1. Space Research Institute
Space whether affects on power systems: prediction, risk analysis and modeling
Vitaliy Yatsenko
Panos Pardalos
Nikita Boiko
Steffen Rebbenack
Space Research Institute
NASU & NSAU
University of Florida
ІКД

2. Problem
Modeling natural space ionizing radiation effects on devices and materials
Space whether prediction
Risk analysis
space nuclear power systems
electrons damage satellites
nano-engineered super-capacitors
micro-solar power systems
optical devices and lasers 2

3. What is space weather?
Space weather describes the physical processes induced by solar activity that have impact on our terrestrial and space environment, on ground based and space technological systems, and on human activities and health.

4. Early views

5. Manifestations of space weather

6. Space weather affects on electrical power system
Space weather storm can cause electricity to flow in Earth’s atmosphere
Space weather storm mess up the flow of electricity to homes
Transformers work fine with AC (alternating current) electricity, but can damage if too much DC (direct current) electricity flows into them.

7. Electrons damage satellites
In January 1994, three geostationary satellites suffered total failures of their momentum wheel control circuitry. Services were affected for hours, and one satellite never fully recovered. At the time it was well known that satellites could suffer damage when high energy particles were emitted from the sun during an explosive Solar Particle Event (SPE). Protons and electrons travelling at relativistic speeds (a significant fraction of the speed of light such as 0.3c) could impact with orbiting satellites causing damage in a number of different ways. In this case, however, no SPE had been observed. 7

8. Main goals of space weather
establishing the scientific basis to understand physical phenomena and processes in near space;
developing operational tools to predict and forecast them.
Space weather measurements
Space weather on the Earth is measured by geomagnetic indices. There are lots of them, but the most widely used are 3: storm-time disturbance Dst, planetary index Kp and auroral index AE.

9. Number of traumas due to traffic accidents in Kyiv correlates with solar activity

10. Introduction
The most straightforward approach in understanding the dynamics of the magnetosphere is to study the whole complex chain of physical processes involved in its dynamics and to conjugate them in a global model of the evolution of the magnetosphere under the influence of the solar wind.

11. Problem Problem Problem Problem
Space radiation comes in many forms and affects electronic components in diverse ways.
Aerospace investigations of how energetic particles interact with integrated circuits and other electronics have been helping spacecraft designers and mission planners minimize the risk of component failure or performance degradation. 11

12. Problem Problem Problem Problem
Explosions on the Sun create storms of radiation, fluctuating magnetic fields, and swarms of energetic particles.
These phenomena travel outward through the Solar System with the solar wind.
Upon arrival at Earth, they interact in complex ways with Earth's magnetic field, creating Earth's radiation belts and the Aurora.
Some space weather storms can damage satellites, disable electric power grids, and disrupt cell phone communications systems. 12

13. Solar wind parameters solar wind speed density positive ions protons
magnetic field
electric field 13

14. Problem y(k+1) y(k+m) u(k) z=f(v,u) μ(v)=Ef(v,u) v(k) Black Box
Prediction
Device
Risk Analysis
Black Box
Prediction
Device
Risk Analysis
u(k)
Solar wind
parameters
z=f(v,u)
μ(v)=Ef(v,u)
v(k)
Fig. 1 Prediction and Risk Analysis 14

15. Problem B E V
Burton, R. K., R. L. McPherron, and C. T. Russell, The terrestrial magnetosphere: A half-wave rectifier of the interplanetary electric field, Science, 189, 717, 1975.
Burton, R. K., R. L. McPherron, and C. T. Russell, An empirical relationship between interplanetary conditions and Dst, J. Geophys. Res., 80, , 1975.
Kan, J. R., and L. C. Lee, Energy coupling function and solar wind-magnetosphere dynamo, Geophys. Res. Lett, 6, , 1979.
Boyle, C. B., P. H. Reiff, and M. R. Hairston, Empirical polar cap potentials, J. Geophys. Res., 102, , 1997.

16. Experimental data
The SPDF hosts the S3C Active Archive, which consists of web-based services for survey and high resolution data, trajectories, and modeling software. The Facility delivers value-added services and leads in the definition, development, operation, and promotion of collaborative projects.

