Review on the regression rate-improvement techniques and mechanical performance of hybrid rocket fuels

Human spaceflight, space tourism, and the launch of microsatellites are all expected to grow in the future. In fact, with the recent increase of the satellite market, almost 1000 smallsats per year are foreseen to be launched over the next decade. Hybrid rocket propulsion has received significant attention for military and commercial applications due to its potential safety, throttleable, and restart ability when compared with solid rockets, economicity, simplicity, and compactness features when compared to liquid rockets. However, in order to make this new technology the future of the next generation of rockets, some drawbacks of the heterogeneous combustion in hybrid rockets such as low fuel regression rate and varying oxidizer-to-fuel ratio during the combustion process must be well addressed. The diffusion-limited combustion in hybrid rocket motor is responsible for the low regression and poor combustion efficiency of fuels such as Hydroxyl-terminated polybutadiene (HTPB), Poly methylmethacrylate (PMMA), and other polymeric binder-fuels. The paraffin-based solid fuel represents a potential solution to the slow regression rate of current solid polymeric fuels. However, paraffin-based fuels suffer from poor mechanical properties and rapid volatilization, preventing their full development and applications for a space mission. In this work, a review of various techniques to improve hybrid rocket fuel's ballistic and mechanical performance is presented

Oxidation reaction kinetics of HTPB-boron carbide/polytetrafluoroethylene formulations as a solid fuel

A solid-fuel ramjet engine powered by boron carbide (B4C) can generate nearly the same amount of energy as boron. However, the inherent oxide layer on the B4C surface restricts the energy released during its oxidation. In this study, we examine the effect of polytetrafluoroethylene (PTFE) on the oxidation of B4C and the removal of the oxide layer during the oxidation reaction. The B4C/PTFE binary composite powder was prepared using a ball milling process at three different concentrations (5:20, 10:20, and 15:20). Hydroxyl-terminated polybutadiene (HTPB) loaded with binary composite powder was manufactured by vacuum casting technique. The pure HTPB and HTPB/PTFE fuels were manufactured as reference formulations. The B4C/PTFE binary composite powder was characterized by X-ray diffraction (XRD), Fourier transform infrared (FTIR), and high-resolution scanning electron microscope (HRSEM). The thermal oxidation characteristics of prepared fuel formulations were studied using the thermogravimetric technique. The kinetics of the oxidation reaction was studied using both isothermal and non-isothermal methods. The thermogravimetric curves showed that the oxidation reaction of HTPB-based fuel occurred in four steps. When B4C/PTFE binary composite powder is added to HTPB, it decomposes faster and at a higher rate. The decomposed fluorine species of PTFE significantly improved the oxidation reaction of composite powder and increased the energy release rate of B4C. The kinetic studies of oxidation suggested that the addition of B4C/PTFE binary composite powder into HTPB lowered the activation energy (Ea: S1 > S2 > S3 > S4 > S5) required to prompt the oxidation reaction. Based on thermal and kinetic results, a potential oxidation promotion mechanism of B4C/PTFE composite powder was proposed. The initial stages of B4C oxidation resulted in a glassy layer of B2O3 oxide forming at the interface of B4C and PTFE powder. As a result of the oxidation reaction between B4C/PTFE and O2, CF4, Trifluoroboron (BF3) and CO2 were generated. At high temperatures, the oxide shell ruptured, allowing the O2 to diffuse into the core of the B4C particle and releasing a large amount of heat energy

Thermal decomposition kinetics and combustion performance of paraffin-based fuel in the presence of CeO2 catalyst

