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Sample records for model mm5 driven

  1. Statistical Studies of Mesoscale Forecast Models MM5 and WRF

    National Research Council Canada - National Science Library

    Henmi, Teizi

    2004-01-01

    ... models were carried out and the results were compared with surface observation data. Both models tended to overforecast temperature and dew-point temperature, although the correlation coefficients between forecast and observations were fairly high...

  2. 2-way coupling the hydrological land surface model PROMET with the regional climate model MM5

    Directory of Open Access Journals (Sweden)

    F. Zabel

    2013-05-01

    Full Text Available Most land surface hydrological models (LSHMs consider land surface processes (e.g. soil–plant–atmosphere interactions, lateral water flows, snow and ice in a spatially detailed manner. The atmosphere is considered as exogenous driver, neglecting feedbacks between the land surface and the atmosphere. On the other hand, regional climate models (RCMs generally simulate land surface processes through coarse descriptions and spatial scales but include land–atmosphere interactions. What is the impact of the differently applied model physics and spatial resolution of LSHMs on the performance of RCMs? What feedback effects are induced by different land surface models? This study analyses the impact of replacing the land surface module (LSM within an RCM with a high resolution LSHM. A 2-way coupling approach was applied using the LSHM PROMET (1 × 1 km2 and the atmospheric part of the RCM MM5 (45 × 45 km2. The scaling interface SCALMET is used for down- and upscaling the linear and non-linear fluxes between the model scales. The change in the atmospheric response by MM5 using the LSHM is analysed, and its quality is compared to observations of temperature and precipitation for a 4 yr period from 1996 to 1999 for the Upper Danube catchment. By substituting the Noah-LSM with PROMET, simulated non-bias-corrected near-surface air temperature improves for annual, monthly and daily courses when compared to measurements from 277 meteorological weather stations within the Upper Danube catchment. The mean annual bias was improved from −0.85 to −0.13 K. In particular, the improved afternoon heating from May to September is caused by increased sensible heat flux and decreased latent heat flux as well as more incoming solar radiation in the fully coupled PROMET/MM5 in comparison to the NOAH/MM5 simulation. Triggered by the LSM replacement, precipitation overall is reduced; however simulated precipitation amounts are still of high uncertainty, both

  3. A shallow convection parameterization for the non-hydrostatic MM5 mesoscale model

    Energy Technology Data Exchange (ETDEWEB)

    Seaman, N.L.; Kain, J.S.; Deng, A. [Pennsylvania State Univ., University Park, PA (United States)

    1996-04-01

    A shallow convection parameterization suitable for the Pennsylvannia State University (PSU)/National Center for Atmospheric Research nonhydrostatic mesoscale model (MM5) is being developed at PSU. The parameterization is based on parcel perturbation theory developed in conjunction with a 1-D Mellor Yamada 1.5-order planetary boundary layer scheme and the Kain-Fritsch deep convection model.

  4. Surface Energy Balance in Jakarta and Neighboring Regions As Simulated Using Fifth Mesoscale Model (MM5

    Directory of Open Access Journals (Sweden)

    Yopi Ilhamsyah

    2014-04-01

    Full Text Available The objective of the present research was to assess the surface energy balance particularly in terms of the computed surface energy and radiation balance and the development of boundary layer over Jakarta and Neighboring Regions (JNR by means of numerical model of fifth generation of Mesoscale Model (MM5. The MM5 with four domains of 9 kilometers in spatial resolution presenting the outermost and the innermost of JNR is utilized. The research focuses on the third and fourth domains covering the entire JNR. The description between radiation and energy balance at the surface is obtained from the model. The result showed that energy balance is higher in the city area during daytime. Meanwhile, energy components, e.g., surface sensible and latent heat flux showed that at the sea and in the city areas were higher than other areas. Moreover, ground flux showed eastern region was higher than others. In general, radiation and energy balance was higher in the daytime and lower in the nighttime for all regions. The calculation of Bowen Ratio, the ratio of surface sensible and latent heat fluxes, was also higher in the city area, reflecting the dominations of urban and built-up land in the region. Meanwhile, Bowen Ratio in the rural area dominated by irrigated cropland was lower. It is consistent with changes of land cover properties, e.g. albedo, soil moisture, and thermal characteristics. In addition, the boundary layer is also higher in the city. Meanwhile western region dominated by suburban showed higher boundary layer instead of eastern region.

  5. Spatiao – Temporal Evaluation and Comparison of MM5 Model using Similarity Algorithm

    Directory of Open Access Journals (Sweden)

    N. Siabi

    2016-02-01

    Full Text Available Introduction temporal and spatial change of meteorological and environmental variables is very important. These changes can be predicted by numerical prediction models over time and in different locations and can be provided as spatial zoning maps with interpolation methods such as geostatistics (16, 6. But these maps are comparable to each other as visual, qualitative and univariate for a limited number of maps (15. To resolve this problem the similarity algorithm is used. This algorithm is a simultaneous comparison method to a large number of data (18. Numerical prediction models such as MM5 were used in different studies (10, 22, and 23. But a little research is done to compare the spatio-temporal similarity of the models with real data quantitatively. The purpose of this paper is to integrate geostatistical techniques with similarity algorithm to study the spatial and temporal MM5 model predicted results with real data. Materials and Methods The study area is north east of Iran. 55 to 61 degrees of longitude and latitude is 30 to 38 degrees. Monthly and annual temperature and precipitation actual data for the period of 1990-2010 was received from the Meteorological Agency and Department of Energy. MM5 Model Data, with a spatial resolution 0.5 × 0.5 degree were downloaded from the NASA website (5. GS+ and ArcGis software were used to produce each variable map. We used multivariate methods co-kriging and kriging with an external drift by applying topography and height as a secondary variable via implementing Digital Elevation Model. (6,12,14. Then the standardize and similarity algorithms (9,11 was applied by programming in MATLAB software to each map grid point. The spatial and temporal similarities between data collections and model results were obtained by F values. These values are between 0 and 0.5 where the value below 0.2 indicates good similarity and above 0.5 shows very poor similarity. The results were plotted on maps by MATLAB

  6. SIMULASI KESEIMBANGAN ENERGI PERMUKAAN DI JAKARTA DAN SEKITARNYA MENGGUNAKAN MODEL NUMERIK MM5

    Directory of Open Access Journals (Sweden)

    Yopi Ilhamsyah

    2016-03-01

    Full Text Available Studi simulasi keseimbangan energi permukaan di Jakarta dan daerah sekitarnya menggunakan model numerik Fifth-Generation Penn State/NCAR Mesoscale Model (MM5 telah dilakukan. Empat domain dengan resolusi spasial 9 km yang menggambarkan daerah Jakarta dan sekitarnya disimulasikan selama 5 hari pada tanggal 04-08 Agustus 2004 untuk memperoleh hubungan radiasi dan keseimbangan energi di wilayah tersebut. Hasil menunjukkan bahwa keseimbangan energi lebih tinggi pada siang hari terjadi di perkotaan dibandingkan daerah lainnya. Sementara itu, komponen energi seperti fluks bahang terindera dan laten di permukaan masing-masing menunjukkan bahwa wilayah laut dan perkotaan lebih tinggi daripada daerah lainnya. Sebaliknya, fluks bahang tanah menunjukkan daerah rural di bagian timur Jakarta lebih tinggi dibandingkan daerah lainnya. Secara umum, keseimbangan radiasi dan energi pada siang hari lebih tinggi daripada malam hari di seluruh daerah. Rasio Bowen di wilayah kota yang mencerminkan kawasan bangunan dan perkotaan lebih tinggi daripada di daerah rural yang didominasi oleh lahan pertanian beririgasi. Hal ini sesuai dengan perubahan sifat fisik tutupan lahan seperti albedo, kelembaban tanah dan karakteristik bahang.    A study of surface energy balance simulation in Jakarta and surrounding areas by using Fifth-Generation Penn State/NCAR Mesoscale Model (MM5 numerical model was done. Four domains that presented the outermost and the innermost of Jakarta and surrounding areaswere utilized. All domains have spatial resolutions of 9 km. Model was simulated for 5 days on August 4-8, 2004. The relation of radiation and energy balance at the surface were derived from model output. The result showed that energy balance was higher in the city during daytime. Meanwhile, energy component, i.e., surface sensible and latent heat flux showed that sea and city were higher than others, respectively. Moreover, ground flux showed eastern rural areawas higher than others

  7. MM5 simulations for air quality modeling: An application to a coastal area with complex terrain

    Science.gov (United States)

    Lee, Sang-Mi; Princevac, Marko; Mitsutomi, Satoru; Cassmassi, Joe

    A series of modifications were implemented in MM5 simulation in order to account for wind along the Santa Clarita valley, a north-south running valley located in the north of Los Angeles. Due to high range mountains in the north and the east of the Los Angeles Air Basin, sea breeze entering Los Angeles exits into two directions. One branch moves toward the eastern part of the basin and the other to the north toward the Santa Clarita valley. However, the northward flow has not been examined thoroughly nor simulated successfully in the previous studies. In the present study, we proposed four modifications to trigger the flow separation. They were (1) increasing drag over the ocean, (2) increasing soil moisture content, (3) selective observational nudging, and (4) one-way nesting for the innermost domain. The Control run overpredicted near-surface wind speed over the ocean and sensible heat flux, in an urbanized area, which justifies the above 1st and 2nd modification. The Modified run provided an improvement in near-surface temperature, sensible heat flux and wind fields including southeasterly flow along the Santa Clarita valley. The improved MM5 wind field triggered a transport to the Santa Clarita valley generating a plume elongated from an urban center to the north, which did not exist in MM5 Control run. In all, the modified MM5 fields yielded better agreement in both CO and O3 simulations especially in the Santa Clarita area.

  8. Simulation of coastal winds along the central west coast of India using the MM5 mesoscale model

    Digital Repository Service at National Institute of Oceanography (India)

    Pushpadas, D.; Vethamony, P.; Sudheesh, K.; George, S.; Babu, M.T.; Nair, T.M.B.

    A high-resolution mesoscale numerical model (MM5) has been used to study the coastal atmospheric circulation of the central west coast of India, and Goa in particular. The model is employed with three nested domains. The innermost domain of 3 km...

  9. Temperature sensitivity to the land-surface model in MM5 climate simulations over the Iberian Peninsula

    Energy Technology Data Exchange (ETDEWEB)

    Jerez, Sonia; Montavez, Juan P.; Gomez-Navarro, Juan J.; Jimenez-Guerrero, Pedro [Dept. de Fisica, Univ. de Murcia (Spain); Jimenez, Jose M.; Gonzalez-Rouco, Jesus F. [Dept. de Astrofisica y CC. de la Atmosfera, Univ. Complutense de Madrid (Spain)

    2010-06-15

    Three different Land Surface Models have been used in three high resolution climate simulations performed with the mesoscale model MM5 over the Iberian Peninsula. The main difference among them lies in the soil moisture treatment, which is dynamically modelled by only two of them (Noah and Pleim and Xiu models), while in the simplest model (Simple Five-Layers) it is fixed to climatological values. The simulated period covers 1958-2002, using the ERA40 reanalysis data as driving conditions. Focusing on near-surface air temperature, this work evaluates the skill of each simulation in reproducing mean values and temporal variability, by comparing the simulations with observed temperature series. When the simplest simulation was analyzed, the greatest discrepances were observed for the summer season, when both, the mean values and the temporal variability of the temperature series, were badly underestimated. These weaknesses are largely overcome in the other two simulations (performed by coupling a more advanced soil model to MM5), and there was greater concordance between the simulated and observed spatial patterns. The influence of a dynamic soil moisture parameterization and, therefore, a more realistic simulation of the latent and sensible heat fluxes between the land and the atmosphere, helps to explain these results. (orig.)

  10. Application of WRF/Chem over East Asia: Part I. Model evaluation and intercomparison with MM5/CMAQ

    Science.gov (United States)

    Zhang, Yang; Zhang, Xin; Wang, Litao; Zhang, Qiang; Duan, Fengkui; He, Kebin

    2016-01-01

    In this work, the application of the online-coupled Weather Research and Forecasting model with chemistry (WRF/Chem) version 3.3.1 is evaluated over East Asia for January, April, July, and October 2005 and compared with results from a previous application of an offline model system, i.e., the Mesoscale Model and Community Multiple Air Quality modeling system (MM5/CMAQ). The evaluation of WRF/Chem is performed using multiple observational datasets from satellites and surface networks in mainland China, Hong Kong, Taiwan, and Japan. WRF/Chem simulates well specific humidity (Q2) and downward longwave and shortwave radiation (GLW and GSW) with normalized mean biases (NMBs) within 24%, but shows moderate to large biases for temperature at 2-m (T2) (NMBs of -9.8% to 75.6%) and precipitation (NMBs of 11.4-92.7%) for some months, and wind speed at 10-m (WS10) (NMBs of 66.5-101%), for all months, indicating some limitations in the YSU planetary boundary layer scheme, the Purdue Lin cloud microphysics, and the Grell-Devenyi ensemble scheme. WRF/Chem can simulate the column abundances of gases reasonably well with NMBs within 30% for most months but moderately to significantly underpredicts the surface concentrations of major species at all sites in nearly all months with NMBs of -72% to -53.8% for CO, -99.4% to -61.7% for NOx, -84.2% to -44.5% for SO2, -63.9% to -25.2% for PM2.5, and -68.9% to 33.3% for PM10, and aerosol optical depth in all months except for October with NMBs of -38.7% to -16.2%. The model significantly overpredicts surface concentrations of O3 at most sites in nearly all months with NMBs of up to 160.3% and NO3- at the Tsinghua site in all months. Possible reasons for large underpredictions include underestimations in the anthropogenic emissions of CO, SO2, and primary aerosol, inappropriate vertical distributions of emissions of SO2 and NO2, uncertainties in upper boundary conditions (e.g., for O3 and CO), missing or inaccurate model representations (e

  11. Simulation of atmospheric temperature inversions over greater cairo using the MM5 Meso-Scale atmospheric model

    International Nuclear Information System (INIS)

    Kandil, H.A.; Elhadidi, B.M.; Kader, A. A.; Moaty, A.A.; Sherif, A.O.

    2006-01-01

    Air pollution episodes have been recorded in Cairo, during the fall season, since 1999, as a result of specific meteorological conditions combined with large quantity of pollutants created by several ground-based sources. The main reason for the smog-like episodes (black clouds) is adverse weather conditions with low and variable winds, high humidity and strong temperature inversions in the few-hundred meters above the ground. The two important types of temperature inversion affecting the air pollution are surface or ground (radiation) inversion and subsidence (elevated) inversion. The surface temperature inversion is associated with a rapid decrease in the ground surface temperature with the simultaneous existence of warm air in the lower troposphere. The inversion develops at dusk and continues until the surface warms again the following day. Pollutants emitted during the night are caught under this i nversion lid. S ubsidence inversion forms when warm air masses move over colder air masses. The inversion develops with a stagnating high-pressure system (generally associated with fair weather). Under these conditions, the pressure gradient becomes progressively weaker so that winds become light. These light winds greatly reduce the horizontal transport and dispersion of pollutants. At the same time, the subsidence inversion acts as a barrier to the vertical dispersion of the pollutants. In this study, the Penn State/NCAR meso -scale model (MM5) is used to simulate the temperature inversion phenomenon over Greater Cairo region during the fall season of 2004. Accurate computations of the heat transfer at the surface are needed to capture this phenomenon. This can only be achieved by high-resolution simulations in both horizontal and vertical directions. Hence, for accurate simulation of the temperature inversion over Greater Cairo, four nested domains of resolutions of 27 km, 9 km, 3 km and 1 km, respectively, were used in the horizontal planes. Furthermore, 42

  12. Sensitivity of the Community Multiscale Air Quality (CMAQ model v4.7 results for the eastern United States to MM5 and WRF meteorological drivers

    Directory of Open Access Journals (Sweden)

    K. W. Appel

    2010-02-01

    Full Text Available This paper presents a comparison of the operational performances of two Community Multiscale Air Quality (CMAQ model v4.7 simulations that utilize input data from the 5th-generation Mesoscale Model (MM5 and the Weather Research and Forecasting (WRF meteorological models. Two sets of CMAQ model simulations were performed for January and August 2006. One set utilized MM5 meteorology (MM5-CMAQ and the other utilized WRF meteorology (WRF-CMAQ, while all other model inputs and options were kept the same. For January, predicted ozone (O3 mixing ratios were higher in the Southeast and lower Mid-west regions in the WRF-CMAQ simulation, resulting in slightly higher bias and error as compared to the MM5-CMAQ simulations. The higher predicted O3 mixing ratios are attributed to less dry deposition of O3 in the WRF-CMAQ simulation due to differences in the calculation of the vegetation fraction between the MM5 and WRF models. The WRF-CMAQ results showed better performance for particulate sulfate (SO42−, similar performance for nitrate (NO3, and slightly worse performance for nitric acid (HNO3, total carbon (TC and total fine particulate (PM2.5 mass than the corresponding MM5-CMAQ results. For August, predictions of O3 were notably higher in the WRF-CMAQ simulation, particularly in the southern United States, resulting in increased model bias. Concentrations of predicted particulate SO42− were lower in the region surrounding the Ohio Valley and higher along the Gulf of Mexico in the WRF-CMAQ simulation, contributing to poorer model performance. The primary causes of the differences in the MM5-CMAQ and WRF-CMAQ simulations appear to be due to differences in the calculation of wind speed, planetary boundary layer height, cloud cover and the friction velocity (u in the MM5 and WRF model simulations, while

  13. New method for model coupling using Stampi. Application to the coupling of atmosphere model (MM5) and land-surface model (SOLVEG)

    International Nuclear Information System (INIS)

    Nagai, Haruyasu

    2003-12-01

    A new method to couple atmosphere and land-surface models using the message passing interface (MPI) was proposed to develop an atmosphere-land model for studies on heat, water, and material exchanges around the land surface. A non-hydrostatic atmospheric dynamic model of Pennsylvania State University and National Center for Atmospheric Research (PUS/NCAR-MM5) and a detailed land surface model (SOLVEG) including the surface-layer atmosphere, soil, and vegetation developed at Japan Atomic Energy Research Institute (JAERI) are used as the atmosphere and land-surface models, respectively. Concerning the MPI, a message passing library named Stampi developed at JAERI that can be used between different parallel computers is used. The models are coupled by exchanging calculation results by using MPI on their independent parallel calculations. The modifications for this model coupling are easy, simply adding some modules for data exchanges to each model code without changing each model's original structure. Moreover, this coupling method is flexible and allows the use of independent time step and grid interval for each model. (author)

  14. Evaluating the performance of an integrated CALPUFF-MM5 modeling system for predicting SO{sub 2} emission from a refinery

    Energy Technology Data Exchange (ETDEWEB)

    Abdul-Wahab, Sabah Ahmed [Sultan Qaboos University, Department of Mechanical and Industrial Engineering, College of Engineering, Muscat (Oman); Ali, Sappurd [National Engineering and Scientific Commission (NESCOM), Islamabad (Pakistan); Sardar, Sabir; Irfan, Naseem [Pakistan Institute of Engineering and Applied Sciences (PIEAS), Islamabad (Pakistan); Al-Damkhi, Ali [Public Authority for Applied Education and Training (PAAET), Department of Environmental Sciences College of Health Sciences, Salmiyah (Kuwait)

    2011-12-15

    Oil refineries are one of the proven sources of environmental pollution as they emit more than 100 chemicals into the atmosphere including sulfur dioxide (SO{sub 2}). The dispersion patterns of SO{sub 2} from emissions of Sohar refinery was simulated by employing California Puff (CALPUFF) model integrated with state of the art meteorological Mesoscale Model (MM5). The results of this simulation were used to quantify the ground level concentrations of SO{sub 2} in and around the refinery. The evaluation of the CALPUFF and MM5 modeling system was carried out by comparing the estimated results with that of observed data of the same area. The predicted concentrations of SO{sub 2} agreed well with the observed data, with minor differences in magnitudes. In addition, the ambient air quality of the area was checked by comparing the model results with the regulatory limits for SO{sub 2} set by the Ministry of Environment and Climate Affairs (MECA) in Oman. From the analysis of results, it was found that the concentration of SO{sub 2} in the nearby communities of Sohar refinery is well within the regulatory limits specified by MECA. Based on these results, it was concluded that no health risk, due to SO{sub 2} emissions, is present in areas adjacent to the refinery. (orig.)

  15. Regional climate simulations over South America: sensitivity to model physics and to the treatment of lateral boundary conditions using the MM5 model

    Energy Technology Data Exchange (ETDEWEB)

    Solman, Silvina A. [CONICET-UBA, Centro de Investigaciones del Mar y la Atmosfera (CIMA), Buenos Aires (Argentina); Universidad de Buenos Aires, Departamento de Ciencias de la Atmosfera y los Oceanos. Facultad de Ciencias Exactas y Naturales, Buenos Aires (Argentina); Pessacg, Natalia L. [CONICET-UBA, Centro de Investigaciones del Mar y la Atmosfera (CIMA), Buenos Aires (Argentina)

    2012-01-15

    In this study the capability of the MM5 model in simulating the main mode of intraseasonal variability during the warm season over South America is evaluated through a series of sensitivity experiments. Several 3-month simulations nested into ERA40 reanalysis were carried out using different cumulus schemes and planetary boundary layer schemes in an attempt to define the optimal combination of physical parameterizations for simulating alternating wet and dry conditions over La Plata Basin (LPB) and the South Atlantic Convergence Zone regions, respectively. The results were compared with different observational datasets and model evaluation was performed taking into account the spatial distribution of monthly precipitation and daily statistics of precipitation over the target regions. Though every experiment was able to capture the contrasting behavior of the precipitation during the simulated period, precipitation was largely underestimated particularly over the LPB region, mainly due to a misrepresentation in the moisture flux convergence. Experiments using grid nudging of the winds above the planetary boundary layer showed a better performance compared with those in which no constrains were imposed to the regional circulation within the model domain. Overall, no single experiment was found to perform the best over the entire domain and during the two contrasting months. The experiment that outperforms depends on the area of interest, being the simulation using the Grell (Kain-Fritsch) cumulus scheme in combination with the MRF planetary boundary layer scheme more adequate for subtropical (tropical) latitudes. The ensemble of the sensitivity experiments showed a better performance compared with any individual experiment. (orig.)

  16. Application of TRMM PR and TMI Measurements to Assess Cloud Microphysical Schemes in the MM5 Model for a Winter Storm

    Science.gov (United States)

    Han, Mei; Braun, Scott A.; Olson, William S.; Persson, P. Ola G.; Bao, Jian-Wen

    2009-01-01

    Seen by the human eye, precipitation particles are commonly drops of rain, flakes of snow, or lumps of hail that reach the ground. Remote sensors and numerical models usually deal with information about large collections of rain, snow, and hail (or graupel --also called soft hail ) in a volume of air. Therefore, the size and number of the precipitation particles and how particles interact, evolve, and fall within the volume of air need to be represented using physical laws and mathematical tools, which are often implemented as cloud and precipitation microphysical parameterizations in numerical models. To account for the complexity of the precipitation physical processes, scientists have developed various types of such schemes in models. The accuracy of numerical weather forecasting may vary dramatically when different types of these schemes are employed. Therefore, systematic evaluations of cloud and precipitation schemes are of great importance for improvement of weather forecasts. This study is one such endeavor; it pursues quantitative assessment of all the available cloud and precipitation microphysical schemes in a weather model (MM5) through comparison with the observations obtained by National Aeronautics and Space Administration (NASA) s and Japan Aerospace Exploration Agency (JAXA) s Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and microwave imager (TMI). When satellite sensors (like PR or TMI) detect information from precipitation particles, they cannot directly observe the microphysical quantities (e.g., water species phase, density, size, and amount etc.). Instead, they tell how much radiation is absorbed by rain, reflected away from the sensor by snow or graupel, or reflected back to the satellite. On the other hand, the microphysical quantities in the model are usually well represented in microphysical schemes and can be converted to radiative properties that can be directly compared to the corresponding PR and TMI observations

  17. Evaluation of the tropospheric flows to a major Southern Hemisphere stratospheric warming event using NCEP/NCAR Reanalysis data with a PSU/NCAR nudging MM5V3 model

    Science.gov (United States)

    Wang, K.

    2008-04-01

    Previous studies of the exceptional 2002 Southern Hemisphere (SH) stratospheric warming event lead to some uncertainty, namely the question of whether excessive heat fluxes in the upper troposphere and lower stratosphere are a symptom or cause of the 2002 SH warming event. In this work, we use a hemispheric version of the MM5 model with nudging capability and we devised a novel approach to separately test the significance of the stratosphere and troposphere for this year. We paired the flow conditions from 2002 in the stratosphere and troposphere, respectively, against the conditions in 1998 (a year with displaced polar vortex) and in 1948 (a year with strong polar vortex that coincided with the geographical South Pole). Our experiments show that the flow conditions from below determine the stratospheric flow features over the polar region. Regardless of the initial stratospheric conditions in 1998 or 1948, when we simulated these past stratospheres with the troposphere/lower stratosphere conditions constrained to 2002 levels, the simulated middle stratospheres resemble those observed in 2002 stratosphere over the polar region. On the other hand, when the 2002 stratosphere was integrated with the troposphere/lower stratosphere conductions constrained to 1948 and 1998, respectively, the simulated middle stratospheric conditions over the polar region shift toward those of 1948 and 1998. Thus, our experiments further support the wave-forcing theory as the cause of the 2002 SH warming event.

  18. 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.

  19. 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.

  20. Same-source parallel implementation of the PSU/NCAR MM5

    Energy Technology Data Exchange (ETDEWEB)

    Michalakes, J.

    1997-12-31

    The Pennsylvania State/National Center for Atmospheric Research Mesoscale Model is a limited-area model of atmospheric systems, now in its fifth generation, MM5. Designed and maintained for vector and shared-memory parallel architectures, the official version of MM5 does not run on message-passing distributed memory (DM) parallel computers. The authors describe a same-source parallel implementation of the PSU/NCAR MM5 using FLIC, the Fortran Loop and Index Converter. The resulting source is nearly line-for-line identical with the original source code. The result is an efficient distributed memory parallel option to MM5 that can be seamlessly integrated into the official version.

  1. Assimilation of GMS-5 satellite winds using nudging method with MM5

    Science.gov (United States)

    Gao, Shanhong; Wu, Zengmao; Yang, Bo

    2006-09-01

    With the aid of Meteorological Information Composite and Processing System (MICAPS), satellite wind vectors derived from the Geostationary Meteorological Statellite-5 (GMS-5) and retrieved by National Satellite Meteorology Center of China (NSMC) can be obtained. Based on the nudging method built in the fifth-generation Mesoscale Model (MM5) of Pennsylvania State University and National Center for Atmospheric Research, a data preprocessor is developed to convert these satellite wind vectors to those with specified format required in MM5. To examine the data preprocessor and evaluate the impact of satellite winds from GMS-5 on MM5 simulations, a series of numerical experimental forecasts consisting of four typhoon cases in 2002 are designed and implemented. The results show that the preprocessor can process satellite winds smoothly and MM5 model runs successfully with a little extra computational load during ingesting these winds, and that assimilation of satellite winds by MM5 nudging method can obviously improve typhoon track forecast but contributes a little to typhoon intensity forecast. The impact of the satellite winds depends heavily upon whether the typhoon bogussing scheme in MM5 was turned on or not. The data preprocessor developed in this paper not only can treat GMS-5 satellite winds but also has capability with little modification to process derived winds from other geostationary satellites.

  2. 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

  3. Simulation of boundary layer trajectory dispersion sensitivity to soil moisture conditions: MM5 and noah-based investigation

    Science.gov (United States)

    The sensitivity of trajectories from experiments in which volumetric values of soil moisture were changed with respect to control values were analyzed during three different synoptic episodes in June 2006. The MM5 and Noah land surface models were used to simulate the response of the planetary boun...

  4. 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.

  5. An analysis of MM5 sensitivity to different parameterizations for high-resolution climate simulations

    Science.gov (United States)

    Argüeso, D.; Hidalgo-Muñoz, J. M.; Gámiz-Fortis, S. R.; Esteban-Parra, M. J.; Castro-Díez, Y.

    2009-04-01

    An evaluation of MM5 mesoscale model sensitivity to different parameterizations schemes is presented in terms of temperature and precipitation for high-resolution integrations over Andalusia (South of Spain). As initial and boundary conditions ERA-40 Reanalysis data are used. Two domains were used, a coarse one with dimensions of 55 by 60 grid points with spacing of 30 km and a nested domain of 48 by 72 grid points grid spaced 10 km. Coarse domain fully covers Iberian Peninsula and Andalusia fits loosely in the finer one. In addition to parameterization tests, two dynamical downscaling techniques have been applied in order to examine the influence of initial conditions on RCM long-term studies. Regional climate studies usually employ continuous integration for the period under survey, initializing atmospheric fields only at the starting point and feeding boundary conditions regularly. An alternative approach is based on frequent re-initialization of atmospheric fields; hence the simulation is divided in several independent integrations. Altogether, 20 simulations have been performed using varying physics options, of which 4 were fulfilled applying the re-initialization technique. Surface temperature and accumulated precipitation (daily and monthly scale) were analyzed for a 5-year period covering from 1990 to 1994. Results have been compared with daily observational data series from 110 stations for temperature and 95 for precipitation Both daily and monthly average temperatures are generally well represented by the model. Conversely, daily precipitation results present larger deviations from observational data. However, noticeable accuracy is gained when comparing with monthly precipitation observations. There are some especially conflictive subregions where precipitation is scarcely captured, such as the Southeast of the Iberian Peninsula, mainly due to its extremely convective nature. Regarding parameterization schemes performance, every set provides very

  6. 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.

  7. 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....

  8. 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

  9. 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

  10. 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...

  11. 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.

  12. 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...

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. Model Driven Software Development for Agricultural Robotics

    DEFF Research Database (Denmark)

    Larsen, Morten

    The design and development of agricultural robots, consists of both mechan- ical, electrical and software components. All these components must be de- signed and combined such that the overall goal of the robot is fulfilled. The design and development of these systems require collaboration between...... processing, control engineering, etc. This thesis proposes a Model-Driven Software Develop- ment based approach to model, analyse and partially generate the software implementation of a agricultural robot. Furthermore, Guidelines for mod- elling the architecture of an agricultural robots are provided......, assisting with bridging the different engineering disciplines. Timing play an important role in agricultural robotic applications, synchronisation of robot movement and implement actions is important in order to achieve precision spraying, me- chanical weeding, individual feeding, etc. Discovering...

  18. Model-Driven Configuration of SELinux Policies

    Science.gov (United States)

    Agreiter, Berthold; Breu, Ruth

    The need for access control in computer systems is inherent. However, the complexity to configure such systems is constantly increasing which affects the overall security of a system negatively. We think that it is important to define security requirements on a non-technical level while taking the application domain into respect in order to have a clear and separated view on security configuration (i.e. unblurred by technical details). On the other hand, security functionality has to be tightly integrated with the system and its development process in order to provide comprehensive means of enforcement. In this paper, we propose a systematic approach based on model-driven security configuration to leverage existing operating system security mechanisms (SELinux) for realising access control. We use UML models and develop a UML profile to satisfy these needs. Our goal is to exploit a comprehensive protection mechanism while rendering its security policy manageable by a domain specialist.

  19. Data driven propulsion system weight prediction model

    Science.gov (United States)

    Gerth, Richard J.

    1994-10-01

    The objective of the research was to develop a method to predict the weight of paper engines, i.e., engines that are in the early stages of development. The impetus for the project was the Single Stage To Orbit (SSTO) project, where engineers need to evaluate alternative engine designs. Since the SSTO is a performance driven project the performance models for alternative designs were well understood. The next tradeoff is weight. Since it is known that engine weight varies with thrust levels, a model is required that would allow discrimination between engines that produce the same thrust. Above all, the model had to be rooted in data with assumptions that could be justified based on the data. The general approach was to collect data on as many existing engines as possible and build a statistical model of the engines weight as a function of various component performance parameters. This was considered a reasonable level to begin the project because the data would be readily available, and it would be at the level of most paper engines, prior to detailed component design.

  20. Simulation of heavy precipitation episode over eastern Peninsular Malaysia using MM5: sensitivity to cumulus parameterization schemes

    Science.gov (United States)

    Salimun, Ester; Tangang, Fredolin; Juneng, Liew

    2010-06-01

    A comparative study has been conducted to investigate the skill of four convection parameterization schemes, namely the Anthes-Kuo (AK), the Betts-Miller (BM), the Kain-Fritsch (KF), and the Grell (GR) schemes in the numerical simulation of an extreme precipitation episode over eastern Peninsular Malaysia using the Pennsylvania State University—National Center for Atmospheric Research Center (PSU-NCAR) Fifth Generation Mesoscale Model (MM5). The event is a commonly occurring westward propagating tropical depression weather system during a boreal winter resulting from an interaction between a cold surge and the quasi-stationary Borneo vortex. The model setup and other physical parameterizations are identical in all experiments and hence any difference in the simulation performance could be associated with the cumulus parameterization scheme used. From the predicted rainfall and structure of the storm, it is clear that the BM scheme has an edge over the other schemes. The rainfall intensity and spatial distribution were reasonably well simulated compared to observations. The BM scheme was also better in resolving the horizontal and vertical structures of the storm. Most of the rainfall simulated by the BM simulation was of the convective type. The failure of other schemes (AK, GR and KF) in simulating the event may be attributed to the trigger function, closure assumption, and precipitation scheme. On the other hand, the appropriateness of the BM scheme for this episode may not be generalized for other episodes or convective environments.

  1. 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

  2. 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.

  3. 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

  4. 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....

  5. 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

  6. Test Driven Development of Scientific Models

    Science.gov (United States)

    Clune, Thomas L.

    2012-01-01

    Test-Driven Development (TDD) is a software development process that promises many advantages for developer productivity and has become widely accepted among professional software engineers. As the name suggests, TDD practitioners alternate between writing short automated tests and producing code that passes those tests. Although this overly simplified description will undoubtedly sound prohibitively burdensome to many uninitiated developers, the advent of powerful unit-testing frameworks greatly reduces the effort required to produce and routinely execute suites of tests. By testimony, many developers find TDD to be addicting after only a few days of exposure, and find it unthinkable to return to previous practices. Of course, scientific/technical software differs from other software categories in a number of important respects, but I nonetheless believe that TDD is quite applicable to the development of such software and has the potential to significantly improve programmer productivity and code quality within the scientific community. After a detailed introduction to TDD, I will present the experience within the Software Systems Support Office (SSSO) in applying the technique to various scientific applications. This discussion will emphasize the various direct and indirect benefits as well as some of the difficulties and limitations of the methodology. I will conclude with a brief description of pFUnit, a unit testing framework I co-developed to support test-driven development of parallel Fortran applications.

  7. 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.

  8. Test Driven Development of Scientific Models

    Science.gov (United States)

    Clune, Thomas L.

    2014-01-01

    Test-Driven Development (TDD), a software development process that promises many advantages for developer productivity and software reliability, has become widely accepted among professional software engineers. As the name suggests, TDD practitioners alternate between writing short automated tests and producing code that passes those tests. Although this overly simplified description will undoubtedly sound prohibitively burdensome to many uninitiated developers, the advent of powerful unit-testing frameworks greatly reduces the effort required to produce and routinely execute suites of tests. By testimony, many developers find TDD to be addicting after only a few days of exposure, and find it unthinkable to return to previous practices.After a brief overview of the TDD process and my experience in applying the methodology for development activities at Goddard, I will delve more deeply into some of the challenges that are posed by numerical and scientific software as well as tools and implementation approaches that should address those challenges.

  9. 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

  10. 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

  11. 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

  12. 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

  13. Model Driven Engineering with Ontology Technologies

    Science.gov (United States)

    Staab, Steffen; Walter, Tobias; Gröner, Gerd; Parreiras, Fernando Silva

    Ontologies constitute formal models of some aspect of the world that may be used for drawing interesting logical conclusions even for large models. Software models capture relevant characteristics of a software artifact to be developed, yet, most often these software models have limited formal semantics, or the underlying (often graphical) software language varies from case to case in a way that makes it hard if not impossible to fix its semantics. In this contribution, we survey the use of ontology technologies for software modeling in order to carry over advantages from ontology technologies to the software modeling domain. It will turn out that ontology-based metamodels constitute a core means for exploiting expressive ontology reasoning in the software modeling domain while remaining flexible enough to accommodate varying needs of software modelers.

  14. Task-Driven Comparison of Topic Models.

    Science.gov (United States)

    Alexander, Eric; Gleicher, Michael

    2016-01-01

    Topic modeling, a method of statistically extracting thematic content from a large collection of texts, is used for a wide variety of tasks within text analysis. Though there are a growing number of tools and techniques for exploring single models, comparisons between models are generally reduced to a small set of numerical metrics. These metrics may or may not reflect a model's performance on the analyst's intended task, and can therefore be insufficient to diagnose what causes differences between models. In this paper, we explore task-centric topic model comparison, considering how we can both provide detail for a more nuanced understanding of differences and address the wealth of tasks for which topic models are used. We derive comparison tasks from single-model uses of topic models, which predominantly fall into the categories of understanding topics, understanding similarity, and understanding change. Finally, we provide several visualization techniques that facilitate these tasks, including buddy plots, which combine color and position encodings to allow analysts to readily view changes in document similarity.

  15. MODEL DRIVEN DEVELOPMENT OF ONLINE BANKING SYSTEMS

    Directory of Open Access Journals (Sweden)

    Bresfelean Vasile Paul

    2011-07-01

    Full Text Available In case of online applications the cycle of software development varies from the routine. The online environment, the variety of users, the treatability of the mass of information created by them, the reusability and the accessibility from different devices are all factors of these systems complexity. The use of model drive approach brings several advantages that ease up the development process. Working prototypes that simplify client relationship and serve as the base of model tests can be easily made from models describing the system. These systems make possible for the banks clients to make their desired actions from anywhere. The user has the possibility of accessing information or making transactions.

  16. 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.

  17. 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

  18. 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

  19. 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…

  20. Six Sigma Driven Enterprise Model Transformation

    Directory of Open Access Journals (Sweden)

    Raymond Vella

    2009-10-01

    Full Text Available Enterprise architecture methods provide a structured system to understand enterprise activities. However, existing enterprise modelling methodologies take static views of the enterprise and do not naturally lead to a path of improvement during enterprise model transformation. This paper discusses the need for a methodology to facilitate changes for improvement in an enterprise. The six sigma methodology is proposed as the tool to facilitate progressive and continual Enterprise Model Transformation to allow businesses to adapt to meet increased customer expectation and global competition. An alignment of six sigma with phases of GERAM life cycle is described with inclusion of Critical-To-Satisfaction (CTS requirements. The synergies of combining the two methodologies are presented in an effort to provide a more culturally embedded framework for Enterprise Model Transformation that builds on the success of six sigma.

  1. A Data-Driven Reflectance Model

    OpenAIRE

    Matusik, Wojciech; Pfister, Hanspeter; Brand, Matt; McMillan, Leonard

    2003-01-01

    We present a generative model for isotropic bidirectional reflectance distribution functions (BRDFs) based on acquired reflectance data. Instead of using analytical reflectance models, we represent each BRDF as a dense set of measurements. This allows us to interpolate and extrapolate in the space of acquired BRDFs to create new BRDFs. We treat each acquired BRDF as a single high-dimensional vector taken from a space of all possible BRDFs. We apply both linear (subspace) and non-linear (manif...

  2. Evaluation of two MM5-PBL parameterization for solar radiation and temperature estimation in the South-Eastern area of the Iberian Peninsula

    International Nuclear Information System (INIS)

    Ruiz-Arias, J.A.; Pozo-Vasquez, D.; Sanchez-Sanchez, N.; Hayas-Barru, A.; Tovar-Pescador, J.; Montavez, J.P.

    2008-01-01

    We study the relative performance of two different MM5-PBL parametrizations (Blackadar and MRF) simulating hourly values of solar irradiance and temperature in the south-eastern part of the Iberian Peninsula. The evaluation was carried out throughout the different season of the year 2005 and for three different sky conditions: clear-sky, broken-clouds and overcast conditions. Two integrations, one per PBL parameterization, were carried out for every sky condition and season of the year and results were compared with observational data. Overall, the MM5 model, both using the Blackadar or MRF PBL parameterization, revealed to be a valid tool to estimate hourly values of solar radiation and temperature over the study area. The influence of the PBL parameterization on the model estimates was found to be more important for the solar radiation than for the temperature and highly dependent on the season and sky conditions. Particularly, a detailed analysis revealed that, during broken-clouds conditions, the ability of the model to reproduce hourly changes in the solar radiation strongly depends upon the selected PBL parameterization. Additionally, it was found that solar radiation RMSE values are about one order of magnitude higher during broken-clouds and overcast conditions compared to clear-sky conditions. For the temperature, the two PBL parameterizations provide very similar estimates. Only under overcast conditions and during the autumn, the MRF provides significantly better estimates.

  3. 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...

  4. Data driven mathematical models for policy making

    OpenAIRE

    Nannyonga, Betty

    2011-01-01

    This thesis consists of two papers. 1. Betty Nannyonga, D.J.T. Sumpter, J.Y.T. Mugisha and L.S. Luboobi: The Dynamics,causes and possible prevention of Hepaititis E outbreaks. 2. Betty Nannyonga, D.J.T. Sumpter, andStam Nicolis: A dynamical systems approach tosocial and economic development. The first paper deals with a deterministic approach of modelling a Hepatitis E outbreak whenmalaria is endemic in a population. We design three models based on the epidemiology ofHepatitis E, malaria, and...

  5. Driven dynamics of simplified tribological models

    Energy Technology Data Exchange (ETDEWEB)

    Vanossi, A [CNR-INFM National Research Center S3 and Department of Physics, University of Modena and Reggio Emilia, Via Campi 213/A, 41100 Modena (Italy); Braun, O M [Institute of Physics, National Academy of Sciences of Ukraine, 03028 Kiev (Ukraine)

    2007-08-01

    Over the last decade, remarkable developments in nanotechnology, notably the use of atomic and friction force microscopes (AFM/FFM), the surface-force apparatus (SFA) and the quartz-crystal microbalance (QCM), have provided the possibility to build experimental devices able to perform analysis on well-characterized materials at the nano- and microscale. Simultaneously, tremendous advances in computing hardware and methodology (molecular dynamics techniques and ab initio calculations) have dramatically increased the ability of theoreticians to simulate tribological processes, supplying very detailed information on the atomic scale for realistic sliding systems. This acceleration in experiments and computations, leading often to very detailed yet complex data, has deeply stimulated the search, rediscovery and implementation of simpler mathematical models such as the generalized Frenkel-Kontorova and Tomlinson models, capable of describing and interpreting, in a more immediate way, the essential physics involved in nonlinear sliding phenomena.

  6. Driven dynamics of simplified tribological models

    International Nuclear Information System (INIS)

    Vanossi, A; Braun, O M

    2007-01-01

    Over the last decade, remarkable developments in nanotechnology, notably the use of atomic and friction force microscopes (AFM/FFM), the surface-force apparatus (SFA) and the quartz-crystal microbalance (QCM), have provided the possibility to build experimental devices able to perform analysis on well-characterized materials at the nano- and microscale. Simultaneously, tremendous advances in computing hardware and methodology (molecular dynamics techniques and ab initio calculations) have dramatically increased the ability of theoreticians to simulate tribological processes, supplying very detailed information on the atomic scale for realistic sliding systems. This acceleration in experiments and computations, leading often to very detailed yet complex data, has deeply stimulated the search, rediscovery and implementation of simpler mathematical models such as the generalized Frenkel-Kontorova and Tomlinson models, capable of describing and interpreting, in a more immediate way, the essential physics involved in nonlinear sliding phenomena

  7. A bulk viscosity driven inflationary model

    International Nuclear Information System (INIS)

    Waga, I.; Falcao, R.C.; Chanda, R.

    1985-01-01

    Bulk viscosity associated with the production of heavy particles during the GUT phase transition can lead to exponential or 'generalized' inflation. The condition of inflation proposed is independent of the details of the phase transition and remains unaltered in presence of a cosmological constant. Such mechanism avoids the extreme supercooling and reheating needed in the usual inflationary models. The standard baryongenesis mechanism can be maintained. (Author) [pt

  8. 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...

  9. 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...

  10. 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.

  11. 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...

  12. 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...

  13. 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.

  14. 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

  15. 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.

  16. 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

  17. 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.

  18. Validation of buoyancy driven spectral tensor model using HATS data

    DEFF Research Database (Denmark)

    Chougule, A.; Mann, Jakob; Kelly, Mark C.

    2016-01-01

    We present a homogeneous spectral tensor model for wind velocity and temperature fluctuations, driven by mean vertical shear and mean temperature gradient. Results from the model, including one-dimensional velocity and temperature spectra and the associated co-spectra, are shown in this paper....... The model also reproduces two-point statistics, such as coherence and phases, via cross-spectra between two points separated in space. Model results are compared with observations from the Horizontal Array Turbulence Study (HATS) field program (Horst et al. 2004). The spectral velocity tensor in the model...

  19. 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...

  20. 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

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. Aspect-Oriented Model-Driven Software Product Line Engineering

    Science.gov (United States)

    Groher, Iris; Voelter, Markus

    Software product line engineering aims to reduce development time, effort, cost, and complexity by taking advantage of the commonality within a portfolio of similar products. The effectiveness of a software product line approach directly depends on how well feature variability within the portfolio is implemented and managed throughout the development lifecycle, from early analysis through maintenance and evolution. This article presents an approach that facilitates variability implementation, management, and tracing by integrating model-driven and aspect-oriented software development. Features are separated in models and composed of aspect-oriented composition techniques on model level. Model transformations support the transition from problem to solution space models. Aspect-oriented techniques enable the explicit expression and modularization of variability on model, template, and code level. The presented concepts are illustrated with a case study of a home automation system.

  6. Formal Model-Driven Engineering: Generating Data and Behavioural Components

    Directory of Open Access Journals (Sweden)

    Chen-Wei Wang

    2012-12-01

    Full Text Available Model-driven engineering is the automatic production of software artefacts from abstract models of structure and functionality. By targeting a specific class of system, it is possible to automate aspects of the development process, using model transformations and code generators that encode domain knowledge and implementation strategies. Using this approach, questions of correctness for a complex, software system may be answered through analysis of abstract models of lower complexity, under the assumption that the transformations and generators employed are themselves correct. This paper shows how formal techniques can be used to establish the correctness of model transformations used in the generation of software components from precise object models. The source language is based upon existing, formal techniques; the target language is the widely-used SQL notation for database programming. Correctness is established by giving comparable, relational semantics to both languages, and checking that the transformations are semantics-preserving.

  7. 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

  8. 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.

  9. 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.

  10. A data driven nonlinear stochastic model for blood glucose dynamics.

    Science.gov (United States)

    Zhang, Yan; Holt, Tim A; Khovanova, Natalia

    2016-03-01

    The development of adequate mathematical models for blood glucose dynamics may improve early diagnosis and control of diabetes mellitus (DM). We have developed a stochastic nonlinear second order differential equation to describe the response of blood glucose concentration to food intake using continuous glucose monitoring (CGM) data. A variational Bayesian learning scheme was applied to define the number and values of the system's parameters by iterative optimisation of free energy. The model has the minimal order and number of parameters to successfully describe blood glucose dynamics in people with and without DM. The model accounts for the nonlinearity and stochasticity of the underlying glucose-insulin dynamic process. Being data-driven, it takes full advantage of available CGM data and, at the same time, reflects the intrinsic characteristics of the glucose-insulin system without detailed knowledge of the physiological mechanisms. We have shown that the dynamics of some postprandial blood glucose excursions can be described by a reduced (linear) model, previously seen in the literature. A comprehensive analysis demonstrates that deterministic system parameters belong to different ranges for diabetes and controls. Implications for clinical practice are discussed. This is the first study introducing a continuous data-driven nonlinear stochastic model capable of describing both DM and non-DM profiles. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

  11. Econophysics and Data Driven Modelling of Market Dynamics

    CERN Document Server

    Aoyama, Hideaki; Chakrabarti, Bikas; Chakraborti, Anirban; Ghosh, Asim; Econophysics and Data Driven Modelling of Market Dynamics

    2015-01-01

    This book presents the works and research findings of physicists, economists, mathematicians, statisticians, and financial engineers who have undertaken data-driven modelling of market dynamics and other empirical studies in the field of Econophysics. During recent decades, the financial market landscape has changed dramatically with the deregulation of markets and the growing complexity of products. The ever-increasing speed and decreasing costs of computational power and networks have led to the emergence of huge databases. The availability of these data should permit the development of models that are better founded empirically, and econophysicists have accordingly been advocating that one should rely primarily on the empirical observations in order to construct models and validate them. The recent turmoil in financial markets and the 2008 crash appear to offer a strong rationale for new models and approaches. The Econophysics community accordingly has an important future role to play in market modelling....

  12. 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.

  13. 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.

  14. Quantum tunneling in the driven SU(2) model

    International Nuclear Information System (INIS)

    Kaminski, P.; Ploszajczak, M.; Arvieu, R.

    1992-01-01

    The tunneling rate is investigated in the quantum and classical limits using an exactly soluble 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 presence of the classical chaotic structures leads to the enormous growth in the tunneling rate. The results suggest the existence of a new mechanism of quantum tunneling, involving transport of the wave-function between stable regions of the classical phase-space due to a coupling with 'chaotic' levels. (author) 17 refs., 13 figs

  15. 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…

  16. 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.

  17. The Ability of MM5 to Simulate Ice Clouds: Systematic Comparison between Simulated and Measured Fluxes and Lidar/Radar Profiles at SIRTA Atmospheric Observatory

    Energy Technology Data Exchange (ETDEWEB)

    Chiriaco, M.; Vautard, R.; Chepfer, H.; Haeffelin, M.; Wanherdrick, Y.; Morille, Y.; Protat, A.; Dudhia, J.

    2005-03-18

    Ice clouds play a major role in the radiative energy budget of the Earth-atmosphere system (Liou 1986). Their radiative effect is governed primarily by the equilibrium between their albedo and greenhouse effects. Both macrophysical and microphysical properties of ice clouds regulate this equilibrium. For quantifying the effect of these clouds onto climate and weather systems, they must be properly characterized in atmospheric models. In this paper we use remote-sensing measurements from the SIRTA ground based atmospheric observatory (Site Instrumental de Recherche par Teledetection Atmospherique, http://sirta.lmd.polytechnique.fr). Lidar and radar observations taken over 18 months are used, in order to gain statistical confidence in the model evaluation. Along this period of time, 62 days are selected for study because they contain parts of ice clouds. We use the ''model to observations'' approach by simulating lidar and radar signals from MM5 outputs. Other more classical variables such as shortwave and longwave radiative fluxes are also used. Four microphysical schemes, among which that proposed by Reisner et al. (1998) with original or modified parameterizations of particle terminal fall velocities (Zurovac-Jevtic and Zhang 2003, Heymsfield and Donner 1990), and the simplified Dudhia (1989) scheme are evaluated in this study.

  18. 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...

  19. 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.

  20. 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.

  1. Facilitating Data Driven Business Model Innovation - A Case study

    DEFF Research Database (Denmark)

    Bjerrum, Torben Cæsar Bisgaard; Andersen, Troels Christian; Aagaard, Annabeth

    2016-01-01

    . The businesses interdisciplinary capabilities come into play in the BMI process, where knowledge from the facilitation strategy and knowledge from phases of the BMI process needs to be present to create new knowledge, hence new BMs and innovations. Depending on the environment and shareholders, this also exposes......This paper aims to understand the barriers that businesses meet in understanding their current business models (BM) and in their attempt at innovating new data driven business models (DDBM) using data. The interdisciplinary challenge of knowledge exchange occurring outside and/or inside businesses......, that gathers knowledge is of great importance. The SMEs have little, if no experience, within data handling, data analytics, and working with structured Business Model Innovation (BMI), that relates to both new and conventional products, processes and services. This new frontier of data and BMI will have...

  2. A Transition Towards a Data-Driven Business Model (DDBM)

    DEFF Research Database (Denmark)

    Zaki, Mohamed; Bøe-Lillegraven, Tor; Neely, Andy

    2016-01-01

    Nettavisen is a Norwegian online start-up that experienced a boost after the financial crisis of 2009. Since then, the firm has been able to increase its market share and profitability through the use of highly disruptive business models, allowing the relatively small staff to outcompete powerhouse...... legacy-publishing companies and new media players such as Facebook and Google. These disruptive business models have been successful, as Nettavisen captured a large market share in Norway early on, and was consistently one of the top-three online news sites in Norway. Capitalising on media data explosion...... and the recent acquisition of blogger network ‘Blog.no’, Nettavisen is moving towards a data-driven business model (DDBM). In particular, the firm aims to analyse huge volumes of user Web browsing and purchasing habits....

  3. Model-Driven Approach for Body Area Network Application Development.

    Science.gov (United States)

    Venčkauskas, Algimantas; Štuikys, Vytautas; Jusas, Nerijus; Burbaitė, Renata

    2016-05-12

    This paper introduces the sensor-networked IoT model as a prototype to support the design of Body Area Network (BAN) applications for healthcare. Using the model, we analyze the synergistic effect of the functional requirements (data collection from the human body and transferring it to the top level) and non-functional requirements (trade-offs between energy-security-environmental factors, treated as Quality-of-Service (QoS)). We use feature models to represent the requirements at the earliest stage for the analysis and describe a model-driven methodology to design the possible BAN applications. Firstly, we specify the requirements as the problem domain (PD) variability model for the BAN applications. Next, we introduce the generative technology (meta-programming as the solution domain (SD)) and the mapping procedure to map the PD feature-based variability model onto the SD feature model. Finally, we create an executable meta-specification that represents the BAN functionality to describe the variability of the problem domain though transformations. The meta-specification (along with the meta-language processor) is a software generator for multiple BAN-oriented applications. We validate the methodology with experiments and a case study to generate a family of programs for the BAN sensor controllers. This enables to obtain the adequate measure of QoS efficiently through the interactive adjustment of the meta-parameter values and re-generation process for the concrete BAN application.

