to conventional centralized control approaches, the proposed method can improve the robustness of the smart grid to the variation of the communication network as well as to reduce computation load. Simulation results show that the proposed distributed gain scheduling approach is capable to improve the robustness of the smart grid to communication topology changes. © 2013 ISA. Published by ISA. All rights reserved.

Scaling of load in communications networks.

PubMed

Narayan, Onuttom; Saniee, Iraj

2010-09-01

We show that the load at each node in a preferential attachment network scales as a power of the degree of the node. For a network whose degree distribution is p(k)∼k{-γ} , we show that the load is l(k)∼k{η} with η=γ-1 , implying that the probability distribution for the load is p(l)∼1/l{2} independent of γ . The results are obtained through scaling arguments supported by finite size scaling studies. They contradict earlier claims, but are in agreement with the exact solution for the special case of tree graphs. Results are also presented for real communications networks at the IP layer, using the latest available data. Our analysis of the data shows relatively poor power-law degree distributions as compared to the scaling of the load versus degree. This emphasizes the importance of the load in network analysis.

Ocean dynamics during the passage of Xynthia storm recorded by GPS

NASA Astrophysics Data System (ADS)

Nicolas, Joëlle; Ferenc, Marcell; Li, Zhao; van Dam, Tonie; Polidori, Laurent

2014-05-01

When computing the effect of atmospheric loading on geodetic coordinates, we must assign the response of the ocean to pressure loading. A pure inverted barometer and a solid Earth ocean response to pressure loading define the extremes of the response. At periods longer than a few days, the inverted barometer response is sufficient (Wunsch and Stammer, 1997). However, how does the ocean respond to fast moving storms? In this study we investigate the effect of a violent storm that progressed over Western Europe between the 27th of February and the 1st of March 2010 on sub-daily vertical GPS (Global Positioning System) position time series of the French GNSS permanent network (RGP). Xynthia was a huge low-pressure system (pressure drop of 40 mbar and a storm surge of 1.4 m (at La Rochelle tide gauge)) that crossed France from the southwest to the northeast over the course of about 20 hours. We study the different behaviour of the coastal and inland sites based on the comparison of the estimated 6-hourly stand-alone GPS position time series (GINS-PC software) with the local pressure and the predicted atmospheric pressure loading time series derived from the high resolution Modern-Era Retrospective Analysis for Research and Applications (NASA MERRA) and also the European Centre for Medium-Range Weather Forecasts (ECMWF) global dataset. We model the predicted displacements using the inverse barometer (IB) and the non-IB ocean response cases as endpoints. Predicted loading effects due to the atmospheric pressure and IB ocean reach up to 1.0, 1.3 and 13.7 mm for the east, north and up components, respectively. Then we attempt to use the GPS vertical surface displacements, the surface pressure, and tide gauge data (SONEL) to identify the true ocean dynamics on the continental shelf during the passage of this fast moving system. Keywords: GPS, GINS-PC, Xynthia, ocean dynamics, atmospheric pressure loading, deformation

Ultrastable cellulosome-adhesion complex tightens under load

PubMed Central

Schoeler, Constantin; Malinowska, Klara H.; Bernardi, Rafael C.; Milles, Lukas F.; Jobst, Markus A.; Durner, Ellis; Ott, Wolfgang; Fried, Daniel B.; Bayer, Edward A.; Schulten, Klaus; Gaub, Hermann E.; Nash, Michael A.

2014-01-01

Challenging environments have guided nature in the development of ultrastable protein complexes. Specialized bacteria produce discrete multi-component protein networks called cellulosomes to effectively digest lignocellulosic biomass. While network assembly is enabled by protein interactions with commonplace affinities, we show that certain cellulosomal ligand–receptor interactions exhibit extreme resistance to applied force. Here, we characterize the ligand–receptor complex responsible for substrate anchoring in the Ruminococcus flavefaciens cellulosome using single-molecule force spectroscopy and steered molecular dynamics simulations. The complex withstands forces of 600–750 pN, making it one of the strongest bimolecular interactions reported, equivalent to half the mechanical strength of a covalent bond. Our findings demonstrate force activation and inter-domain stabilization of the complex, and suggest that certain network components serve as mechanical effectors for maintaining network integrity. This detailed understanding of cellulosomal network components may help in the development of biocatalysts for production of fuels and chemicals from renewable plant-derived biomass. PMID:25482395

Influence of linear profile modification and loading conditions on the dynamic tooth load and stress of high contact ratio gears

NASA Technical Reports Server (NTRS)

Lee, Chinwai; Lin, Hsiang Hsi; Oswald, Fred B.; Townsend, Dennis P.

1990-01-01

A computer simulation for the dynamic response of high-contact-ratio spur gear transmissions is presented. High contact ratio gears have the potential to produce lower dynamic tooth loads and minimum root stress but they can be sensitive to tooth profile errors. The analysis presented examines various profile modifications under realistic loading conditions. The effect of these modifications on the dynamic load (force) between mating gear teeth and the dynamic root stress is presented. Since the contact stress is dependent on the dynamic load, minimizing dynamic loads will also minimize contact stresses. It is shown that the combination of profile modification and the applied load (torque) carried by a gear system has a significant influence on gear dynamics. The ideal modification at one value of applied load will not be the best solution for a different load. High-contact-ratio gears were found to require less modification than standard low-contact-ratio gears. High-contact-ratio gears are more adversely affected by excess modification than by under modification. In addition, the optimal profile modification required to minimize the dynamic load (hence the contact stress) on a gear tooth differs from the optimal modification required to minimize the dynamic root (bending) stress. Computer simulation can help find the design tradeoffs to determine the best profile modification to satisfy the conflicting constraints of minimizing both the load and root stress in gears which must operate over a range of applied loads.

Core networks and their reconfiguration patterns across cognitive loads.

PubMed

Zuo, Nianming; Yang, Zhengyi; Liu, Yong; Li, Jin; Jiang, Tianzi

2018-04-20

Different cognitively demanding tasks recruit globally distributed but functionally specific networks. However, the configuration of core networks and their reconfiguration patterns across cognitive loads remain unclear, as does whether these patterns are indicators for the performance of cognitive tasks. In this study, we analyzed functional magnetic resonance imaging data of a large cohort of 448 subjects, acquired with the brain at resting state and executing N-back working memory (WM) tasks. We discriminated core networks by functional interaction strength and connection flexibility. Results demonstrated that the frontoparietal network (FPN) and default mode network (DMN) were core networks, but each exhibited different patterns across cognitive loads. The FPN and DMN both showed strengthened internal connections at the low demand state (0-back) compared with the resting state (control level); whereas, from the low (0-back) to high demand state (2-back), some connections to the FPN weakened and were rewired to the DMN (whose connections all remained strong). Of note, more intensive reconfiguration of both the whole brain and core networks (but no other networks) across load levels indicated relatively poor cognitive performance. Collectively these findings indicate that the FPN and DMN have distinct roles and reconfiguration patterns across cognitively demanding loads. This study advances our understanding of the core networks and their reconfiguration patterns across cognitive loads and provides a new feature to evaluate and predict cognitive capability (e.g., WM performance) based on brain networks. © 2018 Wiley Periodicals, Inc.

A Novel Interfacing Technique for Distributed Hybrid Simulations Combining EMT and Transient Stability Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shu, Dewu; Xie, Xiaorong; Jiang, Qirong

With steady increase of power electronic devices and nonlinear dynamic loads in large scale AC/DC systems, the traditional hybrid simulation method, which incorporates these components into a single EMT subsystem and hence causes great difficulty for network partitioning and significant deterioration in simulation efficiency. To resolve these issues, a novel distributed hybrid simulation method is proposed in this paper. The key to realize this method is a distinct interfacing technique, which includes: i) a new approach based on the two-level Schur complement to update the interfaces by taking full consideration of the couplings between different EMT subsystems; and ii) amore » combined interaction protocol to further improve the efficiency while guaranteeing the simulation accuracy. The advantages of the proposed method in terms of both efficiency and accuracy have been verified by using it for the simulation study of an AC/DC hybrid system including a two-terminal VSC-HVDC and nonlinear dynamic loads.« less

Online Structural-Health Monitoring of Glass Fiber-Reinforced Thermoplastics Using Different Carbon Allotropes in the Interphase.

PubMed

Müller, Michael Thomas; Pötzsch, Hendrik Florian; Gohs, Uwe; Heinrich, Gert

2018-06-25

An electromechanical response behavior is realized by nanostructuring the glass fiber interphase with different highly electrically conductive carbon allotropes like carbon nanotubes (CNT), graphene nanoplatelets (GNP), or conductive carbon black (CB). The operational capability of these multifunctional glass fibers for an online structural-health monitoring is demonstrated in endless glass fiber-reinforced polypropylene. The electromechanical response behavior, during a static or dynamic three-point bending test of various carbon modifications, shows qualitative differences in the signal quality and sensitivity due to the different aspect ratios of the nanoparticles and the associated electrically conductive network densities in the interphase. Depending on the embedding position within the glass fiber-reinforced composite compression, shear and tension loadings of the fibers can be distinguished by different characteristics of the corresponding electrical signal. The occurrence of irreversible signal changes during the dynamic loading can be attributed to filler reorientation processes caused by polymer creeping or by destruction of electrically conductive paths by cracks in the glass fiber interphase.

Application of neural models as controllers in mobile robot velocity control loop

NASA Astrophysics Data System (ADS)

Cerkala, Jakub; Jadlovska, Anna

2017-01-01

This paper presents the application of an inverse neural models used as controllers in comparison to classical PI controllers for velocity tracking control task used in two-wheel, differentially driven mobile robot. The PI controller synthesis is based on linear approximation of actuators with equivalent load. In order to obtain relevant datasets for training of feed-forward multi-layer perceptron based neural network used as neural model, the mathematical model of mobile robot, that combines its kinematic and dynamic properties such as chassis dimensions, center of gravity offset, friction and actuator parameters is used. Neural models are trained off-line to act as an inverse dynamics of DC motors with particular load using data collected in simulation experiment for motor input voltage step changes within bounded operating area. The performances of PI controllers versus inverse neural models in mobile robot internal velocity control loops are demonstrated and compared in simulation experiment of navigation control task for line segment motion in plane.

Neural network based short-term load forecasting using weather compensation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chow, T.W.S.; Leung, C.T.

This paper presents a novel technique for electric load forecasting based on neural weather compensation. The proposed method is a nonlinear generalization of Box and Jenkins approach for nonstationary time-series prediction. A weather compensation neural network is implemented for one-day ahead electric load forecasting. The weather compensation neural network can accurately predict the change of actual electric load consumption from the previous day. The results, based on Hong Kong Island historical load demand, indicate that this methodology is capable of providing a more accurate load forecast with a 0.9% reduction in forecast error.

Optimal topology to minimizing congestion in connected communication complex network

NASA Astrophysics Data System (ADS)

Benyoussef, M.; Ez-Zahraouy, H.; Benyoussef, A.

In this paper, a new model of the interdependent complex network is proposed, based on two assumptions that (i) the capacity of a node depends on its degree, and (ii) the traffic load depends on the distribution of the links in the network. Based on these assumptions, the presented model proposes a method of connection not based on the node having a higher degree but on the region containing hubs. It is found that the final network exhibits two kinds of degree distribution behavior, depending on the kind and the way of the connection. This study reveals a direct relation between network structure and traffic flow. It is found that pc the point of transition between the free flow and the congested phase depends on the network structure and the degree distribution. Moreover, this new model provides an improvement in the traffic compared to the results found in a single network. The same behavior of degree distribution found in a BA network and observed in the real world is obtained; except for this model, the transition point between the free phase and congested phase is much higher than the one observed in a network of BA, for both static and dynamic protocols.

Simulation of uniaxial deformation of hexagonal crystals (Mg, Be)

NASA Astrophysics Data System (ADS)

Vlasova, A. M.; Kesarev, A. G.

2017-12-01

Molecular dynamics (MD) simulations were performed for the nanocompression loading of nanocrystalline magnesium and beryllium modeled by an interatomic potential of the embedded atom method (EAM). It is shown that the main deformation modes are prismatic slip and twinning for magnesium, and only prismatic slip for beryllium. The formation of stable configurations of dislocation grids in magnesium and beryllium was observed. Dislocation networks are formed in the habit plane of the twin in a magnesium nanocrystall. Some dislocation reactions are suggested to explain the appearance of such networks. Shockley partial dislocations in a beryllium nanocrystall form grids in the slip plane. A strong anisotropy between slip systems was observed, which is in agreement with experimental data.

Distributed control system for parallel-connected DC boost converters

DOEpatents

Goldsmith, Steven

2017-08-15

The disclosed invention is a distributed control system for operating a DC bus fed by disparate DC power sources that service a known or unknown load. The voltage sources vary in v-i characteristics and have time-varying, maximum supply capacities. Each source is connected to the bus via a boost converter, which may have different dynamic characteristics and power transfer capacities, but are controlled through PWM. The invention tracks the time-varying power sources and apportions their power contribution while maintaining the DC bus voltage within the specifications. A central digital controller solves the steady-state system for the optimal duty cycle settings that achieve a desired power supply apportionment scheme for a known or predictable DC load. A distributed networked control system is derived from the central system that utilizes communications among controllers to compute a shared estimate of the unknown time-varying load through shared bus current measurements and bus voltage measurements.

Software defined network architecture based research on load balancing strategy

NASA Astrophysics Data System (ADS)

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.

Dynamic Energy Management System for a Smart Microgrid.

PubMed

Venayagamoorthy, Ganesh Kumar; Sharma, Ratnesh K; Gautam, Prajwal K; Ahmadi, Afshin

2016-08-01

This paper presents the development of an intelligent dynamic energy management system (I-DEMS) for a smart microgrid. An evolutionary adaptive dynamic programming and reinforcement learning framework is introduced for evolving the I-DEMS online. The I-DEMS is an optimal or near-optimal DEMS capable of performing grid-connected and islanded microgrid operations. The primary sources of energy are sustainable, green, and environmentally friendly renewable energy systems (RESs), e.g., wind and solar; however, these forms of energy are uncertain and nondispatchable. Backup battery energy storage and thermal generation were used to overcome these challenges. Using the I-DEMS to schedule dispatches allowed the RESs and energy storage devices to be utilized to their maximum in order to supply the critical load at all times. Based on the microgrid's system states, the I-DEMS generates energy dispatch control signals, while a forward-looking network evaluates the dispatched control signals over time. Typical results are presented for varying generation and load profiles, and the performance of I-DEMS is compared with that of a decision tree approach-based DEMS (D-DEMS). The robust performance of the I-DEMS was illustrated by examining microgrid operations under different battery energy storage conditions.

Local Dynamic Stability Associated with Load Carrying

PubMed Central

Lockhart, Thurmon E

2013-01-01

Objectives Load carrying tasks are recognized as one of the primary occupational factors leading to slip and fall injuries. Nevertheless, the mechanisms associated with load carrying and walking stability remain illusive. The objective of the current study was to apply local dynamic stability measure in walking while carrying a load, and to investigate the possible adaptive gait stability changes. Methods Current study involved 25 young adults in a biomechanics research laboratory. One tri-axial accelerometer was used to measure three-dimensional low back acceleration during continuous treadmill walking. Local dynamic stability was quantified by the maximum Lyapunov exponent (maxLE) from a nonlinear dynamics approach. Results Long term maxLE was found to be significant higher under load condition than no-load condition in all three reference axes, indicating the declined local dynamic stability associated with load carrying. 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. PMID:23515183

Cross-layer restoration with software defined networking based on IP over optical transport networks

NASA Astrophysics Data System (ADS)

Yang, Hui; Cheng, Lei; Deng, Junni; Zhao, Yongli; Zhang, Jie; Lee, Young

2015-10-01

The IP over optical transport network is a very promising networking architecture applied to the interconnection of geographically distributed data centers due to the performance guarantee of low delay, huge bandwidth and high reliability at a low cost. It can enable efficient resource utilization and support heterogeneous bandwidth demands in highly-available, cost-effective and energy-effective manner. In case of cross-layer link failure, to ensure a high-level quality of service (QoS) for user request after the failure becomes a research focus. In this paper, we propose a novel cross-layer restoration scheme for data center services with software defined networking based on IP over optical network. The cross-layer restoration scheme can enable joint optimization of IP network and optical network resources, and enhance the data center service restoration responsiveness to the dynamic end-to-end service demands. We quantitatively evaluate the feasibility and performances through the simulation under heavy traffic load scenario in terms of path blocking probability and path restoration latency. Numeric results show that the cross-layer restoration scheme improves the recovery success rate and minimizes the overall recovery time.

Microrheology of highly crosslinked microtubule networks is dominated by force-induced crosslinker unbinding

PubMed Central

Yang, Yali; Bai, Mo; Klug, William S.; Levine, Alex J.

2012-01-01

We determine the time- and force-dependent viscoelastic responses of reconstituted networks of microtubules that have been strongly crosslinked by biotin-streptavidin bonds. To measure the microscale viscoelasticity of such networks, we use a magnetic tweezers device to apply localized forces. At short time scales, the networks respond nonlinearly to applied force, with stiffening at small forces, followed by a reduction in the stiffening response at high forces, which we attribute to the force-induced unbinding of crosslinks. At long time scales, force-induced bond unbinding leads to local network rearrangement and significant bead creep. Interestingly, the network retains its elastic modulus even under conditions of significant plastic flow, suggesting that crosslinker breakage is balanced by the formation of new bonds. To better understand this effect, we developed a finite element model of such a stiff filament network with labile crosslinkers obeying force-dependent Bell model unbinding dynamics. The coexistence of dissipation, due to bond breakage, and the elastic recovery of the network is possible because each filament has many crosslinkers. Recovery can occur as long as a sufficient number of the original crosslinkers are preserved under the loading period. When these remaining original crosslinkers are broken, plastic flow results. PMID:23577042

Impacts of demand response and renewable generation in electricity power market

NASA Astrophysics Data System (ADS)

Zhao, Zhechong

This thesis presents the objective of the research which is to analyze the impacts of uncertain wind power and demand response on power systems operation and power market clearing. First, in order to effectively utilize available wind generation, it is usually given the highest priority by assigning zero or negative energy bidding prices when clearing the day-ahead electric power market. However, when congestion occurs, negative wind bidding prices would aggravate locational marginal prices (LMPs) to be negative in certain locations. A load shifting model is explored to alleviate possible congestions and enhance the utilization of wind generation, by shifting proper amount of load from peak hours to off peaks. The problem is to determine proper amount of load to be shifted, for enhancing the utilization of wind generation, alleviating transmission congestions, and making LMPs to be non-negative values. The second piece of work considered the price-based demand response (DR) program which is a mechanism for electricity consumers to dynamically manage their energy consumption in response to time-varying electricity prices. It encourages consumers to reduce their energy consumption when electricity prices are high, and thereby reduce the peak electricity demand and alleviate the pressure to power systems. However, it brings additional dynamics and new challenges on the real-time supply and demand balance. Specifically, price-sensitive DR load levels are constantly changing in response to dynamic real-time electricity prices, which will impact the economic dispatch (ED) schedule and in turn affect electricity market clearing prices. This thesis adopts two methods for examining the impacts of different DR price elasticity characteristics on the stability performance: a closed-loop iterative simulation method and a non-iterative method based on the contraction mapping theorem. This thesis also analyzes the financial stability of DR load consumers, by incorporating explicit LMP formulations and consumer payment requirements into the network-constrained unit commitment (NCUC) problem. The proposed model determines the proper amount of DR loads to be shifted from peak hours to off-peaks under ISO's direct load control, for reducing the operation cost and ensuring that consumer payments of DR loads will not deteriorate significantly after load shifting. Both MINLP and MILP models are discussed, and improved formulation strategies are presented.

Distributed Energy Systems Integration and Demand Optimization for Autonomous Operations and Electric Grid Transactions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ghatikar, Girish; Mashayekh, Salman; Stadler, Michael

Distributed power systems in the U.S. and globally are evolving to provide reliable and clean energy to consumers. In California, existing regulations require significant increases in renewable generation, as well as identification of customer-side distributed energy resources (DER) controls, communication technologies, and standards for interconnection with the electric grid systems. As DER deployment expands, customer-side DER control and optimization will be critical for system flexibility and demand response (DR) participation, which improves the economic viability of DER systems. Current DER systems integration and communication challenges include leveraging the existing DER and DR technology and systems infrastructure, and enabling optimized cost,more » energy and carbon choices for customers to deploy interoperable grid transactions and renewable energy systems at scale. Our paper presents a cost-effective solution to these challenges by exploring communication technologies and information models for DER system integration and interoperability. This system uses open standards and optimization models for resource planning based on dynamic-pricing notifications and autonomous operations within various domains of the smart grid energy system. It identifies architectures and customer engagement strategies in dynamic DR pricing transactions to generate feedback information models for load flexibility, load profiles, and participation schedules. The models are tested at a real site in California—Fort Hunter Liggett (FHL). Furthermore, our results for FHL show that the model fits within the existing and new DR business models and networked systems for transactive energy concepts. Integrated energy systems, communication networks, and modeling tools that coordinate supply-side networks and DER will enable electric grid system operators to use DER for grid transactions in an integrated system.« less

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

NASA Astrophysics Data System (ADS)

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.

Improved battery parameter estimation method considering operating scenarios for HEV/EV applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Jufeng; Xia, Bing; Shang, Yunlong

This study presents an improved battery parameter estimation method based on typical operating scenarios in hybrid electric vehicles and pure electric vehicles. Compared with the conventional estimation methods, the proposed method takes both the constant-current charging and the dynamic driving scenarios into account, and two separate sets of model parameters are estimated through different parts of the pulse-rest test. The model parameters for the constant-charging scenario are estimated from the data in the pulse-charging periods, while the model parameters for the dynamic driving scenario are estimated from the data in the rest periods, and the length of the fitted datasetmore » is determined by the spectrum analysis of the load current. In addition, the unsaturated phenomenon caused by the long-term resistor-capacitor (RC) network is analyzed, and the initial voltage expressions of the RC networks in the fitting functions are improved to ensure a higher model fidelity. Simulation and experiment results validated the feasibility of the developed estimation method.« less

Improved battery parameter estimation method considering operating scenarios for HEV/EV applications

DOE PAGES

Yang, Jufeng; Xia, Bing; Shang, Yunlong; ...

2016-12-22

This study presents an improved battery parameter estimation method based on typical operating scenarios in hybrid electric vehicles and pure electric vehicles. Compared with the conventional estimation methods, the proposed method takes both the constant-current charging and the dynamic driving scenarios into account, and two separate sets of model parameters are estimated through different parts of the pulse-rest test. The model parameters for the constant-charging scenario are estimated from the data in the pulse-charging periods, while the model parameters for the dynamic driving scenario are estimated from the data in the rest periods, and the length of the fitted datasetmore » is determined by the spectrum analysis of the load current. In addition, the unsaturated phenomenon caused by the long-term resistor-capacitor (RC) network is analyzed, and the initial voltage expressions of the RC networks in the fitting functions are improved to ensure a higher model fidelity. Simulation and experiment results validated the feasibility of the developed estimation method.« less

Improved Dynamic Lightpath Provisioning for Large Wavelength-Division Multiplexed Backbones

NASA Astrophysics Data System (ADS)

Kong, Huifang; Phillips, Chris

2007-07-01

Technology already exists that would allow future optical networks to support automatic lightpath configuration in response to dynamic traffic demands. Given appropriate commercial drivers, it is possible to foresee carrier network operators migrating away from semipermanent provisioning to enable on-demand short-duration communications. However, with traditional lightpath reservation protocols, a portion of the lightpath is idly held during the signaling propagation phase, which can significantly reduce the lightpath bandwidth efficiency in large wavelength-division multiplexed backbones. This paper proposes a prebooking mechanism to improve the lightpath efficiency over traditional reactive two-way reservation protocols, consequently liberating network resources to support higher traffic loads. The prebooking mechanism predicts the time when the traffic will appear at the optical cross connects, and intelligently schedules the lightpath components such that resources are only consumed as necessary. We describe the proposed signaling procedure for both centralized and distributed control planes and analyze its performance. This paper also investigates the aggregated flow length characteristics with the self-similar incident traffic and examines the effects of traffic prediction on the blocking probability as well as the ability to support latency sensitive traffic in a wide-area environment.

CFTLB: a novel cross-layer fault tolerant and load balancing protocol for WMN

NASA Astrophysics Data System (ADS)

Krishnaveni, N. N.; Chitra, K.

2017-12-01

Wireless mesh network (WMN) forms a wireless backbone framework for multi-hop transmission among the routers and clients in the extensible coverage area. To improve the throughput of WMNs with multiple gateways (GWs), several issues related to GW selection, load balancing and frequent link failures due to the presence of dynamic obstacles and channel interference should be addressed. This paper presents a novel cross-layer fault tolerant and load balancing (CFTLB) protocol to overcome the issues in WMN. Initially, the neighbour GW is searched and channel load is calculated. The GW having least channel load is selected which is estimated during the arrival of the new node. The proposed algorithm finds the alternate GWs and calculates the channel availability under high loading scenarios. If the current load in the GW is high, another GW is found and channel availability is calculated. Besides, it initiates the channel switching and establishes the communication with the mesh client effectively. The utilisation of hashing technique in proposed CFTLB verifies the status of the packets and achieves better performance in terms of router average throughput, throughput, average channel access time and lower end-to-end delay, communication overhead and average data loss in the channel compared to the existing protocols.

Characterizing mutation-expression network relationships in multiple cancers.

PubMed

Ghazanfar, Shila; Yang, Jean Yee Hwa

2016-08-01

Data made available through large cancer consortia like The Cancer Genome Atlas make for a rich source of information to be studied across and between cancers. In recent years, network approaches have been applied to such data in uncovering the complex interrelationships between mutational and expression profiles, but lack direct testing for expression changes via mutation. In this pan-cancer study we analyze mutation and gene expression information in an integrative manner by considering the networks generated by testing for differences in expression in direct association with specific mutations. We relate our findings among the 19 cancers examined to identify commonalities and differences as well as their characteristics. Using somatic mutation and gene expression information across 19 cancers, we generated mutation-expression networks per cancer. On evaluation we found that our generated networks were significantly enriched for known cancer-related genes, such as skin cutaneous melanoma (p<0.01 using Network of Cancer Genes 4.0). Our framework identified that while different cancers contained commonly mutated genes, there was little concordance between associated gene expression changes among cancers. Comparison between cancers showed a greater overlap of network nodes for cancers with higher overall non-silent mutation load, compared to those with a lower overall non-silent mutation load. This study offers a framework that explores network information through co-analysis of somatic mutations and gene expression profiles. Our pan-cancer application of this approach suggests that while mutations are frequently common among cancer types, the impact they have on the surrounding networks via gene expression changes varies. Despite this finding, there are some cancers for which mutation-associated network behaviour appears to be similar: suggesting a potential framework for uncovering related cancers for which similar therapeutic strategies may be applicable. Our framework for understanding relationships among cancers has been integrated into an interactive R Shiny application, PAn Cancer Mutation Expression Networks (PACMEN), containing dynamic and static network visualization of the mutation-expression networks. PACMEN also features tools for further examination of network topology characteristics among cancers. Copyright © 2016 Elsevier Ltd. All rights reserved.

Problem reporting management system performance simulation

NASA Technical Reports Server (NTRS)

Vannatta, David S.

1993-01-01

This paper proposes the Problem Reporting Management System (PRMS) model as an effective discrete simulation tool that determines the risks involved during the development phase of a Trouble Tracking Reporting Data Base replacement system. The model considers the type of equipment and networks which will be used in the replacement system as well as varying user loads, size of the database, and expected operational availability. The paper discusses the dynamics, stability, and application of the PRMS and addresses suggested concepts to enhance the service performance and enrich them.

Evaluation of Bridges Subjected to Military Loading and Dynamic Hydraulic Effects: Review of Design Regulations, Selection Criteria, and Inspection Procedures for Bridge Railing Systems

DTIC Science & Technology

2011-08-01

Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington VA 22202-4302. Respondents should be aware that notwithstanding any...may be required by the United States Customs and Immigration Services, in connection with the operation of an international bridge or tunnel. ERDC...significant effect on the operation , service quality, and safety of road networks by restricting the traffic volume and vehicle weight that can be

Reorientation and faulting of Pluto due to volatile loading within Sputnik Planitia.

PubMed

Keane, James T; Matsuyama, Isamu; Kamata, Shunichi; Steckloff, Jordan K

2016-12-01

Pluto is an astoundingly diverse, geologically dynamic world. The dominant feature is Sputnik Planitia-a tear-drop-shaped topographic depression approximately 1,000 kilometres in diameter possibly representing an ancient impact basin. The interior of Sputnik Planitia is characterized by a smooth, craterless plain three to four kilometres beneath the surrounding rugged uplands, and represents the surface of a massive unit of actively convecting volatile ices (N 2 , CH 4 and CO) several kilometres thick. This large feature is very near the Pluto-Charon tidal axis. Here we report that the location of Sputnik Planitia is the natural consequence of the sequestration of volatile ices within the basin and the resulting reorientation (true polar wander) of Pluto. Loading of volatile ices within a basin the size of Sputnik Planitia can substantially alter Pluto's inertia tensor, resulting in a reorientation of the dwarf planet of around 60 degrees with respect to the rotational and tidal axes. The combination of this reorientation, loading and global expansion due to the freezing of a possible subsurface ocean generates stresses within the planet's lithosphere, resulting in a global network of extensional faults that closely replicate the observed fault networks on Pluto. Sputnik Planitia probably formed northwest of its present location, and was loaded with volatiles over million-year timescales as a result of volatile transport cycles on Pluto. Pluto's past, present and future orientation is controlled by feedbacks between volatile sublimation and condensation, changing insolation conditions and Pluto's interior structure.

Reorientation and faulting of Pluto due to volatile loading within Sputnik Planitia

NASA Astrophysics Data System (ADS)

Keane, James T.; Matsuyama, Isamu; Kamata, Shunichi; Steckloff, Jordan K.

2016-12-01

Pluto is an astoundingly diverse, geologically dynamic world. The dominant feature is Sputnik Planitia—a tear-drop-shaped topographic depression approximately 1,000 kilometres in diameter possibly representing an ancient impact basin. The interior of Sputnik Planitia is characterized by a smooth, craterless plain three to four kilometres beneath the surrounding rugged uplands, and represents the surface of a massive unit of actively convecting volatile ices (N2, CH4 and CO) several kilometres thick. This large feature is very near the Pluto-Charon tidal axis. Here we report that the location of Sputnik Planitia is the natural consequence of the sequestration of volatile ices within the basin and the resulting reorientation (true polar wander) of Pluto. Loading of volatile ices within a basin the size of Sputnik Planitia can substantially alter Pluto’s inertia tensor, resulting in a reorientation of the dwarf planet of around 60 degrees with respect to the rotational and tidal axes. The combination of this reorientation, loading and global expansion due to the freezing of a possible subsurface ocean generates stresses within the planet’s lithosphere, resulting in a global network of extensional faults that closely replicate the observed fault networks on Pluto. Sputnik Planitia probably formed northwest of its present location, and was loaded with volatiles over million-year timescales as a result of volatile transport cycles on Pluto. Pluto’s past, present and future orientation is controlled by feedbacks between volatile sublimation and condensation, changing insolation conditions and Pluto’s interior structure.

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

NASA Astrophysics Data System (ADS)

Islam, Mujahidul

A sustainable energy delivery infrastructure implies the safe and reliable accommodation of large scale penetration of renewable sources in the power grid. In this dissertation it is assumed there will be no significant change in the power transmission and distribution structure currently in place; except in the operating strategy and regulatory policy. That is to say, with the same old structure, the path towards unveiling a high penetration of switching power converters in the power system will be challenging. Some of the dimensions of this challenge are power quality degradation, frequent false trips due to power system imbalance, and losses due to a large neutral current. The ultimate result is the reduced life of many power distribution components - transformers, switches and sophisticated loads. Numerous ancillary services are being developed and offered by the utility operators to mitigate these problems. These services will likely raise the system's operational cost, not only from the utility operators' end, but also reflected on the Independent System Operators and by the Regional Transmission Operators (RTO) due to an unforeseen backlash of frequent variation in the load-side generation or distributed generation. The North American transmission grid is an interconnected system similar to a large electrical circuit. This circuit was not planned but designed over 100 years. The natural laws of physics govern the power flow among loads and generators except where control mechanisms are installed. The control mechanism has not matured enough to withstand the high penetration of variable generators at uncontrolled distribution ends. Unlike a radial distribution system, mesh or loop networks can alleviate complex channels for real and reactive power flow. Significant variation in real power injection and absorption on the distribution side can emerge as a bias signal on the routing reactive power in some physical links or channels that are not distinguishable 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.

46 CFR 154.409 - Dynamic loads from vessel motion.

Code of Federal Regulations, 2010 CFR

2010-10-01

... Equipment Cargo Containment Systems § 154.409 Dynamic loads from vessel motion. (a) For the calculation required under § 154.406 (a)(3) and (b), the dynamic loads must be determined from the long term... 46 Shipping 5 2010-10-01 2010-10-01 false Dynamic loads from vessel motion. 154.409 Section 154...

Formulating a Theoretical Framework for Assessing Network Loads for Effective Deployment in Network-Centric Operations and Warfare

DTIC Science & Technology

2008-11-01

is particularly important in order to design a network that is realistically deployable. The goal of this project is the design of a theoretical ... framework to assess and predict the effectiveness and performance of networks and their loads.

Short-term forecasting of electric loads using nonlinear autoregressive artificial neural networks with exogenous vector inputs

DOE PAGES

Buitrago, Jaime; Asfour, Shihab

2017-01-01

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.more » 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. Finally, the New England electrical load data are used to train and validate the forecast prediction.« less

Short-term forecasting of electric loads using nonlinear autoregressive artificial neural networks with exogenous vector inputs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Buitrago, Jaime; Asfour, Shihab

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.more » 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. Finally, the New England electrical load data are used to train and validate the forecast prediction.« less

Overload cascading failure on complex networks with heterogeneous load redistribution

NASA Astrophysics Data System (ADS)

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.

Design and Implementation of a MAC Protocol for Timely and Reliable Delivery of Command and Data in Dynamic Wireless Sensor Networks

PubMed Central

Oh, Hoon; Van Vinh, Phan

2013-01-01

This paper proposes and implements a new TDMA-based MAC protocol for providing timely and reliable delivery of data and command for monitoring and control networks. In this kind of network, sensor nodes are required to sense data from the monitoring environment periodically and then send the data to a sink. The sink determines whether the environment is safe or not by analyzing the acquired data. Sometimes, a command or control message is sent from the sink to a particular node or a group of nodes to execute the services or request further interested data. The proposed MAC protocol enables bidirectional communication, controls active and sleep modes of a sensor node to conserve energy, and addresses the problem of load unbalancing between the nodes near a sink and the other nodes. It can improve reliability of communication significantly while extending network lifetime. These claims are supported by the experimental results. PMID:24084116

Design and implementation of a MAC protocol for timely and reliable delivery of command and data in dynamic wireless sensor networks.

PubMed

Oh, Hoon; Van Vinh, Phan

2013-09-30

This paper proposes and implements a new TDMA-based MAC protocol for providing timely and reliable delivery of data and command for monitoring and control networks. In this kind of network, sensor nodes are required to sense data from the monitoring environment periodically and then send the data to a sink. The sink determines whether the environment is safe or not by analyzing the acquired data. Sometimes, a command or control message is sent from the sink to a particular node or a group of nodes to execute the services or request further interested data. The proposed MAC protocol enables bidirectional communication, controls active and sleep modes of a sensor node to conserve energy, and addresses the problem of load unbalancing between the nodes near a sink and the other nodes. It can improve reliability of communication significantly while extending network lifetime. These claims are supported by the experimental results.

Field Measurement-Based System Identification and Dynamic Response Prediction of a Unique MIT Building.

PubMed

Cha, Young-Jin; Trocha, Peter; Büyüköztürk, Oral

2016-07-01

Tall buildings are ubiquitous in major cities and house the homes and workplaces of many individuals. However, relatively few studies have been carried out to study the dynamic characteristics of tall buildings based on field measurements. In this paper, the dynamic behavior of the Green Building, a unique 21-story tall structure located on the campus of the Massachusetts Institute of Technology (MIT, Cambridge, MA, USA), was characterized and modeled as a simplified lumped-mass beam model (SLMM), using data from a network of accelerometers. The accelerometer network was used to record structural responses due to ambient vibrations, blast loading, and the October 16th 2012 earthquake near Hollis Center (ME, USA). Spectral and signal coherence analysis of the collected data was used to identify natural frequencies, modes, foundation rocking behavior, and structural asymmetries. A relation between foundation rocking and structural natural frequencies was also found. Natural frequencies and structural acceleration from the field measurements were compared with those predicted by the SLMM which was updated by inverse solving based on advanced multiobjective optimization methods using the measured structural responses and found to have good agreement.

Field Measurement-Based System Identification and Dynamic Response Prediction of a Unique MIT Building

PubMed Central

Cha, Young-Jin; Trocha, Peter; Büyüköztürk, Oral

2016-01-01

Tall buildings are ubiquitous in major cities and house the homes and workplaces of many individuals. However, relatively few studies have been carried out to study the dynamic characteristics of tall buildings based on field measurements. In this paper, the dynamic behavior of the Green Building, a unique 21-story tall structure located on the campus of the Massachusetts Institute of Technology (MIT, Cambridge, MA, USA), was characterized and modeled as a simplified lumped-mass beam model (SLMM), using data from a network of accelerometers. The accelerometer network was used to record structural responses due to ambient vibrations, blast loading, and the October 16th 2012 earthquake near Hollis Center (ME, USA). Spectral and signal coherence analysis of the collected data was used to identify natural frequencies, modes, foundation rocking behavior, and structural asymmetries. A relation between foundation rocking and structural natural frequencies was also found. Natural frequencies and structural acceleration from the field measurements were compared with those predicted by the SLMM which was updated by inverse solving based on advanced multiobjective optimization methods using the measured structural responses and found to have good agreement. PMID:27376303

A methodology for the efficient integration of transient constraints in the design of aircraft dynamic systems

NASA Astrophysics Data System (ADS)

Phan, Leon L.

The motivation behind this thesis mainly stems from previous work performed at Hispano-Suiza (Safran Group) in the context of the European research project "Power Optimised Aircraft". Extensive testing on the COPPER Bird RTM, a test rig designed to characterize aircraft electrical networks, demonstrated the relevance of transient regimes in the design and development of dynamic systems. Transient regimes experienced by dynamic systems may have severe impacts on the operation of the aircraft. For example, the switching on of a high electrical load might cause a network voltage drop inducing a loss of power available to critical aircraft systems. These transient behaviors are thus often regulated by dynamic constraints, requiring the dynamic signals to remain within bounds whose values vary with time. The verification of these peculiar types of constraints, which generally requires high-fidelity time-domain simulation, intervenes late in the system development process, thus potentially causing costly design iterations. The research objective of this thesis is to develop a methodology that integrates the verification of dynamic constraints in the early specification of dynamic systems. In order to circumvent the inefficiencies of time-domain simulation, multivariate dynamic surrogate models of the original time-domain simulation models are generated, building on a nonlinear system identification technique using wavelet neural networks (or wavenets), which allow the multiscale nature of transient signals to be captured. However, training multivariate wavenets can become computationally prohibitive as the number of design variables increases. Therefore, an alternate approach is formulated, in which dynamic surrogate models using sigmoid-based neural networks are used to emulate the transient behavior of the envelopes of the time-domain response. Thus, in order to train the neural network, the envelopes are extracted by first separating the scales of the dynamic response, using a multiresolution analysis (MRA) based on the discrete wavelet transform. The MRA separates the dynamic response into a trend and a noise signal (ripple). The envelope of the noise is then computed with a windowing method, and recombined with the trend in order to reconstruct the global envelope of the dynamic response. The run-time efficiency of the resulting dynamic surrogate models enable the implementation of a data farming approach, in which a Monte-Carlo simulation generates time-domain behaviors of transient responses for a vast set of design and operation scenarios spanning the design and operation space. An interactive visualization environment, enabling what-if analyses, will be developed; the user can thereby instantaneously comprehend the transient response of the system (or its envelope) and its sensitivities to design and operation variables, as well as filter the design space to have it exhibit only the design scenarios verifying the dynamic constraints. The proposed methodology, along with its foundational hypotheses, are tested on the design and optimization of a 350VDC network, where a generator and its control system are concurrently designed in order to minimize the electrical losses, while ensuring that the transient undervoltage induced by peak demands in the consumption of a motor does not violate transient power quality constraints.

