Nonlinear dynamics based digital logic and circuits.

Science.gov (United States)

Kia, Behnam; Lindner, John F; Ditto, William L

2015-01-01

We discuss the role and importance of dynamics in the brain and biological neural networks and argue that dynamics is one of the main missing elements in conventional Boolean logic and circuits. We summarize a simple dynamics based computing method, and categorize different techniques that we have introduced to realize logic, functionality, and programmability. We discuss the role and importance of coupled dynamics in networks of biological excitable cells, and then review our simple coupled dynamics based method for computing. In this paper, for the first time, we show how dynamics can be used and programmed to implement computation in any given base, including but not limited to base two.

Optimal blood glucose control in diabetes mellitus treatment using dynamic programming based on Ackerman’s linear model

Science.gov (United States)

Pradanti, Paskalia; Hartono

2018-03-01

Determination of insulin injection dose in diabetes mellitus treatment can be considered as an optimal control problem. This article is aimed to simulate optimal blood glucose control for patient with diabetes mellitus. The blood glucose regulation of diabetic patient is represented by Ackerman’s Linear Model. This problem is then solved using dynamic programming method. The desired blood glucose level is obtained by minimizing the performance index in Lagrange form. The results show that dynamic programming based on Ackerman’s Linear Model is quite good to solve the problem.

Optimization of fuel-cell tram operation based on two dimension dynamic programming

Science.gov (United States)

Zhang, Wenbin; Lu, Xuecheng; Zhao, Jingsong; Li, Jianqiu

2018-02-01

This paper proposes an optimal control strategy based on the two-dimension dynamic programming (2DDP) algorithm targeting at minimizing operation energy consumption for a fuel-cell tram. The energy consumption model with the tram dynamics is firstly deduced. Optimal control problem are analyzed and the 2DDP strategy is applied to solve the problem. The optimal tram speed profiles are obtained for each interstation which consist of three stages: accelerate to the set speed with the maximum traction power, dynamically adjust to maintain a uniform speed and decelerate to zero speed with the maximum braking power at a suitable timing. The optimal control curves of all the interstations are connected with the parking time to form the optimal control method of the whole line. The optimized speed profiles are also simplified for drivers to follow.

A dynamic regrouping based sequential dynamic programming algorithm for unit commitment of combined heat and power systems

DEFF Research Database (Denmark)

Rong, Aiying; Hakonen, Henri; Lahdelma, Risto

2009-01-01

efficiency of the plants. We introduce in this paper the DRDP-RSC algorithm, which is a dynamic regrouping based dynamic programming (DP) algorithm based on linear relaxation of the ON/OFF states of the units, sequential commitment of units in small groups. Relaxed states of the plants are used to reduce...... the dimension of the UC problem and dynamic regrouping is used to improve the solution quality. Numerical results based on real-life data sets show that this algorithm is efficient and optimal or near-optimal solutions with very small optimality gap are obtained....

Dynamic Programming Foundations and Principles

CERN Document Server

Sniedovich, Moshe

2010-01-01

Focusing on the modeling and solution of deterministic multistage decision problems, this book looks at dynamic programming as a problem-solving optimization method. With over 400 useful references, this edition discusses the dynamic programming analysis of a problem, illustrates the rationale behind this analysis, and clarifies the theoretical grounds that justify the rationale. It also explains the meaning and role of the concept of state in dynamic programming, examines the purpose and function of the principle of optimality, and outlines solution strategies for problems defiant of conventi

The sequence relay selection strategy based on stochastic dynamic programming

Science.gov (United States)

Zhu, Rui; Chen, Xihao; Huang, Yangchao

2017-07-01

Relay-assisted (RA) network with relay node selection is a kind of effective method to improve the channel capacity and convergence performance. However, most of the existing researches about the relay selection did not consider the statically channel state information and the selection cost. This shortage limited the performance and application of RA network in practical scenarios. In order to overcome this drawback, a sequence relay selection strategy (SRSS) was proposed. And the performance upper bound of SRSS was also analyzed in this paper. Furthermore, in order to make SRSS more practical, a novel threshold determination algorithm based on the stochastic dynamic program (SDP) was given to work with SRSS. Numerical results are also presented to exhibit the performance of SRSS with SDP.

Research on Automotive Dynamic Weighing Method Based on Piezoelectric Sensor

Directory of Open Access Journals (Sweden)

Zhang Wei

2017-01-01

Full Text Available In order to effectively measure the dynamic axle load of vehicles in motion, the dynamic weighing method of vehicles based on piezoelectric sensor was studied. Firstly, the influencing factors of the measurement accuracy in the dynamic weighing process were analyzed systematically, and the impacts of road irregularities and dynamic weighing system vibration on measurement error were discussed. On the basis of the analysis, the arithmetic mean filter method was used in the software algorithm to filter out the periodic interference added in the sensor signal, the most suitable n value was selected to get the better filtering result by simulation comparison. Then, the dynamic axle load calculation model of high speed vehicles was studied deeply, based on the theoretical response curve of the sensor, the dynamic axle load calculation method based on frequency reconstruction was established according to actual measurement signals of sensors and the analysis from time domain and frequency domain, also the least square method was used to realize the identification of temperature correction coefficient. A large amount of data that covered the usual vehicle weighing range was collected by experiment. The results show that the dynamic weighing signal system identification error all controlled within 10% at the same temperature and 60% of the vehicle data error can be controlled within 7%. The temperature correction coefficient and the correction formula at different temperatures ranges are well adapted to ensure that the vehicle temperature error at different temperatures can also be controlled within 10% and 70% of the vehicle data error within 7%. Furthermore, the weighing results remain stable regardless of the speed of the vehicle which meets the requirements for high-speed dynamic weighing.

Simple estimating method of damages of concrete gravity dam based on linear dynamic analysis

Energy Technology Data Exchange (ETDEWEB)

Sasaki, T.; Kanenawa, K.; Yamaguchi, Y. [Public Works Research Institute, Tsukuba, Ibaraki (Japan). Hydraulic Engineering Research Group

2004-07-01

Due to the occurrence of large earthquakes like the Kobe Earthquake in 1995, there is a strong need to verify seismic resistance of dams against much larger earthquake motions than those considered in the present design standard in Japan. Problems exist in using nonlinear analysis to evaluate the safety of dams including: that the influence which the set material properties have on the results of nonlinear analysis is large, and that the results of nonlinear analysis differ greatly according to the damage estimation models or analysis programs. This paper reports the evaluation indices based on a linear dynamic analysis method and the characteristics of the progress of cracks in concrete gravity dams with different shapes using a nonlinear dynamic analysis method. The study concludes that if simple linear dynamic analysis is appropriately conducted to estimate tensile stress at potential locations of initiating cracks, the damage due to cracks would be predicted roughly. 4 refs., 1 tab., 13 figs.

Dynamic model based on Bayesian method for energy security assessment

International Nuclear Information System (INIS)

Augutis, Juozas; Krikštolaitis, Ričardas; Pečiulytė, Sigita; Žutautaitė, Inga

2015-01-01

Highlights: • Methodology for dynamic indicator model construction and forecasting of indicators. • Application of dynamic indicator model for energy system development scenarios. • Expert judgement involvement using Bayesian method. - Abstract: The methodology for the dynamic indicator model construction and forecasting of indicators for the assessment of energy security level is presented in this article. An indicator is a special index, which provides numerical values to important factors for the investigated area. In real life, models of different processes take into account various factors that are time-dependent and dependent on each other. Thus, it is advisable to construct a dynamic model in order to describe these dependences. The energy security indicators are used as factors in the dynamic model. Usually, the values of indicators are obtained from statistical data. The developed dynamic model enables to forecast indicators’ variation taking into account changes in system configuration. The energy system development is usually based on a new object construction. Since the parameters of changes of the new system are not exactly known, information about their influences on indicators could not be involved in the model by deterministic methods. Thus, dynamic indicators’ model based on historical data is adjusted by probabilistic model with the influence of new factors on indicators using the Bayesian method

A Method Based on Dial's Algorithm for Multi-time Dynamic Traffic Assignment

Directory of Open Access Journals (Sweden)

Rongjie Kuang

2014-03-01

Full Text Available Due to static traffic assignment has poor performance in reflecting actual case and dynamic traffic assignment may incurs excessive compute cost, method of multi-time dynamic traffic assignment combining static and dynamic traffic assignment balances factors of precision and cost effectively. A method based on Dial's logit algorithm is proposed in the article to solve the dynamic stochastic user equilibrium problem in dynamic traffic assignment. Before that, a fitting function that can proximately reflect overloaded traffic condition of link is proposed and used to give corresponding model. Numerical example is given to illustrate heuristic procedure of method and to compare results with one of same example solved by other literature's algorithm. Results show that method based on Dial's algorithm is preferable to algorithm from others.

Iterative Adaptive Dynamic Programming for Solving Unknown Nonlinear Zero-Sum Game Based on Online Data.

Science.gov (United States)

Zhu, Yuanheng; Zhao, Dongbin; Li, Xiangjun

2017-03-01

H ∞ control is a powerful method to solve the disturbance attenuation problems that occur in some control systems. The design of such controllers relies on solving the zero-sum game (ZSG). But in practical applications, the exact dynamics is mostly unknown. Identification of dynamics also produces errors that are detrimental to the control performance. To overcome this problem, an iterative adaptive dynamic programming algorithm is proposed in this paper to solve the continuous-time, unknown nonlinear ZSG with only online data. A model-free approach to the Hamilton-Jacobi-Isaacs equation is developed based on the policy iteration method. Control and disturbance policies and value are approximated by neural networks (NNs) under the critic-actor-disturber structure. The NN weights are solved by the least-squares method. According to the theoretical analysis, our algorithm is equivalent to a Gauss-Newton method solving an optimization problem, and it converges uniformly to the optimal solution. The online data can also be used repeatedly, which is highly efficient. Simulation results demonstrate its feasibility to solve the unknown nonlinear ZSG. When compared with other algorithms, it saves a significant amount of online measurement time.

Study on the Reduced Traffic Congestion Method Based on Dynamic Guidance Information

Science.gov (United States)

Li, Shu-Bin; Wang, Guang-Min; Wang, Tao; Ren, Hua-Ling; Zhang, Lin

2018-05-01

This paper studies how to generate the reasonable information of travelers’ decision in real network. This problem is very complex because the travelers’ decision is constrained by different human behavior. The network conditions can be predicted by using the advanced dynamic OD (Origin-Destination, OD) estimation techniques. Based on the improved mesoscopic traffic model, the predictable dynamic traffic guidance information can be obtained accurately. A consistency algorithm is designed to investigate the travelers’ decision by simulating the dynamic response to guidance information. The simulation results show that the proposed method can provide the best guidance information. Further, a case study is conducted to verify the theoretical results and to draw managerial insights into the potential of dynamic guidance strategy in improving traffic performance. Supported by National Natural Science Foundation of China under Grant Nos. 71471104, 71771019, 71571109, and 71471167; The University Science and Technology Program Funding Projects of Shandong Province under Grant No. J17KA211; The Project of Public Security Department of Shandong Province under Grant No. GATHT2015-236; The Major Social and Livelihood Special Project of Jinan under Grant No. 20150905

Numerical simulation of particle dynamics in storage rings using BETACOOL program

International Nuclear Information System (INIS)

Meshkov, I.N.; Pivin, R.V.; Sidorin, A.O.; Smirnov, A.V.; Trubnikov, G.V.

2006-01-01

BETACOOL program developed by JINR electron cooling group is a kit of algorithms based on common format of input and output files. The program is oriented to simulation of the ion beam dynamics in a storage ring in the presence of cooling and heating effects. The version presented in this report includes three basic algorithms: simulation of rms parameters of the ion distribution function evolution in time, simulation of the distribution function evolution using Monte-Carlo method and tracking algorithm based on molecular dynamics technique. General processes to be investigated with the program are intrabeam scattering in the ion beam, electron cooling, interaction with residual gas and internal target

Research on pipeline leak detection method based on pressure and dynamic pressure

Energy Technology Data Exchange (ETDEWEB)

Wang, Likun; Xiong, Min; Zhao, Jinyun; Wang, Hongchao; Xu, Bin; Yu, DongLiang; Sun, Yi; Cai, Yongjun [RnD center of PetroChina Pipeline Company, Langfang, Hebei, (China)

2010-07-01

Pipeline leakages are very frequent and need to be detected as fast as possible to avoid safety and environment issues. Many leakage detection processes have been developed. Acoustic wave methods based on static pressure and dynamic pressure are both used for pipeline leakage detection. This study investigated a new pipeline leak detection method based on joint pressure and dynamic pressure. A dynamic pressure transmitter was designed based on a piezoelectric dynamic pressure sensor. The study showed that the dynamic pressure signal should be used for pipeline leak detection with a quick-change in pipeline internal pressure, while the static pressure signal provides better results with a slow-change of pipeline internal pressure. The in-field results showed that the location error of dynamic pressure is reduced to 80 m with a leakage ratio of 0.6 % pipeline throughput.

Non-Destructive Evaluation Method Based On Dynamic Invariant Stress Resultants

Directory of Open Access Journals (Sweden)

Zhang Junchi

2015-01-01

Full Text Available Most of the vibration based damage detection methods are based on changes in frequencies, mode shapes, mode shape curvature, and flexibilities. These methods are limited and typically can only detect the presence and location of damage. Current methods seldom can identify the exact severity of damage to structures. This paper will present research in the development of a new non-destructive evaluation method to identify the existence, location, and severity of damage for structural systems. The method utilizes the concept of invariant stress resultants (ISR. The basic concept of ISR is that at any given cross section the resultant internal force distribution in a structural member is not affected by the inflicted damage. The method utilizes dynamic analysis of the structure to simulate direct measurements of acceleration, velocity and displacement simultaneously. The proposed dynamic ISR method is developed and utilized to detect the damage of corresponding changes in mass, damping and stiffness. The objectives of this research are to develop the basic theory of the dynamic ISR method, apply it to the specific types of structures, and verify the accuracy of the developed theory. Numerical results that demonstrate the application of the method will reflect the advanced sensitivity and accuracy in characterizing multiple damage locations.

A Case for Dynamic Reverse-code Generation to Debug Non-deterministic Programs

Directory of Open Access Journals (Sweden)

Jooyong Yi

2013-09-01

Full Text Available Backtracking (i.e., reverse execution helps the user of a debugger to naturally think backwards along the execution path of a program, and thinking backwards makes it easy to locate the origin of a bug. So far backtracking has been implemented mostly by state saving or by checkpointing. These implementations, however, inherently do not scale. Meanwhile, a more recent backtracking method based on reverse-code generation seems promising because executing reverse code can restore the previous states of a program without state saving. In the literature, there can be found two methods that generate reverse code: (a static reverse-code generation that pre-generates reverse code through static analysis before starting a debugging session, and (b dynamic reverse-code generation that generates reverse code by applying dynamic analysis on the fly during a debugging session. In particular, we espoused the latter one in our previous work to accommodate non-determinism of a program caused by e.g., multi-threading. To demonstrate the usefulness of our dynamic reverse-code generation, this article presents a case study of various backtracking methods including ours. We compare the memory usage of various backtracking methods in a simple but nontrivial example, a bounded-buffer program. In the case of non-deterministic programs such as this bounded-buffer program, our dynamic reverse-code generation outperforms the existing backtracking methods in terms of memory efficiency.

Pathwise dynamic programming

NARCIS (Netherlands)

Bender, Christian; Gärtner, Christian; Schweizer, Nikolaus

2017-01-01

We present a novel method for deriving tight Monte Carlo confidence intervals for solutions of stochastic dynamic programming equations. Taking some approximate solution to the equation as an input, we construct pathwise recursions with a known bias. Suitably coupling the recursions for lower and

Neural-network-observer-based optimal control for unknown nonlinear systems using adaptive dynamic programming

Science.gov (United States)

Liu, Derong; Huang, Yuzhu; Wang, Ding; Wei, Qinglai

2013-09-01

In this paper, an observer-based optimal control scheme is developed for unknown nonlinear systems using adaptive dynamic programming (ADP) algorithm. First, a neural-network (NN) observer is designed to estimate system states. Then, based on the observed states, a neuro-controller is constructed via ADP method to obtain the optimal control. In this design, two NN structures are used: a three-layer NN is used to construct the observer which can be applied to systems with higher degrees of nonlinearity and without a priori knowledge of system dynamics, and a critic NN is employed to approximate the value function. The optimal control law is computed using the critic NN and the observer NN. Uniform ultimate boundedness of the closed-loop system is guaranteed. The actor, critic, and observer structures are all implemented in real-time, continuously and simultaneously. Finally, simulation results are presented to demonstrate the effectiveness of the proposed control scheme.

Dynamic electricity pricing—Which programs do consumers prefer?

International Nuclear Information System (INIS)

Dütschke, Elisabeth; Paetz, Alexandra-Gwyn

2013-01-01

Dynamic pricing is being discussed as one method of demand side management (DSM) which could be crucial for integrating more renewable energy sources into the electricity system. At the same time, there have been very few analyses of consumer preferences in this regard: Which type of pricing program are consumers most likely to choose and why? This paper sheds some light on these issues based on two empirical studies from Germany: (1) A questionnaire study including a conjoint analysis-design and (2) A field experiment with test-residents of a smart home laboratory. The results show that consumers are open to dynamic pricing, but prefer simple programs to complex and highly dynamic ones; smart home technologies including demand automation are seen as a prerequisite for DSM. The study provides some indications that consumers might be more willing to accept more dynamic pricing programs if they have the chance to experience in practice how these can be managed in everyday life. At the same time, the individual and societal advantages of such programs are not obvious to consumers. For this reason, any market roll-out will need to be accompanied by convincing communication and information campaigns to ensure that these advantages are perceived. - Highlights: • Little is known about consumer preferences on dynamic pricing. • Two studies are conducted to analyze this topic. • A survey shows that consumers without experience prefer conventional programs. • Test residents of a smart home were more open to dynamic pricing. • They also prefer well-structured programs

Control method for biped locomotion robots based on ZMP information

International Nuclear Information System (INIS)

Kume, Etsuo

1994-01-01

The Human Acts Simulation Program (HASP) started as a ten year program of Computing and Information Systems Center (CISC) at Japan Atomic Energy Research Institute (JAERI) in 1987. A mechanical design study of biped locomotion robots for patrol and inspection in nuclear facilities is being performed as an item of the research scope. One of the goals of our research is to design a biped locomotion robot for practical use in nuclear facilities. So far, we have been studying for several dynamic walking patterns. In conventional control methods for biped locomotion robots, the program control is used based on preset walking patterns, so it dose not have the robustness such as a dynamic change of walking pattern. Therefore, a real-time control method based on dynamic information of the robot states is necessary for the high performance of walking. In this study a new control method based on Zero Moment Point (ZMP) information is proposed as one of real-time control methods. The proposed method is discussed and validated based on the numerical simulation. (author)

Methods for evaluation of industry training programs

International Nuclear Information System (INIS)

Morisseau, D.S.; Roe, M.L.; Persensky, J.J.

1987-01-01

The NRC Policy Statement on Training and Qualification endorses the INPO-managed Training Accreditation Program in that it encompasses the elements of effective performance-based training. Those elements are: analysis of the job, performance-based learning objectives, training design and implementation, trainee evaluation, and program evaluation. As part of the NRC independent evaluation of utilities implementation of training improvement programs, the staff developed training review criteria and procedures that address all five elements of effective performance-based training. The staff uses these criteria to perform reviews of utility training programs that have already received accreditation. Although no performance-based training program can be said to be complete unless all five elements are in place, the last two, trainee and program evaluation, are perhaps the most important because they determine how well the first three elements have been implemented and ensure the dynamic nature of training. This paper discusses the evaluation elements of the NRC training review criteria. The discussion will detail the elements of evaluation methods and techniques that the staff expects to find as integral parts of performance-based training programs at accredited utilities. Further, the review of the effectiveness of implementation of the evaluation methods is discussed. The paper also addresses some of the qualitative differences between what is minimally acceptable and what is most desirable with respect to trainee and program evaluation mechanisms and their implementation

Dual Dynamic Programming - DDP

International Nuclear Information System (INIS)

Velasquez Bermudez, Jesus M

1998-01-01

Objections are presented to the mathematical formulation of the denominated Dual Dynamic programming-PDD that is the theoretical base of several computational model available for the optimal formulation of interconnected hydrothermal systems

Dynamic modeling method for infrared smoke based on enhanced discrete phase model

Science.gov (United States)

Zhang, Zhendong; Yang, Chunling; Zhang, Yan; Zhu, Hongbo

2018-03-01

The dynamic modeling of infrared (IR) smoke plays an important role in IR scene simulation systems and its accuracy directly influences the system veracity. However, current IR smoke models cannot provide high veracity, because certain physical characteristics are frequently ignored in fluid simulation; simplifying the discrete phase as a continuous phase and ignoring the IR decoy missile-body spinning. To address this defect, this paper proposes a dynamic modeling method for IR smoke, based on an enhanced discrete phase model (DPM). A mathematical simulation model based on an enhanced DPM is built and a dynamic computing fluid mesh is generated. The dynamic model of IR smoke is then established using an extended equivalent-blackbody-molecule model. Experiments demonstrate that this model realizes a dynamic method for modeling IR smoke with higher veracity.

A novel energy conversion based method for velocity correction in molecular dynamics simulations

Energy Technology Data Exchange (ETDEWEB)

Jin, Hanhui [School of Aeronautics and Astronautics, Zhejiang University, Hangzhou 310027 (China); Collaborative Innovation Center of Advanced Aero-Engine, Hangzhou 310027 (China); Liu, Ningning [School of Aeronautics and Astronautics, Zhejiang University, Hangzhou 310027 (China); Ku, Xiaoke, E-mail: xiaokeku@zju.edu.cn [School of Aeronautics and Astronautics, Zhejiang University, Hangzhou 310027 (China); Fan, Jianren [State Key Laboratory of Clean Energy Utilization, Zhejiang University, Hangzhou 310027 (China)

2017-05-01

Molecular dynamics (MD) simulation has become an important tool for studying micro- or nano-scale dynamics and the statistical properties of fluids and solids. In MD simulations, there are mainly two approaches: equilibrium and non-equilibrium molecular dynamics (EMD and NEMD). In this paper, a new energy conversion based correction (ECBC) method for MD is developed. Unlike the traditional systematic correction based on macroscopic parameters, the ECBC method is developed strictly based on the physical interaction processes between the pair of molecules or atoms. The developed ECBC method can apply to EMD and NEMD directly. While using MD with this method, the difference between the EMD and NEMD is eliminated, and no macroscopic parameters such as external imposed potentials or coefficients are needed. With this method, many limits of using MD are lifted. The application scope of MD is greatly extended.

A novel energy conversion based method for velocity correction in molecular dynamics simulations

International Nuclear Information System (INIS)

Jin, Hanhui; Liu, Ningning; Ku, Xiaoke; Fan, Jianren

2017-01-01

Molecular dynamics (MD) simulation has become an important tool for studying micro- or nano-scale dynamics and the statistical properties of fluids and solids. In MD simulations, there are mainly two approaches: equilibrium and non-equilibrium molecular dynamics (EMD and NEMD). In this paper, a new energy conversion based correction (ECBC) method for MD is developed. Unlike the traditional systematic correction based on macroscopic parameters, the ECBC method is developed strictly based on the physical interaction processes between the pair of molecules or atoms. The developed ECBC method can apply to EMD and NEMD directly. While using MD with this method, the difference between the EMD and NEMD is eliminated, and no macroscopic parameters such as external imposed potentials or coefficients are needed. With this method, many limits of using MD are lifted. The application scope of MD is greatly extended.

Runway Scheduling Using Generalized Dynamic Programming

Science.gov (United States)

Montoya, Justin; Wood, Zachary; Rathinam, Sivakumar

2011-01-01

A generalized dynamic programming method for finding a set of pareto optimal solutions for a runway scheduling problem is introduced. The algorithm generates a set of runway fight sequences that are optimal for both runway throughput and delay. Realistic time-based operational constraints are considered, including miles-in-trail separation, runway crossings, and wake vortex separation. The authors also model divergent runway takeoff operations to allow for reduced wake vortex separation. A modeled Dallas/Fort Worth International airport and three baseline heuristics are used to illustrate preliminary benefits of using the generalized dynamic programming method. Simulated traffic levels ranged from 10 aircraft to 30 aircraft with each test case spanning 15 minutes. The optimal solution shows a 40-70 percent decrease in the expected delay per aircraft over the baseline schedulers. Computational results suggest that the algorithm is promising for real-time application with an average computation time of 4.5 seconds. For even faster computation times, two heuristics are developed. As compared to the optimal, the heuristics are within 5% of the expected delay per aircraft and 1% of the expected number of runway operations per hour ad can be 100x faster.

Dynamic programming models and applications

CERN Document Server

Denardo, Eric V

2003-01-01

Introduction to sequential decision processes covers use of dynamic programming in studying models of resource allocation, methods for approximating solutions of control problems in continuous time, production control, more. 1982 edition.

Dynamic Power Management for Portable Hybrid Power-Supply Systems Utilizing Approximate Dynamic Programming

Directory of Open Access Journals (Sweden)

Jooyoung Park

2015-05-01

Full Text Available Recently, the optimization of power flows in portable hybrid power-supply systems (HPSSs has become an important issue with the advent of a variety of mobile systems and hybrid energy technologies. In this paper, a control strategy is considered for dynamically managing power flows in portable HPSSs employing batteries and supercapacitors. Our dynamic power management strategy utilizes the concept of approximate dynamic programming (ADP. ADP methods are important tools in the fields of stochastic control and machine learning, and the utilization of these tools for practical engineering problems is now an active and promising research field. We propose an ADP-based procedure based on optimization under constraints including the iterated Bellman inequalities, which can be solved by convex optimization carried out offline, to find the optimal power management rules for portable HPSSs. The effectiveness of the proposed procedure is tested through dynamic simulations for smartphone workload scenarios, and simulation results show that the proposed strategy can successfully cope with uncertain workload demands.

Study on the Dynamics of Laser Gyro Strapdown Inertial Measurement Unit System Based on Transfer Matrix Method for Multibody System

Directory of Open Access Journals (Sweden)

Gangli Chen

2013-01-01

Full Text Available The dynamic test precision of the strapdown inertial measurement unit (SIMU is the basis of estimating accurate motion of various vehicles such as warships, airplanes, spacecrafts, and missiles. So, it is paid great attention in the above fields to increase the dynamic precision of SIMU by decreasing the vibration of the vehicles acting on the SIMU. In this paper, based on the transfer matrix method for multibody system (MSTMM, the multibody system dynamics model of laser gyro strapdown inertial measurement unit (LGSIMU is developed; the overall transfer equation of the system is deduced automatically. The computational results show that the frequency response function of the LGSIMU got by the proposed method and Newton-Euler method have good agreements. Further, the vibration reduction performance and the attitude error responses under harmonic and random excitations are analyzed. The proposed method provides a powerful technique for studying dynamics of LGSIMU because of using MSTMM and its following features: without the global dynamics equations of the system, high programming, low order of system matrix, and high computational speed.

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

Science.gov (United States)

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

2018-03-01

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

Efficient Kinect Sensor-Based Reactive Path Planning Method for Autonomous Mobile Robots in Dynamic Environments

Energy Technology Data Exchange (ETDEWEB)

Tuvshinjargal, Doopalam; Lee, Deok Jin [Kunsan National University, Gunsan (Korea, Republic of)

2015-06-15

In this paper, an efficient dynamic reactive motion planning method for an autonomous vehicle in a dynamic environment is proposed. The purpose of the proposed method is to improve the robustness of autonomous robot motion planning capabilities within dynamic, uncertain environments by integrating a virtual plane-based reactive motion planning technique with a sensor fusion-based obstacle detection approach. The dynamic reactive motion planning method assumes a local observer in the virtual plane, which allows the effective transformation of complex dynamic planning problems into simple stationary ones proving the speed and orientation information between the robot and obstacles. In addition, the sensor fusion-based obstacle detection technique allows the pose estimation of moving obstacles using a Kinect sensor and sonar sensors, thus improving the accuracy and robustness of the reactive motion planning approach. The performance of the proposed method was demonstrated through not only simulation studies but also field experiments using multiple moving obstacles in hostile dynamic environments.

Efficient Kinect Sensor-Based Reactive Path Planning Method for Autonomous Mobile Robots in Dynamic Environments

International Nuclear Information System (INIS)

Tuvshinjargal, Doopalam; Lee, Deok Jin

2015-01-01

In this paper, an efficient dynamic reactive motion planning method for an autonomous vehicle in a dynamic environment is proposed. The purpose of the proposed method is to improve the robustness of autonomous robot motion planning capabilities within dynamic, uncertain environments by integrating a virtual plane-based reactive motion planning technique with a sensor fusion-based obstacle detection approach. The dynamic reactive motion planning method assumes a local observer in the virtual plane, which allows the effective transformation of complex dynamic planning problems into simple stationary ones proving the speed and orientation information between the robot and obstacles. In addition, the sensor fusion-based obstacle detection technique allows the pose estimation of moving obstacles using a Kinect sensor and sonar sensors, thus improving the accuracy and robustness of the reactive motion planning approach. The performance of the proposed method was demonstrated through not only simulation studies but also field experiments using multiple moving obstacles in hostile dynamic environments

A Dynamic and Adaptive Selection Radar Tracking Method Based on Information Entropy

Directory of Open Access Journals (Sweden)

Ge Jianjun

2017-12-01

Full Text Available Nowadays, the battlefield environment has become much more complex and variable. This paper presents a quantitative method and lower bound for the amount of target information acquired from multiple radar observations to adaptively and dynamically organize the detection of battlefield resources based on the principle of information entropy. Furthermore, for minimizing the given information entropy’s lower bound for target measurement at every moment, a method to dynamically and adaptively select radars with a high amount of information for target tracking is proposed. The simulation results indicate that the proposed method has higher tracking accuracy than that of tracking without adaptive radar selection based on entropy.

Comparisons of Energy Management Methods for a Parallel Plug-In Hybrid Electric Vehicle between the Convex Optimization and Dynamic Programming

Directory of Open Access Journals (Sweden)

Renxin Xiao

2018-01-01

Full Text Available This paper proposes a comparison study of energy management methods for a parallel plug-in hybrid electric vehicle (PHEV. Based on detailed analysis of the vehicle driveline, quadratic convex functions are presented to describe the nonlinear relationship between engine fuel-rate and battery charging power at different vehicle speed and driveline power demand. The engine-on power threshold is estimated by the simulated annealing (SA algorithm, and the battery power command is achieved by convex optimization with target of improving fuel economy, compared with the dynamic programming (DP based method and the charging depleting–charging sustaining (CD/CS method. In addition, the proposed control methods are discussed at different initial battery state of charge (SOC values to extend the application. Simulation results validate that the proposed strategy based on convex optimization can save the fuel consumption and reduce the computation burden obviously.

Introduction to dynamic programming

CERN Document Server

Cooper, Leon; Rodin, E Y

1981-01-01

Introduction to Dynamic Programming provides information pertinent to the fundamental aspects of dynamic programming. This book considers problems that can be quantitatively formulated and deals with mathematical models of situations or phenomena that exists in the real world.Organized into 10 chapters, this book begins with an overview of the fundamental components of any mathematical optimization model. This text then presents the details of the application of dynamic programming to variational problems. Other chapters consider the application of dynamic programming to inventory theory, Mark

Model-based control strategies for systems with constraints of the program type

Science.gov (United States)

Jarzębowska, Elżbieta

2006-08-01

The paper presents a model-based tracking control strategy for constrained mechanical systems. Constraints we consider can be material and non-material ones referred to as program constraints. The program constraint equations represent tasks put upon system motions and they can be differential equations of orders higher than one or two, and be non-integrable. The tracking control strategy relies upon two dynamic models: a reference model, which is a dynamic model of a system with arbitrary order differential constraints and a dynamic control model. The reference model serves as a motion planner, which generates inputs to the dynamic control model. It is based upon a generalized program motion equations (GPME) method. The method enables to combine material and program constraints and merge them both into the motion equations. Lagrange's equations with multipliers are the peculiar case of the GPME, since they can be applied to systems with constraints of first orders. Our tracking strategy referred to as a model reference program motion tracking control strategy enables tracking of any program motion predefined by the program constraints. It extends the "trajectory tracking" to the "program motion tracking". We also demonstrate that our tracking strategy can be extended to a hybrid program motion/force tracking.

Explicit/multi-parametric model predictive control (MPC) of linear discrete-time systems by dynamic and multi-parametric programming

KAUST Repository

Kouramas, K.I.

2011-08-01

This work presents a new algorithm for solving the explicit/multi- parametric model predictive control (or mp-MPC) problem for linear, time-invariant discrete-time systems, based on dynamic programming and multi-parametric programming techniques. The algorithm features two key steps: (i) a dynamic programming step, in which the mp-MPC problem is decomposed into a set of smaller subproblems in which only the current control, state variables, and constraints are considered, and (ii) a multi-parametric programming step, in which each subproblem is solved as a convex multi-parametric programming problem, to derive the control variables as an explicit function of the states. The key feature of the proposed method is that it overcomes potential limitations of previous methods for solving multi-parametric programming problems with dynamic programming, such as the need for global optimization for each subproblem of the dynamic programming step. © 2011 Elsevier Ltd. All rights reserved.

NONLINEAR FILTER METHOD OF GPS DYNAMIC POSITIONING BASED ON BANCROFT ALGORITHM

Institute of Scientific and Technical Information of China (English)

ZHANGQin; TAOBen-zao; ZHAOChao-ying; WANGLi

2005-01-01

Because of the ignored items after linearization, the extended Kalman filter (EKF) becomes a form of suboptimal gradient descent algorithm. The emanative tendency exists in GPS solution when the filter equations are ill-posed. The deviation in the estimation cannot be avoided. Furthermore, the true solution may be lost in pseudorange positioning because the linearized pseudorange equations are partial solutions. To solve the above problems in GPS dynamic positioning by using EKF, a closed-form Kalman filter method called the two-stage algorithm is presented for the nonlinear algebraic solution of GPS dynamic positioning based on the global nonlinear least squares closed algorithm--Bancroft numerical algorithm of American. The method separates the spatial parts from temporal parts during processing the GPS filter problems, and solves the nonlinear GPS dynamic positioning, thus getting stable and reliable dynamic positioning solutions.

Spatial cluster detection using dynamic programming

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Sverchkov Yuriy

2012-03-01

Full Text Available Abstract Background The task of spatial cluster detection involves finding spatial regions where some property deviates from the norm or the expected value. In a probabilistic setting this task can be expressed as finding a region where some event is significantly more likely than usual. Spatial cluster detection is of interest in fields such as biosurveillance, mining of astronomical data, military surveillance, and analysis of fMRI images. In almost all such applications we are interested both in the question of whether a cluster exists in the data, and if it exists, we are interested in finding the most accurate characterization of the cluster. Methods We present a general dynamic programming algorithm for grid-based spatial cluster detection. The algorithm can be used for both Bayesian maximum a-posteriori (MAP estimation of the most likely spatial distribution of clusters and Bayesian model averaging over a large space of spatial cluster distributions to compute the posterior probability of an unusual spatial clustering. The algorithm is explained and evaluated in the context of a biosurveillance application, specifically the detection and identification of Influenza outbreaks based on emergency department visits. A relatively simple underlying model is constructed for the purpose of evaluating the algorithm, and the algorithm is evaluated using the model and semi-synthetic test data. Results When compared to baseline methods, tests indicate that the new algorithm can improve MAP estimates under certain conditions: the greedy algorithm we compared our method to was found to be more sensitive to smaller outbreaks, while as the size of the outbreaks increases, in terms of area affected and proportion of individuals affected, our method overtakes the greedy algorithm in spatial precision and recall. The new algorithm performs on-par with baseline methods in the task of Bayesian model averaging. Conclusions We conclude that the dynamic

Spacecraft Dynamic Characterization by Strain Energies Method

Science.gov (United States)

Bretagne, J.-M.; Fragnito, M.; Massier, S.

2002-01-01

In the last years the significant increase in satellite broadcasting demand, with the wide band communication dawn, has given a great impulse to the telecommunication satellite market. The big demand is translated from operators (such as SES/Astra, Eutelsat, Intelsat, Inmarsat, EuroSkyWay etc.) in an increase of orders of telecom satellite to the world industrials. The largest part of these telecom satellite orders consists of Geostationary platforms which grow more and more in mass (over 5 tons) due to an ever longer demanded lifetime (up to 20 years), and become more complex due to the need of implementing an ever larger number of repeaters, antenna reflectors and feeds, etc... In this frame, the mechanical design and verification of these large spacecraft become difficult and ambitious at the same time, driven by the dry mass limitation objective. By the Finite Element Method (FEM), and on the basis of the telecom satellite heritage of a world leader constructor such as Alcatel Space Industries it is nowadays possible to model these spacecraft in a realistic and confident way in order to identify the main global dynamic aspects such as mode shapes, mass participation and/or dynamic responses. But on the other hand, one of the main aims consists in identifying soon in a program the most critical aspects of the system behavior in the launch dynamic environment, such as possible dynamic coupling between the different subsystems and secondary structures of the spacecraft (large deployable reflectors, thrusters, etc.). To this aim a numerical method has been developed in the frame of the Alcatel SPACEBUS family program, using MSC/Nastran capabilities and it is presented in this paper. The method is based on Spacecraft sub-structuring and strain energy calculation. The method mainly consists of two steps : 1) subsystem modal strain energy ratio (with respect to the global strain energy); 2) subsystem strain energy calculation for each mode according to the base driven

Methods of choosing the best methods of building a dynamic visualization environment

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В.А. Бородін

2009-02-01

Full Text Available In work is offered the methods of the choice of the most optimum combination of the methods which provides the building of the visual image of the dynamic scenes on the displays of real-time ANGS, which defines the optimal percent of the use for each of m software programs, that are in complex, n methods, optimizing velocity of the image of the visual image. The calculation of the ratio is carried out using the details of this problem to the linear programming problem. In work is offered the calculation of the optimum methods for building a visual image of a dynamic scenes for a specific task.

Probabilistic dual heuristic programming-based adaptive critic

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Herzallah, Randa

2010-02-01

Adaptive critic (AC) methods have common roots as generalisations of dynamic programming for neural reinforcement learning approaches. Since they approximate the dynamic programming solutions, they are potentially suitable for learning in noisy, non-linear and non-stationary environments. In this study, a novel probabilistic dual heuristic programming (DHP)-based AC controller is proposed. Distinct to current approaches, the proposed probabilistic (DHP) AC method takes uncertainties of forward model and inverse controller into consideration. Therefore, it is suitable for deterministic and stochastic control problems characterised by functional uncertainty. Theoretical development of the proposed method is validated by analytically evaluating the correct value of the cost function which satisfies the Bellman equation in a linear quadratic control problem. The target value of the probabilistic critic network is then calculated and shown to be equal to the analytically derived correct value. Full derivation of the Riccati solution for this non-standard stochastic linear quadratic control problem is also provided. Moreover, the performance of the proposed probabilistic controller is demonstrated on linear and non-linear control examples.

Chaotic system optimal tracking using data-based synchronous method with unknown dynamics and disturbances

International Nuclear Information System (INIS)

Song Ruizhuo; Wei Qinglai

2017-01-01

We develop an optimal tracking control method for chaotic system with unknown dynamics and disturbances. The method allows the optimal cost function and the corresponding tracking control to update synchronously. According to the tracking error and the reference dynamics, the augmented system is constructed. Then the optimal tracking control problem is defined. The policy iteration (PI) is introduced to solve the min-max optimization problem. The off-policy adaptive dynamic programming (ADP) algorithm is then proposed to find the solution of the tracking Hamilton–Jacobi–Isaacs (HJI) equation online only using measured data and without any knowledge about the system dynamics. Critic neural network (CNN), action neural network (ANN), and disturbance neural network (DNN) are used to approximate the cost function, control, and disturbance. The weights of these networks compose the augmented weight matrix, and the uniformly ultimately bounded (UUB) of which is proven. The convergence of the tracking error system is also proven. Two examples are given to show the effectiveness of the proposed synchronous solution method for the chaotic system tracking problem. (paper)

Dynamic programming algorithms for biological sequence comparison.

Science.gov (United States)

Pearson, W R; Miller, W

1992-01-01

Efficient dynamic programming algorithms are available for a broad class of protein and DNA sequence comparison problems. These algorithms require computer time proportional to the product of the lengths of the two sequences being compared [O(N2)] but require memory space proportional only to the sum of these lengths [O(N)]. Although the requirement for O(N2) time limits use of the algorithms to the largest computers when searching protein and DNA sequence databases, many other applications of these algorithms, such as calculation of distances for evolutionary trees and comparison of a new sequence to a library of sequence profiles, are well within the capabilities of desktop computers. In particular, the results of library searches with rapid searching programs, such as FASTA or BLAST, should be confirmed by performing a rigorous optimal alignment. Whereas rapid methods do not overlook significant sequence similarities, FASTA limits the number of gaps that can be inserted into an alignment, so that a rigorous alignment may extend the alignment substantially in some cases. BLAST does not allow gaps in the local regions that it reports; a calculation that allows gaps is very likely to extend the alignment substantially. Although a Monte Carlo evaluation of the statistical significance of a similarity score with a rigorous algorithm is much slower than the heuristic approach used by the RDF2 program, the dynamic programming approach should take less than 1 hr on a 386-based PC or desktop Unix workstation. For descriptive purposes, we have limited our discussion to methods for calculating similarity scores and distances that use gap penalties of the form g = rk. Nevertheless, programs for the more general case (g = q+rk) are readily available. Versions of these programs that run either on Unix workstations, IBM-PC class computers, or the Macintosh can be obtained from either of the authors.

