A Quantitative Optimization Framework for Market-Driven Academic Program Portfolios

NARCIS (Netherlands)

Burgher, Joshua; Hamers, Herbert

2017-01-01

We introduce a quantitative model that can be used for decision support for planning and optimizing the composition of portfolios of market-driven academic programs within the context of higher education. This model is intended to enable leaders in colleges and universities to maximize financial

Improved Model for Depth Bias Correction in Airborne LiDAR Bathymetry Systems

Directory of Open Access Journals (Sweden)

Jianhu Zhao

2017-07-01

Full Text Available Airborne LiDAR bathymetry (ALB is efficient and cost effective in obtaining shallow water topography, but often produces a low-accuracy sounding solution due to the effects of ALB measurements and ocean hydrological parameters. In bathymetry estimates, peak shifting of the green bottom return caused by pulse stretching induces depth bias, which is the largest error source in ALB depth measurements. The traditional depth bias model is often applied to reduce the depth bias, but it is insufficient when used with various ALB system parameters and ocean environments. Therefore, an accurate model that considers all of the influencing factors must be established. In this study, an improved depth bias model is developed through stepwise regression in consideration of the water depth, laser beam scanning angle, sensor height, and suspended sediment concentration. The proposed improved model and a traditional one are used in an experiment. The results show that the systematic deviation of depth bias corrected by the traditional and improved models is reduced significantly. Standard deviations of 0.086 and 0.055 m are obtained with the traditional and improved models, respectively. The accuracy of the ALB-derived depth corrected by the improved model is better than that corrected by the traditional model.

Novelty-driven Particle Swarm Optimization

DEFF Research Database (Denmark)

Galvao, Diana; Lehman, Joel Anthony; Urbano, Paulo

2015-01-01

Particle Swarm Optimization (PSO) is a well-known population-based optimization algorithm. Most often it is applied to optimize objective-based fitness functions that reward progress towards a desired objective or behavior. As a result, search increasingly focuses on higher-fitness areas. However......, in problems with many local optima, such focus often leads to premature convergence that precludes reaching the intended objective. To remedy this problem in certain types of domains, this paper introduces Novelty-driven Particle Swarm Optimization (NdPSO), which is motivated by the novelty search algorithm...

Finite-Time Thermoeconomic Optimization of a Solar-Driven Heat Engine Model

Directory of Open Access Journals (Sweden)

Fernando Angulo-Brown

2011-01-01

Full Text Available In the present paper, the thermoeconomic optimization of an irreversible solar-driven heat engine model has been carried out by using finite-time/finite-size thermodynamic theory. In our study we take into account losses due to heat transfer across finite time temperature differences, heat leakage between thermal reservoirs and internal irreversibilities in terms of a parameter which comes from the Clausius inequality. In the considered heat engine model, the heat transfer from the hot reservoir to the working fluid is assumed to be Dulong-Petit type and the heat transfer to the cold reservoir is assumed of the Newtonian type. In this work, the optimum performance and two design parameters have been investigated under two objective functions: the power output per unit total cost and the ecological function per unit total cost. The effects of the technical and economical parameters on the thermoeconomic performance have been also discussed under the aforementioned two criteria of performance.

The impact of bathymetry input on flood simulations

Science.gov (United States)

Khanam, M.; Cohen, S.

2017-12-01

Flood prediction and mitigation systems are inevitable for improving public safety and community resilience all over the worldwide. Hydraulic simulations of flood events are becoming an increasingly efficient tool for studying and predicting flood events and susceptibility. A consistent limitation of hydraulic simulations of riverine dynamics is the lack of information about river bathymetry as most terrain data record water surface elevation. The impact of this limitation on the accuracy on hydraulic simulations of flood has not been well studies over a large range of flood magnitude and modeling frameworks. Advancing our understanding of this topic is timely given emerging national and global efforts for developing automated flood predictions systems (e.g. NOAA National Water Center). Here we study the response of flood simulation to the incorporation of different bathymetry and floodplain surveillance source. Different hydraulic models are compared, Mike-Flood, a 2D hydrodynamic model, and GSSHA, a hydrology/hydraulics model. We test a hypothesis that the impact of inclusion/exclusion of bathymetry data on hydraulic model results will vary in its magnitude as a function of river size. This will allow researcher and stake holders more accurate predictions of flood events providing useful information that will help local communities in a vulnerable flood zone to mitigate flood hazards. Also, it will help to evaluate the accuracy and efficiency of different modeling frameworks and gage their dependency on detailed bathymetry input data.

Gridded multibeam bathymetry and SHOALS LIDAR bathymetry of Penguin Bank, Hawaii, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry (5 m cell size) of Penguin Bank, Hawaii, USA. The netCDF grid and ArcGIS ASCII file include multibeam bathymetry from the Simrad EM3002d, and...

EMODNet Bathymetry - building and providing a high resolution digital bathymetry for European seas

Science.gov (United States)

Schaap, Dick M. A.

2016-04-01

Access to marine data is a key issue for the EU Marine Strategy Framework Directive and the EU Marine Knowledge 2020 agenda and includes the European Marine Observation and Data Network (EMODNet) initiative. EMODNet aims at assembling European marine data, data products and metadata from diverse sources in a uniform way. The EMODNet data infrastructure is developed through a stepwise approach in three major phases. Currently EMODNet is entering its 3rd phase with operational portals providing access to marine data for bathymetry, geology, physics, chemistry, biology, seabed habitats and human activities, complemented by checkpoint projects, analyzing the fitness for purpose of data provision. The EMODNet Bathymetry project develops and publishes Digital Terrain Models (DTM) for the European seas. These are produced from survey and aggregated data sets that are indexed with metadata by adopting from SeaDataNet the Common Data Index (CDI) data discovery and access service and the Sextant data products catalogue service. SeaDataNet is a network of major oceanographic data centers around the European seas that manage, operate and further develop a pan-European infrastructure for marine and ocean data management. SeaDataNet is also setting and governing marine data standards, and exploring and establishing interoperability solutions to connect to other e-infrastructures on the basis of standards such as ISO and OGC. The SeaDataNet portal provides users a number of interrelated meta directories, an extensive range of controlled vocabularies, and the various SeaDataNet standards and tools. SeaDataNet at present gives overview and access to more than 1.8 million data sets for physical oceanography, chemistry, geology, geophysics, bathymetry and biology from more than 100 connected data centers from 34 countries riparian to European seas. The latest EMODNet Bathymetry DTM has a resolution of 1/8 arc minute * 1/8 arc minute and covers all European sea regions. Use is made of

Mosaic of gridded multibeam bathymetry, gridded LiDAR bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Tinian Island, Commonwealth of the Northern Marianas Islands, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with gridded LiDAR bathymetry and bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size)...

Bathymetry and digital elevation models of Coyote Creek and Alviso Slough, South San Francisco Bay, California

Science.gov (United States)

Foxgrover, Amy C.; Finlayson, David P.; Jaffe, Bruce E.; Fregoso, Theresa A.

2012-01-05

In 2010 the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center completed three cruises to map the bathymetry of the main channel and shallow intertidal mudflats in the southernmost part of south San Francisco Bay. The three surveys were merged to generate comprehensive maps of Coyote Creek (from Calaveras Point east to the railroad bridge) and Alviso Slough (from the bay to the town of Alviso) to establish baseline bathymetry prior to the breaching of levees adjacent to Alviso and Guadalupe Sloughs as part of the South Bay Salt Pond Restoration Project (http://www.southbayrestoration.org). Since 2010 the USGS has conducted twelve additional surveys to monitor bathymetric change in this region as restoration progresses.The bathymetry surveys were conducted using the state-of-the-art research vessel R/V Parke Snavely outfitted with an interferometric sidescan sonar for swath mapping in extremely shallow water. This publication provides high-resolution bathymetric data collected by the USGS. For the 2010 baseline survey we have merged the bathymetry with aerial lidar data that were collected for the USGS during the same time period to create a seamless, high-resolution digital elevation model (DEM) of the study area. The series of bathymetry datasets are provided at 1 m resolution and the 2010 bathymetric/topographic DEM at 2 m resolution. The data are formatted as both X, Y, Z text files and ESRI Arc ASCII files that are accompanied by Federal Geographic Data Committee (FGDC) compliant metadata.

Modelling of storm-driven shelf waves north of Scotland—I. Idealized models

Science.gov (United States)

Heaps, N. S.; Huthnance, J. M.; Jones, J. E.; Wolf, J.

1988-11-01

Storm-driven currents observed over the Scottish continental shelf were described by GORDON and HUTHNANCE (1987 , Continental Shelf Research, 7, 1015-1048). Their suggestion of continental shelf-wave responses is investigated here using semi-analytic and numerical models of a straight continental shelf. Grid resolution, boundary conditions, truncations and differences of depth profile are considered with the semi-analytic model, from which dispersion curves and wave forms are derived. These forms are closely matched by the fully numerical model forced by specified elevations at one end. Further numerical calculations are described, for idealized wind forcing along or across limited regions of the shelf or slope. Localized forcing of short duration gives currents of the type observed, being rotary (clockwise) with roughly 22 h period. More extensive alongshelf forcing gives predominantly alongshelf currents with a strength tending to follow the forcing; the second form of observed response. Frictional effects are considered. A companion paper ( FLATHER and PROCTOR, 1988 , in preparation) describes the results of numerical simulations using realistic meteorological forcing and bathymetry.

Response to Comment on "Sensitivity of seafloor bathymetry to climate-driven fluctuations in mid-ocean ridge magma supply".

Science.gov (United States)

Olive, J-A; Behn, M D; Ito, G; Buck, W R; Escartín, J; Howell, S

2016-07-15

Tolstoy reports the existence of a characteristic 100 thousand year (ky) period in the bathymetry of fast-spreading seafloor but does not argue that sea level change is a first-order control on seafloor morphology worldwide. Upon evaluating the overlap between tectonic and Milankovitch periodicities across spreading rates, we reemphasize that fast-spreading ridges are the best potential recorders of a sea level signature in seafloor bathymetry. Copyright © 2016, American Association for the Advancement of Science.

Topology optimization of inertia driven dosing units

DEFF Research Database (Denmark)

Andreasen, Casper Schousboe

2017-01-01

This paper presents a methodology for optimizing inertia driven dosing units, sometimes referred to as eductors, for use in small scale flow applications. The unit is assumed to operate at low to moderate Reynolds numbers and under steady state conditions. By applying topology optimization...

Efficient Data Assimilation Algorithms for Bathymetry Applications

Science.gov (United States)

Ghorbanidehno, H.; Kokkinaki, A.; Lee, J. H.; Farthing, M.; Hesser, T.; Kitanidis, P. K.; Darve, E. F.

2016-12-01

Information on the evolving state of the nearshore zone bathymetry is crucial to shoreline management, recreational safety, and naval operations. The high cost and complex logistics of using ship-based surveys for bathymetry estimation have encouraged the use of remote sensing monitoring. Data assimilation methods combine monitoring data and models of nearshore dynamics to estimate the unknown bathymetry and the corresponding uncertainties. Existing applications have been limited to the basic Kalman Filter (KF) and the Ensemble Kalman Filter (EnKF). The former can only be applied to low-dimensional problems due to its computational cost; the latter often suffers from ensemble collapse and uncertainty underestimation. This work explores the use of different variants of the Kalman Filter for bathymetry applications. In particular, we compare the performance of the EnKF to the Unscented Kalman Filter and the Hierarchical Kalman Filter, both of which are KF variants for non-linear problems. The objective is to identify which method can better handle the nonlinearities of nearshore physics, while also having a reasonable computational cost. We present two applications; first, the bathymetry of a synthetic one-dimensional cross section normal to the shore is estimated from wave speed measurements. Second, real remote measurements with unknown error statistics are used and compared to in situ bathymetric survey data collected at the USACE Field Research Facility in Duck, NC. We evaluate the information content of different data sets and explore the impact of measurement error and nonlinearities.

Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Tutuila Island, American Samoa, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Rose Atoll, American Samoa, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry were...

A Data-Driven Stochastic Reactive Power Optimization Considering Uncertainties in Active Distribution Networks and Decomposition Method

DEFF Research Database (Denmark)

Ding, Tao; Yang, Qingrun; Yang, Yongheng

2018-01-01

To address the uncertain output of distributed generators (DGs) for reactive power optimization in active distribution networks, the stochastic programming model is widely used. The model is employed to find an optimal control strategy with minimum expected network loss while satisfying all......, in this paper, a data-driven modeling approach is introduced to assume that the probability distribution from the historical data is uncertain within a confidence set. Furthermore, a data-driven stochastic programming model is formulated as a two-stage problem, where the first-stage variables find the optimal...... control for discrete reactive power compensation equipment under the worst probability distribution of the second stage recourse. The second-stage variables are adjusted to uncertain probability distribution. In particular, this two-stage problem has a special structure so that the second-stage problem...

EMODNet Bathymetry - building and providing a high resolution digital bathymetry for European seas

Science.gov (United States)

Schaap, D.

2016-12-01

Access to marine data is a key issue for the EU Marine Strategy Framework Directive and the EU Marine Knowledge 2020 agenda and includes the European Marine Observation and Data Network (EMODnet) initiative. The EMODnet Bathymetry project develops and publishes Digital Terrain Models (DTM) for the European seas. These are produced from survey and aggregated data sets that are indexed with metadata by adopting from SeaDataNet the Common Data Index (CDI) data discovery and access service and the Sextant data products catalogue service. SeaDataNet is a network of major oceanographic data centres around the European seas that manage, operate and further develop a pan-European infrastructure for marine and ocean data management. SeaDataNet is also setting and governing marine data standards, and exploring and establishing interoperability solutions to connect to other e-infrastructures on the basis of standards such as ISO and OGC. The SeaDataNet portal provides users a number of interrelated meta directories, an extensive range of controlled vocabularies, and the various SeaDataNet standards and tools. SeaDataNet at present gives overview and access to more than 1.8 million data sets for physical oceanography, chemistry, geology, geophysics, bathymetry and biology from more than 100 connected data centres from 34 countries riparian to European seas. The latest EMODnet Bathymetry DTM has a resolution of 1/8 arcminute * 1/8 arcminute and covers all European sea regions. Use is made of available and gathered surveys and already more than 13.000 surveys have been indexed by 27 European data providers from 15 countries. Also use is made of composite DTMs as generated and maintained by several data providers for their areas of interest. Already 44 composite DTMs are included in the Sextant data products catalogue. For areas without coverage use is made of the latest global DTM of GEBCO who is partner in the EMODnet Bathymetry project. In return GEBCO integrates the EMODnet

Study of 3D bathymetry modelling using LAPAN Surveillance Unmanned Aerial Vehicle 02 (LSU-02) photo data with stereo photogrammetry technique, Wawaran Beach, Pacitan, East Java, Indonesia

Science.gov (United States)

Sari, N. M.; Nugroho, J. T.; Chulafak, G. A.; Kushardono, D.

2018-05-01

Coastal is an ecosystem that has unique object and phenomenon. The potential of the aerial photo data with very high spatial resolution covering coastal area is extensive. One of the aerial photo data can be used is LAPAN Surveillance UAV 02 (LSU-02) photo data which is acquired in 2016 with a spatial resolution reaching 10cm. This research aims to create an initial bathymetry model with stereo photogrammetry technique using LSU-02 data. In this research the bathymetry model was made by constructing 3D model with stereo photogrammetry technique that utilizes the dense point cloud created from overlapping of those photos. The result shows that the 3D bathymetry model can be built with stereo photogrammetry technique. It can be seen from the surface and bathymetry transect profile.

Advances in Optimizing Weather Driven Electric Power Systems.

Science.gov (United States)

Clack, C.; MacDonald, A. E.; Alexander, A.; Dunbar, A. D.; Xie, Y.; Wilczak, J. M.

2014-12-01

The importance of weather-driven renewable energies for the United States (and global) energy portfolio is growing. The main perceived problems with weather-driven renewable energies are their intermittent nature, low power density, and high costs. The National Energy with Weather System Simulator (NEWS) is a mathematical optimization tool that allows the construction of weather-driven energy sources that will work in harmony with the needs of the system. For example, it will match the electric load, reduce variability, decrease costs, and abate carbon emissions. One important test run included existing US carbon-free power sources, natural gas power when needed, and a High Voltage Direct Current power transmission network. This study shows that the costs and carbon emissions from an optimally designed national system decrease with geographic size. It shows that with achievable estimates of wind and solar generation costs, that the US could decrease its carbon emissions by up to 80% by the early 2030s, without an increase in electric costs. The key requirement would be a 48 state network of HVDC transmission, creating a national market for electricity not possible in the current AC grid. These results were found without the need for storage. Further, we tested the effect of changing natural gas fuel prices on the optimal configuration of the national electric power system. Another test that was carried out was an extension to global regions. The extension study shows that the same properties found in the US study extend to the most populous regions of the planet. The extra test is a simplified version of the US study, and is where much more research can be carried out. We compare our results to other model results.

Optimal Hedging with the Vector Autoregressive Model

NARCIS (Netherlands)

L. Gatarek (Lukasz); S.G. Johansen (Soren)

2014-01-01

markdownabstract__Abstract__ We derive the optimal hedging ratios for a portfolio of assets driven by a Cointegrated Vector Autoregressive model with general cointegration rank. Our hedge is optimal in the sense of minimum variance portfolio. We consider a model that allows for the hedges to be

Quantification of Surf Zone Bathymetry from Video Observations of Wave Breaking

Science.gov (United States)

Aarninkhof, S.; Ruessink, G.

2002-12-01

Cost-efficient methods to quantify surf zone bathymetry with high resolution in time and space would be of great value for coastal research and management. Automated video techniques provide the potential to do so. Time-averaged video observations of the nearshore zone show bright intensities at locations where waves preferentially break. Highly similar patterns are found from model simulations of depth-induced wave breaking, which show increasing rates of wave dissipation in shallow areas like sand bars. Thus, video observations of wave breaking - at least qualitatively - reflect sub-merged beach bathymetry. In search of the quantification of this relationship, we present a new model concept to map sub-merged beach bathymetry from time-averaged video images. This is achieved by matching model-predicted and video-observed rates of wave dissipation. First, time-averaged image intensities are sampled along a cross-shore array and interpreted in terms of a wave dissipation parameter. This involves a correction for the effect of persistent foam, which is visible at time-averaged video images but not predicted by common wave propagation models. The dissipation profiles thus obtained are used to update an initial beach bathymetry through optimisation of the match between measured and modelled rates of wave dissipation. The latter is done by raising the bottom elevation in areas where the measured dissipation rate exceeds the computed dissipation and vice versa. Since the model includes video data with high resolution in time (typically multiple images over a tidal cycle), it allows for virtually continous monitoring of surfzone bathymetry . Model tests against a synthetic data set of artificially generated wave dissipation profiles have shown the model's capability to accurately reconstruct beach bathymetry, over a wide range of morphological configurations. Maximum model deviations were found in the case of highly developed bar-trough systems (bar heights up to 4 m) and

Data driven approaches for diagnostics and optimization of NPP operation

International Nuclear Information System (INIS)

Pliska, J.; Machat, Z.

2014-01-01

The efficiency and heat rate is an important indicator of both the health of the power plant equipment and the quality of power plant operation. To achieve this challenges powerful tool is a statistical data processing of large data sets which are stored in data historians. These large data sets contain useful information about process quality and equipment and sensor health. The paper discusses data-driven approaches for model building of main power plant equipment such as condenser, cooling tower and the overall thermal cycle as well using multivariate regression techniques based on so called a regression triplet - data, model and method. Regression models comprise a base for diagnostics and optimization tasks. Diagnostics and optimization tasks are demonstrated on practical cases - diagnostics of main power plant equipment to early identify equipment fault, and optimization task of cooling circuit by cooling water flow control to achieve for a given boundary conditions the highest power output. (authors)

EMODNet Bathymetry - building and providing a high resolution digital bathymetry for European seas

Science.gov (United States)

Schaap, Dick M. A.

2015-04-01

Access to marine data is a key issue for the implementation of the EU Marine Strategy Framework Directive (MSFD). The EU communication 'Marine Knowledge 2020' underpins the importance of data availability and harmonising access to marine data from different sources. The European Marine Observation and Data Network (EMODnet) is a long term marine data initiative from the European Commission Directorate-General for Maritime Affairs and Fisheries (DG MARE) underpinning the Marine Knowledge 2020 strategy. EMODnet is a consortium of organisations assembling European marine data, data products and metadata from diverse sources in a uniform way. The main purpose of EMODnet is to unlock fragmented and hidden marine data resources and to make these available to individuals and organisations (public and private), and to facilitate investment in sustainable coastal and offshore activities through improved access to quality-assured, standardised and harmonised marine data which are interoperable and free of restrictions on use. The EMODnet data infrastructure is developed through a stepwise approach in three major phases. Currently EMODnet is in the 2nd phase of development with seven sub-portals in operation that provide access to marine data from the following themes: bathymetry, geology, physics, chemistry, biology, seabed habitats and human activities. EMODnet development is a dynamic process so new data, products and functionality are added regularly while portals are continuesly improved to make the service more fit for purpose and user friendly with the help of users and stakeholders. The EMODnet Bathymetry project develops and publishes Digital Terrain Models (DTM) for the European seas. These are produced from survey and aggregated data sets, that are indexed with metadata by adopting the SeaDataNet Common Data Index (CDI) data discovery and access service and the SeaDataNet Sextant data products catalogue service. The new EMODnet DTM will have a resolution of 1

Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Palmyra Atoll, Pacific Remote Island Area, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral World View-2 satellite imagery of Sarigan Island, Territory of Mariana, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral World View-2 satellite data. Gridded (10 m cell size) multibeam bathymetry...

Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral World View-2 satellite imagery of Rota Island, Territory of Mariana, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral World View-2 satellite data. Gridded (5 m cell size) multibeam bathymetry...

Observer and data-driven model based fault detection in Power Plant Coal Mills

DEFF Research Database (Denmark)

Fogh Odgaard, Peter; Lin, Bao; Jørgensen, Sten Bay

2008-01-01

model with motor power as the controlled variable, data-driven methods for fault detection are also investigated. Regression models that represent normal operating conditions (NOCs) are developed with both static and dynamic principal component analysis and partial least squares methods. The residual...... between process measurement and the NOC model prediction is used for fault detection. A hybrid approach, where a data-driven model is employed to derive an optimal unknown input observer, is also implemented. The three methods are evaluated with case studies on coal mill data, which includes a fault......This paper presents and compares model-based and data-driven fault detection approaches for coal mill systems. The first approach detects faults with an optimal unknown input observer developed from a simplified energy balance model. Due to the time-consuming effort in developing a first principles...

Optimal hedging with the cointegrated vector autoregressive model

DEFF Research Database (Denmark)

Gatarek, Lukasz; Johansen, Søren

We derive the optimal hedging ratios for a portfolio of assets driven by a Coin- tegrated Vector Autoregressive model (CVAR) with general cointegration rank. Our hedge is optimal in the sense of minimum variance portfolio. We consider a model that allows for the hedges to be cointegrated with the...

Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Ofu and Olosega Islands, Territory of American Samoa, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multipectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

Threshold-driven optimization for reference-based auto-planning

Science.gov (United States)

Long, Troy; Chen, Mingli; Jiang, Steve; Lu, Weiguo

2018-02-01

We study threshold-driven optimization methodology for automatically generating a treatment plan that is motivated by a reference DVH for IMRT treatment planning. We present a framework for threshold-driven optimization for reference-based auto-planning (TORA). Commonly used voxel-based quadratic penalties have two components for penalizing under- and over-dosing of voxels: a reference dose threshold and associated penalty weight. Conventional manual- and auto-planning using such a function involves iteratively updating the preference weights while keeping the thresholds constant, an unintuitive and often inconsistent method for planning toward some reference DVH. However, driving a dose distribution by threshold values instead of preference weights can achieve similar plans with less computational effort. The proposed methodology spatially assigns reference DVH information to threshold values, and iteratively improves the quality of that assignment. The methodology effectively handles both sub-optimal and infeasible DVHs. TORA was applied to a prostate case and a liver case as a proof-of-concept. Reference DVHs were generated using a conventional voxel-based objective, then altered to be either infeasible or easy-to-achieve. TORA was able to closely recreate reference DVHs in 5-15 iterations of solving a simple convex sub-problem. TORA has the potential to be effective for auto-planning based on reference DVHs. As dose prediction and knowledge-based planning becomes more prevalent in the clinical setting, incorporating such data into the treatment planning model in a clear, efficient way will be crucial for automated planning. A threshold-focused objective tuning should be explored over conventional methods of updating preference weights for DVH-guided treatment planning.

Neural networks for the generation of sea bed models using airborne lidar bathymetry data

Science.gov (United States)

Kogut, Tomasz; Niemeyer, Joachim; Bujakiewicz, Aleksandra

2016-06-01

Various sectors of the economy such as transport and renewable energy have shown great interest in sea bed models. The required measurements are usually carried out by ship-based echo sounding, but this method is quite expensive. A relatively new alternative is data obtained by airborne lidar bathymetry. This study investigates the accuracy of these data, which was obtained in the context of the project `Investigation on the use of airborne laser bathymetry in hydrographic surveying'. A comparison to multi-beam echo sounding data shows only small differences in the depths values of the data sets. The IHO requirements of the total horizontal and vertical uncertainty for laser data are met. The second goal of this paper is to compare three spatial interpolation methods, namely Inverse Distance Weighting (IDW), Delaunay Triangulation (TIN), and supervised Artificial Neural Networks (ANN), for the generation of sea bed models. The focus of our investigation is on the amount of required sampling points. This is analyzed by manually reducing the data sets. We found that the three techniques have a similar performance almost independently of the amount of sampling data in our test area. However, ANN are more stable when using a very small subset of points.

Neural networks for the generation of sea bed models using airborne lidar bathymetry data

Directory of Open Access Journals (Sweden)

Kogut Tomasz

2016-06-01

Full Text Available Various sectors of the economy such as transport and renewable energy have shown great interest in sea bed models. The required measurements are usually carried out by ship-based echo sounding, but this method is quite expensive. A relatively new alternative is data obtained by airborne lidar bathymetry. This study investigates the accuracy of these data, which was obtained in the context of the project ‘Investigation on the use of airborne laser bathymetry in hydrographic surveying’. A comparison to multi-beam echo sounding data shows only small differences in the depths values of the data sets. The IHO requirements of the total horizontal and vertical uncertainty for laser data are met. The second goal of this paper is to compare three spatial interpolation methods, namely Inverse Distance Weighting (IDW, Delaunay Triangulation (TIN, and supervised Artificial Neural Networks (ANN, for the generation of sea bed models. The focus of our investigation is on the amount of required sampling points. This is analyzed by manually reducing the data sets. We found that the three techniques have a similar performance almost independently of the amount of sampling data in our test area. However, ANN are more stable when using a very small subset of points.

Mosaic of 10 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Alamagan Island, Commonwealth of Northern Mariana Islands, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (10 m cell size) multibeam bathymetry collected...

Mosaic of 5 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Alamagan Island, Commonwealth of Northern Mariana Islands, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral World View-2 satellite imagery of Baker Island, Pacific Remote Island Areas, Central Pacific.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral World View-2 satellite data. Gridded (10 m cell size) multibeam bathymetry...

Bathymetry for Louisiana, Geographic NAD83, LOSCO (1994) [bathymetry_NOAA_1994

Data.gov (United States)

Louisiana Geographic Information Center — This is a line data depicting the offshore bathymetry_NOAA_1994 for Louisiana. The contour interval is 2 meters. These data were derived from point depths depicted...

Gridded bathymetry of Penguin Bank, Hawaii, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry (5 m cell size) of Penguin Bank, Hawaii, USA. The netCDF grid and ArcGIS ASCII file include multibeam bathymetry from the Simrad EM3002d, and...

Design optimization and fatigue testing of an electronically-driven mechanically-resonant cantilever spring mechanism

International Nuclear Information System (INIS)

Kheng, Lim Boon; Kean, Koay Loke; Gitano-Briggs, Horizon

2010-01-01

A light scanning device consisting of an electronically-driven mechanically-resonant cantilever spring-mirror system has been developed for innovative lighting applications. The repeated flexing of the cantilever spring during operation can lead to premature fatigue failure. A model was created to optimize the spring design. The optimized spring design can reduce stress by approximately one-third from the initial design. Fatigue testing showed that the optimized spring design can operate continuously for over 1 month without failure. Analysis of failures indicates surface cracks near the root of the spring are responsible for the failures.

Model Driven Engineering

Science.gov (United States)

Gaševic, Dragan; Djuric, Dragan; Devedžic, Vladan

A relevant initiative from the software engineering community called Model Driven Engineering (MDE) is being developed in parallel with the Semantic Web (Mellor et al. 2003a). The MDE approach to software development suggests that one should first develop a model of the system under study, which is then transformed into the real thing (i.e., an executable software entity). The most important research initiative in this area is the Model Driven Architecture (MDA), which is Model Driven Architecture being developed under the umbrella of the Object Management Group (OMG). This chapter describes the basic concepts of this software engineering effort.

Pharmacist-driven antimicrobial optimization in the emergency department.

Science.gov (United States)

Davis, Lucretia C; Covey, Robin B; Weston, Jaye S; Hu, Bee Bee Y; Laine, Gregory A

2016-03-01

A pharmacist-driven antimicrobial optimization service in the non-trauma emergency department (ED) of an 864-bed non-profit tertiary care teaching hospital was reviewed to assess its value. Local antimicrobial resistance patterns of urine, wound, stool, and blood cultures were also studied to determine whether or not empiric prescribing practices should be modified. A retrospective electronic chart review was performed for ED patients with positive cultures during two different three-month periods. During Period 1, ED nursing management performed positive culture follow-up. During Period 2, ED clinical pharmacists performed this role. The primary objective was to determine the value of the pharmacist-driven antimicrobial optimization service as measured by the number of clinical interventions made when indicated. The secondary objective was to examine resistance patterns of urine and wound isolates in order to determine if empiric prescribing patterns in the ED should be modified. During Period 1, there were 499 patient visits with subsequent positive cultures. Of those, 76 patients (15%) were discharged home. Nursing management intervened on 21 of 42 (50%) positive cultures that required an intervention; in Period 2, there were 473 patient visits with subsequent positive cultures, and 64 (14%) were discharged home. Pharmacists intervened on 24 of 30 (80%) cultures where an intervention was indicated resulting in a 30% increase in interventions for inappropriate therapy (p = 0.01). A review of the secondary objective revealed a 38% fluoroquinolone resistance rate of E. coli, the most frequently isolated urinary organism. Pharmacist-driven antimicrobial stewardship program resulted in a 30% absolute increase in interventions for inappropriate therapy as compared to the nursing-driven model. This stewardship program has further demonstrated the value of ED pharmacists. Pharmacist interventions should help to ensure that infections are resolved through modification of

Mosaic of 10 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Asuncion Island, Commonwealth of the Northern Marianas Islands, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (10 m cell size) multibeam bathymetry collected...

Mosaic of 5 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Asuncion Island, Commonwealth of the Northern Marianas Islands, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

Great Lakes Bathymetry

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetry of Lakes Michigan, Erie, Saint Clair, Ontario and Huron has been compiled as a component of a NOAA project to rescue Great Lakes lake floor geological and...

Mosaic of 10 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Maug Island, Commonwealth of the Northern Marianas Islands, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (5m and 10 m cell size) multibeam bathymetry...

Mosaic of 5 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Maug Island, Commonwealth of the Northern Marianas Islands, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (5m and 10 m cell size) multibeam bathymetry...

Experimental modelling of wave amplification over irregular bathymetry for investigations of boulder transport by extreme wave events.

Science.gov (United States)

O'Boyle, Louise; Whittaker, Trevor; Cox, Ronadh; Elsäßer, Björn

2017-04-01

During the winter of 2013-2014 the west coast of Ireland was exposed to 6 storms over a period of 8 weeks with wind speeds equating to hurricane categories 3 and 4. During this period, the largest significant wave height recorded at the Marine Institute M6 wave buoy, approximately 300km from the site, was 13.6m (on 26th January 2014). However, this may not be the largest sea state of that winter, because the buoy stopped logging on 30th January and therefore failed to capture the full winter period. During the February 12th 2014 "Darwin" storm, the Kinsale Energy Gas Platform off Ireland's south coast measured a wave height of 25 m, which remains the highest wave measured off Ireland's coasts[1]. Following these storms, significant dislocation and transportation of boulders and megagravel was observed on the Aran Islands, Co. Galway at elevations of up to 25m above the high water mark and distances up to 220 m inland including numerous clasts with masses >50t, and at least one megagravel block weighing >500t [2]. Clast movements of this magnitude would not have been predicted from the measured wave heights. This highlights a significant gap in our understanding of the relationships between storms and the coastal environment: how are storm waves amplified and modified by interactions with bathymetry? To gain further understanding of wave amplification, especially over steep and irregular bathymetry, we have designed Froude-scaled wave tank experiments using the 3D coastal wave basin facility at Queen's University Belfast. The basin is 18m long by 16m wide with wave generation by means of a 12m wide bank of 24 top hinged, force feedback, sector carrier wave paddles at one end. The basin is equipped with gravel beaches to dissipate wave energy on the remaining three sides, capable of absorbing up to 99% of the incident wave energy, to prevent unwanted reflections. Representative bathymetry for the Aran Islands is modelled in the basin based on a high resolution

Data-Driven Handover Optimization in Next Generation Mobile Communication Networks

Directory of Open Access Journals (Sweden)

Po-Chiang Lin

2016-01-01

Full Text Available Network densification is regarded as one of the important ingredients to increase capacity for next generation mobile communication networks. However, it also leads to mobility problems since users are more likely to hand over to another cell in dense or even ultradense mobile communication networks. Therefore, supporting seamless and robust connectivity through such networks becomes a very important issue. In this paper, we investigate handover (HO optimization in next generation mobile communication networks. We propose a data-driven handover optimization (DHO approach, which aims to mitigate mobility problems including too-late HO, too-early HO, HO to wrong cell, ping-pong HO, and unnecessary HO. The key performance indicator (KPI is defined as the weighted average of the ratios of these mobility problems. The DHO approach collects data from the mobile communication measurement results and provides a model to estimate the relationship between the KPI and features from the collected dataset. Based on the model, the handover parameters, including the handover margin and time-to-trigger, are optimized to minimize the KPI. Simulation results show that the proposed DHO approach could effectively mitigate mobility problems.

Gridded bathymetry of Barbers Point, Oahu Hawaii, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry (1m) of Barbers Point ship grounding site, Oahu, Hawaii, USA. The data include multibeam bathymetry from the Reson 8101 multibeam sonar collected...

Small Rov Marine Boat for Bathymetry Surveys of Shallow Waters - Potential Implementation in Malaysia

Science.gov (United States)

Suhari, K. T.; Karim, H.; Gunawan, P. H.; Purwanto, H.

2017-10-01

Current practices in bathymetry survey (available method) are indeed having some limitations. New technologies for bathymetry survey such as using unmanned boat has becoming popular in developed countries - filled in and served those limitations of existing survey methods. Malaysia as one of tropical country has it own river/water body characteristics and suitable approaches in conducting bathymetry survey. Thus, a study on this emerging technology should be conducted using enhanced version of small ROV boat with Malaysian rivers and best approaches so that the surveyors get benefits from the innovative surveying product. Among the available ROV boat for bathymetry surveying in the market, an Indonesian product called SHUMOO is among the promising products - economically and practically proven using a few sample areas in Indonesia. The boat was equipped and integrated with systems of remote sensing technology, GNSS, echo sounder and navigational engine. It was designed for riverbed surveys on shallow area such as small /medium river, lakes, reservoirs, oxidation/detention pond and other water bodies. This paper tries to highlight the needs and enhancement offered to Malaysian' bathymetry surveyors/practitioners on the new ROV boat which make their task easier, faster, safer, economically effective and better riverbed modelling results. The discussion continues with a sample of Indonesia river (data collection and modelling) since it is mostly similar to Malaysia's river characteristics and suggests some improvement for Malaysia best practice.

OESbathy version 1.0: a method for reconstructing ocean bathymetry with realistic continental shelf-slope-rise structures

Science.gov (United States)

Goswami, A.; Olson, P. L.; Hinnov, L. A.; Gnanadesikan, A.

2015-04-01

We present a method for reconstructing global ocean bathymetry that uses a plate cooling model for the oceanic lithosphere, the age distribution of the oceanic crust, global oceanic sediment thicknesses, plus shelf-slope-rise structures calibrated at modern active and passive continental margins. Our motivation is to reconstruct realistic ocean bathymetry based on parameterized relationships of present-day variables that can be applied to global oceans in the geologic past, and to isolate locations where anomalous processes such as mantle convection may affect bathymetry. Parameters of the plate cooling model are combined with ocean crustal age to calculate depth-to-basement. To the depth-to-basement we add an isostatically adjusted, multicomponent sediment layer, constrained by sediment thickness in the modern oceans and marginal seas. A continental shelf-slope-rise structure completes the bathymetry reconstruction, extending from the ocean crust to the coastlines. Shelf-slope-rise structures at active and passive margins are parameterized using modern ocean bathymetry at locations where a complete history of seafloor spreading is preserved. This includes the coastal regions of the North, South, and Central Atlantic Ocean, the Southern Ocean between Australia and Antarctica, and the Pacific Ocean off the west coast of South America. The final products are global maps at 0.1° × 0.1° resolution of depth-to-basement, ocean bathymetry with an isostatically adjusted, multicomponent sediment layer, and ocean bathymetry with reconstructed continental shelf-slope-rise structures. Our reconstructed bathymetry agrees with the measured ETOPO1 bathymetry at most passive margins, including the east coast of North America, north coast of the Arabian Sea, and northeast and southeast coasts of South America. There is disagreement at margins with anomalous continental shelf-slope-rise structures, such as around the Arctic Ocean, the Falkland Islands, and Indonesia.

Optimal design and control of buoyancy-driven ventilation

DEFF Research Database (Denmark)

Terpager Andersen, Karl

2016-01-01

Relationships between airflow rates and opening areas of importance for design and control are analysed for buoyancy-driven ventilation in a room with two openings and uniform temperature. The optimal ratio between the inlet and outlet areas is found. The consequences of deviations from the optimum...

Comparision of Bathymetry and Bottom Characteristics From Hyperspectral Remote Sensing Data and Shipborne Acoustic Measurements

Science.gov (United States)

McIntyre, M. L.; Naar, D. F.; Carder, K. L.; Howd, P. A.; Lewis, J. M.; Donahue, B. T.; Chen, F. R.

2002-12-01

There is growing interest in applying optical remote sensing techniques to shallow-water geological applications such as bathymetry and bottom characterization. Model inversions of hyperspectral remote-sensing reflectance imagery can provide estimates of bottom albedo and depth. This research was conducted in support of the HyCODE (Hyperspectral Coupled Ocean Dynamics Experiment) project in order to test optical sensor performance and the use of a hyperspectral remote-sensing reflectance algorithm for shallow waters in estimating bottom depths and reflectance. The objective of this project was to compare optically derived products of bottom depths and reflectance to shipborne acoustic measurements of bathymetry and backscatter. A set of three high-resolution, multibeam surveys within an 18 km by 1.5 km shore-perpendicular transect 5 km offshore of Sarasota, Florida were collected at water depths ranging from 8 m to 16 m. These products are compared to bottom depths derived from aircraft remote-sensing data collected with the AVIRIS (Airborne Visible-Infrared Imaging Spectrometer) instrument data by means of a semi-analytical remote sensing reflectance model. The pixel size of the multibeam bathymetry and AVIRIS data are 0.25 m and 10 m, respectively. When viewed at full resolution, the multibeam bathymetry data show small-scale sedimentary bedforms (wavelength ~10m, amplitude ~1m) that are not observed in the lower resolution hyperspectral bathymetry. However, model-derived bottom depths agree well with a smoothed version of the multibeam bathymetry. Depths derived from shipborne hyperspectral measurements were accurate within 13%. In areas where diver observations confirmed biological growth and bioturbation, derived bottom depths were less accurate. Acoustic backscatter corresponds well with the aircraft hyperspectral imagery and in situ measurements of bottom reflectance. Acoustic backscatter was used to define the distribution of different bottom types

CryoSat-2 altimetry derived Arctic bathymetry map: first results and validation

Science.gov (United States)

Andersen, O. B.; Abulaitijiang, A.; Cancet, M.; Knudsen, P.

2017-12-01

The Technical University of Denmark (DTU), DTU Space has been developing high quality high resolution gravity fields including the new highly accurate CryoSat-2 radar altimetry satellite data which extends the global coverage of altimetry data up to latitude 88°. With its exceptional Synthetic Aperture Radar (SAR) mode being operating throughout the Arctic Ocean, leads, i.e., the ocean surface heights, is used to retrieve the sea surface height with centimeter-level range precision. Combined with the long repeat cycle ( 369 days), i.e., dense cross-track coverage, the high-resolution Arctic marine gravity can be modelled using the CryoSat-2 altimetry. Further, the polar gap can be filled by the available ArcGP product, thus yielding the complete map of the Arctic bathymetry map. In this presentation, we will make use of the most recent DTU17 marine gravity, to derive the arctic bathymetry map using inversion based on best available hydrographic maps. Through the support of ESA a recent evaluation of existing hydrographic models of the Arctic Ocean Bathymetry models (RTOPO, GEBCO, IBCAO etc) and various inconsistencies have been identified and means to rectify these inconsistencies have been taken prior to perform the inversion using altimetry. Simultaneously DTU Space has been placing great effort on the Arctic data screening, filtering, and de-noising using various altimetry retracking solutions and classifications. All the pre-processing contributed to the fine modelling of Actic gravity map. Thereafter, the arctic marine gravity grids will eventually be translated (downward continuation operation) to a new altimetry enhanced Arctic bathymetry map using appropriate band-pass filtering.

Mosaic of 5m gridded multibeam bathymetry and bathymetry derived from multispectral World View-2 satellite imagery of Swains Island, Territory of American Samoa, South Pacific, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral World View-2 satellite data. Gridded (5 m cell size) multibeam bathymetry...

Optimal Design of a 3-DOF Cable-Driven Upper Arm Exoskeleton

Directory of Open Access Journals (Sweden)

Zhu-Feng Shao

2014-04-01

Full Text Available With outstanding advantages, such as large workspace, flexibility, and lightweight and low inertia, cable-driven parallel manipulator shows great potential for application as the exoskeleton rehabilitation robot. However, the optimal design is still a challenging problem to be solved. In this paper, the optimal design of a 3-DOF (3-degree-of-freedom cable-driven upper arm exoskeleton is accomplished considering the force exerted on the arm. After analysis of the working conditions, two promising configurations of the cable-driven upper arm exoskeleton are put forward and design parameters are simplified. Then, candidate ranges of two angle parameters are determined with the proposed main workspace requirement. Further, global force indices are defined to evaluate the force applied to the arm by the exoskeleton, in order to enhance the system safety and comfort. Finally, the optimal design of each configuration is obtained with proposed force indices. In addition, atlases and charts given in this paper well illustrate trends of workspace and force with different values of design parameters.

Optimizing preventive maintenance policy: A data-driven application for a light rail braking system.