  4. Model-Driven Approach for Body Area Network Application Development

    Science.gov (United States)

    Venčkauskas, Algimantas; Štuikys, Vytautas; Jusas, Nerijus; Burbaitė, Renata

    2016-01-01

    This paper introduces the sensor-networked IoT model as a prototype to support the design of Body Area Network (BAN) applications for healthcare. Using the model, we analyze the synergistic effect of the functional requirements (data collection from the human body and transferring it to the top level) and non-functional requirements (trade-offs between energy-security-environmental factors, treated as Quality-of-Service (QoS)). We use feature models to represent the requirements at the earliest stage for the analysis and describe a model-driven methodology to design the possible BAN applications. Firstly, we specify the requirements as the problem domain (PD) variability model for the BAN applications. Next, we introduce the generative technology (meta-programming as the solution domain (SD)) and the mapping procedure to map the PD feature-based variability model onto the SD feature model. Finally, we create an executable meta-specification that represents the BAN functionality to describe the variability of the problem domain though transformations. The meta-specification (along with the meta-language processor) is a software generator for multiple BAN-oriented applications. We validate the methodology with experiments and a case study to generate a family of programs for the BAN sensor controllers. This enables to obtain the adequate measure of QoS efficiently through the interactive adjustment of the meta-parameter values and re-generation process for the concrete BAN application. PMID:27187394

  5. Model-Driven Approach for Body Area Network Application Development

    Directory of Open Access Journals (Sweden)

    Algimantas Venčkauskas

    2016-05-01

    Full Text Available This paper introduces the sensor-networked IoT model as a prototype to support the design of Body Area Network (BAN applications for healthcare. Using the model, we analyze the synergistic effect of the functional requirements (data collection from the human body and transferring it to the top level and non-functional requirements (trade-offs between energy-security-environmental factors, treated as Quality-of-Service (QoS. We use feature models to represent the requirements at the earliest stage for the analysis and describe a model-driven methodology to design the possible BAN applications. Firstly, we specify the requirements as the problem domain (PD variability model for the BAN applications. Next, we introduce the generative technology (meta-programming as the solution domain (SD and the mapping procedure to map the PD feature-based variability model onto the SD feature model. Finally, we create an executable meta-specification that represents the BAN functionality to describe the variability of the problem domain though transformations. The meta-specification (along with the meta-language processor is a software generator for multiple BAN-oriented applications. We validate the methodology with experiments and a case study to generate a family of programs for the BAN sensor controllers. This enables to obtain the adequate measure of QoS efficiently through the interactive adjustment of the meta-parameter values and re-generation process for the concrete BAN application.

  6. Damped trophic cascades driven by fishing in model marine ecosystems

    DEFF Research Database (Denmark)

    Andersen, Ken Haste; Pedersen, Martin

    2010-01-01

    The largest perturbation on upper trophic levels of many marine ecosystems stems from fishing. The reaction of the ecosystem goes beyond the trophic levels directly targeted by the fishery. This reaction has been described either as a change in slope of the overall size spectrum or as a trophic...... cascade triggered by the removal of top predators. Here we use a novel size- and trait-based model to explore how marine ecosystems might react to perturbations from different types of fishing pressure. The model explicitly resolves the whole life history of fish, from larvae to adults. The results show...... that fishing does not change the overall slope of the size spectrum, but depletes the largest individuals and induces trophic cascades. A trophic cascade can propagate both up and down in trophic levels driven by a combination of changes in predation mortality and food limitation. The cascade is damped...

  7. A Model-driven Framework for Educational Game Design

    Directory of Open Access Journals (Sweden)

    Bill Roungas

    2016-09-01

    Full Text Available Educational games are a class of serious games whose main purpose is to teach some subject to their players. Despite the many existing design frameworks, these games are too often created in an ad-hoc manner, and typically without the use of a game design document (GDD. We argue that a reason for this phenomenon is that current ways to structure, create and update GDDs do not increase the value of the artifact in the design and development process. As a solution, we propose a model-driven, web-based knowledge management environment that supports game designers in the creation of a GDD that accounts for and relates educational and entertainment game elements. The foundation of our approach is our devised conceptual model for educational games, which also defines the structure of the design environment. We present promising results from an evaluation of our environment with eight experts in serious games.

  8. 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

  9. Analysis of Intelligent Transportation Systems Using Model-Driven Simulations

    Directory of Open Access Journals (Sweden)

    Alberto Fernández-Isabel

    2015-06-01

    Full Text Available Intelligent Transportation Systems (ITSs integrate information, sensor, control, and communication technologies to provide transport related services. Their users range from everyday commuters to policy makers and urban planners. Given the complexity of these systems and their environment, their study in real settings is frequently unfeasible. Simulations help to address this problem, but present their own issues: there can be unintended mistakes in the transition from models to code; their platforms frequently bias modeling; and it is difficult to compare works that use different models and tools. In order to overcome these problems, this paper proposes a framework for a model-driven development of these simulations. It is based on a specific modeling language that supports the integrated specification of the multiple facets of an ITS: people, their vehicles, and the external environment; and a network of sensors and actuators conveniently arranged and distributed that operates over them. The framework works with a model editor to generate specifications compliant with that language, and a code generator to produce code from them using platform specifications. There are also guidelines to help researchers in the application of this infrastructure. A case study on advanced management of traffic lights with cameras illustrates its use.

  10. A dynamic, climate-driven model of Rift Valley fever

    Directory of Open Access Journals (Sweden)

    Joseph Leedale

    2016-03-01

    Full Text Available Outbreaks of Rift Valley fever (RVF in eastern Africa have previously occurred following specific rainfall dynamics and flooding events that appear to support the emergence of large numbers of mosquito vectors. As such, transmission of the virus is considered to be sensitive to environmental conditions and therefore changes in climate can impact the spatiotemporal dynamics of epizootic vulnerability. Epidemiological information describing the methods and parameters of RVF transmission and its dependence on climatic factors are used to develop a new spatio-temporal mathematical model that simulates these dynamics and can predict the impact of changes in climate. The Liverpool RVF (LRVF model is a new dynamic, process-based model driven by climate data that provides a predictive output of geographical changes in RVF outbreak susceptibility as a result of the climate and local livestock immunity. This description of the multi-disciplinary process of model development is accessible to mathematicians, epidemiological modellers and climate scientists, uniting dynamic mathematical modelling, empirical parameterisation and state-of-the-art climate information.

  11. Numerical modeling of buoyancy-driven turbulent flows in enclosures

    International Nuclear Information System (INIS)

    Hsieh, K.J.; Lien, F.S.

    2004-01-01

    Modeling turbulent natural convection in enclosures with differentially heated vertical walls is numerically challenging, in particular, when low-Reynolds-number (low-Re) models are adopted. When the turbulence level in the core region of cavity is low, most low-Re models, particular those showing good performance for bypass transitional flows, tend to relaminarize the flow and, as a consequence, significantly underpredict the near-wall turbulence intensities and boundary-layer thickness. Another challenge associated with low-turbulence buoyancy-driven flows in enclosures is its inherent unsteadiness, which can pose convergence problems when a steady Reynolds-averaged Navier-Stokes (RANS) equation is solved. In the present study, an unsteady RANS approach in conjunction with the low-Re k-ε model of Lien and Leschziner [Int. J. Comput. Fluid Dyn. 12 (1999) 1] is initially adopted and the predicted flow field is found effectively relaminarized. To overcome this difficulty, likely caused by the low-Re functions in the ε-equation, the two-layer approach is attempted, in which ε is prescribed algebraically using the one-equation k-l model of Wolfshtein [Int. J. Heat Mass Transfer 12 (1969) 301]. The two-layer approach combined with a quadratic stress-strain relation gives overall the best performance in terms of mean velocities, temperature and turbulence quantities

  12. Model-driven Privacy Assessment in the Smart Grid

    Energy Technology Data Exchange (ETDEWEB)

    Knirsch, Fabian [Salzburg Univ. (Austria); Engel, Dominik [Salzburg Univ. (Austria); Neureiter, Christian [Salzburg Univ. (Austria); Frincu, Marc [Univ. of Southern California, Los Angeles, CA (United States); Prasanna, Viktor [Univ. of Southern California, Los Angeles, CA (United States)

    2015-02-09

    In a smart grid, data and information are transported, transmitted, stored, and processed with various stakeholders having to cooperate effectively. Furthermore, personal data is the key to many smart grid applications and therefore privacy impacts have to be taken into account. For an effective smart grid, well integrated solutions are crucial and for achieving a high degree of customer acceptance, privacy should already be considered at design time of the system. To assist system engineers in early design phase, frameworks for the automated privacy evaluation of use cases are important. For evaluation, use cases for services and software architectures need to be formally captured in a standardized and commonly understood manner. In order to ensure this common understanding for all kinds of stakeholders, reference models have recently been developed. In this paper we present a model-driven approach for the automated assessment of such services and software architectures in the smart grid that builds on the standardized reference models. The focus of qualitative and quantitative evaluation is on privacy. For evaluation, the framework draws on use cases from the University of Southern California microgrid.

  13. Simulation of Road Traffic Applying Model-Driven Engineering

    Directory of Open Access Journals (Sweden)

    Alberto FERNÁNDEZ-ISABEL

    2016-05-01

    Full Text Available Road traffic is an important phenomenon in modern societies. The study of its different aspects in the multiple scenarios where it happens is relevant for a huge number of problems. At the same time, its scale and complexity make it hard to study. Traffic simulations can alleviate these difficulties, simplifying the scenarios to consider and controlling their variables. However, their development also presents difficulties. The main ones come from the need to integrate the way of working of researchers and developers from multiple fields. Model-Driven Engineering (MDE addresses these problems using Modelling Languages (MLs and semi-automatic transformations to organise and describe the development, from requirements to code. This paper presents a domain-specific MDE framework for simulations of road traffic. It comprises an extensible ML, support tools, and development guidelines. The ML adopts an agent-based approach, which is focused on the roles of individuals in road traffic and their decision-making. A case study shows the process to model a traffic theory with the ML, and how to specialise that specification for an existing target platform and its simulations. The results are the basis for comparison with related work.

  14. Robust Real-Time Musculoskeletal Modeling Driven by Electromyograms.

    Science.gov (United States)

    Durandau, Guillaume; Farina, Dario; Sartori, Massimo

    2018-03-01

    Current clinical biomechanics involves lengthy data acquisition and time-consuming offline analyses with biomechanical models not operating in real-time for man-machine interfacing. We developed a method that enables online analysis of neuromusculoskeletal function in vivo in the intact human. We used electromyography (EMG)-driven musculoskeletal modeling to simulate all transformations from muscle excitation onset (EMGs) to mechanical moment production around multiple lower-limb degrees of freedom (DOFs). We developed a calibration algorithm that enables adjusting musculoskeletal model parameters specifically to an individual's anthropometry and force-generating capacity. We incorporated the modeling paradigm into a computationally efficient, generic framework that can be interfaced in real-time with any movement data collection system. The framework demonstrated the ability of computing forces in 13 lower-limb muscle-tendon units and resulting moments about three joint DOFs simultaneously in real-time. Remarkably, it was capable of extrapolating beyond calibration conditions, i.e., predicting accurate joint moments during six unseen tasks and one unseen DOF. The proposed framework can dramatically reduce evaluation latency in current clinical biomechanics and open up new avenues for establishing prompt and personalized treatments, as well as for establishing natural interfaces between patients and rehabilitation systems. The integration of EMG with numerical modeling will enable simulating realistic neuromuscular strategies in conditions including muscular/orthopedic deficit, which could not be robustly simulated via pure modeling formulations. This will enable translation to clinical settings and development of healthcare technologies including real-time bio-feedback of internal mechanical forces and direct patient-machine interfacing.

  15. 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

  16. 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.

  17. Forecasting wind-driven wildfires using an inverse modelling approach

    Directory of Open Access Journals (Sweden)

    O. Rios

    2014-06-01

    Full Text Available A technology able to rapidly forecast wildfire dynamics would lead to a paradigm shift in the response to emergencies, providing the Fire Service with essential information about the ongoing fire. This paper presents and explores a novel methodology to forecast wildfire dynamics in wind-driven conditions, using real-time data assimilation and inverse modelling. The forecasting algorithm combines Rothermel's rate of spread theory with a perimeter expansion model based on Huygens principle and solves the optimisation problem with a tangent linear approach and forward automatic differentiation. Its potential is investigated using synthetic data and evaluated in different wildfire scenarios. The results show the capacity of the method to quickly predict the location of the fire front with a positive lead time (ahead of the event in the order of 10 min for a spatial scale of 100 m. The greatest strengths of our method are lightness, speed and flexibility. We specifically tailor the forecast to be efficient and computationally cheap so it can be used in mobile systems for field deployment and operativeness. Thus, we put emphasis on producing a positive lead time and the means to maximise it.

  18. Statistics of a neuron model driven by asymmetric colored noise.

    Science.gov (United States)

    Müller-Hansen, Finn; Droste, Felix; Lindner, Benjamin

    2015-02-01

    Irregular firing of neurons can be modeled as a stochastic process. Here we study the perfect integrate-and-fire neuron driven by dichotomous noise, a Markovian process that jumps between two states (i.e., possesses a non-Gaussian statistics) and exhibits nonvanishing temporal correlations (i.e., represents a colored noise). Specifically, we consider asymmetric dichotomous noise with two different transition rates. Using a first-passage-time formulation, we derive exact expressions for the probability density and the serial correlation coefficient of the interspike interval (time interval between two subsequent neural action potentials) and the power spectrum of the spike train. Furthermore, we extend the model by including additional Gaussian white noise, and we give approximations for the interspike interval (ISI) statistics in this case. Numerical simulations are used to validate the exact analytical results for pure dichotomous noise, and to test the approximations of the ISI statistics when Gaussian white noise is included. The results may help to understand how correlations and asymmetry of noise and signals in nerve cells shape neuronal firing statistics.

  19. West Coast Swing Dancing as a Driven Harmonic Oscillator Model

    Science.gov (United States)

    Ferrara, Davon; Holzer, Marie; Kyere, Shirley

    The study of physics in sports not only provides valuable insight for improved athletic performance and injury prevention, but offers undergraduate students an opportunity to engage in both short- and long-term research efforts. In this project, conducted by two non-physics majors, we hypothesized that a driven harmonic oscillator model can be used to better understand the interaction between two west coast swing dancers since the stiffness of the physical connection between dance partners is a known factor in the dynamics of the dance. The hypothesis was tested by video analysis of two dancers performing a west coast swing basic, the sugar push, while changing the stiffness of the physical connection. The difference in stiffness of the connection from the ideal was estimated by the leader; the position with time data from the video was used to measure changes in the amplitude and phase difference between the leader and follower. While several aspects of our results agree with the proposed model, some key characteristics do not, possibly due to the follower relying on visual leads. Corresponding author and principal investigator.

  20. Computational Model of a Biomass Driven Absorption Refrigeration System

    Directory of Open Access Journals (Sweden)

    Munyeowaji Mbikan

    2017-02-01

    Full Text Available The impact of vapour compression refrigeration is the main push for scientists to find an alternative sustainable technology. Vapour absorption is an ideal technology which makes use of waste heat or renewable heat, such as biomass, to drive absorption chillers from medium to large applications. In this paper, the aim was to investigate the feasibility of a biomass driven aqua-ammonia absorption system. An estimation of the solid biomass fuel quantity required to provide heat for the operation of a vapour absorption refrigeration cycle (VARC is presented; the quantity of biomass required depends on the fuel density and the efficiency of the combustion and heat transfer systems. A single-stage aqua-ammonia refrigeration system analysis routine was developed to evaluate the system performance and ascertain the rate of energy transfer required to operate the system, and hence, the biomass quantity needed. In conclusion, this study demonstrated the results of the performance of a computational model of an aqua-ammonia system under a range of parameters. The model showed good agreement with published experimental data.

  1. EXPLORING DATA-DRIVEN SPECTRAL MODELS FOR APOGEE M DWARFS

    Science.gov (United States)

    Lua Birky, Jessica; Hogg, David; Burgasser, Adam J.; Jessica Birky

    2018-01-01

    The Cannon (Ness et al. 2015; Casey et al. 2016) is a flexible, data-driven spectral modeling and parameter inference framework, demonstrated on high-resolution Apache Point Galactic Evolution Experiment (APOGEE; λ/Δλ~22,500, 1.5-1.7µm) spectra of giant stars to estimate stellar labels (Teff, logg, [Fe/H], and chemical abundances) to precisions higher than the model-grid pipeline. The lack of reliable stellar parameters reported by the APOGEE pipeline for temperatures less than ~3550K, motivates extension of this approach to M dwarf stars. Using a training set of 51 M dwarfs with spectral types ranging M0-M9 obtained from SDSS optical spectra, we demonstrate that the Cannon can infer spectral types to a precision of +/-0.6 types, making it an effective tool for classifying high-resolution near-infrared spectra. We discuss the potential for extending this work to determine the physical stellar labels Teff, logg, and [Fe/H].This work is supported by the SDSS Faculty and Student (FAST) initiative.

  2. A question driven socio-hydrological modeling process

    Science.gov (United States)

    Garcia, M.; Portney, K.; Islam, S.

    2016-01-01

    Human and hydrological systems are coupled: human activity impacts the hydrological cycle and hydrological conditions can, but do not always, trigger changes in human systems. Traditional modeling approaches with no feedback between hydrological and human systems typically cannot offer insight into how different patterns of natural variability or human-induced changes may propagate through this coupled system. Modeling of coupled human-hydrological systems, also called socio-hydrological systems, recognizes the potential for humans to transform hydrological systems and for hydrological conditions to influence human behavior. However, this coupling introduces new challenges and existing literature does not offer clear guidance regarding model conceptualization. There are no universally accepted laws of human behavior as there are for the physical systems; furthermore, a shared understanding of important processes within the field is often used to develop hydrological models, but there is no such consensus on the relevant processes in socio-hydrological systems. Here we present a question driven process to address these challenges. Such an approach allows modeling structure, scope and detail to remain contingent on and adaptive to the question context. We demonstrate the utility of this process by revisiting a classic question in water resources engineering on reservoir operation rules: what is the impact of reservoir operation policy on the reliability of water supply for a growing city? Our example model couples hydrological and human systems by linking the rate of demand decreases to the past reliability to compare standard operating policy (SOP) with hedging policy (HP). The model shows that reservoir storage acts both as a buffer for variability and as a delay triggering oscillations around a sustainable level of demand. HP reduces the threshold for action thereby decreasing the delay and the oscillation effect. As a result, per capita demand decreases during

  3. 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

  4. 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.

  5. Modelling and simulation of surface morphology driven by ion bombardment

    Energy Technology Data Exchange (ETDEWEB)

    Yewande, E.O.

    2006-05-02

    Non-equilibrium surfaces, at nanometer length scales, externally driven via bombardment with energetic particles are known to exhibit well ordered patterns with a variety of applications in nano-technology. These patterns emerge at time scales on the order of minutes. Continuum theory has been quite successful in giving a general picture of the processes that interplay to give the observed patterns, as well as how such competition might determine the properties of the nanostructures. However, continuum theoretical descriptions are ideal only in the asymptotic limit. The only other theoretical alternative, which happens to be more suitable for the characteristic length-and time-scales of pattern formation, is Monte Carlo simulation. In this thesis, surface morphology is studied using discrete solid-on-solid Monte Carlo models of sputtering and surface diffusion. The simulations are performed in the context of the continuum theories and experiments. In agreement with the experiments, the ripples coarsen with time and the ripple velocity exhibits a power-law behaviour with the ripple wavelength, in addition, the exponent was found to depend on the simulation temperature, which suggests future experimental studies of flux dependence. Moreover, a detailed exploration of possible topographies, for different sputtering conditions, corresponding to different materials, was performed. And different surface topographies e.g. holes, ripples, and dots, were found at oblique incidence, without sample rotation. With sample rotation no new topography was found, its only role being to destroy any inherent anisotropy in the system. (orig.)

  6. Nonspherical Radiation Driven Wind Models Applied to Be Stars

    Science.gov (United States)

    Arauxo, F. X.

    1990-11-01

    ABSTRACT. In this work we present a model for the structure of a radiatively driven wind in the meridional plane of a hot star. Rotation effects and simulation of viscous forces were included in the motion equations. The line radiation force is considered with the inclusion of the finite disk correction in self-consistent computations which also contain gravity darkening as well as distortion of the star by rotation. An application to a typical BlV star leads to mass-flux ratios between equator and pole of the order of 10 and mass loss rates in the range 5.l0 to Mo/yr. Our envelope models are flattened towards the equator and the wind terminal velocities in that region are rather high (1000 Km/s). However, in the region near the star the equatorial velocity field is dominated by rotation. RESUMEN. Se presenta un modelo de la estructura de un viento empujado radiativamente en el plano meridional de una estrella caliente. Se incluyeron en las ecuaciones de movimiento los efectos de rotaci6n y la simulaci6n de fuerzas viscosas. Se consider6 la fuerza de las lineas de radiaci6n incluyendo la correcci6n de disco finito en calculos autoconsistentes los cuales incluyen oscurecimiento gravitacional asi como distorsi6n de la estrella por rotaci6n. La aplicaci6n a una estrella tipica BlV lleva a cocientes de flujo de masa entre el ecuador y el polo del orden de 10 de perdida de masa en el intervalo 5.l0 a 10 Mo/ano. Nuestros modelos de envolvente estan achatados hacia el ecuador y las velocidads terminales del viento en esa regi6n son bastante altas (1000 Km/s). Sin embargo, en la regi6n cercana a la estrella el campo de velocidad ecuatorial esta dominado por la rotaci6n. Key words: STARS-BE -- STARS-WINDS

  7. Comparing Transformation Possibilities of Topological Functioning Model and BPMN in the Context of Model Driven Architecture

    Directory of Open Access Journals (Sweden)

    Solomencevs Artūrs

    2016-05-01

    Full Text Available The approach called “Topological Functioning Model for Software Engineering” (TFM4SE applies the Topological Functioning Model (TFM for modelling the business system in the context of Model Driven Architecture. TFM is a mathematically formal computation independent model (CIM. TFM4SE is compared to an approach that uses BPMN as a CIM. The comparison focuses on CIM modelling and on transformation to UML Sequence diagram on the platform independent (PIM level. The results show the advantages and drawbacks the formalism of TFM brings into the development.

  8. 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

  9. Hydrography-driven coarsening of grid digital elevation models

    Science.gov (United States)

    Moretti, G.; Orlandini, S.

    2017-12-01

    A new grid coarsening strategy, denoted as hydrography-driven (HD) coarsening, is developed in the present study. The HD coarsening strategy is designed to retain the essential hydrographic features of surface flow paths observed in high-resolution digital elevation models (DEMs): (1) depressions are filled in the considered high-resolution DEM, (2) the obtained topographic data are used to extract a reference grid network composed of all surface flow paths, (3) the Horton order is assigned to each link of the reference grid network, and (4) within each coarse grid cell, the elevation of the point lying along the highest-order path of the reference grid network and displaying the minimum distance to the cell center is assigned to this coarse grid cell center. The capabilities of the HD coarsening strategy to provide consistent surface flow paths with respect to those observed in high-resolution DEMs are evaluated over a synthetic valley and two real drainage basins located in the Italian Alps and in the Italian Apennines. The HD coarsening is found to yield significantly more accurate surface flow path profiles than the standard nearest neighbor (NN) coarsening. In addition, the proposed strategy is found to reduce drastically the impact of depression-filling procedures in coarsened topographic data. The HD coarsening strategy is therefore advocated for all those cases in which the relief of the extracted drainage network is an important hydrographic feature. The figure below reports DEMs of a synthetic valley and extracted surface flow paths. (a) 10-m grid DEM displaying no depressions and extracted surface flow path (gray line). (b) 1-km grid DEM obtained from NN coarsening. (c) 1-km grid DEM obtained from NN coarsening plus depression-filling and extracted surface flow path (light blue line). (d) 1-km grid DEM obtained from HD coarsening and extracted surface flow path (magenta line).

  10. Study on distributions and recoveries of tetrachlorodibenzo-p-dioxin and octachlorodibenzo-p-dioxin in a mm5 sampling train

    International Nuclear Information System (INIS)

    Finkel, J.M.; James, R.H.; Baughman, K.W.

    1990-12-01

    14 C-dioxin tracers were used to evaluate whole MM5 sampling train recoveries of dioxin and to determine the distribution of dioxins spiked into a sampling train that was concurrently sampling emissions from a burn of either natural gas ('clean' burn) or kerosene ('dirty' burn). The spike tests were made with a pilot-scale furnace constructed and operated in the laboratory. Recovery of 14 C-dioxin from the MM5 sampling train was determined by scintillation spectrometry. The experimental results indicate that the amount of spiked TCDD- 14 C recovered was approximately 85% during a natural gas test and 83% during a kerosene test. The amount of spiked OCDD- 14 C recovered was approximately 88% during a kerosene test. Also, the data indicate that during the kerosene tests OCDD- 14 C is collected primarily in the front half of the sampling train but TCDD- 14 C is often found in the XAD and the rear filter bell, riser and condenser of the sampling train. During the natural gas tests, TCDD- 14 C was primarily in the XAD. The distribution of the TCDD- 14 C in the kerosene tests was dependent on the rigid operation of the sampling train. The information from the study will be used to determine procedural areas that need improvements or modifications to allow the efficient collection and accurate determination of trace levels of dioxins and furans using the MM5 Method

  11. Data driven model generation based on computational intelligence

    Science.gov (United States)

    Gemmar, Peter; Gronz, Oliver; Faust, Christophe; Casper, Markus

    2010-05-01

    The simulation of discharges at a local gauge or the modeling of large scale river catchments are effectively involved in estimation and decision tasks of hydrological research and practical applications like flood prediction or water resource management. However, modeling such processes using analytical or conceptual approaches is made difficult by both complexity of process relations and heterogeneity of processes. It was shown manifold that unknown or assumed process relations can principally be described by computational methods, and that system models can automatically be derived from observed behavior or measured process data. This study describes the development of hydrological process models using computational methods including Fuzzy logic and artificial neural networks (ANN) in a comprehensive and automated manner. Methods We consider a closed concept for data driven development of hydrological models based on measured (experimental) data. The concept is centered on a Fuzzy system using rules of Takagi-Sugeno-Kang type which formulate the input-output relation in a generic structure like Ri : IFq(t) = lowAND...THENq(t+Δt) = ai0 +ai1q(t)+ai2p(t-Δti1)+ai3p(t+Δti2)+.... The rule's premise part (IF) describes process states involving available process information, e.g. actual outlet q(t) is low where low is one of several Fuzzy sets defined over variable q(t). The rule's conclusion (THEN) estimates expected outlet q(t + Δt) by a linear function over selected system variables, e.g. actual outlet q(t), previous and/or forecasted precipitation p(t ?Δtik). In case of river catchment modeling we use head gauges, tributary and upriver gauges in the conclusion part as well. In addition, we consider temperature and temporal (season) information in the premise part. By creating a set of rules R = {Ri|(i = 1,...,N)} the space of process states can be covered as concise as necessary. Model adaptation is achieved by finding on optimal set A = (aij) of conclusion

  12. 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

  13. Scenario and modelling uncertainty in global mean temperature change derived from emission driven Global Climate Models

    Science.gov (United States)

    Booth, B. B. B.; Bernie, D.; McNeall, D.; Hawkins, E.; Caesar, J.; Boulton, C.; Friedlingstein, P.; Sexton, D.

    2012-09-01

    We compare future changes in global mean temperature in response to different future scenarios which, for the first time, arise from emission driven rather than concentration driven perturbed parameter ensemble of a Global Climate Model (GCM). These new GCM simulations sample uncertainties in atmospheric feedbacks, land carbon cycle, ocean physics and aerosol sulphur cycle processes. We find broader ranges of projected temperature responses arising when considering emission rather than concentration driven simulations (with 10-90 percentile ranges of 1.7 K for the aggressive mitigation scenario up to 3.9 K for the high end business as usual scenario). A small minority of simulations resulting from combinations of strong atmospheric feedbacks and carbon cycle responses show temperature increases in excess of 9 degrees (RCP8.5) and even under aggressive mitigation (RCP2.6) temperatures in excess of 4 K. While the simulations point to much larger temperature ranges for emission driven experiments, they do not change existing expectations (based on previous concentration driven experiments) on the timescale that different sources of uncertainty are important. The new simulations sample a range of future atmospheric concentrations for each emission scenario. Both in case of SRES A1B and the Representative Concentration Pathways (RCPs), the concentration pathways used to drive GCM ensembles lies towards the lower end of our simulated distribution. This design decision (a legecy of previous assessments) is likely to lead concentration driven experiments to under-sample strong feedback responses in concentration driven projections. Our ensemble of emission driven simulations span the global temperature response of other multi-model frameworks except at the low end, where combinations of low climate sensitivity and low carbon cycle feedbacks lead to responses outside our ensemble range. The ensemble simulates a number of high end responses which lie above the CMIP5 carbon

  14. Constraint driven software design: an escape from the waterfall model

    NARCIS (Netherlands)

    de Hoog, Robert; de Jong, Anthonius J.M.; de Vries, Frits

    1994-01-01

    This paper presents the principles of a development methodology for software design. The methodology is based on a nonlinear, product-driven approach that integrates quality aspects. The principles are made more concrete in two examples: one for developing educational simulations and one for

  15. 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...

  16. 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...

  17. Comparison of data-driven and model-driven approaches to brightness temperature diurnal cycle interpolation

    CSIR Research Space (South Africa)

    Van den Bergh, F

    2006-01-01

    Full Text Available This paper presents two new schemes for interpolating missing samples in satellite diurnal temperature cycles (DTCs). The first scheme, referred to here as the cosine model, is an improvement of the model proposed in [2] and combines a cosine...

  18. Modeling of Perpendicularly Driven Dual-Frequency Capacitively Coupled Plasma

    International Nuclear Information System (INIS)

    Wang Hongyu; Sun Peng; Zhao Shuangyun; Li Yang; Jiang Wei

    2016-01-01

    We analyzed perpendicularly configured dual-frequency (DF) capacitively coupled plasmas (CCP). In this configuration, two pairs of electrodes are arranged oppositely, and the discharging is perpendicularly driven by two radio frequency (RF) sources. Particle-in-cell/Monte Carlo (PIC/MC) simulation showed that the configuration had some advantages as this configuration eliminated some dual frequency coupling effects. Some variation and potential application of the discharging configuration is discussed briefly. (paper)

  19. Constraint driven software design: an escape from the waterfall model

    OpenAIRE

    de Hoog, Robert; de Jong, Anthonius J.M.; de Vries, Frits

    1994-01-01

    This paper presents the principles of a development methodology for software design. The methodology is based on a nonlinear, product-driven approach that integrates quality aspects. The principles are made more concrete in two examples: one for developing educational simulations and one for developing expert systems. It is shown that the flexibility needed for building high quality systems leads to integrated development environments in which methodology, product and tools are closely attune...

  20. Deterministic and Advanced Statistical Modeling of Wind-Driven Sea

    Science.gov (United States)

    2015-07-06

    It gives a ground for use an asymptotic approach for wind-driven seas in a spirit of our previous works [R16,R17]. Then we use simple...b𔃼)-—{b’’— b2 ) 1 - --r 2 b-k{\\b’\\2)--{b’k{\\b\\2)) ox *-(6’ 2) -. dx dx dx This equation has localized breather-type solution b{x,t) = B{x

  1. 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.

  2. Employer-driven consumerism: integrating health into the business model.

    Science.gov (United States)

    Thompson, Michael; Checkley, Joseph

    2006-01-01

    Consumer-driven health care is a misnomer. Notwithstanding the enormous role the individual consumer has to play in reshaping the U.S. health care delivery system, this article will focus on the employer as the key driver of change and innovation in the consumerism revolution. American Standard provides a case study of how one major employer has evaluated health care in the context of its business and aggressively integrated consumerism and health into the core of its business. Other companies will appropriately execute consumerism strategies in a fashion consistent with their own needs, culture, resources and populations. However, the principles supporting those strategies will be very much consistent.

  3. Data-Driven Model Reduction and Transfer Operator Approximation

    Science.gov (United States)

    Klus, Stefan; Nüske, Feliks; Koltai, Péter; Wu, Hao; Kevrekidis, Ioannis; Schütte, Christof; Noé, Frank

    2018-06-01

    In this review paper, we will present different data-driven dimension reduction techniques for dynamical systems that are based on transfer operator theory as well as methods to approximate transfer operators and their eigenvalues, eigenfunctions, and eigenmodes. The goal is to point out similarities and differences between methods developed independently by the dynamical systems, fluid dynamics, and molecular dynamics communities such as time-lagged independent component analysis, dynamic mode decomposition, and their respective generalizations. As a result, extensions and best practices developed for one particular method can be carried over to other related methods.

  4. Service and Data Driven Multi Business Model Platform in a World of Persuasive Technologies

    DEFF Research Database (Denmark)

    Andersen, Troels Christian; Bjerrum, Torben Cæsar Bisgaard

    2016-01-01

    companies in establishing a service organization that delivers, creates and captures value through service and data driven business models by utilizing their network, resources and customers and/or users. Furthermore, based on literature and collaboration with the case company, the suggestion of a new...... framework provides the necessary construction of how the manufac- turing companies can evolve their current business to provide multi service and data driven business models, using the same resources, networks and customers....

  5. 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

  6. Model-driven design of simulation support for the TERRA robot software tool suite

    NARCIS (Netherlands)

    Lu, Zhou; Bezemer, M.M.; Broenink, Johannes F.

    2015-01-01

    Model-Driven Development (MDD) – based on the concepts of model, meta-model and model transformation – is an approach to develop predictable and re- liable software for Cyber-Physical Systems (CPS). The work presented here concerns a methodology to design simulation software based on MDD techniques,

  7. 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.

  8. Modeling and evaluation of HE driven shock effects in copper with the MTS model

    International Nuclear Information System (INIS)

    Murphy, M.J.; Lassila, D.F.

    1997-01-01

    Many experimental studies have investigated the effect of shock pressure on the post-shock mechanical properties of OFHC copper. These studies have shown that significant hardening occurs during shock loading due to dislocation processes and twinning. It has been demonstrated that when an appropriate initial value of the Mechanical Threshold Stress (MTS) is specified, the post-shock flow stress of OFE copper is well described by relationships derived independently for unshocked materials. In this study we consider the evolution of the MTS during HE driven shock loading processes and the effect on the subsequent flow stress of the copper. An increased post shock flow stress results in a higher material temperature due to an increase in the plastic work. An increase in temperature leads to thermal softening which reduces the flow stress. These coupled effects will determine if there is melting in a shaped charge jet or a necking instability in an EFP Ww. 'Me critical factor is the evolution path followed combined with the 'current' temperature, plastic strain, and strain rate. Preliminary studies indicate that in simulations of HE driven shock with very high resolution zoning, the MTS saturates because of the rate dependence in the evolution law. On going studies are addressing this and other issues with the goal of developing a version of the MT'S model that treats HE driven, shock loading, temperature, strain, and rate effects apriori

  9. A solvable two-species catalysis-driven aggregation model

    CERN Document Server

    Ke Jian Hong

    2003-01-01

    We study the kinetics of a two-species catalysis-driven aggregation system, in which an irreversible aggregation between any two clusters of one species occurs only with the catalytic action of another species. By means of a generalized mean-field rate equation, we obtain the asymptotic solutions of the cluster mass distributions in a simple process with a constant rate kernel. For the case without any consumption of the catalyst, the cluster mass distribution of either species always approaches a conventional scaling law. However, the evolution behaviour of the system in the case with catalyst consumption is complicated and depends crucially on the relative data of the initial concentrations of the two species.

  10. 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.

  11. 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...

  12. 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

  13. 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,

  14. 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

  15. 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…

  16. A Data-Driven Air Transportation Delay Propagation Model Using Epidemic Process Models

    Directory of Open Access Journals (Sweden)

    B. Baspinar

    2016-01-01

    Full Text Available In air transport network management, in addition to defining the performance behavior of the system’s components, identification of their interaction dynamics is a delicate issue in both strategic and tactical decision-making process so as to decide which elements of the system are “controlled” and how. This paper introduces a novel delay propagation model utilizing epidemic spreading process, which enables the definition of novel performance indicators and interaction rates of the elements of the air transportation network. In order to understand the behavior of the delay propagation over the network at different levels, we have constructed two different data-driven epidemic models approximating the dynamics of the system: (a flight-based epidemic model and (b airport-based epidemic model. The flight-based epidemic model utilizing SIS epidemic model focuses on the individual flights where each flight can be in susceptible or infected states. The airport-centric epidemic model, in addition to the flight-to-flight interactions, allows us to define the collective behavior of the airports, which are modeled as metapopulations. In network model construction, we have utilized historical flight-track data of Europe and performed analysis for certain days involving certain disturbances. Through this effort, we have validated the proposed delay propagation models under disruptive events.

  17. Modeling net ecosystem carbon exchange of alpine grasslands with a satellite-driven model.

    Directory of Open Access Journals (Sweden)

    Wei Yan

    Full Text Available Estimate of net ecosystem carbon exchange (NEE between the atmosphere and terrestrial ecosystems, the balance of gross primary productivity (GPP and ecosystem respiration (Reco has significant importance for studying the regional and global carbon cycles. Using models driven by satellite data and climatic data is a promising approach to estimate NEE at regional scales. For this purpose, we proposed a semi-empirical model to estimate NEE in this study. In our model, the component GPP was estimated with a light response curve of a rectangular hyperbola. The component Reco was estimated with an exponential function of soil temperature. To test the feasibility of applying our model at regional scales, the temporal variations in the model parameters derived from NEE observations in an alpine grassland ecosystem on Tibetan Plateau were investigated. The results indicated that all the inverted parameters exhibit apparent seasonality, which is in accordance with air temperature and canopy phenology. In addition, all the parameters have significant correlations with the remote sensed vegetation indexes or environment temperature. With parameters estimated with these correlations, the model illustrated fair accuracy both in the validation years and at another alpine grassland ecosystem on Tibetan Plateau. Our results also indicated that the model prediction was less accurate in drought years, implying that soil moisture is an important factor affecting the model performance. Incorporating soil water content into the model would be a critical step for the improvement of the model.

  18. Profile-driven regression for modeling and runtime optimization of mobile networks

    DEFF Research Database (Denmark)

    McClary, Dan; Syrotiuk, Violet; Kulahci, Murat

    2010-01-01

    Computer networks often display nonlinear behavior when examined over a wide range of operating conditions. There are few strategies available for modeling such behavior and optimizing such systems as they run. Profile-driven regression is developed and applied to modeling and runtime optimization...... of throughput in a mobile ad hoc network, a self-organizing collection of mobile wireless nodes without any fixed infrastructure. The intermediate models generated in profile-driven regression are used to fit an overall model of throughput, and are also used to optimize controllable factors at runtime. Unlike...

  19. 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...

  20. 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...

  1. Business model driven service architecture design for enterprise application integration

    OpenAIRE

    Gacitua-Decar, Veronica; Pahl, Claus

    2008-01-01

    Increasingly, organisations are using a Service-Oriented Architecture (SOA) as an approach to Enterprise Application Integration (EAI), which is required for the automation of business processes. This paper presents an architecture development process which guides the transition from business models to a service-based software architecture. The process is supported by business reference models and patterns. Firstly, the business process models are enhanced with domain model elements, applicat...

  2. 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.

  3. 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

  4. Advanced Computational Models for Accelerator-Driven Systems

    International Nuclear Information System (INIS)

    Talamo, A.; Ravetto, P.; Gudowsk, W.

    2012-01-01

    In the nuclear engineering scientific community, Accelerator Driven Systems (ADSs) have been proposed and investigated for the transmutation of nuclear waste, especially plutonium and minor actinides. These fuels have a quite low effective delayed neutron fraction relative to uranium fuel, therefore the subcriticality of the core offers a unique safety feature with respect to critical reactors. The intrinsic safety of ADS allows the elimination of the operational control rods, hence the reactivity excess during burnup can be managed by the intensity of the proton beam, fuel shuffling, and eventually by burnable poisons. However, the intrinsic safety of a subcritical system does not guarantee that ADSs are immune from severe accidents (core melting), since the decay heat of an ADS is very similar to the one of a critical system. Normally, ADSs operate with an effective multiplication factor between 0.98 and 0.92, which means that the spallation neutron source contributes little to the neutron population. In addition, for 1 GeV incident protons and lead-bismuth target, about 50% of the spallation neutrons has energy below 1 MeV and only 15% of spallation neutrons has energies above 3 MeV. In the light of these remarks, the transmutation performances of ADS are very close to those of critical reactors.

  5. Positioning performance of the NTCM model driven by GPS Klobuchar model parameters

    Science.gov (United States)

    Hoque, Mohammed Mainul; Jakowski, Norbert; Berdermann, Jens

    2018-03-01

    Users of the Global Positioning System (GPS) utilize the Ionospheric Correction Algorithm (ICA) also known as Klobuchar model for correcting ionospheric signal delay or range error. Recently, we developed an ionosphere correction algorithm called NTCM-Klobpar model for single frequency GNSS applications. The model is driven by a parameter computed from GPS Klobuchar model and consecutively can be used instead of the GPS Klobuchar model for ionospheric corrections. In the presented work we compare the positioning solutions obtained using NTCM-Klobpar with those using the Klobuchar model. Our investigation using worldwide ground GPS data from a quiet and a perturbed ionospheric and geomagnetic activity period of 17 days each shows that the 24-hour prediction performance of the NTCM-Klobpar is better than the GPS Klobuchar model in global average. The root mean squared deviation of the 3D position errors are found to be about 0.24 and 0.45 m less for the NTCM-Klobpar compared to the GPS Klobuchar model during quiet and perturbed condition, respectively. The presented algorithm has the potential to continuously improve the accuracy of GPS single frequency mass market devices with only little software modification.

  6. Modeling of Two-Wheeled Self-Balancing Robot Driven by DC Gearmotors

    Directory of Open Access Journals (Sweden)

    Frankovský P.

    2017-08-01

    Full Text Available This paper is aimed at modelling a two-wheeled self-balancing robot driven by the geared DC motors. A mathematical model consists of two main parts, the model of robot’s mechanical structure and the model of the actuator. Linearized equations of motion are derived and the overall model of the two-wheeled self-balancing robot is represented in state-space realization for the purpose of state feedback controller design.

  7. Modeling of Two-Wheeled Self-Balancing Robot Driven by DC Gearmotors

    Science.gov (United States)

    Frankovský, P.; Dominik, L.; Gmiterko, A.; Virgala, I.; Kurylo, P.; Perminova, O.

    2017-08-01

    This paper is aimed at modelling a two-wheeled self-balancing robot driven by the geared DC motors. A mathematical model consists of two main parts, the model of robot's mechanical structure and the model of the actuator. Linearized equations of motion are derived and the overall model of the two-wheeled self-balancing robot is represented in state-space realization for the purpose of state feedback controller design.

  8. 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.

  9. Data Driven Broiler Weight Forecasting using Dynamic Neural Network Models

    DEFF Research Database (Denmark)

    Johansen, Simon Vestergaard; Bendtsen, Jan Dimon; Riisgaard-Jensen, Martin

    2017-01-01

    In this article, the dynamic influence of environmental broiler house conditions and broiler growth is investigated. Dynamic neural network forecasting models have been trained on farm-scale broiler batch production data from 12 batches from the same house. The model forecasts future broiler weight...... and uses environmental conditions such as heating, ventilation, and temperature along with broiler behavior such as feed and water consumption. Training data and forecasting data is analyzed to explain when the model might fail at generalizing. We present ensemble broiler weight forecasts to day 7, 14, 21...

  10. 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,

  11. Development of flexible process-centric web applications: An integrated model driven approach

    NARCIS (Netherlands)

    Bernardi, M.L.; Cimitile, M.; Di Lucca, G.A.; Maggi, F.M.

    2012-01-01

    In recent years, Model Driven Engineering (MDE) approaches have been proposed and used to develop and evolve WAs. However, the definition of appropriate MDE approaches for the development of flexible process-centric WAs is still limited. In particular, (flexible) workflow models have never been

  12. The state of the art of innovation-driven business models in the financial services industry

    NARCIS (Netherlands)

    Lüftenegger, E.R.; Angelov, S.A.; Linden, van der E.; Grefen, P.W.P.J.

    2010-01-01

    Emerging innovation-driven business models are changing the financial services landscape. Most companies are using innovation to sustain their business models. However, new entrants into the financial services market innovate in a way that disrupts the industry. Typically, directions for innovation

  13. Biodefense-driven murine model of pneumonic melioidosis.

    Science.gov (United States)

    Jeddeloh, J A; Fritz, D L; Waag, D M; Hartings, J M; Andrews, G P

    2003-01-01

    A whole-body mouse model of pneumonic melioidosis was established for future evaluation of biodefense vaccine candidates. The aerosol 50% lethal doses of Burkholderia pseudomallei strain 1026b for BALB/c and C57BL/6 mice and the times to death, dissemination in organs, and tissue loads after exposure of the mice to low- and high-dose aerosols are reported. In addition, rpsL mutant backgrounds were attenuated in this acute model of disease.

  14. Studies on modelling of bubble driven flows in chemical reactors

    Energy Technology Data Exchange (ETDEWEB)

    Grevskott, Sverre

    1997-12-31

    Multiphase reactors are widely used in the process industry, especially in the petrochemical industry. They very often are characterized by very good thermal control and high heat transfer coefficients against heating and cooling surfaces. This thesis first reviews recent advances in bubble column modelling, focusing on the fundamental flow equations, drag forces, transversal forces and added mass forces. The mathematical equations for the bubble column reactor are developed, using an Eulerian description for the continuous and dispersed phase in tensor notation. Conservation equations for mass, momentum, energy and chemical species are given, and the k-{epsilon} and Rice-Geary models for turbulence are described. The different algebraic solvers used in the model are described, as are relaxation procedures. Simulation results are presented and compared with experimental values. Attention is focused on the modelling of void fractions and gas velocities in the column. The energy conservation equation has been included in the bubble column model in order to model temperature distributions in a heated reactor. The conservation equation of chemical species has been included to simulate absorption of CO{sub 2}. Simulated axial and radial mass fraction profiles for CO{sub 2} in the gas phase are compared with measured values. Simulations of the dynamic behaviour of the column are also presented. 189 refs., 124 figs., 1 tab.

  15. Data-driven modelling of structured populations a practical guide to the integral projection model

    CERN Document Server

    Ellner, Stephen P; Rees, Mark

    2016-01-01

    This book is a “How To” guide for modeling population dynamics using Integral Projection Models (IPM) starting from observational data. It is written by a leading research team in this area and includes code in the R language (in the text and online) to carry out all computations. The intended audience are ecologists, evolutionary biologists, and mathematical biologists interested in developing data-driven models for animal and plant populations. IPMs may seem hard as they involve integrals. The aim of this book is to demystify IPMs, so they become the model of choice for populations structured by size or other continuously varying traits. The book uses real examples of increasing complexity to show how the life-cycle of the study organism naturally leads to the appropriate statistical analysis, which leads directly to the IPM itself. A wide range of model types and analyses are presented, including model construction, computational methods, and the underlying theory, with the more technical material in B...

  16. Test-Driven, Model-Based Systems Engineering

    DEFF Research Database (Denmark)

    Munck, Allan

    Hearing systems have evolved over many years from simple mechanical devices (horns) to electronic units consisting of microphones, amplifiers, analog filters, loudspeakers, batteries, etc. Digital signal processors replaced analog filters to provide better performance end new features. Central....... This thesis concerns methods for identifying, selecting and implementing tools for various aspects of model-based systems engineering. A comprehensive method was proposed that include several novel steps such as techniques for analyzing the gap between requirements and tool capabilities. The method...... was verified with good results in two case studies for selection of a traceability tool (single-tool scenario) and a set of modeling tools (multi-tool scenarios). Models must be subjected to testing to allow engineers to predict functionality and performance of systems. Test-first strategies are known...

  17. An induction Linac driven heavy-ion fusion systems model

    International Nuclear Information System (INIS)

    Zuckerman, D.S.; Driemeyer, D.E.; Waganer, L.M.; Dudziak, D.J.

    1988-01-01

    A computerized systems model of a heavy-ion fusion (HIF) reactor power plant is presented. The model can be used to analyze the behavior and projected costs of a commercial power plant using an induction linear accelerator (Linac) as a driver. Each major component of the model (targets, reactor cavity, Linac, beam transport, power flow, balance of plant, and costing) is discussed. Various target, reactor cavity, Linac, and beam transport schemes are examined and compared. The preferred operating regime for such a power plant is also examined. The results show that HIF power plants can compete with other advanced energy concepts at the 1000-MW (electric) power level [cost of electricity (COE) -- 50 mill/kW . h] provided that the cost savings predicted for Linacs using higher charge-state ions (+3) can be realized

  18. Experimentally driven atomistic model of 1,2 polybutadiene

    Energy Technology Data Exchange (ETDEWEB)

    Gkourmpis, Thomas, E-mail: thomas.gkourmpis@borealisgroup.com [Polymer Science Centre, J. J. Thomson Physical Laboratory, Department of Physics, University of Reading, Reading RG6 6AF (United Kingdom); Mitchell, Geoffrey R. [Polymer Science Centre, J. J. Thomson Physical Laboratory, Department of Physics, University of Reading, Reading RG6 6AF (United Kingdom); Centre for Rapid and Sustainable Product Development, Institute Polytechnic Leiria, Marinha Grande (Portugal)

    2014-02-07

    We present an efficient method of combining wide angle neutron scattering data with detailed atomistic models, allowing us to perform a quantitative and qualitative mapping of the organisation of the chain conformation in both glass and liquid phases. The structural refinement method presented in this work is based on the exploitation of the intrachain features of the diffraction pattern and its intimate linkage with atomistic models by the use of internal coordinates for bond lengths, valence angles, and torsion rotations. Atomic connectivity is defined through these coordinates that are in turn assigned by pre-defined probability distributions, thus allowing for the models in question to be built stochastically. Incremental variation of these coordinates allows for the construction of models that minimise the differences between the observed and calculated structure factors. We present a series of neutron scattering data of 1,2 polybutadiene at the region 120–400 K. Analysis of the experimental data yields bond lengths for Cî—¸C and C î—» C of 1.54 Å and 1.35 Å, respectively. Valence angles of the backbone were found to be at 112° and the torsion distributions are characterised by five rotational states, a three-fold trans-skew± for the backbone and gauche± for the vinyl group. Rotational states of the vinyl group were found to be equally populated, indicating a largely atactic chan. The two backbone torsion angles exhibit different behaviour with respect to temperature of their trans population, with one of them adopting an almost all trans sequence. Consequently, the resulting configuration leads to a rather persistent chain, something indicated by the value of the characteristic ratio extrapolated from the model. We compare our results with theoretical predictions, computer simulations, RIS models and previously reported experimental results.

  19. Modeling Quasi-Static and Fatigue-Driven Delamination Migration

    Science.gov (United States)

    De Carvalho, N. V.; Ratcliffe, J. G.; Chen, B. Y.; Pinho, S. T.; Baiz, P. M.; Tay, T. E.

    2014-01-01

    An approach was proposed and assessed for the high-fidelity modeling of progressive damage and failure in composite materials. It combines the Floating Node Method (FNM) and the Virtual Crack Closure Technique (VCCT) to represent multiple interacting failure mechanisms in a mesh-independent fashion. Delamination, matrix cracking, and migration were captured failure and migration criteria based on fracture mechanics. Quasi-static and fatigue loading were modeled within the same overall framework. The methodology proposed was illustrated by simulating the delamination migration test, showing good agreement with the available experimental data.

  20. Ultrasound-driven Viscous Streaming, Modelled via Momentum Injection

    Directory of Open Access Journals (Sweden)

    James PACKER

    2008-12-01

    Full Text Available Microfluidic devices can use steady streaming caused by the ultrasonic oscillation of one or many gas bubbles in a liquid to drive small scale flow. Such streaming flows are difficult to evaluate, as analytic solutions are not available for any but the simplest cases, and direct computational fluid dynamics models are unsatisfactory due to the large difference in flow velocity between the steady streaming and the leading order oscillatory motion. We develop a numerical technique which uses a two-stage multiscale computational fluid dynamics approach to find the streaming flow as a steady problem, and validate this model against experimental results.

  1. A Model-Driven, Science Data Product Registration Service

    Science.gov (United States)

    Hardman, S.; Ramirez, P.; Hughes, J. S.; Joyner, R.; Cayanan, M.; Lee, H.; Crichton, D. J.

    2011-12-01

    The Planetary Data System (PDS) has undertaken an effort to overhaul the PDS data architecture (including the data model, data structures, data dictionary, etc.) and to deploy an upgraded software system (including data services, distributed data catalog, etc.) that fully embraces the PDS federation as an integrated system while taking advantage of modern innovations in information technology (including networking capabilities, processing speeds, and software breakthroughs). A core component of this new system is the Registry Service that will provide functionality for tracking, auditing, locating, and maintaining artifacts within the system. These artifacts can range from data files and label files, schemas, dictionary definitions for objects and elements, documents, services, etc. This service offers a single reference implementation of the registry capabilities detailed in the Consultative Committee for Space Data Systems (CCSDS) Registry Reference Model White Book. The CCSDS Reference Model in turn relies heavily on the Electronic Business using eXtensible Markup Language (ebXML) standards for registry services and the registry information model, managed by the OASIS consortium. Registries are pervasive components in most information systems. For example, data dictionaries, service registries, LDAP directory services, and even databases provide registry-like services. These all include an account of informational items that are used in large-scale information systems ranging from data values such as names and codes, to vocabularies, services and software components. The problem is that many of these registry-like services were designed with their own data models associated with the specific type of artifact they track. Additionally these services each have their own specific interface for interacting with the service. This Registry Service implements the data model specified in the ebXML Registry Information Model (RIM) specification that supports the various

  2. Verification-Driven Slicing of UML/OCL Models

    DEFF Research Database (Denmark)

    Shaikh, Asadullah; Clarisó Viladrosa, Robert; Wiil, Uffe Kock

    2010-01-01

    computational complexity can limit their scalability. In this paper, we consider a specific static model (UML class diagrams annotated with unrestricted OCL constraints) and a specific property to verify (satisfiability, i.e., “is it possible to create objects without violating any constraint?”). Current...... approaches to this problem have an exponential worst-case runtime. We propose a technique to improve their scalability by partitioning the original model into submodels (slices) which can be verified independently and where irrelevant information has been abstracted. The definition of the slicing procedure...

  3. Detailed modelling of the susceptibility of a thermally populated, strongly driven circuit-QED system

    International Nuclear Information System (INIS)

    Kockum, Anton Frisk; Johansson, Göran; Sandberg, Martin; Vissers, Michael R; Gao, Jiansong; Pappas, David P

    2013-01-01

    We present measurements and modelling of the susceptibility of a 2D microstrip cavity coupled to a driven transmon qubit. We are able to fit the response of the cavity to a weak probe signal with high accuracy in the strong coupling, low detuning, i.e., non-dispersive, limit over a wide bandwidth. The observed spectrum is rich in multi-photon processes for the doubly dressed transmon. These features are well explained by including the higher transmon levels in the driven Jaynes–Cummings model and solving the full master equation to calculate the susceptibility of the cavity. (paper)

  4. 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....

