Advanced Computational Fluid Dynamics Research Articles

How does turbulence intensity affect the fatigue life of composite airfoils based on existing CFD and experimental data?

This research investigates the effect of airflow turbulence intensity on the fatigue life of composite airfoil structures in aerospace engineering. Using advanced Computational Fluid Dynamics (CFD) simulations, this study provides a comprehensive analysis of how varying levels of turbulence intensity—ranging from mild (5%) to severe (30%)—impact the mechanical degradation and fatigue performance of carbon-fiber-reinforced polymers (CFRPs) used in airfoil designs. The research quantifies the relationship between turbulence levels and changes in stress distribution, highlighting critical points of fatigue crack initiation and subsequent propagation. The study includes detailed comparisons of CFD results to experimental data to validate the predictive models and discusses how localized stress fluctuations under high-intensity turbulence accelerate the onset of fatigue failure. We present significant findings that demonstrate a non-linear relationship between turbulence intensity and the reduction in fatigue life, suggesting optimal design modifications for enhanced durability. Furthermore, this paper explores current challenges in merging CFD data with real-world fatigue testing and proposes advanced techniques such as adaptive mesh refinement and hybrid simulation models to improve predictive accuracy and computational efficiency in future research.

State-of-the-Art CFD Simulation: A Review of Techniques, Validation Methods, and Application Scenarios

This review examines recent advancements in Computational Fluid Dynamics (CFD) simulation, focusing on state-of-the-art techniques, validation methods, and their application across various fields. CFD techniques, including Direct Numerical Simulation (DNS), Large Eddy Simulation (LES), Reynolds-Averaged Navier-Stokes (RANS), and hybrid methods, are compared in terms of computational demands, accuracy, and suitability for different fluid flow scenarios. Effective validation methods such as wind tunnel testing, analytical solutions, and field measurements are highlighted to ensure simulation reliability and align models with experimental data. Additionally, this review explores application scenarios in aerospace, automotive, environmental, and biomedical engineering, discussing how each field adapts CFD techniques to optimize performance and ensure realistic simulation outcomes. The comparative analysis offers insights into the trade-offs between accuracy and computational cost. It underscores the need for careful technique selection and robust validation to enhance CFD's applicability in both research and industry. The review aims to guide practitioners in selecting the most appropriate CFD approaches for their specific engineering challenges.

Hypersonic Flow past LD-Haack Series, Parabolic Series, Power Series Nose Cone: A Comparative Study

This research paper presents a detailed aerodynamic analysis of three rocket nose cone designs—LD-Haack, Parabolic, and Power Series—under hypersonic conditions ranging from Mach 5 to Mach 12. Using advanced Computational Fluid Dynamics (CFD) simulations in ANSYS Fluent, the study focuses on key aerodynamic parameters, including drag force, drag coefficient, velocity, pressure, and temperature distributions. The results indicate that the Parabolic Nose Cone offers the most favorable aerodynamic performance, with the lowest drag force and drag coefficient across all Mach numbers. This superior performance can be attributed to its ability to streamline airflow and minimize boundary layer separation, effectively reducing pressure drag and limiting the onset of turbulent wake regions. In contrast, the LD-Haack Series Nose Cone, though designed to minimize wave drag at supersonic speeds, shows moderate drag at hypersonic velocities due to its less optimal control of boundary layer behavior. The Power Series Nose Cone, despite its highly tapered shape, experiences the highest drag. This is largely caused by increased flow separation and turbulent wake generation, which exacerbate pressure drag, particularly at higher Mach numbers. These findings highlight the critical influence of nose cone geometry on aerodynamic efficiency and emphasize the importance of optimizing designs for hypersonic applications. This study provides valuable insights for aerospace engineers seeking to reduce drag and improve performance in high-speed flight scenarios.

Advanced Numerical Techniques for Supersonic Flow Analysis: From Euler Equations to Practical Applications in Aerospace and Turbomachinery Engineering

This paper explores advanced numerical techniques for analyzing supersonic flow, with a particular focus on the application of Euler equations in aerospace and turbomachinery engineering. Theoretical foundations such as boundary conditions, error evaluation, grid partitioning, and the Successive Over-Relaxation (SOR) method are thoroughly examined. Rigorous numerical simulations are conducted to investigate the final velocity field distribution and convergence characteristics under various conditions. The research underscores the precision and efficiency of these numerical methods, highlighting their practical applications in the aerodynamic design of aircraft and potential use in turbomachinery design. The findings contribute significantly to the advancement of computational fluid dynamics in supersonic flow regimes, providing valuable insights for engineers and researchers engaged in this specialized area. The study not only enhances understanding of complex flow dynamics but also supports the development of more effective engineering solutions in high-speed applications.

