Abstract The prediction of flow distribution in regenerative cooling channels of scramjet can provide valuable reference information for flow regulation. The non-intrusive monitoring method based on deep learning is a promising approach. In this work, a generative adversarial networks-like (GAN-like) model is proposed, where the generator and discriminator are employed for temperature field reconstruction and flow distribution prediction respectively. The generator utilizes the sensor data to reconstruct the temperature field of the combustor outer wall, while the discriminator employs the generated temperature field to forecast the flow distribution within the parallel channels. The trained GAN-like model exhibits a commendable capability in predicting temperature field features and flow distribution states under the current dataset. The generator attains remarkable proficiency in reconstruction, evidenced by a structural similarity index surpassing 0.95 and a correlation coefficient exceeding 0.96. Additionally, it showcases an unforeseen aptitude at the boundary location. The discriminator exhibits stable precision in flow rate prediction, as indicated by an absolute error below 0.02 g/s and a relative error lower than 3%.

Abstract Numerical simulations are performed to investigate the propagation characteristics of ethylene/air rotating detonation waves in a two-dimensional computational domain, by solving the Navier–Stokes equations with an in-house code. Five injection area ratios (100%, 80%, 60%, 50%, and 40%) are adopted to analyze the differences in the structures of the flow field between full-area and discrete injection, as well as the effects of injection area ratios on the stability of rotating detonation waves and the parameters of detonation waves. The results show that under a full-area injection condition, the reverse waves cause the injection blockage and fuel leakage may occur when the height of the accumulated reactants increases rapidly. Under a discrete injection condition, the nonuniformity distribution of the reactants ahead of the wave affects the stability of detonation waves. The detonative front is distorted and wrinkled, accompanied by local extinction and re-ignition, when the injection area ratio is relatively small. As the injection area ratio reduces, the quantity of reactants consumed by deflagrative combustion increases and the pressurization capacity becomes weaker. The inlet mass flow rate decreases, whereas the inlet blocking ratio stays almost constant. In addition, the wave velocity is influenced by the propagation features of the detonation waves.

Abstract Supercritical fluids (SCFs) hold potential in the fields of energy and advanced propulsion, highlighting the significance of comprehensively investigating SCF flow and heat transfer characteristics. The intricate and nonlinear thermophysical property variations of SCFs coupled with the primitive variables in the conservation equations pose several challenges in effectively modeling and simulating SCF flows and heat transfer. This paper conducts a thorough assessment of commonly used equations of state and look-up tables for describing the thermophysical properties of SCFs. The data-driven methods based on machine learning for SCFs are also discussed. The challenges associated with direct numerical simulation, Reynolds-averaged simulation, and large-eddy simulation of SCFs are examined. Emphasis is placed on the evaluation and discussion of the issue of turbulence modeling strategies that stem from low-pressure or ideal-gas conditions directly applied to SCF flow and heat transfer. The primary objective is to provide guidance for future research, thereby advancing and promoting the modeling and simulations of SCF flows and heat transfer.

Abstract Regenerative cooling technology is an important approach for thermal protection in scramjet engines. Non-uniform axial and circumferential heat flow distribution on the combustor leads to improper flow distribution, resulting in reduced cooling efficiency and localized overheating, potentially causing thermal protection failure. To effectively utilize the fuel heat sink and enhance cooling efficiency, it is necessary to investigate the mechanism of flow distribution in the channels under different heat flow conditions. This study investigates the flow and heat transfer characteristics in single cooling and parallel channels under various heat flux. The heat transfer characteristics, flow resistance changes, and the influence of heat flux on heat transfer deterioration are analyzed. There are two types of heat transfer deterioration in channels, caused by the inlet effect and the mutation of fuel supercritical properties. Furthermore, the mechanism behind flow deviation induced by non-uniform heat flux in parallel channels is investigated. When a supercritical process occurs, non-uniform heat flux induces temperature deviations, resulting in density distribution variations. This, in turn, influences velocity distribution and leads to disparities in flow resistance distribution. Consequently, flow deviation occurs, and the cracking reaction amplifies flow deviation while reducing temperature deviation.

Abstract An iterative dynamic chemical stiffness removal method (IDCSR) based on quasi-steady-state approximation (QSSA) is proposed. The IDCSR method is built on a previously developed non-iterative method which has proved to work well for small timestep sizes. A novel iterative procedure is designed in IDCSR to enable explicit time integration of stiff chemistry at relatively large timestep sizes relevant to practical reacting flow simulations. The effectiveness of the iterative procedure is first demonstrated with a toy problem and homogeneous auto-ignition with fixed integration step sizes, showing that larger timestep sizes can be allowed for explicit time integration using IDCSR compared with the previous non-iterative method. IDCSR is then compared with existing explicit chemistry solvers for simulations of homogeneous auto-ignition and shows similar or lower computational cost but significantly higher accuracy across a wide range of timestep sizes. IDCSR is further combined with an automatic adaptive time-stepping scheme for simulations of 0-D homogeneous auto-ignition and a 2-D laminar lifted n-dodecane jet flame. For the 0-D auto-ignition simulations, IDCSR is shown to reduce both the error (by 43%–90%) and computational cost (by 6–15 times) compared with existing explicit solvers, while achieving speed-up factors of up to 400 compared with VODE for a wide range of timestep sizes and reaction mechanisms. For the 2-D jet flame simulations, speed-up factors of 15 and 31 for chemistry integration, and 5 and 9 for overall simulation, are achieved by IDCSR compared with CVODE with and without analytic Jacobian, respectively.

Abstract Hydrogen energy is essential to establishing a sustainable and reliable energy system. The continuously growing demand for hydrogen is driven by the challenges associated with greenhouse gas emissions and resource depletion. This paper investigates and summarizes some intriguing hydrogen production processes that have evolved from laboratory stages to mature commercial applications. The analysis of techno-economic, environmental effects and investment trends of these processes are included. Currently, hydrogen is dominantly produced by methods with fossil fuels as feed. These technology processes are relatively mature and account for the majority of the world's hydrogen production, around 99%. However, these results in significant carbon emissions. Around 1400 million tons of carbon dioxide are emitted into the atmosphere. To achieve carbon neutral strategy, the hydrogen production from hydrocarbon fuels needs to become clean. Equipping carbon capture, utilization, and storage system is a promising way to reduce carbon emissions. In addition, hydrogen production schemes with zero carbon emissions like electrolytic and photocatalysis are attracting increasing attention. The survey results suggest that the price of hydrogen production associated with the addition of carbon capture equipment ranges from 1.47 to 6.04 USD/kg, which is higher than the value for the price without the additional facility (1.03–2.08 USD/kg). The introduction of carbon tax is expected to narrow the cost gap between the two. Besides, the cost of electrolysis remains expensive (6.25–12.2 USD/kg), depending on the energy source and electrolytic cell equipment. The high-pressure autothermal reforming technique coupled with carbon capture and electrolytic technique powered by renewable energy are favored by global commercial investment. Finally, key challenges and opportunities for clean hydrogen production are discussed in this paper. More attention should be paid to catalyst blockage or deactivation and the cost of carbon capture equipment for fossil fuel hydrogen production. For the new zero-carbon hydrogen production method, designing efficient, economical catalysts and electrolysis materials is essential for its large-scale application.