Review of various dynamic modeling methods and development of an intuitive modeling method for dynamic systems

International Nuclear Information System (INIS)

Shin, Seung Ki; Seong, Poong Hyun

2008-01-01

Conventional static reliability analysis methods are inadequate for modeling dynamic interactions between components of a system. Various techniques such as dynamic fault tree, dynamic Bayesian networks, and dynamic reliability block diagrams have been proposed for modeling dynamic systems based on improvement of the conventional modeling methods. In this paper, we review these methods briefly and introduce dynamic nodes to the existing Reliability Graph with General Gates (RGGG) as an intuitive modeling method to model dynamic systems. For a quantitative analysis, we use a discrete-time method to convert an RGGG to an equivalent Bayesian network and develop a software tool for generation of probability tables

Efficient generalized Golub-Kahan based methods for dynamic inverse problems

Science.gov (United States)

Chung, Julianne; Saibaba, Arvind K.; Brown, Matthew; Westman, Erik

2018-02-01

We consider efficient methods for computing solutions to and estimating uncertainties in dynamic inverse problems, where the parameters of interest may change during the measurement procedure. Compared to static inverse problems, incorporating prior information in both space and time in a Bayesian framework can become computationally intensive, in part, due to the large number of unknown parameters. In these problems, explicit computation of the square root and/or inverse of the prior covariance matrix is not possible, so we consider efficient, iterative, matrix-free methods based on the generalized Golub-Kahan bidiagonalization that allow automatic regularization parameter and variance estimation. We demonstrate that these methods for dynamic inversion can be more flexible than standard methods and develop efficient implementations that can exploit structure in the prior, as well as possible structure in the forward model. Numerical examples from photoacoustic tomography, space-time deblurring, and passive seismic tomography demonstrate the range of applicability and effectiveness of the described approaches. Specifically, in passive seismic tomography, we demonstrate our approach on both synthetic and real data. To demonstrate the scalability of our algorithm, we solve a dynamic inverse problem with approximately 43 000 measurements and 7.8 million unknowns in under 40 s on a standard desktop.

Dynamic Obstacle Avoidance for Unmanned Underwater Vehicles Based on an Improved Velocity Obstacle Method

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Wei Zhang

2017-11-01

Full Text Available In view of a dynamic obstacle environment with motion uncertainty, we present a dynamic collision avoidance method based on the collision risk assessment and improved velocity obstacle method. First, through the fusion optimization of forward-looking sonar data, the redundancy of the data is reduced and the position, size and velocity information of the obstacles are obtained, which can provide an accurate decision-making basis for next-step collision avoidance. Second, according to minimum meeting time and the minimum distance between the obstacle and unmanned underwater vehicle (UUV, this paper establishes the collision risk assessment model, and screens key obstacles to avoid collision. Finally, the optimization objective function is established based on the improved velocity obstacle method, and a UUV motion characteristic is used to calculate the reachable velocity sets. The optimal collision speed of UUV is searched in velocity space. The corresponding heading and speed commands are calculated, and outputted to the motion control module. The above is the complete dynamic obstacle avoidance process. The simulation results show that the proposed method can obtain a better collision avoidance effect in the dynamic environment, and has good adaptability to the unknown dynamic environment.

Dynamic Positioning Capability Analysis for Marine Vessels Based on A DPCap Polar Plot Program

Science.gov (United States)

Wang, Lei; Yang, Jian-min; Xu, Sheng-wen

2018-03-01

Dynamic positioning capability (DPCap) analysis is essential in the selection of thrusters, in their configuration, and during preliminary investigation of the positioning ability of a newly designed vessel dynamic positioning system. DPCap analysis can help determine the maximum environmental forces, in which the DP system can counteract in given headings. The accuracy of the DPCap analysis is determined by the precise estimation of the environmental forces as well as the effectiveness of the thrust allocation logic. This paper is dedicated to developing an effective and efficient software program for the DPCap analysis for marine vessels. Estimation of the environmental forces can be obtained by model tests, hydrodynamic computation and empirical formulas. A quadratic programming method is adopted to allocate the total thrust on every thruster of the vessel. A detailed description of the thrust allocation logic of the software program is given. The effectiveness of the new program DPCap Polar Plot (DPCPP) was validated by a DPCap analysis for a supply vessel. The present study indicates that the developed program can be used in the DPCap analysis for marine vessels. Moreover, DPCap analysis considering the thruster failure mode might give guidance to the designers of vessels whose thrusters need to be safer.

Analysis of the Multi Strategy Goal Programming for Micro-Grid Based on Dynamic ant Genetic Algorithm

Science.gov (United States)

Qiu, J. P.; Niu, D. X.

Micro-grid is one of the key technologies of the future energy supplies. Take economic planning. reliability, and environmental protection of micro grid as a basis for the analysis of multi-strategy objective programming problems for micro grid which contains wind power, solar power, and battery and micro gas turbine. Establish the mathematical model of each power generation characteristics and energy dissipation. and change micro grid planning multi-objective function under different operating strategies to a single objective model based on AHP method. Example analysis shows that in combination with dynamic ant mixed genetic algorithm can get the optimal power output of this model.

The application of dynamic programming in production planning

Science.gov (United States)

Wu, Run

2017-05-01

Nowadays, with the popularity of the computers, various industries and fields are widely applying computer information technology, which brings about huge demand for a variety of application software. In order to develop software meeting various needs with most economical cost and best quality, programmers must design efficient algorithms. A superior algorithm can not only soul up one thing, but also maximize the benefits and generate the smallest overhead. As one of the common algorithms, dynamic programming algorithms are used to solving problems with some sort of optimal properties. When solving problems with a large amount of sub-problems that needs repetitive calculations, the ordinary sub-recursive method requires to consume exponential time, and dynamic programming algorithm can reduce the time complexity of the algorithm to the polynomial level, according to which we can conclude that dynamic programming algorithm is a very efficient compared to other algorithms reducing the computational complexity and enriching the computational results. In this paper, we expound the concept, basic elements, properties, core, solving steps and difficulties of the dynamic programming algorithm besides, establish the dynamic programming model of the production planning problem.

A dynamic programming approach to missing data estimation using neural networks

CSIR Research Space (South Africa)

Nelwamondo, FV

2013-01-01

Full Text Available method where dynamic programming is not used. This paper also suggests a different way of formulating a missing data problem such that the dynamic programming is applicable to estimate the missing data....

An evolutionary programming based simulated annealing method for solving the unit commitment problem

Energy Technology Data Exchange (ETDEWEB)

Christober Asir Rajan, C. [Department of EEE, Pondicherry Engineering College, Pondicherry 605014 (India); Mohan, M.R. [Department of EEE, Anna University, Chennai 600 025 (India)

2007-09-15

This paper presents a new approach to solve the short-term unit commitment problem using an evolutionary programming based simulated annealing method. The objective of this paper is to find the generation scheduling such that the total operating cost can be minimized, when subjected to a variety of constraints. This also means that it is desirable to find the optimal generating unit commitment in the power system for the next H hours. Evolutionary programming, which happens to be a global optimisation technique for solving unit commitment Problem, operates on a system, which is designed to encode each unit's operating schedule with regard to its minimum up/down time. In this, the unit commitment schedule is coded as a string of symbols. An initial population of parent solutions is generated at random. Here, each schedule is formed by committing all the units according to their initial status (''flat start''). Here the parents are obtained from a pre-defined set of solution's, i.e. each and every solution is adjusted to meet the requirements. Then, a random recommitment is carried out with respect to the unit's minimum down times. And SA improves the status. The best population is selected by evolutionary strategy. The Neyveli Thermal Power Station (NTPS) Unit-II in India demonstrates the effectiveness of the proposed approach; extensive studies have also been performed for different power systems consists of 10, 26, 34 generating units. Numerical results are shown comparing the cost solutions and computation time obtained by using the Evolutionary Programming method and other conventional methods like Dynamic Programming, Lagrangian Relaxation and Simulated Annealing and Tabu Search in reaching proper unit commitment. (author)

INDDGO: Integrated Network Decomposition & Dynamic programming for Graph Optimization

Energy Technology Data Exchange (ETDEWEB)

Groer, Christopher S [ORNL; Sullivan, Blair D [ORNL; Weerapurage, Dinesh P [ORNL

2012-10-01

It is well-known that dynamic programming algorithms can utilize tree decompositions to provide a way to solve some \\emph{NP}-hard problems on graphs where the complexity is polynomial in the number of nodes and edges in the graph, but exponential in the width of the underlying tree decomposition. However, there has been relatively little computational work done to determine the practical utility of such dynamic programming algorithms. We have developed software to construct tree decompositions using various heuristics and have created a fast, memory-efficient dynamic programming implementation for solving maximum weighted independent set. We describe our software and the algorithms we have implemented, focusing on memory saving techniques for the dynamic programming. We compare the running time and memory usage of our implementation with other techniques for solving maximum weighted independent set, including a commercial integer programming solver and a semi-definite programming solver. Our results indicate that it is possible to solve some instances where the underlying decomposition has width much larger than suggested by the literature. For certain types of problems, our dynamic programming code runs several times faster than these other methods.

Students’ Views about the Problem Based Collaborative Learning Environment Supported By Dynamic Web Technologies

Directory of Open Access Journals (Sweden)

Erhan ÜNAL

2017-04-01

Full Text Available The purpose of this study is to design a problem based collaborative learning environment supported by dynamic web technologies and examine students’ views about this learning environment. The study was designed as a qualitative research. 36 students who took Object Oriented Programming I-II course from a public university at the department of computer programming participated in the study. During the research process, the Object Oriented Programming I-II course was designed with incorporating different dynamic web technologies (Edmodo, Google Services, and Mind42 and Nelson (1999’s collaborative problem solving method. At the end of the course, there were focus group interviews in regards to the students’ views on a learning environment supported by dynamic web technologies and collaborative problem solving method. At the end of the focus group interviews, 4 themes were obtained from the students’ views, including positive aspects of the learning environment, difficulties faced in the learning environment, advantages of the learning environment, and skills gained as a result of the project. The results suggest that problem based collaborative learning methods and dynamic web technologies can be used in learning environments in community colleges.

A Total Variation-Based Reconstruction Method for Dynamic MRI

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Germana Landi

2008-01-01

Full Text Available In recent years, total variation (TV regularization has become a popular and powerful tool for image restoration and enhancement. In this work, we apply TV minimization to improve the quality of dynamic magnetic resonance images. Dynamic magnetic resonance imaging is an increasingly popular clinical technique used to monitor spatio-temporal changes in tissue structure. Fast data acquisition is necessary in order to capture the dynamic process. Most commonly, the requirement of high temporal resolution is fulfilled by sacrificing spatial resolution. Therefore, the numerical methods have to address the issue of images reconstruction from limited Fourier data. One of the most successful techniques for dynamic imaging applications is the reduced-encoded imaging by generalized-series reconstruction method of Liang and Lauterbur. However, even if this method utilizes a priori data for optimal image reconstruction, the produced dynamic images are degraded by truncation artifacts, most notably Gibbs ringing, due to the spatial low resolution of the data. We use a TV regularization strategy in order to reduce these truncation artifacts in the dynamic images. The resulting TV minimization problem is solved by the fixed point iteration method of Vogel and Oman. The results of test problems with simulated and real data are presented to illustrate the effectiveness of the proposed approach in reducing the truncation artifacts of the reconstructed images.

Dynamic Allan Variance Analysis Method with Time-Variant Window Length Based on Fuzzy Control

Directory of Open Access Journals (Sweden)

Shanshan Gu

2015-01-01

Full Text Available To solve the problem that dynamic Allan variance (DAVAR with fixed length of window cannot meet the identification accuracy requirement of fiber optic gyro (FOG signal over all time domains, a dynamic Allan variance analysis method with time-variant window length based on fuzzy control is proposed. According to the characteristic of FOG signal, a fuzzy controller with the inputs of the first and second derivatives of FOG signal is designed to estimate the window length of the DAVAR. Then the Allan variances of the signals during the time-variant window are simulated to obtain the DAVAR of the FOG signal to describe the dynamic characteristic of the time-varying FOG signal. Additionally, a performance evaluation index of the algorithm based on radar chart is proposed. Experiment results show that, compared with different fixed window lengths DAVAR methods, the change of FOG signal with time can be identified effectively and the evaluation index of performance can be enhanced by 30% at least by the DAVAR method with time-variant window length based on fuzzy control.

Decomposition and Cross-Product-Based Method for Computing the Dynamic Equation of Robots

Directory of Open Access Journals (Sweden)

Ching-Long Shih

2012-08-01

Full Text Available This paper aims to demonstrate a clear relationship between Lagrange equations and Newton-Euler equations regarding computational methods for robot dynamics, from which we derive a systematic method for using either symbolic or on-line numerical computations. Based on the decomposition approach and cross-product operation, a computing method for robot dynamics can be easily developed. The advantages of this computing framework are that: it can be used for both symbolic and on-line numeric computation purposes, and it can also be applied to biped systems, as well as some simple closed-chain robot systems.

Separable programming theory and methods

CERN Document Server

Stefanov, Stefan M

2001-01-01

In this book, the author considers separable programming and, in particular, one of its important cases - convex separable programming Some general results are presented, techniques of approximating the separable problem by linear programming and dynamic programming are considered Convex separable programs subject to inequality equality constraint(s) and bounds on variables are also studied and iterative algorithms of polynomial complexity are proposed As an application, these algorithms are used in the implementation of stochastic quasigradient methods to some separable stochastic programs Numerical approximation with respect to I1 and I4 norms, as a convex separable nonsmooth unconstrained minimization problem, is considered as well Audience Advanced undergraduate and graduate students, mathematical programming operations research specialists

Adaptive dynamic programming for discrete-time linear quadratic regulation based on multirate generalised policy iteration

Science.gov (United States)

Chun, Tae Yoon; Lee, Jae Young; Park, Jin Bae; Choi, Yoon Ho

2018-06-01

In this paper, we propose two multirate generalised policy iteration (GPI) algorithms applied to discrete-time linear quadratic regulation problems. The proposed algorithms are extensions of the existing GPI algorithm that consists of the approximate policy evaluation and policy improvement steps. The two proposed schemes, named heuristic dynamic programming (HDP) and dual HDP (DHP), based on multirate GPI, use multi-step estimation (M-step Bellman equation) at the approximate policy evaluation step for estimating the value function and its gradient called costate, respectively. Then, we show that these two methods with the same update horizon can be considered equivalent in the iteration domain. Furthermore, monotonically increasing and decreasing convergences, so called value iteration (VI)-mode and policy iteration (PI)-mode convergences, are proved to hold for the proposed multirate GPIs. Further, general convergence properties in terms of eigenvalues are also studied. The data-driven online implementation methods for the proposed HDP and DHP are demonstrated and finally, we present the results of numerical simulations performed to verify the effectiveness of the proposed methods.

Physical models and numerical methods of the reactor dynamic computer program RETRAN

International Nuclear Information System (INIS)

Kamelander, G.; Woloch, F.; Sdouz, G.; Koinig, H.

1984-03-01

This report describes the physical models and the numerical methods of the reactor dynamic code RETRAN simulating reactivity transients in Light-Water-Reactors. The neutron-physical part of RETRAN bases on the two-group-diffusion equations which are solved by discretization similar to the TWIGL-method. An exponential transformation is applied and the inner iterations are accelerated by a coarse-mesh-rebalancing procedure. The thermo-hydraulic model approximates the equation of state by a built-in steam-water-table and disposes of options for the calculation of heat-conduction coefficients and heat transfer coefficients. (Author) [de

Development of Quadratic Programming Algorithm Based on Interior Point Method with Estimation Mechanism of Active Constraints

Science.gov (United States)

Hashimoto, Hiroyuki; Takaguchi, Yusuke; Nakamura, Shizuka

Instability of calculation process and increase of calculation time caused by increasing size of continuous optimization problem remain the major issues to be solved to apply the technique to practical industrial systems. This paper proposes an enhanced quadratic programming algorithm based on interior point method mainly for improvement of calculation stability. The proposed method has dynamic estimation mechanism of active constraints on variables, which fixes the variables getting closer to the upper/lower limit on them and afterwards releases the fixed ones as needed during the optimization process. It is considered as algorithm-level integration of the solution strategy of active-set method into the interior point method framework. We describe some numerical results on commonly-used bench-mark problems called “CUTEr” to show the effectiveness of the proposed method. Furthermore, the test results on large-sized ELD problem (Economic Load Dispatching problems in electric power supply scheduling) are also described as a practical industrial application.

Bellman's GAP--a language and compiler for dynamic programming in sequence analysis.

Science.gov (United States)

Sauthoff, Georg; Möhl, Mathias; Janssen, Stefan; Giegerich, Robert

2013-03-01

Dynamic programming is ubiquitous in bioinformatics. Developing and implementing non-trivial dynamic programming algorithms is often error prone and tedious. Bellman's GAP is a new programming system, designed to ease the development of bioinformatics tools based on the dynamic programming technique. In Bellman's GAP, dynamic programming algorithms are described in a declarative style by tree grammars, evaluation algebras and products formed thereof. This bypasses the design of explicit dynamic programming recurrences and yields programs that are free of subscript errors, modular and easy to modify. The declarative modules are compiled into C++ code that is competitive to carefully hand-crafted implementations. This article introduces the Bellman's GAP system and its language, GAP-L. It then demonstrates the ease of development and the degree of re-use by creating variants of two common bioinformatics algorithms. Finally, it evaluates Bellman's GAP as an implementation platform of 'real-world' bioinformatics tools. Bellman's GAP is available under GPL license from http://bibiserv.cebitec.uni-bielefeld.de/bellmansgap. This Web site includes a repository of re-usable modules for RNA folding based on thermodynamics.

Direct heuristic dynamic programming for damping oscillations in a large power system.

Science.gov (United States)

Lu, Chao; Si, Jennie; Xie, Xiaorong

2008-08-01

This paper applies a neural-network-based approximate dynamic programming method, namely, the direct heuristic dynamic programming (direct HDP), to a large power system stability control problem. The direct HDP is a learning- and approximation-based approach to addressing nonlinear coordinated control under uncertainty. One of the major design parameters, the controller learning objective function, is formulated to directly account for network-wide low-frequency oscillation with the presence of nonlinearity, uncertainty, and coupling effect among system components. Results include a novel learning control structure based on the direct HDP with applications to two power system problems. The first case involves static var compensator supplementary damping control, which is used to provide a comprehensive evaluation of the learning control performance. The second case aims at addressing a difficult complex system challenge by providing a new solution to a large interconnected power network oscillation damping control problem that frequently occurs in the China Southern Power Grid.

A short note on dynamic programming in a band.

Science.gov (United States)

Gibrat, Jean-François

2018-06-15

Third generation sequencing technologies generate long reads that exhibit high error rates, in particular for insertions and deletions which are usually the most difficult errors to cope with. The only exact algorithm capable of aligning sequences with insertions and deletions is a dynamic programming algorithm. In this note, for the sake of efficiency, we consider dynamic programming in a band. We show how to choose the band width in function of the long reads' error rates, thus obtaining an [Formula: see text] algorithm in space and time. We also propose a procedure to decide whether this algorithm, when applied to semi-global alignments, provides the optimal score. We suggest that dynamic programming in a band is well suited to the problem of aligning long reads between themselves and can be used as a core component of methods for obtaining a consensus sequence from the long reads alone. The function implementing the dynamic programming algorithm in a band is available, as a standalone program, at: https://forgemia.inra.fr/jean-francois.gibrat/BAND_DYN_PROG.git.

Evaluation of Electric Power Procurement Strategies by Stochastic Dynamic Programming

Science.gov (United States)

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

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

Planar multibody dynamics formulation, programming and applications

CERN Document Server

Nikravesh, Parviz E

2007-01-01

Introduction Multibody Mechanical Systems Types of Analyses Methods of Formulation Computer Programming Application Examples Unit System Remarks Preliminaries Reference Axes Scalars and Vectors Matrices Vector, Array, and Matrix Differentiation Equations and Expressions Remarks Problems Fundamentals of Kinematics A Particle Kinematics of a Rigid Body Definitions Remarks Problems Fundamentals of Dynamics Newton's Laws of Motion Dynamics of a Body Force Elements Applied Forces Reaction Force Remarks Problems Point-Coordinates: Kinematics Multipoint

A composite experimental dynamic substructuring method based on partitioned algorithms and localized Lagrange multipliers

Science.gov (United States)

Abbiati, Giuseppe; La Salandra, Vincenzo; Bursi, Oreste S.; Caracoglia, Luca

2018-02-01

Successful online hybrid (numerical/physical) dynamic substructuring simulations have shown their potential in enabling realistic dynamic analysis of almost any type of non-linear structural system (e.g., an as-built/isolated viaduct, a petrochemical piping system subjected to non-stationary seismic loading, etc.). Moreover, owing to faster and more accurate testing equipment, a number of different offline experimental substructuring methods, operating both in time (e.g. the impulse-based substructuring) and frequency domains (i.e. the Lagrange multiplier frequency-based substructuring), have been employed in mechanical engineering to examine dynamic substructure coupling. Numerous studies have dealt with the above-mentioned methods and with consequent uncertainty propagation issues, either associated with experimental errors or modelling assumptions. Nonetheless, a limited number of publications have systematically cross-examined the performance of the various Experimental Dynamic Substructuring (EDS) methods and the possibility of their exploitation in a complementary way to expedite a hybrid experiment/numerical simulation. From this perspective, this paper performs a comparative uncertainty propagation analysis of three EDS algorithms for coupling physical and numerical subdomains with a dual assembly approach based on localized Lagrange multipliers. The main results and comparisons are based on a series of Monte Carlo simulations carried out on a five-DoF linear/non-linear chain-like systems that include typical aleatoric uncertainties emerging from measurement errors and excitation loads. In addition, we propose a new Composite-EDS (C-EDS) method to fuse both online and offline algorithms into a unique simulator. Capitalizing from the results of a more complex case study composed of a coupled isolated tank-piping system, we provide a feasible way to employ the C-EDS method when nonlinearities and multi-point constraints are present in the emulated system.

A coherency-based method to increase dynamic security in power systems

Energy Technology Data Exchange (ETDEWEB)

De Tuglie, E. [Dipartimento di Ingegneria dell' Ambiente e per lo Sviluppo Sostenibile - DIASS, Politecnico di Bari, Viale del Turismo 8, 74100 Taranto (Italy); Iannone, S.M.; Torelli, F. [Dipartimento di Elettrotecnica ed Elettronica - DEE, Politecnico di Bari, Via Re David 200, 70125 Bari (Italy)

2008-08-15

Dynamic security analysis is the evaluation of the ability of a system to withstand contingencies by surviving transient conditions to acceptable steady-state operative states. When potential instability due to contingency is detected, preventive action may be desired to improve the system security. This is very important in the on-line operation of a power system, especially when the system is stability-limited. The method proposed in this paper is based on the idea that increasing coherency between generators in the transient behaviour following a system perturbation gives rise to a more stable system. In this paper, we suggest the use of the ''input-output feedback-linearization'' with a reference trajectory obtained using a system dynamic equivalent based on the centre of inertia. To quantify coherency levels a new coherency indicator has been assumed for the given reference trajectory. The result is an increasing level in coherency, critical clearing time and system stability. The method is tested on the IEEE 30 bus test system. (author)

Optimization of Algorithms Using Extensions of Dynamic Programming

KAUST Repository

AbouEisha, Hassan M.

2017-04-09

We study and answer questions related to the complexity of various important problems such as: multi-frontal solvers of hp-adaptive finite element method, sorting and majority. We advocate the use of dynamic programming as a viable tool to study optimal algorithms for these problems. The main approach used to attack these problems is modeling classes of algorithms that may solve this problem using a discrete model of computation then defining cost functions on this discrete structure that reflect different complexity measures of the represented algorithms. As a last step, dynamic programming algorithms are designed and used to optimize those models (algorithms) and to obtain exact results on the complexity of the studied problems. The first part of the thesis presents a novel model of computation (element partition tree) that represents a class of algorithms for multi-frontal solvers along with cost functions reflecting various complexity measures such as: time and space. It then introduces dynamic programming algorithms for multi-stage and bi-criteria optimization of element partition trees. In addition, it presents results based on optimal element partition trees for famous benchmark meshes such as: meshes with point and edge singularities. New improved heuristics for those benchmark meshes were ob- tained based on insights of the optimal results found by our algorithms. The second part of the thesis starts by introducing a general problem where different problems can be reduced to and show how to use a decision table to model such problem. We describe how decision trees and decision tests for this table correspond to adaptive and non-adaptive algorithms for the original problem. We present exact bounds on the average time complexity of adaptive algorithms for the eight elements sorting problem. Then bounds on adaptive and non-adaptive algorithms for a variant of the majority problem are introduced. Adaptive algorithms are modeled as decision trees whose depth

EP BASED PSO METHOD FOR SOLVING PROFIT BASED MULTI AREA UNIT COMMITMENT PROBLEM

Directory of Open Access Journals (Sweden)

K. VENKATESAN

2015-04-01

Full Text Available This paper presents a new approach to solve the profit based multi area unit commitment problem (PBMAUCP using an evolutionary programming based particle swarm optimization (EPPSO method. The objective of this paper is to maximize the profit of generation companies (GENCOs with considering system social benefit. The proposed method helps GENCOs to make a decision, how much power and reserve should be sold in markets, and how to schedule generators in order to receive the maximum profit. Joint operation of generation resources can result in significant operational cost savings. Power transfer between the areas through the tie lines depends upon the operating cost of generation at each hour and tie line transfer limits. The tie line transfer limits were considered as a set of constraints during optimization process to ensure the system security and reliability. The overall algorithm can be implemented on an IBM PC, which can process a fairly large system in a reasonable period of time. Case study of four areas with different load pattern each containing 7 units (NTPS and 26 units connected via tie lines have been taken for analysis. Numerical results showed comparing the profit of evolutionary programming-based particle swarm optimization method (EPPSO with conventional dynamic programming (DP, evolutionary programming (EP, and particle swarm optimization (PSO method. Experimental results shows that the application of this evolutionary programming based particle swarm optimization method have the potential to solve profit based multi area unit commitment problem with lesser computation time.

MyDTW - Dynamic Time Warping program for stratigraphical time series

Science.gov (United States)

Kotov, Sergey; Paelike, Heiko

2017-04-01

One of the general tasks in many geological disciplines is matching of one time or space signal to another. It can be classical correlation between two cores or cross-sections in sedimentology or marine geology. For example, tuning a paleoclimatic signal to a target curve, driven by variations in the astronomical parameters, is a powerful technique to construct accurate time scales. However, these methods can be rather time-consuming and can take ours of routine work even with the help of special semi-automatic software. Therefore, different approaches to automate the processes have been developed during last decades. Some of them are based on classical statistical cross-correlations such as the 'Correlator' after Olea [1]. Another ones use modern ideas of dynamic programming. A good example is as an algorithm developed by Lisiecki and Lisiecki [2] or dynamic time warping based algorithm after Pälike [3]. We introduce here an algorithm and computer program, which are also stemmed from the Dynamic Time Warping algorithm class. Unlike the algorithm of Lisiecki and Lisiecki, MyDTW does not lean on a set of penalties to follow geological logics, but on a special internal structure and specific constrains. It differs also from [3] in basic ideas of implementation and constrains design. The algorithm is implemented as a computer program with a graphical user interface using Free Pascal and Lazarus IDE and available for Windows, Mac OS, and Linux. Examples with synthetic and real data are demonstrated. Program is available for free download at http://www.marum.de/Sergey_Kotov.html . References: 1. Olea, R.A. Expert systems for automated correlation and interpretation of wireline logs // Math Geol (1994) 26: 879. doi:10.1007/BF02083420 2. Lisiecki L. and Lisiecki P. Application of dynamic programming to the correlation of paleoclimate records // Paleoceanography (2002), Volume 17, Issue 4, pp. 1-1, CiteID 1049, doi: 10.1029/2001PA000733 3. Pälike, H. Extending the

Introduction to stochastic dynamic programming

CERN Document Server

Ross, Sheldon M; Lukacs, E

1983-01-01

Introduction to Stochastic Dynamic Programming presents the basic theory and examines the scope of applications of stochastic dynamic programming. The book begins with a chapter on various finite-stage models, illustrating the wide range of applications of stochastic dynamic programming. Subsequent chapters study infinite-stage models: discounting future returns, minimizing nonnegative costs, maximizing nonnegative returns, and maximizing the long-run average return. Each of these chapters first considers whether an optimal policy need exist-providing counterexamples where appropriate-and the

Dynamic Programming Approaches for the Traveling Salesman Problem with Drone

OpenAIRE

Bouman, Paul; Agatz, Niels; Schmidt, Marie

2017-01-01

markdownabstractA promising new delivery model involves the use of a delivery truck that collaborates with a drone to make deliveries. Effectively combining a drone and a truck gives rise to a new planning problem that is known as the Traveling Salesman Problem with Drone (TSP-D). This paper presents an exact solution approach for the TSP-D based on dynamic programming and present experimental results of different dynamic programming based heuristics. Our numerical experiments show that our a...

Optimal blood glucose level control using dynamic programming based on minimal Bergman model

Science.gov (United States)

Rettian Anggita Sari, Maria; Hartono

2018-03-01

The purpose of this article is to simulate the glucose dynamic and the insulin kinetic of diabetic patient. The model used in this research is a non-linear Minimal Bergman model. Optimal control theory is then applied to formulate the problem in order to determine the optimal dose of insulin in the treatment of diabetes mellitus such that the glucose level is in the normal range for some specific time range. The optimization problem is solved using dynamic programming. The result shows that dynamic programming is quite reliable to represent the interaction between glucose and insulin levels in diabetes mellitus patient.

A New Method Based on Simulation-Optimization Approach to Find Optimal Solution in Dynamic Job-shop Scheduling Problem with Breakdown and Rework

Directory of Open Access Journals (Sweden)

Farzad Amirkhani

2017-03-01

The proposed method is implemented on classical job-shop problems with objective of makespan and results are compared with mixed integer programming model. Moreover, the appropriate dispatching priorities are achieved for dynamic job-shop problem minimizing a multi-objective criteria. The results show that simulation-based optimization are highly capable to capture the main characteristics of the shop and produce optimal/near-optimal solutions with highly credibility degree.

Dynamic RCS Simulation of a Missile Target Group Based on the High-frequency Asymptotic Method

Directory of Open Access Journals (Sweden)

Zhao Tao

2014-04-01

Full Text Available To simulate dynamic Radar Cross Section (RCS of missile target group, an efficient RCS prediction approach is proposed based on the high-frequency asymptotic theory. The minimal energy trajectory and coordinate transformation is used to get trajectories of the missile, decoys and roll booster, and establish the dynamic scene for the separate procedure of the target group, and the dynamic RCS including specular reflection, edge diffraction and multi-reflection from the target group are obtained by Physical Optics (PO, Equivalent Edge Currents (EEC and Shooting-and-Bouncing Ray (SBR methods. Compared with the dynamic RCS result with the common interpolation method, the proposed method is consistent with the common method when the targets in the scene are far away from each other and each target is not sheltered by others in the incident direction. When the target group is densely distributed and the shelter effect can not be neglected, the interpolation method is extremely difficult to realize, whereas the proposed method is successful.

Approximate Dynamic Programming Based on High Dimensional Model Representation

Czech Academy of Sciences Publication Activity Database

Pištěk, Miroslav

2013-01-01

Roč. 49, č. 5 (2013), s. 720-737 ISSN 0023-5954 R&D Projects: GA ČR(CZ) GAP102/11/0437 Institutional support: RVO:67985556 Keywords : approximate dynamic programming * Bellman equation * approximate HDMR minimization * trust region problem Subject RIV: BC - Control Systems Theory Impact factor: 0.563, year: 2013 http://library.utia.cas.cz/separaty/2013/AS/pistek-0399560.pdf

Optimal Operation of Radial Distribution Systems Using Extended Dynamic Programming

DEFF Research Database (Denmark)

Lopez, Juan Camilo; Vergara, Pedro P.; Lyra, Christiano

2018-01-01

An extended dynamic programming (EDP) approach is developed to optimize the ac steady-state operation of radial electrical distribution systems (EDS). Based on the optimality principle of the recursive Hamilton-Jacobi-Bellman equations, the proposed EDP approach determines the optimal operation o...... approach is illustrated using real-scale systems and comparisons with commercial programming solvers. Finally, generalizations to consider other EDS operation problems are also discussed.......An extended dynamic programming (EDP) approach is developed to optimize the ac steady-state operation of radial electrical distribution systems (EDS). Based on the optimality principle of the recursive Hamilton-Jacobi-Bellman equations, the proposed EDP approach determines the optimal operation...... of the EDS by setting the values of the controllable variables at each time period. A suitable definition for the stages of the problem makes it possible to represent the optimal ac power flow of radial EDS as a dynamic programming problem, wherein the 'curse of dimensionality' is a minor concern, since...

Supervision and prognosis architecture based on dynamical classification method for the predictive maintenance of dynamical evolving systems

International Nuclear Information System (INIS)

Traore, M.; Chammas, A.; Duviella, E.

2015-01-01

In this paper, we are concerned by the improvement of the safety, availability and reliability of dynamical systems’ components subjected to slow degradations (slow drifts). We propose an architecture for efficient Predictive Maintenance (PM) according to the real time estimate of the future state of the components. The architecture is built on supervision and prognosis tools. The prognosis method is based on an appropriated supervision technique that consists in drift tracking of the dynamical systems using AUDyC (AUto-adaptive and Dynamical Clustering), that is an auto-adaptive dynamical classifier. Thus, due to the complexity and the dynamical of the considered systems, the Failure Mode Effect and Criticity Analysis (FMECA) is used to identify the key components of the systems. A component is defined as an element of the system that can be impacted by only one failure. A failure of a key component causes a long downtime of the system. From the FMECA, a Fault Tree Analysis (FTA) of the system are built to determine the propagation laws of a failure on the system by using a deductive method. The proposed architecture is implemented for the PM of a thermoregulator. The application on this real system highlights the interests and the performances of the proposed architecture

Adopting an Evidence-Based Lifestyle Physical Activity Program: Dissemination Study Design and Methods.

Science.gov (United States)

Dunn, Andrea L; Buller, David B; Dearing, James W; Cutter, Gary; Guerra, Michele; Wilcox, Sara; Bettinghaus, Erwin P

2012-06-01

BACKGROUND: There is a scarcity of research studies that have examined academic-commercial partnerships to disseminate evidence-based physical activity programs. Understanding this approach to dissemination is essential because academic-commercial partnerships are increasingly common. Private companies have used dissemination channels and strategies to a degree that academicians have not, and declining resources require academicians to explore these partnerships. PURPOSE: This paper describes a retrospective case-control study design including the methods, demographics, organizational decision-making, implementation rates, and marketing strategy for Active Living Every Day (ALED), an evidence-based lifestyle physical activity program that has been commercially available since 2001. Evidence-based public health promotion programs rely on organizations and targeted sectors to disseminate these programs although relatively little is known about organizational-level and sector-level influences that lead to their adoption and implementation. METHODS: Cases (n=154) were eligible if they had signed an ALED license agreement with Human Kinetics (HK), publisher of the program's textbooks and facilitator manuals, between 2001 and 2008. Two types of controls were matched (2:2:1) and stratified by sector and region. Active controls (Control 1; n=319) were organizations that contacted HK to consider adopting ALED. Passive controls (Control 2; n=328) were organizations that received unsolicited marketing materials and did not initiate contact with HK. We used Diffusion of Innovations Theory (DIT) constructs as the basis for developing the survey of cases and controls. RESULTS: Using the multi-method strategy recommended by Dillman, a total of n=801 cases and controls were surveyed. Most organizations were from the fitness sector followed by medical, nongovernmental, governmental, educational, worksite and other sectors with significantly higher response rates from government

Stochastic integer programming by dynamic programming

NARCIS (Netherlands)

Lageweg, B.J.; Lenstra, J.K.; Rinnooy Kan, A.H.G.; Stougie, L.; Ermoliev, Yu.; Wets, R.J.B.

1988-01-01

Stochastic integer programming is a suitable tool for modeling hierarchical decision situations with combinatorial features. In continuation of our work on the design and analysis of heuristics for such problems, we now try to find optimal solutions. Dynamic programming techniques can be used to

Application of Dynamic Analysis in Semi-Analytical Finite Element Method.

Science.gov (United States)

Liu, Pengfei; Xing, Qinyan; Wang, Dawei; Oeser, Markus

2017-08-30

Analyses of dynamic responses are significantly important for the design, maintenance and rehabilitation of asphalt pavement. In order to evaluate the dynamic responses of asphalt pavement under moving loads, a specific computational program, SAFEM, was developed based on a semi-analytical finite element method. This method is three-dimensional and only requires a two-dimensional FE discretization by incorporating Fourier series in the third dimension. In this paper, the algorithm to apply the dynamic analysis to SAFEM was introduced in detail. Asphalt pavement models under moving loads were built in the SAFEM and commercial finite element software ABAQUS to verify the accuracy and efficiency of the SAFEM. The verification shows that the computational accuracy of SAFEM is high enough and its computational time is much shorter than ABAQUS. Moreover, experimental verification was carried out and the prediction derived from SAFEM is consistent with the measurement. Therefore, the SAFEM is feasible to reliably predict the dynamic response of asphalt pavement under moving loads, thus proving beneficial to road administration in assessing the pavement's state.

A conceptual framework for formulating a focused and cost-effective fire protection program based on analyses of risk and the dynamics of fire effects

International Nuclear Information System (INIS)

Dey, M.K.

1999-01-01

This paper proposes a conceptual framework for developing a fire protection program at nuclear power plants based on probabilistic risk analysis (PRA) of fire hazards, and modeling the dynamics of fire effects. The process for categorizing nuclear power plant fire areas based on risk is described, followed by a discussion of fire safety design methods that can be used for different areas of the plant, depending on the degree of threat to plant safety from the fire hazard. This alternative framework has the potential to make programs more cost-effective, and comprehensive, since it will allow a more systematic and broader examination of fire risk, and provide a means to distinguish between high and low risk fire contributors. (orig.)

Dynamic Learning Objects to Teach Java Programming Language

Science.gov (United States)

Narasimhamurthy, Uma; Al Shawkani, Khuloud

2010-01-01

This article describes a model for teaching Java Programming Language through Dynamic Learning Objects. The design of the learning objects was based on effective learning design principles to help students learn the complex topic of Java Programming. Visualization was also used to facilitate the learning of the concepts. (Contains 1 figure and 2…

Adaptive Dynamic Programming for Control Algorithms and Stability

CERN Document Server

Zhang, Huaguang; Luo, Yanhong; Wang, Ding

2013-01-01

There are many methods of stable controller design for nonlinear systems. In seeking to go beyond the minimum requirement of stability, Adaptive Dynamic Programming for Control approaches the challenging topic of optimal control for nonlinear systems using the tools of  adaptive dynamic programming (ADP). The range of systems treated is extensive; affine, switched, singularly perturbed and time-delay nonlinear systems are discussed as are the uses of neural networks and techniques of value and policy iteration. The text features three main aspects of ADP in which the methods proposed for stabilization and for tracking and games benefit from the incorporation of optimal control methods: • infinite-horizon control for which the difficulty of solving partial differential Hamilton–Jacobi–Bellman equations directly is overcome, and  proof provided that the iterative value function updating sequence converges to the infimum of all the value functions obtained by admissible control law sequences; • finite-...

Computationally efficient dynamic modeling of robot manipulators with multiple flexible-links using acceleration-based discrete time transfer matrix method

DEFF Research Database (Denmark)

Zhang, Xuping; Sørensen, Rasmus; RahbekIversen, Mathias

2018-01-01

This paper presents a novel and computationally efficient modeling method for the dynamics of flexible-link robot manipulators. In this method, a robot manipulator is decomposed into components/elements. The component/element dynamics is established using Newton–Euler equations, and then is linea......This paper presents a novel and computationally efficient modeling method for the dynamics of flexible-link robot manipulators. In this method, a robot manipulator is decomposed into components/elements. The component/element dynamics is established using Newton–Euler equations......, and then is linearized based on the acceleration-based state vector. The transfer matrices for each type of components/elements are developed, and used to establish the system equations of a flexible robot manipulator by concatenating the state vector from the base to the end-effector. With this strategy, the size...... manipulators, and only involves calculating and transferring component/element dynamic equations that have small size. The numerical simulations and experimental testing of flexible-link manipulators are conducted to validate the proposed methodologies....

Quantum optical device accelerating dynamic programming

OpenAIRE

Grigoriev, D.; Kazakov, A.; Vakulenko, S.

2005-01-01

In this paper we discuss analogue computers based on quantum optical systems accelerating dynamic programming for some computational problems. These computers, at least in principle, can be realized by actually existing devices. We estimate an acceleration in resolving of some NP-hard problems that can be obtained in such a way versus deterministic computers

Dynamic neural network-based methods for compensation of nonlinear effects in multimode communication lines

Science.gov (United States)

Sidelnikov, O. S.; Redyuk, A. A.; Sygletos, S.

2017-12-01

We consider neural network-based schemes of digital signal processing. It is shown that the use of a dynamic neural network-based scheme of signal processing ensures an increase in the optical signal transmission quality in comparison with that provided by other methods for nonlinear distortion compensation.

Transient dynamic and inelastic analysis of shells of revolution - a survey of programs

International Nuclear Information System (INIS)

Svalbonas, V.

1976-01-01

Advances in the limits of structural use in the aerospace and nuclear power industries over the past years have increased the requirements upon the applicable analytical computer programs to include accurate capabilities for inelastic and transient dynamic analyses. In many minds, however, this advanced capability is unequivocally linked with the large scale, general purpose, finite element programs. This idea is also combined with the view that such analyses are therefore prohibitively expensive and should be relegated to the 'last resort' classification. While this, in the general sense, may indeed be the case, if the user needs only to analyze structures falling into limited categories, however, he may find that a variety of smaller special purpose programs are available which do not put an undue strain upon his resources. One such structural category is shells of revolution. This survey of programs concentrates upon the analytical tools which have been developed predominantly for shells of revolution. The survey is subdivided into three parts: (a) consideration of programs for transient dynamic analysis; (b) consideration of programs for inelastic analysis and finally; (c) consideration of programs capable of dynamic plasticity analysis. In each part, programs based upon finite difference, finite element, and numerical integration methods are considered. The programs are compared on the basis of analytical capabilities, and ease of idealization and use. In each part of the survey sample problems are utilized to exemplify the state-of-the-art. (Auth.)

Prediction-based dynamic load-sharing heuristics

Science.gov (United States)

Goswami, Kumar K.; Devarakonda, Murthy; Iyer, Ravishankar K.

