Real-time prediction of respiratory motion based on a local dynamic model in an augmented space.

Science.gov (United States)

Hong, S-M; Jung, B-H; Ruan, D

2011-03-21

Motion-adaptive radiotherapy aims to deliver ablative radiation dose to the tumor target with minimal normal tissue exposure, by accounting for real-time target movement. In practice, prediction is usually necessary to compensate for system latency induced by measurement, communication and control. This work focuses on predicting respiratory motion, which is most dominant for thoracic and abdominal tumors. We develop and investigate the use of a local dynamic model in an augmented space, motivated by the observation that respiratory movement exhibits a locally circular pattern in a plane augmented with a delayed axis. By including the angular velocity as part of the system state, the proposed dynamic model effectively captures the natural evolution of respiratory motion. The first-order extended Kalman filter is used to propagate and update the state estimate. The target location is predicted by evaluating the local dynamic model equations at the required prediction length. This method is complementary to existing work in that (1) the local circular motion model characterizes 'turning', overcoming the limitation of linear motion models; (2) it uses a natural state representation including the local angular velocity and updates the state estimate systematically, offering explicit physical interpretations; (3) it relies on a parametric model and is much less data-satiate than the typical adaptive semiparametric or nonparametric method. We tested the performance of the proposed method with ten RPM traces, using the normalized root mean squared difference between the predicted value and the retrospective observation as the error metric. Its performance was compared with predictors based on the linear model, the interacting multiple linear models and the kernel density estimator for various combinations of prediction lengths and observation rates. The local dynamic model based approach provides the best performance for short to medium prediction lengths under relatively

Real-time modelling of a ventilation system for a power plant simulator

International Nuclear Information System (INIS)

Kocher, P.; Welfonder, E.

1992-01-01

This paper describes how to simulate in real-time the ventilation system of a nuclear power plant. The simulation is made under difficult computing time conditions. The ventilation system program is part of a simulator which simulates the whole nuclear power plant process in realtime. Therefore the ventilation system is split up into several smaller units. For each of these process units a real-time module has been developed, being as simple as possible but nevertheless coming close enough to the real dynamic behaviour. After that the simple real-time modules are linked together to form the total dynamic model ''ventilation system''. The continuous dynamic model developed is numerically integrated by the Euler method. The stability of this explicit method is maintained by special modelling measures such as the increasing of too low flow resistances or the limitation of too high gain factors. At the end of the paper some curves, recorded at the simulator, illustrate the behaviour of the ventilation system in the case of an accident. (author)

Model Checking Real-Time Systems

DEFF Research Database (Denmark)

Bouyer, Patricia; Fahrenberg, Uli; Larsen, Kim Guldstrand

2018-01-01

This chapter surveys timed automata as a formalism for model checking real-time systems. We begin with introducing the model, as an extension of finite-state automata with real-valued variables for measuring time. We then present the main model-checking results in this framework, and give a hint...

Real-Time Corrected Traffic Correlation Model for Traffic Flow Forecasting

Directory of Open Access Journals (Sweden)

Hua-pu Lu

2015-01-01

Full Text Available This paper focuses on the problems of short-term traffic flow forecasting. The main goal is to put forward traffic correlation model and real-time correction algorithm for traffic flow forecasting. Traffic correlation model is established based on the temporal-spatial-historical correlation characteristic of traffic big data. In order to simplify the traffic correlation model, this paper presents correction coefficients optimization algorithm. Considering multistate characteristic of traffic big data, a dynamic part is added to traffic correlation model. Real-time correction algorithm based on Fuzzy Neural Network is presented to overcome the nonlinear mapping problems. A case study based on a real-world road network in Beijing, China, is implemented to test the efficiency and applicability of the proposed modeling methods.

Real-time high dynamic range laser scanning microscopy

Science.gov (United States)

Vinegoni, C.; Leon Swisher, C.; Fumene Feruglio, P.; Giedt, R. J.; Rousso, D. L.; Stapleton, S.; Weissleder, R.

2016-04-01

In conventional confocal/multiphoton fluorescence microscopy, images are typically acquired under ideal settings and after extensive optimization of parameters for a given structure or feature, often resulting in information loss from other image attributes. To overcome the problem of selective data display, we developed a new method that extends the imaging dynamic range in optical microscopy and improves the signal-to-noise ratio. Here we demonstrate how real-time and sequential high dynamic range microscopy facilitates automated three-dimensional neural segmentation. We address reconstruction and segmentation performance on samples with different size, anatomy and complexity. Finally, in vivo real-time high dynamic range imaging is also demonstrated, making the technique particularly relevant for longitudinal imaging in the presence of physiological motion and/or for quantification of in vivo fast tracer kinetics during functional imaging.

Dynamic Reconfiguration in Real-Time Systems Energy, Performance, and Thermal Perspectives

CERN Document Server

Wang, Weixun; Ranka, Sanjay

2013-01-01

Given the widespread use of real-time multitasking systems, there are tremendous optimization opportunities if reconfigurable computing can be effectively incorporated while maintaining performance and other design constraints of typical applications. The focus of this book is to describe the dynamic reconfiguration techniques that can be safely used in real-time systems. This book provides comprehensive approaches by considering synergistic effects of computation, communication as well as storage together to significantly improve overall performance, power, energy and temperature.  Provides a comprehensive introduction to optimization and dynamic reconfiguration techniques in real-time embedded systems; Covers state-of-the-art techniques and ongoing research in reconfigurable architectures; Focuses on algorithms tuned for dynamic reconfiguration techniques in real-time systems;  Provides reference for anyone designing low-power systems, energy-/temperature-constrained devices, and power-performance efficie...

Hybrid automata models of cardiac ventricular electrophysiology for real-time computational applications.

Science.gov (United States)

Andalam, Sidharta; Ramanna, Harshavardhan; Malik, Avinash; Roop, Parthasarathi; Patel, Nitish; Trew, Mark L

2016-08-01

Virtual heart models have been proposed for closed loop validation of safety-critical embedded medical devices, such as pacemakers. These models must react in real-time to off-the-shelf medical devices. Real-time performance can be obtained by implementing models in computer hardware, and methods of compiling classes of Hybrid Automata (HA) onto FPGA have been developed. Models of ventricular cardiac cell electrophysiology have been described using HA which capture the complex nonlinear behavior of biological systems. However, many models that have been used for closed-loop validation of pacemakers are highly abstract and do not capture important characteristics of the dynamic rate response. We developed a new HA model of cardiac cells which captures dynamic behavior and we implemented the model in hardware. This potentially enables modeling the heart with over 1 million dynamic cells, making the approach ideal for closed loop testing of medical devices.

Innovative tools for real-time simulation of dynamic systems

NARCIS (Netherlands)

Palli, Gianluca; Carloni, Raffaella; Melchiorri, Claudio

2008-01-01

In this paper, we present a software architecture, based on RTAI-Linux, for the real-time simulation of dynamic systems and for the rapid prototyping of digital controllers. Our aim is to simplify the testing phase of digital controllers by providing the real-time simulation of the plant with the

Real-time tumor ablation simulation based on the dynamic mode decomposition method

KAUST Repository

Bourantas, George C.; Ghommem, Mehdi; Kagadis, George C.; Katsanos, Konstantinos H.; Loukopoulos, Vassilios C.; Burganos, Vasilis N.; Nikiforidis, George C.

2014-01-01

Purpose: The dynamic mode decomposition (DMD) method is used to provide a reliable forecasting of tumor ablation treatment simulation in real time, which is quite needed in medical practice. To achieve this, an extended Pennes bioheat model must

Coordinated scheduling for dynamic real-time systems

Science.gov (United States)

Natarajan, Swaminathan; Zhao, Wei

1994-01-01

In this project, we addressed issues in coordinated scheduling for dynamic real-time systems. In particular, we concentrated on design and implementation of a new distributed real-time system called R-Shell. The design objective of R-Shell is to provide computing support for space programs that have large, complex, fault-tolerant distributed real-time applications. In R-shell, the approach is based on the concept of scheduling agents, which reside in the application run-time environment, and are customized to provide just those resource management functions which are needed by the specific application. With this approach, we avoid the need for a sophisticated OS which provides a variety of generalized functionality, while still not burdening application programmers with heavy responsibility for resource management. In this report, we discuss the R-Shell approach, summarize the achievement of the project, and describe a preliminary prototype of R-Shell system.

Control-Oriented Models for Real-Time Simulation of Automotive Transmission Systems

Directory of Open Access Journals (Sweden)

Cavina N.

2015-01-01

Full Text Available A control-oriented model of a Dual Clutch Transmission (DCT was developed for real-time Hardware In the Loop (HIL applications, to support model-based development of the DCT controller and to systematically test its performance. The model is an innovative attempt to reproduce the fast dynamics of the actuation system while maintaining a simulation step size large enough for real-time applications. The model comprehends a detailed physical description of hydraulic circuit, clutches, synchronizers and gears, and simplified vehicle and internal combustion engine sub-models. As the oil circulating in the system has a large bulk modulus, the pressure dynamics are very fast, possibly causing instability in a real-time simulation; the same challenge involves the servo valves dynamics, due to the very small masses of the moving elements. Therefore, the hydraulic circuit model has been modified and simplified without losing physical validity, in order to adapt it to the real-time simulation requirements. The results of offline simulations have been compared to on-board measurements to verify the validity of the developed model, which was then implemented in a HIL system and connected to the Transmission Control Unit (TCU. Several tests have been performed on the HIL simulator, to verify the TCU performance: electrical failure tests on sensors and actuators, hydraulic and mechanical failure tests on hydraulic valves, clutches and synchronizers, and application tests comprehending all the main features of the control actions performed by the TCU. Being based on physical laws, in every condition the model simulates a plausible reaction of the system. A test automation procedure has finally been developed to permit the execution of a pattern of tests without the interaction of the user; perfectly repeatable tests can be performed for non-regression verification, allowing the testing of new software releases in fully automatic mode.

Dynamic Bus Travel Time Prediction Models on Road with Multiple Bus Routes.

Science.gov (United States)

Bai, Cong; Peng, Zhong-Ren; Lu, Qing-Chang; Sun, Jian

2015-01-01

Accurate and real-time travel time information for buses can help passengers better plan their trips and minimize waiting times. A dynamic travel time prediction model for buses addressing the cases on road with multiple bus routes is proposed in this paper, based on support vector machines (SVMs) and Kalman filtering-based algorithm. In the proposed model, the well-trained SVM model predicts the baseline bus travel times from the historical bus trip data; the Kalman filtering-based dynamic algorithm can adjust bus travel times with the latest bus operation information and the estimated baseline travel times. The performance of the proposed dynamic model is validated with the real-world data on road with multiple bus routes in Shenzhen, China. The results show that the proposed dynamic model is feasible and applicable for bus travel time prediction and has the best prediction performance among all the five models proposed in the study in terms of prediction accuracy on road with multiple bus routes.

Dynamic Bus Travel Time Prediction Models on Road with Multiple Bus Routes

Science.gov (United States)

Bai, Cong; Peng, Zhong-Ren; Lu, Qing-Chang; Sun, Jian

2015-01-01

Accurate and real-time travel time information for buses can help passengers better plan their trips and minimize waiting times. A dynamic travel time prediction model for buses addressing the cases on road with multiple bus routes is proposed in this paper, based on support vector machines (SVMs) and Kalman filtering-based algorithm. In the proposed model, the well-trained SVM model predicts the baseline bus travel times from the historical bus trip data; the Kalman filtering-based dynamic algorithm can adjust bus travel times with the latest bus operation information and the estimated baseline travel times. The performance of the proposed dynamic model is validated with the real-world data on road with multiple bus routes in Shenzhen, China. The results show that the proposed dynamic model is feasible and applicable for bus travel time prediction and has the best prediction performance among all the five models proposed in the study in terms of prediction accuracy on road with multiple bus routes. PMID:26294903

A Dynamic Travel Time Estimation Model Based on Connected Vehicles

Directory of Open Access Journals (Sweden)

Daxin Tian

2015-01-01

Full Text Available With advances in connected vehicle technology, dynamic vehicle route guidance models gradually become indispensable equipment for drivers. Traditional route guidance models are designed to direct a vehicle along the shortest path from the origin to the destination without considering the dynamic traffic information. In this paper a dynamic travel time estimation model is presented which can collect and distribute traffic data based on the connected vehicles. To estimate the real-time travel time more accurately, a road link dynamic dividing algorithm is proposed. The efficiency of the model is confirmed by simulations, and the experiment results prove the effectiveness of the travel time estimation method.

Real-Time Simulation of Coaxial Rotor Configurations with Combined Finite State Dynamic Wake and VPM

OpenAIRE

Zhao, Jinggen; He, Chengjian

2017-01-01

This paper describes a first-principle based finite state dynamic rotor wake model that addresses the complex aerodynamic interference inherent to coaxial rotor configurations in support of advanced vertical lift aircraft simulation, design, and analysis. The high fidelity rotor dynamic wake solution combines an enhanced real-time finite state dynamic wake model (DYW) with a first-principle based viscous Vortex Particle Method (VPM). The finite state dynamic wake model provides a state-spa...

Compiling models into real-time systems

International Nuclear Information System (INIS)

Dormoy, J.L.; Cherriaux, F.; Ancelin, J.

1992-08-01

This paper presents an architecture for building real-time systems from models, and model-compiling techniques. This has been applied for building a real-time model-based monitoring system for nuclear plants, called KSE, which is currently being used in two plants in France. We describe how we used various artificial intelligence techniques for building it: a model-based approach, a logical model of its operation, a declarative implementation of these models, and original knowledge-compiling techniques for automatically generating the real-time expert system from those models. Some of those techniques have just been borrowed from the literature, but we had to modify or invent other techniques which simply did not exist. We also discuss two important problems, which are often underestimated in the artificial intelligence literature: size, and errors. Our architecture, which could be used in other applications, combines the advantages of the model-based approach with the efficiency requirements of real-time applications, while in general model-based approaches present serious drawbacks on this point

Compiling models into real-time systems

International Nuclear Information System (INIS)

Dormoy, J.L.; Cherriaux, F.; Ancelin, J.

1992-08-01

This paper presents an architecture for building real-time systems from models, and model-compiling techniques. This has been applied for building a real-time model-base monitoring system for nuclear plants, called KSE, which is currently being used in two plants in France. We describe how we used various artificial intelligence techniques for building it: a model-based approach, a logical model of its operation, a declarative implementation of these models, and original knowledge-compiling techniques for automatically generating the real-time expert system from those models. Some of those techniques have just been borrowed from the literature, but we had to modify or invent other techniques which simply did not exist. We also discuss two important problems, which are often underestimated in the artificial intelligence literature: size, and errors. Our architecture, which could be used in other applications, combines the advantages of the model-based approach with the efficiency requirements of real-time applications, while in general model-based approaches present serious drawbacks on this point

Application of Real Time Models Updating in ABO Central Field

International Nuclear Information System (INIS)

Heikal, S.; Adewale, D.; Doghmi, A.; Augustine, U.

2003-01-01

ABO central field is the first deep offshore oil production in Nigeria located in OML 125 (ex-OPL316). The field was developed in a water depth of between 500 and 800 meters. Deep-water development requires much faster data handling and model updates in order to make the best possible technical decision. This required an easy way to incorporate the latest information and dynamic update of the reservoir model enabling real time reservoir management. The paper aims at discussing the benefits of real time static and dynamic model update and illustrates with a horizontal well example how this update was beneficial prior and during the drilling operation minimizing the project CAPEX Prior to drilling, a 3D geological model was built based on seismic and offset wells' data. The geological model was updated twice, once after the pilot hole drilling and then after reaching the landing point and prior drilling the horizontal section .Forward modeling ws made was well using the along the planned trajectory. During the drilling process both geo- steering and LWD data were loaded in real time to the 3D modeling software. The data was analyzed and compared with the predicted model. The location of markers was changed as drilling progressed and the entire 3D Geological model was rapidly updated. The target zones were revaluated in the light of the new model updates. Recommendations were communicated to the field, and the well trajectory was modified to take into account the new information. The combination of speed, flexibility and update-ability of the 3D modeling software enabled continues geological model update on which the asset team based their trajectory modification decisions throughout the drilling phase. The well was geo-steered through 7 meters thickness of sand. After the drilling, the testing showed excellent results with a productivity and fluid properties data were used to update the dynamic model reviewing the well production plateau providing optimum reservoir

A real-time extension of density matrix embedding theory for non-equilibrium electron dynamics

Science.gov (United States)

Kretchmer, Joshua S.; Chan, Garnet Kin-Lic

2018-02-01

We introduce real-time density matrix embedding theory (DMET), a dynamical quantum embedding theory for computing non-equilibrium electron dynamics in strongly correlated systems. As in the previously developed static DMET, real-time DMET partitions the system into an impurity corresponding to the region of interest coupled to the surrounding environment, which is efficiently represented by a quantum bath of the same size as the impurity. In this work, we focus on a simplified single-impurity time-dependent formulation as a first step toward a multi-impurity theory. The equations of motion of the coupled impurity and bath embedding problem are derived using the time-dependent variational principle. The accuracy of real-time DMET is compared to that of time-dependent complete active space self-consistent field (TD-CASSCF) theory and time-dependent Hartree-Fock (TDHF) theory for a variety of quantum quenches in the single impurity Anderson model (SIAM), in which the Hamiltonian is suddenly changed (quenched) to induce a non-equilibrium state. Real-time DMET shows a marked improvement over the mean-field TDHF, converging to the exact answer even in the non-trivial Kondo regime of the SIAM. However, as expected from analogous behavior in static DMET, the constrained structure of the real-time DMET wavefunction leads to a slower convergence with respect to active space size, in the single-impurity formulation, relative to TD-CASSCF. Our initial results suggest that real-time DMET provides a promising framework to simulate non-equilibrium electron dynamics in which strong electron correlation plays an important role, and lays the groundwork for future multi-impurity formulations.

Electron-phonon thermalization in a scalable method for real-time quantum dynamics

Science.gov (United States)

Rizzi, Valerio; Todorov, Tchavdar N.; Kohanoff, Jorge J.; Correa, Alfredo A.

2016-01-01

We present a quantum simulation method that follows the dynamics of out-of-equilibrium many-body systems of electrons and oscillators in real time. Its cost is linear in the number of oscillators and it can probe time scales from attoseconds to hundreds of picoseconds. Contrary to Ehrenfest dynamics, it can thermalize starting from a variety of initial conditions, including electronic population inversion. While an electronic temperature can be defined in terms of a nonequilibrium entropy, a Fermi-Dirac distribution in general emerges only after thermalization. These results can be used to construct a kinetic model of electron-phonon equilibration based on the explicit quantum dynamics.

A system for EPID-based real-time treatment delivery verification during dynamic IMRT treatment.

Science.gov (United States)

Fuangrod, Todsaporn; Woodruff, Henry C; van Uytven, Eric; McCurdy, Boyd M C; Kuncic, Zdenka; O'Connor, Daryl J; Greer, Peter B

2013-09-01

To design and develop a real-time electronic portal imaging device (EPID)-based delivery verification system for dynamic intensity modulated radiation therapy (IMRT) which enables detection of gross treatment delivery errors before delivery of substantial radiation to the patient. The system utilizes a comprehensive physics-based model to generate a series of predicted transit EPID image frames as a reference dataset and compares these to measured EPID frames acquired during treatment. The two datasets are using MLC aperture comparison and cumulative signal checking techniques. The system operation in real-time was simulated offline using previously acquired images for 19 IMRT patient deliveries with both frame-by-frame comparison and cumulative frame comparison. Simulated error case studies were used to demonstrate the system sensitivity and performance. The accuracy of the synchronization method was shown to agree within two control points which corresponds to approximately ∼1% of the total MU to be delivered for dynamic IMRT. The system achieved mean real-time gamma results for frame-by-frame analysis of 86.6% and 89.0% for 3%, 3 mm and 4%, 4 mm criteria, respectively, and 97.9% and 98.6% for cumulative gamma analysis. The system can detect a 10% MU error using 3%, 3 mm criteria within approximately 10 s. The EPID-based real-time delivery verification system successfully detected simulated gross errors introduced into patient plan deliveries in near real-time (within 0.1 s). A real-time radiation delivery verification system for dynamic IMRT has been demonstrated that is designed to prevent major mistreatments in modern radiation therapy.

Key Technologies and Applications of Satellite and Sensor Web-coupled Real-time Dynamic Web Geographic Information System

Directory of Open Access Journals (Sweden)

CHEN Nengcheng

2017-10-01

Full Text Available The geo-spatial information service has failed to reflect the live status of spot and meet the needs of integrated monitoring and real-time information for a long time. To tackle the problems in observation sharing and integrated management of space-borne, air-borne, and ground-based platforms and efficient service of spatio-temporal information, an observation sharing model was proposed. The key technologies in real-time dynamic geographical information system (GIS including maximum spatio-temporal coverage-based optimal layout of earth-observation sensor Web, task-driven and feedback-based control, real-time access of streaming observations, dynamic simulation, warning and decision support were detailed. An real-time dynamic Web geographical information system (WebGIS named GeoSensor and its applications in sensing and management of spatio-temporal information of Yangtze River basin including navigation, flood prevention, and power generation were also introduced.

Conversion and Validation of Distribution System Model from a QSTS-Based Tool to a Real-Time Dynamic Phasor Simulator

Energy Technology Data Exchange (ETDEWEB)

Chamana, Manohar; Prabakar, Kumaraguru; Palmintier, Bryan; Baggu, Murali M.

2017-05-11

A software process is developed to convert distribution network models from a quasi-static time-series tool (OpenDSS) to a real-time dynamic phasor simulator (ePHASORSIM). The description of this process in this paper would be helpful for researchers who intend to perform similar conversions. The converter could be utilized directly by users of real-time simulators who intend to perform software-in-the-loop or hardware-in-the-loop tests on large distribution test feeders for a range of use cases, including testing functions of advanced distribution management systems against a simulated distribution system. In the future, the developers intend to release the conversion tool as open source to enable use by others.

A system for EPID-based real-time treatment delivery verification during dynamic IMRT treatment

Energy Technology Data Exchange (ETDEWEB)

Fuangrod, Todsaporn [Faculty of Engineering and Built Environment, School of Electrical Engineering and Computer Science, the University of Newcastle, NSW 2308 (Australia); Woodruff, Henry C.; O’Connor, Daryl J. [Faculty of Science and IT, School of Mathematical and Physical Sciences, the University of Newcastle, NSW 2308 (Australia); Uytven, Eric van; McCurdy, Boyd M. C. [Division of Medical Physics, CancerCare Manitoba, 675 McDermot Avenue, Winnipeg, Manitoba R3E 0V9 (Canada); Department of Physics and Astronomy, University of Manitoba, Winnipeg, Manitoba R3T 2N2 (Canada); Department of Radiology, University of Manitoba, Winnipeg, Manitoba R3T 2N2 (Canada); Kuncic, Zdenka [School of Physics, University of Sydney, Sydney, NSW 2006 (Australia); Greer, Peter B. [Faculty of Science and IT, School of Mathematical and Physical Sciences, the University of Newcastle, NSW 2308, Australia and Department of Radiation Oncology, Calvary Mater Newcastle Hospital, Locked Bag 7, Hunter region Mail Centre, Newcastle, NSW 2310 (Australia)

2013-09-15

Purpose: To design and develop a real-time electronic portal imaging device (EPID)-based delivery verification system for dynamic intensity modulated radiation therapy (IMRT) which enables detection of gross treatment delivery errors before delivery of substantial radiation to the patient.Methods: The system utilizes a comprehensive physics-based model to generate a series of predicted transit EPID image frames as a reference dataset and compares these to measured EPID frames acquired during treatment. The two datasets are using MLC aperture comparison and cumulative signal checking techniques. The system operation in real-time was simulated offline using previously acquired images for 19 IMRT patient deliveries with both frame-by-frame comparison and cumulative frame comparison. Simulated error case studies were used to demonstrate the system sensitivity and performance.Results: The accuracy of the synchronization method was shown to agree within two control points which corresponds to approximately ∼1% of the total MU to be delivered for dynamic IMRT. The system achieved mean real-time gamma results for frame-by-frame analysis of 86.6% and 89.0% for 3%, 3 mm and 4%, 4 mm criteria, respectively, and 97.9% and 98.6% for cumulative gamma analysis. The system can detect a 10% MU error using 3%, 3 mm criteria within approximately 10 s. The EPID-based real-time delivery verification system successfully detected simulated gross errors introduced into patient plan deliveries in near real-time (within 0.1 s).Conclusions: A real-time radiation delivery verification system for dynamic IMRT has been demonstrated that is designed to prevent major mistreatments in modern radiation therapy.

A system for EPID-based real-time treatment delivery verification during dynamic IMRT treatment

International Nuclear Information System (INIS)

Fuangrod, Todsaporn; Woodruff, Henry C.; O’Connor, Daryl J.; Uytven, Eric van; McCurdy, Boyd M. C.; Kuncic, Zdenka; Greer, Peter B.

2013-01-01

Purpose: To design and develop a real-time electronic portal imaging device (EPID)-based delivery verification system for dynamic intensity modulated radiation therapy (IMRT) which enables detection of gross treatment delivery errors before delivery of substantial radiation to the patient.Methods: The system utilizes a comprehensive physics-based model to generate a series of predicted transit EPID image frames as a reference dataset and compares these to measured EPID frames acquired during treatment. The two datasets are using MLC aperture comparison and cumulative signal checking techniques. The system operation in real-time was simulated offline using previously acquired images for 19 IMRT patient deliveries with both frame-by-frame comparison and cumulative frame comparison. Simulated error case studies were used to demonstrate the system sensitivity and performance.Results: The accuracy of the synchronization method was shown to agree within two control points which corresponds to approximately ∼1% of the total MU to be delivered for dynamic IMRT. The system achieved mean real-time gamma results for frame-by-frame analysis of 86.6% and 89.0% for 3%, 3 mm and 4%, 4 mm criteria, respectively, and 97.9% and 98.6% for cumulative gamma analysis. The system can detect a 10% MU error using 3%, 3 mm criteria within approximately 10 s. The EPID-based real-time delivery verification system successfully detected simulated gross errors introduced into patient plan deliveries in near real-time (within 0.1 s).Conclusions: A real-time radiation delivery verification system for dynamic IMRT has been demonstrated that is designed to prevent major mistreatments in modern radiation therapy

Real Time Emulation of Dynamic Tariff for Congestion Management in Distribution Networks

DEFF Research Database (Denmark)

Rasmussen, Theis Bo; Wu, Qiuwei; Huang, Shaojun

2016-01-01

This paper presents the real time evaluation of the dynamic tariff (DT) method for alleviating congestion in a distribution networks with high penetration of distributed energy resources (DERs). The DT method is implemented in a real time digital testing platform that emulates a real distribution...

A Sarsa(λ)-based control model for real-time traffic light coordination.

Science.gov (United States)

Zhou, Xiaoke; Zhu, Fei; Liu, Quan; Fu, Yuchen; Huang, Wei

2014-01-01

Traffic problems often occur due to the traffic demands by the outnumbered vehicles on road. Maximizing traffic flow and minimizing the average waiting time are the goals of intelligent traffic control. Each junction wants to get larger traffic flow. During the course, junctions form a policy of coordination as well as constraints for adjacent junctions to maximize their own interests. A good traffic signal timing policy is helpful to solve the problem. However, as there are so many factors that can affect the traffic control model, it is difficult to find the optimal solution. The disability of traffic light controllers to learn from past experiences caused them to be unable to adaptively fit dynamic changes of traffic flow. Considering dynamic characteristics of the actual traffic environment, reinforcement learning algorithm based traffic control approach can be applied to get optimal scheduling policy. The proposed Sarsa(λ)-based real-time traffic control optimization model can maintain the traffic signal timing policy more effectively. The Sarsa(λ)-based model gains traffic cost of the vehicle, which considers delay time, the number of waiting vehicles, and the integrated saturation from its experiences to learn and determine the optimal actions. The experiment results show an inspiring improvement in traffic control, indicating the proposed model is capable of facilitating real-time dynamic traffic control.

A Sarsa(λ-Based Control Model for Real-Time Traffic Light Coordination

Directory of Open Access Journals (Sweden)

Xiaoke Zhou

2014-01-01

Full Text Available Traffic problems often occur due to the traffic demands by the outnumbered vehicles on road. Maximizing traffic flow and minimizing the average waiting time are the goals of intelligent traffic control. Each junction wants to get larger traffic flow. During the course, junctions form a policy of coordination as well as constraints for adjacent junctions to maximize their own interests. A good traffic signal timing policy is helpful to solve the problem. However, as there are so many factors that can affect the traffic control model, it is difficult to find the optimal solution. The disability of traffic light controllers to learn from past experiences caused them to be unable to adaptively fit dynamic changes of traffic flow. Considering dynamic characteristics of the actual traffic environment, reinforcement learning algorithm based traffic control approach can be applied to get optimal scheduling policy. The proposed Sarsa(λ-based real-time traffic control optimization model can maintain the traffic signal timing policy more effectively. The Sarsa(λ-based model gains traffic cost of the vehicle, which considers delay time, the number of waiting vehicles, and the integrated saturation from its experiences to learn and determine the optimal actions. The experiment results show an inspiring improvement in traffic control, indicating the proposed model is capable of facilitating real-time dynamic traffic control.

Real-Time Dynamics in U(1 Lattice Gauge Theories with Tensor Networks

Directory of Open Access Journals (Sweden)

T. Pichler

2016-03-01

Full Text Available Tensor network algorithms provide a suitable route for tackling real-time-dependent problems in lattice gauge theories, enabling the investigation of out-of-equilibrium dynamics. We analyze a U(1 lattice gauge theory in (1+1 dimensions in the presence of dynamical matter for different mass and electric-field couplings, a theory akin to quantum electrodynamics in one dimension, which displays string breaking: The confining string between charges can spontaneously break during quench experiments, giving rise to charge-anticharge pairs according to the Schwinger mechanism. We study the real-time spreading of excitations in the system by means of electric-field and particle fluctuations. We determine a dynamical state diagram for string breaking and quantitatively evaluate the time scales for mass production. We also show that the time evolution of the quantum correlations can be detected via bipartite von Neumann entropies, thus demonstrating that the Schwinger mechanism is tightly linked to entanglement spreading. To present a variety of possible applications of this simulation platform, we show how one could follow the real-time scattering processes between mesons and the creation of entanglement during scattering processes. Finally, we test the quality of quantum simulations of these dynamics, quantifying the role of possible imperfections in cold atoms, trapped ions, and superconducting circuit systems. Our results demonstrate how entanglement properties can be used to deepen our understanding of basic phenomena in the real-time dynamics of gauge theories such as string breaking and collisions.

Nonadiabatic Dynamics for Electrons at Second-Order: Real-Time TDDFT and OSCF2.

Science.gov (United States)

Nguyen, Triet S; Parkhill, John

2015-07-14

We develop a new model to simulate nonradiative relaxation and dephasing by combining real-time Hartree-Fock and density functional theory (DFT) with our recent open-systems theory of electronic dynamics. The approach has some key advantages: it has been systematically derived and properly relaxes noninteracting electrons to a Fermi-Dirac distribution. This paper combines the new dissipation theory with an atomistic, all-electron quantum chemistry code and an atom-centered model of the thermal environment. The environment is represented nonempirically and is dependent on molecular structure in a nonlocal way. A production quality, O(N(3)) closed-shell implementation of our theory applicable to realistic molecular systems is presented, including timing information. This scaling implies that the added cost of our nonadiabatic relaxation model, time-dependent open self-consistent field at second order (OSCF2), is computationally inexpensive, relative to adiabatic propagation of real-time time-dependent Hartree-Fock (TDHF) or time-dependent density functional theory (TDDFT). Details of the implementation and numerical algorithm, including factorization and efficiency, are discussed. We demonstrate that OSCF2 approaches the stationary self-consistent field (SCF) ground state when the gap is large relative to k(b)T. The code is used to calculate linear-response spectra including the effects of bath dynamics. Finally, we show how our theory of finite-temperature relaxation can be used to correct ground-state DFT calculations.

Conversion and Validation of Distribution System Model from a QSTS-Based Tool to a Real-Time Dynamic Phasor Simulator: Preprint

Energy Technology Data Exchange (ETDEWEB)

Chamana, Manohar; Prabakar, Kumaraguru; Palmintier, Bryan; Baggu, Murali M.

2017-04-11

A software process is developed to convert distribution network models from a quasi-static time-series tool (OpenDSS) to a real-time dynamic phasor simulator (ePHASORSIM). The description of this process in this paper would be helpful for researchers who intend to perform similar conversions. The converter could be utilized directly by users of real-time simulators who intend to perform software-in-the-loop or hardware-in-the-loop tests on large distribution test feeders for a range of use cases, including testing functions of advanced distribution management systems against a simulated distribution system. In the future, the developers intend to release the conversion tool as open source to enable use by others.

Improved real-time dynamics from imaginary frequency lattice simulations

Directory of Open Access Journals (Sweden)

Pawlowski Jan M.

2018-01-01

Full Text Available The computation of real-time properties, such as transport coefficients or bound state spectra of strongly interacting quantum fields in thermal equilibrium is a pressing matter. Since the sign problem prevents a direct evaluation of these quantities, lattice data needs to be analytically continued from the Euclidean domain of the simulation to Minkowski time, in general an ill-posed inverse problem. Here we report on a novel approach to improve the determination of real-time information in the form of spectral functions by setting up a simulation prescription in imaginary frequencies. By carefully distinguishing between initial conditions and quantum dynamics one obtains access to correlation functions also outside the conventional Matsubara frequencies. In particular the range between ω0 and ω1 = 2πT, which is most relevant for the inverse problem may be more highly resolved. In combination with the fact that in imaginary frequencies the kernel of the inverse problem is not an exponential but only a rational function we observe significant improvements in the reconstruction of spectral functions, demonstrated in a simple 0+1 dimensional scalar field theory toy model.

Improved real-time dynamics from imaginary frequency lattice simulations

Science.gov (United States)

Pawlowski, Jan M.; Rothkopf, Alexander

2018-03-01

The computation of real-time properties, such as transport coefficients or bound state spectra of strongly interacting quantum fields in thermal equilibrium is a pressing matter. Since the sign problem prevents a direct evaluation of these quantities, lattice data needs to be analytically continued from the Euclidean domain of the simulation to Minkowski time, in general an ill-posed inverse problem. Here we report on a novel approach to improve the determination of real-time information in the form of spectral functions by setting up a simulation prescription in imaginary frequencies. By carefully distinguishing between initial conditions and quantum dynamics one obtains access to correlation functions also outside the conventional Matsubara frequencies. In particular the range between ω0 and ω1 = 2πT, which is most relevant for the inverse problem may be more highly resolved. In combination with the fact that in imaginary frequencies the kernel of the inverse problem is not an exponential but only a rational function we observe significant improvements in the reconstruction of spectral functions, demonstrated in a simple 0+1 dimensional scalar field theory toy model.

Dynamic Beam Solutions for Real-Time Simulation and Control Development of Flexible Rockets

Science.gov (United States)

Su, Weihua; King, Cecilia K.; Clark, Scott R.; Griffin, Edwin D.; Suhey, Jeffrey D.; Wolf, Michael G.

2016-01-01

In this study, flexible rockets are structurally represented by linear beams. Both direct and indirect solutions of beam dynamic equations are sought to facilitate real-time simulation and control development for flexible rockets. The direct solution is completed by numerically integrate the beam structural dynamic equation using an explicit Newmark-based scheme, which allows for stable and fast transient solutions to the dynamics of flexile rockets. Furthermore, in the real-time operation, the bending strain of the beam is measured by fiber optical sensors (FOS) at intermittent locations along the span, while both angular velocity and translational acceleration are measured at a single point by the inertial measurement unit (IMU). Another study in this paper is to find the analytical and numerical solutions of the beam dynamics based on the limited measurement data to facilitate the real-time control development. Numerical studies demonstrate the accuracy of these real-time solutions to the beam dynamics. Such analytical and numerical solutions, when integrated with data processing and control algorithms and mechanisms, have the potential to increase launch availability by processing flight data into the flexible launch vehicle's control system.

Transient response of a five-region nonequilibrium real-time pressurizer model

International Nuclear Information System (INIS)

Fakory, M.R.; Seifaee, F.

1987-01-01

Recent accidents at nuclear power plants in the US and abroad have prompted accurate analysis and simulation of the plant systems and the training of reactor operators on plant-specific simulators that are equipped with the simulation models. Consequently, several models for real-time and off-time simulation of nuclear reactor systems, with various levels of accuracy and simulation fidelity, have been introduced. Experience with power plant simulation demonstrates that in order to realistically predict and simulate reactor responses during unanticipated transients, it is necessary to equip the simulation model with a multielement pressurizer model. The objective of this paper is to present the results of a five-region drift-flux-based pressurizer model, which has been developed for integration with real-time training simulators. A comparison between the plant data and the results of the nonequilibrium pressurizer model demonstrates that the model is well capable of close simulation of dynamic behavior of the pressurizer system

Tool-driven Design and Automated Parameterization for Real-time Generic Drivetrain Models

Directory of Open Access Journals (Sweden)

Schwarz Christina

2015-01-01

Full Text Available Real-time dynamic drivetrain modeling approaches have a great potential for development cost reduction in the automotive industry. Even though real-time drivetrain models are available, these solutions are specific to single transmission topologies. In this paper an environment for parameterization of a solution is proposed based on a generic method applicable to all types of gear transmission topologies. This enables tool-guided modeling by non- experts in the fields of mechanic engineering and control theory leading to reduced development and testing efforts. The approach is demonstrated for an exemplary automatic transmission using the environment for automated parameterization. Finally, the parameterization is validated via vehicle measurement data.

Real-time advanced nuclear reactor core model

International Nuclear Information System (INIS)

Koclas, J.; Friedman, F.; Paquette, C.; Vivier, P.

1990-01-01

The paper describes a multi-nodal advanced nuclear reactor core model. The model is based on application of modern equivalence theory to the solution of neutron diffusion equation in real time employing the finite differences method. The use of equivalence theory allows the application of the finite differences method to cores divided into hundreds of nodes, as opposed to the much finer divisions (in the order of ten thousands of nodes) where the unmodified method is currently applied. As a result the model can be used for modelling of the core kinetics for real time full scope training simulators. Results of benchmarks, validate the basic assumptions of the model and its applicability to real-time simulation. (orig./HP)

Model-Checking Real-Time Control Programs

DEFF Research Database (Denmark)

Iversen, T. K.; Kristoffersen, K. J.; Larsen, Kim Guldstrand

2000-01-01

In this paper, we present a method for automatic verification of real-time control programs running on LEGO(R) RCX(TM) bricks using the verification tool UPPALL. The control programs, consisting of a number of tasks running concurrently, are automatically translated into the mixed automata model...... of UPPAAL. The fixed scheduling algorithm used by the LEGO(R) RCX(TM) processor is modeled in UPPALL, and supply of similar (sufficient) timed automata models for the environment allows analysis of the overall real-time system using the tools of UPPALL. To illustrate our technique for sorting LEGO(R) bricks...

Dynamic fiber Bragg grating strain sensor interrogation with real-time measurement

Science.gov (United States)

Park, Jinwoo; Kwon, Yong Seok; Ko, Myeong Ock; Jeon, Min Yong

2017-11-01

We demonstrate a 1550 nm band resonance Fourier-domain mode-locked (FDML) fiber laser with fiber Bragg grating (FBG) array. Using the FDML fiber laser, we successfully demonstrate real-time monitoring of dynamic FBG strain sensor interrogation for structural health monitoring. The resonance FDML fiber laser consists of six multiplexed FBGs, which are arranged in series with delay fiber lengths. It is operated by driving the fiber Fabry-Perot tunable filter (FFP-TF) with a sinusoidal waveform at a frequency corresponding to the round-trip time of the laser cavity. Each FBG forms a laser cavity independently in the FDML fiber laser because the light travels different length for each FBG. The very closely positioned two FBGs in a pair are operated simultaneously with a frequency in the FDML fiber laser. The spatial positions of the sensing pair can be distinguished from the variation of the applied frequency to the FFP-TF. One of the FBGs in the pair is used as a reference signal and the other one is fixed on the piezoelectric transducer stack to apply the dynamic strain. We successfully achieve real-time measurement of the abrupt change of the frequencies applied to the FBG without any signal processing delay. The real-time monitoring system is displayed simultaneously on the monitor for the variation of the two peaks, the modulation interval of the two peaks, and their fast Fourier transform spectrum. The frequency resolution of the dynamic variation could reach up to 0.5 Hz for 2 s integration time. It depends on the integration time to measure the dynamic variation. We believe that the real-time monitoring system will have a potential application for structural health monitoring.

Real-time dynamic analysis for complete loop of direct steam generation solar trough collector

International Nuclear Information System (INIS)

Guo, Su; Liu, Deyou; Chu, Yinghao; Chen, Xingying; Shen, Bingbing; Xu, Chang; Zhou, Ling; Wang, Pei

2016-01-01

Highlights: • A nonlinear distribution parameter dynamic model has been developed. • Real-time local heat transfer coefficient and friction coefficient are adopted. • The dynamic behavior of the solar trough collector loop are simulated. • High-frequency chattering of outlet fluid flow are analyzed and modeled. • Irradiance disturbance at subcooled water region generates larger influence. - Abstract: Direct steam generation is a potential approach to further reduce the levelized electricity cost of solar trough. Dynamic modeling of the collector loop is essential for operation and control of direct steam generation solar trough. However, the dynamic behavior of fluid based on direct steam generation is complex because of the two-phase flow in the pipeline. In this work, a nonlinear distribution parameter model has been developed to model the dynamic behaviors of direct steam generation parabolic trough collector loops under either full or partial solar irradiance disturbance. Compared with available dynamic model, the proposed model possesses two advantages: (1) real-time local values of heat transfer coefficient and friction resistance coefficient, and (2) considering of the complete loop of collectors, including subcooled water region, two-phase flow region and superheated steam region. The proposed model has shown superior performance, particularly in case of sensitivity study of fluid parameters when the pipe is partially shaded. The proposed model has been validated using experimental data from Solar Thermal Energy Laboratory of University of New South Wales, with an outlet fluid temperature relative error of only 1.91%. The validation results show that: (1) The proposed model successfully outperforms two reference models in predicting the behavior of direct steam generation solar trough. (2) The model theoretically predicts that, during solar irradiance disturbance, the discontinuities of fluid physical property parameters and the moving back and

Design base transient analysis using the real-time nuclear reactor simulator model

International Nuclear Information System (INIS)

Tien, K.K.; Yakura, S.J.; Morin, J.P.; Gregory, M.V.

1987-01-01

A real-time simulation model has been developed to describe the dynamic response of all major systems in a nuclear process reactor. The model consists of a detailed representation of all hydraulic components in the external coolant circulating loops consisting of piping, valves, pumps and heat exchangers. The reactor core is described by a three-dimensional neutron kinetics model with detailed representation of assembly coolant and moderator thermal hydraulics. The models have been developed to support a real-time training simulator, therefore, they reproduce system parameters characteristic of steady state normal operation with high precision. The system responses for postulated severe transients such as large pipe breaks, loss of pumping power, piping leaks, malfunctions in control rod insertion, and emergency injection of neutron absorber are calculated to be in good agreement with reference safety analyses. Restrictions were imposed by the requirement that the resulting code be able to run in real-time with sufficient spare time to allow interfacing with secondary systems and simulator hardware. Due to hardware set-up and real plant instrumentation, simplifications due to symmetry were not allowed. The resulting code represents a coarse-node engineering model in which the level of detail has been tailored to the available computing power of a present generation super-minicomputer. Results for several significant transients, as calculated by the real-time model, are compared both to actual plant data and to results generated by fine-mesh analysis codes

Design base transient analysis using the real-time nuclear reactor simulator model

International Nuclear Information System (INIS)

Tien, K.K.; Yakura, S.J.; Morin, J.P.; Gregory, M.V.

