Modeling Periodic Impulsive Effects on Online TV Series Diffusion

PubMed Central

Fang, Qiwen; Wang, Xi

2016-01-01

Background Online broadcasting substantially affects the production, distribution, and profit of TV series. In addition, online word-of-mouth significantly affects the diffusion of TV series. Because on-demand streaming rates are the most important factor that influences the earnings of online video suppliers, streaming statistics and forecasting trends are valuable. In this paper, we investigate the effects of periodic impulsive stimulation and pre-launch promotion on on-demand streaming dynamics. We consider imbalanced audience feverish distribution using an impulsive susceptible-infected-removed(SIR)-like model. In addition, we perform a correlation analysis of online buzz volume based on Baidu Index data. Methods We propose a PI-SIR model to evolve audience dynamics and translate them into on-demand streaming fluctuations, which can be observed and comprehended by online video suppliers. Six South Korean TV series datasets are used to test the model. We develop a coarse-to-fine two-step fitting scheme to estimate the model parameters, first by fitting inter-period accumulation and then by fitting inner-period feverish distribution. Results We find that audience members display similar viewing habits. That is, they seek new episodes every update day but fade away. This outcome means that impulsive intensity plays a crucial role in on-demand streaming diffusion. In addition, the initial audience size and online buzz are significant factors. On-demand streaming fluctuation is highly correlated with online buzz fluctuation. Conclusion To stimulate audience attention and interpersonal diffusion, it is worthwhile to invest in promotion near update days. Strong pre-launch promotion is also a good marketing tool to improve overall performance. It is not advisable for online video providers to promote several popular TV series on the same update day. Inter-period accumulation is a feasible forecasting tool to predict the future trend of the on-demand streaming amount. The buzz in public social communities also represents a highly correlated analysis tool to evaluate the advertising value of TV series. PMID:27669520

An Experiment of GMPLS-Based Dispersion Compensation Control over In-Field Fibers

NASA Astrophysics Data System (ADS)

Seno, Shoichiro; Horiuchi, Eiichi; Yoshida, Sota; Sugihara, Takashi; Onohara, Kiyoshi; Kamei, Misato; Baba, Yoshimasa; Kubo, Kazuo; Mizuochi, Takashi

As ROADMs (Reconfigurable Optical Add/Drop Multiplexers) are becoming widely used in metro/core networks, distributed control of wavelength paths by extended GMPLS (Generalized MultiProtocol Label Switching) protocols has attracted much attention. For the automatic establishment of an arbitrary wavelength path satisfying dynamic traffic demands over a ROADM or WXC (Wavelength Cross Connect)-based network, precise determination of chromatic dispersion over the path and optimized assignment of dispersion compensation capabilities at related nodes are essential. This paper reports an experiment over in-field fibers where GMPLS-based control was applied for the automatic discovery of chromatic dispersion, path computation, and wavelength path establishment with dynamic adjustment of variable dispersion compensation. The GMPLS-based control scheme, which the authors called GMPLS-Plus, extended GMPLS's distributed control architecture with attributes for automatic discovery, advertisement, and signaling of chromatic dispersion. In this experiment, wavelength paths with distances of 24km and 360km were successfully established and error-free data transmission was verified. The experiment also confirmed path restoration with dynamic compensation adjustment upon fiber failure.

Advanced end-to-end fiber optic sensing systems for demanding environments

NASA Astrophysics Data System (ADS)

Black, Richard J.; Moslehi, Behzad

2010-09-01

Optical fibers are small-in-diameter, light-in-weight, electromagnetic-interference immune, electrically passive, chemically inert, flexible, embeddable into different materials, and distributed-sensing enabling, and can be temperature and radiation tolerant. With appropriate processing and/or packaging, they can be very robust and well suited to demanding environments. In this paper, we review a range of complete end-to-end fiber optic sensor systems that IFOS has developed comprising not only (1) packaged sensors and mechanisms for integration with demanding environments, but (2) ruggedized sensor interrogators, and (3) intelligent decision aid algorithms software systems. We examine the following examples: " Fiber Bragg Grating (FBG) optical sensors systems supporting arrays of environmentally conditioned multiplexed FBG point sensors on single or multiple optical fibers: In conjunction with advanced signal processing, decision aid algorithms and reasoners, FBG sensor based structural health monitoring (SHM) systems are expected to play an increasing role in extending the life and reducing costs of new generations of aerospace systems. Further, FBG based structural state sensing systems have the potential to considerably enhance the performance of dynamic structures interacting with their environment (including jet aircraft, unmanned aerial vehicles (UAVs), and medical or extravehicular space robots). " Raman based distributed temperature sensing systems: The complete length of optical fiber acts as a very long distributed sensor which may be placed down an oil well or wrapped around a cryogenic tank.

Automated Dynamic Demand Response Implementation on a Micro-grid

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

Kuppannagari, Sanmukh R.; Kannan, Rajgopal; Chelmis, Charalampos

In this paper, we describe a system for real-time automated Dynamic and Sustainable Demand Response with sparse data consumption prediction implemented on the University of Southern California campus microgrid. Supply side approaches to resolving energy supply-load imbalance do not work at high levels of renewable energy penetration. Dynamic Demand Response (D 2R) is a widely used demand-side technique to dynamically adjust electricity consumption during peak load periods. Our D 2R system consists of accurate machine learning based energy consumption forecasting models that work with sparse data coupled with fast and sustainable load curtailment optimization algorithms that provide the ability tomore » dynamically adapt to changing supply-load imbalances in near real-time. Our Sustainable DR (SDR) algorithms attempt to distribute customer curtailment evenly across sub-intervals during a DR event and avoid expensive demand peaks during a few sub-intervals. It also ensures that each customer is penalized fairly in order to achieve the targeted curtailment. We develop near linear-time constant-factor approximation algorithms along with Polynomial Time Approximation Schemes (PTAS) for SDR curtailment that minimizes the curtailment error defined as the difference between the target and achieved curtailment values. Our SDR curtailment problem is formulated as an Integer Linear Program that optimally matches customers to curtailment strategies during a DR event while also explicitly accounting for customer strategy switching overhead as a constraint. We demonstrate the results of our D 2R system using real data from experiments performed on the USC smartgrid and show that 1) our prediction algorithms can very accurately predict energy consumption even with noisy or missing data and 2) our curtailment algorithms deliver DR with extremely low curtailment errors in the 0.01-0.05 kWh range.« less

Agent-Based Modeling of Mitochondria Links Sub-Cellular Dynamics to Cellular Homeostasis and Heterogeneity.

PubMed

Dalmasso, Giovanni; Marin Zapata, Paula Andrea; Brady, Nathan Ryan; Hamacher-Brady, Anne

2017-01-01

Mitochondria are semi-autonomous organelles that supply energy for cellular biochemistry through oxidative phosphorylation. Within a cell, hundreds of mobile mitochondria undergo fusion and fission events to form a dynamic network. These morphological and mobility dynamics are essential for maintaining mitochondrial functional homeostasis, and alterations both impact and reflect cellular stress states. Mitochondrial homeostasis is further dependent on production (biogenesis) and the removal of damaged mitochondria by selective autophagy (mitophagy). While mitochondrial function, dynamics, biogenesis and mitophagy are highly-integrated processes, it is not fully understood how systemic control in the cell is established to maintain homeostasis, or respond to bioenergetic demands. Here we used agent-based modeling (ABM) to integrate molecular and imaging knowledge sets, and simulate population dynamics of mitochondria and their response to environmental energy demand. Using high-dimensional parameter searches we integrated experimentally-measured rates of mitochondrial biogenesis and mitophagy, and using sensitivity analysis we identified parameter influences on population homeostasis. By studying the dynamics of cellular subpopulations with distinct mitochondrial masses, our approach uncovered system properties of mitochondrial populations: (1) mitochondrial fusion and fission activities rapidly establish mitochondrial sub-population homeostasis, and total cellular levels of mitochondria alter fusion and fission activities and subpopulation distributions; (2) restricting the directionality of mitochondrial mobility does not alter morphology subpopulation distributions, but increases network transmission dynamics; and (3) maintaining mitochondrial mass homeostasis and responding to bioenergetic stress requires the integration of mitochondrial dynamics with the cellular bioenergetic state. Finally, (4) our model suggests sources of, and stress conditions amplifying, cell-to-cell variability of mitochondrial morphology and energetic stress states. Overall, our modeling approach integrates biochemical and imaging knowledge, and presents a novel open-modeling approach to investigate how spatial and temporal mitochondrial dynamics contribute to functional homeostasis, and how subcellular organelle heterogeneity contributes to the emergence of cell heterogeneity.

Agent-Based Modeling of Mitochondria Links Sub-Cellular Dynamics to Cellular Homeostasis and Heterogeneity

PubMed Central

Dalmasso, Giovanni; Marin Zapata, Paula Andrea; Brady, Nathan Ryan; Hamacher-Brady, Anne

2017-01-01

Mitochondria are semi-autonomous organelles that supply energy for cellular biochemistry through oxidative phosphorylation. Within a cell, hundreds of mobile mitochondria undergo fusion and fission events to form a dynamic network. These morphological and mobility dynamics are essential for maintaining mitochondrial functional homeostasis, and alterations both impact and reflect cellular stress states. Mitochondrial homeostasis is further dependent on production (biogenesis) and the removal of damaged mitochondria by selective autophagy (mitophagy). While mitochondrial function, dynamics, biogenesis and mitophagy are highly-integrated processes, it is not fully understood how systemic control in the cell is established to maintain homeostasis, or respond to bioenergetic demands. Here we used agent-based modeling (ABM) to integrate molecular and imaging knowledge sets, and simulate population dynamics of mitochondria and their response to environmental energy demand. Using high-dimensional parameter searches we integrated experimentally-measured rates of mitochondrial biogenesis and mitophagy, and using sensitivity analysis we identified parameter influences on population homeostasis. By studying the dynamics of cellular subpopulations with distinct mitochondrial masses, our approach uncovered system properties of mitochondrial populations: (1) mitochondrial fusion and fission activities rapidly establish mitochondrial sub-population homeostasis, and total cellular levels of mitochondria alter fusion and fission activities and subpopulation distributions; (2) restricting the directionality of mitochondrial mobility does not alter morphology subpopulation distributions, but increases network transmission dynamics; and (3) maintaining mitochondrial mass homeostasis and responding to bioenergetic stress requires the integration of mitochondrial dynamics with the cellular bioenergetic state. Finally, (4) our model suggests sources of, and stress conditions amplifying, cell-to-cell variability of mitochondrial morphology and energetic stress states. Overall, our modeling approach integrates biochemical and imaging knowledge, and presents a novel open-modeling approach to investigate how spatial and temporal mitochondrial dynamics contribute to functional homeostasis, and how subcellular organelle heterogeneity contributes to the emergence of cell heterogeneity. PMID:28060865

Water quality modeling in the dead end sections of drinking water distribution networks.

PubMed

Abokifa, Ahmed A; Yang, Y Jeffrey; Lo, Cynthia S; Biswas, Pratim

2016-02-01

Dead-end sections of drinking water distribution networks are known to be problematic zones in terms of water quality degradation. Extended residence time due to water stagnation leads to rapid reduction of disinfectant residuals allowing the regrowth of microbial pathogens. Water quality models developed so far apply spatial aggregation and temporal averaging techniques for hydraulic parameters by assigning hourly averaged water demands to the main nodes of the network. Although this practice has generally resulted in minimal loss of accuracy for the predicted disinfectant concentrations in main water transmission lines, this is not the case for the peripheries of the distribution network. This study proposes a new approach for simulating disinfectant residuals in dead end pipes while accounting for both spatial and temporal variability in hydraulic and transport parameters. A stochastic demand generator was developed to represent residential water pulses based on a non-homogenous Poisson process. Dispersive solute transport was considered using highly dynamic dispersion rates. A genetic algorithm was used to calibrate the axial hydraulic profile of the dead-end pipe based on the different demand shares of the withdrawal nodes. A parametric sensitivity analysis was done to assess the model performance under variation of different simulation parameters. A group of Monte-Carlo ensembles was carried out to investigate the influence of spatial and temporal variations in flow demands on the simulation accuracy. A set of three correction factors were analytically derived to adjust residence time, dispersion rate and wall demand to overcome simulation error caused by spatial aggregation approximation. The current model results show better agreement with field-measured concentrations of conservative fluoride tracer and free chlorine disinfectant than the simulations of recent advection dispersion reaction models published in the literature. Accuracy of the simulated concentration profiles showed significant dependence on the spatial distribution of the flow demands compared to temporal variation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Micro-Level Adaptation, Macro-Level Selection, and the Dynamics of Market Partitioning

PubMed Central

García-Díaz, César; van Witteloostuijn, Arjen; Péli, Gábor

2015-01-01

This paper provides a micro-foundation for dual market structure formation through partitioning processes in marketplaces by developing a computational model of interacting economic agents. We propose an agent-based modeling approach, where firms are adaptive and profit-seeking agents entering into and exiting from the market according to their (lack of) profitability. Our firms are characterized by large and small sunk costs, respectively. They locate their offerings along a unimodal demand distribution over a one-dimensional product variety, with the distribution peak constituting the center and the tails standing for the peripheries. We found that large firms may first advance toward the most abundant demand spot, the market center, and release peripheral positions as predicted by extant dual market explanations. However, we also observed that large firms may then move back toward the market fringes to reduce competitive niche overlap in the center, triggering nonlinear resource occupation behavior. Novel results indicate that resource release dynamics depend on firm-level adaptive capabilities, and that a minimum scale of production for low sunk cost firms is key to the formation of the dual structure. PMID:26656107

Micro-Level Adaptation, Macro-Level Selection, and the Dynamics of Market Partitioning.

PubMed

García-Díaz, César; van Witteloostuijn, Arjen; Péli, Gábor

2015-01-01

This paper provides a micro-foundation for dual market structure formation through partitioning processes in marketplaces by developing a computational model of interacting economic agents. We propose an agent-based modeling approach, where firms are adaptive and profit-seeking agents entering into and exiting from the market according to their (lack of) profitability. Our firms are characterized by large and small sunk costs, respectively. They locate their offerings along a unimodal demand distribution over a one-dimensional product variety, with the distribution peak constituting the center and the tails standing for the peripheries. We found that large firms may first advance toward the most abundant demand spot, the market center, and release peripheral positions as predicted by extant dual market explanations. However, we also observed that large firms may then move back toward the market fringes to reduce competitive niche overlap in the center, triggering nonlinear resource occupation behavior. Novel results indicate that resource release dynamics depend on firm-level adaptive capabilities, and that a minimum scale of production for low sunk cost firms is key to the formation of the dual structure.

Encapsulating urban traffic rhythms into road networks.

PubMed

Wang, Junjie; Wei, Dong; He, Kun; Gong, Hang; Wang, Pu

2014-02-20

Using road GIS (geographical information systems) data and travel demand data for two U.S. urban areas, the dynamical driver sources of each road segment were located. A method to target road clusters closely related to urban traffic congestion was then developed to improve road network efficiency. The targeted road clusters show different spatial distributions at different times of a day, indicating that our method can encapsulate dynamical travel demand information into the road networks. As a proof of concept, when we lowered the speed limit or increased the capacity of road segments in the targeted road clusters, we found that both the number of congested roads and extra travel time were effectively reduced. In addition, the proposed modeling framework provided new insights on the optimization of transport efficiency in any infrastructure network with a specific supply and demand distribution.

Encapsulating Urban Traffic Rhythms into Road Networks

PubMed Central

Wang, Junjie; Wei, Dong; He, Kun; Gong, Hang; Wang, Pu

2014-01-01

Using road GIS (geographical information systems) data and travel demand data for two U.S. urban areas, the dynamical driver sources of each road segment were located. A method to target road clusters closely related to urban traffic congestion was then developed to improve road network efficiency. The targeted road clusters show different spatial distributions at different times of a day, indicating that our method can encapsulate dynamical travel demand information into the road networks. As a proof of concept, when we lowered the speed limit or increased the capacity of road segments in the targeted road clusters, we found that both the number of congested roads and extra travel time were effectively reduced. In addition, the proposed modeling framework provided new insights on the optimization of transport efficiency in any infrastructure network with a specific supply and demand distribution. PMID:24553203

Novel dynamic caching for hierarchically distributed video-on-demand systems

NASA Astrophysics Data System (ADS)

Ogo, Kenta; Matsuda, Chikashi; Nishimura, Kazutoshi

1998-02-01

It is difficult to simultaneously serve the millions of video streams that will be needed in the age of 'Mega-Media' networks by using only one high-performance server. To distribute the service load, caching servers should be location near users. However, in previously proposed caching mechanisms, the grade of service depends on whether the data is already cached at a caching server. To make the caching servers transparent to the users, the ability to randomly access the large volume of data stored in the central server should be supported, and the operational functions of the provided service should not be narrowly restricted. We propose a mechanism for constructing a video-stream-caching server that is transparent to the users and that will always support all special playback functions for all available programs to all the contents with a latency of only 1 or 2 seconds. This mechanism uses Variable-sized-quantum-segment- caching technique derived from an analysis of the historical usage log data generated by a line-on-demand-type service experiment and based on the basic techniques used by a time- slot-based multiple-stream video-on-demand server.

Modeling complexity in engineered infrastructure system: Water distribution network as an example

NASA Astrophysics Data System (ADS)

Zeng, Fang; Li, Xiang; Li, Ke

2017-02-01

The complex topology and adaptive behavior of infrastructure systems are driven by both self-organization of the demand and rigid engineering solutions. Therefore, engineering complex systems requires a method balancing holism and reductionism. To model the growth of water distribution networks, a complex network model was developed following the combination of local optimization rules and engineering considerations. The demand node generation is dynamic and follows the scaling law of urban growth. The proposed model can generate a water distribution network (WDN) similar to reported real-world WDNs on some structural properties. Comparison with different modeling approaches indicates that a realistic demand node distribution and co-evolvement of demand node and network are important for the simulation of real complex networks. The simulation results indicate that the efficiency of water distribution networks is exponentially affected by the urban growth pattern. On the contrary, the improvement of efficiency by engineering optimization is limited and relatively insignificant. The redundancy and robustness, on another aspect, can be significantly improved through engineering methods.

The NUONCE engine for LEO networks

NASA Technical Reports Server (NTRS)

Lo, Martin W.; Estabrook, Polly

1995-01-01

Typical LEO networks use constellations which provide a uniform coverage. However, the demand for telecom service is dynamic and unevenly distributed around the world. We examine a more efficient and cost effective design by matching the satellite coverage with the cyclical demand for service around the world. Our approach is to use a non-uniform satellite distribution for the network. We have named this constellation design NUONCE for Non Uniform Optimal Network Communications Engine.

A simulation-based study on different control strategies for variable speed pump in distributed ground source heat pump systems

DOE PAGES

Liu, Xiaobing; Zheng, O'Neill; Niu, Fuxin

2016-01-01

Most commercial ground source heat pump systems (GSHP) in the United States are in a distributed configuration. These systems circulate water or an anti-freeze solution through multiple heat pump units via a central pumping system, which usually uses variable speed pump(s). Variable speed pumps have potential to significantly reduce pumping energy use; however, the energy savings in reality could be far away from its potential due to improper pumping system design and controls. In this paper, a simplified hydronic pumping system was simulated with the dynamic Modelica models to evaluate three different pumping control strategies. This includes two conventional controlmore » strategies, which are to maintain a constant differential pressure across either the supply and return mains, or at the most hydraulically remote heat pump; and an innovative control strategy, which adjusts system flow rate based on the demand of each heat pump. The simulation results indicate that a significant overflow occurs at part load conditions when the variable speed pump is controlled to main a constant differential pressure across the supply and return mains of the piping system. On the other hand, an underflow occurs at part load conditions when the variable speed pump is controlled to maintain a constant differential pressure across the furthest heat pump. The flow-demand-based control can provide needed flow rate to each heat pump at any given time, and with less pumping energy use than the two conventional controls. Finally, a typical distributed GSHP system was studied to evaluate the energy saving potential of applying the flow-demand-based pumping control strategy. This case study shows that the annual pumping energy consumption can be reduced by 62% using the flow-demand-based control compared with that using the conventional pressure-based control to maintain a constant differential pressure a cross the supply and return mains.« less

Mapping Multi-Cropped Land Use to Estimate Water Demand Using the California Pesticide Reporting Database

NASA Astrophysics Data System (ADS)

Henson, W.; Baillie, M. N.; Martin, D.

2017-12-01

Detailed and dynamic land-use data is one of the biggest data deficiencies facing food and water security issues. Better land-use data results in improved integrated hydrologic models that are needed to look at the feedback between land and water use, specifically for adequately representing changes and dynamics in rainfall-runoff, urban and agricultural water demands, and surface fluxes of water (e.g., evapotranspiration, runoff, and infiltration). Currently, land-use data typically are compiled from annual (e.g., Crop Scape) or multi-year composites if mapped at all. While this approach provides information about interannual land-use practices, it does not capture the dynamic changes in highly developed agricultural lands prevalent in California agriculture such as (1) dynamic land-use changes from high frequency multi-crop rotations and (2) uncertainty in sub-annual crop distribution, planting times, and cropped areas. California has collected spatially distributed data for agricultural pesticide use since 1974 through the California Pesticide Information Portal (CalPIP). A method leveraging the CalPIP database has been developed to provide vital information about dynamic agricultural land use (e.g., crop distribution and planting times) and water demand issues in Salinas Valley, California, along the central coast. This 7 billion dollar/year agricultural area produces up to 50% of U.S. lettuce and broccoli. Therefore, effective and sustainable water resource development in the area must balance the needs of this essential industry, other beneficial uses, and the environment. This new tool provides a way to provide more dynamic crop data in hydrologic models. While the current application focuses on the Salinas Valley, the methods are extensible to all of California and other states with similar pesticide reporting. The improvements in representing variability in crop patterns and associated water demands increase our understanding of land-use change and precision of hydrologic decision models. Ultimately, further refinement to the parcel level will completely capture the changing topology of agricultural land use.

Dynamics of assembly production flow

NASA Astrophysics Data System (ADS)

Ezaki, Takahiro; Yanagisawa, Daichi; Nishinari, Katsuhiro

2015-06-01

Despite recent developments in management theory, maintaining a manufacturing schedule remains difficult because of production delays and fluctuations in demand and supply of materials. The response of manufacturing systems to such disruptions to dynamic behavior has been rarely studied. To capture these responses, we investigate a process that models the assembly of parts into end products. The complete assembly process is represented by a directed tree, where the smallest parts are injected at leaves and the end products are removed at the root. A discrete assembly process, represented by a node on the network, integrates parts, which are then sent to the next downstream node as a single part. The model exhibits some intriguing phenomena, including overstock cascade, phase transition in terms of demand and supply fluctuations, nonmonotonic distribution of stockout in the network, and the formation of a stockout path and stockout chains. Surprisingly, these rich phenomena result from only the nature of distributed assembly processes. From a physical perspective, these phenomena provide insight into delay dynamics and inventory distributions in large-scale manufacturing systems.

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.

Indonesia’s Electricity Demand Dynamic Modelling

NASA Astrophysics Data System (ADS)

Sulistio, J.; Wirabhuana, A.; Wiratama, M. G.

2017-06-01

Electricity Systems modelling is one of the emerging area in the Global Energy policy studies recently. System Dynamics approach and Computer Simulation has become one the common methods used in energy systems planning and evaluation in many conditions. On the other hand, Indonesia experiencing several major issues in Electricity system such as fossil fuel domination, demand - supply imbalances, distribution inefficiency, and bio-devastation. This paper aims to explain the development of System Dynamics modelling approaches and computer simulation techniques in representing and predicting electricity demand in Indonesia. In addition, this paper also described the typical characteristics and relationship of commercial business sector, industrial sector, and family / domestic sector as electricity subsystems in Indonesia. Moreover, it will be also present direct structure, behavioural, and statistical test as model validation approach and ended by conclusions.

Efficient On-Demand Operations in Large-Scale Infrastructures

ERIC Educational Resources Information Center

Ko, Steven Y.

2009-01-01

In large-scale distributed infrastructures such as clouds, Grids, peer-to-peer systems, and wide-area testbeds, users and administrators typically desire to perform "on-demand operations" that deal with the most up-to-date state of the infrastructure. However, the scale and dynamism present in the operating environment make it challenging to…

2010 Neuroscience Director’s Strategic Initiative

DTIC Science & Technology

2011-02-01

distribution unlimited. 13. SUPPLEMENTARY NOTES 14. ABSTRACT Understanding how Soldiers’ cognitive abilities meet the increasing demands of dynamic...In order to acquire, monitor, and assess Soldier sensory, perceptual, emotional, cognitive , and physical performance within realistic operational...brain state classification algorithm from EEG data acquired from participants performing tasks with varied cognitive demands. Third, Kaleb McDowell

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

Liu, Xiaobing; Zheng, O'Neill; Niu, Fuxin

Most commercial ground source heat pump systems (GSHP) in the United States are in a distributed configuration. These systems circulate water or an anti-freeze solution through multiple heat pump units via a central pumping system, which usually uses variable speed pump(s). Variable speed pumps have potential to significantly reduce pumping energy use; however, the energy savings in reality could be far away from its potential due to improper pumping system design and controls. In this paper, a simplified hydronic pumping system was simulated with the dynamic Modelica models to evaluate three different pumping control strategies. This includes two conventional controlmore » strategies, which are to maintain a constant differential pressure across either the supply and return mains, or at the most hydraulically remote heat pump; and an innovative control strategy, which adjusts system flow rate based on the demand of each heat pump. The simulation results indicate that a significant overflow occurs at part load conditions when the variable speed pump is controlled to main a constant differential pressure across the supply and return mains of the piping system. On the other hand, an underflow occurs at part load conditions when the variable speed pump is controlled to maintain a constant differential pressure across the furthest heat pump. The flow-demand-based control can provide needed flow rate to each heat pump at any given time, and with less pumping energy use than the two conventional controls. Finally, a typical distributed GSHP system was studied to evaluate the energy saving potential of applying the flow-demand-based pumping control strategy. This case study shows that the annual pumping energy consumption can be reduced by 62% using the flow-demand-based control compared with that using the conventional pressure-based control to maintain a constant differential pressure a cross the supply and return mains.« less

Blockchain Based Decentralized Management of Demand Response Programs in Smart Energy Grids.

PubMed

Pop, Claudia; Cioara, Tudor; Antal, Marcel; Anghel, Ionut; Salomie, Ioan; Bertoncini, Massimo

2018-01-09

In this paper, we investigate the use of decentralized blockchain mechanisms for delivering transparent, secure, reliable, and timely energy flexibility, under the form of adaptation of energy demand profiles of Distributed Energy Prosumers, to all the stakeholders involved in the flexibility markets (Distribution System Operators primarily, retailers, aggregators, etc.). In our approach, a blockchain based distributed ledger stores in a tamper proof manner the energy prosumption information collected from Internet of Things smart metering devices, while self-enforcing smart contracts programmatically define the expected energy flexibility at the level of each prosumer, the associated rewards or penalties, and the rules for balancing the energy demand with the energy production at grid level. Consensus based validation will be used for demand response programs validation and to activate the appropriate financial settlement for the flexibility providers. The approach was validated using a prototype implemented in an Ethereum platform using energy consumption and production traces of several buildings from literature data sets. The results show that our blockchain based distributed demand side management can be used for matching energy demand and production at smart grid level, the demand response signal being followed with high accuracy, while the amount of energy flexibility needed for convergence is reduced.

An access control model with high security for distributed workflow and real-time application

NASA Astrophysics Data System (ADS)

Han, Ruo-Fei; Wang, Hou-Xiang

2007-11-01

The traditional mandatory access control policy (MAC) is regarded as a policy with strict regulation and poor flexibility. The security policy of MAC is so compelling that few information systems would adopt it at the cost of facility, except some particular cases with high security requirement as military or government application. However, with the increasing requirement for flexibility, even some access control systems in military application have switched to role-based access control (RBAC) which is well known as flexible. Though RBAC can meet the demands for flexibility but it is weak in dynamic authorization and consequently can not fit well in the workflow management systems. The task-role-based access control (T-RBAC) is then introduced to solve the problem. It combines both the advantages of RBAC and task-based access control (TBAC) which uses task to manage permissions dynamically. To satisfy the requirement of system which is distributed, well defined with workflow process and critically for time accuracy, this paper will analyze the spirit of MAC, introduce it into the improved T&RBAC model which is based on T-RBAC. At last, a conceptual task-role-based access control model with high security for distributed workflow and real-time application (A_T&RBAC) is built, and its performance is simply analyzed.

Water quality modeling in the dead end sections of drinking water (Supplement)

EPA Pesticide Factsheets

Dead-end sections of drinking water distribution networks are known to be problematic zones in terms of water quality degradation. Extended residence time due to water stagnation leads to rapid reduction of disinfectant residuals allowing the regrowth of microbial pathogens. Water quality models developed so far apply spatial aggregation and temporal averaging techniques for hydraulic parameters by assigning hourly averaged water demands to the main nodes of the network. Although this practice has generally resulted in minimal loss of accuracy for the predicted disinfectant concentrations in main water transmission lines, this is not the case for the peripheries of the distribution network. This study proposes a new approach for simulating disinfectant residuals in dead end pipes while accounting for both spatial and temporal variability in hydraulic and transport parameters. A stochastic demand generator was developed to represent residential water pulses based on a non-homogenous Poisson process. Dispersive solute transport was considered using highly dynamic dispersion rates. A genetic algorithm was used tocalibrate the axial hydraulic profile of the dead-end pipe based on the different demand shares of the withdrawal nodes. A parametric sensitivity analysis was done to assess the model performance under variation of different simulation parameters. A group of Monte-Carlo ensembles was carried out to investigate the influence of spatial and temporal variation

Water Quality Modeling in the Dead End Sections of Drinking ...

EPA Pesticide Factsheets

Dead-end sections of drinking water distribution networks are known to be problematic zones in terms of water quality degradation. Extended residence time due to water stagnation leads to rapid reduction of disinfectant residuals allowing the regrowth of microbial pathogens. Water quality models developed so far apply spatial aggregation and temporal averaging techniques for hydraulic parameters by assigning hourly averaged water demands to the main nodes of the network. Although this practice has generally resulted in minimal loss of accuracy for the predicted disinfectant concentrations in main water transmission lines, this is not the case for the peripheries of a distribution network. This study proposes a new approach for simulating disinfectant residuals in dead end pipes while accounting for both spatial and temporal variability in hydraulic and transport parameters. A stochastic demand generator was developed to represent residential water pulses based on a non-homogenous Poisson process. Dispersive solute transport was considered using highly dynamic dispersion rates. A genetic algorithm was used to calibrate the axial hydraulic profile of the dead-end pipe based on the different demand shares of the withdrawal nodes. A parametric sensitivity analysis was done to assess the model performance under variation of different simulation parameters. A group of Monte-Carlo ensembles was carried out to investigate the influence of spatial and temporal variations

Human factors and safety in emergency medicine

NASA Technical Reports Server (NTRS)

Schaefer, H. G.; Helmreich, R. L.; Scheidegger, D.

1994-01-01

A model based on an input process and outcome conceptualisation is suggested to address safety-relevant factors in emergency medicine. As shown in other dynamic and demanding environments, human factors play a decisive role in attaining high quality service. Attitudes held by health-care providers, organisational shells and work-cultural parameters determine communication, conflict resolution and workload distribution within and between teams. These factors should be taken into account to improve outcomes such as operational integrity, job satisfaction and morale.

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

PubMed

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

2016-07-25

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

Joint Real-Time Energy and Demand-Response Management using a Hybrid Coalitional-Noncooperative Game

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

He, Fulin; Gu, Yi; Hao, Jun

In order to model the interactions among utility companies, building demands and renewable energy generators (REGs), a hybrid coalitional-noncooperative game framework has been proposed. We formulate a dynamic non-cooperative game to study the energy dispatch within multiple utility companies, while we take a coalitional perspective on REGs and buildings demands through a hedonic coalition formation game approach. In this case, building demands request different power supply from REGs, then the building demands can be organized into an ultimate coalition structure through a distributed hedonic shift algorithm. At the same time, utility companies can also obtain a stable power generation profile.more » In addition, the interactive progress among the utility companies and building demands which cannot be supplied by REGs is implemented by distributed game theoretic algorithms. Numerical results illustrate that the proposed hybrid coalitional-noncooperative game scheme reduces the cost of both building demands and utility companies compared with the initial scene.« less

Electrical utilities model for determining electrical distribution capacity

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

Fritz, R. L.

1997-09-03

In its simplest form, this model was to obtain meaningful data on the current state of the Site`s electrical transmission and distribution assets, and turn this vast collection of data into useful information. The resulting product is an Electrical Utilities Model for Determining Electrical Distribution Capacity which provides: current state of the electrical transmission and distribution systems; critical Hanford Site needs based on outyear planning documents; decision factor model. This model will enable Electrical Utilities management to improve forecasting requirements for service levels, budget, schedule, scope, and staffing, and recommend the best path forward to satisfy customer demands at themore » minimum risk and least cost to the government. A dynamic document, the model will be updated annually to reflect changes in Hanford Site activities.« less

Supply based on demand dynamical model

NASA Astrophysics Data System (ADS)

Levi, Asaf; Sabuco, Juan; Sanjuán, Miguel A. F.

2018-04-01

We propose and numerically analyze a simple dynamical model that describes the firm behaviors under uncertainty of demand. Iterating this simple model and varying some parameter values, we observe a wide variety of market dynamics such as equilibria, periodic, and chaotic behaviors. Interestingly, the model is also able to reproduce market collapses.

The dynamics of total outputs of Indonesian industrial sectors: A further study

NASA Astrophysics Data System (ADS)

Zuhdi, Ubaidillah

2017-03-01

The purpose of the current study is to extend the previous studies which analyze the impacts of final demands modifications on the total outputs of industrial sectors of a particular country. More specifically, the study conducts the analysis regarding the impacts on the total outputs of Indonesian industrial sectors. The study employs a demand-pull Input-Output (IO) quantity model, one of the calculation instruments in the IO analysis. The study focuses on seventeen industries. There are two scenarios used in this study, namely other final demands and import modifications. The “whole sector change” condition is implemented in the calculations. An initial period in this study is 2010. The results show that the positive impacts on the total outputs of focused sectors are distributed by scenario 1, the change of other final demands. On the contrary, the negative impacts are delivered by scenario 2, the modification of imports. The suggestions for improving the total outputs of discussed industries are based on the results.

Distributed control system for demand response by servers

NASA Astrophysics Data System (ADS)

Hall, Joseph Edward

Within the broad topical designation of smart grid, research in demand response, or demand-side management, focuses on investigating possibilities for electrically powered devices to adapt their power consumption patterns to better match generation and more efficiently integrate intermittent renewable energy sources, especially wind. Devices such as battery chargers, heating and cooling systems, and computers can be controlled to change the time, duration, and magnitude of their power consumption while still meeting workload constraints such as deadlines and rate of throughput. This thesis presents a system by which a computer server, or multiple servers in a data center, can estimate the power imbalance on the electrical grid and use that information to dynamically change the power consumption as a service to the grid. Implementation on a testbed demonstrates the system with a hypothetical but realistic usage case scenario of an online video streaming service in which there are workloads with deadlines (high-priority) and workloads without deadlines (low-priority). The testbed is implemented with real servers, estimates the power imbalance from the grid frequency with real-time measurements of the live outlet, and uses a distributed, real-time algorithm to dynamically adjust the power consumption of the servers based on the frequency estimate and the throughput of video transcoder workloads. Analysis of the system explains and justifies multiple design choices, compares the significance of the system in relation to similar publications in the literature, and explores the potential impact of the system.

Blockchain Based Decentralized Management of Demand Response Programs in Smart Energy Grids

PubMed Central

Pop, Claudia; Cioara, Tudor; Antal, Marcel; Anghel, Ionut; Salomie, Ioan; Bertoncini, Massimo

2018-01-01

In this paper, we investigate the use of decentralized blockchain mechanisms for delivering transparent, secure, reliable, and timely energy flexibility, under the form of adaptation of energy demand profiles of Distributed Energy Prosumers, to all the stakeholders involved in the flexibility markets (Distribution System Operators primarily, retailers, aggregators, etc.). In our approach, a blockchain based distributed ledger stores in a tamper proof manner the energy prosumption information collected from Internet of Things smart metering devices, while self-enforcing smart contracts programmatically define the expected energy flexibility at the level of each prosumer, the associated rewards or penalties, and the rules for balancing the energy demand with the energy production at grid level. Consensus based validation will be used for demand response programs validation and to activate the appropriate financial settlement for the flexibility providers. The approach was validated using a prototype implemented in an Ethereum platform using energy consumption and production traces of several buildings from literature data sets. The results show that our blockchain based distributed demand side management can be used for matching energy demand and production at smart grid level, the demand response signal being followed with high accuracy, while the amount of energy flexibility needed for convergence is reduced. PMID:29315250

Autonomous Information Fading and Provision to Achieve High Response Time in Distributed Information Systems

NASA Astrophysics Data System (ADS)

Lu, Xiaodong; Arfaoui, Helene; Mori, Kinji

In highly dynamic electronic commerce environment, the need for adaptability and rapid response time to information service systems has become increasingly important. In order to cope with the continuously changing conditions of service provision and utilization, Faded Information Field (FIF) has been proposed. FIF is a distributed information service system architecture, sustained by push/pull mobile agents to bring high-assurance of services through a recursive demand-oriented provision of the most popular information closer to the users to make a tradeoff between the cost of information service allocation and access. In this paper, based on the analysis of the relationship that exists among the users distribution, information provision and access time, we propose the technology for FIF design to resolve the competing requirements of users and providers to improve users' access time. In addition, to achieve dynamic load balancing with changing users preference, the autonomous information reallocation technology is proposed. We proved the effectiveness of the proposed technology through the simulation and comparison with the conventional system.

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.

A Community-Based Approach to Leading the Nation in Smart Energy Use

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

None, None

2013-12-31

Project Objectives The AEP Ohio gridSMART® Demonstration Project (Project) achieved the following objectives: • Built a secure, interoperable, and integrated smart grid infrastructure in northeast central Ohio that demonstrated the ability to maximize distribution system efficiency and reliability and consumer use of demand response programs that reduced energy consumption, peak demand, and fossil fuel emissions. • Actively attracted, educated, enlisted, and retained consumers in innovative business models that provided tools and information reducing consumption and peak demand. • Provided the U.S. Department of Energy (DOE) information to evaluate technologies and preferred smart grid business models to be extended nationally. Projectmore » Description Ohio Power Company (the surviving company of a merger with Columbus Southern Power Company), doing business as AEP Ohio (AEP Ohio), took a community-based approach and incorporated a full suite of advanced smart grid technologies for 110,000 consumers in an area selected for its concentration and diversity of distribution infrastructure and consumers. It was organized and aligned around: • Technology, implementation, and operations • Consumer and stakeholder acceptance • Data management and benefit assessment Combined, these functional areas served as the foundation of the Project to integrate commercially available products, innovative technologies, and new consumer products and services within a secure two-way communication network between the utility and consumers. The Project included Advanced Metering Infrastructure (AMI), Distribution Management System (DMS), Distribution Automation Circuit Reconfiguration (DACR), Volt VAR Optimization (VVO), and Consumer Programs (CP). These technologies were combined with two-way consumer communication and information sharing, demand response, dynamic pricing, and consumer products, such as plug-in electric vehicles and smart appliances. In addition, the Project incorporated comprehensive cyber security capabilities, interoperability, and a data assessment that, with grid simulation capabilities, made the demonstration results an adaptable, integrated solution for AEP Ohio and the nation.« less

Advancing Underwater Acoustic Communication for Autonomous Distributed Networks via Sparse Channel Sensing, Coding, and Navigation Support

DTIC Science & Technology

2014-09-30

underwater acoustic communication technologies for autonomous distributed underwater networks , through innovative signal processing, coding, and...4. TITLE AND SUBTITLE Advancing Underwater Acoustic Communication for Autonomous Distributed Networks via Sparse Channel Sensing, Coding, and...coding: 3) OFDM modulated dynamic coded cooperation in underwater acoustic channels; 3 Localization, Networking , and Testbed: 4) On-demand

Energy management and cooperation in microgrids

NASA Astrophysics Data System (ADS)

Rahbar, Katayoun

Microgrids are key components of future smart power grids, which integrate distributed renewable energy generators to efficiently serve the load demand locally. However, random and intermittent characteristics of renewable energy generations may hinder the reliable operation of microgrids. This thesis is thus devoted to investigating new strategies for microgrids to optimally manage their energy consumption, energy storage system (ESS) and cooperation in real time to achieve the reliable and cost-effective operation. This thesis starts with a single microgrid system. The optimal energy scheduling and ESS management policy is derived to minimize the energy cost of the microgrid resulting from drawing conventional energy from the main grid under both the off-line and online setups, where the renewable energy generation/load demand are assumed to be non-causally known and causally known at the microgrid, respectively. The proposed online algorithm is designed based on the optimal off-line solution and works under arbitrary (even unknown) realizations of future renewable energy generation/load demand. Therefore, it is more practically applicable as compared to solutions based on conventional techniques such as dynamic programming and stochastic programming that require the prior knowledge of renewable energy generation and load demand realizations/distributions. Next, for a group of microgrids that cooperate in energy management, we study efficient methods for sharing energy among them for both fully and partially cooperative scenarios, where microgrids are of common interests and self-interested, respectively. For the fully cooperative energy management, the off-line optimization problem is first formulated and optimally solved, where a distributed algorithm is proposed to minimize the total (sum) energy cost of microgrids. Inspired by the results obtained from the off-line optimization, efficient online algorithms are proposed for the real-time energy management, which are of low complexity and work given arbitrary realizations of renewable energy generation/load demand. On the other hand, for self-interested microgrids, the partially cooperative energy management is formulated and a distributed algorithm is proposed to optimize the energy cooperation such that energy costs of individual microgrids reduce simultaneously over the case without energy cooperation while limited information is shared among the microgrids and the central controller.

Distribution network design under demand uncertainty using genetic algorithm and Monte Carlo simulation approach: a case study in pharmaceutical industry

NASA Astrophysics Data System (ADS)

Izadi, Arman; Kimiagari, Ali mohammad

2014-01-01

Distribution network design as a strategic decision has long-term effect on tactical and operational supply chain management. In this research, the location-allocation problem is studied under demand uncertainty. The purposes of this study were to specify the optimal number and location of distribution centers and to determine the allocation of customer demands to distribution centers. The main feature of this research is solving the model with unknown demand function which is suitable with the real-world problems. To consider the uncertainty, a set of possible scenarios for customer demands is created based on the Monte Carlo simulation. The coefficient of variation of costs is mentioned as a measure of risk and the most stable structure for firm's distribution network is defined based on the concept of robust optimization. The best structure is identified using genetic algorithms and 14% reduction in total supply chain costs is the outcome. Moreover, it imposes the least cost variation created by fluctuation in customer demands (such as epidemic diseases outbreak in some areas of the country) to the logistical system. It is noteworthy that this research is done in one of the largest pharmaceutical distribution firms in Iran.

Distribution network design under demand uncertainty using genetic algorithm and Monte Carlo simulation approach: a case study in pharmaceutical industry

NASA Astrophysics Data System (ADS)

Izadi, Arman; Kimiagari, Ali Mohammad

2014-05-01

Distribution network design as a strategic decision has long-term effect on tactical and operational supply chain management. In this research, the location-allocation problem is studied under demand uncertainty. The purposes of this study were to specify the optimal number and location of distribution centers and to determine the allocation of customer demands to distribution centers. The main feature of this research is solving the model with unknown demand function which is suitable with the real-world problems. To consider the uncertainty, a set of possible scenarios for customer demands is created based on the Monte Carlo simulation. The coefficient of variation of costs is mentioned as a measure of risk and the most stable structure for firm's distribution network is defined based on the concept of robust optimization. The best structure is identified using genetic algorithms and 14 % reduction in total supply chain costs is the outcome. Moreover, it imposes the least cost variation created by fluctuation in customer demands (such as epidemic diseases outbreak in some areas of the country) to the logistical system. It is noteworthy that this research is done in one of the largest pharmaceutical distribution firms in Iran.

Intelligent and robust optimization frameworks for smart grids

NASA Astrophysics Data System (ADS)

Dhansri, Naren Reddy

A smart grid implies a cyberspace real-time distributed power control system to optimally deliver electricity based on varying consumer characteristics. Although smart grids solve many of the contemporary problems, they give rise to new control and optimization problems with the growing role of renewable energy sources such as wind or solar energy. Under highly dynamic nature of distributed power generation and the varying consumer demand and cost requirements, the total power output of the grid should be controlled such that the load demand is met by giving a higher priority to renewable energy sources. Hence, the power generated from renewable energy sources should be optimized while minimizing the generation from non renewable energy sources. This research develops a demand-based automatic generation control and optimization framework for real-time smart grid operations by integrating conventional and renewable energy sources under varying consumer demand and cost requirements. Focusing on the renewable energy sources, the intelligent and robust control frameworks optimize the power generation by tracking the consumer demand in a closed-loop control framework, yielding superior economic and ecological benefits and circumvent nonlinear model complexities and handles uncertainties for superior real-time operations. The proposed intelligent system framework optimizes the smart grid power generation for maximum economical and ecological benefits under an uncertain renewable wind energy source. The numerical results demonstrate that the proposed framework is a viable approach to integrate various energy sources for real-time smart grid implementations. The robust optimization framework results demonstrate the effectiveness of the robust controllers under bounded power plant model uncertainties and exogenous wind input excitation while maximizing economical and ecological performance objectives. Therefore, the proposed framework offers a new worst-case deterministic optimization algorithm for smart grid automatic generation control.

Dynamic Price Vector Formation Model-Based Automatic Demand Response Strategy for PV-Assisted EV Charging Stations

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

Chen, Qifang; Wang, Fei; Hodge, Bri-Mathias

A real-time price (RTP)-based automatic demand response (ADR) strategy for PV-assisted electric vehicle (EV) Charging Station (PVCS) without vehicle to grid is proposed. The charging process is modeled as a dynamic linear program instead of the normal day-ahead and real-time regulation strategy, to capture the advantages of both global and real-time optimization. Different from conventional price forecasting algorithms, a dynamic price vector formation model is proposed based on a clustering algorithm to form an RTP vector for a particular day. A dynamic feasible energy demand region (DFEDR) model considering grid voltage profiles is designed to calculate the lower and uppermore » bounds. A deduction method is proposed to deal with the unknown information of future intervals, such as the actual stochastic arrival and departure times of EVs, which make the DFEDR model suitable for global optimization. Finally, both the comparative cases articulate the advantages of the developed methods and the validity in reducing electricity costs, mitigating peak charging demand, and improving PV self-consumption of the proposed strategy are verified through simulation scenarios.« less

Fuzzy Energy Management for a Catenary-Battery-Ultracapacitor based Hybrid Tramway

NASA Astrophysics Data System (ADS)

Jibin, Yang; Jiye, Zhang; Pengyun, Song

2017-05-01

In this paper, an energy management strategy (EMS) based on fuzzy logic control for a catenary-battery-ultracapacitor powered hybrid modern tramway was presented. The fuzzy logic controller for the catenary zone and catenary-less zone was respectively designed by analyzing the structure and working mode of the hybrid system, then an energy management strategy based on double fuzzy logic control was proposed to enhance the fuel economy. The hybrid modern tramway simulation model was developed based on MATLAB/Simulink environment. The simulation results show that the proposed EMS can satisfy the demand of dynamic performance of the tramway and achieve the power distribution reasonably between the each power source.

Flexible Demand Management under Time-Varying Prices

NASA Astrophysics Data System (ADS)

Liang, Yong

In this dissertation, the problem of flexible demand management under time-varying prices is studied. This generic problem has many applications, which usually have multiple periods in which decisions on satisfying demand need to be made, and prices in these periods are time-varying. Examples of such applications include multi-period procurement problem, operating room scheduling, and user-end demand scheduling in the Smart Grid, where the last application is used as the main motivating story throughout the dissertation. The current grid is experiencing an upgrade with lots of new designs. What is of particular interest is the idea of passing time-varying prices that reflect electricity market conditions to end users as incentives for load shifting. One key component, consequently, is the demand management system at the user-end. The objective of the system is to find the optimal trade-off between cost saving and discomfort increment resulted from load shifting. In this dissertation, we approach this problem from the following aspects: (1) construct a generic model, solve for Pareto optimal solutions, and analyze the robust solution that optimizes the worst-case payoffs, (2) extend to a distribution-free model for multiple types of demand (appliances), for which an approximate dynamic programming (ADP) approach is developed, and (3) design other efficient algorithms for practical purposes of the flexible demand management system. We first construct a novel multi-objective flexible demand management model, in which there are a finite number of periods with time-varying prices, and demand arrives in each period. In each period, the decision maker chooses to either satisfy or defer outstanding demand to minimize costs and discomfort over a certain number of periods. We consider both the deterministic model, models with stochastic demand or prices, and when only partial information about the stochastic demand or prices is known. We first analyze the stochastic optimization problem when the objective is to minimize the expected total cost and discomfort, then since the decision maker is likely to be risk-averse, and she wants to protect herself from price spikes, we study the robust optimization problem to address the risk-aversion of the decision maker. We conduct numerical studies to evaluate the price of robustness. Next, we present a detailed model that manages multiple types of flexible demand in the absence of knowledge regarding the distributions of related stochastic processes. Specifically, we consider the case in which time-varying prices with general structures are offered to users, and an energy management system for each household makes optimal energy usage, storage, and trading decisions according to the preferences of users. Because of the uncertainties associated with electricity prices, local generation, and the arrival processes of demand, we formulate a stochastic dynamic programming model, and outline a novel and tractable ADP approach to overcome the curses of dimensionality. Then, we perform numerical studies, whose results demonstrate the effectiveness of the ADP approach. At last, we propose another approximation approach based on Q-learning. In addition, we also develop another decentralization-based heuristic. Both the Q-learning approach and the heuristic make necessary assumptions on the knowledge of information, and each of them has unique advantages. We conduct numerical studies on a testing problem. The simulation results show that both the Q-learning and the decentralization based heuristic approaches work well. Lastly, we conclude the paper with some discussions on future extension directions.

An estimation of distribution method for infrared target detection based on Copulas

NASA Astrophysics Data System (ADS)

Wang, Shuo; Zhang, Yiqun

2015-10-01

Track-before-detect (TBD) based target detection involves a hypothesis test of merit functions which measure each track as a possible target track. Its accuracy depends on the precision of the distribution of merit functions, which determines the threshold for a test. Generally, merit functions are regarded Gaussian, and on this basis the distribution is estimated, which is true for most methods such as the multiple hypothesis tracking (MHT). However, merit functions for some other methods such as the dynamic programming algorithm (DPA) are non-Guassian and cross-correlated. Since existing methods cannot reasonably measure the correlation, the exact distribution can hardly be estimated. If merit functions are assumed Guassian and independent, the error between an actual distribution and its approximation may occasionally over 30 percent, and is divergent by propagation. Hence, in this paper, we propose a novel estimation of distribution method based on Copulas, by which the distribution can be estimated precisely, where the error is less than 1 percent without propagation. Moreover, the estimation merely depends on the form of merit functions and the structure of a tracking algorithm, and is invariant to measurements. Thus, the distribution can be estimated in advance, greatly reducing the demand for real-time calculation of distribution functions.

A two-stage stochastic optimization model for scheduling electric vehicle charging loads to relieve distribution-system constraints

DOE PAGES

Wu, Fei; Sioshansi, Ramteen

2017-05-25

Electric vehicles (EVs) hold promise to improve the energy efficiency and environmental impacts of transportation. However, widespread EV use can impose significant stress on electricity-distribution systems due to their added charging loads. This paper proposes a centralized EV charging-control model, which schedules the charging of EVs that have flexibility. This flexibility stems from EVs that are parked at the charging station for a longer duration of time than is needed to fully recharge the battery. The model is formulated as a two-stage stochastic optimization problem. The model captures the use of distributed energy resources and uncertainties around EV arrival timesmore » and charging demands upon arrival, non-EV loads on the distribution system, energy prices, and availability of energy from the distributed energy resources. We use a Monte Carlo-based sample-average approximation technique and an L-shaped method to solve the resulting optimization problem efficiently. We also apply a sequential sampling technique to dynamically determine the optimal size of the randomly sampled scenario tree to give a solution with a desired quality at minimal computational cost. Here, we demonstrate the use of our model on a Central-Ohio-based case study. We show the benefits of the model in reducing charging costs, negative impacts on the distribution system, and unserved EV-charging demand compared to simpler heuristics. Lastly, we also conduct sensitivity analyses, to show how the model performs and the resulting costs and load profiles when the design of the station or EV-usage parameters are changed.« less

Hierarchical control framework for integrated coordination between distributed energy resources and demand response

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

Wu, Di; Lian, Jianming; Sun, Yannan

Demand response is representing a significant but largely untapped resource that can greatly enhance the flexibility and reliability of power systems. In this paper, a hierarchical control framework is proposed to facilitate the integrated coordination between distributed energy resources and demand response. The proposed framework consists of coordination and device layers. In the coordination layer, various resource aggregations are optimally coordinated in a distributed manner to achieve the system-level objectives. In the device layer, individual resources are controlled in real time to follow the optimal power generation or consumption dispatched from the coordination layer. For the purpose of practical applications,more » a method is presented to determine the utility functions of controllable loads by taking into account the real-time load dynamics and the preferences of individual customers. The effectiveness of the proposed framework is validated by detailed simulation studies.« less

Power management and frequency regulation for microgrid and smart grid: A real-time demand response approach

NASA Astrophysics Data System (ADS)

Pourmousavi Kani, Seyyed Ali

Future power systems (known as smart grid) will experience a high penetration level of variable distributed energy resources to bring abundant, affordable, clean, efficient, and reliable electric power to all consumers. However, it might suffer from the uncertain and variable nature of these generations in terms of reliability and especially providing required balancing reserves. In the current power system structure, balancing reserves (provided by spinning and non-spinning power generation units) usually are provided by conventional fossil-fueled power plants. However, such power plants are not the favorite option for the smart grid because of their low efficiency, high amount of emissions, and expensive capital investments on transmission and distribution facilities, to name a few. Providing regulation services in the presence of variable distributed energy resources would be even more difficult for islanded microgrids. The impact and effectiveness of demand response are still not clear at the distribution and transmission levels. In other words, there is no solid research reported in the literature on the evaluation of the impact of DR on power system dynamic performance. In order to address these issues, a real-time demand response approach along with real-time power management (specifically for microgrids) is proposed in this research. The real-time demand response solution is utilized at the transmission (through load-frequency control model) and distribution level (both in the islanded and grid-tied modes) to provide effective and fast regulation services for the stable operation of the power system. Then, multiple real-time power management algorithms for grid-tied and islanded microgrids are proposed to economically and effectively operate microgrids. Extensive dynamic modeling of generation, storage, and load as well as different controller design are considered and developed throughout this research to provide appropriate models and simulation environment to evaluate the effectiveness of the proposed methodologies. Simulation results revealed the effectiveness of the proposed methods in providing balancing reserves and microgrids' economic and stable operation. The proposed tools and approaches can significantly enhance the application of microgrids and demand response in the smart grid era. They will also help to increase the penetration level of variable distributed generation resources in the smart grid.

Research on strategy and optimization method of PRT empty vehicles resource allocation based on traffic demand forecast

NASA Astrophysics Data System (ADS)

Xiang, Yu; Tao, Cheng

2018-05-01

During the operation of the personal rapid transit system(PRT), the empty vehicle resources is distributed unevenly because of different passenger demand. In order to maintain the balance between supply and demand, and to meet the passenger needs of the ride, PRT empty vehicle resource allocation model is constructed based on the future demand forecasted by historical demand in this paper. The improved genetic algorithm is implied in distribution of the empty vehicle which can reduce the customers waiting time and improve the operation efficiency of the PRT system so that all passengers can take the PRT vehicles in the shortest time. The experimental result shows that the improved genetic algorithm can allocate the empty vehicle from the system level optimally, and realize the distribution of the empty vehicle resources reasonably in the system.

Spatiotemporal Dynamics and Fitness Analysis of Global Oil Market: Based on Complex Network

PubMed Central

Wang, Minggang; Fang, Guochang; Shao, Shuai

2016-01-01

We study the overall topological structure properties of global oil trade network, such as degree, strength, cumulative distribution, information entropy and weight clustering. The structural evolution of the network is investigated as well. We find the global oil import and export networks do not show typical scale-free distribution, but display disassortative property. Furthermore, based on the monthly data of oil import values during 2005.01–2014.12, by applying random matrix theory, we investigate the complex spatiotemporal dynamic from the country level and fitness evolution of the global oil market from a demand-side analysis. Abundant information about global oil market can be obtained from deviating eigenvalues. The result shows that the oil market has experienced five different periods, which is consistent with the evolution of country clusters. Moreover, we find the changing trend of fitness function agrees with that of gross domestic product (GDP), and suggest that the fitness evolution of oil market can be predicted by forecasting GDP values. To conclude, some suggestions are provided according to the results. PMID:27706147

Pollution source localization in an urban water supply network based on dynamic water demand.

PubMed

Yan, Xuesong; Zhu, Zhixin; Li, Tian

2017-10-27

Urban water supply networks are susceptible to intentional, accidental chemical, and biological pollution, which pose a threat to the health of consumers. In recent years, drinking-water pollution incidents have occurred frequently, seriously endangering social stability and security. The real-time monitoring for water quality can be effectively implemented by placing sensors in the water supply network. However, locating the source of pollution through the data detection obtained by water quality sensors is a challenging problem. The difficulty lies in the limited number of sensors, large number of water supply network nodes, and dynamic user demand for water, which leads the pollution source localization problem to an uncertainty, large-scale, and dynamic optimization problem. In this paper, we mainly study the dynamics of the pollution source localization problem. Previous studies of pollution source localization assume that hydraulic inputs (e.g., water demand of consumers) are known. However, because of the inherent variability of urban water demand, the problem is essentially a fluctuating dynamic problem of consumer's water demand. In this paper, the water demand is considered to be stochastic in nature and can be described using Gaussian model or autoregressive model. On this basis, an optimization algorithm is proposed based on these two dynamic water demand change models to locate the pollution source. The objective of the proposed algorithm is to find the locations and concentrations of pollution sources that meet the minimum between the analogue and detection values of the sensor. Simulation experiments were conducted using two different sizes of urban water supply network data, and the experimental results were compared with those of the standard genetic algorithm.

Mitochondrial dynamics in the regulation of neurogenesis: From development to the adult brain.

PubMed

Khacho, Mireille; Slack, Ruth S

2018-01-01

Mitochondria are classically known to be the cellular energy producers, but a renewed appreciation for these organelles has developed with the accumulating discoveries of additional functions. The importance of mitochondria within the brain has been long known, particularly given the high-energy demanding nature of neurons. The energy demands imposed by neurons require the well-orchestrated morphological adaptation and distribution of mitochondria. Recent studies now reveal the importance of mitochondrial dynamics not only in mature neurons but also during neural development, particularly during the process of neurogenesis and neural stem cell fate decisions. In this review, we will highlight the recent findings that illustrate the importance of mitochondrial dynamics in neurodevelopment and neural stem cell function. Developmental Dynamics 247:47-53, 2018. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

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).

Experimental evaluation of four ground-motion scaling methods for dynamic response-history analysis of nonlinear structures

USGS Publications Warehouse

O'Donnell, Andrew P.; Kurama, Yahya C.; Kalkan, Erol; Taflanidis, Alexandros A.

2017-01-01

This paper experimentally evaluates four methods to scale earthquake ground-motions within an ensemble of records to minimize the statistical dispersion and maximize the accuracy in the dynamic peak roof drift demand and peak inter-story drift demand estimates from response-history analyses of nonlinear building structures. The scaling methods that are investigated are based on: (1) ASCE/SEI 7–10 guidelines; (2) spectral acceleration at the fundamental (first mode) period of the structure, Sa(T1); (3) maximum incremental velocity, MIV; and (4) modal pushover analysis. A total of 720 shake-table tests of four small-scale nonlinear building frame specimens with different static and dynamic characteristics are conducted. The peak displacement demands from full suites of 36 near-fault ground-motion records as well as from smaller “unbiased” and “biased” design subsets (bins) of ground-motions are included. Out of the four scaling methods, ground-motions scaled to the median MIV of the ensemble resulted in the smallest dispersion in the peak roof and inter-story drift demands. Scaling based on MIValso provided the most accurate median demands as compared with the “benchmark” demands for structures with greater nonlinearity; however, this accuracy was reduced for structures exhibiting reduced nonlinearity. The modal pushover-based scaling (MPS) procedure was the only method to conservatively overestimate the median drift demands.

Dynamics of market structure driven by the degree of consumer’s rationality

NASA Astrophysics Data System (ADS)

Yanagita, Tatsuo; Onozaki, Tamotsu

2010-03-01

We study a simple model of market share dynamics with boundedly rational consumers and firms interacting with each other. As the number of consumers is large, we employ a statistical description to represent firms’ distribution of consumer share, which is characterized by a single parameter representing how rationally the mass of consumers pursue higher utility. As the boundedly rational firm does not know the shape of demand function it faces, it revises production and price so as to raise its profit with the aid of a simple reinforcement learning rule. Simulation results show that (1) three phases of market structure, i.e. the uniform share phase, the oligopolistic phase, and the monopolistic phase, appear depending upon how rational consumers are, and (2) in an oligopolistic phase, the market share distribution of firms follows Zipf’s law and the growth-rate distribution of firms follows Gibrat’s law, and (3) an oligopolistic phase is the best state of market in terms of consumers’ utility but brings the minimum profit to the firms because of severe competition based on the moderate rationality of consumers.

Application of a distributed network in computational fluid dynamic simulations

NASA Technical Reports Server (NTRS)

Deshpande, Manish; Feng, Jinzhang; Merkle, Charles L.; Deshpande, Ashish

1994-01-01

A general-purpose 3-D, incompressible Navier-Stokes algorithm is implemented on a network of concurrently operating workstations using parallel virtual machine (PVM) and compared with its performance on a CRAY Y-MP and on an Intel iPSC/860. The problem is relatively computationally intensive, and has a communication structure based primarily on nearest-neighbor communication, making it ideally suited to message passing. Such problems are frequently encountered in computational fluid dynamics (CDF), and their solution is increasingly in demand. The communication structure is explicitly coded in the implementation to fully exploit the regularity in message passing in order to produce a near-optimal solution. Results are presented for various grid sizes using up to eight processors.

Optimal Power Scheduling for a Medium Voltage AC/DC Hybrid Distribution Network

DOE PAGES

Zhu, Zhenshan; Liu, Dichen; Liao, Qingfen; ...

2018-01-26

With the great increase of renewable generation as well as the DC loads in the distribution network; DC distribution technology is receiving more attention; since the DC distribution network can improve operating efficiency and power quality by reducing the energy conversion stages. This paper presents a new architecture for the medium voltage AC/DC hybrid distribution network; where the AC and DC subgrids are looped by normally closed AC soft open point (ACSOP) and DC soft open point (DCSOP); respectively. The proposed AC/DC hybrid distribution systems contain renewable generation (i.e., wind power and photovoltaic (PV) generation); energy storage systems (ESSs); softmore » open points (SOPs); and both AC and DC flexible demands. An energy management strategy for the hybrid system is presented based on the dynamic optimal power flow (DOPF) method. The main objective of the proposed power scheduling strategy is to minimize the operating cost and reduce the curtailment of renewable generation while meeting operational and technical constraints. The proposed approach is verified in five scenarios. The five scenarios are classified as pure AC system; hybrid AC/DC system; hybrid system with interlinking converter; hybrid system with DC flexible demand; and hybrid system with SOPs. Results show that the proposed scheduling method can successfully dispatch the controllable elements; and that the presented architecture for the AC/DC hybrid distribution system is beneficial for reducing operating cost and renewable generation curtailment.« less

Optimal Power Scheduling for a Medium Voltage AC/DC Hybrid Distribution Network

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

Zhu, Zhenshan; Liu, Dichen; Liao, Qingfen

With the great increase of renewable generation as well as the DC loads in the distribution network; DC distribution technology is receiving more attention; since the DC distribution network can improve operating efficiency and power quality by reducing the energy conversion stages. This paper presents a new architecture for the medium voltage AC/DC hybrid distribution network; where the AC and DC subgrids are looped by normally closed AC soft open point (ACSOP) and DC soft open point (DCSOP); respectively. The proposed AC/DC hybrid distribution systems contain renewable generation (i.e., wind power and photovoltaic (PV) generation); energy storage systems (ESSs); softmore » open points (SOPs); and both AC and DC flexible demands. An energy management strategy for the hybrid system is presented based on the dynamic optimal power flow (DOPF) method. The main objective of the proposed power scheduling strategy is to minimize the operating cost and reduce the curtailment of renewable generation while meeting operational and technical constraints. The proposed approach is verified in five scenarios. The five scenarios are classified as pure AC system; hybrid AC/DC system; hybrid system with interlinking converter; hybrid system with DC flexible demand; and hybrid system with SOPs. Results show that the proposed scheduling method can successfully dispatch the controllable elements; and that the presented architecture for the AC/DC hybrid distribution system is beneficial for reducing operating cost and renewable generation curtailment.« less

Bifurcation Analysis of a DC-DC Bidirectional Power Converter Operating with Constant Power Loads

NASA Astrophysics Data System (ADS)

Cristiano, Rony; Pagano, Daniel J.; Benadero, Luis; Ponce, Enrique

Direct current (DC) microgrids (MGs) are an emergent option to satisfy new demands for power quality and integration of renewable resources in electrical distribution systems. This work addresses the large-signal stability analysis of a DC-DC bidirectional converter (DBC) connected to a storage device in an islanding MG. This converter is responsible for controlling the balance of power (load demand and generation) under constant power loads (CPLs). In order to control the DC bus voltage through a DBC, we propose a robust sliding mode control (SMC) based on a washout filter. Dynamical systems techniques are exploited to assess the quality of this switching control strategy. In this sense, a bifurcation analysis is performed to study the nonlinear stability of a reduced model of this system. The appearance of different bifurcations when load parameters and control gains are changed is studied in detail. In the specific case of Teixeira Singularity (TS) bifurcation, some experimental results are provided, confirming the mathematical predictions. Both a deeper insight in the dynamic behavior of the controlled system and valuable design criteria are obtained.

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.

Critical capacity, travel time delays and travel time distribution of rapid mass transit systems

NASA Astrophysics Data System (ADS)

Legara, Erika Fille; Monterola, Christopher; Lee, Kee Khoon; Hung, Gih Guang

2014-07-01

We set up a mechanistic agent-based model of a rapid mass transit system. Using empirical data from Singapore's unidentifiable smart fare card, we validate our model by reconstructing actual travel demand and duration of travel statistics. We subsequently use this model to investigate two phenomena that are known to significantly affect the dynamics within the RTS: (1) overloading in trains and (2) overcrowding in the RTS platform. We demonstrate that by varying the loading capacity of trains, a tipping point emerges at which an exponential increase in the duration of travel time delays is observed. We also probe the impact on the rail system dynamics of three types of passenger growth distribution across stations: (i) Dirac delta, (ii) uniform and (iii) geometric, which is reminiscent of the effect of land use on transport. Under the assumption of a fixed loading capacity, we demonstrate the dependence of a given origin-destination (OD) pair on the flow volume of commuters in station platforms.

Microgrid to enable optimal distributed energy retail and end-user demand response

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

Jin, Ming; Feng, Wei; Marnay, Chris

In the face of unprecedented challenges in environmental sustainability and grid resilience, there is an increasingly held consensus regarding the adoption of distributed and renewable energy resources such as microgrids (MGs), and the utilization of flexible electric loads by demand response (DR) to potentially drive a necessary paradigm shift in energy production and consumption patterns. However, the potential value of distributed generation and demand flexibility has not yet been fully realized in the operation of MGs. This study investigates the pricing and operation strategy with DR for a MG retailer in an integrated energy system (IES). Based on co-optimizing retailmore » rates and MG dispatch formulated as a mixed integer quadratic programming (MIQP) problem, our model devises a dynamic pricing scheme that reflects the cost of generation and promotes DR, in tandem with an optimal dispatch plan that exploits spark spread and facilitates the integration of renewables, resulting in improved retailer profits and system stability. Main issues like integrated energy coupling and customer bill reduction are addressed during pricing to ensure rates competitiveness and customer protection. By evaluating on real datasets, the system is demonstrated to optimally coordinate storage, renewables, and combined heat and power (CHP), reduce carbon dioxide emission while maintaining profits, and effectively alleviate the PV curtailment problem. Finally, the model can be used by retailers and MG operators to optimize their operations, as well as regulators to design new utility rates in support of the ongoing transformation of energy systems.« less

Microgrid to enable optimal distributed energy retail and end-user demand response

DOE PAGES

Jin, Ming; Feng, Wei; Marnay, Chris; ...