1993-01-01

The authors present dynamic load-sharing heuristics that use predicted resource requirements of processes to manage workloads in a distributed system. A previously developed statistical pattern-recognition method is employed for resource prediction. While nonprediction-based heuristics depend on a rapidly changing system status, the new heuristics depend on slowly changing program resource usage patterns. Furthermore, prediction-based heuristics can be more effective since they use future requirements rather than just the current system state. Four prediction-based heuristics, two centralized and two distributed, are presented. Using trace driven simulations, they are compared against random scheduling and two effective nonprediction based heuristics. Results show that the prediction-based centralized heuristics achieve up to 30 percent better response times than the nonprediction centralized heuristic, and that the prediction-based distributed heuristics achieve up to 50 percent improvements relative to their nonprediction counterpart.

Analysis of operator support method based on intelligent dynamic interlock in lead-cooled fast reactor simulator

International Nuclear Information System (INIS)

Xu, Peng; Wang, Jianye; Yang, Minghan; Wang, Weitian; Bai, Yunqing; Song, Yong

2017-01-01

Highlights: • We development an operator support method based on intelligent dynamic interlock. • We offer an integrated aid system to reduce the working strength of operators. • The method can help operators avoid dangerous, irreversible operation. • This method can be used in the fusion research reactor in the further. - Abstract: In nuclear systems, operators have to carry out corrective actions when abnormal situations occur. However, operators might make mistakes under pressure. In order to avoid serious consequences of the human errors, a new method for operators support based on intelligent dynamic interlock was proposed. The new method based on full digital instrumentation and control system, contains real-time alarm analysis process, decision support process and automatic safety interlock process. Once abnormal conditions occur, necessary safety interlock parameter based on analysis of real-time alarm and decision support process can be loaded into human-machine interfaces and controllers automatically, and avoid human errors effectively. Furthermore, the new method can make recommendations for further use and development of this technique in nuclear power plant or fusion research reactor.

The Dynamic Programming Method of Stochastic Differential Game for Functional Forward-Backward Stochastic System

Directory of Open Access Journals (Sweden)

Shaolin Ji

2013-01-01

Full Text Available This paper is devoted to a stochastic differential game (SDG of decoupled functional forward-backward stochastic differential equation (FBSDE. For our SDG, the associated upper and lower value functions of the SDG are defined through the solution of controlled functional backward stochastic differential equations (BSDEs. Applying the Girsanov transformation method introduced by Buckdahn and Li (2008, the upper and the lower value functions are shown to be deterministic. We also generalize the Hamilton-Jacobi-Bellman-Isaacs (HJBI equations to the path-dependent ones. By establishing the dynamic programming principal (DPP, we derive that the upper and the lower value functions are the viscosity solutions of the corresponding upper and the lower path-dependent HJBI equations, respectively.

An optimal maintenance policy for machine replacement problem using dynamic programming

OpenAIRE

Mohsen Sadegh Amalnik; Morteza Pourgharibshahi

2017-01-01

In this article, we present an acceptance sampling plan for machine replacement problem based on the backward dynamic programming model. Discount dynamic programming is used to solve a two-state machine replacement problem. We plan to design a model for maintenance by consid-ering the quality of the item produced. The purpose of the proposed model is to determine the optimal threshold policy for maintenance in a finite time horizon. We create a decision tree based on a sequential sampling inc...

A Method on Dynamic Path Planning for Robotic Manipulator Autonomous Obstacle Avoidance Based on an Improved RRT Algorithm.

Science.gov (United States)

Wei, Kun; Ren, Bingyin

2018-02-13

In a future intelligent factory, a robotic manipulator must work efficiently and safely in a Human-Robot collaborative and dynamic unstructured environment. Autonomous path planning is the most important issue which must be resolved first in the process of improving robotic manipulator intelligence. Among the path-planning methods, the Rapidly Exploring Random Tree (RRT) algorithm based on random sampling has been widely applied in dynamic path planning for a high-dimensional robotic manipulator, especially in a complex environment because of its probability completeness, perfect expansion, and fast exploring speed over other planning methods. However, the existing RRT algorithm has a limitation in path planning for a robotic manipulator in a dynamic unstructured environment. Therefore, an autonomous obstacle avoidance dynamic path-planning method for a robotic manipulator based on an improved RRT algorithm, called Smoothly RRT (S-RRT), is proposed. This method that targets a directional node extends and can increase the sampling speed and efficiency of RRT dramatically. A path optimization strategy based on the maximum curvature constraint is presented to generate a smooth and curved continuous executable path for a robotic manipulator. Finally, the correctness, effectiveness, and practicability of the proposed method are demonstrated and validated via a MATLAB static simulation and a Robot Operating System (ROS) dynamic simulation environment as well as a real autonomous obstacle avoidance experiment in a dynamic unstructured environment for a robotic manipulator. The proposed method not only provides great practical engineering significance for a robotic manipulator's obstacle avoidance in an intelligent factory, but also theoretical reference value for other type of robots' path planning.

Bellman’s GAP—a language and compiler for dynamic programming in sequence analysis

Science.gov (United States)

Sauthoff, Georg; Möhl, Mathias; Janssen, Stefan; Giegerich, Robert

2013-01-01

Motivation: Dynamic programming is ubiquitous in bioinformatics. Developing and implementing non-trivial dynamic programming algorithms is often error prone and tedious. Bellman’s GAP is a new programming system, designed to ease the development of bioinformatics tools based on the dynamic programming technique. Results: In Bellman’s GAP, dynamic programming algorithms are described in a declarative style by tree grammars, evaluation algebras and products formed thereof. This bypasses the design of explicit dynamic programming recurrences and yields programs that are free of subscript errors, modular and easy to modify. The declarative modules are compiled into C++ code that is competitive to carefully hand-crafted implementations. This article introduces the Bellman’s GAP system and its language, GAP-L. It then demonstrates the ease of development and the degree of re-use by creating variants of two common bioinformatics algorithms. Finally, it evaluates Bellman’s GAP as an implementation platform of ‘real-world’ bioinformatics tools. Availability: Bellman’s GAP is available under GPL license from http://bibiserv.cebitec.uni-bielefeld.de/bellmansgap. This Web site includes a repository of re-usable modules for RNA folding based on thermodynamics. Contact: robert@techfak.uni-bielefeld.de Supplementary information: Supplementary data are available at Bioinformatics online PMID:23355290

Parametric synthesis of a robust controller on a base of mathematical programming method

Science.gov (United States)

Khozhaev, I. V.; Gayvoronskiy, S. A.; Ezangina, T. A.

2018-05-01

Considered paper is dedicated to deriving sufficient conditions, linking root indices of robust control quality with coefficients of interval characteristic polynomial, on the base of mathematical programming method. On the base of these conditions, a method of PI- and PID-controllers, providing aperiodic transient process with acceptable stability degree and, subsequently, acceptable setting time, synthesis was developed. The method was applied to a problem of synthesizing a controller for a depth control system of an unmanned underwater vehicle.

LCP method for a planar passive dynamic walker based on an event-driven scheme

Science.gov (United States)

Zheng, Xu-Dong; Wang, Qi

2018-06-01

The main purpose of this paper is to present a linear complementarity problem (LCP) method for a planar passive dynamic walker with round feet based on an event-driven scheme. The passive dynamic walker is treated as a planar multi-rigid-body system. The dynamic equations of the passive dynamic walker are obtained by using Lagrange's equations of the second kind. The normal forces and frictional forces acting on the feet of the passive walker are described based on a modified Hertz contact model and Coulomb's law of dry friction. The state transition problem of stick-slip between feet and floor is formulated as an LCP, which is solved with an event-driven scheme. Finally, to validate the methodology, four gaits of the walker are simulated: the stance leg neither slips nor bounces; the stance leg slips without bouncing; the stance leg bounces without slipping; the walker stands after walking several steps.

A Shellcode Detection Method Based on Full Native API Sequence and Support Vector Machine

Science.gov (United States)

Cheng, Yixuan; Fan, Wenqing; Huang, Wei; An, Jing

2017-09-01

Dynamic monitoring the behavior of a program is widely used to discriminate between benign program and malware. It is usually based on the dynamic characteristics of a program, such as API call sequence or API call frequency to judge. The key innovation of this paper is to consider the full Native API sequence and use the support vector machine to detect the shellcode. We also use the Markov chain to extract and digitize Native API sequence features. Our experimental results show that the method proposed in this paper has high accuracy and low detection rate.

Two-step algorithm of generalized PAPA method applied to linear programming solution of dynamic matrix control

International Nuclear Information System (INIS)

Shimizu, Yoshiaki

1991-01-01

In recent complicated nuclear systems, there are increasing demands for developing highly advanced procedures for various problems-solvings. Among them keen interests have been paid on man-machine communications to improve both safety and economy factors. Many optimization methods have been good enough to elaborate on these points. In this preliminary note, we will concern with application of linear programming (LP) for this purpose. First we will present a new superior version of the generalized PAPA method (GEPAPA) to solve LP problems. We will then examine its effectiveness when applied to derive dynamic matrix control (DMC) as the LP solution. The approach is to aim at the above goal through a quality control of process that will appear in the system. (author)

Dynamic airspace configuration method based on a weighted graph model

Directory of Open Access Journals (Sweden)

Chen Yangzhou

2014-08-01

Full Text Available This paper proposes a new method for dynamic airspace configuration based on a weighted graph model. The method begins with the construction of an undirected graph for the given airspace, where the vertices represent those key points such as airports, waypoints, and the edges represent those air routes. Those vertices are used as the sites of Voronoi diagram, which divides the airspace into units called as cells. Then, aircraft counts of both each cell and of each air-route are computed. Thus, by assigning both the vertices and the edges with those aircraft counts, a weighted graph model comes into being. Accordingly the airspace configuration problem is described as a weighted graph partitioning problem. Then, the problem is solved by a graph partitioning algorithm, which is a mixture of general weighted graph cuts algorithm, an optimal dynamic load balancing algorithm and a heuristic algorithm. After the cuts algorithm partitions the model into sub-graphs, the load balancing algorithm together with the heuristic algorithm transfers aircraft counts to balance workload among sub-graphs. Lastly, airspace configuration is completed by determining the sector boundaries. The simulation result shows that the designed sectors satisfy not only workload balancing condition, but also the constraints such as convexity, connectivity, as well as minimum distance constraint.

Optimum Repartition of Transport Capacities in the Logistic System using Dynamic Programming

Directory of Open Access Journals (Sweden)

Gheorghe BĂŞANU

2011-08-01

Full Text Available Transportations take an essential role in logistics, interconnecting the majority of processes and operations within logistic system. The efficient use of transportation capacity is a priority whose achievement can diminish logistic costs. This objective is today difficult to achieve due to increasing complexity of transportation monitoring and coordination. This complexity is determined by transportation number and diversity, by the volume and diversity of orders, by increasing the targets to be supplied.Dynamic programming represents a highly useful tool for logistic managers, considering that its specific techniques and methods are oriented toward solving problems related to resource optimum allocation and utilization.The present paper presents briefly a series of theoretical elements of dynamic programming applied in logistics, based on which it is shown a mathematic model to determine the optimum policy for transport capacity repartition for the area attached to a logistic centre, through three distribution centres.

A Dynamic Programming Approach for Base Station Sleeping in Cellular Networks

Science.gov (United States)

Gong, Jie; Zhou, Sheng; Niu, Zhisheng

The energy consumption of the information and communication technology (ICT) industry, which has become a serious problem, is mostly due to the network infrastructure rather than the mobile terminals. In this paper, we focus on reducing the energy consumption of base stations (BSs) by adjusting their working modes (active or sleep). Specifically, the objective is to minimize the energy consumption while satisfying quality of service (QoS, e.g., blocking probability) requirement and, at the same time, avoiding frequent mode switching to reduce signaling and delay overhead. The problem is modeled as a dynamic programming (DP) problem, which is NP-hard in general. Based on cooperation among neighboring BSs, a low-complexity algorithm is proposed to reduce the size of state space as well as that of action space. Simulations demonstrate that, with the proposed algorithm, the active BS pattern well meets the time variation and the non-uniform spatial distribution of system traffic. Moreover, the tradeoff between the energy saving from BS sleeping and the cost of switching is well balanced by the proposed scheme.

A Thrust Allocation Method for Efficient Dynamic Positioning of a Semisubmersible Drilling Rig Based on the Hybrid Optimization Algorithm

Directory of Open Access Journals (Sweden)

Luman Zhao

2015-01-01

Full Text Available A thrust allocation method was proposed based on a hybrid optimization algorithm to efficiently and dynamically position a semisubmersible drilling rig. That is, the thrust allocation was optimized to produce the generalized forces and moment required while at the same time minimizing the total power consumption under the premise that forbidden zones should be taken into account. An optimization problem was mathematically formulated to provide the optimal thrust allocation by introducing the corresponding design variables, objective function, and constraints. A hybrid optimization algorithm consisting of a genetic algorithm and a sequential quadratic programming (SQP algorithm was selected and used to solve this problem. The proposed method was evaluated by applying it to a thrust allocation problem for a semisubmersible drilling rig. The results indicate that the proposed method can be used as part of a cost-effective strategy for thrust allocation of the rig.

A mathematical programming approach for sequential clustering of dynamic networks

Science.gov (United States)

Silva, Jonathan C.; Bennett, Laura; Papageorgiou, Lazaros G.; Tsoka, Sophia

2016-02-01

A common analysis performed on dynamic networks is community structure detection, a challenging problem that aims to track the temporal evolution of network modules. An emerging area in this field is evolutionary clustering, where the community structure of a network snapshot is identified by taking into account both its current state as well as previous time points. Based on this concept, we have developed a mixed integer non-linear programming (MINLP) model, SeqMod, that sequentially clusters each snapshot of a dynamic network. The modularity metric is used to determine the quality of community structure of the current snapshot and the historical cost is accounted for by optimising the number of node pairs co-clustered at the previous time point that remain so in the current snapshot partition. Our method is tested on social networks of interactions among high school students, college students and members of the Brazilian Congress. We show that, for an adequate parameter setting, our algorithm detects the classes that these students belong more accurately than partitioning each time step individually or by partitioning the aggregated snapshots. Our method also detects drastic discontinuities in interaction patterns across network snapshots. Finally, we present comparative results with similar community detection methods for time-dependent networks from the literature. Overall, we illustrate the applicability of mathematical programming as a flexible, adaptable and systematic approach for these community detection problems. Contribution to the Topical Issue "Temporal Network Theory and Applications", edited by Petter Holme.

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.

Study on non-linear bistable dynamics model based EEG signal discrimination analysis method.

Science.gov (United States)

Ying, Xiaoguo; Lin, Han; Hui, Guohua

2015-01-01

Electroencephalogram (EEG) is the recording of electrical activity along the scalp. EEG measures voltage fluctuations generating from ionic current flows within the neurons of the brain. EEG signal is looked as one of the most important factors that will be focused in the next 20 years. In this paper, EEG signal discrimination based on non-linear bistable dynamical model was proposed. EEG signals were processed by non-linear bistable dynamical model, and features of EEG signals were characterized by coherence index. Experimental results showed that the proposed method could properly extract the features of different EEG signals.

Convergence of Sample Path Optimal Policies for Stochastic Dynamic Programming

National Research Council Canada - National Science Library

Fu, Michael C; Jin, Xing

2005-01-01

.... These results have practical implications for Monte Carlo simulation-based solution approaches to stochastic dynamic programming problems where it is impractical to extract the explicit transition...

Granular contact dynamics using mathematical programming methods

DEFF Research Database (Denmark)

Krabbenhoft, K.; Lyamin, A. V.; Huang, J.

2012-01-01

granular contact dynamics formulation uses an implicit time discretization, thus allowing for large time steps. Moreover, in the limit of an infinite time step, the general dynamic formulation reduces to a static formulation that is useful in simulating common quasi-static problems such as triaxial tests...... is developed and it is concluded that the associated sliding rule, in the context of granular contact dynamics, may be viewed as an artifact of the time discretization and that the use of an associated flow rule at the particle scale level generally is physically acceptable. (C) 2012 Elsevier Ltd. All rights...

A Simple Method for Dynamic Scheduling in a Heterogeneous Computing System

OpenAIRE

Žumer, Viljem; Brest, Janez

2002-01-01

A simple method for the dynamic scheduling on a heterogeneous computing system is proposed in this paper. It was implemented to minimize the parallel program execution time. The proposed method decomposes the program workload into computationally homogeneous subtasks, which may be of the different size, depending on the current load of each machine in a heterogeneous computing system.

An intelligent environment for dynamic simulation program generation of nuclear reactor systems

International Nuclear Information System (INIS)

Ishizaka, Hiroaki; Gofuku, Akio; Yoshikawa, Hidekazu

2004-01-01

A graphical user interface system was developed for the two dynamic simulation systems based on modular programming methods: MSS and DSNP. The following works were made in conjunction with the system development: (1) conversion of the module libraries of both DSNP and MSS, (2) extension of DSNP- pre-compiler, (3) graphical interface for module integration, and (4) automatic converter of simple language descriptions for DSNP, where (1) and (2) were made on an engineering work station, while the rest (3) and (4), on Macintosh HyperCard. By using the graphical interface, a user can specify the structure of a simulation model, geometrical data, initial values of variables, etc. only by handling modules as icon on the pallet fields. The use of extended DSNP pre-compiler then generates the final product of dynamic simulation program automatically. The capability and effectiveness of the system was confirmed by a sample simulation of PWR SBLOCA transient in PORV stuck open event. (author)

Optimal Control of Complex Systems Based on Improved Dual Heuristic Dynamic Programming Algorithm

Directory of Open Access Journals (Sweden)

Hui Li

2017-01-01

Full Text Available When applied to solving the data modeling and optimal control problems of complex systems, the dual heuristic dynamic programming (DHP technique, which is based on the BP neural network algorithm (BP-DHP, has difficulty in prediction accuracy, slow convergence speed, poor stability, and so forth. In this paper, a dual DHP technique based on Extreme Learning Machine (ELM algorithm (ELM-DHP was proposed. Through constructing three kinds of network structures, the paper gives the detailed realization process of the DHP technique in the ELM. The controller designed upon the ELM-DHP algorithm controlled a molecular distillation system with complex features, such as multivariability, strong coupling, and nonlinearity. Finally, the effectiveness of the algorithm is verified by the simulation that compares DHP and HDP algorithms based on ELM and BP neural network. The algorithm can also be applied to solve the data modeling and optimal control problems of similar complex systems.

Model-based dynamic multi-parameter method for peak power estimation of lithium-ion batteries

NARCIS (Netherlands)

Sun, F.; Xiong, R.; He, H.; Li, W.; Aussems, J.E.E.

2012-01-01

A model-based dynamic multi-parameter method for peak power estimation is proposed for batteries and battery management systems (BMSs) used in hybrid electric vehicles (HEVs). The available power must be accurately calculated in order to not damage the battery by over charging or over discharging or

Dislocation-dynamics method

International Nuclear Information System (INIS)

Van Brutzel, L.

2015-01-01

Dislocation-Dynamics (DD) technique is identified as the method able to model the evolution of material plastic properties as a function of the microstructural transformation predicted at the atomic scale. Indeed, it is the only simulation method capable of taking into account the collective behaviour of a large number of dislocations inside a realistic microstructure. DD simulations are based on the elastic dislocation theory following rules inherent to the dislocation core structure often call 'local rules'. All the data necessary to establish the local rules for DD have to come directly from experiment or alternatively from simulations carried out at the atomic scale such as molecular dynamics or ab initio calculations. However, no precise information on the interaction between two dislocations or between dislocations and defects induced by irradiation are available for nuclear fuels. Therefore, in this article the DD technique will be presented and some examples are given of what can be achieved with it. (author)

Variable Displacement Control of the Concrete Pumping System Based on Dynamic Programming

Directory of Open Access Journals (Sweden)

Ye Min

2017-01-01

Full Text Available To solve the problems of cylinder piston striking cylinder and the hydraulic shocking of the main pump, and causing energy waste problem, the method of variable displacement control of piston stroke was proposed. In order to achieve effective control of the piston stroke, variable displacement control model was established under the physical constraint condition of non-collision between piston and cylinder. And the control process was realized by Dynamic Programming(DP, the simulation and test results show that piston of concrete pumping system don’t strike cylinder and reduce the hydraulic shock of the main pump outlet, meanwhile improve the response speed of the cylinder and achieve energy-saving purposes under varying loads. This control model built in the integration design space of structure variable and control variable is of guiding significance for solving open-loop system’s engineering problems.

Method of dynamic fuzzy symptom vector in intelligent diagnosis

International Nuclear Information System (INIS)

Sun Hongyan; Jiang Xuefeng

2010-01-01

Aiming at the requirement of diagnostic symptom real-time updating brought from diagnostic knowledge accumulation and great gap in unit and value of diagnostic symptom in multi parameters intelligent diagnosis, the method of dynamic fuzzy symptom vector is proposed. The concept of dynamic fuzzy symptom vector is defined. Ontology is used to specify the vector elements, and the vector transmission method based on ontology is built. The changing law of symptom value is analyzed and fuzzy normalization method based on fuzzy membership functions is built. An instance proved method of dynamic fussy symptom vector is efficient to solve the problems of symptom updating and unify of symptom value and unit. (authors)

Solving the Single-Sink, Fixed-Charge, Multiple-Choice Transportation Problem by Dynamic Programming

DEFF Research Database (Denmark)

Christensen, Tue; Andersen, Kim Allan; Klose, Andreas

2013-01-01

This paper considers a minimum-cost network flow problem in a bipartite graph with a single sink. The transportation costs exhibit a staircase cost structure because such types of transportation cost functions are often found in practice. We present a dynamic programming algorithm for solving...... this so-called single-sink, fixed-charge, multiple-choice transportation problem exactly. The method exploits heuristics and lower bounds to peg binary variables, improve bounds on flow variables, and reduce the state-space variable. In this way, the dynamic programming method is able to solve large...... instances with up to 10,000 nodes and 10 different transportation modes in a few seconds, much less time than required by a widely used mixed-integer programming solver and other methods proposed in the literature for this problem....

Gr-GDHP: A New Architecture for Globalized Dual Heuristic Dynamic Programming.

Science.gov (United States)

Zhong, Xiangnan; Ni, Zhen; He, Haibo

2017-10-01

Goal representation globalized dual heuristic dynamic programming (Gr-GDHP) method is proposed in this paper. A goal neural network is integrated into the traditional GDHP method providing an internal reinforcement signal and its derivatives to help the control and learning process. From the proposed architecture, it is shown that the obtained internal reinforcement signal and its derivatives can be able to adjust themselves online over time rather than a fixed or predefined function in literature. Furthermore, the obtained derivatives can directly contribute to the objective function of the critic network, whose learning process is thus simplified. Numerical simulation studies are applied to show the performance of the proposed Gr-GDHP method and compare the results with other existing adaptive dynamic programming designs. We also investigate this method on a ball-and-beam balancing system. The statistical simulation results are presented for both the Gr-GDHP and the GDHP methods to demonstrate the improved learning and controlling performance.

Identification of Dynamic Loads Based on Second-Order Taylor-Series Expansion Method

Directory of Open Access Journals (Sweden)

Xiaowang Li

2016-01-01

Full Text Available A new method based on the second-order Taylor-series expansion is presented to identify the structural dynamic loads in the time domain. This algorithm expresses the response vectors as Taylor-series approximation and then a series of formulas are deduced. As a result, an explicit discrete equation which associates system response, system characteristic, and input excitation together is set up. In a multi-input-multi-output (MIMO numerical simulation study, sinusoidal excitation and white noise excitation are applied on a cantilever beam, respectively, to illustrate the effectiveness of this algorithm. One also makes a comparison between the new method and conventional state space method. The results show that the proposed method can obtain a more accurate identified force time history whether the responses are polluted by noise or not.

Extraction of Static and Dynamic Reservoir Operation Rules by Genetic Programming

Directory of Open Access Journals (Sweden)

Habib Akbari Alashti

2014-11-01

Full Text Available Considering the necessity of desirable operation of limited water resources and assuming the significant role of dams in controlling and consuming the surface waters, highlights the advantageous of suitable operation rules for optimal and sustainable operation of dams. This study investigates the hydroelectric supply of a one-reservoir system of Karoon3 using nonlinear programming (NLP, genetic algorithm (GA, genetic programming (GP and fixed length gen GP (FLGGP in real-time operation of dam considering two approaches of static and dynamic operation rules. In static operation rule, only one rule curve is extracted for all months in a year whereas in dynamic operation rule, monthly rule curves (12 rules are extracted for each month of a year. In addition, nonlinear decision rule (NLDR curves are considered, and the total deficiency function as the target (objective function have been used for evaluating the performance of each method and approach. Results show appropriate efficiency of GP and FLGGP methods in extracting operation rules in both approaches. Superiority of these methods to operation methods yielded by GA and NLP is 5%. Moreover, according to the results, it can be remarked that, FLGGP method is an alternative for GP method, whereas the GP method cannot be used due to its limitations. Comparison of two approaches of static and dynamic operation rules demonstrated the superiority of dynamic operation rule to static operation rule (about 10% and therefore this method has more capabilities in real-time operation of the reservoirs systems.

Identification of Dynamic Loads Based on Second-Order Taylor-Series Expansion Method

OpenAIRE

Li, Xiaowang; Deng, Zhongmin

2016-01-01

A new method based on the second-order Taylor-series expansion is presented to identify the structural dynamic loads in the time domain. This algorithm expresses the response vectors as Taylor-series approximation and then a series of formulas are deduced. As a result, an explicit discrete equation which associates system response, system characteristic, and input excitation together is set up. In a multi-input-multi-output (MIMO) numerical simulation study, sinusoidal excitation and white no...

Air-Breathing Hypersonic Vehicle Tracking Control Based on Adaptive Dynamic Programming.

Science.gov (United States)

Mu, Chaoxu; Ni, Zhen; Sun, Changyin; He, Haibo

2017-03-01

In this paper, we propose a data-driven supplementary control approach with adaptive learning capability for air-breathing hypersonic vehicle tracking control based on action-dependent heuristic dynamic programming (ADHDP). The control action is generated by the combination of sliding mode control (SMC) and the ADHDP controller to track the desired velocity and the desired altitude. In particular, the ADHDP controller observes the differences between the actual velocity/altitude and the desired velocity/altitude, and then provides a supplementary control action accordingly. The ADHDP controller does not rely on the accurate mathematical model function and is data driven. Meanwhile, it is capable to adjust its parameters online over time under various working conditions, which is very suitable for hypersonic vehicle system with parameter uncertainties and disturbances. We verify the adaptive supplementary control approach versus the traditional SMC in the cruising flight, and provide three simulation studies to illustrate the improved performance with the proposed approach.

Neutrophil programming dynamics and its disease relevance.

Science.gov (United States)

Ran, Taojing; Geng, Shuo; Li, Liwu

2017-11-01

Neutrophils are traditionally considered as first responders to infection and provide antimicrobial host defense. However, recent advances indicate that neutrophils are also critically involved in the modulation of host immune environments by dynamically adopting distinct functional states. Functionally diverse neutrophil subsets are increasingly recognized as critical components mediating host pathophysiology. Despite its emerging significance, molecular mechanisms as well as functional relevance of dynamically programmed neutrophils remain to be better defined. The increasing complexity of neutrophil functions may require integrative studies that address programming dynamics of neutrophils and their pathophysiological relevance. This review aims to provide an update on the emerging topics of neutrophil programming dynamics as well as their functional relevance in diseases.

SEU mitigation technique by Dynamic Reconfiguration method in FPGA based DSP application

International Nuclear Information System (INIS)

Dey, Madhusudan; Singh, Abhishek; Roy, Amitava

2012-01-01

Field Programmable Gate Array (FPGA), an SRAM based configurable devices meant for implementation of any digital circuits is susceptible to malfunction in the harsh radiation environment. It causes the corruption of the configuration memory of FPGA and the digital circuits starts malfunctioning. There is a need to restore the system as early as possible. This paper discusses about one such technique named dynamic partial reconfiguration (DPR) method. This paper also touches upon the signal processing by DPR method. The framework consisting of ADC, DAC and ICAP controllers designed using dedicated state machines to study the best possible downtime also for verifying the performance of digital filters for signal processing

An interval-based possibilistic programming method for waste management with cost minimization and environmental-impact abatement under uncertainty.

Science.gov (United States)

Li, Y P; Huang, G H

2010-09-15

Considerable public concerns have been raised in the past decades since a large amount of pollutant emissions from municipal solid waste (MSW) disposal of processes pose risks on surrounding environment and human health. Moreover, in MSW management, various uncertainties exist in the related costs, impact factors and objectives, which can affect the optimization processes and the decision schemes generated. In this study, an interval-based possibilistic programming (IBPP) method is developed for planning the MSW management with minimized system cost and environmental impact under uncertainty. The developed method can deal with uncertainties expressed as interval values and fuzzy sets in the left- and right-hand sides of constraints and objective function. An interactive algorithm is provided for solving the IBPP problem, which does not lead to more complicated intermediate submodels and has a relatively low computational requirement. The developed model is applied to a case study of planning a MSW management system, where mixed integer linear programming (MILP) technique is introduced into the IBPP framework to facilitate dynamic analysis for decisions of timing, sizing and siting in terms of capacity expansion for waste-management facilities. Three cases based on different waste-management policies are examined. The results obtained indicate that inclusion of environmental impacts in the optimization model can change the traditional waste-allocation pattern merely based on the economic-oriented planning approach. The results obtained can help identify desired alternatives for managing MSW, which has advantages in providing compromised schemes under an integrated consideration of economic efficiency and environmental impact under uncertainty. Copyright 2010 Elsevier B.V. All rights reserved.

Automated Flight Routing Using Stochastic Dynamic Programming

Science.gov (United States)

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

2010-01-01

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

High dynamic range image acquisition based on multiplex cameras

Science.gov (United States)

Zeng, Hairui; Sun, Huayan; Zhang, Tinghua

2018-03-01

High dynamic image is an important technology of photoelectric information acquisition, providing higher dynamic range and more image details, and it can better reflect the real environment, light and color information. Currently, the method of high dynamic range image synthesis based on different exposure image sequences cannot adapt to the dynamic scene. It fails to overcome the effects of moving targets, resulting in the phenomenon of ghost. Therefore, a new high dynamic range image acquisition method based on multiplex cameras system was proposed. Firstly, different exposure images sequences were captured with the camera array, using the method of derivative optical flow based on color gradient to get the deviation between images, and aligned the images. Then, the high dynamic range image fusion weighting function was established by combination of inverse camera response function and deviation between images, and was applied to generated a high dynamic range image. The experiments show that the proposed method can effectively obtain high dynamic images in dynamic scene, and achieves good results.

Configuring Airspace Sectors with Approximate Dynamic Programming

Science.gov (United States)

Bloem, Michael; Gupta, Pramod

2010-01-01

In response to changing traffic and staffing conditions, supervisors dynamically configure airspace sectors by assigning them to control positions. A finite horizon airspace sector configuration problem models this supervisor decision. The problem is to select an airspace configuration at each time step while considering a workload cost, a reconfiguration cost, and a constraint on the number of control positions at each time step. Three algorithms for this problem are proposed and evaluated: a myopic heuristic, an exact dynamic programming algorithm, and a rollouts approximate dynamic programming algorithm. On problem instances from current operations with only dozens of possible configurations, an exact dynamic programming solution gives the optimal cost value. The rollouts algorithm achieves costs within 2% of optimal for these instances, on average. For larger problem instances that are representative of future operations and have thousands of possible configurations, excessive computation time prohibits the use of exact dynamic programming. On such problem instances, the rollouts algorithm reduces the cost achieved by the heuristic by more than 15% on average with an acceptable computation time.

Dynamic analysis program for frame structure

International Nuclear Information System (INIS)

Ando, Kozo; Chiba, Toshio

1975-01-01

A general purpose computer program named ISTRAN/FD (Isub(HI) STRucture ANalysis/Frame structure, Dynamic analysis) has been developed for dynamic analysis of three-dimensional frame structures. This program has functions of free vibration analysis, seismic response analysis, graphic display by plotter and CRT, etc. This paper introduces ISTRAN/FD; examples of its application are shown with various problems : idealization of the cantilever, dynamic analysis of the main tower of the suspension bridge, three-dimensional vibration in the plate girder bridge, seismic response in the boiler steel structure, and dynamic properties of the underground LNG tank. In this last example, solid elements, in addition to beam elements, are especially used for the analysis. (auth.)

HVAC-DYNAMIC; A training simulator for dynamic analysis of HVAC plants

Energy Technology Data Exchange (ETDEWEB)

Heintz, M; Novakovic, V [SINTEF Division of Applied Thermodynamic, HVAC Group, Trondheim (Norway); Oegaard, O [SINTEF Division of Automatic Control, Trondheim (Norway); Brustad, G [Computer Aided Modelling, CAMO A/S, Trondheim (Norway)

1989-01-01

HVAC-DYNAMIC is a software tool for the dynamic simulation of Heating, Ventilation and Air Conditioning (HVAC) plants. The program is designed to be used by HVAC engineers during design or troubleshooting of plants and by plant operators in their training. The program is based on a set of the most-used HVAC plant configurations and requires only a minimum of knowledge in numeric methods and programming. A brief presentation of the program structure and examples showing some of the application of the program are given. 4 figs., 4 refs.

HVAC-DYNAMIC: a training simulator for dynamic analysis of HVAC plants

Directory of Open Access Journals (Sweden)

Morten Heintz

1989-07-01

Full Text Available HVAC-DYNAMIC is a software tool for the dynamic simulation of Heating, Ventilation and Air Conditioning (HVAC plants. The program is designed to be used by HVAC engineers during design or troubleshooting of plants and by plant operators in their training. The program is based on a set of the most-used HVAC plant configurations and requires only a minimum of knowledge in numeric methods and programming. A brief presentation of the program structure and examples showing some of the application of the program are given.

Convergence of the standard RLS method and UDUT factorisation of covariance matrix for solving the algebraic Riccati equation of the DLQR via heuristic approximate dynamic programming

Science.gov (United States)

Moraes Rêgo, Patrícia Helena; Viana da Fonseca Neto, João; Ferreira, Ernesto M.

2015-08-01

The main focus of this article is to present a proposal to solve, via UDUT factorisation, the convergence and numerical stability problems that are related to the covariance matrix ill-conditioning of the recursive least squares (RLS) approach for online approximations of the algebraic Riccati equation (ARE) solution associated with the discrete linear quadratic regulator (DLQR) problem formulated in the actor-critic reinforcement learning and approximate dynamic programming context. The parameterisations of the Bellman equation, utility function and dynamic system as well as the algebra of Kronecker product assemble a framework for the solution of the DLQR problem. The condition number and the positivity parameter of the covariance matrix are associated with statistical metrics for evaluating the approximation performance of the ARE solution via RLS-based estimators. The performance of RLS approximators is also evaluated in terms of consistence and polarisation when associated with reinforcement learning methods. The used methodology contemplates realisations of online designs for DLQR controllers that is evaluated in a multivariable dynamic system model.

Discrete Globalised Dual Heuristic Dynamic Programming in Control of the Two-Wheeled Mobile Robot

OpenAIRE

Marcin Szuster; Zenon Hendzel

2014-01-01

Network-based control systems have been emerging technologies in the control of nonlinear systems over the past few years. This paper focuses on the implementation of the approximate dynamic programming algorithm in the network-based tracking control system of the two-wheeled mobile robot, Pioneer 2-DX. The proposed discrete tracking control system consists of the globalised dual heuristic dynamic programming algorithm, the PD controller, the supervisory term, and an additional control signal...

PERMUTATION-BASED POLYMORPHIC STEGO-WATERMARKS FOR PROGRAM CODES

Directory of Open Access Journals (Sweden)

Denys Samoilenko

2016-06-01

Full Text Available Purpose: One of the most actual trends in program code protection is code marking. The problem consists in creation of some digital “watermarks” which allow distinguishing different copies of the same program codes. Such marks could be useful for authority protection, for code copies numbering, for program propagation monitoring, for information security proposes in client-server communication processes. Methods: We used the methods of digital steganography adopted for program codes as text objects. The same-shape symbols method was transformed to same-semantic element method due to codes features which makes them different from ordinary texts. We use dynamic principle of marks forming making codes similar to be polymorphic. Results: We examined the combinatorial capacity of permutations possible in program codes. As a result it was shown that the set of 5-7 polymorphic variables is suitable for the most modern network applications. Marks creation and restoration algorithms where proposed and discussed. The main algorithm is based on full and partial permutations in variables names and its declaration order. Algorithm for partial permutation enumeration was optimized for calculation complexity. PHP code fragments which realize the algorithms were listed. Discussion: Methodic proposed in the work allows distinguishing of each client-server connection. In a case if a clone of some network resource was found the methodic could give information about included marks and thereby data on IP, date and time, authentication information of client copied the resource. Usage of polymorphic stego-watermarks should improve information security indexes in network communications.

Physiotherapists supporting self-management through health coaching: a mixed methods program evaluation.

Science.gov (United States)

Dufour, Sinéad Patricia; Graham, Shane; Friesen, Josh; Rosenblat, Michael; Rous, Colin; Richardson, Julie

2015-01-01

To evaluate a program in support of chronic disease self-management (CDSM) that is founded on a health coaching (HC) approach, includes supervised exercise and mindfulness-based stress reduction components and is delivered within a private practice physiotherapy setting. An explanatory mixed method design, framed by theory-based program evaluation, was employed to evaluate an eight-week group-based program. Standardized self-rated and performance measures were evaluated pre- and post intervention. Additionally, participant focus groups were conducted following the intervention period. An inductive thematic approach was undertaken to analyze the qualitative data. Seventeen participants (N = 17) completed the study. Improvements were seen in both self-report and performance outcomes. Participants explained how and why they felt the program was beneficial. Six themes were generated: (1) group dynamic; (2) learning versus doing; (3) holism and comprehensive care; (4) self-efficacy and empowerment; (5) previous solutions versus new management strategies; and (6) healthcare provider support. This study established that a group program in support of CDSM founded on a HC approach demonstrated potential value from participants as well as favorable outcomes. A pragmatic randomized control trial is required to determine efficacy of this intervention.

Program packages for dynamics systems analysis and design

International Nuclear Information System (INIS)

Athani, V.V.

1976-01-01

The development of computer program packages for dynamic system analysis and design are reported. The purpose of developing these program packages is to take the burden of writing computer programs off the mind of the system engineer and to enable him to concentrate on his main system analysis and design work. Towards this end, four standard computer program packages have been prepared : (1) TFANA - starting from system transfer function this program computes transient response, frequency response, root locus and stability by Routh Hurwitz criterion, (2) TFSYN - classical synthesis using algebraic method of Shipley, (3) MODANA - starting from state equations of the system this program computes solution of state equations, controllability, observability and stability, (4) OPTCON - This program obtains solutions of (i) linear regulator problem, (ii) servomechanism problems and (iii) problem of pole placement. The paper describes these program packages with the help of flowcharts and illustrates their use with the help of examples. (author)

A Multiobjective Programming Method for Ranking All Units Based on Compensatory DEA Model

Directory of Open Access Journals (Sweden)

Haifang Cheng

2014-01-01

Full Text Available In order to rank all decision making units (DMUs on the same basis, this paper proposes a multiobjective programming (MOP model based on a compensatory data envelopment analysis (DEA model to derive a common set of weights that can be used for the full ranking of all DMUs. We first revisit a compensatory DEA model for ranking all units, point out the existing problem for solving the model, and present an improved algorithm for which an approximate global optimal solution of the model can be obtained by solving a sequence of linear programming. Then, we applied the key idea of the compensatory DEA model to develop the MOP model in which the objectives are to simultaneously maximize all common weights under constraints that the sum of efficiency values of all DMUs is equal to unity and the sum of all common weights is also equal to unity. In order to solve the MOP model, we transform it into a single objective programming (SOP model using a fuzzy programming method and solve the SOP model using the proposed approximation algorithm. To illustrate the ranking method using the proposed method, two numerical examples are solved.

Time-history simulation of civil architecture earthquake disaster relief- based on the three-dimensional dynamic finite element method

Directory of Open Access Journals (Sweden)

Liu Bing

2014-10-01

Full Text Available Earthquake action is the main external factor which influences long-term safe operation of civil construction, especially of the high-rise building. Applying time-history method to simulate earthquake response process of civil construction foundation surrounding rock is an effective method for the anti-knock study of civil buildings. Therefore, this paper develops a civil building earthquake disaster three-dimensional dynamic finite element numerical simulation system. The system adopts the explicit central difference method. Strengthening characteristics of materials under high strain rate and damage characteristics of surrounding rock under the action of cyclic loading are considered. Then, dynamic constitutive model of rock mass suitable for civil building aseismic analysis is put forward. At the same time, through the earthquake disaster of time-history simulation of Shenzhen Children’s Palace, reliability and practicability of system program is verified in the analysis of practical engineering problems.

Effect of Hydrotherapy on Static and Dynamic Balance in Older Adults: Comparison of Perturbed and Non-Perturbed Programs

Directory of Open Access Journals (Sweden)

Elham Azimzadeh

2013-01-01

Full Text Available Objectives: Falling is a main cause of mortality in elderly. Balance training exercises can help to prevent falls in older adults. According to the principle of specificity of training, the perturbation-based trainings are more similar to the real world. So these training programs can improve balance in elderly. Furthermore, exercising in an aquatic environment can reduce the limitations for balance training rather than a non-aquatic on. The aim of this study is comparing the effectiveness of perturbed and non-perturbed balance training programs in water on static and dynamic balance in aforementioned population group. Methods & Materials: 37 old women (age 80-65, were randomized to the following groups: perturbation-based training (n=12, non-perturbation-based training (n=12 and control (n=13 groups. Static and dynamic balance had been tested before and after the eight weeks of training by the postural stability test of the Biodex balance system using dynamic (level 4 and static platform. The data were analyzed by one sample paired t-test, Independent t-test and ANOVA. Results: There was a significant improvement for all indexes of static and dynamic balance in perturbation-based training (P<0.05. However, in non-perturbed group, all indexes were improved except ML (P<0.05. ANOVA showed that perturbed training was more effective than non-perturbed training on both static and dynamic balances. Conclusion: The findings confirmed the specificity principle of training. Although balance training can improve balance abilities, these kinds of trainings are not such specific for improving balance neuromuscular activities.The perturbation-based trainings can activate postural compensatory responses and reduce falling risk. According to results, we can conclude that hydrotherapy especially with perturbation-based programs will be useful for rehabilitation interventions in elderly .