Science.gov (United States)

Corman, Francesco; Kraijema, Sander; Godjevac, Milinko; Lodewijks, Gabriel

2017-10-01

This article presents a case study determining the optimal preventive maintenance policy for a light rail rolling stock system in terms of reliability, availability, and maintenance costs. The maintenance policy defines one of the three predefined preventive maintenance actions at fixed time-based intervals for each of the subsystems of the braking system. Based on work, maintenance, and failure data, we model the reliability degradation of the system and its subsystems under the current maintenance policy by a Weibull distribution. We then analytically determine the relation between reliability, availability, and maintenance costs. We validate the model against recorded reliability and availability and get further insights by a dedicated sensitivity analysis. The model is then used in a sequential optimization framework determining preventive maintenance intervals to improve on the key performance indicators. We show the potential of data-driven modelling to determine optimal maintenance policy: same system availability and reliability can be achieved with 30% maintenance cost reduction, by prolonging the intervals and re-grouping maintenance actions.

Task driven optimal leg trajectories in insect-scale legged microrobots

Science.gov (United States)

Doshi, Neel; Goldberg, Benjamin; Jayaram, Kaushik; Wood, Robert

Origami inspired layered manufacturing techniques and 3D-printing have enabled the development of highly articulated legged robots at the insect-scale, including the 1.43g Harvard Ambulatory MicroRobot (HAMR). Research on these platforms has expanded its focus from manufacturing aspects to include design optimization and control for application-driven tasks. Consequently, the choice of gait selection, body morphology, leg trajectory, foot design, etc. have become areas of active research. HAMR has two controlled degrees-of-freedom per leg, making it an ideal candidate for exploring leg trajectory. We will discuss our work towards optimizing HAMR's leg trajectories for two different tasks: climbing using electroadhesives and level ground running (5-10 BL/s). These tasks demonstrate the ability of single platform to adapt to vastly different locomotive scenarios: quasi-static climbing with controlled ground contact, and dynamic running with un-controlled ground contact. We will utilize trajectory optimization methods informed by existing models and experimental studies to determine leg trajectories for each task. We also plan to discuss how task specifications and choice of objective function have contributed to the shape of these optimal leg trajectories.

An explicit parametrization for casting constraints in gradient driven topology optimization

DEFF Research Database (Denmark)

Gersborg, Allan Roulund; Andreasen, Casper Schousboe

From a practical point of view it is often desirable to limit the complexity of a topology design such that casting/milling type manufacturing techniques can be applied. In the context of gradient driven topology optimization this work studies how castable designs can be obtained by use of a Heav......From a practical point of view it is often desirable to limit the complexity of a topology design such that casting/milling type manufacturing techniques can be applied. In the context of gradient driven topology optimization this work studies how castable designs can be obtained by use...

3rd International Workshop on Advances in Simulation-Driven Optimization and Modeling

CERN Document Server

Leifsson, Leifur; Yang, Xin-She

2016-01-01

This edited volume is devoted to the now-ubiquitous use of computational models across most disciplines of engineering and science, led by a trio of world-renowned researchers in the field. Focused on recent advances of modeling and optimization techniques aimed at handling computationally-expensive engineering problems involving simulation models, this book will be an invaluable resource for specialists (engineers, researchers, graduate students) working in areas as diverse as electrical engineering, mechanical and structural engineering, civil engineering, industrial engineering, hydrodynamics, aerospace engineering, microwave and antenna engineering, ocean science and climate modeling, and the automotive industry, where design processes are heavily based on CPU-heavy computer simulations. Various techniques, such as knowledge-based optimization, adjoint sensitivity techniques, and fast replacement models (to name just a few) are explored in-depth along with an array of the latest techniques to optimize the...

OESbathy version 1.0: a method for reconstructing ocean bathymetry with generalized continental shelf-slope-rise structures

Science.gov (United States)

Goswami, A.; Olson, P. L.; Hinnov, L. A.; Gnanadesikan, A.

2015-09-01

We present a method for reconstructing global ocean bathymetry that combines a standard plate cooling model for the oceanic lithosphere based on the age of the oceanic crust, global oceanic sediment thicknesses, plus generalized shelf-slope-rise structures calibrated at modern active and passive continental margins. Our motivation is to develop a methodology for reconstructing ocean bathymetry in the geologic past that includes heterogeneous continental margins in addition to abyssal ocean floor. First, the plate cooling model is applied to maps of ocean crustal age to calculate depth to basement. To the depth to basement we add an isostatically adjusted, multicomponent sediment layer constrained by sediment thickness in the modern oceans and marginal seas. A three-parameter continental shelf-slope-rise structure completes the bathymetry reconstruction, extending from the ocean crust to the coastlines. Parameters of the shelf-slope-rise structures at active and passive margins are determined from modern ocean bathymetry at locations where a complete history of seafloor spreading is preserved. This includes the coastal regions of the North, South, and central Atlantic, the Southern Ocean between Australia and Antarctica, and the Pacific Ocean off the west coast of South America. The final products are global maps at 0.1° × 0.1° resolution of depth to basement, ocean bathymetry with an isostatically adjusted multicomponent sediment layer, and ocean bathymetry with reconstructed continental shelf-slope-rise structures. Our reconstructed bathymetry agrees with the measured ETOPO1 bathymetry at most passive margins, including the east coast of North America, north coast of the Arabian Sea, and northeast and southeast coasts of South America. There is disagreement at margins with anomalous continental shelf-slope-rise structures, such as around the Arctic Ocean, the Falkland Islands, and Indonesia.

Modeling and optimization of HVAC energy consumption

Energy Technology Data Exchange (ETDEWEB)

Kusiak, Andrew; Li, Mingyang; Tang, Fan [Department of Mechanical and Industrial Engineering, University of Iowa, Iowa City, IA 52242 - 1527 (United States)

2010-10-15

A data-driven approach for minimization of the energy to air condition a typical office-type facility is presented. Eight data-mining algorithms are applied to model the nonlinear relationship among energy consumption, control settings (supply air temperature and supply air static pressure), and a set of uncontrollable parameters. The multiple-linear perceptron (MLP) ensemble outperforms other models tested in this research, and therefore it is selected to model a chiller, a pump, a fan, and a reheat device. These four models are integrated into an energy optimization model with two decision variables, the setpoint of the supply air temperature and the static pressure in the air handling unit. The model is solved with a particle swarm optimization algorithm. The optimization results have demonstrated the total energy consumed by the heating, ventilation, and air-conditioning system is reduced by over 7%. (author)

Optimal Stopping Problems Driven by Lévy Processes and Pasting Principles

NARCIS (Netherlands)

Surya, B.A.

2007-01-01

Solving optimal stopping problems driven by Lévy processes has been a challenging task and has found many applications in modern theory of mathematical finance. For example situations in which optimal stopping typically arise include the problem of finding the arbitrage-free price of the American

Design Optimization of a Cable-Driven Two-DOF Flexible Joint Module

Directory of Open Access Journals (Sweden)

Zhao Zhang

2012-11-01

Full Text Available This paper focuses on the kinematics, kinetostatics and design optimization of a 2-DOF cable-driven flexible joint module. Based on the motion characteristics of the 2-DOF joint module, the concept of instantaneous screw axis in conjunction with the Product-Of-Exponentials (POE formula is proposed to formulate its kinematic model. However, as the instantaneous screw axis is unfixed, the Lie group method is employed to derive the instantaneous kinematic model of the joint module. In order to generate the feasible workspace subject to positive tension constraint, the kinetostatics of the joint module is addressed, where the stiffness resulting from both the driving cables and the flexible backbone are considered. A numerical orientation workspace evaluation method is proposed based on an equi-volumetric partition in its parametric space and the volume-element associated integral factor. A global singular value (GSV index, which considers the minimum singular value of the stiffness matrix of joint module over the achievable workspace, is employed to optimize the geometric size of joint module. The simulation results demonstrate the effectiveness of the proposed GSV optimization algorithm.

Bathymetry of Lake Ontario

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetry of Lake Ontario has been compiled as a component of a NOAA project to rescue Great Lakes lake floor geological and geophysical data and make it more...

Bathymetry of Lake Michigan

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetry of Lake Michigan has been compiled as a component of a NOAA project to rescue Great Lakes lake floor geological and geophysical data and make it more...

Bathymetry of Lake Superior

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetry of Lake Superior has been compiled as a component of a NOAA project to rescue Great Lakes lake floor geological and geophysical data and make it more...

Bathymetry of Lake Huron

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetry of Lake Huron has been compiled as a component of a NOAA project to rescue Great Lakes lake floor geological and geophysical data and make it more...

Infrared laser driven double proton transfer. An optimal control theory study

Science.gov (United States)

Abdel-Latif, Mahmoud K.; Kühn, Oliver

2010-02-01

Laser control of ultrafast double proton transfer is investigated for a two-dimensional model system describing stepwise and concerted transfer pathways. The pulse design has been done by employing optimal control theory in combination with the multiconfiguration time-dependent Hartree wave packet propagation. The obtained laser fields correspond to multiple pump-dump pulse sequences. Special emphasis is paid to the relative importance of stepwise and concerted transfer pathways for the driven wave packet and its dependence on the parameters of the model Hamiltonian as well as on the propagation time. While stepwise transfer is dominating in all cases considered, for high barrier systems concerted transfer proceeding via tunneling can make a contribution.

SMALL ROV MARINE BOAT FOR BATHYMETRY SURVEYS OF SHALLOW WATERS – POTENTIAL IMPLEMENTATION IN MALAYSIA

Directory of Open Access Journals (Sweden)

K. T. Suhari

2017-10-01

Full Text Available Current practices in bathymetry survey (available method are indeed having some limitations. New technologies for bathymetry survey such as using unmanned boat has becoming popular in developed countries - filled in and served those limitations of existing survey methods. Malaysia as one of tropical country has it own river/water body characteristics and suitable approaches in conducting bathymetry survey. Thus, a study on this emerging technology should be conducted using enhanced version of small ROV boat with Malaysian rivers and best approaches so that the surveyors get benefits from the innovative surveying product. Among the available ROV boat for bathymetry surveying in the market, an Indonesian product called SHUMOO is among the promising products – economically and practically proven using a few sample areas in Indonesia. The boat was equipped and integrated with systems of remote sensing technology, GNSS, echo sounder and navigational engine. It was designed for riverbed surveys on shallow area such as small /medium river, lakes, reservoirs, oxidation/detention pond and other water bodies. This paper tries to highlight the needs and enhancement offered to Malaysian’ bathymetry surveyors/practitioners on the new ROV boat which make their task easier, faster, safer, economically effective and better riverbed modelling results. The discussion continues with a sample of Indonesia river (data collection and modelling since it is mostly similar to Malaysia’s river characteristics and suggests some improvement for Malaysia best practice.

Optimal Velocity Control for a Battery Electric Vehicle Driven by Permanent Magnet Synchronous Motors

Directory of Open Access Journals (Sweden)

Dongbin Lu

2014-01-01

Full Text Available The permanent magnet synchronous motor (PMSM has high efficiency and high torque density. Field oriented control (FOC is usually used in the motor to achieve maximum efficiency control. In the electric vehicle (EV application, the PMSM efficiency model, combined with the EV and road load system model, is used to study the optimal energy-saving control strategy, which is significant for the economic operation of EVs. With the help of GPS, IMU, and other information technologies, the road conditions can be measured in advance. Based on this information, the optimal velocity of the EV driven by PMSM can be obtained through the analytical algorithm according to the efficiency model of PMSM and the vehicle dynamic model in simple road conditions. In complex road conditions, considering the dynamic characteristics, the economic operating velocity trajectory of the EV can be obtained through the dynamic programming (DP algorithm. Simulation and experimental results show that the minimum energy consumption and global energy optimization can be achieved when the EV operates in the economic operation area.

Minimization of energy consumption in HVAC systems with data-driven models and an interior-point method

International Nuclear Information System (INIS)

Kusiak, Andrew; Xu, Guanglin; Zhang, Zijun

2014-01-01

Highlights: • We study the energy saving of HVAC systems with a data-driven approach. • We conduct an in-depth analysis of the topology of developed Neural Network based HVAC model. • We apply interior-point method to solving a Neural Network based HVAC optimization model. • The uncertain building occupancy is incorporated in the minimization of HVAC energy consumption. • A significant potential of saving HVAC energy is discovered. - Abstract: In this paper, a data-driven approach is applied to minimize energy consumption of a heating, ventilating, and air conditioning (HVAC) system while maintaining the thermal comfort of a building with uncertain occupancy level. The uncertainty of arrival and departure rate of occupants is modeled by the Poisson and uniform distributions, respectively. The internal heating gain is calculated from the stochastic process of the building occupancy. Based on the observed and simulated data, a multilayer perceptron algorithm is employed to model and simulate the HVAC system. The data-driven models accurately predict future performance of the HVAC system based on the control settings and the observed historical information. An optimization model is formulated and solved with the interior-point method. The optimization results are compared with the results produced by the simulation models

Surrogate-Based Optimization of Biogeochemical Transport Models

Science.gov (United States)

Prieß, Malte; Slawig, Thomas

2010-09-01

First approaches towards a surrogate-based optimization method for a one-dimensional marine biogeochemical model of NPZD type are presented. The model, developed by Oschlies and Garcon [1], simulates the distribution of nitrogen, phytoplankton, zooplankton and detritus in a water column and is driven by ocean circulation data. A key issue is to minimize the misfit between the model output and given observational data. Our aim is to reduce the overall optimization cost avoiding expensive function and derivative evaluations by using a surrogate model replacing the high-fidelity model in focus. This in particular becomes important for more complex three-dimensional models. We analyse a coarsening in the discretization of the model equations as one way to create such a surrogate. Here the numerical stability crucially depends upon the discrete stepsize in time and space and the biochemical terms. We show that for given model parameters the level of grid coarsening can be choosen accordingly yielding a stable and satisfactory surrogate. As one example of a surrogate-based optimization method we present results of the Aggressive Space Mapping technique (developed by John W. Bandler [2, 3]) applied to the optimization of this one-dimensional biogeochemical transport model.

Mosaic of gridded multibeam and lidar bathymetry of the US Territory of Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with gridded lidar bathymetry. Gridded (5 m cell size) multibeam bathymetry were collected aboard NOAA Ship Hiialaka'i and...

EMODnet High Resolution Seabed Mapping - further developing a high resolution digital bathymetry for European seas

Science.gov (United States)

Schaap, D.; Schmitt, T.

2017-12-01

Access to marine data is a key issue for the EU Marine Strategy Framework Directive and the EU Marine Knowledge 2020 agenda and includes the European Marine Observation and Data Network (EMODnet) initiative. EMODnet aims at assembling European marine data, data products and metadata from diverse sources in a uniform way. The EMODnet Bathymetry project has developed Digital Terrain Models (DTM) for the European seas. These have been produced from survey and aggregated data sets that are indexed with metadata by adopting the SeaDataNet Catalogue services. SeaDataNet is a network of major oceanographic data centres around the European seas that manage, operate and further develop a pan-European infrastructure for marine and ocean data management. The latest EMODnet Bathymetry DTM release has a grid resolution of 1/8 arcminute and covers all European sea regions. Use has been made of circa 7800 gathered survey datasets and composite DTMs. Catalogues and the EMODnet DTM are published at the dedicated EMODnet Bathymetry portal including a versatile DTM viewing and downloading service. End December 2016 the Bathymetry project has been succeeded by EMODnet High Resolution Seabed Mapping (HRSM). This continues gathering of bathymetric in-situ data sets with extra efforts for near coastal waters and coastal zones. In addition Satellite Derived Bathymetry data are included to fill gaps in coverage of the coastal zones. The extra data and composite DTMs will increase the coverage of the European seas and its coastlines, and provide input for producing an EMODnet DTM with a common resolution of 1/16 arc minutes. The Bathymetry Viewing and Download service will be upgraded to provide a multi-resolution map and including 3D viewing. The higher resolution DTMs will also be used to determine best-estimates of the European coastline for a range of tidal levels (HAT, MHW, MSL, Chart Datum, LAT), thereby making use of a tidal model for Europe. Extra challenges will be `moving to the

Gridded multibeam bathymetry of Apra Harbor, Guam U.S. Territory

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry from Apra Harbor, Guam U.S. Territory. The netCDF and Arc ASCII grids include multibeam bathymetry from the Reson SeaBat 8125 multibeam sonar...

Data-driven forward model inference for EEG brain imaging

DEFF Research Database (Denmark)

Hansen, Sofie Therese; Hauberg, Søren; Hansen, Lars Kai

2016-01-01

Electroencephalography (EEG) is a flexible and accessible tool with excellent temporal resolution but with a spatial resolution hampered by volume conduction. Reconstruction of the cortical sources of measured EEG activity partly alleviates this problem and effectively turns EEG into a brain......-of-concept study, we show that, even when anatomical knowledge is unavailable, a suitable forward model can be estimated directly from the EEG. We propose a data-driven approach that provides a low-dimensional parametrization of head geometry and compartment conductivities, built using a corpus of forward models....... Combined with only a recorded EEG signal, we are able to estimate both the brain sources and a person-specific forward model by optimizing this parametrization. We thus not only solve an inverse problem, but also optimize over its specification. Our work demonstrates that personalized EEG brain imaging...

Rugosity grid derived from gridded bathymetry of Ni'ihau Island, Hawaii, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (5 m cell size) multibeam bathymetry, collected aboard NOAA ship Hi'ialakai and R/V AHI using the Benthic Terrain Modeler with...

Rugosity grid derived from gridded bathymetry of French Frigate Shoals, Hawaii, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (5 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hiialaka'i and R/V AHI, using the Benthic Terrain Modeler with...

An X-Band Radar System for Bathymetry and Wave Field Analysis in a Harbour Area

Directory of Open Access Journals (Sweden)

Giovanni Ludeno

2015-01-01

Full Text Available Marine X-band radar based systems are well tested to provide information about sea state and bathymetry. It is also well known that complex geometries and non-uniform bathymetries provide a much bigger challenge than offshore scenarios. In order to tackle this issue a retrieval method is proposed, based on spatial partitioning of the data and the application of the Normalized Scalar Product (NSP, which is an innovative procedure for the joint estimation of bathymetry and surface currents. The strategy is then applied to radar data acquired around a harbour entrance, and results show that the reconstructed bathymetry compares well with ground truth data obtained by an echo-sounder campaign, thus proving the reliability of the whole procedure. The spectrum thus retrieved is then analysed to show the evidence of reflected waves from the harbour jetties, as confirmed by chain of hydrodynamic models of the sea wave field. The possibility of using a land based radar to reveal sea wave reflection is entirely new and may open up new operational applications of the system.

Evaluating integration of inland bathymetry in the U.S. Geological Survey 3D Elevation Program, 2014

Science.gov (United States)

Miller-Corbett, Cynthia

2016-09-01

Inland bathymetry survey collections, survey data types, features, sources, availability, and the effort required to integrate inland bathymetric data into the U.S. Geological Survey 3D Elevation Program are assessed to help determine the feasibility of integrating three-dimensional water feature elevation data into The National Map. Available data from wading, acoustic, light detection and ranging, and combined technique surveys are provided by the U.S. Geological Survey, National Oceanic and Atmospheric Administration, U.S. Army Corps of Engineers, and other sources. Inland bathymetric data accessed through Web-hosted resources or contacts provide useful baseline parameters for evaluating survey types and techniques used for collection and processing, and serve as a basis for comparing survey methods and the quality of results. Historically, boat-mounted acoustic surveys have provided most inland bathymetry data. Light detection and ranging techniques that are beneficial in areas hard to reach by boat, that can collect dense data in shallow water to provide comprehensive coverage, and that can be cost effective for surveying large areas with good water clarity are becoming more common; however, optimal conditions and techniques for collecting and processing light detection and ranging inland bathymetry surveys are not yet well defined.Assessment of site condition parameters important for understanding inland bathymetry survey issues and results, and an evaluation of existing inland bathymetry survey coverage are proposed as steps to develop criteria for implementing a useful and successful inland bathymetry survey plan in the 3D Elevation Program. These survey parameters would also serve as input for an inland bathymetry survey data baseline. Integration and interpolation techniques are important factors to consider in developing a robust plan; however, available survey data are usually in a triangulated irregular network format or other format compatible with

Product quality driven design of bakery operations using dynamic optimization

NARCIS (Netherlands)

Hadiyanto, M.; Esveld, D.C.; Boom, R.M.; Straten, van G.; Boxtel, van A.J.B.

2008-01-01

Abstract Quality driven design uses specified product qualities as a starting point for process design. By backward reasoning the required process conditions and processing system were found. In this work dynamic optimization was used as a tool to generate processing solutions for baking processes

Test-driven verification/validation of model transformations

Institute of Scientific and Technical Information of China (English)

László LENGYEL; Hassan CHARAF

2015-01-01

Why is it important to verify/validate model transformations? The motivation is to improve the quality of the trans-formations, and therefore the quality of the generated software artifacts. Verified/validated model transformations make it possible to ensure certain properties of the generated software artifacts. In this way, verification/validation methods can guarantee different requirements stated by the actual domain against the generated/modified/optimized software products. For example, a verified/ validated model transformation can ensure the preservation of certain properties during the model-to-model transformation. This paper emphasizes the necessity of methods that make model transformation verified/validated, discusses the different scenarios of model transformation verification and validation, and introduces the principles of a novel test-driven method for verifying/ validating model transformations. We provide a solution that makes it possible to automatically generate test input models for model transformations. Furthermore, we collect and discuss the actual open issues in the field of verification/validation of model transformations.

Hybrid kriging methods for interpolating sparse river bathymetry point data

Directory of Open Access Journals (Sweden)

Pedro Velloso Gomes Batista

Full Text Available ABSTRACT Terrain models that represent riverbed topography are used for analyzing geomorphologic changes, calculating water storage capacity, and making hydrologic simulations. These models are generated by interpolating bathymetry points. River bathymetry is usually surveyed through cross-sections, which may lead to a sparse sampling pattern. Hybrid kriging methods, such as regression kriging (RK and co-kriging (CK employ the correlation with auxiliary predictors, as well as inter-variable correlation, to improve the predictions of the target variable. In this study, we use the orthogonal distance of a (x, y point to the river centerline as a covariate for RK and CK. Given that riverbed elevation variability is abrupt transversely to the flow direction, it is expected that the greater the Euclidean distance of a point to the thalweg, the greater the bed elevation will be. The aim of this study was to evaluate if the use of the proposed covariate improves the spatial prediction of riverbed topography. In order to asses such premise, we perform an external validation. Transversal cross-sections are used to make the spatial predictions, and the point data surveyed between sections are used for testing. We compare the results from CK and RK to the ones obtained from ordinary kriging (OK. The validation indicates that RK yields the lowest RMSE among the interpolators. RK predictions represent the thalweg between cross-sections, whereas the other methods under-predict the river thalweg depth. Therefore, we conclude that RK provides a simple approach for enhancing the quality of the spatial prediction from sparse bathymetry data.

Determining an energy-optimal thermal management strategy for electric driven vehicles

Energy Technology Data Exchange (ETDEWEB)

Suchaneck, Andre; Probst, Tobias; Puente Leon, Fernando [Karlsruher Institut fuer Technology (KIT), Karlsruhe (Germany). Inst. of Industrial Information Technology (IIIT)

2012-11-01

In electric, hybrid electric and fuel cell vehicles, thermal management may have a significant impact on vehicle range. Therefore, optimal thermal management strategies are required. In this paper a method for determining an energy-optimal control strategy for thermal power generation in electric driven vehicles is presented considering all controlled devices (pumps, valves, fans, and the like) as well as influences like ambient temperature, vehicle speed, motor and battery and cooling cycle temperatures. The method is designed to be generic to increase the thermal management development process speed and to achieve the maximal energy reduction for any electric driven vehicle (e.g., by waste heat utilization). Based on simulations of a prototype electric vehicle with an advanced cooling cycle structure, the potential of the method is shown. (orig.)

Performance Assessment of High Resolution Airborne Full Waveform LiDAR for Shallow River Bathymetry

Directory of Open Access Journals (Sweden)

Zhigang Pan

2015-04-01

Full Text Available We evaluate the performance of full waveform LiDAR decomposition algorithms with a high-resolution single band airborne LiDAR bathymetry system in shallow rivers. A continuous wavelet transformation (CWT is proposed and applied in two fluvial environments, and the results are compared to existing echo retrieval methods. LiDAR water depths are also compared to independent field measurements. In both clear and turbid water, the CWT algorithm outperforms the other methods if only green LiDAR observations are available. However, both the definition of the water surface, and the turbidity of the water significantly influence the performance of the LiDAR bathymetry observations. The results suggest that there is no single best full waveform processing algorithm for all bathymetric situations. Overall, the optimal processing strategies resulted in a determination of water depths with a 6 cm mean at 14 cm standard deviation for clear water, and a 16 cm mean and 27 cm standard deviation in more turbid water.

Optimization of a solar driven absorption refrigerator in the transient regime

International Nuclear Information System (INIS)

Hamed, Mouna; Fellah, Ali; Ben Brahim, Ammar

2012-01-01

Highlights: ► Dynamic behavior of a solar absorption refrigerator endoreversible model. ► Using the principles of classical thermodynamics, mass and heat transfers. ► Minimizing heat exchange time to reach maximum performances. ► Major influence of the collector temperature on the model’s characteristics. ► Analogous effects of both the thermal load and the thermal conductance. -- Abstract: This contribution deals with the theoretical study in dynamic mode of an absorption refrigerator endoreversible model. The system is a cold generating station driven by solar energy. The main elements of the cycle are a refrigerated space, an absorption refrigerator and a solar collector form. A mathematical model is developed. It combines the classical thermodynamics and mass and heat transfers principles. The numerical simulation is made for different operating and conceptual conditions. A global minimizing time optimization is performed in view to reach maximum performances. Appropriate dimensionless groups are defined. The results are presented in normalized charts for general applications. The collector temperature presents major influence on the conceptual and functional characteristics compared to the stagnation temperature influence. On the other hand the thermal load in the refrigerated space and the thermal conductance of the walls has analogous effects, therefore important to be considered in actual design. As a result, the model is expected to be a useful tool for simulation, design, and optimization of solar collector based energy systems.

Rugosity grid derived from gridded bathymetry of Apra Harbor, Guam U.S. Territory

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (1 m cell size) multibeam bathymetry, collected aboard the Survey Vessel Swamp Fox using the Terrain Modeler with rugosity methods...

Coverage map of gridded multibeam and lidar bathymetry of the US Territory of Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with gridded lidar bathymetry. Gridded (5 m cell size) multibeam bathymetry were collected aboard NOAA Ship Hiialaka'i and...

Multiple Active Contours Driven by Particle Swarm Optimization for Cardiac Medical Image Segmentation

Science.gov (United States)

Cruz-Aceves, I.; Aviña-Cervantes, J. G.; López-Hernández, J. M.; González-Reyna, S. E.

2013-01-01

This paper presents a novel image segmentation method based on multiple active contours driven by particle swarm optimization (MACPSO). The proposed method uses particle swarm optimization over a polar coordinate system to increase the energy-minimizing capability with respect to the traditional active contour model. In the first stage, to evaluate the robustness of the proposed method, a set of synthetic images containing objects with several concavities and Gaussian noise is presented. Subsequently, MACPSO is used to segment the human heart and the human left ventricle from datasets of sequential computed tomography and magnetic resonance images, respectively. Finally, to assess the performance of the medical image segmentations with respect to regions outlined by experts and by the graph cut method objectively and quantifiably, a set of distance and similarity metrics has been adopted. The experimental results demonstrate that MACPSO outperforms the traditional active contour model in terms of segmentation accuracy and stability. PMID:23762177

OESbathy version 1.0: a method for reconstructing ocean bathymetry with realistic continental shelf-slope-rise structures

OpenAIRE

A. Goswami; P. L. Olson; L. A. Hinnov; A. Gnanadesikan

2015-01-01

We present a method for reconstructing global ocean bathymetry that uses a plate cooling model for the oceanic lithosphere, the age distribution of the oceanic crust, global oceanic sediment thicknesses, plus shelf-slope-rise structures calibrated at modern active and passive continental margins. Our motivation is to reconstruct realistic ocean bathymetry based on parameterized relationships of present-day variables that can be applied to global oceans in th...

Data Driven Economic Model Predictive Control

Directory of Open Access Journals (Sweden)

Masoud Kheradmandi

2018-04-01

Full Text Available This manuscript addresses the problem of data driven model based economic model predictive control (MPC design. To this end, first, a data-driven Lyapunov-based MPC is designed, and shown to be capable of stabilizing a system at an unstable equilibrium point. The data driven Lyapunov-based MPC utilizes a linear time invariant (LTI model cognizant of the fact that the training data, owing to the unstable nature of the equilibrium point, has to be obtained from closed-loop operation or experiments. Simulation results are first presented demonstrating closed-loop stability under the proposed data-driven Lyapunov-based MPC. The underlying data-driven model is then utilized as the basis to design an economic MPC. The economic improvements yielded by the proposed method are illustrated through simulations on a nonlinear chemical process system example.

Rugosity 5m grid derived from gridded bathymetry of Brooks Banks, Hawaii, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (5 m cell size) multibeam bathymetry, collected aboard NOAA ship Hi'ialakai and R/V AHI using the Benthic Terrain Modeler with...

An explicit parameterization for casting constraints in gradient driven topology optimization

DEFF Research Database (Denmark)

Gersborg, Allan Roulund; Andreasen, Casper Schousboe

2011-01-01

From a practical point of view it is often desirable to limit the complexity of a topology optimization design such that casting/milling type manufacturing techniques can be applied. In the context of gradient driven topology optimization this work studies how castable designs can be obtained...... by use of a Heaviside design parameterization in a specified casting direction. This reduces the number of design variables considerably and the approach is simple to implement....

Cost optimization of ADS design: Comparative study of externally driven heterogeneous and homogeneous two-zone subcritical reactor systems

International Nuclear Information System (INIS)

Gulik, Volodymyr; Tkaczyk, Alan H.

2014-01-01

Highlights: • The optimization of two-zone homogeneous subcritical systems has been performed. • A Serpent model for two-zone heterogeneous subcritical systems has been developed. • The optimization of two-zone heterogeneous subcritical systems has been carried out. • Economically optimal core composition of two-zone subcritical system was found. • The neutron spectra of the heterogeneous subcritical systems have been obtained. - Abstract: Subcritical systems driven by external neutron sources, commonly known as Accelerator-Driven System (ADS), are one type of advanced nuclear reactor exhibiting attractive characteristics, distinguished from the traditional critical systems by their intrinsic safety features. In addition, an ADS can be used for the transmutation of the nuclear waste, accumulated during the operation of existing reactors. The optimization of a subcritical nuclear reactor in terms of materials (fuel content, coolant, etc.), geometrical, and economical parameters is a crucial step in the process of their design and construction. This article describes the optimization modeling performed for homogeneous and heterogeneous two-zone subcritical systems in terms of geometry of the fuel zones. Economical assessment was also carried out for the costs of the fuel in the core of the system. Optimization modeling was performed with the Serpent-1.1.18 Monte Carlo code. The model of a two-zone subcritical system with a fast inner and a thermal gas-cooled graphite-moderated outer zone was developed, simulated, and analyzed. The optimal value for the pitch of fuel elements in the thermal outer zone was investigated from the viewpoint of the cost of subcritical system. As the main goal of ADS development is nuclear waste transmutation, neutron spectra for both fast and thermal zones were obtained for different system configurations. The results of optimization modeling of homogeneous and heterogeneous two-zone subcritical systems show that an optimal

Test-driven modeling of embedded systems

DEFF Research Database (Denmark)

Munck, Allan; Madsen, Jan

2015-01-01

To benefit maximally from model-based systems engineering (MBSE) trustworthy high quality models are required. From the software disciplines it is known that test-driven development (TDD) can significantly increase the quality of the products. Using a test-driven approach with MBSE may have...... a similar positive effect on the quality of the system models and the resulting products and may therefore be desirable. To define a test-driven model-based systems engineering (TD-MBSE) approach, we must define this approach for numerous sub disciplines such as modeling of requirements, use cases...... suggest that our method provides a sound foundation for rapid development of high quality system models....

Theoretical modelling and optimization of bubble column dehumidifier for a solar driven humidification-dehumidification system

Science.gov (United States)

Ranjitha, P. Raj; Ratheesh, R.; Jayakumar, J. S.; Balakrishnan, Shankar

2018-02-01

Availability and utilization of energy and water are the top most global challenges being faced by the new millennium. At the present state water scarcity has become a global as well as a regional challenge. 40 % of world population faces water shortage. Challenge of water scarcity can be tackled only with increase in water supply beyond what is obtained from hydrological cycle. This can be achieved either by desalinating the sea water or by reusing the waste water. High energy requirement need to be overcome for either of the two processes. Of many desalination technologies, humidification dehumidification (HDH) technology powered by solar energy is widely accepted for small scale production. Detailed optimization studies on system have the potential to effectively utilize the solar energy for brackish water desalination. Dehumidification technology, specifically, require further study because the dehumidifier effectiveness control the energetic performance of the entire HDH system. The reason attributes to the high resistance involved to diffuse dilute vapor through air in a dehumidifier. The present work intends to optimize the design of a bubble column dehumidifier for a solar energy driven desalination process. Optimization is carried out using Matlab simulation. Design process will identify the unique needs of a bubble column dehumidifier in HDH system.

Multibeam swath bathymetry signal processing techniques

Digital Repository Service at National Institute of Oceanography (India)

Ranade, G.; Sudhakar, T.

Mathematical advances and the advances in the real time signal processing techniques in the recent times, have considerably improved the state of art in the bathymetry systems. These improvements have helped in developing high resolution swath...

Water Storage Changes using Floodplain Bathymetry from InSAR and satellite altimetry in the Congo River Basin

Science.gov (United States)

Yuan, T.; Lee, H.; Jung, H. C.; Beighley, E.; Alsdorf, D. E.

2016-12-01

Extensive wetlands and swamps expand along the Congo River and its tributaries. These wetlands store water and attenuate flood wave during high water season. Substantial dissolved and solid substances are also transported with the water flux, influencing geochemical environment and biogeochemistry processes both in the wetlands and the river. To understand the role of the wetlands in partitioning the surface water and the accompanied material movement, water storage change is one of the most fundamental observations. The water flow through the wetlands is complex, affected by topography, vegetation resistance, and hydraulic variations. Interferometric Synthetic Aperture Radar (InSAR) has been successfully used to map relative water level changes in the vegetated wetlands with high spatial resolution. By examining interferograms generated from ALOS PALSAR along the middle reach of the Congo River floodplain, we found greater water level changes near the Congo mainstem. Integrated analysis of InSAR and Envisat altimetry data has shown that proximal floodplain with higher water level change has lower elevation during dry season. This indicates that the spatial variation of water level change in the Congo floodplain is mostly controlled by floodplain bathymetry. A method based on water level and bathymetry model is proposed to estimate water storage change. The bathymetry model is composed of (1) elevation at the intersection of the floodplain and the river and (2) floodplain bathymetry slope. We first constructed the floodplain bathymetry by selecting an Envisat altimetry profile during low water season to estimate elevation at the intersection of the floodplain and the river. Floodplain bathymetry slope was estimated using InSAR measurements. It is expected that our new method can estimate water storage change with higher temporal resolution corresponding to altimeter's repeat cycle. In addition, given the multi-decadal archive of satellite altimetry measurements

60 m Rugosity grid derived from gridded bathymetry of Wake Island, West Central Pacific.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (60 m cell size) multibeam bathymetry, collected aboard NOAA ship Hi'ialakai and R/V AHI using the Benthic Terrain Modeler with...

CRED Rugosity grid derived from gridded bathymetry of Tutuila Island, American Samoa, South Pacific

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (5 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hiialaka'i and R/V AHI, using the Benthic Terrain Modeler with...

Rugosity 60 m grid derived from gridded bathymetry of Rota Island, Mariana Islands, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (60 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hiialaka'i and R/V AHI, using the Benthic Terrain Modeler with...

Data-driven non-Markovian closure models

Science.gov (United States)

Kondrashov, Dmitri; Chekroun, Mickaël D.; Ghil, Michael

2015-03-01

This paper has two interrelated foci: (i) obtaining stable and efficient data-driven closure models by using a multivariate time series of partial observations from a large-dimensional system; and (ii) comparing these closure models with the optimal closures predicted by the Mori-Zwanzig (MZ) formalism of statistical physics. Multilayer stochastic models (MSMs) are introduced as both a generalization and a time-continuous limit of existing multilevel, regression-based approaches to closure in a data-driven setting; these approaches include empirical model reduction (EMR), as well as more recent multi-layer modeling. It is shown that the multilayer structure of MSMs can provide a natural Markov approximation to the generalized Langevin equation (GLE) of the MZ formalism. A simple correlation-based stopping criterion for an EMR-MSM model is derived to assess how well it approximates the GLE solution. Sufficient conditions are derived on the structure of the nonlinear cross-interactions between the constitutive layers of a given MSM to guarantee the existence of a global random attractor. This existence ensures that no blow-up can occur for a broad class of MSM applications, a class that includes non-polynomial predictors and nonlinearities that do not necessarily preserve quadratic energy invariants. The EMR-MSM methodology is first applied to a conceptual, nonlinear, stochastic climate model of coupled slow and fast variables, in which only slow variables are observed. It is shown that the resulting closure model with energy-conserving nonlinearities efficiently captures the main statistical features of the slow variables, even when there is no formal scale separation and the fast variables are quite energetic. Second, an MSM is shown to successfully reproduce the statistics of a partially observed, generalized Lotka-Volterra model of population dynamics in its chaotic regime. The challenges here include the rarity of strange attractors in the model's parameter

Accuracy limits on rapid assessment of gently varying bathymetry

Science.gov (United States)

McDonald, B. Edward; Holland, Charles

2002-05-01

Accuracy limits for rapidly probing shallow water bathymetry are investigated as a function of bottom slope and other relevant parameters. The probe scheme [B. E. McDonald and Charles Holland, J. Acoust. Soc. Am. 110, 2767 (2001)] uses a time reversed mirror (TRM) to ensonify a thin annulus on the ocean bottom at ranges of a few km from a vertical send/ receive array. The annulus is shifted in range by variable bathymetry (perturbation theory shows that the focal annulus experiences a radial shift proportional to the integrated bathymetry along a given azimuth). The range shift implies an azimuth-dependent time of maximum reverberation. Thus the reverberant return contains information that might be inverted to give bathymetric parameters. The parameter range over which the perturbation result is accurate is explored using the RAM code for propagation in arbitrarily range-dependent environments. [Work supported by NRL.

Geometry-Driven-Diffusion filtering of MR Brain Images using dissimilarities and optimal relaxation parameter

Energy Technology Data Exchange (ETDEWEB)

Bajla, Ivan [Austrian Research Centres Sibersdorf, Department of High Performance Image Processing and Video-Technology, A-2444 Seibersdorf (Austria); Hollander, Igor [Institute of information Processing, Austrian Academy of Sciences, Sonnenfelsgasse 19/2, 1010 Wien (Austria)

1999-12-31

A novel method of local adapting of the conductance using a pixel dissimilarity measure is developed. An alternative processing methodology is proposed, which is based on intensity gradient histogram calculated for region interiors and boundaries of a phantom which models real MR brain scans. It involves a specific cost function suitable for the calculation of the optimum relaxation parameter Kopt and for the selection of the optimal exponential conductance. Computer experiments for locally adaptive geometry-driven-diffusion filtering of an MR brain phantom have been performed and evaluated. (authors) 6 refs., 3 figs.2 tabs.

Geometry-Driven-Diffusion filtering of MR Brain Images using dissimilarities and optimal relaxation parameter

International Nuclear Information System (INIS)

Bajla, Ivan; Hollander, Igor

1998-01-01

A novel method of local adapting of the conductance using a pixel dissimilarity measure is developed. An alternative processing methodology is proposed, which is based on intensity gradient histogram calculated for region interiors and boundaries of a phantom which models real MR brain scans. It involves a specific cost function suitable for the calculation of the optimum relaxation parameter Kopt and for the selection of the optimal exponential conductance. Computer experiments for locally adaptive geometry-driven-diffusion filtering of an MR brain phantom have been performed and evaluated. (authors)

Model-Driven Theme/UML

Science.gov (United States)

Carton, Andrew; Driver, Cormac; Jackson, Andrew; Clarke, Siobhán

Theme/UML is an existing approach to aspect-oriented modelling that supports the modularisation and composition of concerns, including crosscutting ones, in design. To date, its lack of integration with model-driven engineering (MDE) techniques has limited its benefits across the development lifecycle. Here, we describe our work on facilitating the use of Theme/UML as part of an MDE process. We have developed a transformation tool that adopts model-driven architecture (MDA) standards. It defines a concern composition mechanism, implemented as a model transformation, to support the enhanced modularisation features of Theme/UML. We evaluate our approach by applying it to the development of mobile, context-aware applications-an application area characterised by many non-functional requirements that manifest themselves as crosscutting concerns.

High Spatio-Temporal Resolution Bathymetry Estimation and Morphology

Science.gov (United States)

Bergsma, E. W. J.; Conley, D. C.; Davidson, M. A.; O'Hare, T. J.

2015-12-01

In recent years, bathymetry estimates using video images have become increasingly accurate. With the cBathy code (Holman et al., 2013) fully operational, bathymetry results with 0.5 metres accuracy have been regularly obtained at Duck, USA. cBathy is based on observations of the dominant frequencies and wavelengths of surface wave motions and estimates the depth (and hence allows inference of bathymetry profiles) based on linear wave theory. Despite the good performance at Duck, large discrepancies were found related to tidal elevation and camera height (Bergsma et al., 2014) and on the camera boundaries. A tide dependent floating pixel and camera boundary solution have been proposed to overcome these issues (Bergsma et al., under review). The video-data collection is set estimate depths hourly on a grid with resolution in the order of 10x25 meters. Here, the application of the cBathy at Porthtowan in the South-West of England is presented. Hourly depth estimates are combined and analysed over a period of 1.5 years (2013-2014). In this work the focus is on the sub-tidal region, where the best cBathy results are achieved. The morphology of the sub-tidal bar is tracked with high spatio-temporal resolution on short and longer time scales. Furthermore, the impact of the storm and reset (sudden and large changes in bathymetry) of the sub-tidal area is clearly captured with the depth estimations. This application shows that the high spatio-temporal resolution of cBathy makes it a powerful tool for coastal research and coastal zone management.

Bathymetry Determination via X-Band Radar Data: A New Strategy and Numerical Results

Directory of Open Access Journals (Sweden)

Francesco Soldovieri

2010-07-01

Full Text Available This work deals with the question of sea state monitoring using marine X-band radar images and focuses its attention on the problem of sea depth estimation. We present and discuss a technique to estimate bathymetry by exploiting the dispersion relation for surface gravity waves. This estimation technique is based on the correlation between the measured and the theoretical sea wave spectra and a simple analysis of the approach is performed through test cases with synthetic data. More in detail, the reliability of the estimate technique is verified through simulated data sets that are concerned with different values of bathymetry and surface currents for two types of sea spectrum: JONSWAP and Pierson-Moskowitz. The results show how the estimated bathymetry is fairly accurate for low depth values, while the estimate is less accurate as the bathymetry increases, due to a less significant role of the bathymetry on the sea surface waves as the water depth increases.

Development of a Stochastically-driven, Forward Predictive Performance Model for PEMFCs

Science.gov (United States)

Harvey, David Benjamin Paul

A one-dimensional multi-scale coupled, transient, and mechanistic performance model for a PEMFC membrane electrode assembly has been developed. The model explicitly includes each of the 5 layers within a membrane electrode assembly and solves for the transport of charge, heat, mass, species, dissolved water, and liquid water. Key features of the model include the use of a multi-step implementation of the HOR reaction on the anode, agglomerate catalyst sub-models for both the anode and cathode catalyst layers, a unique approach that links the composition of the catalyst layer to key properties within the agglomerate model and the implementation of a stochastic input-based approach for component material properties. The model employs a new methodology for validation using statistically varying input parameters and statistically-based experimental performance data; this model represents the first stochastic input driven unit cell performance model. The stochastic input driven performance model was used to identify optimal ionomer content within the cathode catalyst layer, demonstrate the role of material variation in potential low performing MEA materials, provide explanation for the performance of low-Pt loaded MEAs, and investigate the validity of transient-sweep experimental diagnostic methods.