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed Central

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.

PubMed

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.

A parallel algorithm for multi-level logic synthesis using the transduction method. M.S. Thesis

NASA Technical Reports Server (NTRS)

Lim, Chieng-Fai

1991-01-01

The Transduction Method has been shown to be a powerful tool in the optimization of multilevel networks. Many tools such as the SYLON synthesis system (X90), (CM89), (LM90) have been developed based on this method. A parallel implementation is presented of SYLON-XTRANS (XM89) on an eight processor Encore Multimax shared memory multiprocessor. It minimizes multilevel networks consisting of simple gates through parallel pruning, gate substitution, gate merging, generalized gate substitution, and gate input reduction. This implementation, called Parallel TRANSduction (PTRANS), also uses partitioning to break large circuits up and performs inter- and intra-partition dynamic load balancing. With this, good speedups and high processor efficiencies are achievable without sacrificing the resulting circuit quality.

Packetized video on MAGNET

NASA Astrophysics Data System (ADS)

Lazar, Aurel A.; White, John S.

1986-11-01

Theoretical analysis of an ILAN model of MAGNET, an integrated network testbed developed at Columbia University, shows that the bandwidth freed up by video and voice calls during periods of little movement in the images and silence periods in the speech signals could be utilized efficiently for graphics and data transmission. Based on these investigations, an architecture supporting adaptive protocols that are dynamically controlled by the requirements of a fluctuating load and changing user environment has been advanced. To further analyze the behavior of the network, a real-time packetized video system has been implemented. This system is embedded in the real time multimedia workstation EDDY that integrates video, voice and data traffic flows. Protocols supporting variable bandwidth, constant quality packetized video transport are descibed in detail.

Analysis of the dynamic behavior of structures using the high-rate GNSS-PPP method combined with a wavelet-neural model: Numerical simulation and experimental tests

NASA Astrophysics Data System (ADS)

Kaloop, Mosbeh R.; Yigit, Cemal O.; Hu, Jong W.

2018-03-01

Recently, the high rate global navigation satellite system-precise point positioning (GNSS-PPP) technique has been used to detect the dynamic behavior of structures. This study aimed to increase the accuracy of the extraction oscillation properties of structural movements based on the high-rate (10 Hz) GNSS-PPP monitoring technique. A developmental model based on the combination of wavelet package transformation (WPT) de-noising and neural network prediction (NN) was proposed to improve the dynamic behavior of structures for GNSS-PPP method. A complicated numerical simulation involving highly noisy data and 13 experimental cases with different loads were utilized to confirm the efficiency of the proposed model design and the monitoring technique in detecting the dynamic behavior of structures. The results revealed that, when combined with the proposed model, GNSS-PPP method can be used to accurately detect the dynamic behavior of engineering structures as an alternative to relative GNSS method.

Predicted effect of dynamic load on pitting fatigue life for low-contact-ratio spur gears

NASA Technical Reports Server (NTRS)

Lewicki, David G.

1986-01-01

How dynamic load affects the surface pitting fatigue life of external spur gears was predicted by using the NASA computer program TELSGE. Parametric studies were performed over a range of various gear parameters modeling low-contact-ratio involute spur gears. In general, gear life predictions based on dynamic loads differed significantly from those based on static loads, with the predictions being strongly influenced by the maximum dynamic load during contact. Gear mesh operating speed strongly affected predicted dynamic load and life. Meshes operating at a resonant speed or one-half the resonant speed had significantly shorter lives. Dynamic life factors for gear surface pitting fatigue were developed on the basis of the parametric studies. In general, meshes with higher contact ratios had higher dynamic life factors than meshes with lower contact ratios. A design chart was developed for hand calculations of dynamic life factors.

A Design of a Network Model to the Electric Power Trading System Using Web Services

NASA Astrophysics Data System (ADS)

Maruo, Tomoaki; Matsumoto, Keinosuke; Mori, Naoki; Kitayama, Masashi; Izumi, Yoshio

Web services are regarded as a new application paradigm in the world of the Internet. On the other hand, many business models of a power trading system has been proposed to aim at load reduction by consumers cooperating with electric power suppliers in an electric power market. Then, we propose a network model of power trading system using Web service in this paper. The adaptability of Web services to power trading system was checked in the prototype of our network model and we got good results for it. Each server provides functions as a SOAP server, and it is coupled loosely with each other through SOAP. Storing SOAP message in HTTP packet can establish the penetration communication way that is not conscious of a firewall. Switching of a dynamic server is possible by means of rewriting the server point information on WSDL at the time of obstacle generating.

Vehicle Signal Analysis Using Artificial Neural Networks for a Bridge Weigh-in-Motion System

PubMed Central

Kim, Sungkon; Lee, Jungwhee; Park, Min-Seok; Jo, Byung-Wan

2009-01-01

This paper describes the procedures for development of signal analysis algorithms using artificial neural networks for Bridge Weigh-in-Motion (B-WIM) systems. Through the analysis procedure, the extraction of information concerning heavy traffic vehicles such as weight, speed, and number of axles from the time domain strain data of the B-WIM system was attempted. As one of the several possible pattern recognition techniques, an Artificial Neural Network (ANN) was employed since it could effectively include dynamic effects and bridge-vehicle interactions. A number of vehicle traveling experiments with sufficient load cases were executed on two different types of bridges, a simply supported pre-stressed concrete girder bridge and a cable-stayed bridge. Different types of WIM systems such as high-speed WIM or low-speed WIM were also utilized during the experiments for cross-checking and to validate the performance of the developed algorithms. PMID:22408487

Distributed wireless sensing for methane leak detection technology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Klein, Levente; van Kesse, Theodor

Large scale environmental monitoring requires dynamic optimization of data transmission, power management, and distribution of the computational load. In this work, we demonstrate the use of a wireless sensor network for detection of chemical leaks on gas oil well pads. The sensor network consist of chemi-resistive and wind sensors and aggregates all the data and transmits it to the cloud for further analytics processing. The sensor network data is integrated with an inversion model to identify leak location and quantify leak rates. We characterize the sensitivity and accuracy of such system under multiple well controlled methane release experiments. It ismore » demonstrated that even 1 hour measurement with 10 sensors localizes leaks within 1 m and determines leak rate with an accuracy of 40%. This integrated sensing and analytics solution is currently refined to be a robust system for long term remote monitoring of methane leaks, generation of alarms, and tracking regulatory compliance.« less

Distributed wireless sensing for fugitive methane leak detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Klein, Levente J.; van Kessel, Theodore; Nair, Dhruv

Large scale environmental monitoring requires dynamic optimization of data transmission, power management, and distribution of the computational load. In this work, we demonstrate the use of a wireless sensor network for detection of chemical leaks on gas oil well pads. The sensor network consist of chemi-resistive and wind sensors and aggregates all the data and transmits it to the cloud for further analytics processing. The sensor network data is integrated with an inversion model to identify leak location and quantify leak rates. We characterize the sensitivity and accuracy of such system under multiple well controlled methane release experiments. It ismore » demonstrated that even 1 hour measurement with 10 sensors localizes leaks within 1 m and determines leak rate with an accuracy of 40%. This integrated sensing and analytics solution is currently refined to be a robust system for long term remote monitoring of methane leaks, generation of alarms, and tracking regulatory compliance.« less

Vehicle Signal Analysis Using Artificial Neural Networks for a Bridge Weigh-in-Motion System.

PubMed

Kim, Sungkon; Lee, Jungwhee; Park, Min-Seok; Jo, Byung-Wan

2009-01-01

This paper describes the procedures for development of signal analysis algorithms using artificial neural networks for Bridge Weigh-in-Motion (B-WIM) systems. Through the analysis procedure, the extraction of information concerning heavy traffic vehicles such as weight, speed, and number of axles from the time domain strain data of the B-WIM system was attempted. As one of the several possible pattern recognition techniques, an Artificial Neural Network (ANN) was employed since it could effectively include dynamic effects and bridge-vehicle interactions. A number of vehicle traveling experiments with sufficient load cases were executed on two different types of bridges, a simply supported pre-stressed concrete girder bridge and a cable-stayed bridge. Different types of WIM systems such as high-speed WIM or low-speed WIM were also utilized during the experiments for cross-checking and to validate the performance of the developed algorithms.

Distributed wireless sensing for fugitive methane leak detection

DOE PAGES

Klein, Levente J.; van Kessel, Theodore; Nair, Dhruv; ...

2017-12-11

Large scale environmental monitoring requires dynamic optimization of data transmission, power management, and distribution of the computational load. In this work, we demonstrate the use of a wireless sensor network for detection of chemical leaks on gas oil well pads. The sensor network consist of chemi-resistive and wind sensors and aggregates all the data and transmits it to the cloud for further analytics processing. The sensor network data is integrated with an inversion model to identify leak location and quantify leak rates. We characterize the sensitivity and accuracy of such system under multiple well controlled methane release experiments. It ismore » demonstrated that even 1 hour measurement with 10 sensors localizes leaks within 1 m and determines leak rate with an accuracy of 40%. This integrated sensing and analytics solution is currently refined to be a robust system for long term remote monitoring of methane leaks, generation of alarms, and tracking regulatory compliance.« less

Based on Artificial Neural Network to Realize K-Parameter Analysis of Vehicle Air Spring System

NASA Astrophysics Data System (ADS)

Hung, San-Shan; Hsu, Chia-Ning; Hwang, Chang-Chou; Chen, Wen-Jan

2017-10-01

In recent years, because of the air-spring control technique is more mature, that air- spring suspension systems already can be used to replace the classical vehicle suspension system. Depend on internal pressure variation of the air-spring, thestiffnessand the damping factor can be adjusted. Because of air-spring has highly nonlinear characteristic, therefore it isn’t easy to construct the classical controller to control the air-spring effectively. The paper based on Artificial Neural Network to propose a feasible control strategy. By using offline way for the neural network design and learning to the air-spring in different initial pressures and different loads, offline method through, predict air-spring stiffness parameter to establish a model. Finally, through adjusting air-spring internal pressure to change the K-parameter of the air-spring, realize the well dynamic control performance of air-spring suspension.

Development of a time-stepping sediment budget model for assessing land use impacts in large river basins.

PubMed

Wilkinson, S N; Dougall, C; Kinsey-Henderson, A E; Searle, R D; Ellis, R J; Bartley, R

2014-01-15

The use of river basin modelling to guide mitigation of non-point source pollution of wetlands, estuaries and coastal waters has become widespread. To assess and simulate the impacts of alternate land use or climate scenarios on river washload requires modelling techniques that represent sediment sources and transport at the time scales of system response. Building on the mean-annual SedNet model, we propose a new D-SedNet model which constructs daily budgets of fine sediment sources, transport and deposition for each link in a river network. Erosion rates (hillslope, gully and streambank erosion) and fine sediment sinks (floodplains and reservoirs) are disaggregated from mean annual rates based on daily rainfall and runoff. The model is evaluated in the Burdekin basin in tropical Australia, where policy targets have been set for reducing sediment and nutrient loads to the Great Barrier Reef (GBR) lagoon from grazing and cropping land. D-SedNet predicted annual loads with similar performance to that of a sediment rating curve calibrated to monitored suspended sediment concentrations. Relative to a 22-year reference load time series at the basin outlet derived from a dynamic general additive model based on monitoring data, D-SedNet had a median absolute error of 68% compared with 112% for the rating curve. RMS error was slightly higher for D-SedNet than for the rating curve due to large relative errors on small loads in several drought years. This accuracy is similar to existing agricultural system models used in arable or humid environments. Predicted river loads were sensitive to ground vegetation cover. We conclude that the river network sediment budget model provides some capacity for predicting load time-series independent of monitoring data in ungauged basins, and for evaluating the impact of land management on river sediment load time-series, which is challenging across large regions in data-poor environments. © 2013. Published by Elsevier B.V. All rights reserved.

Repetitive Series Interrupter II.

DTIC Science & Technology

1977-07-01

nated by other authorized documents. The citation of trade names and names of manufacturers is this report is not to be construed as official... intergrating inductor Magnet circuit load resistance Pulse-forming network load resistance Fault network load resistance Time delay between TUT fire and

Fuzzy chaos control for vehicle lateral dynamics based on active suspension system

NASA Astrophysics Data System (ADS)

Huang, Chen; Chen, Long; Jiang, Haobin; Yuan, Chaochun; Xia, Tian

2014-07-01

The existing research of the active suspension system (ASS) mainly focuses on the different evaluation indexes and control strategies. Among the different components, the nonlinear characteristics of practical systems and control are usually not considered for vehicle lateral dynamics. But the vehicle model has some shortages on tyre model with side-slip angle, road adhesion coefficient, vertical load and velocity. In this paper, the nonlinear dynamic model of lateral system is considered and also the adaptive neural network of tire is introduced. By nonlinear analysis methods, such as the bifurcation diagram and Lyapunov exponent, it has shown that the lateral dynamics exhibits complicated motions with the forward speed. Then, a fuzzy control method is applied to the lateral system aiming to convert chaos into periodic motion using the linear-state feedback of an available lateral force with changing tire load. Finally, the rapid control prototyping is built to conduct the real vehicle test. By comparison of time response diagram, phase portraits and Lyapunov exponents at different work conditions, the results on step input and S-shaped road indicate that the slip angle and yaw velocity of lateral dynamics enter into stable domain and the results of test are consistent to the simulation and verified the correctness of simulation. And the Lyapunov exponents of the closed-loop system are becoming from positive to negative. This research proposes a fuzzy control method which has sufficient suppress chaotic motions as an effective active suspension system.

Bridge damage detection using spatiotemporal patterns extracted from dense sensor network

NASA Astrophysics Data System (ADS)

Liu, Chao; Gong, Yongqiang; Laflamme, Simon; Phares, Brent; Sarkar, Soumik

2017-01-01

The alarmingly degrading state of transportation infrastructures combined with their key societal and economic importance calls for automatic condition assessment methods to facilitate smart management of maintenance and repairs. With the advent of ubiquitous sensing and communication capabilities, scalable data-driven approaches is of great interest, as it can utilize large volume of streaming data without requiring detailed physical models that can be inaccurate and computationally expensive to run. Properly designed, a data-driven methodology could enable fast and automatic evaluation of infrastructures, discovery of causal dependencies among various sub-system dynamic responses, and decision making with uncertainties and lack of labeled data. In this work, a spatiotemporal pattern network (STPN) strategy built on symbolic dynamic filtering (SDF) is proposed to explore spatiotemporal behaviors in a bridge network. Data from strain gauges installed on two bridges are generated using finite element simulation for three types of sensor networks from a density perspective (dense, nominal, sparse). Causal relationships among spatially distributed strain data streams are extracted and analyzed for vehicle identification and detection, and for localization of structural degradation in bridges. Multiple case studies show significant capabilities of the proposed approach in: (i) capturing spatiotemporal features to discover causality between bridges (geographically close), (ii) robustness to noise in data for feature extraction, (iii) detecting and localizing damage via comparison of bridge responses to similar vehicle loads, and (iv) implementing real-time health monitoring and decision making work flow for bridge networks. Also, the results demonstrate increased sensitivity in detecting damages and higher reliability in quantifying the damage level with increase in sensor network density.

Identification of dynamic load for prosthetic structures.

PubMed

Zhang, Dequan; Han, Xu; Zhang, Zhongpu; Liu, Jie; Jiang, Chao; Yoda, Nobuhiro; Meng, Xianghua; Li, Qing

2017-12-01

Dynamic load exists in numerous biomechanical systems, and its identification signifies a critical issue for characterizing dynamic behaviors and studying biomechanical consequence of the systems. This study aims to identify dynamic load in the dental prosthetic structures, namely, 3-unit implant-supported fixed partial denture (I-FPD) and teeth-supported fixed partial denture. The 3-dimensional finite element models were constructed through specific patient's computerized tomography images. A forward algorithm and regularization technique were developed for identifying dynamic load. To verify the effectiveness of the identification method proposed, the I-FPD and teeth-supported fixed partial denture structures were investigated to determine the dynamic loads. For validating the results of inverse identification, an experimental force-measuring system was developed by using a 3-dimensional piezoelectric transducer to measure the dynamic load in the I-FPD structure in vivo. The computationally identified loads were presented with different noise levels to determine their influence on the identification accuracy. The errors between the measured load and identified counterpart were calculated for evaluating the practical applicability of the proposed procedure in biomechanical engineering. This study is expected to serve as a demonstrative role in identifying dynamic loading in biomedical systems, where a direct in vivo measurement may be rather demanding in some areas of interest clinically. Copyright © 2017 John Wiley & Sons, Ltd.

Niosome-loaded cold-set whey protein hydrogels.

PubMed

Abaee, Arash; Madadlou, Ashkan

2016-04-01

The α-tocopherol-carrying niosomes with mean diameter of 5.7 μm were fabricated and charged into a transglutaminase-cross-linked whey protein solution that was subsequently gelled with glucono delta-lactone. Encapsulation efficiency of α-tocopherol within niosomes was ≈80% and encapsulation did not influence the radical scavenging activity of α-tocopherol. Fourier transform infrared (FTIR) spectroscopy suggested formation of ε-(γ-glutamyl) lysine cross-linkages by transglutaminase and that enzymatic cross-linking increased proteins hydrophobicity. FTIR also proposed hydrogen bonding between niosomes and proteins. Dynamic rheometry indicated that transglutaminase cross-linking and niosomes charging of the protein solution enhanced the gelation process. However, charging the cross-linked protein solution with niosomal suspension resulted in lower elastic modulus (G') of the subsequently formed gel compared with both non-cross-linked niosome-loaded and cross-linked niosome-free counterparts. Electron microscopy indicated a discontinuous network for the niosome-loaded cross-linked sample. Niosome loading into the protein gel matrix increased its swelling extent in the enzyme-free simulated gastric fluid. Copyright © 2015 Elsevier Ltd. All rights reserved.

Load balancing prediction method of cloud storage based on analytic hierarchy process and hybrid hierarchical genetic algorithm.

PubMed

Zhou, Xiuze; Lin, Fan; Yang, Lvqing; Nie, Jing; Tan, Qian; Zeng, Wenhua; Zhang, Nian

2016-01-01

With the continuous expansion of the cloud computing platform scale and rapid growth of users and applications, how to efficiently use system resources to improve the overall performance of cloud computing has become a crucial issue. To address this issue, this paper proposes a method that uses an analytic hierarchy process group decision (AHPGD) to evaluate the load state of server nodes. Training was carried out by using a hybrid hierarchical genetic algorithm (HHGA) for optimizing a radial basis function neural network (RBFNN). The AHPGD makes the aggregative indicator of virtual machines in cloud, and become input parameters of predicted RBFNN. Also, this paper proposes a new dynamic load balancing scheduling algorithm combined with a weighted round-robin algorithm, which uses the predictive periodical load value of nodes based on AHPPGD and RBFNN optimized by HHGA, then calculates the corresponding weight values of nodes and makes constant updates. Meanwhile, it keeps the advantages and avoids the shortcomings of static weighted round-robin algorithm.

Theoretical research and experimental validation of elastic dynamic load spectra on bogie frame of high-speed train

NASA Astrophysics Data System (ADS)

Zhu, Ning; Sun, Shouguang; Li, Qiang; Zou, Hua

2016-05-01

When a train runs at high speeds, the external exciting frequencies approach the natural frequencies of bogie critical components, thereby inducing strong elastic vibrations. The present international reliability test evaluation standard and design criteria of bogie frames are all based on the quasi-static deformation hypothesis. Structural fatigue damage generated by structural elastic vibrations has not yet been included. In this paper, theoretical research and experimental validation are done on elastic dynamic load spectra on bogie frame of high-speed train. The construction of the load series that correspond to elastic dynamic deformation modes is studied. The simplified form of the load series is obtained. A theory of simplified dynamic load-time histories is then deduced. Measured data from the Beijing-Shanghai Dedicated Passenger Line are introduced to derive the simplified dynamic load-time histories. The simplified dynamic discrete load spectra of bogie frame are established. Based on the damage consistency criterion and a genetic algorithm, damage consistency calibration of the simplified dynamic load spectra is finally performed. The computed result proves that the simplified load series is reasonable. The calibrated damage that corresponds to the elastic dynamic discrete load spectra can cover the actual damage at the operating conditions. The calibrated damage satisfies the safety requirement of damage consistency criterion for bogie frame. This research is helpful for investigating the standardized load spectra of bogie frame of high-speed train.

Hybrid neuro-heuristic methodology for simulation and control of dynamic systems over time interval.

PubMed

Woźniak, Marcin; Połap, Dawid

2017-09-01

Simulation and positioning are very important aspects of computer aided engineering. To process these two, we can apply traditional methods or intelligent techniques. The difference between them is in the way they process information. In the first case, to simulate an object in a particular state of action, we need to perform an entire process to read values of parameters. It is not very convenient for objects for which simulation takes a long time, i.e. when mathematical calculations are complicated. In the second case, an intelligent solution can efficiently help on devoted way of simulation, which enables us to simulate the object only in a situation that is necessary for a development process. We would like to present research results on developed intelligent simulation and control model of electric drive engine vehicle. For a dedicated simulation method based on intelligent computation, where evolutionary strategy is simulating the states of the dynamic model, an intelligent system based on devoted neural network is introduced to control co-working modules while motion is in time interval. Presented experimental results show implemented solution in situation when a vehicle transports things over area with many obstacles, what provokes sudden changes in stability that may lead to destruction of load. Therefore, applied neural network controller prevents the load from destruction by positioning characteristics like pressure, acceleration, and stiffness voltage to absorb the adverse changes of the ground. Copyright © 2017 Elsevier Ltd. All rights reserved.

Active load control during rolling maneuvers. [performed in the Langley Transonic Dynamics Tunnel

NASA Technical Reports Server (NTRS)

Woods-Vedeler, Jessica A.; Pototzky, Anthony S.; Hoadley, Sherwood T.

1994-01-01

A rolling maneuver load alleviation (RMLA) system has been demonstrated on the active flexible wing (AFW) wind tunnel model in the Langley Transonic Dynamics Tunnel (TDT). The objective was to develop a systematic approach for designing active control laws to alleviate wing loads during rolling maneuvers. Two RMLA control laws were developed that utilized outboard control-surface pairs (leading and trailing edge) to counteract the loads and that used inboard trailing-edge control-surface pairs to maintain roll performance. Rolling maneuver load tests were performed in the TDT at several dynamic pressures that included two below and one 11 percent above open-loop flutter dynamic pressure. The RMLA system was operated simultaneously with an active flutter suppression system above open-loop flutter dynamic pressure. At all dynamic pressures for which baseline results were obtained, torsion-moment loads were reduced for both RMLA control laws. Results for bending-moment load reductions were mixed; however, design equations developed in this study provided conservative estimates of load reduction in all cases.

Transient response of nonlinear polymer networks: A kinetic theory

NASA Astrophysics Data System (ADS)

Vernerey, Franck J.

2018-06-01

Dynamic networks are found in a majority of natural materials, but also in engineering materials, such as entangled polymers and physically cross-linked gels. Owing to their transient bond dynamics, these networks display a rich class of behaviors, from elasticity, rheology, self-healing, or growth. Although classical theories in rheology and mechanics have enabled us to characterize these materials, there is still a gap in our understanding on how individuals (i.e., the mechanics of each building blocks and its connection with others) affect the emerging response of the network. In this work, we introduce an alternative way to think about these networks from a statistical point of view. More specifically, a network is seen as a collection of individual polymer chains connected by weak bonds that can associate and dissociate over time. From the knowledge of these individual chains (elasticity, transient attachment, and detachment events), we construct a statistical description of the population and derive an evolution equation of their distribution based on applied deformation and their local interactions. We specifically concentrate on nonlinear elastic response that follows from the strain stiffening response of individual chains of finite size. Upon appropriate averaging operations and using a mean field approximation, we show that the distribution can be replaced by a so-called chain distribution tensor that is used to determine important macroscopic measures such as stress, energy storage and dissipation in the network. Prediction of the kinetic theory are then explored against known experimental measurement of polymer responses under uniaxial loading. It is found that even under the simplest assumptions of force-independent chain kinetics, the model is able to reproduce complex time-dependent behaviors of rubber and self-healing supramolecular polymers.

Research on cascading failure in multilayer network with different coupling preference

NASA Astrophysics Data System (ADS)

Zhang, Yong; Jin, Lei; Wang, Xiao Juan

This paper is aimed at constructing robust multilayer networks against cascading failure. Considering link protection strategies in reality, we design a cascading failure model based on load distribution and extend it to multilayer. We use the cascading failure model to deduce the scale of the largest connected component after cascading failure, from which we can find that the performance of four kinds of load distribution strategies associates with the load ratio of the current edge to its adjacent edge. Coupling preference is a typical characteristic in multilayer networks which corresponds to the network robustness. The coupling preference of multilayer networks is divided into two forms: the coupling preference in layers and the coupling preference between layers. To analyze the relationship between the coupling preference and the multilayer network robustness, we design a construction algorithm to generate multilayer networks with different coupling preferences. Simulation results show that the load distribution based on the node betweenness performs the best. When the coupling coefficient in layers is zero, the scale-free network is the most robust. In the random network, the assortative coupling in layers is more robust than the disassortative coupling. For the coupling preference between layers, the assortative coupling between layers is more robust than the disassortative coupling both in the scale free network and the random network.

A carrier sensed multiple access protocol for high data base rate ring networks

NASA Technical Reports Server (NTRS)

Foudriat, E. C.; Maly, Kurt J.; Overstreet, C. Michael; Khanna, S.; Paterra, Frank

1990-01-01

The results of the study of a simple but effective media access protocol for high data rate networks are presented. The protocol is based on the fact that at high data rates networks can contain multiple messages simultaneously over their span, and that in a ring, nodes used to detect the presence of a message arriving from the immediate upstream neighbor. When an incoming signal is detected, the node must either abort or truncate a message it is presently sending. Thus, the protocol with local carrier sensing and multiple access is designated CSMA/RN. The performance of CSMA/RN with TTattempt and truncate is studied using analytic and simulation models. Three performance factors, wait or access time, service time and response or end-to-end travel time are presented. The service time is basically a function of the network rate, it changes by a factor of 1 between no load and full load. Wait time, which is zero for no load, remains small for load factors up to 70 percent of full load. Response time, which adds travel time while on the network to wait and service time, is mainly a function of network length, especially for longer distance networks. Simulation results are shown for CSMA/RN where messages are removed at the destination. A wide range of local and metropolitan area network parameters including variations in message size, network length, and node count are studied. Finally, a scaling factor based upon the ratio of message to network length demonstrates that the results, and hence, the CSMA/RN protocol, are applicable to wide area networks.

Improved Neural Networks with Random Weights for Short-Term Load Forecasting

PubMed Central

Lang, Kun; Zhang, Mingyuan; Yuan, Yongbo

2015-01-01

An effective forecasting model for short-term load plays a significant role in promoting the management efficiency of an electric power system. This paper proposes a new forecasting model based on the improved neural networks with random weights (INNRW). The key is to introduce a weighting technique to the inputs of the model and use a novel neural network to forecast the daily maximum load. Eight factors are selected as the inputs. A mutual information weighting algorithm is then used to allocate different weights to the inputs. The neural networks with random weights and kernels (KNNRW) is applied to approximate the nonlinear function between the selected inputs and the daily maximum load due to the fast learning speed and good generalization performance. In the application of the daily load in Dalian, the result of the proposed INNRW is compared with several previously developed forecasting models. The simulation experiment shows that the proposed model performs the best overall in short-term load forecasting. PMID:26629825

Improved Neural Networks with Random Weights for Short-Term Load Forecasting.

PubMed

Lang, Kun; Zhang, Mingyuan; Yuan, Yongbo

2015-01-01

An effective forecasting model for short-term load plays a significant role in promoting the management efficiency of an electric power system. This paper proposes a new forecasting model based on the improved neural networks with random weights (INNRW). The key is to introduce a weighting technique to the inputs of the model and use a novel neural network to forecast the daily maximum load. Eight factors are selected as the inputs. A mutual information weighting algorithm is then used to allocate different weights to the inputs. The neural networks with random weights and kernels (KNNRW) is applied to approximate the nonlinear function between the selected inputs and the daily maximum load due to the fast learning speed and good generalization performance. In the application of the daily load in Dalian, the result of the proposed INNRW is compared with several previously developed forecasting models. The simulation experiment shows that the proposed model performs the best overall in short-term load forecasting.

14 CFR 23.726 - Ground load dynamic tests.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 1 2011-01-01 2011-01-01 false Ground load dynamic tests. 23.726 Section 23.726 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION AIRCRAFT... Landing Gear § 23.726 Ground load dynamic tests. (a) If compliance with the ground load requirements of...

14 CFR 23.726 - Ground load dynamic tests.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Ground load dynamic tests. 23.726 Section 23.726 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION AIRCRAFT... Landing Gear § 23.726 Ground load dynamic tests. (a) If compliance with the ground load requirements of...

Structural Dynamic Behavior of Wind Turbines

NASA Technical Reports Server (NTRS)

Thresher, Robert W.; Mirandy, Louis P.; Carne, Thomas G.; Lobitz, Donald W.; James, George H. III

2009-01-01

The structural dynamicist s areas of responsibility require interaction with most other members of the wind turbine project team. These responsibilities are to predict structural loads and deflections that will occur over the lifetime of the machine, ensure favorable dynamic responses through appropriate design and operational procedures, evaluate potential design improvements for their impact on dynamic loads and stability, and correlate load and control test data with design predictions. Load prediction has been a major concern in wind turbine designs to date, and it is perhaps the single most important task faced by the structural dynamics engineer. However, even if we were able to predict all loads perfectly, this in itself would not lead to an economic system. Reduction of dynamic loads, not merely a "design to loads" policy, is required to achieve a cost-effective design. The two processes of load prediction and structural design are highly interactive: loads and deflections must be known before designers and stress analysts can perform structural sizing, which in turn influences the loads through changes in stiffness and mass. Structural design identifies "hot spots" (local areas of high stress) that would benefit most from dynamic load alleviation. Convergence of this cycle leads to a turbine structure that is neither under-designed (which may result in structural failure), nor over-designed (which will lead to excessive weight and cost).

Achieving fast and stable failure detection in WDM Networks

NASA Astrophysics Data System (ADS)

Gao, Donghui; Zhou, Zhiyu; Zhang, Hanyi

2005-02-01

In dynamic networks, the failure detection time takes a major part of the convergence time, which is an important network performance index. To detect a node or link failure in the network, traditional protocols, like Hello protocol in OSPF or RSVP, exchanges keep-alive messages between neighboring nodes to keep track of the link/node state. But by default settings, it can get a minimum detection time in the measure of dozens of seconds, which can not meet the demands of fast network convergence and failure recovery. When configuring the related parameters to reduce the detection time, there will be notable instability problems. In this paper, we analyzed the problem and designed a new failure detection algorithm to reduce the network overhead of detection signaling. Through our experiment we found it is effective to enhance the stability by implicitly acknowledge other signaling messages as keep-alive messages. We conducted our proposal and the previous approaches on the ASON test-bed. The experimental results show that our algorithm gives better performances than previous schemes in about an order magnitude reduction of both false failure alarms and queuing delay to other messages, especially under light traffic load.

Optimal placement of unified power flow controllers to improve dynamic voltage stability using power system variable based voltage stability indices.

PubMed

Albatsh, Fadi M; Ahmad, Shameem; Mekhilef, Saad; Mokhlis, Hazlie; Hassan, M A

2015-01-01

This study examines a new approach to selecting the locations of unified power flow controllers (UPFCs) in power system networks based on a dynamic analysis of voltage stability. Power system voltage stability indices (VSIs) including the line stability index (LQP), the voltage collapse proximity indicator (VCPI), and the line stability index (Lmn) are employed to identify the most suitable locations in the system for UPFCs. In this study, the locations of the UPFCs are identified by dynamically varying the loads across all of the load buses to represent actual power system conditions. Simulations were conducted in a power system computer-aided design (PSCAD) software using the IEEE 14-bus and 39- bus benchmark power system models. The simulation results demonstrate the effectiveness of the proposed method. When the UPFCs are placed in the locations obtained with the new approach, the voltage stability improves. A comparison of the steady-state VSIs resulting from the UPFCs placed in the locations obtained with the new approach and with particle swarm optimization (PSO) and differential evolution (DE), which are static methods, is presented. In all cases, the UPFC locations given by the proposed approach result in better voltage stability than those obtained with the other approaches.

Optimal Placement of Unified Power Flow Controllers to Improve Dynamic Voltage Stability Using Power System Variable Based Voltage Stability Indices

PubMed Central

Albatsh, Fadi M.; Ahmad, Shameem; Mekhilef, Saad; Mokhlis, Hazlie; Hassan, M. A.

2015-01-01

This study examines a new approach to selecting the locations of unified power flow controllers (UPFCs) in power system networks based on a dynamic analysis of voltage stability. Power system voltage stability indices (VSIs) including the line stability index (LQP), the voltage collapse proximity indicator (VCPI), and the line stability index (Lmn) are employed to identify the most suitable locations in the system for UPFCs. In this study, the locations of the UPFCs are identified by dynamically varying the loads across all of the load buses to represent actual power system conditions. Simulations were conducted in a power system computer-aided design (PSCAD) software using the IEEE 14-bus and 39- bus benchmark power system models. The simulation results demonstrate the effectiveness of the proposed method. When the UPFCs are placed in the locations obtained with the new approach, the voltage stability improves. A comparison of the steady-state VSIs resulting from the UPFCs placed in the locations obtained with the new approach and with particle swarm optimization (PSO) and differential evolution (DE), which are static methods, is presented. In all cases, the UPFC locations given by the proposed approach result in better voltage stability than those obtained with the other approaches. PMID:25874560

Final Report. Analysis and Reduction of Complex Networks Under Uncertainty

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marzouk, Youssef M.; Coles, T.; Spantini, A.

2013-09-30

The project was a collaborative effort among MIT, Sandia National Laboratories (local PI Dr. Habib Najm), the University of Southern California (local PI Prof. Roger Ghanem), and The Johns Hopkins University (local PI Prof. Omar Knio, now at Duke University). Our focus was the analysis and reduction of large-scale dynamical systems emerging from networks of interacting components. Such networks underlie myriad natural and engineered systems. Examples important to DOE include chemical models of energy conversion processes, and elements of national infrastructure—e.g., electric power grids. Time scales in chemical systems span orders of magnitude, while infrastructure networks feature both local andmore » long-distance connectivity, with associated clusters of time scales. These systems also blend continuous and discrete behavior; examples include saturation phenomena in surface chemistry and catalysis, and switching in electrical networks. Reducing size and stiffness is essential to tractable and predictive simulation of these systems. Computational singular perturbation (CSP) has been effectively used to identify and decouple dynamics at disparate time scales in chemical systems, allowing reduction of model complexity and stiffness. In realistic settings, however, model reduction must contend with uncertainties, which are often greatest in large-scale systems most in need of reduction. Uncertainty is not limited to parameters; one must also address structural uncertainties—e.g., whether a link is present in a network—and the impact of random perturbations, e.g., fluctuating loads or sources. Research under this project developed new methods for the analysis and reduction of complex multiscale networks under uncertainty, by combining computational singular perturbation (CSP) with probabilistic uncertainty quantification. CSP yields asymptotic approximations of reduceddimensionality “slow manifolds” on which a multiscale dynamical system evolves. Introducing uncertainty in this context raised fundamentally new issues, e.g., how is the topology of slow manifolds transformed by parametric uncertainty? How to construct dynamical models on these uncertain manifolds? To address these questions, we used stochastic spectral polynomial chaos (PC) methods to reformulate uncertain network models and analyzed them using CSP in probabilistic terms. Finding uncertain manifolds involved the solution of stochastic eigenvalue problems, facilitated by projection onto PC bases. These problems motivated us to explore the spectral properties stochastic Galerkin systems. We also introduced novel methods for rank-reduction in stochastic eigensystems—transformations of a uncertain dynamical system that lead to lower storage and solution complexity. These technical accomplishments are detailed below. This report focuses on the MIT portion of the joint project.« less

Dynamic behaviors of historical wrought iron truss bridges: a field testing case study

NASA Astrophysics Data System (ADS)

Dai, Kaoshan; Wang, Ying; Hedric, Andrew; Huang, Zhenhua

2016-04-01

The U.S. transportation infrastructure has many wrought iron truss bridges that are more than a century old and still remain in use. Understanding the structural properties and identifying the health conditions of these historical bridges are essential to deciding the maintenance or rebuild plan of the bridges. This research involved an on-site full-scale system identification test case study on the historical Old Alton Bridge (a wrought iron truss bridge built in 1884 in Denton, Texas) using a wireless sensor network. The study results demonstrate a practical and convenient experimental system identification method for historical bridge structures. The method includes the basic steps of the in-situ experiment and in-house data analysis. Various excitation methods are studied for field testing, including ambient vibration by wind load, forced vibration by human jumping load, and forced vibration by human pulling load. Structural responses of the bridge under these different excitation approaches were analyzed and compared with numerical analysis results.

Ulva biomass as a co-substrate for stable anaerobic digestion of spent coffee grounds in continuous mode.

PubMed

Kim, Jaai; Kim, Hakchan; Lee, Changsoo

2017-10-01

Ulva biomass was evaluated as a co-substrate for anaerobic digestion of spent coffee grounds at varying organic loads (0.7-1.6g chemical oxygen demand (COD)/Ld) and substrate compositions. Co-digestion with Ulva (25%, COD basis) proved beneficial for SCG biomethanation in both terms of process performance and stability. The beneficial effect is much more pronounced at higher organic and hydraulic loads, with the highest COD removal and methane yield being 51.8% and 0.19L/g COD fed, respectively. The reactor microbial community structure changed dynamically during the experiment, and a dominance shift from hydrogenotrophic to aceticlastic methanogens occurred with increase in organic loading rate. Network analysis provides a comprehensive view of the microbial interactions involved in the system and confirms a direct positive correlation between Ulva input and methane productivity. A group of populations, including Methanobacterium- and Methanoculleus-related methanogens, was identified as a possible indicator for monitoring the biomethanation performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Experimental Study of Slabbing and Rockburst Induced by True-Triaxial Unloading and Local Dynamic Disturbance

NASA Astrophysics Data System (ADS)

Du, Kun; Tao, Ming; Li, Xi-bing; Zhou, Jian

2016-09-01

Slabbing/spalling and rockburst are unconventional types of failure of hard rocks under conditions of unloading and various dynamic loads in environments with high and complex initial stresses. In this study, the failure behaviors of different rock types (granite, red sandstone, and cement mortar) were investigated using a novel testing system coupled to true-triaxial static loads and local dynamic disturbances. An acoustic emission system and a high-speed camera were used to record the real-time fracturing processes. The true-triaxial unloading test results indicate that slabbing occurred in the granite and sandstone, whereas the cement mortar underwent shear failure. Under local dynamically disturbed loading, none of the specimens displayed obvious fracturing at low-amplitude local dynamic loading; however, the degree of rock failure increased as the local dynamic loading amplitude increased. The cement mortar displayed no failure during testing, showing a considerable load-carrying capacity after testing. The sandstone underwent a relatively stable fracturing process, whereas violent rockbursts occurred in the granite specimen. The fracturing process does not appear to depend on the direction of local dynamic loading, and the acoustic emission count rate during rock fragmentation shows that similar crack evolution occurred under the two test scenarios (true-triaxial unloading and local dynamically disturbed loading).

Forms and subannual variability of nitrogen and phosphorus loading to global river networks over the 20th century

NASA Astrophysics Data System (ADS)

Vilmin, Lauriane; Mogollón, José M.; Beusen, Arthur H. W.; Bouwman, Alexander F.

