Dynamic modeling and analysis of load sharing characteristics of wind turbine gearbox

Directory of Open Access Journals (Sweden)

Pengxing Yi

2015-03-01

Full Text Available A coupled dynamic model, which contains helical gears-shafts-bearings for a wind turbine gearbox transmission system, was built considering nonlinear factors of the time-varying mesh stiffness, the external varying load, and the dynamic transmission error at first. The model is confirmed to be right after comparing the theoretical data with the experimental load sharing values, and also it is found that the static load sharing is conservative to evaluate the non-equilibrium effect of a planetary gear system. Besides, the analyzing results of the influence of average error and amplitude error on the load sharing show that the load sharing could be decreased if the error goes up a little. Then, by means of treating the static tracing point as the dynamic initial values, we analyzed the initial position’s influence on the load sharing of transmission system to provide a theoretical basis of load sharing control. Furthermore, we explored the influence of high-speed shaft position angle on the load sharing and the dynamic load factor of gears fixed on the parallel shafts. The results provide useful theoretical guidelines for the design of parallel shaft gear system in the wind turbines.

Load Sharing Behavior of Star Gearing Reducer for Geared Turbofan Engine

Science.gov (United States)

Mo, Shuai; Zhang, Yidu; Wu, Qiong; Wang, Feiming; Matsumura, Shigeki; Houjoh, Haruo

2017-07-01

Load sharing behavior is very important for power-split gearing system, star gearing reducer as a new type and special transmission system can be used in many industry fields. However, there is few literature regarding the key multiple-split load sharing issue in main gearbox used in new type geared turbofan engine. Further mechanism analysis are made on load sharing behavior among star gears of star gearing reducer for geared turbofan engine. Comprehensive meshing error analysis are conducted on eccentricity error, gear thickness error, base pitch error, assembly error, and bearing error of star gearing reducer respectively. Floating meshing error resulting from meshing clearance variation caused by the simultaneous floating of sun gear and annular gear are taken into account. A refined mathematical model for load sharing coefficient calculation is established in consideration of different meshing stiffness and supporting stiffness for components. The regular curves of load sharing coefficient under the influence of interactions, single action and single variation of various component errors are obtained. The accurate sensitivity of load sharing coefficient toward different errors is mastered. The load sharing coefficient of star gearing reducer is 1.033 and the maximum meshing force in gear tooth is about 3010 N. This paper provides scientific theory evidences for optimal parameter design and proper tolerance distribution in advanced development and manufacturing process, so as to achieve optimal effects in economy and technology.

Price-Dynamics of Shares and Bohmian Mechanics: Deterministic or Stochastic Model?

Science.gov (United States)

Choustova, Olga

2007-02-01

We apply the mathematical formalism of Bohmian mechanics to describe dynamics of shares. The main distinguishing feature of the financial Bohmian model is the possibility to take into account market psychology by describing expectations of traders by the pilot wave. We also discuss some objections (coming from conventional financial mathematics of stochastic processes) against the deterministic Bohmian model. In particular, the objection that such a model contradicts to the efficient market hypothesis which is the cornerstone of the modern market ideology. Another objection is of pure mathematical nature: it is related to the quadratic variation of price trajectories. One possibility to reply to this critique is to consider the stochastic Bohm-Vigier model, instead of the deterministic one. We do this in the present note.

Vehicle-to-Grid Automatic Load Sharing with Driver Preference in Micro-Grids

Energy Technology Data Exchange (ETDEWEB)

Wang, Yubo; Nazaripouya, Hamidreza; Chu, Chi-Cheng; Gadh, Rajit; Pota, Hemanshu R.

2014-10-15

Integration of Electrical Vehicles (EVs) with power grid not only brings new challenges for load management, but also opportunities for distributed storage and generation. This paper comprehensively models and analyzes distributed Vehicle-to-Grid (V2G) for automatic load sharing with driver preference. In a micro-grid with limited communications, V2G EVs need to decide load sharing based on their own power and voltage profile. A droop based controller taking into account driver preference is proposed in this paper to address the distributed control of EVs. Simulations are designed for three fundamental V2G automatic load sharing scenarios that include all system dynamics of such applications. Simulation results demonstrate that active power sharing is achieved proportionally among V2G EVs with consideration of driver preference. In additional, the results also verify the system stability and reactive power sharing analysis in system modelling, which sheds light on large scale V2G automatic load sharing in more complicated cases.

Stochastic Optimization Model to STudy the Operational Impacts of High Wind Penetrations in Ireland

DEFF Research Database (Denmark)

Meibom, Peter; Barth, R.; Hasche, B.

2011-01-01

A stochastic mixed integer linear optimization scheduling model minimizing system operation costs and treating load and wind power production as stochastic inputs is presented. The schedules are updated in a rolling manner as more up-to-date information becomes available. This is a fundamental...... change relative to day-ahead unit commitment approaches. The need for reserves dependent on forecast horizon and share of wind power has been estimated with a statistical model combining load and wind power forecast errors with scenarios of forced outages. The model is used to study operational impacts...

Simulation of load-sharing in standalone distributed generation system

Science.gov (United States)

Ajewole, Titus O.; Craven, Robert P. M.; Kayode, Olakunle; Babalola, Olufisayo S.

2018-05-01

This paper presents a study on load-sharing among the component generating units of a multi-source electric microgrid that is operated as an autonomous ac supply-mode system. Emerging trend in power system development permits deployment of microgrids for standalone or stand-by applications, thereby requiring active- and reactive power sharing among the discrete generating units contained in hybrid-source microgrids. In this study, therefore, a laboratory-scale model of a microgrid energized with three renewable energy-based sources is employed as a simulation platform to investigate power sharing among the power-generating units. Each source is represented by a source emulator that captures the real operational characteristics of the mimicked generating unit and, with implementation of real-life weather data and load profiles on the model; the sharing of the load among the generating units is investigated. There is a proportionate generation of power by the three source emulators, with their frequencies perfectly synchronized at the point of common coupling as a result of balance flow of power among them. This hybrid topology of renewable energy-based microgrid could therefore be seamlessly adapted into national energy mix by the indigenous electric utility providers in Nigeria.

Load-Sharing Characteristics of Power-Split Transmission System Based on Deformation Compatibility and Loaded Tooth Contact Analysis

Directory of Open Access Journals (Sweden)

Hao Dong

2015-01-01

Full Text Available In order to implement the uniform load distribution of the power-split transmission system, a pseudostatic model is built. Based on the loaded tooth contact analysis (LTCA technique, the actual meshing process of each gear pair is simulated and the fitting curve of time-varying mesh stiffness is obtained. And then, the torsional angle deformation compatibility conditions are proposed according to the closed-loop characteristic of power flow, which will be combined with the torque equilibrium conditions and elastic support conditions to calculate the transfer torque of each gear pair. Finally, the load-sharing coefficient of the power-split transmission system is obtained, and the influences of the installation errors are analyzed. The results show that the above-mentioned installation errors comprehensively influence the load-sharing characteristics, and the reduction of only one error could not effectively achieve perfect load-sharing characteristics. Allowing for the spline clearance floating and constrained by the radial spacing ring, the influence of the floating pinion is analyzed. It shows that the floating pinion can improve the load-sharing characteristics. Through the comparison between the theoretical and related experimental data, the reasonability and feasibility of the above-proposed method and model are verified.

Heat Load Sharing in a Capillary Pumped Loop with Multiple Evaporators and Multiple Condensers

Science.gov (United States)

Ku, Jentung

2005-01-01

This paper describes the heat load sharing function among multiple parallel evaporators in a capillary pumped loop (CPL). In the normal mode of operation, the evaporators cool the instruments by absorbing the waste heat. When an instruments is turned off, the attached evaporator can keep it warm by receiving heat from other evaporators serving the operating instruments. This is referred to as heat load sharing. A theoretical basis of heat load sharing is given first. The fact that the wicks in the powered evaporators will develop capillary pressure to force the generated vapor to flow to cold locations where the pressure is lower leads to the conclusion that heat load sharing is an inherent function of a CPL with multiple evaporators. Heat load sharing has been verified with many CPLs in ground tests. Experimental results of the Capillary Pumped Loop 3 (CAPL 3) Flight Experiment are presented in this paper. Factors that affect the amount of heat being shared are discussed. Some constraints of heat load sharing are also addressed.

Self-organized dynamics in local load-sharing fiber bundle models.

Science.gov (United States)

Biswas, Soumyajyoti; Chakrabarti, Bikas K

2013-10-01

We study the dynamics of a local load-sharing fiber bundle model in two dimensions under an external load (which increases with time at a fixed slow rate) applied at a single point. Due to the local load-sharing nature, the redistributed load remains localized along the boundary of the broken patch. The system then goes to a self-organized state with a stationary average value of load per fiber along the (increasing) boundary of the broken patch (damaged region) and a scale-free distribution of avalanche sizes and other related quantities are observed. In particular, when the load redistribution is only among nearest surviving fiber(s), the numerical estimates of the exponent values are comparable with those of the Manna model. When the load redistribution is uniform along the patch boundary, the model shows a simple mean-field limit of this self-organizing critical behavior, for which we give analytical estimates of the saturation load per fiber values and avalanche size distribution exponent. These are in good agreement with numerical simulation results.

Sharing of nonlinear load in parallel-connected three-phase converters

DEFF Research Database (Denmark)

Borup, Uffe; Blaabjerg, Frede; Enjeti, Prasad N.

2001-01-01

compensation are connected in parallel. Without the new solution, they are normally not able to distinguish the harmonic currents that flow to the load and harmonic currents that circulate between the converters. Analysis and experimental results on two 90-kVA 400-Hz converters in parallel are presented......In this paper, a new control method is presented which enables equal sharing of linear and nonlinear loads in three-phase power converters connected in parallel, without communication between the converters. The paper focuses on solving the problem that arises when two converters with harmonic....... The results show that both linear and nonlinear loads can be shared equally by the proposed concept....

Stochastic Still Water Response Model

DEFF Research Database (Denmark)

Friis-Hansen, Peter; Ditlevsen, Ove Dalager

2002-01-01

In this study a stochastic field model for the still water loading is formulated where the statistics (mean value, standard deviation, and correlation) of the sectional forces are obtained by integration of the load field over the relevant part of the ship structure. The objective of the model is...... out that an important parameter of the stochastic cargo field model is the mean number of containers delivered by each customer.......In this study a stochastic field model for the still water loading is formulated where the statistics (mean value, standard deviation, and correlation) of the sectional forces are obtained by integration of the load field over the relevant part of the ship structure. The objective of the model...... is to establish the stochastic load field conditional on a given draft and trim of the vessel. The model contributes to a realistic modelling of the stochastic load processes to be used in a reliability evaluation of the ship hull. Emphasis is given to container vessels. The formulation of the model for obtaining...

Fatigue in Welded High-Strength Steel Plate Elements under Stochastic Loading

DEFF Research Database (Denmark)

Agerskov, Henning; Petersen, R.I.; Martinez, L. Lopez

1999-01-01

The present project is a part of an investigation on fatigue in offshore structures in high-strength steel. The fatigue life of plate elements with welded attachments is studied. The material used has a yield stress of ~ 810-840 MPa, and high weldability and toughness properties. Fatigue test...... series with constant amplitude loading and with various types of stochastic loading have been carried through on test specimens in high-strength steel, and - for a comparison - on test specimens in conventional offshore structural steel with a yield stress of ~ 400-410 MPa.A comparison between constant...... amplitude and variable amplitude fatigue test results shows shorter fatigue lives in variable amplitude loading than should be expected from the linear fatigue damage accumulation formula. Furthermore, in general longer fatigue lives were obtained for the test specimens in high-strength steel than those...

PROBABILISTIC FLOW DISTRIBUTION AS A REACTION TO THE STOCHASTICITY OF THE LOAD IN THE POWER SYSTEM

Directory of Open Access Journals (Sweden)

A. M. Hashimov

2016-01-01

Full Text Available For the analysis and control of power systems deterministic approaches that are implemented in the form of well-known methods and models of calculation of steady-state and transient modes are mostly use in current practice. With the use of these methods it is possible to obtain solutions only for fixed circuit parameters of the system scheme and assuming that active and reactive powers as well as generation in nodal points of the network remain the same. In reality the stochastic character of power consumption cause the casual fluctuations of voltages at the nodes and power flows in electric power lines of the power system. Such casual fluctuations of operation can be estimated with the use of probabilistic simulation of the power flows. In the article the results of research of the influence of depth of casual fluctuations of the load power of the system on the probability distribution of voltage at nodes as well as on the flows of active and reactive power in the lines are presented. Probabilistic modeling of flow under stochastic load change is performed for different levels of fluctuations and under loading of the mode of the system up to peak load power. Test study to quantify the effect of stochastic variability of loads on the probabilistic distribution parameters of the modes was carried out on behalf of the electrical network of the real power system. The results of the simulation of the probability flow distribution for these fluctuations of the load, represented in the form of discrete sample values of the active power obtained with the use of the analytical Monte-Carlo method, and real data measurements of their values in the network under examination were compared.

Lifetime fatigue reliability evaluation of short to medium span bridges under site-specific stochastic truck loading

OpenAIRE

Yan, Donghuang; Luo, Yuan; Yuan, Ming; Lu, Naiwei

2017-01-01

Bridges are vulnerable to the fatigue damage accumulation caused by traffic loading over the service period. A continuous growth in both the vehicle weight and the traffic volume may cause a safety hazard to existing bridges. This study presented a computational framework for probabilistic modeling of the fatigue damage accumulation of short to medium span bridges under actual traffic loading. Stochastic truck-load models were simulated based on site-specific weigh-in-motion measurements. A r...

Dynamic load-sharing characteristic analysis of face gear power-split gear system based on tooth contact characteristics

Science.gov (United States)

Dong, Hao; Hu, Yahui

2018-04-01

The bend-torsion coupling dynamics load-sharing model of the helicopter face gear split torque transmission system is established by using concentrated quality standard, to analyzing the dynamic load-sharing characteristic. The mathematical models include nonlinear support stiffness, time-varying meshing stiffness, damping, gear backlash. The results showed that the errors collectively influenced the load sharing characteristics, only reduce a certain error, it is never fully reached the perfect loading sharing characteristics. The system load-sharing performance can be improved through floating shaft support. The above-method will provide a theoretical basis and data support for its dynamic performance optimization design.

Estimating total maximum daily loads with the Stochastic Empirical Loading and Dilution Model

Science.gov (United States)

Granato, Gregory; Jones, Susan Cheung

2017-01-01

The Massachusetts Department of Transportation (DOT) and the Rhode Island DOT are assessing and addressing roadway contributions to total maximum daily loads (TMDLs). Example analyses for total nitrogen, total phosphorus, suspended sediment, and total zinc in highway runoff were done by the U.S. Geological Survey in cooperation with FHWA to simulate long-term annual loads for TMDL analyses with the stochastic empirical loading and dilution model known as SELDM. Concentration statistics from 19 highway runoff monitoring sites in Massachusetts were used with precipitation statistics from 11 long-term monitoring sites to simulate long-term pavement yields (loads per unit area). Highway sites were stratified by traffic volume or surrounding land use to calculate concentration statistics for rural roads, low-volume highways, high-volume highways, and ultraurban highways. The median of the event mean concentration statistics in each traffic volume category was used to simulate annual yields from pavement for a 29- or 30-year period. Long-term average yields for total nitrogen, phosphorus, and zinc from rural roads are lower than yields from the other categories, but yields of sediment are higher than for the low-volume highways. The average yields of the selected water quality constituents from high-volume highways are 1.35 to 2.52 times the associated yields from low-volume highways. The average yields of the selected constituents from ultraurban highways are 1.52 to 3.46 times the associated yields from high-volume highways. Example simulations indicate that both concentration reduction and flow reduction by structural best management practices are crucial for reducing runoff yields.

Optimal loading and protection of multi-state systems considering performance sharing mechanism

International Nuclear Information System (INIS)

Xiao, Hui; Shi, Daimin; Ding, Yi; Peng, Rui

2016-01-01

Engineering systems are designed to carry the load. The performance of the system largely depends on how much load it carries. On the other hand, the failure rate of the system is strongly affected by its load. Besides internal failures, such as fatigue and aging process, systems may also fail due to external impacts such as nature disasters and terrorism. In this paper, we integrate the effect of loading and protection of external impacts on multi-state systems with performance sharing mechanism. The objective of this research is to determine how to balance the load and protection on system elements. An availability evaluation algorithm of the proposed system is suggested and the corresponding optimization problem is solved utilizing genetic algorithms. - Highlights: • Performance sharing of multi-state systems is considered. • The effect of load on system elements is analyzed. • Joint optimization model of element loading and protection is formulated. • Genetic Algorithms are adapted to solve the reliability optimization problem.

Load sharing in tungsten fiber reinforced Kanthal composites

International Nuclear Information System (INIS)

Clausen, B.; Bourke, Mark A.M.; Brown, Donald W.; Ustuendag, E.

2006-01-01

The load sharing in three tungsten fiber reinforced Kanthal matrix composites (with fiber volume fractions of 10, 20 and 30%) have been determined using in situ neutron diffraction measurements. The expected iso-strain region was limited in the 20 and 30% composites due to thermal residual stresses. The experimental data have been used to validate the predictions of a unit-cell finite element model. The model was able to accurately predict the measured in situ loading data for all three composites using the same material properties for all calculations

Load sharing in tungsten fiber reinforced Kanthal composites

Energy Technology Data Exchange (ETDEWEB)

Clausen, B. [Los Alamos National Laboratory, LANSCE-12, P.O. Box 1663, MS H805, Los Alamos, NM 87545 (United States)]. E-mail: clausen@lanl.gov; Bourke, Mark A.M. [Los Alamos National Laboratory, MST-8, P.O. Box 1663, MS H805, Los Alamos, NM 87545 (United States); Brown, Donald W. [Los Alamos National Laboratory, MST-8, P.O. Box 1663, MS H805, Los Alamos, NM 87545 (United States); Ustuendag, E. [California Institute of Technology, Keck Laboratory, M/C 138-78, 1200 E. California Blvd., Pasadena, CA 91125 (United States)

2006-04-15

The load sharing in three tungsten fiber reinforced Kanthal matrix composites (with fiber volume fractions of 10, 20 and 30%) have been determined using in situ neutron diffraction measurements. The expected iso-strain region was limited in the 20 and 30% composites due to thermal residual stresses. The experimental data have been used to validate the predictions of a unit-cell finite element model. The model was able to accurately predict the measured in situ loading data for all three composites using the same material properties for all calculations.

Research on the parallel load sharing principle of a novel self-decoupled piezoelectric six-dimensional force sensor.

Science.gov (United States)

Li, Ying-Jun; Yang, Cong; Wang, Gui-Cong; Zhang, Hui; Cui, Huan-Yong; Zhang, Yong-Liang

2017-09-01

This paper presents a novel integrated piezoelectric six-dimensional force sensor which can realize dynamic measurement of multi-dimensional space load. Firstly, the composition of the sensor, the spatial layout of force-sensitive components, and measurement principle are analyzed and designed. There is no interference of piezoelectric six-dimensional force sensor in theoretical analysis. Based on the principle of actual work and deformation compatibility coherence, this paper deduces the parallel load sharing principle of the piezoelectric six-dimensional force sensor. The main effect factors which affect the load sharing ratio are obtained. The finite element model of the piezoelectric six-dimensional force sensor is established. In order to verify the load sharing principle of the sensor, a load sharing test device of piezoelectric force sensor is designed and fabricated. The load sharing experimental platform is set up. The experimental results are in accordance with the theoretical analysis and simulation results. The experiments show that the multi-dimensional and heavy force measurement can be realized by the parallel arrangement of the load sharing ring and the force sensitive element in the novel integrated piezoelectric six-dimensional force sensor. The ideal load sharing effect of the sensor can be achieved by appropriate size parameters. This paper has an important guide for the design of the force measuring device according to the load sharing mode. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

The interpolation method of stochastic functions and the stochastic variational principle

International Nuclear Information System (INIS)

Liu Xianbin; Chen Qiu

1993-01-01

Uncertainties have been attaching more importance to increasingly in modern engineering structural design. Viewed on an appropriate scale, the inherent physical attributes (material properties) of many structural systems always exhibit some patterns of random variation in space and time, generally the random variation shows a small parameter fluctuation. For a linear mechanical system, the random variation is modeled as a random one of a linear partial differential operator and, in stochastic finite element method, a random variation of a stiffness matrix. Besides the stochasticity of the structural physical properties, the influences of random loads which always represent themselves as the random boundary conditions bring about much more complexities in structural analysis. Now the stochastic finite element method or the probabilistic finite element method is used to study the structural systems with random physical parameters, whether or not the loads are random. Differing from the general finite element theory, the main difficulty which the stochastic finite element method faces is the inverse operation of stochastic operators and stochastic matrices, since the inverse operators and the inverse matrices are statistically correlated to the random parameters and random loads. So far, many efforts have been made to obtain the reasonably approximate expressions of the inverse operators and inverse matrices, such as Perturbation Method, Neumann Expansion Method, Galerkin Method (in appropriate Hilbert Spaces defined for random functions), Orthogonal Expansion Method. Among these methods, Perturbation Method appear to be the most available. The advantage of these methods is that the fairly accurate response statistics can be obtained under the condition of the finite information of the input. However, the second-order statistics obtained by use of Perturbation Method and Neumann Expansion Method are not always the appropriate ones, because the relevant second

A load-sharing control scheme for a microgrid with a fixed frequency inverter

Energy Technology Data Exchange (ETDEWEB)

Zhang, Zhihao; Huang, Xinhong; Jiang, Jin [Department of Electrical and Computer Engineering, The University of Western Ontario, 1151 Richmond St., London, Ontario (Canada); Wu, Bin [Department of Electrical and Computer Engineering, Ryerson University, Toronto, Ontario (Canada)

2010-03-15

In this paper, a load-sharing control strategy is developed for a microgrid consisting of a fuel cell power module and two synchronous generators in a stand-alone environment. The fuel cell is interfaced with the synchronous generators through a DC/AC inverter to convert unregulated DC to a three-phase AC. Since the frequency of the DC/AC inverter is fixed, the conventional load-frequency control scheme cannot be used for load-sharing control. To alleviate this problem, a load-voltage control scheme is developed. The theoretical analysis and experimental validation of the proposed scheme are presented. It is shown, by theoretical analysis and experiments, that this control strategy can effectively distribute the load among the different energy sources based on their individual pre-defined load-voltage droop characteristics. (author)

A stochastic framework for the grid integration of wind power using flexible load approach

International Nuclear Information System (INIS)

Heydarian-Forushani, E.; Moghaddam, M.P.; Sheikh-El-Eslami, M.K.; Shafie-khah, M.; Catalão, J.P.S.

2014-01-01

Highlights: • This paper focuses on the potential of Demand Response Programs (DRPs) to contribute to flexibility. • A stochastic network constrained unit commitment associated with DR is presented. • DR participation levels and electricity tariffs are evaluated on providing a flexible load profile. • Novel quantitative indices for evaluating flexibility are defined to assess the success of DRPs. • DR types and customer participation levels are the main factors to modify the system load profile. - Abstract: Wind power integration has always been a key research area due to the green future power system target. However, the intermittent nature of wind power may impose some technical and economic challenges to Independent System Operators (ISOs) and increase the need for additional flexibility. Motivated by this need, this paper focuses on the potential of Demand Response Programs (DRPs) as an option to contribute to the flexible operation of power systems. On this basis, in order to consider the uncertain nature of wind power and the reality of electricity market, a Stochastic Network Constrained Unit Commitment associated with DR (SNCUCDR) is presented to schedule both generation units and responsive loads in power systems with high penetration of wind power. Afterwards, the effects of both price-based and incentive-based DRPs are evaluated, as well as DR participation levels and electricity tariffs on providing a flexible load profile and facilitating grid integration of wind power. For this reason, novel quantitative indices for evaluating flexibility are defined to assess the success of DRPs in terms of wind integration. Sensitivity studies indicate that DR types and customer participation levels are the main factors to modify the system load profile to support wind power integration

Stochastic Optimization of Wind Turbine Power Factor Using Stochastic Model of Wind Power

DEFF Research Database (Denmark)

Chen, Peiyuan; Siano, Pierluigi; Bak-Jensen, Birgitte

2010-01-01

This paper proposes a stochastic optimization algorithm that aims to minimize the expectation of the system power losses by controlling wind turbine (WT) power factors. This objective of the optimization is subject to the probability constraints of bus voltage and line current requirements....... The optimization algorithm utilizes the stochastic models of wind power generation (WPG) and load demand to take into account their stochastic variation. The stochastic model of WPG is developed on the basis of a limited autoregressive integrated moving average (LARIMA) model by introducing a crosscorrelation...... structure to the LARIMA model. The proposed stochastic optimization is carried out on a 69-bus distribution system. Simulation results confirm that, under various combinations of WPG and load demand, the system power losses are considerably reduced with the optimal setting of WT power factor as compared...

Robust Topology Optimization Based on Stochastic Collocation Methods under Loading Uncertainties

Directory of Open Access Journals (Sweden)

Qinghai Zhao

2015-01-01

Full Text Available A robust topology optimization (RTO approach with consideration of loading uncertainties is developed in this paper. The stochastic collocation method combined with full tensor product grid and Smolyak sparse grid transforms the robust formulation into a weighted multiple loading deterministic problem at the collocation points. The proposed approach is amenable to implementation in existing commercial topology optimization software package and thus feasible to practical engineering problems. Numerical examples of two- and three-dimensional topology optimization problems are provided to demonstrate the proposed RTO approach and its applications. The optimal topologies obtained from deterministic and robust topology optimization designs under tensor product grid and sparse grid with different levels are compared with one another to investigate the pros and cons of optimization algorithm on final topologies, and an extensive Monte Carlo simulation is also performed to verify the proposed approach.

Controllable load sharing for soft adhesive interfaces on three-dimensional surfaces

Science.gov (United States)

Song, Sukho; Drotlef, Dirk-Michael; Majidi, Carmel; Sitti, Metin

2017-05-01

For adhering to three-dimensional (3D) surfaces or objects, current adhesion systems are limited by a fundamental trade-off between 3D surface conformability and high adhesion strength. This limitation arises from the need for a soft, mechanically compliant interface, which enables conformability to nonflat and irregularly shaped surfaces but significantly reduces the interfacial fracture strength. In this work, we overcome this trade-off with an adhesion-based soft-gripping system that exhibits enhanced fracture strength without sacrificing conformability to nonplanar 3D surfaces. Composed of a gecko-inspired elastomeric microfibrillar adhesive membrane supported by a pressure-controlled deformable gripper body, the proposed soft-gripping system controls the bonding strength by changing its internal pressure and exploiting the mechanics of interfacial equal load sharing. The soft adhesion system can use up to ˜26% of the maximum adhesion of the fibrillar membrane, which is 14× higher than the adhering membrane without load sharing. Our proposed load-sharing method suggests a paradigm for soft adhesion-based gripping and transfer-printing systems that achieves area scaling similar to that of a natural gecko footpad.

High-speed Stochastic Fatigue Testing

DEFF Research Database (Denmark)

Brincker, Rune; Sørensen, John Dalsgaard

1990-01-01

Good stochastic fatigue tests are difficult to perform. One of the major reasons is that ordinary servohydraulic loading systems realize the prescribed load history accurately at very low testing speeds only. If the speeds used for constant amplitude testing are applied to stochastic fatigue...

Microcogeneration in buildings with low energy demand in load sharing application

International Nuclear Information System (INIS)

Angrisani, Giovanni; Canelli, Michele; Roselli, Carlo; Sasso, Maurizio

2015-01-01

Highlights: • The use of microcogenerator (MCHP) in buildings with low energy demand is evaluated. • The load sharing approach leads to suitable thermal and electric loads for MCHP. • Dynamic simulations are carried out considering two different climates. • A sensitivity analysis with respect to the self-consumed electricity is performed. • MCHPs with internal combustion engine perfectly match with well-insulated buildings. - Abstract: The paper investigates the introduction of a MCHP (Micro Combined Heat and Power) system in buildings with low energy demand with respect to the current building stock. A load sharing approach between a multifamily residential building and an office one is taken into account. Dynamic simulations are carried out in order to evaluate the thermo-economic performance of the analyzed system. Particular attention is given to the estimation of the electric load of the different users, as the economic profitability of a MCHP system is strongly influenced by the amount of self-consumed electricity. In order to analyze the influence of climatic conditions, two different geographical locations in Italy (Naples and Turin, having 1034 and 2617 heating degree days, respectively) are considered. The results of this study indicate that the installation of MCHP systems in buildings with low energy demand allows to increase the percentage of self-consumed electricity reducing the bidirectional electricity flow between the users and the external grid, as well as the impact on the grid itself due to the large diffusion of distributed generation systems. Moreover this study shows that the load sharing approach between users with different load profile leads to better energy, environmental and economic results with respect to a conventional system. The climatic conditions play an important role on the MCHP operational hours and hence on the thermo-economic performance of the system. The primary energy saving of the system located in Turin is

Footbridge Response Predictions and Their Sensitivity to Stochastic Load Assumptions

DEFF Research Database (Denmark)

Pedersen, Lars; Frier, Christian

2011-01-01

Knowledge about footbridges response to actions of walking is important in assessments of vibration serviceability. In a number of design codes for footbridges, the vibration serviceability limit state is assessed using a walking load model in which the walking parameters (step frequency, pedestr......Knowledge about footbridges response to actions of walking is important in assessments of vibration serviceability. In a number of design codes for footbridges, the vibration serviceability limit state is assessed using a walking load model in which the walking parameters (step frequency...... of pedestrians for predicting footbridge response, which is meaningful, and a step forward. Modelling walking parameters stochastically, however, requires decisions to be made in terms of their statistical distribution and the parameters describing the statistical distribution. The paper investigates...... the sensitivity of results of computations of bridge response to some of the decisions to be made in this respect. This is a useful approach placing focus on which decisions (and which information) are important for sound estimation of bridge response. The studies involve estimating footbridge responses using...

Planetary Load Sharing in Three-Point Mounted Wind Turbine Gearboxes: A Design and Test Comparison

Energy Technology Data Exchange (ETDEWEB)

Keller, Jonathan [National Renewable Energy Lab. (NREL), Golden, CO (United States); Guo, Yi [National Renewable Energy Lab. (NREL), Golden, CO (United States); Zhang, Zhiwei [Romax InSight, Nottingham, (United Kingdom); Lucas, Doug [The Timken Company, Jackson Township, OH (United States)

2017-04-06

This work compares the planetary load-sharing characteristics of wind turbine gearboxes supported by cylindrical roller bearings (CRBs) and preloaded tapered roller bearings (TRBs) when subjected to rotor moments. Planetary bearing loads were measured in field-representative dynamometer tests and compared to loads predicted by finite-element models. Preloaded TRBs significantly improved load sharing. In pure torque conditions, the upwind planet bearing load in the gearbox with preloaded TRBs was only 14% more than the assumed load compared to 47% more for the gearbox with CRBs. Consequently, the predicted fatigue life of the complete set of planetary bearings for the gearbox with preloaded TRBs is 3.5 times greater than that of the gearbox with CRBs.

Effects of Peer-Tutor Competences on Learner Cognitive Load and Learning Performance during Knowledge Sharing

Science.gov (United States)

Hsiao, Ya-Ping; Brouns, Francis; van Bruggen, Jan; Sloep, Peter B.

2012-01-01

In Learning Networks, learners need to share knowledge with others to build knowledge. In particular, when working on complex tasks, they often need to acquire extra cognitive resources from others to process a high task load. However, without support high task load and organizing knowledge sharing themselves might easily overload learners'…

Reliability demonstration test for load-sharing systems with exponential and Weibull components.

Directory of Open Access Journals (Sweden)

Jianyu Xu

Full Text Available Conducting a Reliability Demonstration Test (RDT is a crucial step in production. Products are tested under certain schemes to demonstrate whether their reliability indices reach pre-specified thresholds. Test schemes for RDT have been studied in different situations, e.g., lifetime testing, degradation testing and accelerated testing. Systems designed with several structures are also investigated in many RDT plans. Despite the availability of a range of test plans for different systems, RDT planning for load-sharing systems hasn't yet received the attention it deserves. In this paper, we propose a demonstration method for two specific types of load-sharing systems with components subject to two distributions: exponential and Weibull. Based on the assumptions and interpretations made in several previous works on such load-sharing systems, we set the mean time to failure (MTTF of the total system as the demonstration target. We represent the MTTF as a summation of mean time between successive component failures. Next, we introduce generalized test statistics for both the underlying distributions. Finally, RDT plans for the two types of systems are established on the basis of these test statistics.

Stochastic rocket dynamics under random nozzle side loads: Ornstein-Uhlenbeck boundary layer separation and its coarse grained connection to side loading and rocket response

Energy Technology Data Exchange (ETDEWEB)

Keanini, R.G.; Srivastava, N.; Tkacik, P.T. [Department of Mechanical Engineering, University of North Carolina at Charlotte, 9201 University City Blvd., Charlotte, NC 28078 (United States); Weggel, D.C. [Department of Civil and Environmental Engineering, University of North Carolina at Charlotte, 9201 University City Blvd., Charlotte, NC 28078 (United States); Knight, P.D. [Mitchell Aerospace and Engineering, Statesville, North Carolina 28677 (United States)

2011-06-15

A long-standing, though ill-understood problem in rocket dynamics, rocket response to random, altitude-dependent nozzle side-loads, is investigated. Side loads arise during low altitude flight due to random, asymmetric, shock-induced separation of in-nozzle boundary layers. In this paper, stochastic evolution of the in-nozzle boundary layer separation line, an essential feature underlying side load generation, is connected to random, altitude-dependent rotational and translational rocket response via a set of simple analytical models. Separation line motion, extant on a fast boundary layer time scale, is modeled as an Ornstein-Uhlenbeck process. Pitch and yaw responses, taking place on a long, rocket dynamics time scale, are shown to likewise evolve as OU processes. Stochastic, altitude-dependent rocket translational motion follows from linear, asymptotic versions of the full nonlinear equations of motion; the model is valid in the practical limit where random pitch, yaw, and roll rates all remain small. Computed altitude-dependent rotational and translational velocity and displacement statistics are compared against those obtained using recently reported high fidelity simulations [Srivastava, Tkacik, and Keanini, J. Appl. Phys. 108, 044911 (2010)]; in every case, reasonable agreement is observed. As an important prelude, evidence indicating the physical consistency of the model introduced in the above article is first presented: it is shown that the study's separation line model allows direct derivation of experimentally observed side load amplitude and direction densities. Finally, it is found that the analytical models proposed in this paper allow straightforward identification of practical approaches for: (i) reducing pitch/yaw response to side loads, and (ii) enhancing pitch/yaw damping once side loads cease. (Copyright copyright 2011 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

Reliability Analysis of Load-Sharing K-out-of-N System Considering Component Degradation

Directory of Open Access Journals (Sweden)

Chunbo Yang

2015-01-01

Full Text Available The K-out-of-N configuration is a typical form of redundancy techniques to improve system reliability, where at least K-out-of-N components must work for successful operation of system. When the components are degraded, more components are needed to meet the system requirement, which means that the value of K has to increase. The current reliability analysis methods overestimate the reliability, because using constant K ignores the degradation effect. In a load-sharing system with degrading components, the workload shared on each surviving component will increase after a random component failure, resulting in higher failure rate and increased performance degradation rate. This paper proposes a method combining a tampered failure rate model with a performance degradation model to analyze the reliability of load-sharing K-out-of-N system with degrading components. The proposed method considers the value of K as a variable which is derived by the performance degradation model. Also, the load-sharing effect is evaluated by the tampered failure rate model. Monte-Carlo simulation procedure is used to estimate the discrete probability distribution of K. The case of a solar panel is studied in this paper, and the result shows that the reliability considering component degradation is less than that ignoring component degradation.

Stochastic differential equation (SDE) model of opening gold share price of bursa saham malaysia

Science.gov (United States)

Hussin, F. N.; Rahman, H. A.; Bahar, A.

2017-09-01

Black and Scholes option pricing model is one of the most recognized stochastic differential equation model in mathematical finance. Two parameter estimation methods have been utilized for the Geometric Brownian model (GBM); historical and discrete method. The historical method is a statistical method which uses the property of independence and normality logarithmic return, giving out the simplest parameter estimation. Meanwhile, discrete method considers the function of density of transition from the process of diffusion normal log which has been derived from maximum likelihood method. These two methods are used to find the parameter estimates samples of Malaysians Gold Share Price data such as: Financial Times and Stock Exchange (FTSE) Bursa Malaysia Emas, and Financial Times and Stock Exchange (FTSE) Bursa Malaysia Emas Shariah. Modelling of gold share price is essential since fluctuation of gold affects worldwide economy nowadays, including Malaysia. It is found that discrete method gives the best parameter estimates than historical method due to the smallest Root Mean Square Error (RMSE) value.

Proportional Load Sharing and Stability of DC Microgrid with Distributed Architecture Using SM Controller

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Muhammad Rashad

2018-01-01

Full Text Available DC microgrids look attractive in distribution systems due to their high reliability, high efficiency, and easy integration with renewable energy sources. The key objectives of the DC microgrid include proportional load sharing and precise voltage regulation. Droop controllers are based on decentralized control architectures which are not effective in achieving these objectives simultaneously due to the voltage error and load power variation. A centralized controller can achieve these objectives using a high speed communication link. However, it loses reliability due to the single point failure. Additionally, these controllers are realized through proportional integral (PI controllers which cannot ensure load sharing and stability in all operating conditions. To address limitations, a distributed architecture using sliding mode (SM controller utilizing low bandwidth communication is proposed for DC microgrids in this paper. The main advantages are high reliability, load power sharing, and precise voltage regulation. Further, the SM controller shows high robustness, fast dynamic response, and good stability for large load variations. To analyze the stability and dynamic performance, a system model is developed and its transversality, reachability, and equivalent control conditions are verified. Furthermore, the dynamic behavior of the modeled system is investigated for underdamped and critically damped responses. Detailed simulations are carried out to show the effectiveness of the proposed controller.

A GPS-Based Control Method for Load Sharing and Power Quality Improvement in Microgrids

DEFF Research Database (Denmark)

Golsorkhi, Mohammad; Lu, Dylan; Savaghebi, Mehdi

2016-01-01

This paper proposes a novel control method for accurate sharing of load current among the Distributed Energy Resources (DER) and high power quality operating in islanded ac microgrids. This control scheme is based on hierarchical structure comprising of decentralized primary controllers and a cen....... The secondary controller produces compensation signals at fundamental and dominant harmonics to improve the voltage quality at a sensitive load bus. Experimental results are presented to validate the efficacy of the proposed method.......This paper proposes a novel control method for accurate sharing of load current among the Distributed Energy Resources (DER) and high power quality operating in islanded ac microgrids. This control scheme is based on hierarchical structure comprising of decentralized primary controllers...

Planetary Load Sharing in Three-Point- Mounted Wind Turbine Gearboxes: Preprint

Energy Technology Data Exchange (ETDEWEB)

Guo, Yi [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Keller, Jonathan A [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-09-15

Wind turbine gearboxes do not achieve their expected design life. The cost of gearbox replacements and rebuilds and the downtime associated with these failures increase the cost of wind energy. In 2007, the U.S. Department of Energy established the National Renewable Energy Laboratory (NREL) Gearbox Reliability Collaborative (GRC). Its goals are to understand the root causes of premature gearbox failures and improve their reliability. To date, the GRC has focused on a 750-kW drivetrain with a three-stage, three-point-mounted gearbox. A nonproprietary version of the gearbox containing CRBs with C3 clearances in the planetary stage was customized. Two of these gearboxes, GB1 and GB2, were manufactured and then tested in the National Wind Technology Center's 2.5-MW dynamometer and in the field. Major GRC findings include the detrimental effect of rotor moments on planetary load sharing and predicted fatigue, and the risk of bearing sliding in low-torque conditions for three-point configuration drivetrains. Based on the knowledge gained from testing and analysis of the original design, the GRC gearbox was redesigned to improve its load-sharing characteristics and predicted fatigue. This new gearbox is named GB3. As shown in Figure 1, its key improvement is the incorporation of preloaded TRBs that support the planet carrier and planets. Roller loads can be optimized and bearing life maximized with a small preload [4]. These preloaded bearings, along with interference-fitted planet pins, improve alignments and load-sharing characteristics. A semi-integrated planet bearing design also increases capacity and eliminates outer race fretting. Romax Technology, with Powertrain Engineers and the Timken Company (Timken), completed the redesign. Timken manufactured and instrumented the planet gears and bearings. Brad Foote Gearing manufactured the other gearing and assembled the gearbox.

Time-dependent fiber bundles with local load sharing. II. General Weibull fibers.

Science.gov (United States)

Phoenix, S Leigh; Newman, William I

2009-12-01

Fiber bundle models (FBMs) are useful tools in understanding failure processes in a variety of material systems. While the fibers and load sharing assumptions are easily described, FBM analysis is typically difficult. Monte Carlo methods are also hampered by the severe computational demands of large bundle sizes, which overwhelm just as behavior relevant to real materials starts to emerge. For large size scales, interest continues in idealized FBMs that assume either equal load sharing (ELS) or local load sharing (LLS) among fibers, rules that reflect features of real load redistribution in elastic lattices. The present work focuses on a one-dimensional bundle of N fibers under LLS where life consumption in a fiber follows a power law in its load, with exponent rho , and integrated over time. This life consumption function is further embodied in a functional form resulting in a Weibull distribution for lifetime under constant fiber stress and with Weibull exponent, beta. Thus the failure rate of a fiber depends on its past load history, except for beta=1 . We develop asymptotic results validated by Monte Carlo simulation using a computational algorithm developed in our previous work [Phys. Rev. E 63, 021507 (2001)] that greatly increases the size, N , of treatable bundles (e.g., 10(6) fibers in 10(3) realizations). In particular, our algorithm is O(N ln N) in contrast with former algorithms which were O(N2) making this investigation possible. Regimes are found for (beta,rho) pairs that yield contrasting behavior for large N. For rho>1 and large N, brittle weakest volume behavior emerges in terms of characteristic elements (groupings of fibers) derived from critical cluster formation, and the lifetime eventually goes to zero as N-->infinity , unlike ELS, which yields a finite limiting mean. For 1/21 but with 0

A stochastic aerodynamic model for stationary blades in unsteady 3D wind fields

International Nuclear Information System (INIS)

Fluck, Manuel; Crawford, Curran

2016-01-01

Dynamic loads play an important roll in the design of wind turbines, but establishing the life-time aerodynamic loads (e.g. extreme and fatigue loads) is a computationally expensive task. Conventional (deterministic) methods to analyze long term loads, which rely on the repeated analysis of multiple different wind samples, are usually too expensive to be included in optimization routines. We present a new stochastic approach, which solves the aerodynamic system equations (Lagrangian vortex model) in the stochastic space, and thus arrive directly at a stochastic description of the coupled loads along a turbine blade. This new approach removes the requirement of analyzing multiple different realizations. Instead, long term loads can be extracted from a single stochastic solution, a procedure that is obviously significantly faster. Despite the reduced analysis time, results obtained from the stochastic approach match deterministic result well for a simple test-case (a stationary blade). In future work, the stochastic method will be extended to rotating blades, thus opening up new avenues to include long term loads into turbine optimization. (paper)

Conditional load and store in a shared memory

Science.gov (United States)

Blumrich, Matthias A; Ohmacht, Martin

2015-02-03

A method, system and computer program product for implementing load-reserve and store-conditional instructions in a multi-processor computing system. The computing system includes a multitude of processor units and a shared memory cache, and each of the processor units has access to the memory cache. In one embodiment, the method comprises providing the memory cache with a series of reservation registers, and storing in these registers addresses reserved in the memory cache for the processor units as a result of issuing load-reserve requests. In this embodiment, when one of the processor units makes a request to store data in the memory cache using a store-conditional request, the reservation registers are checked to determine if an address in the memory cache is reserved for that processor unit. If an address in the memory cache is reserved for that processor, the data are stored at this address.

Stochastic Load Models and Footbridge Response

DEFF Research Database (Denmark)

Pedersen, Lars; Frier, Christian

2015-01-01

Pedestrians may cause vibrations in footbridges and these vibrations may potentially be annoying. This calls for predictions of footbridge vibration levels and the paper considers a stochastic approach to modeling the action of pedestrians assuming walking parameters such as step frequency, pedes...

Research on Multiple-Split Load Sharing Characteristics of 2-Stage External Meshing Star Gear System in Consideration of Displacement Compatibility

Directory of Open Access Journals (Sweden)

Shuai Mo

2017-01-01

Full Text Available This paper studies the multiple-split load sharing mechanism of gears in two-stage external meshing planetary transmission system of aeroengine. According to the eccentric error, gear tooth thickness error, pitch error, installation error, and bearing manufacturing error, we performed the meshing error analysis of equivalent angles, respectively, and we also considered the floating meshing error caused by the variation of the meshing backlash, which is from the floating of all gears at the same time. Finally, we obtained the comprehensive angle meshing error of the two-stage meshing line, established a refined mathematical computational model of 2-stage external 3-split loading sharing coefficient in consideration of displacement compatibility, got the regular curves of the load sharing coefficient and load sharing characteristic curve of full floating multiple-split and multiple-stage system, and took the variation law of the floating track and the floating quantity of the center wheel. These provide a scientific theory to determine the load sharing coefficient, reasonable load distribution, and control tolerances in aviation design and manufacturing.

Optimum Parameters of a Tuned Liquid Column Damper in a Wind Turbine Subject to Stochastic Load

Science.gov (United States)

Alkmim, M. H.; de Morais, M. V. G.; Fabro, A. T.

2017-12-01

Parameter optimization for tuned liquid column dampers (TLCD), a class of passive structural control, have been previously proposed in the literature for reducing vibration in wind turbines, and several other applications. However, most of the available work consider the wind excitation as either a deterministic harmonic load or random load with white noise spectra. In this paper, a global direct search optimization algorithm to reduce vibration of a tuned liquid column damper (TLCD), a class of passive structural control device, is presented. The objective is to find optimized parameters for the TLCD under stochastic load from different wind power spectral density. A verification is made considering the analytical solution of undamped primary system under white noise excitation by comparing with result from the literature. Finally, it is shown that different wind profiles can significantly affect the optimum TLCD parameters.

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.

Optimal task partition and state-dependent loading in heterogeneous two-element work sharing system

International Nuclear Information System (INIS)

Levitin, Gregory; Xing, Liudong; Ben-Haim, Hanoch; Dai, Yuanshun

2016-01-01

Many real-world systems such as multi-channel data communication, multi-path flow transmission and multi-processor computing systems have work sharing attributes where system elements perform different portions of the same task simultaneously. Motivated by these applications, this paper models a heterogeneous work-sharing system with two non-repairable elements. When one element fails, the other element takes over the uncompleted task of the failed element upon finishing its own part; the load level of the remaining operating element can change at the time of the failure, which further affects its performance, failure behavior and operation cost. Considering these dynamics, mission success probability (MSP), expected mission completion time (EMCT) and expected cost of successful mission (ECSM) are first derived. Further, optimization problems are formulated and solved, which find optimal task partition and element load levels maximizing MSP, minimizing EMCT or minimizing ECSM. Effects of element reliability, performance, operation cost on the optimal solutions are also investigated through examples. Results of this work can facilitate a tradeoff analysis of different mission performance indices for heterogeneous work-sharing systems. - Highlights: • A heterogeneous work-sharing system with two non-repairable elements is considered. • The optimal work distribution and element loading problem is formulated and solved. • Effects of element reliability, performance, operation cost on the optimal solutions are investigated.

Stochastic Fatigue Analysis of Jacket Type Offshore Structures

DEFF Research Database (Denmark)

Sigurdsson, Gudfinnur

In this paper, a stochastic reliability assessment for jacket type offshore structures subjected to wave loads in deep water environments is outlined. In the reliability assessment, structural and loading uncertainties are taken into account by means of some stochastic variables. To estimate stat...... statistical measures of structural stress variations the modal spectral analysis method is applied....

Investigation of Load Sharing in Hybrid (2G/3G) Mobile Networks

OpenAIRE

Martynas Stirbys; Karolis Žvinys

2015-01-01

The main purpose of this work is to investigate load sharing methods for 2G/3G cellular networks in order to determine their impact on the network and users. One of the study aims is to analyze the performance of the methods. Moreover the paper provides an overview of the methods circumstances, limitations. Directed Retry and Load Based Handover methods were chosen. Data was obtained from real Lithuanian mobile operator’s network. The paper also discusses the changes in Key Performance Indica...

Investigation of Load Sharing in Hybrid (2G/3G Mobile Networks

Directory of Open Access Journals (Sweden)

Martynas Stirbys

2015-07-01

Full Text Available The main purpose of this work is to investigate load sharing methods for 2G/3G cellular networks in order to determine their impact on the network and users. One of the study aims is to analyze the performance of the methods. Moreover the paper provides an overview of the methods circumstances, limitations. Directed Retry and Load Based Handover methods were chosen. Data was obtained from real Lithuanian mobile operator’s network. The paper also discusses the changes in Key Performance Indicators.

Active load current sharing in fuel cell and battery fed DC motor drive for electric vehicle application

International Nuclear Information System (INIS)

Pany, Premananda; Singh, R.K.; Tripathi, R.K.

