Air-core dynamics during the hydrocyclone operation play an essential role in determining the separation efficiency. Precise monitoring of air-core dynamics during operation can suggest possible strategies to prevent underflow discharge problems. Electrical resistance tomography (ERT) facilitates online analysis of the internal behavior of air-core, because of its high temporal resolution. Existing results for ERT-based air-core reconstructions in hydrocyclones employ general algorithms that do not utilize process knowledge. In this paper, two noniterative methods, viz., monotonicity and factorization algorithms, which are process-Aware, are evaluated to estimate air-core diameters in hydrocyclone under feed pressure variations. To further investigate the performance of these algorithms, comparison studies are made with Gauss-Newton (GN) and Total Variation (TV) algorithms. Initially, the algorithms are compared on simulated phantoms for qualitative analysis and to select hyper-parameters. A threshold method is developed for quantitative analysis of experimental data to obtain a crisp radius value. The ground truth is calculated from image processing on images obtained from a video camera. It is observed that GN, monotonicity, and factorization methods result in a similar performance on the experimental data. However, for very fine meshes, monotonicity and factorization algorithms are much faster than GN and TV methods. © 2022 American Chemical Society. All rights reserved.