Model Reduction in Co-Rotated Multi-Body Dynamics Based on the Dual Craig-Bampton Method

NARCIS (Netherlands)

Weerathunge Kadawathagedara, S.T.; Rixen, D.J.

2011-01-01

A new reduction method for dynamical analsis of multi-body systems is presented in this paper. It fundamentally differs from the ones previously published in the way kinematical constraints are handled. Our approach is based on component mode synthesis, but the specificity of articulated mechanism,

Social influence and bullying behavior: intervention-based network dynamics of the fairplayer.manual bullying prevention program.

Science.gov (United States)

Wölfer, Ralf; Scheithauer, Herbert

2014-01-01

Bullying is a social phenomenon and although preventive interventions consequently address social mechanisms, evaluations hardly consider the complexity of peer processes. Therefore, the present study analyzes the efficacy of the fairplayer.manual bullying prevention program from a social network perspective. Within a pretest-posttest control group design, longitudinal data were available from 328 middle-school students (MAge  = 13.7 years; 51% girls), who provided information on bullying behavior and interaction patterns. The revealed network parameters were utilized to examine the network change (MANCOVA) and the network dynamics (SIENA). Across both forms of analyses, findings revealed the hypothesized intervention-based decrease of bullies' social influence. Hence the present bullying prevention program, as one example of programs that successfully addresses both individual skills and social mechanisms, demonstrates the desired effect of reducing contextual opportunities for the exhibition of bullying behavior. © 2014 Wiley Periodicals, Inc.

Leak detection method for long pipeline based on dynamic pressure and wavelet analysis

Energy Technology Data Exchange (ETDEWEB)

Xu, Bin; Wang, Likun; Wang, Hongchao; Xiong, Min; Yu, Dongliang; Tan, Dongjie [RnD center of PetroChina Pipeline Company, Langfang, Hebei, (China)

2010-07-01

Leaks appear frequently in pipelines, raising the possibility of safety issues. The detection of pipeline leakage is very important for the pipeline industry. This paper investigated a leak detection method on a long pipeline using a dynamic pressure sensor. A new leakage system is proposed based on the measurements obtained from this dynamic pressure sensor. The data were analyzed using the wavelet transformation method. First, the signal provided by the pressure sensor its denoised and then leaks are detected from the presence of singularities in the signal. Field tests were carried out on a product oil pipeline of 94 km length. The in-field test results showed that the minimum ratio of detectable leakage is 0.6 % of throughput and the location error is below 300 m. The response time is less than 120 seconds. This new system has been applied in 5000 km pipelines in China and is proving its efficiency in detecting leak points.

Two Monthly Continuous Dynamic Model Based on Nash Bargaining Theory for Conflict Resolution in Reservoir System.

Science.gov (United States)

Homayounfar, Mehran; Zomorodian, Mehdi; Martinez, Christopher J; Lai, Sai Hin

2015-01-01

So far many optimization models based on Nash Bargaining Theory associated with reservoir operation have been developed. Most of them have aimed to provide practical and efficient solutions for water allocation in order to alleviate conflicts among water users. These models can be discussed from two viewpoints: (i) having a discrete nature; and (ii) working on an annual basis. Although discrete dynamic game models provide appropriate reservoir operator policies, their discretization of variables increases the run time and causes dimensionality problems. In this study, two monthly based non-discrete optimization models based on the Nash Bargaining Solution are developed for a reservoir system. In the first model, based on constrained state formulation, the first and second moments (mean and variance) of the state variable (water level in the reservoir) is calculated. Using moment equations as the constraint, the long-term utility of the reservoir manager and water users are optimized. The second model is a dynamic approach structured based on continuous state Markov decision models. The corresponding solution based on the collocation method is structured for a reservoir system. In this model, the reward function is defined based on the Nash Bargaining Solution. Indeed, it is used to yield equilibrium in every proper sub-game, thereby satisfying the Markov perfect equilibrium. Both approaches are applicable for water allocation in arid and semi-arid regions. A case study was carried out at the Zayandeh-Rud river basin located in central Iran to identify the effectiveness of the presented methods. The results are compared with the results of an annual form of dynamic game, a classical stochastic dynamic programming model (e.g. Bayesian Stochastic Dynamic Programming model, BSDP), and a discrete stochastic dynamic game model (PSDNG). By comparing the results of alternative methods, it is shown that both models are capable of tackling conflict issues in water allocation

Two Monthly Continuous Dynamic Model Based on Nash Bargaining Theory for Conflict Resolution in Reservoir System.

Directory of Open Access Journals (Sweden)

Mehran Homayounfar

Full Text Available So far many optimization models based on Nash Bargaining Theory associated with reservoir operation have been developed. Most of them have aimed to provide practical and efficient solutions for water allocation in order to alleviate conflicts among water users. These models can be discussed from two viewpoints: (i having a discrete nature; and (ii working on an annual basis. Although discrete dynamic game models provide appropriate reservoir operator policies, their discretization of variables increases the run time and causes dimensionality problems. In this study, two monthly based non-discrete optimization models based on the Nash Bargaining Solution are developed for a reservoir system. In the first model, based on constrained state formulation, the first and second moments (mean and variance of the state variable (water level in the reservoir is calculated. Using moment equations as the constraint, the long-term utility of the reservoir manager and water users are optimized. The second model is a dynamic approach structured based on continuous state Markov decision models. The corresponding solution based on the collocation method is structured for a reservoir system. In this model, the reward function is defined based on the Nash Bargaining Solution. Indeed, it is used to yield equilibrium in every proper sub-game, thereby satisfying the Markov perfect equilibrium. Both approaches are applicable for water allocation in arid and semi-arid regions. A case study was carried out at the Zayandeh-Rud river basin located in central Iran to identify the effectiveness of the presented methods. The results are compared with the results of an annual form of dynamic game, a classical stochastic dynamic programming model (e.g. Bayesian Stochastic Dynamic Programming model, BSDP, and a discrete stochastic dynamic game model (PSDNG. By comparing the results of alternative methods, it is shown that both models are capable of tackling conflict issues in

Optimal Control Method of Robot End Position and Orientation Based on Dynamic Tracking Measurement

Science.gov (United States)

Liu, Dalong; Xu, Lijuan

2018-01-01

In order to improve the accuracy of robot pose positioning and control, this paper proposed a dynamic tracking measurement robot pose optimization control method based on the actual measurement of D-H parameters of the robot, the parameters is taken with feedback compensation of the robot, according to the geometrical parameters obtained by robot pose tracking measurement, improved multi sensor information fusion the extended Kalan filter method, with continuous self-optimal regression, using the geometric relationship between joint axes for kinematic parameters in the model, link model parameters obtained can timely feedback to the robot, the implementation of parameter correction and compensation, finally we can get the optimal attitude angle, realize the robot pose optimization control experiments were performed. 6R dynamic tracking control of robot joint robot with independent research and development is taken as experimental subject, the simulation results show that the control method improves robot positioning accuracy, and it has the advantages of versatility, simplicity, ease of operation and so on.

Module-based Simulation System for efficient development of nuclear simulation programs

International Nuclear Information System (INIS)

Yoshikawa, Hidekazu; Wakabayashi, Jiro

1990-01-01

Module-based Simulation System (MSS) has been developed to realize a new software environment enabling versatile dynamic simulation of a complex nuclear power plant system flexibly. Described in the paper are (i) fundamental methods utilized in MMS and its software systemization, (ii) development of human interface system to help users in generating integrated simulation programs automatically, and (iii) development of an intelligent user support system for helping users in the two phases of automatical semantic diagnosis and consultation to automatic input data setup for the MSS-generated programs. (author)

Environmental/dynamic mechanical equipment qualification and dynamic electrical equipment qualification program (EDQP)

International Nuclear Information System (INIS)

Hunter, J.A.

1984-01-01

Equipment qualification research is being conducted to investigate acceptable criteria, requirements, and methodologies for the dynamic (including seismic) and environmental qualification of mechanical equipment and for the dynamic (including seismic) qualification of electrical equipment. The program is organized into three elements: (1) General Research, (2) Environmental Research, and (3) Dynamic Research. This paper presents the highlights of the results to date in these three elements of the program

A Recourse-Based Type-2 Fuzzy Programming Method for Water Pollution Control under Uncertainty

Directory of Open Access Journals (Sweden)

Jing Liu

2017-11-01

Full Text Available In this study, a recourse-based type-2 fuzzy programming (RTFP method is developed for supporting water pollution control of basin systems under uncertainty. The RTFP method incorporates type-2 fuzzy programming (TFP within a two-stage stochastic programming with recourse (TSP framework to handle uncertainties expressed as type-2 fuzzy sets (i.e., a fuzzy set in which the membership function is also fuzzy and probability distributions, as well as to reflect the trade-offs between conflicting economic benefits and penalties due to violated policies. The RTFP method is then applied to a real case of water pollution control in the Heshui River Basin (a rural area of China, where chemical oxygen demand (COD, total nitrogen (TN, total phosphorus (TP, and soil loss are selected as major indicators to identify the water pollution control strategies. Solutions of optimal production plans of economic activities under each probabilistic pollutant discharge allowance level and membership grades are obtained. The results are helpful for the authorities in exploring the trade-off between economic objective and pollutant discharge decision-making based on river water pollution control.

Three-dimensional interactive Molecular Dynamics program for the study of defect dynamics in crystals

Science.gov (United States)

Patriarca, M.; Kuronen, A.; Robles, M.; Kaski, K.

2007-01-01

difficult to detect and track even within numerical experiments, especially when one is interested in studying their dynamical properties and time evolution. Furthermore, traditional simulation methods require the storage of a huge amount of data which in turn may imply a long work for their analysis. Method of solution:Simplifications of the simulation work described above strongly depend also on the computer performance. It has now become possible to realize some of such simplifications thanks to the real possibility of using interactive programs. The solution proposed here is based on the development of an interactive graphical simulation program both for avoiding large storage of data and the subsequent elaboration and analysis as well as for visualizing and tracking many phenomena inside three-dimensional samples. However, the full computational power of traditional simulation programs may not be available in general in programs with graphical user interfaces, due to their interactive nature. Nevertheless interactive programs can still be very useful for detecting processes difficult to visualize, restricting the range or making a fine tuning of the parameters, and tailoring the faster programs toward precise targets. Restrictions on the complexity of the problem:The restrictions on the applicability of the program are related to the computer resources available. The graphical interface and interactivity demand computational resources that depend on the particular numerical simulation to be performed. To preserve a balance between speed and resources, the choice of the number of atoms to be simulated is critical. With an average current computer, simulations of systems with more than 10 5 atoms may not be easily feasible on an interactive scheme. Another restriction is related to the fact that the program was originally designed to simulate systems in the solid phase, so that problems in the simulation may occur if some particular physical quantities are computed

Improved non-dimensional dynamic influence function method based on tow-domain method for vibration analysis of membranes

Directory of Open Access Journals (Sweden)

SW Kang

2015-02-01

Full Text Available This article introduces an improved non-dimensional dynamic influence function method using a sub-domain method for efficiently extracting the eigenvalues and mode shapes of concave membranes with arbitrary shapes. The non-dimensional dynamic influence function method (non-dimensional dynamic influence function method, which was developed by the authors in 1999, gives highly accurate eigenvalues for membranes, plates, and acoustic cavities, compared with the finite element method. However, it needs the inefficient procedure of calculating the singularity of a system matrix in the frequency range of interest for extracting eigenvalues and mode shapes. To overcome the inefficient procedure, this article proposes a practical approach to make the system matrix equation of the concave membrane of interest into a form of algebraic eigenvalue problem. It is shown by several case studies that the proposed method has a good convergence characteristics and yields very accurate eigenvalues, compared with an exact method and finite element method (ANSYS.

A simplified dynamic method for field capacity estimation and its parameter analysis

Institute of Scientific and Technical Information of China (English)

Zhen-tao CONG; Hua-fang LÜ; Guang-heng NI

2014-01-01

This paper presents a simplified dynamic method based on the definition of field capacity. Two soil hydraulic characteristics models, the Brooks-Corey (BC) model and the van Genuchten (vG) model, and four soil data groups were used in this study. The relative drainage rate, which is a unique parameter and independent of the soil type in the simplified dynamic method, was analyzed using the pressure-based method with a matric potential of−1/3 bar and the flux-based method with a drainage flux of 0.005 cm/d. As a result, the relative drainage rate of the simplified dynamic method was determined to be 3% per day. This was verified by the similar field capacity results estimated with the three methods for most soils suitable for cultivating plants. In addition, the drainage time calculated with the simplified dynamic method was two to three days, which agrees with the classical definition of field capacity. We recommend the simplified dynamic method with a relative drainage rate of 3% per day due to its simple application and clearly physically-based concept.

Cost-effectiveness of screening programs for Chlamydia trachomatis - A population-based dynamic approach

NARCIS (Netherlands)

Welte, R; Kretzschmar, M; Leidl, R; Van den Hoek, A; Jager, JC; Postma, MJ

2000-01-01

Background: Models commonly used for the economic assessment of chamydial screening programs do not consider population effects. Goal: To develop a novel dynamic approach for the economic evaluation of chlamydial prevention measures and to determine the cost-effectiveness of a general

Analytical methods in rotor dynamics

CERN Document Server

Dimarogonas, Andrew D; Chondros, Thomas G

2013-01-01

The design and construction of rotating machinery operating at supercritical speeds was, in the 1920s, an event of revolutionary importance for the then new branch of dynamics known as rotor dynamics. In the 1960s, another revolution occurred: In less than a decade, imposed by operational and economic needs, an increase in the power of turbomachinery by one order of magnitude took place. Dynamic analysis of complex rotor forms became a necessity, while the importance of approximate methods for dynamic analysis was stressed. Finally, the emergence of fracture mechanics, as a new branch of applied mechanics, provided analytical tools to investigate crack influence on the dynamic behavior of rotors. The scope of this book is based on all these developments. No topics related to the well-known classical problems are included, rather the book deals exclusively with modern high-power turbomachinery.

Reinforcement learning for partially observable dynamic processes: adaptive dynamic programming using measured output data.

Science.gov (United States)

Lewis, F L; Vamvoudakis, Kyriakos G

2011-02-01

Approximate dynamic programming (ADP) is a class of reinforcement learning methods that have shown their importance in a variety of applications, including feedback control of dynamical systems. ADP generally requires full information about the system internal states, which is usually not available in practical situations. In this paper, we show how to implement ADP methods using only measured input/output data from the system. Linear dynamical systems with deterministic behavior are considered herein, which are systems of great interest in the control system community. In control system theory, these types of methods are referred to as output feedback (OPFB). The stochastic equivalent of the systems dealt with in this paper is a class of partially observable Markov decision processes. We develop both policy iteration and value iteration algorithms that converge to an optimal controller that requires only OPFB. It is shown that, similar to Q -learning, the new methods have the important advantage that knowledge of the system dynamics is not needed for the implementation of these learning algorithms or for the OPFB control. Only the order of the system, as well as an upper bound on its "observability index," must be known. The learned OPFB controller is in the form of a polynomial autoregressive moving-average controller that has equivalent performance with the optimal state variable feedback gain.

Rigid Finite Element Method in Analysis of Dynamics of Offshore Structures

CERN Document Server

Wittbrodt, Edmund; Maczyński, Andrzej; Wojciech, Stanisław

2013-01-01

This book describes new methods developed for modelling dynamics of machines commonly used in the offshore industry. These methods are based both on the rigid finite element method, used for the description of link deformations, and on homogeneous transformations and joint coordinates, which is applied to the modelling of multibody system dynamics. In this monograph, the bases of the rigid finite element method  and homogeneous transformations are introduced. Selected models for modelling dynamics of offshore devices are then verified both by using commercial software, based on the finite element method, as well as by using additional methods. Examples of mathematical models of offshore machines, such as a gantry crane for Blowout-Preventer (BOP) valve block transportation, a pedestal crane with shock absorber, and pipe laying machinery are presented. Selected problems of control in offshore machinery as well as dynamic optimization in device control are also discussed. Additionally, numerical simulations of...

QoS Differential Scheduling in Cognitive-Radio-Based Smart Grid Networks: An Adaptive Dynamic Programming Approach.

Science.gov (United States)

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

2016-02-01

As the next-generation power grid, smart grid will be integrated with a variety of novel communication technologies to support the explosive data traffic and the diverse requirements of quality of service (QoS). Cognitive radio (CR), which has the favorable ability to improve the spectrum utilization, provides an efficient and reliable solution for smart grid communications networks. In this paper, we study the QoS differential scheduling problem in the CR-based smart grid communications networks. The scheduler is responsible for managing the spectrum resources and arranging the data transmissions of smart grid users (SGUs). To guarantee the differential QoS, the SGUs are assigned to have different priorities according to their roles and their current situations in the smart grid. Based on the QoS-aware priority policy, the scheduler adjusts the channels allocation to minimize the transmission delay of SGUs. The entire transmission scheduling problem is formulated as a semi-Markov decision process and solved by the methodology of adaptive dynamic programming. A heuristic dynamic programming (HDP) architecture is established for the scheduling problem. By the online network training, the HDP can learn from the activities of primary users and SGUs, and adjust the scheduling decision to achieve the purpose of transmission delay minimization. Simulation results illustrate that the proposed priority policy ensures the low transmission delay of high priority SGUs. In addition, the emergency data transmission delay is also reduced to a significantly low level, guaranteeing the differential QoS in smart grid.

Automatic programming via iterated local search for dynamic job shop scheduling.

Science.gov (United States)

Nguyen, Su; Zhang, Mengjie; Johnston, Mark; Tan, Kay Chen

2015-01-01

Dispatching rules have been commonly used in practice for making sequencing and scheduling decisions. Due to specific characteristics of each manufacturing system, there is no universal dispatching rule that can dominate in all situations. Therefore, it is important to design specialized dispatching rules to enhance the scheduling performance for each manufacturing environment. Evolutionary computation approaches such as tree-based genetic programming (TGP) and gene expression programming (GEP) have been proposed to facilitate the design task through automatic design of dispatching rules. However, these methods are still limited by their high computational cost and low exploitation ability. To overcome this problem, we develop a new approach to automatic programming via iterated local search (APRILS) for dynamic job shop scheduling. The key idea of APRILS is to perform multiple local searches started with programs modified from the best obtained programs so far. The experiments show that APRILS outperforms TGP and GEP in most simulation scenarios in terms of effectiveness and efficiency. The analysis also shows that programs generated by APRILS are more compact than those obtained by genetic programming. An investigation of the behavior of APRILS suggests that the good performance of APRILS comes from the balance between exploration and exploitation in its search mechanism.

SoC-Based Dynamic Power Sharing Method with AC-Bus Voltage Restoration for Microgrid Applications

DEFF Research Database (Denmark)

Lu, Xiaonan; Sun, Kai; Guerrero, Josep M.

2012-01-01

In a microgrid system, distributed energy storage units are commonly employed as the energy buffers. In this paper, a dynamic power sharing method based on the state-of-charge (SoC) of each energy storage unit is proposed. Droop control is employed as the basic control strategy for the distributed...

Joint Chance-Constrained Dynamic Programming

Science.gov (United States)

Ono, Masahiro; Kuwata, Yoshiaki; Balaram, J. Bob

2012-01-01

This paper presents a novel dynamic programming algorithm with a joint chance constraint, which explicitly bounds the risk of failure in order to maintain the state within a specified feasible region. A joint chance constraint cannot be handled by existing constrained dynamic programming approaches since their application is limited to constraints in the same form as the cost function, that is, an expectation over a sum of one-stage costs. We overcome this challenge by reformulating the joint chance constraint into a constraint on an expectation over a sum of indicator functions, which can be incorporated into the cost function by dualizing the optimization problem. As a result, the primal variables can be optimized by a standard dynamic programming, while the dual variable is optimized by a root-finding algorithm that converges exponentially. Error bounds on the primal and dual objective values are rigorously derived. We demonstrate the algorithm on a path planning problem, as well as an optimal control problem for Mars entry, descent and landing. The simulations are conducted using a real terrain data of Mars, with four million discrete states at each time step.

Approximate Dynamic Programming Solving the Curses of Dimensionality

CERN Document Server

Powell, Warren B

2011-01-01

Praise for the First Edition "Finally, a book devoted to dynamic programming and written using the language of operations research (OR)! This beautiful book fills a gap in the libraries of OR specialists and practitioners."-Computing Reviews This new edition showcases a focus on modeling and computation for complex classes of approximate dynamic programming problems Understanding approximate dynamic programming (ADP) is vital in order to develop practical and high-quality solutions to complex industrial problems, particularly when those problems involve making decisions in the presence of unce

Permission-Based Separation Logic for Multithreaded Java Programs

NARCIS (Netherlands)

Haack, Christian; Huisman, Marieke; Hurlin, C.

2011-01-01

This paper motivates and presents a program logic for reasoning about multithreaded Java-like programs with concurrency primitives such as dynamic thread creation, thread joining and reentrant object monitors. The logic is based on concurrent separation logic. It is the first detailed adaptation of

Quadratic temporal finite element method for linear elastic structural dynamics based on mixed convolved action

International Nuclear Information System (INIS)

Kim, Jin Kyu; Kim, Dong Keon

2016-01-01

A common approach for dynamic analysis in current practice is based on a discrete time-integration scheme. This approach can be largely attributed to the absence of a true variational framework for initial value problems. To resolve this problem, a new stationary variational principle was recently established for single-degree-of-freedom oscillating systems using mixed variables, fractional derivatives and convolutions of convolutions. In this mixed convolved action, all the governing differential equations and initial conditions are recovered from the stationarity of a single functional action. Thus, the entire description of linear elastic dynamical systems is encapsulated. For its practical application to structural dynamics, this variational formalism is systemically extended to linear elastic multidegree- of-freedom systems in this study, and a corresponding weak form is numerically implemented via a quadratic temporal finite element method. The developed numerical method is symplectic and unconditionally stable with respect to a time step for the underlying conservative system. For the forced-damped vibration, a three-story shear building is used as an example to investigate the performance of the developed numerical method, which provides accurate results with good convergence characteristics

Quadratic temporal finite element method for linear elastic structural dynamics based on mixed convolved action

Energy Technology Data Exchange (ETDEWEB)

Kim, Jin Kyu [School of Architecture and Architectural Engineering, Hanyang University, Ansan (Korea, Republic of); Kim, Dong Keon [Dept. of Architectural Engineering, Dong A University, Busan (Korea, Republic of)

2016-09-15

A common approach for dynamic analysis in current practice is based on a discrete time-integration scheme. This approach can be largely attributed to the absence of a true variational framework for initial value problems. To resolve this problem, a new stationary variational principle was recently established for single-degree-of-freedom oscillating systems using mixed variables, fractional derivatives and convolutions of convolutions. In this mixed convolved action, all the governing differential equations and initial conditions are recovered from the stationarity of a single functional action. Thus, the entire description of linear elastic dynamical systems is encapsulated. For its practical application to structural dynamics, this variational formalism is systemically extended to linear elastic multidegree- of-freedom systems in this study, and a corresponding weak form is numerically implemented via a quadratic temporal finite element method. The developed numerical method is symplectic and unconditionally stable with respect to a time step for the underlying conservative system. For the forced-damped vibration, a three-story shear building is used as an example to investigate the performance of the developed numerical method, which provides accurate results with good convergence characteristics.

Nonlinear dynamic analysis using Petrov-Galerkin natural element method

International Nuclear Information System (INIS)

Lee, Hong Woo; Cho, Jin Rae

2004-01-01

According to our previous study, it is confirmed that the Petrov-Galerkin Natural Element Method (PG-NEM) completely resolves the numerical integration inaccuracy in the conventional Bubnov-Galerkin Natural Element Method (BG-NEM). This paper is an extension of PG-NEM to two-dimensional nonlinear dynamic problem. For the analysis, a constant average acceleration method and a linearized total Lagrangian formulation is introduced with the PG-NEM. At every time step, the grid points are updated and the shape functions are reproduced from the relocated nodal distribution. This process enables the PG-NEM to provide more accurate and robust approximations. The representative numerical experiments performed by the test Fortran program, and the numerical results confirmed that the PG-NEM effectively and accurately approximates the nonlinear dynamic problem

Rigid finite element method in analysis of dynamics of offshore structures

Energy Technology Data Exchange (ETDEWEB)

Wittbrodt, Edmund [Gdansk Univ. of Technology (Poland); Szczotka, Marek; Maczynski, Andrzej; Wojciech, Stanislaw [Bielsko-Biala Univ. (Poland)

2013-07-01

This book describes new methods developed for modelling dynamics of machines commonly used in the offshore industry. These methods are based both on the rigid finite element method, used for the description of link deformations, and on homogeneous transformations and joint coordinates, which is applied to the modelling of multibody system dynamics. In this monograph, the bases of the rigid finite element method and homogeneous transformations are introduced. Selected models for modelling dynamics of offshore devices are then verified both by using commercial software, based on the finite element method, as well as by using additional methods. Examples of mathematical models of offshore machines, such as a gantry crane for Blowout-Preventer (BOP) valve block transportation, a pedestal crane with shock absorber, and pipe laying machinery are presented. Selected problems of control in offshore machinery as well as dynamic optimization in device control are also discussed. Additionally, numerical simulations of pipe-laying operations taking active reel drive into account are shown.

New method dynamically models hydrocarbon fractionation

Energy Technology Data Exchange (ETDEWEB)

Kesler, M.G.; Weissbrod, J.M.; Sheth, B.V. [Kesler Engineering, East Brunswick, NJ (United States)

1995-10-01

A new method for calculating distillation column dynamics can be used to model time-dependent effects of independent disturbances for a range of hydrocarbon fractionation. It can model crude atmospheric and vacuum columns, with relatively few equilibrium stages and a large number of components, to C{sub 3} splitters, with few components and up to 300 equilibrium stages. Simulation results are useful for operations analysis, process-control applications and closed-loop control in petroleum, petrochemical and gas processing plants. The method is based on an implicit approach, where the time-dependent variations of inventory, temperatures, liquid and vapor flows and compositions are superimposed at each time step on the steady-state solution. Newton-Raphson (N-R) techniques are then used to simultaneously solve the resulting finite-difference equations of material, equilibrium and enthalpy balances that characterize distillation dynamics. The important innovation is component-aggregation and tray-aggregation to contract the equations without compromising accuracy. This contraction increases the N-R calculations` stability. It also significantly increases calculational speed, which is particularly important in dynamic simulations. This method provides a sound basis for closed-loop, supervisory control of distillation--directly or via multivariable controllers--based on a rigorous, phenomenological column model.

BEAMPATH: a program library for beam dynamics simulation in linear accelerators

International Nuclear Information System (INIS)

Batygin, Y.K.

1992-01-01

A structured programming technique was used to develop software for space charge dominated beams investigation in linear accelerators. The method includes hierarchical program design using program independent modules and a flexible combination of modules to provide a most effective version of structure for every specific case of simulation. A modular program BEAMPATH was developed for 2D and 3D particle-in-cell simulation of beam dynamics in a structure containing RF gaps, radio-frequency quadrupoles (RFQ), multipole lenses, waveguides, bending magnets and solenoids. (author) 5 refs.; 2 figs

Evaluation of data reduction methods for dynamic PET series based on Monte Carlo techniques and the NCAT phantom

International Nuclear Information System (INIS)

Thireou, Trias; Rubio Guivernau, Jose Luis; Atlamazoglou, Vassilis; Ledesma, Maria Jesus; Pavlopoulos, Sotiris; Santos, Andres; Kontaxakis, George

2006-01-01

A realistic dynamic positron-emission tomography (PET) thoracic study was generated, using the 4D NURBS-based (non-uniform rational B-splines) cardiac-torso (NCAT) phantom and a sophisticated model of the PET imaging process, simulating two solitary pulmonary nodules. Three data reduction and blind source separation methods were applied to the simulated data: principal component analysis, independent component analysis and similarity mapping. All methods reduced the initial amount of image data to a smaller, comprehensive and easily managed set of parametric images, where structures were separated based on their different kinetic characteristics and the lesions were readily identified. The results indicate that the above-mentioned methods can provide an accurate tool for the support of both visual inspection and subsequent detailed kinetic analysis of the dynamic series via compartmental or non-compartmental models

SEWER NETWORK DISCHARGE OPTIMIZATION USING THE DYNAMIC PROGRAMMING

Directory of Open Access Journals (Sweden)

Viorel MINZU

2015-12-01

Full Text Available It is necessary to adopt an optimal control that allows an efficient usage of the existing sewer networks, in order to avoid the building of new retention facilities. The main objective of the control action is to minimize the overflow volume of a sewer network. This paper proposes a method to apply a solution obtained by discrete dynamic programming through a realistic closed loop system.

Dynamics based alignment of proteins: an alternative approach to quantify dynamic similarity

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Lyngsø Rune

2010-04-01

Full Text Available Abstract Background The dynamic motions of many proteins are central to their function. It therefore follows that the dynamic requirements of a protein are evolutionary constrained. In order to assess and quantify this, one needs to compare the dynamic motions of different proteins. Comparing the dynamics of distinct proteins may also provide insight into how protein motions are modified by variations in sequence and, consequently, by structure. The optimal way of comparing complex molecular motions is, however, far from trivial. The majority of comparative molecular dynamics studies performed to date relied upon prior sequence or structural alignment to define which residues were equivalent in 3-dimensional space. Results Here we discuss an alternative methodology for comparative molecular dynamics that does not require any prior alignment information. We show it is possible to align proteins based solely on their dynamics and that we can use these dynamics-based alignments to quantify the dynamic similarity of proteins. Our method was tested on 10 representative members of the PDZ domain family. Conclusions As a result of creating pair-wise dynamics-based alignments of PDZ domains, we have found evolutionarily conserved patterns in their backbone dynamics. The dynamic similarity of PDZ domains is highly correlated with their structural similarity as calculated with Dali. However, significant differences in their dynamics can be detected indicating that sequence has a more refined role to play in protein dynamics than just dictating the overall fold. We suggest that the method should be generally applicable.

Constitutive Investigation on Viscoelasticity of PolyVinyl Butyral: Experiments Based on Dynamic Mechanical Analysis Method

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Bohan Liu

2014-01-01

Full Text Available PolyVinyl Butyral (PVB film is now widely used in automotive industry and architectures serving as the protective interlayer. The dynamic modulus of PVB is measured through systematic experiments based on Dynamic Mechanical Analysis (DMA method at various temperatures, heating rates, and vibration frequencies. Further, viscoelasticity of PVB influenced by time and temperature is systematically studied. Fitted empirical formulas describing the relationship between glass transition temperature and frequency, as well as the heating rate of PVB, are established. The master curve of PVB at 293 K is suggested based on the experiment data as to express the dynamic modulus variation at various frequencies in a wider range. Constitutive behavior of PVB is then analyzed based on Generalized Maxwell (GM model and Fractional Derivative (FD model, respectively. It is shown that PVB has higher efficiency of energy dissipation in its high energy absorption state, while both fifth-order GM model and FD model can characterize the viscoelasticity of PVB at glassy transition area. Results may offer useful fundamental experimental data and important constitutive characteristics of PVB and shed lights on further studies on viscoelasticity behavior of PVB and energy mitigation ability of laminated glass.

Dynamic Error Analysis Method for Vibration Shape Reconstruction of Smart FBG Plate Structure

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Hesheng Zhang

2016-01-01

Full Text Available Shape reconstruction of aerospace plate structure is an important issue for safe operation of aerospace vehicles. One way to achieve such reconstruction is by constructing smart fiber Bragg grating (FBG plate structure with discrete distributed FBG sensor arrays using reconstruction algorithms in which error analysis of reconstruction algorithm is a key link. Considering that traditional error analysis methods can only deal with static data, a new dynamic data error analysis method are proposed based on LMS algorithm for shape reconstruction of smart FBG plate structure. Firstly, smart FBG structure and orthogonal curved network based reconstruction method is introduced. Then, a dynamic error analysis model is proposed for dynamic reconstruction error analysis. Thirdly, the parameter identification is done for the proposed dynamic error analysis model based on least mean square (LMS algorithm. Finally, an experimental verification platform is constructed and experimental dynamic reconstruction analysis is done. Experimental results show that the dynamic characteristics of the reconstruction performance for plate structure can be obtained accurately based on the proposed dynamic error analysis method. The proposed method can also be used for other data acquisition systems and data processing systems as a general error analysis method.

Modular programming method at JAERI

International Nuclear Information System (INIS)

Asai, Kiyoshi; Katsuragi, Satoru

1982-02-01

In this report the histories, concepts and a method for the construction and maintenance of nuclear code systems of Japan Atomic Energy Research Institute (JAERI) are presented. The method is mainly consisted of novel computer features. The development process of the features and experiences with them which required many man-months and efforts of scientists and engineers of JAERI and a computer manufacturer are also described. One of the features is a file handling program named datapool. The program is being used in code systems which are under development at JAERI. The others are computer features such as dynamic linking, reentrant coding of Fortran programs, interactive programming facility, document editor, quick system output viewer and editor, flexible man-machine interactive Fortran executor, and selective use of time-sharing or batch oriented computer in an interactive porgramming environment. In 1980 JAERI has replaced its two old computer systems by three FACOM M-200 computer systems and they have such features as mentioned above. Since 1981 most code systems, or even big single codes can be changed to modular code systems even if the developers or users of the systems will not recognize the fact that they are using modular code systems. The purpose of this report is to describe our methodology of modular programming from aspects of computer features and some of their applications to nuclear codes to get sympathetic understanding of it from persons of organizations who are concerned with the effective use of computers, especially, in nuclear research fields. (author)

Adaptive dynamic programming with applications in optimal control

CERN Document Server

Liu, Derong; Wang, Ding; Yang, Xiong; Li, Hongliang

2017-01-01

This book covers the most recent developments in adaptive dynamic programming (ADP). The text begins with a thorough background review of ADP making sure that readers are sufficiently familiar with the fundamentals. In the core of the book, the authors address first discrete- and then continuous-time systems. Coverage of discrete-time systems starts with a more general form of value iteration to demonstrate its convergence, optimality, and stability with complete and thorough theoretical analysis. A more realistic form of value iteration is studied where value function approximations are assumed to have finite errors. Adaptive Dynamic Programming also details another avenue of the ADP approach: policy iteration. Both basic and generalized forms of policy-iteration-based ADP are studied with complete and thorough theoretical analysis in terms of convergence, optimality, stability, and error bounds. Among continuous-time systems, the control of affine and nonaffine nonlinear systems is studied using the ADP app...

Finite-Temperature Non-equilibrium Quasicontinuum Method based on Langevin Dynamics

Energy Technology Data Exchange (ETDEWEB)

Marian, J; Venturini, G; Hansen, B; Knap, J; Ortiz, M; Campbell, G

2009-05-08

The concurrent bridging of molecular dynamics and continuum thermodynamics presents a number of challenges, mostly associated with energy transmission and changes in the constitutive description of a material across domain boundaries. In this paper, we propose a framework for simulating coarse dynamic systems in the canonical ensemble using the Quasicontinuum method (QC). The equations of motion are expressed in reduced QC coordinates and are strictly derived from dissipative Lagrangian mechanics. The derivation naturally leads to a classical Langevin implementation where the timescale is governed by vibrations emanating from the finest length scale occurring in the computational cell. The equations of motion are integrated explicitly via Newmark's ({beta} = 0; {gamma} = 1/2) method, leading to a robust numerical behavior and energy conservation. In its current form, the method only allows for wave propagations supported by the less compliant of the two meshes across a heterogeneous boundary, which requires the use of overdamped dynamics to avoid spurious heating due to reflected vibrations. We have applied the method to two independent crystallographic systems characterized by different interatomic potentials (Al and Ta) and have measured thermal expansion in order to quantify the vibrational entropy loss due to homogenization. We rationalize the results in terms of system size, mesh coarseness, and nodal cluster diameter within the framework of the quasiharmonic approximation. For Al, we find that the entropy loss introduced by mesh coarsening varies linearly with the element size, and that volumetric effects are not critical in driving the anharmonic behavior of the simulated systems. In Ta, the anomalies of the interatomic potential employed result in negative and zero thermal expansion at low and high temperatures, respectively.

A dynamic integrated fault diagnosis method for power transformers.

Science.gov (United States)

Gao, Wensheng; Bai, Cuifen; Liu, Tong

2015-01-01

In order to diagnose transformer fault efficiently and accurately, a dynamic integrated fault diagnosis method based on Bayesian network is proposed in this paper. First, an integrated fault diagnosis model is established based on the causal relationship among abnormal working conditions, failure modes, and failure symptoms of transformers, aimed at obtaining the most possible failure mode. And then considering the evidence input into the diagnosis model is gradually acquired and the fault diagnosis process in reality is multistep, a dynamic fault diagnosis mechanism is proposed based on the integrated fault diagnosis model. Different from the existing one-step diagnosis mechanism, it includes a multistep evidence-selection process, which gives the most effective diagnostic test to be performed in next step. Therefore, it can reduce unnecessary diagnostic tests and improve the accuracy and efficiency of diagnosis. Finally, the dynamic integrated fault diagnosis method is applied to actual cases, and the validity of this method is verified.

A Dynamic Integrated Fault Diagnosis Method for Power Transformers

Science.gov (United States)

Gao, Wensheng; Liu, Tong

2015-01-01

In order to diagnose transformer fault efficiently and accurately, a dynamic integrated fault diagnosis method based on Bayesian network is proposed in this paper. First, an integrated fault diagnosis model is established based on the causal relationship among abnormal working conditions, failure modes, and failure symptoms of transformers, aimed at obtaining the most possible failure mode. And then considering the evidence input into the diagnosis model is gradually acquired and the fault diagnosis process in reality is multistep, a dynamic fault diagnosis mechanism is proposed based on the integrated fault diagnosis model. Different from the existing one-step diagnosis mechanism, it includes a multistep evidence-selection process, which gives the most effective diagnostic test to be performed in next step. Therefore, it can reduce unnecessary diagnostic tests and improve the accuracy and efficiency of diagnosis. Finally, the dynamic integrated fault diagnosis method is applied to actual cases, and the validity of this method is verified. PMID:25685841

Fluid dynamics computer programs for NERVA turbopump

Science.gov (United States)

Brunner, J. J.

1972-01-01

During the design of the NERVA turbopump, numerous computer programs were developed for the analyses of fluid dynamic problems within the machine. Program descriptions, example cases, users instructions, and listings for the majority of these programs are presented.

Management Optimization of Saguling Reservoir with Bellman Dynamic Programming and “Du Couloir” Iterative Method

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Mariana Marselina

2016-08-01

Full Text Available The increasingly growth of population and industry sector have lead to an enhanced demand for electrical energy. One of the electricity providers in the area of Java-Madura Bali (Jamali is Saguling Reservoir. Saguling Reservoir is one of the three reservoirs that stem the flow of Citarum River in advance of to Jatiluhur and Cirata Reservoir. The average electricity production of Saguling Reservoir was 2,334,318.138 MWh/year in the period of 1986-2014. The water intake of Saguling Reservoir is the upstream Citarum Watershed with an area of 2340.88 km2 which also serves as the irrigation, inland fisheries, recreation, and other activities. An effort to improve the function of Saguling Reservoir in producing electrical energy is by optimizing the reservoir management. The optimization of Saguling Reservoir management in this study refers to Government Regulation No. 37/2010 on Dam/Reservoir Article 44 which states that the system of reservoir management consisting of the operation system in dry years, normal years, and wet years. In this research, the determination of the trajectory guideline in Saguling operation was divided in dry, normal and wet years. Trajectory guideline was conducted based on the electricity price of turbine inflow that various in every month. The determination of the trajectory guideline in various electricity price was done by using Program Dynamic Bellman (PD Bellman and “Du Couloir” iterative method which the objective to optimize the gain from electricity production. and “Du Couloir” iterative method was development of PD Bellman that can calculate the value of gain with a smaller discretization until 0,1 juta m3 effectively where PD Bellman just calculate until 10 million m3.  Smaller discretization can give maximum benefit from electricity production and the trajectory guideline will be closer to trajectory actual so optimization of Saguling operation will be achieved.

Permission-based separation logic for multi-threaded Java programs

NARCIS (Netherlands)

Amighi, A.; Haack, Christian; Huisman, Marieke; Hurlin, C.

This paper presents a program logic for reasoning about multithreaded Java-like programs with concurrency primitives such as dynamic thread creation, thread joining and reentrant object monitors. The logic is based on concurrent separation logic. It is the first detailed adaptation of concurrent

Dynamic and quantitative method of analyzing service consistency evolution based on extended hierarchical finite state automata.

Science.gov (United States)

Fan, Linjun; Tang, Jun; Ling, Yunxiang; Li, Benxian

2014-01-01

This paper is concerned with the dynamic evolution analysis and quantitative measurement of primary factors that cause service inconsistency in service-oriented distributed simulation applications (SODSA). Traditional methods are mostly qualitative and empirical, and they do not consider the dynamic disturbances among factors in service's evolution behaviors such as producing, publishing, calling, and maintenance. Moreover, SODSA are rapidly evolving in terms of large-scale, reusable, compositional, pervasive, and flexible features, which presents difficulties in the usage of traditional analysis methods. To resolve these problems, a novel dynamic evolution model extended hierarchical service-finite state automata (EHS-FSA) is constructed based on finite state automata (FSA), which formally depict overall changing processes of service consistency states. And also the service consistency evolution algorithms (SCEAs) based on EHS-FSA are developed to quantitatively assess these impact factors. Experimental results show that the bad reusability (17.93% on average) is the biggest influential factor, the noncomposition of atomic services (13.12%) is the second biggest one, and the service version's confusion (1.2%) is the smallest one. Compared with previous qualitative analysis, SCEAs present good effectiveness and feasibility. This research can guide the engineers of service consistency technologies toward obtaining a higher level of consistency in SODSA.