2018-06-07

In the face of unprecedented challenges in environmental sustainability and grid resilience, there is an increasingly held consensus regarding the adoption of distributed and renewable energy resources such as microgrids (MGs), and the utilization of flexible electric loads by demand response (DR) to potentially drive a necessary paradigm shift in energy production and consumption patterns. However, the potential value of distributed generation and demand flexibility has not yet been fully realized in the operation of MGs. This study investigates the pricing and operation strategy with DR for a MG retailer in an integrated energy system (IES). Based on co-optimizing retailmore » rates and MG dispatch formulated as a mixed integer quadratic programming (MIQP) problem, our model devises a dynamic pricing scheme that reflects the cost of generation and promotes DR, in tandem with an optimal dispatch plan that exploits spark spread and facilitates the integration of renewables, resulting in improved retailer profits and system stability. Main issues like integrated energy coupling and customer bill reduction are addressed during pricing to ensure rates competitiveness and customer protection. By evaluating on real datasets, the system is demonstrated to optimally coordinate storage, renewables, and combined heat and power (CHP), reduce carbon dioxide emission while maintaining profits, and effectively alleviate the PV curtailment problem. Finally, the model can be used by retailers and MG operators to optimize their operations, as well as regulators to design new utility rates in support of the ongoing transformation of energy systems.« less

2025 California Demand Response Potential Study - Charting California’s Demand Response Future. Final Report on Phase 2 Results

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

Alstone, Peter; Potter, Jennifer; Piette, Mary Ann

California’s legislative and regulatory goals for renewable energy are changing the power grid’s dynamics. Increased variable generation resource penetration connected to the bulk power system, as well as, distributed energy resources (DERs) connected to the distribution system affect the grid’s reliable operation over many different time scales (e.g., days to hours to minutes to seconds). As the state continues this transition, it will require careful planning to ensure resources with the right characteristics are available to meet changing grid management needs. Demand response (DR) has the potential to provide important resources for keeping the electricity grid stable and efficient, tomore » defer upgrades to generation, transmission and distribution systems, and to deliver customer economic benefits. This study estimates the potential size and cost of future DR resources for California’s three investor-owned utilities (IOUs): Pacific Gas and Electric Company (PG&E), Southern California Edison Company (SCE), and San Diego Gas & Electric Company (SDG&E). Our goal is to provide data-driven insights as the California Public Utilities Commission (CPUC) evaluates how to enhance DR’s role in meeting California’s resource planning needs and operational requirements. We address two fundamental questions: 1. What cost-competitive DR service types will meet California’s future grid needs as it moves towards clean energy and advanced infrastructure? 2. What is the size and cost of the expected resource base for the DR service types?« less

Decentralized control of units in smart grids for the support of renewable energy supply

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

Sonnenschein, Michael, E-mail: Michael.Sonnenschein@Uni-Oldenburg.DE; Lünsdorf, Ontje, E-mail: Ontje.Luensdorf@OFFIS.DE; Bremer, Jörg, E-mail: Joerg.Bremer@Uni-Oldenburg.DE

Due to the significant environmental impact of power production from fossil fuels and nuclear fission, future energy systems will increasingly rely on distributed and renewable energy sources (RES). The electrical feed-in from photovoltaic (PV) systems and wind energy converters (WEC) varies greatly both over short and long time periods (from minutes to seasons), and (not only) by this effect the supply of electrical power from RES and the demand for electrical power are not per se matching. In addition, with a growing share of generation capacity especially in distribution grids, the top-down paradigm of electricity distribution is gradually replaced bymore » a bottom-up power supply. This altogether leads to new problems regarding the safe and reliable operation of power grids. In order to address these challenges, the notion of Smart Grids has been introduced. The inherent flexibilities, i.e. the set of feasible power schedules, of distributed power units have to be controlled in order to support demand–supply matching as well as stable grid operation. Controllable power units are e.g. combined heat and power plants, power storage systems such as batteries, and flexible power consumers such as heat pumps. By controlling the flexibilities of these units we are particularly able to optimize the local utilization of RES feed-in in a given power grid by integrating both supply and demand management measures with special respect to the electrical infrastructure. In this context, decentralized systems, autonomous agents and the concept of self-organizing systems will become key elements of the ICT based control of power units. In this contribution, we first show how a decentralized load management system for battery charging/discharging of electrical vehicles (EVs) can increase the locally used share of supply from PV systems in a low voltage grid. For a reliable demand side management of large sets of appliances, dynamic clustering of these appliances into uniformly controlled appliance sets is necessary. We introduce a method for self-organized clustering for this purpose and show how control of such clusters can affect load peaks in distribution grids. Subsequently, we give a short overview on how we are going to expand the idea of self-organized clusters of units into creating a virtual control center for dynamic virtual power plants (DVPP) offering products at a power market. For an efficient organization of DVPPs, the flexibilities of units have to be represented in a compact and easy to use manner. We give an introduction how the problem of representing a set of possibly 10{sup 100} feasible schedules can be solved by a machine-learning approach. In summary, this article provides an overall impression how we use agent based control techniques and methods of self-organization to support the further integration of distributed and renewable energy sources into power grids and energy markets. - Highlights: • Distributed load management for electrical vehicles supports local supply from PV. • Appliances can self-organize into so called virtual appliances for load control. • Dynamic VPPs can be controlled by extensively decentralized control centers. • Flexibilities of units can efficiently be represented by support-vector descriptions.« less

Simulating Residential Demand in Singapore through Five Decades of Demographic Change

NASA Astrophysics Data System (ADS)

Davis, N. R.; Fernández, J.

2011-12-01

Singapore's rapid and well-documented development over the last half-century provides an ideal case for studying urban metabolism. Extensive data [1, 2] facilitate the modeling of historical dynamics of population and resource consumption. This paper presents an agent-based population model that simulates key demographic factors - number, size, and relative income of households - through fifty years of development in Singapore. This is the first step in a broader study linking demographic factors to residential demand for urban land, materials, water, and energy. Previous studies of the resource demands of housing stock have accounted for demographics by modifying the important population driver with a single, aggregated "lifestyle" term [3, 4]. However, demographic changes that result from development can influence the nature of the residential sector, and warrant a closer look. Increasing levels of education and affluence coupled with decreasing birth rates have yielded an aging population and changing family structures in Singapore [5]. These factors all contribute to an increasingly resource-intense residential sector. Singaporeans' elevated per capita income and life expectancy have created demand for larger household area, which means a growing percentage of available land must be dedicated to residential use [6]. While the majority of Singapore's housing is public - a strategy designed to maximize land use efficiency - residents are increasingly seeking private alternatives [7]. In the private sector, lower density housing puts even greater pressure on the finite supply of undeveloped land. Agent-based modeling is used to study the selected aspects of demography. The population is disaggregated into historical time-series distributions of age, family size, education, and income. We propose a simplified methodology correlating average education level with birth rate, and income to categorize households and establish housing unit demand. Aggregated lifestyle variables have proven useful for simulating past resource consumption in some cases, but demographic shifts are important causal factors in future demand that would not be captured by these simple terms. For this reason disaggregated population modeling provides better insight into the size and income distributions of households that ultimately drive residential resource consumption. References [1] Yearbook of Statistics Singapore. Dept. of Statistics, Ministry of Trade & Industry, 1960-2011. [2] HDB Annual Report. Housing & Development Board, Ministry of National Development, 1960-2011. [3] B. Muller, "Stock dynamics for forecasting material flows-case study for housing in the Netherlands," Ecol Econ, vol. 59, no. 1, pp. 142-156, 2006. [4] H. Bergsdal, et al., "Dynamic material flow analysis for Norway's dwelling stock," Build Res Inf, vol. 35, no. 5, pp. 557-570, 2007. [5] D. Phillips and H. Bartlett, "Aging trends-Singapore," J Cross Cult Gerontol, vol. 10, no. 4, pp. 349-356, 1995. [6] T. Wong and A. Yap, Four decades of transformation: Land use in Singapore, 1960-2000. Eastern University Press, 2004. [7] -, "From universal public housing to meeting the increasing aspiration for private housing in Singapore," Habitat Int, vol. 27, no. 3, pp. 361-380, 2003.

An index for plant water deficit based on root-weighted soil water content

NASA Astrophysics Data System (ADS)

Shi, Jianchu; Li, Sen; Zuo, Qiang; Ben-Gal, Alon

2015-03-01

Governed by atmospheric demand, soil water conditions and plant characteristics, plant water status is dynamic, complex, and fundamental to efficient agricultural water management. To explore a centralized signal for the evaluation of plant water status based on soil water status, two greenhouse experiments investigating the effect of the relative distribution between soil water and roots on wheat and rice were conducted. Due to the significant offset between the distributions of soil water and roots, wheat receiving subsurface irrigation suffered more from drought than wheat under surface irrigation, even when the arithmetic averaged soil water content (SWC) in the root zone was higher. A significant relationship was found between the plant water deficit index (PWDI) and the root-weighted (rather than the arithmetic) average SWC over root zone. The traditional soil-based approach for the estimation of PWDI was improved by replacing the arithmetic averaged SWC with the root-weighted SWC to take the effect of the relative distribution between soil water and roots into consideration. These results should be beneficial for scheduling irrigation, as well as for evaluating plant water consumption and root density profile.

From hydrological regimes to water use regimes: influence of the type of habitat on drinking water demand dynamics in alpine tourist resorts.

NASA Astrophysics Data System (ADS)

Calianno, Martin

2017-04-01

In the last decades, integrated water resources management studies produced integrated models that focus mainly on the assessment of water resources and water stress in the future. In some cases, socioeconomic development results to cause more impacts on the evolution of water systems than climate (Reynard et al., 2014). There is thus a need to develop demand-side approaches in the observation and modeling of human-influenced hydrological systems (Grouillet et al., 2015). We define the notion of water use cycle to differentiate water volumes that are withdrawn from the hydrological system and that circulate through anthropic hydro-systems along various steps: withdrawals, distribution, demands, consumption, restitution (Calianno et al., submitted). To address the spatial distribution and the temporal dynamics of the water use cycle, we define the concepts of water use basins and water use regimes (Calianno et al., submitted). The assessment of the temporal variability of water demands is important at thin time steps in touristic areas, where water resource regimes and water demands are highly variable. This is the case for are alpine ski resorts, where the high touristic season (winter) takes place during the low flow period in nival and glacio-nival basins. In this work, a monitoring of drinking water demands was undergone, at high temporal resolution, on different types of buildings in the ski resort of Megève (France). A dataset was created, from which a typology of water demand regimes was extracted. The analysis of these temporal signatures highlighted the factors influencing the volumes and the dynamics of drinking water demand. The main factors are the type of habitat (single family, collective, house, apartment blocks), the presence of a garden or an infrastructure linked to high standing chalets (pool, spa), the proportion of permanent and temporary habitat, the presence of snow in the ski resort. Also, temporalities linked to weekends and weekly tourism are observed. This typology of water demand regimes is at tool that can be developed to reproduce the temporal dynamics of water demands, when knowing the characteristics of habitat in a given region. References: Calianno M, Reynard E, Milano M (in prep). Water use cycle in tourist mountain territories: water demand basins and regimes. To be submitted to Water Resources Management. Calianno M, Reynard E, Milano M, Buchs A (submitted). Quantifier les usages de l'eau : concepts, terminologie et confusions. Submitted to VertigO. Grouillet B, Fabre J, Ruelland D, Dezetter A (2015) Historical reconstruction and 2050 projections of water demand under anthropogenic and climate changes in two contrasted mediterranean catchments. J Hydrol 522:684-696. Reynard E, Bonriposi M, Graefe O, Homewood C, Huss M, Kauzlaric M, Liniger H, Rey E, Rist S, Schädler B, Schneider F, Weingartner R (2014) Interdisciplinary assessment of complex regional water systems and their future evolution: how socioeconomic drivers can matter more than climate. WIREs Water 1(4):413-426.

Delivery of video-on-demand services using local storages within passive optical networks.

PubMed

Abeywickrama, Sandu; Wong, Elaine

2013-01-28

At present, distributed storage systems have been widely studied to alleviate Internet traffic build-up caused by high-bandwidth, on-demand applications. Distributed storage arrays located locally within the passive optical network were previously proposed to deliver Video-on-Demand services. As an added feature, a popularity-aware caching algorithm was also proposed to dynamically maintain the most popular videos in the storage arrays of such local storages. In this paper, we present a new dynamic bandwidth allocation algorithm to improve Video-on-Demand services over passive optical networks using local storages. The algorithm exploits the use of standard control packets to reduce the time taken for the initial request communication between the customer and the central office, and to maintain the set of popular movies in the local storage. We conduct packet level simulations to perform a comparative analysis of the Quality-of-Service attributes between two passive optical networks, namely the conventional passive optical network and one that is equipped with a local storage. Results from our analysis highlight that strategic placement of a local storage inside the network enables the services to be delivered with improved Quality-of-Service to the customer. We further formulate power consumption models of both architectures to examine the trade-off between enhanced Quality-of-Service performance versus the increased power requirement from implementing a local storage within the network.

Geostatistical modeling of the spatial distribution of sediment oxygen demand within a Coastal Plain blackwater watershed

PubMed Central

Todd, M. Jason; Lowrance, R. Richard; Goovaerts, Pierre; Vellidis, George; Pringle, Catherine M.

2010-01-01

Blackwater streams are found throughout the Coastal Plain of the southeastern United States and are characterized by a series of instream floodplain swamps that play a critical role in determining the water quality of these systems. Within the state of Georgia, many of these streams are listed in violation of the state’s dissolved oxygen (DO) standard. Previous work has shown that sediment oxygen demand (SOD) is elevated in instream floodplain swamps and due to these areas of intense oxygen demand, these locations play a major role in determining the oxygen balance of the watershed as a whole. This work also showed SOD rates to be positively correlated with the concentration of total organic carbon. This study builds on previous work by using geostatistics and Sequential Gaussian Simulation to investigate the patchiness and distribution of total organic carbon (TOC) at the reach scale. This was achieved by interpolating TOC observations and simulated SOD rates based on a linear regression. Additionally, this study identifies areas within the stream system prone to high SOD at representative 3rd and 5th order locations. Results show that SOD was spatially correlated with the differences in distribution of TOC at both locations and that these differences in distribution are likely a result of the differing hydrologic regime and watershed position. Mapping of floodplain soils at the watershed scale shows that areas of organic sediment are widespread and become more prevalent in higher order streams. DO dynamics within blackwater systems are a complicated mix of natural and anthropogenic influences, but this paper illustrates the importance of instream swamps in enhancing SOD at the watershed scale. Moreover, our study illustrates the influence of instream swamps on oxygen demand while providing support that many of these systems are naturally low in DO. PMID:20938491

Design and implementation of flexible TWDM-PON with PtP WDM overlay based on WSS for next-generation optical access networks

NASA Astrophysics Data System (ADS)

Wu, Bin; Yin, Hongxi; Qin, Jie; Liu, Chang; Liu, Anliang; Shao, Qi; Xu, Xiaoguang

2016-09-01

Aiming at the increasing demand of the diversification services and flexible bandwidth allocation of the future access networks, a flexible passive optical network (PON) scheme combining time and wavelength division multiplexing (TWDM) with point-to-point wavelength division multiplexing (PtP WDM) overlay is proposed for the next-generation optical access networks in this paper. A novel software-defined optical distribution network (ODN) structure is designed based on wavelength selective switches (WSS), which can implement wavelength and bandwidth dynamical allocations and suits for the bursty traffic. The experimental results reveal that the TWDM-PON can provide 40 Gb/s downstream and 10 Gb/s upstream data transmission, while the PtP WDM-PON can support 10 GHz point-to-point dedicated bandwidth as the overlay complement system. The wavelengths of the TWDM-PON and PtP WDM-PON are allocated dynamically based on WSS, which verifies the feasibility of the proposed structure.

Adam Smith's invisible hand is unstable: physics and dynamics reasoning applied to economic theorizing

NASA Astrophysics Data System (ADS)

McCauley, Joseph L.

2002-11-01

Neo-classical economic theory is based on the postulated, nonempiric notion of utility. Neo-classical economists assume that prices, dynamics, and market equilibria are supposed to be derived from utility. The results are supposed to represent mathematically the stabilizing action of Adam Smith's invisible hand. In deterministic excess demand dynamics, however, a utility function generally does not exist mathematically due to nonintegrability. Price as a function of demand does not exist and all equilibria are unstable. Qualitatively, and empirically, the neo-classical prediction of price as a function of demand describes neither consumer nor trader demand. We also discuss five inconsistent definitions of equilibrium used in economics and finance, only one of which is correct, and then explain the fallacy in the economists’ notion of ‘temporary price equilibria’.

Towards a 3d Spatial Urban Energy Modelling Approach

NASA Astrophysics Data System (ADS)

Bahu, J.-M.; Koch, A.; Kremers, E.; Murshed, S. M.

2013-09-01

Today's needs to reduce the environmental impact of energy use impose dramatic changes for energy infrastructure and existing demand patterns (e.g. buildings) corresponding to their specific context. In addition, future energy systems are expected to integrate a considerable share of fluctuating power sources and equally a high share of distributed generation of electricity. Energy system models capable of describing such future systems and allowing the simulation of the impact of these developments thus require a spatial representation in order to reflect the local context and the boundary conditions. This paper describes two recent research approaches developed at EIFER in the fields of (a) geo-localised simulation of heat energy demand in cities based on 3D morphological data and (b) spatially explicit Agent-Based Models (ABM) for the simulation of smart grids. 3D city models were used to assess solar potential and heat energy demand of residential buildings which enable cities to target the building refurbishment potentials. Distributed energy systems require innovative modelling techniques where individual components are represented and can interact. With this approach, several smart grid demonstrators were simulated, where heterogeneous models are spatially represented. Coupling 3D geodata with energy system ABMs holds different advantages for both approaches. On one hand, energy system models can be enhanced with high resolution data from 3D city models and their semantic relations. Furthermore, they allow for spatial analysis and visualisation of the results, with emphasis on spatially and structurally correlations among the different layers (e.g. infrastructure, buildings, administrative zones) to provide an integrated approach. On the other hand, 3D models can benefit from more detailed system description of energy infrastructure, representing dynamic phenomena and high resolution models for energy use at component level. The proposed modelling strategies conceptually and practically integrate urban spatial and energy planning approaches. The combined modelling approach that will be developed based on the described sectorial models holds the potential to represent hybrid energy systems coupling distributed generation of electricity with thermal conversion systems.

Modeling Framework and Validation of a Smart Grid and Demand Response System for Wind Power Integration

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

Broeer, Torsten; Fuller, Jason C.; Tuffner, Francis K.

2014-01-31

Electricity generation from wind power and other renewable energy sources is increasing, and their variability introduces new challenges to the power system. The emergence of smart grid technologies in recent years has seen a paradigm shift in redefining the electrical system of the future, in which controlled response of the demand side is used to balance fluctuations and intermittencies from the generation side. This paper presents a modeling framework for an integrated electricity system where loads become an additional resource. The agent-based model represents a smart grid power system integrating generators, transmission, distribution, loads and market. The model incorporates generatormore » and load controllers, allowing suppliers and demanders to bid into a Real-Time Pricing (RTP) electricity market. The modeling framework is applied to represent a physical demonstration project conducted on the Olympic Peninsula, Washington, USA, and validation simulations are performed using actual dynamic data. Wind power is then introduced into the power generation mix illustrating the potential of demand response to mitigate the impact of wind power variability, primarily through thermostatically controlled loads. The results also indicate that effective implementation of Demand Response (DR) to assist integration of variable renewable energy resources requires a diversity of loads to ensure functionality of the overall system.« less

A novel LTE scheduling algorithm for green technology in smart grid.

PubMed

Hindia, Mohammad Nour; Reza, Ahmed Wasif; Noordin, Kamarul Ariffin; Chayon, Muhammad Hasibur Rashid

2015-01-01

Smart grid (SG) application is being used nowadays to meet the demand of increasing power consumption. SG application is considered as a perfect solution for combining renewable energy resources and electrical grid by means of creating a bidirectional communication channel between the two systems. In this paper, three SG applications applicable to renewable energy system, namely, distribution automation (DA), distributed energy system-storage (DER) and electrical vehicle (EV), are investigated in order to study their suitability in Long Term Evolution (LTE) network. To compensate the weakness in the existing scheduling algorithms, a novel bandwidth estimation and allocation technique and a new scheduling algorithm are proposed. The technique allocates available network resources based on application's priority, whereas the algorithm makes scheduling decision based on dynamic weighting factors of multi-criteria to satisfy the demands (delay, past average throughput and instantaneous transmission rate) of quality of service. Finally, the simulation results demonstrate that the proposed mechanism achieves higher throughput, lower delay and lower packet loss rate for DA and DER as well as provide a degree of service for EV. In terms of fairness, the proposed algorithm shows 3%, 7 % and 9% better performance compared to exponential rule (EXP-Rule), modified-largest weighted delay first (M-LWDF) and exponential/PF (EXP/PF), respectively.

A Novel LTE Scheduling Algorithm for Green Technology in Smart Grid

PubMed Central

Hindia, Mohammad Nour; Reza, Ahmed Wasif; Noordin, Kamarul Ariffin; Chayon, Muhammad Hasibur Rashid

2015-01-01

Smart grid (SG) application is being used nowadays to meet the demand of increasing power consumption. SG application is considered as a perfect solution for combining renewable energy resources and electrical grid by means of creating a bidirectional communication channel between the two systems. In this paper, three SG applications applicable to renewable energy system, namely, distribution automation (DA), distributed energy system-storage (DER) and electrical vehicle (EV), are investigated in order to study their suitability in Long Term Evolution (LTE) network. To compensate the weakness in the existing scheduling algorithms, a novel bandwidth estimation and allocation technique and a new scheduling algorithm are proposed. The technique allocates available network resources based on application’s priority, whereas the algorithm makes scheduling decision based on dynamic weighting factors of multi-criteria to satisfy the demands (delay, past average throughput and instantaneous transmission rate) of quality of service. Finally, the simulation results demonstrate that the proposed mechanism achieves higher throughput, lower delay and lower packet loss rate for DA and DER as well as provide a degree of service for EV. In terms of fairness, the proposed algorithm shows 3%, 7 % and 9% better performance compared to exponential rule (EXP-Rule), modified-largest weighted delay first (M-LWDF) and exponential/PF (EXP/PF), respectively. PMID:25830703

The dynamic model on the impact of biodiesel blend mandate (B5) on Malaysian palm oil domestic demand: A preliminary finding

NASA Astrophysics Data System (ADS)

Abidin, Norhaslinda Zainal; Applanaidu, Shri-Dewi; Sapiri, Hasimah

2014-12-01

Over the last ten years, world biofuels production has increased dramatically. The biodiesel demand is driven by the increases in fossil fuel prices, government policy mandates, income from gross domestic product and population growth. In the European Union, biofuel consumption is mostly driven by blending mandates in both France and Germany. In the case of Malaysia, biodiesel has started to be exported since 2006. The B5 of 5% blend of palm oil based biodiesel into diesel in all government vehicles was implemented in February 2009 and it is expected to be implemented nationwide in the nearest time. How will the blend mandate will project growth in the domestic demand of palm oil in Malaysia? To analyze this issue, a system dynamics model was constructed to evaluate the impact of blend mandate implementation on the palm oil domestic demand influence. The base run of simulation analysis indicates that the trend of domestic demand will increase until 2030 in parallel with the implementation of 5 percent of biodiesel mandate. Finally, this study depicts that system dynamics is a useful tool to gain insight and to experiment with the impact of changes in blend mandate implementation on the future growth of Malaysian palm oil domestic demand sector.

Cost analysis of an electricity supply chain using modification of price based dynamic economic dispatch in wheeling transaction scheme

NASA Astrophysics Data System (ADS)

Wahyuda; Santosa, Budi; Rusdiansyah, Ahmad

2018-04-01

Deregulation of the electricity market requires coordination between parties to synchronize the optimization on the production side (power station) and the transport side (transmission). Electricity supply chain presented in this article is designed to facilitate the coordination between the parties. Generally, the production side is optimized with price based dynamic economic dispatch (PBDED) model, while the transmission side is optimized with Multi-echelon distribution model. Both sides optimization are done separately. This article proposes a joint model of PBDED and multi-echelon distribution for the combined optimization of production and transmission. This combined optimization is important because changes in electricity demand on the customer side will cause changes to the production side that automatically also alter the transmission path. The transmission will cause two cost components. First, the cost of losses. Second, the cost of using the transmission network (wheeling transaction). Costs due to losses are calculated based on ohmic losses, while the cost of using transmission lines using the MW - mile method. As a result, this method is able to provide best allocation analysis for electrical transactions, as well as emission levels in power generation and cost analysis. As for the calculation of transmission costs, the Reverse MW-mile method produces a cheaper cost than the Absolute MW-mile method

Composition-dependent trap distributions in CdSe and InP quantum dots probed using photoluminescence blinking dynamics.

PubMed

Chung, Heejae; Cho, Kyung-Sang; Koh, Weon-Kyu; Kim, Dongho; Kim, Jiwon

2016-07-21

Although Group II-VI quantum dots (QDs) have attracted much attention due to their wide range of applications in QD-based devices, the presence of toxic ions in II-VI QDs raises environmental concerns. To fulfill the demands of nontoxic QDs, synthetic routes for III-V QDs have been developed. However, only a few comparative analyses on optical properties of III-V QDs have been performed. In this study, the composition-related energetic trap distributions have been explored by using three different types of core/multishell QDs: CdSe-CdS (CdSe/CdS/ZnS), InP-ZnSe (InP/ZnSe/ZnS), and InP-GaP (InP/GaP/ZnS). It was shown that CdSe-CdS QDs have much larger trap densities than InP-shell QDs at higher energy states (at least 1Eg (band gap energy) above the lowest conduction band edge) based on probability density plots and Auger ionization efficiencies which are determined by analyses of photoluminescence blinking dynamics. This result suggests that the composition of encapsulated QDs is closely associated with the charge trapping processes, and also provides an insight into the development of more environmentally friendly QD-based devices.

History-Based Response Threshold Model for Division of Labor in Multi-Agent Systems

PubMed Central

Lee, Wonki; Kim, DaeEun

2017-01-01

Dynamic task allocation is a necessity in a group of robots. Each member should decide its own task such that it is most commensurate with its current state in the overall system. In this work, the response threshold model is applied to a dynamic foraging task. Each robot employs a task switching function based on the local task demand obtained from the surrounding environment, and no communication occurs between the robots. Each individual member has a constant-sized task demand history that reflects the global demand. In addition, it has response threshold values for all of the tasks and manages the task switching process depending on the stimuli of the task demands. The robot then determines the task to be executed to regulate the overall division of labor. This task selection induces a specialized tendency for performing a specific task and regulates the division of labor. In particular, maintaining a history of the task demands is very effective for the dynamic foraging task. Various experiments are performed using a simulation with multiple robots, and the results show that the proposed algorithm is more effective as compared to the conventional model. PMID:28555031

Wire-positioning algorithm for coreless Hall array sensors in current measurement

NASA Astrophysics Data System (ADS)

Chen, Wenli; Zhang, Huaiqing; Chen, Lin; Gu, Shanyun

2018-05-01

This paper presents a scheme of circular-arrayed, coreless Hall-effect current transformers. It can satisfy the demands of wide dynamic range and bandwidth current in the distribution system, as well as the demand of AC and DC simultaneous measurements. In order to improve the signal to noise ratio (SNR) of the sensor, a wire-positioning algorithm is proposed, which can improve the measurement accuracy based on the post-processing of measurement data. The simulation results demonstrate that the maximum errors are 70%, 6.1% and 0.95% corresponding to Ampère’s circuital method, approximate positioning algorithm and precise positioning algorithm, respectively. It is obvious that the accuracy of the positioning algorithm is significantly improved when compared with that of the Ampère’s circuital method. The maximum error of the positioning algorithm is smaller in the experiment.

End-User Tools Towards AN Efficient Electricity Consumption: the Dynamic Smart Grid

NASA Astrophysics Data System (ADS)

Kamel, Fouad; Kist, Alexander A.

2010-06-01

Growing uncontrolled electrical demands have caused increased supply requirements. This causes volatile electrical markets and has detrimental unsustainable environmental impacts. The market is presently characterized by regular daily peak demand conditions associated with high electricity prices. A demand-side response system can limit peak demands to an acceptable level. The proposed scheme is based on energy demand and price information which is available online. An online server is used to communicate the information of electricity suppliers to users, who are able to use the information to manage and control their own demand. A configurable, intelligent switching system is used to control local loads during peak events and mange the loads at other times as necessary. The aim is to shift end user loads towards periods where energy demand and therefore also prices are at the lowest. As a result, this will flatten the load profile and avoiding load peeks which are costly for suppliers. The scheme is an endeavour towards achieving a dynamic smart grid demand-side-response environment using information-based communication and computer-controlled switching. Diffusing the scheme shall lead to improved electrical supply services and controlled energy consumption and prices.

Distributed and decentralized state estimation in gas networks as distributed parameter systems.

PubMed

Ahmadian Behrooz, Hesam; Boozarjomehry, R Bozorgmehry

2015-09-01

In this paper, a framework for distributed and decentralized state estimation in high-pressure and long-distance gas transmission networks (GTNs) is proposed. The non-isothermal model of the plant including mass, momentum and energy balance equations are used to simulate the dynamic behavior. Due to several disadvantages of implementing a centralized Kalman filter for large-scale systems, the continuous/discrete form of extended Kalman filter for distributed and decentralized estimation (DDE) has been extended for these systems. Accordingly, the global model is decomposed into several subsystems, called local models. Some heuristic rules are suggested for system decomposition in gas pipeline networks. In the construction of local models, due to the existence of common states and interconnections among the subsystems, the assimilation and prediction steps of the Kalman filter are modified to take the overlapping and external states into account. However, dynamic Riccati equation for each subsystem is constructed based on the local model, which introduces a maximum error of 5% in the estimated standard deviation of the states in the benchmarks studied in this paper. The performance of the proposed methodology has been shown based on the comparison of its accuracy and computational demands against their counterparts in centralized Kalman filter for two viable benchmarks. In a real life network, it is shown that while the accuracy is not significantly decreased, the real-time factor of the state estimation is increased by a factor of 10. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

BrainBrowser: distributed, web-based neurological data visualization.

PubMed

Sherif, Tarek; Kassis, Nicolas; Rousseau, Marc-Étienne; Adalat, Reza; Evans, Alan C

2014-01-01

Recent years have seen massive, distributed datasets become the norm in neuroimaging research, and the methodologies used to analyze them have, in response, become more collaborative and exploratory. Tools and infrastructure are continuously being developed and deployed to facilitate research in this context: grid computation platforms to process the data, distributed data stores to house and share them, high-speed networks to move them around and collaborative, often web-based, platforms to provide access to and sometimes manage the entire system. BrainBrowser is a lightweight, high-performance JavaScript visualization library built to provide easy-to-use, powerful, on-demand visualization of remote datasets in this new research environment. BrainBrowser leverages modern web technologies, such as WebGL, HTML5 and Web Workers, to visualize 3D surface and volumetric neuroimaging data in any modern web browser without requiring any browser plugins. It is thus trivial to integrate BrainBrowser into any web-based platform. BrainBrowser is simple enough to produce a basic web-based visualization in a few lines of code, while at the same time being robust enough to create full-featured visualization applications. BrainBrowser can dynamically load the data required for a given visualization, so no network bandwidth needs to be waisted on data that will not be used. BrainBrowser's integration into the standardized web platform also allows users to consider using 3D data visualization in novel ways, such as for data distribution, data sharing and dynamic online publications. BrainBrowser is already being used in two major online platforms, CBRAIN and LORIS, and has been used to make the 1TB MACACC dataset openly accessible.

BrainBrowser: distributed, web-based neurological data visualization

PubMed Central

Sherif, Tarek; Kassis, Nicolas; Rousseau, Marc-Étienne; Adalat, Reza; Evans, Alan C.

2015-01-01

Recent years have seen massive, distributed datasets become the norm in neuroimaging research, and the methodologies used to analyze them have, in response, become more collaborative and exploratory. Tools and infrastructure are continuously being developed and deployed to facilitate research in this context: grid computation platforms to process the data, distributed data stores to house and share them, high-speed networks to move them around and collaborative, often web-based, platforms to provide access to and sometimes manage the entire system. BrainBrowser is a lightweight, high-performance JavaScript visualization library built to provide easy-to-use, powerful, on-demand visualization of remote datasets in this new research environment. BrainBrowser leverages modern web technologies, such as WebGL, HTML5 and Web Workers, to visualize 3D surface and volumetric neuroimaging data in any modern web browser without requiring any browser plugins. It is thus trivial to integrate BrainBrowser into any web-based platform. BrainBrowser is simple enough to produce a basic web-based visualization in a few lines of code, while at the same time being robust enough to create full-featured visualization applications. BrainBrowser can dynamically load the data required for a given visualization, so no network bandwidth needs to be waisted on data that will not be used. BrainBrowser's integration into the standardized web platform also allows users to consider using 3D data visualization in novel ways, such as for data distribution, data sharing and dynamic online publications. BrainBrowser is already being used in two major online platforms, CBRAIN and LORIS, and has been used to make the 1TB MACACC dataset openly accessible. PMID:25628562

Emigration dynamics in Bangladesh.

PubMed

Mahmood, R A

1995-01-01

This study of emigration dynamics opens by noting that emigration is one of the most dynamic economic and social elements in Bangladesh. The history of emigration from Bangladesh is sketched, and the level and trend of emigration is described for various destinations (especially the UK, the Middle East and North Africa, and Japan) and in terms of the socioeconomic background of migrants, channels of migration, occupations, the potential level of emigration, and applications for US Visas. The next section of the report presents the economic and demographic setting in terms of the gross national and domestic products, quality of life, the size and distribution of the population, the labor force, literacy, unemployment and underemployment, urbanization, internal migration, poverty, and income distribution. The discussion then centers on the sociopolitical setting and such factors as unmet basic human needs, the demand for expatriate workers, and emigration policy. It is concluded that the desperate economic situation in Bangladesh has combined with the demand for expatriate workers and the development of institutions to facilitate emigration. The result is increasing interest in emigration, which is fueled by mass communication highlighting the differences between the quality of life in Bangladesh and abroad.

Non-Gaussian power grid frequency fluctuations characterized by Lévy-stable laws and superstatistics

NASA Astrophysics Data System (ADS)

Schäfer, Benjamin; Beck, Christian; Aihara, Kazuyuki; Witthaut, Dirk; Timme, Marc

2018-02-01

Multiple types of fluctuations impact the collective dynamics of power grids and thus challenge their robust operation. Fluctuations result from processes as different as dynamically changing demands, energy trading and an increasing share of renewable power feed-in. Here we analyse principles underlying the dynamics and statistics of power grid frequency fluctuations. Considering frequency time series for a range of power grids, including grids in North America, Japan and Europe, we find a strong deviation from Gaussianity best described as Lévy-stable and q-Gaussian distributions. We present a coarse framework to analytically characterize the impact of arbitrary noise distributions, as well as a superstatistical approach that systematically interprets heavy tails and skewed distributions. We identify energy trading as a substantial contribution to today's frequency fluctuations and effective damping of the grid as a controlling factor enabling reduction of fluctuation risks, with enhanced effects for small power grids.

A method for optimizing multi-objective reservoir operation upon human and riverine ecosystem demands

NASA Astrophysics Data System (ADS)

Ai, Xueshan; Dong, Zuo; Mo, Mingzhu

2017-04-01

The optimal reservoir operation is in generally a multi-objective problem. In real life, most of the reservoir operation optimization problems involve conflicting objectives, for which there is no single optimal solution which can simultaneously gain an optimal result of all the purposes, but rather a set of well distributed non-inferior solutions or Pareto frontier exists. On the other hand, most of the reservoirs operation rules is to gain greater social and economic benefits at the expense of ecological environment, resulting to the destruction of riverine ecology and reduction of aquatic biodiversity. To overcome these drawbacks, this study developed a multi-objective model for the reservoir operating with the conflicting functions of hydroelectric energy generation, irrigation and ecological protection. To solve the model with the objectives of maximize energy production, maximize the water demand satisfaction rate of irrigation and ecology, we proposed a multi-objective optimization method of variable penalty coefficient (VPC), which was based on integrate dynamic programming (DP) with discrete differential dynamic programming (DDDP), to generate a well distributed non-inferior along the Pareto front by changing the penalties coefficient of different objectives. This method was applied to an existing China reservoir named Donggu, through a course of a year, which is a multi-annual storage reservoir with multiple purposes. The case study results showed a good relationship between any two of the objectives and a good Pareto optimal solutions, which provide a reference for the reservoir decision makers.

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

A Vision for Co-optimized T&D System Interaction with Renewables and Demand Response

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

Anderson, Lindsay; Zéphyr, Luckny; Cardell, Judith B.

The evolution of the power system to the reliable, efficient and sustainable system of the future will involve development of both demand- and supply-side technology and operations. The use of demand response to counterbalance the intermittency of renewable generation brings the consumer into the spotlight. Though individual consumers are interconnected at the low-voltage distribution system, these resources are typically modeled as variables at the transmission network level. In this paper, a vision for cooptimized interaction of distribution systems, or microgrids, with the high-voltage transmission system is described. In this framework, microgrids encompass consumers, distributed renewables and storage. The energy managementmore » system of the microgrid can also sell (buy) excess (necessary) energy from the transmission system. Preliminary work explores price mechanisms to manage the microgrid and its interactions with the transmission system. Wholesale market operations are addressed through the development of scalable stochastic optimization methods that provide the ability to co-optimize interactions between the transmission and distribution systems. Modeling challenges of the co-optimization are addressed via solution methods for large-scale stochastic optimization, including decomposition and stochastic dual dynamic programming.« less

Linking interseismic deformation with coseismic slip using dynamic rupture simulations

NASA Astrophysics Data System (ADS)

Yang, H.; He, B.; Weng, H.

2017-12-01

The largest earthquakes on earth occur at subduction zones, sometimes accompanied by devastating tsunamis. Reducing losses from megathrust earthquakes and tsunami demands accurate estimate of rupture scenarios for future earthquakes. Interseismic locking distribution derived from geodetic observations is often used to qualitatively evaluate future earthquake potential. However, how to quantitatively estimate the coseismic slip from the locking distribution remains challenging. Here we derive the coseismic rupture process of the 2012 Mw 7.6 Nicoya, Costa Rica, earthquake from interseismic locking distribution using spontaneous rupture simulation. We construct a three-dimensional elastic medium with a curved fault, which is governed by the linear slip-weakening law. The initial stress on the fault is set based on the build-up stress inferred from locking and the dynamic friction coefficient from fast-speed sliding experiments. Our numerical results of coseismic slip distribution, moment rate function and final earthquake moment are well consistent with those derived from seismic and geodetic observations. Furthermore, we find that the epicentral locations affect rupture scenarios and may lead to various sizes of earthquakes given the heterogeneous stress distribution. In the Nicoya region, less than half of rupture initiation regions where the locking degree is greater than 0.6 can develop into large earthquakes (Mw > 7.2). The results of location-dependent earthquake magnitudes underscore the necessity of conducting a large number of simulations to quantitatively evaluate seismic hazard from the interseismic locking models.

[Dynamic changes of ecological footprint and ecological capacity in Fujian Province].

PubMed

Weng, Boqi; Wang, Yixiang; Huang, Yibin; Ying, Zhaoyang; Huang, Qinlou

2006-11-01

The analysis on the dynamic changes of ecological footprint and ecological capacity in Fujian Province showed that in 1999-2003, the ecological footprint per capita in the Province increased from 1.428 hm2 to 1.658 hm2, while the ecological capacity per capita decreased from 0.683 hm2 to 0.607 hm2, with an increased ecological deficit year after year. The contradiction between the ecological footprint and ecological capacity pricked up gradually, and the ecological environment was at risk. There existed a severe imbalance in the supply and demand of ecological footprint per capita. The main body of the demands was grassland and fossil fuel, accouting for 55.74% - 63.43% of the total, while their supply only occupied 0.77% - 0.82% and next to nothing of the ecological capacity per capita, respectively. As a whole, the ecological footprint per ten thousand yuan GDP declined in the five years, indicating that the resources use efficiency in the Province was improved gradually. Based on the analysis of the present situation of the economic development and resources distribution in the Province, the strategies on reducing ecological deficit were put forward.

Dynamic spectrum management: an impact on EW systems

NASA Astrophysics Data System (ADS)

Gajewski, P.; Łopatka, J.; Suchanski, M.

2017-04-01

Rapid evolution of wireless systems caused an enormous growth of data streams transmitted through the networks and, as a consequence, an accompanying demand concerning spectrum resources (SR). An avoidance of advisable disturbances is one of the main demands in military communications. To solve the interference problems, dynamic spectrum management (DSM) techniques can be used. Two main techniques are possible: centralized Coordinated Dynamic Spectrum Access (CDSA) and distributed Opportunistic Spectrum Access (OSA). CDSA enables the wireless networks planning automation, and systems dynamic reaction to random changes of Radio Environment (RE). For OSA, cognitive radio (CR) is the most promising technology that enables avoidance of interference with the other spectrum users due to CR's transmission parameters adaptation to the current radio situation, according to predefined Radio Policies rules. If DSM techniques are used, the inherent changes in EW systems are also needed. On one hand, new techniques of jamming should be elaborated, on the other hand, the rules and protocols of cooperation between communication network and EW systems should be developed.

Holidays in lights: Tracking cultural patterns in demand for energy services

NASA Astrophysics Data System (ADS)

Román, Miguel O.; Stokes, Eleanor C.

2015-06-01

Successful climate change mitigation will involve not only technological innovation, but also innovation in how we understand the societal and individual behaviors that shape the demand for energy services. Traditionally, individual energy behaviors have been described as a function of utility optimization and behavioral economics, with price restructuring as the dominant policy lever. Previous research at the macro-level has identified economic activity, power generation and technology, and economic role as significant factors that shape energy use. However, most demand models lack basic contextual information on how dominant social phenomenon, the changing demographics of cities, and the sociocultural setting within which people operate, affect energy decisions and use patterns. Here we use high-quality Suomi-NPP VIIRS nighttime environmental products to: (1) observe aggregate human behavior through variations in energy service demand patterns during the Christmas and New Year's season and the Holy Month of Ramadan and (2) demonstrate that patterns in energy behaviors closely track sociocultural boundaries at the country, city, and district level. These findings indicate that energy decision making and demand is a sociocultural process as well as an economic process, often involving a combination of individual price-based incentives and societal-level factors. While nighttime satellite imagery has been used to map regional energy infrastructure distribution, tracking daily dynamic lighting demand at three major scales of urbanization is novel. This methodology can enrich research on the relative importance of drivers of energy demand and conservation behaviors at fine scales. Our initial results demonstrate the importance of seating energy demand frameworks in a social context.

Holiday in Lights: Tracking Cultural Patterns in Demand for Energy Services

NASA Technical Reports Server (NTRS)

Roman, Miguel O.; Stokes, Eleanor C.

2015-01-01

Successful climate change mitigation will involve not only technological innovation, but also innovation in how we understand the societal and individual behaviors that shape the demand for energy services. Traditionally, individual energy behaviors have been described as a function of utility optimization and behavioral economics, with price restructuring as the dominant policy lever. Previous research at the macro-level has identified economic activity, power generation and technology, and economic role as significant factors that shape energy use. However, most demand models lack basic contextual information on how dominant social phenomenon, the changing demographics of cities, and the sociocultural setting within which people operate, affect energy decisions and use patterns. Here we use high-quality Suomi-NPP VIIRS nighttime environmental products to: (1) observe aggregate human behavior through variations in energy service demand patterns during the Christmas and New Year's season and the Holy Month of Ramadan and (2) demonstrate that patterns in energy behaviors closely track sociocultural boundaries at the country, city, and district level. These findings indicate that energy decision making and demand is a sociocultural process as well as an economic process, often involving a combination of individual price-based incentives and societal-level factors. While nighttime satellite imagery has been used to map regional energy infrastructure distribution, tracking daily dynamic lighting demand at three major scales of urbanization is novel. This methodology can enrich research on the relative importance of drivers of energy demand and conservation behaviors at fine scales. Our initial results demonstrate the importance of seating energy demand frameworks in a social context.

Holidays in lights: Tracking cultural patterns in demand for energy services.

PubMed

Román, Miguel O; Stokes, Eleanor C

2015-06-01

Successful climate change mitigation will involve not only technological innovation, but also innovation in how we understand the societal and individual behaviors that shape the demand for energy services. Traditionally, individual energy behaviors have been described as a function of utility optimization and behavioral economics, with price restructuring as the dominant policy lever. Previous research at the macro-level has identified economic activity, power generation and technology, and economic role as significant factors that shape energy use. However, most demand models lack basic contextual information on how dominant social phenomenon, the changing demographics of cities, and the sociocultural setting within which people operate, affect energy decisions and use patterns. Here we use high-quality Suomi-NPP VIIRS nighttime environmental products to: (1) observe aggregate human behavior through variations in energy service demand patterns during the Christmas and New Year's season and the Holy Month of Ramadan and (2) demonstrate that patterns in energy behaviors closely track sociocultural boundaries at the country, city, and district level. These findings indicate that energy decision making and demand is a sociocultural process as well as an economic process, often involving a combination of individual price-based incentives and societal-level factors. While nighttime satellite imagery has been used to map regional energy infrastructure distribution, tracking daily dynamic lighting demand at three major scales of urbanization is novel. This methodology can enrich research on the relative importance of drivers of energy demand and conservation behaviors at fine scales. Our initial results demonstrate the importance of seating energy demand frameworks in a social context.

Study on the complexity pricing game and coordination of the duopoly air conditioner market with disturbance demand

NASA Astrophysics Data System (ADS)

Ma, Junhai; Xie, Lei

2016-03-01

The paper focuses on the dynamic pricing game of the duopoly air conditioner market with disturbance in demand and analyzes the influence of disturbance on the dynamic game system. Considering the demand for products, such as air conditioner, varies with different seasons, we assume three cases based on the condition of disturbance, including growth market (Case 1), declining market (Case 2) and completely random market (Case 3). By analyzing these three cases and making comparison among them, the paper shows that the growth market is more sensitive to the changing parameters such as the adjustment variable and the competitive factor than the declining market. It is more difficult to keep the system stable in a growth market. Although the demand is completely random, the dynamic system can reach a stable state, on condition that the adjustment variable is small enough. The results also indicate that the bullwhip effect between the order quantity and the actual demand is weakened gradually along with the price adjustment.

Dynamic Strategic Planning in a Professional Knowledge-Based Organization

ERIC Educational Resources Information Center

Olivarius, Niels de Fine; Kousgaard, Marius Brostrom; Reventlow, Susanne; Quelle, Dan Grevelund; Tulinius, Charlotte

2010-01-01

Professional, knowledge-based institutions have a particular form of organization and culture that makes special demands on the strategic planning supervised by research administrators and managers. A model for dynamic strategic planning based on a pragmatic utilization of the multitude of strategy models was used in a small university-affiliated…

Pricing the Services in Dynamic Environment: Agent Pricing Model

NASA Astrophysics Data System (ADS)

Žagar, Drago; Rupčić, Slavko; Rimac-Drlje, Snježana

New Internet applications and services as well as new user demands open many new issues concerning dynamic management of quality of service and price for received service, respectively. The main goals of Internet service providers are to maximize profit and maintain a negotiated quality of service. From the users' perspective the main goal is to maximize ratio of received QoS and costs of service. However, achieving these objectives could become very complex if we know that Internet service users might during the session become highly dynamic and proactive. This connotes changes in user profile or network provider/s profile caused by high level of user mobility or variable level of user demands. This paper proposes a new agent based pricing architecture for serving the highly dynamic customers in context of dynamic user/network environment. The proposed architecture comprises main aspects and basic parameters that will enable objective and transparent assessment of the costs for the service those Internet users receive while dynamically change QoS demands and cost profile.

Robust scalable stabilisability conditions for large-scale heterogeneous multi-agent systems with uncertain nonlinear interactions: towards a distributed computing architecture

NASA Astrophysics Data System (ADS)

Manfredi, Sabato

2016-06-01

Large-scale dynamic systems are becoming highly pervasive in their occurrence with applications ranging from system biology, environment monitoring, sensor networks, and power systems. They are characterised by high dimensionality, complexity, and uncertainty in the node dynamic/interactions that require more and more computational demanding methods for their analysis and control design, as well as the network size and node system/interaction complexity increase. Therefore, it is a challenging problem to find scalable computational method for distributed control design of large-scale networks. In this paper, we investigate the robust distributed stabilisation problem of large-scale nonlinear multi-agent systems (briefly MASs) composed of non-identical (heterogeneous) linear dynamical systems coupled by uncertain nonlinear time-varying interconnections. By employing Lyapunov stability theory and linear matrix inequality (LMI) technique, new conditions are given for the distributed control design of large-scale MASs that can be easily solved by the toolbox of MATLAB. The stabilisability of each node dynamic is a sufficient assumption to design a global stabilising distributed control. The proposed approach improves some of the existing LMI-based results on MAS by both overcoming their computational limits and extending the applicative scenario to large-scale nonlinear heterogeneous MASs. Additionally, the proposed LMI conditions are further reduced in terms of computational requirement in the case of weakly heterogeneous MASs, which is a common scenario in real application where the network nodes and links are affected by parameter uncertainties. One of the main advantages of the proposed approach is to allow to move from a centralised towards a distributed computing architecture so that the expensive computation workload spent to solve LMIs may be shared among processors located at the networked nodes, thus increasing the scalability of the approach than the network size. Finally, a numerical example shows the applicability of the proposed method and its advantage in terms of computational complexity when compared with the existing approaches.

Future Opportunities and Challenges with Using Demand Response as a Resource in Distribution System Operation and Planning Activities

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

Cappers, Peter; MacDonald, Jason; Page, Janie

2016-01-01

This scoping study focuses on identifying the ability for current and future demand response opportunities to contribute to distribution system management. To do so, this scoping study will identify the needs of a distribution system to operate efficiently, safely and reliably; summarize both benefits and challenges for the operation of the distribution system with high penetration levels of distributed energy resources; define a suite of services based on those changing operational needs that could be provided by resources; identify existing demand response opportunities sponsored by distribution utilities and/or aggregators of retail customers; assess the extent to which distribution system servicesmore » can be provided via DR opportunities both in their current form and with alterations to their design; and provide a qualitative assessment of coordination issues that bulk power and distribution system providers of DR opportunities will need to address.« less

Outlook of the world steel cycle based on the stock and flow dynamics.

PubMed

Hatayama, Hiroki; Daigo, Ichiro; Matsuno, Yasunari; Adachi, Yoshihiro

2010-08-15

We present a comprehensive analysis of steel use in the future compiled using dynamic material flow analysis (MFA). A dynamic MFA for 42 countries depicted the global in-use stock and flow up to the end of 2005. On the basis of the transition of steel stock for 2005, the growth of future steel stock was then estimated considering the economic growth for every country. Future steel demand was estimated using dynamic analysis under the new concept of "stocks drive flows". The significant results follow. World steel stock reached 12.7 billion t in 2005, and has doubled in the last 25 years. The world stock in 2005 mainly consisted of construction (60%) and vehicles (10%). Stock in these end uses will reach 55 billion t in 2050, driven by a 10-fold increase in Asia. Steel demand will reach 1.8 billion t in 2025, then slightly decrease, and rise again by replacement of buildings. The forecast of demand clearly represents the industrial shift; at first the increase is dominated by construction, and then, after 2025, demand for construction decreases and demand for vehicles increases instead. This study thus provides the dynamic mechanism of steel stock and flow toward the future, which contributes to the design of sustainable steel use.

Study of activities of postmen motorcyclists: a look at motorcycle accidents.

PubMed

Nascimento, Lícia Maria Barreto do; Bortolotto, Gracielle Aparecida Orlando

2012-01-01

This article presents the steps of transforming the material and organizational aspects in the work environment, beyond the social order for the proper development of activities in the Household Distribution Center, the Postmen Motorcyclists. The demand was made by managers from the accident records, establishing the need to identify the working conditions of postmen motorcyclists, regarding motorcycle accidents occurring on public roads. Based on the characteristics of the steps required by the methodology, was necessary to realize internal and external observations, with the aim of identifying the dynamics of the accident and the collective dimensions of activity which requires a strategy for monitoring the work on the street.

A fast and precise indoor localization algorithm based on an online sequential extreme learning machine.

PubMed

Zou, Han; Lu, Xiaoxuan; Jiang, Hao; Xie, Lihua

2015-01-15

Nowadays, developing indoor positioning systems (IPSs) has become an attractive research topic due to the increasing demands on location-based service (LBS) in indoor environments. WiFi technology has been studied and explored to provide indoor positioning service for years in view of the wide deployment and availability of existing WiFi infrastructures in indoor environments. A large body of WiFi-based IPSs adopt fingerprinting approaches for localization. However, these IPSs suffer from two major problems: the intensive costs of manpower and time for offline site survey and the inflexibility to environmental dynamics. In this paper, we propose an indoor localization algorithm based on an online sequential extreme learning machine (OS-ELM) to address the above problems accordingly. The fast learning speed of OS-ELM can reduce the time and manpower costs for the offline site survey. Meanwhile, its online sequential learning ability enables the proposed localization algorithm to adapt in a timely manner to environmental dynamics. Experiments under specific environmental changes, such as variations of occupancy distribution and events of opening or closing of doors, are conducted to evaluate the performance of OS-ELM. The simulation and experimental results show that the proposed localization algorithm can provide higher localization accuracy than traditional approaches, due to its fast adaptation to various environmental dynamics.

Metabolic Turnover of Synaptic Proteins: Kinetics, Interdependencies and Implications for Synaptic Maintenance

PubMed Central

Cohen, Laurie D.; Zuchman, Rina; Sorokina, Oksana; Müller, Anke; Dieterich, Daniela C.; Armstrong, J. Douglas; Ziv, Tamar; Ziv, Noam E.

2013-01-01

Chemical synapses contain multitudes of proteins, which in common with all proteins, have finite lifetimes and therefore need to be continuously replaced. Given the huge numbers of synaptic connections typical neurons form, the demand to maintain the protein contents of these connections might be expected to place considerable metabolic demands on each neuron. Moreover, synaptic proteostasis might differ according to distance from global protein synthesis sites, the availability of distributed protein synthesis facilities, trafficking rates and synaptic protein dynamics. To date, the turnover kinetics of synaptic proteins have not been studied or analyzed systematically, and thus metabolic demands or the aforementioned relationships remain largely unknown. In the current study we used dynamic Stable Isotope Labeling with Amino acids in Cell culture (SILAC), mass spectrometry (MS), Fluorescent Non–Canonical Amino acid Tagging (FUNCAT), quantitative immunohistochemistry and bioinformatics to systematically measure the metabolic half-lives of hundreds of synaptic proteins, examine how these depend on their pre/postsynaptic affiliation or their association with particular molecular complexes, and assess the metabolic load of synaptic proteostasis. We found that nearly all synaptic proteins identified here exhibited half-lifetimes in the range of 2–5 days. Unexpectedly, metabolic turnover rates were not significantly different for presynaptic and postsynaptic proteins, or for proteins for which mRNAs are consistently found in dendrites. Some functionally or structurally related proteins exhibited very similar turnover rates, indicating that their biogenesis and degradation might be coupled, a possibility further supported by bioinformatics-based analyses. The relatively low turnover rates measured here (∼0.7% of synaptic protein content per hour) are in good agreement with imaging-based studies of synaptic protein trafficking, yet indicate that the metabolic load synaptic protein turnover places on individual neurons is very substantial. PMID:23658807

A web service and android application for the distribution of rainfall estimates and Earth observation data

NASA Astrophysics Data System (ADS)

Mantas, V. M.; Liu, Z.; Pereira, A. J. S. C.

2015-04-01

The full potential of Satellite Rainfall Estimates (SRE) can only be realized if timely access to the datasets is possible. Existing data distribution web portals are often focused on global products and offer limited customization options, especially for the purpose of routine regional monitoring. Furthermore, most online systems are designed to meet the needs of desktop users, limiting the compatibility with mobile devices. In response to the growing demand for SRE and to address the current limitations of available web portals a project was devised to create a set of freely available applications and services, available at a common portal that can: (1) simplify cross-platform access to Tropical Rainfall Measuring Mission Online Visualization and Analysis System (TOVAS) data (including from Android mobile devices), (2) provide customized and continuous monitoring of SRE in response to user demands and (3) combine data from different online data distribution services, including rainfall estimates, river gauge measurements or imagery from Earth Observation missions at a single portal, known as the Tropical Rainfall Measuring Mission (TRMM) Explorer. The TRMM Explorer project suite includes a Python-based web service and Android applications capable of providing SRE and ancillary data in different intuitive formats with the focus on regional and continuous analysis. The outputs include dynamic plots, tables and data files that can also be used to feed downstream applications and services. A case study in Southern Angola is used to describe the potential of the TRMM Explorer for SRE distribution and analysis in the context of ungauged watersheds. The development of a collection of data distribution instances helped to validate the concept and identify the limitations of the program, in a real context and based on user feedback. The TRMM Explorer can successfully supplement existing web portals distributing SRE and provide a cost-efficient resource to small and medium-sized organizations with specific SRE monitoring needs, namely in developing and transition countries.

Selective randomized load balancing and mesh networks with changing demands

NASA Astrophysics Data System (ADS)

Shepherd, F. B.; Winzer, P. J.

2006-05-01

We consider the problem of building cost-effective networks that are robust to dynamic changes in demand patterns. We compare several architectures using demand-oblivious routing strategies. Traditional approaches include single-hop architectures based on a (static or dynamic) circuit-switched core infrastructure and multihop (packet-switched) architectures based on point-to-point circuits in the core. To address demand uncertainty, we seek minimum cost networks that can carry the class of hose demand matrices. Apart from shortest-path routing, Valiant's randomized load balancing (RLB), and virtual private network (VPN) tree routing, we propose a third, highly attractive approach: selective randomized load balancing (SRLB). This is a blend of dual-hop hub routing and randomized load balancing that combines the advantages of both architectures in terms of network cost, delay, and delay jitter. In particular, we give empirical analyses for the cost (in terms of transport and switching equipment) for the discussed architectures, based on three representative carrier networks. Of these three networks, SRLB maintains the resilience properties of RLB while achieving significant cost reduction over all other architectures, including RLB and multihop Internet protocol/multiprotocol label switching (IP/MPLS) networks using VPN-tree routing.

Synchronous Bioimaging of Intracellular pH and Chloride Based on LSS Fluorescent Protein.

PubMed

Paredes, Jose M; Idilli, Aurora I; Mariotti, Letizia; Losi, Gabriele; Arslanbaeva, Lyaysan R; Sato, Sebastian Sulis; Artoni, Pietro; Szczurkowska, Joanna; Cancedda, Laura; Ratto, Gian Michele; Carmignoto, Giorgio; Arosio, Daniele

2016-06-17

Ion homeostasis regulates critical physiological processes in the living cell. Intracellular chloride concentration not only contributes in setting the membrane potential of quiescent cells but it also plays a role in modulating the dynamic voltage changes during network activity. Dynamic chloride imaging demands new tools, allowing faster acquisition rates and correct accounting of concomitant pH changes. Joining a long-Stokes-shift red-fluorescent protein to a GFP variant with high sensitivity to pH and chloride, we obtained LSSmClopHensor, a genetically encoded fluorescent biosensor optimized for the simultaneous chloride and pH imaging and requiring only two excitation wavelengths (458 and 488 nm). LSSmClopHensor allowed us to monitor the dynamic changes of intracellular pH and chloride concentration during seizure like discharges in neocortical brain slices. Only cells with tightly controlled resting potential revealed a narrow distribution of chloride concentration peaking at about 5 and 8 mM, in neocortical neurons and SK-N-SH cells, respectively. We thus showed that LSSmClopHensor represents a new versatile tool for studying the dynamics of chloride and proton concentration in living systems.

GSKY: A scalable distributed geospatial data server on the cloud

NASA Astrophysics Data System (ADS)

Rozas Larraondo, Pablo; Pringle, Sean; Antony, Joseph; Evans, Ben

2017-04-01

Earth systems, environmental and geophysical datasets are an extremely valuable sources of information about the state and evolution of the Earth. Being able to combine information coming from different geospatial collections is in increasing demand by the scientific community, and requires managing and manipulating data with different formats and performing operations such as map reprojections, resampling and other transformations. Due to the large data volume inherent in these collections, storing multiple copies of them is unfeasible and so such data manipulation must be performed on-the-fly using efficient, high performance techniques. Ideally this should be performed using a trusted data service and common system libraries to ensure wide use and reproducibility. Recent developments in distributed computing based on dynamic access to significant cloud infrastructure opens the door for such new ways of processing geospatial data on demand. The National Computational Infrastructure (NCI), hosted at the Australian National University (ANU), has over 10 Petabytes of nationally significant research data collections. Some of these collections, which comprise a variety of observed and modelled geospatial data, are now made available via a highly distributed geospatial data server, called GSKY (pronounced [jee-skee]). GSKY supports on demand processing of large geospatial data products such as satellite earth observation data as well as numerical weather products, allowing interactive exploration and analysis of the data. It dynamically and efficiently distributes the required computations among cloud nodes providing a scalable analysis framework that can adapt to serve large number of concurrent users. Typical geospatial workflows handling different file formats and data types, or blending data in different coordinate projections and spatio-temporal resolutions, is handled transparently by GSKY. This is achieved by decoupling the data ingestion and indexing process as an independent service. An indexing service crawls data collections either locally or remotely by extracting, storing and indexing all spatio-temporal metadata associated with each individual record. GSKY provides the user with the ability of specifying how ingested data should be aggregated, transformed and presented. It presents an OGC standards-compliant interface, allowing ready accessibility for users of the data via Web Map Services (WMS), Web Processing Services (WPS) or raw data arrays using Web Coverage Services (WCS). The presentation will show some cases where we have used this new capability to provide a significant improvement over previous approaches.

The 18/30 GHz fixed communications system service demand assessment. Volume 2: Main text

NASA Technical Reports Server (NTRS)

Gabriszeski, T.; Reiner, P.; Rogers, J.; Terbo, W.

1979-01-01

The total demand for communications services, and satellite transmission services at the 4/6 GHz, 12/14 GHz, and 18/30 GHz frequencies is assessed. The services are voice, video, and data services. Traffic demand, by service, is distributed by geographical regions, population density, and distance between serving points. Further distribution of traffic is made among four major end user groups: business, government, institutions and private individuals. A traffic demand analysis is performed on a typical metropolitan city to examine service distribution trends. The projected cost of C and Ku band satellite systems are compared on an individual service basis to projected terrestrial rates. Separation of traffic between transmission systems, including 18/30 GHz systems, is based on cost, user, and technical considerations.

Dynamic ambulance reallocation for the reduction of ambulance response times using system status management.

PubMed

Lam, Sean Shao Wei; Zhang, Ji; Zhang, Zhong Cheng; Oh, Hong Choon; Overton, Jerry; Ng, Yih Yng; Ong, Marcus Eng Hock

2015-02-01

Dynamically reassigning ambulance deployment locations throughout a day to balance ambulance availability and demands can be effective in reducing response times. The objectives of this study were to model dynamic ambulance allocation plans in Singapore based on the system status management (SSM) strategy and to evaluate the dynamic deployment plans using a discrete event simulation (DES) model. The geographical information system-based analysis and mathematical programming were used to develop the dynamic ambulance deployment plans for SSM based on ambulance calls data from January 1, 2011, to June 30, 2011. A DES model that incorporated these plans was used to compare the performance of the dynamic SSM strategy against static reallocation policies under various demands and travel time uncertainties. When the deployment plans based on the SSM strategy were followed strictly, the DES model showed that the geographical information system-based plans resulted in approximately 13-second reduction in the median response times compared to the static reallocation policy, whereas the mathematical programming-based plans resulted in approximately a 44-second reduction. The response times and coverage performances were still better than the static policy when reallocations happened for only 60% of all the recommended moves. Dynamically reassigning ambulance deployment locations based on the SSM strategy can result in superior response times and coverage performance compared to static reallocation policies even when the dynamic plans were not followed strictly. Copyright © 2014 Elsevier Inc. All rights reserved.

Reconfiguration of the upper extremity relative to the pushrim affects load distribution during wheelchair propulsion.

PubMed

Munaretto, Joseph M; McNitt-Gray, Jill L; Flashner, Henryk; Requejo, Philip S

2013-08-01

Repetitive loading during manual wheelchair propulsion (WCP) is associated with overuse injury to the upper extremity (UE). The aim of this study was to determine how RF redirection and load distribution are affected by changes upper extremity kinematic modifications associated with modifications in seat positions during a WCP task. The aim of this study was to determine how RF redirection and load distribution are affected by upper extremity kinematic changes associated with seat position adjustment during a WCP task. Dynamic simulations using an experiment-based multi-link inverse dynamics model were used to generate solutions for redistributing UE mechanical load in different seating positions without decrements in WCP task performance. Experimental RF and kinematic data were collected for one subject propelling at a self-selected speed and used as input into the model. Shoulder/axle distance, wrist angular position, and RF direction were systematically modified to simulate how the mechanical demand imposed on the upper extremity (elbow and shoulder net joint moments (NJMs) and net joint forces) may vary. Load distribution depended on UE orientation relative to the wheel. At peak force, lower shoulder/axle distances and more anterior wrist positions on the pushrim allowed for more extended elbow positions and reduced total NJM load. Simulation results incorporating subject-specific data may provide mechanically based information to guide clinical interventions that aim to maintain WCP performance and redistribute load by modifying RF direction, seat configuration and hand/rim interaction. Copyright © 2012 IPEM. Published by Elsevier Ltd. All rights reserved.

A decision support tool for sustainable planning of urban water systems: presenting the Dynamic Urban Water Simulation Model.

PubMed

Willuweit, Lars; O'Sullivan, John J

2013-12-15

Population growth, urbanisation and climate change represent significant pressures on urban water resources, requiring water managers to consider a wider array of management options that account for economic, social and environmental factors. The Dynamic Urban Water Simulation Model (DUWSiM) developed in this study links urban water balance concepts with the land use dynamics model MOLAND and the climate model LARS-WG, providing a platform for long term planning of urban water supply and water demand by analysing the effects of urbanisation scenarios and climatic changes on the urban water cycle. Based on potential urbanisation scenarios and their effects on a city's water cycle, DUWSiM provides the functionality for assessing the feasibility of centralised and decentralised water supply and water demand management options based on forecasted water demand, stormwater and wastewater generation, whole life cost and energy and potential for water recycling. DUWSiM has been tested using data from Dublin, the capital of Ireland, and it has been shown that the model is able to satisfactorily predict water demand and stormwater runoff. Copyright © 2013 Elsevier Ltd. All rights reserved.

