User-specified Time Interval Research Articles

Real-Time Monitoring System Using IoT for Photovoltaic Parameters

The monitoring performance of the photovoltaic system in real time is required for estimation and optimization purposes. This monitoring system has been the subject of extensive research, but in general it employs costly commercial software and as well as other license-based software. This paper discusses the design of a photovoltaic parameter monitoring system that uses Internet of Things technology to monitor in real time. This software is intended to be as interactive as possible in order to display all measurement data in the form of graphical according to a user-specified time interval. The constructed system is tested to display the measurement parameters of the fixed and dual axis solar tracker. The test results indicate that the system can display data in real time. Every data shown is accessible from any location and at any time, so long as the device being used is connected to the Internet. This system obviously can be applied and developed for an internet of thing-based photovoltaic parameter monitoring system to facilitate system estimation and optimization.

Intelligent and Flexible Bandwidth Scheduling for Data Transfers in Dedicated High-Performance Networks

High-demanding transfers of extremely large amounts of data have been increasingly supported by the bandwidth reservation services in dedicated high-performance networks (HPNs). To use the bandwidth reservation service, a user needs to initialize a bandwidth reservation request (BRR) containing parameters and requirements of the bandwidth reservation or data transfer, such as the time interval. Upon receiving one BRR, existing researches and bandwidth reservation service providers return either the best-case bandwidth reservation (BR) or a reject message if not all the BRR requirements can be satisfied. In this paper, we study the intelligent and flexible bandwidth scheduling of two common types of BRRs: direct bandwidth reservation and indirect bandwidth reservation (data transfer). When not all the requirements of the first type can be satisfied, instead of a direct reject message, we identify and return two alternative BRs made within the closest time intervals before and after the user-specified time interval; for the second type, besides the above two alternative BRs, we also identify and return the alternative BR made within the closest time interval crossing the user-specified time interval. For each problem, we design a flexible bandwidth scheduling algorithm with rigorous optimality proofs to compute both the best-case and alternative BRs. For comparison, we also design two heuristic algorithms adapted from existing bandwidth scheduling algorithms. We then conduct extensive simulations to compare their overall performance, and the simulation results show that the proposed optimal algorithms have superior performance to those in comparison. To the best of our knowledge, our work in this paper is among the first to study intelligent and adaptive bandwidth scheduling with alternative BRs in HPNs.

Some Improvements in State/Parameter Estimation Using the Cell-to-Cell Mapping Technique

The cell-to-cell-mapping technique (CCMT) models system evolution in terms of probability of transitions within a user-specified time interval (e.g., data-sampling interval) between sets of user-defined parameter/state variable magnitude intervals (cells). The cell-to-cell transition probabilities are obtained from the given linear or nonlinear plant model. In conjunction with monitored data and the plant model, the Dynamic System Doctor (DSD) software package uses the CCMT to determine the probability of finding the unmonitored parameter/state variables in a given cell at a given time recursively from a Markov chain. The most important feature of the methodology with regard to model-based fault diagnosis is that it can automatically account for uncertainties in the monitored system state, inputs, and modeling uncertainties through the appropriate choice of the cells, as well as providing a probabilistic measure to rank the likelihood of faults in view of these uncertainties. Such a ranking is particularly important for risk-informed regulation and risk monitoring of nuclear power plants. The DSD estimation algorithm is based on the assumptions that (a) the measurement noise is uniformly distributed and (b) the measured variables are part of the state variable vector. A new theoretical basis is presented for CCMT-based state/parameter estimation that waives these assumptions using a Bayesian interpretation of the approach and expands the applicability range of DSD, as well as providing a link to the conventional state/parameter estimation schemes. The resulting improvements are illustrated using a point reactor xenon evolution model in the presence of thermal feedback and compared to the previous DSD algorithm. The results of the study show that the new theoretical basis (a) increases the applicability of methodology to arbitrary observers and arbitrary noise distributions in the monitored data, as well as to arbitrary uncertainties in the model parameters; (b) leads to improvements in the estimation speed and accuracy; and (c) allows the estimator to be used for noise reduction in the monitored data. The connection between DSD and conventional state/parameter estimation schemes is shown and illustrated for the least-squares estimator, maximum likelihood estimator, and Kalman filter using a recently proposed scheme for directly measuring local power density in nuclear reactor cores.

A Methodology for Probabilistic Accident Management

While techniques have been developed to tackle different tasks in accident management, there have been very few attempts to develop an on-line operator assistance tool for accident management and none that can be found in the literature that uses probabilistic arguments, which are important in today’s licensing climate. The state/parameter estimation capability of the dynamic system doctor (DSD) approach is combined with the dynamic event-tree generation capability of the integrated safety assessment (ISA) methodology to address this issue. The DSD uses the cell-to-cell mapping technique for system representation that models the system evolution in terms of probability of transitions in time between sets of user-defined parameter/state variable magnitude intervals (cells) within a user-specified time interval (e.g., data sampling interval). The cell-to-cell transition probabilities are obtained from the given system model. The ISA follows the system dynamics in tree form and braches every time a setpoint for system/operator intervention is exceeded. The combined approach (a) can automatically account for uncertainties in the monitored system state, inputs, and modeling uncertainties through the appropriate choice of the cells, as well as providing a probabilistic measure to rank the likelihood of possible system states in view of these uncertainties; (b) allows flexibility in system representation; (c) yields the lower and upper bounds on the estimated values of state variables/parameters as well as their expected values; and (d) leads to fewer branchings in the dynamic event-tree generation. Using a simple but realistic pressurizer model, the potential use of the DSD-ISA methodology for on-line probabilistic accident management is illustrated.

Deterministic generation of a bit-stream of single-photon pulses

We report a high efficiency scheme for generating a single-photon state transmitted out of an optical cavity. For realistic cavity QED parameters, we show that the scheme can produce a single-photon pulse with a probability exceeding 99% in a user-specified time interval. By recycling the system, the scheme can be used to create a bit-stream of single-photon pulses.

EivaN - An interactive orbital trajectory planning tool

EivaN is an interactive orbital trajectory planning tool that runs on a desktop computer with commercially available software. Orbital operations at any altitude around any celestial body can be planned and plotted on one's desktop with eivaN. After inputting the initial position of an object, such as an orbital maneuvering vehicle, with respect to a stationary object, such as a space station in a circular orbit, the operator enters the parameters of thruster firings in four dimensions (three spatial, one temporal) in order to simulate a particular mission, such as a docking maneuver. EivaN then plots the resulting trajectory. Currently, up to 5 burns may be used with 21 points plotted for each burn at a user-specified time interval. However, both the number of points and the number of burns may be modified. EivaN has successfully been used in several studies. One demonstrated the ability of naive subjects to plan docking maneuvers; the other determined velocity increment requirements for the self-rescue of a stranded extra-vehicular activity crewperson. EivaN is being used by researchers both domestic and international. NASA's computer database, COSMIC, has evaluated eivaN and is in charge of its distribution.

FISA-2/WS, A Compact Real-Time Simulator for Two-Loop Pressurized Water Reactor Plants

The FISA-2/WS simulator pack-age is divided into three modules: plant, on-line graphic display, and interactive communication. The plant module consists of models for core kinetics, reactor coolant system, steam generator, main steam line, and control and safety systems. Simulation results are displayed periodically at a user-specified time interval on a color monitor by the on-line graphic display module. The FISA-2/WS interactive communication module enables the user to initiate or mitigate accidents and to select one of the menu-driven graphic displays with the mouse and keyboard. The results presented here are obtained from simulations of steady state, turbine load change transient, and small-break loss-of-coolant accidents