A Data-Driven Frequency-Domain Approach for Robust Controller Design via Convex Optimization

CERN Document Server

AUTHOR|(CDS)2092751; Martino, Michele

The objective of this dissertation is to develop data-driven frequency-domain methods for designing robust controllers through the use of convex optimization algorithms. Many of today's industrial processes are becoming more complex, and modeling accurate physical models for these plants using first principles may be impossible. Albeit a model may be available; however, such a model may be too complex to consider for an appropriate controller design. With the increased developments in the computing world, large amounts of measured data can be easily collected and stored for processing purposes. Data can also be collected and used in an on-line fashion. Thus it would be very sensible to make full use of this data for controller design, performance evaluation, and stability analysis. The design methods imposed in this work ensure that the dynamics of a system are captured in an experiment and avoids the problem of unmodeled dynamics associated with parametric models. The devised methods consider robust designs...

A fuzzy multi-criteria decision-making model for CCHP systems driven by different energy sources

International Nuclear Information System (INIS)

Jing Youyin; Bai He; Wang Jiangjiang

2012-01-01

Because of its energy-saving and pollutant emission reduction potentials, combined cooling, heating and power (CCHP) system has been widely used in different kinds of buildings to solve building-related energetic problems and environmental issues. As various kinds of clean energy and renewable energy have been focused and applied to CCHP systems, it is urgent to find a practical decision making methodology for CCHP systems driven by different energy sources. In this paper, an evaluation model which integrates fuzzy theory with multi-criteria decision making process is proposed to assess the comprehensive benefits of CCHP systems from technology, economic, society and environment criterions. Grey relation analysis and combination weighting method are also employed to compare the integrated performances of CCHP systems driven by natural gas, fuel cell, biomass energy and combined gas-steam cycle respectively with a separation production system. Finally, a baseline residential building in Beijing, China is selected as a case to obtain the optimal CCHP system alternative. The results indicate that gas–steam combined cycle CCHP system is the optimum scheme among the five options. - Graphical abstract: A fuzzy multi-criteria decision-making model combined with combination weighting method and grey system theory is presented in this paper, which can be used to evaluate CCHP systems driven by different energy sources from technology, economic, environment and society criteria. Highlights: ► The integrated benefits of CCHP systems driven by different energy sources are evaluated. ► A fuzzy multi-criteria model combined with combination weighting method is proposed. ► Environment evaluation criteria play an important role in the decision-making process. ► CCHP system driven by gas–steam combined cycle is the optimal alternative.

CRED 20m Gridded bathymetry of Necker Island, Hawaii, USA (Arc ASCII format)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry of the shelf and slope environments of Necker Island, Northwestern Hawaiian Islands, Hawaii, USA. This ASCII includes multibeam bathymetry from...

Estimated Bathymetry of the Puerto Rico shelf

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This classification of estimated depth represents the relative bathymetry of Puerto Rico's shallow waters based on Landsat imagery for NOAA's Coastal Centers for...

Remote Sensing-Derived Bathymetry of Lake Poopó

Directory of Open Access Journals (Sweden)

Adalbert Arsen

2013-12-01

Full Text Available Located within the Altiplano at 3,686 m above sea level, Lake Poopó is remarkably shallow and very sensitive to hydrologic recharge. Progressive drying has been observed in the entire Titicaca-Poopó-Desaguadero-Salar de Coipasa (TPDS system during the last decade, causing dramatic changes to Lake Poopó’s surface and its regional water supplies. Our research aims to improve understanding of Lake Poopó water storage capacity. Thus, we propose a new method based on freely available remote sensing data to reproduce Lake Poopó bathymetry. Laser ranging altimeter ICESat (Ice, Cloud, and land Elevation Satellite is used during the lake’s lowest stages to measure vertical heights with high precision over dry land. These heights are used to estimate elevations of water contours obtained with Landsat imagery. Contour points with assigned elevation are filtered and grouped in a points cloud. Mesh gridding and interpolation function are then applied to construct 3D bathymetry. Complementary analysis of Moderate Resolution Imaging Spectroradiometer (MODIS surfaces from 2000 to 2012 combined with bathymetry gives water levels and storage evolution every 8 days.

Optimization of an RF driven H- ion source

International Nuclear Information System (INIS)

Leung, K.N.; DiVergilio, W.F.; Hauck, C.A.; Kunkel, W.B.; McDonald, D.S.

1991-04-01

A radio-frequency driven multicusp source has recently been developed to generate volume-produced H - ion beams with extracted current density higher than 200 mA/cm 2 . We have improved the output power of the rf generator and the insulation coating of the antenna coil. We have also optimized the antenna positions and geometry and the filter magnetic field for high power pulsed operation. A total H - current of 30 mA can be obtained with a 5.4-mm-diam extraction aperture and with an rf input power of 50 kW. 4 refs., 5 figs

A data-driven fault-tolerant control design of linear multivariable systems with performance optimization.

Science.gov (United States)

Li, Zhe; Yang, Guang-Hong

2017-09-01

In this paper, an integrated data-driven fault-tolerant control (FTC) design scheme is proposed under the configuration of the Youla parameterization for multiple-input multiple-output (MIMO) systems. With unknown system model parameters, the canonical form identification technique is first applied to design the residual observer in fault-free case. In faulty case, with online tuning of the Youla parameters based on the system data via the gradient-based algorithm, the fault influence is attenuated with system performance optimization. In addition, to improve the robustness of the residual generator to a class of system deviations, a novel adaptive scheme is proposed for the residual generator to prevent its over-activation. Simulation results of a two-tank flow system demonstrate the optimized performance and effect of the proposed FTC scheme. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Global optimization driven by genetic algorithms for disruption predictors based on APODIS architecture

Energy Technology Data Exchange (ETDEWEB)

Rattá, G.A., E-mail: giuseppe.ratta@ciemat.es [Laboratorio Nacional de Fusión, CIEMAT, Madrid (Spain); Vega, J. [Laboratorio Nacional de Fusión, CIEMAT, Madrid (Spain); Murari, A. [Consorzio RFX, Associazione EURATOM/ENEA per la Fusione, Padua (Italy); Dormido-Canto, S. [Dpto. de Informática y Automática, Universidad Nacional de Educación a Distancia, Madrid (Spain); Moreno, R. [Laboratorio Nacional de Fusión, CIEMAT, Madrid (Spain)

2016-11-15

Highlights: • A global optimization method based on genetic algorithms was developed. • It allowed improving the prediction of disruptions using APODIS architecture. • It also provides the potential opportunity to develop a spectrum of future predictors using different training datasets. • The future analysis of how their structures reassemble and evolve in each test may help to improve the development of disruption predictors for ITER. - Abstract: Since year 2010, the APODIS architecture has proven its accuracy predicting disruptions in JET tokamak. Nevertheless, it has shown margins for improvements, fact indisputable after the enhanced performances achieved in posterior upgrades. In this article, a complete optimization driven by Genetic Algorithms (GA) is applied to it aiming at considering all possible combination of signals, signal features, quantity of models, their characteristics and internal parameters. This global optimization targets the creation of the best possible system with a reduced amount of required training data. The results harbor no doubts about the reliability of the global optimization method, allowing to outperform the ones of previous versions: 91.77% of predictions (89.24% with an anticipation higher than 10 ms) with a 3.55% of false alarms. Beyond its effectiveness, it also provides the potential opportunity to develop a spectrum of future predictors using different training datasets.

Global optimization driven by genetic algorithms for disruption predictors based on APODIS architecture

International Nuclear Information System (INIS)

Rattá, G.A.; Vega, J.; Murari, A.; Dormido-Canto, S.; Moreno, R.

2016-01-01

Highlights: • A global optimization method based on genetic algorithms was developed. • It allowed improving the prediction of disruptions using APODIS architecture. • It also provides the potential opportunity to develop a spectrum of future predictors using different training datasets. • The future analysis of how their structures reassemble and evolve in each test may help to improve the development of disruption predictors for ITER. - Abstract: Since year 2010, the APODIS architecture has proven its accuracy predicting disruptions in JET tokamak. Nevertheless, it has shown margins for improvements, fact indisputable after the enhanced performances achieved in posterior upgrades. In this article, a complete optimization driven by Genetic Algorithms (GA) is applied to it aiming at considering all possible combination of signals, signal features, quantity of models, their characteristics and internal parameters. This global optimization targets the creation of the best possible system with a reduced amount of required training data. The results harbor no doubts about the reliability of the global optimization method, allowing to outperform the ones of previous versions: 91.77% of predictions (89.24% with an anticipation higher than 10 ms) with a 3.55% of false alarms. Beyond its effectiveness, it also provides the potential opportunity to develop a spectrum of future predictors using different training datasets.

Geometrical Optimization Approach to Isomerization: Models and Limitations.

Science.gov (United States)

Chang, Bo Y; Shin, Seokmin; Engel, Volker; Sola, Ignacio R

2017-11-02

We study laser-driven isomerization reactions through an excited electronic state using the recently developed Geometrical Optimization procedure. Our goal is to analyze whether an initial wave packet in the ground state, with optimized amplitudes and phases, can be used to enhance the yield of the reaction at faster rates, driven by a single picosecond pulse or a pair of femtosecond pulses resonant with the electronic transition. We show that the symmetry of the system imposes limitations in the optimization procedure, such that the method rediscovers the pump-dump mechanism.

Turbid Flows and Their Deposits on Slopes with Minibasins : A Modelling Approach

NARCIS (Netherlands)

Wang, X.

2015-01-01

Passive continental margins display a great diversity of seafloor bathymetries induced by gravity driven extensional faulting and compressional folding, as well as diapiric movements of salt or mud. In many diapirically controlled settings, slope bathymetries are complicated and characterized by

CRED 20m Gridded bathymetry of Nihoa Island, Hawaii, USA (Arc ASCII format)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry (20m) of the shelf and slope environments of Nihoa Island, Hawaii, USA. The ASCII includes multibeam bathymetry from the Simrad EM120, Simrad...

Slope grid (5 m) derived from gridded bathymetry of US Territory of Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Slope is derived from gridded (5 m cell size) bathymetry from four sources: Multibeam bathymetry collected by Coral Reef Ecosystem Division aboard NOAA R/V AHI, and...

Analysis of MABEL Bathymetry in Keweenaw Bay and Implications for ICESat-2 ATLAS

Directory of Open Access Journals (Sweden)

Nicholas A. Forfinski-Sarkozi

2016-09-01

Full Text Available In 2018, the National Aeronautics and Space Administration (NASA is scheduled to launch the Ice, Cloud, and land Elevation Satellite-2 (ICESat-2, with a new six-beam, green-wavelength, photon-counting lidar system, Advanced Topographic Laser Altimeter System (ATLAS. The primary objectives of the ICESat-2 mission are to measure ice-sheet elevations, sea-ice thickness, and global biomass. However, if bathymetry can be reliably retrieved from ATLAS data, this could assist in addressing a key data need in many coastal and inland water body areas, including areas that are poorly-mapped and/or difficult to access. Additionally, ATLAS-derived bathymetry could be used to constrain bathymetry derived from complementary data, such as passive, multispectral imagery and synthetic aperture radar (SAR. As an important first step in evaluating the ability to map bathymetry from ATLAS, this study involves a detailed assessment of bathymetry from the Multiple Altimeter Beam Experimental Lidar (MABEL, NASA’s airborne ICESat-2 simulator, flown on the Earth Resources 2 (ER-2 high-altitude aircraft. An interactive, web interface, MABEL Viewer, was developed and used to identify bottom returns in Keweenaw Bay, Lake Superior. After applying corrections for refraction and channel-specific elevation biases, MABEL bathymetry was compared against National Oceanic and Atmospheric Administration (NOAA data acquired two years earlier. The results indicate that MABEL reliably detected bathymetry in depths of up to 8 m, with a root mean square (RMS difference of 0.7 m, with respect to the reference data. Additionally, a version of the lidar equation was developed for predicting bottom-return signal levels in MABEL and tested using the Keweenaw Bay data. Future work will entail extending these results to ATLAS, as the technical specifications of the sensor become available.

Modeling Reservoir-River Networks in Support of Optimizing Seasonal-Scale Reservoir Operations

Science.gov (United States)

Villa, D. L.; Lowry, T. S.; Bier, A.; Barco, J.; Sun, A.

2011-12-01

each timestep and minimize computational overhead. Power generation for each reservoir is estimated using a 2-dimensional regression that accounts for both the available head and turbine efficiency. The object-oriented architecture makes run configuration easy to update. The dynamic model inputs include inflow and meteorological forecasts while static inputs include bathymetry data, reservoir and power generation characteristics, and topological descriptors. Ensemble forecasts of hydrological and meteorological conditions are supplied in real-time by Pacific Northwest National Laboratory and are used as a proxy for uncertainty, which is carried through the simulation and optimization process to produce output that describes the probability that different operational scenario's will be optimal. The full toolset, which includes HydroSCOPE, is currently being tested on the Feather River system in Northern California and the Upper Colorado Storage Project.

TH-CD-207B-09: Task-Driven Fluence Field Modulation Design for Model-Based Iterative Reconstruction in CT

International Nuclear Information System (INIS)

Gang, G; Siewerdsen, J; Stayman, J

2016-01-01

Purpose: There has been increasing interest in integrating fluence field modulation (FFM) devices with diagnostic CT scanners for dose reduction purposes. Conventional FFM strategies, however, are often either based on heuristics or the analysis of filtered-backprojection (FBP) performance. This work investigates a prospective task-driven optimization of FFM for model-based iterative reconstruction (MBIR) in order to improve imaging performance at the same total dose as conventional strategies. Methods: The task-driven optimization framework utilizes an ultra-low dose 3D scout as a patient-specific anatomical model and a mathematical formation of the imaging task. The MBIR method investigated is quadratically penalized-likelihood reconstruction. The FFM objective function uses detectability index, d’, computed as a function of the predicted spatial resolution and noise in the image. To optimize performance throughout the object, a maxi-min objective was adopted where the minimum d’ over multiple locations is maximized. To reduce the dimensionality of the problem, FFM is parameterized as a linear combination of 2D Gaussian basis functions over horizontal detector pixels and projection angles. The coefficients of these bases are found using the covariance matrix adaptation evolution strategy (CMA-ES) algorithm. The task-driven design was compared with three other strategies proposed for FBP reconstruction for a calcification cluster discrimination task in an abdomen phantom. Results: The task-driven optimization yielded FFM that was significantly different from those designed for FBP. Comparing all four strategies, the task-based design achieved the highest minimum d’ with an 8–48% improvement, consistent with the maxi-min objective. In addition, d’ was improved to a greater extent over a larger area within the entire phantom. Conclusion: Results from this investigation suggests the need to re-evaluate conventional FFM strategies for MBIR. The task

TH-CD-207B-09: Task-Driven Fluence Field Modulation Design for Model-Based Iterative Reconstruction in CT

Energy Technology Data Exchange (ETDEWEB)

Gang, G; Siewerdsen, J; Stayman, J [Johns Hopkins University, Baltimore, MD (United States)

2016-06-15

Purpose: There has been increasing interest in integrating fluence field modulation (FFM) devices with diagnostic CT scanners for dose reduction purposes. Conventional FFM strategies, however, are often either based on heuristics or the analysis of filtered-backprojection (FBP) performance. This work investigates a prospective task-driven optimization of FFM for model-based iterative reconstruction (MBIR) in order to improve imaging performance at the same total dose as conventional strategies. Methods: The task-driven optimization framework utilizes an ultra-low dose 3D scout as a patient-specific anatomical model and a mathematical formation of the imaging task. The MBIR method investigated is quadratically penalized-likelihood reconstruction. The FFM objective function uses detectability index, d’, computed as a function of the predicted spatial resolution and noise in the image. To optimize performance throughout the object, a maxi-min objective was adopted where the minimum d’ over multiple locations is maximized. To reduce the dimensionality of the problem, FFM is parameterized as a linear combination of 2D Gaussian basis functions over horizontal detector pixels and projection angles. The coefficients of these bases are found using the covariance matrix adaptation evolution strategy (CMA-ES) algorithm. The task-driven design was compared with three other strategies proposed for FBP reconstruction for a calcification cluster discrimination task in an abdomen phantom. Results: The task-driven optimization yielded FFM that was significantly different from those designed for FBP. Comparing all four strategies, the task-based design achieved the highest minimum d’ with an 8–48% improvement, consistent with the maxi-min objective. In addition, d’ was improved to a greater extent over a larger area within the entire phantom. Conclusion: Results from this investigation suggests the need to re-evaluate conventional FFM strategies for MBIR. The task

Limitations of demand- and pressure-driven modeling for large deficient networks

Science.gov (United States)

Braun, Mathias; Piller, Olivier; Deuerlein, Jochen; Mortazavi, Iraj

2017-10-01

The calculation of hydraulic state variables for a network is an important task in managing the distribution of potable water. Over the years the mathematical modeling process has been improved by numerous researchers for utilization in new computer applications and the more realistic modeling of water distribution networks. But, in spite of these continuous advances, there are still a number of physical phenomena that may not be tackled correctly by current models. This paper will take a closer look at the two modeling paradigms given by demand- and pressure-driven modeling. The basic equations are introduced and parallels are drawn with the optimization formulations from electrical engineering. These formulations guarantee the existence and uniqueness of the solution. One of the central questions of the French and German research project ResiWater is the investigation of the network resilience in the case of extreme events or disasters. Under such extraordinary conditions where models are pushed beyond their limits, we talk about deficient network models. Examples of deficient networks are given by highly regulated flow, leakage or pipe bursts and cases where pressure falls below the vapor pressure of water. These examples will be presented and analyzed on the solvability and physical correctness of the solution with respect to demand- and pressure-driven models.

Merged/integrated Bathymetric Data Derived from Multibeam Sonar, LiDAR, and Satellite-derived Bathymetry

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with derived bathymetry from alternate sources to provide a GIS layer with expanded spatial coverage. Integrated products...

Contraction Options and Optimal Multiple-Stopping in Spectrally Negative Lévy Models

Energy Technology Data Exchange (ETDEWEB)

Yamazaki, Kazutoshi, E-mail: kyamazak@kansai-u.ac.jp [Kansai University, Department of Mathematics, Faculty of Engineering Science (Japan)

2015-08-15

This paper studies the optimal multiple-stopping problem arising in the context of the timing option to withdraw from a project in stages. The profits are driven by a general spectrally negative Lévy process. This allows the model to incorporate sudden declines of the project values, generalizing greatly the classical geometric Brownian motion model. We solve the one-stage case as well as the extension to the multiple-stage case. The optimal stopping times are of threshold-type and the value function admits an expression in terms of the scale function. A series of numerical experiments are conducted to verify the optimality and to evaluate the efficiency of the algorithm.

Contraction Options and Optimal Multiple-Stopping in Spectrally Negative Lévy Models

International Nuclear Information System (INIS)

Yamazaki, Kazutoshi

2015-01-01

This paper studies the optimal multiple-stopping problem arising in the context of the timing option to withdraw from a project in stages. The profits are driven by a general spectrally negative Lévy process. This allows the model to incorporate sudden declines of the project values, generalizing greatly the classical geometric Brownian motion model. We solve the one-stage case as well as the extension to the multiple-stage case. The optimal stopping times are of threshold-type and the value function admits an expression in terms of the scale function. A series of numerical experiments are conducted to verify the optimality and to evaluate the efficiency of the algorithm

Altimetry, bathymetry and geoid variations at the Gavdos permanent Cal/Val facility

DEFF Research Database (Denmark)

Mertikas, Stelios P.; Daskalakis, Antonis; Tziavos, Ilias N.

2013-01-01

The aim of this work has been to examine the relationship of steep bathymetry in the coastal areas around the permanent Cal/Val facility of Gavdos, and their influence on the produced calibration values for the Jason-2 satellite altimeter. The paper describes how changes in seafloor topography...... (from 200 to 3500m depth over a distance of 10km) are reflected on the determined altimeter parameters using different reference surfaces for satellite calibration. Finally, it describes the relation between these parameter trends and the region’s local characteristics.Using 3.5years of Jason-2...... to be related to the general oceanographic circulation, but others of short wavelength (in the order of 1km) are because of the insufficient geoid model resolution. Along Pass No. 109, the concealed effect of bathymetry on the geoid has produced a slope of 3.1cm over 14–21km from Gavdos. Along the other Pass No...

Rugosity grid (5 m) derived from gridded bathymetry of the US Territory of Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (5 m cell size) bathymetry from four sources: Multibeam bathymetry collected by Coral Reef Ecosystem Division aboard NOAA R/V AHI,...

Satellite derived bathymetry: mapping the Irish coastline

Science.gov (United States)

Monteys, X.; Cahalane, C.; Harris, P.; Hanafin, J.

2017-12-01

Ireland has a varied coastline in excess of 3000 km in length largely characterized by extended shallow environments. The coastal shallow water zone can be a challenging and costly environment in which to acquire bathymetry and other oceanographic data using traditional survey methods or airborne LiDAR techniques as demonstrated in the Irish INFOMAR program. Thus, large coastal areas in Ireland, and much of the coastal zone worldwide remain unmapped using modern techniques and is poorly understood. Earth Observations (EO) missions are currently being used to derive timely, cost effective, and quality controlled information for mapping and monitoring coastal environments. Different wavelengths of the solar light penetrate the water column to different depths and are routinely sensed by EO satellites. A large selection of multispectral imagery (MS) from many platforms were examined, as well as from small aircrafts and drones. A number of bays representing very different coastal environments were explored in turn. The project's workflow is created by building a catalogue of satellite and field bathymetric data to assess the suitability of imagery captured at a range of spatial, spectral and temporal resolutions. Turbidity indices are derived from the multispectral information. Finally, a number of spatial regression models using water-leaving radiance parameters and field calibration data are examined. Our assessment reveals that spatial regression algorithms have the potential to significantly improve the accuracy of the predictions up to 10m WD and offer a better handle on the error and uncertainty budget. The four spatial models investigated show better adjustments than the basic non-spatial model. Accuracy of the predictions is better than 10% WD at 95% confidence. Future work will focus on improving the accuracy of the predictions incorporating an analytical model in conjunction with improved empirical methods. The recently launched ESA Sentinel 2 will become the

Adaptive surrogate model based multiobjective optimization for coastal aquifer management

Science.gov (United States)

Song, Jian; Yang, Yun; Wu, Jianfeng; Wu, Jichun; Sun, Xiaomin; Lin, Jin

2018-06-01

In this study, a novel surrogate model assisted multiobjective memetic algorithm (SMOMA) is developed for optimal pumping strategies of large-scale coastal groundwater problems. The proposed SMOMA integrates an efficient data-driven surrogate model with an improved non-dominated sorted genetic algorithm-II (NSGAII) that employs a local search operator to accelerate its convergence in optimization. The surrogate model based on Kernel Extreme Learning Machine (KELM) is developed and evaluated as an approximate simulator to generate the patterns of regional groundwater flow and salinity levels in coastal aquifers for reducing huge computational burden. The KELM model is adaptively trained during evolutionary search to satisfy desired fidelity level of surrogate so that it inhibits error accumulation of forecasting and results in correctly converging to true Pareto-optimal front. The proposed methodology is then applied to a large-scale coastal aquifer management in Baldwin County, Alabama. Objectives of minimizing the saltwater mass increase and maximizing the total pumping rate in the coastal aquifers are considered. The optimal solutions achieved by the proposed adaptive surrogate model are compared against those solutions obtained from one-shot surrogate model and original simulation model. The adaptive surrogate model does not only improve the prediction accuracy of Pareto-optimal solutions compared with those by the one-shot surrogate model, but also maintains the equivalent quality of Pareto-optimal solutions compared with those by NSGAII coupled with original simulation model, while retaining the advantage of surrogate models in reducing computational burden up to 94% of time-saving. This study shows that the proposed methodology is a computationally efficient and promising tool for multiobjective optimizations of coastal aquifer managements.

Rhombicuboctahedron unit cell based scaffolds for bone regeneration: geometry optimization with a mechanobiology - driven algorithm.

Science.gov (United States)

Boccaccio, Antonio; Fiorentino, Michele; Uva, Antonio E; Laghetti, Luca N; Monno, Giuseppe

2018-02-01

In a context more and more oriented towards customized medical solutions, we propose a mechanobiology-driven algorithm to determine the optimal geometry of scaffolds for bone regeneration that is the most suited to specific boundary and loading conditions. In spite of the huge number of articles investigating different unit cells for porous biomaterials, no studies are reported in the literature that optimize the geometric parameters of such unit cells based on mechanobiological criteria. Parametric finite element models of scaffolds with rhombicuboctahedron unit cell were developed and incorporated into an optimization algorithm that combines them with a computational mechanobiological model. The algorithm perturbs iteratively the geometry of the unit cell until the best scaffold geometry is identified, i.e. the geometry that allows to maximize the formation of bone. Performances of scaffolds with rhombicuboctahedron unit cell were compared with those of other scaffolds with hexahedron unit cells. We found that scaffolds with rhombicuboctahedron unit cell are particularly suited for supporting medium-low loads, while, for higher loads, scaffolds with hexahedron unit cells are preferable. The proposed algorithm can guide the orthopaedic/surgeon in the choice of the best scaffold to be implanted in a patient-specific anatomic region. Copyright © 2017 Elsevier B.V. All rights reserved.

Estimated Bathymetry of the U.S. Virgin Islands

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This classification of estimated depth represents the relative bathymetry of the U.S. Virgin Islands shallow waters based on Landsat imagery for NOAA's Coastal...

Bathymetric Position Index (BPI) Structures 5 m grid derived from gridded bathymetry of the US Territory of Guam.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from a focal mean analysis on bathymetry and slope. The bathymetry grid (5 m cell size) is derived from bathymetry from four sources:...

Archive of bathymetry data collected in South Florida from 1995 to 2015

Science.gov (United States)

Hansen, Mark Erik; DeWitt, Nancy T.; Reynolds, Billy J.

2017-08-10

DescriptionLand development and alterations of the ecosystem in south Florida over the past 100 years have decreased freshwater and increased nutrient flows into many of Florida's estuaries, bays, and coastal regions. As a result, there has been a decrease in the water quality in many of these critical habitats, often prompting seagrass die-offs and reduced fish and aquatic life populations. Restoration of water quality in many of these habitats will depend partly upon using numerical-circulation and sediment-transport models to establish water-quality targets and to assess progress toward reaching restoration targets. Application of these models is often complicated because of complex sea floor topography and tidal flow regimes. Consequently, accurate and modern sea-floor or bathymetry maps are critical for numerical modeling research. Modern bathymetry data sets will also permit a comparison to historical data in order to help assess sea-floor changes within these critical habitats. New and detailed data sets also support marine biology studies to help understand migratory and feeding habitats of marine life.This data series is a compilation of 13 mapping projects conducted in south Florida between 1995 and 2015 and archives more than 45 million bathymetric soundings. Data were collected primarily with a single beam sound navigation and ranging (sonar) system called SANDS developed by the U.S. Geological Survey (USGS) in 1993. Bathymetry data for the Estero Bay project were supplemented with the National Aeronautics and Space Administration's (NASA) Experimental Advanced Airborne Research Lidar (EAARL) system. Data from eight rivers in southwest Florida were collected with an interferometric swath bathymetry system. The projects represented in this data series were funded by the USGS Coastal and Marine Geology Program (CMGP), the USGS South Florida Ecosystem Restoration Project- formally named Placed Based Studies, and other non-Federal agencies. The purpose of

Bathymetric Position Index (BPI) Zones 5 m grid derived from gridded bathymetry of the US Territory of Guam.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The bathymetry grid (5 m cell size) is derived from bathymetry from four sources: Multibeam...

Optimal Orientation Planning and Control Deviation Estimation on FAST Cable-Driven Parallel Robot

Directory of Open Access Journals (Sweden)

Hui Li

2014-03-01

Full Text Available The paper is devoted theoretically to the optimal orientation planning and control deviation estimation of FAST cable-driven parallel robot. Regarding the robot characteristics, the solutions are obtained from two constrained optimizations, both of which are based on the equilibrium of the cabin and the attention on force allocation among 6 cable tensions. A kind of control algorithm is proposed based on the position and force feedbacks. The analysis proves that the orientation control depends on force feedback and the optimal tension solution corresponding to the planned orientation. Finally, the estimation of orientation deviation is given under the limit range of tension errors.

Rapid optimization of tension distribution for cable-driven parallel manipulators with redundant cables

Science.gov (United States)

Ouyang, Bo; Shang, Weiwei

2016-03-01

The solution of tension distributions is infinite for cable-driven parallel manipulators(CDPMs) with redundant cables. A rapid optimization method for determining the optimal tension distribution is presented. The new optimization method is primarily based on the geometry properties of a polyhedron and convex analysis. The computational efficiency of the optimization method is improved by the designed projection algorithm, and a fast algorithm is proposed to determine which two of the lines are intersected at the optimal point. Moreover, a method for avoiding the operating point on the lower tension limit is developed. Simulation experiments are implemented on a six degree-of-freedom(6-DOF) CDPM with eight cables, and the results indicate that the new method is one order of magnitude faster than the standard simplex method. The optimal distribution of tension distribution is thus rapidly established on real-time by the proposed method.

Estimation of tissue stiffness, reflex activity, optimal muscle length and slack length in stroke patients using an electromyography driven antagonistic wrist model.

Science.gov (United States)

de Gooijer-van de Groep, Karin L; de Vlugt, Erwin; van der Krogt, Hanneke J; Helgadóttir, Áróra; Arendzen, J Hans; Meskers, Carel G M; de Groot, Jurriaan H

2016-06-01

About half of all chronic stroke patients experience loss of arm function coinciding with increased stiffness, reduced range of motion and a flexed wrist due to a change in neural and/or structural tissue properties. Quantitative assessment of these changes is of clinical importance, yet not trivial. The goal of this study was to quantify the neural and structural properties contributing to wrist joint stiffness and to compare these properties between healthy subjects and stroke patients. Stroke patients (n=32) and healthy volunteers (n=14) were measured using ramp-and-hold rotations applied to the wrist joint by a haptic manipulator. Neural (reflexive torque) and structural (connective tissue stiffness and slack lengths and (contractile) optimal muscle lengths) parameters were estimated using an electromyography driven antagonistic wrist model. Kruskal-Wallis analysis with multiple comparisons was used to compare results between healthy subjects, stroke patients with modified Ashworth score of zero and stroke patients with modified Ashworth score of one or more. Stroke patients with modified Ashworth score of one or more differed from healthy controls (Pslack length of connective tissue of the flexor muscles. Non-invasive quantitative analysis, including estimation of optimal muscle lengths, enables to identify neural and non-neural changes in chronic stroke patients. Monitoring these changes in time is important to understand the recovery process and to optimize treatment. Copyright © 2016 Elsevier Ltd. All rights reserved.

A global, high-resolution data set of ice sheet topography, cavity geometry, and ocean bathymetry

Science.gov (United States)

Schaffer, Janin; Timmermann, Ralph; Arndt, Jan Erik; Savstrup Kristensen, Steen; Mayer, Christoph; Morlighem, Mathieu; Steinhage, Daniel

2016-10-01

The ocean plays an important role in modulating the mass balance of the polar ice sheets by interacting with the ice shelves in Antarctica and with the marine-terminating outlet glaciers in Greenland. Given that the flux of warm water onto the continental shelf and into the sub-ice cavities is steered by complex bathymetry, a detailed topography data set is an essential ingredient for models that address ice-ocean interaction. We followed the spirit of the global RTopo-1 data set and compiled consistent maps of global ocean bathymetry, upper and lower ice surface topographies, and global surface height on a spherical grid with now 30 arcsec grid spacing. For this new data set, called RTopo-2, we used the General Bathymetric Chart of the Oceans (GEBCO_2014) as the backbone and added the International Bathymetric Chart of the Arctic Ocean version 3 (IBCAOv3) and the International Bathymetric Chart of the Southern Ocean (IBCSO) version 1. While RTopo-1 primarily aimed at a good and consistent representation of the Antarctic ice sheet, ice shelves, and sub-ice cavities, RTopo-2 now also contains ice topographies of the Greenland ice sheet and outlet glaciers. In particular, we aimed at a good representation of the fjord and shelf bathymetry surrounding the Greenland continent. We modified data from earlier gridded products in the areas of Petermann Glacier, Hagen Bræ, and Sermilik Fjord, assuming that sub-ice and fjord bathymetries roughly follow plausible Last Glacial Maximum ice flow patterns. For the continental shelf off Northeast Greenland and the floating ice tongue of Nioghalvfjerdsfjorden Glacier at about 79° N, we incorporated a high-resolution digital bathymetry model considering original multibeam survey data for the region. Radar data for surface topographies of the floating ice tongues of Nioghalvfjerdsfjorden Glacier and Zachariæ Isstrøm have been obtained from the data centres of Technical University of Denmark (DTU), Operation Icebridge (NASA

Bathymetry and acoustic backscatter-outer mainland shelf, eastern Santa Barbara Channel, California

Science.gov (United States)

Dartnell, Peter; Finlayson, David P.; Ritchie, Andrew C.; Cochrane, Guy R.; Erdey, Mercedes D.

2012-01-01

In 2010 and 2011, scientists from the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC), acquired bathymetry and acoustic-backscatter data from the outer shelf region of the eastern Santa Barbara Channel, California. These surveys were conducted in cooperation with the Bureau of Ocean Energy Management (BOEM). BOEM is interested in maps of hard-bottom substrates, particularly natural outcrops that support reef communities in areas near oil and gas extraction activity. The surveys were conducted using the USGS R/V Parke Snavely, outfitted with an interferometric sidescan sonar for swath mapping and real-time kinematic navigation equipment. This report provides the bathymetry and backscatter data acquired during these surveys in several formats, a summary of the mapping mission, maps of bathymetry and backscatter, and Federal Geographic Data Committee (FGDC) metadata.

The Role of Near-Shore Bathymetry During Tsunami Inundation in a Reef Island Setting: A Case Study of Tutuila Island

Science.gov (United States)

Dilmen, Derya I.; Roe, Gerard H.; Wei, Yong; Titov, Vasily V.

2018-04-01

On September 29, 2009 at 17:48 UTC, an M w = 8.1 earthquake in the Tonga Trench generated a tsunami that caused heavy damage across Samoa, American Samoa, and Tonga. One of the worst hits was the volcanic island of Tutuila in American Samoa. Tutuila has a typical tropical island bathymetry setting influenced by coral reefs, and so the event provided an opportunity to evaluate the relationship between tsunami dynamics and the bathymetry in that typical island environment. Previous work has come to differing conclusions regarding how coral reefs affect tsunami dynamics through their influence on bathymetry and dissipation. This study presents numerical simulations of this event with a focus on two main issues: first, how roughness variations affect tsunami run-up and whether different values of Manning's roughness parameter, n, improve the simulated run-up compared to observations; and second, how depth variations in the shelf bathymetry with coral reefs control run-up and inundation on the island coastlines they shield. We find that no single value of n provides a uniformly good match to all observations; and we find substantial bay-to-bay variations in the impact of varying n. The results suggest that there are aspects of tsunami wave dissipation which are not captured by a simplified drag formulation used in shallow-water waves model. The study also suggests that the primary impact of removing the near-shore bathymetry in coral reef environment is to reduce run-up, from which we conclude that, at least in this setting, the impact of the near-shore bathymetry is to increase run-up and inundation.

The Role of Near-Shore Bathymetry During Tsunami Inundation in a Reef Island Setting: A Case Study of Tutuila Island

Science.gov (United States)

Dilmen, Derya I.; Roe, Gerard H.; Wei, Yong; Titov, Vasily V.

2018-02-01

On September 29, 2009 at 17:48 UTC, an M w = 8.1 earthquake in the Tonga Trench generated a tsunami that caused heavy damage across Samoa, American Samoa, and Tonga. One of the worst hits was the volcanic island of Tutuila in American Samoa. Tutuila has a typical tropical island bathymetry setting influenced by coral reefs, and so the event provided an opportunity to evaluate the relationship between tsunami dynamics and the bathymetry in that typical island environment. Previous work has come to differing conclusions regarding how coral reefs affect tsunami dynamics through their influence on bathymetry and dissipation. This study presents numerical simulations of this event with a focus on two main issues: first, how roughness variations affect tsunami run-up and whether different values of Manning's roughness parameter, n, improve the simulated run-up compared to observations; and second, how depth variations in the shelf bathymetry with coral reefs control run-up and inundation on the island coastlines they shield. We find that no single value of n provides a uniformly good match to all observations; and we find substantial bay-to-bay variations in the impact of varying n. The results suggest that there are aspects of tsunami wave dissipation which are not captured by a simplified drag formulation used in shallow-water waves model. The study also suggests that the primary impact of removing the near-shore bathymetry in coral reef environment is to reduce run-up, from which we conclude that, at least in this setting, the impact of the near-shore bathymetry is to increase run-up and inundation.

Task-driven image acquisition and reconstruction in cone-beam CT

International Nuclear Information System (INIS)

Gang, Grace J; Stayman, J Webster; Siewerdsen, Jeffrey H; Ehtiati, Tina

2015-01-01

This work introduces a task-driven imaging framework that incorporates a mathematical definition of the imaging task, a model of the imaging system, and a patient-specific anatomical model to prospectively design image acquisition and reconstruction techniques to optimize task performance. The framework is applied to joint optimization of tube current modulation, view-dependent reconstruction kernel, and orbital tilt in cone-beam CT. The system model considers a cone-beam CT system incorporating a flat-panel detector and 3D filtered backprojection and accurately describes the spatially varying noise and resolution over a wide range of imaging parameters in the presence of a realistic anatomical model. Task-based detectability index (d′) is incorporated as the objective function in a task-driven optimization of image acquisition and reconstruction techniques. The orbital tilt was optimized through an exhaustive search across tilt angles ranging ±30°. For each tilt angle, the view-dependent tube current and reconstruction kernel (i.e. the modulation profiles) that maximized detectability were identified via an alternating optimization. The task-driven approach was compared with conventional unmodulated and automatic exposure control (AEC) strategies for a variety of imaging tasks and anthropomorphic phantoms. The task-driven strategy outperformed the unmodulated and AEC cases for all tasks. For example, d′ for a sphere detection task in a head phantom was improved by 30% compared to the unmodulated case by using smoother kernels for noisy views and distributing mAs across less noisy views (at fixed total mAs) in a manner that was beneficial to task performance. Similarly for detection of a line-pair pattern, the task-driven approach increased d′ by 80% compared to no modulation by means of view-dependent mA and kernel selection that yields modulation transfer function and noise-power spectrum optimal to the task. Optimization of orbital tilt identified the

Simulation-based investigation of the generality of Lyzenga's multispectral bathymetry formula in Case-1 coral reef water

Science.gov (United States)

Manessa, Masita Dwi Mandini; Kanno, Ariyo; Sagawa, Tatsuyuki; Sekine, Masahiko; Nurdin, Nurjannah

2018-01-01

Lyzenga's multispectral bathymetry formula has attracted considerable interest due to its simplicity. However, there has been little discussion of the effect that variation in optical conditions and bottom types-which commonly appears in coral reef environments-has on this formula's results. The present paper evaluates Lyzenga's multispectral bathymetry formula for a variety of optical conditions and bottom types. A noiseless dataset of above-water remote sensing reflectance from WorldView-2 images over Case-1 shallow coral reef water is simulated using a radiative transfer model. The simulation-based assessment shows that Lyzenga's formula performs robustly, with adequate generality and good accuracy, under a range of conditions. As expected, the influence of bottom type on depth estimation accuracy is far greater than the influence of other optical parameters, i.e., chlorophyll-a concentration and solar zenith angle. Further, based on the simulation dataset, Lyzenga's formula estimates depth when the bottom type is unknown almost as accurately as when the bottom type is known. This study provides a better understanding of Lyzenga's multispectral bathymetry formula under various optical conditions and bottom types.

Optimization of Regional Geodynamic Models for Mantle Dynamics

Science.gov (United States)

Knepley, M.; Isaac, T.; Jadamec, M. A.

2016-12-01

The SubductionGenerator program is used to construct high resolution, 3D regional thermal structures for mantle convection simulations using a variety of data sources, including sea floor ages and geographically referenced 3D slab locations based on seismic observations. The initial bulk temperature field is constructed using a half-space cooling model or plate cooling model, and related smoothing functions based on a diffusion length-scale analysis. In this work, we seek to improve the 3D thermal model and test different model geometries and dynamically driven flow fields using constraints from observed seismic velocities and plate motions. Through a formal adjoint analysis, we construct the primal-dual version of the multi-objective PDE-constrained optimization problem for the plate motions and seismic misfit. We have efficient, scalable preconditioners for both the forward and adjoint problems based upon a block preconditioning strategy, and a simple gradient update is used to improve the control residual. The full optimal control problem is formulated on a nested hierarchy of grids, allowing a nonlinear multigrid method to accelerate the solution.

Evolution of errors in the altimetric bathymetry model used by Google Earth and GEBCO

Science.gov (United States)

Marks, K. M.; Smith, W. H. F.; Sandwell, D. T.

2010-09-01

We analyze errors in the global bathymetry models of Smith and Sandwell that combine satellite altimetry with acoustic soundings and shorelines to estimate depths. Versions of these models have been incorporated into Google Earth and the General Bathymetric Chart of the Oceans (GEBCO). We use Japan Agency for Marine-Earth Science and Technology (JAMSTEC) multibeam surveys not previously incorporated into the models as "ground truth" to compare against model versions 7.2 through 12.1, defining vertical differences as "errors." Overall error statistics improve over time: 50th percentile errors declined from 57 to 55 to 49 m, and 90th percentile errors declined from 257 to 235 to 219 m, in versions 8.2, 11.1 and 12.1. This improvement is partly due to an increasing number of soundings incorporated into successive models, and partly to improvements in the satellite gravity model. Inspection of specific sites reveals that changes in the algorithms used to interpolate across survey gaps with altimetry have affected some errors. Versions 9.1 through 11.1 show a bias in the scaling from gravity in milliGals to topography in meters that affected the 15-160 km wavelength band. Regionally averaged (>160 km wavelength) depths have accumulated error over successive versions 9 through 11. These problems have been mitigated in version 12.1, which shows no systematic variation of errors with depth. Even so, version 12.1 is in some respects not as good as version 8.2, which employed a different algorithm.

Model-driven software engineering

NARCIS (Netherlands)

Amstel, van M.F.; Brand, van den M.G.J.; Protic, Z.; Verhoeff, T.; Hamberg, R.; Verriet, J.

2014-01-01

Software plays an important role in designing and operating warehouses. However, traditional software engineering methods for designing warehouse software are not able to cope with the complexity, size, and increase of automation in modern warehouses. This chapter describes Model-Driven Software

Bathymetry of Lake Erie and Lake Saint Clair

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetry of Lake Erie and Lake Saint Clair has been compiled as a component of a NOAA project to rescue Great Lakes lake floor geological and geophysical data and...

Semantic Web and Model-Driven Engineering

CERN Document Server

Parreiras, Fernando S

2012-01-01

The next enterprise computing era will rely on the synergy between both technologies: semantic web and model-driven software development (MDSD). The semantic web organizes system knowledge in conceptual domains according to its meaning. It addresses various enterprise computing needs by identifying, abstracting and rationalizing commonalities, and checking for inconsistencies across system specifications. On the other side, model-driven software development is closing the gap among business requirements, designs and executables by using domain-specific languages with custom-built syntax and se

Mapping bathymetry in an active surf zone with the WorldView2 multispectral satellite

Science.gov (United States)

Trimble, S. M.; Houser, C.; Brander, R.; Chirico, P.

