Solar concentrators may be classified as (i) tracking type and (ii) nontracking type. Tracking may be continuous or intermittent. It may be of one-axis or two-axes design. The Sun may be followed by moving either the focusing part or the receiver or both. Solar concentrators may also be classified on the basis of optical components. They may be (i) reflecting or refracting type, (ii) imaging or nonimaging type, and (iii) line focusing or point focusing type.
There are a number of methods by which the flux of radiation on receivers can be increased. A few of them are described below:
A cylindrical parabolic trough is a conventional optical imaging device used as a solar concentrator...Read More
If the point of consumption is relatively close to the point of production (e. g. less than 1 mile), the biomethane would typically be distributed via dedicated biogas pipelines (buried or above ground). For example, biomethane intended for use as CNG vehicle fuel could be transported via dedicated pipelines to a CNG refuelling station. For short distances over privately owned property where easements are not required, this is usually the most cost-effective method. Note that biomethane distributed via dedicated biomethane pipelines must compete with natural gas prices in the marketplace.Read More
On completion of the equipotential bonding phase, lightning current is distributed at the grounding resistance Re and across the conductors that are part of the equipotential bonding installation, while at the same time the potential increase induced by the lightning strike decreases accordingly. Described in [6.20] is a method for distributing lightning current across the various conductors and leads. It can be assumed that around half of the lightning current will be dissipated by the grounding resistance and the remaining
Connection to low voltage utility grid
D Water conduit
Connection to foundation grounding
half by the building’s nL in equal shares. In a conductor comprising nA leads, lightning current iL is distributed equally to all leads...Read More
Neural network is a massively parallel distributed processor made up of simple processing units, which has a natural property of storing experimental knowledge and making it available for use. It resembles the brain in two respects:
– Knowledge is acquired by the network from its environment through learning process.
– The interneuron connection strengths, known as synaptic weights are used to store the acquired knowledge.
The primary significance of the neural network is the ability of the network to learn from its environments and to improve its performance through learning. It learns about its environment through an interactive process of adjustments applied to its synaptic weights and biases...Read More