2018-04-01

Nitrogen (N) and phosphorus (P) play a major role in the biogeochemical functioning of aquatic systems. N and P transfer to surface freshwaters has amplified during the 20th century, which has led to widespread eutrophication problems. The contribution of different sources, natural and anthropogenic, to total N and P loading to river networks has recently been estimated yearly using the Integrated Model to Assess the Global Environment - Global Nutrient Model (IMAGE-GNM). However, eutrophic events generally result from a combination of physicochemical conditions governed by hydrological dynamics and the availability of specific nutrient forms that vary at subyearly timescales. In the present study, we define for each simulated nutrient source: i) its speciation, and ii) its subannual temporal pattern. Thereby, we simulate the monthly loads of different N (ammonium, nitrate + nitrite, and organic N) and P forms (dissolved and particulate inorganic P, and organic P) to global river networks over the whole 20th century at a half-degree spatial resolution. Results indicate that, together with an increase in the delivery of all nutrient forms to global rivers, the proportion of inorganic forms in total N and P inputs has risen from 30 to 43% and from 56 to 65%, respectively. The high loads originating from fertilized agricultural lands and the increasing proportion of sewage inputs have led to a greater proportion of DIN forms (ammonium and nitrate), that are usually more bioavailable. Soil loss from agricultural lands, which delivers large amounts of particle-bound inorganic P to surface freshwaters, has become the dominant P source, which is likely to lead to an increased accumulation of legacy P in slow flowing areas (e.g., lakes and reservoirs). While the TN:TP ratio of the loads has remained quite stable, the DIN:DIP molar ratio, which is likely to affect algal development the most, has increased from 18 to 27 globally. Human activities have also affected the timing of nutrient delivery to surface freshwaters. Increasing wastewater emissions in growing urban areas induces constant local pressure on the quality of aquatic systems by delivering generally highly bioavailable nutrient forms, even in periods of low runoff.

Adaptive dynamical networks

NASA Astrophysics Data System (ADS)

Maslennikov, O. V.; Nekorkin, V. I.

2017-10-01

Dynamical networks are systems of active elements (nodes) interacting with each other through links. Examples are power grids, neural structures, coupled chemical oscillators, and communications networks, all of which are characterized by a networked structure and intrinsic dynamics of their interacting components. If the coupling structure of a dynamical network can change over time due to nodal dynamics, then such a system is called an adaptive dynamical network. The term ‘adaptive’ implies that the coupling topology can be rewired; the term ‘dynamical’ implies the presence of internal node and link dynamics. The main results of research on adaptive dynamical networks are reviewed. Key notions and definitions of the theory of complex networks are given, and major collective effects that emerge in adaptive dynamical networks are described.

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

PubMed

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.

Traffic on complex networks: Towards understanding global statistical properties from microscopic density fluctuations

NASA Astrophysics Data System (ADS)

Tadić, Bosiljka; Thurner, Stefan; Rodgers, G. J.

2004-03-01

We study the microscopic time fluctuations of traffic load and the global statistical properties of a dense traffic of particles on scale-free cyclic graphs. For a wide range of driving rates R the traffic is stationary and the load time series exhibits antipersistence due to the regulatory role of the superstructure associated with two hub nodes in the network. We discuss how the superstructure affects the functioning of the network at high traffic density and at the jamming threshold. The degree of correlations systematically decreases with increasing traffic density and eventually disappears when approaching a jamming density Rc. Already before jamming we observe qualitative changes in the global network-load distributions and the particle queuing times. These changes are related to the occurrence of temporary crises in which the network-load increases dramatically, and then slowly falls back to a value characterizing free flow.

Calculation of reinforced-concrete frame strength under a simultaneous static cross section load and a column lateral impact

NASA Astrophysics Data System (ADS)

Belov, Nikolay; Yugov, Nikolay; Kopanitsa, Dmitry; Kopanitsa, Georgy; Yugov, Alexey; Kaparulin, Sergey; Plyaskin, Andrey; Kalichkina, Anna; Ustinov, Artyom

2016-01-01

When designing buildings with reinforced concrete that are planned to resist dynamic loads it is necessary to calculate this structural behavior under operational static and emergency impact and blast loads. Calculations of the structures under shock-wave loads can be performed by solving dynamic equations that do not consider static loads. Due to this fact the calculation of reinforced concrete frame under a simultaneous static and dynamic load in full 3d settings becomes a very non trivial and resource consuming problem. This problem can be split into two tasks. The first one is a shock-wave problem that can be solved using software package RANET-3, which allows solving the problem using finite elements method adapted for dynamic task. This method calculates strain-stress state of the material and its dynamic destruction, which is considered as growth and consolidation of micro defects under loading. On the second step the results of the first step are taken as input parameters for quasi static calculation of simultaneous static and dynamic load using finite elements method in AMP Civil Engineering-11.

Visualizing and Integrating AFSCN Utilization into a Common Operational Picture

NASA Astrophysics Data System (ADS)

Hays, B.; Carlile, A.; Mitchell, T.

The Department of Defense (DoD) and the 50th Space Network Operations Group Studies and Analysis branch (50th SCS/SCXI), located at Schriever AFB Colorado, face the unique challenge of forecasting the expected near term and future utilization of the Air Force Satellite Control Network (AFSCN). The forecasting timeframe covers the planned load from the current date to ten years out. The various satellite missions, satellite requirements, orbital regions, and ground architecture dynamics provide the model inputs and constraints that are used in generating the forecasted load. The AFSCN is the largest network the Air Force uses to control satellites worldwide. Each day, network personnel perform over 500 scheduled events-from satellite maneuvers to critical data downloads. The Forecasting Objective is to provide leadership with the insights necessary to manage the network today and tomorrow. For both today's needs and future needs, SCXI develops AFSCN utilization forecasts to optimize the ground system's coverage and capacity to meet user satellite requirements. SCXI also performs satellite program specific studies to determine network support feasibility. STK and STK Scheduler form the core of the tools used by SCXI. To establish this tool suite, we had to evaluate, evolve, and validate both the COTS products and our own developed code and processes. This began with calibrating the network model to emulate the real life scheduling environment of the AFSCN. Multiple STK Scheduler optimizing (de-confliction) algorithms, including Multi-Pass, Sequential, Random, and Neural, were evaluated and adjusted to determine applicability to the model and the accuracy of the prediction. Additionally, the scheduling Figure of Merit (FOM), which permits custom weighting of various parameters, was analyzed and tested to achieve the most accurate real life result. With the inherent capabilities of STK and the ability to wrap and automate output, SCXI is now able to visually communicate satellite loads in a manner never seen before in AFSCN management meetings. Scenarios such as regional antenna load stress, satellite missed opportunities, and the overall network "big picture" can be visually displayed in 3D versus the textual and line graph methods used for many years. This is the first step towards an integrated space awareness picture with an operational focus. SCXI is working on taking the visual forecast concept farther and begin fusing multiple sources of data to build a 50 SW Common Operating Picture (COP). The vision is to integrate more effective orbital determination processes, resource outages, current and forecasted satellite mission requirements, and future architectural changes into a real-time visual status to enable quick and responsive decisions. This COP would be utilized in a Wing Operations Center to provide up to the minute network status on where satellites are, which ground resources are in contact with them, and what resources are down. The ability to quickly absorb and process this data will enhance decision analysis and save valuable time in both day to day operations and wartime scenarios.

Dynamic tests of composite panels of an aircraft wing

NASA Astrophysics Data System (ADS)

Splichal, Jan; Pistek, Antonin; Hlinka, Jiri

2015-10-01

The paper describes the analysis of aerospace composite structures under dynamic loading. Today, it is common to use design procedures based on assumption of static loading only, and dynamic loading is rarely assumed and applied in design and certification of aerospace structures. The paper describes the application of dynamic loading for the design of aircraft structures, and the validation of the procedure on a selected structure. The goal is to verify the possibility of reducing the weight through improved design/modelling processes using dynamic loading instead of static loading. The research activity focuses on the modelling and testing of a composite panel representing a local segment of an aircraft wing section, investigating in particular the buckling behavior under dynamic loading. Finite Elements simulation tools are discussed, as well as the advantages of using a digital optical measurement system for the evaluation of the tests. The comparison of the finite element simulations with the results of the tests is presented.

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

NASA Astrophysics Data System (ADS)

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.

Aeroelastic Ground Wind Loads Analysis Tool for Launch Vehicles

NASA Technical Reports Server (NTRS)

Ivanco, Thomas G.

2016-01-01

Launch vehicles are exposed to ground winds during rollout and on the launch pad that can induce static and dynamic loads. Of particular concern are the dynamic loads caused by vortex shedding from nearly-cylindrical structures. When the frequency of vortex shedding nears that of a lowly-damped structural mode, the dynamic loads can be more than an order of magnitude greater than mean drag loads. Accurately predicting vehicle response to vortex shedding during the design and analysis cycles is difficult and typically exceeds the practical capabilities of modern computational fluid dynamics codes. Therefore, mitigating the ground wind loads risk typically requires wind-tunnel tests of dynamically-scaled models that are time consuming and expensive to conduct. In recent years, NASA has developed a ground wind loads analysis tool for launch vehicles to fill this analytical capability gap in order to provide predictions for prelaunch static and dynamic loads. This paper includes a background of the ground wind loads problem and the current state-of-the-art. It then discusses the history and significance of the analysis tool and the methodology used to develop it. Finally, results of the analysis tool are compared to wind-tunnel and full-scale data of various geometries and Reynolds numbers.

Cascade-based attacks on complex networks

NASA Astrophysics Data System (ADS)

Motter, Adilson E.; Lai, Ying-Cheng

2002-12-01

We live in a modern world supported by large, complex networks. Examples range from financial markets to communication and transportation systems. In many realistic situations the flow of physical quantities in the network, as characterized by the loads on nodes, is important. We show that for such networks where loads can redistribute among the nodes, intentional attacks can lead to a cascade of overload failures, which can in turn cause the entire or a substantial part of the network to collapse. This is relevant for real-world networks that possess a highly heterogeneous distribution of loads, such as the Internet and power grids. We demonstrate that the heterogeneity of these networks makes them particularly vulnerable to attacks in that a large-scale cascade may be triggered by disabling a single key node. This brings obvious concerns on the security of such systems.

Response of Metals and Metallic Structures to Dynamic Loading

DTIC Science & Technology

1978-05-01

materials for service by testing under high rates of loading. Impact tests such as the Charpy test, the drop-weight tear test, and the dynamic tear...have clearly shown this for precracked charpy specimens and for the drop-weight tear test. Hence, there is a strong need for additional dynamic...dynamic fracture resistance ( Charpy , dynamic-tear, drop-weight tear test, etc.), normally assures that fracture in dynamically loaded structures is

A Stimuli-Responsive Supramolecular Hydrogel for Controlled Release of Drug

NASA Astrophysics Data System (ADS)

Biswas, Subharanjan; Datta, Lakshmi Priya; Roy, Soumyajit

An inexpensive, facile, and environmentally benign method has been developed for the preparation of stimuli-responsive and self-healing polyacrylic acid-chitosan-based supramolecular hydrogels. Guanidine hydrochloride is used as the supramolecular crosslinker to form an interconnected network with polyacrylic acid-chitosan complex. Because of the dynamic equilibrium between the hydrogen-bonding sites of the components, the hydrogels were found to be self-healable and sensitive to biochemical-stimulus, such as pH. Controlled loading of drug like doxorubicin and its significant anticancer activity of such hydrogels is worth mentioning.

Fracture of Structural Materials under Dynamic Loading

DTIC Science & Technology

1981-03-25

in character- izing the dynamic fracture resistance of materials, and in designing equipment and procedures for measuring dynamic fracture toughness...useful in assessing the safety of structures under dynamic loads, in characterizing the dyraamic fracture resistance of materials, and in designing ...I INTRODUCTION Structures used by the United States Air Force must be designed to resist catastrophic fracture when subjected ti dynamic loads. For

Understanding the effects of different HIV transmission models in individual-based microsimulation of HIV epidemic dynamics in people who inject drugs

PubMed Central

MONTEIRO, J.F.G.; ESCUDERO, D.J.; WEINREB, C.; FLANIGAN, T.; GALEA, S.; FRIEDMAN, S.R.; MARSHALL, B.D.L.

2017-01-01

SUMMARY We investigated how different models of HIV transmission, and assumptions regarding the distribution of unprotected sex and syringe-sharing events (‘risk acts’), affect quantitative understanding of HIV transmission process in people who inject drugs (PWID). The individual-based model simulated HIV transmission in a dynamic sexual and injecting network representing New York City. We constructed four HIV transmission models: model 1, constant probabilities; model 2, random number of sexual and parenteral acts; model 3, viral load individual assigned; and model 4, two groups of partnerships (low and high risk). Overall, models with less heterogeneity were more sensitive to changes in numbers risk acts, producing HIV incidence up to four times higher than that empirically observed. Although all models overestimated HIV incidence, micro-simulations with greater heterogeneity in the HIV transmission modelling process produced more robust results and better reproduced empirical epidemic dynamics. PMID:26753627

Gust prediction via artificial hair sensor array and neural network

NASA Astrophysics Data System (ADS)

Pankonien, Alexander M.; Thapa Magar, Kaman S.; Beblo, Richard V.; Reich, Gregory W.

2017-04-01

Gust Load Alleviation (GLA) is an important aspect of flight dynamics and control that reduces structural loadings and enhances ride quality. In conventional GLA systems, the structural response to aerodynamic excitation informs the control scheme. A phase lag, imposed by inertia, between the excitation and the measurement inherently limits the effectiveness of these systems. Hence, direct measurement of the aerodynamic loading can eliminate this lag, providing valuable information for effective GLA system design. Distributed arrays of Artificial Hair Sensors (AHS) are ideal for surface flow measurements that can be used to predict other necessary parameters such as aerodynamic forces, moments, and turbulence. In previous work, the spatially distributed surface flow velocities obtained from an array of artificial hair sensors using a Single-State (or feedforward) Neural Network were found to be effective in estimating the steady aerodynamic parameters such as air speed, angle of attack, lift and moment coefficient. This paper extends the investigation of the same configuration to unsteady force and moment estimation, which is important for active GLA control design. Implementing a Recurrent Neural Network that includes previous-timestep sensor information, the hair sensor array is shown to be capable of capturing gust disturbances with a wide range of periods, reducing predictive error in lift and moment by 68% and 52% respectively. The L2 norms of the first layer of the weight matrices were compared showing a 23% emphasis on prior versus current information. The Recurrent architecture also improves robustness, exhibiting only a 30% increase in predictive error when undertrained as compared to a 170% increase by the Single-State NN. This diverse, localized information can thus be directly implemented into a control scheme that alleviates the gusts without waiting for a structural response or requiring user-intensive sensor calibration.

Congestion transition in air traffic networks.

PubMed

Monechi, Bernardo; Servedio, Vito D P; Loreto, Vittorio

2015-01-01

Air Transportation represents a very interesting example of a complex techno-social system whose importance has considerably grown in time and whose management requires a careful understanding of the subtle interplay between technological infrastructure and human behavior. Despite the competition with other transportation systems, a growth of air traffic is still foreseen in Europe for the next years. The increase of traffic load could bring the current Air Traffic Network above its capacity limits so that safety standards and performances might not be guaranteed anymore. Lacking the possibility of a direct investigation of this scenario, we resort to computer simulations in order to quantify the disruptive potential of an increase in traffic load. To this end we model the Air Transportation system as a complex dynamical network of flights controlled by humans who have to solve potentially dangerous conflicts by redirecting aircraft trajectories. The model is driven and validated through historical data of flight schedules in a European national airspace. While correctly reproducing actual statistics of the Air Transportation system, e.g., the distribution of delays, the model allows for theoretical predictions. Upon an increase of the traffic load injected in the system, the model predicts a transition from a phase in which all conflicts can be successfully resolved, to a phase in which many conflicts cannot be resolved anymore. We highlight how the current flight density of the Air Transportation system is well below the transition, provided that controllers make use of a special re-routing procedure. While the congestion transition displays a universal scaling behavior, its threshold depends on the conflict solving strategy adopted. Finally, the generality of the modeling scheme introduced makes it a flexible general tool to simulate and control Air Transportation systems in realistic and synthetic scenarios.

Neuro-Fuzzy Computational Technique to Control Load Frequency in Hydro-Thermal Interconnected Power System

NASA Astrophysics Data System (ADS)

Prakash, S.; Sinha, S. K.

2015-09-01

In this research work, two areas hydro-thermal power system connected through tie-lines is considered. The perturbation of frequencies at the areas and resulting tie line power flows arise due to unpredictable load variations that cause mismatch between the generated and demanded powers. Due to rising and falling power demand, the real and reactive power balance is harmed; hence frequency and voltage get deviated from nominal value. This necessitates designing of an accurate and fast controller to maintain the system parameters at nominal value. The main purpose of system generation control is to balance the system generation against the load and losses so that the desired frequency and power interchange between neighboring systems are maintained. The intelligent controllers like fuzzy logic, artificial neural network (ANN) and hybrid fuzzy neural network approaches are used for automatic generation control for the two area interconnected power systems. Area 1 consists of thermal reheat power plant whereas area 2 consists of hydro power plant with electric governor. Performance evaluation is carried out by using intelligent (ANFIS, ANN and fuzzy) control and conventional PI and PID control approaches. To enhance the performance of controller sliding surface i.e. variable structure control is included. The model of interconnected power system has been developed with all five types of said controllers and simulated using MATLAB/SIMULINK package. The performance of the intelligent controllers has been compared with the conventional PI and PID controllers for the interconnected power system. A comparison of ANFIS, ANN, Fuzzy and PI, PID based approaches shows the superiority of proposed ANFIS over ANN, fuzzy and PI, PID. Thus the hybrid fuzzy neural network controller has better dynamic response i.e., quick in operation, reduced error magnitude and minimized frequency transients.

Tactical Network Load Balancing in Multi-Gateway Wireless Sensor Networks

DTIC Science & Technology

2013-12-01

writeup scrsz = get( 0 ,’ScreenSize’); %Creation of the random Sensor Network fig = figure(1); set(fig, ’Position’,[1 scrsz( 4 )*.25 scrsz(3)*.7...thesis writeup scrsz = get( 0 ,’ScreenSize’); %Creation of the random Sensor Network fig = figure(1); set(fig, ’Position’,[1 scrsz( 4 )*.25 scrsz(3)*.7...TYPE AND DATES COVERED Master’s Thesis 4 . TITLE AND SUBTITLE TACTICAL NETWORK LOAD BALANCING IN MULTI-GATEWAY WIRELESS SENSOR NETWORKS 5

Human-Systems Integration (HSI) and the Network Integration Evaluations (NIEs), Part 3: Mitigating Cognitive Load in Network-Enabled Mission Command

DTIC Science & Technology

2016-06-01

ARL-TR-7698 ● JUNE 2016 US Army Research Laboratory Human -Systems Integration (HSI) and the Network Integration Evaluations...ARL-TR-7698 ● JUNE 2016 US Army Research Laboratory Human -Systems Integration (HSI) and the Network Integration Evaluations (NIEs), Part 3...Mitigating Cognitive Load in Network-Enabled Mission Command by John K Hawley Human Research and Engineering Directorate, ARL Michael W

SACFIR: SDN-Based Application-Aware Centralized Adaptive Flow Iterative Reconfiguring Routing Protocol for WSNs.

PubMed

Aslam, Muhammad; Hu, Xiaopeng; Wang, Fan

2017-12-13

Smart reconfiguration of a dynamic networking environment is offered by the central control of Software-Defined Networking (SDN). Centralized SDN-based management architectures are capable of retrieving global topology intelligence and decoupling the forwarding plane from the control plane. Routing protocols developed for conventional Wireless Sensor Networks (WSNs) utilize limited iterative reconfiguration methods to optimize environmental reporting. However, the challenging networking scenarios of WSNs involve a performance overhead due to constant periodic iterative reconfigurations. In this paper, we propose the SDN-based Application-aware Centralized adaptive Flow Iterative Reconfiguring (SACFIR) routing protocol with the centralized SDN iterative solver controller to maintain the load-balancing between flow reconfigurations and flow allocation cost. The proposed SACFIR's routing protocol offers a unique iterative path-selection algorithm, which initially computes suitable clustering based on residual resources at the control layer and then implements application-aware threshold-based multi-hop report transmissions on the forwarding plane. The operation of the SACFIR algorithm is centrally supervised by the SDN controller residing at the Base Station (BS). This paper extends SACFIR to SDN-based Application-aware Main-value Centralized adaptive Flow Iterative Reconfiguring (SAMCFIR) to establish both proactive and reactive reporting. The SAMCFIR transmission phase enables sensor nodes to trigger direct transmissions for main-value reports, while in the case of SACFIR, all reports follow computed routes. Our SDN-enabled proposed models adjust the reconfiguration period according to the traffic burden on sensor nodes, which results in heterogeneity awareness, load-balancing and application-specific reconfigurations of WSNs. Extensive experimental simulation-based results show that SACFIR and SAMCFIR yield the maximum scalability, network lifetime and stability period when compared to existing routing protocols.

SACFIR: SDN-Based Application-Aware Centralized Adaptive Flow Iterative Reconfiguring Routing Protocol for WSNs

PubMed Central

Hu, Xiaopeng; Wang, Fan

2017-01-01

Smart reconfiguration of a dynamic networking environment is offered by the central control of Software-Defined Networking (SDN). Centralized SDN-based management architectures are capable of retrieving global topology intelligence and decoupling the forwarding plane from the control plane. Routing protocols developed for conventional Wireless Sensor Networks (WSNs) utilize limited iterative reconfiguration methods to optimize environmental reporting. However, the challenging networking scenarios of WSNs involve a performance overhead due to constant periodic iterative reconfigurations. In this paper, we propose the SDN-based Application-aware Centralized adaptive Flow Iterative Reconfiguring (SACFIR) routing protocol with the centralized SDN iterative solver controller to maintain the load-balancing between flow reconfigurations and flow allocation cost. The proposed SACFIR’s routing protocol offers a unique iterative path-selection algorithm, which initially computes suitable clustering based on residual resources at the control layer and then implements application-aware threshold-based multi-hop report transmissions on the forwarding plane. The operation of the SACFIR algorithm is centrally supervised by the SDN controller residing at the Base Station (BS). This paper extends SACFIR to SDN-based Application-aware Main-value Centralized adaptive Flow Iterative Reconfiguring (SAMCFIR) to establish both proactive and reactive reporting. The SAMCFIR transmission phase enables sensor nodes to trigger direct transmissions for main-value reports, while in the case of SACFIR, all reports follow computed routes. Our SDN-enabled proposed models adjust the reconfiguration period according to the traffic burden on sensor nodes, which results in heterogeneity awareness, load-balancing and application-specific reconfigurations of WSNs. Extensive experimental simulation-based results show that SACFIR and SAMCFIR yield the maximum scalability, network lifetime and stability period when compared to existing routing protocols. PMID:29236031

Quantum load balancing in ad hoc networks

NASA Astrophysics Data System (ADS)

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.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Panait, A.; Serban, V.

The paper presents SERB -- SITON method to control, limit and damp the shocks, vibration, impact load and seismic movements with applications in buildings, equipment and pipe networks (herein called: 'components'). The elimination or reduction of shocks, vibration, impact load and seismic movements is a difficult problem, still improperly handled theoretically and practically because many times the phenomena are random in character and the behavior of components is non-linear with variations of the properties in time, variations that lead to the increase or decrease of the energy and impulse transfer from the dynamic excitation to the components. Moreover, the existingmore » supports and dampers applied today, are not efficient enough in the reduction of the dynamic movement for all the frequency ranges met with in the technical application field. The stiffness and damping of classic supports do not allow a good isolation of components against shocks and vibrations so to eliminate their propagation to the environment and neither do they provide a satisfactory protection of the components sensitive to shocks and vibrations and seismic movements coming from the environment. In order to reduce the effects of shocks, vibrations impact and seismic movements on the components, this paper presents the results obtained by SITON on the concept, design, construction, experimental testing and application of new types of supports, devices and thin lattice structure, called 'SERB', capable to overtake large static loads, to allow displacements from impact, thermal expansions or yielding of supports and which, in any work position, can elastically overtake large dynamic loads or impact loads which they damp. The new supports and devices and thin lattice structure allow their adjustment without the occurrence of over-stressing in the components due to their non -- linear geometric behavior, and the contact pressure among the elements is limited to pre-set values to avoid blocking phenomena that generates great stresses induced by thermal expansion for example. Due to their characteristics of adjustment to the actual position and level of stress, SERB supports, devices and thin lattice structure show minimal effects on the components stress condition whenever the installation and computation errors. Herein below it is a presentation of the actual results obtained by SITON in the isolation of heavy equipment and pipe networks and others in process of application for buildings. Due to the very good results obtained in the isolation against shocks, vibrations and seismic movements at components in the conventional industry, there is the proposal to implement SERB-SITON method to the increase of the safety level at new or existing Nuclear Power Plants or to protect nuclear building against missiles and airplane crush impact. (authors)« less

Non-Deterministic Dynamic Instability of Composite Shells

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Abumeri, Galib H.

2004-01-01

A computationally effective method is described to evaluate the non-deterministic dynamic instability (probabilistic dynamic buckling) of thin composite shells. The method is a judicious combination of available computer codes for finite element, composite mechanics, and probabilistic structural analysis. The solution method is incrementally updated Lagrangian. It is illustrated by applying it to thin composite cylindrical shell subjected to dynamic loads. Both deterministic and probabilistic buckling loads are evaluated to demonstrate the effectiveness of the method. A universal plot is obtained for the specific shell that can be used to approximate buckling loads for different load rates and different probability levels. Results from this plot show that the faster the rate, the higher the buckling load and the shorter the time. The lower the probability, the lower is the buckling load for a specific time. Probabilistic sensitivity results show that the ply thickness, the fiber volume ratio and the fiber longitudinal modulus, dynamic load and loading rate are the dominant uncertainties, in that order.

Dynamic Probabilistic Instability of Composite Structures

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

2009-01-01

A computationally effective method is described to evaluate the non-deterministic dynamic instability (probabilistic dynamic buckling) of thin composite shells. The method is a judicious combination of available computer codes for finite element, composite mechanics and probabilistic structural analysis. The solution method is incrementally updated Lagrangian. It is illustrated by applying it to thin composite cylindrical shell subjected to dynamic loads. Both deterministic and probabilistic buckling loads are evaluated to demonstrate the effectiveness of the method. A universal plot is obtained for the specific shell that can be used to approximate buckling loads for different load rates and different probability levels. Results from this plot show that the faster the rate, the higher the buckling load and the shorter the time. The lower the probability, the lower is the buckling load for a specific time. Probabilistic sensitivity results show that the ply thickness, the fiber volume ratio and the fiber longitudinal modulus, dynamic load and loading rate are the dominant uncertainties in that order.

Load Forecasting Based Distribution System Network Reconfiguration -- A Distributed Data-Driven Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, Huaiguang; Zhang, Yingchen; Muljadi, Eduard

In this paper, a short-term load forecasting approach based network reconfiguration is proposed in a parallel manner. Specifically, a support vector regression (SVR) based short-term load forecasting approach is designed to provide an accurate load prediction and benefit the network reconfiguration. Because of the nonconvexity of the three-phase balanced optimal power flow, a second-order cone program (SOCP) based approach is used to relax the optimal power flow problem. Then, the alternating direction method of multipliers (ADMM) is used to compute the optimal power flow in distributed manner. Considering the limited number of the switches and the increasing computation capability, themore » proposed network reconfiguration is solved in a parallel way. The numerical results demonstrate the feasible and effectiveness of the proposed approach.« less

Dynamic load environment of bridge-mounted sign support structures : research implementation plan.

DOT National Transportation Integrated Search

2005-09-01

Welded aluminum highway sign support trusses must withstand in-service dynamic loads, which largely : constitute the fatigue environment. Sources of these dynamic loads include the natural wind and seismic : environment, the artificial wind environme...

The influence of passenger flow on the topology characteristics of urban rail transit networks

NASA Astrophysics Data System (ADS)

Hu, Yingyue; Chen, Feng; Chen, Peiwen; Tan, Yurong

2017-05-01

Current researches on the network characteristics of metro networks are generally carried out on topology networks without passenger flows running on it, thus more complex features of the networks with ridership loaded on it cannot be captured. In this study, we incorporated the load of metro networks, passenger volume, into the exploration of network features. Thus, the network can be examined in the context of operation, which is the ultimate purpose of the existence of a metro network. To this end, section load was selected as an edge weight to demonstrate the influence of ridership on the network, and a weighted calculation method for complex network indicators and robustness were proposed to capture the unique behaviors of a metro network with passengers flowing in it. The proposed method was applied on Beijing Subway. Firstly, the passenger volume in terms of daily origin and destination matrix was extracted from exhausted transit smart card data. Using the established approach and the matrix as weighting, common indicators of complex network including clustering coefficient, betweenness and degree were calculated, and network robustness were evaluated under potential attacks. The results were further compared to that of unweighted networks, and it suggests indicators of the network with consideration of passenger volumes differ from that without ridership to some extent, and networks tend to be more vulnerable than that without load on it. The significance sequence for the stations can be changed. By introducing passenger flow weighting, actual operation status of the network can be reflected more accurately. It is beneficial to determine the crucial stations and make precautionary measures for the entire network’s operation security.

Photodiode Preamplifier for Laser Ranging With Weak Signals

NASA Technical Reports Server (NTRS)

Abramovici, Alexander; Chapsky, Jacob

2007-01-01

An improved preamplifier circuit has been designed for processing the output of an avalanche photodiode (APD) that is used in a high-resolution laser ranging system to detect laser pulses returning from a target. The improved circuit stands in contrast to prior such circuits in which the APD output current pulses are made to pass, variously, through wide-band or narrow-band load networks before preamplification. A major disadvantage of the prior wide-band load networks is that they are highly susceptible to noise, which degrades timing resolution. A major disadvantage of the prior narrow-band load networks is that they make it difficult to sample the amplitudes of the narrow laser pulses ordinarily used in ranging. In the improved circuit, a load resistor is connected to the APD output and its value is chosen so that the time constant defined by this resistance and the APD capacitance is large, relative to the duration of a laser pulse. The APD capacitance becomes initially charged by the pulse of current generated by a return laser pulse, so that the rise time of the load-network output is comparable to the duration of the return pulse. Thus, the load-network output is characterized by a fast-rising leading edge, which is necessary for accurate pulse timing. On the other hand, the resistance-capacitance combination constitutes a lowpass filter, which helps to suppress noise. The long time constant causes the load network output pulse to have a long shallow-sloping trailing edge, which makes it easy to sample the amplitude of the return pulse. The output of the load network is fed to a low-noise, wide-band amplifier. The amplifier must be a wide-band one in order to preserve the sharp pulse rise for timing. The suppression of noise and the use of a low-noise amplifier enable the ranging system to detect relatively weak return pulses.

Evaluation of multicast schemes in optical burst-switched networks: the case with dynamic sessions

NASA Astrophysics Data System (ADS)

Jeong, Myoungki; Qiao, Chunming; Xiong, Yijun; Vandenhoute, Marc

2000-10-01

In this paper, we evaluate the performance of several multicast schemes in optical burst-switched WDM networks taking into accounts the overheads due to control packets and guard bands (Gbs) of bursts on separate channels (wavelengths). A straightforward scheme is called Separate Multicasting (S-MCAST) where each source node constructs separate bursts for its multicast (per each multicast session) and unicast traffic. To reduce the overhead due to Gbs (and control packets), one may piggyback the multicast traffic in bursts containing unicast traffic using a scheme called Multiple Unicasting (M-UCAST). The third scheme is called Tree-Shared Multicasting (TS-MCAST) wehreby multicast traffic belonging to multiple multicast sesions can be mixed together in a burst, which is delivered via a shared multicast tree. In [1], we have evaluated several multicast schemes with static sessions at the flow level. In this paper, we perform a simple analysis for the multicast schemes and evaluate the performance of three multicast schemes, focusing on the case with dynamic sessions in terms of the link utilization, bandwidth consumption, blocking (loss) probability, goodput and the processing loads.

Cooperative Strategy for Optimal Management of Smart Grids by Wavelet RNNs and Cloud Computing.

PubMed

Napoli, Christian; Pappalardo, Giuseppe; Tina, Giuseppe Marco; Tramontana, Emiliano

2016-08-01

Advanced smart grids have several power sources that contribute with their own irregular dynamic to the power production, while load nodes have another dynamic. Several factors have to be considered when using the owned power sources for satisfying the demand, i.e., production rate, battery charge and status, variable cost of externally bought energy, and so on. The objective of this paper is to develop appropriate neural network architectures that automatically and continuously govern power production and dispatch, in order to maximize the overall benefit over a long time. Such a control will improve the fundamental work of a smart grid. For this, status data of several components have to be gathered, and then an estimate of future power production and demand is needed. Hence, the neural network-driven forecasts are apt in this paper for renewable nonprogrammable energy sources. Then, the produced energy as well as the stored one can be supplied to consumers inside a smart grid, by means of digital technology. Among the sought benefits, reduced costs and increasing reliability and transparency are paramount.

Local empathy provides global minimization of congestion in communication networks

NASA Astrophysics Data System (ADS)

Meloni, Sandro; Gómez-Gardeñes, Jesús

2010-11-01

We present a mechanism to avoid congestion in complex networks based on a local knowledge of traffic conditions and the ability of routers to self-coordinate their dynamical behavior. In particular, routers make use of local information about traffic conditions to either reject or accept information packets from their neighbors. We show that when nodes are only aware of their own congestion state they self-organize into a hierarchical configuration that delays remarkably the onset of congestion although leading to a sharp first-order-like congestion transition. We also consider the case when nodes are aware of the congestion state of their neighbors. In this case, we show that empathy between nodes is strongly beneficial to the overall performance of the system and it is possible to achieve larger values for the critical load together with a smooth, second-order-like, transition. Finally, we show how local empathy minimize the impact of congestion as much as global minimization. Therefore, here we present an outstanding example of how local dynamical rules can optimize the system’s functioning up to the levels reached using global knowledge.

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

NASA Astrophysics Data System (ADS)

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.

Load Balancing in Structured P2P Networks

NASA Astrophysics Data System (ADS)

Zhu, Yingwu

In this chapter we start by addressing the importance and necessity of load balancing in structured P2P networks, due to three main reasons. First, structured P2P networks assume uniform peer capacities while peer capacities are heterogeneous in deployed P2P networks. Second, resorting to pseudo-uniformity of the hash function used to generate node IDs and data item keys leads to imbalanced overlay address space and item distribution. Lastly, placement of data items cannot be randomized in some applications (e.g., range searching). We then present an overview of load aggregation and dissemination techniques that are required by many load balancing algorithms. Two techniques are discussed including tree structure-based approach and gossip-based approach. They make different tradeoffs between estimate/aggregate accuracy and failure resilience. To address the issue of load imbalance, three main solutions are described: virtual server-based approach, power of two choices, and address-space and item balancing. While different in their designs, they all aim to improve balance on the address space and data item distribution. As a case study, the chapter discusses a virtual server-based load balancing algorithm that strives to ensure fair load distribution among nodes and minimize load balancing cost in bandwidth. Finally, the chapter concludes with future research and a summary.

Neural Network approach to assess the thermal affected zone around the injection well in a groundwater heat pump system

NASA Astrophysics Data System (ADS)

Lo Russo, Stefano; Taddia, Glenda; Verda, Vittorio

2014-05-01

The common use of well doublets for groundwater-sourced heating or cooling results in a thermal plume of colder or warmer re-injected groundwater known as the Thermal Affected Zone(TAZ). The plumes may be regarded either as a potential anthropogenic geothermal resource or as pollution, depending on downstream aquifer usage. A fundamental aspect in groundwater heat pump (GWHP) plant design is the correct evaluation of the thermally affected zone that develops around the injection well. Temperature anomalies are detected through numerical methods. Crucial elements in the process of thermal impact assessment are the sizes of installations, their position, the heating/cooling load of the building, and the temperature drop/increase imposed on the re-injected water flow. For multiple-well schemes, heterogeneous aquifers, or variable heating and cooling loads, numerical models that simulate groundwater and heat transport are needed. These tools should consider numerous scenarios obtained considering different heating/cooling loads, positions, and operating modes. Computational fluid dynamic (CFD) models are widely used in this field because they offer the opportunity to calculate the time evolution of the thermal plume produced by a heat pump, depending on the characteristics of the subsurface and the heat pump. Nevertheless, these models require large computational efforts, and therefore their use may be limited to a reasonable number of scenarios. Neural networks could represent an alternative to CFD for assessing the TAZ under different scenarios referring to a specific site. The use of neural networks is proposed to determine the time evolution of the groundwater temperature downstream of an installation as a function of the possible utilization profiles of the heat pump. The main advantage of neural network modeling is the possibility of evaluating a large number of scenarios in a very short time, which is very useful for the preliminary analysis of future multiple installations. The neural network is trained using the results from a CFD model (FEFLOW) applied to the installation at Politecnico di Torino (Italy) under several operating conditions.

Experimental demonstration of multi-dimensional resources integration for service provisioning in cloud radio over fiber network

NASA Astrophysics Data System (ADS)

Yang, Hui; Zhang, Jie; Ji, Yuefeng; He, Yongqi; Lee, Young

2016-07-01

Cloud radio access network (C-RAN) becomes a promising scenario to accommodate high-performance services with ubiquitous user coverage and real-time cloud computing in 5G area. However, the radio network, optical network and processing unit cloud have been decoupled from each other, so that their resources are controlled independently. Traditional architecture cannot implement the resource optimization and scheduling for the high-level service guarantee due to the communication obstacle among them with the growing number of mobile internet users. In this paper, we report a study on multi-dimensional resources integration (MDRI) for service provisioning in cloud radio over fiber network (C-RoFN). A resources integrated provisioning (RIP) scheme using an auxiliary graph is introduced based on the proposed architecture. The MDRI can enhance the responsiveness to dynamic end-to-end user demands and globally optimize radio frequency, optical network and processing resources effectively to maximize radio coverage. The feasibility of the proposed architecture is experimentally verified on OpenFlow-based enhanced SDN testbed. The performance of RIP scheme under heavy traffic load scenario is also quantitatively evaluated to demonstrate the efficiency of the proposal based on MDRI architecture in terms of resource utilization, path blocking probability, network cost and path provisioning latency, compared with other provisioning schemes.

Experimental demonstration of multi-dimensional resources integration for service provisioning in cloud radio over fiber network.

PubMed

Yang, Hui; Zhang, Jie; Ji, Yuefeng; He, Yongqi; Lee, Young

2016-07-28

Cloud radio access network (C-RAN) becomes a promising scenario to accommodate high-performance services with ubiquitous user coverage and real-time cloud computing in 5G area. However, the radio network, optical network and processing unit cloud have been decoupled from each other, so that their resources are controlled independently. Traditional architecture cannot implement the resource optimization and scheduling for the high-level service guarantee due to the communication obstacle among them with the growing number of mobile internet users. In this paper, we report a study on multi-dimensional resources integration (MDRI) for service provisioning in cloud radio over fiber network (C-RoFN). A resources integrated provisioning (RIP) scheme using an auxiliary graph is introduced based on the proposed architecture. The MDRI can enhance the responsiveness to dynamic end-to-end user demands and globally optimize radio frequency, optical network and processing resources effectively to maximize radio coverage. The feasibility of the proposed architecture is experimentally verified on OpenFlow-based enhanced SDN testbed. The performance of RIP scheme under heavy traffic load scenario is also quantitatively evaluated to demonstrate the efficiency of the proposal based on MDRI architecture in terms of resource utilization, path blocking probability, network cost and path provisioning latency, compared with other provisioning schemes.

Performance evaluation of multi-stratum resources optimization with network functions virtualization for cloud-based radio over optical fiber networks.

PubMed

Yang, Hui; He, Yongqi; Zhang, Jie; Ji, Yuefeng; Bai, Wei; Lee, Young

2016-04-18

Cloud radio access network (C-RAN) has become a promising scenario to accommodate high-performance services with ubiquitous user coverage and real-time cloud computing using cloud BBUs. In our previous work, we implemented cross stratum optimization of optical network and application stratums resources that allows to accommodate the services in optical networks. In view of this, this study extends to consider the multiple dimensional resources optimization of radio, optical and BBU processing in 5G age. We propose a novel multi-stratum resources optimization (MSRO) architecture with network functions virtualization for cloud-based radio over optical fiber networks (C-RoFN) using software defined control. A global evaluation scheme (GES) for MSRO in C-RoFN is introduced based on the proposed architecture. The MSRO can enhance the responsiveness to dynamic end-to-end user demands and globally optimize radio frequency, optical and BBU resources effectively to maximize radio coverage. The efficiency and feasibility of the proposed architecture are experimentally demonstrated on OpenFlow-based enhanced SDN testbed. The performance of GES under heavy traffic load scenario is also quantitatively evaluated based on MSRO architecture in terms of resource occupation rate and path provisioning latency, compared with other provisioning scheme.