Intra-Urban Human Mobility and Activity Transition: Evidence from Social Media Check-In Data

PubMed Central

Wu, Lun; Zhi, Ye; Sui, Zhengwei; Liu, Yu

2014-01-01

Most existing human mobility literature focuses on exterior characteristics of movements but neglects activities, the driving force that underlies human movements. In this research, we combine activity-based analysis with a movement-based approach to model the intra-urban human mobility observed from about 15 million check-in records during a yearlong period in Shanghai, China. The proposed model is activity-based and includes two parts: the transition of travel demands during a specific time period and the movement between locations. For the first part, we find the transition probability between activities varies over time, and then we construct a temporal transition probability matrix to represent the transition probability of travel demands during a time interval. For the second part, we suggest that the travel demands can be divided into two classes, locationally mandatory activity (LMA) and locationally stochastic activity (LSA), according to whether the demand is associated with fixed location or not. By judging the combination of predecessor activity type and successor activity type we determine three trip patterns, each associated with a different decay parameter. To validate the model, we adopt the mechanism of an agent-based model and compare the simulated results with the observed pattern from the displacement distance distribution, the spatio-temporal distribution of activities, and the temporal distribution of travel demand transitions. The results show that the simulated patterns fit the observed data well, indicating that these findings open new directions for combining activity-based analysis with a movement-based approach using social media check-in data. PMID:24824892

Static and dynamic factors in an information-based multi-asset artificial stock market

NASA Astrophysics Data System (ADS)

Ponta, Linda; Pastore, Stefano; Cincotti, Silvano

2018-02-01

An information-based multi-asset artificial stock market characterized by different types of stocks and populated by heterogeneous agents is presented. In the market, agents trade risky assets in exchange for cash. Beside the amount of cash and of stocks owned, each agent is characterized by sentiments and agents share their sentiments by means of interactions that are determined by sparsely connected networks. A central market maker (clearing house mechanism) determines the price processes for each stock at the intersection of the demand and the supply curves. Single stock price processes exhibit volatility clustering and fat-tailed distribution of returns whereas multivariate price process exhibits both static and dynamic stylized facts, i.e., the presence of static factors and common trends. Static factors are studied making reference to the cross-correlation of returns of different stocks. The common trends are investigated considering the variance-covariance matrix of prices. Results point out that the probability distribution of eigenvalues of the cross-correlation matrix of returns shows the presence of sectors, similar to those observed on real empirical data. As regarding the dynamic factors, the variance-covariance matrix of prices point out a limited number of assets prices series that are independent integrated processes, in close agreement with the empirical evidence of asset price time series of real stock markets. These results remarks the crucial dependence of statistical properties of multi-assets stock market on the agents' interaction structure.

Optimization of pressure gauge locations for water distribution systems using entropy theory.

PubMed

Yoo, Do Guen; Chang, Dong Eil; Jun, Hwandon; Kim, Joong Hoon

2012-12-01

It is essential to select the optimal pressure gauge location for effective management and maintenance of water distribution systems. This study proposes an objective and quantified standard for selecting the optimal pressure gauge location by defining the pressure change at other nodes as a result of demand change at a specific node using entropy theory. Two cases are considered in terms of demand change: that in which demand at all nodes shows peak load by using a peak factor and that comprising the demand change of the normal distribution whose average is the base demand. The actual pressure change pattern is determined by using the emitter function of EPANET to reflect the pressure that changes practically at each node. The optimal pressure gauge location is determined by prioritizing the node that processes the largest amount of information it gives to (giving entropy) and receives from (receiving entropy) the whole system according to the entropy standard. The suggested model is applied to one virtual and one real pipe network, and the optimal pressure gauge location combination is calculated by implementing the sensitivity analysis based on the study results. These analysis results support the following two conclusions. Firstly, the installation priority of the pressure gauge in water distribution networks can be determined with a more objective standard through the entropy theory. Secondly, the model can be used as an efficient decision-making guide for gauge installation in water distribution systems.

Electron Microscopy of Living Cells During in Situ Fluorescence Microscopy

PubMed Central

Liv, Nalan; van Oosten Slingeland, Daan S. B.; Baudoin, Jean-Pierre; Kruit, Pieter; Piston, David W.; Hoogenboom, Jacob P.

2016-01-01

We present an approach toward dynamic nanoimaging: live fluorescence of cells encapsulated in a bionanoreactor is complemented with in situ scanning electron microscopy (SEM) on an integrated microscope. This allows us to take SEM snapshots on-demand, that is, at a specific location in time, at a desired region of interest, guided by the dynamic fluorescence imaging. We show that this approach enables direct visualization, with EM resolution, of the distribution of bioconjugated quantum dots on cellular extensions during uptake and internalization. PMID:26580231

Control of dispatch dynamics for lowering the cost of distributed generation in the built environment

NASA Astrophysics Data System (ADS)

Flores, Robert Joseph

Distributed generation can provide many benefits over traditional central generation such as increased reliability and efficiency while reducing emissions. Despite these potential benefits, distributed generation is generally not purchased unless it reduces energy costs. Economic dispatch strategies can be designed such that distributed generation technologies reduce overall facility energy costs. In this thesis, a microturbine generator is dispatched using different economic control strategies, reducing the cost of energy to the facility. Several industrial and commercial facilities are simulated using acquired electrical, heating, and cooling load data. Industrial and commercial utility rate structures are modeled after Southern California Edison and Southern California Gas Company tariffs and used to find energy costs for the simulated buildings and corresponding microturbine dispatch. Using these control strategies, building models, and utility rate models, a parametric study examining various generator characteristics is performed. An economic assessment of the distributed generation is then performed for both the microturbine generator and parametric study. Without the ability to export electricity to the grid, the economic value of distributed generation is limited to reducing the individual costs that make up the cost of energy for a building. Any economic dispatch strategy must be built to reduce these individual costs. While the ability of distributed generation to reduce cost depends of factors such as electrical efficiency and operations and maintenance cost, the building energy demand being serviced has a strong effect on cost reduction. Buildings with low load factors can accept distributed generation with higher operating costs (low electrical efficiency and/or high operations and maintenance cost) due to the value of demand reduction. As load factor increases, lower operating cost generators are desired due to a larger portion of the building load being met in an effort to reduce demand. In addition, buildings with large thermal demand have access to the least expensive natural gas, lowering the cost of operating distributed generation. Recovery of exhaust heat from DG reduces cost only if the buildings thermal demand coincides with the electrical demand. Capacity limits exist where annual savings from operation of distributed generation decrease if further generation is installed. For low operating cost generators, the approximate limit is the average building load. This limit decreases as operating costs increase. In addition, a high capital cost of distributed generation can be accepted if generator operating costs are low. As generator operating costs increase, capital cost must decrease if a positive economic performance is desired.

Coordinated control of micro-grid based on distributed moving horizon control.

PubMed

Ma, Miaomiao; Shao, Liyang; Liu, Xiangjie

2018-05-01

This paper proposed the distributed moving horizon coordinated control scheme for the power balance and economic dispatch problems of micro-grid based on distributed generation. We design the power coordinated controller for each subsystem via moving horizon control by minimizing a suitable objective function. The objective function of distributed moving horizon coordinated controller is chosen based on the principle that wind power subsystem has the priority to generate electricity while photovoltaic power generation coordinates with wind power subsystem and the battery is only activated to meet the load demand when necessary. The simulation results illustrate that the proposed distributed moving horizon coordinated controller can allocate the output power of two generation subsystems reasonably under varying environment conditions, which not only can satisfy the load demand but also limit excessive fluctuations of output power to protect the power generation equipment. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Research on Generating Method of Embedded Software Test Document Based on Dynamic Model

NASA Astrophysics Data System (ADS)

Qu, MingCheng; Wu, XiangHu; Tao, YongChao; Liu, Ying

2018-03-01

This paper provides a dynamic model-based test document generation method for embedded software that provides automatic generation of two documents: test requirements specification documentation and configuration item test documentation. This method enables dynamic test requirements to be implemented in dynamic models, enabling dynamic test demand tracking to be easily generated; able to automatically generate standardized, standardized test requirements and test documentation, improved document-related content inconsistency and lack of integrity And other issues, improve the efficiency.

Regional Differences in Demand for Coal as A Basis for Development of A Product Distribution Model for Mining Companies in the Individual Customers Segment

NASA Astrophysics Data System (ADS)

Magda, Roman; Bogacz, Paweł; Franik, Tadeusz; Celej, Maciej; Migza, Marcin

2014-10-01

The article presents a proposal of methodology based on the process of relationship marketing, serving to determine the level of demand for coal in the individual customer segment, as well as fuel distribution model for this customer group in Poland developed on the basis of this methodology. It also includes selected results of tests carried out using the proposed methods. These proposals have been defined on the basis of market capacity indicators, which can be determined for the district level based on data from the Polish Central Statistical Office. The study also included the use of linear programming, based on the cost of coal logistics, data concerning railway, road and storage infrastructure present on the Polish market and taking into account the legal aspects. The presented results may provide a basis for mining companies to develop a system of coal distribution management in the locations with the highest demand values.

Market-based demand forecasting promotes informed strategic financial planning.

PubMed

Beech, A J

2001-11-01

Market-based demand forecasting is a method of estimating future demand for a healthcare organization's services by using a broad range of data that describe the nature of demand within the organization's service area. Such data include the primary and secondary service areas, the service-area populations by various demographic groupings, discharge utilization rates, market size, and market share by service line and organizationwide. Based on observable market dynamics, strategic planners can make a variety of explicit assumptions about future trends regarding these data to develop scenarios describing potential future demand. Financial planners then can evaluate each scenario to determine its potential effect on selected financial and operational measures, such as operating margin, days cash on hand, and debt-service coverage, and develop a strategic financial plan that covers a range of contingencies.

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

NASA Astrophysics Data System (ADS)

Hortos, William S.

1997-04-01

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

Natural Gas Value-Chain and Network Assessments

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

Kobos, Peter H.; Outkin, Alexander V.; Beyeler, Walter E.

2015-09-01

The current expansion of natural gas (NG) development in the United States requires an understanding of how this change will affect the natural gas industry, downstream consumers, and economic growth in order to promote effective planning and policy development. The impact of this expansion may propagate through the NG system and US economy via changes in manufacturing, electric power generation, transportation, commerce, and increased exports of liquefied natural gas. We conceptualize this problem as supply shock propagation that pushes the NG system and the economy away from its current state of infrastructure development and level of natural gas use. Tomore » illustrate this, the project developed two core modeling approaches. The first is an Agent-Based Modeling (ABM) approach which addresses shock propagation throughout the existing natural gas distribution system. The second approach uses a System Dynamics-based model to illustrate the feedback mechanisms related to finding new supplies of natural gas - notably shale gas - and how those mechanisms affect exploration investments in the natural gas market with respect to proven reserves. The ABM illustrates several stylized scenarios of large liquefied natural gas (LNG) exports from the U.S. The ABM preliminary results demonstrate that such scenario is likely to have substantial effects on NG prices and on pipeline capacity utilization. Our preliminary results indicate that the price of natural gas in the U.S. may rise by about 50% when the LNG exports represent 15% of the system-wide demand. The main findings of the System Dynamics model indicate that proven reserves for coalbed methane, conventional gas and now shale gas can be adequately modeled based on a combination of geologic, economic and technology-based variables. A base case scenario matches historical proven reserves data for these three types of natural gas. An environmental scenario, based on implementing a $50/tonne CO 2 tax results in less proven reserves being developed in the coming years while demand may decrease in the absence of acceptable substitutes, incentives or changes in consumer behavior. An increase in demand of 25% increases proven reserves being developed by a very small amount by the end of the forecast period of 2025.« less

Operational characterisation of requirements and early validation environment for high demanding space systems

NASA Technical Reports Server (NTRS)

Barro, E.; Delbufalo, A.; Rossi, F.

1993-01-01

The definition of some modern high demanding space systems requires a different approach to system definition and design from that adopted for traditional missions. System functionality is strongly coupled to the operational analysis, aimed at characterizing the dynamic interactions of the flight element with its surrounding environment and its ground control segment. Unambiguous functional, operational and performance requirements are to be defined for the system, thus improving also the successive development stages. This paper proposes a Petri Nets based methodology and two related prototype applications (to ARISTOTELES orbit control and to Hermes telemetry generation) for the operational analysis of space systems through the dynamic modeling of their functions and a related computer aided environment (ISIDE) able to make the dynamic model work, thus enabling an early validation of the system functional representation, and to provide a structured system requirements data base, which is the shared knowledge base interconnecting static and dynamic applications, fully traceable with the models and interfaceable with the external world.

A Vision for Co-optimized T&D System Interaction with Renewables and Demand Response

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

Anderson, C. Lindsay; Zéphyr, Luckny; Liu, Jialin

The evolution of the power system to the reliable, effi- cient and sustainable system of the future will involve development of both demand- and supply-side technology and operations. The use of demand response to counterbalance the intermittency of re- newable generation brings the consumer into the spotlight. Though individual consumers are interconnected at the low-voltage distri- bution system, these resources are typically modeled as variables at the transmission network level. In this paper, a vision for co- optimized interaction of distribution systems, or microgrids, with the high-voltage transmission system is described. In this frame- work, microgrids encompass consumers, distributed renewablesmore » and storage. The energy management system of the microgrid can also sell (buy) excess (necessary) energy from the transmission system. Preliminary work explores price mechanisms to manage the microgrid and its interactions with the transmission system. Wholesale market operations are addressed through the devel- opment of scalable stochastic optimization methods that provide the ability to co-optimize interactions between the transmission and distribution systems. Modeling challenges of the co-optimization are addressed via solution methods for large-scale stochastic op- timization, including decomposition and stochastic dual dynamic programming.« less

A Multiple-player-game Approach to Agricultural Water Use in Regions of Seasonal Drought

NASA Astrophysics Data System (ADS)

Lu, Z.

2013-12-01

In the wide distributed regions of seasonal drought, conflicts of water allocation between multiple stakeholders (which means water consumers and policy makers) are frequent and severe problems. These conflicts become extremely serious in the dry seasons, and are ultimately caused by an intensive disparity between the lack of natural resource and the great demand of social development. Meanwhile, these stakeholders are often both competitors and cooperators in water saving problems, because water is a type of public resource. Conflicts often occur due to lack of appropriate water allocation scheme. Among the many uses of water, the need of agricultural irrigation water is highly elastic, but this factor has not yet been made full use to free up water from agriculture use. The primary goal of this work is to design an optimal distribution scheme of water resource for dry seasons to maximize benefits from precious water resources, considering the high elasticity of agriculture water demand due to the dynamic of soil moisture affected by the uncertainty of precipitation and other factors like canopy interception. A dynamic programming model will be used to figure out an appropriate allocation of water resources among agricultural irrigation and other purposes like drinking water, industry, and hydropower, etc. In this dynamic programming model, we analytically quantify the dynamic of soil moisture in the agricultural fields by describing the interception with marked Poisson process and describing the rainfall depth with exponential distribution. Then, we figure out a water-saving irrigation scheme, which regulates the timetable and volumes of water in irrigation, in order to minimize irrigation water requirement under the premise of necessary crop yield (as a constraint condition). And then, in turn, we provide a scheme of water resource distribution/allocation among agriculture and other purposes, taking aim at maximizing benefits from precious water resources, or in other words, make best use of limited water resource.

Evolution of weighted complex bus transit networks with flow

NASA Astrophysics Data System (ADS)

Huang, Ailing; Xiong, Jie; Shen, Jinsheng; Guan, Wei

2016-02-01

Study on the intrinsic properties and evolutional mechanism of urban public transit networks (PTNs) has great significance for transit planning and control, particularly considering passengers’ dynamic behaviors. This paper presents an empirical analysis for exploring the complex properties of Beijing’s weighted bus transit network (BTN) based on passenger flow in L-space, and proposes a bi-level evolution model to simulate the development of transit routes from the view of complex network. The model is an iterative process that is driven by passengers’ travel demands and dual-controlled interest mechanism, which is composed of passengers’ spatio-temporal requirements and cost constraint of transit agencies. Also, the flow’s dynamic behaviors, including the evolutions of travel demand, sectional flow attracted by a new link and flow perturbation triggered in nearby routes, are taken into consideration in the evolutional process. We present the numerical experiment to validate the model, where the main parameters are estimated by using distribution functions that are deduced from real-world data. The results obtained have proven that our model can generate a BTN with complex properties, such as the scale-free behavior or small-world phenomenon, which shows an agreement with our empirical results. Our study’s results can be exploited to optimize the real BTN’s structure and improve the network’s robustness.

Blue water scarcity and the economic impacts of future agricultural trade and demand

NASA Astrophysics Data System (ADS)

Schmitz, Christoph; Lotze-Campen, Hermann; Gerten, Dieter; Dietrich, Jan Philipp; Bodirsky, Benjamin; Biewald, Anne; Popp, Alexander

2013-06-01

An increasing demand for agricultural goods affects the pressure on global water resources over the coming decades. In order to quantify these effects, we have developed a new agroeconomic water scarcity indicator, considering explicitly economic processes in the agricultural system. The indicator is based on the water shadow price generated by an economic land use model linked to a global vegetation-hydrology model. Irrigation efficiency is implemented as a dynamic input depending on the level of economic development. We are able to simulate the heterogeneous distribution of water supply and agricultural water demand for irrigation through the spatially explicit representation of agricultural production. This allows in identifying regional hot spots of blue water scarcity and explicit shadow prices for water. We generate scenarios based on moderate policies regarding future trade liberalization and the control of livestock-based consumption, dependent on different population and gross domestic product (GDP) projections. Results indicate increased water scarcity in the future, especially in South Asia, the Middle East, and north Africa. In general, water shadow prices decrease with increasing liberalization, foremost in South Asia, Southeast Asia, and the Middle East. Policies to reduce livestock consumption in developed countries not only lower the domestic pressure on water but also alleviate water scarcity to a large extent in developing countries. It is shown that one of the two policy options would be insufficient for most regions to retain water scarcity in 2045 on levels comparable to 2005.

BIRD: Bio-Image Referral Database. Design and implementation of a new web based and patient multimedia data focused system for effective medical diagnosis and therapy.

PubMed

Pinciroli, Francesco; Masseroli, Marco; Acerbo, Livio A; Bonacina, Stefano; Ferrari, Roberto; Marchente, Mario

2004-01-01

This paper presents a low cost software platform prototype supporting health care personnel in retrieving patient referral multimedia data. These information are centralized in a server machine and structured by using a flexible eXtensible Markup Language (XML) Bio-Image Referral Database (BIRD). Data are distributed on demand to requesting client in an Intranet network and transformed via eXtensible Stylesheet Language (XSL) to be visualized in an uniform way on market browsers. The core server operation software has been developed in PHP Hypertext Preprocessor scripting language, which is very versatile and useful for crafting a dynamic Web environment.

Advanced Laser-Based Techniques for Gas-Phase Diagnostics in Combustion and Aerospace Engineering.

PubMed

Ehn, Andreas; Zhu, Jiajian; Li, Xuesong; Kiefer, Johannes

2017-03-01

Gaining information of species, temperature, and velocity distributions in turbulent combustion and high-speed reactive flows is challenging, particularly for conducting measurements without influencing the experimental object itself. The use of optical and spectroscopic techniques, and in particular laser-based diagnostics, has shown outstanding abilities for performing non-intrusive in situ diagnostics. The development of instrumentation, such as robust lasers with high pulse energy, ultra-short pulse duration, and high repetition rate along with digitized cameras exhibiting high sensitivity, large dynamic range, and frame rates on the order of MHz, has opened up for temporally and spatially resolved volumetric measurements of extreme dynamics and complexities. The aim of this article is to present selected important laser-based techniques for gas-phase diagnostics focusing on their applications in combustion and aerospace engineering. Applicable laser-based techniques for investigations of turbulent flows and combustion such as planar laser-induced fluorescence, Raman and Rayleigh scattering, coherent anti-Stokes Raman scattering, laser-induced grating scattering, particle image velocimetry, laser Doppler anemometry, and tomographic imaging are reviewed and described with some background physics. In addition, demands on instrumentation are further discussed to give insight in the possibilities that are offered by laser flow diagnostics.

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

Emergency material allocation with time-varying supply-demand based on dynamic optimization method for river chemical spills.

PubMed

Liu, Jie; Guo, Liang; Jiang, Jiping; Jiang, Dexun; Wang, Peng

2018-04-13

Aiming to minimize the damage caused by river chemical spills, efficient emergency material allocation is critical for an actual emergency rescue decision-making in a quick response. In this study, an emergency material allocation framework based on time-varying supply-demand constraint is developed to allocate emergency material, minimize the emergency response time, and satisfy the dynamic emergency material requirements in post-accident phases dealing with river chemical spills. In this study, the theoretically critical emergency response time is firstly obtained for the emergency material allocation system to select a series of appropriate emergency material warehouses as potential supportive centers. Then, an enumeration method is applied to identify the practically critical emergency response time, the optimum emergency material allocation and replenishment scheme. Finally, the developed framework is applied to a computational experiment based on south-to-north water transfer project in China. The results illustrate that the proposed methodology is a simple and flexible tool for appropriately allocating emergency material to satisfy time-dynamic demands during emergency decision-making. Therefore, the decision-makers can identify an appropriate emergency material allocation scheme in a balance between time-effective and cost-effective objectives under the different emergency pollution conditions.

Reinforcement learning techniques for controlling resources in power networks

NASA Astrophysics Data System (ADS)

Kowli, Anupama Sunil

As power grids transition towards increased reliance on renewable generation, energy storage and demand response resources, an effective control architecture is required to harness the full functionalities of these resources. There is a critical need for control techniques that recognize the unique characteristics of the different resources and exploit the flexibility afforded by them to provide ancillary services to the grid. The work presented in this dissertation addresses these needs. Specifically, new algorithms are proposed, which allow control synthesis in settings wherein the precise distribution of the uncertainty and its temporal statistics are not known. These algorithms are based on recent developments in Markov decision theory, approximate dynamic programming and reinforcement learning. They impose minimal assumptions on the system model and allow the control to be "learned" based on the actual dynamics of the system. Furthermore, they can accommodate complex constraints such as capacity and ramping limits on generation resources, state-of-charge constraints on storage resources, comfort-related limitations on demand response resources and power flow limits on transmission lines. Numerical studies demonstrating applications of these algorithms to practical control problems in power systems are discussed. Results demonstrate how the proposed control algorithms can be used to improve the performance and reduce the computational complexity of the economic dispatch mechanism in a power network. We argue that the proposed algorithms are eminently suitable to develop operational decision-making tools for large power grids with many resources and many sources of uncertainty.

The Distributed Geothermal Market Demand Model (dGeo): Documentation

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

McCabe, Kevin; Mooney, Meghan E; Sigrin, Benjamin O

The National Renewable Energy Laboratory (NREL) developed the Distributed Geothermal Market Demand Model (dGeo) as a tool to explore the potential role of geothermal distributed energy resources (DERs) in meeting thermal energy demands in the United States. The dGeo model simulates the potential for deployment of geothermal DERs in the residential and commercial sectors of the continental United States for two specific technologies: ground-source heat pumps (GHP) and geothermal direct use (DU) for district heating. To quantify the opportunity space for these technologies, dGeo leverages a highly resolved geospatial database and robust bottom-up, agent-based modeling framework. This design is consistentmore » with others in the family of Distributed Generation Market Demand models (dGen; Sigrin et al. 2016), including the Distributed Solar Market Demand (dSolar) and Distributed Wind Market Demand (dWind) models. dGeo is intended to serve as a long-term scenario-modeling tool. It has the capability to simulate the technical potential, economic potential, market potential, and technology deployment of GHP and DU through the year 2050 under a variety of user-defined input scenarios. Through these capabilities, dGeo can provide substantial analytical value to various stakeholders interested in exploring the effects of various techno-economic, macroeconomic, financial, and policy factors related to the opportunity for GHP and DU in the United States. This report documents the dGeo modeling design, methodology, assumptions, and capabilities.« less

The Influence of Wheelchair Propulsion Hand Pattern on Upper Extremity Muscle Power and Stress

PubMed Central

Slowik, Jonathan S.; Requejo, Philip S.; Mulroy, Sara J.; Neptune, Richard R.

2016-01-01

The hand pattern (i.e., full-cycle hand path) used during manual wheelchair propulsion is frequently classified as one of four distinct hand pattern types: arc, single loop, double loop and semicircular. Current clinical guidelines recommend the use of the semicircular pattern, which is based on advantageous levels of broad biomechanical metrics implicitly related to the demand placed on the upper extremity (e.g., lower cadence). However, an understanding of the influence of hand pattern on specific measures of upper extremity muscle demand (e.g., muscle power and stress) is needed to help make such recommendations, but these quantities are difficult and impractical to measure experimentally. The purpose of this study was to use musculoskeletal modeling and forward dynamics simulations to investigate the influence of the hand pattern used on specific measures of upper extremity muscle demand. The simulation results suggest that the double loop and semicircular patterns produce the most favorable levels of overall muscle stress and total muscle power. The double loop pattern had the lowest full-cycle and recovery-phase upper extremity demand but required high levels of muscle power during the relatively short contact phase. The semicircular pattern had the second-lowest full-cycle levels of overall muscle stress and total muscle power, and demand was more evenly distributed between the contact and recovery phases. These results suggest that in order to decrease upper extremity demand, manual wheelchair users should use either the double loop or semicircular pattern when propelling their wheelchairs at a self-selected speed on level ground. PMID:27062591

EQUITY EVALUATION OF PADDY IRRIGATION WATER DISTRIBUTION BY SOCIETY-JUSTICE-WATER DISTRIBUTION RULE HYPOTHESIS

NASA Astrophysics Data System (ADS)

Tanji, Hajime; Kiri, Hirohide; Kobayashi, Shintaro

When total supply is smaller than total demand, it is difficult to apply the paddy irrigation water distribution rule. The gap must be narrowed by decreasing demand. Historically, the upstream served rule, rotation schedule, or central schedule weight to irrigated area was adopted. This paper proposes the hypothesis that these rules are dependent on social justice, a hypothesis called the "Society-Justice-Water Distribution Rule Hypothesis". Justice, which means a balance of efficiency and equity of distribution, is discussed under the political philosophy of utilitarianism, liberalism (Rawls), libertarianism, and communitarianism. The upstream served rule can be derived from libertarianism. The rotation schedule and central schedule can be derived from communitarianism. Liberalism can provide arranged schedule to adjust supply and demand based on "the Difference Principle". The authors conclude that to achieve efficiency and equity, liberalism may provide the best solution after modernization.

Application of dynamic traffic assignment to advanced managed lane modeling.

DOT National Transportation Integrated Search

2013-11-01

In this study, a demand estimation framework is developed for assessing the managed lane (ML) : strategies by utilizing dynamic traffic assignment (DTA) modeling, instead of the traditional : approaches that are based on the static traffic assignment...

Models@Home: distributed computing in bioinformatics using a screensaver based approach.

PubMed

Krieger, Elmar; Vriend, Gert

2002-02-01

Due to the steadily growing computational demands in bioinformatics and related scientific disciplines, one is forced to make optimal use of the available resources. A straightforward solution is to build a network of idle computers and let each of them work on a small piece of a scientific challenge, as done by Seti@Home (http://setiathome.berkeley.edu), the world's largest distributed computing project. We developed a generally applicable distributed computing solution that uses a screensaver system similar to Seti@Home. The software exploits the coarse-grained nature of typical bioinformatics projects. Three major considerations for the design were: (1) often, many different programs are needed, while the time is lacking to parallelize them. Models@Home can run any program in parallel without modifications to the source code; (2) in contrast to the Seti project, bioinformatics applications are normally more sensitive to lost jobs. Models@Home therefore includes stringent control over job scheduling; (3) to allow use in heterogeneous environments, Linux and Windows based workstations can be combined with dedicated PCs to build a homogeneous cluster. We present three practical applications of Models@Home, running the modeling programs WHAT IF and YASARA on 30 PCs: force field parameterization, molecular dynamics docking, and database maintenance.

A Fast and Precise Indoor Localization Algorithm Based on an Online Sequential Extreme Learning Machine †

PubMed Central

Zou, Han; Lu, Xiaoxuan; Jiang, Hao; Xie, Lihua

2015-01-01

Nowadays, developing indoor positioning systems (IPSs) has become an attractive research topic due to the increasing demands on location-based service (LBS) in indoor environments. WiFi technology has been studied and explored to provide indoor positioning service for years in view of the wide deployment and availability of existing WiFi infrastructures in indoor environments. A large body of WiFi-based IPSs adopt fingerprinting approaches for localization. However, these IPSs suffer from two major problems: the intensive costs of manpower and time for offline site survey and the inflexibility to environmental dynamics. In this paper, we propose an indoor localization algorithm based on an online sequential extreme learning machine (OS-ELM) to address the above problems accordingly. The fast learning speed of OS-ELM can reduce the time and manpower costs for the offline site survey. Meanwhile, its online sequential learning ability enables the proposed localization algorithm to adapt in a timely manner to environmental dynamics. Experiments under specific environmental changes, such as variations of occupancy distribution and events of opening or closing of doors, are conducted to evaluate the performance of OS-ELM. The simulation and experimental results show that the proposed localization algorithm can provide higher localization accuracy than traditional approaches, due to its fast adaptation to various environmental dynamics. PMID:25599427

A System Dynamics Modeling of Water Supply and Demand in Las Vegas Valley

NASA Astrophysics Data System (ADS)

Parajuli, R.; Kalra, A.; Mastino, L.; Velotta, M.; Ahmad, S.

2017-12-01

The rise in population and change in climate have posed the uncertainties in the balance between supply and demand of water. The current study deals with the water management issues in Las Vegas Valley (LVV) using Stella, a system dynamics modeling software, to model the feedback based relationship between supply and demand parameters. Population parameters were obtained from Center for Business and Economic Research while historical water demand and conservation practices were modeled as per the information provided by local authorities. The water surface elevation of Lake Mead, which is the prime source of water supply to the region, was modeled as the supply side whereas the water demand in LVV was modeled as the demand side. The study was done from the period of 1989 to 2049 with 1989 to 2012 as the historical one and the period from 2013 to 2049 as the future period. This study utilizes Coupled Model Intercomparison Project data sets (2013-2049) (CMIP3&5) to model different future climatic scenarios. The model simulates the past dynamics of supply and demand, and then forecasts the future water budget for the forecasted future population and future climatic conditions. The results can be utilized by the water authorities in understanding the future water status and hence plan suitable conservation policies to allocate future water budget and achieve sustainable water management.

An Agent-Based Modeling Framework and Application for the Generic Nuclear Fuel Cycle

NASA Astrophysics Data System (ADS)

Gidden, Matthew J.

Key components of a novel methodology and implementation of an agent-based, dynamic nuclear fuel cycle simulator, Cyclus , are presented. The nuclear fuel cycle is a complex, physics-dependent supply chain. To date, existing dynamic simulators have not treated constrained fuel supply, time-dependent, isotopic-quality based demand, or fuel fungibility particularly well. Utilizing an agent-based methodology that incorporates sophisticated graph theory and operations research techniques can overcome these deficiencies. This work describes a simulation kernel and agents that interact with it, highlighting the Dynamic Resource Exchange (DRE), the supply-demand framework at the heart of the kernel. The key agent-DRE interaction mechanisms are described, which enable complex entity interaction through the use of physics and socio-economic models. The translation of an exchange instance to a variant of the Multicommodity Transportation Problem, which can be solved feasibly or optimally, follows. An extensive investigation of solution performance and fidelity is then presented. Finally, recommendations for future users of Cyclus and the DRE are provided.

Distributed Energy Generation Systems Based on Renewable Energy and Natural Gas Blending: New Business Models for Economic Incentives, Electricity Market Design and Regulatory Innovation

NASA Astrophysics Data System (ADS)

Nyangon, Joseph

Expansion of distributed energy resources (DERs) including solar photovoltaics, small- and medium-sized wind farms, gas-fired distributed generation, demand-side management, and energy storage poses significant complications to the design, operation, business model, and regulation of electricity systems. Using statistical regression analysis, this dissertation assesses if increased use of natural gas results in reduced renewable energy capacity, and if natural gas growth is correlated with increased or decreased non-fossil renewable fuels demand. System Generalized Method of Moments (System GMM) estimation of the dynamic relationship was performed on the indicators in the econometric model for the ten states with the fastest growth in solar generation capacity in the U.S. (e.g., California, North Carolina, Arizona, Nevada, New Jersey, Utah, Massachusetts, Georgia, Texas, and New York) to analyze the effect of natural gas on renewable energy diffusion and the ratio of fossil fuels increase for the period 2001-2016 to policy driven solar demand. The study identified ten major drivers of change in electricity systems, including growth in distributed energy generation systems such as intermittent renewable electricity and gas-fired distributed generation; flat to declining electricity demand growth; aging electricity infrastructure and investment gaps; proliferation of affordable information and communications technologies (e.g., advanced meters or interval meters), increasing innovations in data and system optimization; and greater customer engagement. In this ongoing electric power sector transformation, natural gas and fast-flexing renewable resources (mostly solar and wind energy) complement each other in several sectors of the economy. The dissertation concludes that natural gas has a positive impact on solar and wind energy development: a 1% rise in natural gas capacity produces 0.0304% increase in the share of renewable energy in the short-run (monthly) compared to the long-term effect estimated at 0.9696% (15-year period). Evidence from the main policy, environmental, and economic indicators for solar and wind-power development such as feed-in tariffs, state renewable portfolio standards, public benefits fund, net metering, interconnection standards, environmental quality, electricity import ratio, per-capita energy-related carbon dioxide emissions, average electricity price, per-capita real gross domestic product, and energy intensity are discussed and evaluated in detail in order to elucidate their effectiveness in supporting the utility industry transformation. The discussion is followed by a consideration of a plausible distributed utility framework that is tailored for major DERs development that has emerged in New York called Reforming the Energy Vision. This framework provides a conceptual base with which to imagine the utility of the future as well as a practical solution to study the potential of DERs in other states. The dissertation finds this grid and market modernization initiative has considerable influence and importance beyond New York in the development of a new market economy in which customer choice and distributed utilities are prominent.

Earth Observation in Support of Sustainable Urban Planning: Results of the Dragon-3 Monitor Project

NASA Astrophysics Data System (ADS)

Cartalis, C.; Polydoros, A.; Mavrakou, T.; Asimakopoulos, D. N.

2016-08-01

Sustainable urban planning increasingly demands innovative concepts and techniques to obtain up-to-date and area-wide information on the characteristics and development of the urban system. In this paper, a thorough and conclusive presentation is made in terms of the results of the DRAGON-3 MONITOR project as based on the use of Earth Observation. Results refer in particular to a set of EO based dynamic urban indicators (i.e. urban form and expansion, land use/land cover changes, land surface temperature distribution, the presence and strength of urban heat island) with the capacity to describe the state, dynamic changes and interaction of the land and thermal environment in urban areas. Furthermore results are assessed in terms of their potential to operationally support sustainable urban planning and bridge the gap between EO scientists and urban planners. Constraints related to the spatial resolution and revisit time of satellite sensors are discussed as they influence the accuracy and applicability of the indicators. Methodologies to improve the applicability of the indicators are also discussed along with the presentation of the respective results.

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.

Mesoscopic Effects in an Agent-Based Bargaining Model in Regular Lattices

PubMed Central

Poza, David J.; Santos, José I.; Galán, José M.; López-Paredes, Adolfo

2011-01-01

The effect of spatial structure has been proved very relevant in repeated games. In this work we propose an agent based model where a fixed finite population of tagged agents play iteratively the Nash demand game in a regular lattice. The model extends the multiagent bargaining model by Axtell, Epstein and Young [1] modifying the assumption of global interaction. Each agent is endowed with a memory and plays the best reply against the opponent's most frequent demand. We focus our analysis on the transient dynamics of the system, studying by computer simulation the set of states in which the system spends a considerable fraction of the time. The results show that all the possible persistent regimes in the global interaction model can also be observed in this spatial version. We also find that the mesoscopic properties of the interaction networks that the spatial distribution induces in the model have a significant impact on the diffusion of strategies, and can lead to new persistent regimes different from those found in previous research. In particular, community structure in the intratype interaction networks may cause that communities reach different persistent regimes as a consequence of the hindering diffusion effect of fluctuating agents at their borders. PMID:21408019

Mesoscopic effects in an agent-based bargaining model in regular lattices.

PubMed

Poza, David J; Santos, José I; Galán, José M; López-Paredes, Adolfo

2011-03-09

The effect of spatial structure has been proved very relevant in repeated games. In this work we propose an agent based model where a fixed finite population of tagged agents play iteratively the Nash demand game in a regular lattice. The model extends the multiagent bargaining model by Axtell, Epstein and Young modifying the assumption of global interaction. Each agent is endowed with a memory and plays the best reply against the opponent's most frequent demand. We focus our analysis on the transient dynamics of the system, studying by computer simulation the set of states in which the system spends a considerable fraction of the time. The results show that all the possible persistent regimes in the global interaction model can also be observed in this spatial version. We also find that the mesoscopic properties of the interaction networks that the spatial distribution induces in the model have a significant impact on the diffusion of strategies, and can lead to new persistent regimes different from those found in previous research. In particular, community structure in the intratype interaction networks may cause that communities reach different persistent regimes as a consequence of the hindering diffusion effect of fluctuating agents at their borders.

The future of copper in China--A perspective based on analysis of copper flows and stocks.

PubMed

Zhang, Ling; Cai, Zhijian; Yang, Jiameng; Yuan, Zengwei; Chen, Yan

2015-12-01

This study attempts to speculate on the future of copper metabolism in China based on dynamic substance flow analysis. Based on tremendous growth of copper consumption over the past 63 years, China will depict a substantially increasing trend of copper in-use stocks for the next 30 years. The highest peak will be possibly achieved in 2050, with the maximum ranging between 163 Mt and 171 Mt. After that, total stocks are expected to slowly decline 147-154 Mt by the year 2080. Owing to the increasing demand of in-use stocks, China will continue to have a profound impact on global copper consumption with its high import dependence until around 2020, and the peak demand for imported copper are expected to approach 5.5 Mt/year. Thereafter, old scrap generated by domestic society will occupy an increasingly important role in copper supply. In around 2060, approximately 80% of copper resources could come from domestic recycling of old scrap, implying a major shift from primary production to secondary production. With regard to the effect of lifetime distribution uncertainties in different end-use sectors of copper stocks on the predict results, uncertainty evaluation was performed and found the model was relatively robust to these changes. Copyright © 2015 Elsevier B.V. All rights reserved.

Autonomous Decentralized Control of Supply and Demand by Inverter Based Distributed Generations in Isolated Microgrid

NASA Astrophysics Data System (ADS)

Shiki, Akira; Yokoyama, Akihiko; Baba, Jyunpei; Takano, Tomihiro; Gouda, Takahiro; Izui, Yoshio

Recently, because of the environmental burden mitigation, energy conservations, energy security, and cost reductions, distributed generations are attracting our strong attention. These distributed generations (DGs) have been already installed to the distribution system, and much more DGs will be expected to be connected in the future. On the other hand, a new concept called “Microgrid” which is a small power supply network consisting of only DGs was proposed and some prototype projects are ongoing in Japan. The purpose of this paper is to develop the three-phase instantaneous valued digital simulator of microgrid consisting of a lot of inverter based DGs and to develop a supply and demand control method in isolated microgrid. First, microgrid is modeled using MATLAB/SIMULINK. We develop models of three-phase instantaneous valued inverter type CVCF generator, PQ specified generator, PV specified generator, PQ specified load as storage battery, photovoltaic generation, fuel cell and inverter load respectively. Then we propose an autonomous decentralized control method of supply and demand in isolated microgrid where storage batteries, fuel cells, photovoltaic generations and loads are connected. It is proposed here that the system frequency is used as a means to control DG output. By changing the frequency of the storage battery due to unbalance of supply and demand, all inverter based DGs detect the frequency fluctuation and change their own outputs. Finally, a new frequency control method in autonomous decentralized control of supply and demand is proposed. Though the frequency is used to transmit the information on the supply and demand unbalance to DGs, after the frequency plays the role, the frequency finally has to return to a standard value. To return the frequency to the standard value, the characteristic curve of the fuel cell is shifted in parallel. This control is carried out corresponding to the fluctuation of the load. The simulation shows that the frequency can be controlled well and has been made clear the effectiveness of the frequency control system.

Smart Building: Decision Making Architecture for Thermal Energy Management.

PubMed

Uribe, Oscar Hernández; Martin, Juan Pablo San; Garcia-Alegre, María C; Santos, Matilde; Guinea, Domingo

2015-10-30

Smart applications of the Internet of Things are improving the performance of buildings, reducing energy demand. Local and smart networks, soft computing methodologies, machine intelligence algorithms and pervasive sensors are some of the basics of energy optimization strategies developed for the benefit of environmental sustainability and user comfort. This work presents a distributed sensor-processor-communication decision-making architecture to improve the acquisition, storage and transfer of thermal energy in buildings. The developed system is implemented in a near Zero-Energy Building (nZEB) prototype equipped with a built-in thermal solar collector, where optical properties are analysed; a low enthalpy geothermal accumulation system, segmented in different temperature zones; and an envelope that includes a dynamic thermal barrier. An intelligent control of this dynamic thermal barrier is applied to reduce the thermal energy demand (heating and cooling) caused by daily and seasonal weather variations. Simulations and experimental results are presented to highlight the nZEB thermal energy reduction.

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

Base stock system for patient vs impatient customers with varying demand distribution

NASA Astrophysics Data System (ADS)

Fathima, Dowlath; Uduman, P. Sheik

2013-09-01

An optimal Base-Stock inventory policy for Patient and Impatient Customers using finite-horizon models is examined. The Base stock system for Patient and Impatient customers is a different type of inventory policy. In case of the model I, Base stock for Patient customer case is evaluated using the Truncated Exponential Distribution. The model II involves the study of Base-stock inventory policies for Impatient customer. A study on these systems reveals that the Customers wait until the arrival of the next order or the customers leaves the system which leads to lost sale. In both the models demand during the period [0, t] is taken to be a random variable. In this paper, Truncated Exponential Distribution satisfies the Base stock policy for the patient customer as a continuous model. So far the Base stock for Impatient Customers leaded to a discrete case but, in this paper we have modeled this condition into a continuous case. We justify this approach mathematically and also numerically.

An integrated and dynamic optimisation model for the multi-level emergency logistics network in anti-bioterrorism system

NASA Astrophysics Data System (ADS)

Liu, Ming; Zhao, Lindu

2012-08-01

Demand for emergency resources is usually uncertain and varies quickly in anti-bioterrorism system. Besides, emergency resources which had been allocated to the epidemic areas in the early rescue cycle will affect the demand later. In this article, an integrated and dynamic optimisation model with time-varying demand based on the epidemic diffusion rule is constructed. The heuristic algorithm coupled with the MATLAB mathematical programming solver is adopted to solve the optimisation model. In what follows, the application of the optimisation model as well as a short sensitivity analysis of the key parameters in the time-varying demand forecast model is presented. The results show that both the model and the solution algorithm are useful in practice, and both objectives of inventory level and emergency rescue cost can be controlled effectively. Thus, it can provide some guidelines for decision makers when coping with emergency rescue problem with uncertain demand, and offers an excellent reference when issues pertain to bioterrorism.

[The decline in population growth, income distribution, and economic recession].

PubMed

Banguero, H

1983-05-01

This work uses Keynesian principles and an analysis of the Colombian population in the 1970s to argue that the Colombian policy of slowing population growth, which was adopted with the aim of improving the general welfare of the population, has had shortterm negative effects on effective demand and thus on the level of employment and welfare. These negative effects were caused by the inflexibility of income distribution, which prevented expansion of the internal market, complicated by the stagnant condition of the external sector and the budget deficit. The results of the Colombian case study demonstrate how the deceleration of population growth beginning in the 1960s had a significant impact on the levels of consumption and savings and on the patterns of consumption, leading to low levels of investment and little dynamism. Although the current Colombian economic recession is aggravated by contextual factors such as the world economic recession, the high cost of capital, the industrial recession, and declining food production among others, at the core of the crisis are longer term structural determinants such as the decline in the rate of population growth and the highly unequal distribution of income and wealth, which have contributed to a shrinking of the internal market for some types of goods. Given the unlikelihood of renewed rapid population growth, the Keynesian model suggests that the only alternative for increasing aggregate demand is state intervention through public spending and investment and reorientation of the financial system to achieve a dynamic redistribution of income. Based on these findings and on proposals of other analysts, a stragegy for revitalization is proposed which would imply a gradual income redistribution to allow increased consumption of mass produced goods by the low income groups. Direct consumption subsidies would be avoided because of their inflationary and import-expanding tendencies; rather, incentives and support would be provided to 3 productive sectors: traditional agriculture, small factories producing mass consumption goods, and construction of low income housing. The strategy would promote economic growth and expansion without further deterioration of income distribution, employment, and price stability. A simulation study demonstrated the advantages of such a strategy in relation to alternative strategies.

Mathematic simulation of mining company’s power demand forecast (by example of “Neryungri” coal strip mine)

NASA Astrophysics Data System (ADS)

Antonenkov, D. V.; Solovev, D. B.

2017-10-01

The article covers the aspects of forecasting and consideration of the wholesale market environment in generating the power demand forecast. Major mining companies that operate in conditions of the present day power market have to provide a reliable energy demand request for a certain time period ahead, thus ensuring sufficient reduction of financial losses associated with deviations of the actual power demand from the expected figures. Normally, under the power supply agreement, the consumer is bound to provide a per-month and per-hour request annually. It means that the consumer has to generate one-month-ahead short-term and medium-term hourly forecasts. The authors discovered that empiric distributions of “Yakutugol”, Holding Joint Stock Company, power demand belong to the sustainable rank parameter H-distribution type used for generating forecasts based on extrapolation of such distribution parameters. For this reason they justify the need to apply the mathematic rank analysis in short-term forecasting of the contracted power demand of “Neryungri” coil strip mine being a component of the technocenosis-type system of the mining company “Yakutugol”, Holding JSC.

Examining the Use of the Cloud for Seismic Data Centers

NASA Astrophysics Data System (ADS)

Yu, E.; Meisenhelter, S.; Clayton, R. W.

2011-12-01

The Southern California Earthquake Data Center (SCEDC) archives seismic and station sensor metadata related to earthquake activity in southern California. It currently archives nearly 8400 data streams continuously from over 420 stations in near real time at a rate of 584 GB/month to a repository approximately 18 TB in size. Triggered waveform data from an average 12,000 earthquakes/year is also archived. Data are archived on mirrored disk arrays that are maintained and backed-up locally. These data are served over the Internet to scientists and the general public in many countries. The data demand has a steady component, largely needed for ambient noise correlation studies, and an impulsive component that is driven by earthquake activity. Designing a reliable, cost effective, system architecture equipped to handle periods of relatively low steady demand punctuated by unpredictable sharp spikes in demand immediately following a felt earthquake remains a major challenge. To explore an alternative paradigm, we have put one-month of the data in the "cloud" and have developed a user interface with the Google Apps Engine. The purpose is to assess the modifications in data structures that are necessary to make efficient searches. To date we have determined that the database schema must be "denormalized" to take advantage of the dynamic computational capabilities, and that it is likely advantageous to preprocess the waveform data to remove overlaps, gaps, and other artifacts. The final purpose of this study is to compare the cost of the cloud compared to ground-based centers. The major motivations for this study are the security and dynamic load capabilities of the cloud. In the cloud, multiple copies of the data are held in distributed centers thus eliminating the single point of failure associated with one center. The cloud can dynamically increase the level of computational resources during an earthquake, and the major tasks of managing a disk farm are eliminated. The center can also managed from anywhere and is not bound to a particular location.

Evaluating Outdoor Water Use Demand under Changing Climatic and Demographic Conditions: An Agent-based Modeling Approach

NASA Astrophysics Data System (ADS)

Kanta, L.

2016-12-01

Outdoor water use for landscape and irrigation constitutes a significant end use in residential water demand. In periods of water shortages, utilities may reduce garden demands by implementing irrigation system audits, rebate programs, local ordinances, and voluntary or mandatory water use restrictions. Because utilities do not typically record outdoor and indoor water uses separately, the effects of policies for reducing garden demands cannot be readily calculated. The volume of water required to meet garden demands depends on the housing density or lawn size, type of vegetation, climatic conditions, efficiency of garden irrigation systems, and consumer water-use behaviors. Many existing outdoor demand estimation methods are deterministic and do not include consumer responses to conservation campaigns. In addition, mandatory restrictions may have a substantial impact on reducing outdoor demands, but the effectiveness of mandatory restrictions depends on the timing and the frequency of restrictions, in addition to the distribution of housing density and consumer types within a community. This research investigates a garden end-use model by coupling an agent-based modeling approach and a mechanistic-stochastic water demand model to create a methodology for estimating garden demand and evaluating demand reduction policies. The garden demand model is developed for two water utilities, using a diverse data sets, including residential customer billing records, records of outdoor conservation programs, frequency and type of mandatory water use restrictions, lot size distribution, population growth, and climatic data. A set of garden irrigation parameter values, which are based on the efficiency of irrigation systems and irrigation habits of consumers, are determined for a set of conservation ordinances and restrictions. The model parameters are then validated using customer water usage data from the participating water utilities. A sensitivity analysis is conducted for garden irrigation parameters to determine the most significant factors that should be considered by water utilities to reduce outdoor demand. Data from multiple sources and the agent-based modeling methodology are integrated using a holistic approach to assist utilities in efficiently and sustainably managing outdoor demand.

Evaluating Outdoor Water Use Demand under Changing Climatic and Demographic Conditions: An Agent-based Modeling Approach

NASA Astrophysics Data System (ADS)

Kanta, L.; Berglund, E. Z.; Soh, M. H.

2017-12-01

Outdoor water-use for landscape and irrigation constitutes a significant end-use in total residential water demand. In periods of water shortages, utilities may reduce garden demands by implementing irrigation system audits, rebate programs, local ordinances, and voluntary or mandatory water-use restrictions. Because utilities do not typically record outdoor and indoor water-uses separately, the effects of policies for reducing garden demands cannot be readily calculated. The volume of water required to meet garden demands depends on the housing density, lawn size, type of vegetation, climatic conditions, efficiency of garden irrigation systems, and consumer water-use behaviors. Many existing outdoor demand estimation methods are deterministic and do not include consumer responses to conservation campaigns. In addition, mandatory restrictions may have a substantial impact on reducing outdoor demands, but the effectiveness of mandatory restrictions depends on the timing and the frequency of restrictions, in addition to the distribution of housing density and consumer types within a community. This research investigates a garden end-use model by coupling an agent-based modeling approach and a mechanistic-stochastic water demand model to create a methodology for estimating garden demand and evaluating demand reduction policies. The garden demand model is developed for two water utilities, using a diverse data sets, including residential customer billing records, outdoor conservation programs, frequency and type of mandatory water-use restrictions, lot size distribution, population growth, and climatic data. A set of garden irrigation parameter values, which are based on the efficiency of irrigation systems and irrigation habits of consumers, are determined for a set of conservation ordinances and restrictions. The model parameters are then validated using customer water usage data from the participating water utilities. A sensitivity analysis is conducted for garden irrigation parameters to determine the most significant factors that should be considered by water utilities to reduce outdoor demand. Data from multiple sources and the agent-based modeling methodology are integrated using a holistic approach to assist utilities in efficiently and sustainably managing outdoor demand.

A genetic algorithm for dynamic inbound ordering and outbound dispatching problem with delivery time windows

NASA Astrophysics Data System (ADS)

Kim, Byung Soo; Lee, Woon-Seek; Koh, Shiegheun

2012-07-01

This article considers an inbound ordering and outbound dispatching problem for a single product in a third-party warehouse, where the demands are dynamic over a discrete and finite time horizon, and moreover, each demand has a time window in which it must be satisfied. Replenishing orders are shipped in containers and the freight cost is proportional to the number of containers used. The problem is classified into two cases, i.e. non-split demand case and split demand case, and a mathematical model for each case is presented. An in-depth analysis of the models shows that they are very complicated and difficult to find optimal solutions as the problem size becomes large. Therefore, genetic algorithm (GA) based heuristic approaches are designed to solve the problems in a reasonable time. To validate and evaluate the algorithms, finally, some computational experiments are conducted.

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

Buying and Pricing: Instructor Material. Curriculum: Distributive Education.

ERIC Educational Resources Information Center

Missouri Univ., Columbia. Instructional Materials Lab.

This secondary distributive education performance-based instructional unit on buying and pricing contains thirteen lesson plans, each based on a fifty-five minute period. Among the topics covered are the following: (1) the importance of analysing the customers' demands for merchandise before planning what and when to buy, (2) questions about…

Demand forecasting for automotive sector in Malaysia by system dynamics approach

NASA Astrophysics Data System (ADS)

Zulkepli, Jafri; Fong, Chan Hwa; Abidin, Norhaslinda Zainal

2015-12-01

In general, Proton as an automotive company needs to forecast future demand of the car to assist in decision making related to capacity expansion planning. One of the forecasting approaches that based on judgemental or subjective factors is normally used to forecast the demand. As a result, demand could be overstock that eventually will increase the operation cost; or the company will face understock, which resulted losing their customers. Due to automotive industry is very challenging process because of high level of complexity and uncertainty involved in the system, an accurate tool to forecast the future of automotive demand from the modelling perspective is required. Hence, the main objective of this paper is to forecast the demand of automotive Proton car industry in Malaysia using system dynamics approach. Two types of intervention namely optimistic and pessimistic experiments scenarios have been tested to determine the capacity expansion that can prevent the company from overstocking. Finding from this study highlighted that the management needs to expand their production for optimistic scenario, whilst pessimistic give results that would otherwise. Finally, this study could help Proton Edar Sdn. Bhd (PESB) to manage the long-term capacity planning in order to meet the future demand of the Proton cars.

Sustainable infrastructure system modeling under uncertainties and dynamics

NASA Astrophysics Data System (ADS)

Huang, Yongxi

Infrastructure systems support human activities in transportation, communication, water use, and energy supply. The dissertation research focuses on critical transportation infrastructure and renewable energy infrastructure systems. The goal of the research efforts is to improve the sustainability of the infrastructure systems, with an emphasis on economic viability, system reliability and robustness, and environmental impacts. The research efforts in critical transportation infrastructure concern the development of strategic robust resource allocation strategies in an uncertain decision-making environment, considering both uncertain service availability and accessibility. The study explores the performances of different modeling approaches (i.e., deterministic, stochastic programming, and robust optimization) to reflect various risk preferences. The models are evaluated in a case study of Singapore and results demonstrate that stochastic modeling methods in general offers more robust allocation strategies compared to deterministic approaches in achieving high coverage to critical infrastructures under risks. This general modeling framework can be applied to other emergency service applications, such as, locating medical emergency services. The development of renewable energy infrastructure system development aims to answer the following key research questions: (1) is the renewable energy an economically viable solution? (2) what are the energy distribution and infrastructure system requirements to support such energy supply systems in hedging against potential risks? (3) how does the energy system adapt the dynamics from evolving technology and societal needs in the transition into a renewable energy based society? The study of Renewable Energy System Planning with Risk Management incorporates risk management into its strategic planning of the supply chains. The physical design and operational management are integrated as a whole in seeking mitigations against the potential risks caused by feedstock seasonality and demand uncertainty. Facility spatiality, time variation of feedstock yields, and demand uncertainty are integrated into a two-stage stochastic programming (SP) framework. In the study of Transitional Energy System Modeling under Uncertainty, a multistage stochastic dynamic programming is established to optimize the process of building and operating fuel production facilities during the transition. Dynamics due to the evolving technologies and societal changes and uncertainty due to demand fluctuations are the major issues to be addressed.

A hybrid system dynamics and optimization approach for supporting sustainable water resources planning in Zhengzhou City, China

NASA Astrophysics Data System (ADS)

Li, Zhi; Li, Chunhui; Wang, Xuan; Peng, Cong; Cai, Yanpeng; Huang, Weichen

2018-01-01

Problems with water resources restrict the sustainable development of a city with water shortages. Based on system dynamics (SD) theory, a model of sustainable utilization of water resources using the STELLA software has been established. This model consists of four subsystems: population system, economic system, water supply system and water demand system. The boundaries of the four subsystems are vague, but they are closely related and interdependent. The model is applied to Zhengzhou City, China, which has a serious water shortage. The difference between the water supply and demand is very prominent in Zhengzhou City. The model was verified with data from 2009 to 2013. The results show that water demand of Zhengzhou City will reach 2.57 billion m3 in 2020. A water resources optimization model is developed based on interval-parameter two-stage stochastic programming. The objective of the model is to allocate water resources to each water sector and make the lowest cost under the minimum water demand. Using the simulation results, decision makers can easily weigh the costs of the system, the water allocation objectives, and the system risk. The hybrid system dynamics method and optimization model is a rational try to support water resources management in many cities, particularly for cities with potential water shortage and it is solidly supported with previous studies and collected data.

High-efficient and high-content cytotoxic recording via dynamic and continuous cell-based impedance biosensor technology.

PubMed

Hu, Ning; Fang, Jiaru; Zou, Ling; Wan, Hao; Pan, Yuxiang; Su, Kaiqi; Zhang, Xi; Wang, Ping

2016-10-01

Cell-based bioassays were effective method to assess the compound toxicity by cell viability, and the traditional label-based methods missed much information of cell growth due to endpoint detection, while the higher throughputs were demanded to obtain dynamic information. Cell-based biosensor methods can dynamically and continuously monitor with cell viability, however, the dynamic information was often ignored or seldom utilized in the toxin and drug assessment. Here, we reported a high-efficient and high-content cytotoxic recording method via dynamic and continuous cell-based impedance biosensor technology. The dynamic cell viability, inhibition ratio and growth rate were derived from the dynamic response curves from the cell-based impedance biosensor. The results showed that the biosensors has the dose-dependent manners to diarrhetic shellfish toxin, okadiac acid based on the analysis of the dynamic cell viability and cell growth status. Moreover, the throughputs of dynamic cytotoxicity were compared between cell-based biosensor methods and label-based endpoint methods. This cell-based impedance biosensor can provide a flexible, cost and label-efficient platform of cell viability assessment in the shellfish toxin screening fields.

Research and Design of the Three-tier Distributed Network Management System Based on COM / COM + and DNA

NASA Astrophysics Data System (ADS)

Liang, Likai; Bi, Yushen

Considered on the distributed network management system's demand of high distributives, extensibility and reusability, a framework model of Three-tier distributed network management system based on COM/COM+ and DNA is proposed, which adopts software component technology and N-tier application software framework design idea. We also give the concrete design plan of each layer of this model. Finally, we discuss the internal running process of each layer in the distributed network management system's framework model.

SeaWiFS Technical Report Series. Volume 7: Cloud screening for polar orbiting visible and infrared (IR) satellite sensors

NASA Technical Reports Server (NTRS)

Darzi, Michael; Hooker, Stanford B. (Editor); Firestone, Elaine R. (Editor)

1992-01-01

Methods for detecting and screening cloud contamination from satellite derived visible and infrared data are reviewed in this document. The methods are applicable to past, present, and future polar orbiting satellite radiometers. Such instruments include the Coastal Zone Color Scanner (CZCS), operational from 1978 through 1986; the Advanced Very High Resolution Radiometer (AVHRR); the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), scheduled for launch in August 1993; and the Moderate Resolution Imaging Spectrometer (IMODIS). Constant threshold methods are the least demanding computationally, and often provide adequate results. An improvement to these methods are the least demanding computationally, and often provide adequate results. An improvement to these methods is to determine the thresholds dynamically by adjusting them according to the areal and temporal distributions of the surrounding pixels. Spatial coherence methods set thresholds based on the expected spatial variability of the data. Other statistically derived methods and various combinations of basic methods are also reviewed. The complexity of the methods is ultimately limited by the computing resources. Finally, some criteria for evaluating cloud screening methods are discussed.

Data center thermal management

DOEpatents

Hamann, Hendrik F.; Li, Hongfei

2016-02-09

Historical high-spatial-resolution temperature data and dynamic temperature sensor measurement data may be used to predict temperature. A first formulation may be derived based on the historical high-spatial-resolution temperature data for determining a temperature at any point in 3-dimensional space. The dynamic temperature sensor measurement data may be calibrated based on the historical high-spatial-resolution temperature data at a corresponding historical time. Sensor temperature data at a plurality of sensor locations may be predicted for a future time based on the calibrated dynamic temperature sensor measurement data. A three-dimensional temperature spatial distribution associated with the future time may be generated based on the forecasted sensor temperature data and the first formulation. The three-dimensional temperature spatial distribution associated with the future time may be projected to a two-dimensional temperature distribution, and temperature in the future time for a selected space location may be forecasted dynamically based on said two-dimensional temperature distribution.

Optimized maritime emergency resource allocation under dynamic demand.

PubMed

Zhang, Wenfen; Yan, Xinping; Yang, Jiaqi

2017-01-01

Emergency resource is important for people evacuation and property rescue when accident occurs. The relief efforts could be promoted by a reasonable emergency resource allocation schedule in advance. As the marine environment is complicated and changeful, the place, type, severity of maritime accident is uncertain and stochastic, bringing about dynamic demand of emergency resource. Considering dynamic demand, how to make a reasonable emergency resource allocation schedule is challenging. The key problem is to determine the optimal stock of emergency resource for supplier centers to improve relief efforts. This paper studies the dynamic demand, and which is defined as a set. Then a maritime emergency resource allocation model with uncertain data is presented. Afterwards, a robust approach is developed and used to make sure that the resource allocation schedule performs well with dynamic demand. Finally, a case study shows that the proposed methodology is feasible in maritime emergency resource allocation. The findings could help emergency manager to schedule the emergency resource allocation more flexibly in terms of dynamic demand.

Optimized maritime emergency resource allocation under dynamic demand

PubMed Central

Yan, Xinping; Yang, Jiaqi

2017-01-01

Emergency resource is important for people evacuation and property rescue when accident occurs. The relief efforts could be promoted by a reasonable emergency resource allocation schedule in advance. As the marine environment is complicated and changeful, the place, type, severity of maritime accident is uncertain and stochastic, bringing about dynamic demand of emergency resource. Considering dynamic demand, how to make a reasonable emergency resource allocation schedule is challenging. The key problem is to determine the optimal stock of emergency resource for supplier centers to improve relief efforts. This paper studies the dynamic demand, and which is defined as a set. Then a maritime emergency resource allocation model with uncertain data is presented. Afterwards, a robust approach is developed and used to make sure that the resource allocation schedule performs well with dynamic demand. Finally, a case study shows that the proposed methodology is feasible in maritime emergency resource allocation. The findings could help emergency manager to schedule the emergency resource allocation more flexibly in terms of dynamic demand. PMID:29240792

Voltage-Load Sensitivity Matrix Based Demand Response for Voltage Control in High Solar Penetration Distribution Feeders

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

Zhu, Xiangqi; Wang, Jiyu; Mulcahy, David

This paper presents a voltage-load sensitivity matrix (VLSM) based voltage control method to deploy demand response resources for controlling voltage in high solar penetration distribution feeders. The IEEE 123-bus system in OpenDSS is used for testing the performance of the preliminary VLSM-based voltage control approach. A load disaggregation process is applied to disaggregate the total load profile at the feeder head to each load nodes along the feeder so that loads are modeled at residential house level. Measured solar generation profiles are used in the simulation to model the impact of solar power on distribution feeder voltage profiles. Different casemore » studies involving various PV penetration levels and installation locations have been performed. Simulation results show that the VLSM algorithm performance meets the voltage control requirements and is an effective voltage control strategy.« less

A tool for modeling concurrent real-time computation

NASA Technical Reports Server (NTRS)

Sharma, D. D.; Huang, Shie-Rei; Bhatt, Rahul; Sridharan, N. S.

1990-01-01

Real-time computation is a significant area of research in general, and in AI in particular. The complexity of practical real-time problems demands use of knowledge-based problem solving techniques while satisfying real-time performance constraints. Since the demands of a complex real-time problem cannot be predicted (owing to the dynamic nature of the environment) powerful dynamic resource control techniques are needed to monitor and control the performance. A real-time computation model for a real-time tool, an implementation of the QP-Net simulator on a Symbolics machine, and an implementation on a Butterfly multiprocessor machine are briefly described.

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

Nutrient limitation in tropical savannas across multiple scales and mechanisms.

PubMed

Pellegrini, Adam F A

2016-02-01

Nutrients have been hypothesized to influence the distribution of the savanna biome through two possible mechanisms. Low nutrient availability may restrict growth rates of trees, thereby allowing for intermittent fires to maintain low tree cover; alternatively, nutrient deficiency may even place an absolute constraint on the ability of forests to form, independent of fire. However, we have little understanding of the scales at which nutrient limitation operates, what nutrients are limiting, and the mechanisms that influence how nutrient limitation regulates savanna-forest transitions. Here, I review literature, synthesize existing data, and present a simple calculation of nutrient demand to evaluate how nutrient limitation may regulate the distribution of the savanna biome. The literature primarily supports the hypothesis that nutrients may interact dynamically with fire to restrict the transition of savanna into forest. A compilation of indirect metrics of nutrient limitation suggest that nitrogen and phosphorus are both in short supply and may limit plants. Nutrient demand calculations provided a number of insights. First, trees required high rates of nitrogen and phosphorus supply relative to empirically determined inputs. Second, nutrient demand increased as landscapes approached the transition point between savanna and forest. Third, the potential for fire-driven nutrient losses remained high throughout transitions, which may exaggerate limitation and could be a key feedback stabilizing the savanna biome. Fourth, nutrient limitation varied between functional groups, with fast-growing forest species having substantially greater nutrient demand and a higher susceptibility to fire-driven nutrient losses. Finally, African savanna trees required substantially larger amounts of nutrients supplied at greater rates, although this varied across plant functional groups. In summary, the ability of nutrients to control transitions emerges at individual and landscape scales, and is regulated through different mechanisms based on spatial (differences in underlying geology), temporal (stage in biome transition) and biological (species traits and community composition) variability.

Income distribution trends and future food demand.

PubMed

Cirera, Xavier; Masset, Edoardo

2010-09-27

This paper surveys the theoretical literature on the relationship between income distribution and food demand, and identifies main gaps of current food modelling techniques that affect the accuracy of food demand projections. At the heart of the relationship between income distribution and food demand is Engel's law. Engel's law establishes that as income increases, households' demand for food increases less than proportionally. A consequence of this law is that the particular shape of the distribution of income across individuals and countries affects the rate of growth of food demand. Our review of the literature suggests that existing models of food demand fail to incorporate the required Engel flexibility when (i) aggregating different food budget shares among households; and (ii) changing budget shares as income grows. We perform simple simulations to predict growth in food demand under alternative income distribution scenarios taking into account nonlinearity of food demand. Results suggest that (i) distributional effects are to be expected from changes in between-countries inequality, rather than within-country inequality; and (ii) simulations of an optimistic and a pessimistic scenario of income inequality suggest that world food demand in 2050 would be 2.7 per cent higher and 5.4 per cent lower than distributional-neutral growth, respectively.

The role of storage dynamics in annual wheat prices

NASA Astrophysics Data System (ADS)

Schewe, Jacob; Otto, Christian; Frieler, Katja

2017-05-01

Identifying the drivers of global crop price fluctuations is essential for estimating the risks of unexpected weather-induced production shortfalls and for designing optimal response measures. Here we show that with a consistent representation of storage dynamics, a simple supply-demand model can explain most of the observed variations in wheat prices over the last 40 yr solely based on time series of annual production and long term demand trends. Even the most recent price peaks in 2007/08 and 2010/11 can be explained by additionally accounting for documented changes in countries’ trade policies and storage strategies, without the need for external drivers such as oil prices or speculation across different commodity or stock markets. This underlines the critical sensitivity of global prices to fluctuations in production. The consistent inclusion of storage into a dynamic supply-demand model closes an important gap when it comes to exploring potential responses to future crop yield variability under climate and land-use change.

Wireless Technology Recognition Based on RSSI Distribution at Sub-Nyquist Sampling Rate for Constrained Devices.

PubMed

Liu, Wei; Kulin, Merima; Kazaz, Tarik; Shahid, Adnan; Moerman, Ingrid; De Poorter, Eli

2017-09-12

Driven by the fast growth of wireless communication, the trend of sharing spectrum among heterogeneous technologies becomes increasingly dominant. Identifying concurrent technologies is an important step towards efficient spectrum sharing. However, due to the complexity of recognition algorithms and the strict condition of sampling speed, communication systems capable of recognizing signals other than their own type are extremely rare. This work proves that multi-model distribution of the received signal strength indicator (RSSI) is related to the signals' modulation schemes and medium access mechanisms, and RSSI from different technologies may exhibit highly distinctive features. A distinction is made between technologies with a streaming or a non-streaming property, and appropriate feature spaces can be established either by deriving parameters such as packet duration from RSSI or directly using RSSI's probability distribution. An experimental study shows that even RSSI acquired at a sub-Nyquist sampling rate is able to provide sufficient features to differentiate technologies such as Wi-Fi, Long Term Evolution (LTE), Digital Video Broadcasting-Terrestrial (DVB-T) and Bluetooth. The usage of the RSSI distribution-based feature space is illustrated via a sample algorithm. Experimental evaluation indicates that more than 92% accuracy is achieved with the appropriate configuration. As the analysis of RSSI distribution is straightforward and less demanding in terms of system requirements, we believe it is highly valuable for recognition of wideband technologies on constrained devices in the context of dynamic spectrum access.

