Haynes 282 is a weldable, gamma prime strengthened Ni-based superalloy and is a suitable
candidate for aerospace and power-generation applications. Laser powder bed fusion (LPBF) of
Haynes 282 is gaining attention recently due to its superior mechanical properties than its
conventional counterparts. Integrated computational materials engineering (ICME) approach can be
used to tune the process parameters to obtain desired microstructure, instead of trial-and-error
methods. ICME framework integrating process and microstructure models has been established to
simulate microstructural evolution during LPBF and post-processing of Haynes 282. In addition to
the ICME framework, the challenges concerning the crystallographic anisotropy has to be
addressed. One critical but less studied parameter that influences crystallographic anisotropy is the
laser scan rotation angle. This study investigates the possibility of controlling the microstructure
and crystallographic texture by modifying the laser scan rotation angle. Further, three-dimensional
Finite difference-Monte Carlo simulations were performed to understand the microstructure
evolution with varying process parameters. Additionally, the near-rapid solidification conditions
during additive manufacturing can lead to the selection of non-equilibrium phases. Sharp interface
models via interface response functions have been used earlier to explain the microstructure
selection under such solidification conditions. However, most of the sharp interface models assume
linear superposition of contributions of alloying elements without considering the non-linearity
associated with multicomponent phase diagrams. In this work, both planar and dendritic Calphad
coupled sharp interface models have been implemented and used to explain the growth-controlled
phase selection observed at high solidification velocities relevant to additive manufacturing. The
implemented model predicted the growth-controlled phase selection in multicomponent alloys,
which the other models with linear phase diagrams did not predict. These models are calculated for
Haynes 282 and the results are compared with experimental observations.