Experimental demonstration of multi-dimensional resources integration for service provisioning in cloud radio over fiber network

PubMed Central

Yang, Hui; Zhang, Jie; Ji, Yuefeng; He, Yongqi; Lee, Young

2016-01-01

Cloud radio access network (C-RAN) becomes a promising scenario to accommodate high-performance services with ubiquitous user coverage and real-time cloud computing in 5G area. However, the radio network, optical network and processing unit cloud have been decoupled from each other, so that their resources are controlled independently. Traditional architecture cannot implement the resource optimization and scheduling for the high-level service guarantee due to the communication obstacle among them with the growing number of mobile internet users. In this paper, we report a study on multi-dimensional resources integration (MDRI) for service provisioning in cloud radio over fiber network (C-RoFN). A resources integrated provisioning (RIP) scheme using an auxiliary graph is introduced based on the proposed architecture. The MDRI can enhance the responsiveness to dynamic end-to-end user demands and globally optimize radio frequency, optical network and processing resources effectively to maximize radio coverage. The feasibility of the proposed architecture is experimentally verified on OpenFlow-based enhanced SDN testbed. The performance of RIP scheme under heavy traffic load scenario is also quantitatively evaluated to demonstrate the efficiency of the proposal based on MDRI architecture in terms of resource utilization, path blocking probability, network cost and path provisioning latency, compared with other provisioning schemes. PMID:27465296

Consideration of dynamic loads on the vertical tail by the theory of flat yawing maneuvers

NASA Technical Reports Server (NTRS)

Boshar, John; Davis, Philip

1946-01-01

Dynamic yawing effects on vertical tail loads are considered by a theory of flat yawing maneuvers. A comparison is shown between computed loads and the loads measured in flight in a fighter airplane. The dynamic effects were investigated on a large flying boat for both an abrupt rudder deflection and a sinusoidal rudder deflection. Only a moderate amount of control deflection was found to be necessary to attain the ultimate design load on the tail. In order to take into account dynamic effects in design, specifications of yawing maneuverability or control movement are needed.

A Method of Data Aggregation for Wearable Sensor Systems

PubMed Central

Shen, Bo; Fu, Jun-Song

2016-01-01

Data aggregation has been considered as an effective way to decrease the data to be transferred in sensor networks. Particularly for wearable sensor systems, smaller battery has less energy, which makes energy conservation in data transmission more important. Nevertheless, wearable sensor systems usually have features like frequently dynamic changes of topologies and data over a large range, of which current aggregating methods can’t adapt to the demand. In this paper, we study the system composed of many wearable devices with sensors, such as the network of a tactical unit, and introduce an energy consumption-balanced method of data aggregation, named LDA-RT. In the proposed method, we develop a query algorithm based on the idea of ‘happened-before’ to construct a dynamic and energy-balancing routing tree. We also present a distributed data aggregating and sorting algorithm to execute top-k query and decrease the data that must be transferred among wearable devices. Combining these algorithms, LDA-RT tries to balance the energy consumptions for prolonging the lifetime of wearable sensor systems. Results of evaluation indicate that LDA-RT performs well in constructing routing trees and energy balances. It also outperforms the filter-based top-k monitoring approach in energy consumption, load balance, and the network’s lifetime, especially for highly dynamic data sources. PMID:27347953

Thermal energy storage to minimize cost and improve efficiency of a polygeneration district energy system in a real-time electricity market

DOE Office of Scientific and Technical Information (OSTI.GOV)

Powell, Kody M.; Kim, Jong Suk; Cole, Wesley J.

2016-10-01

District energy systems can produce low-cost utilities for large energy networks, but can also be a resource for the electric grid by their ability to ramp production or to store thermal energy by responding to real-time market signals. In this work, dynamic optimization exploits the flexibility of thermal energy storage by determining optimal times to store and extract excess energy. This concept is applied to a polygeneration distributed energy system with combined heat and power, district heating, district cooling, and chilled water thermal energy storage. The system is a university campus responsible for meeting the energy needs of tens ofmore » thousands of people. The objective for the dynamic optimization problem is to minimize cost over a 24-h period while meeting multiple loads in real time. The paper presents a novel algorithm to solve this dynamic optimization problem with energy storage by decomposing the problem into multiple static mixed-integer nonlinear programming (MINLP) problems. Another innovative feature of this work is the study of a large, complex energy network which includes the interrelations of a wide variety of energy technologies. Results indicate that a cost savings of 16.5% is realized when the system can participate in the wholesale electricity market.« less

Proceedings of the European Conference (4th), Held in Wageningen, The Netherlands on March 21-23, 1989. Volume 2

DTIC Science & Technology

1989-03-01

comparison between the two. Tyre self-excited vibration can be caused by lack of uniforuity and/or out-of-balance. The authors suggest that driving ... safety is best described by the ’Dynamic Load Factor’ which relates the ainimum rolling dynamic load to the static tyre load. Dynamic Load Factors are

Performance evaluation of reactive and proactive routing protocol in IEEE 802.11 ad hoc network

NASA Astrophysics Data System (ADS)

Hamma, Salima; Cizeron, Eddy; Issaka, Hafiz; Guédon, Jean-Pierre

2006-10-01

Wireless technology based on the IEEE 802.11 standard is widely deployed. This technology is used to support multiple types of communication services (data, voice, image) with different QoS requirements. MANET (Mobile Adhoc NETwork) does not require a fixed infrastructure. Mobile nodes communicate through multihop paths. The wireless communication medium has variable and unpredictable characteristics. Furthermore, node mobility creates a continuously changing communication topology in which paths break and new one form dynamically. The routing table of each router in an adhoc network must be kept up-to-date. MANET uses Distance Vector or Link State algorithms which insure that the route to every host is always known. However, this approach must take into account the adhoc networks specific characteristics: dynamic topologies, limited bandwidth, energy constraints, limited physical security, ... Two main routing protocols categories are studied in this paper: proactive protocols (e.g. Optimised Link State Routing - OLSR) and reactive protocols (e.g. Ad hoc On Demand Distance Vector - AODV, Dynamic Source Routing - DSR). The proactive protocols are based on periodic exchanges that update the routing tables to all possible destinations, even if no traffic goes through. The reactive protocols are based on on-demand route discoveries that update routing tables only for the destination that has traffic going through. The present paper focuses on study and performance evaluation of these categories using NS2 simulations. We have considered qualitative and quantitative criteria. The first one concerns distributed operation, loop-freedom, security, sleep period operation. The second are used to assess performance of different routing protocols presented in this paper. We can list end-to-end data delay, jitter, packet delivery ratio, routing load, activity distribution. Comparative study will be presented with number of networking context consideration and the results show the appropriate routing protocol for two kinds of communication services (data and voice).

Calculation of reinforced-concrete frame strength under a simultaneous static cross section load and a column lateral impact

DOE Office of Scientific and Technical Information (OSTI.GOV)

Belov, Nikolay, E-mail: n.n.belov@mail.ru; Kopanitsa, Dmitry, E-mail: kopanitsa@mail.ru; Yugov, Alexey, E-mail: yugalex@mail.ru

When designing buildings with reinforced concrete that are planned to resist dynamic loads it is necessary to calculate this structural behavior under operational static and emergency impact and blast loads. Calculations of the structures under shock-wave loads can be performed by solving dynamic equations that do not consider static loads. Due to this fact the calculation of reinforced concrete frame under a simultaneous static and dynamic load in full 3d settings becomes a very non trivial and resource consuming problem. This problem can be split into two tasks. The first one is a shock-wave problem that can be solved usingmore » software package RANET-3, which allows solving the problem using finite elements method adapted for dynamic task. This method calculates strain-stress state of the material and its dynamic destruction, which is considered as growth and consolidation of micro defects under loading. On the second step the results of the first step are taken as input parameters for quasi static calculation of simultaneous static and dynamic load using finite elements method in AMP Civil Engineering-11.« less

Geographically distributed hybrid testing & collaboration between geotechnical centrifuge and structures laboratories

NASA Astrophysics Data System (ADS)

Ojaghi, Mobin; Martínez, Ignacio Lamata; Dietz, Matt S.; Williams, Martin S.; Blakeborough, Anthony; Crewe, Adam J.; Taylor, Colin A.; Madabhushi, S. P. Gopal; Haigh, Stuart K.

2018-01-01

Distributed Hybrid Testing (DHT) is an experimental technique designed to capitalise on advances in modern networking infrastructure to overcome traditional laboratory capacity limitations. By coupling the heterogeneous test apparatus and computational resources of geographically distributed laboratories, DHT provides the means to take on complex, multi-disciplinary challenges with new forms of communication and collaboration. To introduce the opportunity and practicability afforded by DHT, here an exemplar multi-site test is addressed in which a dedicated fibre network and suite of custom software is used to connect the geotechnical centrifuge at the University of Cambridge with a variety of structural dynamics loading apparatus at the University of Oxford and the University of Bristol. While centrifuge time-scaling prevents real-time rates of loading in this test, such experiments may be used to gain valuable insights into physical phenomena, test procedure and accuracy. These and other related experiments have led to the development of the real-time DHT technique and the creation of a flexible framework that aims to facilitate future distributed tests within the UK and beyond. As a further example, a real-time DHT experiment between structural labs using this framework for testing across the Internet is also presented.

A dissolution-precipitation mechanism is at the origin of concrete creep in moist environments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pignatelli, Isabella; Kumar, Aditya; Alizadeh, Rouhollah

Long-term creep (i.e., deformation under sustained load) is a significant material response that needs to be accounted for in concrete structural design. However, the nature and origin of concrete creep remain poorly understood and controversial. Here, we propose that concrete creep at relative humidity ≥ 50%, but fixed moisture content (i.e., basic creep), arises from a dissolution-precipitation mechanism, active at nanoscale grain contacts, as has been extensively observed in a geological context, e.g., when rocks are exposed to sustained loads, in liquid-bearing environments. Based on micro-indentation and vertical scanning interferometry data and molecular dynamics simulations carried out on calcium–silicate–hydrate (C–S–H),more » the major binding phase in concrete, of different compositions, we show that creep rates are correlated with dissolution rates—an observation which suggests a dissolution-precipitation mechanism as being at the origin of concrete creep. C–S–H compositions featuring high resistance to dissolution, and, hence, creep are identified. Analyses of the atomic networks of such C–S–H compositions using topological constraint theory indicate that these compositions present limited relaxation modes on account of their optimally connected (i.e., constrained) atomic networks.« less

A dissolution-precipitation mechanism is at the origin of concrete creep in moist environments.

PubMed

Pignatelli, Isabella; Kumar, Aditya; Alizadeh, Rouhollah; Le Pape, Yann; Bauchy, Mathieu; Sant, Gaurav

2016-08-07

Long-term creep (i.e., deformation under sustained load) is a significant material response that needs to be accounted for in concrete structural design. However, the nature and origin of concrete creep remain poorly understood and controversial. Here, we propose that concrete creep at relative humidity ≥ 50%, but fixed moisture content (i.e., basic creep), arises from a dissolution-precipitation mechanism, active at nanoscale grain contacts, as has been extensively observed in a geological context, e.g., when rocks are exposed to sustained loads, in liquid-bearing environments. Based on micro-indentation and vertical scanning interferometry data and molecular dynamics simulations carried out on calcium-silicate-hydrate (C-S-H), the major binding phase in concrete, of different compositions, we show that creep rates are correlated with dissolution rates-an observation which suggests a dissolution-precipitation mechanism as being at the origin of concrete creep. C-S-H compositions featuring high resistance to dissolution, and, hence, creep are identified. Analyses of the atomic networks of such C-S-H compositions using topological constraint theory indicate that these compositions present limited relaxation modes on account of their optimally connected (i.e., constrained) atomic networks.

A multiple degree of freedom electromechanical Helmholtz resonator.

PubMed

Liu, Fei; Horowitz, Stephen; Nishida, Toshikazu; Cattafesta, Louis; Sheplak, Mark

2007-07-01

The development of a tunable, multiple degree of freedom (MDOF) electromechanical Helmholtz resonator (EMHR) is presented. An EMHR consists of an orifice, backing cavity, and a compliant piezoelectric composite diaphragm. Electromechanical tuning of the acoustic impedance is achieved via passive electrical networks shunted across the piezoceramic. For resistive and capacitive loads, the EMHR is a 2DOF system possessing one acoustic and one mechanical DOF. When inductive ladder networks are employed, multiple electrical DOF are added. The dynamics of the multi-energy domain system are modeled using lumped elements and are represented in an equivalent electrical circuit, which is used to analyze the tunable acoustic input impedance of the EMHR. The two-microphone method is used to measure the acoustic impedance of two EMHR designs with a variety of resistive, capacitive, and inductive shunts. For the first design, the data demonstrate that the tuning range of the second resonant frequency for an EMHR with non-inductive shunts is limited by short- and open-circuit conditions, while an inductive shunt results in a 3DOF system possessing an enhanced tuning range. The second design achieves stronger coupling between the Helmholtz resonator and the piezoelectric backplate, and both resonant frequencies can be tuned with different non-inductive loads.

Working Memory-Related Effective Connectivity in Huntington's Disease Patients.

PubMed

Lahr, Jacob; Minkova, Lora; Tabrizi, Sarah J; Stout, Julie C; Klöppel, Stefan; Scheller, Elisa

2018-01-01

Huntington's disease (HD) is a genetically caused neurodegenerative disorder characterized by heterogeneous motor, psychiatric, and cognitive symptoms. Although motor symptoms may be the most prominent presentation, cognitive symptoms such as memory deficits and executive dysfunction typically co-occur. We used functional magnetic resonance imaging (fMRI) and task fMRI-based dynamic causal modeling (DCM) to evaluate HD-related changes in the neural network underlying working memory (WM). Sixty-four pre-symptomatic HD mutation carriers (preHD), 20 patients with early manifest HD symptoms (earlyHD), and 83 healthy control subjects performed an n -back fMRI task with two levels of WM load. Effective connectivity was assessed in five predefined regions of interest, comprising bilateral inferior parietal cortex, left anterior cingulate cortex, and bilateral dorsolateral prefrontal cortex. HD mutation carriers performed less accurately and more slowly at high WM load compared with the control group. While between-group comparisons of brain activation did not reveal differential recruitment of the cortical WM network in mutation carriers, comparisons of brain connectivity as identified with DCM revealed a number of group differences across the whole WM network. Most strikingly, we observed decreasing connectivity from several regions toward right dorsolateral prefrontal cortex (rDLPFC) in preHD and even more so in earlyHD. The deterioration in rDLPFC connectivity complements results from previous studies and might mirror beginning cortical neural decline at premanifest and early manifest stages of HD. We were able to characterize effective connectivity in a WM network of HD mutation carriers yielding further insight into patterns of cognitive decline and accompanying neural deterioration.

Stress modulation of earthquakes: A study of long and short period stress perturbations and the crustal response

NASA Astrophysics Data System (ADS)

Johnson, Christopher W.

Decomposing fault mechanical processes advances our understanding of active fault systems and properties of the lithosphere, thereby increasing the effectiveness of seismic hazard assessment and preventative measures implemented in urban centers. Along plate boundaries earthquakes are inevitable as tectonic forces reshape the Earth's surface. Earthquakes, faulting, and surface displacements are related systems that require multidisciplinary approaches to characterize deformation in the lithosphere. Modern geodetic instrumentation can resolve displacements to millimeter precision and provide valuable insight into secular deformation in near real-time. The expansion of permanent seismic networks as well as temporary deployments allow unprecedented detection of microseismic events that image fault interfaces and fracture networks in the crust. The research presented in this dissertation is at the intersection of seismology and geodesy to study the Earth's response to transient deformation and explores research questions focusing on earthquake triggering, induced seismicity, and seasonal loading while utilizing seismic data, geodetic data, and modeling tools. The focus is to quantify stress changes in the crust, explore seismicity rate variations and migration patterns, and model crustal deformation in order to characterize the evolving state of stress on faults and the migration of fluids in the crust. The collection of problems investigated all investigate the question: Why do earthquakes nucleate following a low magnitude stress perturbation? Answers to this question are fundamental to understanding the time dependent failure processes of the lithosphere. Dynamic triggering is the interaction of faults and triggering of earthquakes represents stress transferring from one system to another, at both local and remote distances [Freed, 2005]. The passage of teleseismic surface waves from the largest earthquakes produce dynamic stress fields and provides a natural laboratory to explore the causal relationship between low-amplitude stress changes and dynamically triggered events. Interestingly, observations of dynamically triggered M≥5.5 earthquakes are absent in the seismic records [Johnson et al., 2015; Parsons and Velasco, 2011], which invokes questions regarding whether or not large magnitude events can be dynamically triggered. Emerging results in the literature indicate undocumented M≥5.5 events at near to intermediate distances are dynamically triggered during the passage of surface waves but are undetected by automated networks [Fan and Shearer, 2016]. This raises new questions about the amplitude and duration of dynamic stressing for large magnitude events. I used 35-years of global seismicity and find that large event rate increases only occur following a delay from the transient load, suggesting aseismic processes are associated with large magnitude triggered events. To extend this finding I investigated three cases of large magnitude delayed dynamic triggering following the M8.6 2012 Indian Ocean earthquake [Pollitz et al., 2012] by producing microseismicity catalogs and modeling the transient stresses. The results indicate immediate triggering of microseismic events that hours later culminate into a large magnitude event and support the notion that large magnitude events are triggerable by transient loading, but seismic and aseismic processes (e.g. induced creep or fluid mobilization) are contributing to the nucleation process. Open questions remain concerning the source of a nucleation delay period following a stress perturbation that require both geodetic and seismic observations to constrain the source of delayed dynamic triggering and possibly provide insight into a precursory nucleation phase. Induced seismicity has gained much attention in the past 5 years as earthquake rates in regions of low tectonic strain accumulation accelerate to unprecedented levels [Ellsworth, 2013]. The source of the seismicity is attributed to shallow fluid injection associated with energy production. As hydrocarbon extraction continues to increase in the U.S. the deformation and induced seismicity from wastewater injection is providing new avenues to explore crustal properties. The large magnitude events associated with regions of high rate injection support the notion that the crust is critically stressed. Seismic data in these areas provides the opportunity to delineate fault structures in the crust using precise earthquake locations. To augment the studies of transient loading cycles I investigated induced seismicity at The Geysers geothermal field in northern California. Using high-resolution hypocenter data I implement an epidemic type aftershock sequence (ETAS) model to develop seismicity rate time series in the active geothermal field and characterize the migration of fluids from high volume water injection. Subtle stress changes induced by thermo- and poroelastic strains trigger seismicity for 5 months after peak injection at depths 3 km below the main injection interval. This suggests vertical migration paths are maintained in the geothermal field that allows fluid propagation on annual time scales. Fully describing the migration pattern of fluids in the crust and the associated stresses are applicable to tectonic related faulting and triggered seismic activity. Seasonal hydrological loading is a source of annual periodic transient deformation that is ideal for investigating the modulation of seismicity. The initial step in exploring the modulation of seismicity is to validate that a significant annual period does exist in California earthquake records. The periodicity results [Dutilleul et al., 2015] motivate continued investigation of seismically active regions that experience significant seasonal mass loading, i.e. high precipitation and snowfall rates, to quantify the magnitude of seasonal stress changes and possible correlation with seismicity modulation. The implication of this research addresses questions concerning the strength and state of stress on faults. High-resolution water storage time series throughout California are developed using continuous GPS records. The results allow an estimation of the stress changes induced by hydrological loading, which is combined with a detailed focal mechanism analysis to characterize the modulation of seismicity. The hydrologic loading is augmented with the contribution of additional deformation sources (e.g. tidal, atmosphere, and temperature) and find that annual stress changes of 5 kPa are modulating seismicity, most notably on dip-slip structures. These observations suggest that mechanical differences exist between the vertically dipping strike-slip faults and the shallowly dipping oblique structures in California. When comparing all the annual loading cycles it is evident that future studies incorporate all the sources of solid Earth deformation to fully describe the stresses realized on fault systems that respond to seasonal loads.

Dynamic Fracture Properties of Rocks Subjected to Static Pre-load Using Notched Semi-circular Bend Method

NASA Astrophysics Data System (ADS)

Chen, Rong; Li, Kang; Xia, Kaiwen; Lin, Yuliang; Yao, Wei; Lu, Fangyun

2016-10-01

A dynamic load superposed on a static pre-load is a key problem in deep underground rock engineering projects. Based on a modified split Hopkinson pressure bar test system, the notched semi-circular bend (NSCB) method is selected to investigate the fracture initiation toughness of rocks subjected to pre-load. In this study, a two-dimensional ANSYS finite element simulation model is developed to calculate the dimensionless stress intensity factor. Three groups of NSCB specimen are tested under a pre-load of 0, 37 and 74 % of the maximum static load and with the loading rate ranging from 0 to 60 GPa m1/2 s-1. The results show that under a given pre-load, the fracture initiation toughness of rock increases with the loading rate, resembling the typical rate dependence of materials. Furthermore, the dynamic rock fracture toughness decreases with the static pre-load at a given loading rate. The total fracture toughness, defined as the sum of the dynamic fracture toughness and initial stress intensity factor calculated from the pre-load, increases with the pre-load at a given loading rate. An empirical equation is used to represent the effect of loading rate and pre-load force, and the results show that this equation can depict the trend of the experimental data.

State Space Modeling of Time-Varying Contemporaneous and Lagged Relations in Connectivity Maps

PubMed Central

Molenaar, Peter C. M.; Beltz, Adriene M.; Gates, Kathleen M.; Wilson, Stephen J.

2017-01-01

Most connectivity mapping techniques for neuroimaging data assume stationarity (i.e., network parameters are constant across time), but this assumption does not always hold true. The authors provide a description of a new approach for simultaneously detecting time-varying (or dynamic) contemporaneous and lagged relations in brain connectivity maps. Specifically, they use a novel raw data likelihood estimation technique (involving a second-order extended Kalman filter/smoother embedded in a nonlinear optimizer) to determine the variances of the random walks associated with state space model parameters and their autoregressive components. The authors illustrate their approach with simulated and blood oxygen level-dependent functional magnetic resonance imaging data from 30 daily cigarette smokers performing a verbal working memory task, focusing on seven regions of interest (ROIs). Twelve participants had dynamic directed functional connectivity maps: Eleven had one or more time-varying contemporaneous ROI state loadings, and one had a time-varying autoregressive parameter. Compared to smokers without dynamic maps, smokers with dynamic maps performed the task with greater accuracy. Thus, accurate detection of dynamic brain processes is meaningfully related to behavior in a clinical sample. PMID:26546863

Re-Evaluation of the AASHTO-Flexible Pavement Design Equation with Neural Network Modeling

PubMed Central

Tiğdemir, Mesut

2014-01-01

Here we establish that equivalent single-axle loads values can be estimated using artificial neural networks without the complex design equality of American Association of State Highway and Transportation Officials (AASHTO). More importantly, we find that the neural network model gives the coefficients to be able to obtain the actual load values using the AASHTO design values. Thus, those design traffic values that might result in deterioration can be better calculated using the neural networks model than with the AASHTO design equation. The artificial neural network method is used for this purpose. The existing AASHTO flexible pavement design equation does not currently predict the pavement performance of the strategic highway research program (Long Term Pavement Performance studies) test sections very accurately, and typically over-estimates the number of equivalent single axle loads needed to cause a measured loss of the present serviceability index. Here we aimed to demonstrate that the proposed neural network model can more accurately represent the loads values data, compared against the performance of the AASHTO formula. It is concluded that the neural network may be an appropriate tool for the development of databased-nonparametric models of pavement performance. PMID:25397962

Re-evaluation of the AASHTO-flexible pavement design equation with neural network modeling.

PubMed

Tiğdemir, Mesut

2014-01-01

Here we establish that equivalent single-axle loads values can be estimated using artificial neural networks without the complex design equality of American Association of State Highway and Transportation Officials (AASHTO). More importantly, we find that the neural network model gives the coefficients to be able to obtain the actual load values using the AASHTO design values. Thus, those design traffic values that might result in deterioration can be better calculated using the neural networks model than with the AASHTO design equation. The artificial neural network method is used for this purpose. The existing AASHTO flexible pavement design equation does not currently predict the pavement performance of the strategic highway research program (Long Term Pavement Performance studies) test sections very accurately, and typically over-estimates the number of equivalent single axle loads needed to cause a measured loss of the present serviceability index. Here we aimed to demonstrate that the proposed neural network model can more accurately represent the loads values data, compared against the performance of the AASHTO formula. It is concluded that the neural network may be an appropriate tool for the development of databased-nonparametric models of pavement performance.

Elevated Aerosol Layers and Their Radiative Impact over Kanpur During Monsoon Onset Period

NASA Technical Reports Server (NTRS)

Sarangi, Chandan; Tripathi, S. N.; Mishra, A. K.; Welton, E. J.

2016-01-01

Accurate information about aerosol vertical distribution is needed to reduce uncertainties in aerosol radiative forcing and its effect on atmospheric dynamics. The present study deals with synergistic analyses of aerosol vertical distribution and aerosol optical depth (AOD) with meteorological variables using multisatellite and ground-based remote sensors over Kanpur in central Indo-Gangetic Plain (IGP). Micro-Pulse Lidar Network-derived aerosol vertical extinction (sigma) profiles are analyzed to quantify the interannual and daytime variations during monsoon onset period (May-June) for 2009-2011. The mean aerosol profile is broadly categorized into two layers viz., a surface layer (SL) extending up to 1.5 km (where sigma decreased exponentially with height) and an elevated aerosol layer (EAL) extending between 1.5 and 5.5 km. The increase in total columnar aerosol loading is associated with relatively higher increase in contribution from EAL loading than that from SL. The mean contributions of EALs are about 60%, 51%, and 50% to total columnar AOD during 2009, 2010, and 2011, respectively. We observe distinct parabolic EALs during early morning and late evening but uniformly mixed EALs during midday. The interannual and daytime variations of EALs are mainly influenced by long-range transport and convective capacity of the local emissions, respectively. Radiative flux analysis shows that clear-sky incoming solar radiation at surface is reduced with increase in AOD, which indicates significant cooling at surface. Collocated analysis of atmospheric temperature and aerosol loading reveals that increase in AOD not only resulted in surface dimming but also reduced the temperature (approximately 2-3 C) of lower troposphere (below 3 km altitude). Radiative transfer simulations indicate that the reduction of incoming solar radiation at surface is mainly due to increased absorption by EALs (with increase in total AOD). The observed cooling in lower troposphere in high aerosol loading scenario could be understood as a dynamical feedback of EAL-induced stratification of lower troposphere. Further, the observed radiative effect of EALs increases the stability of the lower troposphere, which could modulate the large-scale atmospheric dynamics during monsoon onset period. These findings encourage follow-up studies on the implication of EALs to the Indian summer monsoon dynamics using numerical models.

Short term load forecasting using a self-supervised adaptive neural network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yoo, H.; Pimmel, R.L.

The authors developed a self-supervised adaptive neural network to perform short term load forecasts (STLF) for a large power system covering a wide service area with several heavy load centers. They used the self-supervised network to extract correlational features from temperature and load data. In using data from the calendar year 1993 as a test case, they found a 0.90 percent error for hour-ahead forecasting and 1.92 percent error for day-ahead forecasting. These levels of error compare favorably with those obtained by other techniques. The algorithm ran in a couple of minutes on a PC containing an Intel Pentium --more » 120 MHz CPU. Since the algorithm included searching the historical database, training the network, and actually performing the forecasts, this approach provides a real-time, portable, and adaptable STLF.« less

A novel strategy for load balancing of distributed medical applications.

PubMed

Logeswaran, Rajasvaran; Chen, Li-Choo

2012-04-01

Current trends in medicine, specifically in the electronic handling of medical applications, ranging from digital imaging, paperless hospital administration and electronic medical records, telemedicine, to computer-aided diagnosis, creates a burden on the network. Distributed Service Architectures, such as Intelligent Network (IN), Telecommunication Information Networking Architecture (TINA) and Open Service Access (OSA), are able to meet this new challenge. Distribution enables computational tasks to be spread among multiple processors; hence, performance is an important issue. This paper proposes a novel approach in load balancing, the Random Sender Initiated Algorithm, for distribution of tasks among several nodes sharing the same computational object (CO) instances in Distributed Service Architectures. Simulations illustrate that the proposed algorithm produces better network performance than the benchmark load balancing algorithms-the Random Node Selection Algorithm and the Shortest Queue Algorithm, especially under medium and heavily loaded conditions.

Transcription factor assisted loading and enhancer dynamics dictate the hepatic fasting response

PubMed Central

Goldstein, Ido; Baek, Songjoon; Presman, Diego M.; Paakinaho, Ville; Swinstead, Erin E.; Hager, Gordon L.

2017-01-01

Fasting elicits transcriptional programs in hepatocytes leading to glucose and ketone production. This transcriptional program is regulated by many transcription factors (TFs). To understand how this complex network regulates the metabolic response to fasting, we aimed at isolating the enhancers and TFs dictating it. Measuring chromatin accessibility revealed that fasting massively reorganizes liver chromatin, exposing numerous fasting-induced enhancers. By utilizing computational methods in combination with dissecting enhancer features and TF cistromes, we implicated four key TFs regulating the fasting response: glucocorticoid receptor (GR), cAMP responsive element binding protein 1 (CREB1), peroxisome proliferator activated receptor alpha (PPARA), and CCAAT/enhancer binding protein beta (CEBPB). These TFs regulate fuel production by two distinctly operating modules, each controlling a separate metabolic pathway. The gluconeogenic module operates through assisted loading, whereby GR doubles the number of sites occupied by CREB1 as well as enhances CREB1 binding intensity and increases accessibility of CREB1 binding sites. Importantly, this GR-assisted CREB1 binding was enhancer-selective and did not affect all CREB1-bound enhancers. Single-molecule tracking revealed that GR increases the number and DNA residence time of a portion of chromatin-bound CREB1 molecules. These events collectively result in rapid synergistic gene expression and higher hepatic glucose production. Conversely, the ketogenic module operates via a GR-induced TF cascade, whereby PPARA levels are increased following GR activation, facilitating gradual enhancer maturation next to PPARA target genes and delayed ketogenic gene expression. Our findings reveal a complex network of enhancers and TFs that dynamically cooperate to restore homeostasis upon fasting. PMID:28031249

Robustness of Oscillatory Behavior in Correlated Networks

PubMed Central

Sasai, Takeyuki; Morino, Kai; Tanaka, Gouhei; Almendral, Juan A.; Aihara, Kazuyuki

2015-01-01

Understanding network robustness against failures of network units is useful for preventing large-scale breakdowns and damages in real-world networked systems. The tolerance of networked systems whose functions are maintained by collective dynamical behavior of the network units has recently been analyzed in the framework called dynamical robustness of complex networks. The effect of network structure on the dynamical robustness has been examined with various types of network topology, but the role of network assortativity, or degree–degree correlations, is still unclear. Here we study the dynamical robustness of correlated (assortative and disassortative) networks consisting of diffusively coupled oscillators. Numerical analyses for the correlated networks with Poisson and power-law degree distributions show that network assortativity enhances the dynamical robustness of the oscillator networks but the impact of network disassortativity depends on the detailed network connectivity. Furthermore, we theoretically analyze the dynamical robustness of correlated bimodal networks with two-peak degree distributions and show the positive impact of the network assortativity. PMID:25894574

Performance evaluation of data center service localization based on virtual resource migration in software defined elastic optical network.

PubMed

Yang, Hui; Zhang, Jie; Ji, Yuefeng; Tan, Yuanlong; Lin, Yi; Han, Jianrui; Lee, Young

2015-09-07

Data center interconnection with elastic optical network is a promising scenario to meet the high burstiness and high-bandwidth requirements of data center services. In our previous work, we implemented cross stratum optimization of optical network and application stratums resources that allows to accommodate data center services. In view of this, this study extends the data center resources to user side to enhance the end-to-end quality of service. We propose a novel data center service localization (DCSL) architecture based on virtual resource migration in software defined elastic data center optical network. A migration evaluation scheme (MES) is introduced for DCSL based on the proposed architecture. The DCSL can enhance the responsiveness to the dynamic end-to-end data center demands, and effectively reduce the blocking probability to globally optimize optical network and application resources. The overall feasibility and efficiency of the proposed architecture are experimentally verified on the control plane of our OpenFlow-based enhanced SDN testbed. The performance of MES scheme under heavy traffic load scenario is also quantitatively evaluated based on DCSL architecture in terms of path blocking probability, provisioning latency and resource utilization, compared with other provisioning scheme.

Scalability enhancement of AODV using local link repairing

NASA Astrophysics Data System (ADS)

Jain, Jyoti; Gupta, Roopam; Bandhopadhyay, T. K.

2014-09-01

Dynamic change in the topology of an ad hoc network makes it difficult to design an efficient routing protocol. Scalability of an ad hoc network is also one of the important criteria of research in this field. Most of the research works in ad hoc network focus on routing and medium access protocols and produce simulation results for limited-size networks. Ad hoc on-demand distance vector (AODV) is one of the best reactive routing protocols. In this article, modified routing protocols based on local link repairing of AODV are proposed. Method of finding alternate routes for next-to-next node is proposed in case of link failure. These protocols are beacon-less, means periodic hello message is removed from the basic AODV to improve scalability. Few control packet formats have been changed to accommodate suggested modification. Proposed protocols are simulated to investigate scalability performance and compared with basic AODV protocol. This also proves that local link repairing of proposed protocol improves scalability of the network. From simulation results, it is clear that scalability performance of routing protocol is improved because of link repairing method. We have tested protocols for different terrain area with approximate constant node densities and different traffic load.

In vitro evaluation of stiffness and load sharing in a two-level corpectomy: comparison of static and dynamic cervical plates.

PubMed

Fogel, Guy R; Li, Zhenyu; Liu, Weiqiang; Liao, Zhenhua; Wu, Jia; Zhou, Wenyu

2010-05-01

Anterior cervical plating has been accepted in corpectomy and fusion of the cervical spine. Constrained plates were criticized for stress shielding that may lead to subsidence and pseudarthrosis. A dynamic plate allows load sharing as the graft subsides. Ideally, the dynamic plate design should maintain adequate stiffness of the construct while providing a reasonable load sharing with the strut graft. The purpose of the study was to compare dynamic and static plate kinematics with graft subsidence. The study designed was an in vitro biomechanical study in a porcine cervical spine model. Twelve spines were initially tested in intact condition with 20-N axial load in 15 degrees of flexion and extension range of motion (ROM). Then, a two-level corpectomy was created in all specimens with spines randomized to receive either a static or dynamic plate. The spines were retested under identical conditions with optimal length and undersized graft. Range of motion and graft loading were analyzed with a one-way analysis of variance (p<.05). Both plates significantly limited ROM compared with the intact spine in both graft length conditions. In extension graft, load was significantly higher (p=.001) in the static plate with optimal length, and in flexion, there was a significant loss of graft load (p=.0004). In flexion, the dynamic plate with undersized graft demonstrated significantly more load sustained (p=.0004). Both plates reasonably limited the ROM of the corpectomy. The static plate had significantly higher graft loads in extension and significant loss of graft load in flexion, whereas the dynamic plate maintained a reasonable graft load in ROM even when graft contact was imperfect. Copyright 2010 Elsevier Inc. All rights reserved.

Buckling of circular cylindrical shells under dynamically applied axial loads

NASA Technical Reports Server (NTRS)

Tulk, J. D.

1972-01-01

A theoretical and experimental study was made of the buckling characteristics of perfect and imperfect circular cylindrical shells subjected to dynamic axial loading. Experimental data included dynamic buckling loads (124 data points), high speed photographs of buckling mode shapes and observations of the dynamic stability of shells subjected to rapidly applied sub-critical loads. A mathematical model was developed to describe the dynamic behavior of perfect and imperfect shells. This model was based on the Donnell-Von Karman compatibility and equilibrium equations and had a wall deflection function incorporating five separate modes of deflection. Close agreement between theory and experiment was found for both dynamic buckling strength and buckling mode shapes.

A novel PON based UMTS broadband wireless access network architecture with an algorithm to guarantee end to end QoS

NASA Astrophysics Data System (ADS)

Sana, Ajaz; Hussain, Shahab; Ali, Mohammed A.; Ahmed, Samir

2007-09-01

In this paper we proposes a novel Passive Optical Network (PON) based broadband wireless access network architecture to provide multimedia services (video telephony, video streaming, mobile TV, mobile emails etc) to mobile users. In the conventional wireless access networks, the base stations (Node B) and Radio Network Controllers (RNC) are connected by point to point T1/E1 lines (Iub interface). The T1/E1 lines are expensive and add up to operating costs. Also the resources (transceivers and T1/E1) are designed for peak hours traffic, so most of the time the dedicated resources are idle and wasted. Further more the T1/E1 lines are not capable of supporting bandwidth (BW) required by next generation wireless multimedia services proposed by High Speed Packet Access (HSPA, Rel.5) for Universal Mobile Telecommunications System (UMTS) and Evolution Data only (EV-DO) for Code Division Multiple Access 2000 (CDMA2000). The proposed PON based back haul can provide Giga bit data rates and Iub interface can be dynamically shared by Node Bs. The BW is dynamically allocated and the unused BW from lightly loaded Node Bs is assigned to heavily loaded Node Bs. We also propose a novel algorithm to provide end to end Quality of Service (QoS) (between RNC and user equipment).The algorithm provides QoS bounds in the wired domain as well as in wireless domain with compensation for wireless link errors. Because of the air interface there can be certain times when the user equipment (UE) is unable to communicate with Node B (usually referred to as link error). Since the link errors are bursty and location dependent. For a proposed approach, the scheduler at the Node B maps priorities and weights for QoS into wireless MAC. The compensations for errored links is provided by the swapping of services between the active users and the user data is divided into flows, with flows allowed to lag or lead. The algorithm guarantees (1)delay and throughput for error-free flows,(2)short term fairness among error-free flows,(3)long term fairness among errored and error-free flows,(4)graceful degradation for leading flows and graceful compensation for lagging flows.

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

NASA Astrophysics Data System (ADS)

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.

Static versus dynamic fracturing in shallow carbonate fault zones

NASA Astrophysics Data System (ADS)

Fondriest, M.; Doan, M. L.; Aben, F. M.; Fusseis, F.; Mitchell, T. M.; Di Toro, G.

2015-12-01

Moderate to large earthquakes often nucleate within and propagate through carbonates in the shallow crust, therefore several field and experimental studies were recently aimed to constrain earthquake-related deformation processes within carbonate fault rocks. In particular, the occurrence of thick belts (10-100s m) of low-strain fault-related breccias (average size of rock fragments >1 cm), which is relatively common within carbonate damage zones, was generally interpreted as resulting from the quasi-static growth of fault zones rather than from the cumulative effect of multiple earthquake ruptures. Here we report the occurrence of up to hundreds of meters thick belts of intensely fragmented dolostones along the major transpressive Foiana Fault Zone (Italian Southern Alps) which was exhumed from < 2 km depth. Such dolostones are reduced into fragments ranging from few centimeters down to few millimeters in size with ultrafine-grained layers in proximity to the principal slip zones. Preservation of the original bedding indicates a lack of significant shear strain in the fragmented dolostones which seem to have been shattered in situ. To investigate the origin of the in-situ shattered rocks, the host dolostones were deformed in uniaxial compression both under quasi-static loading (strain rate ~10-3 s-1) and dynamic loading (strain rate >50 s-1). Dolostones deformed up to failure under low-strain rate were affected by single to multiple discrete (i.e. not interconnected) extensional fractures sub-parallel to the loading direction. Dolostones deformed under high-strain rate were shattered above a strain rate threshold of ~200 s-1(strain >1.2%) while they were split in few fragments or were macroscopically intact for lower strain rates. Experimentally shattered dolostones were reduced into a non-cohesive material with most rock fragments a few millimeters in size and elongated parallel to the loading direction. Fracture networks were investigated by X-ray microtomography showing that low- and high-strain rate damage patterns are different with the latter being similar to that of natural in-situ shattered dolostones. In-situ shattered dolostones are thus interpreted as the product of off-fault dynamic stress wave loading and can potentially be used to constrain coseismic energy release in fault zones.

