The origin of the asymmetry in the irradiation distribution at high latitudes

The possibility of using solar energy during winter depends on the available solar radiation and on the geometry of the receiving surface. For high latitudes, the annual distribution of the available radiation is characterized by high asymmetry with a large amount of solar radiation from high altitude angles during the summer and a small amount of direct radiation from small altitude angles during the winter. This article deals with the origin of the difference between available solar radiation during summer and winter at high latitudes. Factors like the tilt of the earth’s axis, the eccentricity of the earth’s orbit, absorption and scattering of radiation in the atmosphere and seasonal changes in the weather conditions are discussed. Numerical examples of how these factors contribute to the reduction of the winter radiation compared to the summer radiation on surfaces with different orientation in Stockholm, latitude 59.4°N, are given. It is shown that the influence of the atmosphere and seasonal changes in the climate, and not pure earth-sun geometry, are the main reasons why it is hard to utilize solar energy at high latitudes during the winter.

Anomalous spin-related quantum phase in mesoscopic hole rings

We have obtained numerically exact results for the spin-related geometric quantum phases that arise in p-type semiconductor ring structures. The interplay between gate-controllable (Rashba) spin splitting and quantum-confinement-induced mixing between hole-spin states causes a much higher sensitivity of magnetoconductance oscillations to external parameters than previously expected. Our results imply a much-enhanced functionality of hole-ring spin-interference devices and shed new light on recent experimental findings.

Modeling and forecasting long-term natural gas (NG) consumption in Iran, using particle swarm optimization (PSO)

The gradual changes in the world development have brought energy issues back into high profile. An ongoing challenge for countries around the world is to balance the development gains against its effects on the environment. The energy management is the key factor of any sustainable development program. All the aspects of development in agriculture, power generation, social welfare and industry in Iran are crucially related to the energy and its revenue. Forecasting end-use natural gas consumption is an important Factor for efficient system operation and a basis for planning decisions. In this thesis, particle swarm optimization (PSO) used to forecast long run natural gas consumption in Iran. Gas consumption data in Iran for the previous 34 years is used to predict the consumption for the coming years. Four linear and nonlinear models proposed and six factors such as Gross Domestic Product (GDP), Population, National Income (NI), Temperature, Consumer Price Index (CPI) and yearly Natural Gas (NG) demand investigated.