2016-01-01

Highlights: • Load current sharing in FC and battery fed dc drive. • Active current sharing control using LabVIEW. • Detail hardware implementation. • Controller performance is verified through MATLAB simulation and experimental results. - Abstract: In order to reduce the stress on fuel cell based hybrid source fed electric drive system the controller design is made through active current sharing (ACS) technique. The effectiveness of the proposed ACS technique is tested on a dc drive system fed from fuel cell and battery energy sources which enables both load current sharing and source power management. High efficiency and reliability of the hybrid system can be achieved by proper energy conversion and management of power to meet the load demand in terms of required voltage and current. To overcome the slow dynamics feature of FC, a battery bank of adequate power capacity has to be incorporated as FC voltage drops heavily during fast load demand. The controller allows fuel cell to operate in normal load region and draw the excess power from battery. In order to demonstrate the performance of the drive using ACS control strategy different modes of operation of the hybrid source with the static and dynamic behavior of the control system is verified through simulation and experimental results. This control scheme is implemented digitally in LabVIEW with PCI 6251 DAQ I/O interface card. The efficacy of the controller performance is demonstrated in system changing condition supplemented by experimental validation.

Circuit for automatic load sharing in parallel converter modules

Science.gov (United States)

Nagano, S. (Inventor)

1979-01-01

A nondissipative circuit for automatic load sharing in parallel converter modules having push-pull power transistors is presented. Each transistor has a separate current-sensing transformer and an impedance-adjusting transformer in series with its collector. The impedance-adjusting transformer functions as a current-controlled variable impedance that is responsive to the difference between the peak collector current of the transistor and the average peak current of all collector currents of power transistors in all modules, thereby to control the collector currents of all power transistors with reference to the average peak collector current.

Influence of stochastic geometric imperfections on the load-carrying behaviour of thin-walled structures using constrained random fields

Science.gov (United States)

Lauterbach, S.; Fina, M.; Wagner, W.

2018-04-01

Since structural engineering requires highly developed and optimized structures, the thickness dependency is one of the most controversially debated topics. This paper deals with stability analysis of lightweight thin structures combined with arbitrary geometrical imperfections. Generally known design guidelines only consider imperfections for simple shapes and loading, whereas for complex structures the lower-bound design philosophy still holds. Herein, uncertainties are considered with an empirical knockdown factor representing a lower bound of existing measurements. To fully understand and predict expected bearable loads, numerical investigations are essential, including geometrical imperfections. These are implemented into a stand-alone program code with a stochastic approach to compute random fields as geometric imperfections that are applied to nodes of the finite element mesh of selected structural examples. The stochastic approach uses the Karhunen-Loève expansion for the random field discretization. For this approach, the so-called correlation length l_c controls the random field in a powerful way. This parameter has a major influence on the buckling shape, and also on the stability load. First, the impact of the correlation length is studied for simple structures. Second, since most structures for engineering devices are more complex and combined structures, these are intensively discussed with the focus on constrained random fields for e.g. flange-web-intersections. Specific constraints for those random fields are pointed out with regard to the finite element model. Further, geometrical imperfections vanish where the structure is supported.

The Comprehensive Biomechanics and Load-Sharing of Semirigid PEEK and Semirigid Posterior Dynamic Stabilization Systems

Directory of Open Access Journals (Sweden)

D. K. Sengupta

2013-01-01

Full Text Available Alternatives to conventional rigid fusion have been proposed for several conditions related to degenerative disc disease when nonoperative treatment has failed. Semirigid fixation, in the form of dynamic stabilization or PEEK rods, is expected to provide compression under loading as well as an intermediate level of stabilization. This study systematically examines both the load-sharing characteristics and kinematics of these two devices compared to the standard of internal rigid fixators. Load-sharing was studied by using digital pressure films inserted between an artificially machined disc and two loading fixtures. Rigid rods, PEEK rods, and the dynamic stabilization system were inserted posteriorly for stabilization. The kinematics were quantified on ten, human, cadaver lumbosacral spines (L3-S1 which were tested under a pure bending moment, in flexion-extension, lateral bending, and axial rotation. The magnitude of load transmission through the anterior column was significantly greater with the dynamic device compared to PEEK rods and rigid rods. The contact pressures were distributed more uniformly, throughout the disc with the dynamic stabilization devices, and had smaller maximum point-loading (pressures on any particular point within the disc. Kinematically, the motion was reduced by both semirigid devices similarly in all directions, with slight rigidity imparted by a lateral interbody device.

Decentralized Load Sharing in a Low-Voltage Direct Current Microgrid With an Adaptive Droop Approach Based on a Superimposed Frequency

DEFF Research Database (Denmark)

Peyghami, Saeed; Mokhtari, Hossein; Blaabjerg, Frede

2017-01-01

Conventional droop methods for load sharing control in low-voltage direct current microgrids suffer from poor power sharing and voltage regulation, especially in the case when operating many dc sources with long feeders. Hence, the communication-based approaches are employed to improve the load s...

Water Quality Trading when Nonpoint Pollution Loads are Stochastic

OpenAIRE

Ghosh, Gaurav; Shortle, James

2009-01-01

We compare two tradable permit markets in their ability to meet a stated environmental target at least cost when some polluters have stochastic and non-measurable emissions. The environmental target is of the safety-first type, which requires probabilistic emissions control. One market is built around the trading ratio, which defines the substitution rate between stochastic and deterministic pollution, and is modeled on existing markets for water quality trading. The other market is built aro...

Comparison of the load-sharing characteristics between pedicle-based dynamic and rigid rod devices

International Nuclear Information System (INIS)

Ahn, Yoon-Ho; Chen, W-M; Lee, Kwon-Yong; Park, Kyung-Woo; Lee, Sung-Jae

2008-01-01

Recently, numerous types of posterior dynamic stabilization (PDS) devices have been introduced as an alternative to the fusion devices for the surgical treatment of degenerative lumbar spine. It is hypothesized that the use of 'compliant' materials such as Nitinol (Ni-Ti alloy, elastic modulus = 75 GPa) or polyether-etherketone (PEEK, elastic modulus = 3.2 GPa) in PDS can restore stability of the lumbar spine without adverse stress-shielding effects that have often been found with 'rigid' fusion devices made of 'rigid' Ti alloys (elastic modulus = 114 GPa). Previous studies have shown that suitably designed PDS devices made of more compliant material may be able to help retain kinematic behavior of the normal spine with optimal load sharing between the anterior and posterior spinal elements. However, only a few studies on their biomechanical efficacies are available. In this study, we conducted a finite-element (FE) study to investigate changes in load-sharing characteristics of PDS devices. The implanted models were constructed after modifying the previously validated intact model of L3-4 spine. Posterior lumbar fusion with three different types of pedicle screw systems was simulated: a conventional rigid fixation system (Ti6Al4V, Φ = 6.0 mm) and two kinds of PDS devices (one with Nitinol rod with a three-coiled turn manner, Φ = 4.0 mm; the other with PEEK rod with a uniform cylindrical shape, Φ = 6.0 mm). To simulate the load on the lumbar spine in a neutral posture, an axial compressive load (400 N) was applied. Subsequently, the changes in load-sharing characteristics and stresses were investigated. When the compressive load was applied on the implanted models (Nitinol rod, PEEK rod, Ti-alloy rod), the predicted axial compressive loads transmitted through the devices were 141.8 N, 109.8 N and 266.8 N, respectively. Axial forces across the PDS devices (Nitinol rod, PEEK rod) and rigid system (Ti-alloy rod) with facet joints were predicted to take over 41%, 33

Stochastic Wake Modelling Based on POD Analysis

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David Bastine

2018-03-01

Full Text Available In this work, large eddy simulation data is analysed to investigate a new stochastic modeling approach for the wake of a wind turbine. The data is generated by the large eddy simulation (LES model PALM combined with an actuator disk with rotation representing the turbine. After applying a proper orthogonal decomposition (POD, three different stochastic models for the weighting coefficients of the POD modes are deduced resulting in three different wake models. Their performance is investigated mainly on the basis of aeroelastic simulations of a wind turbine in the wake. Three different load cases and their statistical characteristics are compared for the original LES, truncated PODs and the stochastic wake models including different numbers of POD modes. It is shown that approximately six POD modes are enough to capture the load dynamics on large temporal scales. Modeling the weighting coefficients as independent stochastic processes leads to similar load characteristics as in the case of the truncated POD. To complete this simplified wake description, we show evidence that the small-scale dynamics can be captured by adding to our model a homogeneous turbulent field. In this way, we present a procedure to derive stochastic wake models from costly computational fluid dynamics (CFD calculations or elaborated experimental investigations. These numerically efficient models provide the added value of possible long-term studies. Depending on the aspects of interest, different minimalized models may be obtained.

Stochastic Optimisation of Battery System Operation Strategy under different Utility Tariff Structures

OpenAIRE

Erdal, Jørgen Sørgård

2017-01-01

This master thesis develops a stochastic optimisation software for household grid-connected batteries combined with PV-systems. The objective of the optimisation is to operate the battery system in order to minimise the costs of the consumer, and it was implemented in MATLAB using a self-written stochastic dynamic programming algorithm. Load was considered as a stochastic variable and modelled as a Markov Chain. Transition probabilities between time steps were calculated using historic load p...

Optimized load sharing control by means of thermal reliability management

DEFF Research Database (Denmark)

Nesgaard, Carsten; Andersen, Michael Andreas E.

2004-01-01

time and system cost. However, due to non-ideal parts each converter unit deviates from the ideal case, which makes a power system comprised of parallel-connected converters a rather poor performing system. To account for the non-ideal parts some form of load sharing is needed, whereby it is ensured......With new applications for high-current low-output voltage power systems emerging nearly every day the need for new and cost-efficient power system designs is a matter of course. As output voltage levels continue to decrease an approach that seems more and more attractive is the implementation...... that each converter in the configuration delivers its share of the total output power. In other words parallel-operation of multiple converters is employed when specifications require a highly reliable system, designable within a very short time frame and at low costs. However, to make full use...

Stochastic Modeling and Analysis of Power System with Renewable Generation

DEFF Research Database (Denmark)

Chen, Peiyuan

Unlike traditional fossil-fuel based power generation, renewable generation such as wind power relies on uncontrollable prime sources such as wind speed. Wind speed varies stochastically, which to a large extent determines the stochastic behavior of power generation from wind farms...... that such a stochastic model can be used to simulate the effect of load management on the load duration curve. As CHP units are turned on and off by regulating power, CHP generation has discrete output and thus can be modeled by a transition matrix based discrete Markov chain. As the CHP generation has a strong diurnal...

Stiffness Matters: Part II - The Effects of Plate Stiffness on Load-Sharing and the Progression of Fusion Following ACDF In Vivo.

Science.gov (United States)

Peterson, Joshua M; Chlebek, Carolyn; Clough, Ashley M; Wells, Alexandra K; Batzinger, Kathleen E; Houston, John M; Kradinova, Katerina; Glennon, Joseph C; DiRisio, Darryl J; Ledet, Eric H

2018-03-19

Real time in vivo measurement of forces in the cervical spine of goats following anterior cervical discectomy and fusion (ACDF). To measure interbody forces in the cervical spine during the time course of fusion following ACDF with plates of different stiffnesses. Following ACDF, the biomechanics of the arthrodesis is largely dictated by the plate. The properties of the plate prescribe the extent of load-sharing through the disc space versus the extent of stress-shielding. Load-sharing promotes interbody bone formation and stress-shielding can inhibit maturation of bone. However, these principles have never been validated in vivo. Measuring in vivo biomechanics of the cervical spine is critical to understanding the complex relationships between implant design, interbody loading, load-sharing, and the progression of fusion. Anterior cervical plates of distinct bending stiffnesses were placed surgically following ACDF in goats. A validated custom force-sensing interbody implant was placed in the disc space to measure load-sharing in the spine. Interbody loads were measured in vivo in real time during the course of fusion for each plate. Interbody forces during flexion/extension were highly dynamic. In animals that received high stiffness plates, maximum forces were in extension whereas in animals that received lower stiffness plates, maximum forces were in flexion. As fusion progressed, interbody load magnitude decreased. The magnitude of interbody forces in the cervical spine is dynamic and correlates to activity and posture of the head and neck. The magnitude and consistency of forces in the interbody space correlates to plate stiffness with more compliant plates resulting in more consistent load-sharing. The magnitude of interbody forces decreases as fusion matures suggesting that smart interbody implants may be used as a diagnostic tool to indicate the progression of interbody fusion. N/A.

Decentralized Method for Load Sharing and Power Management in a PV/Battery Hybrid Source Islanded Microgrid

DEFF Research Database (Denmark)

Karimi, Yaser; Oraee, Hashem; Golsorkhi, Mohammad

2017-01-01

This paper proposes a new decentralized power management and load sharing method for a photovoltaic based islanded microgrid consisting of various PV units, battery units and hybrid PV/battery units. Unlike the previous methods in the literature, there is no need to communication among the units......, the operation of each unit is divided into five states and modified active power-frequency droop functions are used according to operating states. The frequency level is used as trigger for switching between the states. Efficacy of the proposed method in different load, PV generation and battery conditions...... and the proposed method is not limited to the systems with separate PV and battery units or systems with only one hybrid unit. The proposed method takes into account the available PV power and battery conditions of the units to share the load among them. To cover all possible conditions of the microgrid...

Stochastic theory of fatigue corrosion

Science.gov (United States)

Hu, Haiyun

1999-10-01

A stochastic theory of corrosion has been constructed. The stochastic equations are described giving the transportation corrosion rate and fluctuation corrosion coefficient. In addition the pit diameter distribution function, the average pit diameter and the most probable pit diameter including other related empirical formula have been derived. In order to clarify the effect of stress range on the initiation and growth behaviour of pitting corrosion, round smooth specimen were tested under cyclic loading in 3.5% NaCl solution.

Stochastic quantization and topological theories

International Nuclear Information System (INIS)

Fainberg, V.Y.; Subbotin, A.V.; Kuznetsov, A.N.

1992-01-01

In the last two years topological quantum field theories (TQFT) have attached much attention. This paper reports that from the very beginning it was realized that due to a peculiar BRST-like symmetry these models admitted so-called Nicolai mapping: the Nicolai variables, in terms of which actions of the theories become gaussian, are nothing but (anti-) selfduality conditions or their generalizations. This fact became a starting point in the quest of possible stochastic interpretation to topological field theories. The reasons behind were quite simple and included, in particular, the well-known relations between stochastic processes and supersymmetry. The main goal would have been achieved, if it were possible to construct stochastic processes governed by Langevin or Fokker-Planck equations in a real Euclidean time leading to TQFT's path integrals (equivalently: to reformulate TQFTs as non-equilibrium phase dynamics of stochastic processes). Further on, if it would appear that these processes correspond to the stochastic quantization of theories of some definite kind, one could expect (d + 1)-dimensional TQFTs to share some common properties with d-dimensional ones

Sensitivity of Footbridge Vibrations to Stochastic Walking Parameters

DEFF Research Database (Denmark)

Pedersen, Lars; Frier, Christian

2010-01-01

of the pedestrian. A stochastic modelling approach is adopted for this paper and it facilitates quantifying the probability of exceeding various vibration levels, which is useful in a discussion of serviceability of a footbridge design. However, estimates of statistical distributions of footbridge vibration levels...... to walking loads might be influenced by the models assumed for the parameters of the load model (the walking parameters). The paper explores how sensitive estimates of the statistical distribution of vertical footbridge response are to various stochastic assumptions for the walking parameters. The basis...... for the study is a literature review identifying different suggestions as to how the stochastic nature of these parameters may be modelled, and a parameter study examines how the different models influence estimates of the statistical distribution of footbridge vibrations. By neglecting scatter in some...

Influence of inclination angles on intra- and inter-limb load-sharing during uphill walking.

Science.gov (United States)

Hong, Shih-Wun; Leu, Tsai-Hsueh; Li, Jia-Da; Wang, Ting-Ming; Ho, Wei-Ping; Lu, Tung-Wu

2014-01-01

Uphill walking is an inevitable part of daily living, placing more challenges on the locomotor system with greater risk of falls than level walking does. The current study aimed to investigate the effects of inclination angles on the inter-joint and inter-limb load-sharing during uphill walking in terms of total support moment and contributions of individual joint moments to the total support moment. Fifteen young adults walked up walkways with 0°, 5°, 10° and 15° of slope while kinematic and kinetic data were collected and analyzed. With increasing inclination angles, the first peak of the total support moment was increased with unaltered individual joint contributions, suggesting an unaltered inter-joint control pattern in the leading limb to meet the increased demands. The second peak of the total support moment remained unchanged with increasing inclination angles primarily through a compensatory redistribution of the hip and knee moments. During DLS, the leading limb shared the majority of the whole body support moments. The current results reveal basic intra- and inter-limb load-sharing patterns of uphill walking, which will be helpful for a better understanding of the control strategies adopted and for subsequent clinical applications. Copyright © 2013 Elsevier B.V. All rights reserved.

The effect of elbow angle and external moment on load sharing of elbow muscles

NARCIS (Netherlands)

Praagman, M.; Chadwick, E.K.J.; van der Helm, F.C.T.; Veeger, H.E.J.

2010-01-01

To study elbow muscle load sharing we investigated the effect of external flexion-extension (FE) and pronation-supination (PS) moments and elbow angle on muscle activation and oxygen consumption (V̇O2).Two data sets were obtained. First, (n=6) electromyography (EMG) of elbow flexors (long and short

Reliability-Based Shape Optimization using Stochastic Finite Element Methods

DEFF Research Database (Denmark)

Enevoldsen, Ib; Sørensen, John Dalsgaard; Sigurdsson, G.

1991-01-01

stochastic fields (e.g. loads and material parameters such as Young's modulus and the Poisson ratio). In this case stochastic finite element techniques combined with FORM analysis can be used to obtain measures of the reliability of the structural systems, see Der Kiureghian & Ke (6) and Liu & Der Kiureghian...

Stochastic Sizing of Energy Storage Systems for Wind Integration

Directory of Open Access Journals (Sweden)

D. D. Le

2018-06-01

Full Text Available In this paper, we present an optimal capacity decision model for energy storage systems (ESSs in combined operation with wind energy in power systems. We use a two-stage stochastic programming approach to take into account both wind and load uncertainties. The planning problem is formulated as an AC optimal power flow (OPF model with the objective of minimizing ESS installation cost and system operation cost. Stochastic wind and load inputs for the model are generated from historical data using clustering technique. The model is tested on the IEEE 39-bus system.

Load sharing in distributed real-time systems with state-change broadcasts

Science.gov (United States)

Shin, Kang G.; Chang, Yi-Chieh

1989-01-01

A decentralized dynamic load-sharing (LS) method based on state-change broadcasts is proposed for a distributed real-time system. Whenever the state of a node changes from underloaded to fully loaded and vice versa, the node broadcasts this change to a set of nodes, called a buddy set, in the system. The performance of the method is evaluated with both analytic modeling and simulation. It is modeled first by an embedded Markov chain for which numerical solutions are derived. The model solutions are then used to calculate the distribution of queue lengths at the nodes and the probability of meeting task deadlines. The analytical results show that buddy sets of 10 nodes outperform those of less than 10 nodes, and the incremental benefit gained from increasing the buddy set size beyond 15 nodes is insignificant. These and other analytical results are verified by simulation. The proposed LS method is shown to meet task deadlines with a very high probability.

Stochastic Dual Algorithm for Voltage Regulation in Distribution Networks with Discrete Loads: Preprint

Energy Technology Data Exchange (ETDEWEB)

Dall-Anese, Emiliano [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhou, Xinyang [University of Colorado; Liu, Zhiyuan [University of Colorado; Chen, Lijun [University of Colorado

2017-10-03

This paper considers distribution networks with distributed energy resources and discrete-rate loads, and designs an incentive-based algorithm that allows the network operator and the customers to pursue given operational and economic objectives, while concurrently ensuring that voltages are within prescribed limits. Four major challenges include: (1) the non-convexity from discrete decision variables, (2) the non-convexity due to a Stackelberg game structure, (3) unavailable private information from customers, and (4) different update frequency from two types of devices. In this paper, we first make convex relaxation for discrete variables, then reformulate the non-convex structure into a convex optimization problem together with pricing/reward signal design, and propose a distributed stochastic dual algorithm for solving the reformulated problem while restoring feasible power rates for discrete devices. By doing so, we are able to statistically achieve the solution of the reformulated problem without exposure of any private information from customers. Stability of the proposed schemes is analytically established and numerically corroborated.

An Enhanced Instantaneous Circulating Current Control for Reactive power and Harmonic Load Sharing in Islanded Microgrids

DEFF Research Database (Denmark)

Lorzadeh, Iman; Askarian Abyaneh, Hossein; Savaghebi, Mehdi

2017-01-01

To address inaccurate load demand sharing problems among parallel inverter-interfaced voltage-controlled distributed generation (DG) units in islanded microgrids with different DG power ratings and mismatched feeder impedances, an enhanced voltage control scheme based on actively compensation of ...

A Stochastic Operational Planning Model for Smart Power Systems

Directory of Open Access Journals (Sweden)

Sh. Jadid

2014-12-01

Full Text Available Smart Grids are result of utilizing novel technologies such as distributed energy resources, and communication technologies in power system to compensate some of its defects. Various power resources provide some benefits for operation domain however, power system operator should use a powerful methodology to manage them. Renewable resources and load add uncertainty to the problem. So, independent system operator should use a stochastic method to manage them. A Stochastic unit commitment is presented in this paper to schedule various power resources such as distributed generation units, conventional thermal generation units, wind and PV farms, and demand response resources. Demand response resources, interruptible loads, distributed generation units, and conventional thermal generation units are used to provide required reserve for compensating stochastic nature of various resources and loads. In the presented model, resources connected to distribution network can participate in wholesale market through aggregators. Moreover, a novel three-program model which can be used by aggregators is presented in this article. Loads and distributed generation can contract with aggregators by these programs. A three-bus test system and the IEEE RTS are used to illustrate usefulness of the presented model. The results show that ISO can manage the system effectively by using this model

Reliability estimation of structures under stochastic loading—A case study on nuclear piping

International Nuclear Information System (INIS)

Hari Prasad, M.; Rami Reddy, G.; Dubey, P.N.; Srividya, A.; Verma, A.K.

2013-01-01

Highlights: ► Structures are generally subjected to different types of loadings. ► One such type of loading is random sequence and has been treated as a stochastic fatigue loading. ► In this methodology both stress amplitude and number of cycles to failure have been considered as random variables. ► The methodology has been demonstrated with a case study on nuclear piping. ► The failure probability of piping has been estimated as a function of time. - Abstract: Generally structures are subjected to different types of loadings throughout their life time. These loads can be either discrete in nature or continuous in nature and also these can be either stationary or non stationary processes. This means that the structural reliability analysis not only considers random variables but also considers random variables which are functions of time, referred to as stochastic processes. A stochastic process can be viewed as a family of random variables. When a structure is subjected to a random loading, based on the stresses developed in the structure and failure criteria the failure probability can be estimated. In practice the structures are designed with higher factor of safety to take care of such random loads. In such cases the structure will fail only when the random loads are cyclic in nature. In traditional reliability analysis, the variation in the load is treated as a random variable and to account for the number of occurrences of the loading the concept of extreme value theory is used. But with this method one is neglecting the damage accumulation that will take place from one loading to another loading. Hence, in this paper, a new way of dealing with these types of problems has been discussed by using the concept of stochastic fatigue loading. The random loading has been considered as earthquake loading. The methodology has been demonstrated with a case study on nuclear power plant piping.

Active load sharing technique for on-line efficiency optimization in DC microgrids

DEFF Research Database (Denmark)

Sanseverino, E. Riva; Zizzo, G.; Boscaino, V.

2017-01-01

Recently, DC power distribution is gaining more and more importance over its AC counterpart achieving increased efficiency, greater flexibility, reduced volumes and capital cost. In this paper, a 24-120-325V two-level DC distribution system for home appliances, each including three parallel DC......-DC converters, is modeled. An active load sharing technique is proposed for the on-line optimization of the global efficiency of the DC distribution network. The algorithm aims at the instantaneous efficiency optimization of the whole DC network, based on the on-line load current sampling. A Look Up Table......, is created to store the real efficiencies of the converters taking into account components tolerances. A MATLAB/Simulink model of the DC distribution network has been set up and a Genetic Algorithm has been employed for the global efficiency optimization. Simulation results are shown to validate the proposed...

Fast and Reliable Primary Frequency Reserves From Refrigerators with Decentralized Stochastic Control

DEFF Research Database (Denmark)

Vrettos, Evangelos; Ziras, Charalampos; Andersson, Goran

2016-01-01

in the controller to account for thermostat resolution limitations, and finally, we modify the control design to account for refrigerator door openings. Extensive simulations with actual frequency signal data and with different aggregation sizes, load characteristics, and control parameters, demonstrate......Due to increasing shares of renewable energy sources, more frequency reserves are required to maintain power system stability. In this paper, we present a decentralized control scheme that allows a large aggregation of refrigerators to provide Primary Frequency Control (PFC) reserves to the grid...... based on local frequency measurements and without communication. The control is based on stochastic switching of refrigerators depending on the frequency deviation. We develop methods to account for typical lockout constraints of compressors and increased power consumption during the startup phase...

Stochastic volatility and stochastic leverage

DEFF Research Database (Denmark)

Veraart, Almut; Veraart, Luitgard A. M.

This paper proposes the new concept of stochastic leverage in stochastic volatility models. Stochastic leverage refers to a stochastic process which replaces the classical constant correlation parameter between the asset return and the stochastic volatility process. We provide a systematic...... treatment of stochastic leverage and propose to model the stochastic leverage effect explicitly, e.g. by means of a linear transformation of a Jacobi process. Such models are both analytically tractable and allow for a direct economic interpretation. In particular, we propose two new stochastic volatility...... models which allow for a stochastic leverage effect: the generalised Heston model and the generalised Barndorff-Nielsen & Shephard model. We investigate the impact of a stochastic leverage effect in the risk neutral world by focusing on implied volatilities generated by option prices derived from our new...

Control of thumb force using surface functional electrical stimulation and muscle load sharing

Science.gov (United States)

2013-01-01

Background Stroke survivors often have difficulties in manipulating objects with their affected hand. Thumb control plays an important role in object manipulation. Surface functional electrical stimulation (FES) can assist movement. We aim to control the 2D thumb force by predicting the sum of individual muscle forces, described by a sigmoidal muscle recruitment curve and a single force direction. Methods Five able bodied subjects and five stroke subjects were strapped in a custom built setup. The forces perpendicular to the thumb in response to FES applied to three thumb muscles were measured. We evaluated the feasibility of using recruitment curve based force vector maps in predicting output forces. In addition, we developed a closed loop force controller. Load sharing between the three muscles was used to solve the redundancy problem having three actuators to control forces in two dimensions. The thumb force was controlled towards target forces of 0.5 N and 1.0 N in multiple directions within the individual’s thumb work space. Hereby, the possibilities to use these force vector maps and the load sharing approach in feed forward and feedback force control were explored. Results The force vector prediction of the obtained model had small RMS errors with respect to the actual measured force vectors (0.22±0.17 N for the healthy subjects; 0.17±0.13 N for the stroke subjects). The stroke subjects showed a limited work range due to limited force production of the individual muscles. Performance of feed forward control without feedback, was better in healthy subjects than in stroke subjects. However, when feedback control was added performances were similar between the two groups. Feedback force control lead, especially for the stroke subjects, to a reduction in stationary errors, which improved performance. Conclusions Thumb muscle responses to FES can be described by a single force direction and a sigmoidal recruitment curve. Force in desired direction can be

Distributed Control to Ensure Proportional Load Sharing and Improve Voltage Regulation in Low-Voltage DC Microgrids

DEFF Research Database (Denmark)

Anand, Sandeep; G. Fernandes, Baylon; Guerrero, Josep M.

2013-01-01

DC microgrids are gaining popularity due to high efficiency, high reliability, and easy interconnection of renewable sources as compared to the ac system. Control objectives of dc microgrid are: 1) to ensure equal load sharing (in per unit) among sources; and 2) to maintain low-voltage regulation...

风力发电高塔系统风致随机动力响应分析%Stochastic dynamic analysis of wind turbine systems under wind loads

Institute of Scientific and Technical Information of China (English)

贺广零; 李杰

2011-01-01

Wind energy development is an effective way to solve problems such as energy shortage and environmental pollution, so it is very useful to accurately compute the stochastic dynamic response of wind turbine systems under wind loads. Firstly< a new method termed as generalized probability density evolution method (GPDEM) is presented in the paper. The GPDEM has been proved to be of high accuracy and efficiency in most kinds of stochastic analysis of dynamical systems. Associated with the physical model of stochastic wind field and the integrated finite element model consisting of the rotor, the nacelle. The tower and the foundation, it is very hopeful to apply the GPDEM in stochastic dynamic analysis of wind turbine systems. Then, a 1. 25 MW wind turbine system subject to wind loads is investigated in detail, and the dynamic responses and the stochastic ones are also compared. The results demonstrate that the randomness of wind velocities places a great influence on the stochastic dynamic analysis of wind turbine systems.%介绍了一种高精度且高效的随机动力系统分析方法-广义概率密度演化方法.基于广义概率密度演化方法,结合随机脉动风场物理模型和“桨叶-机舱-塔体-基础”一体化有限元模型,分别对1.25 MW风力发电高钢塔和钢筋混凝土风力发电高塔进行了风致随机动力响应分析,并将分析结果同确定性动力响应分析结果进行比较.研究表明,随机性对风力发电高塔系统结构风致动力响应分析的影响非常显著.

Dynamics of a Stochastic Intraguild Predation Model

Directory of Open Access Journals (Sweden)

Zejing Xing

2016-04-01

Full Text Available Intraguild predation (IGP is a widespread ecological phenomenon which occurs when one predator species attacks another predator species with which it competes for a shared prey species. The objective of this paper is to study the dynamical properties of a stochastic intraguild predation model. We analyze stochastic persistence and extinction of the stochastic IGP model containing five cases and establish the sufficient criteria for global asymptotic stability of the positive solutions. This study shows that it is possible for the coexistence of three species under the influence of environmental noise, and that the noise may have a positive effect for IGP species. A stationary distribution of the stochastic IGP model is established and it has the ergodic property, suggesting that the time average of population size with the development of time is equal to the stationary distribution in space. Finally, we show that our results may be extended to two well-known biological systems: food chains and exploitative competition.

Stochastic energy balancing in substation energy management

Directory of Open Access Journals (Sweden)

Hassan Shirzeh

2015-12-01

Full Text Available In the current research, a smart grid is considered as a network of distributed interacting nodes represented by renewable energy sources, storage and loads. The source nodes become active or inactive in a stochastic manner due to the intermittent nature of natural resources such as wind and solar irradiance. Prediction and stochastic modelling of electrical energy flow is a critical task in such a network in order to achieve load levelling and/or peak shaving in order to minimise the fluctuation between off-peak and peak energy demand. An effective approach is proposed to model and administer the behaviour of source nodes in this grid through a scheduling strategy control algorithm using the historical data collected from the system. The stochastic model predicts future power consumption/injection to determine the power required for storage components. The stochastic models developed based on the Box-Jenkins method predict the most efficient state of the electrical energy flow between a distribution network and nodes and minimises the peak demand and off-peak consumption of acquiring electrical energy from the main grid. The performance of the models is validated against the autoregressive moving average (ARIMA and the Markov chain models used in previous work. The results demonstrate that the proposed method outperforms both the ARIMA and the Markov chain model in terms of forecast accuracy. Results are presented, the strengths and limitations of the approach are discussed, and possible future work is described.

In vitro evaluation of stiffness and load sharing in a two-level corpectomy: comparison of static and dynamic cervical plates.

Science.gov (United States)

Fogel, Guy R; Li, Zhenyu; Liu, Weiqiang; Liao, Zhenhua; Wu, Jia; Zhou, Wenyu

2010-05-01

Anterior cervical plating has been accepted in corpectomy and fusion of the cervical spine. Constrained plates were criticized for stress shielding that may lead to subsidence and pseudarthrosis. A dynamic plate allows load sharing as the graft subsides. Ideally, the dynamic plate design should maintain adequate stiffness of the construct while providing a reasonable load sharing with the strut graft. The purpose of the study was to compare dynamic and static plate kinematics with graft subsidence. The study designed was an in vitro biomechanical study in a porcine cervical spine model. Twelve spines were initially tested in intact condition with 20-N axial load in 15 degrees of flexion and extension range of motion (ROM). Then, a two-level corpectomy was created in all specimens with spines randomized to receive either a static or dynamic plate. The spines were retested under identical conditions with optimal length and undersized graft. Range of motion and graft loading were analyzed with a one-way analysis of variance (p<.05). Both plates significantly limited ROM compared with the intact spine in both graft length conditions. In extension graft, load was significantly higher (p=.001) in the static plate with optimal length, and in flexion, there was a significant loss of graft load (p=.0004). In flexion, the dynamic plate with undersized graft demonstrated significantly more load sustained (p=.0004). Both plates reasonably limited the ROM of the corpectomy. The static plate had significantly higher graft loads in extension and significant loss of graft load in flexion, whereas the dynamic plate maintained a reasonable graft load in ROM even when graft contact was imperfect. Copyright 2010 Elsevier Inc. All rights reserved.

Numerical simulation of effective mechanical properties of stochastic composites with consideration for structural evolution under intensive dynamic loading

Energy Technology Data Exchange (ETDEWEB)

Karakulov, Valerii V., E-mail: valery@ftf.tsu.ru [National Research Tomsk State University, Tomsk, 634050 (Russian Federation); Smolin, Igor Yu., E-mail: smolin@ispms.ru, E-mail: skrp@ftf.tsu.ru; Skripnyak, Vladimir A., E-mail: smolin@ispms.ru, E-mail: skrp@ftf.tsu.ru [National Research Tomsk State University, Tomsk, 634050, Russia and Institute of Strength Physics and Materials Science SB RAS, Tomsk, 634055 (Russian Federation)

2014-11-14

Mechanical behavior of stochastic metal-ceramic composites with the aluminum matrix under high-rate deformation at shock-wave loading is numerically simulated with consideration for structural evolution. Effective values of mechanical parameters of metal-ceramic composites AlB{sub 4}C, AlSiC, and AlAl{sub 2}O{sub 3} are evaluated depending on different concentration of ceramic inclusions.

Stochastic Predictive Control of Multi-Microgrid Systems

DEFF Research Database (Denmark)

Bazmohammadi, Najmeh; Tahsiri, Ahmadreza; Anvari-Moghaddam, Amjad

2018-01-01

This paper presents a stochastic predictive control algorithm for a number of microgrids connected to the same distribution system. Each microgrid includes a variety of distributed resources such as wind turbine, photo voltaic units, energy storage devices and loads. Considering the uncertainty...

Stochastic Analysis of Offshore Steel Structures An Analytical Appraisal

CERN Document Server

Karadeniz, Halil

2013-01-01

Stochastic Analysis of Offshore Steel Structures provides a clear and detailed guide to advanced analysis methods of fixed offshore steel structures using 3D beam finite elements under random wave and earthquake loadings. Advanced and up-to-date research results are coupled with modern analysis methods and essential theoretical information to consider optimal solutions to structural issues. As these methods require and use knowledge of different subject matters, a general introduction to the key areas is provided. This is followed by in-depth explanations supported by design examples, relevant calculations and supplementary material containing related computer programmers. By combining this theoretical and practical approach Stochastic Analysis of Offshore Steel Structures cover a range of key concepts in detail including: ·         The basic principles of standard 3D beam finite elements and special connections, ·         Wave loading - from hydrodynamics to the calculation of wave load...

COMPARISON OF EIGENMODE-BASED AND RANDOM FIELD-BASED IMPERFECTION MODELING FOR THE STOCHASTIC BUCKLING ANALYSIS OF I-SECTION BEAM–COLUMNS

KAUST Repository

STAVREV, A.

2013-03-01

The uncertainty of geometric imperfections in a series of nominally equal I-beams leads to a variability of corresponding buckling loads. Its analysis requires a stochastic imperfection model, which can be derived either by the simple variation of the critical eigenmode with a scalar random variable, or with the help of the more advanced theory of random fields. The present paper first provides a concise review of the two different modeling approaches, covering theoretical background, assumptions and calibration, and illustrates their integration into commercial finite element software to conduct stochastic buckling analyses with the Monte-Carlo method. The stochastic buckling behavior of an example beam is then simulated with both stochastic models, calibrated from corresponding imperfection measurements. The simulation results show that for different load cases, the response statistics of the buckling load obtained with the eigenmode-based and the random field-based models agree very well. A comparison of our simulation results with corresponding Eurocode 3 limit loads indicates that the design standard is very conservative for compression dominated load cases. © 2013 World Scientific Publishing Company.

Outlier robustness for wind turbine extrapolated extreme loads

DEFF Research Database (Denmark)

Natarajan, Anand; Verelst, David Robert

2012-01-01

. Stochastic identification of numerical artifacts in simulated loads is demonstrated using the method of principal component analysis. The extrapolation methodology is made robust to outliers through a weighted loads approach, whereby the eigenvalues of the correlation matrix obtained using the loads with its...

Assessing potential effects of highway runoff on receiving-water quality at selected sites in Oregon with the Stochastic Empirical Loading and Dilution Model (SELDM)

Science.gov (United States)

Risley, John C.; Granato, Gregory E.

2014-01-01

In 2012, the U.S. Geological Survey and the Oregon Department of Transportation began a cooperative study to demonstrate use of the Stochastic Empirical Loading and Dilution Model (SELDM) for runoff-quality analyses in Oregon. SELDM can be used to estimate stormflows, constituent concentrations, and loads from the area upstream of a stormflow discharge site, from the site of interest and in the receiving waters downstream of the discharge. SELDM also can be used to assess the potential effectiveness of best management practices (BMP) for mitigating potential effects of runoff in receiving waters. Nominally, SELDM is a highway-runoff model, but it is well suited for analysis of runoff from other land uses as well. This report provides case studies and examples to demonstrate stochastic-runoff modeling concepts and to demonstrate application of the model. Basin characteristics from six Oregon highway study sites were used to demonstrate various applications of the model. The highway catchment and upstream basin drainage areas of these study sites ranged from 3.85 to 11.83 acres and from 0.16 to 6.56 square miles, respectively. The upstream basins of two sites are urbanized, and the remaining four sites are less than 5 percent impervious. SELDM facilitates analysis by providing precipitation, pre-storm streamflow, and other variables by region or from hydrologically similar sites. In Oregon, there can be large variations in precipitation and streamflow among nearby sites. Therefore, spatially interpolated geographic information system data layers containing storm-event precipitation and pre-storm streamflow statistics specific to Oregon were created for the study using Kriging techniques. Concentrations and loads of cadmium, chloride, chromium, copper, iron, lead, nickel, phosphorus, and zinc were simulated at the six Oregon highway study sites by using statistics from sites in other areas of the country. Water‑quality datasets measured at hydrologically similar

Response of Rubble Foundation to Dynamic Loading

DEFF Research Database (Denmark)

Burcharth, H. F.; Ibsen, Lars Bo

1993-01-01

The soil beneath vertical monolithic structures is subjected to a combination of static load due to the submerged weight of the structure and stochastic non-stationary loads as a result of the wave loads on the vertical wall. The stress conditions in the soil below a foundation exposed to both...

Response of Rubble Foundation to Dynamic Loading

DEFF Research Database (Denmark)

Burcharth, H. F.; Ibsen, Lars Bo

1994-01-01

The soil beneath vertical monolithic structures is subjected to a combination of static load due to the submerged weight of the structure and stochastic non-stationary loads as a result of the wave loads on the vertical wall. The stress conditions in the soil below a foundation exposed to both...

On Space-Time Resolution of Inflow Representations for Wind Turbine Loads Analysis

Directory of Open Access Journals (Sweden)

Lance Manuel

2012-06-01

Full Text Available Efficient spatial and temporal resolution of simulated inflow wind fields is important in order to represent wind turbine dynamics and derive load statistics for design. Using Fourier-based stochastic simulation of inflow turbulence, we first investigate loads for a utility-scale turbine in the neutral atmospheric boundary layer. Load statistics, spectra, and wavelet analysis representations for different space and time resolutions are compared. Next, large-eddy simulation (LES is employed with space-time resolutions, justified on the basis of the earlier stochastic simulations, to again derive turbine loads. Extreme and fatigue loads from the two approaches used in inflow field generation are compared. On the basis of simulation studies carried out for three different wind speeds in the turbine’s operating range, it is shown that inflow turbulence described using 10-meter spatial resolution and 1 Hz temporal resolution is adequate for assessing turbine loads. Such studies on the investigation of adequate filtering or resolution of inflow wind fields help to establish efficient strategies for LES and other physical or stochastic simulation needed in turbine loads studies.

Complexity Dynamic Character Analysis of Retailers Based on the Share of Stochastic Demand and Service

Directory of Open Access Journals (Sweden)

Junhai Ma

2017-01-01

Full Text Available Apart from the price fluctuation, the retailers’ service level becomes another key factor that affects the market demand. This paper depicts a modified price and demand game model based on the stochastic demand and the retailer’s service level which influences the market demand decided by customers’ preference, while the market demand is stochastic in this model. We explore how the price adjustment speed affects the stability of the supply chain system with respect to service level and stochastic demand. The dynamic behavior of the system is researched by simulation and the stability domain and the bifurcation phenomenon are shown clearly. The largest Lyapunov exponent and the chaotic attractor are also given to confirm the chaotic characteristic of the system. The simulation results indicate that relatively small price adjustment speed may maintain the system at stable state. With the price adjustment speed gradually increasing, the price system gets unstable and finally becomes chaotic. This chaotic phenomenon will perturb the product market and this phenomenon should be controlled to keep the system stay in the stable region. So the chaos control is done and the chaos can be controlled completely. The conclusion makes significant contribution to the system referring to the price fluctuation based on the service level and stochastic demand.

Automatic load sharing in inverter modules

Science.gov (United States)

Nagano, S.

1979-01-01

Active feedback loads transistor equally with little power loss. Circuit is suitable for balancing modular inverters in spacecraft, computer power supplies, solar-electric power generators, and electric vehicles. Current-balancing circuit senses differences between collector current for power transistor and average value of load currents for all power transistors. Principle is effective not only in fixed duty-cycle inverters but also in converters operating at variable duty cycles.

Filament wound pressure vessels with load sharing liners for space shuttle orbiter applications

International Nuclear Information System (INIS)

Ecord, G.M.

1976-01-01

Early in the development of orbiter propulsion and environmental control subsystems it was recognized that use of overwrapped pressure vessels with load sharing liners may provide significant weight savings for high pressure gas containment. A program is described which was undertaken by Rockwell International to assess the utility for orbiter applications of titanium 6Al--4V and Inconel 718 liners overwrapped with Kevlar fibers. Also briefly described are programs administered by the NASA Lewis Research Center to evaluate cryoformed steel liners overwrapped with Kevlar fibers and to establish a method that can guarantee cyclic life of the vessels

Enhanced Load Power Sharing Accuracy in Droop-Controlled DC Microgrids with Both Mesh and Radial Configurations

Directory of Open Access Journals (Sweden)

Yiqi Liu

2015-04-01

Full Text Available The rational power sharing among different interface converters should be determined by the converter capacity. In order to guarantee that each converter operates at the ideal condition, considering the radial and mesh configuration, a modified strategy for load power sharing accuracy enhancement in droop-controlled DC microgrid is proposed in this paper. Two compensating terms which include averaging output power control and averaging DC voltage control of neighboring converters are employed. Since only the information of the neighboring converter is used, the complexity of the communication network can be reduced. The rational distribution of load power for different line resistance conditions is realized by using modified droop control that can be regarded as a distributed approach. Low bandwidth communication is used for exchanging sampled information between different converters. The feasibility and effectiveness of the proposed method for different network configurations and line resistances under different communication delay is analyzed in detail. Simulation results derived from a DC microgrid with three converters is implemented in MATLAB/Simulink to verify the proposed approach. Experimental results from a 3 × 10 kW prototype also show the performance of the proposed modified droop control scheme.

Load sharing with a local thermal network fed by a microcogenerator: Thermo-economic optimization by means of dynamic simulations

International Nuclear Information System (INIS)

Angrisani, Giovanni; Canelli, Michele; Rosato, Antonio; Roselli, Carlo; Sasso, Maurizio; Sibilio, Sergio

2014-01-01

The cogeneration is the combined production of electric and/or mechanical and thermal energy starting by a single energy source; in particular in this paper the analysis will be focused on a cogeneration system with electric power lower than 15 kW (micro-cogeneration). The paper analyzes a system consisting of a natural gas-fired micro-cogeneration unit (MCHP), a heat storage and a peak boiler. The system provides thermal and electric energy to two end-users, the former is a tertiary building (office), where the generation system is located, and the latter is a residential building connected to the former through a district heating micro-grid. In order to analyze the influence of climatic conditions, two different geographical locations in Italy (Benevento and Milano) are considered, that are also characterized by different natural gas and electricity tariffs. Particular attention is paid to the choice of the users, in order to obtain more stable and continuous electric and thermal loads (load sharing approach) and to increase the operating hours per year of the MCHP unit. The operation of the MCHP is governed by a control system, aimed to optimize a thermo-economic objective function. The models representing the components, the thermo-economic objective function and the buildings have been implemented in a widely used commercial software for building simulations. The models are calibrated and validated through data obtained from experimental tests carried out in the laboratory of the University of Sannio (Benevento). The results of the simulations highlight the potential benefits of the thermal load sharing approach. In particular, this study shows that an MCHP unit connected by means of a thermal micro-grid to different users in “load sharing mode” can obtain a high number of operating hours as well as significant energy (Primary Energy Saving) and environmental (avoided CO 2 equivalent emissions) benefits with respect to an appropriate reference system

Kinematics and load-sharing of an anterior thoracolumbar spinal reconstruction construct with PEEK rods: An in vitro biomechanical study.

Science.gov (United States)

Zhou, Ruozhou; Huang, Zhiping; Liu, Xiang; Tong, Jie; Ji, Wei; Liu, Sheting; Zhu, Qingan

2016-12-01

Polyetheretherketone rod constructs provide adequate spinal stability. Kinematics and load sharing of anterior thoracolumbar reconstruction with polyetheretherketone rods under preload remains unknown. Eight human cadaveric specimens (T11-L3) were subjected to a pure moment of 5.0Nm in flexion-extension, lateral bending and axial rotation, and flexion-extension with a compressive preload of 300N. An anterior reconstruction of L1 corpectomy was conducted with a surrogate bone graft and anterior rod constructs (polyetheretherketone or titanium rods). An axial load-cell was built in the surrogate bone graft to measure the compressive force in the graft. Range of motion, neutral zone and compressive force in the graft were compared between constructs. The polyetheretherketone rod construct resulted in more motion than the titanium rod construct, particularly in extension (P=0.011) and axial rotation (P=0.001), but less motion than the intact in all directions except in axial rotation. There was no difference in range of motion or neutral zone between constructs in flexion-extension under preload. The polyetheretherketone rod construct kept the graft compressed 52N which was similar to the titanium rod construct (63N), but allowed the graft compressed more under the preload (203N vs. 123N, P=0.003). The compressive forces fluctuated in flexion-extension without preload, but increased in flexion and decreased in extension under preload. The polyetheretherketone rod construct allowed more motion compared to the titanium rod construct, but provided stability in flexion and lateral bending without preload, and flexion and extension under preload. The anterior graft shared higher load under preload, particularly for the polyetheretherketone rod construct. The results of this study suggest that rigidity of rods in the anterior reconstruction affects kinematic behavior and load sharing. Copyright © 2016 Elsevier Ltd. All rights reserved.

Study on Stationarity of Random Load Spectrum Based on the Special Road

Science.gov (United States)

Yan, Huawen; Zhang, Weigong; Wang, Dong

2017-09-01

In the special road quality assessment method, there is a method using a wheel force sensor, the essence of this method is collecting the load spectrum of the car to reflect the quality of road. According to the definition of stochastic process, it is easy to find that the load spectrum is a stochastic process. However, the analysis method and application range of different random processes are very different, especially in engineering practice, which will directly affect the design and development of the experiment. Therefore, determining the type of a random process has important practical significance. Based on the analysis of the digital characteristics of road load spectrum, this paper determines that the road load spectrum in this experiment belongs to a stationary stochastic process, paving the way for the follow-up modeling and feature extraction of the special road.

Stochastic Averaging and Stochastic Extremum Seeking

CERN Document Server

Liu, Shu-Jun

2012-01-01

Stochastic Averaging and Stochastic Extremum Seeking develops methods of mathematical analysis inspired by the interest in reverse engineering  and analysis of bacterial  convergence by chemotaxis and to apply similar stochastic optimization techniques in other environments. The first half of the text presents significant advances in stochastic averaging theory, necessitated by the fact that existing theorems are restricted to systems with linear growth, globally exponentially stable average models, vanishing stochastic perturbations, and prevent analysis over infinite time horizon. The second half of the text introduces stochastic extremum seeking algorithms for model-free optimization of systems in real time using stochastic perturbations for estimation of their gradients. Both gradient- and Newton-based algorithms are presented, offering the user the choice between the simplicity of implementation (gradient) and the ability to achieve a known, arbitrary convergence rate (Newton). The design of algorithms...

An Improved Asymptotic Sampling Approach For Stochastic Finite Element Stiffness of a Laterally Loaded Monopile

DEFF Research Database (Denmark)

Vahdatirad, Mohammadjavad; Bayat, Mehdi; Andersen, Lars Vabbersgaard

2012-01-01

In this study a stochastic approach is conducted to obtain the horizontal and rotational stiffness of an offshore monopile foundation. A nonlinear stochastic p-y curve is integrated into a finite element scheme for calculation of the monopile response in over-consolidated clay having spatial...