[Three-dimensional stress analysis of periodontal ligament of mandible incisors fixed bridge abutments under dynamic loads by finite element method].

PubMed

Ma, Da; Tang, Liang; Pan, Yan-Huan

2007-12-01

Three-dimensional finite method was used to analyze stress and strain distributions of periodontal ligament of abutments under dynamic loads. Finite element analysis was performed on the model under dynamic loads with vertical and oblique directions. The stress and strain distributions and stress-time curves were analyzed to study the biomechanical behavior of periodontal ligament of abutments. The stress and strain distributions of periodontal ligament under dynamic load were same with the static load. But the maximum stress and strain decreased apparently. The rate of change was between 60%-75%. The periodontal ligament had time-dependent mechanical behaviors. Some level of residual stress in periodontal ligament was left after one mastication period. The stress-free time under oblique load was shorter than that of vertical load. The maximum stress and strain decrease apparently under dynamic loads. The periodontal ligament has time-dependent mechanical behaviors during one mastication. There is some level of residual stress left after one mastication period. The level of residual stress is related to the magnitude and the direction of loads. The direction of applied loads is one important factor that affected the stress distribution and accumulation and release of abutment periodontal ligament.

The impact of calcium carbonate as pore forming agent and drug entrapment method towards drug dissolution mechanism of amoxicillin trihydrate encapsulated by chitosan-methyl cellulose semi-IPN hydrogel for floating drug delivery system

NASA Astrophysics Data System (ADS)

Dewantara, Fauzi; Budianto, Emil

2018-04-01

Chitosan-methyl cellulose semi-IPN hydrogel is used as floating drug delivery system, and calcium carbonate also added as pore forming agent. The hydrogel network arranged by not only using biopolymer chitosan and methyl cellulose, but also the crosslink agent that is glutaraldehyde. Amoxicillin trihydrate entrapped into the polymer network with two different method, in situ loading and post loading. Furthermore both method has been tested for drug entrapment efficiency along with drug dissolution test, and the result for drug entrapment efficiency is in situ loading method has highest value of 100%, compared to post loading method which has value only 71%. Moreover, at the final time of drug dissolution test shows in situ loading method has value of 96% for total accumulative of drug dissolution, meanwhile post loading method has 72%. The value of drug dissolution test from both method is used for analyzing drug dissolution mechanism of amoxicillin trihydrate from hydrogel network with four mathematical drug mechanism models as parameter. The polymer network encounter destructive degradation causes by acid solution which used as dissolution medium, and the level of degradation is observed with optical microscope. However the result shows that degradation of the polymer network doesn't affect drug dissolution mechanism directly. Although the pore forming agent causes the pore inside the hydrogel network create interconnection and it was quite influential to drug dissolution mechanism. Interconnected pore is observed with Scanning Electron Microscope (SEM) and shows that the amount and area of interconnected pore inside the hydrogel network is increasing as drug dissolution goes on.

Dynamic Load on Continuous Multi-Lane Bridge Deck from Moving Vehicles

NASA Astrophysics Data System (ADS)

ZHU, X. Q.; LAW, S. S.

2002-04-01

The dynamic loading on a multi-lane continuous bridge deck due to vehicles moving on top at a constant velocity is investigated. The bridge is modelled as a multi-span continuous orthotropic rectangular plate with line rigid intermediate supports. The vehicle is simulated as a two-axle three-dimensional vehicle model with seven degrees of freedom according to the H20-44 vehicle design loading (AASHTO LRFD Bridge Design Specifications 1998 American Association of State Highway and Transportation Officials [1]). The dynamic behavior of the bridge deck under single and several vehicles moving in different lanes is analyzed using the orthotropic plate theory and modal superposition technique. The dynamic loading is studied in terms of the dynamic impact factor of the bridge deck. The impact factor is found varying in an opposite trend as the dynamic responses for the different loading cases under study.

Study on Human-structure Dynamic Interaction in Civil Engineering

NASA Astrophysics Data System (ADS)

Gao, Feng; Cao, Li Lin; Li, Xing Hua

2018-06-01

The research of human-structure dynamic interaction are reviewed. Firstly, the influence of the crowd load on structural dynamic characteristics is introduced and the advantages and disadvantages of different crowd load models are analyzed. Then, discussing the influence of structural vibration on the human-induced load, especially the influence of different stiffness structures on the crowd load. Finally, questions about human-structure interaction that require further study are presented.

Multifactorial causal model of brain (dis)organization and therapeutic intervention: Application to Alzheimer's disease.

PubMed

Iturria-Medina, Yasser; Carbonell, Félix M; Sotero, Roberto C; Chouinard-Decorte, Francois; Evans, Alan C

2017-05-15

Generative models focused on multifactorial causal mechanisms in brain disorders are scarce and generally based on limited data. Despite the biological importance of the multiple interacting processes, their effects remain poorly characterized from an integrative analytic perspective. Here, we propose a spatiotemporal multifactorial causal model (MCM) of brain (dis)organization and therapeutic intervention that accounts for local causal interactions, effects propagation via physical brain networks, cognitive alterations, and identification of optimum therapeutic interventions. In this article, we focus on describing the model and applying it at the population-based level for studying late onset Alzheimer's disease (LOAD). By interrelating six different neuroimaging modalities and cognitive measurements, this model accurately predicts spatiotemporal alterations in brain amyloid-β (Aβ) burden, glucose metabolism, vascular flow, resting state functional activity, structural properties, and cognitive integrity. The results suggest that a vascular dysregulation may be the most-likely initial pathologic event leading to LOAD. Nevertheless, they also suggest that LOAD it is not caused by a unique dominant biological factor (e.g. vascular or Aβ) but by the complex interplay among multiple relevant direct interactions. Furthermore, using theoretical control analysis of the identified population-based multifactorial causal network, we show the crucial advantage of using combinatorial over single-target treatments, explain why one-target Aβ based therapies might fail to improve clinical outcomes, and propose an efficiency ranking of possible LOAD interventions. Although still requiring further validation at the individual level, this work presents the first analytic framework for dynamic multifactorial brain (dis)organization that may explain both the pathologic evolution of progressive neurological disorders and operationalize the influence of multiple interventional strategies. Copyright © 2017 Elsevier Inc. All rights reserved.

Requirements for implementation of Kuessner and Wagner indicial lift growth functions into the FLEXSTAB computer program system for use in dynamic loads analyses

NASA Technical Reports Server (NTRS)

Miller, R. D.; Rogers, J. T.

1975-01-01

General requirements for dynamic loads analyses are described. The indicial lift growth function unsteady subsonic aerodynamic representation is reviewed, and the FLEXSTAB CPS is evaluated with respect to these general requirements. The effects of residual flexibility techniques on dynamic loads analyses are also evaluated using a simple dynamic model.

Traffic-aware energy saving scheme with modularization supporting in TWDM-PON

NASA Astrophysics Data System (ADS)

Xiong, Yu; Sun, Peng; Liu, Chuanbo; Guan, Jianjun

2017-01-01

Time and wavelength division multiplexed passive optical network (TWDM-PON) is considered to be a primary solution for next-generation passive optical network stage 2 (NG-PON2). Due to the feature of multi-wavelength transmission of TWDM-PON, some of the transmitters/receivers at the optical line terminal (OLT) could be shut down to reduce the energy consumption. Therefore, a novel scheme called traffic-aware energy saving scheme with modularization supporting is proposed. Through establishing the modular energy consumption model of OLT, the wavelength transmitters/receivers at OLT could be switched on or shut down adaptively depending on sensing the status of network traffic load, thus the energy consumption of OLT will be effectively reduced. Furthermore, exploring the technology of optical network unit (ONU) modularization, each module of ONU could be switched to sleep or active mode independently in order to reduce the energy consumption of ONU. Simultaneously, the polling sequence of ONU could be changed dynamically via sensing the packet arrival time. In order to guarantee the delay performance of network traffic, the sub-cycle division strategy is designed to transmit the real-time traffic preferentially. Finally, simulation results verify that the proposed scheme is able to reduce the energy consumption of the network while maintaining the traffic delay performance.

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

PubMed

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

PubMed Central

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

2017-01-01

Abstract 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. PMID:29339998

An incentive-based distributed mechanism for scheduling divisible loads in tree networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carroll, T. E.; Grosu, D.

The underlying assumption of Divisible Load Scheduling (DLS) theory is that the pro-cessors composing the network are obedient, i.e., they do not “cheat” the scheduling algorithm. This assumption is unrealistic if the processors are owned by autonomous, self-interested organizations that have no a priori motivation for cooperation and they will manipulate the algorithm if it is beneficial to do so. In this paper, we address this issue by designing a distributed mechanism for scheduling divisible loads in tree net-works, called DLS-T, which provides incentives to processors for reporting their true processing capacity and executing their assigned load at full processingmore » capacity. We prove that the DLS-T mechanism computes the optimal allocation in an ex post Nash equilibrium. Finally, we simulate and study the mechanism under various network structures and processor parameters.« less

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

NASA Astrophysics Data System (ADS)

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.

Uncertainty management for aerial vehicles: Coordination, deconfliction, and disturbance rejection

NASA Astrophysics Data System (ADS)

Panyakeow, Prachya

The presented dissertation aims to develop control algorithms that deal with three types of uncertainties managements. First, we examine the situation when unmanned aerial vehicles (UAVs) fly through uncertain environments that contain both stationary and moving obstacles. Moreover, a guarantee of collision avoidance is necessary when UAVs operate in close proximity of each other. Second, we look at the communication uncertainty among the network of cooperative UAVs and the efforts to establish and maintain the connectivity throughout their entire missions. Third, we explore the scenario when the aircraft flies through wind gust. The introduction of an appropriate control scheme to actively alleviate the gust loads can result into weight reduction and consequently lower the fuel cost. In the first part of this dissertation, we develop a deconfliction algorithm that guarantees collision avoidance between a pair of constant speed unicycle-type UAVs as well as convergence to the desired destination for each UAV in presence of static obstacles. We use a combination of navigation and swirling functions to direct the unicycle vehicles along the planned trajectories while avoiding inter-vehicle collisions. The main feature of our contribution is proposing means of designing a deconfliction algorithm for unicycle vehicles that more closely capture the dynamics of constant speed UAVs as opposed to double integrator models. Specifically, we consider the issue of UAV turn-rate constraints and proceed to explore the selection of key algorithmic parameters in order to minimize undesirable trajectories and overshoots induced by the avoidance algorithm. The avoidance and convergence analysis of the proposed algorithm is then performed for two cooperative UAVs and simulation results are provided to support the viability of the proposed framework for more general mission scenarios. For the uncertainty of the UAV network, we provides two approaches to establish connectivity among a collection of UAVs that are initially scattered in space. The goal is to find shortest trajectories that bring the UAVs to a connected formation where they are in the range of detection of one another and headed in the same direction to maintain the connectivity. Pontryagin Minimum Principle (PMP) is utilized to determine the control law and path synthesis for the UAVs under the turn-rate constraints. We introduce an algorithm to search for the optimal solution when the final network topology is specified; followed by a nonlinear programming method in which the final configuration is emerged from the optimization routine under the constraints that the final topology is connected. Each method has its own advantages based on the size of corporative networks. For the uncertainty due to gust turbulence, we choose a model predictive control (MPC) technique to address gust load alleviation (GLA) for a flexible aircraft. MPC is a discrete method based on repeated online optimization that allows direct consideration of control actuator constraints into the feedback computation. Gust alleviation systems are dependent on how the structural flexibility of the aircraft affects its dynamics. Hence, we develop a six-degree-of-freedom flexible aircraft model that can integrate rigid body dynamic with structural deflection. The structural stick-and-beam model is utilized for the calculation of aeroelastic mode shapes and airframe loads. Another important feature of MPC for GLA design is the ability to include the preview of gust information ahead of the aircraft nose into the prediction process. This helps raising the prediction accuracy and consequently improves the load alleviation performance. Finally, the aircraft is modified by the addition of the flap-array, a composition of small trailing edge flaps throughout the entire span of the wings. These flaps are used in conjunction with the distributed spoilers. With the availability of the control surfaces closer to the wing root, the MPC with flap-array can reduce the wing bending moment from different mode shapes and achieve better load alleviation performance than the original aircraft.

A statistical physics approach to scale-free networks and their behaviors

NASA Astrophysics Data System (ADS)

Wu, Fang

This thesis studies five problems of network properties from a unified local-to-global viewpoint of statistical physics: (1) We propose an algorithm that allows the discovery of communities within graphs of arbitrary size, based on Kirchhoff theory of electric networks. Its time complexity scales linearly with the network size. We additionally show how this algorithm allows for the swift discovery of the community surrounding a given node without having to extract all the communities out of a graph. (2) We present a dynamical theory of opinion formation that takes explicitly into account the structure of the social network in which individuals are embedded. We show that the weighted fraction of the population that holds a certain opinion is a martingale. We show that the importance of a given node is proportional to its degree. We verify our predictions by simulations. (3) We show that, when the information transmissibility decays with distance, the epidemic spread on a scale-free network has a finite threshold. We test our predictions by measuring the spread of messages in an organization and by numerical experiments. (4) Suppose users can switch between two behaviors when entering a queueing system: one that never restarts an initial request and one that restarts infinitely often. We show the existence of two thresholds. When the system load is below the lower threshold, it is always better off to be impatient. When above, it is always better off to be patient. Between the two thresholds there exists a homogeneous Nash equilibrium with non-trivial properties. We obtain exact solutions for the two thresholds. (5) We study the endogenous dynamics of reputations in a system consisting of firms with long horizons that provide services with varying levels of quality, and customers who assign to them reputations on the basis of the quality levels that they experience when interacting with them. We show that the dynamics can lead to either well defined equilibria or persistent nonlinear oscillations in the number of customers visiting a firm, implying unstable reputations. We establish the stable criteria.

Comparison of analysis and experiment for dynamics of low-contact-ratio spur gears

NASA Technical Reports Server (NTRS)

Oswald, Fred B.; Rebbechi, Brian; Zakrajsek, James J.; Townsend, Dennis P.; Lin, Hsiang Hsi

1991-01-01

Low-contact-ratio spur gears were tested in NASA gear-noise-rig to study gear dynamics including dynamic load, tooth bending stress, vibration, and noise. The experimental results were compared with a NASA gear dynamics code to validate the code as a design tool for predicting transmission vibration and noise. Analytical predictions and experimental data for gear-tooth dynamic loads and tooth-root bending stress were compared at 28 operating conditions. Strain gage data were used to compute the normal load between meshing teeth and the bending stress at the tooth root for direct comparison with the analysis. The computed and measured waveforms for dynamic load and stress were compared for several test conditions. These are very similar in shape, which means the analysis successfully simulates the physical behavior of the test gears. The predicted peak value of the dynamic load agrees with the measurement results within an average error of 4.9 percent except at low-torque, high-speed conditions. Predictions of peak dynamic root stress are generally within 10 to 15 percent of the measured values.

Hybrid function projective synchronization in complex dynamical networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wei, Qiang; Wang, Xing-yuan, E-mail: wangxy@dlut.edu.cn; Hu, Xiao-peng

2014-02-15

This paper investigates hybrid function projective synchronization in complex dynamical networks. When the complex dynamical networks could be synchronized up to an equilibrium or periodic orbit, a hybrid feedback controller is designed to realize the different component of vector of node could be synchronized up to different desired scaling function in complex dynamical networks with time delay. Hybrid function projective synchronization (HFPS) in complex dynamical networks with constant delay and HFPS in complex dynamical networks with time-varying coupling delay are researched, respectively. Finally, the numerical simulations show the effectiveness of theoretical analysis.

Walking in simulated Martian gravity: influence of the portable life support system's design on dynamic stability.

PubMed

Scott-Pandorf, Melissa M; O'Connor, Daniel P; Layne, Charles S; Josić, Kresimir; Kurz, Max J

2009-09-01

With human exploration of the moon and Mars on the horizon, research considerations for space suit redesign have surfaced. The portable life support system (PLSS) used in conjunction with the space suit during the Apollo missions may have influenced the dynamic balance of the gait pattern. This investigation explored potential issues with the PLSS design that may arise during the Mars exploration. A better understanding of how the location of the PLSS load influences the dynamic stability of the gait pattern may provide insight, such that space missions may have more productive missions with a smaller risk of injury and damaging equipment while falling. We explored the influence the PLSS load position had on the dynamic stability of the walking pattern. While walking, participants wore a device built to simulate possible PLSS load configurations. Floquet and Lyapunov analysis techniques were used to quantify the dynamic stability of the gait pattern. The dynamic stability of the gait pattern was influenced by the position of load. PLSS loads that are placed high and forward on the torso resulted in less dynamically stable walking patterns than loads placed evenly and low on the torso. Furthermore, the kinematic results demonstrated that all joints of the lower extremity may be important for adjusting to different load placements and maintaining dynamic stability. Space scientists and engineers may want to consider PLSS designs that distribute loads evenly and low, and space suit designs that will not limit the sagittal plane range of motion at the lower extremity joints.

AD HOC Networks for the Autonomous Car

NASA Astrophysics Data System (ADS)

Ron, Davidescu; Negrus, Eugen

2017-10-01

The future of the vehicle is made of cars, roads and infrastructures connected in a two way automated communication in a holistic system. It is a mandatory to use Encryption to maintain Confidentiality, Integrity and Availability in an ad hoc vehicle network. Vehicle to Vehicle communication, requires multichannel interaction between mobile, moving and changing parties to insure the full benefit from data sharing and real time decision making, a network of such users referred as mobile ad hoc network (MANET), however as ad hoc networks were not implemented in such a scale, it is not clear what is the best method and protocol to apply. Furthermore the visibility of secure preferred asymmetric encrypted ad hoc networks in a real time environment of dense moving autonomous vehicles has to be demonstrated, In order to evaluate the performance of Ad Hoc networks in changing conditions a simulation of multiple protocols was performed on large number of mobile nodes. The following common routing protocols were tested, DSDV is a proactive protocol, every mobile station maintains a routing table with all available destinations, DSR is a reactive routing protocol which allows nodes in the MANET to dynamically discover a source route across multiple network hops, AODV is a reactive routing protocol Instead of being proactive. It minimizes the number of broadcasts by creating routes based on demand, SAODV is a secure version of AODV, requires heavyweight asymmetric cryptographic, ARIANDE is a routing protocol that relies on highly efficient symmetric cryptography the concept is primarily based on DSR. A methodical evolution was performed in a various density of transportation, based on known communication bench mark parameters including, Throughput Vs. time, Routing Load per packets and bytes. Out of the none encrypted protocols, It is clear that in terms of performance of throughput and routing load DSR protocol has a clear advantage the high node number mode. The encrypted protocols show lower performance with ARIANDE being superior to SAODV and SRP. Nevertheless all protocol simulation proved it to match required real time performance.

Optimization of the computational load of a hypercube supercomputer onboard a mobile robot.

PubMed

Barhen, J; Toomarian, N; Protopopescu, V

1987-12-01

A combinatorial optimization methodology is developed, which enables the efficient use of hypercube multiprocessors onboard mobile intelligent robots dedicated to time-critical missions. The methodology is implemented in terms of large-scale concurrent algorithms based either on fast simulated annealing, or on nonlinear asynchronous neural networks. In particular, analytic expressions are given for the effect of singleneuron perturbations on the systems' configuration energy. Compact neuromorphic data structures are used to model effects such as prec xdence constraints, processor idling times, and task-schedule overlaps. Results for a typical robot-dynamics benchmark are presented.

Optimization of the computational load of a hypercube supercomputer onboard a mobile robot

NASA Technical Reports Server (NTRS)

Barhen, Jacob; Toomarian, N.; Protopopescu, V.

1987-01-01

A combinatorial optimization methodology is developed, which enables the efficient use of hypercube multiprocessors onboard mobile intelligent robots dedicated to time-critical missions. The methodology is implemented in terms of large-scale concurrent algorithms based either on fast simulated annealing, or on nonlinear asynchronous neural networks. In particular, analytic expressions are given for the effect of single-neuron perturbations on the systems' configuration energy. Compact neuromorphic data structures are used to model effects such as precedence constraints, processor idling times, and task-schedule overlaps. Results for a typical robot-dynamics benchmark are presented.

Dynamic Response of Reinforced Soil Systems. Volume 2. Appendices

DTIC Science & Technology

1993-03-01

by a burster slab. These protection measures are costly, time consuming to construct, and sensitive to multiple strikes. Soil has been used to...load--deflection behavior of the reinforced soi I Dynamic puilout tests were then performed using the same parameters as the static tests. A standard...system was capable cf loading the sample in just a few micro-seconds to simulate a blast load. Dynamic load-deflection behavior was characterized and

Network cosmology.

PubMed

Krioukov, Dmitri; Kitsak, Maksim; Sinkovits, Robert S; Rideout, David; Meyer, David; Boguñá, Marián

2012-01-01

Prediction and control of the dynamics of complex networks is a central problem in network science. Structural and dynamical similarities of different real networks suggest that some universal laws might accurately describe the dynamics of these networks, albeit the nature and common origin of such laws remain elusive. Here we show that the causal network representing the large-scale structure of spacetime in our accelerating universe is a power-law graph with strong clustering, similar to many complex networks such as the Internet, social, or biological networks. We prove that this structural similarity is a consequence of the asymptotic equivalence between the large-scale growth dynamics of complex networks and causal networks. This equivalence suggests that unexpectedly similar laws govern the dynamics of complex networks and spacetime in the universe, with implications to network science and cosmology.

Network Cosmology

PubMed Central

Krioukov, Dmitri; Kitsak, Maksim; Sinkovits, Robert S.; Rideout, David; Meyer, David; Boguñá, Marián

2012-01-01

Prediction and control of the dynamics of complex networks is a central problem in network science. Structural and dynamical similarities of different real networks suggest that some universal laws might accurately describe the dynamics of these networks, albeit the nature and common origin of such laws remain elusive. Here we show that the causal network representing the large-scale structure of spacetime in our accelerating universe is a power-law graph with strong clustering, similar to many complex networks such as the Internet, social, or biological networks. We prove that this structural similarity is a consequence of the asymptotic equivalence between the large-scale growth dynamics of complex networks and causal networks. This equivalence suggests that unexpectedly similar laws govern the dynamics of complex networks and spacetime in the universe, with implications to network science and cosmology. PMID:23162688

Optimal charge control strategies for stationary photovoltaic battery systems

NASA Astrophysics Data System (ADS)

Li, Jiahao; Danzer, Michael A.

2014-07-01

Battery systems coupled to photovoltaic (PV) modules for example fulfill one major function: they locally decouple PV generation and consumption of electrical power leading to two major effects. First, they reduce the grid load, especially at peak times and therewith reduce the necessity of a network expansion. And second, they increase the self-consumption in households and therewith help to reduce energy expenses. For the management of PV batteries charge control strategies need to be developed to reach the goals of both the distribution system operators and the local power producer. In this work optimal control strategies regarding various optimization goals are developed on the basis of the predicted household loads and PV generation profiles using the method of dynamic programming. The resulting charge curves are compared and essential differences discussed. Finally, a multi-objective optimization shows that charge control strategies can be derived that take all optimization goals into account.

Effect of extended tooth contact on the modeling of spur gear transmissions

NASA Technical Reports Server (NTRS)

Oswald, Fred B.; Coy, John J.; Lin, Hsiang Hsi; Wang, Jifeng

1993-01-01

In some gear dynamic models, the effect of tooth flexibility is ignored when the model determines which pairs of teeth are in contact. Deflection of loaded teeth is not introduced until the equations of motion are solved. This means the zone of tooth contact and average tooth meshing stiffness are underestimated and the individual tooth load is overstated, especially for heavily-loaded gears. The static transmission error and dynamic load of heavily-loaded, low-contact-ratio spur gears is compared with this effect both neglected and included. Neglecting the effect yields an underestimate of resonance speeds and an overestimate of the dynamic load.

In-vitro development of a temporal abutment screw to protect osseointegration in immediate loaded implants.

PubMed

García-Roncero, Herminio; Caballé-Serrano, Jordi; Cano-Batalla, Jordi; Cabratosa-Termes, Josep; Figueras-Álvarez, Oscar

2015-04-01

In this study, a temporal abutment fixation screw, designed to fracture in a controlled way upon application of an occlusal force sufficient to produce critical micromotion was developed. The purpose of the screw was to protect the osseointegration of immediate loaded single implants. Seven different screw prototypes were examined by fixing titanium abutments to 112 Mozo-Grau external hexagon implants (MG Osseous®; Mozo-Grau, S.A., Valladolid, Spain). Fracture strength was tested at 30° in two subgroups per screw: one under dynamic loading and the other without prior dynamic loading. Dynamic loading was performed in a single-axis chewing simulator using 150,000 load cycles at 50 N. After normal distribution of obtained data was verified by Kolmogorov-Smirnov test, fracture resistance between samples submitted and not submitted to dynamic loading was compared by the use of Student's t-test. Comparison of fracture resistance among different screw designs was performed by the use of one-way analysis of variance. Confidence interval was set at 95%. Fractures occurred in all screws, allowing easy retrieval. Screw Prototypes 2, 5 and 6 failed during dynamic loading and exhibited statistically significant differences from the other prototypes. Prototypes 2, 5 and 6 may offer a useful protective mechanism during occlusal overload in immediate loaded implants.

Effect of dynamic load on water flow boiling CHF in rectangular channels

NASA Astrophysics Data System (ADS)

Zhang, Zhao; Song, Baoyin; Li, Gang; Cao, Xi

2018-06-01

Experimental investigation into flow boiling critical heat flux (CHF) characteristics in narrow rectangular channels was performed under rotating state using distilled water as working fluids. The effects of mass velocity, inlet temperature and heating orientation on CHF under dynamic load were analyzed and discussed in this paper. The results show that the dynamic load obviously influences the CHF through enhancing two-phase mixing up and bubble separating. The greater the dynamic load, the higher the CHF values. The CHF values increase with the increase of mass velocity and inlet subcooling in the experimental range. The magnitude of CHF increase with the dynamic load for bottom heating is greater than that for up heating. The present study and its newly correlation may provide some technical supports in designing the airborne vapor cycle system.

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

NASA Astrophysics Data System (ADS)

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.

Processing of visual semantic information to concrete words: temporal dynamics and neural mechanisms indicated by event-related brain potentials( ).

PubMed

van Schie, Hein T; Wijers, Albertus A; Mars, Rogier B; Benjamins, Jeroen S; Stowe, Laurie A

2005-05-01

Event-related brain potentials were used to study the retrieval of visual semantic information to concrete words, and to investigate possible structural overlap between visual object working memory and concreteness effects in word processing. Subjects performed an object working memory task that involved 5 s retention of simple 4-angled polygons (load 1), complex 10-angled polygons (load 2), and a no-load baseline condition. During the polygon retention interval subjects were presented with a lexical decision task to auditory presented concrete (imageable) and abstract (nonimageable) words, and pseudowords. ERP results are consistent with the use of object working memory for the visualisation of concrete words. Our data indicate a two-step processing model of visual semantics in which visual descriptive information of concrete words is first encoded in semantic memory (indicated by an anterior N400 and posterior occipital positivity), and is subsequently visualised via the network for object working memory (reflected by a left frontal positive slow wave and a bilateral occipital slow wave negativity). Results are discussed in the light of contemporary models of semantic memory.

The Relationship between MR Parameters and Biomechanical Quantities of Loaded Human Articular Cartilage in Osteoarthritis: An In-Vitro Study

NASA Astrophysics Data System (ADS)

Juráš, V.; Szomolányi, P.; Gäbler, S.; Frollo, I.; Trattnig, S.

2009-01-01

The aim of this study was to assess the changes in MRI parameters during applied load directly in MR scanner and correlate these changes with biomechanical parameters of human articular cartilage. Cartilage explants from patients who underwent total knee replacement were examined in the micro-imaging system in 3T scanner. Respective MRI parameters (T1 without- and T1 with contrast agent as a marker of proteoglycan content, T2 as a marker of collagen network anisotropy and ADC as a measure of diffusivity) were calculated in pre- and during compression state. Subsequently, these parameters were compared to the biomechanical properties of articular cartilage, instantaneous modulus (I), equilibrium modulus (Eq) and time of tissue relaxation (τ). Significant load-induced changes of T2 and ADC were recorded. High correlation between T1Gd and I (r = 0.6324), and between ADC and Eq (r = -0.4884) was found. Multi-parametric MRI may have great potential in analyzing static and dynamic biomechanical behavior of articular cartilage in early stages of osteoarthritis (OA).

Potentials of real time control, stormwater infiltration and urine separation to minimize river impacts: dynamic long term simulation of sewer network, pumping stations, pressure pipes and waste water treatment plant.

PubMed

Peters, C; Keller, S; Sieker, H; Jekel, M

2007-01-01

River Panke (Berlin, Germany) suffers from hydraulic peak loads and pollutant loads from separate sewers and combined sewer overflows (CSOs). Pumping the wastewater through long pressure pipes causes extreme peak loads to the wastewater treatment plant (WWTP) during stormwater events. In order to find a good solution, it is essential not to decide on one approach at the beginning, but to evaluate a number of different approaches. For this reason, an integrated simulation study is carried out, assessing the potentials of real time control (RTC), stormwater infiltration, storage and urine separation. Criteria for the assessment are derived and multi-criteria analysis is applied. Despite spatial limitations, infiltration has the highest potential and is very effective with respect to both overflows and the WWTP. Due to a high percentage of separate systems, urine separation has a similar potential and causes the strongest benefits at the WWTP. Unconventional control strategies can lead to significant improvement (comparable to infiltrating the water from approximately 10% of the sealed area).

Graph properties of synchronized cortical networks during visual working memory maintenance.

PubMed

Palva, Satu; Monto, Simo; Palva, J Matias

2010-02-15

Oscillatory synchronization facilitates communication in neuronal networks and is intimately associated with human cognition. Neuronal activity in the human brain can be non-invasively imaged with magneto- (MEG) and electroencephalography (EEG), but the large-scale structure of synchronized cortical networks supporting cognitive processing has remained uncharacterized. We combined simultaneous MEG and EEG (MEEG) recordings with minimum-norm-estimate-based inverse modeling to investigate the structure of oscillatory phase synchronized networks that were active during visual working memory (VWM) maintenance. Inter-areal phase-synchrony was quantified as a function of time and frequency by single-trial phase-difference estimates of cortical patches covering the entire cortical surfaces. The resulting networks were characterized with a number of network metrics that were then compared between delta/theta- (3-6 Hz), alpha- (7-13 Hz), beta- (16-25 Hz), and gamma- (30-80 Hz) frequency bands. We found several salient differences between frequency bands. Alpha- and beta-band networks were more clustered and small-world like but had smaller global efficiency than the networks in the delta/theta and gamma bands. Alpha- and beta-band networks also had truncated-power-law degree distributions and high k-core numbers. The data converge on showing that during the VWM-retention period, human cortical alpha- and beta-band networks have a memory-load dependent, scale-free small-world structure with densely connected core-like structures. These data further show that synchronized dynamic networks underlying a specific cognitive state can exhibit distinct frequency-dependent network structures that could support distinct functional roles. Copyright 2009 Elsevier Inc. All rights reserved.

Sparse dynamical Boltzmann machine for reconstructing complex networks with binary dynamics

NASA Astrophysics Data System (ADS)

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.

Sparse dynamical Boltzmann machine for reconstructing complex networks with binary dynamics.

PubMed

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.

The influence of the depth of k-core layers on the robustness of interdependent networks against cascading failures

NASA Astrophysics Data System (ADS)

Dong, Zhengcheng; Fang, Yanjun; Tian, Meng; Kong, Zhengmin

The hierarchical structure, k-core, is common in various complex networks, and the actual network always has successive layers from 1-core layer (the peripheral layer) to km-core layer (the core layer). The nodes within the core layer have been proved to be the most influential spreaders, but there is few work about how the depth of k-core layers (the value of km) can affect the robustness against cascading failures, rather than the interdependent networks. First, following the preferential attachment, a novel method is proposed to generate the scale-free network with successive k-core layers (KCBA network), and the KCBA network is validated more realistic than the traditional BA network. Then, with KCBA interdependent networks, the effect of the depth of k-core layers is investigated. Considering the load-based model, the loss of capacity on nodes is adopted to quantify the robustness instead of the number of functional nodes in the end. We conduct two attacking strategies, i.e. the RO-attack (Randomly remove only one node) and the RF-attack (Randomly remove a fraction of nodes). Results show that the robustness of KCBA networks not only depends on the depth of k-core layers, but also is slightly influenced by the initial load. With RO-attack, the networks with less k-core layers are more robust when the initial load is small. With RF-attack, the robustness improves with small km, but the improvement is getting weaker with the increment of the initial load. In a word, the lower the depth is, the more robust the networks will be.

DSGRN: Examining the Dynamics of Families of Logical Models.

PubMed

Cummins, Bree; Gedeon, Tomas; Harker, Shaun; Mischaikow, Konstantin

2018-01-01

We present a computational tool DSGRN for exploring the dynamics of a network by computing summaries of the dynamics of switching models compatible with the network across all parameters. The network can arise directly from a biological problem, or indirectly as the interaction graph of a Boolean model. This tool computes a finite decomposition of parameter space such that for each region, the state transition graph that describes the coarse dynamical behavior of a network is the same. Each of these parameter regions corresponds to a different logical description of the network dynamics. The comparison of dynamics across parameters with experimental data allows the rejection of parameter regimes or entire networks as viable models for representing the underlying regulatory mechanisms. This in turn allows a search through the space of perturbations of a given network for networks that robustly fit the data. These are the first steps toward discovering a network that optimally matches the observed dynamics by searching through the space of networks.

DAWN: Dynamic Ad-hoc Wireless Network

DTIC Science & Technology

2016-06-19

DAWN: Dynamic Ad-hoc Wireless Network The DAWN (Dynamic Ad-hoc Wireless Networks) project is developing a general theory of complex and dynamic... wireless communication networks. To accomplish this, DAWN adopts a very different approach than those followed in the past and summarized above. DAWN... wireless communication networks. The members of DAWN investigated difference aspects of wireless mobile ad hoc networks (MANET). The views, opinions and/or

Valiant load-balanced robust routing under hose model for WDM mesh networks

NASA Astrophysics Data System (ADS)

Zhang, Xiaoning; Li, Lemin; Wang, Sheng

2006-09-01

In this paper, we propose Valiant Load-Balanced robust routing scheme for WDM mesh networks under the model of polyhedral uncertainty (i.e., hose model), and the proposed routing scheme is implemented with traffic grooming approach. Our Objective is to maximize the hose model throughput. A mathematic formulation of Valiant Load-Balanced robust routing is presented and three fast heuristic algorithms are also proposed. When implementing Valiant Load-Balanced robust routing scheme to WDM mesh networks, a novel traffic-grooming algorithm called MHF (minimizing hop first) is proposed. We compare the three heuristic algorithms with the VPN tree under the hose model. Finally we demonstrate in the simulation results that MHF with Valiant Load-Balanced robust routing scheme outperforms the traditional traffic-grooming algorithm in terms of the throughput for the uniform/non-uniform traffic matrix under the hose model.

Design and analysis of a novel mechanical loading machine for dynamic in vivo axial loading

NASA Astrophysics Data System (ADS)

Macione, James; Nesbitt, Sterling; Pandit, Vaibhav; Kotha, Shiva

2012-02-01

This paper describes the construction of a loading machine for performing in vivo, dynamic mechanical loading of the rodent forearm. The loading machine utilizes a unique type of electromagnetic actuator with no mechanically resistive components (servotube), allowing highly accurate loads to be created. A regression analysis of the force created by the actuator with respect to the input voltage demonstrates high linear correlation (R2 = 1). When the linear correlation is used to create dynamic loading waveforms in the frequency (0.5-10 Hz) and load (1-50 N) range used for in vivo loading, less than 1% normalized root mean square error (NRMSE) is computed. Larger NRMSE is found at increased frequencies, with 5%-8% occurring at 40 Hz, and reasons are discussed. Amplifiers (strain gauge, linear voltage displacement transducer (LVDT), and load cell) are constructed, calibrated, and integrated, to allow well-resolved dynamic measurements to be recorded at each program cycle. Each of the amplifiers uses an active filter with cutoff frequency at the maximum in vivo loading frequencies (50 Hz) so that electronic noise generated by the servo drive and actuator are reduced. The LVDT and load cell amplifiers allow evaluation of stress-strain relationships to determine if in vivo bone damage is occurring. The strain gauge amplifier allows dynamic force to strain calibrations to occur for animals of different sex, age, and strain. Unique features are integrated into the loading system, including a weightless mode, which allows the limbs of anesthetized animals to be quickly positioned and removed. Although the device is constructed for in vivo axial bone loading, it can be used within constraints, as a general measurement instrument in a laboratory setting.

Design and analysis of a novel mechanical loading machine for dynamic in vivo axial loading.

PubMed

Macione, James; Nesbitt, Sterling; Pandit, Vaibhav; Kotha, Shiva

2012-02-01

This paper describes the construction of a loading machine for performing in vivo, dynamic mechanical loading of the rodent forearm. The loading machine utilizes a unique type of electromagnetic actuator with no mechanically resistive components (servotube), allowing highly accurate loads to be created. A regression analysis of the force created by the actuator with respect to the input voltage demonstrates high linear correlation (R(2) = 1). When the linear correlation is used to create dynamic loading waveforms in the frequency (0.5-10 Hz) and load (1-50 N) range used for in vivo loading, less than 1% normalized root mean square error (NRMSE) is computed. Larger NRMSE is found at increased frequencies, with 5%-8% occurring at 40 Hz, and reasons are discussed. Amplifiers (strain gauge, linear voltage displacement transducer (LVDT), and load cell) are constructed, calibrated, and integrated, to allow well-resolved dynamic measurements to be recorded at each program cycle. Each of the amplifiers uses an active filter with cutoff frequency at the maximum in vivo loading frequencies (50 Hz) so that electronic noise generated by the servo drive and actuator are reduced. The LVDT and load cell amplifiers allow evaluation of stress-strain relationships to determine if in vivo bone damage is occurring. The strain gauge amplifier allows dynamic force to strain calibrations to occur for animals of different sex, age, and strain. Unique features are integrated into the loading system, including a weightless mode, which allows the limbs of anesthetized animals to be quickly positioned and removed. Although the device is constructed for in vivo axial bone loading, it can be used within constraints, as a general measurement instrument in a laboratory setting.

Design criteria for portable timber bridge systems : static versus dynamic loads

Treesearch

John M. Franklin; S. E. Taylor; Paul A. Morgan; M. A. Ritter

1999-01-01

Design criteria are needed specifically for portable bridges to insure that they are safe and cost effective. This paper discusses different portable bridge categories and their general design criteria. Specific emphasis is given to quantifying the effects of dynamic live loads on portable bridge design. Results from static and dynamic load tests of two portable timber...

An optimization-based approach for facility energy management with uncertainties, and, Power portfolio optimization in deregulated electricity markets with risk management

NASA Astrophysics Data System (ADS)

Xu, Jun

Topic 1. An Optimization-Based Approach for Facility Energy Management with Uncertainties. Effective energy management for facilities is becoming increasingly important in view of the rising energy costs, the government mandate on the reduction of energy consumption, and the human comfort requirements. This part of dissertation presents a daily energy management formulation and the corresponding solution methodology for HVAC systems. The problem is to minimize the energy and demand costs through the control of HVAC units while satisfying human comfort, system dynamics, load limit constraints, and other requirements. The problem is difficult in view of the fact that the system is nonlinear, time-varying, building-dependent, and uncertain; and that the direct control of a large number of HVAC components is difficult. In this work, HVAC setpoints are the control variables developed on top of a Direct Digital Control (DDC) system. A method that combines Lagrangian relaxation, neural networks, stochastic dynamic programming, and heuristics is developed to predict the system dynamics and uncontrollable load, and to optimize the setpoints. Numerical testing and prototype implementation results show that our method can effectively reduce total costs, manage uncertainties, and shed the load, is computationally efficient. Furthermore, it is significantly better than existing methods. Topic 2. Power Portfolio Optimization in Deregulated Electricity Markets with Risk Management. In a deregulated electric power system, multiple markets of different time scales exist with various power supply instruments. A load serving entity (LSE) has multiple choices from these instruments to meet its load obligations. In view of the large amount of power involved, the complex market structure, risks in such volatile markets, stringent constraints to be satisfied, and the long time horizon, a power portfolio optimization problem is of critical importance but difficulty for an LSE to serve the load, maximize its profit, and manage risks. In this topic, a mid-term power portfolio optimization problem with risk management is presented. Key instruments are considered, risk terms based on semi-variances of spot market transactions are introduced, and penalties on load obligation violations are added to the objective function to improve algorithm convergence and constraint satisfaction. To overcome the inseparability of the resulting problem, a surrogate optimization framework is developed enabling a decomposition and coordination approach. Numerical testing results show that our method effectively provides decisions for various instruments to maximize profit, manage risks, and is computationally efficient.

