The condition of maximum power transfer in a network occurs when the load resistance is equal to the Thevenin resistance of the source network as seen from the load's perspective. Under this condition, the power delivered to the load is maximized, and the voltage across the load is effectively utilized. This principle is commonly applied in electrical engineering to optimize the performance of circuits and systems.
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it depends if you are on the heat laxer network or not if your not on the network about 10,000 but if you have the p90x heatlaxer network somewhere in the area of 100,000
Maximum power transfer happens in a circuit when the resistance of the circuit equals the reactance. Impedance Z = R + jX. At R=X, maximum power transfer happens.
Answer Pmax=E^2/(4xRs) The maximum power is transferred when the load impedance is the complex conjugate of the source impedance. For a dc circuit or a purely resistive circuit, the load resistance equals the source resistance.
The Maximum Power Transfer Theorem is not so much a means of analysis as it is an aid to system design. The maximum amount of power will be dissipated by a load resistance when that load resistance is equal to the Thevenin/Norton resistance of the network supplying the power.
Each network supports a maximum of 16,777,214 (2 24 -2) hosts per network
XL=Xc is the resonance condition for an RLC circuit
For maximum power transfer the load resistance should be equal to the source resistance.An often misunderstood theorem. It applies strictly where one wishes maximum power transfer.It was misused for example in early power systems by trying to match the generator resistance to the load resistance.And it has little application in audio systems, where Power is much less important than Distortion. [for least distortion, the output impedance of the amplifier should be less than 10% of the impedance of the load.]
The maximum number of hosts per class B network is 65536.
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The condition for maximum velocity is acceleration equals zero; dv/dt = a= o.
An example of a maximum network flow problem is determining the maximum amount of water that can flow through a network of pipes. This problem can be solved using algorithms like Ford-Fulkerson or Edmonds-Karp, which iteratively find the maximum flow by augmenting paths in the network until no more flow can be added.