Decentralized method for load sharing and power management in a hybrid single/three-phase islanded microgrid consisting of hybrid source PV/battery units

DEFF Research Database (Denmark)

Karimi, Yaser; Guerrero, Josep M.; Oraee, Hashem

2016-01-01

This paper proposes a new decentralized power management and load sharing method for a photovoltaic based, hybrid single/three-phase islanded microgrid consisting of various PV units, battery units and hybrid PV/battery units. The proposed method takes into account the available PV power...... and battery conditions of the units to share the load among them and power flow among different phases is performed automatically through three-phase units. Modified active power-frequency droop functions are used according to operating states of each unit and the frequency level is used as trigger...... for switching between the states. Efficacy of the proposed method in different load, PV generation and battery conditions is validated experimentally in a microgrid lab prototype consisted of one three-phase unit and two single-phase units....

Stochastic modelling of human exposure to food chemicals and nutrients within the "Montecarlo" project: an exploration of the influence of brand loyalty and market share on intake estimates of intense sweeteners from sugar-free soft drinks.

Science.gov (United States)

Leclercq, Catherine; Arcella, Davide; Le Donne, Cinzia; Piccinelli, Raffaela; Sette, Stefania; Soggiu, Maria Eleonora

2003-04-11

To get a more realistic view of exposure to food chemicals, risk managers are getting more interested in stochastic modelling as an alternative to deterministic approaches based on conservative assumptions. It allows to take into account all the available information in the concentration of the chemical present in foods and in food consumption patterns. Within the EC-funded "Montecarlo" project, a comprehensive set of mathematical algorithms was developed to take into account all the necessary components for stochastic modelling of a variety of food chemicals, nutrients and ingredients. An appropriate computer software is being developed. Since the concentration of food chemicals may vary among different brands of the same product, consumer behaviour with respect to brands may have an impact on exposure assessments. Numeric experiments were carried out on different ways of incorporating indicators of market share and brand loyalty in the mathematical algorithms developed within the stochastic model of exposure to intense sweeteners from sugar-free beverages. The 95th percentiles of intake were shown to vary according to the inclusion/exclusion of these indicators. The market share should be included in the model especially if the market is not equitably distributed between brands. If brand loyalty data are not available, the model may be run under theoretical scenarios.

Stochastic Extreme Load Predictions for Marine Structures

DEFF Research Database (Denmark)

Jensen, Jørgen Juncher

1999-01-01

Development of rational design criteria for marine structures requires reliable estimates for the maximum wave-induced loads the structure may encounter during its operational lifetime. The paper discusses various methods for extreme value predictions taking into account the non-linearity of the ......Development of rational design criteria for marine structures requires reliable estimates for the maximum wave-induced loads the structure may encounter during its operational lifetime. The paper discusses various methods for extreme value predictions taking into account the non......-linearity of the waves and the response. As example the wave-induced bending moment in the ship hull girder is considered....

An Approach to Stochastic Peridynamic Theory.

Energy Technology Data Exchange (ETDEWEB)

Demmie, Paul N.

2018-04-01

In many material systems, man-made or natural, we have an incomplete knowledge of geometric or material properties, which leads to uncertainty in predicting their performance under dynamic loading. Given the uncertainty and a high degree of spatial variability in properties of materials subjected to impact, a stochastic theory of continuum mechanics would be useful for modeling dynamic response of such systems. Peridynamic theory is such a theory. It is formulated as an integro- differential equation that does not employ spatial derivatives, and provides for a consistent formulation of both deformation and failure of materials. We discuss an approach to stochastic peridynamic theory and illustrate the formulation with examples of impact loading of geological materials with uncorrelated or correlated material properties. We examine wave propagation and damage to the material. The most salient feature is the absence of spallation, referred to as disorder toughness, which generalizes similar results from earlier quasi-static damage mechanics. Acknowledgements This research was made possible by the support from DTRA grant HDTRA1-08-10-BRCWM. I thank Dr. Martin Ostoja-Starzewski for introducing me to the mechanics of random materials and collaborating with me throughout and after this DTRA project.

A stochastic security approach to energy and spinning reserve scheduling considering demand response program

International Nuclear Information System (INIS)

Partovi, Farzad; Nikzad, Mehdi; Mozafari, Babak; Ranjbar, Ali Mohamad

2011-01-01

In this paper a new algorithm for allocating energy and determining the optimum amount of network active power reserve capacity and the share of generating units and demand side contribution in providing reserve capacity requirements for day-ahead market is presented. In the proposed method, the optimum amount of reserve requirement is determined based on network security set by operator. In this regard, Expected Load Not Supplied (ELNS) is used to evaluate system security in each hour. The proposed method has been implemented over the IEEE 24-bus test system and the results are compared with a deterministic security approach, which considers certain and fixed amount of reserve capacity in each hour. This comparison is done from economic and technical points of view. The promising results show the effectiveness of the proposed model which is formulated as mixed integer linear programming (MILP) and solved by GAMS software. -- Highlights: → Determination of optimal spinning reserve capacity requirement in order to satisfy desired security level set by system operator based on stochastic approach. → Scheduling energy and spinning reserve markets simultaneously. → Comparing the stochastic approach with deterministic approach to determine the advantages and disadvantages of each. → Examine the effect of demand response participation in reserve market to provide spinning reserve.

Stochastic modeling of total suspended solids (TSS) in urban areas during rain events.

Science.gov (United States)

Rossi, Luca; Krejci, Vladimir; Rauch, Wolfgang; Kreikenbaum, Simon; Fankhauser, Rolf; Gujer, Willi

2005-10-01

The load of total suspended solids (TSS) is one of the most important parameters for evaluating wet-weather pollution in urban sanitation systems. In fact, pollutants such as heavy metals, polycyclic aromatic hydrocarbons (PAHs), phosphorous and organic compounds are adsorbed onto these particles so that a high TSS load indicates the potential impact on the receiving waters. In this paper, a stochastic model is proposed to estimate the TSS load and its dynamics during rain events. Information on the various simulated processes was extracted from different studies of TSS in urban areas. The model thus predicts the probability of TSS loads arising from combined sewer overflows (CSOs) in combined sewer systems as well as from stormwater in separate sewer systems in addition to the amount of TSS retained in treatment devices in both sewer systems. The results of this TSS model illustrate the potential of the stochastic modeling approach for assessing environmental problems.

Stochastic Optimal Dispatch of Virtual Power Plant considering Correlation of Distributed Generations

Directory of Open Access Journals (Sweden)

Jie Yu

2015-01-01

Full Text Available Virtual power plant (VPP is an aggregation of multiple distributed generations, energy storage, and controllable loads. Affected by natural conditions, the uncontrollable distributed generations within VPP, such as wind and photovoltaic generations, are extremely random and relative. Considering the randomness and its correlation of uncontrollable distributed generations, this paper constructs the chance constraints stochastic optimal dispatch of VPP including stochastic variables and its random correlation. The probability distributions of independent wind and photovoltaic generations are described by empirical distribution functions, and their joint probability density model is established by Frank-copula function. And then, sample average approximation (SAA is applied to convert the chance constrained stochastic optimization model into a deterministic optimization model. Simulation cases are calculated based on the AIMMS. Simulation results of this paper mathematic model are compared with the results of deterministic optimization model without stochastic variables and stochastic optimization considering stochastic variables but not random correlation. Furthermore, this paper analyzes how SAA sampling frequency and the confidence level influence the results of stochastic optimization. The numerical example results show the effectiveness of the stochastic optimal dispatch of VPP considering the randomness and its correlations of distributed generations.

Decomposition and (importance) sampling techniques for multi-stage stochastic linear programs

Energy Technology Data Exchange (ETDEWEB)

Infanger, G.

1993-11-01

The difficulty of solving large-scale multi-stage stochastic linear programs arises from the sheer number of scenarios associated with numerous stochastic parameters. The number of scenarios grows exponentially with the number of stages and problems get easily out of hand even for very moderate numbers of stochastic parameters per stage. Our method combines dual (Benders) decomposition with Monte Carlo sampling techniques. We employ importance sampling to efficiently obtain accurate estimates of both expected future costs and gradients and right-hand sides of cuts. The method enables us to solve practical large-scale problems with many stages and numerous stochastic parameters per stage. We discuss the theory of sharing and adjusting cuts between different scenarios in a stage. We derive probabilistic lower and upper bounds, where we use importance path sampling for the upper bound estimation. Initial numerical results turned out to be promising.

Designing time-of-use program based on stochastic security constrained unit commitment considering reliability index

International Nuclear Information System (INIS)

Nikzad, Mehdi; Mozafari, Babak; Bashirvand, Mahdi; Solaymani, Soodabeh; Ranjbar, Ali Mohamad

2012-01-01

Recently in electricity markets, a massive focus has been made on setting up opportunities for participating demand side. Such opportunities, also known as demand response (DR) options, are triggered by either a grid reliability problem or high electricity prices. Two important challenges that market operators are facing are appropriate designing and reasonable pricing of DR options. In this paper, time-of-use program (TOU) as a prevalent time-varying program is modeled linearly based on own and cross elasticity definition. In order to decide on TOU rates, a stochastic model is proposed in which the optimum TOU rates are determined based on grid reliability index set by the operator. Expected Load Not Supplied (ELNS) is used to evaluate reliability of the power system in each hour. The proposed stochastic model is formulated as a two-stage stochastic mixed-integer linear programming (SMILP) problem and solved using CPLEX solver. The validity of the method is tested over the IEEE 24-bus test system. In this regard, the impact of the proposed pricing method on system load profile; operational costs and required capacity of up- and down-spinning reserve as well as improvement of load factor is demonstrated. Also the sensitivity of the results to elasticity coefficients is investigated. -- Highlights: ► Time-of-use demand response program is linearly modeled. ► A stochastic model is proposed to determine the optimum TOU rates based on ELNS index set by the operator. ► The model is formulated as a short-term two-stage stochastic mixed-integer linear programming problem.

On the Reliability of Optimization Results for Trigeneration Systems in Buildings, in the Presence of Price Uncertainties and Erroneous Load Estimation

Directory of Open Access Journals (Sweden)

Antonio Piacentino

2016-12-01

Full Text Available Cogeneration and trigeneration plants are widely recognized as promising technologies for increasing energy efficiency in buildings. However, their overall potential is scarcely exploited, due to the difficulties in achieving economic viability and the risk of investment related to uncertainties in future energy loads and prices. Several stochastic optimization models have been proposed in the literature to account for uncertainties, but these instruments share in a common reliance on user-defined probability functions for each stochastic parameter. Being such functions hard to predict, in this paper an analysis of the influence of erroneous estimation of the uncertain energy loads and prices on the optimal plant design and operation is proposed. With reference to a hotel building, a number of realistic scenarios is developed, exploring all the most frequent errors occurring in the estimation of energy loads and prices. Then, profit-oriented optimizations are performed for the examined scenarios, by means of a deterministic mixed integer linear programming algorithm. From a comparison between the achieved results, it emerges that: (i the plant profitability is prevalently influenced by the average “spark-spread” (i.e., ratio between electricity and fuel price and, secondarily, from the shape of the daily price profiles; (ii the “optimal sizes” of the main components are scarcely influenced by the daily load profiles, while they are more strictly related with the average “power to heat” and “power to cooling” ratios of the building.

Simplified rotor load models and fatigue damage estimates for offshore wind turbines.

Science.gov (United States)

Muskulus, M

2015-02-28

The aim of rotor load models is to characterize and generate the thrust loads acting on an offshore wind turbine. Ideally, the rotor simulation can be replaced by time series from a model with a few parameters and state variables only. Such models are used extensively in control system design and, as a potentially new application area, structural optimization of support structures. Different rotor load models are here evaluated for a jacket support structure in terms of fatigue lifetimes of relevant structural variables. All models were found to be lacking in accuracy, with differences of more than 20% in fatigue load estimates. The most accurate models were the use of an effective thrust coefficient determined from a regression analysis of dynamic thrust loads, and a novel stochastic model in state-space form. The stochastic model explicitly models the quasi-periodic components obtained from rotational sampling of turbulent fluctuations. Its state variables follow a mean-reverting Ornstein-Uhlenbeck process. Although promising, more work is needed on how to determine the parameters of the stochastic model and before accurate lifetime predictions can be obtained without comprehensive rotor simulations. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Stochastic Unit Commitment Based on Multi-Scenario Tree Method Considering Uncertainty

Directory of Open Access Journals (Sweden)

Kyu-Hyung Jo

2018-03-01

Full Text Available With the increasing penetration of renewable energy, it is difficult to schedule unit commitment (UC in a power system because of the uncertainty associated with various factors. In this paper, a new solution procedure based on a multi-scenario tree method (MSTM is presented and applied to the proposed stochastic UC problem. In this process, the initial input data of load and wind power are modeled as different levels using the mean absolute percentage error (MAPE. The load and wind scenarios are generated using Monte Carlo simulation (MCS that considers forecasting errors. These multiple scenarios are applied in the MSTM for solving the stochastic UC problem, including not only the load and wind power uncertainties, but also sudden outages of the thermal unit. When the UC problem has been formulated, the simulation is conducted for 24-h period by using the short-term UC model, and the operating costs and additional reserve requirements are thus obtained. The effectiveness of the proposed solution approach is demonstrated through a case study based on a modified IEEE-118 bus test system.

Stochastic simulation of off-shore oil terminal systems

International Nuclear Information System (INIS)

Frankel, E.G.; Oberle, J.

1991-01-01

To cope with the problem of uncertainty and conditionality in the planning, design, and operation of offshore oil transshipment terminal systems, a conditional stochastic simulation approach is presented. Examples are shown, using SLAM II, a computer simulation language based on GERT, a conditional stochastic network analysis methodology in which use of resources such as time and money are expressed by the moment generating function of the statistics of the resource requirements. Similarly each activity has an associated conditional probability of being performed and/or of requiring some of the resources. The terminal system is realistically represented by modelling the statistics of arrivals, loading and unloading times, uncertainties in costs and availabilities, etc

Stochastic Analysis 2010

CERN Document Server

Crisan, Dan

2011-01-01

"Stochastic Analysis" aims to provide mathematical tools to describe and model high dimensional random systems. Such tools arise in the study of Stochastic Differential Equations and Stochastic Partial Differential Equations, Infinite Dimensional Stochastic Geometry, Random Media and Interacting Particle Systems, Super-processes, Stochastic Filtering, Mathematical Finance, etc. Stochastic Analysis has emerged as a core area of late 20th century Mathematics and is currently undergoing a rapid scientific development. The special volume "Stochastic Analysis 2010" provides a sa

Lifetime distribution in thermal fatigue - a stochastic geometry approach

International Nuclear Information System (INIS)

Kullig, E.; Michel, B.

1996-02-01

The present report describes the interpretation approach for crack patterns which are generated on the smooth surface of austenitic specimens under thermal fatigue loading. A framework for the fracture mechanics characterization of equibiaxially loaded branched surface cracks is developed which accounts also for crack interaction effects. Advanced methods for the statistical evaluation of crack patterns using suitable characteristic quantities are developed. An efficient simulation procedure allows to identify the impact of different variables of the stochastic crack growth model with respect to the generated crack patterns. (orig.) [de

Decentralized Method for Load Sharing and Power Management in a Hybrid Single/Three-Phase-Islanded Microgrid Consisting of Hybrid Source PV/Battery Units

DEFF Research Database (Denmark)

Karimi, Yaser; Oraee, Hashem; Guerrero, Josep M.

2017-01-01

This paper proposes a new decentralized power management and load sharing method for a photovoltaic based, hybrid single/three-phase islanded microgrid consisting of various PV units, battery units and hybrid PV/battery units. The proposed method is not limited to the systems with separate PV...... in different load, PV generation and battery conditions is validated experimentally in a microgrid lab prototype consisted of one three-phase unit and two single-phase units....

Stochastic petri nets for wireless networks

CERN Document Server

Lei, Lei; Zhong, Zhangdui

2015-01-01

This SpringerBrief presents research in the application of Stochastic Petri Nets (SPN) to the performance evaluation of wireless networks under bursty traffic. It covers typical Quality-of-Service performance metrics such as mean throughput, average delay and packet dropping probability. Along with an introduction of SPN basics, the authors introduce the key motivation and challenges of using SPN to analyze the resource sharing performance in wireless networks. The authors explain two powerful modeling techniques that treat the well-known state space explosion problem: model decomposition and

Comparison of optimization of loading patterns on the basis of SA and PMA algorithms

International Nuclear Information System (INIS)

Beliczai, Botond

2007-01-01

Optimization of loading patterns is a very important task from economical point of view in a nuclear power plant. The optimization algorithms used for this purpose can be categorized basically into two categories: deterministic ones and stochastic ones. In the Paks nuclear power plant a deterministic optimization procedure is used to optimize the loading pattern at BOC, so that the core would have maximal reactivity reserve. To the group of stochastic optimization procedures belong mainly simulated annealing (SA) procedures and genetic algorithms (GA). There are new procedures as well, which try to combine the advantages of SAs and GAs. One of them is called population mutation annealing algorithm (PMA). In the Paks NPP we would like to introduce fuel assemblies including burnable poison (Gd) in the near future. In order to be able to find the optimal loading pattern (or near-optimal loading patterns) in that case, we have to optimize our core not only for objective functions defined at BOC, but at EOC as well. For this purpose I used stochastic algorithms (SA and PMA) to investigate loading pattern optimization results for different objective functions at BOC. (author)

Stochastic and non-stochastic effects - a conceptual analysis

International Nuclear Information System (INIS)

Karhausen, L.R.

1980-01-01

The attempt to divide radiation effects into stochastic and non-stochastic effects is discussed. It is argued that radiation or toxicological effects are contingently related to radiation or chemical exposure. Biological effects in general can be described by general laws but these laws never represent a necessary connection. Actually stochastic effects express contingent, or empirical, connections while non-stochastic effects represent semantic and non-factual connections. These two expressions stem from two different levels of discourse. The consequence of this analysis for radiation biology and radiation protection is discussed. (author)

Constructive role of Brownian motion: Brownian motors and Stochastic Resonance

Science.gov (United States)

Hänggi, Peter

2005-03-01

Noise is usually thought of as the enemy of order rather as a constructive influence. For the phenomena of Stochastic Resonance [1] and Brownian motors [2], however, stochastic noise can play a beneficial role in enhancing detection and/or facilitating directed transmission of information in absence of biasing forces. Brownian motion assisted Stochastic Resonance finds useful applications in physical, technological, biological and biomedical contexts [1,3]. The basic principles that underpin Stochastic Resonance are elucidated and novel applications for nonlinear classical and quantum systems will be addressed. The presence of non-equilibrium disturbances enables to rectify Brownian motion so that quantum and classical objects can be directed around on a priori designed routes in biological and physical systems (Brownian motors). In doing so, the energy from the haphazard motion of (quantum) Brownian particles is extracted to perform useful work against an external load. This very concept together with first experimental realizations are discussed [2,4,5]. [1] L. Gammaitoni, P. Hä'nggi, P. Jung and F. Marchesoni, Stochastic Resonance, Rev. Mod. Phys. 70, 223 (1998).[2] R. D. Astumian and P. Hä'nggi, Brownian motors, Physics Today 55 (11), 33 (2002).[3] P. Hä'nggi, Stochastic Resonace in Physics and Biology, ChemPhysChem 3, 285 (2002).[4] H. Linke, editor, Special Issue on Brownian Motors, Applied Physics A 75, No. 2 (2002).[5] P. Hä'nggi, F. Marchesoni, F. Nori, Brownian motors, Ann. Physik (Leipzig) 14, xxx (2004); cond-mat/0410033.

A Shared Scratchpad Memory with Synchronization Support

DEFF Research Database (Denmark)

Hansen, Henrik Enggaard; Maroun, Emad Jacob; Kristensen, Andreas Toftegaard

2017-01-01

Multicore processors usually communicate via shared memory, which is backed up by a shared level 2 cache and a cache coherence protocol. However, this solution is not a good fit for real-time systems, where we need to provide tight guarantees on execution and memory access times. In this paper, we...... propose a shared scratchpad memory as a time-predictable communication and synchronization structure, instead of the level 2 cache. The shared on-chip memory is accessed via a time division multiplexing arbiter, isolating the execution time of load and store instructions between processing cores....... Furthermore, the arbiter supports an extended time slot where an atomic load and store instruction can be executed to implement synchronization primitives. In the evaluation we show that a shared scratchpad memory is an efficient communication structure for a small number of processors; in our setup, 9 cores...

Wind Structure and Wind Loading

DEFF Research Database (Denmark)

Brorsen, Michael

The purpose of this note is to provide a short description of wind, i.e. of the flow in the atmosphere of the Earth and the loading caused by wind on structures. The description comprises: causes to the generation of windhe interaction between wind and the surface of the Earthhe stochastic nature...

Serviceability design load factors and reliability assessments for reinforced concrete containment structures

International Nuclear Information System (INIS)

Han Bong Koo

1998-01-01

A reinforced concrete nuclear power plant containment structure is subjected to various random static and stochastic loads during its lifetime. Since these loads involve inherent randomness and other uncertainties, an appropriate probabilistic model for each load must be established in order to perform reliability analysis. The current ASME code for reinforced concrete containment structures are not based on probability concepts. The stochastic nature of natural hazard or accidental loads and the variations of material properties require a probabilistic approach for a rational assessment of structural safety and performance. The paper develops probability-based load factors for the limit state design of reinforced concrete containment structures. The purpose of constructing reinforced concrete containment structure is to protect against radioactive release, and so the use of a serviceability limit state against crack failure that can cause the emission of radioactive materials is suggested as a critical limit state for reinforced concrete containment structures. Load factors for the design of reinforced concrete containment structures are proposed and carried out the reliability assessments. (orig.)

Biomechanical validation of load-sharing rip-stop fixation for the repair of tissue-deficient rotator cuff tears.

Science.gov (United States)

Burkhart, Stephen S; Denard, Patrick J; Konicek, John; Hanypsiak, Bryan T

2014-02-01

Poor-quality tendon is one of the most difficult problems the surgeon must overcome in achieving secure fixation during rotator cuff repair. A load-sharing rip-stop construct (LSRS) has recently been proposed as a method for improving fixation strength, but the biomechanical properties of this construct have not yet been examined. To compare the strength of the LSRS construct to that of single-row fixation for rotator cuff repair. Controlled laboratory study. Rotator cuff tears were created in 6 cadaveric matched-pair specimens and repaired with a single row or an LSRS. In the LSRS repair, a 2-mm suture tape was placed as an inverted mattress stitch in the rotator cuff, and sutures from 2 anchors were placed as simple stitches that passed medial to the suture tape. The suture tape limbs were secured with knotless anchors laterally before sutures were tied from the medial anchors. Displacement was observed with video tracking after cyclic loading, and specimens were loaded to failure. The mean load to failure was 371 ± 102 N in single-row repairs compared with 616 ± 185 N in LSRS repairs (P = .031). There was no difference in displacement with cyclic loading between the groups (3.3 ± 0.8 mm vs. 3.5 ± 1.1 mm; P = .561). In the single-row group, 4 of 6 failures occurred at the suture-tendon interface. In the LSRS group, only 1 failure occurred at the suture-tendon interface. The ultimate failure load of the LSRS construct for rotator cuff repair was 1.7 times that of a single-row construct in a cadaveric model. The LSRS rotator cuff repair construct may be useful in the repair of difficult tears such as massive tears, medial tears, and tears with tendon loss.

Attention and Visuospatial Working Memory Share the Same Processing Resources

Directory of Open Access Journals (Sweden)

Jing eFeng

2012-04-01

Full Text Available Attention and visuospatial working memory (VWM share very similar characteristics; both have the same upper bound of about four items in capacity and they recruit overlapping brain regions. We examined whether both attention and visuospatial working memory share the same processing resources using a novel dual-task-costs approach based on a load-varying dual-task technique. With sufficiently large loads on attention and VWM, considerable interference between the two processes was observed. A further load increase on either process produced reciprocal increases in interference on both processes, indicating that attention and VWM share common resources. More critically, comparison among four experiments on the reciprocal interference effects, as measured by the dual-task costs, demonstrates no significant contribution from additional processing other than the shared processes. These results support the notion that attention and VWM share the same processing resources.

Stochastic modeling of reinforced concrete structures exposed to chloride attack

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard; Frier, Christian

2004-01-01

For many reinforced concrete structures corrosion of reinforcement is an important problem since it can result in expensive maintenance and repair actions. Further, a significant reduction of the load-bearing capacity can occur. One mode of corrosion initiation is that the chloride content around...... concentration and reinforcement cover depth are modeled by stochastic fields. The paper contains a description of the parameters to be included in a stochastic model and a proposal for the information needed to obtain values for the parameters in order to be able to perform reliability investigations....... The distribution of the time to initiation of corrosion is estimated by simulation. As an example a bridge pier in a marine environment is considered....

Stochastic Modeling of Reinforced Concrete Structures Exposed to Chloride Attack

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard; Frier, Christian

2003-01-01

For many reinforced concrete structures corrosion of reinforcement is an important problem since it can result in expensive maintenance and repair actions. Further, a significant reduction of the load-bearing capacity can occur. One mode of corrosion initiation is that the chloride content around...... concentration and reinforcement cover depth are modeled by stochastic fields. The paper contains a description of the parameters to be included in a stochastic model and a proposal for the information needed to obtain values for the parameters in order to be ab le to perform reliability investigations....... The distribution of the time to initiation of corrosion is estimated by simulation. As an example a bridge pier in a marine environment is considered....

Control of open end plasma flow utilizing orbital stochasticity

International Nuclear Information System (INIS)

Hojo, Hitoshi

1995-01-01

It has been known that the control of plasma outside the confinement region of diverter plasma and others in a magnetic field confinement device is very important for improveing the confinement of bulk plasma. The control of plasma outside a confinement region bears two roles, one is the reduction of the thermal load on a diverter plate and others due to the plasma particles lost from the confinement region, and another is the restriction of the back flow of cold plasma and impurities generated outside the confinement region to a bulk plasma region. In this study, the new method of controlling plasma outside a confinement region called magnetic diverter is considered. To the plasma particles advancing along magnetic force lines, the reflection and capture of the plasma particles occur in the region of orbital stochasticity, and the thermal load on an end plate and the reverse flow to a bulk plasma region are restricted. The numerical computation model used regarding the particle control utilizing the orbital stochasticity and the results of calculating the orbit of plasma particles in a magnetic field are reported. (K.I.)

Committee VI.1. Extreme Hull Girder Loading

DEFF Research Database (Denmark)

Jensen, Jørgen Juncher

2000-01-01

Committee Mandate. Evaluate and develop direct calculation procedures for extreme wawe loads on ship hull girders. Due consideration shall be given to stochastic and non-linear effects. The procedures shall be assessed by comparison with in-service experiences, model tests and more refined...

On a model for the prediction of the friction coefficient in mixed lubrication based on a load-sharing concapt with measured surface roughness

NARCIS (Netherlands)

Akchurin, Aydar; Bosman, Rob; Lugt, Pieter Martin; van Drogen, Mark

2015-01-01

A new model was developed for the simulation of the friction coefficient in lubricated sliding line contacts. A half-space-based contact algorithm was linked with a numerical elasto-hydrodynamic lubrication solver using the load-sharing concept. The model was compared with an existing asperity-based

The optimization model for multi-type customers assisting wind power consumptive considering uncertainty and demand response based on robust stochastic theory

International Nuclear Information System (INIS)

Tan, Zhongfu; Ju, Liwei; Reed, Brent; Rao, Rao; Peng, Daoxin; Li, Huanhuan; Pan, Ge

2015-01-01

Highlights: • Our research focuses on demand response behaviors of multi-type customers. • A wind power simulation method is proposed based on the Brownian motion theory. • Demand response revenue functions are proposed for multi-type customers. • A robust stochastic optimization model is proposed for wind power consumptive. • Models are built to measure the impacts of demand response on wind power consumptive. - Abstract: In order to relieve the influence of wind power uncertainty on power system operation, demand response and robust stochastic theory are introduced to build a stochastic scheduling optimization model. Firstly, this paper presents a simulation method for wind power considering external environment based on Brownian motion theory. Secondly, price-based demand response and incentive-based demand response are introduced to build demand response model. Thirdly, the paper constructs the demand response revenue functions for electric vehicle customers, business customers, industry customers and residential customers. Furthermore, robust stochastic optimization theory is introduced to build a wind power consumption stochastic optimization model. Finally, simulation analysis is taken in the IEEE 36 nodes 10 units system connected with 650 MW wind farms. The results show the robust stochastic optimization theory is better to overcome wind power uncertainty. Demand response can improve system wind power consumption capability. Besides, price-based demand response could transform customers’ load demand distribution, but its load curtailment capacity is not as obvious as incentive-based demand response. Since price-based demand response cannot transfer customer’s load demand as the same as incentive-based demand response, the comprehensive optimization effect will reach best when incentive-based demand response and price-based demand response are both introduced.

Noncausal stochastic calculus

CERN Document Server

Ogawa, Shigeyoshi

2017-01-01

This book presents an elementary introduction to the theory of noncausal stochastic calculus that arises as a natural alternative to the standard theory of stochastic calculus founded in 1944 by Professor Kiyoshi Itô. As is generally known, Itô Calculus is essentially based on the "hypothesis of causality", asking random functions to be adapted to a natural filtration generated by Brownian motion or more generally by square integrable martingale. The intention in this book is to establish a stochastic calculus that is free from this "hypothesis of causality". To be more precise, a noncausal theory of stochastic calculus is developed in this book, based on the noncausal integral introduced by the author in 1979. After studying basic properties of the noncausal stochastic integral, various concrete problems of noncausal nature are considered, mostly concerning stochastic functional equations such as SDE, SIE, SPDE, and others, to show not only the necessity of such theory of noncausal stochastic calculus but ...

An efficient scenario-based stochastic programming framework for multi-objective optimal micro-grid operation

International Nuclear Information System (INIS)

Niknam, Taher; Azizipanah-Abarghooee, Rasoul; Narimani, Mohammad Rasoul

2012-01-01

Highlights: ► Proposes a stochastic model for optimal energy management. ► Consider uncertainties related to the forecasted values for load demand. ► Consider uncertainties of forecasted values of output power of wind and photovoltaic units. ► Consider uncertainties of forecasted values of market price. ► Present an improved multi-objective teaching–learning-based optimization. -- Abstract: This paper proposes a stochastic model for optimal energy management with the goal of cost and emission minimization. In this model, the uncertainties related to the forecasted values for load demand, available output power of wind and photovoltaic units and market price are modeled by a scenario-based stochastic programming. In the presented method, scenarios are generated by a roulette wheel mechanism based on probability distribution functions of the input random variables. Through this method, the inherent stochastic nature of the proposed problem is released and the problem is decomposed into a deterministic problem. An improved multi-objective teaching–learning-based optimization is implemented to yield the best expected Pareto optimal front. In the proposed stochastic optimization method, a novel self adaptive probabilistic modification strategy is offered to improve the performance of the presented algorithm. Also, a set of non-dominated solutions are stored in a repository during the simulation process. Meanwhile, the size of the repository is controlled by usage of a fuzzy-based clustering technique. The best expected compromise solution stored in the repository is selected via the niching mechanism in a way that solutions are encouraged to seek the lesser explored regions. The proposed framework is applied in a typical grid-connected micro grid in order to verify its efficiency and feasibility.

Sojourn time asymptotics in Processor Sharing queues with varying service rate

NARCIS (Netherlands)

Egorova, R.; Mandjes, M.R.H.; Zwart, B.

2007-01-01

Abstract This paper addresses the sojourn time asymptotics for a GI/GI/⋅ queue operating under the Processor Sharing (PS) discipline with stochastically varying service rate. Our focus is on the logarithmic estimates of the tail of sojourn-time distribution, under the assumption that the job-size

Toward Isolation of Salient Features in Stable Boundary Layer Wind Fields that Influence Loads on Wind Turbines

Directory of Open Access Journals (Sweden)

Jinkyoo Park

2015-04-01

Full Text Available Neutral boundary layer (NBL flow fields, commonly used in turbine load studies and design, are generated using spectral procedures in stochastic simulation. For large utility-scale turbines, stable boundary layer (SBL flow fields are of great interest because they are often accompanied by enhanced wind shear, wind veer, and even low-level jets (LLJs. The generation of SBL flow fields, in contrast to simpler stochastic simulation for NBL, requires computational fluid dynamics (CFD procedures to capture the physics and noted characteristics—such as shear and veer—that are distinct from those seen in NBL flows. At present, large-eddy simulation (LES is the most efficient CFD procedure for SBL flow field generation and related wind turbine loads studies. Design standards, such as from the International Electrotechnical Commission (IEC, provide guidance albeit with simplifying assumptions (one such deals with assuming constant variance of turbulence over the rotor and recommend standard target turbulence power spectra and coherence functions to allow NBL flow field simulation. In contrast, a systematic SBL flow field simulation procedure has not been offered for design or for site assessment. It is instructive to compare LES-generated SBL flow fields with stochastic NBL flow fields and associated loads which we evaluate for a 5-MW turbine; in doing so, we seek to isolate distinguishing characteristics of wind shear, wind veer, and turbulence variation over the rotor plane in the alternative flow fields and in the turbine loads. Because of known differences in NBL-stochastic and SBL-LES wind fields but an industry preference for simpler stochastic simulation in design practice, this study investigates if one can reproduce stable atmospheric conditions using stochastic approaches with appropriate corrections for shear, veer, turbulence, etc. We find that such simple tuning cannot consistently match turbine target SBL load statistics, even though

HSimulator: Hybrid Stochastic/Deterministic Simulation of Biochemical Reaction Networks

Directory of Open Access Journals (Sweden)

Luca Marchetti

2017-01-01

Full Text Available HSimulator is a multithread simulator for mass-action biochemical reaction systems placed in a well-mixed environment. HSimulator provides optimized implementation of a set of widespread state-of-the-art stochastic, deterministic, and hybrid simulation strategies including the first publicly available implementation of the Hybrid Rejection-based Stochastic Simulation Algorithm (HRSSA. HRSSA, the fastest hybrid algorithm to date, allows for an efficient simulation of the models while ensuring the exact simulation of a subset of the reaction network modeling slow reactions. Benchmarks show that HSimulator is often considerably faster than the other considered simulators. The software, running on Java v6.0 or higher, offers a simulation GUI for modeling and visually exploring biological processes and a Javadoc-documented Java library to support the development of custom applications. HSimulator is released under the COSBI Shared Source license agreement (COSBI-SSLA.

Stochastic-Strength-Based Damage Simulation Tool for Ceramic Matrix Composite

Science.gov (United States)

Nemeth, Noel; Bednarcyk, Brett; Pineda, Evan; Arnold, Steven; Mital, Subodh; Murthy, Pappu

2015-01-01

Reported here is a coupling of two NASA developed codes: CARES (Ceramics Analysis and Reliability Evaluation of Structures) with the MAC/GMC (Micromechanics Analysis Code/ Generalized Method of Cells) composite material analysis code. The resulting code is called FEAMAC/CARES and is constructed as an Abaqus finite element analysis UMAT (user defined material). Here we describe the FEAMAC/CARES code and an example problem (taken from the open literature) of a laminated CMC in off-axis loading is shown. FEAMAC/CARES performs stochastic-strength-based damage simulation response of a CMC under multiaxial loading using elastic stiffness reduction of the failed elements.

Assessing Knowledge Sharing Among Academics: A Validation of the Knowledge Sharing Behavior Scale (KSBS).

Science.gov (United States)

Ramayah, T; Yeap, Jasmine A L; Ignatius, Joshua

2014-04-01

There is a belief that academics tend to hold on tightly to their knowledge and intellectual resources. However, not much effort has been put into the creation of a valid and reliable instrument to measure knowledge sharing behavior among the academics. To apply and validate the Knowledge Sharing Behavior Scale (KSBS) as a measure of knowledge sharing behavior within the academic community. Respondents (N = 447) were academics from arts and science streams in 10 local, public universities in Malaysia. Data were collected using the 28-item KSBS that assessed four dimensions of knowledge sharing behavior namely written contributions, organizational communications, personal interactions, and communities of practice. The exploratory factor analysis showed that the items loaded on the dimension constructs that they were supposed to represent, thus proving construct validity. A within-factor analysis revealed that each set of items representing their intended dimension loaded on only one construct, therefore establishing convergent validity. All four dimensions were not perfectly correlated with each other or organizational citizenship behavior, thereby proving discriminant validity. However, all four dimensions correlated with organizational commitment, thus confirming predictive validity. Furthermore, all four factors correlated with both tacit and explicit sharing, which confirmed their concurrent validity. All measures also possessed sufficient reliability (α > .70). The KSBS is a valid and reliable instrument that can be used to formally assess the types of knowledge artifacts residing among academics and the degree of knowledge sharing in relation to those artifacts. © The Author(s) 2014.

A Simulation-Based Dynamic Stochastic Route Choice Model for Evacuation

Directory of Open Access Journals (Sweden)

Xing Zhao

2012-01-01

Full Text Available This paper establishes a dynamic stochastic route choice model for evacuation to simulate the propagation process of traffic flow and estimate the stochastic route choice under evacuation situations. The model contains a lane-group-based cell transmission model (CTM which sets different traffic capacities for links with different turning movements to flow out in an evacuation situation, an actual impedance model which is to obtain the impedance of each route in time units at each time interval and a stochastic route choice model according to the probit-based stochastic user equilibrium. In this model, vehicles loading at each origin at each time interval are assumed to choose an evacuation route under determinate road network, signal design, and OD demand. As a case study, the proposed model is validated on the network nearby Nanjing Olympic Center after the opening ceremony of the 10th National Games of the People's Republic of China. The traffic volumes and clearing time at five exit points of the evacuation zone are calculated by the model to compare with survey data. The results show that this model can appropriately simulate the dynamic route choice and evolution process of the traffic flow on the network in an evacuation situation.

Fuzzy Stochastic Unit Commitment Model with Wind Power and Demand Response under Conditional Value-At-Risk Assessment

Directory of Open Access Journals (Sweden)

Jiafu Yin

2018-02-01

Full Text Available With the increasing penetration of wind power and demand response integrated into the grid, the combined uncertainties from wind power and demand response have been a challenging concern for system operators. It is necessary to develop an approach to accommodate the combined uncertainties in the source side and load side. In this paper, the fuzzy stochastic conditional value-at-risk criterions are proposed as the risk measure of the combination of both wind power uncertainty and demand response uncertainty. To improve the computational tractability without sacrificing the accuracy, the fuzzy stochastic chance-constrained goal programming is proposed to transfer the fuzzy stochastic conditional value-at-risk to a deterministic equivalent. The operational risk of forecast error under fuzzy stochastic conditional value-at-risk assessment is represented by the shortage of reserve resource, which can be further divided into the load-shedding risk and the wind curtailment risk. To identify different priority levels for the different objective functions, the three-stage day-ahead unit commitment model is proposed through preemptive goal programming, in which the reliability requirement has the priority over the economic operation. Finally, a case simulation is performed on the IEEE 39-bus system to verify the effectiveness and efficiency of the proposed model.

Fat versus Thin Threading Approach on GPUs: Application to Stochastic Simulation of Chemical Reactions

KAUST Repository

Klingbeil, Guido; Erban, Radek; Giles, Mike; Maini, Philip K.

2012-01-01

We explore two different threading approaches on a graphics processing unit (GPU) exploiting two different characteristics of the current GPU architecture. The fat thread approach tries to minimize data access time by relying on shared memory and registers potentially sacrificing parallelism. The thin thread approach maximizes parallelism and tries to hide access latencies. We apply these two approaches to the parallel stochastic simulation of chemical reaction systems using the stochastic simulation algorithm (SSA) by Gillespie [14]. In these cases, the proposed thin thread approach shows comparable performance while eliminating the limitation of the reaction system's size. © 2006 IEEE.

Fat versus Thin Threading Approach on GPUs: Application to Stochastic Simulation of Chemical Reactions

KAUST Repository

Klingbeil, Guido

2012-02-01

We explore two different threading approaches on a graphics processing unit (GPU) exploiting two different characteristics of the current GPU architecture. The fat thread approach tries to minimize data access time by relying on shared memory and registers potentially sacrificing parallelism. The thin thread approach maximizes parallelism and tries to hide access latencies. We apply these two approaches to the parallel stochastic simulation of chemical reaction systems using the stochastic simulation algorithm (SSA) by Gillespie [14]. In these cases, the proposed thin thread approach shows comparable performance while eliminating the limitation of the reaction system\\'s size. © 2006 IEEE.

Urn model for products’ shares in international trade

Science.gov (United States)

Barbier, Matthieu; Lee, D.-S.

2017-12-01

International trade fluxes evolve as countries revise their portfolios of trade products towards economic development. Accordingly products’ shares in international trade vary with time, reflecting the transfer of capital between distinct industrial sectors. Here we analyze the share of hundreds of product categories in world trade for four decades and find a scaling law obeyed by the annual variation of product share, which informs us of how capital flows and interacts over the product space. A model of stochastic transfer of capital between products based on the observed scaling relation is proposed and shown to reproduce exactly the empirical share distribution. The model allows analytic solutions as well as numerical simulations, which predict a pseudo-condensation of capital onto few product categories and when it will occur. At the individual level, our model finds certain products unpredictable, the excess or deficient growth of which with respect to the model prediction is shown to be correlated with the nature of goods.

Letter to the Editor: Electric Vehicle Demand Model for Load Flow Studies

DEFF Research Database (Denmark)

Garcia-Valle, Rodrigo; Vlachogiannis, Ioannis (John)

2009-01-01

This paper introduces specific and simple model for electric vehicles suitable for load flow studies. The electric vehicles demand system is modelled as PQ bus with stochastic characteristics based on the concept of queuing theory. All appropriate variables of stochastic PQ buses are given...... with closed formulae as a function of charging time. Specific manufacturer model of electric vehicles is used as study case....

Reduced-complexity adaptive multi-channel assignment for shared access points in over-loaded small-cell networks

KAUST Repository

Radaydeh, Redha Mahmoud

2013-06-01

This paper proposes a reduced-complexity downlink multi-channel assignment scheme when feedback links are capacity-limited. The system model treats the case when multiple access points are allocated to serve scheduled users in over-loaded (i.e. dense) pico/femtocell networks. It assumes that the deployed access points can be shared simultaneously and employ isotropic antenna arrays of arbitrary sizes. Moreover, they transmit their data on a common physical channel and can not coordinate their transmissions. On the other hand, each scheduled user can be served by single transmit channel from each active access point at a time, and it lacks coordination with concurrent active users. The scheme operates according to the occupancy of available transmit channels, wherein extensively occupied access points are avoided adaptively, while reducing the load of processing. The operation is linked to a target performance via controlling the observed aggregate interference from the projected set of serving points. Through the analysis, results for the scheduled user outage performance, and the average number of active access points are presented. Numerical and simulations studies clarify the gains of the proposed scheme for different operating conditions. © 2013 IEEE.

Reduced-complexity adaptive multi-channel assignment for shared access points in over-loaded small-cell networks

KAUST Repository

Radaydeh, Redha Mahmoud; Qaraqe, Khalid A.; Alouini, Mohamed-Slim

2013-01-01

This paper proposes a reduced-complexity downlink multi-channel assignment scheme when feedback links are capacity-limited. The system model treats the case when multiple access points are allocated to serve scheduled users in over-loaded (i.e. dense) pico/femtocell networks. It assumes that the deployed access points can be shared simultaneously and employ isotropic antenna arrays of arbitrary sizes. Moreover, they transmit their data on a common physical channel and can not coordinate their transmissions. On the other hand, each scheduled user can be served by single transmit channel from each active access point at a time, and it lacks coordination with concurrent active users. The scheme operates according to the occupancy of available transmit channels, wherein extensively occupied access points are avoided adaptively, while reducing the load of processing. The operation is linked to a target performance via controlling the observed aggregate interference from the projected set of serving points. Through the analysis, results for the scheduled user outage performance, and the average number of active access points are presented. Numerical and simulations studies clarify the gains of the proposed scheme for different operating conditions. © 2013 IEEE.

STOCHASTIC FLOWS OF MAPPINGS

Institute of Scientific and Technical Information of China (English)

无

2007-01-01

In this paper, the stochastic flow of mappings generated by a Feller convolution semigroup on a compact metric space is studied. This kind of flow is the generalization of superprocesses of stochastic flows and stochastic diffeomorphism induced by the strong solutions of stochastic differential equations.

Stochastic processes

CERN Document Server

Parzen, Emanuel

1962-01-01

Well-written and accessible, this classic introduction to stochastic processes and related mathematics is appropriate for advanced undergraduate students of mathematics with a knowledge of calculus and continuous probability theory. The treatment offers examples of the wide variety of empirical phenomena for which stochastic processes provide mathematical models, and it develops the methods of probability model-building.Chapter 1 presents precise definitions of the notions of a random variable and a stochastic process and introduces the Wiener and Poisson processes. Subsequent chapters examine

Optimal design of distributed energy resource systems based on two-stage stochastic programming

International Nuclear Information System (INIS)

Yang, Yun; Zhang, Shijie; Xiao, Yunhan

2017-01-01

Highlights: • A two-stage stochastic programming model is built to design DER systems under uncertainties. • Uncertain energy demands have a significant effect on the optimal design. • Uncertain energy prices and renewable energy intensity have little effect on the optimal design. • The economy is overestimated if the system is designed without considering the uncertainties. • The uncertainty in energy prices has the significant and greatest effect on the economy. - Abstract: Multiple uncertainties exist in the optimal design of distributed energy resource (DER) systems. The expected energy, economic, and environmental benefits may not be achieved and a deficit in energy supply may occur if the uncertainties are not handled properly. This study focuses on the optimal design of DER systems with consideration of the uncertainties. A two-stage stochastic programming model is built in consideration of the discreteness of equipment capacities, equipment partial load operation and output bounds as well as of the influence of ambient temperature on gas turbine performance. The stochastic model is then transformed into its deterministic equivalent and solved. For an illustrative example, the model is applied to a hospital in Lianyungang, China. Comparative studies are performed to evaluate the effect of the uncertainties in load demands, energy prices, and renewable energy intensity separately and simultaneously on the system’s economy and optimal design. Results show that the uncertainties in load demands have a significant effect on the optimal system design, whereas the uncertainties in energy prices and renewable energy intensity have almost no effect. Results regarding economy show that it is obviously overestimated if the system is designed without considering the uncertainties.

Acid loading test (pH)

Science.gov (United States)

... this page: //medlineplus.gov/ency/article/003615.htm Acid loading test (pH) To use the sharing features on this page, please enable JavaScript. The acid loading test (pH) measures the ability of the ...

Linking agent-based models and stochastic models of financial markets.

Science.gov (United States)

Feng, Ling; Li, Baowen; Podobnik, Boris; Preis, Tobias; Stanley, H Eugene

2012-05-29

It is well-known that financial asset returns exhibit fat-tailed distributions and long-term memory. These empirical features are the main objectives of modeling efforts using (i) stochastic processes to quantitatively reproduce these features and (ii) agent-based simulations to understand the underlying microscopic interactions. After reviewing selected empirical and theoretical evidence documenting the behavior of traders, we construct an agent-based model to quantitatively demonstrate that "fat" tails in return distributions arise when traders share similar technical trading strategies and decisions. Extending our behavioral model to a stochastic model, we derive and explain a set of quantitative scaling relations of long-term memory from the empirical behavior of individual market participants. Our analysis provides a behavioral interpretation of the long-term memory of absolute and squared price returns: They are directly linked to the way investors evaluate their investments by applying technical strategies at different investment horizons, and this quantitative relationship is in agreement with empirical findings. Our approach provides a possible behavioral explanation for stochastic models for financial systems in general and provides a method to parameterize such models from market data rather than from statistical fitting.

A comparative study of failure criteria in probabilistic fields and stochastic failure envelopes of composite materials

International Nuclear Information System (INIS)

Nakayasu, Hidetoshi; Maekawa, Zen'ichiro

1997-01-01

One of the major objectives of this paper is to offer a practical tool for materials design of unidirectional composite laminates under in-plane multiaxial load. Design-oriented failure criteria of composite materials are applied to construct the evaluation model of probabilistic safety based on the extended structural reliability theory. Typical failure criteria such as maximum stress, maximum strain and quadratic polynomial failure criteria are compared from the viewpoint of reliability-oriented materials design of composite materials. The new design diagram which shows the feasible region on in-plane strain space and corresponds to safety index or failure probability is also proposed. These stochastic failure envelope diagrams which are drawn in in-plane strain space enable one to evaluate the stochastic behavior of a composite laminate with any lamination angle under multi-axial stress or strain condition. Numerical analysis for a graphite/epoxy laminate of T300/5208 is shown for the comparative verification of failure criteria under the various combinations of multi-axial load conditions and lamination angles. The stochastic failure envelopes of T300/5208 were also described in in-plane strain space

Load forecasting method considering temperature effect for distribution network

Directory of Open Access Journals (Sweden)

Meng Xiao Fang

2016-01-01

Full Text Available To improve the accuracy of load forecasting, the temperature factor was introduced into the load forecasting in this paper. This paper analyzed the characteristics of power load variation, and researched the rule of the load with the temperature change. Based on the linear regression analysis, the mathematical model of load forecasting was presented with considering the temperature effect, and the steps of load forecasting were given. Used MATLAB, the temperature regression coefficient was calculated. Using the load forecasting model, the full-day load forecasting and time-sharing load forecasting were carried out. By comparing and analyzing the forecast error, the results showed that the error of time-sharing load forecasting method was small in this paper. The forecasting method is an effective method to improve the accuracy of load forecasting.