Dynamic and Quantitative Method of Analyzing Service Consistency Evolution Based on Extended Hierarchical Finite State Automata

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Linjun Fan

2014-01-01

Full Text Available This paper is concerned with the dynamic evolution analysis and quantitative measurement of primary factors that cause service inconsistency in service-oriented distributed simulation applications (SODSA. Traditional methods are mostly qualitative and empirical, and they do not consider the dynamic disturbances among factors in service’s evolution behaviors such as producing, publishing, calling, and maintenance. Moreover, SODSA are rapidly evolving in terms of large-scale, reusable, compositional, pervasive, and flexible features, which presents difficulties in the usage of traditional analysis methods. To resolve these problems, a novel dynamic evolution model extended hierarchical service-finite state automata (EHS-FSA is constructed based on finite state automata (FSA, which formally depict overall changing processes of service consistency states. And also the service consistency evolution algorithms (SCEAs based on EHS-FSA are developed to quantitatively assess these impact factors. Experimental results show that the bad reusability (17.93% on average is the biggest influential factor, the noncomposition of atomic services (13.12% is the second biggest one, and the service version’s confusion (1.2% is the smallest one. Compared with previous qualitative analysis, SCEAs present good effectiveness and feasibility. This research can guide the engineers of service consistency technologies toward obtaining a higher level of consistency in SODSA.

Evaluation of methods to reduce background using the Python-based ELISA_QC program.

Science.gov (United States)

Webster, Rose P; Cohen, Cinder F; Saeed, Fatima O; Wetzel, Hanna N; Ball, William J; Kirley, Terence L; Norman, Andrew B

2018-05-01

Almost all immunological approaches [immunohistochemistry, enzyme-linked immunosorbent assay (ELISA), Western blot], that are used to quantitate specific proteins have had to address high backgrounds due to non-specific reactivity. We report here for the first time a quantitative comparison of methods for reduction of the background of commercial biotinylated antibodies using the Python-based ELISA_QC program. This is demonstrated using a recombinant humanized anti-cocaine monoclonal antibody. Several approaches, such as adjustment of the incubation time and the concentration of blocking agent, as well as the dilution of secondary antibodies, have been explored to address this issue. In this report, systematic comparisons of two different methods, contrasted with other more traditional methods to address this problem are provided. Addition of heparin (HP) at 1 μg/ml to the wash buffer prior to addition of the secondary biotinylated antibody reduced the elevated background absorbance values (from a mean of 0.313 ± 0.015 to 0.137 ± 0.002). A novel immunodepletion (ID) method also reduced the background (from a mean of 0.331 ± 0.010 to 0.146 ± 0.013). Overall, the ID method generated more similar results at each concentration of the ELISA standard curve to that using the standard lot 1 than the HP method, as analyzed by the Python-based ELISA_QC program. We conclude that the ID method, while more laborious, provides the best solution to resolve the high background seen with specific lots of biotinylated secondary antibody. Copyright © 2018. Published by Elsevier B.V.

Linear dynamic analysis of arbitrary thin shells modal superposition by using finite element method

International Nuclear Information System (INIS)

Goncalves Filho, O.J.A.

1978-11-01

The linear dynamic behaviour of arbitrary thin shells by the Finite Element Method is studied. Plane triangular elements with eighteen degrees of freedom each are used. The general equations of movement are obtained from the Hamilton Principle and solved by the Modal Superposition Method. The presence of a viscous type damping can be considered by means of percentages of the critical damping. An automatic computer program was developed to provide the vibratory properties and the dynamic response to several types of deterministic loadings, including temperature effects. The program was written in FORTRAN IV for the Burroughs B-6700 computer. (author)

An improved EMD method for modal identification and a combined static-dynamic method for damage detection

Science.gov (United States)

Yang, Jinping; Li, Peizhen; Yang, Youfa; Xu, Dian

2018-04-01

Empirical mode decomposition (EMD) is a highly adaptable signal processing method. However, the EMD approach has certain drawbacks, including distortions from end effects and mode mixing. In the present study, these two problems are addressed using an end extension method based on the support vector regression machine (SVRM) and a modal decomposition method based on the characteristics of the Hilbert transform. The algorithm includes two steps: using the SVRM, the time series data are extended at both endpoints to reduce the end effects, and then, a modified EMD method using the characteristics of the Hilbert transform is performed on the resulting signal to reduce mode mixing. A new combined static-dynamic method for identifying structural damage is presented. This method combines the static and dynamic information in an equilibrium equation that can be solved using the Moore-Penrose generalized matrix inverse. The combination method uses the differences in displacements of the structure with and without damage and variations in the modal force vector. Tests on a four-story, steel-frame structure were conducted to obtain static and dynamic responses of the structure. The modal parameters are identified using data from the dynamic tests and improved EMD method. The new method is shown to be more accurate and effective than the traditional EMD method. Through tests with a shear-type test frame, the higher performance of the proposed static-dynamic damage detection approach, which can detect both single and multiple damage locations and the degree of the damage, is demonstrated. For structures with multiple damage, the combined approach is more effective than either the static or dynamic method. The proposed EMD method and static-dynamic damage detection method offer improved modal identification and damage detection, respectively, in structures.

Mathematical programming methods for large-scale topology optimization problems

DEFF Research Database (Denmark)

Rojas Labanda, Susana

for mechanical problems, but has rapidly extended to many other disciplines, such as fluid dynamics and biomechanical problems. However, the novelty and improvements of optimization methods has been very limited. It is, indeed, necessary to develop of new optimization methods to improve the final designs......, and at the same time, reduce the number of function evaluations. Nonlinear optimization methods, such as sequential quadratic programming and interior point solvers, have almost not been embraced by the topology optimization community. Thus, this work is focused on the introduction of this kind of second...... for the classical minimum compliance problem. Two of the state-of-the-art optimization algorithms are investigated and implemented for this structural topology optimization problem. A Sequential Quadratic Programming (TopSQP) and an interior point method (TopIP) are developed exploiting the specific mathematical...

Separation of left and right lungs using 3D information of sequential CT images and a guided dynamic programming algorithm

Science.gov (United States)

Park, Sang Cheol; Leader, Joseph Ken; Tan, Jun; Lee, Guee Sang; Kim, Soo Hyung; Na, In Seop; Zheng, Bin

2011-01-01

Objective this article presents a new computerized scheme that aims to accurately and robustly separate left and right lungs on CT examinations. Methods we developed and tested a method to separate the left and right lungs using sequential CT information and a guided dynamic programming algorithm using adaptively and automatically selected start point and end point with especially severe and multiple connections. Results the scheme successfully identified and separated all 827 connections on the total 4034 CT images in an independent testing dataset of CT examinations. The proposed scheme separated multiple connections regardless of their locations, and the guided dynamic programming algorithm reduced the computation time to approximately 4.6% in comparison with the traditional dynamic programming and avoided the permeation of the separation boundary into normal lung tissue. Conclusions The proposed method is able to robustly and accurately disconnect all connections between left and right lungs and the guided dynamic programming algorithm is able to remove redundant processing. PMID:21412104

Dynamic Programming: An Introduction by Example

Science.gov (United States)

Zietz, Joachim

2007-01-01

The author introduces some basic dynamic programming techniques, using examples, with the help of the computer algebra system "Maple". The emphasis is on building confidence and intuition for the solution of dynamic problems in economics. To integrate the material better, the same examples are used to introduce different techniques. One covers the…

Dynamic Programming for Re-Mapping Noisy Fixations in Translation Tasks

DEFF Research Database (Denmark)

Carl, Michael

2013-01-01

possible fixated symbols, including those on the line above and below the naïve fixation mapping. In a second step a dynamic programming algorithm applies a number of heuristics to find the best path through the lattice, based on the probable distance in characters, in words and in pixels between...

Free Vibration Analysis for Shells of Revolution Using an Exact Dynamic Stiffness Method

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Xudong Chen

2016-01-01

Full Text Available An exact generalised formulation for the free vibration of shells of revolution with general shaped meridians and arbitrary boundary conditions is introduced. Starting from the basic shell theories, the vibration governing equations are obtained in the Hamilton form, from which dynamic stiffness is computed using the ordinary differential equations solver COLSYS. Natural frequencies and modes are determined by employing the Wittrick-Williams (W-W algorithm in conjunction with the recursive Newton’s method, thus expanding the applications of the abovementioned techniques from one-dimensional skeletal structures to two-dimensional shells of revolution. A solution for solving the number of clamped-end frequencies J0 in the W-W algorithm is presented for both uniform and nonuniform shell segment members. Based on these theories, a FORTRAN program is written. Numerical examples on circular cylindrical shells, hyperboloidal cooling tower shells, and spherical shells are given, and error analysis is performed. The convergence of the proposed method on J0 is verified, and comparisons with frequencies from existing literature show that the dynamic stiffness method is robust, reliable, and accurate.

Studying Operation Rules of Cascade Reservoirs Based on Multi-Dimensional Dynamics Programming

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Zhiqiang Jiang

2017-12-01

Full Text Available Although many optimization models and methods are applied to the optimization of reservoir operation at present, the optimal operation decision that is made through these models and methods is just a retrospective review. Due to the limitation of hydrological prediction accuracy, it is practical and feasible to obtain the suboptimal or satisfactory solution by the established operation rules in the actual reservoir operation, especially for the mid- and long-term operation. In order to obtain the optimized sample data with global optimality; and make the extracted operation rules more reasonable and reliable, this paper presents the multi-dimensional dynamic programming model of the optimal joint operation of cascade reservoirs and provides the corresponding recursive equation and the specific solving steps. Taking Li Xianjiang cascade reservoirs as a case study, seven uncertain problems in the whole operation period of the cascade reservoirs are summarized after a detailed analysis to the obtained optimal sample data, and two sub-models are put forward to solve these uncertain problems. Finally, by dividing the whole operation period into four characteristic sections, this paper extracts the operation rules of each reservoir for each section respectively. When compared the simulation results of the extracted operation rules with the conventional joint operation method; the result indicates that the power generation of the obtained rules has a certain degree of improvement both in inspection years and typical years (i.e., wet year; normal year and dry year. So, the rationality and effectiveness of the extracted operation rules are verified by the comparative analysis.

Phonon-mediated Thermal Conductivity in Ionic Solids by Lattice Dynamics-based Methods

Energy Technology Data Exchange (ETDEWEB)

Chernatynskiy, Aleksandr [Univ. of Florida, Gainesville, FL (United States); Turney, Joseph E. [Carnegie Mellon Univ., Pittsburgh, PA (United States); McGaughey, Alan J. H. [Carnegie Mellon Univ., Pittsburgh, PA (United States); Amon, Christina H. [Univ. of Toronto, ON (Canada); Phillpot, Simon R. [Univ. of Florida, Gainesville, FL (United States)

2011-07-22

Phonon properties predicted from lattice dynamics calculations and the Boltzmann Transport Equation (BTE) are used to elucidate the thermal-transport properties of ionic materials. It is found that a rigorous treatment of the Coulombic interactions within the harmonic analysis is needed for the analysis of the phonon structure of the solid, while a short-range approximation is sufficient for the third-order force constants. The effects on the thermal conductivity of the relaxation time approximation, the classical approximation to the phonon statistics, the direct summation method for the electrostatic interactions, and the quasi-harmonic approximation to lattice dynamics are quantified. Quantitative agreement is found between predictions from molecular dynamics simulations (a method valid at temperatures above the Debye temperature) and the BTE result within quasi-harmonic approximation over a wide temperature range.

An algorithm for the solution of dynamic linear programs

Science.gov (United States)

Psiaki, Mark L.

1989-01-01

The algorithm's objective is to efficiently solve Dynamic Linear Programs (DLP) by taking advantage of their special staircase structure. This algorithm constitutes a stepping stone to an improved algorithm for solving Dynamic Quadratic Programs, which, in turn, would make the nonlinear programming method of Successive Quadratic Programs more practical for solving trajectory optimization problems. The ultimate goal is to being trajectory optimization solution speeds into the realm of real-time control. The algorithm exploits the staircase nature of the large constraint matrix of the equality-constrained DLPs encountered when solving inequality-constrained DLPs by an active set approach. A numerically-stable, staircase QL factorization of the staircase constraint matrix is carried out starting from its last rows and columns. The resulting recursion is like the time-varying Riccati equation from multi-stage LQR theory. The resulting factorization increases the efficiency of all of the typical LP solution operations over that of a dense matrix LP code. At the same time numerical stability is ensured. The algorithm also takes advantage of dynamic programming ideas about the cost-to-go by relaxing active pseudo constraints in a backwards sweeping process. This further decreases the cost per update of the LP rank-1 updating procedure, although it may result in more changes of the active set that if pseudo constraints were relaxed in a non-stagewise fashion. The usual stability of closed-loop Linear/Quadratic optimally-controlled systems, if it carries over to strictly linear cost functions, implies that the saving due to reduced factor update effort may outweigh the cost of an increased number of updates. An aerospace example is presented in which a ground-to-ground rocket's distance is maximized. This example demonstrates the applicability of this class of algorithms to aerospace guidance. It also sheds light on the efficacy of the proposed pseudo constraint relaxation

Dynamic Loads and Wake Prediction for Large Wind Turbines Based on Free Wake Method

Institute of Scientific and Technical Information of China (English)

Cao Jiufa; Wang Tongguang; Long Hui; Ke Shitang; Xu Bofeng

2015-01-01

With large scale wind turbines ,the issue of aerodynamic elastic response is even more significant on dy-namic behaviour of the system .Unsteady free vortex wake method is proposed to calculate the shape of wake and aerodynamic load .Considering the effect of aerodynamic load ,inertial load and gravity load ,the decoupling dy-namic equations are established by using finite element method in conjunction of the modal method and equations are solved numerically by Newmark approach .Finally ,the numerical simulation of a large scale wind turbine is performed through coupling the free vortex wake modelling with structural modelling .The results show that this coupling model can predict the flexible wind turbine dynamic characteristics effectively and efficiently .Under the influence of the gravitational force ,the dynamic response of flapwise direction contributes to the dynamic behavior of edgewise direction under the operational condition of steady wind speed .The difference in dynamic response be-tween the flexible and rigid wind turbines manifests when the aerodynamics/structure coupling effect is of signifi-cance in both wind turbine design and performance calculation .

Dynamic electricity pricing for electric vehicles using stochastic programming

International Nuclear Information System (INIS)

Soares, João; Ghazvini, Mohammad Ali Fotouhi; Borges, Nuno; Vale, Zita

2017-01-01

Electric Vehicles (EVs) are an important source of uncertainty, due to their variable demand, departure time and location. In smart grids, the electricity demand can be controlled via Demand Response (DR) programs. Smart charging and vehicle-to-grid seem highly promising methods for EVs control. However, high capital costs remain a barrier to implementation. Meanwhile, incentive and price-based schemes that do not require high level of control can be implemented to influence the EVs' demand. Having effective tools to deal with the increasing level of uncertainty is increasingly important for players, such as energy aggregators. This paper formulates a stochastic model for day-ahead energy resource scheduling, integrated with the dynamic electricity pricing for EVs, to address the challenges brought by the demand and renewable sources uncertainty. The two-stage stochastic programming approach is used to obtain the optimal electricity pricing for EVs. A realistic case study projected for 2030 is presented based on Zaragoza network. The results demonstrate that it is more effective than the deterministic model and that the optimal pricing is preferable. This study indicates that adequate DR schemes like the proposed one are promising to increase the customers' satisfaction in addition to improve the profitability of the energy aggregation business. - Highlights: • A stochastic model for energy scheduling tackling several uncertainty sources. • A two-stage stochastic programming is used to tackle the developed model. • Optimal EV electricity pricing seems to improve the profits. • The propose results suggest to increase the customers' satisfaction.

Dynamic analysis of the pump system based on MOC–CFD coupled method

International Nuclear Information System (INIS)

Yang, Shuai; Chen, Xin; Wu, Dazhuan; Yan, Peng

2015-01-01

Highlights: • MOC–CFD coupled method was proposed to get the pump internal and external characteristics. • The coupled strategy and procedure were explained. • Some typical simulation cases were made for different factors. • The pump head deviation grows with the severity of the transient. • Valve closure law in linear and longer pipeline will cause higher pump head deviation. - Abstract: The dynamic characteristics of pump response to transient events were investigated by combining the Method of Characteristic (MOC) and Computational Fluid Dynamics (CFD) together. In a typical pump–pipeline–valve system, similar to the reactor system, the pump is treated as three-dimensional CFD model using Fluent code, whereas the rest is represented by one-dimensional components using MOC. A description of the coupling theory and procedure ensuring proper communication within the two codes is given. Several transient flow operations have been carried out. In the initial steady-state simulation, the coupled method could accurately find the operating condition of the pump when the valve is fully open. When the valve is closed rapidly, preliminary comparative calculations demonstrate that the coupled method is efficient in simulating the dynamic behavior of the pump and capable of getting detailed fluid field evolutions inside the pump. Deviation between the dynamic pump head and the value given by the steady-state curve at the same instantaneous flow-rate was established, and the cause of the deviation was further explained by the comparison of pump internal and external characteristics. Furthermore, it was found that the deviation grows with the severity of the transient. In addition, the effects of valve closure laws and pipe length on the pump dynamic performances were evaluated. All the results showed that MOC–CFD is an efficient and promising way for simulating the interaction between pump model and piping system

An optimal maintenance policy for machine replacement problem using dynamic programming

Directory of Open Access Journals (Sweden)

Mohsen Sadegh Amalnik

2017-06-01

Full Text Available In this article, we present an acceptance sampling plan for machine replacement problem based on the backward dynamic programming model. Discount dynamic programming is used to solve a two-state machine replacement problem. We plan to design a model for maintenance by consid-ering the quality of the item produced. The purpose of the proposed model is to determine the optimal threshold policy for maintenance in a finite time horizon. We create a decision tree based on a sequential sampling including renew, repair and do nothing and wish to achieve an optimal threshold for making decisions including renew, repair and continue the production in order to minimize the expected cost. Results show that the optimal policy is sensitive to the data, for the probability of defective machines and parameters defined in the model. This can be clearly demonstrated by a sensitivity analysis technique.

A Stereo Dual-Channel Dynamic Programming Algorithm for UAV Image Stitching.

Science.gov (United States)

Li, Ming; Chen, Ruizhi; Zhang, Weilong; Li, Deren; Liao, Xuan; Wang, Lei; Pan, Yuanjin; Zhang, Peng

2017-09-08

Dislocation is one of the major challenges in unmanned aerial vehicle (UAV) image stitching. In this paper, we propose a new algorithm for seamlessly stitching UAV images based on a dynamic programming approach. Our solution consists of two steps: Firstly, an image matching algorithm is used to correct the images so that they are in the same coordinate system. Secondly, a new dynamic programming algorithm is developed based on the concept of a stereo dual-channel energy accumulation. A new energy aggregation and traversal strategy is adopted in our solution, which can find a more optimal seam line for image stitching. Our algorithm overcomes the theoretical limitation of the classical Duplaquet algorithm. Experiments show that the algorithm can effectively solve the dislocation problem in UAV image stitching, especially for the cases in dense urban areas. Our solution is also direction-independent, which has better adaptability and robustness for stitching images.

Dynamic compensation of the Silver self-powered neutron detector in the ramp program at the OSIRIS reactor

International Nuclear Information System (INIS)

Moulin, D.J.

1994-01-01

The Silver self-powered neutron detector (SPND) is a common detector used in the ramp program at the OSIRIS reactor. The Silver SPND signal is a reference during steady states, but its response is too slow for monitoring transient tests. In order to compensate for the inherent time delay a mathematical processing method of the Silver SPND signal was developed. Based on a convolution-type resolution of the kinetics equations, a dynamic compensation algorithm can be used for transient conditions as well as steady state conditions. A computer program reconstructs, in real-time, the dynamic neutron flux sensed by the Silver detector from the current measured between the emitter and the collector of the SPND. Although this method decreases slightly the signal-to-noise ratio, it maintains the SPND's characteristics and reduces the response time from about 10 minutes to less than 4 seconds for a step change in flux. This provides for prompt and accurate measurement of fuel rod power during ramp experiments in the OSIRIS reactor. This development makes the Silver SPND very suitable for many on-line monitoring applications

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...

Accurate Detection of Dysmorphic Nuclei Using Dynamic Programming and Supervised Classification.

Science.gov (United States)

Verschuuren, Marlies; De Vylder, Jonas; Catrysse, Hannes; Robijns, Joke; Philips, Wilfried; De Vos, Winnok H

2017-01-01

A vast array of pathologies is typified by the presence of nuclei with an abnormal morphology. Dysmorphic nuclear phenotypes feature dramatic size changes or foldings, but also entail much subtler deviations such as nuclear protrusions called blebs. Due to their unpredictable size, shape and intensity, dysmorphic nuclei are often not accurately detected in standard image analysis routines. To enable accurate detection of dysmorphic nuclei in confocal and widefield fluorescence microscopy images, we have developed an automated segmentation algorithm, called Blebbed Nuclei Detector (BleND), which relies on two-pass thresholding for initial nuclear contour detection, and an optimal path finding algorithm, based on dynamic programming, for refining these contours. Using a robust error metric, we show that our method matches manual segmentation in terms of precision and outperforms state-of-the-art nuclear segmentation methods. Its high performance allowed for building and integrating a robust classifier that recognizes dysmorphic nuclei with an accuracy above 95%. The combined segmentation-classification routine is bound to facilitate nucleus-based diagnostics and enable real-time recognition of dysmorphic nuclei in intelligent microscopy workflows.

Accurate Detection of Dysmorphic Nuclei Using Dynamic Programming and Supervised Classification.

Directory of Open Access Journals (Sweden)

Marlies Verschuuren

Full Text Available A vast array of pathologies is typified by the presence of nuclei with an abnormal morphology. Dysmorphic nuclear phenotypes feature dramatic size changes or foldings, but also entail much subtler deviations such as nuclear protrusions called blebs. Due to their unpredictable size, shape and intensity, dysmorphic nuclei are often not accurately detected in standard image analysis routines. To enable accurate detection of dysmorphic nuclei in confocal and widefield fluorescence microscopy images, we have developed an automated segmentation algorithm, called Blebbed Nuclei Detector (BleND, which relies on two-pass thresholding for initial nuclear contour detection, and an optimal path finding algorithm, based on dynamic programming, for refining these contours. Using a robust error metric, we show that our method matches manual segmentation in terms of precision and outperforms state-of-the-art nuclear segmentation methods. Its high performance allowed for building and integrating a robust classifier that recognizes dysmorphic nuclei with an accuracy above 95%. The combined segmentation-classification routine is bound to facilitate nucleus-based diagnostics and enable real-time recognition of dysmorphic nuclei in intelligent microscopy workflows.

Dynamic baseline detection method for power data network service

Science.gov (United States)

Chen, Wei

2017-08-01

This paper proposes a dynamic baseline Traffic detection Method which is based on the historical traffic data for the Power data network. The method uses Cisco's NetFlow acquisition tool to collect the original historical traffic data from network element at fixed intervals. This method uses three dimensions information including the communication port, time, traffic (number of bytes or number of packets) t. By filtering, removing the deviation value, calculating the dynamic baseline value, comparing the actual value with the baseline value, the method can detect whether the current network traffic is abnormal.

Study on Triopoly Dynamic Game Model Based on Different Demand Forecast Methods in the Market

Directory of Open Access Journals (Sweden)

Junhai Ma

2017-01-01

Full Text Available The impact of inaccurate demand beliefs on dynamics of a Triopoly game is studied. We suppose that all the players make their own estimations on possible demand with errors. A dynamic Triopoly game with such demand belief is set up. Based on this model, existence and local stable region of the equilibriums are investigated by 3D stable regions of Nash equilibrium point. The complex dynamics, such as bifurcation scenarios and route to chaos, are displayed in 2D bifurcation diagrams, in which e1 and α are negatively related to each other. Basins of attraction are investigated and we found that the attraction domain becomes smaller with the increase in price modification speed, which indicates that all the players’ output must be kept within a certain range so as to keep the system stable. Feedback control method is used to keep the system at an equilibrium state.

A Dynamic Fuzzy Approach Based on the EDAS Method for Multi-Criteria Subcontractor Evaluation

Directory of Open Access Journals (Sweden)

Mehdi Keshavarz-Ghorabaee

2018-03-01

Full Text Available Selection of appropriate subcontractors for outsourcing is very important for the success of construction projects. This can improve the overall quality of projects and promote the qualification and reputation of the main contractors. The evaluation of subcontractors can be made by some experts or decision-makers with respect to some criteria. If this process is done in different time periods, it can be defined as a dynamic multi-criteria group decision-making (MCGDM problem. In this study, we propose a new fuzzy dynamic MCGDM approach based on the EDAS (Evaluation based on Distance from Average Solution method for subcontractor evaluation. In the procedure of the proposed approach, the sets of alternatives, criteria and decision-makers can be changed at different time periods. Also, the proposed approach gives more weight to newer decision information for aggregating the overall performance of alternatives. A numerical example is used to illustrate the proposed approach and show the application of it in subcontractor evaluation. The results demonstrate that the proposed approach is efficient and useful in real-world decision-making problems.

Continuation Methods and Non-Linear/Non-Gaussian Estimation for Flight Dynamics, Phase II

Data.gov (United States)

National Aeronautics and Space Administration — We propose herein to augment current NASA spaceflight dynamics programs with algorithms and software from three domains. First, we use parameter continuation methods...

Research on a Hierarchical Dynamic Automatic Voltage Control System Based on the Discrete Event-Driven Method

Directory of Open Access Journals (Sweden)

Yong Min

2013-06-01

Full Text Available In this paper, concepts and methods of hybrid control systems are adopted to establish a hierarchical dynamic automatic voltage control (HD-AVC system, realizing the dynamic voltage stability of power grids. An HD-AVC system model consisting of three layers is built based on the hybrid control method and discrete event-driven mechanism. In the Top Layer, discrete events are designed to drive the corresponding control block so as to avoid solving complex multiple objective functions, the power system’s characteristic matrix is formed and the minimum amplitude eigenvalue (MAE is calculated through linearized differential-algebraic equations. MAE is applied to judge the system’s voltage stability and security and construct discrete events. The Middle Layer is responsible for management and operation, which is also driven by discrete events. Control values of the control buses are calculated based on the characteristics of power systems and the sensitivity method. Then control values generate control strategies through the interface block. In the Bottom Layer, various control devices receive and implement the control commands from the Middle Layer. In this way, a closed-loop power system voltage control is achieved. Computer simulations verify the validity and accuracy of the HD-AVC system, and verify that the proposed HD-AVC system is more effective than normal voltage control methods.

Construction of dynamic model of CANDU-SCWR using moving boundary method

International Nuclear Information System (INIS)

Sun Peiwei; Jiang Jin; Shan Jianqiang

2011-01-01

Highlights: → A dynamic model of a CANDU-SCWR is developed. → The advantages of the moving boundary method are demonstrated. → The dynamic behaviours of the CANDU-SCWR are obtained by simulation. → The model can predict the dynamic behaviours of the CANDU-SCWR. → Linear dynamic models for CANDU-SCWR are derived by system identification techniques. - Abstract: CANDU-SCWR (Supercritical Water-Cooled Reactor) is one type of Generation IV reactors being developed in Canada. Its dynamic characteristics are different from existing CANDU reactors due to the supercritical conditions of the coolant. To study the behaviours of such reactors under disturbances and to design adequate control systems, it is essential to have an accurate dynamic model to describe such a reactor. One dynamic model is developed for CANDU-SCWR in this paper. In the model construction process, three regions have been considered: Liquid Region I, Liquid Region II and Vapour Region, depending on bulk and wall temperatures being higher or lower the pseudo-critical temperature. A moving boundary method is used to describe the movement of boundaries across these regions. Some benefits of adopting moving boundary method are illustrated by comparing with the fixed boundary method. The results of the steady-state simulation based on the developed model agree well with the design parameters. The transient simulations demonstrate that the model can predict the dynamic behaviours of CANDU-SCWR. Furthermore, to investigate the responses of the reactor to small amplitude perturbations and to facilitate control system designs, a least-square based system identification technique is used to obtain a set of linear dynamic models around the design point. The responses based on the linear dynamic models are validated with simulation results from nonlinear CANDU-SCWR dynamic model.

Computational Fluid Dynamics Analysis Method Developed for Rocket-Based Combined Cycle Engine Inlet

Science.gov (United States)

1997-01-01

Renewed interest in hypersonic propulsion systems has led to research programs investigating combined cycle engines that are designed to operate efficiently across the flight regime. The Rocket-Based Combined Cycle Engine is a propulsion system under development at the NASA Lewis Research Center. This engine integrates a high specific impulse, low thrust-to-weight, airbreathing engine with a low-impulse, high thrust-to-weight rocket. From takeoff to Mach 2.5, the engine operates as an air-augmented rocket. At Mach 2.5, the engine becomes a dual-mode ramjet; and beyond Mach 8, the rocket is turned back on. One Rocket-Based Combined Cycle Engine variation known as the "Strut-Jet" concept is being investigated jointly by NASA Lewis, the U.S. Air Force, Gencorp Aerojet, General Applied Science Labs (GASL), and Lockheed Martin Corporation. Work thus far has included wind tunnel experiments and computational fluid dynamics (CFD) investigations with the NPARC code. The CFD method was initiated by modeling the geometry of the Strut-Jet with the GRIDGEN structured grid generator. Grids representing a subscale inlet model and the full-scale demonstrator geometry were constructed. These grids modeled one-half of the symmetric inlet flow path, including the precompression plate, diverter, center duct, side duct, and combustor. After the grid generation, full Navier-Stokes flow simulations were conducted with the NPARC Navier-Stokes code. The Chien low-Reynolds-number k-e turbulence model was employed to simulate the high-speed turbulent flow. Finally, the CFD solutions were postprocessed with a Fortran code. This code provided wall static pressure distributions, pitot pressure distributions, mass flow rates, and internal drag. These results were compared with experimental data from a subscale inlet test for code validation; then they were used to help evaluate the demonstrator engine net thrust.

Parameterizing Coefficients of a POD-Based Dynamical System

Science.gov (United States)

Kalb, Virginia L.

2010-01-01

A method of parameterizing the coefficients of a dynamical system based of a proper orthogonal decomposition (POD) representing the flow dynamics of a viscous fluid has been introduced. (A brief description of POD is presented in the immediately preceding article.) The present parameterization method is intended to enable construction of the dynamical system to accurately represent the temporal evolution of the flow dynamics over a range of Reynolds numbers. The need for this or a similar method arises as follows: A procedure that includes direct numerical simulation followed by POD, followed by Galerkin projection to a dynamical system has been proven to enable representation of flow dynamics by a low-dimensional model at the Reynolds number of the simulation. However, a more difficult task is to obtain models that are valid over a range of Reynolds numbers. Extrapolation of low-dimensional models by use of straightforward Reynolds-number-based parameter continuation has proven to be inadequate for successful prediction of flows. A key part of the problem of constructing a dynamical system to accurately represent the temporal evolution of the flow dynamics over a range of Reynolds numbers is the problem of understanding and providing for the variation of the coefficients of the dynamical system with the Reynolds number. Prior methods do not enable capture of temporal dynamics over ranges of Reynolds numbers in low-dimensional models, and are not even satisfactory when large numbers of modes are used. The basic idea of the present method is to solve the problem through a suitable parameterization of the coefficients of the dynamical system. The parameterization computations involve utilization of the transfer of kinetic energy between modes as a function of Reynolds number. The thus-parameterized dynamical system accurately predicts the flow dynamics and is applicable to a range of flow problems in the dynamical regime around the Hopf bifurcation. Parameter

Dynamic functional connectivity using state-based dynamic community structure: method and application to opioid analgesia.

Science.gov (United States)

Robinson, Lucy F; Atlas, Lauren Y; Wager, Tor D

2015-03-01

We present a new method, State-based Dynamic Community Structure, that detects time-dependent community structure in networks of brain regions. Most analyses of functional connectivity assume that network behavior is static in time, or differs between task conditions with known timing. Our goal is to determine whether brain network topology remains stationary over time, or if changes in network organization occur at unknown time points. Changes in network organization may be related to shifts in neurological state, such as those associated with learning, drug uptake or experimental conditions. Using a hidden Markov stochastic blockmodel, we define a time-dependent community structure. We apply this approach to data from a functional magnetic resonance imaging experiment examining how contextual factors influence drug-induced analgesia. Results reveal that networks involved in pain, working memory, and emotion show distinct profiles of time-varying connectivity. Copyright © 2014 Elsevier Inc. All rights reserved.

A multithreaded parallel implementation of a dynamic programming algorithm for sequence comparison.

Science.gov (United States)

Martins, W S; Del Cuvillo, J B; Useche, F J; Theobald, K B; Gao, G R

2001-01-01

This paper discusses the issues involved in implementing a dynamic programming algorithm for biological sequence comparison on a general-purpose parallel computing platform based on a fine-grain event-driven multithreaded program execution model. Fine-grain multithreading permits efficient parallelism exploitation in this application both by taking advantage of asynchronous point-to-point synchronizations and communication with low overheads and by effectively tolerating latency through the overlapping of computation and communication. We have implemented our scheme on EARTH, a fine-grain event-driven multithreaded execution and architecture model which has been ported to a number of parallel machines with off-the-shelf processors. Our experimental results show that the dynamic programming algorithm can be efficiently implemented on EARTH systems with high performance (e.g., speedup of 90 on 120 nodes), good programmability and reasonable cost.

Dynamic analysis of large structures with uncertain parameters based on coupling component mode synthesis and perturbation method

Directory of Open Access Journals (Sweden)

D. Sarsri

2016-03-01

Full Text Available This paper presents a methodological approach to compute the stochastic eigenmodes of large FE models with parameter uncertainties based on coupling of second order perturbation method and component mode synthesis methods. Various component mode synthesis methods are used to optimally reduce the size of the model. The statistical first two moments of dynamic response of the reduced system are obtained by the second order perturbation method. Numerical results illustrating the accuracy and efficiency of the proposed coupled methodological procedures for large FE models with uncertain parameters are presented.

Detailed analysis of latencies in image-based dynamic MLC tracking

International Nuclear Information System (INIS)

Poulsen, Per Rugaard; Cho, Byungchul; Sawant, Amit; Ruan, Dan; Keall, Paul J.

2010-01-01

Purpose: Previous measurements of the accuracy of image-based real-time dynamic multileaf collimator (DMLC) tracking show that the major contributor to errors is latency, i.e., the delay between target motion and MLC response. Therefore the purpose of this work was to develop a method for detailed analysis of latency contributions during image-based DMLC tracking. Methods: A prototype DMLC tracking system integrated with a linear accelerator was used for tracking a phantom with an embedded fiducial marker during treatment delivery. The phantom performed a sinusoidal motion. Real-time target localization was based on x-ray images acquired either with a portal imager or a kV imager mounted orthogonal to the treatment beam. Each image was stored in a file on the imaging workstation. A marker segmentation program opened the image file, determined the marker position in the image, and transferred it to the DMLC tracking program. This program estimated the three-dimensional target position by a single-imager method and adjusted the MLC aperture to the target position. Imaging intervals ΔT image from 150 to 1000 ms were investigated for both kV and MV imaging. After the experiments, the recorded images were synchronized with MLC log files generated by the MLC controller and tracking log files generated by the tracking program. This synchronization allowed temporal analysis of the information flow for each individual image from acquisition to completed MLC adjustment. The synchronization also allowed investigation of the MLC adjustment dynamics on a considerably finer time scale than the 50 ms time resolution of the MLC log files. Results: For ΔT image =150 ms, the total time from image acquisition to completed MLC adjustment was 380±9 ms for MV and 420±12 ms for kV images. The main part of this time was from image acquisition to completed image file writing (272 ms for MV and 309 ms for kV). Image file opening (38 ms), marker segmentation (4 ms), MLC position

Detailed analysis of latencies in image-based dynamic MLC tracking

Energy Technology Data Exchange (ETDEWEB)

Poulsen, Per Rugaard; Cho, Byungchul; Sawant, Amit; Ruan, Dan; Keall, Paul J. [Department of Radiation Oncology, Stanford University, Stanford, California 94305 and Department of Oncology and Department of Medical Physics, Aarhus University Hospital, 8000 Aarhus (Denmark); Department of Radiation Oncology, Stanford University, Stanford, California 94305 and Department of Radiation Oncology, Asan Medical Center, Seoul 138-736 (Korea, Republic of); Department of Radiation Oncology, Stanford University, Stanford, California 94305 (United States)

2010-09-15

Purpose: Previous measurements of the accuracy of image-based real-time dynamic multileaf collimator (DMLC) tracking show that the major contributor to errors is latency, i.e., the delay between target motion and MLC response. Therefore the purpose of this work was to develop a method for detailed analysis of latency contributions during image-based DMLC tracking. Methods: A prototype DMLC tracking system integrated with a linear accelerator was used for tracking a phantom with an embedded fiducial marker during treatment delivery. The phantom performed a sinusoidal motion. Real-time target localization was based on x-ray images acquired either with a portal imager or a kV imager mounted orthogonal to the treatment beam. Each image was stored in a file on the imaging workstation. A marker segmentation program opened the image file, determined the marker position in the image, and transferred it to the DMLC tracking program. This program estimated the three-dimensional target position by a single-imager method and adjusted the MLC aperture to the target position. Imaging intervals {Delta}T{sub image} from 150 to 1000 ms were investigated for both kV and MV imaging. After the experiments, the recorded images were synchronized with MLC log files generated by the MLC controller and tracking log files generated by the tracking program. This synchronization allowed temporal analysis of the information flow for each individual image from acquisition to completed MLC adjustment. The synchronization also allowed investigation of the MLC adjustment dynamics on a considerably finer time scale than the 50 ms time resolution of the MLC log files. Results: For {Delta}T{sub image}=150 ms, the total time from image acquisition to completed MLC adjustment was 380{+-}9 ms for MV and 420{+-}12 ms for kV images. The main part of this time was from image acquisition to completed image file writing (272 ms for MV and 309 ms for kV). Image file opening (38 ms), marker segmentation (4 ms

Measurement correction method for force sensor used in dynamic pressure calibration based on artificial neural network optimized by genetic algorithm

Science.gov (United States)

Gu, Tingwei; Kong, Deren; Shang, Fei; Chen, Jing

2017-12-01

We present an optimization algorithm to obtain low-uncertainty dynamic pressure measurements from a force-transducer-based device. In this paper, the advantages and disadvantages of the methods that are commonly used to measure the propellant powder gas pressure, the applicable scope of dynamic pressure calibration devices, and the shortcomings of the traditional comparison calibration method based on the drop-weight device are firstly analysed in detail. Then, a dynamic calibration method for measuring pressure using a force sensor based on a drop-weight device is introduced. This method can effectively save time when many pressure sensors are calibrated simultaneously and extend the life of expensive reference sensors. However, the force sensor is installed between the drop-weight and the hammerhead by transition pieces through the connection mode of bolt fastening, which causes adverse effects such as additional pretightening and inertia forces. To solve these effects, the influence mechanisms of the pretightening force, the inertia force and other influence factors on the force measurement are theoretically analysed. Then a measurement correction method for the force measurement is proposed based on an artificial neural network optimized by a genetic algorithm. The training and testing data sets are obtained from calibration tests, and the selection criteria for the key parameters of the correction model is discussed. The evaluation results for the test data show that the correction model can effectively improve the force measurement accuracy of the force sensor. Compared with the traditional high-accuracy comparison calibration method, the percentage difference of the impact-force-based measurement is less than 0.6% and the relative uncertainty of the corrected force value is 1.95%, which can meet the requirements of engineering applications.

Improved decomposition–coordination and discrete differential dynamic programming for optimization of large-scale hydropower system

International Nuclear Information System (INIS)

Li, Chunlong; Zhou, Jianzhong; Ouyang, Shuo; Ding, Xiaoling; Chen, Lu

2014-01-01

Highlights: • Optimization of large-scale hydropower system in the Yangtze River basin. • Improved decomposition–coordination and discrete differential dynamic programming. • Generating initial solution randomly to reduce generation time. • Proposing relative coefficient for more power generation. • Proposing adaptive bias corridor technology to enhance convergence speed. - Abstract: With the construction of major hydro plants, more and more large-scale hydropower systems are taking shape gradually, which brings up a challenge to optimize these systems. Optimization of large-scale hydropower system (OLHS), which is to determine water discharges or water levels of overall hydro plants for maximizing total power generation when subjecting to lots of constrains, is a high dimensional, nonlinear and coupling complex problem. In order to solve the OLHS problem effectively, an improved decomposition–coordination and discrete differential dynamic programming (IDC–DDDP) method is proposed in this paper. A strategy that initial solution is generated randomly is adopted to reduce generation time. Meanwhile, a relative coefficient based on maximum output capacity is proposed for more power generation. Moreover, an adaptive bias corridor technology is proposed to enhance convergence speed. The proposed method is applied to long-term optimal dispatches of large-scale hydropower system (LHS) in the Yangtze River basin. Compared to other methods, IDC–DDDP has competitive performances in not only total power generation but also convergence speed, which provides a new method to solve the OLHS problem

Optimization of decision rules based on dynamic programming approach

KAUST Repository

Zielosko, Beata

2014-01-14

This chapter is devoted to the study of an extension of dynamic programming approach which allows optimization of approximate decision rules relative to the length and coverage. We introduce an uncertainty measure that is the difference between number of rows in a given decision table and the number of rows labeled with the most common decision for this table divided by the number of rows in the decision table. We fix a threshold γ, such that 0 ≤ γ < 1, and study so-called γ-decision rules (approximate decision rules) that localize rows in subtables which uncertainty is at most γ. Presented algorithm constructs a directed acyclic graph Δ γ T which nodes are subtables of the decision table T given by pairs "attribute = value". The algorithm finishes the partitioning of a subtable when its uncertainty is at most γ. The chapter contains also results of experiments with decision tables from UCI Machine Learning Repository. © 2014 Springer International Publishing Switzerland.

An Analysis of Dynamic Instability on TC-Like Vortex Using the Regularization-Based Eigenmode Linear Superposition Method

Directory of Open Access Journals (Sweden)

Shuang Liu

2018-01-01

Full Text Available In this paper, the eigenmode linear superposition (ELS method based on the regularization is used to discuss the distributions of all eigenmodes and the role of their instability to the intensity and structure change in TC-like vortex. Results show that the regularization approach can overcome the ill-posed problem occurring in solving mode weight coefficients as the ELS method are applied to analyze the impacts of dynamic instability on the intensity and structure change of TC-like vortex. The Generalized Cross-validation (GCV method and the L curve method are used to determine the regularization parameters, and the results of the two approaches are compared. It is found that the results based on the GCV method are closer to the given initial condition in the solution of the inverse problem of the vortex system. Then, the instability characteristic of the hollow vortex as the basic state are examined based on the linear barotropic shallow water equations. It is shown that the wavenumber distribution of system instability obtained from the ELS method is well consistent with that of the numerical analysis based on the norm mode. On the other hand, the evolution of the hollow vortex are discussed using the product of each eigenmode and its corresponding weight coefficient. Results show that the intensity and structure change of the system are mainly affected by the dynamic instability in the early stage of disturbance development, and the most unstable mode has a dominant role in the growth rate and the horizontal distribution of intense disturbance in the near-core region. Moreover, the wave structure of the most unstable mode possesses typical characteristics of mixed vortex Rossby-inertio-gravity waves (VRIGWs.