1987-01-01

A real-time simulation model has been developed to describe the dynamic response of all major systems in a nuclear process reactor. The model consists of a detailed representation of all hydraulic components in the external coolant circulating loops consisting of piping, valves, pumps and heat exchangers. The reactor core is described by a three-dimensional neutron kinetics model with detailed representation of assembly coolant and mode-rator thermal hydraulics. The models have been developed to support a real-time training simulator, therefore, they reproduce system parameters characteristic of steady state normal operation with high precision. The system responses for postulated severe transients such as large pipe breaks, loss of pumping power, piping leaks, malfunctions in control rod insertion, and emergency injection of neutron absorber are calculated to be in good agreement with reference safety analyses. Restrictions were imposed by the requirement that the resulting code be able to run in real-time with sufficient spare time to allow interfacing with secondary systems and simulator hardware. Due to hardware set-up and real plant instrumentation, simplifications due to symmetry were not allowed. The resulting code represents a coarse-node engineering model in which the level of detail has been tailored to the available computing power of a present generation super-minicomputer. Results for several significant transients, as calculated by the real-time model, are compared both to actual plant data and to results generated by fine-mesh analysis codes

FPGA-Based Real Time, Multichannel Emulated-Digital Retina Model Implementation

Directory of Open Access Journals (Sweden)

Zsolt Vörösházi

2009-01-01

Full Text Available The function of the low-level image processing that takes place in the biological retina is to compress only the relevant visual information to a manageable size. The behavior of the layers and different channels of the neuromorphic retina has been successfully modeled by cellular neural/nonlinear networks (CNNs. In this paper, we present an extended, application-specific emulated-digital CNN-universal machine (UM architecture to compute the complex dynamic of this mammalian retina in video real time. The proposed emulated-digital implementation of multichannel retina model is compared to the previously developed models from three key aspects, which are processing speed, number of physical cells, and accuracy. Our primary aim was to build up a simple, real-time test environment with camera input and display output in order to mimic the behavior of retina model implementation on emulated digital CNN by using low-cost, moderate-sized field-programmable gate array (FPGA architectures.

Optical Response of Warm Dense Matter Using Real-Time Electron Dynamics

Science.gov (United States)

Baczewski, Andrew; Shulenburger, Luke; Desjarlais, Michael; Magyar, Rudolph

2014-03-01

The extreme temperatures and solid-like densities in warm dense matter present a unique challenge for theory, wherein neither conventional models from condensed matter nor plasma physics capture all of the relevant phenomenology. While Kubo-Greenwood DFT calculations have proven capable of reproducing optical properties of WDM, they require a significant number of virtual orbitals to reach convergence due to their perturbative nature. Real-time TDDFT presents a complementary framework with a number of computationally favorable properties, including reduced cost complexity and better scalability, and has been used to reproduce the optical response of finite and ordered extended systems. We will describe the use of Ehrenfest-TDDFT to evolve coupled electron-nuclear dynamics in WDM systems, and the subsequent evaluation of optical response functions from the real-time electron dynamics. The advantages and disadvantages of this approach will be discussed relative to the current state-of-the-art. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Security Administration under contract DE-AC04-94AL85000.

Solving Algebraic Riccati Equation Real Time for Integrated Vehicle Dynamics Control

NARCIS (Netherlands)

Kunnappillil Madhusudhanan, A; Corno, M.; Bonsen, B.; Holweg, E.

2012-01-01

In this paper we present a comparison study of different computational methods to implement State Dependent Riccati Equation (SDRE) based control in real time for a vehicle dynamics control application. Vehicles are mechatronic systems with nonlinear dynamics. One of the promising nonlinear control

Architecture for dynamically reconfigurable real-time lossless compression

Science.gov (United States)

Carter, Alison J.; Audsley, Neil C.

2004-05-01

Image compression is a computationally intensive task, which can be undertaken most efficiently by dedicated hardware. If a portable device is to carry out real-time compression on a variety of image types, then it may be useful to reconfigure the circuitry dynamically. Using commercial off-the shelf (COTS) chips, reconfiguration is usually implemented by a complete re-load from memory, but it is also possible to perform a partial reconfiguration. This work studies the use of programmable hardware devices to implement the lossless JPEG compression algorithm in real-time on a stream of independent image frames. The data rate is faster than can be compressed serially in hardware by a single processor, so the operation is split amongst several processors. These are implemented as programmable circuits, together with necessary buffering of input and output data. The timing of input and output, bearing in mind the different, and context-dependent amounts of data due to Huffman coding, is analyzed using storage-timing graphs. Because there may be differing parameters from one frame to the next, several different configurations are prepared and stored, ready to load as required. The scheduling of these reconfigurations, and the distribution/recombination of data streams is studied, giving an analysis of the real-time performance.

Aircraft Fault Detection Using Real-Time Frequency Response Estimation

Science.gov (United States)

Grauer, Jared A.

2016-01-01

A real-time method for estimating time-varying aircraft frequency responses from input and output measurements was demonstrated. The Bat-4 subscale airplane was used with NASA Langley Research Center's AirSTAR unmanned aerial flight test facility to conduct flight tests and collect data for dynamic modeling. Orthogonal phase-optimized multisine inputs, summed with pilot stick and pedal inputs, were used to excite the responses. The aircraft was tested in its normal configuration and with emulated failures, which included a stuck left ruddervator and an increased command path latency. No prior knowledge of a dynamic model was used or available for the estimation. The longitudinal short period dynamics were investigated in this work. Time-varying frequency responses and stability margins were tracked well using a 20 second sliding window of data, as compared to a post-flight analysis using output error parameter estimation and a low-order equivalent system model. This method could be used in a real-time fault detection system, or for other applications of dynamic modeling such as real-time verification of stability margins during envelope expansion tests.

Dynamic quality of service model for improving performance of multimedia real-time transmission in industrial networks.

Science.gov (United States)

Gopalakrishnan, Ravichandran C; Karunakaran, Manivannan

2014-01-01

Nowadays, quality of service (QoS) is very popular in various research areas like distributed systems, multimedia real-time applications and networking. The requirements of these systems are to satisfy reliability, uptime, security constraints and throughput as well as application specific requirements. The real-time multimedia applications are commonly distributed over the network and meet various time constraints across networks without creating any intervention over control flows. In particular, video compressors make variable bit-rate streams that mismatch the constant-bit-rate channels typically provided by classical real-time protocols, severely reducing the efficiency of network utilization. Thus, it is necessary to enlarge the communication bandwidth to transfer the compressed multimedia streams using Flexible Time Triggered- Enhanced Switched Ethernet (FTT-ESE) protocol. FTT-ESE provides automation to calculate the compression level and change the bandwidth of the stream. This paper focuses on low-latency multimedia transmission over Ethernet with dynamic quality-of-service (QoS) management. This proposed framework deals with a dynamic QoS for multimedia transmission over Ethernet with FTT-ESE protocol. This paper also presents distinct QoS metrics based both on the image quality and network features. Some experiments with recorded and live video streams show the advantages of the proposed framework. To validate the solution we have designed and implemented a simulator based on the Matlab/Simulink, which is a tool to evaluate different network architecture using Simulink blocks.

Model-based framework for multi-axial real-time hybrid simulation testing

Science.gov (United States)

Fermandois, Gaston A.; Spencer, Billie F.

2017-10-01

Real-time hybrid simulation is an efficient and cost-effective dynamic testing technique for performance evaluation of structural systems subjected to earthquake loading with rate-dependent behavior. A loading assembly with multiple actuators is required to impose realistic boundary conditions on physical specimens. However, such a testing system is expected to exhibit significant dynamic coupling of the actuators and suffer from time lags that are associated with the dynamics of the servo-hydraulic system, as well as control-structure interaction (CSI). One approach to reducing experimental errors considers a multi-input, multi-output (MIMO) controller design, yielding accurate reference tracking and noise rejection. In this paper, a framework for multi-axial real-time hybrid simulation (maRTHS) testing is presented. The methodology employs a real-time feedback-feedforward controller for multiple actuators commanded in Cartesian coordinates. Kinematic transformations between actuator space and Cartesian space are derived for all six-degrees-offreedom of the moving platform. Then, a frequency domain identification technique is used to develop an accurate MIMO transfer function of the system. Further, a Cartesian-domain model-based feedforward-feedback controller is implemented for time lag compensation and to increase the robustness of the reference tracking for given model uncertainty. The framework is implemented using the 1/5th-scale Load and Boundary Condition Box (LBCB) located at the University of Illinois at Urbana- Champaign. To demonstrate the efficacy of the proposed methodology, a single-story frame subjected to earthquake loading is tested. One of the columns in the frame is represented physically in the laboratory as a cantilevered steel column. For realtime execution, the numerical substructure, kinematic transformations, and controllers are implemented on a digital signal processor. Results show excellent performance of the maRTHS framework when six

An Innovative Real-time Environment for Unified Deterministic and Stochastic Groundwater Modeling

Science.gov (United States)

Li, S.; Liu, Q.

2003-12-01

, and mass balance analyses. IGW continually provides and displays results that are intelligently processed, organized, overlaid, and displayed. It seamlessly and dynamically merges heterogeneous geo-spatial data into graphical images - integrating related data to reveal the complex interplay among the geology, hydrology and chemistry across multiple spatial and time scales. This unprecedented capability in real-time modeling, steering, integration, analysis, and visualization transforms the way we model and profoundly expands the utility of groundwater model as a tool for research, education, and professional investigation related to groundwater.

Network Dynamics with BrainX3: A Large-Scale Simulation of the Human Brain Network with Real-Time Interaction

OpenAIRE

Xerxes D. Arsiwalla; Riccardo eZucca; Alberto eBetella; Enrique eMartinez; David eDalmazzo; Pedro eOmedas; Gustavo eDeco; Gustavo eDeco; Paul F.M.J. Verschure; Paul F.M.J. Verschure

2015-01-01

BrainX3 is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX3 in real-time by perturbing brain regions with transient stimula...

Network dynamics with BrainX3: a large-scale simulation of the human brain network with real-time interaction

OpenAIRE

Arsiwalla, Xerxes D.; Zucca, Riccardo; Betella, Alberto; Martínez, Enrique, 1961-; Dalmazzo, David; Omedas, Pedro; Deco, Gustavo; Verschure, Paul F. M. J.

2015-01-01

BrainX3 is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX3 in real-time by perturbing brain regions with transient stimula...

Real-time management of a multipurpose water reservoir with a heteroscedastic inflow model

Science.gov (United States)

Pianosi, F.; Soncini-Sessa, R.

2009-10-01

Stochastic dynamic programming has been extensively used as a method for designing optimal regulation policies for water reservoirs. However, the potential of this method is dramatically reduced by its computational burden, which often forces to introduce strong approximations in the model of the system, especially in the description of the reservoir inflow. In this paper, an approach to partially remedy this problem is proposed and applied to a real world case study. It foresees solving the management problem on-line, using a reduced model of the system and the inflow forecast provided by a dynamic model. By doing so, all the hydrometeorological information that is available in real-time is fully exploited. The model here proposed for the inflow forecasting is a nonlinear, heteroscedastic model that provides both the expected value and the standard deviation of the inflow through dynamic relations. The effectiveness of such model for the purpose of the reservoir regulation is evaluated through simulation and comparison with the results provided by conventional homoscedastic inflow models.

Real-time physics-based 3D biped character animation using an inverted pendulum model.

Science.gov (United States)

Tsai, Yao-Yang; Lin, Wen-Chieh; Cheng, Kuangyou B; Lee, Jehee; Lee, Tong-Yee

2010-01-01

We present a physics-based approach to generate 3D biped character animation that can react to dynamical environments in real time. Our approach utilizes an inverted pendulum model to online adjust the desired motion trajectory from the input motion capture data. This online adjustment produces a physically plausible motion trajectory adapted to dynamic environments, which is then used as the desired motion for the motion controllers to track in dynamics simulation. Rather than using Proportional-Derivative controllers whose parameters usually cannot be easily set, our motion tracking adopts a velocity-driven method which computes joint torques based on the desired joint angular velocities. Physically correct full-body motion of the 3D character is computed in dynamics simulation using the computed torques and dynamical model of the character. Our experiments demonstrate that tracking motion capture data with real-time response animation can be achieved easily. In addition, physically plausible motion style editing, automatic motion transition, and motion adaptation to different limb sizes can also be generated without difficulty.

Real-Time Reactive Power Distribution in Microgrids by Dynamic Programing

DEFF Research Database (Denmark)

Levron, Yoash; Beck, Yuval; Katzir, Liran

2017-01-01

In this paper a new real-time optimization method for reactive power distribution in microgrids is proposed. The method enables location of a globally optimal distribution of reactive power under normal operating conditions. The method exploits the typical compact structure of microgrids to obtain...... combination of reactive powers, by means of dynamic programming. Since every single step involves a one-dimensional problem, the complexity of the solution is only linear with the number of clusters, and as a result, a globally optimal solution may be obtained in real time. The paper includes the results...

Study of Real-Time Programming for Simulation of Nuclear Reactor Dynamics

International Nuclear Information System (INIS)

Aliq; Widi Setiawan; Hendro Tjahjono

2003-01-01

Many aspects of real-time system are reviewed including the method, programming techniques, and its possibility to be applied in research reactor. The main point of real-time system is that it must designed to have a characteristics not only fast response but the most important is on-time response. In order to cover this requirements, real-time system need also a simple operating system consist of a kernel and application software. At the level of programming, real-time system require a modular approach, hard and soft time division and interprocess communications. The implementation can include some real-time (RT) operation system such as: RT-Linux, RT-OS9 and RT-Mat lab. Because of fast and on-time response requirements, if this system is going to be applied to research reactor, the transfer function model maybe more appropriate model compared to point kinetics model for the reason of computation time. (author)

Dynamic Subcarrier Allocation for Real-Time Traffic over Multiuser OFDM Systems

Directory of Open Access Journals (Sweden)

Li VictorOK

2009-01-01

Full Text Available A dynamic resource allocation algorithm to satisfy the packet delay requirements for real-time services, while maximizing the system capacity in multiuser orthogonal frequency division multiplexing (OFDM systems is introduced. Our proposed cross-layer algorithm, called Dynamic Subcarrier Allocation algorithm for Real-time Traffic (DSA-RT, consists of two interactive components. In the medium access control (MAC layer, the users' expected transmission rates in terms of the number of subcarriers per symbol and their corresponding transmission priorities are evaluated. With the above MAC-layer information and the detected subcarriers' channel gains, in the physical (PHY layer, a modified Kuhn-Munkres algorithm is developed to minimize the system power for a certain subcarrier allocation, then a PHY-layer resource allocation scheme is proposed to optimally allocate the subcarriers under the system signal-to-noise ratio (SNR and power constraints. In a system where the number of mobile users changes dynamically, our developed MAC-layer access control and removal schemes can guarantee the quality of service (QoS of the existing users in the system and fully utilize the bandwidth resource. The numerical results show that DSA-RT significantly improves the system performance in terms of the bandwidth efficiency and delay performance for real-time services.

Real time visualization of dynamic magnetic fields with a nanomagnetic ferrolens

Science.gov (United States)

Markoulakis, Emmanouil; Rigakis, Iraklis; Chatzakis, John; Konstantaras, Antonios; Antonidakis, Emmanuel

2018-04-01

Due to advancements in nanomagnetism and latest nanomagnetic materials and devices, a new potential field has been opened up for research and applications which was not possible before. We herein propose a new research field and application for nanomagnetism for the visualization of dynamic magnetic fields in real-time. In short, Nano Magnetic Vision. A new methodology, technique and apparatus were invented and prototyped in order to demonstrate and test this new application. As an application example the visualization of the dynamic magnetic field on a transmitting antenna was chosen. Never seen before high-resolution, photos and real-time color video revealing the actual dynamic magnetic field inside a transmitting radio antenna rod has been captured for the first time. The antenna rod is fed with six hundred volts, orthogonal pulses. This unipolar signal is in the very low frequency (i.e. VLF) range. The signal combined with an extremely short electrical length of the rod, ensures the generation of a relatively strong fluctuating magnetic field, analogue to the signal transmitted, along and inside the antenna. This field is induced into a ferrolens and becomes visible in real-time within the normal human eyes frequency spectrum. The name we have given to the new observation apparatus is, SPIONs Superparamagnetic Ferrolens Microscope (SSFM), a powerful passive scientific observation tool with many other potential applications in the near future.

Dynamic Web Expression for Near-real-time Sensor Networks

Science.gov (United States)

Lindquist, K. G.; Newman, R. L.; Nayak, A.; Vernon, F. L.; Nelson, C.; Hansen, T. S.; Yuen-Wong, R.

2003-12-01

As near-real-time sensor grids become more widespread, and processing systems based on them become more powerful, summarizing the raw and derived information products and delivering them to the end user become increasingly important both for ongoing monitoring and as a platform for cross-disciplinary research. We have re-engineered the dbrecenteqs program, which was designed to express real-time earthquake databases into dynamic web pages, with several powerful new technologies. While the application is still most fully developed for seismic data, the infrastructure is extensible (and being extended) to create a real-time information architecture for numerous signal domains. This work provides a practical, lightweight approach suitable for individual seismic and sensor networks, which does not require a full 'web-services' implementation. Nevertheless, the technologies here are extensible to larger applications such as the Storage-Resource-Broker based VORB project. The technologies included in the new system blend real-time relational databases as a focus for processing and data handling; an XML->XSLT architecture as the core of the web mirroring; PHP extensions to Antelope (the environmental monitoring-system context adopted for RoadNET) in order to support complex, user-driven interactivity; and VRML output for expression of information as web-browsable three-dimensional worlds.

Real-Time Probing of Structural Dynamics by Interaction between Chromophores

DEFF Research Database (Denmark)

Brogaard, Rasmus Y.; Møller, Klaus Braagaard; Sølling, Theis Ivan

2011-01-01

We present an investigation of structural dynamics in excited-state cations probed in real-time by femtosecond timeresolved ion photofragmentation spectroscopy. From photoelectron spectroscopy data on 1,3-dibromopropane we conclude that the pump pulse ionizes the molecule, populating an excited...

Real-time dynamics of dissipative quantum systems

International Nuclear Information System (INIS)

Chow, K.S.

1988-01-01

The first part of this thesis motivates a real time approach to the dynamics of dissipative quantum systems. We review previous imaginary time methods for calculating escape rates and discuss their applications to the analysis of data in macroscopic quantum tunneling experiments. In tunneling experiments on heavily damped Superconducting Quantum Interference Devices, the instanton method gave results that compare reasonably well with data. In tunneling experiments on weakly damped Current Biased Josephson Junctions, two problems arise. First, the classical limit of the instanton result disagrees with the classical rate of thermal activation. Second, the instanton method cannot predict the microwave enhancement of escape rates. In the third chapter, we discuss our real time approach to the dynamics of dissipative systems in terms of a kinetic equation for the reduced density matrix. We demonstrate some known equilibrium properties of dissipative systems through the kinetic equation and derived the bath induced widths and energy shifts. In the low damping limit, the kinetic equation reduces to a much simpler master equation. The classical limit of the master equation is completely equivalent to the Fokker-Planck equation that describes thermal activation. In the fourth chapter, we apply the master equation to the problem of tunneling and resonance enhancement of tunneling in weakly damped current biased Josephson junctions. In the classical regime, microwaves of the appropriate frequency induce resonances between many neighboring levels and an asymmetrical resonance peak is measured. We can calibrate the junction parameters by fitting the stationary solution of the master equation to the classical resonance data. In the quantum regime, the stationary solution of the master equation, predicts well-resolved resonance peaks which agree very well with the observed data

Real-Time Measurements and Modelling on Dynamic Behaviour of SonoVue Bubbles Based on Light Scattering Technology

International Nuclear Information System (INIS)

Juan, Tu; Rongjue, Wei; Guan, J. F.; Matula, T. J.; Crum, L. A.

2008-01-01

The dynamic behaviour of SonoVue microbubbles, a new generation ultrasound contrast agent, is investigated in real time with light scattering method. Highly diluted SonoVue microbubbles are injected into a diluted gel made of xanthan gum and water. The responses of individual SonoVue bubbles to driven ultrasound pulses are measured. Both linear and nonlinear bubble oscillations are observed and the results suggest that SonoVue microbubbles can generate strong nonlinear responses. By fitting the experimental data of individual bubble responses with Sarkar's model, the shell coating parameter of the bubbles and dilatational viscosity is estimated to be 7.0 nm·s·Pa

Real-time control of the 3-DOF sled dynamics of a null-flux Maglev System with a passive sled

NARCIS (Netherlands)

Boeij, de J.; Steinbuch, M.; Gutierrez, H.M.

2006-01-01

The real-time control of the three degrees of freedom (DOF) dynamics of an electrodynamic (EDS) Maglev vehicle is presented. The design is based on a 5-DOF state-space model of the sled dynamics that uses a simple algebraic model to describe the interaction between the -flux coils on the track and

Developing a Tool Point Control Scheme for a Hydraulic Crane Using Interactive Real-time Dynamic Simulation

DEFF Research Database (Denmark)

Pedersen, Mikkel Melters; Hansen, Michael Rygaard; Ballebye, Morten

2010-01-01

This paper describes the implementation of an interactive real-time dynamic simulation model of a hydraulic crane. The user input to the model is given continuously via joystick and output is presented continuously in a 3D animation. Using this simulation model, a tool point control scheme...... is developed for the specific crane, considering the saturation phenomena of the system and practical implementation....

Real-Time Analysis and Forecasting of Multisite River Flow Using a Distributed Hydrological Model

Directory of Open Access Journals (Sweden)

Mingdong Sun

2014-01-01

Full Text Available A spatial distributed hydrological forecasting system was developed to promote the analysis of river flow dynamic state in a large basin. The research presented the real-time analysis and forecasting of multisite river flow in the Nakdong River Basin using a distributed hydrological model with radar rainfall forecast data. A real-time calibration algorithm of hydrological distributed model was proposed to investigate the particular relationship between the water storage and basin discharge. Demonstrate the approach of simulating multisite river flow using a distributed hydrological model couple with real-time calibration and forecasting of multisite river flow with radar rainfall forecasts data. The hydrographs and results exhibit that calibrated flow simulations are very approximate to the flow observation at all sites and the accuracy of forecasting flow is gradually decreased with lead times extending from 1 hr to 3 hrs. The flow forecasts are lower than the flow observation which is likely caused by the low estimation of radar rainfall forecasts. The research has well demonstrated that the distributed hydrological model is readily applicable for multisite real-time river flow analysis and forecasting in a large basin.

A meshless EFG-based algorithm for 3D deformable modeling of soft tissue in real-time.

Science.gov (United States)

Abdi, Elahe; Farahmand, Farzam; Durali, Mohammad

2012-01-01

The meshless element-free Galerkin method was generalized and an algorithm was developed for 3D dynamic modeling of deformable bodies in real time. The efficacy of the algorithm was investigated in a 3D linear viscoelastic model of human spleen subjected to a time-varying compressive force exerted by a surgical grasper. The model remained stable in spite of the considerably large deformations occurred. There was a good agreement between the results and those of an equivalent finite element model. The computational cost, however, was much lower, enabling the proposed algorithm to be effectively used in real-time applications.

Real-Time Dynamic MLC Tracking for Intensity Modulated Arc Therapy

DEFF Research Database (Denmark)

Falk, Marianne

Motion management of intra-fraction tumour motion during radiotherapy treatment can be a challenging task in order to achieve tumour control as well as minimizing the dose to the surrounding healthy tissue. Real-time dynamic multileaf collimator (MLC) tracking is a novel method for intra-fraction...

A Dynamic Time Warping Approach to Real-Time Activity Recognition for Food Preparation

Science.gov (United States)

Pham, Cuong; Plötz, Thomas; Olivier, Patrick

We present a dynamic time warping based activity recognition system for the analysis of low-level food preparation activities. Accelerometers embedded into kitchen utensils provide continuous sensor data streams while people are using them for cooking. The recognition framework analyzes frames of contiguous sensor readings in real-time with low latency. It thereby adapts to the idiosyncrasies of utensil use by automatically maintaining a template database. We demonstrate the effectiveness of the classification approach by a number of real-world practical experiments on a publically available dataset. The adaptive system shows superior performance compared to a static recognizer. Furthermore, we demonstrate the generalization capabilities of the system by gradually reducing the amount of training samples. The system achieves excellent classification results even if only a small number of training samples is available, which is especially relevant for real-world scenarios.

Real-time management (RTM) by cloud computing system dynamics (CCSD) for risk analysis of Fukushima nuclear power plant (NPP) accident

Energy Technology Data Exchange (ETDEWEB)

Cho, Hyo Sung [Yonsei Univ., Wonju Gangwon-do (Korea, Republic of). Dept. of Radiation Convergence Engineering; Woo, Tae Ho [Yonsei Univ., Wonju Gangwon-do (Korea, Republic of). Dept. of Radiation Convergence Engineering; The Cyber Univ. of Korea, Seoul (Korea, Republic of). Dept. of Mechanical and Control Engineering

2017-03-15

The earthquake and tsunami induced accident of nuclear power plant (NPP) in Fukushima disaster is investigated by the real-time management (RTM) method. This non-linear logic of the safety management is applied to enhance the methodological confidence in the NPP reliability. The case study of the earthquake is modeled for the fast reaction characteristics of the RTM. The system dynamics (SD) modeling simulations and cloud computing are applied for the RTM method where the real time simulation has the fast and effective communication for the accident remediation and prevention. Current tablet computing system can improve the safety standard of the NPP. Finally, the procedure of the cloud computing system dynamics (CCSD) modeling is constructed.

Real-time management (RTM) by cloud computing system dynamics (CCSD) for risk analysis of Fukushima nuclear power plant (NPP) accident

International Nuclear Information System (INIS)

Cho, Hyo Sung; Woo, Tae Ho; The Cyber Univ. of Korea, Seoul

2017-01-01

The earthquake and tsunami induced accident of nuclear power plant (NPP) in Fukushima disaster is investigated by the real-time management (RTM) method. This non-linear logic of the safety management is applied to enhance the methodological confidence in the NPP reliability. The case study of the earthquake is modeled for the fast reaction characteristics of the RTM. The system dynamics (SD) modeling simulations and cloud computing are applied for the RTM method where the real time simulation has the fast and effective communication for the accident remediation and prevention. Current tablet computing system can improve the safety standard of the NPP. Finally, the procedure of the cloud computing system dynamics (CCSD) modeling is constructed.

Failure analysis of real-time systems

International Nuclear Information System (INIS)

Jalashgar, A.; Stoelen, K.

1998-01-01

This paper highlights essential aspects of real-time software systems that are strongly related to the failures and their course of propagation. The significant influence of means-oriented and goal-oriented system views in the description, understanding and analysing of those aspects is elaborated. The importance of performing failure analysis prior to reliability analysis of real-time systems is equally addressed. Problems of software reliability growth models taking the properties of such systems into account are discussed. Finally, the paper presents a preliminary study of a goal-oriented approach to model the static and dynamic characteristics of real-time systems, so that the corresponding analysis can be based on a more descriptive and informative picture of failures, their effects and the possibility of their occurrence. (author)

Route around real time

International Nuclear Information System (INIS)

Terrier, Francois

1996-01-01

The greater and greater autonomy and complexity asked to the control and command systems lead to work on introducing techniques such as Artificial Intelligence or concurrent object programming in industrial applications. However, while the critical feature of these systems impose to control the dynamics of the proposed solutions, their complexity often imposes a high adaptability to a partially modelled environment. The studies presented start from low level control and command systems to more complex applications at higher levels, such as 'supervision systems'. Techniques such as temporal reasoning and uncertainty management are proposed for the first studies, while the second are tackled with programming techniques based on the real time object paradigm. The outcomes of this itinerary crystallize on the ACCORD project which targets to manage - on the whole life cycle of a real time application - these two problematics, sometimes antagonistic: control of the dynamics and adaptivity. (author) [fr

Control-oriented modeling of the plasma particle density in tokamaks and application to real-time density profile reconstruction

NARCIS (Netherlands)

Blanken, T.C.; Felici, F.; Rapson, C.J.; de Baar, M.R.; Heemels, W.P.M.H.

2018-01-01

A model-based approach to real-time reconstruction of the particle density profile in tokamak plasmas is presented, based on a dynamic state estimator. Traditionally, the density profile is reconstructed in real-time by solving an ill-conditioned inversion problem using a measurement at a single

Parallel Motion Simulation of Large-Scale Real-Time Crowd in a Hierarchical Environmental Model

Directory of Open Access Journals (Sweden)

Xin Wang

2012-01-01

Full Text Available This paper presents a parallel real-time crowd simulation method based on a hierarchical environmental model. A dynamical model of the complex environment should be constructed to simulate the state transition and propagation of individual motions. By modeling of a virtual environment where virtual crowds reside, we employ different parallel methods on a topological layer, a path layer and a perceptual layer. We propose a parallel motion path matching method based on the path layer and a parallel crowd simulation method based on the perceptual layer. The large-scale real-time crowd simulation becomes possible with these methods. Numerical experiments are carried out to demonstrate the methods and results.

The Research of Car-Following Model Based on Real-Time Maximum Deceleration

Directory of Open Access Journals (Sweden)

Longhai Yang

2015-01-01

Full Text Available This paper is concerned with the effect of real-time maximum deceleration in car-following. The real-time maximum acceleration is estimated with vehicle dynamics. It is known that an intelligent driver model (IDM can control adaptive cruise control (ACC well. The disadvantages of IDM at high and constant speed are analyzed. A new car-following model which is applied to ACC is established accordingly to modify the desired minimum gap and structure of the IDM. We simulated the new car-following model and IDM under two different kinds of road conditions. In the first, the vehicles drive on a single road, taking dry asphalt road as the example in this paper. In the second, vehicles drive onto a different road, and this paper analyzed the situation in which vehicles drive from a dry asphalt road onto an icy road. From the simulation, we found that the new car-following model can not only ensure driving security and comfort but also control the steady driving of the vehicle with a smaller time headway than IDM.

Real-time Visualization of Tissue Dynamics during Embryonic Development and Malignant Transformation

Science.gov (United States)

Yamada, Kenneth

Tissues undergo dramatic changes in organization during embryonic development, as well as during cancer progression and invasion. Recent advances in microscopy now allow us to visualize and track directly the dynamic movements of tissues, their constituent cells, and cellular substructures. This behavior can now be visualized not only in regular tissue culture on flat surfaces (`2D' environments), but also in a variety of 3D environments that may provide physiological cues relevant to understanding dynamics within living organisms. Acquisition of imaging data using various microscopy modalities will provide rich opportunities for determining the roles of physical factors and for computational modeling of complex processes in living tissues. Direct visualization of real-time motility is providing insight into biology spanning multiple spatio-temporal scales. Many cells in our body are known to be in contact with connective tissue and other forms of extracellular matrix. They do so through microscopic cellular adhesions that bind to matrix proteins. In particular, fluorescence microscopy has revealed that cells dynamically probe and bend the matrix at the sites of cell adhesions, and that 3D matrix architecture, stiffness, and elasticity can each regulate migration of the cells. Conversely, cells remodel their local matrix as organs form or tumors invade. Cancer cells can invade tissues using microscopic protrusions that degrade the surrounding matrix; in this case, the local matrix protein concentration is more important for inducing the micro-invasive protrusions than stiffness. On the length scales of tissues, transiently high rates of individual cell movement appear to help establish organ architecture. In fact, isolated cells can self-organize to form tissue structures. In all of these cases, in-depth real-time visualization will ultimately provide the extensive data needed for computer modeling and for testing hypotheses in which physical forces interact

Dynamics in two-elevator traffic system with real-time information

Energy Technology Data Exchange (ETDEWEB)

Nagatani, Takashi, E-mail: wadokeioru@yahoo.co.jp

2013-12-17

We study the dynamics of traffic system with two elevators using a elevator choice scenario. The two-elevator traffic system with real-time information is similar to the two-route vehicular traffic system. The dynamics of two-elevator traffic system is described by the two-dimensional nonlinear map. An elevator runs a neck-and-neck race with another elevator. The motion of two elevators displays such a complex behavior as quasi-periodic one. The return map of two-dimensional map shows a piecewise map.

A Controller for Dynamic Partial Reconfiguration in FPGA-Based Real-Time Systems

DEFF Research Database (Denmark)

Pezzarossa, Luca; Schoeberl, Martin; Sparsø, Jens

2017-01-01

-source DPR controller specially developed for hard real-time systems and prototyped in connection with the open-source multi-core platform for real-time applications T-CREST. The controller enables a processor to perform reconfiguration in a time-predictable manner and supports different operating modes......In real-time systems, the use of hardware accelerators can lead to a worst-case execution-time speed-up, to a simplification of its analysis, and to a reduction of its pessimism. When using FPGA technology, dynamic partial reconfiguration (DPR) can be used to minimize the area, by only loading....... The paper also presents a software tool for bitstream conversion, compression, and for reconfiguration time analysis. The DPR controller is evaluated in terms of hardware cost, operating frequency, speed, and bitstream compression ratio vs. reconfiguration time trade-off. A simple application example...

Using dynamic mode decomposition for real-time background/foreground separation in video

Science.gov (United States)

Kutz, Jose Nathan; Grosek, Jacob; Brunton, Steven; Fu, Xing; Pendergrass, Seth

2017-06-06

The technique of dynamic mode decomposition (DMD) is disclosed herein for the purpose of robustly separating video frames into background (low-rank) and foreground (sparse) components in real-time. Foreground/background separation is achieved at the computational cost of just one singular value decomposition (SVD) and one linear equation solve, thus producing results orders of magnitude faster than robust principal component analysis (RPCA). Additional techniques, including techniques for analyzing the video for multi-resolution time-scale components, and techniques for reusing computations to allow processing of streaming video in real time, are also described herein.

Real Time Mapping and Dynamic Navigation for Mobile Robots

Directory of Open Access Journals (Sweden)

Maki K. Habib

2008-11-01

Full Text Available This paper discusses the importance, the complexity and the challenges of mapping mobile robot?s unknown and dynamic environment, besides the role of sensors and the problems inherited in map building. These issues remain largely an open research problems in developing dynamic navigation systems for mobile robots. The paper presenst the state of the art in map building and localization for mobile robots navigating within unknown environment, and then introduces a solution for the complex problem of autonomous map building and maintenance method with focus on developing an incremental grid based mapping technique that is suitable for real-time obstacle detection and avoidance. In this case, the navigation of mobile robots can be treated as a problem of tracking geometric features that occur naturally in the environment of the robot. The robot maps its environment incrementally using the concept of occupancy grids and the fusion of multiple ultrasonic sensory information while wandering in it and stay away from all obstacles. To ensure real-time operation with limited resources, as well as to promote extensibility, the mapping and obstacle avoidance modules are deployed in parallel and distributed framework. Simulation based experiments has been conducted and illustrated to show the validity of the developed mapping and obstacle avoidance approach.

MAC-Level Communication Time Modeling and Analysis for Real-Time WSNs

Directory of Open Access Journals (Sweden)

STANGACIU, V.

2016-02-01

Full Text Available Low-level communication protocols and their timing behavior are essential to developing wireless sensor networks (WSNs able to provide the support and operating guarantees required by many current real-time applications. Nevertheless, this aspect still remains an issue in the state-of-the-art. In this paper we provide a detailed analysis of a recently proposed MAC-level communication timing model and demonstrate its usability in designing real-time protocols. The results of a large set of measurements are also presented and discussed here, in direct relation to the main time parameters of the analyzed model.

Math modeling and computer mechanization for real time simulation of rotary-wing aircraft

Science.gov (United States)

Howe, R. M.

1979-01-01

Mathematical modeling and computer mechanization for real time simulation of rotary wing aircraft is discussed. Error analysis in the digital simulation of dynamic systems, such as rotary wing aircraft is described. The method for digital simulation of nonlinearities with discontinuities, such as exist in typical flight control systems and rotor blade hinges, is discussed.

Real-time dynamics of lattice gauge theories with a few-qubit quantum computer

Science.gov (United States)

Martinez, Esteban A.; Muschik, Christine A.; Schindler, Philipp; Nigg, Daniel; Erhard, Alexander; Heyl, Markus; Hauke, Philipp; Dalmonte, Marcello; Monz, Thomas; Zoller, Peter; Blatt, Rainer

2016-06-01

Gauge theories are fundamental to our understanding of interactions between the elementary constituents of matter as mediated by gauge bosons. However, computing the real-time dynamics in gauge theories is a notorious challenge for classical computational methods. This has recently stimulated theoretical effort, using Feynman’s idea of a quantum simulator, to devise schemes for simulating such theories on engineered quantum-mechanical devices, with the difficulty that gauge invariance and the associated local conservation laws (Gauss laws) need to be implemented. Here we report the experimental demonstration of a digital quantum simulation of a lattice gauge theory, by realizing (1 + 1)-dimensional quantum electrodynamics (the Schwinger model) on a few-qubit trapped-ion quantum computer. We are interested in the real-time evolution of the Schwinger mechanism, describing the instability of the bare vacuum due to quantum fluctuations, which manifests itself in the spontaneous creation of electron-positron pairs. To make efficient use of our quantum resources, we map the original problem to a spin model by eliminating the gauge fields in favour of exotic long-range interactions, which can be directly and efficiently implemented on an ion trap architecture. We explore the Schwinger mechanism of particle-antiparticle generation by monitoring the mass production and the vacuum persistence amplitude. Moreover, we track the real-time evolution of entanglement in the system, which illustrates how particle creation and entanglement generation are directly related. Our work represents a first step towards quantum simulation of high-energy theories using atomic physics experiments—the long-term intention is to extend this approach to real-time quantum simulations of non-Abelian lattice gauge theories.

Automated Predicate Abstraction for Real-Time Models

Directory of Open Access Journals (Sweden)

Bahareh Badban

2009-11-01

Full Text Available We present a technique designed to automatically compute predicate abstractions for dense real-timed models represented as networks of timed automata. We use the CIPM algorithm in our previous work which computes new invariants for timed automata control locations and prunes the model, to compute a predicate abstraction of the model. We do so by taking information regarding control locations and their newly computed invariants into account.

A real-time crash prediction model for the ramp vicinities of urban expressways

Directory of Open Access Journals (Sweden)

Moinul Hossain

2013-07-01

Full Text Available Ramp vicinities are arguably the known black-spots on urban expressways. There, while maintaining high speed, drivers need to respond to several complex events such as maneuvering, reading road signs, route planning and maintaining safe distance from other maneuvering vehicles simultaneously which demand higher level of cognitive response to ensure safety. Therefore, any additional discomfort caused by traffic dynamics may induce driving error resulting in a crash. This manuscript presents a methodology for identifying these dynamically forming hazardous traffic conditions near the ramp vicinities with high resolution real-time traffic flow data. It separates the ramp vicinities into four zones – upstream and downstream of entrance and exit ramps, and builds four separate real-time crash prediction models. Around two year (December 2007 to October 2009 crash data as well as their matching traffic sensor data from Shibuya 3 and Shinjuku 4 expressways under the jurisdiction of Tokyo Metropolitan Expressway Company Limited have been utilized for this research. Random multinomial logit, a forest of multinomial logit models, has been used to identify the most important variables. Finally, a real-time modeling method, Bayesian belief net (BBN, has been employed to build the four models using ramp flow, flow and congestion index in the upstream and flow and speed in the downstream of the ramp location as variables. The newly proposed models could predict 50%, 42%, 43% and 55% of the future crashes with around 10% false alarm for the downstream of entrance, downstream of exit, upstream of entrance and upstream of exit ramps respectively. The models can be utilized in combination with various traffic smoothing measures such as ramp metering, variable speed limit, warning messages through variable message signs, etc. to enhance safety near the ramp vicinities.

RTMOD: Real-Time MODel evaluation

International Nuclear Information System (INIS)

Graziani, G; Galmarini, S.; Mikkelsen, T.

2000-01-01

The 1998 - 1999 RTMOD project is a system based on an automated statistical evaluation for the inter-comparison of real-time forecasts produced by long-range atmospheric dispersion models for national nuclear emergency predictions of cross-boundary consequences. The background of RTMOD was the 1994 ETEX project that involved about 50 models run in several Institutes around the world to simulate two real tracer releases involving a large part of the European territory. In the preliminary phase of ETEX, three dry runs (i.e. simulations in real-time of fictitious releases) were carried out. At that time, the World Wide Web was not available to all the exercise participants, and plume predictions were therefore submitted to JRC-Ispra by fax and regular mail for subsequent processing. The rapid development of the World Wide Web in the second half of the nineties, together with the experience gained during the ETEX exercises suggested the development of this project. RTMOD featured a web-based user-friendly interface for data submission and an interactive program module for displaying, intercomparison and analysis of the forecasts. RTMOD has focussed on model intercomparison of concentration predictions at the nodes of a regular grid with 0.5 degrees of resolution both in latitude and in longitude, the domain grid extending from 5W to 40E and 40N to 65N. Hypothetical releases were notified around the world to the 28 model forecasters via the web on a one-day warning in advance. They then accessed the RTMOD web page for detailed information on the actual release, and as soon as possible they then uploaded their predictions to the RTMOD server and could soon after start their inter-comparison analysis with other modelers. When additional forecast data arrived, already existing statistical results would be recalculated to include the influence by all available predictions. The new web-based RTMOD concept has proven useful as a practical decision-making tool for realtime

Dynamic state estimation and prediction for real-time control and operation

NARCIS (Netherlands)

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

2013-01-01

Real-time control and operation are crucial to deal with increasing complexity of modern power systems. To effectively enable those functions, it is required a Dynamic State Estimation (DSE) function to provide accurate network state variables at the right moment and predict their trends ahead. This

Real time control of the flexible dynamics of orbital launch vehicles

NARCIS (Netherlands)

Bos, van den J.; Steinbuch, M.; Gutierrez, H.M.

2011-01-01

During this traineeship the flexible dynamics of orbital launch vehicles are estimated and controlled in real time, using distributed fiber-Bragg sensor arrays for motion estimation and cold gas thrusters for control. The use of these cold-gas thrusters to actively control flexible modes is the main

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.

Integration of domain and resource-based reasoning for real-time control in dynamic environments

Science.gov (United States)

Morgan, Keith; Whitebread, Kenneth R.; Kendus, Michael; Cromarty, Andrew S.

1993-01-01

A real-time software controller that successfully integrates domain-based and resource-based control reasoning to perform task execution in a dynamically changing environment is described. The design of the controller is based on the concept of partitioning the process to be controlled into a set of tasks, each of which achieves some process goal. It is assumed that, in general, there are multiple ways (tasks) to achieve a goal. The controller dynamically determines current goals and their current criticality, choosing and scheduling tasks to achieve those goals in the time available. It incorporates rule-based goal reasoning, a TMS-based criticality propagation mechanism, and a real-time scheduler. The controller has been used to build a knowledge-based situation assessment system that formed a major component of a real-time, distributed, cooperative problem solving system built under DARPA contract. It is also being employed in other applications now in progress.

Real-time model for simulating a tracked vehicle on deformable soils

Directory of Open Access Journals (Sweden)

Martin Meywerk

2016-05-01

Full Text Available Simulation is one possibility to gain insight into the behaviour of tracked vehicles on deformable soils. A lot of publications are known on this topic, but most of the simulations described there cannot be run in real-time. The ability to run a simulation in real-time is necessary for driving simulators. This article describes an approach for real-time simulation of a tracked vehicle on deformable soils. The components of the real-time model are as follows: a conventional wheeled vehicle simulated in the Multi Body System software TRUCKSim, a geometric description of landscape, a track model and an interaction model between track and deformable soils based on Bekker theory and Janosi–Hanamoto, on one hand, and between track and vehicle wheels, on the other hand. Landscape, track model, soil model and the interaction are implemented in MATLAB/Simulink. The details of the real-time model are described in this article, and a detailed description of the Multi Body System part is omitted. Simulations with the real-time model are compared to measurements and to a detailed Multi Body System–finite element method model of a tracked vehicle. An application of the real-time model in a driving simulator is presented, in which 13 drivers assess the comfort of a passive and an active suspension of a tracked vehicle.

Applying MDA to SDR for Space to Model Real-time Issues

Science.gov (United States)

Blaser, Tammy M.

2007-01-01

NASA space communications systems have the challenge of designing SDRs with highly-constrained Size, Weight and Power (SWaP) resources. A study is being conducted to assess the effectiveness of applying the MDA Platform-Independent Model (PIM) and one or more Platform-Specific Models (PSM) specifically to address NASA space domain real-time issues. This paper will summarize our experiences with applying MDA to SDR for Space to model real-time issues. Real-time issues to be examined, measured, and analyzed are: meeting waveform timing requirements and efficiently applying Real-time Operating System (RTOS) scheduling algorithms, applying safety control measures, and SWaP verification. Real-time waveform algorithms benchmarked with the worst case environment conditions under the heaviest workload will drive the SDR for Space real-time PSM design.

Approaching near real-time biosensing: microfluidic microsphere based biosensor for real-time analyte detection.

Science.gov (United States)

Cohen, Noa; Sabhachandani, Pooja; Golberg, Alexander; Konry, Tania

2015-04-15

In this study we describe a simple lab-on-a-chip (LOC) biosensor approach utilizing well mixed microfluidic device and a microsphere-based assay capable of performing near real-time diagnostics of clinically relevant analytes such cytokines and antibodies. We were able to overcome the adsorption kinetics reaction rate-limiting mechanism, which is diffusion-controlled in standard immunoassays, by introducing the microsphere-based assay into well-mixed yet simple microfluidic device with turbulent flow profiles in the reaction regions. The integrated microsphere-based LOC device performs dynamic detection of the analyte in minimal amount of biological specimen by continuously sampling micro-liter volumes of sample per minute to detect dynamic changes in target analyte concentration. Furthermore we developed a mathematical model for the well-mixed reaction to describe the near real time detection mechanism observed in the developed LOC method. To demonstrate the specificity and sensitivity of the developed real time monitoring LOC approach, we applied the device for clinically relevant analytes: Tumor Necrosis Factor (TNF)-α cytokine and its clinically used inhibitor, anti-TNF-α antibody. Based on the reported results herein, the developed LOC device provides continuous sensitive and specific near real-time monitoring method for analytes such as cytokines and antibodies, reduces reagent volumes by nearly three orders of magnitude as well as eliminates the washing steps required by standard immunoassays. Copyright © 2014 Elsevier B.V. All rights reserved.