  5. Unraveling Supply-Driven Business Models of Architectural Firms

    NARCIS (Netherlands)

    Bos-De Vos, M.; Volker, L.; Wamelink, J.W.F.; Kaminsky, Jessica; Zerjav, Vedran

    2016-01-01

    Architectural firms deliver services for various, unique projects that are all characterized by a high level of uncertainty. To successfully propose, create and capture value, they need business models that are able to deal with this variety and uncertainty. So far, little is known about the

  6. Models of plastic depinning of driven disordered systems

    Indian Academy of Sciences (India)

    The second class allows for proliferation of topological defects due to the interplay of strong disorder and drive. In mean field theory both models exhibit a tricritical point as a function of disorder strength. At weak disorder depinning is continuous and the sliding state is unique. At strong disorder depinning is discontinuous ...

  7. Model-Driven Development for PDS4 Software and Services

    Science.gov (United States)

    Hughes, J. S.; Crichton, D. J.; Algermissen, S. S.; Cayanan, M. D.; Joyner, R. S.; Hardman, S. H.; Padams, J. H.

    2018-04-01

    PDS4 data product labels provide the information necessary for processing the referenced digital object. However, significantly more information is available in the PDS4 Information Model. This additional information is made available for use, by both software and services, to configure, promote resiliency, and improve interoperability.

  8. A model of ant route navigation driven by scene familiarity.

    Directory of Open Access Journals (Sweden)

    Bart Baddeley

    2012-01-01

    Full Text Available In this paper we propose a model of visually guided route navigation in ants that captures the known properties of real behaviour whilst retaining mechanistic simplicity and thus biological plausibility. For an ant, the coupling of movement and viewing direction means that a familiar view specifies a familiar direction of movement. Since the views experienced along a habitual route will be more familiar, route navigation can be re-cast as a search for familiar views. This search can be performed with a simple scanning routine, a behaviour that ants have been observed to perform. We test this proposed route navigation strategy in simulation, by learning a series of routes through visually cluttered environments consisting of objects that are only distinguishable as silhouettes against the sky. In the first instance we determine view familiarity by exhaustive comparison with the set of views experienced during training. In further experiments we train an artificial neural network to perform familiarity discrimination using the training views. Our results indicate that, not only is the approach successful, but also that the routes that are learnt show many of the characteristics of the routes of desert ants. As such, we believe the model represents the only detailed and complete model of insect route guidance to date. What is more, the model provides a general demonstration that visually guided routes can be produced with parsimonious mechanisms that do not specify when or what to learn, nor separate routes into sequences of waypoints.

  9. 25 Years of Model-Driven Web Engineering: What we achieved, What is missing

    Directory of Open Access Journals (Sweden)

    Gustavo Rossi

    2016-12-01

    Full Text Available Model-Driven Web Engineering (MDWE approaches aim to improve the Web applications development process by focusing on modeling instead of coding, and deriving the running application by transformations from conceptual models to code. The emergence of the Interaction Flow Modeling Language (IFML has been an important milestone in the evolution of Web modeling languages, indicating not only the maturity of the field but also a final convergence of languages. In this paper we explain the evolution of modeling and design approaches since the early years (in the 90’s detailing the forces which drove that evolution and discussing the strengths and weaknesses of some of those approaches. A brief presentation of the IFML is accompanied with a thorough analysis of the most important achievements of the MDWE community as well as the problems and obstacles that hinder the dissemination of model-driven techniques in the Web engineering field.

  10. Model and information abstraction for description-driven systems

    International Nuclear Information System (INIS)

    Estrella, F.; McClatchey, R.; Kovacs, Z.; Goff, J.-M.L.

    2001-01-01

    A crucial factor in the creation of adaptable systems dealing with changing requirements is the suitability of the underlying technology in allowing the evolution of the system. A reflective system utilizes an open architecture where implicit system aspects are reified to become explicit first-class (meta-data) objects. These implicit system aspects are often fundamental structures which are inaccessible and immutable, and their reification as meta-data objects can serve as the basis for changes and extensions to the system, making it self-describing. To address the evolvability issue, the author proposes a reflective architecture based on two orthogonal abstractions-model abstraction and information abstraction. In this architecture the modeling abstractions allow for the separation of the description meta-data from the system aspects they represent so that they can be managed and versioned independently, asynchronously and explicitly

  11. Quantum dynamics of the driven and dissipative Rabi model

    Science.gov (United States)

    Henriet, Loïc; Ristivojevic, Zoran; Orth, Peter P.; Le Hur, Karyn

    2014-08-01

    The Rabi model considers a two-level system (or spin 1/2) coupled to a quantized harmonic oscillator and describes the simplest interaction between matter and light. The recent experimental progress in solid-state circuit quantum electrodynamics has engendered theoretical efforts to quantitatively describe the mathematical and physical aspects of the light-matter interaction beyond the rotating-wave approximation. We develop a stochastic Schrödinger equation approach which enables us to access the strong-coupling limit of the Rabi model and study the effects of dissipation and ac drive in an exact manner. We include the effect of Ohmic noise on the non-Markovian spin dynamics, resulting in Kondo-type correlations, as well as cavity losses. We compute the time evolution of spin variables in various conditions. As a consideration for future work, we discuss the possibility of reaching a steady state with one polariton in realistic experimental conditions.

  12. Model-Driven Test Generation of Distributed Systems

    Science.gov (United States)

    Easwaran, Arvind; Hall, Brendan; Schweiker, Kevin

    2012-01-01

    This report describes a novel test generation technique for distributed systems. Utilizing formal models and formal verification tools, spe cifically the Symbolic Analysis Laboratory (SAL) tool-suite from SRI, we present techniques to generate concurrent test vectors for distrib uted systems. These are initially explored within an informal test validation context and later extended to achieve full MC/DC coverage of the TTEthernet protocol operating within a system-centric context.

  13. Model-Driven Engineering: Automatic Code Generation and Beyond

    Science.gov (United States)

    2015-03-01

    herein to any specific commercial product, process, or service by trade name, trade mark, manufacturer , or otherwise, does not necessarily constitute or...export of an Extensible Markup Language (XML) representation of the model. The XML Metadata Interchange (XMI) is an OMG standard for representing...overall company financial results for the past 3 years. What financial re- sults are you projecting for the next year? 1.2.5.2 Percentage of Gross

  14. 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...

  15. Temperature driven annealing of perforations in bicellar model membranes.

    Science.gov (United States)

    Nieh, Mu-Ping; Raghunathan, V A; Pabst, Georg; Harroun, Thad; Nagashima, Kazuomi; Morales, Hannah; Katsaras, John; Macdonald, Peter

    2011-04-19

    Bicellar model membranes composed of 1,2-dimyristoylphosphatidylcholine (DMPC) and 1,2-dihexanoylphosphatidylcholine (DHPC), with a DMPC/DHPC molar ratio of 5, and doped with the negatively charged lipid 1,2-dimyristoylphosphatidylglycerol (DMPG), at DMPG/DMPC molar ratios of 0.02 or 0.1, were examined using small angle neutron scattering (SANS), (31)P NMR, and (1)H pulsed field gradient (PFG) diffusion NMR with the goal of understanding temperature effects on the DHPC-dependent perforations in these self-assembled membrane mimetics. Over the temperature range studied via SANS (300-330 K), these bicellar lipid mixtures exhibited a well-ordered lamellar phase. The interlamellar spacing d increased with increasing temperature, in direct contrast to the decrease in d observed upon increasing temperature with otherwise identical lipid mixtures lacking DHPC. (31)P NMR measurements on magnetically aligned bicellar mixtures of identical composition indicated a progressive migration of DHPC from regions of high curvature into planar regions with increasing temperature, and in accord with the "mixed bicelle model" (Triba, M. N.; Warschawski, D. E.; Devaux, P. E. Biophys. J.2005, 88, 1887-1901). Parallel PFG diffusion NMR measurements of transbilayer water diffusion, where the observed diffusion is dependent on the fractional surface area of lamellar perforations, showed that transbilayer water diffusion decreased with increasing temperature. A model is proposed consistent with the SANS, (31)P NMR, and PFG diffusion NMR data, wherein increasing temperature drives the progressive migration of DHPC out of high-curvature regions, consequently decreasing the fractional volume of lamellar perforations, so that water occupying these perforations redistributes into the interlamellar volume, thereby increasing the interlamellar spacing. © 2011 American Chemical Society

  16. Scidac-Data: Enabling Data Driven Modeling of Exascale Computing

    Science.gov (United States)

    Mubarak, Misbah; Ding, Pengfei; Aliaga, Leo; Tsaris, Aristeidis; Norman, Andrew; Lyon, Adam; Ross, Robert

    2017-10-01

    The SciDAC-Data project is a DOE-funded initiative to analyze and exploit two decades of information and analytics that have been collected by the Fermilab data center on the organization, movement, and consumption of high energy physics (HEP) data. The project analyzes the analysis patterns and data organization that have been used by NOvA, MicroBooNE, MINERvA, CDF, D0, and other experiments to develop realistic models of HEP analysis workflows and data processing. The SciDAC-Data project aims to provide both realistic input vectors and corresponding output data that can be used to optimize and validate simulations of HEP analysis. These simulations are designed to address questions of data handling, cache optimization, and workflow structures that are the prerequisites for modern HEP analysis chains to be mapped and optimized to run on the next generation of leadership-class exascale computing facilities. We present the use of a subset of the SciDAC-Data distributions, acquired from analysis of approximately 71,000 HEP workflows run on the Fermilab data center and corresponding to over 9 million individual analysis jobs, as the input to detailed queuing simulations that model the expected data consumption and caching behaviors of the work running in high performance computing (HPC) and high throughput computing (HTC) environments. In particular we describe how the Sequential Access via Metadata (SAM) data-handling system in combination with the dCache/Enstore-based data archive facilities has been used to develop radically different models for analyzing the HEP data. We also show how the simulations may be used to assess the impact of design choices in archive facilities.

  17. Translation from mathematical model to data driven knowledge

    OpenAIRE

    Boixareu Fiol, Margarita

    2017-01-01

    Prove if with the acquisition of new samples of data the knowledge we can obtain is more accurate. The projects centers in the data obtained from the patient-specific calibration of a computer simulation of a human heart. Neural networks are used to understand the relation input-output of the data and they are compared with a physical model that relates them. Input data are some parameters of the heart and the output data is the elastance of the heart (variation of pressure/ variation of volu...

  18. Subgrid Modeling of AGN-driven Turbulence in Galaxy Clusters

    Science.gov (United States)

    Scannapieco, Evan; Brüggen, Marcus

    2008-10-01

    Hot, underdense bubbles powered by active galactic nuclei (AGNs) are likely to play a key role in halting catastrophic cooling in the centers of cool-core galaxy clusters. We present three-dimensional simulations that capture the evolution of such bubbles, using an adaptive mesh hydrodynamic code, FLASH3, to which we have added a subgrid model of turbulence and mixing. While pure hydro simulations indicate that AGN bubbles are disrupted into resolution-dependent pockets of underdense gas, proper modeling of subgrid turbulence indicates that this is a poor approximation to a turbulent cascade that continues far beyond the resolution limit. Instead, Rayleigh-Taylor instabilities act to effectively mix the heated region with its surroundings, while at the same time preserving it as a coherent structure, consistent with observations. Thus, bubbles are transformed into hot clouds of mixed material as they move outward in the hydrostatic intracluster medium (ICM), much as large airbursts lead to a distinctive "mushroom cloud" structure as they rise in the hydrostatic atmosphere of Earth. Properly capturing the evolution of such clouds has important implications for many ICM properties. In particular, it significantly changes the impact of AGNs on the distribution of entropy and metals in cool-core clusters such as Perseus.

  19. 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.

  20. Data-driven modeling of solar-powered urban microgrids.

    Science.gov (United States)

    Halu, Arda; Scala, Antonio; Khiyami, Abdulaziz; González, Marta C

    2016-01-01

    Distributed generation takes center stage in today's rapidly changing energy landscape. Particularly, locally matching demand and generation in the form of microgrids is becoming a promising alternative to the central distribution paradigm. Infrastructure networks have long been a major focus of complex networks research with their spatial considerations. We present a systemic study of solar-powered microgrids in the urban context, obeying real hourly consumption patterns and spatial constraints of the city. We propose a microgrid model and study its citywide implementation, identifying the self-sufficiency and temporal properties of microgrids. Using a simple optimization scheme, we find microgrid configurations that result in increased resilience under cost constraints. We characterize load-related failures solving power flows in the networks, and we show the robustness behavior of urban microgrids with respect to optimization using percolation methods. Our findings hint at the existence of an optimal balance between cost and robustness in urban microgrids.

  1. Inspired by design and driven by innovation. A conceptual model for radical design driven as a sustainable business model for Malaysian furniture design

    Science.gov (United States)

    Yusof, Wan Zaiyana Mohd; Fadzline Muhamad Tamyez, Puteri

    2018-04-01

    The definition of innovation does not help the entrepreneurs, business person or innovator to truly grasp what it means to innovate, hence we hear that government has spend millions of ringgit on “innovation” by doing R & D. However, the result has no avail in terms of commercial value. Innovation can be defined as the exploitation of commercialization of an idea or invention to create economic or social value. Most Entrepreneurs and business managers, regard innovation as creating economic value, while forgetting that innovation also create value for society or the environment. The ultimate goal as Entrepreneur, inventor or researcher is to exploit innovation to create value. As changes happen in society and economy, organizations and enterprises have to keep up and this requires innovation. This conceptual paper is to study the radical design driven innovation in the Malaysian furniture industry as a business model which the overall aim of the study is to examine the radical design driven innovation in Malaysia and how it compares with findings from Western studies. This paper will familiarize readers with the innovation and describe the radical design driven perspective that is adopted in its conceptual framework and design process.

  2. Parameterized data-driven fuzzy model based optimal control of a semi-batch reactor.

    Science.gov (United States)

    Kamesh, Reddi; Rani, K Yamuna

    2016-09-01

    A parameterized data-driven fuzzy (PDDF) model structure is proposed for semi-batch processes, and its application for optimal control is illustrated. The orthonormally parameterized input trajectories, initial states and process parameters are the inputs to the model, which predicts the output trajectories in terms of Fourier coefficients. Fuzzy rules are formulated based on the signs of a linear data-driven model, while the defuzzification step incorporates a linear regression model to shift the domain from input to output domain. The fuzzy model is employed to formulate an optimal control problem for single rate as well as multi-rate systems. Simulation study on a multivariable semi-batch reactor system reveals that the proposed PDDF modeling approach is capable of capturing the nonlinear and time-varying behavior inherent in the semi-batch system fairly accurately, and the results of operating trajectory optimization using the proposed model are found to be comparable to the results obtained using the exact first principles model, and are also found to be comparable to or better than parameterized data-driven artificial neural network model based optimization results. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  3. 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.

  4. On Lévy-driven vacation models with correlated busy periods and service interruptions

    NARCIS (Netherlands)

    Kella, O.; Boxma, O.; Mandjes, M.

    2010-01-01

    This paper considers queues with server vacations, but departs from the traditional setting in two ways: (i) the queueing model is driven by Lévy processes rather than just compound Poisson processes; (ii) the vacation lengths depend on the length of the server’s preceding busy period. Regarding the

  5. Way of Working for Embedded Control Software using Model-Driven Development Techniques

    NARCIS (Netherlands)

    Bezemer, M.M.; Groothuis, M.A.; Brugali, D.; Schlegel, C.; Broenink, Johannes F.

    2011-01-01

    Embedded targets normally do not have much resources to aid developing and debugging the software. So model-driven development (MDD) is used for designing embedded software with a `first time right' approach. For such an approach, a good way of working (WoW) is required for embedded software

  6. The Model-Driven openETCS Paradigm for Secure, Safe and Certifiable Train Control Systems

    DEFF Research Database (Denmark)

    Peleska, Jan; Feuser, Johannes; Haxthausen, Anne Elisabeth

    2012-01-01

    -driven openETCS approach, a threat analysis is performed, identifying both safety and security hazards that may be common to all model-based development paradigms for safety-critical railway control systems, or specific to the openETCS approach. In the subsequent sections state-of-the-art methods suitable...

  7. An investigation of potential success factors for an introductory model-driven programming course

    DEFF Research Database (Denmark)

    Bennedsen, Jens; Caspersen, Michael Edelgaard

    2005-01-01

    In order to improve the course design of a CS1 model-driven programming course we study potential indicators of success for such a course. We explain our specific interpretation of objects-first. Of eight potential indicators of success, we have found only two to be significant at a 95% confidence...

  8. Towards a Multi-Stakeholder-Driven Model for Excellence in Higher Education Curriculum Development

    Science.gov (United States)

    Meyer, M. H.; Bushney, M. J.

    2008-01-01

    A multi-stakeholder-driven model for excellence in higher education curriculum development has been developed. It is based on the assumption that current efforts to curriculum development take place within a framework of limited stakeholder consultation. A total of 18 multiple stakeholders are identified, including learners, alumni, government,…

  9. Numerical model for wind-driven circulation in the Bay of Bengal

    Digital Repository Service at National Institute of Oceanography (India)

    Bahulayan, N.; Varadachari, V.V.R.

    Wind-driven circulation in the Bay of Bengal, generated by a southwest wind of constant speed (10 m.sec -1) and direction (225 degrees TN), is presented. A non-linear hydrodynamic model is used for the simulation of circulation. Numerical...

  10. Business Process Modelling in Demand-Driven Agri-Food Supply Chains

    NARCIS (Netherlands)

    Verdouw, C.N.; Beulens, A.J.M.; Trienekens, J.H.; Wolfert, J.

    2010-01-01

    Agri-food companies increasingly participate in demand-driven supply chains that are able to adapt flexibly to changes in the marketplace. The objective of this presentation is to discuss a process modelling framework, which enhances the interoperability and agility of information systems as

  11. Model-driven design-space exploration for embedded systems: the Octopus Toolset

    NARCIS (Netherlands)

    Basten, T.; van Benthum, E.; Geilen, M.C.W.; Hendriks, M.; Houben, F.; Igna, G.; Reckers, F.J.; Smet, de S.; Somers, L.J.A.M.; Teeselink, Egbert; Trcka, N.; Vaandrager, F.W.; Verriet, J.H.; Voorhoeve, M.; Yang, Y.; Margaria, T.; Steffen, B.

    2010-01-01

    The complexity of today’s embedded systems and their development trajectories requires a systematic, model-driven design approach, supported by tooling wherever possible. Only then, development trajectories become manageable, with high-quality, cost-effective results. This paper introduces the

  12. A Proposal to Elicit Usability Requirements within a Model-Driven Development Environment

    NARCIS (Netherlands)

    Isela Ormeno, Y; Panach, I; Condori-Fernandez, O.N.; Pastor, O.

    2014-01-01

    Nowadays there are sound Model-Driven Development (MDD) methods that deal with functional requirements, but in general, usability is not considered from the early stages of the development. Analysts that work with MDD implement usability features manually once the code has been generated. This

  13. A Monthly Water-Balance Model Driven By a Graphical User Interface

    Science.gov (United States)

    McCabe, Gregory J.; Markstrom, Steven L.

    2007-01-01

    This report describes a monthly water-balance model driven by a graphical user interface, referred to as the Thornthwaite monthly water-balance program. Computations of monthly water-balance components of the hydrologic cycle are made for a specified location. The program can be used as a research tool, an assessment tool, and a tool for classroom instruction.

  14. Automated analyses of model-driven artifacts : obtaining insights into industrial application of MDE

    NARCIS (Netherlands)

    Mengerink, J.G.M.; Serebrenik, A.; Schiffelers, R.R.H.; van den Brand, M.G.J.

    2017-01-01

    Over the past years, there has been an increase in the application of model driven engineering in industry. Similar to traditional software engineering, understanding how technologies are actually used in practice is essential for developing good tooling, and decision making processes.

  15. Defining the limits of homology modeling in information-driven protein docking

    NARCIS (Netherlands)

    Garcia Lopes Maia Rodrigues, João; Melquiond, A S J; Karaca, E; Trellet, M; van Dijk, M; van Zundert, G C P; Schmitz, C; de Vries, S J; Bordogna, A; Bonati, L; Kastritis, P L; Bonvin, Alexandre M J J; Garcia Lopes Maia Rodrigues, João

    2013-01-01

    Information-driven docking is currently one of the most successful approaches to obtain structural models of protein interactions as demonstrated in the latest round of CAPRI. While various experimental and computational techniques can be used to retrieve information about the binding mode, the

  16. Elsevier special issue on foundations and applications of model driven architecture

    NARCIS (Netherlands)

    Aksit, Mehmet; Ivanov, Ivan

    2008-01-01

    Model Driven Architecture (MDA) is an approach for software development proposed by Object Management Group (OMG). The basic principle of MDA is the separation of the specification of system functionality from the specification of the implementation of that functionality on a specific platform. The

  17. The MDE Diploma: First International Postgraduate Specialization in Model-Driven Engineering

    Science.gov (United States)

    Cabot, Jordi; Tisi, Massimo

    2011-01-01

    Model-Driven Engineering (MDE) is changing the way we build, operate, and maintain our software-intensive systems. Several projects using MDE practices are reporting significant improvements in quality and performance but, to be able to handle these projects, software engineers need a set of technical and interpersonal skills that are currently…

  18. Assessing Satisfaction with Selected Student Services Using SERVQUAL, a Market-Driven Model of Service Quality.

    Science.gov (United States)

    Ruby, Carl A.

    1998-01-01

    Demonstrates how the use of SERVQUAL, a market-driven assessment model adapted from business, can be used to study student satisfaction with four areas of support services hypothetically related to enrollment management. The sample included 748 students enrolled in general education courses at ten different private institutions. (Contains 27…

  19. Implementation of Argument-Driven Inquiry as an Instructional Model in a General Chemistry Laboratory Course

    Science.gov (United States)

    Kadayifci, Hakki; Yalcin-Celik, Ayse

    2016-01-01

    This study examined the effectiveness of Argument-Driven Inquiry (ADI) as an instructional model in a general chemistry laboratory course. The study was conducted over the course of ten experimental sessions with 125 pre-service science teachers. The participants' level of reflective thinking about the ADI activities, changes in their science…

  20. 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...

  1. Nonperturbative stochastic method for driven spin-boson model

    Science.gov (United States)

    Orth, Peter P.; Imambekov, Adilet; Le Hur, Karyn

    2013-01-01

    We introduce and apply a numerically exact method for investigating the real-time dissipative dynamics of quantum impurities embedded in a macroscopic environment beyond the weak-coupling limit. We focus on the spin-boson Hamiltonian that describes a two-level system interacting with a bosonic bath of harmonic oscillators. This model is archetypal for investigating dissipation in quantum systems, and tunable experimental realizations exist in mesoscopic and cold-atom systems. It finds abundant applications in physics ranging from the study of decoherence in quantum computing and quantum optics to extended dynamical mean-field theory. Starting from the real-time Feynman-Vernon path integral, we derive an exact stochastic Schrödinger equation that allows us to compute the full spin density matrix and spin-spin correlation functions beyond weak coupling. We greatly extend our earlier work [P. P. Orth, A. Imambekov, and K. Le Hur, Phys. Rev. APLRAAN1050-294710.1103/PhysRevA.82.032118 82, 032118 (2010)] by fleshing out the core concepts of the method and by presenting a number of interesting applications. Methodologically, we present an analogy between the dissipative dynamics of a quantum spin and that of a classical spin in a random magnetic field. This analogy is used to recover the well-known noninteracting-blip approximation in the weak-coupling limit. We explain in detail how to compute spin-spin autocorrelation functions. As interesting applications of our method, we explore the non-Markovian effects of the initial spin-bath preparation on the dynamics of the coherence σx(t) and of σz(t) under a Landau-Zener sweep of the bias field. We also compute to a high precision the asymptotic long-time dynamics of σz(t) without bias and demonstrate the wide applicability of our approach by calculating the spin dynamics at nonzero bias and different temperatures.

  2. 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.

  3. From requirements to Java in a snap model-driven requirements engineering in practice

    CERN Document Server

    Smialek, Michal

    2015-01-01

    This book provides a coherent methodology for Model-Driven Requirements Engineering which stresses the systematic treatment of requirements within the realm of modelling and model transformations. The underlying basic assumption is that detailed requirements models are used as first-class artefacts playing a direct role in constructing software. To this end, the book presents the Requirements Specification Language (RSL) that allows precision and formality, which eventually permits automation of the process of turning requirements into a working system by applying model transformations and co

  4. Model-driven development of smart grid services using SoaML

    DEFF Research Database (Denmark)

    Kosek, Anna Magdalena; Gehrke, Oliver

    2014-01-01

    This paper presents a model-driven software devel- opment process which can be applied to the design of smart grid services. The Service Oriented Architecture Modelling Language (SoaML) is used to describe the architecture as well as the roles and interactions between service participants....... The individual modelling steps and an example design of a SoaML model for a voltage control service are presented and explained. Finally, the paper discusses a proof-of-concept implementation of the modelled service in a smart grid testing laboratory....

  5. Model-driven discovery of underground metabolic functions in Escherichia coli

    DEFF Research Database (Denmark)

    Guzmán, Gabriela I.; Utrilla, José; Nurk, Sergey

    2015-01-01

    -scale models, which have been widely used for predicting growth phenotypes in various environments or following a genetic perturbation; however, these predictions occasionally fail. Failed predictions of gene essentiality offer an opportunity for targeting biological discovery, suggesting the presence......E, and gltA and prpC. This study demonstrates how a targeted model-driven approach to discovery can systematically fill knowledge gaps, characterize underground metabolism, and elucidate regulatory mechanisms of adaptation in response to gene KO perturbations....

  6. Efficient and accurate log-Lévy approximations to Lévy driven LIBOR models

    DEFF Research Database (Denmark)

    Papapantoleon, Antonis; Schoenmakers, John; Skovmand, David

    2011-01-01

    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 is growing exponentially fast (as a function of the tenor length). In this work, we con...... ratchet caps show that the approximations perform very well. In addition, we also consider the log-L\\'evy approximation of annuities, which offers good approximations for high volatility regimes....

  7. The Community Water Model (CWATM) / Development of a community driven global water model

    Science.gov (United States)

    Burek, Peter; Satoh, Yusuke; Greve, Peter; Kahil, Taher; Wada, Yoshihide

    2017-04-01

    With a growing population and economic development, it is expected that water demands will increase significantly in the future, especially in developing regions. At the same time, climate change is expected to alter spatial patterns of hydrological cycle and will have global, regional and local impacts on water availability. Thus, it is important to assess water supply, water demand and environmental needs over time to identify the populations and locations that will be most affected by these changes linked to water scarcity, droughts and floods. The Community Water Model (CWATM) will be designed for this purpose in that it includes an accounting of how future water demands will evolve in response to socioeconomic change and how water availability will change in response to climate. CWATM represents one of the new key elements of IIASA's Water program. It has been developed to work flexibly at both global and regional level at different spatial resolutions. The model is open source and community-driven to promote our work amongst the wider water community worldwide and is flexible enough linking to further planned developments such as water quality and hydro-economic modules. CWATM will be a basis to develop a next-generation global hydro-economic modeling framework that represents the economic trade-offs among different water management options over a basin looking at water supply infrastructure and demand managements. The integrated modeling framework will consider water demand from agriculture, domestic, energy, industry and environment, investment needs to alleviate future water scarcity, and will provide a portfolio of economically optimal solutions for achieving future water management options under the Sustainable Development Goals (SDG) for example. In addition, it will be able to track the energy requirements associated with the water supply system e.g., pumping, desalination and interbasin transfer to realize the linkage with the water-energy economy. In

  8. A model of nitrous oxide evolution from soil driven by rainfall events. I - Model structure and sensitivity. II - Model applications

    Science.gov (United States)

    Changsheng, LI; Frolking, Steve; Frolking, Tod A.

    1992-01-01

    Simulations of N2O and CO2 emissions from soils were conducted with a rain-event driven, process-oriented model (DNDC) of nitrogen and carbon cycling processes in soils. The magnitude and trends of simulated N2O (or N2O + N2) and CO2 emissions were consistent with the results obtained in field experiments. The successful simulation of these emissions from the range of soil types examined demonstrates that the DNDC will be a useful tool for the study of linkages among climate, soil-atmosphere interactions, land use, and trace gas fluxes.

  9. Nuclear models, experiments and data libraries needed for numerical simulation of accelerator-driven system

    International Nuclear Information System (INIS)

    Bauge, E.; Bersillon, O.

    2000-01-01

    This paper presents the transparencies of the speech concerning the nuclear models, experiments and data libraries needed for numerical simulation of Accelerator-Driven Systems. The first part concerning the nuclear models defines the spallation process, the corresponding models (intra-nuclear cascade, statistical model, Fermi breakup, fission, transport, decay and macroscopic aspects) and the code systems. The second part devoted to the experiments presents the angular measurements, the integral measurements, the residual nuclei and the energy deposition. In the last part, dealing with the data libraries, the author details the fundamental quantities as the reaction cross-section, the low energy transport databases and the decay libraries. (A.L.B.)

  10. 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

  11. Use case driven approach to develop simulation model for PCS of APR1400 simulator

    International Nuclear Information System (INIS)

    Dong Wook, Kim; Hong Soo, Kim; Hyeon Tae, Kang; Byung Hwan, Bae

    2006-01-01

    The full-scope simulator is being developed to evaluate specific design feature and to support the iterative design and validation in the Man-Machine Interface System (MMIS) design of Advanced Power Reactor (APR) 1400. The simulator consists of process model, control logic model, and MMI for the APR1400 as well as the Power Control System (PCS). In this paper, a use case driven approach is proposed to develop a simulation model for PCS. In this approach, a system is considered from the point of view of its users. User's view of the system is based on interactions with the system and the resultant responses. In use case driven approach, we initially consider the system as a black box and look at its interactions with the users. From these interactions, use cases of the system are identified. Then the system is modeled using these use cases as functions. Lower levels expand the functionalities of each of these use cases. Hence, starting from the topmost level view of the system, we proceeded down to the lowest level (the internal view of the system). The model of the system thus developed is use case driven. This paper will introduce the functionality of the PCS simulation model, including a requirement analysis based on use case and the validation result of development of PCS model. The PCS simulation model using use case will be first used during the full-scope simulator development for nuclear power plant and will be supplied to Shin-Kori 3 and 4 plant. The use case based simulation model development can be useful for the design and implementation of simulation models. (authors)

  12. Model of a thermal driven volumetric pump for energy harvesting in an underwater glider

    International Nuclear Information System (INIS)

    Falcão Carneiro, J.; Gomes de Almeida, F.

    2016-01-01

    Underwater gliders are one of the most promising approaches to achieve an increase of human presence in the oceans. Among existing solutions, thermal driven gliders present long range and endurance capabilities, offering the possibility of remaining years beneath water collecting and transmitting data to shore. A key component in thermal gliders lies in the process used to collect ocean's thermal energy. In this paper a new quasi-static model of a thermal driven volumetric pump, for use in underwater gliders, is presented. The study also encompasses an analysis of the influence different hydraulic system parameters have on the thermodynamic cycle efficiency. Finally, the paper proposes a simple dynamic model of a heat exchanger that uses commercially available materials for the Phase Change Material (PCM) container. Simulation results validate the models developed. - Highlights: • A new model of a thermal driven volumetric pump for underwater gliders is proposed. • The effect hydraulic system parameters have on the cycle efficiency is analyzed. • The energy efficiency may be increased tenfold using adequate hydraulic parameters. • It's shown that the PCM PVT transition surface may not alter the cycle efficiency.

  13. 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.

  14. A 1D ion species model for an RF driven negative ion source

    Science.gov (United States)

    Turner, I.; Holmes, A. J. T.

    2017-08-01

    A one-dimensional model for an RF driven negative ion source has been developed based on an inductive discharge. The RF source differs from traditional filament and arc ion sources because there are no primary electrons present, and is simply composed of an antenna region (driver) and a main plasma discharge region. However the model does still make use of the classical plasma transport equations for particle energy and flow, which have previously worked well for modelling DC driven sources. The model has been developed primarily to model the Small Negative Ion Facility (SNIF) ion source at CCFE, but may be easily adapted to model other RF sources. Currently the model considers the hydrogen ion species, and provides a detailed description of the plasma parameters along the source axis, i.e. plasma temperature, density and potential, as well as current densities and species fluxes. The inputs to the model are currently the RF power, the magnetic filter field and the source gas pressure. Results from the model are presented and where possible compared to existing experimental data from SNIF, with varying RF power, source pressure.

  15. An automotive supply chain model for a demand-driven environment

    Directory of Open Access Journals (Sweden)

    Intaher M. Ambe

    2011-11-01

    Full Text Available The purpose of this article is to demonstrate the development of a supply chain model for the automotive industry that would respond to changing consumer demand. Now more than ever, businesses need to improve the efficiency of their supply chains in order to maintain a competitive advantage. The principles of lean manufacturing and just-intime (JIT inventory control that were renowned for helping companies like Toyota, Dell and Walmart to rise to the top of their respective industries are no longer adequate. Leading companies are applying new technologies and sophisticated analytics to make their supply chains more responsive to customer demand. This challenge is driven by fierce competition, fluctuating market demand and rising customer requirements that have led to customers becoming more demanding with increased preferences. The article is based on theoretical reviews and suggests guidelines for the implementation of an automotive supply chain model for a demand-driven environment.

  16. Single-particle model of a strongly driven, dense, nanoscale quantum ensemble

    Science.gov (United States)

    DiLoreto, C. S.; Rangan, C.

    2018-01-01

    We study the effects of interatomic interactions on the quantum dynamics of a dense, nanoscale, atomic ensemble driven by a strong electromagnetic field. We use a self-consistent, mean-field technique based on the pseudospectral time-domain method and a full, three-directional basis to solve the coupled Maxwell-Liouville equations. We find that interatomic interactions generate a decoherence in the state of an ensemble on a much faster time scale than the excited-state lifetime of individual atoms. We present a single-particle model of the driven, dense ensemble by incorporating interactions into a dephasing rate. This single-particle model reproduces the essential physics of the full simulation and is an efficient way of rapidly estimating the collective dynamics of a dense ensemble.

  17. Data-driven modeling and real-time distributed control for energy efficient manufacturing systems

    International Nuclear Information System (INIS)

    Zou, Jing; Chang, Qing; Arinez, Jorge; Xiao, Guoxian

    2017-01-01

    As manufacturers face the challenges of increasing global competition and energy saving requirements, it is imperative to seek out opportunities to reduce energy waste and overall cost. In this paper, a novel data-driven stochastic manufacturing system modeling method is proposed to identify and predict energy saving opportunities and their impact on production. A real-time distributed feedback production control policy, which integrates the current and predicted system performance, is established to improve the overall profit and energy efficiency. A case study is presented to demonstrate the effectiveness of the proposed control policy. - Highlights: • A data-driven stochastic manufacturing system model is proposed. • Real-time system performance and energy saving opportunity identification method is developed. • Prediction method for future potential system performance and energy saving opportunity is developed. • A real-time distributed feedback control policy is established to improve energy efficiency and overall system profit.

  18. A model-driven approach to designing cross-enterprise business processes

    OpenAIRE

    Bauer, Bernhard (Prof.)

    2004-01-01

    A model-driven approach to designing cross-enterprise business processes / Bernhard Bauer, Jörg P. Müller, Stephan Roser. - In: On the move to meaningful internet systems 2004: OTM 2004 workshops : OTM Confederated International Workshops and Posters, GADA, JTRES, MIOS, WORM, WOSE, PhDS, and INTEROP 2004, Agia Napa, Cyprus, October 25 - 29, 2004 ; proceedings / Robert Meersman ... (eds.). - Berlin u.a. : Springer, 2004. - S. 544-555. - (Lecture Notes in Computer Science ; 3292)

  19. Model Driven Development of Web Application with SPACE Method and Tool-suit

    OpenAIRE

    Rehana, Jinat

    2010-01-01

    Enterprise level software development using traditional software engineeringapproaches with third-generation programming languages is becoming morechallenging and cumbersome task with the increased complexity of products,shortened development cycles and heightened expectations of quality. MDD(Model Driven Development) has been counting as an exciting and magicaldevelopment approach in the software industry from several years. The ideabehind MDD is the separation of business logic of a system ...

  20. Diffusion tensor magnetic resonance imaging driven growth modeling for radiotherapy target definition in glioblastoma

    DEFF Research Database (Denmark)

    Jensen, Morten B; Guldberg, Trine L; Harbøll, Anja

    2017-01-01

    the microscopic tumor cell spread. Gliomas favor spread along the white matter fiber tracts. Tumor growth models incorporating the MRI diffusion tensors (DTI) allow to account more consistently for the glioma growth. The aim of the study was to investigate the potential of a DTI driven growth model to improve...... target definition in glioblastoma (GBM). MATERIAL AND METHODS: Eleven GBM patients were scanned using T1w, T2w FLAIR, T1w + Gd and DTI. The brain was segmented into white matter, gray matter and cerebrospinal fluid. The Fisher-Kolmogorov growth model was used assuming uniform proliferation...

  1. 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.

  2. Scenario driven data modelling: a method for integrating diverse sources of data and data streams

    Science.gov (United States)

    2011-01-01

    Background Biology is rapidly becoming a data intensive, data-driven science. It is essential that data is represented and connected in ways that best represent its full conceptual content and allows both automated integration and data driven decision-making. Recent advancements in distributed multi-relational directed graphs, implemented in the form of the Semantic Web make it possible to deal with complicated heterogeneous data in new and interesting ways. Results This paper presents a new approach, scenario driven data modelling (SDDM), that integrates multi-relational directed graphs with data streams. SDDM can be applied to virtually any data integration challenge with widely divergent types of data and data streams. In this work, we explored integrating genetics data with reports from traditional media. SDDM was applied to the New Delhi metallo-beta-lactamase gene (NDM-1), an emerging global health threat. The SDDM process constructed a scenario, created a RDF multi-relational directed graph that linked diverse types of data to the Semantic Web, implemented RDF conversion tools (RDFizers) to bring content into the Sematic Web, identified data streams and analytical routines to analyse those streams, and identified user requirements and graph traversals to meet end-user requirements. Conclusions We provided an example where SDDM was applied to a complex data integration challenge. The process created a model of the emerging NDM-1 health threat, identified and filled gaps in that model, and constructed reliable software that monitored data streams based on the scenario derived multi-relational directed graph. The SDDM process significantly reduced the software requirements phase by letting the scenario and resulting multi-relational directed graph define what is possible and then set the scope of the user requirements. Approaches like SDDM will be critical to the future of data intensive, data-driven science because they automate the process of converting

  3. A data-driven approach to reverse engineering customer engagement models: towards functional constructs.

    Directory of Open Access Journals (Sweden)

    Natalie Jane de Vries

    Full Text Available Online consumer behavior in general and online customer engagement with brands in particular, has become a major focus of research activity fuelled by the exponential increase of interactive functions of the internet and social media platforms and applications. Current research in this area is mostly hypothesis-driven and much debate about the concept of Customer Engagement and its related constructs remains existent in the literature. In this paper, we aim to propose a novel methodology for reverse engineering a consumer behavior model for online customer engagement, based on a computational and data-driven perspective. This methodology could be generalized and prove useful for future research in the fields of consumer behaviors using questionnaire data or studies investigating other types of human behaviors. The method we propose contains five main stages; symbolic regression analysis, graph building, community detection, evaluation of results and finally, investigation of directed cycles and common feedback loops. The 'communities' of questionnaire items that emerge from our community detection method form possible 'functional constructs' inferred from data rather than assumed from literature and theory. Our results show consistent partitioning of questionnaire items into such 'functional constructs' suggesting the method proposed here could be adopted as a new data-driven way of human behavior modeling.

  4. A data-driven approach to reverse engineering customer engagement models: towards functional constructs.

    Science.gov (United States)

    de Vries, Natalie Jane; Carlson, Jamie; Moscato, Pablo

    2014-01-01

    Online consumer behavior in general and online customer engagement with brands in particular, has become a major focus of research activity fuelled by the exponential increase of interactive functions of the internet and social media platforms and applications. Current research in this area is mostly hypothesis-driven and much debate about the concept of Customer Engagement and its related constructs remains existent in the literature. In this paper, we aim to propose a novel methodology for reverse engineering a consumer behavior model for online customer engagement, based on a computational and data-driven perspective. This methodology could be generalized and prove useful for future research in the fields of consumer behaviors using questionnaire data or studies investigating other types of human behaviors. The method we propose contains five main stages; symbolic regression analysis, graph building, community detection, evaluation of results and finally, investigation of directed cycles and common feedback loops. The 'communities' of questionnaire items that emerge from our community detection method form possible 'functional constructs' inferred from data rather than assumed from literature and theory. Our results show consistent partitioning of questionnaire items into such 'functional constructs' suggesting the method proposed here could be adopted as a new data-driven way of human behavior modeling.

  5. Radiatively-driven winds: model improvements, ionization balance and the infared spectrum

    International Nuclear Information System (INIS)

    Castor, J.I.

    1979-01-01

    Recent improvements to theoretical stellar wind models and the results of empirical modelling of the ionization balance and the infrared continuum are discussed. The model of a wind driven by radiation pressure in spectral lines is improved by accounting for overlap of the driving lines, dependence of ionization balance on density, and stellar rotation. These effects produce a softer velocity law than that given by Castor, Abbott and Klein (1975). The ionization balance in zeta Puppis is shown to agree with that estimated for an optically thick wind at a gas temperature of 60,000 K. The ionization model is not unique. The infrared continuum of zeta Pup measured by Barlow and Cohen is fitted to a cool model with a linear rise of velocity with radius; this fit is also not unique. It is concluded that one should try to find a model that fits several kinds of evidence simultaneously. (Auth.)

  6. A model for an acoustically driven microbubble inside a rigid tube

    KAUST Repository

    Qamar, Adnan

    2014-09-10

    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-Stokes equation and is coupled with the evolving flow field solution inside the tube by a similarity transformation approach. The results are computed, and compared with experiments available in literature, for the initial bubble radius of Ro=1.5μm and 2μm for the tube diameter of D=12μm and 200μm with the acoustic parameters as utilized in the experiments. Results compare quite well with the existing experimental data. When compared to our earlier basic model, better agreement on a larger tube diameter is obtained with the proposed coupled model. The model also predicts, accurately, bubble fragmentation in terms of acoustic and geometric parameters.

  7. A remote sensing driven distributed hydrological model of the Senegal River basin

    DEFF Research Database (Denmark)

    Stisen, Simon; Jensen, Karsten Høgh; Sandholt, Inge

    2008-01-01

    outputs of AET from both model setups was carried out. This revealed substantial differences in the spatial patterns of AET for the examined subcatchment, in spite of similar values of predicted discharge and average AET. The potential for driving large scale hydrological models using remote sensing data......Distributed hydrological models require extensive data amounts for driving the models and for parameterization of the land surface and subsurface. This study investigates the potential of applying remote sensing (RS) based input data in a hydrological model for the 350,000 km2 Senegal River basin...... in West Africa. By utilizing remote sensing data to estimate precipitation, potential evapotranspiration (PET) and leaf area index (LAI) the model was driven entirely by remote sensing based data and independent of traditional meteorological data. The remote sensing retrievals were based on data from...

  8. Towards the final BSA modeling for the accelerator-driven BNCT facility at INFN LNL

    Energy Technology Data Exchange (ETDEWEB)

    Ceballos, C. [Centro de Aplicaciones Tecnlogicas y Desarrollo Nuclear, 5ta y30, Miramar, Playa, Ciudad Habana (Cuba); Esposito, J., E-mail: juan.esposito@lnl.infn.it [INFN, Laboratori Nazionali di Legnaro (LNL), via dell' Universita, 2, I-35020 Legnaro (PD) (Italy); Agosteo, S. [Politecnico di Milano, Dipartimento di Energia, Piazza Leonardo da Vinci 32, 20133 Milano (Italy)] [INFN, Sezione di Milano, via Celoria 16, 20133 Milano (Italy); Colautti, P.; Conte, V.; Moro, D. [INFN, Laboratori Nazionali di Legnaro (LNL), via dell' Universita, 2, I-35020 Legnaro (PD) (Italy); Pola, A. [Politecnico di Milano, Dipartimento di Energia, Piazza Leonardo da Vinci 32, 20133 Milano (Italy)] [INFN, Sezione di Milano, via Celoria 16, 20133 Milano (Italy)

    2011-12-15

    Some remarkable advances have been made in the last years on the SPES-BNCT project of the Istituto Nazionale di Fisica Nucleare (INFN) towards the development of the accelerator-driven thermal neutron beam facility at the Legnaro National Laboratories (LNL), aimed at the BNCT experimental treatment of extended skin melanoma. The compact neutron source will be produced via the {sup 9}Be(p,xn) reactions using the 5 MeV, 30 mA beam driven by the RFQ accelerator, whose modules construction has been recently completed, into a thick beryllium target prototype already available. The Beam Shaping Assembly (BSA) final modeling, using both neutron converter and the new, detailed, Be(p,xn) neutron yield spectra at 5 MeV energy recently measured at the CN Van de Graaff accelerator at LNL, is summarized here.

  9. A unified modeling approach for physical experiment design and optimization in laser driven inertial confinement fusion

    Energy Technology Data Exchange (ETDEWEB)

    Li, Haiyan [Mechatronics Engineering School of Guangdong University of Technology, Guangzhou 510006 (China); Huang, Yunbao, E-mail: Huangyblhy@gmail.com [Mechatronics Engineering School of Guangdong University of Technology, Guangzhou 510006 (China); Jiang, Shaoen, E-mail: Jiangshn@vip.sina.com [Laser Fusion Research Center, China Academy of Engineering Physics, Mianyang 621900 (China); Jing, Longfei, E-mail: scmyking_2008@163.com [Laser Fusion Research Center, China Academy of Engineering Physics, Mianyang 621900 (China); Tianxuan, Huang; Ding, Yongkun [Laser Fusion Research Center, China Academy of Engineering Physics, Mianyang 621900 (China)

    2015-11-15

    Highlights: • A unified modeling approach for physical experiment design is presented. • Any laser facility can be flexibly defined and included with two scripts. • Complex targets and laser beams can be parametrically modeled for optimization. • Automatically mapping of laser beam energy facilitates targets shape optimization. - Abstract: Physical experiment design and optimization is very essential for laser driven inertial confinement fusion due to the high cost of each shot. However, only limited experiments with simple structure or shape on several laser facilities can be designed and evaluated in available codes, and targets are usually defined by programming, which may lead to it difficult for complex shape target design and optimization on arbitrary laser facilities. A unified modeling approach for physical experiment design and optimization on any laser facilities is presented in this paper. Its core idea includes: (1) any laser facility can be flexibly defined and included with two scripts, (2) complex shape targets and laser beams can be parametrically modeled based on features, (3) an automatically mapping scheme of laser beam energy onto discrete mesh elements of targets enable targets or laser beams be optimized without any additional interactive modeling or programming, and (4) significant computation algorithms are additionally presented to efficiently evaluate radiation symmetry on the target. Finally, examples are demonstrated to validate the significance of such unified modeling approach for physical experiments design and optimization in laser driven inertial confinement fusion.

  10. A Model-driven and Service-oriented framework for the business process improvement

    Directory of Open Access Journals (Sweden)

    Andrea Delgado

    2010-07-01

    Full Text Available Business Process Management (BPM importance and benefits for organizations to focus on their business processes is nowadays broadly recognized, as business and technology areas are embracing and adopting the paradigm. The Service Oriented Computing (SOC paradigm bases software development on services to realize business processes. The implementation of business processes as services helps in reducing the gap between these two areas, easing the communication and understanding of business needs. The Model Driven Development (MDD paradigm bases software development in models, metamodels and languages that allow transformation between them. The automatic generation of service models from business process models is a key issue to support the separation of its definition from its technical implementation. In this article, we present MINERVA framework which applies Model Driven Development (MDD and Service Oriented Computing (SOC paradigms to business processes for the continuous business process improvement in organizations, giving support to the stages defined in the business process lifecycle from modeling to evaluation of its execution.

  11. Profile modifications in laser-driven temperature fronts using flux-limiters and delocalization models

    Science.gov (United States)

    Colombant, Denis; Manheimer, Wallace; Busquet, Michel

    2004-11-01

    A simple steady-state model using flux-limiters by Day et al [1] showed that temperature profiles could formally be double-valued. Stability of temperature profiles in laser-driven temperature fronts using delocalization models was also discussed by Prasad and Kershaw [2]. We have observed steepening of the front and flattening of the maximum temperature in laser-driven implosions [3]. Following the simple model first proposed in [1], we solve for a two-boundary value steady-state heat flow problem for various non-local heat transport models. For the more complicated models [4,5], we obtain the steady-state solution as the asymptotic limit of the time-dependent solution. Solutions will be shown and compared for these various models. 1.M.Day, B.Merriman, F.Najmabadi and R.W.Conn, Contrib. Plasma Phys. 36, 419 (1996) 2.M.K.Prasad and D.S.Kershaw, Phys. Fluids B3, 3087 (1991) 3.D.Colombant, W.Manheimer and M.Busquet, Bull. Amer. Phys. Soc. 48, 326 (2003) 4.E.M.Epperlein and R.W.Short, Phys. Fluids B3, 3092 (1991) 5.W.Manheimer and D.Colombant, Phys. Plasmas 11, 260 (2004)

  12. 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/ .

  13. Validity of thermally-driven small-scale ventilated filling box models

    Science.gov (United States)

    Partridge, Jamie L.; Linden, P. F.

    2013-11-01

    The majority of previous work studying building ventilation flows at laboratory scale have used saline plumes in water. The production of buoyancy forces using salinity variations in water allows dynamic similarity between the small-scale models and the full-scale flows. However, in some situations, such as including the effects of non-adiabatic boundaries, the use of a thermal plume is desirable. The efficacy of using temperature differences to produce buoyancy-driven flows representing natural ventilation of a building in a small-scale model is examined here, with comparison between previous theoretical and new, heat-based, experiments.

  14. Economic modeling and parametric studies for SOMBRERO - a laser-driven IFE power plant

    International Nuclear Information System (INIS)

    Meier, W.R.; Rosenberg, C.W. Jr. von

    1992-01-01

    Economic modeling and parametric studies for the SOMBRERO laser-driven inertial fusion energy (IFE) electric power plant have been conducted to determine the most attractive operating point. Cost scaling relationships have been developed and integrated into a cost-performance model of the plant. The figure-of-merit for determining the most attractive design point is the constant-dollar cost of electricity. Results are presented as a function of the driver energy. The sensitivity of the results to variations in the assumed net electric output and target performance is also examined

  15. Model-driven engineering of information systems principles, techniques, and practice

    CERN Document Server

    Cretu, Liviu Gabriel

    2015-01-01

    Model-driven engineering (MDE) is the automatic production of software from simplified models of structure and functionality. It mainly involves the automation of the routine and technologically complex programming tasks, thus allowing developers to focus on the true value-adding functionality that the system needs to deliver. This book serves an overview of some of the core topics in MDE. The volume is broken into two sections offering a selection of papers that helps the reader not only understand the MDE principles and techniques, but also learn from practical examples. Also covered are the

  16. Economic modeling and parametric studies for OSIRIS - a HIB-driven IFE power plant

    International Nuclear Information System (INIS)

    Meier, W.R.; Bieri, R.L.

    1992-01-01

    Economic modeling and parametric studies for the Osiris HIB-driven inertial fusion energy (IFE) electric power plant have been conducted to determine the most attractive operating point. Cost scaling relationships have been developed and integrated into a cost-performance model of the plant. The figure-of-merit for determining the most attractive design point is the constant-dollar cost of electricity. Results are presented as a function of the driver energy. The sensitivity of the results to variations in the assumed net electric output and target performance is also examined

  17. Wind-driven rain as a boundary condition for HAM simulations: analysis of simplified modelling approaches

    DEFF Research Database (Denmark)

    Janssen, Hans; Blocken, Bert; Roels, Staf

    2007-01-01

    While the numerical simulation of moisture transfer inside building components is currently undergoing standardisation, the modelling of the atmospheric boundary conditions has received far less attention. This article analyses the modelling of the wind-driven-rain load on building facades...... though: the full variability with the perpendicular wind speed and horizontal rain intensity should be preserved, where feasible, for improved estimations of the moisture transfer in building components. In the concluding section, it is moreover shown that the dependence of the surface moisture transfer...

  18. Process modelling in demand-driven supply chains: A reference model for the fruit industry

    NARCIS (Netherlands)

    Verdouw, C.N.; Beulens, A.J.M.; Trienekens, J.H.; Wolfert, J.

    2010-01-01

    The growing importance of health in consumption is expected to result in a significant increase of European fruit demand. However, the current fruit supply does not yet sufficiently meet demand requirements. This urges fruit supply chains to become more demand-driven, that is, able to continuously

  19. Hysteresis-controlled instability waves in a scale-free driven current sheet model

    Directory of Open Access Journals (Sweden)

    V. M. Uritsky

    2005-01-01

    Full Text Available Magnetospheric dynamics is a complex multiscale process whose statistical features can be successfully reproduced using high-dimensional numerical transport models exhibiting the phenomenon of self-organized criticality (SOC. Along this line of research, a 2-dimensional driven current sheet (DCS model has recently been developed that incorporates an idealized current-driven instability with a resistive MHD plasma system (Klimas et al., 2004a, b. The dynamics of the DCS model is dominated by the scale-free diffusive energy transport characterized by a set of broadband power-law distribution functions similar to those governing the evolution of multiscale precipitation regions of energetic particles in the nighttime sector of aurora (Uritsky et al., 2002b. The scale-free DCS behavior is supported by localized current-driven instabilities that can communicate in an avalanche fashion over arbitrarily long distances thus producing current sheet waves (CSW. In this paper, we derive the analytical expression for CSW speed as a function of plasma parameters controlling local anomalous resistivity dynamics. The obtained relation indicates that the CSW propagation requires sufficiently high initial current densities, and predicts a deceleration of CSWs moving from inner plasma sheet regions toward its northern and southern boundaries. We also show that the shape of time-averaged current density profile in the DCS model is in agreement with steady-state spatial configuration of critical avalanching models as described by the singular diffusion theory of the SOC. Over shorter time scales, SOC dynamics is associated with rather complex spatial patterns and, in particular, can produce bifurcated current sheets often seen in multi-satellite observations.