Application of stochastic methods for wind speed forecasting and wind turbines design at the area of Thessaly, Greece

Science.gov (United States)

Dimitriadis, Panayiotis; Lazaros, Lappas; Daskalou, Olympia; Filippidou, Ariadni; Giannakou, Marianna; Gkova, Eleni; Ioannidis, Romanos; Polydera, Angeliki; Polymerou, Eleni; Psarrou, Eleftheria; Vyrini, Alexandra; Papalexiou, Simon; Koutsoyiannis, Demetris

2015-04-01

Several methods exist for estimating the statistical properties of wind speed, most of them being deterministic or probabilistic, disregarding though its long-term behaviour. Here, we focus on the stochastic nature of wind. After analyzing several historical timeseries at the area of interest (AoI) in Thessaly (Greece), we show that a Hurst-Kolmogorov (HK) behaviour is apparent. Thus, disregarding the latter could lead to unrealistic predictions and wind load situations, causing some impact on the energy production and management. Moreover, we construct a stochastic model capable of preserving the HK behaviour and we produce synthetic timeseries using a Monte-Carlo approach to estimate the future wind loads in the AoI. Finally, we identify the appropriate types of wind turbines for the AoI (based on the IEC 61400 standards) and propose several industrial solutions. Acknowledgement: This research is conducted within the frame of the undergraduate course "Stochastic Methods in Water Resources" of the National Technical University of Athens (NTUA). The School of Civil Engineering of NTUA provided moral support for the participation of the students in the Assembly.

Stochastic profit-based scheduling of industrial virtual power plant using the best demand response strategy

International Nuclear Information System (INIS)

Nosratabadi, Seyyed Mostafa; Hooshmand, Rahmat-Allah; Gholipour, Eskandar

2016-01-01

Highlights: • VPPs and IVPPs are defined for energy management of aggregated generations. • IVPP can manage industrial microgrid containing some relevant load and generation. • A stochastic modeling is proposed to schedule optimal generations in competition market. • Wind generation and day-ahead and spot market prices are considered to be stochastic. • A new DRL program selection scheme is presented in the scheduling procedure. - Abstract: One of the main classified microgrids in a power system is the industrial microgrid. Due to its behaviors and the heavy loads, its energy management is challengeable. Virtual Power Plant (VPP) can be an important concept in managing such problems in this kind of grids. Here, a transmission power system is considered as a Regional Electric Company (REC) and the VPPs comprising Distributed Generation (DG) units and Demand Response Loads (DRLs) are determined in this system. This paper focuses on Industrial VPP (IVPP) and its management. An IVPP can be determined as a management unit comprising generations and loads in an industrial microgrid. Since the scheduling procedure for these units is very important for their participation in a short-term electric market, a stochastic formulation is proposed for power scheduling in VPPs especially in IVPPs in this paper. By introducing the DRL programs and using the proposed modeling, the operator can select the best DRL program for each VPP in a scheduling procedure. In this regard, a suitable approach is presented to determine the proposed formulation and its solution in a Mixed Integer Non-Linear Programming (MINLP). To validate the performance of the proposed method, the IEEE Reliability Test System (IEEE-RTS) is considered to apply the method on it, while some challenging aspects are presented.

Pricing long-dated insurance contracts with stochastic interest rates and stochastic volatility

NARCIS (Netherlands)

van Haastrecht, A.; Lord, R.; Pelsser, A.; Schrager, D.

2009-01-01

We consider the pricing of long-dated insurance contracts under stochastic interest rates and stochastic volatility. In particular, we focus on the valuation of insurance options with long-term equity or foreign exchange exposures. Our modeling framework extends the stochastic volatility model of

Integration of renewable generation uncertainties into stochastic unit commitment considering reserve and risk: A comparative study

International Nuclear Information System (INIS)

Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas

2016-01-01

The uncertainties of renewable energy have brought great challenges to power system commitment, dispatches and reserve requirement. This paper presents a comparative study on integration of renewable generation uncertainties into SCUC (stochastic security-constrained unit commitment) considering reserve and risk. Renewable forecast uncertainties are captured by a list of PIs (prediction intervals). A new scenario generation method is proposed to generate scenarios from these PIs. Different system uncertainties are considered as scenarios in the stochastic SCUC problem formulation. Two comparative simulations with single (E1: wind only) and multiple sources of uncertainty (E2: load, wind, solar and generation outages) are investigated. Five deterministic and four stochastic case studies are performed. Different generation costs, reserve strategies and associated risks are compared under various scenarios. Demonstrated results indicate the overall costs of E2 is lower than E1 due to penetration of solar power and the associated risk in deterministic cases of E2 is higher than E1. It implies the superimposed effect of uncertainties during uncertainty integration. The results also demonstrate that power systems run a higher level of risk during peak load hours, and that stochastic models are more robust than deterministic ones. - Highlights: • An extensive comparative study for renewable integration is presented. • A novel scenario generation method is proposed. • Wind and solar uncertainties are represented by a list of prediction intervals. • Unit commitment and dispatch costs are discussed considering reserve and risk.

Basic aspects of stochastic reliability analysis for redundancy systems

International Nuclear Information System (INIS)

Doerre, P.

1989-01-01

Much confusion has been created by trying to establish common cause failure (CCF) as an extra phenomenon which has to be treated with extra methods in reliability and data analysis. This paper takes another approach which can be roughly described by the statement that dependent failure is the basic phenomenon, while 'independent failure' refers to a special limiting case, namely the perfectly homogeneous population. This approach is motivated by examples demonstrating that common causes do not lead to dependent failure, so far as physical dependencies like shared components are excluded, and that stochastic dependencies are not related to common causes. The possibility to select more than one failure behaviour from an inhomogeneous population is identified as an additional random process which creates stochastic dependence. However, this source of randomness is usually treated in the deterministic limit, which destroys dependence and hence yields incorrect multiple failure frequencies for redundancy structures, thus creating the need for applying corrective CCF models. (author)

Uncertain Buckling Load and Reliability of Columns with Uncertain Properties

DEFF Research Database (Denmark)

Köylüoglu, H. U.; Nielsen, Søren R. K.; Cakmak, A. S.

Continuous and finite element methods are utilized to determine the buckling load of columns with material and geometrical uncertainties considering deterministic, stochastic and interval models for the bending rigidity of columns. When the bending rigidity field is assumed to be deterministic, t....... for structural design, the lower bound is of crucial interest. The buckling load of fixed-free, simple-supported, pinned-fixed, fixed-fixed columns and a sample frame are calculated....

Auditory Figure-Ground Segregation is Impaired by High Visual Load

OpenAIRE

Lavie, Nilli; Chait, Maria; Molloy, Katharine

2017-01-01

Figure-ground segregation is fundamental to listening in complex acoustic environments. An ongoing debate pertains to whether segregation requires attention or is 'automatic' and pre-attentive. In this magnetoencephalography (MEG) study we tested a prediction derived from Load Theory of attention (1) that segregation requires attention, but can benefit from the automatic allocation of any 'leftover' capacity under low load. Complex auditory scenes were modelled with Stochastic Figure Ground s...

Stochastic thermodynamics

Science.gov (United States)

Eichhorn, Ralf; Aurell, Erik

2014-04-01

'Stochastic thermodynamics as a conceptual framework combines the stochastic energetics approach introduced a decade ago by Sekimoto [1] with the idea that entropy can consistently be assigned to a single fluctuating trajectory [2]'. This quote, taken from Udo Seifert's [3] 2008 review, nicely summarizes the basic ideas behind stochastic thermodynamics: for small systems, driven by external forces and in contact with a heat bath at a well-defined temperature, stochastic energetics [4] defines the exchanged work and heat along a single fluctuating trajectory and connects them to changes in the internal (system) energy by an energy balance analogous to the first law of thermodynamics. Additionally, providing a consistent definition of trajectory-wise entropy production gives rise to second-law-like relations and forms the basis for a 'stochastic thermodynamics' along individual fluctuating trajectories. In order to construct meaningful concepts of work, heat and entropy production for single trajectories, their definitions are based on the stochastic equations of motion modeling the physical system of interest. Because of this, they are valid even for systems that are prevented from equilibrating with the thermal environment by external driving forces (or other sources of non-equilibrium). In that way, the central notions of equilibrium thermodynamics, such as heat, work and entropy, are consistently extended to the non-equilibrium realm. In the (non-equilibrium) ensemble, the trajectory-wise quantities acquire distributions. General statements derived within stochastic thermodynamics typically refer to properties of these distributions, and are valid in the non-equilibrium regime even beyond the linear response. The extension of statistical mechanics and of exact thermodynamic statements to the non-equilibrium realm has been discussed from the early days of statistical mechanics more than 100 years ago. This debate culminated in the development of linear response

Portfolio Optimization with Stochastic Dividends and Stochastic Volatility

Science.gov (United States)

Varga, Katherine Yvonne

2015-01-01

We consider an optimal investment-consumption portfolio optimization model in which an investor receives stochastic dividends. As a first problem, we allow the drift of stock price to be a bounded function. Next, we consider a stochastic volatility model. In each problem, we use the dynamic programming method to derive the Hamilton-Jacobi-Bellman…

A stochastic self-scheduling program for compressed air energy storage (CAES) of renewable energy sources (RESs) based on a demand response mechanism

International Nuclear Information System (INIS)

Ghalelou, Afshin Najafi; Fakhri, Alireza Pashaei; Nojavan, Sayyad; Majidi, Majid; Hatami, Hojat

2016-01-01

Highlights: • Optimal stochastic energy management of renewable energy sources (RESs) is proposed. • The compressed air energy storage (CAES) besides RESs is used in the presence of DRP. • Determination charge and discharge of CAES in order to reduce the expected operation cost. • Moreover, demand response program (DRP) is proposed to minimize the operation cost. • The uncertainty modeling of input data are considered in the proposed stochastic framework. - Abstract: In this paper, a stochastic self-scheduling of renewable energy sources (RESs) considering compressed air energy storage (CAES) in the presence of a demand response program (DRP) is proposed. RESs include wind turbine (WT) and photovoltaic (PV) system. Other energy sources are thermal units and CAES. The time-of-use (TOU) rate of DRP is considered in this paper. This DRP shifts the percentage of load from the expensive period to the cheap one in order to flatten the load curve and minimize the operation cost, consequently. The proposed objective function includes minimizing the operation costs of thermal unit and CAES, considering technical and physical constraints. The proposed model is formulated as mixed integer linear programming (MILP) and it is been solved using General Algebraic Modeling System (GAMS) optimization package. Furthermore, CAES and DRP are incorporated in the stochastic self-scheduling problem by a decision maker to reduce the expected operation cost. Meanwhile, the uncertainty models of market price, load, wind speed, temperature and irradiance are considered in the formulation. Finally, to assess the effects of DRP and CAES on self-scheduling problem, four case studies are utilized, and significant results were obtained, which indicate the validity of the proposed stochastic program.

Deterministic and stochastic trends in the Lee-Carter mortality model

DEFF Research Database (Denmark)

Callot, Laurent; Haldrup, Niels; Kallestrup-Lamb, Malene

The Lee and Carter (1992) model assumes that the deterministic and stochastic time series dynamics loads with identical weights when describing the development of age specific mortality rates. Effectively this means that the main characteristics of the model simplifies to a random walk model...... that characterizes mortality data. We find empirical evidence that this feature of the Lee-Carter model overly restricts the system dynamics and we suggest to separate the deterministic and stochastic time series components at the benefit of improved fit and forecasting performance. In fact, we find...... that the classical Lee-Carter model will otherwise over estimate the reduction of mortality for the younger age groups and will under estimate the reduction of mortality for the older age groups. In practice, our recommendation means that the Lee-Carter model instead of a one-factor model should be formulated...

Momentum and Stochastic Momentum for Stochastic Gradient, Newton, Proximal Point and Subspace Descent Methods

KAUST Repository

Loizou, Nicolas

2017-12-27

In this paper we study several classes of stochastic optimization algorithms enriched with heavy ball momentum. Among the methods studied are: stochastic gradient descent, stochastic Newton, stochastic proximal point and stochastic dual subspace ascent. This is the first time momentum variants of several of these methods are studied. We choose to perform our analysis in a setting in which all of the above methods are equivalent. We prove global nonassymptotic linear convergence rates for all methods and various measures of success, including primal function values, primal iterates (in L2 sense), and dual function values. We also show that the primal iterates converge at an accelerated linear rate in the L1 sense. This is the first time a linear rate is shown for the stochastic heavy ball method (i.e., stochastic gradient descent method with momentum). Under somewhat weaker conditions, we establish a sublinear convergence rate for Cesaro averages of primal iterates. Moreover, we propose a novel concept, which we call stochastic momentum, aimed at decreasing the cost of performing the momentum step. We prove linear convergence of several stochastic methods with stochastic momentum, and show that in some sparse data regimes and for sufficiently small momentum parameters, these methods enjoy better overall complexity than methods with deterministic momentum. Finally, we perform extensive numerical testing on artificial and real datasets, including data coming from average consensus problems.

Momentum and Stochastic Momentum for Stochastic Gradient, Newton, Proximal Point and Subspace Descent Methods

KAUST Repository

Loizou, Nicolas; Richtarik, Peter

2017-01-01

In this paper we study several classes of stochastic optimization algorithms enriched with heavy ball momentum. Among the methods studied are: stochastic gradient descent, stochastic Newton, stochastic proximal point and stochastic dual subspace ascent. This is the first time momentum variants of several of these methods are studied. We choose to perform our analysis in a setting in which all of the above methods are equivalent. We prove global nonassymptotic linear convergence rates for all methods and various measures of success, including primal function values, primal iterates (in L2 sense), and dual function values. We also show that the primal iterates converge at an accelerated linear rate in the L1 sense. This is the first time a linear rate is shown for the stochastic heavy ball method (i.e., stochastic gradient descent method with momentum). Under somewhat weaker conditions, we establish a sublinear convergence rate for Cesaro averages of primal iterates. Moreover, we propose a novel concept, which we call stochastic momentum, aimed at decreasing the cost of performing the momentum step. We prove linear convergence of several stochastic methods with stochastic momentum, and show that in some sparse data regimes and for sufficiently small momentum parameters, these methods enjoy better overall complexity than methods with deterministic momentum. Finally, we perform extensive numerical testing on artificial and real datasets, including data coming from average consensus problems.

Reliability-Based Modeling of Moisture and Load-Duration Effects

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard; Svensson, Staffan

2005-01-01

Load duration effects with respect to reduction of load bearing capacity are very important for structural timber. This paper describes how the load duration effects combined with moisture content and variations c an be determined on basis of simulation of realizations of the time varying load...... and moisture processes. Permanent and snow load sand moisture variations are considered and stochastic models are formulated in accordance with the load models in the Danish structural codes. A damage accumulation model based on fracture mechanics that accounts for both load duration and moisture effects...... is derived. The parameters in the model are fitted to data relevant for Nordic structural timber using the Maximum Likelihood method. The probability of failure as function of time is estimated for representative limit states based on: a) short term strength and b) long term damage accumulation...

Stochastic neuron models

CERN Document Server

Greenwood, Priscilla E

2016-01-01

This book describes a large number of open problems in the theory of stochastic neural systems, with the aim of enticing probabilists to work on them. This includes problems arising from stochastic models of individual neurons as well as those arising from stochastic models of the activities of small and large networks of interconnected neurons. The necessary neuroscience background to these problems is outlined within the text, so readers can grasp the context in which they arise. This book will be useful for graduate students and instructors providing material and references for applying probability to stochastic neuron modeling. Methods and results are presented, but the emphasis is on questions where additional stochastic analysis may contribute neuroscience insight. An extensive bibliography is included. Dr. Priscilla E. Greenwood is a Professor Emerita in the Department of Mathematics at the University of British Columbia. Dr. Lawrence M. Ward is a Professor in the Department of Psychology and the Brain...

FEAMAC/CARES Stochastic-Strength-Based Damage Simulation Tool for Ceramic Matrix Composites

Science.gov (United States)

Nemeth, Noel; Bednarcyk, Brett; Pineda, Evan; Arnold, Steven; Mital, Subodh; Murthy, Pappu; Bhatt, Ramakrishna

2016-01-01

Reported here is a coupling of two NASA developed codes: CARES (Ceramics Analysis and Reliability Evaluation of Structures) with the MAC/GMC (Micromechanics Analysis Code/ Generalized Method of Cells) composite material analysis code. The resulting code is called FEAMAC/CARES and is constructed as an Abaqus finite element analysis UMAT (user defined material). Here we describe the FEAMAC/CARES code and an example problem (taken from the open literature) of a laminated CMC in off-axis loading is shown. FEAMAC/CARES performs stochastic-strength-based damage simulation response of a CMC under multiaxial loading using elastic stiffness reduction of the failed elements.

Optimizing the Loads of multi-player online game Servers using Markov Chains

DEFF Research Database (Denmark)

Saeed, Aamir; Olsen, Rasmus Løvenstein; Pedersen, Jens Myrup

2015-01-01

that is created due to the load balancing of servers. Load balancing among servers is sensitive to correct status information. The Markov based load prediction was introduced in this paper to predict load of under-loaded servers, based on arrival (μ) and departure (λ) rates of players. The prediction based...... that need to be considered when developing load balancing algorithm, that is the reliability of the information that is shared. Simulation results show that Markov based prediction of load information performed better from the normal load status information sharing....

Stochastic tools in turbulence

CERN Document Server

Lumey, John L

2012-01-01

Stochastic Tools in Turbulence discusses the available mathematical tools to describe stochastic vector fields to solve problems related to these fields. The book deals with the needs of turbulence in relation to stochastic vector fields, particularly, on three-dimensional aspects, linear problems, and stochastic model building. The text describes probability distributions and densities, including Lebesgue integration, conditional probabilities, conditional expectations, statistical independence, lack of correlation. The book also explains the significance of the moments, the properties of the

Stochastic interpretation of the advection-diffusion equation and its relevance to bed load transport

Science.gov (United States)

Ancey, C.; Bohorquez, P.; Heyman, J.

2015-12-01

The advection-diffusion equation is one of the most widespread equations in physics. It arises quite often in the context of sediment transport, e.g., for describing time and space variations in the particle activity (the solid volume of particles in motion per unit streambed area). Phenomenological laws are usually sufficient to derive this equation and interpret its terms. Stochastic models can also be used to derive it, with the significant advantage that they provide information on the statistical properties of particle activity. These models are quite useful when sediment transport exhibits large fluctuations (typically at low transport rates), making the measurement of mean values difficult. Among these stochastic models, the most common approach consists of random walk models. For instance, they have been used to model the random displacement of tracers in rivers. Here we explore an alternative approach, which involves monitoring the evolution of the number of particles moving within an array of cells of finite length. Birth-death Markov processes are well suited to this objective. While the topic has been explored in detail for diffusion-reaction systems, the treatment of advection has received no attention. We therefore look into the possibility of deriving the advection-diffusion equation (with a source term) within the framework of birth-death Markov processes. We show that in the continuum limit (when the cell size becomes vanishingly small), we can derive an advection-diffusion equation for particle activity. Yet while this derivation is formally valid in the continuum limit, it runs into difficulty in practical applications involving cells or meshes of finite length. Indeed, within our stochastic framework, particle advection produces nonlocal effects, which are more or less significant depending on the cell size and particle velocity. Albeit nonlocal, these effects look like (local) diffusion and add to the intrinsic particle diffusion (dispersal due

HIV Viral Load: MedlinePlus Lab Test Information

Science.gov (United States)

... this page: https://medlineplus.gov/labtests/hivviralload.html HIV Viral Load To use the sharing features on this page, please enable JavaScript. What is an HIV Viral Load? An HIV viral load is a ...

Feedback, competition and stochasticity in a day ahead electricity market

International Nuclear Information System (INIS)

Giabardo, Paolo; Zugno, Marco; Pinson, Pierre; Madsen, Henrik

2010-01-01

Major recent changes in electricity markets relate to the process for their deregulation, along with increasing participation of renewable (stochastic) generation e.g. wind power. Our general objective is to model how feedback, competition and stochasticity (on the production side) interact in electricity markets, and eventually assess what their effects are on both the participants and the society. For this, day ahead electricity markets are modeled as dynamic closed loop systems, in which the feedback signal is the market price. In parallel, the Cournot competition model is considered. Mixed portfolios with significant share of renewable energy are based on stochastic threshold cost functions. Regarding trading strategies, it is assumed that generators are looking at optimizing their individual profits. The point of view of the society is addressed by analyzing market behavior and stability. The performed simulations show the beneficial effects of employing long term bidding strategies for both generators and society. Sensitivity analyses are performed in order to evaluate the effects of demand elasticity. It is shown that increase in demand elasticity reduces the possibility for the generators to exploit their market power. Furthermore, the results suggest that introduction of wind power generation in the market is beneficial both for the generators and the society.

Feedback, competition and stochasticity in a day ahead electricity market

Energy Technology Data Exchange (ETDEWEB)

Giabardo, Paolo; Zugno, Marco; Pinson, Pierre; Madsen, Henrik [DTU Informatics, Technical University of Denmark, Richard Petersens Plads 305, DK-2800 Kgs. Lyngby (Denmark)

2010-03-15

Major recent changes in electricity markets relate to the process for their deregulation, along with increasing participation of renewable (stochastic) generation e.g. wind power. Our general objective is to model how feedback, competition and stochasticity (on the production side) interact in electricity markets, and eventually assess what their effects are on both the participants and the society. For this, day ahead electricity markets are modeled as dynamic closed loop systems, in which the feedback signal is the market price. In parallel, the Cournot competition model is considered. Mixed portfolios with significant share of renewable energy are based on stochastic threshold cost functions. Regarding trading strategies, it is assumed that generators are looking at optimizing their individual profits. The point of view of the society is addressed by analyzing market behavior and stability. The performed simulations show the beneficial effects of employing long term bidding strategies for both generators and society. Sensitivity analyses are performed in order to evaluate the effects of demand elasticity. It is shown that increase in demand elasticity reduces the possibility for the generators to exploit their market power. Furthermore, the results suggest that introduction of wind power generation in the market is beneficial both for the generators and the society. (author)

Stochastic processes in cell biology

CERN Document Server

Bressloff, Paul C

2014-01-01

This book develops the theory of continuous and discrete stochastic processes within the context of cell biology.  A wide range of biological topics are covered including normal and anomalous diffusion in complex cellular environments, stochastic ion channels and excitable systems, stochastic calcium signaling, molecular motors, intracellular transport, signal transduction, bacterial chemotaxis, robustness in gene networks, genetic switches and oscillators, cell polarization, polymerization, cellular length control, and branching processes. The book also provides a pedagogical introduction to the theory of stochastic process – Fokker Planck equations, stochastic differential equations, master equations and jump Markov processes, diffusion approximations and the system size expansion, first passage time problems, stochastic hybrid systems, reaction-diffusion equations, exclusion processes, WKB methods, martingales and branching processes, stochastic calculus, and numerical methods.   This text is primarily...

Stochastic pump effect and geometric phases in dissipative and stochastic systems

Energy Technology Data Exchange (ETDEWEB)

Sinitsyn, Nikolai [Los Alamos National Laboratory

2008-01-01

The success of Berry phases in quantum mechanics stimulated the study of similar phenomena in other areas of physics, including the theory of living cell locomotion and motion of patterns in nonlinear media. More recently, geometric phases have been applied to systems operating in a strongly stochastic environment, such as molecular motors. We discuss such geometric effects in purely classical dissipative stochastic systems and their role in the theory of the stochastic pump effect (SPE).

Calibration of Load Duration Factor k_mod

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard; Stang, Birgitte Friis Dela; Svensson, Staffan

and the stochastic models are formulated in accordance with the load models in the Danish structural codes, DS 409, and DS 410. three damage accumulation models are considered, namely Gerhards model, Barret & Foschi's model, and Foschi & Yao's model. The parameters in these moels are fitted using data relevant...

Stochastic Optimal Control of a Heave Point Wave Energy Converter Based on a Modified LQG Approach

DEFF Research Database (Denmark)

Sun, Tao; Nielsen, Søren R. K.

2018-01-01

and actuator force are approximately considered by counteracting the absorbed power in the objective quadratic functional. Based on rational approximations to the radiation force and the wave load, the integrated dynamic system can be reformulated as a linear stochastic differential equation which is driven...

Deterministic and stochastic trends in the Lee-Carter mortality model

DEFF Research Database (Denmark)

Callot, Laurent; Haldrup, Niels; Kallestrup-Lamb, Malene

2015-01-01

The Lee and Carter (1992) model assumes that the deterministic and stochastic time series dynamics load with identical weights when describing the development of age-specific mortality rates. Effectively this means that the main characteristics of the model simplify to a random walk model with age...... mortality data. We find empirical evidence that this feature of the Lee–Carter model overly restricts the system dynamics and we suggest to separate the deterministic and stochastic time series components at the benefit of improved fit and forecasting performance. In fact, we find that the classical Lee......–Carter model will otherwise overestimate the reduction of mortality for the younger age groups and will underestimate the reduction of mortality for the older age groups. In practice, our recommendation means that the Lee–Carter model instead of a one-factor model should be formulated as a two- (or several...

Dispersion of Bed Load Particles

OpenAIRE

SAWAI, Kenji

1987-01-01

The motion of bed load particles is so irregular that they disperse remarkably with time.In this study, some flume tests using painted tracer particles were carried out, in which thedispersive property of tracers changed variously with sediment feed rate.In analysing this process, a stochastic simulation model is proposed where it is discussedabout the degree of exposure of individual particle near the bed surface and about the variationof its pick up rate. The exponential distribution of ste...

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

Science.gov (United States)

Harvey, David Benjamin Paul

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

Reliability-Based Calibration of Load Duration Factors for Timber Structures

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard; Svensson, Staffan; Stang, Birgitte Friis Dela

2005-01-01

John Dalsgaard Sørensen, Staffan Svensson, Birgitte Dela Stang : Reliability-Based Calibration of Load Duration Factors for Timber Structures     Abstract :   The load bearing capacity of timber structures decrease with time depending on the type of load and timber. Based on representative limit...... states and stochastic models for timber structures, load duration factors are calibrated using probabilistic methods. Load duration e.ects are estimated on basis of simulation of realizations of wind, snow and imposed loads in accordance with the load models in the Danish structural codes. Three damage...... accumulation models are considered, namely Gerhards model, Barrett and Foschi _ s model and Foschi and Yao _ s model. The parameters in these models are .tted by the Maximum Likelihood Method using data relevant for Danish structural timber and the statistical uncertainty is quanti .ed. The reliability...

A GPS-Based Control Framework for Accurate Current Sharing and Power Quality Improvement in Microgrids

DEFF Research Database (Denmark)

Golsorkhi, Mohammad; Savaghebi, Mehdi; Lu, Dylan

2017-01-01

This paper proposes a novel hierarchical control strategy for improvement of load sharing and power quality in ac microgrids. This control framework is composed of a droop based controller at the primary level, and a combination of distributed power sharing and voltage conditioning schemes...... consensus protocol to ensure proportional sharing of average power. The voltage conditioning scheme produces compensation signals at fundamental and dominant harmonics to improve the voltage quality at a sensitive load bus. Experimental results are presented to validate the efficacy of the proposed method....... dynamic response. The droop coefficient, which acts as a virtual resistance is adaptively changed as a function of the peak current. This strategy not only simplifies the control design but also improves the current sharing accuracy at high loading conditions. The distributed power sharing scheme uses...

Sequential stochastic optimization

CERN Document Server

Cairoli, Renzo

1996-01-01

Sequential Stochastic Optimization provides mathematicians and applied researchers with a well-developed framework in which stochastic optimization problems can be formulated and solved. Offering much material that is either new or has never before appeared in book form, it lucidly presents a unified theory of optimal stopping and optimal sequential control of stochastic processes. This book has been carefully organized so that little prior knowledge of the subject is assumed; its only prerequisites are a standard graduate course in probability theory and some familiarity with discrete-paramet

Singular stochastic differential equations

CERN Document Server

Cherny, Alexander S

2005-01-01

The authors introduce, in this research monograph on stochastic differential equations, a class of points termed isolated singular points. Stochastic differential equations possessing such points (called singular stochastic differential equations here) arise often in theory and in applications. However, known conditions for the existence and uniqueness of a solution typically fail for such equations. The book concentrates on the study of the existence, the uniqueness, and, what is most important, on the qualitative behaviour of solutions of singular stochastic differential equations. This is done by providing a qualitative classification of isolated singular points, into 48 possible types.

Load-aware modeling for uplink cellular networks in a multi-channel environment

KAUST Repository

Alammouri, Ahmad; Elsawy, Hesham; Alouini, Mohamed-Slim

2014-01-01

We exploit tools from stochastic geometry to develop a tractable analytical approach for modeling uplink cellular networks. The developed model is load aware and accounts for per-user power control as well as the limited transmit power constraint

Measures of thermodynamic irreversibility in deterministic and stochastic dynamics

International Nuclear Information System (INIS)

Ford, Ian J

2015-01-01

It is generally observed that if a dynamical system is sufficiently complex, then as time progresses it will share out energy and other properties amongst its component parts to eliminate any initial imbalances, retaining only fluctuations. This is known as energy dissipation and it is closely associated with the concept of thermodynamic irreversibility, measured by the increase in entropy according to the second law. It is of interest to quantify such behaviour from a dynamical rather than a thermodynamic perspective and to this end stochastic entropy production and the time-integrated dissipation function have been introduced as analogous measures of irreversibility, principally for stochastic and deterministic dynamics, respectively. We seek to compare these measures. First we modify the dissipation function to allow it to measure irreversibility in situations where the initial probability density function (pdf) of the system is asymmetric as well as symmetric in velocity. We propose that it tests for failure of what we call the obversibility of the system, to be contrasted with reversibility, the failure of which is assessed by stochastic entropy production. We note that the essential difference between stochastic entropy production and the time-integrated modified dissipation function lies in the sequence of procedures undertaken in the associated tests of irreversibility. We argue that an assumed symmetry of the initial pdf with respect to velocity inversion (within a framework of deterministic dynamics) can be incompatible with the Past Hypothesis, according to which there should be a statistical distinction between the behaviour of certain properties of an isolated system as it evolves into the far future and the remote past. Imposing symmetry on a velocity distribution is acceptable for many applications of statistical physics, but can introduce difficulties when discussing irreversible behaviour. (paper)

Review of Active and Reactive Power Sharing Strategies in Hierarchical Controlled Microgrids

DEFF Research Database (Denmark)

Han, Yang; Li, Hong; Shen, Pan

2017-01-01

Microgrids consist of multiple parallel-connected distributed generation (DG) units with coordinated control strategies, which are able to operate in both grid-connected and islanded mode. Microgrids are attracting more and more attention since they can alleviate the stress of main transmission...... systems, reduce feeder losses, and improve system power quality. When the islanded microgrids are concerned, it is important to maintain system stability and achieve load power sharing among the multiple parallel-connected DG units. However, the poor active and reactive power sharing problems due...... in this paper for active power sharing. Moreover, nonlinear and unbalanced loads could further affect the reactive power sharing when regulating the active power, and it is difficult to share the reactive power accurately only by using the enhanced virtual impedance method. Therefore, the hierarchical control...

Stochastic cooperative advertising in a manufacturer-retailer decentralized supply channel

Science.gov (United States)

Ezimadu, Peter E.; Nwozo, Chukwuma R.

2017-03-01

This work considers cooperative advertising in a manufacturer-retailer supply chain. While the manufacturer is the Stackelberg leader, the retailer is the follower. Using Sethi model it models the dynamic effect of the manufacturer and retailer's advertising efforts on sale. It uses optimal control technique and stochastic differential game theory to obtain the players' advertising strategies and the long-run value of the awareness share. Further, it models the relationship between the payoffs of both players and the awareness share. The work shows that with the provision of subsidy the retail advertising effort increases while the manufacturer's advertising effort reduces. It further shows that the total channel payoff is higher for subsidised retail advertising. However, the subsidy can only be possible if the rate of growth of the manufacturer's payoff is twice higher than that of the retailer.

Stochastic Response of an Inclined Shallow Cable with Linear Viscous Dampers under Stochastic Excitation

DEFF Research Database (Denmark)

Zhou, Qiang; Nielsen, Søren R.K.; Qu, Weilian

2010-01-01

Considering the coupling between the in-plane and out-of-plane vibration, the stochastic response of an inclined shallow cable with linear viscous dampers subjected to Gaussian white noise excitation is investigated in this paper. Selecting the static deflection shape due to a concentrated force...... together with the C-type Gram-Charlier expansion with a fourth-order closure are applied to obtain statistical moments, power spectral density and probabilistic density function of the cable response, whose availability is verified by Monte Carlo method. Taking a typical cable as an example, the influence...... of several factors, which include excitation level and direction as well as damper size, on the dynamic response of the cable is extensively investigated. It is found that the sum of mean square in-plane and out-of-plane displacement is primarily independent of the load direction when the excitation level...

Recent advances in ambit stochastics with a view towards tempo-spatial stochastic volatility/intermittency

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole E.; Benth, Fred Espen; Veraart, Almut

Ambit stochastics is the name for the theory and applications of ambit fields and ambit processes and constitutes a new research area in stochastics for tempo-spatial phenomena. This paper gives an overview of the main findings in ambit stochastics up to date and establishes new results on genera...

Functional Abstraction of Stochastic Hybrid Systems

NARCIS (Netherlands)

Bujorianu, L.M.; Blom, Henk A.P.; Hermanns, H.

2006-01-01

The verification problem for stochastic hybrid systems is quite difficult. One method to verify these systems is stochastic reachability analysis. Concepts of abstractions for stochastic hybrid systems are needed to ease the stochastic reachability analysis. In this paper, we set up different ways

Stochastic quantisation: theme and variation

International Nuclear Information System (INIS)

Klauder, J.R.; Kyoto Univ.

1987-01-01

The paper on stochastic quantisation is a contribution to the book commemorating the sixtieth birthday of E.S. Fradkin. Stochastic quantisation reformulates Euclidean quantum field theory in the language of Langevin equations. The generalised free field is discussed from the viewpoint of stochastic quantisation. An artificial family of highly singular model theories wherein the space-time derivatives are dropped altogether is also examined. Finally a modified form of stochastic quantisation is considered. (U.K.)

The dynamic behaviour of a non-stationary elevator compensating rope system under harmonic and stochastic excitations

Energy Technology Data Exchange (ETDEWEB)

Kaczmarczyk, S [School of Applied Sciences, University of Northampton, St. George' s Avenue, Northampton NN2 6JD (United Kingdom); Iwankiewicz, R [Institute of Mechanics and Ocean Engineering, Hamburg University of Technology, Eissendorfer Strasse 42 D-21073, Hamburg (Germany); Terumichi, Y, E-mail: stefan.kaczmarczyk@northampton.ac.u [Faculty of Science and Technology, Sophia University, 7-1 KIOI-CHO, CHIYODAKU, Tokyo, 102-8554 Japan (Japan)

2009-08-01

Moving slender elastic elements such as ropes, cables and belts are pivotal components of vertical transportation systems such as traction elevators. Their lengths vary within the host building structure during the elevator operation which results in the change of the mass and stiffness characteristics of the system. The structure of modern high-rise buildings is flexible and when subjected to loads due to strong winds and earthquakes it vibrates at low frequencies. The inertial load induced by the building motion excites the flexible components of the elevator system. The compensating ropes due to their lower tension are particularly affected and undergo large dynamic deformations. The paper focuses on the presentation of the non-stationary model of a building-compensating rope system and on the analysis to predict its dynamic response. The excitation mechanism is represented by a harmonic process and the results of computer simulations to predict transient resonance response are presented. The analysis of the simulation results leads to recommendations concerning the selection of the weight of the compensation assembly to minimize the effects of an adverse dynamic response of the system. The scenario when the excitation is represented as a narrow-band stochastic process with the state vector governed by stochastic equations is then discussed and the stochastic differential equations governing the second-order statistical moments of the state vector are developed.

Granular controls on the dispersion of bed load tracers

Science.gov (United States)

Jerolmack, D. J.; Martin, R. L.; Phillips, C. B.

2014-12-01

Coarse particles are transported in a river as bed load, i.e., they move in frequent contact with and are supported by the granular bed. This movement is typically intermittent and may be described by a series of steps are rests, the distributions of which determine particle dispersion. Laboratory and field studies of bed load tracer dispersion have reported sub- and super-diffusive behavior, both of which have been successfully reproduced with stochastic transport models. Although researchers have invoked heavy-tailed step lengths as the cause of anomalous dispersion, most observations report thin-tailed distributions. Little attention has been paid to rest periods, and stochastic transport models have not been connected to the underlying mechanics of particle motion. Based on theoretical and experimental evidence, we argue that step lengths are thin-tailed and do not control the longterm dispersion of bed load tracers; they are determined by momentum balance between the fluid and solid. Using laboratory experiments with both marbles and natural sediments, we demonstrate that the rest time distribution is power law, and argue that this distribution controls asymptotic dispersion. Observed rest times far exceed any hydrodynamic timescale. Experiments reveal that rest times of deposited particles are governed by fluctuations in river bed elevation; in particular, the return time for the bed to scour to the base of a deposited particle. Stochastic fluctuations in bed elevation are describable by an Ornstein-Uhlenbeck (mean-reverting random walk) model that contains two parameters, which we show are directly related to the granular shear rate and range of bed elevation fluctuations, respectively. Combining these results with the theory of asymmetric random walks (particles only move downstream), we predict superdiffusive behavior that is in quantitative agreement with our observations of tracer dispersion in a natural river.

STOCHASTIC ASSESSMENT OF NIGERIAN STOCHASTIC ...

African Journals Online (AJOL)

eobe

STOCHASTIC ASSESSMENT OF NIGERIAN WOOD FOR BRIDGE DECKS ... abandoned bridges with defects only in their decks in both rural and urban locations can be effectively .... which can be seen as the detection of rare physical.

A novel two-stage stochastic programming model for uncertainty characterization in short-term optimal strategy for a distribution company

International Nuclear Information System (INIS)

Ahmadi, Abdollah; Charwand, Mansour; Siano, Pierluigi; Nezhad, Ali Esmaeel; Sarno, Debora; Gitizadeh, Mohsen; Raeisi, Fatima

2016-01-01

In order to supply the demands of the end users in a competitive market, a distribution company purchases energy from the wholesale market while other options would be in access in the case of possessing distributed generation units and interruptible loads. In this regard, this study presents a two-stage stochastic programming model for a distribution company energy acquisition market model to manage the involvement of different electric energy resources characterized by uncertainties with the minimum cost. In particular, the distribution company operations planning over a day-ahead horizon is modeled as a stochastic mathematical optimization, with the objective of minimizing costs. By this, distribution company decisions on grid purchase, owned distributed generation units and interruptible load scheduling are determined. Then, these decisions are considered as boundary constraints to a second step, which deals with distribution company's operations in the hour-ahead market with the objective of minimizing the short-term cost. The uncertainties in spot market prices and wind speed are modeled by means of probability distribution functions of their forecast errors and the roulette wheel mechanism and lattice Monte Carlo simulation are used to generate scenarios. Numerical results show the capability of the proposed method. - Highlights: • Proposing a new a stochastic-based two-stage operations framework in retail competitive markets. • Proposing a Mixed Integer Non-Linear stochastic programming. • Employing roulette wheel mechanism and Lattice Monte Carlo Simulation.

Stochastic quantization and gravity

International Nuclear Information System (INIS)

Rumpf, H.

1984-01-01

We give a preliminary account of the application of stochastic quantization to the gravitational field. We start in Section I from Nelson's formulation of quantum mechanics as Newtonian stochastic mechanics and only then introduce the Parisi-Wu stochastic quantization scheme on which all the later discussion will be based. In Section II we present a generalization of the scheme that is applicable to fields in physical (i.e. Lorentzian) space-time and treat the free linearized gravitational field in this manner. The most remarkable result of this is the noncausal propagation of conformal gravitons. Moreover the concept of stochastic gauge-fixing is introduced and a complete discussion of all the covariant gauges is given. A special symmetry relating two classes of covariant gauges is exhibited. Finally Section III contains some preliminary remarks on full nonlinear gravity. In particular we argue that in contrast to gauge fields the stochastic gravitational field cannot be transformed to a Gaussian process. (Author)

Stochastic climate theory

NARCIS (Netherlands)

Gottwald, G.A.; Crommelin, D.T.; Franzke, C.L.E.; Franzke, C.L.E.; O'Kane, T.J.

2017-01-01

In this chapter we review stochastic modelling methods in climate science. First we provide a conceptual framework for stochastic modelling of deterministic dynamical systems based on the Mori-Zwanzig formalism. The Mori-Zwanzig equations contain a Markov term, a memory term and a term suggestive of

2–stage stochastic Runge–Kutta for stochastic delay differential equations

Energy Technology Data Exchange (ETDEWEB)

Rosli, Norhayati; Jusoh Awang, Rahimah [Faculty of Industrial Science and Technology, Universiti Malaysia Pahang, Lebuhraya Tun Razak, 26300, Gambang, Pahang (Malaysia); Bahar, Arifah; Yeak, S. H. [Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor (Malaysia)

2015-05-15

This paper proposes a newly developed one-step derivative-free method, that is 2-stage stochastic Runge-Kutta (SRK2) to approximate the solution of stochastic delay differential equations (SDDEs) with a constant time lag, r > 0. General formulation of stochastic Runge-Kutta for SDDEs is introduced and Stratonovich Taylor series expansion for numerical solution of SRK2 is presented. Local truncation error of SRK2 is measured by comparing the Stratonovich Taylor expansion of the exact solution with the computed solution. Numerical experiment is performed to assure the validity of the method in simulating the strong solution of SDDEs.

COMPARISON OF EIGENMODE-BASED AND RANDOM FIELD-BASED IMPERFECTION MODELING FOR THE STOCHASTIC BUCKLING ANALYSIS OF I-SECTION BEAM–COLUMNS

KAUST Repository

STAVREV, A.; STEFANOV, D.; SCHILLINGER, D.; RANK, E.

2013-01-01

The uncertainty of geometric imperfections in a series of nominally equal I-beams leads to a variability of corresponding buckling loads. Its analysis requires a stochastic imperfection model, which can be derived either by the simple variation

Fuzzy stochastic analysis of serviceability and ultimate limit states of two-span pedestrian steel bridge

Science.gov (United States)

Kala, Zdeněk; Sandovič, GiedrÄ--

2012-09-01

The paper deals with non-linear analysis of ultimate and serviceability limit states of two-span pedestrian steel bridge. The effects of random material and geometrical characteristics on limit states are analyzed. The Monte Carlo method was applied to stochastic analysis. For the serviceability limit state, also influence of fuzzy uncertainty of the limit deflection value on random characteristics of load capacity of variable action was studied. The results prove that, for the type of structure studied, the serviceability limit state is decisive from the point of view of design. The present paper opens a discussion on the use of stochastic analysis to verify the limit deflections given in the standards EUROCODES.

Space-time-modulated stochastic processes

Science.gov (United States)

Giona, Massimiliano

2017-10-01

Starting from the physical problem associated with the Lorentzian transformation of a Poisson-Kac process in inertial frames, the concept of space-time-modulated stochastic processes is introduced for processes possessing finite propagation velocity. This class of stochastic processes provides a two-way coupling between the stochastic perturbation acting on a physical observable and the evolution of the physical observable itself, which in turn influences the statistical properties of the stochastic perturbation during its evolution. The definition of space-time-modulated processes requires the introduction of two functions: a nonlinear amplitude modulation, controlling the intensity of the stochastic perturbation, and a time-horizon function, which modulates its statistical properties, providing irreducible feedback between the stochastic perturbation and the physical observable influenced by it. The latter property is the peculiar fingerprint of this class of models that makes them suitable for extension to generic curved-space times. Considering Poisson-Kac processes as prototypical examples of stochastic processes possessing finite propagation velocity, the balance equations for the probability density functions associated with their space-time modulations are derived. Several examples highlighting the peculiarities of space-time-modulated processes are thoroughly analyzed.

RES: Regularized Stochastic BFGS Algorithm

Science.gov (United States)

Mokhtari, Aryan; Ribeiro, Alejandro

2014-12-01

RES, a regularized stochastic version of the Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton method is proposed to solve convex optimization problems with stochastic objectives. The use of stochastic gradient descent algorithms is widespread, but the number of iterations required to approximate optimal arguments can be prohibitive in high dimensional problems. Application of second order methods, on the other hand, is impracticable because computation of objective function Hessian inverses incurs excessive computational cost. BFGS modifies gradient descent by introducing a Hessian approximation matrix computed from finite gradient differences. RES utilizes stochastic gradients in lieu of deterministic gradients for both, the determination of descent directions and the approximation of the objective function's curvature. Since stochastic gradients can be computed at manageable computational cost RES is realizable and retains the convergence rate advantages of its deterministic counterparts. Convergence results show that lower and upper bounds on the Hessian egeinvalues of the sample functions are sufficient to guarantee convergence to optimal arguments. Numerical experiments showcase reductions in convergence time relative to stochastic gradient descent algorithms and non-regularized stochastic versions of BFGS. An application of RES to the implementation of support vector machines is developed.

Review: Optimising cognitive load and usability to improve the ...

African Journals Online (AJOL)

Cognitive load theory views learning as involving active processing of information by working memory via separate visual and auditory channels. This system is of ... The fields of cognitive load theory and human-computer interaction share a common goal in striving to reduce extraneous cognitive load. The load induced by ...

Elitism and Stochastic Dominance

OpenAIRE

Bazen, Stephen; Moyes, Patrick

2011-01-01

Stochastic dominance has typically been used with a special emphasis on risk and inequality reduction something captured by the concavity of the utility function in the expected utility model. We claim that the applicability of the stochastic dominance approach goes far beyond risk and inequality measurement provided suitable adpations be made. We apply in the paper the stochastic dominance approach to the measurment of elitism which may be considered the opposite of egalitarianism. While the...

Stochastic Simulation Service: Bridging the Gap between the Computational Expert and the Biologist.

Directory of Open Access Journals (Sweden)

Brian Drawert

2016-12-01

Full Text Available We present StochSS: Stochastic Simulation as a Service, an integrated development environment for modeling and simulation of both deterministic and discrete stochastic biochemical systems in up to three dimensions. An easy to use graphical user interface enables researchers to quickly develop and simulate a biological model on a desktop or laptop, which can then be expanded to incorporate increasing levels of complexity. StochSS features state-of-the-art simulation engines. As the demand for computational power increases, StochSS can seamlessly scale computing resources in the cloud. In addition, StochSS can be deployed as a multi-user software environment where collaborators share computational resources and exchange models via a public model repository. We demonstrate the capabilities and ease of use of StochSS with an example of model development and simulation at increasing levels of complexity.

Stochastic analytic regularization

International Nuclear Information System (INIS)

Alfaro, J.

1984-07-01

Stochastic regularization is reexamined, pointing out a restriction on its use due to a new type of divergence which is not present in the unregulated theory. Furthermore, we introduce a new form of stochastic regularization which permits the use of a minimal subtraction scheme to define the renormalized Green functions. (author)

On Stochastic Dependence

Science.gov (United States)

Meyer, Joerg M.

2018-01-01

The contrary of stochastic independence splits up into two cases: pairs of events being favourable or being unfavourable. Examples show that both notions have quite unexpected properties, some of them being opposite to intuition. For example, transitivity does not hold. Stochastic dependence is also useful to explain cases of Simpson's paradox.

Stochastic massless fields I: Integer spin

International Nuclear Information System (INIS)

Lim, S.C.

1981-04-01

Nelson's stochastic quantization scheme is applied to classical massless tensor potential in ''Coulomb'' gauge. The relationship between stochastic potential field in various gauges is discussed using the case of vector potential as an illustration. It is possible to identify the Euclidean tensor potential with the corresponding stochastic field in physical Minkowski space-time. Stochastic quantization of massless fields can also be carried out in terms of field strength tensors. An example of linearized stochastic gravitational field in vacuum is given. (author)

Short term load forecasting: two stage modelling

Directory of Open Access Journals (Sweden)

SOARES, L. J.

2009-06-01

Full Text Available This paper studies the hourly electricity load demand in the area covered by a utility situated in the Seattle, USA, called Puget Sound Power and Light Company. Our proposal is put into proof with the famous dataset from this company. We propose a stochastic model which employs ANN (Artificial Neural Networks to model short-run dynamics and the dependence among adjacent hours. The model proposed treats each hour's load separately as individual single series. This approach avoids modeling the intricate intra-day pattern (load profile displayed by the load, which varies throughout days of the week and seasons. The forecasting performance of the model is evaluated in similiar mode a TLSAR (Two-Level Seasonal Autoregressive model proposed by Soares (2003 using the years of 1995 and 1996 as the holdout sample. Moreover, we conclude that non linearity is present in some series of these data. The model results are analyzed. The experiment shows that our tool can be used to produce load forecasting in tropical climate places.

Stochastic processes inference theory

CERN Document Server

Rao, Malempati M

2014-01-01

This is the revised and enlarged 2nd edition of the authors’ original text, which was intended to be a modest complement to Grenander's fundamental memoir on stochastic processes and related inference theory. The present volume gives a substantial account of regression analysis, both for stochastic processes and measures, and includes recent material on Ridge regression with some unexpected applications, for example in econometrics. The first three chapters can be used for a quarter or semester graduate course on inference on stochastic processes. The remaining chapters provide more advanced material on stochastic analysis suitable for graduate seminars and discussions, leading to dissertation or research work. In general, the book will be of interest to researchers in probability theory, mathematical statistics and electrical and information theory.