2015-12-01

Rip currents are strong, narrow seaward flows of water that originate in the surf zones of many global beaches. They are related to hundreds of international drownings each year, but exact numbers are difficult to calculate due to logistical difficulties in obtaining accurate incident reports. Annual average rip current fatalities are estimated to be ~100, 53 and 21 in the United States (US), Costa Rica, and Australia respectively. Current warning systems (e.g. National Weather Service) do not account for fine resolution nearshore bathymetry because it is difficult to capture. The method shown here could provide frequent, high resolution maps of nearshore bathymetry at a scale required for improved rip prediction and warning. This study demonstrates a method for mapping bathymetry in the surf zone (20m deep and less), specifically within rip channels, because rips form at topographically low spots in the bathymetry as a result of feedback amongst waves, substrate, and antecedent bathymetry. The methods employ the Digital Globe WorldView2 (WV2) multispectral satellite and field measurements of depth to generate maps of the changing bathymetry at two embayed, rip-prone beaches: Playa Cocles, Puerto Viejo de Talamanca, Costa Rica, and Bondi Beach, Sydney, Australia. WV2 has a 1.1 day pass-over rate with 1.84m ground pixel resolution of 8 bands, including 'yellow' (585-625 nm) and 'coastal blue' (400-450 nm). The data is used to classify bottom type and to map depth to the return in multiple bands. The methodology is tested at each site for algorithm consistency between dates, and again for applicability between sites.

A Hybrid Genetic Wind Driven Heuristic Optimization Algorithm for Demand Side Management in Smart Grid

Directory of Open Access Journals (Sweden)

Nadeem Javaid

2017-03-01

Full Text Available In recent years, demand side management (DSM techniques have been designed for residential, industrial and commercial sectors. These techniques are very effective in flattening the load profile of customers in grid area networks. In this paper, a heuristic algorithms-based energy management controller is designed for a residential area in a smart grid. In essence, five heuristic algorithms (the genetic algorithm (GA, the binary particle swarm optimization (BPSO algorithm, the bacterial foraging optimization algorithm (BFOA, the wind-driven optimization (WDO algorithm and our proposed hybrid genetic wind-driven (GWD algorithm are evaluated. These algorithms are used for scheduling residential loads between peak hours (PHs and off-peak hours (OPHs in a real-time pricing (RTP environment while maximizing user comfort (UC and minimizing both electricity cost and the peak to average ratio (PAR. Moreover, these algorithms are tested in two scenarios: (i scheduling the load of a single home and (ii scheduling the load of multiple homes. Simulation results show that our proposed hybrid GWD algorithm performs better than the other heuristic algorithms in terms of the selected performance metrics.

Model-driven Service Engineering with SoaML

Science.gov (United States)

Elvesæter, Brian; Carrez, Cyril; Mohagheghi, Parastoo; Berre, Arne-Jørgen; Johnsen, Svein G.; Solberg, Arnor

This chapter presents a model-driven service engineering (MDSE) methodology that uses OMG MDA specifications such as BMM, BPMN and SoaML to identify and specify services within a service-oriented architecture. The methodology takes advantage of business modelling practices and provides a guide to service modelling with SoaML. The presentation is case-driven and illuminated using the telecommunication example. The chapter focuses in particular on the use of the SoaML modelling language as a means for expressing service specifications that are aligned with business models and can be realized in different platform technologies.

Master-slave control with trajectory planning and Bouc-Wen model for tracking control of piezo-driven stage

Science.gov (United States)

Lu, Xiaojun; Liu, Changli; Chen, Lei

2018-04-01

In this paper, a redundant Piezo-driven stage having 3RRR compliant mechanism is introduced, we propose the master-slave control with trajectory planning (MSCTP) strategy and Bouc-Wen model to improve its micro-motion tracking performance. The advantage of the proposed controller lies in that its implementation only requires a simple control strategy without the complexity of modeling to avoid the master PEA's tracking error. The dynamic model of slave PEA system with Bouc-Wen hysteresis is established and identified via particle swarm optimization (PSO) approach. The Piezo-driven stage with operating period T=1s and 2s is implemented to track a prescribed circle. The simulation results show that MSCTP with Bouc-Wen model reduces the trajectory tracking errors to the range of the accuracy of our available measurement.

Sensor-Based Model Driven Control Strategy for Precision Irrigation

Directory of Open Access Journals (Sweden)

Camilo Lozoya

2016-01-01

Full Text Available Improving the efficiency of the agricultural irrigation systems substantially contributes to sustainable water management. This improvement can be achieved through an automated irrigation system that includes a real-time control strategy based on the water, soil, and crop relationship. This paper presents a model driven control strategy applied to an irrigation system, in order to make an efficient use of water for large crop fields, that is, applying the correct amount of water in the correct place at the right moment. The proposed model uses a predictive algorithm that senses soil moisture and weather variables, to determine optimal amount of water required by the crop. This proposed approach is evaluated against a traditional irrigation system based on the empirical definition of time periods and against a basic soil moisture control system. Results indicate that the use of a model predictive control in an irrigation system achieves a higher efficiency and significantly reduce the water consumption.

Optical modeling of induction-linac driven free-electron lasers

International Nuclear Information System (INIS)

Scharlemann, E.T.; Fawley, W.M.

1986-01-01

The free-electron laser (FEL) simulation code FRED, developed at Lawrence Livermore National Laboratory (LLNL) primarily to model single-pass FEL amplifiers driven by induction linear accelerators, is described. The main emphasis is on the modeling of optical propagation in the laser and on the differences between the requirements for modeling rf-linac-driven vs. induction-linac-driven FELs. Examples of optical guiding and mode cleanup are presented for a 50 μm FEL

Bathymetry and acoustic backscatter data collected in 2010 from Cat Island, Mississippi

Science.gov (United States)

Buster, Noreen A.; Pfeiffer, William R.; Miselis, Jennifer L.; Kindinger, Jack G.; Wiese, Dana S.; Reynolds, B.J.

2012-01-01

Scientists from the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center (SPCMSC), in collaboration with the U.S. Army Corps of Engineers (USACE), conducted geophysical and sedimentological surveys around Cat Island, the westernmost island in the Mississippi-Alabama barrier island chain (fig. 1). The objectives of the study were to understand the geologic evolution of Cat Island relative to other barrier islands in the northern Gulf of Mexico and to identify relationships between the geologic history, present day morphology, and sediment distribution. This report contains data from the bathymetry and side-scan sonar portion of the study collected during two geophysical cruises. Interferometric swath bathymetry and side-scan sonar data were collected aboard the RV G.K. Gilbert September 7-15, 2010. Single-beam bathymetry was collected in shallow water around the island (Field Activity Collection System (FACS) logs, and formal Federal Geographic Data Committee (FDGC) metadata.

Bathymetric Structure from Motion Photogrammetry: Extracting stream bathymetry from multi-view stereo photogrammetry

Science.gov (United States)

Dietrich, J. T.

2016-12-01

Stream bathymetry is a critical variable in a number of river science applications. In larger rivers, bathymetry can be measured with instruments such as sonar (single or multi-beam), bathymetric airborne LiDAR, or acoustic doppler current profilers. However, in smaller streams with depths less than 2 meters, bathymetry is one of the more difficult variables to map at high-resolution. Optical remote sensing techniques offer several potential solutions for collecting high-resolution bathymetry. In this research, I focus on direct photogrammetric measurements of bathymetry using multi-view stereo photogrammetry, specifically Structure from Motion (SfM). The main barrier to accurate bathymetric mapping with any photogrammetric technique is correcting for the refraction of light as it passes between the two different media (air and water), which causes water depths to appear shallower than they are. I propose and test an iterative approach that calculates a series of refraction correction equations for every point/camera combination in a SfM point cloud. This new method is meant to address shortcomings of other correction techniques and works within the current preferred method for SfM data collection, oblique and highly convergent photographs. The multi-camera refraction correction presented here produces bathymetric datasets with accuracies of 0.02% of the flying height and precisions of 0.1% of the flying height. This methodology, like many fluvial remote sensing methods, will only work under ideal conditions (e.g. clear water), but it provides an additional tool for collecting high-resolution bathymetric datasets for a variety of river, coastal, and estuary systems.

Hybrid neuromusculoskeletal modeling to best track joint moments using a balance between muscle excitations derived from electromyograms and optimization.

Science.gov (United States)

Sartori, Massimo; Farina, Dario; Lloyd, David G

2014-11-28

Current electromyography (EMG)-driven musculoskeletal models are used to estimate joint moments measured from an individual׳s extremities during dynamic movement with varying levels of accuracy. The main benefit is the underlying musculoskeletal dynamics is simulated as a function of realistic, subject-specific, neural-excitation patterns provided by the EMG data. The main disadvantage is surface EMG cannot provide information on deeply located muscles. Furthermore, EMG data may be affected by cross-talk, recording and post-processing artifacts that could adversely influence the EMG׳s information content. This limits the EMG-driven model׳s ability to calculate the multi-muscle dynamics and the resulting joint moments about multiple degrees of freedom. We present a hybrid neuromusculoskeletal model that combines calibration, subject-specificity, EMG-driven and static optimization methods together. In this, the joint moment tracking errors are minimized by balancing the information content extracted from the experimental EMG data and from that generated by a static optimization method. Using movement data from five healthy male subjects during walking and running we explored the hybrid model׳s best configuration to minimally adjust recorded EMGs and predict missing EMGs while attaining the best tracking of joint moments. Minimally adjusted and predicted excitations substantially improved the experimental joint moment tracking accuracy than current EMG-driven models. The ability of the hybrid model to predict missing muscle EMGs was also examined. The proposed hybrid model enables muscle-driven simulations of human movement while enforcing physiological constraints on muscle excitation patterns. This might have important implications for studying pathological movement for which EMG recordings are limited.

Slope grid derived from gridded bathymetry of Ofu and Olosega Islands, Territory of American Samoa, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Slope is derived from gridded (5 m cell size) multibeam bathymetry, collected aboard R/V AHI, and bathymetry derived from multispectral IKONOS satellite imagery....

Development of a Data-Driven Predictive Model of Supply Air Temperature in an Air-Handling Unit for Conserving Energy

Directory of Open Access Journals (Sweden)

Goopyo Hong

2018-02-01

Full Text Available The purpose of this study was to develop a data-driven predictive model that can predict the supply air temperature (SAT in an air-handling unit (AHU by using a neural network. A case study was selected, and AHU operational data from December 2015 to November 2016 was collected. A data-driven predictive model was generated through an evolving process that consisted of an initial model, an optimal model, and an adaptive model. In order to develop the optimal model, input variables, the number of neurons and hidden layers, and the period of the training data set were considered. Since AHU data changes over time, an adaptive model, which has the ability to actively cope with constantly changing data, was developed. This adaptive model determined the model with the lowest mean square error (MSE of the 91 models, which had two hidden layers and sets up a 12-hour test set at every prediction. The adaptive model used recently collected data as training data and utilized the sliding window technique rather than the accumulative data method. Furthermore, additional testing was performed to validate the adaptive model using AHU data from another building. The final adaptive model predicts SAT to a root mean square error (RMSE of less than 0.6 °C.

Feedback Limiting the Coastal Response to Irregularities in Shelf Bathymetry

Science.gov (United States)

List, J. H.; Benedet, L.

2007-12-01

Observations and engineering studies have shown that non-uniform inner shelf bathymetry can influence longshore sediment transport gradients and create patterns of shoreline change. One classic example is from Grand Isle, Louisiana, where two offshore borrow pits caused two zones of shoreline accretion landward of the pits. In addition to anthropogenic cases, many natural situations exist in which irregularities in coastal planform are thought to result from offshore shoals or depressions. Recent studies using the hydrodynamic model Delft3D have successfully simulated the observed nearshore erosion and accretion patterns landward of an inner shelf borrow pit. An analysis of the momentum balance in a steady-state simulation has demonstrated that both alongshore pressure gradients (due to alongshore variations in wave setup) and radiation stress gradients (terms relevant to alongshore forcing) are important for forcing the initial pattern of nearshore sedimentation in response to the borrow pit. The response of the coast to non-uniform inner shelf bathymetry appears to be limited, however, because observed shoreline undulations are often rather subtle. (An exception may exist in the case of a very high angle wave climate.) Therefore, feedbacks in processes must exist such that growth of the shoreline salient itself modifies the transport processes in a way that limits further growth (assuming the perturbation in inner shelf bathymetry itself remains unchanged). Examination of the Delft3D momentum balance for an inner shelf pit test case demonstrates that after a certain degree of morphologic development the forcing associated with the well-known shoreline smoothing process (a.k.a., diffusion) counteracts the forcing associated with the inner shelf pit, producing a negative feedback which arrests further growth of the shoreline salient. These results provide insights into the physical processes that control shoreline changes behind inner shelf bathymetric anomalies (i

Bathymetric Position Index (BPI) Structures 5m grid derived from gridded bathymetry of Saipan Island, Commonwealth of the Northern Marianas

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from a focal mean analysis on bathymetry and slope. The bathymetry grid (5 m cell size) is derived from two sources: Multibeam bathymetry...

Rugosity grid (5 m) derived from gridded bathymetry of Saipan Island, Commonwealth of the Northern Marianas

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (5 m cell size) bathymetry from two sources: Multibeam bathymetry collected by Coral Reef Ecosystem Division aboard NOAA R/V AHI,...

GEMSFITS: Code package for optimization of geochemical model parameters and inverse modeling

International Nuclear Information System (INIS)

Miron, George D.; Kulik, Dmitrii A.; Dmytrieva, Svitlana V.; Wagner, Thomas

2015-01-01

Highlights: • Tool for generating consistent parameters against various types of experiments. • Handles a large number of experimental data and parameters (is parallelized). • Has a graphical interface and can perform statistical analysis on the parameters. • Tested on fitting the standard state Gibbs free energies of aqueous Al species. • Example on fitting interaction parameters of mixing models and thermobarometry. - Abstract: GEMSFITS is a new code package for fitting internally consistent input parameters of GEM (Gibbs Energy Minimization) geochemical–thermodynamic models against various types of experimental or geochemical data, and for performing inverse modeling tasks. It consists of the gemsfit2 (parameter optimizer) and gfshell2 (graphical user interface) programs both accessing a NoSQL database, all developed with flexibility, generality, efficiency, and user friendliness in mind. The parameter optimizer gemsfit2 includes the GEMS3K chemical speciation solver ( (http://gems.web.psi.ch/GEMS3K)), which features a comprehensive suite of non-ideal activity- and equation-of-state models of solution phases (aqueous electrolyte, gas and fluid mixtures, solid solutions, (ad)sorption. The gemsfit2 code uses the robust open-source NLopt library for parameter fitting, which provides a selection between several nonlinear optimization algorithms (global, local, gradient-based), and supports large-scale parallelization. The gemsfit2 code can also perform comprehensive statistical analysis of the fitted parameters (basic statistics, sensitivity, Monte Carlo confidence intervals), thus supporting the user with powerful tools for evaluating the quality of the fits and the physical significance of the model parameters. The gfshell2 code provides menu-driven setup of optimization options (data selection, properties to fit and their constraints, measured properties to compare with computed counterparts, and statistics). The practical utility, efficiency, and

Bathymetric Position Index (BPI) Zones 5m grid derived from gridded bathymetry of Saipan Island, Commonwealth of the Northern Marianas

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The bathymetry grid (5 m cell size) is derived from bathymetry from two sources: Multibeam...

Unmanned aerial vehicle observations of water surface elevation and bathymetry in the cenotes and lagoons of the Yucatan Peninsula, Mexico

Science.gov (United States)

Bandini, Filippo; Lopez-Tamayo, Alejandro; Merediz-Alonso, Gonzalo; Olesen, Daniel; Jakobsen, Jakob; Wang, Sheng; Garcia, Monica; Bauer-Gottwein, Peter

2018-04-01

Observations of water surface elevation (WSE) and bathymetry of the lagoons and cenotes of the Yucatán Peninsula (YP) in southeast Mexico are of hydrogeological interest. Observations of WSE (orthometric water height above mean sea level, amsl) are required to inform hydrological models, to estimate hydraulic gradients and groundwater flow directions. Measurements of bathymetry and water depth (elevation of the water surface above the bed of the water body) improve current knowledge on how lagoons and cenotes connect through the complicated submerged cave systems and the diffuse flow in the rock matrix. A novel approach is described that uses unmanned aerial vehicles (UAVs) to monitor WSE and bathymetry of the inland water bodies on the YP. UAV-borne WSE observations were retrieved using a radar and a global navigation satellite system on-board a multi-copter platform. Water depth was measured using a tethered floating sonar controlled by the UAV. This sonar provides depth measurements also in deep and turbid water. Bathymetry (wet-bed elevation amsl) can be computed by subtracting water depth from WSE. Accuracy of the WSE measurements is better than 5-7 cm and accuracy of the water depth measurements is estimated to be 3.8% of the actual water depth. The technology provided accurate measurements of WSE and bathymetry in both wetlands (lagoons) and cenotes. UAV-borne technology is shown to be a more flexible and lower cost alternative to manned aircrafts. UAVs allow monitoring of remote areas located in the jungle of the YP, which are difficult to access by human operators.

Performance-based parameter tuning method of model-driven PID control systems.

Science.gov (United States)

Zhao, Y M; Xie, W F; Tu, X W

2012-05-01

In this paper, performance-based parameter tuning method of model-driven Two-Degree-of-Freedom PID (MD TDOF PID) control system has been proposed to enhance the control performances of a process. Known for its ability of stabilizing the unstable processes, fast tracking to the change of set points and rejecting disturbance, the MD TDOF PID has gained research interest recently. The tuning methods for the reported MD TDOF PID are based on internal model control (IMC) method instead of optimizing the performance indices. In this paper, an Integral of Time Absolute Error (ITAE) zero-position-error optimal tuning and noise effect minimizing method is proposed for tuning two parameters in MD TDOF PID control system to achieve the desired regulating and disturbance rejection performance. The comparison with Two-Degree-of-Freedom control scheme by modified smith predictor (TDOF CS MSP) and the designed MD TDOF PID tuned by the IMC tuning method demonstrates the effectiveness of the proposed tuning method. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Rugosity 10 m grid derived from gridded bathymetry of Alamagan Island, Commonwealth of the Northern Mariana Islands (CNMI), USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (10 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hi'ialakai and R/V AHI, using the Benthic Terrain Modeler with...

Rugosity 10 m grid derived from gridded bathymetry of Pagan Island, Commonwealth of the Northern Mariana Islands (CNMI), USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (10 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hiialaka'i and R/V AHI, using the Benthic Terrain Modeler with...

Rugosity 10 m grid derived from gridded bathymetry of Agrihan Island, Commonwealth of the Northern Mariana Islands (CNMI), USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (10 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hiialaka'i and R/V AHI, using the Benthic Terrain Modeler with...

Rugosity 10 m grid derived from gridded bathymetry of Maug Island, Commonwealth of the Northern Mariana Islands (CNMI), USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (10 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hiialaka'i and R/V AHI, using the Benthic Terrain Modeler with...

Rugosity 10 m grid derived from gridded bathymetry of Asuncion Island, Commonwealth of the Northern Mariana Islands (CNMI), USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (10 m cell size) multibeam bathymetry collected aboard NOAA Ship Hiialaka'i and R/V AHI, using the Benthic Terrain Modeler with...

Rugosity 10 m grid derived from gridded bathymetry of Guguan Island, Commonwealth of the Northern Mariana Islands (CNMI), USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (5 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hiialaka'i and R/V AHI, using the Benthic Terrain Modeler with...

Space Mapping and Beyond: Knowledge-Driven Microwave Design Optimization

DEFF Research Database (Denmark)

Koziel, Slawomir; Madsen, Kaj

2012-01-01

in such a low-fidelity model allows us to dramatically reduce the number of EM simulations necessary to find a satisfactory design. Here, we review the concept of knowledge-driven design as well as specific design techniques, including space mapping, simulation-based tuning, and various response correction...... models that can replace the CPU-intensive EM-simulated structure of interest in the search for optimum design. The surrogate models exploiting physically-based low-fidelity models (e.g., circuit equivalents) can be particularly efficient: the knowledge about the structure under design embedded...

Optimized Matching Lift Unit Transmission Ratio of Engine Driven Ducted Fan

Directory of Open Access Journals (Sweden)

Xiao Senlin

2018-01-01

Full Text Available As a kind of VTOL technology, ducted fan is not only used by many kinds of aircrafts, but also one of the trends of the future aircraft lift system, and attracts more and more attention. For an engine driven ducted fan lift unit, involving the engine and ducted fan matching problem, the form of transmission and transmission ratio are the key design parameters. In order to design and develop a ducted fan aircraft reasonably, a thrust test platform was set up to connect the engine with the ducted fan through the belt driving. The matching relationship between the engine and the transmission system was experimentally studied and the optimal transmission ratio was determined. The results showed that the optimal transmission ratio for the engine 1 is 2.2:1, and for the engine 2, the optimal transmission ratio should be 2.95:1 based on the current ducted and movable blade aerofoil design. At this time, the lift will exceed 130 kg•f, meeting the aircraft's original design requirements.

Fork-join and data-driven execution models on multi-core architectures: Case study of the FMM

KAUST Repository

Amer, Abdelhalim

2013-01-01

Extracting maximum performance of multi-core architectures is a difficult task primarily due to bandwidth limitations of the memory subsystem and its complex hierarchy. In this work, we study the implications of fork-join and data-driven execution models on this type of architecture at the level of task parallelism. For this purpose, we use a highly optimized fork-join based implementation of the FMM and extend it to a data-driven implementation using a distributed task scheduling approach. This study exposes some limitations of the conventional fork-join implementation in terms of synchronization overheads. We find that these are not negligible and their elimination by the data-driven method, with a careful data locality strategy, was beneficial. Experimental evaluation of both methods on state-of-the-art multi-socket multi-core architectures showed up to 22% speed-ups of the data-driven approach compared to the original method. We demonstrate that a data-driven execution of FMM not only improves performance by avoiding global synchronization overheads but also reduces the memory-bandwidth pressure caused by memory-intensive computations. © 2013 Springer-Verlag.

Optimization of current waveform tailoring for magnetically driven isentropic compression experiments

Energy Technology Data Exchange (ETDEWEB)

Waisman, E. M.; Reisman, D. B.; Stoltzfus, B. S.; Stygar, W. A.; Cuneo, M. E.; Haill, T. A.; Davis, J.-P.; Brown, J. L.; Seagle, C. T. [Sandia National Laboratories, Albuquerque, New Mexico 87185 (United States); Spielman, R. B. [Idaho State University, Pocatello, Idaho 83201 (United States)

2016-06-15

The Thor pulsed power generator is being developed at Sandia National Laboratories. The design consists of up to 288 decoupled and transit time isolated capacitor-switch units, called “bricks,” that can be individually triggered to achieve a high degree of pulse tailoring for magnetically driven isentropic compression experiments (ICE) [D. B. Reisman et al., Phys. Rev. Spec. Top.–Accel. Beams 18, 090401 (2015)]. The connecting transmission lines are impedance matched to the bricks, allowing the capacitor energy to be efficiently delivered to an ICE strip-line load with peak pressures of over 100 GPa. Thor will drive experiments to explore equation of state, material strength, and phase transition properties of a wide variety of materials. We present an optimization process for producing tailored current pulses, a requirement for many material studies, on the Thor generator. This technique, which is unique to the novel “current-adder” architecture used by Thor, entirely avoids the iterative use of complex circuit models to converge to the desired electrical pulse. We begin with magnetohydrodynamic simulations for a given material to determine its time dependent pressure and thus the desired strip-line load current and voltage. Because the bricks are connected to a central power flow section through transit-time isolated coaxial cables of constant impedance, the brick forward-going pulses are independent of each other. We observe that the desired equivalent forward-going current driving the pulse must be equal to the sum of the individual brick forward-going currents. We find a set of optimal brick delay times by requiring that the L{sub 2} norm of the difference between the brick-sum current and the desired forward-going current be a minimum. We describe the optimization procedure for the Thor design and show results for various materials of interest.

A virtual power plant model for time-driven power flow calculations

Directory of Open Access Journals (Sweden)

Gerardo Guerra

2017-11-01

Full Text Available This paper presents the implementation of a custom-made virtual power plant model in OpenDSS. The goal is to develop a model adequate for time-driven power flow calculations in distribution systems. The virtual power plant is modeled as the aggregation of renewable generation and energy storage connected to the distribution system through an inverter. The implemented operation mode allows the virtual power plant to act as a single dispatchable generation unit. The case studies presented in the paper demonstrate that the model behaves according to the specified control algorithm and show how it can be incorporated into the solution scheme of a general parallel genetic algorithm in order to obtain the optimal day-ahead dispatch. Simulation results exhibit a clear benefit from the deployment of a virtual power plant when compared to distributed generation based only on renewable intermittent generation.

CRED 20 m Gridded bathymetry of Brooks Banks and St. Rogatien Bank, Hawaii, USA (Arc ASCII format)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry (20m) of the shelf and slope environments of Brooks Banks and St. Rogatien, Hawaii, USA. The ASCII includes multibeam bathymetry from the Simrad...

Optimization modeling with spreadsheets

CERN Document Server

Baker, Kenneth R

2015-01-01

An accessible introduction to optimization analysis using spreadsheets Updated and revised, Optimization Modeling with Spreadsheets, Third Edition emphasizes model building skills in optimization analysis. By emphasizing both spreadsheet modeling and optimization tools in the freely available Microsoft® Office Excel® Solver, the book illustrates how to find solutions to real-world optimization problems without needing additional specialized software. The Third Edition includes many practical applications of optimization models as well as a systematic framework that il

Envisioning the future of collaborative model-driven software engineering

NARCIS (Netherlands)

Di Ruscio, Davide; Franzago, Mirco; Malavolta, Ivano; Muccini, Henry

2017-01-01

The adoption of Model-driven Software Engineering (MDSE) to develop complex software systems in application domains like automotive and aerospace is being supported by the maturation of model-driven platforms and tools. However, empirical studies show that a wider adoption of MDSE technologies is

Data-Driven Optimization of Incentive-based Demand Response System with Uncertain Responses of Customers

Directory of Open Access Journals (Sweden)

Jimyung Kang

2017-10-01

Full Text Available Demand response is nowadays considered as another type of generator, beyond just a simple peak reduction mechanism. A demand response service provider (DRSP can, through its subcontracts with many energy customers, virtually generate electricity with actual load reduction. However, in this type of virtual generator, the amount of load reduction includes inevitable uncertainty, because it consists of a very large number of independent energy customers. While they may reduce energy today, they might not tomorrow. In this circumstance, a DSRP must choose a proper set of these uncertain customers to achieve the exact preferred amount of load curtailment. In this paper, the customer selection problem for a service provider that consists of uncertain responses of customers is defined and solved. The uncertainty of energy reduction is fully considered in the formulation with data-driven probability distribution modeling and stochastic programming technique. The proposed optimization method that utilizes only the observed load data provides a realistic and applicable solution to a demand response system. The performance of the proposed optimization is verified with real demand response event data in Korea, and the results show increased and stabilized performance from the service provider’s perspective.

Adaptive beamforming for low frequency SAS imagery and bathymetry

NARCIS (Netherlands)

Hayes, M.P.; Hunter, A.J.

2012-01-01

Synthetic aperture side-scan sonar (SAS) is a mature technology for high-resolution sea floor imaging [1]. Interferometric synthetic aperture sonars (InSAS) use additional hydrophones in a vertical array for bathymetric mapping [2]. This has created high-resolution bathymetry in deep water

Bathymetric Position Index (BPI) Structures 20 m grid derived from gridded bathymetry of Brooks Banks, Hawaii, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (20 m cell size) multibeam bathymetry,...

Bathymetric Position Index (BPI) Zones 5 m grid derived from gridded bathymetry of Brooks Banks, Hawaii, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry, collected aboard NOAA...

Bathymetric Position Index (BPI) Structures 5 m grid derived from gridded bathymetry of Kure Atoll, Hawaii, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry,...

Bathymetric Position Index (BPI) Zones 20 m grid derived from gridded bathymetry of Brooks Banks, Hawaii, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (20 m cell size) multibeam bathymetry, collected aboard NOAA...

The Arizona Universities Library Consortium patron-driven e-book model

Directory of Open Access Journals (Sweden)

Jeanne Richardson

2013-03-01

Full Text Available Building on Arizona State University's patron-driven acquisitions (PDA initiative in 2009, the Arizona Universities Library Consortium, in partnership with the Ingram Content Group, created a cooperative patron-driven model to acquire electronic books (e-books. The model provides the opportunity for faculty and students at the universities governed by the Arizona Board of Regents (ABOR to access a core of e-books made accessible through resource discovery services and online catalogs. These books are available for significantly less than a single ABOR university would expend for the same materials. The patron-driven model described is one of many evolving models in digital scholarship, and, although the Arizona Universities Library Consortium reports a successful experience, patron-driven models pose questions to stakeholders in the academic publishing industry.

Bathymetric Position Index (BPI) Zones 5 m grid derived from gridded bathymetry of Kure Atoll, Hawaii, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry, collected aboard R/V...

Gridded bathymetry of 35 fthm Bank, and 37 fthm Bank, north of Farallon de Medinilla, CNMI, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry (5m) of the bank environment of 35-fthm Bank and 37 fthm Bank,CNMI USA. These netCDF and ASCII grids include multibeam bathymetry from the Reson...

Failure-probability driven dose painting

International Nuclear Information System (INIS)

Vogelius, Ivan R.; Håkansson, Katrin; Due, Anne K.; Aznar, Marianne C.; Kristensen, Claus A.; Rasmussen, Jacob; Specht, Lena; Berthelsen, Anne K.; Bentzen, Søren M.

2013-01-01

Purpose: To demonstrate a data-driven dose-painting strategy based on the spatial distribution of recurrences in previously treated patients. The result is a quantitative way to define a dose prescription function, optimizing the predicted local control at constant treatment intensity. A dose planning study using the optimized dose prescription in 20 patients is performed.Methods: Patients treated at our center have five tumor subvolumes from the center of the tumor (PET positive volume) and out delineated. The spatial distribution of 48 failures in patients with complete clinical response after (chemo)radiation is used to derive a model for tumor control probability (TCP). The total TCP is fixed to the clinically observed 70% actuarial TCP at five years. Additionally, the authors match the distribution of failures between the five subvolumes to the observed distribution. The steepness of the dose–response is extracted from the literature and the authors assume 30% and 20% risk of subclinical involvement in the elective volumes. The result is a five-compartment dose response model matching the observed distribution of failures. The model is used to optimize the distribution of dose in individual patients, while keeping the treatment intensity constant and the maximum prescribed dose below 85 Gy.Results: The vast majority of failures occur centrally despite the small volumes of the central regions. Thus, optimizing the dose prescription yields higher doses to the central target volumes and lower doses to the elective volumes. The dose planning study shows that the modified prescription is clinically feasible. The optimized TCP is 89% (range: 82%–91%) as compared to the observed TCP of 70%.Conclusions: The observed distribution of locoregional failures was used to derive an objective, data-driven dose prescription function. The optimized dose is predicted to result in a substantial increase in local control without increasing the predicted risk of toxicity

Rugosity grid derived from gridded bathymetry of Ta'u Island of the Manu'a Island group, American Samoa

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (5 m cell size) multibeam bathymetry, collected aboard R/V AHI, and bathymetry derived from multispectral IKONOS satellite imagery...

Rugosity grid derived from gridded bathymetry Ofu and Olosega Islands of the Manu'a Island group, American Samoa

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (5 m cell size) multibeam bathymetry, collected aboard R/V AHI, and bathymetry derived from multispectral IKONOS satellite imagery...

A data-driven approach for modeling post-fire debris-flow volumes and their uncertainty

Science.gov (United States)

Friedel, Michael J.

2011-01-01

This study demonstrates the novel application of genetic programming to evolve nonlinear post-fire debris-flow volume equations from variables associated with a data-driven conceptual model of the western United States. The search space is constrained using a multi-component objective function that simultaneously minimizes root-mean squared and unit errors for the evolution of fittest equations. An optimization technique is then used to estimate the limits of nonlinear prediction uncertainty associated with the debris-flow equations. In contrast to a published multiple linear regression three-variable equation, linking basin area with slopes greater or equal to 30 percent, burn severity characterized as area burned moderate plus high, and total storm rainfall, the data-driven approach discovers many nonlinear and several dimensionally consistent equations that are unbiased and have less prediction uncertainty. Of the nonlinear equations, the best performance (lowest prediction uncertainty) is achieved when using three variables: average basin slope, total burned area, and total storm rainfall. Further reduction in uncertainty is possible for the nonlinear equations when dimensional consistency is not a priority and by subsequently applying a gradient solver to the fittest solutions. The data-driven modeling approach can be applied to nonlinear multivariate problems in all fields of study.

Model Driven Architecture: Foundations and Applications

NARCIS (Netherlands)

Rensink, Arend

The OMG's Model Driven Architecture (MDA) initiative has been the focus of much attention in both academia and industry, due to its promise of more rapid and consistent software development through the increased use of models. In order for MDA to reach its full potential, the ability to manipulate

Experimental Modeling of Monolithic Resistors for Silicon ICS with a Robust Optimizer-Driving Scheme

Directory of Open Access Journals (Sweden)

Philippe Leduc

2002-06-01

Full Text Available Today, an exhaustive library of models describing the electrical behavior of integrated passive components in the radio-frequency range is essential for the simulation and optimization of complex circuits. In this work, a preliminary study has been done on Tantalum Nitride (TaN resistors integrated on silicon, and this leads to a single p-type lumped-element circuit. An efficient extraction technique will be presented to provide a computer-driven optimizer with relevant initial model parameter values (the "guess-timate". The results show the unicity in most cases of the lumped element determination, which leads to a precise simulation of self-resonant frequencies.

Consistent model driven architecture

Science.gov (United States)

Niepostyn, Stanisław J.

2015-09-01

The goal of the MDA is to produce software systems from abstract models in a way where human interaction is restricted to a minimum. These abstract models are based on the UML language. However, the semantics of UML models is defined in a natural language. Subsequently the verification of consistency of these diagrams is needed in order to identify errors in requirements at the early stage of the development process. The verification of consistency is difficult due to a semi-formal nature of UML diagrams. We propose automatic verification of consistency of the series of UML diagrams originating from abstract models implemented with our consistency rules. This Consistent Model Driven Architecture approach enables us to generate automatically complete workflow applications from consistent and complete models developed from abstract models (e.g. Business Context Diagram). Therefore, our method can be used to check practicability (feasibility) of software architecture models.

SeaDataNet II - EMODNet Bathymetry - building a pan-European infrastructure for marine and ocean data management and a digital high resolution bathymetry for European seas

Science.gov (United States)

Schaap, Dick M. A.; Fichaut, Michele

2015-04-01

European sea regions as part of EMODnet Phase 2, which started mid 2013. EMODnet encourages more data providers to come forward for data sharing and participating in the process of making complete overviews and homogeneous data products. The EMODnet Bathymetry project is very illustrative for the synergy between SeaDataNet and EMODnet and added value of generating public data products. The project develops and publishes Digital Terrain Models (DTM) for the European seas. These are produced from survey and aggregated data sets. The portal provides a versatile DTM viewing service with many relevant map layers and functions for retrieving. A further refinement is taking place as part of phase 2. The presentation will highlight key achievements in SeaDataNet II and give further details and views on the new EMODNet Digital Bathymetry for European seas as to be released early 2015.

CFD-Driven Valve Shape Optimization for Performance Improvement of a Micro Cross-Flow Turbine

Directory of Open Access Journals (Sweden)

Endashaw Tesfaye Woldemariam

2018-01-01

Full Text Available Turbines are critical parts in hydropower facilities, and the cross-flow turbine is one of the widely applied turbine designs in small- and micro-hydro facilities. Cross-flow turbines are relatively simple, flexible and less expensive, compared to other conventional hydro-turbines. However, the power generation efficiency of cross-flow turbines is not yet well optimized compared to conventional hydro-turbines. In this article, a Computational Fluid Dynamics (CFD-driven design optimization approach is applied to one of the critical parts of the turbine, the valve. The valve controls the fluid flow, as well as determines the velocity and pressure magnitudes of the fluid jet leaving the nozzle region in the turbine. The Non-Uniform Rational B-Spline (NURBS function is employed to generate construction points for the valve profile curve. Control points from the function that are highly sensitive to the output power are selected as optimization parameters, leading to the generation of construction points. Metamodel-assisted and metaheuristic optimization tools are used in the optimization. Optimized turbine designs from both optimization methods outperformed the original design with regard to performance of the turbine. Moreover, the metamodel-assisted optimization approach reduced the computational cost, compared to its counterpart.

Bathymetric Position Index (BPI) Structures 10 m grid derived from gridded bathymetry of Wake Island, West Central Pacific.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (10 m cell size) multibeam bathymetry,...

Bathymetric Position Index (BPI) Structures 5 m grid derived from gridded bathymetry of Ni'ihau Island, Hawaii, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry,...

Bathymetric Position Index (BPI) Zones 60 m grid derived from gridded bathymetry of Rota Island, Mariana Islands, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (60 m cell size) multibeam bathymetry, collected aboard NOAA...

Bathymetric Position Index (BPI) Structures 60 m grid derived from gridded bathymetry of Wake Island, West Central Pacific.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (60 m cell size) multibeam bathymetry,...

Bathymetric Position Index (BPI) Zones 5 m grid derived from gridded bathymetry of French Frigate Shoals, Hawaii, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry, collected aboard NOAA...

Bathymetric Position Index (BPI) Zones 5 m grid derived from gridded bathymetry of Ni'ihau Island, Hawaii, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry, collected aboard NOAA...

Bathymetric Position Index (BPI) Structures 5 m grid derived from gridded bathymetry of French Frigate Shoals, Hawaii, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry,...

Bathymetric Position Index (BPI) Zones 60 m grid derived from gridded bathymetry of Wake Island, West Central Pacific.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (60 m cell size) multibeam bathymetry, collected aboard R/V...

A Model-Driven Development Method for Management Information Systems

Science.gov (United States)

Mizuno, Tomoki; Matsumoto, Keinosuke; Mori, Naoki

Traditionally, a Management Information System (MIS) has been developed without using formal methods. By the informal methods, the MIS is developed on its lifecycle without having any models. It causes many problems such as lack of the reliability of system design specifications. In order to overcome these problems, a model theory approach was proposed. The approach is based on an idea that a system can be modeled by automata and set theory. However, it is very difficult to generate automata of the system to be developed right from the start. On the other hand, there is a model-driven development method that can flexibly correspond to changes of business logics or implementing technologies. In the model-driven development, a system is modeled using a modeling language such as UML. This paper proposes a new development method for management information systems applying the model-driven development method to a component of the model theory approach. The experiment has shown that a reduced amount of efforts is more than 30% of all the efforts.

A consistent data set of Antarctic ice sheet topography, cavity geometry, and global bathymetry

Directory of Open Access Journals (Sweden)

R. Timmermann

2010-12-01

Full Text Available Sub-ice shelf circulation and freezing/melting rates in ocean general circulation models depend critically on an accurate and consistent representation of cavity geometry. Existing global or pan-Antarctic topography data sets have turned out to contain various inconsistencies and inaccuracies. The goal of this work is to compile independent regional surveys and maps into a global data set. We use the S-2004 global 1-min bathymetry as the backbone and add an improved version of the BEDMAP topography (ALBMAP bedrock topography for an area that roughly coincides with the Antarctic continental shelf. The position of the merging line is individually chosen in different sectors in order to capture the best of both data sets. High-resolution gridded data for ice shelf topography and cavity geometry of the Amery, Fimbul, Filchner-Ronne, Larsen C and George VI Ice Shelves, and for Pine Island Glacier are carefully merged into the ambient ice and ocean topographies. Multibeam survey data for bathymetry in the former Larsen B cavity and the southeastern Bellingshausen Sea have been obtained from the data centers of Alfred Wegener Institute (AWI, British Antarctic Survey (BAS and Lamont-Doherty Earth Observatory (LDEO, gridded, and blended into the existing bathymetry map. The resulting global 1-min Refined Topography data set (RTopo-1 contains self-consistent maps for upper and lower ice surface heights, bedrock topography, and surface type (open ocean, grounded ice, floating ice, bare land surface. The data set is available in NetCDF format from the PANGAEA database at doi:10.1594/pangaea.741917.

Data-Driven Zero-Sum Neuro-Optimal Control for a Class of Continuous-Time Unknown Nonlinear Systems With Disturbance Using ADP.

Science.gov (United States)

Wei, Qinglai; Song, Ruizhuo; Yan, Pengfei

2016-02-01

This paper is concerned with a new data-driven zero-sum neuro-optimal control problem for continuous-time unknown nonlinear systems with disturbance. According to the input-output data of the nonlinear system, an effective recurrent neural network is introduced to reconstruct the dynamics of the nonlinear system. Considering the system disturbance as a control input, a two-player zero-sum optimal control problem is established. Adaptive dynamic programming (ADP) is developed to obtain the optimal control under the worst case of the disturbance. Three single-layer neural networks, including one critic and two action networks, are employed to approximate the performance index function, the optimal control law, and the disturbance, respectively, for facilitating the implementation of the ADP method. Convergence properties of the ADP method are developed to show that the system state will converge to a finite neighborhood of the equilibrium. The weight matrices of the critic and the two action networks are also convergent to finite neighborhoods of their optimal ones. Finally, the simulation results will show the effectiveness of the developed data-driven ADP methods.

Model-Driven Development of Context-Aware Services

NARCIS (Netherlands)

Andrade Almeida, João; Iacob, Maria Eugenia; Jonkers, Henk; Quartel, Dick; Eliassen, Frank; Montresor, Alberto

2006-01-01

In this paper, we define a model-driven design trajectory for context-aware services consisting of three levels of models with different degrees of abstraction and platform independence. The models at the highest level of platform independence describe the behaviour of a context-aware service and

Analysis of the possibilities of using aerial photographs to determine the bathymetry in shallow coastal zone of the selected section of the Baltic Sea

Science.gov (United States)

Cieszynski, Lukasz; Furmanczyk, Kazimierz

2017-04-01

Bathymetry data for the coastal zone of the Baltic Sea are usually created in profiles based on echo sounding measurements. However, in the shallow coastal zone (up to 4 m depth), the quality and accuracy of data is insufficient because of the spatial variability of the seabed. The green laser - LIDAR - can comprise a solution for studies of such shallow areas. However, this method is still an expensive one and that is why we have decided to use the RGB digital aerial photographs to create a model for mapping the seabed of the shallow coastal zone. So far, in the 60's, researchers in the USA (Musgrove, 1969) and Russia (Zdanowicz, 1963) developed the first method of bathymetry determining from aerial panchromatic (black-white) photographs. This method was adapted for the polish conditions by Furmanczyk in 1975 and in 2014 we have returned to his concept using more advanced techniques of recording and image processing. In our study, we propose to determine the bathymetry in shallow coastal zone of the Baltic Sea by using the digital vertical aerial photographs (both single and multi-channel spectral). These photos are the high-resolution matrix (10 cm per pixel) containing values of the grey level in the individual spectral bands (RGB). This gives great possibilities to determine the bathymetry in order to analyze the changes in the marine coastal zone. Comparing the digital bathymetry maps - obtained by proposed method - in the following periods, you can develop differential maps, which reflect the movements of sea-bottom sediments. This can be used to indicate the most dynamic regions in the examined area. The model is based on the image pixel values and relative depths measured in situ (in selected checkpoints). As a result, the relation of the pixel brightness and sea depth (the algorithm) was defined. Using the algorithm, depth calculations for the whole scene were done and high resolution bathymetric map created. However, the algorithm requires numbers of

The use of radar for bathymetry assessment

OpenAIRE

Aardoom, J.H.; Greidanus, H.S.F.