Wireless Technology Recognition Based on RSSI Distribution at Sub-Nyquist Sampling Rate for Constrained Devices

PubMed Central

Liu, Wei; Kulin, Merima; Kazaz, Tarik; De Poorter, Eli

2017-01-01

Driven by the fast growth of wireless communication, the trend of sharing spectrum among heterogeneous technologies becomes increasingly dominant. Identifying concurrent technologies is an important step towards efficient spectrum sharing. However, due to the complexity of recognition algorithms and the strict condition of sampling speed, communication systems capable of recognizing signals other than their own type are extremely rare. This work proves that multi-model distribution of the received signal strength indicator (RSSI) is related to the signals’ modulation schemes and medium access mechanisms, and RSSI from different technologies may exhibit highly distinctive features. A distinction is made between technologies with a streaming or a non-streaming property, and appropriate feature spaces can be established either by deriving parameters such as packet duration from RSSI or directly using RSSI’s probability distribution. An experimental study shows that even RSSI acquired at a sub-Nyquist sampling rate is able to provide sufficient features to differentiate technologies such as Wi-Fi, Long Term Evolution (LTE), Digital Video Broadcasting-Terrestrial (DVB-T) and Bluetooth. The usage of the RSSI distribution-based feature space is illustrated via a sample algorithm. Experimental evaluation indicates that more than 92% accuracy is achieved with the appropriate configuration. As the analysis of RSSI distribution is straightforward and less demanding in terms of system requirements, we believe it is highly valuable for recognition of wideband technologies on constrained devices in the context of dynamic spectrum access. PMID:28895879

Development of the Optimum Operation Scheduling Model of Domestic Electric Appliances for the Supply-Demand Adjustment in a Power System

NASA Astrophysics Data System (ADS)

Ikegami, Takashi; Iwafune, Yumiko; Ogimoto, Kazuhiko

The high penetration of variable renewable generation such as Photovoltaic (PV) systems will cause the issue of supply-demand imbalance in a whole power system. The activation of the residential power usage, storage and generation by sophisticated scheduling and control using the Home Energy Management System (HEMS) will be needed to balance power supply and demand in the near future. In order to evaluate the applicability of the HEMS as a distributed controller for local and system-wide supply-demand balances, we developed an optimum operation scheduling model of domestic electric appliances using the mixed integer linear programming. Applying this model to several houses with dynamic electricity prices reflecting the power balance of the total power system, it was found that the adequate changes in electricity prices bring about the shift of residential power usages to control the amount of the reverse power flow due to excess PV generation.

Towards Internet QoS provisioning based on generic distributed QoS adaptive routing engine.

PubMed

Haikal, Amira Y; Badawy, M; Ali, Hesham A

2014-01-01

Increasing efficiency and quality demands of modern Internet technologies drive today's network engineers to seek to provide quality of service (QoS). Internet QoS provisioning gives rise to several challenging issues. This paper introduces a generic distributed QoS adaptive routing engine (DQARE) architecture based on OSPFxQoS. The innovation of the proposed work in this paper is its undependability on the used QoS architectures and, moreover, splitting of the control strategy from data forwarding mechanisms, so we guarantee a set of absolute stable mechanisms on top of which Internet QoS can be built. DQARE architecture is furnished with three relevant traffic control schemes, namely, service differentiation, QoS routing, and traffic engineering. The main objective of this paper is to (i) provide a general configuration guideline for service differentiation, (ii) formalize the theoretical properties of different QoS routing algorithms and then introduce a QoS routing algorithm (QOPRA) based on dynamic programming technique, and (iii) propose QoS multipath forwarding (QMPF) model for paths diversity exploitation. NS2-based simulations proved the DQARE superiority in terms of delay, packet delivery ratio, throughput, and control overhead. Moreover, extensive simulations are used to compare the proposed QOPRA algorithm and QMPF model with their counterparts in the literature.

Towards Internet QoS Provisioning Based on Generic Distributed QoS Adaptive Routing Engine

PubMed Central

Haikal, Amira Y.; Badawy, M.; Ali, Hesham A.

2014-01-01

Increasing efficiency and quality demands of modern Internet technologies drive today's network engineers to seek to provide quality of service (QoS). Internet QoS provisioning gives rise to several challenging issues. This paper introduces a generic distributed QoS adaptive routing engine (DQARE) architecture based on OSPFxQoS. The innovation of the proposed work in this paper is its undependability on the used QoS architectures and, moreover, splitting of the control strategy from data forwarding mechanisms, so we guarantee a set of absolute stable mechanisms on top of which Internet QoS can be built. DQARE architecture is furnished with three relevant traffic control schemes, namely, service differentiation, QoS routing, and traffic engineering. The main objective of this paper is to (i) provide a general configuration guideline for service differentiation, (ii) formalize the theoretical properties of different QoS routing algorithms and then introduce a QoS routing algorithm (QOPRA) based on dynamic programming technique, and (iii) propose QoS multipath forwarding (QMPF) model for paths diversity exploitation. NS2-based simulations proved the DQARE superiority in terms of delay, packet delivery ratio, throughput, and control overhead. Moreover, extensive simulations are used to compare the proposed QOPRA algorithm and QMPF model with their counterparts in the literature. PMID:25309955

Water balance in irrigation districts. Uncertainty in on-demand pressurized networks

NASA Astrophysics Data System (ADS)

Sánchez-Calvo, Raúl; Rodríguez-Sinobas, Leonor; Juana, Luis; Laguna, Francisco Vicente

2015-04-01

In on-demand pressurized irrigation distribution networks, applied water volume is usually controlled opening a valve during a calculated time interval, and assuming constant flow rate. In general, pressure regulating devices for controlling the discharged flow rate by irrigation units are needed due to the variability of pressure conditions. A pressure regulating valve PRV is the commonly used pressure regulating device in a hydrant, which, also, executes the open and close function. A hydrant feeds several irrigation units, requiring a wide range in flow rate. In addition, some flow meters are also available, one as a component of the hydrant and the rest are placed downstream. Every land owner has one flow meter for each group of field plots downstream the hydrant. Ideal PRV performance would maintain a constant downstream pressure. However, the true performance depends on both upstream pressure and the discharged flow rate. Theoretical flow rates values have been introduced into a PRV behavioral model, validated in laboratory, coupled with an on-demand irrigation district waterworks, composed by a distribution network and a multi-pump station. Variations on flow rate are simulated by taking into account the consequences of variations on climate conditions and also decisions in irrigation operation, such us duration and frequency application. The model comprises continuity, dynamic and energy equations of the components of both the PRV and the water distribution network. In this work the estimation of water balance terms during the irrigation events in an irrigation campaign has been simulated. The effect of demand concentration peaks has been estimated.

Defense Science Board Task Force Report: The Role of Autonomy in DoD Systems

DTIC Science & Technology

2012-07-01

ASD(R&E) and the Military Services should schedule periodic, on-site collaborations that bring together academia, government and not-for-profit labs...expressing UxV activities, increased problem solving, planning and scheduling capabilities to enable dynamic tasking of distributed UxVs and tools for...industrial, governmental and military. Manufacturing has long exploited planning for logistics and matching product demand to production schedules

Predictive Scheduling for Electric Vehicles Considering Uncertainty of Load and User Behaviors

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

Wang, Bin; Huang, Rui; Wang, Yubo

2016-05-02

Un-coordinated Electric Vehicle (EV) charging can create unexpected load in local distribution grid, which may degrade the power quality and system reliability. The uncertainty of EV load, user behaviors and other baseload in distribution grid, is one of challenges that impedes optimal control for EV charging problem. Previous researches did not fully solve this problem due to lack of real-world EV charging data and proper stochastic model to describe these behaviors. In this paper, we propose a new predictive EV scheduling algorithm (PESA) inspired by Model Predictive Control (MPC), which includes a dynamic load estimation module and a predictive optimizationmore » module. The user-related EV load and base load are dynamically estimated based on the historical data. At each time interval, the predictive optimization program will be computed for optimal schedules given the estimated parameters. Only the first element from the algorithm outputs will be implemented according to MPC paradigm. Current-multiplexing function in each Electric Vehicle Supply Equipment (EVSE) is considered and accordingly a virtual load is modeled to handle the uncertainties of future EV energy demands. This system is validated by the real-world EV charging data collected on UCLA campus and the experimental results indicate that our proposed model not only reduces load variation up to 40% but also maintains a high level of robustness. Finally, IEC 61850 standard is utilized to standardize the data models involved, which brings significance to more reliable and large-scale implementation.« less

Demand forecasting for automotive sector in Malaysia by system dynamics approach

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

Zulkepli, Jafri, E-mail: zhjafri@uum.edu.my; Abidin, Norhaslinda Zainal, E-mail: nhaslinda@uum.edu.my; Fong, Chan Hwa, E-mail: hfchan7623@yahoo.com

In general, Proton as an automotive company needs to forecast future demand of the car to assist in decision making related to capacity expansion planning. One of the forecasting approaches that based on judgemental or subjective factors is normally used to forecast the demand. As a result, demand could be overstock that eventually will increase the operation cost; or the company will face understock, which resulted losing their customers. Due to automotive industry is very challenging process because of high level of complexity and uncertainty involved in the system, an accurate tool to forecast the future of automotive demand frommore » the modelling perspective is required. Hence, the main objective of this paper is to forecast the demand of automotive Proton car industry in Malaysia using system dynamics approach. Two types of intervention namely optimistic and pessimistic experiments scenarios have been tested to determine the capacity expansion that can prevent the company from overstocking. Finding from this study highlighted that the management needs to expand their production for optimistic scenario, whilst pessimistic give results that would otherwise. Finally, this study could help Proton Edar Sdn. Bhd (PESB) to manage the long-term capacity planning in order to meet the future demand of the Proton cars.« less

Effects of planning strategies on writing dynamics and final texts.

PubMed

Limpo, Teresa; Alves, Rui A

2018-06-12

Expert writing involves the interaction among three cognitively demanding processes: planning, translating, and revising. To manage the cognitive load brought on by these processes, writers frequently use strategies. Here, we examined the effects of planning strategies on writing dynamics and final texts. Before writing an argumentative text with the triple-task technique, 63 undergraduates were asked either to elaborate an outline with the argumentative structure embedded (structure-based planning condition), to provide a written list of ideas for the text (list-based planning condition), or to do a non-writing-related filler task (no planning condition). Planning showed no effects on the length of the pre-writing pause and cognitive effort, but influenced writing processes occurrences. Compared to participants in the no-planning condition, those in the planning conditions showed a later activation of revising. Moreover, participants in the structure-based condition were mainly focused on translating in the beginning and middle of composition, whereas their peers tended to distribute their attention among all processes. Planning ahead of writing also resulted in texts with longer words, produced at a higher rate. Only the structure-based planning strategy led to an increase in the number of argumentation elements as well as in essays' persuasiveness and overall quality. There was, however, no indication that these improvements in final texts were associated with changes in the dynamics of writing. Overall, the use of structure-based plans seems to be an effective and efficient way of improving undergraduates' argumentative writing. Copyright © 2018 Elsevier B.V. All rights reserved.

Team Modelling: Survey of Experimental Platforms (Modelisation d’equipes : Examen de plate-formes experimentales)

DTIC Science & Technology

2006-09-01

Control Force Agility Shared Situational Awareness Attentional Demand Interoperability Network Based Operations Effect Based Operations Speed of...Command Self Synchronization Reach Back Reach Forward Information Superiority Increased Mission Effectiveness Humansystems® Team Modelling...communication effectiveness and Distributed Mission Training (DMT) effectiveness . The NASA Ames Centre - Distributed Research Facilities platform could

Maintained benefits and improved survival of dynamic cardiomyoplasty by activity-rest stimulation: 5-year results of the Italian trial on "demand" dynamic cardiomyoplasty.

PubMed

Rigatelli, Gianluca; Barbiero, Mario; Rigatelli, Giorgio; Riccardi, Roberto; Cobelli, Franco; Cotogni, Angelo; Bandello, Attilio; Carraro, Ugo

2003-01-01

Latissimus dorsi (LD) muscular degeneration caused by continuous electrical stimulation has been the main cause of the poor results of dynamic cardiomyoplasty (DCMP) and its exclusion from the recent international guidelines on heart failure. To avoid full transformation of the LD and to improve results, a new stimulation protocol was developed; fewer impulses per day are delivered, providing the LD wrap with daily periods of rest ("demand" stimulation), based on a heart rate cut-off. The aim of this work is to report the results at 5 years of follow-up of the Italian Trial of Demand Dynamic Cardiomyoplasty and to discuss their impact on the destiny of this type of cardiac assistance. Twelve patients with dilated myocardiopathy (M/F=11/1, mean age 58.2+/-5.8 years, sinus rhythm/atrial fibrillation=11/1) were submitted during the period 1993-1996 to DCMP and at different intervals to demand protocol. Clinical, echocardiographic, mechanographic and cardiac invasive assessments were scheduled before initiating the demand protocol and during the follow-up at 0, 6 and every 12 months. The mean duration of follow-up was 40.2+/-13.8 months (range 18-64). There were no perioperative deaths. The demand stimulation protocol showed a decrease in 5 years in New York Health Association (NYHA) class (3.17+/-0.38-1.67+/-0.77, P=0.0001), an improvement of left ventricular ejection fraction (22.6+/-4.38-32.0+/-7.0, P<0.001), a 5-year actuarial survival of 83.3% (one patient was switched to heart transplantation programme due to clinical worsening and another one died of massive pulmonary embolism). Demand DCMP maintains over time LD muscular properties, enhances clinical benefits and improves survival of DCMP, thus reopening the debate whether this type of treatment should be considered in patients with end-stage heart failure.

Effect of Cognitive Demand on Functional Visual Field Performance in Senior Drivers with Glaucoma.

PubMed

Gangeddula, Viswa; Ranchet, Maud; Akinwuntan, Abiodun E; Bollinger, Kathryn; Devos, Hannes

2017-01-01

Purpose: To investigate the effect of cognitive demand on functional visual field performance in drivers with glaucoma. Method: This study included 20 drivers with open-angle glaucoma and 13 age- and sex-matched controls. Visual field performance was evaluated under different degrees of cognitive demand: a static visual field condition (C1), dynamic visual field condition (C2), and dynamic visual field condition with active driving (C3) using an interactive, desktop driving simulator. The number of correct responses (accuracy) and response times on the visual field task were compared between groups and between conditions using Kruskal-Wallis tests. General linear models were employed to compare cognitive workload, recorded in real-time through pupillometry, between groups and conditions. Results: Adding cognitive demand (C2 and C3) to the static visual field test (C1) adversely affected accuracy and response times, in both groups ( p < 0.05). However, drivers with glaucoma performed worse than did control drivers when the static condition changed to a dynamic condition [C2 vs. C1 accuracy; glaucoma: median difference (Q1-Q3) 3 (2-6.50) vs. 2 (0.50-2.50); p = 0.05] and to a dynamic condition with active driving [C3 vs. C1 accuracy; glaucoma: 2 (2-6) vs. 1 (0.50-2); p = 0.02]. Overall, drivers with glaucoma exhibited greater cognitive workload than controls ( p = 0.02). Conclusion: Cognitive demand disproportionately affects functional visual field performance in drivers with glaucoma. Our results may inform the development of a performance-based visual field test for drivers with glaucoma.

From Walras’ auctioneer to continuous time double auctions: a general dynamic theory of supply and demand

NASA Astrophysics Data System (ADS)

Donier, J.; Bouchaud, J.-P.

2016-12-01

In standard Walrasian auctions, the price of a good is defined as the point where the supply and demand curves intersect. Since both curves are generically regular, the response to small perturbations is linearly small. However, a crucial ingredient is absent of the theory, namely transactions themselves. What happens after they occur? To answer the question, we develop a dynamic theory for supply and demand based on agents with heterogeneous beliefs. When the inter-auction time is infinitely long, the Walrasian mechanism is recovered. When transactions are allowed to happen in continuous time, a peculiar property emerges: close to the price, supply and demand vanish quadratically, which we empirically confirm on the Bitcoin. This explains why price impact in financial markets is universally observed to behave as the square root of the excess volume. The consequences are important, as they imply that the very fact of clearing the market makes prices hypersensitive to small fluctuations.

2015 California Demand Response Potential Study - Charting California’s Demand Response Future. Interim Report on Phase 1 Results

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

Alstone, Peter; Potter, Jennifer; Piette, Mary Ann

Demand response (DR) is an important resource for keeping the electricity grid stable and efficient; deferring upgrades to generation, transmission, and distribution systems; and providing other customer economic benefits. This study estimates the potential size and cost of the available DR resource for California’s three investor-owned utilities (IOUs), as the California Public Utilities Commission (CPUC) evaluates how to enhance the role of DR in meeting California’s resource planning needs and operational requirements. As the state forges a clean energy future, the contributions of wind and solar electricity from centralized and distributed generation will fundamentally change the power grid’s operational dynamics.more » This transition requires careful planning to ensure sufficient capacity is available with the right characteristics – flexibility and fast response – to meet reliability needs. Illustrated is a snapshot of how net load (the difference between demand and intermittent renewables) is expected to shift. Increasing contributions from renewable generation introduces steeper ramps and a shift, into the evening, of the hours that drive capacity needs. These hours of peak capacity need are indicated by the black dots on the plots. Ultimately this study quantifies the ability and the cost of using DR resources to help meet the capacity need at these forecasted critical hours in the state.« less

Smart Building: Decision Making Architecture for Thermal Energy Management

PubMed Central

Hernández Uribe, Oscar; San Martin, Juan Pablo; Garcia-Alegre, María C.; Santos, Matilde; Guinea, Domingo

2015-01-01

Smart applications of the Internet of Things are improving the performance of buildings, reducing energy demand. Local and smart networks, soft computing methodologies, machine intelligence algorithms and pervasive sensors are some of the basics of energy optimization strategies developed for the benefit of environmental sustainability and user comfort. This work presents a distributed sensor-processor-communication decision-making architecture to improve the acquisition, storage and transfer of thermal energy in buildings. The developed system is implemented in a near Zero-Energy Building (nZEB) prototype equipped with a built-in thermal solar collector, where optical properties are analysed; a low enthalpy geothermal accumulation system, segmented in different temperature zones; and an envelope that includes a dynamic thermal barrier. An intelligent control of this dynamic thermal barrier is applied to reduce the thermal energy demand (heating and cooling) caused by daily and seasonal weather variations. Simulations and experimental results are presented to highlight the nZEB thermal energy reduction. PMID:26528978

Liquid li structure and dynamics: A comparison between OFDFT and second nearest-neighbor embedded-atom method

DOE PAGES

Chen, Mohan; Vella, Joseph R.; Panagiotopoulos, Athanassios Z.; ...

2015-04-08

The structure and dynamics of liquid lithium are studied using two simulation methods: orbital-free (OF) first-principles molecular dynamics (MD), which employs OF density functional theory (DFT), and classical MD utilizing a second nearest-neighbor embedded-atom method potential. The properties we studied include the dynamic structure factor, the self-diffusion coefficient, the dispersion relation, the viscosity, and the bond angle distribution function. Our simulation results were compared to available experimental data when possible. Each method has distinct advantages and disadvantages. For example, OFDFT gives better agreement with experimental dynamic structure factors, yet is more computationally demanding than classical simulations. Classical simulations can accessmore » a broader temperature range and longer time scales. The combination of first-principles and classical simulations is a powerful tool for studying properties of liquid lithium.« less

Transition from Exponential to Power Law Income Distributions in a Chaotic Market

NASA Astrophysics Data System (ADS)

Pellicer-Lostao, Carmen; Lopez-Ruiz, Ricardo

Economy is demanding new models, able to understand and predict the evolution of markets. To this respect, Econophysics offers models of markets as complex systems, that try to comprehend macro-, system-wide states of the economy from the interaction of many agents at micro-level. One of these models is the gas-like model for trading markets. This tries to predict money distributions in closed economies and quite simply, obtains the ones observed in real economies. However, it reveals technical hitches to explain the power law distribution, observed in individuals with high incomes. In this work, nonlinear dynamics is introduced in the gas-like model in an effort to overcomes these flaws. A particular chaotic dynamics is used to break the pairing symmetry of agents (i, j) ⇔ (j, i). The results demonstrate that a "chaotic gas-like model" can reproduce the Exponential and Power law distributions observed in real economies. Moreover, it controls the transition between them. This may give some insight of the micro-level causes that originate unfair distributions of money in a global society. Ultimately, the chaotic model makes obvious the inherent instability of asymmetric scenarios, where sinks of wealth appear and doom the market to extreme inequality.

Multi-day activity scheduling reactions to planned activities and future events in a dynamic model of activity-travel behavior

NASA Astrophysics Data System (ADS)

Nijland, Linda; Arentze, Theo; Timmermans, Harry

2014-01-01

Modeling multi-day planning has received scarce attention in activity-based transport demand modeling so far. However, new dynamic activity-based approaches are being developed at the current moment. The frequency and inflexibility of planned activities and events in activity schedules of individuals indicate the importance of incorporating those pre-planned activities in the new generation of dynamic travel demand models. Elaborating and combining previous work on event-driven activity generation, the aim of this paper is to develop and illustrate an extension of a need-based model of activity generation that takes into account possible influences of pre-planned activities and events. This paper describes the theory and shows the results of simulations of the extension. The simulation was conducted for six different activities, and the parameter values used were consistent with an earlier estimation study. The results show that the model works well and that the influences of the parameters are consistent, logical, and have clear interpretations. These findings offer further evidence of face and construct validity to the suggested modeling approach.

The eGo grid model: An open-source and open-data based synthetic medium-voltage grid model for distribution power supply systems

NASA Astrophysics Data System (ADS)

Amme, J.; Pleßmann, G.; Bühler, J.; Hülk, L.; Kötter, E.; Schwaegerl, P.

2018-02-01

The increasing integration of renewable energy into the electricity supply system creates new challenges for distribution grids. The planning and operation of distribution systems requires appropriate grid models that consider the heterogeneity of existing grids. In this paper, we describe a novel method to generate synthetic medium-voltage (MV) grids, which we applied in our DIstribution Network GeneratOr (DINGO). DINGO is open-source software and uses freely available data. Medium-voltage grid topologies are synthesized based on location and electricity demand in defined demand areas. For this purpose, we use GIS data containing demand areas with high-resolution spatial data on physical properties, land use, energy, and demography. The grid topology is treated as a capacitated vehicle routing problem (CVRP) combined with a local search metaheuristics. We also consider the current planning principles for MV distribution networks, paying special attention to line congestion and voltage limit violations. In the modelling process, we included power flow calculations for validation. The resulting grid model datasets contain 3608 synthetic MV grids in high resolution, covering all of Germany and taking local characteristics into account. We compared the modelled networks with real network data. In terms of number of transformers and total cable length, we conclude that the method presented in this paper generates realistic grids that could be used to implement a cost-optimised electrical energy system.

Analysing the Effect of Demand Uncertainty in Dynamic Pricing with EAs

NASA Astrophysics Data System (ADS)

Shakya, Siddhartha; Oliveira, Fernando; Owusu, Gilbert

Dynamic pricing is a pricing strategy where a firm adjust the price for their products and services as a function of its perceived demand at different times. In this paper, we show how Evolutionary algorithms (EA) can be used to analyse the effect of demand uncertainty in dynamic pricing. The experiments are conducted in a range of dynamic pricing problems considering a number of different stochastic scenarios with a number of different EAs. The results are analysed, which suggest that higher demand fluctuation may not have adverse effect to the profit in comparison to the lower demand fluctuation, and that the reliability of EA for finding accurate policy could be higher when there is higher fluctuation then when there is lower fluctuation.

Dynamic Emulation Modelling (DEMo) of large physically-based environmental models

NASA Astrophysics Data System (ADS)

Galelli, S.; Castelletti, A.

2012-12-01

In environmental modelling large, spatially-distributed, physically-based models are widely adopted to describe the dynamics of physical, social and economic processes. Such an accurate process characterization comes, however, to a price: the computational requirements of these models are considerably high and prevent their use in any problem requiring hundreds or thousands of model runs to be satisfactory solved. Typical examples include optimal planning and management, data assimilation, inverse modelling and sensitivity analysis. An effective approach to overcome this limitation is to perform a top-down reduction of the physically-based model by identifying a simplified, computationally efficient emulator, constructed from and then used in place of the original model in highly resource-demanding tasks. The underlying idea is that not all the process details in the original model are equally important and relevant to the dynamics of the outputs of interest for the type of problem considered. Emulation modelling has been successfully applied in many environmental applications, however most of the literature considers non-dynamic emulators (e.g. metamodels, response surfaces and surrogate models), where the original dynamical model is reduced to a static map between input and the output of interest. In this study we focus on Dynamic Emulation Modelling (DEMo), a methodological approach that preserves the dynamic nature of the original physically-based model, with consequent advantages in a wide variety of problem areas. In particular, we propose a new data-driven DEMo approach that combines the many advantages of data-driven modelling in representing complex, non-linear relationships, but preserves the state-space representation typical of process-based models, which is both particularly effective in some applications (e.g. optimal management and data assimilation) and facilitates the ex-post physical interpretation of the emulator structure, thus enhancing the credibility of the model to stakeholders and decision-makers. Numerical results from the application of the approach to the reduction of 3D coupled hydrodynamic-ecological models in several real world case studies, including Marina Reservoir (Singapore) and Googong Reservoir (Australia), are illustrated.

Dynamic Singularity Spectrum Distribution of Sea Clutter

NASA Astrophysics Data System (ADS)

Xiong, Gang; Yu, Wenxian; Zhang, Shuning

2015-12-01

The fractal and multifractal theory have provided new approaches for radar signal processing and target-detecting under the background of ocean. However, the related research mainly focuses on fractal dimension or multifractal spectrum (MFS) of sea clutter. In this paper, a new dynamic singularity analysis method of sea clutter using MFS distribution is developed, based on moving detrending analysis (DMA-MFSD). Theoretically, we introduce the time information by using cyclic auto-correlation of sea clutter. For transient correlation series, the instantaneous singularity spectrum based on multifractal detrending moving analysis (MF-DMA) algorithm is calculated, and the dynamic singularity spectrum distribution of sea clutter is acquired. In addition, we analyze the time-varying singularity exponent ranges and maximum position function in DMA-MFSD of sea clutter. For the real sea clutter data, we analyze the dynamic singularity spectrum distribution of real sea clutter in level III sea state, and conclude that the radar sea clutter has the non-stationary and time-varying scale characteristic and represents the time-varying singularity spectrum distribution based on the proposed DMA-MFSD method. The DMA-MFSD will also provide reference for nonlinear dynamics and multifractal signal processing.

A population-based longitudinal study on the implication of demographic changes on blood donation and transfusion demand.

PubMed

Greinacher, Andreas; Weitmann, Kerstin; Schönborn, Linda; Alpen, Ulf; Gloger, Doris; Stangenberg, Wolfgang; Stüpmann, Kerstin; Greger, Nico; Kiefel, Volker; Hoffmann, Wolfgang

2017-06-13

Transfusion safety includes the risk of transmission of pathogens, appropriate transfusion thresholds, and sufficient blood supply. All industrialized countries experience major ongoing demographic changes resulting from low birth rates and aging of the baby boom generation. Little evidence exists about whether future blood supply and demand correlate with these demographic changes. The ≥50% decline in birth rate in the eastern part of Germany after 1990 facilitates systematic study of the effects of pronounced demographic changes on blood donation and demand. In this prospective, 10-year longitudinal study, we enrolled all whole blood donors and all patients receiving red blood cell transfusions in the state of Mecklenburg-West Pomerania. We compared projections made in 2005 based on the projected demographic changes with: (1) number and age distribution of blood donors and transfusion recipients in 2015 and (2) blood demand within specific age and patient groups. Blood donation rates closely followed the demographic changes, showing a decrease of -18% (vs projected -23%). In contrast, 2015 transfusion rates were -21.3% lower than projected. We conclude that although changes in demography are highly predictive for the blood supply, transfusion demand is strongly influenced by changes in medical practice. Given ongoing pronounced demographic change, regular monitoring of the donor/recipient age distributions and associated impact on blood demand/supply relationships is required to allow strategic planning to prevent blood shortages or overproduction.

Seismic Response Control Of Structures Using Semi-Active and Passive Variable Stiffness Devices

NASA Astrophysics Data System (ADS)

Salem, Mohamed M. A.

Controllable devices such as Magneto-Rheological Fluid Dampers, Electro-Rheological Dampers, and controllable friction devices have been studied extensively with limited implementation in real structures. Such devices have shown great potential in reducing seismic demands, either as smart base isolation systems, or as smart devices for multistory structures. Although variable stiffness devices can be used for seismic control of structures, the vast majority of research effort has been given to the control of damping. The primary focus of this dissertation is to evaluate the seismic control of structures using semi-active and passive variable stiffness characteristics. Smart base isolation systems employing variable stiffness devices have been studied, and two semi-active control strategies are proposed. The control algorithms were designed to reduce the superstructure and base accelerations of seismically isolated structures subject to near-fault and far-field ground motions. Computational simulations of the proposed control algorithms on the benchmark structure have shown that excessive base displacements associated with the near-fault ground motions may be better mitigated with the use of variable stiffness devices. However, the device properties must be controllable to produce a wide range of stiffness changes for an effective control of the base displacements. The potential of controllable stiffness devices in limiting the base displacement due to near-fault excitation without compromising the performance of conventionally isolated structures, is illustrated. The application of passive variable stiffness devices for seismic response mitigation of multistory structures is also investigated. A stiffening bracing system (SBS) is proposed to replace the conventional bracing systems of braced frames. An optimization process for the SBS parameters has been developed. The main objective of the design process is to maintain a uniform inter-story drift angle over the building's height, which in turn would evenly distribute the seismic demand over the building. This behavior is particularly essential so that any possible damage is not concentrated in a single story. Furthermore, the proposed design ensures that additional damping devices distributed over the building's height work efficiently with their maximum design capacity, leading to a cost efficient design. An integrated and comprehensive design procedure that can be readily adopted by the current seismic design codes is proposed. An equivalent lateral force distribution is developed that shows a good agreement with the response history analyses in terms of seismic performance and demand prediction. This lateral force pattern explicitly accounts for the higher mode effect, the dynamic characteristics of the structure, the supplemental damping, and the site specific seismic hazard. Therefore, the proposed design procedure is considered as a standalone method for the design of SBS equipped buildings.

Scoping Future Policy Dynamics in Raw Materials Through Scenarios Testing

NASA Astrophysics Data System (ADS)

Correia, Vitor; Keane, Christopher; Sturm, Flavius; Schimpf, Sven; Bodo, Balazs

2017-04-01

The International Raw Materials Observatory (INTRAW) project is working towards a sustainable future for the European Union in access to raw materials, from an availability, economical, and environmental framework. One of the major exercises for the INTRAW project is the evaluation of potential future scenarios for 2050 to frame economic, research, and environmental policy towards a sustainable raw materials supply. The INTRAW consortium developed three possible future scenarios that encompass defined regimes of political, economic, and technological norms. The first scenario, "Unlimited Trade," reflects a world in which free trade continues to dominate the global political and economic environment, with expectations of a growing demand for raw materials from widely distributed global growth. The "National Walls" scenario reflects a world where nationalism and economic protectionism begins to dominate, leading to stagnating economic growth and uneven dynamics in raw materials supply and demand. The final scenario, "Sustainability Alliance," examines the dynamics of a global political and economic climate that is focused on environmental and economic sustainability, leading towards increasingly towards a circular raw materials economy. These scenarios were reviewed, tested, and provided simulations of impacts with members of the Consortium and a panel of global experts on international raw materials issues which led to expected end conditions for 2050. Given the current uncertainty in global politics, these scenarios are informative to identifying likely opportunities and crises. The details of these simulations and expected responses to the research demand, technology investments, and economic components of raw materials system will be discussed.

Distributed Generation Market Demand Model | NREL

Science.gov Websites

Demand Model The Distributed Generation Market Demand (dGen) model simulates the potential adoption of distributed energy resources (DERs) for residential, commercial, and industrial entities in the dGen model can help develop deployment forecasts for distributed resources, including sensitivity to

A Multi Agent-Based Framework for Simulating Household PHEV Distribution and Electric Distribution Network Impact

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

Cui, Xiaohui; Liu, Cheng; Kim, Hoe Kyoung

2011-01-01

The variation of household attributes such as income, travel distance, age, household member, and education for different residential areas may generate different market penetration rates for plug-in hybrid electric vehicle (PHEV). Residential areas with higher PHEV ownership could increase peak electric demand locally and require utilities to upgrade the electric distribution infrastructure even though the capacity of the regional power grid is under-utilized. Estimating the future PHEV ownership distribution at the residential household level can help us understand the impact of PHEV fleet on power line congestion, transformer overload and other unforeseen problems at the local residential distribution network level.more » It can also help utilities manage the timing of recharging demand to maximize load factors and utilization of existing distribution resources. This paper presents a multi agent-based simulation framework for 1) modeling spatial distribution of PHEV ownership at local residential household level, 2) discovering PHEV hot zones where PHEV ownership may quickly increase in the near future, and 3) estimating the impacts of the increasing PHEV ownership on the local electric distribution network with different charging strategies. In this paper, we use Knox County, TN as a case study to show the simulation results of the agent-based model (ABM) framework. However, the framework can be easily applied to other local areas in the US.« less

Adaptive Resource Utilization Prediction System for Infrastructure as a Service Cloud.

PubMed

Zia Ullah, Qazi; Hassan, Shahzad; Khan, Gul Muhammad

2017-01-01

Infrastructure as a Service (IaaS) cloud provides resources as a service from a pool of compute, network, and storage resources. Cloud providers can manage their resource usage by knowing future usage demand from the current and past usage patterns of resources. Resource usage prediction is of great importance for dynamic scaling of cloud resources to achieve efficiency in terms of cost and energy consumption while keeping quality of service. The purpose of this paper is to present a real-time resource usage prediction system. The system takes real-time utilization of resources and feeds utilization values into several buffers based on the type of resources and time span size. Buffers are read by R language based statistical system. These buffers' data are checked to determine whether their data follows Gaussian distribution or not. In case of following Gaussian distribution, Autoregressive Integrated Moving Average (ARIMA) is applied; otherwise Autoregressive Neural Network (AR-NN) is applied. In ARIMA process, a model is selected based on minimum Akaike Information Criterion (AIC) values. Similarly, in AR-NN process, a network with the lowest Network Information Criterion (NIC) value is selected. We have evaluated our system with real traces of CPU utilization of an IaaS cloud of one hundred and twenty servers.

Adaptive Resource Utilization Prediction System for Infrastructure as a Service Cloud

PubMed Central

Hassan, Shahzad; Khan, Gul Muhammad

2017-01-01

Infrastructure as a Service (IaaS) cloud provides resources as a service from a pool of compute, network, and storage resources. Cloud providers can manage their resource usage by knowing future usage demand from the current and past usage patterns of resources. Resource usage prediction is of great importance for dynamic scaling of cloud resources to achieve efficiency in terms of cost and energy consumption while keeping quality of service. The purpose of this paper is to present a real-time resource usage prediction system. The system takes real-time utilization of resources and feeds utilization values into several buffers based on the type of resources and time span size. Buffers are read by R language based statistical system. These buffers' data are checked to determine whether their data follows Gaussian distribution or not. In case of following Gaussian distribution, Autoregressive Integrated Moving Average (ARIMA) is applied; otherwise Autoregressive Neural Network (AR-NN) is applied. In ARIMA process, a model is selected based on minimum Akaike Information Criterion (AIC) values. Similarly, in AR-NN process, a network with the lowest Network Information Criterion (NIC) value is selected. We have evaluated our system with real traces of CPU utilization of an IaaS cloud of one hundred and twenty servers. PMID:28811819

Assessing the ability of potential evapotranspiration models in capturing dynamics of evaporative demand across various biomes and climatic regimes with ChinaFLUX measurements

NASA Astrophysics Data System (ADS)

Zheng, Han; Yu, Guirui; Wang, Qiufeng; Zhu, Xianjin; Yan, Junhua; Wang, Huimin; Shi, Peili; Zhao, Fenghua; Li, Yingnian; Zhao, Liang; Zhang, Junhui; Wang, Yanfen

2017-08-01

Estimates of atmospheric evaporative demand have been widely required for a variety of hydrological analyses, with potential evapotranspiration (PET) being an important measure representing evaporative demand of actual vegetated surfaces under given metrological conditions. In this study, we assessed the ability of various PET models in capturing long-term (typically 2003-2011) dynamics of evaporative demand at eight ecosystems across various biomes and climatic regimes in China. Prior to assessing PET dynamics, we first examined the reasonability of fourteen PET models in representing the magnitudes of evaporative demand using eddy-covariance actual evapotranspiration (AET) as an indicator. Results showed that the robustness of the fourteen PET models differed somewhat across the sites, and only three PET models could produce reasonable magnitudes of evaporative demand (i.e., PET ≥ AET on average) for all eight sites, including the: (i) Penman; (ii) Priestly-Taylor and (iii) Linacre models. Then, we assessed the ability of these three PET models in capturing dynamics of evaporative demand by comparing the annual and seasonal trends in PET against the equivalent trends in AET and precipitation (P) for particular sites. Results indicated that nearly all the three PET models could faithfully reproduce the dynamics in evaporative demand for the energy-limited conditions at both annual and seasonal scales, while only the Penman and Linacre models could represent dynamics in evaporative demand for the water-limited conditions. However, the Linacre model was unable to reproduce the seasonal switches between water- and energy-limited states for some sites. Our findings demonstrated that the choice of PET models would be essential for the evaporative demand analyses and other related hydrological analyses at different temporal and spatial scales.

Model based manipulator control

NASA Technical Reports Server (NTRS)

Petrosky, Lyman J.; Oppenheim, Irving J.

1989-01-01

The feasibility of using model based control (MBC) for robotic manipulators was investigated. A double inverted pendulum system was constructed as the experimental system for a general study of dynamically stable manipulation. The original interest in dynamically stable systems was driven by the objective of high vertical reach (balancing), and the planning of inertially favorable trajectories for force and payload demands. The model-based control approach is described and the results of experimental tests are summarized. Results directly demonstrate that MBC can provide stable control at all speeds of operation and support operations requiring dynamic stability such as balancing. The application of MBC to systems with flexible links is also discussed.

Multidimensional kinetic simulations using dissipative closures and other reduced Vlasov methods for differing particle magnetizations

NASA Astrophysics Data System (ADS)

Newman, David L.

2006-10-01

Kinetic plasma simulations in which the phase-space distribution functions are advanced directly via the coupled Vlasov and Poisson (or Maxwell) equations---better known simply as Vlasov simulations---provide a valuable low-noise complement to the more commonly employed Particle-in-Cell (PIC) simulations. However, in more than one spatial dimension Vlasov simulations become numerically demanding due to the high dimensionality of x--v phase-space. Methods that can reduce this computational demand are therefore highly desirable. Several such methods will be presented, which treat the phase-space dynamics along a dominant dimension (e.g., parallel to a beam or current) with the full Vlasov propagator, while employing a reduced description, such as moment equations, for the evolution perpendicular to the dominant dimension. A key difference between the moment-based (and other reduced) methods considered here and standard fluid methods is that the moments are now functions of a phase-space coordinate (e.g. moments of vy in z--vz--y phase space, where z is the dominant dimension), rather than functions of spatial coordinates alone. Of course, moment-based methods require closure. For effectively unmagnetized species, new dissipative closure methods inspired by those of Hammett and Perkins [PRL, 64, 3019 (1990)] have been developed, which exactly reproduce the linear electrostatic response for a broad class of distributions with power-law tails, as are commonly measured in space plasmas. The nonlinear response, which requires more care, will also be discussed. For weakly magnetized species (i.e., φs<φs) an alternative algorithm has been developed in which the distributions are assumed to gyrate about the magnetic field with a fixed nominal perpendicular ``thermal'' velocity, thereby reducing the required phase-space dimension by one. These reduced algorithms have been incorporated into 2-D codes used to study the evolution of nonlinear structures such as double layers and electron holes in Earth's auroral zone.

Multi-agent based control of large-scale complex systems employing distributed dynamic inference engine

NASA Astrophysics Data System (ADS)

Zhang, Daili

Increasing societal demand for automation has led to considerable efforts to control large-scale complex systems, especially in the area of autonomous intelligent control methods. The control system of a large-scale complex system needs to satisfy four system level requirements: robustness, flexibility, reusability, and scalability. Corresponding to the four system level requirements, there arise four major challenges. First, it is difficult to get accurate and complete information. Second, the system may be physically highly distributed. Third, the system evolves very quickly. Fourth, emergent global behaviors of the system can be caused by small disturbances at the component level. The Multi-Agent Based Control (MABC) method as an implementation of distributed intelligent control has been the focus of research since the 1970s, in an effort to solve the above-mentioned problems in controlling large-scale complex systems. However, to the author's best knowledge, all MABC systems for large-scale complex systems with significant uncertainties are problem-specific and thus difficult to extend to other domains or larger systems. This situation is partly due to the control architecture of multiple agents being determined by agent to agent coupling and interaction mechanisms. Therefore, the research objective of this dissertation is to develop a comprehensive, generalized framework for the control system design of general large-scale complex systems with significant uncertainties, with the focus on distributed control architecture design and distributed inference engine design. A Hybrid Multi-Agent Based Control (HyMABC) architecture is proposed by combining hierarchical control architecture and module control architecture with logical replication rings. First, it decomposes a complex system hierarchically; second, it combines the components in the same level as a module, and then designs common interfaces for all of the components in the same module; third, replications are made for critical agents and are organized into logical rings. This architecture maintains clear guidelines for complexity decomposition and also increases the robustness of the whole system. Multiple Sectioned Dynamic Bayesian Networks (MSDBNs) as a distributed dynamic probabilistic inference engine, can be embedded into the control architecture to handle uncertainties of general large-scale complex systems. MSDBNs decomposes a large knowledge-based system into many agents. Each agent holds its partial perspective of a large problem domain by representing its knowledge as a Dynamic Bayesian Network (DBN). Each agent accesses local evidence from its corresponding local sensors and communicates with other agents through finite message passing. If the distributed agents can be organized into a tree structure, satisfying the running intersection property and d-sep set requirements, globally consistent inferences are achievable in a distributed way. By using different frequencies for local DBN agent belief updating and global system belief updating, it balances the communication cost with the global consistency of inferences. In this dissertation, a fully factorized Boyen-Koller (BK) approximation algorithm is used for local DBN agent belief updating, and the static Junction Forest Linkage Tree (JFLT) algorithm is used for global system belief updating. MSDBNs assume a static structure and a stable communication network for the whole system. However, for a real system, sub-Bayesian networks as nodes could be lost, and the communication network could be shut down due to partial damage in the system. Therefore, on-line and automatic MSDBNs structure formation is necessary for making robust state estimations and increasing survivability of the whole system. A Distributed Spanning Tree Optimization (DSTO) algorithm, a Distributed D-Sep Set Satisfaction (DDSSS) algorithm, and a Distributed Running Intersection Satisfaction (DRIS) algorithm are proposed in this dissertation. Combining these three distributed algorithms and a Distributed Belief Propagation (DBP) algorithm in MSDBNs makes state estimations robust to partial damage in the whole system. Combining the distributed control architecture design and the distributed inference engine design leads to a process of control system design for a general large-scale complex system. As applications of the proposed methodology, the control system design of a simplified ship chilled water system and a notional ship chilled water system have been demonstrated step by step. Simulation results not only show that the proposed methodology gives a clear guideline for control system design for general large-scale complex systems with dynamic and uncertain environment, but also indicate that the combination of MSDBNs and HyMABC can provide excellent performance for controlling general large-scale complex systems.

FPGA-based fused smart sensor for dynamic and vibration parameter extraction in industrial robot links.

PubMed

Rodriguez-Donate, Carlos; Morales-Velazquez, Luis; Osornio-Rios, Roque Alfredo; Herrera-Ruiz, Gilberto; de Jesus Romero-Troncoso, Rene

2010-01-01

Intelligent robotics demands the integration of smart sensors that allow the controller to efficiently measure physical quantities. Industrial manipulator robots require a constant monitoring of several parameters such as motion dynamics, inclination, and vibration. This work presents a novel smart sensor to estimate motion dynamics, inclination, and vibration parameters on industrial manipulator robot links based on two primary sensors: an encoder and a triaxial accelerometer. The proposed smart sensor implements a new methodology based on an oversampling technique, averaging decimation filters, FIR filters, finite differences and linear interpolation to estimate the interest parameters, which are computed online utilizing digital hardware signal processing based on field programmable gate arrays (FPGA).

FPGA-Based Fused Smart Sensor for Dynamic and Vibration Parameter Extraction in Industrial Robot Links

PubMed Central

Rodriguez-Donate, Carlos; Morales-Velazquez, Luis; Osornio-Rios, Roque Alfredo; Herrera-Ruiz, Gilberto; de Jesus Romero-Troncoso, Rene

2010-01-01

Intelligent robotics demands the integration of smart sensors that allow the controller to efficiently measure physical quantities. Industrial manipulator robots require a constant monitoring of several parameters such as motion dynamics, inclination, and vibration. This work presents a novel smart sensor to estimate motion dynamics, inclination, and vibration parameters on industrial manipulator robot links based on two primary sensors: an encoder and a triaxial accelerometer. The proposed smart sensor implements a new methodology based on an oversampling technique, averaging decimation filters, FIR filters, finite differences and linear interpolation to estimate the interest parameters, which are computed online utilizing digital hardware signal processing based on field programmable gate arrays (FPGA). PMID:22319345

Bio-inspired sensing and control for disturbance rejection and stabilization

NASA Astrophysics Data System (ADS)

Gremillion, Gregory; Humbert, James S.

2015-05-01

The successful operation of small unmanned aircraft systems (sUAS) in dynamic environments demands robust stability in the presence of exogenous disturbances. Flying insects are sensor-rich platforms, with highly redundant arrays of sensors distributed across the insect body that are integrated to extract rich information with diminished noise. This work presents a novel sensing framework in which measurements from an array of accelerometers distributed across a simulated flight vehicle are linearly combined to directly estimate the applied forces and torques with improvements in SNR. In simulation, the estimation performance is quantified as a function of sensor noise level, position estimate error, and sensor quantity.

EPPRD: An Efficient Privacy-Preserving Power Requirement and Distribution Aggregation Scheme for a Smart Grid.

PubMed

Zhang, Lei; Zhang, Jing

2017-08-07

A Smart Grid (SG) facilitates bidirectional demand-response communication between individual users and power providers with high computation and communication performance but also brings about the risk of leaking users' private information. Therefore, improving the individual power requirement and distribution efficiency to ensure communication reliability while preserving user privacy is a new challenge for SG. Based on this issue, we propose an efficient and privacy-preserving power requirement and distribution aggregation scheme (EPPRD) based on a hierarchical communication architecture. In the proposed scheme, an efficient encryption and authentication mechanism is proposed for better fit to each individual demand-response situation. Through extensive analysis and experiment, we demonstrate how the EPPRD resists various security threats and preserves user privacy while satisfying the individual requirement in a semi-honest model; it involves less communication overhead and computation time than the existing competing schemes.

EPPRD: An Efficient Privacy-Preserving Power Requirement and Distribution Aggregation Scheme for a Smart Grid

PubMed Central

Zhang, Lei; Zhang, Jing

2017-01-01

A Smart Grid (SG) facilitates bidirectional demand-response communication between individual users and power providers with high computation and communication performance but also brings about the risk of leaking users’ private information. Therefore, improving the individual power requirement and distribution efficiency to ensure communication reliability while preserving user privacy is a new challenge for SG. Based on this issue, we propose an efficient and privacy-preserving power requirement and distribution aggregation scheme (EPPRD) based on a hierarchical communication architecture. In the proposed scheme, an efficient encryption and authentication mechanism is proposed for better fit to each individual demand-response situation. Through extensive analysis and experiment, we demonstrate how the EPPRD resists various security threats and preserves user privacy while satisfying the individual requirement in a semi-honest model; it involves less communication overhead and computation time than the existing competing schemes. PMID:28783122

Modeling hurricane evacuation traffic : development of a time-dependent hurricane evacuation demand model.

DOT National Transportation Integrated Search

2006-04-01

Little attention has been given to estimating dynamic travel demand in transportation planning in the past. However, when factors influencing travel are changing significantly over time such as with an approaching hurricane - dynamic demand and t...

Effect of Cognitive Demand on Functional Visual Field Performance in Senior Drivers with Glaucoma

PubMed Central

Gangeddula, Viswa; Ranchet, Maud; Akinwuntan, Abiodun E.; Bollinger, Kathryn; Devos, Hannes

2017-01-01

Purpose: To investigate the effect of cognitive demand on functional visual field performance in drivers with glaucoma. Method: This study included 20 drivers with open-angle glaucoma and 13 age- and sex-matched controls. Visual field performance was evaluated under different degrees of cognitive demand: a static visual field condition (C1), dynamic visual field condition (C2), and dynamic visual field condition with active driving (C3) using an interactive, desktop driving simulator. The number of correct responses (accuracy) and response times on the visual field task were compared between groups and between conditions using Kruskal–Wallis tests. General linear models were employed to compare cognitive workload, recorded in real-time through pupillometry, between groups and conditions. Results: Adding cognitive demand (C2 and C3) to the static visual field test (C1) adversely affected accuracy and response times, in both groups (p < 0.05). However, drivers with glaucoma performed worse than did control drivers when the static condition changed to a dynamic condition [C2 vs. C1 accuracy; glaucoma: median difference (Q1–Q3) 3 (2–6.50) vs. controls: 2 (0.50–2.50); p = 0.05] and to a dynamic condition with active driving [C3 vs. C1 accuracy; glaucoma: 2 (2–6) vs. controls: 1 (0.50–2); p = 0.02]. Overall, drivers with glaucoma exhibited greater cognitive workload than controls (p = 0.02). Conclusion: Cognitive demand disproportionately affects functional visual field performance in drivers with glaucoma. Our results may inform the development of a performance-based visual field test for drivers with glaucoma. PMID:28912712

A fractional reaction-diffusion description of supply and demand

NASA Astrophysics Data System (ADS)

Benzaquen, Michael; Bouchaud, Jean-Philippe

2018-02-01

We suggest that the broad distribution of time scales in financial markets could be a crucial ingredient to reproduce realistic price dynamics in stylised Agent-Based Models. We propose a fractional reaction-diffusion model for the dynamics of latent liquidity in financial markets, where agents are very heterogeneous in terms of their characteristic frequencies. Several features of our model are amenable to an exact analytical treatment. We find in particular that the impact is a concave function of the transacted volume (aka the "square-root impact law"), as in the normal diffusion limit. However, the impact kernel decays as t-β with β = 1/2 in the diffusive case, which is inconsistent with market efficiency. In the sub-diffusive case the decay exponent β takes any value in [0, 1/2], and can be tuned to match the empirical value β ≈ 1/4. Numerical simulations confirm our theoretical results. Several extensions of the model are suggested. Contribution to the Topical Issue "Continuous Time Random Walk Still Trendy: Fifty-year History, Current State and Outlook", edited by Ryszard Kutner and Jaume Masoliver.

Enhanced intelligence through optimized TCPED concepts for airborne ISR

NASA Astrophysics Data System (ADS)

Spitzer, M.; Kappes, E.; Böker, D.

2012-06-01

Current multinational operations show an increased demand for high quality actionable intelligence for different operational levels and users. In order to achieve sufficient availability, quality and reliability of information, various ISR assets are orchestrated within operational theatres. Especially airborne Intelligence, Surveillance and Reconnaissance (ISR) assets provide - due to their endurance, non-intrusiveness, robustness, wide spectrum of sensors and flexibility to mission changes - significant intelligence coverage of areas of interest. An efficient and balanced utilization of airborne ISR assets calls for advanced concepts for the entire ISR process framework including the Tasking, Collection, Processing, Exploitation and Dissemination (TCPED). Beyond this, the employment of current visualization concepts, shared information bases and information customer profiles, as well as an adequate combination of ISR sensors with different information age and dynamic (online) retasking process elements provides the optimization of interlinked TCPED processes towards higher process robustness, shorter process duration, more flexibility between ISR missions and, finally, adequate "entry points" for information requirements by operational users and commands. In addition, relevant Trade-offs of distributed and dynamic TCPED processes are examined and future trends are depicted.

Representing Water Scarcity in Future Agricultural Assessments

NASA Technical Reports Server (NTRS)

Winter, Jonathan M.; Lopez, Jose R.; Ruane, Alexander C.; Young, Charles A.; Scanlon, Bridget R.; Rosenzweig, Cynthia

2017-01-01

Globally, irrigated agriculture is both essential for food production and the largest user of water. A major challenge for hydrologic and agricultural research communities is assessing the sustainability of irrigated croplands under climate variability and change. Simulations of irrigated croplands generally lack key interactions between water supply, water distribution, and agricultural water demand. In this article, we explore the critical interface between water resources and agriculture by motivating, developing, and illustrating the application of an integrated modeling framework to advance simulations of irrigated croplands. We motivate the framework by examining historical dynamics of irrigation water withdrawals in the United States and quantitatively reviewing previous modeling studies of irrigated croplands with a focus on representations of water supply, agricultural water demand, and impacts on crop yields when water demand exceeds water supply. We then describe the integrated modeling framework for simulating irrigated croplands, which links trends and scenarios with water supply, water allocation, and agricultural water demand. Finally, we provide examples of efforts that leverage the framework to improve simulations of irrigated croplands as well as identify opportunities for interventions that increase agricultural productivity, resiliency, and sustainability.

The reciprocal relationship between work characteristics and employee burnout and engagement: a longitudinal study of firefighters.

PubMed

Ângelo, R P; Chambel, M J

2015-04-01

The paradigm of this study is positive occupational psychology, with the job demands-resources model as the research model and the Conservation of Resources theory as the general stress theory. The research design analyses the job demands-resources model's dynamic nature with normal and reversed causation effects between work characteristics and psychological well-being among Portuguese firefighters. In addition, we analyse a positive (engagement) dimension and a negative (burnout) dimension in the firefighters' well-being, because previously, studies have merely focused on the strain or stress of these professionals. The research questionnaire was distributed to a sample of 651 firefighters, and a two-wave full panel design was used. Cross-lagged panel analyses indicated that the causal direction of the relationship between organizational demands and burnout is reciprocal. Also, we found that the reciprocal model, including cross-lagged reciprocal relationships between organizational demands/supervisory support and burnout/engagement, respectively, is what fits the data best. Practical implications to develop organizational change programmes and suggestions for future research regarding the promotion of occupational health are discussed. Copyright © 2013 John Wiley & Sons, Ltd.

Self-Adaptive Prediction of Cloud Resource Demands Using Ensemble Model and Subtractive-Fuzzy Clustering Based Fuzzy Neural Network

PubMed Central

Chen, Zhijia; Zhu, Yuanchang; Di, Yanqiang; Feng, Shaochong

2015-01-01

In IaaS (infrastructure as a service) cloud environment, users are provisioned with virtual machines (VMs). To allocate resources for users dynamically and effectively, accurate resource demands predicting is essential. For this purpose, this paper proposes a self-adaptive prediction method using ensemble model and subtractive-fuzzy clustering based fuzzy neural network (ESFCFNN). We analyze the characters of user preferences and demands. Then the architecture of the prediction model is constructed. We adopt some base predictors to compose the ensemble model. Then the structure and learning algorithm of fuzzy neural network is researched. To obtain the number of fuzzy rules and the initial value of the premise and consequent parameters, this paper proposes the fuzzy c-means combined with subtractive clustering algorithm, that is, the subtractive-fuzzy clustering. Finally, we adopt different criteria to evaluate the proposed method. The experiment results show that the method is accurate and effective in predicting the resource demands. PMID:25691896

A mission operations architecture for the 21st century

NASA Technical Reports Server (NTRS)

Tai, W.; Sweetnam, D.

1996-01-01

An operations architecture is proposed for low cost missions beyond the year 2000. The architecture consists of three elements: a service based architecture; a demand access automata; and distributed science hubs. The service based architecture is based on a set of standard multimission services that are defined, packaged and formalized by the deep space network and the advanced multi-mission operations system. The demand access automata is a suite of technologies which reduces the need to be in contact with the spacecraft, and thus reduces operating costs. The beacon signaling, the virtual emergency room, and the high efficiency tracking automata technologies are described. The distributed science hubs provide information system capabilities to the small science oriented flight teams: individual access to all traditional mission functions and services; multimedia intra-team communications, and automated direct transparent communications between the scientists and the instrument.

An initial approach towards quality of service based Spectrum Trading

NASA Astrophysics Data System (ADS)

Bastidas, Carlos E. Caicedo; Vanhoy, Garret; Volos, Haris I.; Bose, Tamal

Spectrum scarcity has become an important issue as demands for higher data rates increase in diverse wireless applications and aerospace communication scenarios. To address this problem, it becomes necessary to manage radio spectrum assignment in a way that optimizes the distribution of spectrum resources among several users while taking into account the quality of service (QoS) characteristics desired by the users of spectrum. In this paper, a novel approach to managing spectrum assignment based on Spectrum Trading (ST) will be presented. Market based spectrum assignment mechanisms such as spectrum trading are of growing interest to many spectrum management agencies that are planning to increase the use of these mechanisms for spectrum management and reduce their emphasis on command and control methods. This paper presents some of our initial work into incorporating quality of service information into the mechanisms that determine how spectrum should be traded when using a spectrum exchange. Through simulations and a testbed implementation of a QoS aware spectrum exchange our results show the viability of using QoS based mechanisms in spectrum trading and in the enhancement of dynamic spectrum assignment systems.

GPU-accelerated phase extraction algorithm for interferograms: a real-time application

NASA Astrophysics Data System (ADS)

Zhu, Xiaoqiang; Wu, Yongqian; Liu, Fengwei

2016-11-01

Optical testing, having the merits of non-destruction and high sensitivity, provides a vital guideline for optical manufacturing. But the testing process is often computationally intensive and expensive, usually up to a few seconds, which is sufferable for dynamic testing. In this paper, a GPU-accelerated phase extraction algorithm is proposed, which is based on the advanced iterative algorithm. The accelerated algorithm can extract the right phase-distribution from thirteen 1024x1024 fringe patterns with arbitrary phase shifts in 233 milliseconds on average using NVIDIA Quadro 4000 graphic card, which achieved a 12.7x speedup ratio than the same algorithm executed on CPU and 6.6x speedup ratio than that on Matlab using DWANING W5801 workstation. The performance improvement can fulfill the demand of computational accuracy and real-time application.

Neo-classical theory of competition or Adam Smith's hand as mathematized ideology

NASA Astrophysics Data System (ADS)

McCauley, Joseph L.

2001-10-01

Orthodox economic theory (utility maximization, rational agents, efficient markets in equilibrium) is based on arbitrarily postulated, nonempiric notions. The disagreement between economic reality and a key feature of neo-classical economic theory was criticized empirically by Osborne. I show that the orthodox theory is internally self-inconsistent for the very reason suggested by Osborne: lack of invertibility of demand and supply as functions of price to obtain price as functions of supply and demand. The reason for the noninvertibililty arises from nonintegrable excess demand dynamics, a feature of their theory completely ignored by economists.

Population-based funding formulae cultural coefficients: seeking a more equitable distribution of health dollars in New Zealand.

PubMed

Mellsop, Graham; McClintock, Kahu; Dutu, Gaelle

2007-03-23

Evidence and argument for the allocation of funds to forensic psychiatric services to take account of the ethnic disparities in the use of the Justice System is presented. This would reflect the reality of the distribution of Service demand.

75 FR 70031 - Antitrust Division

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-16

...) operate a branding program based upon distinctive trademarks to create high customer awareness of, demand... or subcontract a branding program; (vii) create printed and/or electronic materials for distribution...

Effects of random tooth profile errors on the dynamic behaviors of planetary gears

NASA Astrophysics Data System (ADS)

Xun, Chao; Long, Xinhua; Hua, Hongxing

2018-02-01

In this paper, a nonlinear random model is built to describe the dynamics of planetary gear trains (PGTs), in which the time-varying mesh stiffness, tooth profile modification (TPM), tooth contact loss, and random tooth profile error are considered. A stochastic method based on the method of multiple scales (MMS) is extended to analyze the statistical property of the dynamic performance of PGTs. By the proposed multiple-scales based stochastic method, the distributions of the dynamic transmission errors (DTEs) are investigated, and the lower and upper bounds are determined based on the 3σ principle. Monte Carlo method is employed to verify the proposed method. Results indicate that the proposed method can be used to determine the distribution of the DTE of PGTs high efficiently and allow a link between the manufacturing precision and the dynamical response. In addition, the effects of tooth profile modification on the distributions of vibration amplitudes and the probability of tooth contact loss with different manufacturing tooth profile errors are studied. The results show that the manufacturing precision affects the distribution of dynamic transmission errors dramatically and appropriate TPMs are helpful to decrease the nominal value and the deviation of the vibration amplitudes.

Frequency Based Real-time Pricing for Residential Prosumers

NASA Astrophysics Data System (ADS)

Hambridge, Sarah Mabel

This work is the first to explore frequency based pricing for secondary frequency control as a price-reactive control mechanism for residential prosumers. A frequency based real-time electricity rate is designed as an autonomous market control mechanism for residential prosumers to provide frequency support as an ancillary service. In addition, prosumers are empowered to participate in dynamic energy transactions, therefore integrating Distributed Energy Resources (DERs), and increasing distributed energy storage onto the distributed grid. As the grid transitions towards DERs, a new market based control system will take the place of the legacy distributed system and possibly the legacy bulk power system. DERs provide many benefits such as energy independence, clean generation, efficiency, and reliability to prosumers during blackouts. However, the variable nature of renewable energy and current lack of installed energy storage on the grid will create imbalances in supply and demand as uptake increases, affecting the grid frequency and system operation. Through a frequency-based electricity rate, prosumers will be encouraged to purchase energy storage systems (ESS) to offset their neighbor's distributed generation (DG) such as solar. Chapter 1 explains the deregulation of the power system and move towards Distributed System Operators (DSOs), as prosumers become owners of microgrids and energy cells connected to the distributed system. Dynamic pricing has been proposed as a benefit to prosumers, giving them the ability to make decisions in the energy market, while also providing a way to influence and control their behavior. Frequency based real-time pricing is a type of dynamic pricing which falls between price-reactive control and transactive control. Prosumer-to-prosumer transactions may take the place of prosumer-to-utility transactions, building The Energy Internet. Frequency based pricing could be a mechanism for determining prosumer prices and supporting stability in a free, competitive, market. Frequency based pricing is applied to secondary frequency control in this work, providing support at one to five minute time intervals. In Chapter 2, a frequency based pricing curve is designed as a preliminary study and the response of the prosumer is optimized for economic dispatch. In Chapter 3, a day-ahead schedule and real-time adjustment energy management framework is presented for the prosumer, creating a market structure similar to the existing energy market supervised by Independent System Operators (ISOs). Enabling technology, such as the solid state transformer (SST) is described for prosumer energy transactions, controlling power flow from the prosumer's energy cell to the grid or neighboring prosumer as an energy router. Experimental results are shown to demonstrate this capability. Additionally, the SST is capable of measuring the grid frequency. Lastly, a frequency based real-time hybrid electricity rate is presented in Chapter 4 and Chapter 5. Chapter 4 specializes in a single direction rate while Chapter 5 presents a bi-directional rate. A Time-of-use (TOU) rate is combined with the real-time frequency based price to lower energy bills for a residential prosumer with ESS, in agreement with the proposed day-ahead and real-time energy management framework. The cost to the ESS is also considered in this section. Linear programming and strategic rule based methods are utilized to find the lowest energy bill. As a result, prosumers can use ESS to balance the grid, reducing their bill as much per kWh as PV or DG under a TOU net-metering price scheme, while providing distributed frequency support to the grid authority. The variability of the frequency based rate is similar to variability in the stock market, which gives a sense of how prosumers will interact with variable prices in a system supported by The Energy Internet.

Estimating Oxygen Needs for Childhood Pneumonia in Developing Country Health Systems: A New Model for Expecting the Unexpected

PubMed Central

Bradley, Beverly D.; Howie, Stephen R. C.; Chan, Timothy C. Y.; Cheng, Yu-Ling

2014-01-01

Background Planning for the reliable and cost-effective supply of a health service commodity such as medical oxygen requires an understanding of the dynamic need or ‘demand’ for the commodity over time. In developing country health systems, however, collecting longitudinal clinical data for forecasting purposes is very difficult. Furthermore, approaches to estimating demand for supplies based on annual averages can underestimate demand some of the time by missing temporal variability. Methods A discrete event simulation model was developed to estimate variable demand for a health service commodity using the important example of medical oxygen for childhood pneumonia. The model is based on five key factors affecting oxygen demand: annual pneumonia admission rate, hypoxaemia prevalence, degree of seasonality, treatment duration, and oxygen flow rate. These parameters were varied over a wide range of values to generate simulation results for different settings. Total oxygen volume, peak patient load, and hours spent above average-based demand estimates were computed for both low and high seasons. Findings Oxygen demand estimates based on annual average values of demand factors can often severely underestimate actual demand. For scenarios with high hypoxaemia prevalence and degree of seasonality, demand can exceed average levels up to 68% of the time. Even for typical scenarios, demand may exceed three times the average level for several hours per day. Peak patient load is sensitive to hypoxaemia prevalence, whereas time spent at such peak loads is strongly influenced by degree of seasonality. Conclusion A theoretical study is presented whereby a simulation approach to estimating oxygen demand is used to better capture temporal variability compared to standard average-based approaches. This approach provides better grounds for health service planning, including decision-making around technologies for oxygen delivery. Beyond oxygen, this approach is widely applicable to other areas of resource and technology planning in developing country health systems. PMID:24587089

Numerical analysis of the transportation characteristics of a self-running sliding stage based on near-field acoustic levitation.

PubMed

Feng, Kai; Liu, Yuanyuan; Cheng, Miaomiao

2015-12-01

Owing to its distinct non-contact and oil-free characteristics, a self-running sliding stage based on near-field acoustic levitation can be used in an environment, which demands clean rooms and zero noise. This paper presents a numerical analysis on the lifting and transportation capacity of a non-contact transportation system. Two simplified structure models, namely, free vibration and force vibration models, are proposed for the study of the displacement amplitude distribution of two cases using the finite element method. After coupling the stage displacement into the film thickness, the Reynolds equation is solved by the finite difference method to obtain the lifting and thrusting forces. Parametric analyses of the effects of amplitude, frequency, and standing wave ratio (SWR) on the sliding stage dynamic performance are investigated. Numerical results show good agreement with published experimental values. The predictions also reveal that greater transportation capacity of the self-running sliding stage is generally achieved at less SWR and at higher amplitude.

Navigating the flow: individual and continuum models for homing in flowing environments

PubMed Central

Painter, Kevin J.; Hillen, Thomas

2015-01-01

Navigation for aquatic and airborne species often takes place in the face of complicated flows, from persistent currents to highly unpredictable storms. Hydrodynamic models are capable of simulating flow dynamics and provide the impetus for much individual-based modelling, in which particle-sized individuals are immersed into a flowing medium. These models yield insights on the impact of currents on population distributions from fish eggs to large organisms, yet their computational demands and intractability reduce their capacity to generate the broader, less parameter-specific, insights allowed by traditional continuous approaches. In this paper, we formulate an individual-based model for navigation within a flowing field and apply scaling to derive its corresponding macroscopic and continuous model. We apply it to various movement classes, from drifters that simply go with the flow to navigators that respond to environmental orienteering cues. The utility of the model is demonstrated via its application to ‘homing’ problems and, in particular, the navigation of the marine green turtle Chelonia mydas to Ascension Island. PMID:26538557

The effect of resistance level and stability demands on recruitment patterns and internal loading of spine in dynamic flexion and extension using a simple trunk model.

PubMed

Zeinali-Davarani, Shahrokh; Shirazi-Adl, Aboulfazl; Dariush, Behzad; Hemami, Hooshang; Parnianpour, Mohamad

2011-07-01

The effects of external resistance on the recruitment of trunk muscles in sagittal movements and the coactivation mechanism to maintain spinal stability were investigated using a simple computational model of iso-resistive spine sagittal movements. Neural excitation of muscles was attained based on inverse dynamics approach along with a stability-based optimisation. The trunk flexion and extension movements between 60° flexion and the upright posture against various resistance levels were simulated. Incorporation of the stability constraint in the optimisation algorithm required higher antagonistic activities for all resistance levels mostly close to the upright position. Extension movements showed higher coactivation with higher resistance, whereas flexion movements demonstrated lower coactivation indicating a greater stability demand in backward extension movements against higher resistance at the neighbourhood of the upright posture. Optimal extension profiles based on minimum jerk, work and power had distinct kinematics profiles which led to recruitment patterns with different timing and amplitude of activation.