Path to Stochastic Stability: Comparative Analysis of Stochastic Learning Dynamics in Games

KAUST Repository

Jaleel, Hassan

2018-04-08

Stochastic stability is a popular solution concept for stochastic learning dynamics in games. However, a critical limitation of this solution concept is its inability to distinguish between different learning rules that lead to the same steady-state behavior. We address this limitation for the first time and develop a framework for the comparative analysis of stochastic learning dynamics with different update rules but same steady-state behavior. We present the framework in the context of two learning dynamics: Log-Linear Learning (LLL) and Metropolis Learning (ML). Although both of these dynamics have the same stochastically stable states, LLL and ML correspond to different behavioral models for decision making. Moreover, we demonstrate through an example setup of sensor coverage game that for each of these dynamics, the paths to stochastically stable states exhibit distinctive behaviors. Therefore, we propose multiple criteria to analyze and quantify the differences in the short and medium run behavior of stochastic learning dynamics. We derive and compare upper bounds on the expected hitting time to the set of Nash equilibria for both LLL and ML. For the medium to long-run behavior, we identify a set of tools from the theory of perturbed Markov chains that result in a hierarchical decomposition of the state space into collections of states called cycles. We compare LLL and ML based on the proposed criteria and develop invaluable insights into the comparative behavior of the two dynamics.

A multi-stage stochastic transmission expansion planning method

International Nuclear Information System (INIS)

Akbari, Tohid; Rahimikian, Ashkan; Kazemi, Ahad

2011-01-01

Highlights: → We model a multi-stage stochastic transmission expansion planning problem. → We include available transfer capability (ATC) in our model. → Involving this criterion will increase the ATC between source and sink points. → Power system reliability will be increased and more money can be saved. - Abstract: This paper presents a multi-stage stochastic model for short-term transmission expansion planning considering the available transfer capability (ATC). The ATC can have a huge impact on the power market outcomes and the power system reliability. The transmission expansion planning (TEP) studies deal with many uncertainties, such as system load uncertainties that are considered in this paper. The Monte Carlo simulation method has been applied for generating different scenarios. A scenario reduction technique is used for reducing the number of scenarios. The objective is to minimize the sum of investment costs (IC) and the expected operation costs (OC). The solution technique is based on the benders decomposition algorithm. The N-1 contingency analysis is also done for the TEP problem. The proposed model is applied to the IEEE 24 bus reliability test system and the results are efficient and promising.

Quantum stochastics

CERN Document Server

Chang, Mou-Hsiung

2015-01-01

The classical probability theory initiated by Kolmogorov and its quantum counterpart, pioneered by von Neumann, were created at about the same time in the 1930s, but development of the quantum theory has trailed far behind. Although highly appealing, the quantum theory has a steep learning curve, requiring tools from both probability and analysis and a facility for combining the two viewpoints. This book is a systematic, self-contained account of the core of quantum probability and quantum stochastic processes for graduate students and researchers. The only assumed background is knowledge of the basic theory of Hilbert spaces, bounded linear operators, and classical Markov processes. From there, the book introduces additional tools from analysis, and then builds the quantum probability framework needed to support applications to quantum control and quantum information and communication. These include quantum noise, quantum stochastic calculus, stochastic quantum differential equations, quantum Markov semigrou...

Stochastic correlative firing for figure-ground segregation.

Science.gov (United States)

Chen, Zhe

2005-03-01

Segregation of sensory inputs into separate objects is a central aspect of perception and arises in all sensory modalities. The figure-ground segregation problem requires identifying an object of interest in a complex scene, in many cases given binaural auditory or binocular visual observations. The computations required for visual and auditory figure-ground segregation share many common features and can be cast within a unified framework. Sensory perception can be viewed as a problem of optimizing information transmission. Here we suggest a stochastic correlative firing mechanism and an associative learning rule for figure-ground segregation in several classic sensory perception tasks, including the cocktail party problem in binaural hearing, binocular fusion of stereo images, and Gestalt grouping in motion perception.

Stochastic cooling

International Nuclear Information System (INIS)

Bisognano, J.; Leemann, C.

1982-03-01

Stochastic cooling is the damping of betatron oscillations and momentum spread of a particle beam by a feedback system. In its simplest form, a pickup electrode detects the transverse positions or momenta of particles in a storage ring, and the signal produced is amplified and applied downstream to a kicker. The time delay of the cable and electronics is designed to match the transit time of particles along the arc of the storage ring between the pickup and kicker so that an individual particle receives the amplified version of the signal it produced at the pick-up. If there were only a single particle in the ring, it is obvious that betatron oscillations and momentum offset could be damped. However, in addition to its own signal, a particle receives signals from other beam particles. In the limit of an infinite number of particles, no damping could be achieved; we have Liouville's theorem with constant density of the phase space fluid. For a finite, albeit large number of particles, there remains a residue of the single particle damping which is of practical use in accumulating low phase space density beams of particles such as antiprotons. It was the realization of this fact that led to the invention of stochastic cooling by S. van der Meer in 1968. Since its conception, stochastic cooling has been the subject of much theoretical and experimental work. The earliest experiments were performed at the ISR in 1974, with the subsequent ICE studies firmly establishing the stochastic cooling technique. This work directly led to the design and construction of the Antiproton Accumulator at CERN and the beginnings of p anti p colliding beam physics at the SPS. Experiments in stochastic cooling have been performed at Fermilab in collaboration with LBL, and a design is currently under development for a anti p accumulator for the Tevatron

Stochastic optimal control, forward-backward stochastic differential equations and the Schroedinger equation

Energy Technology Data Exchange (ETDEWEB)

Paul, Wolfgang; Koeppe, Jeanette [Institut fuer Physik, Martin Luther Universitaet, 06099 Halle (Germany); Grecksch, Wilfried [Institut fuer Mathematik, Martin Luther Universitaet, 06099 Halle (Germany)

2016-07-01

The standard approach to solve a non-relativistic quantum problem is through analytical or numerical solution of the Schroedinger equation. We show a way to go around it. This way is based on the derivation of the Schroedinger equation from conservative diffusion processes and the establishment of (several) stochastic variational principles leading to the Schroedinger equation under the assumption of a kinematics described by Nelson's diffusion processes. Mathematically, the variational principle can be considered as a stochastic optimal control problem linked to the forward-backward stochastic differential equations of Nelson's stochastic mechanics. The Hamilton-Jacobi-Bellmann equation of this control problem is the Schroedinger equation. We present the mathematical background and how to turn it into a numerical scheme for analyzing a quantum system without using the Schroedinger equation and exemplify the approach for a simple 1d problem.

Distributed EMPC of multiple microgrids for coordinated stochastic energy management

International Nuclear Information System (INIS)

Kou, Peng; Liang, Deliang; Gao, Lin

2017-01-01

Highlights: • Reducing the system wide operating cost compared to the no-cooperation energy management strategy. • Maintaining the supply and demand balance within each microgrid. • Handling the uncertainties in both supply and demand. • Converting the stochastic optimization problems to standard quadratic and linear programming problems. • Achieving a good balance between control performance and computationally feasibility. - Abstract: The concept of multi-microgrids has the potential to improve the reliability and economic performance of a distribution system. To realize this potential, a coordination among multiple microgrids is needed. In this context, this paper presents a new distributed economic model predictive control scheme for the coordinated stochastic energy management of multi-microgrids. By optimally coordinating the operation of individual microgrids, this scheme maintains the system-wide supply and demand balance in an economical manner. Based on the probabilistic forecasts of renewable power generation and microgrid load, this scheme effectively handles the uncertainties in both supply and demand. Using the Chebyshev inequality and the Delta method, the corresponding stochastic optimization problems have been converted to quadratic and linear programs. The proposed scheme is evaluated on a large-scale case that includes ten interconnected microgrids. The results indicated that the proposed scheme successfully reduces the system wide operating cost, achieves the supply-demand balance in each microgrid, and brings the energy exchange between DNO and main grid to a predefined trajectory.

Frequency domain fatigue damage estimation methods suitable for deterministic load spectra

Energy Technology Data Exchange (ETDEWEB)

Henderson, A.R.; Patel, M.H. [University Coll., Dept. of Mechanical Engineering, London (United Kingdom)

2000-07-01

The evaluation of fatigue damage due to load spectra, directly in the frequency domain, is a complex phenomena but with the benefit of significant computation time savings. Various formulae have been suggested but have usually relating to a specific application only. The Dirlik method is the exception and is applicable to general cases of continuous stochastic spectra. This paper describes three approaches for evaluating discrete deterministic load spectra generated by the floating wind turbine model developed the UCL/RAL research project. (Author)

Stochastic Analysis : A Series of Lectures

CERN Document Server

Dozzi, Marco; Flandoli, Franco; Russo, Francesco

2015-01-01

This book presents in thirteen refereed survey articles an overview of modern activity in stochastic analysis, written by leading international experts. The topics addressed include stochastic fluid dynamics and regularization by noise of deterministic dynamical systems; stochastic partial differential equations driven by Gaussian or Lévy noise, including the relationship between parabolic equations and particle systems, and wave equations in a geometric framework; Malliavin calculus and applications to stochastic numerics; stochastic integration in Banach spaces; porous media-type equations; stochastic deformations of classical mechanics and Feynman integrals and stochastic differential equations with reflection. The articles are based on short courses given at the Centre Interfacultaire Bernoulli of the Ecole Polytechnique Fédérale de Lausanne, Switzerland, from January to June 2012. They offer a valuable resource not only for specialists, but also for other researchers and Ph.D. students in the fields o...

Stochastic Analysis with Financial Applications

CERN Document Server

Kohatsu-Higa, Arturo; Sheu, Shuenn-Jyi

2011-01-01

Stochastic analysis has a variety of applications to biological systems as well as physical and engineering problems, and its applications to finance and insurance have bloomed exponentially in recent times. The goal of this book is to present a broad overview of the range of applications of stochastic analysis and some of its recent theoretical developments. This includes numerical simulation, error analysis, parameter estimation, as well as control and robustness properties for stochastic equations. This book also covers the areas of backward stochastic differential equations via the (non-li

Two-boundary first exit time of Gauss-Markov processes for stochastic modeling of acto-myosin dynamics.

Science.gov (United States)

D'Onofrio, Giuseppe; Pirozzi, Enrica

2017-05-01

We consider a stochastic differential equation in a strip, with coefficients suitably chosen to describe the acto-myosin interaction subject to time-varying forces. By simulating trajectories of the stochastic dynamics via an Euler discretization-based algorithm, we fit experimental data and determine the values of involved parameters. The steps of the myosin are represented by the exit events from the strip. Motivated by these results, we propose a specific stochastic model based on the corresponding time-inhomogeneous Gauss-Markov and diffusion process evolving between two absorbing boundaries. We specify the mean and covariance functions of the stochastic modeling process taking into account time-dependent forces including the effect of an external load. We accurately determine the probability density function (pdf) of the first exit time (FET) from the strip by solving a system of two non singular second-type Volterra integral equations via a numerical quadrature. We provide numerical estimations of the mean of FET as approximations of the dwell-time of the proteins dynamics. The percentage of backward steps is given in agreement to experimental data. Numerical and simulation results are compared and discussed.

Stochastic analysis of residential micro combined heat and power system

DEFF Research Database (Denmark)

Karami, H.; Sanjari, M. J.; Gooi, H. B.

2017-01-01

In this paper the combined heat and power functionality of a fuel-cell in a residential hybrid energy system, including a battery, is studied. The demand uncertainties are modeled by investigating the stochastic load behavior by applying Monte Carlo simulation. The colonial competitive algorithm...... algorithm. The optimized scheduling of different energy resources is listed in an efficient look-up table for all time intervals. The effects of time of use and the battery efficiency and its size are investigated on the operating cost of the hybrid energy system. The results of this paper are expected...

Stochastic Reachability Analysis of Hybrid Systems

CERN Document Server

Bujorianu, Luminita Manuela

2012-01-01

Stochastic reachability analysis (SRA) is a method of analyzing the behavior of control systems which mix discrete and continuous dynamics. For probabilistic discrete systems it has been shown to be a practical verification method but for stochastic hybrid systems it can be rather more. As a verification technique SRA can assess the safety and performance of, for example, autonomous systems, robot and aircraft path planning and multi-agent coordination but it can also be used for the adaptive control of such systems. Stochastic Reachability Analysis of Hybrid Systems is a self-contained and accessible introduction to this novel topic in the analysis and development of stochastic hybrid systems. Beginning with the relevant aspects of Markov models and introducing stochastic hybrid systems, the book then moves on to coverage of reachability analysis for stochastic hybrid systems. Following this build up, the core of the text first formally defines the concept of reachability in the stochastic framework and then...

Bonds with index-linked stochastic coupons in quantum finance

Science.gov (United States)

Baaquie, Belal Ehsan

2018-06-01

An index-linked coupon bond is defined that pays coupons whose values are stochastic, depending on a market defined index. This is an asset class distinct from the existing coupon bonds. The index-linked coupon bond is an example of a sukuk, which is an instrument that implements one of the cornerstones of Islamic finance (Askari et al., 2012): that an investor must share in the risk of the issuer in order to earn profits from the investment. The index-linked coupon bond is defined using the mathematical framework of quantum finance (Baaquie, 2004, 2010). The coupons are stochastic, with the quantum of coupon payments depending on a publicly traded index that is chosen to reflect the primary drivers of the revenues of the issuer of the bond. The index ensures there is information symmetry - regarding the quantum of coupon being paid - between issuer and investor. The dependence of the coupon on the index is designed so that the variation of the index mirrors the changing fortunes of the issuer, with the coupon's quantum increasing for increasing values of the index and conversely, decreasing with a fall of the index.

The FOSS GIS Workbench on the GFZ Load Sharing Facility compute cluster

Science.gov (United States)

Löwe, P.; Klump, J.; Thaler, J.

2012-04-01

Compute clusters can be used as GIS workbenches, their wealth of resources allow us to take on geocomputation tasks which exceed the limitations of smaller systems. To harness these capabilities requires a Geographic Information System (GIS), able to utilize the available cluster configuration/architecture and a sufficient degree of user friendliness to allow for wide application. In this paper we report on the first successful porting of GRASS GIS, the oldest and largest Free Open Source (FOSS) GIS project, onto a compute cluster using Platform Computing's Load Sharing Facility (LSF). In 2008, GRASS6.3 was installed on the GFZ compute cluster, which at that time comprised 32 nodes. The interaction with the GIS was limited to the command line interface, which required further development to encapsulate the GRASS GIS business layer to facilitate its use by users not familiar with GRASS GIS. During the summer of 2011, multiple versions of GRASS GIS (v 6.4, 6.5 and 7.0) were installed on the upgraded GFZ compute cluster, now consisting of 234 nodes with 480 CPUs providing 3084 cores. The GFZ compute cluster currently offers 19 different processing queues with varying hardware capabilities and priorities, allowing for fine-grained scheduling and load balancing. After successful testing of core GIS functionalities, including the graphical user interface, mechanisms were developed to deploy scripted geocomputation tasks onto dedicated processing queues. The mechanisms are based on earlier work by NETELER et al. (2008). A first application of the new GIS functionality was the generation of maps of simulated tsunamis in the Mediterranean Sea for the Tsunami Atlas of the FP-7 TRIDEC Project (www.tridec-online.eu). For this, up to 500 processing nodes were used in parallel. Further trials included the processing of geometrically complex problems, requiring significant amounts of processing time. The GIS cluster successfully completed all these tasks, with processing times

A stochastic simulation model for reliable PV system sizing providing for solar radiation fluctuations

International Nuclear Information System (INIS)

Kaplani, E.; Kaplanis, S.

2012-01-01

Highlights: ► Solar radiation data for European cities follow the Extreme Value or Weibull distribution. ► Simulation model for the sizing of SAPV systems based on energy balance and stochastic analysis. ► Simulation of PV Generator-Loads-Battery Storage System performance for all months. ► Minimum peak power and battery capacity required for reliable SAPV sizing for various European cities. ► Peak power and battery capacity reduced by more than 30% for operation 95% success rate. -- Abstract: The large fluctuations observed in the daily solar radiation profiles affect highly the reliability of the PV system sizing. Increasing the reliability of the PV system requires higher installed peak power (P m ) and larger battery storage capacity (C L ). This leads to increased costs, and makes PV technology less competitive. This research paper presents a new stochastic simulation model for stand-alone PV systems, developed to determine the minimum installed P m and C L for the PV system to be energy independent. The stochastic simulation model developed, makes use of knowledge acquired from an in-depth statistical analysis of the solar radiation data for the site, and simulates the energy delivered, the excess energy burnt, the load profiles and the state of charge of the battery system for the month the sizing is applied, and the PV system performance for the entire year. The simulation model provides the user with values for the autonomy factor d, simulating PV performance in order to determine the minimum P m and C L depending on the requirements of the application, i.e. operation with critical or non-critical loads. The model makes use of NASA’s Surface meteorology and Solar Energy database for the years 1990–2004 for various cities in Europe with a different climate. The results obtained with this new methodology indicate a substantial reduction in installed peak power and battery capacity, both for critical and non-critical operation, when compared to

Homogenization of the stochastic Navier–Stokes equation with a stochastic slip boundary condition

KAUST Repository

Bessaih, Hakima

2015-11-02

The two-dimensional Navier–Stokes equation in a perforated domain with a dynamical slip boundary condition is considered. We assume that the dynamic is driven by a stochastic perturbation on the interior of the domain and another stochastic perturbation on the boundaries of the holes. We consider a scaling (ᵋ for the viscosity and 1 for the density) that will lead to a time-dependent limit problem. However, the noncritical scaling (ᵋ, β > 1) is considered in front of the nonlinear term. The homogenized system in the limit is obtained as a Darcy’s law with memory with two permeabilities and an extra term that is due to the stochastic perturbation on the boundary of the holes. The nonhomogeneity on the boundary contains a stochastic part that yields in the limit an additional term in the Darcy’s law. We use the two-scale convergence method after extending the solution with 0 inside the holes to pass to the limit. By Itô stochastic calculus, we get uniform estimates on the solution in appropriate spaces. Due to the stochastic integral, the pressure that appears in the variational formulation does not have enough regularity in time. This fact made us rely only on the variational formulation for the passage to the limit on the solution. We obtain a variational formulation for the limit that is solution of a Stokes system with two pressures. This two-scale limit gives rise to three cell problems, two of them give the permeabilities while the third one gives an extra term in the Darcy’s law due to the stochastic perturbation on the boundary of the holes.

Stochastic Estimation via Polynomial Chaos

Science.gov (United States)

2015-10-01

AFRL-RW-EG-TR-2015-108 Stochastic Estimation via Polynomial Chaos Douglas V. Nance Air Force Research...COVERED (From - To) 20-04-2015 – 07-08-2015 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Stochastic Estimation via Polynomial Chaos ...This expository report discusses fundamental aspects of the polynomial chaos method for representing the properties of second order stochastic

Remarks on stochastic acceleration

International Nuclear Information System (INIS)

Graeff, P.

1982-12-01

Stochastic acceleration and turbulent diffusion are strong turbulence problems since no expansion parameter exists. Hence the problem of finding rigorous results is of major interest both for checking approximations and for reference models. Since we have found a way of constructing such models in the turbulent diffusion case the question of the extension to stochastic acceleration now arises. The paper offers some possibilities illustrated by the case of 'stochastic free fall' which may be particularly interesting in the context of linear response theory. (orig.)

Effect of perceptual load on conceptual processing: an extension of Vermeulen's theory.

Science.gov (United States)

Xie, Jiushu; Wang, Ruiming; Sun, Xun; Chang, Song

2013-10-01

The effect of color and shape load on conceptual processing was studied. Perceptual load effects have been found in visual and auditory conceptual processing, supporting the theory of embodied cognition. However, whether different types of visual concepts, such as color and shape, share the same perceptual load effects is unknown. In the current experiment, 32 participants were administered simultaneous perceptual and conceptual tasks to assess the relation between perceptual load and conceptual processing. Keeping color load in mind obstructed color conceptual processing. Hence, perceptual processing and conceptual load shared the same resources, suggesting embodied cognition. Color conceptual processing was not affected by shape pictures, indicating that different types of properties within vision were separate.

Stochastic parameterizing manifolds and non-Markovian reduced equations stochastic manifolds for nonlinear SPDEs II

CERN Document Server

Chekroun, Mickaël D; Wang, Shouhong

2015-01-01

In this second volume, a general approach is developed to provide approximate parameterizations of the "small" scales by the "large" ones for a broad class of stochastic partial differential equations (SPDEs). This is accomplished via the concept of parameterizing manifolds (PMs), which are stochastic manifolds that improve, for a given realization of the noise, in mean square error the partial knowledge of the full SPDE solution when compared to its projection onto some resolved modes. Backward-forward systems are designed to give access to such PMs in practice. The key idea consists of representing the modes with high wave numbers as a pullback limit depending on the time-history of the modes with low wave numbers. Non-Markovian stochastic reduced systems are then derived based on such a PM approach. The reduced systems take the form of stochastic differential equations involving random coefficients that convey memory effects. The theory is illustrated on a stochastic Burgers-type equation.

Stochastic spin-one massive field

International Nuclear Information System (INIS)

Lim, S.C.

1984-01-01

Stochastic quantization schemes of Nelson and Parisi and Wu are applied to a spin-one massive field. Unlike the scalar case Nelson's stochastic spin-one massive field cannot be identified with the corresponding euclidean field even if the fourth component of the euclidean coordinate is taken as equal to the real physical time. In the Parisi-Wu quantization scheme the stochastic Proca vector field has a similar property as the scalar field; which has an asymptotically stationary part and a transient part. The large equal-time limit of the expectation values of the stochastic Proca field are equal to the expectation values of the corresponding euclidean field. In the Stueckelberg formalism the Parisi-Wu scheme gives rise to a stochastic vector field which differs from the massless gauge field in that the gauge cannot be fixed by the choice of boundary condition. (orig.)

A Stochastic Maximum Principle for a Stochastic Differential Game of a Mean-Field Type

Energy Technology Data Exchange (ETDEWEB)

Hosking, John Joseph Absalom, E-mail: j.j.a.hosking@cma.uio.no [University of Oslo, Centre of Mathematics for Applications (CMA) (Norway)

2012-12-15

We construct a stochastic maximum principle (SMP) which provides necessary conditions for the existence of Nash equilibria in a certain form of N-agent stochastic differential game (SDG) of a mean-field type. The information structure considered for the SDG is of a possible asymmetric and partial type. To prove our SMP we take an approach based on spike-variations and adjoint representation techniques, analogous to that of S. Peng (SIAM J. Control Optim. 28(4):966-979, 1990) in the optimal stochastic control context. In our proof we apply adjoint representation procedures at three points. The first-order adjoint processes are defined as solutions to certain mean-field backward stochastic differential equations, and second-order adjoint processes of a first type are defined as solutions to certain backward stochastic differential equations. Second-order adjoint processes of a second type are defined as solutions of certain backward stochastic equations of a type that we introduce in this paper, and which we term conditional mean-field backward stochastic differential equations. From the resulting representations, we show that the terms relating to these second-order adjoint processes of the second type are of an order such that they do not appear in our final SMP equations. A comparable situation exists in an article by R. Buckdahn, B. Djehiche, and J. Li (Appl. Math. Optim. 64(2):197-216, 2011) that constructs a SMP for a mean-field type optimal stochastic control problem; however, the approach we take of using these second-order adjoint processes of a second type to deal with the type of terms that we refer to as the second form of quadratic-type terms represents an alternative to a development, to our setting, of the approach used in their article for their analogous type of term.

A Stochastic Maximum Principle for a Stochastic Differential Game of a Mean-Field Type

International Nuclear Information System (INIS)

Hosking, John Joseph Absalom

2012-01-01

We construct a stochastic maximum principle (SMP) which provides necessary conditions for the existence of Nash equilibria in a certain form of N-agent stochastic differential game (SDG) of a mean-field type. The information structure considered for the SDG is of a possible asymmetric and partial type. To prove our SMP we take an approach based on spike-variations and adjoint representation techniques, analogous to that of S. Peng (SIAM J. Control Optim. 28(4):966–979, 1990) in the optimal stochastic control context. In our proof we apply adjoint representation procedures at three points. The first-order adjoint processes are defined as solutions to certain mean-field backward stochastic differential equations, and second-order adjoint processes of a first type are defined as solutions to certain backward stochastic differential equations. Second-order adjoint processes of a second type are defined as solutions of certain backward stochastic equations of a type that we introduce in this paper, and which we term conditional mean-field backward stochastic differential equations. From the resulting representations, we show that the terms relating to these second-order adjoint processes of the second type are of an order such that they do not appear in our final SMP equations. A comparable situation exists in an article by R. Buckdahn, B. Djehiche, and J. Li (Appl. Math. Optim. 64(2):197–216, 2011) that constructs a SMP for a mean-field type optimal stochastic control problem; however, the approach we take of using these second-order adjoint processes of a second type to deal with the type of terms that we refer to as the second form of quadratic-type terms represents an alternative to a development, to our setting, of the approach used in their article for their analogous type of term.

Stochastic TDHF and the Boltzman-Langevin equation

International Nuclear Information System (INIS)

Suraud, E.; Reinhard, P.G.

1991-01-01

Outgoing from a time-dependent theory of correlations, we present a stochastic differential equation for the propagation of ensembles of Slater determinants, called Stochastic Time-Dependent Hartree-Fock (Stochastic TDHF). These ensembles are allowed to develop large fluctuations in the Hartree-Fock mean fields. An alternative stochastic differential equation, the Boltzmann-Langevin equation, can be derived from Stochastic TDHF by averaging over subensembles with small fluctuations

An electricity price model with consideration to load and gas price effects.

Science.gov (United States)

Huang, Min-xiang; Tao, Xiao-hu; Han, Zhen-xiang

2003-01-01

Some characteristics of the electricity load and prices are studied, and the relationship between electricity prices and gas (fuel) prices is analyzed in this paper. Because electricity prices are strongly dependent on load and gas prices, the authors constructed a model for electricity prices based on the effects of these two factors; and used the Geometric Mean Reversion Brownian Motion (GMRBM) model to describe the electricity load process, and a Geometric Brownian Motion(GBM) model to describe the gas prices; deduced the price stochastic process model based on the above load model and gas price model. This paper also presents methods for parameters estimation, and proposes some methods to solve the model.

SORM correction of FORM results for the FBC load combination problem

DEFF Research Database (Denmark)

Ditlevsen, Ove

2005-01-01

The old stochastic load combination model of Ferry Borges and Castanheta and the corresponding extreme random load effect value is considered. The evaluation of the distribution function of the extreme value by use of a particular first order reliability method was first described in a celebrated...... calculations. The calculation gives a limit state curvature correction factor on the probability approximation obtained by the RF algorithm. This correction factor is based on Breitung’s celebrated asymptotic formula. Example calculations with comparisons with exact results show an impressing accuracy...

Stochastic resonance in a stochastic bistable system with additive noises and square–wave signal

International Nuclear Information System (INIS)

Feng, Guo; Xiang-Dong, Luo; Shao-Fu, Li; Yu-Rong, Zhou

2010-01-01

This paper considers the stochastic resonance in a stochastic bistable system driven by a periodic square-wave signal and a static force as well as by additive white noise and dichotomous noise from the viewpoint of signal-to-noise ratio. It finds that the signal-to-noise ratio appears as stochastic resonance behaviour when it is plotted as a function of the noise strength of the white noise and dichotomous noise, as a function of the system parameters, or as a function of the static force. Moreover, the influence of the strength of the stochastic potential force and the correlation rate of the dichotomous noise on the signal-to-noise ratio is investigated. (general)

Stochastic quantization of Proca field

International Nuclear Information System (INIS)

Lim, S.C.

1981-03-01

We discuss the complications that arise in the application of Nelson's stochastic quantization scheme to classical Proca field. One consistent way to obtain spin-one massive stochastic field is given. It is found that the result of Guerra et al on the connection between ground state stochastic field and the corresponding Euclidean-Markov field extends to the spin-one case. (author)

Stochastic optimization methods

CERN Document Server

Marti, Kurt

2005-01-01

Optimization problems arising in practice involve random parameters. For the computation of robust optimal solutions, i.e., optimal solutions being insensitive with respect to random parameter variations, deterministic substitute problems are needed. Based on the distribution of the random data, and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into deterministic substitute problems. Due to the occurring probabilities and expectations, approximative solution techniques must be applied. Deterministic and stochastic approximation methods and their analytical properties are provided: Taylor expansion, regression and response surface methods, probability inequalities, First Order Reliability Methods, convex approximation/deterministic descent directions/efficient points, stochastic approximation methods, differentiation of probability and mean value functions. Convergence results of the resulting iterative solution procedures are given.

Multi-Objective Demand Response Model Considering the Probabilistic Characteristic of Price Elastic Load

Directory of Open Access Journals (Sweden)

Shengchun Yang

2016-01-01

Full Text Available Demand response (DR programs provide an effective approach for dealing with the challenge of wind power output fluctuations. Given that uncertain DR, such as price elastic load (PEL, plays an important role, the uncertainty of demand response behavior must be studied. In this paper, a multi-objective stochastic optimization problem of PEL is proposed on the basis of the analysis of the relationship between price elasticity and probabilistic characteristic, which is about stochastic demand models for consumer loads. The analysis aims to improve the capability of accommodating wind output uncertainty. In our approach, the relationship between the amount of demand response and interaction efficiency is developed by actively participating in power grid interaction. The probabilistic representation and uncertainty range of the PEL demand response amount are formulated differently compared with those of previous research. Based on the aforementioned findings, a stochastic optimization model with the combined uncertainties from the wind power output and the demand response scenario is proposed. The proposed model analyzes the demand response behavior of PEL by maximizing the electricity consumption satisfaction and interaction benefit satisfaction of PEL. Finally, a case simulation on the provincial power grid with a 151-bus system verifies the effectiveness and feasibility of the proposed mechanism and models.

Relevance of control theory to design and maintenance problems in time-variant reliability: The case of stochastic viability

International Nuclear Information System (INIS)

Rougé, Charles; Mathias, Jean-Denis; Deffuant, Guillaume

2014-01-01

The goal of this paper is twofold: (1) to show that time-variant reliability and a branch of control theory called stochastic viability address similar problems with different points of view, and (2) to demonstrate the relevance of concepts and methods from stochastic viability in reliability problems. On the one hand, reliability aims at evaluating the probability of failure of a system subjected to uncertainty and stochasticity. On the other hand, viability aims at maintaining a controlled dynamical system within a survival set. When the dynamical system is stochastic, this work shows that a viability problem belongs to a specific class of design and maintenance problems in time-variant reliability. Dynamic programming, which is used for solving Markovian stochastic viability problems, then yields the set of design states for which there exists a maintenance strategy which guarantees reliability with a confidence level β for a given period of time T. Besides, it leads to a straightforward computation of the date of the first outcrossing, informing on when the system is most likely to fail. We illustrate this approach with a simple example of population dynamics, including a case where load increases with time. - Highlights: • Time-variant reliability tools cannot devise complex maintenance strategies. • Stochastic viability is a control theory that computes a probability of failure. • Some design and maintenance problems are stochastic viability problems. • Used in viability, dynamic programming can find reliable maintenance actions. • Confronting reliability and control theories such as viability is promising

Phenomenology of stochastic exponential growth

Science.gov (United States)

Pirjol, Dan; Jafarpour, Farshid; Iyer-Biswas, Srividya

2017-06-01

Stochastic exponential growth is observed in a variety of contexts, including molecular autocatalysis, nuclear fission, population growth, inflation of the universe, viral social media posts, and financial markets. Yet literature on modeling the phenomenology of these stochastic dynamics has predominantly focused on one model, geometric Brownian motion (GBM), which can be described as the solution of a Langevin equation with linear drift and linear multiplicative noise. Using recent experimental results on stochastic exponential growth of individual bacterial cell sizes, we motivate the need for a more general class of phenomenological models of stochastic exponential growth, which are consistent with the observation that the mean-rescaled distributions are approximately stationary at long times. We show that this behavior is not consistent with GBM, instead it is consistent with power-law multiplicative noise with positive fractional powers. Therefore, we consider this general class of phenomenological models for stochastic exponential growth, provide analytical solutions, and identify the important dimensionless combination of model parameters, which determines the shape of the mean-rescaled distribution. We also provide a prescription for robustly inferring model parameters from experimentally observed stochastic growth trajectories.

NLP model and stochastic multi-start optimization approach for heat exchanger networks

International Nuclear Information System (INIS)

Núñez-Serna, Rosa I.; Zamora, Juan M.

2016-01-01

Highlights: • An NLP model for the optimal design of heat exchanger networks is proposed. • The NLP model is developed from a stage-wise grid diagram representation. • A two-phase stochastic multi-start optimization methodology is utilized. • Improved network designs are obtained with different heat load distributions. • Structural changes and reductions in the number of heat exchangers are produced. - Abstract: Heat exchanger network synthesis methodologies frequently identify good network structures, which nevertheless, might be accompanied by suboptimal values of design variables. The objective of this work is to develop a nonlinear programming (NLP) model and an optimization approach that aim at identifying the best values for intermediate temperatures, sub-stream flow rate fractions, heat loads and areas for a given heat exchanger network topology. The NLP model that minimizes the total annual cost of the network is constructed based on a stage-wise grid diagram representation. To improve the possibilities of obtaining global optimal designs, a two-phase stochastic multi-start optimization algorithm is utilized for the solution of the developed model. The effectiveness of the proposed optimization approach is illustrated with the optimization of two network designs proposed in the literature for two well-known benchmark problems. Results show that from the addressed base network topologies it is possible to achieve improved network designs, with redistributions in exchanger heat loads that lead to reductions in total annual costs. The results also show that the optimization of a given network design sometimes leads to structural simplifications and reductions in the total number of heat exchangers of the network, thereby exposing alternative viable network topologies initially not anticipated.

Towards an Erlang formula for multiclass networks

NARCIS (Netherlands)

Jonckheere, M.; Mairesse, J.

2010-01-01

Consider a multiclass stochastic network with state-dependent service rates and arrival rates describing bandwidth-sharing mechanisms as well as admission control and/or load balancing schemes. Given Poisson arrival and exponential service requirements, the number of customers in the network evolves

Controlling Buffeting Loads by Rudder and Piezo-Actuation

Science.gov (United States)

Moses, Robert W.; Pototzky, Anthony S.; Henderson, Douglas A.; Galea, Stephen C.; Manokaran, Donald S.; Zimcik, David G.; Wickramasinghe, Viresh; Pitt, Dale M.; Gamble, Michael A.

2005-01-01

High performance aircraft, especially those with twin vertical tails, encounter unsteady buffet loads when flying at high angles of attack. These stochastic loads result in significant stresses, which may cause fatigue damage leading to restricted capabilities and availability of the aircraft. An international collaborative research activity among Australia, Canada and the United States, conducted under the auspices of The Technical Cooperation Program (TTCP) contributed resources toward a program that coalesced a broad range of technical knowledge and expertise into a single investigation to demonstrate the enhanced performance and capability of the advanced active Buffet Load Alleviation ( ) control system in preparation for a flight test demonstration. The research team investigated the use of active structural control to alleviate the damaging structural response to these loads by applying advanced directional piezoelectric actuators, the aircraft rudder, switch mode amplifiers, and advanced control strategies on an F/A-18 aircraft empennage. Some results of the full-scale investigation are presented herein.

Optimal Control for Stochastic Delay Evolution Equations

Energy Technology Data Exchange (ETDEWEB)

Meng, Qingxin, E-mail: mqx@hutc.zj.cn [Huzhou University, Department of Mathematical Sciences (China); Shen, Yang, E-mail: skyshen87@gmail.com [York University, Department of Mathematics and Statistics (Canada)

2016-08-15

In this paper, we investigate a class of infinite-dimensional optimal control problems, where the state equation is given by a stochastic delay evolution equation with random coefficients, and the corresponding adjoint equation is given by an anticipated backward stochastic evolution equation. We first prove the continuous dependence theorems for stochastic delay evolution equations and anticipated backward stochastic evolution equations, and show the existence and uniqueness of solutions to anticipated backward stochastic evolution equations. Then we establish necessary and sufficient conditions for optimality of the control problem in the form of Pontryagin’s maximum principles. To illustrate the theoretical results, we apply stochastic maximum principles to study two examples, an infinite-dimensional linear-quadratic control problem with delay and an optimal control of a Dirichlet problem for a stochastic partial differential equation with delay. Further applications of the two examples to a Cauchy problem for a controlled linear stochastic partial differential equation and an optimal harvesting problem are also considered.

Stochastic Stability in Internet Router Congestion Games

Science.gov (United States)

Chung, Christine; Pyrga, Evangelia

Congestion control at bottleneck routers on the internet is a long standing problem. Many policies have been proposed for effective ways to drop packets from the queues of these routers so that network endpoints will be inclined to share router capacity fairly and minimize the overflow of packets trying to enter the queues. We study just how effective some of these queuing policies are when each network endpoint is a self-interested player with no information about the other players’ actions or preferences. By employing the adaptive learning model of evolutionary game theory, we study policies such as Droptail, RED, and the greedy-flow-punishing policy proposed by Gao et al. [10] to find the stochastically stable states: the states of the system that will be reached in the long run.

Introduction to stochastic calculus

CERN Document Server

Karandikar, Rajeeva L

2018-01-01

This book sheds new light on stochastic calculus, the branch of mathematics that is most widely applied in financial engineering and mathematical finance. The first book to introduce pathwise formulae for the stochastic integral, it provides a simple but rigorous treatment of the subject, including a range of advanced topics. The book discusses in-depth topics such as quadratic variation, Ito formula, and Emery topology. The authors briefly address continuous semi-martingales to obtain growth estimates and study solution of a stochastic differential equation (SDE) by using the technique of random time change. Later, by using Metivier–Pellumail inequality, the solutions to SDEs driven by general semi-martingales are discussed. The connection of the theory with mathematical finance is briefly discussed and the book has extensive treatment on the representation of martingales as stochastic integrals and a second fundamental theorem of asset pricing. Intended for undergraduate- and beginning graduate-level stud...

Load following operation of nuclear power plants for meeting power system requirements

International Nuclear Information System (INIS)

Isoda, Hachiro

1987-01-01

This paper describes a calculating program on the availability factors of nuclear, thermal and pumed storage hydro power stations and some calculated results for typical three load factors, 55 %, 60 % and 71 %, are provided when the share of the nuclea power station in the generation facilities is increased. The load following requirement of the nuclear power station is also provided. Load following requirement: If there is a 10 % pumped storage hydro power station, the nuclear power station enables to be operated with its rated output up to 30 % - 35 % of its share. Its daily load following operation for 40 % and 50 % nuclear power station needs every weekend and every day respectively. Availability factor: The availability factor of the nuclear power station manages to get 80 % (maximum availability factor of the nuclear power station in this study) up to 30 % share of it with 10 % pumpued storage hydro power station. When the nuclear power station shares 40 % and 50 %, its availability factor decreases down 1 % and 5 % respectively. (author)

Brownian motion, martingales, and stochastic calculus

CERN Document Server

Le Gall, Jean-François

2016-01-01

This book offers a rigorous and self-contained presentation of stochastic integration and stochastic calculus within the general framework of continuous semimartingales. The main tools of stochastic calculus, including Itô’s formula, the optional stopping theorem and Girsanov’s theorem, are treated in detail alongside many illustrative examples. The book also contains an introduction to Markov processes, with applications to solutions of stochastic differential equations and to connections between Brownian motion and partial differential equations. The theory of local times of semimartingales is discussed in the last chapter. Since its invention by Itô, stochastic calculus has proven to be one of the most important techniques of modern probability theory, and has been used in the most recent theoretical advances as well as in applications to other fields such as mathematical finance. Brownian Motion, Martingales, and Stochastic Calculus provides a strong theoretical background to the reader interested i...

A methodology for stochastic analysis of share prices as Markov chains with finite states.

Science.gov (United States)

Mettle, Felix Okoe; Quaye, Enoch Nii Boi; Laryea, Ravenhill Adjetey

2014-01-01

Price volatilities make stock investments risky, leaving investors in critical position when uncertain decision is made. To improve investor evaluation confidence on exchange markets, while not using time series methodology, we specify equity price change as a stochastic process assumed to possess Markov dependency with respective state transition probabilities matrices following the identified state pace (i.e. decrease, stable or increase). We established that identified states communicate, and that the chains are aperiodic and ergodic thus possessing limiting distributions. We developed a methodology for determining expected mean return time for stock price increases and also establish criteria for improving investment decision based on highest transition probabilities, lowest mean return time and highest limiting distributions. We further developed an R algorithm for running the methodology introduced. The established methodology is applied to selected equities from Ghana Stock Exchange weekly trading data.

Stochastic line motion and stochastic flux conservation for nonideal hydromagnetic models

International Nuclear Information System (INIS)

Eyink, Gregory L.

2009-01-01

We prove that smooth solutions of nonideal (viscous and resistive) incompressible magnetohydrodynamic (MHD) equations satisfy a stochastic law of flux conservation. This property implies that the magnetic flux through a surface is equal to the average of the magnetic fluxes through an ensemble of surfaces advected backward in time by the plasma velocity perturbed with a random white noise. Our result is an analog of the well-known Alfven theorem of ideal MHD and is valid for any value of the magnetic Prandtl number. A second stochastic conservation law is shown to hold at unit Prandtl number, a random version of the generalized Kelvin theorem derived by Bekenstein and Oron for ideal MHD. These stochastic conservation laws are not only shown to be consequences of the nonideal MHD equations but are proved in fact to be equivalent to those equations. We derive similar results for two more refined hydromagnetic models, Hall MHD and the two-fluid plasma model, still assuming incompressible velocities and isotropic transport coefficients. Finally, we use these results to discuss briefly the infinite-Reynolds-number limit of hydromagnetic turbulence and to support the conjecture that flux conservation remains stochastic in that limit.

Brownian motion and stochastic calculus

CERN Document Server

Karatzas, Ioannis

1998-01-01

This book is designed as a text for graduate courses in stochastic processes. It is written for readers familiar with measure-theoretic probability and discrete-time processes who wish to explore stochastic processes in continuous time. The vehicle chosen for this exposition is Brownian motion, which is presented as the canonical example of both a martingale and a Markov process with continuous paths. In this context, the theory of stochastic integration and stochastic calculus is developed. The power of this calculus is illustrated by results concerning representations of martingales and change of measure on Wiener space, and these in turn permit a presentation of recent advances in financial economics (option pricing and consumption/investment optimization). This book contains a detailed discussion of weak and strong solutions of stochastic differential equations and a study of local time for semimartingales, with special emphasis on the theory of Brownian local time. The text is complemented by a large num...

Variance decomposition in stochastic simulators.

Science.gov (United States)

Le Maître, O P; Knio, O M; Moraes, A

2015-06-28

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

Variance decomposition in stochastic simulators

Science.gov (United States)

Le Maître, O. P.; Knio, O. M.; Moraes, A.

2015-06-01

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

Variance decomposition in stochastic simulators

Energy Technology Data Exchange (ETDEWEB)

Le Maître, O. P., E-mail: olm@limsi.fr [LIMSI-CNRS, UPR 3251, Orsay (France); Knio, O. M., E-mail: knio@duke.edu [Department of Mechanical Engineering and Materials Science, Duke University, Durham, North Carolina 27708 (United States); Moraes, A., E-mail: alvaro.moraesgutierrez@kaust.edu.sa [King Abdullah University of Science and Technology, Thuwal (Saudi Arabia)

2015-06-28

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

Variance decomposition in stochastic simulators

KAUST Repository

Le Maî tre, O. P.; Knio, O. M.; Moraes, Alvaro

2015-01-01

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

Stochastic synaptic plasticity with memristor crossbar arrays

KAUST Repository

Naous, Rawan

2016-11-01

Memristive devices have been shown to exhibit slow and stochastic resistive switching behavior under low-voltage, low-current operating conditions. Here we explore such mechanisms to emulate stochastic plasticity in memristor crossbar synapse arrays. Interfaced with integrate-and-fire spiking neurons, the memristive synapse arrays are capable of implementing stochastic forms of spike-timing dependent plasticity which parallel mean-rate models of stochastic learning with binary synapses. We present theory and experiments with spike-based stochastic learning in memristor crossbar arrays, including simplified modeling as well as detailed physical simulation of memristor stochastic resistive switching characteristics due to voltage and current induced filament formation and collapse. © 2016 IEEE.

Stochastic synaptic plasticity with memristor crossbar arrays

KAUST Repository

Naous, Rawan; Al-Shedivat, Maruan; Neftci, Emre; Cauwenberghs, Gert; Salama, Khaled N.

2016-01-01

Memristive devices have been shown to exhibit slow and stochastic resistive switching behavior under low-voltage, low-current operating conditions. Here we explore such mechanisms to emulate stochastic plasticity in memristor crossbar synapse arrays. Interfaced with integrate-and-fire spiking neurons, the memristive synapse arrays are capable of implementing stochastic forms of spike-timing dependent plasticity which parallel mean-rate models of stochastic learning with binary synapses. We present theory and experiments with spike-based stochastic learning in memristor crossbar arrays, including simplified modeling as well as detailed physical simulation of memristor stochastic resistive switching characteristics due to voltage and current induced filament formation and collapse. © 2016 IEEE.

A worldwide flock of Condors : load sharing among workstation clusters

NARCIS (Netherlands)

Epema, D.H.J.; Livny, M.; Dantzig, van R.; Evers, X.; Pruyne, J.

1996-01-01

Condor is a distributed batch system for sharing the workload of compute-intensive jobs in a pool of unix workstations connected by a network. In such a Condor pool, idle machines are spotted by Condor and allocated to queued jobs, thus putting otherwise unutilized capacity to efficient use. When

An introduction to probability and stochastic processes

CERN Document Server

Melsa, James L

2013-01-01

Geared toward college seniors and first-year graduate students, this text is designed for a one-semester course in probability and stochastic processes. Topics covered in detail include probability theory, random variables and their functions, stochastic processes, linear system response to stochastic processes, Gaussian and Markov processes, and stochastic differential equations. 1973 edition.

Research on nonlinear stochastic dynamical price model

International Nuclear Information System (INIS)

Li Jiaorui; Xu Wei; Xie Wenxian; Ren Zhengzheng

2008-01-01

In consideration of many uncertain factors existing in economic system, nonlinear stochastic dynamical price model which is subjected to Gaussian white noise excitation is proposed based on deterministic model. One-dimensional averaged Ito stochastic differential equation for the model is derived by using the stochastic averaging method, and applied to investigate the stability of the trivial solution and the first-passage failure of the stochastic price model. The stochastic price model and the methods presented in this paper are verified by numerical studies

Stochastic Systems Uncertainty Quantification and Propagation

CERN Document Server

Grigoriu, Mircea

2012-01-01

Uncertainty is an inherent feature of both properties of physical systems and the inputs to these systems that needs to be quantified for cost effective and reliable designs. The states of these systems satisfy equations with random entries, referred to as stochastic equations, so that they are random functions of time and/or space. The solution of stochastic equations poses notable technical difficulties that are frequently circumvented by heuristic assumptions at the expense of accuracy and rigor. The main objective of Stochastic Systems is to promoting the development of accurate and efficient methods for solving stochastic equations and to foster interactions between engineers, scientists, and mathematicians. To achieve these objectives Stochastic Systems presents: ·         A clear and brief review of essential concepts on probability theory, random functions, stochastic calculus, Monte Carlo simulation, and functional analysis   ·          Probabilistic models for random variables an...

Stochastic-field cavitation model

International Nuclear Information System (INIS)

Dumond, J.; Magagnato, F.; Class, A.

2013-01-01

Nonlinear phenomena can often be well described using probability density functions (pdf) and pdf transport models. Traditionally, the simulation of pdf transport requires Monte-Carlo codes based on Lagrangian “particles” or prescribed pdf assumptions including binning techniques. Recently, in the field of combustion, a novel formulation called the stochastic-field method solving pdf transport based on Eulerian fields has been proposed which eliminates the necessity to mix Eulerian and Lagrangian techniques or prescribed pdf assumptions. In the present work, for the first time the stochastic-field method is applied to multi-phase flow and, in particular, to cavitating flow. To validate the proposed stochastic-field cavitation model, two applications are considered. First, sheet cavitation is simulated in a Venturi-type nozzle. The second application is an innovative fluidic diode which exhibits coolant flashing. Agreement with experimental results is obtained for both applications with a fixed set of model constants. The stochastic-field cavitation model captures the wide range of pdf shapes present at different locations

Stochastic-field cavitation model

Science.gov (United States)

Dumond, J.; Magagnato, F.; Class, A.

2013-07-01

Nonlinear phenomena can often be well described using probability density functions (pdf) and pdf transport models. Traditionally, the simulation of pdf transport requires Monte-Carlo codes based on Lagrangian "particles" or prescribed pdf assumptions including binning techniques. Recently, in the field of combustion, a novel formulation called the stochastic-field method solving pdf transport based on Eulerian fields has been proposed which eliminates the necessity to mix Eulerian and Lagrangian techniques or prescribed pdf assumptions. In the present work, for the first time the stochastic-field method is applied to multi-phase flow and, in particular, to cavitating flow. To validate the proposed stochastic-field cavitation model, two applications are considered. First, sheet cavitation is simulated in a Venturi-type nozzle. The second application is an innovative fluidic diode which exhibits coolant flashing. Agreement with experimental results is obtained for both applications with a fixed set of model constants. The stochastic-field cavitation model captures the wide range of pdf shapes present at different locations.

Stochastic Pi-calculus Revisited

DEFF Research Database (Denmark)

Cardelli, Luca; Mardare, Radu Iulian

2013-01-01

We develop a version of stochastic Pi-calculus with a semantics based on measure theory. We dene the behaviour of a process in a rate environment using measures over the measurable space of processes induced by structural congruence. We extend the stochastic bisimulation to include the concept of...

