This presentation provides an overview of a recent study focused on evaluating the validity of the transient heat equation with phase change and temperature-dependent coefficients to predict melt pool evolution in rapid turnaround scan strategies during laser powder bed fusion (PBF-LB) additive manufacturing (AM). In such scenarios, residual heat effects due to short scanning vectors and laser off times between tracks significantly impact the melt pool geometry [1]. Presented results show that the conduction model originally described in [2] accurately captures the rapidly evolving melt pool geometry under these conditions. This is a fundamental discovery, as the ability to predict such dynamic scenarios has previously only been attributed to much more involved models which include fluid-like effects that otherwise require computational fluid-dynamics (CFD). However, the presented ex-situ validation methodology (e.g., validated comparison to surface topography measurements) clearly demonstrates that a large portion of the observed effects is actually captured by the heat diffusion equation, including a common model of phase-change. As a proof of concept for an application of this insight, an example of feedforward control is investigated and presented. Therein, the validated model predicts the melt pool geometry for a modified scan strategy with an increased pause time between tracks and is compared to the original configuration. The results show that increasing the pause time reduces residual heat effects on melt pool geometry leading to more consistent intra-layer melting conditions. However, this modification to the scanning strategy significantly increases build time. Therefore, the talk will provide an outlook on how numerical optimization can be used to design alternative feedforward control schemes based on dynamic laser power, velocity, or beam-shape modulation to mitigate residual heat effects without slowing down the process.