One-laser-based generation/detection of Brillouin dynamic grating and its application to distributed discrimination of strain and temperature.

PubMed

Zou, Weiwen; He, Zuyuan; Hotate, Kazuo

2011-01-31

This paper presents a novel scheme to generate and detect Brillouin dynamic grating in a polarization-maintaining optical fiber based on one laser source. Precise measurement of Brillouin dynamic grating spectrum is achieved benefiting from that the pump, probe and readout waves are coherently originated from the same laser source. Distributed discrimination of strain and temperature is also achieved with high accuracy.

Medium-term electric power demand forecasting based on economic-electricity transmission model

NASA Astrophysics Data System (ADS)

Li, Wenfeng; Bao, Fangmin; Bai, Hongkun; Liu, Wei; Liu, Yongmin; Mao, Yubin; Wang, Jiangbo; Liu, Junhui

2018-06-01

Electric demand forecasting is a basic work to ensure the safe operation of power system. Based on the theories of experimental economics and econometrics, this paper introduces Prognoz Platform 7.2 intelligent adaptive modeling platform, and constructs the economic electricity transmission model that considers the economic development scenarios and the dynamic adjustment of industrial structure to predict the region's annual electricity demand, and the accurate prediction of the whole society's electricity consumption is realized. Firstly, based on the theories of experimental economics and econometrics, this dissertation attempts to find the economic indicator variables that drive the most economical growth of electricity consumption and availability, and build an annual regional macroeconomic forecast model that takes into account the dynamic adjustment of industrial structure. Secondly, it innovatively put forward the economic electricity directed conduction theory and constructed the economic power transfer function to realize the group forecast of the primary industry + rural residents living electricity consumption, urban residents living electricity, the second industry electricity consumption, the tertiary industry electricity consumption; By comparing with the actual value of economy and electricity in Henan province in 2016, the validity of EETM model is proved, and the electricity consumption of the whole province from 2017 to 2018 is predicted finally.

Evaluation of Electric Power Procurement Strategies by Stochastic Dynamic Programming

NASA Astrophysics Data System (ADS)

Saisho, Yuichi; Hayashi, Taketo; Fujii, Yasumasa; Yamaji, Kenji

In deregulated electricity markets, the role of a distribution company is to purchase electricity from the wholesale electricity market at randomly fluctuating prices and to provide it to its customers at a given fixed price. Therefore the company has to take risk stemming from the uncertainties of electricity prices and/or demand fluctuation instead of the customers. The way to avoid the risk is to make a bilateral contact with generating companies or install its own power generation facility. This entails the necessity to develop a certain method to make an optimal strategy for electric power procurement. In such a circumstance, this research has the purpose for proposing a mathematical method based on stochastic dynamic programming and additionally considering the characteristics of the start-up cost of electric power generation facility to evaluate strategies of combination of the bilateral contract and power auto-generation with its own facility for procuring electric power in deregulated electricity market. In the beginning we proposed two approaches to solve the stochastic dynamic programming, and they are a Monte Carlo simulation method and a finite difference method to derive the solution of a partial differential equation of the total procurement cost of electric power. Finally we discussed the influences of the price uncertainty on optimal strategies of power procurement.

The function of neurocognitive networks. Comment on “Understanding brain networks and brain organization” by Pessoa

NASA Astrophysics Data System (ADS)

Bressler, Steven L.

2014-09-01

Pessoa [5] has performed a valuable service by reviewing the extant literature on brain networks and making a number of interesting proposals about their cognitive function. The term function is at the core of understanding the brain networks of cognition, or neurocognitive networks (NCNs) [1]. The great Russian neuropsychologist, Luria [4], defined brain function as the common task executed by a distributed brain network of complex dynamic structures united by the demands of cognition. Casting Luria in a modern light, we can say that function emerges from the interactions of brain regions in NCNs as they dynamically self-organize according to cognitive demands. Pessoa rightly details the mapping between brain function and structure, emphasizing both its pluripotency (one structure having multiple functions) and degeneracy (many structures having the same function). However, he fails to consider the potential importance of a one-to-one mapping between NCNs and function. If NCNs are uniquely composed of specific collections of brain areas, then each NCN has a unique function determined by that composition.

Light requirements of Australian tropical vs. cool-temperate rainforest tree species show different relationships with seedling growth and functional traits.

PubMed

Lusk, Christopher H; Kelly, Jeff W G; Gleason, Sean M

2013-03-01

A trade-off between shade tolerance and growth in high light is thought to underlie the temporal dynamics of humid forests. On the other hand, it has been suggested that tree species sorting on temperature gradients involves a trade-off between growth rate and cold resistance. Little is known about how these two major trade-offs interact. Seedlings of Australian tropical and cool-temperate rainforest trees were grown in glasshouse environments to compare growth versus shade-tolerance trade-offs in these two assemblages. Biomass distribution, photosynthetic capacity and vessel diameters were measured in order to examine the functional correlates of species differences in light requirements and growth rate. Species light requirements were assessed by field estimation of the light compensation point for stem growth. Light-demanding and shade-tolerant tropical species differed markedly in relative growth rates (RGR), but this trend was less evident among temperate species. This pattern was paralleled by biomass distribution data: specific leaf area (SLA) and leaf area ratio (LAR) of tropical species were significantly positively correlated with compensation points, but not those of cool-temperate species. The relatively slow growth and small SLA and LAR of Tasmanian light-demanders were associated with narrow vessels and low potential sapwood conductivity. The conservative xylem traits, small LAR and modest RGR of Tasmanian light-demanders are consistent with selection for resistance to freeze-thaw embolism, at the expense of growth rate. Whereas competition for light favours rapid growth in light-demanding trees native to environments with warm, frost-free growing seasons, frost resistance may be an equally important determinant of the fitness of light-demanders in cool-temperate rainforest, as seedlings establishing in large openings are exposed to sub-zero temperatures that can occur throughout most of the year.

Efficient Computation Of Manipulator Inertia Matrix

NASA Technical Reports Server (NTRS)

Fijany, Amir; Bejczy, Antal K.

1991-01-01

Improved method for computation of manipulator inertia matrix developed, based on concept of spatial inertia of composite rigid body. Required for implementation of advanced dynamic-control schemes as well as dynamic simulation of manipulator motion. Motivated by increasing demand for fast algorithms to provide real-time control and simulation capability and, particularly, need for faster-than-real-time simulation capability, required in many anticipated space teleoperation applications.

Job task characteristics of Australian emergency services volunteers during search and rescue operations.

PubMed

Silk, Aaron; Lenton, Gavin; Savage, Robbie; Aisbett, Brad

2018-02-01

Search and rescue operations are necessary in locating, assisting and recovering individuals lost or in distress. In Australia, land-based search and rescue roles require a range of physically demanding tasks undertaken in dynamic and challenging environments. The aim of the current research was to identify and characterise the physically demanding tasks inherent to search and rescue operation personnel within Australia. These aims were met through a subjective job task analysis approach. In total, 11 criterion tasks were identified by personnel. These tasks were the most physically demanding, frequently occurring and operationally important tasks to these specialist roles. Muscular strength was the dominant fitness component for 7 of the 11 tasks. In addition to the discrete criterion tasks, an operational scenario was established. With the tasks and operational scenario identified, objective task analysis procedures can be undertaken so that practitioners can implement evidence-based strategies, such as physical selection procedures and task-based physical training programs, commensurate with the physical demands of search and rescue job roles. Practitioner Summary: The identification of physically demanding tasks amongst specialist emergency service roles predicates health and safety strategies which can be incorporated into organisations. Knowledge of physical task parameters allows employers to mitigate injury risk through the implementation of strategies modelled on the precise physical demands of the role.

Time of Day and Day of Week Trends in EMS Demand.

PubMed

Cantwell, Kate; Morgans, Amee; Smith, Karen; Livingston, Michael; Spelman, Tim; Dietze, Paul

2015-01-01

We examined temporal variations in overall Emergency Medical Services (EMS) demand, as well as medical and trauma cases separately. We analyzed cases according to time of day and day of week to determine whether population level demand demonstrates temporal patterns that will increase baseline knowledge for EMS planning. We conducted a secondary analysis of data from the Ambulance Victoria data warehouse covering the period 2008-2011. We included all cases of EMS attendance which resulted in 1,203,803 cases for review. Data elements comprised age, gender, date and time of call to the EMS emergency number along with the clinical condition of the patient. We employed Poisson regression to analyze case numbers and trigonometric regression to quantify distribution patterns. EMS demand exhibited a bimodal distribution with the highest peak at 10:00 and a second smaller peak at 19:00. The highest number of cases occurred on Fridays, and the lowest on Tuesdays and Wednesdays. However, the distribution of cases throughout the day differed by day of week. Distribution patterns on Fridays, Saturdays and Sundays differed significantly from the rest of the week (p < 0.001). When categorized into medical or trauma cases, medical cases were more frequent during working hours and involved patients of higher mean age (57 years vs. 49 years for trauma, p < 0.001). Trauma cases peaked on Friday and Saturday nights around midnight. Day of week EMS demand distribution patterns reveal differences that can be masked in aggregate data. Day of week EMS demand distribution patterns showed not only which days have differences in demand but the times of day at which the demand changes. Patterns differed by case type as well. These differences in distribution are important for EMS demand planning. Increased understanding of EMS demand patterns is imperative in a climate of ever-increasing demand and fiscal constraints. Further research is needed into the effect of age and case type on EMS demand.

How to sell a condom? The impact of demand creation tools on male and female condom sales in resource limited settings.

PubMed

Terris-Prestholt, Fern; Windmeijer, Frank

2016-07-01

Despite condoms being cheap and effective in preventing HIV, there remains an 8billion shortfall in condom use in risky sex-acts. Social marketing organisations apply private sector marketing approaches to sell public health products. This paper investigates the impact of marketing tools, including promotion and pricing, on demand for male and female condoms in 52 countries between 1997 and 2009. A static model differentiates drivers of demand between products, while a dynamic panel data estimator estimates their short- and long-run impacts. Products are not equally affected: female condoms are not affected by advertising, but highly affected by interpersonal communication and HIV prevalence. Price and promotion have significant short- and long-run effects, with female condoms far more sensitive to price than male condoms. The design of optimal distribution strategies for new and existing HIV prevention technologies must consider both product and target population characteristics. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

A Study on Grid-Square Statistics Based Estimation of Regional Electricity Demand and Regional Potential Capacity of Distributed Generators

NASA Astrophysics Data System (ADS)

Kato, Takeyoshi; Sugimoto, Hiroyuki; Suzuoki, Yasuo

We established a procedure for estimating regional electricity demand and regional potential capacity of distributed generators (DGs) by using a grid square statistics data set. A photovoltaic power system (PV system) for residential use and a co-generation system (CGS) for both residential and commercial use were taken into account. As an example, the result regarding Aichi prefecture was presented in this paper. The statistical data of the number of households by family-type and the number of employees by business category for about 4000 grid-square with 1km × 1km area was used to estimate the floor space or the electricity demand distribution. The rooftop area available for installing PV systems was also estimated with the grid-square statistics data set. Considering the relation between a capacity of existing CGS and a scale-index of building where CGS is installed, the potential capacity of CGS was estimated for three business categories, i.e. hotel, hospital, store. In some regions, the potential capacity of PV systems was estimated to be about 10,000kW/km2, which corresponds to the density of the existing area with intensive installation of PV systems. Finally, we discussed the ratio of regional potential capacity of DGs to regional maximum electricity demand for deducing the appropriate capacity of DGs in the model of future electricity distribution system.

RIDES: Robust Intrusion Detection System for IP-Based Ubiquitous Sensor Networks

PubMed Central

Amin, Syed Obaid; Siddiqui, Muhammad Shoaib; Hong, Choong Seon; Lee, Sungwon

2009-01-01

The IP-based Ubiquitous Sensor Network (IP-USN) is an effort to build the “Internet of things”. By utilizing IP for low power networks, we can benefit from existing well established tools and technologies of IP networks. Along with many other unresolved issues, securing IP-USN is of great concern for researchers so that future market satisfaction and demands can be met. Without proper security measures, both reactive and proactive, it is hard to envisage an IP-USN realm. In this paper we present a design of an IDS (Intrusion Detection System) called RIDES (Robust Intrusion DEtection System) for IP-USN. RIDES is a hybrid intrusion detection system, which incorporates both Signature and Anomaly based intrusion detection components. For signature based intrusion detection this paper only discusses the implementation of distributed pattern matching algorithm with the help of signature-code, a dynamically created attack-signature identifier. Other aspects, such as creation of rules are not discussed. On the other hand, for anomaly based detection we propose a scoring classifier based on the SPC (Statistical Process Control) technique called CUSUM charts. We also investigate the settings and their effects on the performance of related parameters for both of the components. PMID:22412321

RIDES: Robust Intrusion Detection System for IP-Based Ubiquitous Sensor Networks.

PubMed

Amin, Syed Obaid; Siddiqui, Muhammad Shoaib; Hong, Choong Seon; Lee, Sungwon

2009-01-01

The IP-based Ubiquitous Sensor Network (IP-USN) is an effort to build the "Internet of things". By utilizing IP for low power networks, we can benefit from existing well established tools and technologies of IP networks. Along with many other unresolved issues, securing IP-USN is of great concern for researchers so that future market satisfaction and demands can be met. Without proper security measures, both reactive and proactive, it is hard to envisage an IP-USN realm. In this paper we present a design of an IDS (Intrusion Detection System) called RIDES (Robust Intrusion DEtection System) for IP-USN. RIDES is a hybrid intrusion detection system, which incorporates both Signature and Anomaly based intrusion detection components. For signature based intrusion detection this paper only discusses the implementation of distributed pattern matching algorithm with the help of signature-code, a dynamically created attack-signature identifier. Other aspects, such as creation of rules are not discussed. On the other hand, for anomaly based detection we propose a scoring classifier based on the SPC (Statistical Process Control) technique called CUSUM charts. We also investigate the settings and their effects on the performance of related parameters for both of the components.

Incorporating human-water dynamics in a hyper-resolution land surface model

NASA Astrophysics Data System (ADS)

Vergopolan, N.; Chaney, N.; Wanders, N.; Sheffield, J.; Wood, E. F.

2017-12-01

The increasing demand for water, energy, and food is leading to unsustainable groundwater and surface water exploitation. As a result, the human interactions with the environment, through alteration of land and water resources dynamics, need to be reflected in hydrologic and land surface models (LSMs). Advancements in representing human-water dynamics still leave challenges related to the lack of water use data, water allocation algorithms, and modeling scales. This leads to an over-simplistic representation of human water use in large-scale models; this is in turn leads to an inability to capture extreme events signatures and to provide reliable information at stakeholder-level spatial scales. The emergence of hyper-resolution models allows one to address these challenges by simulating the hydrological processes and interactions with the human impacts at field scales. We integrated human-water dynamics into HydroBlocks - a hyper-resolution, field-scale resolving LSM. HydroBlocks explicitly solves the field-scale spatial heterogeneity of land surface processes through interacting hydrologic response units (HRUs); and its HRU-based model parallelization allows computationally efficient long-term simulations as well as ensemble predictions. The implemented human-water dynamics include groundwater and surface water abstraction to meet agricultural, domestic and industrial water demands. Furthermore, a supply-demand water allocation scheme based on relative costs helps to determine sectoral water use requirements and tradeoffs. A set of HydroBlocks simulations over the Midwest United States (daily, at 30-m spatial resolution for 30 years) are used to quantify the irrigation impacts on water availability. The model captures large reductions in total soil moisture and water table levels, as well as spatiotemporal changes in evapotranspiration and runoff peaks, with their intensity related to the adopted water management strategy. By incorporating human-water dynamics in a hyper-resolution LSM this work allows for progress on hydrological monitoring and predictions, as well as drought preparedness and water impact assessments at relevant decision-making scales.

Using the Viability Theory to Assess the Flexibility of Forest Managers Under Ecological Intensification

NASA Astrophysics Data System (ADS)

Mathias, Jean-Denis; Bonté, Bruno; Cordonnier, Thomas; de Morogues, Francis

2015-11-01

Greater demand for wood material has converged with greater demand for biodiversity conservation to make balancing forest ecosystem services a key societal issue. Forest managers, owners, or policymakers need new approaches and methods to evaluate their ability to adapt to this dual objective. We analyze the ability of forest owners to define sustainable forest management options based on viability theory and a new flexibility index. This new indicator gauges the adaptive capacity of forest owners based on the number of sustainable actions available to them at a given time. Here we study a public forest owner who regulates harvest intensity and frequency in order to meet demand for timber wood at forest scale and to meet a biodiversity recommendation via a minimum permanently maintained volume of deadwood per hectare at stand scale. Dynamical systems theory was used to model uneven-aged forest dynamics—including deadwood dynamics—and the dynamics of timber wood demand and tree removals. Uneven-aged silver fir forest management in the "Quatre Montagnes region" (Vercors, France) is used as an illustrative example. The results explain situations where a joint increase in wood production and deadwood retention does not reduce the flexibility index more than increasing either one dimension alone, thus opening up ecological intensification options. To conclude, we discuss the value of the new flexibility index for addressing environmental management and ecological intensification issues.

The dynamic and indirect spatial effects of neighborhood conditions on land value, spatial panel dynamic econometrics model

NASA Astrophysics Data System (ADS)

Fitriani, Rahma; Sumarminingsih, Eni; Astutik, Suci

2017-05-01

Land value is the product of past decision of its use leading to its value, as well as the value of the surrounded land. It is also affected by the local characteristic and the spillover development demand of the previous time period. The effect of each factor on land value will have dynamic and spatial virtues. Thus, a spatial panel dynamic model is used to estimate the particular effects. The model will be useful for predicting the future land value or the effect of implemented policy on land value. The objective of this paper is to derive the dynamic and indirect spatial marginal effects of the land characteristic and the spillover development demand on land value. Each effect is the partial derivative of the expected land value based on the spatial dynamic model with respect to each variable, by considering different time period and different location. The results indicate that the instant change of local or neighborhood characteristics on land value affect the local and the immediate neighborhood land value. However, the longer the change take place, the effect will spread further, not only on the immediate neighborhood.

Energy Technology Allocation for Distributed Energy Resources: A Technology-Policy Framework

NASA Astrophysics Data System (ADS)

Mallikarjun, Sreekanth

Distributed energy resources (DER) are emerging rapidly. New engineering technologies, materials, and designs improve the performance and extend the range of locations for DER. In contrast, constructing new or modernizing existing high voltage transmission lines for centralized generation are expensive and challenging. In addition, customer demand for reliability has increased and concerns about climate change have created a pull for swift renewable energy penetration. In this context, DER policy makers, developers, and users are interested in determining which energy technologies to use to accommodate different end-use energy demands. We present a two-stage multi-objective strategic technology-policy framework for determining the optimal energy technology allocation for DER. The framework simultaneously considers economic, technical, and environmental objectives. The first stage utilizes a Data Envelopment Analysis model for each end-use to evaluate the performance of each energy technology based on the three objectives. The second stage incorporates factor efficiencies determined in the first stage, capacity limitations, dispatchability, and renewable penetration for each technology, and demand for each end-use into a bottleneck multi-criteria decision model which provides the Pareto-optimal energy resource allocation. We conduct several case studies to understand the roles of various distributed energy technologies in different scenarios. We construct some policy implications based on the model results of set of case studies.

Money-center structures in dynamic banking systems

NASA Astrophysics Data System (ADS)

Li, Shouwei; Zhang, Minghui

2016-10-01

In this paper, we propose a dynamic model for banking systems based on the description of balance sheets. It generates some features identified through empirical analysis. Through simulation analysis of the model, we find that banking systems have the feature of money-center structures, that bank asset distributions are power-law distributions, and that contract size distributions are log-normal distributions.

A dynamic re-partitioning strategy based on the distribution of key in Spark

NASA Astrophysics Data System (ADS)

Zhang, Tianyu; Lian, Xin

2018-05-01

Spark is a memory-based distributed data processing framework, has the ability of processing massive data and becomes a focus in Big Data. But the performance of Spark Shuffle depends on the distribution of data. The naive Hash partition function of Spark can not guarantee load balancing when data is skewed. The time of job is affected by the node which has more data to process. In order to handle this problem, dynamic sampling is used. In the process of task execution, histogram is used to count the key frequency distribution of each node, and then generate the global key frequency distribution. After analyzing the distribution of key, load balance of data partition is achieved. Results show that the Dynamic Re-Partitioning function is better than the default Hash partition, Fine Partition and the Balanced-Schedule strategy, it can reduce the execution time of the task and improve the efficiency of the whole cluster.

Cluster-Based Maximum Consensus Time Synchronization for Industrial Wireless Sensor Networks.

PubMed

Wang, Zhaowei; Zeng, Peng; Zhou, Mingtuo; Li, Dong; Wang, Jintao

2017-01-13

Time synchronization is one of the key technologies in Industrial Wireless Sensor Networks (IWSNs), and clustering is widely used in WSNs for data fusion and information collection to reduce redundant data and communication overhead. Considering IWSNs' demand for low energy consumption, fast convergence, and robustness, this paper presents a novel Cluster-based Maximum consensus Time Synchronization (CMTS) method. It consists of two parts: intra-cluster time synchronization and inter-cluster time synchronization. Based on the theory of distributed consensus, the proposed method utilizes the maximum consensus approach to realize the intra-cluster time synchronization, and adjacent clusters exchange the time messages via overlapping nodes to synchronize with each other. A Revised-CMTS is further proposed to counteract the impact of bounded communication delays between two connected nodes, because the traditional stochastic models of the communication delays would distort in a dynamic environment. The simulation results show that our method reduces the communication overhead and improves the convergence rate in comparison to existing works, as well as adapting to the uncertain bounded communication delays.

Cluster-Based Maximum Consensus Time Synchronization for Industrial Wireless Sensor Networks †

PubMed Central

Wang, Zhaowei; Zeng, Peng; Zhou, Mingtuo; Li, Dong; Wang, Jintao

2017-01-01

Time synchronization is one of the key technologies in Industrial Wireless Sensor Networks (IWSNs), and clustering is widely used in WSNs for data fusion and information collection to reduce redundant data and communication overhead. Considering IWSNs’ demand for low energy consumption, fast convergence, and robustness, this paper presents a novel Cluster-based Maximum consensus Time Synchronization (CMTS) method. It consists of two parts: intra-cluster time synchronization and inter-cluster time synchronization. Based on the theory of distributed consensus, the proposed method utilizes the maximum consensus approach to realize the intra-cluster time synchronization, and adjacent clusters exchange the time messages via overlapping nodes to synchronize with each other. A Revised-CMTS is further proposed to counteract the impact of bounded communication delays between two connected nodes, because the traditional stochastic models of the communication delays would distort in a dynamic environment. The simulation results show that our method reduces the communication overhead and improves the convergence rate in comparison to existing works, as well as adapting to the uncertain bounded communication delays. PMID:28098750

A novel medical information management and decision model for uncertain demand optimization.

PubMed

Bi, Ya

2015-01-01

Accurately planning the procurement volume is an effective measure for controlling the medicine inventory cost. Due to uncertain demand it is difficult to make accurate decision on procurement volume. As to the biomedicine sensitive to time and season demand, the uncertain demand fitted by the fuzzy mathematics method is obviously better than general random distribution functions. To establish a novel medical information management and decision model for uncertain demand optimization. A novel optimal management and decision model under uncertain demand has been presented based on fuzzy mathematics and a new comprehensive improved particle swarm algorithm. The optimal management and decision model can effectively reduce the medicine inventory cost. The proposed improved particle swarm optimization is a simple and effective algorithm to improve the Fuzzy interference and hence effectively reduce the calculation complexity of the optimal management and decision model. Therefore the new model can be used for accurate decision on procurement volume under uncertain demand.

National Renewable Energy Laboratory (NREL) Topic 2 Final Report: End-to-End Communication and Control System to Support Clean Energy Technologies

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

Hudgins, Andrew P.; Carrillo, Ismael M.; Jin, Xin

This document is the final report of a two-year development, test, and demonstration project, 'Cohesive Application of Standards- Based Connected Devices to Enable Clean Energy Technologies.' The project was part of the National Renewable Energy Laboratory's (NREL's) Integrated Network Testbed for Energy Grid Research and Technology (INTEGRATE) initiative hosted at Energy Systems Integration Facility (ESIF). This project demonstrated techniques to control distribution grid events using the coordination of traditional distribution grid devices and high-penetration renewable resources and demand response. Using standard communication protocols and semantic standards, the project examined the use cases of high/low distribution voltage, requests for volt-ampere-reactive (VAR)more » power support, and transactive energy strategies using Volttron. Open source software, written by EPRI to control distributed energy resources (DER) and demand response (DR), was used by an advanced distribution management system (ADMS) to abstract the resources reporting to a collection of capabilities rather than needing to know specific resource types. This architecture allows for scaling both horizontally and vertically. Several new technologies were developed and tested. Messages from the ADMS based on the common information model (CIM) were developed to control the DER and DR management systems. The OpenADR standard was used to help manage grid events by turning loads off and on. Volttron technology was used to simulate a homeowner choosing the price at which to enter the demand response market. Finally, the ADMS used newly developed algorithms to coordinate these resources with a capacitor bank and voltage regulator to respond to grid events.« less

Dynamics of electricity market correlations

NASA Astrophysics Data System (ADS)

Alvarez-Ramirez, J.; Escarela-Perez, R.; Espinosa-Perez, G.; Urrea, R.

2009-06-01

Electricity market participants rely on demand and price forecasts to decide their bidding strategies, allocate assets, negotiate bilateral contracts, hedge risks, and plan facility investments. However, forecasting is hampered by the non-linear and stochastic nature of price time series. Diverse modeling strategies, from neural networks to traditional transfer functions, have been explored. These approaches are based on the assumption that price series contain correlations that can be exploited for model-based prediction purposes. While many works have been devoted to the demand and price modeling, a limited number of reports on the nature and dynamics of electricity market correlations are available. This paper uses detrended fluctuation analysis to study correlations in the demand and price time series and takes the Australian market as a case study. The results show the existence of correlations in both demand and prices over three orders of magnitude in time ranging from hours to months. However, the Hurst exponent is not constant over time, and its time evolution was computed over a subsample moving window of 250 observations. The computations, also made for two Canadian markets, show that the correlations present important fluctuations over a seasonal one-year cycle. Interestingly, non-linearities (measured in terms of a multifractality index) and reduced price predictability are found for the June-July periods, while the converse behavior is displayed during the December-January period. In terms of forecasting models, our results suggest that non-linear recursive models should be considered for accurate day-ahead price estimation. On the other hand, linear models seem to suffice for demand forecasting purposes.

Potential Effects of Health Care Policy Decisions on Physician Availability

NASA Technical Reports Server (NTRS)

Garcia, Christopher; Goodrich, Michael

2011-01-01

Many regions in America are experiencing downward trends in the number of practicing physicians and the number of available physician hours, resulting in a worrisome decrease in the availability of health care services. Recent changes in American health care legislation may induce a rapid change in the demand for health care services, which in turn will result in a new supply-demand equilibrium . In this paper we develop a system dynamics model linking physician availability to health care demand and profitability. We use this model to explore scenarios based on different initial conditions and describe possible outcomes for a range of different policy decisions.

Reversible solid oxide fuel cell for natural gas/renewable hybrid power generation systems

NASA Astrophysics Data System (ADS)

Luo, Yu; Shi, Yixiang; Zheng, Yi; Cai, Ningsheng

2017-02-01

Renewable energy (RE) is expected to be the major part of the future energy. Presently, the intermittence and fluctuation of RE lead to the limitation of its penetration. Reversible solid oxide fuel cell (RSOFC) as the energy storage device can effectively store the renewable energy and build a bidirectional connection with natural gas (NG). In this paper, the energy storage strategy was designed to improve the RE penetration and dynamic operation stability in a distributed system coupling wind generators, internal combustion engine, RSOFC and lithium-ion batteries. By compromising the relative deviation of power supply and demand, RE penetration, system efficiency and capacity requirement, the strategy that no more than 36% of the maximum wind power output is directly supplied to users and the other is stored by the combination of battery and reversible solid oxide fuel cell is optimal for the distributed system. In the case, the RE penetration reached 56.9% and the system efficiency reached 55.2%. The maximum relative deviation of power supply and demand is also lower than 4%, which is significantly superior to that in the wind curtailment case.

Dynamic SLA Negotiation in Autonomic Federated Environments

NASA Astrophysics Data System (ADS)

Rubach, Pawel; Sobolewski, Michael

Federated computing environments offer requestors the ability to dynamically invoke services offered by collaborating providers in the virtual service network. Without an efficient resource management that includes Dynamic SLA Negotiation, however, the assignment of providers to customer's requests cannot be optimized and cannot offer high reliability without relevant SLA guarantees. We propose a new SLA-based SERViceable Metacomputing Environment (SERVME) capable of matching providers based on QoS requirements and performing autonomic provisioning and deprovisioning of services according to dynamic requestor needs. This paper presents the SLA negotiation process that includes on-demand provisioning and uses an object-oriented SLA model for large-scale service-oriented systems supported by SERVME. An initial reference implementation in the SORCER environment is also described.

Self-Organizing Distributed Architecture Supporting Dynamic Space Expanding and Reducing in Indoor LBS Environment

PubMed Central

Jeong, Seol Young; Jo, Hyeong Gon; Kang, Soon Ju

2015-01-01

Indoor location-based services (iLBS) are extremely dynamic and changeable, and include numerous resources and mobile devices. In particular, the network infrastructure requires support for high scalability in the indoor environment, and various resource lookups are requested concurrently and frequently from several locations based on the dynamic network environment. A traditional map-based centralized approach for iLBSs has several disadvantages: it requires global knowledge to maintain a complete geographic indoor map; the central server is a single point of failure; it can also cause low scalability and traffic congestion; and it is hard to adapt to a change of service area in real time. This paper proposes a self-organizing and fully distributed platform for iLBSs. The proposed self-organizing distributed platform provides a dynamic reconfiguration of locality accuracy and service coverage by expanding and contracting dynamically. In order to verify the suggested platform, scalability performance according to the number of inserted or deleted nodes composing the dynamic infrastructure was evaluated through a simulation similar to the real environment. PMID:26016908

Space evolution model and empirical analysis of an urban public transport network

NASA Astrophysics Data System (ADS)

Sui, Yi; Shao, Feng-jing; Sun, Ren-cheng; Li, Shu-jing

2012-07-01

This study explores the space evolution of an urban public transport network, using empirical evidence and a simulation model validated on that data. Public transport patterns primarily depend on traffic spatial-distribution, demands of passengers and expected utility of investors. Evolution is an iterative process of satisfying the needs of passengers and investors based on a given traffic spatial-distribution. The temporal change of urban public transport network is evaluated both using topological measures and spatial ones. The simulation model is validated using empirical data from nine big cities in China. Statistical analyses on topological and spatial attributes suggest that an evolution network with traffic demands characterized by power-law numerical values which distribute in a mode of concentric circles tallies well with these nine cities.

Coupling Cellular Automata Land Use Change with Distributed Hydrologic Models

NASA Astrophysics Data System (ADS)

Shu, L.; Duffy, C.

2017-12-01

There has been extensive research on LUC modeling with broad applications to simulating urban growth and changing demographic patterns across multiple scales. The importance of land conversion is a critical issue in watershed scale studies and is generally not treated in most watershed modeling approaches. In this study we apply spatially explicit hydrologic and landuse change models and the Conestoga Watershed in Lancaster County, Pennsylvania. The Penn State Integrated Hydrologic Model (PIHM) partitions the water balance in space and time over the urban catchment, the coupled Cellular Automata Land Use Change model (CALUC) dynamically simulates the evolution of land use classes based on physical measures associated with population change and land use demand factors. The CALUC model is based on iteratively applying discrete rules to each individual spatial cell. The essence the CA modeling involves calculation of the Transition Potential (TP) for conversion of a grid cell from one land use class to another. This potential includes five factors: random perturbation, suitability, accessibility, neighborhood effect, inertia effects and zonal factors. In spite of simplicity, this CALUC model has been shown to be very effective for simulating LUC leading to the emergence of complex spatial patterns. The components of TP are derived from present land use data for landuse reanalysis and for realistic future land use scenarios. For the CALUC we use early-settlement (circa 1790) initial land class values and final or present-day (2010) land classes to calibrate the model. CALUC- PIHM dynamically simulates the hydrologic response of conversion from pre-settlement to present landuse. The simulations highlight the capability and value of dynamic coupling of catchment hydrology with land use change over long time periods. Analysis of the simulation uses various metrics such as the distributed water balance, flow duration curves, etc. to show how deforestation, urbanization and agricultural land development interact for the period 1790- present.

Phase change energy storage for solar dynamic power systems

NASA Technical Reports Server (NTRS)

Chiaramonte, F. P.; Taylor, J. D.

1992-01-01

This paper presents the results of a transient computer simulation that was developed to study phase change energy storage techniques for Space Station Freedom (SSF) solar dynamic (SD) power systems. Such SD systems may be used in future growth SSF configurations. Two solar dynamic options are considered in this paper: Brayton and Rankine. Model elements consist of a single node receiver and concentrator, and takes into account overall heat engine efficiency and power distribution characteristics. The simulation not only computes the energy stored in the receiver phase change material (PCM), but also the amount of the PCM required for various combinations of load demands and power system mission constraints. For a solar dynamic power system in low earth orbit, the amount of stored PCM energy is calculated by balancing the solar energy input and the energy consumed by the loads corrected by an overall system efficiency. The model assumes an average 75 kW SD power system load profile which is connected to user loads via dedicated power distribution channels. The model then calculates the stored energy in the receiver and subsequently estimates the quantity of PCM necessary to meet peaking and contingency requirements. The model can also be used to conduct trade studies on the performance of SD power systems using different storage materials.

Phase change energy storage for solar dynamic power systems

NASA Astrophysics Data System (ADS)

Chiaramonte, F. P.; Taylor, J. D.

This paper presents the results of a transient computer simulation that was developed to study phase change energy storage techniques for Space Station Freedom (SSF) solar dynamic (SD) power systems. Such SD systems may be used in future growth SSF configurations. Two solar dynamic options are considered in this paper: Brayton and Rankine. Model elements consist of a single node receiver and concentrator, and takes into account overall heat engine efficiency and power distribution characteristics. The simulation not only computes the energy stored in the receiver phase change material (PCM), but also the amount of the PCM required for various combinations of load demands and power system mission constraints. For a solar dynamic power system in low earth orbit, the amount of stored PCM energy is calculated by balancing the solar energy input and the energy consumed by the loads corrected by an overall system efficiency. The model assumes an average 75 kW SD power system load profile which is connected to user loads via dedicated power distribution channels. The model then calculates the stored energy in the receiver and subsequently estimates the quantity of PCM necessary to meet peaking and contingency requirements. The model can also be used to conduct trade studies on the performance of SD power systems using different storage materials.

Effects of the distribution density of a biomass combined heat and power plant network on heat utilisation efficiency in village-town systems.

PubMed

Zhang, Yifei; Kang, Jian

2017-11-01

The building of biomass combined heat and power (CHP) plants is an effective means of developing biomass energy because they can satisfy demands for winter heating and electricity consumption. The purpose of this study was to analyse the effect of the distribution density of a biomass CHP plant network on heat utilisation efficiency in a village-town system. The distribution density is determined based on the heat transmission threshold, and the heat utilisation efficiency is determined based on the heat demand distribution, heat output efficiency, and heat transmission loss. The objective of this study was to ascertain the optimal value for the heat transmission threshold using a multi-scheme comparison based on an analysis of these factors. To this end, a model of a biomass CHP plant network was built using geographic information system tools to simulate and generate three planning schemes with different heat transmission thresholds (6, 8, and 10 km) according to the heat demand distribution. The heat utilisation efficiencies of these planning schemes were then compared by calculating the gross power, heat output efficiency, and heat transmission loss of the biomass CHP plant for each scenario. This multi-scheme comparison yielded the following results: when the heat transmission threshold was low, the distribution density of the biomass CHP plant network was high and the biomass CHP plants tended to be relatively small. In contrast, when the heat transmission threshold was high, the distribution density of the network was low and the biomass CHP plants tended to be relatively large. When the heat transmission threshold was 8 km, the distribution density of the biomass CHP plant network was optimised for efficient heat utilisation. To promote the development of renewable energy sources, a planning scheme for a biomass CHP plant network that maximises heat utilisation efficiency can be obtained using the optimal heat transmission threshold and the nonlinearity coefficient for local roads. Copyright © 2017 Elsevier Ltd. All rights reserved.

Stability assessment of a multi-port power electronic interface for hybrid micro-grid applications

NASA Astrophysics Data System (ADS)

Shamsi, Pourya

Migration to an industrial society increases the demand for electrical energy. Meanwhile, social causes for preserving the environment and reducing pollutions seek cleaner forms of energy sources. Therefore, there has been a growth in distributed generation from renewable sources in the past decade. Existing regulations and power system coordination does not allow for massive integration of distributed generation throughout the grid. Moreover, the current infrastructures are not designed for interfacing distributed and deregulated generation. In order to remedy this problem, a hybrid micro-grid based on nano-grids is introduced. This system consists of a reliable micro-grid structure that provides a smooth transition from the current distribution networks to smart micro-grid systems. Multi-port power electronic interfaces are introduced to manage the local generation, storage, and consumption. Afterwards, a model for this micro-grid is derived. Using this model, the stability of the system under a variety of source and load induced disturbances is studied. Moreover, pole-zero study of the micro-grid is performed under various loading conditions. An experimental setup of this micro-grid is developed, and the validity of the model in emulating the dynamic behavior of the system is verified. This study provides a theory for a novel hybrid micro-grid as well as models for stability assessment of the proposed micro-grid.

The long-term demographic role of community-based family planning in rural Bangladesh.

PubMed

Phillips, J F; Hossain, M B; Arends-Kuenning, M

1996-01-01

Experimental studies demonstrating the effectiveness of nonclinical distribution of contraceptives are typically conducted in settings where contraceptive use is low and unmet need is extensive. Determining the long-term role of active outreach programs after initial demand is met represents an increasingly important policy issue in Asia, where contraceptive prevalence is high and fixed service points are conveniently available. This article examines the long-term rationale for household family planning in Bangladesh-where growing use of contraceptives, rapid fertility decline, and normative change in reproductive preferences are in progress, bringing into question the rationale for large-scale deployment of paid outreach workers. Longitudinal data are analyzed that record outreach encounters and contraceptive use dynamics in a large rural population. Findings demonstrate that outreach has a continuing impact on program effectiveness, even after a decade of household visitation. The policy implications of this finding are reviewed.

Using machine learning and real-time workload assessment in a high-fidelity UAV simulation environment

NASA Astrophysics Data System (ADS)

Monfort, Samuel S.; Sibley, Ciara M.; Coyne, Joseph T.

2016-05-01

Future unmanned vehicle operations will see more responsibilities distributed among fewer pilots. Current systems typically involve a small team of operators maintaining control over a single aerial platform, but this arrangement results in a suboptimal configuration of operator resources to system demands. Rather than devoting the full-time attention of several operators to a single UAV, the goal should be to distribute the attention of several operators across several UAVs as needed. Under a distributed-responsibility system, operator task load would be continuously monitored, with new tasks assigned based on system needs and operator capabilities. The current paper sought to identify a set of metrics that could be used to assess workload unobtrusively and in near real-time to inform a dynamic tasking algorithm. To this end, we put 20 participants through a variable-difficulty multiple UAV management simulation. We identified a subset of candidate metrics from a larger pool of pupillary and behavioral measures. We then used these metrics as features in a machine learning algorithm to predict workload condition every 60 seconds. This procedure produced an overall classification accuracy of 78%. An automated tasker sensitive to fluctuations in operator workload could be used to efficiently delegate tasks for teams of UAV operators.

Molecular dynamics studies of water deposition on hematite surfaces

NASA Astrophysics Data System (ADS)

Kvamme, Bjørn; Kuznetsova, Tatiana; Haynes, Martin

2012-12-01

The interest in carbon dioxide for enhanced oil recovery is increasing proportional to the decrease in naturally driven oil production and also due to the increasing demand for reduced emission of carbon dioxide to the atmosphere. Transport of carbon dioxide in offshore pipelines involves high pressure and low temperatures which may lead to the formation of hydrate between residual water dissolved in carbon dioxide. The critical question is whether the water at some condition of temperature and pressure will drop out as liquid droplets or as water adsorbed on the surfaces of the pipeline and then subsequently form hydrates heterogeneously. In this work we have used the 6-311G basis set with B3LYP to estimate the charge distribution of different sizes of hematite crystals. The obtained surface charge distribution were kept unchanged while the inner charge distribution where scaled so as to result in an overall neutral crystal. These rust particles were embedded in water and chemical potential for adsorbed water molecules were estimated through thermodynamic integration and compared to similar estimates for same size water cluster. Estimated values of water chemical potentials indicate that it is thermodynamically favorable for water to adsorb on hematite, and that evaluation of potential carbon dioxide hydrate formation conditions and kinetics should be based this sequence of processes.

Dynamical complexity changes during two forms of meditation

NASA Astrophysics Data System (ADS)

Li, Jin; Hu, Jing; Zhang, Yinhong; Zhang, Xiaofeng

2011-06-01

Detection of dynamical complexity changes in natural and man-made systems has deep scientific and practical meaning. We use the base-scale entropy method to analyze dynamical complexity changes for heart rate variability (HRV) series during specific traditional forms of Chinese Chi and Kundalini Yoga meditation techniques in healthy young adults. The results show that dynamical complexity decreases in meditation states for two forms of meditation. Meanwhile, we detected changes in probability distribution of m-words during meditation and explained this changes using probability distribution of sine function. The base-scale entropy method may be used on a wider range of physiologic signals.

Compensatory strategies during manual wheelchair propulsion in response to weakness in individual muscle groups: A simulation study.

PubMed

Slowik, Jonathan S; McNitt-Gray, Jill L; Requejo, Philip S; Mulroy, Sara J; Neptune, Richard R

2016-03-01

The considerable physical demand placed on the upper extremity during manual wheelchair propulsion is distributed among individual muscles. The strategy used to distribute the workload is likely influenced by the relative force-generating capacities of individual muscles, and some strategies may be associated with a higher injury risk than others. The objective of this study was to use forward dynamics simulations of manual wheelchair propulsion to identify compensatory strategies that can be used to overcome weakness in individual muscle groups and identify specific strategies that may increase injury risk. Identifying these strategies can provide rationale for the design of targeted rehabilitation programs aimed at preventing the development of pain and injury in manual wheelchair users. Muscle-actuated forward dynamics simulations of manual wheelchair propulsion were analyzed to identify compensatory strategies in response to individual muscle group weakness using individual muscle mechanical power and stress as measures of upper extremity demand. The simulation analyses found the upper extremity to be robust to weakness in any single muscle group as the remaining groups were able to compensate and restore normal propulsion mechanics. The rotator cuff muscles experienced relatively high muscle stress levels and exhibited compensatory relationships with the deltoid muscles. These results underline the importance of strengthening the rotator cuff muscles and supporting muscles whose contributions do not increase the potential for impingement (i.e., the thoracohumeral depressors) and minimize the risk of upper extremity injury in manual wheelchair users. Copyright © 2016 Elsevier Ltd. All rights reserved.

Compensatory Strategies during Manual Wheelchair Propulsion in Response to Weakness in Individual Muscle Groups: A Simulation Study

PubMed Central

Slowik, Jonathan S.; McNitt-Gray, Jill L.; Requejo, Philip S.; Mulroy, Sara J.; Neptune, Richard R.

2016-01-01

Background The considerable physical demand placed on the upper extremity during manual wheelchair propulsion is distributed among the individual muscles. The strategy used to distribute the workload is likely influenced by the relative force-generating capacities of individual muscles, and some strategies may be associated with a higher injury risk than others. The objective of this study was to use forward dynamics simulations of manual wheelchair propulsion to identify compensatory strategies that can be used to overcome weakness in individual muscle groups and identify specific strategies that may increase injury risk. Identifying these strategies can provide rationale for the design of targeted rehabilitation programs aimed at preventing the development of pain and injury in manual wheelchair users. Methods Muscle-actuated forward dynamics simulations of manual wheelchair propulsion were analyzed to identify compensatory strategies in response to individual muscle group weakness, using individual muscle mechanical power and stress as measures of upper extremity demand. Findings The simulation analyses found the upper extremity to be robust to weakness in any single muscle group as the remaining groups were able to compensate and restore normal propulsion mechanics. The rotator cuff muscles experienced relatively high muscle stress levels and exhibited compensatory relationships with the deltoid muscles. Interpretation These results underline the importance of strengthening the rotator cuff muscles and supporting muscles whose contributions do not increase the potential for impingement (i.e., the thoracohumeral depressors) and minimize the risk of upper extremity injury in manual wheelchair users. PMID:26945719

Communication Simulations for Power System Applications

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

Fuller, Jason C.; Ciraci, Selim; Daily, Jeffrey A.

2013-05-29

New smart grid technologies and concepts, such as dynamic pricing, demand response, dynamic state estimation, and wide area monitoring, protection, and control, are expected to require considerable communication resources. As the cost of retrofit can be high, future power grids will require the integration of high-speed, secure connections with legacy communication systems, while still providing adequate system control and security. While considerable work has been performed to create co-simulators for the power domain with load models and market operations, limited work has been performed in integrating communications directly into a power domain solver. The simulation of communication and power systemsmore » will become more important as the two systems become more inter-related. This paper will discuss ongoing work at Pacific Northwest National Laboratory to create a flexible, high-speed power and communication system co-simulator for smart grid applications. The framework for the software will be described, including architecture considerations for modular, high performance computing and large-scale scalability (serialization, load balancing, partitioning, cross-platform support, etc.). The current simulator supports the ns-3 (telecommunications) and GridLAB-D (distribution systems) simulators. Ongoing and future work will be described, including planned future expansions for a traditional transmission solver. A test case using the co-simulator, utilizing a transactive demand response system created for the Olympic Peninsula and AEP gridSMART demonstrations, requiring two-way communication between distributed and centralized market devices, will be used to demonstrate the value and intended purpose of the co-simulation environment.« less

Towards an explanation of orbits in the extreme trans-Neptunian region: The effect of Milgromian dynamics

NASA Astrophysics Data System (ADS)

Paučo, R.

2017-06-01

Context. Milgromian dynamics (MD or MOND) uniquely predicts motion in a galaxy from the distribution of its stars and gas in a remarkable agreement with observations so far. In the solar system, MD predicts the existence of some possibly non-negligible dynamical effects, which can be used to constrain the freedom in MD theories. Known extreme trans-Neptunian objects (ETNOs) have their argument of perihelion, longitude of ascending node, and inclination distributed in highly non-uniform fashion; ETNOs are bodies with perihelion distances greater than the orbit of Neptune and with semimajor axes greater than 150 au and less than 1500 au. It is as if these bodies have been systematically perturbed by some external force. Aims: We investigated a hypothesis that the puzzling orbital characteristics of ETNOs are a consequence of MD. Methods: We set up a dynamical model of the solar system incorporating the external field effect (EFE), which is anticipated to be the dominant effect of MD in the ETNOs region. We used constraints available on the strength of EFE coming from radio tracking of the Cassini spacecraft. We performed several numerical experiments, concentrating on the long-term orbital evolution of primordial (randomised) ETNOs in MD. Results: The EFE could produce distinct non-uniform distributions of the orbital elements of ETNOs that are related to the orientation of an orbit in space. If we demand that EFE is solely responsible for the detachment of Sedna and 2012 VP113, then these distributions are at odds with the currently observed statistics on ETNOs unless the EFE quadrupole strength parameter Q2 has values that are unlikely (with probability <1%) in light of the Cassini data.

Residential Consumption Scheduling Based on Dynamic User Profiling

NASA Astrophysics Data System (ADS)

Mangiatordi, Federica; Pallotti, Emiliano; Del Vecchio, Paolo; Capodiferro, Licia

Deployment of household appliances and of electric vehicles raises the electricity demand in the residential areas and the impact of the building's electrical power. The variations of electricity consumption across the day, may affect both the design of the electrical generation facilities and the electricity bill, mainly when a dynamic pricing is applied. This paper focuses on an energy management system able to control the day-ahead electricity demand in a residential area, taking into account both the variability of the energy production costs and the profiling of the users. The user's behavior is dynamically profiled on the basis of the tasks performed during the previous days and of the tasks foreseen for the current day. Depending on the size and on the flexibility in time of the user tasks, home inhabitants are grouped in, one over N, energy profiles, using a k-means algorithm. For a fixed energy generation cost, each energy profile is associated to a different hourly energy cost. The goal is to identify any bad user profile and to make it pay a highest bill. A bad profile example is when a user applies a lot of consumption tasks and low flexibility in task reallocation time. The proposed energy management system automatically schedules the tasks, solving a multi-objective optimization problem based on an MPSO strategy. The goals, when identifying bad users profiles, are to reduce the peak to average ratio in energy demand, and to minimize the energy costs, promoting virtuous behaviors.

NREL Supports Effort to Take Distributed Photovoltaics to Developing

Science.gov Websites

Photovoltaics to Developing Countries NREL Supports Effort to Take Distributed Photovoltaics to Developing project based not only on its demand for renewable energy but also on its need. Pilot projects are adding renewable energy to the grid. Also many developing countries have signed on to the Paris climate

The production of information in the attention economy

PubMed Central

Ciampaglia, Giovanni Luca; Flammini, Alessandro; Menczer, Filippo

2015-01-01

Online traces of human activity offer novel opportunities to study the dynamics of complex knowledge exchange networks, in particular how emergent patterns of collective attention determine what new information is generated and consumed. Can we measure the relationship between demand and supply for new information about a topic? We propose a normalization method to compare attention bursts statistics across topics with heterogeneous distribution of attention. Through analysis of a massive dataset on traffic to Wikipedia, we find that the production of new knowledge is associated to significant shifts of collective attention, which we take as proxy for its demand. This is consistent with a scenario in which allocation of attention toward a topic stimulates the demand for information about it, and in turn the supply of further novel information. However, attention spikes only for a limited time span, during which new content has higher chances of receiving traffic, compared to content created later or earlier on. Our attempt to quantify demand and supply of information, and our finding about their temporal ordering, may lead to the development of the fundamental laws of the attention economy, and to a better understanding of social exchange of knowledge information networks. PMID:25989177

Decentral Smart Grid Control

NASA Astrophysics Data System (ADS)

Schäfer, Benjamin; Matthiae, Moritz; Timme, Marc; Witthaut, Dirk

2015-01-01

Stable operation of complex flow and transportation networks requires balanced supply and demand. For the operation of electric power grids—due to their increasing fraction of renewable energy sources—a pressing challenge is to fit the fluctuations in decentralized supply to the distributed and temporally varying demands. To achieve this goal, common smart grid concepts suggest to collect consumer demand data, centrally evaluate them given current supply and send price information back to customers for them to decide about usage. Besides restrictions regarding cyber security, privacy protection and large required investments, it remains unclear how such central smart grid options guarantee overall stability. Here we propose a Decentral Smart Grid Control, where the price is directly linked to the local grid frequency at each customer. The grid frequency provides all necessary information about the current power balance such that it is sufficient to match supply and demand without the need for a centralized IT infrastructure. We analyze the performance and the dynamical stability of the power grid with such a control system. Our results suggest that the proposed Decentral Smart Grid Control is feasible independent of effective measurement delays, if frequencies are averaged over sufficiently large time intervals.

Energy Management Policies in Distributed Residential Energy Systems

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

Duan, Sisi; Sun, Jingtao

2016-01-01

In this paper, we study energy management problems in communities with several neighborhood-level Residential Energy Systems (RESs). We consider control problems from both community level and residential level to handle external changes such as restriction on peak demand and restriction on the total demand from the electricity grid. We propose three policies to handle the problems at community level. Based on the collected data from RESs such as predicted energy load, the community controller analyzes the policies, distribute the results to the RES, and each RES can then control and schedule its own energy load based on different coordination functions.more » We utilize a framework to integrate both policy analysis and coordination of functions. With the use of our approach, we show that the policies are useful to resolve the challenges of energy management under external changes.« less

Multivariable Hermite polynomials and phase-space dynamics

NASA Technical Reports Server (NTRS)

Dattoli, G.; Torre, Amalia; Lorenzutta, S.; Maino, G.; Chiccoli, C.

1994-01-01

The phase-space approach to classical and quantum systems demands for advanced analytical tools. Such an approach characterizes the evolution of a physical system through a set of variables, reducing to the canonically conjugate variables in the classical limit. It often happens that phase-space distributions can be written in terms of quadratic forms involving the above quoted variables. A significant analytical tool to treat these problems may come from the generalized many-variables Hermite polynomials, defined on quadratic forms in R(exp n). They form an orthonormal system in many dimensions and seem the natural tool to treat the harmonic oscillator dynamics in phase-space. In this contribution we discuss the properties of these polynomials and present some applications to physical problems.

Bio-Inspired Neural Model for Learning Dynamic Models

NASA Technical Reports Server (NTRS)

Duong, Tuan; Duong, Vu; Suri, Ronald

2009-01-01

A neural-network mathematical model that, relative to prior such models, places greater emphasis on some of the temporal aspects of real neural physical processes, has been proposed as a basis for massively parallel, distributed algorithms that learn dynamic models of possibly complex external processes by means of learning rules that are local in space and time. The algorithms could be made to perform such functions as recognition and prediction of words in speech and of objects depicted in video images. The approach embodied in this model is said to be "hardware-friendly" in the following sense: The algorithms would be amenable to execution by special-purpose computers implemented as very-large-scale integrated (VLSI) circuits that would operate at relatively high speeds and low power demands.

Dynamics of a durable commodity market involving trade at disequilibrium

NASA Astrophysics Data System (ADS)

Panchuk, A.; Puu, T.

2018-05-01

The present work considers a simple model of a durable commodity market involving two agents who trade stocks of two different types. Stock commodities, in contrast to flow commodities, remain on the market from period to period and, consequently, there is neither unique demand function nor unique supply function exists. We also set up exact conditions for trade at disequilibrium, the issue being usually neglected, though a fact of reality. The induced iterative system has infinite number of fixed points and path dependent dynamics. We show that a typical orbit is either attracted to one of the fixed points or eventually sticks at a no-trade point. For the latter the stock distribution always remains the same while the price displays periodic or chaotic oscillations.

Distributed Earth observation data integration and on-demand services based on a collaborative framework of geospatial data service gateway

NASA Astrophysics Data System (ADS)

Xie, Jibo; Li, Guoqing

2015-04-01

Earth observation (EO) data obtained by air-borne or space-borne sensors has the characteristics of heterogeneity and geographical distribution of storage. These data sources belong to different organizations or agencies whose data management and storage methods are quite different and geographically distributed. Different data sources provide different data publish platforms or portals. With more Remote sensing sensors used for Earth Observation (EO) missions, different space agencies have distributed archived massive EO data. The distribution of EO data archives and system heterogeneity makes it difficult to efficiently use geospatial data for many EO applications, such as hazard mitigation. To solve the interoperable problems of different EO data systems, an advanced architecture of distributed geospatial data infrastructure is introduced to solve the complexity of distributed and heterogeneous EO data integration and on-demand processing in this paper. The concept and architecture of geospatial data service gateway (GDSG) is proposed to build connection with heterogeneous EO data sources by which EO data can be retrieved and accessed with unified interfaces. The GDSG consists of a set of tools and service to encapsulate heterogeneous geospatial data sources into homogenous service modules. The GDSG modules includes EO metadata harvesters and translators, adaptors to different type of data system, unified data query and access interfaces, EO data cache management, and gateway GUI, etc. The GDSG framework is used to implement interoperability and synchronization between distributed EO data sources with heterogeneous architecture. An on-demand distributed EO data platform is developed to validate the GDSG architecture and implementation techniques. Several distributed EO data achieves are used for test. Flood and earthquake serves as two scenarios for the use cases of distributed EO data integration and interoperability.

Entraining the topology and the dynamics of a network of phase oscillators

NASA Astrophysics Data System (ADS)

Sendiña-Nadal, I.; Leyva, I.; Buldú, J. M.; Almendral, J. A.; Boccaletti, S.

2009-04-01

We show that the topology and dynamics of a network of unsynchronized Kuramoto oscillators can be simultaneously controlled by means of a forcing mechanism which yields a phase locking of the oscillators to that of an external pacemaker in connection with the reshaping of the network’s degree distribution. The entrainment mechanism is based on the addition, at regular time intervals, of unidirectional links from oscillators that follow the dynamics of a pacemaker to oscillators in the pristine graph whose phases hold a prescribed phase relationship. Such a dynamically based rule in the attachment process leads to the emergence of a power-law shape in the final degree distribution of the graph whenever the network is entrained to the dynamics of the pacemaker. We show that the arousal of a scale-free distribution in connection with the success of the entrainment process is a robust feature, characterizing different networks’ initial configurations and parameters.

Dynamic analysis of combined photovoltaic source and synchronous generator connected to power grid

NASA Astrophysics Data System (ADS)

Mahabal, Divya

In the world of expanding economy and technology, the energy demand is likely to increase even with the global efforts of saving and increasing energy efficiency. Higher oil prices, effects of greenhouse gases, and concerns over other environmental impacts gave way to Distributed Generation (DG). With adequate awareness and support, DG's can meet these rising energy demands at lower prices compared to conventional methods. Extensive research is taking place in different areas like fuel cells, photovoltaic cells, wind turbines, and gas turbines. DG's when connected to a grid increase the overall efficiency of the power grid. It is believed that three-fifth of the world's electricity would account for renewable energy by middle of 21st century. This thesis presents the dynamic analysis of a grid connected photovoltaic (PV) system and synchronous generator. A grid is considered as an infinite bus. The photovol-taic system and synchronous generator act as small scale distributed energy resources. The output of the photovoltaic system depends on the light intensity, temperature, and irradiance levels of sun. The maximum power point tracking and DC/AC converter are also modeled for the photovoltaic system. The PV system is connected to the grid through DC/AC system. Different combinations of PV and synchronous generator are modeled with the grid to study the dynamics of the proposed system. The dynamics of the test system is analyzed by subjecting the system to several disturbances under various conditions. All modules are individually modeled and con-nected using MATLAB/Simulink software package. Results from the study show that, as the penetration of renewable energy sources like PV increases into the power system, the dynamics of the system becomes faster. When considering cases such as load switching, PV cannot deliver more power as the performance of PV depends on environmental conditions. Synchronous generator in power system can produce the required amount of power. As the main aim of this research is to use renewable sources like PV in the system, it is advantageous to use a combination of both PV and synchronous generator in the system.

Forecasting the regional distribution and sufficiency of physicians in Japan with a coupled system dynamics-geographic information system model.

PubMed

Ishikawa, Tomoki; Fujiwara, Kensuke; Ohba, Hisateru; Suzuki, Teppei; Ogasawara, Katsuhiko

2017-09-12

In Japan, the shortage of physicians has been recognized as a major medical issue. In our previous study, we reported that the absolute shortage will be resolved in the long term, but maldistribution among specialties will persist. To address regional shortage, several Japanese medical schools increased existing quota and established "regional quotas." This study aims to assist policy makers in designing effective policies; we built a model for forecasting physician numbers by region to evaluate future physician supply-demand balances. For our case study, we selected Hokkaido Prefecture in Japan, a region displaying disparities in healthcare services availability between urban and rural areas. We combined a system dynamics (SD) model with geographic information system (GIS) technology to analyze the dynamic change in spatial distribution of indicators. For Hokkaido overall and for each secondary medical service area (SMSA) within the prefecture, we analyzed the total number of practicing physicians. For evaluating absolute shortage and maldistribution, we calculated sufficiency levels and Gini coefficient. Our study covered the period 2010-2030 in 5-year increments. According to our forecast, physician shortage in Hokkaido Prefecture will largely be resolved by 2020. Based on current policies, we forecast that four SMSAs in Hokkaido will continue to experience physician shortages past that date, but only one SMSA would still be understaffed in 2030. The results show the possibility that diminishing imbalances between SMSAs would not necessarily mean that regional maldistribution would be eliminated, as seen from the sufficiency levels of the various SMSAs. Urgent steps should be taken to place doctors in areas where our forecasting model predicts that physician shortages could occur in the future.

Static and dynamic crystalline lens accommodation evaluated using quantitative 3-D OCT.

PubMed

Gambra, Enrique; Ortiz, Sergio; Perez-Merino, Pablo; Gora, Michalina; Wojtkowski, Maciej; Marcos, Susana

2013-01-01

Custom high-resolution high-speed anterior segment spectral domain Optical Coherence Tomography (OCT) provided with automatic quantification and distortion correction algorithms was used to characterize three-dimensionally (3-D) the human crystalline lens in vivo in four subjects, for accommodative demands between 0 to 6 D in 1 D steps. Anterior and posterior lens radii of curvature decreased with accommodative demand at rates of 0.73 and 0.20 mm/D, resulting in an increase of the estimated optical power of the eye of 0.62 D per diopter of accommodative demand. Dynamic fluctuations in crystalline lens radii of curvature, anterior chamber depth and lens thickness were also estimated from dynamic 2-D OCT images (14 Hz), acquired during 5-s of steady fixation, for different accommodative demands. Estimates of the eye power from dynamical geometrical measurements revealed an increase of the fluctuations of the accommodative response from 0.07 D to 0.47 D between 0 and 6 D (0.044 D per D of accommodative demand). A sensitivity analysis showed that the fluctuations of accommodation were driven by dynamic changes in the lens surfaces, particularly in the posterior lens surface.

Static and dynamic crystalline lens accommodation evaluated using quantitative 3-D OCT

PubMed Central

Gambra, Enrique; Ortiz, Sergio; Perez-Merino, Pablo; Gora, Michalina; Wojtkowski, Maciej; Marcos, Susana

2013-01-01

Custom high-resolution high-speed anterior segment spectral domain Optical Coherence Tomography (OCT) provided with automatic quantification and distortion correction algorithms was used to characterize three-dimensionally (3-D) the human crystalline lens in vivo in four subjects, for accommodative demands between 0 to 6 D in 1 D steps. Anterior and posterior lens radii of curvature decreased with accommodative demand at rates of 0.73 and 0.20 mm/D, resulting in an increase of the estimated optical power of the eye of 0.62 D per diopter of accommodative demand. Dynamic fluctuations in crystalline lens radii of curvature, anterior chamber depth and lens thickness were also estimated from dynamic 2-D OCT images (14 Hz), acquired during 5-s of steady fixation, for different accommodative demands. Estimates of the eye power from dynamical geometrical measurements revealed an increase of the fluctuations of the accommodative response from 0.07 D to 0.47 D between 0 and 6 D (0.044 D per D of accommodative demand). A sensitivity analysis showed that the fluctuations of accommodation were driven by dynamic changes in the lens surfaces, particularly in the posterior lens surface. PMID:24049680

Customer premises services market demand assessment 1980 - 2000: Volume 2

NASA Technical Reports Server (NTRS)

Gamble, R. B.; Saporta, L.; Heidenrich, G. A.

1983-01-01

Potential customer premises service (CPS), telecommunication services, potential CPS user classes, a primary research survey, comparative economics, market demand forcasts, distance distribution of traffic, segmentation of market demand, and a nationwide traffic distribution model are discussed.

Development of a Dynamic Traffic Assignment Model for Northern Nevada

DOT National Transportation Integrated Search

2014-06-01

The objective of this research is to build and calibrate a DTA model for Northern Nevada (RenoSparks Area) based on the network profile and travel demand information updated to date. The critical procedures include development of consistent and readi...

A distributed algorithm for demand-side management: Selling back to the grid.

PubMed

Latifi, Milad; Khalili, Azam; Rastegarnia, Amir; Zandi, Sajad; Bazzi, Wael M

2017-11-01

Demand side energy consumption scheduling is a well-known issue in the smart grid research area. However, there is lack of a comprehensive method to manage the demand side and consumer behavior in order to obtain an optimum solution. The method needs to address several aspects, including the scale-free requirement and distributed nature of the problem, consideration of renewable resources, allowing consumers to sell electricity back to the main grid, and adaptivity to a local change in the solution point. In addition, the model should allow compensation to consumers and ensurance of certain satisfaction levels. To tackle these issues, this paper proposes a novel autonomous demand side management technique which minimizes consumer utility costs and maximizes consumer comfort levels in a fully distributed manner. The technique uses a new logarithmic cost function and allows consumers to sell excess electricity (e.g. from renewable resources) back to the grid in order to reduce their electric utility bill. To develop the proposed scheme, we first formulate the problem as a constrained convex minimization problem. Then, it is converted to an unconstrained version using the segmentation-based penalty method. At each consumer location, we deploy an adaptive diffusion approach to obtain the solution in a distributed fashion. The use of adaptive diffusion makes it possible for consumers to find the optimum energy consumption schedule with a small number of information exchanges. Moreover, the proposed method is able to track drifts resulting from changes in the price parameters and consumer preferences. Simulations and numerical results show that our framework can reduce the total load demand peaks, lower the consumer utility bill, and improve the consumer comfort level.

Packet-aware transport for video distribution [Invited

NASA Astrophysics Data System (ADS)

Aguirre-Torres, Luis; Rosenfeld, Gady; Bruckman, Leon; O'Connor, Mannix

2006-05-01

We describe a solution based on resilient packet rings (RPR) for the distribution of broadcast video and video-on-demand (VoD) content over a packet-aware transport network. The proposed solution is based on our experience in the design and deployment of nationwide Triple Play networks and relies on technologies such as RPR, multiprotocol label switching (MPLS), and virtual private LAN service (VPLS) to provide the most efficient solution in terms of utilization, scalability, and availability.

Prediction-based manufacturing center self-adaptive demand side energy optimization in cyber physical systems

NASA Astrophysics Data System (ADS)

Sun, Xinyao; Wang, Xue; Wu, Jiangwei; Liu, Youda

2014-05-01

Cyber physical systems(CPS) recently emerge as a new technology which can provide promising approaches to demand side management(DSM), an important capability in industrial power systems. Meanwhile, the manufacturing center is a typical industrial power subsystem with dozens of high energy consumption devices which have complex physical dynamics. DSM, integrated with CPS, is an effective methodology for solving energy optimization problems in manufacturing center. This paper presents a prediction-based manufacturing center self-adaptive energy optimization method for demand side management in cyber physical systems. To gain prior knowledge of DSM operating results, a sparse Bayesian learning based componential forecasting method is introduced to predict 24-hour electric load levels for specific industrial areas in China. From this data, a pricing strategy is designed based on short-term load forecasting results. To minimize total energy costs while guaranteeing manufacturing center service quality, an adaptive demand side energy optimization algorithm is presented. The proposed scheme is tested in a machining center energy optimization experiment. An AMI sensing system is then used to measure the demand side energy consumption of the manufacturing center. Based on the data collected from the sensing system, the load prediction-based energy optimization scheme is implemented. By employing both the PSO and the CPSO method, the problem of DSM in the manufacturing center is solved. The results of the experiment show the self-adaptive CPSO energy optimization method enhances optimization by 5% compared with the traditional PSO optimization method.

Mesoscale energy deposition footprint model for kiloelectronvolt cluster bombardment of solids.

PubMed

Russo, Michael F; Garrison, Barbara J

2006-10-15

Molecular dynamics simulations have been performed to model 5-keV C60 and Au3 projectile bombardment of an amorphous water substrate. The goal is to obtain detailed insights into the dynamics of motion in order to develop a straightforward and less computationally demanding model of the process of ejection. The molecular dynamics results provide the basis for the mesoscale energy deposition footprint model. This model provides a method for predicting relative yields based on information from less than 1 ps of simulation time.