Neural differentiable modeling with diffusion-based super-resolution for two-dimensional spatiotemporal turbulence

Simulating spatiotemporal turbulence with high fidelity remains a cornerstone challenge in computational fluid dynamics (CFD) due to its intricate multiscale nature and prohibitive computational demands. Traditional approaches typically employ closure models, which attempt to represent small-scale features in an unresolved manner. However, these methods often sacrifice accuracy and lose high-frequency/wavenumber information, especially in scenarios involving complex flow physics. In this paper, we introduce an innovative neural differentiable modeling framework designed to enhance the predictability and efficiency of spatiotemporal turbulence simulations. Our approach features differentiable hybrid modeling techniques that seamlessly integrate deep neural networks with numerical PDE solvers within a differentiable programming framework, synergizing deep learning with physics-based CFD modeling. Specifically, a hybrid differentiable neural solver is constructed on a coarser grid to capture large-scale turbulent phenomena, followed by the application of a Bayesian conditional diffusion model that generates small-scale turbulence conditioned on large-scale flow predictions. Two innovative hybrid architecture designs are studied, and their performance is evaluated through comparative analysis against conventional large eddy simulation techniques with physics-based subgrid-scale closures and purely data-driven neural solvers. The findings underscore the potential of the neural differentiable modeling framework to significantly enhance the accuracy and computational efficiency of turbulence simulations. This study not only demonstrates the efficacy of merging deep learning with physics-based numerical solvers but also sets a new precedent for advanced CFD modeling techniques, highlighting the transformative impact of differentiable programming in scientific computing.

Numerical simulation of cavitation flow around a wing with new tubercles design

The study investigates the benefits of adding non-uniform leading-edge tubercles to hydrofoils, drawing inspiration from the complex shaping of humpback whale flippers. The focus is on managing cavitation, a phenomenon that can affect hydrofoil performance. While previous research has mainly looked at uniform sinusoidal tubercles and their positive impact on flow dynamics and cavitation control, this study introduces a new perspective by examining the effects of non-uniform tubercles on hydrofoil performance. Advanced computational fluid dynamics (CFD) simulations using ANSYS Fluent 2024 were used to assess how these non-uniform tubercles affect the lift, drag, and cavitation characteristics of the NACA 634-021 hydrofoil. The simulations incorporated the Schnerr-Sauer cavitation model and the SST k-ω turbulence model to accurately capture the flow dynamics. The results show that non-uniform tubercles improve cavitation control by disrupting the flow in a way that delays the onset and reduces the severity of cavitation. The modified hydrofoils (non-uniform tubercles) display improved hydrodynamic performance compared to baseline designs, with significant reductions in drag and increased lift at higher angles of attack. This study provides valuable insights into the potential of mimicking natural designs to enhance flow stability and address cavitation issues, offering a significant contribution to advanced hydrofoil design in scenarios where controlling cavitation is essential. The broader implications of this research underscore the potential of mimicking natural designs to transform hydrofoil engineering and enhance flow stability in various applications.

CFD Modeling of HBI/scrap Melting in Industrial EAF and the Impact of Charge Layering on Melting Performance.

The melting of scrap and hot briquetted iron (HBI) in an AC electric arc furnace (EAF) is simulated by an advanced 3D computational fluid dynamics (CFD) model that captures the arc heating, the scrap/HBI melting process, and the solid collapse mechanisms. The CFD model is used to simulate a scenario where charge layering and EAF power profiles are provided by a real EAF operation. CFD simulation of the EAF operation shows proper prediction of the charge melting when compared with standard industry practice. Namely, the CFD model predicts a 32.5%/67.5% ratio of solid/liquid steel at the beginning of refining, which approaches the 30%/70% ratio used in standard practice. Based on this prediction, the melting rate in the CFD results differs by 8.3% from actual EAF operation. The impact of charge layering on melting is also investigated. CFD results show that distributing charge material into a greater number of layers in the first bucket (10 layers as compared to 4) enhances the melting rate by 12%. However, including dense material at the bottom of the furnace deteriorates melting performance, reducing the impact of the number of layers of the charge. The CFD platform can be used to optimize the use of HBI/scrap in real EAF operations and to determine best recipe practices.