1998-01-01

The bottom topography in shallow seas can be observed by air- and spaceborne imaging radar. Bathymetric information derived from radar data is limited in accuracy, but radar has a good spatial coverage. The accuracy can be increased by assimilating the radar imagery into existing or insitu gathered bathymetric data. The paper reviews the concepts of bathymetry assessment by radar, the radar imaging mechanism, and the possibilities and limitations of the use of radar data in rapid assessment.

Using data-driven agent-based models for forecasting emerging infectious diseases

Directory of Open Access Journals (Sweden)

Srinivasan Venkatramanan

2018-03-01

Full Text Available Producing timely, well-informed and reliable forecasts for an ongoing epidemic of an emerging infectious disease is a huge challenge. Epidemiologists and policy makers have to deal with poor data quality, limited understanding of the disease dynamics, rapidly changing social environment and the uncertainty on effects of various interventions in place. Under this setting, detailed computational models provide a comprehensive framework for integrating diverse data sources into a well-defined model of disease dynamics and social behavior, potentially leading to better understanding and actions. In this paper, we describe one such agent-based model framework developed for forecasting the 2014–2015 Ebola epidemic in Liberia, and subsequently used during the Ebola forecasting challenge. We describe the various components of the model, the calibration process and summarize the forecast performance across scenarios of the challenge. We conclude by highlighting how such a data-driven approach can be refined and adapted for future epidemics, and share the lessons learned over the course of the challenge. Keywords: Emerging infectious diseases, Agent-based models, Simulation optimization, Bayesian calibration, Ebola

Algorithms for optimization of branching gravity-driven water networks

Directory of Open Access Journals (Sweden)

I. Dardani

2018-05-01

Full Text Available The design of a water network involves the selection of pipe diameters that satisfy pressure and flow requirements while considering cost. A variety of design approaches can be used to optimize for hydraulic performance or reduce costs. To help designers select an appropriate approach in the context of gravity-driven water networks (GDWNs, this work assesses three cost-minimization algorithms on six moderate-scale GDWN test cases. Two algorithms, a backtracking algorithm and a genetic algorithm, use a set of discrete pipe diameters, while a new calculus-based algorithm produces a continuous-diameter solution which is mapped onto a discrete-diameter set. The backtracking algorithm finds the global optimum for all but the largest of cases tested, for which its long runtime makes it an infeasible option. The calculus-based algorithm's discrete-diameter solution produced slightly higher-cost results but was more scalable to larger network cases. Furthermore, the new calculus-based algorithm's continuous-diameter and mapped solutions provided lower and upper bounds, respectively, on the discrete-diameter global optimum cost, where the mapped solutions were typically within one diameter size of the global optimum. The genetic algorithm produced solutions even closer to the global optimum with consistently short run times, although slightly higher solution costs were seen for the larger network cases tested. The results of this study highlight the advantages and weaknesses of each GDWN design method including closeness to the global optimum, the ability to prune the solution space of infeasible and suboptimal candidates without missing the global optimum, and algorithm run time. We also extend an existing closed-form model of Jones (2011 to include minor losses and a more comprehensive two-part cost model, which realistically applies to pipe sizes that span a broad range typical of GDWNs of interest in this work, and for smooth and commercial steel

Algorithms for optimization of branching gravity-driven water networks

Science.gov (United States)

Dardani, Ian; Jones, Gerard F.

2018-05-01

The design of a water network involves the selection of pipe diameters that satisfy pressure and flow requirements while considering cost. A variety of design approaches can be used to optimize for hydraulic performance or reduce costs. To help designers select an appropriate approach in the context of gravity-driven water networks (GDWNs), this work assesses three cost-minimization algorithms on six moderate-scale GDWN test cases. Two algorithms, a backtracking algorithm and a genetic algorithm, use a set of discrete pipe diameters, while a new calculus-based algorithm produces a continuous-diameter solution which is mapped onto a discrete-diameter set. The backtracking algorithm finds the global optimum for all but the largest of cases tested, for which its long runtime makes it an infeasible option. The calculus-based algorithm's discrete-diameter solution produced slightly higher-cost results but was more scalable to larger network cases. Furthermore, the new calculus-based algorithm's continuous-diameter and mapped solutions provided lower and upper bounds, respectively, on the discrete-diameter global optimum cost, where the mapped solutions were typically within one diameter size of the global optimum. The genetic algorithm produced solutions even closer to the global optimum with consistently short run times, although slightly higher solution costs were seen for the larger network cases tested. The results of this study highlight the advantages and weaknesses of each GDWN design method including closeness to the global optimum, the ability to prune the solution space of infeasible and suboptimal candidates without missing the global optimum, and algorithm run time. We also extend an existing closed-form model of Jones (2011) to include minor losses and a more comprehensive two-part cost model, which realistically applies to pipe sizes that span a broad range typical of GDWNs of interest in this work, and for smooth and commercial steel roughness values.

Mid-Ocean Ridge Melt Supply and Glacial Cycles: A 3D EPR Study of Crustal Thickness, Layer 2A, and Bathymetry

Science.gov (United States)

Boulahanis, B.; Aghaei, O.; Carbotte, S. M.; Huybers, P. J.; Langmuir, C. H.; Nedimovic, M. R.; Carton, H. D.; Canales, J. P.

2017-12-01

Recent studies suggest that eustatic sea level fluctuations induced by glacial cycles in the Pleistocene may influence mantle-melting and volcanic eruptions at mid-ocean ridges (MOR), with models predicting variation in oceanic crustal thickness linked to sea level change. Previous analyses of seafloor bathymetry as a proxy for crustal thickness show significant spectral energy at frequencies linked to Milankovitch cycles of 1/23, 1/41, and 1/100 ky-1, however the effects of faulting in seafloor relief and its spectral characteristics are difficult to separate from climatic signals. Here we investigate the hypothesis of climate driven periodicity in MOR magmatism through spectral analysis, time series comparisons, and statistical characterization of bathymetry data, seismic layer 2A thickness (as a proxy for extrusive volcanism), and seafloor-to-Moho thickness (as a proxy for total magma production). We utilize information from a three-dimensional multichannel seismic study of the East Pacific Rise and its flanks from 9°36`N to 9°57`N. We compare these datasets to the paleoclimate "LR04" benthic δ18O stack. The seismic dataset covers 770 km2 and provides resolution of Moho for 92% of the imaged region. This is the only existing high-resolution 3-D image across oceanic crust, making it ideal for assessing the possibility that glacial cycles modulate magma supply at fast spreading MORs. The layer 2A grid extends 9 km (170 ky) from the ridge axis, while Moho imaging extends to a maximum of 16 km (310 ky). Initial results from the East Pacific Rise show a relationship between sea level and both crustal thickness and sea floor depth, consistent with the hypothesis that magma supply to MORs may be modulated by glacial cycles. Analysis of crustal thickness and bathymetry data reveals spectral peaks at Milankovitch frequencies of 1/100 ky-1 and 1/41 ky-1 where datasets extend sufficiently far from the ridge. The layer 2A grid does not extend sufficiently far from the

Information-theoretic model selection for optimal prediction of stochastic dynamical systems from data

Science.gov (United States)

Darmon, David

2018-03-01

In the absence of mechanistic or phenomenological models of real-world systems, data-driven models become necessary. The discovery of various embedding theorems in the 1980s and 1990s motivated a powerful set of tools for analyzing deterministic dynamical systems via delay-coordinate embeddings of observations of their component states. However, in many branches of science, the condition of operational determinism is not satisfied, and stochastic models must be brought to bear. For such stochastic models, the tool set developed for delay-coordinate embedding is no longer appropriate, and a new toolkit must be developed. We present an information-theoretic criterion, the negative log-predictive likelihood, for selecting the embedding dimension for a predictively optimal data-driven model of a stochastic dynamical system. We develop a nonparametric estimator for the negative log-predictive likelihood and compare its performance to a recently proposed criterion based on active information storage. Finally, we show how the output of the model selection procedure can be used to compare candidate predictors for a stochastic system to an information-theoretic lower bound.

Bending of Euler-Bernoulli nanobeams based on the strain-driven and stress-driven nonlocal integral models: a numerical approach

Science.gov (United States)

Oskouie, M. Faraji; Ansari, R.; Rouhi, H.

2018-04-01

Eringen's nonlocal elasticity theory is extensively employed for the analysis of nanostructures because it is able to capture nanoscale effects. Previous studies have revealed that using the differential form of the strain-driven version of this theory leads to paradoxical results in some cases, such as bending analysis of cantilevers, and recourse must be made to the integral version. In this article, a novel numerical approach is developed for the bending analysis of Euler-Bernoulli nanobeams in the context of strain- and stress-driven integral nonlocal models. This numerical approach is proposed for the direct solution to bypass the difficulties related to converting the integral governing equation into a differential equation. First, the governing equation is derived based on both strain-driven and stress-driven nonlocal models by means of the minimum total potential energy. Also, in each case, the governing equation is obtained in both strong and weak forms. To solve numerically the derived equations, matrix differential and integral operators are constructed based upon the finite difference technique and trapezoidal integration rule. It is shown that the proposed numerical approach can be efficiently applied to the strain-driven nonlocal model with the aim of resolving the mentioned paradoxes. Also, it is able to solve the problem based on the strain-driven model without inconsistencies of the application of this model that are reported in the literature.

Data-driven modeling, control and tools for cyber-physical energy systems

Science.gov (United States)

Behl, Madhur

Energy systems are experiencing a gradual but substantial change in moving away from being non-interactive and manually-controlled systems to utilizing tight integration of both cyber (computation, communications, and control) and physical representations guided by first principles based models, at all scales and levels. Furthermore, peak power reduction programs like demand response (DR) are becoming increasingly important as the volatility on the grid continues to increase due to regulation, integration of renewables and extreme weather conditions. In order to shield themselves from the risk of price volatility, end-user electricity consumers must monitor electricity prices and be flexible in the ways they choose to use electricity. This requires the use of control-oriented predictive models of an energy system's dynamics and energy consumption. Such models are needed for understanding and improving the overall energy efficiency and operating costs. However, learning dynamical models using grey/white box approaches is very cost and time prohibitive since it often requires significant financial investments in retrofitting the system with several sensors and hiring domain experts for building the model. We present the use of data-driven methods for making model capture easy and efficient for cyber-physical energy systems. We develop Model-IQ, a methodology for analysis of uncertainty propagation for building inverse modeling and controls. Given a grey-box model structure and real input data from a temporary set of sensors, Model-IQ evaluates the effect of the uncertainty propagation from sensor data to model accuracy and to closed-loop control performance. We also developed a statistical method to quantify the bias in the sensor measurement and to determine near optimal sensor placement and density for accurate data collection for model training and control. Using a real building test-bed, we show how performing an uncertainty analysis can reveal trends about

Data-driven method based on particle swarm optimization and k-nearest neighbor regression for estimating capacity of lithium-ion battery

International Nuclear Information System (INIS)

Hu, Chao; Jain, Gaurav; Zhang, Puqiang; Schmidt, Craig; Gomadam, Parthasarathy; Gorka, Tom

2014-01-01

Highlights: • We develop a data-driven method for the battery capacity estimation. • Five charge-related features that are indicative of the capacity are defined. • The kNN regression model captures the dependency of the capacity on the features. • Results with 10 years’ continuous cycling data verify the effectiveness of the method. - Abstract: Reliability of lithium-ion (Li-ion) rechargeable batteries used in implantable medical devices has been recognized as of high importance from a broad range of stakeholders, including medical device manufacturers, regulatory agencies, physicians, and patients. To ensure Li-ion batteries in these devices operate reliably, it is important to be able to assess the battery health condition by estimating the battery capacity over the life-time. This paper presents a data-driven method for estimating the capacity of Li-ion battery based on the charge voltage and current curves. The contributions of this paper are three-fold: (i) the definition of five characteristic features of the charge curves that are indicative of the capacity, (ii) the development of a non-linear kernel regression model, based on the k-nearest neighbor (kNN) regression, that captures the complex dependency of the capacity on the five features, and (iii) the adaptation of particle swarm optimization (PSO) to finding the optimal combination of feature weights for creating a kNN regression model that minimizes the cross validation (CV) error in the capacity estimation. Verification with 10 years’ continuous cycling data suggests that the proposed method is able to accurately estimate the capacity of Li-ion battery throughout the whole life-time

Energy Optimal Path Planning: Integrating Coastal Ocean Modelling with Optimal Control

Science.gov (United States)

Subramani, D. N.; Haley, P. J., Jr.; Lermusiaux, P. F. J.

2016-02-01

A stochastic optimization methodology is formulated for computing energy-optimal paths from among time-optimal paths of autonomous vehicles navigating in a dynamic flow field. To set up the energy optimization, the relative vehicle speed and headings are considered to be stochastic, and new stochastic Dynamically Orthogonal (DO) level-set equations that govern their stochastic time-optimal reachability fronts are derived. Their solution provides the distribution of time-optimal reachability fronts and corresponding distribution of time-optimal paths. An optimization is then performed on the vehicle's energy-time joint distribution to select the energy-optimal paths for each arrival time, among all stochastic time-optimal paths for that arrival time. The accuracy and efficiency of the DO level-set equations for solving the governing stochastic level-set reachability fronts are quantitatively assessed, including comparisons with independent semi-analytical solutions. Energy-optimal missions are studied in wind-driven barotropic quasi-geostrophic double-gyre circulations, and in realistic data-assimilative re-analyses of multiscale coastal ocean flows. The latter re-analyses are obtained from multi-resolution 2-way nested primitive-equation simulations of tidal-to-mesoscale dynamics in the Middle Atlantic Bight and Shelbreak Front region. The effects of tidal currents, strong wind events, coastal jets, and shelfbreak fronts on the energy-optimal paths are illustrated and quantified. Results showcase the opportunities for longer-duration missions that intelligently utilize the ocean environment to save energy, rigorously integrating ocean forecasting with optimal control of autonomous vehicles.

Rugosity 10 m grid derived from gridded bathymetry of Farallon de Pajaros (Uracas) Island, Commonwealth of the Northern Mariana Islands (CNMI), USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (10 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hiialaka'i and R/V AHI, using the Benthic Terrain Modeler with...

Review on Available Information on Wind, Water Level, Current, Geology and Bathymetry in the DanWEC Area

DEFF Research Database (Denmark)

Margheritini, Lucia

level, geology and bathymetry information at the DanWEC location. The present report has been prepared under the project No. 834101 “DanWEC Vaekstforum 2011”, task 3: “Collection and presentation of basic data about wind, current, water head, bathymetry and geology for the DanWEC site at the Port...

Worldwide Database of Analog Marine Seismics, Bathymetry, Magnetics, and Gravity Data

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Analog Marine Geophysical Underway data file consists primarily of seismic data and some bathymetry, magnetics, and gravity data. Most of the data are released...

Data-driven modeling of nano-nose gas sensor arrays

DEFF Research Database (Denmark)

Alstrøm, Tommy Sonne; Larsen, Jan; Nielsen, Claus Højgård

2010-01-01

We present a data-driven approach to classification of Quartz Crystal Microbalance (QCM) sensor data. The sensor is a nano-nose gas sensor that detects concentrations of analytes down to ppm levels using plasma polymorized coatings. Each sensor experiment takes approximately one hour hence...... the number of available training data is limited. We suggest a data-driven classification model which work from few examples. The paper compares a number of data-driven classification and quantification schemes able to detect the gas and the concentration level. The data-driven approaches are based on state...

Data–driven modeling of nano-nose gas sensor arrays

DEFF Research Database (Denmark)

Alstrøm, Tommy Sonne; Larsen, Jan; Nielsen, Claus Højgård

2010-01-01

We present a data-driven approach to classification of Quartz Crystal Microbalance (QCM) sensor data. The sensor is a nano-nose gas sensor that detects concentrations of analytes down to ppm levels using plasma polymorized coatings. Each sensor experiment takes approximately one hour hence...... the number of available training data is limited. We suggest a data-driven classification model which work from few examples. The paper compares a number of data-driven classification and quantification schemes able to detect the gas and the concentration level. The data-driven approaches are based on state...

Maintenance modeling and optimization integrating human and material resources

International Nuclear Information System (INIS)

Martorell, S.; Villamizar, M.; Carlos, S.; Sanchez, A.

2010-01-01

Maintenance planning is a subject of concern to many industrial sectors as plant safety and business depend on it. Traditionally, the maintenance planning is formulated in terms of a multi-objective optimization (MOP) problem where reliability, availability, maintainability and cost (RAM+C) act as decision criteria and maintenance strategies (i.e. maintenance tasks intervals) act as the only decision variables. However the appropriate development of each maintenance strategy depends not only on the maintenance intervals but also on the resources (human and material) available to implement such strategies. Thus, the effect of the necessary resources on RAM+C needs to be modeled and accounted for in formulating the MOP affecting the set of objectives and constraints. In this paper RAM+C models to explicitly address the effect of human resources and material resources (spare parts) on RAM+C criteria are proposed. This extended model allows accounting for explicitly how the above decision criteria depends on the basic model parameters representing the type of strategies, maintenance intervals, durations, human resources and material resources. Finally, an application case is performed to optimize the maintenance plan of a motor-driven pump equipment considering as decision variables maintenance and test intervals and human and material resources.

Maintenance modeling and optimization integrating human and material resources

Energy Technology Data Exchange (ETDEWEB)

Martorell, S., E-mail: smartore@iqn.upv.e [Dpto. Ingenieria Quimica y Nuclear, Universidad Politecnica Valencia (Spain); Villamizar, M.; Carlos, S. [Dpto. Ingenieria Quimica y Nuclear, Universidad Politecnica Valencia (Spain); Sanchez, A. [Dpto. Estadistica e Investigacion Operativa Aplicadas y Calidad, Universidad Politecnica Valencia (Spain)

2010-12-15

Maintenance planning is a subject of concern to many industrial sectors as plant safety and business depend on it. Traditionally, the maintenance planning is formulated in terms of a multi-objective optimization (MOP) problem where reliability, availability, maintainability and cost (RAM+C) act as decision criteria and maintenance strategies (i.e. maintenance tasks intervals) act as the only decision variables. However the appropriate development of each maintenance strategy depends not only on the maintenance intervals but also on the resources (human and material) available to implement such strategies. Thus, the effect of the necessary resources on RAM+C needs to be modeled and accounted for in formulating the MOP affecting the set of objectives and constraints. In this paper RAM+C models to explicitly address the effect of human resources and material resources (spare parts) on RAM+C criteria are proposed. This extended model allows accounting for explicitly how the above decision criteria depends on the basic model parameters representing the type of strategies, maintenance intervals, durations, human resources and material resources. Finally, an application case is performed to optimize the maintenance plan of a motor-driven pump equipment considering as decision variables maintenance and test intervals and human and material resources.

Bathymetric Position Index (BPI) Zones 60 m grid derived from gridded bathymetry of the U.S. Territory of Guam.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (60 m cell size) multibeam bathymetry, collected aboard NOAA...

Bathymetric Position Index (BPI) Structures 5 m grid derived from gridded bathymetry of Pearl and Hermes Atoll, Hawaii, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry,...

Bathymetric Position Index (BPI) Zones 5 m grid derived from gridded bathymetry of Pearl and Hermes Atoll, Hawaii, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry, collected aboard R/V...

Design and optimization of a compact laser-driven proton beamline.

Science.gov (United States)

Scisciò, M; Migliorati, M; Palumbo, L; Antici, P

2018-04-19

Laser-accelerated protons, generated by irradiating a solid target with a short, energetic laser pulse at high intensity (I > 10 18  W·cm -2 ), represent a complementary if not outperforming source compared to conventional accelerators, due  to their intrinsic features, such as high beam charge and short bunch duration. However, the broadband energy spectrum of these proton sources is a bottleneck that precludes their use in applications requiring a more reduced energy spread. Consequently, in recent times strong effort has been put to overcome these limits and to develop laser-driven proton beamlines with low energy spread. In this paper, we report on beam dynamics simulations aiming at optimizing a laser-driven beamline - i.e. a laser-based proton source coupled to conventional magnetic beam manipulation devices - producing protons with a reduced energy spread, usable for applications. The energy range of investigation goes from 2 to 20 MeV, i.e. the typical proton energies that can be routinely obtained using commercial TW-power class laser systems. Our beamline design is capable of reducing the energy spread below 20%, still keeping the overall transmission efficiency around 1% and producing a proton spot-size in the range of 10 mm 2 . We briefly discuss the results in the context of applications in the domain of Cultural Heritage.

Characterization and optimization of laser-driven electron and photon sources in keV and MeV energy ranges

International Nuclear Information System (INIS)

Bonnet, Thomas

2013-01-01

This work takes place in the framework of the characterization and the optimization of laser-driven electron and photon sources. With the goal of using these sources for nuclear physics experiments, we focused on 2 energy ranges: one around a few MeV and the other around a few tens of keV. The first part of this work is thus dedicated to the study of detectors routinely used for the characterization of laser-driven particle sources: Imaging Plates. A model has been developed and is fitted to experimental data. Response functions to electrons, photons, protons and alpha particles are established for SR, MS and TR Fuji Imaging Plates for energies ranging from a few keV to several MeV. The second part of this work present a study of ultrashort and intense electron and photon sources produced in the interaction of a laser with a solid or liquid target. An experiment was conducted at the ELFIE facility at LULI where beams of electrons and photons were accelerated up to several MeV. Energy and angular distributions of the electron and photons beams were characterized. The sources were optimized by varying the spatial extension of the plasma at both the front and the back end of the initial target position. In the optimal configuration of the laser-plasma coupling, more than 1011 electrons were accelerated. In the case of liquid target, a photon source was produced at a high repetition rate on an energy range of tens of keV by the interaction of the AURORE Laser at CELIA (10 16 W.cm -2 ) and a melted gallium target. It was shown that both the mean energy and the photon number can be increased by creating gallium jets at the surface of the liquid target with a pre-pulse. A physical interpretation supported by numerical simulations is proposed. (author)

Rugosity grid derived from gridded bathymetry of Kure Atoll, Hawaii, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (5 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hiialaka'i and R/V AHI, and IKONOS derived depths using the Benthic...

OW Smith and Sandwell v8.2 - 1/30 Degree Bathymetry & Topography

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Global bathymetry and topography information at 1/30 degree resolution. Data collected by means of in-situ and satellite measurements.

Semi-Empirical Models for Buoyancy-Driven Ventilation

DEFF Research Database (Denmark)

Terpager Andersen, Karl

2015-01-01

A literature study is presented on the theories and models dealing with buoyancy-driven ventilation in rooms. The models are categorised into four types according to how the physical process is conceived: column model, fan model, neutral plane model and pressure model. These models are analysed...... and compared with a reference model. Discrepancies and differences are shown, and the deviations are discussed. It is concluded that a reliable buoyancy model based solely on the fundamental flow equations is desirable....

The ModelCC Model-Driven Parser Generator

Directory of Open Access Journals (Sweden)

Fernando Berzal

2015-01-01

Full Text Available Syntax-directed translation tools require the specification of a language by means of a formal grammar. This grammar must conform to the specific requirements of the parser generator to be used. This grammar is then annotated with semantic actions for the resulting system to perform its desired function. In this paper, we introduce ModelCC, a model-based parser generator that decouples language specification from language processing, avoiding some of the problems caused by grammar-driven parser generators. ModelCC receives a conceptual model as input, along with constraints that annotate it. It is then able to create a parser for the desired textual syntax and the generated parser fully automates the instantiation of the language conceptual model. ModelCC also includes a reference resolution mechanism so that ModelCC is able to instantiate abstract syntax graphs, rather than mere abstract syntax trees.

Bathymetric Position Index (BPI) Structures 5m grid derived from gridded bathymetry of Tinian Island, Aguijan Island and Tatsumi Bank, Commonwealth of the Northern Marianas

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from a focal mean analysis on bathymetry and slope. The bathymetry grid (5 m cell size) is derived from bathymetry from three sources:...

Bathymetric Position Index (BPI) Zones 5m grid derived from gridded bathymetry of Tinian Island, Aguijan Island and Tatsumi Bank, Commonwealth of the Northern Marianas

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The bathymetry grid (5 m cell size) is derived from bathymetry from three sources:...

A characteristic study of CCF modeling techniques and optimization of CCF defense strategies

International Nuclear Information System (INIS)

Kim, Min Chull

2000-02-01

Common Cause Failures (CCFs ) are among the major contributors to risk and core damage frequency (CDF ) from operating nuclear power plants (NPPs ). Our study on CCF focused on the following aspects : 1) a characteristic study on the CCF modeling techniques and 2) development of the optimal CCF defense strategy. Firstly, the characteristics of CCF modeling techniques were studied through sensitivity study of CCF occurrence probability upon system redundancy. The modeling techniques considered in this study include those most widely used worldwide, i.e., beta factor, MGL, alpha factor, and binomial failure rate models. We found that MGL and alpha factor models are essentially identical in terms of the CCF probability. Secondly, in the study for CCF defense, the various methods identified in the previous studies for defending against CCF were classified into five different categories. Based on these categories, we developed a generic method by which the optimal CCF defense strategy can be selected. The method is not only qualitative but also quantitative in nature: the selection of the optimal strategy among candidates is based on the use of analytic hierarchical process (AHP). We applied this method to two motor-driven valves for containment sump isolation in Ulchin 3 and 4 nuclear power plants. The result indicates that the method for developing an optimal CCF defense strategy is effective

Data-Driven Modeling of Complex Systems by means of a Dynamical ANN

Science.gov (United States)

Seleznev, A.; Mukhin, D.; Gavrilov, A.; Loskutov, E.; Feigin, A.

2017-12-01

The data-driven methods for modeling and prognosis of complex dynamical systems become more and more popular in various fields due to growth of high-resolution data. We distinguish the two basic steps in such an approach: (i) determining the phase subspace of the system, or embedding, from available time series and (ii) constructing an evolution operator acting in this reduced subspace. In this work we suggest a novel approach combining these two steps by means of construction of an artificial neural network (ANN) with special topology. The proposed ANN-based model, on the one hand, projects the data onto a low-dimensional manifold, and, on the other hand, models a dynamical system on this manifold. Actually, this is a recurrent multilayer ANN which has internal dynamics and capable of generating time series. Very important point of the proposed methodology is the optimization of the model allowing us to avoid overfitting: we use Bayesian criterion to optimize the ANN structure and estimate both the degree of evolution operator nonlinearity and the complexity of nonlinear manifold which the data are projected on. The proposed modeling technique will be applied to the analysis of high-dimensional dynamical systems: Lorenz'96 model of atmospheric turbulence, producing high-dimensional space-time chaos, and quasi-geostrophic three-layer model of the Earth's atmosphere with the natural orography, describing the dynamics of synoptical vortexes as well as mesoscale blocking systems. The possibility of application of the proposed methodology to analyze real measured data is also discussed. The study was supported by the Russian Science Foundation (grant #16-12-10198).

A Big Data-driven Model for the Optimization of Healthcare Processes.

Science.gov (United States)

Koufi, Vassiliki; Malamateniou, Flora; Vassilacopoulos, George

2015-01-01

Healthcare organizations increasingly navigate a highly volatile, complex environment in which technological advancements and new healthcare delivery business models are the only constants. In their effort to out-perform in this environment, healthcare organizations need to be agile enough in order to become responsive to these increasingly changing conditions. To act with agility, healthcare organizations need to discover new ways to optimize their operations. To this end, they focus on healthcare processes that guide healthcare delivery and on the technologies that support them. Business process management (BPM) and Service-Oriented Architecture (SOA) can provide a flexible, dynamic, cloud-ready infrastructure where business process analytics can be utilized to extract useful insights from mountains of raw data, and make them work in ways beyond the abilities of human brains, or IT systems from just a year ago. This paper presents a framework which provides healthcare professionals gain better insight within and across your business processes. In particular, it performs real-time analysis on process-related data in order reveal areas of potential process improvement.

Collision-model approach to steering of an open driven qubit

Science.gov (United States)

Beyer, Konstantin; Luoma, Kimmo; Strunz, Walter T.

2018-03-01

We investigate quantum steering of an open quantum system by measurements on its environment in the framework of collision models. As an example we consider a coherently driven qubit dissipatively coupled to a bath. We construct local nonadaptive and adaptive as well as nonlocal measurement scenarios specifying explicitly the measured observable on the environment. Our approach shows transparently how the conditional evolution of the open system depends on the type of the measurement scenario and the measured observables. These can then be optimized for steering. The nonlocal measurement scenario leads to maximal violation of the used steering inequality at zero temperature. Further, we investigate the robustness of the constructed scenarios against thermal noise. We find generally that steering becomes harder at higher temperatures. Surprisingly, the system can be steered even when bipartite entanglement between the system and individual subenvironments vanishes.

Data-Driven Assistance Functions for Industrial Automation Systems

International Nuclear Information System (INIS)

Windmann, Stefan; Niggemann, Oliver

2015-01-01

The increasing amount of data in industrial automation systems overburdens the user in process control and diagnosis tasks. One possibility to cope with these challenges consists of using smart assistance systems that automatically monitor and optimize processes. This article deals with aspects of data-driven assistance systems such as assistance functions, process models and data acquisition. The paper describes novel approaches for self-diagnosis and self-optimization, and shows how these assistance functions can be integrated in different industrial environments. The considered assistance functions are based on process models that are automatically learned from process data. Fault detection and isolation is based on the comparison of observations of the real system with predictions obtained by application of the process models. The process models are further employed for energy efficiency optimization of industrial processes. Experimental results are presented for fault detection and energy efficiency optimization of a drive system. (paper)

Optimized Finite-Difference Coefficients for Hydroacoustic Modeling

Science.gov (United States)

Preston, L. A.

2014-12-01

Responsible utilization of marine renewable energy sources through the use of current energy converter (CEC) and wave energy converter (WEC) devices requires an understanding of the noise generation and propagation from these systems in the marine environment. Acoustic noise produced by rotating turbines, for example, could adversely affect marine animals and human-related marine activities if not properly understood and mitigated. We are utilizing a 3-D finite-difference acoustic simulation code developed at Sandia that can accurately propagate noise in the complex bathymetry in the near-shore to open ocean environment. As part of our efforts to improve computation efficiency in the large, high-resolution domains required in this project, we investigate the effects of using optimized finite-difference coefficients on the accuracy of the simulations. We compare accuracy and runtime of various finite-difference coefficients optimized via criteria such as maximum numerical phase speed error, maximum numerical group speed error, and L-1 and L-2 norms of weighted numerical group and phase speed errors over a given spectral bandwidth. We find that those coefficients optimized for L-1 and L-2 norms are superior in accuracy to those based on maximal error and can produce runtimes of 10% of the baseline case, which uses Taylor Series finite-difference coefficients at the Courant time step limit. We will present comparisons of the results for the various cases evaluated as well as recommendations for utilization of the cases studied. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Gridded multibeam bathymetry of Howland Island, Pacific Remote Island Areas, Central Pacific

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry at 40m resolution surrounding Howland Island, within the Pacific Remote Island Areas - Central Pacific Ocean. Bottom coverage was achieved in...

The Application of Cyber Physical System for Thermal Power Plants: Data-Driven Modeling

Directory of Open Access Journals (Sweden)

Yongping Yang

2018-03-01

Full Text Available Optimal operation of energy systems plays an important role to enhance their lifetime security and efficiency. The determination of optimal operating strategies requires intelligent utilization of massive data accumulated during operation or prediction. The investigation of these data solely without combining physical models may run the risk that the established relationships between inputs and outputs, the models which reproduce the behavior of the considered system/component in a wide range of boundary conditions, are invalid for certain boundary conditions, which never occur in the database employed. Therefore, combining big data with physical models via cyber physical systems (CPS is of great importance to derive highly-reliable and -accurate models and becomes more and more popular in practical applications. In this paper, we focus on the description of a systematic method to apply CPS to the performance analysis and decision making of thermal power plants. We proposed a general procedure of CPS with both offline and online phases for its application to thermal power plants and discussed the corresponding methods employed to support each sub-procedure. As an example, a data-driven model of turbine island of an existing air-cooling based thermal power plant is established with the proposed procedure and demonstrates its practicality, validity and flexibility. To establish such model, the historical operating data are employed in the cyber layer for modeling and linking each physical component. The decision-making procedure of optimal frequency of air-cooling condenser is also illustrated to show its applicability of online use. It is concluded that the cyber physical system with the data mining technique is effective and promising to facilitate the real-time analysis and control of thermal power plants.

Optimization of a Solar-Driven Trigeneration System with Nanofluid-Based Parabolic Trough Collectors

Directory of Open Access Journals (Sweden)

Evangelos Bellos

2017-06-01

Full Text Available The objective of this work was to optimize and to evaluate a solar-driven trigeneration system which operates with nanofluid-based parabolic trough collectors. The trigeneration system includes an organic Rankine cycle (ORC and an absorption heat pump operating with LiBr-H2O which is powered by the rejected heat of the ORC. Toluene, n-octane, Octamethyltrisiloxane (MDM and cyclohexane are the examined working fluids in the ORC. The use of CuO and Al2O3 nanoparticles in the Syltherm 800 (base fluid is investigated in the solar field loop. The analysis is performed with Engineering Equation Solver (EES under steady state conditions in order to give the emphasis in the exergetic optimization of the system. Except for the different working fluid investigation, the system is optimized by examining three basic operating parameters in all the cases. The pressure in the turbine inlet, the temperature in the ORC condenser and the nanofluid concentration are the optimization variables. According to the final results, the combination of toluene in the ORC with the CuO nanofluid is the optimum choice. The global maximum exergetic efficiency is 24.66% with pressure ratio is equal to 0.7605, heat rejection temperature 113.7 °C and CuO concentration 4.35%.

Fast and low-cost method for VBES bathymetry generation in coastal areas

Science.gov (United States)

Sánchez-Carnero, N.; Aceña, S.; Rodríguez-Pérez, D.; Couñago, E.; Fraile, P.; Freire, J.

2012-12-01

Sea floor topography is key information in coastal area management. Nowadays, LiDAR and multibeam technologies provide accurate bathymetries in those areas; however these methodologies are yet too expensive for small customers (fishermen associations, small research groups) willing to keep a periodic surveillance of environmental resources. In this paper, we analyse a simple methodology for vertical beam echosounder (VBES) bathymetric data acquisition and postprocessing, using low-cost means and free customizable tools such as ECOSONS and gvSIG (that is compared with industry standard ArcGIS). Echosounder data was filtered, resampled and, interpolated (using kriging or radial basis functions). Moreover, the presented methodology includes two data correction processes: Monte Carlo simulation, used to reduce GPS errors, and manually applied bathymetric line transformations, both improving the obtained results. As an example, we present the bathymetry of the Ría de Cedeira (Galicia, NW Spain), a good testbed area for coastal bathymetry methodologies given its extension and rich topography. The statistical analysis, performed by direct ground-truthing, rendered an upper bound of 1.7 m error, at 95% confidence level, and 0.7 m r.m.s. (cross-validation provided 30 cm and 25 cm, respectively). The methodology presented is fast and easy to implement, accurate outside transects (accuracy can be estimated), and can be used as a low-cost periodical monitoring method.

Bathymetric Position Index (BPI) Zones 5 m grid derived from gridded bathymetry of Tau Island, Territory of American Samoa, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry, collected aboard R/V...

Gridded multibeam bathymetry of Baker Island, Pacific Remote Island Areas, Central Pacific

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry at 40m resolution surrounding Baker Island, within the Pacific Remote Island Areas - Central Pacific Ocean. Bottom coverage was achieved in depths...

Utilization of bathymetry data to examine lead sediment contamination distributions in Lake Ontario

Directory of Open Access Journals (Sweden)

Chris H. Marvin

2016-06-01

Full Text Available Bathymetry data offer interesting opportunities for the analysis of contaminant distribution patterns. This research utilized lead surficial sediment sample data from Lake Ontario that were collected by the Canada Centre for Inland Waters in 1968 and 1998. Traditionally, two-dimensional analyses such as dot maps or proportional circle representation have been utilized to examine pollutant levels. Generating area estimates allows for expanded spatial analysis of contaminant distribution patterns. Lake-wide surfaces were derived using the ordinary kriging technique. These were then layered on bathymetry data to examine three-dimensional relationships between observed pollution patterns and lake-bottom features. Spatial variability was observed in both the 1968 and 1998 datasets. Contamination levels in 1998 dropped substantially, especially in areas that were previously the most heavily polluted and above the Probable Effect Level (4660.23 km2 or 26.72% of the common analysis area lake-bottom in 1998 versus 6189.07 km2 or 62.00% in 1968. Conversely, areas below the Threshold Effect Level increased from 922.09 km2 (5.29% in 1968 to 3484.22 km2 (19.98% in 1998. In both years, shallow and sill/ridge areas tended to have lower levels of contamination than deeper lake basins or contaminant inflow areas. The 1968 dataset likely provides a more detailed estimation surface as there were more points available for interpolation procedures. The kriging surfaces when combined with bathymetry, sedimentology information, and knowledge of physical processes provide a comprehensive illustration of the contaminant distributions whether they are high (1968 or when loadings are significantly reduced (1998. The results have implications for future sediment assessment programs and survey design on a lake-wide basis. The bathymetry data allowed for enhanced interpretation and an improved understanding of observed lead pollution patterns.

Managing business compliance using model-driven security management

Science.gov (United States)

Lang, Ulrich; Schreiner, Rudolf

Compliance with regulatory and governance standards is rapidly becoming one of the hot topics of information security today. This is because, especially with regulatory compliance, both business and government have to expect large financial and reputational losses if compliance cannot be ensured and demonstrated. One major difficulty of implementing such regulations is caused the fact that they are captured at a high level of abstraction that is business-centric and not IT centric. This means that the abstract intent needs to be translated in a trustworthy, traceable way into compliance and security policies that the IT security infrastructure can enforce. Carrying out this mapping process manually is time consuming, maintenance-intensive, costly, and error-prone. Compliance monitoring is also critical in order to be able to demonstrate compliance at any given point in time. The problem is further complicated because of the need for business-driven IT agility, where IT policies and enforcement can change frequently, e.g. Business Process Modelling (BPM) driven Service Oriented Architecture (SOA). Model Driven Security (MDS) is an innovative technology approach that can solve these problems as an extension of identity and access management (IAM) and authorization management (also called entitlement management). In this paper we will illustrate the theory behind Model Driven Security for compliance, provide an improved and extended architecture, as well as a case study in the healthcare industry using our OpenPMF 2.0 technology.

Distributed simulation a model driven engineering approach

CERN Document Server

Topçu, Okan; Oğuztüzün, Halit; Yilmaz, Levent

2016-01-01

Backed by substantive case studies, the novel approach to software engineering for distributed simulation outlined in this text demonstrates the potent synergies between model-driven techniques, simulation, intelligent agents, and computer systems development.

Bathymetric Position Index (BPI) Zones 5 m grid derived from gridded bathymetry of Rose Atoll, Territory of American Samoa, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry, collected aboard R/V AHI...

A Novel Method to Magnetic Flux Linkage Optimization of Direct-Driven Surface-Mounted Permanent Magnet Synchronous Generator Based on Nonlinear Dynamic Analysis

Directory of Open Access Journals (Sweden)

Qian Xie

2016-07-01

Full Text Available This paper pays attention to magnetic flux linkage optimization of a direct-driven surface-mounted permanent magnet synchronous generator (D-SPMSG. A new compact representation of the D-SPMSG nonlinear dynamic differential equations to reduce system parameters is established. Furthermore, the nonlinear dynamic characteristics of new D-SPMSG equations in the process of varying magnetic flux linkage are considered, which are illustrated by Lyapunov exponent spectrums, phase orbits, Poincaré maps, time waveforms and bifurcation diagrams, and the magnetic flux linkage stable region of D-SPMSG is acquired concurrently. Based on the above modeling and analyses, a novel method of magnetic flux linkage optimization is presented. In addition, a 2 MW D-SPMSG 2D/3D model is designed by ANSYS software according to the practical design requirements. Finally, five cases of D-SPMSG models with different magnetic flux linkages are simulated by using the finite element analysis (FEA method. The nephograms of magnetic flux density are agreement with theoretical analysis, which both confirm the correctness and effectiveness of the proposed approach.

CRED 10 m Gridded multibeam bathymetry of Wake Island, West Central Pacific

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry shelf, bank and slope environments of Wake Island, West Central Pacific, under joint management of the United States Dept. of Interior and Air...

CRED 60 m Gridded multibeam bathymetry of Wake Island, West Central Pacific

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry shelf, bank and slope environments of Wake Island, West Central Pacific, under joint management of the United States Dept. of Interior and Air...

Investigation of Current Driven Loudspeakers

DEFF Research Database (Denmark)

Schneider, Henrik; Agerkvist, Finn T.; Knott, Arnold

2015-01-01

Current driven loudspeakers have previously been investigated but the literature is limited and the advantages and disadvantages are yet to be fully identified. This paper makes use of a non-linear loudspeaker model to analyse loudspeakers with distinct non-linear characteristics under voltage an......” woofer where a copper ring in the pole piece has not been implemented to compensate for eddy currents. However the drive method seems to be irrelevant for a 5” woofer where the compliance, force factor as well as the voice coil inductance has been optimized for linearity.......Current driven loudspeakers have previously been investigated but the literature is limited and the advantages and disadvantages are yet to be fully identified. This paper makes use of a non-linear loudspeaker model to analyse loudspeakers with distinct non-linear characteristics under voltage...

Data-Driven Controller Design The H2 Approach

CERN Document Server

Sanfelice Bazanella, Alexandre; Eckhard, Diego

2012-01-01

Data-driven methodologies have recently emerged as an important paradigm alternative to model-based controller design and several such methodologies are formulated as an H2 performance optimization. This book presents a comprehensive theoretical treatment of the H2 approach to data-driven control design. The fundamental properties implied by the H2 problem formulation are analyzed in detail, so that common features to all solutions are identified. Direct methods (VRFT) and iterative methods (IFT, DFT, CbT) are put under a common theoretical framework. The choice of the reference model, the experimental conditions, the optimization method to be used, and several other designer’s choices are crucial to the quality of the final outcome, and firm guidelines for all these choices are derived from the theoretical analysis presented. The practical application of the concepts in the book is illustrated with a large number of practical designs performed for different classes of processes: thermal, fluid processing a...

Optimal arm posture control and tendon traction forces of a coupled tendon-driven manipulator

International Nuclear Information System (INIS)

Ma, Shugen

1997-01-01

In this study, the optimum arm posture of a coupled tendon-driven multijoint manipulator arm (or CT Arm) at maximum payload output was derived and the corresponding tendon traction forces were also analyzed, during management of a heavy payload by the manipulator in a gravity environment. The CT Arm is special tendon traction transmission mechanism in which a pair of tendons used to drive a joint is pulled from base actuators via pulleys mounted on the base-side joints. This mechanism enables optimal utilization of the coupled drive function of tendon traction forces and thus enables the lightweight manipulator to exhibit large payload capability. The properties of the CT Arm mechanism are elucidated by the proposed optimal posture control scheme. Computer simulation was also executed to verify the validity of the proposed control scheme. (author)

Bathymetry 2M Grid, US Virgin Islands, 2005, UTM 20 NAD83

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains a unified ESRI Grid with 2 meter cell size representing the bathymetry of selected portions of seafloor around St. Croix, St. Thomas, and St....