  20. A Global User-Driven Model for Tile Prefetching in Web Geographical Information Systems.

    Science.gov (United States)

    Pan, Shaoming; Chong, Yanwen; Zhang, Hang; Tan, Xicheng

    2017-01-01

    A web geographical information system is a typical service-intensive application. Tile prefetching and cache replacement can improve cache hit ratios by proactively fetching tiles from storage and replacing the appropriate tiles from the high-speed cache buffer without waiting for a client's requests, which reduces disk latency and improves system access performance. Most popular prefetching strategies consider only the relative tile popularities to predict which tile should be prefetched or consider only a single individual user's access behavior to determine which neighbor tiles need to be prefetched. Some studies show that comprehensively considering all users' access behaviors and all tiles' relationships in the prediction process can achieve more significant improvements. Thus, this work proposes a new global user-driven model for tile prefetching and cache replacement. First, based on all users' access behaviors, a type of expression method for tile correlation is designed and implemented. Then, a conditional prefetching probability can be computed based on the proposed correlation expression mode. Thus, some tiles to be prefetched can be found by computing and comparing the conditional prefetching probability from the uncached tiles set and, similarly, some replacement tiles can be found in the cache buffer according to multi-step prefetching. Finally, some experiments are provided comparing the proposed model with other global user-driven models, other single user-driven models, and other client-side prefetching strategies. The results show that the proposed model can achieve a prefetching hit rate in approximately 10.6% ~ 110.5% higher than the compared methods.

  1. Scenario and modelling uncertainty in global mean temperature change derived from emission-driven global climate models

    Directory of Open Access Journals (Sweden)

    B. B. B. Booth

    2013-04-01

    Full Text Available We compare future changes in global mean temperature in response to different future scenarios which, for the first time, arise from emission-driven rather than concentration-driven perturbed parameter ensemble of a global climate model (GCM. These new GCM simulations sample uncertainties in atmospheric feedbacks, land carbon cycle, ocean physics and aerosol sulphur cycle processes. We find broader ranges of projected temperature responses arising when considering emission rather than concentration-driven simulations (with 10–90th percentile ranges of 1.7 K for the aggressive mitigation scenario, up to 3.9 K for the high-end, business as usual scenario. A small minority of simulations resulting from combinations of strong atmospheric feedbacks and carbon cycle responses show temperature increases in excess of 9 K (RCP8.5 and even under aggressive mitigation (RCP2.6 temperatures in excess of 4 K. While the simulations point to much larger temperature ranges for emission-driven experiments, they do not change existing expectations (based on previous concentration-driven experiments on the timescales over which different sources of uncertainty are important. The new simulations sample a range of future atmospheric concentrations for each emission scenario. Both in the case of SRES A1B and the Representative Concentration Pathways (RCPs, the concentration scenarios used to drive GCM ensembles, lies towards the lower end of our simulated distribution. This design decision (a legacy of previous assessments is likely to lead concentration-driven experiments to under-sample strong feedback responses in future projections. Our ensemble of emission-driven simulations span the global temperature response of the CMIP5 emission-driven simulations, except at the low end. Combinations of low climate sensitivity and low carbon cycle feedbacks lead to a number of CMIP5 responses to lie below our ensemble range. The ensemble simulates a number of high

  2. Scenario and modelling uncertainty in global mean temperature change derived from emission-driven global climate models

    Science.gov (United States)

    Booth, B. B. B.; Bernie, D.; McNeall, D.; Hawkins, E.; Caesar, J.; Boulton, C.; Friedlingstein, P.; Sexton, D. M. H.

    2013-04-01

    We compare future changes in global mean temperature in response to different future scenarios which, for the first time, arise from emission-driven rather than concentration-driven perturbed parameter ensemble of a global climate model (GCM). These new GCM simulations sample uncertainties in atmospheric feedbacks, land carbon cycle, ocean physics and aerosol sulphur cycle processes. We find broader ranges of projected temperature responses arising when considering emission rather than concentration-driven simulations (with 10-90th percentile ranges of 1.7 K for the aggressive mitigation scenario, up to 3.9 K for the high-end, business as usual scenario). A small minority of simulations resulting from combinations of strong atmospheric feedbacks and carbon cycle responses show temperature increases in excess of 9 K (RCP8.5) and even under aggressive mitigation (RCP2.6) temperatures in excess of 4 K. While the simulations point to much larger temperature ranges for emission-driven experiments, they do not change existing expectations (based on previous concentration-driven experiments) on the timescales over which different sources of uncertainty are important. The new simulations sample a range of future atmospheric concentrations for each emission scenario. Both in the case of SRES A1B and the Representative Concentration Pathways (RCPs), the concentration scenarios used to drive GCM ensembles, lies towards the lower end of our simulated distribution. This design decision (a legacy of previous assessments) is likely to lead concentration-driven experiments to under-sample strong feedback responses in future projections. Our ensemble of emission-driven simulations span the global temperature response of the CMIP5 emission-driven simulations, except at the low end. Combinations of low climate sensitivity and low carbon cycle feedbacks lead to a number of CMIP5 responses to lie below our ensemble range. The ensemble simulates a number of high-end responses which lie

  3. Perspectives on continuum flow models for force-driven nano-channel liquid flows

    Science.gov (United States)

    Beskok, Ali; Ghorbanian, Jafar; Celebi, Alper

    2017-11-01

    A phenomenological continuum model is developed using systematic molecular dynamics (MD) simulations of force-driven liquid argon flows confined in gold nano-channels at a fixed thermodynamic state. Well known density layering near the walls leads to the definition of an effective channel height and a density deficit parameter. While the former defines the slip-plane, the latter parameter relates channel averaged density with the desired thermodynamic state value. Definitions of these new parameters require a single MD simulation performed for a specific liquid-solid pair at the desired thermodynamic state and used for calibration of model parameters. Combined with our observations of constant slip-length and kinematic viscosity, the model accurately predicts the velocity distribution and volumetric and mass flow rates for force-driven liquid flows in different height nano-channels. Model is verified for liquid argon flow at distinct thermodynamic states and using various argon-gold interaction strengths. Further verification is performed for water flow in silica and gold nano-channels, exhibiting slip lengths of 1.2 nm and 15.5 nm, respectively. Excellent agreements between the model and the MD simulations are reported for channel heights as small as 3 nm for various liquid-solid pairs.

  4. Data-driven integration of genome-scale regulatory and metabolic network models

    Science.gov (United States)

    Imam, Saheed; Schäuble, Sascha; Brooks, Aaron N.; Baliga, Nitin S.; Price, Nathan D.

    2015-01-01

    Microbes are diverse and extremely versatile organisms that play vital roles in all ecological niches. Understanding and harnessing microbial systems will be key to the sustainability of our planet. One approach to improving our knowledge of microbial processes is through data-driven and mechanism-informed computational modeling. Individual models of biological networks (such as metabolism, transcription, and signaling) have played pivotal roles in driving microbial research through the years. These networks, however, are highly interconnected and function in concert—a fact that has led to the development of a variety of approaches aimed at simulating the integrated functions of two or more network types. Though the task of integrating these different models is fraught with new challenges, the large amounts of high-throughput data sets being generated, and algorithms being developed, means that the time is at hand for concerted efforts to build integrated regulatory-metabolic networks in a data-driven fashion. In this perspective, we review current approaches for constructing integrated regulatory-metabolic models and outline new strategies for future development of these network models for any microbial system. PMID:25999934

  5. Data-driven integration of genome-scale regulatory and metabolic network models

    Directory of Open Access Journals (Sweden)

    Saheed eImam

    2015-05-01

    Full Text Available Microbes are diverse and extremely versatile organisms that play vital roles in all ecological niches. Understanding and harnessing microbial systems will be key to the sustainability of our planet. One approach to improving our knowledge of microbial processes is through data-driven and mechanism-informed computational modeling. Individual models of biological networks (such as metabolism, transcription and signaling have played pivotal roles in driving microbial research through the years. These networks, however, are highly interconnected and function in concert – a fact that has led to the development of a variety of approaches aimed at simulating the integrated functions of two or more network types. Though the task of integrating these different models is fraught with new challenges, the large amounts of high-throughput data sets being generated, and algorithms being developed, means that the time is at hand for concerted efforts to build integrated regulatory-metabolic networks in a data-driven fashion. In this perspective, we review current approaches for constructing integrated regulatory-metabolic models and outline new strategies for future development of these network models for any microbial system.

  6. Data-driven techniques to estimate parameters in a rate-dependent ferromagnetic hysteresis model

    International Nuclear Information System (INIS)

    Hu Zhengzheng; Smith, Ralph C.; Ernstberger, Jon M.

    2012-01-01

    The quantification of rate-dependent ferromagnetic hysteresis is important in a range of applications including high speed milling using Terfenol-D actuators. There exist a variety of frameworks for characterizing rate-dependent hysteresis including the magnetic model in Ref. , the homogenized energy framework, Preisach formulations that accommodate after-effects, and Prandtl-Ishlinskii models. A critical issue when using any of these models to characterize physical devices concerns the efficient estimation of model parameters through least squares data fits. A crux of this issue is the determination of initial parameter estimates based on easily measured attributes of the data. In this paper, we present data-driven techniques to efficiently and robustly estimate parameters in the homogenized energy model. This framework was chosen due to its physical basis and its applicability to ferroelectric, ferromagnetic and ferroelastic materials.

  7. Combining engineering and data-driven approaches: Development of a generic fire risk model facilitating calibration

    DEFF Research Database (Denmark)

    De Sanctis, G.; Fischer, K.; Kohler, J.

    2014-01-01

    Fire risk models support decision making for engineering problems under the consistent consideration of the associated uncertainties. Empirical approaches can be used for cost-benefit studies when enough data about the decision problem are available. But often the empirical approaches...... a generic risk model that is calibrated to observed fire loss data. Generic risk models assess the risk of buildings based on specific risk indicators and support risk assessment at a portfolio level. After an introduction to the principles of generic risk assessment, the focus of the present paper...... are not detailed enough. Engineering risk models, on the other hand, may be detailed but typically involve assumptions that may result in a biased risk assessment and make a cost-benefit study problematic. In two related papers it is shown how engineering and data-driven modeling can be combined by developing...

  8. Modeling Cable and Guide Channel Interaction in a High-Strength Cable-Driven Continuum Manipulator.

    Science.gov (United States)

    Moses, Matthew S; Murphy, Ryan J; Kutzer, Michael D M; Armand, Mehran

    2015-12-01

    This paper presents several mechanical models of a high-strength cable-driven dexterous manipulator designed for surgical procedures. A stiffness model is presented that distinguishes between contributions from the cables and the backbone. A physics-based model incorporating cable friction is developed and its predictions are compared with experimental data. The data show that under high tension and high curvature, the shape of the manipulator deviates significantly from a circular arc. However, simple parametric models can fit the shape with good accuracy. The motivating application for this study is to develop a model so that shape can be predicted using easily measured quantities such as tension, so that real-time navigation may be performed, especially in minimally-invasive surgical procedures, while reducing the need for hazardous imaging methods such as fluoroscopy.

  9. Modeling and Predicting Carbon and Water Fluxes Using Data-Driven Techniques in a Forest Ecosystem

    Directory of Open Access Journals (Sweden)

    Xianming Dou

    2017-12-01

    Full Text Available Accurate estimation of carbon and water fluxes of forest ecosystems is of particular importance for addressing the problems originating from global environmental change, and providing helpful information about carbon and water content for analyzing and diagnosing past and future climate change. The main focus of the current work was to investigate the feasibility of four comparatively new methods, including generalized regression neural network, group method of data handling (GMDH, extreme learning machine and adaptive neuro-fuzzy inference system (ANFIS, for elucidating the carbon and water fluxes in a forest ecosystem. A comparison was made between these models and two widely used data-driven models, artificial neural network (ANN and support vector machine (SVM. All the models were evaluated based on the following statistical indices: coefficient of determination, Nash-Sutcliffe efficiency, root mean square error and mean absolute error. Results indicated that the data-driven models are capable of accounting for most variance in each flux with the limited meteorological variables. The ANN model provided the best estimates for gross primary productivity (GPP and net ecosystem exchange (NEE, while the ANFIS model achieved the best for ecosystem respiration (R, indicating that no single model was consistently superior to others for the carbon flux prediction. In addition, the GMDH model consistently produced somewhat worse results for all the carbon flux and evapotranspiration (ET estimations. On the whole, among the carbon and water fluxes, all the models produced similar highly satisfactory accuracy for GPP, R and ET fluxes, and did a reasonable job of reproducing the eddy covariance NEE. Based on these findings, it was concluded that these advanced models are promising alternatives to ANN and SVM for estimating the terrestrial carbon and water fluxes.

  10. Modeling Diffusion and Buoyancy-Driven Convection with Application to Geological CO2 Storage

    KAUST Repository

    Allen, Rebecca

    2015-04-01

    ABSTRACT Modeling Diffusion and Buoyancy-Driven Convection with Application to Geological CO2 Storage Rebecca Allen Geological CO2 storage is an engineering feat that has been undertaken around the world for more than two decades, thus accurate modeling of flow and transport behavior is of practical importance. Diffusive and convective transport are relevant processes for buoyancy-driven convection of CO2 into underlying fluid, a scenario that has received the attention of numerous modeling studies. While most studies focus on Darcy-scale modeling of this scenario, relatively little work exists at the pore-scale. In this work, properties evaluated at the pore-scale are used to investigate the transport behavior modeled at the Darcy-scale. We compute permeability and two different forms of tortuosity, namely hydraulic and diffusive. By generating various pore ge- ometries, we find hydraulic and diffusive tortuosity can be quantitatively different in the same pore geometry by up to a factor of ten. As such, we emphasize that these tortuosities should not be used interchangeably. We find pore geometries that are characterized by anisotropic permeability can also exhibit anisotropic diffusive tortuosity. This finding has important implications for buoyancy-driven convection modeling; when representing the geological formation with an anisotropic permeabil- ity, it is more realistic to also account for an anisotropic diffusivity. By implementing a non-dimensional model that includes both a vertically and horizontally orientated 5 Rayleigh number, we interpret our findings according to the combined effect of the anisotropy from permeability and diffusive tortuosity. In particular, we observe the Rayleigh ratio may either dampen or enhance the diffusing front, and our simulation data is used to express the time of convective onset as a function of the Rayleigh ratio. Also, we implement a lattice Boltzmann model for thermal convective flows, which we treat as an analog for

  11. A frictionally and hydraulically constrained model of the convectively driven mean flow in partially enclosed seas

    Science.gov (United States)

    Maxworthy, T.

    1997-08-01

    A simple three-layer model of the dynamics of partially enclosed seas, driven by a surface buoyancy flux, is presented. It contains two major elements, a hydraulic constraint at the exit contraction and friction in the interior of the main body of the sea; both together determine the vertical structure and magnitudes of the interior flow variables, i.e. velocity and density. Application of the model to the large-scale dynamics of the Red Sea gives results that are not in disagreement with observation once the model is applied, also, to predict the dense outflow from the Gulf of Suez. The latter appears to be the agent responsible for the formation of dense bottom water in this system. Also, the model is reasonably successful in predicting the density of the outflow from the Persian Gulf, and can be applied to any number of other examples of convectively driven flow in long, narrow channels, with or without sills and constrictions at their exits.

  12. Cathode fall model and current-voltage characteristics of field emission driven direct current microplasmas

    Energy Technology Data Exchange (ETDEWEB)

    Venkattraman, Ayyaswamy [Department of Applied Mechanics, Indian Institute of Technology Madras, Chennai 600036 (India)

    2013-11-15

    The post-breakdown characteristics of field emission driven microplasma are studied theoretically and numerically. A cathode fall model assuming a linearly varying electric field is used to obtain equations governing the operation of steady state field emission driven microplasmas. The results obtained from the model by solving these equations are compared with particle-in-cell with Monte Carlo collisions simulation results for parameters including the plasma potential, cathode fall thickness, ion number density in the cathode fall, and current density vs voltage curves. The model shows good overall agreement with the simulations but results in slightly overpredicted values for the plasma potential and the cathode fall thickness attributed to the assumed electric field profile. The current density vs voltage curves obtained show an arc region characterized by negative slope as well as an abnormal glow discharge characterized by a positive slope in gaps as small as 10 μm operating at atmospheric pressure. The model also retrieves the traditional macroscale current vs voltage theory in the absence of field emission.

  13. A zebrafish model of chordoma initiated by notochord-driven expression of HRASV12.

    Science.gov (United States)

    Burger, Alexa; Vasilyev, Aleksandr; Tomar, Ritu; Selig, Martin K; Nielsen, G Petur; Peterson, Randall T; Drummond, Iain A; Haber, Daniel A

    2014-07-01

    Chordoma is a malignant tumor thought to arise from remnants of the embryonic notochord, with its origin in the bones of the axial skeleton. Surgical resection is the standard treatment, usually in combination with radiation therapy, but neither chemotherapeutic nor targeted therapeutic approaches have demonstrated success. No animal model and only few chordoma cell lines are available for preclinical drug testing, and, although no druggable genetic drivers have been identified, activation of EGFR and downstream AKT-PI3K pathways have been described. Here, we report a zebrafish model of chordoma, based on stable transgene-driven expression of HRASV12 in notochord cells during development. Extensive intra-notochordal tumor formation is evident within days of transgene expression, ultimately leading to larval death. The zebrafish tumors share characteristics of human chordoma as demonstrated by immunohistochemistry and electron microscopy. The mTORC1 inhibitor rapamycin, which has some demonstrated activity in a chordoma cell line, delays the onset of tumor formation in our zebrafish model, and improves survival of tumor-bearing fish. Consequently, the HRASV12-driven zebrafish model of chordoma could enable high-throughput screening of potential therapeutic agents for the treatment of this refractory cancer. © 2014. Published by The Company of Biologists Ltd.

  14. A zebrafish model of chordoma initiated by notochord-driven expression of HRASV12

    Directory of Open Access Journals (Sweden)

    Alexa Burger

    2014-07-01

    Full Text Available Chordoma is a malignant tumor thought to arise from remnants of the embryonic notochord, with its origin in the bones of the axial skeleton. Surgical resection is the standard treatment, usually in combination with radiation therapy, but neither chemotherapeutic nor targeted therapeutic approaches have demonstrated success. No animal model and only few chordoma cell lines are available for preclinical drug testing, and, although no druggable genetic drivers have been identified, activation of EGFR and downstream AKT-PI3K pathways have been described. Here, we report a zebrafish model of chordoma, based on stable transgene-driven expression of HRASV12 in notochord cells during development. Extensive intra-notochordal tumor formation is evident within days of transgene expression, ultimately leading to larval death. The zebrafish tumors share characteristics of human chordoma as demonstrated by immunohistochemistry and electron microscopy. The mTORC1 inhibitor rapamycin, which has some demonstrated activity in a chordoma cell line, delays the onset of tumor formation in our zebrafish model, and improves survival of tumor-bearing fish. Consequently, the HRASV12-driven zebrafish model of chordoma could enable high-throughput screening of potential therapeutic agents for the treatment of this refractory cancer.

  15. Magnetically-driven medical robots: An analytical magnetic model for endoscopic capsules design

    Science.gov (United States)

    Li, Jing; Barjuei, Erfan Shojaei; Ciuti, Gastone; Hao, Yang; Zhang, Peisen; Menciassi, Arianna; Huang, Qiang; Dario, Paolo

    2018-04-01

    Magnetic-based approaches are highly promising to provide innovative solutions for the design of medical devices for diagnostic and therapeutic procedures, such as in the endoluminal districts. Due to the intrinsic magnetic properties (no current needed) and the high strength-to-size ratio compared with electromagnetic solutions, permanent magnets are usually embedded in medical devices. In this paper, a set of analytical formulas have been derived to model the magnetic forces and torques which are exerted by an arbitrary external magnetic field on a permanent magnetic source embedded in a medical robot. In particular, the authors modelled cylindrical permanent magnets as general solution often used and embedded in magnetically-driven medical devices. The analytical model can be applied to axially and diametrically magnetized, solid and annular cylindrical permanent magnets in the absence of the severe calculation complexity. Using a cylindrical permanent magnet as a selected solution, the model has been applied to a robotic endoscopic capsule as a pilot study in the design of magnetically-driven robots.

  16. Time-driven activity-based costing: A dynamic value assessment model in pediatric appendicitis.

    Science.gov (United States)

    Yu, Yangyang R; Abbas, Paulette I; Smith, Carolyn M; Carberry, Kathleen E; Ren, Hui; Patel, Binita; Nuchtern, Jed G; Lopez, Monica E

    2017-06-01

    Healthcare reform policies are emphasizing value-based healthcare delivery. We hypothesize that time-driven activity-based costing (TDABC) can be used to appraise healthcare interventions in pediatric appendicitis. Triage-based standing delegation orders, surgical advanced practice providers, and a same-day discharge protocol were implemented to target deficiencies identified in our initial TDABC model. Post-intervention process maps for a hospital episode were created using electronic time stamp data for simple appendicitis cases during February to March 2016. Total personnel and consumable costs were determined using TDABC methodology. The post-intervention TDABC model featured 6 phases of care, 33 processes, and 19 personnel types. Our interventions reduced duration and costs in the emergency department (-41min, -$23) and pre-operative floor (-57min, -$18). While post-anesthesia care unit duration and costs increased (+224min, +$41), the same-day discharge protocol eliminated post-operative floor costs (-$306). Our model incorporating all three interventions reduced total direct costs by 11% ($2753.39 to $2447.68) and duration of hospitalization by 51% (1984min to 966min). Time-driven activity-based costing can dynamically model changes in our healthcare delivery as a result of process improvement interventions. It is an effective tool to continuously assess the impact of these interventions on the value of appendicitis care. II, Type of study: Economic Analysis. Copyright © 2017 Elsevier Inc. All rights reserved.

  17. Cathode fall model and current-voltage characteristics of field emission driven direct current microplasmas

    International Nuclear Information System (INIS)

    Venkattraman, Ayyaswamy

    2013-01-01

    The post-breakdown characteristics of field emission driven microplasma are studied theoretically and numerically. A cathode fall model assuming a linearly varying electric field is used to obtain equations governing the operation of steady state field emission driven microplasmas. The results obtained from the model by solving these equations are compared with particle-in-cell with Monte Carlo collisions simulation results for parameters including the plasma potential, cathode fall thickness, ion number density in the cathode fall, and current density vs voltage curves. The model shows good overall agreement with the simulations but results in slightly overpredicted values for the plasma potential and the cathode fall thickness attributed to the assumed electric field profile. The current density vs voltage curves obtained show an arc region characterized by negative slope as well as an abnormal glow discharge characterized by a positive slope in gaps as small as 10 μm operating at atmospheric pressure. The model also retrieves the traditional macroscale current vs voltage theory in the absence of field emission

  18. 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.

  19. Uncertainty Driven Action (UDA) model: A foundation for unifying perspectives on design activity

    DEFF Research Database (Denmark)

    Cash, Philip; Kreye, Melanie

    2017-01-01

    are linked via uncertainty perception. The foundations of the UDA model in the design literature are elaborated in terms of the three core actions and their links to designer cognition and behaviour, utilising definitions and concepts from Activity Theory. The practical relevance and theoretical......This paper proposes the Uncertainty Driven Action (UDA) model, which unifies the fragmented literature on design activity. The UDA model conceptualises design activity as a process consisting of three core actions: information action, knowledge-sharing action, and representation action, which...... contributions of the UDA model are discussed. This paper contributes to the design literature by offering a comprehensive formalisation of design activity of individual designers, which connects cognition and action, to provide a foundation for understanding previously disparate descriptions of design activity....

  20. Data-driven process decomposition and robust online distributed modelling for large-scale processes

    Science.gov (United States)

    Shu, Zhang; Lijuan, Li; Lijuan, Yao; Shipin, Yang; Tao, Zou

    2018-02-01

    With the increasing attention of networked control, system decomposition and distributed models show significant importance in the implementation of model-based control strategy. In this paper, a data-driven system decomposition and online distributed subsystem modelling algorithm was proposed for large-scale chemical processes. The key controlled variables are first partitioned by affinity propagation clustering algorithm into several clusters. Each cluster can be regarded as a subsystem. Then the inputs of each subsystem are selected by offline canonical correlation analysis between all process variables and its controlled variables. Process decomposition is then realised after the screening of input and output variables. When the system decomposition is finished, the online subsystem modelling can be carried out by recursively block-wise renewing the samples. The proposed algorithm was applied in the Tennessee Eastman process and the validity was verified.

  1. Model-Checking Driven Design of QoS-Based Routing Protocol for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Zhi Chen

    2015-01-01

    Full Text Available Accurate and reliable routing protocols with Quality of Service (QoS support determine the mission-critical application efficiency in WSNs. This paper proposes a model-checking design driven framework for designing the QoS-based routing protocols of WSNs, which involves the light-weight design process, the timed automata model, and the alternative QoS verification properties. The accurate feedback of continually model checking in the iterative design process effectively stimulates the parameter tuning of the protocols. We demonstrate the straightforward and modular characteristics of the proposed framework in designing a prototype QoS-based routing protocol. The prototype study shows that the model-checking design framework may complement other design methods and ensure the QoS implementation of the QoS-based routing protocol design for WSNs.

  2. Threat driven modeling framework using petri nets for e-learning system.

    Science.gov (United States)

    Khamparia, Aditya; Pandey, Babita

    2016-01-01

    Vulnerabilities at various levels are main cause of security risks in e-learning system. This paper presents a modified threat driven modeling framework, to identify the threats after risk assessment which requires mitigation and how to mitigate those threats. To model those threat mitigations aspects oriented stochastic petri nets are used. This paper included security metrics based on vulnerabilities present in e-learning system. The Common Vulnerability Scoring System designed to provide a normalized method for rating vulnerabilities which will be used as basis in metric definitions and calculations. A case study has been also proposed which shows the need and feasibility of using aspect oriented stochastic petri net models for threat modeling which improves reliability, consistency and robustness of the e-learning system.

  3. Filling-driven Mott transition in SU(N ) Hubbard models

    Science.gov (United States)

    Lee, Seung-Sup B.; von Delft, Jan; Weichselbaum, Andreas

    2018-04-01

    We study the filling-driven Mott transition involving the metallic and paramagnetic insulating phases in SU (N ) Fermi-Hubbard models, using the dynamical mean-field theory and the numerical renormalization group as its impurity solver. The compressibility shows a striking temperature dependence: near the critical end-point temperature, it is strongly enhanced in the metallic phase close to the insulating phase. We demonstrate that this compressibility enhancement is associated with the thermal suppression of the quasiparticle peak in the local spectral functions. We also explain that the asymmetric shape of the quasiparticle peak originates from the asymmetry in the dynamics of the generalized doublons and holons.

  4. Modeling laser-driven electron acceleration using WARP with Fourier decomposition

    Energy Technology Data Exchange (ETDEWEB)

    Lee, P., E-mail: patrick.lee@u-psud.fr [LPGP, CNRS, Univ. Paris-Sud, Université Paris-Saclay, 91405 Orsay (France); Audet, T.L. [LPGP, CNRS, Univ. Paris-Sud, Université Paris-Saclay, 91405 Orsay (France); Lehe, R.; Vay, J.-L. [Lawrence Berkeley National Laboratory, Berkeley, CA 94720 (United States); Maynard, G.; Cros, B. [LPGP, CNRS, Univ. Paris-Sud, Université Paris-Saclay, 91405 Orsay (France)

    2016-09-01

    WARP is used with the recent implementation of the Fourier decomposition algorithm to model laser-driven electron acceleration in plasmas. Simulations were carried out to analyze the experimental results obtained on ionization-induced injection in a gas cell. The simulated results are in good agreement with the experimental ones, confirming the ability of the code to take into account the physics of electron injection and reduce calculation time. We present a detailed analysis of the laser propagation, the plasma wave generation and the electron beam dynamics.

  5. Non-equilibrium entanglement in a driven many-body spin-boson model

    Energy Technology Data Exchange (ETDEWEB)

    Bastidas, Victor M; Reina, John H [Universidad del Valle, Departamento de Fisica, A. A. 25360, Cali (Colombia); Brandes, Tobias, E-mail: vicmabas@univalle.edu.c, E-mail: j.reina-estupinan@physics.ox.ac.u [Institut fuer Theoretische Physik, Technische Universitaet Berlin, Hardenbergstr. 36, 10623 Berlin (Germany)

    2009-05-01

    We study the entanglement dynamics in the externally-driven single-mode Dicke model in the thermodynamic limit, when the field is in resonance with the atoms. We compute the correlations in the atoms-field ground state by means of the density operator that represents the pure state of the universe and the reduced density operator for the atoms, which results from taking the partial trace over the field coordinates. As a measure of bipartite entanglement, we calculate the linear entropy, from which we analyze the entanglement dynamics. In particular, we found a strong relation between the stability of the dynamical parameters and the reported entanglement.

  6. 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

  7. Modelling and Control of the Multi-Stage Cable Pulley-Driven Flexible-Joint Robot

    Directory of Open Access Journals (Sweden)

    Phongsaen Pitakwatchara

    2014-07-01

    Full Text Available This work is concerned with the task space impedance control of a robot driven through a multi-stage nonlinear flexible transmission system. Specifically, a two degrees-of-freedom cable pulley-driven flexible-joint robot is considered. Realistic modelling of the system is developed within the bond graph modelling framework. The model captures the nonlinear compliance behaviour of the multi-stage cable pulley transmission system, the spring effect of the augmented counterbalancing mechanism, the major loss throughout the system elements, and the typical inertial dynamics of the robot. Next, a task space impedance controller based on limited information about the angle and the current of the motors is designed. The motor current is used to infer the transmitted torque, by which the motor inertia may be modulated. The motor angle is employed to estimate the stationary distal robot link angle and the robot joint velocity. They are used in the controller to generate the desired damping force and to shape the potential energy of the flexible joint robot system to the desired configuration. Simulation and experimental results of the controlled system signify the competency of the proposed control law.

  8. Network Model-Assisted Inference from Respondent-Driven Sampling Data.

    Science.gov (United States)

    Gile, Krista J; Handcock, Mark S

    2015-06-01

    Respondent-Driven Sampling is a widely-used method for sampling hard-to-reach human populations by link-tracing over their social networks. Inference from such data requires specialized techniques because the sampling process is both partially beyond the control of the researcher, and partially implicitly defined. Therefore, it is not generally possible to directly compute the sampling weights for traditional design-based inference, and likelihood inference requires modeling the complex sampling process. As an alternative, we introduce a model-assisted approach, resulting in a design-based estimator leveraging a working network model. We derive a new class of estimators for population means and a corresponding bootstrap standard error estimator. We demonstrate improved performance compared to existing estimators, including adjustment for an initial convenience sample. We also apply the method and an extension to the estimation of HIV prevalence in a high-risk population.

  9. Kinematics Modelling of Tendon-Driven Continuum Manipulator with Crossed Notches

    Science.gov (United States)

    Yang, Z. X.; Yang, W. L.; Du, Z. J.

    2018-03-01

    Single port surgical robot (SPSR) is a giant leap in the development of minimally invasive surgical robot. An innovative manipulator with high control accuracy and good kinematic dexterity can reduce wound, expedite recovery, and improve the success rate. This paper presents a tendon-driven continuum manipulator with crossed notches. This manipulator has two degrees of freedom (DOF), which possesses good flexibility and high capacity. Then based on cantilever beam theory, a mechanics model is proposed, which connects external force and deformation of a single flexible ring (SFR). By calculating the deformation of each SFR, the manipulator is considered as a series robot whose joint numbers is equal to SFR numbers, and the kinematics model is established through Denavit-Hartenberg (D-H) procedure. In this paper, the total manipulator is described as a curve tube whose curvature is increased from tip to base. Experiments were conducted and the comparison between theoretical and actual results proved the rationality of the models.

  10. Sensor fault analysis using decision theory and data-driven modeling of pressurized water reactor subsystems

    International Nuclear Information System (INIS)

    Upadhyaya, B.R.; Skorska, M.

    1984-01-01

    Instrument fault detection and estimation is important for process surveillance, control, and safety functions of a power plant. The method incorporates the dual-hypotheses decision procedure and system characterization using data-driven time-domain models of signals representing the system. The multivariate models can be developed on-line and can be adapted to changing system conditions. For the method to be effective, specific subsystems of pressurized water reactors were considered, and signal selection was made such that a strong causal relationship exists among the measured variables. The technique is applied to the reactor core subsystem of the loss-of-fluid test reactor using in-core neutron detector and core-exit thermocouple signals. Thermocouple anomalies such as bias error, noise error, and slow drift in the sensor are detected and estimated using appropriate measurement models

  11. Network Model-Assisted Inference from Respondent-Driven Sampling Data

    Science.gov (United States)

    Gile, Krista J.; Handcock, Mark S.

    2015-01-01

    Summary Respondent-Driven Sampling is a widely-used method for sampling hard-to-reach human populations by link-tracing over their social networks. Inference from such data requires specialized techniques because the sampling process is both partially beyond the control of the researcher, and partially implicitly defined. Therefore, it is not generally possible to directly compute the sampling weights for traditional design-based inference, and likelihood inference requires modeling the complex sampling process. As an alternative, we introduce a model-assisted approach, resulting in a design-based estimator leveraging a working network model. We derive a new class of estimators for population means and a corresponding bootstrap standard error estimator. We demonstrate improved performance compared to existing estimators, including adjustment for an initial convenience sample. We also apply the method and an extension to the estimation of HIV prevalence in a high-risk population. PMID:26640328

  12. Data-driven outbreak forecasting with a simple nonlinear growth model.

    Science.gov (United States)

    Lega, Joceline; Brown, Heidi E

    2016-12-01

    Recent events have thrown the spotlight on infectious disease outbreak response. We developed a data-driven method, EpiGro, which can be applied to cumulative case reports to estimate the order of magnitude of the duration, peak and ultimate size of an ongoing outbreak. It is based on a surprisingly simple mathematical property of many epidemiological data sets, does not require knowledge or estimation of disease transmission parameters, is robust to noise and to small data sets, and runs quickly due to its mathematical simplicity. Using data from historic and ongoing epidemics, we present the model. We also provide modeling considerations that justify this approach and discuss its limitations. In the absence of other information or in conjunction with other models, EpiGro may be useful to public health responders. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

  13. Executable Use Cases: a Supplement to Model-Driven Development?

    DEFF Research Database (Denmark)

    Jørgensen, Jens Bæk

    2007-01-01

    -level requirements and more technical software specifications. In MDD, userlevel requirements are not always explicitly described; it is sufficient for MDD that a specification, or platformindependent model, of the software that we are going to develop is provided. Therefore, a combination of EUCs and MDD may have......Executable Use Cases (EUCs) is a model-based approach to requirements engineering. In the introduction to this paper, we briefly discuss how EUCs may be used as a supplement to Model-Driven Development (MDD). Then we present the EUC approach in more detail. An EUC can describe and link user...... potential to cover the full software engineering path from user-level requirements via specifications to implementations of running computer systems....

  14. 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.

  15. Dynamic model reduction using data-driven Loewner-framework applied to thermally morphing structures

    Science.gov (United States)

    Phoenix, Austin A.; Tarazaga, Pablo A.

    2017-05-01

    The work herein proposes the use of the data-driven Loewner-framework for reduced order modeling as applied to dynamic Finite Element Models (FEM) of thermally morphing structures. The Loewner-based modeling approach is computationally efficient and accurately constructs reduced models using analytical output data from a FEM. This paper details the two-step process proposed in the Loewner approach. First, a random vibration FEM simulation is used as the input for the development of a Single Input Single Output (SISO) data-based dynamic Loewner state space model. Second, an SVD-based truncation is used on the Loewner state space model, such that the minimal, dynamically representative, state space model is achieved. For this second part, varying levels of reduction are generated and compared. The work herein can be extended to model generation using experimental measurements by replacing the FEM output data in the first step and following the same procedure. This method will be demonstrated on two thermally morphing structures, a rigidly fixed hexapod in multiple geometric configurations and a low mass anisotropic morphing boom. This paper is working to detail the method and identify the benefits of the reduced model methodology.

  16. A data-driven, mathematical model of mammalian cell cycle regulation.

    Directory of Open Access Journals (Sweden)

    Michael C Weis

    Full Text Available Few of >150 published cell cycle modeling efforts use significant levels of data for tuning and validation. This reflects the difficultly to generate correlated quantitative data, and it points out a critical uncertainty in modeling efforts. To develop a data-driven model of cell cycle regulation, we used contiguous, dynamic measurements over two time scales (minutes and hours calculated from static multiparametric cytometry data. The approach provided expression profiles of cyclin A2, cyclin B1, and phospho-S10-histone H3. The model was built by integrating and modifying two previously published models such that the model outputs for cyclins A and B fit cyclin expression measurements and the activation of B cyclin/Cdk1 coincided with phosphorylation of histone H3. The model depends on Cdh1-regulated cyclin degradation during G1, regulation of B cyclin/Cdk1 activity by cyclin A/Cdk via Wee1, and transcriptional control of the mitotic cyclins that reflects some of the current literature. We introduced autocatalytic transcription of E2F, E2F regulated transcription of cyclin B, Cdc20/Cdh1 mediated E2F degradation, enhanced transcription of mitotic cyclins during late S/early G2 phase, and the sustained synthesis of cyclin B during mitosis. These features produced a model with good correlation between state variable output and real measurements. Since the method of data generation is extensible, this model can be continually modified based on new correlated, quantitative data.

  17. Model-driven methodology for rapid deployment of smart spaces based on resource-oriented architectures.

    Science.gov (United States)

    Corredor, Iván; Bernardos, Ana M; Iglesias, Josué; Casar, José R

    2012-01-01

    Advances in electronics nowadays facilitate the design of smart spaces based on physical mash-ups of sensor and actuator devices. At the same time, software paradigms such as Internet of Things (IoT) and Web of Things (WoT) are motivating the creation of technology to support the development and deployment of web-enabled embedded sensor and actuator devices with two major objectives: (i) to integrate sensing and actuating functionalities into everyday objects, and (ii) to easily allow a diversity of devices to plug into the Internet. Currently, developers who are applying this Internet-oriented approach need to have solid understanding about specific platforms and web technologies. In order to alleviate this development process, this research proposes a Resource-Oriented and Ontology-Driven Development (ROOD) methodology based on the Model Driven Architecture (MDA). This methodology aims at enabling the development of smart spaces through a set of modeling tools and semantic technologies that support the definition of the smart space and the automatic generation of code at hardware level. ROOD feasibility is demonstrated by building an adaptive health monitoring service for a Smart Gym.

  18. Model-Driven Methodology for Rapid Deployment of Smart Spaces Based on Resource-Oriented Architectures

    Directory of Open Access Journals (Sweden)

    José R. Casar

    2012-07-01

    Full Text Available Advances in electronics nowadays facilitate the design of smart spaces based on physical mash-ups of sensor and actuator devices. At the same time, software paradigms such as Internet of Things (IoT and Web of Things (WoT are motivating the creation of technology to support the development and deployment of web-enabled embedded sensor and actuator devices with two major objectives: (i to integrate sensing and actuating functionalities into everyday objects, and (ii to easily allow a diversity of devices to plug into the Internet. Currently, developers who are applying this Internet-oriented approach need to have solid understanding about specific platforms and web technologies. In order to alleviate this development process, this research proposes a Resource-Oriented and Ontology-Driven Development (ROOD methodology based on the Model Driven Architecture (MDA. This methodology aims at enabling the development of smart spaces through a set of modeling tools and semantic technologies that support the definition of the smart space and the automatic generation of code at hardware level. ROOD feasibility is demonstrated by building an adaptive health monitoring service for a Smart Gym.

  19. Microenvironment temperature prediction between body and seat interface using autoregressive data-driven model.

    Science.gov (United States)

    Liu, Zhuofu; Wang, Lin; Luo, Zhongming; Heusch, Andrew I; Cascioli, Vincenzo; McCarthy, Peter W

    2015-11-01

    There is a need to develop a greater understanding of temperature at the skin-seat interface during prolonged seating from the perspectives of both industrial design (comfort/discomfort) and medical care (skin ulcer formation). Here we test the concept of predicting temperature at the seat surface and skin interface during prolonged sitting (such as required from wheelchair users). As caregivers are usually busy, such a method would give them warning ahead of a problem. This paper describes a data-driven model capable of predicting thermal changes and thus having the potential to provide an early warning (15- to 25-min ahead prediction) of an impending temperature that may increase the risk for potential skin damages for those subject to enforced sitting and who have little or no sensory feedback from this area. Initially, the oscillations of the original signal are suppressed using the reconstruction strategy of empirical mode decomposition (EMD). Consequentially, the autoregressive data-driven model can be used to predict future thermal trends based on a shorter period of acquisition, which reduces the possibility of introducing human errors and artefacts associated with longer duration "enforced" sitting by volunteers. In this study, the method had a maximum predictive error of body insensitivity and disability requiring them to be immobile in seats for prolonged periods. Copyright © 2015 Tissue Viability Society. Published by Elsevier Ltd. All rights reserved.

  20. 0-d energetics scaling models for Z-pinch-driven hohlraums

    International Nuclear Information System (INIS)

    CUNEO, MICHAEL E.; VESEY, ROGER A.; HAMMER, J.H.; PORTER, JOHN L.

    2000-01-01

    Wire array Z-pinches on the Z accelerator provide the most intense laboratory source of soft x-rays in the world. The unique combination of a highly-Planckian radiation source with high x-ray production efficiency (15% wall plug), large x-ray powers and energies ( >150 TW, ge1 MJ in 7 ns), large characteristic hohlraum volumes (0.5 to >10 cm 3 ), and long pulse-lengths (5 to 20 ns) may make Z-pinches a good match to the requirements for driving high-yield scale ICF capsules with adequate radiation symmetry and margin. The Z-pinch driven hohlraum approach of Hammer and Porter [Phys.Plasmas, 6, 2129(1999)] may provide a conservative and robust solution to the requirements for high yield, and is currently being studied on the Z accelerator. This paper describes a multiple region, 0-d hohlraum energetic model for Z-pinch driven hohlraums in four configurations. The authors observe consistency between the models and the measured x-ray powers and hohlraum wall temperatures to within ±20% in flux, for the four configurations

  1. Swiss and Dutch "consumer-driven health care": ideal model or reality?

    Science.gov (United States)

    Okma, Kieke G H; Crivelli, Luca

    2013-02-01

    This article addresses three topics. First, it reports on the international interest in the health care reforms of Switzerland and The Netherlands in the 1990s and early 2000s that operate under the label "managed competition" or "consumer-driven health care." Second, the article reviews the behavior assumptions that make plausible the case for the model of "managed competition." Third, it analyze the actual reform experience of Switzerland and Holland to assess to what extent they confirm the validity of those assumptions. The article concludes that there is a triple gap in understanding of those topics: a gap between the theoretical model of managed competition and the reforms as implemented in both Switzerland and The Netherlands; second, a gap between the expectations of policy-makers and the results of the reforms, and third, a gap between reform outcomes and the observations of external commentators that have embraced the reforms as the ultimate success of "consumer-driven health care." The article concludes with a discussion of the implications of this "triple gap". Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  2. Fast parallel algorithm for three-dimensional distance-driven model in iterative computed tomography reconstruction

    International Nuclear Information System (INIS)

    Chen Jian-Lin; Li Lei; Wang Lin-Yuan; Cai Ai-Long; Xi Xiao-Qi; Zhang Han-Ming; Li Jian-Xin; Yan Bin

    2015-01-01

    The projection matrix model is used to describe the physical relationship between reconstructed object and projection. Such a model has a strong influence on projection and backprojection, two vital operations in iterative computed tomographic reconstruction. The distance-driven model (DDM) is a state-of-the-art technology that simulates forward and back projections. This model has a low computational complexity and a relatively high spatial resolution; however, it includes only a few methods in a parallel operation with a matched model scheme. This study introduces a fast and parallelizable algorithm to improve the traditional DDM for computing the parallel projection and backprojection operations. Our proposed model has been implemented on a GPU (graphic processing unit) platform and has achieved satisfactory computational efficiency with no approximation. The runtime for the projection and backprojection operations with our model is approximately 4.5 s and 10.5 s per loop, respectively, with an image size of 256×256×256 and 360 projections with a size of 512×512. We compare several general algorithms that have been proposed for maximizing GPU efficiency by using the unmatched projection/backprojection models in a parallel computation. The imaging resolution is not sacrificed and remains accurate during computed tomographic reconstruction. (paper)

  3. Development of Bubble Driven Flow CFD Model Applied for Aluminium Smelting Cells

    Directory of Open Access Journals (Sweden)

    Y.Q. Feng

    2010-09-01

    Full Text Available This paper presents the development of a computational fluid dynamics (CFD model for the study of bubble driven bath flow in aluminium reduction cells. For validation purposes, the model development was conducted using a full scale air -water model of part of an aluminium reduction cell as a test-bed. The bubble induced turbulence has been modelled by either modifying bubble induced turbulence viscosity directly or by modifying bubble induced turbulence kinetic energy in a standard k- ε turbulence model. The relative performance of the two modelling approaches has been examined through comparison with experimental data taken under similar conditions using Particle Image Velocimetry (PIV. Detailed comparison has been conducted by point-wise comparison of liquid velocities to quantify the level of agreement between CFD simulation and PIV measurement. Both models can capture the key flow patterns determined by PIV measurement, while the modified turbulence kinetic energy model gives better agreement with flow patterns in the gap between anode and cathode.

  4. Developing a Data Driven Process-Based Model for Remote Sensing of Ecosystem Production

    Science.gov (United States)

    Elmasri, B.; Rahman, A. F.

    2010-12-01

    Estimating ecosystem carbon fluxes at various spatial and temporal scales is essential for quantifying the global carbon cycle. Numerous models have been developed for this purpose using several environmental variables as well as vegetation indices derived from remotely sensed data. Here we present a data driven modeling approach for gross primary production (GPP) that is based on a process based model BIOME-BGC. The proposed model was run using available remote sensing data and it does not depend on look-up tables. Furthermore, this approach combines the merits of both empirical and process models, and empirical models were used to estimate certain input variables such as light use efficiency (LUE). This was achieved by using remotely sensed data to the mathematical equations that represent biophysical photosynthesis processes in the BIOME-BGC model. Moreover, a new spectral index for estimating maximum photosynthetic activity, maximum photosynthetic rate index (MPRI), is also developed and presented here. This new index is based on the ratio between the near infrared and the green bands (ρ858.5/ρ555). The model was tested and validated against MODIS GPP product and flux measurements from two eddy covariance flux towers located at Morgan Monroe State Forest (MMSF) in Indiana and Harvard Forest in Massachusetts. Satellite data acquired by the Advanced Microwave Scanning Radiometer (AMSR-E) and MODIS were used. The data driven model showed a strong correlation between the predicted and measured GPP at the two eddy covariance flux towers sites. This methodology produced better predictions of GPP than did the MODIS GPP product. Moreover, the proportion of error in the predicted GPP for MMSF and Harvard forest was dominated by unsystematic errors suggesting that the results are unbiased. The analysis indicated that maintenance respiration is one of the main factors that dominate the overall model outcome errors and improvement in maintenance respiration estimation

  5. Knowledge-driven computational modeling in Alzheimer's disease research: Current state and future trends.

    Science.gov (United States)

    Geerts, Hugo; Hofmann-Apitius, Martin; Anastasio, Thomas J

    2017-11-01

    Neurodegenerative diseases such as Alzheimer's disease (AD) follow a slowly progressing dysfunctional trajectory, with a large presymptomatic component and many comorbidities. Using preclinical models and large-scale omics studies ranging from genetics to imaging, a large number of processes that might be involved in AD pathology at different stages and levels have been identified. The sheer number of putative hypotheses makes it almost impossible to estimate their contribution to the clinical outcome and to develop a comprehensive view on the pathological processes driving the clinical phenotype. Traditionally, bioinformatics approaches have provided correlations and associations between processes and phenotypes. Focusing on causality, a new breed of advanced and more quantitative modeling approaches that use formalized domain expertise offer new opportunities to integrate these different modalities and outline possible paths toward new therapeutic interventions. This article reviews three different computational approaches and their possible complementarities. Process algebras, implemented using declarative programming languages such as Maude, facilitate simulation and analysis of complicated biological processes on a comprehensive but coarse-grained level. A model-driven Integration of Data and Knowledge, based on the OpenBEL platform and using reverse causative reasoning and network jump analysis, can generate mechanistic knowledge and a new, mechanism-based taxonomy of disease. Finally, Quantitative Systems Pharmacology is based on formalized implementation of domain expertise in a more fine-grained, mechanism-driven, quantitative, and predictive humanized computer model. We propose a strategy to combine the strengths of these individual approaches for developing powerful modeling methodologies that can provide actionable knowledge for rational development of preventive and therapeutic interventions. Development of these computational approaches is likely to

  6. Tropically driven and externally forced patterns of Antarctic sea ice change: reconciling observed and modeled trends

    Science.gov (United States)

    Schneider, David P.; Deser, Clara

    2017-09-01

    Recent work suggests that natural variability has played a significant role in the increase of Antarctic sea ice extent during 1979-2013. The ice extent has responded strongly to atmospheric circulation changes, including a deepened Amundsen Sea Low (ASL), which in part has been driven by tropical variability. Nonetheless, this increase has occurred in the context of externally forced climate change, and it has been difficult to reconcile observed and modeled Antarctic sea ice trends. To understand observed-model disparities, this work defines the internally driven and radiatively forced patterns of Antarctic sea ice change and exposes potential model biases using results from two sets of historical experiments of a coupled climate model compared with observations. One ensemble is constrained only by external factors such as greenhouse gases and stratospheric ozone, while the other explicitly accounts for the influence of tropical variability by specifying observed SST anomalies in the eastern tropical Pacific. The latter experiment reproduces the deepening of the ASL, which drives an increase in regional ice extent due to enhanced ice motion and sea surface cooling. However, the overall sea ice trend in every ensemble member of both experiments is characterized by ice loss and is dominated by the forced pattern, as given by the ensemble-mean of the first experiment. This pervasive ice loss is associated with a strong warming of the ocean mixed layer, suggesting that the ocean model does not locally store or export anomalous heat efficiently enough to maintain a surface environment conducive to sea ice expansion. The pervasive upper-ocean warming, not seen in observations, likely reflects ocean mean-state biases.

  7. Tropically driven and externally forced patterns of Antarctic sea ice change: reconciling observed and modeled trends

    Science.gov (United States)

    Schneider, David P.; Deser, Clara

    2018-06-01

    Recent work suggests that natural variability has played a significant role in the increase of Antarctic sea ice extent during 1979-2013. The ice extent has responded strongly to atmospheric circulation changes, including a deepened Amundsen Sea Low (ASL), which in part has been driven by tropical variability. Nonetheless, this increase has occurred in the context of externally forced climate change, and it has been difficult to reconcile observed and modeled Antarctic sea ice trends. To understand observed-model disparities, this work defines the internally driven and radiatively forced patterns of Antarctic sea ice change and exposes potential model biases using results from two sets of historical experiments of a coupled climate model compared with observations. One ensemble is constrained only by external factors such as greenhouse gases and stratospheric ozone, while the other explicitly accounts for the influence of tropical variability by specifying observed SST anomalies in the eastern tropical Pacific. The latter experiment reproduces the deepening of the ASL, which drives an increase in regional ice extent due to enhanced ice motion and sea surface cooling. However, the overall sea ice trend in every ensemble member of both experiments is characterized by ice loss and is dominated by the forced pattern, as given by the ensemble-mean of the first experiment. This pervasive ice loss is associated with a strong warming of the ocean mixed layer, suggesting that the ocean model does not locally store or export anomalous heat efficiently enough to maintain a surface environment conducive to sea ice expansion. The pervasive upper-ocean warming, not seen in observations, likely reflects ocean mean-state biases.

  8. Deriving albedo maps for HAPEX-Sahel from ASAS data using kernel-driven BRDF models

    Directory of Open Access Journals (Sweden)

    P. Lewis

    1999-01-01

    Full Text Available This paper describes the application and testing of a method for deriving spatial estimates of albedo from multi-angle remote sensing data. Linear kernel-driven models of surface bi-directional reflectance have been inverted against high spatial resolution multi-angular, multi- spectral airborne data of the principal cover types within the HAPEX-Sahel study site in Niger, West Africa. The airborne data are obtained from the NASA Airborne Solid-state Imaging Spectrometer (ASAS instrument, flown in Niger in September and October 1992. The maps of model parameters produced are used to estimate integrated reflectance properties related to spectral albedo. Broadband albedo has been estimated from this by weighting the spectral albedo for each pixel within the map as a function of the appropriate spectral solar irradiance and proportion of direct and diffuse illumination. Partial validation of the results was performed by comparing ASAS reflectance and derived directional-hemispherical reflectance with simulations of a millet canopy made with a complex geometric canopy reflectance model, the Botanical Plant Modelling System (BPMS. Both were found to agree well in magnitude. Broadband albedo values derived from the ASAS data were compared with ground-based (point sample albedo measurements and found to agree extremely well. These results indicate that the linear kernel-driven modelling approach, which is to be used operationally to produce global 16 day, 1 km albedo maps from forthcoming NASA Earth Observing System spaceborne data, is both sound and practical for the estimation of angle-integrated spectral reflectance quantities related to albedo. Results for broadband albedo are dependent on spectral sampling and on obtaining the correct spectral weigthings.

  9. A predictive estimation method for carbon dioxide transport by data-driven modeling with a physically-based data model

    Science.gov (United States)

    Jeong, Jina; Park, Eungyu; Han, Weon Shik; Kim, Kue-Young; Jun, Seong-Chun; Choung, Sungwook; Yun, Seong-Taek; Oh, Junho; Kim, Hyun-Jun

    2017-11-01

    In this study, a data-driven method for predicting CO2 leaks and associated concentrations from geological CO2 sequestration is developed. Several candidate models are compared based on their reproducibility and predictive capability for CO2 concentration measurements from the Environment Impact Evaluation Test (EIT) site in Korea. Based on the data mining results, a one-dimensional solution of the advective-dispersive equation for steady flow (i.e., Ogata-Banks solution) is found to be most representative for the test data, and this model is adopted as the data model for the developed method. In the validation step, the method is applied to estimate future CO2 concentrations with the reference estimation by the Ogata-Banks solution, where a part of earlier data is used as the training dataset. From the analysis, it is found that the ensemble mean of multiple estimations based on the developed method shows high prediction accuracy relative to the reference estimation. In addition, the majority of the data to be predicted are included in the proposed quantile interval, which suggests adequate representation of the uncertainty by the developed method. Therefore, the incorporation of a reasonable physically-based data model enhances the prediction capability of the data-driven model. The proposed method is not confined to estimations of CO2 concentration and may be applied to various real-time monitoring data from subsurface sites to develop automated control, management or decision-making systems.

  10. Analytical method of CIM to PIM transformation in Model Driven Architecture (MDA

    Directory of Open Access Journals (Sweden)

    Martin Kardos

    2010-06-01

    Full Text Available Information system’s models on higher level of abstraction have become a daily routine in many software companies. The concept of Model Driven Architecture (MDA published by standardization body OMG1 since 2001 has become a concept for creation of software applications and information systems. MDA specifies four levels of abstraction: top three levels are created as graphical models and the last one as implementation code model. Many research works of MDA are focusing on the lower levels and transformations between each other. The top level of abstraction, called Computation Independent Model (CIM and its transformation to the lower level called Platform Independent Model (PIM is not so extensive research topic. Considering to a great importance and usability of this level in practice of IS2Keywords: transformation, MDA, CIM, PIM, UML, DFD. development now our research activity is focused to this highest level of abstraction – CIM and its possible transformation to the lower PIM level. In this article we are presenting a possible solution of CIM modeling and its analytic method of transformation to PIM.

