A system for accelerated simulation setup for simulating a 3D model of an industrial component, comprising: a simulation setup accelerator configured to: receive a description of a new problem for simulation, the new problem corresponding to simulating the 3D model of the industrial component; extract input data and output data of previous simulation results including solutions to problems not overtly related to the new problem; generate a data representation based on the extracted input data and output data using an ontological algorithm to represent each solved problem of previous simulations as a node in a graph and weighted edges representing distances between each node; quantify similarities, including hidden similarities, between the new problem and the extracted input data and output data based on distances between representations of the input data and the output data; query knowledge based on the quantified similarities and the representation of data to determine a candidate problem simulation based on a similarity score; and on a condition that the similarity score is equal to or greater than a threshold for an acceptable match: infer, by a machine learning component, solution outputs for the new problem based on extrapolation or interpolation of outputs of the candidate problem simulation; and a simulation engine configured to generate a simulation setup for the 3D model of the industrial component on a condition that the similarity score is less than the threshold for an acceptable match, wherein the simulation setup is generated using the queried knowledge, input variables, and input parameters corresponding to the candidate problem simulation. a simulation setup accelerator configured to: receive a description of a new problem for simulation, the new problem corresponding to simulating the 3D model of the industrial component; extract input data and output data of previous simulation results including solutions to problems not overtly related to the new problem; generate a data representation based on the extracted input data and output data using an ontological algorithm to represent each solved problem of previous simulations as a node in a graph and weighted edges representing distances between each node; quantify similarities, including hidden similarities, between the new problem and the extracted input data and output data based on distances between representations of the input data and the output data; query knowledge based on the quantified similarities and the representation of data to determine a candidate problem simulation based on a similarity score; and on a condition that the similarity score is equal to or greater than a threshold for an acceptable match: infer, by a machine learning component, solution outputs for the new problem based on extrapolation or interpolation of outputs of the candidate problem simulation; and receive a description of a new problem for simulation, the new problem corresponding to simulating the 3D model of the industrial component; extract input data and output data of previous simulation results including solutions to problems not overtly related to the new problem; generate a data representation based on the extracted input data and output data using an ontological algorithm to represent each solved problem of previous simulations as a node in a graph and weighted edges representing distances between each node; quantify similarities, including hidden similarities, between the new problem and the extracted input data and output data based on distances between representations of the input data and the output data; query knowledge based on the quantified similarities and the representation of data to determine a candidate problem simulation based on a similarity score; and on a condition that the similarity score is equal to or greater than a threshold for an acceptable match: infer, by a machine learning component, solution outputs for the new problem based on extrapolation or interpolation of outputs of the candidate problem simulation; and a simulation engine configured to generate a simulation setup for the 3D model of the industrial component on a condition that the similarity score is less than the threshold for an acceptable match, wherein the simulation setup is generated using the queried knowledge, input variables, and input parameters corresponding to the candidate problem simulation.