Forecasting two-dimensional channel flow using machine learning

Over the past decade, the integration of artificial neural networks (ANNs) has garnered significant interest, capitalizing on their ability to discern intricate patterns within data. Focused on enhancing computational efficiency, this article explores the application of ANNs in forecasting fluid-dynamics simulations, particularly for the benchmark problem of fluid flow in a two-dimensional (2D) channel. Leveraging a multilayer perceptron trained on finite volume method numerical data, for both interpolation and extrapolation estimations and various grid resolutions, our findings demonstrate the ANN's prowess as a swift and accurate surrogate for traditional numerical methods. Overall, the results of this work mark a pioneering step toward leveraging machine learning for modeling complex relationships in fluids phenomena, promising transformative advancements in computational fluid dynamics.

Applications and Prospects of Smooth Particle Hydrodynamics in Tunnel and Underground Engineering

Smoothed particle hydrodynamics (SPH) is a state-of-the-art numerical simulation method in fluid mechanics. It is a novel approach for modeling and comprehending complex fluid behaviors. In contrast to traditional grid-dependent techniques like finite element and finite difference methods, SPH utilizes a meshless, purely Lagrangian approach, offering significant advantages in fluid simulations. By leveraging a set of arbitrarily distributed particles to represent the continuous fluid medium, SPH enables the precise estimation of partial differential equations. This grid-free methodology effectively addresses many challenges associated with conventional methods, providing a more adaptable and efficient solution framework. SPH’s versatility is evident across a broad spectrum of applications, ranging from advanced computational fluid dynamics (CFD) to complex computational solid mechanics (CSM), and proves effective across various scales—from micro to macro and even astronomical phenomena. Although SPH excels in tackling problems involving multiple degrees of freedom, complex boundaries, and large discontinuous deformations, it is still in its developmental phase and has not yet been widely adopted. As such, a thorough understanding and systematic analysis of SPH’s foundational theories are critical. This paper offers a comprehensive review of the defining characteristics and theoretical foundations of the SPH method, supported by practical examples derived from the Navier–Stokes (N-S) equations. It also provides a critical examination of successful SPH applications across various fields. Additionally, the paper presents case studies of SPH’s application in tunnel and underground engineering based on practical engineering experiences and long-term on-site monitoring, highlighting SPH’s alignment with real-world conditions. The theory and application of SPH have thus emerged as highly dynamic and rapidly evolving research areas. The detailed theoretical analysis and case studies presented in this paper offer valuable insights and practical guidance for scholars and practitioners alike.

Novel packed-bed CFD model for pellet combustion: Validation and application to a stove

An advanced CFD (computational fluid dynamics) model has been developed to describe the combustion of wood pellets. It is based on a packed-bed approach and provides a realistic description of the combustion of pellets, resolved in 3D over the whole fuel bed. It considers the properties of the packed bed rather than the properties of the single fuel particles. Compared to a particle-based description, simulation times are shorter due to the reduced complexity. In the model, the local conditions in different parts of the fuel bed (temperatures, flow conditions, oxygen concentrations …) influence the various stages of the combustion process (drying, pyrolysis, charcoal gasification and combustion). The compaction of the fuel bed due to shrinkage of the fuel particles during conversion and the loss of the particle structure shortly before the conversion is complete are also included in the description. The formulation of the bed compaction, the radiation absorption model and the charcoal conversion reactions have been specifically tuned to the combustion of wood pellets. The detailed pyrolysis model includes not only the main components, but also higher hydrocarbon species and tars in a manner specific to the fuel considered. It has been combined with a chemical gas phase mechanism which is a reduction of a detailed mechanism developed for thermo-chemical biomass conversion. The model has been validated against measurement data from a lab-scale batch reactor, and then applied to simulate the fuel bed of a commercial pellet stove. The simulation results are in good agreement with the corresponding measurements.

