n irrational number whose digits are pseudo-random: conceptual mismatch?
TL;DR The decimal expansion of a fixed rational number is not pseudorandom in the cryptographic sense, but irrational numbers (are conjectured to) exhibit some weaker but interesting forms of pseudorandom behavior.

Roughly speaking, a sequence $s \in \{0, \ldots, B\}^n$ is pseudorandom with respect to distinguishers $\cal A$, if it cannot be distinguished (with non-trivial probability) from a uniformly random sequence sampled from $\{0, \ldots, B\}^n$ by any algorithm $A$ in a class of algorithms $\cal A$. Usually in cryptography, $\cal A$ is the class of polynomial-time algorithms or polynomial-size circuits. Then it is easy to see that any sequence that can be generated in polynomial time by a deterministic algorithm is not pseudorandom: the distinguisher just simulates the generator. For this reason, pseudorandom generators in cryptography are randomized, and we speak of a pseudorandom distribution rather than a fixed pseudorandom sequence.

However, there are weaker notions of pseudorandomness (corresponding to more restricted classes $\cal A$ of distinguishers) that the expansion of an irrational number in an integer basis might satisfy. For example, $\sqrt{2}$, $e$, and $\pi$ are conjectured to be normal, which is a kind of pseudorandomness: each pattern of $k$ digits in base $B$ appears with frequency $1/B^k$, in the limit. This is like pseudorandomness with respect to distinguishers which can only ask "approximately how often does this pattern appear in the expansion of $\sqrt{2}$?" However, at the moment we are unable to prove normality for any of the above fundamental constants, in any base, even though it is conjectured they are absolutely normal, i.e. normal in every base. This is a famous open problem. 

Something that we understand better is sequences like $(k\sqrt{2} \bmod 1)_{k = 1}^\infty$ ($x \bmod 1$ just means the fractional part of $x$). By Weyl's ergodicity criterion, we know that for any Lebesgue integrable function $f$, the average
$$
\overline{f}_n = \frac{1}{n-1}\sum_{k = 0}^{n-1}{f(k\sqrt{2} \bmod 1)},
$$
converges to the expectation $\mathbb{E}[f(x)]$, where $x$ is a uniformly sampled random number from $[0, 1]$. We also have deviation estimates: for $f$ the indicator function of an interval $I = [a, b]$, $a, b \in [0,1]$, the average $\overline{f}_n$ deviates from the expectation $b-a$ by $O((\log n)/n)$ in the worst case, and by $O(\sqrt{\log n}/n)$ on most intervals $[a, b]$ ("most" is measured by the natural product measure). Moreover, Beck has recently shown a central limit theorem, which quantifies the statement that numbers $n$ for which the deviation is large are very rare. For an intro to  the pseudorandomness properties of these sequences, check section 2.3. of Chazelle's discrepancy book.