  11. Mathematical Model of Growth Factor Driven Haptotaxis and Proliferation in a Tissue Engineering Scaffold

    KAUST Repository

    Pohlmeyer, J. V.

    2013-01-29

    Motivated by experimental work (Miller et al. in Biomaterials 27(10):2213-2221, 2006, 32(11):2775-2785, 2011) we investigate the effect of growth factor driven haptotaxis and proliferation in a perfusion tissue engineering bioreactor, in which nutrient-rich culture medium is perfused through a 2D porous scaffold impregnated with growth factor and seeded with cells. We model these processes on the timescale of cell proliferation, which typically is of the order of days. While a quantitative representation of these phenomena requires more experimental data than is yet available, qualitative agreement with preliminary experimental studies (Miller et al. in Biomaterials 27(10):2213-2221, 2006) is obtained, and appears promising. The ultimate goal of such modeling is to ascertain initial conditions (growth factor distribution, initial cell seeding, etc.) that will lead to a final desired outcome. © 2013 Society for Mathematical Biology.

  12. 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.

  13. Constitutive modeling of stress-driven grain growth in nanocrystalline metals

    KAUST Repository

    Gürses, Ercan

    2013-02-08

    In this work, we present a variational multiscale model for grain growth in face-centered cubic nanocrystalline (nc) metals. In particular, grain-growth-induced stress softening and the resulting relaxation phenomena are addressed. The behavior of the polycrystal is described by a conventional Taylor-type averaging scheme in which the grains are treated as two-phase composites consisting of a grain interior phase and a grain boundary-affected zone. Furthermore, a grain-growth law that captures the experimentally observed characteristics of the grain coarsening phenomena is proposed. To this end, the grain size is not taken as constant and varies according to the proposed stress-driven growth law. Several parametric studies are conducted to emphasize the influence of the grain-growth rule on the overall macroscopic response. Finally, the model is shown to provide a good description of the experimentally observed grain-growth-induced relaxation in nc-copper. © 2013 IOP Publishing Ltd.

  14. Automatic sleep classification using a data-driven topic model reveals latent sleep states

    DEFF Research Database (Denmark)

    Koch, Henriette; Christensen, Julie Anja Engelhard; Frandsen, Rune

    2014-01-01

    Latent Dirichlet Allocation. Model application was tested on control subjects and patients with periodic leg movements (PLM) representing a non-neurodegenerative group, and patients with idiopathic REM sleep behavior disorder (iRBD) and Parkinson's Disease (PD) representing a neurodegenerative group......Background: The golden standard for sleep classification uses manual scoring of polysomnography despite points of criticism such as oversimplification, low inter-rater reliability and the standard being designed on young and healthy subjects. New method: To meet the criticism and reveal the latent...... sleep states, this study developed a general and automatic sleep classifier using a data-driven approach. Spectral EEG and EOG measures and eye correlation in 1 s windows were calculated and each sleep epoch was expressed as a mixture of probabilities of latent sleep states by using the topic model...

  15. 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...

  16. Weather models as virtual sensors to data-driven rainfall predictions in urban watersheds

    Science.gov (United States)

    Cozzi, Lorenzo; Galelli, Stefano; Pascal, Samuel Jolivet De Marc; Castelletti, Andrea

    2013-04-01

    Weather and climate predictions are a key element of urban hydrology where they are used to inform water management and assist in flood warning delivering. Indeed, the modelling of the very fast dynamics of urbanized catchments can be substantially improved by the use of weather/rainfall predictions. For example, in Singapore Marina Reservoir catchment runoff processes have a very short time of concentration (roughly one hour) and observational data are thus nearly useless for runoff predictions and weather prediction are required. Unfortunately, radar nowcasting methods do not allow to carrying out long - term weather predictions, whereas numerical models are limited by their coarse spatial scale. Moreover, numerical models are usually poorly reliable because of the fast motion and limited spatial extension of rainfall events. In this study we investigate the combined use of data-driven modelling techniques and weather variables observed/simulated with a numerical model as a way to improve rainfall prediction accuracy and lead time in the Singapore metropolitan area. To explore the feasibility of the approach, we use a Weather Research and Forecast (WRF) model as a virtual sensor network for the input variables (the states of the WRF model) to a machine learning rainfall prediction model. More precisely, we combine an input variable selection method and a non-parametric tree-based model to characterize the empirical relation between the rainfall measured at the catchment level and all possible weather input variables provided by WRF model. We explore different lead time to evaluate the model reliability for different long - term predictions, as well as different time lags to see how past information could improve results. Results show that the proposed approach allow a significant improvement of the prediction accuracy of the WRF model on the Singapore urban area.

  17. 3D finite element model of the diabetic neuropathic foot: a gait analysis driven approach.

    Science.gov (United States)

    Guiotto, Annamaria; Sawacha, Zimi; Guarneri, Gabriella; Avogaro, Angelo; Cobelli, Claudio

    2014-09-22

    Diabetic foot is an invalidating complication of diabetes that can lead to foot ulcers. Three-dimensional (3D) finite element analysis (FEA) allows characterizing the loads developed in the different anatomical structures of the foot in dynamic conditions. The aim of this study was to develop a subject specific 3D foot FE model (FEM) of a diabetic neuropathic (DNS) and a healthy (HS) subject, whose subject specificity can be found in term of foot geometry and boundary conditions. Kinematics, kinetics and plantar pressure (PP) data were extracted from the gait analysis trials of the two subjects with this purpose. The FEM were developed segmenting bones, cartilage and skin from MRI and drawing a horizontal plate as ground support. Materials properties were adopted from previous literature. FE simulations were run with the kinematics and kinetics data of four different phases of the stance phase of gait (heel strike, loading response, midstance and push off). FEMs were then driven by group gait data of 10 neuropathic and 10 healthy subjects. Model validation focused on agreement between FEM-simulated and experimental PP. The peak values and the total distribution of the pressures were compared for this purpose. Results showed that the models were less robust when driven from group data and underestimated the PP in each foot subarea. In particular in the case of the neuropathic subject's model the mean errors between experimental and simulated data were around the 20% of the peak values. This knowledge is crucial in understanding the aetiology of diabetic foot. Copyright © 2014 Elsevier Ltd. All rights reserved.

  18. Simulation of shallow groundwater levels: Comparison of a data-driven and a conceptual model

    Science.gov (United States)

    Fahle, Marcus; Dietrich, Ottfried; Lischeid, Gunnar

    2015-04-01

    Despite an abundance of models aimed at simulating shallow groundwater levels, application of such models is often hampered by a lack of appropriate input data. Difficulties especially arise with regard to soil data, which are typically hard to obtain and prone to spatial variability, eventually leading to uncertainties in the model results. Modelling approaches relying entirely on easily measured quantities are therefore an alternative to encourage the applicability of models. We present and compare two models for calculating 1-day-ahead predictions of the groundwater level that are only based on measurements of potential evapotranspiration, precipitation and groundwater levels. The first model is a newly developed conceptual model that is parametrized using the White method (which estimates the actual evapotranspiration on basis of diurnal groundwater fluctuations) and a rainfall-response ratio. Inverted versions of the two latter approaches are then used to calculate the predictions of the groundwater level. Furthermore, as a completely data-driven alternative, a simple feed-forward multilayer perceptron neural network was trained based on the same inputs and outputs. Data of 4 growing periods (April to October) from a study site situated in the Spreewald wetland in North-east Germany were taken to set-up the models and compare their performance. In addition, response surfaces that relate model outputs to combinations of different input variables are used to reveal those aspects in which the two approaches coincide and those in which they differ. Finally, it will be evaluated whether the conceptual approach can be enhanced by extracting knowledge of the neural network. This is done by replacing in the conceptual model the default function that relates groundwater recharge and groundwater level, which is assumed to be linear, by the non-linear function extracted from the neural network.

  19. A transferable coarse-grained model for diphenylalanine: How to represent an environment driven conformational transition

    Science.gov (United States)

    Dalgicdir, Cahit; Sensoy, Ozge; Peter, Christine; Sayar, Mehmet

    2013-12-01

    One of the major challenges in the development of coarse grained (CG) simulation models that aim at biomolecular structure formation processes is the correct representation of an environment-driven conformational change, for example, a folding/unfolding event upon interaction with an interface or upon aggregation. In the present study, we investigate this transferability challenge for a CG model using the example of diphenylalanine. This dipeptide displays a transition from a trans-like to a cis-like conformation upon aggregation as well as upon transfer from bulk water to the cyclohexane/water interface. Here, we show that one can construct a single CG model that can reproduce both the bulk and interface conformational behavior and the segregation between hydrophobic/hydrophilic medium. While the general strategy to obtain nonbonded interactions in the present CG model is to reproduce solvation free energies of small molecules representing the CG beads in the respective solvents, the success of the model strongly depends on nontrivial decisions one has to make to capture the delicate balance between the bonded and nonbonded interactions. In particular, we found that the peptide's conformational behavior is qualitatively affected by the cyclohexane/water interaction potential, an interaction that does not directly involve the peptide at all but merely influences the properties of the hydrophobic/hydrophilic interface. Furthermore, we show that a small modification to improve the structural/conformational properties of the CG model could dramatically alter the thermodynamic properties.

  20. Data-driven model-independent searches for long-lived particles at the LHC

    Science.gov (United States)

    Coccaro, Andrea; Curtin, David; Lubatti, H. J.; Russell, Heather; Shelton, Jessie

    2016-12-01

    Neutral long-lived particles (LLPs) are highly motivated by many beyond the Standard Model scenarios, such as theories of supersymmetry, baryogenesis, and neutral naturalness, and present both tremendous discovery opportunities and experimental challenges for the LHC. A major bottleneck for current LLP searches is the prediction of Standard Model backgrounds, which are often impossible to simulate accurately. In this paper, we propose a general strategy for obtaining differential, data-driven background estimates in LLP searches, thereby notably extending the range of LLP masses and lifetimes that can be discovered at the LHC. We focus on LLPs decaying in the ATLAS muon system, where triggers providing both signal and control samples are available at LHC run 2. While many existing searches require two displaced decays, a detailed knowledge of backgrounds will allow for very inclusive searches that require just one detected LLP decay. As we demonstrate for the h →X X signal model of LLP pair production in exotic Higgs decays, this results in dramatic sensitivity improvements for proper lifetimes ≳10 m . In theories of neutral naturalness, this extends reach to glueball masses far below the b ¯b threshold. Our strategy readily generalizes to other signal models and other detector subsystems. This framework therefore lends itself to the development of a systematic, model-independent LLP search program, in analogy to the highly successful simplified-model framework of prompt searches.

  1. A transferable coarse-grained model for diphenylalanine: How to represent an environment driven conformational transition

    International Nuclear Information System (INIS)

    Dalgicdir, Cahit; Sensoy, Ozge; Sayar, Mehmet; Peter, Christine

    2013-01-01

    One of the major challenges in the development of coarse grained (CG) simulation models that aim at biomolecular structure formation processes is the correct representation of an environment-driven conformational change, for example, a folding/unfolding event upon interaction with an interface or upon aggregation. In the present study, we investigate this transferability challenge for a CG model using the example of diphenylalanine. This dipeptide displays a transition from a trans-like to a cis-like conformation upon aggregation as well as upon transfer from bulk water to the cyclohexane/water interface. Here, we show that one can construct a single CG model that can reproduce both the bulk and interface conformational behavior and the segregation between hydrophobic/hydrophilic medium. While the general strategy to obtain nonbonded interactions in the present CG model is to reproduce solvation free energies of small molecules representing the CG beads in the respective solvents, the success of the model strongly depends on nontrivial decisions one has to make to capture the delicate balance between the bonded and nonbonded interactions. In particular, we found that the peptide's conformational behavior is qualitatively affected by the cyclohexane/water interaction potential, an interaction that does not directly involve the peptide at all but merely influences the properties of the hydrophobic/hydrophilic interface. Furthermore, we show that a small modification to improve the structural/conformational properties of the CG model could dramatically alter the thermodynamic properties

  2. A transferable coarse-grained model for diphenylalanine: How to represent an environment driven conformational transition

    Energy Technology Data Exchange (ETDEWEB)

    Dalgicdir, Cahit; Sensoy, Ozge; Sayar, Mehmet, E-mail: msayar@ku.edu.tr [College of Engineering, Koç University, 34450 Istanbul (Turkey); Peter, Christine [Max Planck Institute for Polymer Research, 55128 Mainz (Germany); Department of Chemistry, University of Konstanz, 78547 Konstanz (Germany)

    2013-12-21

    One of the major challenges in the development of coarse grained (CG) simulation models that aim at biomolecular structure formation processes is the correct representation of an environment-driven conformational change, for example, a folding/unfolding event upon interaction with an interface or upon aggregation. In the present study, we investigate this transferability challenge for a CG model using the example of diphenylalanine. This dipeptide displays a transition from a trans-like to a cis-like conformation upon aggregation as well as upon transfer from bulk water to the cyclohexane/water interface. Here, we show that one can construct a single CG model that can reproduce both the bulk and interface conformational behavior and the segregation between hydrophobic/hydrophilic medium. While the general strategy to obtain nonbonded interactions in the present CG model is to reproduce solvation free energies of small molecules representing the CG beads in the respective solvents, the success of the model strongly depends on nontrivial decisions one has to make to capture the delicate balance between the bonded and nonbonded interactions. In particular, we found that the peptide's conformational behavior is qualitatively affected by the cyclohexane/water interaction potential, an interaction that does not directly involve the peptide at all but merely influences the properties of the hydrophobic/hydrophilic interface. Furthermore, we show that a small modification to improve the structural/conformational properties of the CG model could dramatically alter the thermodynamic properties.

  3. Particle force model effects in a shock-driven multiphase instability

    Science.gov (United States)

    Black, W. J.; Denissen, N.; McFarland, J. A.

    2018-05-01

    This work presents simulations on a shock-driven multiphase instability (SDMI) at an initial particle volume fraction of 1% with the addition of a suite of particle force models applicable in dense flows. These models include pressure-gradient, added-mass, and interparticle force terms in an effort to capture the effects neighboring particles have in non-dilute flow regimes. Two studies are presented here: the first seeks to investigate the individual contributions of the force models, while the second study focuses on examining the effect of these force models on the hydrodynamic evolution of a SDMI with various particle relaxation times (particle sizes). In the force study, it was found that the pressure gradient and interparticle forces have little effect on the instability under the conditions examined, while the added-mass force decreases the vorticity deposition and alters the morphology of the instability. The relaxation-time study likewise showed a decrease in metrics associated with the evolution of the SDMI for all sizes when the particle force models were included. The inclusion of these models showed significant morphological differences in both the particle and carrier species fields, which increased as particle relaxation times increased.

  4. A beamline systems model for Accelerator-Driven Transmutation Technology (ADTT) facilities

    Energy Technology Data Exchange (ETDEWEB)

    Todd, A.M.M.; Paulson, C.C.; Peacock, M.A. [Grumman Research and Development Center, Princeton, NJ (United States)] [and others

    1995-10-01

    A beamline systems code, that is being developed for Accelerator-Driven Transmutation Technology (ADTT) facility trade studies, is described. The overall program is a joint Grumman, G.H. Gillespie Associates (GHGA) and Los Alamos National Laboratory effort. The GHGA Accelerator Systems Model (ASM) has been adopted as the framework on which this effort is based. Relevant accelerator and beam transport models from earlier Grumman systems codes are being adapted to this framework. Preliminary physics and engineering models for each ADTT beamline component have been constructed. Examples noted include a Bridge Coupled Drift Tube Linac (BCDTL) and the accelerator thermal system. A decision has been made to confine the ASM framework principally to beamline modeling, while detailed target/blanket, balance-of-plant and facility costing analysis will be performed externally. An interfacing external balance-of-plant and facility costing model, which will permit the performance of iterative facility trade studies, is under separate development. An ABC (Accelerator Based Conversion) example is used to highlight the present models and capabilities.

  5. A beamline systems model for Accelerator-Driven Transmutation Technology (ADTT) facilities

    International Nuclear Information System (INIS)

    Todd, Alan M. M.; Paulson, C. C.; Peacock, M. A.; Reusch, M. F.

    1995-01-01

    A beamline systems code, that is being developed for Accelerator-Driven Transmutation Technology (ADTT) facility trade studies, is described. The overall program is a joint Grumman, G. H. Gillespie Associates (GHGA) and Los Alamos National Laboratory effort. The GHGA Accelerator Systems Model (ASM) has been adopted as the framework on which this effort is based. Relevant accelerator and beam transport models from earlier Grumman systems codes are being adapted to this framework. Preliminary physics and engineering models for each ADTT beamline component have been constructed. Examples noted include a Bridge Coupled Drift Tube Linac (BCDTL) and the accelerator thermal system. A decision has been made to confine the ASM framework principally to beamline modeling, while detailed target/blanket, balance-of-plant and facility costing analysis will be performed externally. An interfacing external balance-of-plant and facility costing model, which will permit the performance of iterative facility trade studies, is under separate development. An ABC (Accelerator Based Conversion) example is used to highlight the present models and capabilities

  6. IoT-based user-driven service modeling environment for a smart space management system.

    Science.gov (United States)

    Choi, Hoan-Suk; Rhee, Woo-Seop

    2014-11-20

    The existing Internet environment has been extended to the Internet of Things (IoT) as an emerging new paradigm. The IoT connects various physical entities. These entities have communication capability and deploy the observed information to various service areas such as building management, energy-saving systems, surveillance services, and smart homes. These services are designed and developed by professional service providers. Moreover, users' needs have become more complicated and personalized with the spread of user-participation services such as social media and blogging. Therefore, some active users want to create their own services to satisfy their needs, but the existing IoT service-creation environment is difficult for the non-technical user because it requires a programming capability to create a service. To solve this problem, we propose the IoT-based user-driven service modeling environment to provide an easy way to create IoT services. Also, the proposed environment deploys the defined service to another user. Through the personalization and customization of the defined service, the value and dissemination of the service is increased. This environment also provides the ontology-based context-information processing that produces and describes the context information for the IoT-based user-driven service.

  7. Error Analysis of Satellite Precipitation-Driven Modeling of Flood Events in Complex Alpine Terrain

    Directory of Open Access Journals (Sweden)

    Yiwen Mei

    2016-03-01

    Full Text Available The error in satellite precipitation-driven complex terrain flood simulations is characterized in this study for eight different global satellite products and 128 flood events over the Eastern Italian Alps. The flood events are grouped according to two flood types: rain floods and flash floods. The satellite precipitation products and runoff simulations are evaluated based on systematic and random error metrics applied on the matched event pairs and basin-scale event properties (i.e., rainfall and runoff cumulative depth and time series shape. Overall, error characteristics exhibit dependency on the flood type. Generally, timing of the event precipitation mass center and dispersion of the time series derived from satellite precipitation exhibits good agreement with the reference; the cumulative depth is mostly underestimated. The study shows a dampening effect in both systematic and random error components of the satellite-driven hydrograph relative to the satellite-retrieved hyetograph. The systematic error in shape of the time series shows a significant dampening effect. The random error dampening effect is less pronounced for the flash flood events and the rain flood events with a high runoff coefficient. This event-based analysis of the satellite precipitation error propagation in flood modeling sheds light on the application of satellite precipitation in mountain flood hydrology.

  8. Tensegrity and motor-driven effective interactions in a model cytoskeleton

    Science.gov (United States)

    Wang, Shenshen; Wolynes, Peter G.

    2012-04-01

    Actomyosin networks are major structural components of the cell. They provide mechanical integrity and allow dynamic remodeling of eukaryotic cells, self-organizing into the diverse patterns essential for development. We provide a theoretical framework to investigate the intricate interplay between local force generation, network connectivity, and collective action of molecular motors. This framework is capable of accommodating both regular and heterogeneous pattern formation, arrested coarsening and macroscopic contraction in a unified manner. We model the actomyosin system as a motorized cat's cradle consisting of a crosslinked network of nonlinear elastic filaments subjected to spatially anti-correlated motor kicks acting on motorized (fibril) crosslinks. The phase diagram suggests there can be arrested phase separation which provides a natural explanation for the aggregation and coalescence of actomyosin condensates. Simulation studies confirm the theoretical picture that a nonequilibrium many-body system driven by correlated motor kicks can behave as if it were at an effective equilibrium, but with modified interactions that account for the correlation of the motor driven motions of the actively bonded nodes. Regular aster patterns are observed both in Brownian dynamics simulations at effective equilibrium and in the complete stochastic simulations. The results show that large-scale contraction requires correlated kicking.

  9. Central focused convolutional neural networks: Developing a data-driven model for lung nodule segmentation.

    Science.gov (United States)

    Wang, Shuo; Zhou, Mu; Liu, Zaiyi; Liu, Zhenyu; Gu, Dongsheng; Zang, Yali; Dong, Di; Gevaert, Olivier; Tian, Jie

    2017-08-01

    Accurate lung nodule segmentation from computed tomography (CT) images is of great importance for image-driven lung cancer analysis. However, the heterogeneity of lung nodules and the presence of similar visual characteristics between nodules and their surroundings make it difficult for robust nodule segmentation. In this study, we propose a data-driven model, termed the Central Focused Convolutional Neural Networks (CF-CNN), to segment lung nodules from heterogeneous CT images. Our approach combines two key insights: 1) the proposed model captures a diverse set of nodule-sensitive features from both 3-D and 2-D CT images simultaneously; 2) when classifying an image voxel, the effects of its neighbor voxels can vary according to their spatial locations. We describe this phenomenon by proposing a novel central pooling layer retaining much information on voxel patch center, followed by a multi-scale patch learning strategy. Moreover, we design a weighted sampling to facilitate the model training, where training samples are selected according to their degree of segmentation difficulty. The proposed method has been extensively evaluated on the public LIDC dataset including 893 nodules and an independent dataset with 74 nodules from Guangdong General Hospital (GDGH). We showed that CF-CNN achieved superior segmentation performance with average dice scores of 82.15% and 80.02% for the two datasets respectively. Moreover, we compared our results with the inter-radiologists consistency on LIDC dataset, showing a difference in average dice score of only 1.98%. Copyright © 2017. Published by Elsevier B.V.

  10. 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

  11. Model-based optimization strategy of chiller driven liquid desiccant dehumidifier with genetic algorithm

    International Nuclear Information System (INIS)

    Wang, Xinli; Cai, Wenjian; Lu, Jiangang; Sun, Youxian; Zhao, Lei

    2015-01-01

    This study presents a model-based optimization strategy for an actual chiller driven dehumidifier of liquid desiccant dehumidification system operating with lithium chloride solution. By analyzing the characteristics of the components, energy predictive models for the components in the dehumidifier are developed. To minimize the energy usage while maintaining the outlet air conditions at the pre-specified set-points, an optimization problem is formulated with an objective function, the constraints of mechanical limitations and components interactions. Model-based optimization strategy using genetic algorithm is proposed to obtain the optimal set-points for desiccant solution temperature and flow rate, to minimize the energy usage in the dehumidifier. Experimental studies on an actual system are carried out to compare energy consumption between the proposed optimization and the conventional strategies. The results demonstrate that energy consumption using the proposed optimization strategy can be reduced by 12.2% in the dehumidifier operation. - Highlights: • Present a model-based optimization strategy for energy saving in LDDS. • Energy predictive models for components in dehumidifier are developed. • The Optimization strategy are applied and tested in an actual LDDS. • Optimization strategy can achieve energy savings by 12% during operation

  12. A Discrete Fracture Network Model with Stress-Driven Nucleation and Growth

    Science.gov (United States)

    Lavoine, E.; Darcel, C.; Munier, R.; Davy, P.

    2017-12-01

    The realism of Discrete Fracture Network (DFN) models, beyond the bulk statistical properties, relies on the spatial organization of fractures, which is not issued by purely stochastic DFN models. The realism can be improved by injecting prior information in DFN from a better knowledge of the geological fracturing processes. We first develop a model using simple kinematic rules for mimicking the growth of fractures from nucleation to arrest, in order to evaluate the consequences of the DFN structure on the network connectivity and flow properties. The model generates fracture networks with power-law scaling distributions and a percentage of T-intersections that are consistent with field observations. Nevertheless, a larger complexity relying on the spatial variability of natural fractures positions cannot be explained by the random nucleation process. We propose to introduce a stress-driven nucleation in the timewise process of this kinematic model to study the correlations between nucleation, growth and existing fracture patterns. The method uses the stress field generated by existing fractures and remote stress as an input for a Monte-Carlo sampling of nuclei centers at each time step. Networks so generated are found to have correlations over a large range of scales, with a correlation dimension that varies with time and with the function that relates the nucleation probability to stress. A sensibility analysis of input parameters has been performed in 3D to quantify the influence of fractures and remote stress field orientations.

  13. Tracer kinetic model-driven registration for dynamic contrast-enhanced MRI time-series data.

    Science.gov (United States)

    Buonaccorsi, Giovanni A; O'Connor, James P B; Caunce, Angela; Roberts, Caleb; Cheung, Sue; Watson, Yvonne; Davies, Karen; Hope, Lynn; Jackson, Alan; Jayson, Gordon C; Parker, Geoffrey J M

    2007-11-01

    Dynamic contrast-enhanced MRI (DCE-MRI) time series data are subject to unavoidable physiological motion during acquisition (e.g., due to breathing) and this motion causes significant errors when fitting tracer kinetic models to the data, particularly with voxel-by-voxel fitting approaches. Motion correction is problematic, as contrast enhancement introduces new features into postcontrast images and conventional registration similarity measures cannot fully account for the increased image information content. A methodology is presented for tracer kinetic model-driven registration that addresses these problems by explicitly including a model of contrast enhancement in the registration process. The iterative registration procedure is focused on a tumor volume of interest (VOI), employing a three-dimensional (3D) translational transformation that follows only tumor motion. The implementation accurately removes motion corruption in a DCE-MRI software phantom and it is able to reduce model fitting errors and improve localization in 3D parameter maps in patient data sets that were selected for significant motion problems. Sufficient improvement was observed in the modeling results to salvage clinical trial DCE-MRI data sets that would otherwise have to be rejected due to motion corruption. Copyright 2007 Wiley-Liss, Inc.

  14. A perspective on bridging scales and design of models using low-dimensional manifolds and data-driven model inference

    KAUST Repository

    Tegner, Jesper; Zenil, Hector; Kiani, Narsis A.; Ball, Gordon; Gomez-Cabrero, David

    2016-01-01

    Systems in nature capable of collective behaviour are nonlinear, operating across several scales. Yet our ability to account for their collective dynamics differs in physics, chemistry and biology. Here, we briefly review the similarities and differences between mathematical modelling of adaptive living systems versus physico-chemical systems. We find that physics-based chemistry modelling and computational neuroscience have a shared interest in developing techniques for model reductions aiming at the identification of a reduced subsystem or slow manifold, capturing the effective dynamics. By contrast, as relations and kinetics between biological molecules are less characterized, current quantitative analysis under the umbrella of bioinformatics focuses on signal extraction, correlation, regression and machine-learning analysis. We argue that model reduction analysis and the ensuing identification of manifolds bridges physics and biology. Furthermore, modelling living systems presents deep challenges as how to reconcile rich molecular data with inherent modelling uncertainties (formalism, variables selection and model parameters). We anticipate a new generative data-driven modelling paradigm constrained by identified governing principles extracted from low-dimensional manifold analysis. The rise of a new generation of models will ultimately connect biology to quantitative mechanistic descriptions, thereby setting the stage for investigating the character of the model language and principles driving living systems.

  15. A perspective on bridging scales and design of models using low-dimensional manifolds and data-driven model inference

    KAUST Repository

    Tegner, Jesper

    2016-10-04

    Systems in nature capable of collective behaviour are nonlinear, operating across several scales. Yet our ability to account for their collective dynamics differs in physics, chemistry and biology. Here, we briefly review the similarities and differences between mathematical modelling of adaptive living systems versus physico-chemical systems. We find that physics-based chemistry modelling and computational neuroscience have a shared interest in developing techniques for model reductions aiming at the identification of a reduced subsystem or slow manifold, capturing the effective dynamics. By contrast, as relations and kinetics between biological molecules are less characterized, current quantitative analysis under the umbrella of bioinformatics focuses on signal extraction, correlation, regression and machine-learning analysis. We argue that model reduction analysis and the ensuing identification of manifolds bridges physics and biology. Furthermore, modelling living systems presents deep challenges as how to reconcile rich molecular data with inherent modelling uncertainties (formalism, variables selection and model parameters). We anticipate a new generative data-driven modelling paradigm constrained by identified governing principles extracted from low-dimensional manifold analysis. The rise of a new generation of models will ultimately connect biology to quantitative mechanistic descriptions, thereby setting the stage for investigating the character of the model language and principles driving living systems.

  16. Geophysical monitoring and reactive transport modeling of ureolytically-driven calcium carbonate precipitation

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Y.; Ajo-Franklin, J.B.; Spycher, N.; Hubbard, S.S.; Zhang, G.; Williams, K.H.; Taylor, J.; Fujita, Y.; Smith, R.

    2011-07-15

    Ureolytically-driven calcium carbonate precipitation is the basis for a promising in-situ remediation method for sequestration of divalent radionuclide and trace metal ions. It has also been proposed for use in geotechnical engineering for soil strengthening applications. Monitoring the occurrence, spatial distribution, and temporal evolution of calcium carbonate precipitation in the subsurface is critical for evaluating the performance of this technology and for developing the predictive models needed for engineering application. In this study, we conducted laboratory column experiments using natural sediment and groundwater to evaluate the utility of geophysical (complex resistivity and seismic) sensing methods, dynamic synchrotron x-ray computed tomography (micro-CT), and reactive transport modeling for tracking ureolytically-driven calcium carbonate precipitation processes under site relevant conditions. Reactive transport modeling with TOUGHREACT successfully simulated the changes of the major chemical components during urea hydrolysis. Even at the relatively low level of urea hydrolysis observed in the experiments, the simulations predicted an enhanced calcium carbonate precipitation rate that was 3-4 times greater than the baseline level. Reactive transport modeling results, geophysical monitoring data and micro-CT imaging correlated well with reaction processes validated by geochemical data. In particular, increases in ionic strength of the pore fluid during urea hydrolysis predicted by geochemical modeling were successfully captured by electrical conductivity measurements and confirmed by geochemical data. The low level of urea hydrolysis and calcium carbonate precipitation suggested by the model and geochemical data was corroborated by minor changes in seismic P-wave velocity measurements and micro-CT imaging; the latter provided direct evidence of sparsely distributed calcium carbonate precipitation. Ion exchange processes promoted through NH{sub 4}{sup

  17. A 3D steady-state model of a tendon-driven continuum soft manipulator inspired by the octopus arm

    International Nuclear Information System (INIS)

    Renda, F; Cianchetti, M; Giorelli, M; Arienti, A; Laschi, C

    2012-01-01

    Control and modelling of continuum robots are challenging tasks for robotic researchers. Most works on modelling are limited to piecewise constant curvature. In many cases they neglect to model the actuators or avoid a continuum approach. In particular, in the latter case this leads to a complex model hardly implemented. In this work, a geometrically exact steady-state model of a tendon-driven manipulator inspired by the octopus arm is presented. It takes a continuum approach, fast enough to be implemented in the control law, and includes a model of the actuation system. The model was experimentally validated and the results are reported. In conclusion, the model presented can be used as a tool for mechanical design of continuum tendon-driven manipulators, for planning control strategies or as internal model in an embedded system. (paper)

  18. A Model-Driven Visualization Tool for Use with Model-Based Systems Engineering Projects

    Science.gov (United States)

    Trase, Kathryn; Fink, Eric

    2014-01-01

    Model-Based Systems Engineering (MBSE) promotes increased consistency between a system's design and its design documentation through the use of an object-oriented system model. The creation of this system model facilitates data presentation by providing a mechanism from which information can be extracted by automated manipulation of model content. Existing MBSE tools enable model creation, but are often too complex for the unfamiliar model viewer to easily use. These tools do not yet provide many opportunities for easing into the development and use of a system model when system design documentation already exists. This study creates a Systems Modeling Language (SysML) Document Traceability Framework (SDTF) for integrating design documentation with a system model, and develops an Interactive Visualization Engine for SysML Tools (InVEST), that exports consistent, clear, and concise views of SysML model data. These exported views are each meaningful to a variety of project stakeholders with differing subjects of concern and depth of technical involvement. InVEST allows a model user to generate multiple views and reports from a MBSE model, including wiki pages and interactive visualizations of data. System data can also be filtered to present only the information relevant to the particular stakeholder, resulting in a view that is both consistent with the larger system model and other model views. Viewing the relationships between system artifacts and documentation, and filtering through data to see specialized views improves the value of the system as a whole, as data becomes information

  19. Model-driven design using IEC 61499 a synchronous approach for embedded and automation systems

    CERN Document Server

    Yoong, Li Hsien; Bhatti, Zeeshan E; Kuo, Matthew M Y

    2015-01-01

    This book describes a novel approach for the design of embedded systems and industrial automation systems, using a unified model-driven approach that is applicable in both domains.  The authors illustrate their methodology, using the IEC 61499 standard as the main vehicle for specification, verification, static timing analysis and automated code synthesis.  The well-known synchronous approach is used as the main vehicle for defining an unambiguous semantics that ensures determinism and deadlock freedom. The proposed approach also ensures very efficient implementations either on small-scale embedded devices or on industry-scale programmable automation controllers (PACs). It can be used for both centralized and distributed implementations. Significantly, the proposed approach can be used without the need for any run-time support. This approach, for the first time, blurs the gap between embedded systems and automation systems and can be applied in wide-ranging applications in automotive, robotics, and industri...

  20. 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.

  1. A model-driven approach for representing clinical archetypes for Semantic Web environments.

    Science.gov (United States)

    Martínez-Costa, Catalina; Menárguez-Tortosa, Marcos; Fernández-Breis, Jesualdo Tomás; Maldonado, José Alberto

    2009-02-01

    The life-long clinical information of any person supported by electronic means configures his Electronic Health Record (EHR). This information is usually distributed among several independent and heterogeneous systems that may be syntactically or semantically incompatible. There are currently different standards for representing and exchanging EHR information among different systems. In advanced EHR approaches, clinical information is represented by means of archetypes. Most of these approaches use the Archetype Definition Language (ADL) to specify archetypes. However, ADL has some drawbacks when attempting to perform semantic activities in Semantic Web environments. In this work, Semantic Web technologies are used to specify clinical archetypes for advanced EHR architectures. The advantages of using the Ontology Web Language (OWL) instead of ADL are described and discussed in this work. Moreover, a solution combining Semantic Web and Model-driven Engineering technologies is proposed to transform ADL into OWL for the CEN EN13606 EHR architecture.

  2. Particle-in-cell modeling of the nanosecond field emission driven discharge in pressurized hydrogen

    Science.gov (United States)

    Levko, Dmitry; Yatom, Shurik; Krasik, Yakov E.

    2018-02-01

    The high-voltage field-emission driven nanosecond discharge in pressurized hydrogen is studied using the one-dimensional Particle-in-Cell Monte Carlo collision model. It is obtained that the main part of the field-emitted electrons becomes runaway in the thin cathode sheath. These runaway electrons propagate the entire cathode-anode gap, creating rather dense (˜1012 cm-3) seeding plasma electrons. In addition, these electrons initiate a streamer propagating through this background plasma with a speed ˜30% of the speed of light. Such a high streamer speed allows the self-acceleration mechanism of runaway electrons present between the streamer head and the anode to be realized. As a consequence, the energy of runaway electrons exceeds the cathode-anode gap voltage. In addition, the influence of the field emission switching-off time is analyzed. It is obtained that this time significantly influences the discharge dynamics.

  3. Climate-driven ichthyoplankton drift model predicts growth of top predator young.

    Science.gov (United States)

    Myksvoll, Mari S; Erikstad, Kjell E; Barrett, Robert T; Sandvik, Hanno; Vikebø, Frode

    2013-01-01

    Climate variability influences seabird population dynamics in several ways including access to prey near colonies during the critical chick-rearing period. This study addresses breeding success in a Barents Sea colony of common guillemots Uria aalge where trophic conditions vary according to changes in the northward transport of warm Atlantic Water. A drift model was used to simulate interannual variations in transport of cod Gadus morhua larvae along the Norwegian coast towards their nursery grounds in the Barents Sea. The results showed that the arrival of cod larvae from southern spawning grounds had a major effect on the size of common guillemot chicks at fledging. Furthermore, the fraction of larvae from the south was positively correlated to the inflow of Atlantic Water into the Barents Sea thus clearly demonstrating the mechanisms by which climate-driven bottom-up processes influence interannual variations in reproductive success in a marine top predator.

  4. Climate-driven ichthyoplankton drift model predicts growth of top predator young.

    Directory of Open Access Journals (Sweden)

    Mari S Myksvoll

    Full Text Available Climate variability influences seabird population dynamics in several ways including access to prey near colonies during the critical chick-rearing period. This study addresses breeding success in a Barents Sea colony of common guillemots Uria aalge where trophic conditions vary according to changes in the northward transport of warm Atlantic Water. A drift model was used to simulate interannual variations in transport of cod Gadus morhua larvae along the Norwegian coast towards their nursery grounds in the Barents Sea. The results showed that the arrival of cod larvae from southern spawning grounds had a major effect on the size of common guillemot chicks at fledging. Furthermore, the fraction of larvae from the south was positively correlated to the inflow of Atlantic Water into the Barents Sea thus clearly demonstrating the mechanisms by which climate-driven bottom-up processes influence interannual variations in reproductive success in a marine top predator.

  5. Machine learning based cloud mask algorithm driven by radiative transfer modeling

    Science.gov (United States)

    Chen, N.; Li, W.; Tanikawa, T.; Hori, M.; Shimada, R.; Stamnes, K. H.

    2017-12-01

    Cloud detection is a critically important first step required to derive many satellite data products. Traditional threshold based cloud mask algorithms require a complicated design process and fine tuning for each sensor, and have difficulty over snow/ice covered areas. With the advance of computational power and machine learning techniques, we have developed a new algorithm based on a neural network classifier driven by extensive radiative transfer modeling. Statistical validation results obtained by using collocated CALIOP and MODIS data show that its performance is consistent over different ecosystems and significantly better than the MODIS Cloud Mask (MOD35 C6) during the winter seasons over mid-latitude snow covered areas. Simulations using a reduced number of satellite channels also show satisfactory results, indicating its flexibility to be configured for different sensors.

  6. USACM Thematic Workshop On Uncertainty Quantification And Data-Driven Modeling.

    Energy Technology Data Exchange (ETDEWEB)

    Stewart, James R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-05-01

    The USACM Thematic Workshop on Uncertainty Quantification and Data-Driven Modeling was held on March 23-24, 2017, in Austin, TX. The organizers of the technical program were James R. Stewart of Sandia National Laboratories and Krishna Garikipati of University of Michigan. The administrative organizer was Ruth Hengst, who serves as Program Coordinator for the USACM. The organization of this workshop was coordinated through the USACM Technical Thrust Area on Uncertainty Quantification and Probabilistic Analysis. The workshop website (http://uqpm2017.usacm.org) includes the presentation agenda as well as links to several of the presentation slides (permission to access the presentations was granted by each of those speakers, respectively). Herein, this final report contains the complete workshop program that includes the presentation agenda, the presentation abstracts, and the list of posters.

  7. Input variable selection for data-driven models of Coriolis flowmeters for two-phase flow measurement

    International Nuclear Information System (INIS)

    Wang, Lijuan; Yan, Yong; Wang, Xue; Wang, Tao

    2017-01-01

    Input variable selection is an essential step in the development of data-driven models for environmental, biological and industrial applications. Through input variable selection to eliminate the irrelevant or redundant variables, a suitable subset of variables is identified as the input of a model. Meanwhile, through input variable selection the complexity of the model structure is simplified and the computational efficiency is improved. This paper describes the procedures of the input variable selection for the data-driven models for the measurement of liquid mass flowrate and gas volume fraction under two-phase flow conditions using Coriolis flowmeters. Three advanced input variable selection methods, including partial mutual information (PMI), genetic algorithm-artificial neural network (GA-ANN) and tree-based iterative input selection (IIS) are applied in this study. Typical data-driven models incorporating support vector machine (SVM) are established individually based on the input candidates resulting from the selection methods. The validity of the selection outcomes is assessed through an output performance comparison of the SVM based data-driven models and sensitivity analysis. The validation and analysis results suggest that the input variables selected from the PMI algorithm provide more effective information for the models to measure liquid mass flowrate while the IIS algorithm provides a fewer but more effective variables for the models to predict gas volume fraction. (paper)

  8. A Conceptual Systems Model to Facilitate Hypothesis-driven Ecotoxicogenomics Research on the Teleost Brain-pituitary-gonadal Axis

    Science.gov (United States)

    This provides an overview of a novel open-source conceptuial model of molecular and biochemical pathways involved in the regulation of fish reproduction. Further, it provides concrete examples of how such models can be used to design and conduct hypothesis-driven "omics" experim...

  9. The enhanced local pressure model for the accurate analysis of fluid pressure driven fracture in porous materials

    NARCIS (Netherlands)

    Remij, E.W.; Remmers, J.J.C.; Huyghe, J.M.R.J.; Smeulders, D.M.J.

    2015-01-01

    In this paper, we present an enhanced local pressure model for modelling fluid pressure driven fractures in porous saturated materials. Using the partition-of-unity property of finite element shape functions, we describe the displacement and pressure fields across the fracture as a strong

  10. Impact, runoff and drying of wind-driven rain on a window glass surface: numerical modelling based on experimental validation

    NARCIS (Netherlands)

    Blocken, B.J.E.; Carmeliet, J.E.

    2015-01-01

    This paper presents a combination of two models to study both the impingement and the contact and surface phenomena of rainwater on a glass window surface: a Computational Fluid Dynamics (CFD) model for the calculation of the distribution of the wind-driven rain (WDR) across the building facade and

  11. Old Faithful Model for Radiolytic Gas-Driven Cryovolcanism at Enceladus

    Science.gov (United States)

    Cooper, John F.; Cooper, Paul D.; Sittler, Edward; Sturner, Steven J.; Rymer, Abigail M.

    2009-01-01

    A new model is presented on how chemically driven cryovolcanism might contribute to episodic outgassing at the icy moon Enceladus and potentially elsewhere including Europa and Kuiper Belt Objects. Exposed water ices can become oxidized from radiolytic chemical alteration of near-surface water ice by space environment irradiation. In contact with primordially abundant reductants such as NH3, CH4, and other hydrocarbons, the product oxidants can react exothermically to produce volatile gases driving cryovolcanism via gas-piston forces on any subsurface liquid reservoirs. Radiolytic oxidants such as H2O2 and O2 can continuously accumulate deep in icy regoliths and be conveyed by rheological flows to subsurface chemical reaction zones over million-year time scales indicated by cratering ages for active regions of Enceladus and Europa. Surface blanketing with cryovolcanic plume ejecta would further accelerate regolith burial of radiolytic oxidants. Episodic heating from transient gravitational tides, radioisotope decay, impacts, or other geologic events might occasionally accelerate chemical reaction rates and ignite the exothermic release of cumulative radiolytic oxidant energy. The time history for the suggested "Old Faithful" model of radiolytic gas-driven cryovolcanism at Enceladus and elsewhere therefore consists of long periods of chemical energy accumulation punctuated by much briefer episodes of cryovolcanic activity. The most probable sequence for detection of activity in the current epoch is a long evolutionary phase of slow but continuous oxidant accumulation over billions of years followed by continuous but variable high activity over the past 10(exp 7)-10(exp 8) years. Detectable cryovolcanic activity could then later decline due to near-total oxidation of the rheologically accessible ice crust and depletion the accessible reductant abundances, as may have already occurred for Europa in the more intense radiation environment of Jupiter's magnetosphere

  12. Data-driven models of dominantly-inherited Alzheimer's disease progression.

    Science.gov (United States)

    Oxtoby, Neil P; Young, Alexandra L; Cash, David M; Benzinger, Tammie L S; Fagan, Anne M; Morris, John C; Bateman, Randall J; Fox, Nick C; Schott, Jonathan M; Alexander, Daniel C

    2018-03-22

    Dominantly-inherited Alzheimer's disease is widely hoped to hold the key to developing interventions for sporadic late onset Alzheimer's disease. We use emerging techniques in generative data-driven disease progression modelling to characterize dominantly-inherited Alzheimer's disease progression with unprecedented resolution, and without relying upon familial estimates of years until symptom onset. We retrospectively analysed biomarker data from the sixth data freeze of the Dominantly Inherited Alzheimer Network observational study, including measures of amyloid proteins and neurofibrillary tangles in the brain, regional brain volumes and cortical thicknesses, brain glucose hypometabolism, and cognitive performance from the Mini-Mental State Examination (all adjusted for age, years of education, sex, and head size, as appropriate). Data included 338 participants with known mutation status (211 mutation carriers in three subtypes: 163 PSEN1, 17 PSEN2, and 31 APP) and a baseline visit (age 19-66; up to four visits each, 1.1 ± 1.9 years in duration; spanning 30 years before, to 21 years after, parental age of symptom onset). We used an event-based model to estimate sequences of biomarker changes from baseline data across disease subtypes (mutation groups), and a differential equation model to estimate biomarker trajectories from longitudinal data (up to 66 mutation carriers, all subtypes combined). The two models concur that biomarker abnormality proceeds as follows: amyloid deposition in cortical then subcortical regions (∼24 ± 11 years before onset); phosphorylated tau (17 ± 8 years), tau and amyloid-β changes in cerebrospinal fluid; neurodegeneration first in the putamen and nucleus accumbens (up to 6 ± 2 years); then cognitive decline (7 ± 6 years), cerebral hypometabolism (4 ± 4 years), and further regional neurodegeneration. Our models predicted symptom onset more accurately than predictions that used familial estimates: root mean squared error of 1

  13. How realistic are air quality hindcasts driven by forcings from climate model simulations?

    Science.gov (United States)

    Lacressonnière, G.; Peuch, V.-H.; Arteta, J.; Josse, B.; Joly, M.; Marécal, V.; Saint Martin, D.; Déqué, M.; Watson, L.

    2012-12-01

    Predicting how European air quality could evolve over the next decades in the context of changing climate requires the use of climate models to produce results that can be averaged in a climatologically and statistically sound manner. This is a very different approach from the one that is generally used for air quality hindcasts for the present period; analysed meteorological fields are used to represent specifically each date and hour. Differences arise both from the fact that a climate model run results in a pure model output, with no influence from observations (which are useful to correct for a range of errors), and that in a "climate" set-up, simulations on a given day, month or even season cannot be related to any specific period of time (but can just be interpreted in a climatological sense). Hence, although an air quality model can be thoroughly validated in a "realistic" set-up using analysed meteorological fields, the question remains of how far its outputs can be interpreted in a "climate" set-up. For this purpose, we focus on Europe and on the current decade using three 5-yr simulations performed with the multiscale chemistry-transport model MOCAGE and use meteorological forcings either from operational meteorological analyses or from climate simulations. We investigate how statistical skill indicators compare in the different simulations, discriminating also the effects of meteorology on atmospheric fields (winds, temperature, humidity, pressure, etc.) and on the dependent emissions and deposition processes (volatile organic compound emissions, deposition velocities, etc.). Our results show in particular how differing boundary layer heights and deposition velocities affect horizontal and vertical distributions of species. When the model is driven by operational analyses, the simulation accurately reproduces the observed values of O3, NOx, SO2 and, with some bias that can be explained by the set-up, PM10. We study how the simulations driven by climate

  14. Experimental investigation of the predictive capabilities of data driven modeling techniques in hydrology - Part 2: Application

    Directory of Open Access Journals (Sweden)

    A. Elshorbagy

    2010-10-01

    Full Text Available In this second part of the two-part paper, the data driven modeling (DDM experiment, presented and explained in the first part, is implemented. Inputs for the five case studies (half-hourly actual evapotranspiration, daily peat soil moisture, daily till soil moisture, and two daily rainfall-runoff datasets are identified, either based on previous studies or using the mutual information content. Twelve groups (realizations were randomly generated from each dataset by randomly sampling without replacement from the original dataset. Neural networks (ANNs, genetic programming (GP, evolutionary polynomial regression (EPR, Support vector machines (SVM, M5 model trees (M5, K-nearest neighbors (K-nn, and multiple linear regression (MLR techniques are implemented and applied to each of the 12 realizations of each case study. The predictive accuracy and uncertainties of the various techniques are assessed using multiple average overall error measures, scatter plots, frequency distribution of model residuals, and the deterioration rate of prediction performance during the testing phase. Gamma test is used as a guide to assist in selecting the appropriate modeling technique. Unlike two nonlinear soil moisture case studies, the results of the experiment conducted in this research study show that ANNs were a sub-optimal choice for the actual evapotranspiration and the two rainfall-runoff case studies. GP is the most successful technique due to its ability to adapt the model complexity to the modeled data. EPR performance could be close to GP with datasets that are more linear than nonlinear. SVM is sensitive to the kernel choice and if appropriately selected, the performance of SVM can improve. M5 performs very well with linear and semi linear data, which cover wide range of hydrological situations. In highly nonlinear case studies, ANNs, K-nn, and GP could be more successful than other modeling techniques. K-nn is also successful in linear situations, and it

  15. Experimental investigation of the predictive capabilities of data driven modeling techniques in hydrology - Part 2: Application

    Science.gov (United States)

    Elshorbagy, A.; Corzo, G.; Srinivasulu, S.; Solomatine, D. P.

    2010-10-01

    In this second part of the two-part paper, the data driven modeling (DDM) experiment, presented and explained in the first part, is implemented. Inputs for the five case studies (half-hourly actual evapotranspiration, daily peat soil moisture, daily till soil moisture, and two daily rainfall-runoff datasets) are identified, either based on previous studies or using the mutual information content. Twelve groups (realizations) were randomly generated from each dataset by randomly sampling without replacement from the original dataset. Neural networks (ANNs), genetic programming (GP), evolutionary polynomial regression (EPR), Support vector machines (SVM), M5 model trees (M5), K-nearest neighbors (K-nn), and multiple linear regression (MLR) techniques are implemented and applied to each of the 12 realizations of each case study. The predictive accuracy and uncertainties of the various techniques are assessed using multiple average overall error measures, scatter plots, frequency distribution of model residuals, and the deterioration rate of prediction performance during the testing phase. Gamma test is used as a guide to assist in selecting the appropriate modeling technique. Unlike two nonlinear soil moisture case studies, the results of the experiment conducted in this research study show that ANNs were a sub-optimal choice for the actual evapotranspiration and the two rainfall-runoff case studies. GP is the most successful technique due to its ability to adapt the model complexity to the modeled data. EPR performance could be close to GP with datasets that are more linear than nonlinear. SVM is sensitive to the kernel choice and if appropriately selected, the performance of SVM can improve. M5 performs very well with linear and semi linear data, which cover wide range of hydrological situations. In highly nonlinear case studies, ANNs, K-nn, and GP could be more successful than other modeling techniques. K-nn is also successful in linear situations, and it should

  16. Business Value of Information Technology Service Quality Based on Probabilistic Business-Driven Model

    Directory of Open Access Journals (Sweden)

    Jaka Sembiring

    2015-08-01

    Full Text Available The business value of information technology (IT services is often difficult to assess, especially from the point of view of a non-IT manager. This condition could severely impact organizational IT strategic decisions. Various approaches have been proposed to quantify the business value, but some are trapped in technical complexity while others misguide managers into directly and subjectively judging some technical entities outside their domain of expertise. This paper describes a method on how to properly capture both perspectives based on a  probabilistic business-driven model. The proposed model presents a procedure to calculate the business value of IT services. The model also covers IT security services and their business value as an important aspect of IT services that is not covered in previously published researches. The impact of changes in the quality of IT services on business value will also be discussed. A simulation and a case illustration are provided to show the possible application of the proposed model for a simple business process in an enterprise.

  17. A self-organized criticality model for ion temperature gradient mode driven turbulence in confined plasma

    Science.gov (United States)

    Isliker, H.; Pisokas, Th.; Strintzi, D.; Vlahos, L.

    2010-08-01

    A new self-organized criticality (SOC) model is introduced in the form of a cellular automaton (CA) for ion temperature gradient (ITG) mode driven turbulence in fusion plasmas. Main characteristics of the model are that it is constructed in terms of the actual physical variable, the ion temperature, and that the temporal evolution of the CA, which necessarily is in the form of rules, mimics actual physical processes as they are considered to be active in the system, i.e., a heating process and a local diffusive process that sets on if a threshold in the normalized ITG R /LT is exceeded. The model reaches the SOC state and yields ion temperature profiles of exponential shape, which exhibit very high stiffness, in that they basically are independent of the loading pattern applied. This implies that there is anomalous heat transport present in the system, despite the fact that diffusion at the local level is imposed to be of a normal kind. The distributions of the heat fluxes in the system and of the heat out-fluxes are of power-law shape. The basic properties of the model are in good qualitative agreement with experimental results.

  18. A self-organized criticality model for ion temperature gradient mode driven turbulence in confined plasma

    International Nuclear Information System (INIS)

    Isliker, H.; Pisokas, Th.; Vlahos, L.; Strintzi, D.

    2010-01-01

    A new self-organized criticality (SOC) model is introduced in the form of a cellular automaton (CA) for ion temperature gradient (ITG) mode driven turbulence in fusion plasmas. Main characteristics of the model are that it is constructed in terms of the actual physical variable, the ion temperature, and that the temporal evolution of the CA, which necessarily is in the form of rules, mimics actual physical processes as they are considered to be active in the system, i.e., a heating process and a local diffusive process that sets on if a threshold in the normalized ITG R/L T is exceeded. The model reaches the SOC state and yields ion temperature profiles of exponential shape, which exhibit very high stiffness, in that they basically are independent of the loading pattern applied. This implies that there is anomalous heat transport present in the system, despite the fact that diffusion at the local level is imposed to be of a normal kind. The distributions of the heat fluxes in the system and of the heat out-fluxes are of power-law shape. The basic properties of the model are in good qualitative agreement with experimental results.

