The geomagnetic solar flare effect identified by SIIG as an indicator of a solar flare observed by GOES satellites

This paper studies the efficiency of geomagnetic solar flare effects (gsfe) in X solar flare detection; so during the period 1999–2007 a comparison between solar flare (sf) observed by satellites of the Geostationary Operational Environmental Satellite (GOES) programme and gsfe published by the Service International des Indices Geomagnetiques (SIIG) is made.     

Ionization effect of solar protons in the Earth atmosphere – Case study of the 20 January 2005 SEP event

The cosmic ray ground level enhancement on January 20, 2005 is among the largest recorded events in the history of cosmic ray measurements. The solar protons of MeV energies cause an excess of ionization in the atmosphere, specifically over polar caps following major solar disturbances. The ionization effect in the Earth atmosphere is obtained for various latitudes on the basis of solar proton energy spectra, reconstructed from GOES 11 measurements and subsequent full Monte Carlo simulation of cosmic ray induced atmospheric cascade. The estimation of ionization rates is based on a numerical model for cosmic ray induced ionization. The evolution of atmospheric cascade is performed with the CORSIKA 6.52 code using FLUKA 2006b and QGSJET II hadron interaction models. The atmospheric ion rate ionization is explicitly obtained for 40°N, 60°N and 80°N latitudes. The time evolution of obtained ion rates is presented. It is demonstrated that ionization effect is negative for 40°N and small for 60°N, because of accompanying Forbush decrease. The ionization effect is significant only in sub-polar and polar atmosphere during the major ground level enhancement of 20 January 2005.     

Uncertainties in estimates of the risks of late effects from space radiation.

Methods used to project risks in low-Earth orbit are of questionable merit for exploration missions because of the limited radiobiology data and knowledge of galactic cosmic ray (GCR) heavy ions, which causes estimates of the risk of late effects to be highly uncertain. Risk projections involve a product of many biological and physical factors, each of which has a differential range of uncertainty due to lack of data and knowledge. Using the linear-additivity model for radiation risks, we use Monte-Carlo sampling from subjective uncertainty distributions in each factor to obtain an estimate of the overall uncertainty in risk projections. The resulting methodology is applied to several human space exploration mission scenarios including a deep space outpost and Mars missions of duration of 360, 660, and 1000 days. The major results are the quantification of the uncertainties in current risk estimates, the identification of factors that dominate risk projection uncertainties, and the development of a method to quantify candidate approaches to reduce uncertainties or mitigate risks. The large uncertainties in GCR risk projections lead to probability distributions of risk that mask any potential risk reduction using the "optimization" of shielding materials or configurations. In contrast, the design of shielding optimization approaches for solar particle events and trapped protons can be made at this time and promising technologies can be shown to have merit using our approach. The methods used also make it possible to express risk management objectives in terms of quantitative metrics, e.g., the number of days in space without exceeding a given risk level within well-defined confidence limits.     

Ambiguity Resolution for Satellite Doppler Positioning Systems

The implementation of satellite-based Doppler positioning systems frequently requires the recovery of transmitter position from a single pass of Doppler data. The least-squares approach to the problem yieds conjugate solutions on either side of the satellite subtrack. It is important to develop a procedure for choosing the proper solution which is correct in a high percentage of cases. A test for ambiguity resolution which is the most powerful in the sense that it maximizes the probability of a correct decision is derived. When systematic error sources are properly included in the least-squares reduction process to yield an optimal solution the test reduces to choosing the solution which provides the smaller valuation of the least-squares loss function. When systematic error sources are ignored in the least-squares reduction, the most powerful test is a quadratic form compasison with the weighting matrix of the quadratic form obtained by computing the pseudoinverse of a reduced-rank square matrix. A formula for computing the power of the most powerful test is provided. Numerical examples are included in which the power of the test is computed for situations that are relevant to the design of a satellite-aided search and rescue system.     

Monitoring the thermal condition of permanent-magnet synchronousmotors

This paper describes a novel approach to monitoring the condition of small permanent-magnet synchronous motors (PMSM) operating under thermal stress. The approach begins with the estimation of temperature-dependent motor parameters from measurements of line voltages and currents. The parameters are then used to derive estimates of motor temperatures. Next, the electrically estimated temperatures are combined with a surface measurement of motor temperature and a dynamic thermal model of the motor to yield an observer that is a Kalman filter. The temperatures estimated by the observer are used for failure prevention. Finally, by modifying the observer, it is tuned to use the geometric properties of its innovation for failure detection. The innovation, that is, the difference between the thermally and electrically estimated temperatures, is monitored and compared against appropriate thresholds to detect failures. Failure detection is demonstrated experimentally, and shown to be capable of distinguishing the conditions of normal operation, and operation with obstructed cooling