diff --git a/book/src/cluster/turbine-block-propagation.md b/book/src/cluster/turbine-block-propagation.md
index c792cdad34..cbccc843bc 100644
--- a/book/src/cluster/turbine-block-propagation.md
+++ b/book/src/cluster/turbine-block-propagation.md
@@ -36,6 +36,59 @@ Finally, the following diagram shows a two layer cluster with a Fanout of 2.
 
 Currently, configuration is set when the cluster is launched. In the future, these parameters may be hosted on-chain, allowing modification on the fly as the cluster sizes change.
 
+## Calcuating the required FEC rate
+
+Turbine relies on retransmission of packets between validators.  Due to
+retransmission, any network wide packet loss is compounded, and the
+probability of the packet failing to reach is destination increases
+on each hop.  The FEC rate needs to take into account the network wide
+packet loss, and the propagation depth.
+
+A shred group is the set of data and coding packets that can be used
+to reconstruct each other.  Each shred group has a chance of failure,
+based on the likelyhood of the number of packets failing that exceeds
+the FEC rate. If a validator fails to reconstruct the shred group,
+then the block cannot be reconstructed, and the validator has to rely
+on repair to fixup the blocks.
+
+The probability of the shred group failing can be computed using the
+binomial distribution.  If the FEC rate is `16:4`, then the group size
+is 20, and at least 4 of the shreds must fail for the group to fail.
+Which is equal to the sum of the probability of 4 or more trails failing
+out of 20.
+
+Probability of a block succeeding in turbine:
+
+* Probability of packet failure: `P = 1 - (1 - network_packet_loss_rate)^2`
+* FEC rate: `K:M`
+* Number of trials: `N = K + M`
+* Shred group failure rate: `S = SUM of i=0 -> M for binomial(prob_failure = P,  trials = N, failures = i)`
+* Shreds per block: `G`
+* Block success rate: `B = (1 - S) ^ (G / N) `
+* Binomial distribution for exactly `i` results with probability of P in N trials is defined as `(N choose i) * P^i * (1 - P)^(N-i)`
+
+For example:
+
+* Network packet loss rate is 15%.
+* 50kpts network generates 6400 shreds per second.
+* FEC rate increases the total shres per block by the FEC ratio.
+
+With a FEC rate: `16:4`
+* `G = 8000`
+* `P = 1 - 0.85 * 0.85 = 1 - 0.7225 = 0.2775`
+* `S = SUM of i=0 -> 4 for binomial(prob_failure = 0.2775,  trials = 20, failures = i) = 0.689414`
+* `B = (1 - 0.689) ^ (8000 / 20) = 10^-203`
+
+With FEC rate of `16:16`
+* `G = 12800`
+* `S = SUM of i=0 -> 32 for binomial(prob_failure = 0.2775,  trials = 64, failures = i) = 0.002132`
+* `B = (1 - 0.002132) ^ (12800 / 32) = 0.42583`
+
+With FEC rate of `32:32`
+* `G = 12800`
+* `S = SUM of i=0 -> 32 for binomial(prob_failure = 0.2775,  trials = 64, failures = i) = 0.000048`
+* `B = (1 - 0.000048) ^ (12800 / 64) = 0.99045`
+
 ## Neighborhoods
 
 The following diagram shows how two neighborhoods in different layers interact. To cripple a neighborhood, enough nodes \(erasure codes +1\) from the neighborhood above need to fail. Since each neighborhood receives shreds from multiple nodes in a neighborhood in the upper layer, we'd need a big network failure in the upper layers to end up with incomplete data.