A priori flamelet tabulation methods have been used extensively to model premixed and non-premixed combustion in Reynolds-averaged Navier-Stokes (RANS) and large Eddy simulations (LES). Pre-tabulation of flamelet libraries have led to significant cost reduction of Computational Fluid Dynamics (CFD) simulations. However, these tabulation methods rely on certain simplifying assumptions. The dimensionality of the flamelet manifolds and size of flamelet libraries are also constrained due to memory and computational limitations. This limits the applicability and predictive capability of flamelet models. The traditional representative interactive flamelet (RIF) approach with multiple flamelets on the other hand involves online solution of flamelet equations and presumed probability density function (PDF) integration at each computational cell, making it attractive but computationally expensive and not suitable for LES with large cell counts. The current work discusses the development of a novel methodology that combines the advantages of an online flamelet solver along with the computational efficacy of tabulated models. The novel in situ tabulation approach consists of creating a flamelet table at each computational time step using the unsteady flamelet equations. The flamelets are then integrated in real time based on their respective scalar dissipation rate histories. This approach is capable of including history effects and unsteady chemical kinetic effects as it involves the online solution of unsteady flamelets. Implementation and comprehensive validation of the new framework is carried out against gas-jet flames as well as spray flames at high pressures. The approach is first validated for a partially premixed methane gas-jet flame in a RANS framework. The temperature and species mass fractions are compared against experimental results at different locations of a lifted flame. The approach is able to capture the transient flame characteristics. The model is then validated against an n-dodecane spray flame at high pressures in an LES framework with a 103-species n-dodecane chemistry mechanism. The model is able to capture ignition delays and flame liftoff of the n-dodecane spray over varying ambient temperature conditions. Due to the offsetting of presumed PDF integration cost, the proposed framework is shown to be faster than the traditional RIF approach, and the speedup over RIF increases with an increase in the cell count. This framework enables use of the RIF model for large cell count LES simulations.