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Current CFD calibration work has mainly focused on the CFD model calibration.However no known work has considered the calibration of the CFD results. Inthis paper, we take inspiration from the image editing problem to develop amethodology to calibrate CFD simulation results based on sparse sensorobservations. We formulate the calibration of CFD results as an optimizationproblem. The cost function consists of two terms. One term guarantees a goodlocal adjustment of the simulation results based on the sparse sensorobservations. The other term transmits the adjustment from local regions aroundsensing locations to the global domain. The proposed method can enhance the CFDsimulation results while preserving the overall original profile. An experimentin an air-conditioned room was implemented to verify the effectiveness of theproposed method. In the experiment, four sensor observations were used tocalibrate a simulated thermal map with 167x365 data points. The experimentalresults show that the proposed method is effective and practical.

CFD results calibration from sparse sensor observations with a case study for indoor thermal map