Stochastic control theory dynamic programming principle

CERN Document Server

Nisio, Makiko

2015-01-01

This book offers a systematic introduction to the optimal stochastic control theory via the dynamic programming principle, which is a powerful tool to analyze control problems. First we consider completely observable control problems with finite horizons. Using a time discretization we construct a nonlinear semigroup related to the dynamic programming principle (DPP), whose generator provides the Hamilton–Jacobi–Bellman (HJB) equation, and we characterize the value function via the nonlinear semigroup, besides the viscosity solution theory. When we control not only the dynamics of a system but also the terminal time of its evolution, control-stopping problems arise. This problem is treated in the same frameworks, via the nonlinear semigroup. Its results are applicable to the American option price problem. Zero-sum two-player time-homogeneous stochastic differential games and viscosity solutions of the Isaacs equations arising from such games are studied via a nonlinear semigroup related to DPP (the min-ma...

Optimal Input Design for Aircraft Parameter Estimation using Dynamic Programming Principles

Science.gov (United States)

Morelli, Eugene A.; Klein, Vladislav

1990-01-01

A new technique was developed for designing optimal flight test inputs for aircraft parameter estimation experiments. The principles of dynamic programming were used for the design in the time domain. This approach made it possible to include realistic practical constraints on the input and output variables. A description of the new approach is presented, followed by an example for a multiple input linear model describing the lateral dynamics of a fighter aircraft. The optimal input designs produced by the new technique demonstrated improved quality and expanded capability relative to the conventional multiple input design method.

First-Principles Lattice Dynamics Method for Strongly Anharmonic Crystals

Science.gov (United States)

Tadano, Terumasa; Tsuneyuki, Shinji

2018-04-01

We review our recent development of a first-principles lattice dynamics method that can treat anharmonic effects nonperturbatively. The method is based on the self-consistent phonon theory, and temperature-dependent phonon frequencies can be calculated efficiently by incorporating recent numerical techniques to estimate anharmonic force constants. The validity of our approach is demonstrated through applications to cubic strontium titanate, where overall good agreement with experimental data is obtained for phonon frequencies and lattice thermal conductivity. We also show the feasibility of highly accurate calculations based on a hybrid exchange-correlation functional within the present framework. Our method provides a new way of studying lattice dynamics in severely anharmonic materials where the standard harmonic approximation and the perturbative approach break down.

A Skeleton Based Programming Paradigm for Mobile Multi-Agents on Distributed Systems and Its Realization within the MAGDA Mobile Agents Platform

Directory of Open Access Journals (Sweden)

R. Aversa

2008-01-01

Full Text Available Parallel programming effort can be reduced by using high level constructs such as algorithmic skeletons. Within the MAGDA toolset, supporting programming and execution of mobile agent based distributed applications, we provide a skeleton-based parallel programming environment, based on specialization of Algorithmic Skeleton Java interfaces and classes. Their implementation include mobile agent features for execution on heterogeneous systems, such as clusters of WSs and PCs, and support reliability and dynamic workload balancing. The user can thus develop a parallel, mobile agent based application by simply specialising a given set of classes and methods and using a set of added functionalities.

A Dynamic Programming Solution for Energy-Optimal Video Playback on Mobile Devices

Directory of Open Access Journals (Sweden)

Minseok Song

2016-01-01

Full Text Available Due to the development of mobile technology and wide availability of smartphones, the Internet of Things (IoT starts to handle high volumes of video data to facilitate multimedia-based services, which requires energy-efficient video playback. In video playback, frames have to be decoded and rendered at high playback rate, increasing the computation cost on the CPU. To save the CPU power, dynamic voltage and frequency scaling (DVFS dynamically adjusts the operating voltage of the processor along with frequency, in which appropriate selection of frequency on power could achieve a balance between performance and power. We present a decoding model that allows buffering frames to let the CPU run at low frequency and then propose an algorithm that determines the CPU frequency needed to decode each frame in a video, with the aim of minimizing power consumption while meeting buffer size and deadline constraints, using a dynamic programming technique. We finally extend this algorithm to optimize CPU frequencies over a short sequence of frames, producing a practical method of reducing the energy required for video decoding. Experimental results show a system-wide reduction in energy of 27%, compared with a processor running at full speed.

Optimization of environmental management strategies through a dynamic stochastic possibilistic multiobjective program

Energy Technology Data Exchange (ETDEWEB)

Zhang, Xiaodong, E-mail: xiaodong.zhang@beg.utexas.edu [Bureau of Economic Geology, Jackson School of Geosciences, The University of Texas at Austin, Austin, TX 78713 (United States); Huang, Gordon [Institute of Energy, Environment and Sustainable Communities, University of Regina, Regina, Saskatchewan S4S 0A2 (Canada)

2013-02-15

Highlights: ► A dynamic stochastic possibilistic multiobjective programming model is developed. ► Greenhouse gas emission control is considered. ► Three planning scenarios are analyzed and compared. ► Optimal decision schemes under three scenarios and different p{sub i} levels are obtained. ► Tradeoffs between economics and environment are reflected. -- Abstract: Greenhouse gas (GHG) emissions from municipal solid waste (MSW) management facilities have become a serious environmental issue. In MSW management, not only economic objectives but also environmental objectives should be considered simultaneously. In this study, a dynamic stochastic possibilistic multiobjective programming (DSPMP) model is developed for supporting MSW management and associated GHG emission control. The DSPMP model improves upon the existing waste management optimization methods through incorporation of fuzzy possibilistic programming and chance-constrained programming into a general mixed-integer multiobjective linear programming (MOP) framework where various uncertainties expressed as fuzzy possibility distributions and probability distributions can be effectively reflected. Two conflicting objectives are integrally considered, including minimization of total system cost and minimization of total GHG emissions from waste management facilities. Three planning scenarios are analyzed and compared, representing different preferences of the decision makers for economic development and environmental-impact (i.e. GHG-emission) issues in integrated MSW management. Optimal decision schemes under three scenarios and different p{sub i} levels (representing the probability that the constraints would be violated) are generated for planning waste flow allocation and facility capacity expansions as well as GHG emission control. The results indicate that economic and environmental tradeoffs can be effectively reflected through the proposed DSPMP model. The generated decision variables can help

The dynamic relaxation method in the structural analysis of concrete pressure vessels

International Nuclear Information System (INIS)

Davidson, I.; Assis Bastos, M.R. de; Camargo, P.B. de.

1977-01-01

The dynamic relaxation method, applied to 3 dimensional concrete structures, especially pressure vessels, is demonstrated. It utilizes the finite difference method and allows the growth of cracks to be followed up to the point of vessel rupture. A FORTRAN IV program is developed, which can also be utilized, with the necessary modifications, for other structure calculations [pt

Dynamic PET Image reconstruction for parametric imaging using the HYPR kernel method

Science.gov (United States)

Spencer, Benjamin; Qi, Jinyi; Badawi, Ramsey D.; Wang, Guobao

2017-03-01

Dynamic PET image reconstruction is a challenging problem because of the ill-conditioned nature of PET and the lowcounting statistics resulted from short time-frames in dynamic imaging. The kernel method for image reconstruction has been developed to improve image reconstruction of low-count PET data by incorporating prior information derived from high-count composite data. In contrast to most of the existing regularization-based methods, the kernel method embeds image prior information in the forward projection model and does not require an explicit regularization term in the reconstruction formula. Inspired by the existing highly constrained back-projection (HYPR) algorithm for dynamic PET image denoising, we propose in this work a new type of kernel that is simpler to implement and further improves the kernel-based dynamic PET image reconstruction. Our evaluation study using a physical phantom scan with synthetic FDG tracer kinetics has demonstrated that the new HYPR kernel-based reconstruction can achieve a better region-of-interest (ROI) bias versus standard deviation trade-off for dynamic PET parametric imaging than the post-reconstruction HYPR denoising method and the previously used nonlocal-means kernel.

Method to render second order beam optics programs symplectic

International Nuclear Information System (INIS)

Douglas, D.; Servranckx, R.V.

1984-10-01

We present evidence that second order matrix-based beam optics programs violate the symplectic condition. A simple method to avoid this difficulty, based on a generating function approach to evaluating transfer maps, is described. A simple example illustrating the non-symplectricity of second order matrix methods, and the effectiveness of our solution to the problem, is provided. We conclude that it is in fact possible to bring second order matrix optics methods to a canonical form. The procedure for doing so has been implemented in the program DIMAT, and could be implemented in programs such as TRANSPORT and TURTLE, making them useful in multiturn applications. 15 refs

A program for dynamic noise investigations of reactor systems

International Nuclear Information System (INIS)

Antonov, N.A.; Yaneva, N.B.

1980-01-01

A stochastic process analysis in nuclear reactors is used for the state diagnosis and dynamic characteristic investigation of the reactor system. A program DENSITY adapted and tested on an IBM 360 ES type computer is developed. The program is adjusted for fast processing of long series exploiting a relatively small memory. The testing procedure is discussed and the method of the periodic sequences corresponding to characteristic reactivity perturbations of the reactor systems is considered. The program is written for calculating the auto-power spectral density and the cross-power spectral density, as well as the coherence function of stationary statistical time series using the advantages of the fast Fourier transformation. In particular, it is shown that the multi-frequency binary sequences are very useful with respect to the signal-to-noise ratio and the frequency distribution in view of the frequency reactor test

Skin tumor area extraction using an improved dynamic programming approach.

Science.gov (United States)

Abbas, Qaisar; Celebi, M E; Fondón García, Irene

2012-05-01

Border (B) description of melanoma and other pigmented skin lesions is one of the most important tasks for the clinical diagnosis of dermoscopy images using the ABCD rule. For an accurate description of the border, there must be an effective skin tumor area extraction (STAE) method. However, this task is complicated due to uneven illumination, artifacts present in the lesions and smooth areas or fuzzy borders of the desired regions. In this paper, a novel STAE algorithm based on improved dynamic programming (IDP) is presented. The STAE technique consists of the following four steps: color space transform, pre-processing, rough tumor area detection and refinement of the segmented area. The procedure is performed in the CIE L(*) a(*) b(*) color space, which is approximately uniform and is therefore related to dermatologist's perception. After pre-processing the skin lesions to reduce artifacts, the DP algorithm is improved by introducing a local cost function, which is based on color and texture weights. The STAE method is tested on a total of 100 dermoscopic images. In order to compare the performance of STAE with other state-of-the-art algorithms, various statistical measures based on dermatologist-drawn borders are utilized as a ground truth. The proposed method outperforms the others with a sensitivity of 96.64%, a specificity of 98.14% and an error probability of 5.23%. The results demonstrate that this STAE method by IDP is an effective solution when compared with other state-of-the-art segmentation techniques. The proposed method can accurately extract tumor borders in dermoscopy images. © 2011 John Wiley & Sons A/S.

Modelling of windmill induction generators in dynamic simulation programs

DEFF Research Database (Denmark)

Akhmatov, Vladislav; Knudsen, Hans

1999-01-01

with and without a model of the mechanical shaft. The reason for the discrepancies are explained, and it is shown that the phenomenon is due partly to the presence of DC offset currents in the induction machine stator, and partly to the mechanical shaft system of the wind turbine and the generator rotor......For AC networks with large amounts of induction generators-in case of e.g. windmills-the paper demonstrates a significant discrepancy in the simulated voltage recovery after faults in weak networks, when comparing result obtained with dynamic stability programs and transient programs, respectively....... It is shown that it is possible to include a transient model in dynamic stability programs and thus obtain correct results also in dynamic stability programs. A mechanical model of the shaft system has also been included in the generator model...

Dynamic programming in parallel boundary detection with application to ultrasound intima-media segmentation.

Science.gov (United States)

Zhou, Yuan; Cheng, Xinyao; Xu, Xiangyang; Song, Enmin

2013-12-01

Segmentation of carotid artery intima-media in longitudinal ultrasound images for measuring its thickness to predict cardiovascular diseases can be simplified as detecting two nearly parallel boundaries within a certain distance range, when plaque with irregular shapes is not considered. In this paper, we improve the implementation of two dynamic programming (DP) based approaches to parallel boundary detection, dual dynamic programming (DDP) and piecewise linear dual dynamic programming (PL-DDP). Then, a novel DP based approach, dual line detection (DLD), which translates the original 2-D curve position to a 4-D parameter space representing two line segments in a local image segment, is proposed to solve the problem while maintaining efficiency and rotation invariance. To apply the DLD to ultrasound intima-media segmentation, it is imbedded in a framework that employs an edge map obtained from multiplication of the responses of two edge detectors with different scales and a coupled snake model that simultaneously deforms the two contours for maintaining parallelism. The experimental results on synthetic images and carotid arteries of clinical ultrasound images indicate improved performance of the proposed DLD compared to DDP and PL-DDP, with respect to accuracy and efficiency. Copyright © 2013 Elsevier B.V. All rights reserved.

Evaluating Dynamic Analysis Techniques for Program Comprehension

NARCIS (Netherlands)

Cornelissen, S.G.M.

2009-01-01

Program comprehension is an essential part of software development and software maintenance, as software must be sufficiently understood before it can be properly modified. One of the common approaches in getting to understand a program is the study of its execution, also known as dynamic analysis.

Novel methods for Solving Economic Dispatch of Security-Constrained Unit Commitment Based on Linear Programming

Science.gov (United States)

Guo, Sangang

2017-09-01

There are two stages in solving security-constrained unit commitment problems (SCUC) within Lagrangian framework: one is to obtain feasible units’ states (UC), the other is power economic dispatch (ED) for each unit. The accurate solution of ED is more important for enhancing the efficiency of the solution to SCUC for the fixed feasible units’ statues. Two novel methods named after Convex Combinatorial Coefficient Method and Power Increment Method respectively based on linear programming problem for solving ED are proposed by the piecewise linear approximation to the nonlinear convex fuel cost functions. Numerical testing results show that the methods are effective and efficient.

Model validation of solar PV plant with hybrid data dynamic simulation based on fast-responding generator method

Directory of Open Access Journals (Sweden)

Zhao Dawei

2016-01-01

Full Text Available In recent years, a significant number of large-scale solar photovoltaic (PV plants have been put into operation or been under planning around the world. The model accuracy of solar PV plant is the key factor to investigate the mutual influences between solar PV plants and a power grid. However, this problem has not been well solved, especially in how to apply the real measurements to validate the models of the solar PV plants. Taking fast-responding generator method as an example, this paper presents a model validation methodology for solar PV plant via the hybrid data dynamic simulation. First, the implementation scheme of hybrid data dynamic simulation suitable for DIgSILENT PowerFactory software is proposed, and then an analysis model of solar PV plant integration based on IEEE 9 system is established. At last, model validation of solar PV plant is achieved by employing hybrid data dynamic simulation. The results illustrate the effectiveness of the proposed method in solar PV plant model validation.

The endogenous grid method for discrete-continuous dynamic choice models with (or without) taste shocks

DEFF Research Database (Denmark)

Iskhakov, Fedor; Jørgensen, Thomas H.; Rust, John

2017-01-01

We present a fast and accurate computational method for solving and estimating a class of dynamic programming models with discrete and continuous choice variables. The solution method we develop for structural estimation extends the endogenous grid-point method (EGM) to discrete-continuous (DC) p...

The Functional Programming Language R and the Paradigm of Dynamic Scientific Programming

NARCIS (Netherlands)

Trancón y Widemann, B.; Bolz, C.F.; Grelck, C.; Loidl, H.-W.; Peña, R.

2013-01-01

R is an environment and functional programming language for statistical data analysis and visualization. Largely unknown to the functional programming community, it is popular and influential in many empirical sciences. Due to its integrated combination of dynamic and reflective scripting on one

Methods Research about Accuracy Loss Tracing of Dynamic Measurement System Based on WNN

International Nuclear Information System (INIS)

Lin, S-W; Fei, Y T; Jiang, M L; Tsai, C-Y; Cheng Hsinyu

2006-01-01

The paper presents a method of achieving accuracy loss of the dynamic measurement system according to change of errors on different period of the system. WNN, used to trace the accuracy loss of dynamic measurement system, traces the total precision loss during a certain period to every part of the system, and the accuracy loss of every part can be get, so retaining the accuracy and optimum design of the system is possible. Take tracing the accuracy loss of a simulated system for an example to testify the method

A dynamic programming approach for optimizing train speed profiles with speed restrictions and passage points

DEFF Research Database (Denmark)

Haahr, Jørgen Thorlund; Pisinger, David; Sabbaghian, Mohammad

2017-01-01

This paper considers a novel solution method for generating improved train speed profiles with reduced energy consumption. The solution method makes use of a time-space graph formulation which can be solved through Dynamic Programming. Instead of using uniform discretization of time and space...

Discrete Globalised Dual Heuristic Dynamic Programming in Control of the Two-Wheeled Mobile Robot

Directory of Open Access Journals (Sweden)

Marcin Szuster

2014-01-01

Full Text Available Network-based control systems have been emerging technologies in the control of nonlinear systems over the past few years. This paper focuses on the implementation of the approximate dynamic programming algorithm in the network-based tracking control system of the two-wheeled mobile robot, Pioneer 2-DX. The proposed discrete tracking control system consists of the globalised dual heuristic dynamic programming algorithm, the PD controller, the supervisory term, and an additional control signal. The structure of the supervisory term derives from the stability analysis realised using the Lyapunov stability theorem. The globalised dual heuristic dynamic programming algorithm consists of two structures: the actor and the critic, realised in a form of neural networks. The actor generates the suboptimal control law, while the critic evaluates the realised control strategy by approximation of value function from the Bellman’s equation. The presented discrete tracking control system works online, the neural networks’ weights adaptation process is realised in every iteration step, and the neural networks preliminary learning procedure is not required. The performance of the proposed control system was verified by a series of computer simulations and experiments realised using the wheeled mobile robot Pioneer 2-DX.

Implementing a Dynamic Street-Children's Program: Successes and ...

African Journals Online (AJOL)

dynamic street children's program in Mzuzu Malawi – using a developmental ... dynamics of parentchild, parent-parent and child-parent-environment; life-events; ... of child and adolescent development, and how they can influence the child's ...

A Dynamic Hidden Forwarding Path Planning Method Based on Improved Q-Learning in SDN Environments

Directory of Open Access Journals (Sweden)

Yun Chen

2018-01-01

Full Text Available Currently, many methods are available to improve the target network’s security. The vast majority of them cannot obtain an optimal attack path and interdict it dynamically and conveniently. Almost all defense strategies aim to repair known vulnerabilities or limit services in target network to improve security of network. These methods cannot response to the attacks in real-time because sometimes they need to wait for manufacturers releasing corresponding countermeasures to repair vulnerabilities. In this paper, we propose an improved Q-learning algorithm to plan an optimal attack path directly and automatically. Based on this path, we use software-defined network (SDN to adjust routing paths and create hidden forwarding paths dynamically to filter vicious attack requests. Compared to other machine learning algorithms, Q-learning only needs to input the target state to its agents, which can avoid early complex training process. We improve Q-learning algorithm in two aspects. First, a reward function based on the weights of hosts and attack success rates of vulnerabilities is proposed, which can adapt to different network topologies precisely. Second, we remove the actions and merge them into every state that reduces complexity from O(N3 to O(N2. In experiments, after deploying hidden forwarding paths, the security of target network is boosted significantly without having to repair network vulnerabilities immediately.

Optimal Design of Measurement Programs for the Parameter Identification of Dynamic Systems

DEFF Research Database (Denmark)

Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune

The design of measurement programs devoted to parameter identification of structural dynamic systems is considered. The design problem is formulated as an optimization problem to minimize the total expected cost that is the cost of failure and the cost of the measurement program. All...... the calculations are based on a priori knowledge and engineering judgement. One of the contribution of the approach is that the optimal number of sensors can be estimated. This is shown in a numerical example where the proposed approach is demonstrated. The example is concerned with design of a measurement program...

Optimal Design of Measurement Programs for the Parameter Identification of Dynamic Systems

DEFF Research Database (Denmark)

Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune

The design of a measured program devoted to parameter identification of structural dynamic systems is considered, the design problem is formulated as an optimization problem due to minimize the total expected cost of the measurement program. All the calculations are based on a priori knowledge...... and engineering judgement. One of the contribution of the approach is that the optimal nmber of sensors can be estimated. This is sown in an numerical example where the proposed approach is demonstrated. The example is concerned with design of a measurement program for estimating the modal damping parameters...

Application of iterative method with dynamic weight based on observation equation's constant in NPP's surveying

International Nuclear Information System (INIS)

Chen Benfu; Guo Xianchun; Zou Zili

2009-01-01

It' s useful to identify the data with errors from the large number of observations during the process of adjustment to decrease the influence of the errors and to improve the quality of the final surveying result. Based on practical conditions of the nuclear power plant's plain control network, it has been given on how to simply calculate the threshold value which used to pre-weight each datum before adjustment calculation; it shows some superiorities in efficiency on data snooping and in quality of the final calculation compared with some traditional methods such as robust estimation, which process data with dynamic weight based the observation' s correction after each iteration. (authors)

Dynamic systems models new methods of parameter and state estimation

CERN Document Server

2016-01-01

This monograph is an exposition of a novel method for solving inverse problems, a method of parameter estimation for time series data collected from simulations of real experiments. These time series might be generated by measuring the dynamics of aircraft in flight, by the function of a hidden Markov model used in bioinformatics or speech recognition or when analyzing the dynamics of asset pricing provided by the nonlinear models of financial mathematics. Dynamic Systems Models demonstrates the use of algorithms based on polynomial approximation which have weaker requirements than already-popular iterative methods. Specifically, they do not require a first approximation of a root vector and they allow non-differentiable elements in the vector functions being approximated. The text covers all the points necessary for the understanding and use of polynomial approximation from the mathematical fundamentals, through algorithm development to the application of the method in, for instance, aeroplane flight dynamic...

Efficient dynamic optimization of logic programs

Science.gov (United States)

Laird, Phil

1992-01-01

A summary is given of the dynamic optimization approach to speed up learning for logic programs. The problem is to restructure a recursive program into an equivalent program whose expected performance is optimal for an unknown but fixed population of problem instances. We define the term 'optimal' relative to the source of input instances and sketch an algorithm that can come within a logarithmic factor of optimal with high probability. Finally, we show that finding high-utility unfolding operations (such as EBG) can be reduced to clause reordering.

Sensitivity analysis of dynamic characteristic of the fixture based on design variables

International Nuclear Information System (INIS)

Wang Dongsheng; Nong Shaoning; Zhang Sijian; Ren Wanfa

2002-01-01

The research on the sensitivity analysis is dealt with of structural natural frequencies to structural design parameters. A typical fixture for vibration test is designed. Using I-DEAS Finite Element programs, the sensitivity of its natural frequency to design parameters is analyzed by Matrix Perturbation Method. The research result shows that the sensitivity analysis is a fast and effective dynamic re-analysis method to dynamic design and parameters modification of complex structures such as fixtures

Tensor-Train Split-Operator Fourier Transform (TT-SOFT) Method: Multidimensional Nonadiabatic Quantum Dynamics.

Science.gov (United States)

Greene, Samuel M; Batista, Victor S

2017-09-12

We introduce the "tensor-train split-operator Fourier transform" (TT-SOFT) method for simulations of multidimensional nonadiabatic quantum dynamics. TT-SOFT is essentially the grid-based SOFT method implemented in dynamically adaptive tensor-train representations. In the same spirit of all matrix product states, the tensor-train format enables the representation, propagation, and computation of observables of multidimensional wave functions in terms of the grid-based wavepacket tensor components, bypassing the need of actually computing the wave function in its full-rank tensor product grid space. We demonstrate the accuracy and efficiency of the TT-SOFT method as applied to propagation of 24-dimensional wave packets, describing the S 1 /S 2 interconversion dynamics of pyrazine after UV photoexcitation to the S 2 state. Our results show that the TT-SOFT method is a powerful computational approach for simulations of quantum dynamics of polyatomic systems since it avoids the exponential scaling problem of full-rank grid-based representations.

Fully automated segmentation of left ventricle using dual dynamic programming in cardiac cine MR images

Science.gov (United States)

Jiang, Luan; Ling, Shan; Li, Qiang

2016-03-01

Cardiovascular diseases are becoming a leading cause of death all over the world. The cardiac function could be evaluated by global and regional parameters of left ventricle (LV) of the heart. The purpose of this study is to develop and evaluate a fully automated scheme for segmentation of LV in short axis cardiac cine MR images. Our fully automated method consists of three major steps, i.e., LV localization, LV segmentation at end-diastolic phase, and LV segmentation propagation to the other phases. First, the maximum intensity projection image along the time phases of the midventricular slice, located at the center of the image, was calculated to locate the region of interest of LV. Based on the mean intensity of the roughly segmented blood pool in the midventricular slice at each phase, end-diastolic (ED) and end-systolic (ES) phases were determined. Second, the endocardial and epicardial boundaries of LV of each slice at ED phase were synchronously delineated by use of a dual dynamic programming technique. The external costs of the endocardial and epicardial boundaries were defined with the gradient values obtained from the original and enhanced images, respectively. Finally, with the advantages of the continuity of the boundaries of LV across adjacent phases, we propagated the LV segmentation from the ED phase to the other phases by use of dual dynamic programming technique. The preliminary results on 9 clinical cardiac cine MR cases show that the proposed method can obtain accurate segmentation of LV based on subjective evaluation.

Discrete-Time Nonzero-Sum Games for Multiplayer Using Policy-Iteration-Based Adaptive Dynamic Programming Algorithms.

Science.gov (United States)

Zhang, Huaguang; Jiang, He; Luo, Chaomin; Xiao, Geyang

2017-10-01

In this paper, we investigate the nonzero-sum games for a class of discrete-time (DT) nonlinear systems by using a novel policy iteration (PI) adaptive dynamic programming (ADP) method. The main idea of our proposed PI scheme is to utilize the iterative ADP algorithm to obtain the iterative control policies, which not only ensure the system to achieve stability but also minimize the performance index function for each player. This paper integrates game theory, optimal control theory, and reinforcement learning technique to formulate and handle the DT nonzero-sum games for multiplayer. First, we design three actor-critic algorithms, an offline one and two online ones, for the PI scheme. Subsequently, neural networks are employed to implement these algorithms and the corresponding stability analysis is also provided via the Lyapunov theory. Finally, a numerical simulation example is presented to demonstrate the effectiveness of our proposed approach.

An e-learning Programming Method And It's Implementation Based On Multimedia And Web

International Nuclear Information System (INIS)

Madenda, Sarifuddin; Tommy, F. R.

2001-01-01

New developments in information technology and telecommunication play an important rile in exchanging fast and accurate information which range from text, sound, graphic to video. These technologies seem to be very effective for Distance learning, Virtual University and E-learning. This paper presents an E-learning programming method and it's implementation based on multimedia and Web. An example of the study case corresponds to human organ, where the organ functions are presented as texts and sounds and the activities as graphic and video

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

Science.gov (United States)

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

2016-10-01

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

Testing Object-Oriented Programs using Dynamic Aspects and Non-Determinism

DEFF Research Database (Denmark)

Achenbach, Michael; Ostermann, Klaus

2010-01-01

decisions exposing private data. We present an approach that both improves the expressiveness of test cases using non-deterministic choice and reduces design modifications using dynamic aspect-oriented programming techniques. Non-deterministic choice facilitates local definitions of multiple executions...... without parameterization or generation of tests. It also eases modelling naturally non-deterministic program features like IO or multi-threading in integration tests. Dynamic AOP facilitates powerful design adaptations without exposing test features, keeping the scope of these adaptations local to each...... test. We also combine non-determinism and dynamic aspects in a new approach to testing multi-threaded programs using co-routines....

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

Energy Technology Data Exchange (ETDEWEB)

Chen, Qifang; Wang, Fei; Hodge, Bri-Mathias; Zhang, Jianhua; Li, Zhigang; Shafie-Khah, Miadreza; Catalao, Joao P. S.

2017-11-01

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

Dynamic analysis of suspension cable based on vector form intrinsic finite element method

Science.gov (United States)

Qin, Jian; Qiao, Liang; Wan, Jiancheng; Jiang, Ming; Xia, Yongjun

2017-10-01

A vector finite element method is presented for the dynamic analysis of cable structures based on the vector form intrinsic finite element (VFIFE) and mechanical properties of suspension cable. Firstly, the suspension cable is discretized into different elements by space points, the mass and external forces of suspension cable are transformed into space points. The structural form of cable is described by the space points at different time. The equations of motion for the space points are established according to the Newton’s second law. Then, the element internal forces between the space points are derived from the flexible truss structure. Finally, the motion equations of space points are solved by the central difference method with reasonable time integration step. The tangential tension of the bearing rope in a test ropeway with the moving concentrated loads is calculated and compared with the experimental data. The results show that the tangential tension of suspension cable with moving loads is consistent with the experimental data. This method has high calculated precision and meets the requirements of engineering application.

Detection and Extraction of Roads from High Resolution Satellites Images with Dynamic Programming

Science.gov (United States)

Benzouai, Siham; Smara, Youcef

2010-12-01

The advent of satellite images allows now a regular and a fast digitizing and update of geographic data, especially roads which are very useful for Geographic Information Systems (GIS) applications such as transportation, urban pollution, geomarketing, etc. For this, several studies have been conducted to automate roads extraction in order to minimize the manual processes [4]. In this work, we are interested in roads extraction from satellite imagery with high spatial resolution (at best equal to 10 m). The method is semi automatic and follows a linear approach where road is considered as a linear object. As roads extraction is a pattern recognition problem, it is useful, above all, to characterize roads. After, we realize a pre-processing by applying an Infinite Size Edge Filter -ISEF- and processing method based on dynamic programming concept, in particular, Fishler algorithm designed by F*.

A geometrical method towards first integrals for dynamical systems

International Nuclear Information System (INIS)

Labrunie, S.; Conte, R.

1996-01-01

We develop a method, based on Darboux close-quote s and Liouville close-quote s works, to find first integrals and/or invariant manifolds for a physically relevant class of dynamical systems, without making any assumption on these elements close-quote forms. We apply it to three dynamical systems: Lotka endash Volterra, Lorenz and Rikitake. copyright 1996 American Institute of Physics

The Adjoint Method for Gradient-based Dynamic Optimization of UV Flash Processes

DEFF Research Database (Denmark)

Ritschel, Tobias Kasper Skovborg; Capolei, Andrea; Jørgensen, John Bagterp

2017-01-01

This paper presents a novel single-shooting algorithm for gradient-based solution of optimal control problems with vapor-liquid equilibrium constraints. Dynamic optimization of UV flash processes is relevant in nonlinear model predictive control of distillation columns, certain two-phase flow pro......-component flash process which demonstrate the importance of the optimization solver, the compiler, and the linear algebra software for the efficiency of dynamic optimization of UV flash processes....

A METHOD FOR SOLVING LINEAR PROGRAMMING PROBLEMS WITH FUZZY PARAMETERS BASED ON MULTIOBJECTIVE LINEAR PROGRAMMING TECHNIQUE

OpenAIRE

M. ZANGIABADI; H. R. MALEKI

2007-01-01

In the real-world optimization problems, coefficients of the objective function are not known precisely and can be interpreted as fuzzy numbers. In this paper we define the concepts of optimality for linear programming problems with fuzzy parameters based on those for multiobjective linear programming problems. Then by using the concept of comparison of fuzzy numbers, we transform a linear programming problem with fuzzy parameters to a multiobjective linear programming problem. To this end, w...

Large-scale hydropower system optimization using dynamic programming and object-oriented programming: the case of the Northeast China Power Grid.

Science.gov (United States)

Li, Ji-Qing; Zhang, Yu-Shan; Ji, Chang-Ming; Wang, Ai-Jing; Lund, Jay R

2013-01-01

This paper examines long-term optimal operation using dynamic programming for a large hydropower system of 10 reservoirs in Northeast China. Besides considering flow and hydraulic head, the optimization explicitly includes time-varying electricity market prices to maximize benefit. Two techniques are used to reduce the 'curse of dimensionality' of dynamic programming with many reservoirs. Discrete differential dynamic programming (DDDP) reduces the search space and computer memory needed. Object-oriented programming (OOP) and the ability to dynamically allocate and release memory with the C++ language greatly reduces the cumulative effect of computer memory for solving multi-dimensional dynamic programming models. The case study shows that the model can reduce the 'curse of dimensionality' and achieve satisfactory results.

Application of the IPEBS method to dynamic contingency analysis

Energy Technology Data Exchange (ETDEWEB)

Martins, A C.B. [FURNAS, Rio de Janeiro, RJ (Brazil); Pedroso, A S [Centro de Pesquisas de Energia Eletrica (CEPEL), Rio de Janeiro, RJ (Brazil)

1994-12-31

Dynamic contingency analysis is certainly a demanding task in the context of dynamic performance evaluation. This paper presents the results of a test for checking the contingency screening capability of the IPEBS method. A brazilian 1100-bus, 112-gen system was used in the test; the ranking of the contingencies based on critical clearing times obtained with IPEBS, was compared with the ranking derived from detailed time-domain simulation. The results of this comparison encourages us to recommended the use of the method in industry applications, in a complementary basis to the current method of time domain simulation. (author) 5 refs., 1 fig., 2 tabs.

Estimating Arrhenius parameters using temperature programmed molecular dynamics

International Nuclear Information System (INIS)

Imandi, Venkataramana; Chatterjee, Abhijit

2016-01-01

Kinetic rates at different temperatures and the associated Arrhenius parameters, whenever Arrhenius law is obeyed, are efficiently estimated by applying maximum likelihood analysis to waiting times collected using the temperature programmed molecular dynamics method. When transitions involving many activated pathways are available in the dataset, their rates may be calculated using the same collection of waiting times. Arrhenius behaviour is ascertained by comparing rates at the sampled temperatures with ones from the Arrhenius expression. Three prototype systems with corrugated energy landscapes, namely, solvated alanine dipeptide, diffusion at the metal-solvent interphase, and lithium diffusion in silicon, are studied to highlight various aspects of the method. The method becomes particularly appealing when the Arrhenius parameters can be used to find rates at low temperatures where transitions are rare. Systematic coarse-graining of states can further extend the time scales accessible to the method. Good estimates for the rate parameters are obtained with 500-1000 waiting times.

Estimating Arrhenius parameters using temperature programmed molecular dynamics

Energy Technology Data Exchange (ETDEWEB)

Imandi, Venkataramana; Chatterjee, Abhijit, E-mail: abhijit@che.iitb.ac.in [Department of Chemical Engineering, Indian Institute of Technology Bombay, Mumbai 400076 (India)

2016-07-21

Kinetic rates at different temperatures and the associated Arrhenius parameters, whenever Arrhenius law is obeyed, are efficiently estimated by applying maximum likelihood analysis to waiting times collected using the temperature programmed molecular dynamics method. When transitions involving many activated pathways are available in the dataset, their rates may be calculated using the same collection of waiting times. Arrhenius behaviour is ascertained by comparing rates at the sampled temperatures with ones from the Arrhenius expression. Three prototype systems with corrugated energy landscapes, namely, solvated alanine dipeptide, diffusion at the metal-solvent interphase, and lithium diffusion in silicon, are studied to highlight various aspects of the method. The method becomes particularly appealing when the Arrhenius parameters can be used to find rates at low temperatures where transitions are rare. Systematic coarse-graining of states can further extend the time scales accessible to the method. Good estimates for the rate parameters are obtained with 500-1000 waiting times.

Dynamics of the public concern and risk communication program implementation.

Science.gov (United States)

Zaryabova, Victoria; Israel, Michel

2015-09-01

The public concern about electromagnetic field (EMF) exposure varies due to different reasons. A part of them are connected with the better and higher quality of information that people receive from science, media, Internet, social networks, industry, but others are based on good communication programs performed by the responsible institutions, administration and persons. Especially, in Bulgaria, public concern follows interesting changes, some of them in correlation with the European processes of concern, but others following the economic and political processes in the country. Here, we analyze the dynamics of the public concern over the last 10 years. Our explanation of the decrease of the people's complaints against EMF exposure from base stations for mobile communication is as a result of our risk communication program that is in implementation for >10 years.

Complex fluid network optimization and control integrative design based on nonlinear dynamic model

International Nuclear Information System (INIS)

Sui, Jinxue; Yang, Li; Hu, Yunan

2016-01-01

In view of distribution according to complex fluid network’s needs, this paper proposed one optimization computation method of the nonlinear programming mathematical model based on genetic algorithm. The simulation result shows that the overall energy consumption of the optimized fluid network has a decrease obviously. The control model of the fluid network is established based on nonlinear dynamics. We design the control law based on feedback linearization, take the optimal value by genetic algorithm as the simulation data, can also solve the branch resistance under the optimal value. These resistances can provide technical support and reference for fluid network design and construction, so can realize complex fluid network optimization and control integration design.

Rule of Thumb and Dynamic Programming

NARCIS (Netherlands)

Lettau, M.; Uhlig, H.F.H.V.S.

1995-01-01

This paper studies the relationships between learning about rules of thumb (represented by classifier systems) and dynamic programming. Building on a result about Markovian stochastic approximation algorithms, we characterize all decision functions that can be asymptotically obtained through

Discrete Time McKean–Vlasov Control Problem: A Dynamic Programming Approach

Energy Technology Data Exchange (ETDEWEB)

Pham, Huyên, E-mail: pham@math.univ-paris-diderot.fr; Wei, Xiaoli, E-mail: tyswxl@gmail.com [Laboratoire de Probabilités et Modèles Aléatoires, CNRS, UMR 7599, Université Paris Diderot (France)

2016-12-15

We consider the stochastic optimal control problem of nonlinear mean-field systems in discrete time. We reformulate the problem into a deterministic control problem with marginal distribution as controlled state variable, and prove that dynamic programming principle holds in its general form. We apply our method for solving explicitly the mean-variance portfolio selection and the multivariate linear-quadratic McKean–Vlasov control problem.

Discrete Time McKean–Vlasov Control Problem: A Dynamic Programming Approach

International Nuclear Information System (INIS)

Pham, Huyên; Wei, Xiaoli

2016-01-01

We consider the stochastic optimal control problem of nonlinear mean-field systems in discrete time. We reformulate the problem into a deterministic control problem with marginal distribution as controlled state variable, and prove that dynamic programming principle holds in its general form. We apply our method for solving explicitly the mean-variance portfolio selection and the multivariate linear-quadratic McKean–Vlasov control problem.

Programming Unconventional Computers: Dynamics, Development, Self-Reference

Directory of Open Access Journals (Sweden)

Susan Stepney

2012-10-01

Full Text Available Classical computing has well-established formalisms for specifying, refining, composing, proving, and otherwise reasoning about computations. These formalisms have matured over the past 70 years or so. Unconventional Computing includes the use of novel kinds of substrates–from black holes and quantum effects, through to chemicals, biomolecules, even slime moulds–to perform computations that do not conform to the classical model. Although many of these unconventional substrates can be coerced into performing classical computation, this is not how they “naturally” compute. Our ability to exploit unconventional computing is partly hampered by a lack of corresponding programming formalisms: we need models for building, composing, and reasoning about programs that execute in these substrates. What might, say, a slime mould programming language look like? Here I outline some of the issues and properties of these unconventional substrates that need to be addressed to find “natural” approaches to programming them. Important concepts include embodied real values, processes and dynamical systems, generative systems and their meta-dynamics, and embodied self-reference.

Microsoft Dynamics NAV 7 programming cookbook

CERN Document Server

Raul, Rakesh

2013-01-01

Written in the style of a cookbook. Microsoft Dynamics NAV 7 Programming Cookbook is full of recipes to help you get the job done.If you are a junior / entry-level NAV developer then the first half of the book is designed primarily for you. You may or may not have any experience programming. It focuses on the basics of NAV programming.If you are a mid-level NAV developer, you will find these chapters explain how to think outside of the NAV box when building solutions. There are also recipes that senior developers will find useful.

Hybrid Semantics of Stochastic Programs with Dynamic Reconfiguration

Directory of Open Access Journals (Sweden)

Alberto Policriti

2009-10-01

Full Text Available We begin by reviewing a technique to approximate the dynamics of stochastic programs --written in a stochastic process algebra-- by a hybrid system, suitable to capture a mixed discrete/continuous evolution. In a nutshell, the discrete dynamics is kept stochastic while the continuous evolution is given in terms of ODEs, and the overall technique, therefore, naturally associates a Piecewise Deterministic Markov Process with a stochastic program. The specific contribution in this work consists in an increase of the flexibility of the translation scheme, obtained by allowing a dynamic reconfiguration of the degree of discreteness/continuity of the semantics. We also discuss the relationships of this approach with other hybrid simulation strategies for biochemical systems.

Boolean network identification from perturbation time series data combining dynamics abstraction and logic programming.