Ecohydrological optimality in the Northeast China Transect

NASA Astrophysics Data System (ADS)

Cong, Zhentao; Li, Qinshu; Mo, Kangle; Zhang, Lexin; Shen, Hong

2017-05-01

The Northeast China Transect (NECT) is one of the International Geosphere-Biosphere Program (IGBP) terrestrial transects, where there is a significant precipitation gradient from east to west, as well as a vegetation transition of forest-grassland-desert. It is remarkable to understand vegetation distribution and dynamics under climate change in this transect. We take canopy cover (M), derived from Normalized Difference Vegetation Index (NDVI), as an index to describe the properties of vegetation distribution and dynamics in the NECT. In Eagleson's ecohydrological optimality theory, the optimal canopy cover (M*) is determined by the trade-off between water supply depending on water balance and water demand depending on canopy transpiration. We apply Eagleson's ecohydrological optimality method in the NECT based on data from 2000 to 2013 to get M*, which is compared with M from NDVI to further discuss the sensitivity of M* to vegetation properties and climate factors. The result indicates that the average M* fits the actual M well (for forest, M* = 0.822 while M = 0.826; for grassland, M* = 0.353 while M = 0.352; the correlation coefficient between M and M* is 0.81). Results of water balance also match the field-measured data in the references. The sensitivity analyses show that M* decreases with the increase of leaf area index (LAI), stem fraction and temperature, while it increases with the increase of leaf angle and precipitation amount. Eagleson's ecohydrological optimality method offers a quantitative way to understand the impacts of climate change on canopy cover and provides guidelines for ecorestoration projects.

A multi-criteria decision aid methodology to design electric vehicles public charging networks

NASA Astrophysics Data System (ADS)

Raposo, João; Rodrigues, Ana; Silva, Carlos; Dentinho, Tomaz

2015-05-01

This article presents a new multi-criteria decision aid methodology, dynamic-PROMETHEE, here used to design electric vehicle charging networks. In applying this methodology to a Portuguese city, results suggest that it is effective in designing electric vehicle charging networks, generating time and policy based scenarios, considering offer and demand and the city's urban structure. Dynamic-PROMETHE adds to the already known PROMETHEE's characteristics other useful features, such as decision memory over time, versatility and adaptability. The case study, used here to present the dynamic-PROMETHEE, served as inspiration and base to create this new methodology. It can be used to model different problems and scenarios that may present similar requirement characteristics.

Real-Time Load-Side Control of Electric Power Systems

NASA Astrophysics Data System (ADS)

Zhao, Changhong

Two trends are emerging from modern electric power systems: the growth of renewable (e.g., solar and wind) generation, and the integration of information technologies and advanced power electronics. The former introduces large, rapid, and random fluctuations in power supply, demand, frequency, and voltage, which become a major challenge for real-time operation of power systems. The latter creates a tremendous number of controllable intelligent endpoints such as smart buildings and appliances, electric vehicles, energy storage devices, and power electronic devices that can sense, compute, communicate, and actuate. Most of these endpoints are distributed on the load side of power systems, in contrast to traditional control resources such as centralized bulk generators. This thesis focuses on controlling power systems in real time, using these load side resources. Specifically, it studies two problems. (1) Distributed load-side frequency control: We establish a mathematical framework to design distributed frequency control algorithms for flexible electric loads. In this framework, we formulate a category of optimization problems, called optimal load control (OLC), to incorporate the goals of frequency control, such as balancing power supply and demand, restoring frequency to its nominal value, restoring inter-area power flows, etc., in a way that minimizes total disutility for the loads to participate in frequency control by deviating from their nominal power usage. By exploiting distributed algorithms to solve OLC and analyzing convergence of these algorithms, we design distributed load-side controllers and prove stability of closed-loop power systems governed by these controllers. This general framework is adapted and applied to different types of power systems described by different models, or to achieve different levels of control goals under different operation scenarios. We first consider a dynamically coherent power system which can be equivalently modeled with a single synchronous machine. We then extend our framework to a multi-machine power network, where we consider primary and secondary frequency controls, linear and nonlinear power flow models, and the interactions between generator dynamics and load control. (2) Two-timescale voltage control: The voltage of a power distribution system must be maintained closely around its nominal value in real time, even in the presence of highly volatile power supply or demand. For this purpose, we jointly control two types of reactive power sources: a capacitor operating at a slow timescale, and a power electronic device, such as a smart inverter or a D-STATCOM, operating at a fast timescale. Their control actions are solved from optimal power flow problems at two timescales. Specifically, the slow-timescale problem is a chance-constrained optimization, which minimizes power loss and regulates the voltage at the current time instant while limiting the probability of future voltage violations due to stochastic changes in power supply or demand. This control framework forms the basis of an optimal sizing problem, which determines the installation capacities of the control devices by minimizing the sum of power loss and capital cost. We develop computationally efficient heuristics to solve the optimal sizing problem and implement real-time control. Numerical experiments show that the proposed sizing and control schemes significantly improve the reliability of voltage control with a moderate increase in cost.

3VSR: Three Valued Secure Routing for Vehicular Ad Hoc Networks using Sensing Logic in Adversarial Environment

PubMed Central

Wang, Liangmin

2018-01-01

Today IoT integrate thousands of inter networks and sensing devices e.g., vehicular networks, which are considered to be challenging due to its high speed and network dynamics. The goal of future vehicular networks is to improve road safety, promote commercial or infotainment products and to reduce the traffic accidents. All these applications are based on the information exchange among nodes, so not only reliable data delivery but also the authenticity and credibility of the data itself are prerequisite. To cope with the aforementioned problem, trust management come up as promising candidate to conduct node’s transaction and interaction management, which requires distributed mobile nodes cooperation for achieving design goals. In this paper, we propose a trust-based routing protocol i.e., 3VSR (Three Valued Secure Routing), which extends the widely used AODV (Ad hoc On-demand Distance Vector) routing protocol and employs the idea of Sensing Logic-based trust model to enhance the security solution of VANET (Vehicular Ad-Hoc Network). The existing routing protocol are mostly based on key or signature-based schemes, which off course increases computation overhead. In our proposed 3VSR, trust among entities is updated frequently by means of opinion derived from sensing logic due to vehicles random topologies. In 3VSR the theoretical capabilities are based on Dirichlet distribution by considering prior and posterior uncertainty of the said event. Also by using trust recommendation message exchange, nodes are able to reduce computation and routing overhead. The simulated results shows that the proposed scheme is secure and practical. PMID:29538314

3VSR: Three Valued Secure Routing for Vehicular Ad Hoc Networks using Sensing Logic in Adversarial Environment.

PubMed

Sohail, Muhammad; Wang, Liangmin

2018-03-14

Today IoT integrate thousands of inter networks and sensing devices e.g., vehicular networks, which are considered to be challenging due to its high speed and network dynamics. The goal of future vehicular networks is to improve road safety, promote commercial or infotainment products and to reduce the traffic accidents. All these applications are based on the information exchange among nodes, so not only reliable data delivery but also the authenticity and credibility of the data itself are prerequisite. To cope with the aforementioned problem, trust management come up as promising candidate to conduct node's transaction and interaction management, which requires distributed mobile nodes cooperation for achieving design goals. In this paper, we propose a trust-based routing protocol i.e., 3VSR (Three Valued Secure Routing), which extends the widely used AODV (Ad hoc On-demand Distance Vector) routing protocol and employs the idea of Sensing Logic-based trust model to enhance the security solution of VANET (Vehicular Ad-Hoc Network). The existing routing protocol are mostly based on key or signature-based schemes, which off course increases computation overhead. In our proposed 3VSR, trust among entities is updated frequently by means of opinion derived from sensing logic due to vehicles random topologies. In 3VSR the theoretical capabilities are based on Dirichlet distribution by considering prior and posterior uncertainty of the said event. Also by using trust recommendation message exchange, nodes are able to reduce computation and routing overhead. The simulated results shows that the proposed scheme is secure and practical.

The dynamic simulation of the Progetto Energia combined cycle power plants

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

Giglio, R.; Cerabolini, M.; Pisacane, F.

1996-12-31

Over the next four years, the Progetto Energia project is building several cogeneration plants to satisfy the increasing demands of Italy`s industrial complex and the country`s demand for electrical power. Located at six different sites within Italy`s borders these Combined Cycle Cogeneration Plants will supply a total of 500 MW of electricity and 100 tons/hr of process steam to Italian industries and residences. To ensure project success, a dynamic model of the 50 MW base unit was developed. The goal established for the model was to predict the dynamic behavior of the complex thermodynamic system in order to assess equipmentmore » performance and control system effectiveness for normal operation and, more importantly, abrupt load changes. In addition to fulfilling its goals, the dynamic study guided modifications to controller logic that significantly improved steam drum pressure control and bypassed steam de-superheating performance. Simulations of normal and abrupt transient events allowed engineers to define optimum controller gain coefficients. The paper discusses the Combined Cycle plant configuration, its operating modes and control system, the dynamic model representation, the simulation results and project benefits.« less

Comparative empirical analysis of flow-weighted transit route networks in R-space and evolution modeling

NASA Astrophysics Data System (ADS)

Huang, Ailing; Zang, Guangzhi; He, Zhengbing; Guan, Wei

2017-05-01

Urban public transit system is a typical mixed complex network with dynamic flow, and its evolution should be a process coupling topological structure with flow dynamics, which has received little attention. This paper presents the R-space to make a comparative empirical analysis on Beijing’s flow-weighted transit route network (TRN) and we found that both the Beijing’s TRNs in the year of 2011 and 2015 exhibit the scale-free properties. As such, we propose an evolution model driven by flow to simulate the development of TRNs with consideration of the passengers’ dynamical behaviors triggered by topological change. The model simulates that the evolution of TRN is an iterative process. At each time step, a certain number of new routes are generated driven by travel demands, which leads to dynamical evolution of new routes’ flow and triggers perturbation in nearby routes that will further impact the next round of opening new routes. We present the theoretical analysis based on the mean-field theory, as well as the numerical simulation for this model. The results obtained agree well with our empirical analysis results, which indicate that our model can simulate the TRN evolution with scale-free properties for distributions of node’s strength and degree. The purpose of this paper is to illustrate the global evolutional mechanism of transit network that will be used to exploit planning and design strategies for real TRNs.

The impact of rainfall on the temporal and spatial distribution of taxi passengers

PubMed Central

Zhang, Yong; Gao, Liangpeng; Geng, Nana; Li, Xuefeng

2017-01-01

This paper focuses on the impact of rainfall on the temporal and spatial distribution of taxi passengers. The main objective is to provide guidance for taxi scheduling on rainy days. To this end, we take the occupied and empty states of taxis as units of analysis. By matching a taxi's GPS data to its taximeter data, we can obtain the taxi's operational time and the taxi driver's income from every unit of analysis. The ratio of taxi operation time to taxi drivers' income is used to measure the quality of taxi passengers. The research results show that the spatio-temporal evolution of urban taxi service demand differs based on rainfall conditions and hours of operation. During non-rush hours, taxi demand in peripheral areas is significantly reduced under increasing precipitation conditions, whereas during rush hours, the demand for highly profitable taxi services steadily increases. Thus, as an intelligent response for taxi operations and dispatching, taxi services should guide cruising taxis to high-demand regions to increase their service time and ride opportunities. PMID:28873430

Distributed Optimal Consensus Over Resource Allocation Network and Its Application to Dynamical Economic Dispatch.

PubMed

Li, Chaojie; Yu, Xinghuo; Huang, Tingwen; He, Xing; Chaojie Li; Xinghuo Yu; Tingwen Huang; Xing He; Li, Chaojie; Huang, Tingwen; He, Xing; Yu, Xinghuo

2018-06-01

The resource allocation problem is studied and reformulated by a distributed interior point method via a -logarithmic barrier. By the facilitation of the graph Laplacian, a fully distributed continuous-time multiagent system is developed for solving the problem. Specifically, to avoid high singularity of the -logarithmic barrier at boundary, an adaptive parameter switching strategy is introduced into this dynamical multiagent system. The convergence rate of the distributed algorithm is obtained. Moreover, a novel distributed primal-dual dynamical multiagent system is designed in a smart grid scenario to seek the saddle point of dynamical economic dispatch, which coincides with the optimal solution. The dual decomposition technique is applied to transform the optimization problem into easily solvable resource allocation subproblems with local inequality constraints. The good performance of the new dynamical systems is, respectively, verified by a numerical example and the IEEE six-bus test system-based simulations.

Automated Flight Routing Using Stochastic Dynamic Programming

NASA Technical Reports Server (NTRS)

Ng, Hok K.; Morando, Alex; Grabbe, Shon

2010-01-01

Airspace capacity reduction due to convective weather impedes air traffic flows and causes traffic congestion. This study presents an algorithm that reroutes flights in the presence of winds, enroute convective weather, and congested airspace based on stochastic dynamic programming. A stochastic disturbance model incorporates into the reroute design process the capacity uncertainty. A trajectory-based airspace demand model is employed for calculating current and future airspace demand. The optimal routes minimize the total expected traveling time, weather incursion, and induced congestion costs. They are compared to weather-avoidance routes calculated using deterministic dynamic programming. The stochastic reroutes have smaller deviation probability than the deterministic counterpart when both reroutes have similar total flight distance. The stochastic rerouting algorithm takes into account all convective weather fields with all severity levels while the deterministic algorithm only accounts for convective weather systems exceeding a specified level of severity. When the stochastic reroutes are compared to the actual flight routes, they have similar total flight time, and both have about 1% of travel time crossing congested enroute sectors on average. The actual flight routes induce slightly less traffic congestion than the stochastic reroutes but intercept more severe convective weather.

The roles of competition and habitat in the dynamics of populations and species distributions Ecology

Treesearch

Charles B. Yackulic; Janice Reid; James D. Nichols; James E. Hines; Raymond Davis; Eric Forsman

2014-01-01

The role of competition in structuring biotic communities at fine spatial scales is well known from detailed process-based studies. Our understanding of competition’s importance at broader scales is less resolved and mainly based on static species distribution maps. Here, we bridge this gap by examining the joint occupancy dynamics of an invading species (Barred Owl,...

Understanding Air Transportation Market Dynamics Using a Search Algorithm for Calibrating Travel Demand and Price

NASA Technical Reports Server (NTRS)

Kumar, Vivek; Horio, Brant M.; DeCicco, Anthony H.; Hasan, Shahab; Stouffer, Virginia L.; Smith, Jeremy C.; Guerreiro, Nelson M.

2015-01-01

This paper presents a search algorithm based framework to calibrate origin-destination (O-D) market specific airline ticket demands and prices for the Air Transportation System (ATS). This framework is used for calibrating an agent based model of the air ticket buy-sell process - Airline Evolutionary Simulation (Airline EVOS) -that has fidelity of detail that accounts for airline and consumer behaviors and the interdependencies they share between themselves and the NAS. More specificially, this algorithm simultaneous calibrates demand and airfares for each O-D market, to within specified threshold of a pre-specified target value. The proposed algorithm is illustrated with market data targets provided by the Transportation System Analysis Model (TSAM) and Airline Origin and Destination Survey (DB1B). Although we specify these models and datasources for this calibration exercise, the methods described in this paper are applicable to calibrating any low-level model of the ATS to some other demand forecast model-based data. We argue that using a calibration algorithm such as the one we present here to synchronize ATS models with specialized forecast demand models, is a powerful tool for establishing credible baseline conditions in experiments analyzing the effects of proposed policy changes to the ATS.

Coupling Agent-Based and Groundwater Modeling to Explore Demand Management Strategies for Shared Resources

NASA Astrophysics Data System (ADS)

Al-Amin, S.

2015-12-01

Municipal water demands in growing population centers in the arid southwest US are typically met through increased groundwater withdrawals. Hydro-climatic uncertainties attributed to climate change and land use conversions may also alter demands and impact the replenishment of groundwater supply. Groundwater aquifers are not necessarily confined within municipal and management boundaries, and multiple diverse agencies may manage a shared resource in a decentralized approach, based on individual concerns and resources. The interactions among water managers, consumers, and the environment influence the performance of local management strategies and regional groundwater resources. This research couples an agent-based modeling (ABM) framework and a groundwater model to analyze the effects of different management approaches on shared groundwater resources. The ABM captures the dynamic interactions between household-level consumers and policy makers to simulate water demands under climate change and population growth uncertainties. The groundwater model is used to analyze the relative effects of management approaches on reducing demands and replenishing groundwater resources. The framework is applied for municipalities located in the Verde River Basin, Arizona that withdraw groundwater from the Verde Formation-Basin Fill-Carbonate aquifer system. Insights gained through this simulation study can be used to guide groundwater policy-making under changing hydro-climatic scenarios for a long-term planning horizon.

Electric power market agent design

NASA Astrophysics Data System (ADS)

Oh, Hyungseon

The electric power industry in many countries has been restructured in the hope of a more economically efficient system. In the restructured system, traditional operating and planning tools based on true marginal cost do not perform well since information required is strictly confidential. For developing a new tool, it is necessary to understand offer behavior. The main objective of this study is to create a new tool for power system planning. For the purpose, this dissertation develops models for a market and market participants. A new model is developed in this work for explaining a supply-side offer curve, and several variables are introduced to characterize the curve. Demand is estimated using a neural network, and a numerical optimization process is used to determine the values of the variables that maximize the profit of the agent. The amount of data required for the optimization is chosen with the aid of nonlinear dynamics. To suggest an optimal demand-side bidding function, two optimization problems are constructed and solved for maximizing consumer satisfaction based on the properties of two different types of demands: price-based demand and must-be-served demand. Several different simulations are performed to test how an agent reacts in various situations. The offer behavior depends on locational benefit as well as the offer strategies of competitors.

Examining sufficiency and equity in the geographic distribution of physicians in Japan: a longitudinal study

PubMed Central

Hara, Koji; Otsubo, Tetsuya; Kunisawa, Susumu; Imanaka, Yuichi

2017-01-01

Objectives The objective of this study was to longitudinally examine the geographic distribution of physicians in Japan with adjustment for healthcare demand according to changes in population age structure. Methods We examined trends in the number of physicians per 100 000 population in Japan's secondary medical areas (SMAs) from 2000 to 2014. Healthcare demand was adjusted using health expenditure per capita. Trends in the Gini coefficient and the number of SMAs with a low physician supply were analysed. A subgroup analysis was also conducted where SMAs were divided into 4 groups according to urban–rural classification and initial physician supply. Results The time-based changes in the Gini coefficient and the number of SMAs with a low physician supply indicated that the equity in physician distribution had worsened throughout the study period. The number of physicians per 100 000 population had seemingly increased in all groups, with increases of 22.9% and 34.5% in urban groups with higher and lower initial physician supply, respectively. However, after adjusting healthcare demand, physician supply decreased by 1.3% in the former group and increased by 3.5% in the latter group. Decreases were also observed in the rural groups, where the number of physicians decreased by 4.4% in the group with a higher initial physician supply and 7.6% in the group with a lower initial physician supply. Conclusions Although the total number of physicians increased in Japan, demand-adjusted physician supply decreased in recent years in all areas except for urban areas with a lower initial physician supply. In addition, the equity of physician distribution had consistently deteriorated since 2000. The results indicate that failing to adjust healthcare demand will produce misleading results, and that there is a need for major reform of Japan's healthcare system to improve physician distribution. PMID:28292766

Distributed Load Shedding over Directed Communication Networks with Time Delays

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

Yang, Tao; Wu, Di

When generation is insufficient to support all loads under emergencies, effective and efficient load shedding needs to be deployed in order to maintain the supply-demand balance. This paper presents a distributed load shedding algorithm, which makes efficient decision based on the discovered global information. In the global information discovery process, each load only communicates with its neighboring load via directed communication links possibly with arbitrarily large but bounded time varying communication delays. We propose a novel distributed information discovery algorithm based on ratio consensus. Simulation results are used to validate the proposed method.

Sliding mode-based lateral vehicle dynamics control using tyre force measurements

NASA Astrophysics Data System (ADS)

Kunnappillil Madhusudhanan, Anil; Corno, Matteo; Holweg, Edward

2015-11-01

In this work, a lateral vehicle dynamics control based on tyre force measurements is proposed. Most of the lateral vehicle dynamics control schemes are based on yaw rate whereas tyre forces are the most important variables in vehicle dynamics as tyres are the only contact points between the vehicle and road. In the proposed method, active front steering is employed to uniformly distribute the required lateral force among the front left and right tyres. The force distribution is quantified through the tyre utilisation coefficients. In order to address the nonlinearities and uncertainties of the vehicle model, a gain scheduling sliding-mode control technique is used. In addition to stabilising the lateral dynamics, the proposed controller is able to maintain maximum lateral acceleration. The proposed method is tested and validated on a multi-body vehicle simulator.

Transonic flow theory of airfoils and wings

NASA Technical Reports Server (NTRS)

Garabedian, P. R.

1976-01-01

There are plans to use the supercritical wing on the next generation of commercial aircraft so as to economize on fuel consumption by reducing drag. Computer codes have served well in meeting the consequent demand for new wing sections. The possibility of replacing wind tunnel tests by computational fluid dynamics is discussed. Another approach to the supercritical wing is through shockless airfoils. A novel boundary value problem in the hodograph plane is studied that enables one to design a shockless airfoil so that its pressure distribution very nearly takes on data that are prescribed.

Villacidro solar demo plant: Integration of small-scale CSP and biogas power plants in an industrial microgrid

NASA Astrophysics Data System (ADS)

Camerada, M.; Cau, G.; Cocco, D.; Damiano, A.; Demontis, V.; Melis, T.; Musio, M.

2016-05-01

The integration of small scale concentrating solar power (CSP) in an industrial district, in order to develop a microgrid fully supplied by renewable energy sources, is presented in this paper. The plant aims to assess in real operating conditions, the performance, the effectiveness and the reliability of small-scale concentrating solar power technologies in the field of distributed generation. In particular, the potentiality of small scale CSP with thermal storage to supply dispatchable electricity to an industrial microgrid will be investigated. The microgrid will be realized in the municipal waste treatment plant of the Industrial Consortium of Villacidro, in southern Sardinia (Italy), which already includes a biogas power plant. In order to achieve the microgrid instantaneous energy balance, the analysis of the time evolution of the waste treatment plant demand and of the generation in the existing power systems has been carried out. This has allowed the design of a suitable CSP plant with thermal storage and an electrochemical storage system for supporting the proposed microgrid. At the aim of obtaining the expected energy autonomy, a specific Energy Management Strategy, which takes into account the different dynamic performances and characteristics of the demand and the generation, has been designed. In this paper, the configuration of the proposed small scale concentrating solar power (CSP) and of its thermal energy storage, based on thermocline principle, is initially described. Finally, a simulation study of the entire power system, imposing scheduled profiles based on weather forecasts, is presented.

Substructuring of multibody systems for numerical transfer path analysis in internal combustion engines

NASA Astrophysics Data System (ADS)

Acri, Antonio; Offner, Guenter; Nijman, Eugene; Rejlek, Jan

2016-10-01

Noise legislations and the increasing customer demands determine the Noise Vibration and Harshness (NVH) development of modern commercial vehicles. In order to meet the stringent legislative requirements for the vehicle noise emission, exact knowledge of all vehicle noise sources and their acoustic behavior is required. Transfer path analysis (TPA) is a fairly well established technique for estimating and ranking individual low-frequency noise or vibration contributions via the different transmission paths. Transmission paths from different sources to target points of interest and their contributions can be analyzed by applying TPA. This technique is applied on test measurements, which can only be available on prototypes, at the end of the designing process. In order to overcome the limits of TPA, a numerical transfer path analysis methodology based on the substructuring of a multibody system is proposed in this paper. Being based on numerical simulation, this methodology can be performed starting from the first steps of the designing process. The main target of the proposed methodology is to get information of noise sources contributions of a dynamic system considering the possibility to have multiple forces contemporary acting on the system. The contributions of these forces are investigated with particular focus on distribute or moving forces. In this paper, the mathematical basics of the proposed methodology and its advantages in comparison with TPA will be discussed. Then, a dynamic system is investigated with a combination of two methods. Being based on the dynamic substructuring (DS) of the investigated model, the methodology proposed requires the evaluation of the contact forces at interfaces, which are computed with a flexible multi-body dynamic (FMBD) simulation. Then, the structure-borne noise paths are computed with the wave based method (WBM). As an example application a 4-cylinder engine is investigated and the proposed methodology is applied on the engine block. The aim is to get accurate and clear relationships between excitations and responses of the simulated dynamic system, analyzing the noise and vibrational sources inside a car engine, showing the main advantages of a numerical methodology.

Power-based Shift Schedule for Pure Electric Vehicle with a Two-speed Automatic Transmission

NASA Astrophysics Data System (ADS)

Wang, Jiaqi; Liu, Yanfang; Liu, Qiang; Xu, Xiangyang

2016-11-01

This paper introduces a comprehensive shift schedule for a two-speed automatic transmission of pure electric vehicle. Considering about driving ability and efficiency performance of electric vehicles, the power-based shift schedule is proposed with three principles. This comprehensive shift schedule regards the vehicle current speed and motor load power as input parameters to satisfy the vehicle driving power demand with lowest energy consumption. A simulation model has been established to verify the dynamic and economic performance of comprehensive shift schedule. Compared with traditional dynamic and economic shift schedules, simulation results indicate that the power-based shift schedule is superior to traditional shift schedules.

Ventilatory demand and dynamic hyperinflation induced during ADL-based tests in Chronic Obstructive Pulmonary Disease patients

PubMed Central

dos Santos, Karoliny; Gulart, Aline A.; Munari, Anelise B.; Karloh, Manuela; Mayer, Anamaria F.

2016-01-01

ABSTRACT Background Airflow limitation frequently leads to the interruption of activities of daily living (ADL) in patients with Chronic Obstructive Pulmonary Disease (COPD). These patients commonly show absence of ventilatory reserve, reduced inspiratory reserve volume, and dynamic hyperinflation (DH). Objective To investigate ventilatory response and DH induced by three ADL-based protocols in COPD patients and compare them to healthy subjects. Method Cross-sectional study. COPD group: 23 patients (65±6 years, FEV1 37.2±15.4%pred); control group: 14 healthy subjects (64±4 years) matched for age, sex, and body mass index. Both groups performed all three tests: Glittre-ADL test; an activity test that involved moving objects on a shelf (TSHELF); and a modified shelf protocol isolating activity with upper limbs (TSHELF-M). Ventilatory response and inspiratory capacity were evaluated. Results Baseline ventilatory variables were similar between groups (p>0.05). The ventilatory demand increased and the inspiratory capacity decreased significantly at the end of the tests in the COPD group. Ventilatory demand and DH were higher (p<0.05) in the TSHELF than in the TSHELF–M in the COPD group (p<0.05). There were no differences in DH between the three tests in the control group (p>0.05) and ventilatory demand increased at the end of the tests (p<0.05) but to a lower extent than the COPD group. Conclusion The TSHELF induces similar ventilatory responses to the Glittre-ADL test in COPD patients with higher ventilatory demand and DH. In contrast, the ventilatory response was attenuated in the TSHELF-M, suggesting that squatting and bending down during the Glittre-ADL test could trigger significant ventilatory overload. PMID:27333482

Facilitating preemptive hardware system design using partial reconfiguration techniques.

PubMed

Dondo Gazzano, Julio; Rincon, Fernando; Vaderrama, Carlos; Villanueva, Felix; Caba, Julian; Lopez, Juan Carlos

2014-01-01

In FPGA-based control system design, partial reconfiguration is especially well suited to implement preemptive systems. In real-time systems, the deadline for critical task can compel the preemption of noncritical one. Besides, an asynchronous event can demand immediate attention and, then, force launching a reconfiguration process for high-priority task implementation. If the asynchronous event is previously scheduled, an explicit activation of the reconfiguration process is performed. If the event cannot be previously programmed, such as in dynamically scheduled systems, an implicit activation to the reconfiguration process is demanded. This paper provides a hardware-based approach to explicit and implicit activation of the partial reconfiguration process in dynamically reconfigurable SoCs and includes all the necessary tasks to cope with this issue. Furthermore, the reconfiguration service introduced in this work allows remote invocation of the reconfiguration process and then the remote integration of off-chip components. A model that offers component location transparency is also presented to enhance and facilitate system integration.

Facilitating Preemptive Hardware System Design Using Partial Reconfiguration Techniques

PubMed Central

Rincon, Fernando; Vaderrama, Carlos; Villanueva, Felix; Caba, Julian; Lopez, Juan Carlos

2014-01-01

In FPGA-based control system design, partial reconfiguration is especially well suited to implement preemptive systems. In real-time systems, the deadline for critical task can compel the preemption of noncritical one. Besides, an asynchronous event can demand immediate attention and, then, force launching a reconfiguration process for high-priority task implementation. If the asynchronous event is previously scheduled, an explicit activation of the reconfiguration process is performed. If the event cannot be previously programmed, such as in dynamically scheduled systems, an implicit activation to the reconfiguration process is demanded. This paper provides a hardware-based approach to explicit and implicit activation of the partial reconfiguration process in dynamically reconfigurable SoCs and includes all the necessary tasks to cope with this issue. Furthermore, the reconfiguration service introduced in this work allows remote invocation of the reconfiguration process and then the remote integration of off-chip components. A model that offers component location transparency is also presented to enhance and facilitate system integration. PMID:24672292

Effects of the infectious period distribution on predicted transitions in childhood disease dynamics

PubMed Central

Krylova, Olga; Earn, David J. D.

2013-01-01

The population dynamics of infectious diseases occasionally undergo rapid qualitative changes, such as transitions from annual to biennial cycles or to irregular dynamics. Previous work, based on the standard seasonally forced ‘susceptible–exposed–infectious–removed’ (SEIR) model has found that transitions in the dynamics of many childhood diseases result from bifurcations induced by slow changes in birth and vaccination rates. However, the standard SEIR formulation assumes that the stage durations (latent and infectious periods) are exponentially distributed, whereas real distributions are narrower and centred around the mean. Much recent work has indicated that realistically distributed stage durations strongly affect the dynamical structure of seasonally forced epidemic models. We investigate whether inferences drawn from previous analyses of transitions in patterns of measles dynamics are robust to the shapes of the stage duration distributions. As an illustrative example, we analyse measles dynamics in New York City from 1928 to 1972. We find that with a fixed mean infectious period in the susceptible–infectious–removed (SIR) model, the dynamical structure and predicted transitions vary substantially as a function of the shape of the infectious period distribution. By contrast, with fixed mean latent and infectious periods in the SEIR model, the shapes of the stage duration distributions have a less dramatic effect on model dynamical structure and predicted transitions. All these results can be understood more easily by considering the distribution of the disease generation time as opposed to the distributions of individual disease stages. Numerical bifurcation analysis reveals that for a given mean generation time the dynamics of the SIR and SEIR models for measles are nearly equivalent and are insensitive to the shapes of the disease stage distributions. PMID:23676892

Effects of the infectious period distribution on predicted transitions in childhood disease dynamics.

PubMed

Krylova, Olga; Earn, David J D

2013-07-06

The population dynamics of infectious diseases occasionally undergo rapid qualitative changes, such as transitions from annual to biennial cycles or to irregular dynamics. Previous work, based on the standard seasonally forced 'susceptible-exposed-infectious-removed' (SEIR) model has found that transitions in the dynamics of many childhood diseases result from bifurcations induced by slow changes in birth and vaccination rates. However, the standard SEIR formulation assumes that the stage durations (latent and infectious periods) are exponentially distributed, whereas real distributions are narrower and centred around the mean. Much recent work has indicated that realistically distributed stage durations strongly affect the dynamical structure of seasonally forced epidemic models. We investigate whether inferences drawn from previous analyses of transitions in patterns of measles dynamics are robust to the shapes of the stage duration distributions. As an illustrative example, we analyse measles dynamics in New York City from 1928 to 1972. We find that with a fixed mean infectious period in the susceptible-infectious-removed (SIR) model, the dynamical structure and predicted transitions vary substantially as a function of the shape of the infectious period distribution. By contrast, with fixed mean latent and infectious periods in the SEIR model, the shapes of the stage duration distributions have a less dramatic effect on model dynamical structure and predicted transitions. All these results can be understood more easily by considering the distribution of the disease generation time as opposed to the distributions of individual disease stages. Numerical bifurcation analysis reveals that for a given mean generation time the dynamics of the SIR and SEIR models for measles are nearly equivalent and are insensitive to the shapes of the disease stage distributions.

Some Results of Weak Anticipative Concept Applied in Simulation Based Decision Support in Enterprise

NASA Astrophysics Data System (ADS)

Kljajić, Miroljub; Kofjač, Davorin; Kljajić Borštnar, Mirjana; Škraba, Andrej

2010-11-01

The simulation models are used as for decision support and learning in enterprises and in schools. Tree cases of successful applications demonstrate usefulness of weak anticipative information. Job shop scheduling production with makespan criterion presents a real case customized flexible furniture production optimization. The genetic algorithm for job shop scheduling optimization is presented. Simulation based inventory control for products with stochastic lead time and demand describes inventory optimization for products with stochastic lead time and demand. Dynamic programming and fuzzy control algorithms reduce the total cost without producing stock-outs in most cases. Values of decision making information based on simulation were discussed too. All two cases will be discussed from optimization, modeling and learning point of view.

BoD services in layer 1 VPN with dynamic virtual concatenation group

NASA Astrophysics Data System (ADS)

Du, Shu; Peng, Yunfeng; Long, Keping

2008-11-01

Bandwidth-on-Demand (BoD) services are characteristic of dynamic bandwidth provisioning based on customers' resource requirement, which will be a must for future networks. BoD services become possible with the development of make-before-break, Virtual Concatenation (VCAT) and Link Capacity Adjustment Scheme (LCAS). In this paper, we introduce BoD services into L1VPN, thus the resource assigned to a L1VPN can be gracefully adjusted at various bandwidth granularities based on customers' requirement. And we propose a dynamic bandwidth adjustment scheme, which is compromise between make-before-break and VCAT&LCAS and mainly based on the latter. The scheme minimizes the number of distinct paths to support a connection between a source-destination pair, and uses make-beforebreak technology for re-optimization.

Transportation and dynamic networks: Models, theory, and applications to supply chains, electric power, and financial networks

NASA Astrophysics Data System (ADS)

Liu, Zugang

Network systems, including transportation and logistic systems, electric power generation and distribution networks as well as financial networks, provide the critical infrastructure for the functioning of our societies and economies. The understanding of the dynamic behavior of such systems is also crucial to national security and prosperity. The identification of new connections between distinct network systems is the inspiration for the research in this dissertation. In particular, I answer two questions raised by Beckmann, McGuire, and Winsten (1956) and Copeland (1952) over half a century ago, which are, respectively, how are electric power flows related to transportation flows and does money flow like water or electricity? In addition, in this dissertation, I achieve the following: (1) I establish the relationships between transportation networks and three other classes of complex network systems: supply chain networks, electric power generation and transmission networks, and financial networks with intermediation. The establishment of such connections provides novel theoretical insights as well as new pricing mechanisms, and efficient computational methods. (2) I develop new modeling frameworks based on evolutionary variational inequality theory that capture the dynamics of such network systems in terms of the time-varying flows and incurred costs, prices, and, where applicable, profits. This dissertation studies the dynamics of such network systems by addressing both internal competition and/or cooperation, and external changes, such as varying costs and demands. (3) I focus, in depth, on electric power supply chains. By exploiting the relationships between transportation networks and electric power supply chains, I develop a large-scale network model that integrates electric power supply chains and fuel supply markets. The model captures both the economic transactions as well as the physical transmission constraints. The model is then applied to the New England electric power supply chain consisting of 6 states, 5 fuel types, 82 power generators, with a total of 573 generating units, and 10 demand markets. The empirical case study demonstrates that the regional electricity prices simulated by the model match very well the actual electricity prices in New England. I also utilize the model to study interactions between electric power supply chains and energy fuel markets.

Tablet based distributed intelligent load management

DOEpatents

Lu, Yan; Zhou, Siyuan

2018-01-09

A facility is connected to an electricity utility and is responsive to Demand Response Events. A plurality of devices is each individually connected to the electricity grid via an addressable switch connected to a secure network that is enabled to be individually switched off by a server. An occupant of a room in control of the plurality of devices provides via a Human Machine Interface on a tablet a preferred order of switching off the plurality of devices in case of a Demand Response Event. A configuration file based at least partially on the preferred order and on a severity of the Demand Response Events determines which devices which of the plurality devices will be switched off. The server accesses the configuration file and switches off the devices included in the configuration file.

77 FR 59458 - Regulation of Fuels and Fuel Additives: 2013 Biomass-Based Diesel Renewable Fuel Volume

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-27

... Consumption A. Demand for Biomass-Based Diesel B. Availability of Feedstocks To Produce 1.28 Billion Gallons of Biodiesel 1. Grease and Rendered Fats 2. Corn Oil 3. Soybean Oil 4. Effects on Food Prices 5. Other Bio-Oils C. Production Capacity D. Consumption Capacity E. Biomass-Based Diesel Distribution...

Analysis of stationary fuel cell dynamic ramping capabilities and ultra capacitor energy storage using high resolution demand data

NASA Astrophysics Data System (ADS)

Meacham, James R.; Jabbari, Faryar; Brouwer, Jacob; Mauzey, Josh L.; Samuelsen, G. Scott

Current high temperature fuel cell (HTFC) systems used for stationary power applications (in the 200-300 kW size range) have very limited dynamic load following capability or are simply base load devices. Considering the economics of existing electric utility rate structures, there is little incentive to increase HTFC ramping capability beyond 1 kWs -1 (0.4% s -1). However, in order to ease concerns about grid instabilities from utility companies and increase market adoption, HTFC systems will have to increase their ramping abilities, and will likely have to incorporate electrical energy storage (EES). Because batteries have low power densities and limited lifetimes in highly cyclic applications, ultra capacitors may be the EES medium of choice. The current analyses show that, because ultra capacitors have a very low energy storage density, their integration with HTFC systems may not be feasible unless the fuel cell has a ramp rate approaching 10 kWs -1 (4% s -1) when using a worst-case design analysis. This requirement for fast dynamic load response characteristics can be reduced to 1 kWs -1 by utilizing high resolution demand data to properly size ultra capacitor systems and through demand management techniques that reduce load volatility.

Influence of the operational parameters on bioelectricity generation in continuous microbial fuel cell, experimental and computational fluid dynamics modelling

NASA Astrophysics Data System (ADS)

Sobieszuk, Paweł; Zamojska-Jaroszewicz, Anna; Makowski, Łukasz

2017-12-01

The influence of the organic loading rate (also known as active anodic chamber volume) on bioelectricity generation in a continuous, two-chamber microbial fuel cell for the treatment of synthetic wastewater, with glucose as the only carbon source, was examined. Ten sets of experiments with different combinations of hydraulic retention times (0.24-1.14 d) and influent chemical oxygen demand concentrations were performed to verify the impact of organic loading rate on the voltage generation capacity of a simple dual-chamber microbial fuel cell working in continuous mode. We found that there is an optimal hydraulic retention time value at which the maximum voltage is generated: 0.41 d. However, there were no similar effects, in terms of voltage generation, when a constant hydraulic retention time with different influent chemical oxygen demand of wastewater was used. The obtained maximal voltage value (600 mV) has also been compared to literature data. Computational fluid dynamics (CFD) was used to calculate the fluid flow and the exit age distribution of fluid elements in the reactor to explain the obtained experimental results and identify the crucial parameters for the design of bioreactors on an industrial scale.

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.

Modelling supply and demand of bioenergy from short rotation coppice and Miscanthus in the UK.

PubMed

Bauen, A W; Dunnett, A J; Richter, G M; Dailey, A G; Aylott, M; Casella, E; Taylor, G

2010-11-01

Biomass from lignocellulosic energy crops can contribute to primary energy supply in the short term in heat and electricity applications and in the longer term in transport fuel applications. This paper estimates the optimal feedstock allocation of herbaceous and woody lignocellulosic energy crops for England and Wales based on empirical productivity models. Yield maps for Miscanthus, willow and poplar, constrained by climatic, soil and land use factors, are used to estimate the potential resource. An energy crop supply-cost curve is estimated based on the resource distribution and associated production costs. The spatial resource model is then used to inform the supply of biomass to geographically distributed demand centres, with co-firing plants used as an illustration. Finally, the potential contribution of energy crops to UK primary energy and renewable energy targets is discussed. Copyright 2010 Elsevier Ltd. All rights reserved.

Potential climate change impacts on water availability and cooling water demand in the Lusatian Lignite Mining Region, Central Europe

NASA Astrophysics Data System (ADS)

Pohle, Ina; Koch, Hagen; Gädeke, Anne; Grünewald, Uwe; Kaltofen, Michael; Redetzky, Michael

2014-05-01

In the catchments of the rivers Schwarze Elster, Spree and Lusatian Neisse, hydrologic and socioeconomic systems are coupled via a complex water management system in which water users, reservoirs and water transfers are included. Lignite mining and electricity production are major water users in the region: To allow for open pit lignite mining, ground water is depleted and released into the river system while cooling water is used in the thermal power plants. In order to assess potential climate change impacts on water availability in the catchments as well as on the water demand of the thermal power plants, a climate change impact assessment was performed using the hydrological model SWIM and the long term water management model WBalMo. The potential impacts of climate change were considered by using three regional climate change scenarios of the statistical regional climate model STAR assuming a further temperature increase of 0, 2 or 3 K by the year 2050 in the region respectively. Furthermore, scenarios assuming decreasing mining activities in terms of a decreasing groundwater depression cone, lower mining water discharges, and reduced cooling water demand of the thermal power plants are considered. In the standard version of the WBalMo model cooling water demand is considered as static with regard to climate variables. However, changes in the future cooling water demand over time according to the plans of the local mining and power plant operator are considered. In order to account for climate change impacts on the cooling water demand of the thermal power plants, a dynamical approach for calculating water demand was implemented in WBalMo. As this approach is based on air temperature and air humidity, the projected air temperature and air humidity of the climate scenarios at the locations of the power plants are included in the calculation. Due to increasing temperature and decreasing precipitation declining natural and managed discharges, and hence a lower water availability in the region, were simulated by SWIM and WBalMo respectively. Next to changing climate conditions, also the different mining scenarios have considerable impacts on natural and managed discharges. Using the dynamic approach for cooling water demand, the simulated water demands are lower in winter, but higher in summer compared to the static approach. As a consequence of changes in the seasonal pattern of the cooling water demand of the power plants, lower summer discharges downstream of the thermal power plants are simulated using the dynamical approach. Due to the complex water management system in the region included in the water management model WBalMo, also the simulation of reservoir releases and volumes is impacted by the choice of either the static or the dynamic approach for calculating the cooling water demand of the thermal power plants.

A distributed parallel storage architecture and its potential application within EOSDIS

NASA Technical Reports Server (NTRS)

Johnston, William E.; Tierney, Brian; Feuquay, Jay; Butzer, Tony

1994-01-01

We describe the architecture, implementation, use of a scalable, high performance, distributed-parallel data storage system developed in the ARPA funded MAGIC gigabit testbed. A collection of wide area distributed disk servers operate in parallel to provide logical block level access to large data sets. Operated primarily as a network-based cache, the architecture supports cooperation among independently owned resources to provide fast, large-scale, on-demand storage to support data handling, simulation, and computation.

Analysis of logistic distribution performance of good supply from PT. Mentari Trans Nusantara distribution center to branches using Smart PLS 3.0

NASA Astrophysics Data System (ADS)

Endrawati, Titin; Siregar, M. Tirtana

2018-03-01

PT Mentari Trans Nusantara is a company engaged in the distribution of goods from the manufacture of the product to the distributor branch of the customer so that the product distribution must be controlled directly from the PT Mentari Trans Nusantara Center for faster delivery process. Problems often occur on the expedition company which in charge in sending the goods although it has quite extensive networking. The company is less control over logistics management. Meanwhile, logistics distribution management control policy will affect the company's performance in distributing products to customer distributor branches and managing product inventory in distribution center. PT Mentari Trans Nusantara is an expedition company which engaged in good delivery, including in Jakarta. Logistics management performance is very important due to its related to the supply of goods from the central activities to the branches based oncustomer demand. Supply chain management performance is obviously depends on the location of both the distribution center and branches, the smoothness of transportation in the distribution and the availability of the product in the distribution center to meet the demand in order to avoid losing sales. This study concluded that the company could be more efficient and effective in minimizing the risks of loses by improve its logistic management.

Development of an Unmanned Aerial Vehicle-Borne Crop-Growth Monitoring System.

PubMed

Ni, Jun; Yao, Lili; Zhang, Jingchao; Cao, Weixing; Zhu, Yan; Tai, Xiuxiang

2017-03-03

In view of the demand for a low-cost, high-throughput method for the continuous acquisition of crop growth information, this study describes a crop-growth monitoring system which uses an unmanned aerial vehicle (UAV) as an operating platform. The system is capable of real-time online acquisition of various major indexes, e.g., the normalized difference vegetation index (NDVI) of the crop canopy, ratio vegetation index (RVI), leaf nitrogen accumulation (LNA), leaf area index (LAI), and leaf dry weight (LDW). By carrying out three-dimensional numerical simulations based on computational fluid dynamics, spatial distributions were obtained for the UAV down-wash flow fields on the surface of the crop canopy. Based on the flow-field characteristics and geometrical dimensions, a UAV-borne crop-growth sensor was designed. Our field experiments show that the monitoring system has good dynamic stability and measurement accuracy over the range of operating altitudes of the sensor. The linear fitting determination coefficients (R²) for the output RVI value with respect to LNA, LAI, and LDW are 0.63, 0.69, and 0.66, respectively, and the Root-mean-square errors (RMSEs) are 1.42, 1.02 and 3.09, respectively. The equivalent figures for the output NDVI value are 0.60, 0.65, and 0.62 (LNA, LAI, and LDW, respectively) and the RMSEs are 1.44, 1.01 and 3.01, respectively.

Development of an Unmanned Aerial Vehicle-Borne Crop-Growth Monitoring System

PubMed Central

Ni, Jun; Yao, Lili; Zhang, Jingchao; Cao, Weixing; Zhu, Yan; Tai, Xiuxiang

2017-01-01

In view of the demand for a low-cost, high-throughput method for the continuous acquisition of crop growth information, this study describes a crop-growth monitoring system which uses an unmanned aerial vehicle (UAV) as an operating platform. The system is capable of real-time online acquisition of various major indexes, e.g., the normalized difference vegetation index (NDVI) of the crop canopy, ratio vegetation index (RVI), leaf nitrogen accumulation (LNA), leaf area index (LAI), and leaf dry weight (LDW). By carrying out three-dimensional numerical simulations based on computational fluid dynamics, spatial distributions were obtained for the UAV down-wash flow fields on the surface of the crop canopy. Based on the flow-field characteristics and geometrical dimensions, a UAV-borne crop-growth sensor was designed. Our field experiments show that the monitoring system has good dynamic stability and measurement accuracy over the range of operating altitudes of the sensor. The linear fitting determination coefficients (R2) for the output RVI value with respect to LNA, LAI, and LDW are 0.63, 0.69, and 0.66, respectively, and the Root-mean-square errors (RMSEs) are 1.42, 1.02 and 3.09, respectively. The equivalent figures for the output NDVI value are 0.60, 0.65, and 0.62 (LNA, LAI, and LDW, respectively) and the RMSEs are 1.44, 1.01 and 3.01, respectively. PMID:28273815

A bio-inspired swarm robot coordination algorithm for multiple target searching

NASA Astrophysics Data System (ADS)

Meng, Yan; Gan, Jing; Desai, Sachi

2008-04-01

The coordination of a multi-robot system searching for multi targets is challenging under dynamic environment since the multi-robot system demands group coherence (agents need to have the incentive to work together faithfully) and group competence (agents need to know how to work together well). In our previous proposed bio-inspired coordination method, Local Interaction through Virtual Stigmergy (LIVS), one problem is the considerable randomness of the robot movement during coordination, which may lead to more power consumption and longer searching time. To address these issues, an adaptive LIVS (ALIVS) method is proposed in this paper, which not only considers the travel cost and target weight, but also predicting the target/robot ratio and potential robot redundancy with respect to the detected targets. Furthermore, a dynamic weight adjustment is also applied to improve the searching performance. This new method a truly distributed method where each robot makes its own decision based on its local sensing information and the information from its neighbors. Basically, each robot only communicates with its neighbors through a virtual stigmergy mechanism and makes its local movement decision based on a Particle Swarm Optimization (PSO) algorithm. The proposed ALIVS algorithm has been implemented on the embodied robot simulator, Player/Stage, in a searching target. The simulation results demonstrate the efficiency and robustness in a power-efficient manner with the real-world constraints.

Response of microbial growth to orthophosphate and organic carbon influx in copper and plastic based plumbing water systems.

PubMed

Park, Se-Keun; Kim, Yeong-Kwan; Choi, Sung-Chan

2008-07-01

Consequences of orthophosphate addition for corrosion control in water distribution pipes with respect to microbial growth were investigated using batch and dynamic tests. Batch tests showed that the release of copper in either low or high organic carbon content water was decreased by 69% and 56% with addition 206 microg PO(4)-P, respectively. Dosing of orthophosphate against corrosion did not increase microbial growth potential in the water and in the biofilm in both corroded and uncorroded systems receiving tap water with a low content of organic carbon and of biodegradable organic fraction. However, in tap water having a high concentration of organic carbon from acetate addition, orthophosphate addition promoted the growth of bacteria, allowed more bacteria to assemble on corroded and uncorroded surfaces, and increased the consumption of organic carbon. Orthophosphate consumption did not exceed 1% of the amount of easily biodegradable organic carbon required for microbial growth, and the orthophosphate demand for corrosion control greatly exceeded the nutritional requirement of microbial growth. The results of the dynamic tests demonstrated that there was a significant effect of interaction between biodegradable organic carbon and orthophosphate on biofilm growth, whereby the effect of orthophosphate flux on microbial growth was dependent on the levels of biodegradable organic carbon. Controlling an easily biodegradable organic carbon would be therefore necessary to minimize the microbial growth potential induced by orthophosphate-based anticorrosion treatment.

Emissions markets, power markets and market power: A study of the interactions between contemporary emissions markets and deregulated electricity markets

NASA Astrophysics Data System (ADS)

Dormady, Noah Christopher

Chapter 1: A Monte Carlo Approach. The use of auctions to distribute tradeable property rights to firms in already heavily concentrated markets may further exacerbate the problems of market power that exist within those markets. This chapter provides a model of a two-stage emissions market modeled after a contemporary regional permit trading market in the United States, the Regional Greenhouse Gas Initiative, Inc. (RGGI). It then introduces Oligopsony 1.0, a C# software package constructed in the .NET environment that simulates uniform-price auctions using stochastic Monte Carlo simulation for modeling market power in tradeable property rights auctions. Monte Carlo methods add a probabilistic element to standard auction theoretic equilibria. The results of these simulations indicate that there can be significant non-linearities between profit and market power as exercised through strategic demand reduction. This analysis finds the optimum point of strategic demand reduction that enables the firm to exploit these non-linearities, and it determines the probability distributions of these optima using kernel density analysis. Chapter 2: An Experimental Approach. How will emerging auction-based emissions markets function within the context of today's deregulated auction-based electricity markets? This chapter provides an experimental analysis of a joint energy-emissions market. The impact of market power and collusion among dominant firms is evaluated to determine the extent to which an auction-based tradeable permit market influences performance in an adjacent electricity market. The experimental treatment design controls for a variety of real-world institutional features, including variable demand, permit banking, inter-temporal (multi-round) dynamics, a tightening cap, and resale. Results suggest that the exercise of market power significantly increases electricity auction clearing prices, without significantly increasing emissions auction clearing prices, and in some cases, even significantly suppresses them. The institution of auction-based carbon markets in the already-concentrated energy sector can further strengthen the market position of dominant firms who can leverage energy-emissions market linkages to their operational advantage. Chapter 3: Regulatory Mechanisms and Policy Approaches. Contemporary deregulated electricity markets are defined by a complex array of multi-settlement markets, with additional market-based mechanisms designed, to a large extent, to limit the exercise of market power by dominant firms. On top of the already complex nature of these markets, policymakers are also adding market-based mechanisms to curtail greenhouse gases. Key linkages exist between electricity and emissions markets that may be utilized by dominant firms. This chapter provides an analysis of three specific policy mechanisms that are utilized in contemporary markets to effectively reduce the incentive of dominant firms to exercise market power. These include convergence bidding, consignment auctions and multilevel holding accounts.

Performance Analysis of a CO2 Heat Pump Water Heating System Under a Daily Change in a Simulated Demand

NASA Astrophysics Data System (ADS)

Yokoyama, Ryohei; Kohno, Yasuhiro; Wakui, Tetsuya; Takemura, Kazuhisa

Air-to-water heat pumps using CO2 as a refrigerant have been developed. In addition, water heating systems each of which combines a CO2 heat pump with a hot water storage tank have been commercialized and widespread. They are expected to contribute to energy saving in residential hot water supply. It has become more and more important to enhance the system performance. In this paper, the performance of a CO2 heat pump water heating system is analyzed under a daily change in a simulated hot water demand by numerical simulation. A static model of a CO2 heat pump and a dynamic model of a storage tank result in a set of differential algebraic equations, and it is solved numerically by a hierarchical combination of Runge-Kutta and Newton-Raphson methods. Daily changes in the temperature distributions in the storage tank and the system performance criteria such as volumes of stored and unused hot water, coefficient of performance, and storage and system efficiencies are clarified under a series of daily hot water demands during a month.

CHARACTERIZING SPATIAL AND TEMPORAL DYNAMICS: DEVELOPMENT OF A GRID-BASED WATERSHED MERCURY LOADING MODEL

EPA Science Inventory

A distributed grid-based watershed mercury loading model has been developed to characterize spatial and temporal dynamics of mercury from both point and non-point sources. The model simulates flow, sediment transport, and mercury dynamics on a daily time step across a diverse lan...

Customer premises services market demand assessment 1980 - 2000. Volume 1: Executive summary

NASA Technical Reports Server (NTRS)

Gamble, R. B.; Saporta, L.; Heidenrich, G. A.

1983-01-01

Estimates of market demand for domestic civilian telecommunications services for the years 1980 to 2000 are provided. Overall demand, demand or satellite services, demand for satellite delivered Customer Premises Service (CPS), and demand for 30/20 GHz Customer Premises Services are covered. Emphasis is placed on the CPS market and demand is segmented by market, by service, by user class and by geographic region. Prices for competing services are discussed and the distribution of traffic with respect to distance is estimated. A nationwide traffic distribution model for CPS in terms of demand for CPS traffic and earth stations for each of the major SMSAs in the United States are provided.

Stochastic Online Learning in Dynamic Networks under Unknown Models

DTIC Science & Technology

2016-08-02

Repeated Game with Incomplete Information, IEEE International Conference on Acoustics, Speech, and Signal Processing. 20-MAR-16, Shanghai, China...in a game theoretic framework for the application of multi-seller dynamic pricing with unknown demand models. We formulated the problem as an...infinitely repeated game with incomplete information and developed a dynamic pricing strategy referred to as Competitive and Cooperative Demand Learning

The future of transportation planning : dynamic travel behavior analyses based on stochastic decision-making styles : final report.

DOT National Transportation Integrated Search

2003-08-01

Over the past half-century, the progress of travel behavior research and travel demand forecasting has been spear : headed and continuously propelled by the micro-economic theories, specifically utility maximization. There is no : denial that the tra...

OECD Skills Strategy Diagnostic Report: Italy 2017

ERIC Educational Resources Information Center

OECD Publishing, 2017

2017-01-01

Skills demands are increasing and changing rapidly everywhere, as advanced economies adapt to globalisation, technological change and ageing. Yet Italy is struggling more than other advanced economies to make the transition towards a thriving and dynamic skills-based society. The Organisation for Economic Cooperation and Development (OECD) Skills…

Economic benefits of midseason reordering in apparel retailing

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

Lamont, A.; Elayat, H.

1995-09-27

This report presents a method for determining the value of reordering, explores factors that affect its value, and provides an estimate of the value under a range of conditions. The method is based on a stochastic process model of the demands the retailer faces. It uses a dynamic programming model to determine the optimal quantities to order and the expected profits. The analysis shows that the benefits of reordering are quite sensitive to the uncertainties in the demand and to the assumptions about the markdown of unsold merchandise at the end of the season.

Dynamic Data Citation through Provenance - new approach for reproducible science in Geoscience Australia.

NASA Astrophysics Data System (ADS)

Bastrakova, I.; Car, N.

2017-12-01

Geoscience Australia (GA) is recognised and respected as the National Repository and steward of multiple nationally significance data collections that provides geoscience information, services and capability to the Australian Government, industry and stakeholders. Internally, this brings a challenge of managing large volume (11 PB) of diverse and highly complex data distributed through a significant number of catalogues, applications, portals, virtual laboratories, and direct downloads from multiple locations. Externally, GA is facing constant changer in the Government regulations (e.g. open data and archival laws), growing stakeholder demands for high quality and near real-time delivery of data and products, and rapid technological advances enabling dynamic data access. Traditional approach to citing static data and products cannot satisfy increasing demands for the results from scientific workflows, or items within the workflows to be open, discoverable, thrusted and reproducible. Thus, citation of data, products, codes and applications through the implementation of provenance records is being implemented. This approach involves capturing the provenance of many GA processes according to a standardised data model and storing it, as well as metadata for the elements it references, in a searchable set of systems. This provides GA with ability to cite workflows unambiguously as well as each item within each workflow, including inputs and outputs and many other registered components. Dynamic objects can therefore be referenced flexibly in relation to their generation process - a dataset's metadata indicates where to obtain its provenance from - meaning the relevant facts of its dynamism need not be crammed into a single citation object with a single set of attributes. This allows for simple citations, similar to traditional static document citations such as references in journals, to be used for complex dynamic data and other objects such as software code.

Advanced compilation techniques in the PARADIGM compiler for distributed-memory multicomputers

NASA Technical Reports Server (NTRS)

Su, Ernesto; Lain, Antonio; Ramaswamy, Shankar; Palermo, Daniel J.; Hodges, Eugene W., IV; Banerjee, Prithviraj

1995-01-01

The PARADIGM compiler project provides an automated means to parallelize programs, written in a serial programming model, for efficient execution on distributed-memory multicomputers. .A previous implementation of the compiler based on the PTD representation allowed symbolic array sizes, affine loop bounds and array subscripts, and variable number of processors, provided that arrays were single or multi-dimensionally block distributed. The techniques presented here extend the compiler to also accept multidimensional cyclic and block-cyclic distributions within a uniform symbolic framework. These extensions demand more sophisticated symbolic manipulation capabilities. A novel aspect of our approach is to meet this demand by interfacing PARADIGM with a powerful off-the-shelf symbolic package, Mathematica. This paper describes some of the Mathematica routines that performs various transformations, shows how they are invoked and used by the compiler to overcome the new challenges, and presents experimental results for code involving cyclic and block-cyclic arrays as evidence of the feasibility of the approach.

Locating inefficient links in a large-scale transportation network

NASA Astrophysics Data System (ADS)

Sun, Li; Liu, Like; Xu, Zhongzhi; Jie, Yang; Wei, Dong; Wang, Pu

2015-02-01

Based on data from geographical information system (GIS) and daily commuting origin destination (OD) matrices, we estimated the distribution of traffic flow in the San Francisco road network and studied Braess's paradox in a large-scale transportation network with realistic travel demand. We measured the variation of total travel time Δ T when a road segment is closed, and found that | Δ T | follows a power-law distribution if Δ T < 0 or Δ T > 0. This implies that most roads have a negligible effect on the efficiency of the road network, while the failure of a few crucial links would result in severe travel delays, and closure of a few inefficient links would counter-intuitively reduce travel costs considerably. Generating three theoretical networks, we discovered that the heterogeneously distributed travel demand may be the origin of the observed power-law distributions of | Δ T | . Finally, a genetic algorithm was used to pinpoint inefficient link clusters in the road network. We found that closing specific road clusters would further improve the transportation efficiency.

Navigating the flow: individual and continuum models for homing in flowing environments.

PubMed

Painter, Kevin J; Hillen, Thomas

2015-11-06

Navigation for aquatic and airborne species often takes place in the face of complicated flows, from persistent currents to highly unpredictable storms. Hydrodynamic models are capable of simulating flow dynamics and provide the impetus for much individual-based modelling, in which particle-sized individuals are immersed into a flowing medium. These models yield insights on the impact of currents on population distributions from fish eggs to large organisms, yet their computational demands and intractability reduce their capacity to generate the broader, less parameter-specific, insights allowed by traditional continuous approaches. In this paper, we formulate an individual-based model for navigation within a flowing field and apply scaling to derive its corresponding macroscopic and continuous model. We apply it to various movement classes, from drifters that simply go with the flow to navigators that respond to environmental orienteering cues. The utility of the model is demonstrated via its application to 'homing' problems and, in particular, the navigation of the marine green turtle Chelonia mydas to Ascension Island. © 2015 The Author(s).

Global critical materials markets: An agent-based modeling approach

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

Riddle, Matthew; Macal, Charles M.; Conzelmann, Guenter

As part of efforts to position the United States as a leader in clean energy technology production, the U. S. Department of Energy (DOE) issued two Critical Materials Strategy reports, which assessed 16 materials on the basis of their importance to clean energy development and their supply risk ( U.S. Department of Energy (DOE), 2010 and DOE, 2011). To understand the implications for clean energy of disruptions in supplies of critical materials, it is important to understand supply chain dynamics from mining to final product production. As a case study of critical material supply chains, we focus on the supplymore » of two rare earth metals, neodymium (Nd) and dysprosium (Dy), for permanent magnets used in wind turbines, electric vehicles and other applications. We introduce GCMat, a dynamic agent-based model that includes interacting agents at five supply chain stages consisting of mining, metal refining, magnet production, final product production and demand. Agents throughout the supply chain make pricing, production and inventory management decisions. Deposit developers choose which deposits to develop based on market conditions and detailed data on 57 rare earth deposits. Wind turbine and electric vehicle producers choose from a set of possible production technologies that require different amounts of rare earths. We ran the model under a baseline scenario and four alternative scenarios with different demand and production technology inputs. Model results from 2010 to 2013 fit well with historical data. Projections through 2025 show a number of possible future price, demand, and supply trajectories. For each scenario, we highlight reasons for turning points under market conditions, for differences between Nd and Dy markets, and for differences between scenarios. Because GCMat can model causal dynamics and provide fine-grain representation of agents and their decisions, it provides explanations for turning points under market conditions that are not otherwise available from other modeling approaches. Our baseline projections show very different behaviors for Nd and Dy prices. Nd prices continue to drop and remain low even at the end of our simulation period as new capacity comes online and leads to a market in which production capacity outpaces demand. Dy price movements, on the other hand, change directions several times with several key turning points related to inventory behaviors of particular agents in the supply chain and asymmetric supply and demand trends. Scenario analyses show the impact of stronger demand growth for rare earths, and in particular finds that Nd price impacts are significantly delayed as compared to Dy. This is explained by the substantial excess production capacity for Nd in the early simulation years that keeps prices down. Scenarios that explore the impact of reducing the Dy content of magnets show the intricate interdependencies of these two markets as price trends for both rare earths reverse directions – reducing the Dy content of magnets reduces Dy demand, which drives down Dy prices and translates into lower magnet prices. This in turn raises the demand for magnets and therefore the demand for Nd and eventually drives up the Nd price.« less

Quantum decision-maker theory and simulation

NASA Astrophysics Data System (ADS)

Zak, Michail; Meyers, Ronald E.; Deacon, Keith S.

2000-07-01

A quantum device simulating the human decision making process is introduced. It consists of quantum recurrent nets generating stochastic processes which represent the motor dynamics, and of classical neural nets describing the evolution of probabilities of these processes which represent the mental dynamics. The autonomy of the decision making process is achieved by a feedback from the mental to motor dynamics which changes the stochastic matrix based upon the probability distribution. This feedback replaces unavailable external information by an internal knowledge- base stored in the mental model in the form of probability distributions. As a result, the coupled motor-mental dynamics is described by a nonlinear version of Markov chains which can decrease entropy without an external source of information. Applications to common sense based decisions as well as to evolutionary games are discussed. An example exhibiting self-organization is computed using quantum computer simulation. Force on force and mutual aircraft engagements using the quantum decision maker dynamics are considered.

Power management and distribution considerations for a lunar base

NASA Technical Reports Server (NTRS)

Kenny, Barbara H.; Coleman, Anthony S.

1991-01-01

Design philosophies and technology needs for the power management and distribution (PMAD) portion of a lunar base power system are discussed. A process is described whereby mission planners may proceed from a knowledge of the PMAD functions and mission performance requirements to a definition of design options and technology needs. Current research efforts at the NASA LRC to meet the PMAD system needs for a Lunar base are described. Based on the requirements, the lunar base PMAD is seen as best being accomplished by a utility like system, although with some additional demands including autonomous operation and scheduling and accurate, predictive modeling during the design process.

Development and Simulation of Increased Generation on a Secondary Circuit of a Microgrid

NASA Astrophysics Data System (ADS)

Reyes, Karina

As fossil fuels are depleted and their environmental impacts remain, other sources of energy must be considered to generate power. Renewable sources, for example, are emerging to play a major role in this regard. In parallel, electric vehicle (EV) charging is evolving as a major load demand. To meet reliability and resiliency goals demanded by the electricity market, interest in microgrids are growing as a distributed energy resource (DER). In this thesis, the effects of intermittent renewable power generation and random EV charging on secondary microgrid circuits are analyzed in the presence of a controllable battery in order to characterize and better understand the dynamics associated with intermittent power production and random load demands in the context of the microgrid paradigm. For two reasons, a secondary circuit on the University of California, Irvine (UCI) Microgrid serves as the case study. First, the secondary circuit (UC-9) is heavily loaded and an integral component of a highly characterized and metered microgrid. Second, a unique "next-generation" distributed energy resource has been deployed at the end of the circuit that integrates photovoltaic power generation, battery storage, and EV charging. In order to analyze this system and evaluate the impact of the DER on the secondary circuit, a model was developed to provide a real-time load flow analysis. The research develops a power management system applicable to similarly integrated systems. The model is verified by metered data obtained from a network of high resolution electric meters and estimated load data for the buildings that have unknown demand. An increase in voltage is observed when the amount of photovoltaic power generation is increased. To mitigate this effect, a constant power factor is set. Should the real power change dramatically, the reactive power is changed to mitigate voltage fluctuations.

Development of a Dynamically Configurable, Object-Oriented Framework for Distributed, Multi-modal Computational Aerospace Systems Simulation

NASA Technical Reports Server (NTRS)

Afjeh, Abdollah A.; Reed, John A.

2003-01-01

The following reports are presented on this project:A first year progress report on: Development of a Dynamically Configurable,Object-Oriented Framework for Distributed, Multi-modal Computational Aerospace Systems Simulation; A second year progress report on: Development of a Dynamically Configurable, Object-Oriented Framework for Distributed, Multi-modal Computational Aerospace Systems Simulation; An Extensible, Interchangeable and Sharable Database Model for Improving Multidisciplinary Aircraft Design; Interactive, Secure Web-enabled Aircraft Engine Simulation Using XML Databinding Integration; and Improving the Aircraft Design Process Using Web-based Modeling and Simulation.

Stochastic and Statistical Analysis of Utility Revenues and Weather Data Analysis for Consumer Demand Estimation in Smart Grids

PubMed Central

Ali, S. M.; Mehmood, C. A; Khan, B.; Jawad, M.; Farid, U; Jadoon, J. K.; Ali, M.; Tareen, N. K.; Usman, S.; Majid, M.; Anwar, S. M.

2016-01-01

In smart grid paradigm, the consumer demands are random and time-dependent, owning towards stochastic probabilities. The stochastically varying consumer demands have put the policy makers and supplying agencies in a demanding position for optimal generation management. The utility revenue functions are highly dependent on the consumer deterministic stochastic demand models. The sudden drifts in weather parameters effects the living standards of the consumers that in turn influence the power demands. Considering above, we analyzed stochastically and statistically the effect of random consumer demands on the fixed and variable revenues of the electrical utilities. Our work presented the Multi-Variate Gaussian Distribution Function (MVGDF) probabilistic model of the utility revenues with time-dependent consumer random demands. Moreover, the Gaussian probabilities outcome of the utility revenues is based on the varying consumer n demands data-pattern. Furthermore, Standard Monte Carlo (SMC) simulations are performed that validated the factor of accuracy in the aforesaid probabilistic demand-revenue model. We critically analyzed the effect of weather data parameters on consumer demands using correlation and multi-linear regression schemes. The statistical analysis of consumer demands provided a relationship between dependent (demand) and independent variables (weather data) for utility load management, generation control, and network expansion. PMID:27314229

Stochastic and Statistical Analysis of Utility Revenues and Weather Data Analysis for Consumer Demand Estimation in Smart Grids.

