Synthesized copper oxide nanoparticles were incorporated on the surfaces of carbon nanotubes using ultrasonication condition and incipient wetness impregnation technique (IWI). Morphological surfaces and structures of the prepared nanocomposite were investigated by the Scanning Electron Microscopy (SEM) and X-ray diffraction (XRD). Results showed a modification of thermophysical properties of prepared hybrid nanofluids compared to untreated carbon nanotube-water. Four parameters (Reynolds number, nanofluid volume fraction, twisted (pitch) ratio, and cavity diameter ratio) were investigated, and their impacts on the exergy efficiency enhancement of double-pipe heat exchanger were determined. Modifying response surface methodology-central composite design (RSM-CCD) to realize the optimal exergy efficiency of the system (98.4 %) showed the possibility to improve all control variables contemporarily and with significant accuracy. There was a strong correlation between the experimental and predicted values by Artificial Neural Network-Genetic Algorithm (ANN-GA) (R2 = 0.92). Minimum mean square error (MSE) was found using a three-layer ANN with 10 neurons in the hidden layer. The results show that the increased Reynolds number and nanofluid volume fraction lead to increases in the heat transfer and exergy efficiency of the system. However, while adding pitches and cavities of the spiral strip to heat exchanger increases heat transfer due to the increasing turbulence flow, at larger pitches and cavity numbers, heat transfer and exergy efficiency were reduced. This was confirmed using two computer-modeling approaches which allow optimization of the exergy of the system.