An application of almost marginal conditional stochastic dominance (AMCSD) on forming efficient portfolios

Science.gov (United States)

Slamet, Isnandar; Mardiana Putri Carissa, Siska; Pratiwi, Hasih

2017-10-01

Investors always seek an efficient portfolio which is a portfolio that has a maximum return on specific risk or minimal risk on specific return. Almost marginal conditional stochastic dominance (AMCSD) criteria can be used to form the efficient portfolio. The aim of this research is to apply the AMCSD criteria to form an efficient portfolio of bank shares listed in the LQ-45. This criteria is used when there are areas that do not meet the criteria of marginal conditional stochastic dominance (MCSD). On the other words, this criteria can be derived from quotient of areas that violate the MCSD criteria with the area that violate and not violate the MCSD criteria. Based on the data bank stocks listed on LQ-45, it can be stated that there are 38 efficient portfolios of 420 portfolios where each portfolio comprises of 4 stocks and 315 efficient portfolios of 1710 portfolios with each of portfolio has 3 stocks.

Stochastic volatility of volatility in continuous time

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole; Veraart, Almut

This paper introduces the concept of stochastic volatility of volatility in continuous time and, hence, extends standard stochastic volatility (SV) models to allow for an additional source of randomness associated with greater variability in the data. We discuss how stochastic volatility...... of volatility can be defined both non-parametrically, where we link it to the quadratic variation of the stochastic variance process, and parametrically, where we propose two new SV models which allow for stochastic volatility of volatility. In addition, we show that volatility of volatility can be estimated...

Quantum stochastic calculus associated with quadratic quantum noises

International Nuclear Information System (INIS)

Ji, Un Cig; Sinha, Kalyan B.

2016-01-01

We first study a class of fundamental quantum stochastic processes induced by the generators of a six dimensional non-solvable Lie †-algebra consisting of all linear combinations of the generalized Gross Laplacian and its adjoint, annihilation operator, creation operator, conservation, and time, and then we study the quantum stochastic integrals associated with the class of fundamental quantum stochastic processes, and the quantum Itô formula is revisited. The existence and uniqueness of solution of a quantum stochastic differential equation is proved. The unitarity conditions of solutions of quantum stochastic differential equations associated with the fundamental processes are examined. The quantum stochastic calculus extends the Hudson-Parthasarathy quantum stochastic calculus

Quantum stochastic calculus associated with quadratic quantum noises

Energy Technology Data Exchange (ETDEWEB)

Ji, Un Cig, E-mail: uncigji@chungbuk.ac.kr [Department of Mathematics, Research Institute of Mathematical Finance, Chungbuk National University, Cheongju, Chungbuk 28644 (Korea, Republic of); Sinha, Kalyan B., E-mail: kbs-jaya@yahoo.co.in [Jawaharlal Nehru Centre for Advanced Scientific Research, Jakkur, Bangalore-64, India and Department of Mathematics, Indian Institute of Science, Bangalore-12 (India)

2016-02-15

We first study a class of fundamental quantum stochastic processes induced by the generators of a six dimensional non-solvable Lie †-algebra consisting of all linear combinations of the generalized Gross Laplacian and its adjoint, annihilation operator, creation operator, conservation, and time, and then we study the quantum stochastic integrals associated with the class of fundamental quantum stochastic processes, and the quantum Itô formula is revisited. The existence and uniqueness of solution of a quantum stochastic differential equation is proved. The unitarity conditions of solutions of quantum stochastic differential equations associated with the fundamental processes are examined. The quantum stochastic calculus extends the Hudson-Parthasarathy quantum stochastic calculus.

Set-Valued Stochastic Lebesque Integral and Representation Theorems

Directory of Open Access Journals (Sweden)

Jungang Li

2008-06-01

Full Text Available In this paper, we shall firstly illustrate why we should introduce set-valued stochastic integrals, and then we shall discuss some properties of set-valued stochastic processes and the relation between a set-valued stochastic process and its selection set. After recalling the Aumann type definition of stochastic integral, we shall introduce a new definition of Lebesgue integral of a set-valued stochastic process with respect to the time t . Finally we shall prove the presentation theorem of set-valued stochastic integral and dis- cuss further properties that will be useful to study set-valued stochastic differential equations with their applications.

Instantaneous stochastic perturbation theory

International Nuclear Information System (INIS)

Lüscher, Martin

2015-01-01

A form of stochastic perturbation theory is described, where the representative stochastic fields are generated instantaneously rather than through a Markov process. The correctness of the procedure is established to all orders of the expansion and for a wide class of field theories that includes all common formulations of lattice QCD.

A retrodictive stochastic simulation algorithm

International Nuclear Information System (INIS)

Vaughan, T.G.; Drummond, P.D.; Drummond, A.J.

2010-01-01

In this paper we describe a simple method for inferring the initial states of systems evolving stochastically according to master equations, given knowledge of the final states. This is achieved through the use of a retrodictive stochastic simulation algorithm which complements the usual predictive stochastic simulation approach. We demonstrate the utility of this new algorithm by applying it to example problems, including the derivation of likely ancestral states of a gene sequence given a Markovian model of genetic mutation.

Stochastic processes and quantum theory

International Nuclear Information System (INIS)

Klauder, J.R.

1975-01-01

The author analyses a variety of stochastic processes, namely real time diffusion phenomena, which are analogues of imaginary time quantum theory and convariant imaginary time quantum field theory. He elaborates some standard properties involving probability measures and stochastic variables and considers a simple class of examples. Finally he develops the fact that certain stochastic theories actually exhibit divergences that simulate those of covariant quantum field theory and presents examples of both renormaizable and unrenormalizable behavior. (V.J.C.)

Stochastic quantization of Einstein gravity

International Nuclear Information System (INIS)

Rumpf, H.

1986-01-01

We determine a one-parameter family of covariant Langevin equations for the metric tensor of general relativity corresponding to DeWitt's one-parameter family of supermetrics. The stochastic source term in these equations can be expressed in terms of a Gaussian white noise upon the introduction of a stochastic tetrad field. The only physically acceptable resolution of a mathematical ambiguity in the ansatz for the source term is the adoption of Ito's calculus. By taking the formal equilibrium limit of the stochastic metric a one-parameter family of covariant path-integral measures for general relativity is obtained. There is a unique parameter value, distinguished by any one of the following three properties: (i) the metric is harmonic with respect to the supermetric, (ii) the path-integral measure is that of DeWitt, (iii) the supermetric governs the linearized Einstein dynamics. Moreover the Feynman propagator corresponding to this parameter is causal. Finally we show that a consistent stochastic perturbation theory gives rise to a new type of diagram containing ''stochastic vertices.''

Momentum Maps and Stochastic Clebsch Action Principles

Science.gov (United States)

Cruzeiro, Ana Bela; Holm, Darryl D.; Ratiu, Tudor S.

2018-01-01

We derive stochastic differential equations whose solutions follow the flow of a stochastic nonlinear Lie algebra operation on a configuration manifold. For this purpose, we develop a stochastic Clebsch action principle, in which the noise couples to the phase space variables through a momentum map. This special coupling simplifies the structure of the resulting stochastic Hamilton equations for the momentum map. In particular, these stochastic Hamilton equations collectivize for Hamiltonians that depend only on the momentum map variable. The Stratonovich equations are derived from the Clebsch variational principle and then converted into Itô form. In comparing the Stratonovich and Itô forms of the stochastic dynamical equations governing the components of the momentum map, we find that the Itô contraction term turns out to be a double Poisson bracket. Finally, we present the stochastic Hamiltonian formulation of the collectivized momentum map dynamics and derive the corresponding Kolmogorov forward and backward equations.

Insensitivity of proportional fairness in critically loaded bandwidth sharing networks

NARCIS (Netherlands)

Vlasiou, M.; Zhang, J.; Zwart, B.

2014-01-01

Proportional fairness is a popular service allocation mechanism to describe and analyze the performance of data networks at flow level. Recently, several authors have shown that the invariant distribution of such networks admits a product form distribution under critical loading. Assuming

Feasibility of Stochastic Voltage/VAr Optimization Considering Renewable Energy Resources for Smart Grid

Science.gov (United States)

Momoh, James A.; Salkuti, Surender Reddy

2016-06-01

This paper proposes a stochastic optimization technique for solving the Voltage/VAr control problem including the load demand and Renewable Energy Resources (RERs) variation. The RERs often take along some inputs like stochastic behavior. One of the important challenges i. e., Voltage/VAr control is a prime source for handling power system complexity and reliability, hence it is the fundamental requirement for all the utility companies. There is a need for the robust and efficient Voltage/VAr optimization technique to meet the peak demand and reduction of system losses. The voltages beyond the limit may damage costly sub-station devices and equipments at consumer end as well. Especially, the RERs introduces more disturbances and some of the RERs are not even capable enough to meet the VAr demand. Therefore, there is a strong need for the Voltage/VAr control in RERs environment. This paper aims at the development of optimal scheme for Voltage/VAr control involving RERs. In this paper, Latin Hypercube Sampling (LHS) method is used to cover full range of variables by maximally satisfying the marginal distribution. Here, backward scenario reduction technique is used to reduce the number of scenarios effectively and maximally retain the fitting accuracy of samples. The developed optimization scheme is tested on IEEE 24 bus Reliability Test System (RTS) considering the load demand and RERs variation.

Deterministic and stochastic approach for safety and reliability optimization of captive power plant maintenance scheduling using GA/SA-based hybrid techniques: A comparison of results

International Nuclear Information System (INIS)

Mohanta, Dusmanta Kumar; Sadhu, Pradip Kumar; Chakrabarti, R.

2007-01-01

This paper presents a comparison of results for optimization of captive power plant maintenance scheduling using genetic algorithm (GA) as well as hybrid GA/simulated annealing (SA) techniques. As utilities catered by captive power plants are very sensitive to power failure, therefore both deterministic and stochastic reliability objective functions have been considered to incorporate statutory safety regulations for maintenance of boilers, turbines and generators. The significant contribution of this paper is to incorporate stochastic feature of generating units and that of load using levelized risk method. Another significant contribution of this paper is to evaluate confidence interval for loss of load probability (LOLP) because some variations from optimum schedule are anticipated while executing maintenance schedules due to different real-life unforeseen exigencies. Such exigencies are incorporated in terms of near-optimum schedules obtained from hybrid GA/SA technique during the final stages of convergence. Case studies corroborate that same optimum schedules are obtained using GA and hybrid GA/SA for respective deterministic and stochastic formulations. The comparison of results in terms of interval of confidence for LOLP indicates that levelized risk method adequately incorporates the stochastic nature of power system as compared with levelized reserve method. Also the interval of confidence for LOLP denotes the possible risk in a quantified manner and it is of immense use from perspective of captive power plants intended for quality power

Stochastic biomathematical models with applications to neuronal modeling

CERN Document Server

Batzel, Jerry; Ditlevsen, Susanne

2013-01-01

Stochastic biomathematical models are becoming increasingly important as new light is shed on the role of noise in living systems. In certain biological systems, stochastic effects may even enhance a signal, thus providing a biological motivation for the noise observed in living systems. Recent advances in stochastic analysis and increasing computing power facilitate the analysis of more biophysically realistic models, and this book provides researchers in computational neuroscience and stochastic systems with an overview of recent developments. Key concepts are developed in chapters written by experts in their respective fields. Topics include: one-dimensional homogeneous diffusions and their boundary behavior, large deviation theory and its application in stochastic neurobiological models, a review of mathematical methods for stochastic neuronal integrate-and-fire models, stochastic partial differential equation models in neurobiology, and stochastic modeling of spreading cortical depression.

Supplier Short Term Load Forecasting Using Support Vector Regression and Exogenous Input

Science.gov (United States)

Matijaš, Marin; Vukićcević, Milan; Krajcar, Slavko

2011-09-01

In power systems, task of load forecasting is important for keeping equilibrium between production and consumption. With liberalization of electricity markets, task of load forecasting changed because each market participant has to forecast their own load. Consumption of end-consumers is stochastic in nature. Due to competition, suppliers are not in a position to transfer their costs to end-consumers; therefore it is essential to keep forecasting error as low as possible. Numerous papers are investigating load forecasting from the perspective of the grid or production planning. We research forecasting models from the perspective of a supplier. In this paper, we investigate different combinations of exogenous input on the simulated supplier loads and show that using points of delivery as a feature for Support Vector Regression leads to lower forecasting error, while adding customer number in different datasets does the opposite.

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

Stochastic Finite Elements in Reliability-Based Structural Optimization

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard; Engelund, S.

Application of stochastic finite elements in structural optimization is considered. It is shown how stochastic fields modelling e.g. the modulus of elasticity can be discretized in stochastic variables and how a sensitivity analysis of the reliability of a structural system with respect to optimi......Application of stochastic finite elements in structural optimization is considered. It is shown how stochastic fields modelling e.g. the modulus of elasticity can be discretized in stochastic variables and how a sensitivity analysis of the reliability of a structural system with respect...

Stochastic first passage time accelerated with CUDA

Science.gov (United States)

Pierro, Vincenzo; Troiano, Luigi; Mejuto, Elena; Filatrella, Giovanni

2018-05-01

The numerical integration of stochastic trajectories to estimate the time to pass a threshold is an interesting physical quantity, for instance in Josephson junctions and atomic force microscopy, where the full trajectory is not accessible. We propose an algorithm suitable for efficient implementation on graphical processing unit in CUDA environment. The proposed approach for well balanced loads achieves almost perfect scaling with the number of available threads and processors, and allows an acceleration of about 400× with a GPU GTX980 respect to standard multicore CPU. This method allows with off the shell GPU to challenge problems that are otherwise prohibitive, as thermal activation in slowly tilted potentials. In particular, we demonstrate that it is possible to simulate the switching currents distributions of Josephson junctions in the timescale of actual experiments.

BRST stochastic quantization

International Nuclear Information System (INIS)

Hueffel, H.

1990-01-01

After a brief review of the BRST formalism and of the Parisi-Wu stochastic quantization method we introduce the BRST stochastic quantization scheme. It allows the second quantization of constrained Hamiltonian systems in a manifestly gauge symmetry preserving way. The examples of the relativistic particle, the spinning particle and the bosonic string are worked out in detail. The paper is closed by a discussion on the interacting field theory associated to the relativistic point particle system. 58 refs. (Author)

Stochastic quantum gravity

International Nuclear Information System (INIS)

Rumpf, H.

1987-01-01

We begin with a naive application of the Parisi-Wu scheme to linearized gravity. This will lead into trouble as one peculiarity of the full theory, the indefiniteness of the Euclidean action, shows up already at this level. After discussing some proposals to overcome this problem, Minkowski space stochastic quantization will be introduced. This will still not result in an acceptable quantum theory of linearized gravity, as the Feynman propagator turns out to be non-causal. This defect will be remedied only after a careful analysis of general covariance in stochastic quantization has been performed. The analysis requires the notion of a metric on the manifold of metrics, and a natural candidate for this is singled out. With this a consistent stochastic quantization of Einstein gravity becomes possible. It is even possible, at least perturbatively, to return to the Euclidean regime. 25 refs. (Author)

Stochastic models, estimation, and control

CERN Document Server

Maybeck, Peter S

1982-01-01

This volume builds upon the foundations set in Volumes 1 and 2. Chapter 13 introduces the basic concepts of stochastic control and dynamic programming as the fundamental means of synthesizing optimal stochastic control laws.

Energy management in microgrid based on the multi objective stochastic programming incorporating portable renewable energy resource as demand response option

International Nuclear Information System (INIS)

Tabar, Vahid Sohrabi; Jirdehi, Mehdi Ahmadi; Hemmati, Reza

2017-01-01

Renewable energy resources are often known as cost-effective and lucrative resources and have been widely developed due to environmental-economic issues. Renewable energy utilization even in small scale (e.g., microgrid networks) has attracted significant attention. Energy management in microgrid can be carried out based on the generating side management or demand side management. In this paper, portable renewable energy resource are modeled and included in microgrid energy management as a demand response option. Utilizing such resources could supply the load when microgrid cannot serve the demand. This paper addresses energy management and scheduling in microgrid including thermal and electrical loads, renewable energy sources (solar and wind), CHP, conventional energy sources (boiler and micro turbine), energy storage systems (thermal and electrical ones), and portable renewable energy resource (PRER). Operational cost of microgrid and air pollution are considered as objective functions. Uncertainties related to the parameters are incorporated to make a stochastic programming. The proposed problem is expressed as a constrained, multi-objective, linear, and mixed-integer programing. Augmented Epsilon-constraint method is used to solve the problem. Final results and calculations are achieved using GAMS24.1.3/CPLEX12.5.1. Simulation results demonstrate the viability and effectiveness of the proposed method in microgrid energy management. - Highlights: • Introducing portable renewable energy resource (PRER) and considering effect of them. • Considering reserve margin and sensitivity analysis for validate robustness. • Multi objective and stochastic management with considering various loads and sources. • Using augmented Epsilon-constraint method to solve multi objective program. • Highly decreasing total cost and pollution with PRER in stochastic state.

Stochastic theories of quantum mechanics

International Nuclear Information System (INIS)

De la Pena, L.; Cetto, A.M.

1991-01-01

The material of this article is organized into five sections. In Sect. I the basic characteristics of quantum systems are briefly discussed, with emphasis on their stochastic properties. In Sect. II a version of stochastic quantum mechanics is presented, to conclude that the quantum formalism admits an interpretation in terms of stochastic processes. In Sect. III the elements of stochastic electrodynamics are described, and its possibilities and limitations as a fundamental theory of quantum systems are discussed. Section IV contains a recent reformulation that overcomes the limitations of the theory discussed in the foregoing section. Finally, in Sect. V the theorems of EPR, Von Neumann and Bell are discussed briefly. The material is pedagogically presented and includes an ample list of references, but the details of the derivations are generally omitted. (Author)

A heterogeneous stochastic FEM framework for elliptic PDEs

International Nuclear Information System (INIS)

Hou, Thomas Y.; Liu, Pengfei

2015-01-01

We introduce a new concept of sparsity for the stochastic elliptic operator −div(a(x,ω)∇(⋅)), which reflects the compactness of its inverse operator in the stochastic direction and allows for spatially heterogeneous stochastic structure. This new concept of sparsity motivates a heterogeneous stochastic finite element method (HSFEM) framework for linear elliptic equations, which discretizes the equations using the heterogeneous coupling of spatial basis with local stochastic basis to exploit the local stochastic structure of the solution space. We also provide a sampling method to construct the local stochastic basis for this framework using the randomized range finding techniques. The resulting HSFEM involves two stages and suits the multi-query setting: in the offline stage, the local stochastic structure of the solution space is identified; in the online stage, the equation can be efficiently solved for multiple forcing functions. An online error estimation and correction procedure through Monte Carlo sampling is given. Numerical results for several problems with high dimensional stochastic input are presented to demonstrate the efficiency of the HSFEM in the online stage

Three-Level Supply Chain Coordination under Disruptions Based on Revenue-Sharing Contract with Price Dependent Demand

Directory of Open Access Journals (Sweden)

Qinghua Pang

2014-01-01

Full Text Available Considering the market demand is stochastic and dependent on price, this paper shows that the revenue-sharing contract could coordinate a three-level supply chain consisting of one manufacturer, one distributor, and one retailer under normal environment. However, the original revenue-sharing contract cannot coordinate the supply chain under disruptions in circumstances of certain incidents leading to significant changes in market demand and causing additional deviation costs. To solve the problem, this essay introduces two improved forms of revenue-sharing contract: a mixed contract form based on a quantity discount policy and a pure form, which are characterized by antidisruption ability. The model of improved revenue-sharing contract is optimized when the market demand is in the additive form or in the multiplicative form with price dependent demand. Formulas are given to calculate the optimal contract parameters. Finally, this essay demonstrates the accuracy of the model of improved revenue-sharing contract with the help of numerical examples.

Separable quadratic stochastic operators

International Nuclear Information System (INIS)

Rozikov, U.A.; Nazir, S.

2009-04-01

We consider quadratic stochastic operators, which are separable as a product of two linear operators. Depending on properties of these linear operators we classify the set of the separable quadratic stochastic operators: first class of constant operators, second class of linear and third class of nonlinear (separable) quadratic stochastic operators. Since the properties of operators from the first and second classes are well known, we mainly study the properties of the operators of the third class. We describe some Lyapunov functions of the operators and apply them to study ω-limit sets of the trajectories generated by the operators. We also compare our results with known results of the theory of quadratic operators and give some open problems. (author)

Trajectory averaging for stochastic approximation MCMC algorithms

KAUST Repository

Liang, Faming

2010-01-01

to the stochastic approximation Monte Carlo algorithm [Liang, Liu and Carroll J. Amer. Statist. Assoc. 102 (2007) 305-320]. The application of the trajectory averaging estimator to other stochastic approximationMCMC algorithms, for example, a stochastic

Dynamical and hamiltonian dilations of stochastic processes

International Nuclear Information System (INIS)

Baumgartner, B.; Gruemm, H.-R.

1982-01-01

This is a study of the problem, which stochastic processes could arise from dynamical systems by loss of information. The notions of ''dilation'' and ''approximate dilation'' of a stochastic process are introduced to give exact definitions of this particular relationship. It is shown that every generalized stochastic process is approximately dilatable by a sequence of dynamical systems, but for stochastic processes in full generality one needs nets. (Author)

Sharing wind power forecasts in electricity markets: A numerical analysis

International Nuclear Information System (INIS)

Exizidis, Lazaros; Kazempour, S. Jalal; Pinson, Pierre; Greve, Zacharie de; Vallée, François

2016-01-01

Highlights: • Information sharing among different agents can be beneficial for electricity markets. • System cost decreases by sharing wind power forecasts between different agents. • Market power of wind producer may increase by sharing forecasts with market operator. • Extensive out-of-sample analysis is employed to draw reliable conclusions. - Abstract: In an electricity pool with significant share of wind power, all generators including conventional and wind power units are generally scheduled in a day-ahead market based on wind power forecasts. Then, a real-time market is cleared given the updated wind power forecast and fixed day-ahead decisions to adjust power imbalances. This sequential market-clearing process may cope with serious operational challenges such as severe power shortage in real-time due to erroneous wind power forecasts in day-ahead market. To overcome such situations, several solutions can be considered such as adding flexible resources to the system. In this paper, we address another potential solution based on information sharing in which market players share their own wind power forecasts with others in day-ahead market. This solution may improve the functioning of sequential market-clearing process through making more informed day-ahead schedules, which reduces the need for balancing resources in real-time operation. This paper numerically evaluates the potential value of sharing forecasts for the whole system in terms of system cost reduction. Besides, its impact on each market player’s profit is analyzed. The framework of this study is based on a stochastic two-stage market setup and complementarity modeling, which allows us to gain further insights into information sharing impacts.

Revenue Share between Layers and Investment Incentive for ISP in the Internet Market

Science.gov (United States)

Unno, Masaru; Xu, Hua

In this paper, we consider a revenue-sharing and network investment problem between an Internet service provider (ISP) and a content provider (CP) by applying the dynamic agency theory. We formulate the problem as the principal-agent problem where the ISP is the principal and the CP is the agent. The principal-agent problem is transformed to a stochastic optimal control problem in which the objectives of ISP are to find an optimal revenue-sharing strategy and a network investment strategy, and to advise an incentive compatible effort level to the CP. The sufficient conditions for the existence of the optimal revenue-sharing strategy, the optimal investment strategy and the incentive compatible effort to the CP are obtained. A numerical example is solved to show the existence of such strategies. The practical implications of the results obtained in the paper will also be discussed.

Transport in Stochastic Media

International Nuclear Information System (INIS)

Haran, O.; Shvarts, D.; Thieberger, R.

1998-01-01

Classical transport of neutral particles in a binary, scattering, stochastic media is discussed. It is assumed that the cross-sections of the constituent materials and their volume fractions are known. The inner structure of the media is stochastic, but there exist a statistical knowledge about the lump sizes, shapes and arrangement. The transmission through the composite media depends on the specific heterogeneous realization of the media. The current research focuses on the averaged transmission through an ensemble of realizations, frm which an effective cross-section for the media can be derived. The problem of one dimensional transport in stochastic media has been studied extensively [1]. In the one dimensional description of the problem, particles are transported along a line populated with alternating material segments of random lengths. The current work discusses transport in two-dimensional stochastic media. The phenomenon that is unique to the multi-dimensional description of the problem is obstacle bypassing. Obstacle bypassing tends to reduce the opacity of the media, thereby reducing its effective cross-section. The importance of this phenomenon depends on the manner in which the obstacles are arranged in the media. Results of transport simulations in multi-dimensional stochastic media are presented. Effective cross-sections derived from the simulations are compared against those obtained for the one-dimensional problem, and against those obtained from effective multi-dimensional models, which are partially based on a Markovian assumption

Stochastic Stability of Endogenous Growth: Theory and Applications

OpenAIRE

Boucekkine, Raouf; Pintus, Patrick; Zou, Benteng

2015-01-01

We examine the issue of stability of stochastic endogenous growth. First, stochastic stability concepts are introduced and applied to stochastic linear homogenous differen- tial equations to which several stochastic endogenous growth models reduce. Second, we apply the mathematical theory to two models, starting with the stochastic AK model. It’s shown that in this case exponential balanced paths, which characterize optimal trajectories in the absence of uncertainty, are not robust to uncerta...

Estimating risks for water-quality exceedances of total-copper from highway and urban runoff under predevelopment and current conditions with the Stochastic Empirical Loading and Dilution Model (SELDM)

Science.gov (United States)

Granato, Gregory E.; Jones, Susan C.; Dunn, Christopher N.; Van Weele, Brian

2017-01-01

The stochastic empirical loading and dilution model (SELDM) was used to demonstrate methods for estimating risks for water-quality exceedances of event-mean concentrations (EMCs) of total-copper. Monte Carlo methods were used to simulate stormflow, total-hardness, suspended-sediment, and total-copper EMCs as stochastic variables. These simulations were done for the Charles River Basin upstream of Interstate 495 in Bellingham, Massachusetts. The hydrology and water quality of this site were simulated with SELDM by using data from nearby, hydrologically similar sites. Three simulations were done to assess the potential effects of the highway on receiving-water quality with and without highway-runoff treatment by a structural best-management practice (BMP). In the low-development scenario, total copper in the receiving stream was simulated by using a sediment transport curve, sediment chemistry, and sediment-water partition coefficients. In this scenario, neither the highway runoff nor the BMP effluent caused concentration exceedances in the receiving stream that exceed the once in three-year threshold (about 0.54 percent). In the second scenario, without the highway, runoff from the large urban areas in the basin caused exceedances in the receiving stream in 2.24 percent of runoff events. In the third scenario, which included the effects of the urban runoff, neither the highway runoff nor the BMP effluent increased the percentage of exceedances in the receiving stream. Comparison of the simulated geometric mean EMCs with data collected at a downstream monitoring site indicates that these simulated values are within the 95-percent confidence interval of the geometric mean of the measured EMCs.

Stochastic models: theory and simulation.

Energy Technology Data Exchange (ETDEWEB)

Field, Richard V., Jr.

2008-03-01

Many problems in applied science and engineering involve physical phenomena that behave randomly in time and/or space. Examples are diverse and include turbulent flow over an aircraft wing, Earth climatology, material microstructure, and the financial markets. Mathematical models for these random phenomena are referred to as stochastic processes and/or random fields, and Monte Carlo simulation is the only general-purpose tool for solving problems of this type. The use of Monte Carlo simulation requires methods and algorithms to generate samples of the appropriate stochastic model; these samples then become inputs and/or boundary conditions to established deterministic simulation codes. While numerous algorithms and tools currently exist to generate samples of simple random variables and vectors, no cohesive simulation tool yet exists for generating samples of stochastic processes and/or random fields. There are two objectives of this report. First, we provide some theoretical background on stochastic processes and random fields that can be used to model phenomena that are random in space and/or time. Second, we provide simple algorithms that can be used to generate independent samples of general stochastic models. The theory and simulation of random variables and vectors is also reviewed for completeness.

Decentralized Electric Vehicle Charging Strategies for Reduced Load Variation and Guaranteed Charge Completion in Regional Distribution Grids

Directory of Open Access Journals (Sweden)

Weige Zhang

2017-01-01

Full Text Available A novel, fully decentralized strategy to coordinate charge operation of electric vehicles is proposed in this paper. Based on stochastic switching control of on-board chargers, this strategy ensures high-efficiency charging, reduces load variations to the grid during charging periods, achieves charge completion with high probability, and accomplishes approximate “valley-filling”. Further improvements on the core strategy, including individualized power management, adaptive strategies, and battery support systems, are introduced to further reduce power fluctuation variances and to guarantee charge completion. Stochastic analysis is performed to establish the main properties of the strategies and to quantitatively show the performance improvements. Compared with the existing decentralized charging strategies, the strategies proposed in this paper can be implemented without any information exchange between grid operators and electric vehicles (EVs, resulting in a communications cost reduction. Additionally, it is shown that by using stochastic charging rules, a grid-supporting battery system with a very small energy capacity can achieve substantial reduction of EV load fluctuations with high confidence. An extensive set of simulations and case studies with real-world data are used to demonstrate the benefits of the proposed strategies.

An Augmented Incomplete Factorization Approach for Computing the Schur Complement in Stochastic Optimization

KAUST Repository

Petra, Cosmin G.; Schenk, Olaf; Lubin, Miles; Gä ertner, Klaus

2014-01-01

We present a scalable approach and implementation for solving stochastic optimization problems on high-performance computers. In this work we revisit the sparse linear algebra computations of the parallel solver PIPS with the goal of improving the shared-memory performance and decreasing the time to solution. These computations consist of solving sparse linear systems with multiple sparse right-hand sides and are needed in our Schur-complement decomposition approach to compute the contribution of each scenario to the Schur matrix. Our novel approach uses an incomplete augmented factorization implemented within the PARDISO linear solver and an outer BiCGStab iteration to efficiently absorb pivot perturbations occurring during factorization. This approach is capable of both efficiently using the cores inside a computational node and exploiting sparsity of the right-hand sides. We report on the performance of the approach on highperformance computers when solving stochastic unit commitment problems of unprecedented size (billions of variables and constraints) that arise in the optimization and control of electrical power grids. Our numerical experiments suggest that supercomputers can be efficiently used to solve power grid stochastic optimization problems with thousands of scenarios under the strict "real-time" requirements of power grid operators. To our knowledge, this has not been possible prior to the present work. © 2014 Society for Industrial and Applied Mathematics.

Stochastic diffusion models for substitutable technological innovations

NARCIS (Netherlands)

Wang, L.; Hu, B.; Yu, X.

2004-01-01

Based on the analysis of firms' stochastic adoption behaviour, this paper first points out the necessity to build more practical stochastic models. And then, stochastic evolutionary models are built for substitutable innovation diffusion system. Finally, through the computer simulation of the

Stochasticity in the Josephson map

International Nuclear Information System (INIS)

Nomura, Y.; Ichikawa, Y.H.; Filippov, A.T.

1996-04-01

The Josephson map describes nonlinear dynamics of systems characterized by standard map with the uniform external bias superposed. The intricate structures of the phase space portrait of the Josephson map are examined on the basis of the tangent map associated with the Josephson map. Numerical observation of the stochastic diffusion in the Josephson map is examined in comparison with the renormalized diffusion coefficient calculated by the method of characteristic function. The global stochasticity of the Josephson map occurs at the values of far smaller stochastic parameter than the case of the standard map. (author)

Direct access inter-process shared memory

Science.gov (United States)

Brightwell, Ronald B; Pedretti, Kevin; Hudson, Trammell B

2013-10-22

A technique for directly sharing physical memory between processes executing on processor cores is described. The technique includes loading a plurality of processes into the physical memory for execution on a corresponding plurality of processor cores sharing the physical memory. An address space is mapped to each of the processes by populating a first entry in a top level virtual address table for each of the processes. The address space of each of the processes is cross-mapped into each of the processes by populating one or more subsequent entries of the top level virtual address table with the first entry in the top level virtual address table from other processes.

Energy Sharing Framework for Microgrid-Powered Cellular Base Stations

KAUST Repository

Farooq, Muhammad Junaid

2017-02-07

Cellular base stations (BSs) are increasingly becoming equipped with renewable energy generators to reduce operational expenditures and carbon footprint of wireless communications. Moreover, advancements in the traditional electricity grid allow two-way power flow and metering that enable the integration of distributed renewable energy generators at BS sites into a microgrid. In this paper, we develop an optimized energy management framework for microgrid-connected cellular BSs that are equipped with renewable energy generators and finite battery storage to minimize energy cost. The BSs share excess renewable energy with others to reduce the dependency on the conventional electricity grid. Three cases are investigated where the renewable energy generation is unknown, perfectly known, and partially known ahead of time. For the partially known case where only the statistics of renewable energy generation are available, stochastic programming is used to achieve a conservative solution. Results show the time varying energy management behaviour of the BSs and the effect of energy sharing between them.

Numerical Simulation of the Heston Model under Stochastic Correlation

Directory of Open Access Journals (Sweden)

Long Teng

2017-12-01

Full Text Available Stochastic correlation models have become increasingly important in financial markets. In order to be able to price vanilla options in stochastic volatility and correlation models, in this work, we study the extension of the Heston model by imposing stochastic correlations driven by a stochastic differential equation. We discuss the efficient algorithms for the extended Heston model by incorporating stochastic correlations. Our numerical experiments show that the proposed algorithms can efficiently provide highly accurate results for the extended Heston by including stochastic correlations. By investigating the effect of stochastic correlations on the implied volatility, we find that the performance of the Heston model can be proved by including stochastic correlations.

Stochastic Finite Elements in Reliability-Based Structural Optimization

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard; Engelund, S.

1995-01-01

Application of stochastic finite elements in structural optimization is considered. It is shown how stochastic fields modelling e.g. the modulus of elasticity can be discretized in stochastic variables and how a sensitivity analysis of the reliability of a structural system with respect to optimi......Application of stochastic finite elements in structural optimization is considered. It is shown how stochastic fields modelling e.g. the modulus of elasticity can be discretized in stochastic variables and how a sensitivity analysis of the reliability of a structural system with respect...... to optimization variables can be performed. A computer implementation is described and an illustrative example is given....

Copula-based modeling of stochastic wind power in Europe and implications for the Swiss power grid

International Nuclear Information System (INIS)

Hagspiel, Simeon; Papaemannouil, Antonis; Schmid, Matthias; Andersson, Göran

2012-01-01

Highlights: ► We model stochastic wind power using copula theory. ► Stochastic wind power is integrated in a European system adequacy evaluation. ► The Swiss power grid is put at risk by further integrating wind power in Europe. ► System elements located at or close to Swiss borders are affected the most. ► A criticality indicator allows prioritizing expansion plans on a probabilistic basis. -- Abstract: Large scale integration of wind energy poses new challenges to the European power system due to its stochastic nature and often remote location. In this paper a multivariate uncertainty analysis problem is formulated for the integration of stochastic wind energy in the European grid. By applying copula theory a synthetic set of data is generated from scarce wind speed reanalysis data in order to achieve the increased sample size for the subsequent Monte Carlo simulation. In the presented case study, European wind power samples are generated from the modeled stochastic process. Under the precondition of a modeled perfect market environment, wind power impacts dispatch decisions and therefore leads to alterations in power balances. Stochastic power balances are implemented in a detailed model of the European electricity network, based on the generated samples. Finally, a Monte Carlo method is used to determine power flows and contingencies in the system. An indicator is elaborated in order to analyze risk of overloading and to prioritize necessary grid reinforcements. Implications for the Swiss power grid are investigated in detail, revealing that the current system is significantly put at risk in certain areas by the further integration of wind power in Europe. It is the first time that the results of a probabilistic model for wind energy are further deployed within a power system analysis of the interconnected European grid. The method presented in this paper allows to account for stochastic wind energy in a load flow analysis and to evaluate

Stochastic Modeling and Optimization in a Microgrid: A Survey

Directory of Open Access Journals (Sweden)

Hao Liang

2014-03-01

Full Text Available The future smart grid is expected to be an interconnected network of small-scale and self-contained microgrids, in addition to a large-scale electric power backbone. By utilizing microsources, such as renewable energy sources and combined heat and power plants, microgrids can supply electrical and heat loads in local areas in an economic and environment friendly way. To better adopt the intermittent and weather-dependent renewable power generation, energy storage devices, such as batteries, heat buffers and plug-in electric vehicles (PEVs with vehicle-to-grid systems can be integrated in microgrids. However, significant technical challenges arise in the planning, operation and control of microgrids, due to the randomness in renewable power generation, the buffering effect of energy storage devices and the high mobility of PEVs. The two-way communication functionalities of the future smart grid provide an opportunity to address these challenges, by offering the communication links for microgrid status information collection. However, how to utilize stochastic modeling and optimization tools for efficient, reliable and economic planning, operation and control of microgrids remains an open issue. In this paper, we investigate the key features of microgrids and provide a comprehensive literature survey on the stochastic modeling and optimization tools for a microgrid. Future research directions are also identified.

Environmental vs Demographic Stochasticity in Population Growth

OpenAIRE

Braumann, C. A.

2010-01-01

Compares the effect on population growth of envinonmental stochasticity (random environmental variations described by stochastic differential equations) with demographic stochasticity (random variations in births and deaths described by branching processes and birth-and-death processes), in the density-independent and the density-dependent cases.

Alternative Asymmetric Stochastic Volatility Models

NARCIS (Netherlands)

M. Asai (Manabu); M.J. McAleer (Michael)

2010-01-01

textabstractThe stochastic volatility model usually incorporates asymmetric effects by introducing the negative correlation between the innovations in returns and volatility. In this paper, we propose a new asymmetric stochastic volatility model, based on the leverage and size effects. The model is

Transport stochastic multi-dimensional media

International Nuclear Information System (INIS)

Haran, O.; Shvarts, D.

1996-01-01

Many physical phenomena evolve according to known deterministic rules, but in a stochastic media in which the composition changes in space and time. Examples to such phenomena are heat transfer in turbulent atmosphere with non uniform diffraction coefficients, neutron transfer in boiling coolant of a nuclear reactor and radiation transfer through concrete shields. The results of measurements conducted upon such a media are stochastic by nature, and depend on the specific realization of the media. In the last decade there has been a considerable efforts to describe linear particle transport in one dimensional stochastic media composed of several immiscible materials. However, transport in two or three dimensional stochastic media has been rarely addressed. The important effect in multi-dimensional transport that does not appear in one dimension is the ability to bypass obstacles. The current work is an attempt to quantify this effect. (authors)

Transport stochastic multi-dimensional media

Energy Technology Data Exchange (ETDEWEB)

Haran, O; Shvarts, D [Israel Atomic Energy Commission, Beersheba (Israel). Nuclear Research Center-Negev; Thiberger, R [Ben-Gurion Univ. of the Negev, Beersheba (Israel)

1996-12-01

Many physical phenomena evolve according to known deterministic rules, but in a stochastic media in which the composition changes in space and time. Examples to such phenomena are heat transfer in turbulent atmosphere with non uniform diffraction coefficients, neutron transfer in boiling coolant of a nuclear reactor and radiation transfer through concrete shields. The results of measurements conducted upon such a media are stochastic by nature, and depend on the specific realization of the media. In the last decade there has been a considerable efforts to describe linear particle transport in one dimensional stochastic media composed of several immiscible materials. However, transport in two or three dimensional stochastic media has been rarely addressed. The important effect in multi-dimensional transport that does not appear in one dimension is the ability to bypass obstacles. The current work is an attempt to quantify this effect. (authors).

Modelling and application of stochastic processes

CERN Document Server

1986-01-01

The subject of modelling and application of stochastic processes is too vast to be exhausted in a single volume. In this book, attention is focused on a small subset of this vast subject. The primary emphasis is on realization and approximation of stochastic systems. Recently there has been considerable interest in the stochastic realization problem, and hence, an attempt has been made here to collect in one place some of the more recent approaches and algorithms for solving the stochastic realiza­ tion problem. Various different approaches for realizing linear minimum-phase systems, linear nonminimum-phase systems, and bilinear systems are presented. These approaches range from time-domain methods to spectral-domain methods. An overview of the chapter contents briefly describes these approaches. Also, in most of these chapters special attention is given to the problem of developing numerically ef­ ficient algorithms for obtaining reduced-order (approximate) stochastic realizations. On the application side,...

Turbulent response in a stochastic regime

International Nuclear Information System (INIS)

Molvig, K.; Freidberg, J.P.; Potok, R.; Hirshman, S.P.; Whitson, J.C.; Tajima, T.

1981-06-01

The theory for the non-linear, turbulent response in a system with intrinsic stochasticity is considered. It is argued that perturbative Eulerian theories, such as the Direct Interaction Approximation (DIA), are inherently unsuited to describe such a system. The exponentiation property that characterizes stochasticity appears in the Lagrangian picture and cannot even be defined in the Eulerian representation. An approximation for stochastic systems - the Normal Stochastic Approximation - is developed and states that the perturbed orbit functions (Lagrangian fluctuations) behave as normally distributed random variables. This is independent of the Eulerian statistics and, in fact, we treat the Eulerian fluctuations as fixed. A simple model problem (appropriate for the electron response in the drift wave) is subjected to a series of computer experiments. To within numerical noise the results are in agreement with the Normal Stochastic Approximation. The predictions of the DIA for this mode show substantial qualitative and quantitative departures from the observations

Stochastic modeling and analysis of telecoms networks

CERN Document Server

Decreusefond, Laurent

2012-01-01

This book addresses the stochastic modeling of telecommunication networks, introducing the main mathematical tools for that purpose, such as Markov processes, real and spatial point processes and stochastic recursions, and presenting a wide list of results on stability, performances and comparison of systems.The authors propose a comprehensive mathematical construction of the foundations of stochastic network theory: Markov chains, continuous time Markov chains are extensively studied using an original martingale-based approach. A complete presentation of stochastic recursions from an

Net load forecasting for high renewable energy penetration grids

International Nuclear Information System (INIS)

Kaur, Amanpreet; Nonnenmacher, Lukas; Coimbra, Carlos F.M.

2016-01-01

We discuss methods for net load forecasting and their significance for operation and management of power grids with high renewable energy penetration. Net load forecasting is an enabling technology for the integration of microgrid fleets with the macrogrid. Net load represents the load that is traded between the grids (microgrid and utility grid). It is important for resource allocation and electricity market participation at the point of common coupling between the interconnected grids. We compare two inherently different approaches: additive and integrated net load forecast models. The proposed methodologies are validated on a microgrid with 33% annual renewable energy (solar) penetration. A heuristics based solar forecasting technique is proposed, achieving skill of 24.20%. The integrated solar and load forecasting model outperforms the additive model by 10.69% and the uncertainty range for the additive model is larger than the integrated model by 2.2%. Thus, for grid applications an integrated forecast model is recommended. We find that the net load forecast errors and the solar forecasting errors are cointegrated with a common stochastic drift. This is useful for future planning and modeling because the solar energy time-series allows to infer important features of the net load time-series, such as expected variability and uncertainty. - Highlights: • Net load forecasting methods for grids with renewable energy generation are discussed. • Integrated solar and load forecasting outperforms the additive model by 10.69%. • Net load forecasting reduces the uncertainty between the interconnected grids.

Trajectory averaging for stochastic approximation MCMC algorithms

KAUST Repository

Liang, Faming

2010-10-01

The subject of stochastic approximation was founded by Robbins and Monro [Ann. Math. Statist. 22 (1951) 400-407]. After five decades of continual development, it has developed into an important area in systems control and optimization, and it has also served as a prototype for the development of adaptive algorithms for on-line estimation and control of stochastic systems. Recently, it has been used in statistics with Markov chain Monte Carlo for solving maximum likelihood estimation problems and for general simulation and optimizations. In this paper, we first show that the trajectory averaging estimator is asymptotically efficient for the stochastic approximation MCMC (SAMCMC) algorithm under mild conditions, and then apply this result to the stochastic approximation Monte Carlo algorithm [Liang, Liu and Carroll J. Amer. Statist. Assoc. 102 (2007) 305-320]. The application of the trajectory averaging estimator to other stochastic approximationMCMC algorithms, for example, a stochastic approximation MLE algorithm for missing data problems, is also considered in the paper. © Institute of Mathematical Statistics, 2010.

Stochastic resonance during a polymer translocation process

International Nuclear Information System (INIS)

Mondal, Debasish; Muthukumar, M.

2016-01-01

We have studied the occurrence of stochastic resonance when a flexible polymer chain undergoes a single-file translocation through a nano-pore separating two spherical cavities, under a time-periodic external driving force. The translocation of the chain is controlled by a free energy barrier determined by chain length, pore length, pore-polymer interaction, and confinement inside the donor and receiver cavities. The external driving force is characterized by a frequency and amplitude. By combining the Fokker-Planck formalism for polymer translocation and a two-state model for stochastic resonance, we have derived analytical formulas for criteria for emergence of stochastic resonance during polymer translocation. We show that no stochastic resonance is possible if the free energy barrier for polymer translocation is purely entropic in nature. The polymer chain exhibits stochastic resonance only in the presence of an energy threshold in terms of polymer-pore interactions. Once stochastic resonance is feasible, the chain entropy controls the optimal synchronization conditions significantly.

A simplified model of dynamic interior cooling load evaluation for office buildings

International Nuclear Information System (INIS)

Ding, Yan; Zhang, Qiang; Wang, Zhaoxia; Liu, Min; He, Qing

2016-01-01

Highlights: • The core interior disturbance was determined by principle component analysis. • Influences of occupants on cooling load should be described using time series. • A simplified model was built to evaluate dynamic interior building cooling load. - Abstract: Predicted cooling load is a valuable tool for assessing the operation of air-conditioning systems. Compared with exterior cooling load, interior cooling load is more unpredictable. According to principle components analysis, occupancy was proved to be a typical factor influencing interior cooling loads in buildings. By exploring the regularity of interior disturbances in an office building, a simplified evaluation model for interior cooling load was established in this paper. The stochastic occupancy rate was represented by a Markov transition model. Equipment power, lighting power and fresh air were all related to occupancy rate based on time sequence. The superposition of different types of interior cooling loads was also considered in the evaluation model. The error between the evaluation results and measurement results was found to be lower than 10%. In reference to the cooling loads calculated by the traditional design method and area-based method in case study office rooms, the evaluated cooling loads were suitable for operation regulation.

Is human failure a stochastic process?

International Nuclear Information System (INIS)

Dougherty, Ed M.

1997-01-01

Human performance results in failure events that occur with a risk-significant frequency. System analysts have taken for granted the random (stochastic) nature of these events in engineering assessments such as risk assessment. However, cognitive scientists and error technologists, at least those who have interest in human reliability, have, over the recent years, claimed that human error does not need this stochastic framework. Yet they still use the language appropriate to stochastic processes. This paper examines the potential for the stochastic nature of human failure production as the basis for human reliability analysis. It distinguishes and leaves to others, however, the epistemic uncertainties over the possible probability models for the real variability of human performance

Stochastic Switching Dynamics

DEFF Research Database (Denmark)

Simonsen, Maria

This thesis treats stochastic systems with switching dynamics. Models with these characteristics are studied from several perspectives. Initially in a simple framework given in the form of stochastic differential equations and, later, in an extended form which fits into the framework of sliding...... mode control. It is investigated how to understand and interpret solutions to models of switched systems, which are exposed to discontinuous dynamics and uncertainties (primarily) in the form of white noise. The goal is to gain knowledge about the performance of the system by interpreting the solution...

Stochastic singular optics

CSIR Research Space (South Africa)

Roux, FS

2013-09-01

Full Text Available Roux Presented at the International Conference on Correlation Optics 2013 Chernivtsi, Ukraine 18-20 September 2013 CSIR National Laser Centre, Pretoria, South Africa – p. 1/24 Contents ⊲ Defining Stochastic Singular Optics (SSO) ⊲ Tools of Stochastic... of vortices: topological charge ±1 (higher order are unstable). Positive and negative vortex densities np(x, y, z) and nn(x, y, z) ⊲ Vortex density: V = np + nn ⊲ Topological charge density: T = np − nn – p. 4/24 Subfields of SSO ⊲ Homogeneous, normally...

Universal failure model for multi-unit systems with shared functionality

International Nuclear Information System (INIS)

Volovoi, Vitali

2013-01-01

A Universal Failure Model (UFM) is proposed for complex systems that rely on a large number of entities for performing a common function. Economy of scale or other considerations may dictate the need to pool resources for common purpose, but the resulting strong coupling precludes the grouping of those components into modules. Existing system-level failure models rely on modularity for reducing modeling complexity, so the UFM will fill an important gap in constructing efficient system-level models. Conceptually, the UFM resembles cellular automata (CA) infused with realistic failure mechanisms. Components’ behavior is determined based on the balance between their strength (capacity) and their load (demand) share. If the load exceeds the components’ capacity, the component fails and its load share is distributed among its neighbors (possibly with a time delay and load losses). The strength of components can degrade with time if the load exceeds an elastic threshold. The global load (demand) carried by the system can vary over time, with the peak values providing shocks to the system (e.g., wind loads in civil structures, electricity demand, stressful activities to human bodies, or drought in an ecosystem). Unlike the models traditionally studied by CA, the focus of the presented model is on the system reliability, and specifically on the study of time-to-failure distributions, rather than steady-state patterns and average time-to-failure characteristics. In this context, the relationships between the types of failure distributions and the parameters of the failure model are discussed

The role of demand response in single and multi-objective wind-thermal generation scheduling: A stochastic programming

International Nuclear Information System (INIS)

Falsafi, Hananeh; Zakariazadeh, Alireza; Jadid, Shahram

2014-01-01

This paper focuses on using DR (Demand Response) as a means to provide reserve in order to cover uncertainty in wind power forecasting in SG (Smart Grid) environment. The proposed stochastic model schedules energy and reserves provided by both of generating units and responsive loads in power systems with high penetration of wind power. This model is formulated as a two-stage stochastic programming, where first-stage is associated with electricity market, its rules and constraints and the second-stage is related to actual operation of the power system and its physical limitations in each scenario. The discrete retail customer responses to incentive-based DR programs are aggregated by DRPs (Demand Response Providers) and are submitted as a load change price and amount offer package to ISO (Independent System Operator). Also, price-based DR program behavior and random nature of wind power are modeled by price elasticity concept of the demand and normal probability distribution function, respectively. In the proposed model, DRPs can participate in energy market as well as reserve market and submit their offers to the wholesale electricity market. This approach is implemented on a modified IEEE 30-bus test system over a daily time horizon. The simulation results are analyzed in six different case studies. The cost, emission and multiobjective functions are optimized in both without and with DR cases. The multiobjective generation scheduling model is solved using augmented epsilon constraint method and the best solution can be chosen by Entropy and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) methods. The results indicate demand side participation in energy and reserve scheduling reduces the total operation costs and emissions. - Highlights: • Simultaneous participation of loads in both energy and reserve scheduling. • Environmental/economical scheduling of energy and reserve. • Using demand response for covering wind generation forecast

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

Science.gov (United States)

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

2016-01-01

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

Probabilistic Constrained Load Flow Considering Integration of Wind Power Generation and Electric Vehicles

DEFF Research Database (Denmark)

Vlachogiannis, Ioannis (John)

2009-01-01

A new formulation and solution of probabilistic constrained load flow (PCLF) problem suitable for modern power systems with wind power generation and electric vehicles (EV) demand or supply is represented. The developed stochastic model of EV demand/supply and the wind power generation model...... are incorporated into load flow studies. In the resulted PCLF formulation, discrete and continuous control parameters are engaged. Therefore, a hybrid learning automata system (HLAS) is developed to find the optimal offline control settings over a whole planning period of power system. The process of HLAS...