Real-Time linux dynamic clamp: a fast and flexible way to construct virtual ion channels in living cells.

Science.gov (United States)

Dorval, A D; Christini, D J; White, J A

2001-10-01

We describe a system for real-time control of biological and other experiments. This device, based around the Real-Time Linux operating system, was tested specifically in the context of dynamic clamping, a demanding real-time task in which a computational system mimics the effects of nonlinear membrane conductances in living cells. The system is fast enough to represent dozens of nonlinear conductances in real time at clock rates well above 10 kHz. Conductances can be represented in deterministic form, or more accurately as discrete collections of stochastically gating ion channels. Tests were performed using a variety of complex models of nonlinear membrane mechanisms in excitable cells, including simulations of spatially extended excitable structures, and multiple interacting cells. Only in extreme cases does the computational load interfere with high-speed "hard" real-time processing (i.e., real-time processing that never falters). Freely available on the worldwide web, this experimental control system combines good performance. immense flexibility, low cost, and reasonable ease of use. It is easily adapted to any task involving real-time control, and excels in particular for applications requiring complex control algorithms that must operate at speeds over 1 kHz.

A Dynamic Optimization Method of Indoor Fire Evacuation Route Based on Real-time Situation Awareness

Directory of Open Access Journals (Sweden)

DING Yulin

2016-12-01

Full Text Available How to provide safe and effective evacuation routes is an important safeguard to correctly guide evacuation and reduce the casualties during the fire situation rapidly evolving in complex indoor environment. The traditional static path finding method is difficult to adjust the path adaptively according to the changing fire situation, which lead to the evacuation decision-making blindness and hysteresis. This paper proposes a dynamic method which can dynamically optimize the indoor evacuation routes based on the real-time situation awareness. According to the real-time perception of fire situation parameters and the changing indoor environment information, the evacuation route is optimized dynamically. The integrated representation of multisource indoor fire monitoring sensor observations oriented fire emergency evacuation is presented at first, real-time fire threat situation information inside building is then extracted from the observation data of multi-source sensors, which is used to constrain the dynamical optimization of the topology of the evacuation route. Finally, the simulation experiments prove that this method can improve the accuracy and efficiency of indoor evacuation routing.

Advanced Kalman Filter for Real-Time Responsiveness in Complex Systems

Energy Technology Data Exchange (ETDEWEB)

Welch, Gregory Francis [UNC-Chapel Hill/University of Central Florida; Zhang, Jinghe [UNC-Chapel Hill/Virginia Tech

2014-06-10

Complex engineering systems pose fundamental challenges in real-time operations and control because they are highly dynamic systems consisting of a large number of elements with severe nonlinearities and discontinuities. Today’s tools for real-time complex system operations are mostly based on steady state models, unable to capture the dynamic nature and too slow to prevent system failures. We developed advanced Kalman filtering techniques and the formulation of dynamic state estimation using Kalman filtering techniques to capture complex system dynamics in aiding real-time operations and control. In this work, we looked at complex system issues including severe nonlinearity of system equations, discontinuities caused by system controls and network switches, sparse measurements in space and time, and real-time requirements of power grid operations. We sought to bridge the disciplinary boundaries between Computer Science and Power Systems Engineering, by introducing methods that leverage both existing and new techniques. While our methods were developed in the context of electrical power systems, they should generalize to other large-scale scientific and engineering applications.

Capturing Real-Time Data in Disaster Response Logistics

Directory of Open Access Journals (Sweden)

Kezban Yagci Sokat

2016-06-01

Full Text Available The volume, accuracy, accessibility and level of detail of near real-time data emerging from disaster-affected regions continue to significantly improve. Integration of dynamically evolving in-field data is an important, yet often overlooked, component of the humanitarian logistics models. In this paper, we present a framework for real-time humanitarian logistics data focused on use in mathematical modeling along with modeling implications of this framework. We also discuss how one might measure the attributes of the framework and describe the application of the presented framework to a case study of near real-time data collection in the days following the landfall of Typhoon Haiyan. We detail our first-hand experience of capturing data as the post-disaster response unfolds starting on November 10, 2013 until March 31, 2014 and assess the characteristics and evolution of data pertaining to humanitarian logistics modeling using the proposed framework. The presented logistical content analysis examines the availability of data and informs modelers about the current state of near real-time data. This analysis illustrates what data is available, how early it is available, and how data changes after the disaster. The study describes how our humanitarian logistics team approached the emergence of dynamic online data after the disaster and the challenges faced during the collection process, as well as recommendations to address these challenges in the future (when possible from an academic humanitarian logistics perspective.

Development of a Regularized Dynamic System Response Curve for Real-Time Flood Forecasting Correction

Directory of Open Access Journals (Sweden)

Yiqun Sun

2018-04-01

Full Text Available The dynamic system response curve (DSRC is commonly applied as a real-time flood forecasting error correction method to improve the accuracy of real-time flood forecasting. It has been widely recognized that the least squares (OLS/LS method, employed by DSRC, breaks down ill-posed problems, and therefore, the DSRC method may lead to deterioration in performance caused by meaningless solutions. To address this problem, a diagnostically theoretical analysis was conducted to investigate the relationship between the numerical solution of the Fredholm equation of the first kind and the DSRC method. The analysis clearly demonstrates the derivation of the problem and has implications for an improved approach. To overcome the unstable problem, a new method using regularization techniques (Tikhonov regularization and L-Curve criterion is proposed. Moreover, in this study, to improve the performance of hydrological models, the new method is used as an error correction method to correct a variable from a hydrological model. The proposed method incorporates the information from a hydrological model structure. Based on the analysis of the hydrological model, the free water storage of the Xinanjiang rainfall-runoff (XAJ model is corrected to improve the model’s performance. A numerical example and a real case study are presented to compare the two methods. Results from the numerical example indicate that the mean Nash–Sutcliffe efficiency value (NSE of the regularized DSRC method (RDSRC decreased from 0.99 to 0.55, while the mean NSE of DSRC decreased from 0.98 to −1.84 when the noise level was increased. The overall performance measured by four different criteria clearly demonstrates the robustness of the RDSRC method. Similar results were obtained for the real case study. The mean NSE of 35 flood events obtained by RDSRC method was 0.92, which is significantly higher than the mean NSE of DSRC (0.7. The results demonstrate that the RDSRC method is much

Development of real-time visualization system for Computational Fluid Dynamics on parallel computers

International Nuclear Information System (INIS)

Muramatsu, Kazuhiro; Otani, Takayuki; Matsumoto, Hideki; Takei, Toshifumi; Doi, Shun

1998-03-01

A real-time visualization system for computational fluid dynamics in a network connecting between a parallel computing server and the client terminal was developed. Using the system, a user can visualize the results of a CFD (Computational Fluid Dynamics) simulation on the parallel computer as a client terminal during the actual computation on a server. Using GUI (Graphical User Interface) on the client terminal, to user is also able to change parameters of the analysis and visualization during the real-time of the calculation. The system carries out both of CFD simulation and generation of a pixel image data on the parallel computer, and compresses the data. Therefore, the amount of data from the parallel computer to the client is so small in comparison with no compression that the user can enjoy the swift image appearance comfortably. Parallelization of image data generation is based on Owner Computation Rule. GUI on the client is built on Java applet. A real-time visualization is thus possible on the client PC only if Web browser is implemented on it. (author)

Controller synthesis for dynamic hierarchical real-time plants using timed automata

DEFF Research Database (Denmark)

Bin Waez, Md Tawhid; Wasowski, Andrzej; Dingel, Juergen

2017-01-01

We use timed I/O automata based timed games to synthesize task-level reconfiguration services for cost-effective fault tolerance in a case study. The case study shows that state-space explosion is a severe problem for timed games. By applying suitable abstractions, we dramatically improve...... the scalability. However, timed I/O automata do not facilitate algorithmic abstraction generation techniques. The case study motivates the development of timed process automata to improve modeling and analysis for controller synthesis of time-critical plants which can be hierarchical and dynamic. The model offers...

Creating wavelet-based models for real-time synthesis of perceptually convincing environmental sounds

Science.gov (United States)

Miner, Nadine Elizabeth

1998-09-01

This dissertation presents a new wavelet-based method for synthesizing perceptually convincing, dynamic sounds using parameterized sound models. The sound synthesis method is applicable to a variety of applications including Virtual Reality (VR), multi-media, entertainment, and the World Wide Web (WWW). A unique contribution of this research is the modeling of the stochastic, or non-pitched, sound components. This stochastic-based modeling approach leads to perceptually compelling sound synthesis. Two preliminary studies conducted provide data on multi-sensory interaction and audio-visual synchronization timing. These results contributed to the design of the new sound synthesis method. The method uses a four-phase development process, including analysis, parameterization, synthesis and validation, to create the wavelet-based sound models. A patent is pending for this dynamic sound synthesis method, which provides perceptually-realistic, real-time sound generation. This dissertation also presents a battery of perceptual experiments developed to verify the sound synthesis results. These experiments are applicable for validation of any sound synthesis technique.

Real-time safety risk assessment based on a real-time location system for hydropower construction sites.

Science.gov (United States)

Jiang, Hanchen; Lin, Peng; Fan, Qixiang; Qiang, Maoshan

2014-01-01

The concern for workers' safety in construction industry is reflected in many studies focusing on static safety risk identification and assessment. However, studies on real-time safety risk assessment aimed at reducing uncertainty and supporting quick response are rare. A method for real-time safety risk assessment (RTSRA) to implement a dynamic evaluation of worker safety states on construction site has been proposed in this paper. The method provides construction managers who are in charge of safety with more abundant information to reduce the uncertainty of the site. A quantitative calculation formula, integrating the influence of static and dynamic hazards and that of safety supervisors, is established to link the safety risk of workers with the locations of on-site assets. By employing the hidden Markov model (HMM), the RTSRA provides a mechanism for processing location data provided by the real-time location system (RTLS) and analyzing the probability distributions of different states in terms of false positives and negatives. Simulation analysis demonstrated the logic of the proposed method and how it works. Application case shows that the proposed RTSRA is both feasible and effective in managing construction project safety concerns.

Change Semantic Constrained Online Data Cleaning Method for Real-Time Observational Data Stream

Science.gov (United States)

Ding, Yulin; Lin, Hui; Li, Rongrong

2016-06-01

Recent breakthroughs in sensor networks have made it possible to collect and assemble increasing amounts of real-time observational data by observing dynamic phenomena at previously impossible time and space scales. Real-time observational data streams present potentially profound opportunities for real-time applications in disaster mitigation and emergency response, by providing accurate and timeliness estimates of environment's status. However, the data are always subject to inevitable anomalies (including errors and anomalous changes/events) caused by various effects produced by the environment they are monitoring. The "big but dirty" real-time observational data streams can rarely achieve their full potential in the following real-time models or applications due to the low data quality. Therefore, timely and meaningful online data cleaning is a necessary pre-requisite step to ensure the quality, reliability, and timeliness of the real-time observational data. In general, a straightforward streaming data cleaning approach, is to define various types of models/classifiers representing normal behavior of sensor data streams and then declare any deviation from this model as normal or erroneous data. The effectiveness of these models is affected by dynamic changes of deployed environments. Due to the changing nature of the complicated process being observed, real-time observational data is characterized by diversity and dynamic, showing a typical Big (Geo) Data characters. Dynamics and diversity is not only reflected in the data values, but also reflected in the complicated changing patterns of the data distributions. This means the pattern of the real-time observational data distribution is not stationary or static but changing and dynamic. After the data pattern changed, it is necessary to adapt the model over time to cope with the changing patterns of real-time data streams. Otherwise, the model will not fit the following observational data streams, which may led

CHANGE SEMANTIC CONSTRAINED ONLINE DATA CLEANING METHOD FOR REAL-TIME OBSERVATIONAL DATA STREAM

Directory of Open Access Journals (Sweden)

Y. Ding

2016-06-01

Full Text Available Recent breakthroughs in sensor networks have made it possible to collect and assemble increasing amounts of real-time observational data by observing dynamic phenomena at previously impossible time and space scales. Real-time observational data streams present potentially profound opportunities for real-time applications in disaster mitigation and emergency response, by providing accurate and timeliness estimates of environment’s status. However, the data are always subject to inevitable anomalies (including errors and anomalous changes/events caused by various effects produced by the environment they are monitoring. The “big but dirty” real-time observational data streams can rarely achieve their full potential in the following real-time models or applications due to the low data quality. Therefore, timely and meaningful online data cleaning is a necessary pre-requisite step to ensure the quality, reliability, and timeliness of the real-time observational data. In general, a straightforward streaming data cleaning approach, is to define various types of models/classifiers representing normal behavior of sensor data streams and then declare any deviation from this model as normal or erroneous data. The effectiveness of these models is affected by dynamic changes of deployed environments. Due to the changing nature of the complicated process being observed, real-time observational data is characterized by diversity and dynamic, showing a typical Big (Geo Data characters. Dynamics and diversity is not only reflected in the data values, but also reflected in the complicated changing patterns of the data distributions. This means the pattern of the real-time observational data distribution is not stationary or static but changing and dynamic. After the data pattern changed, it is necessary to adapt the model over time to cope with the changing patterns of real-time data streams. Otherwise, the model will not fit the following observational

Real-time individualization of the unified model of performance.

Science.gov (United States)

Liu, Jianbo; Ramakrishnan, Sridhar; Laxminarayan, Srinivas; Balkin, Thomas J; Reifman, Jaques

2017-12-01

Existing mathematical models for predicting neurobehavioural performance are not suited for mobile computing platforms because they cannot adapt model parameters automatically in real time to reflect individual differences in the effects of sleep loss. We used an extended Kalman filter to develop a computationally efficient algorithm that continually adapts the parameters of the recently developed Unified Model of Performance (UMP) to an individual. The algorithm accomplishes this in real time as new performance data for the individual become available. We assessed the algorithm's performance by simulating real-time model individualization for 18 subjects subjected to 64 h of total sleep deprivation (TSD) and 7 days of chronic sleep restriction (CSR) with 3 h of time in bed per night, using psychomotor vigilance task (PVT) data collected every 2 h during wakefulness. This UMP individualization process produced parameter estimates that progressively approached the solution produced by a post-hoc fitting of model parameters using all data. The minimum number of PVT measurements needed to individualize the model parameters depended upon the type of sleep-loss challenge, with ~30 required for TSD and ~70 for CSR. However, model individualization depended upon the overall duration of data collection, yielding increasingly accurate model parameters with greater number of days. Interestingly, reducing the PVT sampling frequency by a factor of two did not notably hamper model individualization. The proposed algorithm facilitates real-time learning of an individual's trait-like responses to sleep loss and enables the development of individualized performance prediction models for use in a mobile computing platform. © 2017 European Sleep Research Society.

Network Dynamics with BrainX3: A Large-Scale Simulation of the Human Brain Network with Real-Time Interaction

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Xerxes D. Arsiwalla

2015-02-01

Full Text Available BrainX3 is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX3 in real-time by perturbing brain regions with transient stimulations to observe reverberating network activity, simulate lesion dynamics or implement network analysis functions from a library of graph theoretic measures. BrainX3 can thus be used as a novel immersive platform for real-time exploration and analysis of dynamical activity patterns in brain networks, both at rest or in a task-related state, for discovery of signaling pathways associated to brain function and/or dysfunction and as a tool for virtual neurosurgery. Our results demonstrate these functionalities and shed insight on the dynamics of the resting-state attractor. Specifically, we found that a noisy network seems to favor a low firing attractor state. We also found that the dynamics of a noisy network is less resilient to lesions. Our simulations on TMS perturbations show that even though TMS inhibits most of the network, it also sparsely excites a few regions. This is presumably, due to anti-correlations in the dynamics and suggests that even a lesioned network can show sparsely distributed increased activity compared to healthy resting-state, over specific brain areas.

High dynamic range adaptive real-time smart camera: an overview of the HDR-ARTiST project

Science.gov (United States)

Lapray, Pierre-Jean; Heyrman, Barthélémy; Ginhac, Dominique

2015-04-01

Standard cameras capture only a fraction of the information that is visible to the human visual system. This is specifically true for natural scenes including areas of low and high illumination due to transitions between sunlit and shaded areas. When capturing such a scene, many cameras are unable to store the full Dynamic Range (DR) resulting in low quality video where details are concealed in shadows or washed out by sunlight. The imaging technique that can overcome this problem is called HDR (High Dynamic Range) imaging. This paper describes a complete smart camera built around a standard off-the-shelf LDR (Low Dynamic Range) sensor and a Virtex-6 FPGA board. This smart camera called HDR-ARtiSt (High Dynamic Range Adaptive Real-time Smart camera) is able to produce a real-time HDR live video color stream by recording and combining multiple acquisitions of the same scene while varying the exposure time. This technique appears as one of the most appropriate and cheapest solution to enhance the dynamic range of real-life environments. HDR-ARtiSt embeds real-time multiple captures, HDR processing, data display and transfer of a HDR color video for a full sensor resolution (1280 1024 pixels) at 60 frames per second. The main contributions of this work are: (1) Multiple Exposure Control (MEC) dedicated to the smart image capture with alternating three exposure times that are dynamically evaluated from frame to frame, (2) Multi-streaming Memory Management Unit (MMMU) dedicated to the memory read/write operations of the three parallel video streams, corresponding to the different exposure times, (3) HRD creating by combining the video streams using a specific hardware version of the Devebecs technique, and (4) Global Tone Mapping (GTM) of the HDR scene for display on a standard LCD monitor.

A Comparison and Evaluation of Real-Time Software Systems Modeling Languages

Science.gov (United States)

Evensen, Kenneth D.; Weiss, Kathryn Anne

2010-01-01

A model-driven approach to real-time software systems development enables the conceptualization of software, fostering a more thorough understanding of its often complex architecture and behavior while promoting the documentation and analysis of concerns common to real-time embedded systems such as scheduling, resource allocation, and performance. Several modeling languages have been developed to assist in the model-driven software engineering effort for real-time systems, and these languages are beginning to gain traction with practitioners throughout the aerospace industry. This paper presents a survey of several real-time software system modeling languages, namely the Architectural Analysis and Design Language (AADL), the Unified Modeling Language (UML), Systems Modeling Language (SysML), the Modeling and Analysis of Real-Time Embedded Systems (MARTE) UML profile, and the AADL for UML profile. Each language has its advantages and disadvantages, and in order to adequately describe a real-time software system's architecture, a complementary use of multiple languages is almost certainly necessary. This paper aims to explore these languages in the context of understanding the value each brings to the model-driven software engineering effort and to determine if it is feasible and practical to combine aspects of the various modeling languages to achieve more complete coverage in architectural descriptions. To this end, each language is evaluated with respect to a set of criteria such as scope, formalisms, and architectural coverage. An example is used to help illustrate the capabilities of the various languages.

Exponential smoothing approaches for prediction in real-time electricity markets

DEFF Research Database (Denmark)

Jónsson, Tryggvi; Pinson, Pierre; Nielsen, Henrik Aalborg

2014-01-01

The optimal design of offering strategies for wind power producers is commonly based on unconditional (and, hence, constant) expectation values for prices in real-time markets, directly defining their loss function in a stochastic optimization framework. This is why it may certainly be advantageous...... to account for the seasonal and dynamic behavior of such prices, hence translating to time-varying loss functions. With that objective in mind, forecasting approaches relying on simple models that accommodate the seasonal and dynamic nature of real-time prices are derived and analyzed. These are all based...

Real Time Fire Reconnaissance Satellite Monitoring System Failure Model

Science.gov (United States)

Nino Prieto, Omar Ariosto; Colmenares Guillen, Luis Enrique

2013-09-01

In this paper the Real Time Fire Reconnaissance Satellite Monitoring System is presented. This architecture is a legacy of the Detection System for Real-Time Physical Variables which is undergoing a patent process in Mexico. The methodologies for this design are the Structured Analysis for Real Time (SA- RT) [8], and the software is carried out by LACATRE (Langage d'aide à la Conception d'Application multitâche Temps Réel) [9,10] Real Time formal language. The system failures model is analyzed and the proposal is based on the formal language for the design of critical systems and Risk Assessment; AltaRica. This formal architecture uses satellites as input sensors and it was adapted from the original model which is a design pattern for physical variation detection in Real Time. The original design, whose task is to monitor events such as natural disasters and health related applications, or actual sickness monitoring and prevention, as the Real Time Diabetes Monitoring System, among others. Some related work has been presented on the Mexican Space Agency (AEM) Creation and Consultation Forums (2010-2011), and throughout the International Mexican Aerospace Science and Technology Society (SOMECYTA) international congress held in San Luis Potosí, México (2012). This Architecture will allow a Real Time Fire Satellite Monitoring, which will reduce the damage and danger caused by fires which consumes the forests and tropical forests of Mexico. This new proposal, permits having a new system that impacts on disaster prevention, by combining national and international technologies and cooperation for the benefit of humankind.

Real-time radiography

International Nuclear Information System (INIS)

Bossi, R.H.; Oien, C.T.

1981-01-01

Real-time radiography is used for imaging both dynamic events and static objects. Fluorescent screens play an important role in converting radiation to light, which is then observed directly or intensified and detected. The radiographic parameters for real-time radiography are similar to conventional film radiography with special emphasis on statistics and magnification. Direct-viewing fluoroscopy uses the human eye as a detector of fluorescent screen light or the light from an intensifier. Remote-viewing systems replace the human observer with a television camera. The remote-viewing systems have many advantages over the direct-viewing conditions such as safety, image enhancement, and the capability to produce permanent records. This report reviews real-time imaging system parameters and components

Real-time full-field characterization of transient dissipative soliton dynamics in a mode-locked laser

Science.gov (United States)

Ryczkowski, P.; Närhi, M.; Billet, C.; Merolla, J.-M.; Genty, G.; Dudley, J. M.

2018-04-01

Dissipative solitons are remarkably localized states of a physical system that arise from the dynamical balance between nonlinearity, dispersion and environmental energy exchange. They are the most universal form of soliton that can exist, and are seen in far-from-equilibrium systems in many fields, including chemistry, biology and physics. There has been particular interest in studying their properties in mode-locked lasers, but experiments have been limited by the inability to track the dynamical soliton evolution in real time. Here, we use simultaneous dispersive Fourier transform and time-lens measurements to completely characterize the spectral and temporal evolution of ultrashort dissipative solitons as their dynamics pass through a transient unstable regime with complex break-up and collisions before stabilization. Further insight is obtained from reconstruction of the soliton amplitude and phase and calculation of the corresponding complex-valued eigenvalue spectrum. These findings show how real-time measurements provide new insights into ultrafast transient dynamics in optics.

Automated reasoning with dynamic event trees: a real-time, knowledge-based decision aide

International Nuclear Information System (INIS)

Touchton, R.A.; Gunter, A.D.; Subramanyan, N.

1988-01-01

The models and data contained in a probabilistic risk assessment (PRA) Event Sequence Analysis represent a wealth of information that can be used for dynamic calculation of event sequence likelihood. In this paper we report a new and unique computerization methodology which utilizes these data. This sub-system (referred to as PREDICTOR) has been developed and tested as part of a larger system. PREDICTOR performs a real-time (re)calculation of the estimated likelihood of core-melt as a function of plant status. This methodology uses object-oriented programming techniques from the artificial intelligence discipline that enable one to codify event tree and fault tree logic models and associated probabilities developed in a PRA study. Existence of off-normal conditions is reported to PREDICTOR, which then updates the relevant failure probabilities throughout the event tree and fault tree models by dynamically replacing the off-the-shelf (or prior) probabilities with new probabilities based on the current situation. The new event probabilities are immediately propagated through the models (using 'demons') and an updated core-melt probability is calculated. Along the way, the dominant non-success path of each event tree is determined and highlighted. (author)

Multivariate performance reliability prediction in real-time

International Nuclear Information System (INIS)

Lu, S.; Lu, H.; Kolarik, W.J.

2001-01-01

This paper presents a technique for predicting system performance reliability in real-time considering multiple failure modes. The technique includes on-line multivariate monitoring and forecasting of selected performance measures and conditional performance reliability estimates. The performance measures across time are treated as a multivariate time series. A state-space approach is used to model the multivariate time series. Recursive forecasting is performed by adopting Kalman filtering. The predicted mean vectors and covariance matrix of performance measures are used for the assessment of system survival/reliability with respect to the conditional performance reliability. The technique and modeling protocol discussed in this paper provide a means to forecast and evaluate the performance of an individual system in a dynamic environment in real-time. The paper also presents an example to demonstrate the technique

Effect of Streamflow Forecast Uncertainty on Real-Time Reservoir Operation

Science.gov (United States)

Zhao, T.; Cai, X.; Yang, D.

2010-12-01

Various hydrological forecast products have been applied to real-time reservoir operation, including deterministic streamflow forecast (DSF), DSF-based probabilistic streamflow forecast (DPSF), and ensemble streamflow forecast (ESF), which represent forecast uncertainty in the form of deterministic forecast error, deterministic forecast error-based uncertainty distribution, and ensemble forecast errors, respectively. Compared to previous studies that treat these forecast products as ad hoc inputs for reservoir operation models, this paper attempts to model the uncertainties involved in the various forecast products and explores their effect on real-time reservoir operation decisions. In hydrology, there are various indices reflecting the magnitude of streamflow forecast uncertainty; meanwhile, few models illustrate the forecast uncertainty evolution process. This research introduces Martingale Model of Forecast Evolution (MMFE) from supply chain management and justifies its assumptions for quantifying the evolution of uncertainty in streamflow forecast as time progresses. Based on MMFE, this research simulates the evolution of forecast uncertainty in DSF, DPSF, and ESF, and applies the reservoir operation models (dynamic programming, DP; stochastic dynamic programming, SDP; and standard operation policy, SOP) to assess the effect of different forms of forecast uncertainty on real-time reservoir operation. Through a hypothetical single-objective real-time reservoir operation model, the results illustrate that forecast uncertainty exerts significant effects. Reservoir operation efficiency, as measured by a utility function, decreases as the forecast uncertainty increases. Meanwhile, these effects also depend on the type of forecast product being used. In general, the utility of reservoir operation with ESF is nearly as high as the utility obtained with a perfect forecast; the utilities of DSF and DPSF are similar to each other but not as efficient as ESF. Moreover

Dynamic Travel Time Prediction Models for Buses Using Only GPS Data

Directory of Open Access Journals (Sweden)

Wei Fan

2015-01-01

Full Text Available Providing real-time and accurate travel time information of transit vehicles can be very helpful as it assists passengers in planning their trips to minimize waiting times. The purpose of this research is to develop and compare dynamic travel time prediction models which can provide accurate prediction of bus travel time in order to give real-time information at a given downstream bus stop using only global positioning system (GPS data. Historical Average (HA, Kalman Filtering (KF and Artificial Neural Network (ANN models are considered and developed in this paper. A case has been studied by making use of the three models. Promising results are obtained from the case study, indicating that the models can be used to implement an Advanced Public Transport System. The implementation of this system could assist transit operators in improving the reliability of bus services, thus attracting more travelers to transit vehicles and helping relieve congestion. The performances of the three models were assessed and compared with each other under two criteria: overall prediction accuracy and robustness. It was shown that the ANN outperformed the other two models in both aspects. In conclusion, it is shown that bus travel time information can be reasonably provided using only arrival and departure time information at stops even in the absence of traffic-stream data.

Monitor of dynamic parameters in real time; Monitor de parametros dinamicos en tiempo real

Energy Technology Data Exchange (ETDEWEB)

Rojas S, A.S.; Ruiz E, J.A. [ININ, 52750 La Marquesa, Estado de Mexico (Mexico)

2008-07-01

In the complex physical systems exist parameters that are necessary for monitoring in real time. In the nuclear industry, particularly in a reactor this surveillance is important, where the times of the reactions are almost instantaneous. Although many of these parameters are monitored, given the advance of the computer systems the monitoring could either be enlarged direct or indirect of other parameters. The analysis of the neutron noise in the nuclear reactors, plays an important role, the noise signal it contains information about the operation conditions of a system, when analyzing it with analysis methodologies of analogical signals to provide important information for the early detection of possible flaws and to indicate the permissible operation levels. To show the characteristics of the operation of the system of Monitoring of Dynamic Parameters in Real Time, oscillations of neutron noise of the TRIGA Mark III of the ININ were analyzed, these were caused with the control bar to a power of 10 Watts, the oscillations were carried out to a frequency of 1Hz, signal of low frequency. In this work a virtual instrument that allows by means of the spectral analysis method in frequency point by point is presented, to indicate in real time periodic variations that could be presented in the neutron noise signal, visualizing in advance the dynamic behavior of the system or nuclear plant. Another of the tests of the monitoring system presented is that of the oscillatory event happened in the reactor of Laguna Verde Nucleo electric Central, would be convenient to have an instrument of surveillance for monitoring through the neutron noise signal the behavior of some important parameter to predict and to indicate in an immediate way an abnormal condition in the reactor operation or in the plant system. These parameters can be the power, the recirculation water flow, etc. The monitor is based on a personal computer (PC), a data acquisition card (ADC) and a computer program

Real-time modeling of heat distributions

Science.gov (United States)

Hamann, Hendrik F.; Li, Hongfei; Yarlanki, Srinivas

2018-01-02

Techniques for real-time modeling temperature distributions based on streaming sensor data are provided. In one aspect, a method for creating a three-dimensional temperature distribution model for a room having a floor and a ceiling is provided. The method includes the following steps. A ceiling temperature distribution in the room is determined. A floor temperature distribution in the room is determined. An interpolation between the ceiling temperature distribution and the floor temperature distribution is used to obtain the three-dimensional temperature distribution model for the room.

SYSTEM OF GUARANTEED RESOLUTION OF DYNAMIC CONFLICTS OF AIRCRAFTS IN REAL TIME

Directory of Open Access Journals (Sweden)

Svitlana Pavlova

2017-03-01

Full Text Available Purpose: The present work is devoted to improving of flight safety in civil aviation by creating and implementing a new system of resolution of dynamic conflict of aircrafts. The developed system is aimed at ensuring a guaranteed level of safety when resolution of rarefied conflict situations of aircraft in real-time. Methods: The proposed system is based on a new method of conflict resolution of aircraft on the basis of the theory of invariance. Results: The development of the system of conflict resolution of aircraft in real time and the implementation of the respective algorithms such control will ensure effective prevention of dangerous approaches. Discussion: The system is implemented as single unified equipment using satellite and radar navigation systems that will ensure the positioning of aircraft in real time. Provided that the system should be installed on all aircraft and integrated on board to properly ensure its functionality and interact with navigation systems.

Real-time dynamics of typical and untypical states in nonintegrable systems

Science.gov (United States)

Richter, Jonas; Jin, Fengping; De Raedt, Hans; Michielsen, Kristel; Gemmer, Jochen; Steinigeweg, Robin

2018-05-01

Understanding (i) the emergence of diffusion from truly microscopic principles continues to be a major challenge in experimental and theoretical physics. At the same time, isolated quantum many-body systems have experienced an upsurge of interest in recent years. Since in such systems the realization of a proper initial state is the only possibility to induce a nonequilibrium process, understanding (ii) the largely unexplored role of the specific realization is vitally important. Our work reports a substantial step forward and tackles the two issues (i) and (ii) in the context of typicality, entanglement as well as integrability and nonintegrability. Specifically, we consider the spin-1/2 XXZ chain, where integrability can be broken due to an additional next-nearest neighbor interaction, and study the real-time and real-space dynamics of nonequilibrium magnetization profiles for a class of pure states. Summarizing our main results, we show that signatures of diffusion for strong interactions are equally pronounced for the integrable and nonintegrable case. In both cases, we further find a clear difference between the dynamics of states with and without internal randomness. We provide an explanation of this difference by a detailed analysis of the local density of states.

Modelling and analysis of real-time and hybrid systems

Energy Technology Data Exchange (ETDEWEB)

Olivero, A

1994-09-29

This work deals with the modelling and analysis of real-time and hybrid systems. We first present the timed-graphs as model for the real-time systems and we recall the basic notions of the analysis of real-time systems. We describe the temporal properties on the timed-graphs using TCTL formulas. We consider two methods for property verification: in one hand we study the symbolic model-checking (based on backward analysis) and in the other hand we propose a verification method derived of the construction of the simulation graph (based on forward analysis). Both methods have been implemented within the KRONOS verification tool. Their application for the automatic verification on several real-time systems confirms the practical interest of our approach. In a second part we study the hybrid systems, systems combining discrete components with continuous ones. As in the general case the analysis of this king of systems is not decidable, we identify two sub-classes of hybrid systems and we give a construction based method for the generation of a timed-graph from an element into the sub-classes. We prove that in one case the timed-graph obtained is bi-similar with the considered system and that there exists a simulation in the other case. These relationships allow the application of the described technics on the hybrid systems into the defined sub-classes. (authors). 60 refs., 43 figs., 8 tabs., 2 annexes.

Application of the Real-Time Time-Dependent Density Functional Theory to Excited-State Dynamics of Molecules and 2D Materials

Science.gov (United States)

Miyamoto, Yoshiyuki; Rubio, Angel

2018-04-01

We review our recent developments in the ab initio simulation of excited-state dynamics within the framework of time-dependent density functional theory (TDDFT). Our targets range from molecules to 2D materials, although the methods are general and can be applied to any other finite and periodic systems. We discuss examples of excited-state dynamics obtained by real-time TDDFT coupled with molecular dynamics (MD) and the Ehrenfest approximation, including photoisomerization in molecules, photoenhancement of the weak interatomic attraction of noble gas atoms, photoenhancement of the weak interlayer interaction of 2D materials, pulse-laser-induced local bond breaking of adsorbed atoms on 2D sheets, modulation of UV light intensity by graphene nanoribbons at terahertz frequencies, and collision of high-speed ions with the 2D material to simulate the images taken by He ion microscopy. We illustrate how the real-time TDDFT approach is useful for predicting and understanding non-equilibrium dynamics in condensed matter. We also discuss recent developments that address the excited-state dynamics of systems out of equilibrium and future challenges in this fascinating field of research.

DYNAMIC STRAIN MAPPING AND REAL-TIME DAMAGE STATE ESTIMATION UNDER BIAXIAL RANDOM FATIGUE LOADING

Data.gov (United States)

National Aeronautics and Space Administration — DYNAMIC STRAIN MAPPING AND REAL-TIME DAMAGE STATE ESTIMATION UNDER BIAXIAL RANDOM FATIGUE LOADING SUBHASISH MOHANTY*, ADITI CHATTOPADHYAY, JOHN N. RAJADAS, AND CLYDE...

WCET Analysis of ARM Processors using Real-Time Model Checking

DEFF Research Database (Denmark)

Toft, Martin; Olesen, Mads Christian; Dalsgaard, Andreas

2009-01-01

This paper presents a flexible method that utilises real-time model checking to determine safe and sharp WCETs for processes running on hardware platforms featuring pipelining and caching.......This paper presents a flexible method that utilises real-time model checking to determine safe and sharp WCETs for processes running on hardware platforms featuring pipelining and caching....

Real-time traffic signal optimization model based on average delay time per person

Directory of Open Access Journals (Sweden)

Pengpeng Jiao

2015-10-01

Full Text Available Real-time traffic signal control is very important for relieving urban traffic congestion. Many existing traffic control models were formulated using optimization approach, with the objective functions of minimizing vehicle delay time. To improve people’s trip efficiency, this article aims to minimize delay time per person. Based on the time-varying traffic flow data at intersections, the article first fits curves of accumulative arrival and departure vehicles, as well as the corresponding functions. Moreover, this article transfers vehicle delay time to personal delay time using average passenger load of cars and buses, employs such time as the objective function, and proposes a signal timing optimization model for intersections to achieve real-time signal parameters, including cycle length and green time. This research further implements a case study based on practical data collected at an intersection in Beijing, China. The average delay time per person and queue length are employed as evaluation indices to show the performances of the model. The results show that the proposed methodology is capable of improving traffic efficiency and is very effective for real-world applications.

Real-time photorealistic stereoscopic rendering of fire

Science.gov (United States)

Rose, Benjamin M.; McAllister, David F.

2007-02-01

We propose a method for real-time photorealistic stereo rendering of the natural phenomenon of fire. Applications include the use of virtual reality in fire fighting, military training, and entertainment. Rendering fire in real-time presents a challenge because of the transparency and non-static fluid-like behavior of fire. It is well known that, in general, methods that are effective for monoscopic rendering are not necessarily easily extended to stereo rendering because monoscopic methods often do not provide the depth information necessary to produce the parallax required for binocular disparity in stereoscopic rendering. We investigate the existing techniques used for monoscopic rendering of fire and discuss their suitability for extension to real-time stereo rendering. Methods include the use of precomputed textures, dynamic generation of textures, and rendering models resulting from the approximation of solutions of fluid dynamics equations through the use of ray-tracing algorithms. We have found that in order to attain real-time frame rates, our method based on billboarding is effective. Slicing is used to simulate depth. Texture mapping or 2D images are mapped onto polygons and alpha blending is used to treat transparency. We can use video recordings or prerendered high-quality images of fire as textures to attain photorealistic stereo.

Real Time Systems

DEFF Research Database (Denmark)

Christensen, Knud Smed

2000-01-01

Describes fundamentals of parallel programming and a kernel for that. Describes methods for modelling and checking parallel problems. Real time problems.......Describes fundamentals of parallel programming and a kernel for that. Describes methods for modelling and checking parallel problems. Real time problems....

Real-time statistical quality control and ARM

International Nuclear Information System (INIS)

Blough, D.K.

1992-05-01

An important component of the Atmospheric Radiation Measurement (ARM) Program is real-time quality control of data obtained from meteorological instruments. It is the goal of the ARM program to enhance the predictive capabilities of global circulation models by incorporating in them more detailed information on the radiative characteristics of the earth's atmosphere. To this end, a number of Cloud and Radiation Testbeds (CART's) will be built at various locations worldwide. Each CART will consist of an array of instruments designed to collect radiative data. The large amount of data obtained from these instruments necessitates real-time processing in order to flag outliers and possible instrument malfunction. The Bayesian dynamic linear model (DLM) proves to be an effective way of monitoring the time series data which each instrument generates. It provides a flexible yet powerful approach to detecting in real-time sudden shifts in a non-stationary multivariate time series. An application of these techniques to data arising from a remote sensing instrument to be used in the CART is provided. Using real data from a wind profiler, the ability of the DLM to detect outliers is studied. 5 refs

Wave optics modeling of real-time holographic wavefront compensation systems using OSSim

Science.gov (United States)

Carbon, Margarita A.; Guthals, Dennis M.; Logan, Jerry D.

2005-08-01

OSSim (Optical System Simulation) is a wave-optics, time-domain simulation toolbox with both optical and data processing components developed for adaptive optics (AO) systems. Diffractive wavefront control elements have recently been added that accurately model optically and electrically addressed spatial light modulators as real time holographic (RTH) devices in diffractive wavefront control systems. The developed RTH toolbox has found multiple applications for a variety of Boeing programs in solving problems of AO system analysis and design. Several complex diffractive wavefront control systems have been modeled for compensation of static and dynamic aberrations such as imperfect segmented primary mirrors and atmospheric and boundary layer turbulence. The results of OSSim simulations of RTH wavefront compensation show very good agreement with available experimental data.

A real-time, dynamic early-warning model based on uncertainty analysis and risk assessment for sudden water pollution accidents.

Science.gov (United States)

Hou, Dibo; Ge, Xiaofan; Huang, Pingjie; Zhang, Guangxin; Loáiciga, Hugo

2014-01-01

A real-time, dynamic, early-warning model (EP-risk model) is proposed to cope with sudden water quality pollution accidents affecting downstream areas with raw-water intakes (denoted as EPs). The EP-risk model outputs the risk level of water pollution at the EP by calculating the likelihood of pollution and evaluating the impact of pollution. A generalized form of the EP-risk model for river pollution accidents based on Monte Carlo simulation, the analytic hierarchy process (AHP) method, and the risk matrix method is proposed. The likelihood of water pollution at the EP is calculated by the Monte Carlo method, which is used for uncertainty analysis of pollutants' transport in rivers. The impact of water pollution at the EP is evaluated by expert knowledge and the results of Monte Carlo simulation based on the analytic hierarchy process. The final risk level of water pollution at the EP is determined by the risk matrix method. A case study of the proposed method is illustrated with a phenol spill accident in China.

Real time expert systems

International Nuclear Information System (INIS)

Asami, Tohru; Hashimoto, Kazuo; Yamamoto, Seiichi

1992-01-01

Recently, aiming at the application to the plant control for nuclear reactors and traffic and communication control, the research and the practical use of the expert system suitable to real time processing have become conspicuous. In this report, the condition for the required function to control the object that dynamically changes within a limited time is presented, and the technical difference between the real time expert system developed so as to satisfy it and the expert system of conventional type is explained with the actual examples and from theoretical aspect. The expert system of conventional type has the technical base in the problem-solving equipment originating in STRIPS. The real time expert system is applied to the fields accompanied by surveillance and control, to which conventional expert system is hard to be applied. The requirement for the real time expert system, the example of the real time expert system, and as the techniques of realizing real time processing, the realization of interruption processing, dispersion processing, and the mechanism of maintaining the consistency of knowledge are explained. (K.I.)

Dynamic ADMM for Real-time Optimal Power Flow: Preprint

Energy Technology Data Exchange (ETDEWEB)

Dall-Anese, Emiliano [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2018-02-23

This paper considers distribution networks featuring distributed energy resources (DERs), and develops a dynamic optimization method to maximize given operational objectives in real time while adhering to relevant network constraints. The design of the dynamic algorithm is based on suitable linearizations of the AC power flow equations, and it leverages the so-called alternating direction method of multipliers (ADMM). The steps of the ADMM, however, are suitably modified to accommodate appropriate measurements from the distribution network and the DERs. With the aid of these measurements, the resultant algorithm can enforce given operational constraints in spite of inaccuracies in the representation of the AC power flows, and it avoids ubiquitous metering to gather the state of non-controllable resources. Optimality and convergence of the propose algorithm are established in terms of tracking of the solution of a convex surrogate of the AC optimal power flow problem.

Real-Time System for Water Modeling and Management

Science.gov (United States)

Lee, J.; Zhao, T.; David, C. H.; Minsker, B.

2012-12-01

Working closely with the Texas Commission on Environmental Quality (TCEQ) and the University of Texas at Austin (UT-Austin), we are developing a real-time system for water modeling and management using advanced cyberinfrastructure, data integration and geospatial visualization, and numerical modeling. The state of Texas suffered a severe drought in 2011 that cost the state $7.62 billion in agricultural losses (crops and livestock). Devastating situations such as this could potentially be avoided with better water modeling and management strategies that incorporate state of the art simulation and digital data integration. The goal of the project is to prototype a near-real-time decision support system for river modeling and management in Texas that can serve as a national and international model to promote more sustainable and resilient water systems. The system uses National Weather Service current and predicted precipitation data as input to the Noah-MP Land Surface model, which forecasts runoff, soil moisture, evapotranspiration, and water table levels given land surface features. These results are then used by a river model called RAPID, along with an error model currently under development at UT-Austin, to forecast stream flows in the rivers. Model forecasts are visualized as a Web application for TCEQ decision makers, who issue water diversion (withdrawal) permits and any needed drought restrictions; permit holders; and reservoir operation managers. Users will be able to adjust model parameters to predict the impacts of alternative curtailment scenarios or weather forecasts. A real-time optimization system under development will help TCEQ to identify optimal curtailment strategies to minimize impacts on permit holders and protect health and safety. To develop the system we have implemented RAPID as a remotely-executed modeling service using the Cyberintegrator workflow system with input data downloaded from the North American Land Data Assimilation System. The

Real-Time Reliability Verification for UAV Flight Control System Supporting Airworthiness Certification.

Science.gov (United States)

Xu, Haiyang; Wang, Ping

2016-01-01

In order to verify the real-time reliability of unmanned aerial vehicle (UAV) flight control system and comply with the airworthiness certification standard, we proposed a model-based integration framework for modeling and verification of time property. Combining with the advantages of MARTE, this framework uses class diagram to create the static model of software system, and utilizes state chart to create the dynamic model. In term of the defined transformation rules, the MARTE model could be transformed to formal integrated model, and the different part of the model could also be verified by using existing formal tools. For the real-time specifications of software system, we also proposed a generating algorithm for temporal logic formula, which could automatically extract real-time property from time-sensitive live sequence chart (TLSC). Finally, we modeled the simplified flight control system of UAV to check its real-time property. The results showed that the framework could be used to create the system model, as well as precisely analyze and verify the real-time reliability of UAV flight control system.

