A two-dimensional reverse design framework based on explicit B-spline curve and surface representations is proposed for solid rocket motor propellant grains. Given a target chamber pressure curve, the framework first reconstructs the required burning surface regression curve by inverting the equilibrium pressure equation. The grain geometry is then inversely determined by optimizing the control points of the B-spline to match the burning surface regression curve. The fast marching method (FMM) simulates the grain burn-back, while a genetic algorithm (GA) minimizes the loss between simulated and target burning surface regression curves. Numerical results demonstrate that the approach can generates grain configurations that reproduce the desired pressure profile, with optimized shapes distinct from conventional two-dimensional geometries—thus broadening the design space. Compared with data-driven reverse design methods that rely on implicit representations such as neural fields, the B-spline offers intuitive geometric expressiveness, physically interpretable design variables, and strong engineering applicability. By supporting both curve- and surface-based representations, the framework effectively captures complex grain topologies.

Efficient particle combustion is crucial for improving the overall performance of solid rocket ramjets. However, particle combustion is jointly constrained by multiple environmental factors, such as oxidizer supply, gas–solid transport, and residence characteristics, which are difficult to characterize using conventional mixing-ratio-based evaluations fully. To provide a diagnostic evaluation of particle combustion potential under complex flow-field organization during design and optimization, a thermal-environment-informed particle combustion index ITPCI is proposed in this study. The index incorporates oxidizer availability, particle–oxidizer transport, residence-related effects, gas thermal environment, and particle thermal reactivity, and is intended to indicate regions where particle oxidizer-consumption capability can be retained under favorable thermochemical conditions. The reacting duct case shows that ITPCI provides a combustion-potential-oriented description of particle consumption. In the canonical jet-interaction flow, the conventional mixing degree mainly identifies shear-layer-dominated transport boundaries, while ITPCI emphasizes the regions with particle-consumption potential. Application to the afterburner further shows that particle combustion potential is governed by the match among oxidizer supply, particle transport, residence condition, and thermal environment. The head region has favorable thermal and residence conditions but remains oxygen-lean, whereas the downstream regions receive additional oxidizer but are constrained by nonuniform oxygen–particle distributions, thermal environment, and residence time. In the pulsed-jet cases, the variation of ITPCI provides a diagnostic interpretation of changes in particle source-term distribution. For the present configuration, upstream pulsed actuation mainly enhances the head-region response, and the selected case increases the full-domain gaseous-product source term associated with boron combustion by 2.96%. These results indicate that the proposed index can support combustion-potential diagnosis and flow-control assessment in solid rocket ramjet afterburners.

Inverse design of solid propellant grains seeks geometries that reproduce prescribed internal-ballistic pressure–time profiles to enable rapid design iteration under complex performance requirements. Most surrogate-based methods rely on fixed-topology templates, limiting their ability to represent diverse burnback evolutions, while free-form topology optimization often lacks engineering interpretability and compatibility with template-based workflows. This study proposes a unified multi-topology inverse-design framework based on geometric-element-level parameterization within a shared design space. Grain geometries are represented by activatable geometric elements, enabling controlled topology switching while preserving compatibility with conventional parametric representations and engineering interpretability. A physics-consistent multi-topology dataset is constructed through a coupled forward-analysis pipeline integrating level-set burnback simulation with a zero-dimensional internal-ballistic model. A learning-based inverse strategy performs topology identification and topology-conditioned geometric parameter inversion directly from pressure–time inputs. Numerical results demonstrate reliable recovery of topology and key geometric parameters across multiple topologies and burnback scenarios. For the three representative pressure–time targets, the relative errors in total impulse are 0.26%, 1.89%, and 1.73%, with cosine similarities of 0.9853, 0.9938, and 0.9932, respectively. Uncertainty and noise analyses indicate stable topology identification, with variability concentrated near ignition peaks and stage transitions. The proposed framework provides an engineering-compatible pathway for multi-topology inverse grain design.