Dynamics of non-holonomic systems with stochastic transport

Science.gov (United States)

Holm, D. D.; Putkaradze, V.

2018-01-01

This paper formulates a variational approach for treating observational uncertainty and/or computational model errors as stochastic transport in dynamical systems governed by action principles under non-holonomic constraints. For this purpose, we derive, analyse and numerically study the example of an unbalanced spherical ball rolling under gravity along a stochastic path. Our approach uses the Hamilton-Pontryagin variational principle, constrained by a stochastic rolling condition, which we show is equivalent to the corresponding stochastic Lagrange-d'Alembert principle. In the example of the rolling ball, the stochasticity represents uncertainty in the observation and/or error in the computational simulation of the angular velocity of rolling. The influence of the stochasticity on the deterministically conserved quantities is investigated both analytically and numerically. Our approach applies to a wide variety of stochastic, non-holonomically constrained systems, because it preserves the mathematical properties inherited from the variational principle.

Potential for shared log transport services

Science.gov (United States)

Tim McDonald; Steve Taylor; Jorge Valenzuela

2001-01-01

A simulation model of a log transport logistics network was developed. The model could be structured to either share truck capacity among a group of loggers, or to assign a fixed number of trucks to individual loggers. Another variation of the model allowed the use of a staging yard to set out loaded trailers and deliver them to destinations using dedicated shuttle...

Stochastic risk-constrained short-term scheduling of industrial cogeneration systems in the presence of demand response programs

International Nuclear Information System (INIS)

Alipour, Manijeh; Mohammadi-Ivatloo, Behnam; Zare, Kazem

2014-01-01

Highlights: • Short-term self-scheduling problem of customers with CHP units is conducted. • Power demand and pool prices are forecasted using ARIMA models. • Risk management problem is conducted by implementing CVaR methodology. • The demand response program is implemented in self-scheduling problem of CHP units. • Non-convex feasible operation region in different types of CHP units is modeled. - Abstract: This paper presents a stochastic programming framework for solving the scheduling problem faced by an industrial customer with cogeneration facilities, conventional power production system, and heat only units. The power and heat demands of the customer are supplied considering demand response (DR) programs. In the proposed DR program, the responsive load can vary in different time intervals. In the paper, the heat-power dual dependency characteristic in different types of CHP units is taken into account. In addition, a heat buffer tank, with the ability of heat storage, has been incorporated in the proposed framework. The impact of the market and load uncertainties on the scheduling problem is characterized through a stochastic programming formulation. Autoregressive integrated moving average (ARIMA) technique is used to generate the electricity price and the customer demand scenarios. The daily and weekly seasonalities of demand and market prices are taken into account in the scenario generation procedure. The conditional value-at-risk (CVaR) methodology is implemented in order to limit the risk of expected profit due to market price and load forecast volatilities

Stochastic cooling at Fermilab

International Nuclear Information System (INIS)

Marriner, J.

1986-08-01

The topics discussed are the stochastic cooling systems in use at Fermilab and some of the techniques that have been employed to meet the particular requirements of the anti-proton source. Stochastic cooling at Fermilab became of paramount importance about 5 years ago when the anti-proton source group at Fermilab abandoned the electron cooling ring in favor of a high flux anti-proton source which relied solely on stochastic cooling to achieve the phase space densities necessary for colliding proton and anti-proton beams. The Fermilab systems have constituted a substantial advance in the techniques of cooling including: large pickup arrays operating at microwave frequencies, extensive use of cryogenic techniques to reduce thermal noise, super-conducting notch filters, and the development of tools for controlling and for accurately phasing the system

Stochastic inflation in phase space: is slow roll a stochastic attractor?

Energy Technology Data Exchange (ETDEWEB)

Grain, Julien [Institut d' Astrophysique Spatiale, UMR8617, CNRS, Univ. Paris Sud, Université Paris-Saclay, Bt. 121, Orsay, F-91405 (France); Vennin, Vincent, E-mail: julien.grain@ias.u-psud.fr, E-mail: vincent.vennin@port.ac.uk [Institute of Cosmology and Gravitation, University of Portsmouth, Dennis Sciama Building, Burnaby Road, Portsmouth, PO13FX (United Kingdom)

2017-05-01

An appealing feature of inflationary cosmology is the presence of a phase-space attractor, ''slow roll'', which washes out the dependence on initial field velocities. We investigate the robustness of this property under backreaction from quantum fluctuations using the stochastic inflation formalism in the phase-space approach. A Hamiltonian formulation of stochastic inflation is presented, where it is shown that the coarse-graining procedure—where wavelengths smaller than the Hubble radius are integrated out—preserves the canonical structure of free fields. This means that different sets of canonical variables give rise to the same probability distribution which clarifies the literature with respect to this issue. The role played by the quantum-to-classical transition is also analysed and is shown to constrain the coarse-graining scale. In the case of free fields, we find that quantum diffusion is aligned in phase space with the slow-roll direction. This implies that the classical slow-roll attractor is immune to stochastic effects and thus generalises to a stochastic attractor regardless of initial conditions, with a relaxation time at least as short as in the classical system. For non-test fields or for test fields with non-linear self interactions however, quantum diffusion and the classical slow-roll flow are misaligned. We derive a condition on the coarse-graining scale so that observational corrections from this misalignment are negligible at leading order in slow roll.

Stochastic Reformulations of Linear Systems: Algorithms and Convergence Theory

KAUST Repository

Richtarik, Peter; Taká č, Martin

2017-01-01

We develop a family of reformulations of an arbitrary consistent linear system into a stochastic problem. The reformulations are governed by two user-defined parameters: a positive definite matrix defining a norm, and an arbitrary discrete or continuous distribution over random matrices. Our reformulation has several equivalent interpretations, allowing for researchers from various communities to leverage their domain specific insights. In particular, our reformulation can be equivalently seen as a stochastic optimization problem, stochastic linear system, stochastic fixed point problem and a probabilistic intersection problem. We prove sufficient, and necessary and sufficient conditions for the reformulation to be exact. Further, we propose and analyze three stochastic algorithms for solving the reformulated problem---basic, parallel and accelerated methods---with global linear convergence rates. The rates can be interpreted as condition numbers of a matrix which depends on the system matrix and on the reformulation parameters. This gives rise to a new phenomenon which we call stochastic preconditioning, and which refers to the problem of finding parameters (matrix and distribution) leading to a sufficiently small condition number. Our basic method can be equivalently interpreted as stochastic gradient descent, stochastic Newton method, stochastic proximal point method, stochastic fixed point method, and stochastic projection method, with fixed stepsize (relaxation parameter), applied to the reformulations.

Stochastic Reformulations of Linear Systems: Algorithms and Convergence Theory

KAUST Repository

Richtarik, Peter

2017-06-04

We develop a family of reformulations of an arbitrary consistent linear system into a stochastic problem. The reformulations are governed by two user-defined parameters: a positive definite matrix defining a norm, and an arbitrary discrete or continuous distribution over random matrices. Our reformulation has several equivalent interpretations, allowing for researchers from various communities to leverage their domain specific insights. In particular, our reformulation can be equivalently seen as a stochastic optimization problem, stochastic linear system, stochastic fixed point problem and a probabilistic intersection problem. We prove sufficient, and necessary and sufficient conditions for the reformulation to be exact. Further, we propose and analyze three stochastic algorithms for solving the reformulated problem---basic, parallel and accelerated methods---with global linear convergence rates. The rates can be interpreted as condition numbers of a matrix which depends on the system matrix and on the reformulation parameters. This gives rise to a new phenomenon which we call stochastic preconditioning, and which refers to the problem of finding parameters (matrix and distribution) leading to a sufficiently small condition number. Our basic method can be equivalently interpreted as stochastic gradient descent, stochastic Newton method, stochastic proximal point method, stochastic fixed point method, and stochastic projection method, with fixed stepsize (relaxation parameter), applied to the reformulations.

Quantization of dynamical systems and stochastic control theory

International Nuclear Information System (INIS)

Guerra, F.; Morato, L.M.

1982-09-01

In the general framework of stochastic control theory we introduce a suitable form of stochastic action associated to the controlled process. Then a variational principle gives all main features of Nelson's stochastic mechanics. In particular we derive the expression of the current velocity field as the gradient of the phase action. Moreover the stochastic corrections to the Hamilton-Jacobi equation are in agreement with the quantum mechanical form of the Madelung fluid (equivalent to the Schroedinger equation). Therefore stochastic control theory can provide a very simple model simulating quantum mechanical behavior

On Lipschitzian quantum stochastic differential inclusions

International Nuclear Information System (INIS)

Ekhaguere, G.O.S.

1990-12-01

Quantum stochastic differential inclusions are introduced and studied within the framework of the Hudson-Parthasarathy formulation of quantum stochastic calculus. Results concerning the existence of solutions of a Lipschitzian quantum stochastic differential inclusion and the relationship between the solutions of such an inclusion and those of its convexification are presented. These generalize the Filippov existence theorem and the Filippov-Wazewski Relaxation Theorem for classical differential inclusions to the present noncommutative setting. (author). 9 refs

Stochastic temperature and the Nicolai map

International Nuclear Information System (INIS)

Hueffel, H.

1989-01-01

Just as standard temperature can be related to the time coordinate of Euclidean space, a new concept of 'stochastic temperature' may be introduced by associating it to the Parisi-Wu time of stochastic quantization. The perturbative equilibrium limit for a self-interacting scalar field is studied, and a 'thermal' mass shift to one loop is shown. In addition one may interpret the underlying stochastic process as a Nicolai map at nonzero 'temperature'. 22 refs. (Author)

Stochastic Linear Quadratic Optimal Control Problems

International Nuclear Information System (INIS)

Chen, S.; Yong, J.

2001-01-01

This paper is concerned with the stochastic linear quadratic optimal control problem (LQ problem, for short) for which the coefficients are allowed to be random and the cost functional is allowed to have a negative weight on the square of the control variable. Some intrinsic relations among the LQ problem, the stochastic maximum principle, and the (linear) forward-backward stochastic differential equations are established. Some results involving Riccati equation are discussed as well

Optimal Integration of Intermittent Renewables: A System LCOE Stochastic Approach

Directory of Open Access Journals (Sweden)

Carlo Lucheroni

2018-03-01

Full Text Available We propose a system level approach to value the impact on costs of the integration of intermittent renewable generation in a power system, based on expected breakeven cost and breakeven cost risk. To do this, we carefully reconsider the definition of Levelized Cost of Electricity (LCOE when extended to non-dispatchable generation, by examining extra costs and gains originated by the costly management of random power injections. We are thus lead to define a ‘system LCOE’ as a system dependent LCOE that takes properly into account intermittent generation. In order to include breakeven cost risk we further extend this deterministic approach to a stochastic setting, by introducing a ‘stochastic system LCOE’. This extension allows us to discuss the optimal integration of intermittent renewables from a broad, system level point of view. This paper thus aims to provide power producers and policy makers with a new methodological scheme, still based on the LCOE but which updates this valuation technique to current energy system configurations characterized by a large share of non-dispatchable production. Quantifying and optimizing the impact of intermittent renewables integration on power system costs, risk and CO 2 emissions, the proposed methodology can be used as powerful tool of analysis for assessing environmental and energy policies.

Stochastic programming with integer recourse

NARCIS (Netherlands)

van der Vlerk, Maarten Hendrikus

1995-01-01

In this thesis we consider two-stage stochastic linear programming models with integer recourse. Such models are at the intersection of two different branches of mathematical programming. On the one hand some of the model parameters are random, which places the problem in the field of stochastic

Comparison of Traditional Design Nonlinear Programming Optimization and Stochastic Methods for Structural Design

Science.gov (United States)

Patnaik, Surya N.; Pai, Shantaram S.; Coroneos, Rula M.

2010-01-01

Structural design generated by traditional method, optimization method and the stochastic design concept are compared. In the traditional method, the constraints are manipulated to obtain the design and weight is back calculated. In design optimization, the weight of a structure becomes the merit function with constraints imposed on failure modes and an optimization algorithm is used to generate the solution. Stochastic design concept accounts for uncertainties in loads, material properties, and other parameters and solution is obtained by solving a design optimization problem for a specified reliability. Acceptable solutions were produced by all the three methods. The variation in the weight calculated by the methods was modest. Some variation was noticed in designs calculated by the methods. The variation may be attributed to structural indeterminacy. It is prudent to develop design by all three methods prior to its fabrication. The traditional design method can be improved when the simplified sensitivities of the behavior constraint is used. Such sensitivity can reduce design calculations and may have a potential to unify the traditional and optimization methods. Weight versus reliabilitytraced out an inverted-S-shaped graph. The center of the graph corresponded to mean valued design. A heavy design with weight approaching infinity could be produced for a near-zero rate of failure. Weight can be reduced to a small value for a most failure-prone design. Probabilistic modeling of load and material properties remained a challenge.

Stochastic quantization of gravity and string fields

International Nuclear Information System (INIS)

Rumpf, H.

1986-01-01

The stochastic quantization method of Parisi and Wu is generalized so as to make it applicable to Einstein's theory of gravitation. The generalization is based on the existence of a preferred metric in field configuration space, involves Ito's calculus, and introduces a complex stochastic process adapted to Lorentzian spacetime. It implies formally the path integral measure of DeWitt, a causual Feynman propagator, and a consistent stochastic perturbation theory. The lineraized version of the theory is also obtained from the stochastic quantization of the free string field theory of Siegel and Zwiebach. (Author)

Evaluation of flexible demand-side load-following reserves in power systems with high wind generation penetration

NARCIS (Netherlands)

Paterakis, N.G.; Catalao, J.P.S.; Ntomaris, A.V.; Erdinc, O.

2015-01-01

In this study, a two-stage stochastic programming joint energy and reserve day-ahead market structure is proposed in order to procure the required load-following reserves to tackle with wind power production uncertainty. Reserves can be procured both from generation and demand-side. Responsive

Extreme Value Predictions using Monte Carlo Simulations with Artificially Increased Load Spectrum

DEFF Research Database (Denmark)

Jensen, Jørgen Juncher

2011-01-01

In the analysis of structures subjected to stationary stochastic load processes the mean out-crossing rate plays an important role as it can be used to determine the extreme value distribution of any response, usually assuming that the sequence of mean out-crossings can be modelled as a Poisson...... be scaled down to its actual value. In the present paper the usefulness of this approach is investigated, considering problems related to wave loads on marine structures. Here the load scale parameter is conveniently taken as the square of the significant wave height....... be found using the First Order Reliability Method (FORM). The FORM analysis also shows that the reliability index is strictly inversely proportional to the square root of the magnitude of the load spectrum, irrespectively of the non-linearity in the system. However, the FORM analysis only gives...

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.

Evaluation of Fatigue Crack Propagation of Gears Considering Uncertainties in Loading and Material Properties

Directory of Open Access Journals (Sweden)

Haileyesus B. Endeshaw

2017-11-01

Full Text Available Failure prediction of wind turbine gearboxes (WTGs is especially important since the maintenance of these components is not only costly but also causes the longest downtime. One of the most common causes of the premature fault of WTGs is attributed to the fatigue fracture of gear teeth due to fluctuating and cyclic torque, resulting from stochastic wind loading, transmitted to the gearbox. Moreover, the fluctuation of the torque, as well as the inherent uncertainties of the material properties, results in uncertain life prediction for WTGs. It is therefore essential to quantify these uncertainties in the life estimation of gears. In this paper, a framework, constituted by a dynamic model of a one-stage gearbox, a finite element method, and a degradation model for the estimation of fatigue crack propagation in gear, is presented. Torque time history data of a wind turbine rotor was scaled and used to simulate the stochastic characteristic of the loading and uncertainties in the material constants of the degradation model were also quantified. It was demonstrated that uncertainty quantification of load and material constants provides a reasonable estimation of the distribution of the crack length in the gear tooth at any time step.

Thermal mixtures in stochastic mechanics

Energy Technology Data Exchange (ETDEWEB)

Guerra, F [Rome Univ. (Italy). Ist. di Matematica; Loffredo, M I [Salerno Univ. (Italy). Ist. di Fisica

1981-01-17

Stochastic mechanics is extended to systems in thermal equilibrium. The resulting stochastic processes are mixtures of Nelson processes. Their Markov property is investigated in some simple cases. It is found that in order to inforce Markov property the algebra of observable associated to the present must be suitably enlarged.

The Robustness of Stochastic Switching Networks

OpenAIRE

Loh, Po-Ling; Zhou, Hongchao; Bruck, Jehoshua

2009-01-01

Many natural systems, including chemical and biological systems, can be modeled using stochastic switching circuits. These circuits consist of stochastic switches, called pswitches, which operate with a fixed probability of being open or closed. We study the effect caused by introducing an error of size ∈ to each pswitch in a stochastic circuit. We analyze two constructions – simple series-parallel and general series-parallel circuits – and prove that simple series-parallel circuits are robus...

[Effects of the verbal loading on laterality difference in visual field (author's transl)].

Science.gov (United States)

Kawai, M

1980-02-01

In connection with the Kinsbourne's attention-model, the relation between the level of hemisphere sharing of loading task and the visual-laterality difference was examined under verbal loading conditions. The subjects were 13 (8 male and 5 female) right-handed college students. The loading tasks in Exp. I were the "same-different" judgment of Japanese hiragana alphabets and of triliteral hiragana words, and "true-false" judgment of short statements. In Exp. II, a procedure to eliminate configurational matching of the letters was followed. The results of the two experiments suggest that the visual-laterality effect occurs only when the level of hemisphere sharing of the loading task exceeds a certain lower bound.

The intrinsic stochasticity of near-integrable Hamiltonian systems

Energy Technology Data Exchange (ETDEWEB)

Krlin, L [Ceskoslovenska Akademie Ved, Prague (Czechoslovakia). Ustav Fyziky Plazmatu

1989-09-01

Under certain conditions, the dynamics of near-integrable Hamiltonian systems appears to be stochastic. This stochasticity (intrinsic stochasticity, or deterministic chaos) is closely related to the Kolmogorov-Arnold-Moser (KAM) theorem of the stability of near-integrable multiperiodic Hamiltonian systems. The effect of the intrinsic stochasticity attracts still growing attention both in theory and in various applications in contemporary physics. The paper discusses the relation of the intrinsic stochasticity to the modern ergodic theory and to the KAM theorem, and describes some numerical experiments on related astrophysical and high-temperature plasma problems. Some open questions are mentioned in conclusion. (author).

Stochastic hyperelastic constitutive laws and identification procedure for soft biological tissues with intrinsic variability.

Science.gov (United States)

Staber, B; Guilleminot, J

2017-01-01

In this work, we address the constitutive modeling, in a probabilistic framework, of the hyperelastic response of soft biological tissues. The aim is on the one hand to mimic the mean behavior and variability that are typically encountered in the experimental characterization of such materials, and on the other hand to derive mathematical models that are almost surely consistent with the theory of nonlinear elasticity. Towards this goal, we invoke information theory and discuss a stochastic model relying on a low-dimensional parametrization. We subsequently propose a two-step methodology allowing for the calibration of the model using standard data, such as mean and standard deviation values along a given loading path. The framework is finally applied and benchmarked on three experimental databases proposed elsewhere in the literature. It is shown that the stochastic model allows experiments to be accurately reproduced, regardless of the tissue under consideration. Copyright © 2016 Elsevier Ltd. All rights reserved.

Linear stochastic neutron transport theory

International Nuclear Information System (INIS)

Lewins, J.

1978-01-01

A new and direct derivation of the Bell-Pal fundamental equation for (low power) neutron stochastic behaviour in the Boltzmann continuum model is given. The development includes correlation of particle emission direction in induced and spontaneous fission. This leads to generalizations of the backward and forward equations for the mean and variance of neutron behaviour. The stochastic importance for neutron transport theory is introduced and related to the conventional deterministic importance. Defining equations and moment equations are derived and shown to be related to the backward fundamental equation with the detector distribution of the operational definition of stochastic importance playing the role of an adjoint source. (author)

Entropy Production in Stochastics

Directory of Open Access Journals (Sweden)

Demetris Koutsoyiannis

2017-10-01

Full Text Available While the modern definition of entropy is genuinely probabilistic, in entropy production the classical thermodynamic definition, as in heat transfer, is typically used. Here we explore the concept of entropy production within stochastics and, particularly, two forms of entropy production in logarithmic time, unconditionally (EPLT or conditionally on the past and present having been observed (CEPLT. We study the theoretical properties of both forms, in general and in application to a broad set of stochastic processes. A main question investigated, related to model identification and fitting from data, is how to estimate the entropy production from a time series. It turns out that there is a link of the EPLT with the climacogram, and of the CEPLT with two additional tools introduced here, namely the differenced climacogram and the climacospectrum. In particular, EPLT and CEPLT are related to slopes of log-log plots of these tools, with the asymptotic slopes at the tails being most important as they justify the emergence of scaling laws of second-order characteristics of stochastic processes. As a real-world application, we use an extraordinary long time series of turbulent velocity and show how a parsimonious stochastic model can be identified and fitted using the tools developed.

Stochastic approach to microphysics

Energy Technology Data Exchange (ETDEWEB)

Aron, J.C.

1987-01-01

The presently widespread idea of ''vacuum population'', together with the quantum concept of vacuum fluctuations leads to assume a random level below that of matter. This stochastic approach starts by a reminder of the author's previous work, first on the relation of diffusion laws with the foundations of microphysics, and then on hadron spectrum. Following the latter, a random quark model is advanced; it gives to quark pairs properties similar to those of a harmonic oscillator or an elastic string, imagined as an explanation to their asymptotic freedom and their confinement. The stochastic study of such interactions as electron-nucleon, jets in e/sup +/e/sup -/ collisions, or pp -> ..pi../sup 0/ + X, gives form factors closely consistent with experiment. The conclusion is an epistemological comment (complementarity between stochastic and quantum domains, E.P.R. paradox, etc...).

Markov stochasticity coordinates

International Nuclear Information System (INIS)

Eliazar, Iddo

2017-01-01

Markov dynamics constitute one of the most fundamental models of random motion between the states of a system of interest. Markov dynamics have diverse applications in many fields of science and engineering, and are particularly applicable in the context of random motion in networks. In this paper we present a two-dimensional gauging method of the randomness of Markov dynamics. The method–termed Markov Stochasticity Coordinates–is established, discussed, and exemplified. Also, the method is tweaked to quantify the stochasticity of the first-passage-times of Markov dynamics, and the socioeconomic equality and mobility in human societies.

Markov stochasticity coordinates

Energy Technology Data Exchange (ETDEWEB)

Eliazar, Iddo, E-mail: iddo.eliazar@intel.com

2017-01-15

Markov dynamics constitute one of the most fundamental models of random motion between the states of a system of interest. Markov dynamics have diverse applications in many fields of science and engineering, and are particularly applicable in the context of random motion in networks. In this paper we present a two-dimensional gauging method of the randomness of Markov dynamics. The method–termed Markov Stochasticity Coordinates–is established, discussed, and exemplified. Also, the method is tweaked to quantify the stochasticity of the first-passage-times of Markov dynamics, and the socioeconomic equality and mobility in human societies.

Approximating Preemptive Stochastic Scheduling

OpenAIRE

Megow Nicole; Vredeveld Tjark

2009-01-01

We present constant approximative policies for preemptive stochastic scheduling. We derive policies with a guaranteed performance ratio of 2 for scheduling jobs with release dates on identical parallel machines subject to minimizing the sum of weighted completion times. Our policies as well as their analysis apply also to the recently introduced more general model of stochastic online scheduling. The performance guarantee we give matches the best result known for the corresponding determinist...

The stochastic goodwill problem

OpenAIRE

Marinelli, Carlo

2003-01-01

Stochastic control problems related to optimal advertising under uncertainty are considered. In particular, we determine the optimal strategies for the problem of maximizing the utility of goodwill at launch time and minimizing the disutility of a stream of advertising costs that extends until the launch time for some classes of stochastic perturbations of the classical Nerlove-Arrow dynamics. We also consider some generalizations such as problems with constrained budget and with discretionar...

Model of wind shear conditional on turbulence and its impact on wind turbine loads

DEFF Research Database (Denmark)

Dimitrov, Nikolay Krasimirov; Natarajan, Anand; Kelly, Mark C.

2015-01-01

proposed for flat terrain and that can significantly decrease the uncertainty associated with fatigue load predictions for wind turbines with large rotors. An essential contribution is the conditioning of wind shear on the 90% quantile of wind turbulence, such that the appropriate magnitude of the design...... fatigue load is achieved. The proposed wind shear model based on the wind measurements is thereby probabilistic in definition, with shear jointly distributed with wind turbulence. A simplified model for the wind shear exponent is further derived from the full stochastic model. The fatigue loads over...... is most pronounced on the blade flap loads. It is further shown that under moderate wind turbulence, the wind shear exponents may be over-specified in the design standards, and a reduction of wind shear exponent based on the present measurements can contribute to reduced fatigue damage equivalent loads...

Sequential neural models with stochastic layers

DEFF Research Database (Denmark)

Fraccaro, Marco; Sønderby, Søren Kaae; Paquet, Ulrich

2016-01-01

How can we efficiently propagate uncertainty in a latent state representation with recurrent neural networks? This paper introduces stochastic recurrent neural networks which glue a deterministic recurrent neural network and a state space model together to form a stochastic and sequential neural...... generative model. The clear separation of deterministic and stochastic layers allows a structured variational inference network to track the factorization of the model's posterior distribution. By retaining both the nonlinear recursive structure of a recurrent neural network and averaging over...

History-dependent stochastic Petri nets

NARCIS (Netherlands)

Schonenberg, H.; Sidorova, N.; Aalst, van der W.M.P.; Hee, van K.M.; Pnueli, A.; Virbitskaite, I.; Voronkov, A.

2010-01-01

Stochastic Petri Nets are a useful and well-known tool for performance analysis. However, an implicit assumption in the different types of Stochastic Petri Nets is the Markov property. It is assumed that a choice in the Petri net only depends on the current state and not on earlier choices. For many

Stochastic ferromagnetism analysis and numerics

CERN Document Server

Brzezniak, Zdzislaw; Neklyudov, Mikhail; Prohl, Andreas

2013-01-01

This monograph examines magnetization dynamics at elevated temperatures which can be described by the stochastic Landau-Lifshitz-Gilbert equation (SLLG). Comparative computational studies with the stochastic model are included. Constructive tools such as e.g. finite element methods are used to derive the theoretical results, which are then used for computational studies.

Modelling Cow Behaviour Using Stochastic Automata

DEFF Research Database (Denmark)

Jónsson, Ragnar Ingi

This report covers an initial study on the modelling of cow behaviour using stochastic automata with the aim of detecting lameness. Lameness in cows is a serious problem that needs to be dealt with because it results in less profitable production units and in reduced quality of life...... for the affected livestock. By featuring training data consisting of measurements of cow activity, three different models are obtained, namely an autonomous stochastic automaton, a stochastic automaton with coinciding state and output and an autonomous stochastic automaton with coinciding state and output, all...... of which describe the cows' activity in the two regarded behavioural scenarios, non-lame and lame. Using the experimental measurement data the different behavioural relations for the two regarded behavioural scenarios are assessed. The three models comprise activity within last hour, activity within last...

Identification of the structure parameters using short-time non-stationary stochastic excitation

Science.gov (United States)

Jarczewska, Kamila; Koszela, Piotr; Śniady, PaweŁ; Korzec, Aleksandra

2011-07-01

In this paper, we propose an approach to the flexural stiffness or eigenvalue frequency identification of a linear structure using a non-stationary stochastic excitation process. The idea of the proposed approach lies within time domain input-output methods. The proposed method is based on transforming the dynamical problem into a static one by integrating the input and the output signals. The output signal is the structure reaction, i.e. structure displacements due to the short-time, irregular load of random type. The systems with single and multiple degrees of freedom, as well as continuous systems are considered.

Analysis of natural stone block pavements in urban shared areas

Directory of Open Access Journals (Sweden)

Pablo Zoccali

2018-06-01

Full Text Available This paper analysed and verified an existing block stone pavement in an urban shared area. Fatigue and rutting verification was performed respectively for bound and unbound pavement materials using analytical curves available in the literature. The commercial finite element (FE software Abaqus® was used to calculate the response of the pavement when subjected to different loading, construction and geometrical configurations (i.e. type of analysis, shape and size of meshes, boundary conditions, and bonding contacts between the pavements layers. At the end of this study, a static model of a structure with hexahedral blocks having sides of 0.02 m, with full bonded layers and restrained horizontal displacements on the model sides, was implemented to evaluate the maximum tensile stress induced in a block when the load is applied at its centre. This analysis highlighted the need for rigorous criteria for a correct design, in order to avoid inappropriate and expensive use of road materials. Keywords: Block pavement, Commercial vehicle loads, Finite element model, Hexagonal Stone block, Pedestrian pavement, Shared area

Knowledge-Based System to Support Plug Load Management

Data.gov (United States)

National Aeronautics and Space Administration — Electrical plug loads comprise an increasingly larger share of building energy consumption as improvements have been made to Heating, Ventilation, and Air...

Stochastic Evaluation of Maximum Wind Installation in a Radial Distribution Network

DEFF Research Database (Denmark)

Chen, Peiyuan; Bak-Jensen, Birgitte; Chen, Zhe

2011-01-01

This paper proposes an optimization algorithm to find the maximum wind installation in a radial distribution network. The algorithm imposes a limit on the amount of wind energy that can be curtailed annually. The algorithm implements the wind turbine reactive power control and wind energy...... curtailment using sensitivity factors. The optimization is integrated with Monte Carlo simulation to account for the stochastic behavior of load demand and wind power generation. The proposed algorithm is tested on a real 20 kV Danish distribution system in Støvring. It is demonstrated that the algorithm...... executes reactive compensation and energy curtailment sequentially in an effective and efficient manner....

First-passage probability of the deflection of a cable-stayed bridge under long-term site-specific traffic loading

Directory of Open Access Journals (Sweden)

Naiwei Lu

2017-01-01

Full Text Available Long-span bridges suffer from higher traffic loads and the simultaneous presence of multiple vehicles, which in conjunction with the steady traffic growth may pose a threat to the bridge safety. This study presents a methodology for first-passage probability evaluation of long-span bridges subject to stochastic heavy traffic loading. Initially, the stochastic heavy traffic loading was simulated based on long-term weigh-in-motion measurements of a highway bridge in China. A computational framework was presented integrating Rice’s level-crossing theory and the first-passage criterion. The effectiveness of the computational framework was demonstrated through a case study of a cable-stayed bridge. Numerical results show that the upper tail fitting of the up-crossing rate is an appropriate description of probability characteristics of the extreme traffic load effects of long-span bridges. The average daily truck traffic growth increases the probability of exceedance due to an intensive heavy traffic flow and results in a higher first-passage probability, but this increased trend is weakening as the continuous increase of the traffic volume. Since the sustained growth of gross vehicle weight has a constant impact on the probability of failure, setting a reasonable threshold overload ratio is an effective scheme as a traffic management to ensure the bridge serviceability.

Multiagent-Based Reactive Power Sharing and Control Model for Islanded Microgrids

DEFF Research Database (Denmark)

Chen, Feixiong; Chen, Minyou; Li, Qiang

2016-01-01

of the control model, in which the uncertainty of intermittent DGs, variations in load demands, as well as impacts of time delays are considered. The simulation results demonstrate the eectiveness of the control model in proportional reactive power sharing, and the plug and play capability of the control model......In islanded microgrids (MGs), the reactive power cannot be shared proportionally among distributed generators (DGs) with conventional droop control, due to the mismatch in feeder impedances. For the purpose of proportional reactive power sharing, a multiagent system (MAS) based distributed control...

Exact Algorithms for Solving Stochastic Games

DEFF Research Database (Denmark)

Hansen, Kristoffer Arnsfelt; Koucky, Michal; Lauritzen, Niels

2012-01-01

Shapley's discounted stochastic games, Everett's recursive games and Gillette's undiscounted stochastic games are classical models of game theory describing two-player zero-sum games of potentially infinite duration. We describe algorithms for exactly solving these games....

Statistical Methods for Stochastic Differential Equations

CERN Document Server

Kessler, Mathieu; Sorensen, Michael

2012-01-01

The seventh volume in the SemStat series, Statistical Methods for Stochastic Differential Equations presents current research trends and recent developments in statistical methods for stochastic differential equations. Written to be accessible to both new students and seasoned researchers, each self-contained chapter starts with introductions to the topic at hand and builds gradually towards discussing recent research. The book covers Wiener-driven equations as well as stochastic differential equations with jumps, including continuous-time ARMA processes and COGARCH processes. It presents a sp

A Stochastic Flows Approach for Asset Allocation with Hidden Economic Environment

Directory of Open Access Journals (Sweden)

Tak Kuen Siu

2015-01-01

Full Text Available An optimal asset allocation problem for a quite general class of utility functions is discussed in a simple two-state Markovian regime-switching model, where the appreciation rate of a risky share changes over time according to the state of a hidden economy. As usual, standard filtering theory is used to transform a financial model with hidden information into one with complete information, where a martingale approach is applied to discuss the optimal asset allocation problem. Using a martingale representation coupled with stochastic flows of diffeomorphisms for the filtering equation, the integrand in the martingale representation is identified which gives rise to an optimal portfolio strategy under some differentiability conditions.

Stochastic energy procurement of large electricity consumer considering photovoltaic, wind-turbine, micro-turbines, energy storage system in the presence of demand response program

International Nuclear Information System (INIS)

Nojavan, Sayyad; Aalami, Habib allah

2015-01-01

Highlights: • A stochastic energy procurement cost function in presence of DRP is proposed. • The load, price and output power of PV and wind uncertainties are modeled. • Four case studies are used to assess the effects of ESS and DRP on SEPP. • Case 4 is considered the effects of ESS and DRP simultaneously. • The expected energy procurement cost of case 4 is lower than cases 1, 2 and 3. - Abstract: This paper proposes a stochastic energy procurement problem (SEPP) for large electricity consumer (LEC) with multiple energy procurement sources (EPSs) considering the effects of demand response program (DRP) and energy storage system (ESS). The EPSs contain power market (PM), bilateral contracts (BCs), micro-turbines (MTs), and renewable energy sources (RESs). Moreover, the RESs include photovoltaic (PV) systems and wind-turbines (WT). The ESS and DRP are incorporated in the SEPP by the LEC’s decision-maker to reduce the expected energy procurement cost (EEPC). Meanwhile, the uncertainty models of market price, load and RES output power are considered in the SEPP formulation. The error of forecasting of market price, load, temperature and radiation of PV systems are modeled using the normal distribution for generating the related scenarios. Also, the weibull distribution is used to generate variable wind speed scenarios for WT output power uncertainty modeling. Furthermore, the fast forward selection based on Kantorovich distance approach is used for the scenarios reduction. Finally, the influences of ESS and DRP on EEPC are investigated, and four case studies are used to illustrate the capability of the proposed SEPP. The obtained results demonstrate the efficiency of the proposed stochastic program

Stochastic quantization of general relativity

International Nuclear Information System (INIS)

Rumpf, H.

1986-01-01

Following an elementary exposition of the basic mathematical concepts used in the theory of stochastic relaxation processes the stochastic quantization method of Parisi and Wu is briefly reviewed. The method is applied to Einstein's theory of gravitation using a formalism that is manifestly covariant with respect to field redefinitions. This requires the adoption of Ito's calculus and the introduction of a metric in field configuration space, for which there is a unique candidate. Due to the indefiniteness of the Euclidean Einstein-Hilbert action stochastic quantization is generalized to the pseudo-Riemannian case. It is formally shown to imply the DeWitt path integral measure. Finally a new type of perturbation theory is developed. (Author)

Stochastic estimation of electricity consumption

International Nuclear Information System (INIS)

Kapetanovic, I.; Konjic, T.; Zahirovic, Z.

1999-01-01

Electricity consumption forecasting represents a part of the stable functioning of the power system. It is very important because of rationality and increase of control process efficiency and development planning of all aspects of society. On a scientific basis, forecasting is a possible way to solve problems. Among different models that have been used in the area of forecasting, the stochastic aspect of forecasting as a part of quantitative models takes a very important place in applications. ARIMA models and Kalman filter as stochastic estimators have been treated together for electricity consumption forecasting. Therefore, the main aim of this paper is to present the stochastic forecasting aspect using short time series. (author)

Stochastic dynamics and irreversibility

CERN Document Server

Tomé, Tânia

2015-01-01

This textbook presents an exposition of stochastic dynamics and irreversibility. It comprises the principles of probability theory and the stochastic dynamics in continuous spaces, described by Langevin and Fokker-Planck equations, and in discrete spaces, described by Markov chains and master equations. Special concern is given to the study of irreversibility, both in systems that evolve to equilibrium and in nonequilibrium stationary states. Attention is also given to the study of models displaying phase transitions and critical phenomema both in thermodynamic equilibrium and out of equilibrium. These models include the linear Glauber model, the Glauber-Ising model, lattice models with absorbing states such as the contact process and those used in population dynamic and spreading of epidemic, probabilistic cellular automata, reaction-diffusion processes, random sequential adsorption and dynamic percolation. A stochastic approach to chemical reaction is also presented.The textbook is intended for students of ...

Intelligent stochastic optimization routine for in-core fuel cycle design

International Nuclear Information System (INIS)

Parks, G.T.

1988-01-01

Any reactor fuel management strategy must specify the fuel design, batch sizes, loading configurations, and operational procedures for each cycle. To permit detailed design studies, the complex core characteristics must necessarily be computer modeled. Thus, the identification of an optimal fuel cycle design represents an optimization problem with a nonlinear objective function (OF), nonlinear safety constraints, many control variables, and no direct derivative information. Most available library routines cannot tackle such problems; this paper introduces an intelligent stochastic optimization routine that can. There has been considerable interest recently in the application of stochastic methods to difficult optimization problems, based on the statistical mechanics algorithms originally attributed to Metropolis. Previous work showed that, in optimizing the performance of a British advanced gas-cooled reactor fuel stringer, a rudimentary version of the Metropolis algorithm performed as efficiently as the only suitable routine in the Numerical Algorithms Group library. Since then the performance of the Metropolis algorithm has been considerably enhanced by the introduction of self-tuning capabilities by which the routine adjusts its control parameters and search pattern as it progresses. Both features can be viewed as examples of artificial intelligence, in which the routine uses the accumulation of data, or experience, to guide its future actions

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.

Importance of modal cross-correlations on wind loaded structures

OpenAIRE

Denoël, Vincent; Degée, Hervé; De Ville De Goyet, Vincent

2006-01-01

In civil engineering applications the dynamic analysis of large structure is often performed in a modal space. This method is known to offer an interesting decrease of the number of degrees of freedom as well as a decomposition of the structure’s response in “uncoupled” components. Even if the response in each mode can be computed independently from the responses in the other ones, in the context of stochastic loading, the coherence of these modal responses must be accounted fo...

Transport properties of stochastic Lorentz models

NARCIS (Netherlands)

Beijeren, H. van

Diffusion processes are considered for one-dimensional stochastic Lorentz models, consisting of randomly distributed fixed scatterers and one moving light particle. In waiting time Lorentz models the light particle makes instantaneous jumps between scatterers after a stochastically distributed

External representation of argumentation in CSCL and the management of cognitive load

NARCIS (Netherlands)

Bruggen, J.M.; Kirschner, P.A.; Jochems, W.

2002-01-01

Computer-supported collaborative learning (CSCL) environments, particularly environments where students share external representations, are discussed as an interesting area for the application of cognitive load theory (CLT). CSCL environments share a number of characteristics that will induce

Moment Lyapunov Exponent and Stochastic Stability of Binary Airfoil under Combined Harmonic and Non-Gaussian Colored Noise Excitations

Science.gov (United States)

Hu, D. L.; Liu, X. B.

Both periodic loading and random forces commonly co-exist in real engineering applications. However, the dynamic behavior, especially dynamic stability of systems under parametric periodic and random excitations has been reported little in the literature. In this study, the moment Lyapunov exponent and stochastic stability of binary airfoil under combined harmonic and non-Gaussian colored noise excitations are investigated. The noise is simplified to an Ornstein-Uhlenbeck process by applying the path-integral method. Via the singular perturbation method, the second-order expansions of the moment Lyapunov exponent are obtained, which agree well with the results obtained by the Monte Carlo simulation. Finally, the effects of the noise and parametric resonance (such as subharmonic resonance and combination additive resonance) on the stochastic stability of the binary airfoil system are discussed.

Advection and dispersion of bed load tracers

Science.gov (United States)

Lajeunesse, Eric; Devauchelle, Olivier; James, François

2018-05-01

We use the erosion-deposition model introduced by Charru et al. (2004) to numerically simulate the evolution of a plume of bed load tracers entrained by a steady flow. In this model, the propagation of the plume results from the stochastic exchange of particles between the bed and the bed load layer. We find a transition between two asymptotic regimes. The tracers, initially at rest, are gradually set into motion by the flow. During this entrainment regime, the plume is strongly skewed in the direction of propagation and continuously accelerates while spreading nonlinearly. With time, the skewness of the plume eventually reaches a maximum value before decreasing. This marks the transition to an advection-diffusion regime in which the plume becomes increasingly symmetrical, spreads linearly, and advances at constant velocity. We analytically derive the expressions of the position, the variance, and the skewness of the plume and investigate their asymptotic regimes. Our model assumes steady state. In the field, however, bed load transport is intermittent. We show that the asymptotic regimes become insensitive to this intermittency when expressed in terms of the distance traveled by the plume. If this finding applies to the field, it might provide an estimate for the average bed load transport rate.

Stochastic gene expression in Arabidopsis thaliana.

Science.gov (United States)

Araújo, Ilka Schultheiß; Pietsch, Jessica Magdalena; Keizer, Emma Mathilde; Greese, Bettina; Balkunde, Rachappa; Fleck, Christian; Hülskamp, Martin

2017-12-14

Although plant development is highly reproducible, some stochasticity exists. This developmental stochasticity may be caused by noisy gene expression. Here we analyze the fluctuation of protein expression in Arabidopsis thaliana. Using the photoconvertible KikGR marker, we show that the protein expressions of individual cells fluctuate over time. A dual reporter system was used to study extrinsic and intrinsic noise of marker gene expression. We report that extrinsic noise is higher than intrinsic noise and that extrinsic noise in stomata is clearly lower in comparison to several other tissues/cell types. Finally, we show that cells are coupled with respect to stochastic protein expression in young leaves, hypocotyls and roots but not in mature leaves. Our data indicate that stochasticity of gene expression can vary between tissues/cell types and that it can be coupled in a non-cell-autonomous manner.

Stochastic deformation of a thermodynamic symplectic structure

OpenAIRE

Kazinski, P. O.

2008-01-01

A stochastic deformation of a thermodynamic symplectic structure is studied. The stochastic deformation procedure is analogous to the deformation of an algebra of observables like deformation quantization, but for an imaginary deformation parameter (the Planck constant). Gauge symmetries of thermodynamics and corresponding stochastic mechanics, which describes fluctuations of a thermodynamic system, are revealed and gauge fields are introduced. A physical interpretation to the gauge transform...

Stochastic differential equations and diffusion processes

CERN Document Server

Ikeda, N

1989-01-01

Being a systematic treatment of the modern theory of stochastic integrals and stochastic differential equations, the theory is developed within the martingale framework, which was developed by J.L. Doob and which plays an indispensable role in the modern theory of stochastic analysis.A considerable number of corrections and improvements have been made for the second edition of this classic work. In particular, major and substantial changes are in Chapter III and Chapter V where the sections treating excursions of Brownian Motion and the Malliavin Calculus have been expanded and refined. Sectio

Modeling and analysis of stochastic systems

CERN Document Server

Kulkarni, Vidyadhar G

2011-01-01

Based on the author's more than 25 years of teaching experience, Modeling and Analysis of Stochastic Systems, Second Edition covers the most important classes of stochastic processes used in the modeling of diverse systems, from supply chains and inventory systems to genetics and biological systems. For each class of stochastic process, the text includes its definition, characterization, applications, transient and limiting behavior, first passage times, and cost/reward models. Along with reorganizing the material, this edition revises and adds new exercises and examples. New to the second edi

Stochastic resonance: noise-enhanced order

International Nuclear Information System (INIS)

Anishchenko, Vadim S; Neiman, Arkady B; Moss, F; Shimansky-Geier, L

1999-01-01

Stochastic resonance (SR) provides a glaring example of a noise-induced transition in a nonlinear system driven by an information signal and noise simultaneously. In the regime of SR some characteristics of the information signal (amplification factor, signal-to-noise ratio, the degrees of coherence and of order, etc.) at the output of the system are significantly improved at a certain optimal noise level. SR is realized only in nonlinear systems for which a noise-intensity-controlled characteristic time becomes available. In the present review the physical mechanism and methods of theoretical description of SR are briefly discussed. SR features determined by the structure of the information signal, noise statistics and properties of particular systems with SR are studied. A nontrivial phenomenon of stochastic synchronization defined as locking of the instantaneous phase and switching frequency of a bistable system by external periodic force is analyzed in detail. Stochastic synchronization is explored in single and coupled bistable oscillators, including ensembles. The effects of SR and stochastic synchronization of ensembles of stochastic resonators are studied both with and without coupling between the elements. SR is considered in dynamical and nondynamical (threshold) systems. The SR effect is analyzed from the viewpoint of information and entropy characteristics of the signal, which determine the degree of order or self-organization in the system. Applications of the SR concept to explaining the results of a series of biological experiments are discussed. (reviews of topical problems)

Stochastic resonance: noise-enhanced order

Energy Technology Data Exchange (ETDEWEB)

Anishchenko, Vadim S; Neiman, Arkady B [N.G. Chernyshevskii Saratov State University, Saratov (Russian Federation); Moss, F [Department of Physics and Astronomy, University of Missouri at St. Louis (United States); Shimansky-Geier, L [Humboldt University at Berlin (Germany)

1999-01-31

Stochastic resonance (SR) provides a glaring example of a noise-induced transition in a nonlinear system driven by an information signal and noise simultaneously. In the regime of SR some characteristics of the information signal (amplification factor, signal-to-noise ratio, the degrees of coherence and of order, etc.) at the output of the system are significantly improved at a certain optimal noise level. SR is realized only in nonlinear systems for which a noise-intensity-controlled characteristic time becomes available. In the present review the physical mechanism and methods of theoretical description of SR are briefly discussed. SR features determined by the structure of the information signal, noise statistics and properties of particular systems with SR are studied. A nontrivial phenomenon of stochastic synchronization defined as locking of the instantaneous phase and switching frequency of a bistable system by external periodic force is analyzed in detail. Stochastic synchronization is explored in single and coupled bistable oscillators, including ensembles. The effects of SR and stochastic synchronization of ensembles of stochastic resonators are studied both with and without coupling between the elements. SR is considered in dynamical and nondynamical (threshold) systems. The SR effect is analyzed from the viewpoint of information and entropy characteristics of the signal, which determine the degree of order or self-organization in the system. Applications of the SR concept to explaining the results of a series of biological experiments are discussed. (reviews of topical problems)

E-Supply Chain Incentive and Coordination Based on Revenue Sharing Contract

Institute of Scientific and Technical Information of China (English)

常志平; 蒋馥

2004-01-01

This paper took the buyer-biased electronic market as an example, where multiple suppliers selling short-life-cycle products are bidding for an order from a powerful buyer with stochastic customer demand. It used a single period newsvendor model to analyze the decision of supplied and buyers to do or not do business online. The results suggest that lack of Incentive is the key factor of B2B electronic markets failure. At the same time, it designed a revenue sharing contract to coordinate the E-supply chain in order to prevent failure of E-market.

Stochastic Community Assembly: Does It Matter in Microbial Ecology?