Intelligent data management for real-time spacecraft monitoring

Science.gov (United States)

Schwuttke, Ursula M.; Gasser, Les; Abramson, Bruce

1992-01-01

Real-time AI systems have begun to address the challenge of restructuring problem solving to meet real-time constraints by making key trade-offs that pursue less than optimal strategies with minimal impact on system goals. Several approaches for adapting to dynamic changes in system operating conditions are known. However, simultaneously adapting system decision criteria in a principled way has been difficult. Towards this end, a general technique for dynamically making such trade-offs using a combination of decision theory and domain knowledge has been developed. Multi-attribute utility theory (MAUT), a decision theoretic approach for making one-time decisions is discussed and dynamic trade-off evaluation is described as a knowledge-based extension of MAUT that is suitable for highly dynamic real-time environments, and provides an example of dynamic trade-off evaluation applied to a specific data management trade-off in a real-world spacecraft monitoring application.

Modeling and Analyzing Real-Time Multiprocessor Systems

NARCIS (Netherlands)

Wiggers, M.H.; Thiele, Lothar; Lee, Edward A.; Schlieker, Simon; Bekooij, Marco Jan Gerrit

2010-01-01

Researchers have proposed approaches to verify that real-time multiprocessor systems meet their timeliness constraints. These approaches make assumptions on the model of computation, the load placed on the multiprocessor system, and the faults that can arise. This heterogeneous set of assumptions

Platform for real-time simulation of dynamic systems and hardware-in-the-loop for control algorithms.

Science.gov (United States)

de Souza, Isaac D T; Silva, Sergio N; Teles, Rafael M; Fernandes, Marcelo A C

2014-10-15

The development of new embedded algorithms for automation and control of industrial equipment usually requires the use of real-time testing. However, the equipment required is often expensive, which means that such tests are often not viable. The objective of this work was therefore to develop an embedded platform for the distributed real-time simulation of dynamic systems. This platform, called the Real-Time Simulator for Dynamic Systems (RTSDS), could be applied in both industrial and academic environments. In industrial applications, the RTSDS could be used to optimize embedded control algorithms. In the academic sphere, it could be used to support research into new embedded solutions for automation and control and could also be used as a tool to assist in undergraduate and postgraduate teaching related to the development of projects concerning on-board control systems.

Combining driveline and suspension models for real-time simulations / Kombination von Antriebs- und Fahrwerksmodellen zur Echtzeit-Simulation

NARCIS (Netherlands)

Vis, M.A.; Venne, J.W.C.M. van de; Vink, W.J.; Steen, M. van der; Lupker, H.A.

2000-01-01

A Modular Vehicle (MoVe) library is presented, containing driveline and vehicle dynamics component models. The library is built in Matlab\\Simulink, taking advantage of its modular capabilities and real-time application possibilities. Its use is demonstrated with the construction of a 4-wheel car,

D Model Visualization Enhancements in Real-Time Game Engines

Science.gov (United States)

Merlo, A.; Sánchez Belenguer, C.; Vendrell Vidal, E.; Fantini, F.; Aliperta, A.

2013-02-01

This paper describes two procedures used to disseminate tangible cultural heritage through real-time 3D simulations providing accurate-scientific representations. The main idea is to create simple geometries (with low-poly count) and apply two different texture maps to them: a normal map and a displacement map. There are two ways to achieve models that fit with normal or displacement maps: with the former (normal maps), the number of polygons in the reality-based model may be dramatically reduced by decimation algorithms and then normals may be calculated by rendering them to texture solutions (baking). With the latter, a LOD model is needed; its topology has to be quad-dominant for it to be converted to a good quality subdivision surface (with consistent tangency and curvature all over). The subdivision surface is constructed using methodologies for the construction of assets borrowed from character animation: these techniques have been recently implemented in many entertainment applications known as "retopology". The normal map is used as usual, in order to shade the surface of the model in a realistic way. The displacement map is used to finish, in real-time, the flat faces of the object, by adding the geometric detail missing in the low-poly models. The accuracy of the resulting geometry is progressively refined based on the distance from the viewing point, so the result is like a continuous level of detail, the only difference being that there is no need to create different 3D models for one and the same object. All geometric detail is calculated in real-time according to the displacement map. This approach can be used in Unity, a real-time 3D engine originally designed for developing computer games. It provides a powerful rendering engine, fully integrated with a complete set of intuitive tools and rapid workflows that allow users to easily create interactive 3D contents. With the release of Unity 4.0, new rendering features have been added, including Direct

Stress Analysis and Fatigue Behaviour of PTFE-Bronze Layered Journal Bearing under Real-Time Dynamic Loading

Science.gov (United States)

Duman, M. S.; Kaplan, E.; Cuvalcı, O.

2018-01-01

The present paper is based on experimental studies and numerical simulations on the surface fatigue failure of the PTFE-bronze layered journal bearings under real-time loading. ‘Permaglide Plain Bearings P10’ type journal bearings were experimentally tested under different real time dynamic loadings by using real time journal bearing test system in our laboratory. The journal bearing consists of a PTFE-bronze layer approximately 0.32 mm thick on the steel support layer with 2.18 mm thick. Two different approaches have been considered with in experiments: (i) under real- time constant loading with varying bearing widths, (ii) under different real-time loadings at constant bearing widths. Fatigue regions, micro-crack dispersion and stress distributions occurred at the journal bearing were experimentally and theoretically investigated. The relation between fatigue region and pressure distributions were investigated by determining the circumferential pressure distribution under real-time dynamic loadings for the position of every 10° crank angles. In the theoretical part; stress and deformation distributions at the surface of the journal bearing analysed by using finite element methods to determine the relationship between stress and fatigue behaviour. As a result of this study, the maximum oil pressure and fatigue cracks were observed in the most heavily loaded regions of the bearing surface. Experimental results show that PTFE-Bronze layered journal bearings fatigue behaviour is better than the bearings include white metal alloy.

Real-time Social Internet Data to Guide Forecasting Models

Energy Technology Data Exchange (ETDEWEB)

Del Valle, Sara Y. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-09-20

Our goal is to improve decision support by monitoring and forecasting events using social media, mathematical models, and quantifying model uncertainty. Our approach is real-time, data-driven forecasts with quantified uncertainty: Not just for weather anymore. Information flow from human observations of events through an Internet system and classification algorithms is used to produce quantitatively uncertain forecast. In summary, we want to develop new tools to extract useful information from Internet data streams, develop new approaches to assimilate real-time information into predictive models, validate approaches by forecasting events, and our ultimate goal is to develop an event forecasting system using mathematical approaches and heterogeneous data streams.

Real-space and real-time dynamics of CRISPR-Cas9 visualized by high-speed atomic force microscopy.

Science.gov (United States)

Shibata, Mikihiro; Nishimasu, Hiroshi; Kodera, Noriyuki; Hirano, Seiichi; Ando, Toshio; Uchihashi, Takayuki; Nureki, Osamu

2017-11-10

The CRISPR-associated endonuclease Cas9 binds to a guide RNA and cleaves double-stranded DNA with a sequence complementary to the RNA guide. The Cas9-RNA system has been harnessed for numerous applications, such as genome editing. Here we use high-speed atomic force microscopy (HS-AFM) to visualize the real-space and real-time dynamics of CRISPR-Cas9 in action. HS-AFM movies indicate that, whereas apo-Cas9 adopts unexpected flexible conformations, Cas9-RNA forms a stable bilobed structure and interrogates target sites on the DNA by three-dimensional diffusion. These movies also provide real-time visualization of the Cas9-mediated DNA cleavage process. Notably, the Cas9 HNH nuclease domain fluctuates upon DNA binding, and subsequently adopts an active conformation, where the HNH active site is docked at the cleavage site in the target DNA. Collectively, our HS-AFM data extend our understanding of the action mechanism of CRISPR-Cas9.

Logic Model Checking of Time-Periodic Real-Time Systems

Science.gov (United States)

Florian, Mihai; Gamble, Ed; Holzmann, Gerard

2012-01-01

In this paper we report on the work we performed to extend the logic model checker SPIN with built-in support for the verification of periodic, real-time embedded software systems, as commonly used in aircraft, automobiles, and spacecraft. We first extended the SPIN verification algorithms to model priority based scheduling policies. Next, we added a library to support the modeling of periodic tasks. This library was used in a recent application of the SPIN model checker to verify the engine control software of an automobile, to study the feasibility of software triggers for unintended acceleration events.

Real-time process optimization based on grey-box neural models

Directory of Open Access Journals (Sweden)

F. A. Cubillos

2007-09-01

Full Text Available This paper investigates the feasibility of using grey-box neural models (GNM in Real Time Optimization (RTO. These models are based on a suitable combination of fundamental conservation laws and neural networks, being used in at least two different ways: to complement available phenomenological knowledge with empirical information, or to reduce dimensionality of complex rigorous physical models. We have observed that the benefits of using these simple adaptable models are counteracted by some difficulties associated with the solution of the optimization problem. Nonlinear Programming (NLP algorithms failed in finding the global optimum due to the fact that neural networks can introduce multimodal objective functions. One alternative considered to solve this problem was the use of some kind of evolutionary algorithms, like Genetic Algorithms (GA. Although these algorithms produced better results in terms of finding the appropriate region, they took long periods of time to reach the global optimum. It was found that a combination of genetic and nonlinear programming algorithms can be use to fast obtain the optimum solution. The proposed approach was applied to the Williams-Otto reactor, considering three different GNM models of increasing complexity. Results demonstrated that the use of GNM models and mixed GA/NLP optimization algorithms is a promissory approach for solving dynamic RTO problems.

Dynamic factor analysis in the frequency domain: causal modeling of multivariate psychophysiological time series

NARCIS (Netherlands)

Molenaar, P.C.M.

1987-01-01

Outlines a frequency domain analysis of the dynamic factor model and proposes a solution to the problem of constructing a causal filter of lagged factor loadings. The method is illustrated with applications to simulated and real multivariate time series. The latter applications involve topographic

Realistic 3D Terrain Roaming and Real-Time Flight Simulation

Science.gov (United States)

Que, Xiang; Liu, Gang; He, Zhenwen; Qi, Guang

2014-12-01

This paper presents an integrate method, which can provide access to current status and the dynamic visible scanning topography, to enhance the interactive during the terrain roaming and real-time flight simulation. A digital elevation model and digital ortho-photo map data integrated algorithm is proposed as the base algorithm for our approach to build a realistic 3D terrain scene. A new technique with help of render to texture and head of display for generating the navigation pane is used. In the flight simulating, in order to eliminate flying "jump", we employs the multidimensional linear interpolation method to adjust the camera parameters dynamically and steadily. Meanwhile, based on the principle of scanning laser imaging, we draw pseudo color figures by scanning topography in different directions according to the real-time flying status. Simulation results demonstrate that the proposed algorithm is prospective for applications and the method can improve the effect and enhance dynamic interaction during the real-time flight.

A Dynamic Traffic Signal Timing Model and its Algorithm for Junction of Urban Road

DEFF Research Database (Denmark)

Cai, Yanguang; Cai, Hao

2012-01-01

As an important part of Intelligent Transportation System, the scientific traffic signal timing of junction can improve the efficiency of urban transport. This paper presents a novel dynamic traffic signal timing model. According to the characteristics of the model, hybrid chaotic quantum...... evolutionary algorithm is employed to solve it. The proposed model has simple structure, and only requires traffic inflow speed and outflow speed are bounded functions with at most finite number of discontinuity points. The condition is very loose and better meets the requirements of the practical real......-time and dynamic signal control of junction. To obtain the optimal solution of the model by hybrid chaotic quantum evolutionary algorithm, the model is converted to an easily solvable form. To simplify calculation, we give the expression of the partial derivative and change rate of the objective function...

Real-time Face Detection using Skin Color Model

Institute of Scientific and Technical Information of China (English)

LU Yao-xin; LIU Zhi-Qiang; ZHU Xiang-hua

2004-01-01

This paper presents a new face detection approach to real-time applications, which is based on the skin color model and the morphological filtering. First the non-skin color pixels of the input image are removed based on the skin color model in the YCrCb chrominance space, from which we extract candidate human face regions. Then a mathematical morphological filter is used to remove noisy regions and fill the holes in the candidate skin color regions. We adopt the similarity between the human face features and the candidate face regions to locate the face regions in the original image. We have implemented the algorithm in our smart media system. The experiment results show that this system is effective in real-time applications.

Optimizing Real-Time Vaccine Allocation in a Stochastic SIR Model.

Directory of Open Access Journals (Sweden)

Chantal Nguyen

Full Text Available Real-time vaccination following an outbreak can effectively mitigate the damage caused by an infectious disease. However, in many cases, available resources are insufficient to vaccinate the entire at-risk population, logistics result in delayed vaccine deployment, and the interaction between members of different cities facilitates a wide spatial spread of infection. Limited vaccine, time delays, and interaction (or coupling of cities lead to tradeoffs that impact the overall magnitude of the epidemic. These tradeoffs mandate investigation of optimal strategies that minimize the severity of the epidemic by prioritizing allocation of vaccine to specific subpopulations. We use an SIR model to describe the disease dynamics of an epidemic which breaks out in one city and spreads to another. We solve a master equation to determine the resulting probability distribution of the final epidemic size. We then identify tradeoffs between vaccine, time delay, and coupling, and we determine the optimal vaccination protocols resulting from these tradeoffs.

Real-time dynamics of matrix quantum mechanics beyond the classical approximation

Science.gov (United States)

Buividovich, Pavel; Hanada, Masanori; Schäfer, Andreas

2018-03-01

We describe a numerical method which allows to go beyond the classical approximation for the real-time dynamics of many-body systems by approximating the many-body Wigner function by the most general Gaussian function with time-dependent mean and dispersion. On a simple example of a classically chaotic system with two degrees of freedom we demonstrate that this Gaussian state approximation is accurate for significantly smaller field strengths and longer times than the classical one. Applying this approximation to matrix quantum mechanics, we demonstrate that the quantum Lyapunov exponents are in general smaller than their classical counterparts, and even seem to vanish below some temperature. This behavior resembles the finite-temperature phase transition which was found for this system in Monte-Carlo simulations, and ensures that the system does not violate the Maldacena-Shenker-Stanford bound λL < 2πT, which inevitably happens for classical dynamics at sufficiently small temperatures.

A dynamic real time in vivo and static ex vivo analysis of granulomonocytic cell migration in the collagen-induced arthritis model.

Directory of Open Access Journals (Sweden)

Ruth Byrne

Full Text Available Neutrophilic granulocytes and monocytes (granulomonocytic cells; GMC drive the inflammatory process at the earliest stages of rheumatoid arthritis (RA. The migratory behavior and functional properties of GMC within the synovial tissue are, however, only incompletely characterized. Here we have analyzed GMC in the murine collagen-induced arthritis (CIA model of RA using multi-photon real time in vivo microscopy together with ex vivo analysis of GMC in tissue sections.GMC were abundant as soon as clinical arthritis was apparent. GMC were motile and migrated randomly through the synovial tissue. In addition, we observed the frequent formation of cell clusters consisting of both neutrophilic granulocytes and monocytes that actively contributed to the inflammatory process of arthritis. Treatment of animals with a single dose of prednisolone reduced the mean velocity of cell migration and diminished the overall immigration of GMC.In summary, our study shows that the combined application of real time in vivo microscopy together with elaborate static post-mortem analysis of GMC enables the description of dynamic migratory characteristics of GMC together with their precise location in a complex anatomical environment. Moreover, this approach is sensitive enough to detect subtle therapeutic effects within a very short period of time.

The effects of combining dynamic pricing, AC load control, and real-time energy feedback. SMUD'S 2011 Residential Summer Solutions Study

Energy Technology Data Exchange (ETDEWEB)

Herter, K. [Herter Energy Research Solutions, El Dorado Hills, CA (United States); Wood, V. [Sacramento Municipal Utility District, Sacramento, CA (United States); Blozis, S. [University of California, Davis, CA (United States)

2013-11-15

The 2011 Residential Summer Solutions Study compared the hourly load effects of three different real-time information treatments and two program options. The information treatments included: Baseline information (no real-time data), real-time Home information (whole-house data), and real-time Appliance information (data for the whole house plus three individual appliances). Compared to the Baseline group, real-time Home information lowered overall energy use by about 4 %. Real-time information at both the Home and Appliance levels had a significant effect on non-event peak loads: compared to the Baseline group, real-time Home data lowered peak load by 5 %, while Appliance data lowered peak load by 7 %. All three information treatments averaged a 1-kW (40 %) load shed during events. The customer-chosen program options included a dynamic time-of-use rate and a load control incentive program. Customers were more likely to sign up for the dynamic rate, and those who did saved significantly more peak load on both event days (>50 % savings) and non-event days (>20 % savings) than did those on the load control program alone. In addition, those on the dynamic rate saved twice as much on their summer bills as did those who chose to remain on the standard tiered rate. At the end of the summer, more than 90 % of participants signed up to participate again the following year.

Modeling dynamic swarms

KAUST Repository

Ghanem, Bernard

2013-01-01

This paper proposes the problem of modeling video sequences of dynamic swarms (DSs). We define a DS as a large layout of stochastically repetitive spatial configurations of dynamic objects (swarm elements) whose motions exhibit local spatiotemporal interdependency and stationarity, i.e., the motions are similar in any small spatiotemporal neighborhood. Examples of DS abound in nature, e.g., herds of animals and flocks of birds. To capture the local spatiotemporal properties of the DS, we present a probabilistic model that learns both the spatial layout of swarm elements (based on low-level image segmentation) and their joint dynamics that are modeled as linear transformations. To this end, a spatiotemporal neighborhood is associated with each swarm element, in which local stationarity is enforced both spatially and temporally. We assume that the prior on the swarm dynamics is distributed according to an MRF in both space and time. Embedding this model in a MAP framework, we iterate between learning the spatial layout of the swarm and its dynamics. We learn the swarm transformations using ICM, which iterates between estimating these transformations and updating their distribution in the spatiotemporal neighborhoods. We demonstrate the validity of our method by conducting experiments on real and synthetic video sequences. Real sequences of birds, geese, robot swarms, and pedestrians evaluate the applicability of our model to real world data. © 2012 Elsevier Inc. All rights reserved.

A generalised Dynamic Overflow Risk Assessment (DORA) for Real Time Control of urban drainage systems

DEFF Research Database (Denmark)

Vezzaro, Luca; Grum, Morten

2014-01-01

An innovative and generalised approach to the integrated Real Time Control of urban drainage systems is presented. The Dynamic Overflow Risk Assessment (DORA) strategy aims to minimise the expected Combined Sewer Overflow (CSO) risk by considering (i) the water volume presently stored in the drai......An innovative and generalised approach to the integrated Real Time Control of urban drainage systems is presented. The Dynamic Overflow Risk Assessment (DORA) strategy aims to minimise the expected Combined Sewer Overflow (CSO) risk by considering (i) the water volume presently stored...... and their uncertainty contributed to further improving the performance of drainage systems. The results of this paper will contribute to the wider usage of global RTC methods in the management of urban drainage networks....

Forecasting Hourly Water Demands With Seasonal Autoregressive Models for Real-Time Application

Science.gov (United States)

Chen, Jinduan; Boccelli, Dominic L.

2018-02-01

Consumer water demands are not typically measured at temporal or spatial scales adequate to support real-time decision making, and recent approaches for estimating unobserved demands using observed hydraulic measurements are generally not capable of forecasting demands and uncertainty information. While time series modeling has shown promise for representing total system demands, these models have generally not been evaluated at spatial scales appropriate for representative real-time modeling. This study investigates the use of a double-seasonal time series model to capture daily and weekly autocorrelations to both total system demands and regional aggregated demands at a scale that would capture demand variability across a distribution system. Emphasis was placed on the ability to forecast demands and quantify uncertainties with results compared to traditional time series pattern-based demand models as well as nonseasonal and single-seasonal time series models. Additional research included the implementation of an adaptive-parameter estimation scheme to update the time series model when unobserved changes occurred in the system. For two case studies, results showed that (1) for the smaller-scale aggregated water demands, the log-transformed time series model resulted in improved forecasts, (2) the double-seasonal model outperformed other models in terms of forecasting errors, and (3) the adaptive adjustment of parameters during forecasting improved the accuracy of the generated prediction intervals. These results illustrate the capabilities of time series modeling to forecast both water demands and uncertainty estimates at spatial scales commensurate for real-time modeling applications and provide a foundation for developing a real-time integrated demand-hydraulic model.

Using a Bayesian Probabilistic Forecasting Model to Analyze the Uncertainty in Real-Time Dynamic Control of the Flood Limiting Water Level for Reservoir Operation

DEFF Research Database (Denmark)

Liu, Dedi; Li, Xiang; Guo, Shenglian

2015-01-01

Dynamic control of the flood limiting water level (FLWL) is a valuable and effective way to maximize the benefits from reservoir operation without exceeding the design risk. In order to analyze the impacts of input uncertainty, a Bayesian forecasting system (BFS) is adopted. Applying quantile water...... inflow values and their uncertainties obtained from the BFS, the reservoir operation results from different schemes can be analyzed in terms of benefits, dam safety, and downstream impacts during the flood season. When the reservoir FLWL dynamic control operation is implemented, there are two fundamental......, also deterministic water inflow was tested. The proposed model in the paper emphasizes the importance of analyzing the uncertainties of the water inflow forecasting system for real-time dynamic control of the FLWL for reservoir operation. For the case study, the selected quantile inflow from...

Dynamical Behaviors in Complex-Valued Love Model With or Without Time Delays

Science.gov (United States)

Deng, Wei; Liao, Xiaofeng; Dong, Tao

2017-12-01

In this paper, a novel version of nonlinear model, i.e. a complex-valued love model with two time delays between two individuals in a love affair, has been proposed. A notable feature in this model is that we separate the emotion of one individual into real and imaginary parts to represent the variation and complexity of psychophysiological emotion in romantic relationship instead of just real domain, and make our model much closer to reality. This is because love is a complicated cognitive and social phenomenon, full of complexity, diversity and unpredictability, which refers to the coexistence of different aspects of feelings, states and attitudes ranging from joy and trust to sadness and disgust. By analyzing associated characteristic equation of linearized equations for our model, it is found that the Hopf bifurcation occurs when the sum of time delays passes through a sequence of critical value. Stability of bifurcating cyclic love dynamics is also derived by applying the normal form theory and the center manifold theorem. In addition, it is also shown that, for some appropriate chosen parameters, chaotic behaviors can appear even without time delay.

On the Designing of Model Checkers for Real-Time Distributed Systems

Directory of Open Access Journals (Sweden)

D. Yu. Volkanov

2012-01-01

Full Text Available To verify real-time properties of UML statecharts one may apply a UPPAAL, toolbox for model checking of real-time systems. One of the most suitable ways to specify an operational semantics of UML statecharts is to invoke the formal model of Hierarchical Timed Automata. Since the model language of UPPAAL is based on Networks of Timed Automata one has to provide a conversion of Hierarchical Timed Automata to Networks of Timed Automata. In this paper we describe this conversion algorithm and prove that it is correct w.r.t. UPPAAL query language which is based on the subset of Timed CTL.

Real-time dynamic calibration of a tunable frequency laser source using a Fabry-Pérot interferometer

Energy Technology Data Exchange (ETDEWEB)

Mandula, Gábor, E-mail: mandula.gabor@wigner.mta.hu; Kis, Zsolt; Lengyel, Krisztián [Wigner Research Centre for Physics of the Hungarian Academy of Sciences, Konkoly-Thege Miklós út 29-33, H-1121 Budapest (Hungary)

2015-12-15

We report on a method for real-time dynamic calibration of a tunable external cavity diode laser by using a partially mode-matched plano-concave Fabry-Pérot interferometer in reflection geometry. Wide range laser frequency scanning is carried out by piezo-driven tilting of a diffractive grating playing the role of a frequency selective mirror in the laser cavity. The grating tilting system has a considerable mechanical inertness, so static laser frequency calibration leads to false results. The proposed real-time dynamic calibration based on the identification of primary- and Gouy-effect type secondary interference peaks with known frequency and temporal history can be used for a wide scanning range (from 0.2 GHz to more than 1 GHz). A concave spherical mirror with a radius of R = 100 cm and a plain 1% transmitting mirror was used as a Fabry-Pérot interferometer with various resonator lengths to investigate and demonstrate real-time calibration procedures for two kinds of laser frequency scanning functions.

Real-time GIS data model and sensor web service platform for environmental data management.

Science.gov (United States)

Gong, Jianya; Geng, Jing; Chen, Zeqiang

2015-01-09

Effective environmental data management is meaningful for human health. In the past, environmental data management involved developing a specific environmental data management system, but this method often lacks real-time data retrieving and sharing/interoperating capability. With the development of information technology, a Geospatial Service Web method is proposed that can be employed for environmental data management. The purpose of this study is to determine a method to realize environmental data management under the Geospatial Service Web framework. A real-time GIS (Geographic Information System) data model and a Sensor Web service platform to realize environmental data management under the Geospatial Service Web framework are proposed in this study. The real-time GIS data model manages real-time data. The Sensor Web service platform is applied to support the realization of the real-time GIS data model based on the Sensor Web technologies. To support the realization of the proposed real-time GIS data model, a Sensor Web service platform is implemented. Real-time environmental data, such as meteorological data, air quality data, soil moisture data, soil temperature data, and landslide data, are managed in the Sensor Web service platform. In addition, two use cases of real-time air quality monitoring and real-time soil moisture monitoring based on the real-time GIS data model in the Sensor Web service platform are realized and demonstrated. The total time efficiency of the two experiments is 3.7 s and 9.2 s. The experimental results show that the method integrating real-time GIS data model and Sensor Web Service Platform is an effective way to manage environmental data under the Geospatial Service Web framework.

Time Extensions of Petri Nets for Modelling and Verification of Hard Real-Time Systems

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Tomasz Szmuc

2002-01-01

Full Text Available The main aim ofthe paper is a presentation of time extensions of Petri nets appropriate for modelling and analysis of hard real-time systems. It is assumed, that the extensions must provide a model of time flow an ability to force a transition to fire within a stated timing constraint (the so-called the strong firing rule, and timing constraints represented by intervals. The presented survey includes extensions of classical Place/Transition Petri nets, as well as the ones applied to high-level Petri nets. An expressiveness of each time extension is illustrated using simple hard real-time system. The paper includes also a brief description of analysis and veryication methods related to the extensions, and a survey of software tools supporting modelling and analysis ofthe considered Petri nets.

Real-time inextensible surgical thread simulation.

Science.gov (United States)

Xu, Lang; Liu, Qian

2018-03-27

This paper discusses a real-time simulation method of inextensible surgical thread based on the Cosserat rod theory using position-based dynamics (PBD). The method realizes stable twining and knotting of surgical thread while including inextensibility, bending, twisting and coupling effects. The Cosserat rod theory is used to model the nonlinear elastic behavior of surgical thread. The surgical thread model is solved with PBD to achieve a real-time, extremely stable simulation. Due to the one-dimensional linear structure of surgical thread, the direct solution of the distance constraint based on tridiagonal matrix algorithm is used to enhance stretching resistance in every constraint projection iteration. In addition, continuous collision detection and collision response guarantee a large time step and high performance. Furthermore, friction is integrated into the constraint projection process to stabilize the twining of multiple threads and complex contact situations. Through comparisons with existing methods, the surgical thread maintains constant length under large deformation after applying the direct distance constraint in our method. The twining and knotting of multiple threads correspond to stable solutions to contact and friction forces. A surgical suture scene is also modeled to demonstrate the practicality and simplicity of our method. Our method achieves stable and fast simulation of inextensible surgical thread. Benefiting from the unified particle framework, the rigid body, elastic rod, and soft body can be simultaneously simulated. The method is appropriate for applications in virtual surgery that require multiple dynamic bodies.

A Model for Real-Time Data Reputation Via Cyber Telemetry

Science.gov (United States)

2016-06-01

methodology which focuses on iterative cycles, known as sprints, to produce the capabilities of the system. Traditional waterfall models do not allow for...NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS Approved for public release; distribution is unlimited A MODEL FOR REAL...Master’s Thesis 4. TITLE AND SUBTITLE A MODEL FOR REAL-TIME DATA REPUTATION VIA CYBER TELEMETRY 5. FUNDING NUMBERS 6. AUTHOR(S) Beau M

Real-time stylistic prediction for whole-body human motions.

Science.gov (United States)

Matsubara, Takamitsu; Hyon, Sang-Ho; Morimoto, Jun

2012-01-01

The ability to predict human motion is crucial in several contexts such as human tracking by computer vision and the synthesis of human-like computer graphics. Previous work has focused on off-line processes with well-segmented data; however, many applications such as robotics require real-time control with efficient computation. In this paper, we propose a novel approach called real-time stylistic prediction for whole-body human motions to satisfy these requirements. This approach uses a novel generative model to represent a whole-body human motion including rhythmic motion (e.g., walking) and discrete motion (e.g., jumping). The generative model is composed of a low-dimensional state (phase) dynamics and a two-factor observation model, allowing it to capture the diversity of motion styles in humans. A real-time adaptation algorithm was derived to estimate both state variables and style parameter of the model from non-stationary unlabeled sequential observations. Moreover, with a simple modification, the algorithm allows real-time adaptation even from incomplete (partial) observations. Based on the estimated state and style, a future motion sequence can be accurately predicted. In our implementation, it takes less than 15 ms for both adaptation and prediction at each observation. Our real-time stylistic prediction was evaluated for human walking, running, and jumping behaviors. Copyright © 2011 Elsevier Ltd. All rights reserved.

Real-Time Dynamic Simulation of Korean Power Grid for Frequency Regulation Control by MW Battery Energy Storage System

Directory of Open Access Journals (Sweden)

Tae-Hwan Jin

2016-12-01

Full Text Available The aim of this study was to develop a real-time dynamic simulator of a power grid with power plant and battery model. The simulator was used to investigate the frequency control characteristics of a megawatt-scale high-capacity energy storage system connected to the electric power grid. In this study, a lithium-ion secondary battery was chosen as one of the batteries for a grid-connected model. The dynamics of the model was analysed in both steady and transient states. The frequency control system of the battery model plays a role in regulating the grid frequency by controlling the power of energy storage systems according to process variables and grid frequencies. The power grid model based on the current power network of South Korea, included power plants, substations and power demands. The power supply is classified by the type of turbine generator as thermal, nuclear, hydro power, pumped power storage, combined power plants, and batteries, including high-capacity energy storage systems rated for a maximum of 500 MW. This study deals with an installed capacity of 87.17 GW and peak load of 77.30 GW in the Korean power grid. For 24 hours of operation, the maximum and minimum power outputs were simulated as 61.59 GW and 46.32 GW, respectively. The commercialized real-time dynamic simulation software ProTRAX was used. The simulation was conducted to observe the operation characteristics of the frequency control system during a breakdown of power plants, as well as under governor-free operation, auto generation control operation, and with the battery energy storage system connected. The results show that the model is valid for each power plant breakdown simulation. They also confirm that the output power and frequency controls of the battery operated well during simulations.

Real-time stability monitoring method for boiling water reactor nuclear power plants

International Nuclear Information System (INIS)

Fukunishi, K.; Suzuki, S.

1987-01-01

A method for real-time stability monitoring is developed for supervising the steady-state operation of a boiling water reactor core. The decay ratio of the reactor power fluctuation is determined by measuring only the output neutron noise. The concept of an inverse system is introduced to identify the dynamic characteristics of the reactor core. The adoption of an adaptive digital filter is useful in real-time identification. A feasibility test that used measured output noise as an indication of reactor power suggests that this method is useful in a real-time stability monitoring system. Using this method, the tedious and difficult work for modeling reactor core dynamics can be reduced. The method employs a simple algorithm that eliminates the need for stochastic computation, thus making the method suitable for real-time computation with a simple microprocessor. In addition, there is no need to disturb the reactor core during operation. Real-time stability monitoring using the proposed algorithm may allow operation under less stable margins

Real-time face and gesture analysis for human-robot interaction

Science.gov (United States)

Wallhoff, Frank; Rehrl, Tobias; Mayer, Christoph; Radig, Bernd

2010-05-01

Human communication relies on a large number of different communication mechanisms like spoken language, facial expressions, or gestures. Facial expressions and gestures are one of the main nonverbal communication mechanisms and pass large amounts of information between human dialog partners. Therefore, to allow for intuitive human-machine interaction, a real-time capable processing and recognition of facial expressions, hand and head gestures are of great importance. We present a system that is tackling these challenges. The input features for the dynamic head gestures and facial expressions are obtained from a sophisticated three-dimensional model, which is fitted to the user in a real-time capable manner. Applying this model different kinds of information are extracted from the image data and afterwards handed over to a real-time capable data-transferring framework, the so-called Real-Time DataBase (RTDB). In addition to the head and facial-related features, also low-level image features regarding the human hand - optical flow, Hu-moments are stored into the RTDB for the evaluation process of hand gestures. In general, the input of a single camera is sufficient for the parallel evaluation of the different gestures and facial expressions. The real-time capable recognition of the dynamic hand and head gestures are performed via different Hidden Markov Models, which have proven to be a quick and real-time capable classification method. On the other hand, for the facial expressions classical decision trees or more sophisticated support vector machines are used for the classification process. These obtained results of the classification processes are again handed over to the RTDB, where other processes (like a Dialog Management Unit) can easily access them without any blocking effects. In addition, an adjustable amount of history can be stored by the RTDB buffer unit.

Real-time dynamic control of the Three Gorges Reservoir by coupling numerical weather rainfall prediction and flood forecasting

DEFF Research Database (Denmark)

Wang, Y.; Chen, H.; Rosbjerg, Dan

2013-01-01

In reservoir operation improvement of the accuracy of forecast flood inflow and extension of forecast lead-time can effectively be achieved by using rainfall forecasts from numerical weather predictions with a hydrological catchment model. In this study, the Regional Spectrum Model (RSM), which...... is developed by the Japan Meteorological Agency, was used to forecast rainfall with 5 days lead-time in the upper region of the Three Gorges Reservoir (TGR). A conceptual hydrological model, the Xinanjiang Model, has been set up to forecast the inflow flood of TGR by the Ministry of Water Resources Information...... season 2012 as example, real-time dynamic control of the FLWL was implemented by using the forecasted reservoir flood inflow as input. The forecasted inflow with 5 days lead-time rainfall forecast was evaluated by several performance indices, including the mean relative error of the volumetric reservoir...

Real-time monitoring/emergency response modeling workstation for a tritium facility

International Nuclear Information System (INIS)

Lawver, B.S.; Sims, J.M.; Baskett, R.L.

1993-01-01

At Lawrence Livermore National Laboratory (LLNL) we have developed a real-time system to monitor two stacks on our tritium handling facility. The monitors transmit the stack data to a workstation, which computes a three-dimensional numerical model of atmospheric dispersion. The workstation also collects surface and upper air data from meteorological towers and a sodar. The complex meteorological and terrain setting in the Livermore Valley demands more sophisticated resolution of the three-dimensional structure of the atmosphere to reliably calculate plume dispersion than afforded by Gaussian models. We experience both mountain valley and sea breeze flows. To address these complexities, we have implemented the three-dimensional diagnostic MATHEW mass-adjusted wind field and ADPIC particle-in-cell dispersion models on the workstation for use in real-time emergency response modeling. Both MATHEW and ADPIC have shown their utility in a variety of complex settings over the last 15 yr within the U.S. Department of Energy's Atmospheric Release Advisory Capability (ARAC) project. Faster workstations and real-time instruments allow utilization of more complex three-dimensional models, which provides a foundation for building a real-time monitoring and emergency response workstation for a tritium facility. The stack monitors are two ion chambers per stack

Specifying and verifying requirements of real-time systems

DEFF Research Database (Denmark)

Ravn, Anders P.; Rischel, Hans; Hansen, Kirsten Mark

1993-01-01

, a real-time interval logic, where predicates define durations of states. Requirements define safety and functionality constraints on the system or a component. A top-level design is given by a control law: a predicate that defines an automation controlling the transition between phases of operation. Each......An approach to specification of requirements and verification of design for real-time systems is presented. A system is defined by a conventional mathematical model for a dynamic system where application specific states denote functions of real time. Specifications are formulas in duration calculus...... phase maintains certain relations among the system states; this is analogous to the control functions known from conventional control theory. The top-level design is decomposed into an architecture for a distributed system with specifications for sensor, actuator, and program components. Programs...

A DP based scheme for real-time reconfiguration of solar cell arrays exposed to dynamic changing inhomogeneous illuminations

DEFF Research Database (Denmark)

Shi, Liping; Brehm, Robert

2016-01-01

The overall energy conversion efficiency of solar cell arrays is highly effected by partial shading effects. Especially for solar panel arrays installed in environments which are exposed to inhomogeneous dynamic changing illuminations such as on roof tops of electrical vehicles the overall system...... efficiency is drastically reduced. Dynamic real-time reconfiguration of the solar panel array can reduce effects on the output efficiency due to partial shading. This results in a maximized power output of the panel array when exposed to dynamic changing illuminations. The optimal array configuration...... with respect to shading patterns can be stated as a combinatorial optimization problem and this paper proposes a dynamic programming (DP) based algorithm which finds the optimal feasible solution to reconfigure the solar panel array for maximum efficiency in real-time with linear time complexity. It is shown...

Real-time Nyquist signaling with dynamic precision and flexible non-integer oversampling.

Science.gov (United States)

Schmogrow, R; Meyer, M; Schindler, P C; Nebendahl, B; Dreschmann, M; Meyer, J; Josten, A; Hillerkuss, D; Ben-Ezra, S; Becker, J; Koos, C; Freude, W; Leuthold, J

2014-01-13

We demonstrate two efficient processing techniques for Nyquist signals, namely computation of signals using dynamic precision as well as arbitrary rational oversampling factors. With these techniques along with massively parallel processing it becomes possible to generate and receive high data rate Nyquist signals with flexible symbol rates and bandwidths, a feature which is highly desirable for novel flexgrid networks. We achieved maximum bit rates of 252 Gbit/s in real-time.

Co-simulation for real time safety verification of nuclear power plants

International Nuclear Information System (INIS)

Boafo, E.K.; Zhang, L.; Nasimi, E.; Gabbar, H.A.

2015-01-01

Small and major accidents and near misses are still occurring in nuclear power plants (NPPs). Risk level has increased with the degradation of NPP equipment and instrumentations. In order to achieve NPP safety, it is important to continuously evaluate risk for all potential hazard and fault propagation scenarios and map protection layers to fault / failure / hazard propagation scenarios to be able to evaluate and verify safety level during NPP operation. There are major limitations in current real time safety verification tools, as it is mainly offline and with no integration to NPP simulation tools. The main goal of this research is to develop real time safety verification with co-simulation tool to be integrated with plant operation support systems. This includes the development of static and dynamic fault semantic network (FSN) to model all possible fault propagation scenarios and the interrelationships among associated process variables. Safety and protection layers along with their reliability are mapped to FSN so that safety levels can be verified during plant operation. Errors between multiphysics models and real time data are modeled to accurately and dynamically tune FSN for each fault propagation scenario. The detailed methodology will show how to integrate process models, construction of static FSN with fault propagation scenarios, and evaluation and tuning of dynamic FSN with probabilistic and process variable interaction values. Principle Component Analysis method is used reduce dimensionality and reduce process variables associated with each fault scenario. Then map independent protection layers (IPL) to FSN with estimated reliability measures of each protection layer to accurately verify safety for different operational scenarios. Intelligent algorithms is used with multivariate techniques to accurate define the interrelation among process variables, in terms of signal strength and time delay, using Genetic Programming (GP), which will provide basis

Boat, wake, and wave real-time simulation

Science.gov (United States)

Świerkowski, Leszek; Gouthas, Efthimios; Christie, Chad L.; Williams, Owen M.

2009-05-01

We describe the extension of our real-time scene generation software VIRSuite to include the dynamic simulation of small boats and their wakes within an ocean environment. Extensive use has been made of the programmabilty available in the current generation of GPUs. We have demonstrated that real-time simulation is feasible, even including such complexities as dynamical calculation of the boat motion, wake generation and calculation of an FFTgenerated sea state.

Real-time forecasting of an epidemic using a discrete time stochastic model: a case study of pandemic influenza (H1N1-2009

Directory of Open Access Journals (Sweden)

Nishiura Hiroshi

2011-02-01

Full Text Available Abstract Background Real-time forecasting of epidemics, especially those based on a likelihood-based approach, is understudied. This study aimed to develop a simple method that can be used for the real-time epidemic forecasting. Methods A discrete time stochastic model, accounting for demographic stochasticity and conditional measurement, was developed and applied as a case study to the weekly incidence of pandemic influenza (H1N1-2009 in Japan. By imposing a branching process approximation and by assuming the linear growth of cases within each reporting interval, the epidemic curve is predicted using only two parameters. The uncertainty bounds of the forecasts are computed using chains of conditional offspring distributions. Results The quality of the forecasts made before the epidemic peak appears largely to depend on obtaining valid parameter estimates. The forecasts of both weekly incidence and final epidemic size greatly improved at and after the epidemic peak with all the observed data points falling within the uncertainty bounds. Conclusions Real-time forecasting using the discrete time stochastic model with its simple computation of the uncertainty bounds was successful. Because of the simplistic model structure, the proposed model has the potential to additionally account for various types of heterogeneity, time-dependent transmission dynamics and epidemiological details. The impact of such complexities on forecasting should be explored when the data become available as part of the disease surveillance.

A deformable surface model for real-time water drop animation.

Science.gov (United States)

Zhang, Yizhong; Wang, Huamin; Wang, Shuai; Tong, Yiying; Zhou, Kun

2012-08-01

A water drop behaves differently from a large water body because of its strong viscosity and surface tension under the small scale. Surface tension causes the motion of a water drop to be largely determined by its boundary surface. Meanwhile, viscosity makes the interior of a water drop less relevant to its motion, as the smooth velocity field can be well approximated by an interpolation of the velocity on the boundary. Consequently, we propose a fast deformable surface model to realistically animate water drops and their flowing behaviors on solid surfaces. Our system efficiently simulates water drop motions in a Lagrangian fashion, by reducing 3D fluid dynamics over the whole liquid volume to a deformable surface model. In each time step, the model uses an implicit mean curvature flow operator to produce surface tension effects, a contact angle operator to change droplet shapes on solid surfaces, and a set of mesh connectivity updates to handle topological changes and improve mesh quality over time. Our numerical experiments demonstrate a variety of physically plausible water drop phenomena at a real-time rate, including capillary waves when water drops collide, pinch-off of water jets, and droplets flowing over solid materials. The whole system performs orders-of-magnitude faster than existing simulation approaches that generate comparable water drop effects.

Real-Time Projection-Based Augmented Reality System for Dynamic Objects in the Performing Arts

Directory of Open Access Journals (Sweden)

Jaewoon Lee

2015-02-01

Full Text Available This paper describes the case study of applying projection-based augmented reality, especially for dynamic objects in live performing shows, such as plays, dancing, or musicals. Our study aims to project imagery correctly inside the silhouettes of flexible objects, in other words, live actors or the surface of actor’s costumes; the silhouette transforms its own shape frequently. To realize this work, we implemented a special projection system based on the real-time masking technique, that is to say real-time projection-based augmented reality system for dynamic objects in performing arts. We installed the sets on a stage for live performance, and rehearsed particular scenes of a musical. In live performance, using projection-based augmented reality technology enhances technical and theatrical aspects which were not possible with existing video projection techniques. The projected images on the surfaces of actor’s costume could not only express the particular scene of a performance more effectively, but also lead the audience to an extraordinary visual experience.

Model Checking Real Time Java Using Java PathFinder

Science.gov (United States)

Lindstrom, Gary; Mehlitz, Peter C.; Visser, Willem

2005-01-01

The Real Time Specification for Java (RTSJ) is an augmentation of Java for real time applications of various degrees of hardness. The central features of RTSJ are real time threads; user defined schedulers; asynchronous events, handlers, and control transfers; a priority inheritance based default scheduler; non-heap memory areas such as immortal and scoped, and non-heap real time threads whose execution is not impeded by garbage collection. The Robust Software Systems group at NASA Ames Research Center has JAVA PATHFINDER (JPF) under development, a Java model checker. JPF at its core is a state exploring JVM which can examine alternative paths in a Java program (e.g., via backtracking) by trying all nondeterministic choices, including thread scheduling order. This paper describes our implementation of an RTSJ profile (subset) in JPF, including requirements, design decisions, and current implementation status. Two examples are analyzed: jobs on a multiprogramming operating system, and a complex resource contention example involving autonomous vehicles crossing an intersection. The utility of JPF in finding logic and timing errors is illustrated, and the remaining challenges in supporting all of RTSJ are assessed.