Identifikasi Kedalaman Laut (Bathymetry berdasarkan Warna Permukaan Laut pada Citra Satelit menggunakan Metode ANFIS

Directory of Open Access Journals (Sweden)

Diwan Mukti Pambuko

2013-10-01

mengetahui warna permukaan pada posisi tersebut dapat dibuat sebuah sistem yang bisa mengidentifikasi kedalaman laut pada posisi tertentu dari warna pada permukaan laut tersebut. Sistem yang dibangun ini menggunakan data kedalaman laut hasil pengukuran manual dan dipadukan dengan data gambar satelit pada posisi yang sama. Kemudian dilakukan proses learning menggunakan teknik Neuro-Fuzzy dengan metode ANFIS (Adaptive Neuro-Fuzzy Inference System dengan kinerja model identifikasi dapat diketahui dari nilai MAPE (Mean Absolute Percentage Error dan MSE (Mean Square Error. Hasil dari pembuatan model identifikasi, diperoleh sistem yang dapat melakukan identifikasi sangat baik dengan error yang diperoleh pada saat proses pengujian sebesar MAPE 9.0024 % dan MSE 0.0034. Kata kunci: bathymetry, citra satelit, neuro-fuzzy, ANFIS

Design optimization and transverse coherence analysis for an x-ray free electron laser driven by SLAC LINAC

International Nuclear Information System (INIS)

Xie, M.

1995-01-01

I present a design study for an X-ray Free Electron Laser driven by the SLAC linac, the Linac Coherent Light Source (LCLS). The study assumes the LCLS is based on Self-Amplified Spontaneous Emission (SASE). Following a brief review of the fundamentals of SASE, I will provide without derivation a collection of formulas relating SASE performance to the system parameters. These formulas allow quick evaluation of FEL designs and provide powerful tools for optimization in multi-dimensional parameter space. Optimization is carried out for the LCLS over all independent system parameters modeled, subjected to a number of practical constraints. In addition to the optimizations concerning gain and power, another important consideration for a single pass FEL starting from noise is the transverse coherence property of the amplified radiation, especially at short wavelength. A widely used emittance criteria for FELs requires that the emittance is smaller than the radiation wavelength divided by 4π. For the LCLS the criteria is violated by a factor of 5, at a normalized emittance of 1.5 mm-mrad, wavelength of 1.5 angstrom, and beam energy of 15 GeV. Thus it is important to check quantitatively the emittance effect on the transverse coherence. I will examine the emittance effect on transverse coherence by analyzing different transverse modes and show that full transverse coherence can be obtained even at the LCLS parameter regime

Bathymetric Position Index (BPI) Structures 40 m grid derived from gridded bathymetry of Howland Island, Pacific Remote Island Areas, Central Pacific.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (40 m cell size) multibeam bathymetry,...

Bathymetric Position Index (BPI) Structures 20 m grid derived from gridded bathymetry of Johnston Island, Pacific Remote Island Areas, Central Pacific.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (20 m cell size) multibeam bathymetry,...

Bathymetric Position Index (BPI) Structures derived from gridded bathymetry of Farallon de Medinilla (FDM), Commonwealth of the Northern Mariana (CNMI), USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry,...

Bathymetric Position Index (BPI) Structures 20 m grid derived from gridded bathymetry of Baker Island, Pacific Remote Island Areas, Central Pacific.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (20 m cell size) multibeam bathymetry,...

Bathymetric Position Index (BPI) Structures 5 m grid derived from gridded bathymetry of Ta'u Island, Territory of American Samoa, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry,...

Data mining, knowledge discovery and data-driven modelling

NARCIS (Netherlands)

Solomatine, D.P.; Velickov, S.; Bhattacharya, B.; Van der Wal, B.

2003-01-01

The project was aimed at exploring the possibilities of a new paradigm in modelling - data-driven modelling, often referred as "data mining". Several application areas were considered: sedimentation problems in the Port of Rotterdam, automatic soil classification on the basis of cone penetration

Spatially Explicit Estimation of Optimal Light Use Efficiency for Improved Satellite Data Driven Ecosystem Productivity Modeling

Science.gov (United States)

Madani, N.; Kimball, J. S.; Running, S. W.

2014-12-01

Remote sensing based light use efficiency (LUE) models, including the MODIS (MODerate resolution Imaging Spectroradiometer) MOD17 algorithm are commonly used for regional estimation and monitoring of vegetation gross primary production (GPP) and photosynthetic carbon (CO2) uptake. A common model assumption is that plants in a biome matrix operate at their photosynthetic capacity under optimal climatic conditions. A prescribed biome maximum light use efficiency parameter defines the maximum photosynthetic carbon conversion rate under prevailing climate conditions and is a large source of model uncertainty. Here, we used tower (FLUXNET) eddy covariance measurement based carbon flux data for estimating optimal LUE (LUEopt) over a North American domain. LUEopt was first estimated using tower observed daily carbon fluxes, meteorology and satellite (MODIS) observed fraction of photosynthetically active radiation (FPAR). LUEopt was then spatially interpolated over the domain using empirical models derived from independent geospatial data including global plant traits, surface soil moisture, terrain aspect, land cover type and percent tree cover. The derived LUEopt maps were then used as primary inputs to the MOD17 LUE algorithm for regional GPP estimation; these results were evaluated against tower observations and alternate MOD17 GPP estimates determined using Biome-specific LUEopt constants. Estimated LUEopt shows large spatial variability within and among different land cover classes indicated from a sparse North American tower network. Leaf nitrogen content and soil moisture are two important factors explaining LUEopt spatial variability. GPP estimated from spatially explicit LUEopt inputs shows significantly improved model accuracy against independent tower observations (R2 = 0.76; Mean RMSE plant trait information can explain spatial heterogeneity in LUEopt, leading to improved GPP estimates from satellite based LUE models.

Bathymetric Position Index (BPI) Zones derived from gridded bathymetry of Farallon de Medinilla (FDM), Commonwealth of the Northern Mariana (CNMI), USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is derived from gridded (5 m cell size) bathymetry and was created using the...

Menthor Editor: An Ontology-Driven Conceptual Modeling Platform

NARCIS (Netherlands)

Moreira, João Luiz; Sales, Tiago Prince; Guerson, John; Braga, Bernardo F.B; Brasileiro, Freddy; Sobral, Vinicius

2016-01-01

The lack of well-founded constructs in ontology tools can lead to the construction of non-intended models. In this demonstration we present the Menthor Editor, an ontology-driven conceptual modelling platform which incorporates the theories of the Unified Foundational Ontology (UFO). We illustrate

Quantitative system validation in model driven design

DEFF Research Database (Denmark)

Hermanns, Hilger; Larsen, Kim Guldstrand; Raskin, Jean-Francois

2010-01-01

The European STREP project Quasimodo1 develops theory, techniques and tool components for handling quantitative constraints in model-driven development of real-time embedded systems, covering in particular real-time, hybrid and stochastic aspects. This tutorial highlights the advances made, focus...

Data-Driven Robust RVFLNs Modeling of a Blast Furnace Iron-Making Process Using Cauchy Distribution Weighted M-Estimation

Energy Technology Data Exchange (ETDEWEB)

Zhou, Ping; Lv, Youbin; Wang, Hong; Chai, Tianyou

2017-09-01

Optimal operation of a practical blast furnace (BF) ironmaking process depends largely on a good measurement of molten iron quality (MIQ) indices. However, measuring the MIQ online is not feasible using the available techniques. In this paper, a novel data-driven robust modeling is proposed for online estimation of MIQ using improved random vector functional-link networks (RVFLNs). Since the output weights of traditional RVFLNs are obtained by the least squares approach, a robustness problem may occur when the training dataset is contaminated with outliers. This affects the modeling accuracy of RVFLNs. To solve this problem, a Cauchy distribution weighted M-estimation based robust RFVLNs is proposed. Since the weights of different outlier data are properly determined by the Cauchy distribution, their corresponding contribution on modeling can be properly distinguished. Thus robust and better modeling results can be achieved. Moreover, given that the BF is a complex nonlinear system with numerous coupling variables, the data-driven canonical correlation analysis is employed to identify the most influential components from multitudinous factors that affect the MIQ indices to reduce the model dimension. Finally, experiments using industrial data and comparative studies have demonstrated that the obtained model produces a better modeling and estimating accuracy and stronger robustness than other modeling methods.

Mathematical modeling of compression processes in air-driven boosters

International Nuclear Information System (INIS)

Li Zeyu; Zhao Yuanyang; Li Liansheng; Shu Pengcheng

2007-01-01

The compressed air in normal pressure is used as the source of power of the air-driven booster. The continuous working of air-driven boosters relies on the difference of surface area between driven piston and driving piston, i.e., the different forces acting on the pistons. When the working surface area of the driving piston for providing power is greater than that of the driven piston for compressing gas, the gas in compression chamber will be compressed. On the basis of the first law of thermodynamics, the motion regulation of piston is analyzed and the mathematical model of compression processes is set up. Giving a calculating example, the vary trends of gas pressure and pistons' move in working process of booster have been gotten. The change of parameters at different working conditions is also calculated and compared. And the corresponding results can be referred in the design of air-driven boosters

Towards a sufficiency-driven business model : Experiences and opportunities

NARCIS (Netherlands)

Bocken, N.M.P.; Short, SW

2016-01-01

Business model innovation is an important lever for change to tackle pressing sustainability issues. In this paper, ‘sufficiency’ is proposed as a driver of business model innovation for sustainability. Sufficiency-driven business models seek to moderate overall resource consumption by curbing

A Model-Driven Approach to e-Course Management

Science.gov (United States)

Savic, Goran; Segedinac, Milan; Milenkovic, Dušica; Hrin, Tamara; Segedinac, Mirjana

2018-01-01

This paper presents research on using a model-driven approach to the development and management of electronic courses. We propose a course management system which stores a course model represented as distinct machine-readable components containing domain knowledge of different course aspects. Based on this formally defined platform-independent…

From leaf longevity to canopy seasonality: a carbon optimality phenology model for tropical evergreen forests

Science.gov (United States)

Xu, X.; Medvigy, D.; Wu, J.; Wright, S. J.; Kitajima, K.; Pacala, S. W.

2016-12-01

forests might result from plant adaptation to optimize canopy carbon gain. Finally, this proposed trait-driven prognostic phenology model could potentially be incorporated into next generation TBMs to improve simulation of carbon and water fluxes in the tropics.

WE-EF-207-01: FEATURED PRESENTATION and BEST IN PHYSICS (IMAGING): Task-Driven Imaging for Cone-Beam CT in Interventional Guidance

Energy Technology Data Exchange (ETDEWEB)

Gang, G; Stayman, J; Ouadah, S; Siewerdsen, J [Johns Hopkins University, Baltimore, MD (United States); Ehtiati, T [Siemens Healthcare AX Division, Erlangen, DE (Germany)

2015-06-15

Purpose: This work introduces a task-driven imaging framework that utilizes a patient-specific anatomical model, mathematical definition of the imaging task, and a model of the imaging system to prospectively design acquisition and reconstruction techniques that maximize task-based imaging performance. Utility of the framework is demonstrated in the joint optimization of tube current modulation and view-dependent reconstruction kernel in filtered-backprojection reconstruction and non-circular orbit design in model-based reconstruction. Methods: The system model is based on a cascaded systems analysis of cone-beam CT capable of predicting the spatially varying noise and resolution characteristics as a function of the anatomical model and a wide range of imaging parameters. Detectability index for a non-prewhitening observer model is used as the objective function in a task-driven optimization. The combination of tube current and reconstruction kernel modulation profiles were identified through an alternating optimization algorithm where tube current was updated analytically followed by a gradient-based optimization of reconstruction kernel. The non-circular orbit is first parameterized as a linear combination of bases functions and the coefficients were then optimized using an evolutionary algorithm. The task-driven strategy was compared with conventional acquisitions without modulation, using automatic exposure control, and in a circular orbit. Results: The task-driven strategy outperformed conventional techniques in all tasks investigated, improving the detectability of a spherical lesion detection task by an average of 50% in the interior of a pelvis phantom. The non-circular orbit design successfully mitigated photon starvation effects arising from a dense embolization coil in a head phantom, improving the conspicuity of an intracranial hemorrhage proximal to the coil. Conclusion: The task-driven imaging framework leverages a knowledge of the imaging task within

WE-EF-207-01: FEATURED PRESENTATION and BEST IN PHYSICS (IMAGING): Task-Driven Imaging for Cone-Beam CT in Interventional Guidance

International Nuclear Information System (INIS)

Gang, G; Stayman, J; Ouadah, S; Siewerdsen, J; Ehtiati, T

2015-01-01

Purpose: This work introduces a task-driven imaging framework that utilizes a patient-specific anatomical model, mathematical definition of the imaging task, and a model of the imaging system to prospectively design acquisition and reconstruction techniques that maximize task-based imaging performance. Utility of the framework is demonstrated in the joint optimization of tube current modulation and view-dependent reconstruction kernel in filtered-backprojection reconstruction and non-circular orbit design in model-based reconstruction. Methods: The system model is based on a cascaded systems analysis of cone-beam CT capable of predicting the spatially varying noise and resolution characteristics as a function of the anatomical model and a wide range of imaging parameters. Detectability index for a non-prewhitening observer model is used as the objective function in a task-driven optimization. The combination of tube current and reconstruction kernel modulation profiles were identified through an alternating optimization algorithm where tube current was updated analytically followed by a gradient-based optimization of reconstruction kernel. The non-circular orbit is first parameterized as a linear combination of bases functions and the coefficients were then optimized using an evolutionary algorithm. The task-driven strategy was compared with conventional acquisitions without modulation, using automatic exposure control, and in a circular orbit. Results: The task-driven strategy outperformed conventional techniques in all tasks investigated, improving the detectability of a spherical lesion detection task by an average of 50% in the interior of a pelvis phantom. The non-circular orbit design successfully mitigated photon starvation effects arising from a dense embolization coil in a head phantom, improving the conspicuity of an intracranial hemorrhage proximal to the coil. Conclusion: The task-driven imaging framework leverages a knowledge of the imaging task within

Bathymetric Position Index (BPI) Zones 10 m grid derived from gridded bathymetry of Sarigan Island, Commonwealth of the Northern Mariana Islands, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (10 m cell size) multibeam bathymetry, collected aboard NOAA...

Bathymetric Position Index (BPI) Zones 10 m grid derived from gridded bathymetry of Maug Island, Commonwealth of the Northern Mariana Islands, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (10 m cell size) multibeam bathymetry, collected aboard NOAA...

Bathymetric Position Index (BPI) Zones 10 m grid derived from gridded bathymetry of Asuncion Island, Commonwealth of the Northern Mariana Islands, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (10 m cell size) multibeam bathymetry collected aboard NOAA...

Bathymetric Position Index (BPI) Zones 5 m grid derived from gridded bathymetry of Rota Island, Commonwealth of the Northern Mariana Islands, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry, collected aboard NOAA...

Bathymetric Position Index (BPI) Zones 10 m grid derived from gridded bathymetry of Agrihan Island, Commonwealth of the Northern Mariana Islands, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (10 m cell size) multibeam bathymetry, collected aboard NOAA...

Bathymetric Position Index (BPI) Structures 5 m grid derived from gridded bathymetry of Ofu and Olosega Islands, Territory of American Samoa, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry,...

Risk modelling in portfolio optimization

Science.gov (United States)

Lam, W. H.; Jaaman, Saiful Hafizah Hj.; Isa, Zaidi

2013-09-01

Risk management is very important in portfolio optimization. The mean-variance model has been used in portfolio optimization to minimize the investment risk. The objective of the mean-variance model is to minimize the portfolio risk and achieve the target rate of return. Variance is used as risk measure in the mean-variance model. The purpose of this study is to compare the portfolio composition as well as performance between the optimal portfolio of mean-variance model and equally weighted portfolio. Equally weighted portfolio means the proportions that are invested in each asset are equal. The results show that the portfolio composition of the mean-variance optimal portfolio and equally weighted portfolio are different. Besides that, the mean-variance optimal portfolio gives better performance because it gives higher performance ratio than the equally weighted portfolio.

Technoeconomic Optimization of Waste Heat Driven Forward Osmosis for Flue Gas Desulfurization Wastewater Treatment

Energy Technology Data Exchange (ETDEWEB)

Gingerich, Daniel B [Carnegie Mellon Univ., Pittsburgh, PA (United States); Bartholomew, Timothy V [Carnegie Mellon Univ., Pittsburgh, PA (United States); Mauter, Meagan S [Carnegie Mellon Univ., Pittsburgh, PA (United States)

2017-06-26

With the Environmental Protection Agency’s recent Effluent Limitation Guidelines for Steam Electric Generators, power plants are having to install and operate new wastewater technologies. Many plants are evaluating desalination technologies as possible compliance options. However, the desalination technologies under review that can reduce wastewater volume or treat to a zero-liquid discharges standard have a significant energy penalty to the plant. Waste heat, available from the exhaust gas or cooling water from coal-fired power plants, offers an opportunity to drive wastewater treatment using thermal desalination technologies. One such technology is forward osmosis (FO). Forward osmosis utilizes an osmotic pressure gradient to passively pull water from a saline or wastewater stream across a semi-permeable membrane and into a more concentrated draw solution. This diluted draw solution is then fed into a distillation column, where the addition of low temperature waste heat can drive the separation to produce a reconcentrated draw solution and treated water for internal plant reuse. The use of low-temperature waste heat decouples water treatment from electricity production and eliminates the link between reducing water pollution and increasing air emissions from auxiliary electricity generation. In order to evaluate the feasibility of waste heat driven FO, we first build a model of an FO system for flue gas desulfurization (FGD) wastewater treatment at coal-fired power plants. This model includes the FO membrane module, the distillation column for draw solution recovery, and waste heat recovery from the exhaust gas. We then add a costing model to account for capital and operating costs of the forward osmosis system. We use this techno-economic model to optimize waste heat driven FO for the treatment of FGD wastewater. We apply this model to three case studies: the National Energy Technology Laboratory (NETL) 550 MW model coal fired power plant without carbon

Data and Dynamics Driven Approaches for Modelling and Forecasting the Red Sea Chlorophyll

KAUST Repository

Dreano, Denis

2017-01-01

concentration and have practical applications for fisheries operation and harmful algae blooms monitoring. Modelling approaches can be divided between physics- driven (dynamical) approaches, and data-driven (statistical) approaches. Dynamical models are based

Bathymetric Position Index (BPI) Zones 5 m grid derived from gridded bathymetry of Ofu and Olosega Islands, Territory of American Samoa, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry, collected aboard R/V...

Model-Driven Development of Safety Architectures

Science.gov (United States)

Denney, Ewen; Pai, Ganesh; Whiteside, Iain

2017-01-01

We describe the use of model-driven development for safety assurance of a pioneering NASA flight operation involving a fleet of small unmanned aircraft systems (sUAS) flying beyond visual line of sight. The central idea is to develop a safety architecture that provides the basis for risk assessment and visualization within a safety case, the formal justification of acceptable safety required by the aviation regulatory authority. A safety architecture is composed from a collection of bow tie diagrams (BTDs), a practical approach to manage safety risk by linking the identified hazards to the appropriate mitigation measures. The safety justification for a given unmanned aircraft system (UAS) operation can have many related BTDs. In practice, however, each BTD is independently developed, which poses challenges with respect to incremental development, maintaining consistency across different safety artifacts when changes occur, and in extracting and presenting stakeholder specific information relevant for decision making. We show how a safety architecture reconciles the various BTDs of a system, and, collectively, provide an overarching picture of system safety, by considering them as views of a unified model. We also show how it enables model-driven development of BTDs, replete with validations, transformations, and a range of views. Our approach, which we have implemented in our toolset, AdvoCATE, is illustrated with a running example drawn from a real UAS safety case. The models and some of the innovations described here were instrumental in successfully obtaining regulatory flight approval.

Data-Driven Model Order Reduction for Bayesian Inverse Problems

KAUST Repository

Cui, Tiangang; Youssef, Marzouk; Willcox, Karen

2014-01-01

One of the major challenges in using MCMC for the solution of inverse problems is the repeated evaluation of computationally expensive numerical models. We develop a data-driven projection- based model order reduction technique to reduce

Data-Driven Model Uncertainty Estimation in Hydrologic Data Assimilation

Science.gov (United States)

Pathiraja, S.; Moradkhani, H.; Marshall, L.; Sharma, A.; Geenens, G.

2018-02-01

The increasing availability of earth observations necessitates mathematical methods to optimally combine such data with hydrologic models. Several algorithms exist for such purposes, under the umbrella of data assimilation (DA). However, DA methods are often applied in a suboptimal fashion for complex real-world problems, due largely to several practical implementation issues. One such issue is error characterization, which is known to be critical for a successful assimilation. Mischaracterized errors lead to suboptimal forecasts, and in the worst case, to degraded estimates even compared to the no assimilation case. Model uncertainty characterization has received little attention relative to other aspects of DA science. Traditional methods rely on subjective, ad hoc tuning factors or parametric distribution assumptions that may not always be applicable. We propose a novel data-driven approach (named SDMU) to model uncertainty characterization for DA studies where (1) the system states are partially observed and (2) minimal prior knowledge of the model error processes is available, except that the errors display state dependence. It includes an approach for estimating the uncertainty in hidden model states, with the end goal of improving predictions of observed variables. The SDMU is therefore suited to DA studies where the observed variables are of primary interest. Its efficacy is demonstrated through a synthetic case study with low-dimensional chaotic dynamics and a real hydrologic experiment for one-day-ahead streamflow forecasting. In both experiments, the proposed method leads to substantial improvements in the hidden states and observed system outputs over a standard method involving perturbation with Gaussian noise.

Multibeam bathymetry and CTD measurements in two fjord systems in southeastern Greenland

DEFF Research Database (Denmark)

Kjeldsen, Kristian Kjellerup; Weinrebe, Reimer Wilhelm; Bendtsen, Jørgen

2017-01-01

We present bathymetry and hydrological observations collected in the summer of 2014 from two fjordsystems in southeastern Greenland with a multibeam sonar system. Our results provide a detailed bathymetricmap of the fjord complex around the island of Skjoldungen in Skjoldungen Fjord and the outer...

Slope grid derived from gridded bathymetry of Apra Harbor, Guam U.S. Territory

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Slope is derived from gridded (1 m cell size) multibeam bathymetry, collected aboard the Survey Vessel Swamp Fox. Cell values reflect the maximum rate of change (in...

CRED 5m Gridded multibeam bathymetry of Guam Island, Guam U.S. Territory

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry shelf, bank and slope environments of Guam Island, Guam U.S. Territory. Bottom coverage was achieved in depths between 0 and -3532 meters but this...

Gridded multibeam bathymetry of Rota Island, Commonwealth of the Northern Mariana Islands (CNMI)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry shelf, bank and slope environments of Rota Island, CNMI. Bottom coverage was achieved in depths between 0 and -1905 meters. The netCDF and Arc...

Discrete Event Modeling and Simulation-Driven Engineering for the ATLAS Data Acquisition Network

CERN Document Server

Bonaventura, Matias Alejandro; The ATLAS collaboration; Castro, Rodrigo Daniel

2016-01-01

We present an iterative and incremental development methodology for simulation models in network engineering projects. Driven by the DEVS (Discrete Event Systems Specification) formal framework for modeling and simulation we assist network design, test, analysis and optimization processes. A practical application of the methodology is presented for a case study in the ATLAS particle physics detector, the largest scientific experiment built by man where scientists around the globe search for answers about the origins of the universe. The ATLAS data network convey real-time information produced by physics detectors as beams of particles collide. The produced sub-atomic evidences must be filtered and recorded for further offline scrutiny. Due to the criticality of the transported data, networks and applications undergo careful engineering processes with stringent quality of service requirements. A tight project schedule imposes time pressure on design decisions, while rapid technology evolution widens the palett...

Model-driven software migration a methodology

CERN Document Server

Wagner, Christian

2014-01-01

Today, reliable software systems are the basis of any business or company. The continuous further development of those systems is the central component in software evolution. It requires a huge amount of time- man power- as well as financial resources. The challenges are size, seniority and heterogeneity of those software systems. Christian Wagner addresses software evolution: the inherent problems and uncertainties in the process. He presents a model-driven method which leads to a synchronization between source code and design. As a result the model layer will be the central part in further e

Slope 20 m grid derived from gridded bathymetry of Brooks Banks, Hawaii, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Slope is derived from gridded (20 m cell size) multibeam bathymetry, collected aboard NOAA ship Hi'ialakai and R/V AHI. Cell values reflect the maximum rate of...

Rugosity grid derived from gridded bathymetry of Pearl and Hermes Atoll, Hawaii, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (5 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hiialaka'i and R/V AHI, and IKONOS derived depths using the Benthic...

Digital Elevation Model Correction for the thalweg values of Obion River system, TN

Science.gov (United States)

Dullo, T. T.; Bhuyian, M. N. M.; Hawkins, S. A.; Kalyanapu, A. J.

2016-12-01

Obion River system is located in North-West Tennessee and discharges into the Mississippi River. To facilitate US Department of Agriculture (USDA) to estimate water availability for agricultural consumption a one-dimensional HEC-RAS model has been proposed. The model incorporates the major tributaries (north and south), main stem of Obion River along with a segment of the Mississippi River. A one-meter spatial resolution Light Detection and Ranging (LiDAR) derived Digital Elevation Model (DEM) was used as the primary source of topographic data. LiDAR provides fine-resolution terrain data over given extent. However, it lacks in accurate representation of river bathymetry due to limited penetration beyond a certain water depth. This reduces the conveyance along river channel as represented by the DEM and affects the hydrodynamic modeling performance. This research focused on proposing a method to overcome this issue and test the qualitative improvement by the proposed method over an existing technique. Therefore, objective of this research is to compare effectiveness of a HEC-RAS based bathymetry optimization method with an existing hydraulic based DEM correction technique (Bhuyian et al., 2014) for Obion River system in Tennessee. Accuracy of hydrodynamic simulations (upon employing bathymetry from respective sources) would be regarded as the indicator of performance. The aforementioned river system includes nine major reaches with a total river length of 310 km. The bathymetry of the river was represented via 315 cross sections equally spaced at about one km. This study targeted to selecting best practice for treating LiDAR based terrain data over complex river system at a sub-watershed scale.

Model Driven Integrated Decision-Making in Manufacturing Enterprises

Directory of Open Access Journals (Sweden)

Richard H. Weston

2012-01-01

Full Text Available Decision making requirements and solutions are observed in four world class Manufacturing Enterprises (MEs. Observations made focus on deployed methods of complexity handling that facilitate multi-purpose, distributed decision making. Also observed are examples of partially deficient “integrated decision making” which stem from lack of understanding about how ME structural relations enable and/or constrain reachable ME behaviours. To begin to address this deficiency the paper outlines the use of a “reference model of ME decision making” which can inform the structural design of decision making systems in MEs. Also outlined is a “systematic model driven approach to modelling ME systems” which can particularise the reference model in specific case enterprises and thereby can “underpin integrated ME decision making”. Coherent decomposition and representational mechanisms have been incorporated into the model driven approach to systemise complexity handling. The paper also describes in outline an application of the modelling method in a case study ME and explains how its use has improved the integration of previously distinct planning functions. The modelling approach is particularly innovative in respect to the way it structures the coherent creation and experimental re-use of “fit for purpose” discrete event (predictive simulation models at the multiple levels of abstraction.

A Data-Driven Method for Selecting Optimal Models Based on Graphical Visualisation of Differences in Sequentially Fitted ROC Model Parameters

Directory of Open Access Journals (Sweden)

K S Mwitondi

2013-05-01

Full Text Available Differences in modelling techniques and model performance assessments typically impinge on the quality of knowledge extraction from data. We propose an algorithm for determining optimal patterns in data by separately training and testing three decision tree models in the Pima Indians Diabetes and the Bupa Liver Disorders datasets. Model performance is assessed using ROC curves and the Youden Index. Moving differences between sequential fitted parameters are then extracted, and their respective probability density estimations are used to track their variability using an iterative graphical data visualisation technique developed for this purpose. Our results show that the proposed strategy separates the groups more robustly than the plain ROC/Youden approach, eliminates obscurity, and minimizes over-fitting. Further, the algorithm can easily be understood by non-specialists and demonstrates multi-disciplinary compliance.

Anomalous Structure of Oceanic Lithosphere in the North Atlantic and Arctic Oceans: A Preliminary Analysis Based on Bathymetry, Gravity and Crustal Structure

Science.gov (United States)

Barantsrva, O.

2014-12-01

We present a preliminary analysis of the crustal and upper mantle structure for off-shore regions in the North Atlantic and Arctic oceans. These regions have anomalous oceanic lithosphere: the upper mantle of the North Atlantic ocean is affected by the Iceland plume, while the Arctic ocean has some of the slowest spreading rates. Our specific goal is to constrain the density structure of the upper mantle in order to understand the links between the deep lithosphere dynamics, ocean spreading, ocean floor bathymetry, heat flow and structure of the oceanic lithosphere in the regions where classical models of evolution of the oceanic lithosphere may not be valid. The major focus is on the oceanic lithosphere, but the Arctic shelves with a sufficient data coverage are also included into the analysis. Out major interest is the density structure of the upper mantle, and the analysis is based on the interpretation of GOCE satellite gravity data. To separate gravity anomalies caused by subcrustal anomalous masses, the gravitational effect of water, crust and the deep mantle is removed from the observed gravity field. For bathymetry we use the global NOAA database ETOPO1. The crustal correction to gravity is based on two crustal models: (1) global model CRUST1.0 (Laske, 2013) and, for a comparison, (2) a regional seismic model EUNAseis (Artemieva and Thybo, 2013). The crustal density structure required for the crustal correction is constrained from Vp data. Previous studies have shown that a large range of density values corresponds to any Vp value. To overcome this problem and to reduce uncertainty associated with the velocity-density conversion, we account for regional tectonic variations in the Northern Atlantics as constrained by numerous published seismic profiles and potential-field models across the Norwegian off-shore crust (e.g. Breivik et al., 2005, 2007), and apply different Vp-density conversions for different parts of the region. We present preliminary results

Editorial - Special Issue on Model-driven Service-oriented architectures

NARCIS (Netherlands)

Andrade Almeida, João; Ferreira Pires, Luis; van Sinderen, Marten J.; Steen, M.W.A.

2009-01-01

Model-driven approaches to software development have proliferated in recent years owing to the availability of techniques based on metamodelling and model transformations, such as the meta-object facility (MOF) and the query view transformation (QVT) standards. During the same period,

Beginning SQL Server Modeling Model-driven Application Development in SQL Server

CERN Document Server

Weller, Bart

2010-01-01

Get ready for model-driven application development with SQL Server Modeling! This book covers Microsoft's SQL Server Modeling (formerly known under the code name "Oslo") in detail and contains the information you need to be successful with designing and implementing workflow modeling. Beginning SQL Server Modeling will help you gain a comprehensive understanding of how to apply DSLs and other modeling components in the development of SQL Server implementations. Most importantly, after reading the book and working through the examples, you will have considerable experience using SQL M

The NTeQ ISD Model: A Tech-Driven Model for Digital Natives (DNs)

Science.gov (United States)

Williams, C.; Anekwe, J. U.

2017-01-01

Integrating Technology for enquiry (NTeQ) instructional development model (ISD), is believed to be a technology-driven model. The authors x-rayed the ten-step model to reaffirm the ICT knowledge demand of the learner and the educator; hence computer-based activities at various stages of the model are core elements. The model also is conscious of…

Reflection of a Year Long Model-Driven Business and UI Modeling Development Project

Science.gov (United States)

Sukaviriya, Noi; Mani, Senthil; Sinha, Vibha

Model-driven software development enables users to specify an application at a high level - a level that better matches problem domain. It also promises the users with better analysis and automation. Our work embarks on two collaborating domains - business process and human interactions - to build an application. Business modeling expresses business operations and flows then creates business flow implementation. Human interaction modeling expresses a UI design, its relationship with business data, logic, and flow, and can generate working UI. This double modeling approach automates the production of a working system with UI and business logic connected. This paper discusses the human aspects of this modeling approach after a year long of building a procurement outsourcing contract application using the approach - the result of which was deployed in December 2008. The paper discusses in multiple areas the happy endings and some heartache. We end with insights on how a model-driven approach could do better for humans in the process.

Bathymetric Position Index (BPI) Structures 10 m grid derived from gridded bathymetry of Supply Reef, Commonwealth of the Northern Mariana Islands (CNMI), USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (10 m cell size) multibeam bathymetry,...

Bathymetric Position Index (BPI) Structures 10 m grid derived from gridded bathymetry of Maug Island, Commonwealth of the Northern Mariana Islands (CNMI), USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (10 m cell size) multibeam bathymetry,...

Bathymetric Position Index (BPI) Structures 10 m grid derived from gridded bathymetry of Alamagan Island, Commonwealth of the Northern Mariana Islands (CNMI), USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (10 m cell size) multibeam bathymetry,...

Bathymetric Position Index (BPI) Structures 5 m grid derived from gridded bathymetry of Rota Island, Commonwealth of the Northern Mariana Islands (CNMI), USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry,...

Bathymetric Position Index (BPI) Structures 10 m grid derived from gridded bathymetry of Guguan Island, Commonwealth of the Northern Mariana Islands (CNMI), USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (10 m cell size) multibeam bathymetry,...

Bathymetric Position Index (BPI) Structures 10 m grid derived from gridded bathymetry of Pagan Island, Commonwealth of the Northern Mariana Islands (CNMI), USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (10 m cell size) multibeam bathymetry,...

Bathymetric Position Index (BPI) Structures 10 m grid derived from gridded bathymetry of Asuncion Island, Commonwealth of the Northern Mariana Islands (CNMI), USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — BPI Structures are derived from two scales of a focal mean analysis on bathymetry and slope. The grid is based on gridded (10 m cell size) multibeam bathymetry...

A PSO Driven Intelligent Model Updating and Parameter Identification Scheme for Cable-Damper System

Directory of Open Access Journals (Sweden)

Danhui Dan

2015-01-01

Full Text Available The precise measurement of the cable force is very important for monitoring and evaluating the operation status of cable structures such as cable-stayed bridges. The cable system should be installed with lateral dampers to reduce the vibration, which affects the precise measurement of the cable force and other cable parameters. This paper suggests a cable model updating calculation scheme driven by the particle swarm optimization (PSO algorithm. By establishing a finite element model considering the static geometric nonlinearity and stress-stiffening effect firstly, an automatically finite element method model updating powered by PSO algorithm is proposed, with the aims to identify the cable force and relevant parameters of cable-damper system precisely. Both numerical case studies and full-scale cable tests indicated that, after two rounds of updating process, the algorithm can accurately identify the cable force, moment of inertia, and damping coefficient of the cable-damper system.

Subthreshold SPICE Model Optimization

Science.gov (United States)

Lum, Gregory; Au, Henry; Neff, Joseph; Bozeman, Eric; Kamin, Nick; Shimabukuro, Randy

2011-04-01

The first step in integrated circuit design is the simulation of said design in software to verify proper functionally and design requirements. Properties of the process are provided by fabrication foundries in the form of SPICE models. These SPICE models contain the electrical data and physical properties of the basic circuit elements. A limitation of these models is that the data collected by the foundry only accurately model the saturation region. This is fine for most users, but when operating devices in the subthreshold region they are inadequate for accurate simulation results. This is why optimizing the current SPICE models to characterize the subthreshold region is so important. In order to accurately simulate this region of operation, MOSFETs of varying widths and lengths are fabricated and the electrical test data is collected. From the data collected the parameters of the model files are optimized through parameter extraction rather than curve fitting. With the completed optimized models the circuit designer is able to simulate circuit designs for the sub threshold region accurately.

Quality management using model-driven engineering: an overview

OpenAIRE

Ruiz-Rube, Iván; Escalona, María José

2014-01-01

Quality Management (QM) is one of the critical points of any software development process. In recent years, several proposals have emerged on this issue, mainly with regard to maturity models, quality standards and best practices collections. Besides, Model Driven Engineering (MDE) aims to build software systems through the construction and transformation of models. However, MDE might be used for other different tasks. In this poster, we summarize the main contributions abou...

Network-driven design principles for neuromorphic systems

OpenAIRE

Partzsch, Johannes; Sch?ffny, Rene

2015-01-01

Synaptic connectivity is typically the most resource-demanding part of neuromorphic systems. Commonly, the architecture of these systems is chosen mainly on technical considerations. As a consequence, the potential for optimization arising from the inherent constraints of connectivity models is left unused. In this article, we develop an alternative, network-driven approach to neuromorphic architecture design. We describe methods to analyse performance of existing neuromorphic architectures i...

Model-driven dependability assessment of software systems

CERN Document Server

Bernardi, Simona; Petriu, Dorina C

2013-01-01

In this book, the authors present cutting-edge model-driven techniques for modeling and analysis of software dependability. Most of them are based on the use of UML as software specification language. From the software system specification point of view, such techniques exploit the standard extension mechanisms of UML (i.e., UML profiling). UML profiles enable software engineers to add non-functional properties to the software model, in addition to the functional ones. The authors detail the state of the art on UML profile proposals for dependability specification and rigorously describe the t

The effectiveness and efficiency of model driven game design

NARCIS (Netherlands)

Dormans, Joris

2012-01-01

In order for techniques from Model Driven Engineering to be accepted at large by the game industry, it is critical that the effectiveness and efficiency of these techniques are proven for game development. There is no lack of game design models, but there is no model that has surfaced as an industry

Construction of UML class diagram with Model-Driven Development

Directory of Open Access Journals (Sweden)

Tomasz Górski

2016-03-01

Full Text Available Model transformations play a key role in software development projects based on Model--Driven Development (MDD principles. Transformations allow for automation of repetitive and well-defined steps, thus shortening design time and reducing a number of errors. In the object-oriented approach, the key elements are use cases. They are described, modelled and later designed until executable application code is obtained. The aim of the paper is to present transformation of a model-to-model type, Communication-2-Class, which automates construction of Unified Modelling Language (UML class diagram in the context of the analysis/design model. An UML class diagram is created based on UML communication diagram within use case realization. As a result, a class diagram shows all of the classes involved in the use case realization and the relationships among them. The plug-in which implements Communication-2-Class transformation was implemented in the IBM Rational Software Architect. The article presents the tests results of developed plug-in, which realizes Communication-2-Class transformation, showing capabilities of shortening use case realization’s design time.[b]Keywords[/b]: Model-Driven Development, transformations, Unified Modelling Language, analysis/design model, UML class diagram, UML communication diagram

Modeling of laser-driven hydrodynamics experiments

Science.gov (United States)

di Stefano, Carlos; Doss, Forrest; Rasmus, Alex; Flippo, Kirk; Desjardins, Tiffany; Merritt, Elizabeth; Kline, John; Hager, Jon; Bradley, Paul

2017-10-01

Correct interpretation of hydrodynamics experiments driven by a laser-produced shock depends strongly on an understanding of the time-dependent effect of the irradiation conditions on the flow. In this talk, we discuss the modeling of such experiments using the RAGE radiation-hydrodynamics code. The focus is an instability experiment consisting of a period of relatively-steady shock conditions in which the Richtmyer-Meshkov process dominates, followed by a period of decaying flow conditions, in which the dominant growth process changes to Rayleigh-Taylor instability. The use of a laser model is essential for capturing the transition. also University of Michigan.

Optimized Flow Sheet for a Reference Commercial-Scale Nuclear-Driven High-Temperature Electrolysis Hydrogen Production Plant

International Nuclear Information System (INIS)

M. G. McKellar; J. E. O'Brien; E. A. Harvego; J. S. Herring

2007-01-01

This report presents results from the development and optimization of a reference commercial scale high-temperature electrolysis (HTE) plant for hydrogen production. The reference plant design is driven by a high-temperature helium-cooled reactor coupled to a direct Brayton power cycle. The reference design reactor power is 600 MWt, with a primary system pressure of 7.0 MPa, and reactor inlet and outlet fluid temperatures of 540 C and 900 C, respectively. The electrolysis unit used to produce hydrogen consists of 4.176 - 10 6 cells with a per-cell active area of 225 cm2. A nominal cell area-specific resistance, ASR, value of 0.4 Ohm-cm2 with a current density of 0.25 A/cm2 was used, and isothermal boundary conditions were assumed. The optimized design for the reference hydrogen production plant operates at a system pressure of 5.0 MPa, and utilizes an air-sweep system to remove the excess oxygen that is evolved on the anode side of the electrolyzer. The inlet air for the air-sweep system is compressed to the system operating pressure of 5.0 MPa in a four-stage compressor with intercooling. The overall system thermal-to-hydrogen production efficiency (based on the low heating value of the produced hydrogen) is 49.07% at a hydrogen production rate of 2.45 kg/s with the high-temperature helium-cooled reactor concept. The information presented in this report is intended to establish an optimized design for the reference nuclear-driven HTE hydrogen production plant so that parameters can be compared with other hydrogen production methods and power cycles to evaluate relative performance characteristics and plant economics

Model-Driven Policy Framework for Data Centers

DEFF Research Database (Denmark)

Caba, Cosmin Marius; Kentis, Angelos Mimidis; Soler, José

2016-01-01

. Moreover, the lack of simple solutions for managing the configuration and behavior of the DC components makes the DC hard to configure and slow in adapting to changes in business needs. In this paper, we propose a model-driven framework for policy-based management for DCs, to simplify not only the service...

Evaluating the potential for near-shore bathymetry on the Majuro Atoll, Republic of the Marshall Islands, using Landsat 8 and WorldView-3 imagery

Science.gov (United States)

Poppenga, Sandra K.; Palaseanu-Lovejoy, Monica; Gesch, Dean B.; Danielson, Jeffrey J.; Tyler, Dean J.

2018-04-16

Satellite-derived near-shore bathymetry (SDB) is becoming an increasingly important method for assessing vulnerability to climate change and natural hazards in low-lying atolls of the northern tropical Pacific Ocean. Satellite imagery has become a cost-effective means for mapping near-shore bathymetry because ships cannot collect soundings safely while operating close to the shore. Also, green laser light detection and ranging (lidar) acquisitions are expensive in remote locations. Previous research has demonstrated that spectral band ratio-based techniques, commonly called the natural logarithm approach, may lead to more precise measurements and modeling of bathymetry because of the phenomenon that different substrates at the same depth have approximately equal ratio values. The goal of this research was to apply the band ratio technique to Landsat 8 at-sensor radiance imagery and WorldView-3 atmospherically corrected imagery in the coastal waters surrounding the Majuro Atoll, Republic of the Marshall Islands, to derive near-shore bathymetry that could be incorporated into a seamless topobathymetric digital elevation model of Majuro. Attenuation of light within the water column was characterized by measuring at-sensor radiance and reflectance at different depths and calculating an attenuation coefficient. Bathymetric lidar data, collected by the U.S. Naval Oceanographic Office in 2006, were used to calibrate the SDB results. The bathymetric lidar yielded a strong linear relation with water depths. The Landsat 8-derived SDB estimates derived from the blue/green band ratio exhibited a water attenuation extinction depth of 6 meters with a coefficient of determination R2=0.9324. Estimates derived from the coastal/red band ratio had an R2=0.9597. At the same extinction depth, SDB estimates derived from WorldView-3 imagery exhibited an R2=0.9574. Because highly dynamic coastal shorelines can be affected by erosion, wetland loss, hurricanes, sea-level rise, urban

Shallow water bathymetry mapping using Support Vector Machine (SVM) technique and multispectral imagery

NARCIS (Netherlands)

Misra, Ankita; Vojinovic, Zoran; Ramakrishnan, Balaji; Luijendijk, Arjen; Ranasinghe, Roshanka

2018-01-01

Satellite imagery along with image processing techniques prove to be efficient tools for bathymetry retrieval as they provide time and cost-effective alternatives to traditional methods of water depth estimation. In this article, a nonlinear machine learning technique of Support Vector Machine (SVM)

Tag-Driven Online Novel Recommendation with Collaborative Item Modeling

Directory of Open Access Journals (Sweden)

Fenghuan Li

2018-04-01

Full Text Available Online novel recommendation recommends attractive novels according to the preferences and characteristics of users or novels and is increasingly touted as an indispensable service of many online stores and websites. The interests of the majority of users remain stable over a certain period. However, there are broad categories in the initial recommendation list achieved by collaborative filtering (CF. That is to say, it is very possible that there are many inappropriately recommended novels. Meanwhile, most algorithms assume that users can provide an explicit preference. However, this assumption does not always hold, especially in online novel reading. To solve these issues, a tag-driven algorithm with collaborative item modeling (TDCIM is proposed for online novel recommendation. Online novel reading is different from traditional book marketing and lacks preference rating. In addition, collaborative filtering frequently suffers from the Matthew effect, leading to ignored personalized recommendations and serious long tail problems. Therefore, item-based CF is improved by latent preference rating with a punishment mechanism based on novel popularity. Consequently, a tag-driven algorithm is constructed by means of collaborative item modeling and tag extension. Experimental results show that online novel recommendation is improved greatly by a tag-driven algorithm with collaborative item modeling.