PubMed

Ali, S M; Mehmood, C A; Khan, B; Jawad, M; Farid, U; Jadoon, J K; Ali, M; Tareen, N K; Usman, S; Majid, M; Anwar, S M

2016-01-01

In smart grid paradigm, the consumer demands are random and time-dependent, owning towards stochastic probabilities. The stochastically varying consumer demands have put the policy makers and supplying agencies in a demanding position for optimal generation management. The utility revenue functions are highly dependent on the consumer deterministic stochastic demand models. The sudden drifts in weather parameters effects the living standards of the consumers that in turn influence the power demands. Considering above, we analyzed stochastically and statistically the effect of random consumer demands on the fixed and variable revenues of the electrical utilities. Our work presented the Multi-Variate Gaussian Distribution Function (MVGDF) probabilistic model of the utility revenues with time-dependent consumer random demands. Moreover, the Gaussian probabilities outcome of the utility revenues is based on the varying consumer n demands data-pattern. Furthermore, Standard Monte Carlo (SMC) simulations are performed that validated the factor of accuracy in the aforesaid probabilistic demand-revenue model. We critically analyzed the effect of weather data parameters on consumer demands using correlation and multi-linear regression schemes. The statistical analysis of consumer demands provided a relationship between dependent (demand) and independent variables (weather data) for utility load management, generation control, and network expansion.

Distributed dynamic simulations of networked control and building performance applications.

PubMed

Yahiaoui, Azzedine

2018-02-01

The use of computer-based automation and control systems for smart sustainable buildings, often so-called Automated Buildings (ABs), has become an effective way to automatically control, optimize, and supervise a wide range of building performance applications over a network while achieving the minimum energy consumption possible, and in doing so generally refers to Building Automation and Control Systems (BACS) architecture. Instead of costly and time-consuming experiments, this paper focuses on using distributed dynamic simulations to analyze the real-time performance of network-based building control systems in ABs and improve the functions of the BACS technology. The paper also presents the development and design of a distributed dynamic simulation environment with the capability of representing the BACS architecture in simulation by run-time coupling two or more different software tools over a network. The application and capability of this new dynamic simulation environment are demonstrated by an experimental design in this paper.

Connecting micro dynamics and population distributions in system dynamics models

PubMed Central

Rahmandad, Hazhir; Chen, Hsin-Jen; Xue, Hong; Wang, Youfa

2014-01-01

Researchers use system dynamics models to capture the mean behavior of groups of indistinguishable population elements (e.g., people) aggregated in stock variables. Yet, many modeling problems require capturing the heterogeneity across elements with respect to some attribute(s) (e.g., body weight). This paper presents a new method to connect the micro-level dynamics associated with elements in a population with the macro-level population distribution along an attribute of interest without the need to explicitly model every element. We apply the proposed method to model the distribution of Body Mass Index and its changes over time in a sample population of American women obtained from the U.S. National Health and Nutrition Examination Survey. Comparing the results with those obtained from an individual-based model that captures the same phenomena shows that our proposed method delivers accurate results with less computation than the individual-based model. PMID:25620842

Distributed dynamic simulations of networked control and building performance applications

PubMed Central

Yahiaoui, Azzedine

2017-01-01

The use of computer-based automation and control systems for smart sustainable buildings, often so-called Automated Buildings (ABs), has become an effective way to automatically control, optimize, and supervise a wide range of building performance applications over a network while achieving the minimum energy consumption possible, and in doing so generally refers to Building Automation and Control Systems (BACS) architecture. Instead of costly and time-consuming experiments, this paper focuses on using distributed dynamic simulations to analyze the real-time performance of network-based building control systems in ABs and improve the functions of the BACS technology. The paper also presents the development and design of a distributed dynamic simulation environment with the capability of representing the BACS architecture in simulation by run-time coupling two or more different software tools over a network. The application and capability of this new dynamic simulation environment are demonstrated by an experimental design in this paper. PMID:29568135

Modeling operational behavior of a disassembly line

NASA Astrophysics Data System (ADS)

Kizilkaya, Elif A.; Gupta, Surendra M.

2004-12-01

In this paper we present a dynamic kanban (pull) system specifically developed for disassembly lines. This type of kanban system is much more complex than the traditional kanban system used in assembly lines. For instance, unlike the assembly line where the external demand occurs only at the last station, the demands in the disassembly case also occur at any of the intermittent stations. The reason is that as a product moves on the disassembly line, various parts are disassembled at every station and accumulated at that station. Therefore, there are as many demand sources as there are number of parts. We consider a case example involving the end-of-life products. Based on the precedence relationships and other criteria such as hazardous properties of the parts, we balance the disassembly line. The results of the disassembly line-balancing problem (DLBP) are used as input to the proposed dynamic kanban system for disassembly line (DKSDL). We compare the performance of the DKSDL to the modified kanban system for disassembly line (MKSDL), which was previously introduced by the authors. We show, via simulation, that the DKSDL is far superior to MKSDL considered.

Distributing vs. Blocking Learning Questions in a Web-Based Learning Environment

ERIC Educational Resources Information Center

Kapp, Felix; Proske, Antje; Narciss, Susanne; Körndle, Hermann

2015-01-01

Effective studying in web-based learning environments (web-LEs) requires cognitive engagement and demands learners to regulate their learning activities. One way to support learners in web-LEs is to provide interactive learning questions within the learning environment. Even though research on learning questions has a long tradition, there are…

Long-gauge FBGs interrogated by DTR3 for dynamic distributed strain measurement of helicopter blade model

NASA Astrophysics Data System (ADS)

Nishiyama, M.; Igawa, H.; Kasai, T.; Watanabe, N.

2014-05-01

In this paper, we describe characteristics of distributed strain sensing based on a Delayed Transmission/Reflection Ratiometric Reflectometry (DTR3) scheme with a long-gauge Fiber Bragg Grating (FBG), which is attractive to dynamic structural deformation monitoring such as a helicopter blade and an airplane wing. The DTR3 interrogator using the longgauge FBG has capability of detecting distributed strain with 50 cm spatial resolution in 100 Hz sampling rate. We evaluated distributed strain sensing characteristics of the long-gauge FBG attached on a 5.5 m helicopter blade model in static tests and free vibration dynamic tests.

A Drought Early Warning System Using System Dynamics Model and Seasonal Climate Forecasts: a case study in Hsinchu, Taiwan.

NASA Astrophysics Data System (ADS)

Tien, Yu-Chuan; Tung, Ching-Ping; Liu, Tzu-Ming; Lin, Chia-Yu

2016-04-01

In the last twenty years, Hsinchu, a county of Taiwan, has experienced a tremendous growth in water demand due to the development of Hsinchu Science Park. In order to fulfill the water demand, the government has built the new reservoir, Baoshan second reservoir. However, short term droughts still happen. One of the reasons is that the water level of the reservoirs in Hsinchu cannot be reasonably forecasted, which sometimes even underestimates the severity of drought. The purpose of this study is to build a drought early warning system that projects the water levels of two important reservoirs, Baoshan and Baoshan second reservoir, and also the spatial distribution of water shortagewith the lead time of three months. Furthermore, this study also attempts to assist the government to improve water resources management. Hence, a system dynamics model of Touchien River, which is the most important river for public water supply in Hsinchu, is developed. The model consists of several important subsystems, including two reservoirs, water treatment plants and agricultural irrigation districts. Using the upstream flow generated by seasonal weather forecasting data, the model is able to simulate the storage of the two reservoirs and the distribution of water shortage. Moreover, the model can also provide the information under certain emergency scenarios, such as the accident or failure of a water treatment plant. At last, the performance of the proposed method and the original water resource management method that the government used were also compared. Keyword: Water Resource Management, Hydrology, Seasonal Climate Forecast, Reservoir, Early Warning, Drought

Assessing air quality and climate impacts of future ground freight choice in United States

NASA Astrophysics Data System (ADS)

Liu, L.; Bond, T. C.; Smith, S.; Lee, B.; Ouyang, Y.; Hwang, T.; Barkan, C.; Lee, S.; Daenzer, K.

2013-12-01

The demand for freight transportation has continued to increase due to the growth of domestic and international trade. Emissions from ground freight (truck and railways) account for around 7% of the greenhouse gas emissions, 4% of the primary particulate matter emission and 25% of the NOx emissions in the U.S. Freight railways are generally more fuel efficient than trucks and cause less congestion. Freight demand and emissions are affected by many factors, including economic activity, the spatial distribution of demand, freight modal choice and routing decision, and the technology used in each modal type. This work links these four critical aspects of freight emission system to project the spatial distribution of emissions and pollutant concentration from ground freight transport in the U.S. between 2010 and 2050. Macroeconomic scenarios are used to forecast economic activities. Future spatial structure of employment and commodity demand in major metropolitan areas are estimated using spatial models and a shift-share model, respectively. Freight flow concentration and congestion patterns in inter-regional transportation networks are predicted from a four-step freight demand forecasting model. An asymptotic vehicle routing model is also developed to estimate delivery ton-miles for intra-regional freight shipment in metropolitan areas. Projected freight activities are then converted into impacts on air quality and climate. CO2 emissions are determined using a simple model of freight activity and fuel efficiency, and compared with the projected CO2 emissions from the Second Generation Model. Emissions of air pollutants including PM, NOx and CO are calculated with a vehicle fleet model SPEW-Trend, which incorporates the dynamic change of technologies. Emissions are projected under three economic scenarios to represent different plausible futures. Pollutant concentrations are then estimated using tagged chemical tracers in an atmospheric model with the emissions serving as input.

Modeling relief demands in an emergency supply chain system under large-scale disasters based on a queuing network.

PubMed

He, Xinhua; Hu, Wenfa

2014-01-01

This paper presents a multiple-rescue model for an emergency supply chain system under uncertainties in large-scale affected area of disasters. The proposed methodology takes into consideration that the rescue demands caused by a large-scale disaster are scattered in several locations; the servers are arranged in multiple echelons (resource depots, distribution centers, and rescue center sites) located in different places but are coordinated within one emergency supply chain system; depending on the types of rescue demands, one or more distinct servers dispatch emergency resources in different vehicle routes, and emergency rescue services queue in multiple rescue-demand locations. This emergency system is modeled as a minimal queuing response time model of location and allocation. A solution to this complex mathematical problem is developed based on genetic algorithm. Finally, a case study of an emergency supply chain system operating in Shanghai is discussed. The results demonstrate the robustness and applicability of the proposed model.

Modeling Relief Demands in an Emergency Supply Chain System under Large-Scale Disasters Based on a Queuing Network

PubMed Central

He, Xinhua

2014-01-01

This paper presents a multiple-rescue model for an emergency supply chain system under uncertainties in large-scale affected area of disasters. The proposed methodology takes into consideration that the rescue demands caused by a large-scale disaster are scattered in several locations; the servers are arranged in multiple echelons (resource depots, distribution centers, and rescue center sites) located in different places but are coordinated within one emergency supply chain system; depending on the types of rescue demands, one or more distinct servers dispatch emergency resources in different vehicle routes, and emergency rescue services queue in multiple rescue-demand locations. This emergency system is modeled as a minimal queuing response time model of location and allocation. A solution to this complex mathematical problem is developed based on genetic algorithm. Finally, a case study of an emergency supply chain system operating in Shanghai is discussed. The results demonstrate the robustness and applicability of the proposed model. PMID:24688367

Prediction-based dynamic load-sharing heuristics

NASA Technical Reports Server (NTRS)

Goswami, Kumar K.; Devarakonda, Murthy; Iyer, Ravishankar K.

1993-01-01

The authors present dynamic load-sharing heuristics that use predicted resource requirements of processes to manage workloads in a distributed system. A previously developed statistical pattern-recognition method is employed for resource prediction. While nonprediction-based heuristics depend on a rapidly changing system status, the new heuristics depend on slowly changing program resource usage patterns. Furthermore, prediction-based heuristics can be more effective since they use future requirements rather than just the current system state. Four prediction-based heuristics, two centralized and two distributed, are presented. Using trace driven simulations, they are compared against random scheduling and two effective nonprediction based heuristics. Results show that the prediction-based centralized heuristics achieve up to 30 percent better response times than the nonprediction centralized heuristic, and that the prediction-based distributed heuristics achieve up to 50 percent improvements relative to their nonprediction counterpart.

Force Reduction Impacts on Resourcing Army Operational Requirements

DTIC Science & Technology

2017-03-10

scenarios involving parametric changes to demand for and supply of manpower and equipment from the institutional Army. This type of mission- based ...i SPECIAL REPORT Force Reduction Impacts on Resourcing Army Operational Requirements By Dynamics Research Corporation In Partial... Research .................................................................................................. 12 2.1.2 Identifying and Collecting Unit

Towards the Discovery of Learner Metacognition from Reflective Writing

ERIC Educational Resources Information Center

Gibson, Andrew; Kitto, Kirsty; Bruza, Peter

2016-01-01

Modern society demands renewed attention on the competencies required to best equip students for a dynamic and uncertain future. We present exploratory work based on the premise that metacognitive and reflective competencies are essential for this task. Bringing the concepts of metacognition and reflection together into a conceptual model within…

Using Approximate Dynamic Programming to Solve the Stochastic Demand Military Inventory Routing Problem with Direct Delivery

DTIC Science & Technology

due to the dangers of utilizing convoy operations. However, enemy actions, austere conditions, and inclement weather pose a significant risk to a...squares temporal differencing for policy evaluation. We construct a representative problem instance based on an austere combat environment in order to

Model documentation: Natural gas transmission and distribution model of the National Energy Modeling System. Volume 1

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

NONE

1995-02-17

The Natural Gas Transmission and Distribution Model (NGTDM) is the component of the National Energy Modeling System (NEMS) that is used to represent the domestic natural gas transmission and distribution system. NEMS was developed in the Office of integrated Analysis and Forecasting of the Energy information Administration (EIA). NEMS is the third in a series of computer-based, midterm energy modeling systems used since 1974 by the EIA and its predecessor, the Federal Energy Administration, to analyze domestic energy-economy markets and develop projections. The NGTDM is the model within the NEMS that represents the transmission, distribution, and pricing of natural gas.more » The model also includes representations of the end-use demand for natural gas, the production of domestic natural gas, and the availability of natural gas traded on the international market based on information received from other NEMS models. The NGTDM determines the flow of natural gas in an aggregate, domestic pipeline network, connecting domestic and foreign supply regions with 12 demand regions. The methodology employed allows the analysis of impacts of regional capacity constraints in the interstate natural gas pipeline network and the identification of pipeline capacity expansion requirements. There is an explicit representation of core and noncore markets for natural gas transmission and distribution services, and the key components of pipeline tariffs are represented in a pricing algorithm. Natural gas pricing and flow patterns are derived by obtaining a market equilibrium across the three main elements of the natural gas market: the supply element, the demand element, and the transmission and distribution network that links them. The NGTDM consists of four modules: the Annual Flow Module, the Capacity F-expansion Module, the Pipeline Tariff Module, and the Distributor Tariff Module. A model abstract is provided in Appendix A.« less

Distributed dynamic large strain optical fiber sensor based on the detection of spontaneous Brillouin scattering.

PubMed

Masoudi, Ali; Belal, Mohammad; Newson, Trevor P

2013-09-01

A Brillouin-based distributed optical fiber dynamic strain sensor is described which converts strain-induced Brillouin frequency shift into optical intensity variations by using an imbalanced Mach-Zhender interferometer. A 3×3 coupler is used at the output of this interferometer to permit differentiate and cross multiply demodulation. The demonstrated sensor is capable of probing dynamic strain disturbances over 2 km of sensing length every 0.5 s up to a strain of 10 mε with an accuracy of ±50 με and spatial resolution of 1.3 m.

Distributed neural network control for adaptive synchronization of uncertain dynamical multiagent systems.

PubMed

Peng, Zhouhua; Wang, Dan; Zhang, Hongwei; Sun, Gang

2014-08-01

This paper addresses the leader-follower synchronization problem of uncertain dynamical multiagent systems with nonlinear dynamics. Distributed adaptive synchronization controllers are proposed based on the state information of neighboring agents. The control design is developed for both undirected and directed communication topologies without requiring the accurate model of each agent. This result is further extended to the output feedback case where a neighborhood observer is proposed based on relative output information of neighboring agents. Then, distributed observer-based synchronization controllers are derived and a parameter-dependent Riccati inequality is employed to prove the stability. This design has a favorable decouple property between the observer and the controller designs for nonlinear multiagent systems. For both cases, the developed controllers guarantee that the state of each agent synchronizes to that of the leader with bounded residual errors. Two illustrative examples validate the efficacy of the proposed methods.

Mitochondrial dynamics in Parkinson's disease

PubMed Central

Van Laar, Victor S.; Berman, Sarah B.

2009-01-01

The unique energy demands of neurons require well-orchestrated distribution and maintenance of mitochondria. Thus, dynamic properties of mitochondria, including fission, fusion, trafficking, biogenesis, and degradation, are critical to all cells, but may be particularly important in neurons. Dysfunction in mitochondrial dynamics has been linked to neuropathies and is increasingly being linked to several neurodegenerative diseases, but the evidence is particularly strong, and continuously accumulating, in Parkinson's disease (PD). The unique characteristics of neurons that degenerate in PD may predispose those neuronal populations to susceptibility to alterations in mitochondrial dynamics. In addition, evidence from PD-related toxins supports that mitochondrial fission, fusion, and transport may be involved in pathogenesis. Furthermore, rapidly increasing evidence suggests that two proteins linked to familial forms of the disease, parkin and PINK1, interact in a common pathway to regulate mitochondrial fission/fusion. Parkin may also play a role in maintaining mitochondrial homeostasis through targeting damaged mitochondria for mitophagy. Taken together, the current data suggests that mitochondrial dynamics may play a role in PD pathogenesis, and a better understanding of mitochondrial dynamics within the neuron may lead to future therapeutic treatments for PD, potentially aimed at some of the earliest pathogenic events. PMID:19332061

Estimating spatially specific demand and supply of dental services: a longitudinal comparison in Northern Germany.

PubMed

Schwendicke, Falk; Jäger, Ralf; Hoffmann, Wolfgang; Jordan, Rainer A; van den Berg, Neeltje

2016-09-01

Assessing the spatial distribution of oral morbidity-related demand and the workforce-related supply is relevant for planning dental services. We aimed to establish and validate a model for estimating the spatially specific demand and supply. This model was then applied to compare demand-supply ratios in 2001 and 2011 in the federal state of Mecklenburg-Vorpommern (Northern Germany). The spatial units were zip code areas. Demand per area was estimated by linking population-specific oral morbidities to working times via insurance claim data. Estimated demand was validated against the provided demand in 2001 and 2011. Supply was calculated for both years using cohort data from the dentist register. The ratio of demand and supply was geographically mapped and its distribution between areas assessed using the Gini coefficient. Between 2001 and 2011, a significant decrease of the general population (-7.0 percent), the annual demand (-13.1 percent), and the annual supply (-12.9 percent) was recorded. The estimated demands were nearly (2001: -4 percent) and completely (2011: ±0 percent) congruent with provided demands. The average demand-supply-ratio did not change significantly between 2001 and 2011 (P > 0.05), but was increasingly unequally distributed. In both years, few areas were over-serviced, while many were under-serviced. The established model can be used to estimate spatially specific demand and supply. © 2016 American Association of Public Health Dentistry.

Dynamic airspace configuration algorithms for next generation air transportation system

NASA Astrophysics Data System (ADS)

Wei, Jian

The National Airspace System (NAS) is under great pressure to safely and efficiently handle the record-high air traffic volume nowadays, and will face even greater challenge to keep pace with the steady increase of future air travel demand, since the air travel demand is projected to increase to two to three times the current level by 2025. The inefficiency of traffic flow management initiatives causes severe airspace congestion and frequent flight delays, which cost billions of economic losses every year. To address the increasingly severe airspace congestion and delays, the Next Generation Air Transportation System (NextGen) is proposed to transform the current static and rigid radar based system to a dynamic and flexible satellite based system. New operational concepts such as Dynamic Airspace Configuration (DAC) have been under development to allow more flexibility required to mitigate the demand-capacity imbalances in order to increase the throughput of the entire NAS. In this dissertation, we address the DAC problem in the en route and terminal airspace under the framework of NextGen. We develop a series of algorithms to facilitate the implementation of innovative concepts relevant with DAC in both the en route and terminal airspace. We also develop a performance evaluation framework for comprehensive benefit analyses on different aspects of future sector design algorithms. First, we complete a graph based sectorization algorithm for DAC in the en route airspace, which models the underlying air route network with a weighted graph, converts the sectorization problem into the graph partition problem, partitions the weighted graph with an iterative spectral bipartition method, and constructs the sectors from the partitioned graph. The algorithm uses a graph model to accurately capture the complex traffic patterns of the real flights, and generates sectors with high efficiency while evenly distributing the workload among the generated sectors. We further improve the robustness and efficiency of the graph based DAC algorithm by incorporating the Multilevel Graph Partitioning (MGP) method into the graph model, and develop a MGP based sectorization algorithm for DAC in the en route airspace. In a comprehensive benefit analysis, the performance of the proposed algorithms are tested in numerical simulations with Enhanced Traffic Management System (ETMS) data. Simulation results demonstrate that the algorithmically generated sectorizations outperform the current sectorizations in different sectors for different time periods. Secondly, based on our experience with DAC in the en route airspace, we further study the sectorization problem for DAC in the terminal airspace. The differences between the en route and terminal airspace are identified, and their influence on the terminal sectorization is analyzed. After adjusting the graph model to better capture the unique characteristics of the terminal airspace and the requirements of terminal sectorization, we develop a graph based geometric sectorization algorithm for DAC in the terminal airspace. Moreover, the graph based model is combined with the region based sector design method to better handle the complicated geometric and operational constraints in the terminal sectorization problem. In the benefit analysis, we identify the contributing factors to terminal controller workload, define evaluation metrics, and develop a bebefit analysis framework for terminal sectorization evaluation. With the evaluation framework developed, we demonstrate the improvements on the current sectorizations with real traffic data collected from several major international airports in the U.S., and conduct a detailed analysis on the potential benefits of dynamic reconfiguration in the terminal airspace. Finally, in addition to the research on the macroscopic behavior of a large number of aircraft, we also study the dynamical behavior of individual aircraft from the perspective of traffic flow management. We formulate the mode-confusion problem as hybrid estimation problem, and develop a state estimation algorithm for the linear hybrid system with continuous-state-dependent transitions based on sparse observations. We also develop an estimated time of arrival prediction algorithm based on the state-dependent transition hybrid estimation algorithm, whose performance is demonstrated with simulations on the landing procedure following the Continuous Descend Approach (CDA) profile.

Impact of Rate Design Alternatives on Residential Solar Customer Bills: Increased Fixed Charges, Minimum Bills and Demand-Based Rates

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

McLaren, Joyce; Davidson, Carolyn; Miller, John

Utilities are proposing changes to residential rate structures to address concerns about lost revenue due to increased adoption of distributed solar generation. An investigation of the impacts of increased fixed charges, minimum bills and residential demand charges on PV and non-PV customer bills suggests that minimum bills more accurately capture utilities' revenue requirement than fixed charges, while not acting as a disincentive to efficiency or negatively impacting low-income customers.

Network-based production quality control

NASA Astrophysics Data System (ADS)

Kwon, Yongjin; Tseng, Bill; Chiou, Richard

2007-09-01

This study investigates the feasibility of remote quality control using a host of advanced automation equipment with Internet accessibility. Recent emphasis on product quality and reduction of waste stems from the dynamic, globalized and customer-driven market, which brings opportunities and threats to companies, depending on the response speed and production strategies. The current trends in industry also include a wide spread of distributed manufacturing systems, where design, production, and management facilities are geographically dispersed. This situation mandates not only the accessibility to remotely located production equipment for monitoring and control, but efficient means of responding to changing environment to counter process variations and diverse customer demands. To compete under such an environment, companies are striving to achieve 100%, sensor-based, automated inspection for zero-defect manufacturing. In this study, the Internet-based quality control scheme is referred to as "E-Quality for Manufacturing" or "EQM" for short. By its definition, EQM refers to a holistic approach to design and to embed efficient quality control functions in the context of network integrated manufacturing systems. Such system let designers located far away from the production facility to monitor, control and adjust the quality inspection processes as production design evolves.

A methodology towards virtualisation-based high performance simulation platform supporting multidisciplinary design of complex products

NASA Astrophysics Data System (ADS)

Ren, Lei; Zhang, Lin; Tao, Fei; (Luke) Zhang, Xiaolong; Luo, Yongliang; Zhang, Yabin

2012-08-01

Multidisciplinary design of complex products leads to an increasing demand for high performance simulation (HPS) platforms. One great challenge is how to achieve high efficient utilisation of large-scale simulation resources in distributed and heterogeneous environments. This article reports a virtualisation-based methodology to realise a HPS platform. This research is driven by the issues concerning large-scale simulation resources deployment and complex simulation environment construction, efficient and transparent utilisation of fine-grained simulation resources and high reliable simulation with fault tolerance. A framework of virtualisation-based simulation platform (VSIM) is first proposed. Then the article investigates and discusses key approaches in VSIM, including simulation resources modelling, a method to automatically deploying simulation resources for dynamic construction of system environment, and a live migration mechanism in case of faults in run-time simulation. Furthermore, the proposed methodology is applied to a multidisciplinary design system for aircraft virtual prototyping and some experiments are conducted. The experimental results show that the proposed methodology can (1) significantly improve the utilisation of fine-grained simulation resources, (2) result in a great reduction in deployment time and an increased flexibility for simulation environment construction and (3)achieve fault tolerant simulation.

Using droplet-on-demand based printing to guide self-assembly in a peptide-protein based bioink

NASA Astrophysics Data System (ADS)

Hedegaard, Clara; Collin, Estelle; Redondo-Gomez, Carlos; Nguyen, Luong T. H.; Ng, Kee Woei; Castrejon-Pita, Alfonso A.; Castrejon-Pita, J. Rafael; Mata, Alvaro

2017-11-01

Tissue engineering aims to capture details of the extracellular matrix (ECM) that stimulate tissue regeneration. Advanced biofabrication techniques have enabled structural complexity, however they are restricted by the choice of material due to stringent printing requirements, leading to a lack of nanoscale control and molecular versatility. In this project, we exploit the dynamics of droplet fluid interactions combined with the co-assembly of peptide amphiphiles (PAs) with biomolecules/proteins to develop a new approach to droplet-based biofabrication. A custom-made droplet generator was developed and used to controllably dispense droplets of PA into a protein solution resulting in gel formation within milliseconds. Taking advantage of the interfacial and inertial forces during the droplet/liquid interaction, it is possible to control the co-assembly kinetics, to give rise to aligned or disordered nanofibers, hydrogel structures of different geometries and sizes, surface topographies, and higher-ordered structures made from multiple hydrogels. The process allows multiple cell types to be spatially distributed on the outside or embedded within the ECM mimetic scaffolds, whilst exhibiting high cell viability (>88%). ERC Starting Grant (STROFUNSCAFF), FP7-PEOPLE-2013-CIG Biomorph and the Royal Society.

Autonomous Agents for Dynamic Process Planning in the Flexible Manufacturing System

NASA Astrophysics Data System (ADS)

Nik Nejad, Hossein Tehrani; Sugimura, Nobuhiro; Iwamura, Koji; Tanimizu, Yoshitaka

Rapid changes of market demands and pressures of competition require manufacturers to maintain highly flexible manufacturing systems to cope with a complex manufacturing environment. This paper deals with development of an agent-based architecture of dynamic systems for incremental process planning in the manufacturing systems. In consideration of alternative manufacturing processes and machine tools, the process plans and the schedules of the manufacturing resources are generated incrementally and dynamically. A negotiation protocol is discussed, in this paper, to generate suitable process plans for the target products real-timely and dynamically, based on the alternative manufacturing processes. The alternative manufacturing processes are presented by the process plan networks discussed in the previous paper, and the suitable process plans are searched and generated to cope with both the dynamic changes of the product specifications and the disturbances of the manufacturing resources. We initiatively combine the heuristic search algorithms of the process plan networks with the negotiation protocols, in order to generate suitable process plans in the dynamic manufacturing environment.

A Transactional Approach to Children's Learning in a Knowledge-Based Society.

ERIC Educational Resources Information Center

Seng, Seok-Hoon

The 21st century promises to make very different demands on our children and schools in a knowledge-based society. A slow but dynamic shift has been occurring in the Singapore educational system toward a learning nation and thinking school ethos. In the midst of this change, children will need to acquire a new set of skills. They will need to be…

Stochastic optimization model for order acceptance with multiple demand classes and uncertain demand/supply

NASA Astrophysics Data System (ADS)

Yang, Wen; Fung, Richard Y. K.

2014-06-01

This article considers an order acceptance problem in a make-to-stock manufacturing system with multiple demand classes in a finite time horizon. Demands in different periods are random variables and are independent of one another, and replenishments of inventory deviate from the scheduled quantities. The objective of this work is to maximize the expected net profit over the planning horizon by deciding the fraction of the demand that is going to be fulfilled. This article presents a stochastic order acceptance optimization model and analyses the existence of the optimal promising policies. An example of a discrete problem is used to illustrate the policies by applying the dynamic programming method. In order to solve the continuous problems, a heuristic algorithm based on stochastic approximation (HASA) is developed. Finally, the computational results of a case example illustrate the effectiveness and efficiency of the HASA approach, and make the application of the proposed model readily acceptable.

Considering inventory distributions in a stochastic periodic inventory routing system

NASA Astrophysics Data System (ADS)

Yadollahi, Ehsan; Aghezzaf, El-Houssaine

2017-07-01

Dealing with the stochasticity of parameters is one of the critical issues in business and industry nowadays. Supply chain planners have difficulties in forecasting stochastic parameters of a distribution system. Demand rates of customers during their lead time are one of these parameters. In addition, holding a huge level of inventory at the retailers is costly and inefficient. To cover the uncertainty of forecasting demand rates, researchers have proposed the usage of safety stock to avoid stock-out. However, finding the precise level of safety stock depends on forecasting the statistical distribution of demand rates and their variations in different settings among the planning horizon. In this paper the demand rate distributions and its parameters are taken into account for each time period in a stochastic periodic IRP. An analysis of the achieved statistical distribution of the inventory and safety stock level is provided to measure the effects of input parameters on the output indicators. Different values for coefficient of variation are applied to the customers' demand rate in the optimization model. The outcome of the deterministic equivalent model of SPIRP is simulated in form of an illustrative case.

Exploring the Dynamics and Modeling National Budget as a Supply Chain System: A Proposal for Reengineering the Budgeting Process and for Developing a Management Flight Simulator

DTIC Science & Technology

2012-09-01

Elmendorf, D. W., & Gregory Mankiw , N. (1999). Government debt. Handbook of Macroeconomics , 1, 1615-1669. European Union. European financial stability...budget process, based on the supply chain demand management process principles of operations and it is introduced the idea of developing a Budget... principles of systems dynamics, a proposal for the development of a Budget Management Flight Simulator, that will operate as a learning and educational

Experimental demonstration of bandwidth on demand (BoD) provisioning based on time scheduling in software-defined multi-domain optical networks

NASA Astrophysics Data System (ADS)

Zhao, Yongli; Li, Yajie; Wang, Xinbo; Chen, Bowen; Zhang, Jie

2016-09-01

A hierarchical software-defined networking (SDN) control architecture is designed for multi-domain optical networks with the Open Daylight (ODL) controller. The OpenFlow-based Control Virtual Network Interface (CVNI) protocol is deployed between the network orchestrator and the domain controllers. Then, a dynamic bandwidth on demand (BoD) provisioning solution is proposed based on time scheduling in software-defined multi-domain optical networks (SD-MDON). Shared Risk Link Groups (SRLG)-disjoint routing schemes are adopted to separate each tenant for reliability. The SD-MDON testbed is built based on the proposed hierarchical control architecture. Then the proposed time scheduling-based BoD (Ts-BoD) solution is experimentally demonstrated on the testbed. The performance of the Ts-BoD solution is evaluated with respect to blocking probability, resource utilization, and lightpath setup latency.

Revisiting r > g-The asymptotic dynamics of wealth inequality

NASA Astrophysics Data System (ADS)

Berman, Yonatan; Shapira, Yoash

2017-02-01

Studying the underlying mechanisms of wealth inequality dynamics is essential for its understanding and for policy aiming to regulate its level. We apply a heterogeneous non-interacting agent-based modeling approach, solved using iterated maps to model the dynamics of wealth inequality based on 3 parameters-the economic output growth rate g, the capital value change rate a and the personal savings rate s and show that for a < g the wealth distribution reaches an asymptotic shape and becomes close to the income distribution. If a > g, the wealth distribution constantly becomes more and more inegalitarian. We also show that when a < g, wealth is asymptotically accumulated at the same rate as the economic output, which also implies that the wealth-disposable income ratio asymptotically converges to s /(g - a) .

Supply-demand 3D dynamic model in water resources evaluation: taking Lebanon as an example

NASA Astrophysics Data System (ADS)

Fang, Hong; Hou, Zhimin

2017-05-01

In this paper, supply-demand 3D dynamic model is adopted to create a measurement of a region’s capacity to provide available water to meet the needs of its population. First of all, we draw a diagram between supply and demand. Then taking the main dynamic factors into account, we establish an index to evaluate the balance of supply and demand. The three dimension vector reflects the scarcity of industrial, agricultural and residential water. Lebanon is chosen as the object of case study, and we do quantitative analysis of its current situation. After data collecting and processing, we calculate the 3D vector in 2012, which reveals that agriculture is susceptible to water scarcity. Water resources of Lebanon are “physical rich” but “economic scarcity” according to the correlation chart and other statistical analysis.

Making Medicare Advantage a Middle-Class Program

PubMed Central

Glazer, Jacob; McGuire, Thomas

2013-01-01

This paper studies the role of Medicare's premium policy in sorting beneficiaries between traditional Medicare (TM) and managed care plans in the Medicare Advantage (MA) program. Beneficiaries vary in their demand for care. TM fully accommodates demand but creates a moral hazard inefficiency. MA rations care but disregards some elements of the demand. We describe an efficient assignment of beneficiaries to these two options, and argue that efficiency requires an MA program oriented to serve the large middle part of the distribution of demand: the “middle class.” Current Medicare policy of a “single premium” for MA plans cannot achieve efficient sorting. We characterize the demand-based premium policy that can implement the efficient assignment of enrollees to plans. If only a single premium is feasible, the second-best policy involves too many of the low-demand individuals in MA and a too low level of services relative to the first best. We identify approaches to using premium policy to revitalize MA and improve the efficiency of Medicare. PMID:23454916

Making Medicare advantage a middle-class program.

PubMed

Glazer, Jacob; McGuire, Thomas G

2013-03-01

This paper studies the role of Medicare's premium policy in sorting beneficiaries between traditional Medicare (TM) and managed care plans in the Medicare advantage (MA) program. Beneficiaries vary in their demand for care. TM fully accommodates demand but creates a moral hazard inefficiency. MA rations care but disregards some elements of the demand. We describe an efficient assignment of beneficiaries to these two options, and argue that efficiency requires an MA program oriented to serve the large middle part of the distribution of demand: the "middle class." Current Medicare policy of a "single premium" for MA plans cannot achieve efficient sorting. We characterize the demand-based premium policy that can implement the efficient assignment of enrollees to plans. If only a single premium is feasible, the second-best policy involves too many of the low-demand individuals in MA and a too low level of services relative to the first best. We identify approaches to using premium policy to revitalize MA and improve the efficiency of Medicare. Copyright © 2012 Elsevier B.V. All rights reserved.

Hydration-Dependent Dynamical Modes in Xyloglucan from Molecular Dynamics Simulation of 13C NMR Relaxation Times and Their Distributions.

PubMed

Chen, Pan; Terenzi, Camilla; Furó, István; Berglund, Lars A; Wohlert, Jakob

2018-05-15

Macromolecular dynamics in biological systems, which play a crucial role for biomolecular function and activity at ambient temperature, depend strongly on moisture content. Yet, a generally accepted quantitative model of hydration-dependent phenomena based on local relaxation and diffusive dynamics of both polymer and its adsorbed water is still missing. In this work, atomistic-scale spatial distributions of motional modes are calculated using molecular dynamics simulations of hydrated xyloglucan (XG). These are shown to reproduce experimental hydration-dependent 13 C NMR longitudinal relaxation times ( T 1 ) at room temperature, and relevant features of their broad distributions, which are indicative of locally heterogeneous polymer reorientational dynamics. At low hydration, the self-diffusion behavior of water shows that water molecules are confined to particular locations in the randomly aggregated XG network while the average polymer segmental mobility remains low. Upon increasing water content, the hydration network becomes mobile and fully accessible for individual water molecules, and the motion of hydrated XG segments becomes faster. Yet, the polymer network retains a heterogeneous gel-like structure even at the highest level of hydration. We show that the observed distribution of relaxations times arises from the spatial heterogeneity of chain mobility that in turn is a result of heterogeneous distribution of water-chain and chain-chain interactions. Our findings contribute to the picture of hydration-dependent dynamics in other macromolecules such as proteins, DNA, and synthetic polymers, and hold important implications for the mechanical properties of polysaccharide matrixes in plants and plant-based materials.

Is health workforce planning recognising the dynamic interplay between health literacy at an individual, organisation and system level?

PubMed

Naccarella, Lucio; Wraight, Brenda; Gorman, Des

2016-02-01

The growing demands on the health system to adapt to constant change has led to investment in health workforce planning agencies and approaches. Health workforce planning approaches focusing on identifying, predicting and modelling workforce supply and demand are criticised as being simplistic and not contributing to system-level resiliency. Alternative evidence- and needs-based health workforce planning approaches are being suggested. However, to contribute to system-level resiliency, workforce planning approaches need to also adopt system-based approaches. The increased complexity and fragmentation of the healthcare system, especially for patients with complex and chronic conditions, has also led to a focus on health literacy not simply as an individual trait, but also as a dynamic product of the interaction between individual (patients, workforce)-, organisational- and system-level health literacy. Although it is absolutely essential that patients have a level of health literacy that enables them to navigate and make decisions, so too the health workforce, organisations and indeed the system also needs to be health literate. Herein we explore whether health workforce planning is recognising the dynamic interplay between health literacy at an individual, organisation and system level, and the potential for strengthening resiliency across all those levels.

A New Approach to Site Demand-Based Level Inventory Optimization

DTIC Science & Technology

2016-06-01

Command (2016) Navy supply chain management. Accessed April 17, 2016, https://www.navsup.navy.mil/navsup/capabilities/nscm Salmeron J, Craparo E (2016...Engineering 53: 122-142. Naval Supply Systems Command (2016a) Navy supply chain management. Accessed April 17, 2016, https://www.navsup.navy.mil...distribution is unlimited 12b. DISTRIBUTION CODE 13. ABSTRACT (maximum 200 words) Naval Supply Systems Command (NAVSUP) supports Navy, Marine Corps

Dynamic modeling of hybrid renewable energy systems for off-grid applications

NASA Astrophysics Data System (ADS)

Hasemeyer, Mark David

The volatile prices of fossil fuels and their contribution to global warming have caused many people to turn to renewable energy systems. Many developing communities are forced to use these systems as they are too far from electrical distribution. As a result, numerous software models have been developed to simulate hybrid renewable energy systems. However almost, if not all, implementations are static in design. A static design limits the ability of the model to account for changes over time. Dynamic modeling can be used to fill the gaps where other modeling techniques fall short. This modeling practice allows the user to account for the effects of technological and economic factors over time. These factors can include changes in energy demand, energy production, and income level. Dynamic modeling can be particularly useful for developing communities who are off-grid and developing at rapid rates. In this study, a dynamic model was used to evaluate a real world system. A non-governmental organization interested in improving their current infrastructure was selected. Five different scenarios were analyzed and compared in order to discover which factors the model is most sensitive to. In four of the scenarios, a new energy system was purchased in order to account for the opening of a restaurant that would be used as a source of local income generation. These scenarios were then compared to a base case in which a new system was not purchased, and the restaurant was not opened. Finally, the results were used to determine which variables had the greatest impact on the various outputs of the simulation.

Quality of service management framework for dynamic chaining of geographic information services

NASA Astrophysics Data System (ADS)

Onchaga, Richard

2006-06-01

Dynamic chaining of geographic information services (geo-services) is gaining popularity as a new paradigm for evolving flexible geo-information systems and for providing on-demand access to geo-information. In dynamic chaining, disparate geo-services are discovered and composed at run time to yield more elaborate functionality and create value-added geo-information. Common approaches to service chaining discover and compose disparate geo-services based on the functional capability of individual geo-services. The primary concern of common approaches is thus the emergent behavior of the resulting composite geo-service. However, as geo-services become mundane and take on a greater and more strategic role in mission critical processes, deliverable quality of service (QoS) becomes an important concern. QoS concerns operational characteristics of a service that determine its utility in an application context. To address pertinent QoS requirements, a new approach to service chaining becomes necessary. In this paper we propose a QoS-aware chaining approach in which geo-services are discovered, composed and executed considering both functional and QoS requirements. We prescribe a QoS management framework that defines fundamental principles, concepts and mechanisms which can be applied to evolve an effective distributed computing platform for QoS-aware chaining of geo-services - the so-called geo-service infrastructure. The paper also defines an extensible QoS model for services delivered by dynamic compositions of geo-services. The process of orthophoto generation is used to demonstrate the applicability of the prescribed framework to service-oriented geographic information processing.

A quasi-molecular dynamics simulation study on the effect of particles collisions in pulsed-laser desorption

NASA Astrophysics Data System (ADS)

Xinyu-Tan; Duanming-Zhang; Shengqin-Feng; Li, Zhi-hua; Li, Guan; Li, Li; Dan, Liu

2006-05-01

The dynamics characteristic and effect of atoms and particulates ejected from the surface generated by nanosecond pulsed-laser ablation are very important. In this work, based on the consideration of the inelasticity and non-uniformity of the plasma particles thermally desorbed from a plane surface into vacuum induced by nanosecond laser ablation, the one-dimensional particles flow is studied on the basis of a quasi-molecular dynamics (QMD) simulation. It is assumed that atoms and particulates ejected from the surface of a target have a Maxwell velocity distribution corresponding to the surface temperature. Particles collisions in the ablation plume. The particles mass is continuous and satisfies fractal theory distribution. Meanwhile, the particles are inelastic. Our results show that inelasticity and non-uniformity strongly affect the dynamics behavior of the particles flow. Along with the decrease of restitution coefficient e and increase of fractional dimension D, velocity distributions of plasma particles system all deviate from the initial Gaussian distribution. The increasing of dissipation energy ΔE leads to density distribution clusterized and closed up to the center mass. Predictions of the particles action based on the proposed fractal and inelasticity model are found to be in agreement with the experimental observation. This verifies the validity of the present model for the dynamics behavior of pulsed-laser-induced particles flow.

Efficiency of a novel "Food to waste to food" system including anaerobic digestion of food waste and cultivation of vegetables on digestate in a bubble-insulated greenhouse.

PubMed

Stoknes, K; Scholwin, F; Krzesiński, W; Wojciechowska, E; Jasińska, A

2016-10-01

At urban locations certain challenges are concentrated: organic waste production, the need for waste treatment, energy demand, food demand, the need for circular economy and limited area for food production. Based on these factors the project presented here developed a novel technological approach for processing organic waste into new food. In this system, organic waste is converted into biogas and digester residue. The digester residue is being used successfully as a stand-alone fertilizer as well as main substrate component for vegetables and mushrooms for the first time - a "digeponics" system - in a closed new low energy greenhouse system with dynamic soap bubble insulation. Biogas production provides energy for the process and CO2 for the greenhouse. With very limited land use highly efficient resource recycling was established at pilot scale. In the research project it was proven that a low energy dynamic bubble insulated greenhouse can be operated continuously with 80% energy demand reduction compared to conventional greenhouses. Commercial crop yields were achieved based on fertilization with digestate; in individual cases they were even higher than the control yields of vegetables such as tomatoes, cucumber and lettuce among others. For the first time an efficient direct use of digestate as substrate and fertilizer has been developed and demonstrated. Copyright © 2016 Elsevier Ltd. All rights reserved.

Reliability evaluation of microgrid considering incentive-based demand response

NASA Astrophysics Data System (ADS)

Huang, Ting-Cheng; Zhang, Yong-Jun

2017-07-01

Incentive-based demand response (IBDR) can guide customers to adjust their behaviour of electricity and curtail load actively. Meanwhile, distributed generation (DG) and energy storage system (ESS) can provide time for the implementation of IBDR. The paper focus on the reliability evaluation of microgrid considering IBDR. Firstly, the mechanism of IBDR and its impact on power supply reliability are analysed. Secondly, the IBDR dispatch model considering customer’s comprehensive assessment and the customer response model are developed. Thirdly, the reliability evaluation method considering IBDR based on Monte Carlo simulation is proposed. Finally, the validity of the above models and method is studied through numerical tests on modified RBTS Bus6 test system. Simulation results demonstrated that IBDR can improve the reliability of microgrid.

Data collapse and critical dynamics in neuronal avalanche data

NASA Astrophysics Data System (ADS)

Butler, Thomas; Friedman, Nir; Dahmen, Karin; Beggs, John; Deville, Lee; Ito, Shinya

2012-02-01

The tasks of information processing, computation, and response to stimuli require neural computation to be remarkably flexible and diverse. To optimally satisfy the demands of neural computation, neuronal networks have been hypothesized to operate near a non-equilibrium critical point. In spite of their importance for neural dynamics, experimental evidence for critical dynamics has been primarily limited to power law statistics that can also emerge from non-critical mechanisms. By tracking the firing of large numbers of synaptically connected cortical neurons and comparing the resulting data to the predictions of critical phenomena, we show that cortical tissues in vitro can function near criticality. Among the most striking predictions of critical dynamics is that the mean temporal profiles of avalanches of widely varying durations are quantitatively described by a single universal scaling function (data collapse). We show for the first time that this prediction is confirmed in neuronal networks. We also show that the data have three additional features predicted by critical phenomena: approximate power law distributions of avalanche sizes and durations, samples in subcritical and supercritical phases, and scaling laws between anomalous exponents.

Distributed interactive virtual environments for collaborative experiential learning and training independent of distance over Internet2.

PubMed

Alverson, Dale C; Saiki, Stanley M; Jacobs, Joshua; Saland, Linda; Keep, Marcus F; Norenberg, Jeffrey; Baker, Rex; Nakatsu, Curtis; Kalishman, Summers; Lindberg, Marlene; Wax, Diane; Mowafi, Moad; Summers, Kenneth L; Holten, James R; Greenfield, John A; Aalseth, Edward; Nickles, David; Sherstyuk, Andrei; Haines, Karen; Caudell, Thomas P

2004-01-01

Medical knowledge and skills essential for tomorrow's healthcare professionals continue to change faster than ever before creating new demands in medical education. Project TOUCH (Telehealth Outreach for Unified Community Health) has been developing methods to enhance learning by coupling innovations in medical education with advanced technology in high performance computing and next generation Internet2 embedded in virtual reality environments (VRE), artificial intelligence and experiential active learning. Simulations have been used in education and training to allow learners to make mistakes safely in lieu of real-life situations, learn from those mistakes and ultimately improve performance by subsequent avoidance of those mistakes. Distributed virtual interactive environments are used over distance to enable learning and participation in dynamic, problem-based, clinical, artificial intelligence rules-based, virtual simulations. The virtual reality patient is programmed to dynamically change over time and respond to the manipulations by the learner. Participants are fully immersed within the VRE platform using a head-mounted display and tracker system. Navigation, locomotion and handling of objects are accomplished using a joy-wand. Distribution is managed via the Internet2 Access Grid using point-to-point or multi-casting connectivity through which the participants can interact. Medical students in Hawaii and New Mexico (NM) participated collaboratively in problem solving and managing of a simulated patient with a closed head injury in VRE; dividing tasks, handing off objects, and functioning as a team. Students stated that opportunities to make mistakes and repeat actions in the VRE were extremely helpful in learning specific principles. VRE created higher performance expectations and some anxiety among VRE users. VRE orientation was adequate but students needed time to adapt and practice in order to improve efficiency. This was also demonstrated successfully between Western Australia and UNM. We successfully demonstrated the ability to fully immerse participants in a distributed virtual environment independent of distance for collaborative team interaction in medical simulation designed for education and training. The ability to make mistakes in a safe environment is well received by students and has a positive impact on their understanding, as well as memory of the principles involved in correcting those mistakes. Bringing people together as virtual teams for interactive experiential learning and collaborative training, independent of distance, provides a platform for distributed "just-in-time" training, performance assessment and credentialing. Further validation is necessary to determine the potential value of the distributed VRE in knowledge transfer, improved future performance and should entail training participants to competence in using these tools.

Predicting dynamic metabolic demands in the photosynthetic eukaryote Chlorella vulgaris

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

Zuniga, Cristal; Levering, Jennifer; Antoniewicz, Maciek R.

Phototrophic organisms exhibit a highly dynamic proteome, adapting their biomass composition in response to diurnal light/dark cycles and nutrient availability. We used experimentally determined biomass compositions over the course of growth to determine and constrain the biomass objective function (BOF) in a genome-scale metabolic model of Chlorella vulgaris UTEX 395 over time. Changes in the BOF, which encompasses all metabolites necessary to produce biomass, influence the state of the metabolic network thus directly affecting predictions. Simulations using dynamic BOFs predicted distinct proteome demands during heterotrophic or photoautotrophic growth. Model-driven analysis of extracellular nitrogen concentrations and predicted nitrogen uptake rates revealedmore » an intracellular nitrogen pool, which contains 38% of the total nitrogen provided in the medium for photoautotrophic and 13% for heterotrophic growth. Agreement between flux and gene expression trends was determined by statistical comparison. Accordance between predicted fluxes trends and gene expression trends was found for 65% of multi-subunit enzymes and 75% of allosteric reactions. Reactions with the highest agreement between simulations and experimental data were associated with energy metabolism, terpenoid biosynthesis, fatty acids, nucleotides, and amino acids metabolism. Moreover, predicted flux distributions at each time point were compared with gene expression data to gain new insights into intracellular compartmentalization, specifically for transporters. A total of 103 genes related to internal transport reactions were identified and added to the updated model of C. vulgaris, iCZ946, thus increasing our knowledgebase by 10% for this model green alga.« less

Predicting dynamic metabolic demands in the photosynthetic eukaryote Chlorella vulgaris

DOE PAGES

Zuniga, Cristal; Levering, Jennifer; Antoniewicz, Maciek R.; ...

2017-09-26

Phototrophic organisms exhibit a highly dynamic proteome, adapting their biomass composition in response to diurnal light/dark cycles and nutrient availability. We used experimentally determined biomass compositions over the course of growth to determine and constrain the biomass objective function (BOF) in a genome-scale metabolic model of Chlorella vulgaris UTEX 395 over time. Changes in the BOF, which encompasses all metabolites necessary to produce biomass, influence the state of the metabolic network thus directly affecting predictions. Simulations using dynamic BOFs predicted distinct proteome demands during heterotrophic or photoautotrophic growth. Model-driven analysis of extracellular nitrogen concentrations and predicted nitrogen uptake rates revealedmore » an intracellular nitrogen pool, which contains 38% of the total nitrogen provided in the medium for photoautotrophic and 13% for heterotrophic growth. Agreement between flux and gene expression trends was determined by statistical comparison. Accordance between predicted fluxes trends and gene expression trends was found for 65% of multi-subunit enzymes and 75% of allosteric reactions. Reactions with the highest agreement between simulations and experimental data were associated with energy metabolism, terpenoid biosynthesis, fatty acids, nucleotides, and amino acids metabolism. Moreover, predicted flux distributions at each time point were compared with gene expression data to gain new insights into intracellular compartmentalization, specifically for transporters. A total of 103 genes related to internal transport reactions were identified and added to the updated model of C. vulgaris, iCZ946, thus increasing our knowledgebase by 10% for this model green alga.« less

Scenarios of land use change for agriculture: the role of Land Evaluation in improving model simulation

NASA Astrophysics Data System (ADS)

Mereu, V.; Santini, M.; Dettori, G.; Muresu, P.; Spano, D.; Duce, P.

2009-12-01

Integrated scenarios of future climate and land use represent a useful input for impact studies about global changes. In particular, improving future land use simulations is essential for the agricultural sector, which is influenced by both biogeophysical constraints and human needs. Often land use change models are mainly based on statistical relationships between known land use distribution and biophysical or socio-economic factors, neglecting the necessary consideration of physical constraints that interact in making lands more or less capable for agriculture and suitable for supporting specific crops. In this study, a well developed land use change model (CLUE@CMCC) was suited for the Mediterranean basin case study, focusing on croplands. Several climate scenarios and future demands for croplands were combined to drive the model, while the same climate scenarios were used to more reliably allocate crops in the most suitable areas on the basis of Land Evaluation techniques. The probability for each map unit to sustain a specific crop, usually related to location characteristics, elasticity to conversion and competition among land use types, now includes specific crop-favoring location characteristics. Results, besides improving the consistency of the land use change model to allocate land for the future, can have the main feedback to suggest feasibility or reasonable thresholds to adjust land use demands during dynamic simulations.

[Ecological carrying capacity and Chongming Island's ecological construction].

PubMed

Wang, Kaiyun; Zou, Chunjing; Kong, Zhenghong; Wang, Tianhou; Chen, Xiaoyong

2005-12-01

This paper overviewed the goals of Chongming Island's ecological construction and its background, analyzed the current eco-economic status and constraints of the Island, and put forward some scientific issues on its ecological construction. It was suggested that for the resources-saving and sustainable development of the Island, the researches on its ecological construction should be based on its ecological carrying capacity, fully take the regional characteristics into consideration, and refer the successful development modes at home and abroad. The carrying capacity study should ground on systemic and dynamic views, give a thorough evaluation of the Island's present carrying capacity, simulate its possible changes, and forecast its demands and risks. Operable countermeasures to promote the Island's carrying capacity should be worked out, new industry structure, population scale, and optimized distribution projects conforming to regional carrying capacity should be formulated, and effective ecological security alarming and control system should be built, with the aim of providing suggestions and strategic evidences for the decision-making of economic development and sustainable environmental resources use of the region.

Tools for Analyzing Computing Resource Management Strategies and Algorithms for SDR Clouds

NASA Astrophysics Data System (ADS)

Marojevic, Vuk; Gomez-Miguelez, Ismael; Gelonch, Antoni

2012-09-01

Software defined radio (SDR) clouds centralize the computing resources of base stations. The computing resource pool is shared between radio operators and dynamically loads and unloads digital signal processing chains for providing wireless communications services on demand. Each new user session request particularly requires the allocation of computing resources for executing the corresponding SDR transceivers. The huge amount of computing resources of SDR cloud data centers and the numerous session requests at certain hours of a day require an efficient computing resource management. We propose a hierarchical approach, where the data center is divided in clusters that are managed in a distributed way. This paper presents a set of computing resource management tools for analyzing computing resource management strategies and algorithms for SDR clouds. We use the tools for evaluating a different strategies and algorithms. The results show that more sophisticated algorithms can achieve higher resource occupations and that a tradeoff exists between cluster size and algorithm complexity.

TROPHIC DYNAMICS OF STRIPED BASS IN SMITH MOUNTAIN LAKE, VIRGINIA

EPA Science Inventory

We examined the adequacy of the forage base to meet demand of striped bass in Smith Mountain Lake, Virginia. In regards to prey supply, mean alewife biomass from 1993-1998 was 37 kg/ha and mean gizzard shad biomass from 1990-1997 was 112 kg/ha. Mean annual alewife surplus produ...

North American pulp & paper model (NAPAP)

Treesearch

Peter J. Ince; Joseph Buongiorno

2007-01-01

This chapter describes the development and structure of the NAPAP model and compares it to other forest sector models. The NAPAP model was based on PELPS and adapted to describe paper and paperboard product demand, pulpwood and recovered paper supply, and production capacity and technology, with spatially dynamic market equilibria. We describe how the model predicts...

Examining sufficiency and equity in the geographic distribution of physicians in Japan: a longitudinal study.

PubMed

Hara, Koji; Otsubo, Tetsuya; Kunisawa, Susumu; Imanaka, Yuichi

2017-03-14

The objective of this study was to longitudinally examine the geographic distribution of physicians in Japan with adjustment for healthcare demand according to changes in population age structure. We examined trends in the number of physicians per 100 000 population in Japan's secondary medical areas (SMAs) from 2000 to 2014. Healthcare demand was adjusted using health expenditure per capita. Trends in the Gini coefficient and the number of SMAs with a low physician supply were analysed. A subgroup analysis was also conducted where SMAs were divided into 4 groups according to urban-rural classification and initial physician supply. The time-based changes in the Gini coefficient and the number of SMAs with a low physician supply indicated that the equity in physician distribution had worsened throughout the study period. The number of physicians per 100 000 population had seemingly increased in all groups, with increases of 22.9% and 34.5% in urban groups with higher and lower initial physician supply, respectively. However, after adjusting healthcare demand, physician supply decreased by 1.3% in the former group and increased by 3.5% in the latter group. Decreases were also observed in the rural groups, where the number of physicians decreased by 4.4% in the group with a higher initial physician supply and 7.6% in the group with a lower initial physician supply. Although the total number of physicians increased in Japan, demand-adjusted physician supply decreased in recent years in all areas except for urban areas with a lower initial physician supply. In addition, the equity of physician distribution had consistently deteriorated since 2000. The results indicate that failing to adjust healthcare demand will produce misleading results, and that there is a need for major reform of Japan's healthcare system to improve physician distribution. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Starting a sleep center.

PubMed

Epstein, Lawrence J; Valentine, Paul S

2010-05-01

The demand for sleep medicine services has grown tremendously during the last decade and will likely continue. To date, growth in demand has been met by growth in the number of new sleep centers. The need for more new centers will be dependent on market drivers that include increasing regulatory requirements, personnel shortages, integration of home sleep testing, changes in reimbursement, a shift in emphasis from diagnostics to treatment, and an increased consumer focus on sleep. The decision to open a new center should be based on understanding the market dynamics, completing a market analysis, and developing a business plan. The business plan should include an overview of the facility, a personnel and organizational structure, an evaluation of the business environment, a financial plan, a description of services provided, and a strategy for obtaining, managing, and extending a referral base. Implementation of the business plan and successful operation require ongoing planning and monitoring of operational parameters. The need for new sleep centers will likely continue, but the shifting market dynamics indicate a greater need for understanding the marketplace and careful planning.

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

Melton, Ron

The Pacific Northwest Smart Grid Demonstration (PNWSGD), a $179 million project that was co-funded by the U.S. Department of Energy (DOE) in late 2009, was one of the largest and most comprehensive demonstrations of electricity grid modernization ever completed. The project was one of 16 regional smart grid demonstrations funded by the American Recovery and Reinvestment Act. It was the only demonstration that included multiple states and cooperation from multiple electric utilities, including rural electric co-ops, investor-owned, municipal, and other public utilities. No fewer than 55 unique instantiations of distinct smart grid systems were demonstrated at the projects’ sites. Themore » local objectives for these systems included improved reliability, energy conservation, improved efficiency, and demand responsiveness. The demonstration developed and deployed an innovative transactive system, unique in the world, that coordinated many of the project’s distributed energy resources and demand-responsive components. With the transactive system, additional regional objectives were also addressed, including the mitigation of renewable energy intermittency and the flattening of system load. Using the transactive system, the project coordinated a regional response across the 11 utilities. This region-wide connection from the transmission system down to individual premises equipment was one of the major successes of the project. The project showed that this can be done and assets at the end points can respond dynamically on a wide scale. In principle, a transactive system of this type might eventually help coordinate electricity supply, transmission, distribution, and end uses by distributing mostly automated control responsibilities among the many distributed smart grid domain members and their smart devices.« less

Electric terminal performance and characterization of solid oxide fuel cells and systems

NASA Astrophysics Data System (ADS)

Lindahl, Peter Allan

Solid Oxide Fuel Cells (SOFCs) are electrochemical devices which can effect efficient, clean, and quiet conversion of chemical to electrical energy. In contrast to conventional electricity generation systems which feature multiple discrete energy conversion processes, SOFCs are direct energy conversion devices. That is, they feature a fully integrated chemical to electrical energy conversion process where the electric load demanded of the cell intrinsically drives the electrochemical reactions and associated processes internal to the cell. As a result, the cell's electric terminals provide a path for interaction between load side electric demand and the conversion side processes. The implication of this is twofold. First, the magnitude and dynamic characteristics of the electric load demanded of the cell can directly impact the long-term efficacy of the cell's chemical to electrical energy conversion. Second, the electric terminal response to dynamic loads can be exploited for monitoring the cell's conversion side processes and used in diagnostic analysis and degradation-mitigating control schemes. This dissertation presents a multi-tier investigation into this electric terminal based performance characterization of SOFCs through the development of novel test systems, analysis techniques and control schemes. First, a reference-based simulation system is introduced. This system scales up the electric terminal performance of a prototype SOFC system, e.g. a single fuel cell, to that of a full power-level stack. This allows realistic stack/load interaction studies while maintaining explicit ability for post-test analysis of the prototype system. Next, a time-domain least squares fitting method for electrochemical impedance spectroscopy (EIS) is developed for reduced-time monitoring of the electrochemical and physicochemical mechanics of the fuel cell through its electric terminals. The utility of the reference-based simulator and the EIS technique are demonstrated through their combined use in the performance testing of a hybrid-source power management (HSPM) system designed to allow in-situ EIS monitoring of a stack under dynamic loading conditions. The results from the latter study suggest that an HSPM controller allows an opportunity for in-situ electric terminal monitoring and control-based mitigation of SOFC degradation. As such, an exploration of control-based SOFC degradation mitigation is presented and ideas for further work are suggested.

Dynamic virtual machine allocation policy in cloud computing complying with service level agreement using CloudSim

NASA Astrophysics Data System (ADS)

Aneri, Parikh; Sumathy, S.

2017-11-01

Cloud computing provides services over the internet and provides application resources and data to the users based on their demand. Base of the Cloud Computing is consumer provider model. Cloud provider provides resources which consumer can access using cloud computing model in order to build their application based on their demand. Cloud data center is a bulk of resources on shared pool architecture for cloud user to access. Virtualization is the heart of the Cloud computing model, it provides virtual machine as per application specific configuration and those applications are free to choose their own configuration. On one hand, there is huge number of resources and on other hand it has to serve huge number of requests effectively. Therefore, resource allocation policy and scheduling policy play very important role in allocation and managing resources in this cloud computing model. This paper proposes the load balancing policy using Hungarian algorithm. Hungarian Algorithm provides dynamic load balancing policy with a monitor component. Monitor component helps to increase cloud resource utilization by managing the Hungarian algorithm by monitoring its state and altering its state based on artificial intelligent. CloudSim used in this proposal is an extensible toolkit and it simulates cloud computing environment.

Simulating Forest Dynamics of Lowland Rainforests in Eastern Madagascar

NASA Technical Reports Server (NTRS)

Armstrong, Amanda; Fischer, Rico; Huth, Andreas; Shugart, Herman; Fatoyinbo, Temilola

2018-01-01

Ecological modeling and forecasting are essential tools for the understanding of complex vegetation dynamics. The parametric demands of some of these models are often lacking or scant for threatened ecosystems, particularly in diverse tropical ecosystems. One such ecosystem and also one of the world's biodiversity hotspots, Madagascar's lowland rainforests, have disappeared at an alarming rate. The processes that drive tree species growth and distribution remain as poorly understood as the species themselves. We investigated the application of the process-based individual-based FORMIND model to successfully simulate a Madagascar lowland rainforest using previously collected multi-year forest inventory plot data. We inspected the model's ability to characterize growth and species abundance distributions over the study site, and then validated the model with an independently collected forest-inventory dataset from another lowland rainforest in eastern Madagascar. Following a comparative analysis using inventory data from the two study sites, we found that FORMIND accurately captures the structure and biomass of the study forest, with r(squared) values of 0.976, 0.895, and 0.995 for 1:1 lines comparing observed and simulated values across all plant functional types for aboveground biomass (tonnes/ha), stem numbers, and basal area (m(squared)/ha), respectively. Further, in validation with a second study forest site, FORMIND also compared well, only slightly over-estimating shade-intermediate species as compared to the study site, and slightly under-representing shade-tolerant species in percentage of total aboveground biomass. As an important application of the FORMIND model, we measured the net ecosystem exchange (NEE, in tons of carbon per hectare per year) for 50 ha of simulated forest over a 1000-year run from bare ground. We found that NEE values ranged between 1 and -1 t Cha(exp -1)year(exp -1), consequently the study forest can be considered as a net neutral or a very slight carbon sink ecosystem, after the initial 130 years of growth. Our study found that FORMIND represents a valuable tool toward simulating forest dynamics in the immensely diverse Madagascar rainforests.

Geographic information systems (GIS): an emerging method to assess demand and provision for rehabilitation services.

PubMed

Passalent, Laura; Borsy, Emily; Landry, Michel D; Cott, Cheryl

2013-09-01

To illustrate the application of geographic information systems (GIS) as a tool to assess rehabilitation service delivery by presenting results from research recently conducted to assess demand and provision for community rehabilitation service delivery in Ontario, Canada. Secondary analysis of data obtained from existing sources was used to establish demand and provision profiles for community rehabilitation services. These data were integrated using GIS software. A number of descriptive maps were produced that show the geographical distribution of service provision variables (location of individual rehabilitation health care providers and location of private and publicly funded community rehabilitation clinics) in relation to the distribution of demand variables (location of the general population; location of specific populations (i.e., residents age 65 and older) and distribution of household income). GIS provides a set of tools for describing and understanding the spatial organization of the health of populations and the distribution of health services that can aid the development of health policy and answer key research questions with respect to rehabilitation health services delivery. Implications for Rehabilitation It is important to seek out alternative and innovative methods to examine rehabilitation service delivery. GIS is a computer-based program that takes any data linked to a geographically referenced location and processes it through a software system that manages, analyses and displays the data in the form of a map, allowing for an alternative level of analysis. GIS provides a set of tools for describing and understanding the spatial organization of population health and health services that can aid the development of health policy and answer key research questions with respect to rehabilitation health services delivery.

Estimation of Operating Condition of Appliances Using Circuit Current Data on Electric Distribution Boards

NASA Astrophysics Data System (ADS)

Iwafune, Yumiko; Ogimoto, Kazuhiko; Yagita, Yoshie

The Energy management systems (EMS) on demand sides are expected as a method to enhance the capability of supply and demand balancing of a power system under the anticipated penetration of renewable energy generation such as Photovoltaics (PV). Elucidation of energy consumption structure in a building is one of important elements for realization of EMS and contributes to the extraction of potential energy saving. In this paper, we propose the estimation method of operating condition of household appliances using circuit current data on an electric distribution board. Circuit current data are broken down by their shape using a self-organization map method and aggregated by appliance based on customers' information of appliance possessed. Proposed method is verified using residential energy consumption measurement survey data.

Toward On-Demand Deep Brain Stimulation Using Online Parkinson's Disease Prediction Driven by Dynamic Detection.

PubMed

Mohammed, Ameer; Zamani, Majid; Bayford, Richard; Demosthenous, Andreas

2017-12-01

In Parkinson's disease (PD), on-demand deep brain stimulation is required so that stimulation is regulated to reduce side effects resulting from continuous stimulation and PD exacerbation due to untimely stimulation. Also, the progressive nature of PD necessitates the use of dynamic detection schemes that can track the nonlinearities in PD. This paper proposes the use of dynamic feature extraction and dynamic pattern classification to achieve dynamic PD detection taking into account the demand for high accuracy, low computation, and real-time detection. The dynamic feature extraction and dynamic pattern classification are selected by evaluating a subset of feature extraction, dimensionality reduction, and classification algorithms that have been used in brain-machine interfaces. A novel dimensionality reduction technique, the maximum ratio method (MRM) is proposed, which provides the most efficient performance. In terms of accuracy and complexity for hardware implementation, a combination having discrete wavelet transform for feature extraction, MRM for dimensionality reduction, and dynamic k-nearest neighbor for classification was chosen as the most efficient. It achieves a classification accuracy of 99.29%, an F1-score of 97.90%, and a choice probability of 99.86%.