Dynamic Value Engineering Method Optimizing the Risk on Real Time Operating System

Directory of Open Access Journals (Sweden)

Prashant Kumar Patra

2014-04-01

Full Text Available The value engineering is the umbrella of the many more sub-system like quality assurance, quality control, quality function design and development for manufacturability. The system engineering & value engineering is two part of the coin. The value engineering is the high level of technology management for every aspect of engineering fields. The value engineering is the high utilization of System Product (i.e. Processor, Memory & Encryption key, Services, Business and Resources at minimal cost. The high end operating system providing highest services at optimal cost & time. The value engineering provides the maximum performance, accountability, reliability, integrity and availability of processor, memory, encryption key and other inter dependency sub-components. The value engineering is the ratio of the maximum functionality of individual components to the optimal cost. VE=k [(P, M, E, C, A]/optimal cost. Where k is the proportionality constant. The VE is directly proportional to performance of individual components and inversely proportional to the minimal cost. The VE is directly proportional to the risk assessment. The VE maximize the business throughput & decision process mean while minimize the risk and down time. We have to develop the dynamic value engineering model & mechanism for risk optimization over a complex real time operating system This proposed composition model definite will be resolve our objective at top high level. Product

Real-Time Aircraft Cosmic Ray Radiation Exposure Predictions from the NAIRAS Model

Science.gov (United States)

Mertens, C. J.; Tobiska, W.; Kress, B. T.; Xu, X.

2012-12-01

The Nowcast of Atmospheric Ionizing Radiation for Aviation Safety (NAIRAS) is a prototype operational model for predicting commercial aircraft radiation exposure from galactic and solar cosmic rays. NAIRAS predictions are currently streaming live from the project's public website, and the exposure rate nowcast is also available on the SpaceWx smartphone app for iPhone, IPad, and Android. Cosmic rays are the primary source of human exposure to high linear energy transfer radiation at aircraft altitudes, which increases the risk of cancer and other adverse health effects. Thus, the NAIRAS model addresses an important national need with broad societal, public health and economic benefits. There is also interest in extending NAIRAS to the LEO environment to address radiation hazard issues for the emerging commercial spaceflight industry. The processes responsible for the variability in the solar wind, interplanetary magnetic field, solar energetic particle spectrum, and the dynamical response of the magnetosphere to these space environment inputs, strongly influence the composition and energy distribution of the atmospheric ionizing radiation field. Real-time observations are required at a variety of locations within the geospace environment. The NAIRAS model is driven by real-time input data from ground-, atmospheric-, and space-based platforms. During the development of the NAIRAS model, new science questions and observational data gaps were identified that must be addressed in order to obtain a more reliable and robust operational model of atmospheric radiation exposure. The focus of this talk is to present the current capabilities of the NAIRAS model, discuss future developments in aviation radiation modeling and instrumentation, and propose strategies and methodologies of bridging known gaps in current modeling and observational capabilities.

Functional Fault Modeling Conventions and Practices for Real-Time Fault Isolation

Science.gov (United States)

Ferrell, Bob; Lewis, Mark; Perotti, Jose; Oostdyk, Rebecca; Brown, Barbara

2010-01-01

The purpose of this paper is to present the conventions, best practices, and processes that were established based on the prototype development of a Functional Fault Model (FFM) for a Cryogenic System that would be used for real-time Fault Isolation in a Fault Detection, Isolation, and Recovery (FDIR) system. The FDIR system is envisioned to perform health management functions for both a launch vehicle and the ground systems that support the vehicle during checkout and launch countdown by using a suite of complimentary software tools that alert operators to anomalies and failures in real-time. The FFMs were created offline but would eventually be used by a real-time reasoner to isolate faults in a Cryogenic System. Through their development and review, a set of modeling conventions and best practices were established. The prototype FFM development also provided a pathfinder for future FFM development processes. This paper documents the rationale and considerations for robust FFMs that can easily be transitioned to a real-time operating environment.

Variable slip wind generator modeling for real-time simulation

Energy Technology Data Exchange (ETDEWEB)

Gagnon, R.; Brochu, J.; Turmel, G. [Hydro-Quebec, Varennes, PQ (Canada). IREQ

2006-07-01

A model of a wind turbine using a variable slip wound-rotor induction machine was presented. The model was created as part of a library of generic wind generator models intended for wind integration studies. The stator winding of the wind generator was connected directly to the grid and the rotor was driven by the turbine through a drive train. The variable resistors was synthesized by an external resistor in parallel with a diode rectifier. A forced-commutated power electronic device (IGBT) was connected to the wound rotor by slip rings and brushes. Simulations were conducted in a Matlab/Simulink environment using SimPowerSystems blocks to model power systems elements and Simulink blocks to model the turbine, control system and drive train. Detailed descriptions of the turbine, the drive train and the control system were provided. The model's implementation in the simulator was also described. A case study demonstrating the real-time simulation of a wind generator connected at the distribution level of a power system was presented. Results of the case study were then compared with results obtained from the SimPowerSystems off-line simulation. Results showed good agreement between the waveforms, demonstrating the conformity of the real-time and the off-line simulations. The capability of Hypersim for real-time simulation of wind turbines with power electronic converters in a distribution network was demonstrated. It was concluded that hardware-in-the-loop (HIL) simulation of wind turbine controllers for wind integration studies in power systems is now feasible. 5 refs., 1 tab., 6 figs.

Real-time computing platform for spiking neurons (RT-spike).

Science.gov (United States)

Ros, Eduardo; Ortigosa, Eva M; Agís, Rodrigo; Carrillo, Richard; Arnold, Michael

2006-07-01

A computing platform is described for simulating arbitrary networks of spiking neurons in real time. A hybrid computing scheme is adopted that uses both software and hardware components to manage the tradeoff between flexibility and computational power; the neuron model is implemented in hardware and the network model and the learning are implemented in software. The incremental transition of the software components into hardware is supported. We focus on a spike response model (SRM) for a neuron where the synapses are modeled as input-driven conductances. The temporal dynamics of the synaptic integration process are modeled with a synaptic time constant that results in a gradual injection of charge. This type of model is computationally expensive and is not easily amenable to existing software-based event-driven approaches. As an alternative we have designed an efficient time-based computing architecture in hardware, where the different stages of the neuron model are processed in parallel. Further improvements occur by computing multiple neurons in parallel using multiple processing units. This design is tested using reconfigurable hardware and its scalability and performance evaluated. Our overall goal is to investigate biologically realistic models for the real-time control of robots operating within closed action-perception loops, and so we evaluate the performance of the system on simulating a model of the cerebellum where the emulation of the temporal dynamics of the synaptic integration process is important.

[A review of progress of real-time tumor tracking radiotherapy technology based on dynamic multi-leaf collimator].

Science.gov (United States)

Liu, Fubo; Li, Guangjun; Shen, Jiuling; Li, Ligin; Bai, Sen

2017-02-01

While radiation treatment to patients with tumors in thorax and abdomen is being performed, further improvement of radiation accuracy is restricted by the tumor intra-fractional motion due to respiration. Real-time tumor tracking radiation is an optimal solution to tumor intra-fractional motion. A review of the progress of real-time dynamic multi-leaf collimator(DMLC) tracking is provided in the present review, including DMLC tracking method, time lag of DMLC tracking system, and dosimetric verification.

A real-time dynamic imaging system for centrifugal microflow platforms

International Nuclear Information System (INIS)

Chang, Hsing-Cheng; Tsou, Chingfu; Lai, Chi-Chih; Wun, Guo-Hong

2008-01-01

Based on the operational concept of quasi-static state and optoelectronic measurement technology, this research develops a real-time dynamic imaging system for centrifugal microfluidic platforms. Unlike the conventional centrifugal inspection system, which can only be used for examination of the final steady stage in microflow analysis, the developed system with a multi-speed controller and object tracking design is fabricated with low cost to recognize dynamic microflow patterns for different kinds of compact disc-type centrifugal microstructures. The characteristics of rotational control efficiency and image acquisition quality are obtained from fluidic microvalve experiments that are achieved in measuring microflow dynamic responses and in visualizing transient microflow patterns. A man–machine interface was connected with a computer to perform the control and alignment adjustments to catch exact image data for following analysis. The rotation stability of the system has been evaluated, and the rotation speed up to 4500 rpm with vertical vibration less than ±0.2 mm is achieved measured at radial distance of 5 cm. The image acquisition is transferred via USB 2.0 at a speed of up to 30 images per second to the display and memory module

Exponential Smoothing Approaches for Prediction in Real-Time Electricity Markets

Directory of Open Access Journals (Sweden)

Tryggvi Jónsson

2014-06-01

Full Text Available The optimal design of offering strategies for wind power producers is commonly based on unconditional (and, hence, constant expectation values for prices in real-time markets, directly defining their loss function in a stochastic optimization framework. This is why it may certainly be advantageous to account for the seasonal and dynamic behavior of such prices, hence translating to time-varying loss functions. With that objective in mind, forecasting approaches relying on simple models that accommodate the seasonal and dynamic nature of real-time prices are derived and analyzed. These are all based on the well-known Holt–Winters model with a daily seasonal cycle, either in its conventional form or conditioned upon exogenous variables, such as: (i day-ahead price; (ii system load; and (iii wind power penetration. The superiority of the proposed approach over a number of common benchmarks is subsequently demonstrated through an empirical investigation for the Nord Pool, mimicking practical forecasting for a three-year period over 2008–2011.

Network dynamics with BrainX(3): a large-scale simulation of the human brain network with real-time interaction.

Science.gov (United States)

Arsiwalla, Xerxes D; Zucca, Riccardo; Betella, Alberto; Martinez, Enrique; Dalmazzo, David; Omedas, Pedro; Deco, Gustavo; Verschure, Paul F M J

2015-01-01

BrainX(3) is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX(3) in real-time by perturbing brain regions with transient stimulations to observe reverberating network activity, simulate lesion dynamics or implement network analysis functions from a library of graph theoretic measures. BrainX(3) can thus be used as a novel immersive platform for exploration and analysis of dynamical activity patterns in brain networks, both at rest or in a task-related state, for discovery of signaling pathways associated to brain function and/or dysfunction and as a tool for virtual neurosurgery. Our results demonstrate these functionalities and shed insight on the dynamics of the resting-state attractor. Specifically, we found that a noisy network seems to favor a low firing attractor state. We also found that the dynamics of a noisy network is less resilient to lesions. Our simulations on TMS perturbations show that even though TMS inhibits most of the network, it also sparsely excites a few regions. This is presumably due to anti-correlations in the dynamics and suggests that even a lesioned network can show sparsely distributed increased activity compared to healthy resting-state, over specific brain areas.

Network dynamics with BrainX3: a large-scale simulation of the human brain network with real-time interaction

Science.gov (United States)

Arsiwalla, Xerxes D.; Zucca, Riccardo; Betella, Alberto; Martinez, Enrique; Dalmazzo, David; Omedas, Pedro; Deco, Gustavo; Verschure, Paul F. M. J.

2015-01-01

BrainX3 is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX3 in real-time by perturbing brain regions with transient stimulations to observe reverberating network activity, simulate lesion dynamics or implement network analysis functions from a library of graph theoretic measures. BrainX3 can thus be used as a novel immersive platform for exploration and analysis of dynamical activity patterns in brain networks, both at rest or in a task-related state, for discovery of signaling pathways associated to brain function and/or dysfunction and as a tool for virtual neurosurgery. Our results demonstrate these functionalities and shed insight on the dynamics of the resting-state attractor. Specifically, we found that a noisy network seems to favor a low firing attractor state. We also found that the dynamics of a noisy network is less resilient to lesions. Our simulations on TMS perturbations show that even though TMS inhibits most of the network, it also sparsely excites a few regions. This is presumably due to anti-correlations in the dynamics and suggests that even a lesioned network can show sparsely distributed increased activity compared to healthy resting-state, over specific brain areas. PMID:25759649

Embedded Artificial Neuval Network-Based Real-Time Half-Wave Dynamic Resistance Estimation during the A.C. Resistance Spot Welding Process

Directory of Open Access Journals (Sweden)

Liang Gong

2013-01-01

Full Text Available Online monitoring of the instantaneous resistance variation during the A.C. resistance spot welding is of paramount importance for the weld quality control. On the basis of the welding transformer circuit model, a new method is proposed to measure the transformer primary-side signal for estimating the secondary-side resistance in each 1/4 cycle. The tailored computing system ensures that the measuring method possesses a real-time computational capacity with satisfying accuracy. Since the dynamic resistance cannot be represented via an explicit function with respect to measurable parameters from the primary side of the welding transformer, an offline trained embedded artificial neural network (ANN successfully realizes the real-time implicit function calculation or estimation. A DSP-based resistance spot welding monitoring system is developed to perform ANN computation. Experimental results indicate that the proposed method is applicable for measuring the dynamic resistance in single-phase, half-wave controlled rectifier circuits.

Real-time nonlinear feedback control of pattern formation in (bio)chemical reaction-diffusion processes: a model study.

Science.gov (United States)

Brandt-Pollmann, U; Lebiedz, D; Diehl, M; Sager, S; Schlöder, J

2005-09-01

Theoretical and experimental studies related to manipulation of pattern formation in self-organizing reaction-diffusion processes by appropriate control stimuli become increasingly important both in chemical engineering and cellular biochemistry. In a model study, we demonstrate here exemplarily the application of an efficient nonlinear model predictive control (NMPC) algorithm to real-time optimal feedback control of pattern formation in a bacterial chemotaxis system modeled by nonlinear partial differential equations. The corresponding drift-diffusion model type is representative for many (bio)chemical systems involving nonlinear reaction dynamics and nonlinear diffusion. We show how the computed optimal feedback control strategy exploits the system inherent physical property of wave propagation to achieve desired control aims. We discuss various applications of our approach to optimal control of spatiotemporal dynamics.

Comparison of three-way and four-way calibration for the real-time quantitative analysis of drug hydrolysis in complex dynamic samples by excitation-emission matrix fluorescence

Science.gov (United States)

Yin, Xiao-Li; Gu, Hui-Wen; Liu, Xiao-Lu; Zhang, Shan-Hui; Wu, Hai-Long

2018-03-01

Multiway calibration in combination with spectroscopic technique is an attractive tool for online or real-time monitoring of target analyte(s) in complex samples. However, how to choose a suitable multiway calibration method for the resolution of spectroscopic-kinetic data is a troubling problem in practical application. In this work, for the first time, three-way and four-way fluorescence-kinetic data arrays were generated during the real-time monitoring of the hydrolysis of irinotecan (CPT-11) in human plasma by excitation-emission matrix fluorescence. Alternating normalization-weighted error (ANWE) and alternating penalty trilinear decomposition (APTLD) were used as three-way calibration for the decomposition of the three-way kinetic data array, whereas alternating weighted residual constraint quadrilinear decomposition (AWRCQLD) and alternating penalty quadrilinear decomposition (APQLD) were applied as four-way calibration to the four-way kinetic data array. The quantitative results of the two kinds of calibration models were fully compared from the perspective of predicted real-time concentrations, spiked recoveries of initial concentration, and analytical figures of merit. The comparison study demonstrated that both three-way and four-way calibration models could achieve real-time quantitative analysis of the hydrolysis of CPT-11 in human plasma under certain conditions. However, it was also found that both of them possess some critical advantages and shortcomings during the process of dynamic analysis. The conclusions obtained in this paper can provide some helpful guidance for the reasonable selection of multiway calibration models to achieve the real-time quantitative analysis of target analyte(s) in complex dynamic systems.

Real-time tumor ablation simulation based on the dynamic mode decomposition method

KAUST Repository

Bourantas, George C.

2014-05-01

Purpose: The dynamic mode decomposition (DMD) method is used to provide a reliable forecasting of tumor ablation treatment simulation in real time, which is quite needed in medical practice. To achieve this, an extended Pennes bioheat model must be employed, taking into account both the water evaporation phenomenon and the tissue damage during tumor ablation. Methods: A meshless point collocation solver is used for the numerical solution of the governing equations. The results obtained are used by the DMD method for forecasting the numerical solution faster than the meshless solver. The procedure is first validated against analytical and numerical predictions for simple problems. The DMD method is then applied to three-dimensional simulations that involve modeling of tumor ablation and account for metabolic heat generation, blood perfusion, and heat ablation using realistic values for the various parameters. Results: The present method offers very fast numerical solution to bioheat transfer, which is of clinical significance in medical practice. It also sidesteps the mathematical treatment of boundaries between tumor and healthy tissue, which is usually a tedious procedure with some inevitable degree of approximation. The DMD method provides excellent predictions of the temperature profile in tumors and in the healthy parts of the tissue, for linear and nonlinear thermal properties of the tissue. Conclusions: The low computational cost renders the use of DMD suitable forin situ real time tumor ablation simulations without sacrificing accuracy. In such a way, the tumor ablation treatment planning is feasible using just a personal computer thanks to the simplicity of the numerical procedure used. The geometrical data can be provided directly by medical image modalities used in everyday practice. © 2014 American Association of Physicists in Medicine.

Real-time measurement of dynamic structure for Pd-D system in heavy-water electrolysis cell

International Nuclear Information System (INIS)

Wang Jun; Zeng Xianxin; Yang Jilian; Zhang Baisheng; Ruan Jinghui

1993-01-01

The real-time dynamic structure of Pd-D system in D 2 O electrolysis cell is measured on neutron powder diffractometer in CIAE. Diffraction patterns in 2 θ range of 34 degree-95 degree are obtained under the conditions of electrolysing for 0, 3 and 48 A ·h respectively, and the gradual transition of Pd-D system from α-phase to β-phase is observed. The real-time measurements of β peak of (220) reflection show that intensity of β peak almost reaches the saturation point after electrolysing for 0.65 A · h and increases slowly with further electrolysis afterwards

Automatic real time drilling support on Ekofisk utilizing eDrilling

Energy Technology Data Exchange (ETDEWEB)

Rommetveit, Rolv; Bjorkevoll, Knut S.; Halsey, George W.; Kluge, Roald; Molde, Dag Ove; Odegard, Sven Inge [SINTEF Petroleum Research, Trondheim (Norway); Herbert, Mike [HITEC Products Drilling, Stavanger (Norway); ConocoPhillips Norge, Stavanger (Norway)

2008-07-01

eDrilling is a new and innovative system for real time drilling simulation, 3D visualization and control from a remote drilling expert centre. The concept uses all available real time drilling data (surface and downhole) in combination with real time modelling to monitor and optimize the drilling process. This information is used to visualize the wellbore in 3D in real time. eDrilling has been implemented in an Onshore Drilling Center in Norway. The system is composed of the following elements, some of which are unique and ground-breaking: an advanced and fast Integrated Drilling Simulator which is capable to model the different drilling sub-processes dynamically, and also the interaction between these sub-processes in real time; automatic quality check and corrections of drilling data; making them suitable for processing by computer models; real time supervision methodology for the drilling process using time based drilling data as well as drilling models / the integrated drilling simulator; methodology for diagnosis of the drilling state and conditions. This is obtained from comparing model predictions with measured data. Advisory technology for more optimal drilling. A Virtual Wellbore, with advanced visualization of the downhole process. Dat low and computer infrastructure. e-Drilling has been implemented in an Onshore Drilling Center on Ekofisk in Norway. The system is being used on drilling operations, and experiences from its use are presented. The supervision and diagnosis functionalities have been useful in particular, as the system has given early warnings on ECD and friction related problems. This paper will present the eDrilling system as well as experiences from its use. (author)

The economic analysis of power market architectures: application to real-time market design

International Nuclear Information System (INIS)

Saguan, M.

2007-04-01

This work contributes to the economic analysis of power market architectures. A modular framework is used to separate problems of market design in different modules. The work's goal is to study real-time market design. A two-stage market equilibrium model is used to analyse the two main real-time designs: the 'market' and the 'mechanism' (with penalty). Numerical simulations show that design applied in real-time is not neutral vis-a-vis of energy markets sequence and the competition dynamic. Designs using penalty (mechanisms) cause distortions, inefficiencies and can create barriers to entry. The size of distortions is given by the temporal position of the gate that closure the forward markets. This model has also allowed us to show the key role of real-time integration between zones and the importance of good harmonization between real-time designs of each zone. (author)

Real time implementation and control validation of the wind energy conversion system

Science.gov (United States)

Sattar, Adnan

The purpose of the thesis is to analyze dynamic and transient characteristics of wind energy conversion systems including the stability issues in real time environment using the Real Time Digital Simulator (RTDS). There are different power system simulation tools available in the market. Real time digital simulator (RTDS) is one of the powerful tools among those. RTDS simulator has a Graphical User Interface called RSCAD which contains detail component model library for both power system and control relevant analysis. The hardware is based upon the digital signal processors mounted in the racks. RTDS simulator has the advantage of interfacing the real world signals from the external devices, hence used to test the protection and control system equipments. Dynamic and transient characteristics of the fixed and variable speed wind turbine generating systems (WTGSs) are analyzed, in this thesis. Static Synchronous Compensator (STATCOM) as a flexible ac transmission system (FACTS) device is used to enhance the fault ride through (FRT) capability of the fixed speed wind farm. Two level voltage source converter based STATCOM is modeled in both VSC small time-step and VSC large time-step of RTDS. The simulation results of the RTDS model system are compared with the off-line EMTP software i.e. PSCAD/EMTDC. A new operational scheme for a MW class grid-connected variable speed wind turbine driven permanent magnet synchronous generator (VSWT-PMSG) is developed. VSWT-PMSG uses fully controlled frequency converters for the grid interfacing and thus have the ability to control the real and reactive powers simultaneously. Frequency converters are modeled in the VSC small time-step of the RTDS and three phase realistic grid is adopted with RSCAD simulation through the use of optical analogue digital converter (OADC) card of the RTDS. Steady state and LVRT characteristics are carried out to validate the proposed operational scheme. Simulation results show good agreement with real

Reliable real-time applications - and how to use tests to model and understand

DEFF Research Database (Denmark)

Jensen, Peter Krogsgaard

Test and analysis of real-time applications, where temporal properties are inspected, analyzed, and verified in a model developed from timed traces originating from measured test result on a running application......Test and analysis of real-time applications, where temporal properties are inspected, analyzed, and verified in a model developed from timed traces originating from measured test result on a running application...

Ovation Prime Real-Time

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Ovation Prime Real-Time (OPRT) product is a real-time forecast and nowcast model of auroral power and is an operational implementation of the work by Newell et...

MODELING OF POWER SYSTEMS AND TESTING OF RELAY PROTECTION DEVICES IN REAL AND MODEL TIME

Directory of Open Access Journals (Sweden)

I. V. Novash

2017-01-01

Full Text Available The methods of modelling of power system modes and of testing of relay protection devices with the aid the simulation complexes in real time and with the help of computer software systems that enables the simulation of virtual time scale are considered. Information input protection signals in the simulation of the virtual model time are being obtained in the computational experiment, whereas the tests of protective devices are carried out with the help of hardware and software test systems with the use of estimated input signals. Study of power system stability when modes of generating and consuming electrical equipment and conditions of devices of relay protection are being changed requires testing with the use of digital simulators in a mode of a closed loop. Herewith feedbacks between a model of the power system operating in a real time and external devices or their models must be determined (modelled. Modelling in real time and the analysis of international experience in the use of digital simulation power systems for real-time simulation (RTDS simulator have been fulfilled. Examples are given of the use of RTDS systems by foreign energy companies to test relay protection systems and control, to test the equipment and devices of automatic control, analysis of cyber security and evaluation of the operation of energy systems under different scenarios of occurrence of emergency situations. Some quantitative data on the distribution of RTDS in different countries and Russia are presented. It is noted that the leading energy universities of Russia use the real-time simulation not only to solve scientific and technical problems, but also to conduct training and laboratory classes on modelling of electric networks and anti-emergency automatic equipment with the students. In order to check serviceability of devices of relay protection without taking into account the reaction of the power system tests can be performed in an open loop mode with the

REAL TIME SYSTEM OPERATIONS 2006-2007

Energy Technology Data Exchange (ETDEWEB)

Eto, Joseph H.; Parashar, Manu; Lewis, Nancy Jo

2008-08-15

The Real Time System Operations (RTSO) 2006-2007 project focused on two parallel technical tasks: (1) Real-Time Applications of Phasors for Monitoring, Alarming and Control; and (2) Real-Time Voltage Security Assessment (RTVSA) Prototype Tool. The overall goal of the phasor applications project was to accelerate adoption and foster greater use of new, more accurate, time-synchronized phasor measurements by conducting research and prototyping applications on California ISO's phasor platform - Real-Time Dynamics Monitoring System (RTDMS) -- that provide previously unavailable information on the dynamic stability of the grid. Feasibility assessment studies were conducted on potential application of this technology for small-signal stability monitoring, validating/improving existing stability nomograms, conducting frequency response analysis, and obtaining real-time sensitivity information on key metrics to assess grid stress. Based on study findings, prototype applications for real-time visualization and alarming, small-signal stability monitoring, measurement based sensitivity analysis and frequency response assessment were developed, factory- and field-tested at the California ISO and at BPA. The goal of the RTVSA project was to provide California ISO with a prototype voltage security assessment tool that runs in real time within California ISO?s new reliability and congestion management system. CERTS conducted a technical assessment of appropriate algorithms, developed a prototype incorporating state-of-art algorithms (such as the continuation power flow, direct method, boundary orbiting method, and hyperplanes) into a framework most suitable for an operations environment. Based on study findings, a functional specification was prepared, which the California ISO has since used to procure a production-quality tool that is now a part of a suite of advanced computational tools that is used by California ISO for reliability and congestion management.

Real-time single-molecule co-immunoprecipitation analyses reveal cancer-specific Ras signalling dynamics

Science.gov (United States)

Lee, Hong-Won; Kyung, Taeyoon; Yoo, Janghyun; Kim, Tackhoon; Chung, Chaeuk; Ryu, Ji Young; Lee, Hanki; Park, Kihyun; Lee, Sangkyu; Jones, Walton D.; Lim, Dae-Sik; Hyeon, Changbong; Do Heo, Won; Yoon, Tae-Young

2013-01-01

Co-immunoprecipitation (co-IP) has become a standard technique, but its protein-band output provides only static, qualitative information about protein–protein interactions. Here we demonstrate a real-time single-molecule co-IP technique that generates real-time videos of individual protein–protein interactions as they occur in unpurified cell extracts. By analysing single Ras–Raf interactions with a 50-ms time resolution, we have observed transient intermediates of the protein–protein interaction and determined all the essential kinetic rates. Using this technique, we have quantified the active fraction of native Ras proteins in xenograft tumours, normal tissue and cancer cell lines. We demonstrate that the oncogenic Ras mutations selectively increase the active-Ras fraction by one order of magnitude, without affecting total Ras levels or single-molecule signalling kinetics. Our approach allows us to probe the previously hidden, dynamic aspects of weak protein–protein interactions. It also suggests a path forward towards precision molecular diagnostics at the protein–protein interaction level. PMID:23422673

Parity-Time Symmetry and the Toy Models of Gain-Loss Dynamics near the Real Kato's Exceptional Points

Czech Academy of Sciences Publication Activity Database

Znojil, Miloslav

2016-01-01

Roč. 8, č. 6 (2016), s. 52 ISSN 2073-8994 R&D Projects: GA ČR GA16-22945S Institutional support: RVO:61389005 Keywords : parity-time symmetry * Schrodinger equation * physical Hilbert space * inner-product metric operator * real exceptional points * solvable models * quantum Big Bang * quantum Inflation period Subject RIV: BE - Theoretical Physics Impact factor: 1.457, year: 2016

Real time modeling, simulation and control of dynamical systems

CERN Document Server

Mughal, Asif Mahmood

2016-01-01

This book introduces modeling and simulation of linear time invariant systems and demonstrates how these translate to systems engineering, mechatronics engineering, and biomedical engineering. It is organized into nine chapters that follow the lectures used for a one-semester course on this topic, making it appropriate for students as well as researchers. The author discusses state space modeling derived from two modeling techniques and the analysis of the system and usage of modeling in control systems design. It also contains a unique chapter on multidisciplinary energy systems with a special focus on bioengineering systems and expands upon how the bond graph augments research in biomedical and bio-mechatronics systems.

Real-time modeling and simulation of distribution feeder and distributed resources

Science.gov (United States)

Singh, Pawan

The analysis of the electrical system dates back to the days when analog network analyzers were used. With the advent of digital computers, many programs were written for power-flow and short circuit analysis for the improvement of the electrical system. Real-time computer simulations can answer many what-if scenarios in the existing or the proposed power system. In this thesis, the standard IEEE 13-Node distribution feeder is developed and validated on a real-time platform OPAL-RT. The concept and the challenges of the real-time simulation are studied and addressed. Distributed energy resources include some of the commonly used distributed generation and storage devices like diesel engine, solar photovoltaic array, and battery storage system are modeled and simulated on a real-time platform. A microgrid encompasses a portion of an electric power distribution which is located downstream of the distribution substation. Normally, the microgrid operates in paralleled mode with the grid; however, scheduled or forced isolation can take place. In such conditions, the microgrid must have the ability to operate stably and autonomously. The microgrid can operate in grid connected and islanded mode, both the operating modes are studied in the last chapter. Towards the end, a simple microgrid controller modeled and simulated on the real-time platform is developed for energy management and protection for the microgrid.

Dense time discretization technique for verification of real time systems

International Nuclear Information System (INIS)

Makackas, Dalius; Miseviciene, Regina

2016-01-01

Verifying the real-time system there are two different models to control the time: discrete and dense time based models. This paper argues a novel verification technique, which calculates discrete time intervals from dense time in order to create all the system states that can be reached from the initial system state. The technique is designed for real-time systems specified by a piece-linear aggregate approach. Key words: real-time system, dense time, verification, model checking, piece-linear aggregate

Emergent Auditory Feature Tuning in a Real-Time Neuromorphic VLSI System.

Science.gov (United States)

Sheik, Sadique; Coath, Martin; Indiveri, Giacomo; Denham, Susan L; Wennekers, Thomas; Chicca, Elisabetta

2012-01-01

Many sounds of ecological importance, such as communication calls, are characterized by time-varying spectra. However, most neuromorphic auditory models to date have focused on distinguishing mainly static patterns, under the assumption that dynamic patterns can be learned as sequences of static ones. In contrast, the emergence of dynamic feature sensitivity through exposure to formative stimuli has been recently modeled in a network of spiking neurons based on the thalamo-cortical architecture. The proposed network models the effect of lateral and recurrent connections between cortical layers, distance-dependent axonal transmission delays, and learning in the form of Spike Timing Dependent Plasticity (STDP), which effects stimulus-driven changes in the pattern of network connectivity. In this paper we demonstrate how these principles can be efficiently implemented in neuromorphic hardware. In doing so we address two principle problems in the design of neuromorphic systems: real-time event-based asynchronous communication in multi-chip systems, and the realization in hybrid analog/digital VLSI technology of neural computational principles that we propose underlie plasticity in neural processing of dynamic stimuli. The result is a hardware neural network that learns in real-time and shows preferential responses, after exposure, to stimuli exhibiting particular spectro-temporal patterns. The availability of hardware on which the model can be implemented, makes this a significant step toward the development of adaptive, neurobiologically plausible, spike-based, artificial sensory systems.

Emergent auditory feature tuning in a real-time neuromorphic VLSI system

Directory of Open Access Journals (Sweden)

Sadique eSheik

2012-02-01

Full Text Available Many sounds of ecological importance, such as communication calls, are characterised by time-varying spectra. However, most neuromorphic auditory models to date have focused on distinguishing mainly static patterns, under the assumption that dynamic patterns can be learned as sequences of static ones. In contrast, the emergence of dynamic feature sensitivity through exposure to formative stimuli has been recently modeled in a network of spiking neurons based on the thalamocortical architecture. The proposed network models the effect of lateral and recurrent connections between cortical layers, distance-dependent axonal transmission delays, and learning in the form of Spike Timing Dependent Plasticity (STDP, which effects stimulus-driven changes in the pattern of network connectivity. In this paper we demonstrate how these principles can be efficiently implemented in neuromorphic hardware. In doing so we address two principle problems in the design of neuromorphic systems: real-time event-based asynchronous communication in multi-chip systems, and the realization in hybrid analog/digital VLSI technology of neural computational principles that we propose underlie plasticity in neural processing of dynamic stimuli. The result is a hardware neural network that learns in real-time and shows preferential responses, after exposure, to stimuli exhibiting particular spectrotemporal patterns. The availability of hardware on which the model can be implemented, makes this a significant step towards the development of adaptive, neurobiologically plausible, spike-based, artificial sensory systems.

Real time simulation techniques in Taiwan - Maanshan compact simulator

International Nuclear Information System (INIS)

Liang, K.-S.; Chuang, Y.-M.; Ko, H.-T.

2004-01-01

Recognizing the demand and potential market of simulators in various industries, a special project for real time simulation technology transfer was initiated in Taiwan in 1991. In this technology transfer program, the most advanced real-time dynamic modules for nuclear power simulation were introduced. Those modules can be divided into two categories; one is modeling related to catch dynamic response of each system, and the other is computer related to provide special real time computing environment and man-machine interface. The modeling related modules consist of the thermodynamic module, the three-dimensional core neutronics module and the advanced balance of plant module. As planned in the project, the technology transfer team should build a compact simulator for the Maanshan power plant before the end of the project to demonstrate the success of the technology transfer program. The compact simulator was designed to support the training from the regular full scope simulator which was already equipped in the Maanshan plant. The feature of this compact simulator focused on providing know-why training by the enhanced graphic display. The potential users were identified as senior operators, instructors and nuclear engineers. Total about 13 important systems were covered in the scope of the compact simulator, and multi-graphic displays from three color monitors mounted on the 10 feet compact panel were facilitated to help the user visualize detailed phenomena under scenarios of interest. (author)

Comparison of three-way and four-way calibration for the real-time quantitative analysis of drug hydrolysis in complex dynamic samples by excitation-emission matrix fluorescence.

Science.gov (United States)

Yin, Xiao-Li; Gu, Hui-Wen; Liu, Xiao-Lu; Zhang, Shan-Hui; Wu, Hai-Long

2018-03-05

Multiway calibration in combination with spectroscopic technique is an attractive tool for online or real-time monitoring of target analyte(s) in complex samples. However, how to choose a suitable multiway calibration method for the resolution of spectroscopic-kinetic data is a troubling problem in practical application. In this work, for the first time, three-way and four-way fluorescence-kinetic data arrays were generated during the real-time monitoring of the hydrolysis of irinotecan (CPT-11) in human plasma by excitation-emission matrix fluorescence. Alternating normalization-weighted error (ANWE) and alternating penalty trilinear decomposition (APTLD) were used as three-way calibration for the decomposition of the three-way kinetic data array, whereas alternating weighted residual constraint quadrilinear decomposition (AWRCQLD) and alternating penalty quadrilinear decomposition (APQLD) were applied as four-way calibration to the four-way kinetic data array. The quantitative results of the two kinds of calibration models were fully compared from the perspective of predicted real-time concentrations, spiked recoveries of initial concentration, and analytical figures of merit. The comparison study demonstrated that both three-way and four-way calibration models could achieve real-time quantitative analysis of the hydrolysis of CPT-11 in human plasma under certain conditions. However, it was also found that both of them possess some critical advantages and shortcomings during the process of dynamic analysis. The conclusions obtained in this paper can provide some helpful guidance for the reasonable selection of multiway calibration models to achieve the real-time quantitative analysis of target analyte(s) in complex dynamic systems. Copyright © 2017 Elsevier B.V. All rights reserved.

An Experimental Evaluation of Real-Time DVFS Scheduling Algorithms

OpenAIRE

Saha, Sonal

2011-01-01

Dynamic voltage and frequency scaling (DVFS) is an extensively studied energy manage- ment technique, which aims to reduce the energy consumption of computing platforms by dynamically scaling the CPU frequency. Real-Time DVFS (RT-DVFS) is a branch of DVFS, which reduces CPU energy consumption through DVFS, while at the same time ensures that task time constraints are satisfied by constructing appropriate real-time task schedules. The literature presents numerous RT-DVFS schedul...

Aerodynamic Modeling of NREL 5-MW Wind Turbine for Nonlinear Control System Design: A Case Study Based on Real-Time Nonlinear Receding Horizon Control

Directory of Open Access Journals (Sweden)

Pedro A. Galvani

2016-08-01

Full Text Available The work presented in this paper has two major aspects: (i investigation of a simple, yet efficient model of the NREL (National Renewable Energy Laboratory 5-MW reference wind turbine; (ii nonlinear control system development through a real-time nonlinear receding horizon control methodology with application to wind turbine control dynamics. In this paper, the results of our simple wind turbine model and a real-time nonlinear control system implementation are shown in comparison with conventional control methods. For this purpose, the wind turbine control problem is converted into an optimization problem and is directly solved by the nonlinear backwards sweep Riccati method to generate the control protocol, which results in a non-iterative algorithm. One main contribution of this paper is that we provide evidence through simulations, that such an advanced control strategy can be used for real-time control of wind turbine dynamics. Examples are provided to validate and demonstrate the effectiveness of the presented scheme.

Modeling solvation effects in real-space and real-time within density functional approaches

Energy Technology Data Exchange (ETDEWEB)

Delgado, Alain [Istituto Nanoscienze - CNR, Centro S3, via Campi 213/A, 41125 Modena (Italy); Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear, Calle 30 # 502, 11300 La Habana (Cuba); Corni, Stefano; Pittalis, Stefano; Rozzi, Carlo Andrea [Istituto Nanoscienze - CNR, Centro S3, via Campi 213/A, 41125 Modena (Italy)

2015-10-14

The Polarizable Continuum Model (PCM) can be used in conjunction with Density Functional Theory (DFT) and its time-dependent extension (TDDFT) to simulate the electronic and optical properties of molecules and nanoparticles immersed in a dielectric environment, typically liquid solvents. In this contribution, we develop a methodology to account for solvation effects in real-space (and real-time) (TD)DFT calculations. The boundary elements method is used to calculate the solvent reaction potential in terms of the apparent charges that spread over the van der Waals solute surface. In a real-space representation, this potential may exhibit a Coulomb singularity at grid points that are close to the cavity surface. We propose a simple approach to regularize such singularity by using a set of spherical Gaussian functions to distribute the apparent charges. We have implemented the proposed method in the OCTOPUS code and present results for the solvation free energies and solvatochromic shifts for a representative set of organic molecules in water.

Dynamic I/O Power Management for Hard Real-Time Systems

Science.gov (United States)

2005-01-01

recently emerged as an attractive alternative to inflexible hardware solutions. DPM for hard real - time systems has received relatively little attention...In particular, energy-driven I/O device scheduling for real - time systems has not been considered before. We present the first online DPM algorithm...which we call Low Energy Device Scheduler (LEDES), for hard real - time systems . LEDES takes as inputs a predetermined task schedule and a device-usage

Integrating real-time and manual monitored data to predict hillslope soil moisture dynamics with high spatio-temporal resolution using linear and non-linear models

Science.gov (United States)

Spatio-temporal variability of soil moisture (') is a challenge that remains to be better understood. A trade-off exists between spatial coverage and temporal resolution when using the manual and real-time ' monitoring methods. This restricted the comprehensive and intensive examination of ' dynamic...

Prototyping real-time systems

OpenAIRE

Clynch, Gary

1994-01-01

The traditional software development paradigm, the waterfall life cycle model, is defective when used for developing real-time systems. This thesis puts forward an executable prototyping approach for the development of real-time systems. A prototyping system is proposed which uses ESML (Extended Systems Modelling Language) as a prototype specification language. The prototyping system advocates the translation of non-executable ESML specifications into executable LOOPN (Language of Object ...

High Fidelity, “Faster than Real-Time” Simulator for Predicting Power System Dynamic Behavior - Final Technical Report

Energy Technology Data Exchange (ETDEWEB)

Flueck, Alex [Illinois Inst. of Technology, Chicago, IL (United States)

2017-07-14

The “High Fidelity, Faster than Real­Time Simulator for Predicting Power System Dynamic Behavior” was designed and developed by Illinois Institute of Technology with critical contributions from Electrocon International, Argonne National Laboratory, Alstom Grid and McCoy Energy. Also essential to the project were our two utility partners: Commonwealth Edison and AltaLink. The project was a success due to several major breakthroughs in the area of large­scale power system dynamics simulation, including (1) a validated faster than real­ time simulation of both stable and unstable transient dynamics in a large­scale positive sequence transmission grid model, (2) a three­phase unbalanced simulation platform for modeling new grid devices, such as independently controlled single­phase static var compensators (SVCs), (3) the world’s first high fidelity three­phase unbalanced dynamics and protection simulator based on Electrocon’s CAPE program, and (4) a first­of­its­ kind implementation of a single­phase induction motor model with stall capability. The simulator results will aid power grid operators in their true time of need, when there is a significant risk of cascading outages. The simulator will accelerate performance and enhance accuracy of dynamics simulations, enabling operators to maintain reliability and steer clear of blackouts. In the long­term, the simulator will form the backbone of the newly conceived hybrid real­time protection and control architecture that will coordinate local controls, wide­area measurements, wide­area controls and advanced real­time prediction capabilities. The nation’s citizens will benefit in several ways, including (1) less down time from power outages due to the faster­than­real­time simulator’s predictive capability, (2) higher levels of reliability due to the detailed dynamics plus protection simulation capability, and (3) more resiliency due to the three­ phase unbalanced simulator’s ability to

Hard real-time multibody simulations using ARM-based embedded systems

Energy Technology Data Exchange (ETDEWEB)

Pastorino, Roland, E-mail: roland.pastorino@kuleuven.be, E-mail: rpastorino@udc.es; Cosco, Francesco, E-mail: francesco.cosco@kuleuven.be; Naets, Frank, E-mail: frank.naets@kuleuven.be; Desmet, Wim, E-mail: wim.desmet@kuleuven.be [KU Leuven, PMA division, Department of Mechanical Engineering (Belgium); Cuadrado, Javier, E-mail: javicuad@cdf.udc.es [Universidad de La Coruña, Laboratorio de Ingeniería Mecánica (Spain)

2016-05-15

The real-time simulation of multibody models on embedded systems is of particular interest for controllers and observers such as model predictive controllers and state observers, which rely on a dynamic model of the process and are customarily executed in electronic control units. This work first identifies the software techniques and tools required to easily write efficient code for multibody models to be simulated on ARM-based embedded systems. Automatic Programming and Source Code Translation are the two techniques that were chosen to generate source code for multibody models in different programming languages. Automatic Programming is used to generate procedural code in an intermediate representation from an object-oriented library and Source Code Translation is used to translate the intermediate representation automatically to an interpreted language or to a compiled language for efficiency purposes. An implementation of these techniques is proposed. It is based on a Python template engine and AST tree walkers for Source Code Generation and on a model-driven translator for the Source Code Translation. The code is translated from a metalanguage to any of the following four programming languages: Python-Numpy, Matlab, C++-Armadillo, C++-Eigen. Two examples of multibody models were simulated: a four-bar linkage with multiple loops and a 3D vehicle steering system. The code for these examples has been generated and executed on two ARM-based single-board computers. Using compiled languages, both models could be simulated faster than real-time despite the low resources and performance of these embedded systems. Finally, the real-time performance of both models was evaluated when executed in hard real-time on Xenomai for both embedded systems. This work shows through measurements that Automatic Programming and Source Code Translation are valuable techniques to develop real-time multibody models to be used in embedded observers and controllers.

Hard real-time multibody simulations using ARM-based embedded systems

International Nuclear Information System (INIS)

Pastorino, Roland; Cosco, Francesco; Naets, Frank; Desmet, Wim; Cuadrado, Javier

2016-01-01

The real-time simulation of multibody models on embedded systems is of particular interest for controllers and observers such as model predictive controllers and state observers, which rely on a dynamic model of the process and are customarily executed in electronic control units. This work first identifies the software techniques and tools required to easily write efficient code for multibody models to be simulated on ARM-based embedded systems. Automatic Programming and Source Code Translation are the two techniques that were chosen to generate source code for multibody models in different programming languages. Automatic Programming is used to generate procedural code in an intermediate representation from an object-oriented library and Source Code Translation is used to translate the intermediate representation automatically to an interpreted language or to a compiled language for efficiency purposes. An implementation of these techniques is proposed. It is based on a Python template engine and AST tree walkers for Source Code Generation and on a model-driven translator for the Source Code Translation. The code is translated from a metalanguage to any of the following four programming languages: Python-Numpy, Matlab, C++-Armadillo, C++-Eigen. Two examples of multibody models were simulated: a four-bar linkage with multiple loops and a 3D vehicle steering system. The code for these examples has been generated and executed on two ARM-based single-board computers. Using compiled languages, both models could be simulated faster than real-time despite the low resources and performance of these embedded systems. Finally, the real-time performance of both models was evaluated when executed in hard real-time on Xenomai for both embedded systems. This work shows through measurements that Automatic Programming and Source Code Translation are valuable techniques to develop real-time multibody models to be used in embedded observers and controllers.

