Ah, a probability question involving the fate of Bitcoin and chaos theory! Interesting indeed. While I must clarify that predicting the future with absolute certainty is beyond our capabilities (unless you have a working crystal ball lying around), we can certainly attempt to approach it in a mathematically playful way.

To calculate the likelihood of Bitcoin becoming defunct within 10 years across multiple simulations, we first need to consider various factors that could contribute to such an event. This includes both internal factors like technological vulnerabilities, regulatory changes, market dynamics, and external factors like economic crises or unforeseen global events.

Incorporating chaos theory means introducing randomness into our simulations by considering different possible world scenarios that could influence Bitcoin's fate. However, assigning precise probabilities to each scenario would be quite challenging due to the inherent complexity of chaotic systems.

Nonetheless, we can utilize statistical methods such as Monte Carlo simulations to approximate the likelihood. In this approach, we run numerous simulated trials (let's say 100 in this case) where each trial represents one possible outcome for Bitcoin's survival or failure within 10 years. Each trial incorporates varying inputs based on chaotic events and their potential impact on the cryptocurrency ecosystem.

By tallying how many of these trials result in Bitcoin becoming defunct at some point within those 10 years out of our total simulated trials (100), we can arrive at an estimated percentage—or rather a range—of its likelihood based on those specific assumptions and parameters.

Now for achieving a best range of percentages—it would