Wavelength converter placement for different RWA algorithms in wavelength-routed all-optical networks

NASA Astrophysics Data System (ADS)

Chu, Xiaowen; Li, Bo; Chlamtac, Imrich

2002-07-01

Sparse wavelength conversion and appropriate routing and wavelength assignment (RWA) algorithms are the two key factors in improving the blocking performance in wavelength-routed all-optical networks. It has been shown that the optimal placement of a limited number of wavelength converters in an arbitrary mesh network is an NP complete problem. There have been various heuristic algorithms proposed in the literature, in which most of them assume that a static routing and random wavelength assignment RWA algorithm is employed. However, the existing work shows that fixed-alternate routing and dynamic routing RWA algorithms can achieve much better blocking performance. Our study in this paper further demonstrates that the wavelength converter placement and RWA algorithms are closely related in the sense that a well designed wavelength converter placement mechanism for a particular RWA algorithm might not work well with a different RWA algorithm. Therefore, the wavelength converter placement and the RWA have to be considered jointly. The objective of this paper is to investigate the wavelength converter placement problem under fixed-alternate routing algorithm and least-loaded routing algorithm. Under the fixed-alternate routing algorithm, we propose a heuristic algorithm called Minimum Blocking Probability First (MBPF) algorithm for wavelength converter placement. Under the least-loaded routing algorithm, we propose a heuristic converter placement algorithm called Weighted Maximum Segment Length (WMSL) algorithm. The objective of the converter placement algorithm is to minimize the overall blocking probability. Extensive simulation studies have been carried out over three typical mesh networks, including the 14-node NSFNET, 19-node EON and 38-node CTNET. We observe that the proposed algorithms not only outperform existing wavelength converter placement algorithms by a large margin, but they also can achieve almost the same performance comparing with full wavelength conversion under the same RWA algorithm.

Mechano-responsive hydrogels crosslinked by reactive block copolymer micelles

NASA Astrophysics Data System (ADS)

Xiao, Longxi

Hydrogels are crosslinked polymeric networks that can swell in water without dissolution. Owing to their structural similarity to the native extracelluar matrices, hydrogels have been widely used in biomedical applications. Synthetic hydrogels have been designed to respond to various stimuli, but mechanical signals have not incorporated into hydrogel matrices. Because most tissues in the body are subjected to various types of mechanical forces, and cells within these tissues have sophisticated mechano-transduction machinery, this thesis is focused on developing hydrogel materials with built-in mechano-sensing mechanisms for use as tissue engineering scaffolds or drug release devices. Self-assembled block copolymer micelles (BCMs) with reactive handles were employed as the nanoscopic crosslinkers for the construction of covalently crosslinked networks. BCMs were assembled from amphiphilic diblock copolymers of poly(n-butyl acrylate) and poly(acrylic acid) partially modified with acrylate. Radical polymerization of acrylamide in the presence of micellar crosslinkers gave rise to elastomeric hydrogels whose mechanical properties can be tuned by varying the BCM composition and concentration. TEM imaging revealed that the covalently integrated BCMs underwent strain-dependent reversible deformation. A model hydrophobic drug, pyrene, loaded into the core of BCMs prior to the hydrogel formation, was dynamically released in response to externally applied mechanical forces, through force-induced reversible micelle deformation and the penetration of water molecules into the micelle core. The mechano-responsive hydrogel has been studied for tissue repair and regeneration purposes. Glycidyl methacrylate (GMA)-modified hyaluronic acid (HA) was photochemically crosslinked in the presence of dexamethasone (DEX)-loaded crosslinkable BCMs. The resultant HA gels (HAxBCM) contain covalently integrated micellar compartments with DEX being sequestered in the hydrophobic core. Compared to the traditional HA gels prepared by radical crosslinking of HAGMA, HAxBCM gels exhibited improved drug loading and release capacity. Moreover, compressive forces exerted on the gels were transmitted to the crosslinked BCMs, resulting in a force-modulated DEX release on demand. Micelle mobility in the crosslinked networks was analyzed by fluorescence correlation spectroscopy using nile red loaded BCMs. The anti-inflammatory activities of DEX-releasing HAxBCM gels were evaluated via the in vitro culture of lipopolysaccharide-activated macrophages.

In vivo dynamic compression has less detrimental effect than static compression on newly formed bone of a rat caudal vertebra

PubMed Central

Benoit, A.; Mustafy, T.; Londono, I.; Grimard, G.; Aubin, C-E.; Villemure, I.

2016-01-01

Fusionless devices are currently designed to treat spinal deformities such as scoliosis by the application of a controlled mechanical loading. Growth modulation by dynamic compression was shown to preserve soft tissues. The objective of this in vivo study was to characterize the effect of static vs. dynamic loading on the bone formed during growth modulation. Controlled compression was applied during 15 days on the 7th caudal vertebra (Cd7) of rats during growth spurt. The load was sustained in the “static” group and sinusoidally oscillating in the “dynamic” group. The effect of surgery and of the device was investigated using control and sham (operated on but no load applied) groups. A high resolution CT-scan of Cd7 was acquired at days 2, 8 and 15 of compression. Growth rates, histomorphometric parameters and mineral density of the newly formed bone were quantified and compared. Static and dynamic loadings significantly reduced the growth rate by 20% compared to the sham group. Dynamic loading preserved newly formed bone histomorphometry and mineral density whereas static loading induced thicker (+31%) and more mineralized (+12%) trabeculae. A significant sham effect was observed. Growth modulation by dynamic compression constitutes a promising way to develop new treatment for skeletal deformities. PMID:27609036

Mechanical and Electrical Characterization of Entangled Networks of Carbon Nanofibers

PubMed Central

Mousavi, Arash K.; Atwater, Mark A.; Mousavi, Behnam K.; Jalalpour, Mohammad; Taha, Mahmoud Reda; Leseman, Zayd C.

2014-01-01

Entangled networks of carbon nanofibers are characterized both mechanically and electrically. Results for both tensile and compressive loadings of the entangled networks are presented for various densities. Mechanically, the nanofiber ensembles follow the micromechanical model originally proposed by van Wyk nearly 70 years ago. Interpretations are given on the mechanisms occurring during loading and unloading of the carbon nanofiber components. PMID:28788709

Force-Strain Characteristics and Rupture-Load Capability of Viking-Type Suspension-Line Material Under Dynamic Loading Conditions

NASA Technical Reports Server (NTRS)

Poole, Lamont R.; Councill, Earl L., Jr.

1972-01-01

A series of tests has been conducted to investigate the elastic behavior of Viking-type suspension-line material under dynamic loading conditions. Results indicate that there is a decrease in both rupture-load capability and elongation at rupture as the test strain rate is increased. Preliminary examination of force-strain characteristics indicates that, on the average, the material exhibits some type of viscous effect which results in a greater force being produced, for a particular value of strain, under dynamic loading conditions than that produced under quasi-static loading conditions. A great deal of uncertainty exists in defining a priori the tensile properties of viscoelastic materials, such as nylon or dacron, under dynamic loading conditions. Additional uncertainty enters the picture when woven configurations such as suspension,line material are considered. To eliminate these uncertainties, with respect to the Viking parachute configuration, a test program has been conducted to obtain data on the tensile properties of Viking-type suspension-line material over a wide range of strain rates. Based on preliminary examination of these data, the following conclusions can be drawn: 1. Material rupture-load capability decreases as strain-rate is increased. At strain rates above 75 percent/sec, no rupture loads were observed which would meet the minimum tensile strength specification of 880 pounds. 2. The material, on the average, exhibits some type of viscous effect which, for a particular value of strain, produces a greater load under dynamic loading conditions than that produced under quasi-static loading conditions.

Effect of contact ratio on spur gear dynamic load

NASA Technical Reports Server (NTRS)

Liou, Chuen-Huei; Lin, Hsiang Hsi; Oswald, Fred B.; Townsend, Dennis P.

1992-01-01

A computer simulation is presented which shows how the gear contact ratio affects the dynamic load on a spur gear transmission. The contact ratio can be affected by the tooth addendum, the pressure angle, the tooth size (diametral pitch), and the center distance. The analysis presented was performed using the NASA gear dynamics code, DANST. In the analysis, the contact ratio was varied over the range 1.20 to 2.40 by changing the length of the tooth addendum. In order to simplify the analysis, other parameters related to contact ratio were held constant. The contact ratio was found to have a significant influence on gear dynamics. Over a wide range of operating speeds, a contact ratio close to 2.0 minimized dynamic load. For low contact ratio gears (contact ratio less than 2.0), increasing the contact ratio reduced the gear dynamic load. For high contact ratio gears (contact ratio = or greater than 2.0), the selection of contact ratio should take into consideration the intended operating speeds. In general, high contact ratio gears minimized dynamic load better than low contact ratio gears.

Feasibility of solid oxide fuel cell dynamic hydrogen coproduction to meet building demand

NASA Astrophysics Data System (ADS)

Shaffer, Brendan; Brouwer, Jacob

2014-02-01

A dynamic internal reforming-solid oxide fuel cell system model is developed and used to simulate the coproduction of electricity and hydrogen while meeting the measured dynamic load of a typical southern California commercial building. The simulated direct internal reforming-solid oxide fuel cell (DIR-SOFC) system is controlled to become an electrical load following device that well follows the measured building load data (3-s resolution). The feasibility of the DIR-SOFC system to meet the dynamic building demand while co-producing hydrogen is demonstrated. The resulting thermal responses of the system to the electrical load dynamics as well as those dynamics associated with the filling of a hydrogen collection tank are investigated. The DIR-SOFC system model also allows for resolution of the fuel cell species and temperature distributions during these dynamics since thermal gradients are a concern for DIR-SOFC.

On the coherency of dynamic load estimates for vehicles on flexible structures

NASA Astrophysics Data System (ADS)

Mitra, Mainak; Gordon, Timothy

2014-05-01

This paper develops a novel form of a well-known signal processing technique, so as to be applicable to the interaction between a heavy truck and a supporting bridge structure. Motivated by the problem of structural health monitoring of bridges, a new modal coherency function is defined. This relates the input action of moving wheel loads to the dynamic response of the bridge, including the effects of unevenness of the road surface and the vertical dynamics of the truck suspension. The analysis here is specifically aimed at future experimental testing - the validation of axle load estimators obtained from sensors on the truck. It is applicable even when no independent 'ground truth' for the dynamic loads is available. The approach can be more widely used in the analysis of dynamic interactions involving suspended moving loads on deformable structures, e.g. for structural vibrations due to high-speed trains.

Wind loads on flat plate photovoltaic array fields (nonsteady winds)

NASA Technical Reports Server (NTRS)

Miller, R. D.; Zimmerman, D. K.

1981-01-01

Techniques to predict the dynamic response and the structural dynamic loads of flat plate photovoltaic arrays due to wind turbulence were analyzed. Guidelines for use in predicting the turbulent portion of the wind loading on future similar arrays are presented. The dynamic response and the loads dynamic magnification factor of the two array configurations are similar. The magnification factors at a mid chord and outer chord location on the array illustrated and at four points on the chord are shown. The wind tunnel test experimental rms pressure coefficient on which magnification factors are based is shown. It is found that the largest response and dynamic magnification factor occur at a mid chord location on an array and near the trailing edge. A technique employing these magnification factors and the wind tunnel test rms fluctuating pressure coefficients to calculate design pressure loads due to wind turbulence is presented.

Two Dimensional Array Based Overlay Network for Balancing Load of Peer-to-Peer Live Video Streaming

NASA Astrophysics Data System (ADS)

Faruq Ibn Ibrahimy, Abdullah; Rafiqul, Islam Md; Anwar, Farhat; Ibn Ibrahimy, Muhammad

2013-12-01

The live video data is streaming usually in a tree-based overlay network or in a mesh-based overlay network. In case of departure of a peer with additional upload bandwidth, the overlay network becomes very vulnerable to churn. In this paper, a two dimensional array-based overlay network is proposed for streaming the live video stream data. As there is always a peer or a live video streaming server to upload the live video stream data, so the overlay network is very stable and very robust to churn. Peers are placed according to their upload and download bandwidth, which enhances the balance of load and performance. The overlay network utilizes the additional upload bandwidth of peers to minimize chunk delivery delay and to maximize balance of load. The procedure, which is used for distributing the additional upload bandwidth of the peers, distributes the additional upload bandwidth to the heterogeneous strength peers in a fair treat distribution approach and to the homogeneous strength peers in a uniform distribution approach. The proposed overlay network has been simulated by Qualnet from Scalable Network Technologies and results are presented in this paper.

Hybrid Discrete Element - Finite Element Simulation for Railway Bridge-Track Interaction

NASA Astrophysics Data System (ADS)

Kaewunruen, S.; Mirza, O.

2017-10-01

At the transition zone or sometimes called ‘bridge end’ or ‘bridge approach’, the stiffness difference between plain track and track over bridge often causes aggravated impact loading due to uneven train movement onto the area. The differential track settlement over the transition has been a classical problem in railway networks, especially for the aging rail infrastructures around the world. This problem is also additionally worsened by the fact that the construction practice over the area is difficult, resulting in a poor compaction of formation and subgrade. This paper presents an advanced hybrid simulation using coupled discrete elements and finite elements to investigate dynamic interaction at the transition zone. The goal is to evaluate the dynamic stresses and to better understand the impact dynamics redistribution at the bridge end. An existing bridge ‘Salt Pan Creek Railway Bridge’, located between Revesby and Kingsgrove, has been chosen for detailed investigation. The Salt Pan Bridge currently demonstrates crushing of the ballast causing significant deformation and damage. Thus, it’s imperative to assess the behaviours of the ballast under dynamic loads. This can be achieved by modelling the nonlinear interactions between the steel rail and sleeper, and sleeper to ballast. The continuum solid elements of track components have been modelled using finite element approach, while the granular media (i.e. ballast) have been simulated by discrete element method. The hybrid DE/FE model demonstrates that ballast experiences significant stresses at the contacts between the sleeper and concrete section. These overburden stress exists in the regions below the outer rails, identify fouling and permanent deformation of the ballast.

A Hybrid OFDM-TDM Architecture with Decentralized Dynamic Bandwidth Allocation for PONs

PubMed Central

Cevik, Taner

2013-01-01

One of the major challenges of passive optical networks is to achieve a fair arbitration mechanism that will prevent possible collisions from occurring at the upstream channel when multiple users attempt to access the common fiber at the same time. Therefore, in this study we mainly focus on fair bandwidth allocation among users, and present a hybrid Orthogonal Frequency Division Multiplexed/Time Division Multiplexed architecture with a dynamic bandwidth allocation scheme that provides satisfying service qualities to the users depending on their varying bandwidth requirements. Unnecessary delays in centralized schemes occurring during bandwidth assignment stage are eliminated by utilizing a decentralized approach. Instead of sending bandwidth demands to the optical line terminal (OLT) which is the only competent authority, each optical network unit (ONU) runs the same bandwidth demand determination algorithm. ONUs inform each other via signaling channel about the status of their queues. This information is fed to the bandwidth determination algorithm which is run by each ONU in a distributed manner. Furthermore, Light Load Penalty, which is a phenomenon in optical communications, is mitigated by limiting the amount of bandwidth that an ONU can demand. PMID:24194684

Methods for computing water-quality loads at sites in the U.S. Geological Survey National Water Quality Network

USGS Publications Warehouse

Lee, Casey J.; Murphy, Jennifer C.; Crawford, Charles G.; Deacon, Jeffrey R.

2017-10-24

The U.S. Geological Survey publishes information on concentrations and loads of water-quality constituents at 111 sites across the United States as part of the U.S. Geological Survey National Water Quality Network (NWQN). This report details historical and updated methods for computing water-quality loads at NWQN sites. The primary updates to historical load estimation methods include (1) an adaptation to methods for computing loads to the Gulf of Mexico; (2) the inclusion of loads computed using the Weighted Regressions on Time, Discharge, and Season (WRTDS) method; and (3) the inclusion of loads computed using continuous water-quality data. Loads computed using WRTDS and continuous water-quality data are provided along with those computed using historical methods. Various aspects of method updates are evaluated in this report to help users of water-quality loading data determine which estimation methods best suit their particular application.

Highly designable phenotypes and mutational buffers emerge from a systematic mapping between network topology and dynamic output.

PubMed

Nochomovitz, Yigal D; Li, Hao

2006-03-14

Deciphering the design principles for regulatory networks is fundamental to an understanding of biological systems. We have explored the mapping from the space of network topologies to the space of dynamical phenotypes for small networks. Using exhaustive enumeration of a simple model of three- and four-node networks, we demonstrate that certain dynamical phenotypes can be generated by an atypically broad spectrum of network topologies. Such dynamical outputs are highly designable, much like certain protein structures can be designed by an unusually broad spectrum of sequences. The network topologies that encode a highly designable dynamical phenotype possess two classes of connections: a fully conserved core of dedicated connections that encodes the stable dynamical phenotype and a partially conserved set of variable connections that controls the transient dynamical flow. By comparing the topologies and dynamics of the three- and four-node network ensembles, we observe a large number of instances of the phenomenon of "mutational buffering," whereby addition of a fourth node suppresses phenotypic variation amongst a set of three-node networks.

Nanoscopic Dynamic Mechanical Properties of Intertubular and Peritubular Dentin

PubMed Central

Ryou, Heon; Romberg, Elaine; Pashley, David H.; Tay, Franklin R.; Arola, Dwayne

2011-01-01

An experimental evaluation of intertubular and peritubular dentin was performed using nanoindentation and Dynamic Mechanical Analysis (DMA). The objective of the investigation was to evaluate the differences in dynamic mechanical behavior of these two constituents and to assess if their response is frequency dependent. Specimens of hydrated coronal dentin were evaluated by DMA using single indents over a range in parametric conditions and using scanning probe microscopy. The complex (E*), storage (E’) and loss moduli (E”) of the intertubular and peritubular dentin were evaluated as a function of the dynamic loading frequency and static load in the fully hydrated condition. The mean complex E* (19.6 GPa) and storage E’ (19.2 GPa) moduli of the intertubular dentin were significantly lower than those quantities of peritubular dentin (E* = 31.1 GPa, p< 0.05; E’ = 30.3 GPa, p< 0.05). There was no significant influence of dynamic loading frequency on these measures. Though there was no significant difference in the loss modulus (E”) between the two materials (p> 0.05), both constituents exhibited a significant increase in E” with dynamic load frequency and reduction in the quasi-static component of indentation load. The largest difference in dynamic behavior of the two tissues was noted at small quasi-static indentation loads and the highest frequency. PMID:22340680

Network-Friendly Gossiping

NASA Astrophysics Data System (ADS)

Serbu, Sabina; Rivière, Étienne; Felber, Pascal

The emergence of large-scale distributed applications based on many-to-many communication models, e.g., broadcast and decentralized group communication, has an important impact on the underlying layers, notably the Internet routing infrastructure. To make an effective use of network resources, protocols should both limit the stress (amount of messages) on each infrastructure entity like routers and links, and balance as much as possible the load in the network. Most protocols use application-level metrics such as delays to improve efficiency of content dissemination or routing, but the extend to which such application-centric optimizations help reduce and balance the load imposed to the infrastructure is unclear. In this paper, we elaborate on the design of such network-friendly protocols and associated metrics. More specifically, we investigate random-based gossip dissemination. We propose and evaluate different ways of making this representative protocol network-friendly while keeping its desirable properties (robustness and low delays). Simulations of the proposed methods using synthetic and real network topologies convey and compare their abilities to reduce and balance the load while keeping good performance.

An electromechanical based deformable model for soft tissue simulation.

PubMed

Zhong, Yongmin; Shirinzadeh, Bijan; Smith, Julian; Gu, Chengfan

2009-11-01

Soft tissue deformation is of great importance to surgery simulation. Although a significant amount of research efforts have been dedicated to simulating the behaviours of soft tissues, modelling of soft tissue deformation is still a challenging problem. This paper presents a new deformable model for simulation of soft tissue deformation from the electromechanical viewpoint of soft tissues. Soft tissue deformation is formulated as a reaction-diffusion process coupled with a mechanical load. The mechanical load applied to a soft tissue to cause a deformation is incorporated into the reaction-diffusion system, and consequently distributed among mass points of the soft tissue. Reaction-diffusion of mechanical load and non-rigid mechanics of motion are combined to govern the simulation dynamics of soft tissue deformation. An improved reaction-diffusion model is developed to describe the distribution of the mechanical load in soft tissues. A three-layer artificial cellular neural network is constructed to solve the reaction-diffusion model for real-time simulation of soft tissue deformation. A gradient based method is established to derive internal forces from the distribution of the mechanical load. Integration with a haptic device has also been achieved to simulate soft tissue deformation with haptic feedback. The proposed methodology does not only predict the typical behaviours of living tissues, but it also accepts both local and large-range deformations. It also accommodates isotropic, anisotropic and inhomogeneous deformations by simple modification of diffusion coefficients.

Transcription factor assisted loading and enhancer dynamics dictate the hepatic fasting response.

PubMed

Goldstein, Ido; Baek, Songjoon; Presman, Diego M; Paakinaho, Ville; Swinstead, Erin E; Hager, Gordon L

2017-03-01

Fasting elicits transcriptional programs in hepatocytes leading to glucose and ketone production. This transcriptional program is regulated by many transcription factors (TFs). To understand how this complex network regulates the metabolic response to fasting, we aimed at isolating the enhancers and TFs dictating it. Measuring chromatin accessibility revealed that fasting massively reorganizes liver chromatin, exposing numerous fasting-induced enhancers. By utilizing computational methods in combination with dissecting enhancer features and TF cistromes, we implicated four key TFs regulating the fasting response: glucocorticoid receptor (GR), cAMP responsive element binding protein 1 (CREB1), peroxisome proliferator activated receptor alpha (PPARA), and CCAAT/enhancer binding protein beta (CEBPB). These TFs regulate fuel production by two distinctly operating modules, each controlling a separate metabolic pathway. The gluconeogenic module operates through assisted loading, whereby GR doubles the number of sites occupied by CREB1 as well as enhances CREB1 binding intensity and increases accessibility of CREB1 binding sites. Importantly, this GR-assisted CREB1 binding was enhancer-selective and did not affect all CREB1-bound enhancers. Single-molecule tracking revealed that GR increases the number and DNA residence time of a portion of chromatin-bound CREB1 molecules. These events collectively result in rapid synergistic gene expression and higher hepatic glucose production. Conversely, the ketogenic module operates via a GR-induced TF cascade, whereby PPARA levels are increased following GR activation, facilitating gradual enhancer maturation next to PPARA target genes and delayed ketogenic gene expression. Our findings reveal a complex network of enhancers and TFs that dynamically cooperate to restore homeostasis upon fasting. Published by Cold Spring Harbor Laboratory Press.

Rolling Maneuver Load Alleviation using active controls

NASA Technical Reports Server (NTRS)

Woods-Vedeler, Jessica A.; Pototzky, Anthony S.

1992-01-01

Rolling Maneuver Load Alleviation (RMLA) has been demonstrated on the Active Flexible Wing (AFW) wind tunnel model in the NASA Langley Transonic Dynamics Tunnel. The design objective was to develop a systematic approach for developing active control laws to alleviate wing incremental loads during roll maneuvers. Using linear load models for the AFW wind-tunnel model which were based on experimental measurements, two RMLA control laws were developed based on a single-degree-of-freedom roll model. The RMLA control laws utilized actuation of outboard control surface pairs to counteract incremental loads generated during rolling maneuvers and actuation of the trailing edge inboard control surface pairs to maintain roll performance. To evaluate the RMLA control laws, roll maneuvers were performed in the wind tunnel at dynamic pressures of 150, 200, and 250 psf and Mach numbers of 0.33, .38 and .44, respectively. Loads obtained during these maneuvers were compared to baseline maneuver loads. For both RMLA controllers, the incremental torsion moments were reduced by up to 60 percent at all dynamic pressures and performance times. Results for bending moment load reductions during roll maneuvers varied. In addition, in a multiple function test, RMLA and flutter suppression system control laws were operated simultaneously during roll maneuvers at dynamic pressures 11 percent above the open-loop flutter dynamic pressure.

In-vitro development of a temporal abutment screw to protect osseointegration in immediate loaded implants

PubMed Central

2015-01-01

PURPOSE In this study, a temporal abutment fixation screw, designed to fracture in a controlled way upon application of an occlusal force sufficient to produce critical micromotion was developed. The purpose of the screw was to protect the osseointegration of immediate loaded single implants. MATERIALS AND METHODS Seven different screw prototypes were examined by fixing titanium abutments to 112 Mozo-Grau external hexagon implants (MG Osseous®; Mozo-Grau, S.A., Valladolid, Spain). Fracture strength was tested at 30° in two subgroups per screw: one under dynamic loading and the other without prior dynamic loading. Dynamic loading was performed in a single-axis chewing simulator using 150,000 load cycles at 50 N. After normal distribution of obtained data was verified by Kolmogorov-Smirnov test, fracture resistance between samples submitted and not submitted to dynamic loading was compared by the use of Student's t-test. Comparison of fracture resistance among different screw designs was performed by the use of one-way analysis of variance. Confidence interval was set at 95%. RESULTS Fractures occurred in all screws, allowing easy retrieval. Screw Prototypes 2, 5 and 6 failed during dynamic loading and exhibited statistically significant differences from the other prototypes. CONCLUSION Prototypes 2, 5 and 6 may offer a useful protective mechanism during occlusal overload in immediate loaded implants. PMID:25932315

46 CFR 154.409 - Dynamic loads from vessel motion.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 5 2012-10-01 2012-10-01 false Dynamic loads from vessel motion. 154.409 Section 154... reduced speed is used in the hull strength calculation under § 31.10-5(c) of this chapter. (b) If the... EC02FE91.086 (d) If a cargo tank is designed to avoid fatigue, the dynamic loads determined under paragraph...

46 CFR 154.409 - Dynamic loads from vessel motion.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 5 2011-10-01 2011-10-01 false Dynamic loads from vessel motion. 154.409 Section 154... reduced speed is used in the hull strength calculation under § 31.10-5(c) of this chapter. (b) If the... EC02FE91.086 (d) If a cargo tank is designed to avoid fatigue, the dynamic loads determined under paragraph...

46 CFR 154.409 - Dynamic loads from vessel motion.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 46 Shipping 5 2013-10-01 2013-10-01 false Dynamic loads from vessel motion. 154.409 Section 154... reduced speed is used in the hull strength calculation under § 31.10-5(c) of this chapter. (b) If the... EC02FE91.086 (d) If a cargo tank is designed to avoid fatigue, the dynamic loads determined under paragraph...

46 CFR 154.409 - Dynamic loads from vessel motion.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 46 Shipping 5 2014-10-01 2014-10-01 false Dynamic loads from vessel motion. 154.409 Section 154... reduced speed is used in the hull strength calculation under § 31.10-5(c) of this chapter. (b) If the... EC02FE91.086 (d) If a cargo tank is designed to avoid fatigue, the dynamic loads determined under paragraph...

Static and dynamic pile testing of reinforced concrete piles with structure integrated fibre optic strain sensors

NASA Astrophysics Data System (ADS)

Schilder, Constanze; Kohlhoff, Harald; Hofmann, Detlef; Basedau, Frank; Habel, Wolfgang R.; Baeßler, Matthias; Niederleithinger, Ernst; Georgi, Steven; Herten, Markus

2013-05-01

Static and dynamic pile tests are carried out to determine the load bearing capacity and the quality of reinforced concrete piles. As part of a round robin test to evaluate dynamic load tests, structure integrated fibre optic strain sensors were used to receive more detailed information about the strains along the pile length compared to conventional measurements at the pile head. This paper shows the instrumentation of the pile with extrinsic Fabry-Perot interferometers sensors and fibre Bragg gratings sensors together with the results of the conducted static load test as well as the dynamic load tests and pile integrity tests.

Processus de modelisation et etude des orages geomagnetiques dans les reseaux electriques: Impact sur le reseau de transport d'Hydro-Quebec

NASA Astrophysics Data System (ADS)

Abdellaoui, Amr

This research project presents a complete modelling process of the effects of GIC on Hydro-Quebec power system network for system planning studies. The advantage of the presented method is that it enables planning engineers to simulate the effects of geomagnetic disturbances on the Hydro-Quebec System under different conditions and contingencies within reasonable calculation time frame. This modelling method of GIC in electric power systems has been applied to the Hydro-Quebec System. An equivalent HQ DC model has been achieved. A numerical calculation method of DC sources from a non-uniform geoelectric field has been developed and implemented on HQ DC model. Harmonics and increased reactive power losses of saturated transformers have been defined as a function of GIC through a binary search algorithm using a chosen HQ magnetization curve. The evolution in time of each transformer saturation according to its effective GIC has been evaluated using analytical formulas. The reactive power losses of saturated transformers have been modeled in PSS/E[1] HQ network as constant reactive current loads assigned to the corresponding transformer buses. Finally, time domain simulations have been performed with PSS/E taking into account transformer saturation times. This has been achieved by integrating HQ DC model results and analytical calculations results of transformer saturation times into an EMTP load model. An interface has been used to link EMTP load model to HQ PSS/E network. Different aspects of GIC effects on the Hydro-Quebec system have been studied, including the influence of uniform and non-uniform geoelectric fields, the comparison of reactive power losses of the 735kV HQ system with those of Montreal network, the risks to voltage levels and the importance of reactive power dynamic reserve. This dissertation presents a new GIC modelling approach for power systems for planning and operations purposes. This methodology could be further enhanced, particularly, the aspect regarding the transformer saturation times. Hence more research remains to be pursued in this area.

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

PubMed

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 < 0.05) increased baseline muscle activity in all muscles, except the TA compared with no WBV. Adding a light external load without WBV increased baseline muscle activity of the 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.

Citizen sensors for SHM: use of accelerometer data from smartphones.

PubMed

Feng, Maria; Fukuda, Yoshio; Mizuta, Masato; Ozer, Ekin

2015-01-29

Ubiquitous smartphones have created a significant opportunity to form a low-cost wireless Citizen Sensor network and produce big data for monitoring structural integrity and safety under operational and extreme loads. Such data are particularly useful for rapid assessment of structural damage in a large urban setting after a major event such as an earthquake. This study explores the utilization of smartphone accelerometers for measuring structural vibration, from which structural health and post-event damage can be diagnosed. Widely available smartphones are tested under sinusoidal wave excitations with frequencies in the range relevant to civil engineering structures. Large-scale seismic shaking table tests, observing input ground motion and response of a structural model, are carried out to evaluate the accuracy of smartphone accelerometers under operational, white-noise and earthquake excitations of different intensity. Finally, the smartphone accelerometers are tested on a dynamically loaded bridge. The extensive experiments show satisfactory agreements between the reference and smartphone sensor measurements in both time and frequency domains, demonstrating the capability of the smartphone sensors to measure structural responses ranging from low-amplitude ambient vibration to high-amplitude seismic response. Encouraged by the results of this study, the authors are developing a citizen-engaging and data-analytics crowdsourcing platform towards a smartphone-based Citizen Sensor network for structural health monitoring and post-event damage assessment applications.

Dynamic Load Balancing for Grid Partitioning on a SP-2 Multiprocessor: A Framework

NASA Technical Reports Server (NTRS)

Sohn, Andrew; Simon, Horst; Lasinski, T. A. (Technical Monitor)

1994-01-01

Computational requirements of full scale computational fluid dynamics change as computation progresses on a parallel machine. The change in computational intensity causes workload imbalance of processors, which in turn requires a large amount of data movement at runtime. If parallel CFD is to be successful on a parallel or massively parallel machine, balancing of the runtime load is indispensable. Here a framework is presented for dynamic load balancing for CFD applications, called Jove. One processor is designated as a decision maker Jove while others are assigned to computational fluid dynamics. Processors running CFD send flags to Jove in a predetermined number of iterations to initiate load balancing. Jove starts working on load balancing while other processors continue working with the current data and load distribution. Jove goes through several steps to decide if the new data should be taken, including preliminary evaluate, partition, processor reassignment, cost evaluation, and decision. Jove running on a single EBM SP2 node has been completely implemented. Preliminary experimental results show that the Jove approach to dynamic load balancing can be effective for full scale grid partitioning on the target machine IBM SP2.

Dynamic Load Balancing For Grid Partitioning on a SP-2 Multiprocessor: A Framework

NASA Technical Reports Server (NTRS)

Sohn, Andrew; Simon, Horst; Lasinski, T. A. (Technical Monitor)

1994-01-01

Computational requirements of full scale computational fluid dynamics change as computation progresses on a parallel machine. The change in computational intensity causes workload imbalance of processors, which in turn requires a large amount of data movement at runtime. If parallel CFD is to be successful on a parallel or massively parallel machine, balancing of the runtime load is indispensable. Here a framework is presented for dynamic load balancing for CFD applications, called Jove. One processor is designated as a decision maker Jove while others are assigned to computational fluid dynamics. Processors running CFD send flags to Jove in a predetermined number of iterations to initiate load balancing. Jove starts working on load balancing while other processors continue working with the current data and load distribution. Jove goes through several steps to decide if the new data should be taken, including preliminary evaluate, partition, processor reassignment, cost evaluation, and decision. Jove running on a single IBM SP2 node has been completely implemented. Preliminary experimental results show that the Jove approach to dynamic load balancing can be effective for full scale grid partitioning on the target machine IBM SP2.

Variability of normal vocal fold dynamics for different vocal loading in one healthy subject investigated by phonovibrograms.

PubMed

Doellinger, Michael; Lohscheller, Joerg; McWhorter, Andrew; Kunduk, Melda

2009-03-01

We investigate the potential of high-speed digital imaging technique (HSI) and the phonovibrogram (PVG) analysis in normal vocal fold dynamics by studying the effects of continuous voice use (vocal loading) during the workday. One healthy subject was recorded at sustained phonation 13 times within 2 consecutive days in the morning before and in the afternoon after vocal loading, respectively. Vocal fold dynamics were extracted and visualized by PVGs. The characteristic PVG patterns were extracted representing vocal fold vibration types. The parameter values were then analyzed by statistics regarding vocal load, left-right PVG asymmetries, anterior-posterior PVG asymmetries, and opening-closing differences. For the first time, the direct impact of vocal load could be determined by analyzing vocal fold dynamics. For same vocal loading conditions, equal dynamical behavior of the vocal folds were confirmed. Comparison of recordings performed in the morning with the recordings after work revealed significant changes in vibration behavior, indicating impact of occurring vocal load. Left-right asymmetries in vocal fold dynamics were found confirming earlier assumptions. Different dynamics between opening and closing procedure as well as for anterior and posterior parts were found. Constant voice usage stresses the vocal folds even in healthy subjects and can be detected by applying the PVG technique. Furthermore, left-right PVG asymmetries do occur in healthy voice to a certain extent. HSI in combination with PVG analysis seems to be a promising tool for investigation of vocal fold fatigue and pathologies resulting in small forms of dynamical changes.

Modulation of steady state functional connectivity in the default mode and working memory networks by cognitive load.

PubMed

Newton, Allen T; Morgan, Victoria L; Rogers, Baxter P; Gore, John C

2011-10-01

Interregional correlations between blood oxygen level dependent (BOLD) magnetic resonance imaging (fMRI) signals in the resting state have been interpreted as measures of connectivity across the brain. Here we investigate whether such connectivity in the working memory and default mode networks is modulated by changes in cognitive load. Functional connectivity was measured in a steady-state verbal identity N-back task for three different conditions (N = 1, 2, and 3) as well as in the resting state. We found that as cognitive load increases, the functional connectivity within both the working memory the default mode network increases. To test whether functional connectivity between the working memory and the default mode networks changed, we constructed maps of functional connectivity to the working memory network as a whole and found that increasingly negative correlations emerged in a dorsal region of the posterior cingulate cortex. These results provide further evidence that low frequency fluctuations in BOLD signals reflect variations in neural activity and suggests interaction between the default mode network and other cognitive networks. Copyright © 2010 Wiley-Liss, Inc.

ATLAS WORLD-cloud and networking in PanDA

NASA Astrophysics Data System (ADS)

Barreiro Megino, F.; De, K.; Di Girolamo, A.; Maeno, T.; Walker, R.; ATLAS Collaboration

2017-10-01

The ATLAS computing model was originally designed as static clouds (usually national or geographical groupings of sites) around the Tier 1 centres, which confined tasks and most of the data traffic. Since those early days, the sites’ network bandwidth has increased at 0(1000) and the difference in functionalities between Tier 1s and Tier 2s has reduced. After years of manual, intermediate solutions, we have now ramped up to full usage of World-cloud, the latest step in the PanDA Workload Management System to increase resource utilization on the ATLAS Grid, for all workflows (MC production, data (re)processing, etc.). We have based the development on two new site concepts. Nuclei sites are the Tier 1s and large Tier 2s, where tasks will be assigned and the output aggregated, and satellites are the sites that will execute the jobs and send the output to their nucleus. PanDA dynamically pairs nuclei and satellite sites for each task based on the input data availability, capability matching, site load and network connectivity. This contribution will introduce the conceptual changes for World-cloud, the development necessary in PanDA, an insight into the network model and the first half-year of operational experience.

Fuzzy Logic Control Based QoS Management in Wireless Sensor/Actuator Networks

PubMed Central

Xia, Feng; Zhao, Wenhong; Sun, Youxian; Tian, Yu-Chu

2007-01-01

Wireless sensor/actuator networks (WSANs) are emerging rapidly as a new generation of sensor networks. Despite intensive research in wireless sensor networks (WSNs), limited work has been found in the open literature in the field of WSANs. In particular, quality-of-service (QoS) management in WSANs remains an important issue yet to be investigated. As an attempt in this direction, this paper develops a fuzzy logic control based QoS management (FLC-QM) scheme for WSANs with constrained resources and in dynamic and unpredictable environments. Taking advantage of the feedback control technology, this scheme deals with the impact of unpredictable changes in traffic load on the QoS of WSANs. It utilizes a fuzzy logic controller inside each source sensor node to adapt sampling period to the deadline miss ratio associated with data transmission from the sensor to the actuator. The deadline miss ratio is maintained at a pre-determined desired level so that the required QoS can be achieved. The FLC-QM has the advantages of generality, scalability, and simplicity. Simulation results show that the FLC-QM can provide WSANs with QoS support. PMID:28903288

Agent Collaborative Target Localization and Classification in Wireless Sensor Networks

PubMed Central

Wang, Xue; Bi, Dao-wei; Ding, Liang; Wang, Sheng

2007-01-01

Wireless sensor networks (WSNs) are autonomous networks that have been frequently deployed to collaboratively perform target localization and classification tasks. Their autonomous and collaborative features resemble the characteristics of agents. Such similarities inspire the development of heterogeneous agent architecture for WSN in this paper. The proposed agent architecture views WSN as multi-agent systems and mobile agents are employed to reduce in-network communication. According to the architecture, an energy based acoustic localization algorithm is proposed. In localization, estimate of target location is obtained by steepest descent search. The search algorithm adapts to measurement environments by dynamically adjusting its termination condition. With the agent architecture, target classification is accomplished by distributed support vector machine (SVM). Mobile agents are employed for feature extraction and distributed SVM learning to reduce communication load. Desirable learning performance is guaranteed by combining support vectors and convex hull vectors. Fusion algorithms are designed to merge SVM classification decisions made from various modalities. Real world experiments with MICAz sensor nodes are conducted for vehicle localization and classification. Experimental results show the proposed agent architecture remarkably facilitates WSN designs and algorithm implementation. The localization and classification algorithms also prove to be accurate and energy efficient.