FPGA-based Fused Smart Sensor for Real-Time Plant-Transpiration Dynamic Estimation

Directory of Open Access Journals (Sweden)

Irineo Torres-Pacheco

2010-09-01

Full Text Available Plant transpiration is considered one of the most important physiological functions because it constitutes the plants evolving adaptation to exchange moisture with a dry atmosphere which can dehydrate or eventually kill the plant. Due to the importance of transpiration, accurate measurement methods are required; therefore, a smart sensor that fuses five primary sensors is proposed which can measure air temperature, leaf temperature, air relative humidity, plant out relative humidity and ambient light. A field programmable gate array based unit is used to perform signal processing algorithms as average decimation and infinite impulse response filters to the primary sensor readings in order to reduce the signal noise and improve its quality. Once the primary sensor readings are filtered, transpiration dynamics such as: transpiration, stomatal conductance, leaf-air-temperature-difference and vapor pressure deficit are calculated in real time by the smart sensor. This permits the user to observe different primary and calculated measurements at the same time and the relationship between these which is very useful in precision agriculture in the detection of abnormal conditions. Finally, transpiration related stress conditions can be detected in real time because of the use of online processing and embedded communications capabilities.

FPGA-based Fused Smart Sensor for Real-Time Plant-Transpiration Dynamic Estimation

Science.gov (United States)

Millan-Almaraz, Jesus Roberto; de Jesus Romero-Troncoso, Rene; Guevara-Gonzalez, Ramon Gerardo; Contreras-Medina, Luis Miguel; Carrillo-Serrano, Roberto Valentin; Osornio-Rios, Roque Alfredo; Duarte-Galvan, Carlos; Rios-Alcaraz, Miguel Angel; Torres-Pacheco, Irineo

2010-01-01

Plant transpiration is considered one of the most important physiological functions because it constitutes the plants evolving adaptation to exchange moisture with a dry atmosphere which can dehydrate or eventually kill the plant. Due to the importance of transpiration, accurate measurement methods are required; therefore, a smart sensor that fuses five primary sensors is proposed which can measure air temperature, leaf temperature, air relative humidity, plant out relative humidity and ambient light. A field programmable gate array based unit is used to perform signal processing algorithms as average decimation and infinite impulse response filters to the primary sensor readings in order to reduce the signal noise and improve its quality. Once the primary sensor readings are filtered, transpiration dynamics such as: transpiration, stomatal conductance, leaf-air-temperature-difference and vapor pressure deficit are calculated in real time by the smart sensor. This permits the user to observe different primary and calculated measurements at the same time and the relationship between these which is very useful in precision agriculture in the detection of abnormal conditions. Finally, transpiration related stress conditions can be detected in real time because of the use of online processing and embedded communications capabilities. PMID:22163656

A Circuit Model of Real Time Human Body Hydration.

Science.gov (United States)

Asogwa, Clement Ogugua; Teshome, Assefa K; Collins, Stephen F; Lai, Daniel T H

2016-06-01

Changes in human body hydration leading to excess fluid losses or overload affects the body fluid's ability to provide the necessary support for healthy living. We propose a time-dependent circuit model of real-time human body hydration, which models the human body tissue as a signal transmission medium. The circuit model predicts the attenuation of a propagating electrical signal. Hydration rates are modeled by a time constant τ, which characterizes the individual specific metabolic function of the body part measured. We define a surrogate human body anthropometric parameter θ by the muscle-fat ratio and comparing it with the body mass index (BMI), we find theoretically, the rate of hydration varying from 1.73 dB/min, for high θ and low τ to 0.05 dB/min for low θ and high τ. We compare these theoretical values with empirical measurements and show that real-time changes in human body hydration can be observed by measuring signal attenuation. We took empirical measurements using a vector network analyzer and obtained different hydration rates for various BMI, ranging from 0.6 dB/min for 22.7 [Formula: see text] down to 0.04 dB/min for 41.2 [Formula: see text]. We conclude that the galvanic coupling circuit model can predict changes in the volume of the body fluid, which are essential in diagnosing and monitoring treatment of body fluid disorder. Individuals with high BMI would have higher time-dependent biological characteristic, lower metabolic rate, and lower rate of hydration.

Energy efficient approach for transient fault recovery in real time ...

African Journals Online (AJOL)

DR OKE

Keywords: DVS, Fault tolerance, Real Time System, Transient Fault. ... in which missing the deadline may cause a failure and soft real time system, ..... Pillai, P., Shin, K., Real-time dynamic voltage scaling for low-power embedded operating ...

Real-Time and Real-Fast Performance of General-Purpose and Real-Time Operating Systems in Multithreaded Physical Simulation of Complex Mechanical Systems

Directory of Open Access Journals (Sweden)

Carlos Garre

2014-01-01

Full Text Available Physical simulation is a valuable tool in many fields of engineering for the tasks of design, prototyping, and testing. General-purpose operating systems (GPOS are designed for real-fast tasks, such as offline simulation of complex physical models that should finish as soon as possible. Interfacing hardware at a given rate (as in a hardware-in-the-loop test requires instead maximizing time determinism, for which real-time operating systems (RTOS are designed. In this paper, real-fast and real-time performance of RTOS and GPOS are compared when simulating models of high complexity with large time steps. This type of applications is usually present in the automotive industry and requires a good trade-off between real-fast and real-time performance. The performance of an RTOS and a GPOS is compared by running a tire model scalable on the number of degrees-of-freedom and parallel threads. The benchmark shows that the GPOS present better performance in real-fast runs but worse in real-time due to nonexplicit task switches and to the latency associated with interprocess communication (IPC and task switch.

A real-time architecture for time-aware agents.

Science.gov (United States)

Prouskas, Konstantinos-Vassileios; Pitt, Jeremy V

2004-06-01

This paper describes the specification and implementation of a new three-layer time-aware agent architecture. This architecture is designed for applications and environments where societies of humans and agents play equally active roles, but interact and operate in completely different time frames. The architecture consists of three layers: the April real-time run-time (ART) layer, the time aware layer (TAL), and the application agents layer (AAL). The ART layer forms the underlying real-time agent platform. An original online, real-time, dynamic priority-based scheduling algorithm is described for scheduling the computation time of agent processes, and it is shown that the algorithm's O(n) complexity and scalable performance are sufficient for application in real-time domains. The TAL layer forms an abstraction layer through which human and agent interactions are temporally unified, that is, handled in a common way irrespective of their temporal representation and scale. A novel O(n2) interaction scheduling algorithm is described for predicting and guaranteeing interactions' initiation and completion times. The time-aware predicting component of a workflow management system is also presented as an instance of the AAL layer. The described time-aware architecture addresses two key challenges in enabling agents to be effectively configured and applied in environments where humans and agents play equally active roles. It provides flexibility and adaptability in its real-time mechanisms while placing them under direct agent control, and it temporally unifies human and agent interactions.

TRSM-a thermal-hydraulic real-time simulation model for PWR

International Nuclear Information System (INIS)

Zhou Weichang

1997-01-01

TRSM (a Thermal-hydraulic Real-time Simulation Model) has been developed for PWR real-time simulation and best-estimate prediction of normal operating and abnormal accident conditions. It is a non-equilibrium two phase flow thermal-hydraulic model based on five basic conservation equations. A drift flux model is used to account for the unequal velocities of liquid and gaseous mixture, with or without the presence of the noncondensibles. Critical flow models are applied for break flow and valve flow calculations. A 5-regime two phase heat convection model is applied for clad-to-coolant as well as fluid-to-tubing heat transfer. A rigorous reactor coolant pump model is used to calculate the pressure drop and rise for the suction and discharge ends with complete pump characteristics curves included. The TRSM model has been adapted in the full-scale training simulator of Qinshan Nuclear Power Plant 300 MW unit to simulate the thermal-hydraulic performance of the NSSS. The simulation results of a cold leg LOCA and a steam generator tube rupture (SGTR) accident are presented

Research in Distributed Real-Time Systems

Science.gov (United States)

Mukkamala, R.

1997-01-01

This document summarizes the progress we have made on our study of issues concerning the schedulability of real-time systems. Our study has produced several results in the scalability issues of distributed real-time systems. In particular, we have used our techniques to resolve schedulability issues in distributed systems with end-to-end requirements. During the next year (1997-98), we propose to extend the current work to address the modeling and workload characterization issues in distributed real-time systems. In particular, we propose to investigate the effect of different workload models and component models on the design and the subsequent performance of distributed real-time systems.

Can Real-Time Systems Benefit from Dynamic Partial Reconfiguration?

DEFF Research Database (Denmark)

Pezzarossa, Luca; Kristensen, Andreas Toftegaard; Schoeberl, Martin

2017-01-01

In real-time systems, a solution where hardware accelerators are used to implement computationally intensive tasks can be easier to analyze, in terms of worst-case execution time (WCET), than a pure software solution. However, when using FPGAs, the amount and the complexity of the hardware...... hardware accelerators in real-time systems and presents an experimental analysis of the trade-offs between hardware utilization and WCET increase due to the reconfiguration time overhead of DPR. We also investigate the trade-off between the use of multiple specialized accelerators combined with DPR instead...

Real-time visualization of the vibrational wavepacket dynamics in electronically excited pyrimidine via femtosecond time-resolved photoelectron imaging

Science.gov (United States)

Li, Shuai; Long, Jinyou; Ling, Fengzi; Wang, Yanmei; Song, Xinli; Zhang, Song; Zhang, Bing

2017-07-01

The vibrational wavepacket dynamics at the very early stages of the S1-T1 intersystem crossing in photoexcited pyrimidine is visualized in real time by femtosecond time-resolved photoelectron imaging and time-resolved mass spectroscopy. A coherent superposition of the vibrational states is prepared by the femtosecond pump pulse at 315.3 nm, resulting in a vibrational wavepacket. The composition of the prepared wavepacket is directly identified by a sustained quantum beat superimposed on the parent-ion transient, possessing a frequency in accord with the energy separation between the 6a1 and 6b2 states. The dephasing time of the vibrational wavepacket is determined to be 82 ps. More importantly, the variable Franck-Condon factors between the wavepacket components and the dispersed cation vibrational levels are experimentally illustrated to identify the dark state and follow the energy-flow dynamics on the femtosecond time scale. The time-dependent intensities of the photoelectron peaks originated from the 6a1 vibrational state exhibit a clear quantum beating pattern with similar periodicity but a phase shift of π rad with respect to those from the 6b2 state, offering an unambiguous picture of the restricted intramolecular vibrational energy redistribution dynamics in the 6a1/6b2 Fermi resonance.

Real time wave forecasting using wind time history and numerical model

Science.gov (United States)

Jain, Pooja; Deo, M. C.; Latha, G.; Rajendran, V.

Operational activities in the ocean like planning for structural repairs or fishing expeditions require real time prediction of waves over typical time duration of say a few hours. Such predictions can be made by using a numerical model or a time series model employing continuously recorded waves. This paper presents another option to do so and it is based on a different time series approach in which the input is in the form of preceding wind speed and wind direction observations. This would be useful for those stations where the costly wave buoys are not deployed and instead only meteorological buoys measuring wind are moored. The technique employs alternative artificial intelligence approaches of an artificial neural network (ANN), genetic programming (GP) and model tree (MT) to carry out the time series modeling of wind to obtain waves. Wind observations at four offshore sites along the east coast of India were used. For calibration purpose the wave data was generated using a numerical model. The predicted waves obtained using the proposed time series models when compared with the numerically generated waves showed good resemblance in terms of the selected error criteria. Large differences across the chosen techniques of ANN, GP, MT were not noticed. Wave hindcasting at the same time step and the predictions over shorter lead times were better than the predictions over longer lead times. The proposed method is a cost effective and convenient option when a site-specific information is desired.

Real-time maneuver optimization of space-based robots in a dynamic environment: Theory and on-orbit experiments

Science.gov (United States)

Chamitoff, Gregory E.; Saenz-Otero, Alvar; Katz, Jacob G.; Ulrich, Steve; Morrell, Benjamin J.; Gibbens, Peter W.

2018-01-01

This paper presents the development of a real-time path-planning optimization approach to controlling the motion of space-based robots. The algorithm is capable of planning three dimensional trajectories for a robot to navigate within complex surroundings that include numerous static and dynamic obstacles, path constraints and performance limitations. The methodology employs a unique transformation that enables rapid generation of feasible solutions for complex geometries, making it suitable for application to real-time operations and dynamic environments. This strategy was implemented on the Synchronized Position Hold Engage Reorient Experimental Satellite (SPHERES) test-bed on the International Space Station (ISS), and experimental testing was conducted onboard the ISS during Expedition 17 by the first author. Lessons learned from the on-orbit tests were used to further refine the algorithm for future implementations.

Adaptive Anchoring Model: How Static and Dynamic Presentations of Time Series Influence Judgments and Predictions.

Science.gov (United States)

Kusev, Petko; van Schaik, Paul; Tsaneva-Atanasova, Krasimira; Juliusson, Asgeir; Chater, Nick

2018-01-01

When attempting to predict future events, people commonly rely on historical data. One psychological characteristic of judgmental forecasting of time series, established by research, is that when people make forecasts from series, they tend to underestimate future values for upward trends and overestimate them for downward ones, so-called trend-damping (modeled by anchoring on, and insufficient adjustment from, the average of recent time series values). Events in a time series can be experienced sequentially (dynamic mode), or they can also be retrospectively viewed simultaneously (static mode), not experienced individually in real time. In one experiment, we studied the influence of presentation mode (dynamic and static) on two sorts of judgment: (a) predictions of the next event (forecast) and (b) estimation of the average value of all the events in the presented series (average estimation). Participants' responses in dynamic mode were anchored on more recent events than in static mode for all types of judgment but with different consequences; hence, dynamic presentation improved prediction accuracy, but not estimation. These results are not anticipated by existing theoretical accounts; we develop and present an agent-based model-the adaptive anchoring model (ADAM)-to account for the difference between processing sequences of dynamically and statically presented stimuli (visually presented data). ADAM captures how variation in presentation mode produces variation in responses (and the accuracy of these responses) in both forecasting and judgment tasks. ADAM's model predictions for the forecasting and judgment tasks fit better with the response data than a linear-regression time series model. Moreover, ADAM outperformed autoregressive-integrated-moving-average (ARIMA) and exponential-smoothing models, while neither of these models accounts for people's responses on the average estimation task. Copyright © 2017 The Authors. Cognitive Science published by Wiley

Rapid Modeling of and Response to Large Earthquakes Using Real-Time GPS Networks (Invited)

Science.gov (United States)

Crowell, B. W.; Bock, Y.; Squibb, M. B.

2010-12-01

Real-time GPS networks have the advantage of capturing motions throughout the entire earthquake cycle (interseismic, seismic, coseismic, postseismic), and because of this, are ideal for real-time monitoring of fault slip in the region. Real-time GPS networks provide the perfect supplement to seismic networks, which operate with lower noise and higher sampling rates than GPS networks, but only measure accelerations or velocities, putting them at a supreme disadvantage for ascertaining the full extent of slip during a large earthquake in real-time. Here we report on two examples of rapid modeling of recent large earthquakes near large regional real-time GPS networks. The first utilizes Japan’s GEONET consisting of about 1200 stations during the 2003 Mw 8.3 Tokachi-Oki earthquake about 100 km offshore Hokkaido Island and the second investigates the 2010 Mw 7.2 El Mayor-Cucapah earthquake recorded by more than 100 stations in the California Real Time Network. The principal components of strain were computed throughout the networks and utilized as a trigger to initiate earthquake modeling. Total displacement waveforms were then computed in a simulated real-time fashion using a real-time network adjustment algorithm that fixes a station far away from the rupture to obtain a stable reference frame. Initial peak ground displacement measurements can then be used to obtain an initial size through scaling relationships. Finally, a full coseismic model of the event can be run minutes after the event, given predefined fault geometries, allowing emergency first responders and researchers to pinpoint the regions of highest damage. Furthermore, we are also investigating using total displacement waveforms for real-time moment tensor inversions to look at spatiotemporal variations in slip.

Learning Constructive Primitives for Real-time Dynamic Difficulty Adjustment in Super Mario Bros

OpenAIRE

Shi, Peizhi; Chen, Ke

2017-01-01

Among the main challenges in procedural content generation (PCG), content quality assurance and dynamic difficulty adjustment (DDA) of game content in real time are two major issues concerned in adaptive content generation. Motivated by the recent learning-based PCG framework, we propose a novel approach to seamlessly address two issues in Super Mario Bros (SMB). To address the quality assurance issue, we exploit the synergy between rule-based and learning-based methods to produce quality gam...

Modeling Nonstationary Emotion Dynamics in Dyads using a Time-Varying Vector-Autoregressive Model.

Science.gov (United States)

Bringmann, Laura F; Ferrer, Emilio; Hamaker, Ellen L; Borsboom, Denny; Tuerlinckx, Francis

2018-01-01

Emotion dynamics are likely to arise in an interpersonal context. Standard methods to study emotions in interpersonal interaction are limited because stationarity is assumed. This means that the dynamics, for example, time-lagged relations, are invariant across time periods. However, this is generally an unrealistic assumption. Whether caused by an external (e.g., divorce) or an internal (e.g., rumination) event, emotion dynamics are prone to change. The semi-parametric time-varying vector-autoregressive (TV-VAR) model is based on well-studied generalized additive models, implemented in the software R. The TV-VAR can explicitly model changes in temporal dependency without pre-existing knowledge about the nature of change. A simulation study is presented, showing that the TV-VAR model is superior to the standard time-invariant VAR model when the dynamics change over time. The TV-VAR model is applied to empirical data on daily feelings of positive affect (PA) from a single couple. Our analyses indicate reliable changes in the male's emotion dynamics over time, but not in the female's-which were not predicted by her own affect or that of her partner. This application illustrates the usefulness of using a TV-VAR model to detect changes in the dynamics in a system.

The dosimetric impact of inversely optimized arc radiotherapy plan modulation for real-time dynamic MLC tracking delivery

DEFF Research Database (Denmark)

Falk, Marianne; Larsson, Tobias; Keall, P.

2012-01-01

Purpose: Real-time dynamic multileaf collimator (MLC) tracking for management of intrafraction tumor motion can be challenging for highly modulated beams, as the leaves need to travel far to adjust for target motion perpendicular to the leaf travel direction. The plan modulation can be reduced......-to-peak displacement of 2 cm and a cycle time of 6 s. The delivery was adjusted to the target motion using MLC tracking, guided in real-time by an infrared optical system. The dosimetric results were evaluated using gamma index evaluation with static target measurements as reference. Results: The plan quality...

Modeling biological pathway dynamics with timed automata.

Science.gov (United States)

Schivo, Stefano; Scholma, Jetse; Wanders, Brend; Urquidi Camacho, Ricardo A; van der Vet, Paul E; Karperien, Marcel; Langerak, Rom; van de Pol, Jaco; Post, Janine N

2014-05-01

Living cells are constantly subjected to a plethora of environmental stimuli that require integration into an appropriate cellular response. This integration takes place through signal transduction events that form tightly interconnected networks. The understanding of these networks requires capturing their dynamics through computational support and models. ANIMO (analysis of Networks with Interactive Modeling) is a tool that enables the construction and exploration of executable models of biological networks, helping to derive hypotheses and to plan wet-lab experiments. The tool is based on the formalism of Timed Automata, which can be analyzed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signaling networks. This enforces precision and uniformity in the definition of signaling pathways, contributing to the integration of isolated signaling events into complex network models. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic behavior of the network of interest. A user-friendly interface hides the use of Timed Automata from the user, while keeping the expressive power intact. Abstraction to single-parameter kinetics speeds up construction of models that remain faithful enough to provide meaningful insight. The resulting dynamic behavior of the network components is displayed graphically, allowing for an intuitive and interactive modeling experience.

Real-time characterization of partially observed epidemics using surrogate models.

Energy Technology Data Exchange (ETDEWEB)

Safta, Cosmin; Ray, Jaideep; Lefantzi, Sophia; Crary, David (Applied Research Associates, Arlington, VA); Sargsyan, Khachik; Cheng, Karen (Applied Research Associates, Arlington, VA)

2011-09-01

We present a statistical method, predicated on the use of surrogate models, for the 'real-time' characterization of partially observed epidemics. Observations consist of counts of symptomatic patients, diagnosed with the disease, that may be available in the early epoch of an ongoing outbreak. Characterization, in this context, refers to estimation of epidemiological parameters that can be used to provide short-term forecasts of the ongoing epidemic, as well as to provide gross information on the dynamics of the etiologic agent in the affected population e.g., the time-dependent infection rate. The characterization problem is formulated as a Bayesian inverse problem, and epidemiological parameters are estimated as distributions using a Markov chain Monte Carlo (MCMC) method, thus quantifying the uncertainty in the estimates. In some cases, the inverse problem can be computationally expensive, primarily due to the epidemic simulator used inside the inversion algorithm. We present a method, based on replacing the epidemiological model with computationally inexpensive surrogates, that can reduce the computational time to minutes, without a significant loss of accuracy. The surrogates are created by projecting the output of an epidemiological model on a set of polynomial chaos bases; thereafter, computations involving the surrogate model reduce to evaluations of a polynomial. We find that the epidemic characterizations obtained with the surrogate models is very close to that obtained with the original model. We also find that the number of projections required to construct a surrogate model is O(10)-O(10{sup 2}) less than the number of samples required by the MCMC to construct a stationary posterior distribution; thus, depending upon the epidemiological models in question, it may be possible to omit the offline creation and caching of surrogate models, prior to their use in an inverse problem. The technique is demonstrated on synthetic data as well as

Implementation of the frequency dependent line model in a real-time power system simulator

Directory of Open Access Journals (Sweden)

Reynaldo Iracheta-Cortez

2017-09-01

Full Text Available In this paper is described the implementation of the frequency-dependent line model (FD-Line in a real-time digital power system simulator. The main goal with such development is to describe a general procedure to incorporate new realistic models of power system components in modern real-time simulators based on the Electromagnetic Transients Program (EMTP. In this procedure are described, firstly, the steps to obtain the time domain solution of the differential equations that models the electromagnetic behavior in multi-phase transmission lines with frequency dependent parameters. After, the algorithmic solution of the FD-Line model is implemented in Simulink environment, through an S-function programmed in C language, for running off-line simulations of electromagnetic transients. This implementation allows the free assembling of the FD Line model with any element of the Power System Blockset library and also, it can be used to build any network topology. The main advantage of having a power network built in Simulink is that can be executed in real-time by means of the commercial eMEGAsim simulator. Finally, several simulation cases are presented to validate the accuracy and the real-time performance of the FD-Line model.

Real-time Fatigue and Free-Living Physical Activity in Hematopoietic Stem Cell Transplantation Cancer Survivors and Healthy Controls: A Preliminary Examination of the Temporal, Dynamic Relationship.

Science.gov (United States)

Hacker, Eileen Danaher; Kim, Inah; Park, Chang; Peters, Tara

Fatigue and physical inactivity, critical problems facing cancer survivors, impact overall health and functioning. Our group designed a novel methodology to evaluate the temporal, dynamic patterns in real-world settings. Using real-time technology, the temporal, dynamic relationship between real-time fatigue and free-living is described and compared in cancer survivors who were treated with hematopoietic stem cell transplantation (n = 25) and age- and gender-matched healthy controls (n = 25). Subjects wore wrist actigraphs on their nondominant hand to assess free-living physical activity, measured in 1-minute epochs, over 7 days. Subjects entered real-time fatigue assessments directly into the subjective event marker of the actigraph 5 times per day. Running averages of mean 1-minute activity counts 30, 60, and 120 minutes before and after each real-time fatigue score were correlated with real-time fatigue using generalized estimating equations, RESULTS:: A strong inverse relationship exists between real-time fatigue and subsequent free-living physical activity. This inverse relationship suggests that increasing real-time fatigue limits subsequent physical activity (B range= -0.002 to -0.004; P < .001). No significant differences in the dynamic patterns of real-time fatigue and free-living physical activity were found between groups. To our knowledge, this is the first study to document the temporal and potentially causal relationship between real-time fatigue and free-living physical activity in real-world setting. These findings suggest that fatigue drives the subsequent physical activity and the relationship may not be bidirectional. Understanding the temporal, dynamic relationship may have important health implications for developing interventions to address fatigue in cancer survivors.

Real-time objects development: Study and proposal for a parallel scheduling architecture

International Nuclear Information System (INIS)

Rioux, Laurent

1997-01-01

This thesis contributes to the programming and the execution control of real-time object oriented applications. Using real-time objects is very interesting for programming real- time applications, because this model can introduce the concurrence with the encapsulation properties, with modularity and reusability by taking into account the real-time constraints of the application. One essential quality of this approach is that it can directly specify the parallelism and the real-time constraints at the model level of the application. An annotation system of C++ has been defined to describe the real-time specifications in the model (or in the source code) of the application. It will supply to the execution support the different information it needs for the control. In this approach of multitasking, the control is distributed and encapsulated inside each real time object. Three complementary levels of control have been defined: the state level (defining the capability of an object to treat an operation), the concurrence level (assuring the coherence between the object attributes) and a scheduling control (allocating the processors resources to the object by taking real-time constraints into account). The proposed control architecture, named OROS, manages the attribute access of each object in an individual way, then it can parallel treatments which do not access at the same data. This architecture makes a dynamic control of an application that can take benefit from the parallelism of the new machines both for the execution parallelism and the control itself. This architecture uses only the simplest primitives of the industrial real-time operating systems which ensures its feasibility and portability. (author) [fr

Reasoning about real-time systems with temporal interval logic constraints on multi-state automata

Science.gov (United States)

Gabrielian, Armen

1991-01-01

Models of real-time systems using a single paradigm often turn out to be inadequate, whether the paradigm is based on states, rules, event sequences, or logic. A model-based approach to reasoning about real-time systems is presented in which a temporal interval logic called TIL is employed to define constraints on a new type of high level automata. The combination, called hierarchical multi-state (HMS) machines, can be used to model formally a real-time system, a dynamic set of requirements, the environment, heuristic knowledge about planning-related problem solving, and the computational states of the reasoning mechanism. In this framework, mathematical techniques were developed for: (1) proving the correctness of a representation; (2) planning of concurrent tasks to achieve goals; and (3) scheduling of plans to satisfy complex temporal constraints. HMS machines allow reasoning about a real-time system from a model of how truth arises instead of merely depending of what is true in a system.

A real-time computational model for estimating kinematics of ankle ligaments.

Science.gov (United States)

Zhang, Mingming; Davies, T Claire; Zhang, Yanxin; Xie, Sheng Quan

2016-01-01

An accurate assessment of ankle ligament kinematics is crucial in understanding the injury mechanisms and can help to improve the treatment of an injured ankle, especially when used in conjunction with robot-assisted therapy. A number of computational models have been developed and validated for assessing the kinematics of ankle ligaments. However, few of them can do real-time assessment to allow for an input into robotic rehabilitation programs. An ankle computational model was proposed and validated to quantify the kinematics of ankle ligaments as the foot moves in real-time. This model consists of three bone segments with three rotational degrees of freedom (DOFs) and 12 ankle ligaments. This model uses inputs for three position variables that can be measured from sensors in many ankle robotic devices that detect postures within the foot-ankle environment and outputs the kinematics of ankle ligaments. Validation of this model in terms of ligament length and strain was conducted by comparing it with published data on cadaver anatomy and magnetic resonance imaging. The model based on ligament lengths and strains is in concurrence with those from the published studies but is sensitive to ligament attachment positions. This ankle computational model has the potential to be used in robot-assisted therapy for real-time assessment of ligament kinematics. The results provide information regarding the quantification of kinematics associated with ankle ligaments related to the disability level and can be used for optimizing the robotic training trajectory.

A Distributed Web-based Solution for Ionospheric Model Real-time Management, Monitoring, and Short-term Prediction

Science.gov (United States)

Kulchitsky, A.; Maurits, S.; Watkins, B.

2006-12-01

With the widespread availability of the Internet today, many people can monitor various scientific research activities. It is important to accommodate this interest providing on-line access to dynamic and illustrative Web-resources, which could demonstrate different aspects of ongoing research. It is especially important to explain and these research activities for high school and undergraduate students, thereby providing more information for making decisions concerning their future studies. Such Web resources are also important to clarify scientific research for the general public, in order to achieve better awareness of research progress in various fields. Particularly rewarding is dissemination of information about ongoing projects within Universities and research centers to their local communities. The benefits of this type of scientific outreach are mutual, since development of Web-based automatic systems is prerequisite for many research projects targeting real-time monitoring and/or modeling of natural conditions. Continuous operation of such systems provide ongoing research opportunities for the statistically massive validation of the models, as well. We have developed a Web-based system to run the University of Alaska Fairbanks Polar Ionospheric Model in real-time. This model makes use of networking and computational resources at the Arctic Region Supercomputing Center. This system was designed to be portable among various operating systems and computational resources. Its components can be installed across different computers, separating Web servers and computational engines. The core of the system is a Real-Time Management module (RMM) written Python, which facilitates interactions of remote input data transfers, the ionospheric model runs, MySQL database filling, and PHP scripts for the Web-page preparations. The RMM downloads current geophysical inputs as soon as they become available at different on-line depositories. This information is processed to

Breaking Computational Barriers: Real-time Analysis and Optimization with Large-scale Nonlinear Models via Model Reduction

Energy Technology Data Exchange (ETDEWEB)

Carlberg, Kevin Thomas [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Quantitative Modeling and Analysis; Drohmann, Martin [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Quantitative Modeling and Analysis; Tuminaro, Raymond S. [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Computational Mathematics; Boggs, Paul T. [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Quantitative Modeling and Analysis; Ray, Jaideep [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Quantitative Modeling and Analysis; van Bloemen Waanders, Bart Gustaaf [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Optimization and Uncertainty Estimation

2014-10-01

Model reduction for dynamical systems is a promising approach for reducing the computational cost of large-scale physics-based simulations to enable high-fidelity models to be used in many- query (e.g., Bayesian inference) and near-real-time (e.g., fast-turnaround simulation) contexts. While model reduction works well for specialized problems such as linear time-invariant systems, it is much more difficult to obtain accurate, stable, and efficient reduced-order models (ROMs) for systems with general nonlinearities. This report describes several advances that enable nonlinear reduced-order models (ROMs) to be deployed in a variety of time-critical settings. First, we present an error bound for the Gauss-Newton with Approximated Tensors (GNAT) nonlinear model reduction technique. This bound allows the state-space error for the GNAT method to be quantified when applied with the backward Euler time-integration scheme. Second, we present a methodology for preserving classical Lagrangian structure in nonlinear model reduction. This technique guarantees that important properties--such as energy conservation and symplectic time-evolution maps--are preserved when performing model reduction for models described by a Lagrangian formalism (e.g., molecular dynamics, structural dynamics). Third, we present a novel technique for decreasing the temporal complexity --defined as the number of Newton-like iterations performed over the course of the simulation--by exploiting time-domain data. Fourth, we describe a novel method for refining projection-based reduced-order models a posteriori using a goal-oriented framework similar to mesh-adaptive h -refinement in finite elements. The technique allows the ROM to generate arbitrarily accurate solutions, thereby providing the ROM with a 'failsafe' mechanism in the event of insufficient training data. Finally, we present the reduced-order model error surrogate (ROMES) method for statistically quantifying reduced- order-model

Resolving dynamics of cell signaling via real-time imaging of the immunological synapse.

Energy Technology Data Exchange (ETDEWEB)

Stevens, Mark A.; Pfeiffer, Janet R. (University of New Mexico, Albuquerque, NM); Wilson, Bridget S. (University of New Mexico, Albuquerque, NM); Timlin, Jerilyn Ann; Thomas, James L. (University of New Mexico, Albuquerque, NM); Lidke, Keith A. (University of New Mexico, Albuquerque, NM); Spendier, Kathrin (University of New Mexico, Albuquerque, NM); Oliver, Janet M. (University of New Mexico, Albuquerque, NM); Carroll-Portillo, Amanda (University of New Mexico, Albuquerque, NM); Aaron, Jesse S.; Mirijanian, Dina T.; Carson, Bryan D.; Burns, Alan Richard; Rebeil, Roberto

2009-10-01

This highly interdisciplinary team has developed dual-color, total internal reflection microscopy (TIRF-M) methods that enable us to optically detect and track in real time protein migration and clustering at membrane interfaces. By coupling TIRF-M with advanced analysis techniques (image correlation spectroscopy, single particle tracking) we have captured subtle changes in membrane organization that characterize immune responses. We have used this approach to elucidate the initial stages of cell activation in the IgE signaling network of mast cells and the Toll-like receptor (TLR-4) response in macrophages stimulated by bacteria. To help interpret these measurements, we have undertaken a computational modeling effort to connect the protein motion and lipid interactions. This work provides a deeper understanding of the initial stages of cellular response to external agents, including dynamics of interaction of key components in the signaling network at the 'immunological synapse,' the contact region of the cell and its adversary.

Borehole modelling: a comparison between a steady-state model and a novel dynamic model in a real ON/OFF GSHP operation

International Nuclear Information System (INIS)

De Rosa, M; Tagliafico, L A; Ruiz-Calvo, F; Corberán, J M; Montagud, C

2014-01-01

The correct design and optimization of complex energy systems requires the ability to reproduce the dynamic thermal behavior of each system component. In ground source heat pump (GSHP) systems, modelling the borehole heat exchangers (BHE) dynamic response is especially relevant in the development of control strategies for energy optimization purposes. Over the last years, several models have been developed but most of them are based on steady- state approaches, which makes them unsuitable for short-term simulation purposes. In fact, in order to accurately predict the evolution of the fluid temperatures due to the ON/OFF cycles of the heat pump, it is essential to correctly characterize the dynamic response of BHE for very short time periods. The aim of the present paper is to compare the performance of an analytical steady-state model, available in TRNSYS environment (Type 557), with a novel short-term dynamic model. The new dynamic model is based on the thermal-network approach coupled with a vertical discretization of the borehole which takes into account both the advection due to the fluid circulating along the U-tube, and the heat transfer in the borehole and in the ground. These two approaches were compared against experimental data collected from a real GSHP system installed at the Universitat Politecnica de Valencia. The analysis was performed comparing the outlet temperature profiles predicted by both models during daily standard ON/OFF operating conditions, both in heating and cooling mode, and the between both approaches were highlighted. Finally, the obtained results have been discussed focusing on the potential impact that the differences found in the prediction of the temperature evolution could have in design and optimization of GSHP systems

Multiprocessor scheduling for real-time systems

CERN Document Server

Baruah, Sanjoy; Buttazzo, Giorgio

2015-01-01

This book provides a comprehensive overview of both theoretical and pragmatic aspects of resource-allocation and scheduling in multiprocessor and multicore hard-real-time systems.  The authors derive new, abstract models of real-time tasks that capture accurately the salient features of real application systems that are to be implemented on multiprocessor platforms, and identify rules for mapping application systems onto the most appropriate models.  New run-time multiprocessor scheduling algorithms are presented, which are demonstrably better than those currently used, both in terms of run-time efficiency and tractability of off-line analysis.  Readers will benefit from a new design and analysis framework for multiprocessor real-time systems, which will translate into a significantly enhanced ability to provide formally verified, safety-critical real-time systems at a significantly lower cost.

Processor tradeoffs in distributed real-time systems

Science.gov (United States)

Krishna, C. M.; Shin, Kang G.; Bhandari, Inderpal S.

1987-01-01

The problem of the optimization of the design of real-time distributed systems is examined with reference to a class of computer architectures similar to the continuously reconfigurable multiprocessor flight control system structure, CM2FCS. Particular attention is given to the impact of processor replacement and the burn-in time on the probability of dynamic failure and mean cost. The solution is obtained numerically and interpreted in the context of real-time applications.

Benefits of real-time gas management

International Nuclear Information System (INIS)

Nolty, R.; Dolezalek, D. Jr.

1994-01-01

In today's competitive gas gathering, processing, storage and transportation business environment, the requirements to do business are continually changing. These changes arise from government regulations such as the amendments to the Clean Air Act concerning the environment and FERC Order 636 concerning business practices. Other changes are due to advances in technology such as electronic flow measurement (EFM) and real-time communications capabilities within the gas industry. Gas gathering, processing, storage and transportation companies must be flexible in adapting to these changes to remain competitive. These dynamic requirements can be met with an open, real-time gas management computer information system. Such a system provides flexible services with a variety of software applications. Allocations, nominations management and gas dispatching are examples of applications that are provided on a real-time basis. By providing real-time services, the gas management system enables operations personnel to make timely adjustments within the current accounting period. Benefits realized from implementing a real-time gas management system include reduced unaccountable gas, reduced imbalance penalties, reduced regulatory violations, improved facility operations and better service to customers. These benefits give a company the competitive edge. This article discusses the applications provided, the benefits from implementing a real-time gas management system, and the definition of such a system

GNSS global real-time augmentation positioning: Real-time precise satellite clock estimation, prototype system construction and performance analysis

Science.gov (United States)

Chen, Liang; Zhao, Qile; Hu, Zhigang; Jiang, Xinyuan; Geng, Changjiang; Ge, Maorong; Shi, Chuang

2018-01-01

Lots of ambiguities in un-differenced (UD) model lead to lower calculation efficiency, which isn't appropriate for the high-frequency real-time GNSS clock estimation, like 1 Hz. Mixed differenced model fusing UD pseudo-range and epoch-differenced (ED) phase observations has been introduced into real-time clock estimation. In this contribution, we extend the mixed differenced model for realizing multi-GNSS real-time clock high-frequency updating and a rigorous comparison and analysis on same conditions are performed to achieve the best real-time clock estimation performance taking the efficiency, accuracy, consistency and reliability into consideration. Based on the multi-GNSS real-time data streams provided by multi-GNSS Experiment (MGEX) and Wuhan University, GPS + BeiDou + Galileo global real-time augmentation positioning prototype system is designed and constructed, including real-time precise orbit determination, real-time precise clock estimation, real-time Precise Point Positioning (RT-PPP) and real-time Standard Point Positioning (RT-SPP). The statistical analysis of the 6 h-predicted real-time orbits shows that the root mean square (RMS) in radial direction is about 1-5 cm for GPS, Beidou MEO and Galileo satellites and about 10 cm for Beidou GEO and IGSO satellites. Using the mixed differenced estimation model, the prototype system can realize high-efficient real-time satellite absolute clock estimation with no constant clock-bias and can be used for high-frequency augmentation message updating (such as 1 Hz). The real-time augmentation message signal-in-space ranging error (SISRE), a comprehensive accuracy of orbit and clock and effecting the users' actual positioning performance, is introduced to evaluate and analyze the performance of GPS + BeiDou + Galileo global real-time augmentation positioning system. The statistical analysis of real-time augmentation message SISRE is about 4-7 cm for GPS, whlile 10 cm for Beidou IGSO/MEO, Galileo and about 30 cm

Using Self-Adaptive Evolutionary Algorithms to Evolve Dynamism-Oriented Maps for a Real Time Strategy Game

OpenAIRE

Lara-Cabrera, Raúl; Cotta, Carlos; Fernández Leiva, Antonio J.

2013-01-01

This work presents a procedural content generation system that uses an evolutionary algorithm in order to generate interesting maps for a real-time strategy game, called Planet Wars. Interestingness is here captured by the dynamism of games (i.e., the extent to which they are action-packed). We consider two different approaches to measure the dynamism of the games resulting from these generated maps, one based on fluctuations in the resources controlled by either player and another one based ...

Online gaming for learning optimal team strategies in real time

Science.gov (United States)

Hudas, Gregory; Lewis, F. L.; Vamvoudakis, K. G.

2010-04-01

This paper first presents an overall view for dynamical decision-making in teams, both cooperative and competitive. Strategies for team decision problems, including optimal control, zero-sum 2-player games (H-infinity control) and so on are normally solved for off-line by solving associated matrix equations such as the Riccati equation. However, using that approach, players cannot change their objectives online in real time without calling for a completely new off-line solution for the new strategies. Therefore, in this paper we give a method for learning optimal team strategies online in real time as team dynamical play unfolds. In the linear quadratic regulator case, for instance, the method learns the Riccati equation solution online without ever solving the Riccati equation. This allows for truly dynamical team decisions where objective functions can change in real time and the system dynamics can be time-varying.

A real-time prediction model for post-irradiation malignant cervical lymph nodes.

Science.gov (United States)

Lo, W-C; Cheng, P-W; Shueng, P-W; Hsieh, C-H; Chang, Y-L; Liao, L-J

2018-04-01

To establish a real-time predictive scoring model based on sonographic characteristics for identifying malignant cervical lymph nodes (LNs) in cancer patients after neck irradiation. One-hundred forty-four irradiation-treated patients underwent ultrasonography and ultrasound-guided fine-needle aspirations (USgFNAs), and the resultant data were used to construct a real-time and computerised predictive scoring model. This scoring system was further compared with our previously proposed prediction model. A predictive scoring model, 1.35 × (L axis) + 2.03 × (S axis) + 2.27 × (margin) + 1.48 × (echogenic hilum) + 3.7, was generated by stepwise multivariate logistic regression analysis. Neck LNs were considered to be malignant when the score was ≥ 7, corresponding to a sensitivity of 85.5%, specificity of 79.4%, positive predictive value (PPV) of 82.3%, negative predictive value (NPV) of 83.1%, and overall accuracy of 82.6%. When this new model and the original model were compared, the areas under the receiver operating characteristic curve (c-statistic) were 0.89 and 0.81, respectively (P real-time sonographic predictive scoring model was constructed to provide prompt and reliable guidance for USgFNA biopsies to manage cervical LNs after neck irradiation. © 2017 John Wiley & Sons Ltd.

Parity-Time Symmetry and the Toy Models of Gain-Loss Dynamics near the Real Kato’s Exceptional Points

Directory of Open Access Journals (Sweden)

Miloslav Znojil

2016-06-01

Full Text Available For a given operator D ( t of an observable in theoretical parity-time symmetric quantum physics (or for its evolution-generator analogues in the experimental gain-loss classical optics, etc. the instant t c r i t i c a l of a spontaneous breakdown of the parity-time alias gain-loss symmetry should be given, in the rigorous language of mathematics, the Kato’s name of an “exceptional point”, t c r i t i c a l = t ( E P . In the majority of conventional applications the exceptional point (EP values are not real. In our paper, we pay attention to several exactly tractable toy-model evolutions for which at least some of the values of t ( E P become real. These values are interpreted as “instants of a catastrophe”, be it classical or quantum. In the classical optical setting the discrete nature of our toy models might make them amenable to simulations. In the latter context the instant of Big Bang is mentioned as an illustrative sample of possible physical meaning of such an EP catastrophe in quantum cosmology.

Near-real-time regional troposphere models for the GNSS precise point positioning technique

International Nuclear Information System (INIS)

Hadas, T; Kaplon, J; Bosy, J; Sierny, J; Wilgan, K

2013-01-01

The GNSS precise point positioning (PPP) technique requires high quality product (orbits and clocks) application, since their error directly affects the quality of positioning. For real-time purposes it is possible to utilize ultra-rapid precise orbits and clocks which are disseminated through the Internet. In order to eliminate as many unknown parameters as possible, one may introduce external information on zenith troposphere delay (ZTD). It is desirable that the a priori model is accurate and reliable, especially for real-time application. One of the open problems in GNSS positioning is troposphere delay modelling on the basis of ground meteorological observations. Institute of Geodesy and Geoinformatics of Wroclaw University of Environmental and Life Sciences (IGG WUELS) has developed two independent regional troposphere models for the territory of Poland. The first one is estimated in near-real-time regime using GNSS data from a Polish ground-based augmentation system named ASG-EUPOS established by Polish Head Office of Geodesy and Cartography (GUGiK) in 2008. The second one is based on meteorological parameters (temperature, pressure and humidity) gathered from various meteorological networks operating over the area of Poland and surrounding countries. This paper describes the methodology of both model calculation and verification. It also presents results of applying various ZTD models into kinematic PPP in the post-processing mode using Bernese GPS Software. Positioning results were used to assess the quality of the developed models during changing weather conditions. Finally, the impact of model application to simulated real-time PPP on precision, accuracy and convergence time is discussed. (paper)

Real-time simulation of MHD/steam power plants by digital parallel processors

International Nuclear Information System (INIS)

Johnson, R.M.; Rudberg, D.A.