Low combustion efficiency and unsteady mixing dynamics within the ram-combustor are persistent issues that limit the performance envelope of solid rocket ramjets. A fundamental challenge is the difficulty in evaluating the complex, unsteady mixing process between fuel-rich gas and ingested air. In this study, an optimization framework based on Lagrangian Coherent Structures is established. By extracting the ridges of the Finite-Time Lyapunov Exponent (FTLE) in non-reacting flows, a metric termed the Ridge Area Fraction (RAF) is introduced to characterize the spatial extent of coherent structures and to support the assessment of reacting-flow combustion performance. Both RAF and the Ridge Area-Averaged Intensity are examined during the qualitative mechanism analysis. Under the present operating condition and sample size, intensity do not provide statistically meaningful additional explanatory improvement beyond the RAF-ratio-based formulation. Therefore, the final quantitative correlation is constructed using the Forward-to-Backward RAF ratios in the three inlet zones. Results indicate that the base configuration suffers from aerodynamic barriers and spatial misalignment between air and fuel streams, leading to severe flow stratification. In contrast, optimized staggered designs enhance performance through distinct mechanisms: the symmetry configuration relies on targeted transport, while the shear configuration leverages swirl-induced particle dispersion. The optimal three-stage configurations achieve up to 16.67% combustion efficiency improvement. Within the present design space, higher-efficiency configurations tend to exhibit an inter-stage Forward-to-Backward RAF ratio above approximately 0.6, indicating that sufficient inter-stage topological balance is required to break flow confinement. Combining the RAF-ratio trend with ignition-related physical constraints suggests that the areas of Inlet I and Inlet II should remain comparable, while Inlet III should be enlarged relative to Inlet II. These results demonstrate that the proposed analysis can employ non-reacting flow topology to guide optimization of ram-combustors within the same geometry family under consistent operating conditions.

The reverse design of solid rocket motor (SRM) propellant grain involves determining the grain geometry to closely match a predefined internal ballistic curve. While existing reverse design methods are feasible, they often face challenges such as lengthy computation times and limited accuracy. To achieve rapid and accurate matching between the targeted ballistic curve and complex grain shape, this paper proposes a novel reverse design method for SRM propellant grain based on time-series data imaging and convolutional neural network (CNN). First, a finocyl grain shape-internal ballistic curve dataset is created using parametric modeling techniques to comprehensively cover the design space. Next, the internal ballistic time-series data is encoded into three-channel images, establishing a potential relationship between the ballistic curves and their image representations. A CNN is then constructed and trained using these encoded images. Once trained, the model enables efficient inference of propellant grain dimensions from a target internal ballistic curve. This paper conducts comparative experiments across various neural network models, validating the effectiveness of the feature extraction method that transforms internal ballistic time-series data into images, as well as its generalization capability across different CNN architectures. Ignition tests were performed based on the predicted propellant grain. The results demonstrate that the relative error between the experimental internal ballistic curves and the target curves is less than 5%, confirming the validity and feasibility of the proposed reverse design methodology.

Liquid-solid flow plays a dominant role in the mixing and pouring of hydroxyl-terminated polybutadiene (HTPB) propellants and has been modeled using various approaches. However, predicting solid flow patterns and particle interactions with continuum-based models remains challenging. In this study, the computational fluid dynamics-discrete element method approach was employed to investigate liquid-solid flow during percolation of slurry in microchannels. The results revealed particle segregation during the slurry percolation process and showed that the microchannel width influenced the solid flow patterns significantly. The mechanisms by which coarse and fine particles are influenced by the fluid differ, leading to variations in volume fraction within the microchannels. By employing a particle staining and grouping method and investigating porosity and particle coordination number, a better understanding of the liquid-solid flow mechanism was achieved. The presence of particle segregation was confirmed by scanning electron microscopy, Fourier transform infrared spectroscopy, and differential scanning calorimetry tests on the thin film obtained from slurry curing in the microchannel. Sensitivity test results demonstrated that the slurry in the 0.3-mm microchannel had high safety performance, ensuring intrinsic safety during propellant manufacturing. The results provide significant engineering insights into the design of core molds and safety assessment of the charging process.

