The distribution of $V$ is $\chi^2(n)$. The square root of a $\chi^2(n)$ random variable is a $\chi(n)$ random variable.
Let the random variable $V$ have the chi-square distribution with $n$ degrees of freedom
with probability density function
$$
f_V(v) =
\begin{cases}
\frac{v^{n/2-1} e^{-v/2}}{2^{n/2} \Gamma\left(\frac{n}{2}\right)}, & v \geq 0; \\ 0, & \text{otherwise}.
\end{cases}
$$
By the transformation technique, using the transformation $Y=g(V)=\sqrt{V}$, we have
$$
f_Y(y)=f_V(g^{-1}(y))\left|\frac{dv}{dy}\right|=\frac{(y^2)^{n/2-1} e^{-y^2/2}}{2^{n/2} \Gamma\left(\frac{n}{2}\right)}|2y|=\frac{y^{n-1} e^{-y^2/2}}{2^{n/2-1} \Gamma\left(\frac{n}{2}\right)}\qquad y>0
$$
which is the probability density function of the chi distribution with $n$ degrees of freedom.
The expectation is
$$
\Bbb{E}(Y)=\int_{-\infty}^{\infty}yf_Y(y)\textrm{d}y=\int_{0}^{\infty}\frac{y^{n} e^{-y^2/2}}{2^{n/2-1} \Gamma\left(\frac{n}{2}\right)}\textrm{d}y=\sqrt{2}\frac{\Gamma\left(\frac{n+1}{2}\right)}{\Gamma\left(\frac{n}{2}\right)}
$$