1981-01-01

Attention is given to a large FORTRAN coded program which simulates the dynamic response of the MHD/steam plant on either a SEL 32/55 or VAX 11/780 computer. The code realizes a detailed first-principle model of the plant. Quite recently, in addition to the VAX 11/780, an AD-10 has been installed for usage as a real-time simulation facility. The parallel processor AD-10 is capable of simulating the MHD/steam plant at several times real-time rates. This is desirable in order to develop rapidly a large data base of varied plant operating conditions. The combined-cycle MHD/steam plant model is discussed, taking into account a number of disadvantages. The disadvantages can be overcome with the aid of an array processor used as an adjunct to the unit processor. The conversion of some computations for real-time simulation is considered

Real-time systems

OpenAIRE

Badr, Salah M.; Bruztman, Donald P.; Nelson, Michael L.; Byrnes, Ronald Benton

1992-01-01

This paper presents an introduction to the basic issues involved in real-time systems. Both real-time operating sys and real-time programming languages are explored. Concurrent programming and process synchronization and communication are also discussed. The real-time requirements of the Naval Postgraduate School Autonomous Under Vehicle (AUV) are then examined. Autonomous underwater vehicle (AUV), hard real-time system, real-time operating system, real-time programming language, real-time sy...

CD-SEM real time bias correction using reference metrology based modeling

Science.gov (United States)

Ukraintsev, V.; Banke, W.; Zagorodnev, G.; Archie, C.; Rana, N.; Pavlovsky, V.; Smirnov, V.; Briginas, I.; Katnani, A.; Vaid, A.

2018-03-01

Accuracy of patterning impacts yield, IC performance and technology time to market. Accuracy of patterning relies on optical proximity correction (OPC) models built using CD-SEM inputs and intra die critical dimension (CD) control based on CD-SEM. Sub-nanometer measurement uncertainty (MU) of CD-SEM is required for current technologies. Reported design and process related bias variation of CD-SEM is in the range of several nanometers. Reference metrology and numerical modeling are used to correct SEM. Both methods are slow to be used for real time bias correction. We report on real time CD-SEM bias correction using empirical models based on reference metrology (RM) data. Significant amount of currently untapped information (sidewall angle, corner rounding, etc.) is obtainable from SEM waveforms. Using additional RM information provided for specific technology (design rules, materials, processes) CD extraction algorithms can be pre-built and then used in real time for accurate CD extraction from regular CD-SEM images. The art and challenge of SEM modeling is in finding robust correlation between SEM waveform features and bias of CD-SEM as well as in minimizing RM inputs needed to create accurate (within the design and process space) model. The new approach was applied to improve CD-SEM accuracy of 45 nm GATE and 32 nm MET1 OPC 1D models. In both cases MU of the state of the art CD-SEM has been improved by 3x and reduced to a nanometer level. Similar approach can be applied to 2D (end of line, contours, etc.) and 3D (sidewall angle, corner rounding, etc.) cases.

Real-time object-oriented programming: studies and proposals

International Nuclear Information System (INIS)

Fouquier, Gilles

1996-01-01

This thesis contributes to the introduction of real-time features in object-oriented programming. Object-oriented programming favours modularity and reusability. Therefore, its application to real-time introduces many theoretical and conceptual problems. To deal with these problems, a new real-time object-oriented programming model is presented. This model is based on the active object model which allows concurrence and maintains the encapsulation property. The real-time aspect is treated by replacing the concept of task by the concept of method processing and by associating a real-time constraint to each message (priority or deadline). The set of all the running methods is scheduled. This model, called ATOME, contains several sub-models to deal with the usual concurrence control integrating their priority and deadline processing. The classical HPF and EDF scheduling avoid priority or deadline inversion. This model and its variants are new proposals to program real-time applications in the object-oriented way, therefore easing reusability and code writing. The feasibility of this approach is demonstrated by extending and existing active object-based language to real-time, in using the rules defined in the ATOME model. (author) [fr

Real-time PCR Machine System Modeling and a Systematic Approach for the Robust Design of a Real-time PCR-on-a-Chip System

Directory of Open Access Journals (Sweden)

Da-Sheng Lee

2010-01-01

Full Text Available Chip-based DNA quantification systems are widespread, and used in many point-of-care applications. However, instruments for such applications may not be maintained or calibrated regularly. Since machine reliability is a key issue for normal operation, this study presents a system model of the real-time Polymerase Chain Reaction (PCR machine to analyze the instrument design through numerical experiments. Based on model analysis, a systematic approach was developed to lower the variation of DNA quantification and achieve a robust design for a real-time PCR-on-a-chip system. Accelerated lift testing was adopted to evaluate the reliability of the chip prototype. According to the life test plan, this proposed real-time PCR-on-a-chip system was simulated to work continuously for over three years with similar reproducibility in DNA quantification. This not only shows the robustness of the lab-on-a-chip system, but also verifies the effectiveness of our systematic method for achieving a robust design.

Modeling dynamic effects of promotion on interpurchase times

NARCIS (Netherlands)

D. Fok (Dennis); R. Paap (Richard); Ph.H.B.F. Franses (Philip Hans)

2002-01-01

textabstractIn this paper we put forward a duration model to analyze the dynamic effects of marketing-mix variables on interpurchase times. We extend the accelerated failure-time model with an autoregressive structure. An important feature of our model is that it allows for different long-run and

Interdyad Differences in Early Mother-Infant Face-to-Face Communication: Real-Time Dynamics and Developmental Pathways

Science.gov (United States)

Lavelli, Manuela; Fogel, Alan

2013-01-01

A microgenetic research design with a multiple case study method and a combination of quantitative and qualitative analyses was used to investigate interdyad differences in real-time dynamics and developmental change processes in mother-infant face-to-face communication over the first 3 months of life. Weekly observations of 24 mother-infant dyads…

A Spatial Reference Grid for Real-Time Autonomous Underwater Modeling using 3-D Sonar

Energy Technology Data Exchange (ETDEWEB)

Auran, P.G.

1996-12-31

The offshore industry has recognized the need for intelligent underwater robotic vehicles. This doctoral thesis deals with autonomous underwater vehicles (AUVs) and concentrates on a data representation for real-time image formation and analysis. Its main objective is to develop a 3-D image representation suitable for autonomous perception objectives underwater, assuming active sonar as the main sensor for perception. The main contributions are: (1) A dynamical image representation for 3-D range data, (2) A basic electronic circuit and software system for 3-D sonar sampling and amplitude thresholding, (3) A model for target reliability, (4) An efficient connected components algorithm for 3-D segmentation, (5) A method for extracting general 3-D geometrical representations from segmented echo clusters, (6) Experimental results of planar and curved target modeling. 142 refs., 120 figs., 10 tabs.

Real-time dynamic coupling of GPC-enhanced diffraction-limited focal spots

Science.gov (United States)

Villangca, Mark; Bañas, Andrew; Kopylov, Oleksii; Palima, Darwin; Glückstad, Jesper

2015-03-01

We have previously demonstrated on-demand dynamic coupling of an optically manipulated wave-guided optical waveguide (WOW) using diffractive techniques on a "point and shoot" approach. In this work, the generation of the coupling focal spots is done in real-time following the position of the WOW. Object-tracking routine has been added in the trapping program to get the position of the WOW. This approach allows continuous coupling of light through the WOWs which may be useful in some application. In addition, we include a GPC light shaper module in the holography setup to efficiently illuminate the spatial light modulator (SLM). The ability to switch from on-demand to continuous addressing with efficient illumination leverages our WOWs for potential applications in stimulation and nonlinear optics.

Real-time Dynamic Coupling of GPC-enhanced Diffraction-limited Focal Spots

DEFF Research Database (Denmark)

Villangca, Mark Jayson; Bañas, Andrew Rafael; Kopylov, Oleksii

2015-01-01

We have previously demonstrated on-demand dynamic coupling of an optically manipulated wave-guided optical waveguide (WOW) using diffractive techniques on a “point and shoot” approach. In this work, the generation of the coupling focal spots is done in real-time following the position of the WOW....... Object-tracking routine has been added in the trapping program to get the position of the WOW. This approach allows continuous coupling of light through the WOWs which may be useful in some application. In addition, we include a GPC light shaper module in the holography setup to efficiently illuminate...... the spatial light modulator (SLM). The ability to switch from on-demand to continuous addressing with efficient illumination leverages our WOWs for potential applications in stimulation and nonlinear optics....

Dynamic thermal signature prediction for real-time scene generation

Science.gov (United States)

Christie, Chad L.; Gouthas, Efthimios (Themie); Williams, Owen M.; Swierkowski, Leszek

2013-05-01

At DSTO, a real-time scene generation framework, VIRSuite, has been developed in recent years, within which trials data are predominantly used for modelling the radiometric properties of the simulated objects. Since in many cases the data are insufficient, a physics-based simulator capable of predicting the infrared signatures of objects and their backgrounds has been developed as a new VIRSuite module. It includes transient heat conduction within the materials, and boundary conditions that take into account the heat fluxes due to solar radiation, wind convection and radiative transfer. In this paper, an overview is presented, covering both the steady-state and transient performance.

Real-Time Simulation Technique of a Microgrid Model for DER Penetration

Directory of Open Access Journals (Sweden)

Konstantina Mentesidi

2014-12-01

Full Text Available Comprehensive analysis of Distributed Energy Resources (DER integration requires tools that provide computational power and flexibility. In this context, throughout this paper PHIL simulations are performed to emulate the energy management system of a real microgrid including a diesel synchronous machine and inverter-based sources. Moreover, conventional frequency and voltage droops were incorporated into the respective inverters. The results were verified at the real microgrid installation in the Centre for Renewable Energy Sources (CRES premises. This research work is divided into two steps: A Real time in RSCAD/RTDS and Power Hardware-in-the-Loop (PHIL simulations where the diesel generator´s active power droop control is evaluated, the battery inverter´s droop curves are simulated and the load sharing for parallel operation of the system´s generation units is examined. B microgrid experiments during which various tests were executed concerning the diesel generator and the battery inverters in order to examine their dynamic operation within the LV islanded power system.

Internal models of target motion: expected dynamics overrides measured kinematics in timing manual interceptions.

Science.gov (United States)

Zago, Myrka; Bosco, Gianfranco; Maffei, Vincenzo; Iosa, Marco; Ivanenko, Yuri P; Lacquaniti, Francesco

2004-04-01

Prevailing views on how we time the interception of a moving object assume that the visual inputs are informationally sufficient to estimate the time-to-contact from the object's kinematics. Here we present evidence in favor of a different view: the brain makes the best estimate about target motion based on measured kinematics and an a priori guess about the causes of motion. According to this theory, a predictive model is used to extrapolate time-to-contact from expected dynamics (kinetics). We projected a virtual target moving vertically downward on a wide screen with different randomized laws of motion. In the first series of experiments, subjects were asked to intercept this target by punching a real ball that fell hidden behind the screen and arrived in synchrony with the visual target. Subjects systematically timed their motor responses consistent with the assumption of gravity effects on an object's mass, even when the visual target did not accelerate. With training, the gravity model was not switched off but adapted to nonaccelerating targets by shifting the time of motor activation. In the second series of experiments, there was no real ball falling behind the screen. Instead the subjects were required to intercept the visual target by clicking a mousebutton. In this case, subjects timed their responses consistent with the assumption of uniform motion in the absence of forces, even when the target actually accelerated. Overall, the results are in accord with the theory that motor responses evoked by visual kinematics are modulated by a prior of the target dynamics. The prior appears surprisingly resistant to modifications based on performance errors.

3D Display of Spacecraft Dynamics Using Real Telemetry

Directory of Open Access Journals (Sweden)

Sanguk Lee

2002-12-01

Full Text Available 3D display of spacecraft motion by using telemetry data received from satellite in real-time is described. Telemetry data are converted to the appropriate form for 3-D display by the real-time preprocessor. Stored playback telemetry data also can be processed for the display. 3D display of spacecraft motion by using real telemetry data provides intuitive comprehension of spacecraft dynamics.

Reduced computational cost in the calculation of worst case response time for real time systems

OpenAIRE

Urriza, José M.; Schorb, Lucas; Orozco, Javier D.; Cayssials, Ricardo

2009-01-01

Modern Real Time Operating Systems require reducing computational costs even though the microprocessors become more powerful each day. It is usual that Real Time Operating Systems for embedded systems have advance features to administrate the resources of the applications that they support. In order to guarantee either the schedulability of the system or the schedulability of a new task in a dynamic Real Time System, it is necessary to know the Worst Case Response Time of the Real Time tasks ...

Real-time simulation of large-scale floods

Science.gov (United States)

Liu, Q.; Qin, Y.; Li, G. D.; Liu, Z.; Cheng, D. J.; Zhao, Y. H.

2016-08-01

According to the complex real-time water situation, the real-time simulation of large-scale floods is very important for flood prevention practice. Model robustness and running efficiency are two critical factors in successful real-time flood simulation. This paper proposed a robust, two-dimensional, shallow water model based on the unstructured Godunov- type finite volume method. A robust wet/dry front method is used to enhance the numerical stability. An adaptive method is proposed to improve the running efficiency. The proposed model is used for large-scale flood simulation on real topography. Results compared to those of MIKE21 show the strong performance of the proposed model.

Nonlinear dynamic interrelationships between real activity and stock returns

DEFF Research Database (Denmark)

Lanne, Markku; Nyberg, Henri

We explore the differences between the causal and noncausal vector autoregressive (VAR) models in capturing the real activity-stock return-relationship. Unlike the conventional linear VAR model, the noncausal VAR model is capable of accommodating various nonlinear characteristics of the data....... In quarterly U.S. data, we find strong evidence in favor of noncausality, and the best causal and noncausal VAR models imply quite different dynamics. In particular, the linear VAR model appears to underestimate the importance of the stock return shock for the real activity, and the real activity shock...

Optimal dynamic voltage scaling for wireless sensor nodes with real-time constraints

Science.gov (United States)

Cassandras, Christos G.; Zhuang, Shixin

2005-11-01

Sensors are increasingly embedded in manufacturing systems and wirelessly networked to monitor and manage operations ranging from process and inventory control to tracking equipment and even post-manufacturing product monitoring. In building such sensor networks, a critical issue is the limited and hard to replenish energy in the devices involved. Dynamic voltage scaling is a technique that controls the operating voltage of a processor to provide desired performance while conserving energy and prolonging the overall network's lifetime. We consider such power-limited devices processing time-critical tasks which are non-preemptive, aperiodic and have uncertain arrival times. We treat voltage scaling as a dynamic optimization problem whose objective is to minimize energy consumption subject to hard or soft real-time execution constraints. In the case of hard constraints, we build on prior work (which engages a voltage scaling controller at task completion times) by developing an intra-task controller that acts at all arrival times of incoming tasks. We show that this optimization problem can be decomposed into two simpler ones whose solution leads to an algorithm that does not actually require solving any nonlinear programming problems. In the case of soft constraints, this decomposition must be partly relaxed, but it still leads to a scalable (linear in the number of tasks) algorithm. Simulation results are provided to illustrate performance improvements in systems with intra-task controllers compared to uncontrolled systems or those using inter-task control.

Spatiotemporal Segmentation and Modeling of the Mitral Valve in Real-Time 3D Echocardiographic Images.

Science.gov (United States)

Pouch, Alison M; Aly, Ahmed H; Lai, Eric K; Yushkevich, Natalie; Stoffers, Rutger H; Gorman, Joseph H; Cheung, Albert T; Gorman, Joseph H; Gorman, Robert C; Yushkevich, Paul A

2017-09-01

Transesophageal echocardiography is the primary imaging modality for preoperative assessment of mitral valves with ischemic mitral regurgitation (IMR). While there are well known echocardiographic insights into the 3D morphology of mitral valves with IMR, such as annular dilation and leaflet tethering, less is understood about how quantification of valve dynamics can inform surgical treatment of IMR or predict short-term recurrence of the disease. As a step towards filling this knowledge gap, we present a novel framework for 4D segmentation and geometric modeling of the mitral valve in real-time 3D echocardiography (rt-3DE). The framework integrates multi-atlas label fusion and template-based medial modeling to generate quantitatively descriptive models of valve dynamics. The novelty of this work is that temporal consistency in the rt-3DE segmentations is enforced during both the segmentation and modeling stages with the use of groupwise label fusion and Kalman filtering. The algorithm is evaluated on rt-3DE data series from 10 patients: five with normal mitral valve morphology and five with severe IMR. In these 10 data series that total 207 individual 3DE images, each 3DE segmentation is validated against manual tracing and temporal consistency between segmentations is demonstrated. The ultimate goal is to generate accurate and consistent representations of valve dynamics that can both visually and quantitatively provide insight into normal and pathological valve function.

Absorption dynamics and delay time in complex potentials

Science.gov (United States)

Villavicencio, Jorge; Romo, Roberto; Hernández-Maldonado, Alberto

2018-05-01

The dynamics of absorption is analyzed by using an exactly solvable model that deals with an analytical solution to Schrödinger’s equation for cutoff initial plane waves incident on a complex absorbing potential. A dynamical absorption coefficient which allows us to explore the dynamical loss of particles from the transient to the stationary regime is derived. We find that the absorption process is characterized by the emission of a series of damped periodic pulses in time domain, associated with damped Rabi-type oscillations with a characteristic frequency, ω = (E + ε)/ℏ, where E is the energy of the incident waves and ‑ε is energy of the quasidiscrete state of the system induced by the absorptive part of the Hamiltonian; the width γ of this resonance governs the amplitude of the pulses. The resemblance of the time-dependent absorption coefficient with a real decay process is discussed, in particular the transition from exponential to nonexponential regimes, a well-known feature of quantum decay. We have also analyzed the effect of the absorptive part of the potential on the dynamical delay time, which behaves differently from the one observed in attractive real delta potentials, exhibiting two regimes: time advance and time delay.

Real-time modelling and simulation of an active power filter

Energy Technology Data Exchange (ETDEWEB)

Beaulieu, S.; Ouhrouche, M. [Quebec Univ., Chicoutimi, PQ (Canada); Dufour, C.; Allaire, P.F. [Opal RT Technologies Inc., Montreal, PQ (Canada)

2007-07-01

Power electronics converters generate harmonics and cause electromagnetic compatibility problems. Active power filter (APF) technology has advanced to the point that it can compensate for harmonics in electrical networks and provide reactive power and neutral current in AC networks. This paper presented a contribution in the design of a shunt APF for harmonics compensation in real-time simulation using the RT-LAB software package running on a simple personal computer. Real-time simulations were performed to validate the effectiveness of the proposed model. Several high-tech industries have adopted this tool for rapid control prototyping and for Hardware-in-the-Loop applications. The switching signals of the APF are determined by the hysteresis band current controller. The suitable current reference signals were determined by the algorithm based on synchronous reference frame. Real-time simulation runs showed good performance in harmonics compensation, thus satisfying the requirements of IEEE Standard 519-1992. The rate of total harmonic distortion for the source current decreased from 30 to 5 per cent. 12 refs., 1 tab., 9 figs.

Real-time detection of musical onsets with linear prediction and sinusoidal modeling

Science.gov (United States)

Glover, John; Lazzarini, Victor; Timoney, Joseph

2011-12-01

Real-time musical note onset detection plays a vital role in many audio analysis processes, such as score following, beat detection and various sound synthesis by analysis methods. This article provides a review of some of the most commonly used techniques for real-time onset detection. We suggest ways to improve these techniques by incorporating linear prediction as well as presenting a novel algorithm for real-time onset detection using sinusoidal modelling. We provide comprehensive results for both the detection accuracy and the computational performance of all of the described techniques, evaluated using Modal, our new open source library for musical onset detection, which comes with a free database of samples with hand-labelled note onsets.

Integrative real-time geographic visualization of energy resources

International Nuclear Information System (INIS)

Sorokine, A.; Shankar, M.; Stovall, J.; Bhaduri, B.; King, T.; Fernandez, S.; Datar, N.; Omitaomu, O.

2009-01-01

'Full text:' Several models forecast that climatic changes will increase the frequency of disastrous events like droughts, hurricanes, and snow storms. Responding to these events and also to power outages caused by system errors such as the 2003 North American blackout require an interconnect-wide real-time monitoring system for various energy resources. Such a system should be capable of providing situational awareness to its users in the government and energy utilities by dynamically visualizing the status of the elements of the energy grid infrastructure and supply chain in geographic contexts. We demonstrate an approach that relies on Google Earth and similar standard-based platforms as client-side geographic viewers with a data-dependent server component. The users of the system can view status information in spatial and temporal contexts. These data can be integrated with a wide range of geographic sources including all standard Google Earth layers and a large number of energy and environmental data feeds. In addition, we show a real-time spatio-temporal data sharing capability across the users of the system, novel methods for visualizing dynamic network data, and a fine-grain access to very large multi-resolution geographic datasets for faster delivery of the data. The system can be extended to integrate contingency analysis results and other grid models to assess recovery and repair scenarios in the case of major disruption. (author)

A real-time PUFF-model for accidental releases in complex terrain

International Nuclear Information System (INIS)

Thykier-Nielsen, S.; Mikkelsen, T.; Larsen, S.E.; Troen, I.; Baas, A.F. de; Kamada, R.; Skupniewicz, C.; Schacher, G.

1990-01-01

LINCOM-RIMPUFF, a combined flow/puff model, was developed at Riso National Laboratory for the Vandenberg AFB Meteorology and Plume Dispersion Handbook and is suitable as is for real time response to emergency spills and vents of gases and radionuclides. LINCOM is a linear, diagnostic, spectral, potential flow model which extends the Jackson-Hunt theory of non-hydrostatic, adiabatic wind flow over hills to the mesoscale domain. It is embedded in a weighted objective analysis (WOA) of real-time Vandenberg tower winds and may be used in ultra-high speed lookup table mode. The mesoscale dispersion model RIMPUFF is a flexible Gaussian puff model equipped with computer-time effective features for terrain and stability-dependent dispersion parameterization, plume rise formulas, inversion and ground-level reflection capabilities and wet/dry (source) depletion. It can treat plume bifurcation in complex terrain by using a puff-splitting scheme. It allows the flow-model to compute the larger scale wind field, reserving turbulent diffusion calculations for the sub-grid scale. In diagnostic mode toxic exposure are well assessed via the release of a single initial puff. With optimization, processing time for RIMPUFF should be on the order of 2 CPU minutes or less on a PC-system. In prognostic mode with shifting winds, multiple puff releases may become necessary, thereby lengthening processing time

Real-time monitoring of capacity loss for vanadium redox flow battery

Science.gov (United States)

Wei, Zhongbao; Bhattarai, Arjun; Zou, Changfu; Meng, Shujuan; Lim, Tuti Mariana; Skyllas-Kazacos, Maria

2018-06-01

The long-term operation of the vanadium redox flow battery is accompanied by ion diffusion across the separator and side reactions, which can lead to electrolyte imbalance and capacity loss. The accurate online monitoring of capacity loss is therefore valuable for the reliable and efficient operation of vanadium redox flow battery system. In this paper, a model-based online monitoring method is proposed to detect capacity loss in the vanadium redox flow battery in real time. A first-order equivalent circuit model is built to capture the dynamics of the vanadium redox flow battery. The model parameters are online identified from the onboard measureable signals with the recursive least squares, in seeking to keep a high modeling accuracy and robustness under a wide range of working scenarios. Based on the online adapted model, an observer is designed with the extended Kalman Filter to keep tracking both the capacity and state of charge of the battery in real time. Experiments are conducted on a lab-scale battery system. Results suggest that the online adapted model is able to simulate the battery behavior with high accuracy. The capacity loss as well as the state of charge can be estimated accurately in a real-time manner.

Model of Coupled Drives Apparatus – Static and Dynamic Characteristics

Directory of Open Access Journals (Sweden)

Chalupa Petr

2016-01-01

Full Text Available The paper presents an initial part of a modelling the Coupled Drives Apparatus CE108 developed by TecQuipment Ltd. The final model should be used in the process of control design for the apparatus. The model derived by the developers of the apparatus using first-principle modelling is used as a starting point for comparison of its properties with measured characteristics. The static and dynamic characteristics of the real-time apparatus are presented and discussed. Special attention is paid to principal differences between the model and the real-time apparatus. Real-time measurements are obtained using MATLAB / Simulink environment in connection with a Real-time Toolbox. Evaluation of the experiments is also performed in the MATLAB environment

Computational model for real-time determination of tritium inventory in a detritiation installation

International Nuclear Information System (INIS)

Bornea, Anisia; Stefanescu, Ioan; Zamfirache, Marius; Stefan, Iuliana; Sofalca, Nicolae; Bidica, Nicolae

2008-01-01

Full text: At ICIT Rm.Valcea an experimental pilot plant was built having as main objective the development of a technology for detritiation of heavy water processed in the CANDU-type reactors of the nuclear power plant at Cernavoda, Romania. The aspects related to safeguards and safety for such a detritiation installation being of great importance, a complex computational model has been developed. The model allows real-time calculation of tritium inventory in a working installation. The applied detritiation technology is catalyzed isotopic exchange coupled with cryogenic distillation. Computational models for non-steady working conditions have been developed for each process of isotopic exchange. By coupling these processes tritium inventory can be determined in real-time. The computational model was developed based on the experience gained on the pilot installation. The model uses a set of parameters specific to isotopic exchange processes. These parameters were experimentally determined in the pilot installation. The model is included in the monitoring system and uses as input data the parameters acquired in real-time from automation system of the pilot installation. A friendly interface has been created to visualize the final results as data or graphs. (authors)

Real-time video quality monitoring

Science.gov (United States)

Liu, Tao; Narvekar, Niranjan; Wang, Beibei; Ding, Ran; Zou, Dekun; Cash, Glenn; Bhagavathy, Sitaram; Bloom, Jeffrey

2011-12-01

The ITU-T Recommendation G.1070 is a standardized opinion model for video telephony applications that uses video bitrate, frame rate, and packet-loss rate to measure the video quality. However, this model was original designed as an offline quality planning tool. It cannot be directly used for quality monitoring since the above three input parameters are not readily available within a network or at the decoder. And there is a great room for the performance improvement of this quality metric. In this article, we present a real-time video quality monitoring solution based on this Recommendation. We first propose a scheme to efficiently estimate the three parameters from video bitstreams, so that it can be used as a real-time video quality monitoring tool. Furthermore, an enhanced algorithm based on the G.1070 model that provides more accurate quality prediction is proposed. Finally, to use this metric in real-world applications, we present an example emerging application of real-time quality measurement to the management of transmitted videos, especially those delivered to mobile devices.

Analyzing Oil Futures with a Dynamic Nelson-Siegel Model

DEFF Research Database (Denmark)

Hansen, Niels Strange; Lunde, Asger

In this paper we are interested in the term structure of futures contracts on oil. The objective is to specify a relatively parsimonious model which explains data well and performs well in a real time out of sample forecasting. The dynamic Nelson-Siegel model is normally used to analyze and forec......In this paper we are interested in the term structure of futures contracts on oil. The objective is to specify a relatively parsimonious model which explains data well and performs well in a real time out of sample forecasting. The dynamic Nelson-Siegel model is normally used to analyze...... and forecast interest rates of different maturities. The structure of oil futures resembles the structure of interest rates and this motivates the use of this model for our purposes. The data set is vast and the dynamic Nelson-Siegel model allows for a significant dimension reduction by introducing three...

Real-Time Station Grouping under Dynamic Traffic for IEEE 802.11ah.

Science.gov (United States)

Tian, Le; Khorov, Evgeny; Latré, Steven; Famaey, Jeroen

2017-07-04

RAW grouping under dynamic traffic in real time, which is a major leap towards applying RAW mechanism in real-life IoT networks.

Dynamical analysis of an n‑H‑T cosmological quintessence real gas model with a general equation of state

Science.gov (United States)

Ivanov, Rossen I.; Prodanov, Emil M.

2018-01-01

The cosmological dynamics of a quintessence model based on real gas with general equation of state is presented within the framework of a three-dimensional dynamical system describing the time evolution of the number density, the Hubble parameter and the temperature. Two global first integrals are found and examples for gas with virial expansion and van der Waals gas are presented. The van der Waals system is completely integrable. In addition to the unbounded trajectories, stemming from the presence of the conserved quantities, stable periodic solutions (closed orbits) also exist under certain conditions and these represent models of a cyclic Universe. The cyclic solutions exhibit regions characterized by inflation and deflation, while the open trajectories are characterized by inflation in a “fly-by” near an unstable critical point.

Modeling of requirement specification for safety critical real time computer system using formal mathematical specifications

International Nuclear Information System (INIS)

Sankar, Bindu; Sasidhar Rao, B.; Ilango Sambasivam, S.; Swaminathan, P.

2002-01-01

Full text: Real time computer systems are increasingly used for safety critical supervision and control of nuclear reactors. Typical application areas are supervision of reactor core against coolant flow blockage, supervision of clad hot spot, supervision of undesirable power excursion, power control and control logic for fuel handling systems. The most frequent cause of fault in safety critical real time computer system is traced to fuzziness in requirement specification. To ensure the specified safety, it is necessary to model the requirement specification of safety critical real time computer systems using formal mathematical methods. Modeling eliminates the fuzziness in the requirement specification and also helps to prepare the verification and validation schemes. Test data can be easily designed from the model of the requirement specification. Z and B are the popular languages used for modeling the requirement specification. A typical safety critical real time computer system for supervising the reactor core of prototype fast breeder reactor (PFBR) against flow blockage is taken as case study. Modeling techniques and the actual model are explained in detail. The advantages of modeling for ensuring the safety are summarized

Real and financial market interactions in a multiplier-accelerator model: Nonlinear dynamics, multistability and stylized facts

Science.gov (United States)

Cavalli, F.; Naimzada, A.; Pecora, N.

2017-10-01

In the present paper, we investigate the dynamics of a model in which the real part of the economy, described within a multiplier-accelerator framework, interacts with a financial market with heterogeneous speculators, in order to study the channels through which the two sectors influence each other. Employing analytical and numerical tools, we investigate stability conditions as well as bifurcations and possible periodic, quasi-periodic, and chaotic dynamics, enlightening how the degree of market interaction, together with the accelerator parameter and the intervention of the fiscal authority, may affect the business cycle and the course of the financial market. In particular, we show that even if the steady state is locally stable, multistability phenomena can occur, with several and complex dynamic structures coexisting with the steady state. Finally, simulations reveal that the proposed model is able to explain several statistical properties and stylized facts observed in real financial markets, including persistent high volatility, fat-tailed return distributions, volatility clustering, and positive autocorrelation of absolute returns.

Real-Time Dynamics in the (1+1)-D Abelian Higgs Model with Fermions

NARCIS (Netherlands)

Aarts, G.; Smit, J.

2000-01-01

In approximate dynamical equations, inhomogenous classical (mean) gauge and Higgs fields are coupled to quantized fermions. The equations are solved numerically on a spacetime lattice. The fermions appear to equilibrate according to the Fermi-Dirac distribution with time-dependent temperature and

Real-time expert systems and deep knowledge models

International Nuclear Information System (INIS)

Felkel, L.

1990-01-01

To guide operators in normal and disturbed plant conditions expert systems are feasible. These, however, must be on-line and real-time systems. The knowledge contained in such a system cannot be represented in a 'classical' role-based manner. The paper describes problems and solutions with regard to process reference models as these are important in order to provide so-called deep-knowledge for the operators. The system described is being implemented and is meant to support both diagnosis and prediction

Real-time monitoring of a microbial electrolysis cell using an electrical equivalent circuit model.

Science.gov (United States)

Hussain, S A; Perrier, M; Tartakovsky, B

2018-04-01

Efforts in developing microbial electrolysis cells (MECs) resulted in several novel approaches for wastewater treatment and bioelectrosynthesis. Practical implementation of these approaches necessitates the development of an adequate system for real-time (on-line) monitoring and diagnostics of MEC performance. This study describes a simple MEC equivalent electrical circuit (EEC) model and a parameter estimation procedure, which enable such real-time monitoring. The proposed approach involves MEC voltage and current measurements during its operation with periodic power supply connection/disconnection (on/off operation) followed by parameter estimation using either numerical or analytical solution of the model. The proposed monitoring approach is demonstrated using a membraneless MEC with flow-through porous electrodes. Laboratory tests showed that changes in the influent carbon source concentration and composition significantly affect MEC total internal resistance and capacitance estimated by the model. Fast response of these EEC model parameters to changes in operating conditions enables the development of a model-based approach for real-time monitoring and fault detection.

CHIMERA II - A real-time multiprocessing environment for sensor-based robot control

Science.gov (United States)

Stewart, David B.; Schmitz, Donald E.; Khosla, Pradeep K.

1989-01-01

A multiprocessing environment for a wide variety of sensor-based robot system, providing the flexibility, performance, and UNIX-compatible interface needed for fast development of real-time code is addressed. The requirements imposed on the design of a programming environment for sensor-based robotic control is outlined. The details of the current hardware configuration are presented, along with the details of the CHIMERA II software. Emphasis is placed on the kernel, low-level interboard communication, user interface, extended file system, user-definable and dynamically selectable real-time schedulers, remote process synchronization, and generalized interprocess communication. A possible implementation of a hierarchical control model, the NASA/NBS standard reference model for telerobot control system is demonstrated.

Verifying real-time systems against scenario-based requirements

DEFF Research Database (Denmark)

Larsen, Kim Guldstrand; Li, Shuhao; Nielsen, Brian

2009-01-01

We propose an approach to automatic verification of real-time systems against scenario-based requirements. A real-time system is modeled as a network of Timed Automata (TA), and a scenario-based requirement is specified as a Live Sequence Chart (LSC). We define a trace-based semantics for a kernel...... subset of the LSC language. By equivalently translating an LSC chart into an observer TA and then non-intrusively composing this observer with the original system model, the problem of verifying a real-time system against a scenario-based requirement reduces to a classical real-time model checking...

Temporal Specification and Verification of Real-Time Systems.

Science.gov (United States)

1991-08-30

of concrete real - time systems can be modeled adequately. Specification: We present two conservative extensions of temporal logic that allow for the...logic. We present both model-checking algorithms for the automatic verification of finite-state real - time systems and proof methods for the deductive verification of real - time systems .

Games and Scenarios for Real-Time System Validation

DEFF Research Database (Denmark)

Li, Shuhao

This thesis presents research on the validation of real-time embedded software systems in the context of model-based development. The thesis proposes scenario-based and game-theoretic approaches to system analysis, verification, synthesis and testing to address the challenges that arise from....... By linking our prototype translators with existing model checker Uppaal and game solver Uppaal-Tiga, we show that these methods contribute to the interaction correctness and timeliness of early system designs. The thesis also shows that testing a real-time reactive system can be viewed as playing a timed...... communicating real-time systems can be modeled and specified with LSC. By translating LSC to timed automata (TAs), we reduce scenario-based model consistency checking and property verification to CTL real-time model checking problems, and reduce scenario-based synthesis to a timed game solving problem...

EcoPAD, an interactive platform for near real-time ecological forecasting by assimilating data into model

Science.gov (United States)

MA, S.; Huang, Y.; Stacy, M.; Jiang, J.; Sundi, N.; Ricciuto, D. M.; Hanson, P. J.; Luo, Y.; Saruta, V.

2017-12-01

Ecological forecasting is critical in various aspects of our coupled human-nature systems, such as disaster risk reduction, natural resource management and climate change mitigation. Novel advancements are in urgent need to deepen our understandings of ecosystem dynamics, boost the predictive capacity of ecology, and provide timely and effective information for decision-makers in a rapidly changing world. Our study presents a smart system - Ecological Platform for Assimilation of Data (EcoPAD) - which streamlines web request-response, data management, model execution, result storage and visualization. EcoPAD allows users to (i) estimate model parameters or state variables, (ii) quantify uncertainty of estimated parameters and projected states of ecosystems, (iii) evaluate model structures, (iv) assess sampling strategies, (v) conduct ecological forecasting, and (vi) detect ecosystem acclimation to climate change. One of the key innovations of the web-based EcoPAD is the automated near- or real-time forecasting of ecosystem dynamics with uncertainty fully quantified. The user friendly webpage enables non-modelers to explore their data for simulation and data assimilation. As a case study, we applied EcoPAD to the Spruce and Peatland Responses Under Climatic and Environmental Change Experiment (SPRUCE), a whole ecosystem warming and CO2 enrichment treatment project in the northern peatland, assimilated multiple data streams into a process based ecosystem model, enhanced timely feedback between modelers and experimenters, ultimately improved ecosystem forecasting and made better use of current knowledge. Built in a framework with flexible API, EcoPAD is easily portable and will benefit scientific communities, policy makers as well as the general public.

Bayesian dynamic modeling of time series of dengue disease case counts.

Science.gov (United States)

Martínez-Bello, Daniel Adyro; López-Quílez, Antonio; Torres-Prieto, Alexander

2017-07-01

The aim of this study is to model the association between weekly time series of dengue case counts and meteorological variables, in a high-incidence city of Colombia, applying Bayesian hierarchical dynamic generalized linear models over the period January 2008 to August 2015. Additionally, we evaluate the model's short-term performance for predicting dengue cases. The methodology shows dynamic Poisson log link models including constant or time-varying coefficients for the meteorological variables. Calendar effects were modeled using constant or first- or second-order random walk time-varying coefficients. The meteorological variables were modeled using constant coefficients and first-order random walk time-varying coefficients. We applied Markov Chain Monte Carlo simulations for parameter estimation, and deviance information criterion statistic (DIC) for model selection. We assessed the short-term predictive performance of the selected final model, at several time points within the study period using the mean absolute percentage error. The results showed the best model including first-order random walk time-varying coefficients for calendar trend and first-order random walk time-varying coefficients for the meteorological variables. Besides the computational challenges, interpreting the results implies a complete analysis of the time series of dengue with respect to the parameter estimates of the meteorological effects. We found small values of the mean absolute percentage errors at one or two weeks out-of-sample predictions for most prediction points, associated with low volatility periods in the dengue counts. We discuss the advantages and limitations of the dynamic Poisson models for studying the association between time series of dengue disease and meteorological variables. The key conclusion of the study is that dynamic Poisson models account for the dynamic nature of the variables involved in the modeling of time series of dengue disease, producing useful

[Dynamic road vehicle emission inventory simulation study based on real time traffic information].

Science.gov (United States)

Huang, Cheng; Liu, Juan; Chen, Chang-Hong; Zhang, Jian; Liu, Deng-Guo; Zhu, Jing-Yu; Huang, Wei-Ming; Chao, Yuan

2012-11-01

The vehicle activity survey, including traffic flow distribution, driving condition, and vehicle technologies, were conducted in Shanghai. The databases of vehicle flow, VSP distribution and vehicle categories were established according to the surveyed data. Based on this, a dynamic vehicle emission inventory simulation method was designed by using the real time traffic information data, such as traffic flow and average speed. Some roads in Shanghai city were selected to conduct the hourly vehicle emission simulation as a case study. The survey results show that light duty passenger car and taxi are major vehicles on the roads of Shanghai city, accounting for 48% - 72% and 15% - 43% of the total flow in each hour, respectively. VSP distribution has a good relationship with the average speed. The peak of VSP distribution tends to move to high load section and become lower with the increase of average speed. Vehicles achieved Euro 2 and Euro 3 standards are majorities of current vehicle population in Shanghai. Based on the calibration of vehicle travel mileage data, the proportions of Euro 2 and Euro 3 standard vehicles take up 11% - 70% and 17% - 51% in the real-world situation, respectively. The emission simulation results indicate that the ratios of emission peak and valley for the pollutants of CO, VOC, NO(x) and PM are 3.7, 4.6, 9.6 and 19.8, respectively. CO and VOC emissions mainly come from light-duty passenger car and taxi, which has a good relationship with the traffic flow. NO(x) and PM emissions are mainly from heavy-duty bus and public buses and mainly concentrate in the morning and evening peak hours. The established dynamic vehicle emission simulation method can reflect the change of actual road emission and output high emission road sectors and hours in real time. The method can provide an important technical means and decision-making basis for transportation environment management.

WE-G-18C-08: Real Time Tumor Imaging Using a Novel Dynamic Keyhole MRI Reconstruction Technique

International Nuclear Information System (INIS)

Lee, D; Pollock, S; Whelan, B; Keall, P; Greer, P; Kim, T

2014-01-01

Purpose: To test the hypothesis that the novel Dynamic Keyhole MRI reconstruction technique can accelerate image acquisition whilst maintaining high image quality for lung cancer patients. Methods: 18 MRI datasets from 5 lung cancer patients were acquired using a 3T MRI scanner. These datasets were retrospectively reconstructed using (A) The novel Dynamic Keyhole technique, (B) The conventional keyhole technique and (C) the conventional zero filling technique. The dynamic keyhole technique in MRI refers to techniques in which previously acquired k-space data is used to supplement under sampled data obtained in real time. The novel Dynamic Keyhole technique utilizes a previously acquired a library of kspace datasets in conjunction with central k-space datasets acquired in realtime. A simultaneously acquired respiratory signal is utilized to sort, match and combine the two k-space streams with respect to respiratory displacement. Reconstruction performance was quantified by (1) comparing the keyhole size (which corresponds to imaging speed) required to achieve the same image quality, and (2) maintaining a constant keyhole size across the three reconstruction methods to compare the resulting image quality to the ground truth image. Results: (1) The dynamic keyhole method required a mean keyhole size which was 48% smaller than the conventional keyhole technique and 60% smaller than the zero filling technique to achieve the same image quality. This directly corresponds to faster imaging. (2) When a constant keyhole size was utilized, the Dynamic Keyhole technique resulted in the smallest difference of the tumor region compared to the ground truth. Conclusion: The dynamic keyhole is a simple and adaptable technique for clinical applications requiring real-time imaging and tumor monitoring such as MRI guided radiotherapy. Based on the results from this study, the dynamic keyhole method could increase the imaging frequency by a factor of five compared with full k

Human Activity Recognition in Real-Times Environments using Skeleton Joints

Directory of Open Access Journals (Sweden)

Ajay Kumar

2016-06-01

Full Text Available In this research work, we proposed a most effective noble approach for Human activity recognition in real-time environments. We recognize several distinct dynamic human activity actions using kinect. A 3D skeleton data is processed from real-time video gesture to sequence of frames and getter skeleton joints (Energy Joints, orientation, rotations of joint angles from selected setof frames. We are using joint angle and orientations, rotations information from Kinect therefore less computation required. However, after extracting the set of frames we implemented several classification techniques Principal Component Analysis (PCA with several distance based classifiers and Artificial Neural Network (ANN respectively with some variants for classify our all different gesture models. However, we conclude that use very less number of frame (10-15% for train our system efficiently from the entire set of gesture frames. Moreover, after successfully completion of our classification methods we clinch an excellent overall accuracy 94%, 96% and 98% respectively. We finally observe that our proposed system is more useful than comparing to other existing system, therefore our model is best suitable for real-time application such as in video games for player action/gesture recognition.

A dynamical systems perspective for a real-time response to a marine oil spill.

Science.gov (United States)

García-Garrido, V J; Ramos, A; Mancho, A M; Coca, J; Wiggins, S

2016-11-15

This paper discusses the combined use of tools from dynamical systems theory and remote sensing techniques and shows how they are effective instruments which may greatly contribute to the decision making protocols of the emergency services for the real-time management of oil spills. This work presents the successful interplay of these techniques for a recent situation, the sinking of the Oleg Naydenov fishing ship that took place in Spain, close to the Canary Islands, in April 2015. Copyright © 2016. Published by Elsevier Ltd.

Analytical model for real time, noninvasive estimation of blood glucose level.

Science.gov (United States)

Adhyapak, Anoop; Sidley, Matthew; Venkataraman, Jayanti

2014-01-01

The paper presents an analytical model to estimate blood glucose level from measurements made non-invasively and in real time by an antenna strapped to a patient's wrist. Some promising success has been shown by the RIT ETA Lab research group that an antenna's resonant frequency can track, in real time, changes in glucose concentration. Based on an in-vitro study of blood samples of diabetic patients, the paper presents a modified Cole-Cole model that incorporates a factor to represent the change in glucose level. A calibration technique using the input impedance technique is discussed and the results show a good estimation as compared to the glucose meter readings. An alternate calibration methodology has been developed that is based on the shift in the antenna resonant frequency using an equivalent circuit model containing a shunt capacitor to represent the shift in resonant frequency with changing glucose levels. Work under progress is the optimization of the technique with a larger sample of patients.

Real Time Radioactivity Monitoring and its Interface with predictive atmospheric transport modelling

International Nuclear Information System (INIS)

Raes, F.