The digital simulation and optimization design method has been widely applied in the Solid Rocket Motor (SRM) design industry. However, they still fall short in robustness and integrated optimization to fully meet the needs of the general department. Regarding simulation calculations, challenges exist in executing simulations for factors such as structural dynamics and flow fields across the entire time span. Additionally, the generality of optimization design tools is poor, and the levels of software integration and automation remain low. The study proposes a framework for the Mass-concept based Optimum Seeking Method (MBOS) concept in SRM design, following a pathway of “Geometry Model Generation–Performance Simulation–Design Scheme Evaluation–Global Optimization”. The framework establishes a design methodology for SRMs based on Design Space Traversal and Full-time Simulation. It enables automated multi-physics modelling and simulation across the entire time span, multidimensional global performance optimization of schemes.

To obtain propellant formulations with superior comprehensive and robustness performance, the study establishes a multi-objective optimization model that accounts for uncertainties. The model adopts a bi-layer structure. The inner layer computes performance bounds to construct uncertainty intervals, which are subsequently transformed into deterministic performance via interval order relations. The outer layer optimizes component mass fractions using MOEA/D (Multi-objective Evolutionary Algorithm Based on Decomposition) to maximize the deterministic performance. The study leverages Large Language Models (LLMs) as pre-trained optimizers to automate the operator design of MOEA/D. Designers can identify formulations that satisfy the performance requirements and robustness criteria by adjusting uncertainty levels and MOEA/D weight coefficients. The results on ZDTs and UFs demonstrate that MOEA/D-LLM achieves approximately a 4.0% improvement in hypervolume values compared to MOEA/D. Additionally, the NEPE propellant optimization case shows that MOEA/D-LLM improves the computational speed by about 13.05% and enhances hypervolume values by around 2.7% compared to MOEA/D. The specific impulse increases by 1.11%, the generation of aluminum oxide and hydrogen chloride decreases by approximately 18.43% and 16.40%, respectively, and the impact sensitivity is reduced by about 1.67%.

During the primary combustion of boron-containing propellants, boron particles tend to adhere and aggregate, leading to secondary combustion occurring in the form of multi-particle aggregates. Once the aggregates reach their melting point, the molten droplets gradually become spherical, significantly reducing the reactive surface area and affecting the accuracy of boron particle combustion models. This study numerically investigates the influence of flow and mass transfer processes on the morphological evolution of molten boron aggregates. Results indicate that larger aggregates contain more internal cavities and spheroidize at a slower rate. The “micro-explosion” phenomenon during secondary combustion is primarily caused by the evaporation of residual low-boiling impurities and is independent of flow conditions. Furthermore, higher impurity content leads to a greater degree of droplet fragmentation.

To reduce the high computational cost and lengthy design cycles of traditional solid rocket motor (SRM) development, this paper proposes an efficient surrogate-assisted multi-objective optimization approach. A comprehensive performance model was first established, integrating internal ballistics, grain structural integrity, and cost estimation, to enable holistic assessment of the coupled effects of key motor components. A parametric analysis framework was then developed to automate the model, facilitating seamless data exchange and coordination among sub-models through chain coupling. Leveraging this framework, a large-scale, high-fidelity dataset was generated via uniform sampling of the design space. The Kriging surrogate model with the highest global fitting accuracy was subsequently employed to replicate the integrated model’s complex responses and reveal underlying design principles. Finally, an enhanced NSGA-III algorithm incorporating a phased hybrid crossover operator was applied to improve global search performance and guide solution evolution along the Pareto front. Applied to a specific SRM, the proposed method achieved a 4.72% increase in total impulse and a 6.73% reduction in cost compared with the initial design, while satisfying all constraints.