Full-scale evaluation of FFU configurations in an optical cleanroom injection molding for improving thermal performance and contaminant removal

Cleanrooms are critical in the semiconductor industry, particularly for optical fabrication, where even minor contamination can compromise product quality. Effective airflow and uniform airflow distribution help to prevent contaminant accumulation, mitigate temperature variations, and avoid cross-contamination, which is crucial for achieving high-quality results and compliance with industry standards. This study introduces a novel approach to optimizing Fan Filter Unit (FFU) configurations to enhance thermal performance and contaminant removal in cleanroom settings. Integrating field measurements with advanced Computational Fluid Dynamics (CFD) simulations to comprehensively evaluate four distinct FFU designs, from dispersed to centralized configurations, focused on their impact on airflow dynamics, temperature uniformity, and particle concentration. The study identifies a significant advancement in FFU configuration by demonstrating that centralized arrangements (Designs 2 and 4) substantially improve cleanroom performance. Design 4 emerged as the most effective, showcasing a marked improvement in airflow circulation, a 12 % reduction in temperature variation, and a 15 % decrease in particle concentration compared to conventional designs. This achievement underscores the novel contribution of this study in optimizing FFU configurations to enhance both thermal performance and contaminant control. These findings not only advance the theoretical understanding of FFU design but also provide practical insights for improving cleanroom environments. The study offers a significant step forward in developing efficient cleanroom designs, contributing valuable guidelines for achieving good environmental control in sensitive manufacturing processes.

Enhancing ozonation technology: A case study on full-scale airlift reactor upgrades in the existing wastewater treatment plant's ozonation tank using CFD

Traditional pneumatic bubble column reactors (PBCRs) in wastewater treatment often have limitations in ozone distribution and disinfection efficacy. This study introduces an optimized Airlift Reactor (ALR) design, enhanced with Computational Fluid Dynamics (CFD), to improve ozone contact time and uniform distribution. Tailored for the SONATRACH GP1/Z Complex in Bethioua, Algeria, the ALR addresses the treatment needs of the facility's WWTP Phase-1, handling domestic wastewater. The study is unique for its full-scale implementation of the ALR, as previous research focused on lab-scale cases. Advanced CFD simulations optimized the ALR design, focusing on baffle configurations to enhance ozone disinfection. The upgraded One Side Baffled Airlift (OS-BALR) variant achieved a Total Coliform inactivation rate of 94.52 %, compared to 74 % with the traditional design. The OS-BALR also demonstrated a lower ozone mass transfer coefficient (KLa) of 0.0048 s−1, improving treatment efficiency and reducing energy consumption. While the Baffled Bubble Column (BBC) reactor showed a higher KLa of 0.0055 s−1 and a microbial removal efficacy of 96.12 %, it is more energy-intensive. This study advances wastewater treatment by bridging innovation with industrial application, contributing to sustainable wastewater management practices globally.

A novel phase-field lattice Boltzmann framework for diffusion-driven multiphase evaporation

Heat transfer and phase change phenomena, particularly diffusion-driven droplet evaporation, play pivotal roles in various industrial applications and natural processes. Despite advancements in computational fluid dynamics, modeling multiphase flows with large density ratios remains challenging. In this study, we developed a robust and stable conservative Allen–Cahn-based phase-field lattice Boltzmann method to solve the flow field equations. This method is coupled with the finite difference discretization of vapor species transport equation and the energy equation. The coupling between the vapor concentration and temperature field at the interface is modeled by the well-known Clausius–Clapeyron correlation. Our approach is capable of simulations under real physical conditions and is compatible with graphics processing unit architecture, making it ideal for large-scale industrial simulations. Three validation test cases are conducted to demonstrate the consistency of the presented model, including simulations of Stefan flow, the evaporation of suspended droplets containing water, acetone, and ethanol in the air, and the evaporation of a water sessile droplet on a flat surface. The results show that the model is able to predict the behavior and characteristics of each case accurately. Notably, our numerical results exhibit a maximum relative error of approximately 1% in simulations of Stefan flow. In the case of suspended droplet evaporation, the observed maximum difference between the calculated wet bulb temperatures and those derived from psychrometric charts is approximately 0.9 K. Moreover, our analysis of the sessile droplet reveals a good agreement between the results obtained by our model for the evaporative mass flux and those obtained from the existing models in the literature for different contact angles.

