Two-stage compression for fast volume rendering of time-varying scalar data

A two-stage scheduling robust predictive control (RPC) algorithm, which is based on the time-varying coefficient information of the state-dependent ARX (SD-ARX) model, is designed for the output tracking control of a class of nonlinear systems. First, by using the parameter variation range information of the SD-ARX, a strategy for constructing the system’s polytopic model is designed. To further reduce the conservativeness of the convex polytopic sets which are designed to wrap the system’s future dynamics, the variation range information of the SD-ARX model’s parameters is also considered and compressed. In this method, the polytopic state-space model of the system is constructed directly based on the special structure of the SD-ARX model itself, and there is no need to make such assumption that the bounds on the parameter’s variation range in the system model are known or measurable. And then, a two-stage scheduling RPC algorithm is designed for the output tracking control. A numerical example is presented to demonstrate the effectiveness of the proposed RPC strategy.

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Two-Stage Active and Reactive Power Coordinated Optimal Dispatch for Active Distribution Network Considering Load Flexibility

Energies ◽

10.3390/en13225922 ◽

2020 ◽

Vol 13 (22) ◽

pp. 5922

Author(s):

Yu Zhang ◽

Xiaohui Song ◽

Yong Li ◽

Zilong Zeng ◽

Chenchen Yong ◽

...

Keyword(s):

Real Time ◽

Prediction Error ◽

Reactive Power ◽

Distribution Network ◽

Constant Current ◽

Economic Losses ◽

Time Varying ◽

Two Stage ◽

Active Distribution Network ◽

Active And Reactive Power

A high proportion of renewable energy connected to the power grid has caused power quality problems. Voltage-sensitive loads are extremely susceptible to voltage fluctuations, causing power system safety issues and economic losses. Considering the uncertainty factor and the time-varying characteristic, a linearized random ZIP model (constant impedance (Z), constant current (I), and constant power (P)) with time-varying characteristics was proposed. In order to improve the voltage quality of the voltage-sensitive loads in the day-here stage in an active distribution network (ADN), a linearized two-stage active and reactive power coordinated stochastic optimization model was established. The day-ahead active and reactive power coordination optimization was to smooth the large voltage fluctuation and develop a reserve plan to eliminate the unbalanced power caused by the prediction error in the day-here optimization. In the day-here real-time redispatch, the voltage was further improved by the continuous reactive power compensation device. Finally, the simulation results on the IEEE-33 bus system showed that the control strategy could better eliminate the unbalanced power caused by the prediction error and obviously improve the voltage of sensitive loads in the real-time stage on the premise of maintaining economic optimality.

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The Evaluation of Direct Volume Rendering-Based Uncertainty Visualization Techniques for 3D Scalar Data

International Journal of Image and Graphics ◽

10.1142/s021946781450017x ◽

2014 ◽

Vol 14 (04) ◽

pp. 1450017

Author(s):

Ji Ma ◽

David Murphy ◽

Gregory Provan ◽

Cian O'Mathuna ◽

Michael Hayes

Keyword(s):

Volume Rendering ◽

Completion Time ◽

User Study ◽

Task Completion ◽

Direct Volume Rendering ◽

Uncertainty Visualization ◽

Task Completion Time ◽

Scalar Data ◽

Novel Method ◽

Visualization Techniques

Many techniques have been proposed to represent uncertainty in data visualization. However, little research has been reported on the evaluation of their effectiveness. Moreover, no studies have been conducted to evaluate direct volume rendering (DVR)-based uncertainty visualization techniques. In this paper, we present a novel method that evaluates the perceptual effectiveness of four existing and one proposed DVR-based uncertainty visualization techniques. Four types of searching tasks that include identifying the maximum uncertainty data, identifying the minimum uncertainty data, identifying the maximum scalar data and identifying the minimum scalar data have been involved in this study, and a total of twenty-eight participants have contributed to the final main user study. Our analysis suggested that the proposed linked views and interactive specification (LVIS) technique appears to be the most accurate among all techniques, although it takes the longest task completion time. For the four existing techniques, the overlays technique appears to be the most advantageous, and it takes similar task completion time as the others. We believe that these findings can provide useful guidance for future uncertainty visualization design.

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Shaft Instabilities in Two-Stage Gear Systems

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.275-277.930 ◽

2013 ◽

Vol 275-277 ◽

pp. 930-935

Author(s):

Zhe Rao ◽

Chun Yan Zhou

Keyword(s):

Multiple Scale ◽

Gear System ◽

Dynamic Equations ◽

Time Varying ◽

Kutta Method ◽

Two Stage ◽

Scale Method ◽

System A ◽

Runge Kutta Method ◽

Intermediate Shaft

The present paper is focused on the torsional instabilities of the intermediate shaft in a two stage gear system. A theoretical model is established taking account in the torsional flexibility of the intermediate shaft and the meshing time-varying stiffness of the gears. Multiple scale method is applied to analysis the instability areas of the gear system for which the generalized modal coordinate is adopted. The result is certificated by numerical integrals of the dynamic equations by Runge-Kutta Method.

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