After the combustion of the solid rocket motor's grain is basically completed, residual gases continue to be expelled due to remaining grain burning and ablation of the insulation layer in the descent segment of the internal ballistic, generating additional thrust. The paper takes the moment when the combustion of the grain is essentially complete as the starting point of the descent segment, and employs solid modeling to calculate the residual grain burning surface during descent and considering the insulation layer ablation mechanism, combining theoretical mathematical models of motor operation with semi-empirical formulas derived from experiments, presenting an engineering algorithm for the descent segment. The validation of the engineering algorithm was conducted through firing test of ablative motor. The results indicated that the engineering algorithm had a maximum relative error of 11.6%. The model can reasonably predict the energy of the descent segment.

In order to study the combustion instability of solid rocket motors, the vibration-acoustic vibration-burning rate oscillation-thrust oscillation coupling system of solid rocket motors is analyzed. In this paper, a numerical model covering the pressure oscillation, combustion, pseudo-one-dimensional fluid field, and overall thrust is built. We investigate the thrust oscillation caused by projectile structure vibration and the response characteristics of thrust oscillation. By conducting a sine sweep test, we obtain the response function of thrust in relation to pressure oscillation. A physical experiment shows that the calculated frequency response function is consistent with the experimental results.

We propose a method for computing the finite-time Lyapunov exponent (FTLE) based on the discrete phase model (DPM), which is integrated with a CFD solver and has several advantages as follows. Unlike the conventional method that calculates the fine velocity field first and then calculates the particle trajectory based on the velocity field, the particle position and velocity field in the resulting method are solved simultaneously in the CFD solver, which saves memory and improves the computational efficiency. The resulting method can be applied to arbitrarily complex three-dimensional flows, which helps to promote Lagrangian analysis in the complex flows in aerospace. The discrete phase model used in the resulting method is flexible and easy to be extended. For example, it can be extended from massless tracer particles to real particles with mass. The finite-time Lyapunov exponent is also used to evaluate the uniformity of scalar convection mixing, it is found that the larger the finite-time Lyapunov exponent at the mixture contact line, the longer the contact line for the next time period, indicating more uniform convective mixing.

C/C composite and resin materials have been applied in rocket motor nozzles. This study aims to investigate the thermal contact resistance (TCR) between C/C composite and resin materials. Contact surfaces are scanned by surface morphological-measuring instrument. The TCR values are solved numerically. With the steady-state heat flux method, the TCR values are experimentally measured at different temperatures and pressures. The study results show that the TCR value between C/C composite and resin materials varies in the range of 1.8245 x 10(-3) similar to 7.5851 x 10(-3) K center dot m(2)center dot W-1 at different pressures and temperatures. The average TCR error between numerical analysis and test results is 8%, which indicates a high accuracy. The developed TCR numerical prediction model can provide a reference for thermal-structural design and analysis of nozzles.

Solid rocket ramjet faces the problems of large angle maneuvering and stage transformation in the actual operation. In order to study the effect of the change of angle of attack and excess air coefficient on the performance of boron-containing solid rocket ramjet, the fluid field with different conditions were calculated. The applicability of the numerical model was verified by ground direct-connected experiments. The results showed that as the angle of attack increases, the mixing in the head reflux area and the initial air-gas contact area are enhanced. The combustion ratio of combustible components in the front section is greatly increased, which helps to improve the combustion efficiency of the motor. When the excess air coefficient increases from less than 1 to much greater than 1, the mixing combustion in the head region is also strengthened. However, the radial impact of excess air causes the gas to deflect to the upper side of chamber, and then most of the particles move close to the wall, resulting in a lower level of combustion. The general trend is as follows, under the same mixing-dominated pattern, the average mixing at the outlet decreases with increasing angle of attack, and the combustion efficiency is reversed. Under different mixing-dominated patterns, higher combustion efficiency can be obtained at lower mixing when the head region dominates.