Science.gov (United States)

Ostrowski, M; Paulevé, L; Schaub, T; Siegel, A; Guziolowski, C

2016-11-01

Boolean networks (and more general logic models) are useful frameworks to study signal transduction across multiple pathways. Logic models can be learned from a prior knowledge network structure and multiplex phosphoproteomics data. However, most efficient and scalable training methods focus on the comparison of two time-points and assume that the system has reached an early steady state. In this paper, we generalize such a learning procedure to take into account the time series traces of phosphoproteomics data in order to discriminate Boolean networks according to their transient dynamics. To that end, we identify a necessary condition that must be satisfied by the dynamics of a Boolean network to be consistent with a discretized time series trace. Based on this condition, we use Answer Set Programming to compute an over-approximation of the set of Boolean networks which fit best with experimental data and provide the corresponding encodings. Combined with model-checking approaches, we end up with a global learning algorithm. Our approach is able to learn logic models with a true positive rate higher than 78% in two case studies of mammalian signaling networks; for a larger case study, our method provides optimal answers after 7min of computation. We quantified the gain in our method predictions precision compared to learning approaches based on static data. Finally, as an application, our method proposes erroneous time-points in the time series data with respect to the optimal learned logic models. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Dynamic Behavior Analysis of Non-Contacting Hydrodynamic Finger Seal Based on Fluid-Solid-Interaction Method

Directory of Open Access Journals (Sweden)

Su Hua

2018-01-01

Full Text Available Finger seal is an advanced compliant seal and can be utilized to separate high (HP and low pressure (LP zones in high speed rotating shaft environment. The work to be presented concerns the dynamic behavior of a repetitive section of a two-layer finger seal with high-and padded low-pressure laminates. The dynamic performance of the finger seal are analyzed by the coupled fluid-solid-interaction (FSI simulations. By using the commercial software ANSYS-CFX, the numerical simulation results of interactions between the gas flow and fingers structural deformation are described when the radial periodic excitation from the shaft applies to the finger seal. And the gas film loading capacity, gas film stiffness and leakage varied with time are put forward in different working conditions. Compared with the dynamic performance analysis results based on equivalent dynamic method, the FSI dynamic analysis shows some different characteristics which are more accordance with actual circumstance. Moreover, it is shown that under low pressure differential and high rotation speed the non-contacting finger seal with advance features both in sealing effectiveness and potential unlimited life span can be obtained by rational structure design. But for the non-contacting finger seal with circumferential convergent pad working in high pressure and low rotating speed conditions, it is difficult to improve the sealing performance by the way of changing the structure parameters of finger seal. It is because the high pressure plays a major role on this sealing situation.

Dynamic Programming Approach for Construction of Association Rule Systems

KAUST Repository

Alsolami, Fawaz

2016-11-18

In the paper, an application of dynamic programming approach for optimization of association rules from the point of view of knowledge representation is considered. The association rule set is optimized in two stages, first for minimum cardinality and then for minimum length of rules. Experimental results present cardinality of the set of association rules constructed for information system and lower bound on minimum possible cardinality of rule set based on the information obtained during algorithm work as well as obtained results for length.

Dynamic Programming Approach for Construction of Association Rule Systems

KAUST Repository

Alsolami, Fawaz; Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata

2016-01-01

In the paper, an application of dynamic programming approach for optimization of association rules from the point of view of knowledge representation is considered. The association rule set is optimized in two stages, first for minimum cardinality and then for minimum length of rules. Experimental results present cardinality of the set of association rules constructed for information system and lower bound on minimum possible cardinality of rule set based on the information obtained during algorithm work as well as obtained results for length.

The Quadrotor Dynamic Modeling and Indoor Target Tracking Control Method

Directory of Open Access Journals (Sweden)

Dewei Zhang

2014-01-01

Full Text Available A reliable nonlinear dynamic model of the quadrotor is presented. The nonlinear dynamic model includes actuator dynamic and aerodynamic effect. Since the rotors run near a constant hovering speed, the dynamic model is simplified at hovering operating point. Based on the simplified nonlinear dynamic model, the PID controllers with feedback linearization and feedforward control are proposed using the backstepping method. These controllers are used to control both the attitude and position of the quadrotor. A fully custom quadrotor is developed to verify the correctness of the dynamic model and control algorithms. The attitude of the quadrotor is measured by inertia measurement unit (IMU. The position of the quadrotor in a GPS-denied environment, especially indoor environment, is estimated from the downward camera and ultrasonic sensor measurements. The validity and effectiveness of the proposed dynamic model and control algorithms are demonstrated by experimental results. It is shown that the vehicle achieves robust vision-based hovering and moving target tracking control.

Three-dimensional static and dynamic reactor calculations by the nodal expansion method

International Nuclear Information System (INIS)

Christensen, B.

1985-05-01

This report reviews various method for the calculation of the neutron-flux- and power distribution in an nuclear reactor. The nodal expansion method (NEM) is especially described in much detail. The nodal expansion method solves the diffusion equation. In this method the reactor core is divided into nodes, typically 10 to 20 cm in each direction, and the average flux in each node is calculated. To obtain the coupling between the nodes the local flux inside each node is expressed by use of a polynomial expansion. The expansion is one-dimensional, so inside each node such three expansions occur. To calculate the expansion coefficients it is necessary that the polynomial expansion is a solution to the one-dimensional diffusion equation. When the one-dimensional diffusion equation is established a term with the transversal leakage occur, and this term is expanded after the same polynomials. The resulting equation system with the expansion coefficients as the unknowns is solved with weigthed residual technique. The nodal expansion method is built into a computer program (also called NEM), which is divided into two parts, one part for steady-state calculations and one part for dynamic calculations. It is possible to take advantage of symmetry properties of the reactor core. The program is very flexible with regard to the number of energy groups, the node size, the flux expansion order and the transverse leakage expansion order. The boundary of the core is described by albedos. The program and input to it are described. The program is tested on a number of examples extending from small theoretical one up to realistic reactor cores. Many calculations are done on the wellknown IAEA benchmark case. The calculations have tested the accuracy and the computing time for various node sizes and polynomial expansions. In the dynamic examples various strategies for variation of the time step-length have been tested. (author)

Communication: Time-dependent optimized coupled-cluster method for multielectron dynamics

Science.gov (United States)

Sato, Takeshi; Pathak, Himadri; Orimo, Yuki; Ishikawa, Kenichi L.

2018-02-01

Time-dependent coupled-cluster method with time-varying orbital functions, called time-dependent optimized coupled-cluster (TD-OCC) method, is formulated for multielectron dynamics in an intense laser field. We have successfully derived the equations of motion for CC amplitudes and orthonormal orbital functions based on the real action functional, and implemented the method including double excitations (TD-OCCD) and double and triple excitations (TD-OCCDT) within the optimized active orbitals. The present method is size extensive and gauge invariant, a polynomial cost-scaling alternative to the time-dependent multiconfiguration self-consistent-field method. The first application of the TD-OCC method of intense-laser driven correlated electron dynamics in Ar atom is reported.

Probability-based load combinations for design of category I structures - overview of research program and recent results

International Nuclear Information System (INIS)

Reich, M.; Hwang, H.

1984-01-01

This paper discusses the probability-based load combinations for the program dealing with the design of Category I structures, currently being worked on at Brookhaven National Laboratory (BNL) for the Office of Nuclear Regulatory Research, U.S. Nuclear Regulatory Commission (NRC). The objective of this program is to develop a probabilistic approach for the safety evaluations of reactor containments and other seismic Category I structures subjected to multiple static and dynamic loadings. Furthermore, on the basis of the developed probabilistic approach, a load combination methodology for the design of seismic Category I structures will also be established. The major tasks of this program are: (1) establish probabilistic representations for various loads and structural resistance, (2) select appropriate structural analysis methods and identify limit states of structures, (3) develop a reliability analysis method applicable to nuclear structures, (4) apply the developed methodology to existing Category I structures in order to evaluate the reliability levels implied in the current design criteria, and (5) recommend load combination design criteria for Category I structures. When the program is completed, it will be possible to (1) provide a method that can evaluate the safety margins of existing containment and other Category I structures and (2) recommended probability-based load combinations and load factors for the design of Category I structures. At the present time, a reliability analysis method for seismic Category I concrete structures has been completed. By utilizing this method, it is possible to evaluate the safety of structures under various static and dynamic loads. In this paper, results of a reliability analysis of a realistic reinforced concrete containment structure under dead load, accidental pressure, and earthquake ground acceleration are presented to demonstrate the feasibility of the methodology. (orig.)

Multi-objective dynamic economic emission dispatch of electric power generation integrated with game theory based demand response programs

International Nuclear Information System (INIS)

Nwulu, Nnamdi I.; Xia, Xiaohua

2015-01-01

Highlights: • In this work, a game theory based DR program is integrated into the DEED problem. • Objectives are to minimize fuel and emissions costs and maximize the DR benefit. • Optimal generator output, customer load and customer incentive are determined. • Developed model is tested with two different scenarios. • Model provides superior results than independent optimization of DR or DEED. - Abstract: The dynamic economic emission dispatch (DEED) of electric power generation is a multi-objective mathematical optimization problem with two objective functions. The first objective is to minimize all the fuel costs of the generators in the power system, whilst the second objective seeks to minimize the emissions cost. Both objective functions are subject to constraints such as load demand constraint, ramp rate constraint, amongst other constraints. In this work, we integrate a game theory based demand response program into the DEED problem. The game theory based demand response program determines the optimal hourly incentive to be offered to customers who sign up for load curtailment. The game theory model has in built mechanisms to ensure that the incentive offered the customers is greater than the cost of interruption while simultaneously being beneficial to the utility. The combined DEED and game theoretic demand response model presented in this work, minimizes fuel and emissions costs and simultaneously determines the optimal incentive and load curtailment customers have to perform for maximal power system relief. The developed model is tested on two test systems with industrial customers and obtained results indicate the practical benefits of the proposed model

Evolution of the DeNOC-based dynamic modelling for multibody systems

Directory of Open Access Journals (Sweden)

S. K. Saha

2013-01-01

Full Text Available Dynamic modelling of a multibody system plays very essential role in its analyses. As a result, several methods for dynamic modelling have evolved over the years that allow one to analyse multibody systems in a very efficient manner. One such method of dynamic modelling is based on the concept of the Decoupled Natural Orthogonal Complement (DeNOC matrices. The DeNOC-based methodology for dynamics modelling, since its introduction in 1995, has been applied to a variety of multibody systems such as serial, parallel, general closed-loop, flexible, legged, cam-follower, and space robots. The methodology has also proven useful for modelling of proteins and hyper-degree-of-freedom systems like ropes, chains, etc. This paper captures the evolution of the DeNOC-based dynamic modelling applied to different type of systems, and its benefits over other existing methodologies. It is shown that the DeNOC-based modelling provides deeper understanding of the dynamics of a multibody system. The power of the DeNOC-based modelling has been illustrated using several numerical examples.

Program Transformation to Identify List-Based Parallel Skeletons

Directory of Open Access Journals (Sweden)

Venkatesh Kannan

2016-07-01

Full Text Available Algorithmic skeletons are used as building-blocks to ease the task of parallel programming by abstracting the details of parallel implementation from the developer. Most existing libraries provide implementations of skeletons that are defined over flat data types such as lists or arrays. However, skeleton-based parallel programming is still very challenging as it requires intricate analysis of the underlying algorithm and often uses inefficient intermediate data structures. Further, the algorithmic structure of a given program may not match those of list-based skeletons. In this paper, we present a method to automatically transform any given program to one that is defined over a list and is more likely to contain instances of list-based skeletons. This facilitates the parallel execution of a transformed program using existing implementations of list-based parallel skeletons. Further, by using an existing transformation called distillation in conjunction with our method, we produce transformed programs that contain fewer inefficient intermediate data structures.

A simple interface to computational fluid dynamics programs for building environment simulations

Energy Technology Data Exchange (ETDEWEB)

Broderick, III, C R; Chen, Q [Massachusetts Institute of Technology, Cambridge, MA (United States)

2000-07-01

It is becoming a popular practice for architects and HVAC engineers to simulate airflow in and around buildings by computational fluid dynamics (CFD) methods in order to predict indoor and outdoor environment. However, many CFD programs are crippled by a historically poor and inefficient user interface system, particularly for users with little training in numerical simulation. This investigation endeavors to create a simplified CFD interface (SCI) that allows architects and buildings engineers to use CFD without excessive training. The SCI can be easily integrated into new CFD programs. (author)

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

POLYANA-A tool for the calculation of molecular radial distribution functions based on Molecular Dynamics trajectories

Science.gov (United States)

Dimitroulis, Christos; Raptis, Theophanes; Raptis, Vasilios

2015-12-01

We present an application for the calculation of radial distribution functions for molecular centres of mass, based on trajectories generated by molecular simulation methods (Molecular Dynamics, Monte Carlo). When designing this application, the emphasis was placed on ease of use as well as ease of further development. In its current version, the program can read trajectories generated by the well-known DL_POLY package, but it can be easily extended to handle other formats. It is also very easy to 'hack' the program so it can compute intermolecular radial distribution functions for groups of interaction sites rather than whole molecules.

Dynamic and stochastic multi-project planning

CERN Document Server

Melchiors, Philipp

2015-01-01

This book deals with dynamic and stochastic methods for multi-project planning. Based on the idea of using queueing networks for the analysis of dynamic-stochastic multi-project environments this book addresses two problems: detailed scheduling of project activities, and integrated order acceptance and capacity planning. In an extensive simulation study, the book thoroughly investigates existing scheduling policies. To obtain optimal and near optimal scheduling policies new models and algorithms are proposed based on the theory of Markov decision processes and Approximate Dynamic programming.

Numerical methods in multibody dynamics

CERN Document Server

Eich-Soellner, Edda

1998-01-01

Today computers play an important role in the development of complex mechanical systems, such as cars, railway vehicles or machines. Efficient simulation of these systems is only possible when based on methods that explore the strong link between numerics and computational mechanics. This book gives insight into modern techniques of numerical mathematics in the light of an interesting field of applications: multibody dynamics. The important interaction between modeling and solution techniques is demonstrated by using a simplified multibody model of a truck. Different versions of this mechanical model illustrate all key concepts in static and dynamic analysis as well as in parameter identification. The book focuses in particular on constrained mechanical systems. Their formulation in terms of differential-algebraic equations is the backbone of nearly all chapters. The book is written for students and teachers in numerical analysis and mechanical engineering as well as for engineers in industrial research labor...

Online Synchrophasor-Based Dynamic State Estimation using Real-Time Digital Simulator

DEFF Research Database (Denmark)

Khazraj, Hesam; Adewole, Adeyemi Charles; Udaya, Annakkage

2018-01-01

Dynamic state estimation is a very important control center application used in the dynamic monitoring of state variables. This paper presents and validates a time-synchronized phasor measurement unit (PMU)-based for dynamic state estimation by unscented Kalman filter (UKF) method using the real-...... using the RTDS (real-time digital simulator). The dynamic state variables of multi-machine systems are monitored and measured for the study on the transient behavior of power systems.......Dynamic state estimation is a very important control center application used in the dynamic monitoring of state variables. This paper presents and validates a time-synchronized phasor measurement unit (PMU)-based for dynamic state estimation by unscented Kalman filter (UKF) method using the real......-time digital simulator (RTDS). The dynamic state variables of the system are the rotor angle and speed of the generators. The performance of the UKF method is tested with PMU measurements as inputs using the IEEE 14-bus test system. This test system was modeled in the RSCAD software and tested in real time...

PID Based on Attractive Ellipsoid Method for Dynamic Uncertain and External Disturbances Rejection in Mechanical Systems

Directory of Open Access Journals (Sweden)

Jesus Patricio Ordaz Oliver

2015-01-01

Full Text Available This paper presents a stability analysis for LNDS (Lagrangian nonlinear dynamical systems with dynamic uncertain using a PID controller with external disturbances rejection based on attractive ellipsoid methods, since the PID-CT (proportional integral derivative computed torque compensator has been used for the nonlinear trajectory tracking of an LNDS, when there are external perturbations and system uncertainties. The global system convergence of the trivial solution has not been proved. In this sense, we propose an approach to find the gains of the nonlinear PID-CT controller to guarantee the boundedness of the trivial solution by means of the concept of the UUB (uniform-ultimately bounded stability. In order to show the effectiveness of the methodology proposed, we applied it in a real 2-DoF robot system.

Wavelet and adaptive methods for time dependent problems and applications in aerosol dynamics

Science.gov (United States)

Guo, Qiang

Time dependent partial differential equations (PDEs) are widely used as mathematical models of environmental problems. Aerosols are now clearly identified as an important factor in many environmental aspects of climate and radiative forcing processes, as well as in the health effects of air quality. The mathematical models for the aerosol dynamics with respect to size distribution are nonlinear partial differential and integral equations, which describe processes of condensation, coagulation and deposition. Simulating the general aerosol dynamic equations on time, particle size and space exhibits serious difficulties because the size dimension ranges from a few nanometer to several micrometer while the spatial dimension is usually described with kilometers. Therefore, it is an important and challenging task to develop efficient techniques for solving time dependent dynamic equations. In this thesis, we develop and analyze efficient wavelet and adaptive methods for the time dependent dynamic equations on particle size and further apply them to the spatial aerosol dynamic systems. Wavelet Galerkin method is proposed to solve the aerosol dynamic equations on time and particle size due to the fact that aerosol distribution changes strongly along size direction and the wavelet technique can solve it very efficiently. Daubechies' wavelets are considered in the study due to the fact that they possess useful properties like orthogonality, compact support, exact representation of polynomials to a certain degree. Another problem encountered in the solution of the aerosol dynamic equations results from the hyperbolic form due to the condensation growth term. We propose a new characteristic-based fully adaptive multiresolution numerical scheme for solving the aerosol dynamic equation, which combines the attractive advantages of adaptive multiresolution technique and the characteristics method. On the aspect of theoretical analysis, the global existence and uniqueness of

Three-Dimensional Dynamic Topology Optimization with Frequency Constraints Using Composite Exponential Function and ICM Method

Directory of Open Access Journals (Sweden)

Hongling Ye

2015-01-01

Full Text Available The dynamic topology optimization of three-dimensional continuum structures subject to frequency constraints is investigated using Independent Continuous Mapping (ICM design variable fields. The composite exponential function (CEF is selected to be a filter function which recognizes the design variables and to implement the changing process of design variables from “discrete” to “continuous” and back to “discrete.” Explicit formulations of frequency constraints are given based on filter functions, first-order Taylor series expansion. And an improved optimal model is formulated using CEF and the explicit frequency constraints. Dual sequential quadratic programming (DSQP algorithm is used to solve the optimal model. The program is developed on the platform of MSC Patran & Nastran. Finally, numerical examples are given to demonstrate the validity and applicability of the proposed method.

The computer coordination method and research of inland river traffic based on ship database

Science.gov (United States)

Liu, Shanshan; Li, Gen

2018-04-01

A computer coordinated management method for inland river ship traffic is proposed in this paper, Get the inland ship's position, speed and other navigation information by VTS, building ship's statics and dynamic data bases, writing a program of computer coordinated management of inland river traffic by VB software, Automatic simulation and calculation of the meeting states of ships, Providing ship's long-distance collision avoidance information. The long-distance collision avoidance of ships will be realized. The results show that, Ships avoid or reduce meetings, this method can effectively control the macro collision avoidance of ships.

Explicit/multi-parametric model predictive control (MPC) of linear discrete-time systems by dynamic and multi-parametric programming

KAUST Repository

Kouramas, K.I.; Faí sca, N.P.; Panos, C.; Pistikopoulos, E.N.

2011-01-01

This work presents a new algorithm for solving the explicit/multi- parametric model predictive control (or mp-MPC) problem for linear, time-invariant discrete-time systems, based on dynamic programming and multi-parametric programming techniques

Optimization of control poison management by dynamic programming

International Nuclear Information System (INIS)

Ponzoni Filho, P.

1974-01-01

A dynamic programming approach was used to optimize the poison distribution in the core of a nuclear power plant between reloading. This method was applied to a 500 M We PWR subject to two different fuel management policies. The beginning of a stage is marked by a fuel management decision. The state vector of the system is defined by the burnups in the three fuel zones of the core. The change of the state vector is computed in several time steps. A criticality conserving poison management pattern is chosen at the beginning of each step. The burnups at the end of a step are obtained by means of depletion calculations, assuming constant neutron distribution during the step. The violation of burnup and power peaking constraints during the step eliminates the corresponding end states. In the case of identical end states, all except that which produced the largest amount of energy, are eliminated. Among the several end states one is selected for the subsequent stage, when it is subjected to a fuel management decision. This selection is based on an optimally criterion previously chosen, such as: discharged fuel burnup maximization, energy generation cost minimization, etc. (author)

Implementation of a Small Type DC Microgrid Based on Fuzzy Control and Dynamic Programming

Directory of Open Access Journals (Sweden)

Chin-Hsing Cheng

2016-09-01

Full Text Available A DC microgrid (DC-MG is a novel power system that uses DC distribution in order to provide high quality power. The study system is made by a photovoltaic array (PV, a wind generator (WG, a fuel cell (FC, and an energy storage system (ESS to establish a small type DC microgrid, with the bus being established by DC/DC converters with fuzzy controllers. An overall power dispatch was designed for the proposed system to distribute the power flows among the different energy sources and the storage unit in the system in order to satisfy the load requirements throughout an entire 24-h period. The structure of a power supervisor based on an optimal power dispatch algorithm is here proposed. Optimization was performed using dynamic programming (DP. In this paper, a system configuration of a DC microgrid is analyzed in different scenarios to show the efficacy of the control for all devices for the variable weather conditions with different DC loads. Thus, the voltage level and the power flow of the system are shown for different load conditions.

A method of recovering the initial vectors of globally coupled map lattices based on symbolic dynamics

International Nuclear Information System (INIS)

Sun Li-Sha; Kang Xiao-Yun; Zhang Qiong; Lin Lan-Xin

2011-01-01

Based on symbolic dynamics, a novel computationally efficient algorithm is proposed to estimate the unknown initial vectors of globally coupled map lattices (CMLs). It is proved that not all inverse chaotic mapping functions are satisfied for contraction mapping. It is found that the values in phase space do not always converge on their initial values with respect to sufficient backward iteration of the symbolic vectors in terms of global convergence or divergence (CD). Both CD property and the coupling strength are directly related to the mapping function of the existing CML. Furthermore, the CD properties of Logistic, Bernoulli, and Tent chaotic mapping functions are investigated and compared. Various simulation results and the performances of the initial vector estimation with different signal-to-noise ratios (SNRs) are also provided to confirm the proposed algorithm. Finally, based on the spatiotemporal chaotic characteristics of the CML, the conditions of estimating the initial vectors using symbolic dynamics are discussed. The presented method provides both theoretical and experimental results for better understanding and characterizing the behaviours of spatiotemporal chaotic systems. (general)

A method of recovering the initial vectors of globally coupled map lattices based on symbolic dynamics

Science.gov (United States)

Sun, Li-Sha; Kang, Xiao-Yun; Zhang, Qiong; Lin, Lan-Xin

2011-12-01

Based on symbolic dynamics, a novel computationally efficient algorithm is proposed to estimate the unknown initial vectors of globally coupled map lattices (CMLs). It is proved that not all inverse chaotic mapping functions are satisfied for contraction mapping. It is found that the values in phase space do not always converge on their initial values with respect to sufficient backward iteration of the symbolic vectors in terms of global convergence or divergence (CD). Both CD property and the coupling strength are directly related to the mapping function of the existing CML. Furthermore, the CD properties of Logistic, Bernoulli, and Tent chaotic mapping functions are investigated and compared. Various simulation results and the performances of the initial vector estimation with different signal-to-noise ratios (SNRs) are also provided to confirm the proposed algorithm. Finally, based on the spatiotemporal chaotic characteristics of the CML, the conditions of estimating the initial vectors using symbolic dynamics are discussed. The presented method provides both theoretical and experimental results for better understanding and characterizing the behaviours of spatiotemporal chaotic systems.

Online Adaptive Optimal Control of Vehicle Active Suspension Systems Using Single-Network Approximate Dynamic Programming

Directory of Open Access Journals (Sweden)

Zhi-Jun Fu

2017-01-01

Full Text Available In view of the performance requirements (e.g., ride comfort, road holding, and suspension space limitation for vehicle suspension systems, this paper proposes an adaptive optimal control method for quarter-car active suspension system by using the approximate dynamic programming approach (ADP. Online optimal control law is obtained by using a single adaptive critic NN to approximate the solution of the Hamilton-Jacobi-Bellman (HJB equation. Stability of the closed-loop system is proved by Lyapunov theory. Compared with the classic linear quadratic regulator (LQR approach, the proposed ADP-based adaptive optimal control method demonstrates improved performance in the presence of parametric uncertainties (e.g., sprung mass and unknown road displacement. Numerical simulation results of a sedan suspension system are presented to verify the effectiveness of the proposed control strategy.

Combinatorial computational chemistry approach of tight-binding quantum chemical molecular dynamics method to the design of the automotive catalysts

International Nuclear Information System (INIS)

Ito, Yuki; Jung, Changho; Luo, Yi; Koyama, Michihisa; Endou, Akira; Kubo, Momoji; Imamura, Akira; Miyamoto, Akira

2006-01-01

Recently, we have developed a new tight-binding quantum chemical molecular dynamics program 'Colors' for combinatorial computational chemistry approach. This methodology is based on our original tight-binding approximation and realized over 5000 times acceleration compared to the conventional first-principles molecular dynamics method. In the present study, we applied our new program to the simulations on various realistic large-scale models of the automotive three-way catalysts, ultrafine Pt particle/CeO 2 (111) support. Significant electron transfer from the Pt particle to the CeO 2 (111) surface was observed and it was found to strongly depend on the size of the Pt particle. Furthermore, our simulation results suggest that the reduction of the Ce atom due to the electron transfer from the Pt particle to the CeO 2 surface is a main reason for the strong interaction of the Pt particle and CeO 2 (111) support

Molecular dynamics simulation based on the multi-component molecular orbital method: Application to H5O2+,D5O2+,andT5O2+

International Nuclear Information System (INIS)

Ishimoto, Takayoshi; Koyama, Michihisa

2012-01-01

Graphical abstract: Molecular dynamics method based on multi-component molecular orbital method was applied to basic hydrogen bonding systems, H 5 O 2 + , and its isotopomers (D 5 O 2 + andT 5 O 2 + ). Highlights: ► Molecular dynamics method with nuclear quantum effect was developed. ► Multi-component molecular orbital method was used as ab initio MO calculation. ► Developed method applied to basic hydrogen bonding system, H 5 O 2 + , and isotopomers. ► O ⋯ O vibrational stretching reflected to the distribution of protonic wavefunctions. ► H/D/T isotope effect was also analyzed. - Abstract: We propose a molecular dynamics (MD) method based on the multi-component molecular orbital (MC M O) method, which takes into account the quantum effect of proton directly, for the detailed analyses of proton transfer in hydrogen bonding system. The MC M O based MD (MC M O-MD) method is applied to the basic structures, H 5 O 2 + (called “Zundel ion”), and its isotopomers (D 5 O 2 + andT 5 O 2 + ). We clearly demonstrate the geometrical difference of hydrogen bonded O ⋯ O distance induced by H/D/T isotope effect because the O ⋯ O in H-compound was longer than that in D- or T-compound. We also find the strong relation between stretching vibration of O ⋯ O and the distribution of hydrogen bonded protonic wavefunction because the protonic wavefunction tends to delocalize when the O ⋯ O distance becomes short during the dynamics. Our proposed MC M O-MD simulation is expected as a powerful tool to analyze the proton dynamics in hydrogen bonding systems.

Integration agent-based models and GIS as a virtual urban dynamic laboratory

Science.gov (United States)

Chen, Peng; Liu, Miaolong

2007-06-01

Based on the Agent-based Model and spatial data model, a tight-coupling integrating method of GIS and Agent-based Model (ABM) is to be discussed in this paper. The use of object-orientation for both spatial data and spatial process models facilitates their integration, which can allow exploration and explanation of spatial-temporal phenomena such as urban dynamic. In order to better understand how tight coupling might proceed and to evaluate the possible functional and efficiency gains from such a tight coupling, the agent-based model and spatial data model are discussed, and then the relationships affecting spatial data model and agent-based process models interaction. After that, a realistic crowd flow simulation experiment is presented. Using some tools provided by general GIS systems and a few specific programming languages, a new software system integrating GIS and MAS as a virtual laboratory applicable for simulating pedestrian flows in a crowd activity centre has been developed successfully. Under the environment supported by the software system, as an applicable case, a dynamic evolution process of the pedestrian's flows (dispersed process for the spectators) in a crowds' activity center - The Shanghai Stadium has been simulated successfully. At the end of the paper, some new research problems have been pointed out for the future.

Optimal Design of Measurement Programs for the Parameter Identification of Dynamic Systems

DEFF Research Database (Denmark)

Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune

1993-01-01

The design of a measurement program devoted to parameter identification of structural dynamic systems is considered. The design problem is formulated as an optimization problem to minimize the total expected cost that is the cost of failure and the cost of the measurement program. All...... the calculations are based on a priori knowledge and engineering judgement. One of the contribution of the approach is that the optimal number of sensory can be estimated. This is shown in an numerical example where the proposed approach is demonstrated. The example is concerned with design of a measurement...

Optimal Design of Measurement Programs for the Parameter Identification of Dynamic Systems

DEFF Research Database (Denmark)

Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune

1991-01-01

The design of a measurement program devoted to parameter identification of structural dynamic systems is considered. The design problem is formulated as an optimization problem to minimize the total expected cost, i.e. the cost of failure and the cost of the measurement program. All...... the calculations are based on a priori knowledge and engineering judgement. One of the contributions of the approach is that the optimal number of sensors can be estimated. This is shown in a numerical example where the proposed approach is demonstrated. The example is concerned with design of a measurement...

Element Partition Trees For H-Refined Meshes to Optimize Direct Solver Performance. Part I: Dynamic Programming

KAUST Repository

AbouEisha, Hassan M.

2017-07-13

We consider a class of two-and three-dimensional h-refined meshes generated by an adaptive finite element method. We introduce an element partition tree, which controls the execution of the multi-frontal solver algorithm over these refined grids. We propose and study algorithms with polynomial computational cost for the optimization of these element partition trees. The trees provide an ordering for the elimination of unknowns. The algorithms automatically optimize the element partition trees using extensions of dynamic programming. The construction of the trees by the dynamic programming approach is expensive. These generated trees cannot be used in practice, but rather utilized as a learning tool to propose fast heuristic algorithms. In this first part of our paper we focus on the dynamic programming approach, and draw a sketch of the heuristic algorithm. The second part will be devoted to a more detailed analysis of the heuristic algorithm extended for the case of hp-adaptive

Element Partition Trees For H-Refined Meshes to Optimize Direct Solver Performance. Part I: Dynamic Programming

KAUST Repository

AbouEisha, Hassan M.; Calo, Victor Manuel; Jopek, Konrad; Moshkov, Mikhail; Paszyńka, Anna; Paszyński, Maciej; Skotniczny, Marcin

2017-01-01

We consider a class of two-and three-dimensional h-refined meshes generated by an adaptive finite element method. We introduce an element partition tree, which controls the execution of the multi-frontal solver algorithm over these refined grids. We propose and study algorithms with polynomial computational cost for the optimization of these element partition trees. The trees provide an ordering for the elimination of unknowns. The algorithms automatically optimize the element partition trees using extensions of dynamic programming. The construction of the trees by the dynamic programming approach is expensive. These generated trees cannot be used in practice, but rather utilized as a learning tool to propose fast heuristic algorithms. In this first part of our paper we focus on the dynamic programming approach, and draw a sketch of the heuristic algorithm. The second part will be devoted to a more detailed analysis of the heuristic algorithm extended for the case of hp-adaptive

Multi-coupling dynamic model and 3d simulation program for in-situ leaching of uranium mining

International Nuclear Information System (INIS)

Tan Kaixuan; Zeng Sheng; Sang Xiao; Sun Bing

2010-01-01

The in-situ leaching of uranium mining is a very complicated non-linear dynamic system, which involves couplings and positive/negative feedback among many factors and processes. A comprehensive, coupled multi-factors and processes dynamic model and simulation method was established to study the in-situ leaching of uranium mining. The model accounts for most coupling among various processes as following: (1) rock texture mechanics and its evolution, (2)the incremental stress rheology of rock deformation, (3) 3-D viscoelastic/ plastic multi-deformation processes, (4) hydrofracturing, (5) tensorial (anisotropic) fracture and rock permeability, (6) water-rock interactions and mass-transport (both advective and diffusive), (7) dissolution-induced chemical compaction, (8) multi-phase fluid flow. A 3-D simulation program was compiled based on Fortran and C++. An example illustrating the application of this model to simulating acidification, production and terminal stage of in situ leaching of uranium mining is presented for the some mine in Xinjiang, China. This model and program can be used for theoretical study, mine design, production management, the study of contaminant transport and restoration in groundwater of in-situ leaching of uranium mining. (authors)

Musical structure analysis using similarity matrix and dynamic programming

Science.gov (United States)

Shiu, Yu; Jeong, Hong; Kuo, C.-C. Jay

2005-10-01

Automatic music segmentation and structure analysis from audio waveforms based on a three-level hierarchy is examined in this research, where the three-level hierarchy includes notes, measures and parts. The pitch class profile (PCP) feature is first extracted at the note level. Then, a similarity matrix is constructed at the measure level, where a dynamic time warping (DTW) technique is used to enhance the similarity computation by taking the temporal distortion of similar audio segments into account. By processing the similarity matrix, we can obtain a coarse-grain music segmentation result. Finally, dynamic programming is applied to the coarse-grain segments so that a song can be decomposed into several major parts such as intro, verse, chorus, bridge and outro. The performance of the proposed music structure analysis system is demonstrated for pop and rock music.

Gradient-based optimization in nonlinear structural dynamics

DEFF Research Database (Denmark)

Dou, Suguang

The intrinsic nonlinearity of mechanical structures can give rise to rich nonlinear dynamics. Recently, nonlinear dynamics of micro-mechanical structures have contributed to developing new Micro-Electro-Mechanical Systems (MEMS), for example, atomic force microscope, passive frequency divider......, frequency stabilization, and disk resonator gyroscope. For advanced design of these structures, it is of considerable value to extend current optimization in linear structural dynamics into nonlinear structural dynamics. In this thesis, we present a framework for modelling, analysis, characterization......, and optimization of nonlinear structural dynamics. In the modelling, nonlinear finite elements are used. In the analysis, nonlinear frequency response and nonlinear normal modes are calculated based on a harmonic balance method with higher-order harmonics. In the characterization, nonlinear modal coupling...

New numerical methods for open-loop and feedback solutions to dynamic optimization problems

Science.gov (United States)

Ghosh, Pradipto

The topic of the first part of this research is trajectory optimization of dynamical systems via computational swarm intelligence. Particle swarm optimization is a nature-inspired heuristic search method that relies on a group of potential solutions to explore the fitness landscape. Conceptually, each particle in the swarm uses its own memory as well as the knowledge accumulated by the entire swarm to iteratively converge on an optimal or near-optimal solution. It is relatively straightforward to implement and unlike gradient-based solvers, does not require an initial guess or continuity in the problem definition. Although particle swarm optimization has been successfully employed in solving static optimization problems, its application in dynamic optimization, as posed in optimal control theory, is still relatively new. In the first half of this thesis particle swarm optimization is used to generate near-optimal solutions to several nontrivial trajectory optimization problems including thrust programming for minimum fuel, multi-burn spacecraft orbit transfer, and computing minimum-time rest-to-rest trajectories for a robotic manipulator. A distinct feature of the particle swarm optimization implementation in this work is the runtime selection of the optimal solution structure. Optimal trajectories are generated by solving instances of constrained nonlinear mixed-integer programming problems with the swarming technique. For each solved optimal programming problem, the particle swarm optimization result is compared with a nearly exact solution found via a direct method using nonlinear programming. Numerical experiments indicate that swarm search can locate solutions to very great accuracy. The second half of this research develops a new extremal-field approach for synthesizing nearly optimal feedback controllers for optimal control and two-player pursuit-evasion games described by general nonlinear differential equations. A notable revelation from this development

The long-run dynamic relationship between exchange rate and its attention index: Based on DCCA and TOP method

Science.gov (United States)

Wang, Xuan; Guo, Kun; Lu, Xiaolin

2016-07-01

The behavior information of financial market plays a more and more important role in modern economic system. The behavior information reflected in INTERNET search data has already been used in short-term prediction for exchange rate, stock market return, house price and so on. However, the long-run relationship between behavior information and financial market fluctuation has not been studied systematically. Further, most traditional statistic methods and econometric models could not catch the dynamic and non-linear relationship. An attention index of CNY/USD exchange rate is constructed based on search data from 360 search engine of China in this paper. Then the DCCA and Thermal Optimal Path methods are used to explore the long-run dynamic relationship between CNY/USD exchange rate and the corresponding attention index. The results show that the significant interdependency exists and the change of exchange rate is 1-2 days lag behind the attention index.

An evidence-based rehabilitation program for tracheoesophageal speakers

NARCIS (Netherlands)

Jongmans, P.; Rossum, M.; As-Brooks, C.; Hilgers, F.; Pols, L.; Hilgers, F.J.M.; Pols, L.C.W.; van Rossum, M.; van den Brekel, M.W.M.

2008-01-01

Objectives: to develop an evidence-based therapy program aimed at improving tracheoesophageal speech intelligibility. The therapy program is based on particular problems found for TE speakers in a previous study as performed by the authors. Patients/Materials and Methods: 9 male laryngectomized

Dynamic Programming and Graph Algorithms in Computer Vision*

Science.gov (United States)

Felzenszwalb, Pedro F.; Zabih, Ramin

2013-01-01

Optimization is a powerful paradigm for expressing and solving problems in a wide range of areas, and has been successfully applied to many vision problems. Discrete optimization techniques are especially interesting, since by carefully exploiting problem structure they often provide non-trivial guarantees concerning solution quality. In this paper we briefly review dynamic programming and graph algorithms, and discuss representative examples of how these discrete optimization techniques have been applied to some classical vision problems. We focus on the low-level vision problem of stereo; the mid-level problem of interactive object segmentation; and the high-level problem of model-based recognition. PMID:20660950

Sensitivity Analysis of Dynamic Tariff Method for Congestion Management in Distribution Networks

DEFF Research Database (Denmark)

Huang, Shaojun; Wu, Qiuwei; Liu, Zhaoxi

2015-01-01

The dynamic tariff (DT) method is designed for the distribution system operator (DSO) to alleviate the congestions that might occur in a distribution network with high penetration of distribute energy resources (DERs). Sensitivity analysis of the DT method is crucial because of its decentralized...... control manner. The sensitivity analysis can obtain the changes of the optimal energy planning and thereby the line loading profiles over the infinitely small changes of parameters by differentiating the KKT conditions of the convex quadratic programming, over which the DT method is formed. Three case...

The finite volume method in computational fluid dynamics an advanced introduction with OpenFOAM and Matlab

CERN Document Server

Moukalled, F; Darwish, M

2016-01-01

This textbook explores both the theoretical foundation of the Finite Volume Method (FVM) and its applications in Computational Fluid Dynamics (CFD). Readers will discover a thorough explanation of the FVM numerics and algorithms used for the simulation of incompressible and compressible fluid flows, along with a detailed examination of the components needed for the development of a collocated unstructured pressure-based CFD solver. Two particular CFD codes are explored. The first is uFVM, a three-dimensional unstructured pressure-based finite volume academic CFD code, implemented within Matlab. The second is OpenFOAM®, an open source framework used in the development of a range of CFD programs for the simulation of industrial scale flow problems. With over 220 figures, numerous examples and more than one hundred exercise on FVM numerics, programming, and applications, this textbook is suitable for use in an introductory course on the FVM, in an advanced course on numerics, and as a reference for CFD programm...

The dynamic time-over-threshold method for multi-channel APD based gamma-ray detectors

Energy Technology Data Exchange (ETDEWEB)

Orita, T., E-mail: orita.tadashi@jaea.go.jp [Japan Atomic Energy Agency, Fukushima (Japan); Shimazoe, K.; Takahashi, H. [Department of Nuclear Management and Engineering, The University of Tokyo, Bunkyō (Japan)

2015-03-01

t– Recent advances in manufacturing technology have enabled the use of multi-channel pixelated detectors in gamma-ray imaging applications. When obtaining gamma-ray measurements, it is important to obtain pulse height information in order to avoid unnecessary events such as scattering. However, as the number of channels increases, more electronics are needed to process each channel's signal, and the corresponding increases in circuit size and power consumption can result in practical problems. The time-over-threshold (ToT) method, which has recently become popular in the medical field, is a signal processing technique that can effectively avoid such problems. However, ToT suffers from poor linearity and its dynamic range is limited. We therefore propose a new ToT technique called the dynamic time-over-threshold (dToT) method [4]. A new signal processing system using dToT and CR-RC shaping demonstrated much better linearity than that of a conventional ToT. Using a test circuit with a new Gd{sub 3}Al{sub 2}Ga{sub 3}O{sub 12} (GAGG) scintillator and an avalanche photodiode, the pulse height spectra of {sup 137}Cs and {sup 22}Na sources were measured with high linearity. Based on these results, we designed a new application-specific integrated circuit (ASIC) for this multi-channel dToT system, measured the spectra of a {sup 22}Na source, and investigated the linearity of the system.

Finite Countermodel Based Verification for Program Transformation (A Case Study

Directory of Open Access Journals (Sweden)

Alexei P. Lisitsa

2015-12-01

Full Text Available Both automatic program verification and program transformation are based on program analysis. In the past decade a number of approaches using various automatic general-purpose program transformation techniques (partial deduction, specialization, supercompilation for verification of unreachability properties of computing systems were introduced and demonstrated. On the other hand, the semantics based unfold-fold program transformation methods pose themselves diverse kinds of reachability tasks and try to solve them, aiming at improving the semantics tree of the program being transformed. That means some general-purpose verification methods may be used for strengthening program transformation techniques. This paper considers the question how finite countermodels for safety verification method might be used in Turchin's supercompilation method. We extract a number of supercompilation sub-algorithms trying to solve reachability problems and demonstrate use of an external countermodel finder for solving some of the problems.

A user's guide to the Flexible Spacecraft Dynamics and Control Program

Science.gov (United States)

Fedor, J. V.

1984-01-01

A guide to the use of the Flexible Spacecraft Dynamics Program (FSD) is presented covering input requirements, control words, orbit generation, spacecraft description and simulation options, and output definition. The program can be used in dynamics and control analysis as well as in orbit support of deployment and control of spacecraft. The program is applicable to inertially oriented spinning, Earth oriented or gravity gradient stabilized spacecraft. Internal and external environmental effects can be simulated.

Accurate Natural Trail Detection Using a Combination of a Deep Neural Network and Dynamic Programming.