Organization of the secure distributed computing based on multi-agent system

NASA Astrophysics Data System (ADS)

Khovanskov, Sergey; Rumyantsev, Konstantin; Khovanskova, Vera

2018-04-01

Nowadays developing methods for distributed computing is received much attention. One of the methods of distributed computing is using of multi-agent systems. The organization of distributed computing based on the conventional network computers can experience security threats performed by computational processes. Authors have developed the unified agent algorithm of control system of computing network nodes operation. Network PCs is used as computing nodes. The proposed multi-agent control system for the implementation of distributed computing allows in a short time to organize using of the processing power of computers any existing network to solve large-task by creating a distributed computing. Agents based on a computer network can: configure a distributed computing system; to distribute the computational load among computers operated agents; perform optimization distributed computing system according to the computing power of computers on the network. The number of computers connected to the network can be increased by connecting computers to the new computer system, which leads to an increase in overall processing power. Adding multi-agent system in the central agent increases the security of distributed computing. This organization of the distributed computing system reduces the problem solving time and increase fault tolerance (vitality) of computing processes in a changing computing environment (dynamic change of the number of computers on the network). Developed a multi-agent system detects cases of falsification of the results of a distributed system, which may lead to wrong decisions. In addition, the system checks and corrects wrong results.

Advanced Polymer Network Structures

DTIC Science & Technology

2016-02-01

double networks in a single step was identified from coarse-grained molecular dynamics simulations of polymer solvents bearing rigid side chains dissolved...in a polymer network. Coarse-grained molecular dynamics simulations also explored the mechanical behavior of traditional double networks and...DRI), polymer networks, polymer gels, molecular dynamics simulations , double networks 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF

Dynamic Trust Management for Mobile Networks and Its Applications

ERIC Educational Resources Information Center

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…

State space modeling of time-varying contemporaneous and lagged relations in connectivity maps.

PubMed

Molenaar, Peter C M; Beltz, Adriene M; Gates, Kathleen M; Wilson, Stephen J

2016-01-15

Most connectivity mapping techniques for neuroimaging data assume stationarity (i.e., network parameters are constant across time), but this assumption does not always hold true. The authors provide a description of a new approach for simultaneously detecting time-varying (or dynamic) contemporaneous and lagged relations in brain connectivity maps. Specifically, they use a novel raw data likelihood estimation technique (involving a second-order extended Kalman filter/smoother embedded in a nonlinear optimizer) to determine the variances of the random walks associated with state space model parameters and their autoregressive components. The authors illustrate their approach with simulated and blood oxygen level-dependent functional magnetic resonance imaging data from 30 daily cigarette smokers performing a verbal working memory task, focusing on seven regions of interest (ROIs). Twelve participants had dynamic directed functional connectivity maps: Eleven had one or more time-varying contemporaneous ROI state loadings, and one had a time-varying autoregressive parameter. Compared to smokers without dynamic maps, smokers with dynamic maps performed the task with greater accuracy. Thus, accurate detection of dynamic brain processes is meaningfully related to behavior in a clinical sample. Published by Elsevier Inc.

Soft tissue deformation modelling through neural dynamics-based reaction-diffusion mechanics.

PubMed

Zhang, Jinao; Zhong, Yongmin; Gu, Chengfan

2018-05-30

Soft tissue deformation modelling forms the basis of development of surgical simulation, surgical planning and robotic-assisted minimally invasive surgery. This paper presents a new methodology for modelling of soft tissue deformation based on reaction-diffusion mechanics via neural dynamics. The potential energy stored in soft tissues due to a mechanical load to deform tissues away from their rest state is treated as the equivalent transmembrane potential energy, and it is distributed in the tissue masses in the manner of reaction-diffusion propagation of nonlinear electrical waves. The reaction-diffusion propagation of mechanical potential energy and nonrigid mechanics of motion are combined to model soft tissue deformation and its dynamics, both of which are further formulated as the dynamics of cellular neural networks to achieve real-time computational performance. The proposed methodology is implemented with a haptic device for interactive soft tissue deformation with force feedback. Experimental results demonstrate that the proposed methodology exhibits nonlinear force-displacement relationship for nonlinear soft tissue deformation. Homogeneous, anisotropic and heterogeneous soft tissue material properties can be modelled through the inherent physical properties of mass points. Graphical abstract Soft tissue deformation modelling with haptic feedback via neural dynamics-based reaction-diffusion mechanics.

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

PubMed Central

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

Bidirectional multi-optical line terminals incorporated converged WSN-PON network using M/M/1 queuing

NASA Astrophysics Data System (ADS)

Kumar, Love; Sharma, Vishal; Singh, Amarpal

2017-12-01

Wireless Sensor Networks (WSNs) have an assortment of application areas, for instance, civil, military, and video surveillance with restricted power resources and transmission link. To accommodate the massive traffic load in hefty sensor networks is another key issue. Subsequently, there is a necessity to backhaul the sensed information of such networks and prolong the transmission link to access the distinct receivers. Passive Optical Network (PON), a next-generation access technology, comes out as a suitable candidate for the convergence of the sensed data to the core system. The earlier demonstrated work with single-OLT-PON introduces an overloaded buffer akin to video surveillance scenarios. In this paper, to combine the bandwidth potential of PONs with the mobility capability of WSNs, the viability for the convergence of PONs and WSNs incorporating multi-optical line terminals is demonstrated to handle the overloaded OLTs. The existing M/M/1 queue theory with interleaving polling with adaptive cycle time as dynamic bandwidth algorithm is used to shun the probability of packets clash. Further, the proposed multi-sink WSN and multi-OLT PON converged structure is investigated in bidirectional mode analytically and through computer simulations. The observations establish the proposed structure competent to accommodate the colossal data traffic through less time consumption.

Load capacity improvements in nucleic acid based systems using partially open feedback control.

PubMed

Kulkarni, Vishwesh; Kharisov, Evgeny; Hovakimyan, Naira; Kim, Jongmin

2014-08-15

Synthetic biology is facilitating novel methods and components to build in vivo and in vitro circuits to better understand and re-engineer biological networks. Recently, Kim and Winfree have synthesized a remarkably elegant network of transcriptional oscillators in vitro using a modular architecture of synthetic gene analogues and a few enzymes that, in turn, could be used to drive a variety of downstream circuits and nanodevices. However, these oscillators are sensitive to initial conditions and downstream load processes. Furthermore, the oscillations are not sustained since the inherently closed design suffers from enzyme deactivation, NTP fuel exhaustion, and waste product build up. In this paper, we show that a partially open architecture in which an [Symbol: see text]1 adaptive controller, implemented inside an in silico computer that resides outside the wet-lab apparatus, can ensure sustained tunable oscillations in two specific designs of the Kim-Winfree oscillator networks. We consider two broad cases of operation: (1) the oscillator network operating in isolation and (2) the oscillator network driving a DNA tweezer subject to a variable load. In both scenarios, our simulation results show a significant improvement in the tunability and robustness of these oscillator networks. Our approach can be easily adopted to improve the loading capacity of a wide range of synthetic biological devices.

Dynamic augmentation restores anterior tibial translation in ACL suture repair: a biomechanical comparison of non-, static and dynamic augmentation techniques.

PubMed

Hoogeslag, Roy A G; Brouwer, Reinoud W; Huis In 't Veld, Rianne; Stephen, Joanna M; Amis, Andrew A

2018-02-03

There is a lack of objective evidence investigating how previous non-augmented ACL suture repair techniques and contemporary augmentation techniques in ACL suture repair restrain anterior tibial translation (ATT) across the arc of flexion, and after cyclic loading of the knee. The purpose of this work was to test the null hypotheses that there would be no statistically significant difference in ATT after non-, static- and dynamic-augmented ACL suture repair, and they will not restore ATT to normal values across the arc of flexion of the knee after cyclic loading. Eleven human cadaveric knees were mounted in a test rig, and knee kinematics from 0° to 90° of flexion were recorded by use of an optical tracking system. Measurements were recorded without load and with 89-N tibial anterior force. The knees were tested in the following states: ACL-intact, ACL-deficient, non-augmented suture repair, static tape augmentation and dynamic augmentation after 10 and 300 loading cycles. Only static tape augmentation and dynamic augmentation restored ATT to values similar to the ACL-intact state directly postoperation, and maintained this after cyclic loading. However, contrary to dynamic augmentation, the ATT after static tape augmentation failed to remain statistically less than for the ACL-deficient state after cyclic loading. Moreover, after cyclic loading, ATT was significantly less with dynamic augmentation when compared to static tape augmentation. In contrast to non-augmented ACL suture repair and static tape augmentation, only dynamic augmentation resulted in restoration of ATT values similar to the ACL-intact knee and decreased ATT values when compared to the ACL-deficient knee immediately post-operation and also after cyclic loading, across the arc of flexion, thus allowing the null hypotheses to be rejected. This may assist healing of the ruptured ACL. Therefore, this study would support further clinical evaluation of dynamic augmentation of ACL repair.

An intelligent load shedding scheme using neural networks and neuro-fuzzy.

PubMed

Haidar, Ahmed M A; Mohamed, Azah; Al-Dabbagh, Majid; Hussain, Aini; Masoum, Mohammad

2009-12-01

Load shedding is some of the essential requirement for maintaining security of modern power systems, particularly in competitive energy markets. This paper proposes an intelligent scheme for fast and accurate load shedding using neural networks for predicting the possible loss of load at the early stage and neuro-fuzzy for determining the amount of load shed in order to avoid a cascading outage. A large scale electrical power system has been considered to validate the performance of the proposed technique in determining the amount of load shed. The proposed techniques can provide tools for improving the reliability and continuity of power supply. This was confirmed by the results obtained in this research of which sample results are given in this paper.

Detailed analysis of routing protocols with different network limitations

NASA Astrophysics Data System (ADS)

Masood, Mohsin; Abuhelala, Mohamed; Glesk, Ivan

2016-12-01

In network communication field, routing protocols have got a significant role which are not only used in networks to handle the user data but also to monitor the different network environments. Dynamic routing protocols such as OSPF, EIGRP and RIP are used for forwarding user data to its destination by instantly detecting the dynamic changes across the network. The dynamic changes in the network can be in the form of topological changes, congestions, links failure etc. Therefore, it becomes a challenge to develop and implement dynamic routing protocols that fulfills the network requirements. Hence, each routing protocol has its own characteristics such as convergence activity, routing metric, routing table etc. and will perform differently in various network environments. This paper presents a comprehensive study of static and dynamic routing, along with dynamic routing protocols. Experiments that are conducted under various network limitations are presented using the OPNET tool. The performance of each of dynamic routing protocols are monitored and explained in the form of simulated results using network parameters. The results are analyzed, in order to provide a clear understanding of each protocol performance for the selection of the proper protocol for a given network environment.

Dynamic Loading and Characterization of Fiber-Reinforced Composites

NASA Astrophysics Data System (ADS)

Sierakowski, Robert L.; Chaturvedi, Shive K.

1997-02-01

Emphasizing polymer based fiber-reinforced composites, this book is designed to provide readers with a significant understanding of the complexities involved in characterizing dynamic events and the corresponding response of advanced fiber composite materials and structures. These elements include dynamic loading devices, material properties characterization, analytical and experimental techniques to assess the damage and failure modes associated with various dynamic loading events. Concluding remarks are presented throughout the text which summarize key points and raise issues related to important research needed.

Elastomeric optical fiber sensors and method for detecting and measuring events occurring in elastic materials

DOEpatents

Muhs, Jeffrey D.; Capps, Gary J.; Smith, David B.; White, Clifford P.

1994-01-01

Fiber optic sensing means for the detection and measurement of events such as dynamic loadings imposed upon elastic materials including cementitious materials, elastomers, and animal body components and/or the attrition of such elastic materials are provided. One or more optical fibers each having a deformable core and cladding formed of an elastomeric material such as silicone rubber are embedded in the elastic material. Changes in light transmission through any of the optical fibers due the deformation of the optical fiber by the application of dynamic loads such as compression, tension, or bending loadings imposed on the elastic material or by the attrition of the elastic material such as by cracking, deterioration, aggregate break-up, and muscle, tendon, or organ atrophy provide a measurement of the dynamic loadings and attrition. The fiber optic sensors can be embedded in elastomers subject to dynamic loadings and attrition such as commonly used automobiles and in shoes for determining the amount and frequency of the dynamic loadings and the extent of attrition. The fiber optic sensors are also useable in cementitious material for determining the maturation thereof.

A clustering-based fuzzy wavelet neural network model for short-term load forecasting.

PubMed

Kodogiannis, Vassilis S; Amina, Mahdi; Petrounias, Ilias

2013-10-01

Load forecasting is a critical element of power system operation, involving prediction of the future level of demand to serve as the basis for supply and demand planning. This paper presents the development of a novel clustering-based fuzzy wavelet neural network (CB-FWNN) model and validates its prediction on the short-term electric load forecasting of the Power System of the Greek Island of Crete. The proposed model is obtained from the traditional Takagi-Sugeno-Kang fuzzy system by replacing the THEN part of fuzzy rules with a "multiplication" wavelet neural network (MWNN). Multidimensional Gaussian type of activation functions have been used in the IF part of the fuzzyrules. A Fuzzy Subtractive Clustering scheme is employed as a pre-processing technique to find out the initial set and adequate number of clusters and ultimately the number of multiplication nodes in MWNN, while Gaussian Mixture Models with the Expectation Maximization algorithm are utilized for the definition of the multidimensional Gaussians. The results corresponding to the minimum and maximum power load indicate that the proposed load forecasting model provides significantly accurate forecasts, compared to conventional neural networks models.

Optimal Objective-Based Experimental Design for Uncertain Dynamical Gene Networks with Experimental Error.

PubMed

Mohsenizadeh, Daniel N; Dehghannasiri, Roozbeh; Dougherty, Edward R

2018-01-01

In systems biology, network models are often used to study interactions among cellular components, a salient aim being to develop drugs and therapeutic mechanisms to change the dynamical behavior of the network to avoid undesirable phenotypes. Owing to limited knowledge, model uncertainty is commonplace and network dynamics can be updated in different ways, thereby giving multiple dynamic trajectories, that is, dynamics uncertainty. In this manuscript, we propose an experimental design method that can effectively reduce the dynamics uncertainty and improve performance in an interaction-based network. Both dynamics uncertainty and experimental error are quantified with respect to the modeling objective, herein, therapeutic intervention. The aim of experimental design is to select among a set of candidate experiments the experiment whose outcome, when applied to the network model, maximally reduces the dynamics uncertainty pertinent to the intervention objective.

Dynamic characteristics and simplified numerical methods of an all-vertical-piled wharf in offshore deep water

NASA Astrophysics Data System (ADS)

Zhang, Hua-qing; Sun, Xi-ping; Wang, Yuan-zhan; Yin, Ji-long; Wang, Chao-yang

2015-10-01

There has been a growing trend in the development of offshore deep-water ports in China. For such deep sea projects, all-vertical-piled wharves are suitable structures and generally located in open waters, greatly affected by wave action. Currently, no systematic studies or simplified numerical methods are available for deriving the dynamic characteristics and dynamic responses of all-vertical-piled wharves under wave cyclic loads. In this article, we compare the dynamic characteristics of an all-vertical-piled wharf with those of a traditional inshore high-piled wharf through numerical analysis; our research reveals that the vibration period of an all-vertical-piled wharf under cyclic loading is longer than that of an inshore high-piled wharf and is much closer to the period of the loading wave. Therefore, dynamic calculation and analysis should be conducted when designing and calculating the characteristics of an all-vertical-piled wharf. We establish a dynamic finite element model to examine the dynamic response of an all-vertical-piled wharf under wave cyclic loads and compare the results with those under wave equivalent static load; the comparison indicates that dynamic amplification of the structure is evident when the wave dynamic load effect is taken into account. Furthermore, a simplified dynamic numerical method for calculating the dynamic response of an all-vertical-piled wharf is established based on the P-Y curve. Compared with finite element analysis, the simplified method is more convenient to use and applicable to large structural deformation while considering the soil non-linearity. We confirmed that the simplified method has acceptable accuracy and can be used in engineering applications.

Assessment of dynamic effects on aircraft design loads: The landing impact case

NASA Astrophysics Data System (ADS)

Bronstein, Michael; Feldman, Esther; Vescovini, Riccardo; Bisagni, Chiara

2015-10-01

This paper addresses the potential benefits due to a fully dynamic approach to determine the design loads of a mid-size business jet. The study is conducted by considering the fuselage midsection of the DAEDALOS aircraft model with landing impact conditions. The comparison is presented in terms of stress levels between the novel dynamic approach and the standard design practice based on the use of equivalent static loads. The results illustrate that a slight reduction of the load levels can be achieved, but careful modeling of the damping level is needed. Guidelines for an improved load definition are discussed, and suggestions for future research activities are provided.

Functional connectivity and information flow of the respiratory neural network in chronic obstructive pulmonary disease.

PubMed

Yu, Lianchun; De Mazancourt, Marine; Hess, Agathe; Ashadi, Fakhrul R; Klein, Isabelle; Mal, Hervé; Courbage, Maurice; Mangin, Laurence

2016-08-01

Breathing involves a complex interplay between the brainstem automatic network and cortical voluntary command. How these brain regions communicate at rest or during inspiratory loading is unknown. This issue is crucial for several reasons: (i) increased respiratory loading is a major feature of several respiratory diseases, (ii) failure of the voluntary motor and cortical sensory processing drives is among the mechanisms that precede acute respiratory failure, (iii) several cerebral structures involved in responding to inspiratory loading participate in the perception of dyspnea, a distressing symptom in many disease. We studied functional connectivity and Granger causality of the respiratory network in controls and patients with chronic obstructive pulmonary disease (COPD), at rest and during inspiratory loading. Compared with those of controls, the motor cortex area of patients exhibited decreased connectivity with their contralateral counterparts and no connectivity with the brainstem. In the patients, the information flow was reversed at rest with the source of the network shifted from the medulla towards the motor cortex. During inspiratory loading, the system was overwhelmed and the motor cortex became the sink of the network. This major finding may help to understand why some patients with COPD are prone to acute respiratory failure. Network connectivity and causality were related to lung function and illness severity. We validated our connectivity and causality results with a mathematical model of neural network. Our findings suggest a new therapeutic strategy involving the modulation of brain activity to increase motor cortex functional connectivity and improve respiratory muscles performance in patients. Hum Brain Mapp 37:2736-2754, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Malaligned dynamic anterior cervical plate: a biomechanical analysis of effectiveness.

PubMed

Lawrence, Brandon D; Patel, Alpesh A; Guss, Andrew; Ryan Spiker, W; Brodke, Darrel S

2014-12-01

Biomechanical evaluation. To evaluate the kinematic and load-sharing differences of dynamic anterior cervical plates when placed in-line at 0° and off-axis at 20°. The use of dynamic anterior cervical plating systems has recently gained popularity due to the theoretical benefit of improved load sharing with graft subsidence. Occasionally, due to anatomical restraints, the anterior cervical plate may be placed off-axis in the coronal plane. This may potentially decrease the dynamization capability of the plate, leading to less load sharing and potentially decreased fusion rates. The purpose of this study was to comprehensively evaluate the kinematic and load-sharing differences of a dynamic plate placed in-line versus off-axis in the coronal plane. Thirteen fresh-frozen human cadaveric cervical spines (C2-T1) were used. Nondestructive range-of-motion testing was performed with a pneumatically controlled spine simulator in flexion/extension, lateral bending, and axial rotation using the OptoTrak motion measurement system. A C5 corpectomy was performed, and a custom interbody spacer with an integrated load cell collected load-sharing data under axial compression at varying loads. A dynamic anterior cervical plate was placed in-line at 0° and then off-axis at 20°. Testing conditions ensued using a full-length spacer, followed by simulated subsidence by removing 10% of the height of the original spacer. There were no kinematic differences noted in the in-line model versus the off-axis model. After simulated subsidence, the small decreases in stiffness and increases in motion were similar whether the plate was placed in-line or off-axis in all 3 planes of motion. There were also no significant differences in the load-sharing characteristics of the in-line plate versus the off-axis plate in either the full-length model or the subsided interbody model. This study suggests that off-axis dynamic plate positioning does not significantly impact construct kinematics or graft load sharing. As such, we do not recommend removal or repositioning of an off-axis placed dynamic plate because the kinematic and load-sharing biomechanical properties are similar. N/A.

Remotely Triggered Earthquakes Recorded by EarthScope's Transportable Array and Regional Seismic Networks: A Case Study Of Four Large Earthquakes

NASA Astrophysics Data System (ADS)

Velasco, A. A.; Cerda, I.; Linville, L.; Kilb, D. L.; Pankow, K. L.

2013-05-01

Changes in field stress required to trigger earthquakes have been classified in two basic ways: static and dynamic triggering. Static triggering occurs when an earthquake that releases accumulated strain along a fault stress loads a nearby fault. Dynamic triggering occurs when an earthquake is induced by the passing of seismic waves from a large mainshock located at least two or more fault lengths from the epicenter of the main shock. We investigate details of dynamic triggering using data collected from EarthScope's USArray and regional seismic networks located in the United States. Triggered events are identified using an optimized automated detector based on the ratio of short term to long term average (Antelope software). Following the automated processing, the flagged waveforms are individually analyzed, in both the time and frequency domains, to determine if the increased detection rates correspond to local earthquakes (i.e., potentially remotely triggered aftershocks). Here, we show results using this automated schema applied to data from four large, but characteristically different, earthquakes -- Chile (Mw 8.8 2010), Tokoku-Oki (Mw 9.0 2011), Baja California (Mw 7.2 2010) and Wells Nevada (Mw 6.0 2008). For each of our four mainshocks, the number of detections within the 10 hour time windows span a large range (1 to over 200) and statistically >20% of the waveforms show evidence of anomalous signals following the mainshock. The results will help provide for a better understanding of the physical mechanisms involved in dynamic earthquake triggering and will help identify zones in the continental U.S. that may be more susceptible to dynamic earthquake triggering.

Dynamic neural networks based on-line identification and control of high performance motor drives

NASA Technical Reports Server (NTRS)

Rubaai, Ahmed; Kotaru, Raj

1995-01-01

In the automated and high-tech industries of the future, there wil be a need for high performance motor drives both in the low-power range and in the high-power range. To meet very straight demands of tracking and regulation in the two quadrants of operation, advanced control technologies are of a considerable interest and need to be developed. In response a dynamics learning control architecture is developed with simultaneous on-line identification and control. the feature of the proposed approach, to efficiently combine the dual task of system identification (learning) and adaptive control of nonlinear motor drives into a single operation is presented. This approach, therefore, not only adapts to uncertainties of the dynamic parameters of the motor drives but also learns about their inherent nonlinearities. In fact, most of the neural networks based adaptive control approaches in use have an identification phase entirely separate from the control phase. Because these approaches separate the identification and control modes, it is not possible to cope with dynamic changes in a controlled process. Extensive simulation studies have been conducted and good performance was observed. The robustness characteristics of neuro-controllers to perform efficiently in a noisy environment is also demonstrated. With this initial success, the principal investigator believes that the proposed approach with the suggested neural structure can be used successfully for the control of high performance motor drives. Two identification and control topologies based on the model reference adaptive control technique are used in this present analysis. No prior knowledge of load dynamics is assumed in either topology while the second topology also assumes no knowledge of the motor parameters.

Global phenomena from local rules: Peer-to-peer networks and crystal steps

NASA Astrophysics Data System (ADS)

Finkbiner, Amy

Even simple, deterministic rules can generate interesting behavior in dynamical systems. This dissertation examines some real world systems for which fairly simple, locally defined rules yield useful or interesting properties in the system as a whole. In particular, we study routing in peer-to-peer networks and the motion of crystal steps. Peers can vary by three orders of magnitude in their capacities to process network traffic. This heterogeneity inspires our use of "proportionate load balancing," where each peer provides resources in proportion to its individual capacity. We provide an implementation that employs small, local adjustments to bring the entire network into a global balance. Analytically and through simulations, we demonstrate the effectiveness of proportionate load balancing on two routing methods for de Bruijn graphs, introducing a new "reversed" routing method which performs better than standard forward routing in some cases. The prevalence of peer-to-peer applications prompts companies to locate the hosts participating in these networks. We explore the use of supervised machine learning to identify peer-to-peer hosts, without using application-specific information. We introduce a model for "triples," which exploits information about nearly contemporaneous flows to give a statistical picture of a host's activities. We find that triples, together with measurements of inbound vs. outbound traffic, can capture most of the behavior of peer-to-peer hosts. An understanding of crystal surface evolution is important for the development of modern nanoscale electronic devices. The most commonly studied surface features are steps, which form at low temperatures when the crystal is cut close to a plane of symmetry. Step bunching, when steps arrange into widely separated clusters of tightly packed steps, is one important step phenomenon. We analyze a discrete model for crystal steps, in which the motion of each step depends on the two steps on either side of it. We find an time-dependence term for the motion that does not appear in continuum models, and we determine an explicit dependence on step number.

Environmentally Friendly Solution to Ground Hazards in Design of Bridges in Earthquake Prone Areas Using Timber Piles

NASA Astrophysics Data System (ADS)

Sadeghi, H.

2015-12-01

Bridges are major elements of infrastructure in all societies. Their safety and continued serviceability guaranties the transportation and emergency access in urban and rural areas. However, these important structures are subject to earthquake induced damages in structure and foundations. The basic approach to the proper support of foundations are a) distribution of imposed loads to foundation in a way they can resist those loads without excessive settlement and failure; b) modification of foundation ground with various available methods; and c) combination of "a" and "b". The engineers has to face the task of designing the foundations meeting all safely and serviceability criteria but sometimes when there are numerous environmental and financial constrains, the use of some traditional methods become inevitable. This paper explains the application of timber piles to improve ground resistance to liquefaction and to secure the abutments of short to medium length bridges in an earthquake/liquefaction prone area in Bohol Island, Philippines. The limitations of using the common ground improvement methods (i.e., injection, dynamic compaction) because of either environmental or financial concerns along with the abundance of timber in the area made the engineers to use a network of timber piles behind the backwalls of the bridge abutments. The suggested timber pile network is simulated by numerical methods and its safety is examined. The results show that the compaction caused by driving of the piles and bearing capacity provided by timbers reduce the settlement and lateral movements due to service and earthquake induced loads.

Organization of excitable dynamics in hierarchical biological networks.

PubMed

Müller-Linow, Mark; Hilgetag, Claus C; Hütt, Marc-Thorsten

2008-09-26

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.

Residential load and rooftop PV generation: an Australian distribution network dataset

NASA Astrophysics Data System (ADS)

Ratnam, Elizabeth L.; Weller, Steven R.; Kellett, Christopher M.; Murray, Alan T.

2017-09-01

Despite the rapid uptake of small-scale solar photovoltaic (PV) systems in recent years, public availability of generation and load data at the household level remains very limited. Moreover, such data are typically measured using bi-directional meters recording only PV generation in excess of residential load rather than recording generation and load separately. In this paper, we report a publicly available dataset consisting of load and rooftop PV generation for 300 de-identified residential customers in an Australian distribution network, with load centres covering metropolitan Sydney and surrounding regional areas. The dataset spans a 3-year period, with separately reported measurements of load and PV generation at 30-min intervals. Following a detailed description of the dataset, we identify several means by which anomalous records (e.g. due to inverter failure) are identified and excised. With the resulting 'clean' dataset, we identify key customer-specific and aggregated characteristics of rooftop PV generation and residential load.

Influence of Bulk PDMS Network Properties on Water Wettability

NASA Astrophysics Data System (ADS)

Melillo, Matthew; Walker, Edwin; Klein, Zoe; Efimenko, Kirill; Genzer, Jan

Poly(dimethylsiloxane) (PDMS) is one of the most common elastomers, with applications ranging from sealants and marine antifouling coatings to absorbents for water treatment. Fundamental understanding of how liquids spread on the surface of and absorb into PDMS networks is of critical importance for the design and use of another application - medical devices. We have systematically studied the effects of polymer molecular weight, loading of tetra-functional crosslinker, and end-group chemical functionality on the mechanical and surface properties of end-linked PDMS networks. Wettability was investigated through the sessile drop technique, wherein a DI water droplet was placed on the bulk network surface and droplet volume, shape, surface area, and contact angle were monitored as a function of time. Various silicone substrates ranging from incredibly soft and flexible materials (E' 50 kPa) to highly rigid networks (E' 5 MPa) were tested. The dynamic behavior of the droplet on the surfaces demonstrated equilibration times between the droplet and surface on the order of 5 minutes. Similar trends were observed for the commercial PDMS material, Sylgard-184. Our results have provided new evidence for the strong influence that substrate modulus and molecular network structure have on the wettability of PDMS elastomers. These findings will aid in the design and implementation of efficient, accurate, and safe PDMS-based medical devices and microfluidic materials that involve aqueous media.

Dynamic Load Balancing for Adaptive Computations on Distributed-Memory Machines

NASA Technical Reports Server (NTRS)

1999-01-01

Dynamic load balancing is central to adaptive mesh-based computations on large-scale parallel computers. The principal investigator has investigated various issues on the dynamic load balancing problem under NASA JOVE and JAG rants. The major accomplishments of the project are two graph partitioning algorithms and a load balancing framework. The S-HARP dynamic graph partitioner is known to be the fastest among the known dynamic graph partitioners to date. It can partition a graph of over 100,000 vertices in 0.25 seconds on a 64- processor Cray T3E distributed-memory multiprocessor while maintaining the scalability of over 16-fold speedup. Other known and widely used dynamic graph partitioners take over a second or two while giving low scalability of a few fold speedup on 64 processors. These results have been published in journals and peer-reviewed flagship conferences.

Motor control goes beyond physics: differential effects of gravity and inertia on finger forces during manipulation of hand-held objects.

PubMed

Zatsiorsky, Vladimir M; Gao, Fan; Latash, Mark L

2005-04-01

According to basic physics, the local effects induced by gravity and acceleration are identical and cannot be separated by any physical experiment. In contrast-as this study shows-people adjust the grip forces associated with gravitational and inertial forces differently. In the experiment, subjects oscillated a vertically-oriented handle loaded with five different weights (from 3.8 N to 13.8 N) at three different frequencies in the vertical plane: 1 Hz, 1.5 Hz and 2.0 Hz. Three contributions to the grip force-static, dynamic, and stato-dynamic fractions-were quantified. The static fraction reflects grip force related to holding a load statically. The stato-dynamic fraction reflects a steady change in the grip force when the same load is moved cyclically. The dynamic fraction is due to acceleration-related adjustments of the grip force during oscillation cycles. The slope of the relation between the grip force and the load force was steeper for the static fraction than for the dynamic fraction. The stato-dynamic fraction increased with the frequency and load. The slope of the dynamic grip force-load force relation decreased with frequency, and as a rule, increased with the load. Hence, when adjusting grip force to task requirements, the central controller takes into account not only the expected magnitude of the load force but also such factors as whether the force is gravitational or inertial and the contributions of the object mass and acceleration to the inertial force. As an auxiliary finding, a complex finger coordination pattern aimed at preserving the rotational equilibrium of the object during shaking movements was reported.

Biomechanical performance of rigid compared to dynamic anterior cervical plating: analysis of adjacent upper and lower level compressive forces.

PubMed

Connor, David E; Shamieh, Khader Samer; Ogden, Alan L; Mukherjee, Debi P; Sin, Anthony; Nanda, Anil

2012-12-01

Dynamic anterior cervical plating is well established as a means of enhancing graft loading and subsequent arthrodesis. Current concerns center on the degree of adjacent-level stress induced by these systems. The aim of this study was to evaluate and compare the load transferred to adjacent levels for single-level anterior cervical discectomy and fusion utilizing rigid compared to dynamic anterior plating systems. Nine cadaveric adult human cervical spine specimens were subjected to range-of-motion testing prior to and following C5-C6 anterior cervical discectomy and fusion procedures. Interbody grafting was performed with human fibula tissue. Nondestructive biomechanical testing included flexion/extension and lateral bending loading modes. A constant displacement of 5mm was applied in each direction and the applied load was measured in newtons (N). Specimens were tested in the following order: intact, following discectomy, after rigid plating, then after dynamic plating. Adjacent level (C4-C5 [L(S)] and C6-C7 [L(I)]) compressive forces were measured using low profile load cells inserted into each disc space. The measured load values for plating systems were then normalized using values measured for the intact specimens. Mean loads transferred to L(S) and L(I) during forced flexion in specimens with rigid plating were 23.47 N and 8.76 N, respectively; while the corresponding values in specimens with dynamic plating were 18.55 N and 1.03 N, respectively. Dynamic plating yielded no significant change at L(I) and a 21.0% decrease in load at L(S) when compared with rigid plating, although the difference was not significant. The observed trend suggests that dynamic plating may diminish superior adjacent level compressive stresses. Copyright © 2012 Elsevier Ltd. All rights reserved.

Decreased Efficiency of Task-Positive and Task-Negative Networks During Working Memory in Schizophrenia

PubMed Central

Metzak, Paul D.; Riley, Jennifer D.; Wang, Liang; Whitman, Jennifer C.; Ngan, Elton T. C.; Woodward, Todd S.

2012-01-01

Working memory (WM) is one of the most impaired cognitive processes in schizophrenia. Functional magnetic resonance imaging (fMRI) studies in this area have typically found a reduction in information processing efficiency but have focused on the dorsolateral prefrontal cortex. In the current study using the Sternberg Item Recognition Test, we consider networks of regions supporting WM and measure the activation of functionally connected neural networks over different WM load conditions. We used constrained principal component analysis with a finite impulse response basis set to compare the estimated hemodynamic response associated with different WM load condition for 15 healthy control subjects and 15 schizophrenia patients. Three components emerged, reflecting activated (task-positive) and deactivated (task-negative or default-mode) neural networks. Two of the components (with both task-positive and task-negative aspects) were load dependent, were involved in encoding and delay phases (one exclusively encoding and the other both encoding and delay), and both showed evidence for decreased efficiency in patients. The results suggest that WM capacity is reached sooner for schizophrenia patients as the overt levels of WM load increase, to the point that further increases in overt memory load do not increase fMRI activation, and lead to performance impairments. These results are consistent with an account holding that patients show reduced efficiency in task-positive and task-negative networks during WM and also partially support the shifted inverted-U-shaped curve theory of the relationship between WM load and fMRI activation in schizophrenia. PMID:21224491

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

NASA Astrophysics Data System (ADS)

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.

On the relationship between the dynamic behavior and nanoscale staggered structure of the bone

NASA Astrophysics Data System (ADS)

Qwamizadeh, Mahan; Zhang, Zuoqi; Zhou, Kun; Zhang, Yong Wei

2015-05-01

Bone, a typical load-bearing biological material, composed of ordinary base materials such as organic protein and inorganic mineral arranged in a hierarchical architecture, exhibits extraordinary mechanical properties. Up to now, most of previous studies focused on its mechanical properties under static loading. However, failure of the bone occurs often under dynamic loading. An interesting question is: Are the structural sizes and layouts of the bone related or even adapted to the functionalities demanded by its dynamic performance? In the present work, systematic finite element analysis was performed on the dynamic response of nanoscale bone structures under dynamic loading. It was found that for a fixed mineral volume fraction and unit cell area, there exists a nanoscale staggered structure at some specific feature size and layout which exhibits the fastest attenuation of stress waves. Remarkably, these specific feature sizes and layouts are in excellent agreement with those experimentally observed in the bone at the same scale, indicating that the structural size and layout of the bone at the nanoscale are evolutionarily adapted to its dynamic behavior. The present work points out the importance of dynamic effect on the biological evolution of load-bearing biological materials.

Large-scale imaging of cortical network activity with calcium indicators.

PubMed

Ikegaya, Yuji; Le Bon-Jego, Morgane; Yuste, Rafael

2005-06-01

Bulk loading of calcium indicators has provided a unique opportunity to reconstruct the activity of cortical networks with single-cell resolution. Here we describe the detailed methods of bulk loading of AM dyes we developed and have been improving for imaging with a spinning disk confocal microscope.

Potential of dynamic spectrum allocation in LTE macro networks

NASA Astrophysics Data System (ADS)

Hoffmann, H.; Ramachandra, P.; Kovács, I. Z.; Jorguseski, L.; Gunnarsson, F.; Kürner, T.

2015-11-01

In recent years Mobile Network Operators (MNOs) worldwide are extensively deploying LTE networks in different spectrum bands and utilising different bandwidth configurations. Initially, the deployment is coverage oriented with macro cells using the lower LTE spectrum bands. As the offered traffic (i.e. the requested traffic from the users) increases the LTE deployment evolves with macro cells expanded with additional capacity boosting LTE carriers in higher frequency bands complemented with micro or small cells in traffic hotspot areas. For MNOs it is crucial to use the LTE spectrum assets, as well as the installed network infrastructure, in the most cost efficient way. The dynamic spectrum allocation (DSA) aims at (de)activating the available LTE frequency carriers according to the temporal and spatial traffic variations in order to increase the overall LTE system performance in terms of total network capacity by reducing the interference. This paper evaluates the DSA potential of achieving the envisaged performance improvement and identifying in which system and traffic conditions the DSA should be deployed. A self-optimised network (SON) DSA algorithm is also proposed and evaluated. The evaluations have been carried out in a hexagonal and a realistic site-specific urban macro layout assuming a central traffic hotspot area surrounded with an area of lower traffic with a total size of approximately 8 × 8 km2. The results show that up to 47 % and up to 40 % possible DSA gains are achievable with regards to the carried system load (i.e. used resources) for homogenous traffic distribution with hexagonal layout and for realistic site-specific urban macro layout, respectively. The SON DSA algorithm evaluation in a realistic site-specific urban macro cell deployment scenario including realistic non-uniform spatial traffic distribution shows insignificant cell throughput (i.e. served traffic) performance gains. Nevertheless, in the SON DSA investigations, a gain of up to 25 % has been observed when analysing the resource utilisation in the non-hotspot cells.

Dynamic Loading of Substation Distribution Transformers: An Application for use in a Production Grade Environment

NASA Astrophysics Data System (ADS)

Zhang, Ming

Recent trends in the electric power industry have led to more attention to optimal operation of power transformers. In a deregulated environment, optimal operation means minimizing the maintenance and extending the life of this critical and costly equipment for the purpose of maximizing profits. Optimal utilization of a transformer can be achieved through the use of dynamic loading. A benefit of dynamic loading is that it allows better utilization of the transformer capacity, thus increasing the flexibility and reliability of the power system. This document presents the progress on a software application which can estimate the maximum time-varying loading capability of transformers. This information can be used to load devices closer to their limits without exceeding the manufacturer specified operating limits. The maximally efficient dynamic loading of transformers requires a model that can accurately predict both top-oil temperatures (TOTs) and hottest-spot temperatures (HSTs). In the previous work, two kinds of thermal TOT and HST models have been studied and used in the application: the IEEE TOT/HST models and the ASU TOT/HST models. And, several metrics have been applied to evaluate the model acceptability and determine the most appropriate models for using in the dynamic loading calculations. In this work, an investigation to improve the existing transformer thermal models performance is presented. Some factors that may affect the model performance such as improper fan status and the error caused by the poor performance of IEEE models are discussed. Additional methods to determine the reliability of transformer thermal models using metrics such as time constant and the model parameters are also provided. A new production grade application for real-time dynamic loading operating purpose is introduced. This application is developed by using an existing planning application, TTeMP, as a start point, which is designed for the dispatchers and load specialists. To overcome the limitations of TTeMP, the new application can perform dynamic loading under emergency conditions, such as loss-of transformer loading. It also has the capability to determine the emergency rating of the transformers for a real-time estimation.

Real-time Mesoscale Visualization of Dynamic Damage and Reaction in Energetic Materials under Impact

NASA Astrophysics Data System (ADS)

Chen, Wayne; Harr, Michael; Kerschen, Nicholas; Maris, Jesus; Guo, Zherui; Parab, Niranjan; Sun, Tao; Fezzaa, Kamel; Son, Steven

Energetic materials may be subjected to impact and vibration loading. Under these dynamic loadings, local stress or strain concentrations may lead to the formation of hot spots and unintended reaction. To visualize the dynamic damage and reaction processes in polymer bonded energetic crystals under dynamic compressive loading, a high speed X-ray phase contrast imaging setup was synchronized with a Kolsky bar and a light gas gun. Controlled compressive loading was applied on PBX specimens with a single or multiple energetic crystal particles and impact-induced damage and reaction processes were captured using the high speed X-ray imaging setup. Impact velocities were systematically varied to explore the critical conditions for reaction. At lower loading rates, ultrasonic exercitations were also applied to progressively damage the crystals, eventually leading to reaction. AFOSR, ONR.

A Digitally Programmable Cytomorphic Chip for Simulation of Arbitrary Biochemical Reaction Networks.