  19. A stress driven growth model for soft tissue considering biological availability

    International Nuclear Information System (INIS)

    Oller, S; Bellomo, F J; Nallim, L G; Armero, F

    2010-01-01

    Some of the key factors that regulate growth and remodeling of tissues are fundamentally mechanical. However, it is important to take into account the role of bioavailability together with the stresses and strains in the processes of normal or pathological growth. In this sense, the model presented in this work is oriented to describe the growth of soft biological tissue under 'stress driven growth' and depending on the biological availability of the organism. The general theoretical framework is given by a kinematic formulation in large strain combined with the thermodynamic basis of open systems. The formulation uses a multiplicative decomposition of deformation gradient, splitting it in a growth part and visco-elastic part. The strains due to growth are incompatible and are controlled by an unbalanced stresses related to a homeostatic state. Growth implies a volume change with an increase of mass maintaining constant the density. One of the most interesting features of the proposed model is the generation of new tissue taking into account the contribution of mass to the system controlled through biological availability. Because soft biological tissues in general have a hierarchical structure with several components (usually a soft matrix reinforced with collagen fibers), the developed growth model is suitable for the characterization of the growth of each component. This allows considering a different behavior for each of them in the context of a generalized theory of mixtures. Finally, we illustrate the response of the model in case of growth and atrophy with an application example.

  20. Quantum model for a periodically driven selectivity filter in a K+ ion channel

    International Nuclear Information System (INIS)

    Cifuentes, A A; Semião, F L

    2014-01-01

    In this work, we present a quantum transport model for the selectivity filter in the KcsA potassium ion channel. This model is fully consistent with the fact that two conduction pathways are involved in the translocation of ions through the filter, and we show that the presence of a second path may actually bring advantages for the filter as a result of quantum interference. To highlight interferences and resonances in the model, we consider the selectivity filter to be driven by a controlled time-dependent external field, which changes the free-energy scenario and consequently the conduction of the ions. In particular, we demonstrate that the two-pathway conduction mechanism is more advantageous for the filter when dephasing in the transient configurations is lower than in the main configurations. As a matter of fact, K + ions in the main configurations are highly coordinated by oxygen atoms of the filter backbone, and this increases noise. Moreover, we also show that for a wide range of dephasing rates and driving frequencies, the two-pathway conduction used by the filter leads to higher ionic currents than the single–path model. (paper)

  1. Gravity-driven groundwater flow and slope failure potential: 1. Elastic effective-stress model

    Science.gov (United States)

    Iverson, Richard M.; Reid, Mark E.

    1992-01-01

    Hilly or mountainous topography influences gravity-driven groundwater flow and the consequent distribution of effective stress in shallow subsurface environments. Effective stress, in turn, influences the potential for slope failure. To evaluate these influences, we formulate a two-dimensional, steady state, poroelastic model. The governing equations incorporate groundwater effects as body forces, and they demonstrate that spatially uniform pore pressure changes do not influence effective stresses. We implement the model using two finite element codes. As an illustrative case, we calculate the groundwater flow field, total body force field, and effective stress field in a straight, homogeneous hillslope. The total body force and effective stress fields show that groundwater flow can influence shear stresses as well as effective normal stresses. In most parts of the hillslope, groundwater flow significantly increases the Coulomb failure potential Φ, which we define as the ratio of maximum shear stress to mean effective normal stress. Groundwater flow also shifts the locus of greatest failure potential toward the slope toe. However, the effects of groundwater flow on failure potential are less pronounced than might be anticipated on the basis of a simpler, one-dimensional, limit equilibrium analysis. This is a consequence of continuity, compatibility, and boundary constraints on the two-dimensional flow and stress fields, and it points to important differences between our elastic continuum model and limit equilibrium models commonly used to assess slope stability.

  2. Modeling of strongly heat-driven flow in partially saturated fractured porous media

    International Nuclear Information System (INIS)

    Pruess, K.; Tsang, Y.W.; Wang, J.S.Y.

    1985-01-01

    The authors have performed modeling studies on the simultaneous transport of heat, liquid water, vapor, and air in partially saturated fractured porous media, with particular emphasis on strongly heat-driven flow. The presence of fractures makes the transport problem very complex, both in terms of flow geometry and physics. The numerical simulator used for their flow calculations takes into account most of the physical effects which are important in multi-phase fluid and heat flow. It has provisions to handle the extreme non-linearities which arise in phase transitions, component disappearances, and capillary discontinuities at fracture faces. They model a region around an infinite linear string of nuclear waste canisters, taking into account both the discrete fractures and the porous matrix. From an analysis of the results obtained with explicit fractures, they develop equivalent continuum models which can reproduce the temperature, saturation, and pressure variation, and gas and liquid flow rates of the discrete fracture-porous matrix calculations. The equivalent continuum approach makes use of a generalized relative permeability concept to take into account the fracture effects. This results in a substantial simplification of the flow problem which makes larger scale modeling of complicated unsaturated fractured porous systems feasible. Potential applications for regional scale simulations and limitations of the continuum approach are discussed. 27 references, 13 figures, 2 tables

  3. A Hamiltonian driven quantum-like model for overdistribution in episodic memory recollection.

    Science.gov (United States)

    Broekaert, Jan B.; Busemeyer, Jerome R.

    2017-06-01

    While people famously forget genuine memories over time, they also tend to mistakenly over-recall equivalent memories concerning a given event. The memory phenomenon is known by the name of episodic overdistribution and occurs both in memories of disjunctions and partitions of mutually exclusive events and has been tested, modeled and documented in the literature. The total classical probability of recalling exclusive sub-events most often exceeds the probability of recalling the composed event, i.e. a subadditive total. We present a Hamiltonian driven propagation for the Quantum Episodic Memory model developed by Brainerd (et al., 2015) for the episodic memory overdistribution in the experimental immediate item false memory paradigm (Brainerd and Reyna, 2008, 2010, 2015). Following the Hamiltonian method of Busemeyer and Bruza (2012) our model adds time-evolution of the perceived memory state through the stages of the experimental process based on psychologically interpretable parameters - γ_c for recollection capability of cues, κ_p for bias or description-dependence by probes and β for the average gist component in the memory state at start. With seven parameters the Hamiltonian model shows good accuracy of predictions both in the EOD-disjunction and in the EOD-subadditivity paradigm. We noticed either an outspoken preponderance of the gist over verbatim trace, or the opposite, in the initial memory state when β is real. Only for complex β a mix of both traces is present in the initial state for the EOD-subadditivity paradigm.

  4. Modeling and simulations of radiative blast wave driven Rayleigh-Taylor instability experiments

    Science.gov (United States)

    Shimony, Assaf; Huntington, Channing M.; Trantham, Matthew; Malamud, Guy; Elbaz, Yonatan; Kuranz, Carolyn C.; Drake, R. Paul; Shvarts, Dov

    2017-10-01

    Recent experiments at the National Ignition Facility measured the growth of Rayleigh-Taylor RT instabilities driven by radiative blast waves, relevant to astrophysics and other HEDP systems. We constructed a new Buoyancy-Drag (BD) model, which accounts for the ablation effect on both bubble and spike. This ablation effect is accounted for by using the potential flow model ]Oron et al PoP 1998], adding another term to the classical BD formalism: βDuA / u , where β the Takabe constant, D the drag term, uA the ablation velocity and uthe instability growth velocity. The model results are compared with the results of experiments and 2D simulations using the CRASH code, with nominal radiation or reduced foam opacity (by a factor of 1000). The ablation constant of the model, βb / s, for the bubble and for the spike fronts, are calibrated using the results of the radiative shock experiments. This work is funded by the Lawrence Livermore National Laboratory under subcontract B614207, and was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract No. DE-AC52-07NA27344.

  5. Exploring a model-driven architecture (MDA) approach to health care information systems development.

    Science.gov (United States)

    Raghupathi, Wullianallur; Umar, Amjad

    2008-05-01

    To explore the potential of the model-driven architecture (MDA) in health care information systems development. An MDA is conceptualized and developed for a health clinic system to track patient information. A prototype of the MDA is implemented using an advanced MDA tool. The UML provides the underlying modeling support in the form of the class diagram. The PIM to PSM transformation rules are applied to generate the prototype application from the model. The result of the research is a complete MDA methodology to developing health care information systems. Additional insights gained include development of transformation rules and documentation of the challenges in the application of MDA to health care. Design guidelines for future MDA applications are described. The model has the potential for generalizability. The overall approach supports limited interoperability and portability. The research demonstrates the applicability of the MDA approach to health care information systems development. When properly implemented, it has the potential to overcome the challenges of platform (vendor) dependency, lack of open standards, interoperability, portability, scalability, and the high cost of implementation.

  6. The social structure of ''experimental'' strings at Fermilab; a physics and detector driven model

    International Nuclear Information System (INIS)

    Bodnarczuk, M.

    1990-01-01

    Physicists in HEP have been forced to organize large scientific projects without a well defined organizational or sociological model to guide them. In the absence of such models, what structures do experimentalists use to develop social structures in HEP? In this paper, I claim that physicists organize around what they know best, the physics problems they study and the detectors and devices they study them with. After describing the advent of ''management'' in HEP, I use a case study of 4 Fermilab experiments as the base upon which to propose a physics and detector driven model of social structure for experiments. In addition, I show how this model can be extended to describe ''strings'' of experiments, where continuities of physics interests, spectrometer design, and a core group of physicists become a definable sociological unit that can exist for over 15 years. A dominate theme that emerges from my analysis is the conscious attempt on the part of experimenters to remove the uncertainties that are part of the practice of HEP

  7. Modeling of strongly heat-driven flow in partially saturated fractured porous media

    International Nuclear Information System (INIS)

    Pruess, K.; Tsang, Y.W.; Wang, J.S.Y.

    1984-10-01

    We have performed modeling studies on the simultaneous transport of heat, liquid water, vapor, and air in partially saturated fractured porous media, with particular emphasis on strongly heat-driven flow. The presence of fractures makes the transport problem very complex, both in terms of flow geometry and physics. The numerical simulator used for our flow calculations takes into account most of the physical effects which are important in multi-phase fluid and heat flow. It has provisions to handle the extreme non-linearities which arise in phase transitions, component disappearances, and capillary discontinuities at fracture faces. We model a region around an infinite linear string of nuclear waste canisters, taking into account both the discrete fractures and the porous matrix. From an analysis of the results obtained with explicit fractures, we develop equivalent continuum models which can reproduce the temperature, saturation, and pressure variation, and gas and liquid flow rates of the discrete fracture-porous matrix calculations. The equivalent continuum approach makes use of a generalized relative permeability concept to take into account for fracture effects. This results in a substantial simplification of the flow problem which makes larger scale modeling of complicated unsaturated fractured porous systems feasible. Potential applications for regional scale simulations and limitations of the continuum approach are discussed. 27 references, 13 figures, 2 tables

  8. A non-linear dimension reduction methodology for generating data-driven stochastic input models

    Science.gov (United States)

    Ganapathysubramanian, Baskar; Zabaras, Nicholas

    2008-06-01

    Stochastic analysis of random heterogeneous media (polycrystalline materials, porous media, functionally graded materials) provides information of significance only if realistic input models of the topology and property variations are used. This paper proposes a framework to construct such input stochastic models for the topology and thermal diffusivity variations in heterogeneous media using a data-driven strategy. Given a set of microstructure realizations (input samples) generated from given statistical information about the medium topology, the framework constructs a reduced-order stochastic representation of the thermal diffusivity. This problem of constructing a low-dimensional stochastic representation of property variations is analogous to the problem of manifold learning and parametric fitting of hyper-surfaces encountered in image processing and psychology. Denote by M the set of microstructures that satisfy the given experimental statistics. A non-linear dimension reduction strategy is utilized to map M to a low-dimensional region, A. We first show that M is a compact manifold embedded in a high-dimensional input space Rn. An isometric mapping F from M to a low-dimensional, compact, connected set A⊂Rd(d≪n) is constructed. Given only a finite set of samples of the data, the methodology uses arguments from graph theory and differential geometry to construct the isometric transformation F:M→A. Asymptotic convergence of the representation of M by A is shown. This mapping F serves as an accurate, low-dimensional, data-driven representation of the property variations. The reduced-order model of the material topology and thermal diffusivity variations is subsequently used as an input in the solution of stochastic partial differential equations that describe the evolution of dependant variables. A sparse grid collocation strategy (Smolyak algorithm) is utilized to solve these stochastic equations efficiently. We showcase the methodology by constructing low

  9. Diffusion tensor magnetic resonance imaging driven growth modeling for radiotherapy target definition in glioblastoma.

    Science.gov (United States)

    Jensen, Morten B; Guldberg, Trine L; Harbøll, Anja; Lukacova, Slávka; Kallehauge, Jesper F

    2017-11-01

    The clinical target volume (CTV) in radiotherapy is routinely based on gadolinium contrast enhanced T1 weighted (T1w + Gd) and T2 weighted fluid attenuated inversion recovery (T2w FLAIR) magnetic resonance imaging (MRI) sequences which have been shown to over- or underestimate the microscopic tumor cell spread. Gliomas favor spread along the white matter fiber tracts. Tumor growth models incorporating the MRI diffusion tensors (DTI) allow to account more consistently for the glioma growth. The aim of the study was to investigate the potential of a DTI driven growth model to improve target definition in glioblastoma (GBM). Eleven GBM patients were scanned using T1w, T2w FLAIR, T1w + Gd and DTI. The brain was segmented into white matter, gray matter and cerebrospinal fluid. The Fisher-Kolmogorov growth model was used assuming uniform proliferation and a difference in white and gray matter diffusion of a ratio of 10. The tensor directionality was tested using an anisotropy weighting parameter set to zero (γ0) and twenty (γ20). The volumetric comparison was performed using Hausdorff distance, Dice similarity coefficient (DSC) and surface area. The median of the standard CTV (CTVstandard) was 180 cm 3 . The median surface area of CTVstandard was 211 cm 2 . The median surface area of respective CTV γ0 and CTV γ20 significantly increased to 338 and 376 cm 2 , respectively. The Hausdorff distance was greater than zero and significantly increased for both CTV γ0 and CTV γ20 with respective median of 18.7 and 25.2 mm. The DSC for both CTV γ0 and CTV γ20 were significantly below one with respective median of 0.74 and 0.72, which means that 74 and 72% of CTVstandard were included in CTV γ0 and CTV γ20, respectively. DTI driven growth models result in CTVs with a significantly increased surface area, a significantly increased Hausdorff distance and decreased overlap between the standard and model derived volume.

  10. A non-linear dimension reduction methodology for generating data-driven stochastic input models

    International Nuclear Information System (INIS)

    Ganapathysubramanian, Baskar; Zabaras, Nicholas

    2008-01-01

    Stochastic analysis of random heterogeneous media (polycrystalline materials, porous media, functionally graded materials) provides information of significance only if realistic input models of the topology and property variations are used. This paper proposes a framework to construct such input stochastic models for the topology and thermal diffusivity variations in heterogeneous media using a data-driven strategy. Given a set of microstructure realizations (input samples) generated from given statistical information about the medium topology, the framework constructs a reduced-order stochastic representation of the thermal diffusivity. This problem of constructing a low-dimensional stochastic representation of property variations is analogous to the problem of manifold learning and parametric fitting of hyper-surfaces encountered in image processing and psychology. Denote by M the set of microstructures that satisfy the given experimental statistics. A non-linear dimension reduction strategy is utilized to map M to a low-dimensional region, A. We first show that M is a compact manifold embedded in a high-dimensional input space R n . An isometric mapping F from M to a low-dimensional, compact, connected set A is contained in R d (d<< n) is constructed. Given only a finite set of samples of the data, the methodology uses arguments from graph theory and differential geometry to construct the isometric transformation F:M→A. Asymptotic convergence of the representation of M by A is shown. This mapping F serves as an accurate, low-dimensional, data-driven representation of the property variations. The reduced-order model of the material topology and thermal diffusivity variations is subsequently used as an input in the solution of stochastic partial differential equations that describe the evolution of dependant variables. A sparse grid collocation strategy (Smolyak algorithm) is utilized to solve these stochastic equations efficiently. We showcase the methodology

  11. Large-Scale Modelling of the Environmentally-Driven Population Dynamics of Temperate Aedes albopictus (Skuse.

    Directory of Open Access Journals (Sweden)

    Kamil Erguler

    Full Text Available The Asian tiger mosquito, Aedes albopictus, is a highly invasive vector species. It is a proven vector of dengue and chikungunya viruses, with the potential to host a further 24 arboviruses. It has recently expanded its geographical range, threatening many countries in the Middle East, Mediterranean, Europe and North America. Here, we investigate the theoretical limitations of its range expansion by developing an environmentally-driven mathematical model of its population dynamics. We focus on the temperate strain of Ae. albopictus and compile a comprehensive literature-based database of physiological parameters. As a novel approach, we link its population dynamics to globally-available environmental datasets by performing inference on all parameters. We adopt a Bayesian approach using experimental data as prior knowledge and the surveillance dataset of Emilia-Romagna, Italy, as evidence. The model accounts for temperature, precipitation, human population density and photoperiod as the main environmental drivers, and, in addition, incorporates the mechanism of diapause and a simple breeding site model. The model demonstrates high predictive skill over the reference region and beyond, confirming most of the current reports of vector presence in Europe. One of the main hypotheses derived from the model is the survival of Ae. albopictus populations through harsh winter conditions. The model, constrained by the environmental datasets, requires that either diapausing eggs or adult vectors have increased cold resistance. The model also suggests that temperature and photoperiod control diapause initiation and termination differentially. We demonstrate that it is possible to account for unobserved properties and constraints, such as differences between laboratory and field conditions, to derive reliable inferences on the environmental dependence of Ae. albopictus populations.

  12. 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).

  13. 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.

  14. Probing the dynamics of identified neurons with a data-driven modeling approach.

    Directory of Open Access Journals (Sweden)

    Thomas Nowotny

    2008-07-01

    Full Text Available In controlling animal behavior the nervous system has to perform within the operational limits set by the requirements of each specific behavior. The implications for the corresponding range of suitable network, single neuron, and ion channel properties have remained elusive. In this article we approach the question of how well-constrained properties of neuronal systems may be on the neuronal level. We used large data sets of the activity of isolated invertebrate identified cells and built an accurate conductance-based model for this cell type using customized automated parameter estimation techniques. By direct inspection of the data we found that the variability of the neurons is larger when they are isolated from the circuit than when in the intact system. Furthermore, the responses of the neurons to perturbations appear to be more consistent than their autonomous behavior under stationary conditions. In the developed model, the constraints on different parameters that enforce appropriate model dynamics vary widely from some very tightly controlled parameters to others that are almost arbitrary. The model also allows predictions for the effect of blocking selected ionic currents and to prove that the origin of irregular dynamics in the neuron model is proper chaoticity and that this chaoticity is typical in an appropriate sense. Our results indicate that data driven models are useful tools for the in-depth analysis of neuronal dynamics. The better consistency of responses to perturbations, in the real neurons as well as in the model, suggests a paradigm shift away from measuring autonomous dynamics alone towards protocols of controlled perturbations. Our predictions for the impact of channel blockers on the neuronal dynamics and the proof of chaoticity underscore the wide scope of our approach.

  15. A predictive estimation method for carbon dioxide transport by data-driven modeling with a physically-based data model.

    Science.gov (United States)

    Jeong, Jina; Park, Eungyu; Han, Weon Shik; Kim, Kue-Young; Jun, Seong-Chun; Choung, Sungwook; Yun, Seong-Taek; Oh, Junho; Kim, Hyun-Jun

    2017-11-01

    In this study, a data-driven method for predicting CO 2 leaks and associated concentrations from geological CO 2 sequestration is developed. Several candidate models are compared based on their reproducibility and predictive capability for CO 2 concentration measurements from the Environment Impact Evaluation Test (EIT) site in Korea. Based on the data mining results, a one-dimensional solution of the advective-dispersive equation for steady flow (i.e., Ogata-Banks solution) is found to be most representative for the test data, and this model is adopted as the data model for the developed method. In the validation step, the method is applied to estimate future CO 2 concentrations with the reference estimation by the Ogata-Banks solution, where a part of earlier data is used as the training dataset. From the analysis, it is found that the ensemble mean of multiple estimations based on the developed method shows high prediction accuracy relative to the reference estimation. In addition, the majority of the data to be predicted are included in the proposed quantile interval, which suggests adequate representation of the uncertainty by the developed method. Therefore, the incorporation of a reasonable physically-based data model enhances the prediction capability of the data-driven model. The proposed method is not confined to estimations of CO 2 concentration and may be applied to various real-time monitoring data from subsurface sites to develop automated control, management or decision-making systems. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. Implementation, Comparison and Application of an Average Simulation Model of a Wind Turbine Driven Doubly Fed Induction Generator

    Directory of Open Access Journals (Sweden)

    Lidula N. Widanagama Arachchige

    2017-10-01

    Full Text Available Wind turbine driven doubly-fed induction generators (DFIGs are widely used in the wind power industry. With the increasing penetration of wind farms, analysis of their effect on power systems has become a critical requirement. This paper presents the modeling of wind turbine driven DFIGs using the conventional vector controls in a detailed model of a DFIG that represents power electronics (PE converters with device level models and proposes an average model eliminating the PE converters. The PSCAD/EMTDC™ (4.6 electromagnetic transient simulation software is used to develop the detailed and the proposing average model of a DFIG. The comparison of the two models reveals that the designed average DFIG model is adequate for simulating and analyzing most of the transient conditions.

  17. A mathematical model for IL-6-mediated, stem cell driven tumor growth and targeted treatment

    Science.gov (United States)

    Nör, Jacques Eduardo

    2018-01-01

    Targeting key regulators of the cancer stem cell phenotype to overcome their critical influence on tumor growth is a promising new strategy for cancer treatment. Here we present a modeling framework that operates at both the cellular and molecular levels, for investigating IL-6 mediated, cancer stem cell driven tumor growth and targeted treatment with anti-IL6 antibodies. Our immediate goal is to quantify the influence of IL-6 on cancer stem cell self-renewal and survival, and to characterize the subsequent impact on tumor growth dynamics. By including the molecular details of IL-6 binding, we are able to quantify the temporal changes in fractional occupancies of bound receptors and their influence on tumor volume. There is a strong correlation between the model output and experimental data for primary tumor xenografts. We also used the model to predict tumor response to administration of the humanized IL-6R monoclonal antibody, tocilizumab (TCZ), and we found that as little as 1mg/kg of TCZ administered weekly for 7 weeks is sufficient to result in tumor reduction and a sustained deceleration of tumor growth. PMID:29351275

  18. PRAGMATICS DRIVEN LAND COVER SERVICE COMPOSITION UTILIZING BEHAVIOR-INTENTION MODEL

    Directory of Open Access Journals (Sweden)

    H. Wu

    2016-06-01

    Full Text Available Web service composition is one of the key issues to develop a global land cover (GLC information service portal. Aiming at the defect that traditional syntax and semantic service compositionare difficult to take pragmatic information into account, the paper firstly analyses three tiers of web service language and their succession relations, discusses the conceptual model of pragmatic web service, and proposes the idea of pragmatics-oriented adaptive composition method based on the analysis of some examples. On this basis it puts forward the pragmatic web service model based on Behavior-Intention through presetting and expression of service usability, users' intention, and other pragmatic information, develops the on-demand assembly method based on the agent theory and matching and reconstruction method on heterogeneous message, solves the key technological issue of algorithm applicability and heterogeneous message transformation in the process of covering web service composition on the ground, applies these methods into service combination, puts forward the pragmatic driven service composition method based on behavior-intention model, and effectively settles the issue of coordination and interaction of composite service invocation.

  19. Modeling X-ray Absorbers in AGNs with MHD-Driven Accretion-Disk Winds

    Science.gov (United States)

    Fukumura, Keigo; Kazanas, D.; Shrader, C. R.; Tombesi, F.; Contopoulos, J.; Behar, E.

    2013-04-01

    We have proposed a systematic view of the observed X-ray absorbers, namely warm absorbers (WAs) in soft X-ray and highly-ionized ultra-fast outflows (UFOs), in the context of magnetically-driven accretion-disk wind models. While potentially complicated by variability and thermal instability in these energetic outflows, in this simplistic model we have calculated 2D kinematic field as well as density and ionization structure of the wind with density profile of 1/r corresponding to a constant column distribution per decade of ionization parameter. In particular we show semi-analytically that the inner layer of the disk-wind manifests itself as the strongly-ionized fast outflows while the outer layer is identified as the moderately-ionized absorbers. The computed characteristics of these two apparently distinct absorbers are consistent with X-ray data (i.e. a factor of ~100 difference in column and ionization parameters as well as low wind velocity vs. near-relativistic flow). With the predicted contour curves for these wind parameters one can constrain allowed regions for the presence of WAs and UFOs.The model further implies that the UFO's gas pressure is comparable to that of the observed radio jet in 3C111 suggesting that the magnetized disk-wind with density profile of 1/r is a viable agent to help sustain such a self-collimated jet at small radii.

  20. A Model-Driven Co-Design Framework for Fusing Control and Scheduling Viewpoints.

    Science.gov (United States)

    Sundharam, Sakthivel Manikandan; Navet, Nicolas; Altmeyer, Sebastian; Havet, Lionel

    2018-02-20

    Model-Driven Engineering (MDE) is widely applied in the industry to develop new software functions and integrate them into the existing run-time environment of a Cyber-Physical System (CPS). The design of a software component involves designers from various viewpoints such as control theory, software engineering, safety, etc. In practice, while a designer from one discipline focuses on the core aspects of his field (for instance, a control engineer concentrates on designing a stable controller), he neglects or considers less importantly the other engineering aspects (for instance, real-time software engineering or energy efficiency). This may cause some of the functional and non-functional requirements not to be met satisfactorily. In this work, we present a co-design framework based on timing tolerance contract to address such design gaps between control and real-time software engineering. The framework consists of three steps: controller design, verified by jitter margin analysis along with co-simulation, software design verified by a novel schedulability analysis, and the run-time verification by monitoring the execution of the models on target. This framework builds on CPAL (Cyber-Physical Action Language), an MDE design environment based on model-interpretation, which enforces a timing-realistic behavior in simulation through timing and scheduling annotations. The application of our framework is exemplified in the design of an automotive cruise control system.

  1. A Model-driven Role-based Access Control for SQL Databases

    Directory of Open Access Journals (Sweden)

    Raimundas Matulevičius

    2015-07-01

    Full Text Available Nowadays security has become an important aspect in information systems engineering. A mainstream method for information system security is Role-based Access Control (RBAC, which restricts system access to authorised users. While the benefits of RBAC are widely acknowledged, the implementation and administration of RBAC policies remains a human intensive activity, typically postponed until the implementation and maintenance phases of system development. This deferred security engineering approach makes it difficult for security requirements to be accurately captured and for the system’s implementation to be kept aligned with these requirements as the system evolves. In this paper we propose a model-driven approach to manage SQL database access under the RBAC paradigm. The starting point of the approach is an RBAC model captured in SecureUML. This model is automatically translated to Oracle Database views and instead-of triggers code, which implements the security constraints. The approach has been fully instrumented as a prototype and its effectiveness has been validated by means of a case study.

  2. The "Village" model: a consumer-driven approach for aging in place.

    Science.gov (United States)

    Scharlach, Andrew; Graham, Carrie; Lehning, Amanda

    2012-06-01

    This study examines the characteristics of the "Village" model, an innovative consumer-driven approach that aims to promote aging in place through a combination of member supports, service referrals, and consumer engagement. Thirty of 42 fully operational Villages completed 2 surveys. One survey examined Villages' member characteristics, membership types, and fee structures. An additional survey collected information about organizational mission, goals, methods of operation, funding sources, challenges, and older adults' roles. Villages provide a variety of support services designed to help members age in place, meet service needs, and promote health and quality of life. Most Villages operate relatively autonomously, relying primarily on member fees and donations. Village members typically are highly involved in organizational development and oversight and provide services to other members in almost half of the Villages. Members predominantly are aged 65 years or older, White, non-Hispanic, homeowners, and have care needs that are slightly lower than those of the elderly U.S. population overall. Villages are a promising model for addressing service needs among middle-class seniors who seek to age in their own homes and communities. Financial sustainability is apt to be a challenge unless Villages secure more stable sources of funding. Organizational sustainability may be promoted through affiliations with social service agencies and other sources of technical and financial assistance. Future evaluation is needed regarding the impact of Villages on elders' ability to age in place as well as the long-term sustainability of the Village model.

  3. A Model-Driven Co-Design Framework for Fusing Control and Scheduling Viewpoints

    Science.gov (United States)

    Navet, Nicolas; Havet, Lionel

    2018-01-01

    Model-Driven Engineering (MDE) is widely applied in the industry to develop new software functions and integrate them into the existing run-time environment of a Cyber-Physical System (CPS). The design of a software component involves designers from various viewpoints such as control theory, software engineering, safety, etc. In practice, while a designer from one discipline focuses on the core aspects of his field (for instance, a control engineer concentrates on designing a stable controller), he neglects or considers less importantly the other engineering aspects (for instance, real-time software engineering or energy efficiency). This may cause some of the functional and non-functional requirements not to be met satisfactorily. In this work, we present a co-design framework based on timing tolerance contract to address such design gaps between control and real-time software engineering. The framework consists of three steps: controller design, verified by jitter margin analysis along with co-simulation, software design verified by a novel schedulability analysis, and the run-time verification by monitoring the execution of the models on target. This framework builds on CPAL (Cyber-Physical Action Language), an MDE design environment based on model-interpretation, which enforces a timing-realistic behavior in simulation through timing and scheduling annotations. The application of our framework is exemplified in the design of an automotive cruise control system. PMID:29461489

  4. A Model-Driven Co-Design Framework for Fusing Control and Scheduling Viewpoints

    Directory of Open Access Journals (Sweden)

    Sakthivel Manikandan Sundharam

    2018-02-01

    Full Text Available Model-Driven Engineering (MDE is widely applied in the industry to develop new software functions and integrate them into the existing run-time environment of a Cyber-Physical System (CPS. The design of a software component involves designers from various viewpoints such as control theory, software engineering, safety, etc. In practice, while a designer from one discipline focuses on the core aspects of his field (for instance, a control engineer concentrates on designing a stable controller, he neglects or considers less importantly the other engineering aspects (for instance, real-time software engineering or energy efficiency. This may cause some of the functional and non-functional requirements not to be met satisfactorily. In this work, we present a co-design framework based on timing tolerance contract to address such design gaps between control and real-time software engineering. The framework consists of three steps: controller design, verified by jitter margin analysis along with co-simulation, software design verified by a novel schedulability analysis, and the run-time verification by monitoring the execution of the models on target. This framework builds on CPAL (Cyber-Physical Action Language, an MDE design environment based on model-interpretation, which enforces a timing-realistic behavior in simulation through timing and scheduling annotations. The application of our framework is exemplified in the design of an automotive cruise control system.

  5. Disparity-driven vs blur-driven models of accommodation and convergence in binocular vision and intermittent strabismus.

    Science.gov (United States)

    Horwood, Anna M; Riddell, Patricia M

    2014-12-01

    To propose an alternative and practical model to conceptualize clinical patterns of concomitant intermittent strabismus, heterophoria, and convergence and accommodation anomalies. Despite identical ratios, there can be a disparity- or blur-biased "style" in three hypothetical scenarios: normal; high ratio of accommodative convergence to accommodation (AC/A) and low ratio of convergence accommodation to convergence (CA/C); low AC/A and high CA/C. We calculated disparity bias indices (DBI) to reflect these biases and provide early objective data from small illustrative clinical groups that fit these styles. Normal adults (n = 56) and children (n = 24) showed disparity bias (adult DBI 0.43 [95% CI, 0.50-0.36], child DBI 0.20 [95% CI, 0.31-0.07]; P = 0.001). Accommodative esotropia (n = 3) showed less disparity-bias (DBI 0.03). In the high AC/A-low CA/C scenario, early presbyopia (n = 22) showed mean DBI of 0.17 (95% CI, 0.28-0.06), compared to DBI of -0.31 in convergence excess esotropia (n=8). In the low AC/A-high CA/C scenario near exotropia (n = 17) showed mean DBI of 0.27. DBI ranged between 1.25 and -1.67. Establishing disparity or blur bias adds to AC/A and CA/C ratios to explain clinical patterns. Excessive bias or inflexibility in near-cue use increases risk of clinical problems. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

  6. Electrostatic models of electron-driven proton transfer across a lipid membrane

    International Nuclear Information System (INIS)

    Smirnov, Anatoly Yu; Nori, Franco; Mourokh, Lev G

    2011-01-01

    We present two models for electron-driven uphill proton transport across lipid membranes, with the electron energy converted to the proton gradient via the electrostatic interaction. In the first model, associated with the cytochrome c oxidase complex in the inner mitochondria membranes, the electrostatic coupling to the site occupied by an electron lowers the energy level of the proton-binding site, making proton transfer possible. In the second model, roughly describing the redox loop in a nitrate respiration of E. coli bacteria, an electron displaces a proton from the negative side of the membrane to a shuttle, which subsequently diffuses across the membrane and unloads the proton to its positive side. We show that both models can be described by the same approach, which can be significantly simplified if the system is separated into several clusters, with strong Coulomb interaction inside each cluster and weak transfer couplings between them. We derive and solve the equations of motion for the electron and proton creation/annihilation operators, taking into account the appropriate Coulomb terms, tunnel couplings, and the interaction with the environment. For the second model, these equations of motion are solved jointly with a Langevin-type equation for the shuttle position. We obtain expressions for the electron and proton currents and determine their dependence on the electron and proton voltage build-ups, on-site charging energies, reorganization energies, temperature, and other system parameters. We show that the quantum yield in our models can be up to 100% and the power-conversion efficiency can reach 35%.

  7. Full field reservoir modeling of shale assets using advanced data-driven analytics

    Directory of Open Access Journals (Sweden)

    Soodabeh Esmaili

    2016-01-01

    Full Text Available Hydrocarbon production from shale has attracted much attention in the recent years. When applied to this prolific and hydrocarbon rich resource plays, our understanding of the complexities of the flow mechanism (sorption process and flow behavior in complex fracture systems - induced or natural leaves much to be desired. In this paper, we present and discuss a novel approach to modeling, history matching of hydrocarbon production from a Marcellus shale asset in southwestern Pennsylvania using advanced data mining, pattern recognition and machine learning technologies. In this new approach instead of imposing our understanding of the flow mechanism, the impact of multi-stage hydraulic fractures, and the production process on the reservoir model, we allow the production history, well log, completion and hydraulic fracturing data to guide our model and determine its behavior. The uniqueness of this technology is that it incorporates the so-called “hard data” directly into the reservoir model, so that the model can be used to optimize the hydraulic fracture process. The “hard data” refers to field measurements during the hydraulic fracturing process such as fluid and proppant type and amount, injection pressure and rate as well as proppant concentration. This novel approach contrasts with the current industry focus on the use of “soft data” (non-measured, interpretive data such as frac length, width, height and conductivity in the reservoir models. The study focuses on a Marcellus shale asset that includes 135 wells with multiple pads, different landing targets, well length and reservoir properties. The full field history matching process was successfully completed using this data driven approach thus capturing the production behavior with acceptable accuracy for individual wells and for the entire asset.

  8. Electrostatic models of electron-driven proton transfer across a lipid membrane

    Energy Technology Data Exchange (ETDEWEB)

    Smirnov, Anatoly Yu; Nori, Franco [Advanced Science Institute, RIKEN, Wako-shi, Saitama, 351-0198 (Japan); Mourokh, Lev G [Department of Physics, Queens College, The City University of New York, Flushing, NY 11367 (United States)

    2011-06-15

    We present two models for electron-driven uphill proton transport across lipid membranes, with the electron energy converted to the proton gradient via the electrostatic interaction. In the first model, associated with the cytochrome c oxidase complex in the inner mitochondria membranes, the electrostatic coupling to the site occupied by an electron lowers the energy level of the proton-binding site, making proton transfer possible. In the second model, roughly describing the redox loop in a nitrate respiration of E. coli bacteria, an electron displaces a proton from the negative side of the membrane to a shuttle, which subsequently diffuses across the membrane and unloads the proton to its positive side. We show that both models can be described by the same approach, which can be significantly simplified if the system is separated into several clusters, with strong Coulomb interaction inside each cluster and weak transfer couplings between them. We derive and solve the equations of motion for the electron and proton creation/annihilation operators, taking into account the appropriate Coulomb terms, tunnel couplings, and the interaction with the environment. For the second model, these equations of motion are solved jointly with a Langevin-type equation for the shuttle position. We obtain expressions for the electron and proton currents and determine their dependence on the electron and proton voltage build-ups, on-site charging energies, reorganization energies, temperature, and other system parameters. We show that the quantum yield in our models can be up to 100% and the power-conversion efficiency can reach 35%.

  9. Fine resolution atmospheric sulfate model driven by operational meteorological data: Comparison with observations

    International Nuclear Information System (INIS)

    Benkovitz, C.M.; Schwartz, S.E.; Berkowitz, C.M.; Easter, R.C.

    1993-09-01

    The hypothesis that anthropogenic sulfur aerosol influences clear-sky and cloud albedo and can thus influence climate has been advanced by several investigators; current global-average climate forcing is estimated to be of comparable magnitude, but opposite sign, to longwave forcing by anthropogenic greenhouse gases. The high space and time variability of sulfate concentrations and column aerosol burdens have been established by observational data; however, geographic and time coverage provided by data from surface monitoring networks is very limited. Consistent regional and global estimates of sulfate aerosol loading, and the contributions to this loading from different sources can be obtained only by modeling studies. Here we describe a sub-hemispheric to global-scale Eulerian transport and transformation model for atmospheric sulfate and its precursors, driven by operational meteorological data, and report results of calculations for October, 1986 for the North Atlantic and adjacent continental regions. The model, which is based on the Global Chemistry Model uses meteorological data from the 6-hour forecast model of the European Center for Medium-Range Weather Forecast to calculate transport and transformation of sulfur emissions. Time- and location-dependent dry deposition velocities were estimated using the methodology of Wesely and colleagues. Chemical reactions includes gaseous oxidation of SO 2 and DMS by OH, and aqueous oxidation of SO 2 by H 2 O 2 and O 3 . Anthropogenic emissions were from the NAPAP and EMEP 1985 inventories and biogenic emissions based on Bates et al. Calculated sulfate concentrations and column burdens exhibit high variability on spatial scale of hundreds of km and temporal scale of days. Calculated daily average sulfate concentrations closely reproduce observed concentrations at locations widespread over the model domain

  10. Agent-based Modeling Automated: Data-driven Generation of Innovation Diffusion Models

    NARCIS (Netherlands)

    Jensen, T.; Chappin, E.J.L.

    2016-01-01

    Simulation modeling is useful to gain insights into driving mechanisms of diffusion of innovations. This study aims to introduce automation to make identification of such mechanisms with agent-based simulation modeling less costly in time and labor. We present a novel automation procedure in which

  11. Quality of process modeling using BPMN: a model-driven approach

    OpenAIRE

    Correia, Anacleto Cortez e

    2014-01-01

    Dissertação para obtenção do Grau de Doutor em Engenharia Informática Context: The BPMN 2.0 specification contains the rules regarding the correct usage of the language’s constructs. Practitioners have also proposed best-practices for producing better BPMN models. However, those rules are expressed in natural language, yielding sometimes ambiguous interpretation, and therefore, flaws in produced BPMN models. Objective: Ensuring the correctness of BPMN models is critical for the au...

  12. The steady state solutions of radiatively driven stellar winds for a non-Sobolev, pure absorption model

    International Nuclear Information System (INIS)

    Poe, C.H.; Owocki, S.P.; Castor, J.I.

    1990-01-01

    The steady state solution topology for absorption line-driven flows is investigated for the condition that the Sobolev approximation is not used to compute the line force. The solution topology near the sonic point is of the nodal type with two positive slope solutions. The shallower of these slopes applies to reasonable lower boundary conditions and realistic ion thermal speed v(th) and to the Sobolev limit of zero of the usual Castor, Abbott, and Klein model. At finite v(th), this solution consists of a family of very similar solutions converging on the sonic point. It is concluded that a non-Sobolev, absorption line-driven flow with a realistic values of v(th) has no uniquely defined steady state. To the extent that a pure absorption model of the outflow of stellar winds is applicable, radiatively driven winds should be intrinsically variable. 34 refs

  13. Automatic extraction of soft tissues from 3D MRI head images using model driven analysis

    International Nuclear Information System (INIS)

    Jiang, Hao; Yamamoto, Shinji; Imao, Masanao.

    1995-01-01

    This paper presents an automatic extraction system (called TOPS-3D : Top Down Parallel Pattern Recognition System for 3D Images) of soft tissues from 3D MRI head images by using model driven analysis algorithm. As the construction of system TOPS we developed, two concepts have been considered in the design of system TOPS-3D. One is the system having a hierarchical structure of reasoning using model information in higher level, and the other is a parallel image processing structure used to extract plural candidate regions for a destination entity. The new points of system TOPS-3D are as follows. (1) The TOPS-3D is a three-dimensional image analysis system including 3D model construction and 3D image processing techniques. (2) A technique is proposed to increase connectivity between knowledge processing in higher level and image processing in lower level. The technique is realized by applying opening operation of mathematical morphology, in which a structural model function defined in higher level by knowledge representation is immediately used to the filter function of opening operation as image processing in lower level. The system TOPS-3D applied to 3D MRI head images consists of three levels. First and second levels are reasoning part, and third level is image processing part. In experiments, we applied 5 samples of 3D MRI head images with size 128 x 128 x 128 pixels to the system TOPS-3D to extract the regions of soft tissues such as cerebrum, cerebellum and brain stem. From the experimental results, the system is robust for variation of input data by using model information, and the position and shape of soft tissues are extracted corresponding to anatomical structure. (author)

  14. Model-driven approach to data collection and reporting for quality improvement.

    Science.gov (United States)

    Curcin, Vasa; Woodcock, Thomas; Poots, Alan J; Majeed, Azeem; Bell, Derek

    2014-12-01

    Continuous data collection and analysis have been shown essential to achieving improvement in healthcare. However, the data required for local improvement initiatives are often not readily available from hospital Electronic Health Record (EHR) systems or not routinely collected. Furthermore, improvement teams are often restricted in time and funding thus requiring inexpensive and rapid tools to support their work. Hence, the informatics challenge in healthcare local improvement initiatives consists of providing a mechanism for rapid modelling of the local domain by non-informatics experts, including performance metric definitions, and grounded in established improvement techniques. We investigate the feasibility of a model-driven software approach to address this challenge, whereby an improvement model designed by a team is used to automatically generate required electronic data collection instruments and reporting tools. To that goal, we have designed a generic Improvement Data Model (IDM) to capture the data items and quality measures relevant to the project, and constructed Web Improvement Support in Healthcare (WISH), a prototype tool that takes user-generated IDM models and creates a data schema, data collection web interfaces, and a set of live reports, based on Statistical Process Control (SPC) for use by improvement teams. The software has been successfully used in over 50 improvement projects, with more than 700 users. We present in detail the experiences of one of those initiatives, Chronic Obstructive Pulmonary Disease project in Northwest London hospitals. The specific challenges of improvement in healthcare are analysed and the benefits and limitations of the approach are discussed. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

  15. First steps towards modeling of ion-driven turbulence in Wendelstein 7-X

    Science.gov (United States)

    Warmer, F.; Xanthopoulos, P.; Proll, J. H. E.; Beidler, C. D.; Turkin, Y.; Wolf, R. C.

    2018-01-01

    Due to foreseen improvement of neoclassical confinement in optimised stellarators—like the newly commissioned Wendelstein 7-X (W7-X) experiment in Greifswald, Germany—it is expected that turbulence will significantly contribute to the heat and particle transport, thus posing a limit to the performance of such devices. In order to develop discharge scenarios, it is thus necessary to develop a model which could reliably capture the basic characteristics of turbulence and try to predict the levels thereof. The outcome will not only be affordable, using only a fraction of the computational cost which is normally required for repetitive direct turbulence simulations, but would also highlight important physics. In this model, we seek to describe the ion heat flux caused by ion temperature gradient (ITG) micro-turbulence, which, in certain heating scenarios, can be a strong source of free energy. With the aid of a relatively small number of state-of-the-art nonlinear gyrokinetic simulations, an initial critical gradient model (CGM) is devised, with the aim to replace an empirical model, stemming from observations in prior stellarator experiments. The novel CGM, in its present form, encapsulates all available knowledge about ion-driven 3D turbulence to date, also allowing for further important extensions, towards an accurate interpretation and prediction of the ‘anomalous’ transport. The CGM depends on the stiffness of the ITG turbulence scaling in W7-X, and implicitly includes the nonlinear zonal flow response. It is shown that the CGM is suitable for a 1D framework turbulence modeling.

  16. New trajectory-driven aerosol and chemical process model Chemical and Aerosol Lagrangian Model (CALM

    Directory of Open Access Journals (Sweden)

    P. Tunved

    2010-11-01

    Full Text Available A new Chemical and Aerosol Lagrangian Model (CALM has been developed and tested. The model incorporates all central aerosol dynamical processes, from nucleation, condensation, coagulation and deposition to cloud formation and in-cloud processing. The model is tested and evaluated against observations performed at the SMEAR II station located at Hyytiälä (61° 51' N, 24° 17' E over a time period of two years, 2000–2001. The model shows good agreement with measurements throughout most of the year, but fails in reproducing the aerosol properties during the winter season, resulting in poor agreement between model and measurements especially during December–January. Nevertheless, through the rest of the year both trends and magnitude of modal concentrations show good agreement with observation, as do the monthly average size distribution properties. The model is also shown to capture individual nucleation events to a certain degree. This indicates that nucleation largely is controlled by the availability of nucleating material (as prescribed by the [H2SO4], availability of condensing material (in this model 15% of primary reactions of monoterpenes (MT are assumed to produce low volatile species and the properties of the size distribution (more specifically, the condensation sink. This is further demonstrated by the fact that the model captures the annual trend in nuclei mode concentration. The model is also used, alongside sensitivity tests, to examine which processes dominate the aerosol size distribution physical properties. It is shown, in agreement with previous studies, that nucleation governs the number concentration during transport from clean areas. It is also shown that primary number emissions almost exclusively govern the CN concentration when air from Central Europe is advected north over Scandinavia. We also show that biogenic emissions have a large influence on the amount of potential CCN observed

  17. A computational model for knowledge-driven monitoring of nuclear power plant operators based on information theory

    International Nuclear Information System (INIS)

    Kim, Man Cheol; Seong, Poong Hyun

    2006-01-01

    To develop operator behavior models such as IDAC, quantitative models for the cognitive activities of nuclear power plant (NPP) operators in abnormal situations are essential. Among them, only few quantitative models for the monitoring and detection have been developed. In this paper, we propose a computational model for the knowledge-driven monitoring, which is also known as model-driven monitoring, of NPP operators in abnormal situations, based on the information theory. The basic assumption of the proposed model is that the probability that an operator shifts his or her attention to an information source is proportional to the expected information from the information source. A small experiment performed to evaluate the feasibility of the proposed model shows that the predictions made by the proposed model have high correlations with the experimental results. Even though it has been argued that heuristics might play an important role on human reasoning, we believe that the proposed model can provide part of the mathematical basis for developing quantitative models for knowledge-driven monitoring of NPP operators when NPP operators are assumed to behave very logically

  18. Experimental investigation of the predictive capabilities of data driven modeling techniques in hydrology - Part 1: Concepts and methodology

    Directory of Open Access Journals (Sweden)

    A. Elshorbagy

    2010-10-01

    Full Text Available A comprehensive data driven modeling experiment is presented in a two-part paper. In this first part, an extensive data-driven modeling experiment is proposed. The most important concerns regarding the way data driven modeling (DDM techniques and data were handled, compared, and evaluated, and the basis on which findings and conclusions were drawn are discussed. A concise review of key articles that presented comparisons among various DDM techniques is presented. Six DDM techniques, namely, neural networks, genetic programming, evolutionary polynomial regression, support vector machines, M5 model trees, and K-nearest neighbors are proposed and explained. Multiple linear regression and naïve models are also suggested as baseline for comparison with the various techniques. Five datasets from Canada and Europe representing evapotranspiration, upper and lower layer soil moisture content, and rainfall-runoff process are described and proposed, in the second paper, for the modeling experiment. Twelve different realizations (groups from each dataset are created by a procedure involving random sampling. Each group contains three subsets; training, cross-validation, and testing. Each modeling technique is proposed to be applied to each of the 12 groups of each dataset. This way, both prediction accuracy and uncertainty of the modeling techniques can be evaluated. The description of the datasets, the implementation of the modeling techniques, results and analysis, and the findings of the modeling experiment are deferred to the second part of this paper.

  19. A Two Species Bump-On-Tail Model With Relaxation for Energetic Particle Driven Modes

    Science.gov (United States)

    Aslanyan, V.; Porkolab, M.; Sharapov, S. E.; Spong, D. A.

    2017-10-01

    Energetic particle driven Alfvén Eigenmodes (AEs) observed in present day experiments exhibit various nonlinear behaviours varying from steady state amplitude at a fixed frequency to bursting amplitudes and sweeping frequency. Using the appropriate action-angle variables, the problem of resonant wave-particle interaction becomes effectively one-dimensional. Previously, a simple one-dimensional Bump-On-Tail (BOT) model has proven to be one of the most effective in describing characteristic nonlinear near-threshold wave evolution scenarios. In particular, dynamical friction causes bursting mode evolution, while diffusive relaxation may give steady-state, periodic or chaotic mode evolution. BOT has now been extended to include two populations of fast particles, with one dominated by dynamical friction at the resonance and the other by diffusion; the relative size of the populations determines the temporal evolution of the resulting wave. This suggests an explanation for recent observations on the TJ-II stellarator, where a transition between steady state and bursting occured as the magnetic configuration varied. The two species model is then applied to burning plasma with drag-dominated alpha particles and diffusion-dominated ICRH accelerated minority ions. This work was supported by the US DoE and the RCUK Energy Programme [Grant Number EP/P012450/1].

  20. Numerical Modelling and Simulation of Dynamic Parameters for Vibration Driven Mobile Robot: Preliminary Study

    Science.gov (United States)

    Baharudin, M. E.; Nor, A. M.; Saad, A. R. M.; Yusof, A. M.

    2018-03-01

    The motion of vibration-driven robots is based on an internal oscillating mass which can move without legs or wheels. The oscillation of the unbalanced mass by a motor is translated into vibration which in turn produces vertical and horizontal forces. Both vertical and horizontal oscillations are of the same frequency but the phases are shifted. The vertical forces will deflect the bristles which cause the robot to move forward. In this paper, the horizontal motion direction caused by the vertically vibrated bristle is numerically simulated by tuning the frequency of their oscillatory actuation. As a preliminary work, basic equations for a simple off-centered vibration location on the robot platform and simulation model for vibration excitement are introduced. It involves both static and dynamic vibration analysis of robots and analysis of different type of parameters. In addition, the orientation of the bristles and oscillators are also analysed. Results from the numerical integration seem to be in good agreement with those achieved from the literature. The presented numerical integration modeling can be used for designing the bristles and controlling the speed and direction of the robot.

  1. 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.

  2. Modeling particle emission and power flow in pulsed-power driven, nonuniform transmission lines

    Directory of Open Access Journals (Sweden)

    Nichelle Bruner

    2008-04-01

    Full Text Available Pulsed-power driven x-ray radiographic systems are being developed to operate at higher power in an effort to increase source brightness and penetration power. Essential to the design of these systems is a thorough understanding of electron power flow in the transmission line that couples the pulsed-power driver to the load. In this paper, analytic theory and fully relativistic particle-in-cell simulations are used to model power flow in several experimental transmission-line geometries fielded on Sandia National Laboratories’ upgraded Radiographic Integrated Test Stand [IEEE Trans. Plasma Sci. 28, 1653 (2000ITPSBD0093-381310.1109/27.901250]. Good agreement with measured electrical currents is demonstrated on a shot-by-shot basis for simulations which include detailed models accounting for space-charge-limited electron emission, surface heating, and stimulated particle emission. Resonant cavity modes related to the transmission-line impedance transitions are also shown to be excited by electron power flow. These modes can drive oscillations in the output power of the system, degrading radiographic resolution.

  3. A data-driven decomposition approach to model aerodynamic forces on flapping airfoils

    Science.gov (United States)

    Raiola, Marco; Discetti, Stefano; Ianiro, Andrea

    2017-11-01

    In this work, we exploit a data-driven decomposition of experimental data from a flapping airfoil experiment with the aim of isolating the main contributions to the aerodynamic force and obtaining a phenomenological model. Experiments are carried out on a NACA 0012 airfoil in forward flight with both heaving and pitching motion. Velocity measurements of the near field are carried out with Planar PIV while force measurements are performed with a load cell. The phase-averaged velocity fields are transformed into the wing-fixed reference frame, allowing for a description of the field in a domain with fixed boundaries. The decomposition of the flow field is performed by means of the POD applied on the velocity fluctuations and then extended to the phase-averaged force data by means of the Extended POD approach. This choice is justified by the simple consideration that aerodynamic forces determine the largest contributions to the energetic balance in the flow field. Only the first 6 modes have a relevant contribution to the force. A clear relationship can be drawn between the force and the flow field modes. Moreover, the force modes are closely related (yet slightly different) to the contributions of the classic potential models in literature, allowing for their correction. This work has been supported by the Spanish MINECO under Grant TRA2013-41103-P.

  4. Spatially explicit integrated modeling and economic valuation of climate driven land use change and its indirect effects.

    OpenAIRE

    Bateman, Ian; Agarwala, M.; Binner, A.; Coombes, E.; Day, B.; Ferrini, Silvia; Fezzi, C.; Hutchins, M.; Lovett, A.; Posen, P.

    2016-01-01

    We present an integrated model of the direct consequences of climate change on land use, and the indirect effects of induced land use change upon the natural environment. The model predicts climate-driven shifts in the profitability of alternative uses of agricultural land. Both the direct impact of climate change and the induced shift in land use patterns will cause secondary effects on the water environment, for which agriculture is the major source of diffuse pollution. We model the impact...

  5. A Model-Driven Approach for 3D Modeling of Pylon from Airborne LiDAR Data

    Directory of Open Access Journals (Sweden)

    Qingquan Li

    2015-09-01

    Full Text Available Reconstructing three-dimensional model of the pylon from LiDAR (Light Detection And Ranging point clouds automatically is one of the key techniques for facilities management GIS system of high-voltage nationwide transmission smart grid. This paper presents a model-driven three-dimensional pylon modeling (MD3DM method using airborne LiDAR data. We start with constructing a parametric model of pylon, based on its actual structure and the characteristics of point clouds data. In this model, a pylon is divided into three parts: pylon legs, pylon body and pylon head. The modeling approach mainly consists of four steps. Firstly, point clouds of individual pylon are detected and segmented from massive high-voltage transmission corridor point clouds automatically. Secondly, an individual pylon is divided into three relatively simple parts in order to reconstruct different parts with different strategies. Its position and direction are extracted by contour analysis of the pylon body in this stage. Thirdly, the geometric features of the pylon head are extracted, from which the head type is derived with a SVM (Support Vector Machine classifier. After that, the head is constructed by seeking corresponding model from pre-build model library. Finally, the body is modeled by fitting the point cloud to planes. Experiment results on several point clouds data sets from China Southern high-voltage nationwide transmission grid from Yunnan Province to Guangdong Province show that the proposed approach can achieve the goal of automatic three-dimensional modeling of the pylon effectively.