17. Dynamic-information forecasting of Dst index
Magnetosphere is considered as a nonlinear complex dynamical system
Dst index
Dst is sought for as an output of a nonlinear dynamical “black-box”
Solar wind parameters
Data are from OMNI2 database:
and Kyoto WDC for Geomagnetism:

18. “Black-box model” approach
Discrete recursive (nonlinear autoregressive moving average model with exogenous inputs) models are considered. This is a so-called ‘black box’ or ‘input-output’ model, which seeks only to reproduce the behaviour of the system’s output in response to changes in its setpoint or inputs.
One of the most important features of models is that model terms are physically interpretable. For example, discrete and continuous time models of the evolution of Dst can be derived using NARMAX methodology.

19. Dynamical-information approach
Dynamical-information approach is based on the “black-box” model and Lyapunov exponents to describe magnetospheric dynamics.
Reconstruction of the dynamical model is based upon the application of multiobjective learning algorithms to identification of model’s structure and parameters.
A forecasting algorithm based on Lyapunov exponents is also proposed.

20. Dynamical-information approach
Time domain techniques are used to identify a dynamical model for the evolution of the Dst index under the influence of the solar wind.
Frequency domain analysis of this model is used to study spectral properties of the Dst index dynamics.

21. Nonlinear AutoRegressive Moving Average model with eXogenous input.
F[.]

22. Mathematical models
y(k) = F[y(k - 1),…,y(k - n), u(k - 1), …, u(k - n), ξ(k - 1),…,ξ(k - n)+ξ(k)]

23. Optimization problem y (k) = ψ(k - 1)T θ + ξ (k) (1) min J(θ)
subject to (2)

24. Numerical algorithms
For structure and parameter identification we use two numerical methods:
Genetic optimization
Nonlinear optimization with constraints

25. Results (genetic optimization)
A comparison of the model predicted values of Dst (red) with real measurements of the Dst (blue) for the test interval.

26. Results (Nonlinear optimization)
Dst, nT
N, hours

27. Numerical results
yi = 1.36 yi−1 − 4.99 ui−1 − 0.18 yi−2 ui−1 − 0.57 yi−4 −
−1.43 ui−4 ui−6 − 0.75 yi− yi− yi−3 ui−1 +
+0.36 yi− ui−6 ui− ui− yi−3 ui−2 +
+0.78 ui−2 ui−5 − 0.91 ui− ui−7 ui−12

28. Identification of linear perturbations
Local maxima correspond to magnetospheric eigenmodes
(Cheremnykh & Yatsenko, 2007)
(Balikhin et al., 2001)
phase
magnitude
Frequency, h-1

29. Neural network prediction of interplanetary shocks
Neural network prediction method based on the data from 5 data channels of ACE spacecraft (EPAM)
Preliminary experimental research showing promising capabilities of the method

30. Risk Analysis of Laser Elements for Complex Characterization of Damages by Space Radiation
Dynamic probabilistic risk analysis of optical elements for complex characterization of damages using physical model of solid state lasers and predictable level of ionizing radiation and space weather.
The following models and software have been studied:
solid-state laser model
mathematical models for dynamic probabilistic risk assessment
software for modeling and prediction of ionizing radiation

31. Risk Analysis of Laser Elements for Complex Characterization of Damages by Space Radiation
Probabilistic risk assessment is a comprehensive, structured, and logical analysis method aimed at identifying and assessing risks in solid-state lasers for the purpose of cost-effectively improving their safety and performance.
This method based on the Conditional Value-at-Risk measure (CVaR) and the expected loss exceeding Value-at-Risk (VaR).
We propose to use a new dynamical-information approach for radiation damage risk assessment of laser elements by cosmic radiation.

32. Optimization problem with constraints on risk
Let z=f(v,u) be a loss function of a device depending upon the control vector v and a random vector u. The control vector v belongs to a feasible set V, satisfying imposed requirements. We assume that the random vector u has a probability density p(u). We can define a function
Optimization model

33. Papers
O. Cheremnykh, V. Yatsenko, O. Semeniv, Iu. Shatokhina. Nonlinear dynamical model for space weather prediction. Ukr. Phys. J , N 5. - P
P. Pardalos, V. Yatsenko. Optimization approach to the estimation and control of Lyapunov exponents. Optimization Theory and its Applications, 2006, 128(1).-P

34. Conclusion
The following models have been proposed: (a) solar wind influences on devices; (b) forecasting of ionizing radiation; and (c) risk assessment in safety analysis.
An application of the multicriterion optimization method to the prediction of the Dst index was proposed.
Two novel algorithms of the identification of discrete input-output models have been developed.
The simulation results shown that the proposed technique provides an efficient method to get the optimum difference equation model of the Dst index.

35. Thank you for coming!