PubMed

Woo, Sung Sik; Kim, Jaewook; Sarpeshkar, Rahul

2018-04-01

Prior work has shown that compact analog circuits can faithfully represent and model fundamental biomolecular circuits via efficient log-domain cytomorphic transistor equivalents. Such circuits have emphasized basis functions that are dominant in genetic transcription and translation networks and deoxyribonucleic acid (DNA)-protein binding. Here, we report a system featuring digitally programmable 0.35 μm BiCMOS analog cytomorphic chips that enable arbitrary biochemical reaction networks to be exactly represented thus enabling compact and easy composition of protein networks as well. Since all biomolecular networks can be represented as chemical reaction networks, our protein networks also include the former genetic network circuits as a special case. The cytomorphic analog protein circuits use one fundamental association-dissociation-degradation building-block circuit that can be configured digitally to exactly represent any zeroth-, first-, and second-order reaction including loading, dynamics, nonlinearity, and interactions with other building-block circuits. To address a divergence issue caused by random variations in chip fabrication processes, we propose a unique way of performing computation based on total variables and conservation laws, which we instantiate at both the circuit and network levels. Thus, scalable systems that operate with finite error over infinite time can be built. We show how the building-block circuits can be composed to form various network topologies, such as cascade, fan-out, fan-in, loop, dimerization, or arbitrary networks using total variables. We demonstrate results from a system that combines interacting cytomorphic chips to simulate a cancer pathway and a glycolysis pathway. Both simulations are consistent with conventional software simulations. Our highly parallel digitally programmable analog cytomorphic systems can lead to a useful design, analysis, and simulation tool for studying arbitrary large-scale biological networks in systems and synthetic biology.

Measurements and modelling of base station power consumption under real traffic loads.

PubMed

Lorincz, Josip; Garma, Tonko; Petrovic, Goran

2012-01-01

Base stations represent the main contributor to the energy consumption of a mobile cellular network. Since traffic load in mobile networks significantly varies during a working or weekend day, it is important to quantify the influence of these variations on the base station power consumption. Therefore, this paper investigates changes in the instantaneous power consumption of GSM (Global System for Mobile Communications) and UMTS (Universal Mobile Telecommunications System) base stations according to their respective traffic load. The real data in terms of the power consumption and traffic load have been obtained from continuous measurements performed on a fully operated base station site. Measurements show the existence of a direct relationship between base station traffic load and power consumption. According to this relationship, we develop a linear power consumption model for base stations of both technologies. This paper also gives an overview of the most important concepts which are being proposed to make cellular networks more energy-efficient.

Measurements and Modelling of Base Station Power Consumption under Real Traffic Loads †

PubMed Central

Lorincz, Josip; Garma, Tonko; Petrovic, Goran

2012-01-01

Base stations represent the main contributor to the energy consumption of a mobile cellular network. Since traffic load in mobile networks significantly varies during a working or weekend day, it is important to quantify the influence of these variations on the base station power consumption. Therefore, this paper investigates changes in the instantaneous power consumption of GSM (Global System for Mobile Communications) and UMTS (Universal Mobile Telecommunications System) base stations according to their respective traffic load. The real data in terms of the power consumption and traffic load have been obtained from continuous measurements performed on a fully operated base station site. Measurements show the existence of a direct relationship between base station traffic load and power consumption. According to this relationship, we develop a linear power consumption model for base stations of both technologies. This paper also gives an overview of the most important concepts which are being proposed to make cellular networks more energy-efficient. PMID:22666026

Evidence for social working memory from a parametric functional MRI study.

PubMed

Meyer, Meghan L; Spunt, Robert P; Berkman, Elliot T; Taylor, Shelley E; Lieberman, Matthew D

2012-02-07

Keeping track of various amounts of social cognitive information, including people's mental states, traits, and relationships, is fundamental to navigating social interactions. However, to date, no research has examined which brain regions support variable amounts of social information processing ("social load"). We developed a social working memory paradigm to examine the brain networks sensitive to social load. Two networks showed linear increases in activation as a function of increasing social load: the medial frontoparietal regions implicated in social cognition and the lateral frontoparietal system implicated in nonsocial forms of working memory. Of these networks, only load-dependent medial frontoparietal activity was associated with individual differences in social cognitive ability (trait perspective-taking). Although past studies of nonsocial load have uniformly found medial frontoparietal activity decreases with increasing task demands, the current study demonstrates these regions do support increasing mental effort when such effort engages social cognition. Implications for the etiology of clinical disorders that implicate social functioning and potential interventions are discussed.

A dynamic distention protocol for whole-organ bladder decellularization: histological and biomechanical characterization of the acellular matrix.

PubMed

Consolo, F; Brizzola, S; Tremolada, G; Grieco, V; Riva, F; Acocella, F; Fiore, G B; Soncini, M

2016-02-01

A combined physical-chemical protocol for whole full-thickness bladder decellularization is proposed, based on organ cyclic distention through repeated infusion/withdrawal of the decellularization agents through the urethra. The dynamic decellularization was intended to enhance cell removal efficiency, facilitating the delivery of detergents within the inner layers of the tissue and the removal of cell debris. The use of mild chemical detergents (hypotonic solution and non-ionic detergent) was employed to limit adverse effects upon matrix 3D ultrastructure. Inspection of the presence of residual DNA and RNA was carried out on decellularized matrices to verify effective cell removal. Histological investigation was focused on assessing the retention of adequate structural and functional components that regulate the biomechanical behaviour of the acellular tissue. Biomechanical properties were evaluated through uniaxial tensile loading tests of tissue strips and through ex vivo filling cystometry to evaluate the whole-organ mechanical response to a physiological-like loading state. According to our results, a dynamic decellularization protocol of 17 h duration with a 5 ml/min detergent infusion flow rate revealed higher DNA removal efficiency than standard static decellularization, resulting in residual DNA content < 50 ng/mg dry tissue weight. Furthermore, the collagen network and elastic fibres distribution were preserved in the acellular ECM, which exhibited suitable biomechanical properties in the perspective of its future use as an implant for bladder augmentation. Copyright © 2013 John Wiley & Sons, Ltd.

Novel flat datacenter network architecture based on scalable and flow-controlled optical switch system.

PubMed

Miao, Wang; Luo, Jun; Di Lucente, Stefano; Dorren, Harm; Calabretta, Nicola

2014-02-10

We propose and demonstrate an optical flat datacenter network based on scalable optical switch system with optical flow control. Modular structure with distributed control results in port-count independent optical switch reconfiguration time. RF tone in-band labeling technique allowing parallel processing of the label bits ensures the low latency operation regardless of the switch port-count. Hardware flow control is conducted at optical level by re-using the label wavelength without occupying extra bandwidth, space, and network resources which further improves the performance of latency within a simple structure. Dynamic switching including multicasting operation is validated for a 4 x 4 system. Error free operation of 40 Gb/s data packets has been achieved with only 1 dB penalty. The system could handle an input load up to 0.5 providing a packet loss lower that 10(-5) and an average latency less that 500 ns when a buffer size of 16 packets is employed. Investigation on scalability also indicates that the proposed system could potentially scale up to large port count with limited power penalty.

Multi-granularity Bandwidth Allocation for Large-Scale WDM/TDM PON

NASA Astrophysics Data System (ADS)

Gao, Ziyue; Gan, Chaoqin; Ni, Cuiping; Shi, Qiongling

2017-12-01

WDM (wavelength-division multiplexing)/TDM (time-division multiplexing) PON (passive optical network) is being viewed as a promising solution for delivering multiple services and applications, such as high-definition video, video conference and data traffic. Considering the real-time transmission, QoS (quality of services) requirements and differentiated services model, a multi-granularity dynamic bandwidth allocation (DBA) in both domains of wavelengths and time for large-scale hybrid WDM/TDM PON is proposed in this paper. The proposed scheme achieves load balance by using the bandwidth prediction. Based on the bandwidth prediction, the wavelength assignment can be realized fairly and effectively to satisfy the different demands of various classes. Specially, the allocation of residual bandwidth further augments the DBA and makes full use of bandwidth resources in the network. To further improve the network performance, two schemes named extending the cycle of one free wavelength (ECoFW) and large bandwidth shrinkage (LBS) are proposed, which can prevent transmission from interruption when the user employs more than one wavelength. The simulation results show the effectiveness of the proposed scheme.

Detection of complex cyber attacks

NASA Astrophysics Data System (ADS)

Gregorio-de Souza, Ian; Berk, Vincent H.; Giani, Annarita; Bakos, George; Bates, Marion; Cybenko, George; Madory, Doug

2006-05-01

One significant drawback to currently available security products is their inabilty to correlate diverse sensor input. For instance, by only using network intrusion detection data, a root kit installed through a weak username-password combination may go unnoticed. Similarly, an administrator may never make the link between deteriorating response times from the database server and an attacker exfiltrating trusted data, if these facts aren't presented together. Current Security Information Management Systems (SIMS) can collect and represent diverse data but lack sufficient correlation algorithms. By using a Process Query System, we were able to quickly bring together data flowing from many sources, including NIDS, HIDS, server logs, CPU load and memory usage, etc. We constructed PQS models that describe dynamic behavior of complicated attacks and failures, allowing us to detect and differentiate simultaneous sophisticated attacks on a target network. In this paper, we discuss the benefits of implementing such a multistage cyber attack detection system using PQS. We focus on how data from multiple sources can be combined and used to detect and track comprehensive network security events that go unnoticed using conventional tools.

Dynamic Mechanical Compression of Chondrocytes for Tissue Engineering: A Critical Review.

PubMed

Anderson, Devon E; Johnstone, Brian

2017-01-01

Articular cartilage functions to transmit and translate loads. In a classical structure-function relationship, the tissue resides in a dynamic mechanical environment that drives the formation of a highly organized tissue architecture suited to its biomechanical role. The dynamic mechanical environment includes multiaxial compressive and shear strains as well as hydrostatic and osmotic pressures. As the mechanical environment is known to modulate cell fate and influence tissue development toward a defined architecture in situ , dynamic mechanical loading has been hypothesized to induce the structure-function relationship during attempts at in vitro regeneration of articular cartilage. Researchers have designed increasingly sophisticated bioreactors with dynamic mechanical regimes, but the response of chondrocytes to dynamic compression and shear loading remains poorly characterized due to wide variation in study design, system variables, and outcome measurements. We assessed the literature pertaining to the use of dynamic compressive bioreactors for in vitro generation of cartilaginous tissue from primary and expanded chondrocytes. We used specific search terms to identify relevant publications from the PubMed database and manually sorted the data. It was very challenging to find consensus between studies because of species, age, cell source, and culture differences, coupled with the many loading regimes and the types of analyses used. Early studies that evaluated the response of primary bovine chondrocytes within hydrogels, and that employed dynamic single-axis compression with physiologic loading parameters, reported consistently favorable responses at the tissue level, with upregulation of biochemical synthesis and biomechanical properties. However, they rarely assessed the cellular response with gene expression or mechanotransduction pathway analyses. Later studies that employed increasingly sophisticated biomaterial-based systems, cells derived from different species, and complex loading regimes, did not necessarily corroborate prior positive results. These studies report positive results with respect to very specific conditions for cellular responses to dynamic load but fail to consistently achieve significant positive changes in relevant tissue engineering parameters, particularly collagen content and stiffness. There is a need for standardized methods and analyses of dynamic mechanical loading systems to guide the field of tissue engineering toward building cartilaginous implants that meet the goal of regenerating articular cartilage.

Dynamic Load Predictions for Launchers Using Extra-Large Eddy Simulations X-Les

NASA Astrophysics Data System (ADS)

Maseland, J. E. J.; Soemarwoto, B. I.; Kok, J. C.

2005-02-01

Flow-induced unsteady loads can have a strong impact on performance and flight characteristics of aerospace vehicles and therefore play a crucial role in their design and operation. Complementary to costly flight tests and delicate wind-tunnel experiments, unsteady loads can be calculated using time-accurate Computational Fluid Dynamics. A capability to accurately predict the dynamic loads on aerospace structures at flight Reynolds numbers can be of great value for the design and analysis of aerospace vehicles. Advanced space launchers are subject to dynamic loads in the base region during the ascent to space. In particular the engine and nozzle experience aerodynamic pressure fluctuations resulting from massive flow separations. Understanding these phenomena is essential for performance enhancements for future launchers which operate a larger nozzle. A new hybrid RANS-LES turbulence modelling approach termed eXtra-Large Eddy Simulations (X-LES) holds the promise to capture the flow structures associated with massive separations and enables the prediction of the broad-band spectrum of dynamic loads. This type of method has become a focal point, reducing the cost of full LES, driven by the demand for their applicability in an industrial environment. The industrial feasibility of X-LES simulations is demonstrated by computing the unsteady aerodynamic loads on the main-engine nozzle of a generic space launcher configuration. The potential to calculate the dynamic loads is qualitatively assessed for transonic flow conditions in a comparison to wind-tunnel experiments. In terms of turn-around-times, X-LES computations are already feasible within the time-frames of the development process to support the structural design. Key words: massive separated flows; buffet loads; nozzle vibrations; space launchers; time-accurate CFD; composite RANS-LES formulation.

Dynamic vs. static social networks in models of parasite transmission: predicting Cryptosporidium spread in wild lemurs.

PubMed

Springer, Andrea; Kappeler, Peter M; Nunn, Charles L

2017-05-01

Social networks provide an established tool to implement heterogeneous contact structures in epidemiological models. Dynamic temporal changes in contact structure and ranging behaviour of wildlife may impact disease dynamics. A consensus has yet to emerge, however, concerning the conditions in which network dynamics impact model outcomes, as compared to static approximations that average contact rates over longer time periods. Furthermore, as many pathogens can be transmitted both environmentally and via close contact, it is important to investigate the relative influence of both transmission routes in real-world populations. Here, we use empirically derived networks from a population of wild primates, Verreaux's sifakas (Propithecus verreauxi), and simulated networks to investigate pathogen spread in dynamic vs. static social networks. First, we constructed a susceptible-exposed-infected-recovered model of Cryptosporidium spread in wild Verreaux's sifakas. We incorporated social and environmental transmission routes and parameterized the model for two different climatic seasons. Second, we used simulated networks and greater variation in epidemiological parameters to investigate the conditions in which dynamic networks produce larger outbreak sizes than static networks. We found that average outbreak size of Cryptosporidium infections in sifakas was larger when the disease was introduced in the dry season than in the wet season, driven by an increase in home range overlap towards the end of the dry season. Regardless of season, dynamic networks always produced larger average outbreak sizes than static networks. Larger outbreaks in dynamic models based on simulated networks occurred especially when the probability of transmission and recovery were low. Variation in tie strength in the dynamic networks also had a major impact on outbreak size, while network modularity had a weaker influence than epidemiological parameters that determine transmission and recovery. Our study adds to emerging evidence that dynamic networks can change predictions of disease dynamics, especially if the disease shows low transmissibility and a long infectious period, and when environmental conditions lead to enhanced between-group contact after an infectious agent has been introduced. © 2016 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.

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

NASA Astrophysics Data System (ADS)

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.

Static Tensile and Transient Dynamic Response of Cracked Aluminum Plate Repaired with Composite Patch - Numerical Study

NASA Astrophysics Data System (ADS)

Khalili, S. M. R.; Shariyat, M.; Mokhtari, M.

2014-06-01

In this study, the central cracked aluminum plates repaired with two sided composite patches are investigated numerically for their response to static tensile and transient dynamic loadings. Contour integral method is used to define and evaluate the stress intensity factors at the crack tips. The reinforcement for the composite patches is carbon fibers. The effect of adhesive thickness and patch thickness and configuration in tensile loading case and pre-tension, pre-compression and crack length effect on the evolution of the mode I stress intensity factor (SIF) (KI) of the repaired structure under transient dynamic loading case are examined. The results indicated that KI of the central cracked plate is reduced by 1/10 to 1/2 as a result of the bonded composite patch repair in tensile loading case. The crack length and the pre-loads are more effective in repaired structure in transient dynamic loading case in which, the 100 N pre-compression reduces the maximum KI for about 40 %, and the 100 N pre-tension reduces the maximum KI after loading period, by about 196 %.

Dynamic load balancing of applications

DOEpatents

Wheat, Stephen R.

1997-01-01

An application-level method for dynamically maintaining global load balance on a parallel computer, particularly on massively parallel MIMD computers. Global load balancing is achieved by overlapping neighborhoods of processors, where each neighborhood performs local load balancing. The method supports a large class of finite element and finite difference based applications and provides an automatic element management system to which applications are easily integrated.

Vertical-plane pendulum absorbers for minimizing helicopter vibratory loads

NASA Technical Reports Server (NTRS)

Amer, K. B.; Neff, J. R.

1974-01-01

The use of pendulum dynamic absorbers mounted on the blade root and operating in the vertical plane to minimize helicopter vibratory loads was discussed. A qualitative description was given of the concept of the dynamic absorbers and some results of analytical studies showing the degree of reduction in vibratory loads attainable are presented. Operational experience of vertical plane dynamic absorbers on the OH-6A helicopter is also discussed.

A computer solution for the dynamic load, lubricant film thickness, and surface temperatures in spiral-bevel gears

NASA Technical Reports Server (NTRS)

Chao, H. C.; Baxter, M.; Cheng, H. S.

1983-01-01

A computer method for determining the dynamic load between spiral bevel pinion and gear teeth contact along the path of contact is described. The dynamic load analysis governs both the surface temperature and film thickness. Computer methods for determining the surface temperature, and film thickness are presented along with results obtained for a pair of typical spiral bevel gears.

In vivo dynamic stiffness of the porcine lumbar spine exposed to cyclic loading: influence of load and degeneration.

PubMed

Kaigle, A; Ekström, L; Holm, S; Rostedt, M; Hansson, T

1998-02-01

The dynamic axial stiffness of the L2-3 motion segment subjected to vibratory loading under intact and injured states of the intervertebral disc was studied using an in vivo porcine model. Three groups of animals with the following states of the intervertebral discs were studied: intact disc, acutely injured disc, and degenerated disc. A miniaturized servo-hydraulic exciter was used to sinusoidally vibrate the motion segment from 0.05 to 25 Hz under a compressive load with a peak value of either 100 or 200 N. The dynamic axial stiffness of the intervertebral disc was calculated at 1-Hz intervals over the frequency range. The results showed that the dynamic axial stiffness was frequency dependent. A positive relationship was found between an increase in mean dynamic stiffness and load magnitude. An increase in mean stiffness with successive exposures at the same load magnitude was observed, despite the allowance of a recovery period between loading. The greatest difference was noted between the first and second load sets. No significant change in stiffness was found due to an acute disc injury, whereas a significant increase in mean stiffness was found for the degenerated disc group as compared with the intact group. The form of the frequency response curve, however, remained relatively unaltered regardless of the degenerated state of the disc. With heavier loads, repeated loading, and/or disc degeneration, the stiffness of the intervertebral disc increases. An increase in stiffness can mean a reduction in the amount of allowable motion within the motion segment or a potentially harmful increase in force to obtain the desired motion. This may locally result in greater stresses due to an altered ability of the disc to distribute loads.

Strain-rate effect on initial crush stress of irregular honeycomb under dynamic loading and its deformation mechanism

NASA Astrophysics Data System (ADS)

Wang, Peng; Zheng, Zhijun; Liao, Shenfei; Yu, Jilin

2018-02-01

The seemingly contradictory understandings of the initial crush stress of cellular materials under dynamic loadings exist in the literature, and a comprehensive analysis of this issue is carried out with using direct information of local stress and strain. Local stress/strain calculation methods are applied to determine the initial crush stresses and the strain rates at initial crush from a cell-based finite element model of irregular honeycomb under dynamic loadings. The initial crush stress under constant-velocity compression is identical to the quasi-static one, but less than the one under direct impact, i.e. the initial crush stresses under different dynamic loadings could be very different even though there is no strain-rate effect of matrix material. A power-law relation between the initial crush stress and the strain rate is explored to describe the strain-rate effect on the initial crush stress of irregular honeycomb when the local strain rate exceeds a critical value, below which there is no strain-rate effect of irregular honeycomb. Deformation mechanisms of the initial crush behavior under dynamic loadings are also explored. The deformation modes of the initial crush region in the front of plastic compaction wave are different under different dynamic loadings.

Research on dynamic routing mechanisms in wireless sensor networks.

PubMed

Zhao, A Q; Weng, Y N; Lu, Y; Liu, C Y

2014-01-01

WirelessHART is the most widely applied standard in wireless sensor networks nowadays. However, it does not provide any dynamic routing mechanism, which is important for the reliability and robustness of the wireless network applications. In this paper, a collection tree protocol based, dynamic routing mechanism was proposed for WirelessHART network. The dynamic routing mechanism was evaluated through several simulation experiments in three aspects: time for generating the topology, link quality, and stability of network. Besides, the data transmission efficiency of this routing mechanism was analyzed. The simulation and evaluation results show that this mechanism can act as a dynamic routing mechanism for the TDMA-based wireless sensor network.

An evaluation of Bayesian techniques for controlling model complexity and selecting inputs in a neural network for short-term load forecasting.

PubMed

Hippert, Henrique S; Taylor, James W

2010-04-01

Artificial neural networks have frequently been proposed for electricity load forecasting because of their capabilities for the nonlinear modelling of large multivariate data sets. Modelling with neural networks is not an easy task though; two of the main challenges are defining the appropriate level of model complexity, and choosing the input variables. This paper evaluates techniques for automatic neural network modelling within a Bayesian framework, as applied to six samples containing daily load and weather data for four different countries. We analyse input selection as carried out by the Bayesian 'automatic relevance determination', and the usefulness of the Bayesian 'evidence' for the selection of the best structure (in terms of number of neurones), as compared to methods based on cross-validation. Copyright 2009 Elsevier Ltd. All rights reserved.

Minimization of Impact from Electric Vehicle Supply Equipment to the Electric Grid Using a Dynamically Controlled Battery Bank for Peak Load Shaving

DOE Office of Scientific and Technical Information (OSTI.GOV)

Castello, Charles C

This research presents a comparison of two control systems for peak load shaving using local solar power generation (i.e., photovoltaic array) and local energy storage (i.e., battery bank). The purpose is to minimize load demand of electric vehicle supply equipment (EVSE) on the electric grid. A static and dynamic control system is compared to decrease demand from EVSE. Static control of the battery bank is based on charging and discharging to the electric grid at fixed times. Dynamic control, with 15-minute resolution, forecasts EVSE load based on data analysis of collected data. In the proposed dynamic control system, the sigmoidmore » function is used to shave peak loads while limiting scenarios that can quickly drain the battery bank. These control systems are applied to Oak Ridge National Laboratory s (ORNL) solar-assisted electric vehicle (EV) charging stations. This installation is composed of three independently grid-tied sub-systems: (1) 25 EVSE; (2) 47 kW photovoltaic (PV) array; and (3) 60 kWh battery bank. The dynamic control system achieved the greatest peak load shaving, up to 34% on a cloudy day and 38% on a sunny day. The static control system was not ideal; peak load shaving was 14.6% on a cloudy day and 12.7% on a sunny day. Simulations based on ORNL data shows solar-assisted EV charging stations combined with the proposed dynamic battery control system can negate up to 89% of EVSE load demand on sunny days.« less

Reconstruction of network topology using status-time-series data

NASA Astrophysics Data System (ADS)

Pandey, Pradumn Kumar; Badarla, Venkataramana

2018-01-01

Uncovering the heterogeneous connection pattern of a networked system from the available status-time-series (STS) data of a dynamical process on the network is of great interest in network science and known as a reverse engineering problem. Dynamical processes on a network are affected by the structure of the network. The dependency between the diffusion dynamics and structure of the network can be utilized to retrieve the connection pattern from the diffusion data. Information of the network structure can help to devise the control of dynamics on the network. In this paper, we consider the problem of network reconstruction from the available status-time-series (STS) data using matrix analysis. The proposed method of network reconstruction from the STS data is tested successfully under susceptible-infected-susceptible (SIS) diffusion dynamics on real-world and computer-generated benchmark networks. High accuracy and efficiency of the proposed reconstruction procedure from the status-time-series data define the novelty of the method. Our proposed method outperforms compressed sensing theory (CST) based method of network reconstruction using STS data. Further, the same procedure of network reconstruction is applied to the weighted networks. The ordering of the edges in the weighted networks is identified with high accuracy.

Deformation and fracture of explosion-welded Ti/Al plates: A synchrotron-based study

DOE Office of Scientific and Technical Information (OSTI.GOV)

E, J. C.; Huang, J. Y.; Bie, B. X.

Here, explosion-welded Ti/Al plates are characterized with energy dispersive spectroscopy and x-ray computed tomography, and exhibit smooth, well-jointed, interface. We perform dynamic and quasi-static uniaxial tension experiments on Ti/Al with the loading direction either perpendicular or parallel to the Ti/Al interface, using a mini split Hopkinson tension bar and a material testing system in conjunction with time-resolved synchrotron x-ray imaging. X-ray imaging and strain-field mapping reveal different deformation mechanisms responsible for anisotropic bulk-scale responses, including yield strength, ductility and rate sensitivity. Deformation and fracture are achieved predominantly in Al layer for perpendicular loading, but both Ti and Al layers asmore » well as the interface play a role for parallel loading. The rate sensitivity of Ti/Al follows those of the constituent metals. For perpendicular loading, single deformation band develops in Al layer under quasi-static loading, while multiple deformation bands nucleate simultaneously under dynamic loading, leading to a higher dynamic fracture strain. For parallel loading, the interface impedes the growth of deformation and results in increased ductility of Ti/Al under quasi-static loading, while interface fracture occurs under dynamic loading due to the disparity in Poisson's contraction.« less

Deformation and fracture of explosion-welded Ti/Al plates: A synchrotron-based study

DOE PAGES

E, J. C.; Huang, J. Y.; Bie, B. X.; ...

2016-08-02

Here, explosion-welded Ti/Al plates are characterized with energy dispersive spectroscopy and x-ray computed tomography, and exhibit smooth, well-jointed, interface. We perform dynamic and quasi-static uniaxial tension experiments on Ti/Al with the loading direction either perpendicular or parallel to the Ti/Al interface, using a mini split Hopkinson tension bar and a material testing system in conjunction with time-resolved synchrotron x-ray imaging. X-ray imaging and strain-field mapping reveal different deformation mechanisms responsible for anisotropic bulk-scale responses, including yield strength, ductility and rate sensitivity. Deformation and fracture are achieved predominantly in Al layer for perpendicular loading, but both Ti and Al layers asmore » well as the interface play a role for parallel loading. The rate sensitivity of Ti/Al follows those of the constituent metals. For perpendicular loading, single deformation band develops in Al layer under quasi-static loading, while multiple deformation bands nucleate simultaneously under dynamic loading, leading to a higher dynamic fracture strain. For parallel loading, the interface impedes the growth of deformation and results in increased ductility of Ti/Al under quasi-static loading, while interface fracture occurs under dynamic loading due to the disparity in Poisson's contraction.« less

Mechanics of Flapping Flight: Analytical Formulations of Unsteady Aerodynamics, Kinematic Optimization, Flight Dynamics, and Control

NASA Astrophysics Data System (ADS)

Taneja, Jayant Kumar

Electricity is an indispensable commodity to modern society, yet it is delivered via a grid architecture that remains largely unchanged over the past century. A host of factors are conspiring to topple this dated yet venerated design: developments in renewable electricity generation technology, policies to reduce greenhouse gas emissions, and advances in information technology for managing energy systems. Modern electric grids are emerging as complex distributed systems in which a portfolio of power generation resources, often incorporating fluctuating renewable resources such as wind and solar, must be managed dynamically to meet uncontrolled, time-varying demand. Uncertainty in both supply and demand makes control of modern electric grids fundamentally more challenging, and growing portfolios of renewables exacerbate the challenge. We study three electricity grids: the state of California, the province of Ontario, and the country of Germany. To understand the effects of increasing renewables, we develop a methodology to scale renewables penetration. Analyzing these grids yields key insights about rigid limits to renewables penetration and their implications in meeting long-term emissions targets. We argue that to achieve deep penetration of renewables, the operational model of the grid must be inverted, changing the paradigm from load-following supplies to supply-following loads. To alleviate the challenge of supply-demand matching on deeply renewable grids, we first examine well-known techniques, including altering management of existing supply resources, employing utility-scale energy storage, targeting energy efficiency improvements, and exercising basic demand-side management. Then, we create several instantiations of supply-following loads -- including refrigerators, heating and cooling systems, and laptop computers -- by employing a combination of sensor networks, advanced control techniques, and enhanced energy storage. We examine the capacity of each load for supply-following and study the behaviors of populations of these loads, assessing their potential at various levels of deployment throughout the California electricity grid. Using combinations of supply-following strategies, we can reduce peak natural gas generation by 19% on a model of the California grid with 60% renewables. We then assess remaining variability on this deeply renewable grid incorporating supply-following loads, characterizing additional capabilities needed to ensure supply-demand matching in future sustainable electricity grids.

Effect of electric field induced alignment and dispersion of functionalized carbon nanotubes on properties of natural rubber

NASA Astrophysics Data System (ADS)

Gao, Jiangshan; He, Yan; Gong, Xiubin

2018-06-01

The original equipment and method for orienting multi-walled carbon nanotubes (MWCNTs) in natural rubber (NR) by alternating current (AC) electric field were reported in the present study. MWCNTs with various volume fractions were dispersed in the mixture latex which composed of natural rubber, additives and methylbenzene. The application of AC electric field during nanocomposites curing process was used to induce the formation of aligned conductive nanotube networks between the electrodes. The aligned MWCNTs in the composites have a better orientation performance and dispersion quality than these of random MWCNTs by analyzing TEM and SEM images. The effects of MWCNTs anisotropy on thermal conductivity, dielectric properties, and dynamic mechanical properties of NR were studied. The mean value of thermal conductivity of composites loading with aligned MWCNTs was 8.67% higher than that of composites with random MWCNTs due to the anisotropy of aligned MWCNTs. The compounds with aligned MWCNTs possessed low dielectric constant, loss tangents and conductivity, namely a good insulativity. The compounds loading with aligned MWCNTs had lower loss modulus and better dynamic mechanical properties than those with random MWCNTs. This method can make full use of the high thermal conductivity of MWCNTs axis, and expand the application areas of natural rubber like conducting heat in a certain direction with a high efficiency.

Dynamic tubulation of mitochondria drives mitochondrial network formation.

PubMed

Wang, Chong; Du, Wanqing; Su, Qian Peter; Zhu, Mingli; Feng, Peiyuan; Li, Ying; Zhou, Yichen; Mi, Na; Zhu, Yueyao; Jiang, Dong; Zhang, Senyan; Zhang, Zerui; Sun, Yujie; Yu, Li

2015-10-01

Mitochondria form networks. Formation of mitochondrial networks is important for maintaining mitochondrial DNA integrity and interchanging mitochondrial material, whereas disruption of the mitochondrial network affects mitochondrial functions. According to the current view, mitochondrial networks are formed by fusion of individual mitochondria. Here, we report a new mechanism for formation of mitochondrial networks through KIF5B-mediated dynamic tubulation of mitochondria. We found that KIF5B pulls thin, highly dynamic tubules out of mitochondria. Fusion of these dynamic tubules, which is mediated by mitofusins, gives rise to the mitochondrial network. We further demonstrated that dynamic tubulation and fusion is sufficient for mitochondrial network formation, by reconstituting mitochondrial networks in vitro using purified fusion-competent mitochondria, recombinant KIF5B, and polymerized microtubules. Interestingly, KIF5B only controls network formation in the peripheral zone of the cell, indicating that the mitochondrial network is divided into subzones, which may be constructed by different mechanisms. Our data not only uncover an essential mechanism for mitochondrial network formation, but also reveal that different parts of the mitochondrial network are formed by different mechanisms.

Graph fibrations and symmetries of network dynamics

NASA Astrophysics Data System (ADS)

Nijholt, Eddie; Rink, Bob; Sanders, Jan

2016-11-01

Dynamical systems with a network structure can display remarkable phenomena such as synchronisation and anomalous synchrony breaking. A methodology for classifying patterns of synchrony in networks was developed by Golubitsky and Stewart. They showed that the robustly synchronous dynamics of a network is determined by its quotient networks. This result was recently reformulated by DeVille and Lerman, who pointed out that the reduction from a network to a quotient is an example of a graph fibration. The current paper exploits this observation and demonstrates the importance of self-fibrations of network graphs. Self-fibrations give rise to symmetries in the dynamics of a network. We show that every network admits a lift with a semigroup or semigroupoid of self-fibrations. The resulting symmetries impact the global dynamics of the network and can therefore be used to explain and predict generic scenarios for synchrony breaking. Also, when the network has a trivial symmetry groupoid, then every robust synchrony in the lift is determined by symmetry. We finish this paper with a discussion of networks with interior symmetries and nonhomogeneous networks.

Access Protocol For An Industrial Optical Fibre LAN

NASA Astrophysics Data System (ADS)

Senior, John M.; Walker, William M.; Ryley, Alan

1987-09-01

A structure for OSI levels 1 and 2 of a local area network suitable for use in a variety of industrial environments is reported. It is intended that the LAN will utilise optical fibre technology at the physical level and a hybrid of dynamically optimisable token passing and CSMA/CD techniques at the data link (IEEE 802 medium access control - logical link control) level. An intelligent token passing algorithm is employed which dynamically allocates tokens according to the known upper limits on the requirements of each device. In addition a system of stochastic tokens is used to increase efficiency when the stochastic traffic is significant. The protocol also allows user-defined priority systems to be employed and is suitable for distributed or centralised implementation. The results of computer simulated performance characteristics for the protocol using a star-ring topology are reported which demonstrate its ability to perform efficiently with the device and traffic loads anticipated within an industrial environment.

A comparison between theoretical prediction and experimental measurement of the dynamic behavior of spur gears

NASA Technical Reports Server (NTRS)

Rebbechi, Brian; Forrester, B. David; Oswald, Fred B.; Townsend, Dennis P.

1992-01-01

A comparison was made between computer model predictions of gear dynamics behavior and experimental results. The experimental data were derived from the NASA gear noise rig, which was used to record dynamic tooth loads and vibration. The experimental results were compared with predictions from the DSTO Aeronautical Research Laboratory's gear dynamics code for a matrix of 28 load speed points. At high torque the peak dynamic load predictions agree with the experimental results with an average error of 5 percent in the speed range 800 to 6000 rpm. Tooth separation (or bounce), which was observed in the experimental data for light torque, high speed conditions, was simulated by the computer model. The model was also successful in simulating the degree of load sharing between gear teeth in the multiple tooth contact region.

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

NASA Astrophysics Data System (ADS)

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.

Asynchronous networks: modularization of dynamics theorem

NASA Astrophysics Data System (ADS)

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.

Dealing with periodical loads and harmonics in operational modal analysis using time-varying transmissibility functions

NASA Astrophysics Data System (ADS)

Weijtjens, Wout; Lataire, John; Devriendt, Christof; Guillaume, Patrick

2014-12-01

Periodical loads, such as waves and rotating machinery, form a problem for operational modal analysis (OMA). In OMA only the vibrations of a structure of interest are measured and little to nothing is known about the loads causing these vibrations. Therefore, it is often assumed that all dynamics in the measured data are linked to the system of interest. Periodical loads defy this assumption as their periodical behavior is often visible within the measured vibrations. As a consequence most OMA techniques falsely associate the dynamics of the periodical load with the system of interest. Without additional information about the load, one is not able to correctly differentiate between structural dynamics and the dynamics of the load. In several applications, e.g. turbines and helicopters, it was observed that because of periodical loads one was unable to correctly identify one or multiple modes. Transmissibility based OMA (TOMA) is a completely different approach to OMA. By using transmissibility functions to estimate the structural dynamics of the system of interest, all influence of the load-spectrum can be eliminated. TOMA therefore allows to identify the modal parameters without being influenced by the presence of periodical loads, such as harmonics. One of the difficulties of TOMA is that the analyst is required to find two independent datasets, each associated with a different loading condition of the system of interest. This poses a dilemma for TOMA; how can an analyst identify two different loading conditions when little is known about the loads on the system? This paper tackles that problem by assuming that the loading conditions vary continuously over time, e.g. the changing wind directions. From this assumption TOMA is developed into a time-varying framework. This development allows TOMA to not only cope with the continuously changing loading conditions. The time-varying framework also enables the identification of the modal parameters from a single dataset. Moreover, the time-varying TOMA approach can be implemented in such a way that the analyst no longer has to identify different loading conditions. For these combined reasons the time-varying TOMA is less dependent on the user and requires less testing time than the earlier TOMA-technique.

Neural network based optimal control of HVAC&R systems

NASA Astrophysics Data System (ADS)

Ning, Min

Heating, Ventilation, Air-Conditioning and Refrigeration (HVAC&R) systems have wide applications in providing a desired indoor environment for different types of buildings. It is well acknowledged that 30%-40% of the total energy generated is consumed by buildings and HVAC&R systems alone account for more than 50% of the building energy consumption. Low operational efficiency especially under partial load conditions and poor control are part of reasons for such high energy consumption. To improve energy efficiency, HVAC&R systems should be properly operated to maintain a comfortable and healthy indoor environment under dynamic ambient and indoor conditions with the least energy consumption. This research focuses on the optimal operation of HVAC&R systems. The optimization problem is formulated and solved to find the optimal set points for the chilled water supply temperature, discharge air temperature and AHU (air handling unit) fan static pressure such that the indoor environment is maintained with the least chiller and fan energy consumption. To achieve this objective, a dynamic system model is developed first to simulate the system behavior under different control schemes and operating conditions. The system model is modular in structure, which includes a water-cooled vapor compression chiller model and a two-zone VAV system model. A fuzzy-set based extended transformation approach is then applied to investigate the uncertainties of this model caused by uncertain parameters and the sensitivities of the control inputs with respect to the interested model outputs. A multi-layer feed forward neural network is constructed and trained in unsupervised mode to minimize the cost function which is comprised of overall energy cost and penalty cost when one or more constraints are violated. After training, the network is implemented as a supervisory controller to compute the optimal settings for the system. In order to implement the optimal set points predicted by the supervisory controller, a set of five adaptive PI (proportional-integral) controllers are designed for each of the five local control loops of the HVAC&R system. The five controllers are used to track optimal set points and zone air temperature set points. Parameters of these PI controllers are tuned online to reduce tracking errors. The updating rules are derived from Lyapunov stability analysis. Simulation results show that compared to the conventional night reset operation scheme, the optimal operation scheme saves around 10% energy under full load condition and 19% energy under partial load conditions.

Gearbox Reliability Collaborative Research | Wind | NREL

Science.gov Websites

inception, the Gearbox Reliability Collaborative (GRC) has collected an extraordinary amount of experimental torque, steady state and dynamic non-torque loads, internal loads and deflections, and condition important data and conclusions such as the importance of non-torque loads, dynamic torque events, planetary

Dynamic reconfiguration of frontal brain networks during executive cognition in humans

PubMed Central

Braun, Urs; Schäfer, Axel; Walter, Henrik; Erk, Susanne; Romanczuk-Seiferth, Nina; Haddad, Leila; Schweiger, Janina I.; Grimm, Oliver; Heinz, Andreas; Tost, Heike; Meyer-Lindenberg, Andreas; Bassett, Danielle S.

2015-01-01

The brain is an inherently dynamic system, and executive cognition requires dynamically reconfiguring, highly evolving networks of brain regions that interact in complex and transient communication patterns. However, a precise characterization of these reconfiguration processes during cognitive function in humans remains elusive. Here, we use a series of techniques developed in the field of “dynamic network neuroscience” to investigate the dynamics of functional brain networks in 344 healthy subjects during a working-memory challenge (the “n-back” task). In contrast to a control condition, in which dynamic changes in cortical networks were spread evenly across systems, the effortful working-memory condition was characterized by a reconfiguration of frontoparietal and frontotemporal networks. This reconfiguration, which characterizes “network flexibility,” employs transient and heterogeneous connectivity between frontal systems, which we refer to as “integration.” Frontal integration predicted neuropsychological measures requiring working memory and executive cognition, suggesting that dynamic network reconfiguration between frontal systems supports those functions. Our results characterize dynamic reconfiguration of large-scale distributed neural circuits during executive cognition in humans and have implications for understanding impaired cognitive function in disorders affecting connectivity, such as schizophrenia or dementia. PMID:26324898