A computational search for the optimal microelectronic heat sink using ANSYS Icepak

The efficient thermal management of microelectronic devices is crucial for their reliability and performance. Heat sinks, particularly those with inline and staggered fin arrangements, are vital in achieving this goal. This study leverages the advancements in computational fluid dynamics (CFD) software to explore the optimal heat sink design for microelectronic devices. While prior research has extensively investigated heat sink design, this work offers novelty by employing ANSYS Icepak software for simulations. This approach enables a comprehensive thermal performance and pressure drop analysis for two distinct fin cross-sections. The study investigates heat sink assemblies housed within a confined space, simulating a realistic operating environment for microelectronic devices. The heat sink is designed to cool a single heat source (chip) mounted on a substrate board. In this paper, two types of fin sections, circular and conical, are studied for two types of fin configurations, inline (IA) and staggered (SA), which are analysed with 36 fins in each case. Each fin is constructed from aluminium and has specified dimensions. Air serves as the cooling fluid within the cabinet, dissipating heat generated by the chip. When comparing the performance of circular pin and cone fins at the same power and mass flow rate, the results indicated that the maximum temperature for circular pin fins is 0.46% of the maximum temperature for cone fins, and they have a higher pressure drop, especially for staggered arrangements. Moreover, the maximum temperature for staggered arrangements is lower than that for inline configurations by a factor of up to 1.17% and 2.035% for circular fins and cone pin fins, respectively. This article focuses on a deep understanding of the design of microelectronic cooling systems. It aims to continuously improve pressure and thermal efficiency by maintaining the minimum limits of pressure drop within the confined space and obtaining the optimal configuration for efficient heat dissipation.

A Review of Computational Fluid Dynamics Approaches Used to Investigate Lubrication of Rolling Element Bearings

Abstract Optimizing bearing performance is based on effective lubrication, especially in high-speed machinery, where minimizing churning and drag losses is of significant importance. Over the past few decades, extensive research has been conducted into the better understanding of different aspects of bearing lubrication. These investigations have employed a combination of experimental methods and advanced computational fluid dynamics (CFD) models. This article provides a comprehensive overview of critical aspects of bearing lubrication, with a specific emphasis on recent advances in CFD models. Lubricant flow and distribution patterns are discussed while examining their impact on drag and churning losses. An extensive discussion is provided on the meshing strategies and modeling approaches used to simulate various flow phenomena within bearings. In addition, relevant trends and impacts of cage design on bearing lubrication and fluid friction have been explored, along with a discussion of prevailing limitations that can be addressed in future bearing CFD models.

Wind characteristics around a skyway bridge of high-rise buildings

To respond the expansion of urban centers, the proliferation of high-rise buildings demands a better understanding of the aerodynamic phenomena around skyway bridges connecting these structures. This analysis, utilizing the advanced computational fluid dynamics verified by wind tunnel test data, investigates the wind characteristics around such bridges, crucial for structural stability, pedestrian comfort, and aerodynamic efficiency. This study focuses on the interactions between a 2 × 2 building array with a building height-to-street width ratio of 30 and a skyway bridge, investigating those factors such as bridge influence, building structures, building height, and bridge position. Using the three-dimensional steady Reynolds-averaged Navier–Stokes equations along with the Reynolds stress model for turbulence closure, the results show that the presence of skyway bridge significantly modifies local wind patterns. Wind speed and turbulence intensity are impacted differently based on the bridge's upstream or downstream settings. Downstream bridges tend to reduce wind speeds due to the sheltering effects, while upstream placement of bridge can enhance wind flow, affecting both the structural design and pedestrian comfort. Additionally, building height variations adjacent to the bridge influence wind velocity and pressure profiles, with taller buildings intensifying wind speeds at lower levels because of the channeling effects. These insights are pivotal for optimizing the skyway bridge designs to improve airflow distribution, enhance environmental sustainability, and ease wind-caused disturbances, offering a guideline for future architectural and urban planning in high-rise districts.

Influence of the flow split ratio on the position of the main atrial vortex: Implications for stasis on the left atrial appendage

Background:Despite the recent advances in computational fluid dynamics (CFD) techniques applied to blood flow within the left atrium (LA), the relationship between atrial geometry, flow patterns, and blood stasis within the left atrial appendage (LAA) remains unclear. A better understanding of this relationship would have important clinical implications, as thrombi originating in the LAA are a common cause of stroke in patients with atrial fibrillation (AF). Aim:To identify the most representative atrial flow patterns on a patient-specific basis and study their influence on LAA blood stasis by varying the flow split ratio and some common atrial modeling assumptions. Methods:Three recent techniques were applied to nine patient-specific computational fluid dynamics (CFD) models of patients with AF: a kinematic atrial model to isolate the influence of wall motion because of AF, projection on a universal LAA coordinate system, and quantification of stagnant blood volume (SBV). Results:We identified three different atrial flow patterns based on the position of the center of the main circulatory flow. The results also illustrate how atrial flow patterns are highly affected by the flow split ratio, increasing the SBV within the LAA. As the flow split ratio is determined by the patient’s lying position, the results suggest that the most frequent position adopted while sleeping may have implications for the medium- and long-term risks of stroke.