In recent years, significant developments have been made in solid-fuel combustion. Paraffin-based fuels could be a potential solid fuel for hybrid and ramjet applications due to their high regression rate, low cost, and minimal environmental impact. This study examines the thermal and combustion performance of paraffin-based fuels loaded with CeO2 combustion catalysts and Al additive. A typical melt-cast technique was used to prepare three different fuel formulations, which are paraffin/10 wt.% of Al (S2), paraffin/10 wt.% of CeO2 (S3), and CeO2-Al (10:10 wt.%) binary composite (S4). The pure paraffin (S1) fuel was manufactured as a reference formulation. The CeO2-Al binary composite powder was prepared by ball-milling of CeO2 and Al powders. The CeO2 and Al nanoparticles were characterized by X-ray diffraction (XRD), particle size distribution (PSD), and scanning electron microscope (SEM). The PSD study revealed that the majority of CeO2, Al, and CeO2-Al binary composite particles are 29 nm, 34 nm, and 26 nm in size, respectively. The thermogravimetric analysis (TGA) was used to investigate the effect of CeO2 and Al on the thermal decomposition of paraffin. The results indicate that the paraffin decomposes faster and at a higher rate when CeO2 and CeO2-Al binary composite additives were added. The activation energy of paraffin-based fuel (S4) was reduced from 254 kJ/mol to 214 kJ/mol when a CeO2-Al combustion catalyst was added. The lab-scale ballistic tests showed that the average regression rate of paraffin-Al (S2) and paraffin-CeO2(S3) samples increased in the range of 1.1-1.4 mm/s and 1.12-1.38 mm/s, respectively, whereas, with the CeO2-Al binary composite (S4) sample, a reasonable improvement of 1.15 mm/s to 1.49 mm/s was reported

Combustion performance of hybrid rocket fuels loaded with MgB2 and carbon black additives

Paraffin-based fuel has a great potential for several innovative missions, including space tourism, due to its safety, low environmental impact, high performance and low cost. Despite the fact that liquefying solid fuels increases the regression rate of hybrid rocket motors, incorporating energetic materials into solid fuel can still improve the performance. The objective and scope of this study is to increase the performance characteristics of the paraffin-based fuel by using magnesium diboride (MgB2) and carbon black (CB) additives. The cylindrical-port fuel grains were manufactured with various additives percentages in mass (wt%: CB-2% and MgB2-10%) and tested using a laboratory-scale ballistic hybrid motor under gaseous oxygen. The mechanical performance results revealed that adding CB and MgB2 improved the ultimate strength and elastic modulus of paraffin-based fuels. The addition of these fillers increased the hardness of fuel by developing a strong interaction in the paraffin matrix. Thermogravimetry (TG) results showed that CB inclusion improved the thermal stability of the paraffin matrix. The average regression rates of fuels loaded with CB and MgB2 were 32% and 52% higher than those of unmodified paraffin wax, respectively. The characteristic velocity efficiency was found in the range of 68%–79% at an O/F ratio of 1.5–2.6. The MgB2 oxidation/combustion in the paraffin matrix was described by a four-step oxidation process ranging from 473 K to 1723 K. Finally, a combustion model of MgB2 in the paraffin matrix was proposed, and four-step oxidation processes were discussed in detail

Hybrid Machine Learning Approach for Gully Erosion Mapping Susceptibility at a Watershed Scale

Gully erosion is a serious threat to the state of ecosystems all around the world. As a result, safeguarding the soil for our own benefit and from our own actions is a must for guaranteeing the long-term viability of a variety of ecosystem services. As a result, developing gully erosion susceptibility maps (GESM) is both suggested and necessary. In this study, we compared the effectiveness of three hybrid machine learning (ML) algorithms with the bivariate statistical index frequency ratio (FR), named random forest-frequency ratio (RF-FR), support vector machine-frequency ratio (SVM-FR), and naïve Bayes-frequency ratio (NB-FR), in mapping gully erosion in the GHISS watershed in the northern part of Morocco. The models were implemented based on the inventory mapping of a total number of 178 gully erosion points randomly divided into 2 groups (70% of points were used for training the models and 30% of points were used for the validation process), and 12 conditioning variables (i.e., elevation, slope, aspect, plane curvature, topographic moisture index (TWI), stream power index (SPI), precipitation, distance to road, distance to stream, drainage density, land use, and lithology). Using the equal interval reclassification method, the spatial distribution of gully erosion was categorized into five different classes, including very high, high, moderate, low, and very low. Our results showed that the very high susceptibility classes derived using RF-FR, SVM-FR, and NB-FR models covered 25.98%, 22.62%, and 27.10% of the total area, respectively. The area under the receiver (AUC) operating characteristic curve, precision, and accuracy were employed to evaluate the performance of these models. Based on the receiver operating characteristic (ROC), the results showed that the RF-FR achieved the best performance (AUC = 0.91), followed by SVM-FR (AUC = 0.87), and then NB-FR (AUC = 0.82), respectively. Our contribution, in line with the Sustainable Development Goals (SDGs), plays a crucial role for understanding and identifying the issue of “where and why” gully erosion occurs, and hence it can serve as a first pathway to reducing gully erosion in this particular area