  6. Recent Successes of Wave/Turbulence Driven Models of Solar Wind Acceleration

    Science.gov (United States)

    Cranmer, S. R.; Hollweg, J. V.; Chandran, B. D.; van Ballegooijen, A. A.

    2010-12-01

    A key obstacle in the way of producing realistic simulations of the Sun-heliosphere system is the lack of a first-principles understanding of coronal heating. Also, it is still unknown whether the solar wind is "fed" through flux tubes that remain open (and are energized by footpoint-driven wavelike fluctuations) or if mass and energy are input intermittently from closed loops into the open-field regions. In this presentation, we discuss self-consistent models that assume the energy comes from solar Alfven waves that are partially reflected, and then dissipated, by magnetohydrodynamic turbulence. These models have been found to reproduce many of the observed features of the fast and slow solar wind without the need for artificial "coronal heating functions" used by earlier models. For example, the models predict a variation with wind speed in commonly measured ratios of charge states and elemental abundances that agrees with observed trends. This contradicts a commonly held assertion that these ratios can only be produced by the injection of plasma from closed-field regions on the Sun. This presentation also reviews two recent comparisons between the models and empirical measurements: (1) The models successfully predict the amplitude and radial dependence of Faraday rotation fluctuations (FRFs) measured by the Helios probes for heliocentric distances between 2 and 15 solar radii. The FRFs are a particularly sensitive test of turbulence models because they depend not only on the plasma density and Alfven wave amplitude in the corona, but also on the turbulent correlation length. (2) The models predict the correct sense and magnitude of changes seen in the polar high-speed solar wind by Ulysses from the previous solar minimum (1996-1997) to the more recent peculiar minimum (2008-2009). By changing only the magnetic field along the polar magnetic flux tube, consistent with solar and heliospheric observations at the two epochs, the model correctly predicts that the

  7. A recombinant lentiviral PDGF-driven mouse model of proneural glioblastoma.

    Science.gov (United States)

    Rahme, Gilbert J; Luikart, Bryan W; Cheng, Chao; Israel, Mark A

    2018-02-19

    Mouse models of glioblastoma (GBM), the most aggressive primary brain tumor, are critical for understanding GBM pathology and can contribute to the preclinical evaluation of therapeutic agents. Platelet-derived growth factor (PDGF) signaling has been implicated in the development and pathogenesis of GBM, specifically the proneural subtype. Although multiple mouse models of PDGF-driven glioma have been described, they require transgenic mice engineered to activate PDGF signaling and/or impair tumor suppressor genes and typically represent lower-grade glioma. We designed recombinant lentiviruses expressing both PDGFB and a short hairpin RNA targeting Cdkn2a to induce gliomagenesis following stereotactic injection into the dentate gyrus of adult immunocompetent mice. We engineered these viruses to coexpress CreERT2 with PDGFB, allowing for deletion of floxed genes specifically in transduced cells, and designed another version of this recombinant lentivirus in which enhanced green fluorescent protein was coexpressed with PDGFB and CreERT2 to visualize transduced cells. The dentate gyrus of injected mice showed hypercellularity one week post-injection and subsequently developed bona fide tumors with the pathologic hallmarks of GBM leading to a median survival of 77 days post-injection. Transcriptomic analysis of these tumors revealed a proneural gene expression signature. Informed by the genetic alterations observed in human GBM, we engineered a novel mouse model of proneural GBM. While reflecting many of the advantages of transgenic mice, this model allows for the facile in vivo testing of gene function in tumor cells and makes possible the rapid production of large numbers of immunocompetent tumor-bearing mice for preclinical testing of therapeutics. © The Author(s) 2017. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

  8. Generalizable occupant-driven optimization model for domestic hot water production in NZEB

    International Nuclear Information System (INIS)

    Kazmi, H.; D’Oca, S.; Delmastro, C.; Lodeweyckx, S.; Corgnati, S.P.

    2016-01-01

    Highlights: • Smart meter data for domestic hot water consumption is collected for 46 NZEB. • Reinforcement learning optimizes energy consumed while constrained on user comfort. • Online optimization models learn occupant behaviour and system thermodynamics. • Offline generalizable models calibrate dynamically the storage vessel operation. • Real world application of the active controls resulted in energy savings of 27%. - Abstract: The primary objective of this paper is to demonstrate improved energy efficiency for domestic hot water (DHW) production in residential buildings. This is done by deriving data-driven optimal heating schedules (used interchangeably with policies) automatically. The optimization leverages actively learnt occupant behaviour and models for thermodynamics of the storage vessel to operate the heating mechanism – an air-source heat pump (ASHP) in this case – at the highest possible efficiency. The proposed algorithm, while tested on an ASHP, is essentially decoupled from the heating mechanism making it sufficiently robust to generalize to other types of heating mechanisms as well. Simulation results for this optimization based on data from 46 Net-Zero Energy Buildings (NZEB) in the Netherlands are presented. These show a reduction of energy consumption for DHW by 20% using a computationally inexpensive heuristic approach, and 27% when using a more intensive hybrid ant colony optimization based method. The energy savings are strongly dependent on occupant comfort level. This is demonstrated in real-world settings for a low-consumption house where active control was performed using heuristics for 3.5 months and resulted in energy savings of 27% (61 kW h). It is straightforward to extend the same models to perform automatic demand side management (ADSM) by treating the DHW vessel as a flexibility bearing device.

  9. Modeling and Experimental Tests on the Hydraulically Driven Control Rod option for IRIS Reactor

    International Nuclear Information System (INIS)

    Cammi, Antonio; Ricotti, Marco E.; Vitulo, Alessia

    2004-01-01

    The adoption of Internal Control Rod Drive Mechanisms (ICRDMs) represents a valuable alternative to classical, external CRDMs based on electro-magnetic devices, as adopted in current PWRs. The advantages on the safety features of the reactor are apparent: inherent elimination of the Rod Ejection accidents and of possible concerns about the vessel head penetrations. A further positive feedback on the design is the reduction of the primary system overall dimensions. Within the frame of the ICRDM concepts, the Hydraulically Driven Control Rod solution is investigated as a possible option for the IRIS integral reactor. After a brief comparison of the solutions currently proposed for integral reactors, the configuration of the Hydraulic Control Rod device for IRIS, made up by an external movable piston and an internal fixed cylinder, is described. A description of the whole control system is reported as well. Particular attention is devoted to the Control Rod profile characterization, performed by means of a Computational Fluid Dynamics (CFD) analysis. The investigation of the system behavior has been carried out, including the dynamic equilibrium and its stability properties, the withdrawal and insertion step movement and the sensitivity study on command time periods. A suitable dynamic model has been set up for the mentioned purposes: the models corresponding to the various Control Rod system devices have been written in an Object-Oriented language (Modelica), thus allowing an easy implementation of such a system into the simulator for the whole reactor. Finally, a preliminary low pressure, low temperature, reduced length experimental facility has been built. Tests on HDCR stability and operational transients have been performed. The results are compared with the dynamic system model and CFD simulation model, showing good agreement between simulations and experimental data. During these preliminary tests, the control system performed correctly, allowing stable dynamic

  10. Variations in Modeled Dengue Transmission over Puerto Rico Using a Climate Driven Dynamic Model

    Science.gov (United States)

    Morin, Cory; Monaghan, Andrew; Crosson, William; Quattrochi, Dale; Luvall, Jeffrey

    2014-01-01

    Dengue fever is a mosquito-borne viral disease reemerging throughout much of the tropical Americas. Dengue virus transmission is explicitly influenced by climate and the environment through its primary vector, Aedes aegypti. Temperature regulates Ae. aegypti development, survival, and replication rates as well as the incubation period of the virus within the mosquito. Precipitation provides water for many of the preferred breeding habitats of the mosquito, including buckets, old tires, and other places water can collect. Because of variations in topography, ocean influences and atmospheric processes, temperature and rainfall patterns vary across Puerto Rico and so do dengue virus transmission rates. Using NASA's TRMM (Tropical Rainfall Measuring Mission) satellite for precipitation input, ground-based observations for temperature input, and laboratory confirmed dengue cases reported by the Centers for Disease Control and Prevention for parameter calibration, we modeled dengue transmission at the county level across Puerto Rico from 2010-2013 using a dynamic dengue transmission model that includes interacting vector ecology and epidemiological components. Employing a Monte Carlo approach, we performed ensembles of several thousands of model simulations for each county in order to resolve the model uncertainty arising from using different combinations of parameter values that are not well known. The top 1% of model simulations that best reproduced the reported dengue case data were then analyzed to determine the most important parameters for dengue virus transmission in each county, as well as the relative influence of climate variability on transmission. These results can be used by public health workers to implement dengue control methods that are targeted for specific locations and climate conditions.

  11. Data-driven reverse engineering of signaling pathways using ensembles of dynamic models.

    Directory of Open Access Journals (Sweden)

    David Henriques

    2017-02-01

    Full Text Available Despite significant efforts and remarkable progress, the inference of signaling networks from experimental data remains very challenging. The problem is particularly difficult when the objective is to obtain a dynamic model capable of predicting the effect of novel perturbations not considered during model training. The problem is ill-posed due to the nonlinear nature of these systems, the fact that only a fraction of the involved proteins and their post-translational modifications can be measured, and limitations on the technologies used for growing cells in vitro, perturbing them, and measuring their variations. As a consequence, there is a pervasive lack of identifiability. To overcome these issues, we present a methodology called SELDOM (enSEmbLe of Dynamic lOgic-based Models, which builds an ensemble of logic-based dynamic models, trains them to experimental data, and combines their individual simulations into an ensemble prediction. It also includes a model reduction step to prune spurious interactions and mitigate overfitting. SELDOM is a data-driven method, in the sense that it does not require any prior knowledge of the system: the interaction networks that act as scaffolds for the dynamic models are inferred from data using mutual information. We have tested SELDOM on a number of experimental and in silico signal transduction case-studies, including the recent HPN-DREAM breast cancer challenge. We found that its performance is highly competitive compared to state-of-the-art methods for the purpose of recovering network topology. More importantly, the utility of SELDOM goes beyond basic network inference (i.e. uncovering static interaction networks: it builds dynamic (based on ordinary differential equation models, which can be used for mechanistic interpretations and reliable dynamic predictions in new experimental conditions (i.e. not used in the training. For this task, SELDOM's ensemble prediction is not only consistently better

  12. User-driven Cloud Implementation of environmental models and data for all

    Science.gov (United States)

    Gurney, R. J.; Percy, B. J.; Elkhatib, Y.; Blair, G. S.

    2014-12-01

    Environmental data and models come from disparate sources over a variety of geographical and temporal scales with different resolutions and data standards, often including terabytes of data and model simulations. Unfortunately, these data and models tend to remain solely within the custody of the private and public organisations which create the data, and the scientists who build models and generate results. Although many models and datasets are theoretically available to others, the lack of ease of access tends to keep them out of reach of many. We have developed an intuitive web-based tool that utilises environmental models and datasets located in a cloud to produce results that are appropriate to the user. Storyboards showing the interfaces and visualisations have been created for each of several exemplars. A library of virtual machine images has been prepared to serve these exemplars. Each virtual machine image has been tailored to run computer models appropriate to the end user. Two approaches have been used; first as RESTful web services conforming to the Open Geospatial Consortium (OGC) Web Processing Service (WPS) interface standard using the Python-based PyWPS; second, a MySQL database interrogated using PHP code. In all cases, the web client sends the server an HTTP GET request to execute the process with a number of parameter values and, once execution terminates, an XML or JSON response is sent back and parsed at the client side to extract the results. All web services are stateless, i.e. application state is not maintained by the server, reducing its operational overheads and simplifying infrastructure management tasks such as load balancing and failure recovery. A hybrid cloud solution has been used with models and data sited on both private and public clouds. The storyboards have been transformed into intuitive web interfaces at the client side using HTML, CSS and JavaScript, utilising plug-ins such as jQuery and Flot (for graphics), and Google Maps

  13. Simulation modelling of central order processing system under resource sharing strategy in demand-driven garment supply chains

    Science.gov (United States)

    Ma, K.; Thomassey, S.; Zeng, X.

    2017-10-01

    In this paper we proposed a central order processing system under resource sharing strategy for demand-driven garment supply chains to increase supply chain performances. We examined this system by using simulation technology. Simulation results showed that significant improvement in various performance indicators was obtained in new collaborative model with proposed system.

  14. Using the Dynamic Model to develop an evidence-based and theory-driven approach to school improvement

    NARCIS (Netherlands)

    Creemers, B.P.M.; Kyriakides, L.

    2010-01-01

    This paper refers to a dynamic perspective of educational effectiveness and improvement stressing the importance of using an evidence-based and theory-driven approach. Specifically, an approach to school improvement based on the dynamic model of educational effectiveness is offered. The recommended

  15. Current Trends in the Detection of Sociocultural Signatures: Data-Driven Models

    Energy Technology Data Exchange (ETDEWEB)

    Sanfilippo, Antonio P.; Bell, Eric B.; Corley, Courtney D.

    2014-09-15

    available that are shaping social computing as a strongly data-driven experimental discipline with an increasingly stronger impact on the decision-making process of groups and individuals alike. In this chapter, we review current advances and trends in the detection of sociocultural signatures. Specific embodiments of the issues discussed are provided with respect to the assessment of violent intent and sociopolitical contention. We begin by reviewing current approaches to the detection of sociocultural signatures in these domains. Next, we turn to the review of novel data harvesting methods for social media content. Finally, we discuss the application of sociocultural models to social media content, and conclude by commenting on current challenges and future developments.

  16. A DATA-DRIVEN ANALYTIC MODEL FOR PROTON ACCELERATION BY LARGE-SCALE SOLAR CORONAL SHOCKS

    Energy Technology Data Exchange (ETDEWEB)

    Kozarev, Kamen A. [Smithsonian Astrophysical Observatory (United States); Schwadron, Nathan A. [Institute for the Study of Earth, Oceans, and Space, University of New Hampshire (United States)

    2016-11-10

    We have recently studied the development of an eruptive filament-driven, large-scale off-limb coronal bright front (OCBF) in the low solar corona, using remote observations from the Solar Dynamics Observatory ’s Advanced Imaging Assembly EUV telescopes. In that study, we obtained high-temporal resolution estimates of the OCBF parameters regulating the efficiency of charged particle acceleration within the theoretical framework of diffusive shock acceleration (DSA). These parameters include the time-dependent front size, speed, and strength, as well as the upstream coronal magnetic field orientations with respect to the front’s surface normal direction. Here we present an analytical particle acceleration model, specifically developed to incorporate the coronal shock/compressive front properties described above, derived from remote observations. We verify the model’s performance through a grid of idealized case runs using input parameters typical for large-scale coronal shocks, and demonstrate that the results approach the expected DSA steady-state behavior. We then apply the model to the event of 2011 May 11 using the OCBF time-dependent parameters derived by Kozarev et al. We find that the compressive front likely produced energetic particles as low as 1.3 solar radii in the corona. Comparing the modeled and observed fluences near Earth, we also find that the bulk of the acceleration during this event must have occurred above 1.5 solar radii. With this study we have taken a first step in using direct observations of shocks and compressions in the innermost corona to predict the onsets and intensities of solar energetic particle events.

  17. Towards a traceable clinical guidelines application. A model-driven approach.

    Science.gov (United States)

    Domínguez, E; Pérez, B; Zapata, M

    2010-01-01

    The goal of this research is to provide an overall framework to enable model-based development of clinical guideline-based decision support systems (GBDSSs). The automatically generated GBDSSs are aimed at providing guided support to the physician during the application of guidelines and automatically storing guideline application data for traceability purposes. The development process of a GBDSS for a guideline is based on model-driven development (MDD) techniques which allow us to carry out such a process automatically, making development more agile and saving on human resource costs. We use UML Statecharts to represent the dynamics of guidelines and, based on this model, we use a MDD-based tool chain to generate the guideline-dependent components of each GBDSS in an automatic way. In particular, as for the traceability capabilities of each GBDSS, MDD techniques are combined with database schema mappings for metadata management in order to automatically generate the GBDSS-persistent component as one of the main contributions of this paper. The complete framework has been implemented as an Eclipse plug-in named GBDSSGenerator which, starting from the statechart representing a guideline, allows the development process to be carried out automatically by only selecting different menu options the plug-in provides. We have successfully validated our overall approach by generating the GBDSS for different types of clinical guidelines, even for laboratory guidelines. The proposed framework allows the development of clinical guideline-based decision support systems in an automatic way making this process more agile and saving on human resource costs.

  18. A Model-Driven Approach for Hybrid Power Estimation in Embedded Systems Design

    Directory of Open Access Journals (Sweden)

    Ben Atitallah Rabie

    2011-01-01

    Full Text Available Abstract As technology scales for increased circuit density and performance, the management of power consumption in system-on-chip (SoC is becoming critical. Today, having the appropriate electronic system level (ESL tools for power estimation in the design flow is mandatory. The main challenge for the design of such dedicated tools is to achieve a better tradeoff between accuracy and speed. This paper presents a consumption estimation approach allowing taking the consumption criterion into account early in the design flow during the system cosimulation. The originality of this approach is that it allows the power estimation for both white-box intellectual properties (IPs using annotated power models and black-box IPs using standalone power estimators. In order to obtain accurate power estimates, our simulations were performed at the cycle-accurate bit-accurate (CABA level, using SystemC. To make our approach fast and not tedious for users, the simulated architectures, including standalone power estimators, were generated automatically using a model driven engineering (MDE approach. Both annotated power models and standalone power estimators can be used together to estimate the consumption of the same architecture, which makes them complementary. The simulation results showed that the power estimates given by both estimation techniques for a hardware component are very close, with a difference that does not exceed 0.3%. This proves that, even when the IP code is not accessible or not modifiable, our approach allows obtaining quite accurate power estimates that early in the design flow thanks to the automation offered by the MDE approach.

  19. Modelling the possible interaction between edge-driven convection and the Canary Islands mantle plume

    Science.gov (United States)

    Negredo, A. M.; Rodríguez-González, J.; Fullea, J.; Van Hunen, J.

    2017-12-01

    The close location between many hotspots and the edges of cratonic lithosphere has led to the hypothesis that these hotspots could be explained by small-scale mantle convection at the edge of cratons (Edge Driven Convection, EDC). The Canary Volcanic Province hotspot represents a paradigmatic example of this situation due to its close location to the NW edge of the African Craton. Geochemical evidence, prominent low seismic velocity anomalies in the upper and lower mantle, and the rough NE-SW age-progression of volcanic centers consistently point out to a deep-seated mantle plume as the origin of the Canary Volcanic Province. It has been hypothesized that the plume material could be affected by upper mantle convection caused by the thermal contrast between thin oceanic lithosphere and thick (cold) African craton. Deflection of upwelling blobs due to convection currents would be responsible for the broader and more irregular pattern of volcanism in the Canary Province compared to the Madeira Province. In this study we design a model setup inspired on this scenario to investigate the consequences of possible interaction between ascending mantle plumes and EDC. The Finite Element code ASPECT is used to solve convection in a 2D box. The compositional field and melt fraction distribution are also computed. Free slip along all boundaries and constant temperature at top and bottom boundaries are assumed. The initial temperature distribution assumes a small long-wavelength perturbation. The viscosity structure is based on a thick cratonic lithosphere progressively varying to a thin, or initially inexistent, oceanic lithosphere. The effects of assuming different rheologies, as well as steep or gradual changes in lithospheric thickness are tested. Modelling results show that a very thin oceanic lithosphere (models assuming temperature-dependent viscosity and large viscosity variations evolve to large-scale (upper mantle) convection cells, with upwelling of hot material being

  20. A Pathophysiological Model-Driven Communication for Dynamic Distributed Medical Best Practice Guidance Systems.

    Science.gov (United States)

    Hosseini, Mohammad; Jiang, Yu; Wu, Poliang; Berlin, Richard B; Ren, Shangping; Sha, Lui

    2016-11-01

    There is a great divide between rural and urban areas, particularly in medical emergency care. Although medical best practice guidelines exist and are in hospital handbooks, they are often lengthy and difficult to apply clinically. The challenges are exaggerated for doctors in rural areas and emergency medical technicians (EMT) during patient transport. In this paper, we propose the concept of distributed executable medical best practice guidance systems to assist adherence to best practice from the time that a patient first presents at a rural hospital, through diagnosis and ambulance transfer to arrival and treatment at a regional tertiary hospital center. We codify complex medical knowledge in the form of simplified distributed executable disease automata, from the thin automata at rural hospitals to the rich automata in the regional center hospitals. However, a main challenge is how to efficiently and safely synchronize distributed best practice models as the communication among medical facilities, devices, and professionals generates a large number of messages. This complex problem of patient diagnosis and transport from rural to center facility is also fraught with many uncertainties and changes resulting in a high degree of dynamism. A critically ill patient's medical conditions can change abruptly in addition to changes in the wireless bandwidth during the ambulance transfer. Such dynamics have yet to be addressed in existing literature on telemedicine. To address this situation, we propose a pathophysiological model-driven message exchange communication architecture that ensures the real-time and dynamic requirements of synchronization among distributed emergency best practice models are met in a reliable and safe manner. Taking the signs, symptoms, and progress of stroke patients transported across a geographically distributed healthcare network as the motivating use case, we implement our communication system and apply it to our developed best practice

  1. HIGH-FIDELITY SIMULATION-DRIVEN MODEL DEVELOPMENT FOR COARSE-GRAINED COMPUTATIONAL FLUID DYNAMICS

    Energy Technology Data Exchange (ETDEWEB)

    Hanna, Botros N.; Dinh, Nam T.; Bolotnov, Igor A.

    2016-06-01

    Nuclear reactor safety analysis requires identifying various credible accident scenarios and determining their consequences. For a full-scale nuclear power plant system behavior, it is impossible to obtain sufficient experimental data for a broad range of risk-significant accident scenarios. In single-phase flow convective problems, Direct Numerical Simulation (DNS) and Large Eddy Simulation (LES) can provide us with high fidelity results when physical data are unavailable. However, these methods are computationally expensive and cannot be afforded for simulation of long transient scenarios in nuclear accidents despite extraordinary advances in high performance scientific computing over the past decades. The major issue is the inability to make the transient computation parallel, thus making number of time steps required in high-fidelity methods unaffordable for long transients. In this work, we propose to apply a high fidelity simulation-driven approach to model sub-grid scale (SGS) effect in Coarse Grained Computational Fluid Dynamics CG-CFD. This approach aims to develop a statistical surrogate model instead of the deterministic SGS model. We chose to start with a turbulent natural convection case with volumetric heating in a horizontal fluid layer with a rigid, insulated lower boundary and isothermal (cold) upper boundary. This scenario of unstable stratification is relevant to turbulent natural convection in a molten corium pool during a severe nuclear reactor accident, as well as in containment mixing and passive cooling. The presented approach demonstrates how to create a correction for the CG-CFD solution by modifying the energy balance equation. A global correction for the temperature equation proves to achieve a significant improvement to the prediction of steady state temperature distribution through the fluid layer.

  2. The effect of ac-driven force on superlubricity in a two-dimensional Frenkel-Kontorova model

    International Nuclear Information System (INIS)

    Lin Maimai

    2010-01-01

    By using the molecular dynamic simulation method with a fourth-order Runge-Kutta algorithm, a two-dimensional dc- and ac-driven Frenkel-Kontorova model with a square symmetry substrate potential for a square lattice layer has been investigated in this paper. For this system, the effects of many different parameters on the static friction force have been studied in detail. It was found that not only the amplitude and frequency of the ac-driven force, but also the direction of dc- and ac-driven forces and the misfit angle between two layers have a strong influence on the static friction force. This indicated that the phenomenon of superlubricity appears easily with larger ac amplitude and smaller ac frequency for some special direction of the external driving force and misfit angle.

  3. 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.

  4. Econometric models for distinguishing between market-driven and publicly-funded energy efficiency

    International Nuclear Information System (INIS)

    Horowitz, Marvin J.

    2005-01-01

    Central to the problem of estimating energy program benefits is the necessity to differentiate between changes in energy use that would have occurred in the absence of public programs versus declines in energy use that would not have occurred but for public programs. The former changes are often referred to as naturally-occurring or market-driven effects. They occur due to a combination of one or more independent variables, such as changes in prices, incomes, weather, and technology. For a rigorous, scientifically-valid program evaluation, it is essential to first control for these variables before making statistical inferences related to public program effects. This paper describes the economic and statistical issues surrounding quantitative studies of energy use, energy efficiency, and public programs. To illustrate the strengths and weaknesses of different impact evaluation approaches, this paper describes three new studies related to electricity use in the U. S. commercial buildings sector. Specification and estimation of time series and cross section econometric models are discussed, as are their capabilities for obtaining long-run estimates of the net impacts of energy efficiency programs

  5. Modeling and simulations of new electrostatically driven, bimorph actuator for high beam steering micromirror deflection angles

    Science.gov (United States)

    Walton, John P.; Coutu, Ronald A.; Starman, LaVern

    2015-02-01

    There are numerous applications for micromirror arrays seen in our everyday lives. From flat screen televisions and computer monitors, found in nearly every home and office, to advanced military weapon systems and space vehicles, each application bringing with it a unique set of requirements. The microelectromechanical systems (MEMS) industry has researched many ways micromirror actuation can be accomplished and the different constraints on performance each design brings with it. This paper investigates a new "zipper" approach to electrostatically driven micromirrors with the intent of improving duel plane beam steering by coupling large deflection angles, over 30°, and a fast switching speed. To accomplish this, an extreme initial deflection is needed which can be reached using high stress bimorph beams. Currently this requires long beams and high voltage for the electrostatic pull in or slower electrothermal switching. The idea for this "zipper" approach is to stack multiple beams of a much shorter length and allow for the deflection of each beam to be added together in order to reach the required initial deflection height. This design requires much less pull-in voltage because the pull-in of one short beam will in turn reduce the height of the all subsequent beams, making it much easier to actuate. Using modeling and simulation software to characterize operations characteristics, different bimorph cantilever beam configurations are explored in order to optimize the design. These simulations show that this new "zipper" approach increases initial deflection as additional beams are added to the assembly without increasing the actuation voltage.

  6. Population reversal driven by unrestrained interactions in molecular dynamics simulations: A dialanine model

    Directory of Open Access Journals (Sweden)

    Filippo Pullara

    2015-10-01

    Full Text Available Standard Molecular Dynamics simulations (MD are usually performed under periodic boundary conditions using the well-established “Ewald summation”. This implies that the distance among each element in a given lattice cell and its corresponding element in another cell, as well as their relative orientations, are constant. Consequently, protein-protein interactions between proteins in different cells—important in many biological activities, such as protein cooperativity and physiological/pathological aggregation—are severely restricted, and features driven by protein-protein interactions are lost. The consequences of these restrictions, although conceptually understood and mentioned in the literature, have not been quantitatively studied before. The effect of protein-protein interactions on the free energy landscape of a model system, dialanine, is presented. This simple system features a free energy diagram with well-separated minima. It is found that, in the case of absence of peptide-peptide (p-p interactions, the ψ = 150° dihedral angle determines the most energetically favored conformation (global free-energy minimum. When strong p-p interactions are induced, the global minimum switches to the ψ = 0° conformation. This shows that the free-energy landscape of an individual molecule is dramatically affected by the presence of other freely interacting molecules of its same type. Results of the study suggest how taking into account p-p interactions in MD allows having a more realistic picture of system activity and functional conformations.

  7. Model of a source-driven plasma interacting with a wall in an oblique magnetic field

    International Nuclear Information System (INIS)

    Ahedo, E.; Carralero, D.

    2009-01-01

    A fluid model of a magnetized source-driven plasma is discussed for regimes with (Debye length)<<(ion Larmor radius)<<(plasma size and collisional mean-free path). Plasma collection by the wall is determined in terms of angle of incidence, magnetic strength, and plasma collisionality. For nonparallel incidence, a three-scale asymptotic analysis reveals a three-region matched structure consisting of a magnetically aligned bulk region, the Chodura layer, and the Debye sheath. Sonic Chodura and Bohm conditions define the singular region transitions. For near-parallel incidence, a separate analysis demonstrates the presence of a diffusive-collisional bulk region followed by a thin collisionless layer, which differs partially from the Chodura layer. A parametric analysis unveils the presence of four regimes depending on plasma collisionality: (1) a collisionless regime, with the magnetically channeled bulk region governed by plasma production; (2) a resistive semicollisional regime, where collisions retard the plasma transport in the bulk region; (3) a diffusive semicollisional regime, where the ExB drift dominates the ion flux in the bulk region; and (4) a collisional regime, where collisions cancel out magnetic effects. At grazing incidence, plasma collection is found to vary nonmonotonically with plasma collisionality. Nonzero Debye-length effects are discussed briefly.

  8. A one-dimensional model of the semiannual oscillation driven by convectively forced gravity waves

    Science.gov (United States)

    Sassi, Fabrizio; Garcia, Rolando R.

    1994-01-01

    A one-dimensional model that solves the time-dependent equations for the zonal mean wind and a wave of specified zonal wavenumber has been used to illustrate the ability of gravity waves forced by time-dependent tropospheric heating to produce a semiannual oscillation (SAO) in the middle atmosphere. When the heating has a strong diurnal cycle, as observed over tropical landmasses, gravity waves with zonal wavelengths of a few thousand kilometers and phase velocities in the range +/- 40-50 m/sec are excited efficiently by the maximum vertical projection criterion (vertical wavelength approximately equals 2 x forcing depth). Calculations show that these waves can account for large zonal mean wind accelerations in the middle atmosphere, resulting in realistic stratopause and mesopause oscillations. Calculations of the temporal evolution of a quasi-conserved tracer indicate strong down-welling in the upper stratosphere near the equinoxes, which is associated with the descent of the SAO westerlies. In the upper mesosphere, there is a semiannual oscillation in tracer mixing ratio driven by seasonal variability in eddy mixing, which increases at the solstices and decreases at the equinoxes.

  9. Coevolution in management fashion: an agent-based model of consultant-driven innovation.

    Science.gov (United States)

    Strang, David; David, Robert J; Akhlaghpour, Saeed

    2014-07-01

    The rise of management consultancy has been accompanied by increasingly marked faddish cycles in management techniques, but the mechanisms that underlie this relationship are not well understood. The authors develop a simple agent-based framework that models innovation adoption and abandonment on both the supply and demand sides. In opposition to conceptions of consultants as rhetorical wizards who engineer waves of management fashion, firms and consultants are treated as boundedly rational actors who chase the secrets of success by mimicking their highest-performing peers. Computational experiments demonstrate that consultant-driven versions of this dynamic in which the outcomes of firms are strongly conditioned by their choice of consultant are robustly faddish. The invasion of boom markets by low-quality consultants undercuts popular innovations while simultaneously restarting the fashion cycle by prompting the flight of high-quality consultants into less densely occupied niches. Computational experiments also indicate conditions involving consultant mobility, aspiration levels, mimic probabilities, and client-provider matching that attenuate faddishness.

  10. A transparent and data-driven global tectonic regionalization model for seismic hazard assessment

    Science.gov (United States)

    Chen, Yen-Shin; Weatherill, Graeme; Pagani, Marco; Cotton, Fabrice

    2018-05-01

    A key concept that is common to many assumptions inherent within seismic hazard assessment is that of tectonic similarity. This recognizes that certain regions of the globe may display similar geophysical characteristics, such as in the attenuation of seismic waves, the magnitude scaling properties of seismogenic sources or the seismic coupling of the lithosphere. Previous attempts at tectonic regionalization, particularly within a seismic hazard assessment context, have often been based on expert judgements; in most of these cases, the process for delineating tectonic regions is neither reproducible nor consistent from location to location. In this work, the regionalization process is implemented in a scheme that is reproducible, comprehensible from a geophysical rationale, and revisable when new relevant data are published. A spatial classification-scheme is developed based on fuzzy logic, enabling the quantification of concepts that are approximate rather than precise. Using the proposed methodology, we obtain a transparent and data-driven global tectonic regionalization model for seismic hazard applications as well as the subjective probabilities (e.g. degree of being active/degree of being cratonic) that indicate the degree to which a site belongs in a tectonic category.

  11. Computational modeling of z-pinch-driven hohlraum experiments on Z

    International Nuclear Information System (INIS)

    Vesey, R.A.; Porter, J.L. Jr.; Cuneo, M.E.

    1999-01-01

    The high-yield inertial confinement fusion concept based on a double-ended z-pinch driven hohlraum tolerates the degree of spatial inhomogeneity present in z-pinch plasma radiation sources by utilizing a relatively large hohlraum wall surface to provide spatial smoothing of the radiation delivered to the fusion capsule. The z-pinch radiation sources are separated from the capsule by radial spoke arrays. Key physics issues for this concept are the behavior of the spoke array (effect on the z-pinch performance, x-ray transmission) and the uniformity of the radiation flux incident on the surface of the capsule. Experiments are underway on the Z accelerator at Sandia National laboratories to gain understanding of these issues in a single-sided drive geometry. These experiments seek to measure the radiation coupling among the z-pinch, source hohlraum, and secondary hohlraum, as well as the uniformity of the radiation flux striking a foam witness ball diagnostic positioned in the secondary hohlraum. This paper will present the results of computational modeling of various aspects of these experiments

  12. Deep Modeling: Circuit Characterization Using Theory Based Models in a Data Driven Framework

    Energy Technology Data Exchange (ETDEWEB)

    Bolme, David S [ORNL; Mikkilineni, Aravind K [ORNL; Rose, Derek C [ORNL; Yoginath, Srikanth B [ORNL; Holleman, Jeremy [University of Tennessee, Knoxville (UTK); Judy, Mohsen [University of Tennessee, Knoxville (UTK), Department of Electrical Engineering and Computer Science

    2017-01-01

    Analog computational circuits have been demonstrated to provide substantial improvements in power and speed relative to digital circuits, especially for applications requiring extreme parallelism but only modest precision. Deep machine learning is one such area and stands to benefit greatly from analog and mixed-signal implementations. However, even at modest precisions, offsets and non-linearity can degrade system performance. Furthermore, in all but the simplest systems, it is impossible to directly measure the intermediate outputs of all sub-circuits. The result is that circuit designers are unable to accurately evaluate the non-idealities of computational circuits in-situ and are therefore unable to fully utilize measurement results to improve future designs. In this paper we present a technique to use deep learning frameworks to model physical systems. Recently developed libraries like TensorFlow make it possible to use back propagation to learn parameters in the context of modeling circuit behavior. Offsets and scaling errors can be discovered even for sub-circuits that are deeply embedded in a computational system and not directly observable. The learned parameters can be used to refine simulation methods or to identify appropriate compensation strategies. We demonstrate the framework using a mixed-signal convolution operator as an example circuit.

  13. 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

  14. 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.

  15. A musculoskeletal model of human locomotion driven by a low dimensional set of impulsive excitation primitives.

    Science.gov (United States)

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

    2013-01-01

    Human locomotion has been described as being generated by an impulsive (burst-like) excitation of groups of musculotendon units, with timing dependent on the biomechanical goal of the task. Despite this view being supported by many experimental observations on specific locomotion tasks, it is still unknown if the same impulsive controller (i.e., a low-dimensional set of time-delayed excitastion primitives) can be used as input drive for large musculoskeletal models across different human locomotion tasks. For this purpose, we extracted, with non-negative matrix factorization, five non-negative factors from a large sample of muscle electromyograms in two healthy subjects during four motor tasks. These included walking, running, sidestepping, and crossover cutting maneuvers. The extracted non-negative factors were then averaged and parameterized to obtain task-generic Gaussian-shaped impulsive excitation curves or primitives. These were used to drive a subject-specific musculoskeletal model of the human lower extremity. Results showed that the same set of five impulsive excitation primitives could be used to predict the dynamics of 34 musculotendon units and the resulting hip, knee and ankle joint moments (i.e., NRMSE = 0.18 ± 0.08, and R (2) = 0.73 ± 0.22 across all tasks and subjects) without substantial loss of accuracy with respect to using experimental electromyograms (i.e., NRMSE = 0.16 ± 0.07, and R (2) = 0.78 ± 0.18 across all tasks and subjects). Results support the hypothesis that biomechanically different motor tasks might share similar neuromuscular control strategies. This might have implications in neurorehabilitation technologies such as human-machine interfaces for the torque-driven, proportional control of powered prostheses and orthoses. In this, device control commands (i.e., predicted joint torque) could be derived without direct experimental data but relying on simple parameterized Gaussian-shaped curves, thus decreasing the input drive

  16. Data-Driven Neural Network Model for Robust Reconstruction of Automobile Casting

    Science.gov (United States)

    Lin, Jinhua; Wang, Yanjie; Li, Xin; Wang, Lu

    2017-09-01

    In computer vision system, it is a challenging task to robustly reconstruct complex 3D geometries of automobile castings. However, 3D scanning data is usually interfered by noises, the scanning resolution is low, these effects normally lead to incomplete matching and drift phenomenon. In order to solve these problems, a data-driven local geometric learning model is proposed to achieve robust reconstruction of automobile casting. In order to relieve the interference of sensor noise and to be compatible with incomplete scanning data, a 3D convolution neural network is established to match the local geometric features of automobile casting. The proposed neural network combines the geometric feature representation with the correlation metric function to robustly match the local correspondence. We use the truncated distance field(TDF) around the key point to represent the 3D surface of casting geometry, so that the model can be directly embedded into the 3D space to learn the geometric feature representation; Finally, the training labels is automatically generated for depth learning based on the existing RGB-D reconstruction algorithm, which accesses to the same global key matching descriptor. The experimental results show that the matching accuracy of our network is 92.2% for automobile castings, the closed loop rate is about 74.0% when the matching tolerance threshold τ is 0.2. The matching descriptors performed well and retained 81.6% matching accuracy at 95% closed loop. For the sparse geometric castings with initial matching failure, the 3D matching object can be reconstructed robustly by training the key descriptors. Our method performs 3D reconstruction robustly for complex automobile castings.

  17. 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.

  18. A satellite-driven, client-server hydro-economic model prototype for agricultural water management

    Science.gov (United States)

    Maneta, Marco; Kimball, John; He, Mingzhu; Payton Gardner, W.

    2017-04-01

    Anticipating agricultural water demand, land reallocation, and impact on farm revenues associated with different policy or climate constraints is a challenge for water managers and for policy makers. While current integrated decision support systems based on programming methods provide estimates of farmer reaction to external constraints, they have important shortcomings such as the high cost of data collection surveys necessary to calibrate the model, biases associated with inadequate farm sampling, infrequent model updates and recalibration, model overfitting, or their deterministic nature, among other problems. In addition, the administration of water supplies and the generation of policies that promote sustainable agricultural regions depend on more than one bureau or office. Unfortunately, managers from local and regional agencies often use different datasets of variable quality, which complicates coordinated action. To overcome these limitations, we present a client-server, integrated hydro-economic modeling and observation framework driven by satellite remote sensing and other ancillary information from regional monitoring networks. The core of the framework is a stochastic data assimilation system that sequentially ingests remote sensing observations and corrects the parameters of the hydro-economic model at unprecedented spatial and temporal resolutions. An economic model of agricultural production, based on mathematical programming, requires information on crop type and extent, crop yield, crop transpiration and irrigation technology. A regional hydro-climatologic model provides biophysical constraints to an economic model of agricultural production with a level of detail that permits the study of the spatial impact of large- and small-scale water use decisions. Crop type and extent is obtained from the Cropland Data Layer (CDL), which is multi-sensor operational classification of crops maintained by the United States Department of Agriculture. Because

  19. Framework for developing hybrid process-driven, artificial neural network and regression models for salinity prediction in river systems

    Science.gov (United States)

    Hunter, Jason M.; Maier, Holger R.; Gibbs, Matthew S.; Foale, Eloise R.; Grosvenor, Naomi A.; Harders, Nathan P.; Kikuchi-Miller, Tahali C.

    2018-05-01

    Salinity modelling in river systems is complicated by a number of processes, including in-stream salt transport and various mechanisms of saline accession that vary dynamically as a function of water level and flow, often at different temporal scales. Traditionally, salinity models in rivers have either been process- or data-driven. The primary problem with process-based models is that in many instances, not all of the underlying processes are fully understood or able to be represented mathematically. There are also often insufficient historical data to support model development. The major limitation of data-driven models, such as artificial neural networks (ANNs) in comparison, is that they provide limited system understanding and are generally not able to be used to inform management decisions targeting specific processes, as different processes are generally modelled implicitly. In order to overcome these limitations, a generic framework for developing hybrid process and data-driven models of salinity in river systems is introduced and applied in this paper. As part of the approach, the most suitable sub-models are developed for each sub-process affecting salinity at the location of interest based on consideration of model purpose, the degree of process understanding and data availability, which are then combined to form the hybrid model. The approach is applied to a 46 km reach of the Murray River in South Australia, which is affected by high levels of salinity. In this reach, the major processes affecting salinity include in-stream salt transport, accession of saline groundwater along the length of the reach and the flushing of three waterbodies in the floodplain during overbank flows of various magnitudes. Based on trade-offs between the degree of process understanding and data availability, a process-driven model is developed for in-stream salt transport, an ANN model is used to model saline groundwater accession and three linear regression models are used

  20. Evaluation of global water quality - the potential of a data- and model-driven analysis

    Science.gov (United States)

    Bärlund, Ilona; Flörke, Martina; Alcamo, Joseph; Völker, Jeanette; Malsy, Marcus; Kaus, Andrew; Reder, Klara; Büttner, Olaf; Katterfeld, Christiane; Dietrich, Désirée; Borchardt, Dietrich

    2016-04-01

    The ongoing socio-economic development presents a new challenge for water quality worldwide, especially in developing and emerging countries. It is estimated that due to population growth and the extension of water supply networks, the amount of waste water will rise sharply. This can lead to an increased risk of surface water quality degradation, if the wastewater is not sufficiently treated. This development has impacts on ecosystems and human health, as well as food security. The United Nations Member States have adopted targets for sustainable development. They include, inter alia, sustainable protection of water quality and sustainable use of water resources. To achieve these goals, appropriate monitoring strategies and the development of indicators for water quality are required. Within the pre-study for a 'World Water Quality Assessment' (WWQA) led by United Nations Environment Programme (UNEP), a methodology for assessing water quality, taking into account the above-mentioned objectives has been developed. The novelty of this methodology is the linked model- and data-driven approach. The focus is on parameters reflecting the key water quality issues, such as increased waste water pollution, salinization or eutrophication. The results from the pre-study show, for example, that already about one seventh of all watercourses in Latin America, Africa and Asia show high organic pollution. This is of central importance for inland fisheries and associated food security. In addition, it could be demonstrated that global water quality databases have large gaps. These must be closed in the future in order to obtain an overall picture of global water quality and to target measures more efficiently. The aim of this presentation is to introduce the methodology developed within the WWQA pre-study and to show selected examples of application in Latin America, Africa and Asia.

  1. Adaptive Admittance Control for an Ankle Exoskeleton Using an EMG-Driven Musculoskeletal Model

    Directory of Open Access Journals (Sweden)

    Shaowei Yao

    2018-04-01

    Full Text Available Various rehabilitation robots have been employed to recover the motor function of stroke patients. To improve the effect of rehabilitation, robots should promote patient participation and provide compliant assistance. This paper proposes an adaptive admittance control scheme (AACS consisting of an admittance filter, inner position controller, and electromyography (EMG-driven musculoskeletal model (EDMM. The admittance filter generates the subject's intended motion according to the joint torque estimated by the EDMM. The inner position controller tracks the intended motion, and its parameters are adjusted according to the estimated joint stiffness. Eight healthy subjects were instructed to wear the ankle exoskeleton robot, and they completed a series of sinusoidal tracking tasks involving ankle dorsiflexion and plantarflexion. The robot was controlled by the AACS and a non-adaptive admittance control scheme (NAACS at four fixed parameter levels. The tracking performance was evaluated using the jerk value, position error, interaction torque, and EMG levels of the tibialis anterior (TA and gastrocnemius (GAS. For the NAACS, the jerk value and position error increased with the parameter levels, and the interaction torque and EMG levels of the TA tended to decrease. In contrast, the AACS could maintain a moderate jerk value, position error, interaction torque, and TA EMG level. These results demonstrate that the AACS achieves a good tradeoff between accurate tracking and compliant assistance because it can produce a real-time response to stiffness changes in the ankle joint. The AACS can alleviate the conflict between accurate tracking and compliant assistance and has potential for application in robot-assisted rehabilitation.

  2. Jupiter Thermospheric General Circulation Model (JTGCM): Global Structure and Dynamics Driven by Auroral and Joule Heating

    Science.gov (United States)

    Bougher, S. W.; J. Il. Waite, Jr.; Majeed, T.

    2005-01-01

    A growing multispectral database plus recent Galileo descent measurements are being used to construct a self-consistent picture of the Jupiter thermosphere/ionosphere system. The proper characterization of Jupiter s upper atmosphere, embedded ionosphere, and auroral features requires the examination of underlying processes, including the feedbacks of energetics, neutral-ion dynamics, composition, and magnetospheric coupling. A fully 3-D Jupiter Thermospheric General Circulation Model (JTGCM) has been developed and exercised to address global temperatures, three-component neutral winds, and neutral-ion species distributions. The domain of this JTGCM extends from 20-microbar (capturing hydrocarbon cooling) to 1.0 x 10(exp -4) nbar (including aurora/Joule heating processes). The resulting JTGCM has been fully spun-up and integrated for greater than or equal to40 Jupiter rotations. Results from three JTGCM cases incorporating moderate auroral heating, ion drag, and moderate to strong Joule heating processes are presented. The neutral horizontal winds at ionospheric heights vary from 0.5 km/s to 1.2 km/s, atomic hydrogen is transported equatorward, and auroral exospheric temperatures range from approx.1200-1300 K to above 3000 K, depending on the magnitude of Joule heating. The equatorial temperature profiles from the JTGCM are compared with the measured temperature structure from the Galileo AS1 data set. The best fit to the Galileo data implies that the major energy source for maintaining the equatorial temperatures is due to dynamical heating induced by the low-latitude convergence of the high-latitude-driven thermospheric circulation. Overall, the Jupiter thermosphere/ionosphere system is highly variable and is shown to be strongly dependent on magnetospheric coupling which regulates Joule heating.

  3. Experience-driven formation of parts-based representations in a model of layered visual memory

    Directory of Open Access Journals (Sweden)

    Jenia Jitsev

    2009-09-01

    Full Text Available Growing neuropsychological and neurophysiological evidence suggests that the visual cortex uses parts-based representations to encode, store and retrieve relevant objects. In such a scheme, objects are represented as a set of spatially distributed local features, or parts, arranged in stereotypical fashion. To encode the local appearance and to represent the relations between the constituent parts, there has to be an appropriate memory structure formed by previous experience with visual objects. Here, we propose a model how a hierarchical memory structure supporting efficient storage and rapid recall of parts-based representations can be established by an experience-driven process of self-organization. The process is based on the collaboration of slow bidirectional synaptic plasticity and homeostatic unit activity regulation, both running at the top of fast activity dynamics with winner-take-all character modulated by an oscillatory rhythm. These neural mechanisms lay down the basis for cooperation and competition between the distributed units and their synaptic connections. Choosing human face recognition as a test task, we show that, under the condition of open-ended, unsupervised incremental learning, the system is able to form memory traces for individual faces in a parts-based fashion. On a lower memory layer the synaptic structure is developed to represent local facial features and their interrelations, while the identities of different persons are captured explicitly on a higher layer. An additional property of the resulting representations is the sparseness of both the activity during the recall and the synaptic patterns comprising the memory traces.

  4. Growth Inhibition by Testosterone in an Androgen Receptor Splice Variant-Driven Prostate Cancer Model.

    Science.gov (United States)

    Nakata, Daisuke; Nakayama, Kazuhide; Masaki, Tsuneo; Tanaka, Akira; Kusaka, Masami; Watanabe, Tatsuya

    2016-12-01

    Castration resistance creates a significant problem in the treatment of prostate cancer. Constitutively active splice variants of androgen receptor (AR) have emerged as drivers for resistance to androgen deprivation therapy, including the next-generation androgen-AR axis inhibitors abiraterone and enzalutamide. In this study, we describe the characteristics of a novel castration-resistant prostate cancer (CRPC) model, designated JDCaP-hr (hormone refractory). JDCaP-hr was established from an androgen-dependent JDCaP xenograft model after surgical castration. The expression of AR and its splice variants in JDCaP-hr was evaluated by immunoblotting and quantitative reverse transcription-polymerase chain reaction. The effects of AR antagonists and testosterone on JDCaP-hr were evaluated in vivo and in vitro. The roles of full-length AR (AR-FL) and AR-V7 in JDCaP-hr cell growth were evaluated using RNA interference. JDCaP-hr acquired a C-terminally truncated AR protein during progression from the parental JDCaP. The expression of AR-FL and AR-V7 mRNA was upregulated by 10-fold in JDCaP-hr compared with that in JDCaP, indicating that the JDCaP and JDCaP-hr models simulate castration resistance with some clinical features, such as overexpression of AR and its splice variants. The AR antagonist bicalutamide did not affect JDCaP-hr xenograft growth, and importantly, testosterone induced tumor regression. In vitro analysis demonstrated that androgen-independent prostate-specific antigen secretion and cell proliferation of JDCaP-hr were predominantly mediated by AR-V7. JDCaP-hr cell growth displayed a bell-shaped dependence on testosterone, and it was suppressed by physiological concentrations of testosterone. Testosterone induced rapid downregulation of both AR-FL and AR-V7 expression at physiological concentrations and suppressed expression of the AR target gene KLK3. Our findings support the clinical value of testosterone therapy, including bipolar androgen therapy, in the

  5. CEREF: A hybrid data-driven model for forecasting annual streamflow from a socio-hydrological system

    Science.gov (United States)

    Zhang, Hongbo; Singh, Vijay P.; Wang, Bin; Yu, Yinghao

    2016-09-01

    Hydrological forecasting is complicated by flow regime alterations in a coupled socio-hydrologic system, encountering increasingly non-stationary, nonlinear and irregular changes, which make decision support difficult for future water resources management. Currently, many hybrid data-driven models, based on the decomposition-prediction-reconstruction principle, have been developed to improve the ability to make predictions of annual streamflow. However, there exist many problems that require further investigation, the chief among which is the direction of trend components decomposed from annual streamflow series and is always difficult to ascertain. In this paper, a hybrid data-driven model was proposed to capture this issue, which combined empirical mode decomposition (EMD), radial basis function neural networks (RBFNN), and external forces (EF) variable, also called the CEREF model. The hybrid model employed EMD for decomposition and RBFNN for intrinsic mode function (IMF) forecasting, and determined future trend component directions by regression with EF as basin water demand representing the social component in the socio-hydrologic system. The Wuding River basin was considered for the case study, and two standard statistical measures, root mean squared error (RMSE) and mean absolute error (MAE), were used to evaluate the performance of CEREF model and compare with other models: the autoregressive (AR), RBFNN and EMD-RBFNN. Results indicated that the CEREF model had lower RMSE and MAE statistics, 42.8% and 7.6%, respectively, than did other models, and provided a superior alternative for forecasting annual runoff in the Wuding River basin. Moreover, the CEREF model can enlarge the effective intervals of streamflow forecasting compared to the EMD-RBFNN model by introducing the water demand planned by the government department to improve long-term prediction accuracy. In addition, we considered the high-frequency component, a frequent subject of concern in EMD

  6. Streamflow in the upper Mississippi river basin as simulated by SWAT driven by 20{sup th} century contemporary results of global climate models and NARCCAP regional climate models

    Energy Technology Data Exchange (ETDEWEB)

    Takle, Eugene S.; Jha, Manoj; Lu, Er; Arritt, Raymond W.; Gutowski, William J. [Iowa State Univ. Ames, IA (United States)

    2010-06-15

    We use Soil and Water Assessment Tool (SWAT) when driven by observations and results of climate models to evaluate hydrological quantities, including streamflow, in the Upper Mississippi River Basin (UMRB) for 1981-2003 in comparison to observed streamflow. Daily meteorological conditions used as input to SWAT are taken from (1) observations at weather stations in the basin, (2) daily meteorological conditions simulated by a collection of regional climate models (RCMs) driven by reanalysis boundary conditions, and (3) daily meteorological conditions simulated by a collection of global climate models (GCMs). Regional models used are those whose data are archived by the North American Regional Climate Change Assessment Program (NARCCAP). Results show that regional models correctly simulate the seasonal cycle of precipitation, temperature, and streamflow within the basin. Regional models also capture interannual extremes represented by the flood of 1993 and the dry conditions of 2000. The ensemble means of both the GCM-driven and RCM-driven simulations by SWAT capture both the timing and amplitude of the seasonal cycle of streamflow with neither demonstrating significant superiority at the basin level. (orig.)

  7. Agglomeration of a comprehensive model for the wind-driven sand transport at the Belgian Coast

    Science.gov (United States)

    Strypsteen, Glenn; Rauwoens, Pieter

    2016-04-01

    Although a lot of research has been done in the area of Aeolian transport, it is only during the last years that attention has been drawn to Aeolian transport in coastal areas. In these areas, the physical processes are more complex, due to a large number of transport limiting parameters. In this PhD-project, which is now in its early stage, a model will be developed which relates the wind-driven sand transport at the Belgian coast with physical parameters such as the wind speed, humidity and grain size of the sand, and the slope of beach and dune surface. For the first time, the interaction between beach and dune dynamics is studied at the Belgian coast. The Belgian coastline is only 67km long, but densely populated and therefore subject to coastal protection and safety. The coast mostly consists of sandy beaches and dikes. Although, still 33km of dunes exist, whose dynamics are far less understood. The overall research approach consists of three pathways: (i) field measurements, (ii) physical model tests, and (iii) numerical simulations. Firstly and most importantly, several field campaigns will provide accurate data of meteo-marine conditions, morphology, and sand transport events on a wide beach at the Belgian Coastline. The experimental set-up consists of a monitoring station, which will provide time series of vegetation cover, shoreline position, fetch distances, surficial moisture content, wind speed and direction and transport processes. The horizontal and vertical variability of the event scale Aeolian sand transport is analyzed with 8 MWAC sand traps. Two saltiphones register the intensity and variations of grain impacts over time. Two meteo-masts, each with four anemometers and one wind vane, provide quantitative measurements of the wind flow at different locations on the beach. Surficial moisture is measured with a moisture sensor. The topography measurements are typically done with laser techniques. To start, two sites are selected for measurement

  8. Modelling and Analysis of Radial Flux Surface Mounted Direct-Driven PMSG in Small Scale Wind Turbine

    Directory of Open Access Journals (Sweden)

    Theint Zar Htet

    2017-11-01

    Full Text Available This paper presents the modelling and analysis of permanent magnet synchronous generator (PMSG which are used in direct driven small scale wind turbines. The 3 kW PM generator which is driven directly without gear system is analyzed by Ansoft Maxwell 2D RMxprt. The performance analysis of generator includes the cogging torque in two teeth, induced coil voltages under load, winding current under load, airgap flux density distribution and so on. The modelling analysis is based on the 2D finite element techniques. In an electrical machine, an accurate determination of the geometry parameters is a vital role. The proper performance results of 3kW PMSG in small scale wind turbine can be seen in this paper.