AnXplore: a comprehensive fluid-structure interaction study of 101 intracranial aneurysms.

Advances in computational fluid dynamics continuously extend the comprehension of aneurysm growth and rupture, intending to assist physicians in devising effective treatment strategies. While most studies have first modelled intracranial aneurysm walls as fully rigid with a focus on understanding blood flow characteristics, some researchers further introduced Fluid-Structure Interaction (FSI) and reported notable haemodynamic alterations for a few aneurysm cases when considering wall compliance. In this work, we explore further this research direction by studying 101 intracranial sidewall aneurysms, emphasizing the differences between rigid and deformable-wall simulations. The proposed dataset along with simulation parameters are shared for the sake of reproducibility. A wide range of haemodynamic patterns has been statistically analyzed with a particular focus on the impact of the wall modelling choice. Notable deviations in flow characteristics and commonly employed risk indicators are reported, particularly with near-dome blood recirculations being significantly impacted by the pulsating dynamics of the walls. This leads to substantial fluctuations in the sac-averaged oscillatory shear index, ranging from -36% to +674% of the standard rigid-wall value. Going a step further, haemodynamics obtained when simulating a flow-diverter stent modelled in conjunction with FSI are showcased for the first time, revealing a 73% increase in systolic sac-average velocity for the compliant-wall setting compared to its rigid counterpart. This last finding demonstrates the decisive impact that FSI modelling can have in predicting treatment outcomes.

Numerical study of energy consumption in spacer-filled feed channels through 3D inverse modeling and computational fluid dynamics

This project employs advanced Computational Fluid Dynamics (CFD) simulations to investigate the complex flow field dynamics within the channel of membrane module featuring a commercially available feed spacer. Utilizing Micro-CT scanning, the intricate three-dimensional (3D) structure of the spacer is accurately captured, enhancing the precision of the simulation models. The project focuses on the effects of varying Reynolds number (Re) and Aspect Ratio (AR) on the energy consumption within the feed channel of membrane module, analyzing streamline patterns, vorticity, and flow separation angles in detail. Findings indicate that the total enstrophy identification method effectively pinpoints areas of high energy consumption, especially at lower Re levels where flow separation significantly contributes to hydraulic losses. As Re increases, the separation vortex shifts rearward, resulting in a marked decrease in the energy consumption coefficient. Furthermore, the flow separation angle consistently declines with increasing Re, stabilizing at higher levels. Significantly, a reduction in AR from 1.015 to 0.725 more than doubles the decrease in flow separation angle, highlighting substantial potential energy savings through spacer design optimization. These insights are crucial for improving the design and efficiency of spiral wound membrane modules and for refining feed spacer configurations to enhance performance.

Impact on air-assisted direct injection on knock and energy conversion in a downsized elliptical rotary engine with high compression ratio

The elliptical rotor engine (ERE) is a novel engine type that enables a high power-to-weight ratio and high compression ratio (CR), resulting in a significant increase in thermal efficiency. However, the high CR also makes the engine prone to knock, limiting its performance potential. Addressing the challenge of knock induced by high CR is essential for optimizing ERE performance. This study introduces an innovative approach, combining CR with an air-assisted direct injection (AADI) device, using advanced computational fluid dynamics simulations to investigate their effects on knock and energy conversion characteristics of a downsized gasoline ERE. The findings reveal that increasing CR from 9.26 to 11 boosts indicated thermal efficiency (ITE) by 18.27%. However, knock occurrence disrupts energy distribution, leading to increased heat transfer losses. Notably, knock appears earlier and more intensely at the front end of the combustion chamber compared to the back end. The incorporation of AADI markedly reduces knock tendency, enhances ITE by 14.28% relative to the prototype, and reduces heat transfer loss by 42.41%. This study demonstrates that AADI not only effectively inhibits knocking, but also significantly improves the overall performance of the ERE, providing a promising solution for the development of high-performance rotary engines.