New models for the size and shape of the Earth's magnetopause and bow shock are derived, based on a criterion for selecting the crossing events and their corresponding up-stream solar wind parameters. In this study, we emphasize the importance of accurate interplanetary parameters for predicting the size and shape of the magnetopause and bow shock. The time lag of the solar wind between the solar wind monitor and the location of crossings is carefully considered, ensuring more reliable up-stream solar wind parameters. With this database new functional forms for the magnetopause and bow shock surfaces are deduced. In this paper, we briefly present the preliminary results. For a given up-stream solar wind dynamic pressure D p , an IMF north-south component B z , a solar wind β and a magnetosonic Mach number M ms , the parameters that describe the magnetopause and bow shock surfaces r 0 and α can be expressed in terms of a set of coefficients determined with a multi-parameter fitting. Applications of these models to extreme solar wind conditions are demonstrated. For convenience, we have assumed that r 0 , B z and D p retain their units, except in equations where they are normalized by 1 R E (Earth radius), 1 nT and 1 nPa, respectively.

A b s t r a c tThe present paper describes an implementation of genetic search methods in multicriterion optimal designs of structural systems with a mix of continuous, integer and discrete design variables. Two distinct strategies to simultaneously generate a family of Pareto optimal designs are presented in the paper. These strategies stem from a consideration of the natural analogue, wherein distinct species of life forms share the available resources of an environment for sustenance. The efficacy of these solution strategies are examined in the context of representative structural optimization problems with multiple objective criteria and with varying dimensionality as determined by the number of design variables and constraints. I n t r o d u c t i o nMathematical nonlinear programming algorithms have been shown to be widely applicable in the automated optimal design of structural systems. They present a general approach to the problem. The more efficient of these classes of methods are gradient based (Sobieszczanski-Sobieski 1983), and require at least the first-order derivatives of both the objective function and constraints with respect to the design variables. With this "hill-climbing" or "slope-descending" ability, gradient based methods locate the relative optimum closest to the initial estimate of the optimum design. These methods do not guarantee the location of the global optimum unless the design space is known to be convex. They are also inappropriate in those applications where the design space is discontinuous, as the derivatives of the objective function or constraints may become singular across the boundary of discontinuity. Furthermore, these methods are largely designed for problems where the design space comprises of continuous real values. A modified mixed integer and discrete programming algorithm using branch-and-bound techniques has been developed (Hajela and Shih 1990), to successfully account for a mix of continuous, integer, and discrete design variables. In this approach, however, the original optimization problem is undesirably expanded to a large number of suboptimization problems.Exhaustive search and simple random search methods are among the simplest and most robust strategies for automated optimal design problems. These methods can work on almost all kinds of design spaces and without any restriction on types of design variables. An improvement on the simple enumerative techniques are methods such as random walk and random walk with direction exploitation. These methods, which require only function information, can quite often deal efficiently with nonconvex and discontinuous functions, and in many cases are capable of working with discrete type design variables. The only drawback is that they often require thousands of function evaluations to achieve the optimum, even for the simplest of problems. It is hence crucial to examine alternate strategies for optimal structural design problems, which need less computational effort than required by the enumerative search techniques, ...

[1] The influence of the solar wind dynamic pressure on the decay and injection of the ring current is investigated empirically, on the basis of the solar wind and the geomagnetic index Dst of the OMNI database, for the period from January 1964 to July 2001. We found that when the position of the ring current is closer to the Earth for a higher solar wind dynamic pressure, the decay time of the ring current decreases. The decay time, in hours, varies as follows, t = 8.70 exp(6.66/(6.04 + P)), for northward interplanetary magnetic fields (IMF), where P is the solar wind dynamic pressure in nanopascals. It is also found, by minimizing the root mean square errors of the hourly Dst difference between the calculated values and the measured ones, that the ring current injection rate is proportional to the solar wind dynamic pressure, with a power index equal to 0.2 during southward IMF. This implies that the ring current injection increases when the magnetosphere is more compressed by high solar wind dynamic pressure. On the basis of our new results we demonstrate that the predictions of Dst using O' Brien and McPherron's [2000a] model are improved, especially for intense geomagnetic storms when the influence of the solar wind dynamic pressure on the decay and injection of ring current is taken into consideration.

We present a multiyear superposed epoch study of the Sounding of the Atmosphere using Broadband Emission Radiometry nitric oxide (NO) emission data. NO is a trace constituent in the thermosphere that acts as cooling agent via infrared (IR) emissions. The NO cooling competes with storm time thermospheric heating, resulting in a thermostat effect. Our study of nearly 200 events reveals that shock‐led interplanetary coronal mass ejections (ICMEs) are prone to early and excessive thermospheric NO production and IR emissions. Excess NO emissions can arrest thermospheric expansion by cooling the thermosphere during intense storms. The strongest events curtail the interval of neutral density increase and produce a phenomenon known as thermospheric “overcooling.” We use Defense Meteorological Satellite Program particle precipitation data to show that interplanetary shocks and their ICME drivers can more than double the fluxes of precipitating particles that are known to trigger the production of thermospheric NO. Coincident increases in Joule heating likely amplify the effect. In turn, NO emissions are more than double. We discuss the roles and features of shock/sheath structures that allow the thermosphere to temper the effects of extreme storm time energy input and explore the implication these structures may have on mesospheric NO. Shock‐driven thermospheric NO IR cooling likely plays an important role in satellite drag forecasting challenges during extreme events.