Hybrid power system intelligent operation and protection involving distributed architectures and pulsed loads

NASA Astrophysics Data System (ADS)

Mohamed, Ahmed

Efficient and reliable techniques for power delivery and utilization are needed to account for the increased penetration of renewable energy sources in electric power systems. Such methods are also required for current and future demands of plug-in electric vehicles and high-power electronic loads. Distributed control and optimal power network architectures will lead to viable solutions to the energy management issue with high level of reliability and security. This dissertation is aimed at developing and verifying new techniques for distributed control by deploying DC microgrids, involving distributed renewable generation and energy storage, through the operating AC power system. To achieve the findings of this dissertation, an energy system architecture was developed involving AC and DC networks, both with distributed generations and demands. The various components of the DC microgrid were designed and built including DC-DC converters, voltage source inverters (VSI) and AC-DC rectifiers featuring novel designs developed by the candidate. New control techniques were developed and implemented to maximize the operating range of the power conditioning units used for integrating renewable energy into the DC bus. The control and operation of the DC microgrids in the hybrid AC/DC system involve intelligent energy management. Real-time energy management algorithms were developed and experimentally verified. These algorithms are based on intelligent decision-making elements along with an optimization process. This was aimed at enhancing the overall performance of the power system and mitigating the effect of heavy non-linear loads with variable intensity and duration. The developed algorithms were also used for managing the charging/discharging process of plug-in electric vehicle emulators. The protection of the proposed hybrid AC/DC power system was studied. Fault analysis and protection scheme and coordination, in addition to ideas on how to retrofit currently available protection concepts and devices for AC systems in a DC network, were presented. A study was also conducted on the effect of changing the distribution architecture and distributing the storage assets on the various zones of the network on the system's dynamic security and stability. A practical shipboard power system was studied as an example of a hybrid AC/DC power system involving pulsed loads. Generally, the proposed hybrid AC/DC power system, besides most of the ideas, controls and algorithms presented in this dissertation, were experimentally verified at the Smart Grid Testbed, Energy Systems Research Laboratory. All the developments in this dissertation were experimentally verified at the Smart Grid Testbed.

A Hybrid TDMA/CSMA-Based Wireless Sensor and Data Transmission Network for ORS Intra-Microsatellite Applications

PubMed Central

Wang, Long; Liu, Yong; Yin, Zengshan

2018-01-01

To achieve launch-on-demand for Operationally Responsive Space (ORS) missions, in this article, an intra-satellite wireless network (ISWN) is presented. It provides a wireless and modularized scheme for intra-spacecraft sensing and data buses. By removing the wired data bus, the commercial off-the-shelf (COTS) based wireless modular architecture will reduce both the volume and weight of the satellite platform, thus achieving rapid design and cost savings in development and launching. Based on the on-orbit data demand analysis, a hybrid time division multiple access/carrier sense multiple access (TDMA/CSMA) protocol is proposed. It includes an improved clear channel assessment (CCA) mechanism and a traffic adaptive slot allocation method. To analyze the access process, a Markov model is constructed. Then a detailed calculation is given in which the unsaturated cases are considered. Through simulations, the proposed protocol is proved to commendably satisfy the demands and performs better than existing schemes. It helps to build a full-wireless satellite instead of the current wired ones, and will contribute to provide dynamic space capabilities for ORS missions. PMID:29757243

A Hybrid TDMA/CSMA-Based Wireless Sensor and Data Transmission Network for ORS Intra-Microsatellite Applications.

PubMed

Wang, Long; Liu, Yong; Yin, Zengshan

2018-05-12

To achieve launch-on-demand for Operationally Responsive Space (ORS) missions, in this article, an intra-satellite wireless network (ISWN) is presented. It provides a wireless and modularized scheme for intra-spacecraft sensing and data buses. By removing the wired data bus, the commercial off-the-shelf (COTS) based wireless modular architecture will reduce both the volume and weight of the satellite platform, thus achieving rapid design and cost savings in development and launching. Based on the on-orbit data demand analysis, a hybrid time division multiple access/carrier sense multiple access (TDMA/CSMA) protocol is proposed. It includes an improved clear channel assessment (CCA) mechanism and a traffic adaptive slot allocation method. To analyze the access process, a Markov model is constructed. Then a detailed calculation is given in which the unsaturated cases are considered. Through simulations, the proposed protocol is proved to commendably satisfy the demands and performs better than existing schemes. It helps to build a full-wireless satellite instead of the current wired ones, and will contribute to provide dynamic space capabilities for ORS missions.

An EOQ Model with Two-Parameter Weibull Distribution Deterioration and Price-Dependent Demand

ERIC Educational Resources Information Center

Mukhopadhyay, Sushanta; Mukherjee, R. N.; Chaudhuri, K. S.

2005-01-01

An inventory replenishment policy is developed for a deteriorating item and price-dependent demand. The rate of deterioration is taken to be time-proportional and the time to deterioration is assumed to follow a two-parameter Weibull distribution. A power law form of the price dependence of demand is considered. The model is solved analytically…

Dynamical Systems Theory in Quantitative Psychology and Cognitive Science: A Fair Discrimination between Deterministic and Statistical Counterparts is Required.

PubMed

Gadomski, Adam; Ausloos, Marcel; Casey, Tahlia

2017-04-01

This article addresses a set of observations framed in both deterministic as well as statistical formal guidelines. It operates within the framework of nonlinear dynamical systems theory (NDS). It is argued that statistical approaches can manifest themselves ambiguously, creating practical discrepancies in psychological and cognitive data analyses both quantitatively and qualitatively. This is sometimes termed in literature as 'questionable research practices.' This communication points to the demand for a deeper awareness of the data 'initial conditions, allowing to focus on pertinent evolution constraints in such systems.' It also considers whether the exponential (Malthus-type) or the algebraic (Pareto-type) statistical distribution ought to be effectively considered in practical interpretations. The role of repetitive specific behaviors by patients seeking treatment is examined within the NDS frame. The significance of these behaviors, involving a certain memory effect seems crucial in determining a patient's progression or regression. With this perspective, it is discussed how a sensitively applied hazardous or triggering factor can be helpful for well-controlled psychological strategic treatments; those attributable to obsessive-compulsive disorders or self-injurious behaviors are recalled in particular. There are both inherent criticality- and complexity-exploiting (reduced-variance based) relations between a therapist and a patient that can be intrinsically included in NDS theory.

Building an Open Source Framework for Integrated Catchment Modeling

NASA Astrophysics Data System (ADS)

Jagers, B.; Meijers, E.; Villars, M.

2015-12-01

In order to develop effective strategies and associated policies for environmental management, we need to understand the dynamics of the natural system as a whole and the human role therein. This understanding is gained by comparing our mental model of the world with observations from the field. However, to properly understand the system we should look at dynamics of water, sediments, water quality, and ecology throughout the whole system from catchment to coast both at the surface and in the subsurface. Numerical models are indispensable in helping us understand the interactions of the overall system, but we need to be able to update and adjust them to improve our understanding and test our hypotheses. To support researchers around the world with this challenging task we started a few years ago with the development of a new open source modeling environment DeltaShell that integrates distributed hydrological models with 1D, 2D, and 3D hydraulic models including generic components for the tracking of sediment, water quality, and ecological quantities throughout the hydrological cycle composed of the aforementioned components. The open source approach combined with a modular approach based on open standards, which allow for easy adjustment and expansion as demands and knowledge grow, provides an ideal starting point for addressing challenging integrated environmental questions.

Digital holographic microscopy of phase separation in multicomponent lipid membranes

NASA Astrophysics Data System (ADS)

Farzam Rad, Vahideh; Moradi, Ali-Reza; Darudi, Ahmad; Tayebi, Lobat

2016-12-01

Lateral in-homogeneities in lipid compositions cause microdomains formation and change in the physical properties of biological membranes. With the presence of cholesterol and mixed species of lipids, phospholipid membranes segregate into lateral domains of liquid-ordered and liquid-disordered phases. Coupling of two-dimensional intralayer phase separations and interlayer liquid-crystalline ordering in multicomponent membranes has been previously demonstrated. By the use of digital holographic microscopy (DHMicroscopy), we quantitatively analyzed the volumetric dynamical behavior of such membranes. The specimens are lipid mixtures composed of sphingomyelin, cholesterol, and unsaturated phospholipid, 1,2-dioleoyl-sn-glycero-3-phosphocholine. DHMicroscopy in a transmission mode is an effective tool for quantitative visualization of phase objects. By deriving the associated phase changes, three-dimensional information on the morphology variation of lipid stacks at arbitrary time scales is obtained. Moreover, the thickness distribution of the object at demanded axial planes can be obtained by numerical focusing. Our results show that the volume evolution of lipid domains follows approximately the same universal growth law of previously reported area evolution. However, the thickness of the domains does not alter significantly by time; therefore, the volume evolution is mostly attributed to the changes in area dynamics. These results might be useful in the field of membrane-based functional materials.

Assessment of the Economic Potential of Distributed Wind in Colorado, Minnesota, and New York

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

McCabe, Kevin; Sigrin, Benjamin O.; Lantz, Eric J.

This work seeks to identify current and future spatial distributions of economic potential for behind-the-meter distributed wind, serving primarily rural or suburban homes, farms, and manufacturing facilities in Colorado, Minnesota, and New York. These states were identified by technical experts based on their current favorability for distributed wind deployment. We use NREL's Distributed Wind Market Demand Model (dWind) (Lantz et al. 2017; Sigrin et al. 2016) to identify and rank counties in each of the states by their overall and per capita potential. From this baseline assessment, we also explore how and where improvements in cost, performance, and other marketmore » sensitivities affect distributed wind potential.« less

POLYANA-A tool for the calculation of molecular radial distribution functions based on Molecular Dynamics trajectories

NASA Astrophysics Data System (ADS)

Dimitroulis, Christos; Raptis, Theophanes; Raptis, Vasilios

2015-12-01

We present an application for the calculation of radial distribution functions for molecular centres of mass, based on trajectories generated by molecular simulation methods (Molecular Dynamics, Monte Carlo). When designing this application, the emphasis was placed on ease of use as well as ease of further development. In its current version, the program can read trajectories generated by the well-known DL_POLY package, but it can be easily extended to handle other formats. It is also very easy to 'hack' the program so it can compute intermolecular radial distribution functions for groups of interaction sites rather than whole molecules.

Highly sensitive distributed birefringence measurements based on a two-pulse interrogation of a dynamic Brillouin grating

NASA Astrophysics Data System (ADS)

Soto, Marcelo A.; Denisov, Andrey; Angulo-Vinuesa, Xabier; Martin-Lopez, Sonia; Thévenaz, Luc; Gonzalez-Herraez, Miguel

2017-04-01

A method for distributed birefringence measurements is proposed based on the interference pattern generated by the interrogation of a dynamic Brillouin grating (DBG) using two short consecutive optical pulses. Compared to existing DBG interrogation techniques, the method here offers an improved sensitivity to birefringence changes thanks to the interferometric effect generated by the reflections of the two pulses. Experimental results demonstrate the possibility to obtain the longitudinal birefringence profile of a 20 m-long Panda fibre with an accuracy of 10-8 using 16 averages and 30 cm spatial resolution. The method enables sub-metric and highly-accurate distributed temperature and strain sensing.

Analysis, modeling, and simulation (AMS) testbed development and evaluation to support dynamic mobility applications (DMA) and active transportation and demand management (ATDM) programs — evaluation summary for DMA program.

DOT National Transportation Integrated Search

2017-07-04

The primary objective of this project is to develop multiple simulation testbeds/transportation models to evaluate the impacts of Dynamic Mobility Application (DMA) connected vehicle applications and Active Transportation and Demand management (ATDM)...

Analysis, modeling, and simulation (AMS) testbed development and evaluation to support dynamic mobility applications (DMA) and active transportation and demand management (ATDM) programs : summary report for the Chicago testbed.

DOT National Transportation Integrated Search

2017-04-01

The primary objective of this project is to develop multiple simulation testbeds and transportation models to evaluate the impacts of Connected Vehicle Dynamic Mobility Applications (DMA) and Active Transportation and Demand Management (ATDM) strateg...

Analysis, Modeling, and Simulation (AMS) Testbed Development and Evaluation to Support Dynamic Mobility Applications (DMA) and Active Transportation and Demand Management (ATDM) Programs : Evaluation Report for the Chicago Testbed

DOT National Transportation Integrated Search

2017-04-01

The primary objective of this project is to develop multiple simulation testbeds and transportation models to evaluate the impacts of Connected Vehicle Dynamic Mobility Applications (DMA) and Active Transportation and Demand Management (ATDM) strateg...

Analysis, modeling, and simulation (AMS) testbed development and evaluation to support dynamic mobility applications (DMA) and active transportation and demand management (ATDM) programs — evaluation report for ATDM program.

DOT National Transportation Integrated Search

2017-07-16

The primary objective of this project is to develop multiple simulation testbeds/transportation models to evaluate the impacts of Dynamic Mobility Applications (DMA) and the Active Transportation and Demand Management (ATDM) strategies. Specifically,...

Dynamic Involvement of Real World Objects in the IoT: A Consensus-Based Cooperation Approach

PubMed Central

Pilloni, Virginia; Atzori, Luigi; Mallus, Matteo

2017-01-01

A significant role in the Internet of Things (IoT) will be taken by mobile and low-cost unstable devices, which autonomously self-organize and introduce highly dynamic and heterogeneous scenarios for the deployment of distributed applications. This entails the devices to cooperate to dynamically find the suitable combination of their involvement so as to improve the system reliability while following the changes in their status. Focusing on the above scenario, we propose a distributed algorithm for resources allocation that is run by devices that can perform the same task required by the applications, allowing for a flexible and dynamic binding of the requested services with the physical IoT devices. It is based on a consensus approach, which maximizes the lifetime of groups of nodes involved and ensures the fulfillment of the requested Quality of Information (QoI) requirements. Experiments have been conducted with real devices, showing an improvement of device lifetime of more than 20%, with respect to a uniform distribution of tasks. PMID:28257030

Dynamic Involvement of Real World Objects in the IoT: A Consensus-Based Cooperation Approach.

PubMed

Pilloni, Virginia; Atzori, Luigi; Mallus, Matteo

2017-03-01

A significant role in the Internet of Things (IoT) will be taken by mobile and low-cost unstable devices, which autonomously self-organize and introduce highly dynamic and heterogeneous scenarios for the deployment of distributed applications. This entails the devices to cooperate to dynamically find the suitable combination of their involvement so as to improve the system reliability while following the changes in their status. Focusing on the above scenario, we propose a distributed algorithm for resources allocation that is run by devices that can perform the same task required by the applications, allowing for a flexible and dynamic binding of the requested services with the physical IoT devices. It is based on a consensus approach, which maximizes the lifetime of groups of nodes involved and ensures the fulfillment of the requested Quality of Information (QoI) requirements. Experiments have been conducted with real devices, showing an improvement of device lifetime of more than 20 % , with respect to a uniform distribution of tasks.

Dynamic data distributions in Vienna Fortran

NASA Technical Reports Server (NTRS)

Chapman, Barbara; Mehrotra, Piyush; Moritsch, Hans; Zima, Hans

1993-01-01

Vienna Fortran is a machine-independent language extension of Fortran, which is based upon the Single-Program-Multiple-Data (SPMD) paradigm and allows the user to write programs for distributed-memory systems using global addresses. The language features focus mainly on the issue of distributing data across virtual processor structures. Those features of Vienna Fortran that allow the data distributions of arrays to change dynamically, depending on runtime conditions are discussed. The relevant language features are discussed, their implementation is outlined, and how they may be used in applications is described.

Dense and dynamic 3D selection for game-based virtual environments.

PubMed

Cashion, Jeffrey; Wingrave, Chadwick; LaViola, Joseph J

2012-04-01

3D object selection is more demanding when, 1) objects densly surround the target object, 2) the target object is significantly occluded, and 3) when the target object is dynamically changing location. Most 3D selection techniques and guidelines were developed and tested on static or mostly sparse environments. In contrast, games tend to incorporate densly packed and dynamic objects as part of their typical interaction. With the increasing popularity of 3D selection in games using hand gestures or motion controllers, our current understanding of 3D selection needs revision. We present a study that compared four different selection techniques under five different scenarios based on varying object density and motion dynamics. We utilized two existing techniques, Raycasting and SQUAD, and developed two variations of them, Zoom and Expand, using iterative design. Our results indicate that while Raycasting and SQUAD both have weaknesses in terms of speed and accuracy in dense and dynamic environments, by making small modifications to them (i.e., flavoring), we can achieve significant performance increases.

The role of innovative global institutions in linking knowledge and action.

PubMed

van Kerkhoff, Lorrae; Szlezák, Nicole A

2016-04-26

It is becoming increasingly recognized that our collective ability to tackle complex problems will require the development of new, adaptive, and innovative institutional arrangements that can deal with rapidly changing knowledge and have effective learning capabilities. In this paper, we applied a knowledge-systems perspective to examine how institutional innovations can affect the generation, sharing, and application of scientific and technical knowledge. We report on a case study that examined the effects that one large innovative organization, The Global Fund to Fight AIDS, Tuberculosis, and Malaria, is having on the knowledge dimensions of decision-making in global health. The case study shows that the organization created demand for new knowledge from a range of actors, but it did not incorporate strategies for meeting this demand into their own rules, incentives, or procedures. This made it difficult for some applicants to meet the organization's dual aims of scientific soundness and national ownership of projects. It also highlighted that scientific knowledge needed to be integrated with managerial and situational knowledge for success. More generally, the study illustrates that institutional change targeting implementation can also significantly affect the dynamics of knowledge creation (learning), access, distribution, and use. Recognizing how action-oriented institutions can affect these dynamics across their knowledge system can help institutional designers build more efficient and effective institutions for sustainable development.

MROrchestrator: A Fine-Grained Resource Orchestration Framework for MapReduce Clusters

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

Sharma, Bikash; Prabhakar, Ramya; Kandemir, Mahmut

2012-01-01

Efficient resource management in data centers and clouds running large distributed data processing frameworks like MapReduce is crucial for enhancing the performance of hosted applications and boosting resource utilization. However, existing resource scheduling schemes in Hadoop MapReduce allocate resources at the granularity of fixed-size, static portions of nodes, called slots. In this work, we show that MapReduce jobs have widely varying demands for multiple resources, making the static and fixed-size slot-level resource allocation a poor choice both from the performance and resource utilization standpoints. Furthermore, lack of co-ordination in the management of mul- tiple resources across nodes prevents dynamic slotmore » reconfigura- tion, and leads to resource contention. Motivated by this, we propose MROrchestrator, a MapReduce resource Orchestrator framework, which can dynamically identify resource bottlenecks, and resolve them through fine-grained, co-ordinated, and on- demand resource allocations. We have implemented MROrches- trator on two 24-node native and virtualized Hadoop clusters. Experimental results with a suite of representative MapReduce benchmarks demonstrate up to 38% reduction in job completion times, and up to 25% increase in resource utilization. We further show how popular resource managers like NGM and Mesos when augmented with MROrchestrator can hike up their performance.« less

Mixed-Fidelity Approach for Design of Low-Boom Supersonic Aircraft

NASA Technical Reports Server (NTRS)

Li, Wu; Shields, Elwood; Geiselhart, Karl

2011-01-01

This paper documents a mixed-fidelity approach for the design of low-boom supersonic aircraft with a focus on fuselage shaping.A low-boom configuration that is based on low-fidelity analysis is used as the baseline. The fuselage shape is modified iteratively to obtain a configuration with an equivalent-area distribution derived from computational fluid dynamics analysis that attempts to match a predetermined low-boom target area distribution and also yields a low-boom ground signature. The ground signature of the final configuration is calculated by using a state-of-the-art computational-fluid-dynamics-based boom analysis method that generates accurate midfield pressure distributions for propagation to the ground with ray tracing. The ground signature that is propagated from a midfield pressure distribution has a shaped ramp front, which is similar to the ground signature that is propagated from the computational fluid dynamics equivalent-area distribution. This result supports the validity of low-boom supersonic configuration design by matching a low-boom equivalent-area target, which is easier to accomplish than matching a low-boom midfield pressure target.

A Mathematical Model of Demand-Supply Dynamics with Collectability and Saturation Factors

NASA Astrophysics Data System (ADS)

Li, Y. Charles; Yang, Hong

We introduce a mathematical model on the dynamics of demand and supply incorporating collectability and saturation factors. Our analysis shows that when the fluctuation of the determinants of demand and supply is strong enough, there is chaos in the demand-supply dynamics. Our numerical simulation shows that such a chaos is not an attractor (i.e. dynamics is not approaching the chaos), instead a periodic attractor (of period-3 under the Poincaré period map) exists near the chaos, and coexists with another periodic attractor (of period-1 under the Poincaré period map) near the market equilibrium. Outside the basins of attraction of the two periodic attractors, the dynamics approaches infinity indicating market irrational exuberance or flash crash. The period-3 attractor represents the product’s market cycle of growth and recession, while period-1 attractor near the market equilibrium represents the regular fluctuation of the product’s market. Thus our model captures more market phenomena besides Marshall’s market equilibrium. When the fluctuation of the determinants of demand and supply is strong enough, a three leaf danger zone exists where the basins of attraction of all attractors intertwine and fractal basin boundaries are formed. Small perturbations in the danger zone can lead to very different attractors. That is, small perturbations in the danger zone can cause the market to experience oscillation near market equilibrium, large growth and recession cycle, and irrational exuberance or flash crash.

Price Based Local Power Distribution Management System (Local Power Distribution Manager) v1.0

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

BROWN, RICHARD E.; CZARNECKI, STEPHEN; SPEARS, MICHAEL

2016-11-28

A trans-active energy micro-grid controller is implemented in the VOLTTRON distributed control platform. The system uses the price of electricity as the mechanism for conducting transactions that are used to manage energy use and to balance supply and demand. In order to allow testing and analysis of the control system, the implementation is designed to run completely as a software simulation, while allowing the inclusion of selected hardware that physically manages power. Equipment to be integrated with the micro-grid controller must have an IP (Internet Protocol)-based network connection and a software "driver" must exist to translate data communications between themore » device and the controller.« less

Modeling vegetation rooting strategies on a hillslope

NASA Astrophysics Data System (ADS)

Sivandran, G.; Bras, R. L.

2011-12-01

The manner in which water and energy is partitioned and redistributed along a hillslope is the result of complex coupled ecohydrological interactions between the climatic, soils, topography and vegetation operating over a wide range of spatiotemporal scales. Distributed process based modeling creates a framework through which the interaction of vegetation with the subtle differences in the spatial and temporal dynamics of soil moisture that arise under localized abiotic conditions along a hillslope can be simulated and examined. One deficiency in the current dynamic vegetation models is the one sided manner in which vegetation responds to soil moisture dynamics. Above ground, vegetation is given the freedom to dynamically evolve through alterations in fractional vegetation cover and/or canopy height and density; however below ground rooting profiles are simplistically represented and often held constant in time and space. The need to better represent the belowground role of vegetation through dynamic rooting strategies is fundamental in capturing the magnitude and timing of water and energy fluxes between the atmosphere and land surface. In order to allow vegetation to adapt to gradients in soil moisture a dynamic rooting scheme was incorporated into tRIBS+VEGGIE (a physically based distributed ecohydrological model). The dynamic rooting scheme allows vegetation the freedom to adapt their rooting depth and distribution in response abiotic conditions in a way that more closely mimics observed plant behavior. The incorporation of this belowground plasticity results in vegetation employing a suite of rooting strategies based on soil texture, climatic conditions and location on the hillslope.

Data Intensive Systems (DIS) Benchmark Performance Summary

DTIC Science & Technology

2003-08-01

models assumed by today’s conventional architectures. Such applications include model- based Automatic Target Recognition (ATR), synthetic aperture...radar (SAR) codes, large scale dynamic databases/battlefield integration, dynamic sensor- based processing, high-speed cryptanalysis, high speed...distributed interactive and data intensive simulations, data-oriented problems characterized by pointer- based and other highly irregular data structures

Wood Residue Distribution Simulator (WORDS)

Treesearch

Douglas A. Eza; James W. McMinn; Peter E. Dress

1984-01-01

Successful development of woody biomass for energy will depend on the distribution of local supply and demand within subregions, rather than on the total inventory of residues. The Wood Residue Distribution Simulator (WORDS) attempts to find a least-cost allocation of residues from local sources of supply to local sources of demand, given the cost of the materials,...

Investigation of subcellular localization and dynamics of membrane proteins in living bacteria by combining optical micromanipulation and high-resolution microscopy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Barroso Peña, Álvaro; Nieves, Marcos; Teper, Konrad; Wedlich-Soldner, Roland; Denz, Cornelia

2016-09-01

The plasma membrane serves as protective interface between cells and their environment. It also constitutes a hub for selective nutrient uptake and signal transduction. Increasing evidence over the last years indicates that, similar to eukaryotic cells, lateral membrane organization plays an important role in the regulation of prokaryotic signaling pathways. However, the mechanisms underlying this phenomenon are still poorly understood. Spatiotemporal characterization of bacterial signal transduction demands very sensitive high-resolution microscopy techniques due to the low expression levels of most signaling proteins and the small size of bacterial cells. In addition, direct study of subcellular confinement and dynamics of bacterial signaling proteins during the different stages of the signal transduction also requires immobilization in order to avoid cell displacement caused by Brownian motion, local fluid flows and bacterial self-propulsion. In this work we present a novel approach based on the combination of high resolution imaging and optical manipulation that enables the investigation of the distribution and dynamics of proteins at the bacterial plasma membrane. For this purpose, we combine the versatility of holographic optical tweezers (HOT) with the sensitivity and resolution of total internal reflection fluorescence (TIRF) microscopy. Furthermore, we discuss the implementation of microfluidic devices in our integrated HOT+TIRF system for the control of growth conditions of bacterial cells. The capabilities of our workstation provides thus new valuable insights into the fundamental cellular and physical mechanisms underlying the regulation of bacterial signal transduction.

Dynamic PROOF clusters with PoD: architecture and user experience

NASA Astrophysics Data System (ADS)

Manafov, Anar

2011-12-01

PROOF on Demand (PoD) is a tool-set, which sets up a PROOF cluster on any resource management system. PoD is a user oriented product with an easy to use GUI and a command-line interface. It is fully automated. No administrative privileges or special knowledge is required to use it. PoD utilizes a plug-in system, to use different job submission front-ends. The current PoD distribution is shipped with LSF, Torque (PBS), Grid Engine, Condor, gLite, and SSH plug-ins. The product is to be extended. We therefore plan to implement a plug-in for AliEn Grid as well. Recently developed algorithms made it possible to efficiently maintain two types of connections: packet-forwarding and native PROOF connections. This helps to properly handle most kinds of workers, with and without firewalls. PoD maintains the PROOF environment automatically and, for example, prevents resource misusage in case when workers idle for too long. As PoD matures as a product and provides more plug-ins, it's used as a standard for setting up dynamic PROOF clusters in many different institutions. The GSI Analysis Facility (GSIAF) is in production since 2007. The static PROOF cluster has been phased out end of 2009. GSIAF is now completely based on PoD. Users create private dynamic PROOF clusters on the general purpose batch farm. This provides an easier resource sharing between interactive local batch and Grid usage. The main user communities are FAIR and ALICE.

Study the fragment size distribution in dynamic fragmentation of laser shock loding tin

NASA Astrophysics Data System (ADS)

He, Weihua; Xin, Jianting; Chu, Genbai; Shui, Min; Xi, Tao; Zhao, Yongqiang; Gu, Yuqiu

2017-06-01

Characterizing the distribution of fragment size produced from dynamic fragmentation process is very important for fundamental science like predicting material dymanic response performance and for a variety of engineering applications. However, only a few data about fragment mass or size have been obtained due to its great challenge in its dynamic measurement. This paper would focus on investigating the fragment size distribution from the dynamic fragmentation of laser shock-loaded metal. Material ejection of tin sample with wedge shape groove in the free surface is collected with soft recovery technique. Via fine post-shot analysis techniques including X-ray micro-tomography and the improved watershed method, it is found that fragments can be well detected. To characterize their size distributions, a random geometric statistics method based on Poisson mixtures was derived for dynamic heterogeneous fragmentation problem, which leads to a linear combinational exponential distribution. Finally we examined the size distribution of laser shock-loaded tin with the derived model, and provided comparisons with other state-of-art models. The resulting comparisons prove that our proposed model can provide more reasonable fitting result for laser shock-loaded metal.

Ambulatory Healthcare Utilization in the United States: A System Dynamics Approach

NASA Technical Reports Server (NTRS)

Diaz, Rafael; Behr, Joshua G.; Tulpule, Mandar

2011-01-01

Ambulatory health care needs within the United States are served by a wide range of hospitals, clinics, and private practices. The Emergency Department (ED) functions as an important point of supply for ambulatory healthcare services. Growth in our aging populations as well as changes stemming from broader healthcare reform are expected to continue trend in congestion and increasing demand for ED services. While congestion is, in part, a manifestation of unmatched demand, the state of the alignment between the demand for, and supply of, emergency department services affects quality of care and profitability. The central focus of this research is to provide an explanation of the salient factors at play within the dynamic demand-supply tensions within which ambulatory care is provided within an Emergency Department. A System Dynamics (SO) simulation model is used to capture the complexities among the intricate balance and conditional effects at play within the demand-supply emergency department environment. Conceptual clarification of the forces driving the elements within the system , quantifying these elements, and empirically capturing the interaction among these elements provides actionable knowledge for operational and strategic decision-making.

Projections of Demand for Waterborne Transportation, Ohio River Basin, 1980, 1990, 2000, 2020, 2040. Volume 4. Group II. Petroleum Fuels.

DTIC Science & Technology

1980-12-01

for1980 and 1985 (OaK Ridge, TN: ORNL , 1978), Table 1. I -11- B-3. Residual Fuel Oil This group mainly includes No. 5 and No. 6 fuel oils. They are used...types of fuels was then distributed to the PSAs. This projection was based on projections from two different sources. Oak Ridge National Laboratory ( ORNL ...nine census regions, 50 states and 173 BEAs. The supply and demand projectiSns were made for seven fuel types and four final consuming sectors. ORNL

Health Care Decision Support System for the Pediatric Emeregency Department Management.

PubMed

Ben Othman, Sarah; Hammadi, Slim; Quilliot, Alain; Martinot, Alain; Renard, Jean-Marie

2015-01-01

Health organization management is facing a high amount of complexity due to the inherent dynamics of the processes and the distributed organization of hospitals. It is therefore necessary for health care institutions to focus on this issue in order to deal with patients' requirements and satisfy their needs. The main objective of this study is to develop and implement a Decision Support System which can help physicians to better manage their organization, to anticipate the overcrowding feature, and to establish avoidance proposals for it. This work is a part of HOST project (Hospital: Optimization, Simulation, and Crowding Avoidance) of the French National Research Agency (ANR). It aims to optimize the functioning of the Pediatric Emergency Department characterized by stochastic arrivals of patients which leads to its overcrowding and services overload. Our study is a set of tools to smooth out patient flows, enhance care quality and minimize long waiting times and costs due to resources allocation. So we defined a decision aided tool based on Multi-agent Systems where actors negotiate and cooperate under some constraints in a dynamic environment. These entities which can be either physical agents representing real actors in the health care institution or software agents allowing the implementation of optimizing tools, cooperate to satisfy the demands of patients while respecting emergency degrees. This paper is concerned with agents' negotiation. It proposes a new approach for multi-skill tasks scheduling based on interactions between agents.

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.

Disaggregating residential water demand for improved forecasts and decision making

NASA Astrophysics Data System (ADS)

Woodard, G.; Brookshire, D.; Chermak, J.; Krause, K.; Roach, J.; Stewart, S.; Tidwell, V.

2003-04-01

Residential water demand is the product of population and per capita demand. Estimates of per capita demand often are based on econometric models of demand, usually based on time series data of demand aggregated at the water provider level. Various studies have examined the impact of such factors as water pricing, weather, and income, with many other factors and details of water demand remaining unclear. Impacts of water conservation programs often are estimated using simplistic engineering calculations. Partly as a result of this, policy discussions regarding water demand management often focus on water pricing, water conservation, and growth control. Projecting water demand is often a straight-forward, if fairly uncertain process of forecasting population and per capita demand rates. SAHRA researchers are developing improved forecasts of residential water demand by disaggregating demand to the level of individuals, households, and specific water uses. Research results based on high-resolution water meter loggers, household-level surveys, economic experiments and recent census data suggest that changes in wealth, household composition, and individual behavior may affect demand more than changes in population or the stock of landscape plants, water-using appliances and fixtures, generally considered the primary determinants of demand. Aging populations and lower fertility rates are dramatically reducing household size, thereby increasing the number of households and residences for a given population. Recent prosperity and low interest rates have raised home ownership rates to unprecented levels. These two trends are leading to increased per capita outdoor water demand. Conservation programs have succeeded in certain areas, such as promoting drought-tolerant native landscaping, but have failed in other areas, such as increasing irrigation efficiency or curbing swimming pool water usage. Individual behavior often is more important than the household's stock of water-using fixtures, and ranges from hedonism (installing pools and whirlpool tubs) to satisficing (adjusting irrigation timers only twice per year) to acting on deeply-held conservation ethics in ways that not only fail any benefit-cost test, but are discouraged, or even illegal (reuse of gray water and black water). Research findings are being captured in dynamic simulation models that integrate social and natural science to create tools to assist water resource managers in providing sustainable water supplies and improving residential water demand forecasts. These models feature simple, graphical user interfaces and output screens that provide decision makers with visual, easy-to-understand information at the basin level. The models reveal connections between various supply and demand components, and highlight direct impacts and feedback mechanisms associated with various policy options.

NAS Demand Predictions, Transportation Systems Analysis Model (TSAM) Compared with Other Forecasts

NASA Technical Reports Server (NTRS)

Viken, Jeff; Dollyhigh, Samuel; Smith, Jeremy; Trani, Antonio; Baik, Hojong; Hinze, Nicholas; Ashiabor, Senanu

2006-01-01

The current work incorporates the Transportation Systems Analysis Model (TSAM) to predict the future demand for airline travel. TSAM is a multi-mode, national model that predicts the demand for all long distance travel at a county level based upon population and demographics. The model conducts a mode choice analysis to compute the demand for commercial airline travel based upon the traveler s purpose of the trip, value of time, cost and time of the trip,. The county demand for airline travel is then aggregated (or distributed) to the airport level, and the enplanement demand at commercial airports is modeled. With the growth in flight demand, and utilizing current airline flight schedules, the Fratar algorithm is used to develop future flight schedules in the NAS. The projected flights can then be flown through air transportation simulators to quantify the ability of the NAS to meet future demand. A major strength of the TSAM analysis is that scenario planning can be conducted to quantify capacity requirements at individual airports, based upon different future scenarios. Different demographic scenarios can be analyzed to model the demand sensitivity to them. Also, it is fairly well know, but not well modeled at the airport level, that the demand for travel is highly dependent on the cost of travel, or the fare yield of the airline industry. The FAA projects the fare yield (in constant year dollars) to keep decreasing into the future. The magnitude and/or direction of these projections can be suspect in light of the general lack of airline profits and the large rises in airline fuel cost. Also, changes in travel time and convenience have an influence on the demand for air travel, especially for business travel. Future planners cannot easily conduct sensitivity studies of future demand with the FAA TAF data, nor with the Boeing or Airbus projections. In TSAM many factors can be parameterized and various demand sensitivities can be predicted for future travel. These resulting demand scenarios can be incorporated into future flight schedules, therefore providing a quantifiable demand for flights in the NAS for a range of futures. In addition, new future airline business scenarios are investigated that illustrate when direct flights can replace connecting flights and larger aircraft can be substituted, only when justified by demand.

Utilizing Traveler Demand Modeling to Predict Future Commercial Flight Schedules in the NAS

NASA Technical Reports Server (NTRS)

Viken, Jeff; Dollyhigh, Samuel; Smith, Jeremy; Trani, Antonio; Baik, Hojong; Hinze, Nicholas; Ashiabor, Senanu

2006-01-01

The current work incorporates the Transportation Systems Analysis Model (TSAM) to predict the future demand for airline travel. TSAM is a multi-mode, national model that predicts the demand for all long distance travel at a county level based upon population and demographics. The model conducts a mode choice analysis to compute the demand for commercial airline travel based upon the traveler s purpose of the trip, value of time, cost and time of the trip,. The county demand for airline travel is then aggregated (or distributed) to the airport level, and the enplanement demand at commercial airports is modeled. With the growth in flight demand, and utilizing current airline flight schedules, the Fratar algorithm is used to develop future flight schedules in the NAS. The projected flights can then be flown through air transportation simulators to quantify the ability of the NAS to meet future demand. A major strength of the TSAM analysis is that scenario planning can be conducted to quantify capacity requirements at individual airports, based upon different future scenarios. Different demographic scenarios can be analyzed to model the demand sensitivity to them. Also, it is fairly well know, but not well modeled at the airport level, that the demand for travel is highly dependent on the cost of travel, or the fare yield of the airline industry. The FAA projects the fare yield (in constant year dollars) to keep decreasing into the future. The magnitude and/or direction of these projections can be suspect in light of the general lack of airline profits and the large rises in airline fuel cost. Also, changes in travel time and convenience have an influence on the demand for air travel, especially for business travel. Future planners cannot easily conduct sensitivity studies of future demand with the FAA TAF data, nor with the Boeing or Airbus projections. In TSAM many factors can be parameterized and various demand sensitivities can be predicted for future travel. These resulting demand scenarios can be incorporated into future flight schedules, therefore providing a quantifiable demand for flights in the NAS for a range of futures. In addition, new future airline business scenarios are investigated that illustrate when direct flights can replace connecting flights and larger aircraft can be substituted, only when justified by demand.

Visualization of the Dynamic Rhizosphere Environment: Microbial and Biogeochemical Perspectives

NASA Astrophysics Data System (ADS)

Cardon, Z. G.; Forbes, E. S.; Thomas, F.; Herron, P. M.; Gage, D. J.; Thomas, S.; Larsen, M.; Arango Pinedo, C.; Sievert, S. M.; Giblin, A. E.

2014-12-01

The rhizosphere is a hotbed of nutrient cycling fueled by carbon from plants and controlled by microbes. Plants also strongly affect the rhizosphere by driving water flow into and out of roots, and by oxygenating saturated soil and sediment. Location and dynamics of plant-spurred microbial growth and activities are impossible to discern with destructive soil assays mixing microbe-scale soil microenvironments in a single"snap-shot" sample. Yet data are needed to inform (and validate) models describing microbial activity and biogeochemistry in the ebb and flow of the dynamic rhizosphere. Dynamics and localization of rapid microbial growth in the rhizosphere can be assessed over time using living soil microbiosensors. We used the bacterium Pseudomonas putida KT2440 as host to plasmid pZKH2 containing a fusion between the strong constituitive promoter nptII and luxCDABE(genes coding for light production). High light production by KT2440/pZKH2 correlated with rapid microbial growth supported by high carbon availability. Biosensors were used in clear-sided microcosms filled with non-sterile soil in which corn, black poplar or tomato were growing. KT2440/pZKH2 revealed that root tips are not necessarily the only, or even the dominant, hotspots for rhizosphere microbial growth, and carbon availability is highly variable in space and time around roots. Roots can also be sources of oxygen (O2) to the rhizosphere in saturated soil. We quantified spatial distributions of O2 using planar optodes placed against the face of sediment blocks cut from vegetated salt marsh at Plum Island Ecosystems LTER. Integrated over time, Spartina alterniflora roots were O2 sources to the rhizosphere. However, "sun-up" (light on) did not uniformly enhance rhizosphere O2 concentrations (as stomata opened and O2 production commenced). In some regions, the balance of O2 supply (from roots) and O2 demand (root and microbial) tipped toward demand at sun-up (repeatedly, over days). We speculate that in these regions, carbon produced during photosynthesis was released from roots and stimulated microbial O2 demand in the light. In situ, such dynamics in O2 and carbon availability around plant roots will influence interlinked sulfur, nitrogen, and carbon cycling in salt marsh rhizosphere.

Alcohol demand and risk preference.

PubMed

Dave, Dhaval; Saffer, Henry

2008-12-01

Both economists and psychologists have studied the concept of risk preference. Economists categorize individuals as more or less risk-tolerant based on the marginal utility of income. Psychologists categorize individuals' propensity towards risk based on harm avoidance, novelty seeking and reward dependence traits. The two concepts of risk are related, although the instruments used for empirical measurement are quite different. Psychologists have found risk preference to be an important determinant of alcohol consumption; however economists have not included risk preference in studies of alcohol demand. This is the first study to examine the effect of risk preference on alcohol consumption in the context of a demand function. The specifications employ multiple waves from the Panel Study of Income Dynamics (PSID) and the Health and Retirement Study (HRS), which permit the estimation of age-specific models based on nationally representative samples. Both of these data sets include a unique and consistent survey instrument designed to directly measure risk preference in accordance with the economist's definition. This study estimates the direct impact of risk preference on alcohol demand and also explores how risk preference affects the price elasticity of demand. The empirical results indicate that risk preference has a significant negative effect on alcohol consumption, with the prevalence and consumption among risk-tolerant individuals being 6-8% higher. Furthermore, the tax elasticity is similar across both risk-averse and risk-tolerant individuals. This suggests that tax policies are as equally effective in deterring alcohol consumption among those who have a higher versus a lower propensity for alcohol use.

Quantifying and Mapping the Supply of and Demand for Carbon Storage and Sequestration Service from Urban Trees.

PubMed

Zhao, Chang; Sander, Heather A

2015-01-01

Studies that assess the distribution of benefits provided by ecosystem services across urban areas are increasingly common. Nevertheless, current knowledge of both the supply and demand sides of ecosystem services remains limited, leaving a gap in our understanding of balance between ecosystem service supply and demand that restricts our ability to assess and manage these services. The present study seeks to fill this gap by developing and applying an integrated approach to quantifying the supply and demand of a key ecosystem service, carbon storage and sequestration, at the local level. This approach follows three basic steps: (1) quantifying and mapping service supply based upon Light Detection and Ranging (LiDAR) processing and allometric models, (2) quantifying and mapping demand for carbon sequestration using an indicator based on local anthropogenic CO2 emissions, and (3) mapping a supply-to-demand ratio. We illustrate this approach using a portion of the Twin Cities Metropolitan Area of Minnesota, USA. Our results indicate that 1735.69 million kg carbon are stored by urban trees in our study area. Annually, 33.43 million kg carbon are sequestered by trees, whereas 3087.60 million kg carbon are emitted by human sources. Thus, carbon sequestration service provided by urban trees in the study location play a minor role in combating climate change, offsetting approximately 1% of local anthropogenic carbon emissions per year, although avoided emissions via storage in trees are substantial. Our supply-to-demand ratio map provides insight into the balance between carbon sequestration supply in urban trees and demand for such sequestration at the local level, pinpointing critical locations where higher levels of supply and demand exist. Such a ratio map could help planners and policy makers to assess and manage the supply of and demand for carbon sequestration.

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

An Innovative Interactive Modeling Tool to Analyze Scenario-Based Physician Workforce Supply and Demand.

PubMed

Gupta, Saurabh; Black-Schaffer, W Stephen; Crawford, James M; Gross, David; Karcher, Donald S; Kaufman, Jill; Knapman, Doug; Prystowsky, Michael B; Wheeler, Thomas M; Bean, Sarah; Kumar, Paramhans; Sharma, Raghav; Chamoli, Vaibhav; Ghai, Vikrant; Gogia, Vineet; Weintraub, Sally; Cohen, Michael B; Robboy, Stanley J

2015-01-01

Effective physician workforce management requires that the various organizations comprising the House of Medicine be able to assess their current and future workforce supply. This information has direct relevance to funding of graduate medical education. We describe a dynamic modeling tool that examines how individual factors and practice variables can be used to measure and forecast the supply and demand for existing and new physician services. The system we describe, while built to analyze the pathologist workforce, is sufficiently broad and robust for use in any medical specialty. Our design provides a computer-based software model populated with data from surveys and best estimates by specialty experts about current and new activities in the scope of practice. The model describes the steps needed and data required for analysis of supply and demand. Our modeling tool allows educators and policy makers, in addition to physician specialty organizations, to assess how various factors may affect demand (and supply) of current and emerging services. Examples of factors evaluated include types of professional services (3 categories with 16 subcategories), service locations, elements related to the Patient Protection and Affordable Care Act, new technologies, aging population, and changing roles in capitated, value-based, and team-based systems of care. The model also helps identify where physicians in a given specialty will likely need to assume new roles, develop new expertise, and become more efficient in practice to accommodate new value-based payment models.

An Innovative Interactive Modeling Tool to Analyze Scenario-Based Physician Workforce Supply and Demand

PubMed Central

Gupta, Saurabh; Black-Schaffer, W. Stephen; Crawford, James M.; Gross, David; Karcher, Donald S.; Kaufman, Jill; Knapman, Doug; Prystowsky, Michael B.; Wheeler, Thomas M.; Bean, Sarah; Kumar, Paramhans; Sharma, Raghav; Chamoli, Vaibhav; Ghai, Vikrant; Gogia, Vineet; Weintraub, Sally; Cohen, Michael B.

2015-01-01

Effective physician workforce management requires that the various organizations comprising the House of Medicine be able to assess their current and future workforce supply. This information has direct relevance to funding of graduate medical education. We describe a dynamic modeling tool that examines how individual factors and practice variables can be used to measure and forecast the supply and demand for existing and new physician services. The system we describe, while built to analyze the pathologist workforce, is sufficiently broad and robust for use in any medical specialty. Our design provides a computer-based software model populated with data from surveys and best estimates by specialty experts about current and new activities in the scope of practice. The model describes the steps needed and data required for analysis of supply and demand. Our modeling tool allows educators and policy makers, in addition to physician specialty organizations, to assess how various factors may affect demand (and supply) of current and emerging services. Examples of factors evaluated include types of professional services (3 categories with 16 subcategories), service locations, elements related to the Patient Protection and Affordable Care Act, new technologies, aging population, and changing roles in capitated, value-based, and team-based systems of care. The model also helps identify where physicians in a given specialty will likely need to assume new roles, develop new expertise, and become more efficient in practice to accommodate new value-based payment models. PMID:28725751

Total Force Fitness in units part 1: military demand-resource model.

PubMed

Bates, Mark J; Fallesen, Jon J; Huey, Wesley S; Packard, Gary A; Ryan, Diane M; Burke, C Shawn; Smith, David G; Watola, Daniel J; Pinder, Evette D; Yosick, Todd M; Estrada, Armando X; Crepeau, Loring; Bowles, Stephen V

2013-11-01

The military unit is a critical center of gravity in the military's efforts to enhance resilience and the health of the force. The purpose of this article is to augment the military's Total Force Fitness (TFF) guidance with a framework of TFF in units. The framework is based on a Military Demand-Resource model that highlights the dynamic interactions across demands, resources, and outcomes. A joint team of subject-matter experts identified key variables representing unit fitness demands, resources, and outcomes. The resulting framework informs and supports leaders, support agencies, and enterprise efforts to strengthen TFF in units by (1) identifying TFF unit variables aligned with current evidence and operational practices, (2) standardizing communication about TFF in units across the Department of Defense enterprise in a variety of military organizational contexts, (3) improving current resources including evidence-based actions for leaders, (4) identifying and addressing of gaps, and (5) directing future research for enhancing TFF in units. These goals are intended to inform and enhance Service efforts to develop Service-specific TFF models, as well as provide the conceptual foundation for a follow-on article about TFF metrics for units. Reprint & Copyright © 2013 Association of Military Surgeons of the U.S.

Prediction-based Dynamic Energy Management in Wireless Sensor Networks

PubMed Central

Wang, Xue; Ma, Jun-Jie; Wang, Sheng; Bi, Dao-Wei

2007-01-01

Energy consumption is a critical constraint in wireless sensor networks. Focusing on the energy efficiency problem of wireless sensor networks, this paper proposes a method of prediction-based dynamic energy management. A particle filter was introduced to predict a target state, which was adopted to awaken wireless sensor nodes so that their sleep time was prolonged. With the distributed computing capability of nodes, an optimization approach of distributed genetic algorithm and simulated annealing was proposed to minimize the energy consumption of measurement. Considering the application of target tracking, we implemented target position prediction, node sleep scheduling and optimal sensing node selection. Moreover, a routing scheme of forwarding nodes was presented to achieve extra energy conservation. Experimental results of target tracking verified that energy-efficiency is enhanced by prediction-based dynamic energy management.

Price impact on urban residential water demand: A dynamic panel data approach

NASA Astrophysics Data System (ADS)

ArbuéS, Fernando; BarberáN, Ramón; Villanúa, Inmaculada

2004-11-01

In this paper, we formulate and estimate a model of residential water demand with the aim of evaluating the potential of pricing policies as a mechanism for managing residential water. The proposed econometric model offers a new perspective on urban water demand analysis by combining microlevel data with a dynamic panel data estimation procedure. The empirical application suggests that residential users are more responsive to a lagged average price specification. Another result of the estimated model is that price is a moderately effective tool in reducing residential water demand within the present range of prices, with the estimated values for income elasticity and "elasticity of consumption with respect to family size" reinforcing this conclusion.

Distributed finite-time containment control for double-integrator multiagent systems.

PubMed

Wang, Xiangyu; Li, Shihua; Shi, Peng

2014-09-01

In this paper, the distributed finite-time containment control problem for double-integrator multiagent systems with multiple leaders and external disturbances is discussed. In the presence of multiple dynamic leaders, by utilizing the homogeneous control technique, a distributed finite-time observer is developed for the followers to estimate the weighted average of the leaders' velocities at first. Then, based on the estimates and the generalized adding a power integrator approach, distributed finite-time containment control algorithms are designed to guarantee that the states of the followers converge to the dynamic convex hull spanned by those of the leaders in finite time. Moreover, as a special case of multiple dynamic leaders with zero velocities, the proposed containment control algorithms also work for the case of multiple stationary leaders without using the distributed observer. Simulations demonstrate the effectiveness of the proposed control algorithms.

Analysis, Modeling, and Simulation (AMS) Testbed Development and Evaluation to Support Dynamic Mobility Applications (DMA) and Active Transportation and Demand Management (ATDM) Programs - Evaluation Report for the San Diego Testbed

DOT National Transportation Integrated Search

2017-07-01

The primary objective of this project is to develop multiple simulation testbeds and transportation models to evaluate the impacts of Connected Vehicle Dynamic Mobility Applications (DMA) and Active Transportation and Demand Management (ATDM) strateg...

Analysis, Modeling, and Simulation (AMS) Testbed Development and Evaluation to Support Dynamic Mobility Applications (DMA) and Active Transportation and Demand Management (ATDM) Programs : Evaluation Report for the San Diego Testbed : Draft Report.

DOT National Transportation Integrated Search

2017-07-01

The primary objective of this project is to develop multiple simulation testbeds and transportation models to evaluate the impacts of Connected Vehicle Dynamic Mobility Applications (DMA) and Active Transportation and Demand Management (ATDM) strateg...

Analysis, modeling, and simulation (AMS) testbed development and evaluation to support dynamic mobility applications (DMA) and active transportation and demand management (ATDM) programs - evaluation summary for the San Diego testbed

DOT National Transportation Integrated Search

2017-08-01

The primary objective of this project is to develop multiple simulation testbeds and transportation models to evaluate the impacts of Connected Vehicle Dynamic Mobility Applications (DMA) and Active Transportation and Demand Management (ATDM) strateg...

Thermal energy storage for organic Rankine cycle solar dynamic space power systems

NASA Astrophysics Data System (ADS)

Heidenreich, G. R.; Parekh, M. B.

An organic Rankine cycle-solar dynamic power system (ORC-SDPS) comprises a concentrator, a radiator, a power conversion unit, and a receiver with a thermal energy storage (TES) subsystem which charges and discharges energy to meet power demands during orbital insolation and eclipse periods. Attention is presently given to the criteria used in designing and evaluating an ORC-SDPS TES, as well as the automated test facility employed. It is found that a substantial data base exists for the design of an ORC-SDPS TES subsystem.

Submembranous recruitment of creatine kinase B supports formation of dynamic actin-based protrusions of macrophages and relies on its C-terminal flexible loop.

PubMed

Venter, Gerda; Polling, Saskia; Pluk, Helma; Venselaar, Hanka; Wijers, Mietske; Willemse, Marieke; Fransen, Jack A M; Wieringa, Bé

2015-02-01

Subcellular partitioning of creatine kinase contributes to the formation of patterns in intracellular ATP distribution and the fuelling of cellular processes with a high and sudden energy demand. We have previously shown that brain-type creatine kinase (CK-B) accumulates at the phagocytic cup in macrophages where it is involved in the compartmentalized generation of ATP for actin remodeling. Here, we report that CK-B catalytic activity also helps in the formation of protrusive ruffle structures which are actin-dependent and abundant on the surface of both unstimulated and LPS-activated macrophages. Recruitment of CK-B to these structures occurred transiently and inhibition of the enzyme's catalytic activity with cyclocreatine led to a general smoothening of surface morphology as visualized by scanning electron microscopy. Comparison of the dynamics of distribution of YFP-tagged CK-mutants and isoforms by live imaging revealed that amino acid residues in the C-terminal segment (aa positions 323-330) that forms one of the protein's two mobile loops are involved in partitioning over inner regions of the cytosol and nearby sites where membrane protrusions occur during induction of phagocytic cup formation. Although wt CK-B, muscle-type CK (CK-M), and a catalytically dead CK-B-E232Q mutant with intact loop region were normally recruited from the cytosolic pool, no dynamic transition to the phagocytic cup area was seen for the CK-homologue arginine kinase and a CK-B-D326A mutant protein. Bioinformatics analysis helped us to predict that conformational flexibility of the C-terminal loop, independent of conformational changes induced by substrate binding or catalytic activity, is likely involved in exposing the enzyme for binding at or near the sites of membrane protrusion formation. Copyright © 2014 Elsevier GmbH. All rights reserved.

Vegetation Water Content (VWC) dynamics in during SMAPVEX16

NASA Astrophysics Data System (ADS)

Steele-Dunne, S. C.; Polo Bermejo, J.; Judge, J.; Bongiovanni, T. E.; Chakrabarti, S.; Liu, P. W.; Bragdon, J.; Hornbuckle, B. K.

2016-12-01

Vegetation water content has a confounding effect on the retrieval of soil moisture from microwave brightness temperatures. The presence of water in the overlying canopy influences the emission from the canopy itself and attenuates the emission from the soil. The purpose of this study is to gain insight into the dynamics of vegetation water content in the context of microwave remote sensing. The key questions are: (1) How is moisture distributed in an agricultural canopy? (2) How does that vertical distribution change in time? (3) How do these dynamics influence the observed brightness temperature? To address these questions, a detailed sampling campaign was undertaken in one corn field and one soybean field at an intensively monitored site near Buckeye, Iowa within the SMAPVEX16 domain. The experiment duration extends from the beginning of IOP1 to the end of IOP2, i.e. from May 18 to August 16 2016. Vegetation sampling was performed on days upon which SMAP had both an ascending and a descending pass. On these days, destructive vegetation samples were generally collected at 6pm and 6pm unless the weather conditions were bad. In addition to measuring the bulk vegetation water content for comparison to the SMAP retrieved VWC, the samples were split into leaves and stems. For the corn plants, leaf moisture content was also measured as a function of height and the stem was cut into 10cm sections. Results will be presented to show the changes in VWC associated with plant development through the vegetative and reproductive stages as well as diurnal variations associated with water availability in the root zone and variations in evaporative demand. In addition, fresh biomass, dry biomass and vegetation water content will be related to brightness temperature observations from (1) the SMAP and SMOS satellite missions, (2) the PALS instrument flown during the SMAPVEX16 IOPs in Iowa (3) the tower-based radiometers located at the soybean and corn fields.

System approach to distributed sensor management

NASA Astrophysics Data System (ADS)

Mayott, Gregory; Miller, Gordon; Harrell, John; Hepp, Jared; Self, Mid

2010-04-01

Since 2003, the US Army's RDECOM CERDEC Night Vision Electronic Sensor Directorate (NVESD) has been developing a distributed Sensor Management System (SMS) that utilizes a framework which demonstrates application layer, net-centric sensor management. The core principles of the design support distributed and dynamic discovery of sensing devices and processes through a multi-layered implementation. This results in a sensor management layer that acts as a System with defined interfaces for which the characteristics, parameters, and behaviors can be described. Within the framework, the definition of a protocol is required to establish the rules for how distributed sensors should operate. The protocol defines the behaviors, capabilities, and message structures needed to operate within the functional design boundaries. The protocol definition addresses the requirements for a device (sensors or processes) to dynamically join or leave a sensor network, dynamically describe device control and data capabilities, and allow dynamic addressing of publish and subscribe functionality. The message structure is a multi-tiered definition that identifies standard, extended, and payload representations that are specifically designed to accommodate the need for standard representations of common functions, while supporting the need for feature-based functions that are typically vendor specific. The dynamic qualities of the protocol enable a User GUI application the flexibility of mapping widget-level controls to each device based on reported capabilities in real-time. The SMS approach is designed to accommodate scalability and flexibility within a defined architecture. The distributed sensor management framework and its application to a tactical sensor network will be described in this paper.

Toward a Dynamically Reconfigurable Computing and Communication System for Small Spacecraft

NASA Technical Reports Server (NTRS)

Kifle, Muli; Andro, Monty; Tran, Quang K.; Fujikawa, Gene; Chu, Pong P.

2003-01-01

Future science missions will require the use of multiple spacecraft with multiple sensor nodes autonomously responding and adapting to a dynamically changing space environment. The acquisition of random scientific events will require rapidly changing network topologies, distributed processing power, and a dynamic resource management strategy. Optimum utilization and configuration of spacecraft communications and navigation resources will be critical in meeting the demand of these stringent mission requirements. There are two important trends to follow with respect to NASA's (National Aeronautics and Space Administration) future scientific missions: the use of multiple satellite systems and the development of an integrated space communications network. Reconfigurable computing and communication systems may enable versatile adaptation of a spacecraft system's resources by dynamic allocation of the processor hardware to perform new operations or to maintain functionality due to malfunctions or hardware faults. Advancements in FPGA (Field Programmable Gate Array) technology make it possible to incorporate major communication and network functionalities in FPGA chips and provide the basis for a dynamically reconfigurable communication system. Advantages of higher computation speeds and accuracy are envisioned with tremendous hardware flexibility to ensure maximum survivability of future science mission spacecraft. This paper discusses the requirements, enabling technologies, and challenges associated with dynamically reconfigurable space communications systems.

Integrated analysis of numerical weather prediction and computational fluid dynamics for estimating cross-ventilation effects on inhaled air quality inside a factory

NASA Astrophysics Data System (ADS)

Murga, Alicia; Sano, Yusuke; Kawamoto, Yoichi; Ito, Kazuhide

2017-10-01

Mechanical and passive ventilation strategies directly impact indoor air quality. Passive ventilation has recently become widespread owing to its ability to reduce energy demand in buildings, such as the case of natural or cross ventilation. To understand the effect of natural ventilation on indoor environmental quality, outdoor-indoor flow paths need to be analyzed as functions of urban atmospheric conditions, topology of the built environment, and indoor conditions. Wind-driven natural ventilation (e.g., cross ventilation) can be calculated through the wind pressure coefficient distributions of outdoor wall surfaces and openings of a building, allowing the study of indoor air parameters and airborne contaminant concentrations. Variations in outside parameters will directly impact indoor air quality and residents' health. Numerical modeling can contribute to comprehend these various parameters because it allows full control of boundary conditions and sampling points. In this study, numerical weather prediction modeling was used to calculate wind profiles/distributions at the atmospheric scale, and computational fluid dynamics was used to model detailed urban and indoor flows, which were then integrated into a dynamic downscaling analysis to predict specific urban wind parameters from the atmospheric to built-environment scale. Wind velocity and contaminant concentration distributions inside a factory building were analyzed to assess the quality of the human working environment by using a computer simulated person. The impact of cross ventilation flows and its variations on local average contaminant concentration around a factory worker, and inhaled contaminant dose, were then discussed.

Dynamic Excitatory and Inhibitory Gain Modulation Can Produce Flexible, Robust and Optimal Decision-making

PubMed Central

Niyogi, Ritwik K.; Wong-Lin, KongFatt

2013-01-01

Behavioural and neurophysiological studies in primates have increasingly shown the involvement of urgency signals during the temporal integration of sensory evidence in perceptual decision-making. Neuronal correlates of such signals have been found in the parietal cortex, and in separate studies, demonstrated attention-induced gain modulation of both excitatory and inhibitory neurons. Although previous computational models of decision-making have incorporated gain modulation, their abstract forms do not permit an understanding of the contribution of inhibitory gain modulation. Thus, the effects of co-modulating both excitatory and inhibitory neuronal gains on decision-making dynamics and behavioural performance remain unclear. In this work, we incorporate time-dependent co-modulation of the gains of both excitatory and inhibitory neurons into our previous biologically based decision circuit model. We base our computational study in the context of two classic motion-discrimination tasks performed in animals. Our model shows that by simultaneously increasing the gains of both excitatory and inhibitory neurons, a variety of the observed dynamic neuronal firing activities can be replicated. In particular, the model can exhibit winner-take-all decision-making behaviour with higher firing rates and within a significantly more robust model parameter range. It also exhibits short-tailed reaction time distributions even when operating near a dynamical bifurcation point. The model further shows that neuronal gain modulation can compensate for weaker recurrent excitation in a decision neural circuit, and support decision formation and storage. Higher neuronal gain is also suggested in the more cognitively demanding reaction time than in the fixed delay version of the task. Using the exact temporal delays from the animal experiments, fast recruitment of gain co-modulation is shown to maximize reward rate, with a timescale that is surprisingly near the experimentally fitted value. Our work provides insights into the simultaneous and rapid modulation of excitatory and inhibitory neuronal gains, which enables flexible, robust, and optimal decision-making. PMID:23825935

A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area

USGS Publications Warehouse

Clarke, K.C.; Hoppen, S.; Gaydos, L.

1997-01-01

In this paper we describe a cellular automaton (CA) simulation model developed to predict urban growth as part of a project for estimating the regional and broader impact of urbanization on the San Francisco Bay area's climate. The rules of the model are more complex than those of a typical CA and involve the use of multiple data sources, including topography, road networks, and existing settlement distributions, and their modification over time. In addition, the control parameters of the model are allowed to self-modify: that is, the CA adapts itself to the circumstances it generates, in particular, during periods of rapid growth or stagnation. In addition, the model was written to allow the accumulation of probabilistic estimates based on Monte Carlo methods. Calibration of the model has been accomplished by the use of historical maps to compare model predictions of urbanization, based solely upon the distribution in year 1900, with observed data for years 1940, 1954, 1962, 1974, and 1990. The complexity of this model has made calibration a particularly demanding step. Lessons learned about the methods, measures, and strategies developed to calibrate the model may be of use in other environmental modeling contexts. With the calibration complete, the model is being used to generate a set of future scenarios for the San Francisco Bay area along with their probabilities based on the Monte Carlo version of the model. Animated dynamic mapping of the simulations will be used to allow visualization of the impact of future urban growth.

Development of a coupled model of a distributed hydrological model and a rice growth model for optimizing irrigation schedule

NASA Astrophysics Data System (ADS)

Tsujimoto, Kumiko; Homma, Koki; Koike, Toshio; Ohta, Tetsu

2013-04-01

A coupled model of a distributed hydrological model and a rice growth model was developed in this study. The distributed hydrological model used in this study is the Water and Energy Budget-based Distributed Hydrological Model (WEB-DHM) developed by Wang et al. (2009). This model includes a modified SiB2 (Simple Biosphere Model, Sellers et al., 1996) and the Geomorphology-Based Hydrological Model (GBHM) and thus it can physically calculate both water and energy fluxes. The rice growth model used in this study is the Simulation Model for Rice-Weather relations (SIMRIW) - rainfed developed by Homma et al. (2009). This is an updated version of the original SIMRIW (Horie et al., 1987) and can calculate rice growth by considering the yield reduction due to water stress. The purpose of the coupling is the integration of hydrology and crop science to develop a tool to support decision making 1) for determining the necessary agricultural water resources and 2) for allocating limited water resources to various sectors. The efficient water use and optimal water allocation in the agricultural sector are necessary to balance supply and demand of limited water resources. In addition, variations in available soil moisture are the main reasons of variations in rice yield. In our model, soil moisture and the Leaf Area Index (LAI) are calculated inside SIMRIW-rainfed so that these variables can be simulated dynamically and more precisely based on the rice than the more general calculations is the original WEB-DHM. At the same time by coupling SIMRIW-rainfed with WEB-DHM, lateral flow of soil water, increases in soil moisture and reduction of river discharge due to the irrigation, and its effects on the rice growth can be calculated. Agricultural information such as planting date, rice cultivar, fertilization amount are given in a fully distributed manner. The coupled model was validated using LAI and soil moisture in a small basin in western Cambodia (Sangker River Basin). This basin is mostly rainfed paddy so that irrigation scheme was firstly switched off. Several simulations with varying irrigation scheme were performed to determine the optimal irrigation schedule in this basin.

An empirical analysis of financial development and energy demand: establishing the role of globalization.

PubMed

Saud, Shah; Danish; Chen, Songsheng

2018-06-14

The rapid mode of globalization is experienced in the last few years. The acceleration in globalization expands economic activities through a share of knowledge and transfer of technology which influence energy demand. So, the objective of this empirical work is to explore the impact of financial development on energy demand incorporating globalization. The empirical finding is based on autoregressive distributed lag (ARDL) bound testing approach from 1980 to 2016 in case of China. Overall, we infer that financial development increases energy demand in China. Furthermore, the finding shows that globalization has a negative and significant impact on energy demand. The additional determinants, such as economic growth, and urbanization stimulate energy consumption. Besides, energy consumption granger cause financial development in the long-run path. Similarly, unidirectional causality is detected between globalization and energy consumption. The result gives direction to policymakers to preserve as well as to enhance efficient energy consumption and sustain economic growth in China with acceleration in globalization.

Caring Disposition and Subordination. Swedish Health and Social Care Teachers' Conceptions of Important Vocational Knowledge

ERIC Educational Resources Information Center

Rehn, Helena; Eliasson, Eva

2015-01-01

Based on the increasing demands for vocational training in upper secondary school to adapt to workplace conditions, the aim of this article is to explore vocational teachers' conceptions regarding vocational knowledge. Drawing on a social constructionist perspective, this study analysed data from 17 interviews. The study showed how power dynamics,…

''Can I Drop It This Time?'' Gender and Collaborative Group Dynamics in an Engineering Design-Based Afterschool Program

ERIC Educational Resources Information Center

Schnittka, Jessica; Schnittka, Christine

2016-01-01

The 21st century has brought an increasing demand for expertise in science, technology, engineering, and math (STEM). Although strides have been made towards increasing gender diversity in several of these disciplines, engineering remains primarily male dominated. In response, the U.S. educational system has attempted to make engineering…

CLUH couples mitochondrial distribution to the energetic and metabolic status.

PubMed

Wakim, Jamal; Goudenege, David; Perrot, Rodolphe; Gueguen, Naig; Desquiret-Dumas, Valerie; Chao de la Barca, Juan Manuel; Dalla Rosa, Ilaria; Manero, Florence; Le Mao, Morgane; Chupin, Stephanie; Chevrollier, Arnaud; Procaccio, Vincent; Bonneau, Dominique; Logan, David C; Reynier, Pascal; Lenaers, Guy; Khiati, Salim

2017-06-01

Mitochondrial dynamics and distribution are critical for supplying ATP in response to energy demand. CLUH is a protein involved in mitochondrial distribution whose dysfunction leads to mitochondrial clustering, the metabolic consequences of which remain unknown. To gain insight into the role of CLUH on mitochondrial energy production and cellular metabolism, we have generated CLUH-knockout cells using CRISPR/Cas9. Mitochondrial clustering was associated with a smaller cell size and with decreased abundance of respiratory complexes, resulting in oxidative phosphorylation (OXPHOS) defects. This energetic impairment was found to be due to the alteration of mitochondrial translation and to a metabolic shift towards glucose dependency. Metabolomic profiling by mass spectroscopy revealed an increase in the concentration of some amino acids, indicating a dysfunctional Krebs cycle, and increased palmitoylcarnitine concentration, indicating an alteration of fatty acid oxidation, and a dramatic decrease in the concentrations of phosphatidylcholine and sphingomyeline, consistent with the decreased cell size. Taken together, our study establishes a clear function for CLUH in coupling mitochondrial distribution to the control of cell energetic and metabolic status. © 2017. Published by The Company of Biologists Ltd.