  9. Retrospective cost adaptive Reynolds-averaged Navier-Stokes k-ω model for data-driven unsteady turbulent simulations

    Science.gov (United States)

    Li, Zhiyong; Hoagg, Jesse B.; Martin, Alexandre; Bailey, Sean C. C.

    2018-03-01

    This paper presents a data-driven computational model for simulating unsteady turbulent flows, where sparse measurement data is available. The model uses the retrospective cost adaptation (RCA) algorithm to automatically adjust the closure coefficients of the Reynolds-averaged Navier-Stokes (RANS) k- ω turbulence equations to improve agreement between the simulated flow and the measurements. The RCA-RANS k- ω model is verified for steady flow using a pipe-flow test case and for unsteady flow using a surface-mounted-cube test case. Measurements used for adaptation of the verification cases are obtained from baseline simulations with known closure coefficients. These verification test cases demonstrate that the RCA-RANS k- ω model can successfully adapt the closure coefficients to improve agreement between the simulated flow field and a set of sparse flow-field measurements. Furthermore, the RCA-RANS k- ω model improves agreement between the simulated flow and the baseline flow at locations at which measurements do not exist. The RCA-RANS k- ω model is also validated with experimental data from 2 test cases: steady pipe flow, and unsteady flow past a square cylinder. In both test cases, the adaptation improves agreement with experimental data in comparison to the results from a non-adaptive RANS k- ω model that uses the standard values of the k- ω closure coefficients. For the steady pipe flow, adaptation is driven by mean stream-wise velocity measurements at 24 locations along the pipe radius. The RCA-RANS k- ω model reduces the average velocity error at these locations by over 35%. For the unsteady flow over a square cylinder, adaptation is driven by time-varying surface pressure measurements at 2 locations on the square cylinder. The RCA-RANS k- ω model reduces the average surface-pressure error at these locations by 88.8%.

  10. Resolving vorticity-driven lateral fire spread using the WRF-Fire coupled atmosphere–fire numerical model

    OpenAIRE

    Simpson, C. C.; Sharples, J. J.; Evans, J. P.

    2014-01-01

    Fire channelling is a form of dynamic fire behaviour, during which a wildland fire spreads rapidly across a steep lee-facing slope in a direction transverse to the background winds, and is often accompanied by a downwind extension of the active flaming region and extreme pyro-convection. Recent work using the WRF-Fire coupled atmosphere-fire model has demonstrated that fire channelling can be characterised as vorticity-driven lateral fire spread (VDLS). In t...

  11. Interaction of pressure and momentum driven flows with thin porous media: Experiments and modeling

    Science.gov (United States)

    Naaktgeboren, Christian

    Flow interaction with thin porous media arise in a variety of natural and man-made settings. Examples include flow through thin grids in electronics cooling, and NOx emissions reduction by means of ammonia injection grids, pulsatile aquatic propulsion with complex trailing anatomy (e.g., jellyfish with tentacles) and microbursts from thunderstorm activity over dense vegetation, unsteady combustion in or near porous materials, pulsatile jet-drying of textiles, and pulsed jet agitation of clothing for trace contaminant sampling. Two types of interactions with thin porous media are considered: (i) forced convection or pressure-driven flows, where fluid advection is maintained by external forces, and (ii) inertial or momentum-driven flows, in which fluid motion is generated but not maintained by external forces. Forced convection analysis through thin permeable media using a porous continuum approach requires the knowledge of porous medium permeability and form coefficients, K and C, respectively, which are defined by the Hazen-Dupuit-Darcy (HDD) equation. Their determination, however, requires the measurement of the pressure-drop per unit of porous medium length. The pressure-drop caused by fluid entering and exiting the porous medium, however, is not related to the porous medium length. Hence, for situations in which the inlet and outlet pressure-drops are not negligible, e.g., for short porous media, the definition of Kand C via the HDD equation becomes ambiguous. This aspect is investigated analytically and numerically using the flow through a restriction in circular pipe and parallel plates channels as preliminary models. Results show that inlet and outlet pressure-drop effects become increasingly important when the inlet and outlet fluid surface fraction φ decreases and the Reynolds number Re increases for both laminar and turbulent flow regimes. A conservative estimate of the minimum porous medium length beyond which the core pressure-drop predominates over the

  12. Constraint-Driven Software Design: An Escape from the Waterfall Model.

    Science.gov (United States)

    de Hoog, Robert; And Others

    1994-01-01

    Presents the principles of a development methodology for software design based on a nonlinear, product-driven approach that integrates quality aspects. Two examples are given to show that the flexibility needed for building high quality systems leads to integrated development environments in which methodology, product, and tools are closely…

  13. First Principles Modeling of the Performance of a Hydrogen-Peroxide-Driven Chem-E-Car

    Science.gov (United States)

    Farhadi, Maryam; Azadi, Pooya; Zarinpanjeh, Nima

    2009-01-01

    In this study, performance of a hydrogen-peroxide-driven car has been simulated using basic conservation laws and a few numbers of auxiliary equations. A numerical method was implemented to solve sets of highly non-linear ordinary differential equations. Transient pressure and the corresponding traveled distance for three different car weights are…

  14. Climate-sensitive feedbacks between hillslope processes and fluvial erosion in sediment-driven incision models

    Science.gov (United States)

    Skov, Daniel S.; Egholm, David L.

    2016-04-01

    Surface erosion and sediment production seem to have accelerated globally as climate cooled in the Late Cenozoic, [Molnar, P. 2004, Herman et al 2013]. Glaciers emerged in many high mountain ranges during the Quaternary, and glaciation therefore represents a likely explanation for faster erosion in such places. Still, observations and measurements point to increases in erosion rates also in landscapes where erosion is driven mainly by fluvial processes [Lease and Ehlers (2013), Reusser (2004)]. Flume experiments and fieldwork have shown that rates of incision are to a large degree controlled by the sediment load of streams [e.g. Sklar and Dietrich (2001), Beer and Turowski (2015)]. This realization led to the formulation of sediment-flux dependent incision models [Sklar and Dietrich (2004)]. The sediment-flux dependence links incision in the channels to hillslope processes that supply sediment to the channels. The rates of weathering and soil transport on the hillslopes are processes that are likely to respond to changing temperatures, e.g. because of vegetation changes or the occurrence of frost. In this study, we perform computational landscape evolution experiments, where the coupling between fluvial incision and hillslope processes is accounted for by coupling a sediment-flux-dependent model for fluvial incision to a climate-dependent model for weathering and hillslope sediment transport. The computational experiments first of all demonstrate a strong positive feedback between channel and hillslope processes. In general, faster weathering leads to higher rates of channel incision, which further increases the weathering rates, mainly because of hillslope steepening. Slower weathering leads to the opposite result. The experiments also demonstrate, however, that the feedbacks vary significantly between different parts of a drainage network. For example, increasing hillslope sediment production may accelerate incision in the upper parts of the catchment, while at

  15. Generalized Boolean logic Driven Markov Processes: A powerful modeling framework for Model-Based Safety Analysis of dynamic repairable and reconfigurable systems

    International Nuclear Information System (INIS)

    Piriou, Pierre-Yves; Faure, Jean-Marc; Lesage, Jean-Jacques

    2017-01-01

    This paper presents a modeling framework that permits to describe in an integrated manner the structure of the critical system to analyze, by using an enriched fault tree, the dysfunctional behavior of its components, by means of Markov processes, and the reconfiguration strategies that have been planned to ensure safety and availability, with Moore machines. This framework has been developed from BDMP (Boolean logic Driven Markov Processes), a previous framework for dynamic repairable systems. First, the contribution is motivated by pinpointing the limitations of BDMP to model complex reconfiguration strategies and the failures of the control of these strategies. The syntax and semantics of GBDMP (Generalized Boolean logic Driven Markov Processes) are then formally defined; in particular, an algorithm to analyze the dynamic behavior of a GBDMP model is developed. The modeling capabilities of this framework are illustrated on three representative examples. Last, qualitative and quantitative analysis of GDBMP models highlight the benefits of the approach.

  16. 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.

  17. Data-driven modeling and predictive control for boiler-turbine unit using fuzzy clustering and subspace methods.

    Science.gov (United States)

    Wu, Xiao; Shen, Jiong; Li, Yiguo; Lee, Kwang Y

    2014-05-01

    This paper develops a novel data-driven fuzzy modeling strategy and predictive controller for boiler-turbine unit using fuzzy clustering and subspace identification (SID) methods. To deal with the nonlinear behavior of boiler-turbine unit, fuzzy clustering is used to provide an appropriate division of the operation region and develop the structure of the fuzzy model. Then by combining the input data with the corresponding fuzzy membership functions, the SID method is extended to extract the local state-space model parameters. Owing to the advantages of the both methods, the resulting fuzzy model can represent the boiler-turbine unit very closely, and a fuzzy model predictive controller is designed based on this model. As an alternative approach, a direct data-driven fuzzy predictive control is also developed following the same clustering and subspace methods, where intermediate subspace matrices developed during the identification procedure are utilized directly as the predictor. Simulation results show the advantages and effectiveness of the proposed approach. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

  18. [Kinematics Modeling and Analysis of Central-driven Robot for Upper Limb Rehabilitation after Stroke].

    Science.gov (United States)

    Yi, Jinhua; Yu, Hongliu; Zhang, Ying; Hu, Xin; Shi, Ping

    2015-12-01

    The present paper proposed a central-driven structure of upper limb rehabilitation robot in order to reduce the volume of the robotic arm in the structure, and also to reduce the influence of motor noise, radiation and other adverse factors on upper limb dysfunction patient. The forward and inverse kinematics equations have been obtained with using the Denavit-Hartenberg (D-H) parameter method. The motion simulation has been done to obtain the angle-time curve of each joint and the position-time curve of handle under setting rehabilitation path by using Solid Works software. Experimental results showed that the rationality with the central-driven structure design had been verified by the fact that the handle could move under setting rehabilitation path. The effectiveness of kinematics equations had been proved, and the error was less than 3° by comparing the angle-time curves obtained from calculation with those from motion simulation.

  19. A Genetically Engineered Mouse Model of Neuroblastoma Driven by Mutated ALK and MYCN

    Science.gov (United States)

    2014-09-01

    super-enhancer driven transcriptional programs in MYCN- amplified cells. George RE. Advances in Neuroblastoma Research Conference, Cologne, Germany ...crizotinib in ALK-mutated cells The above results suggested that deregulated MYCN could contribute to the sustained upregulation of mTORC1 activity in...incomplete inhibition of mTORC1 limits the activity of crizotinib in NB cells that express both ALKF1174L and deregulated MYCN. This interpretation is

  20. Established Models and New Paradigms for Hypoxia-Driven Cancer-Associated Bone Disease

    DEFF Research Database (Denmark)

    Cox, Thomas R.; Erler, Janine T.; Rumney, Robin M.H.

    2018-01-01

    -driven effects in the primary tumour are wide ranging including changes in gene expression, dysregulation of signalling pathways, resistance to chemotherapy, neovascularisation, increased tumour cell proliferation and migration. Paget’s seed and soil theory states that for a metastasising tumour cell ‘the seed...... metastases. This review describes the roles of hypoxia in primary tumour progression to metastasis, with a focus on key signalling pathways and treatment options to reduce patient morbidity and increase survival....

  1. A new costing model in hospital management: time-driven activity-based costing system.

    Science.gov (United States)

    Öker, Figen; Özyapıcı, Hasan

    2013-01-01

    Traditional cost systems cause cost distortions because they cannot meet the requirements of today's businesses. Therefore, a new and more effective cost system is needed. Consequently, time-driven activity-based costing system has emerged. The unit cost of supplying capacity and the time needed to perform an activity are the only 2 factors considered by the system. Furthermore, this system determines unused capacity by considering practical capacity. The purpose of this article is to emphasize the efficiency of the time-driven activity-based costing system and to display how it can be applied in a health care institution. A case study was conducted in a private hospital in Cyprus. Interviews and direct observations were used to collect the data. The case study revealed that the cost of unused capacity is allocated to both open and laparoscopic (closed) surgeries. Thus, by using the time-driven activity-based costing system, managers should eliminate the cost of unused capacity so as to obtain better results. Based on the results of the study, hospital management is better able to understand the costs of different surgeries. In addition, managers can easily notice the cost of unused capacity and decide how many employees to be dismissed or directed to other productive areas.

  2. Data-Driven Nonlinear Subspace Modeling for Prediction and Control of Molten Iron Quality Indices in Blast Furnace Ironmaking

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Ping; Song, Heda; Wang, Hong; Chai, Tianyou

    2017-09-01

    Blast furnace (BF) in ironmaking is a nonlinear dynamic process with complicated physical-chemical reactions, where multi-phase and multi-field coupling and large time delay occur during its operation. In BF operation, the molten iron temperature (MIT) as well as Si, P and S contents of molten iron are the most essential molten iron quality (MIQ) indices, whose measurement, modeling and control have always been important issues in metallurgic engineering and automation field. This paper develops a novel data-driven nonlinear state space modeling for the prediction and control of multivariate MIQ indices by integrating hybrid modeling and control techniques. First, to improve modeling efficiency, a data-driven hybrid method combining canonical correlation analysis and correlation analysis is proposed to identify the most influential controllable variables as the modeling inputs from multitudinous factors would affect the MIQ indices. Then, a Hammerstein model for the prediction of MIQ indices is established using the LS-SVM based nonlinear subspace identification method. Such a model is further simplified by using piecewise cubic Hermite interpolating polynomial method to fit the complex nonlinear kernel function. Compared to the original Hammerstein model, this simplified model can not only significantly reduce the computational complexity, but also has almost the same reliability and accuracy for a stable prediction of MIQ indices. Last, in order to verify the practicability of the developed model, it is applied in designing a genetic algorithm based nonlinear predictive controller for multivariate MIQ indices by directly taking the established model as a predictor. Industrial experiments show the advantages and effectiveness of the proposed approach.

  3. A heat pump driven and hollow fiber membrane-based liquid desiccant air dehumidification system: Modeling and experimental validation

    International Nuclear Information System (INIS)

    Zhang, Li-Zhi; Zhang, Ning

    2014-01-01

    A compression heat pump driven and membrane-based liquid desiccant air dehumidification system is presented. The dehumidifier and the regenerator are made of two hollow fiber membrane bundles packed in two shells. Water vapor can permeate through these membranes effectively, while the liquid desiccant droplets are prevented from cross-over. Simultaneous heating and cooling of the salt solution are realized with a heat pump system to improve energy efficiency. In this research, the system is built up and a complete modeling is performed for the system. Heat and mass transfer processes in the membrane modules, as well as in the evaporator, the condenser, and other key components are modeled in detail. The whole model is validated by experiment. The performances of SDP (specific dehumidification power), dehumidification efficiency, EER (energy efficiency ratio) of heat pump, and the COP (coefficient of performance) of the system are investigated numerically and experimentally. The results show that the model can predict the system accurately. The dehumidification capabilities and the energy efficiencies of the system are high. Further, it performs well even under the harsh hot and humid South China weather conditions. - Highlights: • A membrane-based and heat pump driven air dehumidification system is proposed. • A real experimental set up is built and used to validate the model for the whole system. • Performance under design and varying operation conditions is investigated. • The system performs well even under harsh hot and humid conditions

  4. Arsenic removal by solar-driven membrane distillation: modeling and experimental investigation with a new flash vaporization module.

    Science.gov (United States)

    Pa, Parimal; Manna, Ajay Kumar; Linnanen, Lassi

    2013-01-01

    A modeling and simulation study was carried out on a new flux-enhancing and solar-driven membrane distillation module for removal of arsenic from contaminated groundwater. The developed new model was validated with rigorous experimental investigations using arsenic-contaminated groundwater. By incorporating flash vaporization dynamics, the model turned out to be substantially different from the existing direct contact membrane distillation models and could successfully predict (with relative error of only 0.042 and a Willmott d-index of 0.997) the performance of such an arsenic removal unit where the existing models exhibited wide variation with experimental findings in the new design. The module with greater than 99% arsenic removal efficiency and greater than 50 L/m2 x h flux could be implemented in arsenic-affected villages in Southeast Asian countries with abundant solar energy, and thus could give relief to millions of affected people. These encouraging results will raise scale-up confidence.

  5. Amino acid catabolism-directed biofuel production in Clostridium sticklandii: An insight into model-driven systems engineering

    Directory of Open Access Journals (Sweden)

    C Sangavai

    2017-12-01

    Full Text Available Model-driven systems engineering has been more fascinating process for the microbial production of biofuel and bio-refineries in chemical and pharmaceutical industries. Genome-scale modeling and simulations have been guided for metabolic engineering of Clostridium species for the production of organic solvents and organic acids. Among them, Clostridium sticklandii is one of the potential organisms to be exploited as a microbial cell factory for biofuel production. It is a hyper-ammonia producing bacterium and is able to catabolize amino acids as important carbon and energy sources via Stickland reactions and the development of the specific pathways. Current genomic and metabolic aspects of this bacterium are comprehensively reviewed herein, which provided information for learning about protein catabolism-directed biofuel production. It has a metabolic potential to drive energy and direct solventogenesis as well as acidogenesis from protein catabolism. It produces by-products such as ethanol, acetate, n-butanol, n-butyrate and hydrogen from amino acid catabolism. Model-driven systems engineering of this organism would improve the performance of the industrial sectors and enhance the industrial economy by using protein-based waste in environment-friendly ways. Keywords: Biofuel, Amino acid catabolism, Genome-scale model, Metabolic engineering, Systems biology, ABE fermentation, Clostridium sticklandii

  6. Modeling and experimental investigation of an impact-driven piezoelectric energy harvester from human motion

    International Nuclear Information System (INIS)

    Wei, Sheng; Hu, Hong; He, Siyuan

    2013-01-01

    An impact-driven piezoelectric energy harvester from human motion is proposed in this paper. A high-frequency PZT-5A bimorph cantilever beam with attached proof mass at the free end was selected. A frequency up-conversion strategy was realized using impulse force generated by human motion. An aluminum prototype was attached to the leg of a person on a treadmill and measurements taken of the dissipated electric energy across multiple resistances over a range of walking speeds. The outer dimensions of this prototype are 90 mm × 40 mm × 24 mm. It has been shown that the average output voltage generated by the piezoelectric bimorph increases sequentially with a faster walking speed, the power varies with the external resistances and maximum levels occur at the optimal resistance, which is consistent with the simulation result. An open circuit voltage of 2.47 V and maximum average power of 51 μW can be achieved across a 20 kΩ external load resistance and 5 km h −1 walking speed. Experimental results reveal that the impact-driven piezoelectric energy harvesting system mounted on a person’s leg has the potential for driving wearable devices. (paper)

  7. Shiga Toxin—A Model for Glycolipid-Dependent and Lectin-Driven Endocytosis

    Directory of Open Access Journals (Sweden)

    Ludger Johannes

    2017-10-01

    Full Text Available The cellular entry of the bacterial Shiga toxin and the related verotoxins has been scrutinized in quite some detail. This is due to their importance as a threat to human health. At the same time, the study of Shiga toxin has allowed the discovery of novel molecular mechanisms that also apply to the intracellular trafficking of endogenous proteins at the plasma membrane and in the endosomal system. In this review, the individual steps that lead to Shiga toxin uptake into cells will first be presented from a purely mechanistic perspective. Membrane-biological concepts will be highlighted that are often still poorly explored, such as fluctuation force-driven clustering, clathrin-independent membrane curvature generation, friction-driven scission, and retrograde sorting on early endosomes. It will then be explored whether and how these also apply to other pathogens, pathogenic factors, and cellular proteins. The molecular nature of Shiga toxin as a carbohydrate-binding protein and that of its cellular receptor as a glycosylated raft lipid will be an underlying theme in this discussion. It will thereby be illustrated how the study of Shiga toxin has led to the proposal of the GlycoLipid-Lectin (GL-Lect hypothesis on the generation of endocytic pits in processes of clathrin-independent endocytosis.

  8. Theoretical modeling of a gas clearance phase regulation mechanism for a pneumatically-driven split-Stirling-cycle cryocooler

    Science.gov (United States)

    Zhang, Cun-quan; Zhong, Cheng

    2015-03-01

    The concept of a new type of pneumatically-driven split-Stirling-cycle cryocooler with clearance-phase-adjustor is proposed. In this implementation, the gap between the phase-adjusting part and the cylinder of the spring chamber is used, instead of dry friction acting on the pneumatically-driven rod to control motion damping of the displacer and to adjust the phase difference between the compression piston and displacer. It has the advantages of easy damping adjustment, low cost, and simplified manufacturing and assembly. A theoretical model has been established to simulate its dynamic performance. The linear compressor is modeled under adiabatic conditions, and the displacement of the compression piston is experimentally rectified. The working characteristics of the compressor motor and the principal losses of cooling, including regenerator inefficiency loss, solid conduction loss, shuttle loss, pump loss and radiation loss, are taken into account. The displacer motion was modeled as a single-degree-of-freedom (SDOF) forced system. A set of governing equations can be solved numerically to simulate the cooler's performance. The simulation is useful for understanding the physical processes occurring in the cooler and for predicting the cooler's performance.

  9. Dynamic model and workspace analysis of novel incompletely restrained cable-suspension swing system driven by two cables

    Directory of Open Access Journals (Sweden)

    Naige Wang

    2017-03-01

    Full Text Available The incompletely restrained cable-suspension swing system driven by two cables is introduced in this article. Based on wrench of forces theory and Lagrange’s equation of first kind, the static and dynamics models of incompletely restrained cable-suspension swing system driven by two cables are established, respectively. In order to obtain an intuitive understanding of the trajectory analysis, a dynamics model consisting of governing equation and geometric constraint conditions which is a set of the mixed differential-algebraic equation in mathematics is established. A typical feedback controller and an inverse model were set up to estimate the driving function. The effective workspace, which is used to guarantee an efficient swing process, mostly depends on the geometrical shape rather than the volume itself which was calculated by trajectory analysis. In order to estimate system features and ensure a limited range of tension in underconstrained spatial cable system, the probable location of unbalanced loading was evaluated by pointwise evaluation techniques during normal work.

  10. Classification of iRBD and Parkinson's patients using a general data-driven sleep staging model built on EEG

    DEFF Research Database (Denmark)

    Koch, Henriette; Christensen, Julie Anja Engelhard; Frandsen, Rune

    2013-01-01

    Sleep analysis is an important diagnostic tool for sleep disorders. However, the current manual sleep scoring is time-consuming as it is a crude discretization in time and stages. This study changes Esbroeck and Westover's [1] latent sleep staging model into a global model. The proposed data......-driven method trained a topic mixture model on 10 control subjects and was applied on 10 other control subjects, 10 iRBD patients and 10 Parkinson's patients. In that way 30 topic mixture diagrams were obtained from which features reflecting distinct sleep architectures between control subjects and patients...... were extracted. Two features calculated on basis of two latent sleep states classified subjects as “control” or “patient” by a simple clustering algorithm. The mean sleep staging accuracy compared to classical AASM scoring was 72.4% for control subjects and a clustering of the derived features resulted...

  11. A mathematical model for the motion analysis of embedded straight microcantilevers under a pressure-driven flow

    International Nuclear Information System (INIS)

    Ezkerra, A; Mayora, K; Ruano-López, J M; Wilson, P A

    2008-01-01

    A mathematical model that estimates the deflection of straight microcantilevers embedded in a microchannel under a pressure-driven flow at low Reynolds numbers is presented. The model makes use of the Schwarz–Christoffel mapping in order to couple the geometry of the structure and the flow passing around it. Therefore, it allows the determination of the most influential parameters and suitable modifications in order to achieve the desired performance. The model does not require specific knowledge of the flow conditions in the vicinity of the structure, which improves its practical use during the early stages of design. Estimations have been made for two straight cantilevers under a range of pressures. The results obtained show good agreement with measurements from experiments

  12. Stochastic interest model driven by compound Poisson process andBrownian motion with applications in life contingencies

    Directory of Open Access Journals (Sweden)

    Shilong Li

    2018-03-01

    Full Text Available In this paper, we introduce a class of stochastic interest model driven by a compoundPoisson process and a Brownian motion, in which the jumping times of force of interest obeyscompound Poisson process and the continuous tiny fluctuations are described by Brownian motion, andthe adjustment in each jump of interest force is assumed to be random. Based on the proposed interestmodel, we discuss the expected discounted function, the validity of the model and actuarial presentvalues of life annuities and life insurances under different parameters and distribution settings. Ournumerical results show actuarial values could be sensitive to the parameters and distribution settings,which shows the importance of introducing this kind interest model.

  13. A weakly nonlinear model with exact coefficients for the fluttering and spiraling motions of buoyancy-driven bodies

    Science.gov (United States)

    Magnaudet, Jacques; Tchoufag, Joel; Fabre, David

    2015-11-01

    Gravity/buoyancy-driven bodies moving in a slightly viscous fluid frequently follow fluttering or helical paths. Current models of such systems are largely empirical and fail to predict several of the key features of their evolution, especially close to the onset of path instability. Using a weakly nonlinear expansion of the full set of governing equations, we derive a new generic reduced-order model of this class of phenomena based on a pair of amplitude equations with exact coefficients that drive the evolution of the first pair of unstable modes. We show that the predictions of this model for the style (eg. fluttering or spiraling) and characteristics (eg. frequency and maximum inclination angle) of path oscillations compare well with various recent data for both solid disks and air bubbles.

  14. Weakly Nonlinear Model with Exact Coefficients for the Fluttering and Spiraling Motion of Buoyancy-Driven Bodies

    Science.gov (United States)

    Tchoufag, Joël; Fabre, David; Magnaudet, Jacques

    2015-09-01

    Gravity- or buoyancy-driven bodies moving in a slightly viscous fluid frequently follow fluttering or helical paths. Current models of such systems are largely empirical and fail to predict several of the key features of their evolution, especially close to the onset of path instability. Here, using a weakly nonlinear expansion of the full set of governing equations, we present a new generic reduced-order model based on a pair of amplitude equations with exact coefficients that drive the evolution of the first pair of unstable modes. We show that the predictions of this model for the style (e.g., fluttering or spiraling) and characteristics (e.g., frequency and maximum inclination angle) of path oscillations compare well with various recent data for both solid disks and air bubbles.

  15. Modeling and optimization of a novel two-axis mirror-scanning mechanism driven by piezoelectric actuators

    International Nuclear Information System (INIS)

    Jing, Zijian; Xu, Minglong; Feng, Bo

    2015-01-01

    Mirror-scanning mechanisms are a key component in optical systems for diverse applications. However, the applications of existing piezoelectric scanners are limited due to their small angular travels. To overcome this problem, a novel two-axis mirror-scanning mechanism, which consists of a two-axis tip-tilt flexure mechanism and a set of piezoelectric actuators, is proposed in this paper. The focus of this research is on the design, theoretical modeling, and optimization of the piezoelectric-driven mechanism, with the goal of achieving large angular travels in a compact size. The design of the two-axis tip-tilt flexure mechanism is based on two nonuniform beams, which translate the limited linear output displacements of the piezoelectric actuators into large output angles. To exactly predict the angular travels, we built a voltage-angle model that characterizes the relationship between the input voltages to the piezoelectric actuators and the output angles of the piezoelectric-driven mechanism. Using this analytical model, the optimization is performed to improve the angular travels. A prototype of the mirror-scanning mechanism is fabricated based on the optimization results, and experiments are implemented to test the two-axis output angles. The experimental result shows that the angular travels of the scanner achieve more than 50 mrad, and the error between the analytical model and the experiment is about 11%. This error is much smaller than the error for the model built using the previous method because the influence of the stiffness of the mechanical structure on the deformation of the piezoelectric stack is considered in the voltage-angle model. (paper)

  16. A menu-driven software package of Bayesian nonparametric (and parametric) mixed models for regression analysis and density estimation.

    Science.gov (United States)

    Karabatsos, George

    2017-02-01

    Most of applied statistics involves regression analysis of data. In practice, it is important to specify a regression model that has minimal assumptions which are not violated by data, to ensure that statistical inferences from the model are informative and not misleading. This paper presents a stand-alone and menu-driven software package, Bayesian Regression: Nonparametric and Parametric Models, constructed from MATLAB Compiler. Currently, this package gives the user a choice from 83 Bayesian models for data analysis. They include 47 Bayesian nonparametric (BNP) infinite-mixture regression models; 5 BNP infinite-mixture models for density estimation; and 31 normal random effects models (HLMs), including normal linear models. Each of the 78 regression models handles either a continuous, binary, or ordinal dependent variable, and can handle multi-level (grouped) data. All 83 Bayesian models can handle the analysis of weighted observations (e.g., for meta-analysis), and the analysis of left-censored, right-censored, and/or interval-censored data. Each BNP infinite-mixture model has a mixture distribution assigned one of various BNP prior distributions, including priors defined by either the Dirichlet process, Pitman-Yor process (including the normalized stable process), beta (two-parameter) process, normalized inverse-Gaussian process, geometric weights prior, dependent Dirichlet process, or the dependent infinite-probits prior. The software user can mouse-click to select a Bayesian model and perform data analysis via Markov chain Monte Carlo (MCMC) sampling. After the sampling completes, the software automatically opens text output that reports MCMC-based estimates of the model's posterior distribution and model predictive fit to the data. Additional text and/or graphical output can be generated by mouse-clicking other menu options. This includes output of MCMC convergence analyses, and estimates of the model's posterior predictive distribution, for selected

  17. Modeling of Heat and Mass Transfer in a TEC-Driven Lyophilizer

    Science.gov (United States)

    Yuan, Zeng-Guang; Hegde, Uday; Litwiller, Eric; Flynn, Michael; Fisher, John

    2006-01-01

    Dewatering of wet waste during space exploration missions is important for crew safety as it stabilizes the waste. It may also be used to recover water and serve as a preconditioning step for waste compaction. A thermoelectric cooler (TEC)-driven lyophilizer is under development at NASA Ames Research Center for this purpose. It has three major components: (i) an evaporator section where water vapor sublimes from the frozen waste, (ii) a condenser section where this water vapor deposits as ice, and (iii) a TEC section which serves as a heat pump to transfer heat from the condenser to the evaporator. This paper analyses the heat and mass transfer processes in the lyophilizer in an effort to understand the ice formation behavior in the condenser. The analysis is supported by experimental observations of ice formation patterns in two different condenser units.

  18. Studies on generalized kinetic model and Pareto optimization of a product-driven self-cycling bioprocess.

    Science.gov (United States)

    Sun, Kaibiao; Kasperski, Andrzej; Tian, Yuan

    2014-10-01

    The aim of this study is the optimization of a product-driven self-cycling bioprocess and presentation of a way to determine the best possible decision variables out of a set of alternatives based on the designed model. Initially, a product-driven generalized kinetic model, which allows a flexible choice of the most appropriate kinetics is designed and analysed. The optimization problem is given as the bi-objective one, where maximization of biomass productivity and minimization of unproductive loss of substrate are the objective functions. Then, the Pareto fronts are calculated for exemplary kinetics. It is found that in the designed bioprocess, a decrease of emptying/refilling fraction and an increase of substrate feeding concentration cause an increase of the biomass productivity. An increase of emptying/refilling fraction and a decrease of substrate feeding concentration cause a decrease of unproductive loss of substrate. The preferred solutions are calculated using the minimum distance from an ideal solution method, while giving proposals of their modifications derived from a decision maker's reactions to the generated solutions.

  19. caCORE version 3: Implementation of a model driven, service-oriented architecture for semantic interoperability.

    Science.gov (United States)

    Komatsoulis, George A; Warzel, Denise B; Hartel, Francis W; Shanbhag, Krishnakant; Chilukuri, Ram; Fragoso, Gilberto; Coronado, Sherri de; Reeves, Dianne M; Hadfield, Jillaine B; Ludet, Christophe; Covitz, Peter A

    2008-02-01

    One of the requirements for a federated information system is interoperability, the ability of one computer system to access and use the resources of another system. This feature is particularly important in biomedical research systems, which need to coordinate a variety of disparate types of data. In order to meet this need, the National Cancer Institute Center for Bioinformatics (NCICB) has created the cancer Common Ontologic Representation Environment (caCORE), an interoperability infrastructure based on Model Driven Architecture. The caCORE infrastructure provides a mechanism to create interoperable biomedical information systems. Systems built using the caCORE paradigm address both aspects of interoperability: the ability to access data (syntactic interoperability) and understand the data once retrieved (semantic interoperability). This infrastructure consists of an integrated set of three major components: a controlled terminology service (Enterprise Vocabulary Services), a standards-based metadata repository (the cancer Data Standards Repository) and an information system with an Application Programming Interface (API) based on Domain Model Driven Architecture. This infrastructure is being leveraged to create a Semantic Service-Oriented Architecture (SSOA) for cancer research by the National Cancer Institute's cancer Biomedical Informatics Grid (caBIG).

  20. Suppression of AGN-driven Turbulence by Magnetic Fields in a Magnetohydrodynamic Model of the Intracluster Medium

    Science.gov (United States)

    Bambic, Christopher J.; Morsony, Brian J.; Reynolds, Christopher S.

    2018-04-01

    We investigate the role of active galactic nucleus (AGN) feedback in turbulent heating of galaxy clusters. Specifically, we analyze the production of turbulence by g-modes generated by the supersonic expansion and buoyant rise of AGN-driven bubbles. Previous work that neglects magnetic fields has shown that this process is inefficient, with less than 1% of the injected energy ending up in turbulence. This inefficiency primarily arises because the bubbles are shredded apart by hydrodynamic instabilities before they can excite sufficiently strong g-modes. Using a plane-parallel model of the intracluster medium (ICM) and 3D ideal magnetohydrodynamics (MHD) simulations, we examine the role of a large-scale magnetic field that is able to drape around these rising bubbles, preserving them from hydrodynamic instabilities. We find that while magnetic draping appears better able to preserve AGN-driven bubbles, the driving of g-modes and the resulting production of turbulence is still inefficient. The magnetic tension force prevents g-modes from transitioning into the nonlinear regime, suppressing turbulence in our model ICM. Our work highlights the ways in which ideal MHD is an insufficient description for the cluster feedback process, and we discuss future work such as the inclusion of anisotropic viscosity as a means of simulating high β plasma kinetic effects. These results suggest the hypothesis that other mechanisms of heating the ICM plasma such as sound waves or cosmic rays may be responsible for the observed feedback in galaxy clusters.

  1. A novel model for simulating the racing effect in capillary-driven underfill process in flip chip

    Science.gov (United States)

    Zhu, Wenhui; Wang, Kanglun; Wang, Yan

    2018-04-01

    Underfill is typically applied in flip chips to increase the reliability of the electronic packagings. In this paper, the evolution of the melt-front shape of the capillary-driven underfill flow is studied through 3D numerical analysis. Two different models, the prevailing surface force model and the capillary model based on the wetted wall boundary condition, are introduced to test their applicability, where level set method is used to track the interface of the two phase flow. The comparison between the simulation results and experimental data indicates that, the surface force model produces better prediction on the melt-front shape, especially in the central area of the flip chip. Nevertheless, the two above models cannot simulate properly the racing effect phenomenon that appears during underfill encapsulation. A novel ‘dynamic pressure boundary condition’ method is proposed based on the validated surface force model. Utilizing this approach, the racing effect phenomenon is simulated with high precision. In addition, a linear relationship is derived from this model between the flow front location at the edge of the flip chip and the filling time. Using the proposed approach, the impact of the underfill-dispensing length on the melt-front shape is also studied.

  2. Going beyond best technology and lowest price: on renewable energy investors’ preference for service-driven business models

    International Nuclear Information System (INIS)

    Loock, Moritz

    2012-01-01

    Renewable energy is becoming increasingly important for economies in many countries. But still in an emerging industry, renewable energy requires supportive energy policy helping firms to develop and protect competitive advantages in global competition. As a guideline for designing such policy, we consult well-informed stakeholders within the renewable energy industry: investors. Their preferences serve as explorative indicator for assessing which business models might succeed in competition. To contribute to only limited research on renewable energy investors’ preferences, we ask, which business models investment managers for renewable energy prefer to invest in. We report from an explorative study of 380 choices of renewable energy investment managers. Based on the stated preferences, we modelled three generic business models to calculate the share of investors’ preferences. We find exiting evidence: a “customer intimacy” business model that proposes best services is much more preferred by investors than business models that propose lowest price or best technology. Policy-makers can use those insights for designing policy that supports service-driven business models for renewable energy with a scope on customer needs rather than technology or price. Additionally, we state important implications for renewable energy entrepreneurs, managers and research.

  3. A 'putty-practically-clay' vintage model with R and D driven biases in energy-saving technical change

    International Nuclear Information System (INIS)

    Van Zon, A.; Lontzek, T.

    2005-01-01

    This paper deals with the problem of tackling the adverse effect of output growth on environmental quality. For this purpose we use an intermediate sector that builds 'putty-practically-clay' capital consisting of an energy-raw capital amalgam used for final goods production. The putty-practically-clay model is a strongly simplified version of a full putty-clay model, that mimics all the relevant behaviour of a full puttyclay model, but that does not entail the administrative hassle of a full putty-clay vintage model. In addition to this, we introduce an R and D sector that develops renewable- and conventional energy-based technologies. The allocation of R and D activities over these two uses of R and D gives rise to an induced bias in technical change. In the context of our model, this implies that technological progress is primarily driven by the desire to counteract the upward pressure on production cost implied by a continuing price increase of conventional energy resources. Hotelling's rule suggests that this price rise is unavoidable in the face of the ongoing depletion of conventional energy reserves. By means of some illustrative model simulations we study the effects of energy policy on the dynamics of the model for alternative policy options aimed at achieving GHG emission reductions. We identify the conditions under which energy policy might partly backfire and present some non-standard policy implications

  4. Hybrid Analytical and Data-Driven Modeling for Feed-Forward Robot Control †

    Directory of Open Access Journals (Sweden)

    René Felix Reinhart

    2017-02-01

    Full Text Available Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant’s intrinsic properties and there remain unmodeled dynamics due to varying parameters, unmodeled friction or soft materials. In this context, machine learning is an alternative suitable technique to extract non-linear plant models from data. However, fully data-based models suffer from inaccuracies as well and are inefficient if they include learning of well known analytical models. This paper thus argues that feed-forward control based on hybrid models comprising an analytical model and a learned error model can significantly improve modeling accuracy. Hybrid modeling here serves the purpose to combine the best of the two modeling worlds. The hybrid modeling methodology is described and the approach is demonstrated for two typical problems in robotics, i.e., inverse kinematics control and computed torque control. The former is performed for a redundant soft robot and the latter for a rigid industrial robot with redundant degrees of freedom, where a complete analytical model is not available for any of the platforms.

  5. Hybrid Analytical and Data-Driven Modeling for Feed-Forward Robot Control.

    Science.gov (United States)

    Reinhart, René Felix; Shareef, Zeeshan; Steil, Jochen Jakob

    2017-02-08

    Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant's intrinsic properties and there remain unmodeled dynamics due to varying parameters, unmodeled friction or soft materials. In this context, machine learning is an alternative suitable technique to extract non-linear plant models from data. However, fully data-based models suffer from inaccuracies as well and are inefficient if they include learning of well known analytical models. This paper thus argues that feed-forward control based on hybrid models comprising an analytical model and a learned error model can significantly improve modeling accuracy. Hybrid modeling here serves the purpose to combine the best of the two modeling worlds. The hybrid modeling methodology is described and the approach is demonstrated for two typical problems in robotics, i.e., inverse kinematics control and computed torque control. The former is performed for a redundant soft robot and the latter for a rigid industrial robot with redundant degrees of freedom, where a complete analytical model is not available for any of the platforms.

  6. Hybrid Analytical and Data-Driven Modeling for Feed-Forward Robot Control †

    Science.gov (United States)

    Reinhart, René Felix; Shareef, Zeeshan; Steil, Jochen Jakob

    2017-01-01

    Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant’s intrinsic properties and there remain unmodeled dynamics due to varying parameters, unmodeled friction or soft materials. In this context, machine learning is an alternative suitable technique to extract non-linear plant models from data. However, fully data-based models suffer from inaccuracies as well and are inefficient if they include learning of well known analytical models. This paper thus argues that feed-forward control based on hybrid models comprising an analytical model and a learned error model can significantly improve modeling accuracy. Hybrid modeling here serves the purpose to combine the best of the two modeling worlds. The hybrid modeling methodology is described and the approach is demonstrated for two typical problems in robotics, i.e., inverse kinematics control and computed torque control. The former is performed for a redundant soft robot and the latter for a rigid industrial robot with redundant degrees of freedom, where a complete analytical model is not available for any of the platforms. PMID:28208697

  7. Evaluation of a subject-specific, torque-driven computer simulation model of one-handed tennis backhand groundstrokes.

    Science.gov (United States)

    Kentel, Behzat B; King, Mark A; Mitchell, Sean R

    2011-11-01

    A torque-driven, subject-specific 3-D computer simulation model of the impact phase of one-handed tennis backhand strokes was evaluated by comparing performance and simulation results. Backhand strokes of an elite subject were recorded on an artificial tennis court. Over the 50-ms period after impact, good agreement was found with an overall RMS difference of 3.3° between matching simulation and performance in terms of joint and racket angles. Consistent with previous experimental research, the evaluation process showed that grip tightness and ball impact location are important factors that affect postimpact racket and arm kinematics. Associated with these factors, the model can be used for a better understanding of the eccentric contraction of the wrist extensors during one-handed backhand ground strokes, a hypothesized mechanism of tennis elbow.

  8. User-driven health care: answering multidimensional information needs in individual patients utilizing post-EBM approaches: an operational model.

    Science.gov (United States)

    Biswas, Rakesh; Maniam, Jayanthy; Lee, Edwin Wen Huo; Gopal, Premalatha; Umakanth, Shashikiran; Dahiya, Sumit; Ahmed, Sayeed

    2008-10-01

    The hypothesis in the conceptual model was that a user-driven innovation in presently available information and communication technology infrastructure would be able to meet patient and health professional users information needs and help them attain better health outcomes. An operational model was created to plan a trial on a sample diabetic population utilizing a randomized control trial design, assigning one randomly selected group of diabetics to receive electronic information intervention and analyse if it would improve their health outcomes in comparison with a matched diabetic population who would only receive regular medical intervention. Diabetes was chosen for this particular trial, as it is a major chronic illness in Malaysia as elsewhere in the world. It is in essence a position paper for how the study concept should be organized to stimulate wider discussion prior to beginning the study.

  9. Evaluate transport processes in MERRA driven chemical transport models using updated 222Rn emission inventories and global observations

    Science.gov (United States)

    Zhang, B.; Liu, H.; Crawford, J. H.; Fairlie, T. D.; Chen, G.; Chambers, S. D.; Kang, C. H.; Williams, A. G.; Zhang, K.; Considine, D. B.; Payer Sulprizio, M.; Yantosca, R.

    2015-12-01

    Convective and synoptic processes play a major role in determining the transport and distribution of trace gases and aerosols in the troposphere. The representation of these processes in global models (at ~100-1000 km horizontal resolution) is challenging, because convection is a sub-grid process and needs to be parameterized, while synoptic processes are close to the grid scale. Depending on the parameterization schemes used in climate models, the role of convection in transporting trace gases and aerosols may vary from model to model. 222Rn is a chemically inert and radioactive gas constantly emitted from soil and has a half-life (3.8 days) comparable to synoptic timescale, which makes it an effective tracer for convective and synoptic transport. In this study, we evaluate the convective and synoptic transport in two chemical transport models (GMI and GEOS-Chem), both driven by the NASA's MERRA reanalysis. Considering the uncertainties in 222Rn emissions, we incorporate two more recent scenarios with regionally varying 222Rn emissions into GEOS-Chem/MERRA and compare the simulation results with those using the relatively uniform 222Rn emissions in the standard model. We evaluate the global distribution and seasonality of 222Rn concentrations simulated by the two models against an extended collection of 222Rn observations from 1970s to 2010s. The intercomparison will improve our understanding of the spatial variability in global 222Rn emissions, including the suspected excessive 222Rn emissions in East Asia, and provide useful feedbacks on 222Rn emission models. We will assess 222Rn vertical distributions at different latitudes in the models using observations at surface sites and in the upper troposphere and lower stratosphere. Results will be compared with previous models driven by other meteorological fields (e.g., fvGCM and GEOS4). Since the decay of 222Rn is the source of 210Pb, a useful radionuclide tracer attached to submicron aerosols, improved

  10. A Time-dependent Heliospheric Model Driven by Empirical Boundary Conditions

    Science.gov (United States)

    Kim, T. K.; Arge, C. N.; Pogorelov, N. V.

    2017-12-01

    Consisting of charged particles originating from the Sun, the solar wind carries the Sun's energy and magnetic field outward through interplanetary space. The solar wind is the predominant source of space weather events, and modeling the solar wind propagation to Earth is a critical component of space weather research. Solar wind models are typically separated into coronal and heliospheric parts to account for the different physical processes and scales characterizing each region. Coronal models are often coupled with heliospheric models to propagate the solar wind out to Earth's orbit and beyond. The Wang-Sheeley-Arge (WSA) model is a semi-empirical coronal model consisting of a potential field source surface model and a current sheet model that takes synoptic magnetograms as input to estimate the magnetic field and solar wind speed at any distance above the coronal region. The current version of the WSA model takes the Air Force Data Assimilative Photospheric Flux Transport (ADAPT) model as input to provide improved time-varying solutions for the ambient solar wind structure. When heliospheric MHD models are coupled with the WSA model, density and temperature at the inner boundary are treated as free parameters that are tuned to optimal values. For example, the WSA-ENLIL model prescribes density and temperature assuming momentum flux and thermal pressure balance across the inner boundary of the ENLIL heliospheric MHD model. We consider an alternative approach of prescribing density and temperature using empirical correlations derived from Ulysses and OMNI data. We use our own modeling software (Multi-scale Fluid-kinetic Simulation Suite) to drive a heliospheric MHD model with ADAPT-WSA input. The modeling results using the two different approaches of density and temperature prescription suggest that the use of empirical correlations may be a more straightforward, consistent method.

  11. Asperity-Type Potential Foreshock Sources Driven by Nucleation-Induced Creep within a Rate-and-State Fault Model

    Science.gov (United States)

    Higgins, N.; Lapusta, N.

    2016-12-01

    What physical mechanism drives the occurrence of foreshocks? Many studies have suggested that slow slip from the mainshock nucleation is a necessary ingredient for explaining foreshock observations. We explore this view, investigating asperity-type foreshock sources driven by nucleation-induced creep using rate-and-state fault models, and numerically simulatie their behavior over many rupture cycles. Inspired by the unique laboratory experiments of earthquake nucleation and rupture conducted on a meter-scale slab of granite by McLaskey and colleagues, we model potential foreshock sources as "bumps" on the fault interface by assigning a significantly higher normal compression and, in some cases, increased smoothness (lower characteristic slip) over small patches within a seismogenic fault. In order to study the mechanics of isolated patch-induced seismic events preceding the mainshock, we separate these patches sufficiently in space. The simulation results show that our rate-and-state fault model with patches of locally different properties driven by the slow nucleation of the mainshock is indeed able to produce isolated microseismicity before the mainshock. Remarkably, the stress drops of these precursory events are compatible with observations and approximately independent of the patch compression, despite the wide range of the elevated patch compression used in different simulations. We find that this unexpected property of stress drops for this type of model is due to two factors. Firstly, failure of stronger patches results in rupture further into the surrounding fault, keeping the average stress drop down. Secondly, patches close to their local nucleation size relieve a significant amount of stress via aseismic pre-slip, which also helps to keep the stress drop down. Our current work is directed towards investigating the seismic signature of such events and the potential differences with other types of microseismicity.

  12. Business process modelling in demand-driven agri-food supply chains : a reference framework

    NARCIS (Netherlands)

    Verdouw, C.N.

    2010-01-01

    Keywords: Business process models; Supply chain management; Information systems; Reference information models; Market orientation; Mass customisation; Configuration; Coordination; Control; SCOR; Pot plants; Fruit industry

    Abstract

    The increasing volatility and diversity of

  13. The power of an ontology-driven developmental toxicity database for data mining and computational modeling

    Science.gov (United States)

    Modeling of developmental toxicology presents a significant challenge to computational toxicology due to endpoint complexity and lack of data coverage. These challenges largely account for the relatively few modeling successes using the structure–activity relationship (SAR) parad...

  14. An Integrated Framework for Process-Driven Model Construction in Disease Ecology and Animal Health.

    Science.gov (United States)

    Mancy, Rebecca; Brock, Patrick M; Kao, Rowland R

    2017-01-01

    Process models that focus on explicitly representing biological mechanisms are increasingly important in disease ecology and animal health research. However, the large number of process modelling approaches makes it difficult to decide which is most appropriate for a given disease system and research question. Here, we discuss different motivations for using process models and present an integrated conceptual analysis that can be used to guide the construction of infectious disease process models and comparisons between them. Our presentation complements existing work by clarifying the major differences between modelling approaches and their relationship with the biological characteristics of the epidemiological system. We first discuss distinct motivations for using process models in epidemiological research, identifying the key steps in model design and use associated with each. We then present a conceptual framework for guiding model construction and comparison, organised according to key aspects of epidemiological systems. Specifically, we discuss the number and type of disease states, whether to focus on individual hosts (e.g., cows) or groups of hosts (e.g., herds or farms), how space or host connectivity affect disease transmission, whether demographic and epidemiological processes are periodic or can occur at any time, and the extent to which stochasticity is important. We use foot-and-mouth disease and bovine tuberculosis in cattle to illustrate our discussion and support explanations of cases in which different models are used to address similar problems. The framework should help those constructing models to structure their approach to modelling decisions and facilitate comparisons between models in the literature.

  15. Photosynthesis driven crop growth models for greenhouse cultivation; advances and bottlenecks.

    NARCIS (Netherlands)

    Challa, H.; Heuvelink, E.

    1996-01-01

    In recent years considerable progress has been made in modelling growth of green-house crops. Nevertheless, the share of research in this field compared to crop modelling in general is only a few percent. Yet, crop growth models have a great potential for greenhouse production systems, because they

  16. A spatially explicit scenario-driven model of adaptive capacity to global change in Europe

    NARCIS (Netherlands)

    Acosta, L.; Klein, R.J.T.; Reidsma, P.; Metzger, M.J.; Rounsevell, M.D.A.; Leemans, R.

    2013-01-01

    Traditional impact models combine exposure in the form of scenarios and sensitivity in the form of parameters, providing potential impacts of global change as model outputs. However, adaptive capacity is rarely addressed in these models. This paper presents the first spatially explicit

  17. Knowledge-driven GIS modeling technique for gold exploration, Bulghah gold mine area, Saudi Arabia

    Directory of Open Access Journals (Sweden)

    Ahmed A. Madani

    2011-12-01

    Full Text Available This research aims to generate a favorability map for gold exploration at the Bulghah gold mine area using integration of geo-datasets within a GIS environment. Spatial data analyses and integration of different geo-datasets are carried out based on knowledge-driven and weighting technique. The integration process involves the weighting and scoring of different layers affecting the gold mineralization at the study area using the index overlay method within PCI Geomatica environment. Generation of the binary predictor maps for lithology, lineaments, faults and favorable contacts precede the construction of the favorability map. About 100 m buffer zones are generated for favorable contacts, lineaments and major faults layers. Internal weighting is assigned to each layer based on favorability for gold mineralization. The scores for lithology, major faults, lineaments and favorable contacts layers in the constructed favorability map are 50%, 25%, 10% and 15%, respectively. Final favorability map for the Bulghah gold mine area shows the recording of two new sites for gold mineralization located at the northern and southern extensions of tonalite–diorite intrusions. The northern new site is now exploited for gold from the Bulghah North mine. The southern new site is narrow and small; its rocks resemble those of the Bulghah gold mine.

  18. TTS-Driven Synthetic Behaviour-Generation Model for Artificial Bodies

    Directory of Open Access Journals (Sweden)

    Izidor Mlakar

    2013-10-01

    Full Text Available Visual perception, speech perception and the understanding of perceived information are linked through complex mental processes. Gestures, as part of visual perception and synchronized with verbal information, are a key concept of human social interaction. Even when there is no physical contact (e.g., a phone conversation, humans still tend to express meaning through movement. Embodied conversational agents (ECAs, as well as humanoid robots, are visual recreations of humans and are thus expected to be able to perform similar behaviour in communication. The behaviour generation system proposed in this paper is able to specify expressive behaviour strongly resembling natural movement performed within social interaction. The system is TTS-driven and fused with the time-and-space efficient TTS-engine, called ‘PLATTOS’. Visual content and content presentation is formulated based on several linguistic features that are extrapolated from arbitrary input text sequences and prosodic features (e.g., pitch, intonation, stress, emphasis, etc., as predicted by several verbal modules in the system. According to the evaluation results, when using the proposed system the synchronized co-verbal behaviour can be recreated with a very high-degree of naturalness, either by ECAs or humanoid robots alike.

  19. Charged particle motion in a time-dependent flux-driven ring: an exactly solvable model

    International Nuclear Information System (INIS)

    Luan, P-G; Tang, C-S

    2007-01-01

    We consider a charged particle driven by a time-dependent flux threading a quantum ring. The dynamics of the charged particle is investigated using a classical treatment, a Fourier expansion technique, a time-evolution method, and the Lewis-Riesenfeld approach. We have shown that, by properly managing the boundary conditions, a time-dependent wavefunction can be obtained using a general non-Hermitian time-dependent invariant, which is a specific linear combination of initial angular-momentum and azimuthal-angle operators. It is shown that the linear invariant eigenfunction can be realized as a Gaussian-type wavepacket with a peak moving along the classical angular trajectory, while the distribution of the wavepacket is determined by the ratio of the coefficient of the initial angle to that of the initial canonical angular momentum. From the topologically nontrivial nature as well as the classical trajectory and angular momentum, one can determine the dynamical motion of the wavepacket. It should be noted that the peak position is no longer an expectation value of the angle operator, and hence the Ehrenfest theorem is not directly applicable in such a topologically nontrivial system

  20. 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.