Topology optimization of Channel flow problems

DEFF Research Database (Denmark)

Gersborg-Hansen, Allan; Sigmund, Ole; Haber, R. B.

2005-01-01

function which measures either some local aspect of the velocity field or a global quantity, such as the rate of energy dissipation. We use the finite element method to model the flow, and we solve the optimization problem with a gradient-based math-programming algorithm that is driven by analytical......This paper describes a topology design method for simple two-dimensional flow problems. We consider steady, incompressible laminar viscous flows at low to moderate Reynolds numbers. This makes the flow problem non-linear and hence a non-trivial extension of the work of [Borrvall&Petersson 2002......]. Further, the inclusion of inertia effects significantly alters the physics, enabling solutions of new classes of optimization problems, such as velocity--driven switches, that are not addressed by the earlier method. Specifically, we determine optimal layouts of channel flows that extremize a cost...

Multivariate modeling of complications with data driven variable selection: Guarding against overfitting and effects of data set size

International Nuclear Information System (INIS)

Schaaf, Arjen van der; Xu Chengjian; Luijk, Peter van; Veld, Aart A. van’t; Langendijk, Johannes A.; Schilstra, Cornelis

2012-01-01

Purpose: Multivariate modeling of complications after radiotherapy is frequently used in conjunction with data driven variable selection. This study quantifies the risk of overfitting in a data driven modeling method using bootstrapping for data with typical clinical characteristics, and estimates the minimum amount of data needed to obtain models with relatively high predictive power. Materials and methods: To facilitate repeated modeling and cross-validation with independent datasets for the assessment of true predictive power, a method was developed to generate simulated data with statistical properties similar to real clinical data sets. Characteristics of three clinical data sets from radiotherapy treatment of head and neck cancer patients were used to simulate data with set sizes between 50 and 1000 patients. A logistic regression method using bootstrapping and forward variable selection was used for complication modeling, resulting for each simulated data set in a selected number of variables and an estimated predictive power. The true optimal number of variables and true predictive power were calculated using cross-validation with very large independent data sets. Results: For all simulated data set sizes the number of variables selected by the bootstrapping method was on average close to the true optimal number of variables, but showed considerable spread. Bootstrapping is more accurate in selecting the optimal number of variables than the AIC and BIC alternatives, but this did not translate into a significant difference of the true predictive power. The true predictive power asymptotically converged toward a maximum predictive power for large data sets, and the estimated predictive power converged toward the true predictive power. More than half of the potential predictive power is gained after approximately 200 samples. Our simulations demonstrated severe overfitting (a predicative power lower than that of predicting 50% probability) in a number of small

Data-Driven Model Order Reduction for Bayesian Inverse Problems

KAUST Repository

Cui, Tiangang

2014-01-06

One of the major challenges in using MCMC for the solution of inverse problems is the repeated evaluation of computationally expensive numerical models. We develop a data-driven projection- based model order reduction technique to reduce the computational cost of numerical PDE evaluations in this context.

Modeling the Thermosphere as a Driven-Dissipative Thermodynamic System

Science.gov (United States)

2013-03-01

8 Figure 2: Illustration of the geocentric solar magnetospheric coordinate system............15 Figure 3: Diagram of the...to test new methods of modeling the thermospheric environment. Thermosphere as a Driven-Dissipative Thermodynamic System One approach for modeling... approach uses empirical coupling and relaxation constants to model the 4 input of energy to the thermosphere from the solar wind during

Minimization of distribution system losses by exploiting storage and anticipating market-driven behaviour of wind power producers

NARCIS (Netherlands)

Farrokhseresht, M.; Paterakis, N.G.; Gibescu, M.; Slootweg, J.G.

2017-01-01

This paper presents a stochastic bi-level optimization model to determine the optimal dispatch of energy storage systems controlled directly by the distribution system operator (DSO) in order to achieve minimization of active power losses, taking into account the profit-driven participation of

Towards a multi-stakeholder-driven model for excellence in higher ...

African Journals Online (AJOL)

The model is further based on significant NQF and OBE alignment of all learning ... form the foundation of this strategic-driven model for curriculum development. ... of quality planning, quality management system implementation and quality

Intensification of abamectin pesticide degradation using the combination of ultrasonic cavitation and visible-light driven photocatalytic process: Synergistic effect and optimization study.

Science.gov (United States)

Mosleh, Soleiman; Rahimi, Mahmood Reza

2017-03-01

Degradation of abamectin pesticide was carried out using visible light driven Cu 2 (OH)PO 4 -HKUST-1 MOF photocatalyst through the sonophotocatalytic technique. Cu 2 (OH)PO 4 -HKUST-1 MOF as a visible-light driven photocatalyst, was synthesized and characterized by XRD, SEM, EDS and DRS. The direct bang gaps of HKUST-1 MOF and Cu 2 (OH)PO 4 -HKUST-1 MOF were estimated about 2.63 and 2.59eV, respectively, which reveals that these photocatalysts can be activated under blue light illumination. All sonophotodegradation experiments were performed using a continuous flow-loop reactor. The central composite design (CCD) methodology was applied for modeling, optimization and investigation of influence of operational parameters, i.e. irradiation time, pH, solution flow rate, oxygen flow rate, initial concentration and photocatalyst dosage on the sonophotocatalytic degradation of abamectin. The maximum degradation efficiency of 99.93% was found at optimal values as 20min, 4, 90mL/min, 0.2mL/min, 30mg/L and 0.4g/L, for irradiation time, pH, solution flow rate, oxygen flow rate, initial concentration and photocatalyst dosage, respectively. Evaluation of the synergism in the combination of ultrasonic and photocatalysis lead to a synergistic index of 2.19, which reveals that coupling of ultrasonic and photocatalysis has a greater efficiency than the sum of individual procedures for degradation of abamectin. Copyright © 2016 Elsevier B.V. All rights reserved.

Data to Decisions: Creating a Culture of Model-Driven Drug Discovery.

Science.gov (United States)

Brown, Frank K; Kopti, Farida; Chang, Charlie Zhenyu; Johnson, Scott A; Glick, Meir; Waller, Chris L

2017-09-01

Merck & Co., Inc., Kenilworth, NJ, USA, is undergoing a transformation in the way that it prosecutes R&D programs. Through the adoption of a "model-driven" culture, enhanced R&D productivity is anticipated, both in the form of decreased attrition at each stage of the process and by providing a rational framework for understanding and learning from the data generated along the way. This new approach focuses on the concept of a "Design Cycle" that makes use of all the data possible, internally and externally, to drive decision-making. These data can take the form of bioactivity, 3D structures, genomics, pathway, PK/PD, safety data, etc. Synthesis of high-quality data into models utilizing both well-established and cutting-edge methods has been shown to yield high confidence predictions to prioritize decision-making and efficiently reposition resources within R&D. The goal is to design an adaptive research operating plan that uses both modeled data and experiments, rather than just testing, to drive project decision-making. To support this emerging culture, an ambitious information management (IT) program has been initiated to implement a harmonized platform to facilitate the construction of cross-domain workflows to enable data-driven decision-making and the construction and validation of predictive models. These goals are achieved through depositing model-ready data, agile persona-driven access to data, a unified cross-domain predictive model lifecycle management platform, and support for flexible scientist-developed workflows that simplify data manipulation and consume model services. The end-to-end nature of the platform, in turn, not only supports but also drives the culture change by enabling scientists to apply predictive sciences throughout their work and over the lifetime of a project. This shift in mindset for both scientists and IT was driven by an early impactful demonstration of the potential benefits of the platform, in which expert-level early discovery

LHC-GCS a model-driven approach for automatic PLC and SCADA code generation

CERN Document Server

Thomas, Geraldine; Barillère, Renaud; Cabaret, Sebastien; Kulman, Nikolay; Pons, Xavier; Rochez, Jacques

2005-01-01

The LHC experiments’ Gas Control System (LHC GCS) project [1] aims to provide the four LHC experiments (ALICE, ATLAS, CMS and LHCb) with control for their 23 gas systems. To ease the production and maintenance of 23 control systems, a model-driven approach has been adopted to generate automatically the code for the Programmable Logic Controllers (PLCs) and for the Supervision Control And Data Acquisition (SCADA) systems. The first milestones of the project have been achieved. The LHC GCS framework [4] and the generation tools have been produced. A first control application has actually been generated and is in production, and a second is in preparation. This paper describes the principle and the architecture of the model-driven solution. It will in particular detail how the model-driven solution fits with the LHC GCS framework and with the UNICOS [5] data-driven tools.

Slope 60 m grid derived from gridded bathymetry of Guam Island, Mariana Islands, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Slope is derived from gridded (60 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hiialaka'i and R/V AHI. Cell values reflect the maximum rate of...

Slope 60 m grid derived from gridded bathymetry of Rota Island, Mariana Islands, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Slope is derived from gridded (60 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hiialaka'i and R/V AHI. Cell values reflect the maximum rate of...

Optimization in engineering models and algorithms

CERN Document Server

Sioshansi, Ramteen

2017-01-01

This textbook covers the fundamentals of optimization, including linear, mixed-integer linear, nonlinear, and dynamic optimization techniques, with a clear engineering focus. It carefully describes classical optimization models and algorithms using an engineering problem-solving perspective, and emphasizes modeling issues using many real-world examples related to a variety of application areas. Providing an appropriate blend of practical applications and optimization theory makes the text useful to both practitioners and students, and gives the reader a good sense of the power of optimization and the potential difficulties in applying optimization to modeling real-world systems. The book is intended for undergraduate and graduate-level teaching in industrial engineering and other engineering specialties. It is also of use to industry practitioners, due to the inclusion of real-world applications, opening the door to advanced courses on both modeling and algorithm development within the industrial engineering ...

Efficient and Accurate Log-Levy Approximations of Levy-Driven LIBOR Models

DEFF Research Database (Denmark)

Papapantoleon, Antonis; Schoenmakers, John; Skovmand, David

2012-01-01

The LIBOR market model is very popular for pricing interest rate derivatives but is known to have several pitfalls. In addition, if the model is driven by a jump process, then the complexity of the drift term grows exponentially fast (as a function of the tenor length). We consider a Lévy-driven ...... ratchet caps show that the approximations perform very well. In addition, we also consider the log-Lévy approximation of annuities, which offers good approximations for high-volatility regimes....

A Hypothesis-Driven Approach to Site Investigation

Science.gov (United States)

Nowak, W.

2008-12-01

Variability of subsurface formations and the scarcity of data lead to the notion of aquifer parameters as geostatistical random variables. Given an information need and limited resources for field campaigns, site investigation is often put into the context of optimal design. In optimal design, the types, numbers and positions of samples are optimized under case-specific objectives to meet the information needs. Past studies feature optimal data worth (balancing maximum financial profit in an engineering task versus the cost of additional sampling), or aim at a minimum prediction uncertainty of stochastic models for a prescribed investigation budget. Recent studies also account for other sources of uncertainty outside the hydrogeological range, such as uncertain toxicity, ingestion and behavioral parameters of the affected population when predicting the human health risk from groundwater contaminations. The current study looks at optimal site investigation from a new angle. Answering a yes/no question under uncertainty directly requires recasting the original question as a hypothesis test. Otherwise, false confidence in the resulting answer would be pretended. A straightforward example is whether a recent contaminant spill will cause contaminant concentrations in excess of a legal limit at a nearby drinking water well. This question can only be answered down to a specified chance of error, i.e., based on the significance level used in hypothesis tests. Optimal design is placed into the hypothesis-driven context by using the chance of providing a false yes/no answer as new criterion to be minimized. Different configurations apply for one-sided and two-sided hypothesis tests. If a false answer entails financial liability, the hypothesis-driven context can be re-cast in the context of data worth. The remaining difference is that failure is a hard constraint in the data worth context versus a monetary punishment term in the hypothesis-driven context. The basic principle

Satellite Derived Bathymetry as a Coastal Geo-Intelligence Tool for Alaska

Science.gov (United States)

Ventura, D. C.

2017-12-01

What do marine rescue, navigation safety, resource management, coastal infrastructure management, climate adaptation and resilience, economic investment, habitat protection agencies and institutions all have in common? They all benefit from accurate coastal bathymetric data As Arctic-Related Incidents of National Significance (IoNS) workshop points out, reducing time and cost of collecting coastal bathymetry in the Arctic is fundamental to addressing needs of a multitude of stakeholders. Until recently, high resolution coastal data acquisition involved field mobilization of planes, vessels, and people. Given limited resources, short season and remoteness, this approach results in very modest progress toward filling the Alaska's coastal bathymetry data gap and updating vintage data from circa Captain Cook.After successfully executing Satellite Derived Bathymetry (SDB) projects in other more environmentally suitable locations, Fugro and its partner EOMAP are now assessing suitability SDB technique along the Alaska coast. This includes aaccessing archived satellite data and understanding best environmental conditions for the mapping and defining maximum mapping depth as an initial action to understand potentials for Alaska. Here we leverage the physics-based approach to satellite imagery data extraction to derive water depth and complimentary intelligence such as seafloor habitat mapping and certain water quality parameters, such as clarity, turbidity, sediment and chlorophyll-a concentrations, and seasonal changes. Both new and archive imagery are utilized as part of the process. If successful, the benefits and cost savings of this approach are enormous as repeat rate for data collects like this can be measured in months/years as opposed to decades/centuries. Arctic coasts have multiple vulnerabilities and the rate of change will continue to outpace the budgets. As innovative and learning organizations, Fugro and EOMAP strive to not only share the results of this

Progress and prospects of ion-driven fast ignition

International Nuclear Information System (INIS)

Fernandez, Juan C.; Albright, Brian J.; Flippo, Kirk A.; Gautier, D. Cort; Hegelich, Bjoern M.; Schmitt, Mark J.; Yin Lin; Honrubia, J.J.; Temporal, M.

2009-01-01

Fusion fast ignition (FI) initiated by laser-driven ion beams is a promising concept examined in this paper. FI based on a beam of quasi-monoenergetic ions (protons or heavier ions) has the advantage of a more localized energy deposition, which minimizes the required total beam energy, bringing it close to the ∼10 kJ minimum required for fuel densities ∼500 g cm -3 . High-current, laser-driven ion beams are most promising for this purpose. Because they are born neutralized in picosecond timescales, these beams may deliver the power density required to ignite the compressed DT fuel, ∼10 kJ/10 ps into a spot 20 μm in diameter. Our modelling of ion-based FI include high fusion gain targets and a proof of principle experiment. That modelling indicates the concept is feasible, and provides confirmation of our understanding of the operative physics, a firmer foundation for the requirements, and a better understanding of the optimization trade space. An important benefit of the scheme is that such a high-energy, quasi-monoenergetic ignitor beam could be generated far from the capsule (≥1 cm away), eliminating the need for a reentrant cone in the capsule to protect the ion-generation laser target, a tremendous practical benefit. This paper summarizes the ion-based FI concept, the integrated ion-driven FI modelling, the requirements on the ignitor beam derived from that modelling, and the progress in developing a suitable laser-driven ignitor ion beam.

Ontology Driven Meta-Modeling of Service Oriented Architecture

African Journals Online (AJOL)

pc

2018-03-05

Mar 5, 2018 ... #Department of Computer Applications, National Institute of ... *5Department of Computer Science, Winona State University, MN, USA ..... Further, it has aided in service .... Software: A Research Roadmap”, Workshop on the Future of ... and A. Solberg, “Model-driven service engineering with SoaML”, in.

Portfolio optimization with mean-variance model

Science.gov (United States)

Hoe, Lam Weng; Siew, Lam Weng

2016-06-01

Investors wish to achieve the target rate of return at the minimum level of risk in their investment. Portfolio optimization is an investment strategy that can be used to minimize the portfolio risk and can achieve the target rate of return. The mean-variance model has been proposed in portfolio optimization. The mean-variance model is an optimization model that aims to minimize the portfolio risk which is the portfolio variance. The objective of this study is to construct the optimal portfolio using the mean-variance model. The data of this study consists of weekly returns of 20 component stocks of FTSE Bursa Malaysia Kuala Lumpur Composite Index (FBMKLCI). The results of this study show that the portfolio composition of the stocks is different. Moreover, investors can get the return at minimum level of risk with the constructed optimal mean-variance portfolio.

Model-Driven Engineering of Machine Executable Code

Science.gov (United States)

Eichberg, Michael; Monperrus, Martin; Kloppenburg, Sven; Mezini, Mira

Implementing static analyses of machine-level executable code is labor intensive and complex. We show how to leverage model-driven engineering to facilitate the design and implementation of programs doing static analyses. Further, we report on important lessons learned on the benefits and drawbacks while using the following technologies: using the Scala programming language as target of code generation, using XML-Schema to express a metamodel, and using XSLT to implement (a) transformations and (b) a lint like tool. Finally, we report on the use of Prolog for writing model transformations.

Modelling of two-zone accelerator-driven systems

Directory of Open Access Journals (Sweden)

V. A. Babenko

2012-09-01

Full Text Available Neutron-physical modelings of two-zone subcritical reactor driven by high-intensity neutron generator are considered. The cascade principle in subcritical reactors, the use of which can hypothetically substantially amplify the neutron flux from the external source is discussed in this article. The theoretical preconditions of the cascade principle are discussed, and the directions of practical realization of the cascade subcritical system are considered, namely the possible methods of neutron feedback between reactor sections elimination. The results of Monte Carlo neutron-physical modeling of the cascade subcritical systems are presented and discussed.

A model for information retrieval driven by conceptual spaces

OpenAIRE

Tanase, D.

2015-01-01

A retrieval model describes the transformation of a query into a set of documents. The question is: what drives this transformation? For semantic information retrieval type of models this transformation is driven by the content and structure of the semantic models. In this case, Knowledge Organization Systems (KOSs) are the semantic models that encode the meaning employed for monolingual and cross-language retrieval. The focus of this research is the relationship between these meanings’ repre...

Venturi scrubber modelling and optimization

Energy Technology Data Exchange (ETDEWEB)

Viswanathan, S [National Univ., La Jolla, CA (United States). School of Engineering and Technology; Ananthanarayanan, N.V. [National Univ. of Singapore (Singapore). Dept. of Chemical and Environmental Engineering; Azzopardi, B.J. [Nottingham Univ., Nottingham (United Kingdom). Dept. of Chemical Engineering

2005-04-01

This study presented a method to maintain the efficiency of venturi scrubbers in removing fine particulates during gas clean operations while minimizing pressure drop. Venturi scrubbers meet stringent emission standards. In order to choose the optimal method for predicting pressure drop, 4 established models were compared for their accuracy of prediction and simplicity in application. The enhanced algorithm optimizes Pease-Anthony type venturi scrubber performance by predicting the minimum pressure drop required to achieve the desired collection efficiency. This was accomplished by optimizing the key operating and design parameters such as liquid-to-gas ratio, throat gas velocity, number of nozzles, nozzle diameter and throat aspect ratio. Two of the 4 established models were expanded by providing an empirical algorithm to better predict pressure drop in the venturi throat. Model results were validated with experimental data. The optimization algorithm considers the non-uniformity in liquid distribution. It can be applied to cylindrical and rectangular Pease-Anthony type scrubbers. It offers an effective, systematic and accurate method to optimize the performance of new and existing scrubbers. 54 refs., 5 figs.

Handbook on modelling for discrete optimization

CERN Document Server

Pitsoulis, Leonidas; Williams, H

2006-01-01

The primary objective underlying the Handbook on Modelling for Discrete Optimization is to demonstrate and detail the pervasive nature of Discrete Optimization. While its applications cut across an incredibly wide range of activities, many of the applications are only known to specialists. It is the aim of this handbook to correct this. It has long been recognized that "modelling" is a critically important mathematical activity in designing algorithms for solving these discrete optimization problems. Nevertheless solving the resultant models is also often far from straightforward. In recent years it has become possible to solve many large-scale discrete optimization problems. However, some problems remain a challenge, even though advances in mathematical methods, hardware, and software technology have pushed the frontiers forward. This handbook couples the difficult, critical-thinking aspects of mathematical modeling with the hot area of discrete optimization. It will be done in an academic handbook treatment...

Computational modeling of river flow using bathymetry collected with an experimental, water-penetrating, green LiDAR

Science.gov (United States)

Kinzel, P. J.; Legleiter, C. J.; Nelson, J. M.

2009-12-01

Airborne bathymetric Light Detection and Ranging (LiDAR) systems designed for coastal and marine surveys are increasingly being deployed in fluvial environments. While the adaptation of this technology to rivers and streams would appear to be straightforward, currently technical challenges remain with regard to achieving high levels of vertical accuracy and precision when mapping bathymetry in shallow fluvial settings. Collectively these mapping errors have a direct bearing on hydraulic model predictions made using these data. We compared channel surveys conducted along the Platte River, Nebraska, and the Trinity River, California, using conventional ground-based methods with those made with the hybrid topographic/bathymetric Experimental Advanced Airborne Research LiDAR (EAARL). In the turbid and braided Platte River, a bathymetric-waveform processing algorithm was shown to enhance the definition of thalweg channels over a more simplified, first-surface waveform processing algorithm. Consequently flow simulations using data processed with the shallow bathymetric algorithm resulted in improved prediction of wetted area relative to the first-surface algorithm, when compared to the wetted area in concurrent aerial imagery. However, when compared to using conventionally collected data for flow modeling, the inundation extent was over predicted with the EAARL topography due to higher bed elevations measured by the LiDAR. In the relatively clear, meandering Trinity River, bathymetric processing algorithms were capable of defining a 3 meter deep pool. However, a similar bias in depth measurement was observed, with the LiDAR measuring the elevation of the river bottom above its actual position, resulting in a predicted water surface higher than that measured by field data. This contribution addresses the challenge of making bathymetric measurements with the EAARL in different environmental conditions encountered in fluvial settings, explores technical issues related to

Bathymetry Mapping of the West Florida Shelf (Steamboat Lumps), Gulf of Mexico (NODC Accession 0001410)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — XYZ ASCII format data generated from the 2001 multibeam sonar survey of the West Florida Shelf, Gulf of Mexico. The data include high-resolution bathymetry and...

Towards Product Lining Model-Driven Development Code Generators

OpenAIRE

Roth, Alexander; Rumpe, Bernhard

2015-01-01

A code generator systematically transforms compact models to detailed code. Today, code generation is regarded as an integral part of model-driven development (MDD). Despite its relevance, the development of code generators is an inherently complex task and common methodologies and architectures are lacking. Additionally, reuse and extension of existing code generators only exist on individual parts. A systematic development and reuse based on a code generator product line is still in its inf...

A model for an acoustically driven microbubble inside a rigid tube

KAUST Repository

Qamar, Adnan; Samtaney, Ravi

2014-01-01

A theoretical framework to model the dynamics of acoustically driven microbubble inside a rigid tube is presented. The proposed model is not a variant of the conventional Rayleigh-Plesset category of models. It is derived from the reduced Navier

A multiplexed microfluidic toolbox for the rapid optimization of affinity-driven partition in aqueous two phase systems.

Science.gov (United States)

Bras, Eduardo J S; Soares, Ruben R G; Azevedo, Ana M; Fernandes, Pedro; Arévalo-Rodríguez, Miguel; Chu, Virginia; Conde, João P; Aires-Barros, M Raquel

2017-09-15

Antibodies and other protein products such as interferons and cytokines are biopharmaceuticals of critical importance which, in order to be safely administered, have to be thoroughly purified in a cost effective and efficient manner. The use of aqueous two-phase extraction (ATPE) is a viable option for this purification, but these systems are difficult to model and optimization procedures require lengthy and expensive screening processes. Here, a methodology for the rapid screening of antibody extraction conditions using a microfluidic channel-based toolbox is presented. A first microfluidic structure allows a simple negative-pressure driven rapid screening of up to 8 extraction conditions simultaneously, using less than 20μL of each phase-forming solution per experiment, while a second microfluidic structure allows the integration of multi-step extraction protocols based on the results obtained with the first device. In this paper, this microfluidic toolbox was used to demonstrate the potential of LYTAG fusion proteins used as affinity tags to optimize the partitioning of antibodies in ATPE processes, where a maximum partition coefficient (K) of 9.2 in a PEG 3350/phosphate system was obtained for the antibody extraction in the presence of the LYTAG-Z dual ligand. This represents an increase of approx. 3.7 fold when compared with the same conditions without the affinity molecule (K=2.5). Overall, this miniaturized and versatile approach allowed the rapid optimization of molecule partition followed by a proof-of-concept demonstration of an integrated back extraction procedure, both of which are critical procedures towards obtaining high purity biopharmaceuticals using ATPE. Copyright © 2017 Elsevier B.V. All rights reserved.

Rugosity grid derived from gridded bathymetry of Howland Island, Pacific Remote Island Areas, Central Pacific

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (40 m cell size) multibeam bathymetry, collected aboard R/V AHI and NOAA ship Hi'ialakai. Cell values reflect the (surface area) /...

Optimization Models for Petroleum Field Exploitation

Energy Technology Data Exchange (ETDEWEB)

Jonsbraaten, Tore Wiig

1998-12-31

This thesis presents and discusses various models for optimal development of a petroleum field. The objective of these optimization models is to maximize, under many uncertain parameters, the project`s expected net present value. First, an overview of petroleum field optimization is given from the point of view of operations research. Reservoir equations for a simple reservoir system are derived and discretized and included in optimization models. Linear programming models for optimizing production decisions are discussed and extended to mixed integer programming models where decisions concerning platform, wells and production strategy are optimized. Then, optimal development decisions under uncertain oil prices are discussed. The uncertain oil price is estimated by a finite set of price scenarios with associated probabilities. The problem is one of stochastic mixed integer programming, and the solution approach is to use a scenario and policy aggregation technique developed by Rockafellar and Wets although this technique was developed for continuous variables. Stochastic optimization problems with focus on problems with decision dependent information discoveries are also discussed. A class of ``manageable`` problems is identified and an implicit enumeration algorithm for finding optimal decision policy is proposed. Problems involving uncertain reservoir properties but with a known initial probability distribution over possible reservoir realizations are discussed. Finally, a section on Nash-equilibrium and bargaining in an oil reservoir management game discusses the pool problem arising when two lease owners have access to the same underlying oil reservoir. Because the oil tends to migrate, both lease owners have incentive to drain oil from the competitors part of the reservoir. The discussion is based on a numerical example. 107 refs., 31 figs., 14 tabs.

3D Topology optimization of Stokes flow problems

DEFF Research Database (Denmark)

Gersborg-Hansen, Allan; Dammann, Bernd

of energy efficient devices for 2D Stokes flow. Creeping flow problems are described by the Stokes equations which model very viscous fluids at macro scales or ordinary fluids at very small scales. The latter gives the motivation for topology optimization problems based on the Stokes equations being a model......The present talk is concerned with the application of topology optimization to creeping flow problems in 3D. This research is driven by the fact that topology optimization has proven very successful as a tool in academic and industrial design problems. Success stories are reported from such diverse...

Model Risk in Portfolio Optimization

Directory of Open Access Journals (Sweden)

David Stefanovits

2014-08-01

Full Text Available We consider a one-period portfolio optimization problem under model uncertainty. For this purpose, we introduce a measure of model risk. We derive analytical results for this measure of model risk in the mean-variance problem assuming we have observations drawn from a normal variance mixture model. This model allows for heavy tails, tail dependence and leptokurtosis of marginals. The results show that mean-variance optimization is seriously compromised by model uncertainty, in particular, for non-Gaussian data and small sample sizes. To mitigate these shortcomings, we propose a method to adjust the sample covariance matrix in order to reduce model risk.

Quantum tunneling in the periodically driven SU(2) model

International Nuclear Information System (INIS)

Arvieu, R.

1991-01-01

The tunneling rate is investigated in the quantum and classical limits using an exactly soluble, periodically driven SU(2) model. The tunneling rate is obtained by solving the time-dependent Schroedinger equation and projecting the exact wave-function on the space of coherent states using the Husimi distribution. The oscillatory, coherent tunneling of the wave-function between two Hartree-Fock minima is observed. The driving plays an important role increasing the tunneling rate by orders of magnitude as compared to the semiclassical results. This is due to the dominant role of excited states in the driven quantum tunneling. (author) 15 refs., 4 figs

An optimal generic model for multi-parameters and big data optimizing: a laboratory experimental study

Science.gov (United States)

Utama, D. N.; Ani, N.; Iqbal, M. M.

2018-03-01

Optimization is a process for finding parameter (parameters) that is (are) able to deliver an optimal value for an objective function. Seeking an optimal generic model for optimizing is a computer science study that has been being practically conducted by numerous researchers. Generic model is a model that can be technically operated to solve any varieties of optimization problem. By using an object-oriented method, the generic model for optimizing was constructed. Moreover, two types of optimization method, simulated-annealing and hill-climbing, were functioned in constructing the model and compared to find the most optimal one then. The result said that both methods gave the same result for a value of objective function and the hill-climbing based model consumed the shortest running time.

Model Driven Development of Data Sensitive Systems

DEFF Research Database (Denmark)

Olsen, Petur

2014-01-01

storage systems, where the actual values of the data is not relevant for the behavior of the system. For many systems the values are important. For instance the control flow of the system can be dependent on the input values. We call this type of system data sensitive, as the execution is sensitive...... to the values of variables. This theses strives to improve model-driven development of such data-sensitive systems. This is done by addressing three research questions. In the first we combine state-based modeling and abstract interpretation, in order to ease modeling of data-sensitive systems, while allowing...... efficient model-checking and model-based testing. In the second we develop automatic abstraction learning used together with model learning, in order to allow fully automatic learning of data-sensitive systems to allow learning of larger systems. In the third we develop an approach for modeling and model-based...

Coastal bathymetry data collected in May 2015 from Fire Island, New York—Wilderness breach and shoreface

Science.gov (United States)

Nelson, Timothy R.; Miselis, Jennifer L.; Hapke, Cheryl J.; Brenner, Owen T.; Henderson, Rachel E.; Reynolds, Billy J.; Wilson, Kathleen E.

2017-05-12

Scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center in St. Petersburg, Florida, conducted a bathymetric survey of Fire Island from May 6-20, 2015. The USGS is involved in a post-Hurricane Sandy effort to map and monitor the morphologic evolution of the wilderness breach as a part of the Hurricane Sandy Supplemental Project GS2-2B. During this study, bathymetry data were collected with single-beam echo sounders and Global Positioning Systems, which were mounted to personal watercraft, along the Fire Island shoreface and within the wilderness breach. Additional bathymetry and elevation data were collected using backpack Global Positioning Systems on flood shoals and in shallow channels within the wilderness breach.

Slope grid derived from gridded bathymetry of Johnston Island, Pacific Remote Island Areas, Central Pacific.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Slope is derived from gridded (20 m cell size) multibeam bathymetry, collected aboard R/V AHI, and NOAA ship Hi'ialakai. Cell values reflect the maximum rate of...

Slope grid derived from gridded bathymetry of Howland Island, Pacific Remote Island Areas, Central Pacific.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Slope is derived from gridded (40 m cell size) multibeam bathymetry, collected aboard R/V AHI, and NOAA ship Hi'ialakai. Cell values reflect the maximum rate of...

Bathymetry 1m GRID of St. Thomas, US Virgin Islands, 2004, UTM 20 WGS84

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains an ESRI Grid with 1 meter cell size representing the bathymetry of the south shore of St. Thomas, US Virgin Islands. NOAA's NOS/NCCOS/CCMA...

Bathymetry 2M Grid of Grammanik Bank, US Virgin Islands, 2005, UTM 20 NAD83

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains an ESRI Grid with 2 meter cell size representing the bathymetry of Grammanik Bank south of St. Thomas, US Virgin Islands. NOAA's NOS/NCCOS/CCMA...

Slope grid derived from gridded bathymetry of Baker Island, Pacific Remote Island Areas, Central Pacific.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Slope is derived from gridded (20 m cell size) multibeam bathymetry, collected aboard R/V AHI, and NOAA ship Hi'ialakai. Cell values reflect the maximum rate of...

A framework for reactive optimization in mobile ad hoc networks

DEFF Research Database (Denmark)

McClary, Dan; Syrotiuk, Violet; Kulahci, Murat

2008-01-01

We present a framework to optimize the performance of a mobile ad hoc network over a wide range of operating conditions. It includes screening experiments to quantify the parameters and interactions among parameters influential to throughput. Profile-driven regression is applied to obtain a model....... The predictive accuracy of the model is monitored and used to update the model dynamically. The results indicate the framework may be useful for the optimization of dynamic systems of high dimension....

The effect of bathymetric filtering on nearshore process model results

Science.gov (United States)

Plant, N.G.; Edwards, K.L.; Kaihatu, J.M.; Veeramony, J.; Hsu, L.; Holland, K.T.

2009-01-01

Nearshore wave and flow model results are shown to exhibit a strong sensitivity to the resolution of the input bathymetry. In this analysis, bathymetric resolution was varied by applying smoothing filters to high-resolution survey data to produce a number of bathymetric grid surfaces. We demonstrate that the sensitivity of model-predicted wave height and flow to variations in bathymetric resolution had different characteristics. Wave height predictions were most sensitive to resolution of cross-shore variability associated with the structure of nearshore sandbars. Flow predictions were most sensitive to the resolution of intermediate scale alongshore variability associated with the prominent sandbar rhythmicity. Flow sensitivity increased in cases where a sandbar was closer to shore and shallower. Perhaps the most surprising implication of these results is that the interpolation and smoothing of bathymetric data could be optimized differently for the wave and flow models. We show that errors between observed and modeled flow and wave heights are well predicted by comparing model simulation results using progressively filtered bathymetry to results from the highest resolution simulation. The damage done by over smoothing or inadequate sampling can therefore be estimated using model simulations. We conclude that the ability to quantify prediction errors will be useful for supporting future data assimilation efforts that require this information.

Lessons Learned from Stakeholder-Driven Modeling in the Western Lake Erie Basin

Science.gov (United States)

Muenich, R. L.; Read, J.; Vaccaro, L.; Kalcic, M. M.; Scavia, D.

2017-12-01

Lake Erie's history includes a great environmental success story. Recognizing the impact of high phosphorus loads from point sources, the United States and Canada 1972 Great Lakes Water Quality Agreement set load reduction targets to reduce algae blooms and hypoxia. The Lake responded quickly to those reductions and it was declared a success. However, since the mid-1990s, Lake Erie's algal blooms and hypoxia have returned, and this time with a dominant algae species that produces toxins. Return of the algal blooms and hypoxia is again driven by phosphorus loads, but this time a major source is the agriculturally-dominated Maumee River watershed that covers NW Ohio, NE Indiana, and SE Michigan, and the hypoxic extent has been shown to be driven by Maumee River loads plus those from the bi-national and multiple land-use St. Clair - Detroit River system. Stakeholders in the Lake Erie watershed have a long history of engagement with environmental policy, including modeling and monitoring efforts. This talk will focus on the application of interdisciplinary, stakeholder-driven modeling efforts aimed at understanding the primary phosphorus sources and potential pathways to reduce these sources and the resulting algal blooms and hypoxia in Lake Erie. We will discuss the challenges, such as engaging users with different goals, benefits to modeling, such as improvements in modeling data, and new research questions emerging from these modeling efforts that are driven by end-user needs.

Optimizing velocities and transports for complex coastal regions and archipelagos

OpenAIRE

Haley, Patrick; Agarwal, Arpit; Lermusiaux, Pierre

2015-01-01

We derive and apply a methodology for the initialization of velocity and transport fields in complex multiply-connected regions with multiscale dynamics. The result is initial fields that are consistent with observations, complex geometry and dynamics, and that can simulate the evolution of ocean processes without large spurious initial transients. A class of constrained weighted least squares optimizations is defined to best fit first-guess velocities while satisfying the complex bathymetry,...

Perspectives of data-driven LPV modeling of high-purity distillation columns

NARCIS (Netherlands)

Bachnas, A.A.; Toth, R.; Mesbah, A.; Ludlage, J.H.A.

2013-01-01

Abstract—This paper investigates data-driven, Linear- Parameter-Varying (LPV) modeling of a high-purity distillation column. Two LPV modeling approaches are studied: a local approach, corresponding to the interpolation of Linear Time- Invariant (LTI) models identified at steady-state purity levels,

Optimization Modeling with Spreadsheets

CERN Document Server

Baker, Kenneth R

2011-01-01

This introductory book on optimization (mathematical programming) includes coverage on linear programming, nonlinear programming, integer programming and heuristic programming; as well as an emphasis on model building using Excel and Solver.  The emphasis on model building (rather than algorithms) is one of the features that makes this book distinctive. Most books devote more space to algorithmic details than to formulation principles. These days, however, it is not necessary to know a great deal about algorithms in order to apply optimization tools, especially when relying on the sp

Hypothesis-driven methods to augment human cognition by optimizing cortical oscillations

Directory of Open Access Journals (Sweden)

Jörn M. Horschig

2014-06-01

Full Text Available Cortical oscillations have been shown to represent fundamental functions of a working brain, e.g. communication, stimulus binding, error monitoring, and inhibition, and are directly linked to behavior. Recent studies intervening with these oscillations have demonstrated effective modulation of both the oscillations and behavior. In this review, we collect evidence in favor of how hypothesis-driven methods can be used to augment cognition by optimizing cortical oscillations. We elaborate their potential usefulness for three target groups: healthy elderly, patients with attention deficit/hyperactivity disorder, and healthy young adults. We discuss the relevance of neuronal oscillations in each group and show how each of them can benefit from the manipulation of functionally-related oscillations. Further, we describe methods for manipulation of neuronal oscillations including direct brain stimulation as well as indirect task alterations. We also discuss practical considerations about the proposed techniques. In conclusion, we propose that insights from neuroscience should guide techniques to augment human cognition, which in turn can provide a better understanding of how the human brain works.

Bathymetry of Torssukatak fjord and one century of glacier stability

Science.gov (United States)

An, L.; Rignot, E. J.; Morlighem, M.

2017-12-01

Marine-terminating glaciers dominate the evolution of the Greenland Ice Sheet(GrIS) mass balance as they control 90% of the ice discharge into the ocean. Warm air temperatures thin the glaciers from the top to unground ice fronts from the bed. Warm oceans erode the submerged grounded ice, causing the grounding line to retreat. To interpret the recent and future evolution of two outlet glaciers, Sermeq Avangnardleq (AVA) and Sermeq Kujatdleq (KUJ) in central West Greenland, flowing into the ice-choked Torssukatak fjord (TOR), we need to know their ice thickness and bed topography and the fjord bathymetry. Here, we present a novel mapping of the glacier bed topography, ice thickness and sea floor bathymetry near the grounding line using high resolution airborne gravity data from AIRGrav collected in August 2012 with a helicopter platform, at 500 m spacing grid, 50 knots ground speed, 80 m ground clearance, with submilligal accuracy, i.e. higher than NASA Operation IceBridge (OIB)'s 5.2 km resolution, 290 knots, and 450 m clearance. We also employ MultiBeam Echo Sounding data (MBES) collected in the fjord since 2009. We had to wait until the summer of 2016, during Ocean Melting Greenland (OMG), to map the fjord bathymetry near the ice fronts for the first time. We constrain the 3D inversion of the gravity data with MBES in the fjord and a reconstruction of the glacier bed topography using mass conservation (MC) on land ice. The seamless topography obtained across the grounding line reveal the presence of a 300-m sill for AVA, which explains why this glacier has been stable for a century, despite changes in surface melt and ocean-induced melt and the presence of a deep fjord (800 m) in front of the glacier. For KUJ, we also reveal the presence of a wide sill (300 m depth) near the current ice front which explains its stability and the stranding of iceberg debris in front of the glacier. The results shed new light on the evolution of these glaciers and explain their

Towards an Experimental Framework for Measuring Usability of Model-Driven Tools

NARCIS (Netherlands)

Panach, Jose Ignacio; Condori-Fernandez, Nelly; Baar, Arthur; Vos, Tanja; Romeu, Ignacio; Pastor, Oscar; Campos, Pedro; Graham, Nicholas; Jorge, Joaquim; Nunes, Nuno; Palanque, Philippe; Winckler, Marco

2011-01-01

According to the Model-Driven Development (MDD) paradigm, analysts can substantially improve the software development process concentrating their efforts on a conceptual model, which can be transformed into code by means of transformation rules applied by a model compiler. However, MDD tools are not

Multibeam bathymetry and CTD measurements in two fjord systems in southeastern Greenland

DEFF Research Database (Denmark)

Kjeldsen, Kristian Kjellerup; Weinrebe, Reimer Wilhelm; Bendtsen, Jørgen

2017-01-01

We present bathymetry and hydrological observations collected in the summer of 2014 from two fjordsystems in southeastern Greenland with a multibeam sonar system. Our results provide a detailed bathymetricmap of the fjord complex around the island of Skjoldungen in Skjoldungen Fjord and the outer...... of the distribution of subglacial meltwater. Data are available through the PANGAEA website at https://doi.pangaea.de/10.1594/PANGAEA.860627....

Optimum path planning of mobile robot in unknown static and dynamic environments using Fuzzy-Wind Driven Optimization algorithm

Directory of Open Access Journals (Sweden)

Anish Pandey

2017-02-01

Full Text Available This article introduces a singleton type-1 fuzzy logic system (T1-SFLS controller and Fuzzy-WDO hybrid for the autonomous mobile robot navigation and collision avoidance in an unknown static and dynamic environment. The WDO (Wind Driven Optimization algorithm is used to optimize and tune the input/output membership function parameters of the fuzzy controller. The WDO algorithm is working based on the atmospheric motion of infinitesimal small air parcels navigates over an N-dimensional search domain. The performance of this proposed technique has compared through many computer simulations and real-time experiments by using Khepera-III mobile robot. As compared to the T1-SFLS controller the Fuzzy-WDO algorithm is found good agreement for mobile robot navigation.