Mixing and combustion are the core processes in the operation of the ramjet engine, and the contact line length (2D) or contact area (3D) is an important bridge to analyze the link between mixing and combustion. In this paper, a new formula for calculating the contact area of two components in an arbitrary complex region is proposed, which can analyze the dynamic mixing process of the two components. It can be used to evaluate the mixing efficiency in the dynamic mixing process, the larger the contact area, the higher the mixing efficiency. This paper establishes a new method to evaluate the mixing in ramjet engines based on the Lagrangian coherence structures, and uses this method to study the feasibility of the application of the lobed mixer in ramjet engines. The study shows that the vortex induced by the lobed mixer can significantly increase the contact area between gas and air in the combustion chamber, effectively enhancing the mixing and combustion of gas and air therein. The average mixing efficiency during the operation increased by 11.046% and the combustion efficiency increased by 8.318%.

固化降温工艺对固化降温过程固体发动机药柱的温度场和应力场有显著影响.为准确评估固化降温过程固体发动机药柱的结构完整性水平,优化固化降温工艺,采用数值模拟方法对某碳纤维复合材料壳体发动机药柱在 6 种固化降温工艺条件下的温度场和结构完整性进行计算,计算过程考虑壳体表面对流换热系数的动态变化和热辐射效应,极大提高了降温过程热载荷引起的药柱结构响应的计算精度.计算得到了不同工艺条件下药柱的温度场及变化规律、应力应变响应规律,评估了药柱的结构完整性.结果表明,通过监测壳体表面温度,并结合温差变化规律和药柱温度平衡时滞可估算药柱内的温度及其平衡时间.通过调整降温工艺参数,可提高药柱的安全系数.降温初期缓慢降温可降低药柱应力应变增长速率,同时可降低药柱的累积损伤水平.

It is of great significance to study the mixing combustion characteristics of solid rocket ramjet for better organizing the secondary combustion of the air flowing into the inlet and the combustion-rich gas, enhancing the mixing degree of the supplementary combustion chamber, and improving the combustion efficiency. In this paper, the L-W model is used as the boron particles ignition combustion model. Combined with the UDF function of fluent, the boron particle ignition combustion program is self-programmed, the finite rate/eddy dissipation model is used as the gas combustion model, and the Realizable k-e turbulence model is used as the turbulence model. The numerical simulation was carried out under the cold flow state and the hot flow state, and the flow field distribution and parameters were obtained, and the mixing characteristics were analyzed. The error of simulation results and test results shows that that the numerical simulation results are in good agreement with the experimental results. By comparing the combustion efficiency and mixing degree, it is found that generally, When the mixing effect is not good, the combustion efficiency must be bad; When the mixing effect is good and the mixing degree is high, the combustion efficiency may be high.

In the development process of aircraft, it needs to be tested in different incoming flow environments. Therefore, the test equipment that can provide a wide Mach number range and a fast-response flow field has always been a research hotspot. In this paper, a variable Mach number aerodynamic test device by a rotating profile is constructed with a divergent nozzle. The flow field parameters of the device are calculated by numerical simulation. The influence of the initial divergent half-angle of the cubic curve profile and the profile rotation mode on the test area is analyzed by using the flow quality evaluation method. The results show that when the incoming flow Mach number is 1.5 to 3.0, by adjusting the incoming flow Mach number and the expansion ratio of the test device, the Mach number in the test area can change continuously from 3 to 5 and the atmospheric environment at an altitude of 11 km to 20 km can be simulated. The test device composed of the cubic curve profile with the same initial divergent half-angle as the original straight line has a better flow quality. The both-side rotation mode can ensure the symmetry of the flow direction better than the one-side rotation mode.

针对水下变深度导弹发射问题,提出了通过调节小孔漏气量进而调节发射能量的水下变深度燃气弹射方案.针对该方案的内弹道计算问题:通过三维模型数值仿真与零维模型理论计算的结果比对获取了燃气通过小孔的流量系数;基于小孔流量系数和传统燃气弹射内弹道模型,形成了小孔流动控制模型、低压室零维内弹道模型,最终建立了小孔漏气燃气弹射装置内弹道模型.内弹道模型仿真与实验结果的比对结果表明,该内弹道模型在上下低压室压强峰最大误差小于5％,能满足工程计算精度要求;同时基于该模型进行了内弹道调能研究,结果表明通过调节小孔截面积可以有效的实现导弹变深度发射.