About the Journal

The first aim of this journal is to promote studies on the computation-based energy science. Numerical computation utilizes computers to simulate real energy processes and solve complex numerical systems. The core part of numerical simulation can be roughly divided into four steps: model construction, numerical solution, result analysis, and visualization. Numerical computation is significantly more effective than experimental research methods, allowing users to safely, quickly, and time-effectively improve the cognitive level and further explore on computers. The power of computation-based energy science is reflected in complex layout modeling, solving complex physical-chemical coupled problems and visualizing the dynamic evaluation process. Engineering operations in the energy industry can also be supported by numerical simulations, including production prediction, injection and local pressure control, enhanced recovery, oil-gas-water separation and pipeline dispatching. Especially, AI developments for state-of-art energy applications are welcomed, including reservoir digital twin construction, flow and transport modeling and simulation in the geothermal energy system and CCUS process, hydrogen storage and transportation, and many others.

This journal also aims to highlight the advances in energy-based computational science. The unconditionally energy stable property, required by the second law of thermodynamics, has been proved in a number of numerical models and algorithms, which further exhibit a better performance in computational efficiency and robustness compared with less stable numerical schemes. As a result, energy stability has attracted increasing attentions in model construction and algorithm implementation in computational science, especially for solving problems considering complex multi-component, multi-phase, multi-physics or multi-scale systems. This journal will focus on algorithms designed with energy functionals and energy norms as the main thread and related computational science (especially fully robust numerical algorithms based on discrete energy stability). In addition, the new field of thermodynamic computing is to discover universal laws based on non-equilibrium thermodynamics/statistical mechanics for all information processing (computing) systems, including the popular artificial neural network architectures.

The short name of this new journal is designed to be COMPES, which is pronounced as compass, an instrument for finding directions. The energy landscape and the computational landscape are accelerating rapidly. We wish that this journal could help the community to find future research directions in energy and computational science, with the aid of AI techniques and dialectically following the energy transition popularities.