Modeling and optimization of laser cutting operations

Directory of Open Access Journals (Sweden)

Gadallah Mohamed Hassan

2015-01-01

Full Text Available Laser beam cutting is one important nontraditional machining process. This paper optimizes the parameters of laser beam cutting parameters of stainless steel (316L considering the effect of input parameters such as power, oxygen pressure, frequency and cutting speed. Statistical design of experiments is carried in three different levels and process responses such as average kerf taper (Ta, surface roughness (Ra and heat affected zones are measured accordingly. A response surface model is developed as a function of the process parameters. Responses predicted by the models (as per Taguchi’s L27OA are employed to search for an optimal combination to achieve desired process yield. Response Surface Models (RSMs are developed for mean responses, S/N ratio, and standard deviation of responses. Optimization models are formulated as single objective optimization problem subject to process constraints. Models are formulated based on Analysis of Variance (ANOVA and optimized using Matlab developed environment. Optimum solutions are compared with Taguchi Methodology results. As such, practicing engineers have means to model, analyze and optimize nontraditional machining processes. Validation experiments are carried to verify the developed models with success.

Optimizing phonon scattering by tuning surface-interdiffusion-driven intermixing to break the random-alloy limit of thermal conductivity

Science.gov (United States)

Yang, Xiaolong; Li, Wu

2018-01-01

We investigate the evolution of the cross-plane thermal conductivity κ of superlattices (SLs) as interfaces change from perfectly abrupt to totally intermixed, by using nonequilibrium molecular dynamics simulations in combination with the spectral heat current calculations. We highlight the role of surface-interdiffusion-driven intermixing by calculating the κ of SLs with changing interface roughness, whose tuning allows for κ values much lower than the "alloy limit" and the abrupt interface limit in same cases. The interplay between alloy and interface scattering in different frequency ranges provides a physical basis to predict a minimum of thermal conductivity. More specifically, we also explore how the interface roughness affects the thermal conductivities for SL materials with a broad span of atomic mass and bond strength. In particular, we find that (i) only when the "spacer" thickness of SLs increases up to a critical value, κ of rough SLs can break the corresponding "alloy limit," since SLs with different "spacer" thickness have different characteristic length of phonon transport, which is influenced by surface-interdiffusion-driven intermixing to different extend. (ii) Whether κ changes monotonically with interface roughness strongly depends on the period length and intrinsic behavior of phonon transport for SL materials. Especially, for the SL with large period length, there exists an optimal interface roughness that can minimize the thermal conductivity. (iii) Surface-interdiffusion-driven intermixing is more effective in achieving a low κ below the alloy limit for SL materials with large mass mismatch than with small one. (iv) It is possible for SL materials with large lattice mismatch (i.e., bond strength) to design an ideally abrupt interface structure with κ much below the alloy limit. These results have clear implications for optimization of thermal transport for heat management and for the development of thermoelectric materials.

Integrating Usability Evaluation into Model-Driven Video Game Development

OpenAIRE

Fernandez , Adrian; Insfran , Emilio; Abrahão , Silvia; Carsí , José ,; Montero , Emanuel

2012-01-01

Part 3: Short Papers; International audience; The increasing complexity of video game development highlights the need of design and evaluation methods for enhancing quality and reducing time and cost. In this context, Model-Driven Development approaches seem to be very promising since a video game can be obtained by transforming platform-independent models into platform-specific models that can be in turn transformed into code. Although this approach is started to being used for video game de...

Visual prosthesis wireless energy transfer system optimal modeling.

Science.gov (United States)

Li, Xueping; Yang, Yuan; Gao, Yong

2014-01-16

Wireless energy transfer system is an effective way to solve the visual prosthesis energy supply problems, theoretical modeling of the system is the prerequisite to do optimal energy transfer system design. On the basis of the ideal model of the wireless energy transfer system, according to visual prosthesis application condition, the system modeling is optimized. During the optimal modeling, taking planar spiral coils as the coupling devices between energy transmitter and receiver, the effect of the parasitic capacitance of the transfer coil is considered, and especially the concept of biological capacitance is proposed to consider the influence of biological tissue on the energy transfer efficiency, resulting in the optimal modeling's more accuracy for the actual application. The simulation data of the optimal model in this paper is compared with that of the previous ideal model, the results show that under high frequency condition, the parasitic capacitance of inductance and biological capacitance considered in the optimal model could have great impact on the wireless energy transfer system. The further comparison with the experimental data verifies the validity and accuracy of the optimal model proposed in this paper. The optimal model proposed in this paper has a higher theoretical guiding significance for the wireless energy transfer system's further research, and provide a more precise model reference for solving the power supply problem in visual prosthesis clinical application.

A Pareto-optimal moving average multigene genetic programming model for daily streamflow prediction

Science.gov (United States)

Danandeh Mehr, Ali; Kahya, Ercan

2017-06-01

Genetic programming (GP) is able to systematically explore alternative model structures of different accuracy and complexity from observed input and output data. The effectiveness of GP in hydrological system identification has been recognized in recent studies. However, selecting a parsimonious (accurate and simple) model from such alternatives still remains a question. This paper proposes a Pareto-optimal moving average multigene genetic programming (MA-MGGP) approach to develop a parsimonious model for single-station streamflow prediction. The three main components of the approach that take us from observed data to a validated model are: (1) data pre-processing, (2) system identification and (3) system simplification. The data pre-processing ingredient uses a simple moving average filter to diminish the lagged prediction effect of stand-alone data-driven models. The multigene ingredient of the model tends to identify the underlying nonlinear system with expressions simpler than classical monolithic GP and, eventually simplification component exploits Pareto front plot to select a parsimonious model through an interactive complexity-efficiency trade-off. The approach was tested using the daily streamflow records from a station on Senoz Stream, Turkey. Comparing to the efficiency results of stand-alone GP, MGGP, and conventional multi linear regression prediction models as benchmarks, the proposed Pareto-optimal MA-MGGP model put forward a parsimonious solution, which has a noteworthy importance of being applied in practice. In addition, the approach allows the user to enter human insight into the problem to examine evolved models and pick the best performing programs out for further analysis.

An Indirect Simulation-Optimization Model for Determining Optimal TMDL Allocation under Uncertainty

Directory of Open Access Journals (Sweden)

Feng Zhou

2015-11-01

Full Text Available An indirect simulation-optimization model framework with enhanced computational efficiency and risk-based decision-making capability was developed to determine optimal total maximum daily load (TMDL allocation under uncertainty. To convert the traditional direct simulation-optimization model into our indirect equivalent model framework, we proposed a two-step strategy: (1 application of interval regression equations derived by a Bayesian recursive regression tree (BRRT v2 algorithm, which approximates the original hydrodynamic and water-quality simulation models and accurately quantifies the inherent nonlinear relationship between nutrient load reductions and the credible interval of algal biomass with a given confidence interval; and (2 incorporation of the calibrated interval regression equations into an uncertain optimization framework, which is further converted to our indirect equivalent framework by the enhanced-interval linear programming (EILP method and provides approximate-optimal solutions at various risk levels. The proposed strategy was applied to the Swift Creek Reservoir’s nutrient TMDL allocation (Chesterfield County, VA to identify the minimum nutrient load allocations required from eight sub-watersheds to ensure compliance with user-specified chlorophyll criteria. Our results indicated that the BRRT-EILP model could identify critical sub-watersheds faster than the traditional one and requires lower reduction of nutrient loadings compared to traditional stochastic simulation and trial-and-error (TAE approaches. This suggests that our proposed framework performs better in optimal TMDL development compared to the traditional simulation-optimization models and provides extreme and non-extreme tradeoff analysis under uncertainty for risk-based decision making.

Modelling exciton–phonon interactions in optically driven quantum dots

DEFF Research Database (Denmark)

Nazir, Ahsan; McCutcheon, Dara

2016-01-01

We provide a self-contained review of master equation approaches to modelling phonon effects in optically driven self-assembled quantum dots. Coupling of the (quasi) two-level excitonic system to phonons leads to dissipation and dephasing, the rates of which depend on the excitation conditions...

Simulating large-scale pedestrian movement using CA and event driven model: Methodology and case study

Science.gov (United States)

Li, Jun; Fu, Siyao; He, Haibo; Jia, Hongfei; Li, Yanzhong; Guo, Yi

2015-11-01

Large-scale regional evacuation is an important part of national security emergency response plan. Large commercial shopping area, as the typical service system, its emergency evacuation is one of the hot research topics. A systematic methodology based on Cellular Automata with the Dynamic Floor Field and event driven model has been proposed, and the methodology has been examined within context of a case study involving the evacuation within a commercial shopping mall. Pedestrians walking is based on Cellular Automata and event driven model. In this paper, the event driven model is adopted to simulate the pedestrian movement patterns, the simulation process is divided into normal situation and emergency evacuation. The model is composed of four layers: environment layer, customer layer, clerk layer and trajectory layer. For the simulation of movement route of pedestrians, the model takes into account purchase intention of customers and density of pedestrians. Based on evacuation model of Cellular Automata with Dynamic Floor Field and event driven model, we can reflect behavior characteristics of customers and clerks at the situations of normal and emergency evacuation. The distribution of individual evacuation time as a function of initial positions and the dynamics of the evacuation process is studied. Our results indicate that the evacuation model using the combination of Cellular Automata with Dynamic Floor Field and event driven scheduling can be used to simulate the evacuation of pedestrian flows in indoor areas with complicated surroundings and to investigate the layout of shopping mall.

Modeling, simulation, and fabrication of a fully integrated, acid-stable, scalable solar-driven water-splitting system.

Science.gov (United States)

Walczak, Karl; Chen, Yikai; Karp, Christoph; Beeman, Jeffrey W; Shaner, Matthew; Spurgeon, Joshua; Sharp, Ian D; Amashukeli, Xenia; West, William; Jin, Jian; Lewis, Nathan S; Xiang, Chengxiang

2015-02-01

A fully integrated solar-driven water-splitting system comprised of WO3 /FTO/p(+) n Si as the photoanode, Pt/TiO2 /Ti/n(+) p Si as the photocathode, and Nafion as the membrane separator, was simulated, assembled, operated in 1.0 M HClO4 , and evaluated for performance and safety characteristics under dual side illumination. A multi-physics model that accounted for the performance of the photoabsorbers and electrocatalysts, ion transport in the solution electrolyte, and gaseous product crossover was first used to define the optimal geometric design space for the system. The photoelectrodes and the membrane separators were then interconnected in a louvered design system configuration, for which the light-absorbing area and the solution-transport pathways were simultaneously optimized. The performance of the photocathode and the photoanode were separately evaluated in a traditional three-electrode photoelectrochemical cell configuration. The photocathode and photoanode were then assembled back-to-back in a tandem configuration to provide sufficient photovoltage to sustain solar-driven unassisted water-splitting. The current-voltage characteristics of the photoelectrodes showed that the low photocurrent density of the photoanode limited the overall solar-to-hydrogen (STH) conversion efficiency due to the large band gap of WO3 . A hydrogen-production rate of 0.17 mL hr(-1) and a STH conversion efficiency of 0.24 % was observed in a full cell configuration for >20 h with minimal product crossover in the fully operational, intrinsically safe, solar-driven water-splitting system. The solar-to-hydrogen conversion efficiency, ηSTH , calculated using the multiphysics numerical simulation was in excellent agreement with the experimental behavior of the system. The value of ηSTH was entirely limited by the performance of the photoelectrochemical assemblies employed in this study. The louvered design provides a robust platform for implementation of various types of

Model-driven design, simulation and implementation of service compositions in COSMO

NARCIS (Netherlands)

Quartel, Dick; Dirgahayu, T.; van Sinderen, Marten J.

2009-01-01

The success of software development projects to a large extent depends on the quality of the models that are produced in the development process, which in turn depends on the conceptual and practical support that is available for modelling, design and analysis. This paper focuses on model-driven

Optimizing Likelihood Models for Particle Trajectory Segmentation in Multi-State Systems.

Science.gov (United States)

Young, Dylan Christopher; Scrimgeour, Jan

2018-06-19

Particle tracking offers significant insight into the molecular mechanics that govern the behav- ior of living cells. The analysis of molecular trajectories that transition between different motive states, such as diffusive, driven and tethered modes, is of considerable importance, with even single trajectories containing significant amounts of information about a molecule's environment and its interactions with cellular structures. Hidden Markov models (HMM) have been widely adopted to perform the segmentation of such complex tracks. In this paper, we show that extensive analysis of hidden Markov model outputs using data derived from multi-state Brownian dynamics simulations can be used both for the optimization of the likelihood models used to describe the states of the system and for characterization of the technique's failure mechanisms. This analysis was made pos- sible by the implementation of parallelized adaptive direct search algorithm on a Nvidia graphics processing unit. This approach provides critical information for the visualization of HMM failure and successful design of particle tracking experiments where trajectories contain multiple mobile states. © 2018 IOP Publishing Ltd.

Optimal policy for value-based decision-making.

Science.gov (United States)

Tajima, Satohiro; Drugowitsch, Jan; Pouget, Alexandre

2016-08-18

For decades now, normative theories of perceptual decisions, and their implementation as drift diffusion models, have driven and significantly improved our understanding of human and animal behaviour and the underlying neural processes. While similar processes seem to govern value-based decisions, we still lack the theoretical understanding of why this ought to be the case. Here, we show that, similar to perceptual decisions, drift diffusion models implement the optimal strategy for value-based decisions. Such optimal decisions require the models' decision boundaries to collapse over time, and to depend on the a priori knowledge about reward contingencies. Diffusion models only implement the optimal strategy under specific task assumptions, and cease to be optimal once we start relaxing these assumptions, by, for example, using non-linear utility functions. Our findings thus provide the much-needed theory for value-based decisions, explain the apparent similarity to perceptual decisions, and predict conditions under which this similarity should break down.

Rugosity grid derived from gridded bathymetry of of Baker Island, Pacific Remote Island Areas, Central Pacific.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (20 m cell size) multibeam bathymetry, collected aboard R/V AHI and NOAA ship Hi'ialakai. Cell values reflect the (surface area) /...

Rugosity grid derived from gridded bathymetry of of Johnston Island, Pacific Remote Island Areas, Central Pacific.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (20 m cell size) multibeam bathymetry, collected aboard R/V AHI and NOAA ship Hi'ialakai. Cell values reflect the (surface area) /...

Bathymetry of Mid Shelf Reef, US Virgin Islands 2005, 1M Grid, UTM 20 NAD83

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains an ESRI Grid with 1 meter cell size representing the bathymetry of the Mid Shelf Reef south of St. Thomas, US Virgin Islands. NOAA's...

Mutational landscape of EGFR-, MYC-, and Kras-driven genetically engineered mouse models of lung adenocarcinoma.

Science.gov (United States)

McFadden, David G; Politi, Katerina; Bhutkar, Arjun; Chen, Frances K; Song, Xiaoling; Pirun, Mono; Santiago, Philip M; Kim-Kiselak, Caroline; Platt, James T; Lee, Emily; Hodges, Emily; Rosebrock, Adam P; Bronson, Roderick T; Socci, Nicholas D; Hannon, Gregory J; Jacks, Tyler; Varmus, Harold

2016-10-18

Genetically engineered mouse models (GEMMs) of cancer are increasingly being used to assess putative driver mutations identified by large-scale sequencing of human cancer genomes. To accurately interpret experiments that introduce additional mutations, an understanding of the somatic genetic profile and evolution of GEMM tumors is necessary. Here, we performed whole-exome sequencing of tumors from three GEMMs of lung adenocarcinoma driven by mutant epidermal growth factor receptor (EGFR), mutant Kirsten rat sarcoma viral oncogene homolog (Kras), or overexpression of MYC proto-oncogene. Tumors from EGFR- and Kras-driven models exhibited, respectively, 0.02 and 0.07 nonsynonymous mutations per megabase, a dramatically lower average mutational frequency than observed in human lung adenocarcinomas. Tumors from models driven by strong cancer drivers (mutant EGFR and Kras) harbored few mutations in known cancer genes, whereas tumors driven by MYC, a weaker initiating oncogene in the murine lung, acquired recurrent clonal oncogenic Kras mutations. In addition, although EGFR- and Kras-driven models both exhibited recurrent whole-chromosome DNA copy number alterations, the specific chromosomes altered by gain or loss were different in each model. These data demonstrate that GEMM tumors exhibit relatively simple somatic genotypes compared with human cancers of a similar type, making these autochthonous model systems useful for additive engineering approaches to assess the potential of novel mutations on tumorigenesis, cancer progression, and drug sensitivity.

Mutational landscape of EGFR-, MYC-, and Kras-driven genetically engineered mouse models of lung adenocarcinoma

Science.gov (United States)

McFadden, David G.; Politi, Katerina; Bhutkar, Arjun; Chen, Frances K.; Song, Xiaoling; Pirun, Mono; Santiago, Philip M.; Kim-Kiselak, Caroline; Platt, James T.; Lee, Emily; Hodges, Emily; Rosebrock, Adam P.; Bronson, Roderick T.; Socci, Nicholas D.; Hannon, Gregory J.; Jacks, Tyler; Varmus, Harold

2016-01-01

Genetically engineered mouse models (GEMMs) of cancer are increasingly being used to assess putative driver mutations identified by large-scale sequencing of human cancer genomes. To accurately interpret experiments that introduce additional mutations, an understanding of the somatic genetic profile and evolution of GEMM tumors is necessary. Here, we performed whole-exome sequencing of tumors from three GEMMs of lung adenocarcinoma driven by mutant epidermal growth factor receptor (EGFR), mutant Kirsten rat sarcoma viral oncogene homolog (Kras), or overexpression of MYC proto-oncogene. Tumors from EGFR- and Kras-driven models exhibited, respectively, 0.02 and 0.07 nonsynonymous mutations per megabase, a dramatically lower average mutational frequency than observed in human lung adenocarcinomas. Tumors from models driven by strong cancer drivers (mutant EGFR and Kras) harbored few mutations in known cancer genes, whereas tumors driven by MYC, a weaker initiating oncogene in the murine lung, acquired recurrent clonal oncogenic Kras mutations. In addition, although EGFR- and Kras-driven models both exhibited recurrent whole-chromosome DNA copy number alterations, the specific chromosomes altered by gain or loss were different in each model. These data demonstrate that GEMM tumors exhibit relatively simple somatic genotypes compared with human cancers of a similar type, making these autochthonous model systems useful for additive engineering approaches to assess the potential of novel mutations on tumorigenesis, cancer progression, and drug sensitivity. PMID:27702896

SU-E-T-182: Feasibility of Dose Painting by Numbers in Proton Therapy with Contour-Driven Plan Optimization

International Nuclear Information System (INIS)

Montero, A Barragan; Differding, S; Lee, J; Sterpin, E

2014-01-01

Purpose: The work aims to 1) prove the feasibility of dose painting by numbers (DPBN) in proton therapy with usual contour-driven plan optimization and 2) compare the achieved plan quality to that of rotational IMRT. Methods: For two patients with head and neck cancers, voxel-by-voxel prescription to the target volume (PTV-PET) was calculated from 18 FDG-PET images and converted to contour-based prescription by defining several sub-contours. Treatments were planned with RayStation (RaySearch Laboratories, Sweden) and proton pencil beam scanning modality. In order to determine the optimal plan parameters to approach the DPBN prescription, the effect of the number of fields, number of sub-contours and use of range shifter were tested separately on each patient. The number of sub-contours were increased from 3 to 11 while the number of fields were set to 3, 5, 7 and 9. Treatment plans were also optimized on two rotational IMRT systems (TomoTherapy and Varian RapidArc) using previously published guidelines. Results: For both patients, more than 99% of the PTV-PET received at least 95% of the prescribed dose while less than 1% of the PTV-PET received more than 105%, which demonstrates the feasibility of the treatment. Neither the use of a range shifter nor the increase of the number of fields had a significant influence on PTV coverage. Plan quality increased when increasing number of fields up to 7 or 9 and slightly decreased for a bigger number of sub-contours. Good OAR sparing is achieved while keeping high plan quality. Finally, proton therapy achieved significantly better plan quality than rotational IMRT. Conclusion: Voxel-by-voxel prescriptions can be approximated accurately in proton therapy using a contour-driven optimization. Target coverage is nearly insensitive to the number of fields and the use of a range shifter. Finally, plan quality assessment confirmed the superiority of proton therapy compared to rotational IMRT

Experiences in Teaching a Graduate Course on Model-Driven Software Development

Science.gov (United States)

Tekinerdogan, Bedir

2011-01-01

Model-driven software development (MDSD) aims to support the development and evolution of software intensive systems using the basic concepts of model, metamodel, and model transformation. In parallel with the ongoing academic research, MDSD is more and more applied in industrial practices. After being accepted both by a broad community of…

Data-driven modelling of LTI systems using symbolic regression

NARCIS (Netherlands)

Khandelwal, D.; Toth, R.; Van den Hof, P.M.J.

2017-01-01

The aim of this project is to automate the task of data-driven identification of dynamical systems. The underlying goal is to develop an identification tool that models a physical system without distinguishing between classes of systems such as linear, nonlinear or possibly even hybrid systems. Such

Data Driven Modelling of the Dynamic Wake Between Two Wind Turbines

DEFF Research Database (Denmark)

Knudsen, Torben; Bak, Thomas

2012-01-01

turbine. This paper establishes flow models relating the wind speeds at turbines in a farm. So far, research in this area has been mainly based on first principles static models and the data driven modelling done has not included the loading of the upwind turbine and its impact on the wind speed downwind......Wind turbines in a wind farm, influence each other through the wind flow. Downwind turbines are in the wake of upwind turbines and the wind speed experienced at downwind turbines is hence a function of the wind speeds at upwind turbines but also the momentum extracted from the wind by the upwind....... This paper is the first where modern commercial mega watt turbines are used for data driven modelling including the upwind turbine loading by changing power reference. Obtaining the necessary data is difficult and data is therefore limited. A simple dynamic extension to the Jensen wake model is tested...

Simulation-Driven Development and Optimization of a High-Performance Six-Dimensional Wrist Force/Torque Sensor

Directory of Open Access Journals (Sweden)

Qiaokang LIANG

2010-05-01

Full Text Available This paper describes the Simulation-Driven Development and Optimization (SDDO of a six-dimensional force/torque sensor with high performance. By the implementation of the SDDO, the developed sensor possesses high performance such as high sensitivity, linearity, stiffness and repeatability simultaneously, which is hard for tranditional force/torque sensor. Integrated approach provided by software ANSYS was used to streamline and speed up the process chain and thereby to deliver results significantly faster than traditional approaches. The result of calibration experiment possesses some impressive characters, therefore the developed fore/torque sensor can be usefully used in industry and the methods of design can also be used to develop industrial product.

The Permanent Magnet Operating Mechanism of Double Coil Parallel Driven at a High Speed

Directory of Open Access Journals (Sweden)

WEI Xau-Lao

2017-02-01

Full Text Available Abstract:Operating mechanism is the main part of breaker，and the quality of breaker will directly influence the safe operation of power system. Because of the continuous improvement requirements of switch，in order to mak this actuator faster and more powerful closing，this paper proposes a double coil parallel driven permanent magnet actuator at a high speed. This paper expounds the working principle of single and double coil parallel driven permanent magnet actuator. It uses Ansoft building model and contrasts test results. In prance we designed and produced the single and double coil parallel driven permanent magnet actuator for experimental study. The simulation and experiment results show that double coil parallel driven permanent magnet actuator，compared with single coil parallel driven permanent magnet actuator，has a better and faster action performance. Thus，the double coil parallel driven permanent magnet actuator achieves a kind of optimization.

A Model-Driven Framework to Develop Personalized Health Monitoring

Directory of Open Access Journals (Sweden)

Algimantas Venčkauskas

2016-07-01

Full Text Available Both distributed healthcare systems and the Internet of Things (IoT are currently hot topics. The latter is a new computing paradigm to enable advanced capabilities in engineering various applications, including those for healthcare. For such systems, the core social requirement is the privacy/security of the patient information along with the technical requirements (e.g., energy consumption and capabilities for adaptability and personalization. Typically, the functionality of the systems is predefined by the patient’s data collected using sensor networks along with medical instrumentation; then, the data is transferred through the Internet for treatment and decision-making. Therefore, systems creation is indeed challenging. In this paper, we propose a model-driven framework to develop the IoT-based prototype and its reference architecture for personalized health monitoring (PHM applications. The framework contains a multi-layered structure with feature-based modeling and feature model transformations at the top and the application software generation at the bottom. We have validated the framework using available tools and developed an experimental PHM to test some aspects of the functionality of the reference architecture in real time. The main contribution of the paper is the development of the model-driven computational framework with emphasis on the synergistic effect of security and energy issues.

Single-beam bathymetry data collected in 2015 from Grand Bay, Alabama-Mississippi

Science.gov (United States)

DeWitt, Nancy T.; Stalk, Chelsea A.; Smith, Christopher G.; Locker, Stanley D.; Fredericks, Jake J.; McCloskey, Terrence A.; Wheaton, Cathryn J.

2017-12-01

As part of the Sea-level and Storm Impacts on Estuarine Environments and Shorelines (SSIEES) project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted a single-beam bathymetry survey within the estuarine, open-bay, and tidal creek environments of Grand Bay, Alabama-Mississippi, from May to June 2015. The goal of the SSIEES project is to assess the physical controls of sediment and material exchange between wetlands and estuarine environments along the northern Gulf of Mexico, specifically Grand Bay, Alabama-Mississippi; Vermilion Bay, Louisiana; and, along the east coast, within Chincoteague Bay, Virginia-Maryland. The data described in this report provide baseline bathymetric information for future research investigating wetland-marsh evolution, sediment transport, erosion, recent and long-term geomorphic change, and can also support the modeling of changes in response to restoration and storm impacts. The survey area encompasses more than 40 square kilometers of Grand Bay’s waters.

Following an Optimal Batch Bioreactor Operations Model

DEFF Research Database (Denmark)

Ibarra-Junquera, V.; Jørgensen, Sten Bay; Virgen-Ortíz, J.J.

2012-01-01

The problem of following an optimal batch operation model for a bioreactor in the presence of uncertainties is studied. The optimal batch bioreactor operation model (OBBOM) refers to the bioreactor trajectory for nominal cultivation to be optimal. A multiple-variable dynamic optimization of fed...... as the master system which includes the optimal cultivation trajectory for the feed flow rate and the substrate concentration. The “real” bioreactor, the one with unknown dynamics and perturbations, is considered as the slave system. Finally, the controller is designed such that the real bioreactor...

Bathymetry mapping using a GPS-sonar equipped remote control boat: Application in waste stabilisation ponds

Science.gov (United States)

Coggins, Liah; Ghadouani, Anas; Ghisalberti, Marco

2014-05-01

distribution, but also in calculating sludge accumulation rates, and in evaluating pond hydraulic efficiency (e.g., as input bathymetry for computational fluid dynamics models). This technology is not limited to application for wastewater management, and could potentially have a wider application in the monitoring of other small to medium water bodies, including reservoirs, channels, recreational water bodies, river beds, mine tailings dams and commercial ports.

A Model-Driven Approach for Telecommunications Network Services Definition

Science.gov (United States)

Chiprianov, Vanea; Kermarrec, Yvon; Alff, Patrick D.

Present day Telecommunications market imposes a short concept-to-market time for service providers. To reduce it, we propose a computer-aided, model-driven, service-specific tool, with support for collaborative work and for checking properties on models. We started by defining a prototype of the Meta-model (MM) of the service domain. Using this prototype, we defined a simple graphical modeling language specific for service designers. We are currently enlarging the MM of the domain using model transformations from Network Abstractions Layers (NALs). In the future, we will investigate approaches to ensure the support for collaborative work and for checking properties on models.

Conventional and novel control designs for direct driven PMSG wind turbines

Energy Technology Data Exchange (ETDEWEB)

Li, Shuhui; Haskew, Timothy A.; Xu, Ling [Department of Electrical and Computer Engineering, The University of Alabama, 317 Houser Hall, Tuscaloosa, AL 35487 (United States)

2010-03-15

With the advance of power electronic technology, direct driven permanent magnet synchronous generators (PMSG) have increasingly drawn interests to wind turbine manufactures. This paper studies and compares conventional and a novel control designs for a direct driven PMSG wind turbine. The paper presents transient and steady-state models of a PMSG system in a d-q reference frame. Then, general PMSG characteristics are investigated in the rotor-flux-oriented frame. A shortage of conventional control mechanisms is studied analytically and through computer simulation. A novel direct-current based d-q vector control technique is proposed by integrating fuzzy, adaptive and traditional PID control technologies in an optimal control configuration. Comparison study demonstrates that the proposed control approach, having superior performance in various aspects, is effective not only in achieving desired PMSG control objectives but also in improving the optimal performance of the overall system. (author)

Integrating FMEA in a Model-Driven Methodology

Science.gov (United States)

Scippacercola, Fabio; Pietrantuono, Roberto; Russo, Stefano; Esper, Alexandre; Silva, Nuno

2016-08-01

Failure Mode and Effects Analysis (FMEA) is a well known technique for evaluating the effects of potential failures of components of a system. FMEA demands for engineering methods and tools able to support the time- consuming tasks of the analyst. We propose to make FMEA part of the design of a critical system, by integration into a model-driven methodology. We show how to conduct the analysis of failure modes, propagation and effects from SysML design models, by means of custom diagrams, which we name FMEA Diagrams. They offer an additional view of the system, tailored to FMEA goals. The enriched model can then be exploited to automatically generate FMEA worksheet and to conduct qualitative and quantitative analyses. We present a case study from a real-world project.

South Africa’s freight rail reform: A demand-driven perspective

Directory of Open Access Journals (Sweden)

Jan H. Havenga

2014-11-01

Full Text Available During the 20th century, freight transport in South Africa was employed to attain politicoeconomic ideals, resulting in the overprotection of rail and overregulation of road transport. Increasing industry pressure, combined with the international deregulation trend, led to deregulation in 1988. Myopia resulted in a rail investment hiatus and exponential growth in high-value, long-distance road transport, causing excessive logistics and externality costs for the country. The aim of this study was to propose a freight rail reform agenda based on, (1 lessons from past freight transport policy efforts and (2 the results of freight transport market segmentation driven by models developed over the past two decades. For the study, freight flows were modelled by disaggregating the national input–output model into 372 origin–destination pairs and 71 commodity groups, followed by distance decay gravitymodelling. Logistics costs were calculated by relating commodity-level freight flows to the costs of fulfilling associated logistical functions. The standard management approach of founding strategy development on market-driven segmentation provides a neutral input to steer rail reform discussions in South Africa. Market segmentation points to a dualistic rail reform agenda, enabling both a profit-driven core and a development-driven branch line network. Freight flow insights are steering the policy reform debate towards long-term freight strategy development and optimal freight logistics network design.

Modelling Laccoliths: Fluid-Driven Fracturing in the Lab

Science.gov (United States)

Ball, T. V.; Neufeld, J. A.

2017-12-01

Current modelling of the formation of laccoliths neglects the necessity to fracture rock layers for propagation to occur [1]. In magmatic intrusions at depth the idea of fracture toughness is used to characterise fracturing, however an analogue for near surface intrusions has yet to be explored [2]. We propose an analytical model for laccolith emplacement that accounts for the energy required to fracture at the tip of an intrusion. For realistic physical parameters we find that a lag region exists between the fluid magma front and the crack tip where large negative pressures in the tip cause volatiles to exsolve from the magma. Crucially, the dynamics of this tip region controls the spreading due to the competition between viscous forces and fracture energy. We conduct a series of complementary experiments to investigate fluid-driven fracturing of adhered layers and confirm the existence of two regimes: viscosity dominant spreading, controlled by the pressure in the lag region, and fracture energy dominant spreading, controlled by the energy required to fracture layers. Our experiments provide the first observations, and evolution, of a vapour tip. These experiments and our simplified model provide insight into the key physical processes in near surface magmatic intrusions with applications to fluid-driven fracturing more generally. Michaut J. Geophys. Res. 116(B5), B05205. Bunger & Cruden J. Geophys. Res. 116(B2), B02203.

BedMachine v3: Complete Bed Topography and Ocean Bathymetry Mapping of Greenland From Multibeam Echo Sounding Combined With Mass Conservation

DEFF Research Database (Denmark)

Morlighem, M.; Williams, C. N.; Rignot, E.

2017-01-01

Greenland's bed topography is a primary control on ice flow, grounding line migration, calving dynamics, and subglacial drainage. Moreover, fjord bathymetry regulates the penetration of warm Atlantic water (AW) that rapidly melts and undercuts Greenland's marine‐terminating glaciers. Here we...... present a new compilation of Greenland bed topography that assimilates seafloor bathymetry and ice thickness data through a mass conservation approach. A new 150 m horizontal resolution bed topography/bathymetric map of Greenland is constructed with seamless transitions at the ice/ocean interface...

Detecting Trend and Seasonal Changes in Bathymetry Derived from HICO Imagery: A Case Study of Shark Bay, Western Australia

Science.gov (United States)

Garcia, Rodrigo A.; Fearns, Peter R. C. S.; Mckinna, Lachlan I. W.

2014-01-01

The Hyperspectral Imager for the Coastal Ocean (HICO) aboard the International Space Station has offered for the first time a dedicated space-borne hyperspectral sensor specifically designed for remote sensing of the coastal environment. However, several processing steps are required to convert calibrated top-of-atmosphere radiances to the desired geophysical parameter(s). These steps add various amounts of uncertainty that can cumulatively render the geophysical parameter imprecise and potentially unusable if the objective is to analyze trends and/or seasonal variability. This research presented here has focused on: (1) atmospheric correction of HICO imagery; (2) retrieval of bathymetry using an improved implementation of a shallow water inversion algorithm; (3) propagation of uncertainty due to environmental noise through the bathymetry retrieval process; (4) issues relating to consistent geo-location of HICO imagery necessary for time series analysis, and; (5) tide height corrections of the retrieved bathymetric dataset. The underlying question of whether a temporal change in depth is detectable above uncertainty is also addressed. To this end, nine HICO images spanning November 2011 to August 2012, over the Shark Bay World Heritage Area, Western Australia, were examined. The results presented indicate that precision of the bathymetric retrievals is dependent on the shallow water inversion algorithm used. Within this study, an average of 70% of pixels for the entire HICO-derived bathymetry dataset achieved a relative uncertainty of less than +/-20%. A per-pixel t-test analysis between derived bathymetry images at successive timestamps revealed observable changes in depth to as low as 0.4 m. However, the present geolocation accuracy of HICO is relatively poor and needs further improvements before extensive time series analysis can be performed.

Optimization in liner shipping

DEFF Research Database (Denmark)

Brouer, Berit Dangaard; Karsten, Christian Vad; Pisinger, David

2017-01-01

Seaborne trade is the lynchpin in almost every international supply chain, and about 90% of non-bulk cargo worldwide is transported by container. In this survey we give an overview of data-driven optimization problems in liner shipping. Research in liner shipping is motivated by a need for handling...... still more complex decision problems, based on big data sets and going across several organizational entities. Moreover, liner shipping optimization problems are pushing the limits of optimization methods, creating a new breeding ground for advanced modelling and solution methods. Starting from liner...... shipping network design, we consider the problem of container routing and speed optimization. Next, we consider empty container repositioning and stowage planning as well as disruption management. In addition, the problem of bunker purchasing is considered in depth. In each section we give a clear problem...

Ion beam driven expansion of super-range multilayer plane targets

International Nuclear Information System (INIS)

Piriz, A.R.

1987-08-01

The expansion of a multilayer plane target driven by an ion beam which has a range shorter than the thickness of the slab is described by means of a simple analytic model. The effect of a two-layer structure is studied and criteria for the optimization of the kinetic energy of the unheated part of the slab, the payload, are set. (author). 14 refs, 3 figs

CRED 40 m Gridded bathymetry of Howland Island, Pacific Remote Island Areas, Central Pacific (Arc ASCII Format)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded (40 m cell size) bathymetry of the shelf and slope environments of Howland Island, Pacific Remote Island Areas, Central Pacific. Almost complete bottom...

CRED 5 m Gridded bathymetry of Jarvis Island, Pacific Remote Island Areas, Central Pacific (Arc ASCII Format)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded (5 m cell size) bathymetry of the shelf and slope environments of Jarvis Island, Pacific Remote Island Areas, Central Pacific. Almost complete bottom...

CRED 40 m Gridded bathymetry of Baker Island, Pacific Remote Island Areas, Central Pacific (Arc ASCII Format)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded (40 m cell size) bathymetry of the shelf and slope environments of Baker Island, Pacific Remote Island Areas, Central Pacific. Almost complete bottom...

Web Services and Model-Driven Enterprise Information Services. Proceedings of the Joint Workshop on Web Services and Model-Driven Enterprise Information Services, WSMDEIS 2005.

NARCIS (Netherlands)

Bevinakoppa, S.; Ferreira Pires, Luis; Hammoudi, S.

2005-01-01

Web services and Model-driven development are two emerging research fields and have been receiving a lot of attention in the recent years. New approaches on these two areas can bring many benefits to the development of information systems, distribution flexibility, interoperability, maintainability

Data-driven remaining useful life prognosis techniques stochastic models, methods and applications

CERN Document Server

Si, Xiao-Sheng; Hu, Chang-Hua

2017-01-01

This book introduces data-driven remaining useful life prognosis techniques, and shows how to utilize the condition monitoring data to predict the remaining useful life of stochastic degrading systems and to schedule maintenance and logistics plans. It is also the first book that describes the basic data-driven remaining useful life prognosis theory systematically and in detail. The emphasis of the book is on the stochastic models, methods and applications employed in remaining useful life prognosis. It includes a wealth of degradation monitoring experiment data, practical prognosis methods for remaining useful life in various cases, and a series of applications incorporated into prognostic information in decision-making, such as maintenance-related decisions and ordering spare parts. It also highlights the latest advances in data-driven remaining useful life prognosis techniques, especially in the contexts of adaptive prognosis for linear stochastic degrading systems, nonlinear degradation modeling based pro...

A model-driven approach to information security compliance

Science.gov (United States)

Correia, Anacleto; Gonçalves, António; Teodoro, M. Filomena

2017-06-01

The availability, integrity and confidentiality of information are fundamental to the long-term survival of any organization. Information security is a complex issue that must be holistically approached, combining assets that support corporate systems, in an extended network of business partners, vendors, customers and other stakeholders. This paper addresses the conception and implementation of information security systems, conform the ISO/IEC 27000 set of standards, using the model-driven approach. The process begins with the conception of a domain level model (computation independent model) based on information security vocabulary present in the ISO/IEC 27001 standard. Based on this model, after embedding in the model mandatory rules for attaining ISO/IEC 27001 conformance, a platform independent model is derived. Finally, a platform specific model serves the base for testing the compliance of information security systems with the ISO/IEC 27000 set of standards.

Knowledge management driven leadership, culture and innovation success – an integrative model

OpenAIRE

Zieba, M.; Schivinski, Bruno

2015-01-01

Purpose - This article examines the relation between knowledge management (KM) driven leadership, culture and innovation success of knowledge-intensive small and medium sized companies. By building on the previously reported research on leadership, culture, innovation , and knowledge management, we synergistically integrate d KM-driven leadership and innovation success while exploring the meditational role of culture in that. Design/methodology/approach - A conceptual model comprising three c...

Data driven modelling of vertical atmospheric radiation

International Nuclear Information System (INIS)

Antoch, Jaromir; Hlubinka, Daniel

2011-01-01

In the Czech Hydrometeorological Institute (CHMI) there exists a unique set of meteorological measurements consisting of the values of vertical atmospheric levels of beta and gamma radiation. In this paper a stochastic data-driven model based on nonlinear regression and on nonhomogeneous Poisson process is suggested. In the first part of the paper, growth curves were used to establish an appropriate nonlinear regression model. For comparison we considered a nonhomogeneous Poisson process with its intensity based on growth curves. In the second part both approaches were applied to the real data and compared. Computational aspects are briefly discussed as well. The primary goal of this paper is to present an improved understanding of the distribution of environmental radiation as obtained from the measurements of the vertical radioactivity profiles by the radioactivity sonde system. - Highlights: → We model vertical atmospheric levels of beta and gamma radiation. → We suggest appropriate nonlinear regression model based on growth curves. → We compare nonlinear regression modelling with Poisson process based modeling. → We apply both models to the real data.

Data and Dynamics Driven Approaches for Modelling and Forecasting the Red Sea Chlorophyll

KAUST Repository

Dreano, Denis

2017-05-31

Phytoplankton is at the basis of the marine food chain and therefore play a fundamental role in the ocean ecosystem. However, the large-scale phytoplankton dynamics of the Red Sea are not well understood yet, mainly due to the lack of historical in situ measurements. As a result, our knowledge in this area relies mostly on remotely-sensed observations and large-scale numerical marine ecosystem models. Models are very useful to identify the mechanisms driving the variations in chlorophyll concentration and have practical applications for fisheries operation and harmful algae blooms monitoring. Modelling approaches can be divided between physics- driven (dynamical) approaches, and data-driven (statistical) approaches. Dynamical models are based on a set of differential equations representing the transfer of energy and matter between different subsets of the biota, whereas statistical models identify relationships between variables based on statistical relations within the available data. The goal of this thesis is to develop, implement and test novel dynamical and statistical modelling approaches for studying and forecasting the variability of chlorophyll concentration in the Red Sea. These new models are evaluated in term of their ability to efficiently forecast and explain the regional chlorophyll variability. We also propose innovative synergistic strategies to combine data- and physics-driven approaches to further enhance chlorophyll forecasting capabilities and efficiency.

CONFOLD2: improved contact-driven ab initio protein structure modeling.

Science.gov (United States)

Adhikari, Badri; Cheng, Jianlin

2018-01-25

Contact-guided protein structure prediction methods are becoming more and more successful because of the latest advances in residue-residue contact prediction. To support contact-driven structure prediction, effective tools that can quickly build tertiary structural models of good quality from predicted contacts need to be developed. We develop an improved contact-driven protein modelling method, CONFOLD2, and study how it may be effectively used for ab initio protein structure prediction with predicted contacts as input. It builds models using various subsets of input contacts to explore the fold space under the guidance of a soft square energy function, and then clusters the models to obtain the top five models. CONFOLD2 obtains an average reconstruction accuracy of 0.57 TM-score for the 150 proteins in the PSICOV contact prediction dataset. When benchmarked on the CASP11 contacts predicted using CONSIP2 and CASP12 contacts predicted using Raptor-X, CONFOLD2 achieves a mean TM-score of 0.41 on both datasets. CONFOLD2 allows to quickly generate top five structural models for a protein sequence when its secondary structures and contacts predictions at hand. The source code of CONFOLD2 is publicly available at https://github.com/multicom-toolbox/CONFOLD2/ .

A Model-Driven Methodology for Big Data Analytics-as-a-Service

OpenAIRE

Damiani, Ernesto; Ardagna, Claudio Agostino; Ceravolo, Paolo; Bellandi, Valerio; Bezzi, Michele; Hebert, Cedric

2017-01-01

The Big Data revolution has promised to build a data-driven ecosystem where better decisions are supported by enhanced analytics and data management. However, critical issues still need to be solved in the road that leads to commodization of Big Data Analytics, such as the management of Big Data complexity and the protection of data security and privacy. In this paper, we focus on the first issue and propose a methodology based on Model Driven Engineering (MDE) that aims to substantially lowe...

Dynamic optimization deterministic and stochastic models

CERN Document Server

Hinderer, Karl; Stieglitz, Michael

2016-01-01

This book explores discrete-time dynamic optimization and provides a detailed introduction to both deterministic and stochastic models. Covering problems with finite and infinite horizon, as well as Markov renewal programs, Bayesian control models and partially observable processes, the book focuses on the precise modelling of applications in a variety of areas, including operations research, computer science, mathematics, statistics, engineering, economics and finance. Dynamic Optimization is a carefully presented textbook which starts with discrete-time deterministic dynamic optimization problems, providing readers with the tools for sequential decision-making, before proceeding to the more complicated stochastic models. The authors present complete and simple proofs and illustrate the main results with numerous examples and exercises (without solutions). With relevant material covered in four appendices, this book is completely self-contained.