Science.gov (United States)

Zhou, Jizhong; Ning, Daliang

2017-12-01

Understanding the mechanisms controlling community diversity, functions, succession, and biogeography is a central, but poorly understood, topic in ecology, particularly in microbial ecology. Although stochastic processes are believed to play nonnegligible roles in shaping community structure, their importance relative to deterministic processes is hotly debated. The importance of ecological stochasticity in shaping microbial community structure is far less appreciated. Some of the main reasons for such heavy debates are the difficulty in defining stochasticity and the diverse methods used for delineating stochasticity. Here, we provide a critical review and synthesis of data from the most recent studies on stochastic community assembly in microbial ecology. We then describe both stochastic and deterministic components embedded in various ecological processes, including selection, dispersal, diversification, and drift. We also describe different approaches for inferring stochasticity from observational diversity patterns and highlight experimental approaches for delineating ecological stochasticity in microbial communities. In addition, we highlight research challenges, gaps, and future directions for microbial community assembly research. Copyright © 2017 American Society for Microbiology.

Systematic Evaluation of Stochastic Methods in Power System Scheduling and Dispatch with Renewable Energy

Energy Technology Data Exchange (ETDEWEB)

Wang, Yishen [Univ. of Washington, Seattle, WA (United States); Argonne National Lab. (ANL), Argonne, IL (United States); Zhou, Zhi [Argonne National Lab. (ANL), Argonne, IL (United States); Liu, Cong [Argonne National Lab. (ANL), Argonne, IL (United States); Electric Reliability Council of Texas (ERCOT), Austin, TX (United States); Botterud, Audun [Argonne National Lab. (ANL), Argonne, IL (United States)

2016-08-01

As more wind power and other renewable resources are being integrated into the electric power grid, the forecast uncertainty brings operational challenges for the power system operators. In this report, different operational strategies for uncertainty management are presented and evaluated. A comprehensive and consistent simulation framework is developed to analyze the performance of different reserve policies and scheduling techniques under uncertainty in wind power. Numerical simulations are conducted on a modified version of the IEEE 118-bus system with a 20% wind penetration level, comparing deterministic, interval, and stochastic unit commitment strategies. The results show that stochastic unit commitment provides a reliable schedule without large increases in operational costs. Moreover, decomposition techniques, such as load shift factor and Benders decomposition, can help in overcoming the computational obstacles to stochastic unit commitment and enable the use of a larger scenario set to represent forecast uncertainty. In contrast, deterministic and interval unit commitment tend to give higher system costs as more reserves are being scheduled to address forecast uncertainty. However, these approaches require a much lower computational effort Choosing a proper lower bound for the forecast uncertainty is important for balancing reliability and system operational cost in deterministic and interval unit commitment. Finally, we find that the introduction of zonal reserve requirements improves reliability, but at the expense of higher operational costs.

Predicting the Extreme Loads on a Wind Turbine Considering Uncertainty in Airfoil Data

DEFF Research Database (Denmark)

Abdallah, Imad; Natarajan, Anand; Sørensen, John Dalsgaard

2014-01-01

The sources contributing to uncertainty in a wind turbine blade static airfoil data include wind tunnel testing, CFD calculations, 3D rotational corrections based on CFD or emprircal models, surface roughness corrections, Reynolds number corrections, expansion to the full 360-degree angle of attack...... range, validation by full scale measurements, and geometric distortions of the blade during manufacturing and under loading. In this paper a stochastic model of the static airfoil data is proposed to supplement the prediction of extreme loads effects for large wind turbines. It is shown...... that the uncertainty in airfoil data can have e significant impact on the prediction of extreme loads effects depending on the component, and the correlation along the span of the blade....

Stochastic processes

CERN Document Server

Borodin, Andrei N

2017-01-01

This book provides a rigorous yet accessible introduction to the theory of stochastic processes. A significant part of the book is devoted to the classic theory of stochastic processes. In turn, it also presents proofs of well-known results, sometimes together with new approaches. Moreover, the book explores topics not previously covered elsewhere, such as distributions of functionals of diffusions stopped at different random times, the Brownian local time, diffusions with jumps, and an invariance principle for random walks and local times. Supported by carefully selected material, the book showcases a wealth of examples that demonstrate how to solve concrete problems by applying theoretical results. It addresses a broad range of applications, focusing on concrete computational techniques rather than on abstract theory. The content presented here is largely self-contained, making it suitable for researchers and graduate students alike.

Stochastic chaos in a Duffing oscillator and its control

International Nuclear Information System (INIS)

Wu Cunli; Lei Youming; Fang Tong

2006-01-01

Stochastic chaos discussed here means a kind of chaotic responses in a Duffing oscillator with bounded random parameters under harmonic excitations. A system with random parameters is usually called a stochastic system. The modifier 'stochastic' here implies dependent on some random parameter. As the system itself is stochastic, so is the response, even under harmonic excitations alone. In this paper stochastic chaos and its control are verified by the top Lyapunov exponent of the system. A non-feedback control strategy is adopted here by adding an adjustable noisy phase to the harmonic excitation, so that the control can be realized by adjusting the noise level. It is found that by this control strategy stochastic chaos can be tamed down to the small neighborhood of a periodic trajectory or an equilibrium state. In the analysis the stochastic Duffing oscillator is first transformed into an equivalent deterministic nonlinear system by the Gegenbauer polynomial approximation, so that the problem of controlling stochastic chaos can be reduced into the problem of controlling deterministic chaos in the equivalent system. Then the top Lyapunov exponent of the equivalent system is obtained by Wolf's method to examine the chaotic behavior of the response. Numerical simulations show that the random phase control strategy is an effective way to control stochastic chaos

Stochastic stability and bifurcation in a macroeconomic model

International Nuclear Information System (INIS)

Li Wei; Xu Wei; Zhao Junfeng; Jin Yanfei

2007-01-01

On the basis of the work of Goodwin and Puu, a new business cycle model subject to a stochastically parametric excitation is derived in this paper. At first, we reduce the model to a one-dimensional diffusion process by applying the stochastic averaging method of quasi-nonintegrable Hamiltonian system. Secondly, we utilize the methods of Lyapunov exponent and boundary classification associated with diffusion process respectively to analyze the stochastic stability of the trivial solution of system. The numerical results obtained illustrate that the trivial solution of system must be globally stable if it is locally stable in the state space. Thirdly, we explore the stochastic Hopf bifurcation of the business cycle model according to the qualitative changes in stationary probability density of system response. It is concluded that the stochastic Hopf bifurcation occurs at two critical parametric values. Finally, some explanations are given in a simply way on the potential applications of stochastic stability and bifurcation analysis

Problems of Mathematical Finance by Stochastic Control Methods

Science.gov (United States)

Stettner, Łukasz

The purpose of this paper is to present main ideas of mathematics of finance using the stochastic control methods. There is an interplay between stochastic control and mathematics of finance. On the one hand stochastic control is a powerful tool to study financial problems. On the other hand financial applications have stimulated development in several research subareas of stochastic control in the last two decades. We start with pricing of financial derivatives and modeling of asset prices, studying the conditions for the absence of arbitrage. Then we consider pricing of defaultable contingent claims. Investments in bonds lead us to the term structure modeling problems. Special attention is devoted to historical static portfolio analysis called Markowitz theory. We also briefly sketch dynamic portfolio problems using viscosity solutions to Hamilton-Jacobi-Bellman equation, martingale-convex analysis method or stochastic maximum principle together with backward stochastic differential equation. Finally, long time portfolio analysis for both risk neutral and risk sensitive functionals is introduced.

Stochastic goal-oriented error estimation with memory

Science.gov (United States)

Ackmann, Jan; Marotzke, Jochem; Korn, Peter

2017-11-01

We propose a stochastic dual-weighted error estimator for the viscous shallow-water equation with boundaries. For this purpose, previous work on memory-less stochastic dual-weighted error estimation is extended by incorporating memory effects. The memory is introduced by describing the local truncation error as a sum of time-correlated random variables. The random variables itself represent the temporal fluctuations in local truncation errors and are estimated from high-resolution information at near-initial times. The resulting error estimator is evaluated experimentally in two classical ocean-type experiments, the Munk gyre and the flow around an island. In these experiments, the stochastic process is adapted locally to the respective dynamical flow regime. Our stochastic dual-weighted error estimator is shown to provide meaningful error bounds for a range of physically relevant goals. We prove, as well as show numerically, that our approach can be interpreted as a linearized stochastic-physics ensemble.

Model-based stochastic-deterministic State and Force Estimation using Kalman filtering with Application to Hanko-1 Channel Marker

OpenAIRE

Petersen, Øyvind Wiig

2014-01-01

Force identification in structural dynamics is an inverse problem concerned with finding loads from measured structural response. The main objective of this thesis is to perform and study state (displacement and velocity) and force estimation by Kalman filtering. Theory on optimal control and state-space models are presented, adapted to linear structural dynamics. Accommodation for measurement noise and model inaccuracies are attained by stochastic-deterministic coupling. Explicit requirem...

Stochasticity Modeling in Memristors

KAUST Repository

Naous, Rawan

2015-10-26

Diverse models have been proposed over the past years to explain the exhibiting behavior of memristors, the fourth fundamental circuit element. The models varied in complexity ranging from a description of physical mechanisms to a more generalized mathematical modeling. Nonetheless, stochasticity, a widespread observed phenomenon, has been immensely overlooked from the modeling perspective. This inherent variability within the operation of the memristor is a vital feature for the integration of this nonlinear device into the stochastic electronics realm of study. In this paper, experimentally observed innate stochasticity is modeled in a circuit compatible format. The model proposed is generic and could be incorporated into variants of threshold-based memristor models in which apparent variations in the output hysteresis convey the switching threshold shift. Further application as a noise injection alternative paves the way for novel approaches in the fields of neuromorphic engineering circuits design. On the other hand, extra caution needs to be paid to variability intolerant digital designs based on non-deterministic memristor logic.

Stochasticity Modeling in Memristors

KAUST Repository

Naous, Rawan; Al-Shedivat, Maruan; Salama, Khaled N.

2015-01-01

Diverse models have been proposed over the past years to explain the exhibiting behavior of memristors, the fourth fundamental circuit element. The models varied in complexity ranging from a description of physical mechanisms to a more generalized mathematical modeling. Nonetheless, stochasticity, a widespread observed phenomenon, has been immensely overlooked from the modeling perspective. This inherent variability within the operation of the memristor is a vital feature for the integration of this nonlinear device into the stochastic electronics realm of study. In this paper, experimentally observed innate stochasticity is modeled in a circuit compatible format. The model proposed is generic and could be incorporated into variants of threshold-based memristor models in which apparent variations in the output hysteresis convey the switching threshold shift. Further application as a noise injection alternative paves the way for novel approaches in the fields of neuromorphic engineering circuits design. On the other hand, extra caution needs to be paid to variability intolerant digital designs based on non-deterministic memristor logic.

Electricity price modeling with stochastic time change

International Nuclear Information System (INIS)

Borovkova, Svetlana; Schmeck, Maren Diane

2017-01-01

In this paper, we develop a novel approach to electricity price modeling, based on the powerful technique of stochastic time change. This technique allows us to incorporate the characteristic features of electricity prices (such as seasonal volatility, time varying mean reversion and seasonally occurring price spikes) into the model in an elegant and economically justifiable way. The stochastic time change introduces stochastic as well as deterministic (e.g., seasonal) features in the price process' volatility and in the jump component. We specify the base process as a mean reverting jump diffusion and the time change as an absolutely continuous stochastic process with seasonal component. The activity rate of the stochastic time change can be related to the factors that influence supply and demand. Here we use the temperature as a proxy for the demand and hence, as the driving factor of the stochastic time change, and show that this choice leads to realistic price paths. We derive properties of the resulting price process and develop the model calibration procedure. We calibrate the model to the historical EEX power prices and apply it to generating realistic price paths by Monte Carlo simulations. We show that the simulated price process matches the distributional characteristics of the observed electricity prices in periods of both high and low demand. - Highlights: • We develop a novel approach to electricity price modeling, based on the powerful technique of stochastic time change. • We incorporate the characteristic features of electricity prices, such as seasonal volatility and spikes into the model. • We use the temperature as a proxy for the demand and hence, as the driving factor of the stochastic time change • We derive properties of the resulting price process and develop the model calibration procedure. • We calibrate the model to the historical EEX power prices and apply it to generating realistic price paths.

Stochasticity and transport in Hamiltonian systems

International Nuclear Information System (INIS)

MacKay, R.S.; Meiss, J.D.; Percival, I.C.

1983-08-01

The theory of transport in nonlinear dynamics is developed in terms of leaky barriers which remain when invariant tori are destroyed. We describe the organization of stochastic motion by these barriers and give an explanation of long-time correlations in the stochastic regime

Stochastic quantization

International Nuclear Information System (INIS)

Klauder, J.R.

1983-01-01

The author provides an introductory survey to stochastic quantization in which he outlines this new approach for scalar fields, gauge fields, fermion fields, and condensed matter problems such as electrons in solids and the statistical mechanics of quantum spins. (Auth.)

Long-time correlations in the stochastic regime

International Nuclear Information System (INIS)

Karney, C.F.F.

1982-11-01

The phase space for Hamiltonians of two degrees of freedom is usually divided into stochastic and integrable components. Even when well into the stochastic regime, integrable orbits may surround small stable regions or islands. The effect of these islands on the correlation function for the stochastic trajectories is examined. Depending on the value of the parameter describing the rotation number for the elliptic fixed point at the center of the island, the long-time correlation function may decay as t -5 or exponentially, but more commonly it decays much more slowly (roughly as t -1 ). As a consequence these small islands may have a profound effect on the properties such as the diffusion coefficient, of the stochastic orbits

Stochastic development regression using method of moments

DEFF Research Database (Denmark)

Kühnel, Line; Sommer, Stefan Horst

2017-01-01

This paper considers the estimation problem arising when inferring parameters in the stochastic development regression model for manifold valued non-linear data. Stochastic development regression captures the relation between manifold-valued response and Euclidean covariate variables using...... the stochastic development construction. It is thereby able to incorporate several covariate variables and random effects. The model is intrinsically defined using the connection of the manifold, and the use of stochastic development avoids linearizing the geometry. We propose to infer parameters using...... the Method of Moments procedure that matches known constraints on moments of the observations conditional on the latent variables. The performance of the model is investigated in a simulation example using data on finite dimensional landmark manifolds....

Introduction to stochastic analysis integrals and differential equations

CERN Document Server

Mackevicius, Vigirdas

2013-01-01

This is an introduction to stochastic integration and stochastic differential equations written in an understandable way for a wide audience, from students of mathematics to practitioners in biology, chemistry, physics, and finances. The presentation is based on the naïve stochastic integration, rather than on abstract theories of measure and stochastic processes. The proofs are rather simple for practitioners and, at the same time, rather rigorous for mathematicians. Detailed application examples in natural sciences and finance are presented. Much attention is paid to simulation diffusion pro

Memristor-based neural networks: Synaptic versus neuronal stochasticity

KAUST Repository

Naous, Rawan

2016-11-02

In neuromorphic circuits, stochasticity in the cortex can be mapped into the synaptic or neuronal components. The hardware emulation of these stochastic neural networks are currently being extensively studied using resistive memories or memristors. The ionic process involved in the underlying switching behavior of the memristive elements is considered as the main source of stochasticity of its operation. Building on its inherent variability, the memristor is incorporated into abstract models of stochastic neurons and synapses. Two approaches of stochastic neural networks are investigated. Aside from the size and area perspective, the impact on the system performance, in terms of accuracy, recognition rates, and learning, among these two approaches and where the memristor would fall into place are the main comparison points to be considered.

Decentralized Coordination of Load Shedding and Plant Protection Considering High Share of RESs

DEFF Research Database (Denmark)

Hoseinzadeh, Bakhtyar; Silva, Filipe Miguel Faria da; Bak, Claus Leth

2016-01-01

variable using voltage drop data coordinated with plant protection scheme. A frequency anti stalling scheme is developed to interrupt more load feeders in case of frequency stall between consecutive set points. This time-based approach adjusts the time delay of the relay stages to disconnect the feeders...... with more voltage drop first, in order to bring the frequency back to the permissible range before the tolerable time period of plant protection relays is over. The load curtailment is stopped to avoid over LS, if the proposed algorithm recognizes that the frequency reaches the safe region in time based......This paper estimates the average Rate of Change of Frequency (ROCOF) following islanding and/or cascading event/s using inflection points of frequency profile. Moreover, a frequency collapse barrier scheme is set up by tuning the frequency set points of Load Shedding (LS) relays as a dynamic...

Stochastic reactive power dispatch in hybrid power system with intermittent wind power generation

International Nuclear Information System (INIS)

Taghavi, Reza; Seifi, Ali Reza; Samet, Haidar

2015-01-01

Environmental concerns besides fuel costs are the predominant reasons for unprecedented escalating integration of wind turbine on power systems. Operation and planning of power systems are affected by this type of energy due to the intermittent nature of wind speed inputs with high uncertainty in the optimization output variables. Consequently, in order to model this high inherent uncertainty, a PRPO (probabilistic reactive power optimization) framework should be devised. Although MC (Monte-Carlo) techniques can solve the PRPO with high precision, PEMs (point estimate methods) can preserve the accuracy to attain reasonable results when diminishing the computational effort. Also, this paper introduces a methodology for optimally dispatching the reactive power in the transmission system, while minimizing the active power losses. The optimization problem is formulated as a LFP (linear fuzzy programing). The core of the problem lay on generation of 2m + 1 point estimates for solving PRPO, where n is the number of input stochastic variables. The proposed methodology is investigated using the IEEE-14 bus test system equipped with HVDC (high voltage direct current), UPFC (unified power flow controller) and DFIG (doubly fed induction generator) devices. The accuracy of the method is demonstrated in the case study. - Highlights: • This paper uses stochastic loads in optimization process. • AC–DC load flow is modified to use some advantages of DC part in optimization process. • UPFC and DFIG are simulated in a way that could be effective in optimization process. • Fuzzy set has been used as an uncertainty analysis tool in the optimization

Time-ordered product expansions for computational stochastic system biology

International Nuclear Information System (INIS)

Mjolsness, Eric

2013-01-01

The time-ordered product framework of quantum field theory can also be used to understand salient phenomena in stochastic biochemical networks. It is used here to derive Gillespie’s stochastic simulation algorithm (SSA) for chemical reaction networks; consequently, the SSA can be interpreted in terms of Feynman diagrams. It is also used here to derive other, more general simulation and parameter-learning algorithms including simulation algorithms for networks of stochastic reaction-like processes operating on parameterized objects, and also hybrid stochastic reaction/differential equation models in which systems of ordinary differential equations evolve the parameters of objects that can also undergo stochastic reactions. Thus, the time-ordered product expansion can be used systematically to derive simulation and parameter-fitting algorithms for stochastic systems. (paper)

The Load Level of Modern Wind Turbines according to IEC 61400-1

International Nuclear Information System (INIS)

Freudenreich, K; Argyriadis, K

2007-01-01

The paper describes some effects on the load level of state-of-the art multi megawatt wind turbines introduced by the new edition of the standard IEC 61400-1:2005 W ind Turbines - Part 1: Design requirements . Compared to the previous edition, especially the extreme load determination has been modified by applying stochastic and statistical analyses. Within this paper the effect on the overall load level of wind turbines is demonstrated and occurring problems are discussed. Load simulations have been carried out for four state-of-the-art multi-megawatt wind turbines of different design concepts and from different manufacturers. The blade root bending moments and tip deflection have been determined by applying different extrapolation methods. Advantages and disadvantages of these methods and tail fittings for different load components and wind turbine technologies are discussed and interpreted. Further on, the application of the extreme turbulence model is demonstrated. The dependence of the load level on the turbulence intensity and control system, as well as the interaction with extrapolated loads is discussed and limitations outlined. The obtained load level is compared to the overall load level of the turbines according to the previous edition of the standard, IEC 61400-1:1999

American option pricing with stochastic volatility processes

Directory of Open Access Journals (Sweden)

Ping LI

2017-12-01

Full Text Available In order to solve the problem of option pricing more perfectly, the option pricing problem with Heston stochastic volatility model is considered. The optimal implementation boundary of American option and the conditions for its early execution are analyzed and discussed. In view of the fact that there is no analytical American option pricing formula, through the space discretization parameters, the stochastic partial differential equation satisfied by American options with Heston stochastic volatility is transformed into the corresponding differential equations, and then using high order compact finite difference method, numerical solutions are obtained for the option price. The numerical experiments are carried out to verify the theoretical results and simulation. The two kinds of optimal exercise boundaries under the conditions of the constant volatility and the stochastic volatility are compared, and the results show that the optimal exercise boundary also has stochastic volatility. Under the setting of parameters, the behavior and the nature of volatility are analyzed, the volatility curve is simulated, the calculation results of high order compact difference method are compared, and the numerical option solution is obtained, so that the method is verified. The research result provides reference for solving the problems of option pricing under stochastic volatility such as multiple underlying asset option pricing and barrier option pricing.

Military boot attenuates axial loading to the lower leg.

Science.gov (United States)

Yoganandan, Narayan; Schlick, Michael; Arun, Mike W J; Pintar, Frank A

2014-01-01

Biomechanical tests to understand injury mechanisms and derive injury tolerance information using Post-Mortem Human Subjects (PMHS) have not used foot protection and they have primarily focused on civilian environments such as automotive and athletic- and sports-related events. As military personnel use boots, tests with the boot are required to understand their effect on attenuating lower leg loads. The purpose of this study was therefore, to determine the modulation of human lower leg kinematics with boot compressions and share of the force absorbed by the boot from underbody blast loading. Axial impacts were delivered to the Hybrid III dummy lower leg in the neutral position. The dummy leg was instrumented with its internal upper and lower tibia load cells, and in addition, a knee load cell was attached to the proximal end. Tests were conducted at 4.4 to 8.9 m/s, with and without boots, and repeat tests were done. Morphologies of the force-time responses were similar at the three load cell locations and for all input combinations and booted and unbooted conditions. However, booted tests resulted in considerably lower maximum forces (approximately two-third reduction) than unbooted tests. These results clearly show that boots can absorb a considerable share of the impact energy and decrease impact loads transmitted to the lower leg under vertical loading, thus necessitating the generation of tolerance data using PMHS for this environment.

Foundations of stochastic analysis

CERN Document Server

Rao, M M; Lukacs, E

1981-01-01

Foundations of Stochastic Analysis deals with the foundations of the theory of Kolmogorov and Bochner and its impact on the growth of stochastic analysis. Topics covered range from conditional expectations and probabilities to projective and direct limits, as well as martingales and likelihood ratios. Abstract martingales and their applications are also discussed. Comprised of five chapters, this volume begins with an overview of the basic Kolmogorov-Bochner theorem, followed by a discussion on conditional expectations and probabilities containing several characterizations of operators and mea

Spatial stochasticity and non-continuum effects in gas flows

Energy Technology Data Exchange (ETDEWEB)

Dadzie, S. Kokou, E-mail: k.dadzie@glyndwr.ac.uk [Mechanical and Aeronautical Engineering, Glyndwr University, Mold Road, Wrexham LL11 2AW (United Kingdom); Reese, Jason M., E-mail: jason.reese@strath.ac.uk [Department of Mechanical and Aerospace Engineering, University of Strathclyde, Glasgow G1 1XJ (United Kingdom)

2012-02-06

We investigate the relationship between spatial stochasticity and non-continuum effects in gas flows. A kinetic model for a dilute gas is developed using strictly a stochastic molecular model reasoning, without primarily referring to either the Liouville or the Boltzmann equations for dilute gases. The kinetic equation, a stochastic version of the well-known deterministic Boltzmann equation for dilute gas, is then associated with a set of macroscopic equations for the case of a monatomic gas. Tests based on a heat conduction configuration and sound wave dispersion show that spatial stochasticity can explain some non-continuum effects seen in gases. -- Highlights: ► We investigate effects of molecular spatial stochasticity in non-continuum regime. ► Present a simplify spatial stochastic kinetic equation. ► Present a spatial stochastic macroscopic flow equations. ► Show effects of the new model on sound wave dispersion prediction. ► Show effects of the new approach in density profiles in a heat conduction.

Universality in stochastic exponential growth.

Science.gov (United States)

Iyer-Biswas, Srividya; Crooks, Gavin E; Scherer, Norbert F; Dinner, Aaron R

2014-07-11

Recent imaging data for single bacterial cells reveal that their mean sizes grow exponentially in time and that their size distributions collapse to a single curve when rescaled by their means. An analogous result holds for the division-time distributions. A model is needed to delineate the minimal requirements for these scaling behaviors. We formulate a microscopic theory of stochastic exponential growth as a Master Equation that accounts for these observations, in contrast to existing quantitative models of stochastic exponential growth (e.g., the Black-Scholes equation or geometric Brownian motion). Our model, the stochastic Hinshelwood cycle (SHC), is an autocatalytic reaction cycle in which each molecular species catalyzes the production of the next. By finding exact analytical solutions to the SHC and the corresponding first passage time problem, we uncover universal signatures of fluctuations in exponential growth and division. The model makes minimal assumptions, and we describe how more complex reaction networks can reduce to such a cycle. We thus expect similar scalings to be discovered in stochastic processes resulting in exponential growth that appear in diverse contexts such as cosmology, finance, technology, and population growth.

STOCHASTIC GRADIENT METHODS FOR UNCONSTRAINED OPTIMIZATION

Directory of Open Access Journals (Sweden)

Nataša Krejić

2014-12-01

Full Text Available This papers presents an overview of gradient based methods for minimization of noisy functions. It is assumed that the objective functions is either given with error terms of stochastic nature or given as the mathematical expectation. Such problems arise in the context of simulation based optimization. The focus of this presentation is on the gradient based Stochastic Approximation and Sample Average Approximation methods. The concept of stochastic gradient approximation of the true gradient can be successfully extended to deterministic problems. Methods of this kind are presented for the data fitting and machine learning problems.

SATA II - Stochastic Algebraic Topology and Applications

Science.gov (United States)

2017-01-30

AFRL-AFOSR-UK-TR-2017-0018 SATA II - Stochastic Algebraic Topology and Applications 150032 Robert Adler TECHNION ISRAEL INSTITUTE OF TECHNOLOGY Final...REPORT TYPE Final 3. DATES COVERED (From - To) 15 Dec 2014 to 14 Dec 2016 4. TITLE AND SUBTITLE SATA II - Stochastic Algebraic Topology and Applications... Topology and Applications Continuation of, and associated with SATA: Stochastic Algebraic Topology and Applications FA8655-11-1-3039, 09/1/2011–08/31/2014

Stochastic growth of localized plasma waves

International Nuclear Information System (INIS)

Robinson, P.A.; Cairns, Iver H.

2001-01-01

Localized bursty plasma waves are detected by spacecraft in many space plasmas. The large spatiotemporal scales involved imply that beam and other instabilities relax to marginal stability and that mean wave energies are low. Stochastic wave growth occurs when ambient fluctuations perturb the system, causing fluctuations about marginal stability. This yields regions where growth is enhanced and others where damping is increased; bursts are associated with enhanced growth and can occur even when the mean growth rate is negative. In stochastic growth, energy loss from the source is suppressed relative to secular growth, preserving it far longer than otherwise possible. Linear stochastic growth can operate at wave levels below thresholds of nonlinear wave-clumping mechanisms such as strong-turbulence modulational instability and is not subject to their coherence and wavelength limits. These mechanisms can be distinguished by statistics of the fields, whose strengths are lognormally distributed if stochastically growing and power-law distributed in strong turbulence. Recent applications of stochastic growth theory (SGT) are described, involving bursty plasma waves and unstable particle distributions in type III solar radio sources, the Earth's foreshock, magnetosheath, and polar cap regions. It is shown that when combined with wave-wave processes, SGT also accounts for associated radio emissions

Memristors Empower Spiking Neurons With Stochasticity

KAUST Repository

Al-Shedivat, Maruan

2015-06-01

Recent theoretical studies have shown that probabilistic spiking can be interpreted as learning and inference in cortical microcircuits. This interpretation creates new opportunities for building neuromorphic systems driven by probabilistic learning algorithms. However, such systems must have two crucial features: 1) the neurons should follow a specific behavioral model, and 2) stochastic spiking should be implemented efficiently for it to be scalable. This paper proposes a memristor-based stochastically spiking neuron that fulfills these requirements. First, the analytical model of the memristor is enhanced so it can capture the behavioral stochasticity consistent with experimentally observed phenomena. The switching behavior of the memristor model is demonstrated to be akin to the firing of the stochastic spike response neuron model, the primary building block for probabilistic algorithms in spiking neural networks. Furthermore, the paper proposes a neural soma circuit that utilizes the intrinsic nondeterminism of memristive switching for efficient spike generation. The simulations and analysis of the behavior of a single stochastic neuron and a winner-take-all network built of such neurons and trained on handwritten digits confirm that the circuit can be used for building probabilistic sampling and pattern adaptation machinery in spiking networks. The findings constitute an important step towards scalable and efficient probabilistic neuromorphic platforms. © 2011 IEEE.

Modeling of the time sharing for lecturers

Directory of Open Access Journals (Sweden)

E. Yu. Shakhova

2017-01-01

Full Text Available In the context of modernization of the Russian system of higher education, it is necessary to analyze the working time of the university lecturers, taking into account both basic job functions as the university lecturer, and others.The mathematical problem is presented for the optimal working time planning for the university lecturers. The review of the documents, native and foreign works on the study is made. Simulation conditions, based on analysis of the subject area, are defined. Models of optimal working time sharing of the university lecturers («the second half of the day» are developed and implemented in the system MathCAD. Optimal solutions have been obtained.Three problems have been solved:1 to find the optimal time sharing for «the second half of the day» in a certain position of the university lecturer;2 to find the optimal time sharing for «the second half of the day» for all positions of the university lecturers in view of the established model of the academic load differentiation;3 to find the volume value of the non-standardized part of time work in the department for the academic year, taking into account: the established model of an academic load differentiation, distribution of the Faculty number for the positions and the optimal time sharing «the second half of the day» for the university lecturers of the department.Examples are given of the analysis results. The practical application of the research: the developed models can be used when planning the working time of an individual professor in the preparation of the work plan of the university department for the academic year, as well as to conduct a comprehensive analysis of the administrative decisions in the development of local university regulations.

H∞ robust control of load frequency in diesel-battery hybrid electric propulsion ship

Directory of Open Access Journals (Sweden)

LI Hongyue

2017-05-01

Full Text Available Considering the load frequency fluctuation in the shipboard integrated power system caused by such stochastic uncertainty as wind, wave and current, the battery is adopted here to compensate for the difference between diesel generator output power and ship demand power, and the secondary frequency control is used for the diesel generator to guarantee the power balance in the shipboard integrated power system and suppress the frequency fluctuation. The load frequency control problem is modeled as a state space equation, the robust controller is designed by selecting the appropriate sensitivity function and complementary sensitivity function based on the H∞ mixed sensitivity principle, and the controller is solved by the linear matrix inequality(LMIapproach. The amplitude frequency characteristics denote the reasonability of the designed controller and the design requirement is satisfied by the impact of the impulse signal. The simulation results show that, compared with the classical PI controller, the controller designed by the H∞ robust method can significantly suppress frequency fluctuation under stochastic uncertainty, and improve the power variation of the diesel generator, battery and state of charge(SOC. The robust stability and robust performance of the power system are also advanced.

Stochasticity in materials structure, properties, and processing—A review

Science.gov (United States)

Hull, Robert; Keblinski, Pawel; Lewis, Dan; Maniatty, Antoinette; Meunier, Vincent; Oberai, Assad A.; Picu, Catalin R.; Samuel, Johnson; Shephard, Mark S.; Tomozawa, Minoru; Vashishth, Deepak; Zhang, Shengbai

2018-03-01

We review the concept of stochasticity—i.e., unpredictable or uncontrolled fluctuations in structure, chemistry, or kinetic processes—in materials. We first define six broad classes of stochasticity: equilibrium (thermodynamic) fluctuations; structural/compositional fluctuations; kinetic fluctuations; frustration and degeneracy; imprecision in measurements; and stochasticity in modeling and simulation. In this review, we focus on the first four classes that are inherent to materials phenomena. We next develop a mathematical framework for describing materials stochasticity and then show how it can be broadly applied to these four materials-related stochastic classes. In subsequent sections, we describe structural and compositional fluctuations at small length scales that modify material properties and behavior at larger length scales; systems with engineered fluctuations, concentrating primarily on composite materials; systems in which stochasticity is developed through nucleation and kinetic phenomena; and configurations in which constraints in a given system prevent it from attaining its ground state and cause it to attain several, equally likely (degenerate) states. We next describe how stochasticity in these processes results in variations in physical properties and how these variations are then accentuated by—or amplify—stochasticity in processing and manufacturing procedures. In summary, the origins of materials stochasticity, the degree to which it can be predicted and/or controlled, and the possibility of using stochastic descriptions of materials structure, properties, and processing as a new degree of freedom in materials design are described.

Theory, technology, and technique of stochastic cooling

International Nuclear Information System (INIS)

Marriner, J.

1993-10-01

The theory and technological implementation of stochastic cooling is described. Theoretical and technological limitations are discussed. Data from existing stochastic cooling systems are shown to illustrate some useful techniques

Multivariate moment closure techniques for stochastic kinetic models

International Nuclear Information System (INIS)

Lakatos, Eszter; Ale, Angelique; Kirk, Paul D. W.; Stumpf, Michael P. H.

2015-01-01

Stochastic effects dominate many chemical and biochemical processes. Their analysis, however, can be computationally prohibitively expensive and a range of approximation schemes have been proposed to lighten the computational burden. These, notably the increasingly popular linear noise approximation and the more general moment expansion methods, perform well for many dynamical regimes, especially linear systems. At higher levels of nonlinearity, it comes to an interplay between the nonlinearities and the stochastic dynamics, which is much harder to capture correctly by such approximations to the true stochastic processes. Moment-closure approaches promise to address this problem by capturing higher-order terms of the temporally evolving probability distribution. Here, we develop a set of multivariate moment-closures that allows us to describe the stochastic dynamics of nonlinear systems. Multivariate closure captures the way that correlations between different molecular species, induced by the reaction dynamics, interact with stochastic effects. We use multivariate Gaussian, gamma, and lognormal closure and illustrate their use in the context of two models that have proved challenging to the previous attempts at approximating stochastic dynamics: oscillations in p53 and Hes1. In addition, we consider a larger system, Erk-mediated mitogen-activated protein kinases signalling, where conventional stochastic simulation approaches incur unacceptably high computational costs

Multivariate moment closure techniques for stochastic kinetic models

Energy Technology Data Exchange (ETDEWEB)

Lakatos, Eszter, E-mail: e.lakatos13@imperial.ac.uk; Ale, Angelique; Kirk, Paul D. W.; Stumpf, Michael P. H., E-mail: m.stumpf@imperial.ac.uk [Department of Life Sciences, Centre for Integrative Systems Biology and Bioinformatics, Imperial College London, London SW7 2AZ (United Kingdom)

2015-09-07

Stochastic effects dominate many chemical and biochemical processes. Their analysis, however, can be computationally prohibitively expensive and a range of approximation schemes have been proposed to lighten the computational burden. These, notably the increasingly popular linear noise approximation and the more general moment expansion methods, perform well for many dynamical regimes, especially linear systems. At higher levels of nonlinearity, it comes to an interplay between the nonlinearities and the stochastic dynamics, which is much harder to capture correctly by such approximations to the true stochastic processes. Moment-closure approaches promise to address this problem by capturing higher-order terms of the temporally evolving probability distribution. Here, we develop a set of multivariate moment-closures that allows us to describe the stochastic dynamics of nonlinear systems. Multivariate closure captures the way that correlations between different molecular species, induced by the reaction dynamics, interact with stochastic effects. We use multivariate Gaussian, gamma, and lognormal closure and illustrate their use in the context of two models that have proved challenging to the previous attempts at approximating stochastic dynamics: oscillations in p53 and Hes1. In addition, we consider a larger system, Erk-mediated mitogen-activated protein kinases signalling, where conventional stochastic simulation approaches incur unacceptably high computational costs.

Stochasticity induced by coherent wavepackets

International Nuclear Information System (INIS)

Fuchs, V.; Krapchev, V.; Ram, A.; Bers, A.

1983-02-01

We consider the momentum transfer and diffusion of electrons periodically interacting with a coherent longitudinal wavepacket. Such a problem arises, for example, in lower-hybrid current drive. We establish the stochastic threshold, the stochastic region δv/sub stoch/ in velocity space, the associated momentum transfer j, and the diffusion coefficient D. We concentrate principally on the weak-field regime, tau/sub autocorrelation/ < tau/sub bounce/

Stochastic efficiency: five case studies

International Nuclear Information System (INIS)

Proesmans, Karel; Broeck, Christian Van den

2015-01-01

Stochastic efficiency is evaluated in five case studies: driven Brownian motion, effusion with a thermo-chemical and thermo-velocity gradient, a quantum dot and a model for information to work conversion. The salient features of stochastic efficiency, including the maximum of the large deviation function at the reversible efficiency, are reproduced. The approach to and extrapolation into the asymptotic time regime are documented. (paper)

Stochastic optimization: beyond mathematical programming

CERN Multimedia

CERN. Geneva

2015-01-01

Stochastic optimization, among which bio-inspired algorithms, is gaining momentum in areas where more classical optimization algorithms fail to deliver satisfactory results, or simply cannot be directly applied. This presentation will introduce baseline stochastic optimization algorithms, and illustrate their efficiency in different domains, from continuous non-convex problems to combinatorial optimization problem, to problems for which a non-parametric formulation can help exploring unforeseen possible solution spaces.

Stochastic quantization and gauge invariance

International Nuclear Information System (INIS)

Viana, R.L.

1987-01-01

A survey of the fundamental ideas about Parisi-Wu's Stochastic Quantization Method, with applications to Scalar, Gauge and Fermionic theories, is done. In particular, the Analytic Stochastic Regularization Scheme is used to calculate the polarization tensor for Quantum Electrodynamics with Dirac bosons or Fermions. The regularization influence is studied for both theories and an extension of this method for some supersymmetrical models is suggested. (author)

Multi-objective stochastic distribution feeder reconfiguration problem considering hydrogen and thermal energy production by fuel cell power plants

International Nuclear Information System (INIS)

Niknam, Taher; Kavousi Fard, Abdollah; Baziar, Aliasghar

2012-01-01

This paper assesses the operation and management of electrical energy, hydrogen production and thermal load supplement by the Fuel Cell Power Plants (FCPP) in the distribution systems with regard to the uncertainties which exist in the load demand as well as the price of buying natural gas for FCPPs, fuel cost for residential loads, tariff for purchasing electricity, tariff for selling electricity, hydrogen selling price, operation and maintenance cost and the price of purchasing power from the grid. Therefore, a new modified multi-objective optimization algorithm called Teacher-Learning Algorithm (TLA) is proposed to integrate the optimal operation management of Proton Exchange Membrane FCPPs (PEM-FCPPs) and the optimal configuration of the system through an economic model of the PEM-FCPP. In order to improve the total ability of TLA for global search and exploration, a new modification process is suggested such that the algorithm will search the total search space globally. Also, regarding the uncertainties of the new complicated power systems, in this paper for the first time, the DFR problem is investigated in a stochastic environment by the use of probabilistic load flow technique based on Point Estimate Method (PEM). In order to see the feasibility and the superiority of the proposed method, a standard test system is investigated as the case study. The simulation results are investigated in four different scenarios to show the effect of hydrogen production and thermal recovery more evidently. -- Highlights: ► Present an economical and thermal modeling of PEM-FCPPs. ► Present an approach for optimal operation of PEM-FCPPs in a stochastic environment. ► Consider benefits of thermal recovery and Hydrogen production for PEM-FCPPs. ► Present several scenarios for management of PEM-FCPPs.

Stochastic Thermodynamics: A Dynamical Systems Approach

Directory of Open Access Journals (Sweden)

Tanmay Rajpurohit

2017-12-01

Full Text Available In this paper, we develop an energy-based, large-scale dynamical system model driven by Markov diffusion processes to present a unified framework for statistical thermodynamics predicated on a stochastic dynamical systems formalism. Specifically, using a stochastic state space formulation, we develop a nonlinear stochastic compartmental dynamical system model characterized by energy conservation laws that is consistent with statistical thermodynamic principles. In particular, we show that the difference between the average supplied system energy and the average stored system energy for our stochastic thermodynamic model is a martingale with respect to the system filtration. In addition, we show that the average stored system energy is equal to the mean energy that can be extracted from the system and the mean energy that can be delivered to the system in order to transfer it from a zero energy level to an arbitrary nonempty subset in the state space over a finite stopping time.

Network interdiction and stochastic integer programming

CERN Document Server

2003-01-01

On March 15, 2002 we held a workshop on network interdiction and the more general problem of stochastic mixed integer programming at the University of California, Davis. Jesús De Loera and I co-chaired the event, which included presentations of on-going research and discussion. At the workshop, we decided to produce a volume of timely work on the topics. This volume is the result. Each chapter represents state-of-the-art research and all of them were refereed by leading investigators in the respective fields. Problems - sociated with protecting and attacking computer, transportation, and social networks gain importance as the world becomes more dep- dent on interconnected systems. Optimization models that address the stochastic nature of these problems are an important part of the research agenda. This work relies on recent efforts to provide methods for - dressing stochastic mixed integer programs. The book is organized with interdiction papers first and the stochastic programming papers in the second part....

Double stochastic matrices in quantum mechanics

International Nuclear Information System (INIS)

Louck, J.D.

1997-01-01

The general set of doubly stochastic matrices of order n corresponding to ordinary nonrelativistic quantum mechanical transition probability matrices is given. Lande's discussion of the nonquantal origin of such matrices is noted. Several concrete examples are presented for elementary and composite angular momentum systems with the focus on the unitary symmetry associated with such systems in the spirit of the recent work of Bohr and Ulfbeck. Birkhoff's theorem on doubly stochastic matrices of order n is reformulated in a geometrical language suitable for application to the subset of quantum mechanical doubly stochastic matrices. Specifically, it is shown that the set of points on the unit sphere in cartesian n'-space is subjective with the set of doubly stochastic matrices of order n. The question is raised, but not answered, as to what is the subset of points of this unit sphere that correspond to the quantum mechanical transition probability matrices, and what is the symmetry group of this subset of matrices

Stochastic space-time and quantum theory

International Nuclear Information System (INIS)

Frederick, C.

1976-01-01

Much of quantum mechanics may be derived if one adopts a very strong form of Mach's principle such that in the absence of mass, space-time becomes not flat, but stochastic. This is manifested in the metric tensor which is considered to be a collection of stochastic variables. The stochastic-metric assumption is sufficient to generate the spread of the wave packet in empty space. If one further notes that all observations of dynamical variables in the laboratory frame are contravariant components of tensors, and if one assumes that a Lagrangian can be constructed, then one can obtain an explanation of conjugate variables and also a derivation of the uncertainty principle. Finally the superposition of stochastic metrics and the identification of root -g in the four-dimensional invariant volume element root -g dV as the indicator of relative probability yields the phenomenon of interference as will be described for the two-slit experiment

Stochastic Effects; Application in Nuclear Physics

International Nuclear Information System (INIS)

Mazonka, O.

2000-04-01

Stochastic effects in nuclear physics refer to the study of the dynamics of nuclear systems evolving under stochastic equations of motion. In this dissertation we restrict our attention to classical scattering models. We begin with introduction of the model of nuclear dynamics and deterministic equations of evolution. We apply a Langevin approach - an additional property of the model, which reflect the statistical nature of low energy nuclear behaviour. We than concentrate our attention on the problem of calculating tails of distribution functions, which actually is the problem of calculating probabilities of rare outcomes. Two general strategies are proposed. Result and discussion follow. Finally in the appendix we consider stochastic effects in nonequilibrium systems. A few exactly solvable models are presented. For one model we show explicitly that stochastic behaviour in a microscopic description can lead to ordered collective effects on the macroscopic scale. Two others are solved to confirm the predictions of the fluctuation theorem. (author)

Perturbation theory for continuous stochastic equations

International Nuclear Information System (INIS)

Chechetkin, V.R.; Lutovinov, V.S.

1987-01-01

The various general perturbational schemes for continuous stochastic equations are considered. These schemes have many analogous features with the iterational solution of Schwinger equation for S-matrix. The following problems are discussed: continuous stochastic evolution equations for probability distribution functionals, evolution equations for equal time correlators, perturbation theory for Gaussian and Poissonian additive noise, perturbation theory for birth and death processes, stochastic properties of systems with multiplicative noise. The general results are illustrated by diffusion-controlled reactions, fluctuations in closed systems with chemical processes, propagation of waves in random media in parabolic equation approximation, and non-equilibrium phase transitions in systems with Poissonian breeding centers. The rate of irreversible reaction X + X → A (Smoluchowski process) is calculated with the use of general theory based on continuous stochastic equations for birth and death processes. The threshold criterion and range of fluctuational region for synergetic phase transition in system with Poissonian breeding centers are also considered. (author)

Stochastic models in reliability and maintenance

CERN Document Server

2002-01-01

Our daily lives can be maintained by the high-technology systems. Computer systems are typical examples of such systems. We can enjoy our modern lives by using many computer systems. Much more importantly, we have to maintain such systems without failure, but cannot predict when such systems will fail and how to fix such systems without delay. A stochastic process is a set of outcomes of a random experiment indexed by time, and is one of the key tools needed to analyze the future behavior quantitatively. Reliability and maintainability technologies are of great interest and importance to the maintenance of such systems. Many mathematical models have been and will be proposed to describe reliability and maintainability systems by using the stochastic processes. The theme of this book is "Stochastic Models in Reliability and Main­ tainability. " This book consists of 12 chapters on the theme above from the different viewpoints of stochastic modeling. Chapter 1 is devoted to "Renewal Processes," under which cla...

Stochastic assessment of investment efficiency in a power system

International Nuclear Information System (INIS)

Davidov, Sreten; Pantoš, Miloš

2017-01-01

The assessment of investment efficiency plays a critical role in investment prioritization in the context of electrical network expansion planning. Hence, this paper proposes new criteria for the cost-efficiency investment applied in the investment ranking process in electrical network planning, based on the assessment of the new investment candidates impact on active-power losses, bus voltages and line loadings in the network. These three general criteria are chosen due to their strong economic influence when the active-power losses and line loadings are considered and due to their significant impact on quality of supply allowed for the voltage profile. Electrical network reliability of supply is not addressed, since, this criterion has already been extensively applied in other solutions regarding investment efficiency assessment. The proposed ranking procedure involves a stochastic approach applying the Monte Carlo method in the scenario preparation. The number of scenarios is further reduced by the K-MEANS procedure in order to speed up the investment efficiency assessment. The proposed ranking procedure is tested using the standard New England test system. The results show that based on the newly involved investment assessment criteria indices, system operators will obtain a prioritized list of investments that will prevent excessive and economically wasteful spending. - Highlights: • Active-Power Loss Investment Efficiency Index LEI. • Voltage Profile Investment Efficiency Index VEI. • Active-Power Flow Loading Mitigation Investment Efficiency Index PEI. • Optimization model for network expansion planning with new indices.

A stochastic SIS epidemic model with vaccination

Science.gov (United States)

Cao, Boqiang; Shan, Meijing; Zhang, Qimin; Wang, Weiming

2017-11-01

In this paper, we investigate the basic features of an SIS type infectious disease model with varying population size and vaccinations in presence of environment noise. By applying the Markov semigroup theory, we propose a stochastic reproduction number R0s which can be seen as a threshold parameter to utilize in identifying the stochastic extinction and persistence: If R0s disease-free absorbing set for the stochastic epidemic model, which implies that disease dies out with probability one; while if R0s > 1, under some mild extra conditions, the SDE model has an endemic stationary distribution which results in the stochastic persistence of the infectious disease. The most interesting finding is that large environmental noise can suppress the outbreak of the disease.

Stochastic models of cell motility

DEFF Research Database (Denmark)

Gradinaru, Cristian

2012-01-01

Cell motility and migration are central to the development and maintenance of multicellular organisms, and errors during this process can lead to major diseases. Consequently, the mechanisms and phenomenology of cell motility are currently under intense study. In recent years, a new...... interdisciplinary field focusing on the study of biological processes at the nanoscale level, with a range of technological applications in medicine and biological research, has emerged. The work presented in this thesis is at the interface of cell biology, image processing, and stochastic modeling. The stochastic...... models introduced here are based on persistent random motion, which I apply to real-life studies of cell motility on flat and nanostructured surfaces. These models aim to predict the time-dependent position of cell centroids in a stochastic manner, and conversely determine directly from experimental...

Stochastic Modelling of Hydrologic Systems

DEFF Research Database (Denmark)

Jonsdottir, Harpa

2007-01-01

In this PhD project several stochastic modelling methods are studied and applied on various subjects in hydrology. The research was prepared at Informatics and Mathematical Modelling at the Technical University of Denmark. The thesis is divided into two parts. The first part contains...... an introduction and an overview of the papers published. Then an introduction to basic concepts in hydrology along with a description of hydrological data is given. Finally an introduction to stochastic modelling is given. The second part contains the research papers. In the research papers the stochastic methods...... are described, as at the time of publication these methods represent new contribution to hydrology. The second part also contains additional description of software used and a brief introduction to stiff systems. The system in one of the papers is stiff....

Stochastic dynamics and control

CERN Document Server

Sun, Jian-Qiao; Zaslavsky, George

2006-01-01

This book is a result of many years of author's research and teaching on random vibration and control. It was used as lecture notes for a graduate course. It provides a systematic review of theory of probability, stochastic processes, and stochastic calculus. The feedback control is also reviewed in the book. Random vibration analyses of SDOF, MDOF and continuous structural systems are presented in a pedagogical order. The application of the random vibration theory to reliability and fatigue analysis is also discussed. Recent research results on fatigue analysis of non-Gaussian stress proc

Stochastic Feedforward Control Technique

Science.gov (United States)

Halyo, Nesim