Science.gov (United States)

Adhikari, Shyam Prasad; Yang, Changju; Slot, Krzysztof; Kim, Hyongsuk

2018-01-10

This paper presents a vision sensor-based solution to the challenging problem of detecting and following trails in highly unstructured natural environments like forests, rural areas and mountains, using a combination of a deep neural network and dynamic programming. The deep neural network (DNN) concept has recently emerged as a very effective tool for processing vision sensor signals. A patch-based DNN is trained with supervised data to classify fixed-size image patches into "trail" and "non-trail" categories, and reshaped to a fully convolutional architecture to produce trail segmentation map for arbitrary-sized input images. As trail and non-trail patches do not exhibit clearly defined shapes or forms, the patch-based classifier is prone to misclassification, and produces sub-optimal trail segmentation maps. Dynamic programming is introduced to find an optimal trail on the sub-optimal DNN output map. Experimental results showing accurate trail detection for real-world trail datasets captured with a head mounted vision system are presented.

Modeling Dynamic Systems with Efficient Ensembles of Process-Based Models.

Directory of Open Access Journals (Sweden)

Nikola Simidjievski

Full Text Available Ensembles are a well established machine learning paradigm, leading to accurate and robust models, predominantly applied to predictive modeling tasks. Ensemble models comprise a finite set of diverse predictive models whose combined output is expected to yield an improved predictive performance as compared to an individual model. In this paper, we propose a new method for learning ensembles of process-based models of dynamic systems. The process-based modeling paradigm employs domain-specific knowledge to automatically learn models of dynamic systems from time-series observational data. Previous work has shown that ensembles based on sampling observational data (i.e., bagging and boosting, significantly improve predictive performance of process-based models. However, this improvement comes at the cost of a substantial increase of the computational time needed for learning. To address this problem, the paper proposes a method that aims at efficiently learning ensembles of process-based models, while maintaining their accurate long-term predictive performance. This is achieved by constructing ensembles with sampling domain-specific knowledge instead of sampling data. We apply the proposed method to and evaluate its performance on a set of problems of automated predictive modeling in three lake ecosystems using a library of process-based knowledge for modeling population dynamics. The experimental results identify the optimal design decisions regarding the learning algorithm. The results also show that the proposed ensembles yield significantly more accurate predictions of population dynamics as compared to individual process-based models. Finally, while their predictive performance is comparable to the one of ensembles obtained with the state-of-the-art methods of bagging and boosting, they are substantially more efficient.

Quantum molecular dynamics: Numerical methods and physical study of the structure, thermodynamics, stability and fragmentation of sodium metallic clusters

International Nuclear Information System (INIS)

Blaise, Philippe

1998-01-01

The aim of this thesis is to study metallic sodium clusters by numerical simulation. We have developed two ab initio molecular dynamics programs within the formalism of density functional theory. The first is based on the semi-classical extended Thomas-Fermi approach. We use a real-space grid and a Car-Parrinello-like scheme. The computational cost is O(N), and we have built a pseudopotential that speeds up the calculations. By neglecting quantum shell effects, we are able to study a very large set of clusters. We show that sodium cluster energies fit well a liquid drop formula, by adjusting a few parameters. We have investigated breathing modes, surface oscillations and the net charge density. We have shown that the surface energy varies strongly with temperature, and that clusters have a lower melting point than bulk material. We have calculated fission barriers by a constraint method. The second program is based on the quantum Kohn-Sham approach. We use a real-space grid, and combine a generalized Broyden scheme for assuring self-consistency with an iterative Davidson-Lanczos algorithm for solving the Eigen-problem. The cost of the method is much higher. First of all, we have calculated some stable structures for small clusters and their energetics. We obtained very good agreement with previous works. Then, we have investigated highly charged cluster dynamics. We have identified a chaotic fission process. For high fissility systems, we observe a multi-fragmentation dynamics and we find preferential emission of monomers on a characteristic time scale less than a pico-second. This has been simulated for the first time, with the help of our adaptive grid method which follows each fragment as they move apart during the fragmentation. (author)

Fast and Cache-Oblivious Dynamic Programming with Local Dependencies

DEFF Research Database (Denmark)

Bille, Philip; Stöckel, Morten

2012-01-01

are widely used in bioinformatics to compare DNA and protein sequences. These problems can all be solved using essentially the same dynamic programming scheme over a two-dimensional matrix, where each entry depends locally on at most 3 neighboring entries. We present a simple, fast, and cache......-oblivious algorithm for this type of local dynamic programming suitable for comparing large-scale strings. Our algorithm outperforms the previous state-of-the-art solutions. Surprisingly, our new simple algorithm is competitive with a complicated, optimized, and tuned implementation of the best cache-aware algorithm...

Ant colony optimization and event-based dynamic task scheduling and staffing for software projects

Science.gov (United States)

Ellappan, Vijayan; Ashwini, J.

2017-11-01

In programming change organizations from medium to inconceivable scale broadens, the issue of wander orchestrating is amazingly unusual and testing undertaking despite considering it a manual system. Programming wander-organizing requirements to deal with the issue of undertaking arranging and in addition the issue of human resource portion (also called staffing) in light of the way that most of the advantages in programming ventures are individuals. We propose a machine learning approach with finds respond in due order regarding booking by taking in the present arranging courses of action and an event based scheduler revives the endeavour arranging system moulded by the learning computation in perspective of the conformity in event like the begin with the Ander, the instant at what time possessions be free starting to ended errands, and the time when delegates stick together otherwise depart the wander inside the item change plan. The route toward invigorating the timetable structure by the even based scheduler makes the arranging method dynamic. It uses structure components to exhibit the interrelated surges of endeavours, slip-ups and singular all through different progression organizes and is adjusted to mechanical data. It increases past programming wander movement ask about by taking a gander at a survey based process with a one of a kind model, organizing it with the data based system for peril assessment and cost estimation, and using a choice showing stage.

Computer Vision Based Measurement of Wildfire Smoke Dynamics

Directory of Open Access Journals (Sweden)

BUGARIC, M.

2015-02-01

Full Text Available This article presents a novel method for measurement of wildfire smoke dynamics based on computer vision and augmented reality techniques. The aspect of smoke dynamics is an important feature in video smoke detection that could distinguish smoke from visually similar phenomena. However, most of the existing smoke detection systems are not capable of measuring the real-world size of the detected smoke regions. Using computer vision and GIS-based augmented reality, we measure the real dimensions of smoke plumes, and observe the change in size over time. The measurements are performed on offline video data with known camera parameters and location. The observed data is analyzed in order to create a classifier that could be used to eliminate certain categories of false alarms induced by phenomena with different dynamics than smoke. We carried out an offline evaluation where we measured the improvement in the detection process achieved using the proposed smoke dynamics characteristics. The results show a significant increase in algorithm performance, especially in terms of reducing false alarms rate. From this it follows that the proposed method for measurement of smoke dynamics could be used to improve existing smoke detection algorithms, or taken into account when designing new ones.

The Effect of Water Exercise Program on Static and Dynamic Balance in Elderly Women

Directory of Open Access Journals (Sweden)

Heydar Sadeghi

2008-01-01

Full Text Available Objectives: Poor balance is one of risk factors of falling, a cause of injury and even death in elderly. The aim of this study was to evaluate the effect of a water exercise program on static and dynamic balance in elder women. Methods & Materials: Thirty participants aged 55-70 years completed an exercise program (60 min, 3 days and 6 weeks, in 2 groups, exercise and control, voluntarily. Static and dynamic balances were measured before and after exercise program in both groups. Postural sway parameters, including mean displacement of center of pressure and velocity of center of pressure in Medio-Lateral (ML and Anterio-Posterior (AP directions, in single stance position, as a measure of static balance and functional reach test, functional reach right test and functional reach left test, as dynamic measure of balance was considered. T test for deepened groups was used for evaluation of changes within groups, and T test for independent groups was used for between groups' changes at threshold of 0.05 After 6 weeks. Results: Significant changes were observed in results of Functional Reach Test (FRT, Functional Reach Left Test (FRLT after exercise program, also in average displacement of cop and velocity of cop in ML direction. Between groups significant differences were observed in results of average cop displacement and velocity of displacement, FRT and FRLT. Conclusion: These results suggest that challenging the physiological systems involved in balance control, in water, while on the non stable support surface, improved both static and dynamic balance and probably might decrease the risk of falling.

Optimization of environmental management strategies through a dynamic stochastic possibilistic multiobjective program.

Science.gov (United States)

Zhang, Xiaodong; Huang, Gordon

2013-02-15

Greenhouse gas (GHG) emissions from municipal solid waste (MSW) management facilities have become a serious environmental issue. In MSW management, not only economic objectives but also environmental objectives should be considered simultaneously. In this study, a dynamic stochastic possibilistic multiobjective programming (DSPMP) model is developed for supporting MSW management and associated GHG emission control. The DSPMP model improves upon the existing waste management optimization methods through incorporation of fuzzy possibilistic programming and chance-constrained programming into a general mixed-integer multiobjective linear programming (MOP) framework where various uncertainties expressed as fuzzy possibility distributions and probability distributions can be effectively reflected. Two conflicting objectives are integrally considered, including minimization of total system cost and minimization of total GHG emissions from waste management facilities. Three planning scenarios are analyzed and compared, representing different preferences of the decision makers for economic development and environmental-impact (i.e. GHG-emission) issues in integrated MSW management. Optimal decision schemes under three scenarios and different p(i) levels (representing the probability that the constraints would be violated) are generated for planning waste flow allocation and facility capacity expansions as well as GHG emission control. The results indicate that economic and environmental tradeoffs can be effectively reflected through the proposed DSPMP model. The generated decision variables can help the decision makers justify and/or adjust their waste management strategies based on their implicit knowledge and preferences. Copyright © 2012 Elsevier B.V. All rights reserved.

A Dynamic Resource Scheduling Method Based on Fuzzy Control Theory in Cloud Environment

Directory of Open Access Journals (Sweden)

Zhijia Chen

2015-01-01

Full Text Available The resources in cloud environment have features such as large-scale, diversity, and heterogeneity. Moreover, the user requirements for cloud computing resources are commonly characterized by uncertainty and imprecision. Hereby, to improve the quality of cloud computing service, not merely should the traditional standards such as cost and bandwidth be satisfied, but also particular emphasis should be laid on some extended standards such as system friendliness. This paper proposes a dynamic resource scheduling method based on fuzzy control theory. Firstly, the resource requirements prediction model is established. Then the relationships between resource availability and the resource requirements are concluded. Afterwards fuzzy control theory is adopted to realize a friendly match between user needs and resources availability. Results show that this approach improves the resources scheduling efficiency and the quality of service (QoS of cloud computing.

The Dynamic Geometrisation of Computer Programming

Science.gov (United States)

Sinclair, Nathalie; Patterson, Margaret

2018-01-01

The goal of this paper is to explore dynamic geometry environments (DGE) as a type of computer programming language. Using projects created by secondary students in one particular DGE, we analyse the extent to which the various aspects of computational thinking--including both ways of doing things and particular concepts--were evident in their…

Computer Program for Analysis, Design and Optimization of Propulsion, Dynamics, and Kinematics of Multistage Rockets

Science.gov (United States)

Lali, Mehdi

2009-03-01

A comprehensive computer program is designed in MATLAB to analyze, design and optimize the propulsion, dynamics, thermodynamics, and kinematics of any serial multi-staging rocket for a set of given data. The program is quite user-friendly. It comprises two main sections: "analysis and design" and "optimization." Each section has a GUI (Graphical User Interface) in which the rocket's data are entered by the user and by which the program is run. The first section analyzes the performance of the rocket that is previously devised by the user. Numerous plots and subplots are provided to display the performance of the rocket. The second section of the program finds the "optimum trajectory" via billions of iterations and computations which are done through sophisticated algorithms using numerical methods and incremental integrations. Innovative techniques are applied to calculate the optimal parameters for the engine and designing the "optimal pitch program." This computer program is stand-alone in such a way that it calculates almost every design parameter in regards to rocket propulsion and dynamics. It is meant to be used for actual launch operations as well as educational and research purposes.

An Improved Dynamic Programming Decomposition Approach for Network Revenue Management

OpenAIRE

Dan Zhang

2011-01-01

We consider a nonlinear nonseparable functional approximation to the value function of a dynamic programming formulation for the network revenue management (RM) problem with customer choice. We propose a simultaneous dynamic programming approach to solve the resulting problem, which is a nonlinear optimization problem with nonlinear constraints. We show that our approximation leads to a tighter upper bound on optimal expected revenue than some known bounds in the literature. Our approach can ...

Investigation on thermo-acoustic instability dynamic characteristics of hydrocarbon fuel flowing in scramjet cooling channel based on wavelet entropy method

Science.gov (United States)

Zan, Hao; Li, Haowei; Jiang, Yuguang; Wu, Meng; Zhou, Weixing; Bao, Wen

2018-06-01

As part of our efforts to find ways and means to further improve the regenerative cooling technology in scramjet, the experiments of thermo-acoustic instability dynamic characteristics of hydrocarbon fuel flowing have been conducted in horizontal circular tubes at different conditions. The experimental results indicate that there is a developing process from thermo-acoustic stability to instability. In order to have a deep understanding on the developing process of thermo-acoustic instability, the method of Multi-scale Shannon Wavelet Entropy (MSWE) based on Wavelet Transform Correlation Filter (WTCF) and Multi-Scale Shannon Entropy (MSE) is adopted in this paper. The results demonstrate that the developing process of thermo-acoustic instability from noise and weak signals is well detected by MSWE method and the differences among the stability, the developing process and the instability can be identified. These properties render the method particularly powerful for warning thermo-acoustic instability of hydrocarbon fuel flowing in scramjet cooling channels. The mass flow rate and the inlet pressure will make an influence on the developing process of the thermo-acoustic instability. The investigation on thermo-acoustic instability dynamic characteristics at supercritical pressure based on wavelet entropy method offers guidance on the control of scramjet fuel supply, which can secure stable fuel flowing in regenerative cooling system.

A Dynamic Programming Approach for Pricing Weather Derivatives under Issuer Default Risk

Directory of Open Access Journals (Sweden)

Wolfgang Karl Härdle

2017-10-01

Full Text Available Weather derivatives are contingent claims with payoff based on a pre-specified weather index. Firms exposed to weather risk can transfer it to financial markets via weather derivatives. We develop a utility-based model for pricing baskets of weather derivatives under default risk on the issuer side in over-the-counter markets. In our model, agents maximise the expected utility of their terminal wealth, while they dynamically rebalance their weather portfolios over a finite investment horizon. Using dynamic programming approach, we obtain semi-closed forms for the equilibrium prices of weather derivatives and for the optimal strategies of the agents. We give an example on how to price rainfall derivatives on selected stations in China in the universe of a financial investor and a weather exposed crop insurer.

Wigner method dynamics in the interaction picture

DEFF Research Database (Denmark)

Møller, Klaus Braagaard; Dahl, Jens Peder; Henriksen, Niels Engholm

1994-01-01

that the dynamics of the interaction picture Wigner function is solved by running a swarm of trajectories in the classical interaction picture introduced previously in the literature. Solving the Wigner method dynamics of collision processes in the interaction picture ensures that the calculated transition......The possibility of introducing an interaction picture in the semiclassical Wigner method is investigated. This is done with an interaction Picture description of the density operator dynamics as starting point. We show that the dynamics of the density operator dynamics as starting point. We show...... probabilities are unambiguous even when the asymptotic potentials are anharmonic. An application of the interaction picture Wigner method to a Morse oscillator interacting with a laser field is presented. The calculated transition probabilities are in good agreement with results obtained by a numerical...

Evaluation of a Secure Laptop-Based Testing Program in an Undergraduate Nursing Program: Students' Perspective.

Science.gov (United States)

Tao, Jinyuan; Gunter, Glenda; Tsai, Ming-Hsiu; Lim, Dan

2016-01-01

Recently, the many robust learning management systems, and the availability of affordable laptops, have made secure laptop-based testing a reality on many campuses. The undergraduate nursing program at the authors' university began to implement a secure laptop-based testing program in 2009, which allowed students to use their newly purchased laptops to take quizzes and tests securely in classrooms. After nearly 5 years' secure laptop-based testing program implementation, a formative evaluation, using a mixed method that has both descriptive and correlational data elements, was conducted to seek constructive feedback from students to improve the program. Evaluation data show that, overall, students (n = 166) believed the secure laptop-based testing program helps them get hands-on experience of taking examinations on the computer and gets them prepared for their computerized NCLEX-RN. Students, however, had a lot of concerns about laptop glitches and campus wireless network glitches they experienced during testing. At the same time, NCLEX-RN first-time passing rate data were analyzed using the χ2 test, and revealed no significant association between the two testing methods (paper-and-pencil testing and the secure laptop-based testing) and students' first-time NCLEX-RN passing rate. Based on the odds ratio, however, the odds of students passing NCLEX-RN the first time was 1.37 times higher if they were taught with the secure laptop-based testing method than if taught with the traditional paper-and-pencil testing method in nursing school. It was recommended to the institution that better quality of laptops needs to be provided to future students, measures needed to be taken to further stabilize the campus wireless Internet network, and there was a need to reevaluate the Laptop Initiative Program.

Inference of time-delayed gene regulatory networks based on dynamic Bayesian network hybrid learning method.

Science.gov (United States)

Yu, Bin; Xu, Jia-Meng; Li, Shan; Chen, Cheng; Chen, Rui-Xin; Wang, Lei; Zhang, Yan; Wang, Ming-Hui

2017-10-06

Gene regulatory networks (GRNs) research reveals complex life phenomena from the perspective of gene interaction, which is an important research field in systems biology. Traditional Bayesian networks have a high computational complexity, and the network structure scoring model has a single feature. Information-based approaches cannot identify the direction of regulation. In order to make up for the shortcomings of the above methods, this paper presents a novel hybrid learning method (DBNCS) based on dynamic Bayesian network (DBN) to construct the multiple time-delayed GRNs for the first time, combining the comprehensive score (CS) with the DBN model. DBNCS algorithm first uses CMI2NI (conditional mutual inclusive information-based network inference) algorithm for network structure profiles learning, namely the construction of search space. Then the redundant regulations are removed by using the recursive optimization algorithm (RO), thereby reduce the false positive rate. Secondly, the network structure profiles are decomposed into a set of cliques without loss, which can significantly reduce the computational complexity. Finally, DBN model is used to identify the direction of gene regulation within the cliques and search for the optimal network structure. The performance of DBNCS algorithm is evaluated by the benchmark GRN datasets from DREAM challenge as well as the SOS DNA repair network in Escherichia coli , and compared with other state-of-the-art methods. The experimental results show the rationality of the algorithm design and the outstanding performance of the GRNs.

Theoretical studies of combustion dynamics

Energy Technology Data Exchange (ETDEWEB)

Bowman, J.M. [Emory Univ., Atlanta, GA (United States)

1993-12-01

The basic objectives of this research program are to develop and apply theoretical techniques to fundamental dynamical processes of importance in gas-phase combustion. There are two major areas currently supported by this grant. One is reactive scattering of diatom-diatom systems, and the other is the dynamics of complex formation and decay based on L{sup 2} methods. In all of these studies, the authors focus on systems that are of interest experimentally, and for which potential energy surfaces based, at least in part, on ab initio calculations are available.

Approximate dynamic programming solving the curses of dimensionality

CERN Document Server

Powell, Warren B

2007-01-01

Warren B. Powell, PhD, is Professor of Operations Research and Financial Engineering at Princeton University, where he is founder and Director of CASTLE Laboratory, a research unit that works with industrial partners to test new ideas found in operations research. The recipient of the 2004 INFORMS Fellow Award, Dr. Powell has authored over 100 refereed publications on stochastic optimization, approximate dynamic programming, and dynamic resource management.

Next Generation Extended Lagrangian Quantum-based Molecular Dynamics

Science.gov (United States)

Negre, Christian

2017-06-01

A new framework for extended Lagrangian first-principles molecular dynamics simulations is presented, which overcomes shortcomings of regular, direct Born-Oppenheimer molecular dynamics, while maintaining important advantages of the unified extended Lagrangian formulation of density functional theory pioneered by Car and Parrinello three decades ago. The new framework allows, for the first time, energy conserving, linear-scaling Born-Oppenheimer molecular dynamics simulations, which is necessary to study larger and more realistic systems over longer simulation times than previously possible. Expensive, self-consinstent-field optimizations are avoided and normal integration time steps of regular, direct Born-Oppenheimer molecular dynamics can be used. Linear scaling electronic structure theory is presented using a graph-based approach that is ideal for parallel calculations on hybrid computer platforms. For the first time, quantum based Born-Oppenheimer molecular dynamics simulation is becoming a practically feasible approach in simulations of +100,000 atoms-representing a competitive alternative to classical polarizable force field methods. In collaboration with: Anders Niklasson, Los Alamos National Laboratory.

Dynamic Chest Image Analysis: Model-Based Perfusion Analysis in Dynamic Pulmonary Imaging

Directory of Open Access Journals (Sweden)

Kiuru Aaro

2003-01-01

Full Text Available The "Dynamic Chest Image Analysis" project aims to develop model-based computer analysis and visualization methods for showing focal and general abnormalities of lung ventilation and perfusion based on a sequence of digital chest fluoroscopy frames collected with the dynamic pulmonary imaging technique. We have proposed and evaluated a multiresolutional method with an explicit ventilation model for ventilation analysis. This paper presents a new model-based method for pulmonary perfusion analysis. According to perfusion properties, we first devise a novel mathematical function to form a perfusion model. A simple yet accurate approach is further introduced to extract cardiac systolic and diastolic phases from the heart, so that this cardiac information may be utilized to accelerate the perfusion analysis and improve its sensitivity in detecting pulmonary perfusion abnormalities. This makes perfusion analysis not only fast but also robust in computation; consequently, perfusion analysis becomes computationally feasible without using contrast media. Our clinical case studies with 52 patients show that this technique is effective for pulmonary embolism even without using contrast media, demonstrating consistent correlations with computed tomography (CT and nuclear medicine (NM studies. This fluoroscopical examination takes only about 2 seconds for perfusion study with only low radiation dose to patient, involving no preparation, no radioactive isotopes, and no contrast media.

Proving deadlock freedom of logic programs with dynamic scheduling

NARCIS (Netherlands)

E. Marchiori; F. Teusink (Frank)

1996-01-01

textabstractIn increasingly many logic programming systems, the Prolog left to right selection rule has been replaced with dynamic selection rules, that select an atom of a query among those satisfying suitable conditions. These conditions describe the form of the arguments of every program

An Efficient Mesh Generation Method for Fractured Network System Based on Dynamic Grid Deformation

Directory of Open Access Journals (Sweden)

Shuli Sun

2013-01-01

Full Text Available Meshing quality of the discrete model influences the accuracy, convergence, and efficiency of the solution for fractured network system in geological problem. However, modeling and meshing of such a fractured network system are usually tedious and difficult due to geometric complexity of the computational domain induced by existence and extension of fractures. The traditional meshing method to deal with fractures usually involves boundary recovery operation based on topological transformation, which relies on many complicated techniques and skills. This paper presents an alternative and efficient approach for meshing fractured network system. The method firstly presets points on fractures and then performs Delaunay triangulation to obtain preliminary mesh by point-by-point centroid insertion algorithm. Then the fractures are exactly recovered by local correction with revised dynamic grid deformation approach. Smoothing algorithm is finally applied to improve the quality of mesh. The proposed approach is efficient, easy to implement, and applicable to the cases of initial existing fractures and extension of fractures. The method is successfully applied to modeling of two- and three-dimensional discrete fractured network (DFN system in geological problems to demonstrate its effectiveness and high efficiency.

Shack-Hartmann centroid detection method based on high dynamic range imaging and normalization techniques

International Nuclear Information System (INIS)

Vargas, Javier; Gonzalez-Fernandez, Luis; Quiroga, Juan Antonio; Belenguer, Tomas

2010-01-01

In the optical quality measuring process of an optical system, including diamond-turning components, the use of a laser light source can produce an undesirable speckle effect in a Shack-Hartmann (SH) CCD sensor. This speckle noise can deteriorate the precision and accuracy of the wavefront sensor measurement. Here we present a SH centroid detection method founded on computer-based techniques and capable of measurement in the presence of strong speckle noise. The method extends the dynamic range imaging capabilities of the SH sensor through the use of a set of different CCD integration times. The resultant extended range spot map is normalized to accurately obtain the spot centroids. The proposed method has been applied to measure the optical quality of the main optical system (MOS) of the mid-infrared instrument telescope smulator. The wavefront at the exit of this optical system is affected by speckle noise when it is illuminated by a laser source and by air turbulence because it has a long back focal length (3017 mm). Using the proposed technique, the MOS wavefront error was measured and satisfactory results were obtained.

Pyrochemical and Dry Processing Methods Program. A selected bibliography

Energy Technology Data Exchange (ETDEWEB)

McDuffie, H.F.; Smith, D.H.; Owen, P.T.

1979-03-01

This selected bibliography with abstracts was compiled to provide information support to the Pyrochemical and Dry Processing Methods (PDPM) Program sponsored by DOE and administered by the Argonne National Laboratory. Objectives of the PDPM Program are to evaluate nonaqueous methods of reprocessing spent fuel as a route to the development of proliferation-resistant and diversion-resistant methods for widespread use in the nuclear industry. Emphasis was placed on the literature indexed in the ERDA--DOE Energy Data Base (EDB). The bibliography includes indexes to authors, subject descriptors, EDB subject categories, and titles.

Pyrochemical and Dry Processing Methods Program. A selected bibliography

International Nuclear Information System (INIS)

McDuffie, H.F.; Smith, D.H.; Owen, P.T.

1979-03-01

This selected bibliography with abstracts was compiled to provide information support to the Pyrochemical and Dry Processing Methods (PDPM) Program sponsored by DOE and administered by the Argonne National Laboratory. Objectives of the PDPM Program are to evaluate nonaqueous methods of reprocessing spent fuel as a route to the development of proliferation-resistant and diversion-resistant methods for widespread use in the nuclear industry. Emphasis was placed on the literature indexed in the ERDA--DOE Energy Data Base (EDB). The bibliography includes indexes to authors, subject descriptors, EDB subject categories, and titles

Sandia Dynamic Materials Program Strategic Plan.

Energy Technology Data Exchange (ETDEWEB)

Flicker, Dawn Gustine [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Benage, John F. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Desjarlais, Michael P. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Knudson, Marcus D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Leifeste, Gordon T. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Lemke, Raymond W. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Mattsson, Thomas [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Wise, Jack L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-05-01

Materials in nuclear and conventional weapons can reach multi-megabar pressures and 1000s of degree temperatures on timescales ranging from microseconds to nanoseconds. Understanding the response of complex materials under these conditions is important for designing and assessing changes to nuclear weapons. In the next few decades, a major concern will be evaluating the behavior of aging materials and remanufactured components. The science to enable the program to underwrite decisions quickly and confidently on use, remanufacturing, and replacement of these materials will be critical to NNSA’s new Stockpile Responsiveness Program. Material response is also important for assessing the risks posed by adversaries or proliferants. Dynamic materials research, which refers to the use of high-speed experiments to produce extreme conditions in matter, is an important part of NNSA’s Stockpile Stewardship Program.

A modified precise integration method based on Magnus expansion for transient response analysis of time varying dynamical structure

International Nuclear Information System (INIS)

Yue, Cong; Ren, Xingmin; Yang, Yongfeng; Deng, Wangqun

2016-01-01

This paper provides a precise and efficacious methodology for manifesting forced vibration response with respect to the time-variant linear rotational structure subjected to unbalanced excitation. A modified algorithm based on time step precise integration method and Magnus expansion is developed for instantaneous dynamic problems. The iterative solution is achieved by the ideology of transition and dimensional increment matrix. Numerical examples on a typical accelerating rotation system considering gyroscopic moment and mass unbalance force comparatively demonstrate the validity, effectiveness and accuracy with Newmark-β method. It is shown that the proposed algorithm has high accuracy without loss efficiency.

Approximating high-dimensional dynamics by barycentric coordinates with linear programming

Energy Technology Data Exchange (ETDEWEB)

Hirata, Yoshito, E-mail: yoshito@sat.t.u-tokyo.ac.jp; Aihara, Kazuyuki; Suzuki, Hideyuki [Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505 (Japan); Department of Mathematical Informatics, The University of Tokyo, Bunkyo-ku, Tokyo 113-8656 (Japan); CREST, JST, 4-1-8 Honcho, Kawaguchi, Saitama 332-0012 (Japan); Shiro, Masanori [Department of Mathematical Informatics, The University of Tokyo, Bunkyo-ku, Tokyo 113-8656 (Japan); Mathematical Neuroinformatics Group, Advanced Industrial Science and Technology, Tsukuba, Ibaraki 305-8568 (Japan); Takahashi, Nozomu; Mas, Paloma [Center for Research in Agricultural Genomics (CRAG), Consorci CSIC-IRTA-UAB-UB, Barcelona 08193 (Spain)

2015-01-15

The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data.

Approximating high-dimensional dynamics by barycentric coordinates with linear programming.

Science.gov (United States)

Hirata, Yoshito; Shiro, Masanori; Takahashi, Nozomu; Aihara, Kazuyuki; Suzuki, Hideyuki; Mas, Paloma

2015-01-01

The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data.

Approximating high-dimensional dynamics by barycentric coordinates with linear programming

International Nuclear Information System (INIS)

Hirata, Yoshito; Aihara, Kazuyuki; Suzuki, Hideyuki; Shiro, Masanori; Takahashi, Nozomu; Mas, Paloma

2015-01-01

The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data

Non-Adiabatic Molecular Dynamics Methods for Materials Discovery

Energy Technology Data Exchange (ETDEWEB)

Furche, Filipp [Univ. of California, Irvine, CA (United States); Parker, Shane M. [Univ. of California, Irvine, CA (United States); Muuronen, Mikko J. [Univ. of California, Irvine, CA (United States); Roy, Saswata [Univ. of California, Irvine, CA (United States)

2017-04-04

The flow of radiative energy in light-driven materials such as photosensitizer dyes or photocatalysts is governed by non-adiabatic transitions between electronic states and cannot be described within the Born-Oppenheimer approximation commonly used in electronic structure theory. The non-adiabatic molecular dynamics (NAMD) methods based on Tully surface hopping and time-dependent density functional theory developed in this project have greatly extended the range of molecular materials that can be tackled by NAMD simulations. New algorithms to compute molecular excited state and response properties efficiently were developed. Fundamental limitations of common non-linear response methods were discovered and characterized. Methods for accurate computations of vibronic spectra of materials such as black absorbers were developed and applied. It was shown that open-shell TDDFT methods capture bond breaking in NAMD simulations, a longstanding challenge for single-reference molecular dynamics simulations. The methods developed in this project were applied to study the photodissociation of acetaldehyde and revealed that non-adiabatic effects are experimentally observable in fragment kinetic energy distributions. Finally, the project enabled the first detailed NAMD simulations of photocatalytic water oxidation by titania nanoclusters, uncovering the mechanism of this fundamentally important reaction for fuel generation and storage.

An efficient computational method for a stochastic dynamic lot-sizing problem under service-level constraints

NARCIS (Netherlands)

Tarim, S.A.; Ozen, U.; Dogru, M.K.; Rossi, R.

2011-01-01

We provide an efficient computational approach to solve the mixed integer programming (MIP) model developed by Tarim and Kingsman [8] for solving a stochastic lot-sizing problem with service level constraints under the static–dynamic uncertainty strategy. The effectiveness of the proposed method

A Modified SPH Method for Dynamic Failure Simulation of Heterogeneous Material

Directory of Open Access Journals (Sweden)

G. W. Ma

2014-01-01

Full Text Available A modified smoothed particle hydrodynamics (SPH method is applied to simulate the failure process of heterogeneous materials. An elastoplastic damage model based on an extension form of the unified twin shear strength (UTSS criterion is adopted. Polycrystalline modeling is introduced to generate the artificial microstructure of specimen for the dynamic simulation of Brazilian splitting test and uniaxial compression test. The strain rate effect on the predicted dynamic tensile and compressive strength is discussed. The final failure patterns and the dynamic strength increments demonstrate good agreements with experimental results. It is illustrated that the polycrystalline modeling approach combined with the SPH method is promising to simulate more complex failure process of heterogeneous materials.

Dynamic knock detection and quantification in a spark ignition engine by means of a pressure based method

International Nuclear Information System (INIS)

Galloni, Enzo

2012-01-01

Highlights: ► Experimental data have been analyzed by a pressure based method. ► Knock intensity level depends on a threshold varying with the engine operating point. ► A dynamic method is proposed to overcome the definition of a predetermined threshold. ► The knock intensity of each operating point is quantified by a dimensionless index. ► The knock limited spark advance can be detected by means of this index. - Abstract: In spark ignition engines, knock onset limits the maximum spark advance. An inaccurate identification of this limit penalises the fuel conversion efficiency. Thus it is very important to define a knock detection method able to assess the knock intensity of an engine operating point. Usually, in engine development, knock event is evaluated by analysing the in-cylinder pressure trace. Data are filtered and processed in order to obtain some indices correlated to the knock intensity, then the calculated value is compared to a predetermined threshold. The calibration of this threshold is complex and difficult; statistical approach should be used, but often empirical values are considered. In this paper a method that dynamically calculates the knock threshold necessary to determine the knock event is proposed. The purpose is to resolve cycle by cycle the knock intensity related to an individual engine cycle without setting a predetermined threshold. The method has been applied to an extensive set of experimental data relative to a gasoline spark-ignition engine. Results are correlated to those obtained considering a traditional method, where a statistical approach has been used to detect knock.

Action dependent heuristic dynamic programming based residential energy scheduling with home energy inter-exchange

International Nuclear Information System (INIS)

Xu, Yancai; Liu, Derong; Wei, Qinglai

2015-01-01

Highlights: • The algorithm is developed in the two-household energy management environment. • We develop the absent energy penalty cost for the first time. • The algorithm has ability to keep adapting in real-time operations. • Its application can lower total costs and achieve better load balancing. - Abstract: Residential energy scheduling is a hot topic nowadays in the background of energy saving and environmental protection worldwide. To achieve this objective, a new residential energy scheduling algorithm is developed for energy management, based on action dependent heuristic dynamic programming. The algorithm works under the circumstance of residential real-time pricing and two adjacent housing units with energy inter-exchange, which can reduce the overall cost and enhance renewable energy efficiency after long-term operation. It is designed to obtain the optimal control policy to manage the directions and amounts of electricity energy flux. The algorithm’s architecture is mainly constructed based on neural networks, denoting the learned characteristics in the linkage of layers. To get close to real situations, many constraints such as maximum charging/discharging power of batteries are taken into account. The absent energy penalty cost is developed for the first time as a part of the performance index function. When the environment changes, the residential energy scheduling algorithm gains new features and keeps adapting in real-time operations. Simulation results show that the developed algorithm is beneficial to energy conversation

Numerical methods in dynamic fracture mechanics

International Nuclear Information System (INIS)

Beskos, D.E.

1987-01-01

A review of numerical methods for the solution of dynamic problems of fracture mechanics is presented. Finite difference, finite element and boundary element methods as applied to linear elastic or viscoelastic and non-linear elastoplastic or elastoviscoplastic dynamic fracture mechanics problems are described and critically evaluated. Both cases of stationary cracks and rapidly propagating cracks of simple I, II, III or mixed modes are considered. Harmonically varying with time or general transient dynamic disturbances in the form of external loading or incident waves are taken into account. Determination of the dynamic stress intensity factor for stationary cracks or moving cracks with known velocity history as well as determination of the crack-tip propagation history for given dynamic fracture toughness versus crack velocity relation are described and illustrated by means of certain representative examples. Finally, a brief assessment of the present state of knowledge is made and research needs are identified

Comparison of different methods for the determination of dynamic characteristics of low velocity anemometers

DEFF Research Database (Denmark)

Melikov, Arsen Krikor; Popiolek, Z.

2004-01-01

Three methods for determining the dynamic characteristics of low velocity thermal anemometers were compared. They were: step-up velocity change and step-down velocity change methods and a method based on sinusoidal type velocity fluctuations. Two low velocity thermal anemometers with omnidirectio......Three methods for determining the dynamic characteristics of low velocity thermal anemometers were compared. They were: step-up velocity change and step-down velocity change methods and a method based on sinusoidal type velocity fluctuations. Two low velocity thermal anemometers...... with omnidirectional velocity sensors were tested. The results identify differences in frequency response of low velocity anemometers determined by the three methods. The time constant and the response time determined by the step-up velocity change method and the step-down velocity change method may be substantially...... different and insufficient for describing the frequency response of all low velocity thermal anemometers. Therefore the upper frequency, determined in tests with sinusoidal velocity fluctuations, is recommended to be used in indoor climate standards as a single parameter describing the dynamic...

A Dynamic Simulation Program for a Hydriodic Acid Concentration and Decomposition Process in the VHTR-SI Process

International Nuclear Information System (INIS)

Chang, Ji Woon; Shin, Young Joon; Lee, Tae Hoon; Lee, Ki Young; Kim, Yong Wan; Chang, Jong Hwa; Youn, Cheung

2011-01-01

The Sulfur-Iodine (SI) cycle which can produce hydrogen by using nuclear heat consists of a Bunsen reaction (Section 1), a sulfur acid concentration and decomposition (Section 2), and a hydriodic acid concentration and decomposition (Section 3). The heat required in the SI process can be supplied through an intermediate heat exchanger (IHX) by a Very High Temperature Gas Cooled Reactor (VHTR). The Korea Atomic Energy Research Institute-Dynamic Simulation Code (KAERI-DySCo) based on the Visual C++ is an integration application software that simulates the dynamic behavior of the SI process. KAERI-DySCo was prepared to solve dynamic problem of the seven chemical reactors which consist of Sections 2 and 3. Section 3 is the key part of the SI process, because the strong non-ideality and the partial immiscibility of the binary HI.H 2 O and the ternary HI.I 2 .H 2 O (HIX solution) mixture make it difficult to model and simulate the dynamic behavior of the system. Therefore, it is necessary to compose separately a dynamic simulation program for Section 3 in KAERI-DySCo optimization. In this paper, a simulation program to analyze the dynamic behavior of Section 3 is introduced using the prepared KAERI-DySCo, and results of dynamic simulation are represented by running the program

Java Programs for Using Newmark's Method and Simplified Decoupled Analysis to Model Slope Performance During Earthquakes

Science.gov (United States)

Jibson, Randall W.; Jibson, Matthew W.

2003-01-01

Landslides typically cause a large proportion of earthquake damage, and the ability to predict slope performance during earthquakes is important for many types of seismic-hazard analysis and for the design of engineered slopes. Newmark's method for modeling a landslide as a rigid-plastic block sliding on an inclined plane provides a useful method for predicting approximate landslide displacements. Newmark's method estimates the displacement of a potential landslide block as it is subjected to earthquake shaking from a specific strong-motion record (earthquake acceleration-time history). A modification of Newmark's method, decoupled analysis, allows modeling landslides that are not assumed to be rigid blocks. This open-file report is available on CD-ROM and contains Java programs intended to facilitate performing both rigorous and simplified Newmark sliding-block analysis and a simplified model of decoupled analysis. For rigorous analysis, 2160 strong-motion records from 29 earthquakes are included along with a search interface for selecting records based on a wide variety of record properties. Utilities are available that allow users to add their own records to the program and use them for conducting Newmark analyses. Also included is a document containing detailed information about how to use Newmark's method to model dynamic slope performance. This program will run on any platform that supports the Java Runtime Environment (JRE) version 1.3, including Windows, Mac OSX, Linux, Solaris, etc. A minimum of 64 MB of available RAM is needed, and the fully installed program requires 400 MB of disk space.

Topics in Semantics-based Program Manipulation

DEFF Research Database (Denmark)

Grobauer, Bernt

four articles in the field of semantics-based techniques for program manipulation: three articles are about partial evaluation, a method for program specialization; the fourth article treats an approach to automatic cost analysis. Partial evaluation optimizes programs by specializing them with respect...... article in this dissertation describes how the second Futamura projection can be achieved for type-directed partial evaluation (TDPE), a relatively recent approach to partial evaluation: We derive an ML implementation of the second Futamura projection for TDPE. Due to the differences between ‘traditional...... denotational semantics—allows us to relate various possible semantics to each other both conceptually and formally. We thus are able to explain goal-directed evaluation using an intuitive list-based semantics, while using a continuation semantics for semantics-based compilation through partial evaluation...

Characterizing Dynamic Walking Patterns and Detecting Falls with Wearable Sensors Using Gaussian Process Methods

Directory of Open Access Journals (Sweden)

Taehwan Kim

2017-05-01

Full Text Available By incorporating a growing number of sensors and adopting machine learning technologies, wearable devices have recently become a prominent health care application domain. Among the related research topics in this field, one of the most important issues is detecting falls while walking. Since such falls may lead to serious injuries, automatically and promptly detecting them during daily use of smartphones and/or smart watches is a particular need. In this paper, we investigate the use of Gaussian process (GP methods for characterizing dynamic walking patterns and detecting falls while walking with built-in wearable sensors in smartphones and/or smartwatches. For the task of characterizing dynamic walking patterns in a low-dimensional latent feature space, we propose a novel approach called auto-encoded Gaussian process dynamical model, in which we combine a GP-based state space modeling method with a nonlinear dimensionality reduction method in a unique manner. The Gaussian process methods are fit for this task because one of the most import strengths of the Gaussian process methods is its capability of handling uncertainty in the model parameters. Also for detecting falls while walking, we propose to recycle the latent samples generated in training the auto-encoded Gaussian process dynamical model for GP-based novelty detection, which can lead to an efficient and seamless solution to the detection task. Experimental results show that the combined use of these GP-based methods can yield promising results for characterizing dynamic walking patterns and detecting falls while walking with the wearable sensors.

Intensive Research Program on Advances in Nonsmooth Dynamics 2016

CERN Document Server

Jeffrey, Mike; Lázaro, J; Olm, Josep

2017-01-01

This volume contains extended abstracts outlining selected talks and other selected presentations given by participants throughout the "Intensive Research Program on Advances in Nonsmooth Dynamics 2016", held at the Centre de Recerca Matemàtica (CRM) in Barcelona from February 1st to April 29th, 2016. They include brief research articles reporting new results, descriptions of preliminary work or open problems, and outlines of prominent discussion sessions. The articles are all the result of direct collaborations initiated during the research program. The topic is the theory and applications of Nonsmooth Dynamics. This includes systems involving elements of: impacting, switching, on/off control, hybrid discrete-continuous dynamics, jumps in physical properties, and many others. Applications include: electronics, climate modeling, life sciences, mechanics, ecology, and more. Numerous new results are reported concerning the dimensionality and robustness of nonsmooth models, shadowing variables, numbers of limit...