1990-01-01

After the Chernobyl accident, a programme was initiated at the Joint Research Centre of the Commission of the European Communities named 'Radioactivity Environmental Monitoring' (REM). The main aspects considered in REM are: data handling, atmospheric modelling and data quality control related to radioactivity in the environment. The first REM workshop was held in December 1987: 'Aerosol Measurements and Nuclear Accidents: A Reconsideration'. (CEC EUR 11755 EN). These are the proceedings of the second REM workshop, held in December 1989, dealing with real-time radioactivity monitoring and its interface with predictive atmospheric models. Atmospheric transport models, in applications extending over time scales of the order of a day or more become progressively less reliable to the extent that an interface with real-time radiological field data becomes highly desirable. Through international arrangements for early exchange of information in the event of a nuclear accident (European Community, IAEA) such data might become available on a quasi real-time basis. The question is how best to use such information to improve our predictive capabilities. During the workshop the present status of on-line monitoring networks for airborne radioactivity in the EC Member States has been reviewed. Possibilities were discussed to use data from such networks as soon as they become available, in order to update predictions made with long range transport models. This publication gives the full text of 13 presentations and a report of the Round Table Discussion held afterwards

Time-Optimal Real-Time Test Case Generation using UPPAAL

DEFF Research Database (Denmark)

Hessel, Anders; Larsen, Kim Guldstrand; Nielsen, Brian

2004-01-01

Testing is the primary software validation technique used by industry today, but remains ad hoc, error prone, and very expensive. A promising improvement is to automatically generate test cases from formal models of the system under test. We demonstrate how to automatically generate real...... test purposes or generated automatically from various coverage criteria of the model.......-time conformance test cases from timed automata specifications. Specifically we demonstrate how to fficiently generate real-time test cases with optimal execution time i.e test cases that are the fastest possible to execute. Our technique allows time optimal test cases to be generated using manually formulated...

System-level power optimization for real-time distributed embedded systems

Science.gov (United States)

Luo, Jiong

well. Variable-frequency links have been designed by circuit designers for both parallel and serial links, which can adaptively regulate the supply voltage of transceivers to a desired link frequency, to exploit the variations in bandwidth requirement for power savings. We propose solutions for simultaneous dynamic voltage scaling of processors and links. The proposed solution considers real-time scheduling, flow control, and packet routing jointly. It can trade off the power consumption on processors and communication links via efficient slack allocation, and lead to more power savings than dynamic voltage scaling on processors alone. For battery-operated systems, the battery lifespan is an important concern. Due to the effects of discharge rate and battery recovery, the discharge pattern of batteries has an impact on the battery lifespan. Battery models indicate that even under the same average power consumption, reducing peak power current and variance in the power profile can increase the battery efficiency and thereby prolong battery lifetime. To take advantage of these effects, we propose battery-driven scheduling techniques for embedded applications, to reduce the peak power and the variance in the power profile of the overall system under real-time constraints. The proposed scheduling algorithms are also beneficial in addressing reliability and signal integrity concerns by effectively controlling peak power and variance of the power profile.

VERSE - Virtual Equivalent Real-time Simulation

Science.gov (United States)

Zheng, Yang; Martin, Bryan J.; Villaume, Nathaniel

2005-01-01

Distributed real-time simulations provide important timing validation and hardware in the- loop results for the spacecraft flight software development cycle. Occasionally, the need for higher fidelity modeling and more comprehensive debugging capabilities - combined with a limited amount of computational resources - calls for a non real-time simulation environment that mimics the real-time environment. By creating a non real-time environment that accommodates simulations and flight software designed for a multi-CPU real-time system, we can save development time, cut mission costs, and reduce the likelihood of errors. This paper presents such a solution: Virtual Equivalent Real-time Simulation Environment (VERSE). VERSE turns the real-time operating system RTAI (Real-time Application Interface) into an event driven simulator that runs in virtual real time. Designed to keep the original RTAI architecture as intact as possible, and therefore inheriting RTAI's many capabilities, VERSE was implemented with remarkably little change to the RTAI source code. This small footprint together with use of the same API allows users to easily run the same application in both real-time and virtual time environments. VERSE has been used to build a workstation testbed for NASA's Space Interferometry Mission (SIM PlanetQuest) instrument flight software. With its flexible simulation controls and inexpensive setup and replication costs, VERSE will become an invaluable tool in future mission development.

Modeling Optical Spectra of Large Organic Systems Using Real-Time Propagation of Semiempirical Effective Hamiltonians.

Science.gov (United States)

Ghosh, Soumen; Andersen, Amity; Gagliardi, Laura; Cramer, Christopher J; Govind, Niranjan

2017-09-12

We present an implementation of a time-dependent semiempirical method (INDO/S) in NWChem using real-time (RT) propagation to address, in principle, the entire spectrum of valence electronic excitations. Adopting this model, we study the UV/vis spectra of medium-sized systems such as P3B2 and f-coronene, and in addition much larger systems such as ubiquitin in the gas phase and the betanin chromophore in the presence of two explicit solvents (water and methanol). RT-INDO/S provides qualitatively and often quantitatively accurate results when compared with RT- TDDFT or experimental spectra. Even though we only consider the INDO/S Hamiltonian in this work, our implementation provides a framework for performing electron dynamics in large systems using semiempirical Hartree-Fock Hamiltonians in general.

Nonequilibrium self-energy functional theory. Accessing the real-time dynamics of strongly correlated fermionic lattice systems

Energy Technology Data Exchange (ETDEWEB)

Hofmann, Felix

2016-07-05

The self-energy functional theory (SFT) is extended to the nonequilibrium case and applied to the real-time dynamics of strongly correlated lattice-fermions. Exploiting the basic structure of the well established equilibrium theory the entire formalism is reformulated in the language of Keldysh-Matsubara Green's functions. To this end, a functional of general nonequilibrium self-energies is constructed which is stationary at the physical point where it moreover yields the physical grand potential of the initial thermal state. Nonperturbative approximations to the full self-energy can be constructed by reducing the original lattice problem to smaller reference systems and varying the functional on the space of the respective trial self-energies, which are parametrized by the reference system's one-particle parameters. Approximations constructed in this way can be shown to respect the macroscopic conservation laws related to the underlying symmetries of the original lattice model. Assuming thermal equilibrium, the original SFT is recovered from the extended formalism. However, in the general case, the nonequilibrium variational principle comprises functional derivatives off the physical parameter space. These can be carried out analytically to derive inherently causal conditional equations for the optimal physical parameters of the reference system and a computationally realizable propagation scheme is set up. As a benchmark for the numerical implementation the variational cluster approach is applied to the dynamics of a dimerized Hubbard model after fast ramps of its hopping parameters. Finally, the time-evolution of a homogeneous Hubbard model after sudden quenches and ramps of the interaction parameter is studied by means of a dynamical impurity approximation with a single bath site. Sharply separated by a critical interaction at which fast relaxation to a thermal final state is observed, two differing response regimes can be distinguished, where the

Simulation model for transcervical laryngeal injection providing real-time feedback.

Science.gov (United States)

Ainsworth, Tiffiny A; Kobler, James B; Loan, Gregory J; Burns, James A

2014-12-01

This study aimed to develop and evaluate a model for teaching transcervical laryngeal injections. A 3-dimensional printer was used to create a laryngotracheal framework based on de-identified computed tomography images of a human larynx. The arytenoid cartilages and intrinsic laryngeal musculature were created in silicone from clay casts and thermoplastic molds. The thyroarytenoid (TA) muscle was created with electrically conductive silicone using metallic filaments embedded in silicone. Wires connected TA muscles to an electrical circuit incorporating a cell phone and speaker. A needle electrode completed the circuit when inserted in the TA during simulated injection, providing real-time feedback of successful needle placement by producing an audible sound. Face validation by the senior author confirmed appropriate tactile feedback and anatomical realism. Otolaryngologists pilot tested the model and completed presimulation and postsimulation questionnaires. The high-fidelity simulation model provided tactile and audio feedback during needle placement, simulating transcervical vocal fold injections. Otolaryngology residents demonstrated higher comfort levels with transcervical thyroarytenoid injection on postsimulation questionnaires. This is the first study to describe a simulator for developing transcervical vocal fold injection skills. The model provides real-time tactile and auditory feedback that aids in skill acquisition. Otolaryngologists reported increased confidence with transcervical injection after using the simulator. © The Author(s) 2014.

Prevention of oil spill from shipping by modelling of dynamic risk.

Science.gov (United States)

Eide, Magnus S; Endresen, Oyvind; Breivik, Oyvind; Brude, Odd Willy; Ellingsen, Ingrid H; Røang, Kjell; Hauge, Jarle; Brett, Per Olaf

2007-10-01

This paper presents a new dynamic environmental risk model, with intended use within a new, dynamical approach for risk based ship traffic prioritisation. The philosophy behind this newly developed approach is that shipping risk can be reduced by directing efforts towards ships and areas that have been identified as high priority (high risk), prior to a potential accident. The risk model proposed in this paper separates itself from previous models by drawing on available information on dynamic factors and by focusing on the ship's surroundings. The model estimates the environmental risk of drift grounding accidents for oil tankers in real time and in forecast mode, combining the probability of grounding with oil spill impact on the coastline. Results show that the inherent dynamic risk introduced by an oil tanker sailing along the North Norwegian coast depends, not surprisingly, significantly upon wind and ocean currents, as well as tug position and cargo oil type. Results of this study indicate that the risk model is well suited for real time risk assessment, and effectively separates low risk and high risk situations. The model is well suited as a tool to prioritise oil tankers and coastal segments. This enables dynamic risk based positioning of tugs, using both real-time and projected risk, for effective support in case of a drifting ship situation.

Real-time modelling of the diesel engine combustion process; Echtzeitfaehige Modellierung des dieselmotorischen Verbrennungsprozesses

Energy Technology Data Exchange (ETDEWEB)

Merz, B.

2008-07-01

The publication investigates single-zone models of diesel engine combustion which are capable, in addition to pre-injection and main injection, to represent post-injection processes on a physical basis. These must function in real time as they are used in ''hardware-in-the-loop'' test stands. Methods to adapt the models to other engine types are explained. Validation is made across the whole characteristic field on the basis of measured data provided by two serial engines. For assessing pollutant production, models are integrated that are capable of calculating NOx and soot formation. These, too, are calculated in real time using appropriate hardware systems. A runtime analysis compares the computing times of the models. (orig.)

Simple Models for the Dynamic Modeling of Rotating Tires

Directory of Open Access Journals (Sweden)

J.C. Delamotte

2008-01-01

Full Text Available Large Finite Element (FE models of tires are currently used to predict low frequency behavior and to obtain dynamic model coefficients used in multi-body models for riding and comfort. However, to predict higher frequency behavior, which may explain irregular wear, critical rotating speeds and noise radiation, FE models are not practical. Detailed FE models are not adequate for optimization and uncertainty predictions either, as in such applications the dynamic solution must be computed a number of times. Therefore, there is a need for simpler models that can capture the physics of the tire and be used to compute the dynamic response with a low computational cost. In this paper, the spectral (or continuous element approach is used to derive such a model. A circular beam spectral element that takes into account the string effect is derived, and a method to simulate the response to a rotating force is implemented in the frequency domain. The behavior of a circular ring under different internal pressures is investigated using modal and frequency/wavenumber representations. Experimental results obtained with a real untreaded truck tire are presented and qualitatively compared with the simple model predictions with good agreement. No attempt is made to obtain equivalent parameters for the simple model from the real tire results. On the other hand, the simple model fails to represent the correct variation of the quotient of the natural frequency by the number of circumferential wavelengths with the mode count. Nevertheless, some important features of the real tire dynamic behavior, such as the generation of standing waves and part of the frequency/wavenumber behavior, can be investigated using the proposed simplified model.

Multiobjective Traffic Signal Control Model for Intersection Based on Dynamic Turning Movements Estimation

Directory of Open Access Journals (Sweden)

Pengpeng Jiao

2014-01-01

Full Text Available The real-time traffic signal control for intersection requires dynamic turning movements as the basic input data. It is impossible to detect dynamic turning movements directly through current traffic surveillance systems, but dynamic origin-destination (O-D estimation can obtain it. However, the combined models of dynamic O-D estimation and real-time traffic signal control are rare in the literature. A framework for the multiobjective traffic signal control model for intersection based on dynamic O-D estimation (MSC-DODE is presented. A state-space model using Kalman filtering is first formulated to estimate the dynamic turning movements; then a revised sequential Kalman filtering algorithm is designed to solve the model, and the root mean square error and mean percentage error are used to evaluate the accuracy of estimated dynamic turning proportions. Furthermore, a multiobjective traffic signal control model is put forward to achieve real-time signal control parameters and evaluation indices. Finally, based on practical survey data, the evaluation indices from MSC-DODE are compared with those from Webster method. The actual and estimated turning movements are further input into MSC-DODE, respectively, and results are also compared. Case studies show that results of MSC-DODE are better than those of Webster method and are very close to unavailable actual values.

Three axis electronic flight motion simulator real time control system design and implementation.

Science.gov (United States)

Gao, Zhiyuan; Miao, Zhonghua; Wang, Xuyong; Wang, Xiaohua

2014-12-01

A three axis electronic flight motion simulator is reported in this paper including the modelling, the controller design as well as the hardware implementation. This flight motion simulator could be used for inertial navigation test and high precision inertial navigation system with good dynamic and static performances. A real time control system is designed, several control system implementation problems were solved including time unification with parallel port interrupt, high speed finding-zero method of rotary inductosyn, zero-crossing management with continuous rotary, etc. Tests were carried out to show the effectiveness of the proposed real time control system.

Three axis electronic flight motion simulator real time control system design and implementation

Energy Technology Data Exchange (ETDEWEB)

Gao, Zhiyuan; Miao, Zhonghua, E-mail: zhonghua-miao@163.com; Wang, Xiaohua [School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, 200072 (China); Wang, Xuyong [School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240 (China)

2014-12-15

A three axis electronic flight motion simulator is reported in this paper including the modelling, the controller design as well as the hardware implementation. This flight motion simulator could be used for inertial navigation test and high precision inertial navigation system with good dynamic and static performances. A real time control system is designed, several control system implementation problems were solved including time unification with parallel port interrupt, high speed finding-zero method of rotary inductosyn, zero-crossing management with continuous rotary, etc. Tests were carried out to show the effectiveness of the proposed real time control system.

An FPGA Platform for Real-Time Simulation of Spiking Neuronal Networks.

Science.gov (United States)

Pani, Danilo; Meloni, Paolo; Tuveri, Giuseppe; Palumbo, Francesca; Massobrio, Paolo; Raffo, Luigi

2017-01-01

In the last years, the idea to dynamically interface biological neurons with artificial ones has become more and more urgent. The reason is essentially due to the design of innovative neuroprostheses where biological cell assemblies of the brain can be substituted by artificial ones. For closed-loop experiments with biological neuronal networks interfaced with in silico modeled networks, several technological challenges need to be faced, from the low-level interfacing between the living tissue and the computational model to the implementation of the latter in a suitable form for real-time processing. Field programmable gate arrays (FPGAs) can improve flexibility when simple neuronal models are required, obtaining good accuracy, real-time performance, and the possibility to create a hybrid system without any custom hardware, just programming the hardware to achieve the required functionality. In this paper, this possibility is explored presenting a modular and efficient FPGA design of an in silico spiking neural network exploiting the Izhikevich model. The proposed system, prototypically implemented on a Xilinx Virtex 6 device, is able to simulate a fully connected network counting up to 1,440 neurons, in real-time, at a sampling rate of 10 kHz, which is reasonable for small to medium scale extra-cellular closed-loop experiments.

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.

Real time damage detection using recursive principal components and time varying auto-regressive modeling

Science.gov (United States)

Krishnan, M.; Bhowmik, B.; Hazra, B.; Pakrashi, V.

2018-02-01

In this paper, a novel baseline free approach for continuous online damage detection of multi degree of freedom vibrating structures using Recursive Principal Component Analysis (RPCA) in conjunction with Time Varying Auto-Regressive Modeling (TVAR) is proposed. In this method, the acceleration data is used to obtain recursive proper orthogonal components online using rank-one perturbation method, followed by TVAR modeling of the first transformed response, to detect the change in the dynamic behavior of the vibrating system from its pristine state to contiguous linear/non-linear-states that indicate damage. Most of the works available in the literature deal with algorithms that require windowing of the gathered data owing to their data-driven nature which renders them ineffective for online implementation. Algorithms focussed on mathematically consistent recursive techniques in a rigorous theoretical framework of structural damage detection is missing, which motivates the development of the present framework that is amenable for online implementation which could be utilized along with suite experimental and numerical investigations. The RPCA algorithm iterates the eigenvector and eigenvalue estimates for sample covariance matrices and new data point at each successive time instants, using the rank-one perturbation method. TVAR modeling on the principal component explaining maximum variance is utilized and the damage is identified by tracking the TVAR coefficients. This eliminates the need for offline post processing and facilitates online damage detection especially when applied to streaming data without requiring any baseline data. Numerical simulations performed on a 5-dof nonlinear system under white noise excitation and El Centro (also known as 1940 Imperial Valley earthquake) excitation, for different damage scenarios, demonstrate the robustness of the proposed algorithm. The method is further validated on results obtained from case studies involving

Real-time observation of the conformational dynamics of mitochondrial Hsp70 by spFRET.

Science.gov (United States)

Sikor, Martin; Mapa, Koyeli; von Voithenberg, Lena Voith; Mokranjac, Dejana; Lamb, Don C

2013-05-29

The numerous functions of the important class of molecular chaperones, heat shock proteins 70 (Hsp70), rely on cycles of intricate conformational changes driven by ATP-hydrolysis and regulated by cochaperones and substrates. Here, we used Förster resonance energy transfer to study the conformational dynamics of individual molecules of Ssc1, a mitochondrial Hsp70, in real time. The intrinsic dynamics of the substrate-binding domain of Ssc1 was observed to be uncoupled from the dynamic interactions between substrate- and nucleotide-binding domains. Analysis of the fluctuations in the interdomain separation revealed frequent transitions to a nucleotide-free state. The nucleotide-exchange factor Mge1 did not induce ADP release, as expected, but rather facilitated binding of ATP. These results indicate that the conformational cycle of Ssc1 is more elaborate than previously thought and provide insight into how the Hsp70s can perform a wide variety of functions.

A real time fuzzy logic power management strategy for a fuel cell vehicle

International Nuclear Information System (INIS)

Hemi, Hanane; Ghouili, Jamel; Cheriti, Ahmed

2014-01-01

Highlights: • We present a real time fuzzy logic power management strategy. • This strategy is applied to hybrid electric vehicle dynamic model. • Three configurations evaluated during a drive cycle. • The hydrogen consumption is analysed for the three configurations. - Abstract: This paper presents real time fuzzy logic controller (FLC) approach used to design a power management strategy for a hybrid electric vehicle and to protect the battery from overcharging during the repetitive braking energy accumulation. The fuel cell (FC) and battery (B)/supercapacitor (SC) are the primary and secondary power sources, respectively. This paper analyzes and evaluates the performance of the three configurations, FC/B, FC/SC and FC/B/SC during real time driving conditions and unknown driving cycle. The MATLAB/Simulink and SimPowerSystems software packages are used to model the electrical and mechanical elements of hybrid vehicles and implement a fuzzy logic strategy

Seeing real-space dynamics of liquid water through inelastic x-ray scattering.

Science.gov (United States)

Iwashita, Takuya; Wu, Bin; Chen, Wei-Ren; Tsutsui, Satoshi; Baron, Alfred Q R; Egami, Takeshi

2017-12-01

Water is ubiquitous on earth, but we know little about the real-space motion of molecules in liquid water. We demonstrate that high-resolution inelastic x-ray scattering measurement over a wide range of momentum and energy transfer makes it possible to probe real-space, real-time dynamics of water molecules through the so-called Van Hove function. Water molecules are found to be strongly correlated in space and time with coupling between the first and second nearest-neighbor molecules. The local dynamic correlation of molecules observed here is crucial to a fundamental understanding of the origin of the physical properties of water, including viscosity. The results also suggest that the quantum-mechanical nature of hydrogen bonds could influence its dynamics. The approach used here offers a powerful experimental method for investigating real-space dynamics of liquids.

Design and Implementation of Real-Time Vehicular Camera for Driver Assistance and Traffic Congestion Estimation.

Science.gov (United States)

Son, Sanghyun; Baek, Yunju

2015-08-18

As society has developed, the number of vehicles has increased and road conditions have become complicated, increasing the risk of crashes. Therefore, a service that provides safe vehicle control and various types of information to the driver is urgently needed. In this study, we designed and implemented a real-time traffic information system and a smart camera device for smart driver assistance systems. We selected a commercial device for the smart driver assistance systems, and applied a computer vision algorithm to perform image recognition. For application to the dynamic region of interest, dynamic frame skip methods were implemented to perform parallel processing in order to enable real-time operation. In addition, we designed and implemented a model to estimate congestion by analyzing traffic information. The performance of the proposed method was evaluated using images of a real road environment. We found that the processing time improved by 15.4 times when all the proposed methods were applied in the application. Further, we found experimentally that there was little or no change in the recognition accuracy when the proposed method was applied. Using the traffic congestion estimation model, we also found that the average error rate of the proposed model was 5.3%.

Design and Implementation of Real-Time Vehicular Camera for Driver Assistance and Traffic Congestion Estimation

Directory of Open Access Journals (Sweden)

Sanghyun Son

2015-08-01

Full Text Available As society has developed, the number of vehicles has increased and road conditions have become complicated, increasing the risk of crashes. Therefore, a service that provides safe vehicle control and various types of information to the driver is urgently needed. In this study, we designed and implemented a real-time traffic information system and a smart camera device for smart driver assistance systems. We selected a commercial device for the smart driver assistance systems, and applied a computer vision algorithm to perform image recognition. For application to the dynamic region of interest, dynamic frame skip methods were implemented to perform parallel processing in order to enable real-time operation. In addition, we designed and implemented a model to estimate congestion by analyzing traffic information. The performance of the proposed method was evaluated using images of a real road environment. We found that the processing time improved by 15.4 times when all the proposed methods were applied in the application. Further, we found experimentally that there was little or no change in the recognition accuracy when the proposed method was applied. Using the traffic congestion estimation model, we also found that the average error rate of the proposed model was 5.3%.

A compact multifunctional microfluidic platform for exploring cellular dynamics in real-time using electrochemical detection

DEFF Research Database (Denmark)

Zor, Kinga; Heiskanen, Arto; Caviglia, Claudia

2014-01-01

and electrochemical analysis platform with in-built fluid handling and detection, enabling complete cell based assays comprising on-line electrode cleaning, sterilization, surface functionalization, cell seeding, cultivation and electrochemical real-time monitoring of cellular dynamics. To demonstrate the versatility...... capability. The here presented platform is aimed at applications utilizing cell based assays, ranging from e.g. monitoring of drug effects in pharmacological studies, characterization of neural stem cell differentiation, and screening of genetically modified microorganisms to environmental monitoring....

Draft Forecasts from Real-Time Runs of Physics-Based Models - A Road to the Future

Science.gov (United States)

Hesse, Michael; Rastatter, Lutz; MacNeice, Peter; Kuznetsova, Masha

2008-01-01

The Community Coordinated Modeling Center (CCMC) is a US inter-agency activity aiming at research in support of the generation of advanced space weather models. As one of its main functions, the CCMC provides to researchers the use of space science models, even if they are not model owners themselves. The second focus of CCMC activities is on validation and verification of space weather models, and on the transition of appropriate models to space weather forecast centers. As part of the latter activity, the CCMC develops real-time simulation systems that stress models through routine execution. A by-product of these real-time calculations is the ability to derive model products, which may be useful for space weather operators. After consultations with NOAA/SEC and with AFWA, CCMC has developed a set of tools as a first step to make real-time model output useful to forecast centers. In this presentation, we will discuss the motivation for this activity, the actions taken so far, and options for future tools from model output.

Time-varying correlations in global real estate markets: A multivariate GARCH with spatial effects approach

Science.gov (United States)

Gu, Huaying; Liu, Zhixue; Weng, Yingliang

2017-04-01

The present study applies the multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) with spatial effects approach for the analysis of the time-varying conditional correlations and contagion effects among global real estate markets. A distinguishing feature of the proposed model is that it can simultaneously capture the spatial interactions and the dynamic conditional correlations compared with the traditional MGARCH models. Results reveal that the estimated dynamic conditional correlations have exhibited significant increases during the global financial crisis from 2007 to 2009, thereby suggesting contagion effects among global real estate markets. The analysis further indicates that the returns of the regional real estate markets that are in close geographic and economic proximities exhibit strong co-movement. In addition, evidence of significantly positive leverage effects in global real estate markets is also determined. The findings have significant implications on global portfolio diversification opportunities and risk management practices.

Systematic evaluation of fault trees using real-time model checker UPPAAL

International Nuclear Information System (INIS)

Cha, Sungdeok; Son, Hanseong; Yoo, Junbeom; Jee, Eunkyung; Seong, Poong Hyun

2003-01-01

Fault tree analysis, the most widely used safety analysis technique in industry, is often applied manually. Although techniques such as cutset analysis or probabilistic analysis can be applied on the fault tree to derive further insights, they are inadequate in locating flaws when failure modes in fault tree nodes are incorrectly identified or when causal relationships among failure modes are inaccurately specified. In this paper, we demonstrate that model checking technique is a powerful tool that can formally validate the accuracy of fault trees. We used a real-time model checker UPPAAL because the system we used as the case study, nuclear power emergency shutdown software named Wolsong SDS2, has real-time requirements. By translating functional requirements written in SCR-style tabular notation into timed automata, two types of properties were verified: (1) if failure mode described in a fault tree node is consistent with the system's behavioral model; and (2) whether or not a fault tree node has been accurately decomposed. A group of domain engineers with detailed technical knowledge of Wolsong SDS2 and safety analysis techniques developed fault tree used in the case study. However, model checking technique detected subtle ambiguities present in the fault tree

Scene independent real-time indirect illumination

DEFF Research Database (Denmark)

Frisvad, Jeppe Revall; Christensen, Niels Jørgen; Falster, Peter

2005-01-01

A novel method for real-time simulation of indirect illumination is presented in this paper. The method, which we call Direct Radiance Mapping (DRM), is based on basal radiance calculations and does not impose any restrictions on scene geometry or dynamics. This makes the method tractable for rea...

MicROS-drt: supporting real-time and scalable data distribution in distributed robotic systems.

Science.gov (United States)

Ding, Bo; Wang, Huaimin; Fan, Zedong; Zhang, Pengfei; Liu, Hui

A primary requirement in distributed robotic software systems is the dissemination of data to all interested collaborative entities in a timely and scalable manner. However, providing such a service in a highly dynamic and resource-limited robotic environment is a challenging task, and existing robot software infrastructure has limitations in this aspect. This paper presents a novel robot software infrastructure, micROS-drt, which supports real-time and scalable data distribution. The solution is based on a loosely coupled data publish-subscribe model with the ability to support various time-related constraints. And to realize this model, a mature data distribution standard, the data distribution service for real-time systems (DDS), is adopted as the foundation of the transport layer of this software infrastructure. By elaborately adapting and encapsulating the capability of the underlying DDS middleware, micROS-drt can meet the requirement of real-time and scalable data distribution in distributed robotic systems. Evaluation results in terms of scalability, latency jitter and transport priority as well as the experiment on real robots validate the effectiveness of this work.

Solar Potential Analysis and Integration of the Time-Dependent Simulation Results for Semantic 3d City Models Using Dynamizers

Science.gov (United States)

Chaturvedi, K.; Willenborg, B.; Sindram, M.; Kolbe, T. H.

2017-10-01

Semantic 3D city models play an important role in solving complex real-world problems and are being adopted by many cities around the world. A wide range of application and simulation scenarios directly benefit from the adoption of international standards such as CityGML. However, most of the simulations involve properties, whose values vary with respect to time, and the current generation semantic 3D city models do not support time-dependent properties explicitly. In this paper, the details of solar potential simulations are provided operating on the CityGML standard, assessing and estimating solar energy production for the roofs and facades of the 3D building objects in different ways. Furthermore, the paper demonstrates how the time-dependent simulation results are better-represented inline within 3D city models utilizing the so-called Dynamizer concept. This concept not only allows representing the simulation results in standardized ways, but also delivers a method to enhance static city models by such dynamic property values making the city models truly dynamic. The dynamizer concept has been implemented as an Application Domain Extension of the CityGML standard within the OGC Future City Pilot Phase 1. The results are given in this paper.

Exploiting the time-dynamics of news diffusion on the Internet through a generalized Susceptible-Infected model

Science.gov (United States)

De Martino, Giuseppe; Spina, Serena

2015-11-01

We construct a news spreading model with a time dependent contact rate which generalizes the classical Susceptible-Infected model of epidemiology. In particular, we are interested on the time-dynamics of the sharing and diffusion process of news on the Internet. We focus on the counting process describing the number of connections to a given website, characterizing the cumulative density function of its inter-arrival times. Moreover, starting from the general form of the finite dimensional distribution of the process, we determine a formula for the time-variable rate of the connections and establish its relationship with the probability density function of the interarrival times. We finally show the effectiveness of our theoretical framework analyzing a real-world dataset, the Memetracker dataset, whose parameters characterizing the diffusion process are determined.

Real-Time Monitoring and Prediction of the Pilot Vehicle System (PVS) Closed-Loop Stability

Science.gov (United States)

Mandal, Tanmay Kumar

Understanding human control behavior is an important step for improving the safety of future aircraft. Considerable resources are invested during the design phase of an aircraft to ensure that the aircraft has desirable handling qualities. However, human pilots exhibit a wide range of control behaviors that are a function of external stimulus, aircraft dynamics, and human psychological properties (such as workload, stress factor, confidence, and sense of urgency factor). This variability is difficult to address comprehensively during the design phase and may lead to undesirable pilot-aircraft interaction, such as pilot-induced oscillations (PIO). This creates the need to keep track of human pilot performance in real-time to monitor the pilot vehicle system (PVS) stability. This work focused on studying human pilot behavior for the longitudinal axis of a remotely controlled research aircraft and using human-in-the-loop (HuIL) simulations to obtain information about the human controlled system (HCS) stability. The work in this dissertation is divided into two main parts: PIO analysis and human control model parameters estimation. To replicate different flight conditions, this study included time delay and elevator rate limiting phenomena, typical of actuator dynamics during the experiments. To study human control behavior, this study employed the McRuer model for single-input single-output manual compensatory tasks. McRuer model is a lead-lag controller with time delay which has been shown to adequately model manual compensatory tasks. This dissertation presents a novel technique to estimate McRuer model parameters in real-time and associated validation using HuIL simulations to correctly predict HCS stability. The McRuer model parameters were estimated in real-time using a Kalman filter approach. The estimated parameters were then used to analyze the stability of the closed-loop HCS and verify them against the experimental data. Therefore, the main contribution of

On a fast numerical tool for nuclear accidental dynamic phenomenology and application to the real time simulation of Lady Godiva

International Nuclear Information System (INIS)

Bindel, Laurent; Gamess, Andre; Jasserand, Frederic; Laporte, Sebastien

2003-01-01

This paper present a modern numerical method, implemented in a TUI-code named MacDSP, for solving any set of differential equations and in particular phenomenological accidental dynamic calculations. The speed efficiency of such an approach, thanks to the use of the hybrid-level power offered by C++ and an ad-hoc design, make it possible to construct the first kid of a family of real time simulator employing the video games technology DirectX TM : Lady Godiva Real Time Simulator. (author)

Immunity-based optimal estimation approach for a new real time group elevator dynamic control application for energy and time saving.

Science.gov (United States)

Baygin, Mehmet; Karakose, Mehmet

2013-01-01

Nowadays, the increasing use of group elevator control systems owing to increasing building heights makes the development of high-performance algorithms necessary in terms of time and energy saving. Although there are many studies in the literature about this topic, they are still not effective enough because they are not able to evaluate all features of system. In this paper, a new approach of immune system-based optimal estimate is studied for dynamic control of group elevator systems. The method is mainly based on estimation of optimal way by optimizing all calls with genetic, immune system and DNA computing algorithms, and it is evaluated with a fuzzy system. The system has a dynamic feature in terms of the situation of calls and the option of the most appropriate algorithm, and it also adaptively works in terms of parameters such as the number of floors and cabins. This new approach which provides both time and energy saving was carried out in real time. The experimental results comparatively demonstrate the effects of method. With dynamic and adaptive control approach in this study carried out, a significant progress on group elevator control systems has been achieved in terms of time and energy efficiency according to traditional methods.

Immunity-Based Optimal Estimation Approach for a New Real Time Group Elevator Dynamic Control Application for Energy and Time Saving

Directory of Open Access Journals (Sweden)

Mehmet Baygin

2013-01-01

Full Text Available Nowadays, the increasing use of group elevator control systems owing to increasing building heights makes the development of high-performance algorithms necessary in terms of time and energy saving. Although there are many studies in the literature about this topic, they are still not effective enough because they are not able to evaluate all features of system. In this paper, a new approach of immune system-based optimal estimate is studied for dynamic control of group elevator systems. The method is mainly based on estimation of optimal way by optimizing all calls with genetic, immune system and DNA computing algorithms, and it is evaluated with a fuzzy system. The system has a dynamic feature in terms of the situation of calls and the option of the most appropriate algorithm, and it also adaptively works in terms of parameters such as the number of floors and cabins. This new approach which provides both time and energy saving was carried out in real time. The experimental results comparatively demonstrate the effects of method. With dynamic and adaptive control approach in this study carried out, a significant progress on group elevator control systems has been achieved in terms of time and energy efficiency according to traditional methods.

Designers workbench: toward real-time immersive modeling

Science.gov (United States)

Kuester, Falko; Duchaineau, Mark A.; Hamann, Bernd; Joy, Kenneth I.; Ma, Kwan-Liu

2000-05-01

This paper introduces the Designers Workbench, a semi- immersive virtual environment for two-handed modeling, sculpting and analysis tasks. The paper outlines the fundamental tools, design metaphors and hardware components required for an intuitive real-time modeling system. As companies focus on streamlining productivity to cope with global competition, the migration to computer-aided design (CAD), computer-aided manufacturing, and computer-aided engineering systems has established a new backbone of modern industrial product development. However, traditionally a product design frequently originates form a clay model that, after digitization, forms the basis for the numerical description of CAD primitives. The Designers Workbench aims at closing this technology or 'digital gap' experienced by design and CAD engineers by transforming the classical design paradigm into its fully integrate digital and virtual analog allowing collaborative development in a semi- immersive virtual environment. This project emphasizes two key components form the classical product design cycle: freeform modeling and analysis. In the freedom modeling stage, content creation in the form of two-handed sculpting of arbitrary objects using polygonal, volumetric or mathematically defined primitives is emphasized, whereas the analysis component provides the tools required for pre- and post-processing steps for finite element analysis tasks applied to the created models.

Real-time metabolome profiling of the metabolic switch between starvation and growth.

Science.gov (United States)

Link, Hannes; Fuhrer, Tobias; Gerosa, Luca; Zamboni, Nicola; Sauer, Uwe

2015-11-01

Metabolic systems are often the first networks to respond to environmental changes, and the ability to monitor metabolite dynamics is key for understanding these cellular responses. Because monitoring metabolome changes is experimentally tedious and demanding, dynamic data on time scales from seconds to hours are scarce. Here we describe real-time metabolome profiling by direct injection of living bacteria, yeast or mammalian cells into a high-resolution mass spectrometer, which enables automated monitoring of about 300 compounds in 15-30-s cycles over several hours. We observed accumulation of energetically costly biomass metabolites in Escherichia coli in carbon starvation-induced stationary phase, as well as the rapid use of these metabolites upon growth resumption. By combining real-time metabolome profiling with modeling and inhibitor experiments, we obtained evidence for switch-like feedback inhibition in amino acid biosynthesis and for control of substrate availability through the preferential use of the metabolically cheaper one-step salvaging pathway over costly ten-step de novo purine biosynthesis during growth resumption.

Real-time individualized training vectors for experiential learning.

Energy Technology Data Exchange (ETDEWEB)

Willis, Matt; Tucker, Eilish Marie; Raybourn, Elaine Marie; Glickman, Matthew R.; Fabian, Nathan

2011-01-01

Military training utilizing serious games or virtual worlds potentially generate data that can be mined to better understand how trainees learn in experiential exercises. Few data mining approaches for deployed military training games exist. Opportunities exist to collect and analyze these data, as well as to construct a full-history learner model. Outcomes discussed in the present document include results from a quasi-experimental research study on military game-based experiential learning, the deployment of an online game for training evidence collection, and results from a proof-of-concept pilot study on the development of individualized training vectors. This Lab Directed Research & Development (LDRD) project leveraged products within projects, such as Titan (Network Grand Challenge), Real-Time Feedback and Evaluation System, (America's Army Adaptive Thinking and Leadership, DARWARS Ambush! NK), and Dynamic Bayesian Networks to investigate whether machine learning capabilities could perform real-time, in-game similarity vectors of learner performance, toward adaptation of content delivery, and quantitative measurement of experiential learning.

Real Time Pricing and the Real Live Firm

Energy Technology Data Exchange (ETDEWEB)

Moezzi, Mithra; Goldman, Charles; Sezgen, Osman; Bharvirkar, Ranjit; Hopper, Nicole

2004-05-26

Energy economists have long argued the benefits of real time pricing (RTP) of electricity. Their basis for modeling customers response to short-term fluctuations in electricity prices are based on theories of rational firm behavior, where management strives to minimize operating costs and optimize profit, and labor, capital and energy are potential substitutes in the firm's production function. How well do private firms and public sector institutions operating conditions, knowledge structures, decision-making practices, and external relationships comport with these assumptions and how might this impact price response? We discuss these issues on the basis of interviews with 29 large (over 2 MW) industrial, commercial, and institutional customers in the Niagara Mohawk Power Corporation service territory that have faced day-ahead electricity market prices since 1998. We look at stories interviewees told about why and how they respond to RTP, why some customers report that they can't, and why even if they can, they don't. Some firms respond as theorized, and we describe their load curtailment strategies. About half of our interviewees reported that they were unable to either shift or forego electricity consumption even when prices are high ($0.50/kWh). Reasons customers gave for why they weren't price-responsive include implicit value placed on reliability, pricing structures, lack of flexibility in adjusting production inputs, just-in-time practices, perceived barriers to onsite generation, and insufficient time. We draw these observations into a framework that could help refine economic theory of dynamic pricing by providing real-world descriptions of how firms behave and why.

An Analysis of a Hard Real-Time Execution Environment Extension for FreeRTOS

Directory of Open Access Journals (Sweden)

STANGACIU, C.

2015-08-01

Full Text Available FreeRTOS is a popular real-time operating system, which has been under a significant attention in the last years due to its main advantages: it is open source, portable, well documented and implemented on more than 30 architectures. FreeRTOS execution environment is dynamic, preemptive and priority based, but it is not suitable for hard real-time tasks, because it provides task execution determinism only to a certain degree and cannot guarantee the absence of task execution jitter. As a solution to this problem, we propose a hard real time execution extension to FreeRTOS in order to support a particular model of HRT tasks, called ModXs, which are executed with no jitter. This article presents a detailed analysis, in terms of scheduling, task execution and memory usage of this hard real time execution environment extension. The article is concluding with the advantages this extension brings to the system compared to the small memory and timing overhead introduced.

The Slow Developmental Time Course of Real-Time Spoken Word Recognition

Science.gov (United States)

Rigler, Hannah; Farris-Trimble, Ashley; Greiner, Lea; Walker, Jessica; Tomblin, J. Bruce; McMurray, Bob

2015-01-01

This study investigated the developmental time course of spoken word recognition in older children using eye tracking to assess how the real-time processing dynamics of word recognition change over development. We found that 9-year-olds were slower to activate the target words and showed more early competition from competitor words than…

Robust Real-Time Music Transcription with a Compositional Hierarchical Model.

Science.gov (United States)

Pesek, Matevž; Leonardis, Aleš; Marolt, Matija

2017-01-01

The paper presents a new compositional hierarchical model for robust music transcription. Its main features are unsupervised learning of a hierarchical representation of input data, transparency, which enables insights into the learned representation, as well as robustness and speed which make it suitable for real-world and real-time use. The model consists of multiple layers, each composed of a number of parts. The hierarchical nature of the model corresponds well to hierarchical structures in music. The parts in lower layers correspond to low-level concepts (e.g. tone partials), while the parts in higher layers combine lower-level representations into more complex concepts (tones, chords). The layers are learned in an unsupervised manner from music signals. Parts in each layer are compositions of parts from previous layers based on statistical co-occurrences as the driving force of the learning process. In the paper, we present the model's structure and compare it to other hierarchical approaches in the field of music information retrieval. We evaluate the model's performance for the multiple fundamental frequency estimation. Finally, we elaborate on extensions of the model towards other music information retrieval tasks.

Real-time Tactical and Strategic Sales Management for Intelligent Agents Guided By Economic Regimes

NARCIS (Netherlands)

W. Ketter (Wolfgang); J. Collins (John); M. Gini (Maria); A. Gupta (Alok); P. Schrater (Paul)

2011-01-01

textabstractMany enterprises that participate in dynamic markets need to make product pricing and inventory resource utilization decisions in real-time. We describe a family of statistical models that address these needs by combining characterization of the economic environment with the ability to

Real-Time Tactical and Strategic Sales Management for Intelligent Agents Guided by Economic Regimes

NARCIS (Netherlands)

W. Ketter (Wolfgang); J. Collins (John); M. Gini (Maria); A. Gupta (Alok); P. Schrater (Paul)

2012-01-01

textabstractMany enterprises that participate in dynamic markets need to make product pricing and inventory resource utilization decisions in real time. We describe a family of statistical models that addresses these needs by combining characterization of the economic environment with the ability to

A real-time monitoring/emergency response modeling workstation for a tritium facility

International Nuclear Information System (INIS)

Lawver, B.S.; Sims, J.M.; Baskett, R.L.

1993-07-01

At Lawrence Livermore National Laboratory (LLNL) we developed a real-time system to monitor two stacks on our tritium handling facility. The monitors transmit the stack data to a workstation which computes a 3D numerical model of atmospheric dispersion. The workstation also collects surface and upper air data from meteorological towers and a sodar. The complex meteorological and terrain setting in the Livermore Valley demands more sophisticated resolution of the three-dimensional structure of the atmosphere to reliably calculate plume dispersion than afforded by Gaussian models. We experience both mountain valley and sea breeze flows. To address these complexities, we have implemented the three-dimensional diagnostic MATHEW mass-adjusted wind field and ADPIC particle-in-cell dispersion models on the workstation for use in real-time emergency response modeling. Both MATHEW and ADPIC have shown their utility in a variety of complex settings over the last 15 years within the Department of Energy's Atmospheric Release Advisory Capability (ARAC[1,2]) project

Real-time control data wrangling for development of mathematical control models of technological processes

Science.gov (United States)

Vasilyeva, N. V.; Koteleva, N. I.; Fedorova, E. R.

2018-05-01

The relevance of the research is due to the need to stabilize the composition of the melting products of copper-nickel sulfide raw materials in the Vanyukov furnace. The goal of this research is to identify the most suitable methods for the aggregation of the real time data for the development of a mathematical model for control of the technological process of melting copper-nickel sulfide raw materials in the Vanyukov furnace. Statistical methods of analyzing the historical data of the real technological object and the correlation analysis of process parameters are described. Factors that exert the greatest influence on the main output parameter (copper content in matte) and ensure the physical-chemical transformations are revealed. An approach to the processing of the real time data for the development of a mathematical model for control of the melting process is proposed. The stages of processing the real time information are considered. The adopted methodology for the aggregation of data suitable for the development of a control model for the technological process of melting copper-nickel sulfide raw materials in the Vanyukov furnace allows us to interpret the obtained results for their further practical application.

Real Time Optima Tracking Using Harvesting Models of the Genetic Algorithm

Science.gov (United States)

Baskaran, Subbiah; Noever, D.

1999-01-01

Tracking optima in real time propulsion control, particularly for non-stationary optimization problems is a challenging task. Several approaches have been put forward for such a study including the numerical method called the genetic algorithm. In brief, this approach is built upon Darwinian-style competition between numerical alternatives displayed in the form of binary strings, or by analogy to 'pseudogenes'. Breeding of improved solution is an often cited parallel to natural selection in.evolutionary or soft computing. In this report we present our results of applying a novel model of a genetic algorithm for tracking optima in propulsion engineering and in real time control. We specialize the algorithm to mission profiling and planning optimizations, both to select reduced propulsion needs through trajectory planning and to explore time or fuel conservation strategies.

X-ray absorption in insulators with non-Hermitian real-time time-dependent density functional theory.

Science.gov (United States)

Fernando, Ranelka G; Balhoff, Mary C; Lopata, Kenneth

2015-02-10

Non-Hermitian real-time time-dependent density functional theory was used to compute the Si L-edge X-ray absorption spectrum of α-quartz using an embedded finite cluster model and atom-centered basis sets. Using tuned range-separated functionals and molecular orbital-based imaginary absorbing potentials, the excited states spanning the pre-edge to ∼20 eV above the ionization edge were obtained in good agreement with experimental data. This approach is generalizable to TDDFT studies of core-level spectroscopy and dynamics in a wide range of materials.

A Real-Time Accurate Model and Its Predictive Fuzzy PID Controller for Pumped Storage Unit via Error Compensation

Directory of Open Access Journals (Sweden)